scholarly journals Modeling Rainfall Variability over Urban Areas: A Case Study for Kuwait

2012 ◽  
Vol 2012 ◽  
pp. 1-8 ◽  
Author(s):  
Jaber Almedeij
Keyword(s):  
Urban Areas ◽  
Rainfall Variability ◽  
Rainfall Data ◽  
Point Estimate ◽  
Spatial And Temporal Variability ◽  
Time Duration ◽  
Reliable Model ◽  
Monthly Total ◽  
Seasonal Basis

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.

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.

scholarly journals Spatial and Temporal Rainfall Variability over the Mountainous Central Pindus (Greece)

Climate ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 75 ◽  
Author(s):  
Stefanos Stefanidis ◽  
Dimitrios Stathis
Keyword(s):  
Multiple Regression ◽  
Rainfall Variability ◽  
Multiple Regression Model ◽  
Rainfall Data ◽  
Annual Rainfall ◽  
Spatial And Temporal Variability ◽  
Mountain Range ◽  
Rainfall Time Series ◽  
Distribution Maps ◽  
Mountainous Catchment

In this study, the authors evaluated the spatial and temporal variability of rainfall over the central Pindus mountain range. To accomplish this, long-term (1961–2016) monthly rainfall data from nine rain gauges were collected and analyzed. Seasonal and annual rainfall data were subjected to Mann–Kendall tests to assess the possible upward or downward statistically significant trends and to change-point analyses to detect whether a change in the rainfall time series mean had taken place. Additionally, Sen’s slope method was used to estimate the trend magnitude, whereas multiple regression models were developed to determine the relationship between rainfall and geomorphological factors. The results showed decreasing trends in annual, winter, and spring rainfalls and increasing trends in autumn and summer rainfalls, both not statistically significant, for most stations. Rainfall non-stationarity started to occur in the middle of the 1960s for the annual, autumn, spring, and summer rainfalls and in the early 1970s for the winter rainfall in most of the stations. In addition, the average magnitude trend per decade is approximately −1.9%, −3.2%, +0.7%, +0.2%, and +2.4% for annual, winter, autumn, spring, and summer rainfalls, respectively. The multiple regression model can explain 62.2% of the spatial variability in annual rainfall, 58.9% of variability in winter, 75.9% of variability in autumn, 55.1% of variability in spring, and 32.2% of variability in summer. Moreover, rainfall spatial distribution maps were produced using the ordinary kriging method, through GIS software, representing the major rainfall range within the mountainous catchment of the study area.

scholarly journals Impacts of small scale rainfall variability in urban areas: a case study with 1D and 1D/2D hydrological models in a multifractal framework

2014 ◽  
Vol 12 (8) ◽  
pp. 607-617 ◽  
Author(s):  
Auguste Gires ◽  
Agathe Giangola-Murzyn ◽  
Jean-Baptiste Abbes ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Schertzer ◽  
...  
Keyword(s):  
Urban Areas ◽  
Rainfall Variability ◽  
Small Scale ◽  
Hydrological Models

Assessing the potential of using telecommunication microwave links in urban drainage modelling

2013 ◽  
Vol 68 (8) ◽  
pp. 1810-1818 ◽  
Author(s):  
M. Fencl ◽  
J. Rieckermann ◽  
M. Schleiss ◽  
D. Stránský ◽  
V. Bareš
Keyword(s):  
Urban Areas ◽  
Rainfall Variability ◽  
Rain Gauge ◽  
Urban Drainage ◽  
Rainfall Runoff ◽  
Urban Catchment ◽  
Flow Prediction ◽  
Spatial Coverage ◽  
Spatio Temporal

The ability to predict the runoff response of an urban catchment to rainfall is crucial for managing drainage systems effectively and controlling discharges from urban areas. In this paper we assess the potential of commercial microwave links (MWL) to capture the spatio-temporal rainfall dynamics and thus improve urban rainfall-runoff modelling. Specifically, we perform numerical experiments with virtual rainfall fields and compare the results of MWL rainfall reconstructions to those of rain gauge (RG) observations. In a case study, we are able to show that MWL networks in urban areas are sufficiently dense to provide good information on spatio-temporal rainfall variability and can thus considerably improve pipe flow prediction, even in small subcatchments. In addition, the better spatial coverage also improves the control of discharges from urban areas. This is especially beneficial for heavy rainfall, which usually has a high spatial variability that cannot be accurately captured by RG point measurements.

scholarly journals Modeling Spatiotemporal Rainfall Variability in Paraíba, Brazil

Water ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1843
Author(s):  
Elias Silva de Medeiros ◽  
Renato Ribeiro de Lima ◽  
Ricardo Alves de Olinda ◽  
Carlos Antonio Costa dos Santos
Keyword(s):  
Rainfall Variability ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Future Research ◽  
Time Variability ◽  
Total Rainfall ◽  
Space And Time ◽  
Variable Distribution ◽  
Monthly Total ◽  
The Mean

The purpose of this study was to provide a detailed framework to use the spatiotemporal kriging to model the space-time variability of precipitation data in Paraíba, which is located in the northeastern region of Brazil (NEB). The NEB is characterized by an irregular, highly variable distribution of rainfall in space and time. In this region, it is common to find high rates of rainfall at locations adjacent to those with no record of rain. Paraíba experiences localized periods of drought within rainy seasons and distinct precipitation patterns among the state’s mesoregions. The mean precipitation values observed at several irregularly spaced rain gauge stations from 1994 to 2014 showed remarkable variations among the mesoregions in Paraíba throughout the year. As a consequence of this behavior, there is a need to model the rainfall distribution jointly with space and time. A spatiotemporal geostatistical methodology was applied to monthly total rainfall data from the state of Paraíba. The rainfall data indicate intense spatial and temporal variabilities that directly affect the water resources of the entire region. The results provide a detailed spatial analysis of sectors experiencing precipitation conditions ranging from a scarcity to an excess of rainfall. The present study should help drive future research into spatiotemporal rainfall patterns across all of NEB.

Spatial risk-based assessments for climate adaptation using the SimCLIM modelling system: a case study of domestic rainwater harvesting as the sole source of water

2012 ◽  
Vol 3 (4) ◽  
pp. 257-265 ◽  
Author(s):  
R. Warrick ◽  
G. Ashford ◽  
P. Kouwenhoven ◽  
Y. Li ◽  
P. Urich ◽  
...  
Keyword(s):  
Rainwater Harvesting ◽  
Rainfall Variability ◽  
Sole Source ◽  
Series Data ◽  
Spatial And Temporal Variability ◽  
Water Tank ◽  
Spatial Risk ◽  
Trade Offs ◽  
Modelling System

This paper describes a software modelling system, SimCLIM, for simulating the effects of climate variability and change, and demonstrates its application to domestic rainwater harvesting (RWH). The paper first describes SimCLIM and then focuses on a case study of the reliability of domestic RWH systems as the sole source of water in South East Queensland, a region of high spatial and temporal variability in rainfall. Using the SimCLIM scenario generator along with gridded daily time-series data and a domestic water tank model, ‘risk landscapes’ are created based on the risk of failure of the domestic systems to provide water under both current climate and scenarios of future change. Steep risk gradients were found, with major implications for RWH system configuration. Simulations are then performed in order to examine the trade-offs between two broad strategies – increasing runoff area and increasing tank size – required to maintain a reliable system. The paper concludes that, instead of set specifications, location-specific customisation of RWH systems is preferable in order to ensure reliability under current rainfall variability and sustainability over the long term under climate change. The availability of gridded daily rainfall datasets along with modelling tools like SimCLIM makes this customisation practicable.

scholarly journals Critical scales to explain urban hydrological response: an application in Cranbrook, London

2018 ◽  
Vol 22 (4) ◽  
pp. 2425-2447 ◽  
Author(s):  
Elena Cristiano ◽  
Marie-Claire ten Veldhuis ◽  
Santiago Gaitan ◽  
Susana Ochoa Rodriguez ◽  
Nick van de Giesen
Keyword(s):  
Urban Areas ◽  
Rainfall Variability ◽  
Model Complexity ◽  
Hydrological Response ◽  
Catchment Scale ◽  
Scaling Factors ◽  
Rainfall Events ◽  
Space And Time ◽  
X Band

Abstract. Rainfall variability in space and time, in relation to catchment characteristics and model complexity, plays an important role in explaining the sensitivity of hydrological response in urban areas. In this work we present a new approach to classify rainfall variability in space and time and we use this classification to investigate rainfall aggregation effects on urban hydrological response. Nine rainfall events, measured with a dual polarimetric X-Band radar instrument at the CAESAR site (Cabauw Experimental Site for Atmospheric Research, NL), were aggregated in time and space in order to obtain different resolution combinations. The aim of this work was to investigate the influence that rainfall and catchment scales have on hydrological response in urban areas. Three dimensionless scaling factors were introduced to investigate the interactions between rainfall and catchment scale and rainfall input resolution in relation to the performance of the model. Results showed that (1) rainfall classification based on cluster identification well represents the storm core, (2) aggregation effects are stronger for rainfall than flow, (3) model complexity does not have a strong influence compared to catchment and rainfall scales for this case study, and (4) scaling factors allow the adequate rainfall resolution to be selected to obtain a given level of accuracy in the calculation of hydrological response.

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

2016 ◽  
Author(s):  
Elena Cristiano ◽  
Marie-Claire ten Veldhius ◽  
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 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.

scholarly journals Effect of spatial and temporal variability of gauged and radar rainfall data on hydrological modelingof urban basins

RBRH ◽  
2021 ◽  
Vol 26 ◽  
Author(s):  
Victor Costa Pontes ◽  
Carlos Ruberto Fragoso Jr. ◽  
Marllus Gustavo Ferreira Passos das Neves ◽  
Vladimir Caramori Borges de Souza
Keyword(s):  
Spatial Distribution ◽  
Urban Areas ◽  
Weather Radar ◽  
Radar Data ◽  
Rainfall Data ◽  
Spatial And Temporal Variability ◽  
Peak Time ◽  
Radar Rainfall ◽  
Storm Water Management Model ◽  
Runoff Modeling

ABSTRACT In urban areas, rainfall-runoff modeling provides large uncertainties due to the difficulty in representing the spatial distribution of rainfall events. In this context, the this work aims to evaluate the effect of temporal and spatial of rainfall data (weather radar and distributed rainfall gauges network) on runoff estimation in a urban basin. The Reginaldo basin, inserted in the urban area of the Maceió city, capital of state of Alagoas (Brazil), has a reasonable availability of rainfall datal covered with a high number and spatial distribution of rain gauges and weather radar, which was used as input of a hydrological model The EPA Storm Water Management Model (SWMM) has been used with 3 analysis rainfall scenarios: (i) considering uniform rainfall distribution based on measured average rainfall, (ii) considering distributed rainfall using catchment discretization, and (iii) considering distributed rainfall using radar cell discretization. In order to evaluate the model outcomes, we analyzed four hydrological output variables: (i) the peak flow; (ii) the peak time; (iii) the volume flowed and (iv) the volume losses. Based on this criterion, it was clear that, considering he analyzed scenarios, the effect of spatial distribution of rainfall data on hydrological response in small urban basins, with high impervious coverage, was not divergent for the analyzed scenarios and that the radar data showed significantly higher data resolution than rainfall gauges.

Factors Affecting Financial Literacy of Vietnamese Adults: A Case Study for Hanoi and Nghe An

2017 ◽  
Vol 33 (2) ◽  
Author(s):  
Tue Nguyen Dang
Keyword(s):  
Higher Education ◽  
Multiple Regression ◽  
Financial Literacy ◽  
Urban Areas ◽  
Logistic Models ◽  
Factors Affecting ◽  
Financial Behaviors ◽  
Financial Decisions ◽  
Literacy Level

This research examines the factors affecting the financial literacy of Vietnamese adults. Using a sample of 266 observations of adults in 2 big cities in Vietnam (Hanoi and Vinh in Nghe An Province), the author evaluates the literacy level of adults in these urban areas. The financial literacy of the interviewed people is low. The multiple regression results show that lower financial literacy levels associate with higher age and married status and higher financial literacy levels associate with higher education, more family members, the person making financial decisions and the person attending a useful financial course. This research also explores the association between financial literacy and financial behaviors of individuals employing logistic models. It is found that higher financial literacy associates with less probability of overspending and higher probability of saving money and careful spending. Higher financial literacy is also found to associate with higher probability of opening a savings account and making various investments. 

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