Historical Development and Applications of the EPIC and APEX models

Abstract

The development of the field-scale Erosion Productivity Impact Calculator (EPIC) model was initiated in 1981 to support assessments of soil erosion impacts on soil productivity for soil, climate, and cropping conditions representative of a broad spectrum of U.S. agricultural production regions. The first major application of EPIC was a national analysis performed in support of the 1985 Resources Conservation Act (RCA) assessment. The model has continuously evolved since that time and has been applied for a wide range of field, regional, and national studies both in the U.S. and in other countries. The range of EPIC applications has also expanded greatly over that time, including studies of (1) surface runoff and leaching estimates of nitrogen and phosphorus losses from fertilizer and manure applications, (2) leaching and runoff from simulated pesticide applications, (3) soil erosion losses from wind erosion, (4) climate change impacts on crop yield and erosion, and (5) soil carbon sequestration assessments. The EPIC acronym now stands for Erosion Policy Impact Climate, to reflect the greater diversity of problems to which the model is currently applied. The Agricultural Policy EXtender (APEX) model is essentially a multi-field version of EPIC that was developed in the late 1990s to address environmental problems associated with livestock and other agricultural production systems on a whole-farm or small watershed basis. The APEX model also continues to evolve and to be utilized for a wide variety of environmental assessments. The historical development for both models will be presented, as well as example applications on several different scales.

Evaluation of Evapotranspiration in Brazilian Cerrado Biome Simulated with the SWAT Model

“…Evapotranspiration is associated with plant growth; in SWAT, the plant growth module is a simplification of the "Environmental Policy Impact Climate" (EPIC) crop growth module [29,30], which was developed to support soil erosion assessments of the impacts of soil productivity on the soil, climate, and growing conditions of agricultural production regions in the United States [31]. SWAT uses EPIC's phenological plant development concepts based on daily cumulative heat units.…”

Exploring the potential for nitrogen fertilizer use mitigation with bundles of management interventions

“…Nitrogen embedded in harvested crop biomass (supplementary table S3) was sourced from databases [39] and literature. Nitrogen embedded in crop residues was estimated based on the same sources and crop-specific harvest indices as implemented in the EPIC cropping systems model [40,41]. Removal and burning rates of crop residues for major crops at the national scale were adopted from [42].…”

Drainage models: An evaluation of their applicability for the design of drainage systems in arid regions

“…China (Chen et al, 2020;Zenghui et al, 2019) and USA (Kisekka et al, 2017) DRAINMOD India (Gupta et al, 1993) and Egypt (Abdel-dayam & Skaggs, 1990;Kandil et al, 1995;Wahba et al, 2002;Wahba & Christen, 2006) EPIC Argentina (Bernardos et al, 2001), France (Cabelguenne et al, 1990), Australia (Jones et al, 1989), China (Gao et al, 2017) and USA (Gassman et al, 2005;USDA, 1990) HYDRUS-1D Oman (Al-Maktoumi, 2021), China (Chen et al, 2021;Qian et al, 2021), Morocco (Er-Raki et al, 2021 and Tunisia (Kanzari et al, 2021) WaSim India (Hirekhan et al, 2007) and Colombia (Depeweg & Fabiola Otero, 2004) SWAP Pakistan (Sarwar & Feddes, 2000), India (Bastiaanssen et al, 1996;Verma & Gupta, 2014;Verma & Isaac, 2010) and Argentina (Bastiaanssen et al, 1996) the performance of ADAPT to predict water table depth is comparable with the results obtained from DRAINMOD and SWAT (Desmond et al, 1996;Gowda et al, 2012). The ADAPT model was accurately applied to evaluate water flow and nutrient discharge at the field scale and catchment scale in northern Ohio and Minnesota (Dalzell et al, 2004;Davis et al, 2000;Gowda et al, 1999b).…”

“…EPIC was successfully applied in arid China, to predict maize yield and the contribution of shallow groundwater to evapotranspiration (Gao et al, 2017). EPIC has also been applied to predict crop yield in semi‐arid areas in Texas and California (Gassman et al, 2005; USDA, 1990). However, and critically, EPIC has limited ability to estimate drainage volume and changes in water table depth because of the volume of water applied (via rainfall and/or irrigation) (Wang et al, 2012).…”