A spatiotemporal assessment of the high-resolution CHIRPS rainfall dataset in southwestern Colombia using combined principal component analysis

Ocampo-Marulanda, Camilo; Fernández-Álvarez, Cristhian; Cerón, Wilmar Loaiza; Canchala, Teresita; Carvajal-Escobar, Yesid; Alfonso-Morales, Wilfredo

doi:10.1016/j.asej.2022.101739

Cited by 16 publications

(5 citation statements)

References 72 publications

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“…The data derived included solar radiation (∼1° × 1° spatial resolution), maximum temperature, and minimum temperature (0.5° × 0.5°). The daily precipitation was mainly obtained from CHIRPS because of its high resolution (0.05° × 0.05°) (Ocampo‐Marulanda et al., 2022).…”

Section: Methodsmentioning

confidence: 99%

“…The data derived included solar radiation (∼1˚× 1˚spatial resolution), maximum temperature, and minimum temperature (0.5˚× 0.5˚). The daily precipitation was mainly obtained from CHIRPS because of its high resolution (0.05˚× 0.05˚) (Ocampo-Marulanda et al, 2022). Due to the extensive coverage of the study area, the weather variable retrieval and preparation of weather files into DSSAT weather file format were implemented using the bestiapop Python package (Ojeda et al, 2020).…”

Section: Sources Of Datamentioning

confidence: 99%

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Agronomic management response in maize (Zea mays L.) production across three agroecological zones of Kenya

Kipkulei,

Bellingrath‐Kimura,

Lana

et al. 2024

Agrosystems Geosci & Env

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Maize (Zea mays L.) productivity in Kenya has witnessed a decline attributed to the effects of climate change and biophysical constraints. The assessment of agronomic practices across agroecological zones (AEZs) is limited by inadequate data quality, hindering a precise evaluation of maize yield on a large scale. In this study, we employed the DSSAT‐CERES‐Maize crop model (where CERES is Crop Environment Resource Synthesis and DSSAT is Decision Support System for Agrotechnology Transfer) to investigate the impacts of different agronomic practices on maize yield across different AEZs in two counties of Kenya. The model was calibrated and evaluated with observed grain yield, biomass, leaf area index, phenology, and soil water content from 2‐year experiments. Remote sensing (RS) images derived from the Sentinel‐2 satellite were integrated to delineate maize areas, and the resulting information was merged with DSSAT‐CERES‐Maize yield simulations. This facilitated a comprehensive quantification of various agronomic measures at pixel scales. Evaluation of agronomic measures revealed that sowing dates and cultivar types significantly influenced maize yield across the AEZs. Notably, AEZ II and AEZ III exhibited elevated yields when implementing combined practices of early sowing and cultivar H614. The impacts of optimal management practices varied across the AEZs, resulting in yield increases of 81, 115, and 202 kg ha−1 in AEZ I, AEZ II, and AEZ III, respectively. This study underscores the potential of the CERES‐Maize model and high‐resolution RS data in estimating production at larger scales. Furthermore, this integrated approach holds promise for supporting agricultural decision‐making and designing optimal strategies to enhance productivity while accounting for site‐specific conditions.

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Section: Methodsmentioning

confidence: 99%

Section: Sources Of Datamentioning

confidence: 99%

Agronomic management response in maize (Zea mays L.) production across three agroecological zones of Kenya

Kipkulei,

Bellingrath‐Kimura,

Lana

et al. 2024

Agrosystems Geosci & Env

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“…CHIRPS has provided a rainfall dataset on daily, pentad (5-day), and monthly temporal scales since 1981, with an approximate spatial resolution of 0.05 • (5.5 km) and near-global land coverage (50 • N-50 • S) [47,48]. In this study, we used the CHIRPS v.2.0 at a monthly scale with a resolution of 0.05 • for the period from 1982 to 2019 in the region spanning the Colombian territory (14 The CHIRPS dataset was previously validated in Colombia by Funk et al [43] and Urrea et al [49], and in regions of the Colombian Andes, such as Medellín, by López-Bermeo et al [50] and Nariño by Ocampo-Marulanda et al [51]. We agree that CHIRPS represents a data source that preserves the main features of rainfall on monthly and annual scales.…”

Section: The Climate Hazards Group Infrared Precipitation With Statio...mentioning

confidence: 99%

“…We agree that CHIRPS represents a data source that preserves the main features of rainfall on monthly and annual scales. López-Bermeo et al [50] and Ocampo-Marulanda et al [51] reported that CHIRPS can be used to analyze the seasonal and interannual variability associated with ENSO, as well as spatial rainfall patterns for the studied regions, mainly in mountainous areas.…”

Section: The Climate Hazards Group Infrared Precipitation With Statio...mentioning

confidence: 99%

Multiscale Interactions of Climate Variability and Rainfall in the Sogamoso River Basin: Implications for the 1998–2000 and 2010–2012 Multiyear La Niña Events

Cerón

Díaz

Escobar-Carbonari

et al. 2022

Water

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In this research, we explored rainfall variability in the Sogamoso River Basin (SRB), its relationship with multiple scales of variability associated with El Niño–Southern Oscillation (ENSO), and the implications for rainfall prolongation during multiyear La Niña events. First, we examined time-frequency rainfall variations in the SRB based on the standardized precipitation index (SPI) from 1982 to 2019, using wavelet transform and principal component analysis (PCA). In addition, we applied wavelet analysis to investigate the links at different time scales between ENSO and the main mode of rainfall variability in the SRB. Finally, we explored the role that each scale of variability played in the prolongation and intensity of rainfall in the SRB during the 1998–2000 and 2010–2012 multiyear La Niña events. The results of the wavelet analyses revealed significant ENSO relationships affecting SRB rainfall at three different scales: quasi-biennial (2–3-years) between 1994 and 2002, as well as from 2008 to 2015; interannual (5–7 years) from 1995 to 2011; and quasi-decadal (9–12 years) from 1994 to 2012. This indicates that multiyear events are a consequence of the interaction of several scales of variability rather than a unique scale. During the 1998–2000 event, El Niño conditions were observed during the first half of 1998; subsequently, a cooling of the central and eastern tropical Pacific (western tropical Pacific) on the quasi-biennial (interannual) scale was observed during 1999; in 2000, only La Niña conditions were observed on the interannual scale. Therefore, during this event, the quasi-biennial (interannual) scale promoted wet conditions in the Caribbean, the Andes, and the Colombian Pacific from June–August (JJA) 1998 to JJA 1999 (during 1999–2000). During the 2010–2012 La Niña event, the interbasin sea surface temperature gradient between the tropical Pacific and tropical North Atlantic contributed to strengthening (weakening) of the Choco jet (Caribbean low-level jet) on the quasi-biennial scale during 2010, and the interannual scale prolonged its intensification (weakening) during 2011–2012, acting to extend the rainy periods over most of the Colombian territory. Variations on quasi-decadal scales were modulated by the Pacific decadal oscillation (PDO), resulting in a further intensification of the 2010–2012 La Niña event, which developed under conditions of the cold PDO (CPDO) phase, whereas the 1998–2000 La Niña occurred during the transition from warm (WPDO, 1977–1998) to cold (CPDO, 2001–2015) conditions. These results indicate that the interaction of quasi-biennial to quasi-decadal scales of variability could play a differential role in the configuration and prolongation of rainfall events in the SRB.

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“…Besides rainfall stations, technological advances produce rainfall data from satellites with a high resolution, both spatial resolution (global and regional), as well as temporal resolution (hourly, daily, monthly) [8] [9] [10]. One of the satellites that can be used is the CHIRPS satellite, with a spatial resolution of 0.05° x 0.05° arc degrees or about 5 km and a temporal resolution (daily, monthly, yearly) [11] [12] [13] [14]. In this study, rainfall station network is regulated by World Meteorological Organization (WMO) standard and the rationalization of the rainfall station was carried out using the Kagan-Rodda method.…”

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confidence: 99%

Rationalization of Rainfall Station Network in Welang Watershed Using Kagan-Rodda Method

Haromain

Wahyuni

Limantara

2022

UKaRsT

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Rationalizing rainfall station is important to get an effective and efficient number and distribution of rainfall stations. If rationalization isn’t carried out, it affect to operating and maintenance costs of rainfall stations and accuracy of data. This study aimed to evaluate existing rainfall station and rationalize rainfall station, so rainfall station’s location is evenly distributed. This study is located in Welang watershed with an area 477.78 km2. This research requires rainfall ground data from 9 rainfall stations and CHIRPS satellite rainfall data from Google Earth Engine. The data is tested with consistency, stationary, suitability, and rationalization based on World Meteorological Organization (WMO) standards and Kagan-Rodda method. Later, new rainfall station networks will be obtained with the influence area of rainfall stations suitable to WMO Standard. CHIRPS data is highly suitable with ground data, proven by high NSE, strong correlation, and low relative error, so CHIRPS data can be used for further analysis. According WMO, only 1 rainfall station in Welang watershed has been suitable for WMO standard. Those unsuitable with WMO standards need to be rationalized. Based rationalization results, with average error <10%, Welang watershed requires 4 rainfall stations by maintaining Lawang Station, moving Telebuk to Station B, Selowongko to Station C, and Tutur to Station D. The influence area of recommendation rainfall stations have been suitable to WMO Standards and obtained even distribution rainfall stations. This recommendation are expected to be considered by relevant institutes to move the location of the rainfall station to get more accurate rainfall data.

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A spatiotemporal assessment of the high-resolution CHIRPS rainfall dataset in southwestern Colombia using combined principal component analysis

Cited by 16 publications

References 72 publications

Agronomic management response in maize (Zea mays L.) production across three agroecological zones of Kenya

Agronomic management response in maize (Zea mays L.) production across three agroecological zones of Kenya

Multiscale Interactions of Climate Variability and Rainfall in the Sogamoso River Basin: Implications for the 1998–2000 and 2010–2012 Multiyear La Niña Events

Rationalization of Rainfall Station Network in Welang Watershed Using Kagan-Rodda Method

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