Water Resources and Economics最新文献

With the increasing conflict between the supply and demand of water resources, enhancing water resource use efficiency has gradually become a focus of attention. As a new way to manage water resources, water rights trading pilots have been implemented in China. It is important to explore the impact of water rights trading on regional water resource use efficiency and possible impact paths. This paper employs a global nonradial directional distance function (GNDDF) model to measure water resource use efficiency, which is more accurate and reliable. To discern the effect of China's water rights trading pilot policy on enhancing regional water resource use efficiency, we apply the regression control method (RCM) for counterfactual analysis and test the possible pathways through which the water rights trading policy affects water resource use efficiency. This article draws the following conclusions. (i) China's overall water resource use efficiency has not reached a high level over the past decade, and water resource use efficiency has exhibited substantial regional disparities. (ii) There is some evidence to suggest that the water rights trading policy may have a positive impact on improving water resource use efficiency in the pilot provinces. However, the improvement effect exhibits regional variations, which are likely attributed to the initial water resource use levels in the pilot provinces and the specific implementation modes of water rights trading. (iii) Water rights trading policies can enhance water resource use efficiency through two pathways, including facilitating reclaimed water reuse and promoting water use restructuring.

Adapting to changes in water availability is becoming an increasingly important environmental management objective in many regions around the world. One way for cities to conserve water is to enhance drought-resistant vegetation cover. This revegetation practice can take place on many types of land, including road-side verges (also known as nature strips or boulevards), which, in Western Australia, are publicly owned but managed privately by residents of adjoining properties. As preferences for alternative verge groundcovers are not well understood, designing solutions that help achieve environmental goals and satisfy communities is a challenge. We survey community members in Perth, Western Australia, and find that peoples’ preferences for verge landscape design are largely bimodal, and can be classified under two dominant groups of people: those who prefer native vegetation, which requires little irrigation, and those who prefer watered grass. Neighbourhood norms prevail in their rankings, where individuals whose neighbours have planted water-conserving native vegetation gardens on their verges are also more likely to prefer ecological landscape designs. Increasing the extent of gardens that feature water-conserving native plants in high-profile public areas may further increase community acceptance of low water-use groundcovers, and may assist in driving changes in landscape management practices towards having more ecological landscape designs on verges, and beyond.

California's demand-side urban water management policies, such as shifting water pricing structures from non-conservation to conservation-based rates, have received much attention in terms of meeting the state's short- and long-term water conservation policies. This paper quantifies the effect of pricing structure changes on residential water consumption using a survey dataset of 189 major California water utilities from 1994 to 2019. Results of our study demonstrate that residential per capita per day water consumption was reduced by an average of 2.6% when water agencies switched from non-conservation-based to conservation-based pricing structures. We also found evidence that the longer a utility maintained a non-conservation-based rate structure before switching to conservation-based pricing, the larger the water consumption reduction in that utility's service area. In addition, utilities that reverted to non-conservation rates after having longer-term conservation pricing structures experienced smaller increases compared to having long-term non-conservation ones in water use in their service areas. This suggests evidence of a crowding-in effect for transitions from conservation-based to non-conservation-based pricing structures.

Pumped denitrification bioreactors are currently being assessed in the field to extend the use of traditional, subsurface drainage bioreactors. Pumped bioreactors for the treatment of drainage ditches, surface waters, and cisterns intercepting drainage were evaluated to provide a basis of the unit cost of bioreactor operation ($ kg NO₃–N removed⁻¹) under a variety of scenarios. The unit costs were modeled using a techno-economic analysis. The variables assessed in the analysis included nitrate removal rate, bioreactor lifespan, and operating periods, which were assumed. To evaluate the impact of these variables on the unit cost, a sensitivity analysis was conducted where one variable was adjusted (e.g., lifespan) while the other variables were kept the same as a traditional bioreactor. The cistern and supplemental surface water bioreactors were larger in size and had similar unit costs ranging from ∼$5 to $27 kg NO₃–N removed⁻¹ for all scenarios except for the low mass removal and worst-case scenarios. The smaller, ditch diversion bioreactor had unit costs in the best- and worst-case scenarios in the range of $24 to $619 kg NO₃–N removed⁻¹, respectively. A breakeven analysis indicated increasing the mass removal rate of the bioreactors and ensuring an operating period greater than 6-months had the greatest impact on reducing the unit cost compared to a traditional bioreactor. Overall, the larger-scale surface water and cistern bioreactors had comparable, but slightly higher, unit costs than traditional bioreactors under most scenarios evaluated. This information can be used to optimize and inform of the potential of pumped bioreactor systems.

There is an increasing focus on improving environmental health in major river catchments to address pressures from extensive modification and overuse. However, river catchments often involve many complex and competing uses, making it difficult to prioritise where remediation actions should be concentrated. In this research, the Best Worst Scaling (BWS) technique is applied to assess community views about the relative importance of multiple major issues in the Murray Darling Basin that span environmental, social, economic, and cultural dimensions. The BWS technique was applied by identifying 16 major issues relevant to river management, generating a statement for each, and then using an experimental design to create profiles with four statements each. A random sample of respondents across New South Wales were each presented with four profiles and asked to identify the statement that they agreed with most and least for each profile. The results, analysed through both counting and logistic regression methods, show that the community prioritized environmental issues over economic, social, and cultural aspects. Improved water quality, native animals, water flow management and fish populations were identified as greater priority issues with both the logit model and counting model approaches. The analysis demonstrates how application of the logit model generates greater insights than is available with the counting approach.

This paper estimates the economic benefits of restoring the Waukegan Harbor Area of Concern (AOC) along the shore of Lake Michigan in Waukegan, Illinois. Legacy pollutants left from industrial activities are a threat to human and wildlife health and limit commercial and recreational activities in the harbor. The AOC has undergone substantial remediation since its designation in 1987. We estimate the economic benefits of restoring the AOC using a hedonic analysis of home sales around the harbor before and after several remediation events. We find that home prices within 5 km (3 miles) increased $12,832 on average, with aggregate benefits of $169 million, after the most recent restoration announcement in 2020.

Hotter, drier summers and population growth are causing water management challenges for water authorities in New Zealand. Effective long-term planning requires understanding the dynamics of household responses to demand management and climate variables. This paper analyses a large dataset of household-level demand data over nine years. Dynamic panel time series models are used to estimate short and long-term elasticities, interactions between demand management and climate variables, and associations with property characteristics. The general belief is that water demand becomes more sensitive to price changes over the long term compared to the short term. Yet, previous studies that directly compared long and short-run elasticities had limitations, as they imposed a constraint on the long-run estimate, assuming it to be larger. The models presented in this paper are more flexible and can identify the opposite scenario should it be present. We find long-run price elasticity may not be larger for new high-value properties or high-value properties with small gardens. Low-value properties have smaller short-run and larger long-run price elasticity. High-value properties respond more to outdoor restrictions and associated conservation messages than low-value properties. We discuss the policy implications of these findings.

A system of demand for inputs and productive factors is estimated to calculate the elasticities of substitution and the own-price elasticity of industrial water demand in Chile. A previous study used the Annual National Industrial Survey (ENIA) panel (1995–2014) to estimate the value of water and own-price elasticity through a translog production function. However, that database does not report the industrial firms' location to protect the informants’ statistical secrecy. In contrast, in this study, the survey ENIA 2018 is chosen since it includes the region where each firm is located, which allows for evaluating the endogeneity of the water price variable and using three instrumental variables related to the water supply. In addition, the performance of non-linear regression methods with constraints is evaluated to ensure that the estimated coefficients meet the conditions imposed by economic theory. The results show that the elasticity of industrial water demand is unitary but not statistically significant in most subsectors. The water demand in the wood and paper industry subsector is elastic (−2.2) and statistically significant. On the other hand, the elasticities of substitution obtained adopt values very low, indicating that water is an essential resource that is difficult to replace by other inputs or productive factors.

The impact of COVID-19 on water-related equity indices is analyzed in this paper for different regions around the world by using fractionally integrated methods and an artificial neural network model. Using fractional integration, a lack of mean reversion is observed in all cases except in the USA, which means that, for these regions, a change in the trend will be permanent after COVID-19 unless additional measures are implemented. At the same time, a structural break is observed in all cases between the 4th and March 10, 2020, likely due to the drastic lockdown imposed in many if not most countries. Long memory was tested for the post-break period and mean reversion was found not only in North America but also in Europe. Moreover, the results were strongly aligned with those obtained using the neural network model. This suggests that the water-related equity indices and associated levels of investments in water and related utilities have moved back to their pre-Covid-19 levels.

Water scarcity is an issue that affects the life on earth. Technological advancements, such as IoT water meters, are proven to be effective when it comes to household water reduction. However, there is a lack of research on what influences consumer to apply such devices in their households. This research aims to investigate predictors of the intention to apply smart water meters by extending the Technology of Acceptance Model; hypothesizing that intention to apply IoT water meters is predicted by attitude towards them, which, is determined by perceived usefulness and ease of IoT water meter use. To extend the model frugality, personal innovativeness and environmental concerns were added as moderators of the relationship between perceived ease of use and usefulness as well as attitudes towards IoT water meters. Afterwards, a survey was constructed, and data were collected from 657 participants. The results supported the hypotheses. Intention to adopt water meters was determined by attitude, which was predicted by perceived ease of use and perceived usefulness of IoT water meters. Regarding the moderators, environmental concern was found to be the only variable moderating the influence between perceived ease of use and perceived usefulness on attitudes towards IoT water meters.