Hydrological modeling using a geographic information system (GIS) with a SWAT model in the range of Alvand mountain basin.

Hydrological modeling using a geographic information system (GIS) with a SWAT model in the range of Alvand mountain basin.


Hydrological modeling using a geographic information system (GIS) with a SWAT model in the range of Alvand mountain basin.

نوع: Type: thesis

مقطع: Segment: masters

عنوان: Title: Hydrological modeling using a geographic information system (GIS) with a SWAT model in the range of Alvand mountain basin.

ارائه دهنده: Provider: Alireza Samavati

اساتید راهنما: Supervisors: Yosef Rezai (Ph. D) - Morteza Heidarimozaffar (Ph. D)

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees:

زمان و تاریخ ارائه: Time and date of presentation: January، 04، 2021

مکان ارائه: Place of presentation:

چکیده: Abstract: In Iran, most catchments, especially mountainous and impassable catchments, do not have enough hydrological measuring stations. Also, some stations do not have statistics for a long time. Adequate hydrological data play an important role in the modeling of basins that combine different hydrological processes. The application of conceptual and mathematical hydrological models, as a tool to assess the response of the basin to hydrological loading, requires calibration of the model or, in other words, estimation of model parameters with the aim of maximizing the results of the model with observational values. With the increase in the number of parameters in automated calibration and validation methods, a systematic search in the multidimensional parameter space becomes important. In this dissertation, the automatic calibration of SWAT hydrological model in Alvand mountain basin using SUFI2 algorithm is considered and the results of daily runoff estimation are analyzed by monthly and compared with each other. In this study, the 2012 version of the SWAT model was used to predict runoff and for calibration and validation, the SWAT-CUP software package version 2019 was used. In the study area, data from two synoptic stations and three hydrometric stations were used. In Hamedan station, data from radiation, precipitation, humidity, wind, temperature and Tuyserkan station also used data from precipitation, humidity, wind, temperature (where radiation measuring devices were available only in Hamedan synoptic station) on a daily basis from 2003 to 2017. In the SWAT model, the data must be introduced to the model on a regular basis. Four hydrometric stations were simulated for runoff. The first reason that increased the accuracy of the model was the heating of the model. The heating period is very important in hydrological simulations. Due to the fact that the model was simulated several times and with one-year and two-year warm-up periods, it was observed that the runoff simulation of the early years is very different from the runoff of the observational data. For this reason, the accuracy coefficient of the final simulation results was shown to be unacceptable. After initial modeling and with heating period of 3, 4 and 5 years, it was observed that the accuracy coefficient is increasing. There was no difference in the simulation results for more than 6 years, so the model heating period for the parameters from 2003 to 2008 was considered to be six years. The degree of correlation coefficient and Nash Sutcliffe coefficient in Salehabad station was 0.2 and in other stations it was 0.15 and in simulation and calibration, satisfactory results were obtained. In the second case, due to the fact that in the initial modeling, the peak flow rate was calculated much less than the actual predicted values, so changes in rainfall and temperature values to altitude were applied in the model. This change was made by the height ranges in the model. To do this, in five sub-basins in which there was a large difference in altitude, temperature and precipitation changes in relation to altitude were considered equal to 6 (C / Km) and 1 (mm / Km), respectively. In the final results, the peak discharge rate is less different from the observed peak discharge and also brought the Nash Sutcliffe coefficient closer to one. In the third case, considering that the studied basin is a mountainous basin, after successive simulations and low accuracy coefficient, the input parameters for each sub-basin were considered separately. Therefore, 74 sub-basins were obtained for the use of the studied lands. Similar sub-basins are located in the same class and for optimal sub-basins in land use, the number of which has reached 12 similar sub-basins, which is considered the optimal value. In the case of 74 soil map sub-basins, the number of sub-basins similar to the soil map was separated and the parameters were calibrated again. Calibration of daily discharge results Nash Sutcliffe coefficient for four stations was more than 0.4 and for calibration of monthly discharge results was more than 0.5. In the end, the final results of the model were good and satisfactory. In the second part of the simulation using the LARS-WG6 model, the rainfall and temperature of the stations from 2021 to 2040 were simulated using 9 sensors. Using simulated precipitation and temperature data and calibrated parameters in the past, future runoff was simulated. The miroc2 was more accurate in simulating precipitation and temperature than other sensors. Also, for runoff simulation, miroc2 had less changes than other other measures. The results of surface runoff changes with miroc2 sensor showed that in the average monthly runoff from 2021 to 2040 in Salehabad station -11.65% and in Maryanaj station, TaghsimAb and DareMoradbeig -5.56, -12.69, respectively. And decreases by -6.55%. In addition, other sensors simulated surface runoff less than previous runoff. According to the result of this scenario, Alvand mountain basin in the coming period, will face the problem of reduced rainfall, increased temperature and consequently reduced surface runoff. Key Words: Alvand mountain basin, Hydrological modeling SWAT, Calibration and Validation, SUFI2 algorithm

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