Simulating Regional Dynamic Vegetation and Water Resources with Coupled Biophysical and Hydrologic Models

Climate change, population growth, biofuel production, and a host of other global forces are driving alterations of agricultural production worldwide, with little comprehensive understanding of the impacts these changes will have on water resources. While plot-scale soil-plant-water interactions have been intensively studied and simulated for decades, few tools are available to quantify watershed-to-basin scale impacts of shifting agricultural production systems. A recent class of fully-distributed models that simulate the complete terrestrial hydrologic cycle are well suited for fine-resolution, basin-scale studies. Here we present the first coupling of such a model, the Integrated Landscape Hydrology Model (ILHM), with a dynamic vegetation/crop growth model, the Systems Approach to Land Use Sustainability (SALUS) model. The coupled SALUS-ILHM code was first tested for a series of plots with both intensively monitored agricultural and natural land uses in Michigan. We then simulate a regional watershed in Michigan under current and statistically-downscaled forecast climate to demonstrate the capabilities of the coupled models and validate their performance. Model-predicted leaf area index (LAI) and agricultural yields are compared to remotely-sensed and county-aggregate statistics, respectively. Impacts of explicitly simulating vegetation and root growth on hydrologic model performance are presented. Preliminary climate change forecast scenarios indicate significant alterations to Michigan’s hydrologic and agroecological systems, including longer growing seasons, altered yields for current-generation crops, reduced seasonal snowpacks, and lower summer stream flows.