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Gianni Vesuviano, Adam Griffin and Elizabeth Stewart
Monsoon-related extreme flood events are experienced regularly across India, bringing costly damage, disruption and death to local communities. This study provides a route towards estimating the likely magnitude of extreme floods (e.g., the 1-in-100-year...
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Xuhui Zeng, Shu Wang, Yunqiang Zhu, Mengfei Xu and Zhiqiang Zou
The recommendation system is one of the hotspots in the field of artificial intelligence that can be applied to recommend suitable ecological patterns for the countryside. Countryside ecological patterns mean advanced patterns that can be recommended to ...
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Yog Aryal
Accurately predicting ambient dust plays a crucial role in air quality management and hazard mitigation. Dust emission is a complex, non-linear response to several climatic variables. This study explores the accuracy of Artificial Intelligence (AI) model...
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Kindie Engdaw Tadesse, Assefa M. Melesse, Adane Abebe, Haileyesus Belay Lakew and Paolo Paron
This study presents three global precipitation products and their downscaled versions (CHIRPSv2, TAMSATv3, PERSIANN_CDR, CHIRPS_D, PERSIANNN_CDR_D, and TAMSAT_D) estimated with observed values from 1983 to 2014. Performance evaluation of global precipita...
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Marcelo Chan Fu Wei, Ricardo Canal Filho, Tiago Rodrigues Tavares, José Paulo Molin and Afrânio Márcio Corrêa Vieira
To obtain a better performance when modeling soil spectral data for attribute prediction, researchers frequently resort to data pretreatment, aiming to reduce noise and highlight the spectral features. Even with the awareness of the existence of dimensio...
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Doddi Yudianto, Bobby Minola Ginting, Stephen Sanjaya, Steven Reinaldo Rusli and Albert Wicaksono
This paper introduces a new simple approach for dam-break hazard mapping in a data-sparse region. A hypothetical breaching case of an earthen dam, i.e., the Ketro Dam in Central Java, (Indonesia) was considered. Open-access hydrological databases, i.e., ...
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Iguniwari Thomas Ekeu-wei and George Alan Blackburn
Consistent data are seldom available for whole-catchment flood modelling in many developing regions, hence this study aimed to explore an integrated approach for flood modelling and mapping by combining available segmented hydrographic, topographic, floo...
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András Bárdossy, Faizan Anwar and Jochen Seidel
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Mouhamed Idrissou, Bernd Diekkrüger, Bernhard Tischbein, Boubacar Ibrahim, Yacouba Yira, Gero Steup and Thomas Poméon
This study investigates the robustness of the physically-based hydrological model WaSiM (water balance and flow simulation model) for simulating hydrological processes in two data sparse small-scale inland valley catchments (Bankandi-Loffing and Mebar) i...
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Xinqiang Du, Xiangqin Lu, Jiawei Hou and Xueyan Ye
In data-sparse areas, due to the lack of hydrogeological data, numerical groundwater models have some uncertainties. In this paper, a nested model and a multi-index calibration method are used to improve the reliability of a numerical groundwater model i...
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