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Bridging Policy Gaps through Software
and Modelling
Dr. Sutat Weesakul
Director of Hydro – Informatics Institute (Public Organization)
Ministry of Higher Education, Science, Research and Innovation
Deltares Software Days South-East Asia 2019, 27th November 2019, Bangkok
2 | Bridging Policy Gaps through Software and Modelling
Contents
1
2
3
Principles on Water Governance
Examples of Modelling for Bridging the Gaps
• Supporting decision making under uncertainty
• Improving communication among stakeholders
• Warning and preparation for crisis readiness
• Reaching information in real-time
Conclusions
Principles on Water Governance
4 | Bridging Policy Gaps through Software and Modelling
Water governance cycle
Actions
Water
governance
Policies and
strategies
formulation
Implementation
Monitoring
Evaluation
Principles
Indicators
Bridging gap
New instruments
or improvements
Assessing gaps
Source: OECD (2015), OECD Principles on Water Governance
5 | Bridging Policy Gaps through Software and Modelling
Multi-level governance gaps in water policy
Policy
gap
Accountability
gap
Funding
gap
Capacity
gap
Information
gap
Administrative
gap
Objective
gap
Governance
gaps
• Policy gap - Sectoral fragmentation of water-related tasks across
ministries and agencies.
• Accountability gap - Insufficient users commitment and lack of
concern, awareness, participation.
• Funding gap - Unstable or insufficient funding is undermining the
water policy implementation.
• Capacity gap - Insufficient scientific, technical, infrastructural
capacity of actors.
• Information gap - Asymmetries of information between
different stakeholders involved in water policy.
• Administrative gap - Geographical mismatch between
hydrological and administrative boundaries.
• Objective gap - Different rationales creating obstacles for
adopting convergent targets.
Source: OECD (2011), Water Governance in OECD: A Multi-Level Approach
Modelling for Policy Gaps Bridging
7 | Bridging Policy Gaps through Software and Modelling
Adaptive flood risk
management plan for
Sukhothai Province
Supporting decision making under uncertainty
8 | Bridging Policy Gaps through Software and Modelling
Causes of the flood in Sukhothai
▪ Topography and land use changes.
▪ High intensity of rainfall.
▪ Quick runoff and high peak
discharge from upstream.
▪ River capacity reduction.
Sukhothai
Phrae
Phitsanulok
Phichit
Capacity of Yom River Average annual rainfall of Yom River
Yom River Basin
Avg. Annual Rainfall 1,204 mm.
Avg. Annual Discharge 4,143 MCM.
Sukhothai Province
Avg. Annual Rainfall 1,196 mm.
Avg. Annual Discharge 2,946 MCM.
Kaeng Sua Ten Dam
Storage: 1,175 MCM.
Annual inflow: 978 MCM.
Storage : Inflow = 1 : 0.8
Upper Yom Dam
Storage: 166 MCM.
Annual inflow: 911 MCM.
Storage : Inflow = 1 : 5.5
Yom Dam
Storage: 588 MCM.
Annual inflow: 1,382 MCM.
Storage : Inflow = 1 : 2.4
Sukhothai
Phrae
9 | Bridging Policy Gaps through Software and Modelling
Adaptation pathway for flood risk management
Example of planed decision
Local and regional actions
▪ Reduction of flood vulnerability of
land use.
▪ Raising embankments Sukhothai.
Upstream actions
▪ Large upstream reservoir.
▪ Optimized operation.
Stepwise development of strategies
▪ Early implementation measures (e.g.
bypass around Sukhothai, flood
retardation)
▪ No regret measures (e.g. reduction of
flood vulnerability of land use)
▪ Easily adaptable measures (e.g. diversion
of peak flows, increase discharge capacity
through dredging)
▪ Reservoir measures (e.g. build medium or
large reservoir, optimized operation)
▪ Regional measures (e.g. raising
embankments)
(%)
10 | Bridging Policy Gaps through Software and Modelling
Development of Delft3D FM
flood model for Ayutthaya
City
Improving communication between stakeholders
11 | Bridging Policy Gaps through Software and Modelling
The great flood in 2011
▪ The widespread flooding in the Chao
Phraya River Basin.
▪ Ayutthaya City suffered from serious
damages with almost all area were
under water for months.
Ayutthaya City Ayutthaya City
12 | Bridging Policy Gaps through Software and Modelling
Delft3D FM model outcome
❑ Provide understanding of the event
and verify the effectiveness of
possible measures in an easy way.
❑ Improve communication among
professionals, decision makers and
various stakeholders.
13 | Bridging Policy Gaps through Software and Modelling
Operational forecasting
and early warning system
for the Gulf of Thailand
Warning and preparation for crisis readiness
14 | Bridging Policy Gaps through Software and Modelling
Ocean forecasting system
▪ Hydrodynamic Model (Delft3D FM)
▪ Wave Model (SWAN)
▪ Weather Prediction Model (WRF-ROMS)
▪ Early Warning System (Delft-FEWS)
Early Warning System based on Delft-FEWS
15 | Bridging Policy Gaps through Software and Modelling
▪ 31 Dec 2018 - A disturbance in the southern of the South
China Sea was upgraded to a tropical depression.
▪ 1 Jan 2019 - It was upgraded to the first tropical storm of
the 2019 and was named Pabuk.
▪ 2-3 Jan 2019 - Pabuk accelerated west-northwestward
and entered the Gulf of Thailand.
▪ 4 Jan 2019 - Pabuk had made landfall over Pak Phanang,
Nakhon Si Thammarat.
▪ 5 Jan 2019 - Pabuk had weaken and moved westward to
Andaman Sea.
Tropical Storm Pabuk
31/12/18
1/1/192/1/193/1/19
4/1/19
5/1/19
Legends
TD
TS
16 | Bridging Policy Gaps through Software and Modelling
Water level forecast in the Gulf of Thailand
Pak Phanang,
Nakhon Si Thammarat
03/Jan/19
Pak Phanang,
Nakhon Si
Thammarat
Forecast date: 4 Jan 2019
Reanalysis date: 30 Jan 2019
17 | Bridging Policy Gaps through Software and Modelling
Water level forecast in the Gulf of Thailand
KoLak station
Pak Phanang station
Rayong station
Ko Samui Station
Forecast 3 days ahead, Computation time: 2.5 hrs.
Forecast 7 days ahead, Computation time: 6 hrs.
18 | Bridging Policy Gaps through Software and Modelling
Comparison of observed and forecasted water level on 5th Jan 2019
Highest observed water level
Highest forecasted water level
Ko Lak station
Actual water level
Pak Phanang station
Rayong station
Ko Samui station
Actual water level
Actual water level
Actual water level
19 | Bridging Policy Gaps through Software and Modelling
4 Jan 2019 - Pak Phanang, Nakhon Si Thammarat 5 Jan 2019 - The Upper Gulf of Thailand
Effects of Tropical Storm Pabuk
20 | Bridging Policy Gaps through Software and Modelling
HARRIET (1962) PABUK (2019)
Landfall at Pakpanang, Nakhon Si Thammarat
with wind speed 95 km/hr
Evacuation: None
Losses: 911 casualties
22,296 households destroyed
50,775 households damage
Landfall at Pakpanang, Nakhon Si Thammarat
with wind speed 85 km/hr
Evacuation: 31,665 people were evacuated
Losses: 5 casualties
405 households destroyed
53,008 households damage
HARRIET (1962) vs PABUK (2019)
21 | Bridging Policy Gaps through Software and Modelling
Reaching information in real-time
Rainfall estimation and
nowcasting system using
composite weather radar
data and its application
22 | Bridging Policy Gaps through Software and Modelling
POD FAR CSI
7-Jul-19
F1 0.525 0.456 0.
F2 0.433 0.619 0.
F3 0.400 0.684 0.
URBAN RAINFALL (BANGKOK)
7 June 2019
Rainfall estimation and nowcasting system using composite weather radar data
BKK
23 | Bridging Policy Gaps through Software and Modelling
23rd July 2019 Heavy rainfall event in Bangkok
**BMA reported
highest rainfall
observed in Nongjok
and Klong Samwa
Rainfall estimation and nowcasting system using composite weather radar data
24 | Bridging Policy Gaps through Software and Modelling
COMPOSITE RADAR ON LINE APPLICATION
Rainfall estimation and nowcasting system using composite weather radar data
Composite Radar
Features:
- Push rainfall warnings
- User’s request interaction
25 |
Effectiveness
Clear water policy goals and targets at
different level.
Efficiency
Maximize the benefits of sustainable water
management.
Trust and Engagement
Building public confidence and inclusiveness
of stakeholders.
Adaption pathway
Delft3D FM model
Ocean forecasting
Composite weather radar
Source: OECD (2015), OECD Principles on Water Governance
Conclusions
26 |
Policy
gap
Accountability
gap
Funding
gap
Capacity
gap
Information
gap
Administrative
gap
Objective
gap
Governance
gaps
Adaption pathway
Delft3D FM model
Ocean forecasting
Composite weather radar
Conclusions
27 |
Hydro – Informatics Institute (Public Organization)
Ministry of Higher Education, Science, Research and Innovation, THAILAND
tel +66 2 5180901 fax +66 2 5180910
www.hii.or.th www.thaiwater.net

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DSD-SEA 2019 Bridging Policy Gaps through Software and Modelling - Weesakul

  • 1. Bridging Policy Gaps through Software and Modelling Dr. Sutat Weesakul Director of Hydro – Informatics Institute (Public Organization) Ministry of Higher Education, Science, Research and Innovation Deltares Software Days South-East Asia 2019, 27th November 2019, Bangkok
  • 2. 2 | Bridging Policy Gaps through Software and Modelling Contents 1 2 3 Principles on Water Governance Examples of Modelling for Bridging the Gaps • Supporting decision making under uncertainty • Improving communication among stakeholders • Warning and preparation for crisis readiness • Reaching information in real-time Conclusions
  • 3. Principles on Water Governance
  • 4. 4 | Bridging Policy Gaps through Software and Modelling Water governance cycle Actions Water governance Policies and strategies formulation Implementation Monitoring Evaluation Principles Indicators Bridging gap New instruments or improvements Assessing gaps Source: OECD (2015), OECD Principles on Water Governance
  • 5. 5 | Bridging Policy Gaps through Software and Modelling Multi-level governance gaps in water policy Policy gap Accountability gap Funding gap Capacity gap Information gap Administrative gap Objective gap Governance gaps • Policy gap - Sectoral fragmentation of water-related tasks across ministries and agencies. • Accountability gap - Insufficient users commitment and lack of concern, awareness, participation. • Funding gap - Unstable or insufficient funding is undermining the water policy implementation. • Capacity gap - Insufficient scientific, technical, infrastructural capacity of actors. • Information gap - Asymmetries of information between different stakeholders involved in water policy. • Administrative gap - Geographical mismatch between hydrological and administrative boundaries. • Objective gap - Different rationales creating obstacles for adopting convergent targets. Source: OECD (2011), Water Governance in OECD: A Multi-Level Approach
  • 6. Modelling for Policy Gaps Bridging
  • 7. 7 | Bridging Policy Gaps through Software and Modelling Adaptive flood risk management plan for Sukhothai Province Supporting decision making under uncertainty
  • 8. 8 | Bridging Policy Gaps through Software and Modelling Causes of the flood in Sukhothai ▪ Topography and land use changes. ▪ High intensity of rainfall. ▪ Quick runoff and high peak discharge from upstream. ▪ River capacity reduction. Sukhothai Phrae Phitsanulok Phichit Capacity of Yom River Average annual rainfall of Yom River Yom River Basin Avg. Annual Rainfall 1,204 mm. Avg. Annual Discharge 4,143 MCM. Sukhothai Province Avg. Annual Rainfall 1,196 mm. Avg. Annual Discharge 2,946 MCM. Kaeng Sua Ten Dam Storage: 1,175 MCM. Annual inflow: 978 MCM. Storage : Inflow = 1 : 0.8 Upper Yom Dam Storage: 166 MCM. Annual inflow: 911 MCM. Storage : Inflow = 1 : 5.5 Yom Dam Storage: 588 MCM. Annual inflow: 1,382 MCM. Storage : Inflow = 1 : 2.4 Sukhothai Phrae
  • 9. 9 | Bridging Policy Gaps through Software and Modelling Adaptation pathway for flood risk management Example of planed decision Local and regional actions ▪ Reduction of flood vulnerability of land use. ▪ Raising embankments Sukhothai. Upstream actions ▪ Large upstream reservoir. ▪ Optimized operation. Stepwise development of strategies ▪ Early implementation measures (e.g. bypass around Sukhothai, flood retardation) ▪ No regret measures (e.g. reduction of flood vulnerability of land use) ▪ Easily adaptable measures (e.g. diversion of peak flows, increase discharge capacity through dredging) ▪ Reservoir measures (e.g. build medium or large reservoir, optimized operation) ▪ Regional measures (e.g. raising embankments) (%)
  • 10. 10 | Bridging Policy Gaps through Software and Modelling Development of Delft3D FM flood model for Ayutthaya City Improving communication between stakeholders
  • 11. 11 | Bridging Policy Gaps through Software and Modelling The great flood in 2011 ▪ The widespread flooding in the Chao Phraya River Basin. ▪ Ayutthaya City suffered from serious damages with almost all area were under water for months. Ayutthaya City Ayutthaya City
  • 12. 12 | Bridging Policy Gaps through Software and Modelling Delft3D FM model outcome ❑ Provide understanding of the event and verify the effectiveness of possible measures in an easy way. ❑ Improve communication among professionals, decision makers and various stakeholders.
  • 13. 13 | Bridging Policy Gaps through Software and Modelling Operational forecasting and early warning system for the Gulf of Thailand Warning and preparation for crisis readiness
  • 14. 14 | Bridging Policy Gaps through Software and Modelling Ocean forecasting system ▪ Hydrodynamic Model (Delft3D FM) ▪ Wave Model (SWAN) ▪ Weather Prediction Model (WRF-ROMS) ▪ Early Warning System (Delft-FEWS) Early Warning System based on Delft-FEWS
  • 15. 15 | Bridging Policy Gaps through Software and Modelling ▪ 31 Dec 2018 - A disturbance in the southern of the South China Sea was upgraded to a tropical depression. ▪ 1 Jan 2019 - It was upgraded to the first tropical storm of the 2019 and was named Pabuk. ▪ 2-3 Jan 2019 - Pabuk accelerated west-northwestward and entered the Gulf of Thailand. ▪ 4 Jan 2019 - Pabuk had made landfall over Pak Phanang, Nakhon Si Thammarat. ▪ 5 Jan 2019 - Pabuk had weaken and moved westward to Andaman Sea. Tropical Storm Pabuk 31/12/18 1/1/192/1/193/1/19 4/1/19 5/1/19 Legends TD TS
  • 16. 16 | Bridging Policy Gaps through Software and Modelling Water level forecast in the Gulf of Thailand Pak Phanang, Nakhon Si Thammarat 03/Jan/19 Pak Phanang, Nakhon Si Thammarat Forecast date: 4 Jan 2019 Reanalysis date: 30 Jan 2019
  • 17. 17 | Bridging Policy Gaps through Software and Modelling Water level forecast in the Gulf of Thailand KoLak station Pak Phanang station Rayong station Ko Samui Station Forecast 3 days ahead, Computation time: 2.5 hrs. Forecast 7 days ahead, Computation time: 6 hrs.
  • 18. 18 | Bridging Policy Gaps through Software and Modelling Comparison of observed and forecasted water level on 5th Jan 2019 Highest observed water level Highest forecasted water level Ko Lak station Actual water level Pak Phanang station Rayong station Ko Samui station Actual water level Actual water level Actual water level
  • 19. 19 | Bridging Policy Gaps through Software and Modelling 4 Jan 2019 - Pak Phanang, Nakhon Si Thammarat 5 Jan 2019 - The Upper Gulf of Thailand Effects of Tropical Storm Pabuk
  • 20. 20 | Bridging Policy Gaps through Software and Modelling HARRIET (1962) PABUK (2019) Landfall at Pakpanang, Nakhon Si Thammarat with wind speed 95 km/hr Evacuation: None Losses: 911 casualties 22,296 households destroyed 50,775 households damage Landfall at Pakpanang, Nakhon Si Thammarat with wind speed 85 km/hr Evacuation: 31,665 people were evacuated Losses: 5 casualties 405 households destroyed 53,008 households damage HARRIET (1962) vs PABUK (2019)
  • 21. 21 | Bridging Policy Gaps through Software and Modelling Reaching information in real-time Rainfall estimation and nowcasting system using composite weather radar data and its application
  • 22. 22 | Bridging Policy Gaps through Software and Modelling POD FAR CSI 7-Jul-19 F1 0.525 0.456 0. F2 0.433 0.619 0. F3 0.400 0.684 0. URBAN RAINFALL (BANGKOK) 7 June 2019 Rainfall estimation and nowcasting system using composite weather radar data BKK
  • 23. 23 | Bridging Policy Gaps through Software and Modelling 23rd July 2019 Heavy rainfall event in Bangkok **BMA reported highest rainfall observed in Nongjok and Klong Samwa Rainfall estimation and nowcasting system using composite weather radar data
  • 24. 24 | Bridging Policy Gaps through Software and Modelling COMPOSITE RADAR ON LINE APPLICATION Rainfall estimation and nowcasting system using composite weather radar data Composite Radar Features: - Push rainfall warnings - User’s request interaction
  • 25. 25 | Effectiveness Clear water policy goals and targets at different level. Efficiency Maximize the benefits of sustainable water management. Trust and Engagement Building public confidence and inclusiveness of stakeholders. Adaption pathway Delft3D FM model Ocean forecasting Composite weather radar Source: OECD (2015), OECD Principles on Water Governance Conclusions
  • 27. 27 | Hydro – Informatics Institute (Public Organization) Ministry of Higher Education, Science, Research and Innovation, THAILAND tel +66 2 5180901 fax +66 2 5180910 www.hii.or.th www.thaiwater.net