Multi-dimensional scaling for space-time transformation to achieve sustainable planning and management of water resource under changing land use pattern

The land use transition plays an important role for terrestrial environmental services, which had a mixed impact of positive and negative on the groundwater and terrestrial water resource. The health of ecological systems and groundwater depends on the mapping and management of land use. The Ganga basin is one of the most densely populated and agriculture-intensive river systems in the South Asia and the world. The multi-temporal spatial database includes land use (ESA-CCI), satellite-based gravity anomaly (GRACE/GRACE-FO), and well log (CGWB) adopted in this study for assessment of the impact of land use transition on groundwater depth, groundwater drought, and terrestrial water storage. The methodology includes the computation of land use transition, trend magnitude by Sen's slope, Innovative Trend Analysis (ITA) for graphical visualization, clustering techniques employ to identify pattern & structure, and finally space-time transformation was assessed based on multi-dimensional scaling using Alternating Least Squares Scaling (ALSCAL). The land use transition over two decades shows an increase in forest (2.23%), wetland (2.2%), settlement (208.4%), bare area (3.18%), water (5.18%), and a decrease in agriculture (-1.16%), grassland (-4.5%), & vegetation (-2.8%). The non-parametric climatological trend of groundwater depth, drought, and terrestrial water loss was maximally observed during the post-monsoon season in the Ganga basin. The seasonal climatological trend statistics shows that, the upper Ganga and northern (left) of the Ganga basin shows an alarming rate of groundwater depletion, with increased in the severity of groundwater drought in near future with the loss in terrestrial water storage. The ITA shows the monotonic decreasing trend depicting loss of groundwater and terrestrial water resources. Bi-dimensional regression, ALSCAL shows that the model is efficient based on the input data having stress value and RSQ (proportion of variance) of 0.09 and 0.97 with excellent linear fit. The impact assessment of land use transition was obtained in low dimensional space showing that the conversion from sparse vegetation, agriculture, grassland, wetland and forest to settlement has the maximum impact on groundwater and TWSA loss, although the persistent settlement area is also responsible. The results are extremely useful for the policymakers, scientists, concern Govt. section, and local communities must work together to manage groundwater sustainably. Water resource management can also help to lessen the effects of climate change on groundwater and terrestrial water loss by focusing on the environmental, economic, social, and institutional dimensions of UN-SDG.