Rainfall runoff models are frequently used for design processes for urban infrastructure. The most sensitive input for these models is precipitation data. Therefore, it is crucial to account for temporal and spatial variability of rainfall events as accurately as possible to avoid misleading simulation results. This paper aims to show the significant errors that can occur by using rainfall measurement resolutions in urban environments that are too coarse. We analyzed the spatial variability of rainfall events from two years with the validated data of 22 rain gauges spread out over an urban catchment of 125 km2. By looking at the interstation correlation of the rain gauges for different classes of rainfall intensities, we found that rainfall events with low and intermediate intensities show a good interstation correlation. However, the correlation drops significantly for heavy rainfall events suggesting higher spatial variability for more intense rainstorms. Further, we analyzed the possible deviation from the spatial rainfall interpolation that uses all available rain gauges when reducing the number of rain gauges to interpolate the spatial rainfall for 24 chosen events. With these analyses we found that reducing the available information by half results in deviations of up to 25% for events with return periods shorter than one year and 45% for events with longer return periods. Assuming uniformly distributed rainfall over the entire catchment resulted in deviations of up to 75% and 125%, respectively. These findings are supported by the work of past research projects and underline the necessity of a high spatial measurement density in order to account for spatial variability of intense rainstorms.

Abstract. The importance of deep soil-regolith through flow in a small (3.4 km2) ephemeral catchment in the Adelaide Hills of South Australia was investigated by detailed hydrochemical analysis of soil water and stream flow during autumn and early winter rains. In this Mediterranean climate with strong summer moisture deficits, several significant rainfalls are required to generate soil through flow and stream flow [in ephemeral streams]. During autumn 2007, a large (127 mm) drought-breaking rain occurred in April followed by significant May rains; most of this April and May precipitation occurred prior to the initiation of stream flow in late May. These early events, especially the 127 mm April event, had low stable water isotope values compared with later rains during June and July and average winter precipitation. Thus, this large early autumn rain event with low isotopic values (δ18O, δD) provided an excellent natural tracer. During later June and July rainfall events, daily stream and soil water samples were collected and analysed. Results from major and trace elements, water isotopes (δ18O, δD), and dissolved organic carbon analysis clearly demonstrate that a large component of this early April and May rain was stored and later pushed out of deep soil and regolith zones. This pre-event water was identified in the stream as well as identified in deep soil horizons due to its different isotopic signature which contrasted sharply with the June–July event water. Based on this data, the soil-regolith hydrologic system for this catchment has been re-thought. The catchment area consists of about 60% sandy and 40% clayey soils. Regolith flow in the sandy soil system and not the clayey soil system is now thought to dominate the deep subsurface flow in this catchment. The clayey texture contrast soils had rapid response to rain events and saturation excess overland flow. The sandy soils had delayed soil through flow and infiltration excess overland flow. A pulse of macropore through flow was observed in the sandy soils three days after the rainfall event largely ended. The macropore water was a mixture of pre-event and event water, demonstrating the lag-time and mixing of the water masses in the sandy soil system. By contrast, the clayey soil horizons were not dominated by pre-event water, demonstrating the quicker response and shallow through flow of the clayey soil system. Thus, the sandy terrain has a greater vadose zone storage and greater lag time of through flow than the clayey terrain.

The influence of vegetation and soil texture on the concentration and character of dissolved organic matter (DOM) present in runoff from the surface and sub-surface of zero order catchments of the Myponga Reservoir-catchment (South Australia) was investigated to determine the impacts of catchment characteristics and land management practices on the quality of waters used for domestic supply. Catchments selected have distinct vegetative cover (grass, native vegetation or pine) and contrasting texture of the surface soil horizon (sand or clay loam/clay). Water samples were collected from three slope positions (upper, middle, and lower) at soil depths of ~30 cm and ~60 cm in addition to overland flows. Filtered (0.45 μm) water samples were analyzed for dissolved organic carbon (DOC) and UV-visible absorbance and by F-EEM and HPSEC with UV and fluorescence detection to characterize the DOM. Surface and sub-surface runoff from catchments with clay soils and native vegetation or grass had lower DOC concentrations and lower relative abundances of aromatic, humic-like and high molecular weight organics than runoff from sandy soils with these vegetative types. Sub-surface flows from two catchments with Pinus radiata had similar DOC concentrations and DOM character, regardless of marked variation in surface soil texture. Runoff from catchments under native vegetation and grass on clay soils resulted in lower DOC concentrations and hence would be expected to have lower coagulant demand in conventional treatment for potable water supply than runoff from corresponding sandy soil catchments. However, organics in runoff from clay catchments would be more difficult to remove by coagulation. Surface waters from the native vegetation and grass catchments were generally found to have higher relative abundance of organic compounds amenable to removal by coagulation compared with sub-surface waters. Biophysical and land management practices combine to have a marked influence on the quality of source water used for domestic supply.

Climate change, as well as increasing urbanization, lead to an increase in urban flooding events around the world. Accurate urban flood models are an established tool to predict flooding areas in urban as well as peri-urban catchments, to derive suitable measures to increase resilience against urban flooding. The high computational cost and complex processes of urban flooding with numerous subprocesses are the reason why many studies ignore the discussion of model uncertainties as well as model calibration and validation. In addition, the influence of steep surface (hillside) conditions on calibration parameters such as surface roughness are frequently left out of consideration. This study applies a variance-based approach to analyze the impact of three uncertainty sources on the two variables—flow and water depth—in a steep peri-urban catchment: (i) impact of DEM validation; (ii) calibration of the model parameter; (iii) differences between 1D/2D and 2D models. The results demonstrate the importance of optimizing sensitive model parameters, especially surface roughness, in steep catchments. Additional findings of this work indicate that the sewer system cannot be disregarded in the context of urban flood modeling. Further research with real heavy storm events is to be pursued to confirm the main results of this study.

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