Impacts of climate change on groundwater flooding and ecohydrology in lowland karst

Abstract. Lowland karst aquifers can generate unique wetland habitats which are caused by groundwater fluctuations that result in extensive groundwater-surface water interactions (i.e. flooding). However, the complex hydrogeological attributes of these systems often present difficulty in predicting how they will respond to changing climatological conditions. Extremely fast aquifer recharge processes and flow through well-connected conduit networks in such karst systems make them very susceptible to surcharge conditions – i.e. groundwater-surface water interaction (flooding) – and therefore vulnerable to changes in the sequence and intensity of precipitation patterns. This study investigates the predicted impacts of climate change on a lowland karst catchment by employing a semi-distributed karst model populated with output from high-resolution regional climate models for Ireland. The lowland karst catchment is located on the west coast of Ireland and is characterised by a well-developed karstified limestone aquifer which discharges to the sea via intertidal and submarine springs. Annual above ground flooding associated with this complex karst system has led to the development of unique wetland habitats in the form of ephemeral lakes known as turloughs, however extreme flooding of these features causes widespread damage and disruption in the catchment. This analysis has shown that mean, 95th and 99th percentile flood levels are expected to increase by significant proportions for all future emission scenarios. The frequency of events currently considered to be extreme is predicted to increase, indicating that more significant groundwater flooding events seem likely to become far more common. The seasonality of annual flooding is also predicted to shift later in the flooding season which could have far reaching consequences in terms of ecology and land use in the catchment. The impacts of increasing mean sea levels were also investigated, however it was found that anticipated rises had very little impact on groundwater flooding due to the marginal impact on ebb tide outflow volumes. Overall, this study highlights the vulnerability of lowland karst systems to future changing climate conditions mainly due to the extremely fast recharge which can occur in such systems. The study presents a novel and highly effective methodology for quantifying the potential impact of climate change in lowland karst systems by coupling karst hydrogeological models with the output from high resolution climate simulations.

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Dynamics of water fluxes and storages in an Alpine karst catchment under current and potential future climate conditions

Hydrology and Earth System Sciences ◽

10.5194/hess-22-3807-2018 ◽

2018 ◽

Vol 22 (7) ◽

pp. 3807-3823 ◽

Cited By ~ 13

Author(s):

Zhao Chen ◽

Andreas Hartmann ◽

Thorsten Wagener ◽

Nico Goldscheider

Keyword(s):

Climate Change ◽

Karst Aquifer ◽

Future Climate ◽

Water Fluxes ◽

Aquifer Recharge ◽

Climate Conditions ◽

Changing Climate ◽

Snow Storage ◽

Highly Sensitive ◽

Karst Systems

Abstract. Karst aquifers are difficult to manage due to their unique hydrogeological characteristics. Future climate projections suggest a strong change in temperature and precipitation regimes in European karst regions over the next decades. Alpine karst systems can be especially vulnerable under changing hydro-meteorological conditions since snowmelt in mountainous environments is an important controlling process for aquifer recharge and is highly sensitive to varying climatic conditions. Our paper presents the first study to investigate potential impacts of climate change on mountainous karst systems by using a combined lumped and distributed modeling approach with consideration of subsurface karst drainage structures. The study site is characterized by high-permeability (karstified) limestone formations and low-permeability (non-karst) sedimentary Flysch. The model simulation under current conditions demonstrates that a large proportion of precipitation infiltrates into the karst aquifer as autogenic recharge. Moreover, the result shows that surface snow storage is dominant from November to April, while subsurface water storage in the karst aquifer dominates from May to October. The climate scenario runs demonstrate that varied climate conditions significantly affect the spatiotemporal distribution of water fluxes and storages: (1) the total catchment discharge decreases under all evaluated future climate conditions. (2) The spatiotemporal discharge pattern is strongly controlled by temperature variations, which can shift the seasonal snowmelt pattern, with snow storage in the cold season (December to April) decreasing significantly under all change scenarios. (3) Increased karst aquifer recharge in winter and spring, and decreased recharge in summer and autumn, partly offset each other. (4) Impacts on the karst springs are distinct; the lowest permanent spring presents a “robust” discharge behavior, while the highest overflow outlet is highly sensitive to changing climate. This analysis effectively demonstrates that the impacts on subsurface flow dynamics are regulated by the characteristic dual flow and spatially heterogeneous distributed drainage structure of the karst aquifer. Overall, our study highlights the fast groundwater dynamics in mountainous karst catchments, which make them highly vulnerable to future changing climate conditions. Additionally, this work presents a novel holistic modeling approach, which can be transferred to similar karst systems for studying the impact of climate change on local karst water resources with consideration of their individual hydrogeological complexity and hydraulic heterogeneity.

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An analysis of the risk of cocoa moniliasis occurrence in Brazil as the result of climate change

Summa Phytopathologica ◽

10.1590/s0100-54052012000100005 ◽

2012 ◽

Vol 38 (1) ◽

pp. 30-35 ◽

Cited By ~ 5

Author(s):

Wanderson Bucker Moraes ◽

Waldir Cintra de Jesus Júnior ◽

Leonardo de Azevedo Peixoto ◽

Willian Bucker Moraes ◽

Edson Luiz Furtado ◽

...

Keyword(s):

Climate Change ◽

Potential Risk ◽

Climate Models ◽

Global Climate ◽

Global Climate Models ◽

Future Scenarios ◽

Intergovernmental Panel ◽

Climate Conditions ◽

Third Assessment Report ◽

Impacts Of Climate Change

The aim of this study was to evaluate the potential risk of moniliasis occurrence and the impacts of climate change on this disease in the coming decades, should this pathogen be introduced in Brazil. To this end, climate favorability maps were devised for the occurrence of moniliasis, both for the present and future time. The future scenarios (A2 and B2) focused on the decades of 2020, 2050 and 2080. These scenarios were obtained from six global climate models (GCMs) made available by the third assessment report of Intergovernmental Panel on Climate Change (IPCC). Currently, there are large areas with favorable climate conditions for moniliasis in Brazil, especially in regions at high risk of introduction of that pathogen. Considering the global warming scenarios provided by the IPCC, the potential risk of moniliasis occurrence in Brazil will be reduced. This decrease is predicted for both future scenarios, but will occur more sharply in scenario A2. However, there will still be areas with favorable climate conditions for the development of the disease, particularly in Brazil's main producing regions. Moreover, pathogen and host alike may undergo alterations due to climate change, which will affect the extent of their impacts on this pathosystem.

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Modelling Climate Change’s Impact on the Hydrology of Natura 2000 Wetland Habitats in the Vistula and Odra River Basins in Poland

Water ◽

10.3390/w11102191 ◽

2019 ◽

Vol 11 (10) ◽

pp. 2191 ◽

Cited By ~ 2

Author(s):

Joanna O’Keeffe ◽

Paweł Marcinkowski ◽

Marta Utratna ◽

Mikołaj Piniewski ◽

Ignacy Kardel ◽

...

Keyword(s):

Climate Change ◽

Surface Water ◽

Soil Water ◽

Climate Models ◽

Assessment Tool ◽

Conservation Status ◽

Natura 2000 ◽

River Basins ◽

Overbank Flow ◽

Wetland Habitats

Climate change is expected to affect the water cycle through changes in precipitation, river streamflow, and soil moisture dynamics, and therefore, present a threat to groundwater and surface water-fed wetland habitats and their biodiversity. This article examines the past trends and future impacts of climate change on riparian, water-dependent habitats within the special areas of conservation (SAC) of the Natura 2000 network located within Odra and Vistula River basins in Poland. Hydrological modelling using the Soil and Water Assessment Tool (SWAT) was driven by a set of nine EURO-CORDEX regional climate models under two greenhouse gas concentration trajectories. Changes in the duration of flooding and inundation events were used to assess climate change’s impact on surface water-fed wetland habitats. The groundwater-fed wetlands were evaluated on the basis of changes in soil water content. Information about the current conservation status, threats, and pressures that affect the habitats suggest that the wetlands might dry out. Increased precipitation projected for the future causing increased water supply to both surface water and groundwater-fed wetlands would lead to beneficial outcomes for habitats with good, average, or reduced conservation status. However, habitats with an excellent conservation status that are already in optimum condition could be negatively affected by climate change as increased soil water or duration of overbank flow would exceed their tolerance.

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Dynamics of water fluxes and storages in an Alpine karst catchment under current and potential future climate conditions

10.5194/hess-2017-216 ◽

2017 ◽

Cited By ~ 1

Author(s):

Zhao Chen ◽

Andreas Hartmann ◽

Thorsten Wagener ◽

Nico Goldscheider

Keyword(s):

Climate Change ◽

Karst Aquifer ◽

Future Climate ◽

Subsurface Water ◽

Water Fluxes ◽

Aquifer Recharge ◽

Climate Conditions ◽

Snow Storage ◽

Highly Sensitive ◽

Karst Catchment

Abstract. Climate change projections indicate significant changes to precipitation and temperature regimes in European karst regions. Alpine karst systems can be especially vulnerable under changing hydro-meteorological conditions since snowmelt in mountainous environments is an important controlling process for aquifer recharge, and is highly sensitive to varying climatic conditions. The current study presents an investigation of present and future water fluxes and storages at an Alpine karst catchment using a distributed numerical model. A delta approach combined with random sampling was used to assess the potential impacts of climate changes. The study site is characterized by high permeability (karstified) limestone formations and low permeability (non-karst) sedimentary flysch. The model simulation under current conditions demonstrates that a large proportion of precipitation infiltrates into the karst aquifer as autogenic recharge. Surface runoff in the adjacent non-karst areas partly infiltrates into the karst aquifer as allogenic point recharge. Moreover, the result shows that surface snow storage is dominant from November to April, while subsurface water storage in the karst aquifer dominates from May to October. The climate scenario runs demonstrate that varied climate conditions significantly affect the spatiotemporal distribution of water fluxes and storages: (1) the total catchment discharge decreases under all evaluated future climate conditions. (2) The spatiotemporal discharge pattern is strongly controlled by temperature variations, which can shift the seasonal snowmelt pattern, with snow storage in the cold season (December to April) decreasing significantly under all change scenarios. (3) Increased karst aquifer recharge in winter and spring, and decreased recharge in summer and autumn, partly offset each other. (4) Impacts on the karst springs are distinct; the permanent spring presents a robust discharge behavior, while the estavelle is highly sensitive to changing climate. This analysis effectively demonstrates that the impacts on subsurface flow dynamics are regulated by the characteristic dual flow and spatially heterogeneous distributed drainage structure of the karst aquifer. Overall, our study suggests that bespoke hydrological models tailored to the specific subsurface characteristics of an Alpine karst catchment are needed to understand climate change impact.

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High resolution climate change projections for the Pyrenees region

Advances in Science and Research ◽

10.5194/asr-17-191-2020 ◽

2020 ◽

Vol 17 ◽

pp. 191-208

Author(s):

María P. Amblar-Francés ◽

Petra Ramos-Calzado ◽

Jorge Sanchis-Lladó ◽

Alfonso Hernanz-Lázaro ◽

María C. Peral-García ◽

...

Keyword(s):

Climate Change ◽

High Resolution ◽

21St Century ◽

Statistical Downscaling ◽

Climate Models ◽

Dynamical Downscaling ◽

Climate Projections ◽

Climate Change Projections ◽

Climate Conditions ◽

The Impact

Abstract. The Pyrenees, located in the transition zone of Atlantic and Mediterranean climates, constitute a paradigmatic example of mountains undergoing rapid changes in environmental conditions, with potential impact on the availability of water resources, mainly for downstream populations. High-resolution probabilistic climate change projections for precipitation and temperature are a crucial element for stakeholders to make well-informed decisions on adaptation to new climate conditions. In this line, we have generated high–resolution climate projections for 21st century by applying two statistical downscaling methods (regression for max and min temperatures, and analogue for precipitation) over the Pyrenees region in the frame of the CLIMPY project over a new high-resolution (5 km × 5 km) observational grid using 24 climate models from CMIP5. The application of statistical downscaling to such a high resolution observational grid instead of station data partially circumvent the problems associated to the non-uniform distribution of observational in situ data. This new high resolution projections database based on statistical algorithms complements the widely used EUROCORDEX data based on dynamical downscaling and allows to identify features that are dependent on the particular downscaling method. In our analysis, we not only focus on maximum and minimum temperatures and precipitation changes but also on changes in some relevant extreme indexes, being 1986–2005 the reference period. Although climate models predict a general increase in temperature extremes for the end of the 21st century, the exact spatial distribution of changes in temperature and much more in precipitation remains uncertain as they are strongly model dependent. Besides, for precipitation, the uncertainty associated to models can mask – depending on the zones- the signal of change. However, the large number of downscaled models and the high resolution of the used grid allow us to provide differential information at least at massif level. The impact of the RCP becomes significant for the second half of the 21st century, with changes – differentiated by massifs – of extreme temperatures and analysed associated extreme indexes for RCP8.5 at the end of the century.

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Surface Water Temperature Predictions at a Mid-Latitude Reservoir under Long-Term Climate Change Impacts Using a Deep Neural Network Coupled with a Transfer Learning Approach

Water ◽

10.3390/w13081109 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1109

Author(s):

Nobuaki Kimura ◽

Kei Ishida ◽

Daichi Baba

Keyword(s):

Climate Change ◽

Surface Water ◽

Water Temperature ◽

Transfer Learning ◽

Air Temperature ◽

Climate Models ◽

Temporal Variations ◽

Training Data ◽

Surface Water Temperature

Long-term climate change may strongly affect the aquatic environment in mid-latitude water resources. In particular, it can be demonstrated that temporal variations in surface water temperature in a reservoir have strong responses to air temperature. We adopted deep neural networks (DNNs) to understand the long-term relationships between air temperature and surface water temperature, because DNNs can easily deal with nonlinear data, including uncertainties, that are obtained in complicated climate and aquatic systems. In general, DNNs cannot appropriately predict unexperienced data (i.e., out-of-range training data), such as future water temperature. To improve this limitation, our idea is to introduce a transfer learning (TL) approach. The observed data were used to train a DNN-based model. Continuous data (i.e., air temperature) ranging over 150 years to pre-training to climate change, which were obtained from climate models and include a downscaling model, were used to predict past and future surface water temperatures in the reservoir. The results showed that the DNN-based model with the TL approach was able to approximately predict based on the difference between past and future air temperatures. The model suggested that the occurrences in the highest water temperature increased, and the occurrences in the lowest water temperature decreased in the future predictions.

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Revealing the impacts of climate change on mountainous catchments through high-resolution modelling

Journal of Hydrology ◽

10.1016/j.jhydrol.2021.126806 ◽

2021 ◽

pp. 126806

Author(s):

Jorge Sebastián Moraga ◽

Nadav Peleg ◽

Simone Fatichi ◽

Peter Molnar ◽

Paolo Burlando

Keyword(s):

Climate Change ◽

High Resolution ◽

Mountainous Catchments ◽

Impacts Of Climate Change

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Evaluation of uncertainties in mean and extreme precipitation under climate change for northwestern Mediterranean watersheds from high-resolution Med and Euro-CORDEX ensembles

Hydrology and Earth System Sciences ◽

10.5194/hess-22-673-2018 ◽

2018 ◽

Vol 22 (1) ◽

pp. 673-687 ◽

Cited By ~ 10

Author(s):

Antoine Colmet-Daage ◽

Emilia Sanchez-Gomez ◽

Sophie Ricci ◽

Cécile Llovel ◽

Valérie Borrell Estupina ◽

...

Keyword(s):

Climate Change ◽

High Resolution ◽

Extreme Precipitation ◽

Climate Models ◽

Regional Climate ◽

Regional Climate Models ◽

Historical Period ◽

Mountainous Regions ◽

Extreme Precipitation Events ◽

Precipitation Events

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981–2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.

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A High-Resolution Modeling Strategy to Assess Impacts of Climate Change for Mesoamerica and the Caribbean

American Journal of Climate Change ◽

10.4236/ajcc.2016.52019 ◽

2016 ◽

Vol 05 (02) ◽

pp. 202-228 ◽

Cited By ~ 4

Author(s):

Robert Oglesby ◽

Clinton Rowe ◽

Alfred Grunwaldt ◽

Ines Ferreira ◽

Franklyn Ruiz ◽

...

Keyword(s):

Climate Change ◽

High Resolution ◽

The Caribbean ◽

Modeling Strategy ◽

Impacts Of Climate Change

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Meteorological, soil moisture, surface water, and groundwater data from the St Denis National Wildlife Area, Saskatchewan, Canada

10.5194/essd-2018-125 ◽

2018 ◽

Cited By ~ 1

Author(s):

Edward K. P. Bam ◽

Rosa Brannen ◽

Sujata Budhathoki ◽

Andrew M. Ireson ◽

Chris Spence ◽

...

Keyword(s):

Climate Change ◽

Soil Moisture ◽

Surface Water ◽

Climate Models ◽

Multiple Scales ◽

Full Range ◽

Research Network ◽

Groundwater Levels ◽

Groundwater Availability ◽

Surface Water And Groundwater

Abstract. Long-term meteorological, soil moisture, surface water, and groundwater data provide information on past climate change, most notably information that can be used to analyze past changes in precipitation and groundwater availability in a region. These data are also valuable to test, calibrate and validate hydrological and climate models. CCRN (Changing Cold Regions Network) is a collaborative research network that brought together a team of over 40 experts from 8 universities and 4 federal government agencies in Canada for 5 years (2013–18) through the Climate Change and Atmospheric Research (CCAR) Initiative of the Natural Sciences and Engineering Research Council of Canada (NSERC). The working group aimed to integrate existing and new data with improved predictive and observational tools to understand, diagnose and predict interactions amongst the cryospheric, ecological, hydrological, and climatic components of the changing Earth system at multiple scales, with a geographic focus on the rapidly changing cold interior of Western Canada. The St Denis National Wildlife Area database contains data for the prairie research site, St Denis National Wildlife Research Area, and includes atmosphere, soil, and groundwater. The meteorological measurements are observed every 5 seconds, and half-hourly averages (or totals) are logged. Soil moisture data comprise volumetric water content, soil temperature, electrical conductivity and matric potential for probes installed at depths of 5 cm, 20 cm, 50 cm, 100 cm, 200 cm and 300 cm in all soil profiles. Additional data on snow surveys, pond and groundwater levels, and water isotope isotopes collected on an intermittent basis between 1968 and 2018 are also presented including information on the dates and ground elevations (datum) used to construct hydraulic heads. The metadata table provides location information, information about the full range of measurements carried out on each parameter and GPS locations that are relevant to the interpretation of the records, as well as citations for both publications and archived data. The compiled data are available at https://doi.org/10.20383/101.0115.

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