Yazar "Fathian, Farshad" seçeneğine göre listele

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    Assessment of water demand reliability using SWAT and RIBASIM models with respect to climate change and operational water projects
    (Elsevier, 2022) Fathian, Farshad; Ahmadzadeh, Hojat; Mansouri, Bahareh; Vaheddoost, Babak
    Reliability assessment in the allocation of water resources under the changing climate condition has invaluable importance in planning the water demand at the basin scale. This study details an integrated framework for evaluation of the reliability between water supply and demand under climate change scenarios in the Zarrineh Rood River basin in the northwest of Iran. Initially, recorded climatic data in six synoptic stations are downscaled and projected for the period 2020-2040 based on the 14 GCMs using the LARS-WG method. Afterwards, the SWAT model is used to simulate the basin hydrology with consideration to the baseline and future climate periods at six hydrometric stations. Finally, the available water is allocated using the RIBASIM model based on the current supply-demand chain and predefined governmental water allocation rules for different sectors. Results showed that under climate change, the total runoff of the basin and the entrance catchments to the Zarrineh Rood River dam would decrease about 8% and 28%, respectively. The reliability of the water supply for joint drinkingindustrial and agricultural demands would also decrease from 96.4% to 93.4%, and 90.2-89.5%, respectively. As such, the average annual streamflow from the Zarrineh Rood River ending to Lake Urmia will reduce by 10% if the operational water projects remain active.
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    Exploring Teleconnection-Drought Relationship in Iran Through Dynamic Conditional Correlation and Cluster Analysis
    (Wiley, 2025) Fathian, Farshad; Dehghan, Zohreh; Vaheddoost, Babak; Ongoma, Victor
    An increase in drought frequency and intensity in most parts of the world is a threat to lives and property. Understanding the underlying climatic drivers of drought occurrence and variability is therefore vital for developing effective early warning systems. Large-scale climate variability patterns, commonly referred to as teleconnections, exert significant influence on regional precipitation and drought dynamics. This study explores the relationship between major teleconnections: Southern Oscillation Index (SOI), North Atlantic Oscillation (NAO), and Multivariate El Ni & ntilde;o-Southern Oscillation Index (MEI), and drought in Iran by applying the dynamical conditional correlation (DCC) approach together with cluster analysis to capture regional differences. Monthly precipitation data from 1993 to 2016, sourced from 106 meteorological stations, are used to calculate the standardised precipitation index (SPI) with 1-, 3-, 6-, 9-, and 12-month moving averages. The DCC between SPIs and three teleconnections is then analysed and clustered using the Ward's method. Results demonstrate that the MEI and SOI exhibit a strong correlation with the SPIs, while NAO shows an insignificant association with drought patterns in the region. The influence of teleconnections on SPIs exhibited correlations reaching up to +/- 0.6, reflecting the coherence and density of SPI patterns and the distinct spatial clustering of meteorological stations, with this range varying notably based on terrain complexity and elevation. The strength of teleconnection-SPI relationships appears to be modulated by topographic features, time lag, and shocks, which likely play a crucial role in shaping precipitation dynamics and the spatial distribution of droughts in Iran. The findings underscore the importance of incorporating terrain and elevation when analysing large-scale climatic patterns and their influence on regional climate variability for improved accuracy of weather forecasts of extreme events.
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    Modeling the volatility changes in Lake Urmia water level time series
    (Springer Wien, 2021) Fathian, Farshad; Vaheddoost, Babak
    The decline in Lake Urmia (LU) water level during the past two decades has been addressed by several studies. However, the conducted studies could not come across a practical solution by considering the sample mean in the lake water level time series. For this, the present study suggests a fresh look to the lake water level decline in LU by addressing the volatility changes instead. The Bayesian change-point detection method was used to define the major and critical change points during the study period from January 1966 to December 2016 on a daily scale. Results indicated that major changes occurred in early 2000, and the time series can be studied under the pre- and post-change point events. Afterward, several methods namely shift-track and mono- and multiple-trend line analyses were used to remove the trends associated with the lake water level time series. The de-trending approaches later were applied separately for the entire study period, before 2000 (i.e., 1966-1999) and afterward (i.e., 2000-2016). Then, the de-trended time series were used, and a generalized autoregressive conditional heteroscedasticity (GARCH) model was fitted to the de-trended time series to predict the volatility changes in the data run. Results indicated to descending and ascending changes, respectively, in short- and long-term persistence after 2000. The GARCH(1,1) model was found to be satisfactory to interpret the pre- and post-turn point events, while the changes in short- and the long-term persistence were calculated as 0.53 to 0.75 and 0.46 to 0.24, respectively. In addition, by considering the lake water level anomaly and coefficient of variation in LU and two neighboring cases of Lake Sevan and Lake Van, it is concluded that the changes are exclusive to LU, and the rate of changes was accelerated after 2006.
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    Regional classification of extreme droughts across Iran
    (Springer Science and Business Media Deutschland GmbH, 2024) Fathian, Farshad; Dehghan, Zohreh; Alee, Mohammed Mustafa; Vaheddoost, Babak; Abualigah, Laith Mohammad Qasim; Danandeh Mehr, Ali
    In arid and semi-arid regions like Iran, sustainable urban and agricultural development is intimately intertwined with the severity, frequency, and duration of meteorological droughts. Prolonged meteorological droughts can trigger hydrological and socio-economic droughts, posing significant challenges to the region’s sustainability. Therefore, the primary objective of this study is to perform a comprehensive Regional Frequency Analysis (RFA) for extreme meteorological drought events across Iran. To this end, we meticulously calculated the severity, duration, and magnitude of the Standardized Precipitation Index (SPI) over the 3-, 6-, 9-, and 12-month accumulation periods. The data was derived from monthly precipitation records collected at 106 meteorological stations during the period spanning 1993–2016. Subsequently, we employed a rigorous approach, utilizing Ward’s clustering analysis and the test for heterogeneity using L-moment, to effectively classify and categorize the extreme drought characteristics prevalent across the country. The analysis revealed that the generalized Pareto and Pearson type 3 models are the most suitable distribution functions for RFA across almost all the examined clusters. Additionally, the spatiotemporal analysis of the SPI series at various time scales indicated that the extreme events’ characteristics, such as severity, duration, and magnitude, remain surprisingly unaffected by the local climate conditions. The results also showed that even in the typically humid regions located in the north, west, and northwest of Iran, areas that receive considerable annual precipitation, severe droughts can still occur. These droughts primarily stem from temporal events rather than being solely dependent on the local climate conditions. Therefore, the study concludes that the drought events can largely be attributed to mismanagement and inadequate regional water allocation. Moreover, these situations might have been further exacerbated by the occurrence of extreme climatic conditions. © The Author(s) under exclusive licence to Institute of Geophysics, Polish Academy of Sciences & Polish Academy of Sciences 2023.
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    Studying the Changes in the Hydro-Meteorological Components of Water Budget in Lake Urmia
    (Amer Geophysical Union, 2022) Vaheddoost, Babak; Fathian, Farshad; Gul, Enes; Safari, Mir Jafar Sadegh
    Abrupt changes in the Lake Urmia water level have been addressed in many studies, and yet the link between the water level decline and hydro-meteorological variables in the basin is a major topic for debate between researchers. In this study, a set of data-driven techniques is used to investigate the components of the water budget in Lake Urmia. Then, the rate of monthly depth differences (DD), precipitation (P), evaporation (E), potential groundwater head (G), and streamflow (Q) time series between 1974 and 2014 are used in the analysis. Several scenarios and strategies are developed by considering the major changes in the year-2000, which is believed to be the initiation of the hydrological encroachment in the basin. Simple water budget (WB), dynamic regression (DR), and symbolic regression (SR) techniques are used to simulate the DD with consideration to P, E, G, and Q. Alternatively, the effect of the year 1997 as the potential base-line for the initiation of significant meteorological trends in the basin is investigated. Conducted analysis showed that the DR models of an autoregressive moving average together with multiple exogenous inputs provide an approximate R-2: 0.7 as the best alternative among the selected models. It is shown that the Q and G depict abrupt changes compared to the P and E, while either the year 1997 (climate effect) or the year 2000 (encroachment effect) is considered as the baseline in the study.