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The predicted rainfall from the ensemble meteorological modeling system is then used to drive a physically distributed hydrological model for flood responses in the Lanyang basin during the landfall of Typhoon Nanmadol (2011).
This paper introduces an integrated model for flood loss estimation in a river basin.
This study applies an Adaptive Network-based Fuzzy Inference System (ANFIS) and a Real-Time Recurrent Learning Neural Netwith (RTRLNN) with an optimized reservoir release hydrograph using Mixed Integer Linear Programming (MILP) from historical typhoon events to develop a multi-phase intelligent real-time reservoir operation model for flood control.
So-called "green infrastructure" projects - often involving rooftops being covered in soil and plants - are being used extensively in the US city of Philadelphia where officials say they provide a "model" for flood and sewage management.
Ten independent variables, namely land use/land cover, elevation, slope, topographic wetness index, surface runoff, landform, lithology, distance from the main river, soil texture and soil drainage were used into the FR model for flood vulnerability analysis.
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The main goal of the present research is to examine the usefulness of Remote Sensing (RS), GIS and the frequency ratio (FR) models for flood susceptibility analysis and mapping in the Markham river basin under Morobe province, Papua New Guinea.
In this paper the development of a new model for simulating flood inundation is outlined.
In order to evaluate the applicability of the proposed hierarchical Bayesian model for regional flood frequency analysis, we estimate flood quantiles for three randomly chosen out-of-sample sites and compare with classical estimates using the index flood method.
Therefore, this study tries to improve the decomposition-ensemble framework and propose an adaptive middle and long-term runoff forecast model especially for flood seasons.
There are many models as proposed by different researchers, but it is very important to evaluate the accuracy and success rate to validate the model used for flood susceptibility analysis (Chung and Fabbri 2003; Tien Bui et al. 2012).
It calculates the economic loss to different landuse features based on the simulated flood parameters obtained from the hydrologic model for any flood event.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com