TY - GEN
T1 - Hydrological modeling of High Jungle area sub-basin, using the GR2M, Temez and Lutz Scholtz models
AU - Orozco, Jose Carlos Canales
AU - Aranzana, Maria Fernanda Gonzales
AU - Hurtado, Sissi Santos
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - Scarcity or non-existence of hydrometeorological stations that cover a large percentage of territory of a country leads to the delay in possible research or projects for water resources administration. Therefore, the hydrological balance models together with satellite precipitation products represent one of the ways to estimate flows in a specific period. In Peru, one of the areas that does not have enough monitoring stations and consequently with scarce hydrometeorological data is the High Jungle area. Due to this, this article performs a hydrological balance modeling in a sub-basin in the High Jungle based on the PISCO satellite product and the methodologies of Temez, GR2M and Lutz Scholtz. GR2M model gave better results, with the following validation coefficients: Nash = 0.70, PBIAS = 2.31, R2 = 0.69 and KGE = 0.74. In conclusion, GR2M hydrological balance model has a better fit for the estimation of average flows of sub-basins in areas of High Jungle.
AB - Scarcity or non-existence of hydrometeorological stations that cover a large percentage of territory of a country leads to the delay in possible research or projects for water resources administration. Therefore, the hydrological balance models together with satellite precipitation products represent one of the ways to estimate flows in a specific period. In Peru, one of the areas that does not have enough monitoring stations and consequently with scarce hydrometeorological data is the High Jungle area. Due to this, this article performs a hydrological balance modeling in a sub-basin in the High Jungle based on the PISCO satellite product and the methodologies of Temez, GR2M and Lutz Scholtz. GR2M model gave better results, with the following validation coefficients: Nash = 0.70, PBIAS = 2.31, R2 = 0.69 and KGE = 0.74. In conclusion, GR2M hydrological balance model has a better fit for the estimation of average flows of sub-basins in areas of High Jungle.
KW - GR2M Model
KW - Hydrological Model
KW - Lutz Scholtz Model
KW - Temez Model
UR - https://www.scopus.com/pages/publications/85123610896
U2 - 10.1109/CONIITI53815.2021.9619714
DO - 10.1109/CONIITI53815.2021.9619714
M3 - Contribución a la conferencia
AN - SCOPUS:85123610896
T3 - 2021 7th Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2021 - Conference Proceedings
BT - 2021 7th Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2021 - Conference Proceedings
A2 - Morales, Victor Manuel Fontalvo
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th Congreso Internacional de Innovacion y Tendencias en Ingenieria, CONIITI 2021
Y2 - 29 September 2021 through 1 October 2021
ER -