Here it is a little of summary of Moussa talk.
- agricultural catchment derives from a deep intervention of the natural hydrography, and this obviously affects the hydrological response. In one of his paper he does some virtual experiments in which he compares the hydrologic response of the real catchment with the supposed natural one.
- the variation of hydraulic properties of soil after tillage, and in general, after the agricultural practice. - the role of vegetation, epitomized by a banano cultivation, in preferential collecting the rainfall.
Here it is the abstract of Roger's seminar: Model calibration and analysis of model performance :Case of distributed hydrological modelling of flood events from the plot to the catchment scale.
"During the last decades, flood events which occurred in the Mediterranean zone are a major threat to human life and infrastructures. This situation handicaps development, necessitating the use of modeling approaches for prediction of sites prone to flooding, planning of damage minimization activities, and for environmental prediction of the impact on runoff, erosion and pollutant transport. Moreover, hydrological processes are largely variable in space due to human impact in agricultural and urban zones, causing hydrological discontinuities such as channels, field limits, drains, and tillage practices. MHYDAS (Modélisation HYdrologique Distribuée des AgroSystèmes / Distributed Hydrological Modelling of AgroSystems), a physically based distributed hydrological model, was especially developed to model flood events taking into account hydrological discontinuities. Application cases are shown on catchments from the plot scale (1000 m²) to large scales (2000 km²) in various agro-hydro-climatic conditions : i) to assess the optimal subdivision into sub-catchments for distributed hydrological modeling applications; ii) to study the spatio-temporal distribution of rainfall and the soil hydrodynamic properties; iii) to define a parameterisation strategy, and to compare various multi-objective functions and analyze the significance of well-known criteria functions."
With Roger we actually discussed a little more about other issues regarding the topic of comparing data and simulations. Some considerations derived:
- Discharge data ata should always be checked independently from the outcomes of the model. To verify their correlation structure, and their statistics, i.e. lag times (discharges from rainfall), centroids, time to peak, volumes, runoff coefficients, etc.
- Be conscious of which data you really use, and distinguish model also for their use of data: do they use vegetation information ? Soil information ? What is really distributed in your catchment data set ?
- Do not use excess of distributed information that you cannot justify.
- Keep in mind which are the objective of your modeling. Improving discharge prediction ? Improving calibration methods ? What else ?
- Do not give for granted that the first period in a data set is the calibration one. Sometimes invert calibration and validation !!!
- Always use objective indicator of godness of fit (GOF): but be aware that they can hide some important features, and the best GOFs performances not always means a bette prediction (Roger has a paper on it).
Finally he also, as well as me, felt the need for an infrastructure to support modeling. His institution promote Openfluid, a C++ framework.
Chahinian N, Moussa R, Andrieux P, Voltz M. 2005. Comparison of infiltration models to simulate flood events at the field scale. Journal of Hydrology, 306: 191-214.
Chahinian N, Voltz M, Moussa R, Trotoux G. 2006. Assessing the impact of hydraulic properties of a crusted soil on overland flow modelling at the field scale. Hydrological Processes, 20 : 1701-1722.
Charlier JB, Cattan P, Moussa R, Voltz M. 2008. Hydrologic behaviour and modelling of a volcanic tropical cultivated catchment. Hydrological Processes, 22 : 4355-4370.
Charlier JB, Moussa R, Cattan P, Cabidoche YM, Voltz M. 2009. Modelling runoff at the plot scale taking into account rainfall partitioning by vegetation: application to stemflow of banana (Musa spp.) plant. Hydrology and Earth System Sciences, 13, 2151-2168.
Cheviron B, Gumiere SJ, Le Bissonnais Y, Moussa R, Raclot D, 2010. Sensitivity analysis of distributed erosion models: Framework. Water Resources Research, vol. 46, W08508, 13 p.
Gomez-Delgado F, Roupsard O, Le Maire G, Taugourdeau S, Bonnefond JM, Perez A, van Oijen M, Vaast P, Rapidel B, Voltz M, Imbach P, Harmand JM, Moussa R. 2011. Modelling the hydrological behaviour of a coffee agroforestry basin in Costa Rica. Hydrology and Earth System Sciences, 15, 369–392.
Gumiere S, Raclot D, Cheviron B, Davy G, Louchart X, Fabre JC, Moussa R, Le Bissonnais Y, 2011. MHYDAS-Erosion a distributed single-storm water erosion model for agricultural catchment. Hydrological Processes, in Press .
Lagacherie P, Rabotin M, Colin F, Moussa R, Voltz M, 2010. Geo-MHYDAS: A discretization procedure of Cultivated Landscapes for distributed hydrological modelling. Computers & Geosciences, 36 (2010) 1021–1032.
Moussa R. 2008a. Effect of channel network topology, basin segmentation and rainfall spatial distribution on the GIUH transfer function. Hydrological Processes, 22 : 395-419
Moussa R. 2008b. What controls the width function shape, and can it be used for channel network comparison and regionalization?. Water Resources Research, 44, 20 p., W08456.
Moussa R. 2010. When monstrosity can be beautiful while normality can be ugly: assessing the performance of event-based flood models. Hydrological Sciences Journal, 55(6), 1074 – 1084.
Moussa R, Chahinian N. 2009. Comparison of different multi-objective calibration criteria using a conceptual rainfall-runoff model of flood events. Hydrology and Earth System Sciences, 13, 519-535.
Moussa R, Voltz M, Andrieux P. 2002. Effects of the spatial organization of agricultural management on the hydrological behaviour of a farmed catchment during flood events. Hydrological Processes 16 : 393-412 (DOI: 10.1002/hyp.333).
Moussa R, Chahinian N, Bocquillon, C. 2007. Distributed hydrological modelling of a Mediterranean mountainous catchment - model construction and multi-site validation. Journal of Hydrology 337: 35-51.
Moussa R, Colin F, Rabotin M. 2011. Invariant morphometric properties of headwater subcatchments. Water Resources Research, in Press.
Bibliography of others will follow. Anyone of them is a champion in publishing. So there is lot to read.