Given environmental or hydrological functions influenced by changing river networks in the development of rapid urbanization, a clear understanding of the relationships between comprehensive urbanization (CUB) and river network characteristics (RNC), storage capacity (RSC), and regulation capacity (RRC) is urgently needed. In the rapidly urbanized Tai Lake Plain (TLP), China, various methods and multisource data were integrated to estimate the dynamics of RNC, RSC, and RRC as well as their interactions with urbanization. The bivariate Moran's I methods were applied to detect and visualize the spatial dependency of RNC, RSC, or RRC on urbanization. Geographically weighted regression (GWR) model was set up to characterize spatial heterogeneity of urbanization influences on RNC, RSC and RRC. Our results indicated that RNC, RSC and RRC variables each showed an overall decreasing trend across space from 1960s to 2010s, particularly in those of tributary rivers. RNC, RSC, or RRC had globally negative correlations with CUB, respectively, but looking at local scale the spatial correlations between each pair were categorized as four types: high-high, high-low, low-low, and low-high. GWR was identified to accurately predict the response of most RNC, RSC, or RRC variables to CUB (R-2: 0.6-0.8). The predictive ability of GWR was spatially non-stationary. The obtained relationships presented different directions and strength in space. All variables except for the water surface ratio (Wp) were more positively affected by CUB in the middle eastern parts of TLP. Drainage density, RSC and RRC variables were more negatively influenced by CUB in the northeast compared to other parts. The quantitative results of spatial relationships between urbanization and RNC, RSC or RRC can provide location-specific guidance for river environment protection and regional flood risk management.
Journal of Geophysical Research: Atmospheres,2021年126(21):e2021JD035009-null ISSN：2169-897X
[Yu, Xiaoqin; Han, Longfei; Li, Zhongwu; Lv, Dianqing] Hunan Normal Univ, Coll Geog Sci, Changsha, Peoples R China.;[Xu, Youpeng] Nanjing Univ, Sch Geog & Oceanog Sci, Nanjing, Peoples R China.;[Deng, Xiaojun] Zhejiang Univ Finance & Econ, Sch Econ, Hangzhou, Peoples R China.;[Yang, Liu] Hengyang Normal Univ, Coll City & Tourism, Hengyang, Peoples R China.;[Lv, Dianqing] Jiangsu Univ Technol, Sch Chem & Environm Engn, Changzhou, Jiangsu, Peoples R China.
[Xiao, Mu] A;Arizona State Univ, Sch Sustainable Engn & Built Environm, Tempe, AZ 85281 USA.
urban heat island;long-term urbanization;WRF;Yangtze River Delta (YRD)
Abstract In this study, we examined the summertime climatic effects of urban expansion during 1990–2010 in the Yangtze River Delta (YRD) region by analyzing station observations and performing numerical simulations with the Weather Research and Forecast (WRF) model. Long-term observations showed that urban area experienced a larger increase in summertime 2-m air temperature than rural part during 1980–2018, and the influence of urbanization on the urban-rural contrast was greater in the late stage (after 2000) than the early stage (before 2000). We applied the WRF model incorporated with historical land surface cover data (year 1990, 2000, and 2010) to further evaluate the climatic effects of long-term urbanization. On average, urban expansion over 1990–2010 led to 0.75°C increase in daily average temperature (1.06°C in daily minimum and 0.45°C in daily maximum) during the summer. The summertime daily temperature range decreased by 0.61°C in urban environment during the same period. Compared to the warming effect of urbanization in the 1990s, both the magnitude and affected area have increased after the millennium. Also, urban expansion reduced moisture in low-level atmosphere, and this urban dry island (UDI) effect was enhanced in the late stage. Less moisture in the atmosphere offset heat stress index induced by the warming temperature. We also found that the partitioning of net radiation between sensible and latent heat was the key factor that controlled urban warming effect. Plain Language Summary Urbanization is a long-term dynamic process, while the dynamic climatic effect of urbanization was seldom investigated. In this study, we used both long-term observations and simulations to examine the urban effect on summer climate in Yangtze River Delta. We found that urban daily average temperature increased by 0.75°C, and urban warming effect was greater in the late stage (after 2000) than the early stage (before 2000). Urbanization also caused air humidity loss, which made urban area drier and was known as urban dry island (UDI) effect. The change of heat stress was relatively small due to UDI effect. Urbanization resulted in increased sensible heat fluxes and reduced latent heat fluxes, which determined the urban warming effect. This study provides insights to understand warming air temperature in humid urban agglomeration.
FRONTIERS IN EARTH SCIENCE,2021年9 ISSN：2296-6463
[Feng, Chang; Yang, Liu] Hengyang Normal Univ, Coll Geog & Tourism, Hengyang, Peoples R China.;[Han, Longfei] Hunan Normal Univ, Sch Geog Sci, Changsha, Peoples R China.
[Yang, Liu] H;Hengyang Normal Univ, Coll Geog & Tourism, Hengyang, Peoples R China.
water resources;blue water;green water;climate change;parallel parameter calibration method;prediction uncertainty;SWAT
Green water resources, which are fundamental for plant growth and terrestrial ecosystem services, reflect precipitation that infiltrates into the unsaturated soil layer and returns to the atmosphere by plant transpiration and soil evaporation through the hydrological cycle. However, green water is usually ignored in water resource assessments, especially when considering future climate impacts, and green water modeling generally ignores the calibration of evapotranspiration (ET), which might have a considerable impact on green water resources. This study analyzes the spatiotemporal variations in blue and green water resources under historical and future climate change scenarios by applying a distributed hydrological model in the Xiangjiang River Basin (XRB) of the Yangtze River. An improved model calibration method based on remotely sensed MODIS ET data and observed discharge data is used, and the results show that the parallel parameter calibration method can increase the simulation accuracy of blue and green water while decreasing the output uncertainties. The coefficients (p-factor, r-factor, KGE, NSE, R ( 2 ), and PBIAS) indicate that the blue and green water projections in the calibration and validation periods exhibit good performance. Blue and green water account for 51.9 and 48.1%, respectively, of all water resources in the historical climate scenario, while future blue and green water projections fluctuate to varying degrees under different future climate scenarios because of uncertainties. Blue water resources and green water storage in the XRB will decrease (5.3-21.8% and 8.8-19.7%, respectively), while green water flow will increase (5.9-14.7%). Even taking the 95% parameter prediction uncertainty (95 PPU) range into consideration, the future increasing trend of the predicted green water flow is deemed satisfactory. Therefore, incorporating green water into future water resource management is indispensable for the XRB. In general, this study provides a basis for future blue and green water assessments, and the general modeling framework can be applied to other regions with similar challenges.</p>