Impact of climate change on floods in Pamplona (Spain) by using climate change projections and a distributed hydrological model

Author(s):  
Marco Lompi ◽  
Luis Mediero ◽  
Enrica Caporali

<p>Understanding how floods are expected to change is essential for decision making and flood risk management, as flood risks are expected to increase in the future. Several studies have analysed the impact of climate change on flood risks with rainfall-runoff models and climate projections as input data. Nevertheless, most of these studies involve large-scale river basins instead of focusing on smaller river basins or points of interest like urban areas. This study quantifies the expected changes in flood quantiles at the River Arga in the city of Pamplona (Spain) within the SAFERDAMS project (PID2019-107027RB-I00) funded by the Spanish Ministry of Science and Innovation. It uses climate change projections from 12 climate models of the EURO-CORDEX programme for two Representative Concentration Pathways - RCPs as input data of the RIBS distributed hydrological model (Garrote and Bras 1995 ab, JoH). The analysis considers seven return periods (2, 5, 10, 50, 100, 500 and 1000 years), two greenhouse gas emission scenarios (RCP4.5 and RCP8.5) and three time windows (2011-2040, 2041-2070 and 2070-2100).</p><p>First, the RIBS model has been calibrated with a set of objective functions to minimise the bias between simulations and observations recorded at a streamflow-gauging station located in the Arga River in Pamplona. The seven greatest flood events occurred in Pamplona in the last decade are considered. A long set of random combinations of model parameter values are used. The combination of parameter values that led to the smallest errors were selected.</p><p>Second, 24-h design rainfall storms with a time step of 1 h in the current scenario at a set of rainfall gauge stations in the Arga River catchment are obtained by using an extreme frequency analysis. Expected changes in daily rainfall quantiles in the Arga River catchment obtained by processing climate change projections are used (Garijo and Mediero 2019, Water). Current and future design rainfall storms were obtained for the seven return periods, two RCPs and three time windows. The input data in the RIBS model are provided in a raster format. Hence, design rainfall storms were transformed into spatial distributions of precipitation with the Thiessen polygons technique.</p><p>The findings show a decrease in design peak discharges for return periods smaller than 10 years and an increase for the 500- and 1000-year floods for both RCPs in the three time windows. However, 50- and 100-year return period flood quantiles are expected to increase especially in the 2041-2070 and 2071-2100 time windows only in the emission scenario RCP8.5. The emission scenario RCP8.5 always provides greater increases in flood quantiles than RCP4.5, except for the more frequent floods (2, 5 and 10 years) in the time window 2011-2040. The increases of design discharges are 10-30% higher in RCP8.5 than in RCP4.5 for the greatest return periods. Therefore, flood magnitude changes for the most extreme events seem to be related to the evolution of greenhouse gasses emissions, following the same behaviour of the RCPs: the greatest expected changes are in the 2040 for the RCP4.5 and in the 2100 for the RCP8.5.</p>

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 792
Author(s):  
Marco Lompi ◽  
Luis Mediero ◽  
Enrica Caporali

Understanding how the design hyetographs and floods will change in the future is essential for decision making in flood management plans. This study provides a methodology to quantify the expected changes in future hydraulic risks at the catchment scale in the city of Pamplona. It considers climate change projections supplied by 12 climate models, 7 return periods, 2 emission scenarios (representative concentration pathway RCP 4.5 and RCP 8.5), and 3 time windows (2011–2040, 2041–2070, and 2070–2100). The Real-time Interactive Basin Simulator (RIBS) distributed hydrological model is used to simulate rainfall-runoff processes at the catchment scale. The results point to a decrease in design peak discharges for return periods smaller than 10 years and an increase for the 500- and 1000-year floods for both RCPs in the three time windows. The emission scenario RCP 8.5 usually provides the greatest increases in flood quantiles. The increase of design peak discharges is almost 10–30% higher in RCP 8.5 than in RCP 4.5. Change magnitudes for the most extreme events seem to be related to the greenhouse gas emission predictions in each RCP, as the greatest expected changes are found in 2040 for the RCP 4.5 and in 2100 for the RCP 8.5.


2017 ◽  
Author(s):  
Andreas M. Jobst ◽  
Daniel G. Kingston ◽  
Nicolas J. Cullen ◽  
Josef Schmid

Abstract. As climate change is projected to alter both temperature and precipitation, snow controlled mid-latitude catchments are expected to experience substantial shifts in their seasonal regime, which will have direct implications for water management. In order to provide authoritative projections of climate change impacts, the uncertainty inherent to all components of the modelling chain needs to be accounted for. This study assesses the uncertainty in potential impacts of climate change on the hydro-climate of New Zealand’s largest catchment (the Clutha River) using a fully distributed hydrological model (WaSiM) and unique ensemble encompassing different uncertainty sources: General Circulation Model (GCM), emission scenario, bias correction and snow model. The inclusion of snow models is particularly important, given that (1) they are a rarely considered aspect of uncertainty in hydrological modelling studies, and (2) snow has a considerable influence on seasonal patterns of river flow in alpine catchments such as the Clutha. Projected changes in river flow for the 2050s and 2090s encompass substantial increases in streamflow from May to October, and a decline between December and March. The dominant drivers are changes in the seasonal distribution of precipitation (for the 2090s +25 to +76 % in winter) and substantial decreases in the seasonal snow storage due to temperature increase. A quantitative comparison of uncertainty identified GCM structure as the dominant contributor in the seasonal streamflow signal (44–57 %) followed by emission scenario (16–49 %), bias correction (4–22 %) and snow model (3–10 %). While these findings suggest that the role of the snow model is comparatively small, its contribution to the overall uncertainty was still found to be noticeable for winter and summer.


2021 ◽  
Author(s):  
Tze Huey Tam ◽  
Muhammad Zulkarnain Abdul Rahman ◽  
Sobri Harun ◽  
Sophal Try ◽  
Shamsuddin Shahid ◽  
...  

Abstract Climate change can significantly alter the hydrological cycle and lead to severe hydrological disasters. This study aims to determine the impact of climate change on flood hazards in the Kelantan River Basin of Malaysia. The Climate Change Factor (CCF) is used to calculate 24-hour design rainfall with 50, 100 and 200-year return periods. A distributed hydrological model, Rainfall-Runoff-Inundation (RRI), is used to simulate flood inundation under current and future climate scenarios. The results indicate an increase in 50, 100, and 200 years, design rainfall, streamflow and flood hazard. The expected design rainfall and streamflow for 50, 100, and 200 years would increase by 36.6%, 37.9%, 42.7%, and 43.2%, 32.7%, 36.5%, respectively. Flood hazard is spatially variable in the Kelantan River Basin. Tanah Merah is the town that would face a significant increase in future flooding. The findings of this study can aid relevant agencies and government departments to comprehend the current and future flood hazard situation in the Kelantan River Basin. It would also assist them in formulating appropriate flood management strategies to mitigate future severe flood hazards.


2018 ◽  
Vol 22 (6) ◽  
pp. 3125-3142 ◽  
Author(s):  
Andreas M. Jobst ◽  
Daniel G. Kingston ◽  
Nicolas J. Cullen ◽  
Josef Schmid

Abstract. As climate change is projected to alter both temperature and precipitation, snow-controlled mid-latitude catchments are expected to experience substantial shifts in their seasonal regime, which will have direct implications for water management. In order to provide authoritative projections of climate change impacts, the uncertainty inherent to all components of the modelling chain needs to be accounted for. This study assesses the uncertainty in potential impacts of climate change on the hydro-climate of a headwater sub-catchment of New Zealand's largest catchment (the Clutha River) using a fully distributed hydrological model (WaSiM) and unique ensemble encompassing different uncertainty sources: general circulation model (GCM), emission scenario, bias correction and snow model. The inclusion of snow models is particularly important, given that (1) they are a rarely considered aspect of uncertainty in hydrological modelling studies, and (2) snow has a considerable influence on seasonal patterns of river flow in alpine catchments such as the Clutha. Projected changes in river flow for the 2050s and 2090s encompass substantial increases in streamflow from May to October, and a decline between December and March. The dominant drivers are changes in the seasonal distribution of precipitation (for the 2090s +29 to +84 % in winter) and substantial decreases in the seasonal snow storage due to temperature increase. A quantitative comparison of uncertainty identified GCM structure as the dominant contributor in the seasonal streamflow signal (44–57 %) followed by emission scenario (16–49 %), bias correction (4–22 %) and snow model (3–10 %). While these findings suggest that the role of the snow model is comparatively small, its contribution to the overall uncertainty was still found to be noticeable for winter and summer.


2020 ◽  
Author(s):  
Sugata Narsey ◽  
Josephine R. Brown ◽  
Robert A. Colman ◽  
Francois Delage ◽  
Scott Brendan Power ◽  
...  

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 715
Author(s):  
Cristina Andrade ◽  
Sandra Mourato ◽  
João Ramos

Climate change is expected to influence cooling and heating energy demand of residential buildings and affect overall thermal comfort. Towards this end, the heating (HDD) and cooling (CDD) degree-days along with HDD + CDD were computed from an ensemble of seven high-resolution bias-corrected simulations attained from EURO-CORDEX under two Representative Concentration Pathways (RCP4.5 and RCP8.5). These three indicators were analyzed for 1971–2000 (from E-OBS) and 2011–2040, and 2041–2070, under both RCPs. Results predict a decrease in HDDs most significant under RCP8.5. Conversely, it is projected an increase of CDD values for both scenarios. The decrease in HDDs is projected to be higher than the increase in CDDs hinting to an increase in the energy demand to cool internal environments in Portugal. Statistically significant linear CDD trends were only found for 2041–2070 under RCP4.5. Towards 2070, higher(lower) CDD (HDD and HDD + CDD) anomaly amplitudes are depicted, mainly under RCP8.5. Within the five NUTS II


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hector Lobeto ◽  
Melisa Menendez ◽  
Iñigo J. Losada

AbstractExtreme waves will undergo changes in the future when exposed to different climate change scenarios. These changes are evaluated through the analysis of significant wave height (Hs) return values and are also compared with annual mean Hs projections. Hourly time series are analyzed through a seven-member ensemble of wave climate simulations and changes are estimated in Hs for return periods from 5 to 100 years by the end of the century under RCP4.5 and RCP8.5 scenarios. Despite the underlying uncertainty that characterizes extremes, we obtain robust changes in extreme Hs over more than approximately 25% of the ocean surface. The results obtained conclude that increases cover wider areas and are larger in magnitude than decreases for higher return periods. The Southern Ocean is the region where the most robust increase in extreme Hs is projected, showing local increases of over 2 m regardless the analyzed return period under RCP8.5 scenario. On the contrary, the tropical north Pacific shows the most robust decrease in extreme Hs, with local decreases of over 1.5 m. Relevant divergences are found in several ocean regions between the projected behavior of mean and extreme wave conditions. For example, an increase in Hs return values and a decrease in annual mean Hs is found in the SE Indian, NW Atlantic and NE Pacific. Therefore, an extrapolation of the expected change in mean wave conditions to extremes in regions presenting such divergences should be adopted with caution, since it may lead to misinterpretation when used for the design of marine structures or in the evaluation of coastal flooding and erosion.


2021 ◽  
Vol 9 (6) ◽  
pp. 595
Author(s):  
Américo Soares Ribeiro ◽  
Carina Lurdes Lopes ◽  
Magda Catarina Sousa ◽  
Moncho Gomez-Gesteira ◽  
João Miguel Dias

Ports constitute a significant influence in the economic activity in coastal areas through operations and infrastructures to facilitate land and maritime transport of cargo. Ports are located in a multi-dimensional environment facing ocean and river hazards. Higher warming scenarios indicate Europe’s ports will be exposed to higher risk due to the increase in extreme sea levels (ESL), a combination of the mean sea level, tide, and storm surge. Located on the west Iberia Peninsula, the Aveiro Port is located in a coastal lagoon exposed to ocean and river flows, contributing to higher flood risk. This study aims to assess the flood extent for Aveiro Port for historical (1979–2005), near future (2026–2045), and far future (2081–2099) periods scenarios considering different return periods (10, 25, and 100-year) for the flood drivers, through numerical simulations of the ESL, wave regime, and riverine flows simultaneously. Spatial maps considering the flood extent and calculated area show that most of the port infrastructures' resilience to flooding is found under the historical period, with some marginal floods. Under climate change impacts, the port flood extent gradually increases for higher return periods, where most of the terminals are at high risk of being flooded for the far-future period, whose contribution is primarily due to mean sea-level rise and storm surges.


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