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ARS Home » Midwest Area » Columbus, Ohio » Soil Drainage Research » Research » Publications at this Location » Publication #393092
Research Project: Practices and Technologies for Sustainable Production in Midwestern Tile Drained Agroecosystems

Location: Soil Drainage Research

Title: Feasibility of predicting subsurface drainage discharge with DRAINMOD parameterized by uncalibrated using SURRGO soil properties and ROSETTA3

Author
item ASKAR, MANAL - Michigan State University
item GHANE, EHSAN - Michigan State University
item YOUSSEF, MOHAMED - North Carolina State University
item SHEDEKAR, VINAYAK - The Ohio State University
item King, Kevin
item BHATTARAI, RABIN - University Of Illinois

Submitted to: Journal of Natural Resources and Agricultural Ecosystems
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/7/2024
Publication Date: 2/14/2024
Citation: Askar, M., Ghane, E., Youssef, M., Shedekar, V., King, K.W., Bhattarai, R. 2024. Feasibility of predicting subsurface drainage discharge with DRAINMOD parameterized by uncalibrated using SURRGO soil properties and ROSETTA3. Journal of Natural Resources and Agricultural Ecosystems. 2(2):39-52. https://doi.org/10.13031/jnrae.15735.
DOI: https://doi.org/10.13031/jnrae.15735

Interpretive Summary: Hydrology/water quality models are important simulation tools/technologies and frequently employed to gain a better understanding of natural resource issues and processes as well as project the impacts of implementing conservation practices. However, the input requirements for such models can be daunting and cost prohibitive, specifically as they relate to collecting site specific soil property data. An assessment of a popular hydrology model (DRAINMOD) using publicly available weather and soils data (SSURGO) indicated that daily hydrology from 15 site years of measured data across three tile drained Midwest fields could be reproduced within acceptable ranges. These findings are important for conservation policy makers, educators and practitioners needing to apply hydrology models and not having the resources to collect site specific data.

Technical Abstract: Implementing hydrologic and water quality (HWQ) models in decision-support tools (DSTs) is essential to quantify the site-specific impact of best management practices on nutrient loss under different soil, field management, and climatic scenarios. However, the performance of HWQ models and consequently DSTs in predicting contaminant load is highly dependent on the proper representation of site-specific soil properties. There is a need to study the reliability of using the Soil Survey Geographic Database (SSURGO) soil database and pedotransfer functions in HWQ models such as DRAINMOD. The objective of this study is to assess the accuracy of predicting drainage discharge using SURRGO soil data in combination with Rosetta3 in DRAINMOD. Soil physical parameters obtained from SSURGO were fed into Rosetta3 to estimate soil hydraulic parameters for each soil layer. Measured subsurface drainage discharge from three sites across the Midwest (Ohio, Michigan, and Illinois) with a total of 15 years of data were used to validate this approach. DRAINMOD satisfactorily predicted drainage discharge with daily Nash-Sutcliffe efficiency averages ranging from 0.55 to 0.80 at the three sites. The model underestimated drainage discharge for the Illinois and Michigan sites by 8% and 14%, respectively, and over-predicted it for the Ohio site by 11%. Overall, DRAINMOD predicted drainage discharge using this approach with an acceptable level of accuracy. This study is a first step towards implementing DRAINMOD into a GIS-based DST at the field scale with an automated system that obtains weather and soil data from online databases without relying on field measurements.