- -

Evaluation of Markov Chain Based Drought Forecasts in an Andean Regulated River Basin Using the Skill Scores RPS and GMSS

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Evaluation of Markov Chain Based Drought Forecasts in an Andean Regulated River Basin Using the Skill Scores RPS and GMSS

Mostrar el registro sencillo del ítem

Ficheros en el ítem

[Cerrado]
Nombre: Evaluation of Markov ...
Tamaño: 476.7Kb
Formato: PDF
Descripción: Versión editorial
Solicitar una copia al autor
dc.contributor.author Avilés, Alex es_ES
dc.contributor.author Célleri-Alvear, Rolando es_ES
dc.contributor.author Paredes Arquiola, Javier es_ES
dc.contributor.author Solera Solera, Abel es_ES
dc.date.accessioned 2017-03-01T18:31:29Z
dc.date.available 2017-03-01T18:31:29Z
dc.date.issued 2015
dc.identifier.issn 0920-4741
dc.identifier.uri http://hdl.handle.net/10251/78425
dc.description.abstract On behalf of the decision-makers of Andean regulated river basins a drought index was developed to predict the occurrence and extent of drought events. Two stochastic models, the Markov Chain First Order (MCFO) and the Markov Chain Second Order (MCSO) model, predicting the frequency of monthly droughts were applied and the performance checked using two skill scores, respectively the ranked probability score (RPS) and the Gandin-Murphy skill score (GMSS). Data of the Chulco River basin (3200 4300 m.a.s.l.), situated in the Ecuadorian southern Andes, were employed to test the performance of both models. Results indicate that events with greater drought severity were more accurately predicted. The study also revealed the importance of verifying the quality of the forecasts and to have an assessment of the likely performance of the forecasting models before adopting any model and accepting the resulting information for decision-making. es_ES
dc.description.sponsorship The research was conducted within the frame of the projects "Meteorological Cycles and Evapotranspiration along the Altitudinal Gradient of the Cajas National Park" and "Identification of hydro-meteorological processes that trigger extreme floods in the city of Cuenca using precipitation radar". Both projects were funded by the University of Cuenca and the Public Municipal Company of Water Supply from Cuenca (ETAPA). Thanks are due to INAMHI and CBRM for providing the information of the Chulco river basin. en_EN
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation.ispartof Water Resources Management es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Drought index es_ES
dc.subject Probabilistic forecast es_ES
dc.subject Markov Chains es_ES
dc.subject Forecast evaluation es_ES
dc.subject Andean basins es_ES
dc.subject.classification INGENIERIA HIDRAULICA es_ES
dc.title Evaluation of Markov Chain Based Drought Forecasts in an Andean Regulated River Basin Using the Skill Scores RPS and GMSS es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s11269-015-0921-2
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros de Caminos, Canales y Puertos - Escola Tècnica Superior d'Enginyers de Camins, Canals i Ports es_ES
dc.description.bibliographicCitation Avilés, A.; Célleri-Alvear, R.; Paredes Arquiola, J.; Solera Solera, A. (2015). Evaluation of Markov Chain Based Drought Forecasts in an Andean Regulated River Basin Using the Skill Scores RPS and GMSS. Water Resources Management. 29(6):1949-1963. doi:10.1007/s11269-015-0921-2 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion http://www.dx.doi.org/10.1007/s11269-015-0921-2 es_ES
dc.description.upvformatpinicio 1949 es_ES
dc.description.upvformatpfin 1963 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 29 es_ES
dc.description.issue 6 es_ES
dc.relation.senia 291542 es_ES
dc.contributor.funder Universidad de Cuenca, Ecuador
dc.contributor.funder Empresa Pública Municipal de Telecomunicaciones, Agua Potable, Alcantarillado y Saneamiento de Cuenca es_ES
dc.contributor.funder ETAPA EP
dc.description.references Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Contr 19:716–723. doi: 10.1109/TAC.1974.1100705 es_ES
dc.description.references Banimahd SA, Khalili D (2013) Factors influencing markov chains predictability characteristics, utilizing SPI, RDI, EDI and SPEI drought indices in different climatic zones. Water Resour Manag 27:3911–3928. doi: 10.1007/s11269-013-0387-z es_ES
dc.description.references Barua S, Asce SM, Ng AWM, Perera BJC (2011) Comparative evaluation of drought indexes : case study on the Yarra River catchment in Australia. J Water Resour Plan Manag 137:215–226. doi: 10.1061/(ASCE)WR.1943-5452.0000105 es_ES
dc.description.references Barua S, Ng A, Perera B (2012) Drought assessment and forecasting: a case study on the Yarra River catchment in Victoria, Australia. Aust J Water Resour 15:95–108. doi: 10.7158/W10-848.2012.15.2 es_ES
dc.description.references Beniston M (2003) Climatic change in mountain regions: a review of possible impacts. Clim Chang 59:5–31 es_ES
dc.description.references Buytaert W, Célleri R, De Bièvre B et al (2006a) Human impact on the hydrology of the Andean páramos. Earth Sci Rev 79:53–72. doi: 10.1016/j.earscirev.2006.06.002 es_ES
dc.description.references Buytaert W, Celleri R, Willems P (2006b) Spatial and temporal rainfall variability in mountainous areas: a case study from the south Ecuadorian Andes. J Hydrol 329:413–421. doi: 10.1016/j.jhydrol.2006.02.031 es_ES
dc.description.references Cancelliere A, Di Mauro G, Bonaccorso B, Rossi G (2007) Drought forecasting using the Standardized Precipitation Index. Water Resour Manag 21:801–819. doi: 10.1007/s11269-006-9062-y es_ES
dc.description.references Celleri R, Willems P, Buytaert W, Feyen J (2007) Space – time rainfall variability in the Paute Basin, Ecuadorian Andes. Hydrol Process 21:3316–3327. doi: 10.1002/hyp.6575 es_ES
dc.description.references Gandin LS, Murphy AH (1992) Equitable Skills scores for categorical forecast. Mon Weather Rev 120:361–370 es_ES
dc.description.references Gerrity JP (1992) A note on Gandin and Murphy’s Equitable Skill Scores. Mon Weather Rev 120:2709–2712 es_ES
dc.description.references Keyantash JA, Dracup JA (2004) An aggregate drought index: assessing drought severity based on fluctuations in the hydrologic cycle and surface water storage. Water Resour Res 40:1–13. doi: 10.1029/2003WR002610 es_ES
dc.description.references Khalili D, Farnoud T, Jamshidi H et al (2011) Comparability analyses of the SPI and RDI meteorological drought indices in different climatic zones. Water Resour Manag 25:1737–1757. doi: 10.1007/s11269-010-9772-z es_ES
dc.description.references Labadie JW, Asce M (2004) Optimal operation of multireservoir systems : state-of-the-art review. J Water Resour Plan Manag 130:93–111. doi: 10.1061/(ASCE)0733-9496(2004)130:2~93! es_ES
dc.description.references Lee S-E, Seo K-H (2013) The development of a statistical forecast model for changma. Weather Forecast 28:1304–1321. doi: 10.1175/WAF-D-13-00003.1 es_ES
dc.description.references Liu Y, Gupta H, Springer E, Wagener T (2008) Linking science with environmental decision making: experiences from an integrated modeling approach to supporting sustainable water resources management. Environ Model Softw 23:846–858. doi: 10.1016/j.envsoft.2007.10.007 es_ES
dc.description.references Lohani VK, Loganathan GV (1997) An early warning system for drought management using the Palmer drought index. J Am Water Resour Assoc 33:1375–1386 es_ES
dc.description.references Mason SJ (2004) On using “Climatology” as a reference strategy in the brier and ranked probability skill scores. Mon Weather Rev 132:1891–1895 es_ES
dc.description.references Mauget S, Ko J (2008) A two-tier statistical forecast method for agricultural and resource management simulations. J Appl Meteorol Climatol 47:1573–1589. doi: 10.1175/2007JAMC1749.1 es_ES
dc.description.references McKee TB, Doesken NJ, Kleist J (1993) The relationship of drought frequency and duration to time scales. Proc. 8th Conf. Appl. Climatol. American Meteorological Society Boston, MA, pp 179–183 es_ES
dc.description.references Mishra a K, Desai VR (2005) Drought forecasting using stochastic models. Stoch Environ Res Risk Assess 19:326–339. doi: 10.1007/s00477-005-0238-4 es_ES
dc.description.references Mishra AK, Singh VP (2010) Review paper A review of drought concepts. J Hydrol 391:202–216. doi: 10.1016/j.jhydrol.2010.07.012 es_ES
dc.description.references Mishra AK, Desai VR, Singh VP, Asce F (2007) Drought forecasting using a hybrid stochastic and neural network model. J Hydrol Eng 12:626–638. doi: 10.1061/(ASCE)1084-0699(2007)12:6(626) es_ES
dc.description.references Moreira EE, Coelho C, Paulo A a et al (2008) SPI-based drought category prediction using loglinear models. J Hydrol 354:116–130. doi: 10.1016/j.jhydrol.2008.03.002 es_ES
dc.description.references Muller WA, Appenzeller C, Doblas-Reyes FJ, Liniger MA (2005) A debiased ranked probability skill score to evaluate probabilistic ensemble forecasts with small ensemble sizes. J Clim 18:1513–1523. doi: 10.1175/JCLI3361.1 es_ES
dc.description.references Murphy A (1971) A note on the ranked probability score. J Appl Meteorol 10:155–156 es_ES
dc.description.references Murphy AH (1977) The value of climatological, categorical and probabilistic forecasts in the cost-loss ratio situation. Mon Weather Rev 105:803–816. doi: 10.1175/1520-0493(1977)105<0803:TVOCCA>2.0.CO;2 es_ES
dc.description.references Nalbantis I, Tsakiris G (2009) Assessment of hydrological drought revisited. Water Resour Manag 23:881–897. doi: 10.1007/s11269-008-9305-1 es_ES
dc.description.references Palmer W (1965) Meteorological drought. Paper 45:65 es_ES
dc.description.references Panu US, Sharma TC (2002) Challenges in drought research: some perspectives and future directions. Hydrol Sci J 47:S19–S30. doi: 10.1080/02626660209493019 es_ES
dc.description.references Paulo A, Pereira LS (2007) Prediction of SPI drought class transitions using Markov chains. Water Resour Manag 21:1813–1827. doi: 10.1007/s11269-006-9129-9 es_ES
dc.description.references Ries H, Schlünzen KH, Brümmer B et al (2010) Impact of surface parameter uncertainties on the development of a trough in the Fram Strait region. Tellus A 62:377–392. doi: 10.1111/j.1600-0870.2010.00451.x es_ES
dc.description.references Robertson DE, Wang QJ (2013) Seasonal forecasts of unregulated inflows into the Murray River, Australia. Water Resour Manag 27:2747–2769. doi: 10.1007/s11269-013-0313-4 es_ES
dc.description.references Schwarz G (1978) Estimating the dimension of a model. Ann Stat 6:461–464 es_ES
dc.description.references Shukla S, Wood AW (2008) Use of a standardized runoff index for characterizing hydrologic drought. Geophys Res Lett 35:1–7. doi: 10.1029/2007GL032487 es_ES
dc.description.references Steinemann A (2003) Drought indicators and triggers: a stochastic approach to evaluation. J Am Water Resour Assoc 39:1217–1233 es_ES
dc.description.references Steinemann AC, Cavalcanti LF (2006) Developing multiple indicators and triggers for drought plans. J Water Resour Plan Manag 132:164–174. doi: 10.1061/(ASCE)0733-9496(2006)132:3(164) es_ES
dc.description.references Svoboda M, Hayes M, Wilhite D, Tadesse T (2004) Recent advances in drought monitoring. Drought Mitig Cent Fac Publ 6 es_ES
dc.description.references Tsakiris G, Vangelis H (2005) Establishing a drought index incorporating evapotranspiration. Eur Water 9:3–11 es_ES
dc.description.references Vicente-Serrano SM, Beguería S, López-Moreno JI (2010) A multiscalar drought index sensitive to global warming: the standardized precipitation evapotranspiration index. J Clim 23:1696–1718. doi: 10.1175/2009JCLI2909.1 es_ES
dc.description.references Viviroli D, Archer DR, Buytaert W et al (2011) Climate change and mountain water resources: overview and recommendations for research, management and policy. Hydrol Earth Syst Sci 15:471–504. doi: 10.5194/hess-15-471-2011 es_ES
dc.description.references Westphal KS, Laramie RL, Borgatti D, Stoops R (2007) Drought Management Planning with Economic and Risk Factors. J Water Resour Plan Manag 133:351–362. doi: 10.1061/(ASCE)0733-9496(2007)133:4(351) es_ES
dc.description.references Wilks DS (2011) Statistical methods in the atmospheric sciences. Third Edit. 704 es_ES
dc.description.references Zhang H, Casey T (2000) Verification of categorical probability forecasts. Weather Forecast 15:80–89 es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem