Abstract

Objectives:This study assessed the applicability of the total pollutant load management (TPLM) data on the analysis of impaired waterbody and pollutant source characterization. To achieve the study objective, the TPLM data collected in the downstream of Yeongcheon-Dam within the Geumho A unit-basin, Nakdong River basin for 6 years (2013-2018) were used to analyze the accountability for precipitation conditions, seasons, and flow rates. Methods:The study area is the downstram of Yeongcheon Dam within the Geumho A unit-basin, Nakdong River basin. The TPLM data used in this study were obtained from the two monitoring stations in the mainstream of Geumho River (i.e., Jahocheon and Geumho A station) and the three tributary streams (i.e., Gochoncheon, Sillyeongcheon, and Bugancheon). Precipitation conditions were classified into rainy (>10 mm/day) and non-rainy days (≤10 mm/day) to assess the TPLM data accountability for the two precipitation conditions. Seasonal accountabilities of the TPLM data were assessed for spring (March-May), summer (June-August), autumn (September-November), and winter (December-February). The TPLM data accountability for stream flow rates was assessed using the standardized daily flow rates which were estimated by % of maximum flow rate. The daily flow rates were simulated using the Hydrologic Simulation Program-Fortran (HSPF).Results and Discussion:During the study period (2013-2018), TPLM data were collected 35-41 times throughout a year in the two Geumho River mainstream stations (i.e., Jahocheon, and Geumho A), while the tributary streams (i.e., Gochoncheon, Sillyeongcheon, and Bugancheon) were monitored 36 times per year excluding every January, February, and December. The tributary streams shown the missing data months because those stations were monitored through the implementation assessment for total maximum daily load (TMDL) management. But, the mainstream data were continuously collected by the Water Environment Research Institute. The accountability assessment results shown that 28%, 25%, 28%, and 19% of TPLM data for the two mainstream stations represents spring, summer, autumn, and winter seasons. The three TPLM station data in the tributary streams could not account for winter season with the seasonal data ratios of 29% for spring, 32% for summer, 34% for autumn, and 4% for winter. Secondly, 37.9% and 23.1% of TPLM data for the two mainstream stations and the three tributary streams, respectively, were collected during rainy days. Comparing to 22% of rainy days throughout the study period, the two mainstream stations were monitored more frequently during rainy days than the tributary stations. Lastly, accountability for stream flow rates shown that the annual TPLM data cannot account for mainstream flow conditions. For the tributary stream flow rates, six years composite TPLM data could not represent the flow conditions. Therefore, the TPLM data need to be carefully reviewed before assessing impaired waterbody and pollutant source characterization. Conclusions:TPLM data was widely used in TMDL implementation and research activities. Thus, detailed TPLM monitoring plans should be developed to improve accountability for various stream characteristics including precipitation, season, and flow rate, etc. In addition, further research is needed to represent wide ranges of flow rate which are hard to be predicted due to the large uncertainties induced by precipitation, precipitation intensity, precedent rain days, and other factors (e.g., dams, wastewater treatment plants, etc.).

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