A platform for research: civil engineering, architecture and urbanism
Modeling of subsurface agricultural drainage using two hydrological models with different conceptual approaches as well as dimensions and spatial scales
In regions where soils are seasonally or perennially wet, subsurface drainage represents an essential water management practice. Two hydrological models with different modeling approaches as well as different dimensional and spatial scales, DRAINMOD (1D, lumped and field-scale) and CATHY (3D, spatially distributed and watershed-scale), were compared in terms of their performance to predict tile-drain flow and to simulate evapotranspiration (ET) under field conditions. Two metrics were defined to assess the capacity of the models to represent the soil water dynamics: relative errors in simulating peak flow and drainage volume. Using different hydraulic conductivity scenarios, both models provided similar results. For the total predicted/observed tile-drain flow comparison, the two models yielded very similar results. In terms of coefficient of determination (R 2 ) and Nash-Sutcliffe model efficiency (NSE), their performances were low in simulating tile-drain flows for dry periods (low observed tile-drain flow). During periods with higher observed tile-drain flow, the performance of both models was good (R 2 > 0.75 and NSE mostly > 0.60), but DRAINMOD produced better results than CATHY did. The two models had similar ET values (R 2 > 0.80). Regarding the impact of the hydraulic conductivity of each soil layer on subsurface drainage outflow, this study showed that the soil layer below the tile-drain system was the most influential for the two models.
Modeling of subsurface agricultural drainage using two hydrological models with different conceptual approaches as well as dimensions and spatial scales
In regions where soils are seasonally or perennially wet, subsurface drainage represents an essential water management practice. Two hydrological models with different modeling approaches as well as different dimensional and spatial scales, DRAINMOD (1D, lumped and field-scale) and CATHY (3D, spatially distributed and watershed-scale), were compared in terms of their performance to predict tile-drain flow and to simulate evapotranspiration (ET) under field conditions. Two metrics were defined to assess the capacity of the models to represent the soil water dynamics: relative errors in simulating peak flow and drainage volume. Using different hydraulic conductivity scenarios, both models provided similar results. For the total predicted/observed tile-drain flow comparison, the two models yielded very similar results. In terms of coefficient of determination (R 2 ) and Nash-Sutcliffe model efficiency (NSE), their performances were low in simulating tile-drain flows for dry periods (low observed tile-drain flow). During periods with higher observed tile-drain flow, the performance of both models was good (R 2 > 0.75 and NSE mostly > 0.60), but DRAINMOD produced better results than CATHY did. The two models had similar ET values (R 2 > 0.80). Regarding the impact of the hydraulic conductivity of each soil layer on subsurface drainage outflow, this study showed that the soil layer below the tile-drain system was the most influential for the two models.
Modeling of subsurface agricultural drainage using two hydrological models with different conceptual approaches as well as dimensions and spatial scales
Muma, Mushombe (author) / Rousseau, Alain N / Gumiere, Silvio J
2017
Article (Journal)
English
Local classification TIB:
385/6615
Distributed hydrological modeling of irrigation water use efficiency at different spatial scales
British Library Online Contents | 2010
|Quality of Subsurface Drainage Water Under Different Agricultural Production Systems
British Library Conference Proceedings | 1996
|Spatial Modeling of Soil Properties for Subsurface Drainage Projects
British Library Online Contents | 1998
|Performance evaluation of agricultural drainage water using modeling and statistical approaches
British Library Online Contents | 2016
|