Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Abstract

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.

Estimating annual water storage variations in medium-scale (2000–10 000 km<sup>2</sup>) basins using microwave-based soil moisture retrievals

“…Recent progress in the remote sensing of dS / dt and θ has been mirrored by the increased consideration of satellite-derived E T retrievals in a water balance context (Senay et al, 2011;Hain et al, 2015;Hendrickx et al, 2016;Wang-Erlandsson et al, 2016). In particular, when combined with P and basin-outlet stream flow (Q) measurements, satellite-derived E T estimates can be used to verify estimates of dS / dt obtained from independent sources (Han et al, 2015).…”

Mapping Evapotranspiration Coefficients in a Temperate Maritime Climate Using the METRIC Model and Landsat TM

“…Furthermore, introducing hyperspectral data is possible to improve the accuracy of LST computation, while the use of microwave data during the days affected by weather could make an LST estimation feasible. An integrated use of multi-source, multi-scale remote sensing data to expand temporal scale of ET r F based on the characteristics of study area, is a breakthrough for future research [77][78][79]. On such basis, this study provides the framework for future analysis elsewhere.…”

Adaptive Crop Management under Climate Uncertainty: Changing the Game for Sustainable Water Use

“…The METRIC (Mapping EvapoTranspiration at high spatial Resolution with Internalized Calibration) algorithm [30] with Landsat satellite data was applied to map regional distributions of ET. METRIC has attractive features for retrieval of ET distributions over heterogeneous field sites for the following reasons: (1) it consists of physically based image analysis algorithms; (2) the need for atmospheric correction of short wave and thermal information in images is reduced an internal calibration based on the selection of a cold (well-watered crop under full cover) and hot pixel (bare soil without evaporation) in each image; (3) METRIC includes terrain models for solar and thermal radiation calculation; (4) it was used successfully with Landsat images at spatial scales of 30-60 m and MODIS images at spatial scales of 250-1000 m [31][32][33][34][35][36]; (5) it improves the performance of hydrologic decision support tools compared to their traditional implementations [37].…”