Gaona et al. (2022) Interactions between precipitation, evapotranspiration and soil-moisture-based indices to characterize drought with high-resolution remote sensing and land-surface model data

Identification

• Journal: Natural hazards and earth system sciences
• Year: 2022
• Authors: Jaime Gaona, Pere Quintana Seguí, Maria‐José Escorihuela, Aaron Boone, María Carmen Llasat
• DOI: 10.5194/nhess-22-3461-2022

Research Groups

• Instituto de Investigación en Agrobiotecnología, CIALE, Universidad de Salamanca, Villamayor, Salamanca, Spain
• Hydrology and climate change, Observatori de l'Ebre (Universitat Ramon Llull – CSIC), Roquetes, Catalonia, Spain
• IsardSAT, Parc Tecnològic – Barcelona Activa, Barcelona, Catalonia, Spain
• Groupe de Météorologie de Moyenne Echelle, MOdélisation de l'Atmosphère Nuageuse et Analyse, GMME-MOANA, CNRM-GAME (URA CNRS – Météo-France), Toulouse, France
• Department of Applied Physics, Faculty of Physics, University of Barcelona, Barcelona, Catalonia, Spain

Short Summary

This study investigates the temporal interactions and feedback mechanisms among precipitation (SPI), evapotranspiration (ETDI), and soil moisture (SMDI) indices in the Ebro basin (Iberian Peninsula) using high-resolution remote sensing and land-surface model data. The analysis reveals that evapotranspiration plays a preeminent, self-intensifying role in drought propagation, highlighting the necessity of using a weekly temporal scale for accurate monitoring in semi-arid environments.

Objective

• To evaluate the suitability of high-resolution remote sensing (RS) data (MOD16A2, SMOS1km) and land-surface model (LSM) data (SURFEX-ISBA) for generating weekly-scale Standardized Precipitation Index (SPI), Evapotranspiration Deficit Index (ETDI), and Soil Moisture Deficit Index (SMDI).
• To characterize the temporal interactions (synchronicity, memory, and reciprocity) between precipitation, evapotranspiration, and soil moisture anomalies to better understand drought propagation mechanisms in the semi-arid Ebro basin.
• To compare the results derived from RS and LSM data sources to identify their respective capabilities and limitations for high-resolution drought monitoring.
• To evaluate the advantage of adopting the weekly temporal scale over the traditional monthly scale for capturing short-term drought anomalies.

Study Configuration

• Spatial Scale: Ebro basin, northeastern Iberian Peninsula (85,534 km²). All data were processed and analyzed on a regular grid with 5 km × 5 km resolution.
• Temporal Scale: Analysis period 2010–2017. Drought indices (SPI, ETDI, SMDI) were computed and analyzed primarily at a weekly (7 day) scale. Lag analysis extended up to ±104 weeks.

Methodology and Data

• Models used:
  • SURFEX (Surface Externalisée) land-surface modeling platform.
  • ISBA-DIF (Interaction between Soil Biosphere Atmosphere – Diffusion version) scheme for simulating natural surfaces.
  • SAFRAN meteorological analysis system used for atmospheric forcing of the LSM.
• Data sources:
  • Remote Sensing (RS):
    • MOD16A2 (Evapotranspiration and Potential Evapotranspiration) from MODIS (500 m resolution).
    • SMOS1km (Surface Soil Moisture) derived from SMOS using the DisPATCh algorithm (1 km resolution).
  • Indices: Standardized Precipitation Index (SPI), Evapotranspiration Deficit Index (ETDI), and Soil Moisture Deficit Index (SMDI) were calculated non-parametrically at the weekly scale.
  • Analysis: Pearson correlation coefficient ($r$) was used for correlation matrices and temporal lag analysis between pairs of indices (e.g., ETDIw vs. SPIw-i, SMDIw vs. SPIw-i, ETDIw vs. SMDIw).

Main Results

• Scale Importance: The weekly scale is crucial for capturing the quick onset and evolution of drought, especially in high-energy semi-arid climates, revealing short-term interactions overlooked by the monthly scale.
• Drought Propagation Mechanisms: Lag analysis shows that interactions between indices are concentrated in the short term (within a few weeks). The system exhibits an asymmetrical interaction:
  • Evapotranspiration Dominance: The ETDI shows a stronger and longer-lasting precedent influence (feedback) on the SPI than the SMDI does, suggesting that evapotranspiration plays a preeminent role in linking rainfall and soil moisture anomalies.
  • Self-Intensifying Loop: Drought evolution is often governed by a reinforcing dry loop, particularly during high-energy periods, where negative ET anomalies reduce subsequent rainfall, leading to further soil moisture depletion.
• Data Source Comparison:
  • RS (MOD16A2) and LSM (SURFEX-ISBA) estimates of ETDI show high agreement (monthly $r=0.77$).
  • LSM SMDI results show substantially lower correlations with SPI and ETDI compared to RS SMOS1km results, indicating limitations in the offline LSM simulation's ability to accurately describe surface soil moisture response to atmospheric forcing in this region.

Contributions

• Provides a novel, high-resolution (5 km, weekly scale) characterization of drought mechanisms in the Ebro basin using dedicated single-variable indices (SPI, ETDI, SMDI).
• Quantitatively diagnoses the temporal reciprocity and memory in the land–atmosphere system, confirming that evapotranspiration anomalies drive significant feedback mechanisms that precede and influence precipitation anomalies in semi-arid Mediterranean climates.
• Empirically validates the necessity of adopting a weekly temporal scale for drought monitoring in regions prone to "flash droughts" and rapid hydrological changes.
• Offers a critical evaluation of the performance of high-resolution RS products (MOD16A2, SMOS1km) against an offline land-surface model (SURFEX-ISBA), providing insights for improving regional hydrological modeling, especially concerning surface soil moisture dynamics.

Funding

• Spanish State Research Agency (Agencia Estatal de Investigación, AEI) within the HUMID project (AEI/FEDER EU grant no. CGL2017-85687-R).

Citation

@article{Gaona2022Interactions,
  author = {Gaona, Jaime and Quintana‐Seguí, Pere and Escorihuela, Maria‐José and Boone, Aaron and Llasat, María Carmen},
  title = {Interactions between precipitation, evapotranspiration and soil-moisture-based indices to characterize drought with high-resolution remote sensing and land-surface model data},
  journal = {Natural hazards and earth system sciences},
  year = {2022},
  doi = {10.5194/nhess-22-3461-2022},
  url = {https://doi.org/10.5194/nhess-22-3461-2022}
}

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