Exploring the Driving Factors of the Spatiotemporal Variation of Precipitation in the Jing–Jin–Ji Urban Agglomeration from 2000 to 2015
Abstract
:1. Introduction
2. Materials and Methods
2.1. Study Area
2.2. Data Sources
2.2.1. Variable Selection
2.2.2. Data Source
2.3. Methodology
2.3.1. Linear Regression Analysis
2.3.2. Geographic Detector
3. Results and Analysis
3.1. The Spatial Variation of Urban Precipitation in Different Seasons in Cities of Jing–Jin–Ji
3.2. Geographical Detection of Dominant Factors Affecting Annual Precipitation Variation in Different Seasons
3.2.1. Detection of Impact Factors for Urban Precipitation Variation in Different Seasons
3.2.2. Detection of the Dominant Interaction Factors of Urban Precipitation in Different Seasons
3.2.3. Sensitivity Analysis of Different Factors Affecting Precipitation Change in Different Seasons
4. Discussion
4.1. The Driving Factors of the Changes in Spatiotemporal Patterns
4.2. The Impact of the Interaction of Human Factors and Natural Conditions on Precipitation in the Process of Urbanization
5. Conclusions
- (1)
- Urbanization has significant impacts, but it was not as important as changes in natural/meteorological factors such as RAD, RHU, and so forth. There were differences in the explanatory power of the leading factors of precipitation change in Jing–Jin–Ji in different seasons. The variation of RAD was the leading factor of the change of precipitation in summer, explaining 21.3%; the variation of RHU explained 16.9% of the spatial distribution of precipitation change. The dominant factors in winter were RAD, RHU, WIN, and AREA, for which the explanatory power reached 43.3%, 41.9%, 18.0%, and 11.5%, respectively. On an annual scale, the main factors influencing precipitation variation were changes in RHU, AOD, RAD, and WIN, for which the explanatory power was 33.2%, 30.0%, 19.9%, and 14.6%, respectively.
- (2)
- When considering the interaction, the impact of urbanization was very large, which could amplify the impact of man-made and natural/meteorological factors; the magnification and nonlinear relationship changed with different seasons. The interaction of RAD and NDVI was the most significant in summer. The interaction of UHI and RHU came next, with an explanatory power of 56.4%. This indicates that a change in the underlying surface, together with the variation of UHI combined with RHU, can enhance the variation of precipitation in Jing–Jin–Ji. In the process of urbanization and its expansion, in order to prevent extreme drought and flooding, attention should be paid to the protection of vegetation. The interaction of RHU and AOD was most significant in winter, with an explanatory power of 76.6%. The interaction of RAD and AOD came second, which indicated that air pollution plays an important role in precipitation change in Jing–Jin–Ji in winter. On an annual scale, the interaction of RAD and RHU was the most important factor of precipitation change in Jing–Jin–Ji; the interaction of RAD and AOD came next.
- (3)
- Sensitivity factor. By comparing them with the natural factors, human factors, especially UHI and NLI, would greatly amplify the impact of other factors on precipitation change after interacting with other factors that have emerged as the most important and sensitive factors affecting urbanization. The effect of AOD on precipitation changes in summer and winter is greater than that of RHU, RAD, UHI, and so forth. This indicates that, in the process of urbanization, attention should be paid not only to the mitigation of UHI and the protection of green spaces, but also to the protection of the atmospheric environment.
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Scenario | Interaction Types |
---|---|
q(X1∩X2) < Min(q(X1), q(X2)) | Nonlinear attenuation |
Min(q(X1), q(X2)) < q(X1∩X2) < Max(q(X1), q(X2)) | Single factor nonlinear attenuation |
q(X1∩X2) > Max(q(X1), q(X2)) | Double factor enhancement |
q(X1∩X2) = q(X1) + q(X2) | Independence |
q(X1∩X2) > q(X1) + q(X2) | Nonlinear enhancement |
Factors | Summer | Winter | Annual |
---|---|---|---|
AOD | 0.055 | 0.072 | 0.330 *** |
NDVI | 0.057 | 0.047 | 0.116 |
NLI | 0.034 | 0.058 | 0.055 |
RAD | 0.213 *** | 0.433 *** | 0.199 *** |
RHU | 0.169 *** | 0.419 *** | 0.332 *** |
WIN | 0.082 | 0.180 *** | 0.146 ** |
UHI | 0.094 | 0.049 | 0.048 |
POP | 0.017 | 0.055 | 0.093 |
AREA | 0.099 | 0.115 * | 0.090 |
Summer | Winter | Annual | |
---|---|---|---|
Interaction 1 | RAD∩NDVI | RHU∩AOD | RHU∩RAD |
q value | 0.646 | 0.766 | 0.74 |
Interaction 2 | UHI∩RHU | RAD∩AOD | RAD∩AOD |
q value | 0.564 | 0.733 | 0.694 |
Interaction 3 | WIN∩RAD | WIN∩RHU | AREA∩RHU |
q value | 0.558 | 0.729 | 0.661 |
Interaction 4 | WIN∩RHU | RHU∩RAD | RHU∩AOD |
q value | 0.546 | 0.722 | 0.639 |
Interaction 5 | UHI∩NLI | UHI∩RAD | UHI∩AOD |
q value | 0.54 | 0.713 | 0.638 |
Interaction 6 | UHI∩RAD | WIN∩RAD | NDVI∩AOD |
q value | 0.537 | 0.711 | 0.634 |
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Wei, F.; Liang, Z.; Wang, Y.; Huang, Z.; Wang, H.; Sun, F.; Li, S. Exploring the Driving Factors of the Spatiotemporal Variation of Precipitation in the Jing–Jin–Ji Urban Agglomeration from 2000 to 2015. Sustainability 2020, 12, 7426. https://doi.org/10.3390/su12187426
Wei F, Liang Z, Wang Y, Huang Z, Wang H, Sun F, Li S. Exploring the Driving Factors of the Spatiotemporal Variation of Precipitation in the Jing–Jin–Ji Urban Agglomeration from 2000 to 2015. Sustainability. 2020; 12(18):7426. https://doi.org/10.3390/su12187426
Chicago/Turabian StyleWei, Feili, Ze Liang, Yueyao Wang, Zhibin Huang, Huan Wang, Fuyue Sun, and Shuangcheng Li. 2020. "Exploring the Driving Factors of the Spatiotemporal Variation of Precipitation in the Jing–Jin–Ji Urban Agglomeration from 2000 to 2015" Sustainability 12, no. 18: 7426. https://doi.org/10.3390/su12187426