2021 ◽  
Author(s):  
Stefan Brönnimann ◽  
Peter Stucki ◽  
Jörg Franke ◽  
Veronika Valler ◽  
Yuri Brugnara ◽  
...  

Abstract. European flood frequency and intensity change on a multidecadal scale. Floods were more frequent in the 19th (Central Europe) and early 20th century (Western Europe) than during the mid-20th century and again more frequent since the 1970s. The causes of this variability are not well understood and the relation to climate change is unclear. Palaeoclimate studies from the northern Alps suggest that past flood-rich periods coincided with cold periods. In contrast, some studies suggest that more floods might occur in a future, warming world. Here we reconcile the apparent contradiction by addressing and quantifying the contribution of atmospheric processes to multidecadal flood variability. For this, we use long series of annual peak streamflow, daily weather data, reanalyses, and reconstructions. We show that both changes in atmospheric circulation and moisture content affected multidecadal changes of annual peak streamflow in Central and Western Europe over the past two centuries. We find that during the 19th and early 20th century, atmospheric circulation changes led to high peak values of moisture flux convergence. The circulation was more conducive to strong and long-lasting precipitation events than in the mid-20th century. These changes are also partly reflected in the seasonal mean circulation and reproduced in atmospheric model simulations, pointing to a possible role of oceanic variability. For the period after 1980, increasing moisture content in a warming atmosphere led to extremely high moisture flux convergence. Thus, the main atmospheric driver of flood variability changed from atmospheric circulation variability to water vapour increase.


Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1042
Author(s):  
Andrey Kalugin

The purpose of the study was to analyze the formation conditions of catastrophic floods in the Iya River basin over the observation period, as well as a long-term forecast of the impacts of future climate change on the characteristics of the high flow in the 21st century. The semi-distributed process-based Ecological Model for Applied Geophysics (ECOMAG) was applied to the Iya River basin. Successful model testing results were obtained for daily discharge, annual peak discharge, and discharges exceeding the critical water level threshold over the multiyear period of 1970–2019. Modeling of the high flow of the Iya River was carried out according to a Kling–Gupta efficiency (KGE) of 0.91, a percent bias (PBIAS) of −1%, and a ratio of the root mean square error to the standard deviation of measured data (RSR) of 0.41. The preflood coefficient of water-saturated soil and the runoff coefficient of flood-forming precipitation in the Iya River basin were calculated in 1980, 1984, 2006, and 2019. Possible changes in the characteristics of high flow over summers in the 21st century were calculated using the atmosphere–ocean general circulation model (AOGCM) and the Hadley Centre Global Environment Model version 2-Earth System (HadGEM2-ES) as the boundary conditions in the runoff generation model. Anomalies in values were estimated for the middle and end of the current century relative to the observed runoff over the period 1990–2019. According to various Representative Concentration Pathways (RCP-scenarios) of the future climate in the Iya River basin, there will be less change in the annual peak discharge or precipitation and more change in the hazardous flow and its duration, exceeding the critical water level threshold, at which residential buildings are flooded.


2019 ◽  
Vol 147 ◽  
Author(s):  
C. W. Tian ◽  
H. Wang ◽  
X. M. Luo

AbstractSeasonal autoregressive-integrated moving average (SARIMA) has been widely used to model and forecast incidence of infectious diseases in time-series analysis. This study aimed to model and forecast monthly cases of hand, foot and mouth disease (HFMD) in China. Monthly incidence HFMD cases in China from May 2008 to August 2018 were analysed with the SARIMA model. A seasonal variation of HFMD incidence was found from May 2008 to August 2018 in China, with a predominant peak from April to July and a trough from January to March. In addition, the annual peak occurred periodically with a large annual peak followed by a relatively small annual peak. A SARIMA model of SARIMA (1, 1, 2) (0, 1, 1)12 was identified, and the mean error rate and determination coefficient were 16.86% and 94.27%, respectively. There was an annual periodicity and seasonal variation of HFMD incidence in China, which could be predicted well by a SARIMA (1, 1, 2) (0, 1, 1)12 model.


Sign in / Sign up

Export Citation Format

Share Document