Revealing the positive influence of young water fractions derived from stable isotopes on the robustness of karst water resources predictions

Intense Human Activities Induce the Dynamic Changes of Interaction Pattern Between Karst Water‐Quaternary Groundwater in the Basin‐Mountain Coupling Belt Over the Past 60 Years

“…The 87 Sr/ 86 Sr of NIST‐SRM987 throughout the study was 0.7010223 ± 0.000009 (2 σ ). Stable isotopes (δ 18 O and δD) of the groundwater, used as natural tracers to provide valuable information on sources, pathways, and water exchange in groundwater systems (Binder et al., 2019; Çallı et al., 2023; Gao et al., 2010; Rusjan et al., 2019). Therefore, the water stable isotopes were determined using a liquid water isotope analyzer (IWA‐35‐EP) (912‐0026, Los Gatos Research, America) to ensure accuracy better than ±0.1‰ and ±1‰ for δ 18 O and δD, respectively.…”

Karst water resources in a changing world: Review of solute transport modelling approaches

“…Various substances (i.e., solutes, particles, solids, and gasses) and physical quantities (i.e., temperature or heat) can be used for quantifying flow and transport parameters (i.e., porosity, dispersivity, flow velocity) at the spatiotemporal scales of interest (Benischke, 2021;Field, 2020;Massei et al, 2006). Additionally, tracers are frequently utilized as additional information sources to confirm and/or invalidate for karst simulation models (e.g., Hartmann et al, 2014Hartmann et al, , 2017Mudarra et al, 2019;Rusjan et al, 2019;Zhang et al, 2021;Çallı et al, 2023a).…”

“…In groundwater studies, water age is often denoted as residence time which indicates the time between the water entrance and leave (Aquilina et al, 2003;Maloszewski et al, 1992;Małoszewski & Zuber, 1993;Plummer et al, 1998aPlummer et al, , 1998b whereas travel time is defined as the time required for a volume of water moving across the specified flow paths. The knowledge of water age and/or its distributionsdistributions of the different water agesis particularly useful for revealing the vulnerability of karst aquifers to the contamination risks (Malík et al, 2016;Musgrove et al, 2023;Çallı et al, 2023a) as it provides valuable insight into the karst system's underlying mixing, storage, and transport characteristics (i.e., piston flow, complete mixing) (Figure 3). For instance, the karst aquifers characterized by (relatively) younger water age (i.e., shorter travel time) are often at the risk of contamination problem due to the system's rapid response whilst the karst systems represented with older groundwater ages (i.e., longer residence time) is often an indication of the sufficient time for the contaminant attenuation processes (Figure 3).…”

“…Nonetheless, the characterization methods for the data acquisition and/or interpretation techniques in karst aquifers is rather appropriate for the continuum (Darcy) scale applications where the effective parameters can be readily used for the entire model domain (e.g., Faulkner et al, 2009;Huntoon, 1995;Kresic & Stevanovic, 2009;Zhang et al, 2021). For this reason, when the direct measurements of transport parameters (i.e., dispersivity, mass transfer coefficient) are not practical and/or their values might not be representative in resembling the process of interest, model parameters are frequently estimated manuscript submitted to Review of Geophysics via model calibration (e.g., Bittner et al, 2020;Cinkus et al, 2023;Dewaide et al, 2016;Sivelle et al, 2023;Çallı et al, 2023a).…”

“…In a successful model calibration, the measured variables (i.e., solute concentrations for the transport models, discharge and/or groundwater heads for the flow models) are required to reasonably meet the simulated counterparts (Dietrich & Uniyal, 2020;Neven & Sorab, 2021;Oehlmann et al, 2015;Sullivan et al, 2019). Such a model parameterization requires a calibration metric (i.e., objective function, performance criteria or likelihood) to indicate how well and to what degree the transport model represents the system's reality (Hartmann et al, 2018;Gharari et al, 2021;Çallı et al, 2023a).…”