Modeling irrigation behavior in groundwater systems

Abstract

Integrated hydro-economic models have been widely applied to water management problems in regions of intensive groundwater-fed irrigation. However, policy interpretations may be limited as most existing models do not explicitly consider two important aspects of observed irrigation decision making, namely the limits on instantaneous irrigation rates imposed by well yield and the intraseasonal structure of irrigation planning. We develop a new modeling approach for determining irrigation demand that is based on observed farmer behavior and captures the impacts on production and water use of both well yield and climate. Through a case study of irrigated corn production in the Texas High Plains region of the United States we predict optimal irrigation strategies under variable levels of groundwater supply, and assess the limits of existing models for predicting land and groundwater use decisions by farmers. Our results show that irrigation behavior exhibits complex nonlinear responses to changes in groundwater availability. Declining well yields induce large reductions in the optimal size of irrigated area and irrigation use as constraints on instantaneous application rates limit the ability to maintain sufficient soil moisture to avoid negative impacts on crop yield. We demonstrate that this important behavioral response to limited groundwater availability is not captured by existing modeling approaches, which therefore may be unreliable predictors of irrigation demand, agricultural profitability, and resilience to climate change and aquifer depletion.

The buffer value of groundwater when well yield is limited

“…The instantaneous groundwater supply constraint is dependent on well 109 yield and irrigated area, which together limit the maximum depth of water that 110 can be applied on any day in AquaCrop-OS. This constraint is important as 111 low instantaneous application rates may be insufficient to meet peak crop water 112 requirements during sensitive growth periods, leading to the build up of soil 113 moisture deficits and reductions in crop yields in particular when surface water 114 supply is exhausted early in the growing season (Foster et al, 2014). M is the number of soil moisture target strategies, S is the number of surface wa-136 ter allocations, and G is the number of groundwater supply constraints.…”

“…M is the number of soil moisture target strategies, S is the number of surface wa-136 ter allocations, and G is the number of groundwater supply constraints. Note 137 that the previous methodology developed by Foster et al (2014Foster et al ( , 2015a …”

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

“…Few studies have evaluated the impact of risk aversion on a farmer's irrigation strategy (Boggess et al, 1983;Bernardo, 1988;Peterson and Ding, 2005;Foster et al, 2014). Peterson and Ding (2005) used a production function approach in which crop yield is related to total annual irrigation water applied or total irrigation within crop growth stages.…”

“…However, irrigation with limited water availability is unable to completely mitigate risk, so the degree of risk aversion has an impact on a farmer's irrigation strategy (Boggess et al, 1983;Bernardo, 1988;Peterson and Ding, 2005;Foster et al, 2014). Deficit irrigation may result in greater variability in crop yield compared to full irrigation, particularly for corn (Kisekka et al, 2015).…”

“…Deficit irrigation may result in greater variability in crop yield compared to full irrigation, particularly for corn (Kisekka et al, 2015). Therefore, it is likely that more risk-averse farmers respond by reducing the irrigated area (Foster et al, 2014).…”