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Modeling surface water quality has become crucial in providing better strategies for managing surface water resources, and adequate findings need accurate and geographically dispersed data. Hydrogeological modeling of these data sets is possible using empirically-based models. The other statistical models are also an alternative approach. In this study, a process with maximum probability is considered with the help of machine learning tools (MLT) to have optimized and valid output. The proposed method combines remote sensing and geographic information systems (RS and GIS) and MLT, which are appropriate for the predicament of neither small, large scale, nor long-term simulations. MLT methods such as VAR and ARIMA are developed in the Python programming with Jupyter notebook and tested according to the data in the spatial prediction for surface water quality parameters such as Tr, pH, Ec, TDS, AL, Ca++, NO−3, So, Cl, F−, Fe, and Mg2+ in the Krishna District, Andhra Pradesh, India—lower delta part. The delta with susceptible zones was identified using RS and GIS as those areas are prone to direct exposure to surface water contaminants from aquaculture, agricultural runoff, small- and medium-scale businesses, and household trash. Achieving effective surface water management for this ecosystem is critical for regional water management. The geographical information about the concentrations acquired via the RS and GIS was compared to the statistical modeling findings and verified using real-time measurements. MLT modeling seems more realistic than the experimental setting; data from the previous 20 years (2000–2020) were used for modeling, and the predicted values presented in the paper are predicted for the year 2021. The computed R2 value of ranges between 0.75 and 0.96% is recorded with ARIMA, and VAR posted range between 0.56 and 0.75% with the trained and tested data. The findings show the potential for MLT of geographically dispersed hydrogeological data to be used for pollution-free surface water management. From the surface water management perspective, combining RS and GIS and MLT offers an alternate data analysis approach for obtaining quick results utilizing a less laborious process that produces acceptable results. [ABSTRACT FROM AUTHOR]

This paper presents the salient features of a study undertaken to characterize the geotechnical properties of dredged sediments from a typical reservoir in India by preparing GIS maps of geotechnical data based on the Inverse Distance Weighted technique. Potential of using the fine sediments (< 425 µm) of the dredged material after stabilization in earth work applications is subsequently examined through a series of compaction tests, UCC and CBR tests. The stabilizers used are Class C fly ash, hydrated lime and Ca-lignosulfonate. Results of the study indicate that the prepared spatial maps can serve as useful tools in proper planning of cost-effective dredging operation. The study also indicates that Class C fly ash, in general is a superior stabilizer among the various stabilizers considered for improving fine reservoir sediments, improvement in undrained shear strength and unsoaked CBR value being about fourfold and sixfold, respectively. However, hydrated lime is seen to be a more effective stabilizer than fly ash under sustained rainfall (soaked) condition. Addition of lignosulphonate is seen to improve the ductile nature of the stabilized dredged sediment without much loss of shear strength. SEM analysis provided deep insight into the flocculation and agglomeration mechanism and nature of the stabilized material. [ABSTRACT FROM AUTHOR]

Flash flood is the most recurrent natural threat in northeastern India, especially during the peak of the monsoon season. In recent decades, the frequency of flash floods has considerably increased in the Himalayan watersheds, causing enormous human suffering, infrastructure damage, ecosystem disruption, and economic losses. Considering the exponential rise in the frequency of flash flood events, identifying the Flash Flood Vulnerable Zones (FFVZs) is one of the most crucial findings to limit their negative consequences. In this study, grey fuzzy analytic hierarchy process-based model integrated with the geographic information system is implemented to assess the flash flood vulnerability in the Ranikhola watershed, East Sikkim, India. Additionally, a novel Flash Flood Vulnerability Index (FFVI) is proposed to determine the flash flood vulnerability that takes into account twelve natural and anthropogenic parameters. Further, the FFVI map is classified into three FFVZs: low, moderate, and high. The effectiveness of the methodology implemented is judged by the high EV value (6.4286) and the comparison parameter. The harshest conclusion of this analysis, the major cities, such as Gangtok, Ranipool, and Singtam, are designated high FFVZ. The sensitivity analysis results show the LULC has the maximum positive influence on high FFVZ. [ABSTRACT FROM AUTHOR]

Groundwater is an important source of drinking water and irrigation. However, due to increased anthropogenic activities, its quantity and quality are gradually deteriorating over time. The current paper focuses on the evaluation of groundwater quality and its variability for drinking purpose in Gurugram district of Haryana. Geographical Information System based groundwater quality index (GWQI) is a cost-effective tool for the assessment of groundwater quality and its variability. Nine water quality parameters, i.e., sodium, potassium, magnesium, calcium, chloride, sulfate, nitrate, fluoride, and total dissolved solvent have been considered for quality assessment of pre-monsoonal season. Two GIS-based groundwater quality index maps GWQI-9 (for all the above mentioned parameters) and GWQI-4 (for the critical parameters whose concentrations exceeded the permissible limit) were produced. Subsequently, correlation analysis and factor analysis were performed to determine the degree of correlation and to identify the principal factor of contamination among all nine water quality parameters, respectively. Interpolated maps, concentration maps, and rank maps were developed for each parameter. Furthermore, the rank map was used to assign weight to each parameter. Based on rank and weight, the final GIS-based GWQI-9 and GWQI-4 were developed. Higher GWQI values reflect higher water quality. Overall, the north-eastern parts of the district have high water quality, while the western and northwestern periphery of Gurugram has low water quality. Except northern and north western region, most of region of Gurugram have poor water quality in terms of GWQI-4. It is possible to conclude that GIS-based GWQI could become a comprehensive approach for assessing surface or groundwater quality. [ABSTRACT FROM AUTHOR]

The world is facing immense pressure due to expanding discourse on resource security. The study is conducted in the water–energy–food (WEF) Nexus context to understand the inter-relatedness of the sectors for sustainable development, eliciting stakeholders' perspectives. Banda District lies in Bundelkhand region of India. It is drought-hit and lacks basic infrastructure and hence has been selected for this research. It is facing challenges stemming from WEF resources insecurity which has triggered mass migration, farmer suicide, unemployment, and indebtedness. In this exploratory research study, nineteen parameters are analyzed using multi-criteria decision analysis and weighted index method to calculate the Stakeholder opinion-based development index (SODI). GIS is used for spatial mapping to characterize the grassroots disparity highlighting the perspective and expectations of the 534 surveyed households. The SODI of Banda District is calculated to be 10.157, which lies in the average category. Most parameters (78.95 percent) fall below the average category, showing that the region is backward and the spatial mapping helps in identifying lacunae in the development of the District. The novelty of this research lies in using the analytical method to examine qualitative parameters that highlight stakeholders' perspectives and usage of unique methodology in formulating the index to study the region holistically for sustainable development. It is concluded with recommendations based on findings using a system-based approach. The modified structural approach of the Stakeholder Opinion-based Development Index and research methodology can be employed for profiling and analyzing the Districts of the same characteristics in and out of India. [ABSTRACT FROM AUTHOR]

The expansion of the population and tourism industry, especially near the coast, is altering land use and deteriorating coastal resources. This contributes significantly in increasing the susceptibility of a coastal area to flooding and sea-level rise. Therefore, identifying vulnerable coastal areas through an integrated approach for comprehensive coastal development and realistic management policies is pivotal. This paper presents a method for assessing coastal vulnerability by employing selected physical and human indices. It was applied to the Mandarmani–Dadanpatrabar coastal sector of West Bengal, where the issue of rapid tourism growth at the expense of coastal resources is a major concern. For the assessment of coastal vulnerability, the entire length of the study area was divided into 64 equal segments. A set of six physical variables (shoreline change, beach width, coastal slope, dune discontinuity, vegetation, and coastal geomorphology) and three human variables (land use land cover, coastal protection, and distance of road) were measured using fieldwork and remote sensing and geographical information system. Subsequently, the physical and human vulnerability was calculated and then combined to create an integrated coastal vulnerability index (ICVI). While the majority of the coast is low-to-moderately vulnerable, it was observed that high vulnerability was present in areas where physical resources were rapidly exploited for the growth of tourism. This study emphasizes the need of implementing existing coastal regulation zone guidelines in a more realistic way to prevent loss of assets and promote integrated development. [ABSTRACT FROM AUTHOR]

In a mountainous basin, flash-flood-induced soil erosion and its assessment are of major concern to the researchers. Cloudburst-induced extreme rainfall, undulating terrain, and inadequate water and soil conservation practices aggravate the problem of soil erosion. Alaknanda, a major basin of the upper Ganges in India, has experienced several incidents of flash floods. These have resulted in heavy soil loss, water siltation, and pollution in the basin. This study uses the revised universal soil-loss equation (RUSLE) in the GIS framework to assess the soil loss rate in various sub-basins of the Alaknanda. Further, the study suggests sub-basin prioritisation based on high soil erosion rate and past vulnerability that need attention of the decision-makers. RUSLE, an empirical soil erosion model, is easy to comprehend physically, involves minimum resources, and works on readily available inputs. The parameters used in the assessment include R-Rainfall Erosivity, Cover Management-C, Topographic-LS, Conservation Practice-P, and Soil Erodibility-K. The average R, K, LS, C & P factors for the Alaknanda basis are estimated as 437 MJ mm/ha/yr., 0.07 t ha h MJ-1 ha-1 mm-1, 1.4, 0.7, and 0.62, respectively. The mean annual soil erosion rate in the sub-basins varies from 6 to 27.9 t /ha/year with a mean rate of 13.4 t/ha/year and total erosion of 13.7 Mt/year. The results show that out of the twelve sub-basins, two (WS7 and WS5) fall in the high erosional class (18–30 t/ha/year), nine fall in the moderate erosional class (7–18 t /ha /year) and one basin in the low erosional class (1.0–7.0 t /ha/year). It is hoped that the present study will be helpful to the decision-makers while prioritising the actions to be taken for the water and soil conservation purposes. [ABSTRACT FROM AUTHOR]

The Indo-Ganga–Brahmaputra plain is one of the world's most vulnerable areas to catastrophic flood events. The severity and frequency of floods in this region have grown dramatically during the last few decades. As a result, an authentic map providing detailed spatial information on floods is required for reducing future flood disasters. This sort of map can be an invaluable tool for displaying flood-prone areas and determining the magnitude of flood risk. The Ramganga river (~ 200 km length) flowing in the western Gangetic plain was chosen for this investigation. This river is well known for its channel movement and flood hazards. The analytical hierarchy process model in GIS ambiance was used in this work to quantify and map flood risk in the lower Ramganga river basin. Six hazard-forming factors, namely relief, distance from active channel, slope, geomorphology, rainfall, and vegetation, and seven vulnerability factors, namely population density, household density, female density, road density, land use/land cover, female literacy, and total literacy, were chosen to determine flood risk zone (FRZ). According to the findings, about 35.29 per cent of the basin's total area is in a high to very high flood risk zone, where flooding occurs at one- to three-year recurring intervals. The flood risk map has been validated using ground truth data, and the Kappa index has been computed, indicating a high degree of accuracy for the FRZ thematic classes. [ABSTRACT FROM AUTHOR]

In the present study, the groundwater spring potential zone (GSPZ) was identified using an integrated approach of remote sensing (RS) and geographic information system (GIS), analytic hierarchy process (AHP), and fuzzy-AHP based on multicriteria decision-making (MCDM). Thus, ten associated factors with groundwater springs have been considered: slope, drainage density, lineament density, geomorphology, lithology, soil texture, land use and land cover, rainfall, groundwater level, and spring discharge. The analysis output was categorized into low, moderate, and high. The result of the AHP model shows the area under the high potential zone (16.61%), the moderate potential zone (60.42%), and the low potential zone (22.61%). The result of the fuzzy-AHP model shows that the area falls under the high potential zone (30.40%), moderate potential zone (41.29%), and low potential zone (22.61%). The validation results showed fuzzy-AHP with the area under the curve 0.806, which is slightly better than 0.779 of AHP. So, the resulting GSPZ map confirms that the thematic layers used in the study have a significant role in groundwater spring occurrence and distribution. It was recommended that any groundwater spring rejuvenation or protection activities must be implemented in medium to very high potential zones. [ABSTRACT FROM AUTHOR]

The significant natural energy sources for reducing the global usage of fossil fuels are renewable energy (RE) sources. Solar energy is a crucial and reliable RE source. Site selection for solar photovoltaic (PV) farms is a crucial issue in terms of spatial planning and RE policies. This study adopts a Geographic Information System (GIS)-based Multi-Influencing Factor (MIF) technique to enhance the precision of identifying and delineating optimal locations for solar PV farms. The choice of GIS and MIF is motivated by their ability to integrate diverse influencing factors, facilitating a holistic analysis of spatial data. The selected influencing factors include solar radiation, wind speed, Land Surface Temperature (LST), relative humidity, vegetation, elevation, land use, Euclidean distance from roads, and aspect. The optimal sites of solar PV power plant delineated revealed that 'very low' suitability of site covering 4.866% of the study area, 'low' suitability of site 13.190%, 'moderate' suitability of site 31.640%, 'good' suitability of site 32.347%, and 'very good' suitability of site for solar PV power plant encompassing 17.957% of the study area. The sensitivity analysis results show that the solar radiation, relative humidity, and elevation are the most effective on the accuracy of the prediction. The validation of the results shows the accuracy of solar PV power plant prediction using MIF technique in the study area was 81.80%. The integration of GIS and MIF not only enhances the accuracy of site suitability assessment but also provides a practical implementation strategy. This research offers valuable insights for renewable energy policymakers, urban planners, and other stakeholders seeking to identify and develop optimal locations for solar energy power farms in their respective regions. [ABSTRACT FROM AUTHOR]

Urbanization produces substantial land use changes by causing the construction of different urban infrastructures in the city region for habitation, transportation, industry, and other reasons. As a result, it has a significant impact on Land Surface Temperature (LST) by disrupting the surface energy balance. The objective of this paper is to assess the impact of land-use/land-cover (LU/LC) dynamics on urban land surface temperature (LST) of Bhubaneswar City in Eastern India during 30 years (1991–2021) using Landsat data (TM, ETM + , and OLI/TIRS) and machine learning algorithms (MLA). The finding reveals that the mean LST over the entire study domain grows significantly between 1991 and, 2021due to urbanization (β coefficient 0.400, 0.195, 0.07, and 0.06 in 1991, 2001, 2011, and 2021 respectively) and loss of green space (β coefficient − 0.295, − 0.025, − 0.125 and − 0.065 in 1991, 2001, 2011 and 2021 respectively). The highest class recorded for agricultural land (49.60 km2, accounting for 33.94% of the total land area) was in 1991 followed by vegetation (41.27 km2, 28.19% of the total land area), and built-up land (27.59 km2, 18.84% of the total land area). The sharp decline of vegetation cover will continue until 2021 due to increasing built-up areas (r = − 0.531, − 0.329, − 0.538, and − 0.063 in the 1991, 2001, 2011 and 2021 respectively). Built-up land (62.60 km2, accounting for 42.76% of the total land area, an increase of 35.01 km2 from 1991) as the highest class followed by water bodies (21.57%, 32.60 km2 of the land area), and agricultural land (31.57 km2, 21.57% of the land area) in 2021. Remote sensing techniques proved to be an important tool to urban planners and policymakers to take adequate steps to promote sustainable development and minimize urbanization influence on LST. Urban green space (UGS) can help improve the overall liveability and environmental sustainability of Bhubaneswar city. [ABSTRACT FROM AUTHOR]

Identification of hospital sites and their ranking is important for the planning and development of any country's health infrastructure. The site selection problem is a typical multi-criteria decision making problem involving multiple stakeholders and their interests. Multi-Criteria Decision Analysis (MCDA) is a promising approach to solve a location-based problem due to the constitution of various criteria involved in decision making. In this research, eleven criterion are chosen which are classified under three main criteria; socio-economic, geographical and environmental. This research aims to identify the appropriate MCDA method for the selection of a new hospital sites. Here, two MCDA methods named Analytical Hierarchy Process (AHP) and Fuzzy AHP (FAHP) are used. Further, Geographical Information System (GIS) based MCDA methodology is proposed in this paper. The results obtained with both AHP and FAHP methods are compared. This comparison is based on criterion rankings, proposed hospital locations and sensitivity analysis. The main difference in results is shown in the result of sensitivity analysis in which constant variation in site ranking is obtained when weight change analysis is performed using AHP. The FAHP result shows only one variation in site ranking after a change in weight from +10 to +20%. The result suggests that FAHP may be a better approach to the hospital site selection problem. [ABSTRACT FROM AUTHOR]

The key challenge of India is to provide access to safe drinking water for the increasing population. Hence, it is important to access the current status and progress in the sources and availability of safe drinking water in India for improving the prevailing policies. This paper studies the spatial and temporal patterns in safe drinking water availability and accessibility in Indian states and union territories. State-wise data of safe drinking water sources have been obtained from the Census of India for the period 1981–2011. Their spatial distributions have been shown using choropleth maps in geographical information system (GIS) environment. Rural–Urban differential and Safe Drinking Water Sources Availability and Accessibility Index (SDWSAAI) is computed for all the states and union territories for the year 2011. Findings indicate that India gained a significant advancement in access to safe drinking water from 38% (1981) to 85.5% (2011). In 1981, 26.5% and 75.1% of rural and urban households had access to safe drinking water, respectively, depicting a huge gap of around 49% point. This gap has brought down to only 8.7% point in 2011. Households having a source of drinking water within the premises have increased from 39% to 46.6% during 2001–2011. Nevertheless, households getting drinking water away from the premises have also recorded a marginal rise during the same period. Pondicherry has the highest score in the SDWSAAI followed by Daman and Diu, Chandigarh. Among states, Tamil Nadu has scored the highest, followed by Punjab and Himachal Pradesh. Manipur and Odisha have scored lower in the index. Regional disparity in access to safe drinking water still exists in India and needs further improvement and management for a better quality of life. [ABSTRACT FROM AUTHOR]

Poverty is not only the focal issue that has drawn worldwide attention but is also an essential issue in people's livelihoods. This research examines the primary factors of poverty in the Birbhum district. Multivariate statistical techniques have been used to identify the primary determinants. Ten parameters have been identified as significant drivers of poverty, six of which are physical, viz. slope, elevation, drainage density, pond frequency, soil texture, and rainfall. The remaining four sociocultural and economic parameters are literacy, major market center, population growth, and road density. A linear relationship has been established between the explanatory and response variables where the R-square or coefficient of determination value is 0.741, and this relationship explains more than 74% of the variables. The P-value of multi-linear regression is 0.000, which validates the model and permits the data for factor analysis to extract the major determinants. Factor analysis indicates that five essential factors have been found based on their eigenvalue viz., agro-climatic factor, infrastructural and educational factors, hydrological factor, demographic factor, and pedological factors. All the p-values of the correlation matrix are < 0.05, meaning all the relationships are valid and significant. This research also demonstrates the spatial analysis of data using GIS technology. The western part of the study area has been affected by the high influence of all factors due to the presence of plateau fringe and associated low productivity. The outcomes of the research are scientifically significant and this study helps the planners, higher authorities, and social workers to eradicate poverty from this region through formulating better policies and management. [ABSTRACT FROM AUTHOR]

During the monsoon season, flooding is common in several parts of India, and urban areas are becoming more prone to flooding even during less intense rainfall events as a result of the encroachment of waterbodies and natural drainage channels, increased impervious areas, and subsequent decrease in infiltration capabilities. In the years 2000, 2008, 2016, 2019, 2020, and 2021, severe flood events in our study area, the Saroor Nagar urban watershed in Telangana state, caused human loss, economic devastation, and environmental devastation. Although flood risk cannot be completely eliminated, it can be significantly reduced by developing a flood hazard model to identify flood-prone areas in a watershed, which can assist decision makers seeking comprehensive flood risk management. The flood hazard map is created by integrating Geomatics with multi-criteria decision analysis and the analytical hierarchy process (AHP). Topographic wetness index (TWI), digital elevation model (DEM), slope, precipitation, drainage density, distance to waterbody, soil, and land use land cover (LULC) were the flooding causative elements considered in this study. The resulting flood risk map is divided into four distinct categories that reflect flood danger levels of low, moderate, high, and extremely high. The flood risk map revealed that the moderate risk zone decreased from 50.2 to 45.7% of the study area between 2008 and 2020, while the high-risk zone increased from 45.2 to 52.8%. The flood susceptibility map is validated using crowdsourcing techniques. The findings demonstrated that a Geographic Information System (GIS)-based multi-criteria analysis framework for flood hazard analysis could be effectively used to aid disaster management decision-making. [ABSTRACT FROM AUTHOR]

Mayurjharna Elephant Reserve (MER) is one of the important Elephant Reserve (ER) in southern West Bengal, India. Dense forest, natural water bodies, human habitation, agricultural land, roads and more than 100 wild elephants are present in this elephant reserve. Due to increasing human population density and changing land-use patterns incessantly the naturally dwelling place of the wild elephants has been reduced a lot. As a result of the reduced dwelling spaces, the elephants sometimes enter into the human used areas for searching their basic requirements and then the conflict is started. This conflict is a complex interaction between human and elephant and it is a burning problem not only in the MER but also in southern West Bengal. This research article is an outcome of the empirical investigation to chalk out the spatio-temporal patterns of Human—Elephant Conflict (HEC) in the MER and to yield information helpful for HEC mitigation and elephant conservation. The identified forms of HEC in the MER are elephant threat, crop raiding, property damage, injury to people, human death, elephant death, elephant injury, and livestock death. Here elephant threat is considered as indirect and the rest forms are considered as direct impact of HEC. Among them the elephant threat is counted for the highest number of incidents (60.36%), followed by crop raiding (33.58%), property damage (3.40%), human injury (0.85%), human death (0.74%), elephant death (0.43%), livestock death (0.53%) and elephant injury (0.11%). A dataset on HEC incidents (N = 941) occurred by wild elephants which were collected from the villages within this ER during the survey period (2020–2021). Here the HEC arises throughout the year, but in October (27.95%) and November (24.87%) months having the highest number of incidents. Most of the crop raiding events (51%) occur at a distance of less than 1.0 km far from the dense forest and such events were gradually decreased in respect of increasing distance from the MER. Descriptive statistics, correlation (r), One-way analysis of variance (ANOVA) were used to explain the HEC patterns of the concerned study area. Arc GIS 10.6 software was also used for the preparation of land use and land cover (LULC) map and conflict risk map through Kernel Density Estimation Model (KDEM). [ABSTRACT FROM AUTHOR]

Water bodies play a very important role in maintaining and restoring the ecological balance, but they are one of the most threatened habitats in the world. Anthropogenic intervention is changing the regimes of wetlands almost everywhere particularly in the developing countries. Gorakhpur District is dotted with many big and small flood plain–related water bodies like rivers, streams, tanks, dead arms, oxbow lakes, etc. Some of these water bodies are worst affected and are degraded by encroachment for agriculture and other economic and developmental activities. Channel migration, aggravated by human intervention, on alluvial plain is also very frequent, which has direct impact on the nature of water bodies and land use transformations of the region. In this paper, the authors have made an attempt to (a) bring current geographical and historical background of water bodies/wetlands for the district. It aims to assess long-term (1917–2018) and short-term (pre- and post-monsoon) changes in the water bodies of Gorakhpur District; (b) provide changes in the regime of water bodies/wetlands and their conversion to different types of land use/land cover classes due to human intervention and due to annual rainy season, which inundates a large extent of the area every year; (C) assess the channel characteristics and morphometric analysis of main rivers of the region during the last hundred years. Remote sensing and Geographical Information System (GIS) have been used to prepare the inventory and to perform change detection, using land use/land cover maps. The floodplain areas of water bodies have almost changed their morphological characters due to encroachment by the nearby areas. Canals, drainage channels, and lakes are the most affected water bodies in the region, which have recorded − 65.38% and 43.37% loss in their area. Even permanent rivers have recorded a decrease of − 16.96% in the area. As per the seasonal change, agriculture land suffered the greatest conversion (18.33%) due to floodwater inundation. The study provides a platform to planners to chalk out their policies and also for monitoring the water bodies. Furthermore, analysis on channel migration will help predict the future course of the main rivers. [ABSTRACT FROM AUTHOR]

Chennai Port (13.099872° N, 80.297407° E), located along the southeast coast of India, has been a hub for maritime trade since the fifteenth century. An artificial harbour was initially constructed in 1881 which underwent numerous expansions in the following years. The breakwaters of the harbour intercepted the heavy sediment-laden littoral drift along the coast, resulting in the formation of the world's second-longest urban beach south of the port, i.e. on its up-drift side. Meanwhile, the coast north of the port, i.e. the down-drift side, experienced intense erosion due to a lack of sediment supply and forces induced on the coast due to waves and currents. The shoreline change study in this paper investigates a shoreline stretch of about 6 km (protected by transitional groynes), north of Chennai Port by dividing it into three segments. The rate of shoreline changes over a period of about 12 years across three different segments was assessed using statistical parameters by employing remote sensing techniques complemented with geographical information system (GIS) and digital shoreline analysis system (DSAS) tool. It is inferred that the coast has witnessed accretion and sizable growth in beach width has been observed post the construction of groyne field. [ABSTRACT FROM AUTHOR]

In this study, groundwater irrigation potential zones are identified by measuring an integrated irrigation water quality index using a GIS platform in the Vishwamitri River Basin (VRB) region, Gujarat, India. Classification of different irrigation potential zones is about the collective paraphernalia of thematic maps, namely, electrical conductivity (EC), sodium adsorption ratio (SAR), Na+, Cl−, and HCO3−, which principally regulate the groundwater quality for irrigation. The EC, SAR, and chloride values are > 3000 µS/cm, > 9 meq/L, and > 10 meq/L, respectively, indicating 98.78%, 41.78%, and 84.88% of the total area, respectively, belong to groundwater both hazardous and unsuitable for irrigation. Similarly, 39.55% of the total area is unsuitable for irrigation due to its high Na+ concentration. The permeability, porosity, and infiltration risk usually appear when excessive sodium ions reduce the rate of flow of irrigation water which moves in the lower soil zones. Similarly, high bicarbonate and chloride concentrations have been denoted to hamper the development of several crops causing symptoms analogous to lime-induced chlorosis due to toxic effects of the salt. The final irrigation potential map is marked by four levels, such as "most suitable," "moderately suitable," "moderately unsuitable," and "unsuitable for irrigation." Approximately, 56.69% of the total VRB region are covered with unsuitable for irrigation purposes. In such areas, irrigation must be avoided in usual conditions, and the halophytes, namely, Khati palak (Atriplex stocksii), Lamb's quarters (Chenopodium album), and Rudravanti (Cressa cretica) should be recommended with high soil permeability and proper drainage facilities. The soil must be highly permeable for groundwaters with high salinity and sodicity. Based on this study, policymakers and environmental managers can estimate the resource implications for drinking and irrigation. [ABSTRACT FROM AUTHOR]

The dairy industry is a high-water-consuming sector, making water conservation crucial, especially in countries like India that are top milk producers and have large populations. This research evaluates the performance and effluent characterization of dairy effluent treatment systems in Kerala using modern, cost-effective technology to address this issue. A hybrid electrocoagulation reactor (HECR) is designed to operate simultaneously in coagulation, and the electrocoagulation process is proposed in this study. The wastewater treatment parameters of the HECR with those of six existing dairy effluent treatment plants using geological mapping and geographic information system (GIS) were studied. According to inverse distance weighted (IDW) interpolation findings, HECR's effluent treatment profile is comparable to existing technologies, with a minimum required retention time of 9.58 h. The results show the HECR treatment efficiency, removing up to 75.15% of turbidity and 94.5% of COD. Moreover, the sludge generated from HECR is transformed into nutrient-rich vermicompost by adding suitable fillers in the ratio of 5:1:3:1 (industrial dairy sludge/HECR sludge: cow dung, dry leaf, and seed vermicompost). The optimal conversion times for vermicompost developed from dairy industrial sludge are 40 days, with nitrogen, phosphorus, and potassium (NPK) values per gram vermicompost of 8.86%, 3.18%, and 3.6%, respectively. For HECR sludge, on the 60th day, the observed NPK value for the developed vermicompost is at 4.76%, 1.46%, and 5.1%. Overall, this research offers a promising solution to treat dairy wastewater and transform generated waste sludge into a valuable resource, highlighting the importance of technology adaptation in the dairy industry. [ABSTRACT FROM AUTHOR]

Peri-urban area around a city is a dynamic zone that undergoes considerable changes over time in terms of its functional land use. Analogous to other Indian cities, these changes are also evident in the peri-urban villages of Burdwan city, which has seen intense land use changes between 1987 and 2017. These changes are gauged by using LANDSAT-5 Thematic Mapper (TM) for 1987; LANDSAT-7 Enhanced Thematic Mapper (ETM +) for 2002 and LANDSAT 8 (OLI) for 2017. This study makes a unique contribution by combining the use of remote sensing and intensity analysis to evaluate changes in land use and land cover. The results showed that both the 1987–2002 and 2002–2017 time periods experience rapid change and the land use transformation has been accelerated over the whole period. The profound changes in the vegetation and water bodies are amplified by rampant reclamation for built up and commercial purposes. Results show that the proportion of vegetation and waterbodies decreased by 72.3% and 56.3%, respectively, whereas built-up area has increased by 182.8%. The research also revealed a built up pattern mostly towards the north-west, north, North-East and south-east direction. The current study attempts to analyse the variables causing land transformation and the many actors and their roles in driving these alterations. Finally, the extensive explanation and spatio-temporal differentiation maps and tables created with geospatial data will undoubtedly aid in understanding the peri-urban growth dynamics process and changing form of land-use land cover and aid the decision-making process of local planners, stakeholders, and academicians. [ABSTRACT FROM AUTHOR]

Groundwater is a crucial natural resource for providing reliable and long-lasting water supplies across the globe. The integrated approach used in the current study involved the use of multiple techniques to assess groundwater potential zones (GWPZs) and identify suitable areas for artificial recharge sites. The methods used in the study were a combination of geographic information system (GIS), analytic hierarchy process (AHP), and fuzzy analytic hierarchy process (Fuzzy-AHP) to accomplish this goal. The study considered multiple thematic maps, such as drainage density, elevation, geomorphology, slope, curvature, topographic wetness index (TWI), geology, distance from the river, land use and land cover (LULC), and rainfall, to determine the GWPZs. AHP and Fuzzy-AHP were used to weight thematic maps based on their relative importance in controlling groundwater availability and recharge, and then a weighted overly analysis in a GIS environment was utilized to derive the final GWPZs map. After completing the weighting of thematic maps, both AHP and Fuzzy-AHP models categorized GWPZs into low, moderate, and high categories in the study area. In this study area, GWPZs were classified as poor, moderate, and high using both the AHP and Fuzzy-AHP models. According to the AHP model, 5.41% of the area's GWPZs were categorized as poor, 70.68% as moderate, and 23.91% as high. The Fuzzy-AHP model, on the other hand, categorized 4.92% as poor, 69.75% as moderate, and 25.33% as high. To validate these results, the receiver operating characteristic curve (ROC) and area under the curve (AUC) were used to explore the prediction accuracy, resulting in an accuracy rate of 70.1% for AHP and 71% for Fuzzy-AHP. These findings suggest that the Fuzzy-AHP model is effective in accurately identifying GWPZs in this area. Additionally, using remote sensing (RS) and GIS, the current study created a map by overlaying the lineament and drainage maps to determine suitable locations for artificial recharge. One-hundred-forty suitable locations for artificial recharge sites were identified based on Fuzzy-AHP. The study's reliable findings assist decision-makers and water users in the research area to use groundwater resources sustainably. This information aids in sustainable planning and management of groundwater resources, ensuring their availability and sustainability for future generations. [ABSTRACT FROM AUTHOR]

Mughal road located in the high mountainous region of Kashmir Himalaya, India is prone to landslide hazards because of anthropogenic pressure and ongoing climate change. Landslides along the roads is one of the critical problems in hilly areas. Landslide vulnerability maps can serve as an effective tool for the planning and management of landslide disasters. The primary goal of the present study is to generate a Landslide hazard map along the Mughal Road. An integrated approach of Remote sensing GIS and AHP was used applied for this purpose. The eight most important landslide occurrence parameters including slope aspect, geology, elevation, slope angle, lineament buffer, drainage buffer, landuse/landcover and NDVI were employed in the present model. The Advanced Spaceborne Thermal Emission and Reflection Radiometer Digital Elevation Model and Linear Imaging Self-Scanning Sensor imagery were used to prepare these thematic layers in Arc GIS environment. The analysis of the final landslide hazard map reveals that, very low, low and moderate landslide hazard zones constitute 0.6%, 15.8% and 41.3% of the total area in the study region, respectively. While High and very high landslide hazard zones account for 30.2% and 12.2%, respectively of the total geographical area in the study region. Finally, an inventory of landslides has been used to validate the findings of the study. The landslide hazard zonation map has been also compared with the Landslide inventory map through the ROC-AOC method. The applied model produced an excellent result for landslide hazard mapping in the research region, as shown by the spatial effectiveness of the generated landslide hazard map validated by AUC (77.7% of accuracy). The study can be very useful for policy maker and construction planners. [ABSTRACT FROM AUTHOR]

Land degradation is a problem of grave concern and a major factor leading to it is soil erosion. Soil erosion and its rate are influenced by various factors intrinsic to the soil or related to the soil's external environment. These factors include rainfall, soil erodibility, topographic characteristics, crop cover, and conservation practices. The revised universal soil loss equation (RUSLE) is a well-renowned empirical formula used to compute a particular area's mean annual soil loss. Remote sensing (RS) and geographical information system (GIS) technologies make modeling and execution of RUSLE easy, reliable, and cost-effective. So, these were employed to compute the spatial distribution of soil erosion risk area in Nagavangala micro-watershed in Karnataka state, India. All the factors were generated using metrological data, CartoSat DEM, Quick bird imagery, and laboratory analysis data using GIS software and integrated in a GIS environment to estimate the soil loss rate. It was found that cropland (41.81%) was the dominant land use followed by agricultural plantation (41.5%) and scrubland (11.09%). The average annual soil loss of the watershed was estimated to be 9.80 t/ha/year. The average annual soil loss was highest in the area under scrubland (10.58 t/ha/year) followed by cropland (10.2 t/ha/year). The soil erosion map thus generated can serve as a basis for adopting suitable soil and water conservation measures in the watershed for sustainable management of the resources in it. [ABSTRACT FROM AUTHOR]

The present study addresses the application of weight of evidence (WoE) model (probabilistic approach) to identify the spatial distribution of landslide susceptibility (LS) in Darjeeling Himalaya, Eastern India. Fifteen triggering factors of landslide such as elevation, geology, slope angle, slope curvature, soil, slope aspect, drainage density, lineament density, distance to drainage, distance to lineament, topographic wetness index (TWI), normalized differential vegetation index (NDVI), stream power index (SPI), land use land cover (LULC) and rainfall were considered as spatial database to perform WoE model using remote sensing (RS) and geographic information system (GIS) and to develop landslide susceptibility zonation (LSZ) map. The relative importance of weights of each factor was calculated using the WoE method. The LSZ map depicted that very low (VL), low (L), moderate (M), high (H) and very high (VH) LS zones cover an area of 3.33%, 8.46%, 29.94%, 38.07% and 20.20% respectively. Two thousand seventy-nine landslide locations have been identified and considered to perform the accuracy of the study. The receiver operating characteristics (ROC) curve resulted in 78.90% prediction accuracy with and area ratio of 0.7890 which recognised WoE model as a significant statistical model for LS mapping for Darjeeling Himalaya. Very low to very high LS zones registered with the frequency ratio (FR) of 0.00, 0.21, 0.36, 0.85 and 2.73 respectively, which is positively correlated to landslides. The outcome of the study will be very helpful to the planners and policy makers for implementing effective measures to mitigate landslides hazards in Darjeeling Himalaya. [ABSTRACT FROM AUTHOR]

Agriculture is the primary source of income in the Sub-Himalayan Jalpaiguri District; therefore, identifying the optimal use of existing agricultural land is crucial. The primary objective of this study is to identify potential agricultural sites in the Jalpaiguri District for the sustainable development of the region. About eleven parameters have been considered using the multi-influencing technique in combination with remote sensing (RS) and geographic information system to delineate and model potential agriculture sites. The final agriculture suitability map was created using the 'Weighted Overlay technique,' and the final output can be categorized into five classes, i.e., highly suitability (424.3 km2), moderately suitability (1191.8 km2), marginally suitable (1141.4 km2), currently not suitable (567.1 km2), and permanently not suitable (60.8 km2). Besides, the results have been thoroughly verified using Google Earth images, in comparison with Landsat 8 output, and field visits using GPS to increase the reliability of the results. The finding reveals potential outcomes for agricultural activity; however, building a sustainable management strategy and resilient farming practices should be adopted to boost the region's agricultural output. Farmers, regional planners, and government officials can use the current agriculture suitability map to make comprehensive judgments for the region, such as determining the potential for agriculture sites, improving agricultural growth, and promoting self-reliant local economies. [ABSTRACT FROM AUTHOR]

Soil erosion induced by physical and anthropogenic activities needs serious concern to deal with. In recent days, watersheds have been facing acute soil loss because of deforestation, poor land use management and unscientific agricultural practices. The present paper highlights the goal to decipher soil erosion-susceptible zones in a rain-fed river basin of India having a complex topography comprising the extension of Chotonagpur plateau and parts of Bengal basin. Fuzzy logic algorithm-based analytical hierarchy process (FAHP) with remote sensing and geographical information system (GIS) were used to execute the objective. The soil erosion-susceptible zone (SESZ) was identified assimilating the 14 geo-environmental, hydro-meteorological and anthropogenic conditioning factors such as slope, drainage density, relative relief, stream power index, topographic wetness index, runoff, soil texture, land use and land cover, rainfall erosivity factor, distance from road, distance from settlement, distance from river, geomorphology and soil bareness index based on which sub-basin prioritization for sustainable soil conservation was made. The soil erosion-susceptible zone was classified into five classes, namely very low soil erosion zone (13.20%), low soil erosion zone (25.75%), moderate soil erosion zone (27.62%), high soil erosion zone (21.90%) and very high soil erosion zone (11.53%). Receiver operating characteristics (ROC) curve was generated where area under the curve (AUC) came as 0.82 and a correspondence analysis between the SESZ and the first three ranked factors was also made which together proves the accuracy of the model. [ABSTRACT FROM AUTHOR]

The spatial analysis of primary schools is needed to ensure that they meet standards set by the Government of India. Therefore, mapping of Prayagraj district primary schools is carried out in this research work. The spatial analysis of schools is performed using various parameters that include: literacy rate, student gender ratio, teacher taught ratio, and students' toilets ratio. Several problems were revealed in the GIS based analysis of schools by highlighting their locations on the map. The results identify the location of all those schools where there is a need to take corrective measures. Further, the route analysis between home and school is handled in this research work. Sometimes, commutation is the sole criteria in the selection of a school. Therefore, optimal path analysis has been performed based on three parameters, i.e. population density, traveling distance and traveling time. A combined weight function is also given to find the optimal path. This work will help people to select the best possible path based upon their requirements. There is often a requirement to reach all the schools to distribute the goods or other physical monitoring activities. This work gave the optimal route to visit all the schools by using the Travelling Salesman Problem (TSP). School accessibility results obtained in this research through TSP will assist in choosing the best possible route. This will help the government identify locations where new roads need to be constructed to have road connectivity. [ABSTRACT FROM AUTHOR]

Many tourists have been recently attracted towards the coasts around the world, especially to the large urban centres and economically significant areas. In the last four decades, there is a significant increase in the key coastal developments and tourist's attractions like major ports, minor ports, fishing harbours, desalination plants, shore protection structures, and many more along the southeast coasts of India, in particular, northern Tami Nadu coastal stretches. The shoreline change study of these regions were carried out using the geospatial technologies (satellite remote sensing and geographical information system) to examine potential modifications occurred during the last 32 years between March 1990 and May 2022. This study used Landsat satellite images of spatial resolution 30 m to track the shoreline changes which was extracted using the Digital Image Processing software and techniques. In addition, the United States Geological Survey (USGS) developed Digital Shoreline Analysis System (DSAS) v5.2 software, an add-on tool to ArcGIS used for the statistical analysis to compute the shoreline rate of change. The linear regression rate (LRR) and end point rate (EPR) statistics were used to identify the eroding, accreting, and stable shoreline between Kattupalli coast and Kalpakkam coast of the northern Tamil Nadu coasts. This shoreline study of 106 km was carried out by dividing it into six zones (zone 1 to zone 6), and the DSAS analysis conveys that the shoreline of zone 1 (Kattupalli) and zone 2 (Ennore) shows erosion compared to other four zones. In locations where the coast is vulnerable, national mitigation measures must be implemented. [ABSTRACT FROM AUTHOR]

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Spatial Data Infrastructure (SDI) is considered as a holistic framework for effective collection, integration, discovery, sharing and delivery on a common platform for better utilization of multi-source geospatial data by global community, thereby, resulting in increased awareness of the use of geospatial data and the cooperation between decision-makers and stakeholders. Cloud computing technology can provide convenient and on-demand network access to shared computing resources that can be rapidly provisioned and released with minimal management effort or service provider interaction, and has been widely used in different applications. However, much research could not be found related to adoption of cloud computing in development of SDI at various levels from local to country. The present research is a step forward to fill this research gap by development of an open, interoperable and efficient framework for implementation of SDI at City level (acronym GeoCloud4SDI) for Prayagraj city (India) and deploying the same on OpenStack private cloud. Accordingly, multi-tier client server web GIS based SDI architecture and cloud enabled SDI services and workflow using load balancing and elastic computing architecture is developed. The novel framework for GeoCloud4SDI is developed using four layers, namely, (i) physical layer, (ii) cloud services layer, (iii) geospatial services layer and (iv) client layer. The physical layer and the cloud services layer combined together enables the access of virtualized computing resources from the cloud to enhance the performance of City level SDI. Geospatial services layer provides two different functionalities, namely, (a) management, retrieval and access of spatial data and metadata, and (b) retrieval of cloud services from cloud service layer. The performance of GeoCloud4SDI is examined by cloud enabled load balancing and elastic computing framework and the results show the response time reduced up to 50.43% along with 1.95 s performance gain for 1000 concurrent requests. The developed and implemented cloud enabled framework of GeoCloud4SDI is built via Open Geospatial Consortium (OGC) compliant interoperable service standards using Open Source Software (OSS), thereby ensuring standardisation and interoperability, and can also be adopted for other cities in India and the world. [ABSTRACT FROM AUTHOR]

Background: The areas prone to geological hazards such as liquefaction need special attention with respect to social vulnerability. Though liquefaction by itself may not result in damage, it may trigger a series of ground failures such as ground oscillation, lateral spread, loss of bearing strength, etc., which cause heavy damage. Globally, during the past few decades liquefaction hazard analysis has become one of the important criteria in seismic risk analysis and mitigation management, especially for urban areas. Greater Chennai is one of the million-plus population cities in India. The city also felt earthquakes/tremors in the past history. Method: The present study aims to assess the social vulnerability of the population density of the Greater Chennai area due to liquefaction susceptibility using GIS technology. The liquefaction susceptibility map (hazard) for the Greater Chennai was prepared by integration of geological and geomorphological parameters and analyzed over socioeconomic parameters (exposure) using an integration of GIS and AHP. Results: The result showed that around 53% of Greater Chennai's households and population are very much exposed to liquefaction hazard. Conclusions: This study can be used as a base level study for decision-making during land use planning as well as disaster mitigation planning. [ABSTRACT FROM AUTHOR]

Erosion of soil by water coupled with human activities is considered as one of the most serious agents of land degradation, posing severe threat to agricultural productivity, soil health, water quality, and ecological setup. The assessment of soil erosion and recognition of problematic watersheds are pre-requisite for management of erosion hazards. In the present study, Revised Universal Soil Loss Equation (RUSLE) integrated with remote sensing (RS) and geographic information system (GIS) has been used to assess the soil erosion in lower Sutlej River basin of Punjab, India, and prioritize the watersheds for implementation of land and water conservation measures. The total basin area was about 8577 km2 which was divided into 14 sub-watersheds with the area ranging from 357.8 to 1354 km2. The data on rainfall (IMD gridded data), soil characteristics (FAO soil map), topography (ALOS PALSAR DEM) and land use (ESRI land use and land cover map) were prepared in the form of raster layers and overlaid together to determine the average annual soil loss. The results revealed that the average annual soil loss varied from 1.26 to 25 t ha−1, whereas total soil loss was estimated to be 2,441,639 tonnes. The spatial distribution map of soil erosion showed that about 94.4% and 4.7% of the total area suffered from very slight erosion (0–5 t ha−1 year−1) and slight erosion (5–10 t ha−1 year−1), respectively, whereas 0.11% (9.38 km2) experienced very severe soil loss (> 25 t ha−1 year−1). Based on estimated average annual soil loss of sub-watersheds, WS8 was assigned the highest priority for implementation of soil and water conservation measures (323.5 t ha−1 year−1), followed by WS9 (303.8 t ha−1 year−1), whereas WS2 was given last priority owing to its lowest value of soil loss (122.02 t ha−1 year−1). The present study urges that conservation strategies should be carried out in accordance with the priority ranking of diverse watersheds. These findings can certainly be used to implement soil conservation plans and management practices in order to diminish soil loss in the river basin. [ABSTRACT FROM AUTHOR]

The Kachchh region of western India is located in a plate interior region, but falls under one of the highest seismic zones of India, having very active crustal deformation and erosion. The drainage system, as well as the geomorphic evolution of the region under a semi-arid climate zone with high to very high strength of rocks in areas with high relief, is dominantly controlled by the seismic instability associated with continual tectonics. In the present paper, we have analysed a block close to the epicentre of the 2001 Bhuj earthquake to understand the role of relative active tectonics in the evolution of domal landscape morphology. Shuttle Radar Topographic Mission Digital Elevation Model data were used to extract drainage network in the GIS platform and evaluate active tectonics using different geomorphic indices of the Habo Hill, the second largest domal structure situated in Northern Hill Range of the Kachchh region. The average cumulative weightage of different geomorphic indices provides a quantitative tool, Index of Relative Active Tectonics (IRAT), which shows significant variations in and around the Habo Dome. Activation of earlier lineaments and generation of new lineaments controlled the morphometric evolution of the fault bound block of the region to form the Habo Dome. The undulating topography in addition to the domal shape of the study area resulted from the differential movements along several active transverse faults striking NE–SW, N–S, and NW–SE, and the regional faults striking E–W (the Kachchh Mainland Fault, the Kas Fault, and the Jikadi Fault). Stress propagations from the Himalayan range in the northeast and Suleiman range in the northwest are identified to be the causative factors for active tectonics and drainage anomalies in the area. [ABSTRACT FROM AUTHOR]

With the advancement of GIS technology since its inception in 1960's, many educational institutions, government departments, public/ private sectors and individuals have started its use for the production and management of spatial data. Spatial Data Infrastructure (SDI) concept was introduced in the early1990's and provides a set of technologies, standards, protocols, policies and guidelines on the whole cycle of geospatial data production and distributions, i.e., from data capture to storage and to sharing. SDI initiative at national level, termed as National Spatial Data Infrastructure (NSDI), has been taken by different countries including India. Geospatial community is facing various challenges like handling of large volumes of geospatial data, requirement of high computing resources to process geospatial data, scalability and interoperability. Therefore, need of advanced technologies in the form of SDI and cloud computing is realized to resolve the above challenges. Cloud computing has several characteristics like scalability, elasticity and self-provisioning that offers high-performance computing resources to perform geoprocessing efficiently. The main aim of the present paper is to study SDI and its components along with analysis and comparison of NSDI of various countries as well as to conceptualize and discuss service oriented architecture of cloud enabled SDI. Several challenges of the spatial data handling and processing that occurred due to the high intensity of data and lack of processing capability can be solved by adopting proposed cloud enabled SDI architecture. This research will help geospatial community and SDI developers in various perspectives including data sharing and management, interoperability, security and reliability, fault tolerance, mass market solution, upfront cost and global collaboration. [ABSTRACT FROM AUTHOR]

This study focuses on exploring changes in Land Use and Land Cover (LULC) over Baramulla district of Kashmir using remote sensing and Geographic Information System (GIS). Linkage of LULC with evapotranspiration and precipitation is also explored in this paper. LULC were categorised into dense forest, sparse forest, water body and other classes by using geospatial satellite data from Landsat for the years 1979, 2001 to 2018. The dense forest and water body show decrease in extent from 1979 to 2018. A decrease of about 27 % has been reported from 1979 to 2018 in dense forest. Furthermore, water body shows a reduction of about 36% during the same time span. Significant changes in dense forest and water body affected the water cycle of the region. Reduction in dense forest and water body resulted in significant decrease in evapotranspiration which caused reduction in precipitation over the study area. Reduced precipitation over study area caused conversion from agriculture to horticulture. Increase of about 55% in horticulture has been reported with decrease of about 54% in agriculture over study area. Evapotranspiration from reanalysis shows coherent variation with precipitation from India Meteorological Department (IMD) gridded product. A decadal decrease of about 0.5% in evapotranspiration resulting in decrease of about 0.38% in precipitation over study area is reported. Increased horticulture causes increase in black carbon due to increased biomass which results in increased warming over study area. Changes reported in this study may cause a significant socioeconomic and environmental impact over Baramulla. [ABSTRACT FROM AUTHOR]

Floods are recurrent events in the floodplains of Coochbehar district inundating and damaging considerable quantities of standing crops and hampering the livelihoods of thousands of peoples. This paper addresses an efficient and reliable methodology for preparing flood risk map for the Coochbehar district based on two essential concepts of hazard and vulnerability. With the aid of analytical hierarchy process, a variety of hazard and vulnerability defining criteria have been weighted according to their contributions and were further processed in the geographical information system environment to observe and assess spatial characters of flood hazard index (FHI) and flood vulnerability index (FVI) that collectively have defined the flood risk index (FRI). Accordingly, the eastern, southeastern, southern, central and north-central parts of the district are prone to frequent floods while vulnerability levels are higher at areas locating particularly along the India-Bangladesh international border in the south, southeast and southwest and in some isolated clusters in the central and north-central parts. The influences of these FHI and FVI in shaping the FRI distribution were observed to be varying at places. The Tufanganj subdivision is found to be the least safe administrative unit followed by the Coochbehar Sadar, Mathabhanga and Dinhata subdivisions. The rest, i.e., the Mekliganj subdivision is observed to be relatively safe but is not immune at all. The flood risk distribution yielded the information of 58 (4.91%) settlements with higher FRI scores followed by 145 (12.29%) villages/towns with moderate and 456 (38.64%) villages/towns under low flooding risks. [ABSTRACT FROM AUTHOR]

Nowadays, preparing natural hazard maps has become essential to protect society and its infrastructure from future natural disasters. In this context, the multi-criteria semi-quantitative technique, the analytical hierarchy process (AHP) was integrated into the Geographic Information System (GIS) environment to produce a flood hazard map. The Lower Mahananda basin of India was chosen as the study area that annually suffers from damage from floods. The produced map was categorized into five classes as the zones of flood susceptibility, namely very high, high, moderate, low and very low. The corresponded zones were then examined using sensitivity analysis, and the results show there are very small differences in the spatial distribution of flood susceptible zones. The high flood hazard zones (18%) are located generally along river tracts in the lower portion of the study area that gets flooded more or less every year. The comparison found between the various flood susceptible zones, and the rise in the water level at the Mahananda conveys the accuracy and reliability of the applied methodology. Moreover, the settlement zones were identified within the high flood probable category and the sub-districts situated along the western margin have been found with inadequate medical facilities to combat the flood events. Therefore, the proposed methodology and resultant analysis of the work can be useful for local government authorities to prepare flood mitigation plans and strategies. [ABSTRACT FROM AUTHOR]

There has been excessive use of groundwater resources owing to dwindling water resource potentialities across the globe. As a result, efficient water resource management has become inevitable. However, locating the groundwater potential zones in dry and mountainous regions of many developing countries which lack suitable economic and human resources is challenging. The integrated approach of Remote Sensing (RS) and Geographic Information System (GIS) can offer a solution to this problem as it is useful to fetch first-hand information and has wider applicability. The present study focuses on delineating of groundwater potential zones in Pohru Watershed, of Jhelum Basin-Western Himalaya, India by integrating RS, GIS and Analytical Hierarchy Process (AHP). Seven thematic layers, namely lithology, geomorphology, soil, land use/land cover, slope, drainage density and lineament density have been used in this study. The parameters were weighted using AHP according to their importance in determining the groundwater potential. Five major groundwater potential zones were identified as: Very High (18.14%), High (18.17%), Moderate (19.03%), Low (41.75%) and Very Low (2.88%). The findings reveal that High and Very High Potential Zones are concentrated in the alluvial plains and the adjoining fluvio-lacustrine deposits/ Karewas. However, the highly or moderately dissected hills and the mountain ridges mostly comprise of Low and Very Low groundwater potential zones. The residual hills comprise of Medium and Low groundwater potential zones. The analysis of location and water depth of groundwater wells in the study area was found in accordance with the mapped groundwater potential zones, which validates our study. The Area Under Curve (AUC) value of Receiver Operating Characteristic (ROC) curve for AHP method was calculated as 0.7037, which corresponds to the prediction accuracy of 70.37%, indicating Moderate to High predictability of groundwater recharge zones for the study region. [ABSTRACT FROM AUTHOR]

In this study, soil loss by water in the Chambal river basin (CHB) has been estimated using Google Earth Engine and Geographic Information System platforms employing the Revised Universal Soil Loss Equation (RUSLE). Google Earth Engine, a cloud-based platform, has been used for generating land use/land cover map from the voluminous satellite remote sensing data. The observed mean rate of soil erosion in the CHB is 1.17 t/ha/yr. The study reveals that very severe type of soil erosion in the Chambal river basin is found in the gullies/ravines and barren lands with the highest mean rate of soil erosion in the gully areas at 13.44 t/ha/yr. Catchment-wise soil loss estimates suggest that the four catchments namely Kali Sindh, Lower Chambal, Upper Chambal and Parbati are experiencing much higher soil loss in comparison to others; hence these catchments are prioritised for soil conservation efforts. Sensitivity analysis of individual factors and their interaction effect indicates that LS factor is the most influential factor in the study area followed by C factor. Research highlights: Estimates soil loss by water for the first time at basin scale in the Chambal river basin (mean rate 1.17 t/ha/yr) by integrating Google Earth Engine and GIS employing RUSLE. Provides insight into the spatial pattern and status of soil erosion in the study area. Reveals very severe type of soil erosion in the areas of gullies/ravines with the highest mean rate 13.44 t/ha/yr and 5.92 t/ha/yr, respectively. LS factor is the most influential factor in the study area, followed by C factor. Prioritises Kali Sindh, Lower Chambal, Upper Chambal and Parbati catchments for soil conservation efforts based on much higher soil loss. [ABSTRACT FROM AUTHOR]

Evaluation of groundwater potential zone (GWPZ) in hilly regions is challenging due to its steep slopes, runoff, erosion, landslides, and changing land use patterns. Geographical Information Systems (GIS) and remotely sensed data are integrated with Electrical Resistivity Tomography (ERT) to identify the critical markers influencing the GPWZ. The findings suggest slope exposure, relief, fractures, and weathering are critical features of GWPZ. Hill slopes have distinct zones of varied recharge, whereas foot of a hill has an evenly distributed recharge area with significant evapotranspiration depending on landscape characteristics. The study demonstrates how integrated technologies might aid in overcoming the challenges. The linear combination method of weighted overlay is applied to integrate the GIS maps of different groundwater potential indexes (GWPI) using the analytical hierarchy process (AHP) method. The final map suggests that about 75% of the Aglar watershed in the Tehri Garhwal District, Uttarakhand, India, falls under the "moderate" to "high" GWPZ category, 17% area of the watershed falls under "very high" GWPZ, and the rest 8% of the area is under "very low" to "low" GWPZ. Subsequent integration of 2D ERT with the remote sensing (RS) and GIS outputs, yields a vertical subsurface mapping of soil heterogeneities with an effective depth of saturation that quantifies the GWPZ. The zone of saturation is mainly controlled by fractures and the weathered formation where electrical resistivity ranges between 25 and 225 Ω-m. The mapping techniques affirm that the northern aspect of the watershed has a higher potential for groundwater occurrence than the southern aspect. [ABSTRACT FROM AUTHOR]

This paper attempts to assess the vulnerability to climate change of human communities in selected mouzas of Sagar Island, South 24 Parganas District of India. A primary household survey has been conducted to collect data on socio-demographic profile, livelihood strategy, health, food, water, social network, natural disaster and climate variation indicators, were selected for Livelihood Vulnerability Index (LVI) and Livelihood Vulnerability Index-Intergovernmental Panel on Climate Change (LVI-IPCC) analyses to measure and compare the vulnerability of mouzas (administrative unit) currently suffering from frequent flooding, coastal erosion and embankment breaching on an annual basis. Secondary data collected from the Indian Meteorological Department, the Water Resources Information System of India and the Global Sea Level Observing System have been used to identify dynamics of climate change by employing statistical and Geographic Information System (GIS) techniques. A GPS survey has been conducted to identify locations of embankment breaching, and satellite images obtained from the National Aeronautics and Space Administration and U.S. Geological Survey (NASA USGS) Government website have been applied to shoreline and land use change detection, using a supervised maximum likelihood classification. The results indicate that the study area has experienced increasing temperature, changing precipitation patterns, rise in sea level, higher storm surges, shoreline change, constant land loss, embankment breaching and changing land use, which have had impact on vulnerability, particularly of poorer people. The LVI (0.48 to 0.68) and LVI-IPCC (0.04 to 0.14) scores suggest that the populations of Dhablat, Bankimnagar, Sumatinagar, Muri Ganga and Sibpur mouzas are highly vulnerable (LVI scores of 0.60 to 0.68 and LVI-IPCC scores of 0.11 to 0.14) to climate change both because the communities are more exposed to it, and because poor access to food, health facilities and water makes them extremely sensitive to it and lowers their adaptive capacity. The findings of this study could be crucial to framing further development and adaptation strategies relating to climate change, and to safeguarding the estuarine ecosystem and the vulnerable population. [ABSTRACT FROM AUTHOR]

The paper emphasis the participation of different geomorphic parameters related to various characteristics of drainage in evaluation of active tectonics of an area. For the purpose, the morphotectonic evaluations of the Son valley, central India have been carried by involving various drainage related geomorphic indices viz., stream-gradient index (SL), hypsometric integral (HI), drainage basin asymmetry (AF), valley floor height and width ratio (Vf), transverse topographic symmetry factor (T), mountain front sinuosity (Smf), drainage basin shape (BS) and sinuosity index (SI) and relative rock strength (RRS) for classification of relative index of active tectonics (RIAT) in geographic information systems (GIS) environment to understand the role of active tectonics in geomorphologic evolution of the studied region. The established RIAT classes through field validations categorize the valley into four zones such as class 1- low activity (RIAT < 2.7); class 2-moderate activity (RIAT =2.7 < 2.99); class 3- high activity (RIAT=2.99 < 3.29); and class 4-very high activity (RIAT>3.29). The sub-dendritic, rectilinear and parallel linear drainage styles in RIAT classified basin reveal the traverse of a network of seventeen faults in association with two major faults namely Son-Narmada-North Fault (SNNF) and Son-Narmada South Fault (SNSF) in variable associations of rocks and multiple types of structural elements present in the Son valley. The signature of vertical upliftments may indicate the instability tectonic activities along the identified network of faults associated with SNNF and SNSF. Hence, the study suggests variable tectonically activeness of area in the Son valley. [ABSTRACT FROM AUTHOR]

Ladakh is a famous tourist destination in India. The number of tourists visited in 1974 was 527 which increased to 327,366 in 2018. However, tourism potential has largely remained untapped due to the lack of proper dissemination of information. Nowadays, the GIS-based Tourist Information System has gained great importance among tourists, as it allows familiarizing with places and at the same time exerting profound appeal for trip planning. The purpose of the present study was to develop an interactive GIS-based Tourist Information System for Leh Ladakh. To compile database, topo-sheets and satellite imageries including CARTO-SAT, LISS-IV, and ASTER DEM was used. Besides, GPS and field surveys were conducted to generate vector data layers, viz., hotels, guesthouses, road networks, airports, parks, golf courses, water bodies, fuel stations, health amenities, banks, and ATMs. Moreover, multimedia data like video clips, audio narrations, and photographs were integrated with each feature as attribute data, to make it particularly informative for tourists and other stakeholders. The proposed GIS-based Tourist Information System is a one-time investment and can be uploaded on the internet as well as updated when needed via database updating. It is expected to bring tourists from across the world via virtual travel experience. [ABSTRACT FROM AUTHOR]

The primary objective of this research was to assess the efficiency of RS and GIS for predicting the flood risk in Raiganj Sub-division, Eastern India using the Frequency ratio, Entropy index, and Weight of evidence-information Value models. Consequently, for spatial analyses fourteen flood conditioning variables are constructed. The research region is experiencing floods consequently in the past with moderate to high intensities. The assessment demonstrates that factors such as elevation, LULC, rainfall, distance from rivers, and drainage density contributed significantly to the occurrence of floods. From the estimation, it is found that about 11.02 per cent (Frequency Ratio result), 13.90 per cent (Entropy's result), and 11.50 per cent (WofE-IV results) of the total area has very high vulnerability status respectively. Around 33 per cent to 47 per cent of the total area of each block in the subdivision is projected to be in danger of floods. The validation of the results indicates that the success rate of the presently constructed maps was 0.933 for the FR model, 0.917 for the SEI model, and 0.907 for the WofE model indicating that the frequency ratio model for mapping flood risk in the study region is more authentic, reliable, and useful for delineating flood vulnerable areas and potential flood risk sites. The findings of the analysis will help planners to develop flood prevention measures as part of regional flood risk management programs, as well as provide a foundation for future research in the study area. [ABSTRACT FROM AUTHOR]

Accurate watershed delineation and drainage system extraction are critical tasks for the hydrological and geomorphological model. Watershed morphology evaluation is very important for flood control and recovery planning. It is beneficial for understanding the basin's hydrology. In this study, the Rel river basin was selected, located in Gujarat, India. This study deals with the runoff potential in the semi-gauged Rel river basin depending on the detailed morphometric study. The Survey of India (SOI) topographic sheet (1:50000) and geographical information system (GIS) tools have been used for the detailed study in the evaluation of morphometric parameters. For accuracy in flat terrain, a topographic sheet has been used instead of DEM. Manually digitise the drainage from the SOI topographic sheet to precisely divide the watershed boundary; after that, the Rel basin has been divided into five sub-watersheds (SWs), namely, SW1 SW2, SW3, SW4 and SW5. Twenty-eight morphometric parameters have been calculated for each sub-watershed (SW). For runoff potential, twenty-one effective morphometric parameters have been selected based on previous studies. A compound factor (CF) model has been used for the SWs prioritisation. Twenty-one effective morphometric parameters have been considered in the CF model. The model results indicated that SW2 has a very-high runoff potential, and SW3 has a very-low runoff potential. The methodology developed and the results presented here will be critical in developing a comprehensive sub-watershed management plan. The work's results can better understand the topography, nature of the basin, and the delineation of a suitable soil conservation site and mitigate flash floods in the flat region. [ABSTRACT FROM AUTHOR]

Economic valuation of nature's contribution guides the decision-making process for sustainable resource management. As a pioneer effort to calculate nature's contribution to the Himalayan plateau, this study uses an inclusive wealth method and geographic information system. The statistical analysis estimates the natural capital (NC) of Ladakh, India, and discusses the policy to ensure sustainable management of the natural resources. The economic value of nature's contribution in Ladakh is increasing from the year 1990 to 2018. These economic valuations for nature's contribution include different attributes, such as forest, agricultural land, animal husbandry, fishery, minerals and fossil fuels. Nature's contribution to the economy of the study area is mainly from fossil fuels (91%) and minerals (6.9%) driven. This trend is not sustainable for long-term sustainable growth of the area. The results suggest several policies to ensure sustainable NC management in Ladakh, India. [ABSTRACT FROM AUTHOR]

The study appraised the role of geo physical and socio-economic factors in the causation of respiratory infections in Geographic Information System (GIS). Altitude zonation along with superimposition of human settlements was extracted using Digital Elevation Mode of 30 m resolution and SOI toposheets 1971 in Arc GIS software 10.2. Aerosol Optical Depth (AOD) was generated through Moderate resolution imaging spectroradiometer. Wind Chill Factor the cooling sensation caused by the combination of air temperature °C and wind speed was also calculated using recommended formula of National Weather Services United States of America (US). Geographical vulnerability index were gauged by calculating incidence rate per thousand of population, relative risk rate, odds ratio, normal standard score (Z value) of respiratory cases obtained through medical records and field survey carried under the medical supervision. Kendal ranking method and composite index techniques were used to estimate the intensity of respiratory diseases, medical block analysis to identify hotspot areas by generating disease index map in GIS using SOI toposheets 1971. With non availability of data related to socio-economic and behavioral attitudes, the desired information were carried through semi structured questionnaire. With longitudinal depression valley characterized with high ecological sensitive zone makes the habitants more vulnerable to respiratory infections through exposure to evaded chilly winter months, exposure to pollutants, poor socio-economic and behavioral environment increases the degree of vulnerability. Identifying the hotspot areas in GIS environment will be useful in formulating and executing plans at the ground level more effectively and efficiently. [ABSTRACT FROM AUTHOR]

Urbanisation induced land use and a land cover change is a proliferating phenomenon worldwide. The impacts of chaotic urban growth are all well documented. To overcome the ill effects of urbanisation, continuous monitoring and sustainable planning are the keys. As the future urban growth in India is predicted to take place in small cities of less than a million populations, it is the crucial time to plan a strategy for sustainable urban growth. Mangaluru, being a small, emerging city has the basic fertility required for urban growth. But the deficiencies of spatial data availability and lack of insight for impending urbanisation scenario would hamper the sustainable management of urban growth in the region. In this context, the current study proposes to map land use and land cover and monitor the spatiotemporal dynamics of urban growth in Mangaluru urban agglomeration, India, during 1972–2018. The present study employs techniques of remote sensing and geographic information system (GIS) and uses Landsat series of imageries. The land use and land cover changes and dynamics of urban growth have been studied using change detection, Shannon entropy, and spatial trend analysis. The study reveals that the rapid increase in the built-up area is largely induced by intense in fill growth in the core range of the city which is further corroborated by the Shannon entropy value, which indicates the compact nature of city growth. It has been found that built-up area has increased from 3.68% in 1972 to 18.79% in 2018. Agricultural land on the other hand decreased from 36.51–11.22% during 1972–2018 period. The spatial trend of change analysis represents the expansion of built-up land along with the transport network, and predominantly following a north–south course. Landsat image classification has also shown that Land use and land cover have largely changed during 1972–2018. [ABSTRACT FROM AUTHOR]

The present paper deals with morphometric analysis of Koshalya-Jhajhara (K-J) watershed, tributaries of Ghaggar in northwestern India. The area forms a rugged topography having elevation range from 399 m to 1810 m MSL. Aster DEM and SOI toposheets have been used to calculate various parameters using Geographic Information System (GIS). Linear, areal and relief aspects for morphometric analysis were calculated using GIS. Total number of streams in the watershed are 991 out of which 543 are of 1 order, 259 are of 2 order, 124 are of 3 order, 58 are of 4 order and only 7 are of 5 order. The order of stream determines the chances of flood in the stream. Higher the stream order more the probabilities of flood. The present paper indicates that K-J watershed is of 5 order and less elongated in shape having lower peak flows of longer duration with dendritic pattern and having fine drainage texture. Bifurcation ratio varies from 3 to 5 which indicate that geological structures don't have dominant influence on drainage pattern. High slope is witnessed in NE part and low slope in SW part with very low gradient ratio. Variables like stream frequency and drainage density determines the volume of the water discharge and its speed of flow in the river channels. Higher the stream frequency and drainage density more will be the probability of floods. These variables also effects temporal variations in the speed at which the water flows in the stream when flood reaches its peak. [ABSTRACT FROM AUTHOR]