Search Results (68)

Zooplankton are ubiquitous in aquatic ecosystems and play crucial roles in material cycling and energy flow. However, the mechanisms governing zooplankton community assembly, particularly habitat-specific differences, remain poorly understood. In this two-year study, we monitored zooplankton communities across reservoir and river habitats within the Chayuan watershed, a representative karst region in southwest China. Our findings revealed significant spatial divergence in water-quality variables (including water temperature, pH, total nitrogen, total phosphorus, permanganate index, dissolved oxygen, chlorophyll-a, and ammonia nitrogen) between habitats. Twenty-nine dominant zooplankton species were identified in reservoir and river communities, with only eight shared between the two habitats. The mechanisms underlying the corresponding zooplankton community structures showed distinct segregation between habitats, with deterministic processes predominating in reservoir communities (explaining 25.1% of the variation) and stochastic processes predominating in river communities (3.4% of the variation explained). Environmental drivers differed substantially between habitats: reservoir communities were primarily influenced by total nitrogen, dissolved oxygen, and chlorophyll-a concentrations, whereas river communities responded predominantly to ammonia nitrogen levels. This study provides novel insights into the divergent mechanisms governing zooplankton community assembly in lentic versus lotic systems within a shared karst watershed, offering theoretical foundations for ecosystem-specific management strategies in fragile karst environments. Future research should focus on key climatic variables (e.g., extreme precipitation) and hydrological dynamics (such as flow velocity and water residence time) to further elucidate the mechanisms behind zooplankton community assembly, providing deeper insights to facilitate effective ecosystem management in karst environments. Full article

Rocky desertification is a significant ecological issue in the karst regions of Southwest China, severely affecting both the environment and local livelihoods. Accurate extraction and prediction of rocky desertification are critical for its prevention and control, playing a crucial role in advancing ecological civilization and sustainable land management. This study focuses on the Pearl River source area in Yunnan, analyzing dynamic changes in rocky desertification over eight periods from 1990 to 2023, using long-term remote sensing data and multi-source reference data. It also predicts the intensity and trends of rocky desertification for the next decade. The results indicate that: (1) Rocky desertification is widespread and severe in the study area; however, its further intensification has been effectively mitigated through long-term governance efforts. By 2023, an area of 14,896.19 km² of rocky desertification has been mitigated to varying extents, accounting for 55.77% of the total watershed area. Trend analysis suggests that, under current management conditions, rocky desertification will continue to decline and improve over time. (2) The overall development of rocky desertification in the basin is showing a positive trend, with deep-level rocky desertification gradually transitioning to shallow-level rocky desertification. In future scenarios, the extent of rocky desertification will continue to decrease. (3) The approach of integrating the Google Earth Engine with traditional remote sensing platforms for extracting rocky desertification information has proven to be both fast and efficient. This method retains high extraction accuracy while alleviating the data burden typically associated with exclusive use of local platforms, thereby enhancing processing efficiency. Full article

Water resources are considered to be of paramount importance to the natural world on a global scale, being critical for the sustenance of ecosystems, the support of life, and the achievement of sustainable development. However, these resources are under threat from climate change, population growth, urbanization and pollution. This necessitates the development of robust and effective assessment methods to ensure their sustainable use. Although assessing the ecological footprint (EF) of urban water systems plays a critical role in advancing sustainable cities and managing water assets, existing research has largely overlooked the application of geospatial visualization techniques in evaluating resource allocation strategies within karst mountain watersheds, an oversight this study aims to correct through innovative methodological integration. This research establishes an evaluation framework for predicting water resource availability in Guizhou through the synergistic application of three methodologies: (1) the water-based ecological accounting framework (WEF), (2) ecosystem service thresholds defined by the water ecological carrying capacity of water resources (WECC) thresholds, and (3) composite sustainability metrics, all correlated with contemporary hydrological utilization profiles. Spatiotemporal patterns were quantified across the province’s nine administrative divisions during the 2013–2022 period through time-series analysis, with subsequent WEF projections for 2023–2027 generated via Long Short-Term Memory (LSTM) temporal forecasting techniques. Full article

Rainfall–runoff models are widely used in water management and flood forecasting. In this study, we present a rainfall–runoff model to forecast hourly flows based on an artificial neural network (ANN). This model was developed and applied to the Iton watershed (northwestern France) to solve the problems of nonlinearity in the rainfall–runoff relationship resulting from karst and complex hydrogeological behaviors. The model design required several steps during which we were able to identify the model parameters and create the database needed to perform the flow rate forecast. This work has resulted in an ANN model able to perform an efficient prediction up to a 48 h time horizon. These results confirm that ANN models can play an important role in forecasting the nonlinear rainfall–runoff relationship encountered in many watersheds. Full article

The watershed of the Peixe River lies in central Minas Gerais state, close to Belo Horizonte city, a densely populated area. The area is located in the geological context of Quadrilátero Ferrífero, one of the most prominent mineral provinces in Brazil. To better recognize surface and groundwater availability, some methodologies have been applied to evaluate the minimal surface flow rates, groundwater recharge, and water reserves. The basin includes three main aquifer systems: Cauê (porous and fissured aquifer), related to iron formations; Gandarela, related to karst-fissured rocks; and Cercadinho, related to metapelite rocks. The Cauê aquifer presented the highest effective porosity and hydraulic conductivity. In contrast, the Cercadinho aquitard shows the lowest hydrodynamic parameters. Data between the years of 2004 and 2024 from 21 pumping tests from wells associated with the three aquifer systems were obtained to estimate the respective recharge rate. The recharge was evaluated by numeric recursive filter and recession-curve displacement methods. The recharge results with the numeric filter method showed underestimated values. Regarding the recession-curve displacement method, the results were more consistent with other studies in the surroundings. The average recharge estimated for the basin represents 24% to 54% of annual pluviometry in the hydrological periods of analysis. The recharge data were accounted for in the reserves calculation, including permanent and renewable reserves. Total permanent reserves were estimated to be 3.16 × 10⁹ m³, including the prior aquifer systems of Cauê, Gandarela, and Cercadinho. The total mean renewable reserves of the basin were calculated to be 4.55 × 10⁷ m³/year in the analyzed period. The high BFImax indexes found in baseflow separation, above 90%, suggest a relevant contribution of the karstic Gandarela aquifer on the watershed surface flow. Although in some years it has been concluded that groundwater exploitation outlines the renewable resources availability, in 2024’s scenario, the granted water volume was lower than the estimated availability and reserves. The best methodologies for coupling surface and groundwater are the Weibull distribution for reference surface flows and the recessive-curve displacement for baseflow separations. This research will be a contribution to water resources management strategies for regions with high population growth and water demand increase. Full article

The Soil and Water Assessment Tool (SWAT) model is extensively used globally for hydrological and water quality assessments but encounters challenges in karst regions due to their complex surface and groundwater hydrological environments. This study aims to refine the delineation of hydrological response units within the SWAT model by combining geomorphological classification and to enhance the model with an epikarst zone hydrological process module, exploring the accuracy improvement of SWAT model simulations in karst regions of Southwest China. Compared with the simulation results of the original SWAT model, we simulated runoff and nutrient concentrations in the Mudong watershed from January 2017 to December 2021 using the improved SWAT model. The simulation results indicated that the modified SWAT model responded more rapidly to precipitation events, particularly in bare karst landform, aligning more closely with the actual hydrological processes in Southwest China’s karst regions. In terms of the predictive accuracy for monthly loads of total nitrogen (TN) and total phosphorus (TP), the coefficient of determination (R²) value of the modified model increased by 10.3% and 9.7%, respectively, and the Nash–Sutcliffe efficiency coefficient (NSE) increased by 11.3% and 9.9%, respectively. The modified SWAT model improves prediction accuracy in karst areas and holds significant practical value for guiding non-point source pollution control in agricultural watersheds. Full article

Non-point source pollution poses a significant threat to global water security, and risk assessment and key source area (CSA) identification are critical for its management. While source–sink landscape models are widely used for non-point source pollution evaluation, their application in karst regions is challenged by ecological fragility, shallow soil layers, and severe soil erosion, limiting their effectiveness in accurately identifying pollution risks and CSAs. This study focuses on the Caohai Lake basin in southwestern China; it integrates the landscape-weighted load index (LWLI) and the universal soil loss equation (USLE) to assess non-point source pollution risks in the basin with the aim of precisely delineating critical source areas (CSAs). Total phosphorus (TP) and total nitrogen (TN) served as key predictors of water quality, and their responses to the LWLI and USLE were analyzed in the karst environment. The results revealed the following: (1) source landscapes cover 65% of the basin area, with cropland (40%) being the primary contributor to nitrogen pollution; (2) the LWLI and USLE explain 50–67% of the TP and TN variations during the wet season, with a sharp increase in water quality risk when the LWLI exceeds 0.75; and (3) high-risk and very high-risk areas account for 36.3% and 15.3% of the basin, respectively, and are concentrated in the northwest and south, where intensive agriculture and severe soil erosion dominate. These findings provide a scientific basis for non-point source pollution control in the Caohai Lake basin. Full article

The hydrological processes in karst watersheds are influenced by various factors, including climate characteristics, underlying surface properties, and human activities. Existing watershed hydrological models primarily rely on theoretical concepts or empirical function relationships for simulation, resulting in insufficient accuracy in hydrological process analysis for study areas with limited data. The structure of artificial neural networks is similar to the hydrological process structure in karst watersheds. Based on the hydrological characteristics of the Lijiang River, a BP neural network model is configured with structural parameters set to 13-9-1. Using hydrological data from the Lijiang River from 1995 to 2020 as the foundational dataset, the network is trained and tested for prediction accuracy. The results show that the coefficient of determination for the monthly runoff model in the Lijiang River basin, based on the BP neural network, is 0.942. This suggests that it is feasible to use historical data to predict future flow changes in the Lijiang River basin, assuming that the changes are due exclusively to precipitation and evapotranspiration, but no significant changes occur in the land uses. The findings hold significant importance for water resource management in typical karst watersheds. Full article

Water scarcity is a global issue, especially in semi-arid and arid regions where precipitation is irregularly distributed over time and space. Predicting groundwater flow in heterogeneous karst terrains, which are essential water sources, presents a significant challenge. This article integrates geology, hydrology, and water monitoring to develop a pioneering conceptual and numerical model of groundwater flow in the Montes Claros Region (Vieira River Watershed, Brazil). This model was evaluated under various climate change scenarios, considering changes in rainfall, groundwater consumption, and population growth over the current century. The results indicate that a decline in water table levels is inevitable, primarily driven by population growth and high pumping rates rather than rainfall fluctuations. This underscores the urgent need for improved monitoring, model upgrading, and more importantly, targeted water resource management for Montes Claros. Full article

The hydrochemical characteristics of watersheds are influenced by many factors, with chemical weathering and human activities exerting the most substantial influence. Performing a quantitative evaluation of the factors contributing to the chemical weathering of rocks is of significant scientific importance. This research zeroes in on the Qingtang River basin to elaborate on the hydrochemical characteristic, explore the origins of ions, and quantify the influence of anthropogenic discharges amidst cation interferences, thus improving the accuracy of chemical weathering rate estimations. The samples encompassed surface water, groundwater, and water from dripping in karst caves. The findings indicate that human-induced alterations significantly influence hydrogeochemical dynamics, although chemical weathering of rocks in their natural state is the controlling factor. The mean contributions of cations from atmospheric deposition, human inputs, carbonate weathering, and silicate weathering were 17.56%, 21.05%, 51.77%, and 9.54%, respectively. The chemical weathering rate for carbonate rocks was 62.4 t·km⁻²·a⁻¹, which increased by 27.87% due to the influence of exogenous acids. The anthropogenic impact is predominantly evident in two aspects: (1) the alteration of hydrochemical processes within the watershed through direct input of ions, and (2) the acceleration of rock weathering rates in the watershed due to the exogenous acids. Full article

This study aimed to enhance flood forecasting accuracy in the Liangfeng River basin, a small karst watershed in Southern China, by incorporating the Available Reservoir Capacity of Karst (ARCK) into the HEC-HMS model. This region is often threatened by floods during the rainy season, so an accurate flood forecast can help decision-makers better manage rivers. As a crucial influencing factor on karstic runoff, ARCK is often overlooked in hydrological models. The seasonal and volatile nature of ARCK makes the direct computation of its specific values challenging. In this study, a virtual reservoir for each sub-basin (total of 17) was introduced into the model to simulate the storage and release of ARCK-induced runoff phenomena. Simulations via the enhanced model for rainfall events with significant fluctuations in water levels during 2021–2022 revealed that the Nash–Sutcliffe efficiency coefficient (NSE) of the average simulation accuracy was improved by more than 34%. Normally, rainfalls (even heavy precipitations) during the dry season either do not generate runoff or cause negligible fluctuations in flow rates due to long intervals. Conversely, relatively frequent rainfall events (even light ones) during the wet season result in substantial runoff. Based on this observation, three distinct types of karstic reservoirs with different retaining/releasing capacities were defined, reflecting variations in both the frequency and volume of runoff during both seasons. As a real-time environmental variable, ARCK exhibits higher and lower values during the dry and rainy seasons, respectively, and we can better avoid the risk of flooding according to its special effects. Full article

Comprehending the impacts of land-use type on soil nutrition and stoichiometry in watersheds is crucial for effective regional ecosystem management. However, a deeper understanding of the influence of land-use type on soil stoichiometry in karst agricultural watersheds is still lacking. Here, we analyzed the contents, stoichiometries, and drivers of topsoil C, N, and P in a karst agricultural watershed in China, focusing on six land-use types: paddy fields, dry farmland, tussock land, shrubland, shrubby tussock land, and woodland. We found that woodland exhibited significantly higher soil organic carbon (SOC) content than other land-use types except shrubland. Moreover, woodland exhibited the highest total nitrogen (TN) and total phosphorus (TP) contents compared with other land-use types. C/N and N/P ratios did not vary significantly with land-use type, whereas dry farmland (18.68) showed a significantly lower C/P ratio than woodland (39), shrubland (39.92), and paddy fields (34.87). In addition, our results revealed that soil pH, catalase and invertase activity, and bacterial and actinomycetes abundance significantly influenced C, N, and P content and stoichiometry. These findings reveal that interactions between multiple biotic and abiotic factors drive variability in soil stoichiometry, offering valuable insight for land improvement and ecological management in karst agricultural watersheds. Full article

Hill fires have the potential to influence dissolved organic matter (DOM) in water bodies, yet fewer studies have investigated the effects of hill fires on DOM within watersheds in karst areas. In this study, we employed the three-dimensional fluorescence-parallel factor analysis (EEM-PARAFAC) method to analyze the DOM fluorescence peaks, component compositions, fluorescence indices, and sources within the water body of the Yuanteng River sub-basin, which was impacted by the hill fire, serving as our primary research focus. The results indicate the presence of three primary fluorescent fractions in the water body of the Yuanteng River: C1, resembling humic acid (fulvic acid); C2, consisting of biopolymers and microbial by-products; and C3, containing proteins such as tyrosine and tryptophan. The Yuanteng River exhibited elevated levels of humus-like substances, diminished concentrations of protein-like substances, and demonstrated higher biogenic, freshness, and humification indices compared to unaffected water samples, reflecting the impact of the hill fire. Elevated levels of exogenous humic acid-like inputs into the waters of the Yuanteng River, along with exogenous inputs of DOM, were primarily influenced by stable, high-molecular-weight organic matter. Additionally, agricultural effluent, domestic sewage, and anthropogenic activities contributed to these inputs to a lesser degree. The impacts of endogenous inputs are mainly related to the restoration of ecosystems. The occurrence of hill fires has significantly influenced the composition of dissolved organic matter in the waters of the Yuanteng River. A comprehensive analysis of the impacts of hill fires on dissolved organic matter in water bodies can serve as a valuable reference for characterizing DOM in the water bodies of the Yuanteng River. Furthermore, it can inform strategies for environmental protection, facilitate the traceability of pollutants in water bodies, and contribute to environmental and ecological restoration efforts following hill fires in the region. Full article

Due to the dual influence of climate change and human activities, the water cycle patterns in the lakesheds of the Yunnan karst plateau are undergoing significant changes, leading to increasingly prominent ecological issues. In the history of Lake Yangzong, an artificial water-diversion channel was excavated, altering the lake basin structure. Human activities have intensified, posing severe challenges to water resource supply and water security in recent decades. To investigate the significant increase in human activities, the temporal and phase changes, and the resulting transformation of the water and carbon cycles in the Lake Yangzong basin, we applied X-ray fluorescence spectroscopy (XRF) to scan elements continuously in a 10.2 m sediment core from this lake. By combining correlation analysis, principal component analysis (PCA), core chronology, and total organic carbon (TOC) content, we reconstructed the historical sequence of geochemical element contents in the Lake Yangzong catchment over the past 13,000 years. The results show that PC1 and PC2 contribute 78.4% and 10.3%, respectively, suggesting that erosion intensity is the main factor influencing the lake sedimentation process. From 13,400 to 680 cal a BP (calibrated years before the present), the sedimentation process in Lake Yangzong was mainly controlled by climatic conditions, with vegetation degradation during cold periods and relatively high erosion intensity in the watershed. During the Yuan dynasty, a province was established by the central government in Yunnan, promoting settlement and attracting a large number of immigrants from other provinces to Yunnan. Human activities in the Lake Yangzong basin began to intensify, surpassing natural changes and becoming the dominant force influencing the sedimentation process. In the Ming and Qing dynasties, the population and cultivated land area in Yunnan further increased, resulting in the significant exacerbation of erosion and soil loss in the watershed due to vegetation destruction. In the year 1388, the Tangchi Canal was excavated, transforming Lake Yangzong to an outflow lake, causing Ca²⁺ to be lost through the Tangchi Canal and preventing the formation of precipitation due to oversaturation. The research results indicate that human activities in the Lake Yangzong area have intensified since the Yuan dynasty, leading to increased erosion intensity. The excavation of the outflow canal transformed Lake Yangzong from an inland lake basin into an outflow state, simultaneously generating a significant transformation in the water and carbon cycling patterns in the watershed. Full article

In this study, the hydrochemistry-runoff method and remote sensing estimation method were used to calculate the karst carbon sink flux (KCSF) and the forest vegetation carbon sequestration flux (FVCSF) in Darongjiang (DRJ) and Lingqu (LQ) watersheds. The results show the following: (1) The KCSF in DRJ and LQ watersheds is 238.43 × 10⁵ t·y⁻¹ and 353.44 × 10⁵ t·y⁻¹, respectively. Influenced by changes in flow rate, the two watersheds both show that their KCSF is higher in the rainy season than in the dry season. (2) The FVCSF in DRJ and LQ watersheds was 680.78 × 10⁷ t·y⁻¹ and 229.63 × 10⁷ t·y⁻¹, respectively. Through comparison, it can be seen that the FVCSF is much higher than the KCSF in both watersheds, but the FVCSF and the KCSF are at the same order of magnitude. (3) Through further analysis of the influence factors on the FVCSF and the KCSF, we found that the highest values of FVCSF are mainly distributed around Kitten Mountain on the upper reach and along the LQ watershed. That may be because most of the upper reach areas are mountainous forestland, and the strong weathering of rocks in the LQ watershed promotes the development of forest vegetation carbon sequestration. Therefore, it can be inferred that there is a certain synergistic effect between the karst carbon sink (KCS) and the forest vegetation carbon sequestration (FVCS) in the study area, and such a synergistic effect is caused by rock weathering. Full article