Janusz Niemczynowicz

Urban hydrology and water management – present and future challenges

Abstract Urban hydrology is an applied science that will have an increasing role to play in the sustainability of human societies. Facing present growth of urban population, it is increasingly difficult to find and utilize new sources of water necessary to satisfy growing water demand. For the poor, the residents of peri-urban and squatter areas, an ultimate poverty, the poverty of lacking clean water, is a result. To remove this kind of poverty should be a first priority target for all people and, especially, for people dealing with water management in urban areas. Growth of urban areas brings significant changes in physical properties of land surface increasing integrated vulnerability of inhabitants, agricultural land and rural ecological life supporting systems. Performance of technical solutions depends on climate as well as on social, economical and cultural conditions. Findings from urban hydrological studies based on collection of urban hydrological data, calculations and modeling constitute a necessary fundamental for meaningful water management not only in urban areas but also in entire river basins. Future challenges in urban water management include development of new technical solutions as well as logistic and organizational methods in order to turn present problems into future opportunities. The following current and emerging challenges are discussed in the paper: delivery of drinking water supply for growing cities, water for sanitation versus sanitation without water, recycling of wastewater nutrients, wastewater irrigation, urban agriculture, water to feed depleted aquifers, thoughts about possible future new system solutions, social equity and transfer of knowledge and new technology.

Fractal Analysis of High-Resolution Rainfall Time Series

Two-year series of 1-min rainfall intensities observed by rain gages at six different points are analyzed to obtain information about the fractal behavior of the rainfall distribution in time. First, the rainfall time series are investigated using a monodimensional fractal approach (simple scaling) by calculating the box and correlation dimensions, respectively. The results indicate scaling but with different dimensions for different time aggregation periods. The time periods where changes in dimension occur can be related to average rainfall event durations and average dry period lengths. Also, the dimension is shown to be a decreasing function of the rainfall intensity level. This suggests a multidimensional fractal behavior (multiscaling), and to test this hypothesis, the probability distribution/multiple scaling method was applied to the time series. The results confirm that the investigated rainfall time series display a multidimensional fractal behavior, at least within a significant part of the studied timescales, which indicates that the rainfall process can be described by a multiplicative cascade process.

Multifractal analysis of daily spatial rainfall distributions

The multifractal behavior of daily spatial rainfall distributions observed by a dense gage network in southern Sweden was analyzed by studying the variation of average statistical moments with scale. The data were analyzed both separated into groups depending on the rainfall generating mechanism (warm fronts, cold fronts, and convection, respectively) and pooled into one group representing the total rainfall process in the area. The results indicated that the daily spatial rainfall distributions were well characterized by a multifractal behavior both separated into mechanism groups and pooled into one group. The multifractal properties, however, displayed distinct differences which were related to physical differences of the rainfall generating mechanisms. The multifractal properties of the total rainfall process agreed well with the properties of the cold front group. Investigations of interpolated grids showed that these well preserve the multifractal behavior of the original data, but modify the multifractal properties.

Spatial and temporal scales in rainfall analysis — Some aspects and future perspectives

Abstract Aspects of spatial and temporal rainfall variability and rainfall analysis in relation to some water management problems are surveyed and discussed. It is concluded that relevant modelling of hydrological processes in which the rainfall is a driving force is vital with respect to possibilities of finding solutions to increasing environmental problems following urbanization and industrialization. However, modern computer methods and our knowledge of the spatial and dynamic properties of rainfall fields are seldom used in practical engineering applications. This causes errors and uncertainties in the calculated output. Bridging the gaps between researchers and engineers may overcome some of these problems. It is also argued that experimental studies in a variety of climates and physiographical conditions using an interdisciplinary approach are needed in order to further investigate the scale and dynamics of spatial rainfall variability.

An analysis of the rainfall time structure by box counting—some practical implications

The scale-invariant behavior of the rainfall time structure was investigated by applying the box counting method to rainfall time series. Two years of minute observations, 90 years of daily observations and 170 years of monthly observations were analyzed and the results were interpreted and related to physical properties of the rainfall process. This paper discusses the question of whether an hypothesis of temporal scale invariance is valid for rainfall and the possibilities of using it in practical hydrology.

Storm tracking using rain gauge data

Abstract The unknown spatial distribution and kinematics of short-term rainfall are recognised as the most important reasons for errors in runoff simulation on urban catchments. Since the storm movement influences the shape of the runoff hydrographs, the modern rainfall input should include patterns of this movement. In order to be able to take rainfall kinematics into account in runoff simulation, rain movement parameters must be extracted from the rainfall data itself or taken from other phenomena such as wind movement at high altitude. The paper presents the results of the application of three different storm tracking methods on a set of rainfall data from the 12-gauge network in Lund, Sweden. The main conclusion is that a really objective and reliable storm tracking method does not exist yet. When more than one rainfall cell is simultaneously present over the rain gauge network, all so-called objective methods fail or must lose their objectivity. On the other hand, when the rainfall data are good, the storm movement pattern can be easily, though subjectively, recognized. Then, simple methods based on triangulation work equally well as more sophisticated methods based on spatial correlation. The existence of a relation between rainfall and high-altitude wind movement parameters is now well documented. However, further studies subjected to derivation of storm movement parameters from gauge data are still important in order to quantify this relationship better and to explain eventual regional differences.

The rainfall movement — A valuable complement to short-term rainfall data

Abstract The lack of sufficiently good short-term rainfall data causes errors in runoff simulation in urban areas. The rainfall input traditionally used in urban rainfall-runoff simulation models does not take into account areal and kinematic properties of intensive rainstorms which are relevant in this context. Rainfall data used for runoff simulation may be complemented with rainfall movement parameters, which, in turn, can be calculated from high-altitude wind movement measured at most airports. On examination of ten rainfall events observed in Lund, it is shown that about equally good results in single-event runoff simulations may be obtained using rainfall data from twelve gauges on a 20 km 2 area as when the data from only three gauges complemented with rainfall movement parameters are used. This exemplifies benefits of using rainfall movement as additional information that may favorably complement inadequate rainfall data.

Spatial variability of rainfall in Kuala Lumpur, Malaysia: long and short term characteristics

Abstract Spatial variability of both long and short term rainfall in an urban environment in Malaysia was studied using historical monthly and yearly rainfall data and, unique for the humid tropics region, recently collected, short term rainfall data measured with very small time and space resolution. The results for the yearly data indicated some elongation of the spatial structures of rainfall in the area. The monthly rainfall data showed that the geographical orientation of these structures for the months of December to March was different from that during April to November. These differences were due to the effects caused by monsoon seasonality and by the influence of the sea. The spatial structure and depth-area relationship for short term thunderstorms have been derived. The basic statistics of point observations were also studied. The results showed that the spatial variability of short term rainfall was more significant for short term rainfall than for the long term behaviour. Thus, the spatial st...

Impact of the greenhouse effect on sewerage systems—Lund case study

Abstract The possible impacts of modifications in rainfall patterns due to the greenhouse effect on the function of a sewerage system are studied based on a case study of the city of Lund, Sweden. The Storm Water Management Model is used to simulate changes in the runoff pattern. The paper lists the possible effects of increases in rainfall intensity on the urban water cycle, quantifies changes in the runoff pattern, and discusses the significance of detected changes in terms of economic and environmental consequences and the possibilities to undertake preventative measures. For the purpose of the present study, 10%, 20% and 30% levels of rainfall increase were assumed. In spite of considerable uncertainty regarding the potential future rate of hydrological changes, the examples given of possible impacts of the greenhouse effect on the function of the sewerage system bear witness to the great vulnerability of sewerage systems to the results of climate changes.

Real‐time rainfall prediction at small space‐time scales using a two‐dimensional stochastic advection‐diffusion model

A model based on the two-dimensional stochastic advection-diffusion equation is developed to forecast properties of individual rain cells in urban areas such as speed and spatial rainfall intensity. Two different modeling approaches are employed, and examples of the results are given. The first approach involves a Gaussian distribution as an analytic solution to the advection-diffusion equation, whereas the second one entails a double Fourier series expansion of the rainfall intensity field. Both modeling approaches are used to predict the rainfall intensity field over a small 12-gage urban catchment in southern Sweden. The model parameters are continuously updated by extended Kalman filtering. The Fourier series approach is shown to be the most flexible for practical applications and to give the most accurate forecasts. This model approach gives acceptable forecasts for a lead time of 1-5 min. It gives consistently smaller prediction errors compared to both the Gaussian solution and simple extrapolation calculations. The effect of system noise level on the forecast accuracy and model performance is discussed. The model can be used not only to predict in real time the spatial rainfall, but also to parameterize the variability pattern of small-scale spatial rainfall into a set of physically based parameters, thus separating the effects of advective velocity, turbulent diffusion, and development/decay.