Investigating the response characteristics of various hydrological factors to the construction of water conservancy projects and evaluating their impact on the ecological environment is crucial for ecological protection and restoration in the Loess Plateau, China with a complex environment. In this study, we employed a geomorphology-based hydrological model to simulate the hydrological elements of the Qinhe River Basin in the Loess Plateau. Additionally, we explored the response characteristics of the water cycle and hydrological processes to the construction of reservoirs in the basin. We also examined multiyear changes in peak flood volume and sediment discharge during flood seasons influenced by reservoirs. A thorough evaluation of the simulation results indicated their reliability. The sub-basins hosting reservoirs initially showed an increase in evaporation, followed by a decrease. During the change periods, both runoff and soil water decreased, but remained higher than the mean values for the basin during the same period. The Normalized Difference Vegetation Index of sub-basins associated with five reservoirs was significantly higher than the mean value for the basin during the same period. The peak flood volume and sediment discharge in the basin were characterized by decreasing trends, with the latter showing weak sustainability. The value of each index for a sub-basin associated with a reservoir was higher than the average value for the basin. The construction and operation of reservoirs had a positive impact on the ecology of the basin. Water and soil conservation measures, including sediment regulation and storage using reservoirs, significantly decreased water-related disasters and soil erosion in the basin. This study provides a scientific basis for the design of water conservancy projects and ecological governance in the basin.

Predicting extreme storm and flood events requires analysis to predict probable rainfall in target years. We present a non-stationary frequency analysis for 6 meteorological stations in Korea and Japan: Gangneung, Kwangju, Pohang, Seoul, Kochi, Iida. Non-stationary analysis results in higher estimated rainfall than stationary analysis for all stations. Increased probable rainfall in Korean stations was higher than in Japanese stations (i.e. Z-values of Korean stations were larger than for Japanese stations). Using rainfall data at the 6 sites with increasing trends, we estimate 3 types of probably predicted rainfall for the target years 2020, 2050 and 2070. According to the results of applicability analysis, in the case of a 100-year return period, the probable rainfall estimated by non-stationary methods has a residual of 1.6~2.5% in Kochi, 11.98~16.01% in Gangneung, 4.3~4.9% in Kwangju, and 3.2~5.3% in Seoul. This study indicates that non-stationary methods provide better results in terms of confidence than stationary methods for representing rainfall with increasing trends. The non-stationary rainfall frequency analysis provided more reasonable and well-directed estimates of probable rainfall for the target year. Results show that non-stationary methods estimate probable rainfall well over short timescales based on linear regression of observed data. Further, the probable rainfall estimator for target years reflects the increasing temporal pattern of rainfall and predicts future rainfall. Results from this study can inform the design of flood prevention approaches and effective hydraulic structures.