Utilising data and knowledge from European geological survey organisations in climate change impact assessments and adaptations

2020 ◽  
Author(s):  
Anker Lajer Hojberg ◽  
Ida Bjørnholt Karlsson ◽  
Klaus Hinsby ◽  
Jacob Kidmose ◽  
Hélène Bessiere ◽  
...  
Keyword(s):  
Climate Change ◽  
Decision Support ◽  
Climate Change Impact ◽  
Adaptation Strategies ◽  
Geological Survey ◽  
Geological Data ◽  
Data Infrastructure ◽  
Horizon 2020 ◽  
Change Impact ◽  
The Impact

<p>Climate change (CC) already have widespread and significant impacts in Europe, which is expected to increase in the future. Groundwater plays a vital role for the land phase of the freshwater cycle and have the capability of buffering or enhancing the impact from extreme climate events causing droughts or floods, depending on the subsurface properties and the status of the system (dry/wet) prior to the climate event. Understanding and taking the hydrogeology into account is therefore essential in the assessment of climate change impacts.</p><p>The Geological Survey Organisations (GSOs) in Europe compile the necessary data and knowledge of the groundwater systems across Europe. The overall vision of the project “Tools for Assessment of ClimaTe change ImpacT on Groundwater and Adaptation Strategies – TACTIC” is to enhance the utilisation of these data and knowledge of the subsurface system in CC impact assessments, and the identification and analyses of potential adaptation strategies. To reach this vision, the objective of TACTIC is to contribute to the development of coherent and transparent assessments of CC impacts on groundwater and surface water, supporting improved EU policy making, and providing decision support for stakeholders and decision makers. To accomplish this, an infra-structure among European Geological Survey Organisations are developed in TACTIC to foster advancement and harmonisation of CC assessments, made up by: 1) The TACTIC Toolbox, consisting of relevant tools and methods for CC impact assessments, 2) TACTIC guidelines that will guide GSOs and other relevant stakeholders on the selection of appropriate tools and their use for producing comparable results, 3) The European Geological Data Infrastructure (EGDI) where data, reports and open-access papers will be stored  and made freely available  </p><p>The project is centred around 40 pilot studies covering a variety of CC challenges as well as different hydrogeological settings and different management systems found in Europe. The pilot activities are coordinated centrally in the project, to ensure that assessments, to the extent possible, are harmonised and can be compared across pilots. Synthesizing the experiences and results from the pilots will enable the development of a guideline and future roadmap, with the aim of 1) encouraging more GSOs to contribute in CC impact assessments 2) providing guidance to make the learning curve less steep and 3)ensuring that new assessments are comparable with assessments conducted in TACTIC.</p><p>TACTIC is part of the Horizon 2020 ERA-NET on Applied Geoscience (GeoERA) and together with the three other GeoERA groundwater projects, TACTIC will provide new and important data for further development of the European Geological Data Infrastructure (EGDI) with publicly available data enabling the development of EU-wide decision support systems for sustainable management of subsurface resources in a changing climate.</p><p>This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 731166.</p>

scholarly journals Evaluation of Climate Change Impact on Groundwater Recharge in Groundwater Regions in Taiwan

Water ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1153
Author(s):  
Shih-Jung Wang ◽  
Cheng-Haw Lee ◽  
Chen-Feng Yeh ◽  
Yong Fern Choo ◽  
Hung-Wei Tseng
Keyword(s):  
Climate Change ◽  
Groundwater Recharge ◽  
Climate Change Impact ◽  
Groundwater Resources ◽  
Regression Equations ◽  
Impact Of Climate Change ◽  
Groundwater Systems ◽  
Change Impact ◽  
The Impact ◽  
Assessment Results

Climate change can directly or indirectly influence groundwater resources. The mechanisms of this influence are complex and not easily quantified. Understanding the effect of climate change on groundwater systems can help governments adopt suitable strategies for water resources. The baseflow concept can be used to relate climate conditions to groundwater systems for assessing the climate change impact on groundwater resources. This study applies the stable baseflow concept to the estimation of the groundwater recharge in ten groundwater regions in Taiwan, under historical and climate scenario conditions. The recharge rates at the main river gauge stations in the groundwater regions were assessed using historical data. Regression equations between rainfall and groundwater recharge quantities were developed for the ten groundwater regions. The assessment results can be used for recharge evaluation in Taiwan. The climate change estimation results show that climate change would increase groundwater recharge by 32.6% or decrease it by 28.9% on average under the climate scenarios, with respect to the baseline quantity in Taiwan. The impact of climate change on groundwater systems may be positive. This study proposes a method for assessing the impact of climate change on groundwater systems. The assessment results provide important information for strategy development in groundwater resources management.

Communicating water-related climate change hazards to local stakeholders

2021 ◽  
Author(s):  
Laura Müller ◽  
Petra Döll
Keyword(s):  
Climate Change ◽  
Water Management ◽  
Climate Change Impact ◽  
Biosphere Reserve ◽  
Hydrological Models ◽  
Model Ensemble ◽  
Hydrological Hazards ◽  
Local Stakeholders ◽  
Change Impact ◽  
The Impact

<p>Due to climate change, the water cycle is changing which requires to adapt water management in many regions. The transdisciplinary project KlimaRhön aims at assessing water-related risks and developing adaptation measures in water management in the UNESCO Biosphere Reserve Rhön in Central Germany. One of the challenges is to inform local stakeholders about hydrological hazards in in the biosphere reserve, which has an area of only 2433 km² and for which no regional hydrological simulations are available. To overcome the lack of local simulations of the impact of climate change on water resources, existing simulations by a number of global hydrological models (GHMs) were evaluated for the study area. While the coarse model resolution of 0.5°x0.5° (55 km x 55 km at the equator) is certainly problematic for the small study area, the advantage is that both the uncertainty of climate simulations and hydrological models can be taken into account to provide a best estimate of future hazards and their (large) uncertainties. This is different from most local hydrological climate change impact assessments, where only one hydrological model is used, which leads to an underestimation of future uncertainty as different hydrological models translate climatic changes differently into hydrological changes and, for example, mostly do not take into account the effect of changing atmospheric CO<sub>2</sub> on evapotranspiration and thus runoff.   </p><p>The global climate change impact simulations were performed in a consistent manner by various international modeling groups following a protocol developed by ISIMIP (ISIMIP 2b, www.isimip.org); the simulation results are freely available for download. We processed, analyzed and visualized the results of the multi-model ensemble, which consists of eight GHMs driven by the bias-adjusted output of four general circulation models. The ensemble of potential changes of total runoff and groundwater recharge were calculated for two 30-year future periods relative to a reference period, analyzing annual and seasonal means as well as interannual variability. Moreover, the two representative concentration pathways RCP 2.6 and 8.5 were chosen to inform stakeholders about two possible courses of anthropogenic emissions.</p><p>To communicate the results to local stakeholders effectively, the way to present modeling results and their uncertainty is crucial. The visualization and textual/oral presentation should not be overwhelming but comprehensive, comprehensible and engaging. It should help the stakeholder to understand the likelihood of particular hazards that can be derived from multi-model ensemble projections. In this contribution, we present the communication approach we applied during a stakeholder workshop as well as its evaluation by the stakeholders.</p>

scholarly journals Uncertainty in runoff based on Global Climate Model precipitation and temperature data – Part 2: Estimation and uncertainty of annual runoff and reservoir yield

2014 ◽  
Vol 11 (5) ◽  
pp. 4579-4638 ◽  
Author(s):  
M. C. Peel ◽  
R. Srikanthan ◽  
T. A. McMahon ◽  
D. J. Karoly
Keyword(s):  
Climate Change ◽  
Standard Deviation ◽  
Climate Change Impact ◽  
Global Climate ◽  
Annual Runoff ◽  
Monthly Precipitation ◽  
Change Impact ◽  
The Impact ◽  
Reservoir Yield ◽  
Precipitation And Temperature

Abstract. Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between Global Climate Models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) datasets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to approximate within-GCM uncertainty of monthly precipitation and temperature projections and assess its impact on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. To-date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2014) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from CMIP3 for use in this paper. Here we present within- and between-GCM uncertainty results in mean annual precipitation (MAP), temperature (MAT) and runoff (MAR), the standard deviation of annual precipitation (SDP) and runoff (SDR) and reservoir yield for five CMIP3 GCMs at 17 world-wide catchments. Based on 100 stochastic replicates of each GCM run at each catchment, within-GCM uncertainty was assessed in relative form as the standard deviation expressed as a percentage of the mean of the 100 replicate values of each variable. The average relative within-GCM uncertainty from the 17 catchments and 5 GCMs for 2015–2044 (A1B) were: MAP 4.2%, SDP 14.2%, MAT 0.7%, MAR 10.1% and SDR 17.6%. The Gould–Dincer Gamma procedure was applied to each annual runoff time-series for hypothetical reservoir capacities of 1× MAR and 3× MAR and the average uncertainty in reservoir yield due to within-GCM uncertainty from the 17 catchments and 5 GCMs were: 25.1% (1× MAR) and 11.9% (3× MAR). Our approximation of within-GCM uncertainty is expected to be an underestimate due to not replicating the GCM trend. However, our results indicate that within-GCM uncertainty is important when interpreting climate change impact assessments. Approximately 95% of values of MAP, SDP, MAT, MAR, SDR and reservoir yield from 1× MAR or 3× MAR capacity reservoirs are expected to fall within twice their respective relative uncertainty (standard deviation/mean). Within-GCM uncertainty has significant implications for interpreting climate change impact assessments that report future changes within our range of uncertainty for a given variable – these projected changes may be due solely to within-GCM uncertainty. Since within-GCM variability is amplified from precipitation to runoff and then to reservoir yield, climate change impact assessments that do not take into account within-GCM uncertainty risk providing water resources management decision makers with a sense of certainty that is unjustified.

Climate change impact chains in the water sector: observations from projects on the East India coast

2013 ◽  
Vol 5 (2) ◽  
pp. 216-232
Author(s):  
Sibylle Kabisch ◽  
Ronjon Chakrabarti ◽  
Till Wolf ◽  
Wilhelm Kiewitt ◽  
Ty Gorman ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Management ◽  
Climate Change Impact ◽  
Tamil Nadu ◽  
Causal Chain ◽  
Climate Impacts ◽  
Top Down ◽  
Bottom Up ◽  
Change Impact ◽  
The Impact

With regional variations, climate change has a significant impact on water quality deterioration and scarcity, which are serious challenges in developing countries and emerging economies. Often, effective projects to improve water management in the light of climate change are difficult to develop because of the complex interrelations between direct and indirect climate impacts and local perceptions of vulnerabilities and needs. Adaptation projects can be developed through a combination of participatory, bottom-up needs assessments and top-down analyses. Climate change impact chains can help to display the causal chain of climate signals and resulting impacts and thereby establish a system map as a basis for stakeholder discussions. This article aims to develop specific climate change impact chains for the water management sector in rural coastal India that combine bottom-up and top-down perspectives. Case studies from Tamil Nadu and Andhra Pradesh, India, provide a basis for the impact chains developed. Bottom-up data were gathered through a vulnerability and needs assessment in 18 villages complemented with top-down research data. The article is divided into four steps: (1) system of interest; (2) data on climate change signals; (3) climate change impacts based on top-down as well as bottom-up information; (4) specific impact chains complemented by initial climate change adaptation options.

Drought Effects on Groundwater in Dobrogea Plateau

2015 ◽  
pp. 119-144
Author(s):  
Doina Drăguşin
Keyword(s):  
Climate Change ◽  
Climate Change Impact ◽  
Drought Index ◽  
Anthropogenic Impacts ◽  
Economic Issues ◽  
Structural Context ◽  
Piezometric Surface ◽  
Change Impact ◽  
The Impact ◽  
Drought Effects

The study aims to analyse the impact of the drought phenomenon on groundwater in Dobrogea Plateau, taking into account the specific climatic and hydrological factors and especially the geological and structural context in which it delineates the main hydrostructures. The groundwater is subject to climatic and anthropogenic impacts whose weight are difficult to assess, so until now, a hydrogeological drought index was not identified. The effects of climate change impact are reflected in the fluctuations of the piezometric surface of the shallow aquifers, the deepest aquifers being influenced rather by socio-economic issues. To achieve the objective of the research, the available data (climate, hydrological and hydrogeological) were processed using GIS and Excel softs and the results (maps, graphs, tables) were interpreted and correlated in some relevant conclusions.

Climate Change Impact on Agriculture and Food Security

2018 ◽  
pp. 223-237
Author(s):  
Ali Syed ◽  
Urooj Afshan Jabeen
Keyword(s):  
Climate Change ◽  
Food Security ◽  
Climate Change Impact ◽  
Food Shortage ◽  
Central Province ◽  
Impact Of Climate Change ◽  
Change Impact ◽  
Agriculture And Food ◽  
The Impact ◽  
Late Sowing

Research on the impact of climate change on agriculture and food security is important, especially in the agricultural economies, not only to know the severity of impact but also the policies to be adapted to halt climate change and the technology to be used to mitigate the impact of climate change. The study was conducted in Kapiri Mposhi district of Central Province in Zambia to find out the impact of climate change on agriculture and food security. The objectives of study include to know the intensity of climate change and its impact on area under cultivation, late sowing of seed and damage of seed due to lack of water, fertilizer absorption reduction, food shortage, livestock, and productivity. The chapter also focuses on the sources of credit to the farmers.

Effects of climate change on babesiosis vectors.

2021 ◽  
pp. 223-227
Author(s):  
Jeremy Gray
Keyword(s):  
Climate Change ◽  
Ixodes Ricinus ◽  
Climate Change Impact ◽  
Dermacentor Reticulatus ◽  
Impact Of Climate Change ◽  
Climate Change Effects ◽  
Haemaphysalis Punctata ◽  
Change Impact ◽  
Abundance And Distribution ◽  
The Impact

Abstract This chapter discusses the impact of climate change on the abundance and distribution of babesiosis vectors and, by implication, transmission of Babesia spp. It discusses evidence for climate change impact on the vectors Ixodes ricinus, Dermacentor reticulatus, Haemaphysalis punctata and Hyalomma spp. as well as the absence of evidence of the same climate change effects on the vectors Rhipicephalus spp. and I. scapularis.

scholarly journals Approximating uncertainty of annual runoff and reservoir yield using stochastic replicates of global climate model data

2015 ◽  
Vol 19 (4) ◽  
pp. 1615-1639 ◽  
Author(s):  
M. C. Peel ◽  
R. Srikanthan ◽  
T. A. McMahon ◽  
D. J. Karoly
Keyword(s):  
Climate Change ◽  
Standard Deviation ◽  
Climate Change Impact ◽  
Global Climate ◽  
Annual Runoff ◽  
Monthly Precipitation ◽  
Change Impact ◽  
The Impact ◽  
Reservoir Yield ◽  
Precipitation And Temperature

Abstract. Two key sources of uncertainty in projections of future runoff for climate change impact assessments are uncertainty between global climate models (GCMs) and within a GCM. Within-GCM uncertainty is the variability in GCM output that occurs when running a scenario multiple times but each run has slightly different, but equally plausible, initial conditions. The limited number of runs available for each GCM and scenario combination within the Coupled Model Intercomparison Project phase 3 (CMIP3) and phase 5 (CMIP5) data sets, limits the assessment of within-GCM uncertainty. In this second of two companion papers, the primary aim is to present a proof-of-concept approximation of within-GCM uncertainty for monthly precipitation and temperature projections and to assess the impact of within-GCM uncertainty on modelled runoff for climate change impact assessments. A secondary aim is to assess the impact of between-GCM uncertainty on modelled runoff. Here we approximate within-GCM uncertainty by developing non-stationary stochastic replicates of GCM monthly precipitation and temperature data. These replicates are input to an off-line hydrologic model to assess the impact of within-GCM uncertainty on projected annual runoff and reservoir yield. We adopt stochastic replicates of available GCM runs to approximate within-GCM uncertainty because large ensembles, hundreds of runs, for a given GCM and scenario are unavailable, other than the Climateprediction.net data set for the Hadley Centre GCM. To date within-GCM uncertainty has received little attention in the hydrologic climate change impact literature and this analysis provides an approximation of the uncertainty in projected runoff, and reservoir yield, due to within- and between-GCM uncertainty of precipitation and temperature projections. In the companion paper, McMahon et al. (2015) sought to reduce between-GCM uncertainty by removing poorly performing GCMs, resulting in a selection of five better performing GCMs from CMIP3 for use in this paper. Here we present within- and between-GCM uncertainty results in mean annual precipitation (MAP), mean annual temperature (MAT), mean annual runoff (MAR), the standard deviation of annual precipitation (SDP), standard deviation of runoff (SDR) and reservoir yield for five CMIP3 GCMs at 17 worldwide catchments. Based on 100 stochastic replicates of each GCM run at each catchment, within-GCM uncertainty was assessed in relative form as the standard deviation expressed as a percentage of the mean of the 100 replicate values of each variable. The average relative within-GCM uncertainties from the 17 catchments and 5 GCMs for 2015–2044 (A1B) were MAP 4.2%, SDP 14.2%, MAT 0.7%, MAR 10.1% and SDR 17.6%. The Gould–Dincer Gamma (G-DG) procedure was applied to each annual runoff time series for hypothetical reservoir capacities of 1 × MAR and 3 × MAR and the average uncertainties in reservoir yield due to within-GCM uncertainty from the 17 catchments and 5 GCMs were 25.1% (1 × MAR) and 11.9% (3 × MAR). Our approximation of within-GCM uncertainty is expected to be an underestimate due to not replicating the GCM trend. However, our results indicate that within-GCM uncertainty is important when interpreting climate change impact assessments. Approximately 95% of values of MAP, SDP, MAT, MAR, SDR and reservoir yield from 1 × MAR or 3 × MAR capacity reservoirs are expected to fall within twice their respective relative uncertainty (standard deviation/mean). Within-GCM uncertainty has significant implications for interpreting climate change impact assessments that report future changes within our range of uncertainty for a given variable – these projected changes may be due solely to within-GCM uncertainty. Since within-GCM variability is amplified from precipitation to runoff and then to reservoir yield, climate change impact assessments that do not take into account within-GCM uncertainty risk providing water resources management decision makers with a sense of certainty that is unjustified.

scholarly journals System Dynamics Approach for Assessing the Behaviour of the Lim Reservoir System (Serbia) under Changing Climate Conditions

Water ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1620 ◽  
Author(s):  
Milan Stojkovic ◽  
Slobodan P. Simonovic
Keyword(s):  
Climate Change ◽  
System Dynamics ◽  
Climate Change Impact ◽  
Impact Analysis ◽  
Winter Season ◽  
Water System ◽  
Dynamics Simulation ◽  
Hydropower Generation ◽  
Change Impact ◽  
The Impact

Investigating the impact of climate change on the management of a complex multipurpose water system is a critical issue. The presented study focuses on different steps of the climate change impact analysis process: (i) Use of three regional climate models (RCMs), (ii) use of four bias correction methods (BCMs), (iii) use of three concentration scenarios (CSs), (iv) use of two model averaging procedures, (v) use of the hydrological model and (vi) use of the system dynamics simulation model (SDSM). The analyses are performed for a future period, from 2006 to 2055 and the reference period, from 1971 to 2000. As a case study area, the Lim water system in Serbia (southeast Europe) is used. The Lim river system consists of four hydraulically connected reservoirs (Uvac, Kokin Brod, Radojnja, Potpec) with a primary purpose of hydropower generation. The results of the climate change impact analyses indicate change in the future hydropower generation at the annual level from −3.5% to +17.9%. The change has a seasonal variation with an increase for the winter season up to +20.3% and decrease for the summer season up to −33.6%. Furthermore, the study analyzes the uncertainty in the SDSM outputs introduced by different steps of the modelling process. The most dominant source of uncertainty in power production is the choice of BCMs (54%), followed by the selection of RCMs (41%). The least significant source of uncertainty is the choice of CSs (6%). The uncertainty in the inflows and outflows is equally dominated by the choice of BCM (49%) and RCM (45%).

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