Analyzing the bias in dry weather spot flow rates to periodical mean flow rates in mountain streams: toward determining water pollution loads and optimizing water sampling strategies
May 11th, 2021
Ami Tanno, Shigeki Harada
Received 2020/12/04, Accepted 2021/02/23, Published 2021/05/11
Ami Tanno1), Shigeki Harada2)
1) Higashinihon Concrete Corporation, Japan
2) Department of Agroenvironmental Sciences, Faculty of Food and Agricultural Sciences, Fukushima University, Japan
Low frequency (once a month) but long-term (ca. 6 years) sampling including snow-melt periods in a mountainous stream, the Okura River (Sendai, Japan), revealed that loadings of 5 parameters (COD, TN, TP, TOC and D-SiO2) could be expressed exponentially using discharge (Q), while the coefficients for the 5 loadings were all about 1. Here, mathematically, the periodically averaged Q leads to approximation of that of load (L). We analyzed the bias of the spot Q to that of the periodical (30, 14 and 8 days) means. The results ensured the utilization of the spot Q instead of the periodical mean Q for estimating L because of the high correlation factors (0.872, 0.914 and 0.923 on 30-, 14-, 8-day mean Q analyses, respectively) and suggested the validity of the usage of the observed regression slopes of 1.06, 1.22, and 1.22 over 30, 14, 8 days for quantitative correction of L because the fact that the slopes are larger than 1 indicate that the usage of the spot Q instead of the mean Q leads to the overestimation of L. Both changing correlation factors and the regression slopes realized small improvements via shortening the periods from 14 to 8 days. The protocol proposed here is quite original and is applicable to designing sampling strategies at target sites based on quantification of the limitations and/or reliability of L estimations.
Copyright (c) 2021 The Author(s) CC-BY 4.0