Analysis of Runoff Variation and Future Trends in a Changing Environment: Case Study for Shiyanghe River Basin, Northwest China

Shao, Yilei; Dong, Zengchuan; Meng, Jinyu; Wu, Shuisheng; Li, Yao; Zhu, Shengnan; Zhang, Qiang; Zheng, Zhong

doi:10.3390/su15032173

Cited by 6 publications

(4 citation statements)

References 55 publications

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“…Larger uncertainties in both the magnitude and the direction of change in runoff were projected because of the nonlinear responses of runoff to climate change. Interestingly, the opposite change in summer was projected in a previous study [40], which reported that runoff was expected to diminish from 2011-2050 relative to 1971-2010 under the RCP 2.6, 4.5, and 8.5 scenarios based on the VIC hydrological model and CMIP5 GCMs. Additionally, the study also projected more severe droughts from February-April but less severe droughts in January, May, and December.…”

Section: Uncertainties Of Projectionsmentioning

confidence: 77%

Changes in Runoff in the Source Region of the Yellow River Basin Based on CMIP6 Data under the Goal of Carbon Neutrality

Liu

et al. 2023

Water

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China is committed to achieving carbon neutrality before 2060. This study projected the changes in climate and runoff in the source region of the Yellow River Basin for 2021–2060 under lower carbon emission pathways (SSP1–2.6 and SSP2–4.5) using a statistically downscaled climate dataset and the SWAT hydrological model. Results showed that the climate will become warmer and wetter from 2021–2060. In comparison with the baseline period (1995–2014), in terms of the ensemble mean, annual mean air temperature, annual precipitation, and annual runoff will increase by 1.3 °C and 1.6 °C, by 11.1% and 11.2%, and by 12.8% and 11.9% under SSP1–2.6 and SSP2–4.5 scenarios, respectively. Moreover, the seasonal pattern of runoff was projected to change. The proportion of monthly runoff to the annual total will decrease by 0.6–1.0% in summer but increase by 0.1–1.0% during the period from January to April and September to December. The multimodel ensemble mean (MEM) of extremely high monthly flow (Q10) will increase by 3.5–13.4% in the flood season (June to August) and water storage season (September to December). The MEM of extremely low monthly flow (Q90) will increase by 19.4–26.2% from February to April but decrease by 5.0–8.9% in January, May, and December. Thus, the warmer and wetter climate from 2021–2060 will likely cause flatter seasonal distribution of runoff, lower risk of water scarcity at the annual scale and of drought from February to April, but higher risk both of flood in the flood season and of drought in December, January, and May. Generally, the flatter pattern of runoff would likely alleviate water scarcity in the dry and water storage seasons to some degree, and the increase in monthly runoff in the water storage season will benefit hydroelectric power generation and agriculture and animal husbandry production. However, in some years, the increase in Q10 in the flood season will likely increase flood prevention pressure, and the decrease in Q90 in May will likely obstruct grass revival.

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Section: Uncertainties Of Projectionsmentioning

confidence: 77%

Changes in Runoff in the Source Region of the Yellow River Basin Based on CMIP6 Data under the Goal of Carbon Neutrality

Liu

et al. 2023

Water

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“…Moreover, the research uncovered noteworthy insights into the different subregions within the Shiyang River Basin. Upstream areas, benefiting from ample precipitation and glacier thaw, were found to have sufficient water supply, creating favorable conditions for the growth of forests and grasslands [112]. However, it was observed that while high-altitude sub-humid regions initially benefit from temperature variations, prolonged and persistent temperature increases threaten vegetation health.…”

Section: Discussionmentioning

confidence: 99%

Quantitative Analysis of Desertification-Driving Mechanisms in the Shiyang River Basin: Examining Interactive Effects of Key Factors through the Geographic Detector Model

et al. 2023

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Desertification is a global eco-environmental hazard exacerbated by environmental and anthropogenic factors. However, comprehensive quantification of each driving factor’s relative impact poses significant challenges and remains poorly understood. The present research applied a GIS-based and geographic detector model to quantitatively analyze interactive effects between environmental and anthropogenic factors on desertification in the Shiyang River Basin. A MODIS-based aridity index was used as a dependent variable, while elevation, near-surface air temperature, precipitation, wind velocity, land cover change, soil salinity, road buffers, waterway buffers, and soil types were independent variables for the GeoDetector model. A trend analysis revealed increased aridity in the central parts of the middle reach and most parts of the Minqin oasis and a significant decrease in some regions where ecological rehabilitation projects are underway. The GeoDetector model yielded a power determinant (q) ranging from 0.004 to 0.270, revealing elevation and soil types as the region’s highest contributing factors to desertification. Precipitation, soil salinity, waterway buffer, and wind velocity contributed moderately, while near-surface air temperature, road buffer, and land cover dynamics exhibited a lower impact. In addition, the interaction between driving factors often resulted in mutual or non-linear enhancements, thus aggravating desertification impacts. The prominent linear and mutual enhancement occurred between elevation and soil salinity and between elevation and precipitation. On the other hand, the results exhibited a non-linear enhancement among diverse variables, namely, near-surface air temperature and elevation, soil types and precipitation, and land cover dynamics and soil types, as well as between wind velocity and land cover dynamics. These findings suggest that environmental factors are the primary drivers of desertification and highlight the region’s need for sustainable policy interventions.

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“…Elevation gradient plays a key factor for both climate and vegetation spatial heterogeneity across the Shiyang River Basin, Fig 8. Research revealed that the upstream receives sufficient water resources from precipitation and glacier thaw, rendering this sub-region suitable for forest and grassland growth [105]. In addition, the gradient increase in temperature and evaporation, along with a decrease in rainfall, triggers gradual vegetation covers decline from upstream to lower reaches, rendering the extension of barren Land in lower reaches [22,106]. This corroborates the current spatial distribution of desertification levels across the Shiyang River Basin Fig 6, where around 55% of the area of interest is under severe desertification risk, primarily in the basin's middle and lower reaches.…”

Section: Environmental Risk Detection Of Desertification In the Shiya...mentioning

confidence: 99%

Quantitative analysis of desertification driving mechanisms in the Shiyang River Basin: Examining interactive effects of key factors through the Geographic Detector Model

Ngabire¹,

Wang²,

Lü³

et al. 2023

Preprint

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Desertification is a global environmental and socio-economical issue threatening humanity's survival and development. The Shiyang River Basin ecosystem is vulnerable and prone to desertification. In addition, establishing the quantitative analysis of desertification driving factors and understanding their relative contribution, separately or combined, is still an unresolved problem. The present study applied geographic information system (GIS) techniques and a geographic detector model to quantify desertification spatial extent and driving mechanisms. This research utilized Fractional Vegetation Cover (FVC) to elucidate desertification spatial heterogeneity. The 30 years Coefficient of Variation (CV) of the Normalized Difference Vegetation Index (NDVI) was a dependent variable and indicator of ecosystem terrestrial conditions; Elevation, near-surface air temperature, precipitation, wind velocity, land cover change, soil salinity, road buffers, waterway buffers, and soil types were independent variables. The results showed that 89.41% of the total area is under desertification risk, where 20.99% is extremely desertified, 34.45% is severely desertified, 12.05% is moderately, and 21.92% is slightly desertified. The results from the Geodetector model showed that Power Determinant (PD) values ranged between 0.004 and 0.270. Elevation and soil types had the highest contributing factors with PD values of 0.270 and 0.227, whereas precipitation, soil salinity, the buffer of the waterway, and wind velocity played a moderate role with PD values of 0.146, 0.117, 0.107, and 0.071. Near-surface air temperature, road buffer, and land cover dynamics exhibited lower impact with PD values of 0.028, 0.013, and 0.004. In most cases, investigating the interaction between driving factors resulted in a mutual or non-linear enhancement. There was an apparent linear and mutual enhancement between elevation and soil salinity, precipitation, and soil types with values of 0.3513, 0.3232, and 0.3204, respectively. In addition, there was a mutual enhancement between soil salinity and soil types with a value of 0.2962. On the other hand, a non-linear enhancement was observed between Elevation and near-surface air temperature (0.3116), Elevation and Land cover dynamics (0.2759), soil types and near-surface air temperature (0.2687), land cover dynamics and soil types (0.234), precipitation and near-surface air temperature (0.2248), precipitation and wind velocity (0.2248), and between land cover dynamics and precipitation (0.223). This research revealed irrefutable evidence that environmental factors might be the primary drivers of ecosystem disturbance, provided the basis for the environmental footprint of desertification mechanism, and might be a cornerstone for future policy on ecological restoration sustainability in the Shiyang River Basin.

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Analysis of Runoff Variation and Future Trends in a Changing Environment: Case Study for Shiyanghe River Basin, Northwest China

Cited by 6 publications

References 55 publications

Changes in Runoff in the Source Region of the Yellow River Basin Based on CMIP6 Data under the Goal of Carbon Neutrality

Changes in Runoff in the Source Region of the Yellow River Basin Based on CMIP6 Data under the Goal of Carbon Neutrality

Quantitative Analysis of Desertification-Driving Mechanisms in the Shiyang River Basin: Examining Interactive Effects of Key Factors through the Geographic Detector Model

Quantitative analysis of desertification driving mechanisms in the Shiyang River Basin: Examining interactive effects of key factors through the Geographic Detector Model

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