ALBERT

Description: A statistical model has been developed for forecasting domestic water demand in Haihe river basin of China due to population growth, technological advances and climate change. Historical records of domestic water use, climate, population and urbanization are used for the development of model. An ensemble of seven general circulation models (GCMs) namely, BCC-CSM1-1, BNU-ESM, CNRM-CM5, GISS-E2-R, MIROC-ESM, PI-ESM-LR, MRI-CGCM3 were used for the projection of climate and the changes in water demand in the Haihe River basin under Representative Concentration Pathways (RCPs) 4.5. The results showed that domestic water demand in different sub-basins of the Haihe river basin will gradually increase due to continuous increase of population and rise in temperature. It is projected to increase maximum 136.22 × 108 m3 by GCM BNU-ESM and the minimum 107.25 × 108 m3 by CNRM-CM5 in 2030. In spite of uncertainty in projection, it can be remarked that climate change and population growth would cause increase in water demand and consequently, reduce the gap between water supply and demand, which eventually aggravate the condition of existing water stress in the basin. Water demand management should be emphasized for adaptation to ever increasing water demand and mitigation of the impacts of environmental changes.

Description: The changing characteristics of aridity over a larger spatiotemporal scale have gained interest in recent years due to climate change. The long-term (1901–2016) changes in spatiotemporal patterns of annual and seasonal aridity during two major crop growing seasons of Pakistan, Kharif and Rabi are evaluated in this study using gridded precipitation and potential evapotranspiration (PET) data. UNESCO aridity index was used to estimate aridity at each grid point for all the years between 1901 and 2016. The temporal changes in aridity and its associations with precipitation and PET are evaluated by implementing a moving window of 50-years data with 11-year interval. The modified Mann Kendall trend test is applied to estimate unidirectional change by eliminating the effect of natural variability of climate and the Pettitt’s test is used to detect year of change in aridity. The results reveal that climate over 60 % of Pakistan (mainly in southern parts) is arid. The spatial patterns of aridity trends show a strong influence of the changes in precipitation on aridity trend. The increasing trend in aridity is noticed in the southeast where precipitation is low during Kharif while a decreasing trend in Rabi season in the region which receives high precipitation due to western disturbances. The annual and Kharif aridity are found to decrease at a rate of 0.0001 to 0.0002 per year in northeast while Kharif and Rabi aridity are found to increase at some locations in the south at a rate of −0.0019 to −0.0001. The spatial patterns of aridity changes show a shift from arid to the semi-arid climate in annual and Kharif over a large area while a shift from arid to hyper-arid region during Rabi in a small area. The most of the significant changes in precipitation and aridity are observed in the years between 1971 and 1980. Overall, aridity is found to increase in 0.52 %, 4.44 %, and 0.52 % area and decrease in 11.75 %, 7.57 %, and 9.66 % area for annual, Rabi and Kharif seasons respectively during 1967–2016 relative to 1901–1950.