Effects of spatial and temporal weather data resolutions on streamflow modeling of a semi-arid basin, Northeast Brazil
Abstract
Keywords: climate data resolution, hydrology, SWAT model, semi-arid basin, Brazil
DOI: 10.3965/j.ijabe.20150803.970 Online first on [2015-03-20]
Citation: Bressiani D A, Srinivasan R, Jones C A, Mendiondo E M. Effects of spatial and temporal weather data resolutions on streamflow modeling of a semi-arid basin, Northeast Brazil. Int J Agric & Biol Eng, 2015; 8(3): 125-139.
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Schuol J, Abbaspour K C. Calibration and uncertainty issues of a hydrological model (SWAT) applied to West Africa. Advances in Geosciences, 2006; 9: 137–143. doi: 10.5194/adgeo-9-137-2006
Kite G W, Haberlandt U. Atmospheric model data for macroscale hydrology. Journal of Hydrology, 1999; 217: 303–313. doi: 10.1016/S0022-1694(98)00230-3.
Rivington M, Matthews K B, Bellocchi G, Buchan K. Evaluating uncertainty introduced to process-based simulation model estimates by alternative sources of meteorological data. Agricultural Systems, 2006; 88: 451–471. doi: 10.1016/j. agsy.2005.07.004
Arnold J G, Allen P M, Bernhhardt G. A comprehensive surface groundwater flow model. Journal of Hydrology, 1993; 142: 47–69. doi: 10.1016/0022-1694(93)90004-S
Arnold J G, Srinivasan R, Muttiah R S, Williams J R. Large area hydrologic modeling and assessment-Part 1: Model Development. Journal of the American Water Resources Association, 1998; 34(1): 73–89. doi: 10.1111/j. 1752-1688. 1998.tb05961.x
Yu Z. Chapter 172: Hydrology: modeling and prediction. In Encyclopedia of Atmospheric Science. Academic Press, 2003, 3. pp. 980–986.
Norton J P. Prediction for decision-making under uncertainty. In: Proceedings of MODSIM 2003 International Congress on Modeling and Simulation: Integrative modeling of bhiophysical, social and economic systems for resource management solutions, 14-17 July, 2003, Townsville, Australia, 2003; 4. pp. 1517-1522. Available: http://www.mssanz.org.au/MODSIM03/Volume_03/03_Norton.pdf
Yu M, Chen X, Li L, Bao A, Paix M J. Streamflow Simulation by SWAT Using Different Precipitation Sources in Large Arid Basins with Scarce Raingauges. Water Resources Management, 2011; 25: 2669–2681. Doi: 10.1007/ s11269-011-9832-z
Wilk J, Kniveton D, Andersson L, Layberry R, Todd M C, Hughes D, et al. Estimating rainfall and water balance over the Okavango River Basin for hydrological applications. Journal of Hydrology, 2006; 331: 18–29. Doi: 10.1016/j. jhydrol.2006.04.049
Ercan M B, Goodall J L. Estimating Watershed-Scale Precipitation by Combining Gauge- and Radar-Derived Observations. Journal of Hydrologic Engineering, 2013; 18(8): 983-994. Doi: 10.1061/(ASCE)HE.1943-5584. 0000687.
Bennett M E, Tobin K J. The evolution of remotely sensed precipitation products for hydrological applications with a focus on the tropical rainfall measurement mission (TRMM).
Journal of Environmental Hydrology, 2013; 21: 1–16.
Price K, Purucker S T, Kraemer S R, Babendreier J E, Knightes C D. Comparison of radar and gauge precipitation data in watershed models across varying spatial and temporal scales. Hydrological Processes, 2013; 28(9): 3505–3520. Doi: 10.1002/hyp.9890.
El-Sadek A., Bleiweiss M., Shukla M, Guldan S, Fernald A. Alternative climate data sources for distributed hydrological modelling on a daily time step. Hydrological Processes, 2011; 25: 1542–1557. Doi: 10.1002/hyp.7917
Fuka D R., Walter M T, MacAlister C, Degaetano A T, Steenhuis T S, Easton Z M. Using the Climate Forecast System Reanalysis as weather input data for watershed models. Hydrological Processes, 2013: 28(22): 5613–5623. Doi: 10.1002/hyp.10073.
Strauch M, Bernhofer C, Koide S, Volk M, Lorz C, Makeschin F. Using precipitation data ensemble for uncertainty analysis in SWAT streamflow simulation. Journal of Hydrology, 2012; 414-415: 413–424. doi: 10.1016/j. jhydrol.2011.11.014.
Zhenyao S, Lei C, Qian L, Ruimin L, Qian H. Impact of spatial rainfall variability on hydrology and nonpoint source pollution modeling. Journal of Hydrology, 2012; 472–473: 205–215. Doi: 10.1016/j.jhydrol.2012.09.019.
Galván L, Olías M, Izquierdo T, Cerón J C, Fernández de Villarán R. Rainfall estimation in SWAT: An alternative method to simulate orographic precipitation. Journal of Hydrology, 2014; 509: 257–265. Doi: 10.1016/j.jhydrol. 2013.11.044
Sexton A M, Sadeghi A M, Zhang X, Srinivasan R, Shirmohammadi A. Using NEXRAD and rain gauge precipitation data for hydrologic calibration of SWAT in a Northeastern watershed. American Society of Agricultural and Biological Engineer, 2010; 53(5): 1501–1510. doi: 10.1061/(ASCE)HE.1943-5584.0000618
Sharpley A N, Williams J R. EPIC-Erosion Productivity Impact Calculator, 1. Model Documentation. U. S. Department of Agriculture, Agricultural Research Service, Tech Bull, 1990; No. 1768.
Gatto L C S. (supervisor), Rivas M P, Fortunato F F, Santiago Filho A L, Oliveira F C, Cunha R C M B, et al. Diagnóstico ambiental da bacia do rio jaguaribe: diretrizes gerais para a ordenação territorial. Ministério de Planejamento e Orçamento. Fundação Instituto Brasileiro de Geografia e Estatística- IBGE. Diretoria de Geociências. 1ª Divisão de Geociências do Nordeste – DIGEO 1/ NE.1. 1999. Available on: ftp://geoftp.ibge.gov.br/documentos/ recursos_naturais/diagnosticos/jaguaribe.pdf
Marins R V, Paula Filho F J, Rocha C A S. Phosphorus geochemistry as a proxy of environmental estuarine processes at the Jaguaribe River, northeastern Brazil. Quim. Nova., 2007; 30(5): 1208–1214.
Instituto Brasileiro de Geografia e Estatística – IBGE. Censo Demográfico 2010. Available on: http://cidades.ibge.gov.br/ xtras/ perfil.php?codmun=230440〈=_EN
Krol M, Jaeger A, Bronstert A, Guntner A. Integrated modelling of climate, water, soil, agricultural and socio-economic processes: A general introduction of the methodology and some exemplary results from the semi-arid north-east of Brazil. Journal of Hydrology, 2006; 328: 417– 431. doi: 10.1016/j.jhydrol.2005.12.021
Krol M, Bronstert A. Regional integrated modelling of climate change impacts on natural resources and resource usage in semi-arid Northeast Brazil. Environmental Modelling & Software, 2007; 22: 259–268. doi: 10.1016/ j.envsoft. 2005.07.022
Gassman P W, Reyes M R, Green C H, Arnold J G. The soil and water assessment tool: Historical development, applications, and future research directions. Transactions ASAE, 2007; 50(4): 1211–1250. Available: http://www.card. iastate.edu/environment/items/asabe_swat.pdf. Accessed on: [2013-02-15].
Arnold J G, Moriasi D N, Gassman P W, Abbaspour K C, White M J, Srinivasan R, et al. SWAT: model use, calibration, and validation. Trans. ASABE, 2012; 55(4): 1491–1508. doi: 10.13031/2013.42256.
Gassman P W, Sadeghi A M, Srinivasan R. Applications of the SWAT Model Special Section: Overview and Insights. Journal of Environmental Quality, 2014; 43; 1–8. doi: 10.2134/jeq2013.11.0466
Douglas-Mankin K R, Srinivasan R, Arnold J G. Soil and Water Assessment Tool (SWAT) model: Current Developments and Applications. Transactions of the ASABE, 2010; 53(5): 1423–1431. Available: http://swat. tamu.edu/media/87820/douglas-mankin-et-al-2010-trans-asabe-article.pdf. Accessed on [2014-09-06].
Daniel E B, Camp J V, LeBoeuf E J, Penrod J R, Dobbins J P, Abkowitz M D. Watershed Modeling and its Applications: A State-of-the-Art Review. The Open Hydrology Journal, 2011; 5: 26–50. DOI: 10.2174/1874378101105010026.
Yang J, Reichert P, Abbaspour K. C, Xia H. Comparing uncertainty analysis techniques for a SWAT application to the Chaohe Basin in China. Journal of Hydrology. 2008; 358: 1–23. doi: 10.1016/j.jhydrol.2008.05.012
Neitsch S L, Arnold J G, Kiniry J R, Srinivasan R, Williams J R. Soil and Water Assessment Tool Theoretical Documentation: Version 2005. Temple, TX: Grassland, Soil and Water Research Laboratory, Agricultural Research Service. 2005a. Available: www.brc.tamus.edu/swat/doc.html. Accessed on [2011-07-10].
Demirel M C, Venancio A, Kahya E. Flow forecast by SWAT model and ANN in Pracana basin, Portugal. Advances in Engineering Software. 2009; 40: 467–473. doi: 10.1016/j.advengsoft.2008.08.002.
FUNCEME and World Bank: Adapting Water Resources Planning and Operation to Climate Variability and Climate Change in Selected River Basin in Northeast Brazil. http://www.funceme.br/nlta/index.php?option=com_content&view=frontpage&Itemid=28〈=en. Accessed on [2011-06-11]
USGS- United States Geological Survey 2004. Shuttle Radar Topography Mission, 3 Arc Second scene SRTM, Unfilled Unfinished 2.0, Global Land Cover Facility, University of Maryland, College Park, Maryland. Available: http://earthexplorer.usgs.gov/. Accessed on [2011-07-13].
MA/SUDENE. Exploratory - Recognition Map of Soils for Ceara State.(Mapa Exploratório-Reconhecimento de Solos do Estado do Ceará). Scale 1:600.000. Vectorized by Ceara’s Foundation of Meterology and Water Resources (Fundação Cearense de Meterologia e Recursos Hídricos)- FUNCEME. 1973.
Winchell M, Srinivasan R, Di Luzio M, Arnold J. ARCSWAT interface for SWAT2005: User’s Guide. Texas Agricultural Experiment Station and USDA Agricultural Research Service, Temple, Texas. 2007. Available: http://www.geology.wmich.edu/sultan/5350/Labs/ArcSWAT_ Documentation.pdf. Accessed on [2013-02-10].
ISRIC - World Soil Information. Available: http://www. isric.org/. Accessed on [2011-07-1].
Saxton K E, Rawls WJ. Soil Water Characteristic Estimates by Texture and Organic Matter for Hydrologic Solutions. Soil Science Society of Agronomy Journal, 2006; 70(5); 1569–1578. doi: 10.2136/sssaj2005.0117.
IBGE- Instituto Brasileiro de Geografia e Estatística. Produção Agrícola Municipal. Diretoria de Pesquisas. Coordenação de Agropecuária. IBGE. 2009. Available: http://www.ibge.gov.br/home/estatistica/economia/pam/2009/ tabelas_pdf/tabela02.pdf. Accessed on [2011-07-25].
Barreto P D. Recursos genéticos e programa de melhoramento de feijão-de-corda no Ceará: avanços e perspectivas. In: QUEIRÓZ M A de; GOEDERT C O, RAMOS S R R (Ed). Recursos Genéticos e Melhoramento de Plantas para o Nordeste Brasileiro. Petrolina-PE: Embrapa Semi-Árido/Brasília-DF: Embrapa Recursos Genéticos e Biotecnologia, 1999. Available: http://www.cpatsa. embrapa.br. Accessed on [2013-02-02].
ANA - Agência Nacional de Águas. 2011. Hydrologic Data – Precipitation historic records, Brasil. Available on:
http://hidroweb.ana.gov.br/. Accessed on [2011-06-10].
National Climatic Data Center. National Oceanic and
Atmospheric Administration, NOAA. Monthly Climatic Data for the World. Available on: http://www.ncdc. noaa.gov/IPS/mcdw/mcdw.html. Accessed on [2011-07-01].
INMET – Instituto Nacional de Meterologia. Banco de Dados Metológicos para Ensino e Pesquisa (BDMEP). Climate Database for Research and Education. Available on: http://www.inmet.gov.br/portal/index.php?r=bdmep/bdmep. Accessed on [2013-02-01].
Allen R G, Pereira L S, Raes D, Smith M. Crop evapotranspiration (guidelines for computing crop water requirements). FAO Irrigation and Drainage Paper No. 56. FAO, Rome, Italy. 1998. pp 290.
Smith M. CROPWAT, a computer program for irrigation planning and management. FAO Irrigation and Drainage Paper 46, FAO, Rome. 1992.
Linacre E. Climate and Data Resources: A Reference and Guide. Routledge, London, 1992. p365.
Saha S, Moorthi S, Pan H-L, Wu X, Wang J, Nadiga S, et al. The NCEP Climate Forecast System Reanalysis. Bull. Amer. Meteor. Soc. 2010; 91; 1015–1057; doi: 10.1175/2010 BAMS3001.1.
National Climatic Data Center. National Oceanic and Atmospheric Administration, NOAA. National Centers for Environmental Prediction Climate Forecast System Reanalysis- CFSR. Available on: http://globalweather. tamu.edu/. Accessed on [2013-02-01].
Moriasi D, Arnold J G, Van Liew M W, Bingner R, Harmel R, Veith T L. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Transactions of the ASABE, 2007; 50: 885–900. doi: http://ddr.nal.usda.gov/handle/10113/9298.
Krause P, Boyle D P, Base F. Comparison of different efficiency criteria for hydrological model assessment. Advances in Geosciences, 2005; 5: 89–97. doi: 10.5194/ adgeo-5-89-2005.
Neitsch S L, Arnold J G, Kiniry J R, Williams J R. Soil and Water Assessment Tool Theoretical Documentation: Version 2009. Grassland, Soil and Water Research Laboratory – Agricultural Research Service, Blackland Research Center – Texas AgriLife Research. Texas Water Resources Institute Technical Report No. 406, College Station, Texas. 2011, p 618.
Migliaccio K W, Chaubey I. Spatial Distributions and Stochastic Parameter Influences on SWAT Flow and Sediment Predictions. Journal of Hydrologic Engineering. 2008; 13(4): 258–269. doi: 10.1061/(ASCE)1084-0699(2008) 13:4(258).
Wu K, Johnston C A. Hydrologic response to climatic variability in a Great Lakes Watershed: A case study with the SWAT model. Journal of Hydrology, 2007; 337(1–2): 187–199. doi: 10.1016/j.jhydrol.2007.01.030.
Santhi C, Arnold J G, Williams J R, Dugas W A, Srinivasan R, Hauck L M.. Validation of the SWAT model on a large river basin with point and nonpoint sources. Journal of the American Water Resources Association, 2001; 37(5): 1169- 1188. doi: 10.1111/j.1752-1688.2001.tb03630.x.
Gupta H, Wagener T, Liu Y. Reconciling theory with observations: elements of diagnostic approach to model evaluation. Hydrological Processes. Bognor Regis, 2008; 22 (18): 3802–3813. doi: 10.1002/hyp.6989.
Looper J P, Vieux B E. An assessment of distributed flash flood forecasting accuracy using radar and rain gauge input for a physics-based distributed hydrologic model. Journal of Hydrology, 2012. 412–413: 114–132. doi: 10.1016/ j.jhydrol. 2011.05.046.
Neitsch S L, Arnold J G, Kiniry J R, Srinivasan R, Williams J R. Soil and Water Assessment Tool User’s Manual, Version 2000. Texas Water Resources Institute, College Station, Texas TWRI Report TR-192, 2002.
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