Modeling Hydrological Response to Climate Change in a Data-Scarce Glacierized High Mountain Astore Basin Using a Fully Distributed TOPKAPI Model

Atif, Iqra; Iqbal, Javed; Su, Lijun

doi:10.3390/cli7110127

Cited by 6 publications

(1 citation statement)

References 79 publications

(79 reference statements)

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“…In the last decade, GIS and RS have been extensively and successfully used in disaster management studies, e.g. seismic disasters (Ehrlich et al, 2009;Frigerio et al, 2016); flood disasters Waheed, 2015, Sajjad et al, 2020); geological disasters (Li et al, 2005, Mahboob et al, 2015b, 2019b; droughts (Raut et al, 2020, Atif, Iqbal, andSu, 2019); and fire disasters (Hinkley, 2019). Several commercial and open-source satellite data-sets are available for both pre-and post-disaster analysis and future risk assessments (Mahboob et al, 2019b;Voigt et al, 2007;van Westen, 2013).…”

Section: Introductionmentioning

confidence: 99%

Modelling and analysis of the Brumadinho tailings disaster using advanced geospatial analytics

Atif

Cawood

Mahboob

2020

J. S. Afr. Inst. Min. Metall.

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On 25 January 2019, one of the most significant and deadliest tailings dam failures in history occurred at Brumadinho Córrego do Feijão iron ore mine in Brazil. Twelve million cubic metres of tailings travelling at 120 km/h destroyed a total of 109 buildings, 36 belonging to Vale and 73 local residences. More than 259 people died. Some farmlands were wiped out and left under a sea of mud and tailings up to 8 m deep. Seven sections of local roads, one main road, and one railway bridge were severely damaged. In this research, a GIS-based tailings spill path (TSP) model was developed using the Python programming language for predicting the potential tailings flow path-before failure of the tailings storage facility (TSF). The pre-and post-failure satellite images of the Brumadinho disaster were processed and analysed to map the damaged infrastructure and to extract digital footprints of the tailings waste and flow path. This model was then compared with the post-failure satellite images. The TSP model is capable of generating the possible path of tailings flow and other important outputs like a processed digital elevation model (DEM), processed satellite image, down-path slope direction, and flow accumulation. The model was tested and validated for the Brumadinho and Samarco tailing disasters. The results are very promising and correlate well with the actual tailings spills. The methodology adopted in this research is robust, advanced, and can be applied to other tailings dams for hazard and risk assessment in case of their possible failure. The lack of high-resolution post-disaster satellite images and other topographical data were the main limitations of this research, which if available, could improve the modelling results.

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Section: Introductionmentioning

confidence: 99%

Modelling and analysis of the Brumadinho tailings disaster using advanced geospatial analytics

Atif

Cawood

Mahboob

2020

J. S. Afr. Inst. Min. Metall.

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Impact of climate change on snow precipitation and streamflow in the Upper Indus Basin ending twenty-first century

Romshoo

Marazi

2022

Climatic Change

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Hydrological response under CMIP6 climate projection in Astore River Basin, Pakistan

Ali,

Iqbal,

Khan

et al. 2023

J. Mt. Sci.

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Climate change strongly influences the available water resources in a watershed due to direct linkage of atmospheric driving forces and changes in watershed hydrological processes. Understanding how these climatic changes affect watershed hydrology is essential for human society and environmental processes. Coupled Model Intercomparison Project phase 6 (CMIP6) dataset of three GCM’s (BCC-CSM2-MR, INM-CM5-0, and MPI-ESM1-2-HR) with resolution of 100 km has been analyzed to examine the projected changes in temperature and precipitation over the Astore catchment during 2020–2070. Bias correction method was used to reduce errors. In this study, statistical significance of trends was performed by using the Man- Kendall test. Sen’s estimator determined the magnitude of the trend on both seasonal and annual scales at Rama Rattu and Astore stations. MPI-ESM1-2-HR showed better results with coefficient of determination (COD) ranging from 0.70–0.74 for precipitation and 0.90–0.92 for maximum and minimum temperature at Astore, Rama, and Rattu followed by INM-CM5-0 and BCC-CSM2-MR. University of British Columbia Watershed model was used to attain the future hydrological series and to analyze the hydrological response of Astore River Basin to climate change. Results revealed that by the end of the 2070s, average annual precipitation is projected to increase up to 26.55% under the SSP1–2.6, 6.91% under SSP2–4.5, and decrease up to 21.62% under the SSP5–8.5. Precipitation also showed considerable variability during summer and winter. The projected temperature showed an increasing trend that may cause melting of glaciers. The projected increase in temperature ranges from - 0.66°C to 0.50°C, 0.9°C to 1.5°C and 1.18°C to 2°C under the scenarios of SSP1–2.6, SSP2–4.5 and SSP5–8.5, respectively. Simulated streamflows presented a slight increase by all scenarios. Maximum streamflow was generated under SSP5–8.5 followed by SSP2–4.5 and SSP1–2.6. The snowmelt and groundwater contributions to streamflow have decreased whereas rainfall and glacier melt components have increased on the other hand. The projected streamflows (2020–2070) compared to the control period (1990–2014) showed a reduction of 3%–11%, 2%–9%, and 1%–7% by SSP1–2.6, SSP2–4.5, and SSP5–8.5, respectively. The results revealed detailed insights into the performance of three GCMs, which can serve as a blueprint for regional policymaking and be expanded upon to establish adaption measures.

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Modeling Hydrological Response to Climate Change in a Data-Scarce Glacierized High Mountain Astore Basin Using a Fully Distributed TOPKAPI Model

Cited by 6 publications

References 79 publications

Modelling and analysis of the Brumadinho tailings disaster using advanced geospatial analytics

Modelling and analysis of the Brumadinho tailings disaster using advanced geospatial analytics

Impact of climate change on snow precipitation and streamflow in the Upper Indus Basin ending twenty-first century

Hydrological response under CMIP6 climate projection in Astore River Basin, Pakistan

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