Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
doi:10.5194/hess-2016-671
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
17 Jan 2017
Review status
A revision of this discussion paper is under review for the journal Hydrology and Earth System Sciences (HESS).
The predictability of reported drought events and impacts in the Ebro Basin using six different remote sensing data sets
Clara Linés1, Micha Werner1,2, and Wim Bastiaanssen1,3 1UNESCO-IHE, Department of Water Science and Engineering, 2601 DA, Delft, the Netherlands
2Deltares, 2600 MH, Delft, the Netherlands
3Delft University of Technology, Faculty of Civil Engineering and Geosciences, 2628 CD, Delft, the Netherlands
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 their 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 how much time can be gained to inform operational land and water management practices. Six different remote sensing data sets with different spectral origin and measurement frequency 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 some 6 months before impacts are reported in newspapers, with the best correlation-anticipation relationships for the Standard Precipitation Index (SPI), the Normalized 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 rainfed 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 rainfed 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.

Citation: Linés, C., Werner, M., and Bastiaanssen, W.: The predictability of reported drought events and impacts in the Ebro Basin using six different remote sensing data sets, Hydrol. Earth Syst. Sci. Discuss., doi:10.5194/hess-2016-671, in review, 2017.
Clara Linés et al.
Clara Linés et al.
Clara Linés et al.

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Short summary
This paper aims at identifying earth observation datasets that can help river basin managers detect drought conditions that may lead to impacts early enough to take mitigation actions. Six remote sensing products were assessed using two types of impact data as a benchmark: media records from a regional newspaper and crop yields. Precipitation, vegetation condition and evapotranspiration products showed the best results, offering early signs of impacts up to 6 months before the reported damages.
This paper aims at identifying earth observation datasets that can help river basin managers...
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