Multivariate Analysis for Assessing Irrigation Water Quality: A Case Study of the Bahr Mouise Canal, Eastern Nile Delta

Abstract

Water scarcity and suitable irrigation water management in arid regions represent tangible challenges for sustainable agriculture. The current study aimed to apply multivariate analysis and to develop a simplified water quality assessment using principal component analysis (PCA) and the agglomerative hierarchical clustering (AHC) technique to assess the water quality of the Bahr Mouise canal in El-Sharkia Governorate, Egypt. The proposed methods depended on the monitored water chemical composition (e.g., pH, water electrical conductivity (ECiw), Ca2+, Mg2+, Na+, K+, HCO3−, Cl−, and SO42−) during 2019. Based on the supervised classification of satellite images (Landsat 8 Operational Land Imager (OLI)), the distinguished land use/land cover types around the Bahr Mouise canal were agriculture, urban, and water bodies, while the dominating land use was agriculture. The water quality of the Bahr Mouise canal was classified into two classes based on the application of the irrigation water quality index (IWQI), while the water quality was classified into three classes using the PCA and AHC methods. Temporal variations in water quality were investigated, where the water qualities in winter, autumn, and spring (January, February, March, April, November, and December) were classified as class I (no restrictions) based on IWQI application, and the water salinity, sodicity, and/or alkalinity did not represent limiting factors for irrigation water quality. On the other hand, in the summer season (May, June, July, August, and October), the irrigation water was classified as class II (low restrictions); therefore, irrigation processes during summer may lead to an increase in the alkalinity hazard. The PCA classifications were compared with the IWQI results; the PCA classifications had similar assessment results during the year, except in September, while the water quality was assigned to class II using the PCA method and class I by applying the IWQI. Furthermore, the normalized difference vegetation index (NDVI) around the Bahr Mouise canal over eight months and climatic data assisted in explaining the fluctuations in water quality during 2019 as a result of changing the crop season and agriculture management. Assessments of water quality help to conserve soil, reduce degradation risk, and support decision makers in order to obtain sustainable agriculture, especially under water irrigation scarcity and the limited agricultural land in such an arid region.

Modeling Land Suitability for Rice Crop Using Remote Sensing and Soil Quality Indicators: The Case Study of the Nile Delta

“…The results indicate that there was a correlation of crop production with the degree of soil suitability, where the soils located at south of the study area were characterized by a high degree of suitability for rice, and this was associated with soil fertility condition in those areas, on one hand, and improvement of physical and chemical properties on the other hand. These outputs are consistent with [46][47][48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63]. Meanwhile, for the soils that were classified by low suitability for the rice crop, located at north of the study area, where land degradation factors are active such as salinity, alkalinity and high water table, among others, this was reflected by the NDVI values during the crop growth season, which is consistent with [63,64,[79][80][81].…”

“…These units occupy the northern parts of Nile delta where located south are the lakes such as El Manzala, El Burolous, Edko and Marriott Lakes [59]. The salinity of soils varies between slight to high saline, where the high values of soil salinity in the study area were noted in sand sheets, which are attributed to the effect of the Mediterranean Sea water; this corresponds to the general pattern of the northern delta, where most of the soil is characterized by high soil salinity [60][61][62][63][64]. The rising of the water table level may be due to bad drainage and to the leakage from neighboring channels [65,66].…”

Quantitative Evaluation of Soil Quality Using Principal Component Analysis: The Case Study of El-Fayoum Depression Egypt

“…Figure 7 shows the spatial distribution maps of soil properties; pH varies from 7.06 to 9.28, and soil ECe ranges from low to high soil salinity (0.88-21 dS/m). This difference in soil salinity is a result of the activity of land degradation processes in the Fayoum depression, where inadequate drainage conditions reduce salinity, which is also a common feature in the soils of the North Delta [72,73]. The results show that the study area has low soil OM contents, ranging between 0.4% and 1%.…”

Micro-Clustering and Rank-Learning Profiling of a Small Water-Quality Multi-Index Dataset to Improve a Recycling Process

“…It will be shown how to reduce the imposing multi-index dataset to a single clustered nominal response. This is a new concept and it furnishes an alternative to extracting water quality classification information from small data [49][50][51][52][53][54][55][56]. This would quickly refashion the problem to the naiver non-linear saturated but 'unreplicated' form.…”