•NS-ES-MDA accurately identifies model parameters with limited uncertainty.•Calibrating tracer parameters or conduit length elevates uncertainty of model parameters.•Identification performance is ...correlated with limit and error of observation.
Transient storage model (TSM) is widely used to describe solute transport processes in karst areas. Accurately identifying model parameters is essential for predicting and mitigating groundwater contamination. This paper employs the normal-score ensemble smoother with multiple data assimilation (NS-ES-MDA) algorithm to automatically identify model parameters (cross-sectional area of main channel A, dispersion coefficient D, cross-sectional area of storage zone As, and exchange coefficient α), while evaluating their uncertainty across four cases: identification of only model parameters (case 1), model parameters alongside tracer parameters (case 2), model parameters with conduit length (case 3), and all three –model parameters, tracer parameters, and conduit length (case 4). We examine the variations in uncertainty of model parameters when tracer parameters and/or conduit length are known or unknown. We further investigate the effects of concentration observation limits and observation error variance on the identification performance. The results demonstrate that the proposed method can successfully identify model parameters, even in cases where tracer parameters and/or conduit length are unknown, although with a certain level of uncertainty. However, the calibration of tracer parameters leads to an increase in uncertainty for A and D, and a slight rise in uncertainty for α. The calibration of conduit length significantly elevates the uncertainties of A and As and causes an increase in uncertainty for D. Compared with tracer parameters, conduit length causes larger uncertainty in A and As. The identification performance significantly deteriorates when the tail of observed breakthrough curve (BTC) is truncated, and reaches its peak at an observation error variance of 1 × 10-4. This implies that it is crucial to monitor the tail in BTC and to assign a reasonable observation error when using this method to identify model parameters. Although these findings are derived from a synthetic karst conduit, they offer valuable insights for identifying model parameters as tracer data and/or conduit length are uncertain in field conditions.
OM-MADE (One-dimensional Model for Multiple Advection, Dispersion, and storage in Exchanging zones) is an open-source python code for simulating one-dimensional solute transport in multiple ...exchanging conduits and storage zones in steady-state flow conditions. It aims at helping the interpretation of multi-peaked skewed breakthrough curves (BTCs) that can be observed in tracer tests conducted in karstic systems. OM-MADE is based on the resolution of classical mass conservation equations. In OM-MADE, all parallel and exchanging flow zones are divided along the direction of flow into reaches, in which all model parameters are kept constant. The total flowrate may be modified through lateral in and outflows. The solute may also be affected by decay processes either in mobile or immobile zones. Each reach is subdivided into discrete segments of equal length. The partial differential equations can be solved using two second order schemes, one based on an operator-split approach, the other on Crank-Nicholson pondered scheme. A verification is performed against analytical solutions, OTIS software (Runkel, 1998), and the Dual-Advection Dispersion Equation (DADE) proposed by Field and Leij (2012). An application to a tracer test carried out in the karstic area of Furfooz (Belgium) is then performed to reproduce the double-peaked positively skewed BTC that has been observed. It constitutes a demonstration of the software capacities in the case of two reaches and three exchanging zones, among which two are mobile ones and one represents a storage zone. It thus permits to verify numerically the consistency of the conceptual interpretation of the observed BTC.
•An open-source python code to simulate one-dimensional solute transport in conduits.•Simulate multiple exchanging flow and storage zones in steady-state flow conditions.•Help the interpretation of multi-peaked breakthrough curves observed in karstic system tracer tests.
Southern China is characterized by widespread karst landforms, which pose a significant threat to the safety of underground construction. This study focuses on the excavation of a metro-station in ...sandy soils, taking into account the existence of underlying karst caves. Three-dimensional nonlinear finite element analysis (FEA) is employed to investigate the excavation-induced impact on the surrounding ground and structures. The FEA models are validated through comparison with field data. A series of studies are conducted to analyze the impact of support structure reinforcement and various distributions of karst on excavation. This study reveals that (1) reinforcement measures significantly reduce ground surface settlement and lateral displacement of diaphragm walls, while also shifting the maximum wall displacement closer to the excavation face; (2) at different depths, karst at
Z
=25 m (rock layer) and
Z
=14 m (soil layer) have the most pronounced impact on ground settlement, with karst at
Z
=25 m also affecting the wall moment significantly; (3) karst formations within the excavation pit and near the diaphragm wall in the rock layer have the most substantial influence on the lateral deformation of diaphragm wall. Notably, karst on the inner side of the diaphragm wall within the rock layer has the greatest influence on wall moment. The research results can provide guidance for further exploring the influence of karst caves distribution on excavation of foundation pit.
•Atmospheric circulation and moisture transportation mainly control precipitation δ18O on seasonal-interannual scale.•The stalagmite δ18O indicating Asian Summer Monsoon variation has similar period ...with eleven-year sunspots cycles.•The Asian Summer Monsoon variation is influenced by tropical sea surface temperature related to solar activity.
The oxygen isotope compositions (δ18O) of stalagmites have been widely used to reconstruct summer monsoon variability, which is primarily controlled by the solar radiation on orbital to seasonal timescales. However, the relationship between solar activity and the monsoon system remains unclear. This study is based on a 13-year, from 2010 to 2022, monitoring campaign of the δ18O values of precipitation, cave drips and modern speleothems in Jiguan Cave, central China. By analyzing moisture circulation and the local meteoric water line (LMWL) under different ENSO (El Niño Southern Oscillation) events, it was found that on seasonal–interannual timescales, the precipitation δ18O values reflect the atmospheric moisture circulation. In addition, we used cross-wavelet transform analysis to investigate the periodic relationship between the sunspot number (SSN) and the Asian Summer Monsoon (ASM) since solar activity is one of the most important external influences on the ASM. The stalagmite δ18O data for our study areas reflect the solar activity-induced decadal-scale variations in the local precipitation. The key factors related to the δ18O value include the driving mechanism of the solar activity and ENSO-related sea surface temperature (SST) anomalies. We speculate that changes in solar activity cause anomalies in the tropical SST gradient, which affects central China's hydrological cycle by changing the variability of ENSO and the Indian Ocean Dipole (IOD) and ultimately causes the variations in stalagmites δ18O records.
Snow dominated mountainous karst watersheds are the primary source of water supply in many areas in the western U.S. and worldwide. These watersheds are typically characterized by complex terrain, ...spatiotemporally varying snow accumulation and melt processes, and duality of flow and storage dynamics because of the juxtaposition of matrix (micropores and small fissures) and karst conduits. As a result, predicting streamflow from meteorological inputs has been challenging due to the inability of physically based or conceptual hydrologic models to represent these unique characteristics. We present a hybrid modeling approach that integrates a physically based, spatially distributed, snow model with a deep learning karst model. More specifically, the high‐resolution snow model captures spatiotemporal variability in snowmelt, and the deep learning model simulates the corresponding response of streamflow as influenced by complex surface and subsurface properties. The deep learning model is based on the Convolutional Long Short‐Term Memory (ConvLSTM) architecture capable of handling spatiotemporal recharge patterns and watershed storage dynamics. The hybrid modeling approach is tested on a watershed in northern Utah with seasonal snow cover and variably karstified carbonate bedrock. The hybrid models were able to simulate streamflow at the watershed outlet with high accuracy. The spatial and temporal recharge and discharge patterns learned by the ConvLSTM model were then examined and compared with known hydrogeologic information. Results suggest that ConvLSTM simulates streamflow with higher accuracy than reference models for the study area and provides insight into spatially influenced hydrologic responses that are unavailable within lumped modeling approaches.
Key Points
Physically based and deep learning models were combined to simulate streamflow in a mountainous karst watershed
This hybrid modeling approach explicitly accounts for spatially distributed snowmelt
Convolutional Long Short‐Term Memory simulates streamflow with high accuracy and provides insight into spatial hydrologic responses
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•Time lapse electrical resistivity tomography (TL-ERT) identifies different ERT-zones.•TL-ERT and drip logger network identify lag times of water infiltration and storage.•Isolated, ...persistent water storages are associated with speleothem occurrence.•TL-ERT is part of state of the art tool kit for cave monitoring.
This study provides the example of Golgotha Cave, in the south west of Western Australia, where previous long-term hydrological, geochemical and climate monitoring resulted in a theoretical hydrological model of the karst critical zone. We test this model by presenting the results of a 1.5 year monitoring program above the cave using time-lapse electric resistivity tomography (TL-ERT). Between May 2016 and January 2018 several lines up to 200 m long were monitored using a 100 multi-electrode Lipmann 4point light instrument. Various Wenner and Dipole-Dipole arrays provided information of electric resistivity changes at certain points of the year. Laboratory studies measuring volumetric water content versus electric resistivity of various rocks and soils resulted in three different ERT-hydrogeological zones. Besides the annual infiltration patterns, TL-ERT also identified previously unknown, permanent water storages as well as several areas acting as fast hydrological flow pathways most likely caused by pipe structures in the aeolianite. Specific aspects of the TL-ERT study could be correlated with the long term drip water monitoring and thus confirmed and extended the hydrogeological model of the area. A resulting conceptual model of the flow pathways derived from ERT surveys and cave water monitoring results is presented to visualise water flux from the surface to the ceiling of Golgotha Cave. This includes annual recharge to 40 m depth in less than one hydrological year, preferential flow paths to a persistent store of water, and a time lag between soil moisture saturation and seasonal connection of karst stores that indicates a narrower window for seasonal recharge than indicated by soil moisture data.
The deeply buried river‐connected Xishan karst aquifer (XKA) in western Beijing, China, has been suffering from diminishing recharge for several decades, which in turn leads to the disappearing of ...spring water outflows and continuously lowering of groundwater level in the area. Thus, it is important to correctly recognize the groundwater recharge and flow paths for the sustainable development of the XKA. To investigate these issues, the hydrochemical and isotopic compositions are analysed for both surface water and groundwater samples collected over an area of about 280 km2. Results show that (a) the river water is characterized by high Na contents; (b) the δ2H and δ18O values in the river water are distinctively higher than those of groundwater samples, after experiencing the long‐time evaporative enrichment in the upstream reservoir; (c) the Sr concentrations and 87Sr/86Sr ratios of groundwater clearly indicated the interaction between water and carbonate minerals but excluded the water–silicate interaction; and (d) the groundwater samples in the direct recharge area of the XKA have the lowest Na concentrations and the δ2H and δ18O values. Based on the large differences in the Na contents and 18O values of groundwater and surface water, a simple two‐component mixing model is developed for the study area and the fractions of the river water are estimated for groundwater samples. We find that the distribution pattern of the river water fractions in the XKA clearly shows a change of directions in the preferential flow path of the groundwater from its source zone to the discharge area. Overall, our results suggest that the recharged surface water can be a useful evidence for delineating the groundwater flow path in river‐connected karst aquifer. This study improves our understanding of the heterogeneity in karst groundwater systems.
Compared to other landforms, karst areas are among those emerging from the dissolution process that have a higher risk of land degradation. The likelihood of karst landforms being harmed is increased ...by urbanization and other human activities like extensive agriculture. Subsurface streams' water quality gets worse when surface pollutants infiltrate through developed karst features like sinkholes and karst ponors. There is a greater risk of land degradation as more karst features, in this case void size, develop. The purpose of this research is to assess how void development, or the degree of karstification, relates to the potential for karst spring pollution in the event that land degradation occurs on the surface of the Karst Drainage System (KDS). This research was conducted at the KDS of Beton and Gremeng Spring in the Gunungsewu karst area, Indonesia. In addition, this study also provides recommendations related to environmental management on the basis of the level of development of voids at both sites. The degree of karstification represents the phase at which a hydrogeological system has been developing, and this information was later considered in formulating strategies for protecting karst groundwater from contamination. The results show that Beton and Gremeng had a complex discharge regime with degrees of karstification at 8 and 5.5, respectively. Based on flood hydrograph components, it was further confirmed that both areas were in the mature phase. The higher the degree of karstification, the higher the vulnerability to pollution.
Challenged by rapidly changing climate in combination with an increase in anthropogenic pressures, karst groundwater resources in the Old Town of Lijiang (OTLJ), SW China, are diminishing. Higher ...frequency and longer duration of dried-up periods have been observed at the Heilongtan Park (HP) Springs in recent years. Thus, there is an urgent need for an artificial recharge scheme, aimed at replenishing groundwater in the aquifer and increasing the outflow of the springs to ensure effective water resources management. Evaluation of the scheme feasibility, prior to its implementation, is important. In this study, tracer tests were conducted between the recharge area and receiving springs in order to gain insight into the transport mechanisms of karst groundwater and the structural characteristics of the aquifer. Multiple underground flow paths, exhibiting high conductivity between the recharge area and HP Springs, were revealed by the interpretation of tracer breakthrough curves. Three springs considered as the leakages of the scheme were identified. Moreover, the outflow of springs at HP and OTLJ were predicted to be increased by the artificially recharged water after 9.2 and 12.5 days, respectively. Quantitative analysis of tracer recoveries demonstrates that the springs to be recharged and the springs considered as leakages, respectively, share 45 and 55% of the increased outflow. The feasibility of the scheme has been confirmed by the tracer tests. This report provides references for the evaluation of artificial groundwater recharge and protection strategies, particularly in large and poorly investigated karst spring fields.
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