webXTREME :  R -based web tool for calculating agroclimatic indices of extreme events

Klein, Tommy; Samourkasidis, Argyrios; Athanasiadis, Ioannis N.; Bellocchi, Gianni; Calanca, Pierluigi

doi:10.1016/j.compag.2017.03.002

Cited by 12 publications

(4 citation statements)

References 18 publications

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“…The occurrences of extreme weather events during the validation period (refer to Fig 1) were analysed using webXTREME which is an R-based web tool for calculating agro-climatic indices of extreme events (refer to http://modextreme.org/webxtreme/) (Klein et al 2017). In webXTREME, the number of days with extreme aridity are measured as number of days in a growing season [Day of Year(DOY) start, DOYend] with ARID > ARIDcrit, where ARID (Agricultural Reference Index for Drought) denotes the aridity index proposed by Woli et al (2012).…”

Section: Site Descriptionmentioning

confidence: 99%

Modelled impacts of extreme heat and drought on maize yield in South Africa

Mangani

Tesfamariam

Bellocchi³

et al. 2018

Crop Pasture Sci.

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This study assessed two versions of the crop model CropSyst (i.e. EMS, existing; MMS, modified) for their ability to simulate maize (Zea mays L.) yield in South Africa. MMS algorithms explicitly account for the impact of extreme weather events (droughts, heat waves, cold shocks, frost) on leaf development and yield formation. The case study of this research was at an experimental station near Johannesburg where both versions of the model were calibrated and validated by using field data collected from 2004 to 2008. The comparison of EMS and MMS showed considerable difference between the two model versions during extreme drought and heat events. MMS improved grain-yield prediction by ~30% compared with EMS, demonstrating a better ability to capture the behaviour of stressed crops under a range of conditions. MMS also showed a greater variability in response when both versions were forced with scenarios of projected climate change, with increased severity of drought and increased temperature conditions at the horizons 2030 and 2050, which could drive decreased maize yield. Yield was even lower with MMS (8 v. 11 t ha–1 for EMS) at the horizon 2050, relative to the baseline scenario (~13 t ha–1 at the horizon 2000). Modelling solutions accounting for the impact of extreme weather events can be seen as a promising tool for supporting agricultural management strategies and policy decisions in South Africa and globally.

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Section: Site Descriptionmentioning

confidence: 99%

Modelled impacts of extreme heat and drought on maize yield in South Africa

Mangani

Tesfamariam

Bellocchi³

et al. 2018

Crop Pasture Sci.

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“…An analysis of extreme temperature events using webXTREME (An R-web-based web tool for calculating agro-climatic indices of extreme events) (http://www. modextreme.org/webxtreme) (Klein et al 2017) shows a positive shift in the median of the number of days with temperature above 30°C in a growing season as we move from the baseline to the far future scenario (Fig. 3).…”

Section: Resultsmentioning

confidence: 99%

Potential impacts of extreme weather events in main maize (Zea mays L.) producing areas of South Africa under rainfed conditions

et al. 2019

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An important topic of global concern is the likely reduction of maize production in response to climate change in association with increased frequency and intensity of extreme weather events, which threatens food security. We quantified the response of maize yield to projected climate changes in three main maize growing areas of South Africa (Bloemfontein, Lichtenburg and Nelspruit) using two crop modelling solutions: existing (EMS) and modified (MMS) CropSyst. The MMS considers explicitly the impact of extreme heat and drought. Both solutions were run with climate data generated from two radiative forcing scenarios using six general circulation models and three time horizons representing baseline (1990-2020), near future (2021-2050) and far future (2051-2080) time periods. Reduced yields were projected with both modelling solutions especially under far future time period. Simulated maize yield using EMS with high radiative forcing for far future decreased (compared with the simulated baseline for EMS) by 30%, 25.9% and 18.3% at Bloemfontein, Lichtenburg and Nelspruit, respectively. Simulated grain yield with MMS showed reductions of 27.6%, 24.3% and 18.7%, respectively (compared with the simulated baseline for MMS). Grain yield differences between the EMS and MMS ranged between 9 and 21%. This difference showed an increasing trend as time progressed from the baseline to the far future and varied across locations. Accounting explicitly for the impact of extreme weather events (MMS) resulted in lower simulated yields compared with the model without (EMS). Findings from this study warrant the need for location-specific model simulation using MMS-type models to improve crop yield predictions under climate change for better food security planning and policy formulation.

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“…While Shiny has been used across a diverse range of academic fields, to our knowledge, few peer-reviewed papers in the earth and environmental sciences have used the Shiny web application framework. For instance, Klein et al (2017) developed the webXTREME tool to facilitate agroclimatic risk evaluation under climate change. WebXTREME has provided an important link between scientists and decision-makers.…”

Section: Introductionmentioning

confidence: 99%