Testing a Conceptual Lumped Model in Karst Area, Southwest China

Karst aquifers are known for their heterogeneous physical properties and irregular complex flow patterns which make it a challenge to describe the hydrological behavior and to quantitatively define the distribution of river flow components using hydrologic models. In this paper, a conceptual lumped hydrologic model, Xin’anjiang model (XAJ), was applied in Sancha River, which is a karst basin in southwest China, for the simulation of streamflow. The performance of XAJ model was evaluated based on the model’s ability to reproduce the streamflow and baseflow. Percentage of bias (PBIAS), Nash-Sutcliffe efficiency (NSE), coefficient of determination (R2), and standard deviation (RSR) were calculated between the simulated and measured flow for both calibration and validation period. The low PBIAS and RSR (2.7% and 0.367 for calibration period, 1.3% and 0.376 for validation period) and the high NSE and R2 (0.866 and 0.866 for calibration period, 0.858 and 0.860 for validation period) indicate that the model structure and parameters are of reasonable validity. Furthermore, streamflow was separated to baseflow and surface flow using the “baseflow programme,” and the calculated results indicate that the model could also reproduce the response of baseflow in such karst system

Improving the representation of hydrological connectivity in conceptual models

Understanding hydrological connectivity is one of the main objectives in hydrological research. Hydrological models have been proved to be an efficient tool for a better understanding of hydrological connectivity. Conceptual models have shown certain advantages compared to physically-based distributed models in terms of data requirement and computational time. However, the hydrological connectivity in conceptual models is usually not well represented. In this study, the Soil and Water Assessment Tool (SWAT) was selected for further improvements to have a better representation and simulation of hydrological connectivity. SWAT is a semi-distributed hydrological model used to simulate the effect of land use management practices on water, sediment, and nutrient yields at a basin scale. SWAT has been tested and applied worldwide. However, the non-spatial characteristic of the hydrologic response unit (HRU) concept used in SWAT has been identified as one of the main disadvantages for modeling hydrological connectivity. In this study, the hydrologic routing subroutine of SWAT was examined and the groundwater subroutine was modified to account for hydrological connectivity in porous and karst-dominated aquifers. Results show that the current hydrologic routing subroutines of SWAT are not able to simulate hydrological connectivity between river segments in the river network. The Muskingum routing method in SWAT could (1) cause unphysical oscillations in the simulated streamflow and (2) overestimate the evapotranspiration loss in the river and results in a hydrologic disconnectivity during low flow periods. For improving the representation of hydrological connectivity in the subsurface porous aquifer, the multicell aquifer model was proposed and incorporated into SWAT. The modified model, the so-called SWAT-MCA model, was validated in two basins located in Niedersachsen, Germany. The results show that the SWAT-MCA model could well simulate the regional groundwater flow and return flow from aquifer to stream. For improving the representation of hydrological connectivity in the karst-dominated aquifer due to interbasin groundwater flow (IGF) was added to SWAT, the SWAT_IGF was developed. The developed model was applied in a karst area located in the Southwest Harz Mountains, Germany. The model was validated with the observed streamflow and spring flow. Results show that the SWAT_IGF could well represent the hydrological connection due to interbasin groundwater flow in karst areas. The modified models, SWAT-MCA and SWAT_IGF could be applied for other regions to regional groundwater flow in porous aquifer and IGF in karst-dominated aquifers

Storage dynamics, hydrological connectivity and flux ages in a karst catchment : Conceptual modelling using stable isotopes

This research was supported by The UK-China Critical Zone Observatory (CZO) Programme (41571130071), the National Natural Scientific Foundation of China (41571020, 41601013), the National 973 Program of China (2015CB452701), the National Key Research and development Program of China (2016YFC0502602), the Fundamental Research Funds for the Central Universities (2016B04814) and the UK Natural Environment Research Council (NE/N007468/1). In addition, we thank Sylvain Kuppel, the two anonymous reviewers, Thom Bogaard and the editor for their constructive comments which significantly improved the manuscript. The isotope data as well as rainfall and flow measurements used for this paper can be shared after the ending of our project (2019) according to the project executive policy. Anyone who would like to use the data can contact the corresponding author after signing the agreement. The data were obtained through a purchasing agreement for this study. GIS data in this study are available.Peer reviewedPublisher PD

Storage dynamics, hydrological connectivity and flux ages in a karst catchment: conceptual modelling using stable isotopes

We developed a new tracer-aided hydrological model that disaggregates cockpit karst terrain into the two dominant landscape units of hillslopes and depressions (with fast and slow flow systems). The new model was calibrated by using high temporal resolution hydrometric and isotope data in the outflow of Chenqi catchment in Guizhou Province of south-western China. The model could track hourly water and isotope fluxes through each landscape unit and estimate the associated storage and water age dynamics. From the model results we inferred that the fast flow reservoir in the depression had the smallest water storage and the slow flow reservoir the largest, with the hillslope intermediate. The estimated mean ages of water draining the hillslope unit, and the fast and slow flow reservoirs during the study period, were 137, 326 and 493 days, respectively. Distinct seasonal variability in hydroclimatic conditions and associated water storage dynamics (captured by the model) were the main drivers of non-stationary hydrological connectivity between the hillslope and depression. During the dry season, slow flow in the depression contributes the largest proportion (78.4&thinsp;%) of flow to the underground stream draining the catchment, resulting in weak hydrological connectivity between the hillslope and depression. During the wet period, with the resulting rapid increase in storage, the hillslope unit contributes the largest proportion (57.5&thinsp;%) of flow to the underground stream due to the strong hydrological connectivity between the hillslope and depression. Meanwhile, the tracer-aided model can be used to identify the sources of uncertainty in the model results. Our analysis showed that the model uncertainty of the hydrological variables in the different units relies on their connectivity with the outlet when the calibration target uses only the outlet information. The model uncertainty was much lower for the newer water from the fast flow system in the depression and flow from the hillslope unit during the wet season and higher for older water from the slow flow system in the depression. This suggests that to constrain model parameters further, increased high-resolution hydrometric and tracer data on the internal dynamics of systems (e.g. groundwater responses during low flow periods) could be used in calibration.</p

Enhanced Runoff Modeling by Incorporating Information from the GR4J Hydrological Model and Multiple Remotely Sensed Precipitation Datasets

Reliable runoff modeling is essential for water resource allocation and management. However, a key uncertainty source is that the true precipitation field is difficult to measure, making reliable runoff modeling still challenging. To account for this uncertainty, this study developed a two-step approach combining ensemble average and cumulative distribution correction (i.e., EC) to incorporate information from the GR4J (modèle du Génie Rural à 4 paramètres Journalier) hydrological model and multiple remotely sensed precipitation datasets. In the EC approach, firstly, the ensemble average is applied to construct transitional fluxes using the reproduced runoff information, which is yielded by applying various remotely sensed precipitation datasets to drive the GR4J model. Subsequently, the cumulative distribution correction is applied to enhance the transitional fluxes to model runoff. In our experiments, the effectiveness of the EC approach was investigated by runoff modeling to incorporate information from the GR4J model and six precipitation datasets in the Pingtang Watershed (PW; Southwest China), and the single precipitation dataset-based approaches and the ensemble average were used as benchmarks. The results show that the EC method performed better than the benchmarks and had a satisfactory performance with Nash–Sutcliffe values of 0.68 during calibration and validation. Meanwhile, the EC method exhibited a more stable performance than the ensemble averaging method under different incorporation scenarios. However, the single precipitation dataset-based approaches tended to underestimate runoff (regression coefficients < 1), and there were similar errors between the calibration and validation stages. To further illustrate the effectiveness of the EC model, five watersheds (including the PW) of different hydrometeorological features were used to test the EC model and its benchmarks. The results show that both the EC model and the ensemble averaging had good transferability, but the EC model had better performance across all the test watersheds. Conversely, the single precipitation dataset-based approaches exhibited significant regional variations and, therefore, had low transferability. The current study concludes that the EC approach can be a robust alternative to model runoff and highlights the value of the incorporation of multiple precipitation datasets in runoff modeling

Coupled hydrological and biogeochemical modelling of nitrogen transport in the karst critical zone

Transport of nitrogen (N) in karst areas is more complex than in non-karst areas due to marked heterogeneity of hydrodynamic behaviour in the karst critical zone. Here, we present a novel, distributed, coupled hydrological-biogeochemical model that can simulate water and nitrogen transport in the critical zone of karst catchments. This new model was calibrated using integrated hydrometric, water stable isotope, and nitrogen-N concentration data at the outflow of Houzhai catchment in Guizhou province of Southwest China. Hydrological dynamics appears to control N load from the study catchment. Combining flow discharge and water stable isotopes significantly constrained model parameterisation and mitigate the equifinality effects of parameters on the simulated results. Karst geomorphology and land use have functional effects on spatiotemporal variations of hydrological processes and nitrogen transport. In the study catchment, agricultural fertilizer was the largest input source of N, accounting for 86% of the total. Plant uptake consumed about 45% of inputs, primarily in the low-lying valley bottom areas and the plain covered by relatively thick soils. Thus, a large amount of N released from soil reservoirs to the epikarst (via fractures or sinkholes) is then exported to the underground channel in the limestone area to the south. This N draining into groundwater could lead to extensive, potentially long-term contamination of the karst system. Therefore, improving the efficiency of fertilization and agricultural management in valleys/depressions is an urgent need to reduce N losses and contamination risk

Spatial Dimensions of Tower Karst and Cockpit Karst: A Case Study of Guilin, China

Tower karst (fenglin) and cockpit karst (fengcong) are two globally important representative styles of tropical karst. Previously proposed sequential and parallel development models are preliminary, and geomorphological studies to date do not provide enough satisfactory evidence to delineate the spatial and temporal relation between the two landscapes. This unclear interpretation of tower-cockpit relationships not only obscures understanding of the process-form dynamics of these tropical karst landforms, but also confuses their definition. Moreover, previous technological limitations, as well as the fragmental nature of the karst landscapes, has limited incorporation of geologic and other data into broad geospatial frameworks based on geographic information science (GIS) and remote sensing (RS), with such data being spatially and temporally disparate. This study incorporates various data sources to address the fenglin-fengcong relationship, particularly the recently postulated edge effect , which has not been examined in detail previously and which may hinge upon the interaction of multiple environmental variables, including geomorphology, vegetation and hydrology. To address these issues, this research combines geographic, geologic and hydrologic data, using GIS and RS technologies to test quantitatively the edge effect hypothesis. Specifically, there are four inter-related objectives of this study. The first is to develop a method to effectively differentiate fenglin and fengcong. The second is to extract optimally the vegetation information from satellite imagery, and investigate the correlation between tropical karst topography and its vegetation. The third is to combine the regional hydrologic data and solute transport models to estimate geochemicals control of fenglin and fengcong. The fourth one, perhaps the most important, is to test the edge effect hypothesis using the results from the other three objectives. There are several significant conclusions. First, DEM data are very useful for extracting profiles of complex surface landforms from satellite imagery. Second, the vegetation distribution varies between tower karst and cockpit karst and the differences correlate with topographic characteristics. The under-representation of vegetation on the south-southwest aspect of tower karst is remarkable, and its overall distribution is both less abundant and dispersed than in cockpit karst. Third, the edge effect exists in the Guilin area, with variable intensity and extension in different dimensions. In summary, the major contributions of the study include the following. First, the study has developed a method to classify fenglin-fengcong tropical karst effectively, even with the presence of shadows that would otherwise hinder traditional classification. Second, the study showed a variance of vegetation vitality within aspects of fenglin that might relate to its geomorphic difference from fengcong. Third, the study combined groundwater and solute transport models to estimate bicarbonate distributions, representing a novel systematic and quantitative approach to tropical karst studies

Characterizing Karst Mountain Watersheds Through Streamflow Response to Snowmelt

The climate in many parts of the Western US is characterized by cold, wet winters preceding long, dry summers. In the absence of precipitation, water supplies in these regions are sustained by melting snow and mountain groundwater. Changes in regional climate can reduce snow accumulation, accelerate melt, and prolong dry periods, all increasing the importance of groundwater on summertime water availability. In mountainous regions with limestone and dolomite geology, bedrock formations can host significant karst aquifers comprising dissolution-enhanced karst conduits which play an outsized and variable role in how precipitation is translated into streamflow. In this study, we considered an intensively monitored watershed in the Bear River Range of Northern Utah with major karst influences to evaluate geologic and climate controls on streamflow patterns. We evaluated water quality and discharge time-series along with model simulations of snow accumulation and melt for six tributary subcatchments, four mainstem subcatchments, and two major springs within the 554 km2 study area across wet, moderate, and dry years. Most subcatchments had clear annual streamflow and water quality response associated with melting snow, but the magnitude of these responses varied by a factor of 10 across the study area. Unlike many snowmelt-dominated mountain watersheds, the variability in response between subcatchments could not be well described by climate conditions or topographic characteristics. We use the diverse streamflow responses to propose a conceptual model of three attributes that can be used to characterize and facilitate understanding and water management of karst- influenced mountain watersheds: conduit flow direction, matrix flow direction, and degree of karstification