Assessments of Impacts and Adaptations to Climate Change (AIACC)
BEST PRACTICE IN:
Pacific Centre for Environment and Sustainable Development (PACE-SD) of Institute of Applied Sciences (IAS) at University of the South Pacific (USP)
International Global Change Institute (IGCI) at University of Waikato, Hamilton, New Zealand; Fiji Department of Environment, Suva, Fiji; Cook Islands Environment Service, Rarotonga island, Cook Islands
Assessments of Impacts and Adaptations to Climate Change (AIACC); University of the South Pacific (USP)
An important activity of the Pacific Islands Climate Change Assistance Programme (PICCAP), which was a GEF-funded enabling activity, was the development of integrated assessment models to support both Vulnerability and Adaptation (VandA) assessments and capacity building in Pacific island states.
The unique aspect of this work was the linking, through interdisciplinary collaboration, of climate change data, models, and projections with sets of sectoral impact models at the island scale, for both temporal and spatial analyses. Under PICCAP, there were two such modelling developments.
The first was VANDACLIM–The Islands Version (for a fictitious country), a software tool in support of training in VandA assessment. The generic developments for VANDACLIM fuelled the development of a set of prototype integrated assessment models for real places in the Pacific, like Rarotonga (Cook Islands), Viti Levu (Fiji) and Tawara (Kiribati). These “first-order” models contain a climate change scenario generator, island-specific climate data, and a mix of agricultural, coastal, water and health models for impact analyses. The models are designed to be user-friendly, run on a PC and can be easily updated. In effect, these models serve as evolving platforms for integrating scientific knowledge and data for purposes of supporting policy and planning in the context of climate change and variability–a bridge between science and decision-making.
Secondly, recent advances in integrated assessment methods, including those for coastal impacts, adaptation analysis, and economic evaluation were made as part of a recent World Bank supported VandA study focusing on Fiji and Kiribati, for inclusion in the Bank’s Regional Economic Report (RER) for the region.
This study coordinated by the International Global Change Institute (IGCI), provided support for further development of the existing integrated models, especially for Fiji.
Enhance the knowledge base and the technical and human capacity of the PICs for assessing impacts and adaptation to climate change, including the variability and extremes.
To enhance the technical and human capacity of the Pacific Island countries to assess vulnerability and adaptation to climate change, including variability
• To develop the “next generation” of integrated assessment methods and models, for application at island and sub-island scales;
• To expand the understanding and knowledge concerning impacts and adaptation to climate change in the Pacific by implementing, testing and applying the improved methods in case studies representing low atoll and high volcanic island situations; and
• To build in-country research capacity through training in, and transfer of, the advanced methods and integrated assessment models.
The impact of climatic and natural disasters in terms of human and economic losses has risen in recent years, and society in general has become more vulnerable to natural disasters. Those usually most affected by natural, other disasters are the poor and socially disadvantaged groups in the PICs, as they are least equipped to cope with them.
Disaster prevention, mitigation, preparedness, and relief are the four key elements, which contribute to and should gain from the implementation of sustainable development policies in PICs. In addition, environmental protection as a component of sustainable development consistent with poverty alleviation is imperative in the prevention and mitigation of natural disasters.
Some patterns of consumption, production, and development have the potential for increasing the vulnerability to natural disasters, particularly of the poor and socially disadvantaged groups. However, sustainable development can contribute to reduction of this vulnerability, if planned and managed in a way to ameliorate the social and economic conditions of the affected groups and communities.
Thus, these elements, along with environmental protection and sustainable development, are closely interrelated. Therefore, Small Island Nations need to incorporate them in their development plans both at the community and national levels.
The findings most pertinent to this project can be summarised, based on the objectives, as follows:|
The “next generation” integrated model suitable for impact and adaptation assessment in small island states has been developed with following capabilities:
• Capacity for sub-island (community-scale) assessments within the model system. In order to provide the capacity for considering different impacts and adaptation at different scales and to “scale up” from local to national levels, a nested, multi-scale capacity was developed within the single integrated system. This has increased the potential scope of case study applications and the flexibility of addressing a range of impact and adaptation issues.
• Components for the “human dimensions” (e.g. population, infrastructure, land use) of vulnerability.
• The AIACC SIS09 project has developed model components to allow the incorporation of spatially related demographic, land use and infrastructural data. This work includes the development of graphical and tabular tools for displaying such data.
• A socioeconomic scenario generator to project changes in baseline conditions. In order to fit the purposes of the case studies related to risks of river and coastal flooding, this activity focused specifically on the provision of a land use scenario, particularly with regard to buildings at risk from such extreme events. It allows the user to evolve patterns of growth of settlements based on assumptions about trends in population growth, building types and mix, and land constraints.
• Develop the capacity for generating island-specific sea level rise scenarios. The integrated model system was modified to allow the incorporation of local relative sea level trends (as, for example, derived from tide gauge data, which include vertical land movements).
• Regional sea level change patterns (as derived from coupled A-OGCMs), and global-mean projections. The sea level scenario generator was linked to an extreme event analyser in order to perturb sea level time-series data and to examine changes in extreme events (e.g. storm surges) and their return periods. It is also linked to coastal flooding impact models in order to examine impacts and adaptations under climate change.
• Developing coastal impact models appropriate for coral and coral-fringed islands. The emphasis is on impact models relevant to both riverine and coastal flooding, at a scale appropriate for examining community-level impacts. The basic approach has essentially been completed, but there remains work to be done in refining the models to make them “generic” and easily applied in different settings.
• Develop an explicit adaptation component. Modelling capacity has been developed to examine explicitly a set of adaptation options related to flood risks, including raising minimum floor -level requirements for new structures; channelization; and avoidance of building in hazardous areas. These actions represent broad categories of adaptation related to “flood proofing” of structures, engineering works and land use regulation.
• Modify and incorporate economic tools for both valuation of impacts and evaluation of adaptation measures. In the first instance, simple and straightforward methods were developed that could be applied generically across a range of cultural and economic situations found within the Pacific islands. For assessing economic impacts of flooding, generic flood height-damage curves for various categories of building types and contents were developed. These curves can be modified to suit specific situations. Basic tools for benefit-cost analyses were also developed to evaluate the economic viability of adaptation measures. The integrated model allows the user to simulate economic impacts over time for a spectrum of flood events with different return frequencies, which are then aggregated to give present-value, annualised damages (at a user-selected discount rate). Multiple runs--with and without climate change, with and without adaptation–allow the user to separate the benefits and costs of adaptation under climate change from those occurring under natural climate variability.
• The capacity to allow models to run in “transient” mode. Typically, the first generation models (and most impact and adaptation assessments) were run for “time slice” comparisons (e.g. 1990 versus 2050). Running the models in transient mode provides the capacity for capturing the effects of climate variability and extremes along with a changing climate and/or sea level over time. Importantly, this capacity provides the basis for characterising the costs of impacts (and thus the benefits of adaptation) as “streams” or “flows” of effects into the future, which are then discounted back to the present for purposes of evaluation and incremental costing of adaptation options.
• Non-climatic “drivers” such as poor governance and improper land use practices are also important determinants of the overall vulnerability of people to climate change and its present variations as well as extreme weather events. A way forward is to implement climate change adaptation by embracing a connective top-down and bottom-up approach underpinned by lessons learnt from experiences with climate variability and extreme weather events guided by climate-proof development plans. Moreover, there should be clear responsibilities of all stakeholders involved in planning, implementing, and monitoring adaptation measures.
• Local communities in the study sites are “locked” into a vulnerable situation because of their poor socioeconomic conditions coupled with limited input to government decision-making processes and access to financial resources, and therefore need assistance to properly adapt to climate change.
• Project implementation in itself was a learning experience because of the paucity of key relevant data and information, which ultimately dictated variations to be made to the implementation approach and the change in focus of case study applications of the next generation model in Aitutaki and Natadola. Since secondary and tertiary-level students were engaged in the field work, this project helped in raising the capacity of these students to carry out multidisciplinary field assessments where interaction with stakeholders through interviews and observation were followed by analysis of information and data gathered. The field experience gained by these students is an important outcome of this project.
• In terms of long-term capacity building, TrainClim will be incorporated into the USP-based climate change vulnerability and adaptation assessment training. PICs need to be trained in the application of SimCLIM, but more importantly in the interpretation and analysis of the outputs from the next generation model. These needs extend beyond the scope of this project; however, the platform to enable the meeting of this need is the planned incorporation of TrainClim into the USP-based training.
About 40 young pacific professionals working with various government and private agencies have been exposed to the training version (TrainClim) of the SimCLIM model through workshops. The participants appreciated the capacity of the tool to: (i) give pictorial representations of climate change scenarios, (ii) allow the user to use climate change information for simple planning problem, (iii) define and evaluate adaptation options, (iv) perform cost-benefit analysis: time-horizon, discount rate for adaptation measures and (v) be used for coastal inundation, freshwater lens, health impact and shoreline change modelling.
All features of TrainClim are also within SimCLIM as such participants were fully introduced to SimCLIM through its training version. Field surveys were carried out in each of the case study sites using questionnaires designed to gather physical and socioeconomic data. Each of the sites was visited at least thrice within the project.
Information and data gathered included:
• Socioeconomic data (population, economic activities, and income level);
• Building types and values;
• Current land-use and practices;
• Recollection of extreme weather events (tropical cyclones, flash river floods, coastal flooding as a result of storm surge);
• Depth of water in properties during the recent floods;
• Spatial extent of storm surges and floods (coastal and river, where applicable);
• Availability of water (reticulated and rain harvested); • Adaptation options presently implemented (depending on type of risk: floods and drought);
• Barriers experienced in implementing adaptation measures;
• Perception of climate change in general; and
• Important ecosystems and their uses (e.g. mangroves and coral reefs).
In addition to the field surveys, a lot of relevant information was gleaned from available literature, databases (national-statistics, meteorological services, public works departments, mineral resources departments and international-NIWA climate database) and focused interviews with key informants (community leaders, national and local government officials, non-government organisations) from within and outside the study sites.
Kanayathu K., 2007: Modeling Climate Change Impacts of Viti Levu (Fiji) and Aitutaki (Cook Islands). Pacific Centre for Environment and Sustainable Development (PACE-SD), University of South Pacific, Suva, Fiji. Published by The International START Secretariat, Washington DC, USA : http://www.aiaccproject.org/Final%20Reports/Final%20Reports/FinalRept_AIACC_SIS09.pdf