Babak VaheddoostFarshad FathianEnes GulMir Jafar Sadegh SafariVaheddoost, BabakFathian, FarshadSafari, Mir Jafar SadeghGul, Enes2025-10-06202219447973, 004313970043-13971944-797310.1029/2022WR0320302-s2.0-85134881434https://www.scopus.com/inward/record.uri?eid=2-s2.0-85134881434&doi=10.1029%2F2022WR032030&partnerID=40&md5=9f9481ec1a433b4b96be63a5bcbb0070https://gcris.yasar.edu.tr/handle/123456789/8687https://doi.org/10.1029/2022WR032030Abrupt 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 R2: 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. © 2022 Elsevier B.V. All rights reserved.Englishinfo:eu-repo/semantics/closedAccessConceptual Water Budget, Depth Difference, Dynamic Regression, Lake Urmia, Stochastic Model, Symbolic Regression, Budget Control, Groundwater, Lakes, Regression Analysis, Stochastic Systems, Time Series Analysis, Water Levels, Conceptual Water Budget, Data Driven Technique, Depth Difference, Dynamic Regressions, Groundwater Heads, Lake Urmia, Meteorological Variables, Stochastic-modeling, Symbolic Regression, Water Budget, Stochastic Models, Groundwater, Hydrometeorology, Regression Analysis, Stochasticity, Streamflow, Time Series Analysis, Water Budget, Water Level, Iran, Lake UrmiaBudget control, Groundwater, Lakes, Regression analysis, Stochastic systems, Time series analysis, Water levels, Conceptual water budget, Data driven technique, Depth difference, Dynamic regressions, Groundwater heads, Lake urmia, Meteorological variables, Stochastic-modeling, Symbolic regression, Water budget, Stochastic models, groundwater, hydrometeorology, regression analysis, stochasticity, streamflow, time series analysis, water budget, water level, Iran, Lake UrmiaConceptual Water BudgetLake UrmiaDepth DifferenceSymbolic RegressionStochastic ModelDynamic RegressionArticle