Modeling, Simulation and Data Assimilation for Indus River Basin

Management

SimIndus Group of Pakistani Researchers

Presentation by: Dr Abubakr Muhammad (LUMS)

Planning Commission , Islamabad April 8, 2011

The SimIndus Network

Members Mr. Sarwar Nazir (NCP) [Coordinator] Dr. Abubakr Muhammad (LUMS) Dr. Amer Iqbal Bhatti (MAJU) Dr. Shoab Raza (PIEAS) Dr. Yousaf Shad (QAU) Dr. Adiqa Kiani (FUUAST) Mr. Zia-ud-Din (NDC) Mr. Muhammad Akhtar (NDC) Mr. Saifullah (NDC) Ms. Mariya Absar (LUMS/IIASA) Mr. Muhammad Asif (IIU) Mr. Muslim Shah (NDC) Mr. Muhammad Zeeshan (QAU)

NCP Water Connections

PIEAS Water Connections

MAJU Connections

QAU Water Connections

LUMS Water Group

LUMS Water Group

Lab for Cyber Physical Networks & Systems at LUMS-SSE

Motivation / Concerns

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Annual canal diversions and sea escapage Flow reduction due to climate change

Vulnerability sources

Source. UNEP South Asia report, 2008

Motivation / Strengths

Economically feasible hydro power potential.

Crop yields despite drought.

SimIndus Agenda

• Questions – What is the use of models/scientific data for users and

citizens? [People] – Do we need models to design new control Institutions ?

[Governance] – What are the critical paths in maintenance, optimization

and operation that can be solved by modeling? [SimIndus]

• Explorations

– What needs to be done? – Who does what? – What is being ignored by everyone?

SimIndus Interests (Summary)

• Focus on Modeling, simulation and data assimilation for

• Physical models

• Econometric models

• Operational models

• Regulatory methods

• End Product: Decision support systems at multiple level

• End User: Basin managers • Scenario options

• Informed decisions backed by solid science and data

Need for Data Driven Models

Current governance directions • Participatory irrigation management

• Decision making at many levels. (IRSA, PIDA, WUA, FO…)

• Need decision support systems

• Water entitlements • Being defined/debated at trans-boundary,

national, provincial, regional, farm levels. • Need scientific evidence to support legal

claims, treaty/accord negotiation.

• Accountability • Forecast and analysis for future and past

scenarios. • Conflict resolution requires scientific backup. • Correctly interpret conflicting claims (e.g. on

glacial melt)

Participation

Accountability

Entitlements

A complex system of systems

15 January 17, 2012

Models, Data Assimilation and Usage

Data Assimilation

Physical Models

Sensors / Imaging

Operational Models

Regulation

Models

Set-points

Forecasts

Glacial melt Salt mobility Aquifer dynamics Delta ecosystems Siltation River morphology Evapotranspiration

IBMR, Flood Commission WAPDA sector planning Irrigation depts Feasibility studies

Remote Sensing Discharges/diversion Water quality / Sediment Salinity

Econometric

Models

Agronomics Livestock /fishery Cropping Irrigation

Canal command Costing / Pricing Entitlements Cropping Patterns Groundwater balance

Model Repository (WB Picture)

• Types

– Planning

– Operations

• Multi-scale

– Daily

– Monthly

– Seasonal

– Long-term

Source. World Bank, 2005

Need for Accurate Modeling of Very Complex Systems

• Drainage Master Plan estimated that +34M tonnes of salt accumulated in root zone

• But measurements showed that salinity had stabilized, and was declining • Better model predicts −3M tonnes/yr!

18

Bhutta, World Bank, 2005

January 17, 2012

Water

Silt Salt

Courtesy. Asad Abidi, 2009

Need for Instrumentation / data

• You can not control what you can not measure.

• Need to combine accurate models with good data (assimilation).

19 January 17, 2012 Source. Bastiaanssen, 2003

Source. World Bank, 2005

Need to Settle Contradictory Claims

• Contradictory claims – WB, ADB, DFID, …

• No definite answers yet

• Challenges – Sparse data

– Extreme

topography

• Perfect case for

model based

data assimilation

Courtesy. Mariya Absar, COMSTECH, 2010

Need to Settle Contradictory Claims

• Contradictory claims – WB, ADB, DFID, …

• No definite answers yet

• Challenges – Sparse data

– Extreme

topography

• Perfect case for

model based

data assimilation

Courtesy. Mariya Absar, COMSTECH, 2010

Need for Preservation: e.g. Indus Delta

22

• Diverse bio-environment

• 200 species of fish

• 25,000 tonnes of shrimp/yr; 50% exported

• Reduced outflows have led to shrinking mangrove forests, declining fish stocks

• Fishing communities disappearing

• Need for flows into delta has been long recognized; written into Indus Waters Accord

• Need models to forecast and regulate

January 17, 2012

Existing Operational Models

• Indus Basin WB Study(1968)

• Indus Basin Model (IBM, 1982)

• Indus Basin Model Revised

(IBMR, 1986)

• Indus Basin Model Revised-III

(IBMR-III, 1992)

• Water resource database

(2000-)

IBMR models

• Current Limitations

– Most physical models missing

• Flood impact

• Ground water dynamics

• Drainage

• Climate change

– Many econometric models missing

• 15 crops only

• Wheat centric

Existing Usage of Physical Models

• Practically non-existent

• Isolated reports and scientific papers

• Isolated research activities at centers of excellence / universities

• Little/no Instrumentation to test models

• Existing capacity in basic science/hydrogeology – small

• No data assimilation

Water

Silt Salt

Existing Usage of Regulation Models

• Non-existent

• Critical for – System engineering. e.g. canal command automation

– Conflict management

– Improvement in distribution efficiencies

– Real-time Farmer advice

– Demand driven water delivery

– Fair pricing

• Existing capacity for handling data or models in regulation – practically zero

Existing Usage of Operational Models

• Practically non-existent

• Isolated reports and scientific papers

• Isolated research activities at centers of excellence / universities

• Little/no Instrumentation for basin management

• No data assimilation

Efforts within SimIndus

• Operational models

– Basin operation & management (QAU)

• Regulation models

– Canal command automation (LUMS)

• Physical models

– Aquifier dynamics (IAD – PINSTECH)

– Work on glacier melt (PMD, IAD-PINSTECH)

• Econometric models

– Poverty, productivity and food security (FUUAST)

Case 1: Smart Water Grid (LUMS)

Embedded controller

Gate control

Demand driven delivery to farms

Flow Measurements

Wireless connectivity

LUMS Smart Water Grid

• Model based systems engineering

• Increase of distribution efficiency

• Demand based delivery

• Improvement and enforcement of water rights

LUMS Smart Water Grid • Control of nontechnical

losses – Detection of Leak or unauthorized

takeoff

– Detection of unauthorized dumps

• System health monitoring

• Flood/breach security

Case 2: Stochastic Optimization of Indus Basin (QAU)

• Two stage stochastic programming model.

• Stochastic models of river flows and rainfall.

• Can lead to improvements in IBMR.

Case 2: Stochastic Optimization of Indus Basin (QAU)

• Two stage stochastic programming model.

• Stochastic models of river flows and rainfall.

• Can lead to improvements in IBMR.

• Scenario based planning

Case 2: Stochastic Optimization of Indus Basin (QAU)

Case 3: Water Resource Modeling

(GCISC-Water Group)

• Glaciers in Pakistan cover about 13,680 sq.km.

• Melt water contribute 60% of flows from UIB.

• Glacier melt in Himalayas projected to increase within next 2-3 decades, followed by substantial decrease.

• GCISC findings – Projected temperature rise in North Pak is higher than

that in South.

– Projected precipitation change picture is not clear.

– Pakistan water resources picture remains unclear due to uncertain behavior of HKH glaciers.

Source. Regional Conf on Climate Change Challenges for South Asia, Islamabad, 2009

Who would Benefit?

• End Users are decision makers

• Decision support system needed at all levels

• WAPDA, IRSA, SIRSA, Irrigation depts, PIDA bodies

• Critical for ensuring transparency and maximizing efficiency

• Enabler for setting up new legal structures and reform control institutions.

SimIndus Plans

There is an urgent need for

– Consolidation

– Inclusion / feedback from potential users

– Interdisciplinary cross talk

– Expanding the scope to other important models

– Expansion of the research network

– Establishing connections with experts in policy, law and economics

The Way Forward …..

• Expand the Network

• Include water experts from PCRWR, UET (CE), AUF, IWMI, NIO, SUPARCO, GCISC …..

• Develop connections with international bodies like IIASA, ICTP, KAUST

• Field visits to local institutes

• Develop a position paper on national strategy for future research efforts.

References

• Asad Abidi, “Indus Basin: Past, Present and Future.” APSENA meeting, Univ of Illinois, 2009.

• Briscoe, Qamar, et al., “Pakistan Country Water Resources Assistance Strategy-Water Economy: Running Dry”, World Bank, Washington, 2005

• Babel, Wahid, “Freshwater under threat in South Asia”, UNEP Report, 2009.

• Wim Bastiaanssen, “Remote Sensing Applications on the Indus Basin”, Indus Basin Workshop, Islamabad, 2003.

• Abubakr Muhammad, Hasan Nasir, “Towards a Smart Water Grid in the Indus River Basin.” LUMS Technical Report, 2011.

• Yousaf Shad Muhammad, “Water Resources Management by Stochastic Optimization: A Case Study of Indus Basin Irrigation System,” 2010.

• Mariya Absar, “The Impact of Climate Change on the Galciers, Water Resources and Livelihood of Pakistan,” COMSTECH, 2010.