scholarly journals Simulation and analysis of the impact of projected climate change on the spatially distributed waterbalance in Thuringia, Germany

2009 ◽  
Vol 21 ◽  
pp. 33-48 ◽  
Author(s):  
P. Krause ◽  
S. Hanisch
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Hydrological Model ◽  
Actual Evapotranspiration ◽  
Climate Data ◽  
Runoff Generation ◽  
Entire Area ◽  
Spatially Distributed ◽  
The Impact ◽  
Conceptual Hydrological Model

Abstract. The impact of projected climate change on the long-term hydrological balance and seasonal variability in the federal German state of Thuringia was assessed and analysed. For this study projected climate data for the scenarios A2 and B1 were used in conjunction with a conceptual hydrological model. The downscaled climate data are based on outputs of the general circulation model ECHAM5 and provide synthetic climate time series for a large number of precipitation and climate stations in Germany for the time period of 1971 to 2100. These data were used to compute the spatially distributed hydrological quantities, i.e. precipitation, actual evapotranspiration and runoff generation with a conceptual hydrological model. This paper discusses briefly the statistical downscaling method and its validation in Thuringia and includes an overview of the hydrological model. The achieved results show that the projected climate conditions in Thuringia follow the general European climate trends – increased temperature, wetter winters, drier summers. But, in terms of the spatial distribution and interannual variability regional differences occur. The analysis showed that the general increase of the winter precipitation is more distinct in the mid-mountain region and less pronounced in the lowland whereas the decrease of summer precipitation is higher in the lowland and less distinct in the mid-mountains. The actual evapotranspiration showed a statewide increase due to higher temperatures which is largest in the summer period. The resulting runoff generation in winter was found to increase in the mid-mountains and to slightly decrease in the lowland region. In summer and fall a decrease in runoff generation was estimated for the entire area due to lower precipitation and higher evapotranspiration rates. These spatially differentiated results emphasize the need of high resolution climate input data and distributed modelling for regional impact analyses.

scholarly journals Prognostic simulation and analysis of the impact of climate change on the hydrological dynamics in Thuringia, Germany

2007 ◽  
Vol 4 (6) ◽  
pp. 4037-4067
Author(s):  
P. Krause ◽  
S. Hanisch
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Climate Model ◽  
Actual Evapotranspiration ◽  
Series Data ◽  
Runoff Generation ◽  
Entire Area ◽  
German State ◽  
The Mean ◽  
The Impact

Abstract. The impact of predicted climate change on the hydrological dynamics and long term hydrological balance in the federal German state Thuringia was investigated and analysed. For this study the prognostic climate data, provided by the statistical regionalisation approach WETTREG, which is based on results of the global climate model ECHAM5/MPI-OM, was used. This regional climate model provides synthetic climate time series for the existent precipitation and climate station in Germany from 2000 to 2100. This data was processed with the hydrological model J2000g which we used for the regionalisation of the climatological time series data and for the computation of potential and actual evapotranspiration, runoff generation and groundwater recharge. In this study we analysed the two emission scenarios A2 and B1, defined by the Intergovernmental Panel on Climate Change (IPCC) and their impact on the temporal and spatial distribution of temperature, precipitation, evapotranspiration and runoff generation for the time frame 2071–2100 for the entire area of the German state of Thuringia. For this purpose we compared simulation with the scenario data with simulation results based on reference data from 1971–2000. The comparison showed an increase of the mean annual temperature of 1.8 (B1) to 2.2 (A2) °C which is much more distinct during winter. The mean annual precipitation is decreasing only slightly but, the seasonal spatio-temporal rainfall distribution which has major impact on the hydrological water balance is changing significantly. This pattern change results in more precipitation during winter and less in summer. Actual evapotranspiration was computed higher for both scenarios compared to the evapotranspiration of the reference period 1971–2000. As a follow up a decrease in the runoff generation was simulated which was again very variable in space and time. The overall trends worked out in this study showed that it is likely that the extremes of flooding in winter and dry spells in summer might occur more often in Thuringia because of the changing weather conditions due to climate change.

scholarly journals The impact of the climate change on discharge of Suir River Catchment (Ireland) under different climate scenarios

2006 ◽  
Vol 6 (3) ◽  
pp. 387-395 ◽  
Author(s):  
S. Wang ◽  
R. McGrath ◽  
T. Semmler ◽  
C. Sweeney ◽  
P. Nolan
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Hydrological Model ◽  
Climate Model ◽  
Global Climate ◽  
Regional Climate ◽  
General Circulation Models ◽  
Climate Data ◽  
River Catchment ◽  
The Impact

Abstract. The impact of climate change on local discharge variability is investigated in the Suir River Catchment which is located in the south-east of Ireland. In this paper, the Rossby Centre Regional Atmospheric Model (RCA) is driven by different global climate data sets. For the past climate (1961–2000), the model is driven by ECMWF reanalysis (ERA-40) data as well as by the output of the general circulation models (GCM's) ECHAM4 and ECHAM5. For the future simulation (2021–2060), the model is driven by two GCM scenarios: ECHAM4_B2 and ECHAM5_A2. To investigate the influence of changed future climate on local discharge, the precipitation of the model output is used as input for the HBV hydrological model. The calibration and validation results of our ERA-40 driven present day simulation shows that the HBV model can reproduce the discharge fairly well, except the extreme discharge is systematically underestimated by about 15–20%. Altogether the application of a high resolution regional climate model in connection with a conceptual hydrological model is capable of capturing the local variability of river discharge for present-day climate using boundary values assimilated with observations such as ERA-40 data. However, using GCM data to drive RCA and HBV suggests, that there is still large uncertainty connected with the GCM formulation: For present day climate the validation of the ECHAM4 and ECHAM5 driven simulations indicates stronger discharge compared to the observations due to overprediction of precipitation, especially for the ECHAM5 driven simulation in the summer season. Whereas according to the ECHAM4_B2 scenario the discharge generally increases – most pronounced in the wet winter time, there are only slight increases in winter and considerable decreases in summer according to the ECHAM5_A2 scenario. This also leads to a different behaviour in the evolution of return levels of extreme discharge events: Strong increases according to the ECHAM4_B2 scenario and slight decreases according to the ECHAM5_A2 scenario.

Simulated impact of climate change on hydrology of multiple watersheds using traditional and recommended snowmelt runoff model methodology

2016 ◽  
Vol 7 (4) ◽  
pp. 665-682 ◽  
Author(s):  
Emile Elias ◽  
Albert Rango ◽  
Caitriana M. Steele ◽  
John F. Mejia ◽  
Ruben Baca ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
General Circulation Models ◽  
Future Application ◽  
Climate Data ◽  
Snowmelt Runoff ◽  
Change Analysis ◽  
The Impact ◽  
Runoff Model ◽  
Impacts Of Climate Change

For more than two decades researchers have utilized the snowmelt runoff model (SRM) to test the impacts of climate change on streamflow of snow-fed systems. SRM developers recommend a parameter shift during simulations of future climate, but this is often omitted. Here we show the impact of this omission on model results. In this study, the hydrological effects of climate change are modeled over three sequential years with typical and recommended SRM methodology. We predict the impacts of climate change on water resources of five subbasins of an arid region. Climate data are downscaled to weather stations. Period change analysis gives temperature and precipitation changes for 55 general circulation models which are then subsampled to produce four future states per basin. Results indicate an increase in temperature between 3.0 and 6.2 °C and an 18% decrease to 26% increase in precipitation. Without modifications to the snow runoff coefficient (cS), mean results across all basins range from a reduction in total volume of 21% to an increase of 4%. Modifications to cS resulted in a 0–10% difference in simulated annual volume. Future application of SRM should include a parameter shift representing the changed climate.

The impacts of climate change on a Norwegian high-head hydropower system

2013 ◽  
Vol 4 (1) ◽  
pp. 17-37 ◽  
Author(s):  
Haregewoin Haile Chernet ◽  
Knut Alfredsen ◽  
Ånund Killingtveit
Keyword(s):  
Climate Change ◽  
Simulation Model ◽  
General Circulation ◽  
Large Scale ◽  
Hydrological Model ◽  
Circulation Model ◽  
Climate Change Impacts ◽  
Ocean General Circulation Model ◽  
Hydropower System ◽  
The Impact

Hydropower is the most important renewable energy source for electricity in Norway. However, it is the most vulnerable resource to climate change. Despite the importance of hydropower and its vulnerability to climate change, many studies have been mostly concerned with large-scale resources assessment. This study aims to address the climate change impacts on the scale of a single hydropower system in Norway. The impact studies are based on a combination of hydrological model and a hydropower simulation model driven by scenarios from the Atmospheric-Ocean General Circulation Model (AOGCM). These climate scenarios were used for driving the HBV (Hydrologiska Byråns Vattenbalansavdelning) hydrological model to provide inflow scenarios for the hydropower study. The nMAG hydropower simulation model was used to simulate the hydropower system for the control and scenario period and to investigate future changes in power production. In general, the projections indicate an average increase of 11–17% in annual inflow to the system, earlier peaks and a larger increase in spring. The hydropower simulation results show an increase in energy generation of 9–20% under the current reservoir operation strategies.

scholarly journals Effect of Climate Change on the Rainfall Trends: A case study of Pune, India

2021 ◽  
Author(s):  
Shalaka Shah ◽  
Shreenivas Londhe
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
General Circulation Models ◽  
Climate Data ◽  
Maximum Rainfall ◽  
Accurate Model ◽  
Impact Of Climate Change ◽  
The Future ◽  
Grid Points ◽  
The Impact

Abstract It is the need of the hour to predict the impact of climate change, especially rainfall on the future environmental conditions on local as well as global scales. The present work aims at studying the impact of climate change on the rainfall occurring over Pune, the eighth largest city in India. The General Circulation Models (GCMs) are predominantly used to obtain the climate data all over the globe, at various grid points, for past and future years. Rainfall values obtained from these grid points need to be downscaled to make them location specific. This study proposes a soft computing tool, Artificial Neural Network (ANN) for the purpose of downscaling. The rainfall data at 4 grid points surrounding Pune, was extracted from 5 different GCMs and given as input to ANN with observed rainfall as output, thus forming 5 models. For comparison, a pre-existing downscaling technique, Distribution based scaling (DBS) was used. The coefficient of correlation (r) showed that ANN was working better than DBS. The value of r for ANN was 0.73 for its least accurate model whereas DBS managed to reach 0.73 for its most accurate model. The future rainfall estimated with the help of the trained ANN models show an increase in mean rainfall over the Pune region by ∼2 – 15% and decrease in maximum rainfall by ∼40 – 65%. Peak prediction of rainfall simulated by ANN was not very accurate and hence there is still an opportunity for improvement which is the future scope of this study.

scholarly journals Assessing Annual Actual Evapotranspiration Based on Climate, Topography and Soil in Natural and Agricultural Ecosystems

Climate ◽  
2021 ◽  
Vol 9 (2) ◽  
pp. 20
Author(s):  
Kleoniki Demertzi ◽  
Vassilios Pisinaras ◽  
Emanuel Lekakis ◽  
Evangelos Tziritis ◽  
Konstantinos Babakos ◽  
...  
Keyword(s):  
Water Balance ◽  
Large Scale ◽  
Hydrological Model ◽  
Actual Evapotranspiration ◽  
Irrigated Agriculture ◽  
Climate Data ◽  
Natural Ecosystems ◽  
Loading Effects ◽  
Very High ◽  
Of Greece

Simple formulas for estimating annual actual evapotranspiration (AET) based on annual climate data are widely used in large scale applications. Such formulas do not have distinct compartments related to topography, soil and irrigation, and for this reason may be limited in basins with high slopes, where runoff is the dominant water balance component, and in basins where irrigated agriculture is dominant. Thus, a simplistic method for assessing AET in both natural ecosystems and agricultural systems considering the aforementioned elements is proposed in this study. The method solves AET through water balance based on a set of formulas that estimate runoff and percolation. These formulas are calibrated by the results of the deterministic hydrological model GLEAMS (Groundwater Loading Effects of Agricultural Management Systems) for a reference surface. The proposed methodology is applied to the country of Greece and compared with the widely used climate-based methods of Oldekop, Coutagne and Turk. The results show that the proposed methodology agrees very well with the method of Turk for the lowland regions but presents significant differences in places where runoff is expected to be very high (sloppy areas and areas of high rainfall, especially during December–February), suggesting that the proposed method performs better due to its runoff compartment. The method can also be applied in a single application considering irrigation only for the irrigated lands to more accurately estimate AET in basins with a high percentage of irrigated agriculture.

scholarly journals Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Models ◽  
Assessment Tool ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Data ◽  
The Future ◽  
The Impact ◽  
Mountainous River

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.

scholarly journals Impact of climate change on sediment yield in the Mekong River basin: a case study of the Nam Ou basin, Lao PDR

2013 ◽  
Vol 17 (1) ◽  
pp. 1-20 ◽  
Author(s):  
B. Shrestha ◽  
M. S. Babel ◽  
S. Maskey ◽  
A. van Griensven ◽  
S. Uhlenbrook ◽  
...  
Keyword(s):  
Climate Change ◽  
Sediment Yield ◽  
General Circulation ◽  
Climate Models ◽  
Greenhouse Gas Emission ◽  
Circulation Model ◽  
Sediment Flux ◽  
Seasonal Temperature ◽  
Impact Of Climate Change ◽  
The Impact

Abstract. This paper evaluates the impact of climate change on sediment yield in the Nam Ou basin located in northern Laos. Future climate (temperature and precipitation) from four general circulation models (GCMs) that are found to perform well in the Mekong region and a regional circulation model (PRECIS) are downscaled using a delta change approach. The Soil and Water Assessment Tool (SWAT) is used to assess future changes in sediment flux attributable to climate change. Results indicate up to 3.0 °C shift in seasonal temperature and 27% (decrease) to 41% (increase) in seasonal precipitation. The largest increase in temperature is observed in the dry season while the largest change in precipitation is observed in the wet season. In general, temperature shows increasing trends but changes in precipitation are not unidirectional and vary depending on the greenhouse gas emission scenarios (GHGES), climate models, prediction period and season. The simulation results show that the changes in annual stream discharges are likely to range from a 17% decrease to 66% increase in the future, which will lead to predicted changes in annual sediment yield ranging from a 27% decrease to about 160% increase. Changes in intra-annual (monthly) discharge as well as sediment yield are even greater (−62 to 105% in discharge and −88 to 243% in sediment yield). A higher discharge and sediment flux are expected during the wet seasons, although the highest relative changes are observed during the dry months. The results indicate high uncertainties in the direction and magnitude of changes of discharge as well as sediment yields due to climate change. As the projected climate change impact on sediment varies remarkably between the different climate models, the uncertainty should be taken into account in both sediment management and climate change adaptation.

scholarly journals Simulation of future climate scenarios and the impact on the water availability in southern Brazil

2021 ◽  
Vol 43 ◽  
pp. e56026
Author(s):  
Gabriela Leite Neves ◽  
Jorim Sousa das Virgens Filho ◽  
Maysa de Lima Leite ◽  
Frederico Fabio Mauad
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
Water Availability ◽  
Meteorological Data ◽  
Future Climate ◽  
Climate Scenarios ◽  
Southern Brazil ◽  
Climate Data ◽  
Intergovernmental Panel ◽  
The Impact

Water is an essential natural resource that is being impacted by climate change. Thus, knowledge of future water availability conditions around the globe becomes necessary. Based on that, this study aimed to simulate future climate scenarios and evaluate the impact on water balance in southern Brazil. Daily data of rainfall and air temperature (maximum and minimum) were used. The meteorological data were collected in 28 locations over 30 years (1980-2009). For the data simulation, we used the climate data stochastic generator PGECLIMA_R. It was considered two scenarios of the fifth report of the Intergovernmental Panel on Climate Change (IPCC) and a scenario with the historical data trend. The water balance estimates were performed for the current data and the simulated data, through the methodology of Thornthwaite and Mather (1955). The moisture indexes were spatialized by the kriging method. These indexes were chosen as the parameters to represent the water conditions in different situations. The region assessed presented a high variability in water availability among locations; however, it did not present high water deficiency values, even with climate change. Overall, it was observed a reduction of moisture index in most sites and in all scenarios assessed, especially in the northern region when compared to the other regions. The second scenario of the IPCC (the worst situation) promoting higher reductions and dry conditions for the 2099 year. The impacts of climate change on water availability, identified in this study, can affect the general society, therefore, they must be considered in the planning and management of water resources, especially in the regional context

scholarly journals Climate-dependent propagation of precipitation uncertainty into the water cycle

2020 ◽  
Author(s):  
Ali Fallah ◽  
Sungmin O ◽  
Rene Orth
Keyword(s):  
Hydrological Model ◽  
Water Cycle ◽  
State Of The Art ◽  
Rain Gauge ◽  
Multiple Sources ◽  
Current State ◽  
Wide Range ◽  
The Impact ◽  
Conceptual Hydrological Model

Abstract. Precipitation is a crucial variable for hydro-meteorological applications. Unfortunately, rain gauge measurements are sparse and unevenly distributed, which substantially hampers the use of in-situ precipitation data in many regions of the world. The increasing availability of high-resolution gridded precipitation products presents a valuable alternative, especially over gauge-sparse regions. Nevertheless, uncertainties and corresponding differences across products can limit the applicability of these data. This study examines the usefulness of current state-of-the-art precipitation datasets in hydrological modelling. For this purpose, we force a conceptual hydrological model with multiple precipitation datasets in > 200 European catchments. We consider a wide range of precipitation products, which are generated via (1) interpolation of gauge measurements (E-OBS and GPCC V.2018), (2) combination of multiple sources (MSWEP V2) and (3) data assimilation into reanalysis models (ERA-Interim, ERA5, and CFSR). For each catchment, runoff and evapotranspiration simulations are obtained by forcing the model with the various precipitation products. Evaluation is done at the monthly time scale during the period of 1984–2007. We find that simulated runoff values are highly dependent on the accuracy of precipitation inputs, and thus show significant differences between the simulations. By contrast, simulated evapotranspiration is generally much less influenced. The results are further analysed with respect to different hydro-climatic regimes. We find that the impact of precipitation uncertainty on simulated runoff increases towards wetter regions, while the opposite is observed in the case of evapotranspiration. Finally, we perform an indirect performance evaluation of the precipitation datasets by comparing the runoff simulations with streamflow observations. Thereby, E-OBS yields the best agreement, while furthermore ERA5, GPCC V.2018 and MSWEP V2 show good performance. In summary, our findings highlight a climate-dependent propagation of precipitation uncertainty through the water cycle; while runoff is strongly impacted in comparatively wet regions such as Central Europe, there are increasing implications on evapotranspiration towards drier regions.

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