2020
DOI: 10.1371/journal.pone.0241689
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Performances of the WEPP and WaNuLCAS models on soil erosion simulation in a tropical hillslope, Thailand

Abstract: Effective soil erosion prediction models and proper conservation practices are important tools to mitigate soil erosion in hillside agricultural areas. The Water Nutrient and Light Capture in Agroforestry Systems (WaNuLCAS) and Water Erosion Prediction Project (WEPP) models are capable tools in soil erosion simulation in the conventional and conservation cropping systems in hillslopes. We calibrated both the models in maize monocropping and simultaneously validated them in maize-chili intercropping with … Show more

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Cited by 11 publications
(5 citation statements)
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“…Only a few AF models (Hi-SAFE and WaNuLCAS) are widely applied for ESS estimations and others (SCUAF, HyPAR, and HyCAS) have rarely been tested in recent years. While a few AFS models have been developed and applied (Mobbs et al, 1998;Van Noordwijk and Lusiana, 1998;Dupraz et al, 2019), but were not tested dynamically for soil protection and conservation at the field scale (García de Jalón et al, 2018b;Onsamrarn et al, 2020). Models such as HyPAR consequently have limitations regarding basic soil processes, as its simulations of water, runoff, soil water storage capacity, drainage, and water holding capacity are poor, which means it is unsuitable for soil erosion and conservation estimations.…”
Section: Limitations and Key Challenges Of Current Afs Models For The...mentioning
confidence: 99%
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“…Only a few AF models (Hi-SAFE and WaNuLCAS) are widely applied for ESS estimations and others (SCUAF, HyPAR, and HyCAS) have rarely been tested in recent years. While a few AFS models have been developed and applied (Mobbs et al, 1998;Van Noordwijk and Lusiana, 1998;Dupraz et al, 2019), but were not tested dynamically for soil protection and conservation at the field scale (García de Jalón et al, 2018b;Onsamrarn et al, 2020). Models such as HyPAR consequently have limitations regarding basic soil processes, as its simulations of water, runoff, soil water storage capacity, drainage, and water holding capacity are poor, which means it is unsuitable for soil erosion and conservation estimations.…”
Section: Limitations and Key Challenges Of Current Afs Models For The...mentioning
confidence: 99%
“…However, AF models have limitations in terms of their water retention estimations and flood measurements due to their complex structures. Efforts have been made in a few AF models, but there are still limitations as these models lack accurate estimations for these effects under AFS (Wösten et al, 1998;Pansak et al, 2010;Dufour et al, 2013;Onsamrarn et al, 2020). Among the AF models, HyPAR is rarely used, in part because it has poor simulations for hydrological properties (infiltration, water storage capacity, drainage, and water holding capacity) and lacks accurate function estimations for water retention and flooding.…”
Section: Onsite Water Retention To Prevent Floodingmentioning
confidence: 99%
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“…It was designed to simulate Tree-Soil-Crop interactions under a wide range of agroforestry systems. It uses the Rose equation [40] to simulate the erosion process in a simplified 2D approach. However, this component of WaNuLCAS has not been tested extensively and requires further investigation.…”
Section: Model Comparison With Respect To Simulating Soil Erosion In Complex Cropping Systemsmentioning
confidence: 99%
“…The WaNuLCAS model contains a mechanistic approach to water erosion running, as does the rest of the model, on a daily time step. A comparison of a calibrated WaNuLCAS model with the erosion model WEPP [100] for an agroforestry system in Thailand showed a strong overestimation of the surface runoff [101]. The rangeland hydrology and erosion model (RHEM) [102] is based on WEPP, but has been extended with parameters for a better capture of woody patches, but this model package omits routines for plant growth in the herbal/crop and tree layer and is therefore not a subject of this study.…”
Section: Surface Protectionmentioning
confidence: 99%