Quantification of impact of changes in land use-land cover on hydrology in the upper Indus Basin, Pakistan

Younis, Syed Muhammad Zubair; Ammar, Ahmad

doi:10.1016/j.ejrs.2017.11.001

Cited by 25 publications

(15 citation statements)

References 8 publications

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“…The total forest area in the entire district was calculated as 3 km 2 using the GFW data set for 2019. Younis and Ammar [88] Using the supervised image classification method, they mapped the land cover of 1992, 2002, and 2013 and reported that deforestation occurred with a net change of 547.45 km 2 from 1992 to 2013. The total forest area in the entire district was calculated as 63 km 2 using the GFW data set for 2019.…”

Section: Other Districtsmentioning

confidence: 99%

“…The study by Ahmad et al [71] reported 50 validation samples to assess accuracies for classified maps using overall accuracy, kappa coefficient, producer's accuracy, and user's accuracy, but they did not report values in their paper. Younis and Ammar [88] used 98 ground validation points to report overall accuracy of 71.4% and a kappa coefficient of 0.623 for 2010 using Landsat imagery. After this, Rahid and Iqbal [89] analyzed forest cover along a national highway in Pakistan and assessed accuracy using 500 validation points.…”

Section: Accuracies Assessments and Validations For Forest Mappingmentioning

confidence: 99%

See 1 more Smart Citation

A Synthesis of Spatial Forest Assessment Studies Using Remote Sensing Data and Techniques in Pakistan

Ahmad

Gilani

et al. 2021

Forests

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This paper synthesizes research studies on spatial forest assessment and mapping using remote sensing data and techniques in Pakistan. The synthesis states that 73 peer-reviewed research articles were published in the past 28 years (1993–2021). Out of all studies, three were conducted in Azad Jammu & Kashmir, one in Balochistan, three in Gilgit-Baltistan, twelve in Islamabad Capital Territory, thirty-one in Khyber Pakhtunkhwa, six in Punjab, ten in Sindh, and the remaining seven studies were conducted on national/regional scales. This review discusses the remote sensing classification methods, algorithms, published papers' citations, limitations, and challenges of forest mapping in Pakistan. The literature review suggested that the supervised image classification method and maximum likelihood classifier were among the most frequently used image classification and classification algorithms. The review also compared studies before and after the 18th constitutional amendment in Pakistan. Very few studies were conducted before this constitutional amendment, while a steep increase was observed afterward. The image classification accuracies of published papers were also assessed on local, regional, and national scales. The spatial forest assessment and mapping in Pakistan were evaluated only once using active remote sensing data (i.e., SAR). Advanced satellite imageries, the latest tools, and techniques need to be incorporated for forest mapping in Pakistan to facilitate forest stakeholders in managing the forests and undertaking national projects like UN’s REDD+ effectively.

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Section: Other Districtsmentioning

confidence: 99%

Section: Accuracies Assessments and Validations For Forest Mappingmentioning

confidence: 99%

A Synthesis of Spatial Forest Assessment Studies Using Remote Sensing Data and Techniques in Pakistan

Ahmad

Gilani

et al. 2021

Forests

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“…The second important aspect for deriving runoff CN values is vegetation and other land cover. Current studies used HEC-HMS as a tool for analyzing the impact of land use and cover change on surface runoff (Younis & Ammar 2018). The study (Al-Zahrani 2018) focused on land-use changes, and HEC-HMS modelling tool was applied for results evaluations.…”

Section: Land Covermentioning

confidence: 99%

Parameter recalculation for a rainfall-runoff model with a focus on runoff curve numbers

2019

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One of the fundamental issues of hydrology is determination of total runoff volume from rainfall. The mutual relationship of these quantities can be experimentally determined by measuring rainfall and runoff. Rainfall-runoff models describe natural relations on the basis of variables determining physio-geographical conditions of a territorial unit as well as hydraulic properties of the respective river network. In the proposed paper, we focused on parameter recalculation of a rainfall-runoff model with focusing on runoff curve numbers (CN). The objective of this study was to update the data (CN) in the old modelling structures within the FLOREON+ (FLOods REcognition on the Net – Study Area) system and replace them with the new ones. The parameters of runoff CN were estimated according to available GIS layers primarily related to the existing soil conditions and land use. In the first phase, the calculation procedure was prepared for the smaller Porubka and Lubina basins, and then it was applied to the whole basin area. The results showed that the new runoff CN recalculation procedure resulted in reduction of the simulated runoff (peak discharge, volume) in the Odra River sub-basins, which also led to approximation to the real measured runoff in the Ostrava-Svinov profile. The derived method is applicable to other basins as well. Highlights for public administration, management and planning: • Runoff volumes resulting from rainfall significantly contribute to risk processes, such as soil erosion and floods. • The partially automated procedure for rainfall-runoff estimation is preseted, based on data for soil conditions and land cover. • Derivation is based on the original principles determined by the US Soil Conservation Service and can be applied to any river basin in the area of the Czech Republic. • In the future, the proposed methodology will be adapted to run within the ArcMap application.

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“…Several hydrology models can be used to assess the impacts of land use/land cover change on the hydrologic responses of a catchment, for the land use/land cover data derived from the remote sensing. These including Hydrologic Simulation Program Fortran (HSPF) model (Zhang and Ross 2015), MIKE SHE (Im et al 2009), PRMS (Legesse et al 2010), HBV (Ashagrie et al 2006), HEC-HMS (Younis and Ahmad 2018), DHSVM (Safeeq and Fares 2012), WaSIM-ETH (Bormann and Elfert 2010), SWAT (Bieger et al 2015). However, the SWAT model has been mostly applied to assess the impacts of land-use change on catchment hydrology, around the world.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Land Use Change Prediction and Analysis of Its Impacts on Streamflow for Dabus Watershed, Upper Blue Nile Basin

Nb¹,

Berhe²

2021

Preprint

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Based on the recorded watershed characteristics, the future conditions on the basin system can be predicted using a different method. In this study, dynamic land-use change and its impacts on the streamflow for the Dabus watershed were predicted using ANN-CA based method. The model performance for accurate prediction of the future land-use change on the Dabus River watershed has been checked by validation of the simulated value with the actual value, hence the overall kappa value (k) = 0.83 for the simulated 2016-LULC validated with actual 2016-LULC. Then, 2026-LULC was predicted based on the 2004 and 2009-LULC. The streamflow for the case of 2004 and 2009-LULC has been simulated using the SWAT model. The value of NSE = 0.87 and 0.90 was attained during validation of simulated streamflow for 2004 and 2009-LULC data cases, respectively. The agreement of simulated value of streamflow with the observed data is indicated as R2 = 0.91 and 0.96 for 2004-LULC and 2009-LULC. The effects of the dynamic land-use change on streamflow for the predicted land use(2026-LULC) catchment were evaluated by T-test analysis. Hence, T-stat =0.04 and -0.002 in the case of simulated streamflow used 2004-LULC and 2009-LULC, respectively compared with simulated value using 2026-LULC.

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Quantification of impact of changes in land use-land cover on hydrology in the upper Indus Basin, Pakistan

Cited by 25 publications

References 8 publications

A Synthesis of Spatial Forest Assessment Studies Using Remote Sensing Data and Techniques in Pakistan

A Synthesis of Spatial Forest Assessment Studies Using Remote Sensing Data and Techniques in Pakistan

Parameter recalculation for a rainfall-runoff model with a focus on runoff curve numbers

Dynamic Land Use Change Prediction and Analysis of Its Impacts on Streamflow for Dabus Watershed, Upper Blue Nile Basin

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