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

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

10.5194/hess-2020-203 ◽

2020 ◽

Author(s):

Patrick Morrissey ◽

Paul Nolan ◽

Ted McCormack ◽

Paul Johnston ◽

Owen Naughton ◽

...

Keyword(s):

Climate Change ◽

Surface Water ◽

High Resolution ◽

Climate Models ◽

Aquifer Recharge ◽

Climate Conditions ◽

Karst Catchment ◽

Karst Systems ◽

Wetland Habitats ◽

Impacts Of Climate Change

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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Bias correction of extreme values of high resolution climate simulations for risk analysis.

10.21203/rs.3.rs-264479/v1 ◽

2021 ◽

Author(s):

luis Augusto sanabria ◽

Xuerong Qin ◽

Jin Li ◽

Robert Peter Cechet

Keyword(s):

Climate Change ◽

Bias Correction ◽

Extreme Values ◽

The Body ◽

Future Climate ◽

Return Periods ◽

Climate Conditions ◽

Mitigation And Adaptation ◽

Climate Simulations ◽

The Impact

Abstract Most climatic models show that climate change affects natural perils' frequency and severity. Quantifying the impact of future climate conditions on natural hazard is essential for mitigation and adaptation planning. One crucial factor to consider when using climate simulations projections is the inherent systematic differences (bias) of the modelled data compared with observations. This bias can originate from the modelling process, the techniques used for downscaling of results, and the ensembles' intrinsic variability. Analysis of climate simulations has shown that the biases associated with these data types can be significant. Hence, it is often necessary to correct the bias before the data can be reliably used for further analysis. Natural perils are often associated with extreme climatic conditions. Analysing trends in the tail end of distributions are already complicated because noise is much more prominent than that in the mean climate. The bias of the simulations can introduce significant errors in practical applications. In this paper, we present a methodology for bias correction of climate simulated data. The technique corrects the bias in both the body and the tail of the distribution (extreme values). As an illustration, maps of the 50 and 100-year Return Period of climate simulated Forest Fire Danger Index (FFDI) in Australia are presented and compared against the corresponding observation-based maps. The results show that the algorithm can substantially improve the calculation of simulation-based Return Periods. Forthcoming work will focus on the impact of climate change on these Return Periods considering future climate conditions.

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Potential impacts to freshwater ecosystems caused by flow regime alteration under changing climate conditions in Taiwan

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-5-3005-2008 ◽

2008 ◽

Vol 5 (6) ◽

pp. 3005-3032 ◽

Cited By ~ 1

Author(s):

J.-P. Suen

Keyword(s):

Climate Change ◽

Flow Regime ◽

River Flow ◽

Aquatic Organisms ◽

Freshwater Ecosystems ◽

Climate Conditions ◽

Regime Changes ◽

Changing Climate ◽

Extreme Flood ◽

Precautionary Measures

Abstract. Observed increases in the Earth's surface temperature bring with them associated changes in precipitation and atmospheric moisture that consequentially alter river flow regimes. This paper uses the Indicators of Hydrologic Alteration approach to examine climate-induced flow regime changes that can potentially affect freshwater ecosystems. Analyses of the annual extreme water conditions at 23 gauging stations throughout Taiwan reveal large alterations in recent years; extreme flood and drought events were more frequent in the period after 1991 than from 1961–1990, and the frequency and duration of the flood and drought events also show high fluctuation. Climate change forecasts suggest that such flow regime alterations are going to continue into the foreseeable future. Aquatic organisms not only feel the effects of anthropogenic damage to river systems, but they also face on-going threats of thermal and flow regime alterations associated with climate change. This paper calls attention to the issue, so that water resources managers can take precautionary measures that reduce the cumulative effects from anthropogenic influence and changing climate conditions.

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Evaluating catchment response to artificial rainfall from four weather generators for present and future climate

Water Science & Technology ◽

10.2166/wst.2018.217 ◽

2018 ◽

Vol 77 (11) ◽

pp. 2578-2588 ◽

Cited By ~ 3

Author(s):

Hjalte Jomo Danielsen Sørup ◽

Steffen Davidsen ◽

Roland Löwe ◽

Søren Liedtke Thorndahl ◽

Morten Borup ◽

...

Keyword(s):

Climate Change ◽

Future Climate ◽

Control Measures ◽

Rainfall Time Series ◽

Urban Water ◽

Combined Sewer Overflows ◽

Climate Conditions ◽

Artificial Rainfall ◽

Weather Generators ◽

Catchment Responses

Abstract The technical lifetime of urban water infrastructure has a duration where climate change has to be considered when alterations to the system are planned. Also, models for urban water management are reaching a very high complexity level with, for example, decentralized stormwater control measures being included. These systems have to be evaluated under as close-to-real conditions as possible. Long term statistics (LTS) modelling with observational data is the most close-to-real solution for present climate conditions, but for future climate conditions artificial rainfall time series from weather generators (WGs) have to be used. In this study, we ran LTS simulations with four different WG products for both present and future conditions on two different catchments. For the present conditions, all WG products result in realistic catchment responses when it comes to the number of full flowing pipes and the number and volume of combined sewer overflows (CSOs). For future conditions, the differences in the WGs representation of the expectations to climate change is evident. Nonetheless, all future results indicate that the catchments will have to handle more events that utilize the full capacity of the drainage systems. Generally, WG products are relevant to use in planning of future changes to sewer systems.

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Trading space for time: Assessment of tree habitat shifts under climate change using bioclimatic envelopes

10.5194/egusphere-egu21-2135 ◽

2021 ◽

Author(s):

Katharina Enigl ◽

Matthias Schlögl ◽

Christoph Matulla

Keyword(s):

Climate Change ◽

Tree Species ◽

Ips Typographus ◽

Future Climate ◽

Forest Damage ◽

Climate Conditions ◽

North East ◽

Bioclimatic Variables ◽

The Future ◽

Forest District

Climate change constitutes a main driver of altering population dynamics of spruce bark beetles (Ips typographus) all over Europe. Their swarming activity as well as development rate are strongly dependent on temperature and the availability of brood trees. Especially over the last years, the latter has substantially increased due to major drought events which led to a widespread weakening of spruce stands. Since both higher temperatures and longer drought periods are to be expected in Central Europe in the decades ahead, foresters face the challenges of maintaining sustainable forest management and safeguarding future yields. One approach used to foster decision support in silviculture relies on the identification of possible alternative tree species suitable for adapting to expected future climate conditions in threatened regions.&#160;In this study, we focus on the forest district of Horn, a region in Austria&#8216;s north east that is beneficially influenced by the mesoclimate of the Pannonian basin. This fertile yet dry area has been severely affected by mass propagations of Ips typographus due to extensive droughts since 2017, and consequently has suffered from substantial forest damage in recent years. The urgent need for action was realized and has expedited the search for more robust alternative species to ensure sustainable silviculture in the area.The determination of suitable tree species is based on the identification of regions whose climatic conditions in the recent past are similar to those that are to be expected in the forest district of Horn in the future. To characterize these conditions, we consider 19 bioclimatic variables that are derived from monthly temperature and rainfall values. Using downscaled CMIP6 projections with a spatial resolution of 2.5 minutes, we determine future conditions in Horn throughout the 21st century. By employing 20-year periods from 2021 to 2100 for the scenarios SSP1-26, SSP2-45, SSP3-70 and SSP5-85,&#160; and comparing them to worldwide past climate conditions, we obtain corresponding bioclimatic regions for four future time slices until the end of the century. The Euclidian distance is applied as measure of similarity, effectively yielding similarity maps on a continuous scale. In order to account for the spatial variability within the forest district, this procedure is performed for the colder northwest and the warmer southeast of the area, individually seeking similar bioclimatic regions for each of these two subregions. Results point to Eastern Europe as well as the Po Valley in northern Italy as areas exhibiting the highest similarity to the future climate in this North-Eastern part of Austria.

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Evaluating the Tourist Climate Comfortable Period of China in a Changing Climate

Advances in Meteorology ◽

10.1155/2020/8886316 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Dan-Dan Yu ◽

Shan Li ◽

Zhong-Yang Guo

Keyword(s):

Climate Change ◽

Global Climate ◽

Scientific Evidence ◽

Climatic Conditions ◽

Climate Index ◽

Climate Indices ◽

Climate Data ◽

Climate Conditions ◽

Positive Effects ◽

Changing Climate

The evaluation of climate comfort for tourism can provide information for tourists selecting destinations and tourism operators. Understanding how climate conditions for tourism evolve is increasingly important for strategic tourism planning, particularly in rapidly developing tourism markets like China in a changing climate. Multidimensional climate indices are needed to evaluate climate for tourism, and previous studies in China have used the much criticized “climate index” with low resolution climate data. This study uses the Holiday Climate Index (HCI) and daily data from 775 weather stations to examine interregional differences in the tourist climate comfortable period (TCCP) across China and summarizes the spatiotemporal evolution of TCCP from 1981 to 2010 in a changing climate. Overall, most areas in China have an “excellent” climate for tourism, such that tourists may visit anytime with many choices available. The TCCP in most regions shows an increasing trend, and China benefits more from positive effects of climate change in climatic conditions for tourism, especially in spring and autumn. These results can provide some scientific evidence for understanding human settlement environmental constructions and further contribute in improving local or regional resilience responding to global climate change.

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Simulated Biomass, Climate Change Impacts, and Nitrogen Management to Achieve Switchgrass Biofuel Production at Diverse Sites in U.S.

Agronomy ◽

10.3390/agronomy10040503 ◽

2020 ◽

Vol 10 (4) ◽

pp. 503 ◽

Cited By ~ 3

Author(s):

Sumin Kim ◽

Sojung Kim ◽

Jaepil Cho ◽

Seonggyu Park ◽

Fernando Xavier Jarrín Perez ◽

...

Keyword(s):

Climate Change ◽

Panicum Virgatum ◽

Warm Season ◽

Field Trials ◽

N Fertilization ◽

N Fertilizer ◽

Future Climate ◽

Biofuel Production ◽

Climate Conditions ◽

Functional Relationships

Switchgrass (Panicum virgatum L.) is a C4, warm season, perennial native grass that has been strongly recommended as an ideal biofuel feedstock. Accurate forecasting of switchgrass yield across a geographically diverse region and under future climate conditions is essential for determining realistic future ethanol production from switchgrass. This study compiled a switchgrass database through reviewing the existing literature from field trials across the U.S. Using observed switchgrass data, a process-based model (ALMANAC) was developed. The ALMANAC simulation results showed that crop management had more effect on yield than location. The ALMANAC model consists of functional relationships that provide a better understanding of interactions among plant physiological processes and environmental factors (water, soil, climate, and nutrients) giving realistic predictions in different climate conditions. This model was used to quantify the impacts of climate change on switchgrass yields. Simulated lowland switchgrass would have more yield increases between Illinois and Ohio in future (2021–2050) under both Representative Concentration Pathway (RCP) 4.5 and 8.5 pathways with low N fertilizer inputs than high N fertilizer inputs. There was no significant effect of climate variability on upland simulated yields, which means that N fertilization is a key factor in controlling upland switchgrass yields under future climate conditions.

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A comparison between direct and indirect frameworks to evaluate impacts of climate change on streamflows: case study of Karkheh River basin in Iran

Journal of Water and Climate Change ◽

10.2166/wcc.2017.043 ◽

2017 ◽

Vol 8 (4) ◽

pp. 652-674 ◽

Cited By ~ 6

Author(s):

Mohsen Nasseri ◽

Banafsheh Zahraie ◽

Leila Forouhar

Keyword(s):

Climate Change ◽

River Basin ◽

Hydrological Modeling ◽

Future Climate ◽

Multivariate Adaptive Regression Splines ◽

Group Method ◽

Climate Projections ◽

Climate Conditions ◽

Karkheh River Basin ◽

Impacts Of Climate Change

Abstract In this paper, two approaches to assess the impacts of climate change on streamflows have been used. In the first approach (direct), a statistical downscaling technique was utilized to predict future streamflows based on large-scale data of general circulation models (GCMs). In the second approach (indirect), GCM outputs were downscaled to produce local climate conditions which were then used as inputs to a hydrological simulation model. In this article, some data-mining methods such as model-tree, multivariate adaptive regression splines and group method of data handling were utilized for direct downscaling of streamflows. Projections of HadCM3 model for A2 and B2 SRES scenarios were also used to simulate future climate conditions. These evaluations were done over three sub-basins of Karkheh River basin in southwest Iran. To achieve a comprehensive assessment, a global uncertainty assessment method was used to evaluate the results of the models. The results indicated that despite simplifications included in the direct downscaling, this approach is accurate enough to be used for assessing climate change impacts on streamflows without computational efforts of hydrological modeling. Furthermore, comparing future climate projections, the uncertainty associated with elimination of hydrological modeling is estimated to be high.

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Projecting future vegetation change for northeast China using CMIP6

10.5194/egusphere-egu2020-9639 ◽

2020 ◽

Author(s):

Wei Yuan ◽

Shuang-ye Wu ◽

Shugui Hou

Keyword(s):

Climate Change ◽

Vegetation Change ◽

Management Strategies ◽

Future Climate ◽

Future Climate Change ◽

Vegetation Changes ◽

Emission Scenarios ◽

Climate Data ◽

Climate Conditions ◽

Temperature And Precipitation

This study aims to establish future vegetation changes in the east and central of northern China (ECNC), an ecologically sensitive region in the transition zonal from humid monsoonal to arid continental climate. The region has experienced significant greening in the past several decades. However, few studies exist on how vegetation will change with future climate change, and great uncertainties exist due to complex, and often spatially non-stationary, relationships between vegetation and climate. In this study, we first used historical NDVI and climate data to model this spatially variable relationship with Geographically Weighted Logit Regression. We found that temperature and precipitation could explain, on average, 43% of NDVI variance, and they could be used to&#160;model NDVI fairly well. We then establish future climate change using the output of 11 CMIP6 models for the medium (SSP245) and high (SSP585) emission scenarios for the mid-century (2041-2070) and late-century (2071-2100). The results show that for this region, both temperature and precipitation will increase under both scenarios. By late-century under SSP585, precipitation is projected to increase by 25.12% and temperature is projected to increase 5.87oC in ECNC. Finally, we used future climate conditions as input for the regression models to project future vegetation (indicated by NDVI). We found that NDVI will increase under climate change. By mid-century, the average NDVI in ECNC will increase by 0.024 and 0.021 under SSP245 and SSP585. By late-century, it will increase by 0.016 and 0.006 under SSP245 and SSP585&#160;respectively. Although NDVI is projected to increase, the magnitude of increase is likely to diminish with higher emission scenarios, possibly due to the benefit of precipitation increase being gradually encroached by the detrimental effects of temperature increase. Moreover, despite the overall NDVI increase, the area likely to suffer vegetation degradation will also expands, particularly in the western part of ECNC. With higher emissions and later into the century, region with low NDVI is likely to shift and/or expand north-forward. Our results could provide important information on possible&#160;vegetation changes, which could help to develop effective management strategies to ensure ecological and economic sustainability&#160;in the future.

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