Analysis of the Evolution of Land-Use Types in the Qilian Mountains from 1980 to 2020

Wang, Miao; Yang, Meixue

doi:10.3390/land12020287

Cited by 7 publications

(6 citation statements)

References 42 publications

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“…The common land use in the Dayekou Basin in the Qilian Mountains of China, as evidenced by the published literature, is primarily grassland. Multiple studies conducted over different periods have consistently identified grassland as the dominant land use type in this region [21,22]. Additionally, there is a presence of construction land, farmland, unused land, and woodland, though these cover smaller proportions compared to the grassland.…”

Section: Study Areamentioning

confidence: 97%

Climate-Driven Dynamics of Runoff in the Dayekou Basin: A Comprehensive Analysis of Temperature, Precipitation, and Anthropogenic Influences over a 25-Year Period

Xu,

Ren,

Amoah

et al. 2024

Water

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Understanding runoff dynamics is vital for effective water management in climate-affected areas. This study focuses on the Dayekou basin in China’s Qilian Mountains, known for their high climate variability. Using 25 years of data (1994–2018) on river runoff, precipitation, and temperature, statistical methods were applied to explore the annual variations and climate change impacts on these parameters. Results reveal a significant variability in the river runoff (132.27 to 225.03 mm), precipitation (340.19 to 433.29 mm), and average temperature (1.38 to 2.08 °C) over the period. Decadal rising rates average 17 mm for runoff, 17 mm for precipitation, and 0.25 °C for temperature, with the peak precipitation and runoff occurring in 1998–2000, 2008, and 2016. The annual runoff distribution also exhibited a unimodal pattern, peaking at 39.68 mm in July. The cumulative runoff during low periods constituted only 13.84% of the annual total, concentrated in the second half of the year, particularly during the June-October flood season. The correlation analysis underscored a strong relationship between river runoff and precipitation (correlation coefficient > 0.80), while the temperature correlation was weaker (correlation coefficient < 0.80). This 25-year analysis provides valuable insights into runoff variation, elucidating the interconnected effects of temperature and precipitation in the Dayekou basin, with substantial implications for sustainable development amid climate challenges.

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Section: Study Areamentioning

confidence: 97%

Climate-Driven Dynamics of Runoff in the Dayekou Basin: A Comprehensive Analysis of Temperature, Precipitation, and Anthropogenic Influences over a 25-Year Period

Xu,

Ren,

Amoah

et al. 2024

Water

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“…These data represent the latest generation of this data type. The ERA5 model combines observational data using physical laws to produce a dataset that covers specific areas and periods [27]. The current study used precipitation data from ERA5-Land with a 0.25 • × 0.25 • spatial resolution.…”

Section: Datamentioning

confidence: 99%

Estimating Evapotranspiration in the Qilian Mountains Using GRACE/GRACE-FO Satellite Data

Bai,

Yue,

Ren

et al. 2024

Remote Sensing

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Evapotranspiration (ET) is the most significant constituent of the response to climate warming. It serves as a crucial link in the soil–vegetation–atmospheric continuum. Analyzing the driving forces and response of ET to regional-scale climate warming holds scientific significance in improving global water resource assessment methods and drought monitoring techniques. The innovation presented in this article is the calculation of ET by using GRACE/GRACE-FO satellite data through the water balance equation. The inter-annual and seasonal changes in ET in different regions of the Qilian Mountains were analyzed, along with quantifying the contribution of environmental meteorological factors to ET. The ETGRACE and ETMonitor products have good consistency, with a monthly correlation coefficient of 0.92, an NSE coefficient of 0.80, and a root mean square error of 10.38 mm. The results indicate that the increasing trend of ET in the Qilian Mountains region exhibits a “medium–high–low” distribution pattern. The rate of increase in ET is 5.2 mm/year in the central segment. In spring and summer, the overall trend of ET is an increasing one. However, the central and western segments exhibit a slight decreasing trend of ET in autumn. During winter, the southern part of the Qilian Mountains experiences a notable reduction in ET. The correlation between the changes in ET and soil moisture exhibited a strong association, with soil moisture change contributing significantly to ET: 57.8% for the eastern section, 52.8% for the middle section, and 46.9% for the western section. The thermal effect primarily controls ET variations within eastern sections, where temperature change accounts for approximately 6.7% of the total variation in ET levels. Conversely, the moisture factor dominates western sections, where precipitation change accounts for about 6.5% of the total variation in ET levels. Due to the distinct gradient characteristics of environmental meteorological factors in the central segment, the fluctuation of these factors collaboratively drives ET changes. This article provides a new approach for obtaining continuous and reliable actual evapotranspiration in high-altitude areas.

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“…The dynamic degree is based on the desert (oasis) area, reflecting the magnitude and rate of change of the desert (oasis) area in different periods, including single dynamic degree and comprehensive dynamic degree [34,[39][40][41][42].…”

Section: Dynamic Degreementioning

confidence: 99%

“…The comprehensive dynamic degree is the ratio of the total decrease (or total increase) of each class (referring to oasis or desert) in the region to two times the total area of the regional land class [34,41]. The model reflects the magnitude and rate of change in the overall land use type (referring to oasis or desert) area over the study period, and the formula is as follows:…”

Section: Dynamic Degreementioning

confidence: 99%

“…Existing studies on drivers mainly use qualitative and quantitative methods [30][31][32][33], among which the qualitative methods cannot specifically derive the extent to which drivers influence spatial and temporal evolution. In contrast, quantitative methods such as gray correlation and correlation analysis are less objective [34,35]. Wang et al [36] proposed a geographic detector as a novel statistical model for detecting spatial differentiation and revealing its driving forces.…”

Section: Introductionmentioning

confidence: 99%

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Geographical Detector-Based Research of Spatiotemporal Evolution and Driving Factors of Oasification and Desertification in Manas River Basin, China

Lee

Yin

Zhu

et al. 2023

Land

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Oasification and desertification are two essential processes of land use and cover (LULC) change in arid regions. Compared to desertification, which is widely regarded as the most severe global ecological issue, the importance of oasification has not received universal recognition. However, neglecting oasification can lead to detrimental outcomes to the effectiveness of ecological governance by affecting the comprehensiveness of environmental policies proposed only based on desertification. Therefore, this study incorporates oasification into the examination of desertification by analyzing land use data for five representative periods spanning from 1980 to 2020, as well as socioeconomic and environmental data from 2000 to 2010. The aim is to evaluate the spatial and temporal dynamics of oasification and desertification in the Manas River Basin and identify the underlying factors driving these processes. The findings indicated that (1) the general trend of oasification and desertification exhibited the expansion of oases and the retreat of deserts. Specifically, the oasification area showed a “decrease-increase-decrease” pattern over time, while the desertification area consistently decreased. (2) In terms of spatial distribution, oasification and desertification displayed a transition from scattered and disordered patterns to an overall more organized pattern, with the hotspot area of desertification shifting from Shawan County to Manas County over time. (3) Population density, average land GDP, soil type and annual precipitation significantly influenced the degree of oasification, with driving force q-values above 0.4, which were the key factors driving oasification. Population density and average land GDP significantly affected the degree of desertification, with driving force q-values above 0.35, which were the key factors driving desertification. The driving force of all factors increased significantly after the interaction, and socioeconomic factors influenced oasification and desertification more than other factors. The study’s findings aim to provide a scientific basis for land resource use, ecological governance and sustainable development in the Manas River basin.

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Analysis of the Evolution of Land-Use Types in the Qilian Mountains from 1980 to 2020

Cited by 7 publications

References 42 publications

Climate-Driven Dynamics of Runoff in the Dayekou Basin: A Comprehensive Analysis of Temperature, Precipitation, and Anthropogenic Influences over a 25-Year Period

Climate-Driven Dynamics of Runoff in the Dayekou Basin: A Comprehensive Analysis of Temperature, Precipitation, and Anthropogenic Influences over a 25-Year Period

Estimating Evapotranspiration in the Qilian Mountains Using GRACE/GRACE-FO Satellite Data

Geographical Detector-Based Research of Spatiotemporal Evolution and Driving Factors of Oasification and Desertification in Manas River Basin, China

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