Article citationsMore>>
Huffman, G.J., Bolvin, D.T., Braithwaite, D., Hsu, K.L., Joyce, R.J., Kidd, C., et al. (2019). Integrated Multi-Satellite Retrievals for the Global Precipitation Measurement (GPM) Mission (IMERG). In: Levizzani, V., Kidd, C., Kirschbaum, D.B., Kummerow, C.D., Nakamura, K. and Turk, F.J., Eds., Satellite Precipitation Measurement, Springer, Cham, 343-353.
https://doi.org/10.1007/978-3-030-24568-9_19
has been cited by the following article:
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TITLE:
Hydrometeorological Modeling of Limpopo River Basin in Mozambique with TOPMODEL and Remote Sensing
AUTHORS:
Tomásio Eduardo Januário, Augusto José Pereira Filho, Marcos Figueiredo Salviano
KEYWORDS:
Floods Simulations, Limpopo River, TOPMODEL, CMORPH, IMERG
JOURNAL NAME:
Open Journal of Modern Hydrology,
Vol.12 No.2,
April
11,
2022
ABSTRACT: The Limpopo River basin (LRB) is known for its
vulnerability to floods, high rates of evapotranspiration, and droughts that
cause significant losses to the local community. The present study aimed to
perform simulations of flood events occurring in two Mozambican sub-basins of
LRB, namely Chókwè and Xai-Xai from 2000 to 2015 with
TOPography-based hydrological MODEL (TOPMODEL) and satellite remote sensing
data. As input in TOPMODEL, data from two high-resolution global
satellite-based precipitation products: Climate Prediction Center MORPHing
technique (CMORPH) and Integrated Multi-Satellite Retrievals for the Global
Precipitation Mission (GPM) algorithm (IMERG), 8-day MOD16 evapotranspiration
product and surface runoff data estimated by Global Land Data Assimilation
System (GLDAS) were used. The sensitivity tests of TOPMODEL parameters were applied
using the Monte Carlo simulation. Calibration and validation of the model were
performed by the Shuffled Complex Evolution (SCE-UA) method and were evaluated
with the Kling-Gupta Efficiency (KGE) index. The results indicated that
simulations with the GPM-IMERG (KGE: 0.59 and 0.65) tended to underestimate the
stream flows, while with the CMORPH product the performance was much better
(KGE: 0.66 and 0.77) in both sub-basins. Thus, TOPMODEL can help to develop
flood monitoring systems from satellite remotely sensed data in similar regions
of Mozambique.
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