Regional Sustainability ›› 2021, Vol. 2 ›› Issue (1): 60-72.doi: 10.1016/j.regsus.2021.01.004cstr: 32279.14.j.regsus.2021.01.004

Previous Articles     Next Articles

Effect of future climate change on the water footprint of major crops in southern Tajikistan

Muhammadjon Kobulieva,b,c,d, Tie Liua,b,d,e,*(), Zainalobudin Kobulievc, Xi Chena,b, Aminjon Gulakhmadova,b,c, Anming Baoa,b,e   

  1. aState Key Laboratory of Desert and Oasis, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China
    bUniversity of Chinese Academy of Sciences, Beijing, 100049, China
    cInstitute of Water Problems, Hydropower and Ecology of the Academy of Sciences of the Republic of Tajikistan, Dushanbe, 734042, Tajikistan
    dResearch Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi, 830011, China
    eChina-Pakistan Joint Research Center on Earth Sciences, CAS-HEC, Islamabad, 45320, Pakistan.
  • Received:2020-09-26 Revised:2020-12-29 Accepted:2021-01-25 Published:2021-01-20 Online:2021-03-11
  • Contact: Tie Liu E-mail:liutie@ms.xjb.ac.cn

Abstract:

Danghara, a major food production area in southern Tajikistan, is currently suffering from the impact of rapid climate change and intensive human activities. Assessing the future impact of climate change on crop water requirements (CWRs) for the current growing period and defining the optimal sowing date to reduce future crop water demand are essential for local/regional water and food planning. Therefore, this study attempted to analyze possible future climate change effects on the water requirements of major crops using the statistical downscaling method in the Danghara District to simulate the future temperature and precipitation for two future periods (2021-2050 and 2051-2080), under three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5) according to the CanESM2 global climate model. The water footprint (WFP) of major crops was calculated as a measure of their CWRs. The increased projection of precipitation and temperature probably caused an increase in the main crop’s WFP for the current growing period, which was mainly due to the green water (GW) component in the long term and a decrease in the blue water (BW) component during the second future period, except for cotton, where all components were predicted to remain stable. Under three scenarios for the two future periods, a 10 d early sowing time was defined as an optimal sowing date, in which the WFPs of potato and winter wheat decreased from 5.7% to 4.8% and 3.4% to 2.2%, respectively. Although the WFP of cotton demonstrated a stable increase, according to the optimal sowing date, a decrease in irrigation demand or BW was expected. The results of our study might be useful for developing a new strategy related to irrigation systems and could help to find a balance between water and food for environmental water demands and human use.

Key words: Optimal sowing date Representative concentration pathway, Crop water requirement, Statistical downscaling method, Green water, Blue waterSouthern Tajikistan