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www.cienciadigital.org

                                                 =                                                              = ISSN: 2602-8085

=                              Vol. 3, N°3.1, p. 115-126, julio - septiembre, 201 9

Desarrollo= de un modelo de precipitación escorrentía semi-distribuido para la evaluación de los recursos hídricos del río Jalón

Development of a model of semi-distributed runoff precipitation for the evaluation of the water resources of the Jalón River.

 

Daniel Chuquin.[1]= , Nelson = Chuquin.[2], Juan = Chuquin.[3], Lidia Castro.[4] & R= amiro Cepeda.[5]

 

Recibido: 29-04-2019 / Revisado: 26-05-2019 /Aceptado: 28-06-2019/ Publicado: 15-07-2019

 

Abstra= ct:        <= /span>            DOI: https://doi.org= /10.33262/cienciadigital.v3i3.1.680=

 

The main goal of this study is = the water resources evaluation in the Jalon river basin, with 9718 km2, and the study of the behavior of the Jalon system subbasins, one of the most important tributaries of the Ebro River.<= /p>

For this goal, a semi-distribut= ed rainfall-runoff model has been developed, in order to evaluate the effects produced over the studio basin based on the hydrological response of each hydrographic subbasin of the system. The employed model has been H= BV, conceptual semi-distributed model developed by the Meteorological and Hydrological Institute of Sweden. The tool that has been employed in the mo= del, is RS Minerve 2.0, software that simulates rainfall-runoff processes, being based on object-oriented programming.=

Finally, it is remarkable the c= ontributions generated by the model, as correctly validated, could be really useful in upcoming jobs in hydrologic planning and management, ecological flow management, demands guarantees estimations, etc.

This contributions have been co= mpared with natural regime SIMPA model, developed by the Center for Studies and Experimentation of Public Works (CEDEX) and used by the CHE, in order to estimate whether they are overestimating or underestimating the contributio= ns, trying to find possible mistakes which they may be done.<= /p>

       Keywords: Calibration, runoff, Jalón, modeling, = Rs Minerve, sub-basin, validation.

 

Resúmen:

El estu= dio tiene como principal objetivo evaluar los recursos hídricos en la cuenca del río Jalón la cual tiene una superficie de 9718 km2, con esto se pretende te= ner un conocimiento más a detalle desde el punto de vista hidrológico del comportamiento de las subcuencas que se extienden a lo largo del sistema de explotación del Jalón, la cual constituye uno de los principales afluentes = del río Ebro.

Se empl= eó un modelo hidrológico precipitación-escorrentía (MPE) sem= idistribuido con el fin de evaluar los efectos que se producen sobre las características= de la cuenca en estudio en base a la respuesta hidrológica de cada subcuenca hidrográfica que componen el sistema. El modelo utilizado fue el HBV que se trata de un modelo conceptual semidistribuido desarrollado por el Instituto Meteorológico e Hidrológico de Suecia. La herramienta empleada para la modelación ha sido RS Min= erve 2.0, software que simula los procesos de precipitación-escorrentía y se bas= a en la programación orientada a objetos.

Finalme= nte destacar la importancia de las aportaciones generadas por el modelo, que si= endo validado resulta fundamental para posteriores trabajos en materia de gestió= n y planificación hidrológica, gestión de caudales ecológicos, estimación de garantías de las demandas etc. Estas aportaciones han sido comparadas con l= as aportaciones en régimen natural del modelo SIMPA, desarrollado por el Centr= o de Estudios y Experimentación de Obras de Públicas (CEDEX) y empleado por la Confederación Hidrográfica del Ebro (CHE), con el fin de estimar si ellos e= stán sobreestimando o infravalorando las aportaciones, es decir es posible determinar los posibles errores que se pueden estar cometiendo.<= /span>

 

Palabras claves: = Calibración, escorrentía, Jalón, modelación, Rs Minerve, subcuenca, validación.

 

Introduccion

El agua constituye en la actualidad un recurso no renovable indispensable para el desarrollo de la vida y a la vez= una de las principales materias primas en la mayoría de los procesos productivo= s, por tal razón surge la necesidad de implantar mecanismos para la gestión y planificación del recurso hídrico mediante la aplicación de acciones tanto estructurales (construcción de infraestructura) como medidas no estructurales(medidas que promuevan la eficiencia de uso del agua y tecnolo= gías que disminuyan el riesgo hídrico). Dentro de la hidrología los modelos hidrológicos constituyen una herramienta que merece especial importancia pa= ra la gestión y planificación de los recursos ambientales e hídricos. Dada la exigencia en cuanto a la capacidad predictiva que un modelo conlleva, hoy en día existe la necesidad de fortalecer los modelos existentes.

A lo largo de la historia la modelación h= idrológica ha ido cambiando continuamente, desde el Método Racional (Mulvany et al., 1850) a modelos físicos distribuidos (Wigmosta= et la., 1994; Abbott et al., 1986b; Refsgaard et al., 1995; Ewen et al., 2000; Benoit et = al., 2000; Bates et al., 2000; De Roo et al, 2000; Vivoni et al., 2003).Durante el mismo período, se desarrolló el hidrograma unitario simple (Sherman, 1932), modelos de entrada y salida actualmente llamados modelos basados en datos, mismos que han evolucionado a modelos de redes neuronales artificiales (García, 2001). La elección del modelo más apropiad= o es una tarea difícil dado que cada modelador intenta persuadir y a la vez prom= over su programa desarrollado.

Los modelos hidrológicos son representaci= ones conceptuales y simplificadas de una parte del ciclo hidrológico, generalmen= te son usados para la predicción y comprensión de los procesos hidrológicos qu= e se llevan a cabo en la naturaleza. Estos toman especial importancia cuando se evidencia la carencia de base de datos que establezcan las características = de la línea base (iniciales) y determinen de esta manera los impactos a largo plazo. Los modelos a su vez son capaces de simular los procesos hidrológico= s en el espacio y serie de temporal deseada (De vos et al, 2006; Taffese., 2011).

El modelo hidrológico empleado en el estu= dio para la evaluación de los recursos hídricos es el HBV (Bergstrom et al., 1995; Lindstrom et al., 1197)) se ha el= egido este modelo debido a que no tiene gran cantidad de parámetros, satisfaciendo así el principio de parsimonia y constituyendo un modelo robusto y versátil= .

El software empleado en la modelación fue= RS-Minerve (García et al., 2013, Jo= rdan et al., 2010) mismo que simula la formación y propagación de la escorrentía superficial y capaz de modelar redes hidráulicas e hidrológicas complejas de acuerdo a un esquema semidistribuido conceptual= , ha sido utilizado para diferentes estudios en varios países.

 

Importancia del problema

El objetivo principal del presente estudi= o es evaluar el recurso hídrico disponible en la cuenca del río Jalón que tiene = un área de 9718 km2 aproximadamente, mediante el uso de modelos de precipitación-escorrentía (MPE) teniendo como primicia el análisis y diagnóstico de la gestión del sistema. Además, una vez desarrollado el mode= lo se compara las series de aportaciones generadas con las aportaciones provenientes del modelo SIMPA (Simulación Precipitación-Aportación) que es = el empleado por la confederación hidrográfica del Ebro para el estudio de las aportaciones en régimen natural con el fin de establecer un juicio crítico = para determinar si el organismo en cuestión sobreestima o subestima los recursos disponibles para la posterior gestión del fluido en el medio.

 

Metodología=

La elaboración de modelos de precipitación-escorrentía (MPE) requiere de información necesari= a e indispensable para la ejecución del mismo, la cual debe caracterizarse por = ser representativa de la cuenca a modelar, por tal motivo, los datos disponibles atraviesan una etapa de tratamiento y depuración para posteriormente procesarla.

En la Figura 1 se especifica el procedimiento que se ha seguido para la elaboración, calibrac= ión y validación del MPE.

 

Figura 1.<= /span> Metodología empleada para el desarrollo del modelo

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


Inputs= de entrada: Los datos de precipitación y temperatura= se obtuvieron a partir de la base de datos del proyecto S= pain 02 v2.1,[18], los datos resultan de una serie de interpolaciones empleando = el método de krigeado. En cuanto a la evapotranspi= ración se empleó el modelo de Hargreaves (Hargreves, 1= 985).

 

     

=  

(1)

 

Donde: Kc es el coeficiente de cultivo, ETo la evapotranspiraci= ón potencial, la Eto se calcula en función de la radiación solar incidente, del coeficiente de cultivo y de las temperaturas máximas y mínimas, mediante la Ec. 2:

 

      

=  

(2)

 

Donde: ETo es la evapotranspiración potencial diaria (de referencia) (mm/dia) T la temperatura media dia= ria (C), Tmax la temperatura máxima diaria (C), Tmin la temperatura mínima diaria (C), Ra la radiación solar extraterrestre (mm/dia), K: Coeficiente de cultivo.

El coeficiente de cultivo se determinó en función de la cobertura vegetal del mismo, empleand= o la información que viene dado en la base de datos de usos de suelos de Corine_= 2006 (Coordination on information of the environmet) del insti= tuto geográfico militar.

&= nbsp;

Aplica= ción del modelo HBV: El modelo HBV (Figura = 2) tiene 3 principios fundamentales: la acumulación y el derretimiento de la nieve, la humedad del suelo, el ciclo fluvial de los ríos y la respuesta de= los mismos respecto al proceso que se genera en la cuenca. Se basa en una modelación a través de tanques o reservorios en el cual cada uno presenta ciertas características específicas entre las que destacan el umbral para la producción de escorrentía, constantes que conceptualizan la velocidad con l= a que se propagan los procesos. Este modelo utiliza la precipitación, la temperat= ura y la evapotranspiración potencial como parámetros de entrada a partir de los cuales se estima la producción de escorrentía a través de la cuenca.

 

      = =

=  

(3)

 

Donde: Qr es la escorrentía directa (m<= sup>3/s), Qu es el flujo procedente del reservorio superior (m3/s) y Ql el flujo base (m3/s).=

 

Figura 2.<= /span> Conceptualización del modelo HBV=

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 


Régime= n de Aportaciones, calibración y validación del modelo: Se ejecutó el modelo HBV a través del software Rs Minerve con los respectivos datos meteorológico= s, generando así el régimen de aportaciones para el periodo 1987-2007 (20 años hidrológicos) para cada subcuenca del sistema de explotación del río Jalón.=

 

Previo al periodo = de calibración se realizó una fase de calentamiento (3 años) con el fin de establecer las condiciones iniciales del suelo para cada una de las subcuen= cas del sistema y minimizar así los efectos que podrían ocasionar en la etapa de calibración.

 

La calibración de = las subcuencas (12 años) se lo realizó en función de los caudales registrados en las estaciones de aforo existentes en la cuenca (39 estaciones de la Red Oficial de Estaciones de Aforo (R.O.E.A)) que corresponden a la desembocadu= ra de los diferentes subsistemas hídricos que componen el sistema del río Jaló= n.

 

Finalmente se real= izó una etapa de validación del modelo (5 años) en donde se evaluó la funcional= idad y eficiencia del HBV.

Tanto para la calibración como validación del régimen de aportaciones (caudales) generados por el modelo HBV se empleó una función objetivo (FO) (enfatizan los difere= ntes aspectos y características de un hidrograma y al mismo tiempo establecen de manera aproximada el rendimiento del conjunto de parámetros seleccionado ),= que sea capaz de reproducir adecuadamente los caudales registrados en las estaciones de aforo, de este modo se estima la incertidumbre de las series = de caudales determinados por el modelo desarrollado.

 

     

=  

(4)

 

Donde: F1 - Índice= de Nash: Estima el error cuadrático medio de la varianza normalizada observada, dando el peso más significativo a grandes errores, los cuales no necesariam= ente ocurren en períodos de gran cantidad de flujo.

(5)

 

 

F2- Indice de Nash – in (Logarítmico): Transforma flujos = que conllevan grandes pesos en errores durante flujos bajos.<= /p>

 

(6)

 

F3- Coeficiente de correlación de Pearson: Mide= la covarianza de los simulados y observados.

 

(7)

 

F4 - Bias Score: Me= dida simétrica entre el promedio de los valores simulados y el promedio de los de los valores observados.

 

(8)

 

Resultados

En la Tabla 1 se presenta un resumen detallado de los periodos bajo los cuales se desarrolló la calibración y validación para cada una de las subcuencas del sistema de explotación del r= ío Jalón (Figura 3), además se detalla los resultados de la función objetivo global en base a los cuales se establecieron los juicios críticos para determinar la validez del MPE desarrollado para obtener el régimen de aportaciones para la serie hidrológica 1985 – 2007.

 

Figura 3. MPE desarrollado para el sistema de explotación del = río Jalón a partir del cual se obtuvieron el régimen de aportaciones

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 = ;

 = ;


Tabla 1: Resumen de las Calibraciones y validaciones del mode= lo MPE para el sistema de explotación del río Jalón.

E AFORO<= /b>

UNIDAD

PERÍODO CALIBRA= CIÓN

FO

PERÍODO VALIDAC= IÓN

FO

SISTEMA JILOCA<= /span>

Pancrudo Navarrete

912

1986-2001

0.8001

2001-2006

0.7206

Daroca

908

1986-2001

0.9351

2001-2006

0.8804

Morata

909,911<= span lang=3DES style=3D'font-size:10.0pt;mso-fareast-font-family:"Times New Ro= man"; color:black;mso-font-kerning:0pt;mso-ansi-language:ES;mso-fareast-languag= e: ES'>

1986 – 2001

0.6408

2001-2006

0.7495

SISTEMA PIEDRA<= /span>

Járaba

905

1987-2001

0.7539

2001-2006

0.6570

Nuévalos

901,902<= span lang=3DES style=3D'font-size:10.0pt;mso-fareast-font-family:"Times New Ro= man"; color:black;mso-font-kerning:0pt;mso-ansi-language:ES;mso-fareast-languag= e: ES'>

1984-1997

0.8293

1997-2000

0.7005

Tranquera

906

1987-2001

0.7518

2001-2007

0.7968

SISTEMA MANUBLE= S

Ateca

816

1989-2000

0.7900

2000-2006

0.5988

SISTEMA ARANDA<= /span>

Maidevera

823

1991-2002

0.7385

2002-2007

0.7758

SISTEMA JALÓN

Barrio Blanco

813

1996-2003

0.7803

2003-2007

0.8184

Jubera

801

1987-2001

0.8479

2001-2007

0.8565

Ateca

803

1987-2001

0.777

2001-2007

0.8799

Calatayud

804,91

1994-2001

0.8905

2001-2007

0.8510

Chodes

806,817,819

2000-2005

0.8554

2005-2008

0.6675

Grisen

807,821,822,82<= /span>

1987-1998

0.8309

2004-2007

0.6745

4,825,827

 

Figura 4. a) Sistema de Explotación del Río Jalón, b) Calibrac= ión del río Jiloca, c) Calibración del río Piedra, d) Calibración del río Manubles, e) Calibración del río Isuelas, f) Calibración del sistema en conjunto del sistema de explotación del río J= alón

 

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&= nbsp;

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Discusión

Según el análisis de calibración del mode= lo de precipitación y escorrentía, y considerando los valores de la función objet= ivo (Figura 4), se deduce los mejores ajustes se obtuvieron sobre todo en aquel= las subcuencas de cabecera, mismas que no abarcaban una gran extensión y que a = la vez no se veían afectadas en gran medida por las detracciones de agua para satisfacer demandas ya sea de tipo agraria, urbana o industrial. Las cuenca= s de cabecera al encontrarse en régimen natural facilitaron y favorecieron el aj= uste y calibración adecuada de los caudales simulados frente a los observados. U= na vez conocido en cierto grado la naturaleza y el comportamiento de la zona mediante la aplicación del modelo HBV, a partir de las respuestas (aportaciones) obtenidas en cada sistema mediante el software Rs Minerve, se comparó co= n las aportaciones resultantes del modelo SIMPA (Simulación Precipitación- Aportación), desarrollado por el Centro de Estudios Hidrográficos del Centr= o de Estudios y Experimentación de Obras Públicas (CEDEX), que es el modelo que emplea la Confederación Hidrográfica del Ebro para la gestión y evaluación = de los recursos hídricos en régimen natural para determinar las aportaciones d= el sistema de explotación del río Jalón.

Como se muestra en la Figura 5, las aportaciones del modelo SIMPA durante el periodo analizado (1950-2006) se encuentran casi en su totalidad por encima de las del modelo HBV, estas en varios casos como en el año hidrológico 1987 se encuentran sobreestimando l= os caudales circulantes en el sistema en gran proporción siendo junio/ del año hidrológico 1987 el punto de mayor diferencia entre los dos modelos (91.47 = Hm3/mes). En toda la serie se evidencia que los picos de caudales distan en la mayorí= a de los casos aproximadamente 15 Hm3/mes. Para el caso de la estimación de caud= ales bajos estos se correlacionan más entre sí, siendo en este caso que las aportaciones del modelo HBV se encuentran en todo momento en igualdad o ligeramente inferiores a las estimaciones realizadas por el modelo SIMPA.

 

Figura 5. Aportaciones anuales del Sistema de Explotación del río Jalón

 

 

 

Conclusiones

·      =    En este estudio se desarrolló la evaluación de los recursos hídricos del sistema del río Jalón a través de la aplicación de modelos de precipitación-escorrentía en forma semidistribuida empleando la herramienta Rs Minerve 2.0 la cual mediante el modelo HBV permitió analizar el comportamiento de l= os recursos hídricos, flujos superficiales, subterráneos e influencia que ejer= cen las estructuras de regulación en todas las subcuencas que forman parte del sistema de explotación.

·&nb= sp;        Los resultados del análisis en desem= bocadura calibrados y validados (0.83 y 0.67 respectivamente) del sistema de explota= ción del río Jalón fueron buenos a pesar de la incertidumbre que conllevan los M= PE y de los errores sistemáticos de calibración mientras más aguas abajo nos encontramos en el sistema, esto debido a las alteraciones que se derivan de= los embalses, y a las importantes detracciones de agua para satisfacer las demandas.

·&nb= sp;        Realizado el análisis se deduce que = el modelo SIMPA se encuentra sobreestimando los caudales, mismas que pueden te= ner repercusiones al momento de la gestión de la demanda, dado que al hipotéticamente disponer de más recursos se podría asignar los mismos a otro tipo de demandas, sin embargo si en la realidad estas aportaciones estimada= s no se cumplen se podría generar fallos en el sistema, razón por la cual se debe tener cuidado al momento de tomar decisiones, en la planificación y gestión= de los recursos, teniendo en cuenta que siempre debemos estar del lado de la seguridad.

·      =    Finalmente, hay que señalar que los = modelos de precipitación constituyen una herramienta indispensable en la gestión de= los recursos hídricos, las aportaciones generadas por los MPE generalmente se emplean como entradas a los modelos de gestión cuyo objetivo principal es la estimación de garantías de suministro a las demandas, predicción de avenida= s, gestionar adecuadamente los recursos, entre otras. Además, es importante recordar que la efectividad del modelo y su capacidad de predicción depende= n en gran parte de la forma y circunstancias bajo las cuales fueron elaboradas y principalmente de la comprensión y entendimiento de los procesos hidrológic= os que se desarrollan en la cuenca que se está estudiando.

Agradecimiento

·&nb= sp;        A la Confederación Hidrográfica del = rio Jalón, por ser el ente que facilitó el régimen de aportaciones para el dearrollo del modelo.

 

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Bates, P. D., & De Roo, A. P. J. (2000). A simple raster-based model for flood inundation simulation. Journal of hydrology, 2= 36(1), 54-77.

Benoit, R., Pellerin, P., Kouwen, N., Ritchie, H., Donaldson, N., Joe, P., & Soulis<= /span>, E. D. (2000). Toward the use of coupled atmospheric and hydrologic models at regional scale. Monthly Weather Review, 128(6), 1681- 1706.

Bergström, S., & Singh,= V. P. (1995). The HBV model. Computer models of watershed hydrology. 443-476.

De Roo, A. P. J. (1998). Modelling runoff and sediment transport in catchments using GIS. Hydrological processes, 12(6), 905-922.<= o:p>

De vos, N.J., Rientjes, T.H.M. and Savenije, H.H.G, 2006 Enhanced conce= ptual rainfall - runoff modeling through ensemble Kalman filtering.

Ewen, J., Parkin, G., & O'Connell, P. E. (2000). SHET= RAN: distributed river basin flow and transport modeling system. Journal of hydrologic engineering, 5(3), 250-258.

García Hernández, J., Boillat, J.-L., Feller, I. and Schleiss A. J. (2013). Présent et futur des prévisions hydrologiques = pour la gestion des crues. Le cas du Rhône alpin. Mémoire de la Société vaudoise des Sciences naturelles 25: 55-70. ISSN 0037-9611.

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Mulvany, W. T., Fraser, W= ., Roberts, S., Mulvany, T. J., & O'Flaherty, = J. (1850). Appendix No. V: Notices of Antiquities Presented to the Royal Irish Academy by WT Mulvany, Esq., MRIA, on the Part = of the Commissioners of Public Works. Proceedings of the Royal Irish Academy (1836-1869), 5, xxxi-lxvi.

Refsgaard, J. C., Storm, B.= , & Refsgaard, A. (1995). Recent developments of the Systeme Hydrologique Europeen(SHE) towards the MIKE SHE. International Association of Hydrological Sciences, Publication, (231), 427-434.

Sherman, L. K. (1932). Streamflow from rainfall by the unit-graph method. Eng. News Record, 108, 501-505.

Taffese, T. E. W. O. D. R= . O. S. (2011). Physically based rainfall: Runoff modelling in the northern Ethiopi= an highlands: The case of Mizewa watershed.

Vivoni<= /span>, E. R., & Camilli, R. (2003). Real-time streaming of environm= ental field data. Computers & Geosciences, 29(4), 457-468.<= /p>

Wigmosta, M. S., Vail, L. = W., & Lettenmaier, D. P. (1994). A distributed hydrology‐vegetation model for complex terrain. Water resources research, 30(6), 1665-1679.

 

 

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<= span style=3D'font-size:12.0pt;color:black;mso-color-alt:windowtext;background:w= hite; mso-ansi-language:ES-EC'>Chuquin, D., Chuquin, N., Chuquin, J., Castro, L., & Cepeda, R. (2019). Desarrollo de un modelo de precipitación escorrentía semi-distribuido para= la evaluación de los recursos hídricos del río Jalón. Ciencia Digital3(3.1), 115-126. https://doi.org= /10.33262/cienciadigital.v3i3.1.680=

 

 

<= br clear=3Dall style=3D'mso-special-character:line-break'>

El artículo que se publica = es de exclusiva responsabilidad de los autores y no necesariamente reflejan el pensamiento de la Revista Ciencia Digital.

El artículo queda en propiedad de la revista y, por tanto, su publicación parcial y/o total en otro medio tiene que ser autoriz= ado por el director de la Revista Cien= cia Digital.



= [1] Escuela Superior Politécnica de Chimborazo, Chimborazo, Ecuador, daniel.chuquin@espoch.edu.e= c

= [2] Escuela Superior Politécnica de Chimborazo, Chimborazo, Ecuador, nelson.chuquin@espoch.edu.ec

= [3] Escuela Superior Politécnica de Chimborazo, Chimborazo, Ecuador, juan.chuquin@espoch.edu.ec

= [4] Escuela Superior Politécnica de Chimborazo, Chimborazo, Ecuador, lidia.castro@espoch.edu.ec<= o:p>

= [5] Escuela Superior Politécnica de Chimborazo, Chimborazo, Ecuador, ccepeda@espoch.edu.ec

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                                                 =                                                              = ISSN: 2602-8085

=                              Vol. 3, N°3.1, p. 115-126, julio - septiembre, 201 9

Explor= ador Digital               =                                                                          =                                               Página 102

 

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