Analysis of spatio-temporal rainfall trends across southern African biomes between 1981 and 2016

Marumbwa, Farai Maxwell; Cho, Moses Azong; Chirwa, Paxie W.

doi:10.1016/j.pce.2019.10.004

Cited by 30 publications

(22 citation statements)

References 29 publications

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“…Marumbwa et al 104 suggested that the analysis of historical rainfall trend is very crucial in several fields like water resource management, sustainable agricultural planning, ecosystem management and health sector. The rainfall data of 115 years were used to investigate the variability of annual and seasonal rainfall in very detail and analyzed the trend in several ways for thirty-four meteorological sub-divisions.…”

Section: Discussionmentioning

confidence: 99%

Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches

Praveen

Talukdar

Shahfahad

et al. 2020

Sci Rep

304

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this study analyzes and forecasts the long-term Spatio-temporal changes in rainfall using the data from 1901 to 2015 across India at meteorological divisional level. The Pettitt test was employed to detect the abrupt change point in time frame, while the Mann-Kendall (MK) test and Sen's innovative trend analysis were performed to analyze the rainfall trend. The Artificial Neural Network-Multilayer Perceptron (ANN-MLP) was employed to forecast the upcoming 15 years rainfall across India. We mapped the rainfall trend pattern for whole country by using the geo-statistical technique like Kriging in ArcGIS environment. Results show that the most of the meteorological divisions exhibited significant negative trend of rainfall in annual and seasonal scales, except seven divisions during. Out of 17 divisions, 11 divisions recorded noteworthy rainfall declining trend for the monsoon season at 0.05% significance level, while the insignificant negative trend of rainfall was detected for the winter and premonsoon seasons. Furthermore, the significant negative trend (−8.5) was recorded for overall annual rainfall. Based on the findings of change detection, the most probable year of change detection was occurred primarily after 1960 for most of the meteorological stations. The increasing rainfall trend had observed during the period 1901-1950, while a significant decline rainfall was detected after 1951. The rainfall forecast for upcoming 15 years for all the meteorological divisions' also exhibit a significant decline in the rainfall. The results derived from ECMWF ERA5 reanalysis data exhibit that increasing/ decreasing precipitation convective rate, elevated low cloud cover and inadequate vertically integrated moisture divergence might have influenced on change of rainfall in India. Findings of the study have some implications in water resources management considering the limited availability of water resources and increase in the future water demand. Rainfall is a key part of hydrological cycle and alteration of its pattern directly affect the water resources 1. The changing pattern of rainfall in consequence of climate change is now concerning issues to water resource managers and hydrologists 2. Srivastava et al. 3 and Islam et al. 4 reported that the changes of rainfall quantities and frequencies directly changing the stream flow pattern and its demand, spatiotemporal allocation of runoff , ground water reserves and soil moisture. Consequently, these changes showed the widespread consequences on the water resource, environment, terrestrial ecosystem, ocean, biodiversity , agricultural and food security. The drought and flood like hazardous events can be occurred frequently because of the extreme changes of rainfall trend 5. Gupta et al. 6 documented that the amount of soil moisture for crop production is totally determined by the amount of rainfall. The monsoon rainfall plays a vital role for agriculture in India. 68% of cultivated land to the total cultivated land of India is occupying by the rain fed agriculture which...

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Section: Discussionmentioning

confidence: 99%

Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches

Praveen

Talukdar

Shahfahad

et al. 2020

Sci Rep

304

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“…and time (T) (Marumbwa et al 2019). The minimum and maximum temperature spacetime analysis has been carried out using the emerging HS Analysis tool in ArcPro 2.4…”

Section: Discussionmentioning

confidence: 99%

Sub-division Level Temperature Patterns and Trends Across East-Coast Industrial Corridor, India

2021

Preprint

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Temperature patterns and trends influence many sectors. The newly planned industrial corridors will have to consider the variations in temperature and other climatic parameters. The present article aims to investigate the patterns and trends of maximum and minimum temperature at the Sub-division (sub-district) level. We analyse annual and seasonal temperature data from 1958 to 2018 for the India’s first east-coast corridor, the Visakhapatnam–Chennai industrial corridor (VCIC) using a combination of Getis–Ord–Gi and Mann–Kendall trend test for spatiotemporal patterns and trends. The results show domination of intensifying hot spots across the VCIC and an overall increase in both maximum and minimum temperature for annual (0.013 oC/y and 0.011 oC/y) and seasonal trends. However, the variations of pattern and trends are unambiguous within districts. There is a clear distinction in patterns and trends between southern and north-eastern districts, indicating the need for localised planning. As the industrial areas are planned at a microlevel, such studies will enable planners and decision-makers to plan and prioritise site-specific climate change adaptation and mitigation measures in industrial and urban areas.

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“…Emerging hotspot analysis (EHA) incorporates temporal trends in the spatial distribution for examining the spatial-temporal in patterns relating to deforestation (Reddy et al, 2019), fire activity (Reddy et al, 2019(Reddy et al, , 2020, disease (Karunaweera et al, 2020), and rainfall patterns (Marumbwa et al, 2019). EHA is underpinned by a space-time pattern mining paradigm within a geographic context that help examine the complex data trends that occur across a landscape over time (Portillo-Quintero & Smith, 2018;Reddy et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Spatial–temporal variations in deforestation hotspots in Sumatra and Kalimantan from 2001–2018

Singh

Yan

2021

Ecology and Evolution

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Analysis of spatio-temporal rainfall trends across southern African biomes between 1981 and 2016

Cited by 30 publications

References 29 publications

Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches

Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches

Sub-division Level Temperature Patterns and Trends Across East-Coast Industrial Corridor, India

Spatial–temporal variations in deforestation hotspots in Sumatra and Kalimantan from 2001–2018

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