Sep 20, 2024
USDA LTAR Common Experiment measurement: Overland flow
- Kevin Cole1,
- Anthony R. Buda2,
- Pamela J. Rice3,
- Claire Baffaut4
- 1USDA Agricultural Research Service, National Laboratory for Agriculture and the Environment, Ames, IA;
- 2USDA Agricultural Research Service, Pasture Systems and Watershed Management Research Unit, University Park, PA;
- 3USDA Agricultural Research Service, Soil and Water Management Research, St. Paul, MN;
- 4USDA Agricultural Research Service, Cropping Systems and Water Quality Research Unit, Columbia, MO
External link: https://ltar.ars.usda.gov
Protocol Citation: Kevin Cole, Anthony R. Buda, Pamela J. Rice, Claire Baffaut 2024. USDA LTAR Common Experiment measurement: Overland flow. protocols.io https://dx.doi.org/10.17504/protocols.io.kxygxyk2zl8j/v1
License: This is an open access protocol distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Protocol status: Working
We use this protocol and it's working
Created: February 20, 2024
Last Modified: September 20, 2024
Protocol Integer ID: 97108
Keywords: Long-Term Agroecosystem Research, LTAR, USDA LTAR, Common Experiment, overland flow, rain, snow, cropland, rangelands, watersheds, hydraulic flumes, weirs, water budget, overland flow measurement, measuring overland flow, overland flow on cropland, overland flow, overland flow overland flow, continuous estimates of overland flow, volume of overland flow, small watershed study, usda ltar common experiment measurement, drainage area, agricultural field, drainage, several hydrology textbook, pollutant losses from agricultural field, associated pollutants traverse cropland, outlets of drainage area, detailed guidance on weir, response to rainfall, land surface, concentrated flow, rangeland system, improved agricultural management, measurements of water height, sheet flow, rainfall, expected flow, other water input, key water pathway, beneficial effects of improved agricultural management, water height, weir
Funders Acknowledgements:
United States Department of Agriculture
Grant ID: -
Abstract
Overland flow is water that flows over a land surface (sheet flow) or in rills and gullies (concentrated flow) in response to rainfall or melting snow. Measuring overland flow on croplands and rangelands is important because it represents a key water pathway that controls pollutant losses from agricultural fields. When overland flow is accurately measured along with other water inputs and outputs, scientists can develop budgets describing how water and associated pollutants traverse cropland and rangeland systems. Tracking these budgets over extended time frames (years, decades) helps quantify the beneficial effects of improved agricultural management. In many edge-of-field and small watershed studies, overland flow measurements typically involve control structures such as flumes or weirs. Several hydrology textbooks and agency manuals (USDA, USGS) provide detailed guidance on weir and flume development, installation, and operation. In general, weirs and flumes are located at the outlets of drainage areas where overland flow exits an agricultural field. The devices are sized based on the range of expected flows. In most instances, weirs and flumes have preset equations that calculate discharge (the volume of overland flow leaving a field over a given unit of time) based on measurements of water height, or stage. A wide variety of sensors are useful in measuring stage in weirs and flumes, including floats, bubblers, and pressure transducers. Stage data from these sensors are then recorded at frequent time steps (seconds to hours) to provide continuous estimates of overland flow.
Materials
Equipment
i. Primary control structures such as weirs and flumes. Stilling wells are usually installed to provide a smooth water surface for water level measurements.
ii. Water level sensors such as bubbler stage sensors, submersible pressure transducers, floats, or ultrasonic sensors (minimum 0.003 meter accuracy).
iii. Rainfall sensor. Rainfall data help when reviewing flow data to evaluate whether stage sensors function correctly. Rainfall data are also used to trigger water sampling protocols.
iv. Air temperature sensor. Air temperature data are valuable in areas where freezing temperatures help ensure high-quality data by indicating snow melt and where freezing temperatures may cause stage sensors to report erroneous data.
v. Data logger
vi. Power source
Troubleshooting
1. Data collection
5m
Measurement
Collect sensor data every 5 minutes. More frequent measurements may be desirable in areas of very rapid runoff response.
Note
Please refer to the "Placement and site maintenance", "Data logger integrity", and "Equipment calibration" sections in the USDA LTAR Common Experiment measurement: Best practices for collection, handling, and analyses of water quantity measurements (Baffaut et al., 2024).
Site Maintenance
Visit weekly to ensure sensors (rain gauge and water level), flumes, and weirs are clear of debris and sediment.
Perform routine water level field verification and recalibration if needed. One method would be to physically block the primary control structure and then pump water above the structure to check stage readings.
Perform general site maintenance to prevent vegetation and debris from impeding site operation.
Data processing and quality control
Screen the data for out-of-range values due to debris or ice buildup.
Note
Please refer to the “Quality control” section in the USDA LTAR Common Experiment measurement: Best practices for collection, handling, and analyses of water quantity measurements (Baffaut et al., 2024).
Apply water level shifts because of field verification results.
Fill the data gaps and set quality flag. If gaps are detected during runoff events, use field notes and observations to try reconstructing data from manual stage readings or backup stage sensors. Set a quality flag for all data records with at least four levels, such as good, fair, estimated, and suspect.
Data file formats and metadata
Data format: Site identifier, datetime value, sensor values. Archive the data as raw or production (corrected).
Metadata: Unique site identifiers, spatial coordinates, description of primary control structure, drainage basin area, record of units, indication of accuracy, sensor type, data logger program reference. Record the data adjustments in the metadata.
Note
Please refer to the "Metadata" and "Data storage and accessibility" sections in the USDA LTAR Common Experiment measurement: Best practices for collection, handling, and analyses of water quantity measurements (Baffaut et al., 2024).
Illustrative media
Flume and water sampler during snowmelt event
Flume in grass waterway with rainfall sensors
Overland flow collector in a plot
Recommendations for data collection
Table 1. Summary of recommendations for measuring overland flow.
| A | B | C | |
| Attribute | Preferred | Minimum | |
| Spatial scale | Plot and field | Plot | |
| Frequency | Event | Daily | |
| Covariate metrics | Precipitation, air temperature | Precipitation |
Protocol references
1) Brakensiek, D.L., H.B. Osborn, and W.J. Rawls. 1979. Field Manual for Research in Agricultural Hydrology. U.S. Department of Agriculture, Agriculture Handbook 224, 550 pp. https://naldc.nal.usda.gov/catalog/CAT87209759
2) Chow, V.T., D.R. Maidment, and L.W. Mays. 1988. Applied Hydrology. New York, N.Y. McGraw-Hill.
3) Herschy, R. 2009. Streamflow Measurement. New York, N.Y. Routledge.
4) Maidment, D.R. ed. 1993. Handbook of Hydrology. New York, N.Y. McGraw-Hill.
5) Rantz, S.E. 1982. Measurement and computation of streamflow. U.S. Geological Survey Water Supply Paper 2175.
6) U.S. Department of the Interior, Bureau of Reclamation. 2001. Water Measurement Manual, 3rd. Ed. U.S. Government Printing Office, Washington, DC. https://www.usbr.gov/tsc/techreferences/mands/wmm/
7) Baffaut, C., Schomberg, H., Cosh, M. H., O'Reilly, A. M., Saha, A., Saliendra, N. Z., Schreiner-McGraw, A., & Snyder, K. A. (2024). USDA LTAR Common Experiment measurement: Best practices for collection, handling, and analyses of water quantity measurements. protocols.io
8) U.S. Department of Agriculture, Natural Resources Conservation Service. National Engineering Handbook, Part 630 – Hydrology. Washington, D.C. https://directives.sc.egov.usda.gov/viewerFS.aspx?id=2572
9) U.S. Department of Agriculture, Natural Resources Conservation Service. National Engineering Handbook, Part 650 – Engineering Field Handbook. Washington, D.C. https://directives.sc.egov.usda.gov/viewerFS.aspx?id=3619
10) Kilpatrick, F.A. and V.R. Schneider. 1983. Use of flumes in measuring discharge, Techniques of Water-Resources Investigations 03-A14. U.S. Geological Survey, 46 pp. https://doi.org/10.3133/twri03A14
11) Stuntebeck, T.D., M.J. Komiskey, D.W. Owens, and D.W. Hall. 2008. Methods of Data Collection, Sample Processing, and Data Analysis for Edge-of-Field, Streamgaging, Subsurface-Tile, and Meteorological Stations at Discovery Farms and Pioneer Farm in Wisconsin, 2001-7. U.S. Department of the Interior, U.S. Geological Survey, Open-File Report
2008-1015. 62 pp., https://pubs.usgs.gov/of/2008/1015/pdf/ofr2008-1015.pdf
12) U.S. Department of Agriculture, Natural Resources Conservation Service. 2001. References on time of concentration with respect to sheet flow. 9 pp. https://www.nrcs.usda.gov/Internet/FSE_DOCUMENTS/16/stelprdb1043054.doc
Acknowledgements
This research is a contribution from the Long-Term Agroecosystem Research (LTAR) network. LTAR is supported by the United States Department of Agriculture. The use of trade, firm, or corporation names in this publication is for the information and convenience of the reader. Such use does not constitute an official endorsement or approval by the United States Department of Agriculture or the Agricultural Research Service of any product or service to the exclusion of others that may be suitable. USDA is an equal opportunity provider and employer.