Geospatial Technology for Sustainable Agricultural Water Management in India—A Systematic Review

Geomatics, Journal Year: 2024, Volume and Issue: 4(2), P. 91 - 123

Published: March 22, 2024

Effective management of water resources is crucial for sustainable development in any region. When considering computer-aided analysis resource management, geospatial technology, i.e., the use remote sensing (RS) combined with Geographic Information Systems (GIS) proves to be highly valuable. Geospatial technology more cost-effective and requires less labor compared ground-based surveys, making it suitable a wide range agricultural applications. Effectively utilizing timely, accurate, objective data provided by RS technologies presents challenge field management. Satellite-based measurements offer consistent information on hydrological conditions across extensive land areas. In this study, we carried out detailed focused addressing issues India through application GIS technologies. Adhering Preferred Reporting Items Systematic Reviews Meta-Analysis (PRISMA) guidelines, systematically reviewed published research articles, providing comprehensive analysis. This study aims explore practices goal enhancing their effectiveness efficiency. primarily examines current Indian sustainability. We revealed that considerable has used multispectral Landsat series data. Cutting-edge like Sentinel, Unmanned Aerial Vehicles (UAVs), hyperspectral have not been fully investigated assessment monitoring resources. Integrating allows monitoring, offering valuable recommendations effective

Language: Английский

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Addressing water scarcity challenges through rainwater harvesting: A comprehensive analysis of potential zones and model performance in arid and semi-arid regions–A case study on Purulia, India

HydroResearch, Journal Year: 2024, Volume and Issue: 7, P. 201 - 212

Published: Jan. 1, 2024

Water scarcity in arid and semi-arid regions is a critical global concern, necessitating innovative solutions to address increasing water demands these vulnerable areas. This study focuses on tackling this challenge by identifying classifying rainwater harvesting zones based their potentiality comparing the performance of two machine learning models, Artificial Neural Network (ANN) Random Forest (RF), for optimizing strategies. The area Purulia, district India. Extensive literature review was conducted identify key factors influencing harvesting. Open-source remotely sensed data were employed pinpoint potential zones. A multi-criteria decision-making technique applied assess importance various factors. Results indicated that rainfall, slope, runoff potential, soil, land cover, drainage density are six crucial selecting suitable locations. Approximately 2% unsuitable, 8% poorly suitable, 33% moderately 45% highly remaining 12% extremely Purulia. Two predictive models developed, with RF algorithm demonstrating nearly 99% accuracy. Finally, remedial techniques mitigating through discussed separately urban rural research article embraces comprehensive approach water-related concerns, offering replicable framework applicable globally, specific focus regions.

Language: Английский

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Scaling Up Indigenous Rainwater Harvesting: A Preliminary Assessment in Rajasthan, India

Water, Journal Year: 2023, Volume and Issue: 15(11), P. 2042 - 2042

Published: May 27, 2023

Rainwater harvesting (RWH) has the potential to enhance sustainability of ground and surface water meet increasing demands constrained supplies, even under a changing climate. Since arid semi-arid regions frequently experience highly variable spatiotemporal rainfall patterns, rural communities have developed indigenous RWH techniques capture store rainwater for multiple uses. However, selecting appropriate sites RWH, especially across large regions, remains challenging since data required evaluate suitability using critical criteria are often lacking. This study aimed identify essential develop methodology select in Rajasthan (India). We combined GIS modeling (multicriteria decision analysis) with applied remote sensing as it assess land RWH. As assessment criteria, spatial datasets relating use/cover, rainfall, slope, soil texture, NDVI, drainage density were considered. Later, weights assigned each criterion based on their relative importance system, evidence from published literature, local expert advice, field visits. analyses used create maps (high, moderate, unsuited maps). The sensitivity analysis was also carried out identified check inadequacy inconsistency among preferences. It estimated that 3.6%, 8.2%, 27.3% area highly, moderately, unsuitable, respectively, Chauka implementation. Further, results show LULC is sensitive NDVI least parameter selected region, which suggests weight these parameters more likely decide outcome. Overall, this shows applicability GIS-based MCDA approach up-scaling traditional systems its other similar conditions, where offers increase resource availability reliability support livelihoods.

Language: Английский

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A holistic multi-tiered decision framework for evaluating rainwater harvesting potential in arid regions: A case study of the southeastern basin of Djibouti

Groundwater for Sustainable Development, Journal Year: 2024, Volume and Issue: 25, P. 101090 - 101090

Published: Jan. 13, 2024

Language: Английский

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A GIS based approach for identifying potential sites for harvesting rain water in the Hathamati River Basin, India

ISH Journal of Hydraulic Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 12

Published: Jan. 29, 2025

Language: Английский

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Multi‐Criteria Analysis for Effective Rain Water Harvesting Site Identification in Konso Zone, Ethiopia

Global Challenges, Journal Year: 2025, Volume and Issue: 9(4)

Published: March 7, 2025

Abstract The Konso area of southern Ethiopia has limited resources and is highly vulnerable to climate change. Traditional agriculture practices in this region are adversely affected by water scarcity. purpose study determine the most effective site for rainwater harvesting (RWH) through multi‐criteria analysis combined with Geographic Information Sysytem. decision‐making criteria used included rainfall, land cover, curve number, topographic wetness index, slope, distance from agriculture, lineament density, geology, road city distance. These categorized into five suitability levels based on their significance using an analytical hierarchical process (AHP). also mapped restricted area, which includes built‐up accounting ≈6% total area. very high RWH ≈658 km2, representing 28.3% model validated cross‐checking existing ponds appropriate map. It found that located within moderately suitable zones, 92.6% This research highlights effectiveness integrating MCA GIS identifying sites, especially arid, semi‐arid, data‐scarce areas. weighted overlay (WOP), available data, methods utilized achieve goal.

Language: Английский

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Spatio-temporal assessment of rainwater harvesting sites using geospatial techniques in Ewaso Ng’iro south river basin

Sustainable Water Resources Management, Journal Year: 2025, Volume and Issue: 11(2)

Published: March 13, 2025

Language: Английский

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GIS-Based Modeling for Water Resource Monitoring and Management: A Critical Review

Springer geography, Journal Year: 2025, Volume and Issue: unknown, P. 537 - 561

Published: Jan. 1, 2025

Language: Английский

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Rainwater Harvesting Site Selection for Drought-Prone Areas in Somali and Borena Zones, Oromia Regional State, Ethiopia: A Geospatial and Multi-Criteria Decision Analysis

Water, Journal Year: 2024, Volume and Issue: 16(13), P. 1789 - 1789

Published: June 25, 2024

Rainwater collection systems play a crucial role in enhancing water availability regions with low precipitation. This study focused on identifying potential rainwater harvesting (RWH) locations drought-prone areas, specifically the Borena zone of Oromia and regional states Somali. research leveraged geospatial techniques multi-criteria decision analysis (MCDA) to assess feasible RWH sites. The dataset comprises essential factors such as rainfall, drainage density, slope, soil texture type, land use/land cover. These thematic layers serve inputs for analysis, each factor being weighted using Analytical Hierarchy Process (AHP) method based its significance. Reclassifying into subclasses facilitates suitability analysis. linear combination (WLC) technique is applied identify prioritize (PRWH) four classes: highly suitable, moderately suitability, unsuitable. Our findings reveal that 1% area, covering approximately 3288 km2, suitable RWH. Areas moderate constitute 12% (37,498 km2), while representing majority, encompass about 75% (242,170 km2). Additionally, 13% (41,000 km2) area deemed unsuitable proposed sites adaptable other low-precipitation regions. However, before implementing structures, further imperative. exploration socioeconomic variables future urged an in-depth examination various aspects environmental sustainability. paves way adapting align community needs life cycles also exploring socio-economic dimensions sustainability study. insights offer promising solutions address urgent issues associated scarcity. should include comprehensive site depictions, social economic activities, meticulous preparation cost-benefit

Language: Английский

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Integrated geospatial approach for adaptive rainwater harvesting site selection under the impact of climate change

Stochastic Environmental Research and Risk Assessment, Journal Year: 2023, Volume and Issue: 38(3), P. 1009 - 1033

Published: Nov. 29, 2023

Abstract The impact of global climate change on water resources is a pressing concern, particularly in arid and semi-arid regions, where shortages are becoming increasingly severe. Rainwater harvesting (RWH) offers promising solution to address these challenges. However, the process selecting suitable RWH sites complex. This paper introduces comprehensive methodology that leverages various technologies data sources identify locations northern region Iraq, considering both historical future scenarios. study employs remote sensing geographic information systems collect geospatial data, which essential for site selection process. AHP utilized as decision-making tool assess rank potential based multiple criteria, helping prioritize most sites. WLC approach used combine weigh factors, enabling systematic evaluation suitability. To account uncertainty associated with conditions, stochastic weather generator employed simulate precipitation period (1980–2022) (2031–2100). ensures assessment considers changing patterns. Historical values ranged from 270 490 mm, while projections indicate decrease, varying 255 390 mm. suggests reduction available due change. runoff rainfall 190 mm (poor) (very good). In projections, vary 180 poor) (good). analysis highlights reduced availability. There strong correlation between runoff, 95% 98.83% projections. indicates changes directly affect runoff. incorporates several criteria model, including soil texture, land use/cover, slope, drainage density. These were selected nature dataset suitability zones classified into four categories zones: very high suitability, covering approximately 8.2%. High encompassing around 22.6%. Moderate constituting about 37.4%. Low accounting 31.8% region. For projection, distribution follows: 6.1%. 18.3%. roughly 31.2%. making up 44.4% research's findings have significant implications sustainable resource management Iraq. As exacerbates scarcity, identifying becomes crucial ensuring methodology, incorporating advanced technology sources, provides valuable addressing challenges enhancing face more investigations studies need be conducted near

Language: Английский

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