Climate Change Impact and Vulnerability Assessment of Water Resources in the Lower Brahmaputra Basin

1. Climate change impact and vulnerability assessment of water resources systems: the case of Lower Brahmaputra River Basin (LBRB) Candidate: Animesh Kumar Gain, 25th Cycle Tutor: Carlo Giupponi, Ca’ Foscari University of Venice Co-tutor: FabriceRenaud, United Nations University (UNU-EHS) Email: animesh.gain@gmail.com

2. Content • Background • Contribution • Results • Conclusion

3. Content • Background • Contribution • Results • Conclusion

4. Background • Water is a scare resources because of its temporal and spatial variation • Water is the primary medium through which CC influences the Earth’s ecosystems and people’s livelihood and wellbeing (UN Water, 2009) • population pressure, economic growth, and other development pressure on Water demand. • these supply and demand-side changes are increasing vulnerability of water resources systems (WRS)

5. Background • WRSs are complex in nature and can be described, analysed, and possibly managed on the basis of their main Socio-ecosystems (SESs) • there is no universally accepted approach for assessing vulnerability... • there are instead several distinct schools of thought: CCA, DRR, GEC etc. • IPCC-SREX (IPCC 2012) has significantly contributed to integrate DRR & CCA approaches, and to find common terminologies… • but still operational solutions are not available

6. Background • This study attempts to assess impact and VA of WRS at Lower Brahmaputra River Basin (LBRB) • CC, Himalayan Snow melting & riverflow, sea level rise, monsoon climate • Water governance status is very poor • Trans-boundary river China, India, BD, Bhutan

7. Content • Background • Contribution • Results • Conclusion

8. Contribution • Investigating CC impact & VA, it is required IA of WRS (LBRB) that includes following sub-topics: 1. CC Impact on streamflow of lower Brahmaputra 2. Threshold of streamflow (for LBRB) & investigation of CC effect 3. Assessment of water governance trend of Bangladesh 4. Development of generalized framework on VA of WRS & feasibility study in LBRB 5. A dynamic assessment of water scarcity risk and climate change adaptation in LBRB

9. Outline of the Thesis • General Introduction 1. CC impact on streamflow of LB: trends in high & lowflow based on discharge weighted ensemble modelling 2. Threshold of hydrologic flow regime of a river and investigation of CC impact – the case of LBRB 3. An assessment of water governance trend: the case of BD 4. CCA & VA of WRS in developing countries: a generalized framework and feasibility study in BD 5. A dynamic assessment of water scarcity risk and climate change adaptation in LBRB • Conclusion

10. Content • Background • Contribution • Results • Conclusion

11. Results: 1CC Impact on streamflow of lower Brahmaputra Gain, A. K., Immerzeel, W. W., Sperna Weiland, F. C., & Bierkens, M. F. P. (2011). Impact of climate change on the stream flow of the lower Brahmaputra: trends in high and low flows based on discharge-weighted ensemble modelling. Hydrology and Earth System Sciences, 15(5), 1537-1545. doi:10.5194/hess-15-1537-2011

12. Results: 1CC Impact on streamflow of lower Brahmaputra • multi-model ensemble analysis: 12 GCMs outputs that are forced by a global hydrological model. Fig. Multi-model ensemble analysis Table. Weighting factor of each GCM

13. Results: 1CC Impact on streamflow of lower Brahmaputra Fig. Future streamflow for different seasons

14. Results: 1CC Impact on streamflow of lower Brahmaputra • More flooding is expected in the future years. Fig. Future yearly maximum flow Table. Future 7-day low-flow

15. Results: 2 Threshold of streamflow & investigation of CC effect Gain, A. K., Apel, H., Renaud, F., & Giupponi, C. (2012). Threshold of hydrologic flow regime of a river and investigation of climate change impact – the case of lower Brahmaputra river Basin. Under Review, Climatic Change. Ecological flow threshold was determined based on ‘RVA’ approach by Richter et al. (1997)

16. Results: 2Threshold of streamflow & investigation of CC effect Different extent flood

17. Results: 3Assessment of water governance trend of Bangladesh Gain, A. K., & Schwab, M. (2012). An assessment of water governance trends: the case of Bangladesh. Water Policy (IWA). doi:10.2166/wp.2012.143

18. Results: 3Assessment of water governance trend of Bangladesh • 7 indicators of legal, political & administrative aspects by Saleth & Dinar (2004). • Water governance trend based on policy review and stakeholder consultations. • Changes are analysed, shifts indicated by policy documents and the quality of governance perceived by water user groups

19. Results: 3Assessment of water governance trend of Bangladesh • According to the policy documents, all notions of governance have significantly improved and will further improve. • But, according to water user groups, the actual implementation of these policies seems to be far behind what policy documents indicate. • The gap has even been increasing over time.

20. Results: 4Generalized framework on VA of WRS & feasibility at LBRB Gain, A. K., Giupponi, C., & Renaud, F. (2012). Climate Change Adaptation and Vulnerability Assessment of Water Resources Systems in developing countries: A generalized framework and a feasibility study in Bangladesh. Water, 4 (2), 345-366. doi:10.3390/w4020345

21. Results: 4Generalized framework on VA of WRS & feasibility at LBRB • For developing the framework, the evolution of the concept of VA related to WRS have been reviewed. • From the current practices, the research gaps are identified. • forward looking aspects of vulnerability, • seasonal level assessment reflecting both water abundance and scarcity regimes, • a move towards dynamic assessments based upon the concept of SES, with the involvement of stakeholders.

22. Results: 4Generalized framework on VA of WRS & feasibility at LBRB • With an aim to overcome these gaps, a generalized assessment framework is developed and a feasibility study is presented in the context of the Lower Brahmaputra River Basin (LBRB).

23. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB • distinct schools of thought of VA: CCA, DRR Gain, A. K., Giupponi, C. (2013). A dynamic assessment of water scarcity risk and climate change adaptation in Lower Brahmaputra River Basin. In progress. • Recently, IPCC-SREX (IPCC 2012) has significantly contributed to integrate DRR & CCA approaches, and to find common terminologies… • but still operational solutions are not available • This part of study attempts to operationalize previously developed theoretical framework for VA of WRS.

24. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB RECALL Comprehensive Framework Source: Gain, et al (2012). Water, 4 (2), 345-366.

25. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB Risk Assessment Model Source: Giupponi et al (2012).

26. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB Selected Indicators in AHP

27. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB Selected Indicators

28. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB Normalization of indicators value function approach Beinat, 1997

29. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB Normalization of indicators value function approach Beinat, 1997

30. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB Aggregation of indicators: participatory modeling • Aggregation: non-additive aggregation using Choquet integral; Giupponi et el 2012 Möbius coefficients (m): m(1) =μ (1) m(2) =μ (2) m(3) =μ (3) m(1,2) = μ (1,2) – [μ (1) + μ (2)] m(1,3) = μ (1,3) – [μ (1) + μ (3)] m(2,3) = μ (2,3) – [μ (2) + μ (3)] m(1,2,3) = μ (1,2,3) – [μ (1,2) + μ (1,3)+ μ (2,3)] + [μ (1) + μ (2)+ μ (3)] Cm(x1, x2, x3) = m(1) •x1 + m(2) •x2 + m(3) •x3 + m(1,2) •min(x1, x2) + m(1,3) •min(x1, x3) + m(2,3) •min(x2, x3) + + m(1,2,3) •min(x1, x2, x3)

31. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB Aggregation of indicators: participatory modeling • Questionnaire Interview: qualitative • relative importance of the indicators • synergies/ redundancies/ additive. • complementarity/ substitutability between all the indicators when considered together. • The specific numerical measures are then assigned in a numerical computation program (Frisari et al., 2012), Shapley Value for 1 є [x-a; x+a] Shapley Value for 2 є [y-a; y+a] Shapley Value for 3 є [z-a; z+a] • Second Question: conditions on Couples • Strong Synergy: 1.2* [m(1)+m(2)] < m(1,2) • Synergy: 1* [m(1)+m(2)] < m(1,2) <1.5*[m(1)+m(2)] • Additivity: 0.8* [m(1)+m(2)] < m(1,2) < 1.2*[m(1)+m(2)] • Redundancy: 0.5* [m(1)+m(2)] < m(1,2) < 1*[m(1)+m(2)] • Strong Redundancy: m(1,2) < 0.5*[m(1)+m(2)] • The following thresholds have been chosen: • Perfect Compatibility: OI є [0;0.2] • Strong Compatibility: OI є [0.2;0.4] • Neither Comp/Substitutability: OI є [0.4;0.6] • Strong Substitutability: OI є [0.6;0.8] • Perfect Substitutability: OI є [0.8;1]

32. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB Aggregation of indicators: participatory modeling

33. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB Aggregation of indicators: system dynamic model

34. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB Simulation results

35. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB Simulation results Hazard:dry season water scarcity is increasing. Exposure: The people and rice cultivated area which are highly exposed to water scarcity show increasing trend.

36. Results: 5A dynamic assessment of water scarcity risk and climate change adaptation in LBRB Simulation results • Although social vulnerability is shows a decreasing trend,… • …simulated risk increases and fluctuates as a function of hazard levels. • The analysis suggests that during the dry season risks related to water scarcity may increase in the near future.

37. Content • Background • Contribution • Results • Conclusion

38. Conclusion • Discharge time series (for SRES A1B and A2 scenario) was constructed based on ensemble modelling. • Due to CC, hydrologic parameters (i.e., 22 RVA & flood types) exceeds the threshold condition • All notions of governance improved in policy documents but implementation of policies seems to be far behind what policy documents indicate. • From the current practices of VA, the research gaps are identified and to overcome these gaps, a generalized assessment framework is developed. • Application of the framework integrating DRR and CCA considering operationlization of the framework

39. Conclusion • VA/risk assessment results can be used to select adaptation option • After selecting options, water resources decision making will be implemented in the participatory way

40. Thank you very much for your attention