1 / 29

VIDRA FLOOD SIMULATION AND FORCASTING MODEL

VIDRA FLOOD SIMULATION AND FORCASTING MODEL. National Institute of Hydrology and Water Management Bucharest, ROMANIA. The VIDRA model has been developed in the National Institute of Meteorology and Hydrology – Bucharest, Romania.

candie
Télécharger la présentation

VIDRA FLOOD SIMULATION AND FORCASTING MODEL

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. VIDRA FLOOD SIMULATION AND FORCASTING MODEL National Institute of Hydrology and Water Management Bucharest, ROMANIA

  2. The VIDRA model has been developed in the National Institute of Meteorology and Hydrology – Bucharest, Romania. The original purpose of the model was to be used in flood wave forecasting both in small and large basins with/without hydraulic structures of various kinds. The model has been applied to flood simulation for the Romanian rivers starting with 1984.

  3. DESCRIPTION The model is a conceptual model with physically based semi-distributed parameters simulating the reaction of the natural and structured river basins to various precipitation impulses. The major structures of the model are: water release from the snow cover, effective rainfall determination, flood wave routing in the river bed, flood wave attenuation through reservoirs and forecasting.

  4. VIDRA complex model includes the following sub-models in view to compute the water flow: • Snow melting model allowing the evaluation of the water release from the snow cover, by knowing its characteristics and the causing meteorological elements; • Effective rain calculation model allowing to extract from the total water flow entering the basin (precipitation and water release from the snow cover) the losses through the evapotranspiration and infiltration finally resulting in the effective rain that contribute to runoff formation; • Transfer model by means of which the discharge hydrograph in the sub-basins is calculated by knowing the effective rain and the parameters of the transfer function; • Routing model achieving the composition of the runoff occurred in the sub-basins (tributaries) and its routing through the bed; • Attenuation model of the runoff through: • Reservoirs provided with any type of dischargers (including hydropower users or derivation channels); • Reservoirs with lateral polders with any type of discharger between the reservoir and the polder, at the outlet from the polder respectively downstream the dam; • Lateral polders on the river beds; the water entrance and evacuation can be done by any type of dischargers; • Derivation channels on the riverbeds with admission controlled or not by driving mechanisms.

  5. The large basins are divided into homogenous units (sub-basins with surfaces smaller than 150-300 km2). The model computes the discharge hydrographs on sub-basins, their integration and routing on the main river and on the tributaries and estimates the flood mitigation through reservoirs. The model has updating procedures, in principle based of the comparison between the simulated discharges and those achieved at various moments of the forecast elaboration. Internal time step for calculation of the VIDRA model is 1 hour and temporal resolution of output may vary between 1 hour and 24 hours.

  6. Input data Permanent input data Model parameters corresponding to each sub-basin and to each component of VIDRA module structure; • these parameters are loaded in a specific file for a given basin; • the computer program has an interactive facility to call this file and change in real time the parameters, both in calibration process and in forecasting work; Hydrographic basin and network features and the constructive characteristics of the hydraulic structures that alter the natural flow.

  7. Variable Input data Meteorological data (precipitation and temperatures): The averaged rainfall over the basin, determined as the arithmetic mean rainfall recorded at the meteorological stations as well as those measured at the rain-gauge points. The time step’s distribution of the averaged rainfall over the basin, computed on the basis of the time step’s precipitation recorded at the meteorological stations. For the periods when the pluviographs did not operate, a uniform time distribution was considered. The characteristic elements of the snow cover (depth and density) necessary for the determination of the water equivalent of the snow cover recorded at the meteorological stations. The air temperatures recorded at the meteorological station to which some correction has been applied taking into account the difference between the altitude of the meteorological station and the mean altitude of the river basin.

  8. Input data Hydrological data: The time-step’s discharges at the control gauging station (being needed to calibrate, verify and updating the outputs in operational forecasting; these data are loaded in a specific file for a given basin). Soil moisture estimation for each sub-basin. Initial conditions for each sub-basins refer to the antecedent soil moisture index in correlation with the load level of the reservoir of the unsaturated zone, the load levels of the interception and depression reservoirs (usually they are considered empty before the flood event), the water equivalent of the snow cover at the beginning of the forecast interval (only for the snowmelt events) and start stream flow that give the load level of reservoir of the saturated zone); default all these values are zero; the data are loaded in a specific file for a given basin.

  9. STRUCTURES • Determination of the snow-melt water - The degree-day method • Calculation of the effective rainfall - PNET deterministic reservoir model • Integration of the effective rainfall on the slopes and in the primary river network - Unit hydrograph method • Composition of the flood waves and their routing along the riverbed - Muskingum transfer function • Flood wave mitigation through reservoirs - Puls method • Forecasting updating - CORA procedure

  10. DETERMINATION OF SNOWMELT WATERComputing equations Snow melting model allowing the evaluation of the water release from the snow cover, by knowing its characteristics and the causing meteorological elements. In order to determine the daily release of snowmelt water from the snow cover in the intervals without rainfall and during intervals with rainfall respectively the following equations given below are used: where: hz - the daily amount of snowmelt water (mm); Te - the equilibrium temperature ( ºC) whereof any heat exchange between the snow cover and the environment; Tm - the mean daily air temperature (ºC) above the Tetemperature value; M - the melting factor or the degree-day factor (mm/ºC day); hp - the amount of rainfall (mm/day); W - the wind speed (m/s); p - the forest cover coefficient; kv - a parameter having the value 1 for a deforested basin and 0,2 for a completely forested one; ki - a slope coefficient.

  11. The effective rainfall computation model is based on the hypothesis that runoff in a watershed is similar to the runoff in a sequence of four interconnected reservoirs. EFFECTIVE RAINFALLConceptual scheme

  12. Effective rainfall calculation model allowing to extract from the total water flow entering the basin (precipitation and water release from the snow cover) the losses through the evapotranspiration and infiltration finally resulting in the effective rainfall that contributes to runoff formation. EFFECTIVE RAINFALLComputing equations (1/3) In view of determining the infiltration, the model uses a variable infiltration curve depending on the initial soil saturation: with: where: FOM - the maximum infiltration capacity, corresponding to the plant withering point and to the rainfall intensity I; FC - the minimum infiltration capacity of the ground, corresponding to soil saturation state and to the rainfall intensity; SF - a factor considering the seasonal variation of infiltration function of the vegetation state of the slopes; USZNN - the field capacity of the reservoir corresponding to the non-saturated zone; USZN - soil moisture; UI - the initial soil moisture content; Is - standard rainfall intensity.

  13. EFFECTIVE RAINFALLComputing equations (2/3) Function of the amount of precipitation P the mean infiltration INFB over the basin is: The amount of available water for surface flow is: The surface flow SS, sub-surface flow SH, percolation PERC and basic flow SB are computed in terms of the following equations: where: UD - the amount of water available in the depressions; UDM - the maximum capacity of the depression reservoir; CH - the subsurface flow parameter; PSH - the subsurface flow threshold; CB - the base flow parameter; USZN - the amount of water available in the reservoir corresponding to the saturated zone.

  14. EFFECTIVE RAINFALLComputing equations (3/3) The amount of water available in the depressions will be infiltrated and evaporated. The additional infiltration in depressions is computed as follows: At each time interval the humidity from the depression reservoir and from the reservoirs corresponding to the non-saturated zone and to the saturated one, respectively, are determined as follows: The effective rainfall at each time interval (usually 1 hour) is computed as follows:

  15. Transfer model by means of which the discharge hydrographs in the sub-basins are calculated by knowing the effective rainfalls and the parameters of the transfer function. TRANSFER FUNCTIONComputing equations The computation of the discharge hydrographs in small basins (sub-basins) is based on the unit hydrograph method (a discrete transfer function): with: where: uj - the ordinate of the transfer function; kr - the coefficient of the hydrograph falling curve; t - time interval; N - the number of ordinates of the transfer function; T et k - parameters. For a hydrographic basin one considers three transfer functions depending on intensity range of the effective rainfall: small, medium and high.

  16. Routing model achieving the composition of the runoff occurred in the sub-basins (tributaries) and its routing through the river bed. FLOOD ROUTINGComputing equations The computation of the flood routing along the river bed is done by use of a Muskingum type equation: with: where: Q1 et Q2 - the ordinates of the outflow hydrograph from the river reach at the moments 1 and 2; I1 et I2 - the ordinates of the inflow hydrograph to the river reach at the moments 1 and 2;  et  - parameters.

  17. FLOOD ATTENUATION AND COORDINATED CONTROL OF RESERVOIRS In watersheds with hydraulic structures there is a close connection between the hydrological forecasting and reservoir control. Therefore, on account of flood wave forecasting the optimum way for reservoir control is established, i.e. the reservoir outflow hydrographs are employ for hydrological forecasting downstream the reservoirs. In view of flood wave attenuation and control through the reservoirs the coordinated operation method is used. It is based on a certain classification of reservoirs into types and defining for each type, the sets of outflow hydrographs that should satisfy certain objectives and meet the operation restrictions.

  18. CORA procedure detects the error type (amplitude, phase or shape) and realises the necessary corrections in two steps: the rough and the fine updating. UPDATING OF THE FORECAST

  19. UPDATING OF THE FORECASTThe rough updating The rough updating is applied only in the situations where the forecast error is bigger than 10%. • If the error concerns the amplitude the input variables of the model (average rainfall over the basin and/or the effective rainfall) have to be corrected applying a coefficient. • In the situation where the error concerns the phase one shifts to the left or to right the simulated hydrograph, of such manner that it correspond as better as possible to the measured hydrograph. The phase errors are due to the modifications of the roughness of the bed after the calibration works and the embankment of the various river sectors. • If the errors concern the hydrograph shape, another type of unit hydrograph according to the rainfall intensity range is considered in the model. • In the situations where the forecasted hydrographs have to be updated, it is necessary to adapt the exploitation rules of reservoirs according to the updated hydrographs.

  20. UPDATING OF THE FORECASTThe fine updating The fine updating is applied for all the situations aiming to achieve a continuity between the measured hydrograph at the moment of the issue of the forecast and the simulated hydrograph after this moment. In the case of the gauged basins, the fine updating is performed by use of the following recurrent relations: with: where: QFj+1 - the forecasted discharge; QMj - the measured discharge at the moment j; kr - the coefficient of the hydrograph falling curve; u1, u2, u3, ... - the ordinates of the transfer function; PNj-1, PNj, PNj+1 - the effective rainfall at the moments j-1, j and j+1. In the situations of river sectors, the fine updating is realized while using the propagation equation in which one replaces the forecasted discharge by the measured discharge to that moment.

  21. CASE STUDIES The case studies were solved by means of VIDRA model applying aiming to: • flood wave forecasting; • assessment of anthropic influences on the natural hydrological regime; • determination of maximum discharges in basins with hydraulic structures; • computation of probable maximum floods; • assessment of the climate change impact on the hydrological resources of the analyzed basins.

  22. The VIDRA model has been applied usually in the research studies (assessment of man activity impact on the natural hydrological regime, to calculate the maximum discharges with different return probability needed in the design of hydraulics structure (dams, dikes, bridges, etc.), assessment of climate change impact on the hydrological resources) with good results, but also for the Siret river basin for flood forecasting, for the Hydropower Company’s purposes.

  23. Case study for the Mures river basin One application of VIDRA model was achieved in EFFS project (European Flood Forecasting System) under the FP5 (EVK1-1999-00044). The model has been applied for the Mures river basin.

  24. a) b) Examples of mono-waves hydrographs (a) and of double-waves hydrographs (b) in various hydrometric sections from Mures river basin (recorded - red line- and simulated - blue dotted line- hydrographs)

  25. a) b) The recorded (red line) and simulated (blue dotted line) hydrographs corresponding to two gauging stations along the Mures river for the 22 March – 17 April 2000 flood event (a) and for the 25 June – 31 July 1997 flood non- event (b)

  26. a b c Results of VIDRA model parameters calibration for Lunguletu cross section on dambovita river (recorded - red line- and simulated - blue dotted line- hydrographs) for the three flood events: May 1973 (a), July 1975 (b) and June 1979 (c) Topological modeling of the Dambovita river basin

  27. Conclusions regarding the calibration and validation of the VIDRA model parameters in the Mures river basin: • Analyzing the calibration results the VIDRA model can be considered a good model for flood forecasting. The validation made on the flood event from the spring 2000 confirms the calibrated parameters. • The results of the simulations obtained using the VIDRA model for a non flood event show that the model is more appropriate for the floods events, for the non-flood events the errors are greater than those accepted for hydrological forecasts. • Also, the simulations using different flood events with diverse characteristics of the generating factors show that the model is more adequate for the floods generated by precipitation evenly distributed over the basin. • The overall errors are both due to the model errors and to the availability and accuracy of the input data. The main error is found as being stemmed by lack in the spatial distribution of the precipitation over the basin.

  28. Present state of work • We are preparing a data contract with the National Meteorological Administration • We initiate the test for preparation of data collected with the automatic system install in the DESWAT project. The preparation for the online use of the model • We start the calibration of the model for snow data

  29. For more information: • ciprian.corbus@hidro.ro • simota@hidro.ro andreea.marin@hidro.ro ghinescu.andreea@hidro.ro

More Related