Utility of Remotely Sensed Evapotranspiration Products to Assess an Improved Model Structure

Abstract

There is a certain level of predictive uncertainty when hydrologic models are applied for operational purposes. Whether structural improvements address uncertainty has not well been evaluated due to the lack of observational data. This study investigated the utility of remotely sensed evapotranspiration (RS-ET) products to quantitatively represent improvements in model predictions owing to structural improvements. Two versions of the Soil and Water Assessment Tool (SWAT), representative of original and improved versions, were calibrated against streamflow and RS-ET. The latter version contains a new soil moisture module, referred to as RSWAT. We compared outputs from these two versions with the best performance metrics (Kling–Gupta Efficiency [KGE], Nash-Sutcliffe Efficiency [NSE] and Percent-bias [P-bias]). Comparisons were conducted at two spatial scales by partitioning the RS-ET into two scales, while streamflow comparisons were only conducted at one scale. At the watershed level, SWAT and RSWAT produced similar metrics for daily streamflow (NSE of 0.29 and 0.37, P-bias of 1.7 and 15.9, and KGE of 0.47 and 0.49, respectively) and ET (KGE of 0.48 and 0.52, respectively). At the subwatershed level, the KGE of RSWAT (0.53) for daily ET was greater than that of SWAT (0.47). These findings demonstrated that RS-ET has the potential to increase prediction accuracy from model structural improvements and highlighted the utility of remotely sensed data in hydrologic modeling.

Multivariate Calibration of the SWAT Model Using Remotely Sensed Datasets

“…The findings of this study share bo"h si'Ilarities and differences with other studies that showed improvements in model calibration using remote sensing ET products, such as those conducted by Lee et al [10,11]. They found that using ET products improved the model performance for ET, whereas we did not find substantial differences in model performance when including ET products in model calibration.…”

“…Remotely sensed data can provide crucial information about the dynamics of the water budget [5][6][7][8]. As such, the hydrologic calibration process can benefit from the inclusion of remotely sensed soil moisture [9] and ET [10,11] data, in addition to traditionally used streamflow measurements, to capture the spatiotemporal distribution of the water budget components [2,12,13], particularly in arid/semi-arid watersheds with regulated water resources systems, where evapotranspiration (ET) and soil moisture content play an important role in determining groundwater recharge and irrigation water requirements [7,14].…”

The Application of SWAT Model and Remotely Sensed Products to Characterize the Dynamic of Streamflow and Snow in a Mountainous Watershed in the High Atlas

“…One of the most promising approaches is the use of recently developed earth observations [ 112 ]. Previous studies have demonstrated the efficacy of remotely sensed products to implement and calibrate hydrological models [ 113 , 114 , 115 , 116 ]. For example, several studies have used remotely sensed evapotranspiration [ 112 , 117 ], soil moisture [ 118 ], leaf area index [ 116 , 119 ], and snow water equivalent [ 44 ] to calibrate the SWAT model.…”

PESTIPOND: A descriptive model of pesticide fate in artificial ponds: II. Model application and evaluation

“…The KGE and NSE values are >0.5, and the RMSE does not exceed 0.07. Considering how wide the goodness-of-fit-range of variations are (NSE (-∞, 1] and KGE (-∞, 1]), the model performance can be considered as "good" due to the annual calibration (Lee et al, 2021;Moriasi et al, 2007;Moriasi et al, 2015). The simulations of the daily concentrations and masses of bentazon and diflufenican align with the observations.…”