scholarly journals The role of storm dynamics and scale in controlling urban flood response

2017 ◽  
Author(s):  
Marie-Claire ten Veldhuis ◽  
Zhengzheng Zhou ◽  
Long Yang ◽  
Shuguang Liu ◽  
James Smith
Keyword(s):  
Spatial Distribution ◽  
Spatial Scales ◽  
Rainfall Variability ◽  
Spatial And Temporal Variability ◽  
Hydrological Response ◽  
Radar Rainfall ◽  
Peak Flows ◽  
Basin Scale ◽  
Urban Catchments ◽  
The Impact

Abstract. The impact of spatial and temporal variability of rainfall on hydrological response remains poorly understood, in particular in urban catchments due to their high variability in land-use, high degree of imperviousness and the presence of stormwater infrastructure. In this study, we analyse the effect of rainfall spatial distribution with respect to basin scale and flowpath network structure on urban hydrological response based on a large, high quality observational dataset. A catalog of 279 peak events was extracted from 15 years of high resolution flow observations and radar rainfall data for five (semi)urbanised basins ranging from 7.0 to 111.1 km2 in size. Results showed that largest peak flows in the event catalog were associated with storm core scales exceeding basin scale, for all except the largest basin. Spatial scale of flood-producing storm events in the smaller basins fell into two groups: storms of large spatial scales exceeding basin size or small, concentrated events, with storm core much smaller than basin size. For the majority of events, spatial rainfall variability was strongly smoothed by the flowpath network, increasingly so for larger basin size. Correlation analysis showed that position of the storm in relation to the flowpath network was significantly correlated with peak flow in the smallest and in the two more urbanised basins. Analysis of storm movement relative to the flow path network showed that direction of storm movement, upstream or downstream relative to the flowpath network, had little influence on hydrological response variability. Slow-moving storms tend to be associated with higher peak flows and longer lag times. Unexpectedly, spatial distribution of imperviousness along the flowpath network did not significantly alter hydrological response in relation to spatial storm characteristics. These findings show the importance of observation-based analysis in validating and improving our understanding of interactions between rainfall and catchment variability.

scholarly journals The role of storm scale, position and movement in controlling urban flood response

2018 ◽  
Vol 22 (1) ◽  
pp. 417-436 ◽  
Author(s):  
Marie-Claire ten Veldhuis ◽  
Zhengzheng Zhou ◽  
Long Yang ◽  
Shuguang Liu ◽  
James Smith
Keyword(s):  
Spatial Scales ◽  
Rainfall Variability ◽  
Flow Path ◽  
Spatial And Temporal Variability ◽  
Hydrological Response ◽  
Radar Rainfall ◽  
Peak Flows ◽  
Basin Scale ◽  
Urban Catchments ◽  
The Impact

Abstract. The impact of spatial and temporal variability of rainfall on hydrological response remains poorly understood, in particular in urban catchments due to their strong variability in land use, a high degree of imperviousness and the presence of stormwater infrastructure. In this study, we analyze the effect of storm scale, position and movement in relation to basin scale and flow-path network structure on urban hydrological response. A catalog of 279 peak events was extracted from a high-quality observational dataset covering 15 years of flow observations and radar rainfall data for five (semi)urbanized basins ranging from 7.0 to 111.1 km2 in size. Results showed that the largest peak flows in the event catalog were associated with storm core scales exceeding basin scale, for all except the largest basin. Spatial scale of flood-producing storm events in the smaller basins fell into two groups: storms of large spatial scales exceeding basin size or small, concentrated events, with storm core much smaller than basin size. For the majority of events, spatial rainfall variability was strongly smoothed by the flow-path network, increasingly so for larger basin size. Correlation analysis showed that position of the storm in relation to the flow-path network was significantly correlated with peak flow in the smallest and in the two more urbanized basins. Analysis of storm movement relative to the flow-path network showed that direction of storm movement, upstream or downstream relative to the flow-path network, had little influence on hydrological response. Slow-moving storms tend to be associated with higher peak flows and longer lag times. Unexpectedly, position of the storm relative to impervious cover within the basins had little effect on flow peaks. These findings show the importance of observation-based analysis in validating and improving our understanding of interactions between the spatial distribution of rainfall and catchment variability.

scholarly journals On the sensitivity of urban hydrodynamic modelling to rainfall spatial and temporal resolution

2014 ◽  
Vol 11 (6) ◽  
pp. 5991-6033 ◽  
Author(s):  
G. Bruni ◽  
R. Reinoso ◽  
N. C. van de Giesen ◽  
F. H. L. R. Clemens ◽  
J. A. E. ten Veldhuis
Keyword(s):  
Spatial Resolution ◽  
Temporal Resolution ◽  
Rainfall Variability ◽  
Accurate Information ◽  
Hydrological Response ◽  
Radar Rainfall ◽  
Catchment Size ◽  
Maximum Water ◽  
Urban Catchments ◽  
Water Depths

Abstract. Cities are increasingly vulnerable to floods generated by intense rainfall, because of their high degree of imperviousness, implementation of infrastructures, and changes in precipitation patterns due to climate change. Accurate information of convective storm characteristics at high spatial and temporal resolution is a crucial input for urban hydrological models to be able to simulate fast runoff processes and enhance flood prediction. In this paper, a detailed study of the sensitivity of urban hydrological response to high resolution radar rainfall was conducted. Rainfall rates derived from X-band dual polarimetric weather radar for four rainstorms were used as input into a detailed hydrodynamic sewer model for an urban catchment in Rotterdam, the Netherlands. Dimensionless parameters were derived to compare results between different storm conditions and to describe the effect of rainfall spatial resolution in relation to storm and hydrodynamic model properties: rainfall sampling number (rainfall resolution vs. storm size), catchment sampling number (rainfall resolution vs. catchment size), runoff and sewer sampling number (rainfall resolution vs. runoff and sewer model resolution respectively). Results show catchment smearing effect for rainfall resolution approaching half the catchment size, i.e. for catchments sampling numbers greater than 0.5 averaged rainfall volumes decrease about 20%. Moreover, deviations in maximum water depths, form 10 to 30% depending on the storm, occur for rainfall resolution close to storm size, describing storm smearing effect due to rainfall coarsening. Model results also show the sensitivity of modelled runoff peaks and maximum water depths to the resolution of the runoff areas and sewer density respectively. Sensitivity to temporal resolution of rainfall input seems low compared to spatial resolution, for the storms analysed in this study. Findings are in agreement with previous studies on natural catchments, thus the sampling numbers seem to be promising as an approach to describe sensitivity of hydrological response to rainfall variability for intra-urban catchments and local convective storms. More storms and different urban catchments of varying characteristics need to be analysed in order to validate these findings.

scholarly journals Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas – a review

2017 ◽  
Vol 21 (7) ◽  
pp. 3859-3878 ◽  
Author(s):  
Elena Cristiano ◽  
Marie-Claire ten Veldhuis ◽  
Nick van de Giesen
Keyword(s):  
Temporal Variability ◽  
Urban Areas ◽  
Rainfall Variability ◽  
Urban Environments ◽  
Hydrological Processes ◽  
Small Scale ◽  
Spatial And Temporal Variability ◽  
Hydrological Response ◽  
Weather Radars ◽  
New Instruments

Abstract. In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal rainfall variability. At the same time, new models have been proposed to reproduce hydrological response, based on small-scale representation of urban catchment spatial variability. Despite these efforts, interactions between rainfall variability, catchment heterogeneity, and hydrological response remain poorly understood. This paper presents a review of our current understanding of hydrological processes in urban environments as reported in the literature, focusing on their spatial and temporal variability aspects. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge needs to be further developed to improve our understanding of and capability to predict urban hydrological response.

The Water Gap Risk Index – a novel approach for spatially distributed and sector-specific water scarcity risk calculations in urbanized catchments

2021 ◽  
Author(s):  
Mehmet Umit Taner ◽  
Dimmie Hendiriks ◽  
Lieke Huesken ◽  
Niels Mulder ◽  
Diana Morales Irato ◽  
...  
Keyword(s):  
Water Scarcity ◽  
Water Demand ◽  
Risk Index ◽  
Spatial And Temporal Variability ◽  
The Novel ◽  
User Group ◽  
User Groups ◽  
Urban Catchments ◽  
Gap Risk ◽  
The Impact

<p>An increasing number of mega-cities, such as Cape Town, Lima, and São Paulo, are confronted with increasing droughts as well as an increase in water demand. Inevitably, this leads to increasing pressure on the available water resources and associated risks and economic impact for the water-dependent sectors (eg. drinking water supply, industry, energy production, agriculture, nature) and different user groups within the sectors (eg. low, middle- and high-income households, self-subsistence farmers, large farms). To address these problems and to develop targeted mitigation strategies, risk analyses are required that quantify the impact of water scarcity on the various sectors and users-groups in different parts of the catchment.</p><p>Here, we present the Water Gap Risk Index (WGRI) that quantifies water scarcity and its impacts on a variety of economic sectors and user groups. The WGRI provides a normalized score to reflect high spatial and temporal variability typical for urban catchments that apply to different settings and problems. Index calculation involves the combination of unmet water demand and its characteristics with socioeconomic aspects related to vulnerability and exposure. The Water Gap term quantifies water system performance over a defined time period taking into account the frequency, persistence, and severity of unmet water demand.  Vulnerability metrics provide a score for each sector and user-group separately using context-specific vulnerability indicators of each sector and user-group.</p><p>In the novel WGRI special attention is paid to the vulnerability of different water user-groups, based on their socio-economic status level (expressed in income, consumption, or other indicators) and respective water use. We consider that 1 liter of water does not have the same utility for different user groups, based on the principle of the diminishing marginal utility curve. As a result, the impact of water scarcity and mitigation measures will also play out differently for these different user groups.</p><p>The novel WGRI is being applied in the context of the WaterLOUPE approach[1], to the catchment of Sao Paolo, Lima, and Chennai.</p><p>[1] https://doi.org/10.5194/egusphere-egu2020-20505</p>

scholarly journals Ocean Exchange and Circulation

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 882
Author(s):  
Miroslav Gačić ◽  
Manuel Bensi
Keyword(s):  
World Ocean ◽  
Northwest Pacific ◽  
Spatial And Temporal Variability ◽  
Oceanic Circulation ◽  
Special Issue ◽  
Mixing Processes ◽  
Norwegian Sea ◽  
Basin Scale ◽  
Mean Circulation ◽  
The Impact

The great spatial and temporal variability, which characterizes the marine environment, requires a huge effort to be observed and studied properly since changes in circulation and mixing processes directly influence the variability of the physical and biogeochemical properties. A multi-platform approach and a collaborative effort, in addition to optimizing both data collection and quality, is needed to bring the scientific community to more efficient monitoring and predicting of the world ocean processes. This Special Issue consists of nine original scientific articles that address oceanic circulation and water mass exchange. Most of them deal with mean circulation, basin and sub-basin-scale flows, mesoscale eddies, and internal processes (e.g., mixing and internal waves) that contribute to the redistribution of oceanic properties and energy within the ocean. One paper deals with numerical modelling application finalized to evaluate the capacity of coastal vegetated areas to mitigate the impact of a tsunami. The study areas in which these topics are developed include both oceanic areas and semi-enclosed seas such as the Mediterranean Sea, the Norwegian Sea and the Fram Strait, the South China Sea, and the Northwest Pacific. Scientific findings presented in this Special Issue highlight how a combination of various modern observation techniques can improve our understanding of the complex physical and biogeochemical processes in the ocean.

Accounting for the spatial rainfall variability in urban modelling applications

2002 ◽  
Vol 45 (2) ◽  
pp. 105-112 ◽  
Author(s):  
P. Williams ◽  
J. Berlamont
Keyword(s):  
Spatial Distribution ◽  
Spatial Variability ◽  
Rainfall Variability ◽  
Hydrodynamic Modelling ◽  
Correction Factors ◽  
Ongoing Research ◽  
Flemish Community ◽  
Urban Modelling ◽  
Urban Catchments ◽  
Stochastic Simulation Model

In hydrological and hydrodynamic modelling of urban catchments, the spatial variability of rainfall is often neglected. This spatial variability encloses two aspects: (1) the spatial variability of the statistical properties of rainfall, and (2) the non-uniform spatial distribution of rainfall over the modelled catchments. In an ongoing research project for the Ministry of the Flemish Community (Belgium), the influence of this spatial rainfall variability on the results of modelling applications is studied. At the same time, most efficient methods to reduce this influence are determined. The results of the research can be applied directly in Flanders. They consist of a combination of unified IDF-relationships, spatial correction factors (generally applicable formulas), a stochastic simulation model for spatial rainfall (software) and a methodology for improving the spatial correction factors in a case-specific way by performing simulations with the model.

A spatially explicit population model of the effect of spatial scale of heterogeneity in grass–clover grazing systems

2013 ◽  
Vol 152 (3) ◽  
pp. 394-407 ◽  
Author(s):  
J. M. SHARP ◽  
G. R. EDWARDS ◽  
M. J. JEGER
Keyword(s):  
Spatial Scales ◽  
Spatial Separation ◽  
Grazing Pressure ◽  
Complete Separation ◽  
Spatially Explicit ◽  
Spatial And Temporal Variability ◽  
N Fixation ◽  
Pasture Management ◽  
Grazed Pasture ◽  
The Impact

SUMMARYThe benefits of using white clover (Trifolium repensL.) as a source of nitrogen (N) and nutritious feed in pasture grazed by ruminant livestock have been widely recognized. However, clover is considered inadequate and unreliable as the main source of N input, since its abundance in pasture is patchy, low (typically <0·20) and shows great year-to-year variation. This is thought to be due to the metabolic costs of N fixation, competition with grass, the preference for clover by grazing animals and patchy dung and urine deposition. One solution suggested by a number of authors is to increase the heterogeneity within the pasture by spatially separating clover from grass. This method of pasture management, in order to sustain higher clover content in both the sward and diet of grazing animals, would remove inter-specific competition and equalize grazing pressure, allowing clover to grow unimpeded in greater abundance than previously observed. An existing spatially explicit grass–clover simulation model, developed to investigate the intrinsic spatial and temporal variability within mixed grass–clover swards, was modified and then used to examine the impact of spatial separation on the content, variability and patchiness of clover in pasture. The results show that spatial separation increases both the content and spatial aggregation of clover and reduces year-to-year variation compared with a mixed pasture that fluctuates around a lower mean. The same model was also used to examine the impact of spatial separation across a range of spatial scales, from narrow strips to complete separation, as a means of managing the concerns over disruption to the N cycle within the pasture. The present study shows the importance of the initial sowing arrangement of plant species in sustaining a high content of clover within a pasture in the short term, to at least 20 years depending on the scale of separation, and demonstrates that the spatial separation of clover from grass within a grazed pasture may overcome some of the limitations associated with the use of clover in conventional grass–clover pastures. Results are discussed in terms of benefits to both herbage dry matter production and animal performance.

Impact of rainfall temporal resolution on urban water quality modelling performance and uncertainties

2013 ◽  
Vol 68 (1) ◽  
pp. 68-75 ◽  
Author(s):  
Bastian Johann Manz ◽  
Juan Pablo Rodríguez ◽  
Čedo Maksimović ◽  
Neil McIntyre
Keyword(s):  
Water Quality ◽  
Temporal Resolution ◽  
Rainfall Variability ◽  
Water Quality Model ◽  
Urban Water ◽  
Water Quality Modelling ◽  
Quality Model ◽  
Urban Water Quality ◽  
Urban Catchments ◽  
The Impact

A key control on the response of an urban drainage model is how well the observed rainfall records represent the real rainfall variability. Particularly in urban catchments with fast response flow regimes, the selection of temporal resolution in rainfall data collection is critical. Furthermore, the impact of the rainfall variability on the model response is amplified for water quality estimates, as uncertainty in rainfall intensity affects both the rainfall-runoff and pollutant wash-off sub-models, thus compounding uncertainties. A modelling study was designed to investigate the impact of altering rainfall temporal resolution on the magnitude and behaviour of uncertainties associated with the hydrological modelling compared with water quality modelling. The case study was an 85-ha combined sewer sub-catchment in Bogotá (Colombia). Water quality estimates showed greater sensitivity to the inter-event variability in rainfall hyetograph characteristics than to changes in the rainfall input temporal resolution. Overall, uncertainties from the water quality model were two- to five-fold those of the hydrological model. However, owing to the intrinsic scarcity of observations in urban water quality modelling, total model output uncertainties, especially from the water quality model, were too large to make recommendations for particular model structures or parameter values with respect to rainfall temporal resolution.

scholarly journals The Effect of Satellite Rainfall Error Modeling on Soil Moisture Prediction Uncertainty

2011 ◽  
Vol 12 (3) ◽  
pp. 413-428 ◽  
Author(s):  
Viviana Maggioni ◽  
Rolf H. Reichle ◽  
Emmanouil N. Anagnostou
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Spatial Scales ◽  
Error Model ◽  
Error Modeling ◽  
Surface Model ◽  
Radar Rainfall ◽  
Error Structure ◽  
Satellite Rainfall ◽  
The Impact

Abstract This study assesses the impact of satellite rainfall error structure on soil moisture simulations with the NASA Catchment land surface model. Specifically, the study contrasts a complex satellite rainfall error model (SREM2D) with the standard rainfall error model used to generate ensembles of rainfall fields as part of the Land Data Assimilation System (LDAS) developed at the NASA Global Modeling and Assimilation Office. The study is conducted in the Oklahoma region, which offers good coverage by weather radars and in situ meteorological and soil moisture measurement stations. The authors used high-resolution (25 km, 3-hourly) satellite rainfall fields derived from the NOAA/Climate Prediction Center morphing (CMORPH) global satellite product and rain gauge–calibrated radar rainfall fields (considered as the reference rainfall). The LDAS simulations are evaluated in terms of rainfall and soil moisture error. Comparisons of rainfall ensembles generated by SREM2D and LDAS against reference rainfall show that both rainfall error models preserve the satellite rainfall error characteristics across a range of spatial scales. The error structure in SREM2D is shown to generate rainfall replicates with higher variability that better envelop the reference rainfall than those generated by the LDAS error model. Likewise, the SREM2D-generated soil moisture ensemble shows slightly higher spread than the LDAS-generated ensemble and thus better encapsulates the reference soil moisture. Soil moisture errors, however, are less sensitive than precipitation errors to the complexity of the precipitation error modeling approach because soil moisture dynamics are dissipative and nonlinear.

scholarly journals A modeling approach to assess the hydrological response of small mediterranean catchments to the variability of soil characteristics in a context of extreme events

2009 ◽  
Vol 13 (2) ◽  
pp. 79-97 ◽  
Author(s):  
C. Manus ◽  
S. Anquetin ◽  
I. Braud ◽  
J.-P. Vandervaere ◽  
J.-D. Creutin ◽  
...  
Keyword(s):  
Extreme Events ◽  
Rainfall Variability ◽  
Soil Characteristics ◽  
Model Verification ◽  
Hydrological Response ◽  
Ungauged Catchments ◽  
Radar Rainfall ◽  
Modeling Approach ◽  
In Situ Investigation ◽  
Modeling Study

Abstract. This paper presents a modeling study aiming at quantifying the possible impact of soil characteristics on the hydrological response of small ungauged catchments in a context of extreme events. The study focuses on the September 2002 event in the Gard region (South-Eastern France), which led to catastrophic flash-floods. The proposed modeling approach is able to take into account rainfall variability and soil profiles variability. Its spatial discretization is determined using Digital Elevation Model (DEM) and a soil map. The model computes infiltration, ponding and vertical soil water distribution, as well as river discharge. In order to be applicable to ungauged catchments, the model is set up without any calibration and the soil parameter specification is based on an existing soil database. The model verification is based on a regional evaluation using 17 estimated discharges obtained from an extensive post-flood investigation. Thus, this approach provides a spatial view of the hydrological response across a large range of scales. To perform the simulations, radar rainfall estimations are used at a 1 km2 and 5 min resolution. To specify the soil hydraulic properties, two types of pedotransfer function (PTF) are compared. It is shown that the PTF including information about soil structure reflects better the spatial variability that can be encountered in the field. The study is focused on four small ungauged catchments of less than 10 km2, which experienced casualties. Simulated specific peak discharges are found to be in agreement with estimations from a post-event in situ investigation. Examining the dynamics of simulated infiltration and saturation degrees, two different behaviors are shown which correspond to different runoff production mechanisms that could be encountered within catchments of less than 10 km2. They produce simulated runoff coefficients that evolve in time and highlight the variability of the infiltration capacity of the various soil types. Therefore, we propose a cartography distinguishing between areas prone to saturation excess and areas prone only to infiltration excess mechanisms. The questions raised by this modeling study will be useful to improve field observations, aiming at better understanding runoff generation for these extreme events and examine the possibility for early warning, even in very small ungauged catchments.

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