Environmental monitoring data for planning, implementing and evaluating the Total Maximum Daily Loads (TMDL) management system have been measured at about 8-day intervals in a number of rivers in Korea since 2004. In the present study, water quality parameters such as Suspended Solids (SS), Biochemical Oxygen Demand (BOD), Dissolved Oxygen (DO), Total Nitrogen (TN), and Total Phosphorus (TP) and the corresponding runoff were collected from six stations in the Yeongsan River basin for six years and transformed into monthly mean values. With the primary objective to understand spatiotemporal characteristics of the data, a methodologically systematic application of a Self-Organizing Map (SOM) was made. The SOM application classified the environmental monitoring data into nine clusters showing exclusively distinguishable patterns. Data frequency at each station on a monthly basis identified the spatiotemporal distribution for the first time in the study area. Consequently, the SOM application provided useful information that the sub-basin containing a metropolitan city is associated with deteriorating water quality and should be monitored and managed carefully during spring and summer for water quality improvement in the river basin.

In this study, the high-resolution polygonal land cover data of EEA Urban Atlas was applied for land-use characterization in the dynamic multi-basin hydrological model, HYPE. The objective of the study was to compare this dedicated urban land cover data in semi-distributed hydrological modelling with the widely used but less detailed EEA CORINE. The model was set up for a basin including a small town named Svedala in southern Sweden. In order to verify the ability of the HYPE model to reproduce the observed flow rate, the simulated flow rate was evaluated based on river flow time series, statistical indicators and flow duration curves. Flow rate simulated by the model based on Urban Atlas generally agreed better with observations of summer storm events than the CORINE-based model, especially when the daily rainfall amount was 10 mm/day or more, or the flow exceedance probability was 0.02 to 0.5. It suggests that the added value of the Urban Atlas model is higher for heavy-to-medium storm events dominated by direct runoff. To conclude, the effectiveness of the proposed approach, which aims at improving the accuracy of hydrological simulations in urbanized basins, was supported.

Since the 20th century, Japan has experienced a period of very rapid urbanization. Cities have experienced substantial densification and expansion, resulting in gradually elevated flood risk. Urban flooding has also occurred in most large cities in Japan, particularly in Tokyo. In response to this growing problem, much effort and resources have been spent on research and development aimed at understanding, simulating, and managing urban flood risk in Japan. The objective of this review is to summarize, discuss, and share key outputs from some of the main research directions in this field, significant parts of which have been uniquely developed in Japan and only published in Japanese. After a general introduction to urban runoff modeling, in the next section, key historical works in Japan are summarized, followed by a description of the situation in Japan with respect to observations of precipitation and water level. Then, the storage function model approach is reviewed, including an extension to urban basins, as well as recent experiments with AI-based emulation in Japanese basins. Subsequently, we review the prospects of detailed hydrodynamic modeling involving high-resolution, vector-based Geographical Information System (GIS) data for the optimal description of the urban environment with applications in Tokyo. We conclude the paper with some future prospects related to urban flood risk modeling and assessment in Japan.