Trong hồ chứa bị ô nhiễm hữu cơ, tình trạng phân tầng do nhiệt diễn ra mạnh mẽ hơn dẫn tới sự gia tăng của quá trình yếm khí trong hồ chứa. Quá trình này kết hợp với ô nhiễm hữu cơ trong hồ làm gia tăng quá trình phát thải các chất gây hại từ lớp bùn sình dưới đáy hồ trong thời gian bị yếm khí. Trong nghiên cứu này, chúng tôi tiến hành ứng dụng mô hình toán nhằm đánh giá môi trường nước dưới tác động của tình trạng yếm khí trong hồ bị ô nhiễm hữu cơ.
Trang 1Application of the Ecosystem Model to the Mathematical Simulation of Water Environment Dynamic under Anaerobic
State in the Organically Polluted Agricultural Reservoir
Laboratory of Water Environment EngineeringGraduate School of Bioresourse and Bioenvironment SciencesKyushu University
HOANG QUANG DUONG
2nd Master’s course
Trang 2BACKGROUND
Trang 3Thermal Stratification
Anoxic Condition
Sediment
Increase of PO4
-P and NH4-N due to Elution
P N
Increase of Toxic Substance - Sulfide
Trang 4Thermal Stratification
Anoxic Condition
Sediment
Increase of PO4
-P and NH4-N due to Elution
P N
Increase of Toxic Substance - Sulfide
Deterioration
of Water Environment
It is necessary to evaluate quantitatively
PO4-P, NH4-N and sulfide under anaerobic
state
PO4 Sulfide
Trang 5POM DOM
DO
DO DO
consumption
reaeration
Schematic Diagram of Ecosystem Model
It is necessary to evaluate quantitatively
PO4-P, NH4-N and sulfide under anaerobic
Trang 6However …
In current ecosystem model:
① There are large errors in simulation
of PO4-P and NH4-N
Simulation of ecosystem model is not accurate due to
internal load under anaerobic state
Prob lem
To reflect dynamic characteristic of water
quality under anaerobic state
Trang 7To reflect dynamic characteristic of water
quality under anaerobic state
To modify dimensional vertical ecosystem model by
one-Fortran
Trang 8FIELD OBSERVATION & WATER DYNAMIC
CHARACTERISTICS
Trang 9RESEARCH AREA
No.5 Regulation Reservoir:
• Location: Ito campus – Kyushu University
• Purpose: supply water for cultivation
activities at the downstream
• Maximum depth: 8 m
• Catchment area: 31.3 ha
• Surface area: 19,300 m2
• Total storage capacity: 63,000 m3
• In summer, anoxic condition occurs due to
heavy organic pollution
No.5 Reservoir
Ag ri-B
io R es ea rch
La bo rato ry
https://www.google.co.jp/maps/
Trang 10Water temperature, DO, ORP,
etc
0.5 m interval
Indoor analysis
1 m interval
Trang 11WATER QUALITY CHARACTERISTIC
DO was exhausted
Trang 12WATER QUALITY CHARACTERISTIC
DO was exhausted
0 0.5 1 1.5 2
8 7 6 5 4 3 2 1 0
0 0.1 0.2
8 7 6 5 4 3 2 1 0
Trang 13WATER QUALITY CHARACTERISTIC
DO increases when thermal stratification
Trang 14WATER QUALITY CHARACTERISTIC
0
0.5
1
4 5 6 7 8 9 10 11 12 0
Trang 15WATER QUALITY CHARACTERISTIC
Fig DO and NO3-N at 7m Fig DO and NO3-N at 8m
Denitrification starts when DO ≈ 0.5 mg/l
4 5 6 7 8 9 10 11 12 0
0.1 0.2 0.3 0.4
Trang 16WATER QUALITY CHARACTERISTIC
Fig DO, NO3-N and NH4-N at 7m Fig DO, NO3-N and NH4-N at 8m
0 0.1 0.2 0.3 0.4
4 5 6 7 8 9 10 11 12 0
1 2 3
NO3-N=0.1
Trang 17WATER QUALITY CHARACTERISTIC
Fig DO, NO3-N and Sulfide at 7m Fig DO, NO3-N and Sulfide at 8m
0 0.1 0.2 0.3 0.4
4 5 6 7 8 9 10 11 12 0
0.1 0.2 0.3
0 200 400 600 800
Trang 18ONE-DIMENSIONAL VERTICAL
ECOSYSTEM MODEL
Trang 19Input by diffusion flux
Input by incident light flux
Output by
diffusion flux
Output by incident light flux
Internal production or consumption
Trang 20Preferential ingestion of NO3-N
Denitrification x was determined by DO ≤ x
trial and error Denitrification under DO ≤ 0.5 mg/l
variation of
sulfide due to
sulfate reduction
There is no simulation of sulfide
Zero-order reaction Limiting condition: DO = 0 and
NO3-N = 0
Trang 21MODEL DEVELOPMENT
• Meteorology data: Observation data
(10 minutes)
• Transparency: Observation data
• Inflow data: Lack of inflow data
• Calculation time: April to December
Fig Current situation
of box culvert in 2015 Inflow data from box culvert cannot
measure due to deposition of sediment
Trang 22MODEL DEVELOPMENT
• Meteorology data: Observation data
(10 minutes)
• Transparency: Observation data
• Inflow data: Lack of inflow data
• Calculation time: April to December
Fig Current situation
of box culvert in 2015
4 5 6 7 8 9 10 11 12 4
5
6
7
300 200 100 0
Fig DOC and rainfall in 2015
DOC varies much when heavy rainfall occurs
Trang 23MODEL DEVELOPMENT
• Meteorology data: Observation data
(10 minutes)
• Transparency: Observation data
• Inflow data: Lack of inflow data
• Calculation time: April to December
Fig Current situation
of box culvert in 2015
4 5 6 7 8 9 10 11 12 4
5
6
7
300 200 100 0
Fig DOC and rainfall in 2015
DOC varies much when heavy rainfall occurs
It is necessary to divide into 2 calculation periods including spring-summer and summer- winter based on heavy rainfall
Trang 24SIMULATION RESULT
Fig Simulation of Chl.a and nutrient
salts in the previous model at 0m
0 0.2
0.4
0.6
4 5 6 7 8 9 10 11 12 0
0.02
0.04
0 0.1
4 5 6 7 8 9 10 11 12 0
0.02 0.04
0 0.1 0.2 0.3 0.4 0.5 0 20 40 60
Fig Simulation of Chl.a and nutrient
salts in the modified model at 0m
Trang 25SIMULATION RESULT
0 0.2
0.4
0.6
4 5 6 7 8 9 10 11 12 0
0.02
0.04
0 0.1
4 5 6 7 8 9 10 11 12 0
0.02 0.04
0 0.1 0.2 0.3 0.4 0.5 0 20 40 60
Fig Simulation of Chl.a and nutrient
salts in the previous model at 0m
Fig Simulation of Chl.a and nutrient
salts in the modified model at 0m
Trang 26SIMULATION RESULT
Fig Simulation of DO in the
previous model at 7m and 8m
Fig Simulation of DO in the
modified model at 7m and 8m
0 2 4 6 8
4 5 6 7 8 9 10 11 12 0
2 4 6 8
4 5 6 7 8 9 10 11 12 0
2 4 6 8
Trang 27SIMULATION RESULT
Fig Simulation of DO in the
previous model at 7m and 8m
Fig Simulation of DO in the
modified model at 7m and 8m
0 2 4 6 8
4 5 6 7 8 9 10 11 12 0
2 4 6 8
4 5 6 7 8 9 10 11 12 0
2 4 6 8
Trang 28SIMULATION RESULT
Fig Simulation of nutrients salts
in the previous model at 7m
Fig Simulation of nutrients salts
in the previous model at 8m
0 1 2 3
4 5 6 7 8 9 10 11 12 0
0.1 0.2 0.3
0 0.1 0.2 0.3 0.4 0.5
4 5 6 7 8 9 10 11 12 0
0.1
0.2
0.3
0 0.1
Trang 29SIMULATION RESULT
Fig Simulation of nutrients salts
in the previous model at 7m
Fig Simulation of nutrients salts
in the previous model at 8m
0 1 2 3
4 5 6 7 8 9 10 11 12 0
0.1 0.2 0.3
0 0.1 0.2 0.3 0.4 0.5
4 5 6 7 8 9 10 11 12 0
0.1
0.2
0.3
0 0.1
Trang 30SIMULATION RESULT
Fig Simulation of nutrients salts and
sulfide in the modified model at 7m
Fig Simulation of nutrients salts and
sulfide in the modified model at 8m
0 0.1 0.2 0.3
4 5 6 7 8 9 10 11 12 0
200 400 600 800
0 0.1 0.2 0.3 0.4 0.5
Nash-Sutcliffe coefficient is a normalized statistic that determines the relative magnitude of the residual variance compared to the measured data variance
Trang 310 0.1 0.2 0.3
4 5 6 7 8 9 10 11 12 0
200 400 600 800
0 0.1 0.2 0.3 0.4 0.5
Fig Simulation of nutrients salts and
sulfide in the modified model at 7m
Fig Simulation of nutrients salts and
sulfide in the modified model at 8m
Nash-Sutcliffe coefficient (NS)
Nash-Sutcliffe coefficient is a normalized statistic that determines the relative magnitude of the residual variance compared to the measured data variance
Trang 32Scenario 1: Low Transparency (0.5 m)
Scenario 2: High Transparency (4.5 m)
Impacts of NO3-N
Trang 33SCENARIO ANALYSIS: Transparency
Fig Results of Scenario 1 and
Scenario1 Scenario2
Scenario1 Scenario2
0 0.1 0.2
4 5 6 7 8 9 10 11 12 0
200 400 600 800
0 2 4 6 8 10
Scenario1 Scenario2
Scenario1 Scenario2
Elution of nutrient salts are much strongerGeneration of sulfide is much higher
Transparency has strong impact on water quality under anaerobic
state
Trang 34Scenario3 Scenario4
Scenario3 Scenario4
0 0.1 0.2
4 5 6 7 8 9 10 11 12 0
200 400 600 800
0 2 4 6 8 10
Scenario3 Scenario4
Scenario3 Scenario4
Generation of sulfide is higher
Nitrate has impact
on water quality under anaerobic state but is not as strong as transparency
Trang 35CONCLUSION
Trang 37THANK YOU FOR YOUR
ATTENTION !
Welcome your questions, suggestion, and comments !
THANK YOU FOR YOUR
ATTENTION !
Welcome your questions, suggestion, and comments !