Nonpoint Source Pollution Model Research Articles

Characterization and prediction of soil hydraulic and solute transport parameters using a random forest model

AbstractTo effectively control nonpoint source pollution and predict its transport and load, understanding water and solute transport processes, patterns and mechanisms is essential. However, the measurement of water movement and solute transport parameters is usually a laborious and time‐consuming task. It is important to predict water movement and solute transport parameters from more readily available soil physical and chemical properties. In this study, a database of soil hydraulic and solute transport parameters containing information retrieved from 83 published studies on soil properties, land use, management measures, etc. was established to characterize and simulate soil water movement and solute transport processes. Our results showed that the soil particle composition was closely related to all soil hydraulic and solute transport parameters. As the soil texture changed from sand to clay, the soil residual water content (θr) obviously increased. The soil porosity was significantly positively correlated with θr, saturated water content (θs), van Genuchten parameter α, dispersity (λ) and retardation factor (R) and negatively correlated with van Genuchten parameter n (p < 0.01). The use of random forest models allowed the prediction of soil hydraulic and solute transport parameters by inputting common or even incomplete soil property parameters. The bulk density and particle composition jointly contributed 66% to the prediction of the soil hydraulic parameters and 44% to the prediction of the solute transport parameters. The pH exerted a notable impact on the solute transport parameters, especially dispersion coefficient (D), λ and R. The results may be useful in providing data support and facilitating the development of watershed nonpoint source pollution models.

A validation of WEPP water quality routines in uniform and nonuniform agricultural hillslopes

Current watershed-scale, nonpoint source pollution models do not represent the processes and impacts of agricultural best management practices on water quality with sufficient detail. A Water Erosion Prediction Project-Water Quality (WEPP-WQ) model was recently developed which is capable of simulating nonpoint source pollutant transport in nonuniform hillslope conditions such as those with BMPs. However, WEPP-WQ has not been validated for these conditions, and prior validation work only evaluated calibrated performance rather than uncalibrated performance, with the latter being most relevant to model applications. This study evaluated uncalibrated and calibrated model performance in two plot-scale, artificial rainfall studies. 179 observations were compared to corresponding WEPP-WQ simulations of runoff, sediment yield, and soluble and particulate nutrient forms for both nitrogen and phosphorus. Uncalibrated validation results were mixed for the different field conditions, model configurations, and prediction variables. Nash-Sutcliffe Efficiencies for uncalibrated simulations of uniform conditions were generally greater than 0.6 except for soluble nitrogen predictions which were poor. Simulations of nonuniform conditions were generally ‘unsatisfactory’ except for runoff predictions which were quite good (NSE = 0.78). Performance was improved substantially for almost all endpoints with calibration. Some exceptions to this occurred because the objective function for calibration was based on log-space differences so as to more equally-weight calibration of unsaturated conditions that tend to produce lesser runoff volumes and sediment yields. Calibrated results for both uniform and nonuniform conditions were generally ‘satisfactory’ or ‘good’ according to widely accepted model performance criteria.

An Overview of Non-Point Source Pollution Modeling: Current Status and Future Prospect

Non-point source (NPS) pollution control is an increasingly important topic in aquatic environment protection due to its significant adverse effect on water quality. Characterizing NPS pollution loads is crucial for preparing BMPs to improve water quality and protect the aquatic ecosystem. Modeling tools are commonly used for simulating NPS pollution in watersheds; however, the modeling process contains uncertainties and complications, which makes the prediction of NPS pollution loads challenging and complicated. To deal with this issue, significant progress has been made to address NPS pollution modeling problems in the past few decades. The current study reviews different approaches being used for NPS pollution modeling. In this context, the main methods in NPS modeling are described and classified into three categories. 1. Empirical models, 2. Physically based models, and 3. Simulation based optimization models. The present study contributes to fulfilling the gaps in the classification of NPS pollution modeling approaches and highlights the advantages and drawbacks of each approach in order to set a standard for choosing a proper simulation tool for estimating NPS pollution loads based on the limitations and requirements of the understudy circumstance

Impact of Riparian Buffer Zone Design on Surface Water Quality at the Watershed Scale, a Case Study in the Jinghe Watershed in China

This study was conducted to evaluate the impact of riparian buffer zones on water quality in the Jinghe watershed, China. To evaluate the effectiveness of riparian buffers in reducing sediments and nutrients in surface runoff, we employed two validated models: the agricultural non-point source pollution model (AnnAGNPS) and the riparian ecosystem management model (REMM). The AnnAGNPS was used to divide the catchment into homogeneous drainage areas and generate upland loadings for the REMM. The REMM model was then utilized to assess the impact of different riparian buffer designs on sediments and nutrient reduction in surface runoff. We tested five designs, including the recommended standard design by the United States Department of Agriculture (USDA). This design with 20 m herbaceous perennials next to the field (Zone 3), followed by a 20 m wide harvestable deciduous forest in the middle (Zone 2), and a 10 m wide non-harvestable deciduous forest adjacent to the river (Zone 1). We also evaluated alternative designs, such as removing Zone 3, removing Zone 2, and reducing the widths of the buffer zones further. For the entire Jinghe watershed, we calculated, compared, and analyzed the annual totals of water inflow, sediment yields, and dissolved nitrogen in surface runoff into and out of Zone 1, 2, and 3 for all the designs. The analysis indicated that the removal efficiency of sediments ranged from 85.7% to 90.8%, and the removal efficiency of dissolved nitrogen in surface runoff ranged from 85.4% to 91.9% for all the designs. It is also indicated that riparian buffer zones are highly effective in reducing sediments and nutrients in agricultural runoff, even with reduced buffer widths. This finding underscores the importance of implementing riparian buffer zones as a valuable approach in the agricultural intensive watershed with constraints for allocating for the creation of standard riparian buffers.

An improved non-point source pollution model for catchment-scale hydrological processes and phosphorus loads

Non-point source (NPS) pollutants may cause water quality deterioration and eutrophication, posing a significant threat to aquatic systems. Understanding and modelling surface and sub-surface hydrological processes and nutrient cycles are therefore essential for water resources management and pollution control. This paper presents a new hydrological-water quality model for application in humid and semi-humid catchments in China, considering both hydrological processes, and nutrient transport and transformation. The model divides the soil into three layers, and each layer is implemented with individual computational procedures for soil wetness and nutrient process. Nutrient transport is driven by hydrological processes and follows the same pathways as water flow in the model: surface runoff, infiltration, and outflow from individual soil layers. River channels are described separately with routines to account for the turnover of nutrients. Model parameters are selected according to literature/open-sourced data or estimated from soil texture or land use types. The model is applied to simulate the hydrological processes and phosphorus transport in the Tongyang River Basin in China and the model performance is confirmed by comparing the predicted discharge and total phosphorus concentrations with measured data at the catchment outlets of Tonghe River and Yanghe River over 3 years. Uncertainty analysis has been further carried out using the GLUE method to demonstrate sensitivity of the simulation results to the selection of model parameters. After model calibration, the predicted results are found to compare well with field observations in terms of flow discharge and total phosphorus concentration. From sensitivity analysis, it is found that the recession coefficient of channel system (CS) and the pollutant recession coefficient of surface runoff (pKS) are the most influential hydrological and water quality parameters that control the arrival time and duration of flood peak and nutrient concentration peak, respectively.

Understanding the spatiotemporal variability in nonpoint source nutrient loads and its effect on water quality in the upper Xin’an river basin, Eastern China

Understanding the spatiotemporal characteristics of major nonpoint sources (NPSs) are crucial for protecting river water quality in drinking water source areas. This study employed a geomorphology-based nonpoint source pollution (GBNP) model to simulate hydrological processes together with NPS pollutant transport and transformation processes from 1980 to 2019 in the upper Xin’an River basin, an important drinking water headwater. The simulations revealed the spatiotemporal characteristics of nitrogen and phosphorus loads and their influences on river water quality. The results showed that the long-term average total nitrogen (TN) and total phosphorus (TP) loads were 3219 kg∙km−2∙yr−1 and 293 kg∙km−2∙yr−1, respectively. The proportional coefficients for TN and TP entering the rivers from the watershed were 0.40 and 0.37. The TN and TP loads during the April to July flood season accounted for 65.0 % and 63.2 % of the annual total, respectively. Annual TN load was significantly correlated with annual runoff depth, soil erosion and TN input in the interannual variation, while the interannual variation of TP load was significantly correlated with annual runoff depth and soil erosion. The long-term average TN and TP loads showed spatial patterns similar to those of land use and runoff depth, respectively. The daily TN concentrations showed a clockwise hysteresis relationship with discharge during flood events, while the daily TP concentrations had a single positive correlation with discharge throughout a whole year. Without atmospheric N deposition, the average TN load would decrease from 3122 kg∙km−2∙yr−1 to 1266 kg∙km−2∙yr−1 in 2000–2009. The TN load from atmospheric deposition accounted for 65 %-71 % of the total load, which implies that river water quality protection must include local basin eco-environmental protection and air pollution control over broader areas. This study showed that the distributed modelling of hydrological and biogeochemical processes is crucial to understand the spatiotemporal variability in nonpoint source nutrient loads over the watershed and is helpful to identifying key factors affecting river water quality.

Assessing Soil Vulnerability Index classification with respect to rainfall characteristics

The Soil Vulnerability Index (SVI) uses widely available inputs from the SSURGO database to classify cropland into four levels of vulnerability to sediment and nutrient losses: Low, Moderate, Moderately High, and High. Previous work has identified inconsistencies in SVI assessments across the United States, possibly because neither precipitation amount nor intensity were included in the development of SVI. This study aimed to determine if rainfall characteristics influence the SVI classification and which ones are most critical. The objectives were to (1) evaluate the impact of precipitation characteristics on land vulnerability to sediment loss, and (2) evaluate if rainfall characteristics alter the degree of agreement between the simulated sediment yield and SVI classification. The study focused on four Conservation Effects Assessment Project (CEAP) watersheds in Ohio, Missouri, Mississippi, and Pennsylvania for which sediment yields were simulated using previously calibrated models. The models were run with input precipitation data from these four watersheds. In addition, in order to examine a wider range of precipitation characteristics, model runs were made for the same four watersheds utilizing precipitation data from two CEAP areas in Georgia and Maryland. Sediment yields for all the cropland units in four of the watersheds were simulated using the Soil and Water Assessment Tool or the Annualized Agricultural Nonpoint Source Pollution Model using 1985 to 2014 precipitation data from all six areas as inputs. Similarities and differences between precipitation characteristics such as precipitation amount, intensity, and rainfall erosivity R-factors were compared with the similarities and differences in simulated sediment loss. Results confirmed that SVI is a useful tool for relative ranking of cropland at risk of erosion within a region, as SVI and the model-based vulnerability classifications agreed for 55% to 100% of the watersheds’ subunits. However, model-based classification of field vulnerability could shift due to changes in precipitation characteristics. Thus, the range of soil loss for each vulnerability class can shift from one region to another. The results suggest that precipitation intensity or annual R-factor may help improve the correspondence between vulnerability and the range of expected soil loss.

The global progress on the non-point source pollution research from 2012 to 2021: a bibliometric analysis

BackgroundWith effective control of point source pollution, non-point source (NPS) pollution has been widely concerned as the primary reason for the improvement of global water environmental quality. Some bibliometric analysis related to NPS pollution has been carried out before the mid-2010s. Analyzing the research status and hot issues of NPS pollution in the past decade is important for guiding the control and management of NPS pollution in the future.ResultsA bibliometric analysis was conducted based on 3407 publications retrieved from the Web of Science during 2012–2021. China, USA and UK were the most productive countries. Sci. Total Environ, Environ. Sci. Pollut. Res, and Water were the most productive journals. The NPS pollutant, pollution types, driving forces, technology and the research object were retrieved from the keywords analysis. The common NPS pollutants of nitrogen, phosphorus, and heavy metals grabbed the highest attention, while the emerging contaminants have attracted increased attention. The migration and transformation of agricultural NPS pollution and urban NPS pollution driven by climate change and land use change were hot issues related to NPS pollution studies. Technologies related to the combination of 3S technology (RS, GIS, and GPS) and NPS pollution models, the sustainable control technologies, the technology of accurate traceability and automatic monitoring, and the comprehensive management plan were the important research areas related to NPS pollution. Although the research locations were mostly concentrated in the surface water and groundwater, the ocean and drinking water have great potential for future research.ConclusionsThis study illustrates the global focuses related to NPS pollution during 2012–2021 according to analyzing the publication outputs, source journals, source country, author, institution and the high-frequency keywords. Results demonstrated that the migration and transformation mechanism and ecological risk assessment for heavy metals and emerging pollutants, accurate traceability techniques, sustainable ecological restoration control techniques, and marine pollution have attracted rising attention. Additionally, developing countries will have a higher interest in NPS pollution in the future, because developed countries have already made great progress in controlling NPS pollution.

Review of Nonpoint Source Pollution Models: Current Status and Future Direction

Modelling tools are commonly used for predicting non-point source (NPS) pollutants and it is timely to review progress that has been made in terms of the development of NPS models. This paper: (1) proposes a systematic description of model framework and generalizes some commonly used models; (2) identifies the common challenges in model structure and applications; (3) summarizes the future directions of NPS models. Challenges in model construction and application are based on the following: (1) limitations in understanding specific NPS pollution processes; (2) model expansion to different scales; (3) data scarcity and its impacts on model performance; (4) prediction uncertainty due to model input, parameter and model structure; (5) insufficient accuracy for decision-making. Finally, this paper proposes future directions for model development, including: (1) a source–flow–sink framework for model development; (2) standardization for model input and parameter; (3) reliable decision support for environmental management. The findings of this review provide helps in the accurate prediction and management of NPS pollution around the world.

Improving the accuracy of nonpoint-source pollution estimates in inland waters with coupled satellite-UAV data

Quantitatively and accurately analyzing nonpoint-source (NPS) pollution is essential for efficiently preventing the input of NPS loads into inland waters. However, the accuracy of previous NPS pollution models is limited by the accuracy of ground parameter data. In addition, there are few effective methods that thoroughly verify modeling results at large scales. This paper presents a framework for accurate NPS pollution estimation by coupling satellite and unmanned aerial vehicle (UAV) monitoring data, and the results are verified by both field sampling and a newly developed inlet NPS pollution “observation” simulation method. Fractional vegetation coverage (FVC) data obtained by satellite were used to improve the accuracy of the runoff module of the framework. Satellite and UAV data were coupled to acquire livestock data, determine inlets, and identify reservoir buffer zones and vegetation types. These new data were then used to improve the accuracy of the livestock and runoff modules in the framework. The results show that the estimation accuracy of total nitrogen, total phosphorus, ammonia nitrogen, and chemical oxygen demand with FVC were improved by 39.96%, 69.29%, 54.05% and 47.22% (in relative error), respectively. The high-resolution livestock data acquisition improved the estimation accuracy of the NPS pollution load by 7–53%. The high-resolution inlet extraction improved the accuracy by 3–24%. The high-resolution buffer zone identification improved the accuracy with the estimated NPS pollutant concentration into reservoir decreasing by 60–99%. Finally, the high-resolution vegetation type identification improved the accuracy by 10–72%. The framework performs satisfactorily, which was verified based on the simulated NPS observations with an average relative error of 11.54–24.31%. We found that the FVC, livestock number, and inlet number are key parameters for NPS pollution modeling; the introduction of monthly variation in the FVC makes the modeled NPS pollution load much higher in areas with mature complex forested ecosystems or densely distributed vegetation but much lower in areas with sparsely distributed vegetation. The above methods provide a scientific reference for high-efficiency NPS pollution prevention in inland waters, laying a solid basis for decision-making regarding water quality management in data-scarce regions around the world.

An improved minimum cumulative resistance model for risk assessment of agricultural non-point source pollution in the coastal zone

Agricultural non-point source pollution (AGNPSP) is an important risk factor affecting the water environment. Among the areas where cropland NPSP occurs, the coastal zone should be of greater concern. Typhoons, heavy precipitation, and abundant rivers and ponds accelerate the transport process of AGNPSP to the offshore waters. It is urgent to construct a simple and accurate model to assess the risk of AGNPSP in the coastal zones. Thus, this study takes the nitrogen pollution from agricultural cultivation in the coastal zone of the Yellow River Delta as an example. A new minimum cumulative resistance (MCR) to agricultural non-point source pollution (AGNPSP-MCR) model is first proposed to simulate the transport process of cropland NPSP into the sea based on the “source-sink” theory in landscape ecology. Finally, the risk is assessed for AGNPSP transport into the sea. The results show the following. (1) The environmental factors of vegetation cover, rainfall erosivity, and soil erodibility are the three most important factors in pollution transportation, weighted 0.3433, 0.2608, and 0.2219, respectively, while the least influential factor is slope, with a weight of only 0.0053. (2) The minimum cumulative resistance of AGNPSP transportation shows a significant positive correlation with the distance to the river and sea, and is higher on the west sides away from the ocean, and smaller in the eastern coastal area near the sea. (3) Similarly, the regions facing serious AGNPSP risk are concentrated in the eastern coastal area, and the cropland area above medium risk was 252.72 km2, accounting for 47.57% of the total cultivated land area. (4) Compared with the traditional MCR model, the AGNPSP-MCR model takes into account the quantitative differences of the transport process characteristics of AGNPSP, and it is constrained by the topographical parameter, so the results of AGNPSP risk are more reliable. This study provides a new reference for risk assessments of AGNPSP in the coastal zones.

Simulation of water and nitrogen movement mechanism in cold regions during freeze-thaw period based on a distributed nonpoint source pollution model closely coupled water, heat, and nitrogen processes at the watershed scale.

The nitrogen cycle in cold regions during the freeze-thaw period is complex. Although previous studies have investigated the phenomenon of nitrogen transport and transformation, the underlying mechanisms are vague. Existing models have limitations in terms of loose coupling or weak physical mechanisms. Therefore, a new distributed nonpoint source pollution model, the water and energy transfer processes and nitrogen cycle processes model in cold regions, was developed in this study, with closely coupled water, heat, and nitrogen processes at the watershed scale. The model considered the driving effects of pressure, gravity, solute, and temperature potentials on water and nitrogen movement in soil and the transformation relationship among nitrogen forms. Physical evaluation and simulations were conducted for the Heidingzi River Watershed during two freeze-thaw periods: 2017-2018 and 2018-2019. The soil temperature absolute error was < 0.82℃. The relative errors in stratified liquid water, soil nitrogen content, river flow rate, and river nitrogen concentration were mostly < 10%. Nitrogen transport with water had an obvious "upward agglomeration effect" during the freezing period and a "concentrated release effect" during the thawing period, which was attributed to changes in soil water potential as the freezing front moved down. Disregarding the effects of solute potential and temperature potential will result in an underestimate of the outflow of pollutants during the thawing period. The model can be applied to reveal water quality deterioration in cold regions during thawing.

Coupling with high-resolution remote sensing data to evaluate urban non-point source pollution in Tongzhou, China

Urban non-point source (NPS) pollution has gradually become one of the important factors affecting the urban water environment. The quantitative evaluation of urban NPS pollution is the priority to identify key control area of urban NPS pollution. Current model applied in China is mainly focused on small-scale area, large-scale spatial continuous simulation is lacking. In this study A spatial continuous evaluation method coupled with high-resolution remote sensing data has been established and the method was applied to Tongzhou, China. With the spatial distribution of land-use type and built-up area which were been obtained by remote sensing technology, the accumulative and wash-off load of urban NPS nitrogen and phosphorus were estimated for the prominent problems of nitrogen and phosphorus nutrient pollution in the rivers in the study area. The main sources of urban NPS Nitrogen and phosphorus pollution are roof and road rainfall runoff respectively. Compared to other urban NPS pollution models, the method developed in this study can quickly realize spatial visualization assessment of urban NPS pollution and provide a means to estimate urban NPS loads in entire city or urban agglomeration, it is applicable for common urban NPS pollutants and also has advantages in areas without data.

基于径流路径的分布式面源污染模型研发与应用进展

PDF HTML阅读 XML下载 导出引用 引用提醒 基于径流路径的分布式面源污染模型研发与应用进展 DOI: 10.5846/stxb202103100655 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 中国科学院战略性先导科技专项（A类）（XDA2304040303） Progress on the development and application of a runoff pathway-based Spatially and Temporally distributed Model for Non-Point Source pollution Author: Affiliation: Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:精准刻画地表径流的路径及其所携带的面源污染物随径流的输移过程是准确估算面源污染入水体量、污染关键源区辨识和高效防控的关键，在我国以小农户种植为主、景观特征复杂的地理条件下尤为重要。鉴于目前常用的面源污染模型大都起源于国外，往往对径流路径的空间差异性及污染物陆面输移过程进行概化，介绍了一个基于径流路径的分布式面源污染模型（STEM-NPS）及其研发与应用进展。阐述了该模型的研发背景、模型原理和结构，说明了STEM-NPS模型对地表径流汇流及其所携带的污染物输移过程的精细化表达方法；介绍了该模型在不同地理环境及尺度的应用进展，展示了其在地块尺度的面源污染关键源区辨识，关键过程和关键影响因素解析及面源污染监管决策支持等方面的功能；探讨了STEM-NPS模型与其他常用模型的异同，并结合生态学研究和面源污染精准防控的需求，提出模型的应用前景及进一步发展的方向。 Abstract:Non-point source pollution models are useful tools to simulate pollution loads entering water bodies, identify critical source areas and assess best management practices. The accuracy and the reliability of the above information generated by models is highly determined by how a model delineates surface runoff pathways and how it simulates pollutant transport processes along the runoff pathways, which is especially important in complex watersheds with fragment landscapes. Agriculture in China is characterized with small and various types of fields in limited areas, which means fragment landscapes are common. Currently, widely used non-point source models are most developed in western countries, which usually ignore the heterogeneity of fine-scale runoff pathways and simulate terrestrial pollutant transport within a sub-watershed by a lumped approach. This paper presented a Spatially and Temporally distributed Model for Non-Point Source pollution (STEM-NPS) that simulates pollutant transport processes based on fine-scale runoff pathways. First, the background, development process and model theory of STEM-NPS was described. STEM-NPS was first published in international journals in 2017 while the development and modifications continue till right now. The model simulates runoff, nutrient loads and water quality on a grid cell basis and a daily time step. The hydrological module of STEM-NPS is the Distributed Hydrological Model for Watershed Mangement (DHM-WM) which delineates runoff pathways, simulate surface, subsurface and base flow and calculates runoff travel time along pathways. DHM-WM has two water balance routines:local routine is for watersheds dominated by infiltration-excess runoff while global routine is for watersheds with both infiltration-excess and saturation-excess runoff. The pollutant transport module of STEM-NPS simulates nutrient loads generated from source areas and loads entering water bodies with zero-order mobilization and first-order delivery functions respectively. Then, model application cases in different geographic regions and scales were presented. One case was in a plateau watershed in Yunnan province and the other case was in a plain county in Henan province. The application cases showed the model functions in tracking fine-scale runoff pathways, identifying fine-scale critical source areas, analyzing key processes and driving factors of pollutant losses, as well as how the model was used in an on-line support-decision system of non-point source pollution monitoring and control. After that, STEM-NPS was compared with some commonly used models such as SWAT, APEX, HSPF, AnnAGNPS, L-THIA, STEPL-WEB, CADA-ECM and SPARROW, specifically for their functions in identifying critical source areas and assessing best management practices (BMPs). Based on the comparison, application perspectives of STEM-NPS in ecology were proposed, such as assessing the impact of hydrologic connectivity on nutrient transport and analyzing social-economic development impact on water environment. Although with advantage in supporting fine-scale non-point source pollution control, the STEM-NPS model still needs further modifications, such as representing nutrient legacy effect in the nutrient transport module and developing a user-friendly BMP assessment module. 参考文献 相似文献 引证文献

流域水文模型在面源污染模拟与管控中的应用研究进展

PDF HTML阅读 XML下载 导出引用 引用提醒 流域水文模型在面源污染模拟与管控中的应用研究进展 DOI: 10.5846/stxb202109062508 作者: 作者单位: 作者简介: 通讯作者: 中图分类号: 基金项目: 国家重点研发计划(2021YFD1700600)；国家自然科学基金项目(42007362，51809177) Research of the HSPF model on nonpoint source pollution modeling and management：progresses and perspectives Author: Affiliation: Fund Project: National Key R&D Program of China；National Natural Science Foundation of China 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:面源污染是影响流域水环境和水安全的重要污染来源,对其进行有效防控需要对其负荷以及防控措施效果进行科学高效精准的预测。流域水文模型(Hydrological Simulation Program-FORTRAN,HSPF)具有突出的综合性和灵活性,是面源污染模型的典范。近年来,HSPF模型应用于我国流域面源污染相关的研究和实践有了飞速发展,但同样也面临着模型机理和参数本地化、模型构建精细化、模型结构不确定性较大等方面的挑战。围绕该模型在面源污染模拟与管控中的研究进展,对其在变化环境下的模拟方法和成果,以及应对参数识别、不确定性分析、措施效果评估和总量控制的思路和方法等方面进行了总结,并分析了现代化环境模拟形势下HSPF模型的延伸发展。结合模型相关研究的总结,强调了面向我国流域特色的本地化模型改进、服务河长制精细监管的大尺度精细化模拟、以及模型与大数据统计及人工智能耦合的互馈集合模拟等后续研究是需要重点关注的发展动向。 Abstract:Non-point source (NPS) pollution has become a major threat to watershed environment and security in recent decades. The occurrence and transport of NPS pollution include several dynamic processes which are characterized by randomness, complexity, uncertainty, etc. Existing monitoring network is not sufficient to accurately evaluate the contribution of NPS pollution and understand the underlying mechanisms. Efficient and sound assessment tools are needed to facilitate preventing and controlling NPS pollution. Nowadays many watershed models become increasingly popular to simulate, predict, and analyze NPS pollution processes and assist in decision makings for integrated watershed management. HSPF (Hydrological Simulation Program-FORTRAN) is one of the most comprehensive and flexible NPS models around the world. It has been developed and maintained mainly by the U.S. Environment Protection Agency and is highly recommended in flood-control planning and operations, water quality planning and management, conservation practices evaluation, etc. The HSPF model conceptualizes a watershed system into surface, soil, and stream segments to simulate the continuous, storm event, or steady-state behavior of both hydrologic and water quality processes in natural or manmade water systems. The model has proven its ability to be used with reasonable accuracy in diverse hydrologic regimes, which leads to its broad application worldwide. The research and practice of the HSPF model applied to watersheds in China have expanded rapidly in recent years, but the model is also facing challenges in terms of localization for model theory and parameters, refinement during the model setup process, and uncertainty embedded in the simulated results. Therefore, this paper focused on the research progress of the HSPF model in NPS pollution modeling and control by reviewing existing relative papers. The conceptualization principles of the HSPF model to simulate NPS pollution was first described. This was followed by extensive reviews of the modeling methods and application in changing environment, as well as the ideas and methods for parameter identification, uncertainty analysis, control measures evaluation and total emission control. The extended development of HSPF model under the modern environmental modeling situation was also summarized. PyHSPF and HSP2 as two representatives were specifically discussed in their improvement in compiling environment, data management, dynamic representation of watershed properties, parallel computing, and Application Program Interface. The suggested developments in future studies include: localization model improvement for China's watershed characteristics, large-scale refinement modeling to cope with the fine regulatory services of the river chief system, coupling with big data statistics and artificial intelligence for crossfeed ensemble modeling. 参考文献 相似文献 引证文献

Soil erosion assessment in Ethiopia: A review

Soil erosion is a critical problem affecting rural livelihoods in Ethiopia. Large numbers of studies have been undertaken to identify critical areas of soil loss and prioritize conservation options. With the advancement of geospatial analysis techniques, the use of spatially distributed soil erosion assessment options has become increasingly common. The lack of database and documentation related to soil erosion assessment undermines coordination leading to duplication of efforts and in some instances generating contradictory results. The purpose of this study is to (1) review existing knowledge related to the extent and spatial distribution of soil erosion, (2) document the associated methods employed to assess soil erosion, and (3) assess the spatio-temporal dynamics of soil erosion and the determinant factors in Ethiopia. The review shows that there are about 170 peer-reviewed papers published in scientific journals related to soil erosion in Ethiopia. In those scientific articles, 15 different approaches were used to assess soil loss and sediment yield at different scales. Considering the data set, soil loss rate in Ethiopia varies between 0 and 220 t ha^–1 y^–1, and sediment yield ranges between 2 and 70 t ha^–1 y^–1. Based on the database, the national average gross soil erosion rate is estimated to be 38 t ha^–1 y^–1, while the net sediment yield is about 26 t ha^–1 y^–1. Generally, the observed gross soil loss is slightly lower than the mean value from cultivated lands reported in previous estimates (42 t ha^–1 y^–1) by Hurni (1993). The estimate made using the Revised Universal Soil Loss Equation gives the highest soil loss (51 t ha^–1 y^–1), while that based on field-survey approaches gives the lowest (20 t ha^–1 y^–1). The highest average net soil loss rate (40 t ha^–1 y^–1) is obtained using plot-level measurements, while the lowest (18 t ha^–1 y^–1) is obtained using the AGricultural Non-Point Source pollution model. The highest average soil erosion rate is observed in the moist agro-ecological zone (57 ± 7.8 t ha^–1 y^–1), while the lowest is obtained in the submoist (23.6 ± 2.7 t ha^–1 y^–1) following the arid zone (28.8 ± 6.5 t ha^–1 y^–1). The wide range of soil erosion estimates imply spatio-temporal dynamics of soil erosion in the country, which is mainly a reflection of heterogeneity of the various sites, mainly associated with different values of cover and management factors. Such knowledge can enable making informed conservation decisions by focusing on critical hotspots.

Using Arc GIS to explore the impact of environmental and ecological factors on water body

As water pollution is more and more serious, ArcGIS is proposed to explore the impact of environmental and ecological factors on water. Taking the river water quality as the research object, this paper simulates and analyzes the endogenous and non-point source pollution and water quality through indoor physical model experiment, hydrological and water quality numerical model and water quality numerical model, and analyzes the impact of different environmental changes on river water quality and pollution sources from micro and macro perspectives. The main contents include: experimental study on the influence mechanism of overlying water velocity, disturbance and water temperature on sediment endogenous release, construction and simulation of watershed non-point source pollution model, construction and simulation of watershed river water quality model, as well as the impact of environmental change on river water quality and quantitative analysis of river pollution sources.

Performance of AnnAGNPS model in predicting runoff and sediment yields in Nan Province, Thailand

Land use changes such as deforestation and urban development influences the river discharge, soil erosion and sediment yield. It is important to evaluate tools which can be used to assess such impacts on water and sediment yield. Therefore, this study evaluated the Annualized Agricultural Non-Point Source Pollutant (AnnAGNPS) model's performance in simulating runoff and sediment loads in Nan Province, Thailand using seven years of continuous monitoring data. The river discharge and sediment yield data from 2011–2013 were used for calibration, and data from 2014–2017 were used for validation. Several input parameters were computed using methods suggested by other researchers and previous studies. In this study, the runoff curve number, soil erodibility factor (K), and RUSLE-C value were used to accurately simulate runoff and sediment loads. The results indicate that the model satisfactorily simulated runoff and sediment loads (R2 = 0.65 and NSE = 0.53 for runoff volume, and R2 = 0.62 and NSE = 0.60 for sediment yields). Moreover, the model estimated the total sediment yield, which contributed 12,932 hundred tons of material to the Nan River in 2017. The maximum sediment yield was obtained below the catchment (Na Noi sub-district, Na Noi district), which corresponds to areas with high crop densities. Cropland generated the highest soil erosion of all investigated land use (87.52% of total soil erosion). Thus, the AnnAGNPS model has the potential to use for investigating management practices to reduce soil erosion and controlling floods and droughts in Nan Province of Thailand.

Simulation of interception capacity of Nanhe initial rain storage tanks

River pollution sources are generally divided into point source, non-point source and internal source, non-point source pollution is mainly urban surface runoff. In this paper, the non-point source pollution model of SWMM in Nanhe region is constructed, and the water quantity and quality are verified by the measured data, and the verification results are in good agreement with the measured data. On this basis, the detention time and the interception amount of initial rain are analyzed. The results show that after intercepting the initial rainwater, the pollutants into the river are significantly reduced, and the lower the frequency is, the better the interception effect of the storage tank on the initial rainwater is. Comprehensive analysis shows that the overall removal rate of pollutants in each frequency of the four outlets of the storage tank can reach 37~39%.

Simulation of Runoff and Sediment Yield Using AnnAGNPS Model at Dawe Watershed, Eastern Hararghe, Ethiopia

The high erosion rates are mainly affecting the developing countries due to intensive cultivation, deforestation; extreme climate hazard, sediment transport and loss of agricultural nutrients were caused by unwise land use practices, intensive cultivation and improper management. Soil conservation is the only known way to protect the productive land. In this study a physically based watershed model, Annualized Agricultural Non-Point Source (AnnAGNPS) pollution model was applied to the Dawe River watershed for simulation of the runoff and sediment yield. The objectives were to estimate potential runoff and sediment yield and to recommend and design appropriate soil and water conservation measures on a sub watershed basis in Dawe watershed of east hararghe zone. Sensitivity analysis, model calibration and validation were also performed. Four highly sensitive parameters were identified and of which CN was the most sensitive one. For model calibration, model efficiencies of 0.742, -231.081 and 0.828 were observed for surface runoff, peak runoff rate, and sediment yield, respectively. The corresponding determination of coefficients was 0.825, 0.1669 and 0.848, respectively. Runoff and sediment yield were well predicted but, peak runoff rate was over predicted. Validation results produced model efficiencies NSE of 0.769, -73.801 and 0.718 for surface runoff, peak runoff rate and sediment yield, respectively. With coefficient of determination (R²) of 0.9215, 0.235 and 0.764 for runoff, peak runoff rate and sediment yield, respectively. Surface runoff and sediment yield simulation were well in the validation stage and peak runoff rate shows the same trend as calibration. Dawe watershed was divided in thirteen sub-watersheds. Runoff and sediment yield for each sub-watershed were quantified. Average annual watershed runoff, average annual soil loss and total annual sediment outflow from Dawe watershed was 194.48mm, 22.467 tons/ha/yr and 354215 tons/yr, respectively. In Dawe watershed, gully, rill and inter-rill erosions were identified as major problems. Thus, check dam and bench terrace designed and vegetative waterway are recommended for intensively cultivated crop land of Dawe watershed.