Zobrazeno 1 - 10
of 93
pro vyhledávání: '"Chengguang Lai"'
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 52, Iss , Pp 101739- (2024)
Study region: Yangtze River Delta core urban agglomeration, China Study focus: Traditional research on flood susceptibility assessment using machine learning often seeks to enhance model performance by increasing the number of input variables, which
Externí odkaz:
https://doaj.org/article/a8cb1a3806d14b0697b2142eb8da2f10
Autor:
Xiangdong Lei, Jie Jiang, Zifeng Deng, Di Wu, Fangyi Wang, Chengguang Lai, Zhaoli Wang, Xiaohong Chen
Publikováno v:
Remote Sensing, Vol 16, Iss 12, p 2246 (2024)
Urban reservoirs contribute significantly to human survival and ecological balance. Machine learning-based remote sensing techniques for monitoring water quality parameters (WQPs) have gained increasing prominence in recent years. However, these tech
Externí odkaz:
https://doaj.org/article/5a1353d62f8f43878b983606af525869
Publikováno v:
Agricultural Water Management, Vol 291, Iss , Pp 108649- (2024)
With global climate warming, the variability of climate and weather tends to increase driving the water resources available for vegetation become more uncertain. Therefore, there is still a debate as to how vegetation response to, and to which extent
Externí odkaz:
https://doaj.org/article/78ae37ef1fcd468a9454a9d2555c6f2d
Publikováno v:
International Journal of Disaster Risk Science, Vol 14, Iss 2, Pp 253-268 (2023)
Abstract Fast and accurate prediction of urban flood is of considerable practical importance to mitigate the effects of frequent flood disasters in advance. To improve urban flood prediction efficiency and accuracy, we proposed a framework for fast m
Externí odkaz:
https://doaj.org/article/04b3ea11b6c24cf58a9e15d36a68f18f
Autor:
Xuezhi Tan, Qiying Mai, Guixing Chen, Bingjun Liu, Zhaoli Wang, Chengguang Lai, Xiaohong Chen
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 46, Iss , Pp 101327- (2023)
Study region: The Guangdong-Hong Kong-Macao Greater Bay Area (GBA), China. Study focus: Using hourly rain gauge data and CMORPH data, we use the duration-dependent generalized extreme value (d-GEV) model and the scaling invariant GEV model inferred b
Externí odkaz:
https://doaj.org/article/ea4c1f441b274285a1f51378458418ed
Publikováno v:
Remote Sensing, Vol 15, Iss 17, p 4210 (2023)
Reliable assessment of satellite-based precipitation estimation (SPE) and production of more accurate precipitation data by data fusion is typically challenging in sparsely gauged and ungauged areas. Triple collocation (TC) is a novel assessment appr
Externí odkaz:
https://doaj.org/article/e5ab238967b3496cab9934289d374872
Publikováno v:
Water, Vol 15, Iss 16, p 2906 (2023)
Insufficient precipitation observations hinder the bias-correction of Global Climate Model (GCM) precipitation outputs in ungauged and remote areas. As a result, the reliability of future precipitation and water resource projections is restricted for
Externí odkaz:
https://doaj.org/article/ea75acea4cf244c19339d7fe5362ee7e
Autor:
Di Wu, Jie Jiang, Fangyi Wang, Yunru Luo, Xiangdong Lei, Chengguang Lai, Xushu Wu, Menghua Xu
Publikováno v:
Water, Vol 15, Iss 2, p 354 (2023)
With the rapid development of urbanization and a population surge, the drawback of water pollution, especially eutrophication, poses a severe threat to ecosystem as well as human well-being. Timely monitoring the variations of water quality is a prec
Externí odkaz:
https://doaj.org/article/9ef3f56a9efd46f9a3a119518e7869b1
Publikováno v:
Remote Sensing, Vol 14, Iss 15, p 3835 (2022)
Obtaining accurate near-real-time precipitation data and merging multiple precipitation estimates require sufficient in-situ rain gauge networks. The triple collocation (TC) approach is a novel error assessment method that does not require rain gauge
Externí odkaz:
https://doaj.org/article/6130add7c9994fc79fa958f9e3f54722
Publikováno v:
Atmosphere, Vol 13, Iss 7, p 1151 (2022)
Drought is one of the most frequent and most widespread natural disasters worldwide, significantly impacting agricultural production and the ecological environment. An investigation of long-term drought changes and its influencing factors provides no
Externí odkaz:
https://doaj.org/article/601c54f464674068872d6c68be1dc68b