scholarly journals Coupling physical understanding and statistical modeling to estimate ice jam flood frequency in the northern Peace-Athabasca Delta under climate change

Author(s):  
Jonathan R. Lamontagne ◽  
Martin Jasek ◽  
Jared D. Smith
2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yukiko Hirabayashi ◽  
Haireti Alifu ◽  
Dai Yamazaki ◽  
Yukiko Imada ◽  
Hideo Shiogama ◽  
...  

AbstractThe ongoing increases in anthropogenic radiative forcing have changed the global water cycle and are expected to lead to more intense precipitation extremes and associated floods. However, given the limitations of observations and model simulations, evidence of the impact of anthropogenic climate change on past extreme river discharge is scarce. Here, a large ensemble numerical simulation revealed that 64% (14 of 22 events) of floods analyzed during 2010-2013 were affected by anthropogenic climate change. Four flood events in Asia, Europe, and South America were enhanced within the 90% likelihood range. Of eight snow-induced floods analyzed, three were enhanced and four events were suppressed, indicating that the effects of climate change are more likely to be seen in the snow-induced floods. A global-scale analysis of flood frequency revealed that anthropogenic climate change enhanced the occurrence of floods during 2010-2013 in wide area of northern Eurasia, part of northwestern India, and central Africa, while suppressing the occurrence of floods in part of northeastern Eurasia, southern Africa, central to eastern North America and South America. Since the changes in the occurrence of flooding are the results of several hydrological processes, such as snow melt and changes in seasonal and extreme precipitation, and because a climate change signal is often not detectable from limited observation records, large ensemble discharge simulation provides insights into anthropogenic effects on past fluvial floods.


2015 ◽  
Vol 19 (1) ◽  
pp. 379-387 ◽  
Author(s):  
I. Andrés-Doménech ◽  
R. García-Bartual ◽  
A. Montanari ◽  
J. B. Marco

Abstract. Measuring the impact of climate change on flood frequency is a complex and controversial task. Identifying hydrological changes is difficult given the factors, other than climate variability, which lead to significant variations in runoff series. The catchment filtering role is often overlooked and thus may hinder the correct identification of climate variability signatures on hydrological processes. Does climate variability necessarily imply hydrological variability? This research aims to analytically derive the flood frequency distribution based on realistic hypotheses about the rainfall process and the rainfall–runoff transformation. The annual maximum peak flow probability distribution is analytically derived to quantify the filtering effect of the rainfall–runoff process on climate change. A sensitivity analysis is performed according to typical semi-arid Mediterranean climatic and hydrological conditions, assuming a simple but common scheme for the rainfall–runoff transformation in small-size ungauged catchments, i.e. the CN-SCS model. Variability in annual maximum peak flows and its statistical significance are analysed when changes in the climatic input are introduced. Results show that depending on changes in the annual number of rainfall events, the catchment filtering role is particularly significant, especially when the event rainfall volume distribution is not strongly skewed. Results largely depend on the return period: for large return periods, peak flow variability is significantly affected by the climatic input, while for lower return periods, infiltration processes smooth out the impact of climate change.


2021 ◽  
Author(s):  
Rebecca Alexandre ◽  
Iain Willis

<p>The re/insurance, banking and mortgage sectors play an essential role in facilitating economic stability. As climate change-related financial risks increase, there has long been a need for tools that contribute to the global industry’s current and future flood risk resiliency. Recognising this gap, JBA Risk Management has pioneered use of climate model data for rapidly deriving future flood risk metrics to support risk-reflective pricing strategies and mortgage analysis for Hong Kong.</p><p>JBA’s established method uses daily temporal resolution precipitation and surface air temperature Regional Climate Model (RCM) data from the Earth System Grid Federation’s CORDEX experiment. Historical and future period RCM data were processed for Representative Concentration Pathways (RCPs) 2.6 and 8.6, and time horizons 2046-2050 and 2070-2080 and used to develop fluvial and pluvial hydrological model change factors for Hong Kong. These change factors were applied to baseline fluvial and pluvial flood depths and extents, extracted from JBA’s high resolution 30m Hong Kong Flood Map. From these, potential changes in flood event frequency and severity for each RCP and time horizon combination were estimated.</p><p>The unique flood frequency and severity profiles for each flood type were then analysed with customised vulnerability functions, linking water depth to expected damage over time for residential and commercial building risks. This resulted in quantitative fluvial and pluvial flood risk metrics for Hong Kong.</p><p>Newly released, Hong Kong Climate Change Pricing Data is already in use by financial institutions. When combined with property total sum insured data, this dataset provides the annualised cost of flood damage for a range of future climate scenarios. For the first time, our industry has a tool to quantify baseline and future flood risk and set risk-reflective pricing for Hong Kong portfolios.</p><p>JBA’s method is adaptable for global use and underwriting tools are already available for the UK and Australia with the aim of improving future financial flood risk mitigation and management. This presentation will outline the method, provide a comparison of baseline and climate change flood impacts for Hong Kong and discuss the wider implications for our scientific and financial industries.</p>


Author(s):  
Yar M. Taraky ◽  
Yongbo Liu ◽  
Bahram Gharabaghi ◽  
Edward McBean ◽  
Prasad Daggupati ◽  
...  

While climate change impacts vary globally, for the Kabul River Basin (KRB), concerns are primarily associated with frequent flooding. This research describes the influence of headwater reservoirs on projections of climate change impacts and flood frequency, and how the riparian countries can benefit from storing of floodwaters for use during dry seasons. Six climate change scenarios and two Representative Concentration Pathways (RCPs) are used in three periods of a quarter-century each. The Soil and Water Assessment Tool (SWAT) is used to assess how the proposed reservoirs will reduce flooding by ~38% during the wet season, reduce the flood frequency from five to 25 years return period, and increase low flows by ~110% during the dry season, which reflect an ~17.5% reduction in the glacier-covered area by the end of the century. The risks and benefits of reservoirs are highlighted in light of the developmental goals of Afghanistan and Pakistan.


2000 ◽  
Vol 4 (3) ◽  
pp. 393-405 ◽  
Author(s):  
D. Cameron ◽  
K. Beven ◽  
P. Naden

Abstract. This paper explores the potential for assessing the impacts of climate change upon flood frequency for the gauged, upland Wye catchment at Plynlimon, Wales, UK, while taking account of uncertainty in modelling rainfall-runoff processes under current conditions. A continuous simulation methodology which uses a stochastic rainfall model to drive the rainfall-runoff model TOPMODEL is utilised. Behavioural parameter sets for both the rainfall model and TOPMODEL are identified prior to the climate change runs using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. The "medium-high" UKCIP98 climate change scenario, obtained from the HadCM2 GCM simulations, is used as a starting point for a variety of different scenarios at the catchment scale. It is demonstrated that while the scenarios have only a small impact upon the likelihood weighted flood frequency uncertainty bounds in comparison with the current condition scenario, the risk of a given discharge as an element in the distribution of T year floods is changed. This underlines the need to account explicitly for uncertainty within hydrological modelling, especially in estimating the impacts of climate change. Keywords: Climate change; Floods; Frequency; TOPMODEL


Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 273 ◽  
Author(s):  
Fatemeh Fadia Maghsood ◽  
Hamidreza Moradi ◽  
Ali Reza Massah Bavani ◽  
Mostafa Panahi ◽  
Ronny Berndtsson ◽  
...  

This study assessed the impact of climate change on flood frequency and flood source area at basin scale considering Coupled Model Intercomparison Project phase 5 General Circulation Models (CMIP5 GCMs) under two Representative Concentration Pathways (RCP) scenarios (2.6 and 8.5). For this purpose, the Soil and Water Assessment Tool (SWAT) hydrological model was calibrated and validated for the Talar River Basin in northern Iran. Four empirical approaches including the Sangal, Fill–Steiner, Fuller, and Slope-based methods were used to estimate the Instantaneous Peak Flow (IPF) on a daily basis. The calibrated SWAT model was run under the two RCP scenarios using a combination of twenty GCMs from CMIP5 for the near future (2020–40). To assess the impact of climate change on flood frequency pattern and to quantify the contribution of each subbasin on the total discharge from the Talar River Basin, Flood Frequency Index (FFI) and Subbasin Flood Source Area Index (SFSAI) were used. Results revealed that the projected climate change will likely lead to an average discharge decrease in January, February, and March for both RCPs and an increase in September and October for RCP 8.5. The maximum and minimum temperature will likely increase for all months in the near future. The annual precipitation could increase by more than 20% in the near future. This is likely to lead to an increase of IPF. The results can help managers and policy makers to better define mitigation and adaptation strategies for basins in similar climates.


Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2266 ◽  
Author(s):  
Enrique Soriano ◽  
Luis Mediero ◽  
Carlos Garijo

Climate projections provided by EURO-CORDEX predict changes in annual maximum series of daily rainfall in the future in some areas of Spain because of climate change. Precipitation and temperature projections supplied by climate models do not usually fit exactly the statistical properties of the observed time series in the control period. Bias correction methods are used to reduce such errors. This paper seeks to find the most adequate bias correction techniques for temperature and precipitation projections that minimizes the errors between observations and climate model simulations in the control period. Errors in flood quantiles are considered to identify the best bias correction techniques, as flood quantiles are used for hydraulic infrastructure design and safety assessment. In addition, this study aims to understand how the expected changes in precipitation extremes and temperature will affect the catchment response in flood events in the future. Hydrological modelling is required to characterize rainfall-runoff processes adequately in a changing climate, in order to estimate flood changes expected in the future. Four catchments located in the central-western part of Spain have been selected as case studies. The HBV hydrological model has been calibrated in the four catchments by using the observed precipitation, temperature and streamflow data available on a daily scale. Rainfall has been identified as the most significant input to the model, in terms of its influence on flood response. The quantile mapping polynomial correction has been found to be the best bias correction method for precipitation. A general reduction in flood quantiles is expected in the future, smoothing the increases identified in precipitation quantiles by the reduction of soil moisture content in catchments, due to the expected increase in temperature and decrease in mean annual precipitations.


2013 ◽  
Vol 14 (3) ◽  
pp. 1215-1227 ◽  
Author(s):  
A. L. Kay ◽  
S. M. Crooks ◽  
H. N. Davies ◽  
C. Prudhomme ◽  
N. S. Reynard

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