Supporting data for the journal article "A New Simulation-Optimization Framework for Estimation of Submarine Groundwater Discharge Based on Hydrodynamic Modeling and Isotopic Data"

Estimation of submarine groundwater discharge (SGD) has traditionally relied on isotopic mass balance calculation, which is a form of regional box modeling. Here we propose an entirely new approach for SGD estimation by coupling a general marine hydrodynamic simulation model with a global optimization algorithm.

This dataset is the isotope sampling data for four seasons from 2015 to 2016 in Daya Bay. The data was used to estimate the submarine groundwater discharge in Daya Bay based on a new simulation-optimization framework. It provides the activities of 223Ra, 224Ra, 226Ra and 228Ra measured at 42 sampling stations (29 seawater stations, 9 coastal groundwater stations, and 4 river stations) during the period from 2015 to 2016. The 226Ra data in autumn is absent with no measurement.

传统上，对海底地下水排泄量（SGD）的估算主要依赖于同位素质量平衡计算，这是一种区域箱式模型的形式。本研究提出了一种全新的海底地下水排泄量估算方法，通过耦合通用海洋水文动力学模拟模型与全局优化算法实现。本数据集收集了2015年至2016年四个季节在 Daya Bay 的同位素采样数据，这些数据用于基于新型模拟-优化框架估算 Daya Bay 的海底地下水排泄量。数据集提供了在2015年至2016年期间于42个采样站（包括29个海水站、9个海岸地下水站和4个河流站）测量的223Ra、224Ra、226Ra和228Ra的活动性。秋季的226Ra数据缺失，未进行测量。