Journal of Water Resources Planning and Management

Incorporating microhydropower (MHP) turbines within water supply networks has the potential to improve the economic and environmental sustainability of the sector. However, long-term flow and head variations in water networks are key risk factors that increase turbine performance uncertainty in the medium-to-long term, potentially impacting the investment payback period. Using high-resolution historical flow and head data across a number of pressure reducing valve sites in water networks in Ireland, this study presents an assessment of the impact of flow and head variations on turbine efficiency and power output over a 20-year period. Results indicated that pumps-as-turbines (PATs) represent a viable low-cost option over the long term at sites with smaller power output potential. Where flow and head rates displayed considerable fluctuation, the integration of a two-PAT configuration could improve operating efficiency and maximize power output. This design strategy opens up the opportunity to conduct energy recovery from sites that may previously have been considered unsuitable for MHP.

Despite mounting demand for a more sustainable worldwide water supply system, available reservoir capacity is relentlessly diminishing due to sedimentation. Neither sustainable reservoir life spans nor intergenerational equity is achieved through conventional cost-benefit analyses (CBAs), which render all benefits and costs projected to occur more than several decades into a project as negligible. Consequently, future costs, including dam decommissioning or retrofitting with sediment management facilities, would be regarded as nonfactors in an analysis. CBAs have also historically failed to account for infrastructure and environmental impacts of sedimentation over time. Alternatives to the traditional application of the CBA do exist, however, such as dam owners instituting retirement funds or insurance policies, beneficiaries paying for rehabilitation or maintenance, and economists incorporating infrastructure damages and potentially logistic discount rates into their analyses. A brief case study of Gavins Point Dam shows that available information on damages due to a lack of sediment management account for 70% of the actual construction cost and would likely exceed construction costs if all damage information were available. By integrating these alternatives, economic analyses for reservoirs will be more accurate, reservoir life spans will be more sustainable, profits will be extended indefinitely, and the economic burdens placed on future generations will be lessened.

Climate change is expected to alter the frequency and intensity of extreme rainfall events, affecting the rainfall intensity-duration-frequency (IDF) curve information used in the design, maintenance, and operation of water infrastructure in Canada. Presented in this study are analyses of precipitation data from 567 Environment Canada hydro-meteorological stations using the web-based IDF_CC tool, which applies a novel equidistance quantile-matching downscaling method to generate future IDF curve information. Results for the year 2100 based on The Second Generation Canadian Earth System Model (CanESM2) and a multimodel ensemble median of 24 global climate models (GCMs) were generated. A natural neighbor spatial interpolation method was used to generate results for ungauged locations. One in 5-year, 2-h and one in 100-year, 24-h precipitation events were explored. Results based on CanESM2 indicated a reduction in extreme precipitation in central regions of Canada under specific analyses and increases in other regions. Relative to the multimodel ensemble median approach, the CanESM2 results suggested more spatial variability in change of IDFs, and the ensemble median generated generally lower values than CanESM2. By using the median value that lowers the importance of extreme outputs, the ensemble median approach obscured uncertainty associated with GCM outputs. While the IDF_CC tool helps fill an important gap related to accessing local climate change information, it is important to consider uncertainty in GCM outputs when making climate change adaptation decisions.

The practical reservoir flood season segmentation is crucial to dynamically adjusting the flood-limiting water level in flood seasons. An ensemble method structure (EMS) was designed to screen out the most suitable method structure for segmenting flood season. The performance of the proposed EMS approach was evaluated in a case study in Chengbihe Reservoir, China. The results indicate that the method structures containing flood volume series sampled by using the peaks-over-threshold (POT) technique outperform the other method structures. To further explore the impacts of the flood volume index and the POT sampling technique on segmentations, the 1-, 3-, and 5-day flood volume series sampled by using the POT1, POT2, and POT3 techniques, respectively, were used to segment the flood season by using the method of directional statistics. The main findings are as follows: (1) the segmentation is most sensitive to the selected indices, sensitive to the sampling techniques, and least sensitive to the segmentation methods; and (2) the variance of the segmentations increases with the amount of flood data used in segmenting flood season. Thus, the segmentations of the flood season in the Chengbihe Reservoir can be obtained by averaging the dates obtained with the latter constructed method structures. The case study demonstrates that the proposed EMS approach can be an effective tool for flood season segmentation.

The combined actions of natural and human factors change the timing and availability of water resources and, correspondingly, water demand in metropolitan areas. This leads to an imbalance between supply and demand and, thus, an increase in the vulnerability of water supply systems. Accordingly, methods for systematic analysis and multifactor assessment are needed to estimate the vulnerability of individual components in an integrated water supply system. This paper introduces a new approach to comprehensively assess vulnerability by integrating water resource system characteristics with factors representing exposure, sensitivity, severity, potential severity, social vulnerability, and adaptive capacity. These factors provide a way to consider broader system elements beyond the traditional vulnerability evaluation methods solely on the basis of the magnitude of failure (i.e., severity). In this way, the new vulnerability index gives a more detailed assessment with the potential to recognize critical conditions and components in an integrated system. The effectiveness and advantages of the proposed approach are checked using an investigation of the water supply system of Salt Lake City (SLC), Utah. First, an integrated water resource model was developed using a system simulation software to allocate water from different sources in SLC among designated demand points. The model contains individual simulation modules with representative interconnections among the natural hydroclimate system, built water infrastructure, and institutional decision making. The results of the analysis illustrate that basing vulnerability on a sole factor may lead to insufficient understanding and, hence, inefficient management of the system. For example, ranking of different water sources on the basis of the traditional vulnerability index (i.e., severity) in SLC is not consistent with the ranking on the basis of the proposed integrated vulnerability index. Therefore, during a failure event in the system, such as a water shortage, incomplete understanding of the system’s performance may lead to incorrect decisions by managers. The new vulnerability index and assessment approach was able to identify the most vulnerable water sources in the SLC integrated water supply system. In conclusion, use of a more comprehensive approach to simulate the system behavior and estimate vulnerability provides more guidance for decision makers to detect vulnerable components of the system and ameliorate decision making.

The exponential increase in groundwater usage over the past few decades in the Punjab province in Pakistan is responsible for the significant groundwater table decline in many parts of the province, leading to an urgent need for policy measures to better manage groundwater use. A better understanding of the underground water balance is necessary for drafting informed groundwater management plans. With limited data, this study develops the first physically-based groundwater model for the entire Punjab province. Using the calibrated provincewide model, simulations are performed to evaluate groundwater dynamics in the future under different scenarios. These scenarios comprise controls on groundwater pumping, canal infrastructure improvements, and precipitation changes. The impacts of these scenarios are highlighted with the mapping of changes in water table, pumping cost, and waterlogged area. The results show that changes in both groundwater abstraction and seepage from the canal system into the aquifer significantly impact groundwater heads, whereas the effect of changing precipitation is negligible. Under status quo conditions, the average provincewide pumping cost is projected to increase by 270% in 23 years. The findings emphasize the heterogeneity in groundwater conditions across Punjab and highlight the need for region-specific management of groundwater resources.