Integrated Systems Modeling for Irrigation Expansion at the River Basin Scale

Understanding the complexities and quantifying the impacts of expanding irrigation in the presence of ongoing socioeconomic developments, population growth, climate change, and policy factors is a challenging task. Simulation models can facilitate such a task and allow visualizing outcomes; they can thus recommend specific policy reforms or suggest a different policy. However, such tools are often challenged by the need to integrate various processes that operate at different spatial or temporal scales, and by the need to produce models that characterize impacts at scales in which policy decisions are made – typically at river basin scale and over long time periods. The central theme of this thesis is to capture the complexity of irrigation expansion for policy assessment under climate change using a systems approach, and to find a balance between temporal modeling scales for integrating models that allows long-term agricultural and water policy assessments while maintaining accurate crop modeling. To this end, potential water policies to address water scarcity at the river basin were extracted from the literature to develop a list for modelers as a starting point for integrated modeling and for policymakers for strategic planning. The list has 51 policy interventions for the agricultural water sector, 55 for the municipal, and 31 for the industrial with relevant citations of successful modeling studies. Further, while process-based crop growth models that run on a daily time step are typically superior, knowledge and computational constraints in integrated assessments require a compromise between the temporal scales at which component processes occur, which may be short or long, and the longer scales of interest to decision makers for policy assessment. Moreover, process-based models may rely on fine-scaled data series that are hard to obtain, time-consuming to generate, or that may simply be unavailable. Therefore, a water-driven process-based crop growth model, CropSD, was developed in a System Dynamics framework based on FAO’s AquaCrop model to run daily, semi-weekly, and weekly simulations in conjunction with weekly weather input data. The aim was to examine the ability of coarser simulations to reproduce the behavior of a fine-scale model such that it can be integrated into other socioeconomic, environmental, or hydrologic models to broaden the scope of their applications. Model skill for simulating crop biomass and yield and water demands at different simulation time steps was assessed with weekly weather input data for a number of hypothetical farms including barley Alberta in Canada, maize in Nebraska in the US, and potatoes in Brussels in Belgium to represent a range of crops and growing environments. The R2 statistic showed a value of 0.95 for daily simulations, 0.83 for semi-weekly simulations, and 0.72 for weekly simulations of crop yields. The results suggest that semi-weekly and weekly simulations provided a compromise between accuracy and longer timescale for process-based crop growth model to be used in integrated assessments. CropSD was then integrated with a socioeconomic system dynamics model to describe the “big picture” of expanding the irrigation sector of Alberta in Canada. The resulting integrated model, Alberta Irrigation Scenario Simulator (AISS), captures the feedback loops between irrigation expansion, and its technical, social, economic, environmental processes, and policy choices. The model was used to simulate the impacts a set of seven scenario groups that covered a range of plausible expansion pathways for Alberta’s irrigation sector. Impacts of climate change, socioeconomic changes, and policy interventions on crop yields, economic returns, irrigation demands, and water withdrawals were assessed. Results showed increasing trends for dry matter crop yields to 2040 for the six major irrigated crops of Alberta with an increase per year of 0.071 t ha-1 for alfalfa, 0.04 t ha-1 for barley, 0.031 t ha-1 for canola, 0.061 t ha-1 for potatoes, 0.065 t ha-1 for sugar beets, and 0.039 t ha-1 for wheat for the high GHG emission climate scenario (RCP 8.5). Irrigation water demands increased by 11% in 2036-2040 based on the expansion plans and policy interventions by the Government of Alberta (GoA) under RCP 8.5. Increasing the reservoirs storage capacity by 5% did not offset the decreased water supply simulated by the SWAT hydrologic model of Alberta in 2035. However, an increase in storage by 10% allowed expansion beyond the goals by the GoA to reach 700,000 hectares.

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