Assessing Climate Change Impacts and Adaptation Using an Integrated Assessment Model

VandaCLIM Training Exercises:

Assessing Climate Change Impacts and Adaptation Using an Integrated Assessment Model

For

Agriculture

Water Resources

Island Groundwater

Coastal Flood Risk

developed and applied for

AIACC Training Workshop on

Climate Change Impacts, Vulnerability and Adaptation

Trieste, Italy

June 2002

By

The International Global Change Institute (IGCI)

The University of Waikato

Hamilton

New Zealand

- Vanda Islands training exercise -

AGRICULTURE

Climatic Risks to Sugarcane Production:

Assessing Impacts and Adaptation

BACKGROUND

Sugarcane is the principal export crop grown in Vanda Islands. It plays an important role in the agricultural sector and for the rural economy. Sugar exports account for approximately 65% of the total export earnings.

The main “Sugar-belt” of Ramaka is located in the relatively dry coastal lowlands of the north and northeast parts of the island where there is a marked dry season (June-August). Sugarcane is normally planted in the December-March period and is harvested 12 months later. Cooler and drier conditions are preferred in the ripening period. On average, Ramaka is able to obtain yields of nearly 60 tonnes per hectare throughout the sugarcane growing area.

However, sugarcane production on Ramaka is quite variable and is susceptible to drought. Since the start of weather records in 1960, drought years have occurred in 1963, 1977, 1983 and 1998 – about once in every ten years, on average. Typically, during these drought events rainfall is about -20% of normal and temperatures are about 0.5 degrees warmer. During these drought years, production also declines markedly. Such declines in sugarcane production severely affect the country’s export earnings and its balance of payments. At the farm level, financial hardship results when yields drop below 46 tonnes/ha, which, in turn, puts strain on the local economy.

Ramaka has partly adapted its sugarcane production to this variable climate. Through both government encouragement and farmers’ own decisions based on experience, the areas of sugarcane production have become concentrated in areas that tend to have the most suitable average climates and soils and that are accessible to transport and processing facilities. This “Sugar-belt” is shown in Figure 1.

However, the residual impacts from extreme years still pose major risks to both farmers, particularly in the more marginal areas, and to the economy of the country as a whole. Moreover, climate change from global warming threatens to increase the risks. Two adaptation strategies have been recommended to government to further reduce the risks:

(1)  Cease sugarcane production in the more marginal areas that are most susceptible to drought events and introduce alternative crops in association with more sustainable land-use practices;

(2)  Intensify sugarcane production in the better land areas through the introduction of irrigation.

MISSION

Your mission is to broadly assess the present and future climatic risks to sugarcane production and to recommend adaptation strategies for reducing the risks. For your analysis, you have available the integrated VandaCLIM system, which contains the model PlantGro for matching land, climate and crops.

TASKS

Task 1: Assess the present climatic risks to sugarcane production:

Step 1.1, current climate and sugarcane yields : Using VandaCLIM, click the Main Menu “Impacts” tab and select the plant icon (see Figure 2). Then make the following selections: Ramaka island; the plant file “sugarcane”; for output images select Yield and Greatest Limitation only. Do not choose a climate scenario at this stage. Click Run. You should get two images. The output images are based on current average climate. Compare the model images to the actual area of sugarcane production on Ramaka (Figure 1).

Q: With average climate, how do average yields vary within the area of sugarcane production? Does the Sugarbelt appear to well adapted to current climate? What are the greatest limiting factors to sugarcane yields?

Step 1.2, impacts of drought: Repeat the procedure as in Step 1, but this time click on Scenario and choose “synthetic” at the top-left corner. Enter the typical drought conditions as regards temperature (+0.5) and rainfall (- 20). Click OK and then Run.

Q: Under drought conditions, how do yields change within the area of sugarcane production? What are the greatest limiting factors to sugarcane yields? What areas appear to be marginal for production (e.g. yield under 46 tonnes/ha) during drought?

(Note: delete the “greatest limitation” images, but keep the “yield” images on the screen).

Task 2: assess the feasibility of sustainable production of sugarcane within the Sugarbelt under average climate change and future drought risk.

The Government of Vanda Islands wishes to plan for the effects of future climate change, with a time horizon out to the year 2050. Furthermore, the Government wishes a single scenario of climate change. As a standard scenario to ensure consistent assessments, the Government Task Force on Climate Change recommended the use of the CSIRO GCM pattern (which validates well in the region) and the IPCC SRES A2 emission scenario, assuming a high value of climate sensitivity. (See attached Box)

Step 2.1, yields under climate change: Using the PlantGro model as above, re-assess sugarcane yields under the scenario of climate change. Select “sugarcane” and tick only the “yield” output image. Click the Scenario button and select “linked-model” scenario generator in the left-top panel. Then follow the Task Force recommendations for climate change scenarios and click OK. You should then get an image of sugarcane yields under future climate change.

Q: Overall, what effect does average climate change have on sugarcane production? Are there areas that appear to be un-sustainable for long-term production within the Sugarbelt?

(note: leave this yield image on the screen along with the previous two images)

Step 2.2, yields under climate change plus drought: Let us assume that the observed distribution of natural climate variability, including drought events, will continue into the future as average climate changes. This simplifying assumption allows us to superimpose the change in climate means on drought events in order to determine their future combined effects. The scenario of climate change for Ramaka used in Step 2.1 produces, by the year 2050, a warming of about 1.0 degree and a change in rainfall of about -8%, averaged over the year. Therefore, future drought events would worsen in intensity, the estimate being 1.5 degrees warmer and -28% drier.

Using PlantGro, examine the effects of such a future droughts on sugarcane. Use the Synthetic scenario generator, entering 1.5 degrees and -28 in the appropriate boxes. Select only “yield” for an output image.

Q: In general, how do the risks – to production, farmers and the economy – of future drought events change by the year 2050?

(note: leave this yield image on the screen along with the previous three images)

Task 3: Consider adaptation options for reducing both current and future risks due to drought and climate change. As noted above, there are two options for adaptation that have been considered: (1) changing land use in more marginal areas; and (2) irrigation (costly, but effective in areas where water availability is the key limiting factor).

Step 3.1, adaptation assessment: Using the four images produced from Tasks 1 and 2 above, provide recommendations regarding the implementation of the two adaptation options.

Q: Where would you recommend changing land use, if at all? Why?

Q: Where would you recommend irrigating, if at all? Why?

Q: In which situations could you argue that adaptation is “no regrets” – that is, it has benefit for the present as well as the future?

Step 3.2, reporting: Please present a summary of your findings to the other groups. Arrange all four images nicely on the screen. Press CTRL-ALT-PrintScrn to capture all the images. The set of images can then be pasted into Powerpoint or Word and copied to a disk for viewing.

- Vanda Islands training exercise -

Coastal Flood Risk

Storm Surge Risks to the Town of Aosis and Tourist Resort:

Assessing Impacts and Adaptation

BACKGROUND

The Republic of Vanda Islands is subject to tropical cyclones. The low pressures and winds that accompany tropical cyclones cause the level of the sea to rise. These “storm surges” can cause extensive coastal flooding. In the past, repeated flood damage to the town of Aosis (population 22,000) and other coastal settlements and infrastructure has prompted the Government of Vanda Islands to establish policies to reduce the coastal flood hazards. According to policy, the official “design risk” associated with development projects is supposed to be the “1-in-25-year” return period.

Two major adaptations to current risks of coastal flooding have already been made. First, due to the growth of the town of Aosis, a sea wall with a height of 1.45 metres was built in the early 1980s to protect the town. Second, the new road around northern Ramaka, built in 1997, was relocated further inland out of reach of the 1-in-25-year storm surge event. However, there are two inter-related concerns for the future: climate change, and increasing urban and tourism development. Both these factors could be increasing the hazard.

On the development side, the population of Aosis is projected to increase by 50%, to 33,000, by the year 2075. Because of land use restrictions on adjacent agricultural land, this increase has to occur within the existing town boundaries. Thus, there will be an increased density of population, housing and commercial development within Aosis. Outside the Aosis town boundaries, exceptions are being made for tourist developments, a crucial aspect of the country’s development strategy. One immediate issue relates to the planned Kai Moana Beach Resort, to be located just east of Aosis. The Government has the dominant stake in this development, with a loan from an international agency. Because tourists like to be very near the beach, the developers wish to locate the resort on the seaward side of the new road. This places the resort within reach of the current 1-in-25-year storm surge event.

As to future climate change, there are two worries. First, sea-level rise due to global warming would effectively increase the height of storm surges and the spatial extent of coastal flooding. Second, there are scientific estimates that storm intensities could increase by 10-20% in a warmer world. The changes would both increase the risks of coastal flooding.

In the face of these future changes, the Government is considering two adaptation options: (1) raising the height of the sea-wall to protect Aosis; and (2) requiring the tourist developers to raise the floor heights of the new buildings.

Figure 1: The Town of Aosis and northern coast,

Ramaka Island, Republic of Vanda Islands

MISSION

Your job is (1) to assess the present coastal flood risks and the adequacy of current adaptation measures; and (2) to assess future changes in risk and evaluate the Governments options for adapting to climate change. For your analysis, you have available the integrated VandaCLIM system, which contains tools for analysing the return periods of storm surge events and their areal extent and for generating future scenarios of sea-level rise that change the risks (Figure 2).

Please follow the attached Work Sheet and enter values into the last column as you work through the Tasks below.

TASKS

Task 1: Assess the present risks of coastal flooding:

Run 1, with current climate: Using VandaCLIM, take the following steps:

1. From the Main Menu select the “wave” Icon (Flood Models).
2. Tick “Inundation Model”, the island “Ramaka” and OK. This will bring up the Scenario Generator.
3. For this Run, leave the year at 1990 (which represents present climate and sea level) and click OK. This will bring up the Sea Level Input Options menu.
4. Leave the settings as they are for this run. Ramaka is geologically stable and shows no vertical movements that would affect relative sea level. As regards the storm surge option, note that the “slide” in the storm surge box is set at the event that will essentially recur every year. Click OK
5. You should now have an image of Ramaka on the screen.

In the image, the blue “inundated” shows the area of reef flat and land that is wet every year. Thus, this image defines the “effective” shoreline at present.

Run 2, current climate with 1-in-25-year event: Repeat Steps 1-3 above. In the Sea Level Input menu, now move the slide until it is set on the 1-in-25 return period (note: you can use the mouse or the arrow keys to fine tune the setting). Click OK. You should now have an image that shows the area of inundation for the 1-in-25 year event. By clicking the “magnifying glass” at the left margin, you can enlarge the area of concern.

Questions:

·  Can you visually verify that the new road is out of reach of the 1-in-25 year surge event?

·  What is the flood height of the 1-in-25 year event? How does it compare to current height of the Aosis sea wall?

·  What is the implied “design risk” of the current sea wall, expressed as a return period (hint: use the slide in the Storm Surge menu to find the return period that matches the wall height).

·  Roughly, what proportion of Aosis is currently at risk from the failure of the sea wall during a 1-in-25 year event (assuming no further adaptation)?

·  How much higher would the wall have to be built in order to achieve an “acceptable level of risk” in accordance with Government policy?

·  The building sites for the planned Kai Moana Beach Resort are all currently 1.25 metres above sea level. Based on a current return period of 1-in-25 year event, how much additional elevation should be added to the floor level in order to satisfy Government risk policy?

Task 2: Assess the future risks of coastal flooding:

The Government of Vanda Islands wishes to plan for the effects of future climate and sea level change, with a time horizon out to the year 2075. Furthermore, the Government wishes a single scenario of climate change. As a standard scenario to ensure consistent assessments, the Government Task Force on Climate Change recommended the use of the IPCC SRES A2 emission scenario, assuming a HIGH value of climate sensitivity. (See attached Box regarding explanation of scenario generation). Also, the Task Force recommends that such scenarios also include a 15% increase in tropical cyclone intensities.