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Combined use of Sentinel-2 and Landsat-8 to monitor water surface area and evaluated drought risk severity using Google Earth Engine

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Abstract

Drought is often one of environmental disasters replicated in Morocco. It is the result of climate variations and human activity that has affected different sectors (water resources, agriculture, ecology, and socio-economy, etc.). The normalized water differential index (NDWI) is a type of spectral water analysis based on one green band and one NIR-band representation. The NDWI was effectively used to gather information around water bodies from remote sensing data. The study area for this work is the Idriss 1st Dam in northeast Morocco, situated downstream from the drainage of the Inaouene River. This basin is mostly affected by drought risk, which will evaluate by calculating NDWI index of image time series, based on Sentinel-2 (2015 to 2020), Landsat-8 (2013 to 2020) and Google Earth Engine (2013 to 2020) as a data processing tool. For the study area drought monitoring, DrinC software is used to calculate the Standardized Precipitation Index (SPI) and the Stream-flow Drought Index (SDI).The result of this paper is mapping water bodies of Idriss 1st Dam, and evaluated drought risk severity and frequency with a high precision.

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Abbreviations

NDWI:

Normalized Difference Water Index

SPI:

Standardized Precipitation Index

SDI:

Streamflow Drought Index

NIR-band:

Near Infrared Band

PDSI:

Palmer Drought Intensity Index

RAI:

Rainfall Anomaly Index

SAI:

Standardized Anomaly Index

SMDI:

Soil Moisture Drought Index

CMI:

Crop Moisture Index

NDVI:

Normalized Difference Vegetation Index

TCI:

Temperature Condition Index

VCI:

Vegetation Condition Index

VHI:

Vegetation Heath Index

SVI:

Standardized Vegetation Index

GIS:

Geographic Information System

SWIR:

Short-Wave Infrared

RS:

Remote Sensing

N:

North

W:

West

m:

Meter

mm:

Millimeter

AHBS:

Sebou Hydraulic Basin Agency

GEE:

Google Earth Engine

OLI:

Operational Land Imager

TIRS:

Thermal Infrared Sensor

MSI:

Multispectral Instruments

UTM:

Universal Transversal Mercator

WGS84:

World Geodetic System 84

SNAP:

Sentinel Application Platform

GUI:

Graphical User Interface

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Acknowledgements

The Authors extend their thanks to the Deanship of Scientific Research at King Khalid University for funding this work through the large research groups under grant number RGP. 2/173/42.

Funding

This research work was supported by the Deanship of Scientific Research at King Khalid University under Grant number RGP. 2/173/42.

Author information

Authors and Affiliations

  1. Department of Geomorphology and Geomatics, Scientific Institute, Mohammed V University in Rabat, Avenue Ibn Batouta, P.O. Box 703, 10106, Rabat, Morocco

    Brahim Benzougagh, Bouchta El Fellah & Mohamed Mastere

  2. Water Resources and Applied Mathematics Research Lab, Nagpur, 440027, India

    Sarita Gajbhiye Meshram

  3. Department of Geology, Faculty of Sciences Dhar El Mahraz, Natural Resource Laboratory Environments and Sustainable Developments (RNE2D), Sidi Mohamed Ben Abdellah University, Fez, Morocco

    Abdallah Dridri

  4. Department of Geology, Faculty of Sciences, Laboratory: Environmental Geology and Natural Resources, Abdelmalek Essaâdi University in Tetouan, Tetouan, Morocco

    Driss Sadkaoui

  5. Department of Geology, Faculty of Sciences, Water Sciences and Environment Engineering Team, University Moulay Ismail, Meknes, Morocco

    Khalid Mimich

  6. Department of Civil Engineering, College of Engineering, King Khalid University, Abha, 61421, Saudi Arabia

    Khaled Mohamed Khedher

  7. Department of Civil Engineering, High Institute of Technological Studies, Mrezgua University Campus, 8000, Nabeul, Tunisia

    Khaled Mohamed Khedher

Authors
  1. Brahim Benzougagh
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  2. Sarita Gajbhiye Meshram
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  3. Bouchta El Fellah
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  6. Driss Sadkaoui
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  8. Khaled Mohamed Khedher
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Correspondence to Sarita Gajbhiye Meshram.

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Communicated by: H. Babaie

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Benzougagh, B., Meshram, S.G., El Fellah, B. et al. Combined use of Sentinel-2 and Landsat-8 to monitor water surface area and evaluated drought risk severity using Google Earth Engine. Earth Sci Inform 15, 929–940 (2022). https://doi.org/10.1007/s12145-021-00761-9

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