Institute: Nebraska
Year Established: 2014 Start Date: 2014-03-01 End Date: 2015-02-28
Total Federal Funds: $14,997 Total Non-Federal Funds: $30,493
Principal Investigators: Francisco MunozArriola
Project Summary: Water and agricultural resources in the Central Great Plains play a critical role in the interplay between water, food, and energy security both in this region, and globally, contributing to economic and social stability from local to national to international levels. A better understanding of both natural and anthropogenic processes involving the water that is needed to sustain both agricultural and natural ecosystems is key to developing stronger model integrations. This proposed project aims to: (1) Better understand the effect of climate variability on the land surface hydrology of the Platte River Basin (PRB) to ultimately improve simulations of surface and ground water connections through model integration. The project will focus on the Platte River Basin, but this methodology could be applied to regions worldwide. We will use gridded observed data to force the Variable Infiltration Capacity (VIC) model to simulate the land surface hydrology. Simulated streamflows, used to identify the effect of extreme-events on the surface hydrology of the PRB, will be used to determine the hydroclimatic controls on the water continuum from the atmosphere to the land surface, and ultimately to the vadose zone and the crop irrigation requirements. MODFLOW-Farming Process (MF-FMP) parameterizes the latter. We will pursue the elucidation and test of model-integration (VIC-MF-FMP) mechanisms by: (1) defining historical states of water forced by climate; (2) identifying the most suitable time-step and grid-size for model integration based on hydroclimatic controls; and (3) evaluating preliminary tests on an off-line coupling between a Land VIC and Farming Process (part of MF-FMP). These procedures will ultimately pursue the integration of agro-ecosystem, and ecosystem processes, and their competing water demands across spatial and temporal scales in the future.