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Remote Sensing
Volume 16
Issue 18
10.3390/rs16183398
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This is an early access version, the complete PDF, HTML, and XML versions will be available soon.
Article

Assessing the Impact of Agricultural Practices and Urban Expansion on Drought Dynamics Using a Multi-Drought Index Application Implemented in Google Earth Engine: A Case Study of the Oum Er-Rbia Watershed, Morocco

by
Imane Serbouti
1,
Jérôme Chenal
1,2,
Biswajeet Pradhan
3,*,
El Bachir Diop
1,
Rida Azmi
1,
Seyid Abdellahi Ebnou Abdem
1,
Meriem Adraoui
1,
Mohammed Hlal
1 and
Mariem Bounabi
1
1
Center of Urban Systems (CUS), Mohammed VI Polytechnic University (UM6P), Ben Guerir 43150, Morocco
2
Urban and Regional Planning Community (CEAT), Ecole Polytechnique Fédérale de Lausanne (EPFL), 1015 Lausanne, Switzerland
3
Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Civil and Environmental Engineering, Faculty of Engineering and Information Technology, University of Technology Sydney, Ultimo, NSW 2007, Australia
*
Author to whom correspondence should be addressed.
Remote Sens. 2024, 16(18), 3398; https://doi.org/10.3390/rs16183398
Submission received: 10 July 2024 / Revised: 8 September 2024 / Accepted: 9 September 2024 / Published: 12 September 2024
(This article belongs to the Special Issue Application of Remote Sensing to Flood and Drought Analysis, Monitoring and Risk Management)
Versions Notes

Abstract

Drought monitoring is a critical environmental challenge, particularly in regions where irrigated agricultural intensification and urban expansion pressure water resources. This study assesses the impact of these activities on drought dynamics in Morocco’s Oum Er-Rbia (OER) watershed from 2002 to 2022, using the newly developed Watershed Integrated Multi-Drought Index (WIMDI), through Google Earth Engine (GEE). WIMDI integrates several drought indices, including SMCI, ESI, VCI, TVDI, SWI, PCI, and SVI, via a localized weighted averaging model (LOWA). Statistical validation against various drought-type indices including SPI, SDI, SEDI, and SMCI showed WIMDI’s strong correlations (r-values up to 0.805) and lower RMSE, indicating superior accuracy. Spatiotemporal validation against aggregated drought indices such as VHI, VDSI, and SDCI, along with time-series analysis, confirmed WIMDI’s robustness in capturing drought variability across the OER watershed. These results highlight WIMDI’s potential as a reliable tool for effective drought monitoring and management across diverse ecosystems and climates.
Keywords: drought monitoring; Google Earth Engine; watershed integrated multi-drought index; LOWA; Oum Er Rbia watershed; irrigated agricultural intensification; urban expansion drought monitoring; Google Earth Engine; watershed integrated multi-drought index; LOWA; Oum Er Rbia watershed; irrigated agricultural intensification; urban expansion

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MDPI and ACS Style

Serbouti, I.; Chenal, J.; Pradhan, B.; Diop, E.B.; Azmi, R.; Abdem, S.A.E.; Adraoui, M.; Hlal, M.; Bounabi, M. Assessing the Impact of Agricultural Practices and Urban Expansion on Drought Dynamics Using a Multi-Drought Index Application Implemented in Google Earth Engine: A Case Study of the Oum Er-Rbia Watershed, Morocco. Remote Sens. 2024, 16, 3398. https://doi.org/10.3390/rs16183398

AMA Style

Serbouti I, Chenal J, Pradhan B, Diop EB, Azmi R, Abdem SAE, Adraoui M, Hlal M, Bounabi M. Assessing the Impact of Agricultural Practices and Urban Expansion on Drought Dynamics Using a Multi-Drought Index Application Implemented in Google Earth Engine: A Case Study of the Oum Er-Rbia Watershed, Morocco. Remote Sensing. 2024; 16(18):3398. https://doi.org/10.3390/rs16183398

Chicago/Turabian Style

Serbouti, Imane, Jérôme Chenal, Biswajeet Pradhan, El Bachir Diop, Rida Azmi, Seyid Abdellahi Ebnou Abdem, Meriem Adraoui, Mohammed Hlal, and Mariem Bounabi. 2024. "Assessing the Impact of Agricultural Practices and Urban Expansion on Drought Dynamics Using a Multi-Drought Index Application Implemented in Google Earth Engine: A Case Study of the Oum Er-Rbia Watershed, Morocco" Remote Sensing 16, no. 18: 3398. https://doi.org/10.3390/rs16183398

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