Hydrological Forecasts and Projections for Improved Decision-Making in the Water Sector in Europe

Abstract Simulations of water fluxes at high spatial resolution that consistently cover historical observations, seasonal forecasts, and future climate projections are key to providing climate services aimed at supporting operational and strategic planning, and developing mitigation and adaptation policies. The End-to-end Demonstrator for improved decision-making in the water sector in Europe (EDgE) is a proof-of-concept project funded by the Copernicus Climate Change Service program that addresses these requirements by combining a multimodel ensemble of state-of-the-art climate model outputs and hydrological models to deliver sectoral climate impact indicators (SCIIs) codesigned with private and public water sector stakeholders from three contrasting European countries. The final product of EDgE is a water-oriented information system implemented through a web application. Here, we present the underlying structure of the EDgE modeling chain, which is composed of four phases: 1) climate data processing, 2) hydrological modeling, 3) stakeholder codesign and SCII estimation, and 4) uncertainty and skill assessments. Daily temperature and precipitation from observational datasets, four climate models for seasonal forecasts, and five climate models under two emission scenarios are consistently downscaled to 5-km spatial resolution to ensure locally relevant simulations based on four hydrological models. The consistency of the hydrological models is guaranteed by using identical input data for land surface parameterizations. The multimodel outputs are composed of 65 years of historical observations, a 19-yr ensemble of seasonal hindcasts, and a century-long ensemble of climate impact projections. These unique, high-resolution hydroclimatic simulations and SCIIs provide an unprecedented information system for decision-making over Europe and can serve as a template for water-related climate services in other regions.

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Are we using the right fuel to drive hydrological models? A climate impact study in the Upper Blue Nile

Hydrology and Earth System Sciences ◽

10.5194/hess-22-2163-2018 ◽

2018 ◽

Vol 22 (4) ◽

pp. 2163-2185 ◽

Cited By ~ 9

Author(s):

Stefan Liersch ◽

Julia Tecklenburg ◽

Henning Rust ◽

Andreas Dobler ◽

Madlen Fischer ◽

...

Keyword(s):

Climate Change ◽

Bias Correction ◽

Climate Models ◽

Regional Climate ◽

Model Performance ◽

Climate Impact ◽

Hydrological Models ◽

Blue Nile ◽

Projected Change ◽

Model Ensembles

Abstract. Climate simulations are the fuel to drive hydrological models that are used to assess the impacts of climate change and variability on hydrological parameters, such as river discharges, soil moisture, and evapotranspiration. Unlike with cars, where we know which fuel the engine requires, we never know in advance what unexpected side effects might be caused by the fuel we feed our models with. Sometimes we increase the fuel's octane number (bias correction) to achieve better performance and find out that the model behaves differently but not always as was expected or desired. This study investigates the impacts of projected climate change on the hydrology of the Upper Blue Nile catchment using two model ensembles consisting of five global CMIP5 Earth system models and 10 regional climate models (CORDEX Africa). WATCH forcing data were used to calibrate an eco-hydrological model and to bias-correct both model ensembles using slightly differing approaches. On the one hand it was found that the bias correction methods considerably improved the performance of average rainfall characteristics in the reference period (1970–1999) in most of the cases. This also holds true for non-extreme discharge conditions between Q20 and Q80. On the other hand, bias-corrected simulations tend to overemphasize magnitudes of projected change signals and extremes. A general weakness of both uncorrected and bias-corrected simulations is the rather poor representation of high and low flows and their extremes, which were often deteriorated by bias correction. This inaccuracy is a crucial deficiency for regional impact studies dealing with water management issues and it is therefore important to analyse model performance and characteristics and the effect of bias correction, and eventually to exclude some climate models from the ensemble. However, the multi-model means of all ensembles project increasing average annual discharges in the Upper Blue Nile catchment and a shift in seasonal patterns, with decreasing discharges in June and July and increasing discharges from August to November.

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Climate impact assessment and “islandness”

International Journal of Climate Change Strategies and Management ◽

10.1108/ijccsm-06-2017-0142 ◽

2018 ◽

Vol 10 (2) ◽

pp. 289-302 ◽

Cited By ~ 2

Author(s):

Aideen Maria Foley

Keyword(s):

Decision Making ◽

Impact Assessment ◽

Climate Models ◽

Local Level ◽

Climate Impact ◽

Assessment Methods ◽

Small Island ◽

Climate Data ◽

Content Type ◽

Climate Impact Assessment

Purpose Climate data, including historical climate observations and climate model outputs, are often used in climate impact assessments, to explore potential climate futures. However, characteristics often associated with “islandness”, such as smallness, land boundedness and isolation, may mean that climate impact assessment methods applied at broader scales cannot simply be downscaled to island settings. This paper aims to discuss information needs and the limitations of climate models and datasets in the context of small islands and explores how such challenges might be addressed. Design/methodology/approach Reviewing existing literature, this paper explores challenges of islandness in top-down, model-led climate impact assessment and bottom-up, vulnerability-led approaches. It examines how alternative forms of knowledge production can play a role in validating models and in guiding adaptation actions at the local level and highlights decision-making techniques that can support adaptation even when data is uncertain. Findings Small island topography is often too detailed for global or even regional climate models to resolve, but equally, local meteorological station data may be absent or uncertain, particularly in island peripheries. However, rather than viewing the issue as decision-making with big data at the regional/global scale versus with little or no data at the small island scale, a more productive discourse can emerge by conceptualising strategies of decision-making with unconventional types of data. Originality/value This paper provides a critical overview and synthesis of issues relating to climate models, data sets and impact assessment methods as they pertain to islands, which can benefit decision makers and other end-users of climate data in island communities.

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Multi-model climate impact assessment and intercomparison for three large-scale river basins on three continents

Earth System Dynamics Discussions ◽

10.5194/esdd-5-849-2014 ◽

2014 ◽

Vol 5 (2) ◽

pp. 849-900 ◽

Cited By ~ 5

Author(s):

T. Vetter ◽

S. Huang ◽

V. Aich ◽

T. Yang ◽

X. Wang ◽

...

Keyword(s):

Impact Assessment ◽

Climate Models ◽

Water Discharge ◽

River Basins ◽

Climate Impact ◽

Climate Impacts ◽

Hydrological Models ◽

Climate Scenarios ◽

Climate Impact Assessment ◽

The Impact

Abstract. Climate change impacts on hydrological processes should be simulated for river basins using validated models and multiple climate scenarios in order to provide reliable results for stakeholders. In the last 10–15 years climate impact assessment was performed for many river basins worldwide using different climate scenarios and models. Nevertheless, the results are hardly comparable and do not allow to create a full picture of impacts and uncertainties. Therefore, a systematic intercomparison of impacts is suggested, which should be done for representative regions using state-of-the-art models. Our study is intended as a step in this direction. The impact assessment presented here was performed for three river basins on three continents: Rhine in Europe, Upper Niger in Africa and Upper Yellow in Asia. For that, climate scenarios from five GCMs and three hydrological models: HBV, SWIM and VIC, were used. Four "Representative Concentration Pathways" (RCPs) covering a range of emissions and land-use change projections were included. The objectives were to analyze and compare climate impacts on future trends considering three runoff quantiles: Q90, Q50 and Q10 and on seasonal water discharge, and to evaluate uncertainties from different sources. The results allow drawing some robust conclusions, but uncertainties are large and shared differently between sources in the studied basins. The robust results in terms of trend direction and slope and changes in seasonal dynamics could be found for the Rhine basin regardless which hydrological model or forcing GCM is used. For the Niger River scenarios from climate models are the largest uncertainty source, providing large discrepancies in precipitation, and therefore clear projections are difficult to do. For the Upper Yellow basin, both the hydrological models and climate models contribute to uncertainty in the impacts, though an increase in high flows in future is a robust outcome assured by all three hydrological models.

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Are we using the right fuel to drive hydrological models? A climate impact study in the Upper Blue Nile

10.5194/hess-2016-422 ◽

2016 ◽

Cited By ~ 4

Author(s):

Stefan Liersch ◽

Julia Tecklenburg ◽

Henning Rust ◽

Andreas Dobler ◽

Madlen Fischer ◽

...

Keyword(s):

Climate Change ◽

Bias Correction ◽

Climate Models ◽

Regional Climate ◽

Model Performance ◽

Climate Impact ◽

Hydrological Models ◽

Blue Nile ◽

Projected Change ◽

Model Ensembles

Abstract. Climate simulations are the fuel to drive hydrological models that are used to assess the impacts of climate change and variability on hydrological parameters, such as river discharges, soil moisture, and evapotranspiration. Unlike with cars, where we know which fuel the engine requires, we never know in advance what unexpected side-effects might be caused by the fuel we feed our models with. Sometimes we increase the fuel's octane number (bias-correction) to achieve better performance and find out that the model behaves differently but not always as was expected or desired. This study investigates the impacts of projected climate change on the hydrology of the Upper Blue Nile catchment using two model ensembles consisting of five global CMIP5 Earth System Models and ten Regional Climate Models (CORDEX Africa). WATCH forcing data were used to calibrate an eco-hydrological model and to bias-correct both model ensembles using slightly differing approaches. On the one hand it was found that the bias-correction methods considerably improved the performance of average rainfall characteristics in the reference period (1970–1999) in most of the cases. This also holds true for non-extreme discharge conditions between Q20 and Q80. On the other hand, bias-corrected simulations tend to overemphasise magnitudes of projected change signals and extremes. A general weakness of both uncorrected and bias-corrected simulations is the rather poor representation of high and low flows and their extremes, which were often deteriorated by bias-correction. This inaccuracy is a crucial deficiency for regional impact studies dealing with water management issues and it is therefore important to analyse model performance and characteristics, the effect of bias-correction, and eventually to exclude some climate models from the ensemble. However, the multi-model means of all ensembles project increasing average annual discharges in the Upper Blue Nile catchment and a shift in seasonal patterns, with decreasing discharges in June and July and increasing discharges from August to November.

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Upgrade of a climate service tailored to water reservoirs management

10.5194/ems2021-154 ◽

2021 ◽

Author(s):

Eroteida Sánchez-García ◽

Inmaculada Abia ◽

Marta Domínguez ◽

José Voces ◽

Juan Carlos Sánchez-Perrino ◽

...

Keyword(s):

Winter Season ◽

Scientific Progress ◽

Water Reservoir ◽

Water Inflow ◽

Hydrological Models ◽

Seasonal Forecasts ◽

Web Tool ◽

Water Reservoirs ◽

Climate Services ◽

Climate Service

In this paper we present the upgrade &#160;of &#160;a web tool designed to help in the decision making process for water reservoirs management in Spain. The tool, called S-ClimWaRe (Seasonal Climate predictions in support of Water Reservoirs management) is organized in two main displaying panels. The first one -diagnostic panel- allows the user to explore, for any water reservoir or grid point over continental Spain, the existing hydrological variability and risk linked to climate variability. &#160;The second one -forecasting panel- provides probabilistic seasonal predictions for some variables of interest. Following users&#8217; need the tool initially covers the extended winter season (from November to March), when the North Atlantic Oscillation pattern strongly influences the hydrological interannual variability in South-Western Europe. This climate service is fully user driven with a strong commitment of users and stakeholders that has allowed &#160;continuous improvement of this tool, meeting users requirements and incorporating latest scientific progress. The latest S-ClimWaRe version -developed in the framework of the MEDSCOPE project within the European Research Area for Climate Services (ERA4CS) initiative- includes some technical enhancements requested by customers and new seasonal predictions obtained through application of two post-processing steps to ECMWF System-5 forecasts. These two steps consist of a &#160;downscaling statistical procedure and a new methodology that combines different skilful NAO forecasts to create an optimal NAO pdf that is then used to weight the ensemble members forecasts of hydrological variables. The new upgraded S-ClimWaRe web tool enriches the forecasting panel with precipitation and water inflow forecast skill, and provides additional forecasts for accumulated snowfall and temperature. A prototype based on two different hydrological models to produce the seasonal forecasts of water inflow has also been tested over a pilot dam. These hydrological models are driven by the &#160;downscaled precipitation and temperature forecasts also introduced in the web viewer. The assessment of this downscaling procedure shows promising results with respect to the existing seasonal forecasts based on a statistical approach.

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Turn climate information into value for the Mediterranean wine sector: the MED-GOLD potential

10.5194/egusphere-egu2020-7046 ◽

2020 ◽

Author(s):

Alessandro Dell'Aquila ◽

Keyword(s):

Climate Change ◽

Decision Making ◽

Climate Models ◽

Food System ◽

Wine Production ◽

Climate Services ◽

Seamless Integration ◽

Horizon 2020 ◽

Wine Sector ◽

The Mediterranean

MED-GOLD is an EU-funded Horizon 2020 project (https://www.med-gold.eu/) whose main objective is to demonstrate the proof-of-concept for climate services in agriculture by developing case studies for three staples of the Mediterranean food system: grapes, olives and durum wheat.MED-GOLD will propose climate services deploying forecast information at seasonal (next 6 months) and long-term (next 30 years). This information will be provided at higher spatial resolution than what is currently available. To provide the highest value for decision-making, the services will be co-developed with professional users from each sector.For the wine sector, the project objective is to use the most recent state-of-the-art climate models outputs to produce user-oriented predictions of essential climate variables, bioclimatic indicators&#160; and ad-hoc implemented compound risk indices. All of these indices&#160; are relevant for viticulture at large scales, and more specifically for the MED-GOLD focus region of the Douro valley (Portugal). The indices&#160; will be readily available for users in the grape and wine sector under several different formats and visualizations, allowing for easy, quick and seamless integration into critical decision-making.Timely warnings of when climate change might impose a disruptive pressure upon wine production systems offers stakeholders a chance to act proactively both at seasonal (operational campaign planning) and decadal (strategic business planning) time-scales, making the wine sector more resilient to the impacts of climate change.

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Multi-model climate impact assessment and intercomparison for three large-scale river basins on three continents

Earth System Dynamics ◽

10.5194/esd-6-17-2015 ◽

2015 ◽

Vol 6 (1) ◽

pp. 17-43 ◽

Cited By ~ 79

Author(s):

T. Vetter ◽

S. Huang ◽

V. Aich ◽

T. Yang ◽

X. Wang ◽

...

Keyword(s):

Impact Assessment ◽

General Circulation ◽

Climate Models ◽

River Basins ◽

Climate Impact ◽

Climate Impacts ◽

Hydrological Models ◽

Climate Scenarios ◽

Climate Impact Assessment ◽

The Impact

Abstract. Climate change impacts on hydrological processes should be simulated for river basins using validated models and multiple climate scenarios in order to provide reliable results for stakeholders. In the last 10–15 years, climate impact assessment has been performed for many river basins worldwide using different climate scenarios and models. However, their results are hardly comparable, and do not allow one to create a full picture of impacts and uncertainties. Therefore, a systematic intercomparison of impacts is suggested, which should be done for representative regions using state-of-the-art models. Only a few such studies have been available until now with the global-scale hydrological models, and our study is intended as a step in this direction by applying the regional-scale models. The impact assessment presented here was performed for three river basins on three continents: the Rhine in Europe, the Upper Niger in Africa and the Upper Yellow in Asia. For that, climate scenarios from five general circulation models (GCMs) and three hydrological models, HBV, SWIM and VIC, were used. Four representative concentration pathways (RCPs) covering a range of emissions and land-use change projections were included. The objectives were to analyze and compare climate impacts on future river discharge and to evaluate uncertainties from different sources. The results allow one to draw some robust conclusions, but uncertainties are large and shared differently between sources in the studied basins. Robust results in terms of trend direction and slope and changes in seasonal dynamics could be found for the Rhine basin regardless of which hydrological model or forcing GCM is used. For the Niger River, scenarios from climate models are the largest uncertainty source, providing large discrepancies in precipitation, and therefore clear projections are difficult to do. For the Upper Yellow basin, both the hydrological models and climate models contribute to uncertainty in the impacts, though an increase in high flows in the future is a robust outcome ensured by all three hydrological models.

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An evaluation of the importance of spatial resolution in global climate and hydrological models based on the Rhine and Mississippi basins

10.5194/hess-2018-437 ◽

2018 ◽

Cited By ~ 1

Author(s):

Imme Benedict ◽

Chiel C. van Heerwaarden ◽

Albrecht H. Weerts ◽

Wilco Hazeleger

Keyword(s):

High Resolution ◽

Spatial Resolution ◽

Large Scale ◽

Climate Models ◽

Hydrological Cycle ◽

Global Climate ◽

Global Climate Models ◽

Hydrological Models ◽

Basin Scale ◽

Parameter Values

Abstract. To study the global hydrological cycle and its response to a changing climate, we rely on global climate models (GCMs) and global hydrological models (GHMs). The spatial resolution of these models is restricted by computational resources and therefore limits the processes and level of detail that can be resolved. We assess and compare the benefits of an increased resolution for a GCM and a GHM for two basins with long observational records; the Rhine and Mississippi basins. Increasing the resolution of a GCM (1.125° to 0.25°) results in an improved precipitation budget over the Rhine basin, attributed to a more realistic large-scale circulation. These improvements with increased resolution are not found for the Mississippi basin, possibly because precipitation is strongly depending on the representation of still unresolved convective processes. Increasing the resolution of vegetation and orography in the high resolution GHM (from 0.5° to 0.05°) shows no significant differences in discharge for both basins, likely because the hydrological processes depend highly on model parameter values that are not readily available at high resolution. Increasing the resolution of the GCM improved the simulations of the monthly averaged discharge for the Rhine, but did not improve the representation of extreme streamflow events. For the Mississippi basin, no substantial differences in precipitation and discharge were found between the two resolutions input GCM and the two resolutions GHM. These findings underline that there is no trivial route from increasing spatial resolution to a more accurately simulated hydrological cycle at basin scale.

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Use of expert elicitation to assign weights to climate and hydrological models in climate impact studies

10.5194/hess-2021-597 ◽

2021 ◽

Author(s):

Eva Sebok ◽

Hans Jørgen Henriksen ◽

Ernesto Pastén-Zapata ◽

Peter Berg ◽

Guillume Thirel ◽

...

Keyword(s):

Climate Models ◽

Climate Model ◽

Model Performance ◽

Climate Impact ◽

Expert Elicitation ◽

Model Structure ◽

Hydrological Models ◽

Model Ensemble ◽

Impact Studies ◽

Model Weighting

Abstract. Various methods are available for assessing uncertainties in climate impact studies. Among such methods, model weighting by expert elicitation is a practical way to provide a weighted ensemble of models for specific real-world impacts. The aim is to decrease the influence of improbable models in the results and easing the decision-making process. In this study both climate and hydrological models are analyzed and the result of a research experiment is presented using model weighting with the participation of 6 climate model experts and 6 hydrological model experts. For the experiment, seven climate models are a-priori selected from a larger Euro-CORDEX ensemble of climate models and three different hydrological models are chosen for each of the three European river basins. The model weighting is based on qualitative evaluation by the experts for each of the selected models based on a training material that describes the overall model structure and literature about climate models and the performance of hydrological models for the present period. The expert elicitation process follows a three-stage approach, with two individual elicitations of probabilities and a final group consensus, where the experts are separated into two different community groups: a climate and a hydrological modeller group. The dialogue reveals that under the conditions of the study, most climate modellers prefer the equal weighting of ensemble members, whereas hydrological impact modellers in general are more open for assigning weights to different models in a multi model ensemble, based on model performance and model structure. Climate experts are more open to exclude models, if obviously flawed, than to put weights on selected models in a relatively small ensemble. The study shows that expert elicitation can be an efficient way to assign weights to different hydrological models, and thereby reduce the uncertainty in climate impact. However, for the climate model ensemble, comprising seven models, the elicitation in the format of this study could only reestablish a uniform weight between climate models.

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Understanding climate and non-climate decision triggers to minimize Spring rainfall risks in vineyards

10.5194/ems2021-489 ◽

2021 ◽

Author(s):

Ilaria Vigo ◽

Raul Marcos ◽

António Graça ◽

Marta Terrado ◽

Nube González-Reviriego ◽

...

Keyword(s):

Decision Making ◽

Plant Protection ◽

Payoff Function ◽

Optimal Decision ◽

Seasonal Forecasts ◽

Climate Services ◽

Climate Risks ◽

Last Mile ◽

Collaboration Process ◽

Canopy Management

Climate services have travelled a long way, however, the last mile still has to be covered until climate information can be appropriately integrated in the users&#8217; decision making processes. When is the signal offered by a seasonal forecast useful? How and when can forecasts influence users&#8217; choices? How does the use of the forecasts compare with the methods currently in place? The answer can vary across users and even across decisions that the same user may take.This work analyses these questions through the decision making process of a wine producer aiming at reducing its exposure to spring rain variability. Spring rain drives risks of fungal disease causing crop loss and increased costs related to plant protection and canopy management. A transdisciplinary approach, including experts from various disciplines and the end user, is used to understand how and when a particular wine producer needs to trigger a decision linked to total Spring rainfall in order to reduce the risk entailed for plant protection and canopy management. Based on close collaboration, we construct a payoff function and simulate the decision driven by the choice of different forecasted probability thresholds and the business-as-usual decision, and we finally compare them to the observation. This exercise is repeated over 23 years to try eliciting the optimal threshold.The results show that the optimal decision to avoid climate risks is not always a feasible solution, demonstrating that climate is only one of the variables taken into account in the complex decision making context of a business. This highlights the importance of interpreting seasonal forecasts appropriately according to each user's context and understanding how this information will be integrated in the decision processes.&#160; Finally, it calls attention to the importance of co-creation in climate services and the need for extending the collaboration process up to the delivery phase, the so-called last mile.&#160;

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