scholarly journals Impacts of future floods and low flows on the economy in the Meuse basin

Author(s):  
B Sinaba ◽  
R Döring ◽  
M Kufeld ◽  
H Schüttrumpf ◽  
A Bauwens
Keyword(s):  
Author(s):  
Ondrej Ledvinka ◽  
◽  
Pavel Coufal ◽  

The territory of Czechia currently suffers from a long-lasting drought period which has been a subject of many studies, including the hydrological ones. Previous works indicated that the basin of the Morava River, a left-hand tributary of the Danube, is very prone to the occurrence of dry spells. It also applies to the development of various hydrological time series that often show decreases in the amount of available water. The purpose of this contribution is to extend the results of studies performed earlier and, using the most updated daily time series of discharge, to look at the situation of the so-called streamflow drought within the basin. 46 water-gauging stations representing the rivers of diverse catchment size were selected where no or a very weak anthropogenic influences are expected and the stability and sensitivity of profiles allow for the proper measurement of low flows. The selected series had to cover the most current period 1981-2018 but they could be much longer, which was considered beneficial for the next determination of the development direction. Various series of drought indices were derived from the original discharge series. Specifically, 7-, 15- and 30-day low flows together with deficit volumes and their durations were tested for trends using the modifications of the Mann– Kendall test that account for short-term and long-term persistence. In order to better reflect the drivers of streamflow drought, the indices were considered for summer and winter seasons separately as well. The places with the situation critical to the future water resources management were highlighted where substantial changes in river regime occur probably due to climate factors. Finally, the current drought episode that started in 2014 was put into a wider context, making use of the information obtained by the analyses.


2013 ◽  
Author(s):  
J. M. Sheridan ◽  
R.G. Williams and D.D. Bosch
Keyword(s):  

2011 ◽  
Vol 26 (6) ◽  
pp. 568-575 ◽  
Author(s):  
Yusuf Serengil ◽  
Wayne T. Swank ◽  
Mark S. Riedel ◽  
James M. Vose
Keyword(s):  

2021 ◽  
Author(s):  
Diver E. Marín ◽  
Juan F. Salazar ◽  
José A. Posada-Marín

<p>Some of the main problems in hydrological sciences are related to how and why river flows change as a result of environmental change, and what are the corresponding implications for society. This has been described as the Panta Rhei context, which refers to the challenge of understanding and quantifying hydrological dynamics in a changing environment, i.e. under the influence of non-stationary effects. The river flow regime in a basin is the result of a complex aggregation process that has been studied by the scaling theory, which allows river basins to be classified as regulated or unregulated and to identify a critical threshold between these states. Regulation is defined here as the basin’s capacity to either dampen high flows or to enhance low flows. This capacity depends on how basins store and release water through time, which in turn depends on many processes that are highly dynamic and sensitive to environmental change. Here we focus on the Magdalena river basin in northwestern South America, which is the main basin for water and energy security in Colombia, and at the same time, it has been identified as one of the most vulnerable regions to be affected by climate change. Building upon some of our previous studies, here we use data analysis to study the evolution of regulation in the Magdalena basin for 1992-2015 based on the scaling theory for extreme flows. In contrast to most previous studies, here we focus on the scaling properties of events rather than on long term averages. We discuss possible relations between changes in the scaling properties and environmental factors such as climate variability, climate change, and land use/land cover change, as well as the potential implications for water security in the country. Our results show that, during the last few decades, the Magdalena river basin has maintained its capacity to regulate low flows (i.e. amplification) whereas it has been losing its capacity to regulate high flows (i.e. dampening), which could be associated with the occurrence of the extremes phases of  El Niño Southern Oscillation (ENSO) and anthropogenic effects, mainly deforestation. These results provide foundations for using the scaling laws as empirical tools for understanding temporal changes of hydrological regulation and simultaneously generate useful scientific evidence that allows stakeholders to take decisions related to water management in the Magdalena river basin in the context of environmental change.</p>


2016 ◽  
Vol 20 (12) ◽  
pp. 4747-4756 ◽  
Author(s):  
Wenfei Liu ◽  
Xiaohua Wei ◽  
Qiang Li ◽  
Houbao Fan ◽  
Honglang Duan ◽  
...  

Abstract. Understanding hydrological responses to reforestation is an important subject in watershed management, particularly in large forested watersheds ( >  1000 km2). In this study, we selected two large forested watersheds (Pingjiang and Xiangshui) located in the upper reach of the Poyang Lake watershed, southeastern China (with an area of 3261.4 and 1458 km2, respectively), along with long-term data on climate and hydrology (1954–2006) to assess the effects of large-scale reforestation on streamflow. Both watersheds have similar climate and experienced comparable and dramatic forest changes during the past decades, but with different watershed properties (e.g., the topography is much steeper in Xiangshui than in Pingjiang), which provides us with a unique opportunity to compare the differences in hydrological recovery in two contrasted watersheds. Streamflow at different percentiles (e.g., 5, 10, 50 and 95 %) were compared using a combination of statistical analysis with a year-wise method for each watershed. The results showed that forest recovery had no significant effects on median flows (Q50%) in both watersheds. However, reforestation significantly reduced high flows in Pingjiang, but had limited influence in Xiangshui. Similarly, reforestation had significant and positive effects on low flows (Q95%) in Pingjiang, while it did not significantly change low flows in Xiangshui. Thus, hydrological recovery is limited and slower in the steeper Xiangshui watershed, highlighting that watershed properties are also important for determining hydrological responses to reforestation. This finding has important implications for designing reforestation and watershed management strategies in the context of hydrological recovery.


2016 ◽  
Vol 2016 ◽  
pp. 1-28 ◽  
Author(s):  
Charles Onyutha

Five hydrological models were applied based on data from the Blue Nile Basin. Optimal parameters of each model were obtained by automatic calibration. Model performance was tested under both moderate and extreme flow conditions. Extreme events for the model performance evaluation were extracted based on seven criteria. Apart from graphical techniques, there were nine statistical “goodness-of-fit” metrics used to judge the model performance. It was found that whereas the influence of model selection may be minimal in the simulation of normal flow events, it can lead to large under- and/or overestimations of extreme events. Besides, the selection of the best model for extreme events may be influenced by the choice of the statistical “goodness-of-fit” measures as well as the criteria for extraction of high and low flows. It was noted that the use of overall water-balance-based objective function not only is suitable for moderate flow conditions but also influences the models to perform better for high flows than low flows. Thus, the choice of a particular model is recommended to be made on a case by case basis with respect to the objectives of the modeling as well as the results from evaluation of the intermodel differences.


2019 ◽  
Vol 653 ◽  
pp. 1077-1094 ◽  
Author(s):  
Lingtong Gai ◽  
João P. Nunes ◽  
Jantiene E.M. Baartman ◽  
Hongming Zhang ◽  
Fei Wang ◽  
...  

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