09 Mar 2022
09 Mar 2022
Status: this preprint is currently under review for the journal NHESS.

Interactions between precipitation, evapotranspiration and soil moisture-based indices to characterize drought with high-resolution remote sensing and land-surface model data

Jaime Gaona1,2, Pere Quintana-Seguí2, María José Escorihuela3, Aaron Boone4, and María Carmen Llasat5 Jaime Gaona et al.
  • 1Instituto de Investigación en Agrobiotecnología, CIALE, Universidad de Salamanca, Villamayor-Salamanca, 37185, Spain
  • 2Hydrology and climate change, Observatori de l’Ebre (Universitat Ramon Llull - CSIC), Roquetes, 43520, Catalonia, Spain
  • 3IsardSAT, Parc Tecnologic Barcelona Activa, Barcelona, 08042, Catalonia, Spain
  • 4GMME/MOANA (Groupe de Météorologie à Moyenne Echelle), MOdélisation de l’Atmosphère Nuageuse et Analyse CNRMGAME (URA CNRS & Météo-France), 42, Av. G. Coriolis, 31057, Toulouse Cedex 1, France
  • 5Applied physics department, Faculty of Physics, University of Barcelona, Barcelona, 08028, Catalonia, Spain

Abstract. The Iberian Peninsula is prone to drought due to the high variability of the Mediterranean climate with severe consequences for drinking water supply, agriculture, hydropower, and ecosystems functioning. In view of the complexity and relevance of droughts in this region, it is necessary to increase our understanding of the temporal interactions of precipitation, evapotranspiration and soil moisture that originate drought within the Ebro basin, in northeast Spain, as study region. Remote sensing and land-surface models provide high spatial and temporal resolution data to characterize evapotranspiration and soil moisture anomalies in detail. The increasing availability of these datasets has potential to overcome the lack of in-situ observations of evapotranspiration and soil moisture. In this study, remote sensing data of evapotranspiration from MOD16A2ET and soil moisture data from SMOS1km as well as SURFEX-ISBA land-surface model data are used to calculate the EvapoTranspiration Deficit Index (ETDI) and the Soil Moisture Deficit Index (SMDI) for the period 2010–2017. The study compares the remote sensing time series of these ETDI and SMDI indices with the ones estimated using the land-surface model SURFEX-ISBA, including the Standardized Precipitation Index (SPI) computed at weekly scale. The study focuses on the analysis of the temporal lags between the indices to identify the synchronicity and memory of the anomalies between precipitation, evapotranspiration and soil moisture to interpret factors involved in drought onset. Lag analysis results demonstrate the capabilities of the SPI, ETDI and SMDI drought indices to inform about the mechanisms of drought propagation at distinct levels of the land-atmosphere system. Relevant feedbacks both for antecedent and subsequent conditions are identified, with a preeminent role of evapotranspiration in the link between rainfall and soil moisture. Both remote sensing and land-surface model show capable to characterize drought events, with specific advantages and drawbacks of the remote sensing and land-surface model datasets. Results underline the value of analyzing drought with dedicated indices, preferably at weekly scale, to better identify the quick self-intensifying and mitigating mechanisms governing drought, which are relevant for drought monitoring in semi-arid areas.

Jaime Gaona et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on nhess-2022-65', Anonymous Referee #1, 04 Apr 2022
  • RC2: 'Comment on nhess-2022-65', Anonymous Referee #2, 08 Apr 2022

Jaime Gaona et al.

Jaime Gaona et al.


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Short summary
Droughts represent a particularly complex natural hazard that requires explorations of its multiple causes. Part of the complexity has roots in the interaction between the continuous changes and deviation from normal conditions of the atmosphere and the land surface. The exchange between the atmospheric and surface conditions defines feedback towards dry or wet conditions. In semi-arid environments, energy seems to exceed water in its impact over the evolution of conditions, favoring drought.