Selecting Sites for Artificial Recharge of Groundwater with the Help of GIS, Remote Sensing and Geophysical Investigations in Jakhaura Block, Lalitpur, Uttar Pradesh

2021 ◽  
Vol 9 (VIII) ◽  
pp. 54-62
Author(s):  
Shubham Chandra Tripathi
Keyword(s):  
Remote Sensing ◽  
Rainwater Harvesting ◽  
Uttar Pradesh ◽  
High Rate ◽  
Thematic Layers ◽  
Multi Criteria Evaluation ◽  
Geophysical Investigations ◽  
A Site ◽  
Resistivity Meter ◽  
Very High

Water is a type of natural resource which has its application in almost every aspect of life and due to this it’s exploitation is observed at an increasingly fast rate. Our country is also suffering from water scarcity because its population is more than almost17% of the world’s population with only 4% of the World’s renewable water resources. In Indian sub-continent our dependency on Groundwater has increased very much. As a result, the Groundwater storage of our country is decreasing at very high rate and to address this we have thought to view the possibility of artificially recharging the Groundwater. This paper aims to find the suitable sites for building rainwater harvesting structures from combined use of Remote sensing, Geophysical technique and GIS in Jakhaura block of Lalitpur, Uttar Pradesh. The hard terrain feature of Jakhaura block makes the runoff very high and as a result infiltration of the rainwater to the groundwater is very low. For multi criteria evaluation, different thematic layers such as base map of area, drainage network, land use/ land cover, slope map, lineament, VES ( Resistivity meter) data, pseudo section using Zohdy software are taken into account. The overlay analysis of thematic layers has helped to make ground water prospects map, which has helped to make a site suitability map of different rainwater harvesting structures including percolation tanks, nala bunds, distillation tank and check dams etc.

scholarly journals Mapping Groundwater Potential for Irrigation, by Geographical Information System and Remote Sensing Techniques: A Case Study of District Lower Dir, Pakistan

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 669
Author(s):  
Abid Sarwar ◽  
Sajid Rashid Ahmad ◽  
Muhammad Ishaq Asif Rehmani ◽  
Muhammad Asif Javid ◽  
Shazia Gulzar ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Table ◽  
Groundwater Potential ◽  
Geographical Information ◽  
Groundwater Potential Zone ◽  
Potential Zone ◽  
Relative Significance ◽  
High Good ◽  
Groundwater Potentiality ◽  
Very High

The changing climate and global warming have rendered existing surface water insufficient, which is projected to adversely influence the irrigated farming systems globally. Consequently, groundwater demand has increased significantly owing to increasing population and demand for plant-based foods especially in South Asia and Pakistan. This study aimed to determine the potential areas for groundwater use for agriculture sector development in the study area Lower Dir District. ArcGIS 10.4 was utilized for geospatial analysis, which is referred to as Multi Influencing Factor (MIF) methodology. Seven parameters including land cover, geology, soil, rainfall, underground faults (liniment) density, drainage density, and slope, were utilized for delineation purpose. Considering relative significance and influence of each parameter in the groundwater recharge rating and weightage was given and potential groundwater areas were classified into very high, high, good, and poor. The result of classification disclosed that the areas of 113.10, 659.38, 674.68, and 124.17 km2 had very high, high, good, and poor potential for groundwater agricultural uses, respectively. Field surveys for water table indicated groundwater potentiality, which was high for Kotkay and Lalqila union councils having shallow water table. However, groundwater potentiality was poor in Zimdara, Khal, and Talash, characterized with a very deep water table. Moreover, the study effectively revealed that remote sensing and GIS could be developed as potent tools for mapping potential sites for groundwater utilization. Furthermore, MIF technique could be a suitable approach for delineation of groundwater potential zone, which can be applied for further research in different areas.

scholarly journals Integrating GIS-Based MCDA Techniques and the SCS-CN Method for Identifying Potential Zones for Rainwater Harvesting in a Semi-Arid Area

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 704
Author(s):  
Hussein Al-Ghobari ◽  
Ahmed Z. Dewidar
Keyword(s):  
Water Conservation ◽  
Surface Runoff ◽  
Rainwater Harvesting ◽  
Global Climate ◽  
Remote Sensing Data ◽  
Curve Number ◽  
Drainage Density ◽  
Promising Alternative ◽  
Thematic Layers ◽  
Scs Cn

An increasing scarcity of water, as well as rapid global climate change, requires more effective water conservation alternatives. One promising alternative is rainwater harvesting (RWH). Nevertheless, the evaluation of RWH potential together with the selection of appropriate sites for RWH structures is significantly difficult for the water managers. This study deals with this difficulty by identifying RWH potential areas and sites for RWH structures utilizing geospatial and multi-criteria decision analysis (MCDA) techniques. The conventional data and remote sensing data were employed to set up needed thematic layers using ArcGIS software. The soil conservation service curve number (SCS-CN) method was used to determine surface runoff, centered on which yearly runoff potential map was produced in the ArcGIS environment. Thematic layers such as drainage density, slope, land use/cover, and runoff were allotted appropriate weights to produced RWH potential areas and zones appropriate for RWH structures maps of the study location. Results analysis revealed that the outcomes of the spatial allocation of yearly surface runoff depth ranging from 83 to 295 mm. Moreover, RWH potential areas results showed that the study areas can be categorized into three RWH potential areas: (a) low suitability, (b) medium suitability, and (c) high suitability. Nearly 40% of the watershed zone falls within medium and high suitability RWH potential areas. It is deduced that the integrated MCDA and geospatial techniques provide a valuable and formidable resource for the strategizing of RWH within the study zones.

scholarly journals Torrential Flood Water Management: Rainwater Harvesting through Relation Based Dam Suitability Analysis and Quantification of Erosion Potential

2021 ◽  
Vol 10 (1) ◽  
pp. 27
Author(s):  
Bilal Ahmad Munir ◽  
Sajid Rashid Ahmad ◽  
Raja Rehan
Keyword(s):  
Sediment Yield ◽  
Soil Loss ◽  
Rainwater Harvesting ◽  
Suitability Analysis ◽  
Valley Bottom ◽  
The North ◽  
Roughness Index ◽  
Dam Site ◽  
Very High

In this study, a relation-based dam suitability analysis (RDSA) technique is developed to identify the most suitable sites for dams. The methodology focused on a group of the most important parameters/indicators (stream order, terrain roughness index, slope, multiresolution valley bottom flatness index, closed depression, valley depth, and downslope gradient difference) and their relation to the dam wall and reservoir suitability. Quantitative assessment results in an elevation-area-capacity (EAC) curve substantiating the capacity determination of selected sites. The methodology also incorporates the estimation of soil erosion (SE) using the Revised Universal Soil Loss Equation (RUSLE) model and sediment yield at the selected dam sites. The RDSA technique identifies two suitable dam sites (A and B) with a maximum collective capacity of approximately 1202 million m3. The RDSA technique was validated with the existing dam, Gomal-Zam, in the north of Sanghar catchment, where RDSA classified the Gomal-Zam Dam in a very high suitability class. The SE estimates show an average of 75 t-ha−1y−1 of soil loss occurs in the study area. The result shows approximately 298,073 and 318,000 tons of annual average sediment yield (SY) will feed the dam A and B respectively. The SE-based sediment yield substantiates the approximate life of Dam-A and Dam-B to be 87 and 90 years, respectively. The approach is dynamic and can be applied for any other location globally for dam site selection and SE estimation.

scholarly journals Flood vulnerability mapping using the spatial multi-criteria evaluation (SMCE) method in the Minraleng Watershed, Maros Regency, South Sulawesi

2020 ◽  
Vol 153 ◽  
pp. 01004
Author(s):  
Muhammad Fadhil ◽  
Yoanna Ristya ◽  
Nahra Oktaviani ◽  
Eko Kusratmoko
Keyword(s):  
Information System ◽  
Rainfall Intensity ◽  
Physical Factors ◽  
Relative Importance ◽  
Flood Vulnerability ◽  
South Sulawesi ◽  
Multi Criteria Evaluation ◽  
Gis Environment ◽  
Very High ◽  
Vulnerable Zones

This study focuses on the assessment of flood-vulnerable areas in the Minraleng watershed, Maros Regency, where the area experiences floods every year. Spatial analysis in the Geographic Information System (GIS) environment has been applied to estimate flood-vulnerable zones using six relevant physical factors, such as rainfall intensity, slope, Elevation, distance from the rivers, land use and soil type. The relative importance of physical factors has been compared in paired matrices to obtain weight values using the Spatial Multi-Criteria Evaluation (SMCE) method. The result showed that the areas located in Camba sub-district had the high vulnerability. The region with a high and very high vulnerability to flood were spread with an area of 436 ha (0,84 %) and 6.168 ha (11.8%).

scholarly journals Mapping Urban Functional Zones by Integrating Very High Spatial Resolution Remote Sensing Imagery and Points of Interest: A Case Study of Xiamen, China

2018 ◽  
Vol 10 (11) ◽  
pp. 1737 ◽  
Author(s):  
Jinchao Song ◽  
Tao Lin ◽  
Xinhu Li ◽  
Alexander V. Prishchepov
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Spatial Resolution ◽  
High Spatial Resolution ◽  
Remote Sensing Images ◽  
Remote Sensing Imagery ◽  
Points Of Interest ◽  
Very High Spatial Resolution ◽  
Functional Zones ◽  
Very High

Fine-scale, accurate intra-urban functional zones (urban land use) are important for applications that rely on exploring urban dynamic and complexity. However, current methods of mapping functional zones in built-up areas with high spatial resolution remote sensing images are incomplete due to a lack of social attributes. To address this issue, this paper explores a novel approach to mapping urban functional zones by integrating points of interest (POIs) with social properties and very high spatial resolution remote sensing imagery with natural attributes, and classifying urban function as residence zones, transportation zones, convenience shops, shopping centers, factory zones, companies, and public service zones. First, non-built and built-up areas were classified using high spatial resolution remote sensing images. Second, the built-up areas were segmented using an object-based approach by utilizing building rooftop characteristics (reflectance and shapes). At the same time, the functional POIs of the segments were identified to determine the functional attributes of the segmented polygon. Third, the functional values—the mean priority of the functions in a road-based parcel—were calculated by functional segments and segmental weight coefficients. This method was demonstrated on Xiamen Island, China with an overall accuracy of 78.47% and with a kappa coefficient of 74.52%. The proposed approach could be easily applied in other parts of the world where social data and high spatial resolution imagery are available and improve accuracy when automatically mapping urban functional zones using remote sensing imagery. It will also potentially provide large-scale land-use information.

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