The predictability of reported drought events and impacts in the Ebro Basin using six different remote sensing data sets

Abstract

Abstract. The implementation of drought management plans contributes to reduce the wide range of adverse impacts caused by water shortage. A crucial element of the development of drought management plans is the selection of appropriate indicators and their associated thresholds to detect drought events and monitor the evolution. Drought indicators should be able to detect emerging drought processes that will lead to impacts with sufficient anticipation to allow measures to be undertaken effectively. However, in the selection of appropriate drought indicators, the connection to the final impacts is often disregarded. This paper explores the utility of remotely sensed data sets to detect early stages of drought at the river basin scale and determine how much time can be gained to inform operational land and water management practices. Six different remote sensing data sets with different spectral origins and measurement frequencies are considered, complemented by a group of classical in situ hydrologic indicators. Their predictive power to detect past drought events is tested in the Ebro Basin. Qualitative (binary information based on media records) and quantitative (crop yields) data of drought events and impacts spanning a period of 12 years are used as a benchmark in the analysis. Results show that early signs of drought impacts can be detected up to 6 months before impacts are reported in newspapers, with the best correlation-anticipation relationships for the standard precipitation index (SPI), the normalised difference vegetation index (NDVI) and evapotranspiration (ET). Soil moisture (SM) and land surface temperature (LST) offer also good anticipation but with weaker correlations, while gross primary production (GPP) presents moderate positive correlations only for some of the rain-fed areas. Although classical hydrological information from water levels and water flows provided better anticipation than remote sensing indicators in most of the areas, correlations were found to be weaker. The indicators show a consistent behaviour with respect to the different levels of crop yield in rain-fed areas among the analysed years, with SPI, NDVI and ET providing again the stronger correlations. Overall, the results confirm remote sensing products' ability to anticipate reported drought impacts and therefore appear as a useful source of information to support drought management decisions.

Spatio-Temporal Analysis of Vegetation Dynamics as a Response to Climate Variability and Drought Patterns in the Semiarid Region, Eritrea

“…The integration of remotely sensed data with climate datasets, e.g., Climate Engine powered with Google Earth, has provided a very valuable spatial dataset to researchers and provided a convenient platform to further reprocess and extract useful spatial information at convenient scales. Indicators such as the SPI and NDVI can generate the best correlation-anticipation relationships for early signs of drought impacts and drought monitoring purposes, such as identifying hot spots at local scales [14,15].…”

Integration of Microwave and Optical/Infrared Derived Datasets for a Drought Hazard Inventory in a Sub-Tropical Region of India

“…The volumetric soil moisture datasets are available in units of m 3 m −3 . The data availability and quality have improved due to a day by day increase in satellite sensors, which has rapidly increased the number of studies using CCI-SM [29][30][31][32]. CCI-SM represents the moisture available in the soil from the surface to a depth of a few millimeters to centimeters from the soil surface.…”

The Utility of Land-Surface Model Simulations to Provide Drought Information in a Water Management Context Using Global and Local Forcing Datasets

“…However, observed data for this variable are rare (Seneviratne et al 2010). AghaKouchak et al (2015) considers that satellite data, which are not currently used for drought monitoring in most basins, offer interesting opportunities to improve early drought warning, and Linés et al (2017) shows that satellite data can be used for the early warning of droughts in the Ebro basin. Concerning remotely sensed soil moisture, recent missions (Entekhabi et al 2010;Kerr et al 2012;Bindlish et al 2015) and new high-resolution datasets (Escorihuela et al 2012;Merlin et al 2013;Molero et al 2016) are producing even more possibilities.…”