Conservation and management of water quality is extermely important to conserve the water environment and to secure good water resources. Water quality has been conventionally controlled by the regulation of its concentration. However, diversity of pollutants and the increase of waste-water in recent years indicate that regulation of the total outflow amount of pollutant will be increasingly important. Moreover, accurate measurement of the total loads of materials such as nitrogen and phosphorous is fundamentally important for elucidating the cycle and mass balance. However, water quality load measurement is not so easy; it requires much time and effort in addtion to high costs. Therefore, we established a new system that can readily determine the total load of water quality. As this paper describes, the system was applied to a forested watershed to validate the system. Results demonstrate that the system operated effectively to measure the total loads of water quality acculately and easily.

　We propose a method for selecting an optimal stochastic distribution that can be used along with hydrologically extreme data. In Japan, many civil engineering departments of governmental organizations refer to the “Guide for River Plan Design for Small and Medium-sized Rivers.” However, the flow chart for estimating T-year hydrological events included in guide includes important defects. For instance, this guide recommends the standard least squares criterion (SLSC) method for estimating the goodness of fit of each distribution. Some researchers have pointed out that SLSC is not a fair criterion. Our proposed method uses not SLSC itself, but the degree of significance: specifically the probability of non-exceedance of SLSC. We propose the following procedures.

1) Estimating parameters of population for various stochastic distributions

2) Estimating SLSC (referring to the “original SLSC”) of each distribution

3) Running a Monte Carlo simulation, which generates various random numbers with estimated distributions and parameters

4) Estimating various SLSCs with generated random numbers and estimating SLSC distributions for each distribution

5) Evaluating the probability of non-exceedance of the “original SLSC” by comparison to the SLSC distribution

6) Comparing the probability of non-exceedance of SLSC for each distribution and selecting the most appropriate distribution for which the probability is smallest

　Results indicate that the optimal distribution selected using our new method is sometimes different from the distribution selected when using SLSC. Data used for this study were one-hour precipitation data calculated by the d4PDF project. Results suggest that the modified method is superior to the conventional method.

　Precipitation and nitrate concentration was measured at shallow wells in the Miyakonojo Basin in February and August during 2007 - 2016. Correlation analysis was applied to investigate relations between the precipitation and nitrate concentration. In addition, since the Act on the Appropriate Treatment and Promotion of Utilization of Livestock Manure was enforced in 1999, the concentration of nitrate nitrogen in the groundwater of the Miyakonojo Bain has tended to decrease year by year. The changes in the precipitation and the nitrate concentration between the observation points were used for correlation analysis. Correlation analysis results showed positive correlation between changes in precipitation and nitrate concentration. In other words, results that the nitrate concentration in groundwater tends to increase along with the precipitation in the Miyakonojo Bain. Additionally, results show that the precipitation up to one month prior was closely related to the nitrate concentration in ground water.

　The author, who is currently a PhD student, introduces herself and her ideal attitude as a researcher, looking back on her fundamental motivation to become a researcher: The learnings from field surveys.