scholarly journals A modified cyanobacteria prediction model based on cellular automata model using N and P concentration reverse data: a case study in Taihu Lake

2022 ◽  
Author(s):  
Fei Zhao ◽  
Sujin Zhang ◽  
Ruonan Chen ◽  
Liyun Xiao ◽  
Guize Luan ◽  
...  
Keyword(s):  
Cellular Automata ◽  
Prediction Model ◽  
Taihu Lake ◽  
Cellular Automata Model ◽  
Model Based ◽  
P Concentration

scholarly journals DEVELOPING A CELLULAR AUTOMATA MODEL FOR SIMULATING RAINFALL-RUNOFF PROCESS (CASE STUDY: BABOL CATCHMENT)

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 697-702
Author(s):  
N. Mahdizadeh Gharakhanlou ◽  
M. S. Mesgari
Keyword(s):  
Cellular Automata ◽  
Flood Management ◽  
Decision Makers ◽  
Second Step ◽  
Management Decision ◽  
Natural Phenomena ◽  
Rainfall Runoff ◽  
Cellular Automata Model ◽  
Ca Model

Abstract. The rainfall-runoff process is one of the central aspects of hydrology. In the rainfall-runoff process, the fast accumulation of rainwater in the catchments and rivers may lead to a flood disaster. To prevent and manage such disasters, it is essential to model and simulate the runoff process. The cellular automata (CA) is a computational model that can represent and simulate complex and dynamic natural phenomena. The main objective of this research is to develop a CA model of the rainfall-runoff process and to use it for simulating and representation of the runoff in the Babol catchment. The study is carried out in two main steps. First, several data manipulation and analyses in ArcGIS 10.3 software are used to prepare the input data of the CA model. In the second step, the CA model is developed and implemented in the NetLogo 6.0.4 platform. The total amount of runoff in each cell during the year 2016 was calculated and presented as the output of the model. A map of the total generated runoff can be an important tool for flood management decision-makers and it can also be used for managing the catchment and assessing the water resources in the study area.

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