Climate info helps planners decide whether to grow vegetables or build houses
Climate info helps planners decide whether to grow vegetables or build houses
Should an area of Cape Town currently used for farming be converted to housing? Anna Taylor, research fellow at the Stockholm Environment Institute, uses the weADAPT web platform in conjunction with relevant climate information to seek answers to this planning conundrum
There is a growing recognition that climate change needs to be considered in planning and managing resources and investments, both public and private. This requires accounting for the range of climate conditions experienced in the past and understanding how conditions might change into the future.
Some climate information can be drawn from people’s direct observation of weather patterns, crop cycles, vegetation, water levels and so on, but for a complete picture you also need systematically collected and analyzed scientific data, as well as future climate projections developed through robust computer modelling.
Now a project supported by CDKN has made it easier to use climate data in adaptation planning and vulnerability assessments. The project strengthened linkages between weADAPT, a web platform created by the Stockholm Environment Institute to facilitate learning, knowledge-sharing and networking, and the Climate Information Portal (CIP), developed by the Climate System Analysis Group at the University of Cape Town. As a result, users can now quickly and easily access climate data for many locations across Africa through an interactive map, and find other adaptation projects in the region or addressing similar issues.
A case study in Cape Town, South Africa, shows how weADAPT and CIP can be used together to address adaptation and development questions. The study involves land-use choices in a suburb called Philippi, which includes roughly 2000 hectares of agricultural land that supplies a large share of Cape Town’s fresh produce.
The Philippi Horticultural Area plays a key role in keeping healthy, nutritious food affordable, and it also provides numerous jobs, especially low-skilled jobs, which are highly sought after. The area overlays an aquifer, which makes groundwater relatively cheap and easy to access, but also leaves many parts prone to flooding during the winter rainy season.
Rapid growth in the city puts huge pressures on the land. Hundreds of thousands of households live in slums, in shacks with only communal taps and toilets, few access roads and open trenches for drainage. This has raised the question: Should Philippi Horticultural Area remain in use for vegetable production, or should it be rezoned and used to develop low-cost housing?
There are, of course, many dimensions to making that choice. Our case study focuses on the climate dimension, following a step-by-step process using weADAPT and CIP together.
Step 1: Define the research question
From a housing perspective, we know the biggest climate concern is flooding from heavy winter rains. Water collects in people’s homes and along footpaths and roads, and often mixes with local sources of waste and sewage, damaging property and causing health problems. Many residents are already in poor health and under-nourished, so they are particularly vulnerable. From a vegetable production perspective, meanwhile, the biggest concern is extreme heat that stresses and kills plants.
Thus, we want to look at both rainfall data, as it relates to flooding, and temperature data, as it relates to heat stress.
Step 2: View climate stations on weADAPT
When looking at Cape Town on the Adaptation Layer in weADAPT, we find two stations, one of which – at Cape Town International Airport – is close to Philippi. Historical climate data is available for the years 1979 to 2000.
Step 3: View historical climate data on CIP
We click through to CIP and explore detailed data that shows the seasonal cycle and year-to-year variability in rainfall and temperatures. Note that it might not only be total monthly rainfall that indicates high flood risk, but also how many days in the month it rained and/or how many days in the month received heavy downpours. In fact, the two don’t always overlap. In the temperature data, we see that all the months with the highest average maximum temperature are in the last few years. However, for assessing the risk of heat stress on vegetable crops, it is the temperature and number of days of extreme heat that are most relevant.
Step 4: View future climate projections
Still in CIP, we look at climate projections downscaled to this station for the years 2040 to 2060, and find most of the models suggest a slight decrease in average total monthly rainfall during the winter months of May, June, July and August. The counts of average number of rainy days per month, and of days with heavy downpours, mostly show very slight decreases across the winter months. Thus, the climate projections suggest that, in terms of rainfall, the risk from flooding in winter is unlikely to increase, or may even reduce slightly.
The temperature projections, meanwhile, show a clear increase in monthly average maximum temperature, by 1°C to 2.5°C in the summer months (January, February and March). More notably, although between 1979 and 2000, on average, summer temperatures only exceeded 32°C on one or two days per month, by 2040 to 2060 this is projected to increase by a further two or three days. This could threaten the productivity of various crops unless adaptation measures are taken.
Step 5: Look at data for other nearby stations
For additional context, we check if the climate patterns at the station we examined are also evident at other local stations. We check the nearby Cape Point and Cape Agulhas stations, and find the projections for winter rainfall are similar. In terms of temperature, Cape Point shows much smaller observed and projected numbers of >32°C days, but this might be expected because the station is right on the coast. An inland station in the region, Robertson, shows much higher figures for both historical and projected hot days.
Step 6: Ask, ‘so what?’
Although the rainfall data suggests that flood risks will not increase, it is important to note that the current flood risk is high, with a frequent need for disaster response interventions. This means adaptation is urgently required. Since no major changes in winter rainfall are expected, adaptation measures can be designed around current levels of risk, without concern that these will be exceeded in the coming decades.
However, rainfall is only one component of flooding. Other key factors are ground cover and drainage capacity. Thus, it would be worth modelling the hydrology of the area to see how run-off patterns and flood risk would change with a shift in surface cover from plants to paving.
The temperature data, meanwhile, suggests a sizable increase in the number of very hot days, which poses a threat to vegetable crop yields in the Philippi area. Adaptation measures such as installing shade cloth tunnels and increasing irrigation capacity could help, but have implications for water consumption. That said, replacing farms with housing could well increase the total annual water demand in the area even more. In a water-stressed region, these considerations require further detailed study.
Step 7: Find other places facing similar issues
Back on weADAPT, we search for other case studies addressing similar issues. We find a study on urbanization, climate change and flooding in Quy Nhon City, Vietnam, for example, and an article on water-sensitive urban design in the context of Australia. Both could provide very relevant insights for Philippi.
Step 8: Add your story to weADAPT
A key aspect of weADAPT is sharing lessons learnt. Thus, we have posted the full case study online. We encourage you to read it and post your own work as well, so we can share best practices and information and help advance adaptation knowledge around the world.
Anna Taylor is based at the African Centre for Cities in Cape Town, South Africa. She can be reached at firstname.lastname@example.org.
Photo courtesy of Mark van Overmeire/iStockphoto
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