Evaluating the effects of climate change on groundwater level in the Varamin plain

Azizi, Hamidreza; Ebrahimi, Hossein; Samani, Hossein Mohammad Vali; Khaki, Vida

doi:10.2166/ws.2021.007

Cited by 10 publications

(3 citation statements)

References 11 publications

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“…The amount and frequency of precipitation in a region play a significant role in affecting groundwater levels. Heavy rainfall enhances groundwater recharge rates, while prolonged dry periods can lead to a decrease in groundwater levels (Jan, Chen and Lo, 2007;Thomas, Behrangi and Famiglietti, 2016;Azizi et al, 2021). In the study area, fluctuations in groundwater levels align with the recorded heavy rainfall at meteorological observation stations, particularly during autumn in Poland, which explains the observed increase in groundwater levels.…”

Section: The Variations Of Groundwater and Surface Water Levelsupporting

confidence: 73%

Interaction of surface water and groundwater in Nida valley, Poland

Phan,

Strużyński,

Kowalik

2024

Journal of Water and Land Development

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The study area of the Nida valley was examined to investigate variations in groundwater and surface water levels, as well as the interaction between them. In the valley, there were three branches. The two actives were the Nida River itself and the Smuga Umianowicka branch while the Stara Nida branch was dry during the measurement session. Over a 12-month period from June 2021 to June 2022, 7 monitoring points were equipped with piezometers, comprising 5 groundwater points and 2 surface water points. The monitoring frequency was set to 30 minutes. The results of this research indicate that there are significant differences in the water level at the same observed point at different times. This study demonstrates seasonal changes in both surface water and groundwater levels with higher levels in autumn and winter and lower levels in spring and summer, which are closely tied to the changes in meteorological conditions during the research period, such as precipitation and air temperature. The study results also indicate that during summer and winter at the Nida River and its riparian area, losing stream is the primary process occurring in the studied reach. Conversely, during autumn and spring, the main process is gaining stream. At the human-maintained Smuga Umianowicka branch and in its riparian area, losing stream is the main process during summer and autumn, and gaining stream is the main process during spring. During winter, losing stream and gaining stream processes can occur simultaneously, and neither process takes place mainly.

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Section: The Variations Of Groundwater and Surface Water Levelsupporting

confidence: 73%

Interaction of surface water and groundwater in Nida valley, Poland

Phan,

Strużyński,

Kowalik

2024

Journal of Water and Land Development

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“…The primary articles used in this study used input data to predict groundwater level changes and address their impact, and our study will look at the climatic data from those studies as well. According to NASA.gov accessed on 9 June 2022 [91], "climate change is a shift in the usual weather found in a place." Groundwater level changes are influenced by climate conditions [92], and climate change is threatening our future.…”

Section: Predictor Variables For Modeling Gwl Changesmentioning

confidence: 99%

Mathematical and Machine Learning Models for Groundwater Level Changes: A Systematic Review and Bibliographic Analysis

et al. 2022

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With the effects of climate change such as increasing heat, higher rainfall, and more recurrent extreme weather events including storms and floods, a unique approach to studying the effects of climatic elements on groundwater level variations is required. These unique approaches will help people make better decisions. Researchers and stakeholders can attain these goals if they become familiar with current machine learning and mathematical model approaches to predicting groundwater level changes. However, descriptions of machine learning and mathematical model approaches for forecasting groundwater level changes are lacking. This study picked 117 papers from the Scopus scholarly database to address this knowledge gap. In a systematic review, the publications were examined using quantitative and qualitative approaches, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was chosen as the reporting format. Machine learning and mathematical model techniques have made significant contributions to predicting groundwater level changes, according to the study. However, the domain is skewed because machine learning has been more popular in recent years, with random forest (RF) methods dominating, followed by the methods of support vector machine (SVM) and artificial neural network (ANN). Machine learning ensembles have also been found to help with aspects of computational complexity, such as performance and training times. Furthermore, compared to mathematical model techniques, machine learning approaches achieve higher accuracies, according to our research. As a result, it is advised that academics employ new machine learning techniques while also considering mathematical model approaches to predicting groundwater level changes.

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“…In this study, the general circulation model (GCM) of the EC-EARTH and the downscaling model of the LARS-WG were applied. The downscaled model showed an increase in temperature up to 1.5 degrees between the future periods of 2020 and 2050 [44]. Azizi (2023) developed a simulationoptimization model in the Varamin aquifer to select a sustainable harvesting plan for this plain.…”

Section: Introductionmentioning

confidence: 99%

Assessing the Impact of Human Activities and Climate Change Effects on Groundwater Quantity and Quality: A Case Study of the Western Varamin Plain, Iran

Asadi,

Zamaniannejatzadeh,

Eilbeigy

2023

Water

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In this paper, the effects of climate change and human activities on the groundwater level and the concentration of pollutants, such as total dissolved solids (TDS), chloride, and sodium, were investigated in the western part of the Varamin Plain. The groundwater flow and pollutant transport were simulated with the two models of MODFLOW and MT3D, respectively. To investigate the impacts of climate change, the two parameters of temperature and precipitation were downscaled under the three scenarios of RCP 2.6, RCP 4.5, and RCP 8.5. Four scenarios, including the current condition (Scenario 0), a 25% increase in the extraction from pumping wells (Scenario 1), the climate change effects (Scenario 2), and an increase in the incoming effluent (TDS) to the Shoor River due to industrial activities (Scenario 3), were investigated for a future period of 30 years (2025–2055). The results show that the highest groundwater decline and chloride and sodium concentrations occur under Scenario 1, while Scenario 3 leads to the maximum TDS concentration (milligrams per liter). In Scenario 1, the average and maximum groundwater decline at the end of the simulation period will be 2.5 m and 7.3 m, and the chloride and sodium concentrations will increase by 7 and 5 milligrams per liter, respectively.

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Evaluating the effects of climate change on groundwater level in the Varamin plain

Cited by 10 publications

References 11 publications

Interaction of surface water and groundwater in Nida valley, Poland

Interaction of surface water and groundwater in Nida valley, Poland

Mathematical and Machine Learning Models for Groundwater Level Changes: A Systematic Review and Bibliographic Analysis

Assessing the Impact of Human Activities and Climate Change Effects on Groundwater Quantity and Quality: A Case Study of the Western Varamin Plain, Iran

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