Water Resource Management Studies at Micro Level Using Geospatial Technologies

Subramoniam, Suresh; Ravindranath, Sudha; Rakkasagi, Shivukumar; Hebbar, R.

doi:10.1007/978-3-030-98981-1_2

Cited by 7 publications

(2 citation statements)

References 21 publications

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“…Clouds and shadows can be seen in the Landsat sceneries; these elements must be hidden to produce correct composites and improve classification accuracy 47 . The pixels on the Landsat cloud mask band categorized as clouds or cloud shadows, were concealed for each scene 48 – 50 .…”

Section: Methodsmentioning

confidence: 99%

Spatiotemporal-based automated inundation mapping of Ramsar wetlands using Google Earth Engine

Goyal,

Rakkasagi,

Shaga

et al. 2023

Sci Rep

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Wetlands are one of the most critical components of an ecosystem, supporting many ecological niches and a rich diversity of flora and fauna. The ecological significance of these sites makes it imperative to study the changes in their inundation extent and propose necessary measures for their conservation. This study analyzes all 64 Ramsar sites in China based on their inundation patterns using Landsat imagery from 1991 to 2020. Annual composites were generated using the short-wave infrared thresholding technique from June to September to create inundation maps. The analysis was carried out on each Ramsar site individually to account for its typical behavior due to regional geographical and climatic conditions. The results of the inundation analysis for each site were subjected to the Mann–Kendall test to determine their trends. The analysis showed that 8 sites exhibited a significantly decreasing trend, while 14 sites displayed a significantly increasing trend. The accuracy of the analysis ranged from a minimum of 72.0% for Hubei Wang Lake to a maximum of 98.0% for Zhangye Heihe Wetland National Nature Reserve. The average overall accuracy of the sites was found to be 90.0%. The findings emphasize the necessity for conservation strategies and policies for Ramsar sites.

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Section: Methodsmentioning

confidence: 99%

Spatiotemporal-based automated inundation mapping of Ramsar wetlands using Google Earth Engine

Goyal,

Rakkasagi,

Shaga

et al. 2023

Sci Rep

Self Cite

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“…Earlier studies in the region [30,31] revealed the geochemical nature of the groundwater and pointed out the water level depletion in the area, with serious concern regarding suitability for different utility purposes [30]. Current global water management research mainly focuses on microlevel management [32] to enhance recharge and sustainability. In this regard, there has been no study reported to identify the suitable region of recharge in the current study area.…”

Section: Introductionmentioning

confidence: 99%

Mapping of Groundwater Recharge Zones in Hard Rock Aquifer through Analytic Hierarchy Process in Geospatial Platform

Subramani,

Kamaraj,

Saravana Kumar

et al. 2024

Water

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Extensive use of groundwater is a result of the growing population; in relation to this, studies have focused on groundwater conservation measures. This study identified groundwater artificial recharge zones (GWARZs) in the upper Manimuktha sub-basin through the application of remote sensing and GIS. A spatial analysis using the analytical hierarchical process (AHP) and weighted overlay analysis (WOA) was employed by integrating several spatial thematic layers such as geology, geomorphology, aquifer thickness, lineament density (LD), drainage density (DD), soil, slope, rainfall, and land use/land cover (LULC) in order to classify the GWARZs. The geomorphology along with lithology, higher aquifer thickness, low lineament densities, higher drainage densities, and gentle slope regions, were identified as suitable areas for artificial recharge zones. The study area was divided up into five classifications based on the integration analysis: excellent (41.1 km2), good (150.6 km2), moderate (123.9 km2), bad (125.5 km2), and very poor (57.7 km2). Excellent and good GWARZs were identified in the eastern and central regions of the study area. The final outcomes of this research were evaluated with seasonal electrical conductivity (EC) variations. The majority of samples with minor seasonal EC variations were observed in the excellent and good GWARZ categories. The results showed that the spatial analysis tool is useful for GWARZ delineation and sustainably managing groundwater resources.

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Comparing Runoff of the NRCS-CN Method and Observed Runoff Data: A Case Study

Sakalesh,

Nyamathi

2023

Disaster Resilience and Green Growth

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Water Resource Management Studies at Micro Level Using Geospatial Technologies

Cited by 7 publications

References 21 publications

Spatiotemporal-based automated inundation mapping of Ramsar wetlands using Google Earth Engine

Spatiotemporal-based automated inundation mapping of Ramsar wetlands using Google Earth Engine

Mapping of Groundwater Recharge Zones in Hard Rock Aquifer through Analytic Hierarchy Process in Geospatial Platform

Comparing Runoff of the NRCS-CN Method and Observed Runoff Data: A Case Study

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