A Remote Sensing Based Decision-Support System for Groundwater Management

Abstract:

Water managers at all levels of government worldwide are challenged to make decisions that support the long-term sustainability of our groundwater resources. The goal of our research is to develop a decision-support system that utilizes abundant remote sensing data, integrated with other forms of hydrologic data, as key inputs to an integrated surface water-groundwater model. We are developing such a prototype system for application in the San Luis Valley of Colorado and Butte County in California. Our approach incorporates the analysis of  >20 years (1992-present) of data to determine the spatial and temporal links between the principle components of the basin-scale water cycle; the model can be continually updated with the addition of newly acquired data. The comparison of model input data derived from remote sensing measurements to those obtained from currently employed sources (e.g. the comparison of rainfall data from TRMM to rain gauge data), allows us to assess any impact that converting to remote sensing data might have on the sensitivity or accuracy of the model. Central to our approach is the use of interferometric synthetic aperture radar (InSAR) deformation images to provide head measurements in the semi/confined aquifers, commonly the least well characterized element of the groundwater system. We have recently developed analysis and interpretation methods, utilizing local well calibration, that allow us to obtain long-term and seasonal head variation at a spatial resolution of ~100 m with sub-meter precision. This gives us the ability to fill in the large temporal and spatial gaps in the traditional well data, including head estimates in regions prior to the existence of any wells. The integration of InSAR and other forms of remote sensing data with hydrologic data addresses critical needs in model development and monitoring, both of which are key elements in making decisions about activities that could impact the sustainability of our groundwater resources.