Retrospective analysis and version improvement of the satellite-based drought composite index. A semi-arid Tensift-Morocco application

This paper aims to offer an improved version of the new composite drought monitoring index (CDMI) and to test its applicability in the context of Tensift watershed in Morocco. A synergistic approach incorporating the remote sensing techniques, hydrometeorological data, simulated data and agricultura...

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Bibliographic Details
Published in:Geocarto international 2022-06, Vol.37 (11), p.3069-3090
Main Authors: Hanadé Houmma, Ismaguil, El Mansouri, Loubna, Hadria, Rachid, Emran, Anas, Chehbouni, Abdelghani
Format: Article
Language:English
Subjects:
Applied geology
CDMI
CDMIa_RF
drought index
Earth Sciences
Ecology, environment
ISMA
Life Sciences
Random Forest
Sciences of the Universe
Semi-arid
SPI-VHI
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Summary:This paper aims to offer an improved version of the new composite drought monitoring index (CDMI) and to test its applicability in the context of Tensift watershed in Morocco. A synergistic approach incorporating the remote sensing techniques, hydrometeorological data, simulated data and agricultural statistics was used for this purpose. After assessing the performance of CDMI, estimated Soil Moisture Anomaly Indicator (ISMA) was processed, validated and incorporated to the composite model. Random Forest algorithm was used to determine the weight of composite model components. Apart from comparative mapping, Pearson's correlation statistical analysis, linear regression and dependency tests were used to assess the performance of the improved composite model (CDMIa_RF). The result show that CDMIa_RF is better correlated with several indices such as: the Standardized Precipitation Index (SPI), (R 2 =0.74); Hydrological Drought Index (R 2 =0.70); grain productivity (R 2 =0.70), CDMI (R 2 =0.95), Vegetation Health Index (VHI), (R 2 =0.87), and Normalized Vegetation Supply Water Index (NVSWI), (R 2 = 0.85).
ISSN:1010-6049
1752-0762
DOI:10.1080/10106049.2020.1844314