Saeideh Khaloei; Shahram Khalighisigaroodi; khaled ahmadauli; arash malekian
Abstract
Recently, the effects of climate change on the hydrological cycle and regime have become an important research topic. The results of atmospheric general circulation models (GCMs) together with hydrological models are used to determine the impacts of climate change on hydrologic regime. The daily minimum ...
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Recently, the effects of climate change on the hydrological cycle and regime have become an important research topic. The results of atmospheric general circulation models (GCMs) together with hydrological models are used to determine the impacts of climate change on hydrologic regime. The daily minimum and maximum temperatures, rainfall and sunshine hours of the Shiraz synoptic station were simulated using the LARSE_WG6.0 statistical model. The efficiency of the model for simulating climate variables was determined using historical data of Shiraz station. To investigate climate change on runoff, two scenarios of the HadGEM2-ES model for two periods were downscaled using the LARSE_WG model. In the next step, runoff was simulated using the SWMM model and its results were compared with the measured runoff. For this purpose, 2 events were used for calibration and one event for validation. Based on coefficient correlation (R), root mean square error (RMSE) and Nash-Sutcliffe efficiency (NSE), the model has a suitable efficiency for simulating runoff. Then, LARSE_WG downscaled data were used in SWMM model and the runoff changes in future periods compared to present. According to RCP4.5 and RCP8.5 climate scenarios, precipitation will increase from 16.10 to 8.88% in 2021-2040 and 14.49% and 19.73% in 2061-2080. Therefore, assuming no change in landuse in Shiraz district 8, the volume of runoff will increase from 13.35 to 21.48 percent.
Hossein Emami; Ali Salajegh; Alireza Moghaddamnia; Shahram Khalighi; Abolhassan Fathbabadi
Abstract
Precipitation is of the most important inputs of runoff modeling. The availability of precipitation data with appropriate temporal and spatial accuracy is very important and necessary for watersheds with small and scattered rainfall stations. Nowadays, climatic satellites are practical and widely-used ...
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Precipitation is of the most important inputs of runoff modeling. The availability of precipitation data with appropriate temporal and spatial accuracy is very important and necessary for watersheds with small and scattered rainfall stations. Nowadays, climatic satellites are practical and widely-used tools in precipitation estimations. In this study, first the efficiency of TRMM satellite precipitation data in the monthly time series of Chehelchai Watershed was evaluated using R2, RMSE, NSE and Bias statistical indices by comparing the precipitation data of rain gauge stations (observed) and the values of these statistical indices were 0.54, 22.70, 0.44 and -14.86, respectively. Considering the value of the coefficient of determination (R2), it can be concluded that the TRMM satellite was able to estimate the 0.54 of observed precipitation. In the next step, three base data models including MLP, ANFIS and SVR were used to estimate the monthly runoff. Two different input scenarios were selected :1) observed precipitation data in t and t-1 time steps and runoff in t-1 time step and 2) satellite precipitation data in t and t-1 time steps and runoff in t-1 time step. To compare the accuracy and error of the models, R2 and RMSE of the validation stage were used. The ANFIS model with the values of R2 and RMSE were 0.80 and 0.97 for the first type input combination and 0.78 and 1.02 for the second type input combination, respectively, as the suitable single model for estimating runoff in the study area were selected. Then weighted-mean method was used in the data fusion approach to provide a data driven combination model for each combination of inputs into the model in the studied watershed. This data fusion approach data-driven model improved the values (R2=0.81) and (Bias=-4.85) for the first type input combination and also improved the value (R2=0.79) for the second type input combination.
Ali Akbar Nazari Samani; Shahram Khalighi Sigaroodi; MAHSA abdolshahnejad; Sina Syadi Lotf Abadi; Majid Habibi Nokhandan
Abstract
Greenhouse gases have continued to increase in the atmosphere. This is largely due to industrial activities. The warming effect of greenhouse gas, increased over the last 200 years, due to carbon dioxide; hence the temperature of the lower levels of atmosphere will be increased. The climate change across ...
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Greenhouse gases have continued to increase in the atmosphere. This is largely due to industrial activities. The warming effect of greenhouse gas, increased over the last 200 years, due to carbon dioxide; hence the temperature of the lower levels of atmosphere will be increased. The climate change across the world resulted in an increased drought; disturbance in rainfall as well as desertification. Desertification has been caused by a variety of factors such as climate change. It is a significant natural resources problem. The aim of this study was to evaluate the desertification during five periods (1978-1987, 1978-2007, 2012-2041, 2042-2071, and 2072-2101) during the last, present, and future, using IMDPA model as well as climate and geology-geomorphology criteria. For each criterion, some indexes were selected, using area condition. First, air temperature and precipitation during the previous time was evaluated. Then, the climate change was estimated using two climatic models of HADCM3 and GFDL2.1 and three scenarios of A2, B1 and A1B of GCM as well as small scale exponentially. The land use map for four classes in two periods (1986 and 2010) was prepared and used for input data to the Markov chain for estimating future land changes through the three periods (1419, 1449, and 1479). Results were used as the land use index for working unit in geology-geomorphology criterion. It was assumed that the tolerance of stone to the erosion and slope of maps were constants. Hence, this criterion was studied during five periods. Results showed that the intensity of desertification was increased during the time.
Mohammad Rostami Khalaj; Ali Salajeghe
Abstract
Rainfall-runoff modeling is on of runoff estimation techniques and an appropriate tool for studying hydrological processes, water resources evaluation and watershed management. But the complexity and the non-linear nature of rainfall-runoff process and not being known factors affecting it and generally ...
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Rainfall-runoff modeling is on of runoff estimation techniques and an appropriate tool for studying hydrological processes, water resources evaluation and watershed management. But the complexity and the non-linear nature of rainfall-runoff process and not being known factors affecting it and generally on discharge at watershed outlet, modeling has become more difficult. Therefore, using the methods that have additionally dynamic, development capability, conceptual structure and user friendly is essential. Therefore, in this study for rainfall-runoff modeling were used system dynamics methods in the Kardeh dam basin of Mashhad. The proposed model includes 6 reservoir including snow storage, canopy storage, impervious storage, surface soil storage, subsurface storage and groundwater storage. The input data required includes average daily precipitation and temperature. To calibrate the model daily discharge data from basin outlet in the period from 1998 to 2008 and for evaluation the discharge from 2009 to 2012 were used. The results of sensitivity analysis showed temperature parameters are more sensitive and have considerable impact on discharge and peak flow. Also the results indicate that the simulated stream flow pattern is quite similar to that observed and Nash-Sutcliffe coefficient obtained in the evaluation period between 0.57-0.67 which represents that the system dynamics methods is high ability to rainfall-runoff modeling.
