A Combination Model for Quantifying Non-Point Source Pollution Based on Land Use Type in a Typical Urbanized Area

Characterizing nitrogen deposited on urban road surfaces: Implication for stormwater runoff pollution control

Nitrogen (N) is one of the most important pollutants on urban road surfaces. Understanding the N deposition forms, load characteristics, and influential factors can help to provide management and control strategies for road stormwater runoff pollution. This study focuses on a highly urbanized area in Guangzhou, China, and presents the characteristics of both dissolved and particulate N deposition forms as well as their correlations with land-use types and traffic factors. In addition, an artificial neural network (ANN) based classification model is utilized to estimate N pollution hotspot area and total nitrogen (TN) flux from road to receiving water bodies. The results showed that N on urban road surfaces mainly existed in the form of particulate organic nitrogen. Land use types dominated by residential area (RA) and urban village (UV) have higher TN build-up loads. Geodetector analysis indicated that land use has a greater impact on nitrogen build-up loads than traffic factors. Through classification and estimation using the ANN model, RA, and UV were classified as hotspot areas, and the TN flux from roads in the study area was calculated to be 3.35 × 105 g. Furthermore, it was estimated that the annual TN flux from roads in Guangzhou accounts for 19 % of the city's total urban domestic discharge. These findings are expected to contribute to the pollution control of stormwater runoff from urban road surfaces and provide valuable guidance for enhancing the ecological health of urban water environments.

Modeling canopy water content in the assessment for rainfall induced surface and groundwater nitrate contamination: The Bilate cropland sub watershed

Nitrate contamination in surface and groundwater remains a widespread problem in agricultural watersheds is primarily associated to high levels of percolation or leakage from fertilized soil, which allows easy infiltration from soil into groundwater. This study was aimed to predict canopy water content to determine the nitrate contamination index resulting from nitrogen fertilizer loss in surface and groundwater. The study used Geographically Weighted Regression (GWR) model using MODIS 006 MOD13Q1-EVI Earth observation data, crop information and rainfall data. Satellite data collection was synchronized with regional crop calendars and calibrated to plant biomass. The average plant biomass during observed plant growth stages was between 0.19 kg/m2 at the minimum and 0.57 kg/m2 at the maximum. These values are based on the growth stages of crops and provide a solid basis for monitoring and validating crop water productivity data. The simulation results were validated with a high correlation coefficient (R2 = 0.996, P < 0.0005) for the observed rainfall in the growing zone compared to the predicted canopy water content. The nitrate contamination index assessment was conducted in 2004, 2008, 2009, 2010, 2011, 2013, 2014, 2015, 2018 and 2020. Canopy water content and root zone seasonal water content were measured in (%) per portion as indicators of the NO-3-N-nitrate contamination index in these years (0.391, 0.316, 0.298, 0.389, 0.380, 0.339, 0.242, 0.342 and 0.356).

Evaluation of sustainable development capacity of water sources: a case study of China

The issue of water scarcity has drawn attention from all over the world. The coordination of the interaction between ecological and environmental development of water sources and socio-economic development is currently an essential issue that needs to be solved in order to safeguard the water resources environment for human survival. In this essay, we suggest a paradigm for assessing the sustainable exploitation of water resources. First, three ecological, economic, and social factors are investigated. Twenty essential evaluation indexes are then constructed using the Delphi approach, along with an index system for assessing the potential of water sources for sustainable development. The weights of each evaluation index were then determined using the combination assignment approach, which was then suggested. The coupled degree evaluation model of the capability for sustainable development of water sources was then developed. In order to confirm the viability and validity of the suggested model, the model was used to assess the Liwu River water source's capacity for sustainable growth in the context of the South-North Water Transfer in Shandong, China. It is believed that the aforementioned study would serve as a helpful resource when evaluating the capacity of water sources for sustainable development.

Spatial optimization of ecological ditches for non-point source pollutants under urban growth scenarios

Non-point source (NPS) pollution is regarded as the major threat to water quality worldwide, and ecological ditches (EDs) are considered an important and widely used method to collect and move NPS pollutants from fields to downstream water bodies. However, few studies have been conducted to optimize the spatial locations of EDs, particularly when the watershed experiences urbanization and rapid land-use changes. As land-use patterns change the spatial distribution of NPS loads, this study used a cellular automata-Markov method to simulate future land-use changes in a typical agricultural watershed. Three scenarios are included as follows: historical trend, rapid urbanization, and ecological protection scenarios. The spatial distributions of particulate phosphorus loads were simulated using the revised universal soil loss equation and sediment transport distribution model. The results suggested that the total particulate phosphorus (TP) load in the Zhuxi watershed decreased by 10,555.2 kg from 2000 to 2020, primarily because the quality and quantity of forests in Zhuxi County improved over the last 20 years. The TP load in Zhuxi watershed would be 2588.49, 2639.15, and 2553.32 kg in 2040 in historical trend, rapid urbanization, and ecological protection scenarios, respectively, compared with 2308.1 kg in 2020. This indicated that urban expansion increases the TP load, and the faster the expansion rate, the more the TP load. Consequently, the optimal locations of EDs were determined based on the intercepted loads and the period during which they existed during land-use changes. The results suggested that rapid urbanization would consequently reduce the space available for building EDs and also increase the cost of building EDs to control the NPS pollution in the watershed.

A review of non-point source water pollution modeling for the urban-rural transitional areas of China: Research status and prospect

China has experienced a rapid period of urbanization since the 1980s. Many traditional agricultural areas were transformed into the urban-rural transitional areas, in which both urban and rural characteristics exist. Non-point source pollution (NPSP) has become a major side effect of urbanization and agricultural production which caused wide public concerns. It is crucial to carry out research on identifying the spatiotemporal variation in NPSP in the urban-rural transitional area (especially in developing countries, e.g., in China), which is a prerequisite for improving water quality and guiding NPSP control efforts. Modeling approaches are great tools to provide quantitative information on NPSP and optimize the best management practices for NPSP control. We reviewed over twenty years of publications on NPSP modeling and applications in urban, rural and its transitional areas. The strengths and limitations of 20 commonly used NPSP models in China were concluded based on a brief introduction and the evolution history. Reporting the strengths and weaknesses of each NPSP model could enhance its utility in practice. In terms of the unique characteristics of urban-rural transitional areas, which are neither strictly urban nor rural, non-point source pollutants are often distinctly different between traditional pollutants from urban and agricultural areas since the great differences in the hydrological processes, and none of existing NPSP models are fully applicable to urban-rural transitional areas. Based on limited NPSP modeling studies in urban-rural transitional areas, the existing research insufficiency were technical and mechanism limitations of the model despite of numerous improvements in the past, concerns about simulation accuracy, limited investigations on new pollutants, and lack of monitoring data. Future development trend and concerns of NPSP models for urban-rural transitional areas were discussed, which could be of great help to the development of NPSP models and their applications in water quality management in the rapid urbanized China.

Monitoring the Landscape Pattern and Characteristics of Non-Point Source Pollution in a Mountainous River Basin

This study aimed to assess the relationship between the landscape patterns and non-point source (NPS) pollution distribution in Qixia County, China. The sub-basin classification was conducted based on a digital elevation model and Landsat8 satellite images. Water samples were collected from each sub-basin, andtheir water quality during the wet and dry seasons was estimated. The correlation between the landscape indices and water pollution indicators was determined by Pearson analysis. The location-weighted landscape contrast index (LWLCI) was calculated based on the "source-sink" theory. Qixia was further divided into five sections based on the LWLCI score to illustrate the potential risk of NPS pollution. The results showed that the water quality in Qixia County was generally good. Cultivated land, orchards, construction areas, and unused land were positively correlated with the water pollution index and weredesignated as the "source" landscape categories, while forests, grasslands, and water bodies, which were negatively correlated with water pollution, were the "sink" landscapes; the LWCI was high in 36.94% of the study area. In these areas, measures such as increasing vegetation buffer zones are necessary to decrease the sediment and nutrient loads carried by precipitation.