Artificial intelligence modelling integrated with Singular Spectral analysis and Seasonal-Trend decomposition using Loess approaches for streamflow predictions

H Apaydin, MT Sattari, K Falsafian, R Prasad - Journal of Hydrology, 2021‏ - Elsevier
The nature of streamflow in the basins is stochastic and complex making it difficult to make
an accurate prediction about the future river flows. Recently, artificial neural-based deep …

Simulating California reservoir operation using the classification and regression‐tree algorithm combined with a shuffled cross‐validation scheme

T Yang, X Gao, S Sorooshian… - Water Resources Research, 2016‏ - Wiley Online Library
The controlled outflows from a reservoir or dam are highly dependent on the decisions made
by the reservoir operators, instead of a natural hydrological process. Difference exists …

A multivariate streamflow forecasting model by integrating improved complete ensemble empirical mode decomposition with additive noise, sample entropy, Gini …

H Apaydin, M Sibtain - Journal of Hydrology, 2021‏ - Elsevier
Accurate and reliable streamflow forecasting is indispensable to deal with the dynamics of
streamflow parameters and for optimal use of water resources, flood, and drought control. In …

Simulating hydropower discharge using multiple decision tree methods and a dynamical model merging technique

T Yang, X Liu, L Wang, P Bai, J Li - Journal of Water Resources …, 2020‏ - ascelibrary.org
Hydropower release decision making relies on multisource information, such as climate
conditions, downstream water quality, inflow and storage, regulation and engineering …

Estimation of sodium adsorption ratio in a river with kernel-based and decision-tree models

MT Sattari, H Feizi, MS Colak, A Ozturk… - Environmental …, 2020‏ - Springer
The control of surface water quality plays an important role in the management of water
resources. In this context, the estimation and assessment of sodium adsorption ratio (SAR) …

Evaluation of feature selection methods in estimation of precipitation based on deep learning artificial neural networks

MT Sattari, A Avram, H Apaydin, O Matei - Water Resources Management, 2023‏ - Springer
Precipitation is the most important element of the water cycle and an indispensable element
of water resources management. This paper's aim is to model the monthly precipitation in 8 …

Using the hybrid simulated annealing-M5 tree algorithms to extract the if-then operation rules in a single reservoir

N Rouzegari, Y Hassanzadeh, MT Sattari - Water Resources Management, 2019‏ - Springer
The environmental water demand of the Mahabad River in the Urmia Lake basin in Iran was
first estimated, using the flow duration curve shifting method (FDC Shifting) in this study …

[PDF][PDF] Comparison of decision tree based rainfall prediction model with data driven model considering climatic variables

N Ramsundram, S Sathya… - … and Drainage Systems …, 2016‏ - pdfs.semanticscholar.org
In hydrological cycle, precipitation initiates the flow and governs the system. The
preciseness in the prediction of rainfall will reduce the uncertainty involved in estimating the …

Investigating the effect of managing scenarios of flow reduction and increasing irrigation water demand on water resources allocation using system dynamics (case …

MT Sattari, R Mirabbasi, H Dolati, FS Sureh… - … Ziraat Fakültesi Dergisi, 2020‏ - dergipark.org.tr
Meeting the healthy nutrition needs of the increasing population in the arid and semi-arid
climates of the different regions of the world such as Iran has become very important for the …

Variation of total suspended solids versus turbidity and Secchi disk depth in the Borçka Dam Reservoir, Çoruh River Basin, Turkey

A Bayram, M Kenanoğlu - Lake and reservoir management, 2016‏ - Taylor & Francis
Bayram A, Kenanoğlu M. 2016. Variation of total suspended solids versus turbidity and
Secchi disk depth in the Borçka Dam Reservoir, Çoruh River Basin, Turkey. Lake Reserv …