Inferring groundwater system dynamics from hydrological time-series data

Doglioni, Angelo; Mancarella, D.; Simeone, Vincenzo; Giustolisi, Orazio

doi:10.1080/02626661003747556

Cited by 32 publications

(15 citation statements)

References 38 publications

(45 reference statements)

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“…The two techniques applied are: multiple linear regression (STEPWISE) and evolutionary polynomial regression (EPR). These techniques have been used for modelling the water related applications (Mountains 2013;Doglioni et al 2010) and achieved good results.…”

Section: Modelled Daily Per Capita Usage With Household Characteristicsmentioning

confidence: 99%

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Assessing and Modelling the Influence of Household Characteristics on Per Capita Water Consumption

Hussien

Memon

Savić

2016

Water Resour Manage

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Sustainable urban water supply management requires, ideally, accurate evidence based estimations on per capita consumption and a good understanding of the factors influencing the consumption. The information can then be used to achieve improved water demand forecasts. Water consumption patterns in the developed countries have been extensively investigated. However, very little is known for the developing world. This paper investigates per capita water consumption resulting from water use activities in different types of households typically found in urban areas of the developing world. A data collection programme was executed for 407 households to extract information on household characteristics, water user behaviour and intensity and the nature of indoor and outdoor water use activities. The rigorous statistical analysis of the data shows that per capita water consumption increases with income: 241, 272 and 290 l/capita/day for low, medium and high income households, respectively. Additionally, the results suggest that per capita consumption increases with the number of adult female members in the household and almost one-third of consumption is via taps. The collected data has been used to develop statistical models using two different regression techniques: multiple linear (STEPWISE) and evolutionary polynomial regression (EPR). The inclusion of demographic parameters in the developed models considerably improved the prediction accuracy. Two of the best performing models are used to forecast the water demand for the city, using four future scenarios: market forces, fortress world, policy reform and great transition. The results suggest that the domestic water demand would be highest in the fortress world scenario due to the increase in population and size of built-up area.

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Section: Modelled Daily Per Capita Usage With Household Characteristicsmentioning

confidence: 99%

“…This technique has been used in a number of other applications, such as evapotranspiration process (El-Baroudy et al 2010), rainfall-groundwater dynamics (Doglioni et al 2010), water distribution and wastewater networks (Berardi et al 2008), and have shown good performance.…”

Section: Models Based On Evolutionary Polynomial Regression (Epr)mentioning

confidence: 99%

Assessing and Modelling the Influence of Household Characteristics on Per Capita Water Consumption

Hussien

Memon

Savić

2016

Water Resour Manage

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“…This method was adopted because it can derive simple and interpretable mathematical equations for parameter estimation and data prediction (Giustolisi & Savic, 2006). It has also been proven effective in modelling environmental and hydrological phenomena, particularly those involving high nonlinearity and uninterpretable dynamics (Doglioni, Mancarella, Simeone, & Giustolisi, 2010;Vassallo, Doglioni, Grimaldi, Di Maio, & Simeone, 2016).…”

Section: Discussionmentioning

confidence: 99%

Interactions between shallow groundwater and low‐impact development underdrain flow at different temporal scales

Zhang

Chui

2018

Hydrological Processes

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Low‐impact development (LID) practices are effective in managing surface run‐off, mitigating nonpoint source pollution, and recharging groundwater. However, they are often less effective in shallow groundwater environments as their surface infiltration and bottom exfiltration rates could be reduced, and the underdrains (i.e., underground drains within the media of the LID practices) may drain groundwater and alter groundwater dynamics. To evaluate and better understand the interactions between shallow groundwater and LID underdrain flow at different temporal scales, multiple statistical analyses were conducted on the monitored groundwater table depth and underdrain flow of porous pavements at the Central Kitsap Community Campus (Washington) and both porous pavements and bioretention cells at the IMAX parking lot (Ontario, Canada). The wavelet power, which represents oscillation behaviour and is obtained by continuous wavelet transform, of underdrain flow was a hybrid of that of rainfall and groundwater table depth. Rainfall variations at finer temporal scales (5 min to 10 days) resulted in finer scale underdrain flow, whereas groundwater fluctuations at coarser temporal scales (10 to 30 days) accounted for coarser scale underdrain flow and extended the duration of it. The impact of groundwater on underdrain flow was greater when the groundwater table was shallower than the underdrain (e.g., <0.6 m), particularly at finer temporal resolutions (5 min to 1 hr), which correspond to short‐term responses of LID practices and their corresponding effects on flooding. It was possible that the local groundwater mounds formed by infiltrated water instead of regional groundwater fluctuations that affected the underdrain flow in these conditions. Finally, through an evolutionary polynomial regression, two simple equations were obtained to predict the total amount and peak of LID underdrain flow using event‐based rainfall, groundwater table depth, and the hydraulic conductivity of media and in situ soils. The results may facilitate LID design and planning, and their implementation in shallow groundwater areas. The derived equations may benefit the real‐time control of LID‐related sewer and treatment systems in shallow groundwater urban catchments.

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“…conflicting objectives; Giustolisi & Savic 2009). The EPR has already been applied successfully to other complex civil engineering problems, see for example Javadi & Rezania (2009), Berardi et al (2008, Doglioni et al (2010) and Laucelli & Giustolisi (2on).…”

Section: Introductionmentioning

confidence: 98%

Evolutionary data-modelling of an innovative low reflective vertical quay

Altomare

Gironella

Laucelli

2012

Journal of Hydroinformatics

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Vertical walls are commonly used as berthing structures. However, conventional vertical quays may have serious technical and environmental problems, as they reflect almost all the energy of the incident waves, thus affecting operational conditions and structural strength. These drawbacks can be overcome by the use of low reflective structures, but for some instances no theoretical equations exist to determine the relationship between the reflection coefficient and parameters that affect the structural response. Therefore, this study tries to fill this gap by examining the wave reflection of an absorbing gravity wall by means of evolutionary polynomial regression, a hybrid evolutionary modelling paradigm that combines the best features of conventional numerical regression and genetic programming. The method implements a multi-modelling approach in which a multi-objective genetic algorithm is used to get optimal models in terms of parsimony of mathematical expressions and fitting to data. A database of physical laboratory observations is used to predict the reflection as a function of a set of variables that characterize wave conditions and structure features. The proposed modelling paradigm proved to be a useful tool for data analysis and is able to find feasible explicit models featured by an appreciable generalization performance

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Inferring groundwater system dynamics from hydrological time-series data

Cited by 32 publications

References 38 publications

Assessing and Modelling the Influence of Household Characteristics on Per Capita Water Consumption

Assessing and Modelling the Influence of Household Characteristics on Per Capita Water Consumption

Interactions between shallow groundwater and low‐impact development underdrain flow at different temporal scales

Evolutionary data-modelling of an innovative low reflective vertical quay

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