TY - JOUR
T1 - Temporal-Spatial changes of monthly vegetation growth and their driving forces in the ancient Yellow river irrigation system, China
AU - Li, Kailong
AU - Huang, Guohe
AU - Zhang, Xiaoyue
AU - Lu, Chen
AU - Wang, Shuo
N1 - Funding Information:
This research was supported by Canada Research Chair Program , Natural Science and Engineering Research Council of Canada , Western Economic Diversification ( 15269 ), and MITACS . We are also very grateful for the helpful inputs from the Editor and anonymous reviewers.
Publisher Copyright:
© 2021 Elsevier B.V.
PY - 2021/12
Y1 - 2021/12
N2 - Irrigation systems play vital roles not only in food production but also in supporting ecosystems. Understanding how the ecosystem has evolved in response to human activities is crucial for sustainable food production, especially for arid and semi-arid regions. In this study, we examined the trends of vegetation growth on a monthly basis in the ancient Yellow River irrigation system in Ningxia, China. We used the leaf area index (LAI) to characterize the vegetation growth from 2007 to 2019. The LAI trends were associated with a series of driving forces, explaining the spatial and temporal change of vegetation growth. With the provision of the Wilks feature importance method, 2-month averaged air temperature and irrigation were identified as the two most important variables for monthly LAI simulation. Future climate projections based on the Regional Climate Model system (RegCM) suggested dryer and longer summers under the RCP 8.5 scenario. These changes will increase the crop water demand during the growing months. In the future, water conflict might be further intensified in May, in which the present irrigation water has already led to a decreased crop growth. Our findings demonstrated that the Mann Kendall monthly trend analysis could provide more helpful information for monitoring the vegetation growth than the trend analysis on a yearly and seasonal basis.
AB - Irrigation systems play vital roles not only in food production but also in supporting ecosystems. Understanding how the ecosystem has evolved in response to human activities is crucial for sustainable food production, especially for arid and semi-arid regions. In this study, we examined the trends of vegetation growth on a monthly basis in the ancient Yellow River irrigation system in Ningxia, China. We used the leaf area index (LAI) to characterize the vegetation growth from 2007 to 2019. The LAI trends were associated with a series of driving forces, explaining the spatial and temporal change of vegetation growth. With the provision of the Wilks feature importance method, 2-month averaged air temperature and irrigation were identified as the two most important variables for monthly LAI simulation. Future climate projections based on the Regional Climate Model system (RegCM) suggested dryer and longer summers under the RCP 8.5 scenario. These changes will increase the crop water demand during the growing months. In the future, water conflict might be further intensified in May, in which the present irrigation water has already led to a decreased crop growth. Our findings demonstrated that the Mann Kendall monthly trend analysis could provide more helpful information for monitoring the vegetation growth than the trend analysis on a yearly and seasonal basis.
KW - Leaf area index
KW - Mann Kendall trend analysis
KW - Reginal climate model projection
KW - Stepwise clustered analysis
UR - http://www.scopus.com/inward/record.url?scp=85118838135&partnerID=8YFLogxK
U2 - 10.1016/j.jconhyd.2021.103911
DO - 10.1016/j.jconhyd.2021.103911
M3 - Journal article
C2 - 34763242
AN - SCOPUS:85118838135
SN - 0169-7722
VL - 243
JO - Journal of Contaminant Hydrology
JF - Journal of Contaminant Hydrology
M1 - 103911
ER -
