Assessing the environmental factors affecting the sustainability of Aini Falaj system

• Published in: PloS one 2024-05, Vol.19 (5), p.e0301832-e0301832
• Main Author: Al-Kindi, Khalifa M
• Format: Article
• Language: English
• Subjects: Agriculture; Analysis; Autocorrelation; Biology and Life Sciences; Climate change; Clustering; Collinearity; Computer and Information Sciences; Computer software industry; Conservation; Conservation of Natural Resources; Datasets; Distribution patterns; Earth Sciences; Ecology and Environmental Sciences; Ecosystem; Environmental assessment; Environmental conditions; Environmental factors; Environmental sustainability; Evaporation; Fisheries; Geographic information systems; Geography; Geospatial data; Groundwater; High density; Independent variables; Inflation (Finance); Irrigation; Land use; Land use management; Land use planning; Machine learning; Multivariate analysis; Oman; Physical Sciences; Precipitation; Radiation; Regression analysis; Remote sensing; Repair & maintenance; Solar radiation; Spatial Analysis; Spatial distribution; Strategic planning (Business); Sustainability; Topography; United States; Water resources; Water shortages; Water supply; Wetness index
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0301832

This study investigates the spatial distribution patterns and environmental factors influencing the Aini Falaj system in a specific study area. The research findings are presented through the lens of the following four categories: collinearity diagnostics, spatial autocorrelation analysis, kernel density (KD) findings, and multivariate geographically weighted regression (MGWR) analysis. The collinearity diagnostics were applied to examine the interrelationships among 18 independent environmental variables. The results indicate the absence of significant multicollinearity concerns, with most variables showing values below the critical threshold of five for variance inflation factors (VIFs). The selected variables indicate minimal intercorrelation, suggesting that researchers should be confident utilizing them in subsequent modelling or regression analyses. A spatial autocorrelation analysis using Moran's Index revealed positive spatial autocorrelation and significant clustering patterns in the distribution of live and non-functional Aini Falajs. High concentrations of live or dead Falajs tended to be surrounded by neighbouring areas with similar characteristics. These findings provide insights into the ecological preferences and habitat associations of Aini Falajs, thereby aiding conservation strategies and targeted studies. The kernel density (KD) analysis depicted distribution patterns of live and dry Aini Falajs through hotspots and cold spots. Specific regions exhibited high-density areas of live Falajs, indicating favourable environmental conditions or historical factors contributing to their concentrated distribution. Identifying these high-density zones can enhance our understanding of the spatial patterns and potential factors influencing the prevalence and sustainability of Aini Falajs. The multivariate geographically weighted regression (MGWR) models revealed strong associations between the live or dead status of Aini Falajs and environmental factors. The precipitation, topographic wetness index (TWI), aspect and slope exerted positive impacts on the live status, while evaporation, solar radiation, distance to drains and drain density exerted negative influences. Similar associations were observed for the dead status, emphasising the importance of controlling evaporation, shading mechanisms, proper drainage planning and sustainable land-use practices. This study provides valuable insights into the spatial distributions and factors influencing the