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Daria V. Sokolova, Dinh Kha Dang, Vadim A. Kuzmin Agreement №

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Presentation on theme: "Daria V. Sokolova, Dinh Kha Dang, Vadim A. Kuzmin Agreement №"— Presentation transcript:

1 Use of «MLCM3» software for flash flood forecasting in changing climate
Daria V. Sokolova, Dinh Kha Dang, Vadim A. Kuzmin Agreement № Introduction Study area & Methods Data Analysis & Results 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. 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, especially, in remote regions of Siberia. However, the developing economy and population safety make us to issue warnings based on reliable forecasts. For this purpose, a new hydrological model, MLCM3 (Multi-Layer Conceptual Model, 3rd generation) has been developed in the Russian State Hydrometeorological University. MLCM3 is a "rainfall−runoff“ model with flexible structure and high level of “conceptualization”. Model forcing includes precipitation and evaporation data basically coming from NWP model output. Water comes to the outlet through several layers; their number as well as two parameters (thickness and infiltration rate) for each of them, surface flow velocity (when the top layer is full of water) are optimized. The software is designed for forecasting river flow, which allows assessing hydrometeorological risks in conditions of climate change and variable anthropogenic load on river watersheds. The program interface Study Area: Creek Privratnyj is the right tributary of the Oredezh River and refers to the catchment area of the Baltic Sea. It originates in a swamp. It has two channels. At first the stream flows in the direction from east to west. Then he changes it and flows through the log with a slight bias. Further, it proceeds on the border of the base section of the RSHU practice base in the village of Daimishche. The length of the stream is about 500 m. The catchment area is approximately 0.05 km2. Catchment forest, overgrown with spruce forest, partially waterlogged. Water discharge in the middle of 0.2 l / s, in the period of rainwater l / s. The Creek Privratnyj refers to flat low watercourses, which are characterized by mixed feeding with predominance of rainwater. Scheme of hydrological model MLCM3 Block for setting calibration, validation and modelling boundaries General view of the data setting area Creek Privratnyj in Russia: from until Used calibration: SLS; Used objective function:MSOF; Used validation function:MSOF Formation of the model "input" can be done in manual and automatic mode. Manual or automatic calibration of the model can be performed using either purposely developed for this model optimization algorithm, or Nelder-Mead’s one, or SLS. For the model calibration, the multi-scale objective function (MSOF) proposed by Koren is used. It has shown its very high efficiency when model forcing data have high level of uncertainty. Other types of objective functions also can be used, such as mean square error, Nash-Sutcliff criterion, and criterion S/𝜎. Multiscale and classic objective functions that we used Objective function MSOF - one of the most important aspects of manual calibration of hydrologic models is that human beings are very good at assessing the quality of model simulation at many different temporal scales of aggregation simultaneously. To emulate this multi-scale nature of manual calibration, we employ in this work an objective function composed of contributions from a wide range of time scales of aggregation. The particular objective function MSOF used in this work was proposed by Koren and has the following form: 𝑞 𝑜,𝑘,𝑖 and 𝑞 𝑠,𝑘,𝑖 — measured and modeled discharge of water averaged over the time interval 𝑘 𝜎 𝑘 — Mean square error deviation of the discharge of water rate of 𝑘, 𝑛— Total number of scales, 𝑚 𝑘 — the number of items of each scale 𝑘 The main advantage of the MLCM3, in comparison to the Sacramento Soil Moisture Accounting Model (SAC-SMA), Australian Water Balance Model (AWBM), Soil Moisture Accounting and Routing (SMAR) model and similar models, is that its automatic calibration is very fast and efficient with less volume of information. For instance, in comparison to SAC-SMA, which is calibrated using either Shuffled Complex Evolution algorithm (SCE-UA), or Stepwise Line Search (SLS), automatically calibrated MLCM3 gives better or comparable results without using any “a priori” data or essential processor resources. This advantage allows using the MLCM3 for very fast streamflow prediction in many basins. When assimilated NWP model output data used to force the model, the forecasts accuracy is quite acceptable and enough for automatic warning. Correlation 𝐒 𝛔 и 𝐒 𝛔 𝛅 reflecting the ratio of the mean-square error of forecasts and the natural variability of the simulated hydrological process, are the official criteria for the accuracy of hydrological forecasts in the Russian Federation S= 𝑖=1 𝑛 ( 𝑦 𝑖 − 𝑦` 𝑖 𝑛−𝑚 𝑦 𝑖 and 𝑦` 𝑖 - actual and modeled water flow, 𝑛- number of terms, 𝑚- degrees of freedom The Nash-Sutcliffe model efficiency coefficient is used to assess the predictive power of hydrological models.  It is defined as E= 𝑡=1 𝑇 ( 𝑄𝑡 0− 𝑄𝑡 𝑚 ) 𝑡=1 𝑇 ( 𝑄𝑡 0− 𝑄 𝑡 0 ) 2 𝑄 o ‒ actual water flow Qm ‒ modeled flow Qot  actual water flow at time  t. Conclusions The software «MLCM3» is intended for forecasting and modeling rainfall flash floods. The «MLCM3» is an application that utilizes an intuitive user interface that makes imputing and editing experiments with data fast and efficient. Key features of the program: High prognostic efficiency of flow forecasting based on the MLCM3 model; The possibility of using the developed technology for effective background flow forecasting on unexplored and poorly known rivers; The software "MLCM3.v3" can be used for interactive and for fully automated flow forecasting The program allows you to obtain comparable results of flow simulation in the lower level of supply with initial data. The main function of the program “MLCM3" is the processing of input files containing data on hydrometeorological variables at the time of the calculation. As a background forecast, the data of the external mesoscale meteorological model (Weather Research and Forecasting (WRF) - a package of modeling meteorological processes) are used. Also please note that, in comparison to the 2nd generation of the model, a very useful new option has been added. Now it is possible to set upvariable infiltration rate of the top layer; this option is quite promising in terms of spring floods modeling. (At the moment it is necessary to perform more numerical experiments with snow melting; obtained results will be reported later. What data do we use? Use special txt format (.dat or .DATA) This research was supported by Ministry of Education and Science of the Russian Federation scientific research project № : "Development of methodological foundations and technologies for water resources management in poorly known river systems by hydrometeorological observations (on the example of the Mekong River basin)". Contact RSHU Russia, St. Petersburg, ; PhD Student Daria Sokolova Professor Vadim Kuzmin VNU Vietnam, Hanoi ; PhD Student Dinh Kha Dang


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