Technical Papers
May 18, 2018

Lumped versus Distributed Hydrological Modeling of the Jacaré-Guaçu Basin, Brazil

Publication: Journal of Environmental Engineering
Volume 144, Issue 8

Abstract

The study aims to understand when the effort required to run a distributed and detailed water balance model leads to effective better results, when compared with a lumped, data-parsimonious, and easier-to-apply hydrological model. The study compares the results obtained from a lumped hydrological model with the results from soil water assessment tool (SWAT) when used to estimate stream flow values from precipitation and climate data. Both models use the curve number (CN) concept, determined from land use, soil hydrologic group, and antecedent soil moisture conditions, and were run with a daily time step. The lumped model input variables and parameters are considered to be uniformly distributed throughout the watershed, while the SWAT model requires an extensive and detailed spatial data, including weather data (rainfall, temperature, humidity, wind, and solar radiation), physical characteristics of the basin (topography and drainage network), as well as soil and land use data. The effort required to fully understand SWAT formulation, to obtain the needed data and to calibrate the model, is time consuming and does not lead to significant better results, when compared with the lumped model results. The results confirm that in many situations, the simpler lumped model leads to reliable values of hydrological variables, both at a daily and monthly scale. The models’ predictability power is higher at a monthly time step, because both models fail to reproduce the daily flow values fully in a consistent way, although they are able to reproduce the overall variability. Lack of data to describe the precipitation accurately may explain the poorer model performance at the daily time step. The study concludes that when available data fail to represent the spatial distribution of the input variables and model parameters, there is little advantage in using the more complex distributed model.

Get full access to this article

View all available purchase options and get full access to this article.

References

Abbaspour, K. C., M. Vejdani, S. Haghighat, and J. Yang. 2007a. “SWAT-CUP calibration and uncertainty programs for SWAT.” In MODSIM 2007 Int. Congress on Modelling and Simulation, Modelling and Simulation Society of Australia and New Zealand, 1596–1602. Canberra, Australia: Modelling and Simulation Society of Australia and New Zealand.
Abbaspour, K. C., J. Yang, I. Maximov, R. Siber, K. Bogner, J. Mieleitner, J. Zobrist, and R. Srinivasan. 2007b. “Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT.” J. Hydrol. 333 (2–4): 413–430. https://doi.org/10.1016/j.jhydrol.2006.09.014.
Ajami, N. K., H. Gupta, T. Wagener, and S. Sorooshian. 2004. “Calibration of a semi-distributed hydrologic model for stream flow estimation along a river system.” J. Hydrol. 298 (1): 112–135. https://doi.org/10.1016/j.jhydrol.2004.03.033.
Alkimim, A., G. Sparovek, and K. C. Clarke. 2015. “Converting Brazil’s pastures to cropland: An alternative way to meet sugarcane demand and to spare forestlands.” Appl. Geogr. 62 (1): 75–84. https://doi.org/10.1016/j.apgeog.2015.04.008.
Arnold, J. G., and N. Fohrer. 2005. “SWAT2000: Current capabilities and research opportunities in applied watershed modeling.” Hydrol. Proc. 19 (3): 563–572. https://doi.org/10.1002/hyp.5611.
Arnold, J. G., D. N. Moriasi, P. W. Gassman, K. C. Abbaspour, M. J. White, R. Srinivasan, and N. Kannan. 2012. “SWAT: Model use, calibration and validation.” Transact. ASABE 55 (4): 1491–1508. https://doi.org/10.13031/2013.42256.
Arnold, J. G., R. Srinivasan, R. S. Muttiah, and J. R. Williams. 1998. “Large-area hydrologic modeling and assessment. Part 1: Model development.” J. Am. Water Resour. Assoc. 34 (1): 73–89. https://doi.org/10.1111/j.1752-1688.1998.tb05961.x.
Chau, K. W., and C. L. Wu. 2010. “A hybrid model coupled with singular spectrum analysis for daily rainfall prediction.” J. Hydroinf. 12 (4): 458–473. https://doi.org/10.2166/hydro.2010.032.
Chen, X. Y., K. W. Chau, and A. O. Busari. 2015. “A comparative study of population-based optimization algorithms for downstream river flow forecasting by a hybrid neural network model.” Eng. Appl. Artif. Intell. 46: 258–268. https://doi.org/10.1016/j.engappai.2015.09.010.
EMBRAPA (Empresa Brasileira de Pesquisa Agropecuária). 1981. Secretaria da Agricultura e abastecimento do estado de São Paulo; Instituto Agronⓞmico de Campinas (IAC). Levantamento pedológico semi-detalhado do estado de São Paulo. Campinas, Brazil: IAC.
Freire, O., J. Gimenez, J. Pessoti, and E. Carraro. 1978. Solos da bacia do Broa, 125. São Paulo, Brazil: Universidade Federal de São Carlos.
Fukunaga, D. C., R. A. Cecilio, S. Zanetti, L. T. Oliveira, and M. A. C. Caiado. 2015. “Application of the SWAT hydrologic model to a tropical watershed at Brazil.” Catena 125 (1): 206–213. https://doi.org/10.1016/j.catena.2014.10.032.
Gassman, P. W., M. R. Reyes, C. H. Green, and J. G. Arnold. 2007. “The soil and water assessment tool: Historical development, applications, and future research directions. Invited review series.” Transact. Am. Soc. Agric. Biol. Eng. 50 (4): 1211–1250.
Hawkins, R. H., A. T. Hjelmfelt Jr., and A. W. Zevenbergen. 1985. “Runoff probability, storm depth, and curve numbers.” J. Irrig. Drain. Eng. 111 (4): 330–340. https://doi.org/10.1061/(ASCE)0733-9437(1985)111:4(330).
Huang, J., and H. Hong. 2010. “Comparative study of two models to simulate diffuse nitrogen and phosphorus pollution in a medium-sized watershed, southeast China.” Estuarine Coastal Shelf Sci. 86 (3): 387–394. https://doi.org/10.1016/j.ecss.2009.04.003.
Huber, W. C., and R. E. Dickinson. 1988. Storm water management model user’s manual, version 4. Athens, GA: Environmental Protection Agency.
Kaleris, V., and L. Andreas. 2017. “Comparison of two rainfall-runoff models: Effects of conceptualization on water budget components.” Hydrol. Sci. J. 62 (5): 729–748. https://doi.org/10.1080/02626667.2016.1250899.
Khoi, D. N., and V. T. Thom. 2015. “Parameter uncertainty analysis for simulating streamflow in a river catchment of Vietnam.” Global Ecol. Conserv. 4 (1): 538–548. https://doi.org/10.1016/j.gecco.2015.10.007.
Kisi, O., J. Shiri, and M. Tombul. 2013. “Modeling rainfall-runoff process using soft computing techniques.” Comput. Geosci. 51 (Feb): 108–117. https://doi.org/10.1016/j.cageo.2012.07.001.
Krause, P., D. P. Boyle, and F. Bãse. 2005. “Comparison of different efficiency criteria for hydrological model assessment.” Adv. Geosci. 5 (1): 89–97.
Lapola, D. M., et al. 2014. “Pervasive transition of the Brazilian land-use system.” Nat. Clim. Change 4 (1): 27–35. https://doi.org/10.1038/nclimate2056.
Leagates, D. R., and G. J. McCabe Jr. 1999. “Evaluating the use of ‘goodness-of-fit’ measures in hydrologic and hydroclimatic model validation.” Water Resour. Res. 35 (1): 233–241.
Lenhart, K., N. F. Eckhardt, and H. G. Frede. 2002. “Comparison of two different approaches of sensitivity analysis.” Phys. Chem. Earth 27 (9–10): 645–654. https://doi.org/10.1016/S1474-7065(02)00049-9.
Li, X., D. E. Weller, and T. E. Jordan. 2010. “Watershed model calibration using multi-objective optimization and multisite averaging.” J. Hydrol. 380 (3–4): 277–288. https://doi.org/10.1016/j.jhydrol.2009.11.003.
Lombardi Neto, F., R. Bellinazzi, Jr., P. A. Galetti, D. Bertolini, I. F. Lepsch, and J. B. Oliveira. 1989. “Nova abordagem para cálculo de espaçamento entre terraços.” In Simpósio Sobre Terraceamento Agrícola, edited by F. Lombardi Neto and R. Belinazzi, Jr., 99–124. Campinas, Brazil: Fundação Cargill.
Me, W., J. M. Abell, and D. P. Hamilton. 2015. “Effects of hydrologic conditions on SWAT model performance and parameter sensitivity for a small, mixed land use catchment in New Zealand.” Hydrol. Earth Syst. Sci. 19 (10): 4127–4147. https://doi.org/10.5194/hess-19-4127-2015.
Michaud, J., and S. Sorooshian. 1994. “Comparison of simple versus complex distributed runoff models on a midsized semiarid watershed.” Water Resour. Res. 30 (3): 593–605. https://doi.org/10.1029/93WR03218.
Moriasi, D. N., J. G. Arnold, M. W. Van Liew, R. L. Bingner, R. D. Harmel, and T. L. Veith. 2007. “Model evaluation guidelines for systematic quantification of accuracy in watershed simulations.” Transact. ASABE 50 (3): 885–900. https://doi.org/10.13031/2013.23153.
Muleta, M. K. 2012. “Improving model performance using season-based evaluation.” J. Hydrol. Eng. 17 (1): 191–200. https://doi.org/10.1061/(ASCE)HE.1943-5584.0000421.
Naef, F. 1981. “Can we model the rainfall-runoff process today?/Peut-on actuellement mettre en modèle le processus pluie-écoulement?” Hydrol. Sci. J. 26 (3): 281–289. https://doi.org/10.1080/02626668109490887.
Nash, J. E., and J. V. Sutcliffe. 1970. “River flow forecasting through conceptual models. Part I—A discussion of principles.” J. Hydrol. 10 (3): 282–290. https://doi.org/10.1016/0022-1694(70)90255-6.
Neitsch, S. L., A. G. Arnold, J. R. Kiniry, J. R. Srinivasan, and J. R. Williams. 2002. Soil and water assessment tool user’s manual: Version 2000. College Station, TX: Texas Water Resources Institute.
Neitsch, S. L., J. G. Arnold, J. R. Kiniry, and J. R. Williams. 2001. Soil and water assessment tool. Theoretical documentation. Version 2000. Temple, TX: Blackland Research Center.
Neitsch, S. L., J. G. Arnold, J. R. Kiniry, J. R. Williams, and K. W. King. 2005. Soil and water assessment tool. Theoretical documentation. Temple, TX: Soil and Water Research Laboratory.
Neitsch, S. L., J. R. Williams, J. G. Arnold, and J. R. Kiniry. 2009. Soil and water assessment tool. Theoretical documentation. Version 2009. College Station, TX : Texas Water Resources Institute.
Nimer, E. 1977. “Clima.” In: IBGE, Geografia do Brasil: Região Sudeste, Vol. 3, 51–89. Rio de Janeiro, Brazil: IBGE.
Oliveira, J. B., and H. Prado. 1984. Levantamento pedológico semidetalhado do Estado de São Paulo: Memorial descritivo, 110. Campinas, Brazil: IAC.
Rabelo, J. L., and E. Wendland. 2009. “Assessment of groundwater recharge and water fluxes of the Guarani Aquifer System, Brazil.” Hydrogeol. J. 17 (7): 1733–1748. https://doi.org/10.1007/s10040-009-0462-y.
Saxton, K. E., and W. J. Rawls. 2006. “Soil water characteristic estimates by texture and organic matter for hydrologic solutions.” Soil Sci. Soc. Am. J. 70 (5): 1569–1578. https://doi.org/10.2136/sssaj2005.0117.
Sloan, F. A., R. D. Feldman, and A. B. Steinwald. 1983. “Effects of teaching on hospital costs.” J. Health Econ. 2 (1): 1–28. https://doi.org/10.1016/0167-6296(83)90009-7.
Strassburg, B. B. N., et al. 2017. “Moment of truth for the Cerrado hotspot.” Nat. Ecol. Evol. 1 (4): 99 https://doi.org/10.1038/s41559-017-0099.
SWAT (Soil and Water Assessment Tool). 2018. “SWAT literature database for peer-reviewed journal articles.” Accessed 26 April, 2018. https://www.card.iastate.edu/swat_articles.
Thornthwaite, C. W. 1948. “An approach toward a rational classification of climate.” Geograph. Rev. 38 (1): 55–94. https://doi.org/10.2307/210739.
Thornthwaite, C. W., and J. R. Mather. 1957. “Instructions and tables for computing potential evapotranspiration and water balance.” Publications in Climatology 10 (3): 1–132.
Thornthwaite, C. W., and J. R. Matter. 1955. “The water balance.” Publications in climatology, 104. Centerton, NJ: Drexel Institute of Technology.
Tundisi, J. G. 1986. “Local community involvement in environmental planning and management: Focus on river basin management—The Horto/Itaqueri-Broa reservoir case study.” Expert group on Environmental Planning and Management for Local Regional Development: Focus on training aspects derived from studies of inland water management, 10–21. Otsu e Nagoya, Japan: Regional Development Dialogue (UNCRD).
U.S. Dept. of Agriculture. 1972. “Hydrology.” Soil conservation service national engineering handbook, 10.5–10.6. Washington, DC: U.S. Department of Agriculture.
Van Griensven, A., T. Meixner, S. Grunwald, T. Bishop, M. Diluzio, and R. Srinivasan. 2006. “A global sensitivity analysis tool for the parameters of multi-variable catchment models.” J. Hydrol. 324 (1–4): 10–23. https://doi.org/10.1016/j.jhydrol.2005.09.008.
World Meteorological Organization. 1975. Intercomparison of conceptual models used in operational hydrological forecasting. Geneva, Switzerland: World Meteorological Organization.
Wu, R. S., and D. A. Haith. 1989. GWLF, generalized watershed loading functions user’s manual. Ithaca, NY: Cornell Univ.
Xu, C. Y., and V. P. Singh. 1998. “A review on monthly water balance models for water resources investigations.” Water Resour. Manage. 12 (1): 20–50. https://doi.org/10.1023/A:1007916816469.

Information & Authors

Information

Published In

Go to Journal of Environmental Engineering
Journal of Environmental Engineering
Volume 144Issue 8August 2018

History

Received: May 9, 2017
Accepted: Feb 1, 2018
Published online: May 18, 2018
Published in print: Aug 1, 2018
Discussion open until: Oct 18, 2018

Permissions

Request permissions for this article.

Authors

Affiliations

Franciane Mendonça dos Santos [email protected]
Ph.D. Student, São Carlos School of Engineering, Center of Water Resources and Environmental Studies, Univ. of São Paulo, Caixa Postal 292, São Carlos, SP 13566590, Brazil; Civil Engineering Research and Innovation for Sustainability, Instituto Superior Técnico, Universidade de Lisboa, Ave. Rovisco Pais, 1049-001 Lisbon, Portugal (corresponding author). Email: [email protected]
Rodrigo Proença de Oliveira [email protected]
Professor, Civil Engineering Research and Innovation for Sustainability, Instituto Superior Técnico, Universidade de Lisboa, Ave. Rovisco Pais, 1049-001 Lisbon, Portugal. Email: [email protected]
Frederico Fábio Mauad [email protected]
Professor, São Carlos School of Engineering, Center of Water Resources and Environmental Studies, Univ. of São Paulo, Caixa Postal 292, São Carlos, SP 13566590, Brazil. Email: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share