The impact of using bias-corrected precipitation in estimating extreme discharge: A study over the Italian Territory

Author(s):  
Matilde García-Valdecasas Ojeda ◽  
Erika Coppola ◽  
Fabio Di Sante ◽  
Francesca Raffaele ◽  
Rita Nogherotto ◽  
...  

<p>A common way to study the impact of climate change on water resources is through hydrological models fed by precipitation from global or regional climate models (GCMs and RCMs, respectively). However, precipitation from climate models is usually affected by systematical biases that may produce inadequate streamflow estimations. For this reason, users find it necessary to apply some bias-corrected technique to reduce errors in precipitation before its use in hydrological simulations. Among the different methods, quantile mapping (QM) is a widely used method as it has shown satisfactory results for historical conditions.</p><p>In recent years, several studies have investigated the QM method, with a focus on mean precipitations. However, it remains quite uncertain how bias-corrected precipitation modifies river discharges, particularly the extreme discharges on a sub-daily timescale. In this framework, this study aims to quantify differences between simulated river discharges using corrected and uncorrected precipitation to feed a hydrological model in the context of flood hazard assessment in Italy.</p><p>To adequately estimate flood events, high spatiotemporal resolution data are required. Therefore, sub-daily precipitation outputs from the ICTP RegCM Regional Climate Model driven by the HadGEM2-ES model at 12 km were contemplated in this study. Precipitation outputs for the period 1976-2100 were bias-corrected concerning the observations from GRIPHO, which is a high-resolution observational product. Then, bias-corrected and uncorrected precipitations were used to feed the CETEMPS Hydrological Model (CHyM) completing thus, a set of hydrological simulations covering the entire Italian Territory, in both present-day and future conditions. Analyses focused on the comparison between simulated and observed discharges for present-day conditions, but also on the comparison between corrected and uncorrected values ​​in the future.</p><p>The results of this study could provide valuable information on whether the use of the QM method is appropriate for studying extreme discharges on a sub-daily scale, an essential issue for assessing the impacts of climate change on extreme hydrological events.</p><p><strong>Keywords</strong>: flood hazard assessment, quantile delta mapping, CHyM model, RegCM model, Italy</p><p><strong>Acknowledgments</strong>: The research reported in this work was supported by OGS and CINECA under HPC-TRES program award number 2020-02.</p>

2013 ◽  
Vol 17 (2) ◽  
pp. 565-578 ◽  
Author(s):  
J. A. Velázquez ◽  
J. Schmid ◽  
S. Ricard ◽  
M. J. Muerth ◽  
B. Gauvin St-Denis ◽  
...  

Abstract. Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 project (Québec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e., lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in Southern Québec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by global climate models over a reference (1971–2000) and a future (2041–2070) period. The results show that, for our hydrological model ensemble, the choice of model strongly affects the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model.


2012 ◽  
Vol 9 (6) ◽  
pp. 7441-7474 ◽  
Author(s):  
J. A. Velázquez ◽  
J. Schmid ◽  
S. Ricard ◽  
M. J. Muerth ◽  
B. Gauvin St-Denis ◽  
...  

Abstract. Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 project (Québec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e. lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in Southern Québec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by a given number of GCMs' members over a reference (1971–2000) and a future (2041–2070) periods. The results show that the choice of the hydrological model does strongly affect the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model. Therefore, the computationally less demanding models (usually simple, lumped and conceptual) give a significant level of trust for high and overall mean flows.


2021 ◽  
Author(s):  
Patrick Nistahl ◽  
Tim Müller ◽  
Gerhard Riedel ◽  
Hannes Müller-Thomy ◽  
Günter Meon

<p>Climate change impact studies performed for Northern Germany indicate a growing demand for water storage capacity to account for flood protection, low flow augmentation, drinking and agricultural water supply. At the same time, larger storage volumes for hydropower plants can be used to cope with the demands of changing energy supply from fossil to renewable energies. To tackle these challenges for the next decades, a novel reservoir system planning instrument is developed, which consists of combined numerical models and evaluation components. It allows to model simultaneously the current interconnected infrastructure of reservoirs as well as additional planning variants (structural and operational) as preparation for climate change. This planning instrument consists of a hydrological model and a detailed reservoir operation model.</p><p>As hydrological model, the conceptual, semi-distributed version of PANTA RHEI is applied.  Bias-corrected regional climate models (based on the RCP 8.5 scenario) are used as meteorological input. The hydrological model is coupled with a detailed reservoir operation model that replicates the complex rules of various interconnected reservoirs based on an hourly time step including pumped storage plants, which may have a subsurface reservoir as a lower basin. Downstream of the reservoirs, the hydrological model is used for routing the reservoir outflows and simulating natural side inflows. In areas of particular interest for flood protection, the hydrological routing is substituted with 2D hydraulic models to calculate the flood risk in terms of expected annual flood damage based on resulting inundation areas.</p><p>For the performance analysis, the simulation runs for all integrated modeling variants are evaluated for a reference period (1971-2000) and for future periods (2041-2070). Performance criteria involve flood protection, drinking water supply, low flow augmentation and energy production. These performance criteria will be used as stake holder information as well as a base for further optimization and ranking of the planning variants.</p><p>The combination of the hydrological model and the reservoir operation model shows a good performance of the existing complex hydraulic infrastructure using observed meteorological forcing as input. The usage of regional climate models as input shows a wide dispersion of several performance criteria, confirming the expected need for an innovative optimization scheme and the communication of the underlying uncertainties.</p>


Author(s):  
Pietro Croce ◽  
Paolo Formichi ◽  
Filippo Landi ◽  
Francesca Marsili

<p>As consequence of global warming extreme weather events might become more frequent and severe across the globe. The evaluation of the impact of climate change on extremes is then a crucial issue for the resilience of infrastructures and buildings and is a key challenge for adaptation planning. In this paper, a suitable procedure for the estimation of future trends of climatic actions is presented starting from the output of regional climate models and taking into account the uncertainty in the model itself. In particular, the influence of climate change on ground snow loads is discussed in detail and the typical uncertainty range is determined applying an innovative algorithm for weather generation. Considering different greenhouse gasses emission scenarios, some results are presented for the Italian Mediterranean region proving the ability of the method to define factors of change for climate extremes also allowing a sound estimate of the uncertainty range associated with different models.</p>


2021 ◽  
Author(s):  
Blanka Bartok

&lt;p&gt;As solar energy share is showing a significant growth in the European electricity generation system, assessments regarding long-term variation of this variable related to climate change are becoming more and more relevant for this sector. Several studies analysed the impact of climate change on the solar energy sector in Europe (Jerez et al, 2015) finding light impact (-14%; +2%) in terms of mean surface solar radiation. The present study focuses on extreme values, namely on the distribution of low surface solar radiation (overcast situation) and high surface solar radiation (clear sky situation), since the frequencies of these situations have high impact on electricity generation.&lt;/p&gt;&lt;p&gt;The study considers 11 high-resolution (0.11 deg) bias-corrected climate projections from the EURO-CORDEX ensemble with 5 Global Climate Models (GCMs) downscaled by 6 Regional Climate Models (RCMs).&lt;/p&gt;&lt;p&gt;Changes in extreme surface solar radiation frequencies show different regional patterns over Europe.&lt;/p&gt;&lt;p&gt;The study also includes a case study determining the changes in solar power generation induced by the extreme situations.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Jerez et al (2015): The impact of climate change on photovoltaic power generation in Europe, Nature Communications 6(1):10014, 10.1038/ncomms10014&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;


2020 ◽  
Vol 172 ◽  
pp. 02006
Author(s):  
Hamed Hedayatnia ◽  
Marijke Steeman ◽  
Nathan Van Den Bossche

Understanding how climate change accelerates or slows down the process of material deterioration is the first step towards assessing adaptive approaches for the preservation of historical heritage. Analysis of the climate change effects on the degradation risk assessment parameters like salt crystallization cycles is of crucial importance when considering mitigating actions. Due to the vulnerability of cultural heritage in Iran to climate change, the impact of this phenomenon on basic parameters plus variables more critical to building damage like salt crystallization index needs to be analyzed. Regional climate modelling projections can be used to asses the impact of climate change effects on heritage. The output of two different regional climate models, the ALARO-0 model (Ghent University-RMI, Belgium) and the REMO model (HZG-GERICS, Germany), is analyzed to find out which model is more adapted to the region. So the focus of this research is mainly on the evaluation to determine the reliability of both models over the region. For model validation, a comparison between model data and observations was performed in 4 different climate zones for 30 years to find out how reliable these models are in the field of building pathology.


2019 ◽  
Vol 19 (5) ◽  
pp. 1087-1103 ◽  
Author(s):  
Alfredo Rodríguez ◽  
David Pérez-López ◽  
Enrique Sánchez ◽  
Ana Centeno ◽  
Iñigo Gómara ◽  
...  

Abstract. Growing trees are quite vulnerable to cold temperatures. To minimise the effect of these cold temperatures, they stop their growth over the coldest months of the year, a state called dormancy. In particular, endodormancy requires accumulating chilling temperatures to finish this sort of dormancy. The accumulation of cool temperatures according to specific rules is called chilling accumulation, and each tree species and variety has specific chilling requirements for correct plant development. Under global warming, it is expected that the fulfilment of the chilling requirements to break dormancy in fruit trees could be compromised. In this study, the impact of climate change on the chilling accumulation over peninsular Spain and the Balearic Islands was assessed. For this purpose, bias-adjusted results of 10 regional climate models (RCMs) under Representative Concentration Pathways (RCPs) 4.5 and 8.5 were used as inputs of four different models for calculating chilling accumulation, and the results for each model were individually compared for the 2021–2050 and 2071–2100 future periods under both RCPs. These results project a generalised reduction in chilling accumulation regardless of the RCP, future period or chilling calculation model used, with higher reductions for the 2071–2100 period and the RCP8.5 scenario. The projected winter chill decrease may threaten the viability of some tree crops and varieties in some areas where the crop is currently grown, but also shows scope for varieties with lower chilling requirements. The results are relevant for planning future tree plantations under climate change, supporting adaptation of spatial distribution of tree crops and varieties in Spain.


2020 ◽  
Vol 147 ◽  
pp. 105765 ◽  
Author(s):  
Amirhossein Shadmehri Toosi ◽  
Shahab Doulabian ◽  
Erfan Ghasemi Tousi ◽  
Giancarlo Humberto Calbimonte ◽  
Sina Alaghmand

2016 ◽  
Vol 8 (1) ◽  
pp. 142-164 ◽  
Author(s):  
Philbert Luhunga ◽  
Ladslaus Chang'a ◽  
George Djolov

The IPCC (Intergovernmental Panel on Climate Change) assessment reports confirm that climate change will hit developing countries the hardest. Adaption is on the agenda of many countries around the world. However, before devising adaption strategies, it is crucial to assess and understand the impacts of climate change at regional and local scales. In this study, the impact of climate change on rain-fed maize (Zea mays) production in the Wami-Ruvu basin of Tanzania was evaluated using the Decision Support System for Agro-technological Transfer. The model was fed with daily minimum and maximum temperatures, rainfall and solar radiation for current climate conditions (1971–2000) as well as future climate projections (2010–2099) for two Representative Concentration Pathways: RCP 4.5 and RCP 8.5. These data were derived from three high-resolution regional climate models, used in the Coordinated Regional Climate Downscaling Experiment program. Results showed that due to climate change future maize yields over the Wami-Ruvu basin will slightly increase relative to the baseline during the current century under RCP 4.5 and RCP 8.5. However, maize yields will decline in the mid and end centuries. The spatial distribution showed that high decline in maize yields are projected over lower altitude regions due to projected increase in temperatures in those areas.


Sign in / Sign up

Export Citation Format

Share Document