NEESI: Numerical Experiments of Estuarine Salt Intrusion dataset

The dataset contains the processed data of 1252 simulations using Delft3D Flexible Mesh (DFM) in which estuaries were designed using a parametric design. Every estuary design is based on thirteen (13) input parameters: three (3) boundary conditions, and ten (10) geomorphological characteristics. The output is represented by two (2) variables: (1) the salt intrusion length, 'L'; and (2) the salt variability, 'V'. Simulations are carried out over a span of nine (9) days of which the first eight (8) are considered spin-up; i.e., one (1) day of the simulation is used for further post-processing. The salt intrusion length is a depth- and tide-averaged estimation of the salt intrusion of this last day; and the salt variability an estimate of the difference between the maximum salinity and the minimum salinity over the tide, depth- and spatially- averaged. The various settings of the simulations are drawn using machine learning techniques.

本数据集包含1252次使用Delft3D Flexible Mesh（DFM，代尔夫特三维柔性网格模型）完成的数值模拟经后处理得到的数据，其中河口系统采用参数化设计方法构建。每个河口设计方案均基于13个输入参数，包含3个边界条件与10个地貌特征参数。该数据集的输出包含两个变量：(1) 盐入侵长度（记为L）；(2) 盐度变异性（记为V）。单次模拟总时长为9天，其中前8天为自旋预热（spin-up）阶段，仅最后1天的数据用于后续后处理分析。盐入侵长度为对最后一天的盐入侵情况进行深度与潮汐平均后的估算值；盐度变异性则为对潮汐、深度及空间维度上的盐度最大值与最小值之差进行平均后的估算值。本次模拟的各类参数设置通过机器学习技术生成。