The Role of Changes in Rainfall Variability - Departures

One of the crucial model components central to the inclusion of rainfall in the AMARC models is the classification of each model year as dry, average or wet. As identified above, the precise nature of this classification has some impact on the modelled outcomes in terms of whether the

rainfall value to be classified represents the precipitation of the current year only or the inclusion of the two previous years as well. However, using a standard definition of a rainfall year ( ) and a standardised means of classifying each year as dry, average or wet (relevant quartile threshold values) in both the analysis of the EMIUB data and each model run allows rainfall to provide a uniform modelled external precursor to migration. As rainfall is therefore used in the same manner in each version of the AMARC3 model, it is difficult to elucidate from model results the precise role of that rainfall plays in the migration decisions of agents.

In an attempt to clarify how rainfall affects the modelled migration decision of agents, three alternative versions of the AMARC3 model are used. AMARC3_Dry runs in the same ‘full model’ manner as AMARC3 but, no matter what the rainfall value of a year, always defines it as below average/dry. As a result, the behavioural attitude values retrieved by agents when making their migration decisions are only ever those calculated from the EMIUB data as being for a below average rainfall year. Similarly, the rainfall assets retrieved for the perceived behavioural control component are only ever average. Models AMARC3_Ave and AMARC3_Wet both have the same core model structure as AMARC3_Dry but define every year as average or above average/wet respectively. As such, only behavioural attitude and rainfall asset values for average and wet years are used respectively. By performing five runs of each of the three AMARC3 dry, average and wet models and comparing the averaged results it is possible to further investigate the role of changes in rainfall variability upon the modelled migration decision. Effectively using three fabricated historical rainfall scenarios, the results from the three models can provide further information on the likely role of changes in rainfall variability in migration decision in Burkina Faso.

Table 4 of Appendix 6 displays the averaged results of five runs of the AMARC3_Dry model. A total of 5,583 migrants are modelled as leaving all zones over the thirty years from 1970-1999 under an artificially dry scenario. Total migration is seen to peak in the AMARC3_Dry model results in 1989 at 264 migrants. Of these, the majority originate in the most populated zone, Centre. The fewest migrants that year meanwhile originate in Ouagadougou.

Table 5 of Appendix 6 displays the five model averaged results from the AMARC3_Ave model.

A total of 6,688 migrants are modelled as leaving all zones between 1970 and 1999 under an artificially average rainfall scenario, 20% more than are modelled by the artificially dry scenario. The year of greatest overall migration modelled by the AMARC3_Ave model is 1990

with 300 migrants. Unlike the modelled results from the dry rainfall scenario run, the majority of these originate in the northernmost zone, Sahel. However, in parallel with the results of the AMARC3_Dry model, the lowest migrant flow that year is modelled by AMARC3_Ave as that originating in Ouagadougou.

Table 6 of Appendix 6 displays the five model averaged results from the AMARC3_Wet model.

A total of 6,192 migrants are modelled as leaving all model zones between 1970 and 1999 under an artificially wet rainfall scenario, 7% less than under the artificially average rainfall scenario and 11% more than the dry. The year of greatest overall migration modelled by AMARC3_Wet is 1989 with 290 migrants. In accordance with the average rainfall version of the model, the majority of these 1989 migrants originate in Sahel while the smallest proportion originates in Ouagadougou. In order to further investigate the role of changes in rainfall variability in the modelled migration decision, Figure 7.13 displays a direct graphical comparison of the total flows of migrants modelled by each version of the AMARC3 model including the ‘full-rainfall’

version.

Figure 7.13: Annual populations of agents modelled by the standard and three rainfall versions of the AMARC3 model as leaving all origin zones between 1970 and 1999. RMSD away from AMARC3 = dry:

30 (15.08%), average: 20 (8.61%) and wet: 22 (10.43%).

Figure 7.13 displays the total migration flows modelled as occurring from all model zones by the three artificial rainfall scenario versions of the AMARC3 model. Between 1970 and 1994 it can be seen that the dry scenario results in the lowest level of total modelled migration.

0 50 100 150 200 250 300 350

AMARC3 AAMRC3_Dry AMARC3_Ave AMARC3_Wet

migrants

However, from 1994 onwards the dry and wet rainfall scenarios show very similar modelled migration flows. The largest total migration flow is modelled by the average rainfall scenario of the AMARC3 model and represents a considerable increase in migration over both the dry and wet scenarios from 1993 onwards.

Results from the standard ‘full-rainfall’ version of the AMARC3 model show consistently higher levels of migration than those modelled under the dry scenario. By contrast, the average and wet rainfall scenarios show modelled total migration flows closer to those of the full model.

Calculating RMSD values that compare migration modelled by the standard version of AMARC3 with each of the artificial rainfall scenario versions show residuals of 30 (15.08%), 20 (8.61%) and 22 (10.43%) for the dry, average and wet scenarios respectively. This suggests that the greatest influence of one rainfall scenario upon total modelled migration in Burkina Faso results from the dry version which models a significant decrease in migration over much of the thirty year test period. As might be anticipated from use of the 1970-1999 rainfall data to define dry, average and wet rainfall conditions, the lowest RMSD residuals score is evident for the average rainfall scenario. Interestingly, towards the end of the model period, total migrant flows modelled by the dry and wet scenarios start to display closer similarities. By the end of the test period the wet scenario modelled flows result in the lowest modelled total migration.

Total modelled migration flow results displayed in Figure 7.13 suggest that, from the approach used to isolate the role of changes in rainfall variability on the migration decision in Burkina Faso, the rainfall conditions that result in the largest overall modelled migration flows are those that are average. Any deviation away from average conditions appears to result in a reduction in migration flows, generally greater throughout the test period under below average rainfall conditions. It appears therefore that the overall flow of migrants in Burkina Faso marginally decreases under wet conditions. In the context of Burkina Faso this could be hypothesised to result from a rainfall-related increase in harvest yield that enables more households to survive the duration of the dry season without having to rely upon migration as a livelihood strategy to support household income. As such, migration becomes more of a choice than a necessity, an occurrence likely replicated in the behavioural attitude values agents in the AMARC model develop towards migration options.

While increased rainfall beyond average conditions is modelled to result in a marginal decrease in total migration, a decrease in rainfall to below average is seen to result in a further reduction