AnnAGNPS模型在潋水河流域产水、产沙的模拟评价

日益严重的土壤侵蚀造成了土地退化、水体污染等一系列的环境和生态问题,利用基于过程的数学模型已成为流域土壤侵蚀状况定量评价和控制的有效方法.利用美国农业部开发的流域尺度AnnAGNPS模型,设计了基于地形特征的cell离散方案,在多种地理数据采集和参数化的基础上,对江西兴国潋水河流域1991～2005年的径流、产沙过程进行了分布式计算机模拟.在对产水量进行径流滤波分析的基础上,分别对模型模拟的地表径流和产沙量进行了校正和验证.地表径流模拟结果多年平均相对误差为11.8%,确定性系数R2为0.94,产沙量模拟结果的多年平均相对误差为19.71%,确定性系数R2为0.77.表明AnnAGNPS能较好地模拟潋水流域年、月尺度的地表径流和产沙过程.地下径流模拟结果误差较大,其原因和地下径流模拟模块在潋水流域的适用性有待进一步研究检验.对潋水流域土壤侵蚀定量分析表明,潋水流域的年平均侵蚀模数为1 150.29.t(km2.a)-1,属于轻度侵蚀等级,流域内侵蚀较严重的区域集中分布于居民地附近和公路沿线,其水土流失与人类活动有很大关系.     

非点源污染模型AnnAGNPS在三峡库区林农复合小流域模拟效果评定

应用连续农业非点源污染AnnAGNPS模型(Annualized AGricultural NonPoint Source Model)模拟三峡库区林农复合小流域的径流、泥沙和营养物输出,以2003年和2004年的小流域观测数据对模型分别进行校准和验证,并以统计参量决定系数(R2)、Nash-Sutcliffe效率系数(E)和相对误差(VE)对模拟结果进行评定.结果表明,径流量模型模拟结果误差在可接受范围之内,模型校准期模拟值VE值为5.0%(R2=0.93,p<0.05),验证期内模型VE值为6.7%(R2=0.90,p<0.05);与径流模拟比较,泥沙模拟结果精度较低,校准期内模型VE值为15.1%(R2=0.63,p<0.05),验证期内模型VE值为26.7%(R2=0.59,p<0.05);次降水较小,产生径流和泥沙较少时,模型模拟值则偏高,反之则偏低.氮输出模拟决定系数R2值0.68(p<0.05),略高于磷输出模拟决定系数(R2=0.65,p<0.05).模型对径流输出的模拟精度高于对泥沙和营养物的输出模拟.在三峡库区农林复合小流域应用AnnAGNPS模型模拟农业非点源污染输出满足流域管理要求.     

基于AnnAGNPS模型四岭水库小流域氮磷流失特征的模拟研究

采用流域尺度的农业非点源污染模型——AnnAGNPS模拟预测苕溪流域四岭水库小流域氮磷流失情况,分析氮磷流失空间分布特征.结果表明,单位面积总氮、总磷流失量在空间分布上有一定的相似性,均呈现出南部大于北部,西部高于东部的特点.以竹林地为主的林地是氮磷输出的最主要来源,其对氮、磷流失总量的贡献率在90%以上.设定不施肥处理(CK)、适地养分管理(SSNM)、当地高产竹农普遍采用的施肥方法(FFP)这3种施肥方式对林地主要植被类型竹林进行情景分析,模拟结果表明,与FFP相比,SSNM在一定程度上减少了氮磷输出,其中溶解性氮和颗粒态氮流失量分别削减8.17%、4.33%,溶性磷和颗粒态磷流失量依次减少9.08%、1.02%.     

DEM格网尺度对AnnAGNPS预测山地小流域径流和物质输出的影响

为了解流域地形空间参数和其它参数的精度对农业非点源污染模型AnnAGNPS预测准确性的影响,利用三峡库区黑河小流域观测资料校准了AnnAGNPS模型,分析了1.5-12.5m格网尺度DEM对地形参数和模型负载输出的影响.结果表明,1.5～12.5m格网尺度DEM对流域径流量、洪峰流量、总N输出影响不显著,但对泥沙、总P、有机碳输出影响显著.三峡库区类似小流域宜采用5m格网尺度DEM,AnnAGNPS模型较不适合于尺度较小、坡度较大的小流域泥沙负载预测.     

基于AnnAGNPS模型的三峡库区小江流域非点源污染负荷评价

运用AnnAGNPS模型对三峡库区小江流域2002～2004年的径流量、输沙量、氮磷负荷量进行模拟估算，并分别采用宝塔窝水文站（控制范围占流域面积的62%）2002～2004年实测数据对径流和泥沙模拟值进行校准和验证，采用小江流域出口2002～2004年实测年均数据对总氮、总磷模拟负荷进行校准和验证，通过敏感性分析确定了影响流域非点源污染负荷输出的主要因子，结果表明模型模拟结果相对可靠，适合于三峡库区流域非点源污染负荷评价。根据模型预测结果，模型对径流输出的模拟精度高于对泥沙和养分的输出模拟，小江流域多年年均泥沙输出量为26189 万t，总氮输出为8 33523 t，总磷输出为43686 t。研究成果对于AnnAGNPS模型在三峡库区的应用具有很好的示范性     

WATERSHED OPTIMIZATION OF AGRICULTURAL BEST MANAGEMENT PRACTICES: CONTINUOUS SIMULATION VERSUS DESIGN STORMS1

ABSTRACT: Nonpoint source (NPS) models and expert opinions are often used to prescribe best management practices (BMPs) for controlling NPS pollution. An optimization algorithm (e.g., a genetic algorithm, or GA) linked with a NPS model (e.g., Annualized AGricultural Nonpoint Source pollution model, or AnnAGNPS), can be used to more objectively prescribe BMPs and to optimize NPS pollution control measures by maximizing pollutant reduction and net monetary return from a watershed. Pollutant loads from design storms and annual loads from a continuous simulation can both be used for optimizing BMP schemes. However, which strategy results in a better solution (in terms of providing water quality protection) for a watershed is not clear. The specific objective of the study was to determine the differences in watershed pollutant loads, in an experimental watershed in Pennsylvania, resulting from optimization analyses performed using pollutant loads from a series of five 2‐yr 24‐hr storm events, a series of five 5‐yr 24‐hr storm events, and cumulative pollutant loads from a continuous simulation of five years of weather data. For each of these three different event alternatives, 100 near optimal solutions (BMP schemes) were generated. Sediment (Sed), sediment nitrogen (SedN), dissolved N (SolN), sediment organic carbon (SedOC), and sediment phosphorus (SedP) loads from a different five‐year period (an evaluation period) suggest that the optimal BMP schemes resulting from the use of annual cumulative pollutant loads from a continuous simulation of five years of weather data provide smaller cumulative NPS pollutant loads at the watershed outlet.     

Estimation of runoff and sediment yield in the Redrock Creek watershed using AnnAGNPS and GIS

Sediment has been identified as a significant threat to water quality and channel clogging that in turn may lead to river flooding. With the increasing awareness of the impairment from sediment to water bodies in a watershed, identifying the locations of the major sediment sources and reducing the sediment through management practices will be important for an effective watershed management. The annualized agricultural non-point sourcepollution(AnnAGNPS) model and newly developed GIS interface for it were applied in a small agricultural watershed, Redrock Creek watershed, Kansas, in this pilot study for exploring the effectiveness of using this model as a management tool. The calibrated model appropriately simulated monthly runoff and sediment yield through the practices in this study and potentially suggested the ways of sediment reduction through evaluating the changes of land use and field operation in the model for the purpose of watershed management.     

Application of Tabu Search Algorithm With a Coupled AnnAGNPS‐CCHE1D Model to Optimize Agricultural Land Use1

Abstract: A principal contributor to soil erosion and nonpoint source pollution, agricultural activities have a major influence on the environmental quality of a watershed. Impact of agricultural activities on the quality of water resources can be minimized by implementing suitable agriculture land‐use types. Currently, land uses are designed (location, type, and operational schedule) based on field study results, and do not involve a science‐based approach to ensure their efficiency under particular regional, climatic, geological, and economical conditions. At present, there is a real need for new methodologies that can optimize the selection, design, and operation of agricultural land uses at the watershed scale by taking into account environmental, technical, and economical considerations, based on realistic simulations of watershed response. In this respect, the present study proposes a new approach, which integrates computational modeling of watershed processes, fluvial processes in the drainage network, and modern heuristic optimization techniques to design cost effective land‐use plans. The watershed model AnnAGNPS and the channel network model CCHE1D are linked together to simulate the sediment and pollutant transport processes. Based on the computational results, a multi‐objective function is set up to minimize soil losses, nutrient yields, and total associated costs, while the production profits from agriculture are maximized. The selected iterative optimization algorithm uses adaptive Tabu Search heuristic to flip (switching from one alternative to another) land‐change variables. USDA’s Goodwin Creek experimental watershed, located in Northern Mississippi, is used to demonstrate the capabilities of the proposed approach. The results show that the optimized land‐use design with BMPs using an integrated approach at the watershed level can provide efficient and cost‐effective conservation of the environmental quality by taking into account both productivity and profitability.     

小流域N、P污染负荷的构成比重研究

对浙江省宁海县颜公河流域N、P污染物负荷的构成比重进行了研究，提出了农业非点源污染造成水体污染的严重性。采用美国农业部的AnnAGNPS模型模拟计算流域中农业面源污染的N、P负荷，并对模型模拟计算的可靠性进行了验证。     

AnnAGNPS模型在流溪河下游流域农业非点源污染模拟应用

本文在珠江三角洲地区选取流溪河下游流域.借助GIS和RS以及相关资料率定模型参数,应用连续-分布式参数模型AnnAGNPS分别模拟了1998年、2000年和2002年三年的面源污染,并对污染负荷的空间和时间分布特征进行了分析,对于利用GIS和RS技术应用AnnAGNPS模型来计算流域面源污染提供了一种比较新的方法和思路,对我国其他地区尤其是经济较发达而环境污染问题较突出的地区研究面源污染具有重要的参考价值.