Integrating models with field experiments to enhance research: cover crop, manure, tillage, and climate change impacts on crops in the humid Mississippi Delta

Authors: Feng, Gary; Anapalli, Saseendran

Submitted to: Advances in Agricultural Systems Modeling
Publication Type: Book / Chapter
Publication Acceptance Date: 4/22/2022
Publication Date: 6/27/2022
Citation: Feng, G.G., Anapalli, S.S. 2022. Integrating models with field experiments to enhance research: cover crop, manure, tillage, and climate change impacts on crops in the humid Mississippi Delta. In: Ahuja, L.R., Kersebaum, K.C., Wendroth, O., editors. Advances in Agricultural Systems Modeling. p. 359-391. https://doi.org/10.1002/9780891183860.ch12.
DOI: https://doi.org/10.1002/9780891183860.ch12

Interpretive Summary: There are numerous examples of model applications to enhance field research by modelers all over the world. Ahuja et al. (2017) presented some simple examples of such applications based on their work about some critical resource areas in the Central Great Plains and Midwest, USA, and China: 1) optimizing the use of limited water in dryland cropping systems through crop selection; 2) optimizing the scheduling of limited irrigations; 3) guiding deficit irrigations based on crop water production functions; 4) minimizing N and pesticide leaching to subsurface drainage (tile flow) and groundwater; and 5) projecting climate change effects and identifying adaptation strategies. Most of these applications utilized the Root Zone Water Quality Model (RZWQM2), developed by Agricultural Systems Research Unit, USDA-ARS, which contains the DSSAT crop models. Importantly, these applications were made in collaboration with field research scientists at several locations (Akron CO, Sidney NE, Sidney MT, Greeley CO, Bushland TX, Ames IA, and several locations in China and other countries), by making them part of the team. Pertinent applications of the DSSAT model by itself and other agricultural system models were cited. For the typical dryland crop rotation of wheat-summer crop-fallow, a decision support tool to select the best summer crop was developed based on the soil water content at planting. Charts were developed for the different N balance components at different water applications and the effect of N application on the crop production function (Anapalli et al., 2008, 2012, 2014). More recently, numerous applications of RZWQM and other models have been extended to the humid southeast United States, such as Mississippi state by Feng’s research group (Feng et al., 2005, 2015, 2016, 2018; Gao et al., 2017, 2019a, b; Tang et al., 2017; Yang et al., 2019a,b, 2020, 2021; Zhang et al., 2016a,b, 2018; Ouyang et al., 2016, 2017) and Anapalli et al. (2019, 2020). Here, very useful applications of RZWQM2 involving a cover crop, poultry litter, crop water requirement, and tillage are summarized.

Technical Abstract: Agricultural system models help integrate, synthesize, and extrapolate data collected in location-specific field experiments with limited spatial and temporal representation to other soils, climates, and locations. Collection of required data representative of the soil, water, crop, and climate where the experiments are conducted is the key to modeling those experiments. Integrating such data collected in field experiments in state-of-the-science agricultural system models and long-term climate data can help us simulate the experiments on a computer and answer ‘what if’ questions when soil-water-crop-climate changes with time and location. The RZWQM2 is an agricultural system simulation model that integrates the physical, chemical, and biological processes in agriculture systems and simulates soil-water-crop management impacts on crop productivity and soil-environmental quality. This article presents some examples of performance and applications of RZWQM2 for simulating staple crop production systems in the Southeast USA, characterized by a humid climate with warm summers and mild winters. Model applications in managing cover crops, soil amendments (poultry litter), tillage, and crop-rotations are presented. Examples of system model assisted investigations of climate variability and change impacts on planting windows, crop production, and water demand availability scenarios in the region are also presented.