平原河网区降雨径流污染负荷测算——以太湖流域望虞河西岸为例

如何精细量化降雨径流污染负荷是流域尺度实现面源精准治污全过程控制的重要前提.本研究以水污染较为严重的望虞河西岸综合示范区为例,通过开展不同土地利用类型的降雨观测实验,修正SCS-CN模型中的初损率,并基于土地利用类型遥感解译和降雨径流污染物浓度测定,精细刻画降雨径流中总磷(TP)、总氮(TN)、氨氮(NH3-N)、化学需氧量(COD) 4类主要污染物的时空分布格局.结果表明:研究区绿地和农田、硬质地表的降雨初损率分别为0.3和0.9;径流深、污染负荷与降雨深之间存在显著的正相关性.随着降雨量逐年递减,研究区降雨径流中TP、TN、NH3-N、COD四类污染物的负荷量分别从2017年的190、1359、445和16041 t减少至2019年的118、949、314和11250 t;单位面积TN和COD负荷最高的用地类型是农村住宅用地,草地的四种污染物单位面积负荷均最低,林地次之.相关研究结果为望虞河流域水污染控制提供了基础数据,也为定量测算平原河网区面源污染负荷提供了方法参考.     

巢湖流域塘西河上游分流制系统降雨径流污染特征及初期冲刷效应

研究城市径流水质变化及初期冲刷效应对控制与治理城市径流污染具有重要指导意义.对塘西河上游6次降雨径流水质水量进行监测分析,计算次降雨径流平均浓度(EMC)和单位面积次降雨径流污染负荷(EPL),作M(V)曲线图研究初期冲刷现象.结果表明:降雨径流中悬浮物(SS)、化学需氧量(CODCr)和总磷(TP)的EMC值相对较大;SS的EMC值波动最为显著;总氮(TN)、TP、COD_(Cr)、SS间的EMC值均呈正相关;TN的EMC值与降雨量呈负相关性.各污染物EPL值与各降雨特征间均呈正相关性,经估算2015年研究区在6-8月共有10.38 tTN、2.29 tTP、1022.43 t SS、161.70 t CODCr和5.18 t NH_3-N随降雨径流排入巢湖;降雨量和雨前干期是城市径流污染的主要影响因素;以FF5050为初期冲刷效应判别依据,5种污染物均有初期冲刷效应出现,冲刷程度表现为SSCODCrTPTNNH_3-N;各水质指标的初期冲刷强度与降雨特征之间无相关性;雨型对初期冲刷现象影响较大;当降雨强度达1.36 mm/h即有径流汇集流出时开始截流,截流时间取440 min,截取的最大径流量取224319.14 m~3.     

城市水系统理论及其模型研制与应用

城市水系统理论是流域水系统科学在城市尺度的拓展,为解决城市化引起的人水关系失衡和突出水问题(内涝、黑臭和水污染、生态退化等)提供了新的系统化解决方案.现有城市水系统相关研究大多关注水循环单一过程,对水循环及其伴生的物质循环、水生态以及人文等过程互馈机制仍需进一步探索.本文以流域水系统科学和水循环理论为基础,发展了城市水系统的概念、理论和技术体系;以城市多种下垫面条件下时变增益降雨-径流模型为核心,耦合自然-社会水循环及其伴生的水环境、水生态等过程和多尺度海绵措施的影响,研发了城市水系统5.0模型,实现了源头降雨-径流-面源污染负荷、排水管网系统水量水质转输、末端调蓄和净化、社会经济水循环、水系统评估和调控等五大关键模拟功能,成果已在武汉市开展示范应用.结果表明:城市水系统应以城市及其联系的河湖为研究对象,探索城市自然-人工侧支水循环和外江调蓄等耦合,以及社会经济发展、海绵措施对水量-水质-水生态等过程的调控机制.研发的城市水系统5.0模型很好地模拟了城区降雨-径流过程、水体总氮和总磷浓度、社会经济发展特征指标等.与实测数据对比,所有降雨-径流场次的相关系数和纳什效率系数分别处于优秀和良...     

设施农业生产区降雨径流和氮磷输出特征及模拟——以滇池东岸花卉大棚种植区为例

为掌握滇池流域花卉大棚种植区的非点源污染特征,提高和改善滇池水环境质量,本研究选取呈贡县斗南村花卉大棚种植区作为研究对象,在实测降雨径流数据的基础上,通过建立Storm Water Management Model模型分别对全年连续降雨条件下和典型设计降雨条件下的降雨径流水质、水量进行了模拟.研究结果表明:1)模型的流量、化学需氧量(COD_(Cr))、悬浮物(SS)、总氮(TN)和总磷(TP)的Nash-Sutcliffe效率系数分别为0.858、0.835、0.803、0.712和0.752,能够较好地模拟研究区域的水质、水量变化.2)研究区域的平均径流系数为0.59,CODCr、SS、TN和TP的单位面积负荷率分别为118.34、82.90、54.64和5.46 kg/(hm~2·a),TN和TP是主要控制的污染物.3)各污染物浓度峰值的出现时间均早于流量峰值出现的时间,因此对滇池东岸花卉大棚种植区应进行污染物尤其是TP、TN浓度与流量错峰控制.     

太湖西苕溪流域径流过程的模拟

西苕溪是太湖集水域的一个主要流域,研究西苕溪流域径流过程及污染物产出对了解太湖水文水质变化以及开展周围其它流域研究工作具有重要意义．作为研究的第一步,采用集总式模型LASCAM建立了西苕溪流域径流模型．以流域内2个水文观测站1968-1988年日径流观测数据对模型作了率定．率定效果满意,模拟日、年径流量与观测值吻合良好．在流域资料不够充分的情况下,模型能获得较为理想的模拟效果,说明所采用的模型适用于数据不足区域．模拟还揭示,西苕溪流域径流产生可能以饱和地面径流机制为主．近河道浅层饱和土体的水位与降雨量相关性好,呈现出明显的日波动周期;而深层地下水位呈年波动周期,在旱季和雨季,水位呈明显的降落和上升趋势．这些发现为进一步细化径流模型以及建立污染物输移模型奠定了基础．     

基于SWAT模型的南四湖流域非点源氮磷污染模拟

本文利用SWAT模型结合实测数据,对南四湖流域2001-2010年年均非点源氮磷污染进行模拟,分析了南四湖流域非点源氮磷负荷空间分布特征,计算各河流流域对南四湖湖区污染的贡献率,并对非点源氮磷污染严重的关键区进行识别.研究表明:(1)先模拟湖东和湖西的两个典型小流域的非点源氮磷污染,并将模型推及整个南四湖流域,该方法不仅提高了计算效率,且得到了较好的模拟结果.通过对比发现,湖东的模拟效果要好于湖西,一定程度上说明SWAT模型在起伏较大的地区能取得更高的精度.(2)南四湖流域非点源氮磷污染严重,几乎所有区域的氮负荷超标,40%以上的区域磷负荷超标严重.湖东非点源氮磷污染较湖西严重,其中洸府河流域是南四湖湖区非点源氮磷污染的主要贡献者.(3)通过对径流量、泥沙负荷、氮负荷、磷负荷的相关分析可以得出,南四湖流域非点源氮负荷以溶解态为主,随径流进入水体;非点源磷负荷以吸附态为主,随泥沙进入水体.     

基于四维变分同化法的巢湖流域南淝河水质模拟

针对河流模拟中未知不确定性源对模拟精度的影响,以巢湖流域南淝河为研究对象,建立了基于四维变分同化方法的南淝河干流水质模型,研究了含未知污染源的南淝河水质过程模拟.模型以未知污染负荷的动态变化过程为控制变量,通过同化沿河不同断面的逐日水质监测数据,识别不同河段的逐日入河污染负荷过程来实现水质过程的模拟,改变了常规模型模拟需提前预知并输入污染负荷的应用前提.模拟结果表明,采用四维变分同化方法的水质模拟结果有明显改进,重点河段水质模拟的纳什效率系数从小于0提高到0.5以上.识别的入河污染过程与降雨过程波动总体一致,证实南淝河的入河污染与降雨过程密切;同时,模型也可识别异常的入河负荷,提高模型对水环境问题的诊断分析能力.该方法可推广应用于复杂河流系统,为巢湖等流域污染来源定量解析、水质预测预警及污染管控提供支持.     

气候变化对沅江流域径流影响研究

温室气体排放量增加造成气候变化,对全球资源环境产生重要影响.本文在水量平衡基础上,建立考虑气象要素和地形变化的月水文模型,利用实测径流资料对模型在时空尺度上进行验证.利用全球气候模型(GCMs)预测的未来气候变化情形,对处于湿润区的沅江流域径流过程进行预测.分析结果表明,该区域径流过程对降雨和气温变化十分敏感.根据英国Hadcm2模型对本世纪中叶气候变化预测结果,沅江流域未来年降雨量减少0.43%气温升高1.55℃,丰水期降雨增加,而枯水期将有较大幅度减少.年径流量相应减少6.8%,丰水期径流量增大11%,枯水期径流减少47%,不利于防洪和水资源开发利用.     

洱海流域低污染水类型、污染负荷及分布

为科学、合理地评估湖泊流域低污染水的类型及其污染负荷,以洱海流域为例,系统研究低污染水的概念及类型,确定了低污染水调查方法,并分析了洱海流域低污染水的来源、类型、产生量、污染物量和分布特征.结果表明,洱海流域低污染水主要包括污水处理厂处理尾水、城镇地表径流、农田排水(含村落地表径流)3种主要类型,产生量为20069×104m3/a.由低污染水带来的总氮(TN)负荷为1393 t/a,总磷(TP)负荷为77 t/a.从空间分布上看,洱海流域西部和北部片区低污染水TN、TP负荷比例最大,分别达到88%和87%,因此应主要针对西部和北部片区特点制定洱海流域低污染水控制措施.     

坡地土壤降雨入渗性能的径流-入流-产流测量方法与模型

坡地土壤的降雨入渗性能对于水文过程、作物水分利用、灌溉管理、土壤侵蚀等方面的研究和实践非常重要. 提出了测量坡地降雨条件下土壤入渗能力的径流/入渗方法. 依据水量平衡原理, 根据径流在坡面上的推进过程和有积水情况下积水深度随时间的变化过程推导得到了计算土壤入渗率(入渗能力)的数学模型. 采用两种工况: 雨强为20 mm/h、坡度0°和雨强60 mm/h、坡度20°, 径流/入渗坡面长度比均为1:1测量土壤入渗性能. 还用双环入渗仪测量了入渗性能用于比照. 用含水量10%的粘黄土进行室内试验, 获取了相关的数据, 并据此计算得到了两种工况的降雨入渗率曲线. 结果表明, 这种新方法可以很好地表征土壤入渗性能的概念, 并能获得很高的初始入渗能力. 分析了这种测量方法和计算模型的合理性. 采用降雨量、入渗量对比方法, 计算了上述两种工况的测量误差各为1.82%/1.39%和4.49%/3.529%(试验/模型), 说明了该方法的测量精度. 由于初始阶段供水能力的限制和土壤团聚体崩解的影响, 双环入渗仪测量得到的瞬态和稳定入渗能力均远小于用该方法测量得到的结果. 本方法可以克服以往降雨器和双环入渗仪方法的不足, 可以用于测量坡地降雨/径流/土壤侵蚀等因素影响下的整个降雨入渗过程曲线. 为相关研究提供了有力的工具.     

NUTRIENT LOAD ESTIMATION METHODS FOR RIVERS

Pollutant load estimation is essential for watershed management and water pollution control. For most watersheds, only sparse water quality measurements (e.g. monthly data) are available. The influence of input data on the accuracy of non-point source pollution load estimation is studied using the water quality and stream flow data from a small watershed in Hong Kong. Comparison and analysis of the results using 8 different methods show that the accuracy of stream-flow runoff is the single most important factor for the calculation of pollutant load. Based on the results, the stream flow correction coefficient is advanced to provide a more reliable load estimation. The improved method of pollutant load estimation can be easily applied in practice since the stream-flow runoff can be measured by hydrological station or estimated with various hydrological methods.     

The non-point source pollution in livestock-breeding areas of the Heihe River basin in Yellow River

A GIS-based distributed soil and water assessment tools (SWAT) model was used to simulate the runoff, sediment yield and the load of the non-point source pollution in the Heihe River basin, which is a tributary and main water supply source of the Yellow River. It is a typical stockbreeding area, and its industry and agriculture are not well developed. The main pollution source of the Heihe River was livestock related non-point source pollution. With GIS and remote sensing techniques, a database of non-point source pollution in the Heihe River basin was established. The SWAT model was parameterized for this area. The pollution load and transportation rules such as nitrogen were illustrated. After several years of hard work, the situations of point source pollution were more and more accurate. This paper provided an effective way to assess and calculate the pollution load in the wide agriculture area in China. With the help of historical data formulated parameters, the non-point source load and the theory of pollution load distribution were illustrated about the Heihe River basin. In 2000, the soluble N load in this area was 1.06 × 106 kg. By the simulation, the main pollution sources were in the south east of the basin, where the pasturing areas located in the south-east of Ruoergai County and in north of the Hongyuan County.     

Hydrological and associated pollution load simulation and estimation for the Three Gorges Reservoir of China

This study demonstrates an integrated study by coupling a NPS pollution load estimation sub-model with a distributed hydrological model to simulate the hydrological processes and associated pollution load processes in the Three Gorges (TG) Reservoir which is the largest water conservancy project in China, and further estimates the pollution loads and their responses to rainfall changes. The distributed hydrological model Easy Distributed Hydrological Model (EasyDHM) is featured as containing easy rain-runoff generation processes, comprehensive pre-process and post-process modules. Based on EasyDHM, this study develops a NPS pollution load estimation sub-model Easy Distributed Non-Point source evaluation sub-model taking both point source (PS) and NPS pollution into consideration. Through the application of the models in the TG area, this study clarifies the mechanism and characteristics of NPS pollution and estimates the pollution loads in the region. This study could provide technical support for the establishment of Best Management Practices for NPS pollution in the region, and references for the government during the processes of formulating and implementing decision-makings on pollution control and comprehensive management in the TG area.     

一种水污染的综合控制模型

本文将水质预测及水污染控制措施有机地结合,选取水环境容量和污染指数作为水污染控制的参数,这样,一给对流－扩散水质方程的求解除就是实现本研究目的的关键,本研究彩和的模型在现有的水质模型基础上有所改进,因为其采用四点隐格式对水质进行预测,推求可接给污染物的环境容量值有为保证水质而陷定的污染物浓度值,从而制定相应的水污染控制措施,为整体考虑各种污染物的情况,建议彩和河流的污染指数进而推求综合污染指数,总之,本研究为水质保护提供了科学的计算方法,该法对水污染及污水对河道水质的影响是实用有效的。     

基于EFDC模型的河道型水库藻类生长对流域污染负荷削减的响应——以广东长潭水库为例

将环境(EFDC)模型应用于广东梅州的河道型水库——长潭水库,经过模型的验证,建立长潭水库水生态数学模型,模拟出水库在现状污染负荷下的藻类生长情况,以叶绿素a浓度为指标,研究水库在丰水年与枯水年富营养化改善程度对不同流域污染削减方案的响应关系.结果表明:现状污染负荷削减10%,在丰水年库尾、库中和库首点位的叶绿素a平均浓度分别降低13.99%、12.00%和10.35%;枯水年3个代表点位叶绿素a平均浓度分别下降8.42%、5.63%和2.10%.污染削减20%的情况下,丰水年3个代表点位的叶绿素a浓度分别降低26.78%、19.25%和17.04%,枯水年对应的降低幅度分别为11.72%、7.97%和5.12%;库尾地区表现出河道的特征,在污染负荷削减的情况下藻类生长能够受到有效遏制,库首地区则表现出湖泊的特性,枯水年这一特征表现更加突出,污染削减20%的情况下,叶绿素a的平均浓度仅降低5.12%.     

Uncertainty based modeling of rainfall-runoff: Combined differential evolution adaptive Metropolis (DREAM) and K-means clustering

Simulation of rainfall-runoff process in urban areas is of great importance considering the consequences and damages of extreme runoff events and floods. The first issue in flood hazard analysis is rainfall simulation. Large scale climate signals have been proved to be effective in rainfall simulation and prediction. In this study, an integrated scheme is developed for rainfall-runoff modeling considering different sources of uncertainty. This scheme includes three main steps of rainfall forecasting, rainfall-runoff simulation and future runoff prediction. In the first step, data driven models are developed and used to forecast rainfall using large scale climate signals as rainfall predictors. Due to high effect of different sources of uncertainty on the output of hydrologic models, in the second step uncertainty associated with input data, model parameters and model structure is incorporated in rainfall-runoff modeling and simulation. Three rainfall-runoff simulation models are developed for consideration of model conceptual (structural) uncertainty in real time runoff forecasting. To analyze the uncertainty of the model structure, streamflows generated by alternative rainfall-runoff models are combined, through developing a weighting method based on K-means clustering. Model parameters and input uncertainty are investigated using an adaptive Markov Chain Monte Carlo method. Finally, calibrated rainfall-runoff models are driven using the forecasted rainfall to predict future runoff for the watershed. The proposed scheme is employed in the case study of the Bronx River watershed, New York City. Results of uncertainty analysis of rainfall-runoff modeling reveal that simultaneous estimation of model parameters and input uncertainty significantly changes the probability distribution of the model parameters. It is also observed that by combining the outputs of the hydrological models using the proposed clustering scheme, the accuracy of runoff simulation in the watershed is remarkably improved up to 50% in comparison to the simulations by the individual models. Results indicate that the developed methodology not only provides reliable tools for rainfall and runoff modeling, but also adequate time for incorporating required mitigation measures in dealing with potentially extreme runoff events and flood hazard. Results of this study can be used in identification of the main factors affecting flood hazard analysis.     

A two-layer model for studying 2D dissolved pollutant runoff over impermeable surfaces

Dissolved pollutants in stormwater are a main contributor to water pollution in urban environments. However, many existing transport models are semi-empirical and only consider one-dimensional flows, which limit their predictive capacity. Combining the shallow water and the advection–diffusion equations, a two-dimensional physically based model is developed for dissolved pollutant transport by adopting the concept of a ‘control layer’. A series of laboratory experiments has been conducted to validate the proposed model, taking into account the effects of buildings and intermittent rainfalls. The predictions are found to be in good agreement with experimental observations, which supports the assumption that the depth of the control layer is constant. Based on the validated model, a parametric study is conducted, focusing on the characteristics of the pollutant distribution and transport rate over the depth. The hyetograph, including the intensity, duration and intermittency, of rainfall event has a significant influence on the pollutant transport rates. The depth of the control layer, rainfall intensity, surface roughness and area length are dominant factors that affect the dissolved pollutant transport. Finally, several perspectives of the new pollutant transport model are discussed. This study contributes to an in-depth understanding of the dissolved pollutant transport processes on impermeable surfaces and urban stormwater management.