RESUMEN
Groundwater resources are enormously affected by land use land cover (LULC) dynamics caused by increasing urbanisation, agricultural and household discharge as a result of global population growth. This study investigates the impact of decadal LULC changes in groundwater quality, human and ecological health from 2009 to 2021 in a diverse landscape, West Bengal, India. Using groundwater quality data from 479 wells in 2009 and 734 well in 2021, a recently proposed Water Pollution Index (WPI) was computed, and its geospatial distribution by a machine learning-based 'Empirical Bayesian Kriging' (EBK) tool manifested a decline in water quality since the number of excellent water category decreased from 30.5% to 28% and polluted water increased from 44% to 45%. ANOVA and Friedman tests revealed statistically significant differences (p < 0.0001) in year-wise water quality parameters as well as group comparisons for both years. Landsat 7 and 8 satellite images were used to classify the LULC types applying machine learning tools for both years, and were coupled with response surface methodology (RSM) for the first time, which revealed that the alteration of groundwater quality were attributed to LULC changes, e.g. WPI showed a positive correlation with built-up areas, village-vegetation cover, agricultural lands, and a negative correlation with surface water, barren lands, and forest cover. Expansion in built-up areas by 0.7%, and village-vegetation orchards by 2.3%, accompanied by a reduction in surface water coverage by 0.6%, and 2.4% in croplands caused a 1.5% drop in excellent water and 1% increase in polluted water category. However, ecological risks through the ecological risk index (ERI) exhibited a lower risk in 2021 attributed to reduced high-risk potential zones. This study highlights the potentiality in linking LULC and water quality changes using some advanced statistical tools like GIS and RSM for better management of water quality and landscape ecology.
Asunto(s)
Sistemas de Información Geográfica , Agua Subterránea , Aprendizaje Automático , Calidad del Agua , Agua Subterránea/análisis , India , Monitoreo del Ambiente/métodos , Teorema de Bayes , Humanos , AgriculturaRESUMEN
The Tanour spring is one of the several karst springs located in the northern part of Jordan. Water samples from the Tanour spring and precipitation were collected in the area of Ajloun in NW Jordan for the analysis of stable oxygen and hydrogen isotopes to evaluate the spring response to precipitation events. Rainwater and snow samples were collected from different elevations during winters of 2013-2014 and 2014-2015. In addition, spring samples were collected between December 2014 and March 2015. δ(18)O values in rainwater vary from -3.26 to -17.34 (average: -7.84 ± 3.23 ), while δ(2)H values range between -4.4 and -110.4 (average: -35.7 ± 25.0 ). Deuterium excess ranges from 17.8 to 34.1 (average: 27.1 ± 4.0 ). The Local Meteoric Water Line for the study area was calculated to be δ(2)H = 7.66*δ(18)O + 24.43 (R(2) = 0.98). Pre-event spring discharge showed variation in δ(18)O (range -6.29 to -7.17 ; average -6.58 ± 0.19 ) and δ(2)H values (range -28.8 to -32.7 ; average: -30.5 ± 1.0 ). In contrast, δ(18)O and δ(2)H rapidly changed to more negative values during rainfall and snowmelt events and persisted for several days before returning to background values. Spring water temperature, spring discharge, and turbidity followed the trend in isotopic composition during and after the precipitation events. The rapid change in the isotopic composition, spring discharge, water temperature, and turbidity in response to recharge events is related to fast water travel times and low storage capacity in the conduit system of the karst aquifer. Based on the changes in the isotopic composition of spring water after the precipitation events, the water travel time in the aquifer is in the order of 5-11 days.