https://experimental-hydrology.net/wiki/api.php?action=feedcontributions&user=Ilja&feedformat=atomExperimental Hydrology Wiki - User contributions [en]2024-03-28T17:46:45ZUser contributionsMediaWiki 1.35.0https://experimental-hydrology.net/wiki/index.php?title=Temperature_-_Hobo_TidbiT_temperature_data_logger&diff=3220Temperature - Hobo TidbiT temperature data logger2013-05-04T21:31:52Z<p>Ilja: </p>
<hr />
<div>==Parameter to be measured:==<br />
Temperature<br />
<br />
==Method:==<br />
<br />
<br />
==Equipment:==<br />
TidbiT v2 Water Temperature Data Logger - UTBI-001 [http://www.onsetcomp.com/products/data-loggers/utbi-001]<br />
<br />
==Advantages:==<br />
If there are several loggers in one location that require the exact same start time, a delayed start time can be set when the loggers are launched. This allows for easy comparison of the time series. <br />
<br />
==Disadvantages:==<br />
Batteries are not replaceable or rechargeable. Therefore each logger only has a 5 year life span regardless of deployment time. <br />
<br />
==What to watch out for:==<br />
The optic communication nodes on the logger need to be protected they will break with hard impacts. <br />
Deploying the loggers in small sections of PVC pipe provided enough protection for the loggers in a high energy stream environment. <br />
Several loggers can be attached to a capped thin PVC pipe and deployed at different depths below the streambed.<br />
<br />
==Problems/Questions:==<br />
Loggers had a high failure rate. After deployment, some loggers may logged the temperature for a few days; the program in the logger may cause errors and not allow for communication or the battery may die rapidly.<br />
Partially depleted batteries found at purchase (In one case ~10% of loggers had 15% battery loss at time of purchase )<br />
<br />
<br />
==Price:==<br />
~$166 (US, 2013)<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
<br />
<br />
Other related web sites:<br />
<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]<br />
[[Category:Temperature]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Temperature_-_Hobo_TidbiT_temperature_data_logger&diff=3193Temperature - Hobo TidbiT temperature data logger2013-05-01T09:49:28Z<p>Ilja: Created page with "==Parameter to be measured:== Temperature ==Method:== ==Equipment:== TidbiT v2 Water Temperature Data Logger - UTBI-001 [http://www.onsetcomp.com/products/data-loggers/utbi..."</p>
<hr />
<div>==Parameter to be measured:==<br />
Temperature<br />
<br />
==Method:==<br />
<br />
<br />
==Equipment:==<br />
TidbiT v2 Water Temperature Data Logger - UTBI-001 [http://www.onsetcomp.com/products/data-loggers/utbi-001]<br />
<br />
==Advantages:==<br />
If there are several loggers in one location that require the exact same start time, a delayed start time can be set when the loggers are launched. This allows for easy comparison of the time series. <br />
<br />
==Disadvantages:==<br />
Batteries are not replaceable or rechargeable. Therefore each logger only has a 5 year life span regardless of deployment time. <br />
<br />
==What to watch out for:==<br />
The optic communication nodes on the logger need to be protected they will break with hard impacts. <br />
Deploying the loggers in small sections of PVC pipe provided enough protection for the loggers in a high energy stream environment. <br />
Several loggers can be attached to a capped thin PVC pipe and deployed at different depths below the streambed.<br />
<br />
==Problems/Questions:==<br />
Loggers had a high failure rate. After deployment, some loggers may logged the temperature for a few days; the program in the logger may cause errors and not allow for communication or the battery may die rapidly.<br />
Partially depleted batteries found at purchase (In one case ~10% of loggers had 15% battery loss at time of purchase )<br />
<br />
<br />
==Price:==<br />
~$166 (US, 2013)<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
<br />
<br />
Other related web sites:<br />
<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Temperature_-_Hobo_pendant_temperature_logger&diff=3192Temperature - Hobo pendant temperature logger2013-05-01T09:16:27Z<p>Ilja: </p>
<hr />
<div>==Parameter to be measured==<br />
Temperature<br />
<br />
==Method==<br />
Using self-recording temperature sensors it is possible to measure the temperature continuously. The loggers can be positioned in different heights. The result is a sample of tempareature dates and the connected calendar dates. the result are temperature values in °C.<br />
<br />
==Equipment==<br />
The '''HOBO Pendant Temperature Data Logger'''/ Doc # 9531-D, MAN-UA-001/ Onset Computer Corporation<br />
is a waterproof, one-channel logger with 10-bit resolution nd can record up to approximately 6,500 (8K model) or 52,000 (64K model) measurements or internal logger events. The logger uses a coupler and optical base station with USB interface for launching and data readout by a computer.<br />
<br />
*Measurement range: -20°C to 70°C (-4° to 158°F)<br />
<br />
*Accuracy: +/- 0.47°C at 25°C (+/-0.85°F at 77°F)<br />
<br />
*Resolution: Temperature: 0.10°C at 25°C (0.18°F at 77°F)<br />
<br />
*Drift: Less than 0.1°C/year (0.2°F/year)<br />
<br />
*Response time: Airflow of 2m/s (4.4 mph): 10 minutes, typical to 90%; Water: 5 minutes, typical to 90%<br />
<br />
*Time accuracy: +/- 1 minute per month at 25°C (77°F)<br />
<br />
*Weight: 18 g<br />
<br />
*Dimensions: 58 x 33 x 23 mm (2.3 x 1.3 x 0.9 inches)<br />
<br />
==Advantages==<br />
Continous measurement; Usage is easy; Position and number of loggers at the location is optional<br />
<br />
==Disadvantages==<br />
If there are several loggers placed on in location and they are connected by a bar, it influences the measurement results. If there is snow, the bar may push on melting around the loggers because of water runnning down the bar.<br />
<br />
In the opposite snow can stay longer on the loggers surface while it is melting in the surrounding area.<br />
<br />
==What to watch out for==<br />
The loggers must be observed from time to time, to avoid disturbation of the measurements, e.g. a defect battery.<br />
<br />
==Problems/Questions==<br />
If there are several loggers in one location it is nearly impossible to start all loggers exactly at the same time. So before working with the data it has to be standardised.<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
<br />
<br />
Other related web sites:<br />
<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]<br />
[[Category:Temperature]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Discharge_-_electromagnetic_flowmeter_FlowSens&diff=2342Discharge - electromagnetic flowmeter FlowSens2012-10-24T23:19:44Z<p>Ilja: </p>
<hr />
<div>{| align="right"<br />
|[[Image:Flowsens.JPG|right|220px|ADC]]<br />
|}<br />
<br />
==Parameter to be measured:==<br />
Flow velocity (, discharge)<br />
<br />
==Method:==<br />
electromagnetic<br />
<br />
==Equipment:==<br />
* probe<br />
* display unit<br />
* wading rod<br />
<br />
==Advantages:==<br />
* direct display of velocity and its standard deviation<br />
* sturdy design<br />
* apparently insensitive to mechanical interference, sensor fouling, high sediment concentrations,...<br />
<br />
<br />
==Disadvantages:==<br />
* bulky display unit <br />
* heavy rods with coarse scale<br />
* (data storage not tested)<br />
<br />
<br />
==What to watch out for:==<br />
* irritated electric eels<br />
<br />
<br />
==Links==<br />
[[ Discharge - comparison of measurements (C2, Flowtracker, Flowsens, ADC, tracer, dipping rod) ]]<br />
<br />
Other related web sites:<br />
<br />
Projects that used the above equipment:<br />
-<br />
<br />
==References==<br />
http://www.niwa.co.nz/__data/assets/pdf_file/0003/42627/Flowsense_current_Meter.pdf<br />
<br />
[[Category:Equipment]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Category:Uncertainty&diff=1571Category:Uncertainty2012-03-21T15:15:55Z<p>Ilja: Created page with "This is a list of all articles describing measurement uncertainties."</p>
<hr />
<div>This is a list of all articles describing measurement uncertainties.</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Discharge_uncertainty&diff=1570Discharge uncertainty2012-03-21T15:12:09Z<p>Ilja: </p>
<hr />
<div><br />
== Typical quantitative results of discharge uncertainty studies: Discharge Uncertainty. ==<br />
<br />
This table originated from McMillan et al. (2012) but is now open to the community to add to and use as a resource.<br />
<br />
PDF = probability density function; RMSE = root mean square error; SD = standard deviation<br />
<br />
{| {{table}}<br />
| align="center" style="background:#f0f0f0;"|'''Uncertainty Type'''<br />
| align="center" style="background:#f0f0f0;"|'''Estimation Method'''<br />
| align="center" style="background:#f0f0f0;"|'''Magnitude'''<br />
| align="center" style="background:#f0f0f0;"|'''Location'''<br />
| align="center" style="background:#f0f0f0;"|'''Reference'''<br />
|-<br />
| '''''Instantaneous Discharge Uncertainty'''''<br />
|- valign="top"<br />
| Single discharge measurement uncertainty when using method of verticals with current meter||SD of relative discharge error calculated from individual uncertainty components||2.3 % using 30 verticals with measurements at 0.2 & 0.8 depth points; other combinations also given||Columbia River, USA (5 sites)||Carter & Anderson (1963)<br />
|- valign="top"<br />
| Single discharge measurement uncertainty using velocity-area method||95 % confidence bounds on relative uncertainty, from literature review||4-17 % for 35-5 verticals at 0.25 m s-1; 5-40 % for velocities 0.5-0.05 m s-1. ||Various||Pelletier (1988)<br />
|- valign="top"<br />
| Single discharge measurement uncertainty under ice||Difference between USGS & Water Survey of Canada instantaneous flow measurements attributed to different setup of current meter on rod or in suspension||2-17 %||Red river at Emerson, Manitoba, Canada (104000 km2). Slope 0.04-0.25 m km-1, mean discharge 94.2 m3 s-1, when under ice 20 m3 s-1, drains glacial plain with moraines.||Pelletier (1989)<br />
|- valign="top"<br />
| Combination of stage error & components of discharge error for wading or cable methods||Standard error computed by root-mean-square of component uncertainties: those derived from previous studies, manufacturer citations and expert knowledge.||2.4 % (Good Cable); 4.0 % (Good Wading); 19 % (Poorest measurements)||||Sauer & Meyer (1992)<br />
|- valign="top"<br />
| Single discharge measurement uncertainty: effect of reducing number of verticals||Halving number of verticals||Approx. 5 % (given as graph relating to % reduction in verticals)||23 sites in UK North-East||Whalley (2001)<br />
|- valign="top"<br />
| Epistemic single discharge measurement uncertainty using current meter for velocity-area method||Combined uncertainty values from expert opinion & previous studies||6 %||Typical example||Herschy (2002)<br />
|- valign="top"<br />
| Single discharge measurement uncertainty: Salt dilution gauging ||SD of instantaneous discharge measured using salt dilution, deviation from rating curve developed using both salt dilution and current metering.||5 %||Stephanie Creek, Vancouver Island, BC, Canada (8.6 km2). Steep rocky creek.||Hudson & Fraser (2002)<br />
|- valign="top"<br />
| ||||7.1%||Flume Creek, Sunshine Coast, BC, Canada (118 ha). Steep creek.||<br />
|- valign="top"<br />
| ||||±42-84 %||South Fork catchment (780 km2), Iowa, USA||<br />
|- valign="top"<br />
| Single discharge measurement uncertainty||Typical bias determined from replicates||<-4 %||||Hamilton & Moore (2012)<br />
|-<br />
| '''''Rating Curve and Combined Uncertainty'''''<br />
|- valign="top"<br />
| Random errors associated with power law rating curves||RMSE of component uncertainties||1.9 % in instantaneous or average daily discharge, 0.5 % in average monthly discharge||Mangawhero at Ore Ore, New Zealand. Mean discharge 13m3 s-1||Dymond & Christian (1982)<br />
|- valign="top"<br />
| Deviation between theoretical & measured rating curve (with current meter)||||20 % at low flows (0.2 m above station datum), 10 % at higher flows||Sprint, UK. Flat-vee crump profile weir structure.||Whalley (2001)<br />
|- valign="top"<br />
| Deviation between theoretical rating curve accounting for non-steady flow & measured discharge (also given for empirical rating curve)||Coefficient of variation calculated from 55 discharge measurements||10 % (in-bank flows); 36% (including out-of-bank flows) ||Illinois River, USA. Low gradient river, discharge 38-3480 m3 s-1, two gauge (slop-stage-discharge) rating station.||Schmidt & Yen (2008)<br />
|- valign="top"<br />
| Total instantaneous discharge uncertainty caused by interpolation / extrapolation of rating curve, unsteady flow conditions & seasonal changes in roughness||95 % uncertainty bounds for relative error calculated through combination of three error components||6.2 % at 1000 m3 s-1 to 42.8 % at 12000 m3 s-1, average 25.6 %||Po River, Italy (70000 km2). Channel width 200-500 m, depth 10-15 m, slope 0.02, floodplain width 1000-3000 m.||Di Baldassarre & Montanari (2009)<br />
|- valign="top"<br />
| Total instantaneous discharge uncertainty caused by rating curve uncertainty||Relative error compared to manual measurements||1-20 % (average 8.76 %), negatively related to stage||Hillslope (172 m2), WS10 catchment, HJA Experimental Forest, Oregon, USA. Stilling well with 30° V-Notch Weir.||Graham et al. (2010); values calculated from original figures<br />
|- valign="top"<br />
| ||||Average 3.6 %, not related to stage||WS10 catchment (10.2 ha), HJA Experimental Forest, Oregon, USA. 90° V-Notch Weir||<br />
|- valign="top"<br />
| Total instantaneous discharge uncertainty caused by gauging errors & rating curve form / extrapolation||Estimate of upper & lower discharge bounds for any given stage through combination of component errors||Relative error from 100 % (low flows) to 10 % (low-mid flows) to 20 % (high flows)||Rowden Experimental Research Platform (1 ha fields), Devon, UK. 250 x 37 cm weir box, stainless steel 45° V-Notch, bucket method & electromagnetic flowmeter (Magflo Mag 5100, Siemens), ave. annual precipitation 1055 mm.||Krueger et al. (2010)<br />
|- valign="top"<br />
| Total instantaneous discharge uncertainty caused by gauging error, rating curve form / extrapolation & instability of rating curve||Estimate of complete instantaneous discharge PDF for any given stage||Relative error from 46 % (low flows) to 10 % (mid-high flows) to 15 % (flood flows), average 22 %||Wairau River, New Zealand (3825 km2). Elevation 0-2309 m a.s.l., braided reach, 100 m width.||McMillan et al. (2010)<br />
|- valign="top"<br />
| Total instantaneous discharge uncertainty caused by gauging error & instability of rating curve||Estimates of upper & lower instantaneous discharge bounds for any given stage using uncertain time-varying rating curve||Difference from constant rating curve ranged from -60 to 90 % (low flows) to ±20 % (mid-high flows); total relative discharge error -43 % to +73 %. Effect of using only 3 stage measurements / day to calculate daily discharge: ±17 %||Choluteca River, Honduras (1766 km2). Mountainous, 660 – 2320 m a.s.l., precipitation mainly convective.||Westerberg et al. (2011)<br />
|-<br />
| '''''Time-averaged Discharge Uncertainty'''''<br />
|- valign="top"<br />
| Total uncertainty of daily discharge||PDF, mean, SD ||Normal, 0, 10 %||Odense basin (1190 km2), Denmark. Low rolling hills, elevation 0-100 m a.s.l.||Refsgaard et al. (2006)<br />
|- valign="top"<br />
| Relative uncertainty of daily & annual discharge estimates in rivers subject to icing||Statistical analysis of uncertainty in the parameters of the fitted quadratic rating curves & ice correction coefficients||Where cross sections assumed stable: 8-25 % for low flows, 2-5 % for high flows (variation for different rivers); where cross section not stable (e.g. with ice): 10-21 % with high frequency gaugings, 15-45 % under the worst conditions in the record||6 largest Eurasian Arctic Rivers (248000-2950000 km2). Mean discharge 2200-18400 m3 s-1.||Shiklomanov et al. (2006)<br />
|- valign="top"<br />
| Monthly discharge uncertainty||Probable error range||±42 %||Small watershed near Riesel, Texas, USA||Harmel & Smith (2007) based on Harmel et al. (2006)<br />
|- valign="top"<br />
| Daily discharge uncertainty||||±42 %; ±100-200 % for low flows; ±100 % for high flows||Reynolds Creek catchment (239 km2), Idaho, USA||<br />
|- valign="top"<br />
| Storm discharge uncertainty||Total probable error based on RMSE propagation method||2-19 %||Various in USA (2.2-5506 ha)||Harmel et al. (2009) based on Harmel et al. (2006)<br />
|- valign="top"<br />
| Deep seepage uncertainty in steady state (as residual water balance component)||Relative uncertainty based on propagation of component uncertainties||57 % (under steady state); 32 % (during irrigation); 34 % (during irrigation + 5 days); 35 % (during irrigation + 10 days)||Hillslope (172 m2), WS10 catchment, HJA Experimental Forest, Oregon, USA. Stilling well with 30° V-Notch Weir.||Graham et al. (2010); values calculated from original figures<br />
|- valign="top"<br />
| ||||84 % (under steady state); 62 % (during irrigation); 93 % (during irrigation + 5 days); 155 % (during irrigation + 10 days)||WS10 catchment (10.2 ha), HJA Experimental Forest, Oregon, USA. 90° V-Notch Weir||<br />
|- valign="top"<br />
| Daily discharge; effect of manual stage reading||Manually minus automatically derived discharge||Up to ±10-50 %||Lillooet River near Pemberton, British Columbia, Canada. Nivo-glacial.||Hamilton & Moore (2012)<br />
|- valign="top"<br />
| Monthly discharge; effect of manual stage reading||||Up to 5-10 %<br />
|}<br />
<br />
== References ==<br />
<br />
Carter, R.W., Anderson, I.E., 1963. Accuracy of current meter measurements. Journal of the Hydraulics Division, 89(4): 105-115.<br />
<br />
Di Baldassarre, G., Montanari, A., 2009. Uncertainty in river discharge observations: a quantitative analysis. Hydrology and Earth System Sciences, 13(6): 913-921.<br />
<br />
Dymond, J.R., Christian, R., 1982. Accuracy of discharge determined from a rating curve. Hydrological Sciences Journal-Journal Des Sciences Hydrologiques, 4(12): 493-504.<br />
<br />
Graham, C.B., van Verseveld, W., Barnard, H.R., McDonnell, J.J., 2010. Estimating the deep seepage component of the hillslope and catchment water balance within a measurement uncertainty framework. Hydrological Processes, 24(25): 3878–3893.<br />
<br />
Hamilton, A.S., Moore, R.D., 2012. Quantifying Uncertainty in Streamflow Records. Canadian Water Resources Journal, 37(1): 3-21.<br />
<br />
Harmel, R.D., Cooper, R.J., Slade, R.M., Haney, R.L., Arnold, J.G., 2006. Cumulative uncertainty in measured streamflow and water quality data for small watersheds. Transactions of the ASABE, 49(3): 689-701.<br />
<br />
Harmel, R.D., Smith, D.R., King, K.W., Slade, R.M., 2009. Estimating storm discharge and water quality data uncertainty: A software tool for monitoring and modeling applications. Environmental Modelling & Software, 24(7): 832-842.<br />
<br />
Harmel, R.D., Smith, P.K., 2007. Consideration of measurement uncertainty in the evaluation of goodness-of-fit in hydrologic and water quality modeling. Journal of Hydrology, 337(3-4): 326-336.<br />
<br />
Herschy, R.W., 2002. The uncertainty in a current meter measurement. Flow Measurement and Instrumentation, 13(5-6): 281-284.<br />
<br />
Hudson R, Fraser J., 2002. Alternative methods of flow rating in small coastal streams. Forest Research Extension Note EN-014 (Hydrology). Vancouver Forest Region.<br />
<br />
Krueger, T., Freer, J., Quinton, J.N., Macleod, C.J.A., Bilotta, G.S., Brazier, R.E., Butler, P., Haygarth, P.M., 2010a. Ensemble evaluation of hydrological model hypotheses. Water Resources Research, 46: W07516.<br />
<br />
McMillan, H., Freer, J., Pappenberger, F., Krueger, T., Clark, M., 2010. Impacts of uncertain river flow data on rainfall-runoff model calibration and discharge predictions. Hydrological Processes, 24(10): 1270-1284.<br />
<br />
McMillan, H., Krueger, T., Freer, J., 2012. Benchmarking observational uncertainties for hydrology: Rainfall, river discharge and water quality. Hydrological Processes.<br />
<br />
Pelletier, P.M.., 1988. Uncertainties in the determination of river discharge: A literature review. Canadian Journal of Civil Engineering, 15: 834-850.<br />
<br />
Pelletier, P. M., 1989. Uncertainties in streamflow measurement under winter ice conditions a case study: The Red River at Emerson, Manitoba, Canada, Water Resour. Res., 25(8), 1857–1867, doi:10.1029/WR025i008p01857.<br />
<br />
Refsgaard, J.C., van der Keur, P., Nilsson, B., Mueller-Wohlfeil, D.I., Brown, J., 2006. Uncertainties in river basin data at various support scales - Example from Odense Pilot River Basin. Hydrology Earth System Sciences Discussions, 3(4): 1943-1985.<br />
<br />
Sauer, V.B., Meyer, R.W., 1992. Determination of error in individual discharge measurements, U.S. Geological Survey Open-File Report 92–144.<br />
<br />
Shiklomanov, A.I., Yakovleva, T.I., Lammers, R.B., Karasev, I.P., Vörösmarty, C.J., Linder, E., 2006. Cold region river discharge uncertainty - Estimates from large Russian rivers. Journal of Hydrology, 326(1-4): 231-256.<br />
<br />
Schmidt, A.R., Yen, B.C., 2008. Theoretical development of stage-discharge ratings for subcritical open-channel flows. Journal of Hydraulic Engineering-ASCE, 134(9): 1245-1256.<br />
<br />
Westerberg, I., Guerrero, J.L., Seibert, J., Beven, K.J., Halldin, S., 2011. Stage-discharge uncertainty derived with a non-stationary rating curve in the Choluteca River, Honduras. Hydrological Processes, 25(4): 603-613.<br />
<br />
Whalley, N., Iredale, R.S., Clare, A.F., 2001. Reliability and uncertainty in flow measurement techniques - Some current thinking. Physics and Chemistry of the Earth Part C-Solar-Terrestial and Planetary Science, 26(10-12): 743-749.<br />
<br />
[[Category:Uncertainty]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Discharge_uncertainty_(ADCP,_ADV,_LSPIV)&diff=1569Discharge uncertainty (ADCP, ADV, LSPIV)2012-03-21T15:11:50Z<p>Ilja: </p>
<hr />
<div><br />
== Typical quantitative results of discharge uncertainty studies: New Measurement Techniques. ==<br />
<br />
This table originated from McMillan et al. (2012) but is now open to the community to add to and use as a resource.<br />
<br />
ADV = acoustic Doppler velocimetry; ADCP = acoustic Doppler current profiling; LSPIV = Large Scale Particle Image Velocimetry; SD = standard deviation<br />
<br />
{| {{table}}<br />
| align="center" style="background:#f0f0f0;"|'''Uncertainty Type'''<br />
| align="center" style="background:#f0f0f0;"|'''Estimation Method'''<br />
| align="center" style="background:#f0f0f0;"|'''Magnitude'''<br />
| align="center" style="background:#f0f0f0;"|'''Location'''<br />
| align="center" style="background:#f0f0f0;"|'''Reference'''<br />
|- valign="top"<br />
| ADCP discharge measurement uncertainty||Relative error of discharge calculated using ADCP vs. current meter and/or rating curve||Mean relative error from multiple transects was -3 to 5 % (from meter) or -7 to 5 % (from rating) dependent on site||USA (5 sites on Illinois, Kankakee, Mississippi and Missouri rivers). Depths 1.1-3.8 m, widths 33-527 m, velocities 0.4-1.3 m s-1.||Mueller (2003)<br />
|- valign="top"<br />
| ||Relative error of discharge calculated using ADCP vs. multiple concurrent current meters||SD of relative error 5.8 %; distributions given from large set of test cases, plus results for alternative measurement set-ups||Multi-location field sites (including USA, Canada, Sweden, Netherlands) plus laboratory testing||Oberg & Mueller (2007)<br />
|- valign="top"<br />
| ADV velocity measurement uncertainty, with & without calibration||Relative error of discharge calculated using ADV velocity (20 min average) vs. impellor velocity (60 s period per sample)||Flow estimates were within 20 % of the current-metered flow for 93 % of samples after calibration (68 % before calibration)||Pontbren, Wales, UK, 5 concrete-lined sections. 3 circular: diameter 0.6-1.6 m, depth 0-0.71 m, velocity 0-3.0 m s-1. 2 rectangular: width 3.17, 4.17 m; depth 0-0.67 m, velocity 0-3.9 m s-1.||McIntyre & Marshall (2008)<br />
|- valign="top"<br />
| Mobile LSPIV instantaneous velocity & discharge measurement uncertainty||Relative error from theoretical velocity field based on 27 error sources; case study comparison with rating curve & ADCP methods||Theoretical errors in velocity from 10-35 % at 95 % confidence level; case study gave discharge error at 2 % compared to rating curve & 5.5 % compared to ADCP||Analysis of typical conditions. Case study at Clear Creek near Coralville, Iowa, USA. 20 m wide, 0.7 m deep, stage 1.2 and velocity 5.2 m s-1 during study.||Kim et al. (2008)<br />
|- valign="top"<br />
| Simulated LSPIV measurements against theoretical true values||Error variance obtained via linear regression of simulated vs. true values||5 % under normal conditions, increasing to 17 % with a high tilt angle (70º)||Numerical simulation||Hauet et al. (2008)<br />
|- valign="top"<br />
| LSPIV instantaneous discharge measurements during high flows compared with rating curve & current meter reference values||Relative error at a number of observation times||47 % at low flows, 13-23 % on rising limb, 2 % during stable high flow period||River Arc, France, during dam release operation. Discharge range 10-150 m3 s-1, width 60-70 m, gravel-bed river.||Jodeau et al. (2008)<br />
|- valign="top"<br />
| Microwave & UHF Doppler Radars uncertainty in instantaneous discharge measurement||Correlation coefficients between radar measurements & conventional rating curve methods over 16-week period||0.883, 0.969, 0.992 dependent on Doppler radar system||Cowlitz River, Washington, USA(5800 km2). Width 92 m, depth 2-7 m.||Costa et al. (2006)<br />
|}<br />
<br />
== References ==<br />
<br />
Costa, J.E., Cheng, R.T., Haeni, F.P., Melcher, N., Spicer, K.R., Hayes, E., Plant, W., Hayes, K., Teague, C., Barrick, D., 2006. Use of radars to monitor stream discharge by noncontact methods. Water Resources Research, 42(7): W07422.<br />
<br />
Hauet, A., Creutin, J.D., Belleudy, P., 2008. Sensitivity study of large-scale particle image velocimetry measurement of river discharge using numerical simulation. Journal of Hydrology, 349(1-2): 178-190.<br />
<br />
Jodeau, M., Hauet, A., Paquier, A., Le Coz, J., Dramais, G., 2008. Application and evaluation of LS-PIV technique for the monitoring of river surface velocities in high flow conditions. Flow Measurement and Instrumentation, 19(2): 117-127.<br />
<br />
Kim, Y., Muste, M., Hauet, A., Krajewski, W.F., Kruger, A., Bradley, A., 2008. Stream discharge using mobile large-scale particle image velocimetry: A proof of concept. Water Resources Research, 44(9): W09502.<br />
<br />
McIntyre, N., Marshall, M., 2008. Field verification of bed-mounted ADV meters. Proceedings of the Institution of Civil Engineers-Water Management, 161(4): 199-206.<br />
<br />
McMillan, H., Krueger, T., Freer, J., 2012. Benchmarking observational uncertainties for hydrology: Rainfall, river discharge and water quality. Hydrological Processes. <br />
<br />
Mueller, D.S., 2003. Field evaluation of boat-mounted acoustic Doppler instruments used to measure streamflow. Proceedings of the IEEE/OES Seventh Working Conference on Current Measurement Technology. IEEE, New York, 30-34 pp.<br />
<br />
Oberg, K., Mueller, D.S., 2007. Validation of streamflow measurements made with acoustic Doppler current profilers. Journal of Hydraulic Engineering-ASCE, 133(12): 1421-1432.<br />
<br />
[[Category:Uncertainty]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Rainfall_interpolation_uncertainty&diff=1568Rainfall interpolation uncertainty2012-03-21T15:11:20Z<p>Ilja: </p>
<hr />
<div><br />
== Typical quantitative results of rainfall uncertainty studies: Interpolation. ==<br />
<br />
This table originated from McMillan et al. (2012) but is now open to the community to add to and use as a resource.<br />
<br />
SD = standard deviation<br />
<br />
{| {{table}}<br />
| align="center" style="background:#f0f0f0;"|'''Uncertainty Type'''<br />
| align="center" style="background:#f0f0f0;"|'''Estimation Method'''<br />
| align="center" style="background:#f0f0f0;"|'''Magnitude'''<br />
| align="center" style="background:#f0f0f0;"|'''Location'''<br />
| align="center" style="background:#f0f0f0;"|'''Reference'''<br />
|- valign="top"<br />
| Rainfall variability in convective events||48 non-recording gauges on 30 m grid over 4.4 ha catchment||4-14 % variation of mean storm rainfall over 100 m distance; -5.6 % greatest difference between areal mean & 4 co-located central gauges||USDA Walnut Gulch Experimental Watershed, Arizona, USA. 4.4 ha, semi-arid, 1250-1585 m a.s.l.||Goodrich et al. (1995)<br />
|- valign="top"<br />
| Standard error in single gauge measurement vs. gauge network||8 rain gauges within a 2 km2 area||33 % (low relief), 45 % (high relief) at 4 mm/15 min rain rate; 90% confidence bounds on the standard error, dependent on rain rate, are also given graphically||Brue catchment, UK (135 km2). 20-250 m a.s.l., temperate climate, orographic rainfall.||Wood et al. (2000)<br />
|- valign="top"<br />
| ||49 rain gauges in 135 km2 area||65 % at 4 mm/15 min rain rate; presented graphically for rain rates 0.2-8 mm/15 min and for three different gauges||||<br />
|- valign="top"<br />
| SD of rainfall rates within 5 km2 area for accumulation periods between 5 min and 1 hour||5 clusters, each of 12-40 rain gauges||12.2, 12.0, 16.1, 7.7 & 9.8 mm h-1 for 5 min totals over 57-515 days, conditioned on rain rates greater than 0.5 mm h-1||Gauge clusters in Guam, Brazil, Florida, Oklahoma, Iowa||Krajewski et al. (2003); also looked at correlation statistics up to 8 km distance with significant reductions<br />
|- valign="top"<br />
| Multiplier from 3-gauge average to areal mean rainfall||Conditional simulation using 13 raingauges to generate ensemble of spatial rainfall fields||Rainfall multipliers have mean 1.15 ± 0.03, standard deviation 0.27 ± 0.02 when accounting separately for rainfall, runoff and structural uncertainty.||Yzeron catchment (129 km2), Rhone-Alpes region, France. 400-917 m a.s.l.. Rainfall 845 mm yr-1, runoff 150 mm yr-1. ||Renard et al. (2011)<br />
|}<br />
<br />
== References ==<br />
<br />
Goodrich, D.C., Faures, J.M., Woolhiser, D.A., Lane, L.J., Sorooshian, S., 1995. Measurement and analysis of small-scale convective storm rainfall variability. Journal of Hydrology, 173(1-4): 283-308.<br />
<br />
Krajewski, W.F., Ciach, G.J., Habib, E., 2003. An analysis of small-scale rainfall variability in different climatic regimes. Hydrological Sciences Journal-Journal Des Sciences Hydrologiques, 48(2): 151-162.<br />
<br />
McMillan, H., Krueger, T., Freer, J., 2012. Benchmarking observational uncertainties for hydrology: Rainfall, river discharge and water quality. Hydrological Processes.<br />
<br />
Renard, B., Kavetski, D., Leblois, E., Thyer, M., Kuczera, G., 2011. Towards a reliable decomposition of predictive uncertainty in hydrological modelling : characterizing rainfall errors using conditional simulation, Water Resources Research, 47: W11516. doi:10.1029/2011WR010643<br />
<br />
Wood, S.J., Jones, D.A., Moore, R.J., 2000. Accuracy of rainfall measurement for scales of hydrological interest. Hydrology and Earth System Sciences, 4(4): 531-543.<br />
<br />
[[Category:Uncertainty]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Rainfall_point_measurement_uncertainty&diff=1567Rainfall point measurement uncertainty2012-03-21T15:11:01Z<p>Ilja: </p>
<hr />
<div><br />
== Typical quantitative results of rainfall uncertainty studies: Point Measurements. ==<br />
<br />
This table originated from McMillan et al. (2012) but is now open to the community to add to and use as a resource.<br />
<br />
{| {{table}}<br />
| align="center" style="background:#f0f0f0;"|'''Uncertainty Type'''<br />
| align="center" style="background:#f0f0f0;"|'''Estimation Method'''<br />
| align="center" style="background:#f0f0f0;"|'''Magnitude'''<br />
| align="center" style="background:#f0f0f0;"|'''Location'''<br />
| align="center" style="background:#f0f0f0;"|'''Reference'''<br />
|-<br />
| '''''Systematic Errors'''''<br />
|- valign="top"<br />
| Wind loss curves dependent on wind speed & raindrop size ||Theoretical calculation using wind velocity field from wind tunnel experiments||1 mm drops: -10 % (6 m s-1), -40 % (9 m s-1), -80 % (12 m s-1); 2 mm drops: -10 % (9 m s-1), -20 % (12 m s-1); 3-5 mm drops: no effect up to 15 m s-1||||Mueller & Kidder (1972)<br />
|- valign="top"<br />
| Wind loss curves||Comparison with shielded gauge||Approx. linear 1 % under-catch per 1 mph wind speed||Danville, Vermont, USA||Larson & Peck (1974); also wind loss curves for snow<br />
|- valign="top"<br />
| Undercatch for gauge mounted at 1 m height||Comparison with pit gauge||5-16 % average undercatch (over 53-321 events), 0-75 % per storm||USA: Reynolds Creek, Idaho; Pullman, Washington; Sidney, Montana; Ekalaka, Montana||Neff (1977)<br />
|- valign="top"<br />
| Loss due to wind field deformation||WMO literature survey & pit gauge comparisons||2-10 % (rain), 10-50 % (snow)||||Sevruk (1982); extensive literature survey is still widely quoted; correction equations are given dependent on gauge type & meteorological conditions<br />
|- valign="top"<br />
| Wetting loss||||2-15 % (summer), 1-8 % (winter)||||<br />
|- valign="top"<br />
| Evaporation loss from open container||||0-4 %||||<br />
|- valign="top"<br />
| Splash-in/out||||1-2 %||||<br />
|- valign="top"<br />
| Undercatch for shielded gauge at 12 inches height & turf wall gauge||Comparison with pit gauge||5 % (unshielded), 2 % (turf wall) annual undercatch||County Londonderry, Ireland. Lowland, coastal, rainfall 900-1100 mm yr-1.||Essery & Wilcock (1991); 1976-1988<br />
|- valign="top"<br />
| Wind-induced error depending on wind speed, rain drop size distribution & gauge design||Comparison between exposed & pit gauges||2–10 % (hourly data; even after popular correction algorithms)||ARS Goodwin Creek experimental watershed, Mississippi, USA. 21.4 km2, rainfall 1400 mm yr-1, 71-128 m a.s.l.||Sieck et al. (2007)<br />
|- valign="top"<br />
| Tipping error per 1 mm rain||Field calibration with known water delivery rate||Up to 10 % dependent on gauge type & rain rate||||<br />
|-<br />
| '''''Random Errors'''''<br />
|- valign="top"<br />
| Coefficient of variation of random errors||12 co-located standard rain gauges||Approx. 5 % for single storm, independent of total storm rainfall||Mount Cargill, Dunedin, New Zealand. Exposed site at 560 m a.s.l.||Hutchinson (1969)<br />
|- valign="top"<br />
| Coefficient of variation of non-recording gauges||9 co-located recording & non-recording gauges||4-5 % for storms >15 mm (monsoon season thunderstorms)||USDA Walnut Gulch Experimental Watershed, Arizona, USA. 4.4 ha, semi-arid, 1250-1585 m a.s.l. ||Goodrich et al. (1995)<br />
|- valign="top"<br />
| Total error of recording gauge||Standard error between single gauges & average of 15 co-located tipping buckets||Decreases with rain rate & accumulation time, e.g. 4.9 % (5 min) & 2.9 % (15 min) at rain rate of 10 mm h-1||USDA field station in Chickasha, Oklahoma, USA||Ciach (2003)<br />
|}<br />
<br />
== References ==<br />
<br />
Ciach, G.J., 2003. Local random errors in tipping-bucket rain gauge measurements. Journal of Atmospheric and Oceanic Technology, 20(5): 752-759.<br />
<br />
Essery, C.I., Wilcock, D.N., 1991. The variation in rainfall catch from standard UK Meteorological-Office rain-gages - A 12 year case-study. Hydrological Sciences Journal-Journal Des Sciences Hydrologiques, 36(1): 23-34.<br />
<br />
Goodrich, D.C., Faures, J.M., Woolhiser, D.A., Lane, L.J., Sorooshian, S., 1995. Measurement and analysis of small-scale convective storm rainfall variability. Journal of Hydrology, 173(1-4): 283-308.<br />
<br />
Hutchinson, P., 1969. A note on random rain-gauge errors. Journal of Hydrology (NZ), 8(1): 8-10.<br />
<br />
Larson, L.W., Peck, E.L., 1974. Accuracy of precipitation measurements for hydrologic models. Water Resources Research, 10(4): 857-863.<br />
<br />
McMillan, H., Krueger, T., Freer, J., 2012. Benchmarking observational uncertainties for hydrology: Rainfall, river discharge and water quality. Hydrological Processes.<br />
<br />
Mueller, C.C., Kidder, E.H., 1972. Rain gage catch variation due to air-flow disturbances around a standard rain gage. Water Resources Research, 8(4): 1077-1082.<br />
<br />
Neff, E.L., 1977. How much rain does a rain gauge gauge? Journal of Hydrology, 35: 213-220.<br />
<br />
Sevruk, B., 1982. Methods of correction for systematic error in point precipitation measurement. World Meteorological Organisation, Operational Hydrology Report No. 21, WMO-No.589. Geneva, Switzerland.<br />
<br />
Sieck, L.C., Burges, S.J., Steiner, M., 2007. Challenges in obtaining reliable measurements of point rainfall. Water Resources Research, 43(1): W01420.<br />
<br />
[[Category:Uncertainty]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Suspended_solids_uncertainty&diff=1566Suspended solids uncertainty2012-03-21T15:10:39Z<p>Ilja: </p>
<hr />
<div><br />
== Typical quantitative results of water quality uncertainty studies: Suspended solids. ==<br />
<br />
This table originated from McMillan et al. (2012) but is now open to the community to add to and use as a resource.<br />
<br />
PDF = probability density function; RMSE = root mean square error; WY = water year<br />
<br />
{| {{table}}<br />
| align="center" style="background:#f0f0f0;"|'''Uncertainty Type'''<br />
| align="center" style="background:#f0f0f0;"|'''Estimation Method'''<br />
| align="center" style="background:#f0f0f0;"|'''Magnitude'''<br />
| align="center" style="background:#f0f0f0;"|'''Location'''<br />
| align="center" style="background:#f0f0f0;"|'''Reference'''<br />
|- valign="top"<br />
| Instantaneous concentration||Relative difference between auto & manual dublicates||Auto sample within 10 % of manual sample||Devon, UK||Walling & Teed (1971)<br />
|- valign="top"<br />
| 8-year load; effect of estimation method||Bias relative to reference load from daily data (1974/75-1981/82); 12 methods tested; 6 sampling frequencies simulated via sub-sampling||-22 to 10 %||Euphrates (444000 km2) at Haditha, Iraq. Ave. annual precipitation <100 mm (South) – 800 mm (north), ave. annual discharge 776 m3 s-1, ave. annual sediment load 1.4 107 t.||Al-Ansari et al. (1988); values calculated from original absolute values<br />
|- valign="top"<br />
| 8-year load; effect of sampling frequency||||-4 to 6 %||||<br />
|- valign="top"<br />
| Instantaneous concentration; effect of cross-section sampling method||Average coefficient of variation with respect to depth- & width-integrated reference concentration||25 %||Various in USA||Horowitz et al. (1990); values calculated from original table<br />
|- valign="top"<br />
| Instantaneous concentration; horizontal cross-section variation||Average coefficient of variation with respect to 5-point average||26 %||||<br />
|- valign="top"<br />
| Instantaneous concentration; sampler effect||Difference between two samplers (EPIC – USGS)||36 % initially, then -1 to -15 %||Humber catchment, UK||Evans et al. (1997); values gleaned from original graph<br />
|- valign="top"<br />
| Concentration exceedance frequency; effect of distribution assumption given censored data||Absolute difference between lognormal & normal models||0-3%, increasing with censoring||Little Cataraqui Creek (45 km2), Kingston Township, Ontario, Canada. Half urban, half forested, flat, ave. annual precipitation 900 mm (~22% snow).||van Buren et al. (1997)<br />
|- valign="top"<br />
| Load; effect of distribution assumption given censored data||Relative difference between lognormal & normal models, relative to lognormal model||25-37 % (calculated from original table)||||<br />
|- valign="top"<br />
| Instantaneous load; horizontal & vertical cross-section variation||Error of point turbidity measurement compared to width- & depth- integrated sample||-2.18 to -14.3 %||Humber catchment, UK, 8 sites (484.3-8231 km2). Wide range of geology, climate, soils and land cover, ave. annual precipitation 600 (east) – 1600 (Pennine Hills) mm.||Wass & Leeks (1999); values from original table<br />
|- valign="top"<br />
| 5-year load; effect of rating curve choice and sampling frequency||Bias relative to reference load from daily data (1979-1983); 4 rating curves tested; 4 sampling frequencies simulated via sub-sampling||-56 to 10 %||Rhine catchment above Rees, Germany (165000 km2), 5 locations. Temperate climate, 600 (lower Rhine) – 2500 (Alpes) mm precipitation, ave. annual discharge 2300 m3 s-1, ave. annual sediment load 3.14 106 t.||Asselman (2000)<br />
|- valign="top"<br />
| Annual & 5-year load; effect of rating curve choice and sampling frequency||Bias relative to reference load from daily data; 4 rating curves tested; 12 subsets of data used to construct rating curves; various sampling frequencies simulated via sub-sampling||WY 1996-2000: -7 to 6 % at 50 d down to -3 % at 1 d; WY 1989 (low flow year): -10 to 3 % at 30 d down to -6 % at 1 d; WY 1995 (median flow year): -11 to 7 % at 30 d down to -1 % at 1 d; WY1982 (high flow year): -11 to 8 % at 30 d down to 3 % at 1 d||Mississippi at Thebes, Illinois, USA (1847188 km2), 01/10/1980-30/09/2000||Horowitz (2003); values gleaned from original graphs<br />
|- valign="top"<br />
| ||||WY 1989-1993: -7 to 13 % at 50 d down to 2 % at 1 d; WY 1976 (low flow year): -11 to 10 % at 50 d down to 0 % at 1 d; WY 1980 (median flow year): -15 to 5 % at 30 d down to -3 % at 1 d; WY1987 (high flow year): -15 to 10 % at 30 d down to -5 % at 1 d||Rhine at Maxau, Germany (50200 km2), 31/10/1973-30/10/1993||<br />
|- valign="top"<br />
| Annual load; effect of temporal sampling method||Relative error with respect to reference method (composite sampling)||-9.1 to 2.7 %||USDA-ARS Grassland Soil & Water Research Laboratory (4.6-125.1 ha), Texas, USA. Vertisol soil, 2-4 % slope, mixed land cover.||Harmel & King (2005)<br />
|- valign="top"<br />
| Storm load; effect of minimum flow threshold for sampling||Professional judgement based on Harmel et al. (2002)||±1-81 %||||Harmel et al. (2006)<br />
|- valign="top"<br />
| Storm load; uncertainty due to manual sampling||||±15-50 % & more||||Quoted in Harmel et al. (2006): Slade (2004)<br />
|- valign="top"<br />
| Storm load; uncertainty due to automatic sampling (intake)||||14-33 %||||Quoted in Harmel et al. (2006): Martin et al. (1992)<br />
|- valign="top"<br />
| Storm load; uncertainty due to automatic sampling (timing)||||-65 to 51 %||||Quoted in Harmel et al. (2006)<br />
|- valign="top"<br />
| Storm load; analytical uncertainty||95 % confidence interval||-9.8 to 5.1 % (sandy); -5.3 to 4.4 % (fine)||||Quoted in Harmel et al. (2006): Gordon et al. (2000)<br />
|- valign="top"<br />
| Annual load; effect of sampling frequency||Bias relative to reference load from daily data (1961-1988); 28 sampling frequencies (2-30 d) simulated via sub-sampling (50 repeats, multiple years)||±30 % at 30 d (central 80 % from repeats & multiple years); decreasing with increasing sampling frequency||Mississippi at St Louis, Missouri, USA (251121 km2). Ave. annual discharge 20.1 l s-1 km-2, ave. annual sediment load 447 t yr-1 km-2.||Moatar et al. (2006); values gleaned from original graph; results from 35 more stations in USA and EU reported as well<br />
|- valign="top"<br />
| Instantaneous concentration||Coefficient of variation between dublicates||33 % (at 15 mg l-1); 10 % (at 242 mg l-1); 0.76 % (at 1707 mg l-1)||||Rode & Suhr (2007)<br />
|- valign="top"<br />
| Analytical errors||PDF, coefficient of variation||Lognormal, 13 %||||Quoted in Rode & Suhr (2007)<br />
|- valign="top"<br />
| Storm load; effect of estimation method||Bias relative to reference load from 1-6 h data (2 events in Sep 1994 & Nov 1999); 6 estimation methods tested; continuous thinning of data down to 1 sample per event||-52 to 19 %||Vène catchment, France (67 km2). Karst geology overlain by clay, mixed fruit/vegetables and urban land cover.||Salles et al. (2008); values gleaned from original graphs<br />
|- valign="top"<br />
| Storm load; effect of sampling frequency||||-25 to 30 % at 1 sample per event; decreasing exponentially with increasing sampling frequency||||<br />
|- valign="top"<br />
| Instantaneous concentration||Absolute difference between auto & manual dublicates||0-100 mg l-1; decreasing with flow||Rowden Experimental Research Platform (1 ha fields), Devon, UK. Dystric Gleysol soil, 7-9 % slope, grassland, ave. annual precipitation 1055 mm, 250 x 37 cm weir box.||Krueger et al. (2009)<br />
|- valign="top"<br />
| Storm concentrations & load||Total probable error (median in parentheses) based on RMSE propagation method||12-26(18) % (concentrations); 15-35(20) % (load)||Various in USA (2.2-5506 ha)||Harmel et al. (2009) based on Harmel et al. (2006)<br />
|- valign="top"<br />
| Concentration exceedance frequency||Uncertainty range based on bootstrapping low resolution data||Approx.10 %||Den Brook catchment (48 ha), Devon, UK. Dystric Gleysol soil, intensive grazing, ave. annual precipitation 1050 mm, flashy response, underdrained.||Bilotta et al. (2010); values gleaned from original graph<br />
|- valign="top"<br />
| Flow-weighted mean concentration (hourly)||Trapezoidal fuzzy number based on analysis of bulk uncertainty as function of number of sub-samples for three timesteps||±10 % core (5-6 samples per hour); ±50 % support (1 sample per hour)||||Krueger et al. (2012)<br />
|}<br />
<br />
== References ==<br />
<br />
Al-Ansari, N.A., Asaad, N.M., Walling, D.E., Hussan, S.A., 1988. The suspended sediment discharge of the River Euphrates at Haditha, Iraq: An assessment of the potential for establishing sediment rating curves. Geografiska Annaler, Series A, Physical Geography, 70(3): 203-213.<br />
<br />
Asselman, N. E. M., 2000. Fitting and interpretation of sediment rating curves. Journal of Hydrology, 234(3-4): 228-248.<br />
<br />
Bilotta, G.S., Krueger, T., Brazier, R.E., Butler, P., Freer, J., Hawkins, J.M.B., Haygarth, P.M., Macleod, C.J.A., Quinton, J.N., 2010. Assessing catchment-scale erosion and yields of suspended solids from improved temperate grassland. Journal of Environmental Monitoring, 12(3): 731-739.<br />
<br />
Evans, J.G., Wass, P.D., Hodgson, P., 1997. Integrated continuous water quality monitoring for the LOIS river programme. Science of the Total Environment, 194: 111-118.<br />
<br />
Gordon, J. D., Newland, C.A., Gagliardi, S.T., 2000. Laboratory performance in the sediment laboratory quality-assurance project, 1996-98. USGS Water Resources Investigations Report 99-4184. Washington, D.C.: USGS.<br />
<br />
Harmel, R.D., Cooper, R.J., Slade, R.M., Haney, R.L., Arnold, J.G., 2006. Cumulative uncertainty in measured streamflow and water quality data for small watersheds. Transactions of the ASABE, 49(3): 689-701.<br />
<br />
Harmel, R.D., King, K.W., 2005. Uncertainty in measured sediment and nutrient flux in runoff from small agricultural watersheds. Transactions of the ASAE, 48(5): 1713-1721.<br />
<br />
Harmel, R.D., Smith, D.R., King, K.W., Slade, R.M., 2009. Estimating storm discharge and water quality data uncertainty: A software tool for monitoring and modeling applications. Environmental Modelling & Software, 24(7): 832-842.<br />
<br />
Horowitz, A.J., 2003. An evaluation of sediment rating curves for estimating suspended sediment concentrations for subsequent flux calculations. Hydrological Processes, 17(17): 3387-3409.<br />
<br />
Horowitz, A.J., Rinella, F.A., Lamothe, P., Miller, T.L., Edwards, T.K., Roche, R.L., Rickert, D.A., 1990. Variations in suspended sediment and associated trace-element concentrations in selected riverine cross-sections. Environmental Science & Technology, 24(9): 1313-1320.<br />
<br />
Krueger, T., Quinton, J.N., Freer, J., Macleod, C.J.A., Bilotta, G.S., Brazier, R.E., Butler, P., Haygarth, P.M., 2009. Uncertainties in data and models to describe event dynamics of agricultural sediment and phosphorus transfer. Journal of Environmental Quality, 38(3): 1137-1148.<br />
<br />
Krueger, T., Quinton, J.N., Freer, J., Macleod, C.J.A., Bilotta, G.S., Brazier, R.E., Hawkins, J.M.B., Haygarth, P.M., 2012. Comparing empirical models for sediment and phosphorus transfer from soils to water at field and catchment scale under data uncertainty. European Journal of Soil Science. doi:10.1111/j.1365-2389.2011.01419.x<br />
<br />
Martin, G. R., Smoot, J. L., White, K. D., 1992. A comparison of surface-grab and cross-sectionally integrated stream-water-quality sampling methods. Water Environ. Res. 64(7): 866-876.<br />
<br />
McMillan, H., Krueger, T., Freer, J., 2012. Benchmarking observational uncertainties for hydrology: Rainfall, river discharge and water quality. Hydrological Processes.<br />
<br />
Moatar, F., Person, G., Meybeck, M., Coynel, A., Etcheber, H., Crouzet, P., 2006. The influence of contrasting suspended particulate matter transport regimes on the bias and precision of flux estimates. Science of the Total Environment, 370(2-3): 515-531.<br />
<br />
Rode, M., Suhr, U., 2007. Uncertainties in selected river water quality data. Hydrology and Earth System Sciences, 11(2): 863-874.<br />
<br />
Salles, C., Tournoud, M.G., Chu, Y., 2008. Estimating nutrient and sediment flood loads in a small Mediterranean river. Hydrological Processes, 22(2): 242-253.<br />
<br />
Slade, R. M., 2004. General Methods, Information, and Sources for Collecting and Analyzing Water-Resources Data. CD-ROM. Copyright 2004 Raymond M. Slade, Jr.<br />
<br />
van Buren, M.A., Watt, W.E., Marsalek, J., 1997. Application of the log-normal and normal distributions to stormwater quality parameters. Water Research, 31(1): 95-104.<br />
<br />
Walling, D.E., Teed, A., 1971. A simple pumping sampler for research into suspended sediment transport in small catchments. Journal of Hydrology, 13: 325-337.<br />
<br />
Wass, P.D., Leeks, G.J.L., 1999. Suspended sediment fluxes in the Humber catchment, UK. Hydrological Processes, 13(7): 935-953.<br />
<br />
[[Category:Uncertainty]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Water_quality_uncertainty_(nitrogen)&diff=1565Water quality uncertainty (nitrogen)2012-03-21T15:10:18Z<p>Ilja: </p>
<hr />
<div><br />
== Typical quantitative results of water quality uncertainty studies: Nitrogen. ==<br />
<br />
This table originated from McMillan et al. (2012) but is now open to the community to add to and use as a resource.<br />
<br />
BFI = base flow index; DIN = dissolved inorganic nitrogen; DN = dissolved nitrogen; PDF = probability density function; PN = particulate nitrogen; RMSE = root mean square error; SD = standard deviation; TKN = total Kjeldahl nitrogen; TN = total nitrogen<br />
<br />
{| {{table}}<br />
| align="center" style="background:#f0f0f0;"|'''Uncertainty Type'''<br />
| align="center" style="background:#f0f0f0;"|'''Estimation Method'''<br />
| align="center" style="background:#f0f0f0;"|'''Magnitude'''<br />
| align="center" style="background:#f0f0f0;"|'''Location'''<br />
| align="center" style="background:#f0f0f0;"|'''Reference'''<br />
|- valign="top"<br />
| Annual load (NO3-N); effect of sampling frequency||8 d routine sampling compared to 2 h composite (8 15 min sub-samples; Nov 1974 – May 1975); all via rating curve||Bias 18 %||River Main at Andraid, Co. Antrim, Northern Ireland (709 km2). Basaltic glacial till geology, 10% arable, 53% grassland, 24% rough grazing, population 54549 (65% connected to sewer), ave. annual precipitation 1181 mm, flashy response.||Stevens & Smith (1978)<br />
|- valign="top"<br />
| Annual load (TN); effect of estimation method & sampling frequency||Bias relative to interpolated stage-triggered instantaneous load timeseries (2-15 min during rising stage, 1-4 h during falling stage, 4-24 h during baseflow); 13 estimation methods tested; 7 sampling frequencies simulated via sub-sampling||-20 to 30 % at 12 samples per year down to -12 to 10 % at 104 samples per year; high-flow biased stratified sampling more biased and less precise||Gelbæk catchment (8.5 km2), Eastern Jutland, Denmark. Lowland, low baseflow, high event-responsiveness, ave. discharge 232 mm.||Kronvang & Bruhn (1996); results gleaned from original graphs<br />
|- valign="top"<br />
| ||||-11 to 25 % at 12 samples per year down to -2 to 9 % at 104 samples per year; high-flow biased stratified sampling more biased and less precise||Gjern Å catchment (103 km2), Eastern Jutland, Denmark. Lowland, high baseflow, low event-responsiveness, ave. discharge 361 mm.||<br />
|- valign="top"<br />
| Annual load (NO3-N); effect of temporal sampling method||Relative error with respect to reference method (composite sampling)||-9.2 to 2 %||USDA-ARS Grassland Soil & Water Research Laboratory (4.6-125.1 ha), Texas, USA. Vertisol soil, 2-4 % slope, mixed land cover.||Harmel & King (2005)<br />
|- valign="top"<br />
| Storm load; effect of minimum flow threshold for sampling||Professional judgement based on Harmel et al. (2002)||±1-81 %||||Harmel et al. (2006)<br />
|- valign="top"<br />
| Storm load; uncertainty due to manual sampling||||±5-25 % (dissolved); ±15-50 % & more (suspended)||||Quoted in Harmel et al. (2006): Slade (2004)<br />
|- valign="top"<br />
| Storm load; uncertainty due to automatic sampling (intake)||||0 % (TN); 0-4 % (DN)||||Quoted in Harmel et al. (2006): Martin et al. (1992)<br />
|- valign="top"<br />
| Storm load; uncertainty due to automatic sampling (timing)||||-65 to 51 %||||Quoted in Harmel et al. (2006)<br />
|- valign="top"<br />
| Storm load; effect of sample preservation & storage||||-90 to 83 % (NH3-N); -65 to 71 % (NO3-N); -84 to 49 % (TKN)||||<br />
|- valign="top"<br />
| Storm load; analytical uncertainty||||Up to ±400 % (DN); ±4-30 % (PN)||||<br />
|- valign="top"<br />
| Total uncertainty (TN)||PDF, mean, SD||Normal, 0, 10 %||Odense basin (1190 km2), Denmark. Glacial/interglacial sediment geology, low rolling hills, ave. annual precipitation/evapotranspiration 900/600 mm.||Refsgaard et al. (2006)<br />
|- valign="top"<br />
| Total analytical uncertainty (NH4-N)||SD based on lab standards||4-19 %, decreasing with concentration||2 streams in Victoria, Australia, 1 forested, 1 urbanised.||Hanafi et al. (2007)<br />
|- valign="top"<br />
| Instantaneous concentration (NO3-N); analytical uncertainty||SD||0, 40, 50, 50 µg l-1 at 100, 200, 800, 2100 µg l-1, respectively||||Rode & Suhr (2007)<br />
|- valign="top"<br />
| Instantaneous concentration (NH4-N); analytical uncertainty||Mean SD||5-8 %||||<br />
|- valign="top"<br />
| Instantaneous concentration (NH4-N); horizontal cross-section variation||Variation from 10-point cross-section average||Up to 50 % & more||Elbe river at Dom Muehlenholz, Germany||<br />
|- valign="top"<br />
| Analytical errors||PDF, coefficient of variation||Normal, 5 % (NO3, Cadmium Reduction Method); normal, 2.5 % (NO3, Electrode Method); normal, 4 % (NO3, Ion Chromatography); normal, 6 % (NO2); normal, 11 % (NH4)||||Quoted in Rode & Suhr (2007): Clesceri et al. (1998)<br />
|- valign="top"<br />
| Instantaneous concentration; analytical uncertainty||Difference to quality control standard||±5 %||Lough Mask catchment, Ireland||Donohue & Irvine (2008)<br />
|- valign="top"<br />
| Instantaneous concentration; effect of lab sub-sampling||Coefficient of variation with respect to 3-sub-sample average (95 % confidence interval)||9.6-11.2 % (TN), 71.8-82 % (lakes) & 77-82.2 % (rivers) attributable to sub-sample variability; 4-6.6 % (DIN), 53.4-71.2 % (lakes) & 67.7-75.1 % (rivers) attributable to sub-sample variability||||<br />
|- valign="top"<br />
| Instantaneous concentration; effect of lab sub-sampling||Mean minimum detectable difference between mean concentrations of two sets of 10 replicate sub-samples from same sample||0.2 mg l-1 (TN); 0.02 mg l-1 (DIN); gleaned from original graphs||||<br />
|- valign="top"<br />
| Storm load (TN); effect of estimation method||Bias relative to reference load from 1-6 h data (2 events in Sep 1994 & Nov 1999); 6 estimation methods tested; continuous thinning of data down to 1 sample per event||-22 to 11 %||Vène catchment, France (67 km2). Karst geology overlain by clay, mixed fruit/vegetables and urban land cover.||Salles et al. (2008); values gleaned from original graphs<br />
|- valign="top"<br />
| Storm load; effect of sampling frequency||||-25 to 20 % (TN), -25 to 10 % (NO3-N) at 1 sample per event; decreasing exponentially with increasing sampling frequency||||<br />
|- valign="top"<br />
| Storm concentrations & load||Total probable error (median in parentheses) based on RMSE propagation method||13-102(17) % (NO3-N concentrations); 14-103(22) % (NO3-N load); 14-104(23) % (TN concentrations); 15-105(27) % (TN load)||Various in USA (2.2-5506 ha)||Harmel et al. (2009) based on Harmel et al. (2006)<br />
|- valign="top"<br />
| Annual load (TON); effect of sampling frequency||Bias relative to reference load from stratified data (2-4 per d when dry, up to 8 per d when wet; Feb 2005 – Jan 2006); 5 sampling frequencies simulated via sub-sampling||-4.2 to 11.2 % (monthly); -3.5 to 3.9 % (fortnightly); -1.8 to 3.5 % (weekly); -0.5 to 0.9 % (daily); -0.1 to 0.3 % (12 h)||Frome at East Stoke, UK (414 km2), Mainly chalk geology, mainly grassland & cereals land cover, one town, ave. annual precipitation 1020 mm, ave. annual discharge 6.38 m3 s-1, BFI 0.84.||Bowes et al. (2009)<br />
|- valign="top"<br />
| Precision of various high frequency nutrient analysers||As stated by manufacturer||±5 % of range (NH4-N & NO3-N, WTWTM VARiON; NH4-N & NO3-N, GreenspanTM Aqualab; NO3-N, YSITM YSI96000); ±3 % of range (TN, NH4-N, NO3-N & NO2-N, SysteaTM Micromac C; NO3-N & NO2-N, S::canTM Spectroanalyser); ±2 % of range (NH4-N & NO3-N, EnvirotechTM AutoLAB/MicroLAB; NH4-N, NO3-N & NO2-N, FIALabTM SIA; NO3-N, SatlanticTM ISUS)||||Bende-Michl & Hairsine (2010)<br />
|}<br />
<br />
== References ==<br />
<br />
Bende-Michl, U., Hairsine, P.B., 2010. A systematic approach to choosing an automated nutrient analyser for river monitoring. Journal of Environmental Monitoring, 12(1): 127-134.<br />
<br />
Bowes, M. J., Smith, J.T., Neal, C., 2009. The value of high-resolution nutrient monitoring: A case study of the River Frome, Dorset, UK. Journal of Hydrology, 378(1-2): 82-96.<br />
<br />
Clesceri, L.S., Greenberg, A.E., Eaton, A.D., (Editors), 1998. Standard methods for the examination of water & wastewater. American Public Health Association, American Water Works Association and Water Environment Federation. 20th edition.<br />
<br />
Donohue, I., Irvine, K., 2008. Quantifying variability within water samples: The need for adequate subsampling. Water Research, 42(1-2): 476-482.<br />
<br />
Hanafi, S., Grace, M., Webb, J.A., Hart, B., 2007. Uncertainty in nutrient spiraling: Sensitivity of spiraling indices to small errors in measured nutrient concentration. Ecosystems, 10(3): 477-487.<br />
<br />
Harmel, R.D., Cooper, R.J., Slade, R.M., Haney, R.L., Arnold, J.G., 2006. Cumulative uncertainty in measured streamflow and water quality data for small watersheds. Transactions of the ASABE, 49(3): 689-701.<br />
<br />
Harmel, R.D., King, K.W., 2005. Uncertainty in measured sediment and nutrient flux in runoff from small agricultural watersheds. Transactions of the ASAE, 48(5): 1713-1721.<br />
<br />
Harmel, R.D., Smith, D.R., King, K.W., Slade, R.M., 2009. Estimating storm discharge and water quality data uncertainty: A software tool for monitoring and modeling applications. Environmental Modelling & Software, 24(7): 832-842.<br />
<br />
Kronvang, B., Bruhn, A.J., 1996. Choice of sampling strategy and estimation method for calculating nitrogen and phosphorus transport in small lowland streams. Hydrological Processes, 10(11): 1483-1501.<br />
<br />
Martin, G. R., Smoot, J. L., White, K. D., 1992. A comparison of surface-grab and cross-sectionally integrated stream-water-quality sampling methods. Water Environ. Res. 64(7): 866-876.<br />
<br />
McMillan, H., Krueger, T., Freer, J., 2012. Benchmarking observational uncertainties for hydrology: Rainfall, river discharge and water quality. Hydrological Processes.<br />
<br />
Refsgaard, J.C., van der Keur, P., Nilsson, B., Mueller-Wohlfeil, D.I., Brown, J., 2006. Uncertainties in river basin data at various support scales - Example from Odense Pilot River Basin. Hydrology Earth System Sciences Discussions, 3(4): 1943-1985.<br />
<br />
Rode, M., Suhr, U., 2007. Uncertainties in selected river water quality data. Hydrology and Earth System Sciences, 11(2): 863-874.<br />
<br />
Salles, C., Tournoud, M.G., Chu, Y., 2008. Estimating nutrient and sediment flood loads in a small Mediterranean river. Hydrological Processes, 22(2): 242-253.<br />
<br />
Slade, R. M., 2004. General Methods, Information, and Sources for Collecting and Analyzing Water-Resources Data. CD-ROM. Copyright 2004 Raymond M. Slade, Jr.<br />
<br />
Stevens, R. J., Smith, R.V., 1978. A comparison of discrete and intensive sampling for measuring the loads of nitrogen and phosphorus in the river main, County Antrim. Water Research, 12(10): 823-830.<br />
<br />
[[Category:Uncertainty]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Water_quality_uncertainty_(phosphorus)&diff=1564Water quality uncertainty (phosphorus)2012-03-21T15:09:56Z<p>Ilja: </p>
<hr />
<div><br />
== Typical quantitative results of water quality uncertainty studies: Phosphorus. ==<br />
<br />
This table originated from McMillan et al. (2012) but is now open to the community to add to and use as a resource.<br />
<br />
BFI = base flow index; DP = dissolved phosphorus; FRP(X µm) = filtered reactive phosphorus (filter size); PDF = probability density function; PP = particulate phosphorus; RMSE = root mean square error; SD = standard deviation; SRP = soluble reactive phosphorus; TIP = total inorganic phosphorus; TP = total phosphorus<br />
<br />
{| {{table}}<br />
| align="center" style="background:#f0f0f0;"|'''Uncertainty Type'''<br />
| align="center" style="background:#f0f0f0;"|'''Estimation Method'''<br />
| align="center" style="background:#f0f0f0;"|'''Magnitude'''<br />
| align="center" style="background:#f0f0f0;"|'''Location'''<br />
| align="center" style="background:#f0f0f0;"|'''Reference'''<br />
|- valign="top"<br />
| Annual load; effect of sampling frequency||8 d routine sampling compared to 2 h composite (8 15 min sub-samples; Nov 1974 – May 1975); all via rating curve||Bias -43 % (TP); 12 % (SRP)||River Main at Andraid, Co. Antrim, Northern Ireland (709 km2). Basaltic glacial till geology, 10% arable, 53% grassland, 24% rough grazing, population 54549 (65% connected to sewer), ave. annual precipitation 1181 mm, flashy response.||Stevens & Smith (1978)<br />
|- valign="top"<br />
| Annual load; effect of estimation method & sampling frequency||Bias relative to reference load from daily data (Mar 1976 to 28 Feb 1977); 3 sampling frequencies simulated via sub-sampling (222-680 repeats); 3-11 estimation methods tested||Average bias, biweekly: -2 to 20 %; Average bias, bi-weekly biased to high flows: 0-2 %; Average bias, bi-weekly biased to low flows: -1 to 2 %||Grand River at Eastmanville, Michigan, USA (13550 km2). Cropland; ave. discharge 101 m3 s-1; ave. annual TP load 1730 kg P d-1.||Dolan et al. (1981); values calculated from original absolute values<br />
|- valign="top"<br />
| Annual load (TP); effect of estimation method & sampling frequency||Bias relative to interpolated stage-triggered instantaneous load timeseries (2-15 min during rising stage, 1-4 h during falling stage, 4-24 h during baseflow); 13 estimation methods tested; 7 sampling frequencies simulated via sub-sampling||-50 to 150 % at 12 samples per year down to -30 to 40 % at 104 samples per year; high-flow biased stratified sampling more biased and less precise||Gelbæk catchment (8.5 km2), Eastern Jutland, Denmark. Lowland, low baseflow, high event-responsiveness, ave. discharge 232 mm.||Kronvang & Bruhn (1996); results gleaned from original graphs<br />
|- valign="top"<br />
| ||||-30 to 110 % at 12 samples per year down to -10 to 10 % at 104 samples per year; high-flow biased stratified sampling more biased and less precise||Gjern Å catchment (103 km2), Eastern Jutland, Denmark. Lowland, high baseflow, low event-responsiveness, ave. discharge 361 mm.||<br />
|- valign="top"<br />
| Instantaneous concentration; analytical uncertainty||Standard uncertainty (square root of variance)||0.25 µg l-1 (FRP(0.2 µm)); 0.32 µg l-1 (TP)||Latrobe River catchment, Victoria, Australia||Lovell et al. (2001)<br />
|- valign="top"<br />
| Instantaneous concentration; spot sampling uncertainty||Standard uncertainty (square root of variance) based on 3 repeats||2.09 µg l-1 (FRP(0.2 µm)); 1.05 µg l-1 (TP)||||<br />
|- valign="top"<br />
| Instantaneous concentration; effect of spatial variation within 100 m reach||Standard uncertainty (square root of variance) based on 6 sampling spots||20.8 µg l-1 (FRP(0.2 µm)); 18.6 µg l-1 (TP)||||<br />
|- valign="top"<br />
| Annual load; effect of temporal sampling method||Relative error with respect to reference method (composite sampling)||-9.2 to 2 % (PO4-P)||USDA-ARS Grassland Soil & Water Research Laboratory (4.6-125.1 ha), Texas, USA. Vertisol soil, 2-4 % slope, mixed land cover.||Harmel & King (2005)<br />
|- valign="top"<br />
| Storm load; effect of minimum flow threshold for sampling||Professional judgement based on Harmel et al. (2002)||±1-81 %||||Harmel et al. (2006)<br />
|- valign="top"<br />
| Storm load; uncertainty due to manual sampling||||±5-25 % (dissolved); ±15-50 % & more (suspended)||||Quoted in Harmel et al. (2006): Slade (2004)<br />
|- valign="top"<br />
| Storm load; uncertainty due to automatic sampling (intake)||||0-17 % (TP); 0 % (DP)||||Quoted in Harmel et al. (2006): Martin et al. (1992)<br />
|- valign="top"<br />
| Storm load; uncertainty due to automatic sampling (timing)||||-65 to 51 %||||Quoted in Harmel et al. (2006)<br />
|- valign="top"<br />
| Storm load; effect of sample preservation & storage||||-64 to 92 % (TP); -52 to 600 % (DP)||||<br />
|- valign="top"<br />
| Storm load; analytical uncertainty||||Up to ±400 % (DP); -2 to 16 % (PP)||||<br />
|- valign="top"<br />
| Flow-weighted mean concentration (TIP, weekly)||Triangular fuzzy number||±40 % support||Crighton Royal Farm (0.5 ha fields), Dumfries, Scotland, UK. Silty clay loam soil, grassland, macropore flow, ave. annual precipitation 1054 mm.||Beven et al. (2006)<br />
|- valign="top"<br />
| Total uncertainty||PDF, mean, SD||Normal, 0, 12 % (TP)||Odense basin (1190 km2), Denmark. Glacial/interglacial sediment geology, low rolling hills, ave. annual precipitation/evapotranspiration 900/600 mm.||Refsgaard et al. (2006)<br />
|- valign="top"<br />
| Total analytical uncertainty||SD based on lab standards||5-15 % (PO4-P), decreasing with concentration||2 streams in Victoria, Australia, 1 forested, 1 urbanised.||Hanafi et al. (2007)<br />
|- valign="top"<br />
| Instantaneous concentration; horizontal cross-section variation||Coefficient of variation with respect to 10-point cross-section average||7 % (SRP)||Elbe river at Dom Muehlenholz, Germany||Rode & Suhr (2007)<br />
|- valign="top"<br />
| Analytical errors||PDF, coefficient of variation||Normal, 6 % (TP, SRP)||||Quoted in Rode & Suhr (2007): Clesceri et al. (1998)<br />
|- valign="top"<br />
| Daily load||Total probable error based on RMSE propagation method||<10 % (TP)||Various in Illinois, USA. Glacial moraine geology, Mollisol soil, flat, mainly corn & soybean land cover, underdrained.||Gentry et al. (2007) based on Harmel et al. (2006)<br />
|- valign="top"<br />
| Instantaneous concentration; analytical uncertainty||Difference to quality control standard||±5 %||Lough Mask catchment, Ireland||Donohue & Irvine (2008)<br />
|- valign="top"<br />
| Instantaneous concentration; effect of lab sub-sampling||Coefficient of variation with respect to 3-sub-sample average (95 % confidence interval)||6.4-8 % (TP); 6.1-7.5 % (SRP) (both almost 100 % attributable to sub-sample variability)||||<br />
|- valign="top"<br />
| Instantaneous concentration; effect of lab sub-sampling||Mean minimum detectable difference between mean concentrations of two sets of 10 replicate sub-samples from same sample||2 µg l-1 (TP); 0.4 µg l-1 (SRP); gleaned from original graphs||||<br />
|- valign="top"<br />
| Storm load (TP); effect of estimation method||Bias relative to reference load from 1-6 h data (2 events in Sep 1994 & Nov 1999); 6 estimation methods tested; continuous thinning of data down to 1 sample per event||-38 to 36 %||Vène catchment, France (67 km2). Karst geology overlain by clay, mixed fruit/vegetables and urban land cover.||Salles et al. (2008); values gleaned from original graphs<br />
|- valign="top"<br />
| Storm load; effect of sampling frequency||||-25 to 30 % (TP, PP), -25 to 65 % (SRP) at 1 sample per event; decreasing exponentially with increasing sampling frequency||||<br />
|- valign="top"<br />
| Storm concentrations & load||Total probable error (median in parentheses) based on RMSE propagation method||13-103(19) % (PO4-P concentrations); 14-104(23) % (PO4-P load); 16-104(24) % (TP concentrations); 17-105(27) % (TP load)||Various in USA (2.2-5506 ha)||Harmel et al. (2009) based on Harmel et al. (2006)<br />
|- valign="top"<br />
| Concentrations & load||Total probable error based on RMSE propagation method||27 % (PO4-P concentrations); 28 % (PO4-P load)||||Quoted in Harmel et al. (2009): Keener et al. (2007)<br />
|- valign="top"<br />
| Instantaneous concentration (TP)||Absolute difference between auto & manual dublicates||0-400 µg l-1; decreasing with flow||Rowden Experimental Research Platform (1 ha fields), Devon, UK. Dystric Gleysol soil, 7-9 % slope, grassland, ave. annual precipitation 1055 mm, surface soil P ~540 mg kg-1, 250 x 37 cm weir box.||Krueger et al. (2009)<br />
|- valign="top"<br />
| Annual load; effect of sampling frequency||Bias relative to reference load from stratified data (2-4 per d when dry, up to 8 per d when wet; Feb 2005 – Jan 2006); 5 sampling frequencies simulated via sub-sampling||Monthly: -21.3 to 35.2 % (TP); -10.6 to 27.9 % (SRP); Fortnightly: -17.5 to 28.1 % (TP); -11 to 15.3 % (SRP); Weekly: -11.6 to 15.4 % (TP); -4.9 to 6.5 % (SRP); Daily: 0 to 4 % (TP); -2.1 to 2.5 % (SRP); 12h: -1.9 to 0.7 % (TP); -0.9 to 1.1 % (SRP)||Frome at East Stoke, UK (414 km2), Mainly chalk geology, mainly grassland & cereals land cover, one town, ave. annual precipitation 1020 mm, ave. annual discharge 6.38 m3 s-1, BFI 0.84.||Bowes et al. (2009)<br />
|- valign="top"<br />
| Precision of various high frequency nutrient analysers||As stated by manufacturer||±2 % of range (PO4-P, GreenspanTM Aqualab; PO4-P, EcotechTM FIA NUT1000; PO4-P, FIALabTM SIA); ±3 % of range (TP & PO4-P, SysteaTM Micromac C; PO4-P, EnvirotechTM AutoLAB/MicroLAB)||||Bende-Michl & Hairsine (2010)<br />
|- valign="top"<br />
| Annual load (TP); effect of temporal sampling method||Bias relative to interpolated 20 min instantaneous load timeseries||Median bias of various methods -50 to +30 %||Co. Monaghan, Ireland (5 km2). Drumlin soils, grassland, flashy, point sources.||Jordan & Cassidy (2011)<br />
|- valign="top"<br />
| Flow-weighted mean concentration (TP, hourly)||Trapezoidal fuzzy number based on analysis of bulk uncertainty as function of number of sub-samples for three timesteps||±10 % core (5-6 samples per hour); ±50 % support (1 sample per hour)||Den Brook catchment (48 ha), Devon, UK. Dystric Gleysol soil, intensive grazing, ave. annual precipitation 1050 mm, flashy response, underdrained.||Krueger et al. (2012)<br />
|}<br />
<br />
== References ==<br />
<br />
Bende-Michl, U., Hairsine, P.B., 2010. A systematic approach to choosing an automated nutrient analyser for river monitoring. Journal of Environmental Monitoring, 12(1): 127-134.<br />
<br />
Beven, K., Page, T., McGechan, M., 2006. Uncertainty estimation in phosphorus models. In: Radcliffe, D.E., Cabrera, M.L. (Eds.), Modeling phosphorus in the environment. CRC Press, Boca Raton, pp. 131-160.<br />
<br />
Bowes, M. J., Smith, J.T., Neal, C., 2009. The value of high-resolution nutrient monitoring: A case study of the River Frome, Dorset, UK. Journal of Hydrology, 378(1-2): 82-96.<br />
<br />
Clesceri, L.S., Greenberg, A.E., Eaton, A.D., (Editors), 1998. Standard methods for the examination of water & wastewater. American Public Health Association, American Water Works Association and Water Environment Federation. 20th edition.<br />
<br />
Dolan, D. M., Yui, A.K., Geist, R.D., 1981. Evaluation of river load estimation methods for total phosphorus. Journal of Great Lakes Research, 7(3): 207-214.<br />
<br />
Donohue, I., Irvine, K., 2008. Quantifying variability within water samples: The need for adequate subsampling. Water Research, 42(1-2): 476-482.<br />
<br />
Gentry, L.E., David, M.B., Royer, T.V., Mitchell, C.A., Starks, K.M., 2007. Phosphorus transport pathways to streams in tile-drained agricultural watersheds. Journal of Environmental Quality, 36(2): 408-415.<br />
<br />
Hanafi, S., Grace, M., Webb, J.A., Hart, B., 2007. Uncertainty in nutrient spiraling: Sensitivity of spiraling indices to small errors in measured nutrient concentration. Ecosystems, 10(3): 477-487.<br />
<br />
Harmel, R.D., Cooper, R.J., Slade, R.M., Haney, R.L., Arnold, J.G., 2006. Cumulative uncertainty in measured streamflow and water quality data for small watersheds. Transactions of the ASABE, 49(3): 689-701.<br />
<br />
Harmel, R.D., King, K.W., 2005. Uncertainty in measured sediment and nutrient flux in runoff from small agricultural watersheds. Transactions of the ASAE, 48(5): 1713-1721.<br />
<br />
Harmel, R.D., Smith, D.R., King, K.W., Slade, R.M., 2009. Estimating storm discharge and water quality data uncertainty: A software tool for monitoring and modeling applications. Environmental Modelling & Software, 24(7): 832-842. <br />
<br />
Jordan, P., Cassidy, R., 2011. Technical Note: Assessing a 24/7 solution for monitoring water quality loads in small river catchments. Hydrology and Earth System Sciences, 15(10): 3093-3100.<br />
<br />
Keener, V.W., Ingram, K.T., Jacobson, B., Jones, J.W., 2007. Effects of El-Nino / Southern Oscillation on simulated phosphorus loading in South Florida. Trans. ASABE 50 (6), 2081–2089.<br />
<br />
Kronvang, B., Bruhn, A.J., 1996. Choice of sampling strategy and estimation method for calculating nitrogen and phosphorus transport in small lowland streams. Hydrological Processes, 10(11): 1483-1501.<br />
<br />
Krueger, T., Quinton, J.N., Freer, J., Macleod, C.J.A., Bilotta, G.S., Brazier, R.E., Butler, P., Haygarth, P.M., 2009. Uncertainties in data and models to describe event dynamics of agricultural sediment and phosphorus transfer. Journal of Environmental Quality, 38(3): 1137-1148.<br />
<br />
Krueger, T., Quinton, J.N., Freer, J., Macleod, C.J.A., Bilotta, G.S., Brazier, R.E., Hawkins, J.M.B., Haygarth, P.M., 2012. Comparing empirical models for sediment and phosphorus transfer from soils to water at field and catchment scale under data uncertainty. European Journal of Soil Science. doi:10.1111/j.1365-2389.2011.01419.x<br />
<br />
Lovell, B., McKelvie, I.D., Nash, D., 2001. Sampling design for total and filterable reactive phosphorus monitoring in a lowland stream: considerations of spatial variability, measurement uncertainty and statistical power. Journal of Environmental Monitoring, 3(5): 463-468.<br />
<br />
Martin, G. R., Smoot, J. L., White, K. D., 1992. A comparison of surface-grab and cross-sectionally integrated stream-water-quality sampling methods. Water Environ. Res. 64(7): 866-876.<br />
<br />
McMillan, H., Krueger, T., Freer, J., 2012. Benchmarking observational uncertainties for hydrology: Rainfall, river discharge and water quality. Hydrological Processes.<br />
<br />
Refsgaard, J.C., van der Keur, P., Nilsson, B., Mueller-Wohlfeil, D.I., Brown, J., 2006. Uncertainties in river basin data at various support scales - Example from Odense Pilot River Basin. Hydrology Earth System Sciences Discussions, 3(4): 1943-1985.<br />
<br />
Rode, M., Suhr, U., 2007. Uncertainties in selected river water quality data. Hydrology and Earth System Sciences, 11(2): 863-874.<br />
<br />
Salles, C., Tournoud, M.G., Chu, Y., 2008. Estimating nutrient and sediment flood loads in a small Mediterranean river. Hydrological Processes, 22(2): 242-253.<br />
<br />
Slade, R. M., 2004. General Methods, Information, and Sources for Collecting and Analyzing Water-Resources Data. CD-ROM. Copyright 2004 Raymond M. Slade, Jr. <br />
<br />
Stevens, R. J., Smith, R.V., 1978. A comparison of discrete and intensive sampling for measuring the loads of nitrogen and phosphorus in the river main, County Antrim. Water Research, 12(10): 823-830.<br />
<br />
[[Category:Uncertainty]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Rainfall_radar_and_satellite_uncertainty&diff=1563Rainfall radar and satellite uncertainty2012-03-21T15:08:54Z<p>Ilja: </p>
<hr />
<div><br />
== Typical quantitative results of rainfall uncertainty studies: Radar and Satellite. ==<br />
<br />
This table originated from McMillan et al. (2012) but is now open to the community to add to and use as a resource.<br />
<br />
RMSE = root mean square error; SD = standard deviation<br />
<br />
{| {{table}}<br />
| align="center" style="background:#f0f0f0;"|'''Uncertainty Type'''<br />
| align="center" style="background:#f0f0f0;"|'''Estimation Method'''<br />
| align="center" style="background:#f0f0f0;"|'''Magnitude'''<br />
| align="center" style="background:#f0f0f0;"|'''Location'''<br />
| align="center" style="background:#f0f0f0;"|'''Reference'''<br />
|-<br />
| '''''Radar'''''<br />
|- valign="top"<br />
| Error between radar estimate and gauge network||Radar RMSE with respect to 30 raingauges||10 % for storms >30 mm after radar bias correction using high quality rain gauge data; when all gauges were used for bias correction without prior quality control RMSE was 10-40 %||ARS Goodwin Creek experimental watershed, Mississippi, USA||Steiner et al. (1999)<br />
|- valign="top"<br />
| Error between radar estimate and gauge network||Standard error of residuals compared with 8 rain gauges in 2 km2 area||50% (low relief) at 4 mm/15 min rain rate; presented graphically for rain rates 0.4-10 mm/15 min||Brue catchment, UK (135 km2). 20-250 m a.s.l., temperate climate, orographic rainfall.||Wood et al. (2000)<br />
|- valign="top"<br />
| ||Standard error of residuals compared with 49 rain gauges in 135 km2 area||55 % at 2km resolution, 60 % at 5 km resolution, for rain rate 4 mm/15 min; presented graphically for rain rates 0.2-8 mm/15 min||||<br />
|- valign="top"<br />
| Error between radar (WSR-88D) estimate and gauge network||SD of the stochastic component of multiplicative error||Conditioned on distance from radar, timescale of observation & season; asymptotic SD at high rainfall rates in the range 0.1-0.7, typically 0.5 for hourly data||Oklahoma, USA. Rainfall 800 mm yr-1, dominated by midlatitude convective systems.||Ciach et al. (2007)<br />
|- valign="top"<br />
| Error between radar (S-band) estimate and gauge network||SD of residuals||Approx. 0.3 (proportion of mean rain rate) for hourly data over 0-100 km distance from radar; values also given for 1, 2, 6, 12 hours & 0-50, 50-100, 0-100 km distances||Cévennes-Vivarais region, France. 200 km *160 km convective and frontal rainfall.||Kirstetter et al. (2010)<br />
|- valign="top"<br />
| Error between radar (WSR-88D) estimate and gauge network||SD of residuals (2 research gauge networks)||0.48 (hourly, 8 km resolution), 1.07 (hourly, 1 km resolution), proportion of mean rain rate; values also given for 15 min, 1 hour at scales 0.5, 1, 2, 4, 8 km||Iowa, USA||Seo & Krajewski (2010); raingauge networks used paired gauges at all sites<br />
|- valign="top"<br />
| Error between radar (X-band) estimate and gauge network||Mean and SD of bias for pixel-based comparison between 2 radars and 20 gauges.||Using a Z-R relationship to estimate rainfall, the mean bias for the 2 radars was -0.24, -0.27; with SD of the relative error 0.46, 0.48.||Southwest Oklahoma, USA. Raingauges – radar distance up to 35 km. Study used 4 storm events of heavy/ broken squall lines with embedded convective cells. ||Vieux and Imgarten (2011)<br />
|-<br />
| '''''Satellite'''''<br />
|- valign="top"<br />
| Bias in estimates of surface rain rate from TRMM (Tropical Rainfall Measuring Mission)||Bayesian modelling approach to estimate SD of each parameter in algorithm used to calculate surface rain rate||SD of combined multiplicative bias in rain rate presented graphically as a function of rain rate: 40-60% at rates up to 18 mm h-1, 150 % at 25 mm h-1,||All oceanic pixels for 10 TRMM orbits||L’Ecuyer and Stephens (2002)<br />
|- valign="top"<br />
| Bias of two NASA satellite products (infrared & passive microwave)||Mean & variance in multiplicative bias at hourly timesteps & 0.25º resolution compared with ground radar||Mean multiplicative hourly bias 0.35-1.09 (with SD of 0.73-0.84) over 4-month study period.||Oklahoma, USA. Southern Plains, 95-100°W, 34-37°N.||Hossain & Anagnostou (2006)<br />
|}<br />
<br />
== References ==<br />
<br />
Ciach, G.J., Krajewski, W.F., Villarini, G., 2007. Product-error-driven uncertainty model for probabilistic quantitative precipitation estimation with NEXRAD data. Journal of Hydrometeorology, 8(6): 1325-1347.<br />
<br />
Hossain, F., Anagnostou, E.N., 2006. Assessment of a multidimensional satellite rainfall error model for ensemble generation of satellite rainfall data. IEEE Geoscience and Remote Sensing Letters, 3(3): 419-423.<br />
<br />
Kirstetter, P.E., Delrieu, G., Boudevillain, B., Obled, C., 2010. Toward an error model for radar quantitative precipitation estimation in the Cevennes-Vivarais region, France. Journal of Hydrology, 394(1-2): 28-41.<br />
<br />
L’Ecuyer, T. S., and G. L. Stephens, 2002. An uncertainty model for Bayesian Monte Carlo retrieval algorithms: Application to the TRMM observing system. Quart. J. Roy. Meteor. Soc.,128, 1713–1737.<br />
<br />
McMillan, H., Krueger, T., Freer, J., 2012. Benchmarking observational uncertainties for hydrology: Rainfall, river discharge and water quality. Hydrological Processes.<br />
<br />
Seo, B.C., Krajewski, W.F., 2010. Scale dependence of radar rainfall uncertainty: Initial evaluation of NEXRAD's new super-resolution data for hydrologic applications. Journal of Hydrometeorology, 11(5): 1191-1198.<br />
<br />
Steiner, M., Smith, J.A., Burges, S.J., Alonso, C.V., Darden, R.W., 1999. Effect of bias adjustment and rain gauge data quality control on radar rainfall estimation. Water Resources Research, 35(8): 2487-2503.<br />
<br />
Vieux, B.E., Imgarten, J.M., 2011. On the scale-dependent propagation of hydrologic uncertainty using high-resolution X-band radar rainfall estimates. Atmospheric Research. 103: 96-105.<br />
<br />
Wood, S.J., Jones, D.A., Moore, R.J., 2000. Accuracy of rainfall measurement for scales of hydrological interest. Hydrology and Earth System Sciences, 4(4): 531-543.<br />
[http://essayshelp.org/service.php online essay service]<br />
<br />
[[Category:Uncertainty]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Stage_measurement_uncertainty&diff=1562Stage measurement uncertainty2012-03-21T15:07:40Z<p>Ilja: </p>
<hr />
<div><br />
== Typical quantitative results of discharge uncertainty studies: Stage Uncertainty. ==<br />
<br />
This table originated from McMillan et al. (2012) but is now open to the community to add to and use as a resource.<br />
<br />
SD = standard deviation<br />
<br />
{| {{table}}<br />
| align="center" style="background:#f0f0f0;"|'''Uncertainty Type'''<br />
| align="center" style="background:#f0f0f0;"|'''Estimation Method'''<br />
| align="center" style="background:#f0f0f0;"|'''Magnitude'''<br />
| align="center" style="background:#f0f0f0;"|'''Location'''<br />
| align="center" style="background:#f0f0f0;"|'''Reference'''<br />
|- valign="top"<br />
| Stage uncertainty||Comparison with neighbouring stations||SD of 25 mm||Netherlands gauging network||Van der Made (1982)<br />
|- valign="top"<br />
| Effect of unstable bed||Expert knowledge; uncertainty for individual measurement||±10 %||Estimate for locations with shifting sand or moving dunes||Sauer & Meyer (1992)<br />
|- valign="top"<br />
| Instrument precision||Review of previous studies; uncertainty for individual measurement||±3-10.8 mm or ±0.1-2 %||||Quoted in Harmel et al. (2006)<br />
|- valign="top"<br />
| Instrument precision||Expert knowledge||Range ±10 mm; local oscillations of water surface can add additional uncertainty of ±20 mm||Typical example of natural rivers||Dottori et al. (2009)<br />
|- valign="top"<br />
| Instrument precision: Float in stilling well||||6 mm||||Quoted in Herschy (1998): Ackers et al. (1978)<br />
|- valign="top"<br />
| Instrument precision: Pressure transducer ||||1.4-40 mm||||Herschy (1998)<br />
|- valign="top"<br />
| Stage uncertainty||Expert knowledge of typical uncertainties||4 mm (high accuracy) to 15 mm (low accuracy)||Norwegian Water Resources & Energy Directorate||Petersen-Øverleir & Reitan (2005)<br />
|- valign="top"<br />
| Stage uncertainty||Observed fluctuation||2-5 mm||Rowden Experimental Research Platform (1 ha fields), Devon, UK. 250 x 37 cm weir box, stainless steel 45° V-Notch, float (Model 6541, Unidata), stilling well, ave. annual precipitation 1055 mm.||Krueger et al. (2010)<br />
|- valign="top"<br />
| Instrument precision||Manufacturer cited random uncertainty||2.5 mm (Trutrack, Model PLUT-HR Water level recorder)||Hillslope (172 m2), WS10 catchment, HJA Experimental Forest, Oregon, USA||Graham et al. (2010)<br />
|- valign="top"<br />
| ||||0.3 mm (Model 2 Stevens Instruments Position Analog Transmitter)||WS10 catchment (10.2 ha), HJA Experimental Forest, Oregon, USA. Mediterranean climate, rainfall 2200 mm yr-1, slopes 30-45 °.||<br />
|- valign="top"<br />
| Stage uncertainty||Nominal uncertainty||3 mm||||Hamilton & Moore (2012)<br />
|}<br />
<br />
== References ==<br />
<br />
Ackers, P., 1978. Weirs and flumes for flow measurement. Wiley, Chichester.<br />
<br />
Dottori, F., Martina, M.L.V., Todini, E., 2009. A dynamic rating curve approach to indirect discharge measurement. Hydrology and Earth System Sciences, 13(6): 847-863.<br />
<br />
Graham, C.B., van Verseveld, W., Barnard, H.R., McDonnell, J.J., 2010. Estimating the deep seepage component of the hillslope and catchment water balance within a measurement uncertainty framework. Hydrological Processes, 24(25): 3878–3893.<br />
<br />
Hamilton, A.S., Moore, R.D., 2012. Quantifying Uncertainty in Streamflow Records. Canadian Water Resources Journal, 37(1): 3-21.<br />
<br />
Harmel, R.D., Cooper, R.J., Slade, R.M., Haney, R.L., Arnold, J.G., 2006. Cumulative uncertainty in measured streamflow and water quality data for small watersheds. Transactions of the ASABE, 49(3): 689-701.<br />
<br />
Herschy, R.W., 1998. Hydrometry : Principles and practices. Wiley, Chichester.<br />
<br />
Krueger, T., Freer, J., Quinton, J.N., Macleod, C.J.A., Bilotta, G.S., Brazier, R.E., Butler, P., Haygarth, P.M., 2010. Ensemble evaluation of hydrological model hypotheses. Water Resources Research, 46: W07516.<br />
<br />
McMillan, H., Krueger, T., Freer, J., 2012. Benchmarking observational uncertainties for hydrology: Rainfall, river discharge and water quality. Hydrological Processes.<br />
<br />
Petersen-Øverleir, A., Reitan, T., 2005. Uncertainty in flood discharges from urban and small rural catchments due to inaccurate head measurement. Nordic Hydrology, 36(3): 245-257.<br />
<br />
Sauer, V.B., Meyer, R.W., 1992. Determination of error in individual discharge measurements, U.S. Geological Survey Open-File Report 92–144.<br />
<br />
van der Made, J.E., 1982. Determination of the accuracy of water level observations, Proceedings of the Exeter Symposium. IAHS Publications 134, pp. 172-184.<br />
[http://iresearchpapers.com/ buy research paper]<br />
<br />
[[Category:Uncertainty]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Main_Categories&diff=1561Main Categories2012-03-21T15:05:42Z<p>Ilja: </p>
<hr />
<div>This is a list of the most important categories in the Experimental Hydrology Wiki.<br />
<br />
<br />
*[[:Category:Equipment|Equipment]]<br />
*[[:Category:Experimental Catchments|Experimental Catchments]]<br />
*[[:Category:Uncertainty|Uncertainty]]<br />
*[[:Category:Parameters|Parameters]]<br />
*[[:Category:Templates|Templates]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Soil_moisture_-_Aquapro&diff=706Soil moisture - Aquapro2009-01-06T01:18:14Z<p>Ilja: </p>
<hr />
<div>[[Image:Aquapro.JPG|right|150px|]]<br />
<br />
==Parameter to be measured:==<br />
Soil moisture<br />
<br />
==Method:==<br />
Capacitance (radio-frequency)<br />
<br />
==Equipment:==<br />
Aquapro sensor<br />
<br />
==Advantages:==<br />
* Cheap to take measurements at many locations and at many depths<br />
* Repeatability because of fixed access tubes<br />
<br />
==Disadvantages:==<br />
The measurement scale is in %Aquapro. In order to convert to volumetric moisture content an additional calibration needs to be done. Percent Aquapro and volumetric moisture content are linearly related for most soils.<br />
<br />
==What to watch out for:==<br />
* Stones and air pockets around the access tube influence the readings. It is very important to carefully install the access tubes.<br />
* You can install tubes longer than 1 m but if the access tubes warp a little bit (and are thus no longer perfectly straight) it is difficult to insert the probe in the tube and the probe may break when you pull the probe out of the access tube.<br />
<br />
==Problems/Questions:==<br />
<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
http://www.sfu.ca/~ilja/Panola.html<br />
<br />
Other related web sites:<br />
http://www.aquapro-sensors.com/<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]<br />
[[Category:Soil moisture]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Soil_moisture_-_Aquapro&diff=705Soil moisture - Aquapro2009-01-06T01:16:10Z<p>Ilja: </p>
<hr />
<div>[[Image:Aquapro.JPG|right|150px|]]<br />
<br />
==Parameter to be measured:==<br />
Soil moisture<br />
<br />
==Method:==<br />
Capacitance (radio-frequency)<br />
<br />
==Equipment:==<br />
Aquapro sensor<br />
<br />
==Advantages:==<br />
* Cheap to take measurements at many locations and at many depths<br />
* Repeatability because of fixed access tubes<br />
<br />
==Disadvantages:==<br />
The measurement scale is in %Aquapro. In order to convert to volumetric moisture content an additional calibration needs to be done. Percent Aquapro and volumetric moisture content are linearly related for most soils.<br />
<br />
==What to watch out for:==<br />
* Stones and air pockets around the access tube influence the readings. It is very important to carefully install the access tubes.<br />
* You can install tubes longer than 1 m but if the access tubes warp a little bit (and are thus no longer perfectly straight) it is difficult to insert the probe in the tube and the probe may break when you pull the probe out of the access tube.<br />
<br />
==Problems/Questions:==<br />
<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
http://www.sfu.ca/~ilja/Panola.html<br />
<br />
Other related web sites:<br />
<br />
<br />
==References==<br />
http://www.aquapro-sensors.com/<br />
<br />
[[Category:Equipment]]<br />
[[Category:Soil moisture]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Soil_moisture_-_Aquapro&diff=704Soil moisture - Aquapro2009-01-06T01:15:42Z<p>Ilja: New page: 150px| ==Parameter to be measured:== Soil moisture ==Method:== Capacitance (radio-frequency) ==Equipment:== Aquapro sensor ==Advantages:== * Cheap to take m...</p>
<hr />
<div>[[Image:Aquapro.JPG|right|150px|]]<br />
<br />
==Parameter to be measured:==<br />
Soil moisture<br />
<br />
==Method:==<br />
Capacitance (radio-frequency)<br />
<br />
==Equipment:==<br />
Aquapro sensor<br />
<br />
==Advantages:==<br />
* Cheap to take measurements at many locations and at many depths<br />
* Repeatability because of fixed access tubes<br />
<br />
==Disadvantages:==<br />
* The measurement scale is in %Aquapro. In order to convert to volumetric moisture content an additional calibration needs to be done. Percent Aquapro and volumetric moisture content are linearly related for most soils.<br />
<br />
==What to watch out for:==<br />
* Stones and air pockets around the access tube influence the readings. It is very important to carefully install the access tubes.<br />
* You can install tubes longer than 1 m but if the access tubes warp a little bit (and are thus no longer perfectly straight) it is difficult to insert the probe in the tube and the probe may break when you pull the probe out of the access tube.<br />
<br />
==Problems/Questions:==<br />
<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
http://www.sfu.ca/~ilja/Panola.html<br />
<br />
Other related web sites:<br />
<br />
<br />
==References==<br />
http://www.aquapro-sensors.com/<br />
<br />
[[Category:Equipment]]<br />
[[Category:Soil moisture]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=File:Aquapro.JPG&diff=703File:Aquapro.JPG2009-01-06T01:12:52Z<p>Ilja: Aquapro</p>
<hr />
<div>Aquapro</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Talk:The_%22Things_that_went_wrong%22-Story_of_the_Month&diff=640Talk:The "Things that went wrong"-Story of the Month2008-12-12T21:23:15Z<p>Ilja: </p>
<hr />
<div>I have had the same error messages and loss of data but did not know what the problem was until I read this story. So this has been very helpful. <br />
Have you contacted Onset (the manufacturer of the HOBO dataloggers)? If so, what did they say about this?<br />
<br />
I will report the problem to Onset now (2008-12-10, 11 CET). As far as I can see the logger's current manual does not contain a warning so far (http://www.onsetcomp.com/files/manual_pdfs/9831_C_MAN_UA-003.pdf).<br />
<br />
... and this is the response from Onset technical support (2008-12-10, 15 CET): "We are aware of this issue and it has been addressed. New pendant loggers come equipped with a black cap. This black cap does not allow as much light into the case, preserving the IR communications."<br />
<br />
I have the black cap but still had the same problems. So to be safe it is better to always use something to provide additional shade.</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Talk:The_%22Things_that_went_wrong%22-Story_of_the_Month&diff=637Talk:The "Things that went wrong"-Story of the Month2008-12-09T07:04:45Z<p>Ilja: New page: I have had the same error messages and loss of data but did not know what the problem was until I read this story. So this has been very helpful. Have you contacted Onset (the manufacture...</p>
<hr />
<div>I have had the same error messages and loss of data but did not know what the problem was until I read this story. So this has been very helpful. <br />
Have you contacted Onset (the manufacturer of the HOBO dataloggers)? If so, what did they say about this?</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Talk:Panola_Mountain_Research_Watershed&diff=636Talk:Panola Mountain Research Watershed2008-12-09T06:51:25Z<p>Ilja: hillslope dataset available from website</p>
<hr />
<div>A part of the Panola hillslope database can be downloaded from: http://www.sfu.ca/PanolaData/</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=The_Malalcahuello_Catchment&diff=238The Malalcahuello Catchment2007-05-01T03:30:52Z<p>Ilja: The Malalcahuello Catchment moved to Malalcahuello Catchment: otherwise it will be filed under the T of the - but not under the M of Malalcahuello</p>
<hr />
<div>#REDIRECT [[Malalcahuello Catchment]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Malalcahuello_Catchment&diff=237Malalcahuello Catchment2007-05-01T03:30:52Z<p>Ilja: The Malalcahuello Catchment moved to Malalcahuello Catchment: otherwise it will be filed under the T of the - but not under the M of Malalcahuello</p>
<hr />
<div>The Malalcahuello Catchment is sometimes also called the catchment of the Tres Arroyos.<br />
<br />
== Location ==<br />
On the southern slope of the volcano Lonquimay, IXth Region, Southern Chile<br />
<br />
== Catchment size ==<br />
ca. 6 km²<br />
<br />
== Climate ==<br />
humid-temperate with altitudinal effects, snow in higher altitudes during winter<br />
<br />
== Geology ==<br />
volcanic ashes, andesite<br />
<br />
== Topography ==<br />
steep slopes, elevations range from 1120 m to 1856 m above sea level<br />
<br />
== Vegetation/Land use ==<br />
old growth forest, no anthropogenic intervention<br />
<br />
== Context of investigation ==<br />
several studies have been carried out in this catchment. Research topics include:<br />
*Runoff generation processes<br />
*Sediment transport<br />
*Debris flow<br />
*Large woody debris<br />
*Interception<br />
<br />
== Measurements/Equipment ==<br />
*[[Water level - capacitive (Trutrack)|water level]]<br />
*[[Rainfall - Tipping bucket (Davis/Hobo)|rainfall]]<br />
*[[Water level - capacitive (Trutrack)|groundwater levels]]<br />
*[[Soil moisture - FDR (profile probe)|soil moisture]]<br />
*tracer experiments<br />
*bedload transport<br />
*...<br />
<br />
== Links to project webpages ==<br />
*[http://brandenburg.geoecology.uni-potsdam.de/projekte/malalcahuello/ Investigation of runoff generation processes in a pristine, poorly gauged catchment in the Chilean Andes]<br />
<br />
*[http://www.uach.cl/externos/epicforce/presentacion_en.html Epic Force: Evidence-based policy for integrated control of forested river catchments in extreme rainfall and snowmelt]<br />
<br />
== References ==<br />
coming soon<br />
<br />
[[Category:Experimental Catchments]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Panola_Mountain_Research_Watershed&diff=236Panola Mountain Research Watershed2007-05-01T03:26:35Z<p>Ilja: </p>
<hr />
<div>[[Image: Panola_map.jpg |right|250px|]] <br />
[[Image: Panola_hillslope_winter.jpg|right|150px|]] <br />
[[Image: Panola_hillslope_summer.JPG|right|150px|]] <br />
[[Image: Panola_trench.JPG|right|150px|]] <br />
[[Image: Panola_outcrop.JPG|right|150px|]] <br />
[[Image: Panola_gauge.JPG|right|150px|]] <br />
<br />
== Location ==<br />
The Panola Mountain Research Watershed (PMRW) is located within the Panola Mountain State Conservation Park, about 25 km southeast of Atlanta, Georgia, USA (84°10’W, 33°37’N).<br />
<br />
== Catchment size ==<br />
* 41 ha main catchment<br />
* 10 ha sub-catchment located in the western part of the main catchment<br />
* 0.1 ha trenched hillslope<br />
<br />
== Climate ==<br />
Humid continental to subtropical.<br />
<br />
The mean annual precipitation is ~1240 mm, which on average is distributed uniformly throughout the year. Rainfall typically has a long duration and low intensity associated with the passage of fronts in the winter and a short duration and high intensity associated with convective rainstorms in the summer. Less than 1% of the precipitation falls as snow or sleet. A long growing season, warm temperatures, and many sunny days result in a high evapotranspiration demand, particularly during the summer. Air temperature averages 15.2°C and the average monthly temperatures range from 5.5°C in January to 25.2°C in July.<br />
<br />
== Geology ==<br />
The bedrock is predominantly the Panola Granite (granodiorite composition), a biotite–oligioclase– quartz–microcline granite of Mississippian to Pennsylvanian age. The Panola granite contains pods of amphibolitic gneiss, particularly at lower elevations. <br />
<br />
Soils are predominantly ultisols developed in colluvium and residuum, which intergrades to inceptisols developed in colluvium, recent alluvium, or in highly eroded landscape positions. Typical soil profiles on the hillslopes are typically <1.6 m thick, grading into saprolite of variable thickness. The riparian zone has the deepest soils (>5 m).<br />
<br />
== Topography ==<br />
The basin relief is 56 m and slopes average 18%.<br />
<br />
== Vegetation/Land use ==<br />
The watershed contains a naturally regenerated second-growth forest on abandoned agricultural land, typical of the Piedmont physiographic province. The watershed is 90% forested, dominated by hickory, oak, tulip poplar, and loblolly pine, and 10% partially vegetated (lichens and mosses) bedrock outcrops. The forested area varies from 100% deciduous to 100% coniferous.<br />
<br />
== Context of investigation ==<br />
The PMRW was established in 1985 as part of the USGS Acid Rain Thrust Program. In 1991, the 41-ha forested watershed became one of five Water, Energy and Biogeochemical Budgets (WEBB) sites focusing research on the movement of water and solutes within a small forested watershed and the effects of anthropogenic and environmental change. The experimental hillslope study site was established in 1995 with the excavation of a 20-m-long trench.<br />
<br />
== Measurements/Equipment ==<br />
41 ha main catchment and 10 ha subcatchment:<br />
* Precipitation<br />
* Climate<br />
* Streamflow<br />
* Several transects with recording wells<br />
* Water quality (weekly and event sampling)<br />
* Soil moisture<br />
<br />
0.1 ha hillslope study site:<br />
* Lateral subsurface flow (trench)<br />
* Soil moisture <br />
* Groundwater<br />
* Sapflow (Summer of 2002)<br />
* Sprinkling experiments (Summer of 2002 and Fall of 2006)<br />
* Tracer experiments (Summer of 2002 and Fall of 2006)<br />
<br />
<br />
== Links to project webpages ==<br />
http://ga.water.usgs.gov/projects/panola/<br />
<br />
== References ==<br />
<br />
<br />
[[Category:Experimental Catchments]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=File:Panola_gauge.JPG&diff=235File:Panola gauge.JPG2007-05-01T03:23:55Z<p>Ilja: PMRW lower (41 ha) gauge</p>
<hr />
<div>PMRW lower (41 ha) gauge</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=File:Panola_outcrop.JPG&diff=234File:Panola outcrop.JPG2007-05-01T03:23:27Z<p>Ilja: PMRW outcrop</p>
<hr />
<div>PMRW outcrop</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=File:Panola_trench.JPG&diff=233File:Panola trench.JPG2007-05-01T03:22:59Z<p>Ilja: PMRW trench</p>
<hr />
<div>PMRW trench</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=File:Panola_hillslope_winter.jpg&diff=232File:Panola hillslope winter.jpg2007-05-01T03:22:22Z<p>Ilja: PMRW hillslope during the winter</p>
<hr />
<div>PMRW hillslope during the winter</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=File:Panola_hillslope_summer.JPG&diff=231File:Panola hillslope summer.JPG2007-05-01T03:21:44Z<p>Ilja: PMRW hillslope during the summer</p>
<hr />
<div>PMRW hillslope during the summer</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Panola_Mountain_Research_Watershed&diff=230Panola Mountain Research Watershed2007-05-01T03:06:47Z<p>Ilja: </p>
<hr />
<div>[[Image: Panola_map.jpg |right|250px|]] <br />
== Location ==<br />
The Panola Mountain Research Watershed (PMRW) is located within the Panola Mountain State Conservation Park, about 25 km southeast of Atlanta, Georgia, USA (84°10’W, 33°37’N).<br />
<br />
== Catchment size ==<br />
* 41 ha main catchment<br />
* 10 ha sub-catchment located in the western part of the main catchment<br />
* 0.1 ha trenched hillslope<br />
<br />
== Climate ==<br />
Humid continental to subtropical.<br />
<br />
The mean annual precipitation is ~1240 mm, which on average is distributed uniformly throughout the year. Rainfall typically has a long duration and low intensity associated with the passage of fronts in the winter and a short duration and high intensity associated with convective rainstorms in the summer. Less than 1% of the precipitation falls as snow or sleet. A long growing season, warm temperatures, and many sunny days result in a high evapotranspiration demand, particularly during the summer. Air temperature averages 15.2°C and the average monthly temperatures range from 5.5°C in January to 25.2°C in July.<br />
<br />
== Geology ==<br />
The bedrock is predominantly the Panola Granite (granodiorite composition), a biotite–oligioclase– quartz–microcline granite of Mississippian to Pennsylvanian age. The Panola granite contains pods of amphibolitic gneiss, particularly at lower elevations. <br />
<br />
Soils are predominantly ultisols developed in colluvium and residuum, which intergrades to inceptisols developed in colluvium, recent alluvium, or in highly eroded landscape positions. Typical soil profiles on the hillslopes are typically <1.6 m thick, grading into saprolite of variable thickness. The riparian zone has the deepest soils (>5 m).<br />
<br />
== Topography ==<br />
The basin relief is 56 m and slopes average 18%.<br />
<br />
== Vegetation/Land use ==<br />
The watershed contains a naturally regenerated second-growth forest on abandoned agricultural land, typical of the Piedmont physiographic province. The watershed is 90% forested, dominated by hickory, oak, tulip poplar, and loblolly pine, and 10% partially vegetated (lichens and mosses) bedrock outcrops. The forested area varies from 100% deciduous to 100% coniferous.<br />
<br />
== Context of investigation ==<br />
The PMRW was established in 1985 as part of the USGS Acid Rain Thrust Program. In 1991, the 41-ha forested watershed became one of five Water, Energy and Biogeochemical Budgets (WEBB) sites focusing research on the movement of water and solutes within a small forested watershed and the effects of anthropogenic and environmental change. The experimental hillslope study site was established in 1995 with the excavation of a 20-m-long trench.<br />
<br />
== Measurements/Equipment ==<br />
41 ha main catchment and 10 ha subcatchment:<br />
* Precipitation<br />
* Climate<br />
* Streamflow<br />
* Several transects with recording wells<br />
* Water quality (weekly and event sampling)<br />
* Soil moisture<br />
<br />
0.1 ha hillslope study site:<br />
* Lateral subsurface flow (trench)<br />
* Soil moisture <br />
* Groundwater<br />
* Sapflow (Summer of 2002)<br />
* Sprinkling experiments (Summer of 2002 and Fall of 2006)<br />
* Tracer experiments (Summer of 2002 and Fall of 2006)<br />
<br />
<br />
== Links to project webpages ==<br />
http://ga.water.usgs.gov/projects/panola/<br />
<br />
== References ==<br />
<br />
<br />
[[Category:Experimental Catchments]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Panola_Mountain_Research_Watershed&diff=229Panola Mountain Research Watershed2007-05-01T02:58:31Z<p>Ilja: /* Location */</p>
<hr />
<div>[[Image: Panola_map.jpg |right|250px|]] <br />
== Location ==<br />
The Panola Mountain Research Watershed (PMRW) is located within the Panola Mountain State Conservation Park, about 25 km southeast of Atlanta, Georgia, USA (84°10’W, 33°37’N).<br />
<br />
== Catchment size ==<br />
* 41 ha main catchment<br />
* 10 ha sub-catchment located in the western part of the catchment<br />
* 0.1 ha trenched hillslope<br />
<br />
== Climate ==<br />
Humid continental to subtropical.<br />
<br />
The mean annual precipitation is ~1240 mm, which on average is distributed uniformly throughout the year. Rainfall typically has a long duration and low intensity associated with the passage of fronts in the winter and has a short duration and high intensity associated with convective rainstorms in the summer. <br />
<br />
== Geology ==<br />
The bedrock is predominantly the Panola Granite (granodiorite composition), a biotite–oligioclase– quartz–microcline granite of Mississippian to Pennsylvanian age. The Panola granite contains pods of amphibolitic gneiss, particularly at lower elevation. <br />
<br />
Soils are predominantly ultisols developed in colluvium and residuum, which intergrades to inceptisols developed in colluvium, recent alluvium, or in highly eroded landscape positions. Typical soil profiles on the hillslopes are 0.6 to 1.6 m thick, grading into saprolite of variable thickness. The riparian zone has the deepest soils (>5 m).<br />
<br />
== Topography ==<br />
The basin relief is 56 m and slopes average 18%.<br />
<br />
== Vegetation/Land use ==<br />
The watershed contains a naturally regenerated second-growth forest on abandoned agricultural land, typical of the Piedmont physiographic province. The watershed is 90% forested, dominated by hickory, oak, tulip poplar, and loblolly pine, and 10% partially vegetated (lichens and mosses) bedrock outcrops. The forested area varies from 100% deciduous to 100% coniferous.<br />
<br />
== Context of investigation ==<br />
The PMRW was established in 1985 as part of the USGS Acid Rain Thrust Program. In 1991, the 41-ha forested watershed became one of five Water, Energy and Biogeochemical Budgets (WEBB) sites focusing research on the movement of water and solutes within a small forested watershed and the effects of anthropogenic and environmental change. The experimental hillslope study site was established in 1995 with the excavation of a 20-m-long trench.<br />
<br />
== Measurements/Equipment ==<br />
41 ha main catchment and 10 ha subcatchment:<br />
* Precipitation<br />
* Climate<br />
* Streamflow at the catchment outlet and the 10 ha sub-catchment<br />
* Several transects with recording wells<br />
* Water quality (weekly and event sampling)<br />
* Soil moisture<br />
<br />
0.1 ha hillslope study site:<br />
* Lateral subsurface flow (trench)<br />
* Soil moisture <br />
* Groundwater<br />
* Sapflow (Summer of 2002)<br />
* Sprinkling experiments (Summer of 2002 and Fall of 2006)<br />
* Tracer experiments (Summer of 2002 and Fall of 2006)<br />
<br />
<br />
== Links to project webpages ==<br />
http://ga.water.usgs.gov/projects/panola/<br />
<br />
== References ==<br />
<br />
<br />
[[Category:Experimental Catchments]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Panola_Mountain_Research_Watershed&diff=228Panola Mountain Research Watershed2007-04-30T23:35:24Z<p>Ilja: </p>
<hr />
<div>[[Image: Panola_map.jpg |right|250px|]] <br />
== Location ==<br />
The Panola Mountain Research Watershed (PMRW) is located within the Panola Mountain State Conservation Park, on the Piedmont of Georgia, USA (84°10’W, 33°37’N), about 25 km southeast of Atlanta, Georgia, USA.<br />
<br />
== Catchment size ==<br />
* 41 ha main catchment<br />
* 10 ha sub-catchment located in the western part of the catchment<br />
* 0.1 ha trenched hillslope<br />
<br />
== Climate ==<br />
Humid continental to subtropical.<br />
<br />
The mean annual precipitation is ~1240 mm, which on average is distributed uniformly throughout the year. Rainfall typically has a long duration and low intensity associated with the passage of fronts in the winter and has a short duration and high intensity associated with convective rainstorms in the summer. <br />
<br />
== Geology ==<br />
The bedrock is predominantly the Panola Granite (granodiorite composition), a biotite–oligioclase– quartz–microcline granite of Mississippian to Pennsylvanian age. The Panola granite contains pods of amphibolitic gneiss, particularly at lower elevation. <br />
<br />
Soils are predominantly ultisols developed in colluvium and residuum, which intergrades to inceptisols developed in colluvium, recent alluvium, or in highly eroded landscape positions. Typical soil profiles on the hillslopes are 0.6 to 1.6 m thick, grading into saprolite of variable thickness. The riparian zone has the deepest soils (>5 m).<br />
<br />
== Topography ==<br />
The basin relief is 56 m and slopes average 18%.<br />
<br />
== Vegetation/Land use ==<br />
The watershed contains a naturally regenerated second-growth forest on abandoned agricultural land, typical of the Piedmont physiographic province. The watershed is 90% forested, dominated by hickory, oak, tulip poplar, and loblolly pine, and 10% partially vegetated (lichens and mosses) bedrock outcrops. The forested area varies from 100% deciduous to 100% coniferous.<br />
<br />
== Context of investigation ==<br />
The PMRW was established in 1985 as part of the USGS Acid Rain Thrust Program. In 1991, the 41-ha forested watershed became one of five Water, Energy and Biogeochemical Budgets (WEBB) sites focusing research on the movement of water and solutes within a small forested watershed and the effects of anthropogenic and environmental change. The experimental hillslope study site was established in 1995 with the excavation of a 20-m-long trench.<br />
<br />
== Measurements/Equipment ==<br />
41 ha main catchment and 10 ha subcatchment:<br />
* Precipitation<br />
* Climate<br />
* Streamflow at the catchment outlet and the 10 ha sub-catchment<br />
* Several transects with recording wells<br />
* Water quality (weekly and event sampling)<br />
* Soil moisture<br />
<br />
0.1 ha hillslope study site:<br />
* Lateral subsurface flow (trench)<br />
* Soil moisture <br />
* Groundwater<br />
* Sapflow (Summer of 2002)<br />
* Sprinkling experiments (Summer of 2002 and Fall of 2006)<br />
* Tracer experiments (Summer of 2002 and Fall of 2006)<br />
<br />
<br />
== Links to project webpages ==<br />
http://ga.water.usgs.gov/projects/panola/<br />
<br />
== References ==<br />
<br />
<br />
[[Category:Experimental Catchments]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Panola_Mountain_Research_Watershed&diff=227Panola Mountain Research Watershed2007-04-30T23:33:05Z<p>Ilja: </p>
<hr />
<div>[[Image: Panola_map.jpg |right|280px|]] Panola_map.jpg<br />
<br />
== Location ==<br />
The Panola Mountain Research Watershed (PMRW) is located within the Panola Mountain State Conservation Park, on the Piedmont of Georgia, USA (84°10’W, 33°37’N), about 25 km southeast of Atlanta, Georgia, USA.<br />
<br />
== Catchment size ==<br />
* 41 ha main catchment<br />
* 10 ha sub-catchment located in the western part of the catchment<br />
* 0.1 ha trenched hillslope<br />
<br />
== Climate ==<br />
Humid continental to subtropical.<br />
<br />
The mean annual precipitation is ~1240 mm, which on average is distributed uniformly throughout the year. Rainfall typically has a long duration and low intensity associated with the passage of fronts in the winter and has a short duration and high intensity associated with convective rainstorms in the summer. <br />
<br />
== Geology ==<br />
The bedrock is predominantly the Panola Granite (granodiorite composition), a biotite–oligioclase– quartz–microcline granite of Mississippian to Pennsylvanian age. The Panola granite contains pods of amphibolitic gneiss, particularly at lower elevation. <br />
<br />
Soils are predominantly ultisols developed in colluvium and residuum, which intergrades to inceptisols developed in colluvium, recent alluvium, or in highly eroded landscape positions. Typical soil profiles on the hillslopes are 0.6 to 1.6 m thick, grading into saprolite of variable thickness. The riparian zone has the deepest soils (>5 m).<br />
<br />
== Topography ==<br />
The basin relief is 56 m and slopes average 18%.<br />
<br />
== Vegetation/Land use ==<br />
The watershed contains a naturally regenerated second-growth forest on abandoned agricultural land, typical of the Piedmont physiographic province. The watershed is 90% forested, dominated by hickory, oak, tulip poplar, and loblolly pine, and 10% partially vegetated (lichens and mosses) bedrock outcrops. The forested area varies from 100% deciduous to 100% coniferous.<br />
<br />
== Context of investigation ==<br />
The PMRW was established in 1985 as part of the USGS Acid Rain Thrust Program. In 1991, the 41-ha forested watershed became one of five Water, Energy and Biogeochemical Budgets (WEBB) sites focusing research on the movement of water and solutes within a small forested watershed and the effects of anthropogenic and environmental change. The experimental hillslope study site was established in 1995 with the excavation of a 20-m-long trench.<br />
<br />
== Measurements/Equipment ==<br />
* Precipitation<br />
* Climate<br />
* Streamflow at the catchment outlet and the 10 ha sub-catchment<br />
* Several transects with recording wells<br />
* Water quality (weekly and event sampling)<br />
* Soil moisture<br />
<br />
<br />
On the 0.1 ha hillslope study site<br />
* Lateral subsurface flow (trench)<br />
* Soil moisture <br />
* Groundwater<br />
* Sapflow (Summer of 2002)<br />
* Sprinkling experiments (Summer of 2002 and Fall of 2006)<br />
* Tracer experiments (Summer of 2002 and Fall of 2006)<br />
<br />
<br />
== Links to project webpages ==<br />
http://ga.water.usgs.gov/projects/panola/<br />
<br />
== References ==<br />
<br />
<br />
[[Category:Experimental Catchments]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Panola_Mountain_Research_Watershed&diff=226Panola Mountain Research Watershed2007-04-30T23:27:30Z<p>Ilja: New page: 300px| Panola_map.jpg == Location == The Panola Mountain Research Watershed (PMRW) is located within the Panola Mountain State Conservation Park, on the P...</p>
<hr />
<div>[[Image: Panola_map.jpg |right|300px|]] Panola_map.jpg<br />
<br />
== Location ==<br />
The Panola Mountain Research Watershed (PMRW) is located within the Panola Mountain State Conservation Park, on the Piedmont of Georgia, USA (84°10’W, 33°37’N), about 25 km southeast of Atlanta, Georgia, USA.<br />
<br />
== Catchment size ==<br />
* 41 ha main catchment<br />
* 10 ha sub-catchment located in the western part of the catchment<br />
* 0.1 ha trenched hillslope<br />
<br />
== Climate ==<br />
Humid continental to subtropical.<br />
<br />
Mean annual precipitation is ~1240 mm, which on average is distributed uniformly throughout the year. Rainfall typically has a long duration and low intensity associated with the passage of fronts in the winter and has a short duration and high intensity associated with convective rainstorms in the summer. <br />
<br />
== Geology ==<br />
The bedrock is predominantly the Panola Granite (granodiorite composition), a biotite–oligioclase– quartz–microcline granite of Mississippian to Pennsylvanian age. The Panola granite contains pods of amphibolitic gneiss, particularly at lower elevation. <br />
<br />
Soils are predominantly ultisols developed in colluvium and residuum, which intergrades to inceptisols developed in colluvium, recent alluvium, or in highly eroded landscape positions. Typical soil profiles on the hillslopes are 0.6 to 1.6 m thick, grading into saprolite of variable thickness. The riparian zone has the deepest soils (>5 m).<br />
<br />
== Topography ==<br />
The basin relief is 56 m and slopes average 18%.<br />
<br />
== Vegetation/Land use ==<br />
The watershed contains a naturally regenerated second-growth forest on abandoned agricultural land, typical of the Piedmont physiographic province. The watershed is 90% forested, dominated by hickory, oak, tulip poplar, and loblolly pine, and 10% partially vegetated (lichens and mosses) bedrock outcrops. The forested area varies from 100% deciduous to 100% coniferous.<br />
<br />
== Context of investigation ==<br />
The PMRW was established in 1985 as part of the USGS Acid Rain Thrust Program. In 1991, the 41-ha forested watershed became one of five Water, Energy and Biogeochemical Budgets (WEBB) sites focusing research on the movement of water and solutes within a small forested watershed and the effects of anthropogenic and environmental change.<br />
<br />
== Measurements/Equipment ==<br />
* Precipitation<br />
* Climate<br />
* Streamflow at the catchment outlet and the 10 ha sub-catchment<br />
* Several transects with recording wells<br />
* Water quality (event samples)<br />
* Soil moisture<br />
<br />
<br />
On the 0.1 ha intensive hillslope study site<br />
* Lateral subsurface flow (trench)<br />
* Soil moisture<br />
* Water tables<br />
* Sapflow (summer of 2002)<br />
* Tracer experiments (Summer of 2002 and Fall of 2006)<br />
<br />
<br />
== Links to project webpages ==<br />
http://ga.water.usgs.gov/projects/panola/<br />
<br />
== References ==<br />
<br />
<br />
[[Category:Experimental Catchments]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=File:Panola_map.jpg&diff=225File:Panola map.jpg2007-04-30T23:23:29Z<p>Ilja: PMRW map</p>
<hr />
<div>PMRW map</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Soil_moisture_-_capacitance_(EC-10)&diff=213Soil moisture - capacitance (EC-10)2007-04-14T00:30:33Z<p>Ilja: </p>
<hr />
<div>[[Image:EC10.jpg|right|175px|]]<br />
==Parameter to be measured:==<br />
Soil moisture<br />
<br />
==Method:==<br />
Capacitance<br />
<br />
==Equipment:==<br />
EC-10 (ECH<sub>2</sub>O)<br />
<br />
==Advantages:==<br />
* Relatively cheap<br />
* Easy to install<br />
* Compatible with many loggers<br />
<br />
==Disadvantages:==<br />
* Only for low salinity soils (Decagon has developed newer ECH<sub>2</sub>O probes that are less sensitive to salinity issues, e.g. the EC-5)<br />
<br />
==What to watch out for:==<br />
* Temperature sensitivity<br />
<br />
==Problems/Questions:==<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
<br />
<br />
Other related web sites:<br />
<br />
http://www.decagon.com/Ech2o/<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]<br />
[[Category:Soil Moisture]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=File:EC10.jpg&diff=212File:EC10.jpg2007-04-14T00:29:44Z<p>Ilja: EC-10 ECHO</p>
<hr />
<div>EC-10 ECHO</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Soil_moisture_-_capacitance_(EC-10)&diff=211Soil moisture - capacitance (EC-10)2007-04-14T00:28:33Z<p>Ilja: New page: ==Parameter to be measured:== Soil moisture ==Method:== Capacitance ==Equipment:== EC-10 (ECH<sub>2</sub>O) ==Advantages:== * Relatively cheap * Easy to install * Compatible with many l...</p>
<hr />
<div>==Parameter to be measured:==<br />
Soil moisture<br />
<br />
==Method:==<br />
Capacitance<br />
<br />
==Equipment:==<br />
EC-10 (ECH<sub>2</sub>O)<br />
<br />
==Advantages:==<br />
* Relatively cheap<br />
* Easy to install<br />
* Compatible with many loggers<br />
<br />
==Disadvantages:==<br />
* Only for low salinity soils (Decagon has developed newer ECH<sub>2</sub>O probes that are less sensitive to salinity issues, e.g. the EC-5)<br />
<br />
==What to watch out for:==<br />
* Temperature sensitivity<br />
<br />
==Problems/Questions:==<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
<br />
<br />
Other related web sites:<br />
<br />
http://www.decagon.com/Ech2o/<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]<br />
[[Category:Soil Moisture]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Soil_matric_potential_-_tensiometer_(T4)&diff=210Soil matric potential - tensiometer (T4)2007-04-13T01:13:24Z<p>Ilja: </p>
<hr />
<div>[[Image:114_T4_Tensiometer.jpg|right|175px|]]<br />
==Parameter to be measured:==<br />
<br />
Soil matric potential<br />
<br />
==Method:==<br />
Tensiometer<br />
<br />
==Equipment:==<br />
T4 with external refilling option<br />
<br />
==Advantages:==<br />
<br />
*Very fast response <br />
*Reliable <br />
*Refilling possible without taking the probes out of the soil<br />
*Great range: -1000 to 0 to 850 hPa<br />
<br />
==Disadvantages:==<br />
*Accuracy could be a disadvantage (+/- 0.25 kPa) according calibration sheet) depending on objective of study<br />
*Some of installed tensiometers showed a stepwise output during small changes in soil matric potential (e.g. during drainage) in the order of 0.25 kPa<br />
<br />
<br />
==What to watch out for:==<br />
<br />
*Freezing conditions at fieldsite: at shallow soildepth (do not install year-round) and above-ground (insulate the shaft with PVC and isolation material)<br />
<br />
[[Image:T4_field.jpg|right|175px|]]<br />
<br />
==Problems/Questions:==<br />
<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
*PhD project WS10 HJ Andrews Experimental Forest<br />
<br />
Other related web sites:<br />
*http://www2.decagon.com/geo/T4<br />
*http://www.ums-muc.de/fileadmin/files/Content/Katalog/5%20Tensiometer-ENG-R3.pdf<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]<br />
[[Category:Soil matric potential]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Soil_matric_potential_-_tensiometer&diff=209Soil matric potential - tensiometer2007-04-13T01:09:38Z<p>Ilja: Soil matric potential - tensiometer moved to Soil matric potential - tensiometer (T5)</p>
<hr />
<div>#REDIRECT [[Soil matric potential - tensiometer (T5)]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Soil_matric_potential_-_tensiometer_(T5)&diff=208Soil matric potential - tensiometer (T5)2007-04-13T01:09:38Z<p>Ilja: Soil matric potential - tensiometer moved to Soil matric potential - tensiometer (T5)</p>
<hr />
<div>[[Image:T5-tensiometer.jpg|right|175px|]]<br />
<br />
==Parameter to be measured:==<br />
Soil matric potential<br />
<br />
==Method:==<br />
Tensiometer<br />
<br />
==Equipment:==<br />
T5<br />
<br />
==Advantages:==<br />
*Small <br />
*Very fast response<br />
*Great resolution when used with the DL6-te Tensiometer Data logger<br />
*Reliable<br />
<br />
<br />
==Disadvantages:==<br />
*Their small size makes them great for laboratory or flume experiments but less appropriate for field measurements.<br />
*They have to be taken out of the soil to refill them.<br />
<br />
<br />
==What to watch out for:==<br />
*Don’t burry them too deep - you will have to dig them out (and thus disturb the soil again) if you need to refill them.<br />
<br />
<br />
==Problems/Questions:==<br />
<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
*http://eflum.epfl.ch/research/erosion.en.php<br />
<br />
<br />
Other related web sites:<br />
*http://www.decagon.com/tensiometers/t5.html<br />
*http://www.ums-muc.de/fileadmin/produkt_downloads/Tensiometer/T5_Datasheet.pdf <br />
<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]<br />
[[Category:Soil matric potential]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Water_level_-_capacitive_(Odyssey)&diff=118Water level - capacitive (Odyssey)2007-03-26T23:23:16Z<p>Ilja: </p>
<hr />
<div>[[Image:odyssey.jpg|right|175px|]]<br />
==Parameter to be measured:==<br />
Water level<br />
<br />
==Method:==<br />
Capacitive<br />
<br />
==Equipment:==<br />
Odyssey<br />
<br />
==Advantages:==<br />
*Cheap <br />
*Logging of 64k of data <br />
*Logger start by starting start time <br />
*The lack of an outer shroud makes it easy to transport the probes<br />
*Available in different lengths<br />
*Available with 2 sizes of brass weights<br />
*The probe fits exactly on a 32 mm (ID) PVC pipe <br />
*You can replace the batteries yourself<br />
<br />
==Disadvantages:==<br />
<br />
==What to watch out for:==<br />
*Don’t damage the wire.<br />
<br />
==Problems/Questions:==<br />
*After 2 years of use, two of my loggers would no longer connect to the computer. All others still worked fined.<br />
*One of my loggers would only record data for a few seconds. Restarting the logger and letting it run until the storage was full seemed to take care of this.<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
<br />
<br />
Other related web sites:<br />
<br />
http://www.odysseydatarecording.com/odyssey_productsview.php?key=1<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]<br />
[[Category:Water level]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Soil_matric_potential_-_tensiometer_(T5)&diff=117Soil matric potential - tensiometer (T5)2007-03-26T23:14:05Z<p>Ilja: </p>
<hr />
<div>[[Image:T5-tensiometer.jpg|right|175px|]]<br />
<br />
==Parameter to be measured:==<br />
Soil matric potential<br />
<br />
==Method:==<br />
Tensiometer<br />
<br />
==Equipment:==<br />
T5<br />
<br />
==Advantages:==<br />
*Small <br />
*Very fast response<br />
*Great resolution when used with the DL6-te Tensiometer Data logger<br />
*Reliable<br />
<br />
<br />
==Disadvantages:==<br />
*Their small size makes them great for laboratory or flume experiments but less appropriate for field measurements.<br />
*They have to be taken out of the soil to refill them.<br />
<br />
<br />
==What to watch out for:==<br />
*Don’t burry them too deep - you will have to dig them out (and thus disturb the soil again) if you need to refill them.<br />
<br />
<br />
==Problems/Questions:==<br />
<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
*http://eflum.epfl.ch/research/erosion.en.php<br />
<br />
<br />
Other related web sites:<br />
*http://www.decagon.com/tensiometers/t5.html<br />
*http://www.ums-muc.de/fileadmin/produkt_downloads/Tensiometer/T5_Datasheet.pdf <br />
<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]<br />
[[Category:Soil matric potential]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=File:T5-tensiometer.jpg&diff=116File:T5-tensiometer.jpg2007-03-26T23:12:18Z<p>Ilja: T5 tensiometer</p>
<hr />
<div>T5 tensiometer</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Water_level_-_capacitive_(Odyssey)&diff=115Water level - capacitive (Odyssey)2007-03-26T23:09:24Z<p>Ilja: </p>
<hr />
<div>[[Image:odyssey.jpg|right|175px|]]<br />
==Parameter to be measured:==<br />
Water level<br />
<br />
==Method:==<br />
Capacitive<br />
<br />
==Equipment:==<br />
Odyssey<br />
<br />
==Advantages:==<br />
*Cheap <br />
*Logging of 64k of data <br />
*Logger start by starting start time <br />
*The lack of an outer shroud makes it easy to transport the probes<br />
*Available in different lengths<br />
*Available with 2 sizes of brass weights<br />
*The probe fits exactly on a 32 mm (ID) PVC pipe <br />
*You can replace the batteries yourself<br />
<br />
==Disadvantages:==<br />
<br />
==What to watch out for:==<br />
*Don’t damage the wire.<br />
<br />
==Problems/Questions:==<br />
*After 2 years of use, two of my loggers would no longer connect to the computer. All others still worked fined.<br />
*One of my loggers would only record data for a few seconds. Restarting the logger and letting it run until the storage was full seemed to take care of this.<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
<br />
<br />
Other related web sites:<br />
<br />
http://www.odysseydatarecording.com/odyssey_productsview.php?key=1<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=File:Odyssey.jpg&diff=114File:Odyssey.jpg2007-03-26T23:03:49Z<p>Ilja: water level - capacitive (2)
Odyssey</p>
<hr />
<div>water level - capacitive (2)<br />
Odyssey</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Water_level_-_capacitive_(Odyssey)&diff=113Water level - capacitive (Odyssey)2007-03-26T23:00:21Z<p>Ilja: New page: ==Parameter to be measured:== Water level ==Method:== Capacitive ==Equipment:== Odyssey ==Advantages:== *Cheap *Logging of 64k of data *Logger start by starting start time *The lack ...</p>
<hr />
<div>==Parameter to be measured:==<br />
Water level<br />
<br />
==Method:==<br />
Capacitive<br />
<br />
==Equipment:==<br />
Odyssey<br />
<br />
==Advantages:==<br />
*Cheap <br />
*Logging of 64k of data <br />
*Logger start by starting start time <br />
*The lack of an outer shroud makes it easy to transport the probes<br />
*Available in different lengths<br />
*Available with 2 sizes of brass weights<br />
*The probe fits exactly on a 32 mm (ID) PVC pipe <br />
*You can replace the batteries yourself<br />
<br />
==Disadvantages:==<br />
<br />
==What to watch out for:==<br />
*Don’t damage the wire.<br />
<br />
==Problems/Questions:==<br />
*After 2 years of use, two of my loggers would no longer connect to the computer. All others still worked fined.<br />
*One of my loggers would only record data for a few seconds. Restarting the logger and letting it run until the storage was full seemed to take care of this.<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
<br />
<br />
Other related web sites:<br />
<br />
http://www.odysseydatarecording.com/odyssey_productsview.php?key=1<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Soil_matric_potential_-_tensiometer_(T5)&diff=94Soil matric potential - tensiometer (T5)2007-03-23T21:31:19Z<p>Ilja: New page: ==Parameter to be measured:== Soil matric potential ==Method:== Tensiometer ==Equipment:== T5 ==Advantages:== *Small *Very fast response *Great resolution when used with the DL6-te Ten...</p>
<hr />
<div>==Parameter to be measured:==<br />
Soil matric potential<br />
<br />
==Method:==<br />
Tensiometer<br />
<br />
==Equipment:==<br />
T5<br />
<br />
==Advantages:==<br />
*Small <br />
*Very fast response<br />
*Great resolution when used with the DL6-te Tensiometer Data logger<br />
*Reliable<br />
<br />
<br />
==Disadvantages:==<br />
*Their small size makes them great for laboratory or flume experiments but less appropriate for field measurements.<br />
*They have to be taken out of the soil to refill them.<br />
<br />
<br />
==What to watch out for:==<br />
*Don’t burry them too deep - you will have to dig them out (and thus disturb the soil again) if you need to refill them.<br />
<br />
<br />
==Problems/Questions:==<br />
<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
*http://eflum.epfl.ch/research/erosion.en.php<br />
<br />
<br />
Other related web sites:<br />
*http://www.decagon.com/tensiometers/t5.html<br />
*http://www.ums-muc.de/fileadmin/produkt_downloads/Tensiometer/T5_Datasheet.pdf <br />
<br />
<br />
==References==<br />
<br />
<br />
[[Category:Equipment]]</div>Iljahttps://experimental-hydrology.net/wiki/index.php?title=Water_level_-_capacitive_(Trutrack)&diff=86Water level - capacitive (Trutrack)2007-03-13T00:05:01Z<p>Ilja: /* Disadvantages: */</p>
<hr />
<div>==Parameter to be measured:==<br />
water level<br />
==Method:==<br />
capacitive<br />
<br />
==Equipment:==<br />
TruTrack WT-HR xxxxx<br />
<br />
==Advantages:==<br />
*Cheap<br />
*Easy to install<br />
*Optional Logging of battery level, water and air temperature in 8 / 12 bit resolution<br />
*Logging of 64 k of data<br />
*Logger start by starting condition or start time<br />
<br />
==Disadvantages:==<br />
*Water level measurement is temperature sensitive. The internal temperature compensation does a unreliable job: (stronger) temperature changes MAY produce periods (up to 60 min) of very noisy data.<br />
*Internal Logger calibration: The loggers can be calibrated for exact water level measurements. The loggers may loose this internal calibration for no apparent reason, producing raw data instead. If independent readings are available, the record may be saved by "post-calibration".<br />
*No outside sign of logger operation: For checking the proper logger operation, you must connect a computer to the logger. A full/not activated/malfunctioning logger cannot be detected otherwise.<br />
*Logger connects via serial port: For most modern laptops you will need a USB to Serial(RS232) adaptor, causing yet other problems (sic).<br />
*Bugs in Logger-Software (OmniLog): The detection of the connected loggers is unstable. Detection may fail for no apparent reasons. Reinstalling the software may help. Another reason may be the slightly reduced voltage at laptop ports being insufficient for communication with the logger. Try a desktop computer. Bringing the loggers inside for a couple of hours/days may also help.<br />
*If any of your records happen to coincide with midnight exactly, the data export to Excel will produce faulty date values for these records.<br />
*Poor (=nonexistent) customer support: No problem-related reply of the manufacturer whatsoever has ever been reported. You will, however, get a quick answer if you make an inquiry about an item you'd like to order.<br />
<br />
==What to watch out for:==<br />
Make sure the inner rod is screwed tightly into the logger-unit. To check that you need to unscrew the metal casing from the logger-unit. Shaking during transport might also loosen this connection.<br />
<br />
==Problems/Questions:==<br />
<br />
==Links==<br />
Projects that used the above equipment:<br />
<br />
- SESAM [http://brandenburg.geoecology.uni-potsdam.de/projekte/sesam/index.php]<br />
<br />
Other related web sites:<br />
<br />
- Trutrack homepage [http://www.trutrack.com/WT-HR.html]<br />
==References==<br />
add references here...<br />
<br />
[[Category:Equipment]]<br />
[[Category:Water level]]</div>Ilja