SciELO - Scientific Electronic Library Online

 
vol.9 issue5Estimación de parámetros en modelos agregados para el estudio de descargas de acuíferos kársticosGeostatistical estimation of the spatial distribution of mean monthly and mean annual rainfall in Nuevo León, Mexico (1930-2014) author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Tecnología y ciencias del agua

On-line version ISSN 2007-2422

Abstract

ZUBIETA, Ricardo; LAQUI, Wilber  and  LAVADO, Waldo. Hydrological modeling using observed and satellite precipitation datasets for the Ilave River basin, 2011-2015 period, Puno, Peru. Tecnol. cienc. agua [online]. 2018, vol.9, n.5, pp.85-105.  Epub Nov 24, 2020. ISSN 2007-2422.  https://doi.org/10.24850/j-tyca-2018-05-04.

Precipitation datasets obtained from satellites can be useful in regions where rainfall is very heterogeneous, such as Peruvian Andes, which is usually poorly monitored. The objective of this study is to characterize the main hydrological variables and to understand the potential of precipitation estimates based on satellite datasets for hydrological modeling. This article evaluates the usefulness of estimated precipitation from observed (rain gauges) and satellites datasets (TMPA V7 and TMPA RT products of the TRMM satellite) as input in GR2M hydrological model to simulate monthly streamflows between 2011-2015 for the Ilave River basin located in the Peruvian Altiplano. The results from observational datasets indicate a deficit of streamflows due to decreased rainfall during wet season (~ 50%), whereas evapotranspiration is greater during dry season (~ 24%). Our results show that TMPA V7 has a higher similarity with respect to precipitation observed during wet season. Results also indicate that GR2M perform better with observed inputs and when TMPA-V7 precipitation datasets are used, while the opposite occurs with TMPA RT dataset. This poor performance of the hydrological model may be due to inadequate rainfall estimation in the water balance.

Keywords : Precipitation datasets; Hydrological modeling; Andes; TRMM; Satellite.

        · abstract in Spanish     · text in English | Spanish