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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:

• 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.