Data underlying the publication: Incorporating Forecast Uncertainty into Anticipatory Flood Management using a Bayesian Decision Support Framework

This research proposes to demonstrate how a Bayesian decision model can be used to identify the optimal anticipatory actions that minimise the expected losses associated with different flood vulnerability characterisations for selected neighbourhoods (Shyahkas) across Alexandria. The dataset includes output files of the Weather Research Forecasting model. The model is initialised with Global Ensemble Forecast System (GEFS) data over the Alexandria area, Egypt.The original NetCDF files have been converted to .npy files to manage the size. The ensemble rainfall data provided in this dataset is used to develop the probability distribution functions used in the Bayesian decision model, as detailed in the publication and thesis. The scripts for the Bayesian Decision model are also included.

本研究旨在阐明贝叶斯决策模型（Bayesian decision model）如何识别最优预判行动，以最小化埃及亚历山大市选定街区（Shyahkas）针对不同洪水脆弱性特征所对应的预期损失。本数据集包含天气研究与预报模型（Weather Research Forecasting model）的输出文件。该模型依托埃及亚历山大地区的全球集合预报系统（Global Ensemble Forecast System, GEFS）数据完成初始化。原始NetCDF文件已被转换为.npy文件以控制数据体量。本数据集提供的集合降雨数据可用于构建贝叶斯决策模型所用的概率分布函数，相关细节已在发表论文及学位论文中详述。此外还附带贝叶斯决策模型的运行脚本。