APPLICATION OF RAINFALL-RUNOFF MODEL: CLIMATE CHANGE IMPACTS ON RESERVOIR INFLOW

2020 ◽  
Author(s):  
Kateřina Knoppová ◽  
◽  
Daniel Marton ◽  
Petr Štěpánek ◽  
◽  
...  
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Drinking Water ◽  
Czech Republic ◽  
River Flow ◽  
Hydrological Modelling ◽  
Rainfall Runoff ◽  
The Czech Republic ◽  
Hydrological Conditions ◽  
Reservoir Inflow

The impacts of climate change are beginning to be felt in the Czech Republic. In recent years, we were challenging a dry period, which threatens to continue affecting Czech economy, agriculture and personal comfort of local people. The need to adapt to climate change is obvious. The groundwater resources are in continuous decline, consequently, the surface water supplies are increasing in importance. How would the quantity of available water change in the future? How much water would we be able to store within the year to manage it during the dry seasons? Rainfall-runoff models enable us to simulate future changes in hydrological conditions based on climate projections. One of such tools is Runoff Prophet, the conceptual lumped model being developed at the Institute of Landscape Water Management at Brno University of Technology. It is used to simulate time series of monthly river flow in a catchment outlet without the need to describe the morphological characteristics of the catchment. Runoff Prophet produced good results of calibration and proved its suitability for conceptual hydrological modelling in variable hydrological conditions of the Czech Republic. The aim of the paper was to assess the possible impact of climate change on future inflow into Vír I. Reservoir, one of the drinking water resources for Brno, a city of 380 000 inhabitants. The recently developed software Runoff Prophet was used to simulate future river flow time series. The model was calibrated on the catchment of gauging station Dalečín on Svratka River as the reservoir inflow. Prognoses of future river flow were performed using climate scenarios prepared by Global Change Research Institute of Czech Academy of Sciences. These scenarios (RCP types) are based on the outcomes from different regional climate models of Euro-CORDEX initiative. Characteristics of possible future air temperature and precipitation in the basin were evaluated in terms of its impact on reservoir management. The results of hydrological modelling gave the perspective of expected changes in Vír I. inflow yield. The options of using Vír I. Reservoir as a drinking water supply for Brno in coming decades were assessed.

Monitoring of pesticides in drinking water: finding the right balance between under- and over-monitoring – experience from the Czech Republic

2021 ◽  
Author(s):  
Filip Kotal ◽  
František Kožíšek ◽  
Hana Jeligová ◽  
Adam Vavrouš ◽  
Daniel Gari Wayessa ◽  
...  
Keyword(s):  
Drinking Water ◽  
Czech Republic ◽  
Water Supply ◽  
The Czech Republic ◽  
The Right

The modern, risk-based approach requires that only those pollutants which are likely to be present in a given water supply should be monitored in drinking water. From this perspective, defining...

scholarly journals The Impact of Climate Change on the Sugar Content of Grapes and the Sustainability of their Production in the Czech Republic

2020 ◽  
Vol 13 (1) ◽  
pp. 222
Author(s):  
Miroslava Navrátilová ◽  
Markéta Beranová ◽  
Lucie Severová ◽  
Karel Šrédl ◽  
Roman Svoboda ◽  
...  
Keyword(s):  
Climate Change ◽  
Czech Republic ◽  
Sugar Content ◽  
Growing Season ◽  
Vegetation Period ◽  
The Czech Republic ◽  
Impact Of Climate Change ◽  
Secondary Sources ◽  
The Impact ◽  
Growing Region

The aim of the presented article is to evaluate the impact of climate change on the sugar content of grapes in the Czech Republic during the period 2000–2019 through selected indicators on the basis of available secondary sources. Attention is focused on the developments in both the main wine-growing regions of Moravia and Bohemia. In the field of viticulture and wine-growing, the sugar content of grapes, as a basic parameter for the classification of wines, plays an important role. In the Czech Republic, the average sugar content of grapes has had a constantly growing trend. This trend is evident both in the wine-growing region of Bohemia and in the wine-growing region of Moravia. The impact of climate change, especially the gradual increase of average temperatures in the growing season, cannot be overlooked. It greatly affects, among other things, the sugar content of grapes. Calculations according to the Huglin Index and the Winkler Index were used to determine the relationship between climate and sugar content. These indexes summarize the course of temperatures during the entire vegetation period into a single numerical value. The results show that both indexes describe the effect of air temperature on sugar content in both wine regions of the Czech Republic in a statistically significant way. The Huglin Index shows a higher correlation rate. The Winkler Index proved to be less suitable for both areas. Alternatively, the Winkler Index calculated for a shorter growing season was tested, which showed a higher degree of correlation with sugar content, approaching the significance of the Huglin Index.

scholarly journals SHETRAN and HEC HMS Model Evaluation for Runoff and Soil Moisture Simulation in the Jičinka River Catchment (Czech Republic)

Water ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 872
Author(s):  
Vesna Đukić ◽  
Ranka Erić
Keyword(s):  
Soil Moisture ◽  
Czech Republic ◽  
Hydrological Model ◽  
Flash Flood ◽  
Model Performance ◽  
Rainfall Runoff ◽  
The Czech Republic ◽  
River Catchment ◽  
Hydrological Variable ◽  
Model Structures

Due to the improvement of computation power, in recent decades considerable progress has been made in the development of complex hydrological models. On the other hand, simple conceptual models have also been advanced. Previous studies on rainfall–runoff models have shown that model performance depends very much on the model structure. The purpose of this study is to determine whether the use of a complex hydrological model leads to more accurate results or not and to analyze whether some model structures are more efficient than others. Different configurations of the two models of different complexity, the Système Hydrologique Européen TRANsport (SHETRAN) and Hydrologic Modeling System (HEC-HMS), were compared and evaluated in simulating flash flood runoff for the small (75.9 km2) Jičinka River catchment in the Czech Republic. The two models were compared with respect to runoff simulations at the catchment outlet and soil moisture simulations within the catchment. The results indicate that the more complex SHETRAN model outperforms the simpler HEC HMS model in case of runoff, but not for soil moisture. It can be concluded that the models with higher complexity do not necessarily provide better model performance, and that the reliability of hydrological model simulations can vary depending on the hydrological variable under consideration.

scholarly journals Change in dissolved oxygen concentrations during aeration and mixing using a combined system

2021 ◽  
Vol 900 (1) ◽  
pp. 012039
Author(s):  
V Singrova ◽  
P Hlustik
Keyword(s):  
Drinking Water ◽  
Czech Republic ◽  
Dissolved Oxygen ◽  
Not Given ◽  
Combined System ◽  
The Czech Republic ◽  
Oxygen Concentrations

Abstract Combined mixing and aeration systems are not given priority in the Czech Republic. Still, they are installed at several WWTPs. Their advantage is mixing and aerating at the same time. This article provides data from actual measurements where a combined system was used for drinking water including necessary chemicals. The text below evaluates the course of changes in the concentration of dissolved oxygen in different points in the reactor depending on time.

scholarly journals Predicted climate change will increase the truffle cultivation potential in central Europe

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Tomáš Čejka ◽  
Miroslav Trnka ◽  
Paul J. Krusic ◽  
Ulrich Stobbe ◽  
Daniel Oliach ◽  
...  
Keyword(s):  
Climate Change ◽  
Czech Republic ◽  
Central Europe ◽  
Agricultural Land ◽  
Economic Benefits ◽  
The Czech Republic ◽  
Truffle Cultivation ◽  
Ecological Requirements ◽  
Wide Range ◽  
Future Warming

AbstractClimate change affects the distribution of many species, including Burgundy and Périgord truffles in central and southern Europe, respectively. The cultivation potential of these high-prized cash crops under future warming, however, remains highly uncertain. Here we perform a literature review to define the ecological requirements for the growth of both truffle species. This information is used to develop niche models, and to estimate their cultivation potential in the Czech Republic under current (2020) and future (2050) climate conditions. The Burgundy truffle is already highly suitable for cultivation on ~ 14% of agricultural land in the Czech Republic (8486 km2), whereas only ~ 8% of the warmest part of southern Moravia are currently characterised by a low suitability for Périgord truffles (6418 km2). Though rising temperatures under RCP8.5 will reduce the highly suitable cultivation areas by 7%, the 250 km2 (3%) expansion under low-emission scenarios will stimulate Burgundy truffles to benefit from future warming. Doubling the moderate and expanding the highly suitable land by 352 km2 in 2050, the overall cultivation potential for Périgord truffles will rise substantially. Our findings suggest that Burgundy and Périgord truffles could become important high-value crops for many regions in central Europe with alkaline soils. Although associated with uncertainty, long-term investments in truffle cultivation could generate a wide range of ecological and economic benefits.

scholarly journals Evaluation of the SWAT model as an integrated management tool in the Švihov drinking water supply catchment

2019 ◽  
Vol 14 (No. 2) ◽  
pp. 76-83
Author(s):  
Jan Gregar ◽  
Jan Petrů ◽  
Jana Novotná
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Czech Republic ◽  
Water Supply ◽  
Integrated Management ◽  
Swat Model ◽  
Point Sources ◽  
Drinking Water Supply ◽  
Management Tool ◽  
The Czech Republic

Švihov dam, the largest drinking water source in the Czech Republic and Central Europe, has problems with eutrophication. The Švihov dam catchment spreads over 1200 km<sup>2</sup> and supplies over 1.5 million people in the capital of Prague and the Central Bohemian region with drinking water. Due to intensive agricultural activities and a lack of wastewater treatment plants in small settlements, the water quality is deteriorating. As a result, corrective measures need to be taken. Technological Agency of the Czech Republic supported this research which proposes different scenarios for a reduction of water quality degradation in the dam. The Trnávka dam watershed was chosen for study purposes as it occupies one quarter of the Švihov dam watershed. Hydrological balance was established using measured data. Point and non-point sources of nutrients were determined by field research and included in a Soil and Water Assessment Tool (SWAT) model. This study aims to propose complex watershed management to improve the state of the environment in the entire area and to reduce eutrophication. Different management practices would reduce nutrient loads of streams and increase water quality which is the critical factor in dam eutrophication. This research brings methodology and systematic approach to integrated management, and can be applied not only for the Švihov dam, but also for other watersheds, including those which function as drinking water supply.

scholarly journals Future Runoff Analysis in the Mekong River Basin under a Climate Change Scenario Using Deep Learning

Water ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 1556 ◽  
Author(s):  
Daeeop Lee ◽  
Giha Lee ◽  
Seongwon Kim ◽  
Sungho Jung
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Change Scenario ◽  
Swat Model ◽  
Mekong River ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Rainfall Runoff ◽  
Runoff Prediction ◽  
Runoff Analysis

In establishing adequate climate change policies regarding water resource development and management, the most essential step is performing a rainfall-runoff analysis. To this end, although several physical models have been developed and tested in many studies, they require a complex grid-based parameterization that uses climate, topography, land-use, and geology data to simulate spatiotemporal runoff. Furthermore, physical rainfall-runoff models also suffer from uncertainty originating from insufficient data quality and quantity, unreliable parameters, and imperfect model structures. As an alternative, this study proposes a rainfall-runoff analysis system for the Kratie station on the Mekong River mainstream using the long short-term memory (LSTM) model, a data-based black-box method. Future runoff variations were simulated by applying a climate change scenario. To assess the applicability of the LSTM model, its result was compared with a runoff analysis using the Soil and Water Assessment Tool (SWAT) model. The following steps (dataset periods in parentheses) were carried out within the SWAT approach: parameter correction (2000–2005), verification (2006–2007), and prediction (2008–2100), while the LSTM model went through the process of training (1980–2005), verification (2006–2007), and prediction (2008–2100). Globally available data were fed into the algorithms, with the exception of the observed discharge and temperature data, which could not be acquired. The bias-corrected Representative Concentration Pathways (RCPs) 4.5 and 8.5 climate change scenarios were used to predict future runoff. When the reproducibility at the Kratie station for the verification period of the two models (2006–2007) was evaluated, the SWAT model showed a Nash–Sutcliffe efficiency (NSE) value of 0.84, while the LSTM model showed a higher accuracy, NSE = 0.99. The trend analysis result of the runoff prediction for the Kratie station over the 2008–2100 period did not show a statistically significant trend for neither scenario nor model. However, both models found that the annual mean flow rate in the RCP 8.5 scenario showed greater variability than in the RCP 4.5 scenario. These findings confirm that the LSTM runoff prediction presents a higher reproducibility than that of the SWAT model in simulating runoff variation according to time-series changes. Therefore, the LSTM model, which derives relatively accurate results with a small amount of data, is an effective approach to large-scale hydrologic modeling when only runoff time-series are available.

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