Evaluation of CHIRPS Satellite Gridded Dataset as an Alternative Rainfall Estimate for Localized Modelling over Uganda

Bamweyana, Ivan; Musinguzi, Moses; Kayondo, Lydia Mazzi

doi:10.4236/acs.2021.114046

Cited by 2 publications

(2 citation statements)

References 34 publications

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“…The indicators used to evaluate the performance were the correlation coefficient (R), percent bias (PBias), RMSE-observation Standard deviation Ratio (RSR), and Nash-Sutcliffe Efficiency coefficient (NSE). Furthermore, the range of R, Pbias, RSR, and NSE was 0-1, -∞ -∞, 0 -∞, and -∞ -1, with the best value being 1, 0, 0, and 1, respectively [35], [54], [55].…”

Section: ) Chirps Data Validationmentioning

confidence: 96%

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Assessment of Extreme Precipitation for Developing Agricultural Adaptation Strategy in the Selo Watershed Area

Nugroho,

Febriamansyah,

Nurhamidah

et al. 2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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The ongoing climate change resulting from the effects of global warming is manifested through increased variability and a rise in extreme precipitation events. Given this situation, it becomes imperative for farmers to adapt to these changes to ensure the long-term sustainability of their businesses. Therefore, this research aimed to assess extreme precipitation for planning adaptation strategies for agricultural water resources in the Selo watershed, Tanah Datar Regency, West Sumatra Province, Indonesia. Climate Hazards Group Infrared Precipitation and Stations (CHIRPS) data were used to accomplish this, spanning 1981 to 2020. A set of indices recommended by ETCCDI, including PRCPTOT, CDD, CWD, R95p, R99p, SDII, R10mm, R20mm, R30mm, and R40mm were employed to assess extreme precipitation. Climate Data Operator (CDO) and GrADS were conducted for downscale and plotting data. Furthermore, the Mann-Kendall test was conducted to determine the significance of change trends in the indices. R-Climdex was used to determine the extreme event based on the data used. The results showed that all indices indicated wet conditions during the period 1981-2020. The topographic characteristics of the watershed served as a basis for selecting suitable adaptation strategies within the agricultural water resources sector. One potential approach involves integrating conservation-based adaptation practices with comprehensive watershed management techniques. Factors such as the areaâ€™s sensitivity to changes in the total intensity or frequency of precipitation, combined with the local environmental conditions, can be considered in determining the optimal adaptation approach.

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Section: ) Chirps Data Validationmentioning

confidence: 96%

“…This research used reanalyzed precipitation information in grid format due to the limitations of in-situ observation data at the location [35]- [37]. The performance test was to evaluate extreme precipitation as performed in previous results [38]- [41].…”

Section: B Datamentioning

confidence: 99%

Assessment of Extreme Precipitation for Developing Agricultural Adaptation Strategy in the Selo Watershed Area

Nugroho,

Febriamansyah,

Nurhamidah

et al. 2023

Int. J. Adv. Sci. Eng. Inf. Technol.

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Water Quality Accuracy Test from Sentinel-2 Imagery in The Pasee-Peusangan Watershed Area

Syafjanuar,

Rahman,

hadi

et al. 2023

Preprint

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The use of satellite imagery for monitoring water quality will be very practical as well as efficient in terms of time and cost, and can provide information on a very wide area. the purpose of this study was to identify water quality against the TSS parameter and in the Pasee-Peusangan watershed using Sentinel-2 Imagery. Evaluation was carried out through a qualitative method of a combination of NDTI and NDWI and TSS water quality parameter values. After that, a validation test was carried out using the RMSE, RE and R^2 methods. The TSS value as a water quality parameter in the Pasee-Peusangan Watershed ranges from 0 to 43.908035 (mg/l), areas with low concentrations of TSS predominate with an area of 533.868 Ha or around 98.15%. While the medium and high categories are between 0.2% and 1% respectively, the very high TSS category is 0.1% of the study area. Test Image validation test using the RMSE, RE and \({R}^{2}\)formulas, RMSE shows the suitability and accuracy of field and image data. The water quality in the Pasee-Peusangan Watershed is in the class 1 and class 2 categories, which means it is still relatively good.

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Evaluation of CHIRPS Satellite Gridded Dataset as an Alternative Rainfall Estimate for Localized Modelling over Uganda

Cited by 2 publications

References 34 publications

Assessment of Extreme Precipitation for Developing Agricultural Adaptation Strategy in the Selo Watershed Area

Assessment of Extreme Precipitation for Developing Agricultural Adaptation Strategy in the Selo Watershed Area

Water Quality Accuracy Test from Sentinel-2 Imagery in The Pasee-Peusangan Watershed Area

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