Studying the Changes in the Hydro-Meteorological Components of Water Budget in Lake Urmia

Loading...
Publication Logo

Date

2022

Authors

Babak Vaheddoost
Farshad Fathian
Enes Gul
Mir Jafar Sadegh Safari

Journal Title

Journal ISSN

Volume Title

Publisher

John Wiley and Sons Inc

Open Access Color

Green Open Access

No

OpenAIRE Downloads

OpenAIRE Views

Publicly Funded

No
Impulse
Top 10%
Influence
Average
Popularity
Top 10%

Research Projects

Journal Issue

Abstract

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 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.

Description

Keywords

Conceptual 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 Urmia, 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 Urmia, Conceptual Water Budget, Lake Urmia, Depth Difference, Symbolic Regression, Stochastic Model, Dynamic Regression, conceptual water budget, dynamic regression, Lake Urmia, depth difference, symbolic regression, stochastic model

Fields of Science

01 natural sciences, 0105 earth and related environmental sciences

Citation

WoS Q

Scopus Q

OpenCitations Logo
OpenCitations Citation Count
9

Source

Water Resources Research

Volume

58

Issue

7

Start Page

End Page

PlumX Metrics
Citations

CrossRef : 4

Scopus : 11

Captures

Mendeley Readers : 15

Google Scholar Logo
Google Scholar™
OpenAlex Logo
OpenAlex FWCI
1.8762

Sustainable Development Goals