生态学报
生態學報
생태학보
ACTA ECOLOGICA SINICA
2009年
12期
6681-6690
,共10页
黄志霖%田耀武%肖文发%曾立雄%马德举
黃誌霖%田耀武%肖文髮%曾立雄%馬德舉
황지림%전요무%초문발%증립웅%마덕거
三峡库区%参数空间聚合%AnnAGNPS模型%流域区划%径流%泥沙%总N%总P
三峽庫區%參數空間聚閤%AnnAGNPS模型%流域區劃%徑流%泥沙%總N%總P
삼협고구%삼수공간취합%AnnAGNPS모형%류역구화%경류%니사%총N%총P
Three Gorges Reservoir Area%parameter spatial aggregation%AnnAGNPS model%watershed delineation%runoff%sediment%total N%total P
农业非点源污染物是长江三峡库区主要污染源之一,已造成令人关注的生态、环境和健康等问题,流域模型(AnnAGNPS)与GIS结合,为空间数据组织和模型参数空间聚合提供技术基础,是其预测和流域规划与管理的有效途径.三峡库区小流域条件下,基于临界源面积(CSA)和最小初始沟道长度(MSCL)值域设定,形成不同流域划分方案,空间离散单元(SDU)水平,即SDU大小及数量,影响输入参数空间聚合效应及模型输出结果.在黑沟小流域(144.4 hm~2)应用已校准AnnAGNPS模型,设定CSA和 MSCL值域为0.5~15hm~2及7.5~200m,10种SDU水平、流域尺度和条件下,结果表明:空间参数聚合程度和模型输出结果均随SDU尺度改变而发生变化.土地利用与土壤类型等参数具有明显的聚合效应,径流、泥沙和养分输出具有不同的SDU适宜水平和范围.SDU尺度聚合效应对径流量影响较小,而对泥沙、总N、总P模拟影响较大;径流量、泥沙、总N、总P模拟输出误差可接受SDU尺度范围分别为0.5~18、2~6、0.5~6 hm~2.因此,应用AnnAGNPS模型,更需要注意不同子模型所需要适宜的SDU尺度水平.
農業非點源汙染物是長江三峽庫區主要汙染源之一,已造成令人關註的生態、環境和健康等問題,流域模型(AnnAGNPS)與GIS結閤,為空間數據組織和模型參數空間聚閤提供技術基礎,是其預測和流域規劃與管理的有效途徑.三峽庫區小流域條件下,基于臨界源麵積(CSA)和最小初始溝道長度(MSCL)值域設定,形成不同流域劃分方案,空間離散單元(SDU)水平,即SDU大小及數量,影響輸入參數空間聚閤效應及模型輸齣結果.在黑溝小流域(144.4 hm~2)應用已校準AnnAGNPS模型,設定CSA和 MSCL值域為0.5~15hm~2及7.5~200m,10種SDU水平、流域呎度和條件下,結果錶明:空間參數聚閤程度和模型輸齣結果均隨SDU呎度改變而髮生變化.土地利用與土壤類型等參數具有明顯的聚閤效應,徑流、泥沙和養分輸齣具有不同的SDU適宜水平和範圍.SDU呎度聚閤效應對徑流量影響較小,而對泥沙、總N、總P模擬影響較大;徑流量、泥沙、總N、總P模擬輸齣誤差可接受SDU呎度範圍分彆為0.5~18、2~6、0.5~6 hm~2.因此,應用AnnAGNPS模型,更需要註意不同子模型所需要適宜的SDU呎度水平.
농업비점원오염물시장강삼협고구주요오염원지일,이조성령인관주적생태、배경화건강등문제,류역모형(AnnAGNPS)여GIS결합,위공간수거조직화모형삼수공간취합제공기술기출,시기예측화류역규화여관리적유효도경.삼협고구소류역조건하,기우림계원면적(CSA)화최소초시구도장도(MSCL)치역설정,형성불동류역화분방안,공간리산단원(SDU)수평,즉SDU대소급수량,영향수입삼수공간취합효응급모형수출결과.재흑구소류역(144.4 hm~2)응용이교준AnnAGNPS모형,설정CSA화 MSCL치역위0.5~15hm~2급7.5~200m,10충SDU수평、류역척도화조건하,결과표명:공간삼수취합정도화모형수출결과균수SDU척도개변이발생변화.토지이용여토양류형등삼수구유명현적취합효응,경류、니사화양분수출구유불동적SDU괄의수평화범위.SDU척도취합효응대경류량영향교소,이대니사、총N、총P모의영향교대;경류량、니사、총N、총P모의수출오차가접수SDU척도범위분별위0.5~18、2~6、0.5~6 hm~2.인차,응용AnnAGNPS모형,경수요주의불동자모형소수요괄의적SDU척도수평.
Agriculture has been identified as a leading source of Nonpoint Source (NPS) pollution as a result of its intensive fertilizer applications and crop management practices, and has led to ecological and human health concerns in the Three Gorges Reservoir Area (TGRA), China. Watershed models, Annualized Agricultural Nonpoint Source (AnnAGNPS), are considered a cost-effective and time-efficient approach for the assessment of pollutant loads and management practices, are coupled with GIS to facilitate watershed planning and management, which offer an unprecedented flexibility in the organization of spatial data, the spatial extent of input parameter aggregation has previously been shown to have a substantial impact on model output. However, the aggregation of spatial information in the GIS, the effects of data aggregation on model input parameters, such as land use and cover and soil type, are not well studied in watershed of TGRA condition. For the study watershed, values of critical source area (CSA) and minimum source channel length (MSCL) was set from 0.5 to 15 hm~2 and the MSCL from 7.5 to 200 m. The study focused on the impact of the size or the number of cells and spatial discretization unit (SDU) used to partition a watershed (10 watershed delineations) on the input parameter spatial aggregation and output of model, the results show that across levels of watershed partitioning, there are different extent of parameter spatial aggregation of land use and soil types. The results indicate that input parameter spatial aggregation had little effect on runoff yields predictions, and more effect on sediment, total nitrogen and phosphorous loads;within the range of acceptable accuracy, in this paper, the applicability and predictive capacity of AnnAGNPS model in TGRA conditions is examined. The optimal threshold values of SDU, relative to the scale of Heigou watershed and TGRA conditions, required to adequately predicting runoff, sediment yields and nitrogen, phosphorous were found to be around 0.5-18, 2-6, 0.5-6 hm~2, respectively. The model can be applied for estimation of runoff and sediment losses with acceptable accuracy in TGRA, the CSA and MSCL values determine the hydrographic segmentation of the watershed and the cell size, especially in heterogeneous areas of the watershed, which can increase the accuracy of model results, which indicates that greater attention should be made to partition a watershed to match the underlying assumptions of sub-models within AnnAGNPS.