• Sorted by Date • Sorted by Last Name of First Author •
Ul Hasan, Mohd Sayeed, Rai, Abhishek Kumar, Momin, Abul Hasan, Khan, Mohammad Amir, Alfaisal, Faisal M., Alam, Shamshad, Al-sareji, Osamah J., and Majdi, Ali, 2025. Multi-dimensional scaling for space-time transformation to achieve sustainable planning and management of water resource under changing land use pattern. Scientific Reports, 15(1):1129, doi:10.1038/s41598-024-82207-y.
• from the NASA Astrophysics Data System • by the DOI System •
@ARTICLE{2025NatSR..15.1129U,
author = {{Ul Hasan}, Mohd Sayeed and {Rai}, Abhishek Kumar and {Momin}, Abul Hasan and {Khan}, Mohammad Amir and {Alfaisal}, Faisal M. and {Alam}, Shamshad and {Al-sareji}, Osamah J. and {Majdi}, Ali},
title = "{Multi-dimensional scaling for space-time transformation to achieve sustainable planning and management of water resource under changing land use pattern}",
journal = {Scientific Reports},
keywords = {ALSCAL, GIS, Innovative Trend Analysis, Multi-dimensional scaling, UPGMA, Environmental Sciences, Environmental Science and Management, Earth Sciences, Physical Geography and Environmental Geoscience},
year = 2025,
month = jan,
volume = {15},
number = {1},
eid = {1129},
pages = {1129},
abstract = "{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.}",
doi = {10.1038/s41598-024-82207-y},
adsurl = {https://ui.adsabs.harvard.edu/abs/2025NatSR..15.1129U},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}
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