How do CMIP6 models project changes in precipitation extremes over seasons and locations across the mid hills of Nepal?

Chhetri, Ramesh; Pandey, Vishnu Prasad; Talchabhadel, Rocky; Thapa, Bhesh Raj

doi:10.1007/s00704-021-03698-7

Cited by 22 publications

(6 citation statements)

References 90 publications

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“…The precipitation is projected to likely increase the most under SSP5-8.5. Bangladesh will likely observe an increase of 4.4-17.1% in the annual mean rainfall [98], 1.6-18.9% for Bhutan, 6.6-21.2% for Sri Lanka [19], 9.3 to 27.3% for India [99], and precipitation in Pakistan is projected to rise by 9.3-26.4% as well as an increase of 3.6-19.5% over Nepal under shared socio-economic pathways [100]. Similar results have reported that future precipitation is projected to increase by 6.0% under RCP-2.6 and 12.0% under the RCP-8.5 scenario over the western highlands of China [101].…”

Section: Discussionmentioning

confidence: 99%

Enhancing Streamflow Modeling by Integrating GRACE Data and Shared Socio-Economic Pathways (SSPs) with SWAT in Hongshui River Basin, China

Touseef

Chen

et al. 2023

Remote Sensing

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Climatic variability and the quantification of climate change impacts on hydrological parameters are persistently uncertain. Remote sensing aids valuable information to streamflow estimations and hydrological parameter projections. However, few studies have been implemented using remote sensing and CMIP6 data embedded with hydrological modeling. This research studied how changing climate influences the hydro-climatic parameters based on the earth system models that participated in the sixth phase of the Coupled Model Intercomparison Project (CMIP6). GRACE evapotranspiration data were forced into the Soil and Water Assessment Tool (SWAT) to project hydrologic responses to future climatic conditions in the Hongshui River basin (HRB) model. A novel approach based on climate elasticity was utilized to determine the extent to which climate variability affects stream flow. CMIP6 SSPs (shared socio-economic pathways) for the second half of the 20th century (1960–2020) and 21st century (2021–2100) projected precipitation (5–16%) for the whole Hongshui River basin (HRB). The ensemble of GCMs projected an increase of 2 °C in mean temperature. The stream flow is projected to increase by 4.2% under SSP-1.26, 6.2% under SSP-2.45, 8.45% under SSP-3.70, and 9.5% under SSP-5.85, based on the average changes throughout the various long-term future scenarios. We used the climate elasticity method and found that climate change contributes 11% to streamflow variability in the Hongshui River basin (HRB). Despite the uncertainty in projected hydrological variables, most members of the modeling ensemble present encouraging findings for future methods of water resource management.

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Section: Discussionmentioning

confidence: 99%

Enhancing Streamflow Modeling by Integrating GRACE Data and Shared Socio-Economic Pathways (SSPs) with SWAT in Hongshui River Basin, China

Touseef

Chen

et al. 2023

Remote Sensing

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“…We downscale and bias-correct the retrieved data from Mishra et al (2020b) relative to monthly climatic data at each meteorological station (refer to Fig. 3 for stations), using a linear scaling method (Teutschbein and Seibert 2012;Shrestha et al 2017;Chhetri et al 2021). The linear scaling method is the simplest yet equally applicable for projection analyses at monthly or seasonal scales compared to complex bias-correction schemes such as quantile mapping (Shrestha et al 2017;Bhatta et al 2019).…”

Section: Hydroclimatic Datasetsmentioning

confidence: 99%

Integrated modeling for assessing climate change impacts on water resources and hydropower potential in the Himalayas

Baniya,

Regmi,

Talchabhadel

et al. 2024

Theor Appl Climatol

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Regional hydroclimatic variability and change can affect water resources and hydropower generation. It is essential to assess hydropower potential under current and future climatic conditions to inform the design and operation of hydropower infrastructures. Here, we employ an integrated modeling framework to assess the impact of projected hydroclimatic conditions on water resources systems and hydropower generation. The integrated framework samples climate model outputs under different scenarios to force a hydrologic model and produces streamflow projections. The projected streamflows are inputs for the future hydropower potential assessment. We implement the framework in the central Himalayan river basin. Our results demonstrate substantial spatiotemporal variability in different water balance components (precipitation, evapotranspiration, and water yield) under current and future climatic conditions. For the selected basin, the average energy production is expected to increase under future hydroclimatic conditions. This increase in energy is driven mainly by the increased streamflow projections, particularly during the dry season and in the late century. Our results highlight the impacts of hydroclimatic variability in hydropower productions and are of practical use to provide decision-relevant information for designing and operating hydropower infrastructures. The integrated modeling framework presented here is regionspecific; however, the approach is reproducible, and the overall insights are generalizable across the Himalayan region.

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“…The uncertainties associated with these climatic variables make long term flood mitigation strategies quite difficult to plan and implement beforehand. However, recent developments have shown that it is possible to project future climate under different scenarios using Global Climatic Models (GCMs) (Chhetri et al, 2021;Mishra et al, 2021). Specifically, the projection of different extreme indices associated with precipitation helps establish a mutual relationship between hydrological extremes (like flood) brought about by them.…”

Section: Implications Under Climate Changementioning

confidence: 99%

Flood Susceptibility Analysis in West Rapti River Basin Using Frequency Ratio Model

Bhattarai

Ghimire

2023

Jalawaayu

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Floods are recognized as lethal natural events, which result in devastating natural and human losses. So, identifying flood susceptible zones is crucial to adopt necessary mitigation strategies beforehand. With the advent of GIS tools and modelling techniques, mapping of such zones has become easier and more precise; yet, flood prone countries like Nepal have not been able to embrace such tools for flood risk management. With a compelling need to address this situation, this paper employs Frequency Ratio model to analyze flood susceptibility in the West Rapti River Basin. The model, created with the help of 77 flood points and tested with 30 points to obtain 80.7% accuracy, maps the flood hazard zones in the area and identifies the lower Terai and settlement regions as high-risk areas. With the increasing threat of changing climate in the future, this study also propounds better preparation of flood inventory maps in the future for more precise susceptibility analysis models and better flood risk management.

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How do CMIP6 models project changes in precipitation extremes over seasons and locations across the mid hills of Nepal?

Cited by 22 publications

References 90 publications

Enhancing Streamflow Modeling by Integrating GRACE Data and Shared Socio-Economic Pathways (SSPs) with SWAT in Hongshui River Basin, China

Enhancing Streamflow Modeling by Integrating GRACE Data and Shared Socio-Economic Pathways (SSPs) with SWAT in Hongshui River Basin, China

Integrated modeling for assessing climate change impacts on water resources and hydropower potential in the Himalayas

Flood Susceptibility Analysis in West Rapti River Basin Using Frequency Ratio Model

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