Climate-induced flood inundation for the Arial Khan River of Bangladesh using open-source SWAT and HEC-RAS model for RCP8.5-SSP5 scenario

AbstractBangladesh is one of the largest flood-prone deltas of the GBM (Ganges–Brahmaputra–Meghna) basins, and recently, it is categorized as the 7th worst climate-affected country in the world. Future climate change along with economic development, urbanization, and increase in population may worsen this situation manifolds. To cope with future flood situations and lessen probable flood losses, it is essential to develop flood maps of the major flood-prone rivers of Bangladesh considering climate change scenarios. In this study, the flood inundation of the Arial Khan River and its floodplain has been assessed for the predicted climate change scenario of RCP 8.5 (Representative Concentration Pathway 8.5) using open-source mathematical models. A calibrated and validated hydrologic model of GBM basins in SWAT (Soil and Water Assessment Tool) model has been used to estimate the future flow magnitudes at Bahadurabad Transit (Brahmaputra River) and Hardinge Bridge (Ganges River) using extreme emission scenario RCP 8.5. Using the flow magnitude of these two stations as the upstream boundaries, an HEC-RAS 1D model has been set up for the Brahmaputra, Ganges, and Padma rivers for generating future flow magnitude at the offtake of the Arial Khan River. Later, an HEC-RAS 1D-2D coupled model is set up for the Arial Khan River floodplain and flood maps are prepared considering flood depth, duration, and inundation extent. The flood assessment for different projections of RCP 8.5 shows that there is an increasing trend of flood in terms of depth, duration, and inundation from the 2020s to the 2080s. Hence, the floodplain becomes more hazardous by the end of this century. The climate change impact on the projected population for the RCP 8.5 scenario is assessed under SSP5 (Shared Socioeconomic Pathways 5) which indicates that the total flood-affected population will be nearly twice in the 2080s compared to the 2020s. So, future climate change is going to have a dreadful effect on the flood situation of the Arial Khan River floodplain.

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Impacts of future climate change on urban flood volumes in Hohhot in northern China: benefits of climate change mitigation and adaptations

Hydrology and Earth System Sciences ◽

10.5194/hess-22-305-2018 ◽

2018 ◽

Vol 22 (1) ◽

pp. 305-316 ◽

Cited By ~ 14

Author(s):

Qianqian Zhou ◽

Guoyong Leng ◽

Maoyi Huang

Keyword(s):

Climate Change ◽

Local Adaptation ◽

Climate Change Mitigation ◽

Northern China ◽

Future Climate ◽

Future Climate Change ◽

Urban Flood ◽

Drainage Systems ◽

Rcp 8.5 ◽

Change Mitigation

Abstract. As China becomes increasingly urbanised, flooding has become a regular occurrence in its major cities. Assessing the effects of future climate change on urban flood volumes is crucial to informing better management of such disasters given the severity of the devastating impacts of flooding (e.g. the 2016 flooding events across China). Although recent studies have investigated the impacts of future climate change on urban flooding, the effects of both climate change mitigation and adaptation have rarely been accounted for together in a consistent framework. In this study, we assess the benefits of mitigating climate change by reducing greenhouse gas (GHG) emissions and locally adapting to climate change by modifying drainage systems to reduce urban flooding under various climate change scenarios through a case study conducted in northern China. The urban drainage model – Storm Water Management Model – was used to simulate urban flood volumes using current and two adapted drainage systems (i.e. pipe enlargement and low-impact development, LID), driven by bias-corrected meteorological forcing from five general circulation models in the Coupled Model Intercomparison Project Phase 5 archive. Results indicate that urban flood volume is projected to increase by 52 % over 2020–2040 compared to the volume in 1971–2000 under the business-as-usual scenario (i.e. Representative Concentration Pathway (RCP) 8.5). The magnitudes of urban flood volumes are found to increase nonlinearly with changes in precipitation intensity. On average, the projected flood volume under RCP 2.6 is 13 % less than that under RCP 8.5, demonstrating the benefits of global-scale climate change mitigation efforts in reducing local urban flood volumes. Comparison of reduced flood volumes between climate change mitigation and local adaptation (by improving drainage systems) scenarios suggests that local adaptation is more effective than climate change mitigation in reducing future flood volumes. This has broad implications for the research community relative to drainage system design and modelling in a changing environment. This study highlights the importance of accounting for local adaptation when coping with future urban floods.

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Evaluation of impacts of future climate change and water use scenarios on regional hydrology

Hydrology and Earth System Sciences ◽

10.5194/hess-22-4793-2018 ◽

2018 ◽

Vol 22 (9) ◽

pp. 4793-4813 ◽

Cited By ~ 3

Author(s):

Seungwoo Chang ◽

Wendy Graham ◽

Jeffrey Geurink ◽

Nisai Wanakule ◽

Tirusew Asefa

Keyword(s):

Climate Change ◽

Surface Water ◽

Water Use ◽

Groundwater Level ◽

Water Demand ◽

Environmental Regulations ◽

Hydrologic Model ◽

Tampa Bay ◽

Future Climate ◽

Future Climate Change

Abstract. General circulation models (GCMs) have been widely used to simulate current and future climate at the global scale. However, the development of frameworks to apply GCMs to assess potential climate change impacts on regional hydrologic systems, ability to meet future water demand, and compliance with water resource regulations is more recent. In this study eight GCMs were bias-corrected and downscaled using the bias correction and stochastic analog (BCSA) downscaling method and then used, together with three ET0 methods and eight different water use scenarios, to drive an integrated hydrologic model previously developed for the Tampa Bay region in western central Florida. Variance-based sensitivity analysis showed that changes in projected streamflow were very sensitive to GCM selection, but relatively insensitive to ET0 method or water use scenario. Changes in projections of groundwater level were sensitive to both GCM and water use scenario, but relatively insensitive to ET0 method. Five of eight GCMs projected a decrease in streamflow and groundwater availability in the future regardless of water use scenario or ET method. For the business as usual water use scenario all eight GCMs indicated that, even with active water conservation programs, increases in public water demand projected for 2045 could not be met from ground and surface water supplies while achieving current groundwater level and surface water flow regulations. With adoption of 40 % wastewater reuse for public supply and active conservation four of the eight GCMs indicate that 2045 public water demand could be met while achieving current environmental regulations; however, drier climates would require a switch from groundwater to surface water use. These results indicate a high probability of a reduction in future freshwater supply in the Tampa Bay region if environmental regulations intended to protect current aquatic ecosystems do not adapt to the changing climate. Broad interpretation of the results of this study may be limited by the fact that all future water use scenarios assumed that increases in water demand would be the result of intensification of water use on existing agricultural, industrial, and urban lands. Future work should evaluate the impacts of a range of potential land use change scenarios, with associated water use change projections, over a larger number of GCMs.

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Quantification of hydrologic impacts of climate change in a Mediterranean basin in Sardinia, Italy, through high-resolution simulations

Hydrology and Earth System Sciences ◽

10.5194/hess-18-5201-2014 ◽

2014 ◽

Vol 18 (12) ◽

pp. 5201-5217 ◽

Cited By ~ 29

Author(s):

M. Piras ◽

G. Mascaro ◽

R. Deidda ◽

E. R. Vivoni

Keyword(s):

Climate Change ◽

High Resolution ◽

Annual Runoff ◽

Hydrologic Model ◽

Future Climate ◽

Future Climate Change ◽

Runoff Generation ◽

Hydrologic Impacts ◽

Generation Mechanisms ◽

Impacts Of Climate Change

Abstract. Future climate projections robustly indicate that the Mediterranean region will experience a significant decrease of mean annual precipitation and an increase in temperature. These changes are expected to seriously affect the hydrologic regime, with a limitation of water availability and an intensification of hydrologic extremes, and to negatively impact local economies. In this study, we quantify the hydrologic impacts of climate change in the Rio Mannu basin (RMB), an agricultural watershed of 472.5 km2 in Sardinia, Italy. To simulate the wide range of runoff generation mechanisms typical of Mediterranean basins, we adopted a physically based, distributed hydrologic model. The high-resolution forcings in reference and future conditions (30-year records for each period) were provided by four combinations of global and regional climate models, bias-corrected and downscaled in space and time (from ~25 km, 24 h to 5 km, 1 h) through statistical tools. The analysis of the hydrologic model outputs indicates that the RMB is expected to be severely impacted by future climate change. The range of simulations consistently predict (i) a significant diminution of mean annual runoff at the basin outlet, mainly due to a decreasing contribution of the runoff generation mechanisms depending on water available in the soil; (ii) modest variations in mean annual runoff and intensification of mean annual discharge maxima in flatter sub-basins with clay and loamy soils, likely due to a higher occurrence of infiltration excess runoff; (iii) reduction of soil water content and actual evapotranspiration in most areas of the basin; and (iv) a drop in the groundwater table. Results of this study are useful to support the adoption of adaptive strategies for management and planning of agricultural activities and water resources in the region.

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Evaluation of impact of climate change and anthropogenic change on regional hydrology

10.5194/hess-2018-91 ◽

2018 ◽

Author(s):

Seungwoo Chang ◽

Wendy Graham ◽

Jeffrey Geurink ◽

Nisai Wanakule ◽

Tirusew Asefa

Keyword(s):

Climate Change ◽

Water Use ◽

Groundwater Level ◽

General Circulation ◽

General Circulation Models ◽

Hydrologic Model ◽

Tampa Bay ◽

Future Climate ◽

Future Climate Change ◽

Groundwater Levels

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Regional Flood Risk Projections under Climate Change

Journal of Hydrometeorology ◽

10.1175/jhm-d-20-0238.1 ◽

2021 ◽

Author(s):

Sanjib Sharma ◽

Michael Gomez ◽

Klaus Keller ◽

Robert Nicholas ◽

Alfonso Mejia

Keyword(s):

Climate Change ◽

Risk Management ◽

Flood Risk ◽

Management Strategies ◽

Hydrologic Model ◽

Future Climate Change ◽

Flood Inundation ◽

Flood Hazards ◽

Delaware River ◽

Risk Management Strategies

AbstractFlood-related risks to people and property are expected to increase in the future due to environmental and demographic changes. It is important to quantify and effectively communicate flood hazards and exposure to inform the design and implementation of flood risk management strategies. Here we develop an integrated modeling framework to assess projected changes in regional riverine flood inundation risks. The framework samples climate model outputs to force a hydrologic model and generate streamflow projections. Together with a statistical and hydraulic model, we use the projected streamflow to map the uncertainty of flood inundation projections for extreme flood events. We implement the framework for rivers across the state of Pennsylvania, United States. Our projections suggest that flood hazards and exposure across Pennsylvania are overall increasing with future climate change. Specific regions, including the main stem Susquehanna River, lower portion of the Allegheny basin and central portion of Delaware River basin, demonstrate higher flood inundation risks. In our analysis, the climate uncertainty dominates the overall uncertainty surrounding the flood inundation projection chain. The combined hydrologic and hydraulic uncertainties can account for as much as 37% of the total uncertainty. We discuss how this framework can provide regional and dynamic flood-risk assessments and help to inform the design of risk-management strategies.

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Quantification of hydrologic impacts of climate change in a Mediterranean basin in Sardinia, Italy, through high-resolution simulations

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-11-8493-2014 ◽

2014 ◽

Vol 11 (7) ◽

pp. 8493-8535

Author(s):

M. Piras ◽

G. Mascaro ◽

R. Deidda ◽

E. R. Vivoni

Keyword(s):

Climate Change ◽

High Resolution ◽

Annual Runoff ◽

Hydrologic Model ◽

Future Climate ◽

Future Climate Change ◽

Runoff Generation ◽

Hydrologic Impacts ◽

Generation Mechanisms ◽

Impacts Of Climate Change

Abstract. Future climate projections robustly indicate that the Mediterranean region will experience a significant decrease of mean annual precipitation and an increase in temperature. These changes are expected to seriously affect the hydrologic regime, with a limitation of water availability and an intensification of hydrologic extremes, and to negatively impact local economies. In this study, we quantify the hydrologic impacts of climate change in the Rio Mannu basin (RMB), an agricultural watershed of 472.5 km2 in Sardinia, Italy. To simulate the wide range of runoff generation mechanisms typical of Mediterranean basins, we adopted a physically-based, distributed hydrologic model. The high-resolution forcings in reference and future conditions (30-year records for each period) were provided by four combinations of global and regional climate models, bias-corrected and downscaled in space and time (from ~25 km, 24 h to 5 km, 1 h) through statistical tools. The analysis of the hydrologic model outputs indicates that the RMB is expected to be severely impacted by future climate change. The range of simulations consistently predict: (i) a significant diminution of mean annual runoff at the basin outlet, mainly due to a decreasing contribution of the runoff generation mechanisms depending on water available in the soil; (ii) modest variations in mean annual runoff and intensification of mean annual discharge maxima in flatter sub-basins with clay and loamy soils, likely due to a higher occurrence of infiltration excess runoff; (iii) reduction of soil water content and real evapotranspiration in most areas of the basin; and (iv) a drop in the groundwater table. Results of this study are useful to support the adoption of adaptive strategies for management and planning of agricultural activities and water resources in the region.

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Simulating Potential Impacts of Future Climate Change on Post-Rainy Season Sorghum Yields in India

Sustainability ◽

10.3390/su14010334 ◽

2021 ◽

Vol 14 (1) ◽

pp. 334

Author(s):

Keerthi Chadalavada ◽

Sridhar Gummadi ◽

Koteswara Rao Kundeti ◽

Dakshina Murthy Kadiyala ◽

Kumara Charyulu Deevi ◽

...

Keyword(s):

Climate Change ◽

Rainy Season ◽

Climate Model ◽

Crop Yields ◽

Coupled Model ◽

Daily Rainfall ◽

Future Climate ◽

Future Climate Change ◽

Air Temperatures ◽

Rcp 8.5

Given the wide use of the multi-climate model mean (MMM) for impact assessment studies, this work examines the fidelity of Coupled Model Intercomparison Project Phase 5 (CMIP5) in simulating the features of Indian summer monsoons as well as the post-rainy seasons for assessing the possible impacts of climate change on post-rainy season sorghum crop yields across India. The MMM simulations captured the spatial patterns and annual cycles of rainfall and surface air temperatures. However, bias was observed in the precipitation amounts and daily rainfall intensity. The trends in the simulations of MMM for both precipitation and temperatures were less satisfactory than the observed climate means. The Crop Environment Resource Synthesis (CERES)-sorghum model was used to estimate the potential impacts of future climate change on post-rainy season sorghum yield values. On average, post-rainy season sorghum yields are projected to vary between −4% and +40% as well as +10% and +59% in the near future (2040–2069) for RCP 4.5 and RCP 8.5, respectively, and between +20% and +70% (RCP 4.5) as well as +38% and +89% (RCP 8.5) in the far future (2070–2099). Even though surface air temperatures are increasing in future climate change projections, the findings suggest that an increase in the post-rainy season sorghum yields was due to an increase in the rainfall amounts up to 23% and an increase in the atmospheric CO2 levels by the end of the 21st century. The results suggest that the projected climate change during the post-rainy season over India is an opportunity for smallholders to capitalize on the increase in rainfall amounts and further increase sorghum yields with appropriate crop management strategies.

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Response of Water Resources to Future Climate Change in a High-Latitude River Basin

Sustainability ◽

10.3390/su11205619 ◽

2019 ◽

Vol 11 (20) ◽

pp. 5619 ◽

Cited By ~ 1

Author(s):

Peng Qi ◽

Guangxin Zhang ◽

Yi Jun Xu ◽

Zhikun Xia ◽

Ming Wang

Keyword(s):

Climate Change ◽

Water Resources ◽

Groundwater Recharge ◽

River Basin ◽

High Latitude ◽

Future Climate ◽

Future Climate Change ◽

Annual Streamflow ◽

Dry Conditions ◽

Rcp 8.5

Global water resources are affected by climate change as never before. However, it is still unclear how water resources in high latitudes respond to climate change. In this study, the water resource data for 2021–2050 in the Naoli River Basin, a high-latitude basin in China, are calculated by using the SWAT-Modflow Model and future climate scenarios RCP4.5 and RCP8.5. The results show a decreasing trend. When compared to the present, future streamflow is predicted to decrease by 2.73 × 108 m3 in 2021–2035 and by 1.51 × 108 m3 in 2036–2050 in the RCP4.5 scenario, and by 8.16 × 108 m3 in 2021–2035 and by 0.56 × 108 m3 in 2036–2050 in the RCP8.5 scenario, respectively. Similarly, groundwater recharge is expected to decrease by −1.79 × 108 m3 in 2021–2035 and −0.75 × 108 m3 in 2036–2050 in the RCP 4.5 scenario, and by −0.62 × 108 m3 in 2021–2035 and −0.12 × 108m3 in 2036–2050 in the RCP 8.5 scenario, respectively. The worst impact of climate change on water resources in the basin could be frequent occurrences of extremely wet and dry conditions. In the RCP 4.5 scenario, the largest annual streamflow is predicted to be almost 14 times that of the smallest one, while it is 18 times for the groundwater recharge. Meanwhile, in the RCP 8.5 scenario, inter-annual fluctuations are expected to be more severe. The difference is 17 times between the largest annual streamflow and the lowest annual one. Moreover, the value is 19 times between the largest and lowest groundwater recharge. This indicates a significant increase in conflict between water use and supply.

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Hydrological Responses to the Future Climate Change in a Data Scarce Region, Northwest China: Application of Machine Learning Models

Water ◽

10.3390/w11081588 ◽

2019 ◽

Vol 11 (8) ◽

pp. 1588 ◽

Cited By ~ 2

Author(s):

Zhu ◽

Yang ◽

Liu ◽

Wen ◽

Zhang ◽

...

Keyword(s):

Climate Change ◽

Artificial Intelligence ◽

Northwest China ◽

Future Climate ◽

Future Climate Change ◽

Hydrological Response ◽

Hydrological Responses ◽

Mountainous Watershed ◽

The Future ◽

Rcp 8.5

Forecasting the potential hydrological response to future climate change is an effective way of assessing the adverse effects of future climate change on water resources. Data-driven models based on machine learning algorithms have great application prospects for hydrological response forecasting as they require less developmental time, minimal input, and are relatively simple compared to dynamic or physical models, especially for data scarce regions. In this study, we employed an ensemble of eight General Circulation Models (GCMs) and two artificial intelligence-based methods (Support Vector Regression, SVR, and Extreme Learning Machine, ELM) to establish the historical streamflow response to climate change and to forecast the future response under Representative Concentration Pathway (RCP) scenarios 4.5 and 8.5 in a mountainous watershed in northwest China. We found that the artificial-intelligence-based SVR and ELM methods showed very good performances in the projection of future hydrological responses. The ensemble of GCM outputs derived very close historical hydrological hindcasts but had great uncertainty in future hydrological projections. Using the variables of GCM outputs as inputs to SVR can reduce intermediate downscaling links between variables and decrease the cumulative effect of bias in projecting future hydrological responses. Future precipitation in the study area will increase in the future under both scenarios, and this increasing trend is more significant under RCP 8.5 than under scenario 4.5. The results also indicate the streamflow change will be more sensitive to temperature (precipitation) under the RCP 8.5 (4.5) scenario. The findings and approach have important implications for hydrological response studies and the evaluation of impacts on localized regions similar to the mountainous watershed in this study.

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A modelling framework to project future climate change impacts on streamflow variability and extremes in the West River, China

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-364-44-2014 ◽

2014 ◽

Vol 364 ◽

pp. 44-50

Author(s):

Y. Fei ◽

T. Yeou-Koung ◽

R. Liliang

Keyword(s):

Climate Change ◽

River Basin ◽

Climate Change Impacts ◽

Hydrologic Model ◽

Future Climate ◽

Future Climate Change ◽

Mapping Technique ◽

The West ◽

Modelling Framework ◽

Streamflow Variability

Abstract. In this study, a hydrological modelling framework was introduced to assess the climate change impacts on future river flow in the West River basin, China, especially on streamflow variability and extremes. The modelling framework includes a delta-change method with the quantile-mapping technique to construct future climate forcings on the basis of observed meteorological data and the downscaled climate model outputs. This method is able to retain the signals of extreme weather events, as projected by climate models, in the constructed future forcing scenarios. Fed with the historical and future forcing data, a large-scale hydrologic model (the Variable Infiltration Capacity model, VIC) was executed for streamflow simulations and projections at daily time scales. A bootstrapping resample approach was used as an indirect alternative to test the equality of means, standard deviations and the coefficients of variation for the baseline and future streamflow time series, and to assess the future changes in flood return levels. The West River basin case study confirms that the introduced modelling framework is an efficient effective tool to quantify streamflow variability and extremes in response to future climate change.

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