Simulating California reservoir operation using the classification and regression-tree algorithm combined with a shuffled cross-validation scheme

The controlled outflows from a reservoir or dam are highly dependent on the decisions made by the reservoir operators, instead of a natural hydrological process. Difference exists between the natural upstream inflows to reservoirs and the controlled outflows from reservoirs that supply the downstream users. With the decision maker's awareness of changing climate, reservoir management requires adaptable means to incorporate more information into decision making, such as water delivery requirement, environmental constraints, dry/wet conditions, etc. In this paper, a robust reservoir outflow simulation model is presented, which incorporates one of the well-developed data-mining models (Classification and Regression Tree) to predict the complicated human-controlled reservoir outflows and extract the reservoir operation patterns. A shuffled cross-validation approach is further implemented to improve CART's predictive performance. An application study of nine major reservoirs in California is carried out. Results produced by the enhanced CART, original CART, and random forest are compared with observation. The statistical measurements show that the enhanced CART and random forest overperform the CART control run in general, and the enhanced CART algorithm gives a better predictive performance over random forest in simulating the peak flows. The results also show that the proposed model is able to consistently and reasonably predict the expert release decisions. Experiments indicate that the release operation in the Oroville Lake is significantly dominated by SWP allocation amount and reservoirs with low elevation are more sensitive to inflow amount than others

Developing Infrastructure Adaptation Pathways to Combat Hurricane Intensification: A Coupled Storm Simulation and Economic Modeling Framework for Coastal Installations

Climate change projections suggest intensification of extreme weather events, including hurricanes, is expected throughout the 21st century. This will lead to increased destruction for coastal military bases unless infrastructure resiliency and adaptation measures are implemented. This research focuses on examining the simulation of probabilistic, climate-intensified hurricane events at Eglin Air Force Base. FEMA Hazus models are combined with climate projections for wind Intensity, tide, and sea-level rise to produce an assessment of losses to the installation. Damage estimates and hurricane intensity outputs are downscaled to the facility-level so that climate adaptation signals can be identified. The facility losses and climate signals are used as inputs for a dynamic adaptation pathway model. Utilizing a variety of infrastructure investment strategies, the pathway model is used to calculate the expected benefits, risks, and costs associated with adaptation. Such pathways can be used to inform campus and installation master plans and are vital to reducing coastal bases vulnerability to future hurricane events

Data-driven modeling of systemic delay propagation under severe meteorological conditions

The upsetting consequences of weather conditions are well known to any person involved in air transportation. Still the quantification of how these disturbances affect delay propagation and the effectiveness of managers and pilots interventions to prevent possible large-scale system failures needs further attention. In this work, we employ an agent-based data-driven model developed using real flight performance registers for the entire US airport network and focus on the events occurring on October 27 2010 in the United States. A major storm complex that was later called the 2010 Superstorm took place that day. Our model correctly reproduces the evolution of the delay-spreading dynamics. By considering different intervention measures, we can even improve the model predictions getting closer to the real delay data. Our model can thus be of help to managers as a tool to assess different intervention measures in order to diminish the impact of disruptive conditions in the air transport system.Comment: 9 pages, 5 figures. Tenth USA/Europe Air Traffic Management Research and Development Seminar (ATM2013

Developing Emergency Preparedness Plans For Orlando International Airport (MCO) Using Microscopic Simulator WATSim

Emergency preparedness typically involves the preparation of detailed plans that can be implemented in response to a variety of possible emergencies or disruptions to the transportation system. One shortcoming of past response plans was that they were based on only rudimentary traffic analysis or in many cases none at all. With the advances in traffic simulation during the last decade, it is now possible to model many traffic problems, such as emergency management, signal control and testing of Intelligent Transportation System technologies. These problems are difficult to solve using the traditional tools, which are based on analytical methods. Therefore, emergency preparedness planning can greatly benefit from the use of micro-simulation models to evaluate the impacts of natural and man-made incidents and assess the effectiveness of various responses. This simulation based study assessed hypothetical emergency preparedness plans and what geometric and/or operational improvements need to be done in response to emergency incidents. A detailed framework outlining the model building, calibration and validation of the model using microscopic traffic simulation model WATSim (academic version) is provided. The Roadway network data consists of geometric layout of the network, number of lanes, intersection description which include the turning bays, signal timings, phasing sequence, turning movement information etc. The network in and around the OIA region is coded into WATSim with 3 main signalized intersections, 180 nodes and 235 links. The travel demand data includes the vehicle counts in each link of the network and was modeled as percentage turning count movements. After the OIA network was coded into WATSim, the road network was calibrated and validated for the peak hour mostly obtained from ADT with 8% K factor by comparing the simulated and actual link counts at 15 different key locations in the network and visual verification done. Ranges of scenarios were tested that includes security checkpoint, route diversion incase of incident in or near the airport and increasing demand on the network. Travel time, maximum queue length and delay were used as measures of effectiveness and the results tabulated. This research demonstrates the potential benefits of using microscopic simulation models when developing emergency preparedness strategies. In all 4 main Events were modeled and analyzed. In Event 1, occurrence of 15 minutes traffic incident on a section of South Access road was simulated and its impact on the network operations was studied. The averaged travel time under the incident duration to Side A was more than doubled (29 minutes, more than a 100% increase) compared to the base case and similarly that of Side B two and a half times more (23 minutes, also more than a 100% increase). The overall network performance in terms of delay was found to be 231.09 sec/veh. and baseline 198.9 sec/veh. In Event 2, two cases with and without traffic diversions were assumed and evaluated under 15 minutes traffic incident modeled at the same link and spot as in Event 1. It was assumed that information about the traffic incident was disseminated upstream of the incident 2 minutes after the incident had occurred. This scenario study demonstrated that on the average, 17% (4 minutes) to 41% (12 minutes) per vehicle of travel time savings are achieved when real-time traffic information was provided to 26% percent of the drivers diverted. The overall network performance in delay for this event was also found to improve significantly (166.92 sec/veh). These findings led to the conclusion that investment in ITS technologies that support dissemination of traffic information (such as Changeable Message Signs, Highway Advisory Radio, etc) would provide a great advantage in traffic management under emergency situations and road diversion strategies. Event 3 simulated a Security Check point. It was observed that on the average, travel times to Sides A and B was 3 and 5 minutes more respectively compared to its baseline. Averaged queue length of 650 feet and 890 feet worst case was observed. Event 4 determined when and where the network breaks down when loaded. Among 10 sets of demand created, the network appeared to be breaking down at 30% increase based on the network-wide delay and at 15% based on Level of Service (LOS). The 90% increase appeared to have the most effect on the network with a total network-wide delay close to 620 seconds per vehicle which is 3 and a half times compared to the baseline. Conclusions and future scope were provided to ensure continued safe and efficient traffic operations inside and outside the Orlando International Airport region and to support efficient and informed decision making in the face of emergency situations

Reusable Launch Vehicle Design Implications for Regeneration Time

In last few years, the Air Force Research Laboratory sponsored several research projects on a Reusable Launch Vehicles (RLV) whose design, operation, and logistics requirements are intended to be much simpler than for the Space Shuttle. As a part of these efforts, previous researchers developed a model that simulated the post-landing, ground maintenance and prelaunch operations of a RLV in order to evaluate how its design parameters affect the logistics operations. The next logical step is to investigate the effects and interactions of all factors used in the existing simulation model in a single experiment that considers the huge number of possible design characteristics’ combinations discovered in the previous studies as well as varying resources such as manpower, ground support equipment and facilities. The goal of this research is to recommend to the AFRL a preferred design strategy that could minimize the resource requirements in terms of equipment and manpower as well as turnaround time of logistics operations. In order to achieve this goal, this study identifies significant effects of the RLV\u27s design characteristics by utilizing the AFRL’s MILEPOST discrete-event simulation model in a systematic design of experiment (DOE) approach. In addition, it assesses the impact of varying resources (manpower, ground support equipment and fleet size) on departure availability. The results of this research is intended to provide the AFRL with valuable and timely information about the combinations of selected RLV design characteristics which could assist in directing efforts in research and development of the future space vehicle

Preparing Water Supply Systems for Climate Change: The Role of Hydrologic Forecasting in the Northeast

Fresh water is a resource strongly impacted by climactic conditions. Water supply systems in the northeastern United States will see the effects of climate change on their water quality and quantity in various ways, including changes in seasonality of flows, changes in the frequency and magnitude of extreme precipitation events, and changes in the variability of precipitation and water availability. Five northeastern water supplies examined are expected to maintain at least 95% monthly reliability over a range of climates wider than the current projections. However, model results indicate that turbidity levels in New York City\u27s Ashokan Reservoir will change with changes in mean annual precipitation and temperature. Through a series of linked models of stochastic weather, hydrologic processes, and the supply system, Chapter 2 demonstrates the robustness of several adaptations available to the New York City Water Supply System to mitigate drought and manage water quality under climate change projections through the end of the century. Results illustrate how reducing demand and managing storage and releases based on hydrologic forecasting reduce the frequency of drought warnings and emergencies and improve system reliability in all climate change scenarios investigated. Through operations that limit turbidity propagation through the system and improvements to the Catskill Aqueduct to lower the minimum flow under conditions with high turbidity, results demonstrate decreases lower turbidity loads and a reduction in emergency Alum use. These options demonstrate cumulative benefits when used in combination. Chapter 3 seeks to quantify the amount of water supply system performance improvement that can be expected from improved forecasting in managing drought conditions. Using existing forecasts for Lancaster, PA, synthetic forecasts with varying quality, and a system model of the Baltimore, MD water supply system, this chapter demonstrated a method for quantifying improved system performance as a function of improved forecast quality, finding improvements in system performance to be approximately linear over a large range of forecast quality. Chapter 4 tests a new method for the creation of statistical first-order autoregressive streamflow forecasts by conditioning the parameters and ensemble variance on a “hydrologic regime,” defined in several different ways. National Weather Service seasonal outlooks for precipitation are used as categorical forecasts of precipitation. The forecasts are found to have small positive skill, and for two of three sites, this skill is enough to result in small gains in the CRPSS of the ensemble hydrologic forecast. Utilizing perfect categorical forecasts indicates that adjusting the ensemble variance (rather than the autoregressive parameter) based on forecasted precipitation is responsible for the majority of improvements in skill for this method. The method is limited by the difficulty of long lead-time precipitation forecasting

Evaluating concepts for short-term control in financial service processes

Financial services are characterised by the integration of customers while the service is being delivered. This integration leads to interruptions and thus delays in the processing of a customer order until for example the customer provides the missing input. Because customer behaviour can only be planned to a certain extent this is a major problem for an efficient control of financial service processes. It would be helpful to know which concept leads to the best solution for a certain situation in controlling the process. A concept contains explicit practical knowledge e.g. using a stand-by-employee or a prioritisation of customer orders with first-infirst-out. As financial services differ from manufacturing processes application knowledge of concepts cannot be transferred one to one. To test concepts regarding their ability to deal efficiently with interruptions by customers short-term simulations should be conducted. Shortterm simulation uses the actual state of a process and is not focussing on steady-state results. The research presented focuses on comparing several concepts for short-term control using case-study data of a typical financial service process. For this process a simulation model is built based on process mining. This approach is used to gather information out of documented timestamps of underlying process-aware information systems. Such timestamps allow a historical analysis to build typical scenarios and to gather the actual state of a financial service process as a starting point for a simulation analysis. The depicted concepts are simulated for different typical scenarios points to determine respectively which concept suits best. The results show which concepts suit best in certain situations for the case study conducted. --short-term control,financial services,business process simulation

Alternative sweetener from curculigo fruits

This study gives an overview on the advantages of Curculigo Latifolia as an alternative sweetener and a health product. The purpose of this research is to provide another option to the people who suffer from diabetes. In this research, Curculigo Latifolia was chosen, due to its unique properties and widely known species in Malaysia. In order to obtain the sweet protein from the fruit, it must go through a couple of procedures. First we harvested the fruits from the Curculigo trees that grow wildly in the garden. Next, the Curculigo fruits were dried in the oven at 50 0C for 3 days. Finally, the dried fruits were blended in order to get a fine powder. Curculin is a sweet protein with a taste-modifying activity of converting sourness to sweetness. The curculin content from the sample shown are directly proportional to the mass of the Curculigo fine powder. While the FTIR result shows that the sample spectrum at peak 1634 cm–1 contains secondary amines. At peak 3307 cm–1 contains alkynes

Assessing the impact of land use changes on hydropower production and erosion in the Coca River basin. A contribution towards Integrated Water Resources Management in Ecuador

Die Region mit der weltweit höchsten Rate an Landnutzungsänderungen sind die feuchten Tropen. Es ist ein weit verbreiteter Prozess in diesen Regionen durch Entwaldung Raum für landwirtschaftliche Flächen und Weiden zu schaffen. Darüber hinaus ist diese Region für ihre große Wasserverfügbarkeit und ihr Potenzial zur Erzeugung von Wasserkraft bekannt. Daher sind in den letzten Jahrzehnten Bemühungen zur Erhaltung und zum Schutz der natürlichen Waldbedeckung der tropischen Wassereinzugsgebiete zu einer Priorität innerhalb der Prozesse des integrierten Wasserressourcenmanagements (IWRM) geworden. Landnutzungsänderungen (LUC) beeinflussen den Wasserhaushalt eines Einzugsgebiets, indem sie das verfügbare Wasser zusammen mit der Veränderung der anderen Wasserhaushaltskomponenten beeinflussen. Das Verständnis der LUC und ihrer Auswirkungen auf die Hydrologie eines Einzugsgebiets ist für das Management und die Nutzung der Wasserressourcen in einem Einzugsgebiet von entscheidender Bedeutung. Daher ist es wichtig, die Auswirkungen von Landnutzungsänderungen in den letzten Jahrzenten auf die Abflussmenge eines Wassereinzugsgebiets zu verstehen, um in Zukunft - innerhalb eines IWRM-Rahmens - ein ordnungsgemäßes Wassermanagement und eine Wasserressourcenplanung durchführen zu können. Diese Studie bewertet die historischen Trends von Niederschlag und Stromfluss und analysiert die Reaktionen des Stromflusses auf Landnutzungsänderungen unter verschiedenen Szenarien und Zukunftsprojektionen im oberen Coca-Einzugsgebiet. Dieses befindet sich am Osthang der ecuadorianischen Anden und ist Teil der oberen ecuadorianischen Amazonasregion. Die Ergebnisse des Mann-Kendall-Tests (MK) zeigen, dass kein statistisch signifikanter Trend in den täglichen Niederschlags- und monatlichen Flussabflussmessungen im Wassereinzugsgebiet existiert. Der Pettitt-Test kann keinen Sprungpunkt in den einzugsgebietsweiten Niederschlagsreihen feststellen. Die Landnutzungskarten von 1990, 2000, 2008 und 2016 werden für die LUC-Erkennungsanalyse verwendet, sowie das CA_Markov-Modell, um die zukünftigen LUC-Projektionen unter drei verschiedenen Szenarien vorherzusagen: Trendszenario, “Best-Case-Szenario”, “Worst-Case-Szenario”. Die Vorhersagen für die Jahre 2026 und 2036 werden unter Berücksichtigung der physischen und sozioökonomischen Treiber der LUC-Dynamik im Einzugsgebiet berechnet. Das Trendszenario behält die für die Jahre 2026 und 2036 prognostizierten Wahrscheinlichkeiten für Landnutzungsänderungen bei. Das Best-Case-Szenario befasst sich mit den Wahrscheinlichkeiten für Änderungen der LUC in Richtung eines ausgewogenen Szenarios, zwischen der Erhaltung natürlicher Ökosysteme und produktiven Aktivitäten innerhalb des Einzugsgebiets. Das “Worst-Case-Szenario” befasst sich mit den Wahrscheinlichkeiten einer Änderung der LUC in Richtung eines Szenarios, in dem Rohstoffaktivitäten vorherrschen und die Produktionsbereiche in der Wasserscheide zunehmen. Die LUC-Erkennungsergebnisse zeigen eine Zunahme der landwirtschaftlichen Flächen und eine Abnahme der Waldbedeckung zwischen 1990 und 2016. Statistisch gesehen, verringerte sich die natürliche Waldbedeckung von 61,2% im Jahr 1990 auf 57,12% im Jahr 2016, während der Anteil der landwirtschaftlichen Flächen von 2,9% auf 7,23% zwischen die Jahren 1990 und 2016 zunahm. Die Ergebnisse der LUC- Projektion für die Jahre 2026 und 2036 in Bezug auf das Jahr 2016 deuten darauf hin, dass die landwirtschaftlichen Flächen im Jahr 2026 voraussichtlich um 9,3% und im Jahr 2036 um 19,2% im Trendszenario zunehmen werden. Für das “Best-Case-Szenario” wird eine Zunahme der landwirtschaftlichen Flächen um 1,1% bzw. 3% im Jahr 2026 bzw. 2036 prognostiziert. Die Ergebnisse des “Worst-Case–Szenarios” für die Jahre 2026 und 2036 prognostizieren eine Zunahme der landwirtschaftlichen Flächen um 26,1% bzw. 54,3%. Darüber hinaus wird für das Trendszenario im Vergleich zu 2016 ein Rückgang der natürlichen Waldbedeckung im Einzugsgebiet um 0,6% (2026) und um 1,5% (2036) prognostiziert. Für das “Best-Case-Szenario” wird prognostiziert, dass die Waldbedeckung um 0,2% (2026) und um 0,4% (2036) abnehmen wird. Das “Worst-Case-Szenario” prognostiziert für die Jahre 2026 und 2036 einen Rückgang der natürlichen Waldbedeckung um 2,6% bzw. 5,8% gegenüber 2016. Die Ergebnisse der hydrologischen Modellierung zeigen, dass aufgrund der Auswirkungen von LUC der durchschnittliche tägliche Stromfluss für das Trendszenario im Vergleich zu 2016 um 1,04% (2026) und 1,45% (2036) anstieg. Für das “Best-Case– Szenario” verringerte sich der durchschnittliche tägliche Stromfluss in den Jahren 2026 und 2036 gegenüber 2016 um 4,91% (-24,8 m³/s) bzw. 6,10% (-30,8 m³/s). Für das Szenario “Worst-Case” wird in Bezug auf das Jahr 2016 ein Anstieg des durchschnittlichen täglichen Stromflusses um 2,08% (2026) und um 2,37% (2036) prognostiziert. Die Ergebnisse zu den Auswirkungen von LUC auf den Stromfluss unter den verschiedenen vorgeschlagenen Szenarien zeigen, dass die Änderungen des Stromflusses kein Faktor sind, der die Wasserkrafterzeugung im Einzugsgebiet beeinflussen könnte. Die Ergebnisse zeigen jedoch, dass die Wasserhaushaltskomponenten durch die räumliche und zeitliche Verteilung von LUC im Untersuchungsgebiet beeinflusst werden, was für ein einzugsgebietsweites integriertes Wasserressourcenmanagement nützlich ist. Das Ausmaß dieser Effekte kann jedoch durch Unsicherheiten verdeckt werden, die sich aus den hydrologischen und LUC-Modellierungsprozessen ergeben. Daher sind weitere Studien zur Optimierung von Landnutzungsänderungen und Untersuchungen zur Bewertung von Niederschlag-Abfluss-Prozessen im Untersuchungsgebiet unerlässlich. Nichtsdestotrotz sollten Nachhaltigkeitsaspekte, die mit dem Vorhandensein der Wasserkraftanlage im Untersuchungsgebiet verbunden sind, nicht vernachlässigt werden. Um eine nachhaltige Entwicklung im Einzugsgebiet gewährleisten zu können (die die langfristige Wasserkraftproduktion, die Erhaltung der Ökosysteme und das sozioökonomische Wohlergehen der Bevölkerung im Einzugsgebiet umfasst), müssen in weiteren Arbeiten innerhalb eines IWRM-Rahmens weitere Variablen und Prozesse analysiert werden, die in dieser Studie nicht behandelt wurden