A multi-perspective approach for selecting CMIP6 scenarios to project climate change impacts on glacio-hydrology with a case study in Upper Indus river basin

Shafeeque, Muhammad; Luo, Yi

doi:10.1016/j.jhydrol.2021.126466

Cited by 36 publications

(17 citation statements)

References 81 publications

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“…Previous studies confirmed a good performance of this model in simulating alpine glaciers (Farinotti et al, 2017;Pelto et al, 2020) and reproducing the millennial trend of glacial evolution in mountainous regions (Goosse et al, 2018;Parkes and Goosse, 2020). For example, OGGM has been successfully applied to simulate High Mountain Asia glaciers, including their thickness, velocity, and future evolutions (Dixit et al, 2021;Pronk et al, 2021;Shafeeque and Luo, 2021;Furian et al, 2022;Chen et al, 2022).…”

Section: Model Descriptionmentioning

confidence: 57%

Timing and climatic-driven mechanisms of glacier advances in Bhutanese Himalaya during the Little Ice Age

Liu

Chu

2022

The Cryosphere

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Abstract. Mountain glaciers provide us a window into past climate changes and landscape evolution, but the pattern of glacier evolution at centennial or suborbital timescale remains elusive, especially in monsoonal Himalayas. We simulated the glacier evolution in Bhutanese Himalaya (BH), a typical monsoon-influenced region, during the Little Ice Age (LIA) using the Open Global Glacier Model driven by six paleoclimate datasets and their average. Compared with geomorphologically mapped glacial landforms, the model can well capture the patterns of glacier length change. Simulation results revealed four glacial substages (the 1270s, 1470s, 1710s, and 1850s) during LIA in the study area. Statistically, a positive correlation between the number of glacial substages and glacier slope was found, indicating that the occurrence of glacial substages might be a result from heterogeneous responses of glaciers to climate change. Monthly climate change analysis and sensitivity experiments indicated that the summer temperature largely dominates the regional glacier evolution during the LIA in BH.

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Section: Model Descriptionmentioning

confidence: 57%

Timing and climatic-driven mechanisms of glacier advances in Bhutanese Himalaya during the Little Ice Age

Liu

Chu

2022

The Cryosphere

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“…This version proposes shared socioeconomic pathways (SSPs), which reflect a variety of scenarios for greenhouse gas emission and land use change, incorporating socio-economic factors such as urban development, economic progression, climate mitigation initiatives, educational and technological development, and global policies computed by integrated assessment models [30]. The CMIP6 model has gained popularity in determining changes in hydrological parameters such as precipitation and temperature in the future [31,32], assessing the risk posed by the climate projected runoff values to the areas [33,34], comparisons of different climate scenarios [35][36][37], and so on. In addition, the CMIP6 version has river discharge as one of the parameters, and the use of this variable has not been given much attention by prior research, and so this research studies the change in river discharge due to climate change based on the CMIP6 model.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Implication of Climate Change to Forecast Future Flood Using CMIP6 Climate Projections and HEC-RAS Modeling

2022

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Climate change has caused uncertainty in the hydrological pattern including weather change, precipitation fluctuations, and extreme temperature, thus triggering unforeseen natural tragedies such as hurricanes, flash flooding, heatwave and more. Because of these unanticipated events occurring all around the globe, the study of the influence of climate change on the alteration of flooding patterns has gained a lot of attention. This research study intends to provide an insight into how the future projected streamflow will affect the flooding-inundation extent by comparing the change in floodplain using both historical and future simulated scenarios. For the future projected data, the climate model Atmosphere/Ocean General Circulation Model (AOGCM) developed by Coupled Model Intercomparison Project Phase 6 (CMIP6) is used, which illustrates that the flood is increasing in considering climate models. Furthermore, a comparison of the existing flood inundation map by the Federal Emergency Management Agency (FEMA) study with the map generated by future projected streamflow data presents the entire inundation area in flood maps, implying the expansion area compared to FEMA needs to be considered in making emergency response plans. The effect of flooding in the inundation area from historical to future flow values, presented mathematically by a calculation of inundation extent percentage, infers that the considered watershed of Rock River is a flood-prone area. The goal is to provide insights on the importance of using the forecasted data for flood analysis and to offer the necessary background needed to strategize an emergency response plan for flood management.

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“…The CMIP6 adds special test designs that are closer to actual physical and biogeochemical processes from the perspective of how to assess future climate change (Ayugi et al 2021;Srivastava et al 2020;Yazdandoost et al 2021). Therefore, the CMIP6 can carry out more numerical experiments according to the new numerical experiment design scheme, thereby continuing to improve the resolution of the models (Mondal et al 2021;Rivera and Arnould 2020;Shafeeque and Luo 2021). At present, the GCMs have been widely used to evaluate the impact of climate change on ecology, environment, hydrology, and agriculture (Guo et al 2021a;Yazdandoost et al 2021;Zhai et al 2020).…”

Section: Introductionmentioning

confidence: 99%

“…At present, the GCMs have been widely used to evaluate the impact of climate change on ecology, environment, hydrology, and agriculture (Guo et al 2021a;Yazdandoost et al 2021;Zhai et al 2020). However, due to differences in mechanism, terrain elevation settings, parameterization schemes, and spatial resolution between the GCMs, there are greater uncertainties in the output results of different models (Kim et al 2020;Lai et al 2020;Shafeeque and Luo 2021). There are also differences in the applicability of the same model in different regions .…”

Section: Introductionmentioning

confidence: 99%

“…The analysis of the changes in the spatio-temporal distribution characteristics of water resources in the HRB under future climate change is conducive to coping with the uncertain challenges brought by climate change (Ayugi et al 2021;Mondal et al 2021). Affected by the rapid economic and social development, the demand for water resources in the HRB has grown rapidly (Rivera and Arnould 2020;Shafeeque and Luo 2021;Wang et al 2021). Reasonable water resources forecasting and planning are more important to ensuring the sustainable development of the HRB.…”

Section: Introductionmentioning

confidence: 99%

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Spatio-temporal changes of precipitation in the Hanjiang River Basin under climate change

Jin

Chen

Zhong

et al. 2021

Theor Appl Climatol

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The Hanjiang River is the source of water for the Middle Route of the South-to-North Water Diversion Project. So a reasonable evaluation on water resources future changes in the Hanjiang River Basin (HRB) is essential to ensure its water safety. In this study, we firstly evaluated the China meteorological forcing dataset (CMFD), and then used it to measure the applicability of the eight global climate models (GCMs). Finally, the empirical orthogonal function (EOF) and clustering algorithms were used to analyze the spatial distribution status of precipitation in the HRB. The results showed that the BCC-CSM2-MR model has the best effect, followed by the IPSL-CM6A-LR model. In the SSP126, SSP245, SSP370, and SSP585 scenarios, total precipitation in the HRB all shows an increasing trend. However, the difference in the spatial distribution of precipitation intensified, for the upstream and downstream tended to be wetter, while the middle reaches had less precipitation. In the future climate scenarios, the areas with more precipitation (Class 1) increased significantly, while the areas with medium precipitation (Class 3) decreased significantly, which will enlarge the precipitation difference between regions in the HRB. The increase in the total amount of precipitation, coupled with the increase in the spatial heterogeneity of precipitation, will make the HRB more vulnerable to flooding disasters. Therefore, the water resources management measures in the HRB should be strengthened in the future.

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A multi-perspective approach for selecting CMIP6 scenarios to project climate change impacts on glacio-hydrology with a case study in Upper Indus river basin

Cited by 36 publications

References 81 publications

Timing and climatic-driven mechanisms of glacier advances in Bhutanese Himalaya during the Little Ice Age

Timing and climatic-driven mechanisms of glacier advances in Bhutanese Himalaya during the Little Ice Age

Assessing the Implication of Climate Change to Forecast Future Flood Using CMIP6 Climate Projections and HEC-RAS Modeling

Spatio-temporal changes of precipitation in the Hanjiang River Basin under climate change

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