Behnoush Farrokhzadeh; Sepideh Choobeh; Hamid Nouri; Massoud Goodarzi
Abstract
In addition to climate change, the land use changes as an ancillary factor affects flooding. Thus evaluation of impacts of climate change and land use change (together) on flood situation in the coming decades will open a new way to deal with this phenomenon. In this research, to study the effects of ...
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In addition to climate change, the land use changes as an ancillary factor affects flooding. Thus evaluation of impacts of climate change and land use change (together) on flood situation in the coming decades will open a new way to deal with this phenomenon. In this research, to study the effects of climate change on 2020s in Balighloo Chai Watershed, HadCM3 under A2 and B1 senarios was downscaled with LARS-WG. Results showed an increase between 8.78 to 12.86 percent in average of annual rainfall in 2020s. Average annual temperture increases 0.66 °C in 2020s. After examining past hanges in land use, two scenarios were developed to predict the impact of land use changes on the runoff in the coming decades: the first scenario assumes a constant in current land use and the second scenario assumes continuation of changes rate during past decades in the future. Results showed a decrease between nine percent in rangelands and five percent increase in agricultural lands area respectively in 2020s. In order to simulate the hydrologic system in the coming decades, HEC-HMS model was calibrated and validated using data of past period, and was used with new curve number, impersive area and hytograph estimated for the future decades. Then the coming decades predicted hydrographs were compared to the past ones. Results showed an increase in peak flow and flood volume in April while they will decrease in March, May and June. If land use change occures with climate change, this increase will be intensified.
Mehdi Sepehri; Seyyed Abbas Atapourfard; Alireza Ildoromi; Hamid Nori; Saba Goodarz; Mohammadmehdi Artimani; Morteza Solgi
Abstract
Peak flow estimation is one of the major issues in water resources and flood management that have basic role in the design of hydraulic structures and biomechanics activities in basins. So that a proper assessment has a basic role in the success of administrative works. In this paper, using artificial ...
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Peak flow estimation is one of the major issues in water resources and flood management that have basic role in the design of hydraulic structures and biomechanics activities in basins. So that a proper assessment has a basic role in the success of administrative works. In this paper, using artificial intelligence methods (MLP Neural Network, the mixture of SOFM with MLP, the mixture of FCM with ANFIS) to estimate Yalfan River’s peak discharge in hydrometer local station. For these models, eight variables have been considered as the inputs that includes rainfall amount in the occurrence time of flood, rainfall of five days ago from occurrence of flood, curve number of the basin (CN), basic discharge and finally peak discharge are considered as the output. In the artificial intelligences after preprocessing of the data, the optimal structure of the models are determined with input and output data, evaluation criteria and trial and error. At the end, the MLP model had better performance compared to ANFIS+FCM, MLP+SOFM, GRNN models.
