نتایج جستجو برای: hms hydrologic engineering center

تعداد نتایج: 541661  

2012
A. Majidi K. Shahedi

Estimation of surface runoff in a watershed based on the rate of received precipitation and quantifying discharge at outlet is important in hydrologic studies. In this study, HEC-HMS hydrological model version 3.4 was used to simulate rainfall-runoff process in Abnama watershed located in south of Iran. To compute infiltration, rainfall excess conversion to runoff and flow routing, methods like...

Journal: :Land 2023

This study was part of a project designed to simulate the long-term landform equilibrium rehabilitated mine site. The utilized event Fine Suspended Sediment (FSS) fluxes in receiving stream following rainfall as an indicator stability. aim this use HEC-HMS determine sediment and discharge quantity upstream how it affects downstream development catchment landform, terms changes geomorphology. Th...

Journal: :Geomatics, Natural Hazards and Risk 2022

With advancements in computational technology, data assimilation techniques, high-resolution remote sensing, and complex climate models, numerous precipitation products are available with different spatiotemporal resolutions; however, their evaluation, especially the Himalayan region, is unexplored. Therefore, this study attempts to assess four sources (gridded observation dataset, reanalysis, ...

2014
Catalina Segura Peter Caldwell Ge Sun Steve McNulty Yang Zhang

Catalina Segura,* Peter Caldwell, Ge Sun, Steve McNulty and Yang Zhang 1 Marine, Earth, and Atmospheric Sciences Department, North Carolina State University, 2800 Faucette Drive, Raleigh, NC 27695-8208, USA 2 Forestry Engineering, Resources, and Management Department, Oregon State University, 280 Peavy Hall, Corvallis, OR 97331, USA 3 Center for Forest Watershed Science, USDA Forest Service, Co...

Journal: :Hydrology 2022

Post-disaster flood risk assessment is extremely difficult owing to the great uncertainties involved in all parts of exercise, e.g., uncertainty hydrologic–hydraulic models and depth–damage curves. In present study, a robust fast data-driven tool for residential introduced. The proposed can be used by scientists, practitioners and/or stakeholders as first step better understanding quantifying m...

Journal: :Journal of forest science 2021

Simulation of the runoff-rainfall process in forest lands is essential for land management. In this research, a hydrologic modelling system (HEC-HMS) and artificial neural network (ANN) were applied to simulate rainfall-runoff (RRP) Kasilian watershed with an area 68 square kilometres. The HMS model was performed using secondary data rainfall discharge at climatology hydrometric stations, Soil ...

Journal: :Applied Mathematics and Computer Science 2015
Maciej Smolka Robert Schaefer Maciej Paszynski David Pardo Julen Álvarez-Aramberri

The paper discusses the complex, agent-oriented hierarchic memetic strategy (HMS) dedicated to solving inverse parametric problems. The strategy goes beyond the idea of two-phase global optimization algorithms. The global search performed by a tree of dependent demes is dynamically alternated with local, steepest descent searches. The strategy offers exceptionally low computational costs, mainl...

Journal: :GeoScience Engineering 2021

Changing of precipitation regime and intensification extreme storms in semi-arid regions because climate change requires the use numerical models to forecast outlet hydrographs. In this paper, HEC-HMS software was applied using a loss method curve number CN estimate excess parametric unit hydrograph model compute transformation into direct runoff over watershed. The Muskingum-Cunge routing used...

2016
Bakinam T. Essawy Jonathan L. Goodall Hao Xu Yolanda Gill

Evaluation of the OntoSoft Ontology for Describing Metadata for Legacy 1 Hydrologic Modeling Software 2 Bakinam T. Essawy , Jonathan L. Goodall , Hao Xu, and Yolanda Gill 3 a Department of Civil and Environmental Engineering, University of Virginia, 351 McCormick 4 Road, PO Box 400742, Charlottesville, VA, 22908, USA 5 b Data Intensive Cyber Environment Center, University of North Carolina, Cha...

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