Abstract

According to IPCC, Morocco is a highly vulnerable country to extreme climate events, especially droughts; this will affect different socioeconomic sectors, mainly the agriculture sector. Droughts are controlled by the variability of precipitation and evapotranspiration but also not neglecting the effect of land surface conditions such as land surface temperature. In this present study, the remote sense observations MODIS Normalized Difference Vegetation Index (NDVI) and CMSAF Land Surface Temperature (LST) were used for calculating the Vegetation Health Index (VHI). The main advantage of remote sensing products is that they are reasonably efficient in terms of temporal and spatial coverage, and they are useful for the monitoring and assessment of drought in the near real-time. Furthermore, ERA5 Reanalysis-based SPEI is calculated. The goal of this study is to assess the spatial and temporal patterns of drought, this study offers the composite of SPEI and VHI drought monitoring obtained by plotting maps and graphs to show the monthly and annual variability of drought for the period 2000–2015 over the whole of Morocco. This monitoring can be used as a near real-time warning system in a changing climate.

Highlights

  • A universal definition of drought is still missing, this makes the drought monitoring and the assessment of their severity more difficult [1,2]

  • The Normalized Difference Vegetation Index (NDVI) is a good indicator to assess the influence of drought estimated by Standardized Precipitation Evapotranspiration Index (SPEI) in the growing season of vegetation

  • The month of maximum NDVI is the month where the impact of thermal stress and vegetation is the strongest[2]. it is usually preferable by several studies to use Vegetation Health Index (VHI) rather than NDVI alone, owing to 99,7% of pixels have the maximum NDVI between October and June, after masking the Desert Region for its persistent very arid character

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Summary

Introduction

A universal definition of drought is still missing, this makes the drought monitoring and the assessment of their severity more difficult [1,2]. Performant drought assessment is needed to supply efficient measures to mitigate the negative impacts. The Palmer Drought Severity Index (PDSI) was a crucial first step to develop drought indices, it catches the precipitation and evapotranspiration into account.[7] It has been often used to quantify dryness and wetness conditions without regard to temporal scales [8]. The Standardized Precipitation Evapotranspiration Index considers the effect of evapotranspiration by incorporating the air temperature data, which makes it a better alternative to the PDSI and SPI.[10,11]

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