Drought occurrence under future climate change scenarios in the Zard River basin, Iran

Mahdavi, Pedram; Kharazi, Hossein Ghorbanizadeh; Eslami, Hossein; Zohrabi, Narges; Razaz, Majid

doi:10.2166/ws.2020.367

Cited by 8 publications

(3 citation statements)

References 32 publications

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“…During the rainy season, increased precipitation and runoff lead to rising GWL, while dry seasons result in decreased groundwater recharge due to higher evaporation rates (Kalantari et al, 2009). Understanding the intricate relationship between human activities, seasonal changes, and hydrology is vital for sustainable water resource management in Iran's Izeh City of Khuzestan province (e.g., Nassery et al, 2009;Mahdavi et al, 2021).…”

Section: Spearman's and Pearson's Correlation And Error Metricsmentioning

confidence: 99%

Predicting groundwater level using traditional and deep machine learning algorithms

Feng,

Ghorbani,

Radwan

2024

Front. Environ. Sci.

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This research aims to evaluate various traditional or deep machine learning algorithms for the prediction of groundwater level (GWL) using three key input variables specific to Izeh City in the Khuzestan province of Iran: groundwater extraction rate (E), rainfall rate (R), and river flow rate (P) (with 3 km distance). Various traditional and deep machine learning (DML) algorithms, including convolutional neural network (CNN), recurrent neural network (RNN), support vector machine (SVM), decision tree (DT), random forest (RF), and generative adversarial network (GAN), were evaluated. The convolutional neural network (CNN) algorithm demonstrated superior performance among all the algorithms evaluated in this study. The CNN model exhibited robustness against noise and variability, scalability for handling large datasets with multiple input variables, and parallelization capabilities for fast processing. Moreover, it autonomously learned and identified data patterns, resulting in fewer outlier predictions. The CNN model achieved the highest accuracy in GWL prediction, with an RMSE of 0.0558 and an R2 of 0.9948. It also showed no outlier data predictions, indicating its reliability. Spearman and Pearson correlation analyses revealed that P and E were the dataset’s most influential variables on GWL. This research has significant implications for water resource management in Izeh City and the Khuzestan province of Iran, aiding in conservation efforts and increasing local crop productivity. The approach can also be applied to predicting GWL in various global regions facing water scarcity due to population growth. Future researchers are encouraged to consider these factors for more accurate GWL predictions. Additionally, the CNN algorithm’s performance can be further enhanced by incorporating additional input variables.

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Section: Spearman's and Pearson's Correlation And Error Metricsmentioning

confidence: 99%

Predicting groundwater level using traditional and deep machine learning algorithms

Feng,

Ghorbani,

Radwan

2024

Front. Environ. Sci.

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“…2 Climate models predict severe droughts on the regional scale in the future, which will fundamentally alter forest composition and distribution in many regions. 3 Embolism removal is the ability of plants to restore water transportation after encountering droughts and air embolisms can form easily in xylem vessels (henceforth referred to as vessel or vessels) under drought conditions. 4 The drought resistance of a particular type of plant is closely related to the ability and capacity of that plant to perform or undergo embolism removal of the vessels.…”

Section: Introductionmentioning

confidence: 99%

Study of the mechanism of embolism removal in xylem vessels by using microfluidic devices

Guo

Liu

et al. 2023

Lab Chip

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“…Numerous reports and scientific articles indicate that forecasts of future climate conditions suggest an increase in the frequency and intensity of droughts in some regions of the world [17][18][19][20][21]. The increase in the frequency of drought occurrence in recent years has not been limited to arid and semi-arid regions [22][23][24][25][26], but has been gradually becoming more common in Atmosphere 2021, 12, 1098 2 of 20 regions with a temperate and humid climate [27][28][29][30][31][32]. Poland, which has one of the most limited water resources in Europe [33], is among those regions experiencing an increase in drought frequency [34].…”

Section: Introductionmentioning

confidence: 99%

The Analysis of Long-Term Trends in the Meteorological and Hydrological Drought Occurrences Using Non-Parametric Methods—Case Study of the Catchment of the Upper Noteć River (Central Poland)

2021

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The study aims to identify long-term trends in the changes of drought occurrences using the Mann-Kendall (MK) test and the Theil-Sen estimator. Trend research was carried out on the example of the catchment area of the Upper Noteć River, which covers an agricultural area of Poland with some of the lowest water reserves. The meteorological droughts were identified based on the Standardized Precipitation Index (SPI), while the hydrological droughts were determined on the basis of the Standardized Runoff Index (SRI) in various time scales (1, 3, 6, 9 and 12 months) in the period of 1981–2016. The relationship between SPI and SRI was determined on the basis of the Pearson correlation analysis. The results showed that statistically significant trends (at the significance level of 0.05) were identified at 3 out of 8 meteorological stations (downward trend at Kłodawa station and upward trend for drought at Sompolno and Kołuda Wielka stations). Statistically significant hydrological droughts showed an increase in occurrences at the Łysek station, while a downward trend was noted at the Noć Kalina station. No trend was found at the Pakość station. The analysis of the correlation between meteorological and hydrological droughts showed a strong relationship in dry years. The maximum correlation coefficient was identified in longer accumulation periods i.e., 6 and 9 months. The example of the catchment of the Upper Noteć River points to the necessity of using several indicators in order to assess the actual condition of the water reserves.

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Drought occurrence under future climate change scenarios in the Zard River basin, Iran

Cited by 8 publications

References 32 publications

Predicting groundwater level using traditional and deep machine learning algorithms

Predicting groundwater level using traditional and deep machine learning algorithms

Study of the mechanism of embolism removal in xylem vessels by using microfluidic devices

The Analysis of Long-Term Trends in the Meteorological and Hydrological Drought Occurrences Using Non-Parametric Methods—Case Study of the Catchment of the Upper Noteć River (Central Poland)

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