A comparative analysis of pre- and post-industrial spatiotemporal drought trends and patterns of Tibet Plateau using Sen slope estimator and steady-state probabilities of Markov Chain

Li, Zhen‐Ya; Ali, Zulfiqar; Cui, Tong; Qamar, Sadia; Ismail, Muhammad; Nazeer, Amna; Faisal, Muhammad

doi:10.1007/s11069-022-05314-x

Cited by 10 publications

(5 citation statements)

References 103 publications

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“…In this case, the null ( H 0 ) assumes that there is no tendency in the studied variable, whereas the alternative hypothesis ( H a ) presumes there is a tendency [ 73 ]. In addition, the Sen slope estimator was implemented to capture the values of changes during the study period [ 74 ].…”

Section: Methodsmentioning

confidence: 99%

Meteorological Drought Variability and Its Impact on Wheat Yields across South Africa

Nxumalo

Bashir

Alsafadi

et al. 2022

IJERPH

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Drought is one of the natural hazards that have negatively affected the agricultural sector worldwide. The aims of this study were to track drought characteristics (duration (DD), severity (DS), and frequency (DF)) in South Africa between 2002 and 2021 and to evaluate its impact on wheat production. Climate data were collected from the South African Weather Service (SAWS) along with wheat yield data from the Department of Agriculture, Forestry and Fisheries (2002–2021). The standard precipitation index (SPI) was calculated on 3-, 6-, 9-, and 12-month time scales, and the trend was then tracked using the Mann–Kendall (MK) test. To signify the climatic effects on crop yield, the standardized yield residual series (SYRS) was computed along with the crop-drought resilience factor (CR) on a provincial scale (2002–2021). The output of the SPI analysis for 32 stations covering all of South Africa indicates a drought tendency across the country. On a regional scale, western coastal provinces (WES-C and NR-C) have been more vulnerable to meteorological droughts over the past 20 years. Positive correlation results between SYRS and wheat yield indicate that the WES-C province was highly influenced by drought during all stages of wheat growth (Apr–Nov). Historical drought spells in 2003, 2009, and 2010 with low CR = 0.64 caused the province to be highly impacted by the negative impacts of droughts on yield loss. Overall, drought events have historically impacted the western part of the country and dominated in the coastal area. Thus, mitigation plans should be commenced, and priority should be given to this region. These findings can assist policymakers in budgeting for irrigation demand in rainfed agricultural regions.

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Section: Methodsmentioning

confidence: 99%

Meteorological Drought Variability and Its Impact on Wheat Yields across South Africa

Nxumalo

Bashir

Alsafadi

et al. 2022

IJERPH

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“…We applied the Sen slope method to estimate the variation amplitude of the meteorological variable trend. The strength of this method can effectively avoid the influence of missing values and outliers by using the slope and intercepts median values of pairs of points as judgment tools (Sen, 1968;Attaur and Dawood, 2016;Li et al, 2022).…”

Section: Sen Slopementioning

confidence: 99%

Impacts of climate change and fruit tree expansion on key hydrological components at different spatial scales

Liu²,

Fan³

et al. 2023

Front. For. Glob. Change

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Assessing how fruit tree expansion and climate variability affect hydrological components (e.g., water yield, surface runoff, underground runoff, soil water, evapotranspiration, and infiltration) at different spatial scales is crucial for the management and protection of watersheds, ecosystems, and engineering design. The Jiujushui watershed (259.32 km2), which experienced drastic forest changes over the past decades, was selected to explore the response mechanisms of hydrological components to fruit tree expansion and climate variability at different spatial scales (whole basin and subbasin scale). Specifically, we set up two change scenarios (average temperature increase of 0.5°C and fruit tree area expansion of 18.97%) in the SWAT model by analyzing historical data (1961∼2011). Results showed that climate change reduced water yield, surface runoff, and underground runoff by 6.75, 0.37, and 5.91 mm, respectively. By contrast, the expansion of fruit trees increased surface runoff and water yield by 2.81 and 4.10 mm, respectively, but decreased underground runoff by 1 mm. Interestingly, the sub-basins showed different intensities and directions of response under climate change and fruit tree expansion scenarios. However, the downstream response was overall more robust than the upstream response. These results suggest that there may be significant differences in the hydrological effects of climate change and fruit tree expansion at different spatial scales, thus any land disturbance measures should be carefully considered.

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“…One of the important indicators used and recommended in drought studies is the standard precipitation index (da Rocha Miranda et al 2022) and (Li et al 2022).…”

Section: )mentioning

confidence: 99%

Analysis and forecasting drought characterisation with using Markov chain model

Javadinejad¹,

Dara²,

Krause

et al. 2023

Saf. Extreme Environ.

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Drought is one of the inseparable parts of climate uctuations that cause a lot of damage every year. Considering the effects of drought on different parts of the environment, agriculture, natural resources, wildlife, etc., its prediction can be useful for managing the crisis and reducing the damages caused by it. In the current research, monthly drought was calculated based on the standard precipitation index in several stations in the south of Iran during the years 1980-2020; Then, using the Markov chain, monthly drought was predicted for the years 2020 to 2040. According to the results, most of the stations have normal, moderate and severe drought conditions.The transition probability matrix showed that in all stations, the probability of passing from a certain state to the same state and the probability of passing from wet to dry state is high; But the probability of transition from dry to wet is low. Also, the predictive results were measured at different stations with different levels of accuracy.In addition, the results showed that the highest probability of drought in the years 2020-2040 is related to normal, moderate and severe classes, and at the level of the studied area, from class one to seven, the 13.4, 26.81, 27,74, 37.11, 4.76, 2.88, and 0.70% of the predicted months drought will happen respectively.

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A comparative analysis of pre- and post-industrial spatiotemporal drought trends and patterns of Tibet Plateau using Sen slope estimator and steady-state probabilities of Markov Chain

Cited by 10 publications

References 103 publications

Meteorological Drought Variability and Its Impact on Wheat Yields across South Africa

Meteorological Drought Variability and Its Impact on Wheat Yields across South Africa

Impacts of climate change and fruit tree expansion on key hydrological components at different spatial scales

Analysis and forecasting drought characterisation with using Markov chain model

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