A forecast-informed reservoir operation framework incorporating climate indices

2020 ◽  
Author(s):  
Guang Yang ◽  
Paul Block
Keyword(s):  
Decision Making ◽  
Reservoir Operation ◽  
Large Scale ◽  
Classification Model ◽  
Climate Index ◽  
Climate Indices ◽  
Reservoir Operations ◽  
Operating Rules ◽  
Dry Conditions ◽  
Index Value

<p>Incorporating streamflow forecasts into reservoir management can often lead to improved operational efficiency. Large-scale climate variables and indices – in addition to local hydrologic variables – may also provide valuable information for reservoir operations given their limitate relationship with streamflow. A new tree-based machine learning approach for updating reservoir operating rules conditioned on large-scale climate indices is proposed by selecting the most suitable reservoir decision-making pattern for each year. Multiple types of reservoir operating rules can be extracted from the historical streamflow data with different hydrological (e.g., wet and dry) conditions. Their performance can be recorded and correlated with climate indices by using a decision-tree classification model, and then the rules with the best performance conditioned on a given climate index value can be selected for reservoir operations. A case study of reservoir operations for the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile River demonstrates that the proposed tree-based reservoir operation framework can accurately select suitable decision-making rules both for normal and forecast-informed reservoir operations. Notably, incorporating May Nino 4.0 values into GERD reservoir operations can increase power generation during flood seasons, especially in extreme years.</p>

scholarly journals Transboundary water sharing policies conditioned on hydrologic variability to inform reservoir operations

2021 ◽  
Author(s):  
Guang Yang ◽  
Paul Block
Keyword(s):  
Water Resources ◽  
Reservoir Operation ◽  
Large Scale ◽  
Policy Framework ◽  
Transboundary Water ◽  
Reservoir Operations ◽  
Water Sharing ◽  
Transboundary Water Resources ◽  
Operating Rules ◽  
Hydrologic Variability

Abstract. Water resources infrastructure is critical for energy and food security, however, the development of large-scale infrastructure, such as hydropower dams, may significantly alter downstream flows, potentially leading to water resources management conflicts and disputes, especially in transboundary river basins. Mutually agreed upon water sharing policies for the operation of existing or new reservoirs is one of the most effective strategies to mitigate conflict, yet this is a complex task involving the estimation of available water, identification of users and demands, procedures for water sharing, etc. We propose a water-sharing policy framework that incorporates reservoir operating rules optimization based on conflicting uses and natural hydrologic variability, specifically tailored to drought conditions. We first establish the trade-off between downstream and upstream water availability utilizing multi-objective optimization of reservoir operating rules. Next, we simulate reservoir operation with the candidate (optimal) rules, evaluate their performance, and select the most suitable rules for balancing water uses. Subsequently, we build a relationship between the reservoir operations simulated from the selected rules and drought-specific conditions to derive water-sharing policies. Finally, we re-optimize the reservoir operating rules to evaluate the effectiveness of the drought-specific water sharing policies. We apply the framework to reservoir operation of the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile River. We find that the derived water sharing policy can balance GERD power generation and downstream releases, especially in dry conditions, effectively sharing the hydrologic risk in inflow variability among riparian countries. The proposed framework offers a robust approach to inform water sharing policies for sustainable management of transboundary water resources.

scholarly journals Water sharing policies conditioned on hydrologic variability to inform reservoir operations

2021 ◽  
Vol 25 (6) ◽  
pp. 3617-3634
Author(s):  
Guang Yang ◽  
Paul Block
Keyword(s):  
Water Resources ◽  
Large Scale ◽  
Policy Framework ◽  
Reservoir Operations ◽  
Water Sharing ◽  
Effective Strategies ◽  
Operating Rules ◽  
Hydrologic Variability ◽  
Dry Conditions ◽  
Management Conflicts

Abstract. Water resources infrastructure is critical for energy and food security; however, the development of large-scale infrastructure, such as hydropower dams, may significantly alter downstream flows, potentially leading to water resources management conflicts and disputes. Mutually agreed upon water sharing policies for the operation of existing or new reservoirs is one of the most effective strategies for mitigating conflict, yet this is a complex task involving the estimation of available water, identification of users and demands, procedures for water sharing, etc. A water sharing policy framework that incorporates reservoir operating rules optimization based on conflicting uses and natural hydrologic variability, specifically tailored to drought conditions, is proposed. First, the trade-off between downstream and upstream water availability utilizing multi-objective optimization of reservoir operating rules is established. Next, reservoir operation with the candidate (optimal) rules is simulated, followed by their performance evaluations, and the rule selections for balancing water uses. Subsequently, a relationship between the reservoir operations simulated from the selected rules and drought-specific conditions is built to derive water sharing policies. Finally, the reservoir operating rules are re-optimized to evaluate the effectiveness of the drought-specific water sharing policies. With a case study of the Grand Ethiopian Renaissance Dam (GERD) on the Blue Nile river, it is demonstrated that the derived water sharing policy can balance GERD power generation and downstream releases, especially in dry conditions, effectively sharing the hydrologic risk in inflow variability among riparian countries. The proposed framework offers a robust approach to inform water sharing policies for sustainable management of water resources.

scholarly journals Combined analysis of temperature and rainfall variability as they relate to climate indices in Northern Algeria over the 1972–2013 period

2016 ◽  
Vol 48 (2) ◽  
pp. 584-595 ◽  
Author(s):  
Ayoub Zeroual ◽  
Ali A. Assani ◽  
Mohamed Meddi
Keyword(s):  
Large Scale ◽  
Southern Oscillation ◽  
Rainfall Variability ◽  
Coastal Region ◽  
Western Mediterranean ◽  
Seasonal Rainfall ◽  
Climate Index ◽  
Climate Indices ◽  
Mean Values ◽  
Northern Algeria

Many studies have highlighted breaks in mean values of temperature and precipitation time series since the 1970s. Given that temperatures have continued to increase following that decade, the first question addressed in this study is whether other breaks in mean values have occurred since that time. The second question is to determine which climate indices influence temperature and rainfall in the coastal region of Northern Algeria. To address these two questions, we analyzed the temporal variability of temperature and annual and seasonal rainfall as they relate to four climate indices at seven coastal stations in Algeria during the 1972–2013 period using the Mann–Kendall, Lombard, and canonical correlation (CC) analysis methods.The annual and seasonal maximum, minimum and mean temperatures increased significantly over that time period. Most of these increases are gradual, implying a slow warming trend. In contrast, total annual and seasonal rainfall did not show any significant change. CC analysis revealed that annual and seasonal temperatures are negatively correlated with the Western Mediterranean Oscillation (WeMOI) climate index that characterizes atmospheric circulation over the Mediterranean basin. On the other hand, rainfall is positively correlated with a large-scale atmospheric index such as the Southern Oscillation Index.

Global within-season yield anomaly prediction for major crops derived using seasonal forecasts of large-scale climate indices and regional temperature and precipitation

2020 ◽  
Author(s):  
Toshichika Iizumi ◽  
Yuhei Takaya ◽  
Wonsik Kim ◽  
Toshiyuki Nakaegawa ◽  
Shuhei Maeda
Keyword(s):  
Large Scale ◽  
Climate Index ◽  
Climate Indices ◽  
Seasonal Forecasts ◽  
Temperature And Precipitation ◽  
Test Operation ◽  
Main Driver ◽  
Complex Models ◽  
Crop Forecasting ◽  
Operation Phase

AbstractWeather and climate variability associated with major climate modes is a main driver of interannual yield variability of commodity crops in global cropland areas. A global crop forecasting service that is currently in the test operation phase is based on temperature and precipitation forecasts, while recent literature suggests that crop forecasting services may benefit from the use of climate index forecasts. However, no consistent comparison is available on prediction skill between yield models relying on forecasts from temperature and precipitation and from climate indices. Here, we present a global assessment of 26-year (1983–2008) within-season yield anomaly hindcasts for maize, rice, wheat and soybean derived using different types of statistical yield models. One type of model utilizes temperature and precipitation for individual cropping areas (the TP model type) to represent the current service, whereas the other type relies on large-scale climate indices (the CI model). For the TP models, three specifications with different model complexities are compared. The results show that the CI model is characterized by a small reduction in the skillful area from the reanalysis model to the hindcast model and shows the largest skillful areas for rice and soybean. In the TP models, the skill of the simple model is comparable to that of the more complex models. Our findings suggest that the use of climate index forecasts for global crop forecasting services in addition to temperature and precipitation forecasts likely increases the total number of crops and countries where skillful yield anomaly prediction is feasible.

scholarly journals Stochastic multiobjective reservoir operation under imprecise objectives: multicriteria decision-making approach

2010 ◽  
Vol 13 (1) ◽  
pp. 110-120 ◽  
Author(s):  
M. Akbari ◽  
A. Afshar ◽  
S. Jamshid Mousavi
Keyword(s):  
Decision Making ◽  
Reservoir Operation ◽  
Stochastic Dynamic Programming ◽  
Multicriteria Decision Making ◽  
Stochastic Dynamic ◽  
Multicriteria Decision ◽  
Operating Rules ◽  
South West ◽  
Fuzzy State ◽  
Random Nature

Multiobjective reservoir operations are generally complex, as they are often associated with a large quantity of uncertain factors in combination with noncommensurable objectives. In this study, fuzzy-state stochastic dynamic programming (FSDP) and multicriteria decision-making (MCDM) are integrated to derive operating rules for a single multiobjective reservoir operation problem. The model addresses uncertainties due to randomness in inflows and imprecision in variables' discretization and objectives. The FSDP model takes into account uncertainties due to the random nature of inflows and imprecision due to variable discretization. Imprecise and noncommensurable objectives are quantified by a set of subjective criteria, the aggregation of which is performed through an MCDM model, by which possible decisions at every stage of the FSDP model are evaluated and compared. The proposed approach is then employed in deriving operating rules for the Karoon 1 reservoir in south-west Iran and the rules are tested and evaluated through simulation. Results show the model's capability in handling different kinds of uncertainties involved in real reservoir operation problems.

Applications of blockchain in healthcare (Preprint)

2020 ◽  
Author(s):  
Pranav C
Keyword(s):  
Decision Making ◽  
Large Scale ◽  
Review Paper ◽  
New Technology ◽  
Personal Identification ◽  
Healthcare Industry ◽  
Healthcare Organizations ◽  
Paper Briefly ◽  
Blockchain Technology ◽  
Audit Trails

UNSTRUCTURED The word blockchain elicits thoughts of cryptocurrency much of the time, which does disservice to this disruptive new technology. Agreed, bitcoin launched in 2011 was the first large scale implementation of blockchain technology. Also, Bitcoin’s success has triggered the establishment of nearly 1000 new cryptocurrencies. This again lead to the delusion that the only application of blockchain technology is for the creation of cryptocurrency. However, the blockchain technology is capable of a lot more than just cryptocurrency creation and may support such things as transactions that require personal identification, peer review, elections and other types of democratic decision-making and audit trails. Blockchain exists with real world implementations beyond cryptocurrencies and these solutions deliver powerful benefits to healthcare organizations, bankers, retailers and consumers among others. One of the areas where blockchain technology can be used effectively is healthcare industry. Proper application of this technology in healthcare will not only save billions of money but also will contribute to the growth in research. This review paper briefly defines blockchain and deals in detail the applications of blockchain in various areas particularly in healthcare industry.

Ban Ki-moon, 2007–2016

2018 ◽  
Author(s):  
Richard Gowan
Keyword(s):  
United States ◽  
Decision Making ◽  
Security Council ◽  
Large Scale ◽  
Central African Republic ◽  
The United States ◽  
Cautious Approach ◽  
Peacekeeping Operations ◽  
Council Decision ◽  
The Face

During Ban Ki-moon’s tenure, the Security Council was shaken by P5 divisions over Kosovo, Georgia, Libya, Syria, and Ukraine. Yet it also continued to mandate and sustain large-scale peacekeeping operations in Africa, placing major burdens on the UN Secretariat. The chapter will argue that Ban initially took a cautious approach to controversies with the Council, and earned a reputation for excessive passivity in the face of crisis and deference to the United States. The second half of the chapter suggests that Ban shifted to a more activist pressure as his tenure went on, pressing the Council to act in cases including Côte d’Ivoire, Libya, and Syria. The chapter will argue that Ban had only a marginal impact on Council decision-making, even though he made a creditable effort to speak truth to power over cases such as the Central African Republic (CAR), challenging Council members to live up to their responsibilities.

scholarly journals BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Real Time ◽  
Large Scale ◽  
Outcome Predictor ◽  
Short Term ◽  
Rts Game

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.

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