GIS AND STATISTICAL EVALUATION OF SOIL QUALITY OF SIDI YAHYA, GHARBPLAIN (MOROCCO)

Mbark  Lahmar; Najib El  Khodrani; Serine  Omrania; Houria  Dakak; Ahmed  Douaik; Hamza  Iaaich; Hasna  Yachou; Ahmed  Ghanimi; Rachid  Moussadek; Mohamed  Mekkaoui; Abdelmjid  Zouahri

doi:10.18006/2021.9(6).881.893

Authors

Mbark Lahmar Laboratory of Spectroscopy, Molecular Modeling, Materials, Nanomaterials, Waters and Environment, CERNE2D, Faculty of Sciences, Mohammed 5 University, Rabat, Morocco
Najib El Khodrani Research Unit on Environment and Natural Resources Conservation, Regional Center of Rabat, National Institute of Agricultural Research (INRA), Rabat, Morocco
Serine Omrania Laboratory of Spectroscopy, Molecular Modeling, Materials, Nanomaterials, Waters and Environment, CERNE2D, Faculty of Sciences, Mohammed 5 University, Rabat, Morocco
Houria Dakak Research Unit on Environment and Natural Resources Conservation, Regional Center of Rabat, National Institute of Agricultural Research (INRA), Rabat, Morocco
Ahmed Douaik Research Unit on Environment and Natural Resources Conservation, Regional Center of Rabat, National Institute of Agricultural Research (INRA), Rabat, Morocco
Hamza Iaaich Research Unit on Environment and Natural Resources Conservation, Regional Center of Rabat, National Institute of Agricultural Research (INRA), Rabat, Morocco
Hasna Yachou Research Unit on Environment and Natural Resources Conservation, Regional Center of Rabat, National Institute of Agricultural Research (INRA), Rabat, Morocco
Ahmed Ghanimi Laboratory of Materials, Nanotechnologies and Environment, Faculty of Sciences, Mohammed 5 University, Rabat, Morocco
Rachid Moussadek International Center for Agricultural Research in the Dry Areas (ICARDA), Rabat Institutes, North-Africa Platform, P.O. Box 6299, 10112 Rabat, Morocco
Mohamed Mekkaoui Laboratory of Spectroscopy, Molecular Modeling, Materials, Nanomaterials, Waters and Environment, CERNE2D, Faculty of Sciences, Mohammed 5 University, Rabat, Morocco
Abdelmjid Zouahri Research Unit on Environment and Natural Resources Conservation, Regional Center of Rabat, National Institute of Agricultural Research (INRA), Rabat, Morocco

DOI:

https://doi.org/10.18006/2021.9(6).881.893

Keywords:

Gharb plain, GIS, Multivariate analysis, SidiYahya perimeter, Soil quality, Spatial interpolation

Abstract

The study of soil quality in irrigated areas is necessary to evaluate the sustainability of the agricultural production system. Indeed, the assessment of this quality is based on the physicochemical and biological characterization of soil parameters, as well as the knowledge of their spatial distribution and their evolution over time. This work aims to make a diagnosis of the current situation of soil quality of SidiYahya in the Gharb plain, Morocco. For this, sampling was carried out from 33 sites distributed over the studied plain during 2019. In this study, different soil properties including specifically texture, pH, electrical conductivity (EC), organic matter (OM), phosphorus (P₂O₅), and potassium (K₂O) were measured while exchangeable sodium percentage (ESP) was calculated using the standard formula. Based on the observed soil properties a map was prepared by using a geographic information system (GIS), which was based specifically on the inverse distance weighted (IDW) spatial interpolation method. Data were processed using different statistical tools like descriptive statistics, correlation, and principal component analysis (PCA). Results of the study revealed that 70% of the soils have a heavy clayey texture with a predominance of vertisols (55%). Further, the study area soil is mainly alkaline (70%), poor in organic matter (61%) and phosphorus (52%), while very rich in potassium (70%), and non-saline (88%) contents. Soil pH was reported to be the least variable whereas sand, phosphorus, and salinity were the highest variable. IDW allowed mapping the soil properties by moving from punctual information to whole extent information. Furthermore, correlations were found between various soil properties by using PCA, 3 principal components (PCs) were able to extract 76% of the information from the 9 initial soil properties. Collected soil samples were grouped into 3 groups, based on their scores on the 3 PCs. Based on these two kinds of information, delineation of management zones can be established for a site-specific supply of agricultural inputs leading to better management of soil and water resources for securing their sustainable use.