Assessment of Remotely Sensed Near-Surface Soil Moisture for Distributed Eco-Hydrological Model Implementation

Carlos Echeverría,Luis Samaniego,Guiomar Ruiz-Pérez,Cristina Puertes,Brian Barrett,Félix Francés

doi:10.3390/w11122613

Abstract

The aim of this study was to implement an eco-hydrological distributed model using only remotely sensed information (soil moisture and leaf area index) during the calibration phase. Four soil moisture-based metrics were assessed, and the best alternative was chosen, which was a metric based on the similarity between the principal components that explained at least 95% of the soil moisture variation and the Nash-Sutcliffe Efficiency (NSE) index between simulated and observed surface soil moisture. The selected alternative was compared with a streamflow-based calibration approach. The results showed that the streamflow-based calibration approach, even presenting satisfactory results in the calibration period (NSE = 0.91), performed poorly in the validation period (NSE = 0.47) and Leaf Area Index (LAI) and soil moisture were neither sensitive to the spatio-temporal pattern nor to the spatial correlation in both calibration and validation periods. Hence, the selected soil moisture-based approach showed an acceptable performance in terms of discharges, presenting a negligible decrease in the validation period (ΔNSE = 0.1) and greater sensitivity to the spatio-temporal variables’ spatial representation.

Highlights

The traditional approach to hydrological model calibration is based only on observed streamflow time series at available gauging stations within the studied basins
There is a high availability of satellite data, almost in real time, with sufficient spatio-temporal resolutions (30 m–25 km) for ecohydrology in most cases and with a spatial distribution covering the entire earth
Among the sources of satellite information that can be used in ecohydrology, the following stand out: real evapotranspiration [19,20,21,22], land surface temperature [23,24], different vegetation indices [25,26,27], near-surface soil moisture, [28,29,30,31,32] and more recently total water storage anomaly [33]

Summary

Introduction

The traditional approach to hydrological model calibration is based only on observed streamflow time series at available gauging stations within the studied basins. The assessment of streamflow for a river basin provides an aggregated signal and provided a limited information on the behavior of other relevant state variables of the system [1,2,3,4,5,6,7]. In order to deal with this, the data obtained from remote sensing satellites has become a key alternative [8,9,10,11,12,13,14,15,16,17], significantly increasing the use of this type of information in recent decades for state variables used in ecohydrology [18]. Among the sources of satellite information that can be used in ecohydrology, the following stand out: real evapotranspiration [19,20,21,22], land surface temperature [23,24], different vegetation indices [25,26,27], near-surface soil moisture (hereafter SM), [28,29,30,31,32] and more recently total water storage anomaly [33]

Objectives

Methods

Conclusion