Performance Comparison of the Neural Networks CANFIS, MLP and Optimized MLP using Genetic Programming for Suspended Sediment Load Simulation (Case study: Zoshk-Abardeh Watershed, Shandiz, Iran)

Tajbakhsh, Seyed Mohammad; Memarian, Hadi; Mohammadi, Fatemeh

doi:10.29252/jwmr.9.17.119

jwmr

2018

DOI: 10.29252/jwmr.9.17.119

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Performance Comparison of the Neural Networks CANFIS, MLP and Optimized MLP using Genetic Programming for Suspended Sediment Load Simulation (Case study: Zoshk-Abardeh Watershed, Shandiz, Iran)

Seyed Mohammad Tajbakhsh¹,

Hadi Memarian²,

Fatemeh Mohammadi³

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2024

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Hydrological simulation and evaluation of drought conditions in the ungauged watershed Parishan lake Iran, using the SWAT model

Ansarifard,

Ghorbanifard,

Boustani

et al. 2024

Journal of Water and Climate Change

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ke Parishan has experienced significant water scarcity, leading to its complete disappearance. This study utilized the SWAT model to assess the impact of changes in vegetation, precipitation, temperature, and evaporation on runoff and the lake's surface. Two strategies were employed: analyzing runoff variations based on land use and land cover (LULC) changes and evaluating the effects of precipitation, temperature, and humidity on runoff during the simulation period. A key challenge was the lack of runoff statistics, which was addressed by using data from donor watershed stations and Copernicus satellite information to improving simulation processes and calibration. The findings reveal that environmental changes, particularly land use, have increased evaporation and temperature fluctuations which results in reducing runoff. While Copernicus satellite data proved useful, runoff statistics from the neighboring Chamchit station provided more accurate simulations. The study finding suggests that the LULC strategy is an effective management approach, as in this case Parishan Lake's historical conditions with less urbanization and agriculture correlated with higher runoff and lake levels. Finally, meteorological and hydrometric drought and its impact on lake area changes were measured to reach a more comprehensive conclusion.

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Hydrological simulation and evaluation of drought conditions in the ungauged watershed Parishan lake Iran, using the SWAT model

Ansarifard,

Ghorbanifard,

Boustani

et al. 2024

Journal of Water and Climate Change

View full text Add to dashboard Cite

show abstract

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Performance Comparison of the Neural Networks CANFIS, MLP and Optimized MLP using Genetic Programming for Suspended Sediment Load Simulation (Case study: Zoshk-Abardeh Watershed, Shandiz, Iran)

Cited by 1 publication

References 22 publications

Hydrological simulation and evaluation of drought conditions in the ungauged watershed Parishan lake Iran, using the SWAT model

Hydrological simulation and evaluation of drought conditions in the ungauged watershed Parishan lake Iran, using the SWAT model

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