Suitability Map Research Articles

An Environmental Operation of Reservoirs through Linking Ecological Storage Model and Evolutionary Optimization

This study proposes an ecological reservoir operation by linking ecological model and optimization model of reservoir. A remote sensing based ecological model was developed in which water temperature and total dissolved solids were simulated in the surface layer of reservoir. Moreover, ecological suitability maps were generated by a fuzzy inference system in which water temperature and total dissolved solids were inputs and normalized suitability was output. An ecological reservoir operation model was developed consistent with the ecological model to minimize ecological suitability loss of the reservoir as well as water supply loss. Moreover, a non-ecological operation was developed to minimize water supply loss only. Reliability and vulnerability indices and average habitat suitability in the reservoir were applied to measure the performance of the optimization model. Results indicated that reliability of water supply is reduced 6% due to using ecological operation model of the reservoir. Furthermore, vulnerability of water supply is increased more than 14% using the ecological operation. In contrast, the average habitat suitability of the reservoir is increased more than 0.35 by ecological operation which means it is remarkably effective on mitigating ecological impacts. Based on case study results, applying ecological operation of the reservoir is necessary to mitigate the ecological impacts of the reservoir on the ecological sustainability of reservoirs as well as downstream. The proposed method is able to balance the habitat requirements and humans’ needs.

Spatiotemporal analysis of seasonal trends in land surface temperature within the distribution range of Moringa peregrina (Forssk.) in Southern and Southeastern Iran.

Temperature fluctuations and related factors are among the main causes of climate change. Understanding the temporal and spatial variations in temperature can shed light on how species respond to climate change. Plants generally persist in suitable microclimates in response to environmental change; however, examining long-term temperature variations within a species' range can be challenging using field observations. Thermal remote sensing, on the other hand, provides multi-scale time-series data with good coverage and regularity to overcome the challenges associated with field observations in environmental monitoring. Although changes in land surface temperature (LST) affect climate, hydrological processes, land-atmosphere interactions, and ecological activities, this metric has not received much research attention. This study aimed to analyze changes in habitat suitability and microclimatic conditions for Moringa peregrina. Seasonal changes in LST within the distribution range of the species were also investigated. To this aim, mean seasonal LST was computed in Google Earth Engine using the daily MODIS/006/MYD13A2 product from 2003 to 2023. Subsequently, a binary habitat suitability map was created based on the true skill statistic (TSS). The Mann-Kendall test was used to analyze seasonal LST trends. Major trends in LST were quantified based on the z-score, and compatibility with habitat suitability was evaluated via GAP analysis and the Kappa index. Seasonal temperature trends were evaluated by comparing each season with the following season using binary comparison. Landforms at presence points were regarded as microclimates and the sensitivity of microclimates to LST was evaluated using two methods: Principal component analysis (PCA) was used to quantify seasonal LST heterogeneity and the random forest (RF) approach was used to evaluate the effect of environmental parameters on habitat suitability within microclimates. The Kappa index revealed a weak overlapping between suitable / unsuitable habitat and the surfaces affected by the trend of changes. Moreover, the suitable habitat of Moringa peregrina in spring, autumn and winter is spatially overlapped by areas that have shown an increasing LST trend, and the presence points have not experienced an increasing temperature trend only in the summer. The findings show that the analysis of seasonal trends in LST provides insights into the effect of LST on habitat suitability and the condition of vegetation. The current study clearly shows that seasonal changes have had a significant impact on the distribution and habitat suitability of M. peregrina, particularly during summer and winter. Improved habitat suitability and range expansion were observed throughout the year. The study also highlights the role of landforms in regulating temperature. Landforms such as local ridges with minimal temperature fluctuations and regions near the Oman Sea were identified as potential future habitats due to favorable humidity conditions.

Distribution Analysis of Green Mussels (Perna viridis) in Banyuurip Village, Ujung Pangkah District, Gresik Regency

The aim of the research was to determine the Distribution analysis of Perna viridis diversity based on the suitability map for green mussel cultivation, analysis of community perceptions and the condition of water bodies. Perna viridis aquaculture is suitable for the waters of Banyuurip village based on the variables of sea depth, sea surface temperature, chlorophyll a concentration, and substrate radiance data. Heavy metal content of Pb is located and distributed in polluted areas. It was found that the potential for green mussel aquaculture is greater in warm water habitats, i.e. closer to the coast. In addition, the northeast was identified as a suitable habitat for green mussels. The mid-ocean area in the north-west is of low suitability due to the lack of substrate and chlorophyll. Analysis of community attitudes and behaviour showed that people remain enthusiastic about green mussel farming, although green mussel shell waste remains an environmental problem. Heavy metal analysis of green mussel samples showed that green mussels are still safe for consumption. Therefore, the main conclusion is that the habitat of Perna viridis in the waters of Banyuurip Village still has potential for cultivation, but the waters must be free from pollution.

Species distribution modeling for disease ecology: A multi-scale case study for schistosomiasis host snails in Brazil.

Species distribution models (SDMs) are increasingly popular tools for profiling disease risk in ecology, particularly for infectious diseases of public health importance that include an obligate non-human host in their transmission cycle. SDMs can create high-resolution maps of host distribution across geographical scales, reflecting baseline risk of disease. However, as SDM computational methods have rapidly expanded, there are many outstanding methodological questions. Here we address key questions about SDM application, using schistosomiasis risk in Brazil as a case study. Schistosomiasis is transmitted to humans through contact with the free-living infectious stage of Schistosoma spp. parasites released from freshwater snails, the parasite's obligate intermediate hosts. In this study, we compared snail SDM performance across machine learning (ML) approaches (MaxEnt, Random Forest, and Boosted Regression Trees), geographic extents (national, regional, and state), types of presence data (expert-collected and publicly-available), and snail species (Biomphalaria glabrata, B. straminea, and B. tenagophila). We used high-resolution (1km) climate, hydrology, land-use/land-cover (LULC), and soil property data to describe the snails' ecological niche and evaluated models on multiple criteria. Although all ML approaches produced comparable spatially cross-validated performance metrics, their suitability maps showed major qualitative differences that required validation based on local expert knowledge. Additionally, our findings revealed varying importance of LULC and bioclimatic variables for different snail species at different spatial scales. Finally, we found that models using publicly-available data predicted snail distribution with comparable AUC values to models using expert-collected data. This work serves as an instructional guide to SDM methods that can be applied to a range of vector-borne and zoonotic diseases. In addition, it advances our understanding of the relevant environment and bioclimatic determinants of schistosomiasis risk in Brazil.

The main impacts of a managed aquifer recharge using AHP-weighted overlay analysis based on GIS in the eastern Wasit province, Iraq

Abstract The management of groundwater recharge success and sustainability depends on many site characteristics. It is essential to integrate the maps of site’s suitability and characteristics to identify suitable areas. The purpose of this study is to use a geographic information system (GIS) to find potential places for a project using managed aquifer recharge (MAR) in the eastern Wasit province, Iraq. Data for four effective criteria, terrain slope, Soil type/texture, drainage density, and hydrogeological efficiency, were collected, and a categorization map for each GIS criterion was subsequently created. The four steps are performed to identify this site: defining the problem, screening for the suitable areas, after the suitability map, and after the screening; the suitability mapping is divided into two zones: suitable zone and unsuitable zone. The results indicate that the site suitability for conducting aquifer recharge was classified into five categories, i.e., very high, high, moderate, low, and very low potentiality. These areas cover 26.83, 34.71, 24.98, 11.56, and 1.79%, respectively. GIS is widely acknowledged as an efficient approach for choosing MAR sites. This approach gives a better reference for analyzing suitable sites and the potential implications of applying MAR in an aquifer in similar water-stressed areas.

Determination of Potential Forest Areas in the Altınapa Dam Lake Basin

In this study, a suitability analysis has been conducted to assess the suitability of forest land use within the Altınapa Dam Lake basin, considering natural and cultural potentials, ecological structure, and forest resource values. Suitability analysis is recognized as a crucial tool for the conservation and sustainable utilization of natural and cultural resources. This analysis was carried out using Geographic Information Systems (GIS) and the Analytic Hierarchy Process (AHP). The result of this analysis is a suitability map, which indicates that approximately half of the basin is considered suitable for forest areas. This finding highlights the importance of forested areas in preserving and enhancing the ecological balance of the basin.

GIS-based Land Suitability Evaluation for Sesame (Sesamum indicum L.) Production using Agro-climatic Indices in the Semi-arid Areas of Tigray

Introduction: Climate is the most important factor in determining crop production systems in Ethiopia. However, land suitability evaluation using climate variables for specific crops has been barely conducted to demonstrate the suitability of a location for the growth and yield of the crop. This study was, therefore, conducted to analyze land suitability evaluation for sesame production using agro-climatic variables by employing a multi-criteria approach. Materials and Methods: Temperature (maximum, minimum, and average temperature), annual rainfall, elevation, slope, growing degree days (GDD), and length of growing period were classified, and re-classified. Finally, a suitability map overlay was produced using ArcMap version 10.3.1 Results and Discussion: The results indicated that areas with higher elevations, like Adi Remets being 1860 meters above sea level, were classified as moderately suitable, whereas the majority of the study area was suitable for sesame production. After re-classifying the climate variables, elevation, and GDD, a suitability map overlay was produced for sesame production. The overall suitability map showed that areas around Humera, Dansha, Sheraro, Badime, Adigoshu, and some parts of Dedebit, Adiremets, and Maygaba were found from highly suitable to suitable, with 1,024,543.2 and 664,545.5 hectares of land, respectively. There has been no evidence with regards to land suitability classification for sesame production in the study area; hence, the results obtained in this study demonstrated the majority of the cultivated areas in the western and northwestern zones of Tigray to be high to moderately suitable for sesame production. Conclusion: Based on the results, a land suitability map representing a homogenous environment for improved sesame production was produced using a multi-criteria approach in the northwestern and western zones of Tigray. While the results obtained in this study might be helpful for agricultural experts, researchers, decision-makers, and farmers for crop intensification and expansion strategies, they can explicitly help in decisions in the marketing processes with respect to the crop’s value chain and provide a homogenous environment in the study area.

Unlocking renewable energy potential: A case study of solar and wind site selection in the Kasserine region, central‐western Tunisia

AbstractDeveloping wind and solar photovoltaics on a large scale requires substantial financial investments, making it crucial to identify the most suitable locations beforehand. To address this issue, a spatial analysis is carried out to determine the most potential sites for hosting large‐scale solar photovoltaic and wind systems in the region of Kasserine, central‐western Tunisia. To this end, an integrated model based on Step‐wise Assessment Ratio Analysis (SWARA), Decision‐Making Trial and Evaluation Laboratory (DEMATEL), and Geographic Information System is proposed. An extensive literature survey is conducted to establish suitability criteria and constraints. The SWARA‐DEMATEL is used to assign weights and capture the interdependencies among the considered criteria, while the raster calculator tool from the ArcGis 10.8 software is utilized to extract the final suitability maps. The obtained results indicate that the region of Kasserine exhibits great solar and wind potential, with areas of 635 and 467 km2 extremely fit for installing solar and wind systems, respectively. Furthermore, 349 km2 are identified as potential locations for hosting solar‐wind hybrid systems. Considering these outcomes, policymakers can take the initiative to accelerate the deployment of these facilities, which would assist the country in achieving its plans by 2030.

Novel GIS-based fuzzy TOPSIS and filtration algorithms for extra-large scale optimal solar energy sites identification

Solar energy stands as an increasingly attractive and environmentally responsible energy source, possessing the potential to meet the burgeoning power needs of the Sarawak region. This paper proposes a novel methodology that combines Geographic Information System-based fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and filtration algorithms to identify the top 100 optimal Solar Energy Sites (SES). The research encompasses the extra-large scale potential SES comprising 19,237 coordinated data points. It evaluates SES based on 12 diverse criteria spanning climatic conditions, technical feasibility, accessibility, environmental considerations, and social factors. This research employs a meticulous double-layer filtration process to systematically eliminate unsuitable locations, resulting in a refined list of 1,862 potential SES. Subsequently, the fuzzy TOPSIS algorithm has further narrowed down the selection to the top 100 SES, constituting the core results of this research. The results reveal an interesting distribution of the identified SES, which mainly clustered in 3 huge categories (Kuching-Samarahan, Sibu-Kapit-Mukah and Bintulu-Miri). The identified 100 SES possess high closeness coefficients, which range from 0.7 to 0.85, where 1 indicates the best solution of the fuzzy TOPSIS algorithm. Additionally, the paper presents a spatial distribution analysis of the top-ranking sites across various divisions and districts. To validate the results obtained from the proposed model, a solar suitability map has been developed in ArcGIS Pro. When comparing the results from the proposed model to those obtained from the solar suitability map, most SES have consistent relative percentages, with only one SES falling below 50 %. To provide an overview of the similarity between the two models, the average relative percentage is computed at 69.01 %, signifying the proximity of SES to the optimal value of the solar suitability map. Furthermore, the developed source code in this research exhibits flexibility, featuring filtration algorithms that can accommodate any raster maps. It serves as an asset for researchers interested in conducting comprehensive large-scale SES identification in future case studies.

Combined use of BWM-TOPSIS methods in the selection of thermal power plant installation site in the Karapinar/Turkiye Region, at risk of sinkhole formation.

With the rapidly increasing world population and the need for industrialization, energy supply has become an important global problem. A significant part of the world's energy needs is provided by fossil fuels. About half of all global coal deposits are low-quality coals, including lignite. Karapınar/Konya, also the study area, has Turkiye's second richest lignite reserve. The region's lignite reserve can be used in thermal power plants for electricity generation in terms of its nature and the amount is an important opportunity to meet the energy demand for both region and country. The region contains many sinkholes, and the potential for the formation of new sinkholes makes the site selection for thermal power plants in the region an even more strategic decision. This study aims to propose the most suitable thermal power plant site for the region by using Multi-Criteria Decision Making methods and Geographic Information Systems in an integrated way. Within the scope of the study, a total of twelve sub-criteria were taken into consideration under the main criteria of Geological, Economic and Environmental. The Best-Worst Method was applied to determine the criteria weights, and by using the weights, a suitability map for the thermal power plant installation site was produced and candidate regions were determined. TOPSIS was applied to determine the most suitable location among the candidate regions. The Candidate Region in the easternmost part of Karapinar district was chosen as the most suitable site for the thermal power plant installation.

Application of AHP and geospatial technologies to assess ecotourism suitability: A case study of Saint Martin's Island in Bangladesh

The study uses the Geographical Information System (GIS) to identify and assess the potentially eco-friendly, sustainable tourist locations on Saint Martin’s Island, Bangladesh. Key informant interview (KII) and the Analytical Hierarchy Process (AHP) have been used to establish a resource inventory and to set a number of sustainable tourism requirements. The suitability map for eco-friendly sustainable tourism was subsequently developed, based on the respective weights deriving from the linear combination of criteria and factors. From the analysis report, it was revealed that the areas of suitable, moderately suitable, less suitable and not suitable were 30%, 32%, 10% and 28% respectively. In this study, attempts were made to specify the degree of ecotourism suitability in the investigated area. The outcome might be useful for the development of resilient policy to design ecotourism. Similarly, this analysis can be used as a guideline for assessing eco-friendly sustainable tourism in other regions. It may also act as a point of departure for potentially more nuanced research.

Spatial multi-criteria decision making approach for wind farm site selection: A case study in Balıkesir, Turkey

This study presents a spatial multi-criteria decision making (SMCDM) approach based on geographic information system (GIS) for determining the sites that have potential for wind farm installation in Balıkesir, Turkey. Topographical, structural, climatic, and environmental criteria consisting of wind speed, land cover type, slope of terrain, and distance from substations, road networks, settlements, fault lines, electricity grid, and seaports are considered in the approach. Weights, derived from evaluation involving the use of the analytical hierarchy process (AHP) questionnaire, and scored criteria maps, are used in creation of a wind farm suitability map. The results of the study demonstrate that 2.34 % of the total area under consideration is in the most suitable class, while 9.34 % is in the next most suitable class. The study introduces the seaport criterion for the first time in onshore wind turbine site selection. The findings show that considering the seaport criterion provides a more realistic approach of feasible wind turbine site selection. This is clearly seen in the 13 % decrease in the most suitable area. When the wind farm suitability map is evaluated on a district scale, Bandırma takes first place compared to other districts. A sensitivity analysis performed with equal criteria weights indicates that the results are generally reliable.

THE ENVIRONMENTAL PARAMETERS SUITABILITY FOR MULTISPECIES-BASED MARICULTURE IN PONGOK ISLAND WATERS, BANGKA BELITUNG

Pongok Island possesses small islands surrounded by waters with some primary commodities of sea farming. Seeking appropriate locations for marine aquaculture is a careful planning step to acquire optimal results. The sustainability of sea farming areas should be set based on considering species for easy implementation. This research aimed to analyse the area's suitability for aquaculture activities of seaweed cultivation, rearing groupers, and lobsters in floating net cages, and pearl oyster farming. This research occurred from June to November 2022 in Pongok Islands, South Bangka Regency, Indonesia. The method used in this research consisted of parameters weighting and scoring for cultivating seaweeds, groupers, or lobsters utilizing floating net cages and pearl oysters. Sea water samples analysis was processed in the Marine Science Laboratory of Bangka Belitung University and PT Global Quality Analytical, Bogor – West Java. Collected data were then scaled based on expert justification of scaling priority on aquaculture suitability. The mapping area of sea farming locations based on potential resources was then determined using map software. This research indicates that cultivating seaweeds is recommended to be established in two stations, 1 (149.79 ha) and 2 (186.46 ha), that are very suitable (S1) and the suitable (S2) categories, respectively. Station 3 (325.41 ha) and 4 (4.11 ha) are grouped into very suitable (S1) categories for pearl oysters and groupers or lobsters using floating net cages, respectively. The total estimate for sea farming in the waters of Pongok Island is 665.77 ha. Allocating seawater spaces should be assigned for sustainable fishery management. Maps of area suitability for sea farming can obviate conflicts in seawater areas.

A Geospatial Approach to Identify and Evaluate Ecological Restoration Sites in Post-Fire Landscapes

Wildfires are a pervasive natural phenomenon in Mediterranean forest ecosystems, causing significant ecological imbalances that demand immediate restoration efforts. The intricacy of reinstating the ecological balance necessitates a proactive approach to identifying and assessing suitable restoration sites. The assessment and investigation of the most suitable restoration sites is of particular importance both for the relevant authorities and for planning and decision making by the state. This study proposes the development of a user-friendly model for evaluating and identifying the most suitable restoration sites immediately after a fire, using geoinformation technologies. For the purposes of demonstrating the method’s applicability, the 2016 fire of “Prinos”, Thasos, Greece, an area that has been repeatedly affected by forest fires, was chosen as a case study. The methodology evaluation was carried out by applying the weighted multicriteria decision analysis method (MCDAM) and was based on a number of variables. The analysis, processing and extraction of the results were performed using primarily remote sensing datasets in a geographical information system (GIS) environment. The methodology proposed herein includes the classification of the individual criteria and their synthesis based on different weighting factors. In the final results, the restoration suitability maps are presented in five suitability zones based on two different scenarios. Based on this study, the integration of geospatial and remote sensing data offers a valuable and cost-effective means for promptly assessing post-fire landscapes, with the aim of identifying suitable restoration sites.

Solar PV technologies selection for the design of photovoltaic installations in Mexico based on the analysis of meteorological satellite data from the region

Mexico’s expansive territory spans diverse climatic conditions, which directly influences the selection of commercial photovoltaic technologies. This study utilizes solar irradiance, temperature, and cloud index data (derived from satellite sources) to generate a suitability map for commercial solar panel technologies through the Analytical Hierarchy Process-Geographical Information Systems methodology. The map illustrates that chalcopyrites and cadmium telluride emerge as the most suitable technologies in 47.12% of the national territory. Following closely behind is amorphous silicon, covering 30.45%, while monocrystalline and polycrystalline silicon account for 22.43%. The primary objective of this paper is to guide the proper selection of solar panel technology types that align optimally with Mexico’s climatic conditions. This strategic approach aims to strengthen the planning and viability of photovoltaic solar energy projects nationwide.

Predicting invasive species distributions using incremental ensemble-based pseudo-labeling

Control strategies for preventing the spread of invasive species require their accurate geographical distribution. Species distribution models (SDMs) that can predict potential habitats of invasive species and thereby derive habitat suitability maps have become a valuable tool for supporting regulatory strategies. To date, machine learning (ML)-based approaches have outperformed profile and statistical-based approaches in terms of species distribution prediction accuracy. However, ML-based approaches often suffer from poor predictive performance when there is insufficient labeled data. Recently, pseudo-labeling (PL), a semi-supervised learning method, has been proposed to alleviate this problem, but pseudo-labels generated using a single-teacher model with very few labeled data points are generally biased and not suitable for training SDMs. In this paper, we propose a novel prediction scheme for invasive species distributions using incremental ensemble-based PL (SDP-EPL). We first build an ensemble-based teacher using multiple conventional SDMs and then incrementally construct a training set, starting with very few labeled data points, by repeating the following process: (i) generating pseudo-labels for unlabeled data using the teacher model, (ii) appending the pseudo-labeled data representing high or low habitat suitability to the training set, and (iii) training the teacher model using the updated training set. We then train a student SDM using the training set. Based on extensive experiments using citizen science datasets for three species, we show that the proposed scheme outperforms other commonly used SDMs in terms of diverse evaluation metrics and achieves performance improvements of up to 14.61% and 5.45% compared to the baseline and state-of-the-art models, respectively. We also demonstrate the effectiveness of the ensemble teacher model and incremental labeling in terms of predictive accuracy.

Potential development of tropical fruits on Kundur Island, Riau Islands Province, Indonesia

Kundur Island has incredible potential for tropical fruits in Riau Islands Province. Land utilization for tropical fruit planting must be supported by land resource data, such as maps of characteristics and land suitability, to optimize tropical fruit production. This study aimed to evaluate the land suitability and determine the dominant limiting factors for tropical fruit growth and development. Land suitability was evaluated by matching the land characteristics, soil, and climatic requirements for durian, rambutan, and duku. The land suitability classes for durian, rambutan, and duku on Kundur Island are mostly marginal (S3), covering an area of 28,361 ha (90.51%), while the rest are moderately suitable (S2) and unsuitable (N). The limiting factors are drainage, root conditions influenced by peat thickness, nutrient retention, nutrient availability, depth of sulfide material, and erosion hazards. Improvements can be made by managing drainage, using cover crops, fertilization, and providing soil ameliorants. Treatments to increase land suitability must be implemented to enhance the potential of durian, rambutan, and duku plantations to be suitable (S1) or moderately suitable (S2). Land potential development for durian, rambutan, and duku is conducted by prioritizing environmental aspects and land sustainability.

Topography and land suitability analysis in the integrated waste management site building (IWMB) at the University of Lampung

Slope class maps are products resulting from the topographical analysis process. The results of this topographical analysis can also be used as a basis for land suitability analysis, supported by land cover maps and indicative maps of built and undeveloped areas. The Integrated Waste Management Site Building (IWMB) at the University of Lampung was used as an AoI (Area of Interest) or a study area for making land suitability maps. The AoI in the Unila campus area was 4.11 hectares. This study aims to explore the capabilities of drones as a complementary vehicle for field survey data to find out topographical data and to analyze spatial suitability plans. The method used in this research was an interpretation of aerial photographs and analysis using the ArcGIS application. From the slope class analysis results, the research location is included in the flat class category to be safe for all buildings (0-8%). For classification in spatial suitability analysis, the area is divided into 8 development plans to provide sustainable green open spaces in the campus area. Based on the research results, information was found that drone technology can assist visual interpretation in an area’s development plan.

Groundwater management in the face of climate change: enhancing groundwater storage in the alluvium aquifer of Wadi Araba, Jordan, through GIS-based managed aquifer recharge and groundwater MODFLOW

Abstract Groundwater is critical in countries such as Jordan, yet demand exceeds availability due to population expansion and arid conditions. The goal of this research is to address water scarcity and adapt to reduced rainfall by investigating the soil aquifer and evaluating the efficiency of managed aquifer recharge (MAR). The Wadi Araba Basin's alluvium aquifer is particularly important and contains a groundwater divide, with water flowing towards the Red Sea to the south and the Dead Sea to the north, as determined by rigorous modelling and scenario analysis. Precipitation infiltration is an important consideration in groundwater budget modelling. This study employs 12 monitoring wells to establish an acceptable relationship between estimated and observed water levels. Furthermore, the study creates a MAR suitability map, which evaluates eight potential MAR locations in the Wadi Araba region. According to forecasted scenarios, implementing MAR in conjunction with increased precipitation recharge has the potential to ameliorate the consequences of decreased rainfall in the model region. The plan aims to raise the water table in three areas by 1.96–3.12%, providing realistic solutions to enhance water availability and adapt to climate change.

Assessment of the solar energy–agriculture–water nexus in the expanding solar energy industry of India: An initiative for sustainable resource management

The rapid expansion of solar energy in India poses challenges in the context of cropland encroachment and water-resource scarcity. To help address these challenges, we used open access satellite observations and GIS technologies over Earth Engine platform to devise the Solar Panel Index (SPI) for efficient detection of solar farms, achieving a Land use/Land cover classification accuracy of 89 %. We have used cropland, water availability, power grid and land surface temperature data-sets for generation of land suitability map. Sentinel-2 data-sets along with SPI were used to develop solar farm locations and their estimated installed capacity within the study area. The outcomes from the study depicted that over 40 % of all solar farms in the country are located on agricultural land, with the highest seen in Karnataka (73.55 %) followed by Tamil Nadu (68.81 %). Furthermore, high installed capacity coincides with low groundwater depths, exacerbating local water strain. Madhya Pradesh was found to have almost no power plant located within 5 km of surface water bodies. Our findings emphasize the significance of the solar-agriculture-water (SAW) nexus for sustainable development. Using high-resolution Land Suitability Map (LSM) as a decision-making criteria for allocating land for power generation reveals that Rajasthan holds the highest potential for solar energy installation. Our integrated approach considering the interplay between solar-energy production, agriculture, and water-resource management contributes to the sustainable growth of the solar-energy sector and regional development.