水文地质工程地质2024，Vol.51Issue(3)：23-33,11.DOI:10.16030/j.cnki.issn.1000-3665.202308022
一种新的估计非高斯分布含水层渗透系数场的方法
A novel approach for estimating hydraulic conductivity of non-Gaussian aquifer
摘要
Abstract
The ensemble Kalman filter(EnKF)is one of the most widely used data assimilation methods.However,it exhibits limitations in handling non-Gaussian problems.To effectively address such issues and accurately describe the connectivity of aquifers,a novel approach named NS-ES-MDA is developed in this study.The proposed NS-ES-MDA synergistically combines the normal-score transformation(NST)with ensemble smoother with multiple data assimilation(ES-MDA).Through comparative experiments,the efficacy of NS-ES-MDA in estimating the hydraulic conductivity of non-Gaussian distributed aquifers is demonstrated.By assimilating the same dataset,NS-ES-MDA exhibits approximately 34％improvement in parameter estimation accuracy and about 35％enhancement in computational efficiency compared to the restart normal-score ensemble Kalman filter(rNS-EnKF).Furthermore,the NS-ES-MDA shows case robustness against the"equifinality"and displays remarkable updating capabilities,which leads to more precise parameter estimates.This study provides an effective solution for parameter estimation in non-Gaussian distributed aquifers.关键词
数据同化/非高斯场/参数估计/集合平滑器/正态分数变换/渗透系数Key words
data assimilation/non-Gaussian fields/parameter estimation/ensemble smoother with multiple data assimilation/normal-score transformation/hydraulic conductivity分类
天文与地球科学引用本文复制引用
孙猛,骆乾坤,孔志伟,郭明,刘明力,钱家忠..一种新的估计非高斯分布含水层渗透系数场的方法[J].水文地质工程地质,2024,51(3):23-33,11.基金项目
国家重点研发计划项目(2022YFC3702200) （2022YFC3702200）
安徽省自然科学基金项目(JZ2022AKZR0451) （JZ2022AKZR0451）
