Surveying Ground Water Level Using Remote Sensing: An Example over the Seco and Hondo Creek Watershed in Texas

摘要

The Normalized Difference Vegetation Index (NDVI) derived from satellite data has been applied to various vegetation studies. The objective of this study was to assess the feasibility of using the NDVI response to plant water content to predict ground water level over a watershed located in the Edwards Aquifer of Texas, USA. Results showed that the precipitation data collected inside the watershed were not highly correlated to ground water depth within 10 d of the event, though a 60-foot sinkhole in the study site was expected to collect rainfall and recharge ground water in a short time. Alternatively, the NDVI derived from SPOT-VEGETATION satellite data and potential evapotranspiration (PET) based on the Hargreaves PET model were significantly correlated to ground water depth. Moreover, the stream flow measurements were correlated to ground water level as well. Two simple models were developed for estimating ground water levels in the artesian and recharge zones. Independent validations were performed to verify both models. All three variables (NDVI, PET, and stream flow) were directly or indirectly related to the precipitation. The PET was mainly controlled by air temperature, and the temperature was negatively related to precipitation. The NDVI values were affected by both temperature and precipitation, and the amount of rainfall was strongly correlated to the stream flow. This study initiated a unique approach to surveying ground water level based on satellite information and meteorological data.