Climate Change Impact - Part 8 - Samoa

Climate Change Impact


Part 8: Example – Samoa


Summary

Some of the roads on Samoa had been damaged in recent storms and the objective of the project was to prepare the rehabilitation taking account of climate change. Climate data, including rainfall at a 10-inute time step for two stations were obtained. The data showed that there was a significant increase in rainfall with elevation (which might explain why the most severe damage to the roads was at highest elevations). A methodology was developed to estimate the storm intensity for a range of durations and return period taking account of climate change.

Introduction

Samoa consists of two main islands shown on the following map. Both islands have a road network. On Upolo there are roads around and across the island. On Savai’I the roads run around the island.
There is a third island, to the east of and smaller than these two, which is a US territory.


Figure 1 Map of Samoa

The main aim of the project was to upgrade some of the roads on the two Islands taking account of climate change. In particular one of the cross-island roads on Upolu had been damaged during a storm and it considered that its reconstruction should not suffer from the same problem.

As the roads around the islands are often close to sea level, the possibility of sea level rise also had to be considered.

Current climate

There are three types of data available in digital format:

  •         10-minute data from 2010 to 2015 for two stations, Nafanua and Afiamalu.
  •         Daily data from 1984 to 2014 for two stations, Faleolo and Apia.
  •         Monthly data from the early 1980s and in some cases earlier for four stations on Savai’i and one on Upolu.

These data were measured by the Samoa Meteorology Division (SAMET). Other data were abstracted from reports. Additional data on climate and flow were also obtained for US Samoa.

The weather of Samoa is influenced by four main factors:

  •         The sub-tropical high-pressure zone in the Eastern Pacific is a large semi-permanent anticyclone.
  •         Trade winds which blow from between east and south-east which contributes to a rain shadow effect to the north and west of the islands.
  •         The South Pacific Convergence Zone whose position helps to determine the seasonal pattern of the rain in which rain from November to March is above the monthly average.
  •         The Southern Oscillation which when in positive mode leads to increased rainfall.

The rain shadow effect is illustrated by Figure 2 which shows isohyets (contours) of the mean annual rainfall. Areas to the north and west of both of the main islands have less rain than areas to the south and east. The map also shows the effect of elevation on rainfall, with higher rainfall being associated with higher elevations.



Figure 2 Mean annual rainfall Samoa

Climate change projections

  1. The only daily record available for Samoa, of good quality and a long duration, is for Apia. This record was used to estimate the daily rainfall of a given frequency of occurrence.
  2. Two records of rainfall measured at 10-minute intervals are available for a period of up to 6-years, to the south of Apia. The rainfall stations are at different elevations and the one at the higher elevation records more rain than the other. However, when the rainfall at a short duration (from 10 minutes to a few hours) is expressed as a proportion of the daily value, the results are almost identical for both stations. Combining the two records, enables a single curve relating rainfall at a short duration to be calculated, as a proportion of the daily rainfall.
  3. The 10-minute rainfall records are at different elevations (796 m and 128 m) and have different daily storm rainfall (331 mm/day and 206 mm day). This implies that storm rainfall is higher at higher elevations. This is potentially an important conclusion but the 10-minute rainfall records are of short duration. These two records were combined with daily data from Apia, and charts and tables from earlier reports covering both islands, to arrive at a justifiable value for this effect.
  4. The data presented in some earlier reports implied that aspect is an important factor in storm rainfall, with storms on a south-facing slopes having twice the rainfall of slopes on the north or east. It was concluded that the limited data available do not allow an accurate value to be ascribed to this effect.
  5. The relationship between monthly and hourly rainfall was examined. The correlation for the two stations was weak at one station and non-existent at the other.
  6. Two methods are used to calculated the flow resulting from the storm rainfall: The Rational Method for small catchments and the Generalised Tropical Flood Model for larger catchments. These were complemented by the use of a hydrological model of American Samoa.
  7. Climate projections were based on 4 climate models: CSIRO, GFDL, HadGem and MIROC. These had been found to perform well in the region.
  8. Projections were provided for 3 time-horizons: 2030, 2055 and 2090.


 The 2055 projection this represents the highest intensities in this century. And was used for drainage design.
For daily values, this represents an increase of 17% on the current daily rainfall figure and for the standard deviation an increase of 7%. Both the daily values and the standard deviation are used to calculate the rainfall intensities for different frequencies of occurrence.
It was mentioned above that flow and climate data were used for a stream on US Samoa. This is very small catchment, 1.52 km2. (It is interesting to note that in another posting in this series that same model was able to successfully simulate flows in the Mekong River at a point where its drainage area was 660,000 km2.) The HYSIM rainfall/runoff model was run at an hourly time step, though the raingauge was outside the catchment. Figure 3 shows the simulated and observed daily flow.

Figure 3 Simulated and observed flow - Pago Stream - US Samoa

The rainfall and flow data were analysed to estimate an appropriate runoff coefficient. It was found that the coefficient increased for storms of higher return periods and was higher for 2-hour storms that 1-hour storms.
Sea level data were also analysed and it was found that in recent decades sea levels had been increasing by 5 mm a year. This is comparable with the projected values.








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