Predicting Sediment Load Using Stochastic Model and Rating Curves in a Hydrological Station-Reference-Cited by-同舟云学术

Predicting Sediment Load Using Stochastic Model and Rating Curves in a Hydrological Station

Published:2020-08 Issue:8 Volume:25 Page:05020017
ISSN:1084-0699
Container-title:Journal of Hydrologic Engineering
language:en
Short-container-title:J. Hydrol. Eng.

Author:

Azadi Saeed¹,Nozari Hamed²^ORCID,Godarzi Ehsan³

Affiliation:

1. Ph.D. Student, Dept. of Water Science Engineering, Faculty of Agriculture, Bu-Ali Sina Univ., Hamedan 65174, Iran.

2. Associate Professor, Dept. of Water Science Engineering, Faculty of Agriculture, Bu-Ali Sina Univ., Hamedan 65174, Iran (corresponding author). ORCID: .

3. Lecturer, Dept. of Civil, Construction, and Environmental Engineering, San Diego State Univ., San Diego, CA 92182.

Publisher

American Society of Civil Engineers (ASCE)

Subject

General Environmental Science,Water Science and Technology,Civil and Structural Engineering,Environmental Chemistry

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29HE.1943-5584.0001967

Reference40 articles.

1. Using stochastic models to produce artificial time series and inflow prediction: A case study of Talog dam reservoir, Khuzestan province, Iran;Adeli A.;Bull. Water Resour. Dev. J.,2015

2. Long-Term Trends and Seasonality Detection of the Observed Flow in Yangtze River Using Mann-Kendall and Sen’s Innovative Trend Method

3. A comparison of artificial neural network and sediment rating curves to estimate suspended sediment: A case study of Jarahi River, Khozestan province, Iran;Amiri A.;Int. Bull. Water Resour. Dev. J.,2015

4. Time Series Analysis and Forecasting: Another Look at the Box-Jenkins Approach

5. An Analysis of Transformations

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