Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Hsiang-Kuan Chang"'
Publikováno v:
Terrestrial, Atmospheric and Oceanic Sciences, Vol 21, Iss 3, p 515 (2010)
The Shanchiao fault, located to the west of the Taipei Basin in northern Taiwan, is a highly active normal fault that has a left-slip component and fault length of over 40 km. We suggest that the Shanchiao fault still has the ability to induce coseis
Externí odkaz:
https://doaj.org/article/764723ead5fb47b984676bde45327faf
Autor:
Hsiang-Kuan Chang, 張向寬
101
Frequent floods caused by extreme weather conditions have caused considerable economic and social losses in recent years. Currently, numerous infrastructures have been built in the lowland areas that are prone to inundation, where measures a
Frequent floods caused by extreme weather conditions have caused considerable economic and social losses in recent years. Currently, numerous infrastructures have been built in the lowland areas that are prone to inundation, where measures a
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/27011093531043651321
This study adopts the rainfall scenario generated by TCCIP (The Taiwan Climate Change Projection Information and Adaptation Knowledge Platform) based on IPCC AR5, which provides the 95th percentile of Taipei’s maximum 24-hour cumulative rainfall du
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0d5be0ae5a2ab0f0bab35a64fbcaa435
https://doi.org/10.5194/egusphere-egu23-3073
https://doi.org/10.5194/egusphere-egu23-3073
This study aimed to assess the effective spatial characteristics of input features by using physics-informed, machine learning (ML)-based inundation forecasting models. To achieve this aim, inundation depth data were simulated using a numerical hydro
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1fcb8bcff722dd25acbabf1bdf81fbde
Publikováno v:
Hydrological Sciences Journal. 63:31-49
A wireless water-level monitoring system for an urban drainage flood warning is developed, and stations equipped with pressure sensors are installed to monitor water levels. The water levels for fl...
Autor:
Peng-An Chen, Jihn-Sung Lai, Hsiang-Kuan Chang, Gwo-Fong Lin, Yih-Chi Tan, Ming-Jui Chang, Yun-Chun Chen
Publikováno v:
Water
Volume 10
Issue 12
Water, Vol 10, Iss 12, p 1734 (2018)
Volume 10
Issue 12
Water, Vol 10, Iss 12, p 1734 (2018)
Accurate real-time forecasts of inundation depth and extent during typhoon flooding are crucial to disaster emergency response. To manage disaster risk, the development of a flood inundation forecasting model has been recognized as essential. In this
Autor:
Hsiang-Kuan Chang, Tsung-Yi Pan, Chi-Tai Hsieh, Hao-Yu Liao, Yih-Chi Tan, Jihn-Sung Lai, Ming-Daw Su
Publikováno v:
Water
Volume 11
Issue 2
Water, Vol 11, Iss 2, p 348 (2019)
Volume 11
Issue 2
Water, Vol 11, Iss 2, p 348 (2019)
Pluvial floods are the most frequent natural hazard impacting urban cities because of extreme rainfall intensity within short duration. Owing to the complex interaction between rainfall, drainage systems and overland flow, pluvial flood warning poses
Autor:
Jihn-Sung Lai, Yung-Bin Lin, Hsiang-Kuan Chang, Fong-Zuo Lee, Wen-Dar Guo, Yih-Chi Tan, Cheng-Chia Huang, Kuo-Chun Chang
Publikováno v:
Scour and Erosion.
In Taiwan, owing to deep slope, frequency of extreme rail fall, typhoon attacking and earthquake impacts, huge amount of sediment would generate from mountain area and flow with flood toward downstream river. Then, the bridge safety issue is serious
Publikováno v:
Natural Hazards. 70:1763-1793
Taiwan suffers from an average of three or four typhoons annually, and the inundation caused by the heavy precipitation that is associated with typhoons frequently occurs in lowlands and floodplains. Potential inundation maps have been widely used as
Publikováno v:
Natural Hazards and Earth System Sciences, Vol 11, Iss 3, Pp 771-787 (2011)
This study attempts to achieve real-time rainfall-inundation forecasting in lowland regions, based on a synthetic potential inundation database. With the principal component analysis and a feed-forward neural network, a rainfall-inundation hybrid neu