Climate Change Impact - Part 12 - Kagera Basin (Rwanda, Burundi, Uganda and Tanzania)

Climate Change Impact


Part 12: Example – Kagera Basin (Rwanda, Burundi, Uganda and Tanzania)


Summary

The Kagera basin flows into Lake Victoria and as such it forms part of the Nile Basin. An extensive data base of climate and flows was available and was used to calibrate the HYSIM hydrological model to 22 sub-basins. Climate projections show that rainfall is projected to increase but temperature (and hence evapotranspiration) is also expected to increase. Whilst the two changes to some extent balance out, the increase in temperature still has important implications for the future of agriculture.

Introduction

The Kagera River Basin and its tributaries flow within four countries (Rwanda, Burundi, Uganda and Tanzania). The Kagera River flows into Lake Victoria which in turn forms part of the Nile River Basin. The aim of the study was to assess the water resources potential of the basin and also to estimate the potential effect of climate change.

Figure 1 is a map of the river basin with the sub-basins used for hydrological modelling delineated.


Figure 1 Kagera River basin showing sub-basins for hydrological modelling



Current situation

The project team was provided with a climate and hydrometric data base developed in the Lake Victoria Environmental Management Program, Phase I. This included river flow, precipitation, temperature and other variables such as wind speed, sunshine and relative humidity needed to calculate potential evapotranspiration. Data were available up to the year 2000.

The methodology was based on use of a hydrological model, HYSIM (in its monthly variant). A hydrological model requires continuous input data so gaps in the data had to be infilled by reference to nearby stations with data.

Temporal infilling is standard option from the HYSIM program.  The program does this as follows:

  •         Reads the data into a monthly array of data from all stations.  If there are more than a set number of days with data, then the total for those days is adjusted pro-rata upwards to give the month's total (in the case of precipitation) or monthly mean, in the case of other variables.
  •         Calculates a matrix of totals/means for concurrent periods for all pairs of stations.
  •         Uses the above totals to calculate the ratio of the totals/mean for all pairs of stations.
  •         Uses these ratios to estimate the errors in the relationship between all possible pairs of stations.
  •         Infills the monthly data using whichever station with data gives the lowest error and which has not itself been infilled.

Even when all stations with data had been infilled there were still large parts of the basin without measurements. To complement the observed values, data on a 10’ geographical grid from the Climatic Research Units of the University of East Anglia were also used.

The data were used to calculate potential evapotranspiration and precipitation on a 10’ grid. The following figure shows contours of rainfall minus potential evapotranspiration (PET). As can be seen the western parts of the basin are in surplus but those to the east are in deficit.


Figure 2 Precipitation minus potential evapotranspiration

A similar process was used for other climatic parameters.

The data base of rainfall and precipitation were used with the HYSIM hydrological model to simulate river flows in the basin. Flows were simulated for each of the 22 sub-catchments that are shown on figure 1.

The following figure shows the simulated and observed flows for the Rivubu at Gitega.

Figure 3 Simulated and observed flows - River Rivubu at Gitega

For most of the time the simulation is good however the accuracy drops off markedly after the early 1990s. Whilst the data base is good up to the end of the 1980s the number of climate stations becomes much fewer for the later years and this can be considered to explain the change in accuracy.

Climate change

The A1B scenario has a balanced emphasis on all energy sources. It is generally considered to be the projection of temperature that might occur in the absence of any international agreed and binding protocol to reduce carbon emissions. This scenario was therefore used.

The choice of models was based on those listed on Table 6 of the IPCC “General Guidelines on the Use of Scenario Data for Climate Impact and Adaptation Assessment”, Version 2, June 2007.  Seven models were listed. The projections were based on the average of those models.

The following figure shows the current average annual temperature in the basin and the projected temperature for two different time horizons 2020 to 2049 and 2070 to 2099.

Figure 4 - Observed and projected basin temperature fro two time horizons

For the period 1970 to 1999 the average basin precipitation was 1570 mm/year. For the period 2020 to 2049 it is projected to be 1644 mm/year and the period 2070 to 2099 is projected to be 1740 mm/year.

The overall conclusion was that the increase in precipitation would counter-balance the increased potential evapotranspiration at a basin level but for individual sub-catchments the picture was more complex. Even though the overall water balance might be the same the higher temperature had implication for the types of crops which could be grown and the amount of irrigation required.





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Climate Change Impact - Part 4 - River Mekong (China, Thailand, Myanmar, Lao DPR, Vietnam)

Climate Change Impact

Part 4: Example – River Mekong


Summary


A component of a study of the impact of climate change in Cambodia examined how flows in the Mekong River will change in the future. Climate data on precipitation, temperature and other climate variables were used as input to a hydrological model, HYSIM, of the Mekong Basin. The model was calibrated to observed flows at six gauging stations on the main river. The calibrated hydrological model was then used with climate projections to estimate future flows in the River Mekong.

Introduction

The Mekong River Basin has a drainage area of 795,000 km2and the river is 4350 km in length. The river rises in China at an elevation 5224 m. The river, or its tributaries, also flow through Myanmar, Laos, Thailand, Cambodia and Vietnam. The river’s flow is highly seasonal, dictated by snow melt in the upper reaches and by the Monsoon in the middle and lower reaches.

(At the point where the flow was simulated, Kompong Cham, the basin area is 660,000 km2. It is interesting to compare this with the smallest basin in this series simulated by HYSIM, Pago Stream in US Samoa, which is only 1.52 km2.)

The primary objective of the project was to estimate the impact of climate change on flooding of rural communities and of rural roads in Cambodia. As part of this study a hydrological model of the Mekong River at a daily time step was developed.  The study of the Mekong was necessary for two reasons. Firstly, for communities bordering the river and secondly due its interaction with the inland lake of Tonle Sap.

Figure 1 Mekong River Basin


Current climate

There is a wide variation in the climate over the basin. In particular the temperature in the headwaters of the river are much lower than those closer to the mouth of the river. At Phnom Penh in Cambodia the annual average temperature is 27.4 °C and the range of monthly temperatures is 4.5 °C. At the headwaters of the Mekong the equivalent values are an average of -4.8 °C and a range of 22.7 °C.


Figure 2 Monthly average temperature - Mekong River Basin


To estimate the impact of climate change it was decided to simulate the flows of the Mekong using the HYSIM rainfall runoff model. This model simulates the hydrological and hydraulic process in a river basin with a high degree of physical realism. The model can operate at a daily or shorter time step and in this case, it was decided to simulate the flows at a daily time step. Given the very low temperatures in the upper basin the fact that HYSIM can simulate snow accretion and snow melt was important. The input data required are daily rainfall and daily or monthly potential evapotranspiration (PET). The calculation of PET in turn requires data on temperature, humidity, solar radiation and wind speed.

Thee data came from a variety of sources including:
·         The Ministry of Water Resources and Meteorology of Cambodia - MOWRAM (Flow and climate for Cambodia.)
·         The National Climatic Data Center of the USA. (Daily precipitation and temperature for the whole basin.)
·         The TuTiempo web site (Daily precipitation, temperature, wind speed and relative humidity for the whole basin.)
·         The Climate Research Unit of the University of East Anglia (average monthly values of temperature, relative humidity, wind speed and solar radiation on a 10-minute grid for the whole basin.)

HYSIM has a number of built in data processing apps, these included double-mass plots, infilling of gaps in the data series and the calculation of PET.

Flow data for Cambodia came from MOWRAM and for the rest of the basin from the Global Data Runoff Centre (GRDC).

Simulation

The first flow measuring station for which data were available was for Chiang Saen, in Thailand immediately downstream of the border with China. The total catchment area at this point is 186,000 km2. However, given the large difference in climate in this part of the basin the catchment was divided in three sub-catchments, each with its own climate data. The following chart shows the simulated daily flow for the period 1988 to 1993 (1993 being the last year with flow data from GRDC site.)

Figure 3 Simulated and observed flow at Chiang Saen


As can be seen, with the exception of 1992 when simulated flows were too high, the simulation is generally accurate.

The simulation was continued downstream with intermediate calibration points at Chiang Khan (Thailand), Mukdahan (Thailand), Pakse (Laos), Stung Treng (Cambodia), Kratie (Cambodia) and Kampong Cham (Cambodia). The following chart shows the flow simulation at Kampong Cham.

Figure 4 Simulated and observed flow at Kampong Cham


For the site in Cambodia data had been ordered for 3 calendar years, 2011 being the last. As can be seen the simulation is generally accurate. There are, evidently, some small differences but given the limited data availability the simulation can be considered satisfactory. There is no doubt that had more time and data been available the simulation could have been improved, in particular if major tributaries had been simulated.

It should also be recognised that the aim of the exercise was to estimate the impact of climate change and the difference in flows.

Climate change

At the time when this study was carried out the latest climate projections based on Representative Concentration Pathways were not available. The earlier SRES projections were used. In this case, based on earlier work in Cambodia, the ECHAM05 model with the A1B projection was used. This option was chosen as the A1B scenario is considered to be the ‘business as usual’ scenario which, given the absence of a successor to the Kyoto protocol limiting CO2 emissions, was appropriate.

The precipitation and temperature were adjusted using projected values of these two parameters. A second form of projection was included based on the work of O’Gorman (Sensitivity of tropical precipitation extremes to climate change. Geophysical Research Letters, published online: 16 September 2012). The paper quantifies the increase in intense precipitation associated with an increase in temperature in the tropics. To use this relationship the daily precipitation values for each calendar year were ranked and the highest precipitation was increased by 10% for each degree of temperature increase and the next two by 6%.

The following chart shows the change in average monthly flow for the River Mekong at Stung Treng, the most upstream flow station in Cambodia.

Figure 5 Projection change in monthly average flow - River Mekong at Stung Treng



This chart shows that, on average, flows in the Mekong will increase as a result of climate change. In particular the flood peak will be higher.

The final chart shows daily simulation of observed flow for the year with average flow, 1987, and projected flows adjusted to represent the increases expected in 2050.

Figure 6 Projected (2050) and observed (1987) flow - Stung Treng



Conclusion

The Mekong is one of the major rivers of the world. This study showed it was possible to accurately simulate flows using data largely in the public domain. When the hydrological model was used with climate projections it was also possible to estimate future flows in the river.


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