[1] The Budyko curve is often used to estimate the actual evaporation as a function of the aridity index in a catchment. Different empirical equations exist to describe this relationship; however, these equations have very limited physical background. The model concept presented in this paper is physically based and uses only measurable parameters. It makes use of two types of evaporation: interception and transpiration. It assumes that interception can be modeled as a threshold process on a daily time scale. If multiplied with the rainfall distribution function, integrated, and multiplied with the expected number of rain days per month, the monthly interception is obtained. In a similar way, the monthly interception can be upscaled to annual interception. Analogous to the interception process, transpiration can be modeled as a threshold process at a monthly time scale and can be upscaled by integration and multiplication with the expected number of rain months. The expected rain days per month are modeled in two ways: as a fixed proportion of the monthly rainfall and as a power function based on Markov properties of rainfall. The latter is solved numerically. It appears that on an annual basis the analytical model does not differ much from the numerical solution. Hence, the analytical model is used and applied on 10 locations in different climates. This paper shows that the empirical Budyko curve can be constructed on the basis of measurable parameters representing evaporation threshold values and the expected number of rain days and rain months and, in addition, a monthly moisture carryover amount for semiarid zones.

Abstract:Depending on season, rainfall characteristics and tree species, interception amounts to 15-50% of total precipitation in a forest under temperate climates. Many studies have investigated the importance of interception of different tree species in all kinds of different climates. Often authors merely determine interception storage capacity of that specific species and the considered event, and only sometimes a distinction is made between foliated and non-foliated trees. However, interception is highly variable in time and space. First, since potential evaporation is higher in summer, but secondly because the storage capacity has a seasonal pattern. Besides weather characteristics, such as wind and rain intensity, snow causes large variations in the maximum storage capacity. In an experimental beech plot in Luxembourg, we found storage capacity of canopy interception to show a clear seasonal pattern varying from 0Ð1 mm in winter to 1Ð2 mm in summer. The capacity of the forest floor appears to be rather constant over time at 1Ð8 mm. Both have a standard deviation as high as š100%. However, the process is not sensitive to this variability resulting only in 11% variation of evaporation estimates. Hence, the number of raindays and the potential evaporation are stronger driving factors on interception. Furthermore, the spatial correlation of the throughfall and infiltration has been investigated with semi-variograms and time stability plots. Within 6-7 m distance, throughfall and infiltration are correlated and the general persistence is rather weak.

Abstract. In hydrological models, evaporation from interception is often disregarded, combined with transpiration, or taken as a fixed percentage of rainfall. In general interception is not considered to be a significant process in rainfallrunoff modelling. However, it appears that on average interception can amount to 20-50% of the precipitation. Therefore, knowledge about the process of interception is important. Traditional research on interception mainly focuses on canopy interception and almost completely denies forest floor interception, although this is an important mechanism that precedes infiltration or runoff. Forest floor interception consists partly of interception by dry soil, partly of interception by short vegetation (mosses, grasses and creeping vegetation) and partly of interception by litter. This research project concentrates on litter interception: to measure its quantities at point scale and subsequently to upscale it to that of a hydrotope. A special measuring device has been developed, which consists of a permeable upper basin filled with forest floor, and a watertight lower basin. Both are weighed continuously. The device has been tested in the Huewelerbach catchment (Luxembourg). The preliminary measuring results show that the device is working properly. For November 2004, evaporation from interception was calculated to be 14 mm of 42 mm throughfall (i.e., 34%).

Abstract.Variations of water stocks in the upper Zambezi river basin have been determined by 2 different hydrological modelling approaches. The purpose was to provide preliminary terrestrial storage estimates in the upper Zambezi, which will be compared with estimates derived from the Gravity Recovery And Climate Experiment (GRACE) in a future study. The first modelling approach is GIS-based, distributed and conceptual (STREAM). The second approach uses Lumped Elementary Watersheds identified and modelled conceptually (LEW). The STREAM model structure has been assessed using GLUE (Generalized Likelihood Uncertainty Estimation) a posteriori to determine parameter identifiability. The LEW approach could, in addition, be tested for model structure, because computational efforts of LEW are low.Both models are threshold models, where the non-linear behaviour of the Zambezi river basin is explained by a combination of thresholds and linear reservoirs.The models were forced by time series of gauged and interpolated rainfall. Where available, runoff station data was used to calibrate the models. Ungauged watersheds were generally given the same parameter sets as their neighbouring calibrated watersheds.It appeared that the LEW model structure could be improved by applying GLUE iteratively. Eventually, it led to better identifiability of parameters and consequently a better model structure than the STREAM model. Hence, the final model structure obtained better represents the true hydrology.After calibration, both models show a comparable efficiency in representing discharge. However the LEW model shows a far greater storage amplitude than the STREAM model. This emphasizes the storage uncertainty related to Correspondence to: H. C. Winsemius (h.c.winsemius@tudelft.nl) hydrological modelling in data-scarce environments such as the Zambezi river basin. It underlines the need and potential for independent observations of terrestrial storage to enhance our understanding and modelling capacity of the hydrological processes. GRACE could provide orthogonal information that can help to constrain and further enhance our models. In the near future, other remotely sensed data sources will be used to force modelling efforts of the Zambezi (e.g. satellite rainfall estimates) and to identify individual storage components in the GRACE observations (e.g. altimeter lake levels and microwave soil moisture). Ultimately, this will create possibilities for state updating of regional hydrological models using GRACE.