Global karst springs hydrograph dataset for research and management of the world’s fastest-flowing groundwater

Abstract

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...

Trogloregions: delimiting subterranean faunistic identities in Afrotropics and Neotropics

“…In addition to the water in ltration being quite accentuated in these landscapes due to its high porosity, subsurface ows may differ from the surface runoff patterns due to the arrangement of aquifers, which may or may not be con ned within the geological barriers 57 . On the other hand, on a regional scale, information about surface drainage is still essential, as it may show zones of allogeneic recharge of subterranean aquifers, where the water ow may come from other non-karstic reliefs 58 . In this sense, our analyses showed that some groups of caves in adjacent basins were grouped according to the similarity of their fauna.…”

Assessing streamflow sensitivity to precipitation variability in karst-influenced catchments with unclosed water balance

“…We have daily forcing data (precipitation and temperature), stream discharge observations from public observation databases, local meteorological and hydrological services, and publications (table 2 and table S4), and spring discharge observations from the World Karst Spring hydrograph database (WoKaS, Olarinoye et al, 2020). All discharge observations are available at daily resolution except for the Spanish This is a non-peer-reviewed manuscript, which has been submitted to Water Resources Research for peer-review.…”

“…Here, we detected karst-influenced catchments using a catchment attribute database (Beck et al, 2019), a karst aquifer map (Chen et al, 2017), and a lithological map (Hartmann & Moosdorf, 2012). Since our approach includes karst spring discharge information to represent the karstic part of a catchment, the karst spring discharge database (Olarinoye et al, 2020) provided additional information on karst spring hydrographs.…”

Assessing Streamflow Sensitivity to Precipitation Variability in Karst‐Influenced Catchments With Unclosed Water Balances

“…Recent achievements in karst research include the creation of a karst spring discharge database to promote data availability for karstic regions (Olarinoye et al., 2020), relating soil moisture networks to karst groundwater storage and flow (Berthelin et al., 2020), using tracer experiments to detect fast and slow pathways and the connectivity of conduit systems (Lüthi, 2019; Morales et al., 2007; Perrin & Luetscher, 2008), investigating contaminant transport and vulnerability of karst systems (Butscher et al., 2011; Mudarra et al., 2019; Pinault et al., 2001), and modeling recharge and discharge time‐series (Gunkel et al., 2015; Jourde et al., 2014; Reimann et al., 2011; Smiatek et al., 2012). The majority of these studies investigates systems at aquifer scales and therefore focuses on groundwater discharge of the karst springs.…”