Using a Crop Simulation Model to Understand the Impact of Risk Aversion on Optimal Irrigation Management

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HighlightsThe progress made in agricultural irrigation scheduling in the past ten years and the current challenges are discussed.The main scientific scheduling strategies are based on soil water status, plant characteristics, and crop modeling.Challenges include large time and data requirements and availability of decision support systems.Opportunities include integration of scheduling strategies and demonstrating their effectiveness through local studies.Abstract. Irrigation scheduling is the process of determining the appropriate amount and timing of water application to achieve desired crop yield and quality, maximize water conservation, and minimize possible negative effects on the environment, such as nutrient leaching below the crop root zone. Effective irrigation scheduling has been shown to save water, save energy, and help agricultural producers achieve improved yields and quality. However, scientific irrigation scheduling methods generally have remained limited to mostly research applications with relatively low adoption by irrigators. There are several main approaches to irrigation scheduling, including those based on soil water status, plant characteristics, and/or crop modeling. Each of these approaches has advantages as well as limitations and sources of uncertainty and variability, depending on application conditions. This article summarizes progress made in the U.S. in each of the main scheduling approaches in the past ten years (since the 2010 Decennial Irrigation Symposium) and existing challenges and opportunities that should be considered moving forward. This article is intended to guide future research and extension projects in improving adoption of scientific irrigation scheduling approaches. Keywords: Computer modeling, Plant characteristics, Soil water status.

Section: Progress Made In the Past Ten Yearsmentioning

confidence: 99%

Irrigation Scheduling for Agriculture in the United States: The Progress Made and the Path Forward

Taghvaeian¹,

Andales²,

Allen³

et al. 2020

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“…The crop modeling category includes studies simulating crop growth or yield, either as stand-alone models or as submodels within hydrologic and water quality models. McDaniel et al, 2017aMcDaniel et al, , 2017bMcDaniel et al, , 2017cMittelstet et al, 2017;Muenich et al, 2017;Renkenberger et al, 2017;Wallace et al, 2017 USLE andWEPP Lang et al, 2107;Svendsen et al, 2017;Wu et al, 2017 WEPP andUSLE Grace III, 2017;Lang et al, 2107;Lisenbee et al, 2017;Srivastava et al, 2017;Wang, L. et al, 2017;Wu et al, 2017Crop modeling APSIM Araya et al, 2017Whitbread et al, 2017AquaCrop Espadafor et al, 2017Linker and Kisekka, 2017;Wibowo et al, 2017DSSAT-CSM-CERES-Beet Anar et al, 2017DSSAT-CSM-CERES-Maize DeJonge and Thorp, 2017Fang et al, 2017aFang et al, , 2017bJoshi et al, 2017;Linker and Kisekka, 2017;Marek et al, 2017;Sharda et Anar et al, 2017;Fang et al, 2017aFang et al, , 2017bLinker and Kisekka, 2017;Liu et al, 2017SWAT Feng et al, 2017 feed value but not crude protein.…”

Section: Crop Yields and Water Usementioning

confidence: 99%

“…Two studies used crop models for soil and water management: one demonstrated no reduction in cotton yield or soil water from a winter-wheat cover crop in Texas (Adhikari et al, 2017), and another demonstrated enhanced simulation of soil-water storage and wheat yields using field-based, rather than labbased, estimates of crop lower-limit and drained upper-limit in low-rainfall cropping systems of southern Australia (Whitbread et al, 2017). A modeling analysis of irrigated corn production in Kansas found that risk-averse irrigation strategies were sensitive to well capacity and soil type and may substantially increase total water use (Wibowo et al, 2017). Two regional studies using crop models to assess climate change effects (Sharda et al, 2017;Tatsumi, 2017) are discussed in the next section.…”

Section: Crop Modelingmentioning

confidence: 99%

Current Research in Land, Water, and Agroecosystems: ASABE Journals 2017 Year in Review

Douglas-Mankin¹

2018

Abstract. This article highlights current research into land and water resources, agroecosystems, and agricultural production systems published by the Natural Resources and Environmental Systems (NRES) community of ASABE journals ( and ) in 2017. Context, scope, and key results of the published articles are reviewed and perhaps more importantly areas for increased research attention are recommended. This article describes experimental and modeling advances in hydrology, agroecosystems, climate change effects, soil erosion, agricultural irrigation, agricultural drainage, forest resource management, livestock systems, natural treatment systems, international water issues, and water quality topic areas. Three special collections were published (International Watershed Technology, Crop Modeling and Decision Support for Optimizing Use of Limited Water, and Advances in Drainage). Other focal areas included 14 articles relating to livestock waste management, 13 concerning irrigated agricultural systems, 8 addressing climate change effects on land, water, and agroecosystems, and 16 on various aspects of soil erosion measurement and modeling. Building on the articles reviewed from 2017 and toward a vision of future agroecosystems research, the NRES community of ASABE journals strives to expand its role in making new knowledge accessible to sustain agricultural and natural systems in a changing world. With this goal in mind, recommendations for future research needs are proposed with an emphasis on increased application of remote sensing data to agroecosystems research, improved assessment of agroecosystem resiliency and vulnerability to land and climate change, development of integrated models of agroecosystem services, meeting stubborn water management challenges in agricultural production systems, and focusing on publishing fully reproducible model results. Keywords: Agriculture, Climate change, Composting, Crop models, Crop water use, Crop yield, Drainage, Drought, Environment, Field experimentation, Food, Forest, Greenhouse gas emissions, Hydrologic modeling, Hydrology, Irrigation, Livestock, Manure management, Mode

“…One article in the collection addresses the topic of risk assessment in relation to irrigation water management using the AquaCrop model and risk aversion assessment techniques (Wibowo et al, 2017). Under limited water, farmers are faced with non-trivial optimization of multiple objectives (e.g., maximization of net profit, optimization of water use through maximization of water productivity, and minimization of risk to net returns).…”

Section: Risk Assessment Of Water-limited Irrigation Managementmentioning

confidence: 99%

“…Under limited water, farmers are faced with non-trivial optimization of multiple objectives (e.g., maximization of net profit, optimization of water use through maximization of water productivity, and minimization of risk to net returns). Wibowo et al (2017) explored this concept using a modeling framework to assess the optimal adjustment along the intensive (i.e., changes in seasonal irrigation depth) and extensive (i.e., changes in the irrigated area) margins. Their empirical application used AquaCrop to simulate corn yields with historical weather in southwest Kansas under a large number of potential irrigation strategies.…”

Section: Risk Assessment Of Water-limited Irrigation Managementmentioning

confidence: 99%

Crop Modeling Applications in Agricultural Water Management

Kisekka¹,

DeJonge²,

Ma³

et al. 2017

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