Aplicación de un sistema de información geográfica en la gestión avanzada de la red de colectores de Valencia

La ingente cantidad de información presente en el Sistema de Drenaje Urbano de cualquier ciudad hace imposible su gestión mediante procedimientos tradicionales. Por otra parte, el mantenimiento y crecimiento de esta red consume todos los años un porcentaje apreciable del presupuesto municipal. Por ello se hace necesario la implantación de un Sistema Avanzado de Gestión que pueda "digerir" la información existente, y pueda ayudar en la priorización de las inversiones futuras en la red. El objetivo de este artículo es presentar SIRA, que es una aplicación de un SIG en la Gestión Avanzada de un Sistema de Drenaje Urbano, y que se encuentra en este momento parcialmente operativo en la ciudad de Valencia

Utilización de la función de distribución de probabilidad TCEV con información no sistemática dentro de un análisis regional. Aplicación a los ríos Júcar y Turia

[ES] Debido a sus implicaciones sociales y económicas, en el análisis de la frecuencia de las avenidas es exigible la mayor precisión posible. Para ello debe seleccionarse el modelo estadístico más adecuado y utilizarse la máxima información disponible. Las avenidas de los ríos mediterráneos se originan mediante dos mecanismos distintos, lo cual exige el empleo de una función de distribución no tradicional como es la TCEV. El incremento de información puede obtenerse mediante la utilización de información no sistemática adicional, o un análisis regional, o ambos (como en el caso del ejemplo presentado). A través del concepto de ganancia estadística se demuestra que el empleo de información no sistemática adicional puede suponer fácilmente disminuciones de más del 50% en el error de estimación de un cuantil. En un análisis regional, el beneficio de la información no sistemática en una estación de aforos, se transmite al resto de estaciones con sólo una pequeña disminución respecto de la ganancia estadística de un análisis local equivalente.El presente trabajo ha estado auspiciado parcialmente por el proyecto de la CICYT con referencia HID96-1318.Francés García, F. (1998). Utilización de la función de distribución de probabilidad TCEV con información no sistemática dentro de un análisis regional. Aplicación a los ríos Júcar y Turia. Ingeniería del Agua. 5(1):47-58. https://doi.org/10.4995/ia.1998.2743SWORD475851Arnell, N.W., S. Gabriele, (1988) The Performance of the Two-Component Extreme Value Distribution in Regional Flood Frequency Analysis. Water Res. Res. 24, 879-887.Baker, V.R., (1987) Paleofloodhydrology and extraordinary flood events. Jour, of Hydrol.96, 79-99.Baker, R., R. C. Kochel and P. C. Patton (eds.), (1988) Flood geomorphology. Wiley, New York.Bartley, P., B.L. Fox, L.E. Schräge, (1987) A Guide to Simulation. Springer-Verlag.Benson, M.A., (1950) Use of Historical Data in Flood Frequency Analysis. Eos. Trans. AGU.31 (3), 419-424.Beran, M., J. R. M. Hosking, and N. Arnell, (1986) Comment on "Two-Component Extreme Value Distribution for Flood Frequency Analysis". WaterRes. Res.22, 263-266.Berga, L., (1991) Flood Forecasting in Spain. Procc. of XXIV IAHR International Congress, Madrid, A 79-88.Boes, D.C., J. Heo, J.D. Salas, (1989) Regional Flood Quantité Estimation for a Weibull Model. Water Res. Res.25, 979-990.Calvo, F., (1989) Grandes Avenidas e Inundaciones Históricas. Reunión Científica Internacional sobre Avenidas Fluviales e Inundaciones en la Cuenca del Mediterráneo. Universidad de Alicante.Carmona González, P., (1990) La Formado de la Plana Al.luvial de València. Institució Valenciana d'Estudis i Investigació, Valencia.Centro de Estudios Hidrográficos, (1983) Actualización de los Estudios de Desagüe de la Autopista Tarragona-Alicante. Tomo IV: Cruce con el rio Júcar. MOPU, Madrid.Cohn, T.A., J.R. Stedinger, (1987) Use of Historical Information in a Maximum Likelihood Framework. Jour, of Hydrol.96, 215-233.Condie, R., y K.H. Lee, (1982) Flood Frequency Analysis with Historic Information. Jour, of Hydrol. 58,47-61.Cunnane, C., (1988) Methods and merits of regional flood frequency analysis. Jour, of Hydrol., 100,269-290.Ferrari, E, (1994) Regional Rainfall and Flood Frequency Analysis in Italy. Preprocc. UNESCO IPH-IV "Developments in Hydrology of Mountainous Areas: Regionalization of Rare Extreme Floods and Precipitation", Stará Lesná, Eslovaquia.Ferrer, J, (1996) El modelo de función de distribución SQRT-ET max en elanálisis regional de máximos hidrológicos: aplicación a lluvias diarias. Tesis doctoral.Ferrer, J y L. Ardiles, (1994) Análisis estadístico de las series anuales de máximas lluvias diarias en España. Ingeniería Civil. 95, 87-100.Francés, F., (1995) Utilización de la Información Histórica en el Análisis Regional de las Avenidas. Centro Internacional de Métodos Numéricos en Ingeniería, monografía n1 27, 242 pp, BarcelonaFrancés, F., J.D. Salas y D.C. Boes, (1991) Flood Frequency Analysis by Using Historical Information. Procc. of XXIV IAHR International Congress, Madrid. A 11-21.Francés, F., J.D. Salas y D.C. Boes, (1994) Flood frequency analysis with systematic and historical or paleoflood data based on the two-parameter general extreme value models. Water Res. Res., 30(6), 1653-1664.Hirsch, R. M., (1987) Probability Plotting Position Formulas for Flood Records with Historical Information.Jour, of Hydrol., 96, 185-199Hosking, J.R.M., J.R. Wallis, (1986a) Paleoflood Hydrology and Flood Frequency Analysis. Water Res. Res., 22 (4), 543-550.Hosking, J.R.M., J.R. Wallis, (1986b) The Value of Historical Data in Flood Frequency Analysis. Water Res. Res., 22 (11), 1606-1612.Hosking, J.R.M. y J.R. Wallis, (1988) The effect of intersite Dependence on regional flood frequency analysis. Water Res. Res., 24 (4), 588-600.Guo, S. L. y C. Cunnane, (1991) Evaluation of the usefulness of historical and paleological floods in quantile estimation. Jour. of Hydrol., 129, 245-262.Jin, M. y J. R. Stedinger, (1989) Flood Frequency Analysis with Regional and Historical Information. Water Res. Res., 25 (5), 925-936.Kendall, M. G. y A. Stuart, (1967) The Advanced Theory of Statistics. Vol. II, 2nd Edition, Hafner Publ. Co., New York.Kottegoda, N.T., 1984. Investigation of Outliers in Annual Maximun Flow Series. Journal of Hydrology, 72, 105-137.Kroll, C.N. y J.R. Stedinger, 1996. Estimation of moments using censored data. Water Res. Res.,32 (4),1005-1012.Landwehr, J.M., N.C. Matalas y J.R. Wallis, (1979) Probability Weighted Moments Compared with some Traditional Techniques in Estimating Gumbel Parameters and Quantiles. Water Res. Res.,15, 1055-1064.Leese, M. N., (1973) Use of Censored Data in the Estimation of Gumbel Distribution Parameters for Annual Maximum Flood Series. Water Res. Res., 9, 1534-1542.Matalas, N. C., J. R. Slack, and J. R. Wallis, (1975) Regional Skew in Search of a Parent. Water Res. Res., 11 (6), 815-826.Phien, H. N. y T. E. Fang, (1989) Maximum likelihood estimation of the parameters and quantiles of the general extreme-value distribution from censored samples. Jour. of HydRol., 105, 139-155.Pilon, P. J. y K. Adamowski, (1993) Asymptotic variance of fload quantile in log Pearson type 111 distribution with historical information. Jour, of Hydrol. 143, 481-503.Potter, W.D., (1958) Upper and Lower Frequency Curves for Peak Rates of Runnof. EOS. Trans. AGU. 39, 100-105.Press, W.H., B.P. Flannery, S.A. Tevkolsky y W.T. Vetterlig, (1989) Numerical REcipies. Cambridge University Press, 702 p.Rossi, F., M. Fiorentino y P. Versace, (1984) Two-Component Extreme Value Distribution for Flood Frequency Analysis Water Res. Res., 20, p. 847- 856.Stedinger, J.R. y T.A. Cohn, 1986. Flood Frequency Analysis with Historical and Paleoflood Information. Water Res. Res., 22 (5), 785-793

Parsimonious Modeling of Snow Accumulation and Snowmelt Processes in High Mountain Basins

[EN] The success of hydrological modeling of a high mountain basin depends in most case on the accurate quantification of the snowmelt. However, mathematically modeling snowmelt is not a simple task due to, on one hand, the high number of variables that can be relevant and can change significantly in space and, in the other hand, the low availability of most of them in practical engineering. Therefore, this research proposes to modify the original equation of the classical degree-day model to introduce the spatial and temporal variability of the degree-day factor. To evaluate the effects of the variability in the hydrological modeling and the snowmelt modeling at the cell and hillslope scale. We propose to introduce the spatial and temporal variability of the degree-day factor using maps of radiation indices. These maps consider the position of the sun according to the time of year, solar radiation, insolation, topography and shaded-relief topography. Our priority has been to keep the parsimony of the snowmelt model that can be implemented in high mountain basins with limited observed input. The snowmelt model was included as a new module in the TETIS distributed hydrological model. The results show significant improvements in hydrological modeling in the spring period when the snowmelt is more important. At cell and hillslope scale errors are diminished in the snowpack, improving the representation of the flows and storages that intervene in high mountain basins.This study was supported by the Universidad de Guanajuato, Spanish National Parks Administration through the ACOPLA project (OAPN 011/2008), the Spanish Ministry of Science and Innovation through the projects ECO-TETIS (CGL2011-28776-C02-01), TETISMED (CGL2014-58127-C3-3-R) and TETISCHANGE (RTI2018-093717-B-I00).Orozco Medina, I.; Francés, F.; Mora, J. (2019). Parsimonious Modeling of Snow Accumulation and Snowmelt Processes in High Mountain Basins. Water. 11(6):1-19. https://doi.org/10.3390/w11061288S119116Riboust, P., Thirel, G., Moine, N. L., & Ribstein, P. (2019). Revisiting a Simple Degree-Day Model for Integrating Satellite Data: Implementation of Swe-Sca Hystereses. Journal of Hydrology and Hydromechanics, 67(1), 70-81. doi:10.2478/johh-2018-0004Beniston, M., Farinotti, D., Stoffel, M., Andreassen, L. M., Coppola, E., Eckert, N., … Vincent, C. (2018). The European mountain cryosphere: a review of its current state, trends, and future challenges. The Cryosphere, 12(2), 759-794. doi:10.5194/tc-12-759-2018Bernsteinová, J., Bässler, C., Zimmermann, L., Langhammer, J., & Beudert, B. (2015). Changes in runoff in two neighbouring catchments in the Bohemian Forest related to climate and land cover changes. Journal of Hydrology and Hydromechanics, 63(4), 342-352. doi:10.1515/johh-2015-0037Mateo-Lázaro, J., Castillo-Mateo, J., Sánchez-Navarro, J., Fuertes-Rodríguez, V., García-Gil, A., & Edo-Romero, V. (2019). Assessment of the Role of Snowmelt in a Flood Event in a Gauged Catchment. Water, 11(3), 506. doi:10.3390/w11030506Vormoor, K., Lawrence, D., Heistermann, M., & Bronstert, A. (2015). Climate change impacts on the seasonality and generation processes of floods – projections and uncertainties for catchments with mixed snowmelt/rainfall regimes. Hydrology and Earth System Sciences, 19(2), 913-931. doi:10.5194/hess-19-913-2015Kling, H., Fürst, J., & Nachtnebel, H. P. (2006). Seasonal, spatially distributed modelling of accumulation and melting of snow for computing runoff in a long-term, large-basin water balance model. Hydrological Processes, 20(10), 2141-2156. doi:10.1002/hyp.6203Verdhen, A., Chahar, B. R., & Sharma, O. P. (2014). Springtime Snowmelt and Streamflow Predictions in the Himalayan Mountains. Journal of Hydrologic Engineering, 19(7), 1452-1461. doi:10.1061/(asce)he.1943-5584.0000816Dudley, R. W., Hodgkins, G. A., McHale, M. R., Kolian, M. J., & Renard, B. (2017). Trends in snowmelt-related streamflow timing in the conterminous United States. Journal of Hydrology, 547, 208-221. doi:10.1016/j.jhydrol.2017.01.051Penna, D., van Meerveld, H. J., Zuecco, G., Dalla Fontana, G., & Borga, M. (2016). Hydrological response of an Alpine catchment to rainfall and snowmelt events. Journal of Hydrology, 537, 382-397. doi:10.1016/j.jhydrol.2016.03.040Vormoor, K., Lawrence, D., Schlichting, L., Wilson, D., & Wong, W. K. (2016). Evidence for changes in the magnitude and frequency of observed rainfall vs. snowmelt driven floods in Norway. Journal of Hydrology, 538, 33-48. doi:10.1016/j.jhydrol.2016.03.066Yilmaz, A. G., Imteaz, M. A., & Ogwuda, O. (2012). Accuracy of HEC-HMS and LBRM Models in Simulating Snow Runoffs in Upper Euphrates Basin. Journal of Hydrologic Engineering, 17(2), 342-347. doi:10.1061/(asce)he.1943-5584.0000442Costa, D., Pomeroy, J., & Wheater, H. (2018). A numerical model for the simulation of snowpack solute dynamics to capture runoff ionic pulses during snowmelt: The PULSE model. Advances in Water Resources, 122, 37-48. doi:10.1016/j.advwatres.2018.09.008Fuka, D. R., Easton, Z. M., Brooks, E. S., Boll, J., Steenhuis, T. S., & Walter, M. T. (2012). A Simple Process-Based Snowmelt Routine to Model Spatially Distributed Snow Depth and Snowmelt in the SWAT Model1. JAWRA Journal of the American Water Resources Association, 48(6), 1151-1161. doi:10.1111/j.1752-1688.2012.00680.xSchilling, O. S., Park, Y.-J., Therrien, R., & Nagare, R. M. (2018). Integrated Surface and Subsurface Hydrological Modeling with Snowmelt and Pore Water Freeze-Thaw. Groundwater, 57(1), 63-74. doi:10.1111/gwat.12841Semádeni-Davies, A. F. (2000). Representation of Snow in Urban Drainage Models. Journal of Hydrologic Engineering, 5(4), 363-370. doi:10.1061/(asce)1084-0699(2000)5:4(363)Žaknić-Ćatović, A., Howard, K. W. F., & Ćatović, Z. (2017). Modification of the degree-day formula for diurnal meltwater generation and refreezing. Theoretical and Applied Climatology, 131(3-4), 1157-1171. doi:10.1007/s00704-017-2034-8Hock, R. (1999). A distributed temperature-index ice- and snowmelt model including potential direct solar radiation. Journal of Glaciology, 45(149), 101-111. doi:10.3189/s0022143000003087Kustas, W. P., Rango, A., & Uijlenhoet, R. (1994). A simple energy budget algorithm for the snowmelt runoff model. Water Resources Research, 30(5), 1515-1527. doi:10.1029/94wr00152Braithwaite, R. J. (1995). Positive degree-day factors for ablation on the Greenland ice sheet studied by energy-balance modelling. Journal of Glaciology, 41(137), 153-160. doi:10.1017/s0022143000017846Cazorzi, F., & Dalla Fontana, G. (1996). Snowmelt modelling by combining air temperature and a distributed radiation index. Journal of Hydrology, 181(1-4), 169-187. doi:10.1016/0022-1694(95)02913-3Hock, R. (2003). Temperature index melt modelling in mountain areas. Journal of Hydrology, 282(1-4), 104-115. doi:10.1016/s0022-1694(03)00257-9Francés, F., Vélez, J. I., & Vélez, J. J. (2007). Split-parameter structure for the automatic calibration of distributed hydrological models. Journal of Hydrology, 332(1-2), 226-240. doi:10.1016/j.jhydrol.2006.06.032Buendia, C., Bussi, G., Tuset, J., Vericat, D., Sabater, S., Palau, A., & Batalla, R. J. (2016). Effects of afforestation on runoff and sediment load in an upland Mediterranean catchment. Science of The Total Environment, 540, 144-157. doi:10.1016/j.scitotenv.2015.07.005Rogelis, M. C., Werner, M., Obregón, N., & Wright, N. (2016). Hydrological model assessment for flood early warning in a tropical high mountain basin. doi:10.5194/hess-2016-30Ruiz-Villanueva, V., Stoffel, M., Bussi, G., Francés, F., & Bréthaut, C. (2014). Climate change impacts on discharges of the Rhone River in Lyon by the end of the twenty-first century: model results and implications. Regional Environmental Change, 15(3), 505-515. doi:10.1007/s10113-014-0707-8Orozco, I., Ramírez, A. I., & Francés, F. (2018). Modelación de los impactos del Cambio Climático sobre los flujos y almacenamientos en una cuenca de alta montaña. Ingeniería del agua, 22(3), 125. doi:10.4995/ia.2018.8931McGrane, S. J., Hutchins, M. G., Miller, J. D., Bussi, G., Kjeldsen, T. R., & Loewenthal, M. (2017). During a winter of storms in a small UK catchment, hydrology and water quality responses follow a clear rural-urban gradient. Journal of Hydrology, 545, 463-477. doi:10.1016/j.jhydrol.2016.12.037Li, Z., & Fang, H. (2017). Modeling the impact of climate change on watershed discharge and sediment yield in the black soil region, northeastern China. Geomorphology, 293, 255-271. doi:10.1016/j.geomorph.2017.06.005Smith, M., Koren, V., Zhang, Z., Moreda, F., Cui, Z., Cosgrove, B., … Staggs, S. (2013). The distributed model intercomparison project – Phase 2: Experiment design and summary results of the western basin experiments. Journal of Hydrology, 507, 300-329. doi:10.1016/j.jhydrol.2013.08.040Simpson, J. J., Dettinger, M. D., Gehrke, F., McIntire, T. J., & Hufford, G. L. (2004). Hydrologic Scales, Cloud Variability, Remote Sensing, and Models: Implications for Forecasting Snowmelt and Streamflow. Weather and Forecasting, 19(2), 251-276. doi:10.1175/1520-0434(2004)0192.0.co;2Rango, A., & Martinec, J. (1995). REVISITING THE DEGREE-DAY METHOD FOR SNOWMELT COMPUTATIONS. Journal of the American Water Resources Association, 31(4), 657-669. doi:10.1111/j.1752-1688.1995.tb03392.xGaren, D. C., & Marks, D. (2005). Spatially distributed energy balance snowmelt modelling in a mountainous river basin: estimation of meteorological inputs and verification of model results. Journal of Hydrology, 315(1-4), 126-153. doi:10.1016/j.jhydrol.2005.03.026Kane, D. L., Gieck, R. E., & Hinzman, L. D. (1997). Snowmelt Modeling at Small Alaskan Arctic Watershed. Journal of Hydrologic Engineering, 2(4), 204-210. doi:10.1061/(asce)1084-0699(1997)2:4(204)Granberg, G., Grip, H., Löfvenius, M. O., Sundh, I., Svensson, B. H., & Nilsson, M. (1999). A simple model for simulation of water content, soil frost, and soil temperatures in boreal mixed mires. Water Resources Research, 35(12), 3771-3782. doi:10.1029/1999wr900216Viviroli, D., Zappa, M., Gurtz, J., & Weingartner, R. (2009). An introduction to the hydrological modelling system PREVAH and its pre- and post-processing-tools. Environmental Modelling & Software, 24(10), 1209-1222. doi:10.1016/j.envsoft.2009.04.001Smith, T. J., & Marshall, L. A. (2010). Exploring uncertainty and model predictive performance concepts via a modular snowmelt-runoff modeling framework. Environmental Modelling & Software, 25(6), 691-701. doi:10.1016/j.envsoft.2009.11.010Ohmura, A., Kasser, P., & Funk, M. (1992). Climate at the Equilibrium Line of Glaciers. Journal of Glaciology, 38(130), 397-411. doi:10.1017/s0022143000002276Fu, P., & Rich, P. M. (2002). A geometric solar radiation model with applications in agriculture and forestry. Computers and Electronics in Agriculture, 37(1-3), 25-35. doi:10.1016/s0168-1699(02)00115-1Duan, Q., Sorooshian, S., & Gupta, V. (1992). Effective and efficient global optimization for conceptual rainfall-runoff models. Water Resources Research, 28(4), 1015-1031. doi:10.1029/91wr02985Duan, Q., Sorooshian, S., & Gupta, V. K. (1994). Optimal use of the SCE-UA global optimization method for calibrating watershed models. Journal of Hydrology, 158(3-4), 265-284. doi:10.1016/0022-1694(94)90057-4K. Ajami, N., Gupta, H., Wagener, T., & Sorooshian, S. (2004). Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology, 298(1-4), 112-135. doi:10.1016/j.jhydrol.2004.03.033Perrin, C., Michel, C., & Andréassian, V. (2003). Improvement of a parsimonious model for streamflow simulation. Journal of Hydrology, 279(1-4), 275-289. doi:10.1016/s0022-1694(03)00225-7Muttil, N., & Jayawardena, A. W. (2008). Shuffled Complex Evolution model calibrating algorithm: enhancing its robustness and efficiency. Hydrological Processes, 22(23), 4628-4638. doi:10.1002/hyp.7082Nash, J. E., & Sutcliffe, J. V. (1970). River flow forecasting through conceptual models part I — A discussion of principles. Journal of Hydrology, 10(3), 282-290. doi:10.1016/0022-1694(70)90255-6Eckhardt, K., Haverkamp, S., Fohrer, N., & Frede, H.-G. (2002). SWAT-G, a version of SWAT99.2 modified for application to low mountain range catchments. Physics and Chemistry of the Earth, Parts A/B/C, 27(9-10), 641-644. doi:10.1016/s1474-7065(02)00048-7Kalin, L., Govindaraju, R. S., & Hantush, M. M. (2003). Effect of geomorphologic resolution on modeling of runoff hydrograph and sedimentograph over small watersheds. Journal of Hydrology, 276(1-4), 89-111. doi:10.1016/s0022-1694(03)00072-6Merz, R., & Blöschl, G. (2004). Regionalisation of catchment model parameters. Journal of Hydrology, 287(1-4), 95-123. doi:10.1016/j.jhydrol.2003.09.028D. N. Moriasi, J. G. Arnold, M. W. Van Liew, R. L. Bingner, R. D. Harmel, & T. L. Veith. (2007). Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations. Transactions of the ASABE, 50(3), 885-900. doi:10.13031/2013.23153Kapnick, S., & Hall, A. (2010). Observed Climate–Snowpack Relationships in California and their Implications for the Future. Journal of Climate, 23(13), 3446-3456. doi:10.1175/2010jcli2903.1Singh, P., Kumar, N., & Arora, M. (2000). Degree–day factors for snow and ice for Dokriani Glacier, Garhwal Himalayas. Journal of Hydrology, 235(1-2), 1-11. doi:10.1016/s0022-1694(00)00249-3Koren, V., Reed, S., Smith, M., Zhang, Z., & Seo, D.-J. (2004). Hydrology laboratory research modeling system (HL-RMS) of the US national weather service. Journal of Hydrology, 291(3-4), 297-318. doi:10.1016/j.jhydrol.2003.12.039Ciarapica, L., & Todini, E. (2002). TOPKAPI: a model for the representation of the rainfall-runoff process at different scales. Hydrological Processes, 16(2), 207-229. doi:10.1002/hyp.342Shamir, E., & Georgakakos, K. P. (2006). Distributed snow accumulation and ablation modeling in the American River basin. Advances in Water Resources, 29(4), 558-570. doi:10.1016/j.advwatres.2005.06.010Shamir, E., & Georgakakos, K. P. (2007). Estimating snow depletion curves for American River basins using distributed snow modeling. Journal of Hydrology, 334(1-2), 162-173. doi:10.1016/j.jhydrol.2006.10.00

On The Influence Of Error Model In The Good Performance Of The Hydrological Model For The Right Reasons.

Hydrological models provide extrapolations or predictions, which are not lacking of uncertainty, which reduces the confidence in their results. One phase of the hydrological implementation process, which significantly contributes to that uncertainty, is the calibration phase in which values of the unknown model parameters are tuned by optimizing an objective function. Traditionally, the most commonly used fitting criterion,has been the simple least squares (SLS), regardless of the SLS criterion involves assumptions about the probability distribution of the errors. Failure of these assumptions introduces noise into the estimation of the parameters, which leads to the phenomenon called model divergence, where the errors variance of the (spatially and temporally) forecasted flows, far exceeds the errors variance in the fitting period. In the present paper it has been carried out an estimation of the parameters of TETIS, a distributed hydrological model with a particular split structure of the effective model parameters (Francés et al., 2007). Such an estimate has been performed with the aid of a Markov Chain Monte Carlo (MCMC) algorithm called Dream-ZS (Laloy & Vrugt, 2012). MCMC algorithm quantifies the uncertainty of the parameters by getting the posterior probability distribution, conditioned on the observed flows. The calibration process is performed with three error model assumptions. The greater or lesser suitability of the three parameter sets is evaluated through the temporal, spatial and spatiotemporal validation of each one. It is concluded that hydrological models calibrated with a correct hypothesis of the error model, significantly reduces the model divergence phenomenon. Similarly a global sensitivity analysis (GSA) reveals that the relative influence of each parameter in the hydrological model is not independent of the assumed error model. In conclusion, model divergence phenomenon appears meaningful when it have been achieved a very good hydrological model results during calibration, but for the wrong reasons

Aplicación de un sistema de información geográfica en la gestión avanzada de la red de colectores de Valencia

[ES] La ingente cantidad de información presente en el Sistema de Drenaje Urbano de cualquier ciudad hace imposible su gestión mediante procedimientos tradicionales. Por otra parte, el mantenimiento y crecimiento de esta red consume todos los años un porcentaje apreciable del presupuesto municipal. Por ello se hace necesario la implantación de un Sistema Avanzado de Gestión que pueda "digerir" la información existente, y pueda ayudar en la priorización de las inversiones futuras en la red. El objetivo de este artículo es presentar SIRA, que es una aplicación de un SIG en la Gestión Avanzada de un Sistema de Drenaje Urbano, y que se encuentra en este momento parcialmente operativo en la ciudad de Valencia.Francés García, F.; Bellver Jiménez, V. (1997). Aplicación de un sistema de información geográfica en la gestión avanzada de la red de colectores de Valencia. Ingeniería del Agua. 4(3):27-32. https://doi.org/10.4995/ia.1997.2727SWORD273243Ayuntamiento de Valencia, (1995) Manual de normalización de los elementos de saneamiento de la ciudad de Valencia. 131 pp.Burdons, S., Y. Sans y A. Morraja, (1995) Sistemas de Información Territorial del alcantarillado de Barcelona. Mapping, marzo, 75-83.DIHMA (Departamento de Ingeniería Hidráulica y Medio Ambiente de la Universidad Politécnica de Valencia), (1986). Informe sobre las propiedades y estructura de las precipitaciones extremas en Valencia. Ayuntamiento de Valencia, 345 pp.DIHMA, (1994) Plan de Reestructuración de las redes de riego y reutilización de aguas residuales en la Huerta de la Ciudad de Valencia. Consellería de Agricultura de la Generalitat Valenciana, pp 72.Ellis, J. B. y J. Marsalek, (1996) Overview of urban drainage: environmental impacts and concerns, means of mitigation and implementation policies. Journal of Hydraulic Research. 34 (6), 723-731.Gutiérrez, L.A., (1995) Control de la polución pluvial urbana. Un nuevo reto en la protección medio-ambiental. Tecnología del Agua, sep., 49-57.Huxhold, W.E., (1991) An introduction to urban geographic systems. Oxford University Press, 337p.Labadie, J. W., y C. Sullivan, (1986) Computerized Decision Support Systems for Water Managers. Jour. of Water Res. Planning and Management, ASCE, 112(3), 299-307.Malgrat, P. (1995) Control de la contaminación producida por las descargas de sistemas unitarios de alcantarillado. O.P. revista del colegio de ICCP, 33.Miranda, A., (1995) El saneamiento urbano: la nueva frontera tecnológica en el sector del agua. O.P.revista del colegio de ICCP, 31, 66-73.Schilling, W. et al. (ed.), (1989) Real Time Control of Urban drainage Systems. The State of the Art. Pergamon Press

On the use of three hydrological models as hypotheses to investigate the behaviour of a small Mediterranean catchment

Selecting an adequate hydrological model is the first step to carry out a rainfall¿runoff modelling exercise. A hydrological model is a hypothesis of catchment functioning, encompassing a description of dominant hydrological processes and predicting how these processes interact to produce the catchment¿s response to external forcing. Current research lines emphasize the importance of multiple working hypotheses for hydrological modelling instead of only using a single model. In line with this philosophy, here different hypotheses were considered and analysed to simulate the nonlinear response of a small Mediterranean catchment and to progress in the analysis of its hydrological behaviour. In particular, three hydrological models were considered representing different potential hypotheses: two lumped models called LU3 and LU4, and one distributed model called TETIS. To determine how well each specific model performed and to assess whether a model was more adequate than another, we raised three complementary tests: one based on the analysis of residual errors series, another based on a sensitivity analysis and the last one based on using multiple evaluation criteria associated to the concept of Pareto frontier. This modelling approach, based on multiple working hypotheses, helped to improve our perceptual model of the catchment behaviour and, furthermore, could be used as a guidance to improve the performance of other environmental models

Assessment of remotely sensed near-surface soil moisture for distributed eco-hydrological model implementation

The aim of this study was to implement an eco-hydrological distributed model using only remotely sensed information (soil moisture and leaf area index) during the calibration phase. Four soil moisture-based metrics were assessed, and the best alternative was chosen, which was a metric based on the similarity between the principal components that explained at least 95% of the soil moisture variation and the Nash-Sutcliffe Efficiency (NSE) index between simulated and observed surface soil moisture. The selected alternative was compared with a streamflow-based calibration approach. The results showed that the streamflow-based calibration approach, even presenting satisfactory results in the calibration period (NSE = 0.91), performed poorly in the validation period (NSE = 0.47) and Leaf Area Index (LAI) and soil moisture were neither sensitive to the spatio-temporal pattern nor to the spatial correlation in both calibration and validation periods. Hence, the selected soil moisture-based approach showed an acceptable performance in terms of discharges, presenting a negligible decrease in the validation period (ΔNSE = 0.1) and greater sensitivity to the spatio-temporal variables’ spatial representation

La variabilidad climática de baja frecuencia en la modelación no estacionaria de los regímenes de las crecidas en las regiones hidrológicas Sinaloa y Presidio San Pedro

El asumir estacionaridad ha sido una de las premisas principales en el estudio de las componentes del ciclo hidrológico y la piedra angular en el análisis de frecuencia de eventos extremos. La estacionaridad ha sido una hipótesis común y práctica en la planificación y gestión derecursos hídricos. A partir de ella se han usado métodos estadísticos para extraer de los datos todos los indicadores hidrológicos útiles para proporcionar estimaciones, donde estas estimaciones pueden ser refinadas año con año conforme los registros en las estaciones hidrométricas se hacen más largos. En años recientes, diversos estudios han demostrado que los registros hidrológicos presentan algún tipo de no estacionaridad, como cambios y tendencias, lo cual ha llevado a los expertos a un consenso, en el sentido de que la hipótesis de estacionaridad a nivel de cuenca se encuentra comprometida. Entre los principales mecanismos que han sido sugeridos como los inductores de cambios en el ciclo hidrológico de las cuencas y en la magnitud y frecuencia de las crecidas se encuentran los efectos de la intervención humana (p. ej., cambio de uso de suelo, embalses), el efecto de la variabilidad climática de baja frecuencia (p. ej., El Niño-Oscilación del Sur, Oscilación Decadal del Pacífico) y el cambio climático debido al incremento de los gases a la atmósfera. El objetivo del presente estudio yace en el desarrollo de un marco para análisis de frecuencia bajo condiciones de no estacionaridad por medio de los Modelos Aditivos Generalizados en Localización, Escala y Forma (GAMLSS por sus siglas en inglés). Dos diferentes aproximaciones para la modelación estadística no estacionaria fueron las aplicadas a los registros de caudales instantáneos máximos anuales en las regiones hidrológicas Sinaloa y Presidio San Pedro en el noroeste del Pacífico mexicano. Estos modelos consisten básicamente en el modelo con incorporación de tendencias temporales en los parámetros de las distribuciones paramétricas y el modelo con incorporación del forzamiento de la variabilidad climática de baja frecuencia. Los resultados en la primera aproximación muestran la capacidad de los modelos para describir la variabilidad presente en los regímenes de crecidas; asimismo, se observa la alta dependencia de los parámetros de las distribuciones paramétricas respecto del tiempo, lo cual sugiere la ausencia de estacionaridad en los regímenes de crecidas en las estaciones de aforo de estudio. En el segundo enfoque, en el cual los índices climáticos (Niño12, Niño3, Niño3.4, SOI y PDO) que describen el comportamiento de los patrones de variabilidad de baja frecuencia fueron incorporados como covariables explicativas en los modelos, permiten resaltar el importante papel de los fenómenos de macroescala que ocurren en el Pacífico, en la variabilidad interanual de los regímenes de las crecidas en la costa del Pacífico mexicano. Además, la comparación de los modelos en la inferencia de cuantiles entre los modelos no estacionarios respecto del clásico modelo estacionario muestra que las diferencias obtenidas asumiendo no estacionaridad y sus equivalentes estacionarios pueden ser importantes durante extensos periodos de tiempo

Empowerment evaluation: Key methodology aspects from participatory research and intervention with Roma girls

Empowerment evaluation (EE) is an especially useful tool that enables people to be involved in both individual and group transformation processes, in particular in contexts characterized by social inequality. By using a participatory approach, this methodological article analyses an Empowerment Evaluation experience within the European RoMoMatteR project. This project, which focuses on the notion of reproductive justice, has involved a group of Roma girls from Alicante (Spain), in a context characterized by discrimination based on ethnicity, gender and age, as well as by structural determinants such as social exclusion. The main research objective has been to analyse the relevance of the methodology designed to assess how project participants have developed a sense of autonomy and the acquisition of socio-cultural resources as assets for their future life choices. Therefore, the study design has followed the model proposed by Fetterman for Empowerment Evaluation: establishing a mission to be assessed, participatory diagnosis of the current status and finally planning for the future to start the desired change. Fetterman's model was adapted by designing and organizing participatory workshops with the girls involved in the project. The results confirm the relevance of the methodological proposal of the workshops to engage aspects of empowerment. The findings also allow to detect the empowerment of the Roma girls especially in two areas of the project: reaching the proposed objectives and the methodology used to register significant information. In the first case, the results show that Roma girls' establish a critical perspective on the idea of reproductive justice, and related to this, the activation of proactive behaviours linked to the acquisition of socio-cultural resources in the development of visions of their personal futures. In the second case, the Roma girls have also shown empowerment in decision-making on technical aspects, methodological design and taking action aimed at the collective construction of useful information in the project.This initiative is funded by the DG Justice of the European Commission in the Call for proposals for action grants under 2017 Rights Equality and Citizenship Work REC-AG #809813. Text editing work was supported by the Generalitat Valenciana Research and Development Programme (2022–2024) [ref. CIAICO/2021/019]