Identification and Analysis of Drought Propagation of Groundwater During Past and Future Periods

Motlagh, Mahdi Soleimani; Ghasemieh, Hoda; Talebi, Ali; Abdollahi, Khodayar

doi:10.1007/s11269-016-1513-5

Cited by 25 publications

(10 citation statements)

References 32 publications

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“…The impact of Hunan Province on drought due to its special topography is also obvious. The reason is manifested in two aspects: (1) The high altitude affects the distribution of airflow, which in turn affects precipitation. (2) The second aspect is directly affected by photosynthesis.…”

Section: Discussionmentioning

confidence: 99%

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Framework for Monitoring the Spatiotemporal Distribution and Clustering of Drought Characteristics in Hunan Province

Huang

Baig

et al. 2021

Applied Sciences

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Drought is a widespread phenomenon in the context of global climate change. Owing to the geographical location of Hunan Province in the middle reaches of Yangtze River and the abundance of forests area in this region with a large population, there is a need to focus on the impacts of drought for devising policies. The spatiotemporal distribution scheme of a given area must be determined to plan water management and protect ecosystems effectively. This study proposes a framework for exploring the spatiotemporal distribution model of drought using comprehensive surveys of historical meteorological stations, which consists of two parts, namely the characteristics of drought extraction in the spatiotemporal distribution and drought models discovered by the clustering method. Firstly, we utilized the run theory to extract drought characteristics, such as drought duration, drought severity, and drought intensity. Secondly, the K-means clustering method was adopted to explore the distribution patterns on the basis of the drought characteristics. Lastly, the method was applied to Hunan Province. Results show that historical drought conditions can be monitored with their characteristics of spatiotemporal variability. Three drought distribution clusters exist in this region. Cluster 1 in western Hunan tends to be a long-term, low-intensity drought, cluster 2 in the southern part tends to be a short-term, high-intensity drought, and cluster 3 in the central part is prone to severe drought. The proposed framework is flexible as it allows parameters to be adjusted and extraction methods to achieve reasonable results for a given area.

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Section: Discussionmentioning

confidence: 99%

“…Droughts, which last for several days or even years, are complex and recurring natural phenomena [1]. Their formation is mainly due to a substantial decline in water availability caused by insufficient precipitation [2,3].…”

Section: Introductionmentioning

confidence: 99%

Framework for Monitoring the Spatiotemporal Distribution and Clustering of Drought Characteristics in Hunan Province

Huang

Baig

et al. 2021

Applied Sciences

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“…However, there are significant differences: there is no meaning in the accumulation over a specified period and the distribution of the observed monthly groundwater levels does not conform to the already analyzed PDFs. Some authors used different distributions to analyze the groundwater data such as the plotting position method (Osti et al, 2008) and the kernel non-parametric distribution (Vidal et al, 2010;Bloomfield and Marchant, 2013;Soleimani Motlagh et al, 2017). The plotting position method is very sensitive to the sample size, especially when the number of data is small; for this reason, the kernel non-parametric method is preferred and used in this study.…”

Section: Standardized Groundwater Index (Sgi)mentioning

confidence: 99%

“…A common approach to explore these links is to use standardized indices (see e.g. Khan et al, 2008;Bloomfield and Marchant, 2013;Kumar et al, 2016;Leelaruban et al, 2017;Soleimani Motlagh et al, 2017;Van Loon et al, 2017;Uddameri et al, 2019;Guo et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

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Impacts of climate change on groundwater droughts by means of standardized indices and regional climate models

Secci

Tanda

D’Oria

et al. 2021

Journal of Hydrology

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Providing optimal cropping patterns and water consumption according to monitored and forecasted drought conditions

Khajehi,

Moghimi,

Zarei

2024

Irrigation and Drainage

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Drought management in the agricultural sector requires monitoring and prediction of this phenomenon, as well as providing a suitable cropping pattern. In this study, the reconnaissance drought index (RDI) was used for drought monitoring in Fars Province, Iran. The status of water resources was predicted using a model that matches the time series of the RDI and the groundwater level. The optimal cropping pattern was obtained according to the predicted available water resources using a genetic algorithm. Generally, the actual and predicted changes in groundwater levels indicate the critical conditions of groundwater resources in the study area. Groundwater resource consumption should be lowered by implementing deficit irrigation scenarios that result in keeping crops with lower sensitivity to water deficit in cropping patterns such as barley, wheat, canola, forage corn and potato. The cropping pattern optimization results suggest an increase in the area allocated to more economical crops in the northern half of Fars Province due to the better temporal distribution of annual rainfall and better water resource conditions. However, with increasing water costs, the cultivation area and the optimal water reduction fraction of these plants decreased.

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Identification and Analysis of Drought Propagation of Groundwater During Past and Future Periods

Cited by 25 publications

References 32 publications

Framework for Monitoring the Spatiotemporal Distribution and Clustering of Drought Characteristics in Hunan Province

Framework for Monitoring the Spatiotemporal Distribution and Clustering of Drought Characteristics in Hunan Province

Impacts of climate change on groundwater droughts by means of standardized indices and regional climate models

Providing optimal cropping patterns and water consumption according to monitored and forecasted drought conditions

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