Research on hydrology

By | 08.12.2012

From April 2011 to November 2012 the company employees with the support of the Ministry of Education and Research performed the research on the topic “Solving inverse problem based on mathematical models of formation spatial-temporal characteristics of river beds for operational short-term forecasts of floods using multi-core supercomputers”.

The project was implemented together with russian scientists —  the employees of the Russian Hydrometeorological Center. The scientific supervisor of the project was Romanov Aleksey Viktorovich, candidate of science, leading research specialist of the department of river hydrological forecasts of the “Hydrometcenter of Russia” FSUE.

As a result of the research, a new accurate method of forecasting floods using rare network of gauging stations was developed — HQ FORECAST.

Description

The HQ FORECAST automated software complex determines the spatial-temporal characteristics of river beds using water regime observations  in order to forecast water levels and flows, and also allows to visualize the flooding zone using digital terrain model. The HQ FORECAST software combines the solutions of direct and inverse hydromodeling problem.

Comparison of the test forecast provided by HQ FORECAST with a lead time of 3 days with actual data

Digital relief of the river floodplain built using HQ FORECAST using laser scanning data

Visualization of the flood zone provided by HQ FORECAST

Solving the inverse problem

The HQ FORECAST software solution of inverse hydrodynamic problems helps to restores such river bed characteristics as width, cross-sectional area, roughness level and throughput.

Main advantages and scope of the HQ FORECAST method application

Nowadays there is no analogue to HQ FORECAST — software that solves inverse and direct problems in complex based on one-dimensional model of unsteady water flow. HQ FORECAST allows to qualitatively solve the problem of forecasting floods using standard water regime observation data.

Such solution is especially important in Russia, where, due to large number of rivers and large areas, there is a serious problem with collecting detailed hydrological data.

Expected effect from HQ FORECAST integration

  • Significant increase in forecasts accuracy due to joint application of the solution of inverse and direct problems based on a one-dimensional model of unsteady water flow;
  • Multiple increase in forecasting speed due to the use of modern methods of working with high-performance computers;
  • More quick and effective response to forecasts due to simultaneous forecasting flooding and simulation of flooding area;
  • The possibility of changing the system of organization of water regime observations with the aim to create more automated water points (measuring only water levels) and to reduce the number of points measuring the water outgo. Transition to such a system of organization of regime observations can give a multiple economic effect while keeping the reliability of forecasts.

According to Roshydrometcenter:

  • the areas of about 500 thousand km2 are periodically flooded in Russia;
  • the areas of about 150 thousand km2 a flooded with catastrophic consequences (more than 300 cities, tens of thousands of villages and more than 7 million hectares of agricultural land are located there);
  • average annual flood damage in Russia is estimated at more than 50 billion rubles
  • the flood damage in the Kuban, which occurred in 2011, is estimated at 2 billion rubles;
  • the flood damage on July 7, 2012 is estimated at 20 billion rubles. The flood damaged thousands of residential building in Gelendzhik, Krymsk and Novorossiysk, as well as a number of settlements in Krasnodar region.The energy, gas and water supply systems, automobile and railway traffic were violated. According to the prosecutor’s office, 168 people were killed, 2 more missing. Most the dead – in Krymsk, where the strongest impact occurred. In this city, 153 people were killed, more than 60 thousand people became victims. 1.69 thousand of buildings were completely destroyed. About 6.1 thousand of buildings were damaged.

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