A quarter century experience in soil salinity mapping and its contribution to sustainable soil management and food security in Morocco

• Published in: Geoderma Regional Vol. 34; p. e00695
• Main Authors: Silatsa, Francis B.T., Kebede, Fassil
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.09.2023
• Subjects: agricultural productivity; data collection; food security; geostatistics; Irrigated lands; irrigation; irrigation water; Morocco; prediction; salinity; Salinity build-up; Soil degradation; soil depth; Soil mapping; soil salinity; sustainable agricultural intensification; uncertainty; Morocco; Soil degradation; Irrigated lands; Morocco; Salinity build-up; Soil mapping
• ISSN: 2352-0094; 2352-0094
• DOI: 10.1016/j.geodrs.2023.e00695

Soil salinity is an acute human-induced plight in places where large scale irrigation activities are practiced. Tadla province of Morocco is typical of those areas and recent decades witnessed numerous efforts toward understanding and mapping the spatial distribution of soil salinity. However, the information remains scattered, though crucial for supporting the sustainable agricultural intensification to address food insecurity. Synthesizing existing information on soil salinity mapping activities conducted over recent decades and deriving lessons learnt is a formidable task. This review aims to inventory the soil salinity mapping studies, while assessing the techniques of data acquisition, analysis, and reporting the drivers of salinity loading in Tadla. Twenty-two soil salinity maps and their study reports were selected from literature search and considered in our assessment, depicting soil salinity mapping activities between 1999 and 2022. Results show that saturated soil pastes and electromagnetic induction methods were mostly used for EC estimation, and the mapping process was mostly with salinity index assessment using multispectral techniques and geostatistics. No study applying machine learning prediction algorithms such as random forest or artificial neural networks was identified. There is a high variability in sampling densities (2–38 sample per km2) and the prediction performances (R2 between 0.55 and 0.98 and RMSE between 0.08 and 2.35 dS m−1). The salinity expansion is controlled by the source and quality of irrigation water and affects about 72 ha of land yearly, impacting agricultural productivity and food security. There is also a silent salinity development with the soil depth, which remains little explored, along with a lack of information on prediction uncertainty. We identified future areas of investigation to consider toward an effective monitoring and management of soil salinity in Tadla and similar areas. •Soil salinity mapping has gain interest in previous decades in Tadla.•Soil salinity extends to about 72 ha yearly.•Uncertainty maps should be provided along with soil salinity map.•Soil salinity mapping supports food security achievement.•Irrigation water quality is the main factors of soil salinity loading.