ALBERT

Description: A data-driven method for extracting temporally persistent information, at different spatial scales, from rainfall data (as measured by radar/satellite) is described, which extends the Empirical Mode Decomposition (EMD) algorithm into two dimensions. The EMD technique is used here to decompose spatial rainfall data into a sequence of high through to low frequency components. This process is equivalent to the application of successive low-pass spatial filters, but based on the observed properties of the data rather than the predetermined basis functions used in traditional Fourier or Wavelet decompositions. It has been suggested in the literature that the lower frequency components (those with large spatial extent) of spatial rainfall data exhibit greater temporal persistence than the higher frequency ones. This idea is explored here in the context of Empirical Mode Decomposition. The paper focuses on the implementation and development of the two-dimensional extension to the EMD algorithm and it's application to radar rainfall data, as well as examining temporal persistence in the data at different spatial scales.

Description: In high mountainous catchments, the spatial precipitation and therefore the overall water balance is generally difficult to estimate. The present paper describes the structure and calibration of a semi-lumped conceptual glacio-hydrological model for the joint simulation of daily discharge and annual glacier mass balance that represents a better integrator of the water balance. The model has been developed for climate change impact studies and has therefore a parsimonious structure; it requires three input times series - precipitation, temperature and potential evapotranspiration - and has 7 parameters to calibrate. A multi-signal approach considering daily discharge and - if available - annual glacier mass balance has been developed for the calibration of these parameters. The model has been calibrated for three different catchments in the Swiss Alps having glaciation rates between 37% and 52%. It simulates well the observed daily discharge, the hydrological regime and some basic glaciological features, such as the annual mass balance.

Description: The application of Artificial Neural Networks (ANNs) in rainfall-runoff modelling needs to be researched more extensively in order to appreciate and fulfil the potential of this modelling approach. This paper reports on the application of multi-layer feedforward ANNs for rainfall-runoff modelling of the Geer catchment (Belgium) using both daily and hourly data. The daily forecast results indicate that ANNs can be considered good alternatives for traditional rainfall-runoff modelling approaches, but the simulations based on hourly data reveal timing errors as a result of a dominating autoregressive component. This component is introduced in model simulations by using previously observed runoff values as ANN model input, which is a popular method for indirectly representing the hydrological state of a catchment. Two possible solutions to this problem of lagged predictions are presented. Firstly, several alternatives for representation of the hydrological state are tested as ANN inputs: moving averages over time of observed discharges and rainfall, and the output of the simple GR4J model component for soil moisture. A combination of these hydrological state representers produces good results in terms of timing, but the overall goodness of fit is not as good as the simulations with previous runoff data. Secondly, the possibility of using multiple measures of model performance during ANN training is mentioned.

Description: The biogeochemistry of the river-sea interface was studied in the Kem' River (the largest river flowing to the White Sea from Karelian coast) estuary and adjacent area of the White Sea onboard the RV "Ekolog" in summer 2001, 2002 and 2003. The study area can be divided into 3 zones: I - the estuary itself, with water depth from 1 to 5m and low salinity in the surface layer (salinity is lower than 0.2psu in the Kem' River and varies from 15 to 20psu in outer part of this zone); II - the intermediate zone with depths from 5 to 10m and salinity at the surface from 16 to 22psu; III - the marine zone with depths from 10 to 29 m and salinity 21-24.5psu. Highest concentrations of the suspended particulate matter (SPM) were registered in the Kem' mouth (5-7mg/l). They sharply decreased to values

Description: The various elements of the hydrological cycle are discussed in outline from the point of view of making progress in analysis through appropriate simplification of these complex processes. Parallels between stochastic and deterministic analysis and between linear and non-linear conceptual models are referred to. The emphasis is on similarities and contrasts between the analysis of hydrologic processes over the range of scales from the water molecule to the global water balance.

Description: For hydrological modelling studies at the river basin scale, decision makers need guidance in assessing the implications of uncertain data used by modellers as an input to modelling tools. Simulated solute transport through the unsaturated zone is associated with uncertainty due to spatial variability of soil hydraulic properties and derived hydraulic model parameters. In general for modelling studies at the river basin scale spatially available data at various scales must be aggregated to an appropriate scale. Estimating soil properties at unsampled points by means of geostatistical techniques require reliable information on the spatial structure of soil data. In this paper this information is assessed by reviewing current developments in the field of soil physical data uncertainty and adopting a classification system. Then spatial variability and structure is inspected by reviewing experimental work on determining spatial length scales for soil physical (and soil chemical) data. Available literature on spatial length scales for soil physical- and chemical properties is reviewed and their use in facilitating change of spatial support discussed. Uncertainty associated to the derivation of hydraulic properties from soil physical properties in this context is also discussed.

Description: In this study we propose an uspcaling approach to derive time series of (a) REW scale state variables, and (b) effective REW scale soil hydraulic functions to test and parameterise models based on the REW approach. To this end we employed a physically based hydrological model, that represents the typical patterns and structures in the study catchment, and has previously been shown to reproduce observed runoff response and state dynamics well. This landscape- and process-compatible model is used to simulate numerical drainage and wetting experiments. The effective soil water retention curve and soil hydraulic conductivity curve are derived using the spatially averaged saturation and capillary pressure as well as averaged fluxes. When driven with observed boundary conditions during a one year simulation the model is used to estimate how the spatial pattern of soil moisture evolved during this period in the catchment. The time series of the volume integrated soil moisture is deemed as best estimate for the average catchment scale soil moisture. The approach is applied to the extensively monitored Weiherbach catchment in Germany. A sensitivity analysis showed that catchment scale model structures different from the landscape- and process compatible one yielded different times series of average catchment scale soil moisture and where not able to reproduce the observed rainfall runoff response. Hence, subscale typical heterogeneity leaves a clear fingerprint in the time series of average catchment scale saturation. In case of the Weiherbach catchment local scale heterogeneity of ks could be neglected and a simple representation of the typical hillslope scale patterns of soil types and macroporosity was sufficient for obtaining effective REW scale soil hydraulic functions. Both the effective soil hydraulic functions and time series of catchment scale saturation turned out to be useful to parameterise and test the CREW model, which is based on the REW approach and was applied to the Weiherbach catchment in a companion study Lee et al. (2006, this issue).

Description: Interactions between groundwater and surface water play a fundamental role in the functioning of riparian ecosystems. In the context of sustainable river basin management it is crucial to understand and quantify exchange processes between groundwater and surface water. Numerous well-known methods exist for parameter estimation and process identification in aquifers and surface waters. Only in recent years has the transition zone become a subject of major research interest; thus, the need has evolved for appropriate methods applicable in this zone. This article provides an overview of the methods that are currently applied and described in the literature for estimating fluxes at the groundwater – surface water interface. Considerations for choosing appropriate methods are given including spatial and temporal scales, uncertainties, and limitations in application. It is concluded that a multi-scale approach combining multiple measuring methods may considerably constrain estimates of fluxes between groundwater and surface water.

Description: The aim of the study was to test the applicability of a physically-based model to simulate the hydrological processes in a headwater catchment in Benin. Field investigations in the catchment have shown that lateral processes such as surface runoff and interflow are most important. Therefore, the 1-D SVAT-model SIMULAT was modified to a semi-distributed hillslope version (SIMULAT-H). Based on a good database, the model was evaluated in a multi-criteria validation using discharge, discharge components and soil moisture data. For the validation of discharge, good results were achieved for dry and wet years. The main differences were observable in the beginning of the rainy season. A comparison of the discharge components determined by hydro-chemical measurements with the simulation revealed that the model simulated the ratio of groundwater fluxes and fast runoff components correctly. For the validation of the discharge components of single events, larger differences were observable, which was partly caused by uncertainties in the precipitation data. The representation of the soil moisture dynamics by the model was good for the top soil layer. For deeper soil horizons, which are characterized by higher gravel content, the differences between simulated and measured soil moisture were larger. A good agreement of simulation results and field investigations was achieved for the runoff generation processes. Interflow is the predominant process on the upper and the middle slopes, while at the bottom of the hillslope groundwater recharge and – during the rainy season – saturated overland flow are important processes.