Large-scale flood hazard assessment under climate change: A case study

Toosi, Amirhossein Shadmehri; Doulabian, Shahab; Tousi, Erfan Ghasemi; Calbimonte, Giancarlo Humberto; Alaghmand, Sina

doi:10.1016/j.ecoleng.2020.105765

Cited by 41 publications

(15 citation statements)

References 21 publications

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“…To highlight the largest impacts of climate change (i.e., considering the largest change in temperature, radiative forcing (>8.5 W/m 2 ) and concentrations (>1370 CO 2 ppm) for 2100 [47], the Representative Concentration Pathway 8.5 (RCP8.5) scenario was selected. This RCP has also been used to evaluate climate change in droughts [48] and hydroelectric power generation [49] in Ecuador. The database includes monthly rainfall and temperature records from meteorological stations and a hydrological station managed by INAMHI (National Meteorological and Hydrological Institute of Ecuador) (Table 1).…”

Section: Gcms Datamentioning

confidence: 99%

“…These statistics facilitate the determination of how much of the overall RMSE difference in the patterns is attributable to a difference in variance and how much is due to poor pattern correlation of observed to simulated values, based on Equations ( 1) and ( 2) [48]. The plot is widely used to evaluate or to track changes in the performance of complex models such as geophysical phenomena [23,[49][50][51].…”

Section: Assessment Of Gcmsmentioning

confidence: 99%

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Impacts of Climate Change on the Precipitation and Streamflow Regimes in Equatorial Regions: Guayas River Basin

Ilbay-Yupa

Ilbay

Zubieta

et al. 2021

Water

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The effects of climate change projected for 2050 to 2079 relative to the 1968–2014 reference period were evaluated using 39 CMIP5 models under the RCP8.5 emissions scenario in the Guayas River basin. The monthly normalized precipitation index (SPI) was used in this study to assess the impact of climate change for wet events and droughts from a meteorological perspective. The GR2M model was used to project changes in the streamflow of the Daule River. The climate projection was based on the four rigorously selected models to represent the climate of the study area. On average, an increase in temperature (~2 °C) and precipitation (~6%) is expected. A 7% increase in precipitation would result in a 10% increase in streamflow for flood periods, while an 8% decrease in precipitation could result in approximately a 60% reduction in flow for dry periods. The analysis of droughts shows that they will be more frequent and prolonged in the highlands (Andes) and the middle part of the basin. In the future, wet periods will be less frequent but of greater duration and intensity on the Ecuadorian coast. These results point to future problems such as water deficit in the dry season but also increased streamflow for floods during the wet season. This information should be taken into account in designing strategies for adaptation to climate change.

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Section: Gcms Datamentioning

confidence: 99%

Section: Assessment Of Gcmsmentioning

confidence: 99%

Impacts of Climate Change on the Precipitation and Streamflow Regimes in Equatorial Regions: Guayas River Basin

Ilbay-Yupa

Ilbay

Zubieta

et al. 2021

Water

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“…The devastating effects of floods and the advancement of technology have led to a growing trend of flood studies from the past to the present throughout the world, including Iran (Pham et al, 2021;Ahiablame and Shakya, 2016;Ogato et al, 2020;Pathak et al, 2020;Moisello et al 2013;Desalegn and Mulu, 2021;Tang et al 2021;Xiao et al 2017;Jahangir et al 2019;Mohammadi et al 2021;Sepehri et al 2019Mirzaei et al 2021Avand et al 2021;Goodarzi et al 2019;Pourghasemi et al 2020;Arabameri et al 2019;Shadmehritoosi et al 2020;Panahi et al 2021;SajediHosseini et al 2020;Shahabi et al 2021;Komi et al 2017;Nazeer and Bork, 2021;Mishra and Sinha, 2020;Figueiredo et al 2020;Zehra et al 2019;Erena and Worku, 2019). Heavy rains, low water flow network capacity, poor land cover and topographic factors are the most important causes of floods in an area (Osei et al 2021).…”

Section: Introductionmentioning

confidence: 99%

An Assessment of the Integrated Multi-Criteria and New Models Efficiency in Watershed Flood Mapping

Solaimani

Shokrian

Darvishi

2022

Water Resour Manage

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Nowadays, with significant climate change, the trend of environmental hazards is increasing.In the meantime, floods have shown a growing trend than other hazards. Haraz watershed in northern Iran is prone to floods due to the heavy rainfall with irregular pattern. Therefore, combining different methods and examining new approaches is an essential step in the development of methods in this field. In the present study, Analytical Network Process, Analytic Hierarchy Process and Fuzzy Analytic Hierarchy Process models were combined with Ordered Weighted Average, Weighted Linear Combination, Local Weighted Linear Combination models to prepare a flood risk map. The performance of two new models, Weighted Multi-Criteria Analysis and Geo-Technique for Order of Preference by Similarity to Ideal Solution, was also evaluated in this field. The results of the models showed that in general the basin is in a moderate risk situation. Meanwhile, the south-eastern parts of the basin show a high flood risk situation. Also, by comparing the models, it was found that the combination of multi-criteria models and the use of Weighted Multi-Criteria Analysis and Geo-Technique for Order of Preference by Similarity to Ideal Solution models are very effective and efficient for preparing flood risk maps.

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“…Rising air temperatures lead to increases in the atmosphere vapor holding capacity and changes in the precipitation frequency and intensity. These changes will significantly affect the hydrological cycle, which further influences water supplies on the local, regional and global scales [2], with potentially powerful effects on the runoff mechanisms [3,4] and natural disasters such as floods [5]. Particularly, the impact of climate change on runoffs receives relatively more attention due to its close relationship with the agriculture, hydropower, tourism and ecology around rivers [6].…”

Section: Introductionmentioning

confidence: 99%

Quantifying the Impact of Future Climate Change on Runoff in the Amur River Basin Using a Distributed Hydrological Model and CMIP6 GCM Projections

Wen

Gao

2021

Atmosphere

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The Amur River is one of the top ten longest rivers in the world, and its hydrological response to future climate change has been rarely investigated. In this study, the outputs of four GCMs in the Coupled Model Intercomparison Project Phase 6 (CMIP6) were corrected and downscaled to drive a distributed hydrological model. Then, the spatial variations of runoff changes under the future climate conditions in the Amur River Basin were quantified. The results suggest that runoffs will tend to increase in the future period (2021–2070) compared with the baseline period (1961–2010), particularly in August and September. Differences were also found among different GCMs and scenarios. The ensemble mean of the GCMs suggests that the basin-averaged annual precipitation will increase by 14.6% and 15.2% under the SSP2-4.5 and SSP5-8.5 scenarios, respectively. The increase in the annual runoff under the SSP2-4.5 scenario (22.5%) is projected to be larger than that under the SSP5-8.5 scenario (19.2%) at the lower reach of the main channel. Future climate changes also tend to enhance the flood peak and flood volume. The findings of this study bring new understandings of the hydrological response to future climate changes and are helpful for water resource management in Eurasia.

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Large-scale flood hazard assessment under climate change: A case study

Cited by 41 publications

References 21 publications

Impacts of Climate Change on the Precipitation and Streamflow Regimes in Equatorial Regions: Guayas River Basin

Impacts of Climate Change on the Precipitation and Streamflow Regimes in Equatorial Regions: Guayas River Basin

An Assessment of the Integrated Multi-Criteria and New Models Efficiency in Watershed Flood Mapping

Quantifying the Impact of Future Climate Change on Runoff in the Amur River Basin Using a Distributed Hydrological Model and CMIP6 GCM Projections

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