Morphometric Analysis to Prioritize Sub-Watershed for Flood Risk Assessment in Central Karakoram National Park Using Gis/Rs Approach

Syed, N. H.; Rehman, Akhtar; Hussain, Dostdar; Ishaq, Sultan; Khan, Arif Raza

doi:10.5194/isprs-annals-iv-4-w4-367-2017

Cited by 14 publications

(5 citation statements)

References 6 publications

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“…The availability of numerous GIS software packages enabled the extraction of channel networks from remote sensing-based DEMs such as ArcGIS [85], Geographic Resources Analysis Support System (GRASS) GIS [99], and Quantum GIS [100]. In this study, we used the ArcGIS environment to introduce our toolbox, because ArcGIS and its powerful geoprocessing toolboxes have been widely used by different authors in different hydrological and geomorphological related research (e.g., References [57,66,101]).…”

Section: Developing Arcgis Python Toolbox For Geometric Assessment Ofmentioning

confidence: 99%

“…Note that airborne LiDAR-based DEMs are only available over a small percentage of the Earth's landmass, due to their high cost. Therefore, for many studies-particularly for flood monitoring and flood hazard zoning-researchers have used the freely available remote sensing-based DEMs with global coverage (e.g., Reference [61][62][63][64][65][66][67][68]). However, most of these researchers did not investigate the nature of the DEM used (i.e., either a DSM or a DTM) and errors that could profoundly affect their developed models.…”

Section: Introductionmentioning

confidence: 99%

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Pixel-Based Geometric Assessment of Channel Networks/Orders Derived from Global Spaceborne Digital Elevation Models

et al. 2019

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Digital Elevation Models (DEMs) contribute to geomorphological and hydrological applications. DEMs can be derived using different remote sensing-based datasets, such as Interferometric Synthetic Aperture Radar (InSAR) (e.g., Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR) and Shuttle Radar Topography Mission (SRTM) DEMs). In addition, there is also the Digital Surface Model (DSM) derived from optical tri-stereo ALOS Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) imagery. In this study, we evaluated satellite-based DEMs, SRTM (Global) GL1 DEM V003 28.5 m, ALOS DSM 28.5 m, and PALSAR DEMs 12.5 m and 28.5 m, and their derived channel networks/orders. We carried out these assessments using Light Detection and Ranging (LiDAR) Digital Surface Models (DSMs) and Digital Terrain Models (DTMs) and their derived channel networks and Strahler orders as reference datasets at comparable spatial resolutions. We introduced a pixel-based method for the quantitative horizontal evaluation of the channel networks and Strahler orders derived from global DEMs utilizing confusion matrices at different flow accumulation area thresholds (ATs) and pixel buffer tolerance values (PBTVs) in both ±X and ±Y directions. A new Python toolbox for ArcGIS was developed to automate the introduced method. A set of evaluation metrics—(i) producer accuracy (PA), (ii) user accuracy (UA), (iii) F-score (F), and (iv) Cohen’s kappa index (KI)—were computed to evaluate the accuracy of the horizontal matching between channel networks/orders extracted from global DEMs and those derived from LiDAR DTMs and DSMs. PALSAR DEM 12.5 m ranked first among the other global DEMs with the lowest root mean square error (RMSE) and mean difference (MD) values of 4.57 m and 0.78 m, respectively, when compared to the LiDAR DTM 12.5 m. The ALOS DSM 28.5 m had the highest vertical accuracy with the lowest recorded RMSE and MD values of 4.01 m and –0.29 m, respectively, when compared to the LiDAR DSM 28.5 m. PALSAR DEM 12.5 m and ALOS DSM 28.5 m-derived channel networks/orders yielded the highest horizontal accuracy when compared to those delineated from LiDAR DTM 12.5 m and LiDAR DSM 28.5 m, respectively. The number of unmatched channels decreased when the PBTV increased from 0 to 3 pixels using different ATs.

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Section: Developing Arcgis Python Toolbox For Geometric Assessment Ofmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Pixel-Based Geometric Assessment of Channel Networks/Orders Derived from Global Spaceborne Digital Elevation Models

et al. 2019

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“…A watershed refers to the region from which runoff from rainfall runs through a single point and into significant streams, lakes, rivers, and seas. A watershed is a naturally occurring hydrologic unit that can be classified according to the surrounding physical, climatic, and topographic conditions (Syed et al 2017). Natural resource availability, such as land and water, is dwindling daily as a result of increasing population pressure.…”

Section: Introductionmentioning

confidence: 99%

Applications of advanced technology for Prioritization of Watershed

Raj,

Rawat,

Tripathi

2024

Environment and Ecology

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Prioritization of sub-watersheds is critical in strategic planning for incorporating management practices in delicate semi-arid regions. Geomorphometric as well as land use/cover data sets are essential for determining subwatershed priorities for integrated watershed management. Prioritizing watersheds entails ranking of sub-watersheds according to their susceptibility based on several variables, including the average yearly soil loss, the depletion of water resources, and ecological deterioration. The sub-watershed prioritization for the study area Muzaffarpur district was done by combining Principal Component Analysis (PCA) and Weighted Sum Approach (WSA). PCA was used to differentiate important parameters but WSA was used to measure compound values for priority ranking and determining weights for significant parameters. The PCA was effective in obtaining the most crucial values (i.e., WB, Dt, Re, and Rb). A load of each significant parameter was successfully defined by the WSA application. Traditional prioritizing procedures uses numerous criteria in a complex manner and presumptively contribute equally but PCA-WSA integration results in more dynamic, effective, and efficient solutions.

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“…The morphometric analysis of drainage basins helps to comprehend aspects of linear, areal, and relief parameters. These parameters have been used by geomorphologists to study runoff, morpho/neotectonics, flash floods [31,32], soil erosion [33], groundwater potential [34], watershed prioritization [35][36][37][38], check dam positioning, etc [13,[39][40][41][42][43][44][45][46][47]. Watershed prioritization has become important in identifying and prioritize the regions which would require treatment for water and soil conservations practices.…”

Section: Introductionmentioning

confidence: 99%

Prioritizing Watershed Restoration, Management, and Development Based on Geo-Morphometric Analysis in Asir Region of Saudi Arabia Using Geospatial Technology

Mallick¹,

Shivhare²,

Singh³

et al. 2022

Pol. J. Environ. Stud.

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The groundwater resource in the Kingdom of Saudi Arabia is a non-renewable resource. Geographical information system and remote sensing are proven to be an efficient tool for locating water harvesting and recharge structures by prioritization of sub-watersheds through morphometric analysis. In this study, the watershed prioritization in Asir Province has been assessed by linear, aerial, and relief morphometric parameters. Morphometric analysis has been attempted to prioritize a total of eleven subwatersheds, of which six sub-watersheds in Tathlith Wadi and five sub-watersheds in Bisha Wadi were delineated using digital elevation model (DEM). Advanced space-borne thermal emission and reflection radiometer of 30m resolution DEM has used to generate drainage networks and delineation of subwatersheds using ArcGIS software. The important derived morphometric parameters have computed on the base of already developed mathematical formulae and methods. A novel and quantitative approach based on the compound parameter by using linear and shape parameters of the respective sub-watershed was attempted for its prioritization. The total area of sub-watershed in Wadi Bisha, which lies under high, medium, and low priority is approximately 40%, 20% and 40% respectively. whereas in Wadi Tathlith, the area under high and medium priority is 67% and 33%. The watersheds BSW2 and BSW4 in Wadi Bisha and TSW1, TSW2, TSW3, and TSW5 in Wadi Tathlith would require immediate intervention and efficient action plan for water and soil conservation. The interrelationship between the various morphometric factors of the basin has been studied using a correlation matrix. Further, morphometric factors have been studied in relation to the sub-basins to understand the existing relation between the factors and the sub-basins. The prioritized watersheds were validated using the

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Morphometric Analysis to Prioritize Sub-Watershed for Flood Risk Assessment in Central Karakoram National Park Using Gis/Rs Approach

Cited by 14 publications

References 6 publications

Pixel-Based Geometric Assessment of Channel Networks/Orders Derived from Global Spaceborne Digital Elevation Models

Pixel-Based Geometric Assessment of Channel Networks/Orders Derived from Global Spaceborne Digital Elevation Models

Applications of advanced technology for Prioritization of Watershed

Prioritizing Watershed Restoration, Management, and Development Based on Geo-Morphometric Analysis in Asir Region of Saudi Arabia Using Geospatial Technology

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