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ARS Home » Midwest Area » Bowling Green, Kentucky » Food Animal Environmental Systems Research » Research » Publications at this Location » Publication #389067

Research Project: Developing Agronomically and Environmentally Beneficial Management Practices to Increase the Sustainability and Safety of Animal Manure Utilization

Location: Food Animal Environmental Systems Research

Title: Rainfall-runoff models compared for tile-drained agricultural fields in the Western Lake Erie Basin, Ohio

Author
item WESSEL, BARRET - University Of Mary Washington
item Bolster, Carl
item King, Kevin
item SHEDEKAR, VINAYAK - The Ohio State University

Submitted to: Journal of Hydrology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/17/2022
Publication Date: 5/24/2022
Citation: Wessel, B., Bolster, C.H., King, K.W., Shedekar, V.S. 2022. Rainfall-runoff models compared for tile-drained agricultural fields in the Western Lake Erie Basin, Ohio. Journal of Hydrology. 610:127959. https://doi.org/10.1016/j.jhydrol.2022.127959.
DOI: https://doi.org/10.1016/j.jhydrol.2022.127959

Interpretive Summary: Surface runoff from agricultural fields has been shown to be a significant pathway of nutrient loss that can have adverse effects on water quality. This is particularly true for tile-drained fields which encompass 22.48 million ha of agricultural fields in the US. Predicting surface runoff from agricultural fields is often completed using the curve number (CN) method, a simple empirical runoff model that has been broadly applied to predict surface runoff from precipitation data for a wide range of field conditions. The appeal to this model is that it only requires a single input variable – the CN. However, the CN method has not been adequately tested in artificially subsurface (tile) drained landscapes. Subsurface (tile) drainage alters the hydrology of these landscapes by expanding the vadose zone, producing a new subsurface flow path, and thereby decreasing the volume of surface runoff (transforming some events that would have generated runoff into zero-runoff events). CNs for tile-drained fields are not available in the published CN tables and the CN method has yet to be evaluated for predictions of surface runoff from tile-drained agricultural fields. In this study we evaluate different methods for predicting surface runoff using data collected from tile-drained agricultural fields in the Western Lake Erie Basin (WLEB) of Ohio. Our results suggest that the CN method is not appropriate in tile-drained landscapes. Rather, the complacent-violent method is recommended for predicting surface runoff from tile-drained fields.

Technical Abstract: Simple models like the curve number method are commonly used to predict runoff volumes from agricultural fields, playing a key role in nutrient transport modeling and watershed management; however, the curve number method has not been evaluated for use in tile-drained fields and it may therefore produce erroneous runoff predictions if applied in these settings. In this study, we evaluate the curve number method at 12 tile-drained research sites in the Western Lake Erie Basin of Ohio. Rainfall and runoff observations at each of these sites were used to calculate curve numbers using six published variations of the curve number method. These were compared to published curve numbers, selected from NRCS tables to correspond to land use in the study sites. In addition to the curve number methods, the complacent-violent method was also used to develop runoff model parameters for the research sites. Methods were compared to one another using Nash-Sutcliffe efficiency, bias, and R-squared. The curve number methods often performed poorly, and sometimes altogether failed to produce a real solution. Of the rainfall-runoff models evaluated, the complacent-violent method produced the most accurate results and should be used in place of the curve number method to make runoff predictions from tile-drained fields.