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Manila Bay - Pasig River - Laguna De Bay Watershed Introduction to Decision Support System & Model Community Initiative

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Manila Bay - Pasig River - Laguna De Bay Watershed Introduction to Decision Support System & Model Community Initiative Manila Bay - Pasig River - Laguna de Bay watershed Introduction to Decision Support System & Model Community Initiative Arno Nolte November 1, 2019 To be told ▪ Timeline for the Decision Support System (DSS) ▪ Introduction to the (available) modeling framework of Manila Bay and Laguna de Bay ▪ Introduction to the Model Community of Practice (CoP) initiative November 1, 2019 Timeline for the Decision Support System Period Project/Program 2000-2003 LLDA Sustainable Development of the Laguna de Bay Environment (SDLBE) 2003-2005 LLDA Follow-up of the SDLBE … … … 2013 PEMSEA Total Pollutant Loading Study in the Laguna de Bay-Pasig River-Manila Bay Watershed (link) 2016-2018 MBCO/LLDA Updating and Application of the Nutrient Reduction Modeling in the Laguna de Bay-Pasig River-Manila Bay Watershed 2017 Manila Water Laguna East Bay water intake 2018-2020 NEDA Manila Bay Sustainable Development Master Plan November 1, 2019 Sustainable Development of the Laguna de Bay Environment (SDLBE) 2000-2003 Decision Support System Manila Bay Area Rainfall- Hydrodynamic Runoff model model (WFLOW) (Delft3D-FLOW) Ecology model (ArcGIS Habitat) Waste Load Water Quality model model (WLM) (Delft3D-WAQ) Currently consisting of six Spatial model interconnected components (MBSM) November 1, 2019 Modeling framework → Spatial Model (MBSM) MODEL INPUT Population growth scenarios MODEL OUTPUT Rainfall- 200 Hydrodynamic 180 Population growth Runoff model 160 model Population and 140 land use on (WFLOW) 120 (Delft3D-FLOW) 100 barangay level 80 60 Ecology model 1. Rich together (SSP1) 2. Middle ground (SSP2) 3. Stagnation (SSP3) Philippinespopulation(million) 40 20 (ArcGIS 0 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 Habitat) 3 scenarios for national GDP in million US$ (constant 2010 US$) $2,500,000 Rich TogetherWaste (SSP1) Middle Load ground (SSP2) Water Quality $2,000,000 Stagnation (SSP3) model model $1,500,000 Economic growth(WLM) (Delft3D-WAQ) $1,000,000 $500,000 $- Time horizons: 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 2055 2015 2022 Spatial model Spatial plans, 2030 (MBSM) road network 2040 2055 Land use July 4, 2018 Modeling framework → Waste Load Model (WLM) MODEL INPUT MODEL OUTPUT Rainfall- Hydrodynamic Runoff model model (WFLOW) (Delft3D-FLOW) River flows (red line) Ecology model (ArcGIS Habitat) Waste Load Water Quality model model (WLM) (Delft3D-WAQ) Silt & Clay Bacteria Land use 6 main catchments Spatial model Bataan, (MBSM) Pampanga, Bulacan, Manila Laguna, Cavite BOD pollution load – Reference Scenario Sewerage Sewerage Sewerage Septic Septic primary secondary tertiary tank tank non- No treatment treatment treatment desludged desludged treatment 2015 Manila Water 14% 0 0% 41% 40% 5% Maynilad 16% 0 0% 40% 39% 5% Other 0% 0 0 15% 65% 20% Reclamation 0% 0 100% 0% 0% 0% 2022 Preliminary result. Manila Water 32% 0 0% 31% 32% 5% Not for distribution. Maynilad 47% 0 0% 24% 24% 5% Other 0% 0 0 15% 65% 20% Reclamation 0% 0 100% 0% 0% 0% 2030 Manila Water 0% 0 95% 5% 0% 0% Maynilad 0% 0 100% 0% 0% 0% Other 0% 0 0 15% 65% 20% Reclamation 0% 0 100% 0% 0% 0% 2040 Manila Water 0% 0 99% 1% 0% 0% Maynilad 0% 0 100% 0% 0% 0% Other 0% 0 0 15% 65% 20% Reclamation 0% 0 100% 0% 0% 0% Percentage of population covered by treatment type per time horizon and per treatment area (data derived from Manila Water and Maynilad development plans) November 1, 2019 BOD pollution load – Reference Scenario Sewerage Sewerage Sewerage Septic Septic primary secondary tertiary tank tank non- No treatment treatment treatment desludged desludged treatment 2015 Manila Water 14% 0 0% 41% 40% 5% Maynilad 16% 0 0% 40% 39% 5% Other 0%Reference 0 cases: Pollution0 load15% of BOD65% entering 20% Manila Bay in million Reclamation 0% 0 100% 0% tons 0% 0% 2022 Preliminary result. 0.40 Manila Water 32% 0 0% 31% 32% 5% Not for distribution. Maynilad 47% 0 0% 24% 24% 5% 0.35 Other 0% 0 0 15% 65% 20% Reclamation0.30 0% 0 100% 0% 0% 0% 2030 Manila Water0.25 0% 0 95% 5% 0% 0% Maynilad 0% 0 100% 0% 0% 0% Other 0.20 0% 0 0 15% 65% 20% Reclamation 0% 0 100% 0% 0% 0% 0.15 2040 Manila Water 0% 0 99% 1% 0% 0% Maynilad 0.10 0% 0 100% 0% 0% 0% Other 0% 0 0 15% 65% 20% Reclamation0.05 0% 0 100% 0% 0% 0% Percentage0.00 of population covered by treatment type per time horizon and2015 per treatment 2020area (data derived2025 from Manila 2030Water and 2035 2040 Maynilad development plans)Rich together Middle ground Stagnation Target November 1, 2019 Model grid → 3D Hydrodynamic & 3D Water Quality models ▪ Laguna de Bay and Manila Bay connected September 16, 2019 Model grid – Pasig connection April 19, 2017 Modeling framework → 3D Water Quality model (Delft3D) MODEL INPUT MODEL OUTPUT Rainfall- Hydrodynamic Runoff model model (WFLOW) (Delft3D-FLOW) 1. Nutrient concentration (N, P, Si) 2. DissolvedEcology model Oxygen (ArcGIS 3. SuspendedHabitat) sediment (turbidity) Waste Load Water Quality model model 4. Chlorophyll-a (WLM) (Delft3D-WAQ) 5. BOD (Biological Oxygen Demand) Dissolved oxygen 6. Pollutants (not included yet) Spatial model (MBSM) NB: And many derived variables and statistics. Water Quality Model Results: Effect of Pollution load reduction on Dissolved Oxygen Preliminary result. Not for distribution. 100% Waste Load (2015) Dissolved oxygen concentration near the seabed Water Quality Model Results: Effect of Pollution load reduction on Dissolved Oxygen Preliminary result. Not for distribution. 100% Waste Load (2015) 50% Waste Load Dissolved oxygen concentration near the seabed Water Quality Model Results: Effect of Pollution load reduction on Dissolved Oxygen Preliminary result. Not for distribution. 100% Waste Load (2015) 50% Waste Load Dissolved oxygen concentration near the seabed 25% Waste Load MODEL COMMUNITY OF PRACTICE November 1, 2019 Model Community of Practice Why a Model Community of Practice? 1. Wide range of topics for which expertise is usually not available in one organization 2. Wide range of topics requires a lot of input data from monitoring which is usually not available in one organization 3. Turnover of trained staff results in drain of expertise 4. Multiple models for the same topic may result in confusion and discussion if model results are not the same. 5. In general, investments are (too) large to be sustainably born by one organization. A Model Community of Practice is a way to share expertise, pool knowledge transfer, combine investments, share maintenance, and optimize developments and monitoring efforts. November 1, 2019 Model CoP covers more than Modeling Policy or Management QUESTIONS SYSTEM UNDERSTANDING Socio-Economy Ecology / Water Qual. Institutional DATA MODEL ▪ Model application must be tailored to the Question(s) at hand. ▪ Model must be based on Understanding how the System works and reacts to measures and/or changes. (Also, model verifies system understanding.) ▪ System understanding must be based (primarily) on data analysis. ▪ Model must be fed by and calibrated/validated against suitable Data. November 1, 2019 Organizations expressing interest The modeling teams of the following organizations expressed interest in a Model CoP initiative: ▪ MBCO ▪ LLDA ▪ PRRC ▪ UP Marine Science Institute ▪ UP Los Banos ▪ UP National Engineering Center ▪ Manila Water ▪ Deltares ▪ … November 1, 2019 Next steps? ▪ Get interested organizations together to explore possibilities ▪ Get institutional support from management ▪ Draft CoP cooperation agreement ▪ Identify and agree on common goal(s) ▪ Find balance between commitment and flexibility ▪ Voluntarily but not without obligation ▪ Set-up supporting structure ▪ People, Cooperation protocols, Computer infrastructure ▪ Define activities and actions for the next year(s) ▪ Arrange continuity November 1, 2019 Thank you! Salamat! November 1, 2019.
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