Use of MLCM3 Software for Flash Flood Modeling and Forecasting

Abstract

The need to protect the rapidly developing Russia's economy and population requires timely warnings based on reliable forecasts. While such warnings should be issued for about one of approximately 2.6 million Russian streams (most of which are ungauged or poorly gauged), this can be done only in fully automated and quite approximate (virtually, qualitative) mode. In changing climate and variable anthropogenic impact on river basins, as well as due to quite low density of the surface hydrometeorological network, flash flood forecasting based on "traditional" physically based, or conceptual, or statistical hydrological models often becomes inefficient [Pivovarova 2016]. Thus, the basic task of the presented study can be posed as developing a fully automated system of qualitative forecasting risks of flooding regardless of the quality and spatiotemporal resolution of the available hydrometeorological data.The authors of the presented study realize that accurate and timely flash floods forecasting, especially, in ungauged and poorly gauged basins, is one of the most important and challenging problems to be solved by the international hydrological community; also, they understand that the accuracy and efficiency of forecasting depend, first of all, on 1 -data resolution and quality and 2 -the ability of used models to reflect the runoff generation processes properly. Therefore, the efficiency of flood forecasting in different basins also Journal of Ecological Engineering ABSTRACTAccurate and timely flash floods forecasting, especially, in ungauged and poorly gauged basins, is one of the most important and challenging problems to be solved by the international hydrological community. In changing climate and variable anthropogenic impact on river basins, as well as due to low density of surface hydrometeorological network, flash flood forecasting based on "traditional" physically based, or conceptual, or statistical hydrological models often becomes inefficient. Unfortunately, most of river basins in Russia are poorly gauged or ungauged; besides, lack of hydrogeological data is quite typical. However, the developing economy and population safety necessitate issuing warnings based on reliable forecasts. For this purpose, a new hydrological model, MLCM3 3 rd generation) has been developed in the Russian State Hydrometeorological University. The model showed good results in more than 50 tested basins.

Investigation of Runoff and Flooding in Urban Areas based on Hydrology Models: A Literature Review

“…For example, the catchment of the Imjin is extended between North and South Korea, classified as one the most critical basins in Korea, and management of flood there is hard to do due to the limitation and sharing of hydrology data between North and South Korea [92]. In Russia, a large country in Asia, nearly 2.6 million streams are still recorded as ungauged or poorly observed data [93], and they developed a hydrology model Multi-Layer Conceptual Model, 3rd generation) (MLCM3) by the Russian State Hydrometeorological University. This model devolved for ungauged Russian catchments.…”