The Amur River flood of 2013: analysis of genesis, frequency assessment, and modeling results
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The Amur River flood of 2013: analysis of genesis, frequency The Amur River flood of 2013: analysis of genesis, frequency assessment, and modeling results assessment, and modeling results A. Gelfan, Yu. Motovilov, A. Kalugin A. Gelfan, Yu. Motovilov, A. Kalugin Water Problem Institute, Russian Academy of Sciences, Moscow, Russia Water Problem Institute, Russian Academy of Sciences, Moscow, Russia e-mail e-mail : : [email protected] [email protected] Abstract The 2013 Amur River flood was one of the most significant and damaging natural disaster ever to hit Russia. During July-September of 2013, almost the whole basin of the Amur River, the tenth largest river basin in the world, was stricken by unprecedentedly powerful and protracted flooding. The magnitude of this flood event was extraordinary: extreme water levels were registered at the streamflow gauges along the main river and its tributaries; within the largest cities (Khabarovsk, Komsomolsk-on- Amur) the Amur River reached the record stage, 1.5-2 meters surpassing the previous records for tens years of observations. In the Russian part of the basin, damages approached $1.3 billion. In our study, two main causes of the Amur flood of 2013 have been analysed as follows: (1) the unique atmospheric situation, which was characterised by formation of the strong extratropical blocking pattern over north-west of the Pacific Ocean during the monsoon season, and resulted in anomalously heavy and prolonged rain events over the basin; and (2) cold, snowy winter of 2012-2013 and late snowmelt season of 2013 lead to saturation of soils over the vast territory just before the heavy rains. The main observed characteristics of flood have been summarized and an attempt has been carried out to assess frequency of the extreme flood peak discharge registered in the Khabarovsk city in August 2013. It has been shown that there is a large uncertainty in statistical assessment of the observed flood hazard: the recurrence interval of the extreme discharge varies from 100 to 300 years depending on the probability distribution curve fitting the available discharge observation data. The physically-based semi-distributed model of runoff generation in the Amur River basin has been developed and applied for reproducing the flood of 2013. The model is based on the ECOMAG modelling system and describes processes of snow accumulation and melt, soil freezing and thawing, water infiltration into unfrozen and frozen soil, evapotranspiration, thermal and water regime of soil, overland and subsurface flow. To simulate channel flow a hydrodynamic MIKE-11 model was coupled with the ECOMAG. The model was applied for the middle part of the Amur River including two largest left tributaries, Zeya and Bureya Rivers, where large reservoirs are located. The model was calibrated using streamflow discharges measured in the different gauges of the main river and its tributaries for 10 years (2000-2009). Validation of the model was carried out for the period of 2010-2013. For the flood of 2013, the Nash and Sutcliffe efficiency criterion of the river stage simulation has been obtained as 0.84- 0.94 depending on the streamflow gauge. Numerical experiments have been carried out to assess the effect of the Zeya reservoir regulation on the middle Amur River stage. It has been shown that in the absence of the reservoir, the water levels within the Blagoveshchensk city (downstream of the Zeya River mouth) would be 0.5-1.5 m higher than the levels measured during the flood of 2013. The extreme flood that formed in the Amur River basin in July September 2013 ⎯ embraced vast territories in the Russian Far East and Northeastern China and became one of the major natural disaster of the XXI century in terms of duration, the area involved, the number of persons affected, and the economic losses. Almost the entire Amur Basin, which ranks tenth in the world in the area (1.85 million km 2 ), suffered from a disastrous flood The Russian part of the basin The total damage is at least USD 1.3 billion The total number of persons affected by the flood was in excess of 168000 More than 12000 houses were destroyed and almost 20% of them are beyond rebuilding The Chinese part of the basin (much more populated) The total damage is at least 5.3 USD billion There had been 85 deaths, and 105 people are missing (Sept., 2013) At least 306,000 homes and structures were damaged or destroyed Genesis of the flood The main factor is the unique synoptic situation characterised by the following main features: 1) the formation of a high frontal zone, along which deep cyclones moved incessantly during two months 2) the formation of a blocking high pressure domain above the northwestern Pacific, which hampered a displacement of those cyclones from the continent toward the Sea of Okhotsk Another critical factor of the Amur flood is the high water saturation of soils in the vast areas of river basins by the beginning of flood season. High moisture content of soils was a result of the cold snowy winter of 2012 2013 and a ⎯ late spring, during which a considerable portion of snowmelt water was absorbed by soils. The saturation of soils has led to a critical drop in their water retention capacity and an abrupt decrease in the natural regulating capacity of river basins before the rains. Near the largest cities, the river stage exceeded the maximal one recorded during the period of instrumental observations Annual maximum flood peak discharge: Amur River at the Khabarovsk city 92 years of observations including maximal discharge of 0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000 1895 1914 1933 1952 1971 1990 46000 м 3 /с 0 10000 20000 30000 40000 50000 60000 70000 80000 90000 0.0001 0.001 0.01 0.1 1 The recurrence interval of the maximal discharge of 46000 m 3 /s (Sept. 08, 2013) estimated using Kritsky Menkel ⎯ distribution is 270 years, while that derived from the Log- Pearson type III distribution is 100 years. Log-Pearson III distributio n Kritsky- Menkel distributi on Physically based modeling of runoff generation in the Amur River basin Semi-distributed physically based model ECOMAG (Motovilov) (Ecological Model for Applied Geophysics) Examples of ECOMAG applications D igital elevation m odel Soil Vegetation D ischarges in rivernetw ork Layerofrunoff H ydrographs Layerofrunoff Soil m oisture Evapotranspiration BaseG IS inform ation Simulation D ata base G IS -analysisofsim ulated results Clim ate Pollution Soil Vegetation Verticalstructure ofECO M AG M odelled area Hydrographs of the water inflow into the Zeya reservoir The ECOMAG calibration (2000-2009) The ECOMAG validation (2010-2013) Conclusions 1. Estimates of the extreme flood frequency obtained from the available scarce data in the Amur River basin are uncertain and information is needed additional to that extracted from the data. The additional information can be obtained from the results of the extreme flood modeling. 2. The model has been developed based on the ECOMAG model of runoff generation coupled with the MIKE-11 model of channel flow. The model has allowed us representing hydrological processes resulted in the extreme flood generation. 3. Numerical experiments have been carried out to assess the effect of the Zeya reservoir regulation on the middle Amur River stage. It has been shown that in the absence of the reservoir regulation capacity, peak water levels Simulated hydrographs at the Zeya River mouth (ECOMAG) Hydrograph is calculated under the assumption of absence of the Zeya reservoir regulation capacity (2) Hydrograph is calculated under the reservoir regulation (1) Numerical experiments on the effect of the Zeya reservoir on flood mitigation Study Area Calibration of the channel flow sub-model (MIKE-11) against the river stage measured at different gauges of the Amur River (1975- 1986) Validation of the channel flow sub-model (MIKE-11) against the river stage measured at different gauges of the Amur River(1994- 2008) Modeling the river stage at the different gauges of the Amur River (01/05/2013 – 30/09/2013) Study basin The major problems that one faces when trying to apply a standard FFA for estimating the recurrence interval of the extreme flood of 2013 is the lack of daily discharge data. Presently, as little as two streamflow gages (Khabarovsk and Bogorodskoe) are in operation on the 2824 km Amur River. m 3 /s Observed annual maximum flood peak discharges m 3 /s The absence of the regulating capacity of the reservoir would cause an increase in water level on the rise of flood wave (7 August) by 1.5 m at Blagoveshchensk and Grodekovo gages, by 1.1 m at Konstantinovka and Poyarkovo gages, and by 1.4 m at Innokent’evka gage , but at flood peak in the Amur (from 20 to 21 August) would cause an increase in water level by 0.45 m at Blagoveshchensk and Grodekovo gages, by 0.35 m at Konstantinovka gage, by 0.4 m at Poyarkovo gage, and by 0.5 m at Innokent'evka gage. Modeling the river stage at the different gauges of the Amur River (MIKE-11) % On the limitations of the standard flood frequency analysis of the Amur streamflow data Modeling results
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The Amur River flood of 2013: analysis of genesis, frequency assessment, and modeling results A. Gelfan , Yu. Motovilov , A. Kalugin Water Problem Institute, Russian Academy of Sciences, Moscow, Russia e-mail : [email protected]. Abstract - PowerPoint PPT Presentation
Transcript of The Amur River flood of 2013: analysis of genesis, frequency assessment, and modeling results
The Amur River flood of 2013: analysis of genesis, frequency assessment, and modeling resultsThe Amur River flood of 2013: analysis of genesis, frequency assessment, and modeling resultsA. Gelfan, Yu. Motovilov, A. Kalugin A. Gelfan, Yu. Motovilov, A. Kalugin
Water Problem Institute, Russian Academy of Sciences, Moscow, RussiaWater Problem Institute, Russian Academy of Sciences, Moscow, Russiae-maile-mail: : [email protected]@aqua.laser.ru
AbstractThe 2013 Amur River flood was one of the most significant and damaging natural disaster ever
to hit Russia. During July-September of 2013, almost the whole basin of the Amur River, the tenth largest river basin in the world, was stricken by unprecedentedly powerful and protracted flooding. The magnitude of this flood event was extraordinary: extreme water levels were registered at the streamflow gauges along the main river and its tributaries; within the largest cities (Khabarovsk, Komsomolsk-on-Amur) the Amur River reached the record stage, 1.5-2 meters surpassing the previous records for tens years of observations. In the Russian part of the basin, damages approached $1.3 billion.
In our study, two main causes of the Amur flood of 2013 have been analysed as follows: (1) the unique atmospheric situation, which was characterised by formation of the strong extratropical blocking pattern over north-west of the Pacific Ocean during the monsoon season, and resulted in anomalously heavy and prolonged rain events over the basin; and (2) cold, snowy winter of 2012-2013 and late snowmelt season of 2013 lead to saturation of soils over the vast territory just before the heavy rains. The main observed characteristics of flood have been summarized and an attempt has been carried out to assess frequency of the extreme flood peak discharge registered in the Khabarovsk city in August 2013. It has been shown that there is a large uncertainty in statistical assessment of the observed flood hazard: the recurrence interval of the extreme discharge varies from 100 to 300 years depending on the probability distribution curve fitting the available discharge observation data.
The physically-based semi-distributed model of runoff generation in the Amur River basin has been developed and applied for reproducing the flood of 2013. The model is based on the ECOMAG modelling system and describes processes of snow accumulation and melt, soil freezing and thawing, water infiltration into unfrozen and frozen soil, evapotranspiration, thermal and water regime of soil, overland and subsurface flow. To simulate channel flow a hydrodynamic MIKE-11 model was coupled with the ECOMAG. The model was applied for the middle part of the Amur River including two largest left tributaries, Zeya and Bureya Rivers, where large reservoirs are located. The model was calibrated using streamflow discharges measured in the different gauges of the main river and its tributaries for 10 years (2000-2009). Validation of the model was carried out for the period of 2010-2013. For the flood of 2013, the Nash and Sutcliffe efficiency criterion of the river stage simulation has been obtained as 0.84-0.94 depending on the streamflow gauge.
Numerical experiments have been carried out to assess the effect of the Zeya reservoir regulation on the middle Amur River stage. It has been shown that in the absence of the reservoir, the water levels within the Blagoveshchensk city (downstream of the Zeya River mouth) would be 0.5-1.5 m higher than the levels measured during the flood of 2013.
The extreme flood that formed in the Amur River basin in July September 2013 ⎯embraced vast territories in the Russian Far East and Northeastern China and became one of the major natural disaster of the XXI century in terms of duration, the area involved, the number of persons affected, and the economic losses. Almost the entire Amur Basin, which ranks tenth in the world in the area (1.85 million km2), suffered from a disastrous flood
The Russian part of the basin The total damage is at least USD 1.3 billion The total number of persons affected by the flood was in excess of 168000 More than 12000 houses were destroyed and almost 20% of them are beyond rebuilding
The Chinese part of the basin (much more populated) The total damage is at least 5.3 USD billion There had been 85 deaths, and 105 people are missing (Sept., 2013) At least 306,000 homes and structures were damaged or destroyed
Genesis of the floodThe main factor is the unique synoptic situation characterised by the following main features: 1) the formation of a high frontal zone, along which deep cyclones moved incessantly during two months2) the formation of a blocking high pressure domain above the northwestern Pacific, which hampered a displacementof those cyclones from the continent toward the Sea of Okhotsk Another critical factor of the Amur flood is the high water saturation of soils in the vast areas of river basins by the beginning of flood season. High moisture content of soils was a result of the cold snowy winter of 2012 2013 and a late spring, during which a ⎯considerable portion of snowmelt water was absorbed by soils. The saturation of soils has led to a critical drop in their water retention capacity and an abrupt decrease in the natural regulating capacity of river basins before the rains.
Near the largest cities, the river stage exceeded the maximal one recorded during the period of instrumental observations
Annual maximum flood peak discharge: Amur River at the Khabarovsk city 92 years of observations including maximal discharge of Sept. 8, 2013
0
5000
10000
15000
20000
25000
30000
35000
40000
45000
50000
1895 1914 1933 1952 1971 1990
46000 м3/с
0
10000
20000
30000
40000
50000
60000
70000
80000
90000
0.0001 0.001 0.01 0.1 1
The recurrence interval of the maximal discharge of 46000 m3/s (Sept. 08, 2013) estimated using Kritsky Menkel distribution is ⎯270 years, while that derived from the Log-Pearson type III distribution is 100 years.
Log-Pearson III distribution
Kritsky-Menkel
distribution
Physically based modeling of runoff generation in the Amur River basinSemi-distributed physically based model ECOMAG (Motovilov)
(Ecological Model for Applied Geophysics)
Examples of ECOMAG applications
Digital elevation model
Soil
Vegetation
Discharges in river network
Layer of runoff
Hydrographs
Layer of runoff
Soil moisture
Evapotranspiration
Base GIS information
Simulation
Data base
GIS - analysis of simulated results
Climate
Pollution
Soil
Vegetation
Vertical structure of ECOMAG
Modelled area
Hydrographs of the water inflow into the Zeya reservoir
The ECOMAG calibration (2000-2009) The ECOMAG validation (2010-2013)
Conclusions1. Estimates of the extreme flood frequency obtained from the available scarce data in the Amur River basin are uncertain and information is needed additional to that extracted from the data. The additional information can be obtained from the results of the extreme flood modeling. 2. The model has been developed based on the ECOMAG model of runoff generation coupled with the MIKE-11 model of channel flow. The model has allowed us representing hydrological processes resulted in the extreme flood generation.3. Numerical experiments have been carried out to assess the effect of the Zeya reservoir regulation on the middle Amur River stage. It has been shown that in the absence of the reservoir regulation capacity, peak water levels within the Blagoveshchensk city (downstream of the Zeya River mouth) would be 0.5-1.5 m higher than the levels measured during the flood of 2013.
Simulated hydrographs at the Zeya River mouth (ECOMAG)Hydrograph is calculated under the assumption of
absence of the Zeya reservoir regulation capacity
(2)Hydrograph is calculated under the reservoir regulation
(1)
Numerical experiments on the effect of the Zeya reservoir on flood mitigation
Study Area
Calibration of the channel flow sub-model (MIKE-11) against the river stage measured at different gauges of the Amur River (1975-1986)
Validation of the channel flow sub-model (MIKE-11) against the river stage measured at different gauges of the Amur River(1994-2008)
Modeling the river stage at the different gauges of the Amur River (01/05/2013 – 30/09/2013)
Study basin
The major problems that one faces when trying to apply a standard FFA for estimating the recurrence interval of the extreme flood of 2013 is the lack of daily discharge data.Presently, as little as two streamflow gages (Khabarovsk and Bogorodskoe) are in operation on the 2824 km Amur River.
m3/s
Observed annual maximum flood peak discharges
m3/s
The absence of the regulating capacity of the reservoir would cause an increase in water level on the rise of flood wave (7 August) by 1.5 m at Blagoveshchensk and Grodekovo gages, by 1.1 m at Konstantinovka and Poyarkovo gages, and by 1.4 m at Innokent’evka gage , but at flood peak in the Amur (from 20 to 21 August) would cause an increase in water level by 0.45 m at Blagoveshchensk and Grodekovo gages, by 0.35 m at Konstantinovka gage, by 0.4 m at Poyarkovo gage, and by 0.5 m at Innokent'evka gage.
Modeling the river stage at the different gauges of the Amur River (MIKE-11)
%
On the limitations of the standard flood frequency analysis of the Amur streamflow data
Modeling results
