Abstract

Accurate estimation of solute transport has significant importance in water resources and environmental engineering. Among the various types of mathematical formulation for modeling of solute transport, the transient storage model has been widely applied by different researchers as an appropriate model. In this study, an improved version of symbiotic organism search (SOS) algorithm was used to estimate the parameters of transient storage model. A large set of data from natural rivers of USA was collected from the literature and used for derivation and validation of the algorithm. The performance of the algorithm was evaluated by standard statistical indices. Accordingly, the values of R and RMSE for transient storage model parameters (K_f, T and ε) were obtained 0.922 and 30.62 (for K_f), 0.596 and 5645 (for T) and, 0.643 and 0.019 (for ε) for whole dataset. In addition, the results of this study were compared with those obtained by different reserachers via other models. The results indicate the higher capability of improved SOS algorithim compared to the others in estimating the transient storage model parameters.

中文翻译：

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改进的共生生物搜索算法在河流溶质运移估算中的性能评估

摘要

准确估算溶质运移在水资源和环境工程中具有重要意义。在用于溶质运移建模的各种数学公式中，瞬态存储模型已被不同的研究人员广泛地用作合适的模型。在这项研究中，共生生物搜索（SOS）算法的改进版本用于估计瞬时存储模型的参数。从文献中收集了来自美国天然河流的大量数据，并将其用于算法的推导和验证。通过标准统计指标评估算法的性能。因此，瞬态存储模型参数的R和RMSE值（K _f，T和ε）分别为0.922和30.62（对于K _f），0.596和5645（对于T）以及0.643和0.019（对于ε）对于整个数据集。此外，本研究的结果与不同研究者通过其他模型获得的结果进行了比较。结果表明，与其他算法相比，改进的SOS算法在估计暂态存储模型参数方面具有更高的能力。