Discussion of "Average annual fulfillment of instream uses" by R. L. Smith and W. J. Carswell, Jr. (October, 1984, Vol. 110, No. 4)

Robert T. Milhous

doi:10.1061/(asce)0733-9496(1987)113:3(443.2)

Home/Archive/USGS

USGS · 70121478

Discussion of "Average annual fulfillment of instream uses" by R. L. Smith and W. J. Carswell, Jr. (October, 1984, Vol. 110, No. 4)

Robert T. Milhous

View original source ↗Export metadata ↓

Abstract

No abstract available.

Explore related subjects

Journal of Water Resources Planning and Management Article

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Robert T. Milhous. 1987. Discussion of "Average annual fulfillment of instream uses" by R. L. Smith and W. J. Carswell, Jr. (October, 1984, Vol. 110, No. 4). https://doi.org/10.1061/(asce)0733-9496(1987)113%3A3(443.2)

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

USGS2026

Multireservoir allocation framework considering societal and ecological needs in a time-frequency domain

Existing reservoir management frameworks traditionally consider historical (predam) flow conditions to deliver environmental flows. Such frameworks may not be feasible because current demand and/or climate could be different from predam conditions. Hence, we developed a multireservoir framework that explicitly considers both human water demands and environmental flow requirements to minimize deviations under current hydroclimatic conditions and demand patterns. The multireservoir framework, Generalized Reservoir Analyses using Probabilistic Streamflow (GRAPS), was modified and implemented to solve the problem of minimizing the flow deviations using feasible sequential quadratic programming for three reservoirs in the Chattahoochee River Basin, Southeastern United States, which is known for its imperiled native biodiversity and productive estuarine ecosystem. Our results show that downstream reservoirs in the cascade system are less influenced by upstream reservoirs’ regulation because the downstream reservoirs receive a significant amount of natural flows. By comparing the average wavelet power spectrum at different periodicities between natural flows and downstream releases, we found that the current release policy and modified releases resulted in highly altered flows under shorter periodicities (e.g., less than 2 months) but synchronized flow variance between natural flow and downstream releases at longer periodicities (e.g., greater than 3 years). This framework of linking the multireservoir allocation model through the time–frequency analysis using wavelet power spectrum could not only advance sustainable water management policies to meet water for human and environmental needs but can also add additional value in meeting the downstream environmental demand at desired periodicities.

Alabama, Florida, Georgia↗

USGS2020

The next frontier: Making research more reproducible

Science and engineering rest on the concept of reproducibility. An important question for any study is: are the results reproducible? Can the results be recreated independently by other researchers or professionals? Research results need to be independently reproduced and validated before they are accepted as fact or theory. Across numerous fields like psychology, computer systems, and water resources there are problems to reproduce research results (Aarts et al. 2015; Collberg et al. 2014; Hutton et al. 2016; Stagge et al. 2019; Stodden et al. 2018). This editorial examines the challenges to reproduce research results and suggests community practices to overcome these challenges. Coordination is needed among the authors, journals, funders and institutions that produce, publish, and report research. Making research more reproducible will allow researchers, professionals, and students to more quickly understand and apply research in follow-on efforts and advance the field.

Journal of Water Resources Planning and Management↗

USGS2017

Stochastic programming with a joint chance constraint model for reservoir refill operation considering flood risk

Reservoir refill operation modeling attempts to maximize a set of benefits while minimizing risks. The benefits and risks can be in opposition to each other, such as having enough water for hydropower generation while leaving enough room for flood protection. In addition to multiple objects, the uncertainty of streamflow can make decision making difficult. This paper develops a stochastic optimization model for reservoir refill operation with the objective of maximizing the expected synthesized energy production for a cascade system of hydropower stations while considering flood risk. Streamflow uncertainty is addressed by discretized streamflow scenarios and flood risk is controlled by a joint chance constraint restricting the occurrence probability. With the variability of flood risk level, two advancing refill scenarios for exploring operation benefit are presented. Scenario I loosens the current stagewise storage bounds conditions and allows advancing reservoir refills but keeps the flood risk level the same as the refill policies obtained under the current storage bounds. Scenario II keeps the current storage bounds unchanged but allows increases in flood risk level. The proposed methodology is applied to the Xiluodu cascade system of reservoirs in China and investigates the optimal refill policies obtained by both scenarios. Compared with the benchmark obtained under the current storage bounds and lowest flood risk level, the results show (1) the synthesized energy production can be improved by 2.13% without changing the flood risk level under Scenario I, and (2) the synthesized energy production can also be increased by 0.21% at the expense of increasing the flood risk level by 4.4% when Scenario II is employed. As Scenario I produces higher benefit and lower risk than Scenario II, it is recommended to loosen the current stagewise storage bounds but to keep the flood risk level unchanged during refill operations.

Xiluodu Cascade Reservoir↗