Study on the Removal Rate Evaluation Model for Non-point Source Best Management Practices

• Main Authors: Wu, Hsiao-Hui, 吳小慧
• Other Authors: Fan, Jen-Chen
• Format: Others
• Language: zh-TW
• Published: 2000
• Online Access: http://ndltd.ncl.edu.tw/handle/30608986561522385311

碩士 === 國立臺灣大學 === 農業工程學研究所 === 88 === The objective of this study is to establish the Best Management Practice (BMP) on the removable efficiency of the grassed waterway and the vegetative filter strip. Our motive is that over-development of the upland watersheds results in the increase of the non-point source (NPS) pollutant increasing dramatically in the last decade. Because the non-point source pollutant is caused by random rainfall events and transported to water bodies mainly by runoff, it has high temporal and spatial variability. A method to evaluate the impact of the pollutant to the water bodies is proposed. In this study, a model was established to evaluate the removable efficiency of the two BMPs, namely, grassed waterway and vegetative filter strip, by using the inflow rate,slope steepness and area of the BMP.Five pollutants such as Tss, PO4, NH3-N, NO3, and COD.were considered. For the removable efficiency of grassed waterway, it was found that the R square values for the five pollutants were 0.81,0.70,0.58,0.61 and 0.58,respectively. As for the removable efficiency of vegetative filter strip, it is found that the R square values for the five pollutants were 0.61,0.55,0.70,0.47 and 0.29,respectively. Since the NPS pollution is highly related surface runoff and surface runoff is influenced by rainfall, accordingly, the established model and average rainfall intensity of each rainfall event within a year could be used to evaluate the NPS pollution removable efficiency of grassed waterway and vegetative filter strip for each single storm. Further, from the occurrence probabilities of rainfall, the NPS pollution removable efficiency could be obtained. Therefore, it might be useful to control the total quantity of NPS pollution. To control the NPS pollution more conveniently, the spatial correlations for the rainfall record of the 33rainfall observation stations in the northern Taiwan were found. Then, the cluster analysis was adopted to classify all rainfall observation stations into three groups. While doing the cluster analysis, Ward’s method and k mean method were used. The statistical means for each group by Ward’s method were 2.25mm/hr, 3.28mm/hr and 1.93mm/hr, and their standard deviations were 0.24mm/hr, 0mm/hr and 1.18mm/hr. The means for each group by k mean method were 2.06mm/hr, 2.62mm/hr and 1.91mm/hr, and their standard deviations were 0.44mm/hr,0.66mm/hr and 1.18mm/hr,respectively.