Land use changes and socio-economic development strongly deteriorate river ecosystem health in one of the largest basins in China

Investigating the impacts of climate change on hydroclimatic extremes in the Tar-Pamlico River basin, North Carolina

Evaluating the forthcoming impacts of climate change is important for formulating efficient and flexible approaches to water resource management. General Circulation Models (GCMs) are primary tools that enable scientists to study both past and potential future climate changes, as well as their impacts on policies and actions. In this work, we quantify the future projected impacts of hydroclimatic extremes on the coastal, risk-prone Tar-Pamlico River basin in North Carolina using GCMs from the Sixth International Coupled Model Intercomparison Project (CMIP6). These models incorporate projected future societal development scenarios (Shared Socioeconomic Pathways, SSPs) as defined in the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6). Specifically, we have utilized historical residential expansion data, the Soil and Water Assessment Tool Plus (SWAT+), the Standardized Precipitation Index (SPI), and the Interquartile Range (IQR) method for analyzing extremes from 2024 to 2100. Our findings include: (1) a trend toward wetter conditions is identified with an increase in flood events toward 2100; (2) projected increases in the severity of flood peaks are found, quantified by a rise of 21% compared to the 2000-2020 period; (3) downstream regions are forecast to experience severe droughts up to 2044; and (4) low-lying and coastal regions are found as particularly susceptible to higher flood peaks and more frequent drought events between 2045 and 2100. This work provides valuable insights into the anticipated shifts in natural disaster patterns and supports decision-makers and authorities in promoting adaptive strategies and sustainable policies to address challenges posed by future climate changes in the Tar-Pamlico region and throughout the state of North Carolina, United States.

Multi-spatial-scale land/use land cover influences on seasonally dominant water quality along Middle Ganga Basin

Studying spatiotemporal water quality characteristics and their correlation with land use/land cover (LULC) patterns is essential for discerning the origins of various pollution sources and for informing strategic land use planning, which, in turn, requires a comprehensive analysis of spatiotemporal water quality data to comprehend how surface water quality evolves across different time and space dimensions. In this study, we compared catchment, riparian, and reach scale models to assess the effect of LULC on WQ. Using various multivariate techniques, a 14-year dataset of 20 WQ variables from 20 monitoring stations (67,200 observations) is studied along the Middle Ganga Basin (MGB). Based on the similarity and dissimilarity of WQPs, the K-means clustering algorithm classified the 20 monitoring stations into four clusters. Seasonally, the three PCs chosen explained 75.69% and 75% of the variance in the data. With PCs > 0.70, the variables EC, pH, Temp, TDS, NO2 + NO3, P-Tot, BOD, COD, and DO have been identified as dominant pollution sources. The applied RDA analysis revealed that LULC has a moderate to strong contribution to WQPs during the wet season but not during the dry season. Furthermore, dense vegetation is critical for keeping water clean, whereas agriculture, barren land, and built-up area degrade WQ. Besides that, the findings suggest that the relationship between WQPs and LULC differs at different scales. The stacked ensemble regression (SER) model is applied to understand the model's predictive power across different clusters and scales. Overall, the results indicate that the riparian scale is more predictive than the watershed and reach scales.

Driving forces of hydrological health and multifractal response of fish habitat in regulated rivers

Climate change and anthropogenic activities are major influences on the hydrological cycle, further altering river hydrological health. However, the characteristics of the forces in driving the variations of hydrological health at long-short time scales (annual, seasonal, monthly), as well as the potential impacts of these variations on aquatic habitats, remain unclear. In this study, the flow threshold method was introduced to identify the inherent characteristics of river hydrological health degree (RHD) evolution in the upper reaches of the Yangtze River (URYR) through the extreme-point symmetric modal decomposition (ESMD) method and range of variation approach (RVA). The RHD under unregulated conditions was reconstructed to quantify the impacts of anthropogenic activities and climate change. Subsequently, a multifractal model was proposed to establish the relationship between RHD and habitat-weighted usage area (WUA) during the spawning period of the Four Famous Major Carps, aiming to analyze the response mechanisms of habitat conditions to RHD fluctuations. The results showed that the RHD in the URYR exhibited degradation characteristics, experiencing a moderate change with a value of 0.44. Climate change was identified as the dominant factor causing the annual-scale decline in RHD, with an average impact weight of 62.9%. At the annual scale, Anthropogenic activities exacerbate (-3.4), counteract (20.1), and counteract (20.5) the adverse climatic impacts at Yichang, Cuntan, and Zhutuo stations, respectively. Additionally, the effect of human activities during the flood season is slight, with the most favorable and unfavorable impacts occurring in December (50.7) at the Zhutuo station and in October (-27.2) at the Yichang station. Under the influence of driving forces, the multifractal correlation of the RHD-WUA system tended to homogenized as the time window increased, indicating the presence of potential nonlinear dependence, asymmetric fractal characteristics, and positive-to-negative persistence transitions. Therefore, modeling river health considering fish habitat cannot be limited to linear paradigms. The findings provide valuable insights for the management and restoration of aquatic ecosystems.

Spatiotemporal distribution characteristics of ecosystem health and the synergetic impact of its driving factors in the Yangtze River Delta, China

In recent years, . the rapid development of the Yangtze River Delta in China has led to increasingly serious regional eco-environmental problems. Therefore, it is of great significance for the construction of ecological civilization to study the ecosystem health in the Yangtze River Delta. In this paper, the assessment framework of "Vigor-Organization-Resilience" was used to assess the ecosystem health index (EHI) of the Yangtze River Delta from 2000 to 2020, and then the spatial autocorrelation method was used to analyze the agglomeration of EHI in 314 counties in this region. Finally, the eXtreme Gradient Boosting (XGBoost) model and the SHapley Additive exPlanation (SHAP) model were combined to explore the synergistic impact of EHI driving factors. The results show that (1) from 2000 to 2020, the EHI in the Yangtze River Delta is at the level of ordinary health, and gradually decreased; (2) the EHI has significant spatial positive correlation and aggregation; (3) the driving factors in descending order of importance are urbanization level (UL), precipitation (PRE), PM2.5 (PM), normalized difference vegetation index (NDVI), and temperature (TEMP); and (4) the relationship between UL and EHI is logarithmic; PRE and EHI are quartic polynomial; PM, NDVI, TEMP, and EHI are quadratic polynomial. The results of this paper are of great significance to the management and restoration of the ecosystem in this region.

Spatial relationship between land urbanization and ecosystem health in the Yangtze River Basin, China

Globally, land-based urbanization had far-reaching impacts on ecosystem health. Determining the spatial relationship between land urbanization and ecosystem health is important for sustainable socioeconomic development and ecological protection. However, existing studies lack research on these relationships in basin regions, which may limit the implementation of effective basin ecological management measures. Based on multi-source data, this study analyzed the spatiotemporal patterns and spatial correlations of land urbanization rate (LUR) and ecosystem health index (EHI) in the Yangtze River basin (YRB) with a series of spatial analysis methods. The results showed that EHI in the YRB decreased by 0.024 during 2000-2020, with a decreasing range of 3.133 %, while LUR increased by 0.216, with an increasing range of 54.135 %. LUR has a significant negative spatial correlation with EHI, with high EHI and high LUR (9.814% in 2020) and high EHI and low LUR (12.397% in 2020) being the main types of agglomeration. The global regression results showed that LUR significantly negatively affected EHI. At the local scale, the LUR positively affected the EHI in the mountainous region, while the opposite was confirmed in the plain region. This study can provide scientific reference for the development of sustainable urban land control measures and basin ecological management measures.

Quantifying the spatial nonstationary response of influencing factors on ecosystem health based on the geographical weighted regression (GWR) model: an example in Inner Mongolia, China, from 1995 to 2020

The identification of ecosystem health and its influencing factors is crucial to the sustainable management of ecosystems and ecosystem restoration. Although numerous studies on ecosystem health have been carried out from different perspectives, few studies have systematically investigated the spatiotemporal heterogeneity between ecosystem health and its influencing factors. Considering this gap, the spatial relationships between ecosystem health and its factors concerning climate, socioeconomic, and natural resource endowment at the county level were estimated based on a geographically weighted regression (GWR) model. The spatiotemporal distribution pattern and driving mechanism of ecosystem health were systematically analysed. The results showed the following: (1) the ecosystem health level in Inner Mongolia spatially increases from northwest to southeast, displaying notable global spatial autocorrelation and local spatial aggregation. (2) The factors influencing ecosystem health exhibit significant spatial heterogeneity. Annual average precipitation (AMP) and biodiversity (BI) are positively correlated with ecosystem health, and annual average temperature (AMT) and land use intensity (LUI) are estimated to be negatively correlated with ecosystem health. (3) Annual average precipitation (AMP) significantly improves ecosystem health, whereas annual average temperature (AMT) significantly worsens eco-health in the eastern and northern regions. LUI negatively impacts ecosystem health in western counties (such as Alxa, Ordos, and Baynnur). This study contributes to extending our understanding of ecosystem health depending on spatial scale and can inform decision-makers about how to control various influencing factors to improve the local ecology under local conditions. Finally, this study also proposes some relevant policy suggestions and provides effective ecosystem preservation and management support in Inner Mongolia.

Regional differences and driving forces of ecosystem health in Yangtze River Basin, China

Ecosystem health in the Yangtze River basin (YRB) shows significant regional differences. Analysis of regional differences and drivers of ecosystem health in YRB is of practical significance for sustainable basin ecological management. However, existing studies lack research on regional differences and driving forces of ecosystem health, especially in big basin regions. Based on multi-source data, this study adopted spatial statistics and distribution dynamics models to quantitatively analyze the regional differences of ecosystem health in the YRB during 2000-2020 and employed the spatial panel model to reveal the driving forces of ecosystem health in the YRB. The ecosystem health index of the upper, middle, and lower reaches of YRB and the entire basin in 2020 was 0.753, 0.781, 0.637, and 0.742, respectively, while they all decreased during 2000-2020. Regional differences in YRB ecosystem health increased during 2000-2020. From the perspective of dynamic evolution, low-level and high-level ecosystem health units evolved to high-level, while medium-high-level ecosystem health units evolved to low-level. High-high (accounting for 30.372% in 2020) and low-low (accounting for 13.533% in 2020) were the main cluster types. Regression result showed that urbanization was the main reason for ecosystem health deterioration. The findings can provide enlightenment to further understand the regional differences of ecosystem health in YRB and provide theoretical reference for the coordinated management of ecosystem at macro-level and the differential regulation of local ecosystem at micro-level in the basin region.

The impact of land use and land cover changes on the landscape pattern and ecosystem service value in Sanjiangyuan region of the Qinghai-Tibet Plateau

Decades of intensifying human activities have caused dramatic changes in land use and land cover (LULC) in the ecologically fragile areas of the Qinghai-Tibet Plateau, which have led to significant changes in ecosystem service value (ESV). Taking the ecologically fragile Sanjiangyuan region of the Qinghai-Tibet Plateau as the research object, we focused on understanding the impact of LULC changes on the Sanjiangyuan's landscape pattern and its corresponding ESV, which was combined with a Markov-Plus model to predict LULC changes in 2030. The results showed: (1) from 2000 to 2020, the LULC of Sanjiangyuan has changed to varying degrees, respectively. In the central and southern regions where animal husbandry is the mainstay activity, the area of grass land converted to bareland had expanded; (2) from 2000 to 2010, the total regional ESV increased sharply. However, the total amount of ESV decreased from 2010 to 2020; (3) the overall ESV in the study area was observed to be trending down and is expected to decrease by approximately 4.25 billion CNY by 2030; (4) the fragmentation and complexity of regional landscape patterns will negatively affect local ecosystem stability and biodiversity. Overall, there is a strong temporal and spatial correlation between LULC and ESV. This study will provide a reference for the local government to provide targeted and sustainable land management policies, thereby promoting the improvement of the Qinghai-Tibet Plateau regional ecology value.

Multifunctional resilience of river health to human service demand in an alluvial quarried reach: a comparison amongst fuzzy logic, entropy, and AHP-based MCDM models

Riverine ecosystem services to human beings are dynamically evaluated by harmonic relationships; however, over growing human service demands (HSDs) are leading to deteriorate the river health resilience. In this study, an assessment index system of river health involving pressure-state-response (PSR) based on twenty indicators of riparian, channel geomorphic, hydroecological, and social attributes was developed to detect the multifunctional reliability and resilience of river system integrity for HSDs at upper (US), middle (MS), and lower segments (LS) of Kangsabati River using fuzzy logic, analytical hierarchical process (AHP), and entropy weight-based multi-criteria decision matrix (MCDM) methods. Borda integrating MCDM results revealed that overall indicator performance is high health score in US (77), medium score in MS (69), but mostly unhealthy score in LS (34); thus, entropy-MCDM models give highest rank to US, medium rank to MS, and least rank to LS, while AHP and fuzzy MCDM models assigned as high priority rank to MS, medium rank to US, and least rank to LS, respectively. According to model validation performances, entropy-MCDM models (RMSE < 2.48) are rationalized to the harmonic relationship of riverine system, whereas fuzzy and AHP-MCDM models (RMSE < 2.79) are signified to HSDs, and these results are closer to real problems. With the acceptability of AHP-MCDM models through the percentage change (73.89%) and intensity change (17.16) assessment, it points that over HSDs are crucial factors for river health degradation. Moreover, final outcome of the present research helps to find out the sick river health sites for ecological restoration.

Watershed health assessment using the coupled integrated multistatistic analyses and PSIR framework

Quantitatively assessing watershed health under anthropogenic activities and management responses is important for the scientific planning and management of watersheds. The current research on watershed health assessments insufficiently reflects watershed scale information from different dimensions, which leads to the incomplete understanding of watersheds and thus the lack of systematic management. This study investigated the health status in the Chaohu Lake watershed (CLW) based on monthly sampling data at 46 river sites in 2018. Watershed health assessment comprehensively considered four dimensions including socioeconomic and natural pressures, nonpoint pollution export, river water quality and management responses with the pressure-state-impact-response (PSIR) framework. Canonical correlation analysis (CCA) and variance partitioning analysis (VPA) were integrated to further quantify the inter-relationships among the variables of each PSIR index. An obstacle degree model was applied to examine the factors of mainly affecting the status of watershed health. The results showed that phosphorus, nitrogen and sediment exports of CLW increased more and river water quality in CLW worsened due to socioeconomic and natural pressures. Water quality improvement effectively responds to increasing woodland and grassland. Compared with natural factors, phosphorus, nitrogen and sediment exports had closer relationships with the pressures from socioeconomic activities. Moreover, socioeconomic pressures explained more changes in phosphorus and nitrogen exports, while natural factors explained relatively more changes in sediment exports. Phosphorus, nitrogen and sediment exports and woodland and grassland coverage explained <35 % of the variation in river water quality. Additionally, the obstacle degrees of pressures and phosphorus, nitrogen and sediment exports were lower, and the obstacle degrees of river water quality and woodland and grassland coverage were higher in urban sub-watersheds, which was the opposite in agricultural sub-watersheds. This research provides a new evaluation framework of watershed health and its obstacle factors, which is crucial to improve watershed health.

Temporal-spatial change of China's coastal ecosystems health and driving factors analysis

Understanding the spatial distribution pattern change and driving factors behind ecosystem health is essential to ecosystem management and restoration. However, in the research of regional ecosystem health, there is little research on ecosystem health in coastal regions, and there is little exploration of its temporal and spatial pattern change and its driving factors. In this study, we use the Vigor-Organization-Resilience-Services (VORS) model and marine ecosystem health index to diagnose the ecosystem health of the whole coastal area of China over the last 20 years, and find the main contributing factors affecting ecosystem health with the help of geographic detectors and geographic weighted regression analysis. Our results show that: (1) the ecosystem health level in the south of the coastal region is higher than that in the north, mainly with 30° north latitude as the main dividing line. (2) The regions with high change rate are mainly concentrated in Bohai Bay, the Yangtze River Estuary, Hangzhou Bay and the Pearl River Estuary, and the change is mainly negative. (3) Both natural and human factors have an impact on ecosystem health, and the influencing factors are different on different scales. The interaction between different factors is greater than the impact of a single factor on ecosystem health. The study puts forward a new evaluation framework for the study of ecosystem health in coastal areas, which can be applied to other coastal areas with similar conditions, and can help the sustainable and healthy development of coastal areas.

Water Quality and Microbial Community in the Context of Ecological Restoration: A Case Study of the Yongding River, Beijing, China

Ecological water replenishment via interbasin water diversion projects provides opportunities for ecological river restoration. Untangling water quality changes, microbiota dynamics, and community functions is necessary for sustainable ecological management. Using the Yongding River as a case study, we monitored the water quality and applied genomic sequencing to investigate microbial communities of the river in different stages after ecological water replenishment. Our results showed that river water quality represented by chemical oxygen demand (COD), total nitrogen (TN), and chlorophyll-a (Chl-a) did not change significantly during months after water replenishment. The bacterial community composition varied in different months and river subsections. The Cyanobium_PCC-6307, CL500-29 marine group, and Pseudomonas were dominant in the later stages after water replenishment. Water temperature, pH, and nutrient levels significantly affected the microbial community composition, and ecological restoration may have the potential to influence nitrogen cycling in the river. Our results can provide ecological insights into sustainable water quality maintenance and river management following ecological restoration enabled by ecological water replenishment.

Phytoplankton community variation and ecological health assessment for impounded lakes along the eastern route of China's South-to-North Water Diversion Project

Interbasin water diversion projects have been proven to effectively alleviate water resource shortages in areas along water diversion lines, but few studies have focused on ecological health in impounded lakes compared with research on water quality and pollutants. Herein, monitoring data were collected during the nonwater diversion period (NWDP) and the water diversion period (WDP) from 2018 to 2019, and the index of biological integrity (IBI) method based on phytoplankton communities was used to evaluate the ecological health of the impounded lakes (Nansi Lake and Dongping Lake) along the eastern route of the South-to-North Water Diversion Project. The results demonstrated that water diversion improved the water quality of the impounded lakes during the WDP, especially total nitrogen and ammonia nitrogen. Meanwhile, the water diversion affected the phytoplankton community structure and diversity, and network analysis further revealed water diversion could be beneficial to the ecological health of impounded lakes. Furthermore, the P-IBI showed that the overall ecological health assessment was "good" during the WDP. Water diversion substantially improved the ecological health status and stability of the impounded lakes during the dry season. Finally, the direct correlations between the water quality parameters and the P-IBI were weak, and water quality parameters could indirectly affect the P-IBI by changing the phytoplankton community structure. These findings will enhance our understanding of the ecological health of the impounded lakes of the South-to-North Water Diversion Project. Furthermore, this study will provide a reference to support the ecosystem security of impounded lakes in other large water diversion projects.

Study on the Spatial Interaction between Urban Economic and Ecological Environment-A Case Study of Wuhan City

In order to study the interactive relationship between urban economic and ecological environment, taking Wuhan as an example, Landsat and MODIS remote sensing satellite data and social and economic data were fused with multisource data, and multidimensional indicators were selected to construct the comprehensive evaluation index system of urban economic and ecological environment. The weights were determined by combining subjective and objective methods. Then, the decoupling elasticity coefficient method and spatial autocorrelation model were used to evaluate the dynamic relationship and spatial relationship between economic development and ecological environment in Wuhan from 2014 to 2020. The results showed that there was an interaction between the urban economic and the ecological environment in Wuhan. The ecological level index had a spatial effect, the adjustment of industrial structure had a positive effect on the improvement of the ecological level, and the improvement of the ecological level was also helpful to promote economic development. The typical districts of Huangpi District, Xinzhou District, Jiangxia District, Hannan District, Caidian District, and Hongshan District had superior location and ecological advantages, as well as high development potential. Lastly, on the basis of the empirical analysis results, policy suggestions are made from four aspects: regional differentiated construction, green development, energy consumption, and wetland construction.

Interactive influences of meteorological and socioeconomic factors on ecosystem service values in a river basin with different geomorphic features

Ecosystem service value (ESV) is influenced by land use and land cover (LULC), and is closely related to natural conditions and human activities. However, the interactions between human and natural systems and ESV remain unclear, especially concerning widely discussed meteorological and socioeconomic factors. In this study, three periods of LULC patterns (2000, 2010, and 2020) in the Haihe River Basin, northern China, were collected to determine the relationship between changes in LULC and ESV over time. Natural and socioeconomic data associated with ESV were obtained and the structural equation model was used to decouple interactions between these factors. Results showed that the total value of regional ecosystem services has decreased as cultivated land shrunk and artificial surfaces increased over the past two decades. The ESV was significantly decreased in the middle of the basin. The direct effects of meteorological factors and socioeconomic factors on ESV were positive (0.094) and negative (-0.203), respectively. The indirect effect of socioeconomic factors on ESV through meteorological and LULC factors was 0.149. Structural equation modeling demonstrated that under the dominance of LULC, interactions between natural and socioeconomic factors affected ESV in a complex manner. These results implied that identifying the direct and indirect effects of economic development and human activities on ESV could guide and implement effective land management policies.

Hydrological Change Detection and Process Simulation for a Semi-Arid Catchment in Northern China

In-depth understanding and accurate simulation of hydrological processes are of great significance for sustainable development and management of water resources. The study focused on a semi-arid catchment, the upper Tang River catchment in northern China, and investigated the performance of the RCCC-WBM model based on the detection results of trend, mutation, and periodicity. Results show that (1) as a result of climate change and intensive human activities, the observed runoff series after TFPW (trend-free pre-whiting) pretreatment presented a significant downward trend with the mutation point in 1996; (2) the abrupt change of air temperature series was also in 1996 with a significant rising trend, while the annual precipitation series exhibited an insignificant declining trend with no obvious mutation during 1973–2014; (3) the precipitation and runoff series had periodic variations roughly 7a multiples with the periodic oscillation strongest around 14a, while the air temperature series showed only one dominant period of 28a; (4) the RCCC-WBM model performed well in discharge simulation before the mutation year but gradually lost its stability after 1996, which was mainly affected by anthropogenic activities. It is essential to accurately identify the characteristics of hydrological elements and improve the applicability of hydrological models in the changing environment in future studies.

A multi-scale assessment of ecosystem health based on the Pressure-State-Response framework: a case in the Middle Reaches of the Yangtze River Urban Agglomerations, China

Anthropogenic activities have reshaped the structure and function of ecosystems in global urban agglomerations. Evaluating the spatiotemporal features of ecosystem health for sustainable and high-quality development and the strategic deployment of ecological civilisation in urban agglomerations is essential. However, existing research lacks a multi-scale assessment of ecosystem health in urban agglomerations, limiting governments in formulating effective ecosystem management policies. To bridge this gap, a multi-scale assessment of ecosystem health at the county and township levels in the Middle Reaches of the Yangtze River Urban Agglomerations (MRYRUA) in China was conducted using the 'Pressure-State-Response' framework. The results showed that most units (> 70%) were at a moderately healthy level, while only a small proportion (< 10%) was at a healthy level from 2000 to 2015 at both scales. The ecosystem health level in the surrounding and central mountainous areas was significantly higher than that in the plain areas. Our results demonstrated that the overall ecosystem health index in the MRYRUA continued to decrease during the study period at both scales. The ecosystem health in the key cities, the surrounding units of the key cities, and the units along the main traffic routes were low. This study provides an overview of ecosystem health and a scientific basis for landscape planning and ecosystem restoration in the MRYRUA.

Development of a Landscape-Based Multi-Metric Index to Assess Wetland Health of the Poyang Lake

Human-induced changes in landscapes are one of the major drivers of wetland loss and degradation. The Poyang Lake wetland in China has been experiencing severe degradation due to human disturbance and landscape modification. Indicators to assess the condition of this wetland are thus needed urgently. Here, a landscape-based multi-metric index (LMI) is developed to evaluate the condition of the Poyang Lake wetland. Twenty-three candidate metrics that have been applied to wetland health assessment in published studies were tested. Metrics that show strong discriminative power to identify reference and impaired sites, having significant correlations with either benthic macroinvertebrate- or vegetation-based indices of biotic integrity (B-IBI or V-IBI), were chosen to form the LMI index. Five of these metrics (largest patch index, modified normalized differential built-up index, Shannon’s diversity index, connectance index, and cultivated land stress index) were selected as our LMI metrics. A 2 km buffer zone around sample sites had the strongest explanatory power of any spatial scale on IBIs, suggesting that protecting landscapes at local scales is essential for wetland conservation. The LMI scores ranged between 1.05 and 5.00, with a mean of 3.25, suggesting that the condition of the Poyang Lake wetland is currently in the “fair” category. The areas along lakeshores were mainly in poor or very poor conditions, while the less accessible inner areas were in better conditions. This study demonstrates significant links between landscape characteristics and wetland biotic integrity, which validates the utility of satellite imagery-derived data in assessing wetland health. The LMI method developed in this study can be used by land managers to quickly assess broad regions of the Poyang Lake wetland.

Dynamic Measurement of Water Use Level Based on SBM-DEA Model and Its Matching Characteristics with Economic and Social Development: A Case Study of the Yellow River Basin, China

Enhancing the level of water use and alleviating the constraints of water shortage on economic and social development are powerful supports to realize the harmonious balance of water and economic society. In this study, the data envelopment analysis (DEA) window analysis method is applied to the study of water use level, and the SBM-DEA model (slack based measure, SBM) is combined to explore the spatial and temporal evolution characteristics of composite water use index (CWUI) in nine provinces from 2012 to 2018. The Malmquist index model is used to decompose the intrinsic causes of total factor productivity (TFP) changes, and the spatial matching degree calculation method is applied to study the matching degree between CWUI and economic and social development levels (E-SDL). The results showed that: (1) the overall trend of CWUI in the nine provinces from 2012 to 2018 was increasing, with significant spatial variability in water use levels; (2) the improvement of TFP of water in the nine provinces was mainly driven by technological change (TC), and the main factor limiting the improvement of TFP of water was technical efficiency change (EC); (3) E-SDL of the nine provinces showed an increasing trend, with the spatial distribution characteristics of decreasing E-SDL of the downstream, midstream and upstream provinces in sequence; (4) the degree of matching between CWUI and E-SDL shows strong regional differences, with different types of matching.

Assessment of Ecosystem Health and Its Key Determinants in the Middle Reaches of the Yangtze River Urban Agglomeration, China

Urban agglomerations have gradually formed in different Chinese cities, exerting great pressure on the ecological environment. Ecosystem health is an important index for the evaluation of the sustainable development of cities, but it has rarely been used for urban agglomerations. In this study, the ecosystem health in the middle reaches of the Yangtze River Urban Agglomeration was assessed using the ecosystem vigor, organization, resilience, and services framework at the county scale. A GeoDetector was used to determine the effects of seven factors on ecosystem health. The results show that: (1) The spatial distribution of ecosystem health differs significantly. The ecosystem health in the centers of Wuhan Metropolis, Changsha-Zhuzhou-Xiangtan City Group, and Poyang Lake City Group is significantly lower than in surrounding areas. (2) Temporally, well-level research units improve gradually; research units with relatively weak levels remain relatively stable. (3) The land use degree is the main factor affecting ecosystem health, with interactions between the different factors. The effects of these factors on ecosystem health are enhanced or nonlinear; (4) The effect of the proportion of construction land on ecosystem health increases over time. The layout used in urban land use planning significantly affects ecosystem health.

Exploring Development Trends of Terrestrial Ecosystem Health—A Case Study from China

Terrestrial ecosystem health (TEH) is the basis of regional sustainability development. The state of TEH is an important research direction in the land science field. The purpose of this paper was to explore the development trends and influencing factors of the. By using the radial basis function (RBF), neural network model, geographic information system (GIS), and the comprehensive index method, this paper predicted the land ecological changes of Henan Province from 2007 to 2025 based on a comprehensive evaluation of the system. The results show that the TEH of Henan Province exhibited a general trend of improvement from 2007 to 2025. The predictions exhibited a tendency to fluctuate and increase, from “severe warning” to “moderate warning” and even to “no warning” state. The early warning index of the subsystem showed a fluctuating upward trend except for the press subsystem, which fluctuated between “extraordinary warning” and “heavy warning” states. The overall TEH level is improving but is largely dependent on effective corresponding measures. The health status of the land ecosystem in Henan Province is guaranteed to be stable due to improvements in rural residential incomes, mechanization levels of cultivated land, domestic sewage treatment rates, and the numbers of scientific and technological personnel per unit of land. The TEH is mainly restricted by the population densities, urbanization levels, inputs of fertilizers and pesticides, and average wastewater load factors of the land. To improve the health level of the land ecosystem, it is necessary to reduce the use of fertilizers and pesticides and to control the urbanization rate. At the same time, improving the level of forest coverage and the effective irrigation rate play a positive role in improving ecosystem health. The results provide a reference for land-use planning and management decisions.

Ecological Health Assessment of Chinese National Parks Based on Landscape Pattern: A Case Study in Shennongjia National Park

Assessing the health of the ecosystem based on the landscape pattern of national parks can facilitate policy makers in formulating more targeted conservation policies to better manage national park ecosystems. To analyze the landscape patterns and characteristics of the national park, the ecosystem health evaluation index system of the national park was constructed using the vigor-organization-resilience (VOR) model to evaluate the health status. In this study, the Shennongjia National Park in China was selected as a case study area to be assessed using the index system. The results revealed that the patches of construction land and farmland are the largest in number and the most complex in shape, reflecting the obvious fragmentation of construction land and farmland patches. All patch types in this national park were evenly distributed. The results of the analysis showed that the comprehensive index of national park heath, according to the VOR model, is 0.74, indicating that the ecosystems in this study area were in a good state of health. Ecosystems in strictly protected areas of this park had the highest ecosystem health index levels, while the traditional utilization areas had the lowest. Ecosystem health levels were characterized by significant spatial agglomeration characteristics, with high-high aggregation distribution areas, mainly clustered in strictly protected areas, and low-low aggregation distribution, mainly clustered in traditional utilization areas and marginal areas. This study provided a set of ecosystem health assessment systems and their practical use in China’s newly established national parks.

Influence of socioeconomic development on river water quality: a case study of two river basins in China

Social and economic development processes require large amounts of natural resources and in some cases seriously deteriorate river water quality. Since the reform and expansion era began, China has vigorously pursued socioeconomic development but neglected environmental protection. However, in recent years, improvements in environmental awareness and the implementation of environmental protection measures have led to a balanced relationship between economic development and the environment. In this study, the Yangtze River Basin and the Yellow River Basin were selected as research areas. We used a combination of canonical correlation analysis (CCA) and a distance-based influence assessment method to quantitatively assess the influence of socioeconomic development on river water quality. The results revealed a strong correlation between socioeconomic development and river water quality. The degree of influence of socioeconomic development on water quality varied not only temporally but also spatially due to differences in socioeconomic development and hydrometeorology in the two basins in North and South China. The average degree of influence in the Yangtze River Basin was between 0.22 and 0.27, and that in the Yellow River Basin was between 0.2 and 0.36. Moreover, the degree of influence in the Yangtze River Basin in the wet season was greater than that in the dry season, whereas the opposite pattern was observed in the Yellow River Basin. The degree of influence in both basins gradually declined after 2011, indicating that the coupling and coordination between socioeconomic development and environmental protection have continuously improved and that the water quality has gradually improved. By analysing the influences of various socioeconomic indicators on water quality, we found that the main factors that influence water quality are per capita GDP and urbanization rate in the Yangtze River Basin and urbanization rate in the Yellow River Basin. The results provide a basis for future sustainable development in the Yangtze River Basin and the Yellow River Basin.

Macro analysis of spatiotemporal variations in ecosystems from 1996 to 2016 in Xishuangbanna in Southwest China

This study used remote sensing images from 1996 to 2016 as the main data source, and selected the average annual ecosystem type net change rate, ecosystem type transfer matrix, and comprehensive index of land development degree, to analyze the macro change of the ecosystem pattern in Xishuangbanna Dai Autonomous Prefecture in the past 20 years. Quantitative analysis was performed on amplitude, rate, type of transition, and degree of disturbance of human activities. The results reveal the spatial and temporal changes of the Xishuangbanna ecosystem and their regional differentiation. The results showed that (1) from 1996 to 2016, Xishuangbanna as a whole was dominated by forest ecosystems and rubber ecosystems, followed by tea, farmland, built-up area, and water ecosystems. (2) During 1996-2016, the ecosystem in Xishuangbanna accounted for more than 99% of the total area has not changed. From 1996 to 2003, the transfer of ecosystem types in Xishuangbanna was mainly between forest and rubber ecosystem. (3) The extent of land development and utilization in Xishuangbanna in the past 20 years is relatively low, slightly lower than the national average, and the overall level of land use is at a medium level of utilization, and over time, the degree of disturbance of human activities has shown an increasing trend.

A Novel Technique for Modeling Ecosystem Health Condition: A Case Study in Saudi Arabia

The present paper proposes a novel fuzzy-VORS (vigor, organization, resilience, ecosystem services) model by integrating fuzzy logic and a VORS model to predict ecosystem health conditions in Abha city of Saudi Arabia from the past to the future. In this study, a support vector machine (SVM) classifier was utilized to classify the land use land cover (LULC) maps for 1990, 2000, and 2018. The LULCs dynamics in 1990–2000, 2000–2018, and 1990–2018 were computed using delta (Δ) change and Markovian transitional probability matrix. The future LULC map for 2028 was predicted using the artificial neural network-cellular automata model (ANN-CA). The machine learning algorithms, such as random forest (RF), classification and regression tree (CART), and probability distribution function (PDF) were utilized to perform sensitivity analysis. Pearson’s correlation technique was used to explore the correlation between the predicted models and their driving variables. The ecosystem health conditions for 1990–2028 were predicted by integrating the fuzzy inference system with the VORS model. The results of LULC maps showed that urban areas increased by 334.4% between 1990 and 2018. Except for dense vegetation, all the natural resources and generated ecosystem services have been decreased significantly due to the rapid and continuous urbanization process. A future LULC map (2028) showed that the built-up area would be 343.72 km2. The new urban area in 2028 would be 169 km2. All techniques for sensitivity analysis showed that proximity to urban areas, vegetation, and scrubland are highly sensitive to land suitability models to simulate and predict LULC maps of 2018 and 2028. Global sensitivity analysis showed that fragmentation or organization was the most sensitive parameter for ecosystem health conditions.

Quantifying the Compound Factors of Forest Land Changes in the Pearl River Delta, China

Forestland has been a focus of urbanization research, yet the effect of urbanization on forest land change on an urban agglomeration scale still remains unclear. Screening and quantifying the main factors affecting forest land changes have practical significance for land planning and management. Considering the characteristics of the region and referring to related studies, 26 natural, social, and economic factors were screened in the Pearl River Delta (PRD), where land-use changes are intense. Geographically weighted regression and the relative importance were used to quantify the spatial heterogeneity of these main factors. There was still a large area of deforestation evident in the PRD with its afforestation area of 604.3 km2 (mainly converted from cropland) and a deforestation area of 1544.6 km2 (mainly converted from built-up land). The effects of socio-economic factors were the main factors for these forest land changes, especially the rural population and migration. Deforestation mainly occurs in urban growth boundaries, which will be the focus area for further land management. These main factors have the potential to provide a methodological contribution to land-use changes, and the results of this study can provide a solid theoretical basis for forest land management and urban planning (e.g., balancing expansion of built-up land and ecological protection that advances forest land protection and restoration).

Coupling Analysis of Ecosystem Services Value and Economic Development in the Yangtze River Economic Belt: A Case Study in Hunan Province, China

Sound ecosystems are a precondition for the sustainable survival and development of human society. However, ecological deterioration caused by socioeconomic activities can result in increasing pressure on ecosystems. Exploration of the spatial interaction between ecosystem and economic development under the background of high-quality and green development is, therefore, necessary. In this study, we analyzed the spatial interaction between the ecosystem services value (ESV) and economic development with the economic and ecological coupling index method based on high-resolution remote-sensing land-use data and socioeconomic statistical data in Hunan Province from 2000 to 2018. The results revealed that the ESV provided by the ecosystems in Hunan Province decreased by US$1256.166 million from 2000 to 2018. The areas with high ESV per unit area were distributed in the mountainous areas, while the areas with low ESV per unit area were distributed in the major cities and their surroundings. The bivariate spatial autocorrelation analysis showed that the ESV had significant spatial dependence on the economic development. In addition, the coupling analysis documented that the relationship between the ESV and economic density was mostly in the low conflict and potential crisis states. These results provide important guidance for the coordinated development of the regional economy and ecosystem conservation.

The impact of land use and socio-economic factors on ammonia nitrogen pollution in Weihe River watershed, China

Rapid socio-economic development has led to a significant deterioration in the water environment, which has limited sustainable regional development. The soil and water assessment tool (SWAT) and statistical regression method were used to model the ammonia nitrogen (NH₄⁺-N) pollution and explore the impacts of land use and socio-economic factors on NH₄⁺-N pollution within the Weihe River watershed in China from 2015 to 2018. The result of SWAT model revealed that the NH₄⁺-N concentrations were usually relatively high under low runoff conditions and relatively low under high runoff conditions. The average NH₄⁺-N concentration in the upper reaches was 0.77 mg/L, whereas it was 0.87 mg/L in the middle and lower reaches of the watershed. Serious NH₄⁺-N pollution mainly occurred in 2015 and 2016, and the V (2.0 mg/L) and V+ (>2.0 mg/L) water quality classes were associated with approximately 6.67% and 28.94% of the total watershed area, respectively. The multiple linear regression indicated that the building land and secondary industry were the significant controlling factors (P < 0.01). According to the scenario analysis, modelled scenarios for interception measures reduced the NH₄⁺-N load to a greater degree than scenarios for source control measures. To improve the surface water quality in the Weihe River, it is recommended to adjust industrial structure, increase sewage treatment, and strengthen the rural management of the watershed.

Comparison between water quality indices in watersheds of the Southern Bahia (Brazil) with different land use

The present study evaluated the influence of land use and occupation on water quality indices (WQI); the WQI developed by the National Sanitation Foundation (NSF), the WQI adapted by the Environmental Company of the São Paulo State (CETESB), WQI proposed by Bascarón and the Canadian Council of Ministers of the Environment (CCME) WQI, obtained for watersheds located in the Eastern Water Planning and Management Region (BA). The study also analyzed the divergences and similarities of these WQI methods. Water quality data were obtained from the Monitoring Program (Monitora) of Environment and Water Resources Institute of Bahia (INEMA), covering the period from 2008 to 2015, at thirteen (13) sampling sites, with quarterly collections, as well as land use and occupation data. The influence of land use and occupation on water quality indices was assessed by principal component analysis (PCA). The PCA showed that urban and agricultural/pasture areas were influencing factors on water quality variables, such as total phosphorus, biochemical oxygen demand, total nitrogen, turbidity total residues and consequently lower WQI values in the Cachoeira watershed. Among the tested methods to evaluate the water quality of watersheds in the study area, the most similar were the NSF WQI, CETESB WQI, and Objective Bascarón WQI.

Urbanization's Impacts on Ecosystem Health Dynamics in the Beijing-Tianjin-Hebei Region, China

Accelerated urbanization disturbs ecosystems and influences ecosystem structures and functions. Ecosystem health (ESH) assessments in regions undergoing the rapid urbanization process assist us in understanding how ESH changes and how urbanization specifically affects ESH. We assessed the ESH of Beijing-Tianjin-Hebei (BTH) region, China, including the ecosystem service value (ESV). In this study, we selected nine indicators and applied multiple pieces of software, including ArcGIS10.4, Fragstats4.2 and Geoda1.14 to detect the impacts of urbanization on regional ESH in 1995, 2000, 2005, 2010 and 2015. The results show that ESH in the BTH region increased from 2000 to 2015, especially in the northern parts. The improvements were due to the implementation of key ecological restoration projects protecting and re-establishing the forest in the north. Furthermore, the spatial correlation results indicate that urbanization had a negative impact on ESH in the BTH region, of which the dominant factor was the population density in 1995. The dominant factor was the construction land proportion from 2005 to 2015. We suggest that ecological restoration projects should be continued in northern regions with strong and relatively strong ESH levels to maintain high-level ecosystem health. In addition, more attention should be paid to the ESH level improvement in peri-urban areas.

Spatial and temporal variations in river water quality of the Middle Ganga Basin using unsupervised machine learning techniques

In this study, cluster analysis (CA), principal component analysis (PCA) and correlation were applied to access the river water quality status and to understand spatiotemporal patterns in the Ganga River Basin, Uttara Pradesh. The study was carried out using data collected over 12 years (2005-2017) regarding 20 water quality parameters (WQPs) covering spatially from upstream to downstream Ankinghat to Chopan, respectively (20 stations under CWC Middle Ganga Basin). The temporal variations of river water quality were established using the Spearman non-parametric correlation coefficient test (Spearman R). The highest Spearman R (-0.866) was observed for temperature with the season and a very significant p value of (0.0000). The parameters EC, pH, TDS, T, Ca, Cl, HCO₃, Mg, NO₂ + NO₃, SiO₂ and DO had a significant correlation with the season (p < 0. 05). K-means clustering algorithm grouped the stations into four different clusters in dry and wet seasons. Based on these clusters, box and whisker plots were generated to study individual clusters in different seasons. The spatial patterns of river WQ on both seasons were examined. PCA was applied to screen out the most significant water quality parameters due to spatial and seasonal variations out of a large data set. It is a data reduction process and a more conventional way of speeding up any machine learning algorithms. A reduced number of three principal components (PCs) were drawn for 20 WQPs with an explained total variance of 75.84% and 80.57% is observed in the dry and wet season, respectively. The parameters DO, EC_ Gen, P-Tot, SO₄ are the most dominating parameters with PC score more than 0.8 in the dry season; similarly, TDS, K, COD, Cl, Na, SiO₂ in the wet season. The different components of water quality monitoring, such as spatiotemporal patterns, scrutinize the most relevant water quality parameters and monitoring stations are well addressed in this study and could be used for the better management of the Ganga River Basin.

Mapping ecological space quality changes for ecological management: A case study in the Pearl River Delta urban agglomeration, China

Compiling information concerning changes in ecological space quality (ESQ) is imperative for urban management and restoration, as proper management promotes sustainable development. Most previous studies have lacked a comprehensive model for evaluating ESQ and are thus unable to provide effective support for decision-makers. Based on the purpose of policy and needs of the public, this paper constructs a comprehensive adaptive evaluation model for mapping ESQ using the Pearl River Delta (PRD) urban agglomeration as an example, and the analysis uncovers the driving forces of urbanization indicators of ESQ change. From 2000 to 2017, the overall ESQ was considered as good, but the overall value decreased slightly, from 52.8 to 51.5. ESQ in the central PRD exhibited a notable downward trend, while coastal cities exhibited an upward trend. There was an approximate negative correlation between ESQ and the urbanization indexes, except for education level and the proportion of primary industry. In the PRD, rural population density, the proportion of primary industry, and education level were the important drivers of magnitude and direction in most cities, but their impacts differed across cities. The ecological management lacked control of in areas good and moderate ESQ, and this was the main factor resulting in the decline of regional ESQ. By quantifying ESQ and the spatially explicit urbanization drivers, the potential for ecological management in the urban agglomeration is also discussed.

Spatiotemporal Characteristics and Driving Force of Ecosystem Health in an Important Ecological Function Region in China

Quantitative assessment can scientifically determine the health status of a regional ecosystem, identify regional eco-environmental problems, and assist in promoting regional sustainable development and environmental management. Taking China's important ecological function region, the Yellow River affected area as an example, this study constructed an extended evaluation index system based on the pressure-state-response framework, and remote sensing and GIS techniques were used to dynamically evaluate the spatial and temporal characteristics of ecosystem health in the study area. Furthermore, influencing factors on ecosystem health in the study area were extensively analyzed using the GeoDetector model. The results show that the ecosystem health level in the study area shows significant spatial heterogeneity from 1995-2015, and showed a fluctuating change process. Areas with large fluctuations in health level were mainly distributed in extreme climate areas, ecologically fragile areas, on plains and in hilly areas. Spatial differences of ecosystem health were well explained by using the biological abundance index, relief degree of land surface, soil type, annual average precipitation, elevation, annual average temperature, and population density. Influencing factors have significant interactive effects on ecosystem health.

Study on the Sustainable Development of an Arid Basin Based on the Coupling Process of Ecosystem Health and Human Wellbeing Under Land Use Change—A Case Study in the Manas River Basin, Xinjiang, China

Due to the differences in the contributions of land use types to ecosystem health and human wellbeing, there is a trade-off and a coordinating relationship between ecosystem health and human wellbeing, which affects the sustainable development of a river basin. To explore the impacts of the responses of ecosystem health and human wellbeing and the combined effects under land use change, this paper, taking the Manas River Basin (MRB) as an example, evaluated the health status of the MRB by the model: Vitality (V), organization (O), resilience (R), and services (S). From a sustainability perspective, an index system of human wellbeing was constructed, which included society and the economy, health and safety, materials and resources, and ecology and the environment. On this basis, the coupling coordination relationship and sustainable development status of the basin was assessed. The results showed that as land use changed, the ecosystem health showed a downward trend, and human wellbeing grew exponentially. The sustainable development index and the coupling coordination degree of the MRB were similar, indicating that the level of balance between ecosystem health and human wellbeing was the key to the sustainable development of the basin, and the overall situation was in a state of moderate imbalance and moderate unsustainability. Therefore, it is necessary to carry out sustainable management of the whole basin.

Impact of Fast Urbanization on Ecosystem Health in Mountainous Regions of Southwest China

Accelerated urbanization has changed land use patterns, leading to the deterioration of ecosystems. Assessments of ecosystem health (ESH) during the urbanization process are used to determine the reasons and mechanism for this, and to uncover negative factors. In this study, we assessed the ESH of Qiannan prefecture, in Guizhou Province, China, based on the ecosystem services value. We selected a series of indicators, including natural, social, and economic aspects, to detect the impact of urbanization on ecosystem services in 1990, 1995, 2000, 2005, 2010, and 2015. The results show that ESH in Qiannan declined from 1990 to 2015, especially in the eastern and northern regions. Further, the results indicate that urbanization had a negative impact on ESH, of which the dominant factor was the proportion of construction land from 1990 to 2005. After 2005, moreover, the dominant factor was the gross domestic product. The impact of urbanization on EHS had spatial differences, however. The most significant negative impact was found in the east and north. After 2010, the western and central regions of Qiannan showed an urbanization trend in favor of ecosystem health. We recommend ecological restoration in regions with weak and relatively weak ESH levels to achieve sustainable development.

Exploring the regional differences of ecosystem health and its driving factors in China

A better understanding of regional differences in ecosystem health and its driving factors is conducive to ecosystem management and restoration. Although various studies on ecosystem health have been carried out in different regions, few studies have been devoted to the insightful exploration of the spatial heterogeneity of ecosystem health and its driving forces at a national scale. In this study, we used an evaluation framework in terms of vigor, organization, resilience, and ecosystem service functions to assess the ecosystem health level in China from 2000 to 2015. Then, spatial agglomeration and regional differences in ecosystem health were examined using the spatial autocorrelation method and K-means clustering analysis, and the factors driving the regional differences of ecosystem health were explored based on the geographical detector model. Our results showed the following: (1) the ecosystem health level in China spatially increases from the northwest to the southeast, exhibiting significant global spatial autocorrelation and local spatial agglomeration; (2) eleven zones with three types were identified to indicate the regional differences of ecosystem health; (3) In terms of the driving factors, the moisture index and land use intensity contributed 24.5% and 20.7% to the variation in ecosystem health at the national scale. The ecosystem health changes were influenced by the interaction of meteorological and socio-economic factors in most regions with high ecosystem health types. Socio-economic factors act as a bridge that linked and reinforced the other factors in most regions with low and medium ecosystem health types. Ecologically protected factors were found to exert a remarkable impact in the southwestern region and the Loess Plateau region. Our findings can provide more effective and detailed decision-making support for ecosystem conservation and management in China.

Modeling the non-point source pollution risks by combing pollutant sources, precipitation, and landscape structure

Traditional models of nutrient simulation usually focus on the pollutant sources and precipitation, lacking the quantification of landscape structure. We developed a new prediction model of pollution risks by combing pollutant sources, precipitation, and landscape structure, which was defined as the source-precipitation-landscape model (SPLM). The SPLM was applied to simulate the non-point source (NPS) total nitrogen (TN) exports in one of the largest river basins in China (the Haihe River Basin, HRB). TN concentrations of 35 sampling catchments in 2013 were used to test the accuracy of the SPLM. Simulated results showed that (1) the SPLM had a relative high accuracy in the simulation of NPS TN export and intensity, especially for TN intensity. (2) The mean TN export and intensity of all the 1578 catchments in the HRB were 441.97 t and 2.08 t/km², respectively. (3) The TN export intensities differed greatly among the sub-basins in the HRB, ranging from 0.64 to 6.81 t/km². On the whole, the TN export intensities of the plain sub-basins (e.g., the Tuhaimajia River, the Heilonggang River, and the Beisihe River) were much higher than those of mountainous sub-basins (e.g., the Yongding River, the Beisanhe River, and the Luanhe River). (4) The contributions to TN exports, from high to low, were land use (38.82%), livestock husbandry (33.57%), and rural population (27.61%). Among all the ten pollution sources, arable land (30.87%), rural population (27.61%), and large livestock (17.73%) had the top three contributions to TN exports. This study provides a feasible tool for policymakers and administrators to develop workable management measures for the mitigation of NPS pollution. This SPLM can be extended to other regions in a rapid urbanization context.

Characterizing interactions of socioeconomic development and environmental impact at a watershed scale

Worldwide socioeconomic development has resulted in huge irretrievable environmental problems in various ecosystems. This study employed seven coastal watersheds in two provinces, Zhejiang and Fujian, China forming a gradient to testify the environmental Kuznets curve (EKC) interactions between socioeconomic development and environmental impact at a watershed scale. Annual socioeconomic indicators, including gross domestic product (GDP) and its components, registered population (agricultural and non-agricultural population), and electricity consumption, and annual discharges of chemical oxygen demand (COD) and ammonium were collected at a county level, and land use pattern to generate watershed level dataset in the period of 2011-2016. Results indicated that non-agricultural GDP per capita of the non-agricultural population and discharge of COD or ammonium per unit of total GDP were top-ranked pair-indicators significantly fitting the EKC model instead of the classic GDP per capita and pollutants. The development of seven selected watersheds have passed the turning point of the EKC and entered impact-reducing development stages along the EKC, i.e., the three Zhejiang watersheds are at the low-impact development stage, the Huotong Stream watershed from Fujian province was at impact-declining development stage right, and other three Fujian watersheds were at medium-impact development stage. In term of the environmental impact indicator, pollutant discharge per unit of total GDP serves as a development impact indictor per se. These findings might provide an EKC-based approach to support and strategize the watershed management for sustainable development in the world.

A new framework for assessing river ecosystem health with consideration of human service demand

In order to study river health status from harmonic relationship between human and natural environment, a river health evaluation method was proposed from the aspects of ecosystem integrity and human service demand, and the understanding of river health connotation. The proposed method is based on the harmony theory and two types of river health assessment methods (the forecasting model and index evaluation). A new framework for assessing river water health was then formed from the perspective of harmony and dynamic evolution between human service demand and river ecosystem integrity. As a case study, the method and framework were applied to the Shaying River Basin, a tributary of the most polluted Huaihe River Basin in China. The health status of the river's ecosystem and its effect on the mainstream of Huaihe River were evaluated based on water ecological experiment. The results indicated that: (1) the water ecological environment in Shaying River was generally poor and showed a gradual changing pattern along the river. The river health levels were generally "medium" in the upstream but mostly "sub-disease" in the midstream and downstream, indicating that the water pollution in Shaying River were mainly concentrated in the midstream and downstream; (2) the water pollution of Shaying River had great influence on the ecosystem of Huaihe River, and the main influencing factors were TN, followed by TP and COD_Mn; (3) the natural attribute of river was transferring toward to the direction of socialization due to the increasing human activities. The stronger the human activity intervention is, the faster the transfer will be and the more river's attributes will match with human service demand. The proposed framework contributes to the research in water ecology and environment management, and the research results can serve as an important reference for basin management in Shaying River and Huaihe River.

Long-Term Changes in Water Clarity in Lake Liangzi Determined by Remote Sensing

Water clarity (via the Secchi disk depth, SDD) is an important indicator of water quality and lake ecosystem health. Monitoring long-term SDD change is vital for water quality assessment and lake management. In this study, we developed and validated an empirical model for estimating the SDD based on Landsat ETM+ and OLI data using the combination of band ratio of the near-infrared (NIR) band to the blue band and the NIR band. Time series data of remotely estimated SDD in Lake Liangzi were retrieved from 2007 to 2016 using the proposed models based on forty Landsat images. The results of the Mann–Kendall test (p = 0.002) and linear regression (R2 = 0.352, p < 0.001) indicated that the SDD in Lake Liangzi demonstrated a significant decreasing trend during the study period. The annual mean SDD in Lake Liangzi was significantly negatively correlated with the population (R2 = 0.530, p = 0.017) and gross domestic product (R2 = 0.619, p = 0.007) of the Lake Liangzi basin. In addition, water level increase and the flood have an important effect on SDD decrease. Our study revealed that anthropogenic activities may be driving factors for the long-term declining trend in the SDD. Additionally, floods and heavy precipitation may decrease the SDD over the short term in Lake Liangzi. A declining trend in the SDD in Lake Liangzi may continue under future intense anthropogenic activities and climate change such as the extreme heavy precipitation event increase.

Spatial heterogeneity of estuarine wetland ecosystem health influenced by complex natural and anthropogenic factors

The evaluation of estuarine wetland ecosystem health (EWEH) is vital and difficult due to complex influencing factors and their spatial heterogeneities. An EWEH evaluation model was established in this study on the basis of the typical features of estuarine wetland ecosystems with focus on spatial heterogeneity. The index system comprises external factors, internal factors, and ecological state, and covers all aspects of the natural and anthropogenic factors, with each index possessing its own spatial heterogeneity. The Yellow River Delta, a typical estuarine wetland in China, was selected as the study area to demonstrate the model. Results indicated that the present EWEH in the entire study area was in good status with distinct spatial heterogeneity. Ecosystem productivity, seawater intrusion, human interference, and Yellow River input were the most relevant indexes of EWEH. The temporal variations of EWEH fluctuated from 1987 to 2016. The decrease in the Yellow River input and the increase in human activity intensity deteriorated EWEH, whereas the alongshore embankment and nature reserve construction improved EWEH in certain parts. The influence of natural factors continuously decreased, and human activity became the main driving factor of the EWEH spatial variation. Our model was proven to possess comprehensive reflections of estuarine wetland ecological characteristics, full exhibitions of spatial heterogeneity, and high applicability; therefore, it can be widely used to evaluate EWEH in different areas.

Spatio-Temporal Dynamic Architecture of Living Brush Mattress: Root System and Soil Shear Strength in Riverbanks

As a basal measure of soil bioengineering, the living brush mattress has been widely applied in riparian ecological protection forest construction. The living brush mattress shows favorable protective effects on riverbanks. However, there are few reports on the root structure and the soil strengthening benefit of the living brush mattress. The present work reports a series of experiments on root morphology and soil shear strength enhancement at the temporal and spatial scales. The object of the study is 24 living brush mattress trees constructed with Salix alba L. ‘Tristis’ (LBS hereafter). Traditional root morphology and mechanical measurement methods were used to collect the parameters. The results showed that the root systems of LBS had the characteristics of symmetry and upslope growth. The roots were mainly distributed in a cylindrical region of the soil (radius × thickness: 0.4 m × 0.5 m) and their biomass increased with different growth rates for the periods from 1 to 5 and from 5 to 7 years. Both age and slope position were factors that influence root growth. The root diameter falls within 0–5 mm, has a significant effect on the soil shear strength and provides a conical-shape potentiation zone to ensure the efficient protection of a riverbank. The results of this study demonstrate that LBS is an efficient and feasible engineering measure in the field of riverbank protection.

An improved export coefficient model to estimate non-point source phosphorus pollution risks under complex precipitation and terrain conditions

To control non-point source (NPS) pollution, it is important to estimate NPS pollution exports and identify sources of pollution. Precipitation and terrain have large impacts on the export and transport of NPS pollutants. We established an improved export coefficient model (IECM) to estimate the amount of agricultural and rural NPS total phosphorus (TP) exported from the Luanhe River Basin (LRB) in northern China. The TP concentrations of rivers from 35 selected catchments in the LRB were used to test the model's explanation capacity and accuracy. The simulation results showed that, in 2013, the average TP export was 57.20 t at the catchment scale. The mean TP export intensity in the LRB was 289.40 kg/km², which was much higher than those of other basins in China. In the LRB topographic regions, the TP export intensity was the highest in the south Yanshan Mountains and was followed by the plain area, the north Yanshan Mountains, and the Bashang Plateau. Among the three pollution categories, the contribution ratios to TP export were, from high to low, the rural population (59.44%), livestock husbandry (22.24%), and land-use types (18.32%). Among all ten pollution sources, the contribution ratios from the rural population (59.44%), pigs (14.40%), and arable land (10.52%) ranked as the top three sources. This study provides information that decision makers and planners can use to develop sustainable measures for the prevention and control of NPS pollution in semi-arid regions.

Assessment of Regional Ecosystem Health-A Case Study of the Golden Triangle of Southern Fujian Province, China

Intensifying urbanization and rapid population growth in Fujian Province, China, has caused pollution of air and water resources; this has adversely impacted ecosystems and human health. China has recently begun pursuing a massive infrastructure and economic development strategy called the Belt and Road Initiative, which could potentially cause further environmental damage. Evaluations of ecosystem health are therefore a first step towards identifying the potential impacts from the development and planning sustainable development strategies in the Golden Triangle of Southern Fujian. To this end, our study analyzed landscape patterns and evaluated ecosystem health in this region. We used an index system method to develop a pressure–state–response (PSR) model for assessing the region’s ecosystem health. We found that: (1) the landscape type with the greatest area in the study region is cultivated land and there were no areas that were undisturbed by human activity; (2) the overall ecological health of the region is good, but there is distinct variation across the region. This study incorporates the landscape pattern into an evaluation of ecosystem health. Using counties as evaluation units, we provide a general evaluation index for this scale. The methods reported here can be used in complex ecological environments to inform sustainable management decisions.