Karst regions offer a variety of natural resources such as freshwater and biodiversity, and many cultural resources. The World Karst Aquifer Map (WOKAM) is the first detailed and complete global geodatabase concerning the distribution of karstifiable rocks (carbonates and evaporites) representing potential karst aquifers. This study presents a statistical evaluation of WOKAM, focusing entirely on karst in carbonate rocks and addressing four main aspects: (1) global occurrence and geographic distribution of karst; (2) karst in various topographic settings and coastal areas; (3) karst in different climatic zones; and (4) populations living on karst. According to the analysis, 15.2% of the global ice-free continental surface is characterized by the presence of karstifiable carbonate rock. The largest percentage is in Europe (21.8%); the largest absolute area occurs in Asia (8.35 million km2). Globally, 31.1% of all surface exposures of carbonate rocks occur in plains, 28.1% in hills and 40.8% in mountains, and 151,400 km or 15.7% of marine coastlines are characterized by carbonate rocks. About 34.2% of all carbonate rocks occur in arid climates, followed by 28.2% in cold and 15.9% in temperate climates, whereas only 13.1 and 8.6% occur in tropical and polar climates, respectively. Globally, 1.18 billion people (16.5% of the global population) live on karst. The highest absolute number occurs in Asia (661.7 million), whereas the highest percentages are in Europe (25.3%) and North America (23.5%). These results demonstrate the global importance of karst and serve as a basis for further research and international water management strategies.

Karst aquifers contribute substantially to freshwater supplies in many regions of the world, but are vulnerable to contamination and difficult to manage because of their unique hydrogeological characteristics. Many karst systems are hydraulically connected over wide areas and require transboundary exploration, protection and management. In order to obtain a better global overview of karst aquifers, to create a basis for sustainable international water-resources management, and to increase the awareness in the public and among decision makers, the World Karst Aquifer Mapping (WOKAM) project was established. The goal is to create a world map and database of karst aquifers, as a further development of earlier maps. This paper presents the basic concepts and the detailed mapping procedure, using France as an example to illustrate the step-by-step workflow, which includes generalization, differentiation of continuous and discontinuous carbonate and evaporite rock areas, and the identification of non-exposed karst aquifers. The map also shows selected caves and karst springs, which are collected in an associated global database. The draft karst aquifer map of Europe shows that 21.6% of the European land surface is characterized by the presence of (continuous or discontinuous) carbonate rocks; about 13.8% of the land surface is carbonate rock outcrop.

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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.

Karst aquifers provide drinking water for 10% of the world's population, support agriculture, groundwater-dependent activities, and ecosystems. These aquifers are characterised by complex groundwater-flow systems, hence, they are extremely vulnerable and protecting them requires an in-depth understanding of the systems. Poor data accessibility has limited advances in karst research and realistic representation of karst processes in large-scale hydrological studies. In this study, we present World Karst Spring hydrograph (WoKaS) database, a community-wide effort to improve data accessibility. WoKaS is the first global karst springs discharge database with over 400 spring observations collected from articles, hydrological databases and researchers. The dataset's coverage compares to the global distribution of carbonate rocks with some bias towards the latitudes of more developed countries. WoKaS database will ensure easy access to a large-sample of good quality datasets suitable for a wide range of applications: comparative studies, trend analysis and model evaluation. This database will largely contribute to research advancement in karst hydrology, supports karst groundwater management, and promotes international and interdisciplinary collaborations. Background & Summary Karst aquifers are essential sources of drinking water to about 10% of the world's population 1. In many regions across the globe, karst groundwater is also an indispensable resource for ecosystems, agriculture and, economic activities, as well as for tourism and recreation 2,3. For example, in Europe, 21.6% of the land surface is underlain by carbonate rock 4 which contributes up to 50% of supplied drinking water in some countries 5-7. However, groundwater flow in karst aquifers is characterised by a complex interplay of fast-flowing conduit and slow-flowing matrix systems 8,9. Hence, the storage capacity of karst aquifers is variable and systems are extremely vulnerable to climatic pressures, human impacts and contamination 10. In order to ensure adequate protection of karst water sources, in-depth hydrogeological knowledge is necessary. Large-scale modelling and comparative water resource research have shown the great value of large datasets in hydrology 11. Numerous studies have applied these large datasets for several purposes such as model evaluation, global parameter estimations, impact studies, statistical and comparative analyses. For instance, large-scale hydrological models such as WaterGAP 12 used discharge data from the Global Runoff Data Centre (https://www. bafg.de/GRDC) for parameter estimation. Likewise, streamflow data from the Model Parameter Estimation Experiment (MOPEX) 13 and the Global Runoff Data Centre (GDRC) were combined to derive global base flow indexes and recession constants 14. Streamflow observations of near-natural catchments obtained from UNESCO's European Water Archive (EWA) were used to investigate the streamflow trends across Europe and differentiated the impacts from climatic variability and anthropogenic dri...

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Abstract. Despite many existing approaches, modeling karst water resources remains challenging as conventional approaches usually heavily rely on distinct system knowledge. Artificial neural networks (ANNs), however, require only little prior knowledge to automatically establish an input–output relationship. For ANN modeling in karst, the temporal and spatial data availability is often an important constraint, as usually no or few climate stations are located within or near karst spring catchments. Hence, spatial coverage is often not satisfactory and can result in substantial uncertainties about the true conditions in the catchment, leading to lower model performance. To overcome these problems, we apply convolutional neural networks (CNNs) to simulate karst spring discharge and to directly learn from spatially distributed climate input data (combined 2D–1D CNNs). We investigate three karst spring catchments in the Alpine and Mediterranean region with different meteorological–hydrological characteristics and hydrodynamic system properties. We compare the proposed approach both to existing modeling studies in these regions and to our own 1D CNN models that are conventionally trained with climate station input data. Our results show that all the models are excellently suited to modeling karst spring discharge (NSE: 0.73–0.87, KGE: 0.63–0.86) and can compete with the simulation results of existing approaches in the respective areas. The 2D models show a better fit than the 1D models in two of three cases and automatically learn to focus on the relevant areas of the input domain. By performing a spatial input sensitivity analysis, we can further show their usefulness in localizing the position of karst catchments.

To protect karst spring water resources, catchments must be known. We have developed a method for correlating spring hydrographs with newly available, high‐resolution, satellite‐based Global Precipitation Measurement data to rapidly and remotely locate recharge areas. We verify the method using a synthetic comparison of ground‐based rain gage data with the satellite precipitation data set. Application to karst springs is proven by correlating satellite data with hydrographs from well‐known springs with published catchments in Europe and North America. Application to an unknown‐catchment spring in Pennsylvania suggests distant recharge, requiring a flow path that crosses topographic divides, as well as multiple lithologies, physiographic provinces, and tectonic boundaries. Although surprising, this latter result is consistent with published geologic/geophysical, monitoring well, and stream gage data. We conclude that the method has considerable potential to improve the speed and accuracy of catchment identification and hydrodynamic characterization, with applications to water resource protection and groundwater exploration, among others.