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Open AccessArticle

Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling

1
Department of Civil Engineering, MVGR College of Engineering, Vizianagaram, Andhra Pradesh 535005, India
2
Department of Civil Engineering, Centurion University of Technology and Management, Bhubaneswar, Odisha 752050, India
3
Department of Biological Systems Engineering, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
4
GFZ German Research Centre for Geosciences, Section 4.4: Hydrology, Telegrafenberg, 14473 Potsdam, Germany
5
Department of Hydrology, Indian Institute of Technology, Roorkee, Uttarakhand 247667, India
*
Author to whom correspondence should be addressed.
Atmosphere 2020, 11(11), 1252; https://doi.org/10.3390/atmos11111252
Received: 13 October 2020 / Revised: 13 November 2020 / Accepted: 17 November 2020 / Published: 20 November 2020
Precipitation is essential for modeling the hydrologic behavior of watersheds. There exist multiple precipitation products of different sources and precision. We evaluate the influence of different precipitation product on model parameters and streamflow predictive uncertainty using a soil water assessment tool (SWAT) model for a forest dominated catchment in India. We used IMD (gridded rainfall dataset), TRMM (satellite product), bias-corrected TRMM (corrected satellite product) and NCEP-CFSR (reanalysis dataset) over a period from 1998–2012 for simulating streamflow. The precipitation analysis using statistical measures revealed that the TRMM and CFSR data slightly overestimate rainfall compared to the ground-based IMD data. However, the TRMM estimates improved, applying a bias correction. The Nash–Sutcliffe (and R2) values for TRMM, TRMMbias and CFSR, are 0.58 (0.62), 0.62 (0.63) and 0.52 (0.54), respectively at model calibrated with IMD data (Scenario A). The models of each precipitation product (Scenario B) yielded Nash–Sutcliffe (and R2) values 0.71 (0.76), 0.74 (0.78) and 0.76 (0.77) for TRMM, TRMMbias and CFSR datasets, respectively. Thus, the hydrological model-based evaluation revealed that the model calibration with individual rainfall data as input showed increased accuracy in the streamflow simulation. IMD and TRMM forced models to perform better in capturing the streamflow simulations than the CFSR reanalysis-driven model. Overall, our results showed that TRMM data after proper correction could be a good alternative for ground observations for driving hydrological models. View Full-Text
Keywords: parameter and prediction uncertainty; IMD; TRMM; CFSR; Nagavali River Basin Region (NRB) parameter and prediction uncertainty; IMD; TRMM; CFSR; Nagavali River Basin Region (NRB)
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MDPI and ACS Style

Setti, S.; Maheswaran, R.; Sridhar, V.; Barik, K.K.; Merz, B.; Agarwal, A. Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling. Atmosphere 2020, 11, 1252. https://doi.org/10.3390/atmos11111252

AMA Style

Setti S, Maheswaran R, Sridhar V, Barik KK, Merz B, Agarwal A. Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling. Atmosphere. 2020; 11(11):1252. https://doi.org/10.3390/atmos11111252

Chicago/Turabian Style

Setti, Sridhara; Maheswaran, Rathinasamy; Sridhar, Venkataramana; Barik, Kamal K.; Merz, Bruno; Agarwal, Ankit. 2020. "Inter-Comparison of Gauge-Based Gridded Data, Reanalysis and Satellite Precipitation Product with an Emphasis on Hydrological Modeling" Atmosphere 11, no. 11: 1252. https://doi.org/10.3390/atmos11111252

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