Assessing Reservoir Performance under Nonstationary Conditions Induced by Climate Change: Application to Pozzillo Reservoir, Italy

2020 ◽  
Author(s):  
David J. Peres ◽  
Rosario Modica ◽  
Antonino Cancelliere
Keyword(s):  
Climate Change ◽  
Reservoir Performance ◽  
Nonstationary Conditions

scholarly journals A Trade-Off Analysis of Adaptive and Non-Adaptive Future Optimized Rule Curves Based on Simulation Algorithm

2021 ◽  
Author(s):  
Mahnoosh Moghaddasi ◽  
Sedigheh Anvari ◽  
Najmeh Akhondi
Keyword(s):  
Climate Change ◽  
Water Shortage ◽  
Vulnerability Index ◽  
Adaptation To Climate Change ◽  
Reservoir Performance ◽  
Static Hedging ◽  
Rule Curve ◽  
Hedging Rules ◽  
Future Data ◽  
Adaptive Policies

Abstract This study aims to investigate the performance of Zarrineh Rud reservoir by implementing strategies for adaptation to climate change. Using sequent peak algorithm (SPA), the rule curve were simulated. Then, the optimal rule curve was procured through GA-SPA, aiming to minimize the water shortage. The future data were downscaled using SDSM based on CanEsm2 model and under RCP2.6 and RCP8.5. Finally, in view of environmental demand, reservoir performance indices were calculated for both non-adaptive and adaptive policies during all future periods (2020–2076). Results showed simulation with the static hedging rules managed to significantly reduce the average vulnerability index (by 60%) compared to no hedging, while the dynamic hedging rules outperformed static hedging rules only by 9%. Therefore, considering the insignificant improvement in reservoir performance using dynamic rules and their complexity, static hedging rules are recommended as the better option for adaptation during climate change.

scholarly journals Developing hydrological and reservoir models under deep uncertainty of climate change: robustness of water supply reservoir

2019 ◽  
Vol 19 (8) ◽  
pp. 2222-2230
Author(s):  
Daniel Marton ◽  
Kateřina Knoppová
Keyword(s):  
Climate Change ◽  
Storage Capacity ◽  
Management Strategies ◽  
Simulation Models ◽  
Mean Flow ◽  
Deep Uncertainty ◽  
Reservoir Storage ◽  
Reservoir Performance ◽  
Climate Change Uncertainty

Abstract Adaptation of water resources to climate change, drought management strategies, and hydrological and reservoir modelling have become serious issues in the context of climate change uncertainty. The aim of this paper is to introduce methods and tools for hydrological analysis and robust reservoir performance evaluation in this time of deep uncertainty. Newly developed lumped water balance and reservoir simulation models will be used to perform hydrological analysis, and a robust reservoir storage capacity reliability assessment will also be conducted. The hydrological data in relation to climate change will be constructed using two climatological datasets created by statistical downscaling tools LARS WG and ENSEMBLE Downscaling Portal. The hydrological analysis and the temporal reliability of the assessment of reservoir storage capacity and robustness in the context of climate change uncertainty will be presented as a case study of the Vir I reservoir and the Svratka River basin in the Czech Republic, in central Europe. The resulting models show a decrease in long-term mean flow, ranging from 6% to 32%, and in reservoir outflow from 1.5% to 26%, depending on the timescale, downscaling tools and emission scenarios.

scholarly journals A Hybrid Model-Based Adaptive Framework for the Analysis of Climate Change Impact on Reservoir Performance

2020 ◽  
Vol 34 (13) ◽  
pp. 4053-4066
Author(s):  
P. Biglarbeigi ◽  
W. A. Strong ◽  
D. Finlay ◽  
R. McDermott ◽  
P. Griffiths
Keyword(s):  
Climate Change ◽  
Water Resource Management ◽  
Supplementary Information ◽  
Reservoir Performance ◽  
Reservoir System ◽  
Future Performance ◽  
Failure State ◽  
Storage Reservoirs ◽  
Model Reliability ◽  
Satisfactory State

Abstract Climate change and population growth have influenced social and physical water scarcity in many regions. Accordingly, the future performance of water storage reservoirs, as one of the fundamental elements in the water resource management, are anticipated to be affected by climate change. This study reports on a framework that can model Reliability-Resiliency-Vulnerability (RRV) measures of water reservoirs in the context of climate change. The framework first develops a hydrological model of a reservoir system using its historical data. The model is then optimised to minimise the water deficit and flooding around the catchment area of the reservoir. The resulting optimal policies are simulated back to the model considering the GCMs. Finally, RRV indices are calculated. RRV indices are effective measures for defining the performance of reservoir systems. Reliability is defined as the probability of the failure of the system, Resiliency is defined as the time needed for the system to go back to its satisfactory state once it entered the failure state, and Vulnerability is defined as the “magnitude of the failure” of a system. The proposed framework has been applied to a reservoir system located in the south-west of Iran on the Dez river. The results show climate change may increase the reliability and resiliency of the system under study while increasing its vulnerability. Therefore, the output of this framework can also provide supplementary information to authorities and decision-makers to inform future water management and planning policies.

Averting robo-bees: why free-flying robotic bees are a bad idea

2019 ◽  
Vol 3 (6) ◽  
pp. 723-729
Author(s):  
Roslyn Gleadow ◽  
Jim Hanan ◽  
Alan Dorin
Keyword(s):  
Climate Change ◽  
Computer Simulation ◽  
Food Security ◽  
European Countries ◽  
Plant Interactions ◽  
Plant Insect Interactions ◽  
Native Habitat ◽  
Insect Pollinators ◽  
Insect Interactions

Food security and the sustainability of native ecosystems depends on plant-insect interactions in countless ways. Recently reported rapid and immense declines in insect numbers due to climate change, the use of pesticides and herbicides, the introduction of agricultural monocultures, and the destruction of insect native habitat, are all potential contributors to this grave situation. Some researchers are working towards a future where natural insect pollinators might be replaced with free-flying robotic bees, an ecologically problematic proposal. We argue instead that creating environments that are friendly to bees and exploring the use of other species for pollination and bio-control, particularly in non-European countries, are more ecologically sound approaches. The computer simulation of insect-plant interactions is a far more measured application of technology that may assist in managing, or averting, ‘Insect Armageddon' from both practical and ethical viewpoints.

Modelling ecosystem adaptation and dangerous rates of global warming

2019 ◽  
Vol 3 (2) ◽  
pp. 221-231 ◽  
Author(s):  
Rebecca Millington ◽  
Peter M. Cox ◽  
Jonathan R. Moore ◽  
Gabriel Yvon-Durocher
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Diffusion Rate ◽  
Individual Species ◽  
Genetic Evolution ◽  
Rates Of Change ◽  
Rapid Climate Change ◽  
Warming Climate ◽  
Intraspecies Competition ◽  
High Trait

Abstract We are in a period of relatively rapid climate change. This poses challenges for individual species and threatens the ecosystem services that humanity relies upon. Temperature is a key stressor. In a warming climate, individual organisms may be able to shift their thermal optima through phenotypic plasticity. However, such plasticity is unlikely to be sufficient over the coming centuries. Resilience to warming will also depend on how fast the distribution of traits that define a species can adapt through other methods, in particular through redistribution of the abundance of variants within the population and through genetic evolution. In this paper, we use a simple theoretical ‘trait diffusion’ model to explore how the resilience of a given species to climate change depends on the initial trait diversity (biodiversity), the trait diffusion rate (mutation rate), and the lifetime of the organism. We estimate theoretical dangerous rates of continuous global warming that would exceed the ability of a species to adapt through trait diffusion, and therefore lead to a collapse in the overall productivity of the species. As the rate of adaptation through intraspecies competition and genetic evolution decreases with species lifetime, we find critical rates of change that also depend fundamentally on lifetime. Dangerous rates of warming vary from 1°C per lifetime (at low trait diffusion rate) to 8°C per lifetime (at high trait diffusion rate). We conclude that rapid climate change is liable to favour short-lived organisms (e.g. microbes) rather than longer-lived organisms (e.g. trees).

Climate change and breeding success: decline of the capercaillie in Scotland

2001 ◽  
Vol 70 (1) ◽  
pp. 47-61 ◽  
Author(s):  
Robert Moss ◽  
James Oswald ◽  
David Baines
Keyword(s):  
Climate Change ◽  
Breeding Success
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