WITHDRAWN: A preliminary assessment on spatial prioritization for integrated urban flood management based on source tracking method.

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Plant functional traits explain long-term differences in ecosystem services between artificial forests and natural grasslands.

Declining ecosystem services have prompted numerous studies aiming at developing more sustainable management practices for vegetation restoration. Advances in functional ecology indicate that the sustainable management of afforestation ecosystems should be performed based on plant functional traits, which provides pivotal knowledge for long-term sustainable vegetation restoration. Currently, the mechanism of how plant functional traits affect long term ecosystem services in restored areas is still unclear.

Evaluating the relationship between groundwater quality and land use in an urbanized watershed.

Understanding the impact of urbanization on groundwater quality is critical. Effective water management requires understanding the relationship between land use and water quality. The study's goals were to compare the effects of land use, identify the types of land that impact hydrochemistry, and define how different land use affects water quality.

Joint Risk Analysis of Extreme Rainfall and High Tide Level Based on Extreme Value Theory in Coastal Area.

Extreme rainfall and high tide levels are the main causal factors of urban flood disasters in coastal areas. As complex interactions between these factors can exacerbate the impact of urban flood disasters in coastal areas, an associated flood risk assessment involves not only the estimation of the extreme values of each variable but also their probability of occurring simultaneously. With a consideration of the Shenzhen River Basin (China), this study used bivariate copula functions to quantitatively evaluate the joint risk of extreme rainfall and a high tide level.

Urban Flood Risk Assessment Based on Dynamic Population Distribution and Fuzzy Comprehensive Evaluation.

Floods are one of the most common natural disasters that can cause considerable economic damage and loss of life in many regions of the world. Urban flood risk assessment is important for urban flood control, disaster reduction, and risk management. In this study, a novel approach for assessing urban flood risk was proposed based on the dynamic population distribution, improved entropy weight method, fuzzy comprehensive evaluation method, and the principle of maximum membership, and the spatial distribution of flood risk in four different sessions or daily time segments (TS1-TS4) in the northern part of the Shenzhen River Basin (China) was assessed using geographic information system technology.

Assessment of the impact of urban water system scheduling on urban flooding by using coupled hydrological and hydrodynamic model in Fuzhou City, China.

With climate change and urbanization development, urban areas are facing more serious floods. As a result, hydrological and hydrodynamic models have recently shown a broad application prospect in urban flood simulating and forecasting. For the area with rich inland rivers, urban water resources can be effectively regulated and redistributed through river networks and hydraulic structures scheduling.

Identification of priority management areas for non-point source pollution based on critical source areas in an agricultural watershed of Northeast China.

Identification of critical source areas (CSAs) for non-point source (NPS) pollution is of great significance for environment governance and prevention. However, the CSAs are generally characterized as great spatial dispersion, and spatially heterogeneous precipitation has a great influence on the spatial distribution of nutrient yields. Therefore, we identify the CSAs for nutrient yields in an agricultural watershed of Northeast China at hydrological response units (HRUs) scale based on the Soil and Water Assessment Tool (SWAT), assess the impacts of spatially heterogeneity of precipitation on the identification of the CSAs, analyze the sensitivity of nutrient yields to precipitation by scenarios analysis method, and further identify priority management areas (PMAs) that have poor ability to retain nutrients.

Mapping of groundwater productivity potential with machine learning algorithms: A case study in the provincial capital of Baluchistan, Pakistan.

Although groundwater (GW) potential zoning can be beneficial for water management, it is currently lacking in several places around the world, including Pakistan's Quetta Valley. Due to ever increasing population growth and industrial development, GW is being used indiscriminately all over the world. Recognizing the importance of GW potential for sustainable growth, this study used to 16 GW drive factors to evaluate their effectiveness by using six machine learning algorithms (MLA's) that include artificial neural networks (ANN), random forest (RF), support vector machine (SVM), K- Nearest Neighbor (KNN), Naïve Bayes (NB) and Extreme Gradient Boosting (XGBoost).

Influences of Shifted Vegetation Phenology on Runoff Across a Hydroclimatic Gradient.

Climate warming has changed vegetation phenology, and the phenology-associated impacts on terrestrial water fluxes remain largely unquantified. The impacts are linked to plant adjustments and responses to climate change and can be different in different hydroclimatic regions. Based on remote sensing data and observed river runoff of hydrological station from six river basins across a hydroclimatic gradient from northeast to southwest in China, the relative contributions of the vegetation (including spring and autumn phenology, growing season length (GSL), and gross primary productivity) and climatic factors affecting the river runoffs over 1982-2015 were investigated by applying gray relational analysis (GRA).

[Quantitative Analysis of the Correlation Between Macrobenthos Community and Water Environmental Factors and Aquatic Ecosystem Health Assessment in the North Canal River Basin of Beijing].

Macrobenthos can reflect the cumulative effect of various ecological threats on the water environment and are closely related to the health of river ecosystems. In this study, taking the North Canal River basin, a typical basin in Beijing, as an example, ecological data from 34 stations were investigated in the summer of 2015. Characteristics of the macrobenthos communities were analyzed, and driving environmental factors were identified using typical correspondence analysis.

Prediction of chemical reproductive toxicity to aquatic species using a machine learning model: An application in an ecological risk assessment of the Yangtze River, China.

The endocrine disrupting chemicals (EDCs) have been at the forefront of environmental issues for over 20 years and are a principle factor considered in every ecological risk assessment, but this kind of risk assessment faces difficulties. The expense, time cost of in vivo tests, and lack of toxicity data are key limiting factors for the ability to conduct ecological risk assessments of EDCs to aquatic species. In this study, a machine learning model named the support vector machine (SVM) was used to predict the reproductive toxicity of EDCs, and the performance of the models was evaluated.

[Impact of Spatial Heterogeneity of Precipitation on the Area Change in Critical Source Area of Non-point Sources Pollution].

Aiming at non-point sources pollution in the agricultural areas with large topographic fluctuations and spatial differences in precipitation, a SWAT model was used to evaluate the spatial variations in the critical source areas (CSAs) of total nitrogen (TN) and total phosphorus (TP) under two precipitation scenarios, i.e., heterogeneous precipitation and uniform precipitation.

Assessment of urban flood susceptibility using semi-supervised machine learning model.

In order to identify flood-prone areas with limited flood inventories, a semi-supervised machine learning model-the weakly labeled support vector machine (WELLSVM)-is used to assess urban flood susceptibility in this study. A spatial database is collected from metropolitan areas in Beijing, including flood inventories from 2004 to 2014 and nine metrological, geographical, and anthropogenic explanatory factors. Urban flood susceptibility is mapped and compared using logistic regression, artificial neural networks, and a support vector machine.

Priorization of River Restoration by Coupling Soil and Water Assessment Tool (SWAT) and Support Vector Machine (SVM) Models in the Taizi River Basin, Northern China.

Identifying priority zones for river restoration is important for biodiversity conservation and catchment management. However, limited data due to the difficulty of field collection has led to research to better understand the ecological status within a catchment and develop a targeted planning strategy for river restoration. To address this need, coupling hydrological and machine learning models were constructed to identify priority zones for river restoration based on a dataset of aquatic organisms (i.

[Health Assessment of the Stream Ecosystem in the North Canal River Basin, Beijing, China].

With increasing urbanization, the stream ecosystem in Beijing has faced great challenges. Phytoplankton, benthic macroinvertebrates, and water quality were investigated based on 25 sampling sites in the North Canal River basin in July 2015, and the quality of the habitat was assessed in situ. A total of 22 metrics, including aquatic organism, hydrology, water quality, and habitat, were calculated to be the candidate indicators.

A systematic approach for watershed ecological restoration strategy making: An application in the Taizi River Basin in northern China.

Aiming to protect freshwater ecosystems, river ecological restoration has been brought into the research spotlight. However, it is challenging for decision makers to set appropriate objectives and select a combination of rehabilitation acts from numerous possible solutions to meet ecological, economic, and social demands. In this study, we developed a systematic approach to help make an optimal strategy for watershed restoration, which incorporated ecological security assessment and multi-objectives optimization (MOO) into the planning process to enhance restoration efficiency and effectiveness.

Mapping flood susceptibility in mountainous areas on a national scale in China.

Mountainous terrain covers nearly half of China and is susceptible to floods, which can lead to substantial losses of human life and property. Historical flooding records from government bulletins and newspapers, the only available information regarding floods that have occurred in some mountainous areas, are valuable for understanding flood disaster mechanisms in these regions. In this study, the flood susceptibility in mountainous regions in China was mapped based on historical flooding records from 1949 to 2000.

Development of a multimetric index based on benthic macroinvertebrates for the assessment of urban stream health in Jinan City, China.

Assessment of the health of urban streams is an important theoretical and practical topic, which is related to the impacts of physiochemical processes, hydrological modifications, and the biological community. However, previous assessments of the urban water quality were predominantly conducted by measuring physical and chemical factors rather than biological monitoring. The purpose of this study was to develop an urban stream multimetric index (USMI) based on benthic macroinvertebrates to assess the health of aquatic ecosystem in Jinan City.

Global assessment of nitrogen losses and trade-offs with yields from major crop cultivations.

Agricultural application of reactive nitrogen (N) for fertilization is a cause of massive negative environmental problems on a global scale. However, spatially explicit and crop-specific information on global N losses into the environment and knowledge of trade-offs between N losses and crop yields are largely lacking. We use a crop growth model, Python-based Environmental Policy Integrated Climate (PEPIC), to determine global N losses from three major food crops: maize, rice, and wheat.

Estimating parameters of the variable infiltration capacity model using ant colony optimization.

Because hydrological models are so important for addressing environmental problems, parameter calibration is a fundamental task for applying them. A broadly used method for obtaining model parameters for the past 20 years is the evolutionary algorithm. This approach can estimate a set of unknown model parameters by simulating the evolution process.

Assessing the effects of changes in land use and climate on runoff and sediment yields from a watershed in the Loess Plateau of China.

The changes in runoff and sediment load in the Loess Plateau of China have received considerable attention owing to their dramatic decline during recent decades. In this paper, the impacts of land-use and climate changes on water and sediment yields in the Huangfuchuan River basin (HFCRB) of the Loess Plateau are investigated by combined usage of statistical tests, hydrological modeling, and land-use maps. The temporal trends and abrupt changes in runoff and sediment loads during 1954-2012 are detected by using non-parametric Mann-Kendall and Pettitt tests.

Changes in Remotely Sensed Vegetation Growth Trend in the Heihe Basin of Arid Northwestern China.

The Heihe River Basin (HRB) is the second largest inland river basin in China, characterized by high diversity in geomorphology and irrigated agriculture in middle reaches. To improve the knowledge about the relationship between biotic and hydrological processes, this study used Global Inventory Modeling and Mapping Studies Normalized Difference Vegetation Index (NDVI) data (1982-2006) to analyze spatiotemporal variations in vegetation growth by using the Mann-Kendall test together with Sen's slope estimator. The results indicate that 10.

A new framework to evaluate ecosystem health: a case study in the Wei River basin, China.

Due to the rapid growth of the population and the development of economies in the Guanzhong district, central China, the river ecosystem is gradually deteriorating, which makes it important to assess the aquatic ecosystem health and take measures to restore the damaged ecosystem. An index of catchment ecosystem health has been developed to assist large-scale management of watersheds by providing an integrated measure of ecosystem health, including aquatic and terrestrial ecosystem. Most researches focus on aquatic ecosystem or terrestrial ecosystem, but little research integrates both of them to assess the catchment ecosystem health.