Improving Sediment Transport Modelling By A Combination Of Field Data And Sensitivity Analysis

Traditionally, the relationship between flow rate and sediment concentration in rivers has been estimated empirically. However, the problem of empirical data collection is that it is often difficult to cover the entire range of flow rates. Especially higher flow rates are often undersampled, which might lead to an underestimation of modelled sediment transport as flood events are often associated with important erosion events. In order to overcome this limitation, the introduction of the transport capacity concept can establish a safe upper bound of this sediment transport relationship. Nevertheless, given the number of implied variables in this equation, there is a high uncertainty associated with it. In this study, we aim to reduce the uncertainty on the modelled sediment transport by constraining the relation between sediment concentration and flow rate by means of a combination of sensitivity analysis and field data. This theory is implemented in a model that was used to simulate sediment transport in the Guadalquivir river basin, one of the most important rivers in the Mediterranean (56 978 km2). The sediment concentration-flow rate relation was established by combining the empirical data for the lower flow domain and Yang’s total load formula for the upper flow domain. In combination with data from automated gauging networks, the total annual sediment transport was calculated to be between 6.0 106 and 13.1 107 Mg year-1. A global sensitivity analysis of the main parameters of Yang’s equation was done to identify key data input constraints. This revealed that one of the most important parameters was the mean sediment diameter. A field sampling of flood deposits was done inmediately after high flow events to determine its range

La hidrofobia en los suelos arenosos del parque natural de Doñana: caracterización y distribución

La hidrofobia, o repelencia al agua que se manifiesta en algunos suelos, dificulta la infiltración del agua, y, consecuentemente, el establecimiento de vegetación. Como la repelencia aparece en zonas aisladas se favorecen los flujos preferenciales en su contorno. En este trabajo se muestran algunas características hidrofóbicas detectadas en los suelos arenosos del cordón dunar del litoral atlántico próximo al Parque Nacional de Doñana, analizando su origen y extensión en las áreas analizadas

Is the von Krmn constant affected by sediment suspension?

Is the von Krmn constant affected by sediment suspension? The presence of suspended sediment in channels and fluvial streams has been known for decades to affect turbulence transfer mechanism in sediment-laden flows, and, therefore, the transport and fate of sediments that determine the bathymetry of natural water courses. This study explores the density stratification effects on the turbulent velocity profile and its impact on the transport of sediment. There is as yet no consensus in the scientific community on the effect of sediment suspension on the von Krmn parameter, . Two different theories based on the empirical log-wake velocity profile are currently under debate: One supports a universal value of =0.41 and a strength of the wake, , that is affected by suspended sediment. The other suggests that both and could vary with suspended sediment. These different theories result in a conceptual problem regarding the effect of suspended sediment on , which has divided the research area. In this study, a new mixing length theory is proposed to describe theoretically the turbulent velocity profile. The analytical approach provides added insight defining as a turbulent parameter which varies with the distance to the bed in sediment-laden flows. The theory is compared with previous experimental data and simulations using a k-turbulence closure to the Reynolds averaged Navier Stokes equations model. The mixing length model indicates that the two contradictory theories incorporate the stratified flow effect into a different component of the log-wake law. The results of this work show that the log-wake fit with a reduced is the physically coherent approximation. © 2012. American Geophysical Union. All Rights Reserved.This research was partially funded by the project P08-AGR-03925 (Junta de Andalucía).Peer Reviewe

Influencia de la variabilidad del suelo en la hidrología superficial de una cuenca

[ES] Un conocimiento previo del comportamiento hidrológico de la cuenca es necesario para la elaboración de los proyectos de ingeniería hidráulica. La importancia de la correcta determinación de las propiedades físicas de cada asociación de suelos, como la conductividad hidráulica saturada, es analizada dentro del marco de un modelo hidrológico estocástico y conceptual previamente propuesto por Freeze (1980). La comparación de los resultados con los obtenidos mediante el uso de un modelo determinístico (KINEROS), cuyos datos de entrada son los valores medios de las propiedades del suelo, ilustra las consecuencias de infravalorar la determinación apropiada de los principales parámetros de la cuenca.Moral, FJ.; Giráldez, JV. (1995). Influencia de la variabilidad del suelo en la hidrología superficial de una cuenca. Ingeniería del Agua. 2(1):51-60. https://doi.org/10.4995/ia.1995.2657SWORD516021Ahuja, L.R., y R.D. Williams (1991) Scaling wáter characteristic and hydraulic conductivity based on Gregson-Hector-McGowan approach. Soil Sci. Soc. Am. J., 55:308-319.Brooks, R.H., y A.T. Corey (1964) Hydraulic properties of porous media. Hydrol. Paper num. 3, Colorado State Univ., Fort Collins.Brutsaert, W. (1966) Probability laws for pore-size distributions. Soil Sci.,101:85-92.Campbell, G.S. (1974) A simple method for determining unsaturated conductivity from moisture retention data. Soil Sci., 117:311-314.Freeze, R.A. (1980) A stochastic-conceptual analysis of rainfall-runoff processes on a hillslope. Water Resour. Res., 16:391-408.Fuentes, G., R. Haverkamp y J.-Y. Parlange (1992) Parameter constraints on closed-form soilwater relationship. J. Hydrol., 134:117-142.Gardner, W.R. (1958) Some steady-state solutions of the unsaturated moisture flow equation with application to evaporation from a water table. Soil Sci., 85:228-232.Gardner, W.R., y M.S. Mayhugh (1958) Solutions and tests of the diffusion equation for movement of water in soil. Soil Sci. Soc. Am. J., 22:197-201.Loague, K.M. (1988) Impact of rainfall hydraulic property information on runoff predictions at the hillslope scale. Water Resour. Res., 24:1501-1510.Nash, J.E., y J.V. Sutcliffe (1970) River flow forecasting through conceptual models. 1. A discussion of principles. J. Hydrol., 10:282-290.Ritjema, P.E. (1965) An analysis of actual evapotranspiration. Agric. Res. Rep. 659. Center for agricultural publications and documentation. Wageningen, Holanda.Sander, G.C., J.-Y. Parlange, V. Kuhnel, W.I. Hogarth, D. Lockington y J.P.J. O'Kane (1988) Exact nonlinear solution for constant flux infiltration. J. Hydrol., 97:341-346.Smith, R.E., y J.-Y. Parlange (1978) A parameter-efficienthydrologicinfiltration model. Water Resour. Res., 14:533-538.Van Genuchten, M.Th. (1980) A closed form equation for predicting the hydraulic conductivity of unsaturated soils. Soil Sci. Soc. Am. J., 44:892-898.Warrick, A.W. (1990) Application of scaling to the characterization of spatial variability in soils, en O. Hillel y D.E. Elrick, eds, Scaling in soil physics: principles and applications. Soil Sci. Soc. Am., Spec. Publ. 25, cap. 4.Warrick, A.W., G.J. Mullen y D.R. Nielsen (1977) Scaling field-measured soil hydraulic properties using a similar media concept. Water Resour. Res., 13:355-362.Woolhiser, D.A. y D.C. Goodrich (1988) Effect of storm rainfall intensity patterns on surface runoff. J. Hydrol., 102:335-354.Woolhiser, D.A., R.E. Smith y D.C. Goodrich (1990) KINEROS, A kinematic runoff and erosion model: Documentation and user manual. U.S. Dept. Agri. ARS, ARS-77, Washingto

Catch-C

El fin principal del Proyecto Catch-C es evaluar la compatibilidad en diferentes explotaciones agroganaderas de prácticas de manejo sostenibles analizando las dificultades, sinergias y ventajas, entre el incremento de la productividad, la mitigación de los efectos del cambio climático y la conservación de la calidad química, física y biológica del suelo. Estos resultados sobre buenas prácticas de manejo y su viabilidad en diferentes tipos de explotaciones y ambientes crearán una conciencia sobre las ventajas e inconvenientes de distintas opciones de manejo y de políticas agrarias

La hidrofobia en los suelos arenosos del parque natural de Doñana

La hidrofobia, o repelencia al agua que se manifiesta en algunos suelos, dificulta la infiltración del agua, y, consecuentemente, el establecimiento de vegetación. Como la repelencia aparece en zonas aisladas se favorecen los flujos preferenciales en su contorno. En este trabajo se muestran algunas características hidrofóbicas detectadas en los suelos arenosos del cordón dunar del litoral atlántico próximo al Parque Nacional de Doñana, analizando su origen y extensión en las áreas analizadas

Impact of Climate Change on Agricultural Droughts in Spain

Drought is an important natural hazard that is expected to increase in frequency and intensity as a consequence of climate change. This study aimed to evaluate the impact of future changes in the temperature and precipitation regime of Spain on agricultural droughts, using novel static and dynamic drought indices. Statistically downscaled climate change scenarios from the model HadGEM2-CC, under the scenario representative concentration pathway 8.5 (RCP8.5), were used at a total of 374 sites for the period 2006 to 2100. The evolution of static and dynamic drought stress indices over time show clearly how drought frequency, duration and intensity increase over time. Values of static and dynamic drought indices increase over time, with more frequent occurrences of maximum index values equal to 1, especially towards the end of the century (2071–2100). Spatially, the increase occurs over almost the entire area, except in the more humid northern Spain, and in areas that are already dry at present, which are located in southeast Spain and in the Ebro valley. This study confirms the potential of static and dynamic indices for monitoring and prediction of drought stress

Hidroquímica de la Laguna de Tiscar (Córdoba, España)

La laguna de Tíscar es uno de los seis espacios lagunares que constituyen la Reserva Natural de las Zonas húmedas de la provincia de Córdoba. De los resultados obtenidos en el presente trabajo se deduce la ubicación de dicha laguna sobre depósitos salinos triásicos, siendo la disolución de este sustrato la fuente originaria de los iones presentes en las aguas subterráneas que la alimentan. La aplicación del programa «Geochem» y la de otros métodos analíticos tradicionales, ponen de manifiesto la presencia en este medio lagunar de yeso y halita como especies minerales mayoritarias, no detectándose en ningún caso la presencia de calcita y dolomita

Evaluation of Drought Stress in Cereal through Probabilistic Modelling of Soil Moisture Dynamics

The early and accurate detection of drought episodes is crucial for managing agricultural yield losses and planning adequate policy responses. This study aimed to evaluate the potential of two novel indices, static and dynamic plant water stress, for drought detection and yield prediction. The study was conducted in SW Spain (Córdoba province), covering a 13-year period (2001–2014). The calculation of static and dynamic drought indices was derived from previous ecohydrological work but using a probabilistic simulation of soil moisture content, based on a bucket-type soil water balance, and measured climate data. The results show that both indices satisfactorily detected drought periods occurring in 2005, 2006 and 2012. Both their frequency and length correlated well with annual precipitation, declining exponentially and increasing linearly, respectively. Static and dynamic drought stresses were shown to be highly sensitive to soil depth and annual precipitation, with a complex response, as stress can either increase or decrease as a function of soil depth, depending on the annual precipitation. Finally, the results show that both static and dynamic drought stresses outperform traditional indicators such as the Standardized Precipitation Index (SPI)-3 as predictors of crop yield, and the R2 values are around 0.70, compared to 0.40 for the latter. The results from this study highlight the potential of these new indicators for agricultural drought monitoring and management (e.g., as early warning systems, insurance schemes or water management tools)

Análisis de la producción de sedimentos en una cuenca con un sistema de información geográfica. El sistema Cubillas-Colomera

[ES] En este trabajo se analiza la producción de sedimentos en las cuencas de los ríos Cubillas y Colomera, afluentes del río Genil, que tienen los embalses conectados. Para ello se ha aplicado la ecuación universal de pérdida de suelo sobre las celdillas de una gran retícula en la que se han dividido las cuencas, abordando el estudio en un sistema de información geográfica. La circulación de sedimentos se basa en los coeficientes de entrega definidos en función del tiempo de viaje por la superficie de la cuenca, propuesta por Dickinson y Rudra (1990) en el modelo GAMES, adaptándola en algunos aspectos al método propuesto. Una vez validado el modelo, mediante la comparación de los resultados obtenidos con los recogidos en la bibliografía, y ante la imposibilidad de realizar una correcta calibración del mismo al no existir datos experimentales suficientes, se ha realizado un análisis de sensibilidad con el propósito de estimar el nivel de error introducido en los resultados del modelo, ante variaciones de su parámetro principal. Finalmente, se han simulado diferentes situaciones para localizar las zonas más susceptibles de mejora con diferentes prácticas de conservación, concluyéndose que el método estima bien los niveles erosivos de las cuencas, y las cantidades de sedimento aportadas a sus respectivos embalses. Además se ha determinado el valor umbral del llamado factor de cubierta por encima del cual es preferible un cambio de manejo del suelo frente a la protección directa de cauces fluviales, para disminuir el sedimento recibido por los embalses.Carvajal Ramírez, F.; Giráldez Cervera, JV. (2000). 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M.A.P.A., Madrid.Dickinson W.T. y Rudra R.P. 1990. Games: The Guelph model for evaluating effects of agricultural management systems on erosion and sedimentation. User's manual. Versión 3.01. University of Guelph. School of engineering. Technical Reports 126-86.Environmental System Research Institute Inc. 1992. ARC/INFO Users guide. Nueva York.Foster G.R y Weissmeier W.H. 1974. Evaluating irregular slopes for soil loss prediction. Trans. ASAE 17: 305-309.Foster G.R. y Meyer L.D. 1975. Mathematical simulation of upland erosion by fundamental erosion mechanism. USDA-ARS-S-40: 190.Govers, G. Y Desmet P.J.J. 1995. A procedure for Calculation of the LS-Factor for USLE-Type Models on Topographically Complex Ladscape Units. Procedings de Joint European Conference and Exhibition on Geographical Information. Netherlands, 26-31 de marzo de 1995.Govindaraju R.S. 1995. Non-dimensional analysis of a physically based rainfall-runoff-erosion model over steep slopes. J. Hydrol. 173: 327-341.Hrissanthou, V. 1990. Application of a sediment routing model to a middle european watershed. Water Resour. Bull. 26: 801-810.IARA. 1986. Estudio Hidrológico de Andalucía. Consejería de Agricultura y Pesca. Junta de Andalucía.ICONA. 1982. Mapa de fenómenos de erosión hídrica en España (Península y Baleares). E 1/100000. Dirección General de Medio Ambiente e ICONA. Madrid.ICONA. 1987. Mapa de estados erosivos. Cuenca Hidrográfica del Guadalquivir. Instituto Nacional para la Conservación de la Naturaleza. MAPA Madrid.Janson M.B. 1982. Land erosion by water in different climates. UNGI Rapport Nr 57. Uppsala University.Lane L.J. Nearing M.A. 1989. USDA-Water Erosion Prediction Project: Hillslope profile model documentation. USDA-Agricultural Research Service.Lane L.J., Shirley E.D. y Singh V.P. 1988. Modelling erosion on hillslopes. En: Modelling Geomorphological Systems. Anderson M.G. ed. John and Sons.Masa M. 1996. Control de la evolución de los sedimentos en el embalse de Cubillas (Granada). Actas de las V Jornadas Españolas de Presas. Comité Nacional Español de Grandes Presas. Valencia.McCool D.K., Brown L.C., Foster G.R., Mutchler C.K. y Meyer L.D. 1987. Revised slope steepness factor for the universal soil loss equation. Trans. ASAE 30: 1387-1396.McCuen, R.H. y Snyder, W.M. 1986. Hydrologic Modeling. Prentice Hall, Englewood Cliffs.Meyer L.D. y Weischmeier W.H. 1969. Mathematical simulation of the process of soil erosion by water. Trans. ASAE 12: 754-758.Moore, I.D. y Burch, G.J. 1986. Physical Basis of the Length-slope Factor in the Universal Soil Loss Ecuation. Soil Sci. Soc. Am. J. 50: 1294-1298.Morgan R.P.C., Morgan D.D.V., y Finney H.J. 1984. A predictive model for the assessment of soil erosion risk, J. Agric. Engng. Res. 30: 245-253.Morgan, R.P.C., Quinton J.N., Smith R.E., Govers G., Poesen J.W.A., Auerswald K., Chisci G., Torri D., Styczen M.E. y Folly A.J.V. 1998. 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Madrid.Singh V.P. 1989. Hydrologic systems. Watershed Modeling. Volumen II. Prentice Hall, Englewood Cliffs.Simons D.B. y Sentürk F, 1992. Sediment transport technology. Water Resources Publication, Littleton.Stocking, M., C. Kalabane, y H. Elwell, 1988. An inproved methodology for erosion mapping. Geogr. Anal. 70A: 169-180.Williams J.R. 1975a. Sediment-yield prediction with Universal Ecuation using runoff energy factor. En: Present and prospective technology for predicting sediment yields and sources. ARS-S-40, USDA-Agricultural Research Service: 244-252.Williams J.R. 1975b. Sediment routing for agricultural watersheds. Water Resour.Bull. 11: 965-974.Williams J.R. 1977. Sediment delivery ratios determined with sediment and runoff models. IAHS, 122: 168-178.Wischmeier W.H. y D.D. Smith. 1958a. Predicting rainfall erosion losses from cropland east of the Rocky Mountains, USDA, Agr. Hbk. 282.Wischmeier W.H. y D.D. Smith. 1958b. Rainfall Energy and Its Relation to Soil Loss. Am. Geophys. Union Trans. 39:285-291.Wischmeier W.H. y D.D. Smith. 1978. Predicting rainfall erosion losses -a guide to conservation planning. USDA, Agric. Hbk. nº 537.Woolhiser D.A., R.E. Smith y D.C. Goodrich. 1990. KINEROS, a kinematic runoff and erosion model. USDA-ARS-7