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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.
Application 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 Engineering Graduate School of Bioresourse and Bioenvironment Sciences Kyushu University HOANG QUANG DUONG 2nd Master’s course BACKGROUND BACKGROUND Closed Water Body in an Organically Polluted Reservoir Hot Low Transparence Thermal Stratification Anoxic Condition Increase of Toxic Substance Sulfide Increase of PO4P and NH4-N due to Elution Cold Sediment N P BACKGROUND Closed Water Body in an Organically Polluted Reservoir Hot Eutrophication Low Transparence Thermal Stratification http://theartfulamoeba.com/ Anoxic Condition PO4-P and NH4-N: Reason PO4 Increase of Toxic Increase of PO4Substance andNH4NH4-N PP and of eutrophication Sulfide Toxic substance Ndue to Elution Sulfide: Cold Sediment N P Deterioration of Water Environment It is necessary to evaluate quantitatively PO4-P, NH4-N and sulfide under anaerobic state BACKGROUND Schematic Diagram of Ecosystem Model reaeration nitrification NH4-N NO2-N NO3-N DO DO It is necessary to settling mortality Phytoplankton defecation/natural death evaluate quantitatively respiration PO4-P, NH4-N and DO grazing sulfide underconsumption anaerobic Bottom Sedimentstate Zooplankton Elution excretion respiration mineralization decomposition DO POM settling PO4-P mineralization DOM It is important to predict and analyze PO4-P, NH4-N and sulfide by using ecosystem model denitrification Photosynthesis DO BACKGROUND of PO4-P and NH4-N ② No simulation of sulfide variation 0.3 PO4-P (mg/l) However … In current ecosystem model: ① There are large errors in simulation Large error 0.2 0.1 Month blem o r P Simulation of ecosystem model is not accurate due to internal load under anaerobic state It is impossible to evaluate and predict variations of water quality d Nee To reflect dynamic characteristic of water quality under anaerobic state 10 11 12 BACKGROUND My Study An one-dimensional vertical ecosystem model that could simulate correctly NO3-N, NH4-N, PO4-P and sulfide under anaerobic state To Implement To modify oneTo analyze biochemical dimensional vertical processes based on d To reflect dynamic characteristic waterby Nee ecosystemofmodel observed data quality under anaerobic Fortran state FIELD OBSERVATION & WATER DYNAMIC CHARACTERISTICS INTRODUCTION No.5 Reservoir RESEARCH AREA ch ar se y Re o r o at Bi or ri- ab Ag L No.5 Regulation Reservoir: • Location: Ito campus – Kyushu University • Purpose: supply water for cultivation activities at the downstream • Maximum depth: m • Catchment area: 31.3 • Surface area: 19,300 m2 • Total storage capacity: 63,000 m3 • In summer, anoxic condition occurs due to heavy organic pollution https://www.google.co.jp/maps/ FIELD OBSERVATION Location: Fix point at the center of the No.5 Reservoir Period: 2015/04/01 – 2015/12/09 Classification Outdoor analysis Indoor analysis Water quality items Notes Transparence Water temperature, DO, ORP, 0.5 m etc interval Chl.a, NO3-N, NH4-N, PO4- m P, Sulfide, SO42-, etc interval MODEL DEVELOPMENT • Meteorology data: Observation data (10 minutes) • Transparency: Observation data • Inflow data: Lack of inflow data • Calculation time: April to December DOC (mg/l) 200 4 Month 10 11 12 Fig DOC and rainfall in 2015 300 Rainfall (mm) It is necessary : Rainfall to divide into Fig Current situation including calculation periods of box culvert in 2015 spring-summer and summer100 winter based on heavy rainfall : DOC DOC varies much when heavy rainfall occurs SIMULATION RESULT : Simulation 40 20 NO3-N (mg/l) 0.2 0.02 Month 10 11 12 Fig Simulation of Chl.a and nutrient salts in the previous model at 0m 40 20 0.5 0.4 0.3 0.2 0.1 NH4-N (mg/l) 0.04 0.4 : Simulation 60 0.6 PO4-P (mg/l) NH4-N (mg/l) 0.5 0.4 0.3 0.2 0.1 0.6 : Observation Chl.a (µg/l) 60 PO4-P (mg/l) NO3-N (mg/l) Chl.a (µg/l) : Observation 0.04 0.4 0.2 0.02 Month 10 11 12 Fig Simulation of Chl.a and nutrient salts in the modified model at 0m SIMULATION RESULT : Simulation : Observation Chl.a (µg/l) 60 40 20 0.04 NO3-N (mg/l) 40 20 0.5 0.4 0.3 0.2 0.1 Better Simulation 0.4 0.2 0.02 Month 10 11 12 Fig Simulation of Chl.a and nutrient salts in the previous model at 0m NH4-N (mg/l) 0.6 : Simulation 60 0.6 PO4-P (mg/l) NH4-N (mg/l) 0.5 0.4 0.3 0.2 0.1 PO4-P (mg/l) NO3-N (mg/l) Chl.a (µg/l) : Observation 0.04 0.4 0.2 0.02 Month 10 11 12 Fig Simulation of Chl.a and nutrient salts in the modified model at 0m SIMULATION RESULT 7m 8m 10 11 12 Month Fig Simulation of DO in the previous model at 7m and 8m : Observation DO (mg/l) : Simulation DO (mg/l) DO (mg/l) DO (mg/l) : Observation : Simulation 7m 8m 10 11 12 Month Fig Simulation of DO in the modified model at 7m and 8m SIMULATION RESULT 7m 8m : Observation DO (mg/l) : Simulation 8 10 11 12 Month Fig Simulation of DO in the previous model at 7m and 8m : Simulation 7m Better Simulation8 DO (mg/l) DO (mg/l) DO (mg/l) : Observation 8m 4 10 11 12 Month Fig Simulation of DO in the modified model at 7m and 8m SIMULATION RESULT : Simulation NH4-N (mg/l) NO3-N (mg/l) 0.5 0.4 0.3 0.2 0.1 : Observation 0.3 PO4-P (mg/l) PO4-P (mg/l) NH4-N (mg/l) NO3-N (mg/l) : Observation 0.2 0.1 10 11 12 Month Fig Simulation of nutrients salts in the previous model at 7m : Simulation 0.5 0.4 0.3 0.2 0.1 0.3 0.2 0.1 10 11 12 Month Fig Simulation of nutrients salts in the previous model at 8m SIMULATION RESULT : Observation NO3-N (mg/l) 0.5 0.4 0.3 0.2 0.1 : Simulation : Simulation 0.5 0.4 0.3 0.2 0.1 NH4-N (mg/l) Simulation of nutrient salts in the previous model0 have large errors 0.3 0.3 PO4-P (mg/l) PO4-P (mg/l) NH4-N (mg/l) NO3-N (mg/l) : Observation 0.2 0.1 10 11 12 Month Fig Simulation of nutrients salts in the previous model at 7m 0.2 0.1 10 11 12 Month Fig Simulation of nutrients salts in the previous model at 8m SIMULATION RESULT NH4-N (mg/l) NS=0.93 NS=0.85 PO4-P (mg/l) 0.3 NS=0.73 0.2 0.1 800 600 400 200 NS=0.70 Month : Observation NO3-N (mg/l) 0.5 0.4 0.3 0.2 0.1 : Simulation Sulfide (µg/l) Sulfide (µg/l) PO4-P (mg/l) NH4-N (mg/l) NO3-N (mg/l) : Observation 10 11 12 Fig Simulation of nutrients salts and sulfide in the modified model at 7m 0.5 0.4 0.3 0.2 0.1 : Simulation NS=0.97 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 NS=0.86 0.3 NS=0.84 0.2 0.1 800 600 400 200 NS=0.86 Month 10 11 12 Fig Simulation of nutrients salts and sulfide in the modified model at 8m SIMULATION RESULT NH4-N (mg/l) NS=0.93 NS=0.85 : Observation NO3-N (mg/l) 0.5 0.4 0.3 0.2 0.1 : Simulation 0.5 0.4 0.3 0.2 0.1 : Simulation NS=0.97 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 NS=0.86 PO4-P (mg/l) Very Good Simulation0.3 0.3 NS=0.73 0.2 0.1 800 600 400 200 Sulfide (µg/l) Sulfide (µg/l) PO4-P (mg/l) NH4-N (mg/l) NO3-N (mg/l) : Observation NS=0.70 Month 10 11 12 Fig Simulation of nutrients salts and sulfide in the modified model at 7m NS=0.84 0.2 0.1 800 600 400 200 NS=0.86 Month 10 11 12 Fig Simulation of nutrients salts and sulfide in the modified model at 8m SCENARIO ANALYSIS Underwater light environment impacts on the anaerobic condition through influences of water temperature and photosynthesis Denitrification impacts on the reduction reaction Impacts of Transparency Scenario 1: Low Transparency (0.5 m) Scenario 2: High Transparency (4.5 m) Impacts of NO3-N Scenario 3: Low NO3-N (0.1 mg/l) Scenario 4: High NO3-N (1.0 mg/l) Scenario1 Scenario2 NH4-N (mg/l) Scenario1 Scenario2 PO4-P (mg/l) Scenario1 Scenario2 0.2 0.1 800 600 400 200 Scenario1 Scenario2 DO (mg/l) 10 2 Sulfide (µg/l) Sulfide (µg/l) PO4-P (mg/l) NH4-N (mg/l) DO (mg/l) SCENARIO ANALYSIS: Transparency 10 11 12 Month Fig Results of Scenario and Scenario at 7m 10 2 Scenario1 Scenario2 Scenario1 Scenario2 Anoxic state is much longer Elution of nutrient salts are much stronger Scenario1 Scenario2 0.2 0.1 800 600 400 200 Generation of sulfide is much higher Scenario1 Scenario2 Impact of transparency Scenario 1: 0.5 m Scenario 2: 4.5 m 10 11 12 Month Fig Results of Scenario and Scenario at 8m Transparency has strong impact on water quality under anaerobic state Scenario3 Scenario4 NH4-N (mg/l) Scenario3 Scenario4 PO4-P (mg/l) Scenario3 Scenario4 0.2 0.1 800 600 400 200 Scenario3 Scenario4 DO (mg/l) 10 2 Sulfide (µg/l) Sulfide (µg/l) PO4-P (mg/l) NH4-N (mg/l) DO (mg/l) SCENARIO ANALYSIS: NO3-N Month 10 11 12 Fig Results of Scenario and Scenario at 7m 10 2 Scenario3 Scenario4 Scenario3 Scenario4 Anoxic state is the same Elution of nutrient salts are stronger Scenario3 Scenario4 0.2 Impact of NO3-N Scenario 3: 0.1 mg/l Scenario 4: 1.0 mg/l 0.1 800 600 400 200 Generation of sulfide is higher Scenario3 Scenario4 10 11 12 Month Fig Results of Scenario and Scenario at 8m Nitrate has impact on water quality under anaerobic state but is not as strong as transparency CONCLUSION CONCLUSION Objective An one-dimensional vertical ecosystem model that could simulate correctly NO3-N, NH4-N, PO4-P and sulfide under anaerobic state Objective is achieved Result The one-dimensional ecosystem model apply for organically polluted reservoir under anaerobic state To understand water quality dynamic in the closed water body under anaerobic state Good calculation of NO3-N, NH4-N, PO4-P and sulfide under anaerobic state in an organically polluted reservoir To analyze impacts of transparency and NO3-N on water environment dynamic under anaerobic state THANK YOU FOR YOUR ATTENTION ! Welcome your questions, suggestion, and comments ! ... polluted reservoir under anaerobic state To understand water quality dynamic in the closed water body under anaerobic state Good calculation of NO3-N, NH4-N, PO4-P and sulfide under anaerobic state. .. Density of the water (kg/m3) : Water temperature (oC) : Specific heat of the water (J/kg/K) : Heat flux of incident light (J/m2) : Water quality item (mg/l) MODEL DEVELOPMENT Process Phytoplankton ingestion... are large errors in simulation Large error 0.2 0.1 Month blem o r P Simulation of ecosystem model is not accurate due to internal load under anaerobic state It is impossible to evaluate and predict