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Review of studies on hydrological modelling in Malaysia

机译:马来西亚水文模型研究综述

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Hydrological models are vital component and essential tools for water resources and environmental planning and management. In recent times, several studies have been conducted with a view of examining the compatibility of model results with streamflow measurements. Some modelers are of the view that even the use of complex modeling techniques does not give better assessment due to soil heterogeneity and climatic changes that plays vital roles in the behavior of streamflow. In Malaysia, several public domain hydrologic models that range from physically-based models, empirical models and conceptual models are in use. These include hydrologic modeling system (HEC-HMS), soil water assessment tool (SWAT), MIKE-SHE, artificial neural network (ANN). In view of this, a study was conducted to evaluate the hydrological models used in Malaysia, determine the coverage of the hydrological models in major river basins and to identify the methodologies used (specifically model performance and evaluation). The results of the review showed that 65% of the studies conducted used physical-based models, 37% used empirical models while 6% used conceptual models. Of the 65% of physical-based modelling studies, 60% utilized HEC-HMS an open source models, 20% used SWAT (public domain model), 9% used MIKE-SHE, MIKE 11 and MIKE 22, Infoworks RS occupied 7% while TREX and IFAS occupy 2% each. Thus, indicating preference for open access models in Malaysia. In the case of empirical models, 46% from the total of empirical researches in Malaysia used ANN, 13% used Logistic Regression (LR), while Fuzzy logic, Unit Hydrograph, Auto-regressive integrated moving average (ARIMA) model and support vector machine (SVM) contributed 8% each. Whereas the remaining proportion is occupied by Numerical weather prediction (NWP), land surface model (LSM), frequency ratio (FR), decision tree (DT) and weight of evidence (WoE). Majority of the hydrological modelling studies utilized one or more statistical measure of evaluating hydrological model performance ( R, R _(2), NSE, RMSE, MAE, etc.) except in some few cases where no specific method was stated. Of the 70 papers reviewed in this study, 16 did not specify the type of model evaluation criteria they used in evaluating their studies, 17 utilized only one method while 37 used two or more methods. NSE with 27% was found to be the most widely used method of evaluating model performance; R and RMSE came second with a percentage use 24% each. R _(2)(20%) was recorded as the third most widely used model evaluation criteria in Malaysia, MAE came fourth with 16% while PBIAS is the least with 11%.The findings of this work will serve as a guide to modelers in identifying the type of hydrological model they need to apply to a particular catchment for a particular problem. It will equally help water resources managers and policy makers in providing them with executive summary of hydrological studies and where more input is needed to achieve sustainable development.
机译:水文模型是水资源和环境规划和管理的重要组成部分和基本工具。最近,已经通过检查模型结果与流流量测量的兼容性进行了几项研究。一些建模者认为,即使使用复杂的建模技术也不会因土壤异质性和气候变化而提供更好的评​​估,这些变化在流流的行为中起着重要作用。在马来西亚,几种公共领域水文模型,范围从基于物理的模型,经验模型和概念模型都在使用中。这些包括水文建模系统(HEC-HMS),土壤水评估工具(SWAT),MIKE-SHE,人工神经网络(ANN)。鉴于此,进行了一项研究以评估马来西亚使用的水文模型,确定主要河流流域水文模型的覆盖率,并识别使用的方法(特别是模型性能和评估)。审查结果表明,65%的研究进行了使用的基于物理模型,37%使用经验模型,而6%使用概念模型。在65%的物理建模研究中,60%利用HEC-HMS开源模型,20%二手SWAT(公共领域模型),9%使用MIKE-SHE,MIKE 11和MIKE 22,Infoworks Rs占用7%而Trex和Ifas占用2%。因此,表明在马来西亚的开放访问模型的偏好。在实证模型的情况下,马来西亚的实证研究总研究46%,使用了13%的使用逻辑回归(LR),而模糊逻辑,单位水文,自动回归综合移动平均(ARIMA)模型和支持向量机(SVM)每人贡献8%。然而,剩余比例由数值天气预报(NWP),陆地表面模型(LSM),频率比(FR),决策树(DT)和证据重量(WOE)占据。除了在没有规定特定方法的情况下,除了评估水文模型性能(R,R _(2),NSE,RMSE,MAE等)的一种或多种统计措施使用一种或多种统计措施。在本研究中审查的70篇论文中,16篇未指定它们用于评估他们的研究的模型评估标准的类型,17只使用一种方法,而37使用两种或更多种方法。有27%的NSE被发现是使用最广泛使用的评估模型性能的方法; R和RMSE排名第二,每个百分比每人24%。 R _(2)(20%)被记录为马来西亚的第三次广泛使用的模型评估标准,Mae排名第四是16%,而PBIA最少,占11%。这项工作的调查结果将作为建模者的指南在识别他们需要应用于特定问题的水文模型的类型。它同样有助于水资源管理人员和决策者为他们提供水文研究的执行摘要,并且需要更多的投入来实现可持续发展。

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