A near real-time drought monitoring system for Spain using automatic weather station network

Vicente‐Serrano, Sergio M.; Domínguez‐Castro, Fernando; Reig, F.; Beguerı́a, Santiago; Tomás-Burguera, Miquel; Latorre, Borja; Peña‐Angulo, Dhais; Noguera, Iván; Rabanaque, Isabel; Luna, M. Y.; Morata, A.; Kenawy, Ahmed El

doi:10.1016/j.atmosres.2022.106095

Cited by 18 publications

(4 citation statements)

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“…To use SPEI for monitoring purposes, the AWS data undergo exhaustive quality control [19] , aggregated weekly and then spatially interpolated using Universal Kriging as soon as new meteorological data are available to generate new SPEI values for the whole of Spain (see all details in Vicente-Serrano et al. [20] ).…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Near-real time flash drought monitoring system and dataset for Spain

et al. 2023

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Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Near-real time flash drought monitoring system and dataset for Spain

et al. 2023

Self Cite

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“…Therefore, using calendar weeks as the reference periods can be challenging since the first day of each year can fall on different days, causing inconsistency throughout the year. Leap years also add difficulties to this comparison (Vicente-Serrano et al 2022). Additionally, a quart.…”

Section: Spi and Spei: Calculation Algorithm And Assumptionsmentioning

confidence: 99%

“…The quart.month time scale is similar to that one adopted in Vicente-Serrano et al (2022). As pointed out by these authors, standardized drought indices are relative metrics that require homogeneous periods.…”

Section: Spi and Spei: Calculation Algorithm And Assumptionsmentioning

confidence: 99%

The PowerSDI: an R-package for implementing and calculating the SPI and SPEI using data from the NASAPOWER project

Blain,

Sobierajski,

Martins

2024

Bragantia

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The standardized precipitation (SPI) and standardized precipitation-evapotranspiration (SPEI) indices are important tools for monitoring drought events, but the low density of weather station networks limits their use in many regions. To address this issue, we developed the PowerSDI R-package, which calculates these two indices using gridded-data from the NASA-POWER project (NASA-SPI and NASA-SPEI). Different from other packages, the PowerSDI package has two modes: the scientific, and the operational. In the scientific mode, the users may assess the quality of the indices estimates through their agreement with a reference/observed series and through the evaluation of how well these estimates meet the conceptual assumptions required for calculating both SPI and SPEI. This evaluation is based on measure of accuracy (e.g., Willmott index of agreement), goodness-of-fit tests (e.g., Anderson-Darling), and normality tests (e.g., Shapiro-Wilk's test), which are calculated by the ScientSDI.R, Reference.R, and Accuracy.R functions. In the operational mode, users can calculate both indices routinely using the OperatSDI.R function. The package also uses a quasi-weekly time scale, allowing for index calculations four times a month. The OperatSDI.R enables users to download NASA-POWER data for all available period or only for the quasi-week they intend to monitor (reducing the function's running time). In short, the PowerSDI facilitates the routine use of these two widely used drought indices and, unlike others existing software, it provides a solid scientific basis for using NASA-POWER data in drought monitoring systems, which can help improve drought preparedness and response efforts worldwide. The package is freely available at two repositories: Github (https://github.com/gabrielblain/PowerSDI), and CRAN (https://CRAN.R-project.org/package=PowerSDI).

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“…In addition to the need to increase soil productivity to satisfy the growing demand for food and the high demands of the market, this must be achieved in a context of high uncertainty about the availability of water for irrigation. In Spain there is high pressure on the use of water resources and projections indicate that, due to climate change, the availability of water for agriculture will decrease and the increase in temperatures will imply a greater water requirement and an extension of the irrigation period for crops Vicente-Serrano et al, 2022, 2020.…”

Section: Introductionmentioning

confidence: 99%

Agronomic strategies to cope with wáter scarcity and increase the sustainability of mandarin tres under semi-arid conditions

Berríos Reyes

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A near real-time drought monitoring system for Spain using automatic weather station network

Cited by 18 publications

References 105 publications

Near-real time flash drought monitoring system and dataset for Spain

Near-real time flash drought monitoring system and dataset for Spain

The PowerSDI: an R-package for implementing and calculating the SPI and SPEI using data from the NASAPOWER project

Agronomic strategies to cope with wáter scarcity and increase the sustainability of mandarin tres under semi-arid conditions

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