GIS Modeling of Territorial Processes using Remote Sensing Data - - PowerPoint PPT Presentation
KAZGEOCOSMOS JSC GIS Modeling of Territorial Processes using Remote Sensing Data Prof. Edige A. Zakarin Director of Remote Sensing Department Inter- -branch branch Geoinformation Geoinformation System System Inter (IGIS) (IGIS) The
Monitoring of agrotechnology, Estimation of plough-land productivity Weather disaster warning Monitoring of transboundary disaster Thermal monitoring seismic activity areas Monitoring of industrial areas Monitoring of nuclear hazard objects Monitoring of sea ice situation Monitoring of minerals quarrying area Wells and oil pipes monitoring
National system of space monitoring Atyrau Astana Subsystem “A dministrator ” Subsystem “Executor” Monitoring of agrotechnology Estimation of plough-land productivity Weather disaster warning Wells and oil pipes monitoring Monitoring of nuclear hazard objects Monitoring of transboundary disaster Thermal monitoringseismic activity areas Monitoring of industrial areas Monitoring of minerals quarrying area Monitoring of ice situation GIS-technology ARC Objects interface MGIS Possibility of GIS- technology adding Output data standard Input data standar d Request Request Report Subsystem “C ustomer ” Customer 4 Customer 3 Customer 2 Customer 1 ARC Objects interface MGIS Possibility of customer adding Search of reports and space images Report viewing tools Almaty _____________________ Data receiving center Test sites Request and reports database Monitoring of agrotechnology Estimation of plough-land productivity Weather disaster warning Wells and oil pipes monitoring Environmental contamination monitoring Dust storm monitoring Thermal monitoringseismic activity areas Monitoring of industrial areas Monitoring of minerals quarrying area Monitoring of ice situation Access permissions Access permissions Query Space images Archive data Geoinformation data Geoinformation database Archives of remote sensing data Metadata database National archives
sensing data Report Space images Archive data Geoinformation data Archives of reports
System consists of three subsystems: “Executor”, “Customer” and “Administrator”. The number of subsystems “Executor” and “Customer” are not limited. All subsystems are the client of one server.
!
!
! Аtyrau
Astana Almaty
12:receivedReport 1:sendOrder 2:processOrder 11:sendReport 3:receiveOrder 10:updateReport 5:imageOrder 6:sendImage 7 : r e c e i v e I m a g e 4 : e x e c u t e O r d e r 9 : s e n d R e p
t 8:makeReport Customer Executor
Subsystems of IGIS will located in different point of territory of
be realized between Atyrau (RS centre), Almaty (SubsysExecuter) and Astana (SubsysCustomer).
IGIS Interfaces Input data Model Common tools Common database Main program «Model - developer» «Model – database» «Model - user» Maps Space images Field data Mathematical models Engineering models New models
ref ref ref ref ref ref IGIS Executor Dispatcher RS Center Draw survey schedule for agriculture year Draw schedule Draw request for survey Draw request Submit Signal OK Submit order
T Submit order
[RADAR SA T] Process [Survey] Carry out primary processing Receive and transmite survey "winter tillage" [IRS] Process Receive images [RADAR SA T] Thematic process "winter tillage" [IRS] Thematic process "winter tillage" Form report "winter tillage" Load DB
{E xe cutor. Agrotechnolog y "winter tilla ge" in Se ptembe r}
Load DB Load DB
Receive ima ges Receive ima ges Form rep
"snow" Form rep
"moisture " {E xe cuto r. Ag rotechnolog y "snow" in Desemb er} {E xecu to r. Ag rotechn
y "moisture " in Apri l} [RADARSA T] Thema ti c process "snow" [IRS ] Thema ti c process "snow" [RADARSA T] Thema ti c process "moisture " [IRS ] Thema ti c process "moisture " Receive ima ges [RADARSA T] Thema ti c process "presowing " [IRS ] Thema ti c pro cess "presowing " {E x e cu to r. Ag rotechn
" in May} Form rep
"presowing "
Load DB
Receive ima ges
Load DB
[RADARSA T] Thema ti c process "sowing " [IRS ] Thema ti c process "sowing " {E x e cu to r. Ag rotechn
g" in May} Form rep
wing" Receive ima ges [RADARSA T] Thema ti c process "harvest" [IRS ] Thema ti c process "harvest" Form rep
st"
Load DB
{E xe cuto r. Ag rotechnolog y "harvest" in Aug
t
Winter tillage
Snow retention
M
s t u r e r e t e n t i
C r
Crop processing M
i n g d
n D i r e c t h a r v e s t G r i n d i n g P p r e s
i n g
Плоскорезная зябь на глубину 22-24 см плоскорезом-глубокорыхлителем ПГ-3-5 Безотвальная зябь на глубину 10-14 см почвообрабатывающим комплексом Кейс Многолетние травы (житняк) Лесные посадки Направление обработки почвы Стерня пшеницы, снегозадержание Стерня пшеницы Стерня ячменя Пар# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
Условные обозначения Агротехнические фоны на 24 декабря 2005 года, ТОО "Агрофирма Актык"# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
61 61 61 61 61 61 61 61 61 62 62 62 62 62 62 62 62 62 63 63 63 63 63 63 63 63 63 64 64 64 64 64 64 64 64 64 65 65 65 65 65 65 65 65 65 66 66 66 66 66 66 66 66 66 68 68 68 68 68 68 68 68 68 67 67 67 67 67 67 67 67 67 69 69 69 69 69 69 69 69 69 70 70 70 70 70 70 70 70 70 71 71 71 71 71 71 71 71 71 72-1 72-1 72-1 72-1 72-1 72-1 72-1 72-1 72-1 60 60 60 60 60 60 60 60 60 45 45 45 45 45 45 45 45 45 47 47 47 47 47 47 47 47 47 49-1 49-1 49-1 49-1 49-1 49-1 49-1 49-1 49-1 49-2 49-2 49-2 49-2 49-2 49-2 49-2 49-2 49-2 51 51 51 51 51 51 51 51 51 52 52 52 52 52 52 52 52 52 53 53 53 53 53 53 53 53 53 54-2 54-2 54-2 54-2 54-2 54-2 54-2 54-2 54-2 56 56 56 56 56 56 56 56 56 57 57 57 57 57 57 57 57 57 59 59 59 59 59 59 59 59 59 48 48 48 48 48 48 48 48 48 50-1 50-1 50-1 50-1 50-1 50-1 50-1 50-1 50-1 50-2 50-2 50-2 50-2 50-2 50-2 50-2 50-2 50-2 54-1 54-1 54-1 54-1 54-1 54-1 54-1 54-1 54-1 53 53 53 53 53 53 53 53 53 58 58 58 58 58 58 58 58 58 41-1 41-1 41-1 41-1 41-1 41-1 41-1 41-1 41-1 41-2 41-2 41-2 41-2 41-2 41-2 41-2 41-2 41-2 42 42 42 42 42 42 42 42 42 43 43 43 43 43 43 43 43 43 23-1 23-1 23-1 23-1 23-1 23-1 23-1 23-1 23-1 24 24 24 24 24 24 24 24 24 26-1 26-1 26-1 26-1 26-1 26-1 26-1 26-1 26-1 26-3 26-3 26-3 26-3 26-3 26-3 26-3 26-3 26-3 28-2 28-2 28-2 28-2 28-2 28-2 28-2 28-2 28-2 30 30 30 30 30 30 30 30 30 32 32 32 32 32 32 32 32 32 34 34 34 34 34 34 34 34 34 36 36 36 36 36 36 36 36 36 38 38 38 38 38 38 38 38 38 67 67 67 67 67 67 67 67 67 25-1 25-1 25-1 25-1 25-1 25-1 25-1 25-1 25-1 6 6 6 6 6 6 6 6 6 23-3 23-3 23-3 23-3 23-3 23-3 23-3 23-3 23-3 25-2 25-2 25-2 25-2 25-2 25-2 25-2 25-2 25-2 8 8 8 8 8 8 8 7-2 7-2 7-2 7-2 7-2 7-2 7-2 7-2 7-2 9 9 9 9 9 9 9 27 27 27 27 27 27 27 27 27 29 29 29 29 29 29 29 29 29 11 11 11 11 11 11 11 11 11 10 10 10 10 10 10 10 10 10 12 12 12 12 12 12 12 12 12 13 13 13 13 13 13 13 13 13 31 31 31 31 31 31 31 31 31 15 15 15 15 15 15 15 15 15 14 14 14 14 14 14 14 14 14 33 33 33 33 33 33 33 33 33 16 16 16 16 16 16 16 16 16 17 17 17 17 17 17 17 17 17 35-1 35-1 35-1 35-1 35-1 35-1 35-1 35-1 35-1 35-3 35-3 35-3 35-3 35-3 35-3 35-3 35-3 35-3 18 18 18 18 18 18 18 18 18 37 37 37 37 37 37 37 37 37 22 22 22 22 22 22 22 22 22 19 19 19 19 19 19 19 19 19 21 21 21 21 21 21 21 21 21 20-1 20-1 20-1 20-1 20-1 20-1 20-1 20-1 20-1 20-2 20-2 20-2 20-2 20-2 20-2 20-2 20-2 20-2 3 3 3 3 3 3 3 4 4 4 4 4 4 4 7-1 7-1 7-1 7-1 7-1 7-1 7-1 7-1 7-1RADARSAT-1, 24.12.05. RADARSAT-1, 21.12.05. Agricultural background, 24.12.2005 RADARSAT-1, 30.04.06. RADARSAT-1, 30.04.06, classification IRS, 7.05.06, classification
З ябь без закрытия влаги З ябь с закры тием влаги Пар без закрытия влаги Пар с закрытием влаги Условные обозначения А гротехнические фоны на 30 апреля 2006 года, ТОО "Агрофирма Актык" 47б/з 47б/з 47б/з 47б/з 47б/з 47б/з 47б/з 47б/з 47б/з 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 6 6 6 6 6 6 6 6 6 7-2 7-2 7-2 7-2 7-2 7-2 7-2 7-2 7-2 7-4 7-4 7-4 7-4 7-4 7-4 7-4 7-4 7-4 8 8 8 8 8 8 8 9 9 9 9 9 9 9 9 9 10 10 10 10 10 10 10 10 10 11 11 11 11 11 11 11 11 11 12 12 12 12 12 12 12 12 12 13 13 13 13 13 13 13 13 13 14 14 14 14 14 14 14 14 14 15 15 15 15 15 15 15 15 15 16з 16з 16з 16з 16з 16з 16з 16з 16з 17 17 17 17 17 17 17 17 17 18 18 18 18 18 18 18 18 18 19 19 19 19 19 19 19 19 19 20-1 20-1 20-1 20-1 20-1 20-1 20-1 20-1 20-1 20-2 20-2 20-2 20-2 20-2 20-2 20-2 20-2 20-2 21 21 21 21 21 21 21 21 21 22 22 22 22 22 22 22 22 22 23-1 23-1 23-1 23-1 23-1 23-1 23-1 23-1 23-1 23-2 23-2 23-2 23-2 23-2 23-2 23-2 23-2 23-2 23-23 23-23 23-23 23-23 23-23 23-23 23-23 23-23 23-23 24 24 24 24 24 24 24 24 24 25-1 25-1 25-1 25-1 25-1 25-1 25-1 25-1 25-1 25-2 25-2 25-2 25-2 25-2 25-2 25-2 25-2 25-2 26-1 26-1 26-1 26-1 26-1 26-1 26-1 26-1 26-1 26-3 26-3 26-3 26-3 26-3 26-3 26-3 26-3 26-3 27 27 27 27 27 27 27 27 27 28-2 28-2 28-2 28-2 28-2 28-2 28-2 28-2 28-2 29 29 29 29 29 29 29 29 29 30 30 30 30 30 30 30 30 30 31 31 31 31 31 31 31 31 31 32 32 32 32 32 32 32 32 32 33 33 33 33 33 33 33 33 33 34 34 34 34 34 34 34 34 34 35-1 35-1 35-1 35-1 35-1 35-1 35-1 35-1 35-1 35-3 35-3 35-3 35-3 35-3 35-3 35-3 35-3 35-3 36 36 36 36 36 36 36 36 36 37 37 37 37 37 37 37 37 37 38 38 38 38 38 38 38 38 38 41-1 41-1 41-1 41-1 41-1 41-1 41-1 41-1 41-1 41-2 41-2 41-2 41-2 41-2 41-2 41-2 41-2 41-2 42 42 42 42 42 42 42 42 42 43 43 43 43 43 43 43 43 43 45 45 45 45 45 45 45 45 45 48 48 48 48 48 48 48 48 48 49-1 49-1 49-1 49-1 49-1 49-1 49-1 49-1 49-1 49-2 49-2 49-2 49-2 49-2 49-2 49-2 49-2 49-2 50-1 50-1 50-1 50-1 50-1 50-1 50-1 50-1 50-1 50-2 50-2 50-2 50-2 50-2 50-2 50-2 50-2 50-2 51 51 51 51 51 51 51 51 51 52 52 52 52 52 52 52 52 52 53 53 53 53 53 53 53 53 53 54-1 54-1 54-1 54-1 54-1 54-1 54-1 54-1 54-1 54-2 54-2 54-2 54-2 54-2 54-2 54-2 54-2 54-2 55 55 55 55 55 55 55 55 55 56 56 56 56 56 56 56 56 56 57 57 57 57 57 57 57 57 57 58 58 58 58 58 58 58 58 58 59 59 59 59 59 59 59 59 59 60 60 60 60 60 60 60 60 60 61 61 61 61 61 61 61 61 61 62 62 62 62 62 62 62 62 62 63 63 63 63 63 63 63 63 63 64 64 64 64 64 64 64 64 64 65 65 65 65 65 65 65 65 65 66 66 66 66 66 66 66 66 66 67 67 67 67 67 67 67 67 67 68 68 68 68 68 68 68 68 68 69 69 69 69 69 69 69 69 69 70 70 70 70 70 70 70 70 70 71 71 71 71 71 71 71 71 71 72-1 72-1 72-1 72-1 72-1 72-1 72-1 72-1 72-1 16б/з 16б/з 16б/з 16б/з 16б/з 16б/з 16б/з 16б/з 16б/з 47з 47з 47з 47з 47з 47з 47з 47з 47зAgricultural background, 30.04.06 RADARSAT-1, 24.10.2005, classification RADARSAT-1, 24.10.2005 Agricultural background, 24.10.2005 Agricultural background, 24.05.06 RADARSAT-1, 24.05.06, classification RADARSAT-1, 24.05.06, classification on combines
Now four stage were analyzed by method of synchronic field work and remote sensing survey:
Collection, qualitative testing and correction of meteo data Daily meteo data processing Data interpolation to grid cells Meteorological grid data
Level 1 –Meteo data generation Level 2 –Modeling of crops growth Level 3 –Estimation of crop-lands productivity
M s.A ST A NA Y ear: 19 90 MWOFOST
Akmola region The scheme of the testing area Soil map
о з. Т енги з Еси л ь К ор гал ж ын С те п но го рс к Е рме н тау Ас тана Леге нд а авт омор фные с олончак и каш танов ые каш танов ые с олонцеват ые каш танов ые с лаборазви тит ые тем но-к аштан овые к олк овые тем но-к аштан овые тем но-к аштан овые с олонцеват ые тем но-к аштан овые с лоборазв иты е гидром орфные солончак и свет ло-каш танов ые сол онцеваты е лесны е почв ы низ когорь я юж ны е черноз ем ы низ когорья обы кнове нные ч ернозем ы низк огорья луговы е луговы е почвы речны х долин луговы е каш танов ые полугидром орфны е соло нчаки черноз ем ы ю жны е к олковы е черноз ем ы ю жны е черноз ем ы ю жны е солон цеваты е черноз ем ы ю жны е слабо развит ые черноз ем ы обы кнов енны е колк овые черноз ем ы обы кнов енны е черноз ем ы обы кнов енны е солонцеват ые черноз ем ы обы кнов енны е слабораз виты е Карта почв Акмолинской областиThe agrotechnical backgrounds
Decades data simulation
Maps of §developmental stage §biomass §leaf area index §…
Historical statistic data of crop capacity Regression analysis
Estimation of crop-lands productivity
GIS-technology based on engineering model is illustrated by task of grain productivity estimation. For this task Crop Growth Monitoring System (CGMS) is used. This system fulfilled by Joint Research Centre (JRC, Ispra) have tree levels for calculation meteo data, crop growth and productivity.
UML Interaction Overview Diagram
UML Sequence Diagram for Calculation of meteomaps UML Sequence Diagram for Calculation of agromaps UML Sequence Diagram for Calculation of productivity
Interaction overview diagram refine the technology including interaction between executor and CGMS.
Timer Crop growth Weather Water balance WOFOST model is a mechanistic model that explains crop growth on the basis of the underlying processes, such as photosynthesis, respiration and how these processes are influenced by environmental conditions.
Variations in crop yield are mainly the result of variations in weather: Rainfall Wind speed Min and max temperature Tmax Tmin Global radiation Vapour pressure
Evapotranspiration: Incoming daily global solar radiation: Growth rate: Development rate at time step t: Total gross assimilation rate: Actual moisture content of the root zone at time step t:
CGMS based on WOFOST
typically engineering model with very simple mathematical formulas but with very large volume of input data.
80% 90% 100%
Percent of change
Field works results on “Storm” test site show that cause of dust storm is fire of 2005 year. As result the dust storm sources appeared
4500 sq.km area.
MODIS/Terra Space monitoring of dust storm is very important and interesting
there were about ten episodes of dust storm on test site located near Zhezkazgan city.
Meteorology and Cartography Dust storm sources parameters
Meteo- situation choice
Calculation
power
Calculation
transfer
0,01 0,02 0,03 0,04 0,05 0,06 0,07 0,08 5 8 10 15 20 25 30 м/с кг/кв.м*с Точка 1 Точка 2 Точка 3 Точка 4 Точка 5 Точка 6 Точка 7 Точка 8 Точка 9 Точка 10 Точка 115 м/с 10 м/с 15 м/с 25 м/с 30 м/с 20 м/с
а b
y = 0,7855x + 0,0999 R
2 = 0,7815
0,2 0,4 0,6 0,8 1 0,2 0,4 0,6 0,8 1
C-Cmin/Cmax-Cmin I-Im in/Im ax-Im in
y = 1,1156x - 0,0691 R
2 = 0,9248
0,2 0,4 0,6 0,8 1 0,2 0,4 0,6 0,8 1
C-Cmin/Cmax-Cmin I-Im in /Im ax-Im in
Very important stage is verification of the model. Model of dust storm
have been verified by compare with remote sensing data.
# # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # #
нефт. нефт. нефт. нефт. нефт. нефт. нефт. нефт. нефт. нефт. нефт. нефт. нефт.
у р . А т а н а к п е с к и с о
Сарыкамыс
г.-сол. Прорва Каратон Кенарал
Кайран Актоты
# # # # # # # # # # # # # # # # # ## # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # ## # # # # # ## ## # # # # # # # # # # # # # # # # # # # # # ## # # # # # ## # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # ## # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
К а с п и й с к о е м о р е
АСТРАХАНЬ Жанбай
АТЫРАУ
ДОССОР МАКАТ КУЛЬСАРЫ КОСЧАГЫЛ САРЫКАМЫС Таучик Сай-Утес з м е н н о с т ь и н я а к с й
П р и к а с п и
Аккыстау Шепте ЕСКЕНЕ ФОРТ-ШЕВЧЕНКО
Легенда
#
Затопленные и подтопляемые скважины Нефтяные месторождения
There are many oil-gas deposits on shore of Caspian Sea. During last 15 years the sea level risen on 1.2 m and many oil wells were flooded. Now it is transformed into ecological problem, as some times the wells pour out oil.
Hydrodynamics gird 10х10 km Source parameters Result of simulation, MIKE21 – HydroDynamics Meteorology Bathymetry Meteorology Bathymetry Space Image Quick Bird, 10.05.2002 Hydrodynamics gird 1х1 km Result of simulation, MIKE21 – Spill Analysis
The following equations, the conservation of mass and momentum integrated over the vertical, describe the flow and water level variations:
2 2 2 2 2 2 2 2 2 2
, 1 ( ) ( ) ( ) 0, 1 ( ) ( )
xx xy q w x a w yy xy w
u v w d x y z t gp p q p p pq gh h h t x h y h x C h x x h fVV p x gp p q q q pq gh h h t y h x h y C h y x ζ τ τ ρ ρ ζ τ τ ρ ∂ ∂ ∂ ∂ + + = ∂ ∂ ∂ ∂ + ∂ ∂ ∂ ∂ ∂ ∂ + + + + − + − Ω − ∂ ∂ ∂ ∂ ∂ ∂ ∂ − + = ∂ + ∂ ∂ ∂ ∂ ∂ ∂ + + + + − + + ∂ ∂ ∂ ∂ ∂ ∂ ( ) 0.
p y a w
h fVV p y ρ Ω − ∂ − + = ∂
( , , ) h x y t is water depth (
d ζ =
. ( , , )
d x y t is time varying water depth (m). ( , , ) x y t ζ
is surface elevation (m).
, ( , , ) p q x y t are flux densities in x- y-directions (m3/s/m)=(uh,vh). (u,v) = depth averaged velocities in x-
and y-directions. ( , )
C x y is Chezy resistance (m1/2/s). g is acceleration due to gravity (m/s2). f(V) is wind
friction factor.
, , ( , , )
x y
V V V x y t are wind speed and components in x- and y-directions (m/s). ( , ) x y Ω
is Coriolis parameter, latitude dependent (s-1).
( , , )
a
p x y t is atmospheric pressure (kg/m/s2). w ρ
is density of water (kg/m3). x,y are space coordinates (m). t is time (s).
, ,
xx xy yy
τ τ τ are components of effective shear
stress.
Transport Spreading Evaporation Emulsification Horizontal dispersion Vertical dispersion Hydrodynamics
3 4 3 1
= A V A K dt dA
A
Dissolution
A M Xmol C Ks dt dV
i i i sat i i dist
ρ = A M Xmol RT P Ke dt dVe
i i i
sat i i i
ρ =
s
Wax A y K y y U K dt dY ζ ζ
− + =
2 max 2 1
) ( ) 1 (
u D δγ µ 50 1 1 3600 ) 1 ( 11 .
2
+ ⋅ + =
[ ] [ ]
p T T p L L
t D R S t D R S ∆ ⋅ ⋅ = ∆ ⋅ ⋅ =
− −
6 6
1 1 1 1
Heat balance
vapor rad water
T air
T
H H t H H H + = + +
− −
) (
[ ]
) , , ( ), , , ( t y x v t y x u U =
Аспа Алга Гран Шалик Дамба Toман Аксай Акжар Манаш Пешной Ракуша Атырау Редуть Алмалы Жанбай Таскала Балыкшы Томарлы Бесикты Чкалово Есмахан Аккутур Есиркеп Кызылуй Шыныбек Кызылжар Жумыскер Аукайран Аккустау Жанаталап Еркинкала Сорочинка Карашыганак Новобогатинское
Caspian sea
Атырау
22.04.2005 23.05.2005
Date: 22.04.2005 Time: 01:00 Date: 22.04.2005 Time: 12:00 Date: 23.04.2005 Time: 00:00 Date: 26.04.2005 Time: 12:00
Актау
Курык Тенге Баянды Жетыбай Мунайшы Жанаозен Мангышлак
Каракиянский район территория г.Актау территория г. Узень Мангистауский район Тупкараганский район Тупкараганский район К а с п и й с к о е м о р е К а с п и й с к о е м о р е
СПН 112 ГНПС Узень ГНПС Актау НПС Жетыбай
Жетыбай Мунайшы
Каракиянский район Мангистауский район вдхр. вдхр. вдхр. вдхр.
84 83 82 81 80 79 78 77 76 75 74 73 72 71 70 69 68 67 66 65 64 63 62 61 60 59 58 57 56 55 54 53 52 51 50 75 74 73 72 71 70 69 68 67 66 65 64 63 62 61 60 59 58 57 56 55 54 53 52 51 50 49 48 47 46 45 44 43 42 41 9 8 7 6 5 4 3 2 1 15 14 13 12 11 10 1024 1023 1022 1021 1020 1019 1018 1017 1016 1015 1014 1013 1012 1011 1010 1009 1008 1007 1006 1005 НПС Жетыбай
Legend
Evaporation Ground burning Sea pollution GIS technology for atmosphere pollution when oil pipeline damage base on model produced specially for this task. At that different variant at damage are consider:
С – the mass concentration averaging over the vertical axis u – vector of wind velocity K – vector of coefficients of turbulent diffusion Q – intensity of volume sources σ – velocity of dry deposition α – intensity of surface source z0 – roughness height H – height of the bottom of the inversion layer μ(z) – vertical distribution of pollutant concentration
Smolarkevich’s numerical method was used as most effective method for quell numerical viscosity.
i i-1 i+1 j+1 j-1 j
k
i i-1 i+1 j+1 j-1 j
k+1 t
Pollutant SO2
Oil pipeline profile «Uzen-Atyrau-Samara» Results Date: 09.05.2005 Time: 06:00 Date: 09.05.2005 Time: 18:00 Date: 09.05.2005 Time: 00:00