Groundwater potential mapping of Tawi River basin of Jammu District, India, using geospatial techniques

A top-down spatial scenario approach for identifying the locations of rainwater harvesting sites in an urban region

Alternative water sources are necessary in developing nations because surface water is not always accessible, and groundwater is depleted. In such situations, rainwater harvesting is considered a promising sustainable water resource management solution. Numerous studies have been conducted to determine suitable locations for rainwater harvesting (RWH) using bottom-up approaches applied to large watersheds. The bottom-up methods begin with various geographic criteria and end with regions suitable for RWH intervention, even considering the distance from settlements to be one of the criteria, excluding urban areas from RWH site identification. This study developed a top-down methodology that began with the distributed pinpoint locations of potential RWH sites, as determined by distributed flow accumulation values produced from a digital elevation model (DEM), and then filtered out the sites based on various criteria in the context of urban areas. The flow accumulation values were apportioned according to the flow-contributing area of each RWH site. Five flow-contributing areal scenarios corresponding to 1 km2, 2.5 km2, 5 km2, 7.5 km2, and 10 km2 were considered in this study, as it is challenging to choose a suitable location for RWH sites in urban zones for efficient water storage owing to a variety of land uses. Based on this technique, a case study was conducted in Jaipur, Rajasthan, India, where it was found that the volumetric potential of rainwater storage is maximum (403,679,424.9 cu. m) for 1 km2 and minimum (169,951,322 cu. m) for 10 km2 flow contributing areal distribution per RWH site.

Mapping coastal groundwater potential zones using remote sensing based AHP model in Al Qunfudhah region along Red Sea, Saudi Arabia

Due to the increases in agriculture and industry sector as well as high population, lack of water is becoming a major problem in the Middle East especially in arid regions. Saudi Arabia needs more groundwater research and explorations because of its higher water use and no source of freshwater. Assessing groundwater zonation in semi-arid locations is essential due to the significant degree of variation in groundwater depth, aquifer features, topographical characteristics, and insufficient precipitation. Mapping prospective groundwater zones in Al Qunfudhah region of southwestern Saudi Arabia has utilized the capability of the multi-criteria decision approaches (MCDA), and the Geographic information system (GIS). We have used the analytical hierarchy process (AHP) as one of the MCDA that is applied to achieve the objective of the current study by integrating twelve controlling factors. These factors are represented by the thematic layers; slope, precipitation, soil type, land use/cover (LULC), drainage density (DD), normalized difference vegetation index (NDVI), curvature, topographic position index (TPI), Terrain Ruggedness Index (TRI), drainage density (DD), and Lineament Density (LD). These thematic layers are combined with GIS to delineate the zones of groundwater potentialities. All factors were classified and weighted according to their importance and its effect on groundwater zones. Their normalized weights were evaluated using a pairwise comparison matrix. The present study shows that the groundwater potential zones (GWPZs) map is represented by five groups ranging between a very high zone with an area of 23781.06 Km2 that represents 4.04 % of the studied area, and a very poor GWPZ with an area of 182944.4 Km2 that represents 31.09 % of the studied area. The AHP model suggests that lineament density, slope, and drainage density are more important for determining the groundwater potentiality than other physiographic factors. The study's findings will be helpful in developing practical strategies for the region's groundwater supply. This analysis shows how the methodology may be used to study a broad coastal groundwater basin. The current study will give the decision makers to select suitable sites with a high groundwater potential.

Assessment of urban sprawls, amenities, and indifferences of LST and AOD in sub-urban area: a case study of Jammu

Urbanization, particularly in peri-urban areas, often results in critically transforming the regional land use and land cover (LULC). The increased built-up in peri-urban areas affects the regional accessibility of residents of urban clusters to requisite amenities and severely affects the regional environment, as observed in the case of Jammu district situated in the foothills of the Indian Himalayas. The present study is aimed at assessing the rise of urban sprawls in Jammu district over the past two decades and how the urbanization has affected the lag in the number of amenities corresponding to the urban growth based on qualitative parameters. Further, a parameterization scheme is developed to assess the amenities quality. A comparison is made with Indore, a planned smart city, to assess the status of urbanization and residential quality based on an amenity index. The study also investigates the indifferences observed in some of the climate variables in the urban and sub-urban settings of the Jammu district. The investigation is conducted through a multi-ring buffer analysis approach utilizing the land use land cover (LULC) products based on Landsat 8/7 satellite imagery of 2002, 2013, and 2021. The indifferences in the settings are analyzed using MODIS aerosol optical depth (AOD) and land surface temperature (LST) products. The analysis leads to determination of critical urban parameters including the urban area, density, and growth rate, revealing significant urbanization at 25-27 km from the city center. Significant indifferences are observed in urban and sub-urban areas indicating higher rise in LST and AOD, particularly in the recent decade. These investigations provide critical information to urban and climate solution authorities for planning and management, particularly in critically endangered areas.

An integrated groundwater resource management approach for sustainable development in a tropical river basin, southern India

Evaluation of aquifer potential is essential, as the potable water demand has increased globally over the last few decades. The present study delineated different zones of groundwater potential and groundwater quality of the Kallada River basin (KRB) in southern India, using geo-environmental and hydrogeochemical parameters, respectively. Geo-environmental variables considered include relative relief, land use/land cover, drainage density, slope angle, geomorphology, and geology, while hydrogeochemical parameters include pH, electrical conductivity (EC), Cl-, Fe3+, and Al3+ concentrations. Analytical hierarchy process (AHP) was used for categorizing groundwater potential and quality zones. Nearly 50% of KRB is categorized as very high and high groundwater potential zones, occupying the western and midland regions. The central and west-central parts of KRB are characterized by excellent groundwater quality zones, while the eastern and western parts are characterized by good and poor groundwater quality zones, respectively. By integrating the groundwater potential and groundwater quality, sustainable groundwater management is observed to be necessary at about 54% of the basin, where site-specific groundwater management structures such as percolation ponds, injection wells, and roof water harvesting have been proposed using a rule-based approach. This integrated groundwater potential-groundwater quality approach helps policymakers to implement the most suitable management strategies with maximum performance.

Identification of suitable zones and sites for rainwater harvesting using GIS and multicriteria decision analysis

Identifying suitable zones for surface water storage and groundwater recharge is needed to enhance irrigation water availability. This study was undertaken to map rainwater harvesting (RWH) potential zones using geospatial tools and analytic hierarchy process (AHP). The suitable locations for RWH were also mapped using the Boolean logic concept. The surface runoff is a vital factor to demarcate the appropriate zones for RWH. The curve number approach was used to estimate the surface runoff potential. The runoff coefficient (RC) map was generated based on rainfall and surface runoff depth. Weights have been allocated to selected themes of RC, drainage density, and slope. The themes were integrated using geographic information system (GIS) and AHP to demarcate the suitable zones for RWH. The derived RWH potential map was categorized into zones like "very good," "good," "moderate," "poor," and "very poor" with an aerial extent of 14.3%, 24.7%, 28.3%, 20.2%, and 12.6%, respectively. The area suitable for farm ponds was found to be about 9% (408 km²), 13% (329 km²), and 4% (244 km²) in Mirzapur, Chandauli, and Sonbhadra districts, respectively. Furthermore, 22, 15, and 21 locations were found suitable for check dams in Mirzapur, Chandauli, and Sonbhadra districts, respectively. At a large scale, effective planning of water management strategies based on multicriteria decision analysis and GIS offers increased availability of surface and groundwater resources and may help for enhancing the agricultural land use options. The higher resolution maps may be further utilized to plan RWH strategies at village level.

Delineation of Groundwater Potential Zones (GWPZs) in a Semi-Arid Basin through Remote Sensing, GIS, and AHP Approaches

Groundwater occurrence in semi-arid regions is variable in space and time due to climate patterns, terrain features, and aquifer properties. Thus, accurate delineation of Groundwater Potential Zones (GWPZs) is essential for sustainable water resources management in these environments. The present research aims to delineate and assess GWPZs in a semi-arid basin of San Luis Potosi (SLP), Mexico, through the integration of Remote Sensing (RS), Geographic Information System (GIS), and Analytic Hierarchy Process (AHP). Seven thematic layers (geology, lineament density, land use and land cover, topographic wetness index (TWI), rainfall, drainage density, and slope) were generated in raster format. After the AHP procedure and rank assignment, the thematic layers were integrated using the raster calculator to obtain the GWPZs map. The results indicated that 68.21% of the area is classified as low groundwater potential, whereas 26.30% is classified as moderate. Validation was done by assessing the water residence time data from 15 wells distributed in the study area. Furthermore, the Receiver Operating Characteristics (ROC) curve was obtained, indicating a satisfactory accuracy prediction (AUC = 0.677). This study provides valuable information for decision-makers regarding the conservation and sustainable management of groundwater resources.

AHP and TOPSIS based flood risk assessment- a case study of the Navsari City, Gujarat, India

Flooding is one of the major natural catastrophic disasters that causes massive environmental and socioeconomic destruction. The magnitude of losses due to floods has prompted researchers to focus more on robust and comprehensive modeling approaches for alleviating flood damages. Recently developed multi-criteria decision making (MCDM) methods are being widely used to construct decision-making process more participatory, rational, and efficient. In this study, two statistical MCDM approaches, namely the analytical hierarchy process (AHP) and the technique for order preference by similarity to ideal solution (TOPSIS), have been employed to generate flood risk maps together with hazard and vulnerability maps in a GIS framework for Navsari city in Gujarat, India, to identify the vulnerable areas that are more susceptible to inundation during floods. The study area was divided into 10 sub areas (i.e., NC1 to NC10) to appraise the degree of flood hazard, vulnerability and risk intensities in terms of areal coverage and categorized under 5 intensity classes, viz., very low, low, moderate, high, and very high. A total of 14 flood indicators, seven each for hazard (i.e., elevation, slope, drainage density, distance to river, rainfall, soil, and flow accumulation) and vulnerability (i.e., population density, female population, land use, road network density, household, distance to hospital, and literacy rate) were considered for evaluating the flood risk. Flood risk coverage evaluated from the two approaches were compared with the flood extent computed from the actual flood data collected at 36 random locations. Results revealed that the TOPSIS approach estimated more precise flood risk coverage than the AHP approach, yielding high R² values, i.e., 0.78 to 0.95 and low RMSE values, i.e., 0.95 to 0.43, for all the 5 risk intensity classes. The sub areas identified under "very high" and "high" risk intensity classes (i.e., NC1, NC4, NC6, NC7, NC8, and NC10) call for immediate flood control measures with a view to palliate the extent of flood risk and consequential damages. The study demonstrates the potential of AHP and TOPSIS integrated with GIS towards precise identification of flood-prone areas for devising effective flood management strategies.