TY  - JOUR
AU  - Wu, Bingfang
AU  - Tian, Fuyou
AU  - Nabil, Mohsen
AU  - Bofana, José
AU  - Lu, Yuming
AU  - Elnashar, Abdelrazek
AU  - Beyene, Awetahegn Niguse
AU  - Zhang, Miao
AU  - Zeng, Hongwei
AU  - Zhu, Weiwei
PY  - 2023
DA  - 2023//
TI  - Mapping global maximum irrigation extent at 30m resolution using the irrigation performances under drought stress
JO  - Global Environmental Change
SP  - 102652
VL  - 79
KW  - Irrigation mapping, Irrigation performance, GMIE, Google Earth Engine
AB  - Accurate global irrigation information is essential for managing water scarcity and improving food security. However, the mapping of high-resolution irrigation at the global scale is challenging due to the wide range of climate conditions, crop types and phenology, ambiguous and heterogeneous spectral features, and farming practices. Here, a robust method is proposed using irrigation performance under drought stress as a proxy for crop productivity stabilization and crop water consumption. For each irrigation mapping zone (IMZ), dry months in the 2017–2019 period and the driest months in the 2010–2019 period were identified over the growing season. The thresholds of the normalized difference vegetation index (NDVI) in the dry months from 2017 to 2019 and the NDVI deviation (NDVIdev) in the driest month were identified to separate irrigated and rainfed cropland with samples. The final threshold from either the NDVI or the NDVIdev of the IMZ was determined with a higher overall accuracy in separating irrigated and non-irrigated areas. The results show that the global maximum irrigation extent (GMIE) at a 30-m resolution was 23.38% of global cropland in 2010–2019, with an overall accuracy of 83.6% globally and significant regional differences in irrigation proportions ranging from 1.1% in western Africa to 100% in Old World deserts among the 110 IMZs and from 0.4% in Belarus to 80.2% in Pakistan and 100% in Egypt among 45 countries. The study quantitatively distinguished annually and intermittently irrigated regions, which had values of 42% and 58% of global cropland, respectively, by applying indicators. This method, using the NDVI and NDVIdev thresholds, is simple, concrete and reproducible and better for zones with homogeneous weather conditions. The study offers independent, consistent and comparable information for defining the baseline, tracking changes in irrigation infrastructure, and leading future changes in how stakeholders plan and design irrigation systems.
SN  - 0959-3780
UR  - https://www.sciencedirect.com/science/article/pii/S0959378023000183
UR  - https://doi.org/https://doi.org/10.1016/j.gloenvcha.2023.102652
DO  - https://doi.org/10.1016/j.gloenvcha.2023.102652
ID  - WU2023102652
ER  -