scholarly journals Climate and hydrological variability: the catchment filtering role

2015 ◽  
Vol 19 (1) ◽  
pp. 379-387 ◽  
Author(s):  
I. Andrés-Doménech ◽  
R. García-Bartual ◽  
A. Montanari ◽  
J. B. Marco
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Peak Flow ◽  
Flood Frequency ◽  
Annual Maximum ◽  
Return Periods ◽  
Rainfall Runoff ◽  
Maximum Peak ◽  
Hydrological Variability ◽  
The Impact

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.

scholarly journals Climate and hydrological variability: the catchment filtering role

2014 ◽  
Vol 11 (9) ◽  
pp. 10411-10430 ◽  
Author(s):  
I. Andrés-Doménech ◽  
R. García-Bartual ◽  
A. Montanari ◽  
J. B. Marco
Keyword(s):  
Climate Change ◽  
Climate Variability ◽  
Peak Flow ◽  
Flood Frequency ◽  
Correct Identification ◽  
Return Periods ◽  
Rainfall Runoff ◽  
Hydrological Variability ◽  
Runoff Series ◽  
The Impact

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 in fact, this may hinder the correct identification of climate variability signatures on hydrological processes. Does climate variability necessarily imply hydrological variability? The research herein presented aims to analytically derive the flood frequency distribution basing on realistic hypotheses about the rainfall process and the rainfall–runoff transformation. The peak flow probability distribution is analytically derived to quantify the filtering effect operated by 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 peak flows and its statistical significance are analysed when changes in the climatic input are introduced. Results show that in regard to changes in the annual number of rainfall events, the catchment filtering role is particularly significant 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 impacted by the climatic input, while for lower return periods, infiltration processes smooth out the effects of climate change.

scholarly journals Anthropogenic climate change has changed frequency of past flood during 2010-2013

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Yukiko Hirabayashi ◽  
Haireti Alifu ◽  
Dai Yamazaki ◽  
Yukiko Imada ◽  
Hideo Shiogama ◽  
...  
Keyword(s):  
Climate Change ◽  
South America ◽  
Radiative Forcing ◽  
Water Cycle ◽  
Flood Frequency ◽  
Anthropogenic Climate Change ◽  
Climate Change Signal ◽  
Northern Eurasia ◽  
Large Ensemble ◽  
The Impact

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.

Bias correction of extreme values of high resolution climate simulations for risk analysis.

2021 ◽  
Author(s):  
luis Augusto sanabria ◽  
Xuerong Qin ◽  
Jin Li ◽  
Robert Peter Cechet
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Extreme Values ◽  
The Body ◽  
Future Climate ◽  
Return Periods ◽  
Climate Conditions ◽  
Mitigation And Adaptation ◽  
Climate Simulations ◽  
The Impact

Abstract Most climatic models show that climate change affects natural perils' frequency and severity. Quantifying the impact of future climate conditions on natural hazard is essential for mitigation and adaptation planning. One crucial factor to consider when using climate simulations projections is the inherent systematic differences (bias) of the modelled data compared with observations. This bias can originate from the modelling process, the techniques used for downscaling of results, and the ensembles' intrinsic variability. Analysis of climate simulations has shown that the biases associated with these data types can be significant. Hence, it is often necessary to correct the bias before the data can be reliably used for further analysis. Natural perils are often associated with extreme climatic conditions. Analysing trends in the tail end of distributions are already complicated because noise is much more prominent than that in the mean climate. The bias of the simulations can introduce significant errors in practical applications. In this paper, we present a methodology for bias correction of climate simulated data. The technique corrects the bias in both the body and the tail of the distribution (extreme values). As an illustration, maps of the 50 and 100-year Return Period of climate simulated Forest Fire Danger Index (FFDI) in Australia are presented and compared against the corresponding observation-based maps. The results show that the algorithm can substantially improve the calculation of simulation-based Return Periods. Forthcoming work will focus on the impact of climate change on these Return Periods considering future climate conditions.

scholarly journals On the asymptotic behavior of flood peak distributions

2006 ◽  
Vol 10 (2) ◽  
pp. 233-243 ◽  
Author(s):  
E. Gaume
Keyword(s):  
Frequency Distribution ◽  
Return Period ◽  
Asymptotic Properties ◽  
Flood Frequency ◽  
Point Of View ◽  
Rainfall Runoff ◽  
New Approach ◽  
Flood Peak ◽  
Flood Quantiles ◽  
The Impact

Abstract. This paper presents some analytical results and numerical illustrations on the asymptotic properties of flood peak distributions obtained through derived flood frequency approaches. It confirms and extends the results of previous works: i.e. the shape of the flood peak distributions are asymptotically controlled by the rainfall statistical properties, given limited and reasonable assumptions concerning the rainfall-runoff process. This result is partial so far: the impact of the rainfall spatial heterogeneity has not been studied for instance. From a practical point of view, it provides a general framework for analysis of the outcomes of previous works based on derived flood frequency approaches and leads to some proposals for the estimation of very large return-period flood quantiles. This paper, focussed on asymptotic distribution properties, does not propose any new approach for the extrapolation of flood frequency distribution to estimate intermediate return period flood quantiles. Nevertheless, the large distance between frequent flood peak values and the asymptotic values as well as the simulations conducted in this paper help quantifying the ill condition of the problem of flood frequency distribution extrapolation: it illustrates how large the range of possibilities for the shapes of flood peak distributions is.

scholarly journals Variation of Runoff and Runoff Components of the Upper Shule River in the Northeastern Qinghai–Tibet Plateau under Climate Change

Water ◽  
2021 ◽  
Vol 13 (23) ◽  
pp. 3357
Author(s):  
Jinkui Wu ◽  
Hongyuan Li ◽  
Jiaxin Zhou ◽  
Shuya Tai ◽  
Xueliang Wang
Keyword(s):  
Climate Change ◽  
Sustainable Use ◽  
Reduction Rate ◽  
Northwest China ◽  
Tibet Plateau ◽  
Glacier Area ◽  
Rainfall Runoff ◽  
Total Runoff ◽  
Increasing Temperature ◽  
The Impact

Quantifying the impact of climate change on hydrologic features is essential for the scientific planning, management and sustainable use of water resources in Northwest China. Based on hydrometeorological data and glacier inventory data, the Spatial Processes in Hydrology (SPHY) model was used to simulate the changes of hydrologic processes in the Upper Shule River (USR) from 1971 to 2020, and variations of runoff and runoff components were quantitatively analyzed using the simulations and observations. The results showed that the glacier area has decreased by 21.8% with a reduction rate of 2.06 km2/a. Significant increasing trends in rainfall runoff, glacier runoff (GR) and baseflow indicate there has been a consistent increase in total runoff due to increasing rainfall and glacier melting. The baseflow has made the largest contribution to total runoff, followed by GR, rainfall runoff and snow runoff, with mean annual contributions of 38%, 28%, 18% and 16%, respectively. The annual contribution of glacier and snow runoff to the total runoff shows a decreasing trend with decreasing glacier area and increasing temperature. Any increase of total runoff in the future will depend on an increase of rainfall, which will exacerbate the impact of drought and flood disasters.

scholarly journals Flood frequency estimation by continuous simulation under climate change (with uncertainty)

2000 ◽  
Vol 4 (3) ◽  
pp. 393-405 ◽  
Author(s):  
D. Cameron ◽  
K. Beven ◽  
P. Naden
Keyword(s):  
Climate Change ◽  
Frequency Estimation ◽  
Flood Frequency ◽  
Change Scenario ◽  
Rainfall Runoff ◽  
Catchment Scale ◽  
Continuous Simulation ◽  
Starting Point ◽  
Rainfall Model ◽  
Impacts Of Climate Change

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

scholarly journals Climate Change Impact on Flood Frequency and Source Area in Northern Iran under CMIP5 Scenarios

Water ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 273 ◽  
Author(s):  
Fatemeh Fadia Maghsood ◽  
Hamidreza Moradi ◽  
Ali Reza Massah Bavani ◽  
Mostafa Panahi ◽  
Ronny Berndtsson ◽  
...  
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Source Area ◽  
Flood Frequency ◽  
Northern Iran ◽  
Rcp Scenarios ◽  
Impact Of Climate Change ◽  
The Impact ◽  
Near Future ◽  
Flood Source

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.

scholarly journals Selection of Bias Correction Methods to Assess the Impact of Climate Change on Flood Frequency Curves

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2266 ◽  
Author(s):  
Enrique Soriano ◽  
Luis Mediero ◽  
Carlos Garijo
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Control Period ◽  
Flood Frequency ◽  
Climate Projections ◽  
The Future ◽  
Flood Quantiles ◽  
The Impact

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.

Risk assessment of post-wildfire hydrological response in semiarid basins: the effects of varying rainfall representations in the KINEROS2/AGWA model

2016 ◽  
Vol 25 (3) ◽  
pp. 268 ◽  
Author(s):  
Gabriel Sidman ◽  
D. Phillip Guertin ◽  
David C. Goodrich ◽  
Carl L. Unkrich ◽  
I. Shea Burns
Keyword(s):  
Risk Assessment ◽  
High Risk ◽  
Peak Flow ◽  
Radar Data ◽  
Burned Area ◽  
Rainfall Runoff ◽  
National Monument ◽  
Bandelier National Monument ◽  
The Impact ◽  
Runoff Events

Representation of precipitation is one of the most difficult aspects of modelling post-fire runoff and erosion and also one of the most sensitive input parameters to rainfall-runoff models. The impact of post-fire convective rainstorms, especially in semiarid watersheds, depends on the overlap between locations of high-intensity rainfall and areas of high-severity burns. One of the most useful applications of models in post-fire situations is risk assessment to quantify peak flow and identify areas at high risk of flooding and erosion. This study used the KINEROS2/AGWA model to compare several spatial and temporal rainfall representations of post-fire rainfall-runoff events to determine the effect of differing representations on modelled peak flow and determine at-risk locations within a watershed. Post-fire rainfall-runoff events at Zion National Park in Utah and Bandelier National Monument in New Mexico were modelled. Representations considered included both uniform and Soil Conservation Service Type II hyetographs, applying rain over the entire watershed and applying rain only on the burned area, and varying rainfall both temporally and spatially according to radar data. Results showed that rainfall representation greatly affected modelled peak flow, but did not significantly alter the model’s predictions for high-risk locations. This has important implications for post-fire assessments before a flood-inducing rainfall event, or for post-storm assessments in areas with low-gauge density or lack of radar data due to mountain beam blockage.

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