Search Results (28)

With rapid socio-economic development, excessive anthropogenic consumption and the exploitation of natural resources have impaired the self-healing, supply, and carrying capacities of ecosystems. The assessment and prediction of ecosystem service values (ESVs) are crucial for the coordinated development of ecology and economy. This research examines the Xiangjiang River Basin and combines land use data from 1995 to 2020, Landsat images, meteorological data, and socio-economic data. These data are incorporated into the PLUS model to simulate land use patterns in 2035 under the following five scenarios: natural development, economic development, farmland protection, ecological protection, and coordinated development. Additionally, this research analyzes the dynamics of land use and changes in ESVs in the Xiangjiang River Basin. The results show that between 1995 and 2020 in the Xiangjiang River Basin, urbanization accelerated, human activities intensified, and the construction land area expanded significantly, while the areas of forest, farmland, and grassland decreased continuously. Based on multi-scenario simulations, the ESV showed the largest and smallest declines under economic development and ecological protection scenarios, respectively. This results from the economic development scenario inducing a rapid expansion in construction land. In contrast, construction land expansion was restricted under the ecological protection scenario, because the ecological functions of forests and water bodies were prioritized. This research proposes land use strategies to coordinate ecological protection and economic development to provide a basis for sustainable development in the Xiangjiang River Basin and constructing a national ecological security barrier, as well as offer Chinese experience and local cases for global ecological environment governance. Full article

Sulfate as a potential pollution source in the water environment of the basin, identifying sulfate sources and migration mechanisms is essential for protecting the water environment and ensuring sustainable water management. Liuyang River is a primary tributary of the Xiangjiang River. It has experienced progressively intensifying anthropogenic influences in recent decades, manifested by sustained sulfate concentration increases. However, the sulfate sources and their contributions were not clear. This study used hydrochemistry and multi-isotopes methods combined with Simmr model to study the hydrochemical characteristics, sulfate sources, and migration–transformation processes of surface water and groundwater. The results showed that the hydrochemical types of surface water were HCO₃-Ca and HCO₃·SO₄-Ca·Mg, and groundwater were HCO₃-Ca, HCO₃-Ca·Mg, and HCO₃·SO₄-Ca. Ions in the water primarily originated from carbonate and silicate rocks dissolution and sulfide oxidation, augmented by mining operations, sewage discharge, and chemical production. The analyses of hydrochemistry, isotopes, and Simmr model revealed that surface water sulfate originated from soil sulfate (35.70%), sulfide oxidation (26.56%), sewage (16.58%), and atmospheric precipitation (12.45%). Groundwater sulfate was derived predominantly from sewage (34.96%), followed by soil sulfate (28.09%), atmospheric precipitation (17.35%), and sulfide oxidation (12.25%). Sulfate migration and transformation were controlled by the natural environment and anthropogenic impacts. When unaffected by human activities, sulfate mainly originated from soil and atmospheric precipitation, relating to topography, geological conditions, agricultural activities, and precipitation intensity. However, in regions with intense human activities, contributions from sewage and sulfide oxidation significantly increased due to the influences of mining and industrial activities. Full article

An important historical and cultural region in southern China, the Xiangjiang River Basin, has formed a unique spatial pattern and regional cultural characteristics in its long-term development. In recent years, the acceleration of urbanization has led to the historical texture and cultural elements of Changsha’s suburban blocks facing deconstruction pressure. How to identify and protect their cultural value at the spatial structure level has become an urgent issue. Taking three typical traditional township blocks in the suburbs of Changsha as the research object, this paper constructs a trinity research framework of “spatial gene identification–diversity analysis–strategy optimization.” It systematically discusses the makeup of the types, quantity, distribution, relative importance ranking, and diversity characteristics of their spatial genes. The results show that (1) the distribution and quantity of spatial genes are affected by multiple driving forces such as historical function, geographic environment, and settlement evolution mechanisms, and that architectural spatial genes have significant advantages in type richness and importance indicators; (2) spatial gene diversity shows the structural characteristics of “enriched artificial space and sparse natural space,” and different blocks show clear differences in node space and boundary space; (3) spatial genetic diversity not only reflects the complexity of the spatial evolution of a block but is also directly related to its cultural inheritance and the feasibility of renewal strategies. Based on this, this paper proposes strategies such as building a spatial gene database, improving the diversity evaluation system, and implementing differentiated protection mechanisms. These strategies provide theoretical support and methods for the protection and sustainable development of cultural heritage in traditional blocks. Full article

Bias correction of global climate model (GCM) simulations is usually required for hydrological impact studies due to the coarse resolution and systematic biases of these simulations. Commonly used bias correction methods are applied at sites independently while ignoring the spatial correlation of variables, which may cause unreasonable hydrological simulation. To solve this problem, a stochastic multisite bias correction (SMBC) method is proposed for hydrological impact studies. It first uses the Daily Bias Correction (DBC) method to correct the distribution of variables, and then the distribution-free shuffle algorithm and Markov chain are used to generate spatial correlation of variables. The performance of this method is compared with the DBC method for hydro-meteorological impact studies in the Xiangjiang River Basin. The results show that the DBC method inherits the bias of the temporal sequence of precipitation and spatial correlation of GCM simulated variables. The mean absolute error (MAE) of the spatial correlation is between 0.25 and 0.38 and between 0.36 and 0.39 for the simulated precipitation occurrence and daily precipitation amount, respectively, while the MAE for the probability of two stations having wet days/dry days simultaneously is around 0.07. The SMBC method effectively reproduces spatial correlation of observations, with the MAE of the above indexes around 0.02. In hydrological simulation, the SMBC method has much better performance in reproducing the return period of the maximum consecutive day for streamflow and the maximum consecutive day’s streamflow. The averaged streamflow process is also well represented. Overall, the SMBC method efficiently reproduces the distribution and spatial correlation of variables, thereby generating more accurate hydrology simulations. Full article

The spatial morphology of traditional villages stems from prolonged interactions between socio-economic conditions and the regional natural environment under specific historical contexts. Over time, these settlements have acquired distinct spatial patterns through continuous adaptation to their surrounding ecosystems. Nevertheless, accelerated urbanization now exerts dual pressures—disrupting the spatial order and degrading natural ecosystems. In this context, an integrated analysis of the relationship between village spatial patterns and ecological conditions is essential for elucidating their formative mechanisms. The Xiangjiang River Basin is Hunan’s cultural core, and the spatial distribution of traditional villages is directly related to environmental variables. This study uses bivariate spatial autocorrelation and geographically weighted regression to investigate the relationship between the spatial distribution of traditional villages and ecological environmental appropriateness. The findings indicate the following: (1) The spatial distribution density of traditional villages in the Xiangjiang River Basin exhibits a negative correlation with the Ecological Environment Index (EEI), as evidenced by a Moran’s I value of −0.228. This suggests that traditional villages tend to be less concentrated in areas with a higher ecological suitability. (2) Among natural factors, the Relief Degree of Land Surface (RDLS), the Temperature Humidity Index (THI), and the Land Cover Index (LCI) display positive correlations with village density, with regression coefficients of 0.865, 0.003, and 11.599, respectively. In contrast, the Water Resource Index (WRI) shows a negative correlation, with a coefficient of −6.448, and (3) the impact of ecological suitability factors on village distribution is spatially heterogeneous: microtopographic variation is the primary driver in flat terrains, whereas the ecological carrying capacity exerts a greater influence in mountainous areas. These findings clarify the role of ecological suitability in shaping the spatial characteristics of traditional villages and provide a scientific basis for developing protection strategies that integrate ecological sustainability with cultural–heritage preservation. Full article

The management of and reduction in ammonia nitrogen (NH₃-N) and total phosphorus (TP) in the water environment are crucial for protecting water quality amid rapid urbanization and population growth in highly industrialized regions. Specifically, in the Xiangjiang River Basin, the development of the Chang–Zhu–Tan urban agglomeration resulted in the deterioration of river water quality in the past, where ammonia nitrogen (NH₃-N) and total phosphorus (TP) were the dominant pollutants. This study aims to assess the influence of anthropogenic and climatic factors on the dynamics of nitrogen and phosphorus in an urbanized river basin in the middle Xiangjiang River Basin, China, from 2016 to 2020. This study examines NH₃-N and TP trends and their influencing factors across six tributaries, as well as how their concentrations have changed in response to urbanization and wastewater treatment management. The results reveal that average NH₃-N and TP concentrations decreased from 2016 to 2020 in the urbanized river system. NH₃-N and TP concentrations exhibited positive correlations with the proportion of cropland and negative correlations with population number, percentages of urban lands, and forests. In contrast, the influence of precipitation and streamflow on NH₃-N and TP concentrations was relatively weak. Consequently, agricultural activity was the primary contributing factor to NH₃-N and TP concentrations. Our study also suggests that the government’s newly implemented water protection regulations can effectively control pollutant levels in urbanized river basins. Full article

Clarifying the relationship between human activities and the provision of ecosystem services has received significant interest in recent years because of a growing need for sustainable socio-ecological system development. Using multi-source remote sensing data, we assessed the spatial and temporal distribution of the human footprint index and five ecosystem services under four human activity gradients from 2010 to 2020 in the Xiangjiang River Basin. The five ecosystem services include water supply, soil conservation, food production, habitat quality, and carbon sequestration. The relationship between human footprint and ecosystem services was analyzed from quantitative and spatial perspectives. The results showed that over the past 10 years, water supply and habitat quality decreased by 4.59% and 16.49%, respectively. The other three services increased, and the upstream area of the basin had a higher level of ecosystem services provision. The human footprint index increased by 28.83% over the 10 years and was characterized by point and patchy clustering in the middle and lower reaches. In terms of quantitative characteristics, the relationship between human footprint and ecosystem services was primarily negative. The ecosystem services were sensitive to the human footprint index within the 0−0.4 range. In terms of spatial characteristics, the relationship was dominated by trade-offs. The risky “high–low” trade-offs were mainly distributed in the middle and lower reaches. As the gradients of human activity increased, the maximum fluctuation in ESs was 43%, and the maximum fluctuation in human footprint was 28%, making their relationship more complex. Our results identified response thresholds of ecosystem services to human activities, providing a guide for ecological management and sustainable development of basins. Full article

This study provides an evidential reasoning method for water quality evaluation based on Gaussian distribution to handle the problem of comprehensive water quality evaluation for a region across a period (multiple sections and multiple time points). The method turns the collection of observed water quality indicator values into a probability distribution of water quality grades by using the Gaussian distribution to compute the confidence assessment of water quality grades over one period. It eliminates the subjectivity involved in determining confidence levels and the problem of information loss during data fusion that arises with conventional approaches. The probability distribution of each assessment grade is then determined by repeatedly synthesizing evidence of the same water quality grade using the improved evidential reasoning synthesis rule. To avoid the subjectivity included in experience-based weight settings, principal component analysis (PCA) is utilized to calculate the weights of water quality indicators based on contribution rates and load coefficients. In the end, utility theory is presented to modify the discrete probability distribution of precise numerical expressions, offering thorough results for the evaluation of water quality and facilitating the comparison of various water quality grades. Using the Xiangjiang River Basin as a case study, the proposed evaluation method is contrasted with popular techniques for assessing water quality, including the Single-Factor Evaluation Method, the Fuzzy Comprehensive Evaluation Method, and the Evidential Reasoning Comprehensive Evaluation Method. The findings suggest that the evidence reasoning approach for evaluating water quality that is based on Gaussian distribution is more rational, accurate, and scientific. Additionally, empirical studies on the annual water quality trends in various regions, the upstream, midstream, and downstream trends, and the water quality trends during wet and dry periods are conducted using this method to assess and analyze changes in water quality in the Xiangjiang River Basin during the “11th Five-Year Plan” and “12th Five-Year Plan” periods. The analysis findings demonstrate that, even if the rate of progress has slowed, the Xiangjiang River Basin’s overall water quality has been steadily improving since management and protection measures were put in place. This shows that the preventive and control efforts implemented in the “11th Five-Year Plan” and “12th Five-Year Plan” periods were successful; nevertheless, carrying out the current tactics might only have a limited impact. As a result, more advanced and creative approaches are required to encourage the ongoing enhancement of the water quality in the Xiangjiang River Basin. Full article

To improve the water resources carrying capacity of the Xiangjiang River Basin and achieve sustainable development, this article evaluates and predicts the Xiangjiang River Basin’s water resources carrying capacity level based on county-level units. This article takes 44 county-level units in the Xiangjiang River Basin as the evaluation target, selects TOPSIS and the entropy weight method to determine weights, calculates the water resources carrying capacity level of the evaluation sample, uses a BP neural network model to calculate the predicted water resources carrying capacity level for the next 5 years, and adds the GIS method for spatiotemporal analysis.(1) The water resources carrying capacity of the Xiangjiang River Basin has remained relatively stable for a long period, with overloaded areas being the majority. (2) There are relatively significant spatial differences in the carrying capacity of water resources: Zixing City, located upstream of the tributary, is far ahead due to its possession of the Dongjiang Reservoir; the water resources carrying capacity in the middle and lower reaches (northern region) is generally higher than that in the upper reaches (southern region). (3) According to the BP neural network model prediction, the water resources carrying capacity of the Xiangjiang River Basin will maintain a stable development trend in 2022, while areas such as Changsha and Zixing City will be in a critical state, and other counties and cities will be in an overloaded state.This study has important references value for the evaluation and early warning work of the Xiangjiang River Basin and related research, providing a scientific and systematic evaluation method and providing strong support for water resource management and planning in Hunan Province and other regions. Full article

Clearing and successfully characterizing ecosystem service flow paths has become a key bottleneck restricting in-depth research on the supply and demand relationships of ecosystem services. At present, although some explorations have been performed using water ecosystem services as a pioneer, the nature of its network and the fact that ecological base flow needs to be eliminated have been ignored. This study used InVEST and network models to consider ecological base flow, quantifying the supply, demand, and flow paths of freshwater ecosystem services in the Xiangjiang River Basin. The results showed that the overall distribution of the water supply in the Xiangjiang River Basin from 2000 to 2020 shows a pattern of higher supply in the south and lower supply in the north. The distribution of water demand shows higher levels in the north and lower levels in the south. The network density remains at its maximum level. The results of this study have provided a scientific basis for water resource management in river basins and improving ecological compensation mechanisms. Full article

Exploring the spatiotemporal distribution and interrelationships among water-related ecosystem services (WESs) and conducting ecological management zoning are crucial for regional sustainable development. Taking the Xiangjiang River Basin (XJRB) as an example, this study first quantified three primary WESs, including water conservation, soil retention, and water purification, from 2000 to 2020. Second, the spatiotemporal variation in the interrelationships among WESs were analyzed using global and local bivariate spatial autocorrelation. Third, a water ecological zoning rule was constructed to divide the watershed into three primary and eight secondary water ecological management zones. The results indicate a strong consistency in the changes in the three WESs throughout the period from 2000 to 2020 in the XJRB. Precipitation patterns and urban expansion were the primary factors affecting alterations in the WESs. Spatial heterogeneity and dependence were evident across these ecosystem services. Both trade-offs and synergies were observed among WESs, with synergies playing a dominant role. Positive synergies occurred primarily in woodlands and grasslands, while negative synergies were observed in cultivated land, water areas, and construction land. Three water ecological management zones, including core water ecological management zones, general management zones, and restoration management zones, were delineated at the grid and country scales according to the aggregation properties of the WESs. Ecological management strategies were proposed for different zones. These findings can offer valuable insights for policy makers in land use planning and water ecological management within the XJRB, and can facilitate similar management endeavors in other regions. Full article

The research focuses on the difficult problem of quantifying the adaptation state of river network system development under rapid urbanization. Based on the river network system data and remote sensing image data of the past 30 years, this study discusses the evolution of the river network system and its adaptability. The geographically and temporally weighted regression (GTWR) model was used to reveal the response of the river network system in the Xiangjiang River Basin to urbanization. The results suggest that the Xiangjiang River Basin has experienced a significant increase in urban land due to the strong disturbance by human activities in the last 25 years. The number indicators of river network system such as overall water surface rate and river network density have decreased by 10.04% and 13.99%, respectively. Drainage structure indicators such as tributary development coefficient and structural stability decreased by 6.89% and 4.40%, respectively. The influence of three-dimensional urbanization on the intensity of river network density change is spatiotemporal heterogeneity during 1995–2020. It shows that population factors have a significant negative impact on the upstream area. The regression coefficient between river network density and per capita GDP in the basin is positive. The regression coefficient of urban land is negative, indicating that urban expansion has a significant negative effect on river network density in Xiangjiang River basin. The analysis of the relationship between urbanization and river network system evolution by using the coordination degree model shows that: in the early stage, the level of urbanization is low, the adjustment capacity and carrying capacity of river network are strong, and the coordination degree of urbanization and river network system is small. The level of urbanization has reached a new height, especially in the upstream central cities such as Chang-Zhu-Tan from 2015 to 2020. At this time, the increase of coordination degree is characterized by the mutual promotion of urbanization and river network development, and the improvement of their adaptive development requirements. This study quantitatively reveals the changing characteristics and influencing factors of the adaptability of river network systems and urban spatial development, which can provide scientific support for regional human–water harmony, flood prevention and mitigation, and green urbanization development. Full article

The collaborative governance of subsystems within a river basin can play a critical role in addressing challenges, such as water scarcity, soil erosion, flooding, sedimentation, and water pollution, to achieve sustainable utilization of water resources. However, the current literature only focuses on isolated observations of these subsystems, leading to uncertainty and water resource destruction. This paper examines the evolution of the collaborative governance of water resources, water conservancy facilities, and socio-economic systems through self-organization theory in the Xiangjiang River Basin, China. The coupling theory and gray Grey Model (1,1) model were utilized with panel data from 2000 to 2019 to assess and predict the governance synergies of five subsystems: natural water, water conservancy facilities, water resource development and utilization, ecological environment, and socio-economic systems. There are 22 indicators contributing to these subsystems that were selected. The results indicate an S-shaped trend in collaborative governance for water resources, water conservancy facilities, and socio-economic systems. The elements of each subsystem exhibit both synergistic and competitive relationships. The unpredictable precipitation triggers a butterfly effect, changing systemic governance coordination, which closely relates to developing the natural water subsystem. Effective water conservation and regulation of water conservancy facilities are the keys to improving water-use efficiency and safeguarding water ecology. This study provides insights into the collaborative governance among subsystems and the evolution of the water resources, water conservancy facilities, and socio-economic systems in the Xiangjiang River Basin to promote sustainable water resource utilization. Full article

Human disturbance and climatic factors alter the hydrological state of rivers in many ways and have a degree of negative impact on the quality of watershed habitats; quantifying the impact of both human disturbance and climatic factors on hydrological change can help improve the quality of watershed habitats. Therefore, in this research, an integrated watershed assessment framework is proposed to analyse the watershed from four perspectives: hydrological situation, environmental flows, drivers, and habitat quality. A meteorological streamflow model based on the Long Short-Term Memory (LSTM) model was employed to analyse the hydrological evolution and quantify the influence of the drivers from the perspective of hydrological and environmental flows. The Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model was then used to evaluate the spatial and temporal evolution of habitat quality in the basin. And, finally, the grey correlation theory was used to reveal the response of habitat quality to hydrological changes. Studies have shown that annual flow and precipitation are increasing in the Xiangjiang River (XJR) basin, while its annual potential evapotranspiration is decreasing significantly. After 1991, the hydrological conditions of the XJR were highly variable, with the combined rate of change of the most Ecologically Relevant Hydrological Indicators, ERHIs-IHA and ERHIs-EFCs, reaching 26.21% and 121.23%, respectively. Climate change and human disturbance are the main drivers of change for both (with contributions of 60% and 71%, respectively). Between 1990 and 2020, the habitat quality in the basin declined over time (from 0.770 to 0.757), with areas of high habitat value located mainly in mountainous areas and habitat degradation being concentrated in urban areas in the middle and lower reaches, gradually evolving towards areas of high habitat value in the periphery. There is a strong correlation between watershed habitat quality and the ERHIs. The results of the study can provide a scientific basis for maintaining regional ecological security and rational allocation of water resources. Full article

Satellite precipitation products (SPPs) have emerged as an important information source of precipitation with high spatio-temporal resolutions, with great potential to improve catchment water resource management and hydrologic modelling, especially in data-sparse regions. As an indirect precipitation measurement, satellite-derived precipitation accuracy is of major concern. There have been numerous evaluation/validation studies worldwide. However, a convincing systematic evaluation/validation of satellite precipitation remains unrealized. In particular, there are still only a limited number of hydrologic evaluations/validations with a long temporal period. Here we present a systematic evaluation of eight popular SPPs (CHIRPS, CMORPH, GPCP, GPM, GSMaP, MSWEP, PERSIANN, and SM2RAIN). The evaluation area used, using daily data from 2007 to 2020, is the Xiangjiang River basin, a mountainous catchment with a humid sub-tropical monsoon climate situated in south China. The evaluation was conducted at various spatial scales (both grid-gauge scale and watershed scale) and temporal scales (annual and seasonal scales). The evaluation paid particular attention to precipitation intensity and especially its impact on hydrologic modelling. In the evaluation of the results, the overall statistical metrics show that GSMaP and MSWEP rank as the two best-performing SPPs, with KGE_Grid ≥ 0.48 and KGE_Watershed ≥ 0.67, while CHIRPS and SM2RAIN were the two worst-performing SPPs with KGE_Grid ≤ 0.25 and KGE_Watershed ≤ 0.42. GSMaP gave the closest agreement with the observations. The GSMaP-driven model also was superior in depicting the rainfall-runoff relationship compared to the hydrologic models driven by other SPPs. This study further demonstrated that satellite remote sensing still has difficulty accurately estimating precipitation over a mountainous region. This study provides helpful information to optimize the generation of algorithms for satellite precipitation products, and valuable guidance for local communities to select suitable alternative precipitation datasets. Full article