The baseflow separation method based on a digital filter is a simple method for separating the baseflow from streamflow. Appropriate estimation of filter parameters is required to use the digital filter method for analysis. We carried out sensitivity analysis on four digital filter methods: Lyne–Hollick (LH), Chapman, Chapman and Maxwell (CM), and exponentially weighted moving average (EWMA). Furthermore, appropriate filter parameters were suggested for each method in this study. By applying them to 25 stage stations in the Nakdong River in the Republic of Korea, the four methods were evaluated. The results of the evaluation showed that the Chapman and CM methods had problems separating the baseflow during the dry seasons. The EWMA and LH methods were able to achieve reliable baseflow separation of the outcomes by selecting appropriate the filter parameters. Thus, the EWMA and LH methods can be used easily and reasonably among the digital filter methods that have one filter parameter.

Water risk has been continuously rising due to climate change and ownership disputes of water resources. Dam construction to secure water resources may lead to environmental problems and upstream immersion. On the other hand, rainwater harvesting systems can effectively supply water at a low cost, although economic efficiency of these systems is still debatable. This study evaluates financial support programs to promote installation of rainwater harvesting systems, increasing economic feasibility. Based on a cost–benefit analysis, capacity optimization methods are further suggested. A sensitivity analysis is performed to determine the relative importance among uncertain parameters such as inflation and discount rates. In doing so, priority factors to consider in the design of rainwater harvesting systems are ultimately identified. A net present value, although it is sensitive to the inflation rate, is shown to be more appropriate to estimate the economic efficiency of rainwater harvesting system, compared to the typical cost–benefit ratio. Because the high future value overestimates the economic feasibility of rainwater harvesting systems, proper inflation rates should be applied. All in all, a funding program to promote rainwater harvesting systems significantly increases the benefits. Thus, national financial support policies are recommended to ensure economic feasibility of rainwater harvesting systems.

Hydrological responses are being impacted by both climate change and human activities. In particular, climate change and regional human activities have accelerated significantly during the last three decades in South Korea. The variation in runoff due to the two types of factors should be quantitatively investigated to aid effective water resources’ planning and management. In water resources’ planning, analysis using various time scales is useful where rainfall is unevenly distributed. However, few studies analyzed the impacts of these two factors over different time scales. In this study, hydrologic model-based approach and hydrologic sensitivity were used to separate the relative impacts of these two factors at monthly, seasonal and annual time scales in the Soyang Dam upper basin and the Seom River basin in South Korea. After trend analysis using the Mann–Kendall nonparametric test to identify the causes of gradual change, three techniques, such as the double mass curve method, Pettitt’s test and the BCP (Bayesian change point) analysis, were used to detect change points caused by abrupt changes in the collected observed runoff. Soil and Water Assessment Tool (SWAT) models calibrated from the natural periods were used to calculate the impacts of human activities. Additionally, six Budyko-based methods were used to verify the results obtained from the hydrological-based approach. The results show that impacts of climate change have been stronger than those of human activities in the Soyang Dam upper basin, while the impacts of human activities have been stronger than those of climate change in the Seom River basin. Additionally, the quantitative characteristics of relative impacts due to these two factors were identified at the monthly, seasonal and annual time scales. Finally, we suggest that the procedure used in this study can be used as a reference for regional water resources’ planning and management.

Especially for periods of drought, the higher the accuracy of reservoir inflow forecasting is, the more reliable the water supply from a dam is. This article focuses on the probabilistic forecasting of quarterly inflow to reservoirs, which determines estimates from the probabilistic quarterly inflow according to drought forecast results. The probabilistic quarterly inflow was forecasted by a copula-based Bayesian network employing a Gaussian copula function. Drought forecasting was performed by calculation of the standardized inflow index value. The calendar year is divided into four quarters, and the total inflow volume of water to a reservoir for three months is referred to as the quarterly inflow. Quarterly inflow forecasting curves, conforming to drought stages, produce estimates of probabilistic quarterly inflow according to the drought forecast results. The forecasted estimates of quarterly inflow were calculated by using the inflow records of Soyanggang and Andong dams in the Republic of Korea. After the probability distribution of the quarterly inflow was determined, a lognormal distribution was found to be the best fit to the quarterly inflow volumes in the case of the Andong dam, except for those of the third quarter. Under the threshold probability of drought occurrences ranging from 50% to 55%, the forecasted quarterly inflows reasonably matched the corresponding drought records. Provided the drought forecasting is accurate, combining drought forecasting with quarterly inflow forecasting can produce reasonable estimates of drought inflow based on the probabilistic forecasting of quarterly inflow to a reservoir.