Evaporative Fraction as an Indicator of Moisture Condition and Water Stress Status in Semi-Arid Rangeland Ecosystems

Abstract

Rangeland monitoring services require the capability to investigate vegetation condition and to assess biomass production, especially in areas where local livelihood depends on rangeland status. Remote sensing solutions are strongly recommended, where the systematic acquisition of field data is not feasible and does not guarantee properly describing the spatio-temporal dynamics of wide areas. Recent research on semi-arid rangelands has focused its attention on the evaporative fraction (EF), a key factor to estimate evapotranspiration (ET) in the energy balance (EB) algorithm. EF is strongly linked to the vegetation water status, and works conducted on eddy covariance towers used this parameter to increase the performances of satellite-based biomass estimation. In this work, a method to estimate EF from MODIS products, originally developed for evapotranspiration estimation, is tested and evaluated. Results show that the EF estimation from low spatial resolution over wide semi-arid area is feasible. Estimated EF resulted in being well correlated to field ET measurements, and the spatial patterns of EF maps are in agreement with the well-known climatic and landscape Sahelian features. The preliminary test on rangeland biomass production shows that satellite-retrieved EF as a water availability factor significantly increased the capacity of a remote sensing operational product to detect the variability of the field biomass measurements.

Evaluating Water Controls on Vegetation Growth in the Semi-Arid Sahel Using Field and Earth Observation Data

“…Merbold et al [22] found that mean annual rainfall is strongly correlated with maximum photosynthetic capacity and is the predominant factor driving C fluxes across Africa. With rainfall, the greening phase commences (Figure 2), and soil moisture is replenished, which impacts the amount of energy partitioned into evapotranspiration [21,23,24]. Rainfall also increases humidity, which lowers the difference between the vapor pressure deficit inside the leaf and that of the air.…”

A New Temperature-Vegetation Triangle Algorithm with Variable Edges (TAVE) for Satellite-Based Actual Evapotranspiration Estimation

“…Various methods have been proposed to locate the wet edge based on various indicators, such as the minimum T s at the maximum NDVI [11], the mean or linear regression of minimum T s values across different NDVI intervals [56], average temperature of inland waterbodies [6], or air temperature [57].…”

Phenology-Based Biomass Estimation to Support Rangeland Management in Semi-Arid Environments

“…The calibration of the regression model using multi-annual and multi-site observations can be performed with different aggregation levels, ranging from the site level (i.e., site by site) to the global level (i.e., all sites pooled together). The site-level calibration can be used to gain insights into the robustness of the relationship by analysing the slope and intercept across sites [9]. However, some level of aggregation is needed to map the biomass.…”

“…The ministry fits a linear regression model between ground measurements of the current season and a NDVI-based metric (maximum NDVI, mean NDVI, or cumulative NDVI are tested, and the best-performing metric is selected) to create a map of rangeland biomass. In 2014, Nutini et al [9] estimated the extent of rangeland biomass at three sites in Niger with a radiation use efficiency model utilising cumulative dry matter productivity derived from SPOT-VGT [10] over a fixed time period, corrected with the evaporative fraction and derived from Moderate-resolution Imaging Spectroradiometer (MODIS) albedo and thermal measurements.…”