Civil Engineering / İnşaat Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/13

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Author: search.filters.author.Tayfur, GökmenSubject: search.filters.subject.Simulation

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  • Book Part
    Numerical Modeling of Transport Processes at Hillslope Scale Accounting for Local Physical Features
    (Nova Science Publishers, Inc., 2011) Tayfur, Gökmen
    Hillslope is the basic unit of a watershed. Typical hillslopes may have a size of 1000 m long and 500 m wide. For watershed modeling, it is essential to accurately describe the illslope-scale processes of flow, erosion and sediment transport, and solute transport. Although these processes are usually considered in experimental studies and theoretical subjects, the existing numerical models that are designed to simulate transport processes at hillslope scale rarely take microtopographic variations into account. Instead, those models assume constant slope, roughness, and infiltration rate for a given basic computational unit (i.e., hillslope). As a result, effects of microtopographic features (e.g., rills) on the aforementioned processes cannot be reflected in modeling results. However, the effects could be important because rill and sheet flows exhibit distinctly different dynamics that influence the transport processes. The objective of this chapter is to review the numerical studies for investigating the transport processes at hillslope scale. The chapter focuses particularly on the modeling efforts with the effects of microtopographic features on the dynamics of the transport processes incorporated.
  • Article
    Citation - WoS: 103
    Citation - Scopus: 126
    Ann and Fuzzy Logic Models for Simulating Event-Based Rainfall-Runoff
    (American Society of Civil Engineers (ASCE), 2006) Tayfur, Gökmen; Singh, Vijay P.
    This study presents the development of artificial neural network (ANN) and fuzzy logic (FL) models for predicting event-based rainfall runoff and tests these models against the kinematic wave approximation (KWA). A three-layer feed-forward ANN was developed using the sigmoid function and the backpropagation algorithm. The FL model was developed employing the triangular fuzzy membership functions for the input and output variables. The fuzzy rules were inferred from the measured data. The measured event based rainfall-runoff peak discharge data from laboratory flume and experimental plots were satisfactorily predicted by the ANN, FL, and KWA models. Similarly, all the three models satisfactorily simulated event-based rainfall-runoff hydrographs from experimental plots with comparable error measures. ANN and FL models also satisfactorily simulated a measured hydrograph from a small watershed 8.44 km2 in area. The results provide insights into the adequacy of ANN and FL methods as well as their competitiveness against the KWA for simulating event-based rainfall-runoff processes.