Inter-Annual Vegetation Changes in Response to Climate Variability in Rwanda

Comprehensive studies on how vegetative ecosystems respond to fluctuations in precipitation and temperature patterns are of great necessity for environmental risk assessment and land-use evaluations. The present study examined the annual trends in vegetation greenness in Rwanda from 2000-2015 and assessed the relationship between these dynamics and climate factors by means of MODIS NDVI, air temperature, SOI and precipitation datasets. Mann Kendal trend test has been utilized to determine the direction and the rates of changes, while Spearman’s rank correlation method has been used to determine the levels of associability between NDVI changes and climatic variables. The results indicate that approximately 11.9% of the country’s vegetation has significantly improved (р < 0.05) from slight to significant improvement while 10.4% of the vegetative cover degraded from slight to severe degradation and an estimated 77.6% of the country’s vegetation cover has remained relatively stable. Much of improvement has been detected in the lowlands of eastern province whereas much of degradation has been highlighted in the western highlands of the Congo Nile ridge and Kigali city. There was a weak correlation between NDVI anomalies and SOI anomalies (rs = 0.36) while near surface air temperature was moderately correlated (rs = 0.47) with changes in Mean NDVI. Precipitation was more significantly associated (r = 0.84) with changes in vegetation health in low plains of Eastern Province (Nyagatare District in particular) than in the high altitude regions of the Congo Nile ridge. A strong positive correlation with precipitation was found in rain fed croplands;mosaic vegetation;mosaic forest or shrubland, herbaceous vegetation/grass-land savannah and sparse vegetation. Identification of degradation hotspots could significantly help the government and local authorities galvanize efforts and foster results driven policies of environmental protection and regeneration countrywide.

Projection of future streamflow of the Hunza River Basin,Karakoram Range(Pakistan)using HBV hydrological model

Hydrologiska Byrans Vattenbalansavdeling(HBV) Light model was used to evaluate the performance of the model in response to climate change in the snowy and glaciated catchment area of Hunza River Basin. The study aimed to understand the temporal variation of streamflow of Hunza River and its contribution to Indus River System(IRS). HBV model performed fairly well both during calibration(R2=0.87, Reff=0.85, PBIAS=-0.36) and validation(R2=0.86, Reff=0.83, PBIAS=-13.58) periods on daily time scale in the Hunza River Basin. Model performed better on monthly time scale with slightly underestimated low flows period during bothcalibration(R2=0.94, Reff=0.88, PBIAS=0.47) and validation(R2=0.92, Reff=0.85, PBIAS=15.83) periods. Simulated streamflow analysis from 1995-2010 unveiled that the average percentage contribution of snow, rain and glacier melt to the streamflow of Hunza River is about 16.5%, 19.4% and 64% respectively. In addition, the HBV-Light model performance was also evaluated for prediction of future streamflow in the Hunza River using future projected data of three General Circulation Model(GCMs) i.e. BCC-CSM1.1, CanESM2, and MIROCESM under RCP2.6, 4.5 and 8.5 and predictions were made over three time periods, 2010-2039, 2040-2069 and 2070-2099, using 1980-2010 as the control period. Overall projected climate results reveal that temperature and precipitation are the most sensitiveparameters to the streamflow of Hunza River. MIROC-ESM predicted the highest increase in the future streamflow of the Hunza River due to increase in temperature and precipitation under RCP4.5 and 8.5 scenarios from 2010-2099 while predicted slight increase in the streamflow under RCP2.6 during the start and end of the 21 th century. However, BCCCSM1.1 predicted decrease in the streamflow under RCP8.5 due to decrease in temperature and precipitation from 2010-2099. However, Can ESM2 predicted 22%-88% increase in the streamflow under RCP4.5 from 2010-2099. The results of this study could be useful for decision making and effective future strategic plans for water management and their sustainability in the region.