Water Use Data Research Articles

An enhanced method for automated end-use classification of household water data

Abstract An accurate estimation of residential end uses of water is helpful in developing efficient water systems. If not obtainable through direct metering, this information can be gathered by disaggregating and classifying household-level water-use data. However, most automated techniques require fine-resolution data (e.g., 1 s) and end-use parameters which may be unavailable to water utilities. To fill the above gap, this study presents a method for the automated disaggregation and classification of indoor water-use data collected at the 1-min temporal resolution, and by exclusively relying on the end-use parameter values available in the literature. Specifically, the features of each water-use event detected at the household level are compared against the most common event features for the selected end-use category. The results obtained by testing the method with real data collected at 14 households in two different countries (Italy and the Netherlands) confirm its potential in disaggregating and classifying water end-use events with an average accuracy higher than 90% and an average (normalized) root-mean-square lower than 0.06 despite the lack of information about end uses in individual households. This demonstrates that end-use detection is possible even with data whose resolution is closer to that of most commercial water meters.

Estimation of Irrigation Water Use by Using Irrigation Signals from SMAP Soil Moisture Data

Accurate irrigation water-use data are essential to agricultural water resources management and optimal allocation. The obscuration presented by ground cover in farmland and the subjectivity of irrigation-related decision-making processes mean that effectively identifying regional irrigation water use remains a critical problem to be solved. In view of the advantages of satellite microwave remote sensing in monitoring soil moisture, previous studies have proposed a method for estimating irrigation water use using the satellite microwave remote sensing of soil moisture. However, the method is affected by false irrigation signals from soil moisture increases caused by non-irrigation factors, causing irrigation water use to be overestimated. Therefore, the purpose of this study is to improve the estimation of irrigation water use in drylands by using irrigation signals from SMAP soil moisture data. In this paper, the irrigation water use in Henan Province is estimated by using the irrigation signals from SMAP (soil moisture active and passive) soil moisture data. Firstly, a method for recognizing irrigation signals in soil moisture data obtained by microwave satellite remote sensing was used. Then, an estimation model of the amount of irrigation water (SM2Rainfall model) was built on each data pixel of the satellite microwave remote sensing of soil moisture. Finally, the amount of irrigation water utilized in Henan Province was estimated by combining the irrigation signals and irrigation water-use estimation model, and the results were evaluated. According to the findings, this study improved the estimation accuracy of irrigation water use by using the irrigation signals in Henan Province. The result of this study is of great importance to accurately obtain irrigation water use in the region.

Unraveling the Impact of COVID-19 Pandemic Dynamics on Commercial Water-Use Variation

Water use was impacted significantly by the COVID-19 pandemic. Although previous studies quantitatively investigated the effects of COVID-19 on water use, the relationship between water-use variation and COVID-19 dynamics (i.e., the spatial-temporal characteristics of COVID-19 cases) has received less attention. This study developed a two-step methodology to unravel the impact of COVID-19 pandemic dynamics on water-use variation. First, using a water-use prediction model, the water-use change percentage (WUCP) indicator, which was calculated as the relative difference between modeled and observed water use, i.e., water-use variation, was used to quantify the COVID-19 effects on water use. Second, two indicators, i.e., the number of existing confirmed cases (NECC) and the spatial risk index (SRI), were applied to characterize pandemic dynamics, and the quantitative relationship between WUCP and pandemic dynamics was examined by means of regression analysis. We collected and analyzed 6-year commercial water-use data from smart meters of Zhongshan District in Dalian City, Northeast China. The results indicate that commercial water use decreased significantly, with an average WUCP of 59.4%, 54.4%, and 45.7%during the three pandemic waves, respectively, in Dalian. Regression analysis showed that there was a positive linear relationship between water-use changes (i.e., WUCP) and pandemic dynamics (i.e., NECC and SRI). Both the number of COVID-19 cases and their spatial distribution impacted commercial water use, and the effects were weakened by restriction strategy improvement, and the accumulation of experience and knowledge about COVID-19. This study provides an in-depth understanding of the impact of COVID-19 dynamics on commercial water use. The results can be used to help predict water demand under during future pandemic periods or other types of natural and human-made disturbance.

Domestic Water Consumption and Its Influencing Factors in the Yellow River Basin Based on Logarithmic Mean Divisia Index and Decoupling Theory

In recent decades, water resources shortage has become a global problem, and it is critical to analyse the trend of domestic water consumption and its influencing factors to optimise water resource management, promote the construction of a water-saving society, and realise the sustainable development of resources and the environment. We chose the Yellow River Basin as the study area and analysed the temporal and spatial characteristics of domestic water using water-use data, identified its influencing factors by Logarithmic Mean Divisia Index, and analysed its relationship with economic development based on the decoupling theory. In this study, we found that: (1) Domestic water consumption increased in the Yellow River Basin between 2006 and 2020, with provinces primarily located south of the river. (2) Technical and economic effects were the major factors leading to changes in domestic water use. The technical effect is the major factor inhibiting the increase, whereas the economic effect encourages the increase in domestic water consumption. (3) In the Yellow River Basin, weak decoupling was achieved between domestic water consumption and economic growth, with domestic water consumption at a slower rate than the economic growth rate.

A spatial agent-based model for hydraulic fracturing water distribution

Agent-based modeling (ABM) has been employed to understand and capture the complexity of the coupled human-nature processes in water resource systems. One of the challenges is to model human decisions in the coupled human and natural systems. Hydraulic fracturing water uses were distributed through a depot-based water allocation system in the Bakken region of western North Dakota, United States. In this study, a spatially explicit ABM was developed to simulate this unique water allocation system. In the ABM, institution theory was used to model the State’s regulatory policies and procedures, while evolutionary programming was employed to allow the water-depot owners (or agents) to select appropriate strategies when applying for water permits. Cognitive maps simulated the water-depot agents’ ability and willingness to compete for more water sales. All agents had their influence boundaries that restricted their competitive behavior toward their neighbors, but not for non-neighboring agents. The decision-making process was constructed and parameterized with both quantitative and qualitative information. The ABM was calibrated against real-world water-use data, and the calibration results showed that the spatial ABM performed well in simulating the total number of water depots as well as the locations and water uses of water depots at the county level. By linking institution theory, evolutionary programming, and cognitive maps, our study exhibited a new exploration of modeling the highly complex dynamics of the decision-making process involved in coupled human-nature water resource systems.

Evapotranspiration and crop coefficients using lysimeter measurements for food crops in the hyper-arid United Arab Emirates

In the hyper-arid United Arab Emirates (UAE) irrigation is needed for food crops because there is limited rainfall of less than100 mm y−1 in the crop-growing parts of the UAE. Groundwater is the main source of irrigation water, yet it is a declining resource both in terms of quantity, and quality as a result of rising salinity. Law 5 has been passed by the Government of Abu Dhabi to manage groundwater extraction by limiting water takes to an amount that is considered to be sufficient to grow a given crop. In order to allocate these water takes, the Environment Agency – Abu Dhabi sought experimental data and a model platform to calculate equitable allocations for each vegetable crop. We designed simple weighing lysimeters to measure directly the water-use lettuce, capsicum, tomato, cucumber and zucchini grown in the field, as well as in a shadehouse and a cooled greenhouse for capsicum, cucumber and tomato. Total crop yields were measured via progressive harvests through to the end of the growing season. The yields in the greenhouse were the highest. The crop water-use efficiency (WUEC, kg crop per m3 crop evapotranspiration ETC) was three fold higher in the greenhouse (≈ 30 kg m−3) than in the shadehouse or field (≈ 10 kg m−3). However, when the water used to cool evaporatively the greenhouse was accounted for in the water productivity (WPI kg crop m−3 water for irrigation and cooling) there were no differences between the field, shadehouse and greenhouse. So whereas the farmer benefits from higher yields in the greenhouse, there is no advantage in terms of water productivity. However, use of alternative waters for greenhouse cooling, such as treated sewage effluent, could be used to protect groundwater. Our water-use data were used to calculate the seasonal pattern of the FAO56 crop coefficient, KC, through the piecewise linear phases of crop growth, the initial (KCini), middle (KCmid), and the end (KCend) of the growing season. These KC values were compared with recent reviews of FAO56 for vegetables. Due to the various training systems for the crops in this study, the KC values varied considerably, with KCini ranging from 0.2 to 0.5, KCmid from 0.5 to 1.35, and KCend from 0.2 to 0.7. These KC values will be used in our Crop Calculator Decision Support Tool (DST) to implement Law 5.

A new insight for real-time wastewater quality prediction using hybridized kernel-based extreme learning machines with advanced optimization algorithms.

Accurate prediction of inlet chemical oxygen demand (COD) is vital for better planning and management of wastewater treatment plants. The COD values at the inlet follow a complex nonstationary pattern, making its prediction challenging. This study compared the performance of several novel machine learning models developed through hybridizing kernel-based extreme learning machines (KELMs) with intelligent optimization algorithms for the reliable prediction of real-time COD values. The combined time-series learning method and consumer behaviours, estimated from water-use data (hour/day), were used as the supplementary inputs of the hybrid KELM models. Comparison of model performances for different input combinations revealed the best performance using up to 2-day lag values of COD with the other wastewater properties. The results also showed the best performance of the KELM-salp swarm algorithm (SSA) model among all the hybrid models with a minimum root mean square error of 0.058 and mean absolute error of 0.044.

Producing energy, depleting water: the energy sector as a driver of seasonal water scarcity in an extractive frontier of the upper Orinoco watershed, Colombia

ABSTRACT The headwaters of the Orinoco are being transformed into an extractive frontier and experiencing drastic water depletion in the dry season. We use the concept of water metabolism to illustrate the impact of the energy sector in a region typically identified with agriculture. Results indicate that oil palm irrigation for biofuel production together with the disposal of production water from oil extraction account for surface water availability being fully allocated during the dry season. We use ranges in water data and generate scenarios to account for the uncertainty generated by inadequate water-use regulation and limited data availability.

A brief description of domestic water-use data in the city of Rabat-Salé (Morocco)

A small-scale experiment is conducted to estimate domestic water-use rate in the city of Rabat-Salé. Water consumption in 171 households has been closely monitored over a 24-month period. During this survey both the net monthly volume of tap water effectively used in each household and the exact number of people who have lived in the same household are observed. This has resulted in a series of reliable realizations of daily per-capita water rate (denoted q). A usual procedure for data summarizing is presented: It is observed that entity q, interpreted as a random variable, is satisfactorily represented by the log-normal distribution. Estimate for the expected value of q along with the corresponding 95% Cox confidence interval are given. Such estimates are (for instance) essential to future water system extension.

Maternal Exposure to Disinfection By-Products and Risk of Hypospadias in the National Birth Defects Prevention Study (2000-2005).

The purpose of this study was to estimate the association between 2nd and 3rd degree hypospadias and maternal exposure to disinfection by-products (DBPs) using data from a large case-control study in the United States. Concentration estimates for total trihalomethanes (TTHMs), the sum of the five most prevalent haloacetic acids (HAA5), and individual species of each were integrated with data on maternal behaviors related to water-use from the National Birth Defects Prevention Study (NBDPS) to create three different exposure metrics: (1) household DBP concentrations; (2) estimates of DBP ingestion; (3) predicted uptake (i.e., internal dose) of trihalomethanes (THMs) via ingestion, showering, and bathing. The distribution of DBP exposure was categorized as follows: (Q1/referent) < 50%; (Q2) ≥ 50% to < 75%; and (Q3) ≥ 75%. Logistic regression was used to estimate adjusted odds ratios (aORs) and 95% confidence intervals (CIs). Generally, null associations were observed with increasing TTHM or HAA5 exposure. An increased risk was observed among women with household bromodichloromethane levels in the second quantile (aOR: 1.8; 95% CI: 1.2, 2.7); however, this association did not persist after the inclusion of individual-level water-use data. Findings from the present study do not support the hypothesis that maternal DBP exposures are related to the occurrence of hypospadias.

Numerical modelling of the impacts of water abstraction for hydraulic fracturing on groundwater–surface water interaction: a case study from northwestern Alberta, Canada

ABSTRACT The temporal dynamics of groundwater–surface water interaction under the impacts of various water abstraction scenarios are presented for hydraulic fracturing in a shale gas and oil play area (23 984.9 km2), Alberta, Canada, using the MIKE-SHE and MIKE-11 models. Water-use data for hydraulic fracturing were obtained for 433 wells drilled in the study area in 2013 and 2014. Modelling results indicate that water abstraction for hydraulic fracturing has very small (<0.35%) negative impacts on mean monthly and annual river and groundwater levels and stream and groundwater flows in the study area, and small (1–4.17%) negative impacts on environmental flows near the water abstraction location during low-flow periods. The impacts on environmental flow depend on the amount of water abstraction and the daily flow over time at a specific river cross-section. The results also indicate a very small (<0.35%) positive impact on mean monthly and annual groundwater contributions to streamflow because of the large study area. The results provide useful information for planning long-term seasonal and annual water abstractions from the river and groundwater for hydraulic fracturing in a large study area.

Practical Head-Outflow Relationship Definition Methodology That Accounts for Varied Water-Supply Methods

Achieving reliable pressure-driven analysis (PDA) results that account for anomalies within water-pipe networks requires a head-outflow relationship (HOR) model that can calculate supply flow rate according to the supply pressure at each node. Many studies have suggested HOR models, but a methodology to define HORs that considers the actual residential environment of users and differing water-supply methods for residential buildings has not yet been proposed. This study considered water-use data from buildings and actual differences in residential environments in a surveyed area (including building heights, topography, and water systems within buildings) and water-supply methods (indirect/direct water supply, existence of a pump within buildings) to develop a methodology and derive a representative HOR for the target area for PDA. Further, a representative HOR was determined for each block by applying the developed methodology for two blocks with similar residential environments but different water-use patterns. It confirmed that the HOR induced through this process could provide high water-supply performance despite a low supply head and needed to reflect the diversity of the water-supply method. The proposed HOR-definition methodology can be easily applied in water-pipe network design and operation processes and ensure objectivity and rationality of HOR selection to yield reliable PDA results.

Climate and human water use diminish wetland networks supporting continental waterbird migration.

Migrating waterbirds moving between upper and lower latitudinal breeding and wintering grounds rely on a limited network of endorheic lakes and wetlands when crossing arid continental interiors. Recent drying of global endorheic water stores raises concerns over deteriorating migratory pathways, yet few studies have considered these effects at the scale of continental flyways. Here, we investigate the resiliency of waterbird migration networks across western North America by reconstructing long‐term patterns (1984–2018) of terminal lake and wetland surface water area in 26 endorheic watersheds. Findings were partitioned regionally by snowmelt‐ and monsoon‐driven hydrologies and combined with climate and human water‐use data to determine their importance in predicting surface water trends. Nonlinear patterns of lake and wetland drying were apparent along latitudinal flyway gradients. Pervasive surface water declines were prevalent in northern snowmelt watersheds (lakes −27%, wetlands −47%) while largely stable in monsoonal watersheds to the south (lakes −13%, wetlands +8%). Monsoonal watersheds represented a smaller proportion of total lake and wetland area, but their distribution and frequency of change within highly arid regions of the continental flyway increased their value to migratory waterbirds. Irrigated agriculture and increasing evaporative demands were the most important drivers of surface water declines. Underlying agricultural and wetland relationships however were more complex. Approximately 7% of irrigated lands linked to flood irrigation and water storage practices supported 61% of all wetland inundation in snowmelt watersheds. In monsoonal watersheds, small earthen dams, meant to capture surface runoff for livestock watering, were a major component of wetland resources (67%) that supported networks of isolated wetlands surrounding endorheic lakes. Ecological trends and human impacts identified herein underscore the importance of assessing flyway‐scale change as our model depictions likely reflect new and emerging bottlenecks to continental migration.

Understanding Municipal Water Use and Data Availability: a Case Study across North Dakota, USA

Tremendous variation exists in how cities, states, countries, and other jurisdictional areas classify water use and consumption. Additionally, water conservation measures have become more common in the past few decades, but little is known about how these conservation measures are implemented across the landscape. The goal of this study is to increase the breadth of knowledge regarding municipal water-use data: retention, storage, availability, and delving into water conservation measures, along with the impact of shale oil extraction on municipal water use in the Bakken region. Two questionnaires were developed and administered to all municipalities in the state of North Dakota, USA with populations greater than 1000 residents, and between 500 and 1000 residents in the Bakken region (total number (n) =59) willing to participate. Results indicate water conservation measures are inconsistent across the landscape, and data categorization at the municipal level is minimal which limits the analysis, interpretations, and projections that can be made from the data. Additionally, the Bakken region is different from the rest of the state in how they acquire water and sell water to other large scale users. Results from this study will aid water use professionals worldwide by providing valuable information on water-use data, access, storage, and impacts of large water users, such as shale oil extraction, on municipal water. This information will also help researchers to understand availability of data for making comparisons across different areas, assessing trends, and making water use projections.

Measurement of water-use by &lt;i&gt;Jatropha curcas&lt;/i&gt; L. using the heat-pulse velocity technique

In response to the proposed introduction of the potential bio-diesel species Jatropha curcas (Linnaeus) to South Africa, field experiments were conducted to investigate its likely water-use impacts relative to other forms of vegetative land use. As no existing water-use data could be found for this species worldwide, sap flow in Jatropha curcas trees was measured continuously for a 17-month period at two sites in eastern South Africa. These consisted of young (4-year-old) trees at a relatively wet site and mature (12-year-old) trees at a dry site. The heat-ratio method of the heat-pulse technique was utilised, together with measurements of meteorological variables and soil water. Sap- flow rates varied according to tree age, season, prevailing meteorological conditions, and soil moisture levels. Peak sap-flow rates occurred during the warm wet summer months, but due to the deciduous nature of the species, water use was negligible during winter. Scaled-up sap-flow measurements resulted in estimates of total annual transpiration of 1 983 l (147 mm) for a 4-year-old J. curcas tree, and 4 884 l (362 mm) for a 12-year-old J. curcas tree. The study concluded that the J. curcas trees studied were conservative in their water use, and were unlikely to transpire more water than indigenous vegetation types of the area.

Challenges for creating a site-specific groundwater-use record for the Ozark Plateaus aquifer system (central USA) from 1900 to 2010

Hydrologic budgets to determine groundwater availability are important tools for water-resource managers. One challenging component for developing hydrologic budgets is quantifying water use through time because historical and site-specific water-use data can be sparse or poorly documented. This research developed a groundwater-use record for the Ozark Plateaus aquifer system (central USA) from 1900 to 2010 that related county-level aggregated water-use data to site-specific well locations and aquifer units. A simple population-based linear model, constrained to 0 million liters per day in 1900, provided the best means to extrapolate groundwater-withdrawal rates pre-1950s when there was a paucity of water-use data. To disaggregate county-level data to individual wells across a regional aquifer system, a programmatic hierarchical process was developed, based on the level of confidence that a well pumped groundwater for a specific use during a specific year. Statistical models tested on a subset of the best-available site-specific water-use data provided a mechanism to bracket historic groundwater use, such that groundwater-withdrawal rates ranged, on average, plus or minus 38% from modeled values. Groundwater withdrawn for public supply and domestic use accounted for between 48 and 74% of total groundwater use since 1901, highlighting that groundwater provides an important drinking-water resource. The compilation, analysis, and spatial and temporal extrapolation of water-use data remain a challenging task for water scientists, but is of paramount importance to better quantify groundwater use and availability.

Water Conservation Potential of Smart Irrigation Technologies in the Catawba-Wateree River Basin

AbstractA 3-year study was conducted in the Catawba-Wateree River Basin during the spring and summer months of 2009–2011 to evaluate the water savings potential of three smart irrigation controllers compared with standard timer-based irrigation controllers. Thirty-six residential sites, 12 on each of three Duke Energy lakes (Lake Norman, Lake Hickory, and Lake Wylie), were selected for the study. Each site had an automated, underground irrigation system that directly drew water from the Duke Energy lake that the property bordered. None of the systems had previously been metered and there was no charge to homeowners for withdrawing water from the bordering lake. All sites were instrumented with water meters in 2009 to monitor irrigation water withdrawals, and irrigation system audits were performed before installation of smart technologies. After collecting baseline water-use data in 2009, existing controllers were replaced with one of three smart controllers at 27 of the study sites in 2010, and irrigatio...

Groundwater vulnerability on small islands

Aquifer characteristics and water use data for 43 widely distributed small island states indicate that 44% are in a state of water stress. While recharge is projected to increase on 12 islands it is projected to decrease by up to 58% on the other 31. The majority of naturally occurring freshwater on small islands is groundwater, which is primarily recharged by precipitation1. Recharge rates are therefore likely to be impacted by climate change2. Freshwater resources on small islands are particularly vulnerable to climate change because they are limited in size and easily compromised3,4,5. Here we have compiled available aquifer system characteristics and water-use data for 43 small island developing states distributed worldwide, based on local expert knowledge, publications and regional data sets. Current vulnerability was assessed by evaluating the recharge volume per capita. For future vulnerability, climate change projections were used to estimate changes in aquifer recharge. We find that 44% of islands are in a state of water stress, and while recharge is projected to increase by as much as 117% on 12 islands situated in the western Pacific and Indian Ocean, recharge is projected to decrease by up to 58% on the remaining 31 islands. Of great concern is the lack of enacted groundwater protection legislation for many of the small island developing states identified as highly vulnerable to current and future conditions. Recharge indicators, shown alongside the state of legal groundwater protections, provide a global picture of groundwater supply vulnerability under current and future climate change conditions.

Residential outdoor water use in one East Texas community

Municipalities continue to implement efforts to encourage water conservation among residents. Landscape irrigation has been central to many of those conservation efforts. Reference evapotranspiration data is a tool that can be used in determining the appropriate amount of water to apply to amenity landscapes. Monthly water-use data for 3 years was examined in 1 neighborhood in Huntsville, Texas. The irrigated area for 1,229 residents was calculated and used to determine the depth of monthly irrigation for each residence. Replacement of 100% of local reference evapotranspiration data, minus rainfall, was used as a determinant of how much water to apply to the landscape each month for 3 years. Potential over-irrigation for each month was then compiled. Data expressed that over-irrigation was occurring among 99.51% of residents, of which 12% of these residents over-irrigated by at least 100,000 gallons in at least 1 month during the 36 month study. In 2011, the entire neighborhood of study over-irrigated by 21.2 million gallons. Outdoor water use accounted for 64% of the total water use by households. Average indoor water usage was 4,302 gallons per month. Based on the data overall, greater conservation efforts in landscape irrigation are crucial for Texas residents if water demands are to be met in the 21st century. Citation: Pannkuk TR, Wolfskill LA. 2015. Residential outdoor water use in one East Texas community. Texas Water Journal. 6(1):79-85. Available from: https://doi.org/10.21423/twj.v6i1.7009.

Land-use impacts on water resources and protected areas: applications of state-and-transition simulation modeling of future scenarios

Human land use will increasingly contribute to habitat loss and water shortages in California, given future population projections and associated land-use demand. Understanding how land-use change may impact future water use and where existing protected areas may be threatened by land-use conversion will be important if effective, sustainable management approaches are to be implemented. We used a state-and-transition simulation modeling (STSM) framework to simulate spatially-explicit (1 km 2 ) historical (1992-2010) and future (2011-2060) land-use change for 52 California counties within Mediterranean California ecoregions. Historical land use and land cover (LULC) change estimates were derived from the Farmland Mapping and Monitoring Program dataset and attributed with county-level agricultural water-use data from the California Department of Water Resources. Five future alternative land-use scenarios were developed and modeled using the historical land-use change estimates and land-use projections based on the Intergovernmental Panel on Climate Change's Special Report on Emission Scenarios A2 and B1 scenarios. Spatial land-use transition outputs across scenarios were combined to reveal scenario agreement and a land conversion threat index was developed to evaluate vulnerability of existing protected areas to proximal land conversion. By 2060, highest LULC conversion threats were projected to impact nearly 10,500 km 2 of land area within 10 km of a protected area boundary and over 18,000 km 2 of land area within essential habitat connectivity areas. Agricultural water use declined across all scenarios perpetuating historical drought-related land use from 2008-2010 and trends of annual cropland conversion into perennial woody crops. STSM is useful in analyzing land-use related impacts on water resource use as well as potential threats to existing protected land. Exploring a range of alternative, yet plausible, LULC change impacts will help to better inform resource management and mitigation strategies.