Testing the simulation skill of hydrological models under transient climate conditions for European case studies

2020 ◽  
Author(s):  
Ernesto Pasten-Zapata ◽  
Paul Royer-Gaspard ◽  
Rafael Pimentel ◽  
Torben O. Sonnenborg ◽  
Anthony Lemoine ◽  
...  
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Climate Models ◽  
Hydrological Model ◽  
Regional Climate ◽  
Circulation Model ◽  
Climatic Conditions ◽  
Climate Change Scenarios ◽  
Hydrological Models ◽  
Climate Conditions

<p>Commonly, the analysis of climate change impacts on hydrology involves a series of steps that begin with a General Circulation Model followed by the application of a downscaling or bias correction method and then coupling the climate outputs to a hydrological model. Nevertheless, frequently the hydrological models employed in these analyses are not tested to assess their skill to simulate the hydrology of a catchment under changing climate regimes. We evaluate such skill by applying a Differential Split Sampling Test (DSST) using the available observations. The models are calibrated during the three most extreme dry (or wet) years and evaluated on the three most wet (or dry) years. The DSST is applied on three catchments located across Europe: Denmark, France and Spain. This spatial distribution allows us to evaluate the method on diverse climatic and hydrological regimes. Furthermore, the DSST is applied to three different models in each of the catchments and case-specific metrics are evaluated to determine the practical usefulness of the models. Based on the DSST results, we assign a weight to the hydrological models and drive them with six Euro-CORDEX Regional Climate Models to assess climate change scenarios for the case-specific metrics. This methodology allows us to increase the confidence of our projections considering the hydrological model uncertainty for transient climatic conditions.</p>

scholarly journals An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources

2013 ◽  
Vol 17 (2) ◽  
pp. 565-578 ◽  
Author(s):  
J. A. Velázquez ◽  
J. Schmid ◽  
S. Ricard ◽  
M. J. Muerth ◽  
B. Gauvin St-Denis ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Models ◽  
Hydrological Model ◽  
Global Climate ◽  
Regional Climate ◽  
Structural Complexity ◽  
Global Climate Models ◽  
Hydrological Models ◽  
The Impact

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.

scholarly journals Development of a SWAT Hydropower Operation Routine and Its Application to Assessing Hydrological Alterations in the Mekong

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2193
Author(s):  
Jayandra P. Shrestha ◽  
Markus Pahlow ◽  
Thomas A. Cochrane
Keyword(s):  
Climate Change ◽  
Reservoir Operation ◽  
General Circulation ◽  
Hydrological Model ◽  
Circulation Model ◽  
Climate Change Scenarios ◽  
Reservoir Operations ◽  
Reservoir Systems ◽  
Hydropower Operation ◽  
Impacts Of Climate Change

Reservoir operations and climate change can alter natural river flow regimes. To assess impacts of climate and hydropower operations on downstream flows and energy generation, an integrated hydropower operations and catchment hydrological model is needed. The widely used hydrological model Soil and Water Assessment Tool (SWAT) is ideal for catchment hydrology, but provides only limited reservoir operation functions. A hydropower reservoir operation routine (HydROR) was thus developed for SWAT to analyze complex reservoir systems under different policies. The Hydrologic Engineering Center’s Reservoir System Simulation (HEC-ResSim) model, a well-established reservoir simulation model, was used to indirectly evaluate functionality of the HydROR. A comparison between HydROR and HEC-ResSim under a range of operation rule curves resulted in R2 values exceeding 0.99. The HydROR was then applied to assess hydrological alterations due to combined impacts of climate change and reservoir operations of 38 hydropower dams in the 3S basin of the Mekong River. Hydropower production under climate change varied from −1.6% to 2.3%, depending on the general circulation model chosen. Changing the hydropower operation policy from maximizing energy production to maintaining ecological flows resulted in a production change of 13%. The calculation of hydrological alteration indices at the outlet of the 3S basin revealed that over 113% alteration in the natural river outflow regime occurred from the combined impacts of climate change and reservoir operations. Furthermore, seasonal flows and extreme water conditions changed by 154% and 104%, respectively. Alterations were also significant within the basin, and, as expected, were larger for high-head and small-river reservoirs. These alterations will adversely affect ecological dynamics, in particular, habitat availability. HydROR proved to be a valuable addition to SWAT for the analyses of complex reservoir systems under different policies and climate change scenarios.

scholarly journals An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources

2012 ◽  
Vol 9 (6) ◽  
pp. 7441-7474 ◽  
Author(s):  
J. A. Velázquez ◽  
J. Schmid ◽  
S. Ricard ◽  
M. J. Muerth ◽  
B. Gauvin St-Denis ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Climate Models ◽  
Hydrological Model ◽  
Regional Climate ◽  
Structural Complexity ◽  
Regional Climate Models ◽  
Hydrological Models ◽  
Distributed Models ◽  
The Impact

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.

scholarly journals An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate Models

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Dongwoo Jang
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Pearson Correlation ◽  
Regional Climate ◽  
Circulation Model ◽  
Regional Climate Models ◽  
Change Scenario ◽  
Climate Change Scenarios ◽  
Precipitation Data ◽  
Simulated Precipitation

Climate change scenarios are used for predicting future precipitation. More detailed regional climate change scenarios are being used through dynamic downscale based on global circulation model results. There is a global tendency to utilize simulated precipitation data from downscaled regional climate models (RCMs) suitable for each country. In Korea, there are studies for improving the accuracy of climate change scenario precipitation forecasts compared with observed precipitation. In this study, the precipitation of five regional climate models and actual observed precipitation provided in Korea are applied to ANN (artificial neural network), which suggests ways to improve prediction accuracy for precipitation. The ANN ensemble of RCMs simulates the actual observed precipitation more accurately than the individual RCM. In particular, it is more effective inland than in coastal areas, where precipitation patterns are complex. Pearson correlation coefficient of ANN is high as 0.04 compared with MRA. It is expected that more detailed analysis will be possible if it is applied not only to four cities but also to other regions in Korea. If observed precipitation data are collected in sufficient quantity, the applicability of the ANN model will widen.

scholarly journals Water Budgets of Managed Forests in Northeast Germany under Climate Change—Results from a Model Study on Forest Monitoring Sites

2021 ◽  
Vol 11 (5) ◽  
pp. 2403
Author(s):  
Daniel Ziche ◽  
Winfried Riek ◽  
Alexander Russ ◽  
Rainer Hentschel ◽  
Jan Martin
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Coupled Model ◽  
Regional Climate Models ◽  
Realistic Model ◽  
Forest Monitoring ◽  
Climate Change Scenarios ◽  
Historical Time ◽  
Time Period

To develop measures to reduce the vulnerability of forests to drought, it is necessary to estimate specific water balances in sites and to estimate their development with climate change scenarios. We quantified the water balance of seven forest monitoring sites in northeast Germany for the historical time period 1961–2019, and for climate change projections for the time period 2010–2100. We used the LWF-BROOK90 hydrological model forced with historical data, and bias-adjusted data from two models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) downscaled with regional climate models under the representative concentration pathways (RCPs) 2.6 and 8.5. Site-specific monitoring data were used to give a realistic model input and to calibrate and validate the model. The results revealed significant trends (evapotranspiration, dry days (actual/potential transpiration < 0.7)) toward drier conditions within the historical time period and demonstrate the extreme conditions of 2018 and 2019. Under RCP8.5, both models simulate an increase in evapotranspiration and dry days. The response of precipitation to climate change is ambiguous, with increasing precipitation with one model. Under RCP2.6, both models do not reveal an increase in drought in 2071–2100 compared to 1990–2019. The current temperature increase fits RCP8.5 simulations, suggesting that this scenario is more realistic than RCP2.6.

Optimized planning and operation of interconnected multi-purpose reservoir systems using integrated modeling for climate change adaptation

2021 ◽  
Author(s):  
Patrick Nistahl ◽  
Tim Müller ◽  
Gerhard Riedel ◽  
Hannes Müller-Thomy ◽  
Günter Meon
Keyword(s):  
Climate Change ◽  
Reservoir Operation ◽  
Climate Models ◽  
Hydrological Model ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Flood Protection ◽  
Performance Criteria ◽  
Low Flow ◽  
Operation Model

&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;As hydrological model, the conceptual, semi-distributed version of PANTA RHEI is applied. &amp;#160;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;

scholarly journals Simulating future precipitation extremes in a complex Alpine catchment

2013 ◽  
Vol 13 (2) ◽  
pp. 263-277 ◽  
Author(s):  
C. Dobler ◽  
G. Bürger ◽  
J. Stötter
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Precipitation Extremes ◽  
Climate Projections ◽  
Research Station ◽  
Climate Change Scenarios ◽  
Station Data

Abstract. The objectives of the present investigation are (i) to study the effects of climate change on precipitation extremes and (ii) to assess the uncertainty in the climate projections. The investigation is performed on the Lech catchment, located in the Northern Limestone Alps. In order to estimate the uncertainty in the climate projections, two statistical downscaling models as well as a number of global and regional climate models were considered. The downscaling models applied are the Expanded Downscaling (XDS) technique and the Long Ashton Research Station Weather Generator (LARS-WG). The XDS model, which is driven by analyzed or simulated large-scale synoptic fields, has been calibrated using ECMWF-interim reanalysis data and local station data. LARS-WG is controlled through stochastic parameters representing local precipitation variability, which are calibrated from station data only. Changes in precipitation mean and variability as simulated by climate models were then used to perturb the parameters of LARS-WG in order to generate climate change scenarios. In our study we use climate simulations based on the A1B emission scenario. The results show that both downscaling models perform well in reproducing observed precipitation extremes. In general, the results demonstrate that the projections are highly variable. The choice of both the GCM and the downscaling method are found to be essential sources of uncertainty. For spring and autumn, a slight tendency toward an increase in the intensity of future precipitation extremes is obtained, as a number of simulations show statistically significant increases in the intensity of 90th and 99th percentiles of precipitation on wet days as well as the 5- and 20-yr return values.

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.

Using machine learning to downscale simulations of climate change induced changes to the shallow groundwater table

2021 ◽  
Author(s):  
Raphael Schneider ◽  
Hans Jørgen Henriksen ◽  
Julian Koch ◽  
Lars Troldborg ◽  
Simon Stisen
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Hydrological Model ◽  
Shallow Groundwater ◽  
Groundwater Table ◽  
Training Data ◽  
Computational Time ◽  
Hydrological Models ◽  
Shallow Groundwater Table ◽  
Induced Changes

&lt;p&gt;The DK-model (https://vandmodel.dk/in-english) is a national water resource model, covering all of Denmark. Its core is a distributed, integrated surface-subsurface hydrological model in 500m horizontal resolution. With recent efforts, a version at a higher resolution of 100m was created. The higher resolution was, amongst others, desired by end-users and to better represent surface and surface-near phenomena such as the location of the uppermost groundwater table. Being presently located close to the surface across substantial parts of the country and partly expected to rise, the groundwater table and its future development due to climate change is of great interest. A rising groundwater table is associated with potential risks for infrastructure, agriculture and ecosystems. However, the 25-fold jump in resolution of the hydrological model also increases the computational effort. Hence, it was deemed unfeasible to run the 100m resolution hydrological model nation-wide with an ensemble of climate models to evaluate climate change impact. The full ensemble run could only be performed with the 500m version of the model. To still produce the desired outputs at 100m resolution, a downscaling method was applied as described in the following.&lt;/p&gt;&lt;p&gt;Five selected subcatchment models covering around 9% of Denmark were run with five selected climate models at 100m resolution (using less than 3% of the computational time for hydrological models compared to a national, full ensemble run at 100m). Using the simulated changes at 100m resolution from those models as training data, combined with a set of covariates including the simulated changes in 500m resolution, Random Forest (RF) algorithms were trained to downscale simulated changes from 500m to 100m.&lt;/p&gt;&lt;p&gt;Generalizing the trained RF algorithms, Denmark-wide maps of expected climate change induced changes to the shallow groundwater table at 100m resolution were modelled. To verify the downscaling results, amongst others, the RF algorithms were successfully validated against results from a sixth hydrological subcatchment model at 100m resolution not used in training the algorithms.&lt;/p&gt;&lt;p&gt;The experience gained also opens for various other applications of similar algorithms where computational limitations inhibit running distributed hydrological models at fine resolutions: The results suggest the potential to downscale other model outputs that are desired at fine resolutions.&lt;/p&gt;

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