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Evaluation of gridded meteorological datasets and their potential hydrological application to a humid area with scarce data for Pirapama River basin, northeastern Brazil

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Abstract

This work evaluated the simulation of streamflow using observed and estimated gridded meteorological datasets and the Soil and Water Assessment Tool (SWAT) model for a humid area with scarce data in northeastern Brazil. The coefficient of determination (R2), Nash-Sutcliffe efficiency (NS), root mean square error (RMSE), normalized root mean square error (NRMSE), and percent bias (PBIAS) were used to assess the SWAT results yielded by estimated and observed rainfall data. The hydrological modeling data from three streamflow stations were used (2000 to 2006 for calibration and 2007 to 2010 for validation). The results show that at daily scale, the estimated rainfall data show a poor agreement (R2 ranging from 0.22 to 0.04) with the observed rainfall but good agreement at monthly (R2 = 0.85) and annual scales (R2 = 0.80). The results showed that estimated accumulated precipitation overestimated the observed data. The results showed that R2 ranged from 0.51 to 0.55 at monthly scale and 0.44-0.52 at annual scale. However, the global data can represent well the variability of rainfall within the region. The results indicated a good correlation in the seasonal variability (R2 ranged from 0.72 to 0.60). The modeling results using monthly TRMM data and observed rainfall data showed good values of NS and R2 during calibration and validation, but PBIAS was unsatisfactory for the three streamflow gauges. The streamflow estimates from the SWAT model using data from the TRMM satellite showed that such data are capable of generating satisfactory results after calibration, although measured rainfall data presented better results; the data could support areas with scarce rainfall data and be applied to other river basins, for example, to analyze the hydrological potential of other basins in the coastal region of northeastern Brazil. Over the past three decades, considerable advances have been made in remote sensing with environmental satellites, increasing the amount of information available, including rainfall estimates. In this context, the use of TRMM data to estimate rainfall has ultimately been shown to be an interesting alternative for areas with scarce rainfall data.

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Data availability

The data about the obtained results will be available (by the corresponding author) upon reasonable requests. The observational and estimated data analyzed in this study may be obtained through the following links:

TRMM

Earth Observing System Data and Information

https://disc.gsfc.nasa.gov

CFSR

Climate Forecast System Reanalysis

https://globalweather.tamu.edu

Streamflow data and rain gauge-measured rainfall data

National Hydrometeorological System

http://www.snirh.gov.br/hidroweb

Meteorological data

Brazilian National Institute of Meteorology

https://tempo.inmet.gov.br/

DEM

United States Geological Service

https://earthexplorer.usgs.gov

Land use and land cover

United States Geological Service

https://glovis.usgs.gov

Report of water resources situation in the state of Pernambuco

https://www.apac.pe.gov.br/images/media/1569522441_PERHPE_volume1.pdf

Soil types

National Program of Brazilian Soils

https://geoportal.cprm.gov.br/pronasolos

Soil parameters

Brazilian Soil Information System

http://www.sisolos.cnptia.embrapa.br

References

  • Abbaspour KC (2012) SWAT-CUP 2012: SWAT Calibration and Uncertainty Programs – a user manual. In: Department of Systems Analysis, Integrated Assessment and Modelling (SIAM). Eawag, Swiss Federal Institute of Aquatic Science and Technology, Duessendorf, Switzerland, p 103p

    Google Scholar 

  • Abbaspour KC, Yang J, Maximov I, Siber R, Bogner K, Mieleitner J, Zobrist J, Srinivasan R (2007) Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. J Hydrol 333:413–430

    Article  Google Scholar 

  • Abbaspour KC, Rouholahnejad E, Vaghefi S, Srinivasan R, Yang H, Kløve B (2015) A continental-scale hydrology and water quality model for Europe: Calibration and uncertainty of a high-resolution large-scale SWAT model. J Hydrol 524:733–752

    Article  Google Scholar 

  • ANA – Agência Nacional de Águas (2019). Atlas Brasil: Abastecimento urbano de água. Available in: http://atlas.ana.gov.br/atlas.

  • Andrade CWL, Montenegro SMGL, Montenegro AAA, Lima JR de S, Srinivasan R, Jones CA (2021) Climate change impact assessment on water resources under RCP scenarios: A case study in Mundaú River Basin, Northeastern Brazil. Int J Climatol 41(S1):E1045–E1061. https://doi.org/10.1002/joc.6751

  • Andrade CWL, Montenegro SMGL, Montenegro AAA, Lima JRS, Srinivasan R, Jones C (2019) A. Soil moisture and discharge modeling in a representative watershed in northeastern Brazil using SWAT. Ecohydrol Hydrobiol 19(2):238–251

    Article  Google Scholar 

  • Anjum MN, Ding Y, Shangguan D, Ahmad I, Ijaz MW, Farid HU, Yagoun YE, Zaman M, Adnan M (2018) Performance evaluation of latest integrated multi-satellite retrievals for Global Precipitation Measurement (IMERG) over the northern highlands of Pakistan. Atmos Res 205:134–146. https://doi.org/10.1016/j.atmosres.2018.02.010

  • Aouissi J, Benabdallah S, Chabaâne ZL, Cudennecc C (2019) Evaluation of potential evapotranspiration assessment methods for hydrological modelling with SWAT—Application in data-scarce rural Tunisia. Agric Water Manag 174(1):39–51

    Google Scholar 

  • APAC – Agência Pernambucana de Águas e Climas (2013). Pernambuco State Water Resources Status Report 2011/2012 – Recife: 2013

  • Arnold JG, Srinivasan R, Muttiah RS, Williams JR (1998) Large area hydrologic modeling and assessment – part I: model development. J Am Water Resour Assoc 34(1):73–89

    Article  Google Scholar 

  • Arnold JG, Moriasi DN, Gassman PW, Abbaspour KC, White MJ, Srinivasan R, Santhi C, Harmel RD, Van Griensven A, Van Liew MW, Kannan N, Jha MK (2012) SWAT: model use, calibration, and validation. Trans ASABE 55(4):1491–1508

    Article  Google Scholar 

  • Baker TJ, Miller SN (2013) Using the Soil and Water Assessment Tool (SWAT) to assess land use impact on water resources in an East African watershed. J Hydrol 486:100–111

    Article  Google Scholar 

  • Bernardi ECS (2016). Qualidade das estimativas de precipitação do satélite TRMM no estado do Rio Grande do Sul. 2016. Ph.D. Dissertation, Universidade Federal de Santa Maria, Rio Grande do Sul

  • Bitew MM, Gebremichael M (2012) Evaluation of high-resolution satellite rainfall products through streamflow simulation in a hydrological modeling of a small mountainous watershed in Ethiopia. J Hydrometeorol 13:338–350

    Article  Google Scholar 

  • Bonumá NB, Reichert JM, Rodrigues MF, Monteiro JAF, Arnold JG, Srinivasan R (2015) Modeling surface hydrology, soil erosion, nutrient transport, and future scenarios with the ecohydrological SWAT model in Brazilian watersheds and river basins. Tópicos de Ciência do Solo 9:241–290

    Google Scholar 

  • Braga ACFM, Silva RM, Santos CAG, Galvão CO, Nobre P (2013) Downscaling of a global climate model for estimation of runoff, sediment yield and dam storage: A case study of Pirapama basin, Brazil. J Hydrol 498(1):46–58

    Article  Google Scholar 

  • Brasil Neto RM, Santos CAG, Silva JFCBC, Silva RM, Santos CAC, Mishra M (2021) Evaluation of the TRMM product for monitoring drought over Paraíba State, northeastern Brazil: A trend analysis. Sci Rep 11:286–296

    Article  Google Scholar 

  • Bressiani DA, Srinivasan R, Jones CA, Mendiondo EM (2015) Effects of different spatial and temporal weather data resolutions on the streamflow modeling of a semi-arid basin, Northeast Brazi. Int J Agric Biol 8(3):125–139

    Google Scholar 

  • Brighenti TM, Bonumá NB, Grison F, Mota AA, Kobiyama M, Chaffe PLB (2019) Two calibration methods for modeling streamflow and suspended sediment with the swat model. Ecol Eng 127:103–113

    Article  Google Scholar 

  • Brito CS, Silva RM, Santos CAG, Brasil Neto RM, Coelho VHR (2021) Monitoring meteorological drought in a semiarid region using two long-term satellite-estimated rainfall datasets: A case study of the Piranhas River basin, northeastern Brazil. Atmos Res 250:105380

    Article  Google Scholar 

  • Carvalho LMT, Clevers JGPW, Skidmore AK, de Jong SM (2004) Selection of imagery data and classifiers for mapping Brazilian semideciduous Atlantic forests. Int J Appl Earth Obs Geoinf 5(3):173–186. https://doi.org/10.1016/j.jag.2004.02.002

  • Congalton, RG, Green, K. (2009). Assessing the accuracy of remotely sensed data: principles and practices. Principles and Practices. New York: Lewis Publishers, 2 ed., 179p

  • CPRH – Companhia Pernambucana de Meio Ambiente (1998). Sistema de informações socioeconômicas da bacia do Prapama. Recife: Companhia Pernambucana de Meio Ambiente. Available in: http://www.cprh.pe.gov.br/downloads/sisapmanual.pdf

  • CPRH – Companhia Pernambucana de Meio Ambiente (2003). Diagnóstico socioambiental do Litoral Sul de Pernambuco. Recife, 2003.

  • Cunha ER, Santos CAG, Silva RM, Bacani VM, Pott A (2021) Future scenarios based on a CA-Markov land use and land cover simulation model for a tropical humid basin in the Cerrado/Atlantic forest ecotone of Brazil. Land Use Policy 101:105141

    Article  Google Scholar 

  • Daggupati P, PAI N, Douglas-Mankin KR, Zeckoski RW, Jeong J, Parajuli PB, Saraswat D, Youssef MA (2015) A recommended calibration and validation strategy for hydrologic and water quality models. Trans ASABE 58:1705–1719

    Article  Google Scholar 

  • De Almeida KN, Dos Reis JAT, Buarque DC, Mendonça ASF, Rodrigues MB, Sá GLN (2020) Performance analysis of TRMM satellite in precipitation estimation for the Itapemirim River basin, Espirito Santo state. Theoretical and Applied Climatology, Brazil

    Book  Google Scholar 

  • De Medeiros IC, Da Costa SJFCB, Silva RM, Santos CAG (2018) Run-off-erosion modelling and water balance in the Epitácio Pessoa Dam River basin, Paraíba State in Brazil. Int J Environ Sci Technol 15:1–14

    Google Scholar 

  • Dile YT, Srinivasan R (2014) Evaluation of CFSR climate data for hydrologic prediction in data-scarce watersheds: an application in the Blue Nile river basin. J Am Water Resour Assoc 50(5):1226–1241

    Article  Google Scholar 

  • Dinku T, Ceccato P, Grover-Kopec E, Lemma M, Connor SJ, Ropelewski CF (2007) Validation of high-resolution satellite rainfall products over complex terrain. Int J Remote Sens 29(14):4097–4110

    Article  Google Scholar 

  • Duan Z, Tuo Y, Liu J, Gao H, Song X, Zhang Z, Yang L, Mekonnen DF (2019) Hydrological evaluation of open-access precipitation and air temperature datasets using SWAT in a poorly gauged basin in Ethiopia. J Hydrol 569:612–626

    Article  Google Scholar 

  • EMBRAPA – Empresa Brasileira de Agropecuária (2013). Sistema Brasileiro de Classificação dos Solos. 3. ed. Rio de Janeiro: EMBRAPA, 2013

  • Essou GR, Brissette F, Lucas-Picher P (2017) Impacts of combining reanalyses and weather station data on the accuracy of discharge modelling. J Hydrol 545:120–131

    Article  Google Scholar 

  • Faramarzi M, Srinivasan R, Iravani M, Bladon KD, Abbaspour KC, Zehnder AJB, Goss GG (2015) Setting up a hydrological model of Alberta: Data discrimination analyses prior to calibration. Environ Model Softw 74:48–65

    Article  Google Scholar 

  • Fedorova N, Levit V, Cruz C (2016) On Frontal Zone Analysis in the Tropical Region of the Northeast Brazil. Pure Appl Geophys 173(4):1403–1421

    Article  Google Scholar 

  • Ferreira da Silva GJ, De Oliveira NM, Santos CAG, Da Silva RM (2020) Spatiotemporal variability of vegetation due to drought dynamics (2012-2017): a case study of the Upper Paraíba River basin, Brazil. Nat Hazards 102:939–964

    Article  Google Scholar 

  • Florencio L, Kato MT, De Lima ES (2001) Integrated measures for preservation, restoration and improvement of the environmental conditions of the Lagoon Olho d’Água basin. Environ Int 26(7-8):551–555

    Article  Google Scholar 

  • Franchito SH, Rao V, Vasques A, Santo C, Conforte JC (2009) Validation of TRMM precipitation radar monthly rainfall estimates over Brazil. J Geophys Res 114(D2):1–9

    Google Scholar 

  • Fuka DR, Walter MT, MacAlister C, Degaetano AT, Steenhuis TS, Easton ZM (2014) Using the climate forecast system reanalysis as weather input data for watershed models. Hydrol Process 18(22):5613–5623

    Article  Google Scholar 

  • Gadelha AN, Coelho VHR, Xavier AC, Barbosa LR, Melo DCD, Xuan Y, Huffman GJ, Petersen WA, Almeida CN (2019) Grid box-level evaluation of IMERG over Brazil at various space and time scales. Atmos Res 218:231–244

    Article  Google Scholar 

  • Gajbhiye S, Mishra SK, Pandey A (2014) Hypsometric analysis of Shakkar river catchment through geographical information system. J Geol Soc India 84:192–196

    Article  Google Scholar 

  • Green CH, Van Griensven A (2008) Autocalibration in hydrologic modeling: Using SWAT2005 in small-scale watersheds. Environ Model Softw 23(4):422–434

    Article  Google Scholar 

  • Green CH, Tomer MD, Di Luzio M, Arnold JG (2006) Hydrologic evaluation of the Soil and Water Assessment Tool for a large tile-drained watershed in Iowa. Trans ASABE 49(2):413–422

    Article  Google Scholar 

  • Huffman GJ, Bolvin DT (2013) TRMM and Other Data Precipitation Data Set Documentation. NASA, Green belt, MD, USA

    Google Scholar 

  • Huffman GJ, Bolvin DT, Adler RF, Gu G (2007) The TRMM Multi-satellite Precipitation Analysis: Quasi-Global, Multi Year, Combined-Sensor Precipitation Estimates at Fine Scale. J Hydrometeorol 8(1):38–55

    Article  Google Scholar 

  • IBGE – Instituto Brasileiro de Geografia e Estatística (2010). Censo Demográfico 2010. IBGE: Rio de Janeiro, 2010. Available at: http://www.ibge.gov.br/home/estatistica/populacao/censo2010/sinopse/sinopse_tab_rm_zip.shtm. Accessed on 2020 October 27

  • Jiang Q, Wen J, Qiu C, Sun W, Fang Q, Xu M, Tan J (2018) Accuracy evaluation of two high-resolution satellite-based rainfall products: TRMM 3B42V7 and CMORPH in Shanghai. Water 10(1):40

    Article  Google Scholar 

  • Kiany MSK, Balling RC, Cerveny RS, Krahenbuhl DS (2018) Diurnal variations in seasonal precipitation in Iran from TRMM measurements. Adv Space Res 62(9):2418–2430

    Article  Google Scholar 

  • Li D, Christakos G, Ding X, Wu J (2018) Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu lake basin, China). J Hydrol 556:1139–1152

    Article  Google Scholar 

  • Lima CES, Costa VSO, Galvíncio JD, Silva RM, Santos CAG (2021) Assessment of automated evapotranspiration estimates obtained using the GP-SEBAL algorithm for dry forest vegetation (Caatinga) and agricultural areas in the Brazilian semiarid region. Agric Water Manag 250:106863

    Article  Google Scholar 

  • Mararakanye N, Le Roux JJ, Franke AC (2020) Using satellite-based weather data as input to SWAT in a data poor catchment. Physics and Chemistry of the Earth, Parts A/B/C 117:102871

    Article  Google Scholar 

  • Meshram SG, Sharma SK (2017) Prioritization of watershed through morphometric parameters: a PCA-based approach. Appl Water Sci 7:1505–1519

    Article  Google Scholar 

  • Monteiro JAF, Strauch M, Srinivasan R, Abbaspour K, Gücker B (2015) Accuracy of grid precipitation data for Brazil: application in river discharge modeling of the Tocantins catchment. Hydrol Process 30(9):1419–1430

    Article  Google Scholar 

  • Moriasi DN, Arnold JG, Van Liew MW, Binger RL, Harmel RD, Veith T (2007) Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Trans ASABE 50(3):885–900

    Article  Google Scholar 

  • Musie M, Sen S, Srivastava P (2019) Comparison and evaluation of gridded precipitation datasets for streamflow simulation in data scarce watersheds of Ethiopia. J Hydrol 579:124168

    Article  Google Scholar 

  • Nastos PT, Kapsomenakis J, Philandras KM (2016) Evaluation of the TRMM 3B43 gridded precipitation estimates over Greece. Atmos Res 169:497–514

    Article  Google Scholar 

  • Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2011) Soil and Water Assessment Tool –theoretical documentation Version 2009. Agricultural Research Service Blackland Research Center – Texas Agrilife Research. Texas A&M University System

  • Ochoa A, Pineda L, Crespo P, Willems P (2014) Evaluation of TRMM 3B42 precipitation estimates and WRF retrospective precipitation simulation over the Pacific–Andean region of Ecuador and Peru. Hydrol Earth Syst Sci 18(8):3179–3193

    Article  Google Scholar 

  • Oliveira PTS, Nearing MA, Moran MS, Goodrich DC, Wendland E, Gupta HV (2014) Trends in water balance components across the Brazilian Cerrado. Water Resour Res 50(9):7100–7114

    Article  Google Scholar 

  • Ouatiki H, Boudhar A, Tramblay Y, Jarlan L, Benabdelouhab T, Hanich L, Meslouhi MR, Chehbouni A (2017) Evaluation of TRMM 3B42 V7 rainfall product over the Oum Er Rbia watershed in Morocco. Climate 5:1

    Article  Google Scholar 

  • Pereira G, Silva MES, Moraes EC, Cardozo FS (2013) Avaliação dos dados de precipitação estimados pelo satélite TRMM para o Brasil. Rev Bras Recur Hidr 18(3):139–148

    Google Scholar 

  • Pereira DR, Martinez MA, de Almeida AQ, Pruski FF, da Silva DD, Zonta JH (2014) Hydrological simulation using SWAT model in headwater basin in Southeast Brazil. Engenharia Agrícola 34:789–799

    Article  Google Scholar 

  • Pereira DR, Martinez MA, da Silva DD, Pruski FF (2016a) Hydrological simulation in a basin of typical tropical climate and soil using the SWAT Model Part II: simulation of hydrological variables and soil use scenarios. Journal of Hydrology: Regional Studies 5(2):149–163

    Google Scholar 

  • Pereira DR, Martinez MA, Pruski FF, da Silva DD (2016b) Hydrological simulation in a basin of typical tropical climate and soil using the SWAT model Part I: calibration and validation tests. Journal of Hydrology: Regional Studies 7(1):14–37

    Google Scholar 

  • Pinto DBF, Silva AM, Beskow S, Mello CR, Coelho G (2013) Application of the Soil and Water Assessment Tool (SWAT) for sediment transport simulation at a headwater watershed in Minas Gerais state, Brazil. Trans ASABE 56:697–709

    Article  Google Scholar 

  • Pombo S, de Oliveira RP (2015) Evaluation of extreme precipitation estimates from TRMM in Angola. J Hydrol 523:663–679

    Article  Google Scholar 

  • Ren P, Li J, Feng P, Guo Y, Ma Q (2018) Evaluation of multiple satellite precipitation products and their use in hydrological modelling over the Luanhe River Basin, China. Water 10(6):677

    Article  Google Scholar 

  • Rouholahnejad E, Abbaspour KC, Vejdani M, Srinivasan R, Schulin R, Lehmann A (2012) A parallelization framework for calibration of hydrological models. Environ Model Softw 31(1):28–36

    Article  Google Scholar 

  • Saha S, Moorthi S, Pan HL, Wu X, Wang J, Nadiga S, Tripp P, Kistler R, Woollen J, Behringer D, Liu H, Stokes D, Grumbine R, Gayno G, Wang J, Hou YT, Chuang HY, Juang HMH, Sela J, Iredell M, Treadon R, Kleist D, van Delst P, Keyser D, Derber J, Ek M, Meng J, Wei H, Yang R, Lord S, van den Dool H, Kumar A, Wang W, Long C, Chelliah M, Xue Y, Huang B, Schemm JK, Ebisuzaki W, Lin R, Xie P, Chen M, Zhou S, Higgins W, Zou CZ, Liu Q, Chen Y, Han Y, Cucurull L, Reynolds RW, Rutledge G, Goldberg M (2010) The NCEP Climate Forecast System Reanalysis. Bulletin of the American Meteorological 91:1015–1057

    Article  Google Scholar 

  • Santhi C, Arnold JG, Williams JR, Dugas WA, Srinivasan R, Hauck LM (2001) Validation of the SWAT model on a large river basin with point and nonpoint sources. J Am Water Resour Assoc 37:169–1188

    Article  Google Scholar 

  • Santos CAG, Silva RM (2007) Application of the hydrological model AÇUMOD based on GIS for water resources management of Pirapama River, Pernambuco, Brazil. Revista Ambiente & Água 2(1):1–14

    Google Scholar 

  • Santos JYG, Da Silva RM, Carvalho Neto JG, Montenegro SMGL, Santos CAG, Silva AM (2014) Assessment of land-use change on streamflow using GIS, remote sensing and a physically-based model, SWAT. Proceedings of the International Association of Hydrological Sciences 364:38–43. https://doi.org/10.5194/piahs-364-38-2014

  • Santos JYG, Silva RM, Carvalho Neto JG, Montenegro SMGL, Santos CAG, Silva AM (2015) Land cover and climate change effects on streamflow and sediment yield: a case study of Tapacurá River basin, Brazil. Proceedings of the International Association of Hydrological Sciences 371:189–193

    Article  Google Scholar 

  • Santos CAG, Brasil Neto RM, Passos JSA, Da Silva RM (2017) Drought assessment using a TRMM-derived standardized precipitation index for the upper São Francisco River basin, Brazil. Environ Monit Assess 189:250–278

    Article  Google Scholar 

  • Santos CAG, Brasil Neto RM, Santos DC, Silva RM (2018a) Innovative approach for geospatial drought severity classification: a case study of Paraíba state, Brazil. Stoch Env Res Risk A 32(12):1–18

    Google Scholar 

  • Santos CAG, Brasil Neto RM, Da Silva RM, Passos JSA (2018b) Integrated spatio temporal trends using TRMM 3B42 data for the Upper São Francisco River basin, Brazil. Environ Monit Assess 190:175–195

    Article  Google Scholar 

  • Santos CAG, Brasil Neto R, Da Silva RM, Costa S (2019a) Cluster Analysis Applied to Spatiotemporal Variability of Monthly Precipitation over Paraíba State Using Tropical Rainfall Measuring Mission (TRMM) Data. Remote Sens 11:637–655

    Article  Google Scholar 

  • Santos CAG, Freire PKMM, Silva RM, Akrami AS (2019b) Hybrid Wavelet Neural Network Approach for Daily Inflow Forecasting Using Tropical Rainfall Measuring Mission Data. J Hydrol Eng 24:04018062

    Article  Google Scholar 

  • Santos CAG, Brasil Neto RM, Nascimento TVM, Silva RM, Mishra M, Frade TG (2021a) Geospatial drought severity analysis based on PERSIANN-CDR-estimated rainfall data for Odisha state in India (1983-2018). Sci Total Environ 750:141258

    Article  Google Scholar 

  • Santos JYG, Montenegro SMGL, Silva RM, Santos CAG, Quinn NW, Xavier APC, Ribeiro Neto A (2021b). Modeling the impacts of future LULC and climate change on runoff and sediment yield in a strategic basin in the Caatinga/Atlantic forest ecotone of Brazil. Catena, 202.

  • Silva RM, Santos CAG, Silva VCL, Silva LP (2013) Erosivity, surface runoff, and soil erosion estimation using GIS-coupled runoff-erosion model in the Mamuaba catchment, Brazil. Environ Monit Assess 185(11):8977–8990

    Article  Google Scholar 

  • Silva RM, Beltrão J, Dantas JC, Santos CAG (2018) Hydrological simulation in a tropical humid basin in the Cerrado biome using the SWAT model. Hydrol Res 49:908–923

    Article  Google Scholar 

  • Soares Cruz MA, Rocha LT, Aragão R, Almeida AQ (2018) Applicability of TRMM precipitation for hydrologic modeling in a basin in the Northeast Brazilian Agreste. Revista Brasileira de Meteorologia 33(1):57–64

    Article  Google Scholar 

  • Soares ASD, da Paz AR, Piccilli DGA (2016) Assessment of rainfall estimates of TRMM satellite on Paraíba state. Rev Bras Recur Hidr 21(2):288–299

    Google Scholar 

  • Stretta C (2000). Hydrodynamic modelling of the Pirapama estuarine system after upstream regulation. Rapport INPT/ENSEEIHT

  • Tapiador FJ, Turk FJ, Petersen W, Hou AY, García-Ortega E, Machado LA, Angelis CF, Salio P, Kidd C, Huffman GJ (2012) Global precipitation measurement: methods, datasets and applications. Atmos Res 104:70–97

    Article  Google Scholar 

  • Tekeli AE, Fouli H (2016) Evaluation of TRMM satellite-based precipitation indexes for flood forecasting over Riyadh City, Saudi Arabia. J Hydrol 541:471–479

    Article  Google Scholar 

  • Tobin KJ, Bennett ME (2014) Satellite precipitation products and hydrologic applications. Water Int 39(3):360–380

    Article  Google Scholar 

  • Viana JFS, Montenegro SMGL, Silva BB, SILVA RM, Srinivasan R (2019) SWAT parameterization for identification of critical erosion watersheds in the Pirapama River basin, Brazil. J Urban Environ Eng 13(1):42–58

    Article  Google Scholar 

  • Worqlul AW, Yen H, Collick AS, Tilahun SA, Langan S, Steenhuis TS (2017) Evaluation of CFSR, TMPA 3B42 and ground-based rainfall data as input for hydrological models, in data-scarce regions: The upper Blue Nile Basin, Ethiopia. Catena 152:242–251

    Article  Google Scholar 

  • Yang Y, Wang G, Wang L, Yu J, Xu Z (2014) Evaluation of gridded precipitation data for driving SWAT model in area upstream of Three Gorges Reservoir. PLoS One 9(11):e112725

    Article  Google Scholar 

  • Yang Y, Tang G, Lei X, Hong Y, Yang N (2018) Can satellite precipitation products estimate probable maximum precipitation: a comparative investigation with gauge data in the Dadu River basin. Remote Sens 10(1):41

    Google Scholar 

  • Zeiger SJ, Hubbart JA (2018) Assessing environmental flow targets using pre-settlement land cover: a SWAT modeling application. Water 10:791

    Article  Google Scholar 

  • Zhang X, Srinivasan R, Van Liew M (2009) Approximating swat model using artificial neural network and support vector machine. J Am Waterworks Ass 45(2):460–474. https://doi.org/10.1111/j.1752-1688.2009.00302.x

  • Zhang G, Su X, Ayantobo OO, Feng K, Guo J (2020) Remote-sensing precipitation and temperature evaluation using soil and water assessment tool with multiobjective calibration in the Shiyang River Basin, Northwest China. J Hydrol 590:125416

    Article  Google Scholar 

  • Zhu H, Li Y, Huang Y, Li Y, Hou C, Shi X (2018) Evaluation and hydrological application of satellite-based precipitation datasets in driving hydrological models over the Huifa River basin in Northeast China. Atmos Res 207(1):28–41

    Article  Google Scholar 

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Acknowledgements

The authors thank Agência Nacional de Águas—ANA (Brazil), Instituto Nacional de Meteorologia—INMET (Brazil), National Centers for Environmental Prediction—NCEP (USA), and National Aeronautics and Space Administration—NASA (USA) for providing the input data.

Code availability

The SWAT model is available at https://swat.tamu.edu/.

Funding

This study was financially supported by CAPES, CNPq, and FACEPE for granting doctoral, sandwich doctorate, and postdoctoral scholarships. This study was also financed in part by the Texas A&M University, the SUPER project funded by CNPq (Proc. 446254/2015) and the CNPq Universal Announcement Project (Proc. 448236/2014-1) for the PQ (Productivity and Research) grants to the second, third, fourth, and sixth authors, Universal MCTIC/CNPq 28/2018 and the PEGASUS project MCTI/CNPq N° 19/2017 (Proc. 441305/2017-2), and CAPES/ANA 19/2015 (Proc. 88887.115873/2015-01).

Author information

Authors and Affiliations

  1. Department of Civil Engineering, Federal University of Pernambuco, Recife, Pernambuco, Brazil

    Jussara Freire de Souza Viana & Suzana Maria Gico Lima Montenegro

  2. Department of Meteorology, Federal University of Campina Grande, Campina Grande, Paraíba, Brazil

    Bernardo Barbosa da Silva

  3. Department of Geosciences, Federal University of Paraíba, João Pessoa, Paraíba, Brazil

    Richarde Marques da Silva

  4. Ecosystem Sciences and Management and Biological and Agricultural Engineering Departments, Texas A&M University, College Station, TX, USA

    Raghavan Srinivasan

  5. Department of Civil and Environmental Engineering, Federal University of Paraíba, João Pessoa, Paraíba, 58051-900, Brazil

    Celso Augusto Guimarães Santos & Clara Gadelha Tavares

  6. Department of Agricultural Engineering, Federal Rural University of Pernambuco, Recife, Pernambuco, 52171-900, Brazil

    Diego Cezar dos Santos Araujo

Authors
  1. Jussara Freire de Souza Viana
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  2. Suzana Maria Gico Lima Montenegro
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  3. Bernardo Barbosa da Silva
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  4. Richarde Marques da Silva
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  5. Raghavan Srinivasan
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  6. Celso Augusto Guimarães Santos
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  7. Diego Cezar dos Santos Araujo
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  8. Clara Gadelha Tavares
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Contributions

RMS and JFdSV designed the research; CAGS, RMS, JFdSV, and DCdSA wrote the original draft; SMGLM, BBdS, RS, RMS, CGT, and CAGS performed the manuscript review and editing; CAGS, SMGLM, and RMS provided funding acquisition, project administration, and resources; and CAGS, JFdSV, and RMS wrote the final paper.

Corresponding author

Correspondence to Celso Augusto Guimarães Santos.

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Viana, J.F.d., Montenegro, S.M.G.L., da Silva, B.B. et al. Evaluation of gridded meteorological datasets and their potential hydrological application to a humid area with scarce data for Pirapama River basin, northeastern Brazil. Theor Appl Climatol 145, 393–410 (2021). https://doi.org/10.1007/s00704-021-03628-7

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  • DOI: https://doi.org/10.1007/s00704-021-03628-7

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