Spatial and temporal dynamics of desertification and its driving mechanism in Hexi region

Abstract

Investigating the spatio‐temporal patterns of desertification and its driving mechanisms is crucial for efforts to improve the ecology and environment and combat desertification. Based on meteorological and satellite remote sensing data, this paper analyzed the dynamic characteristics of desertification in the Hexi region of arid and semiarid land in Northwest China from 2000 to 2018 using a dimidiate pixel model; revealed the relationship between desertification evolution characteristics and climatic variations and anthropogenic events based on the change characteristics of net primary productivity (NPP); and then clarified the response of desertification to climatic variations and anthropogenic events using a geodetector model. Outcomes show that: (1) overall desertification in Hexi region is at a serious level, but during the study period, severe desertification decreased, mainly concentrated in the east and southwest, and non‐desertification increased, mainly near the Qilian Mountains and Shule River basin; (2) there were both spatial and temporal dynamics during the study period, with severe desertification decreasing by 11% and moderate, light, and non‐desertification increasing by 3%, 5%, and 3% respectively; (3) during 2000–2005, human activities, climate change, and their joint contribution to desertification reversal were similar, i.e., 23%, 40%, and 36%, and the former two contributed equally to desertification expansion, 38% and 41%, respectively; climate change predominated in desertification reversal in 2005–2010 and 2015–2018, while human activities predominated in desertification expansion; human activities predominated in desertification reversal and climate change predominated in desertification expansion in 2010–2015. This research can provide a theoretical basis and technical support for ecological and environmental management and sustainable socio‐economic development in arid and semiarid regions.

The Changes of Desertification and Its Driving Factors in the Gonghe Basin of North China over the Past 10 Years

“…This is consistent with previous research on the Qinghai Tibet Plateau [26,27], the source of the Yellow River [35], and the surrounding areas of Qinghai Lake [30]. However, the highest explanatory power of precipitation and land use on desertification in this study is only 0.447, which may be related to the specific geological environment in the Gonghe Basin and the limited factors selection [35,58]. Since 1991, numerous measures have been applied to combat desertification.…”

Multiscale and multifunctional analysis of the coupling relationship between land use and desertification

“…At the large watershed scale, the curve fitting between the ELP and C ks was not significant (Figure 5f), which may be attributed to the opposing effects of the interactions within large watersheds. Water resources are the lifeblood of arid areas (Zhang et al, 2022; Zhao, Chang, et al, 2018), and surface runoff decreases from the upstream region to the midstream and downstream regions (Li et al, 2021). The following feedback path may occur at the large watershed scale: ecological land expansion in the upstream region → increase of water consumption in the upstream region + desertification reversion in the upstream region (intracoupling) → decrease in water inflow in the downstream region → desertification expansion in the downstream region (telecoupling) (Liu, Yu, et al, 2021; Liu, Zhang, et al, 2021).…”

“…At the large watershed scale, the curve fitting between the ELP and C ks was not significant (Figure 5f), which may be attributed to the opposing effects of the interactions within large watersheds. Water resources are the lifeblood of arid areas (Zhang et al, 2022;Zhao, Chang, et al, 2018), and surface runoff decreases from the upstream region to the midstream and downstream regions . The following feedback path may occur at the large watershed scale: ecological land expansion in the upstream region !…”

Spatiotemporal Changes and Driving Force Analysis of Land Sensitivity to Desertification in Xinjiang Based on GEE

“…The first type is to directly use the visual interpretation of remote sensing images or computer classification to understand Land 2023, 12, 849 2 of 20 the status, quantity, and spatial pattern of land desertification, but samples are influenced by human subjective factors, thus limiting the classification accuracy [14,15]. The second category is to construct models to invert the desertification status by selecting several indicators, focusing on spatial and temporal change monitoring [16,17], dynamic process research [18], and driver analysis [19], such as the Integrated Desertification Index, Desertification Degree Index, Environmental Sensitivity Areas Index (ESAI), etc. The Integrated Desertification Index has uncertainties in selecting assessment indicators and determining indicator weights and rank thresholds [20].…”