×
Home Current Archive Editorial board
Instructions for papers
For Authors Aim & Scope Contact
Original scientific article

PRECIPITATION GENERATION FOR VARIOUS RETURN PERIODS USING RAIN4PE AND PISCOP V2.1 GRIDDED PRODUCTS IN THE SUPE RIVER BASIN

By
Rengifo-Arevalo Jhon Filips Orcid logo ,
Rengifo-Arevalo Jhon Filips

Universidad Privada del Norte , Trujillo , Peru

Agramonte-Monge Henry Fabian Orcid logo ,
Agramonte-Monge Henry Fabian

Universidad Privada del Norte , Trujillo , Peru

Abel Carmona Arteaga Orcid logo ,
Abel Carmona Arteaga

Grupo de Investigación Desarrollo e Innovación UPN -IDIUPN, Universidad Privada del Norte , Trujillo , Peru

Campos-Vasquez Neicer Orcid logo
Campos-Vasquez Neicer

Grupo de Investigación Desarrollo e Innovación UPN -IDIUPN, Universidad Privada del Norte , Trujillo , Peru

Abstract

This paper examines the distribution of maximum precipitation of the Supe basin at the return periods of 10, 100, 1000, and 10,000 years using Weibull technique to estimate return time. They compare PISCOp v2.1 and RAIN4PE which are two gridded rain products to evaluate their predictability in terms of extreme precipitation occurrences. These gridded products are compared with the data of the Ambar rainfall station, which is located in the upper part of Supe basin. Findings indicate that the highest values of precipitation using PISCOp v2.1 and RAIN4PE are similar with the highest amount of precipitation at 57.12 mm/day (PISCOp v2.1) and 60.07 mm/day (RAIN4PE) at a 10,000-year return period. These findings were also confirmed by the spatial analysis in ArcGIS and Google Earth Engine, in which the products were verified by means of historical data. The research is valuable to the future hydrological planning as it offers credible terms of precipitation to manage flood risks and water resource planning. The statistical analysis such as the Weibull method and the spatial interpolations (Kriging) show that both gridded products are very helpful in forecasting the rainfall intensities in the area. Nevertheless, PISCOp v2.1 indicates lower precipitation minimum values than RAIN4PE. The results demonstrate the significance of proper forecasting of precipitation in disaster management and planning of infrastructure, especially flood management and river management.

References

1.
Joel MT, Gabriel AO, Abel CA. Precipitation generation for different return times using the Rain4pe and PISCOp V2. 1 gridded product in the Zaña river basin.2023 Dec.
2.
Aybar C, Fernández C, Huerta A, Lavado W, Vega F, Felipe-Obando O. Construction of a highresolution gridded rainfall dataset for Peru from 1981 to the present day. Hydrological Sciences Journal. 2020 Apr 3;65(5):770-85. .
3.
Tran TN, Nguyen BQ, Zhang R, Aryal A, Grodzka-Łukaszewska M, Sinicyn G, Lakshmi V. Quantification of gridded precipitation products for the streamflow simulation on the Mekong River basin using rainfall assessment framework: A case study for the Srepok River subbasin, Central Highland Vietnam. Remote Sensing. 2023 Feb 13;15(4):1030.
4.
Zhao Q, Yu L, Li X, Peng D, Zhang Y, Gong P. Progress and trends in the application of Google Earth and Google Earth Engine. Remote Sensing. 2021 Sep 21;13(18):3778.
5.
Malik S, Pal SC. Potential flood frequency analysis and susceptibility mapping using CMIP5 of MIROC5 and HEC-RAS model: A case study of lower Dwarkeswar River, Eastern India. SN Applied Sciences. 2021 Jan;3(1):31.
6.
Tejada-Diaz FJ, Rojas-Bicerra JKN, Carmona-Arteaga A. Obtaining precipitation for various return periods using the CHIRPS, ERA5-Land, and RAIN4PE datasets in the Ocoña watershed. AiBi Journal of Research, Administration, and Engineering. 2025 May 1;13(2):1-14.
7.
Llauca H. Gridded hydro-meteorological data for Peru A brief review about gridded data-sets developed for the Peruvian domain. Peru Data-Science Hydro-Meteorology.2023 June 4.
8.
Mutanga O, Kumar L. Google earth engine applications. Remote sensing. 2019 Mar 12;11(5):591.
9.
Gorelick N, Hancher M, Dixon M, Ilyushchenko S, Thau D, Moore R. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote sensing of Environment. 2017 Dec 1;202:18-27.
10.
Meroni PL, Schur PH. ANA screening: an old test with new recommendations. Annals of the rheumatic diseases. 2010 Aug 1;69(8):1420-2.
11.
Pizarro SE, Pricope NG, Vargas-Machuca D, Huanca O, Ñaupari J. Mapping land cover types for highland Andean ecosystems in Peru using google earth engine. Remote Sensing. 2022 Mar 24;14(7):1562.
12.
Rojas-Le-Fort M, Valdivieso-López IP, Duarte-Casar R. Representations of Ecuadorian cuisine in the coast and the highlands regions through the free listing technique. Discover Food. 2023 Nov 13;3(1):20.
13.
Qquenta J, Rau P, Bourrel L, Frappart F, Lavado-Casimiro W. Assessment of bottom-up satellite precipitation products on river streamflow estimations in the Peruvian Pacific drainage. Remote Sensing. 2023 Dec 19;16(1):11.
14.
Veneros J, García L. Application of the standardized vegetation index (SVI) and Google Earth Engine (GEE) for drought management in Peru. Tropical and Subtropical Agroecosystems. 2021;(1).
15.
Abbas A, Yang Y, Pan M, Tramblay Y, Shen C, Ji H, Gebrechorkos SH, Pappenberger F, Pyo JC, Feng D, Huffman G. Comprehensive global assessment of 23 gridded precipitation datasets across 16,295 catchments using hydrological modeling. EGUsphere. 2025 Jan 20;2025:1-31.
16.
Serrano‐Notivoli R, Tejedor E. From rain to data: A review of the creation of monthly and daily station‐based gridded precipitation datasets. Wiley Interdisciplinary Reviews: Water. 2021 Nov;8(6): e1555.
17.
Gampe D, Ludwig R. Evaluation of gridded precipitation data products for hydrological applications in complex topography. Hydrology. 2017 Nov 16;4(4):53.
18.
Villafuerte EJ, Angulo EC. Evaluating Statistical Bias Correction Techniques to Enhance Precipitation Projections in the Cachi Basin, Peruvian Andes. Revista de Gestão Social e Ambiental. 2024;18(11):1-40.
19.
Cruz-Baltuano A, Huarahuara-Toma R, Silva-Borda A, Chucuya S, Franco-León P, Huayna G, Ramos-Fernández L, Pino-Vargas E. Assessment of Observed and Projected Extreme Droughts in Perú—Case Study: Candarave, Tacna. Atmosphere. 2024 Dec 27;16(1):18.
20.
Marinelli B, Lutz A, Breuer L, Weeser B, Khanal S, Condom T, Correa A. Assessing the contribution of meltwater to meet environmental flow requirements during drought events in the Andean Santa River basin. Journal of Hydrology: Regional Studies. 2025 Apr;58:102248.

Citation

This is an open access article distributed under the  Creative Commons Attribution Non-Commercial License (CC BY-NC) License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 

Article metrics

Google scholar: See link

The statements, opinions and data contained in the journal are solely those of the individual authors and contributors and not of the publisher and the editor(s). We stay neutral with regard to jurisdictional claims in published maps and institutional affiliations.