Raido Puust

Bio: Raido Puust is an academic researcher from Tallinn University of Technology. The author has contributed to research in topics: Stormwater & Water flow. The author has an hindex of 5, co-authored 27 publications receiving 560 citations.

A review of methods for leakage management in pipe networks

Abstract: Leakage in water distribution systems is an important issue which is affecting water companies and their customers worldwide. It is therefore no surprise that it has attracted a lot of attention by both practitioners and researchers over the past years. Most of the leakage management related methods developed so far can be broadly classified as follows: (1) leakage assessment methods which are focusing on quantifying the amount of water lost; (2) leakage detection methods which are primarily concerned with the detection of leakage hotspots and (3) leakage control models which are focused on the effective control of current and future leakage levels. This paper provides a comprehensive review of the above methods with the objective to identify the current state-of-the-art in the field and to then make recommendations for future work. The review ends with the main conclusion that despite all the advancements made in the past, there is still a lot of scope and need for further work, especially in area of rea...

Probabilistic leak detection in pipe networks using the scem-ua algorithm

Abstract: Several methods have been developed so far which attempt to detect leaks in water distribution systems by taking into account pressure (and possibly other available) measurements. As in many previous approaches, the leak detection problem is formulated and solved here as an inverse problem with unknown leak areas being the calibration parameters. However, unlike the previous approaches, a stochastic (rather than deterministic) leakage detection methodology is developed and used here. This methodology is based on the Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm and is capable of estimating the posterior probability density functions of unknown leak areas in a single model run. Baring in mind the accuracy of similar leak detection approaches, it is believed that the stochastic context used here is more appropriate than the deterministic one used before. To achieve the above goal, the Epanet2 hydraulic network modelling software is linked to the SCEM-UA software in the Matlab programming environment. The SCEM-UA algorithm parameters are tuned to achieve an effective and efficient search for unknown leak areas. The methodology developed is tested on two literature case studies.

Peak flow reduction from small catchments using smart inlets

Abstract: A concept for reducing stormwater peak run-off from existing small urban catchments is developed. Stormwater inflow from the ground to the pipeline is managed by smart gullies. The gullies are real...

A review of methods for leakage management in pipe networks

Abstract: Leakage in water distribution systems is an important issue which is affecting water companies and their customers worldwide. It is therefore no surprise that it has attracted a lot of attention by both practitioners and researchers over the past years. Most of the leakage management related methods developed so far can be broadly classified as follows: (1) leakage assessment methods which are focusing on quantifying the amount of water lost; (2) leakage detection methods which are primarily concerned with the detection of leakage hotspots and (3) leakage control models which are focused on the effective control of current and future leakage levels. This paper provides a comprehensive review of the above methods with the objective to identify the current state-of-the-art in the field and to then make recommendations for future work. The review ends with the main conclusion that despite all the advancements made in the past, there is still a lot of scope and need for further work, especially in area of rea...

The Economics of Happiness

Abstract: Welfare and well-being have traditionally been gauged by using income and employment statistics, life expectancy, and other objective measures. The Economics of Happiness, which is based on people’s reports of how their lives are going, provides a complementary yet radically different approach to studying human well-being. Typically, subjective well-being measures include positive and negative feelings (e.g., momentary experiences of happiness or stress), life evaluations (e.g., life satisfaction), and feelings of having a life purpose. Both businesses and policymakers now increasingly make decisions and craft policies based on such measures. This chapter provides an overview of the Happiness Economics approach and outlines the promises and pitfalls of subjective well-being measures.

Methods and Tools for Managing Losses in Water Distribution Systems

Abstract: The water industry worldwide is facing challenges of water and revenue losses. To reduce these losses and improve efficiency of water distribution systems, tools and methods have been developed over the years. This paper reviews the current tools and methodologies applied to assess, monitor, and control losses in water distribution systems. The aim is to identify the tools and methods that have been applied, knowledge gaps, and future research needs. The review findings indicate that a number of water loss management tools and methods have been developed and applied. They vary from simple managerial tools such as performance indicators to highly sophisticated optimization methods such as evolutionary algorithms. However, their application to real-world water distribution systems has been found to be generally limited. Future research opportunities exist through close collaboration of research institutions and water service providers to close the gap between theory and applications. Although not ex...

Automated Detection of Pipe Bursts and Other Events in Water Distribution Systems

Abstract: This paper presents a new methodology for the automated near-real-time detection of pipe bursts and other events that induce similar abnormal pressure/flow variations (e.g., unauthorized consumptions) at the district metered area (DMA) level. The new methodology makes synergistic use of several self-learning artificial intelligence (AI) techniques and statistical data analysis tools, including wavelets for denoising of the recorded pressure/flow signals, artificial neural networks (ANNs) for the short-term forecasting of pressure/flow signal values, statistical process control (SPC) techniques for short- and long-term analysis of the pipe burst/other event-induced pressure/flow variations, and Bayesian inference systems (BISs) for inferring the probability of a pipe burst/other event occurrence and raising corresponding detection alarms. The methodology presented here is tested and verified on a case study involving several DMAs in the United Kingdom (U.K.) with both real-life pipe burst/other eve...

An approach to identify urban groundwater recharge

Abstract: . Evaluating the proportion in which waters from different origins are mixed in a given water sample is relevant for many hydrogeological problems, such as quantifying total recharge, assessing groundwater pollution risks, or managing water resources. Our work is motivated by urban hydrogeology, where waters with different chemical signature can be identified (losses from water supply and sewage networks, infiltration from surface runoff and other water bodies, lateral aquifers inflows, ...). The relative contribution of different sources to total recharge can be quantified by means of solute mass balances, but application is hindered by the large number of potential origins. Hence, the need to incorporate data from a large number of conservative species, the uncertainty in sources concentrations and measurement errors. We present a methodology to compute mixing ratios and end-members composition, which consists of (i) Identification of potential recharge sources, (ii) Selection of tracers, (iii) Characterization of the hydrochemical composition of potential recharge sources and mixed water samples, and (iv) Computation of mixing ratios and reevaluation of end-members. The analysis performed in a data set from samples of the Barcelona city aquifers suggests that the main contributors to total recharge are the water supply network losses (22%), the sewage network losses (30%), rainfall, concentrated in the non-urbanized areas (17%), from runoff infiltration (20%), and the Besos River (11%). Regarding species, halogens (chloride, fluoride and bromide), sulfate, total nitrogen, and stable isotopes (18O, 2H, and 34S) behaved quite conservatively. Boron, residual alkalinity, EDTA and Zn did not. Yet, including these species in the computations did not affect significantly the proportion estimations.