水文变化条件下农田溪流营养盐滞留效应模拟  

Modeling of nutrient retention effect in an agricultural headwater stream considering hydrological variability

作　　者：李如忠[1] 黄青飞 杨继伟[2] 张瑞钢[3] 金菊良[3] 

机构地区：[1]合肥工业大学资源与环境工程学院,安徽合肥230009 [2]安徽省水利部淮委水利科学研究院,安徽蚌埠233000 [3]合肥工业大学水资源与环境系统工程研究所,安徽合肥230009

出　　处：《中国环境科学》2016年第6期1877-1885,共9页China Environmental Science

基　　金：国家自然科学基金项目(51179042;51579061)

摘　　要：以巢湖流域某一典型农田源头溪流为对象,基于溪流水文条件的动态变化性,从水文概率密度模型与营养盐滞留率模型综合集成角度,解析较长时间尺度下营养盐滞留有效流量的动态变化特征.在对水文概率密度模型Monte Carlo随机模拟的基础上,根据先前10次野外示踪实验获得的营养盐吸收速度等数据信息,定量评估溪流营养盐滞留的总体水平,估算最有效流量和等效流量.结果表明,农田溪流渠段的NH_4^+、PO_4^(3-)滞留能力总体偏低,相应的期望滞留率分别为0.0671(6.71%)和0.0541(5.41%),最有效流量分别为0.0051,0.0049m^3/s,功能等效流量分别为0.044,0.043m^3/s.基于溪流营养盐吸收速度明显偏低的客观现状,有必要从溪流形态和河床地貌特征的改造着手,提升溪流水体营养盐滞留能力.A typical agricultural headwater stream was chosen as the representative to investigate the dynamic characteristics of effective flow for nutrient retention over a longer time scale, based on the change of regional hydrology, from the perspective of coupling the discharge probability density function and nutrient retention efficiency. Through the Monte Carlo simulation for discharge probability density function, the overall level of nutrient retention for the target stream was quantitatively evaluated as well as the most effective flow and the functionally equivalent discharge were calculated, according to the nutrient uptake velocity derived from field tracer experiments. The overall levels of retention capability for NH4＋and PO43- were quite low. The expected values of the retention efficiency of NH4＋and PO43- were 0.0671 （6.71%） and 0.0541 （5.41%）, respectively. The most effective flow for NH4＋ and PO43- were 0.0051m3/s and 0.0049m3/s, and the functionally equivalent discharge for them were 0.044m3/s and 0.043m3/s, respectively. In view of the fact of low nutrient uptake velocity in the stream, it is necessary to improve the nutrient retention efficiency of the target stream by reconstructing stream morphology and streambed geomorphology.

关 键 词：水文变化 营养盐滞留 有效流量 MONTE CARLO模拟 农田源头溪流 

分 类 号：X171.1[环境科学与工程—环境科学]