ALBERT

Description: Due to the combined effect of wind and rain, the importance of storm movement to surface flow has long been recognized, at scales ranging from headwater scales to large basins. This study presents the results of laboratory experiments designed to investigate the influence of moving rainfall storms on the dynamics of sediment transport by surface runoff. Experiments were carried out, using a rain simulator and a soil flume. The movement of rainfall was generated by moving the rain simulator at a constant speed in the upstream and downstream directions along the flume. The main objective of the study was to characterize, in laboratory conditions, the distribution of sediment grain-size transported by rainfall-induced overland flow and its temporal evolution. Grain-size distribution of the eroded material is governed by the capacity of flow that transports sediments. Granulometric curves were constructed using conventional hand sieving and a laser diffraction particle size analyser (material below 0.250 mm) for overland flow and sediment deliveries collected at the flume outlet. Surface slope was set at 2%, 7% and 14%. Rainstorms were moved with a constant speed, upslope and downslope, along the flume or were kept static. The results of laboratory experiments show that storm movement, affecting the spatial and temporal distribution of rainfall, has a marked influence on the grain-size characteristics of sediments transported by overland flow. The downstream-moving rainfall storms have higher stream power than do other storm types.

Description: When debris flow discharges into the main river, the deposition of debris raises the river bed, occupies the path of water conveyance and damages or even destroys buildings, resulting in considerable economic loss and possibly fatalities. Mathematical models are normally employed to compute debris flow. However, most of these models employ empirical formulae and coefficients and their results are seldom reliable. On the other hand, scale model tests associated with debris flow have seldom been conducted due to the lack of corresponding similarity laws and the difficulty of achieving the grain diameter scale. Focusing on pseudo-one-phase flow, this paper discusses the laws of similarity for the confluence of debris flow and main river and conducts a case study of the debris flow that occurred on 13 August 2010, in the Wenjia Gully, China. After satisfying the roughness scale, the kinematic viscosity coefficient scale, and the momentum ratio scale, it was found that the deposition terrain in the model test is consistent with the one in the prototype.

Description: This study describes and interprets the evolution of grain-size distribution of sediment yields generated in an experimental soil flume subjected to downstream and upstream moving rain storms. Results of laboratory experiments show that downstream moving storms cause more soil loss than do upstream moving storms. The pattern of sediment grain-size evolution in time during a runoff event exhibits a clear dependence on the direction of storm movement. A strong relationship between overland flow discharge and mean sediment size is found. Nevertheless, the mean grain-size of sediments transported during the rising limb of the hydrograph is coarser than during the recession limb of the hydrograph. This is more marked for downstream moving storms.

Description: Fundamental to the spatial sampling design of a groundwater quality monitoring network is the spatial structure of groundwater quality variables. The entropy theory presents an alternative approach to describe this variability. A case study is presented which used groundwater quality observations (13 years; 1987-2000) from groundwater domestic wells in the Gaza Strip, Palestine. The analyses of the spatial structure used the following variables: Electrical Conductivity (EC), Total Dissolved Solids (TDS), Calcium (Ca), Magnesium (Mg), Sodium (Na), Potassium (K), Chloride (Cl), Nitrate (NO3), Sulphate (SO4), alkalinity and hardness. For all these variables the spatial structure is described by means of Transinformation as a function of distance between wells (Transinformation Model) and correlation also as a function of distance (Correlation Model). The parameters of the Transinformation Model analysed were: (1) the initial value of the Transinformation; (2) the rate of information decay; (3) the minimum constant value; and (4) the distance at which the Transinformation Model reaches its minimum value. Exponential decay curves were fitted to both models. The Transinformation Model was found to be superior to the Correlation Model in representing the spatial variability (structure). The parameters of the Transinformation Model were different for some variables and similar for others. That leads to a reduction of the variables to be monitored and consequently reduces the cost of monitoring. Keywords: transinformation, correlation, spatial structure, municipal wells, groundwater monitoring, entropy

Description: Changes in land use and land cover (LULC) have been occurring at an accelerated pace in northern parts of China. These changes are significantly impacting the hydrology of these parts, such as Laohahe Catchment. The hydrological effects of these changes occurring in this catchment were investigated using a semi-distributed hydrological model. The semi-distributed hydrological model was coupled with a two-source potential evaportranspiration (PET) model for simulating daily runoff. Model parameters were calibrated using hydrometeorological and LULC data for the same period. The LULC data were available for 1980, 1989, 1996 and 1999. Daily streamflow measurements were available from 1964 to 2005 and were divided into 4 periods: 1964–1979, 1980–1989, 1990–1999 and 2000–2005. These periods represented four different LULC scenarios. Streamflow simulation was conducted for each period under these four LULC scenarios. The results showed that the change in LULC influenced evapotranspiration (ET) and runoff. The LULC data showed that from 1980 to 1996 grass land and water body had decreased and forest land and crop land had increased. This change caused the evaporation from vegetation interception and vegetation transpiration to increase, whereas the soil evaporation tended to decrease. Thus during the period of 1964–1979 the green water or ET increased by 0.95%, but the blue water or runoff decreased by 8.71% in the Laohahe Catchment.

Description: The absence of a generic modeling framework in hydrology has long been recognized. With our current practice of developing more and more complex models for specific individual situations, there is an increasing emphasis and urgency on this issue. There have been some attempts to provide guidelines for a catchment classification framework, but research in this area is still in a state of infancy. To move forward on this classification framework, identification of an appropriate basis and development of a suitable methodology for its representation are vital. The present study argues that hydrologic system complexity is an appropriate basis for this classification framework and nonlinear dynamic concepts constitute a suitable methodology. The study employs a popular nonlinear dynamic method for identification of the level of complexity of streamflow and for its classification. The correlation dimension method, which has its base on data reconstruction and nearest neighbor concepts, is applied to monthly streamflow time series from a large network of 117 gaging stations across 11 states in the western United States (US). The dimensionality of the time series forms the basis for identification of system complexity and, accordingly, streamflows are classified into four major categories: low-dimensional, medium-dimensional, high-dimensional, and unidentifiable. The dimension estimates show some "homogeneity" in flow complexity within certain regions of the western US, but there are also strong exceptions.

Description: In order to investigate the effect of land use and land cover changes on hydrological process in northern parts of China, a distributed hydrological model was developed and applied in the Laohahe catchment. The direct evaporation from the intercepted water, potential canopy transpiration and potential soil evaporation were computed using a physically-based two-source potential evapotranspiration model, which would be regarded as input to the distributed hydrological model for the computation of actual evaportranspiration. Runoff generation was based on mixed runoff mechanisms of infiltration excess runoff and saturation excess runoff and the Muskingum-Cunge method was adopted for flow routing. The land cover data were available for 1980, 1989, 1996 and 1999. Daily streamflow measurements were available from 1964 to 2005 and were divided into 4 periods: 1964–1979, 1980–1989, 1990–1999 and 2000–2005, based on the land cover scenarios. The distributed hydrological model was coupled with a two-source potential evaportranspiration model for simulating daily runoff. The result of runoff simulation showed that the saturation excess runoff generation was dominant in the catchment. Model parameters were calibrated using hydrometeorological and land cover data corresponding to the same period. Streamflow simulation was conducted for each period under these four land cover scenarios. The results showed that the change of land use and land cover had a significant influence on evapotranspiration and runoff. The land cover data showed that forest land and water body had decreased from 1980 through 1999 and farm land and grass land had increased. This change caused the vegetation interception evaporation and vegetation transpiration to decrease, whereas the soil evaporation tended to increase. Thus the green water decreased but the blue water increased over the Laohahe catchment. This result was inconsistent with the fact that runoff ratio had a tendency of decrease in the catchment in 2000. It is this reason that water use out of stream channel has been increasing in recent years.

Description: The absence of a generic modeling framework in hydrology has long been recognized. With our current practice of developing more and more complex models for specific individual situations, there is an increasing emphasis and urgency on this issue. There have been some attempts to provide guidelines for a catchment classification framework, but research in this area is still in a state of infancy. To move forward on this classification framework, identification of an appropriate basis and development of a suitable methodology for its representation are vital. The present study argues that hydrologic system complexity is an appropriate basis for this classification framework and nonlinear dynamic concepts constitute a suitable methodology. Discussing the utility of hydrologic data in describing the complexity of the underlying system, the study also offers a three-step procedure for a classification framework: (1) detection of possible patterns and determination of complexity levels of hydrologic systems; (2) classification of hydrologic systems into groups and sub-groups based on patterns and complexity; and (3) verification of the classification framework through establishing relationships between the data patterns/complexity and the catchment/process properties. The framework is expected to lead to a much more effective and efficient procedure for identifying the appropriate structure and complexity of models for hydrologic systems and, thus, save significant time, data collection, and computational requirements.

Description: We present an overview of the modelling of particle number concentrations (PNC's) in five major European cities, namely Helsinki, Oslo, London, Rotterdam and Athens, in 2008. Novel emission inventories of particle numbers have been compiled both on urban and European scales. We use atmospheric dispersion modelling for PNC's in the five target cities and on a European scale, and evaluate the predicted results against available measured concentrations. The concentrations of PN in the selected cities were mostly influenced by the emissions originated from local vehicular traffic; however, in some of the cities, also harbour and airport activities were significant. The highest values of the predicted PNC's were higher in the megacities, London and Athens, and also in Rotterdam, whereas these were lower in Helsinki and Oslo. It was numerically evaluated that the influence of coagulation and dry deposition on the predicted PNC's was substantial for urban background in Oslo. The predicted and measured annual average PNC's in four cities agreed within approximately ≤ 36 % (measured as fractional biases), except for one traffic station in London. The indexes of agreement (IA) for the comparisons of hourly measured and predicted time-series in Oslo and Helsinki ranged from 0.75 to 0.79.

Description: We present an overview of the modelling of particle number concentrations (PNCs) in five major European cities, namely Helsinki, Oslo, London, Rotterdam, and Athens, in 2008. Novel emission inventories of particle numbers have been compiled both on urban and European scales. We used atmospheric dispersion modelling for PNCs in the five target cities and on a European scale, and evaluated the predicted results against available measured concentrations. In all the target cities, the concentrations of particle numbers (PNs) were mostly influenced by the emissions originating from local vehicular traffic. The influence of shipping and harbours was also significant for Helsinki, Oslo, Rotterdam, and Athens, but not for London. The influence of the aviation emissions in Athens was also notable. The regional background concentrations were clearly lower than the contributions originating from urban sources in Helsinki, Oslo, and Athens. The regional background was also lower than urban contributions in traffic environments in London, but higher or approximately equal to urban contributions in Rotterdam. It was numerically evaluated that the influence of coagulation and dry deposition on the predicted PNCs was substantial for the urban background in Oslo. The predicted and measured annual average PNCs in four cities agreed within approximately  ≤  26 % (measured as fractional biases), except for one traffic station in London. This study indicates that it is feasible to model PNCs in major cities within a reasonable accuracy, although major challenges remain in the evaluation of both the emissions and atmospheric transformation of PNCs.