Quantitative Analysis of Watershed Hydrology for Kandar Dam (Kohat) using Remote Sensing and Geographic Information System (GIS) Techniques

Pakistan Journal of Meteorology

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Title Quantitative Analysis of Watershed Hydrology for Kandar Dam (Kohat) using Remote Sensing and Geographic Information System (GIS) Techniques
Creator Khan, Aftab Ahmad
Muhammad, Jan
Khan, Gul Daraz
Ijaz, Muhammad
Adnan, Muhammad
Subject Hydrological processing, Watershed delineation, Arc hydro tools, Supervised Classification, GDEM
Description Watershed management plays a significant role in water assets engineering and management. Remote Sensing (RS) and Geographical Information System (GIS) techniques provide an effective solution to manage data that signify the hydrological features of the watershed. Determination of high accuracy and imagining topographic features of the earth’s surface is very vital for studying environmental applications at a local level. Land Use Land Cover (LULC) classifications is one of the most important methods of remote sensing and it is also a prime input for hydrological models. Estimation of peak runoff and total runoff volume is always required for hydrological planning. Estimation of runoff is difficult if the catchment area and its characteristics are not known. Determination of catchment area and its boundary is a tedious job through use of simple contour maps. This study was conducted to assess the accuracy and utilization of Advanced Space borne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTERGDEM) and Arc Hydro tools for watershed delineation and catchment area calculation. Furthermore, LULC classes were determined and Weighted Curve Number (WCN) was estimated. The elevations predicted by ASTER GDEM were compared with the elevations of established benchmarks at the watershed. It was then utilized as an input to Arc Hydro tools for watershed delineation. SPOT data (image) of the study site was classified through Supervised Classification in a remote sensing tool, ERDAS Imagine 9.1. Supervised classes were then compared with observed classes. A strong correlation was found between ASTER GDEM and observed benchmarks elevations (R= 0.83with 95 % confidence level). The resultant projected boundaries of watershed obtained, were in a close relevance to observed Global Positioning System (GPS) data. However, its projected catchment area was 71.61 km2instead of 72.31 km2. The overall user accuracy of classification was 94.23 % with overall Kappa (K^) coefficient value of 93.WCN was found to be 76.42 for the mentioned catchment area. It was concluded that ASTER GDEM and Arc Hydro tools are recommended for hydrological processing of small watersheds and SPOT data is good for LULC classification.
Publisher Pakistan Journal of Meteorology
Contributor Global Change Impact Studies Centre (GCISC), Ministry of Climate Change, Islamabad, Pakistan.
Date 2017-07-20
Type info:eu-repo/semantics/article
Peer-reviewed Article
Identifier http://pjm.pmd.gov.pk/index.php/pjm/article/view/50
Source Pakistan Journal of Meteorology; Vol 12, No 24 (2016)
Language eng
Relation http://pjm.pmd.gov.pk/index.php/pjm/article/view/50/8
Rights Copyright (c) 2017 Pakistan Journal of Meteorology

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