Evaporative Fluxes and Surface Soil Moisture Retrievals in a Mediterranean Setting from Sentinel-3 and the “Simplified Triangle”

Random Forests with Bagging and Genetic Algorithms Coupled with Least Trimmed Squares Regression for Soil Moisture Deficit Using SMOS Satellite Soil Moisture

Soil Moisture Deficit (SMD) is a key indicator of soil water content changes and is valuable to a variety of applications, such as weather and climate, natural disasters, agricultural water management, etc. Soil Moisture and Ocean Salinity (SMOS) is a dedicated mission focused on soil moisture retrieval and can be utilized for SMD estimation. In this study, the use of soil moisture derived from SMOS has been provided for the estimation of SMD at a catchment scale. Several approaches for the estimation of SMD are implemented herein, using algorithms such as Random Forests (RF) and Genetic Algorithms coupled with Least Trimmed Squares (GALTS) regression. The results show that for SMD estimation, the RF algorithm performed best as compared to the GALTS, with Root Mean Square Errors (RMSEs) of 0.021 and 0.024, respectively. All in all, our study findings can provide important assistance towards developing the accuracy and applicability of remote sensing-based products for operational use.

Simplified Priestley–Taylor Model to Estimate Land-Surface Latent Heat of Evapotranspiration from Incident Shortwave Radiation, Satellite Vegetation Index, and Air Relative Humidity

An operational and accurate model for estimating global or regional terrestrial latent heat of evapotranspiration (ET) across different land-cover types from satellite data is crucial. Here, a simplified Priestley–Taylor (SPT) model was developed without surface net radiation (Rn) by combining incident shortwave radiation (Rs), satellite vegetation index, and air relative humidity (RH). Ground-measured ET for 2000–2009 collected by 100 global FLUXNET eddy covariance (EC) sites was used to calibrate and evaluate the SPT model. A series of cross-validations demonstrated the reasonable performance of the SPT model to estimate seasonal and spatial ET variability. The coefficients of determination (R2) of the estimated versus observed daily (monthly) ET ranged from 0.42 (0.58) (p < 0.01) at shrubland (SHR) flux sites to 0.81 (0.86) (p < 0.01) at evergreen broadleaf forest (EBF) flux sites. The SPT model was applied to estimate agricultural ET at high spatial resolution (16 m) from Chinese Gaofen (GF)-1 data and monitor long-term (1982–2018) ET variations in the Three-River Headwaters Region (TRHR) of mainland China using the Global LAnd-Surface Satellite (GLASS) normalized difference vegetation index (NDVI) product. The proposed SPT model without Rn provides an alternative model for estimating regional terrestrial ET across different land-cover types.

An Integrated GIS-Hydro Modeling Methodology for Surface Runoff Exploitation via Small-Scale Reservoirs

Efficient and sustainable exploitation of water resources requires the adoption of innovative and contemporary management techniques, a need that becomes even more demanding due to climate change and increasing pressures coming from anthropogenic activities. An important outcome of this reality is the qualitative and quantitative degradation of groundwater, which clearly indicates the need to exploit surface runoff. This study presents an integrated Geographic Information System (GIS)-based methodological framework for revealing and selecting suitable locations to build small-scale reservoirs and exploit surface runoff. In this framework, the SWAT model was used to quantify surface runoff, followed by the simulation of reservoir scenarios through reservoir simulation software. Andros Island (located in Cyclades Prefecture), Greece was selected as the study area. The obtained results indicated the most suitable location for creating a reservoir for maximizing exploitation of surface runoff, based on the specific water demands of the nearby areas and the existing meteorological, hydrological, and geological background potential. Thus, two selected dam locations are analyzed by using the proposed framework. The findings showed that the first dam site is inappropriate for creating a reservoir, as it cannot meet the demand for large water extraction volumes. In addition, the outcomes confirmed the efficiency of the proposed methodology in optimum selection of locations to construct small-scale water exploitation works. This research presents a contemporary methodological framework that highlights the capability of GIS, SWAT modeling, and reservoir simulation coupling in detecting optimal locations for constructing small reservoirs.