基于潮河流域非点源污染分布特征的BMPs优化配置研究
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摘要
国内外开展的多项研究表明,农业非点源污染是导致水环境污染的最主要原因之一。目前对非点源污染进行控制和管理主要是通过采取各种“最佳管理措施”(Best Management Practices, BMPs)来实现的。虽然小区(plot)与农田地块(field)尺度的实地监测发现BMPs对营养盐及泥沙的控制非常有效,但受限于点位差异性及气候等因素影响,简单地将其在流域尺度大范围进行应用,很难达到预期污染控制目标,而且可能会造成预算的严重超支。因此,如何在有限的资金及人力条件下,通过最佳管理措施的空间优化配置,实现流域尺度非点源污染的有效控制己越来越受到科研人员及环保、水利部门的关注。本论文以密云水库上游潮河流域为研究区,从提升最佳管理措施(BMPs)实施效率的角度出发,识别不同空间尺度非点源磷污染负荷分布特征,为BMPs配置方案的提出与概念化流域的构建提供依据;揭示水质显著改善概率(Pw)与流域污染负荷削减比例(Rw)响应关系,生成更有针对性的BMPs实施效果评价指标；辨析不同空间配置下BMPs的成本效益曲线变化趋势,筛选最佳空间配置方案。最终提出一套适用于研究区的BMPs空间层次配置方案,为有效控制水土流失与非点源污染,促进水源地保护和流域健康,提供理论依据和技术支持。论文主要研究结论可概括为以下几个方面：
(1)根据区域非点源污染物空间分布特征构建概念化流域,能够在水文地貌及气象特征可控的条件下,有效地规避大尺度天然流域内各子流域及地块间存在的空间自相关问题,并运用统计模拟的方法将自然流域污染负荷的空间分布特征以相应比例的形式反映到虚拟的流域之中,进而对其采用不同空间配置的BMPs组合配置方案,能够为流域尺度和地块尺度BMPs的优化配置及成本效益优选提供理论依据。
(2) HSPF模型模拟结果符合研究需求,97个子流域的磷污染物负荷主要集中在汛期的6-9月份,泥沙负荷汛期占全年比例的78%～90%,汛期是潮河流域土壤侵蚀和氮、磷非点源污染防治的关键时期。各子流域中平均磷污染负荷为21.32kg,最大为113.85kg,最小为0.91kg,空间上呈正态分布。从修正的磷指数(PI)评价结果来看,研究区内磷流失风险呈正态分布,即高风险区(7.95%)与中值区(19.63%)只占很小一部分,大部分为低风险区(72.42%)。流域尺度的磷流失风险值与实际流失值具有显著的相关关系,有效系数R2=0.67,地块尺度的磷流失量平均值为2.94kg,最低为2.07kg,最高为17.24kg,符合空间上的正态分布,可以为概念化流域的构建提供有效依据。
(3)运用随机抽样的方法,构建的概念化景观负荷模型(100个子流域,10000个地块)经正态分布检验证实能够满足研究需要,可以代表潮河流域磷污染空间分布特征。研究区河道内总磷浓度的时空变化差异较为显著,多个点位的多年监测数据为不同BMPs措施实施比例下水质显著改善概率的估算提供了有力的数据支撑,因此成功地建立了流域负荷削减比例(Rw)与水质显著改善概率(Pw)间的定量关系为：Pw=1+60(e-13.2·Rw)/1.059=-0.059,识别了河流水质改善的人为正面干扰阈值。通过对四种BMPs空间配置方案的成本效益曲线对比发现,目标聚集配置方案为最优方案。从BMPs地块削减效率、不同尺度的磷负荷空间分布规律及水质采样点数量三个角度进行敏感性分析,结果表明该方案在BMPs削减效率值Rf=0.65时的结论是稳定可靠的。
Nonpoint source pollution (NPS) problem can be controlled by implementing various best management practices (BMPs) in the watershed. Although application of conservation practices can effectively reduce nutrients and sediment from plots and fields, simple placement of these mitigation measures in watershed usually can not meet the pollution control target. The reducing efficiency may be influnced by many factors, such as soils, topography, land use, and human activities, etc. Thus, how to optimize spatial placement of BMPs in watershed scale for effective control of NPS with limited funds and labor has been more and more attention from researchers and environmental protection departments. This dissertation took the Chaohe River watershed as the study area and adopted Geographic Information System (GIS), Hydrological Simulation Program-Fortran (HSPF) and Statistical Technique to achieve the objectives which are:1) to identify the spatial distribution frequency of phosphorus pollution loads at two scales (subwatershed and field) and provide the basic data for the development of the conceptual watershed,2) to examine the relationship between probability of statistically significant water quality improvement (Pw) and reduction proportion of pollution load in watershed (Rw)and generate more effect evaluation indices,3) to discriminate the change treands of the four approaches benefit/cost curves for geographically allocating conservation effort. This work will be helpful to further controlling soil erosion and non-point source pollution and protecting drinking water resource watershed. The main results of this doctoral dissertation are listed as follows:
1) Based on the spatial distribution features of agricultural non-point source pollution that were drived from simulated experiments. A simple and easy integrated approach will be established for the purpose of identifying the distribution pattern of phosphorus loading at two spatial scales (watershed and filed) so that different allocation plans of BMPs can be designed. More effective performance benefit index will be generated through identifying relationship between the ratio of TP loading mitigation and the probability of detecting a statistically TP improvement. By comparing the thresholds of logistic curve of cost-benefit, the best allocation plan will be determined. The expected results will be very useful for agricultural nonpoint source pollution control and drinking water source protection in Chaohe River watershed.
2) The HSPF model simulation results can meet the need of conceptual subwatershed construction. The phosphorus load from Chaohe River flowed into Miyun reservoir mainly in June-September (flood season). The loss of sediment in flood season accounted for78%-90%of the whole year load. Thus, the flood season is a critical period for soil erosion control and non-point source pollution prevention. For each subwatershed, the average pollution load was21.32kg, the max value was113.85kg and the min value was0.91kg, respectively. The phosphorus index (PI) results showed that frequency distribution of field P load estimates was best fit by a normal probability distribution. High risk area, moderate risk area and low risk area account for7.95%,19.63%,72.42%of the total area. PI value has a significant correlation (R2=0.67) with the actual loss value at watershed scale. The average values of phosphorus from field scale is2.94kg, the max and min value were17.24kg and2.07kg, fitting a spatial normal distribution. Therefore, it can be used as data basis for the conceptual watershed construction.
3) Conceptual watershed included100model subwatersheds and10000model fields, which were selected for random order among the Chaohe river basin. The pollution load of model landscape had spatial normal probability distribution feature. The phosphorus concentration had significant spatial and temporal difference. The dataset consists of time series of P concentrations from thirty tributaries with more than40%watershed agriculture and provides the best available estimate of P variability in Chaohe River. Based on statistical simulations and stream P concentrations data, a statistically significant waterquality improvement at the outlet of a watershed (PW) was calculated as:Pw=1.059/1+69(e-13.2·Rw)-1.038In realistic implementation scenarios, the aggregated and targeted approach most efficiently improves water quality. The sensitivity analysis (reduction proportion of fied load, load spatial distribution and sample number) indicated that the superiority of the aggregated and targeted approach was robust to uncertainties in model parameters and to assumption choices.
(1)根据区域非点源污染物空间分布特征构建概念化流域,能够在水文地貌及气象特征可控的条件下,有效地规避大尺度天然流域内各子流域及地块间存在的空间自相关问题,并运用统计模拟的方法将自然流域污染负荷的空间分布特征以相应比例的形式反映到虚拟的流域之中,进而对其采用不同空间配置的BMPs组合配置方案,能够为流域尺度和地块尺度BMPs的优化配置及成本效益优选提供理论依据。
(2) HSPF模型模拟结果符合研究需求,97个子流域的磷污染物负荷主要集中在汛期的6-9月份,泥沙负荷汛期占全年比例的78%～90%,汛期是潮河流域土壤侵蚀和氮、磷非点源污染防治的关键时期。各子流域中平均磷污染负荷为21.32kg,最大为113.85kg,最小为0.91kg,空间上呈正态分布。从修正的磷指数(PI)评价结果来看,研究区内磷流失风险呈正态分布,即高风险区(7.95%)与中值区(19.63%)只占很小一部分,大部分为低风险区(72.42%)。流域尺度的磷流失风险值与实际流失值具有显著的相关关系,有效系数R2=0.67,地块尺度的磷流失量平均值为2.94kg,最低为2.07kg,最高为17.24kg,符合空间上的正态分布,可以为概念化流域的构建提供有效依据。
(3)运用随机抽样的方法,构建的概念化景观负荷模型(100个子流域,10000个地块)经正态分布检验证实能够满足研究需要,可以代表潮河流域磷污染空间分布特征。研究区河道内总磷浓度的时空变化差异较为显著,多个点位的多年监测数据为不同BMPs措施实施比例下水质显著改善概率的估算提供了有力的数据支撑,因此成功地建立了流域负荷削减比例(Rw)与水质显著改善概率(Pw)间的定量关系为：Pw=1+60(e-13.2·Rw)/1.059=-0.059,识别了河流水质改善的人为正面干扰阈值。通过对四种BMPs空间配置方案的成本效益曲线对比发现,目标聚集配置方案为最优方案。从BMPs地块削减效率、不同尺度的磷负荷空间分布规律及水质采样点数量三个角度进行敏感性分析,结果表明该方案在BMPs削减效率值Rf=0.65时的结论是稳定可靠的。
Nonpoint source pollution (NPS) problem can be controlled by implementing various best management practices (BMPs) in the watershed. Although application of conservation practices can effectively reduce nutrients and sediment from plots and fields, simple placement of these mitigation measures in watershed usually can not meet the pollution control target. The reducing efficiency may be influnced by many factors, such as soils, topography, land use, and human activities, etc. Thus, how to optimize spatial placement of BMPs in watershed scale for effective control of NPS with limited funds and labor has been more and more attention from researchers and environmental protection departments. This dissertation took the Chaohe River watershed as the study area and adopted Geographic Information System (GIS), Hydrological Simulation Program-Fortran (HSPF) and Statistical Technique to achieve the objectives which are:1) to identify the spatial distribution frequency of phosphorus pollution loads at two scales (subwatershed and field) and provide the basic data for the development of the conceptual watershed,2) to examine the relationship between probability of statistically significant water quality improvement (Pw) and reduction proportion of pollution load in watershed (Rw)and generate more effect evaluation indices,3) to discriminate the change treands of the four approaches benefit/cost curves for geographically allocating conservation effort. This work will be helpful to further controlling soil erosion and non-point source pollution and protecting drinking water resource watershed. The main results of this doctoral dissertation are listed as follows:
1) Based on the spatial distribution features of agricultural non-point source pollution that were drived from simulated experiments. A simple and easy integrated approach will be established for the purpose of identifying the distribution pattern of phosphorus loading at two spatial scales (watershed and filed) so that different allocation plans of BMPs can be designed. More effective performance benefit index will be generated through identifying relationship between the ratio of TP loading mitigation and the probability of detecting a statistically TP improvement. By comparing the thresholds of logistic curve of cost-benefit, the best allocation plan will be determined. The expected results will be very useful for agricultural nonpoint source pollution control and drinking water source protection in Chaohe River watershed.
2) The HSPF model simulation results can meet the need of conceptual subwatershed construction. The phosphorus load from Chaohe River flowed into Miyun reservoir mainly in June-September (flood season). The loss of sediment in flood season accounted for78%-90%of the whole year load. Thus, the flood season is a critical period for soil erosion control and non-point source pollution prevention. For each subwatershed, the average pollution load was21.32kg, the max value was113.85kg and the min value was0.91kg, respectively. The phosphorus index (PI) results showed that frequency distribution of field P load estimates was best fit by a normal probability distribution. High risk area, moderate risk area and low risk area account for7.95%,19.63%,72.42%of the total area. PI value has a significant correlation (R2=0.67) with the actual loss value at watershed scale. The average values of phosphorus from field scale is2.94kg, the max and min value were17.24kg and2.07kg, fitting a spatial normal distribution. Therefore, it can be used as data basis for the conceptual watershed construction.
3) Conceptual watershed included100model subwatersheds and10000model fields, which were selected for random order among the Chaohe river basin. The pollution load of model landscape had spatial normal probability distribution feature. The phosphorus concentration had significant spatial and temporal difference. The dataset consists of time series of P concentrations from thirty tributaries with more than40%watershed agriculture and provides the best available estimate of P variability in Chaohe River. Based on statistical simulations and stream P concentrations data, a statistically significant waterquality improvement at the outlet of a watershed (PW) was calculated as:Pw=1.059/1+69(e-13.2·Rw)-1.038In realistic implementation scenarios, the aggregated and targeted approach most efficiently improves water quality. The sensitivity analysis (reduction proportion of fied load, load spatial distribution and sample number) indicated that the superiority of the aggregated and targeted approach was robust to uncertainties in model parameters and to assumption choices.
引文
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