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Forest resources play a vital role in supporting the livelihoods of rural communities residing in forest-rich areas. In India, a forest-rich country, a significant proportion of non-timber forest products (NTFPs) is consumed locally, supporting numerous rural communities relying on forests for essential resources, such as firewood, timber, and NTFPs. This study focuses on two forest-dominant districts in West Bengal of India, namely, Jhargram District and Paschim Medinipur District. Furthermore, this study aims to enhance the understanding of forest-dependent communities by comparing the standard of living among different village classes. Thus, we categorized villages into three classes based on the distance from home to forests, including inner villages, fringe villages, and outer villages. Through focus group discussions and household surveys, we explored the sources of local economy, income sources of household, and reasons for economic diversification in different village classes. The study findings confirm that substantial variations existed in the income sources and the standard of living in these villages. Forest income varied dramatically among the three village classes, with inner villages having greater forest income than fringe villages and outer villages. Meanwhile, households in outer villages depended on forests and engaged in diverse economic activities for their livelihoods. Compared with inner and fringe villages, households in outer villages derived a significant portion of their income from livestock. This discrepancy can be attributed to challenges, such as inadequate transportation, communication, and underdeveloped market chains in inner villages. Moreover, these findings emphasize the need to develop sustainable forest management practices, create alternative income-generation opportunities, and improve infrastructure and market access in inner villages, as well as promote economic diversification in outer villages. Through targeted policy measures, these forest-rich regions can achieve improved livelihoods, enhanced standard of living, and increased resilience for their communities.

In the recent decades, many worlds' large rivers have been exceptionally modified by human interference. The principal objective of this study is to investigate the causes and consequences of decay of river Jamuna (distributary of river Bhagirathi-Hooghly). The entire investigation was conducted by the data of historical maps like Rennel's map of Bengal, Hunter's map, digital version of US army map, landsat satellite imageries (1980-MSS, 1990-TM, 2000-TM, 2010-ETM+ and 2020-OLI) and fluvio-hydrological study. Maximum likelihood classification algorithm was used to delineate the land use and land cover classes and Kappa based accuracy assessment indices were also used for the validation. There is no scientific work on this historically important river and afterward, millions of people are also underprivileged from this river ecosystem services due to severe degeneration. In this milieu, it is a genuine research gap. Novelty of the work is exposed the authentic causes of river decay and anthropogenic stressors. Result showed that the average width of river Jamuna has been significantly decreased whereas maximum average width of the channel was recorded in the year 1956 (319.81 m) and the present channel is flowing comparatively within narrow path (69.27 m). Rate of siltation (average rate of siltation 0.23 m/year) on channel bed has been increased due to impacts of channelization. Channel bed, natural levee and proximity floodplain have been encroached by large scale human intervention. LULC patterns showed that the urban built-up area is rapidly amplified from 2000 (22.26%) to 2020 (31.50%) whereas, agricultural and swampy land turned into built up area. Off-take of Jamuna is completely detached from the parent river Bhagirathi-Hooghly in the early 1956 and gradual anthropogenic interferences within river corridor accelerate river decaying processes. River restoration is highly required for sustainable river ecosystem health management and environmental development. Some management strategies have been recommended such as reconnecting of river Jamuna with Bhagirathi-Hooghly, dredging, decommissioning of culvert and sluice gate, cleaning of fishing pool and water hyacinth and sustainable land-use planning.

Study region: The Damodar Fan Delta, West Bengal, India. Study focus: The depletion of groundwater resources worldwide is escalating due to its profuse demand for drinking, irrigation, domestic, and industrial uses. Overexploitation of groundwater in a subtropical fan delta region with rapid population growth like the Damodar Fan Delta in India is of great concern for sustainable mapping, monitoring, and managing water resources. During 2000–2020, the Damodar Fan Delta portrayed an increase in semi-critical community development blocks, implying a decline in groundwater level. To this end, the present study intends to show the groundwater level dynamics including its future prediction, using machine learning algorithms based on the seasonal groundwater level data from 2013‐14 to 2020‐21 for 30 wells. New hydrological insights for the region: Post-monsoon kharif and rabi depicted a higher fall rate in the groundwater level compared to the pre-monsoon and monsoon periods. Future predictions using the best-fit model indicated an increasing trend in the depth of groundwater levels in the future (2025–26). The extreme gradient boost regressor appeared to be the best model, while the decision tree regressor was the worst performer. The major controlling factors of groundwater level dynamics were decreasing rainfall and increasing groundwater abstraction due to population growth and increased demand for irrigation, domestic, and industrial water.

Landslides are the indicator of slope instability particularly in mountain terrain and causing different types of reimbursements and threats of life and property. The Himalayan terrains are highly susceptible to different natural hazards as well as disasters particularly land failure activities mainly due to inherent tectonic activities which further enhanced by various Neo-tectonic and Neolithic activities. This scientific study provides an enhanced framework for the assessment of proper and precise landslide susceptibility in the two districts of Arunachal Pradesh (Tawang and West Kameng) considering both physical and anthropogenic factors and various machine learning models (SVM, AdaBoost and XGBoost). At first, landslide inventory maps were developed based on previous landslide events. Here, 70% of the data were randomly selected for training and remaining was used for validation and optimization of the models using statistical implications and validation assessment methods. The result showed that the high and very high landslide susceptible areas are mainly concentrated in the middle portion along the Bhalukpong-Bomdia road section. Based on the AUC value and other statistical indicators it has been observed that AdaBoost is the most efficient model here (AUC = 0.92). AUC values of SVM and XGBoost are 0.85 and 0.89 respectively. AdaBoost model identifies that very low susceptibility class occupies 60.22% area and very high landslide susceptibility class occupies 15.51% area and it will be considered as more encouraging method for landslide susceptibility determination in this kind of cases for better accurateness. This high accuracy susceptibility map positively helps during the execution of various developmental projects.

Abstract The Sundarban mangrove or tidal influenced natural ecosystem is extremely productive and providing multiple goods and services to millions of people. In the last few decades, the quality and quantity of mangrove ecosystem are being deteriorated. The main objectives of this current research are (i) to investigate the ecosystem service values (ESVs) using a time series satellite data (1975, 2000 and 2020) and different unit values (ii) to analyze the dynamic pattern of carbon sequestration through InVEST model and (iii) determination of ESVs change hotspots by Getis-Ord Gi* method. Here, mangrove forest has the highest ecosystem service value and highest carbon sinker. The total loss of ESVs was estimated 3310.79 million USD during last 45 years in Sundarban Biosphere Reserve (SBR) due to high natural and anthropogenic adversities. InVEST model also revealed that the total static carbon storage over the study area was 48.87, 46.65 and 43.33 Tg for the year 1975, 2000 and 2020 respectively. Total 6313944 mg/6.31Tg loss of carbon has been observed in the case of mangrove forest during the overall study period (1975–2020). So, illegal human encroachment should be strictly (through law and regulations) restricted within Sundarban mangrove ecosystem for the benefits of people.

Abstract Increased consumption of water resource due to rapid growth of population has certainly reduced the groundwater storage beneath the earth which leads certain challenges to human being in recent time. For optimal management of this vital resource, exploration of groundwater potential zone (GWPZ) has become essential. We have applied Analytical Hierarchy Process (AHP), Frequency Ratio (FR) and two machine learning techniques specifically Random Forest (RF) and Naïve Bayes (NB) here to delineate GWPZ in Gandheswari River Basin in Chota Nagpur Plateau, India. To achieve the goal of the study, twelve factors that determine occurrence of groundwater have been selected for inter-thematic correlations and overlaid with location of wells. These factors include elevation, drainage density, slope, lithology, geomorphology, topographical wetness index (TWI), distance from the river, rainfall, lineament density, Normalized Difference Vegetation Index (NDVI), soil, and Land use and Land cover (LULC). A total 170 points including 85 in well site and 85 in non-well site have been selected randomly and allocated into two parts: training and testing at the share of 70:30. The implemented methods have significantly provided five GWPZs specifically Very Good (VG), Good (G), Moderate (M), Poor (P) and Very Poor (VP) with high and acceptable accuracy. The study also finds that geomorphology, slope, rainfall and elevation have greater importance in shaping GWPZs than LULC, NDVI, etc. Model performance has been tested with receiver operator characteristics (ROC), Accuracy (ACC), Kappa Coefficient, MAE, RMSE, etc., methods. Area under curve (AUC) in ROC curve has revealed that accuracy level of AHP, FR, RF and NB is 78.8%, 81%, 85.3% and 85.5, respectively. The machine learning techniques coupled with AHP and FR unveil effective delineation of groundwater potential area in said river basin which by genetically offers low primary porosity due to lithological constrains. Therefore, the study can be helpful in watershed management and identifying appropriate location wells in future.

Abstract Groundwater is a vital and purest form of natural resource. In the recent years, various anthropogenic causes threat its natural quality. Therefore, its suitability for drinking, irrigation and other purposes make doubtful conditions of human well-being, especially in developing countries. In this present study, groundwater quality was evaluated for drinking, irrigation and human health hazard purposes particularly in Chotanagpur plateau fringe of India. In total, 58 water samples were collected from different locations in pre-monsoon (February–March 2020) and post-monsoon (October–November 2020) seasons to delineate seasonal variation of groundwater quality according to as reported by WHO (WHO guidelines for drinking-water quality, World Health Organization, Geneva, 2011) guidelines. Groundwater Quality Index (GWQI) and Heavy metal Pollution Index (HPI) have been applied to assess the suitability of drinking purposes. Irrigation parameters (SAR, SSP, MAR, PI, KR) showed the significant deterioration of water quality in pre-monsoon than post-monsoon period. Major cations (such as sodium, calcium) and major anions (such as bicarbonate, nitrate and fluoride) exceeded their standard limit in both the seasons. Non-carcinogenic health risk is found due to heavy metal contamination through drinking water. The health risk index was higher for children in comparison with adults. This research finding can definitely help to planners and administrators for immediate decision making regarding public health (for groundwater quality improvement).

Abstract Scarcity of groundwater is a severe problem in this region due to over exploitation of groundwater from unconfined hard rock aquifers. The main objectives of this study are to analyse the spatiotemporal variability and fluctuation of groundwater table and to predict the location of groundwater depression pockets. Total 21 consecutive years (1996–2017) groundwater monitoring well data (pre- and post-monsoon) have been collected from CGWB, Government of India. The nonparametric Mann–Kendall trend analysis and standardized precipitation index (SPI) have been applied to detect the trend of groundwater level and rainfall variability, respectively. Exponential smoothing has also been fitted for future prediction. The pre- and post-monsoon results (1996–2017) showed that around 77% (22 stations) and 78% (23) monitoring stations were indicating declining trend of groundwater table at the rate of −0.006 to −0.205 m/year and −0.005 to −0.192 m/year, respectively. Similarly, future (2040) groundwater depression result predicted that around 75% (21) stations, the groundwater table will be depleted above 5 m during pre-monsoon while about 53% (16 stations) monitoring wells, the groundwater table will be fallen above 5 m during post-monsoon. Consequently, around 52% (15) and 50% (14) stations are being faced groundwater drought in the recurrent interval of above 2 years during pre-monsoon and post-monsoon, respectively. Driving factors of water table depletion are huge withdrawal of groundwater for dry farming and reduction of recharge areas due to rapid land use modification. The uniqueness of this study exhibits the nature of declining trend of groundwater table and identification of depression pockets.

Abstract Shortage of potable water is a global problem, and this problem can be met by searching new areas where groundwater is available. GIS is an effective and necessary tool to identify groundwater potential zones in an area. In the present study, groundwater potential zones (GWPZs) were identified in the Kangsabati River basin of east India having an area of about 6488 km2 using multi-criteria decision analysis (MCDA) and analytical hierarchy process (AHP). The criteria like geology, geomorphology, elevation, slope, drainage, lineament, curvature, topographic wetness, land use/land cover, and soil were extracted from satellite data and the weights for each parameter and its sub-parameters were assigned through analytical hierarchy process based on their respective relevance as influencing factors for groundwater recharge. Very low, low, moderate, high, and very high groundwater potentiality represent 28.93%, 30.56%, 19.75%, 14.62%, and 6.11% area, respectively. The low-lying flat plains of the southeastern section, as well as the centrally located dam, are ideal for groundwater recharge, while the upland plain of the northwestern part, with its hard rock terrain, is less so. This outcome has been verified using pre-monsoon and post-monsoon groundwater depth data, indicating that the strategy is most appropriate for this region. Thus, the groundwater potential zone maps remain very useful for conducting extensive ground-based hydrogeological studies that facilitate the identification of suitable bore well/dug well sites.

Gully erosion is one of the advanced forms of water erosion. Identifying the effective factors and gully erosion predicting is one of the important tools to control and manage such phenomenon. The main purpose of this study is to evaluate the effect of four different resampling algorithms including cross-validation (5-fold and 10-fold) and bootstrapping (Bootstrap and Optimism bootstrap) on boosted regression tree (BRT), support vector machine (SVM), and random forest (RF) models in spatial modeling and evaluation of head-cut gully erosion in Konduran watershed. For this purpose, based on an extensive field survey, the points of the head-cut of the gully erosion were identified first, and a map of the distribution of head-cut gully erosion in the study area was prepared. Then 18 variable identify and prepare as factors affecting the occurrence of head-cut gully erosion. To assess the efficiency of the models, receiver operating characteristics (ROC) and area under the curve (AUC) were used. The results of the assessment indicated that the use of resampling algorithms increases the efficiency of the models. The integrated optimism-bootstrap-BRT, optimism-bootstrap-SVM, and Optimism-Bootstrap-RF models with AUC 0.85, 0.823 and 0.89 respectively, outperformed the cross-validation 5fold (BRT, SVM, RF), Cross-validation 10fold (BRT, SVM, RF) and Bootstrap (BRT, SVM, RF) integrated algorithms.

Abstract The global economic activities were completely stopped during COVID-19 lockdown and continuous lockdown partially brought some positive effects for the health of the total environment. The multiple industries, cities, towns and rural people are completely depending on large tropical river Damodar (India) but in the last few decades the quality of the river water is being significantly deteriorated. The present study attempts to investigate the river water quality (RWQ) particularly for pre- lockdown, lockdown and unlock period. We considered 20 variables per sample of RWQ data and it was analyzed using novel Modified Water Quality Index (MWQI), Trophic State Index (TSI), Heavy Metal Index (HMI) and Potential Ecological Risk Index (RI). Principal component analysis (PCA) and Pearson’s correlation (r) analysis are applied to determine the influencing variables and relationship among the river pollutants. The results show that during lockdown 54.54% samples were brought significantly positive changes applying MWQI. During lockdown, HMI ranged from 33.96 to 117.33 with 27.27% good water quality which shows the low ecological risk of aquatic ecosystem due to low mixing of toxic metals in the river water. Lockdown effects brought river water to oligotrophic/meso-eutrophic condition from eutrophic/hyper-eutrophic stage. Rejuvenation of river health during lockdown offers ample scope to policymakers, administrators and environmentalists for restoration of river health from huge anthropogenic stress.

Drought is a hydrological extreme and it brings negative consequences over environment, society and livelihood. Globally, drought frequency and magnitude is being amplified due to natural as well as anthropogenic causes. This scientific research attempts to examine the drought severity, trend and consequences applying the SPI and SPEI indices in the extended part of Chhota Nagpur Plateau (India) considering last 25 years period along with 3, 6, 9, and 12 months time scale. Mann-Kendall test and future prediction have also been done to find out the trend of drought. The results show that the frequency and trend of meteorological and ground water drought are being amplified and the years 1999, 2003, 2010, 2015 and 2016 have been recorded as extreme drought. The research revealed that the principal causes of drought are slight change of precipitation, unscientific withdrawal of ground water, modification of cropping patterns and drastic landuse change. District statistical bureau report states that drought events eventually reduce the crop production in most of the blocks of Purulia and severe water crisis creates during post monsoonal months in this particular region. The future prediction result signifies that around 60% mild and 6% severe drought will be faced using SPI index while around 64% mild and 5% severe drought will be occurred considering SPEI index. This scientific study along with integrated watershed management strategies will definitely assist to the regional planners and administrators for sustainable water resource management particularly for semi-arid climatic region of India.

The present work investigates the hydrochemical properties of the surface and groundwater of the Mayurakshi River Basin (India) for assessing their irrigation suitability with respect to irrigation hazards. The study involves 72 water samples classified as 48 surface water samples (pre-monsoon: 24; post-monsoon: 24) and 24 groundwater samples (pre-monsoon:12; post-monsoon: 12). Regarding the specific irrigation hazard, percent of sodium and soluble sodium percentage have demonstrated the groundwater vulnerability to sodium while the surface water is observed to be free from this kind of hazard. Similar findings have also been retained for magnesium hazard and the potential salinity hazard. Moreover, regarding the seasonality of the hazards, the post-monsoon season has depicted a higher level of irrigation hazards compared to the pre-monsoon season. The study found that the general evolution of groundwater hydrochemistry and the suitability of water for irrigation are principally governed by carbonate weathering, sand mining, stone crushing, and the development of brick kiln industries. Our methodology can be a good example for similar contexts, especially in developing and tropical countries.

The East Kolkata Wetlands (EKW) region is an important Ramsar Site (huge provisional, regulatory, cultural and spiritual ecosystem services) which is located at the eastern periphery of Kolkata Metropolitan City (India). But in the recent years, illegal land acquisition, wetlands conversion, aquatic species depletion as well as water pollution related diseases have been experienced in different pockets of EKW region. The main objective is to determine regulating factors and stages of eutrophication. The water samples of consecutive three years 2017, 2018 and 2019 (pre and post monsoon) have been obtained from selective 20 wetlands in EKW. The important physicochemical parameters (temperature, electrical conductivity (EC), turbidity, total alkalinity, pH, total hardness, total dissolved solids (TDS), dissolved oxygen (DO), inorganic nitrogen, total phosphorus, potassium, ammonium-nitrogen (NH4+-N), biological oxygen demand (BOD), Secchi disk depth, chlorophyll - a), trophic status index and statistical techniques (like principal component analysis, hierarchical cluster analysis) have been considered to analyze the water quality of these wetlands. The results portray that the magnification of inorganic nitrogen, total phosphorus, potassium and ammonium-nitrogen accelerates the mechanism of eutrophication in the selective wetlands. The DO level has been diminished during 2019 while the BOD level and chlorophyll concentration have been accelerated amidst 2019.The results reveal that about 40% of wetlands i.e. wetland no. 5, 7, 10, 16, 17 (TSI value – 50–70) and wetland no. 8 and 11 (TSI value – 70–100) come under eutrophic and hyper-eutrophic stages respectively due to higher accumulation of nitrogen and phosphorus contents in the wetlands from various non-point sources and these principal components stimulate the processes of eutrophication of the water bodies. Some relevant mitigation measures have been recommended to protect the “kidney of Kolkata Metropolitan City”.

This study mainly accentuates the effects of urban wetlands on micro climate in the hinterland region and the cooling effects of the wetlands largely control over the intensity of urban heat island (UHI). The magnitude of conurbation or urban agglomeration (with high-rise multi-storeyed buildings) of Kolkata city is growing very fast and this process accelerates the progress of urban heat island. The seven significant urban wetlands have been selected and Landsat satellite data (for the years 2018, 2019 and 2000) and descriptive statistical techniques have also been used. The temperature difference and temperature gradient (from the lake shoreline to the city's periphery) has been analysed to examine the cooling effects of wetlands. Consequently, around 30mts wide buffers have been generated from the shoreline of the wetlands and the temperature variance of each buffer is systematically examined. The result showed that the variance of temperature between first and last buffer is 3.41 °c and the temperature gradient is 1.14 °c/100mts towards the outer margin of the city. Here, heat holding capacity of different objects revealed that the average temperature of build upland is higher (32.59 °c) than the other classes. The average temperature of build upland within 300 mts buffer is 0.745 °c lower than the overall Kolkata metropolitan city region. Except the provisional service of the wetland, it modifies the urban micro climate. This applied research focuses further about the significant role of wetlands for reduction of excessive urban heat stress. This study definitely brings a new shape to frame for sustainable urban environmental management.

Abstract Groundwater is a vital source for drinking and agricultural purposes in semiarid region of Neyshabur area (Iran). The present study assessed the groundwater quality and mapped the spatial variation of water samples in terms of suitability for drinking and irrigation purposes. A total 402 groundwater samples were collected from the field with global positioning system (GPS) from 2010 to 2013 and analyzed for pH, calcium (Ca2+), magnesium (Mg2+), sodium (Na+), potassium, bicarbonate, sulfate, chloride, sodium adsorption ratio (SAR), electrical conductivity (EC), total dissolved solids, and total hardness (TH). A GIS-based ordinary kriging method with best fit semivariogram models was used for preparation of thematic maps of groundwater quality parameters. The results were evaluated and compared with WHO (2011) recommended water quality standard. Results showed that 68.40% of SAR, 25% of Mg2+, 32.62% of Na+, and 1.74% of TH of the total groundwater samples are suitable for the irrigation purpose. Consequently, 55.57% of EC, 89.19% of TDS, 0.75% of pH, and 6.25% of K+ of the total groundwater samples are suitable for the drinking purpose as per the WHO standard. The groundwater quality in the study area is very hard and slightly alkaline in nature. The spatial distribution map of groundwater quality showed 80% of the area suitable for drinking purpose; whereas, 90% of the area demarcated for irrigation purpose.

The ecological, economical, and agricultural benefits of accurate interpolation of spatial distribution patterns of soil organic carbon (SOC) are well recognized. In the present study, different interpolation techniques in a geographical information system (GIS) environment are analyzed and compared for estimating the spatial variation of SOC at three different soil depths (0–20 cm, 20–40 cm and 40–100 cm) in Medinipur Block, West Bengal, India. Stratified random samples of total 98 soils were collected from different landuse sites including agriculture, scrubland, forest, grassland, and fallow land of the study area. A portable global positioning system (GPS) was used to collect coordinates of each sample site. Five interpolation methods such as inverse distance weighting (IDW), local polynomial interpolation (LPI), radial basis function (RBF), ordinary kriging (OK) and Empirical Bayes kriging (EBK) are used to generate spatial distribution of SOC. SOC is concentrated in forest land and less SOC is observed in bare land. The cross validation is applied to evaluate the accuracy of interpolation methods through coefficient of determination (R2) and root mean square error (RMSE). The results indicate that OK is superior method with the least RMSE and highest R2 value for interpolation of SOC spatial distribution. Keywords: Soil organic carbon, Deterministic interpolation, Geostatistical interpolation, Spatial variation, GIS

The present paper is based on field investigation and measurement of rill erosion processes at Rangamati Experimental Station (Medinipur, West Bengal in India). In rill experiments, three different natural rills were studies in field for understanding of the dynamics of soil erosion processes of a rill catchment area. Geometric and morphological characteristics of each rill catchment area were analyzed. Results showed the widening, deepening and extended of rills because of sidewall sloughing, knick-points and head-ward erosion during surface runoff process. Progressive increases of rill volume were observed in the upper, middle and lower catchment with the change of time. Rill area has increased by runoff processes of 4.2 % and 6.8 % for Rill-A and Rill-B respectively. These processes are depends on surface coverage, soil texture, slope gradients and runoff velocity.