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

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.

2016 ◽  
Author(s):  
Elena Cristiano ◽  
Marie-Claire ten Veldhius ◽  
Nick van de Giesen

Abstract. In urban areas, hydrological processes are characterised 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, interaction between input variability and model resolution remains poorly understood, and further investigations are needed. 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. We review recent findings on the effects of rainfall variability on hydrological response and identify gaps where knowledge need to be further developed to improve our understanding of and capability to predict urban hydrological response.


2013 ◽  
Vol 17 (6) ◽  
pp. 2195-2208 ◽  
Author(s):  
N. Peleg ◽  
M. Ben-Asher ◽  
E. Morin

Abstract. Runoff and flash flood generation are very sensitive to rainfall's spatial and temporal variability. The increasing use of radar and satellite data in hydrological applications, due to the sparse distribution of rain gauges over most catchments worldwide, requires furthering our knowledge of the uncertainties of these data. In 2011, a new super-dense network of rain gauges containing 14 stations, each with two side-by-side gauges, was installed within a 4 km2 study area near Kibbutz Galed in northern Israel. This network was established for a detailed exploration of the uncertainties and errors regarding rainfall variability within a common pixel size of data obtained from remote sensing systems for timescales of 1 min to daily. In this paper, we present the analysis of the first year's record collected from this network and from the Shacham weather radar, located 63 km from the study area. The gauge–rainfall spatial correlation and uncertainty were examined along with the estimated radar error. The nugget parameter of the inter-gauge rainfall correlations was high (0.92 on the 1 min scale) and increased as the timescale increased. The variance reduction factor (VRF), representing the uncertainty from averaging a number of rain stations per pixel, ranged from 1.6% for the 1 min timescale to 0.07% for the daily scale. It was also found that at least three rain stations are needed to adequately represent the rainfall (VRF < 5%) on a typical radar pixel scale. The difference between radar and rain gauge rainfall was mainly attributed to radar estimation errors, while the gauge sampling error contributed up to 20% to the total difference. The ratio of radar rainfall to gauge-areal-averaged rainfall, expressed by the error distribution scatter parameter, decreased from 5.27 dB for 3 min timescale to 3.21 dB for the daily scale. The analysis of the radar errors and uncertainties suggest that a temporal scale of at least 10 min should be used for hydrological applications of the radar data. Rainfall measurements collected with this dense rain gauge network will be used for further examination of small-scale rainfall's spatial and temporal variability in the coming years.


2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Jaber Almedeij

This study examines the spatial and temporal variability of monthly total rainfall data obtained from weather stations located in the urban areas of Kuwait. The rainfall data are analyzed by considering statistics on a seasonal basis and by means of periodogram technique to reveal the periods responsible for the variable pattern. The results demonstrate similarity implying that a point estimate of rainfall data can be considered spatially representative over the urban areas of Kuwait. A sinusoidal model triggering the influence of the detected periods is developed accordingly for the time duration from January 1965 to December 2009. The model is capable of describing the rainfall data with some discrepancies between the actual and calculated values resulting from hidden periods that have not been taken into account. This finding suggests that the ability to construct a more reliable model would require a wider range of historical data to detect the other periods affecting the rainfall pattern.


2014 ◽  
Vol 12 (8) ◽  
pp. 607-617 ◽  
Author(s):  
Auguste Gires ◽  
Agathe Giangola-Murzyn ◽  
Jean-Baptiste Abbes ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Schertzer ◽  
...  

2013 ◽  
Vol 13 (9) ◽  
pp. 4941-4961 ◽  
Author(s):  
C. Lac ◽  
R. P. Donnelly ◽  
V. Masson ◽  
S. Pal ◽  
S. Riette ◽  
...  

Abstract. Accurate simulation of the spatial and temporal variability of tracer mixing ratios over urban areas is a challenging and interesting task needed to be performed in order to utilise CO2 measurements in an atmospheric inverse framework and to better estimate regional CO2 fluxes. This study investigates the ability of a high-resolution model to simulate meteorological and CO2 fields around Paris agglomeration during the March field campaign of the CO2-MEGAPARIS project. The mesoscale atmospheric model Meso-NH, running at 2 km horizontal resolution, is coupled with the Town Energy Balance (TEB) urban canopy scheme and with the Interactions between Soil, Biosphere and Atmosphere CO2-reactive (ISBA-A-gs) surface scheme, allowing a full interaction of CO2 modelling between the surface and the atmosphere. Statistical scores show a good representation of the urban heat island (UHI) with stronger urban–rural contrasts on temperature at night than during the day by up to 7 °C. Boundary layer heights (BLH) have been evaluated on urban, suburban and rural sites during the campaign, and also on a suburban site over 1 yr. The diurnal cycles of the BLH are well captured, especially the onset time of the BLH increase and its growth rate in the morning, which are essential for tall tower CO2 observatories. The main discrepancy is a small negative bias over urban and suburban sites during nighttime (respectively 45 m and 5 m), leading to a few overestimations of nocturnal CO2 mixing ratios at suburban sites and a bias of +5 ppm. The diurnal CO2 cycle is generally well captured for all the sites. At the Eiffel tower, the observed spikes of CO2 maxima occur every morning exactly at the time at which the atmospheric boundary layer (ABL) growth reaches the measurement height. At suburban ground stations, CO2 measurements exhibit maxima at the beginning and at the end of each night, when the ABL is fully contracted, with a strong spatio-temporal variability. A sensitivity test without urban parameterisation removes the UHI and underpredicts nighttime BLH over urban and suburban sites, leading to large overestimation of nocturnal CO2 mixing ratio at the suburban sites (bias of +17 ppm). The agreement between observation and prediction for BLH and CO2 concentrations and urban–rural increments, both day and night, demonstrates the potential of using the urban mesoscale system in the context of inverse modelling


2020 ◽  
Author(s):  
Yangzi Qiu ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Scherzter

&lt;p&gt;Nature-Based Solutions (NBS) practices provide many benefits for sustainable development of urban environments, one of which is their ability to mitigate the urban waterlogging. In many previous studies, the performances of NBS practices are analysed with the semi-distributed model and artificial rainfall without considering the spatial variability of rainfall. However, the NBS practices are decentralized in urban areas, their hydrological response is very depends on the small-scale heterogeneity of urban environments. Therefore, this research aims to investigate the impacts of small-scale rainfall variability on the hydrological responses of NBS practices.&lt;/p&gt;&lt;p&gt;In this study, the hydrological response of NBS practices was analysed at the urban catchment scale. A 5.2 km&lt;sup&gt;2&lt;/sup&gt; semi-urban catchment (Guyancourt, located in the South-West of Paris) are investigated under various future NBS implementation scenarios (porous pavement, green roof, rain garden and combined). Regarding the objective of this research, three typical rainfall events are selected. Three sets of distributed rainfall data at a high resolution of 250 m&amp;#215;250 m&amp;#215;3.41 min were obtained from the X-band radar of Ecole des Ponts ParisTech (ENPC). In addition, three sets of corresponded homogeneous rainfall data are applied and used for comparing with the distributed one. Furthermore, a fully distributed and grid based hydrological model (Multi-Hydro), developed at ENPC, which takes into consideration the spatial variability of the whole catchment at 10 m scale. The hydrological response of NBS scenarios was analysed with the percentage error on total volume and peak discharge, with regards to the baseline scenario (current configuration).&lt;/p&gt;&lt;p&gt;Results show that the spatial variability of rainfall has the impact on the hydrological response of NBS scenarios in varying degrees, and it is more evident for green roof scenario. In three rainfall events, the maximum percentage error on peak discharge of green roof scenario under distributed rainfall is 23 %, while that of the green roof scenario under homogeneous rainfall is 17.7%. Overall, the results suggest that the implementation of porous pavement and rain garden is more flexible than implementation of green roof in a semi-urban catchment.&lt;/p&gt;


Author(s):  
Dr. Vasudev S. Salunke ◽  
Pramila. P. Zaware

Rainfall is one of the vital form of precipitation which affects not only agricultural activity but also entire ecology in any region. Hence rainfall distribution and its trends in district is important to understand water availability and to take decisions for the agricultural activities in area. This research paper is an effort to assess the spatial and temporal rainfall variability of Ahmednagar district of Maharashtra State. Ahmednagar is popularly known as the largest district of Maharashtra with fourteen Talukas. The average annual rainfall of this district is 621 mm with an average of 46 rainy days. In this study the spatial and temporal rainfall distribution of this district is taken in to account. Short-term annual rainfall data are considered from 1998 to 2014. The daily rainfalls of monsoon months of all the fourteen Taluka are analyzed for the year 2015.It was found that spatial and temporal variability is high in the District.


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