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Articles

Different calibration procedures for flows estimation using SWAT model

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Pages 205-218 | Received 27 Mar 2019, Accepted 18 May 2020, Published online: 02 Jul 2020

References

  • Abbaspour KC. 2015. SWAT Calibration and Uncertainty Programs: A user manual.
  • 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. doi: 10.1016/j.jhydrol.2015.03.027
  • Abbaspour KC, Yang J, Maximov I, Siber R, Bogner K, Mieleitner J, Zobrist F, Srinivasan R. 2007. Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT. J Hydrol. 333(2-4):413–430. doi: 10.1016/j.jhydrol.2006.09.014
  • Abdelwahab OMM, Ricci GF, de Girolamo AM, Gentile F. 2018. Modelling soil erosion in a Mediterranean watershed: comparison between SWAT and ANNAGNPS models. Environ Res. 166:363–376. doi: 10.1016/j.envres.2018.06.029
  • Almeida R, Pereira SB, Daniel BFP. 2018. Calibration and validation of the SWAT hydrological model for the Mucuri river basin. Engenharia Agrícola. 38(1):55–63. doi: 10.1590/1809-4430-eng.agric.v38n1p55-63/2018
  • Almeida RF, Mamede MCH. 2014. Checklist, conservation status, and sampling effort analysis of Malpighiaceae in Espírito Santo State. Brazil Brazilian J. Bot. 37(3):329–337. doi: 10.1007/s40415-014-0078-x
  • Andrade MA, Mellon CR, Beskow S. 2013. Simulação hidrológica em uma bacia hidrográfica representativa dos latossolos na região Alto Rio Grande, MG [Hydrological simulation in a hydrographic basin representative of the latosols in the Alto Rio Grande region. MG]. Rev Bras Eng Agríc Ambient. 17(1):69–76. (In Portuguese). doi: 10.1590/S1415-43662013000100010
  • Arnold JG, Kiniry JR, Srinivasan R, Williams JR, Haney EB, Neitsch SL. 2012. Soil & Water Assessment Tool: Input/Output Documentation Version 2012.
  • Arnold JG, Moriasi DN, Gassman PW, Abbaspour KC, White MJ, Srinivasan R, Santhi C, Harmel RD, Van Griensven A, Van Liew MW, et al. 2012. SWAT: model use calibration and validation. Biol Eng Trans ASABE. 55(4):1491–1508. doi: 10.13031/2013.42256
  • Ayivi F, Jha MK. 2018. Estimation of water balance and water yield in the Reedy Fork-Buffalo Creek watershed in North Carolina using SWAT. Int Soil Water Conserv Res. 6(3):203–213. doi: 10.1016/j.iswcr.2018.03.007
  • Barbarotto Junior JL. 2014. Análise da disponibilidade hídrica da bacia do rio Jundiaí por meio de simulações hidrológicas de cenários prováveis [Analysis of the water availability of the Jundiaí river basin by means of hydrological simulations of probable scenarios]. Dissertation, University of Campinas (In Portuguese).
  • Baroni G, Zink M, Kumar R, Samaniego L, Attinger S. 2017. Effects of uncertainty in soil properties on simulated hydrological states and fluxes at different spatio-temporal scales. Hydrol Earth Syst Sci. 21(1):2301–2320. doi: 10.5194/hess-21-2301-2017
  • Beven KJ, Binley A. 1992. The future of distributed models: model calibration and uncertainty prediction. Hydrol Process. 6(3):279–298. doi: 10.1002/hyp.3360060305
  • Brighenti TM, Bonumá NB, Chaffe PLB. 2016. Calibração hierárquica do modelo SWAT em uma bacia hidrográfica Catarinense. Revista Brasileira de Recursos Hídricos. 21(1):53–64. doi: 10.21168/rbrh.v21n1.p53-64
  • Brouziyne Y, Abouabdillah A, Bouabid R, Benaabidate L, Oueslati O. 2017. SWAT manual calibration and parameters sensitivity analysis in a semi-arid watershed in North-western Morocco. Arab J Geosci. 10(19):1–13. doi: 10.1007/s12517-017-3220-9
  • Clark MP, Bierkens MFP, Samaniego L, Woods RA, Uijlenhoet R, Bennett KE, Pauwels VRN, Cai X, Wood AW, Lidard CDP. 2017. The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism. Hydrol Earth Syst Sci. 21:3427–3440. doi: 10.5194/hess-21-3427-2017
  • Collischonn W, Allasia D, da Silva BC, Tucci CEM. 2007. The MGB-IPH model for large-scale rainfall-runoff modelling. Hydrol. Sci. J. 52:878–895. doi: 10.1623/hysj.52.5.878
  • Deina MA, Coelho ALN. 2015. A influência da zona convergência do Atlântico Sul (ZCAS) nos eventos de inundação no baixo Jucu em Vila Velha (ES) [The influence of the South Atlantic Convergence Zone (SACZ) in Flood events in Baixo Jucu in Vila Velha (ES)]). Geografia. 24(2):5–23. (In Portuguese).
  • Devia GK, Ganasri BP, Dwarakish GS. 2015. A review on hydrological models. Aquatic Procedia. 4:1001–1007. doi: 10.1016/j.aqpro.2015.02.126
  • Durães MF, de Mello CR, Naghettini M. 2011. Applicability of the swat model for hydrologic simulation in Paraopeba River basin. MG Cerne. 17(4):481–488. doi: 10.1590/S0104-77602011000400006
  • EMBRAPA - Empresa Brasileira De Pesquisa Agropecuária. 1978. Levantamento de Reconhecimento dos Solos do Estado do Espírito Santo, 478. Rio de Janeiro: EMBRAPA. 478p. (In Portuguese).
  • Ercan MB, Goodall JL, Castronova AM, Humphrey M, Beekwilder N. 2014. Calibration of SWAT models using the cloud. Environ Modell Softw. 62(1):188–196. doi: 10.1016/j.envsoft.2014.09.002
  • Fatichi S, Vivoni ER, Ogden FL, Ivanov VY, Mirus B, Gochis D, Downer CW, Camporese M, Davison JH, Ebel B, et al. 2016. An overview of current applications, challenges, and future trends in distributed process-based models in hydrology. J Hydrol. 537:45–60. doi: 10.1016/j.jhydrol.2016.03.026
  • Feldman AD. 2000. Hydrologic Modeling System HEC-HMS, Technical Reference Manual. U.S. Army Corps of Engineers, Hydrologic Engineering Center, HEC, Davis, CA, USA.
  • Francesconi W, Srinivasan R, Pérez-Miñana E, Willcock S, Quintero M. 2016. Using the Soil and Water Assessment Tool (SWAT) to model ecosystem services: A systematic review. J Hydrol J Hydrol. 535:625–636. doi: 10.1016/j.jhydrol.2016.01.034
  • Franco ACL, Bonumá N. 2017. Multi-variable SWAT model calibration with remotely sensed evapotranspiration and observed flow. Revista Brasileira de Recursos Hídricos. 22:1–11.
  • Fukunaga DC. 2012. Estimação de vazão em bacias hidrográficas do sul do Espírito Santo usando o SWAT [Flow estimation in watersheds of southern region of Espírito Santo state using the SWAT]. Dissertation, Federal University of Espírito Santo. (In Portuguese).
  • Gassman P, Osei E, Saleh A, Rodecap J, Norvell S, Williams JR. 2006. Alternative practices for sediment and nutrient loss control on livestock farms in northeast Iowa. Agr Ecosyst Environ. 117(2-3):135–144. doi: 10.1016/j.agee.2006.03.030
  • Golmohammadi G, Rudra R, Dickinson T, Goel P, Veliz M. 2017. Predicting the temporal variation of flow contributing areas using SWAT. J Hydrol. 547:375–386. doi: 10.1016/j.jhydrol.2017.02.008
  • Gupta HV, Sorooshian S, Yapo PO. 1999. Status of Automatic calibration for hydrologic models: comparison with Multilevel Expert calibration. J Hydrol Eng. 4(2):135–143. doi: 10.1061/(ASCE)1084-0699(1999)4:2(135)
  • Gupta HV, Sorooshian S. 2017. Calibration and evaluation of watershed models. Chapter 61. In: Singh VP, editor. Handbook of applied hydrology. New York: McGraw-Hill; p. 61-1–61-11.
  • Hastings WK. 1970. Monte Carlo sampling methods using Markov chains and their applications. Biometrika. 57(1):97–109. doi: 10.1093/biomet/57.1.97
  • IEMA - Instituto Estadual de Meio Ambiente e Recursos Hídricos. 2015. Elaboração de projeto executivo para enquadramento dos corpos de água em classes e plano de bacia para os rios Santa Maria da Vitória e Jucu (Volume I) [Elaboration of an executive project for the water bodies classification and basin plan for the Santa Maria da Vitória and Jucu rivers (Volume I)], 284. Vitória: IEMA, 2015. 284 p. (In Portuguese).
  • Khalid K, Ali MF, Rahman A, Mispan MR. 2016. Application on one-at-a-time sensitivity analysis of semi-distributed hydrological model in tropical watershed. Int J Eng Technol. 8(2):132–136. doi: 10.7763/IJET.2016.V8.872
  • Kuwajima JI. 2012. Análise do modelo SWAT como ferramenta de prevenção e de estimativa de assoreamento no reservatório do lobo (Itirapina/Brotas/SP) [SWAT model analysis as tools for prevention and estimated siltation in the reservoir of the Lobo (Itirapina/Brotas/SP)]. Dissertation, UNiversity of São Paulo (In Portuguese).
  • Lamba J, Thompson AM, Karthikeyan AMKG, Panuska JC, Good LW. 2016. Effect of best management practice implementation on sediment and phosphorus load reductions at subwatershed and watershed scale using SWAT model. International J Sediment Res. 31(4):1–9. doi: 10.1016/j.ijsrc.2016.06.004
  • Lelis TA, Calijuri ML, Santiago AF, de Lima DC, Rocha EO. 2012. Análise de sensibilidade e calibração do modelo SWAT aplicado em bacia hidrográfica da região sudeste do Brasil [Sensitivity analysis and calibration of SWAT model applied to a watershead in southeastern Brazil]. Rev Bras Ciênc Solo. 36(2):623–634. (In Portuguese.). doi: 10.1590/S0100-06832012000200031
  • Malagó A, Bouraoui F, Vigiak O, Grizzetti B, Pastori M. 2017. Modelling water and nutrient fluxes in the Danube River Basin with SWAT. Sci Total Environ. 603-604:196–218. doi: 10.1016/j.scitotenv.2017.05.242
  • Martini AMZ, Fiaschi P, Amorim AM, Paixão JL. 2007. A hot-point within a hot-spot: a high diversity site in Brazil’s Atlantic Forest. Biodivers Conserv. 16(11):3111–3128. doi: 10.1007/s10531-007-9166-6
  • Mello Cd, Norton LD, Pinto LC, Beskow S, Curi N. 2016. Agricultural watershed modeling: a review for hydrology and soil erosion processes. Ciênc Agrotec. 40(1):7–25. doi: 10.1590/S1413-70542016000100001
  • Melo Neto JO. 2013. Análise de sensibilidade escalar do modelo hidrológico SWAT [Scale sensitivity analysis of the SWAT hydrological model]. Dissertation, Federal University of Lavras (In Portuguese).
  • Metcalf and Eddy, Inc., University of Florida and Water Resources Engineers, Inc. 1971. Storm water management model, vol 1-fnal report. EPA Report No. 11024DOV07/71 (NITS PB-203289), Environmental Protection Agency, Washington, D.C.
  • Moreira LL, Schwamback D, Rigo D. 2018. Sensitivity analysis of the Soil and Water Assessment Tools (SWAT) model in streamflow modeling in a rural river basin. Revista Ambiente & Água. 13(6):1–12. doi: 10.4136/ambi-agua.2221
  • Moriasi DN, Arnold JG, Van Liew MW, Bingner RL, Harmel RD, Veith TL. 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Am Soc Agr Biol Eng. 50(3):885–900.
  • Neitsch SL, Arnold GJ, Kiniry JR, Willians JR, King KW. 2011. Soil and water assessment tool: theoretical documentation version 2009.
  • Pereira DR. 2013. Simulação hidrológica na bacia hidrográfica do rio Pomba usando o modelo SWAT [Hydrological simulation in the watershed of the Pomba River using the SWAT model]. Teses, Federal University of Viçosa. (In Portuguese.).
  • Pinto DBF. 2011. Aplicação do modelo SWAT (Soil and Water Assessment Tool) na simulação hidrossedimentológica em bacia hidrográfica da Serra da Mantiqueira, MG [Application of the SWAT (Soil and Water Assessment Tool) model in the hydrosedimentological simulation in a watershed of Serra da Mantiqueira, MG]. Thesis, Federal University of Lavras (In Portuguese).
  • Pontes LM, Viola MR, Silva MLN, Bispo DFA, Curi N. 2016. Hydrological modeling of tributaries of Cantareira system, southeast Brazil, with the SWAT model. Eng Agríc. 36(6):1037–1049.
  • Santos C, Almeida C, Ramos T, Rocha FA, Neves R. 2018. Using a hierarchical approach to calibrate SWAT and predict the semi-arid hydrologic regime of Northeastern Brazil. Water. 10(9):1137–1154. doi: 10.3390/w10091137
  • Shivhare N, Dikshit PKS, Dwivedi SB. 2018. A comparison of swat model calibration techniques for hydrological modeling in the ganga river watershed. Eng. 4(5):643–652. doi: 10.1016/j.eng.2018.08.012
  • Silva Da RM, Dantas JC, Beltrão JA, Santos CAG. 2018. Hydrological simulation in a tropical humid basin in the Cerrado biome using the SWAT model. Hydrol Res. 49(3):908–923. doi: 10.2166/nh.2018.222
  • Silva MG, de Aguiar Netto AO, de Jesus Neves RJA, Do Vasco A, Almeida C, Faccioli GG. 2015. Sensitivity analysis and calibration of hydrological modeling of the watershed Northeast Brazil. J Environ Prot. 6:837–850. doi: 10.4236/jep.2015.68076
  • Silva MT, da Silva V, de PR, de Souza EP, Araújo AL. 2015. Aplicação do modelo SWAT na estimativa da vazão na bacia hidrográfica do submédio rio São Francisco [Application of the SWAT model in the estimation of flow in the São Francisco river basin]. Revista Brasileira de Geografia Física. 08(06):1615–1627. (In Portuguese ). doi: 10.5935/1984-2295.20150086
  • Singh VP. 2018. Hydrologic modeling: progress and future directions: progress and future directions. Geosci Lett. 5(1):1–18. doi: 10.1186/s40562-018-0101-3
  • Song X, Zhang J, Zhan C, Xuan Y, Ye M, Xu C. 2015. Global sensitivity analysis in hydrological modeling: review of concepts, methods, theoretical framework, and applications. J Hydrol. 523:739–757. doi: 10.1016/j.jhydrol.2015.02.013
  • Surfleet CG, Tullos D, Chang H, Jung I. 2012. Selection of hydrologic modeling approaches for climate change assessment: a comparison of model scale and structures. J Hydrol. 46:233–248. doi: 10.1016/j.jhydrol.2012.07.012
  • Taffarello D, Srinivasan R, Mohor GS, Calijuri MC, Mediondo ED. 2018. Modeling freshwater quality scenarios with ecosystem-based adaptation in the headwaters of the Cantareira system. Brazil Hydrol Earth Syst Sc. 22(9):4699–4723. doi: 10.5194/hess-22-4699-2018
  • Tarawneh E, Bridge J, Macdonald N. 2016. A pre-calibration approach to select optimum inputs for hydrological models in data-scarce regions. Hydrol Earth Syst Sci. 20:4391–4407. doi: 10.5194/hess-20-4391-2016
  • Thavhana MP, Savage MJ, Moeletsi ME. 2018. SWAT model uncertainty analysis, calibration and validation for runoff simulation in the Luvuvhu river catchment, South Africa. Phys Chem Earth. 105(6):115–124. doi: 10.1016/j.pce.2018.03.012
  • Tuo Y, Marcolini G, Disse M. 2018. A multi-objective approach to improve SWAT model calibration in alpine catchments. J Hydrol. 559:347–360. doi: 10.1016/j.jhydrol.2018.02.055
  • Van Griensven A, Meixner T, Grunwald S, Bishop T, Diluzio M, Srinivasan R. 2006. A global sensitivity analysis tool for the parameters of multi-variable catchment models. J Hydrol. 324:10–23. doi: 10.1016/j.jhydrol.2005.09.008
  • Woldesenbet TA, Elagib NA, Ribbe L, Heinrich J. 2018. Catchment response to climate and land use changes in the upper Blue Nile sub-basins, Ethiopia. Sci Total Environ. 644:193–206. doi: 10.1016/j.scitotenv.2018.06.198
  • Zadeh FK, Nossent J, Sarrazin D, Pianosi F, Griensven AV, Wagener T, Bauwens W. 2017. Comparison of variance-based and moment-independent global sensitivity analysis approaches by application to the SWAT model. Environ Modell Softw. 91(5):210–222. doi: 10.1016/j.envsoft.2017.02.001
  • Zhang D, Chen X, Yao H, James A. 2016. Moving SWAT model calibration and uncertainty analysis to an enterprise Hadoop-based cloud. Environ Modell Softw. 84:140–148. doi: 10.1016/j.envsoft.2016.06.024

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