63 research outputs found

    Understanding hydrological processes with scarce data in a mountain environment

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    Performance of process-based hydrological models is usually assessed through comparison between simulated and measured streamflow. Although necessary, this analysis is not sufficient to estimate the quality and realism of the modelling since streamflow integrates all processes of the water cycle, including intermediate production or redistribution processes such as snowmelt or groundwater flow. Assessing the performance of hydrological models in simulating accurately intermediate processes is often difficult and requires heavy experimental investments. In this study, conceptual hydrological modelling (using SWAT) of a semi-arid mountainous watershed in the High Atlas in Morocco is attempted. Our objective is to analyse whether good intermediate processes simulation is reached when global-satisfying streamflow simulation is possible. First, parameters presenting intercorrelation issues are identified: from the soil, the groundwater and, to a lesser extent, from the snow. Second, methodologies are developed to retrieve information from accessible intermediate hydrological processes. A geochemical method is used to quantify the contribution of a superficial and a deep reservoir to streamflow. It is shown that, for this specific process, the model formalism is not adapted to our study area and thus leads to poor simulation results. A remote-sensing methodology is proposed to retrieve the snow surfaces. Comparison with the simulation shows that this process can be satisfyingly simulated by the model. The multidisciplinary approach adopted in this study, although supported by the hydrological community, is still uncommon

    Stomatal control of transpiration : examination of Monteith's formulation of canopy resistance

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    The stomatal response to air humidity has been recently reinterpreted in the sense that stomata seem to respond to the rate of transpiration rather to air humidity per se. Monteith suggested that the relation between canopy stomatal resistance r(s) and canopy transpiration E can be written as r(s)/r(sn) = 1/(1-E/E(x)), where r(sn) is a notional minimum canopy resistance, obtained by extrapolation to zero transpiration, and E(x) is a notional maximum transpiration rate, obtained by extrapolation to infinite resistance. The exact significance and possible values of these parameters have not been specified yet. In this study we show that this apparently new relation can be inferred from the common Jarvis-type models, in which canopy stomatal resistance is expressed in the form of a minimal resistance multiplied by a product of independent stress functions (each one representing the influence of one factor). This is made possible by replacing leaf water potential in the corresponding stress function by its dependence on transpiration and soil water potential. The matching of the two formulations (Monteith and Jarvis) allows one to express the two parameters r(sn) and E(x) in terms of the functions and parameters making up the Jarvis-type models ; r(sn) appears to depend upon solar radiation and soil water potential : it represents the canopy stomatal resistance when the leaf water potential is equal to the soil water potential, all other conditions being equal. E(x) depends upon soil water potential and represents the maximum flux of water which can be extracted from the soil by the canopy. (Résumé d'auteur

    Deriving catchment-scale water and energy balance parameters using data assimilation based on extended Kalman filtering

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    Important catchment-scale water and energy balance parameters are derived for a small catchment in southeastern Australia by assimilation in a catchment-scale soil-vegetation-atmosphere transfer (SVAT) model of subcatchment- scale soil water content observations and land surface temperature measurements. In order to incorporate the subcatchment-scale soil moisture variability and its time evolution in a data assimilation scheme, an extended Kalman filter (EK.F) method is used in combination with a cost function minimization approach to derive effective parameters for the catchment as a whole. These parameters are the minimum surface resistance to evaporation and the soil hydrodynamic parameters. This method provides a balanced assessment of all the uncertainties regarding the description of the catchment hydrological behaviour. Moreover, these uncertainties are propagated forward in time in a single framework, which combines soil moisture correction with effective parameter estimation. Two issues are addressed in this paper: (a) the applicability of the method for scaling purposes (effective parameterization) and (b) the relationship between effective parameters obtained by this method and parameters obtained by a classical minimization routine that ignores soil moisture correction and observation uncertainty. Effective parameters are found to be consistent with the available local parameter measurements. Derived parameter sets with and without EKF have been found to be very similar and this has been explained in a number of ways
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