PESERA was applied to simulate current conditions in the Drâa valley.
Actual evapotranspiration (ETact) accounts for more than 90% of the water losses (Figure 2). In the High Atlas Mountains, ETact is lowered due to lower temperature and higher relative humidity. The pattern of surface runoff is opposite to ETact and erosion risk is high (mean rate 19.2 t/ha/a from which 5.6 t/ha/a will reach the reservoir caus-ing severe siltation). In the oases, erosion risk is low although bank erosion may cause losses in agricultural land.
According to the climate scenarios, the Drâa-valley will face a de-crease in rainfall of 30 ± 11mm and an inde-crease in temperature up to 1.4 ± 0.7 °C up to 2050. Rainfall variability and ETact will increase which results in a reduced vegetation coverage amplifying rainfall effects. This results in an increase of the erosion rate up to 21 ± 17%.
Due to increase in temperature, ETact will increase and results in a reduced vegetation coverage which amplifies rainfall effects.
In the socio-economic scenario M1 ”marginalization - low income, high energy costs” soil erosion rate will increase up to 27% while in the scenario M2 “rural development - loss of importance of no-madic lifestyle” it will decrease up to 50% due to reduced pressure on vegetation coverage. The combination of climate change and socio-economic scenarios leads to complex responses which
dif-Figure 2. Results of the PESARA models for surface runoff, actual evapotranspiration, groundwarer recharge, and erosion for the period 1980 to 2000.
fer in the three scenario regions (Figure 3). In the marginalization scenario climate change impact will be aggravated while in the ru-ral development scenarios climate change impacts will partly be compensated by reduced land use. Nevertheless, according to the scenario calculations the remaining reservoir is between nearly 0 and 200 Mio m3 in 2050 which severely threatens water management for the middle Drâa valley (Figure 4).
The options for direct human intervention to attenuate soil erosion risk are limited. The key is to increase vegetation coverage which can not be realized on a short-term. Klose (2009) exemplary analysed two intervention scenarios: first, an afforestation of 6300 ha and second, the exclusion of grazing on 75 000 ha. Both measures take place in the Skoura Mole, which is identified as an erosion hotspot. The efficiency of the measures clearly depends on the spatial scale that is under consideration. At the local scale where the intervention actually takes place, the erosion is reduced by 35.7 to 99.8% up to the year 2050. Thus, afforestation is clearly more efficient than pasture exclusion. At the scale of the High Atlas, the effect of both meas-ures is limited; the soil loss is reduced between 0.6 and 13%. At this scale, the effect of pasture exclusion exceeds that of afforestation,
which is simply due to the larger area. Concerning the sedimentation of the reservoir, the remaining capacity of the reservoir in the year 2050 is 0.7 to 16.8% higher than without intervention. Afforestation raises the reservoir capacity by 2.4 and 0.7% for scenarios M1 and M2, respectively. Pasture exclusion has a more pronounced impact in dampening the reservoir siltation by 16.8 and 4.8% for the M1 and M2 scenarios, respectively. The effect in the M2 scenario is lower due to the already reduced grazing pressure.
The influence of direct human intervention is either limited to the local scale or has to incorporate large areas to mitigate reservoir siltation. The PESERA model is explicitly applicable to the global change impact assessment due to the internal plant growth routine.
The routine allows the protecting vegetation cover to adapt to the changed climate conditions and thus allows the feedback mecha-nisms between climate/vegetation/soil erosion to be identified. In the case of the Drâa catchment, reduction in vegetation cover that is induced by climate change leads to an increase in soil erosion, although precipitation decreases. This relationship would not have been identified with a model that uses static vegetation information such as the USLE.
In conclusion, climate change leads to increased soil loss rates whereas socio-economic development can either aggravate or mitigate the consequences of climate change. The drivers for Global Change are outside of the catchment and can therefore not be influ-enced by the local population. The contribution of the Drâa-valley to Climate Change is negligible and the fate of the economic develop-ment depends on political decision taken at the governdevelop-ment and by money transfer from migrants. The adaptation potential of the local population is limited as they do not have resources for sustain-able use of the environment. Overgrazing, overexploitation of water resources and other degrading activities are a result of poverty. Land degradation and especially soil degradation by water erosion is a severe problem causing on-site and even more important off-site damages. As often observed in those climate zones, reservoir capac-ity is reduced dramatically resulting in reduced buffer capaccapac-ity for coping with climate variability which is likely to increase in future.
Local solutions like afforestation and management of range land requires additional financial support which may be a good investiga-tion if the lifetime of the reservoir is extended by those measures.
Figure 3. Simulated development of the erosion rates in the Drâa valley under socio-economic scenario M1 “marginalization” and M2
“rural development” in the climate change scenario. 250 Mio m3 is required for satisfying water demand of the middle Drâa-valley
Figure 4. Simulated development of the capacity of the reservoir “Mansour Eddahbi” under socioeconomic scenario M1 “marginalization” and M2 “rural development” and climate change scenario. 250 Mio m3 is required for satisfying water demand of the middle Drâa-valley
Acknowledgement
The authors would like to thank the Federal German Ministry of Edu-cation and Research (BMBF, Grant No. 01 LW 06001A/B) as well as the Ministry of Innovation, Science, Research and Technology (MIWFT) of the federal state of Northrhine-Westfalia (Grant No. 313-21200200) for the funding of the IMPETUS project in the framework of the GLOWA program. Many thanks to our partners in Benin and all col-leagues of the IMPETUS project, who provided data and assistance.
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