Zobrazeno 1 - 10
of 71
pro vyhledávání: '"Hongxiang Fan"'
Autor:
Hongxiang Fan, Fan Song, Huawu Wu, Yao Du, Ruiyu Lei, Mengyao Ding, Kaiwen Li, Jing Li, Congsheng Fu
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 56, Iss , Pp 102049- (2024)
Study region: A typical estuarine delta of Gan−Xiu River within Poyang Lake watershed, situated in the north of Jiangxi Province, China Study focus: Although groundwater is considered as a crucial water resource for social development and public he
Externí odkaz:
https://doaj.org/article/ec9b8618219e44f9a51f37690b7a3f19
Publikováno v:
Journal of Hydrology: Regional Studies, Vol 54, Iss , Pp 101912- (2024)
Study Region: A humid subtropical basin, Poyang Lake Basin, China. Study focus: Drought-flood alternation (DFA) is sub-seasonal precipitation anomaly, which has more serious impact on agricultural production, ecology and environment than a single dro
Externí odkaz:
https://doaj.org/article/bf64c08c393b489bbec8bc32289fed35
Publikováno v:
Ecological Indicators, Vol 165, Iss , Pp 112202- (2024)
This study aims to provide a comprehensive numerical solution and quantitative analysis of the thermal stratification and circulation in Fuxian Lake, the largest freshwater deep lake in China, utilizing a high-fidelity Environmental Fluid Dynamics Co
Externí odkaz:
https://doaj.org/article/c7a98b59d44c4253ac268da323a0fe2c
Publikováno v:
Hydrology Research, Vol 54, Iss 3, Pp 401-417 (2023)
Global warming will significantly affect the frequency and intensity of extreme precipitation and further affect the spatio-temporal pattern of disaster-causing risk of extreme precipitation. This study analyzes the spatio-temporal trends of extreme
Externí odkaz:
https://doaj.org/article/3ea9f79ead9840e5a73630ad9c2336bf
Autor:
Ziyu Wang, Peiying Huang, Xiaoyong Li, Jianmin Pei, Wenzhen Liu, Jiahao Hou, Linjie Li, Hongxiang Fan, Liugen Zeng, Daxian Zhao
Publikováno v:
Fishes, Vol 9, Iss 4, p 132 (2024)
This study evaluated the disparities in growth performance and nutritional composition between two common Chinese mitten crab varieties, “Jianghai 21” and “Changjiang 2”, cultured in Jiangxi Province. Over the breeding period, parameters such
Externí odkaz:
https://doaj.org/article/42a5d185cf3546599b5805069dfad939
Publikováno v:
Water, Vol 15, Iss 3, p 576 (2023)
Water level is an important indicator of lake hydrology characteristics, and its fluctuation significantly affects lake ecosystems. In recent years, deep learning models have shown their superiority in the long-time range prediction of hydrology proc
Externí odkaz:
https://doaj.org/article/82f9e6c8fb6f421eaeea8b313b69edc4
Autor:
Guoyu Xu, Jie Xiao, David M. Oliver, Zhiqi Yang, Kangning Xiong, Zhongming Zhao, Lilin Zheng, Hongxiang Fan, Fuxiang Zhang
Publikováno v:
Ecological Indicators, Vol 133, Iss , Pp 108453- (2021)
Excessive nitrogen and phosphorus inputs to land and subsequent export to water via runoff leads to aquatic ecosystem deterioration. The WRB is the world’s largest karst basin which is characterized by a fragile ecosystem coupling with high populat
Externí odkaz:
https://doaj.org/article/1861e195c57f4ab285e3533ef2f0c94a
Publikováno v:
Water, Vol 14, Iss 3, p 506 (2022)
Stable isotopes of lake waters are widely used to identify the relative importance of hydrological processes on the lake water balance across the ungauged landscape via the coupled-isotope tracer model. The isotopic compositions of twenty shallow fre
Externí odkaz:
https://doaj.org/article/bc20d4fb05b149d6bda857e08b6aa823
Publikováno v:
Atmosphere, Vol 11, Iss 10, p 1033 (2020)
Understanding the spatiotemporal regime of summer precipitation at local scales plays a key role in regional prevention and mitigation of floods disasters and water resources management. Previous works focused on spatiotemporal characteristics of a r
Externí odkaz:
https://doaj.org/article/98f15dcc126c4cf4b703495e0215fc03
Publikováno v:
Water, Vol 12, Iss 1, p 175 (2020)
Runoff modeling is one of the key challenges in the field of hydrology. Various approaches exist, ranging from physically based over conceptual to fully data driven models. In this paper, we propose a data driven approach using the state-of-the-art L
Externí odkaz:
https://doaj.org/article/359c444949f049e1a0978dc886d56e03