Calibrating a Basin-scale Groundwater Model to Remotely Sensed Estimates of Groundwater Evapotranspiration

Remotely sensed vegetation indices correspond to canopy vigor and cover and have been successfully used to estimate groundwater evapotranspiration (ETg) over large spatial and temporal scales. However, these data do not provide information on depth to groundwater (dtgw) necessary for groundwater models (GWM) to calculate ETg. An iterative approach is provided that calibrates GWM to ETg derived from Landsat estimates of the Enhanced Vegetation Index (EVI). The approach is applied to different vegetation groups in Mason Valley, Nevada over an 11-year time span. An uncertainty analysis is done to estimate the resulting mean and 90% confidence intervals in ETg to dtgw relationships to quantify errors associated with plant physiologic complexity, species variability, and parameter smoothing to the 100 m GWM-grid, temporal variability in soil moisture and nonuniqueness in the solution. Additionally, a first-order second moment analysis shows ETg to dtgw relationships are almost exclusively sensitive to estimated land surface, or maximum, ETg despite relatively large uncertainty in extinction depths and hydraulic conductivity. The EVI method of estimating ETg appears to bias ETg during years with exceptionally wet spring/summer conditions. Excluding these years improves model performance significantly but highlights the need to develop a methodology that accounts not only on quantity but timing of annual precipitation on phreatophyte greenness. (KEY TERMS: groundwater models; groundwater evapotranspiration; remote sensing; depth to groundwater; Enhanced Vegetation Index; model calibration.) Carroll, Rosemary W.H., Greg M. Pohll, Charles G. Morton, and Justin L. Huntington, 2015. Calibrating a Basin-Scale Groundwater Model to Remotely Sensed Estimates of Groundwater Evapotranspiration. Journal of the American Water Resources Association (JAWRA) 1-14. DOI: 10.1111/jawr.12285