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Sample records for advanced hydrologic prediction

  1. Advanced hydrologic prediction system

    NASA Astrophysics Data System (ADS)

    Connelly, Brian A.; Braatz, Dean T.; Halquist, John B.; Deweese, Michael M.; Larson, Lee; Ingram, John J.

    1999-08-01

    As our Nation's population and infrastructure grow, natural disasters are becoming a greater threat to our society's stability. In an average year, inland flooding claims 133 lives and resulting property losses exceed 4.0 billion. Last year, 1997, these losses totaled 8.7 billion. Because of this blossoming threat, the National Weather Service (NWS) has requested funding within its 2000 budget to begin national implementation of the Advanced Hydrologic Prediction System (AHPS). With this system in place the NWS will be able to utilize precipitation and climate predictions to provide extended probabilistic river forecasts for risk-based decisions. In addition to flood and drought mitigation benefits, extended river forecasts will benefit water resource managers in decision making regarding water supply, agriculture, navigation, hydropower, and ecosystems. It's estimated that AHPS, if implemented nationwide, would save lives and provide $677 million per year in economic benefits. AHPS is used currently on the Des Moines River basin in Iowa and will be implemented soon on the Minnesota River basin in Minnesota. Experience gained from user interaction is leading to refined and enhanced product formats and displays. This discussion will elaborate on the technical requirements associated with AHPS implementation, its enhanced products and informational displays, and further refinements based on customer feedback.

  2. Hydrological Ensemble Prediction System (HEPS)

    NASA Astrophysics Data System (ADS)

    Thielen-Del Pozo, J.; Schaake, J.; Martin, E.; Pailleux, J.; Pappenberger, F.

    2010-09-01

    Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Following on the success of the use of ensembles for weather forecasting, the hydrological community now moves increasingly towards Hydrological Ensemble Prediction Systems (HEPS) for improved flood forecasting using operationally available NWP products as inputs. However, these products are often generated on relatively coarse scales compared to hydrologically relevant basin units and suffer systematic biases that may have considerable impact when passed through the non-linear hydrological filters. Therefore, a better understanding on how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes is necessary. The "Hydrologic Ensemble Prediction Experiment" (HEPEX), is an international initiative consisting of hydrologists, meteorologist and end-users to advance probabilistic hydrologic forecast techniques for flood, drought and water management applications. Different aspects of the hydrological ensemble processor are being addressed including • Production of useful meteorological products relevant for hydrological applications, ranging from nowcasting products to seasonal forecasts. The importance of hindcasts that are consistent with the operational weather forecasts will be discussed to support bias correction and downscaling, statistically meaningful verification of HEPS, and the development and testing of operating rules; • Need for downscaling and post-processing of weather ensembles to reduce bias before entering hydrological applications; • Hydrological model and parameter uncertainty and how to correct and

  3. Advancing Ensemble Streamflow Prediction with Stochastic Meteorological Forcings for Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Caraway, N.; Wood, A. W.; Rajagopalan, B.; Zagona, E. A.; Daugherty, L.

    2012-12-01

    River Forecast Centers of National Weather Service (NWS) produce seasonal streamflow forecasts via a method called Ensemble Streamflow Prediction (ESP). NWS ESP forces the temperature index Snow17 and Sacramento Soil Moisture Accounting model (SAC-SMA) models with historical weather sequences for the forecasting period, starting from models' current watershed initial conditions, to produce ensemble streamflow forecasts. There are two major drawbacks of this method: (i) the ensembles are limited to the length of historical, limiting ensemble variability and (ii) incorporating seasonal climate forecasts (e.g., El Nino Southern Oscillation) relies on adjustment or weighting of ESP streamflow sequences. These drawbacks motivate the research presented here, which has two components: (i) a multi-site stochastic weather generator and (ii) generation of ensemble weather forecast inputs to the NWS model to produce ensemble streamflow forecasts. We enhanced the K-nearest neighbor bootstrap based stochastic generator include: (i) clustering the forecast locations into climatologically homogeneous regions to better capture the spatial heterogeneity and, (ii) conditioning the weather forecasts on a probabilistic seasonal climate forecast. This multi-site stochastic weather generator runs in R and the NWS models run within the new Community Hydrologic Prediction System, a forecasting sequence we label WG-ESP. The WG-ESP framework was applied to generate ensemble forecasts of spring season (April-July) streamflow in the San Juan River Basin, one of the major tributaries of the Colorado River, for the period 1981-2010. The hydrologic model requires daily weather sequences at 66 locations in the basin. The enhanced daily weather generator sequences captured the distributional properties and spatial dependence of the climatological ESP, and also generated weather sequences consistent with conditioning on seasonal climate forecasts. Spring season ensemble forecast lead times from

  4. The Hydrologic Ensemble Prediction Experiment (HEPEX)

    NASA Astrophysics Data System (ADS)

    Wood, A. W.; Thielen, J.; Pappenberger, F.; Schaake, J. C.; Hartman, R. K.

    2012-12-01

    The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF). With support from the US National Weather Service (NWS) and the European Commission (EC), the HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support in emergency management and water resources sectors. The strategy to meet this goal includes meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. HEPEX has organized about a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Today, the HEPEX mission is to demonstrate the added value of hydrological ensemble prediction systems (HEPS) for emergency management and water resources sectors to make decisions that have important consequences for economy, public health, safety, and the environment. HEPEX is now organised around six major themes that represent core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

  5. Modular Curriculum for Hydrologic Advancement (MOCHA)

    NASA Astrophysics Data System (ADS)

    Kelleher, C.; Wagener, T.; Gooseff, M.; McGlynn, B.; Marshall, L.; Meixner, T.; McGuire, K.; Sharma, P.; Zuppe, S.; Pfeiffer, C.

    2008-12-01

    In-class hydrology education is typically strongly biased towards the instructor's background and overcoming this limitation is burdensome within the time-constraints academia. This problem is particularly true for academics in tenure-track positions when most of the material development must occur. To overcome this challenge and advance a broader perspective of hydrology education, we are in the process of establishing the Modular Curriculum for Hydrologic Advancement (MOCHA). The objective is to create an evolving core curriculum for hydrology education freely available to, developed, and reviewed by the worldwide hydrologic community. We seek to establish an online faculty learning community for hydrology education and a modular core curriculum based on modern pedagogical standards. The goal of this effort is to support hydrology faculty in educating hydrologists that can solve today's and tomorrow's interdisciplinary problems that go far beyond the traditional disciplinary biased hydrology education most of us have experienced.

  6. The Hydrologic Ensemble Prediction Experiment (HEPEX)

    NASA Astrophysics Data System (ADS)

    Wood, Andy; Wetterhall, Fredrik; Ramos, Maria-Helena

    2015-04-01

    The Hydrologic Ensemble Prediction Experiment was established in March, 2004, at a workshop hosted by the European Center for Medium Range Weather Forecasting (ECMWF), and co-sponsored by the US National Weather Service (NWS) and the European Commission (EC). The HEPEX goal was to bring the international hydrological and meteorological communities together to advance the understanding and adoption of hydrological ensemble forecasts for decision support. HEPEX pursues this goal through research efforts and practical implementations involving six core elements of a hydrologic ensemble prediction enterprise: input and pre-processing, ensemble techniques, data assimilation, post-processing, verification, and communication and use in decision making. HEPEX has grown through meetings that connect the user, forecast producer and research communities to exchange ideas, data and methods; the coordination of experiments to address specific challenges; and the formation of testbeds to facilitate shared experimentation. In the last decade, HEPEX has organized over a dozen international workshops, as well as sessions at scientific meetings (including AMS, AGU and EGU) and special issues of scientific journals where workshop results have been published. Through these interactions and an active online blog (www.hepex.org), HEPEX has built a strong and active community of nearly 400 researchers & practitioners around the world. This poster presents an overview of recent and planned HEPEX activities, highlighting case studies that exemplify the focus and objectives of HEPEX.

  7. The Modular Curriculum for Hydrologic Advancement (MOCHA)

    NASA Astrophysics Data System (ADS)

    Wagener, T.; Kelleher, C.; Gooseff, M.; McGlynn, B.; Marshall, L.; Meixner, T.; McGuire, K.; Sharma, P.; Zappe, S.

    2009-04-01

    In-class hydrology education is typically strongly biased towards the instructor's background and overcoming this limitation is overly burdensome within the time-constraints of the academic life. This is particularly true for academics in tenure-track positions when most of the material development has to occur. To overcome this issue, we are in the process of establishing the Modular Curriculum for Hydrologic Advancement (MOCHA). Our overall objective is to create an evolving core curriculum for hydrology education freely available to and developed and reviewed by the worldwide hydrologic community. We seek to establish an online faculty learning community for hydrology education and a modular core curriculum based on modern pedagogical standards. The goal of this effort is to support hydrology faculty in educating hydrologists that can solve today's and tomorrow's interdisciplinary problems that go far beyond the traditional disciplinary biased hydrology education most of us have experienced.

  8. Hydrologic Prediction Through Earthcube Enabled Hydrogeophysical Cyberinfrastructure

    NASA Astrophysics Data System (ADS)

    Versteeg, R. J.; Johnson, D.

    2012-12-01

    Accurate prediction of hydrologic processes is contingent on the successful interaction of multiple components, including (1) accurate conceptual and numerical models describing physical, chemical and biological processes (2) a numerical framework for integration of such processes and (3) multidisciplinary temporal data streams which feeds such models. Over the past ten years the main focus in the hydrogeophysical community has been the advancement and developments of conceptual and numerical models. While this advancement still poses numerous challenges (e.g. the in silico modeling of microbiological processes and the coupling of models across different interfaces) there is now a fairly good high level understanding of the types, scales of and interplay between processes. In parallel with this advancement there have been rapid developments in data acquisition capabilities (ranging from satellite based remote sensing to low cost sensor networks) and the associated cyberinfrastructure which allows for mash ups of data from heterogeneous and independent sensor networks. The tools for this in generally have come from outside the hydrogeophysical community - partly these are specific scientific tools developed through NSF, DOE and NASA funding, and partly these are general web2.0 tools or tools developed under commercial initiatives (e.g. the IBM Smarter Planet initiative). One challenge facing the hydrogeophysical community is how to effectively harness all these tools to develop hydrologic prediction tools. One of the primary opportunities for this is the NSF funded EarthCube effort (http://earthcube.ning.com/ ). The goal of EarthCube is to transform the conduct of research by supporting the development of community-guided cyberinfrastructure to integrate data and information for knowledge management across the Geosciences. Note that Earthcube is part of a larger NSF effort (Cyberinfrastructure for the 21st Century (CIF21), and that Earthcube is driven by the vision

  9. Soil hydrology: Recent methodological advances, challenges, and perspectives

    NASA Astrophysics Data System (ADS)

    Vereecken, H.; Huisman, J. A.; Hendricks Franssen, H. J.; Brüggemann, N.; Bogena, H. R.; Kollet, S.; Javaux, M.; van der Kruk, J.; Vanderborght, J.

    2015-04-01

    Technological and methodological progress is essential to improve our understanding of fundamental processes in natural and engineering sciences. In this paper, we will address the potential of new technological and methodological advancements in soil hydrology to move forward our understanding of soil water related processes across a broad range of scales. We will focus on advancements made in quantifying root water uptake processes, subsurface lateral flow, and deep drainage at the field and catchment scale, respectively. We will elaborate on the value of establishing a science-driven network of hydrological observatories to test fundamental hypotheses, to study organizational principles of soil hydrologic processes at catchment scale, and to provide data for the development and validation of models. Finally, we discuss recent developments in data assimilation methods, which provide new opportunities to better integrate observations and models and to improve predictions of the short-term evolution of hydrological processes.

  10. Advances in river ice hydrology

    NASA Astrophysics Data System (ADS)

    Beltaos, Spyros

    2000-06-01

    River ice is present in nearly all Canadian rivers, for periods ranging from days to many months. Whether moving or stationary, it interacts with the river flow in various ways, resulting in multiple impacts on the economy and ecosystem, and posing a major flood threat to riverside communities. In the past 4 years, Canadian research and development efforts have been directed at a variety of problems. A strong focus on ice breakup and ice jam processes resulted in improved understanding of the salient geomorphological and hydroclimatic factors, enhanced modelling and prediction capabilities, and development of techniques for in situ measurement of ice jam properties. Key contributions in the area of ecological impacts of river ice and ice jams have led not only to solid advances in knowledge, but also to an appreciation of the vast scope of this subject and its numerous links to environmental science. A closely related topic, the flux of suspended sediment in ice-laden rivers was studied for the first time, in order to delineate the effects of the ice on sediment and associated contaminant loads. In response to growing concern about climate change and variability, several studies addressed implications to ice regime, and thence, to ecology and economy. Although not fully explored, the potential impacts appear to be numerous and significant, owing to the high sensitivity of river ice processes to climatic factors. In the foreseeable future, research is likely to continue along the above noted lines, although an increased emphasis on climatic and ecological aspects is probable. Insights gained on the mechanisms of breakup and jamming may lead to increased modelling applications and testing of theoretical concepts.

  11. A University Consortium for the Advancement of Hydrologic Research

    NASA Astrophysics Data System (ADS)

    Hooper, R. P.; Wilson, J.; Band, L.; Reckhow, K.

    2003-12-01

    Seventy-six research universities across the United States have joined to form the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI), a non-profit corporation. With support from the National Science Foundation, CUAHSI has embarked upon the design and development of programs to enable hydrologic research at larger spatial scales over longer time periods than has been within the grasp of individual investigators. The guiding principle of this design has been an embracing of the entire hydrologic cycle to enable research at the interfaces among traditional hydrologic subdisciplines and between hydrologic science and allied disciplines in the earth and life sciences. To improve our predictive understanding of hydrologic phenomena, the fundamental approach that has been adopted is the development of multidisciplinary, coherent data sets to enable testing of hypotheses in different hydrologic settings across a range of spatial and temporal scales. Four mutually supportive program elements have been conceived: a network of hydrologic observatories (the subject of this special session) designed strategically to collect additional data at large scales (on the order of 10,000 km2) and to leverage existing investments in small-scale intensive studies and in larger scale monitoring activities; hydrologic information systems to develop a comprehensive data model for integrating disparate data types, to develop the cyberinfrastructure necessary for systematic data collection and dissemination and to support community models; hydrologic measurement technology facility to broker instrumentation services from existing sources, to provide cutting edge tools along with the necessary support to use them, and to develop new hydrologic instrumentation needed to advance the science; and hydrologic synthesis center to provide a venue for hydrologic sciences from a range of disciplines to work on topics ranging from inter-observatory comparison to evolving

  12. Accelerating advances in continental domain hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Archfield, Stacey A.; Clark, Martyn; Arheimer, Berit; Hay, Lauren E.; McMillan, Hilary; Kiang, Julie E.; Seibert, Jan; Hakala, Kirsti; Bock, Andrew; Wagener, Thorsten; Farmer, William H.; Andréassian, Vazken; Attinger, Sabine; Viglione, Alberto; Knight, Rodney; Markstrom, Steven; Over, Thomas

    2015-12-01

    In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.

  13. Accelerating advances in continental domain hydrologic modeling

    USGS Publications Warehouse

    Archfield, Stacey A.; Clark, Martyn; Arheimer, Berit; Hay, Lauren E.; McMillan, Hilary; Kiang, Julie E.; Seibert, Jan; Hakala, Kirsti; Bock, Andrew R.; Wagener, Thorsten; Farmer, William H.; Andreassian, Vazken; Attinger, Sabine; Viglione, Alberto; Knight, Rodney; Markstrom, Steven; Over, Thomas M.

    2015-01-01

    In the past, hydrologic modeling of surface water resources has mainly focused on simulating the hydrologic cycle at local to regional catchment modeling domains. There now exists a level of maturity among the catchment, global water security, and land surface modeling communities such that these communities are converging toward continental domain hydrologic models. This commentary, written from a catchment hydrology community perspective, provides a review of progress in each community toward this achievement, identifies common challenges the communities face, and details immediate and specific areas in which these communities can mutually benefit one another from the convergence of their research perspectives. Those include: (1) creating new incentives and infrastructure to report and share model inputs, outputs, and parameters in data services and open access, machine-independent formats for model replication or reanalysis; (2) ensuring that hydrologic models have: sufficient complexity to represent the dominant physical processes and adequate representation of anthropogenic impacts on the terrestrial water cycle, a process-based approach to model parameter estimation, and appropriate parameterizations to represent large-scale fluxes and scaling behavior; (3) maintaining a balance between model complexity and data availability as well as uncertainties; and (4) quantifying and communicating significant advancements toward these modeling goals.

  14. Rain or snow: hydrologic processes, observations, prediction, and research needs

    NASA Astrophysics Data System (ADS)

    Harpold, Adrian A.; Kaplan, Michael L.; Zion Klos, P.; Link, Timothy; McNamara, James P.; Rajagopal, Seshadri; Schumer, Rina; Steele, Caitriana M.

    2017-01-01

    The phase of precipitation when it reaches the ground is a first-order driver of hydrologic processes in a watershed. The presence of snow, rain, or mixed-phase precipitation affects the initial and boundary conditions that drive hydrological models. Despite their foundational importance to terrestrial hydrology, typical phase partitioning methods (PPMs) specify the phase based on near-surface air temperature only. Our review conveys the diversity of tools available for PPMs in hydrological modeling and the advancements needed to improve predictions in complex terrain with large spatiotemporal variations in precipitation phase. Initially, we review the processes and physics that control precipitation phase as relevant to hydrologists, focusing on the importance of processes occurring aloft. There is a wide range of options for field observations of precipitation phase, but there is a lack of a robust observation networks in complex terrain. New remote sensing observations have the potential to increase PPM fidelity, but generally require assumptions typical of other PPMs and field validation before they are operational. We review common PPMs and find that accuracy is generally increased at finer measurement intervals and by including humidity information. One important tool for PPM development is atmospheric modeling, which includes microphysical schemes that have not been effectively linked to hydrological models or validated against near-surface precipitation-phase observations. The review concludes by describing key research gaps and recommendations to improve PPMs, including better incorporation of atmospheric information, improved validation datasets, and regional-scale gridded data products. Two key points emerge from this synthesis for the hydrologic community: (1) current PPMs are too simple to capture important processes and are not well validated for most locations, (2) lack of sophisticated PPMs increases the uncertainty in estimation of hydrological

  15. It takes a community to raise a hydrologist: the Modular Curriculum for Hydrologic Advancement (MOCHA)

    NASA Astrophysics Data System (ADS)

    Wagener, T.; Kelleher, C.; Weiler, M.; McGlynn, B.; Gooseff, M.; Marshall, L.; Meixner, T.; McGuire, K.; Gregg, S.; Sharma, P.; Zappe, S.

    2012-02-01

    Protection from hydrological extremes and the sustainable supply of hydrological services in the presence of climate change and increasing population pressure are the defining societal challenges for hydrology in the 21st century. A review of the existing literature shows that these challenges and their educational consequences for hydrology were foreseeable and were predicted by some. Surveys of the current educational basis, however, also clearly demonstrate that hydrology education is not yet prepared to deal with this challenge. We present our own vision of the necessary future evolution of hydrology education, which we implemented in the Modular Curriculum for Hydrologic Advancement (MOCHA). The MOCHA project is directly aimed at developing a community-driven basis for hydrology education. In this paper we combine literature review, surveys, discussion and assessment to provide a holistic baseline for future hydrology education.

  16. Improving Hydrologic Prediction at the Basin Scale through State Updating

    NASA Astrophysics Data System (ADS)

    Weerts, A.; Kockx, A.; Schellekens, J.; Drost, N.; Tretjakova, D.; Ren, J.; Lopez Lopez, P.; Hut, R.

    2015-12-01

    Data assimilation (DA) holds considerable potential for improving hydrologic predictions. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. Several challenges exist (see Liu et al., 2012). The objective of this paper is to highlight several recent studies on basin scale data assimilation using distributed hydrologic models that touch upon these challenges including application of streamflow data assimilation using different algorithms, combined streamflow/snow data assimilation and the development of a generic linkage of OpenDA and the open source hydrologic package Openstreams/Wflow based on the (emerging) standard Basic Model Interface (BMI) as advocated by CSDMS using cross-platform webservices (i.e. Apache Thrift). Liu et al., 2012. Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities, Hydrol. Earth Syst. Sci., 16, 3863-3887, doi:10.5194/hess-16-3863-2012.

  17. Hydrologic ensemble prediction: enhancing science, operation and application through HEPEX

    NASA Astrophysics Data System (ADS)

    Wetterhall, Fredrik; Ramos, Maria-Helena; Wang, Qj; Wood, Andy

    2016-04-01

    HEPEX (Hydrologic Ensemble Prediction Experiment) was established in March 2004 at a workshop hosted by the European Centre for Medium Range Weather Forecasts (ECMWF), co-sponsored by the US National Weather Service (NWS) and the European Commission (EC). HEPEX and the community it represents has over its more than 10 years of existence continuously worked to promote and advance the science of hydrologic ensemble prediction as well as operational systems and water management applications. Through workshops and conference sessions, HEPEX has connected the research community, forecasters and forecast users and facilitated the exchange of ideas, data, methods and experience. In particular, the establishment of an online blog portal has greatly enhanced community interaction and knowledge sharing (www.hepex.org). HEPEX has now a strong and active community of nearly 400 researchers and practitioners around the world. In this poster, we present an overview of recent and planned HEPEX activities, and highlight opportunities to further progress ensemble prediction science, operation and application.

  18. Recent advances in understanding Antarctic subglacial lakes and hydrology.

    PubMed

    Siegert, Martin J; Ross, Neil; Le Brocq, Anne M

    2016-01-28

    It is now well documented that over 400 subglacial lakes exist across the bed of the Antarctic Ice Sheet. They comprise a variety of sizes and volumes (from the approx. 250 km long Lake Vostok to bodies of water less than 1 km in length), relate to a number of discrete topographic settings (from those contained within valleys to lakes that reside in broad flat terrain) and exhibit a range of dynamic behaviours (from 'active' lakes that periodically outburst some or all of their water to those isolated hydrologically for millions of years). Here we critique recent advances in our understanding of subglacial lakes, in particular since the last inventory in 2012. We show that within 3 years our knowledge of the hydrological processes at the ice-sheet base has advanced considerably. We describe evidence for further 'active' subglacial lakes, based on satellite observation of ice-surface changes, and discuss why detection of many 'active' lakes is not resolved in traditional radio-echo sounding methods. We go on to review evidence for large-scale subglacial water flow in Antarctica, including the discovery of ancient channels developed by former hydrological processes. We end by predicting areas where future discoveries may be possible, including the detection, measurement and significance of groundwater (i.e. water held beneath the ice-bed interface).

  19. Recent advances in understanding Antarctic subglacial lakes and hydrology

    PubMed Central

    Siegert, Martin J.; Ross, Neil; Le Brocq, Anne M.

    2016-01-01

    It is now well documented that over 400 subglacial lakes exist across the bed of the Antarctic Ice Sheet. They comprise a variety of sizes and volumes (from the approx. 250 km long Lake Vostok to bodies of water less than 1 km in length), relate to a number of discrete topographic settings (from those contained within valleys to lakes that reside in broad flat terrain) and exhibit a range of dynamic behaviours (from ‘active’ lakes that periodically outburst some or all of their water to those isolated hydrologically for millions of years). Here we critique recent advances in our understanding of subglacial lakes, in particular since the last inventory in 2012. We show that within 3 years our knowledge of the hydrological processes at the ice-sheet base has advanced considerably. We describe evidence for further ‘active’ subglacial lakes, based on satellite observation of ice-surface changes, and discuss why detection of many ‘active’ lakes is not resolved in traditional radio-echo sounding methods. We go on to review evidence for large-scale subglacial water flow in Antarctica, including the discovery of ancient channels developed by former hydrological processes. We end by predicting areas where future discoveries may be possible, including the detection, measurement and significance of groundwater (i.e. water held beneath the ice-bed interface). PMID:26667914

  20. Geostatistical enhancement of european hydrological predictions

    NASA Astrophysics Data System (ADS)

    Pugliese, Alessio; Castellarin, Attilio; Parajka, Juraj; Arheimer, Berit; Bagli, Stefano; Mazzoli, Paolo; Montanari, Alberto; Blöschl, Günter

    2016-04-01

    Geostatistical Enhancement of European Hydrological Prediction (GEEHP) is a research experiment developed within the EU funded SWITCH-ON project, which proposes to conduct comparative experiments in a virtual laboratory in order to share water-related information and tackle changes in the hydrosphere for operational needs (http://www.water-switch-on.eu). The main objective of GEEHP deals with the prediction of streamflow indices and signatures in ungauged basins at different spatial scales. In particular, among several possible hydrological signatures we focus in our experiment on the prediction of flow-duration curves (FDCs) along the stream-network, which has attracted an increasing scientific attention in the last decades due to the large number of practical and technical applications of the curves (e.g. hydropower potential estimation, riverine habitat suitability and ecological assessments, etc.). We apply a geostatistical procedure based on Top-kriging, which has been recently shown to be particularly reliable and easy-to-use regionalization approach, employing two different type of streamflow data: pan-European E-HYPE simulations (http://hypeweb.smhi.se/europehype) and observed daily streamflow series collected in two pilot study regions, i.e. Tyrol (merging data from Austrian and Italian stream gauging networks) and Sweden. The merger of the two study regions results in a rather large area (~450000 km2) and might be considered as a proxy for a pan-European application of the approach. In a first phase, we implement a bidirectional validation, i.e. E-HYPE catchments are set as training sites to predict FDCs at the same sites where observed data are available, and vice-versa. Such a validation procedure reveals (1) the usability of the proposed approach for predicting the FDCs over the entire river network of interest using alternatively observed data and E-HYPE simulations and (2) the accuracy of E-HYPE-based predictions of FDCs in ungauged sites. In a

  1. A Hydrological Perspective to Advance Understanding of the Water Cycle

    NASA Astrophysics Data System (ADS)

    Berghuijs, W.

    2014-12-01

    In principle hydrologists are scientists that study relationships within the water cycle. Yet, current technology makes it tempting for hydrology students to lose their "hydrological perspective" and become instead full-time computer programmers or statisticians. I assert that students should ensure their hydrological perspective thrives, notwithstanding the importance and possibilities of current technology. This perspective is necessary to advance the science of hydrology. As other hydrologists have pondered similar views before, I make no claims of originality here. I just hope that in presenting my perspective on this issue I may spark the interest of other early career hydrologists.

  2. It takes a community to raise a hydrologist: the Modular Curriculum for Hydrologic Advancement (MOCHA)

    NASA Astrophysics Data System (ADS)

    Wagener, T.; Kelleher, C.; Weiler, M.; McGlynn, B.; Gooseff, M.; Marshall, L.; Meixner, T.; McGuire, K.; Gregg, S.; Sharma, P.; Zappe, S.

    2012-09-01

    Protection from hydrological extremes and the sustainable supply of hydrological services in the presence of changing climate and lifestyles as well as rocketing population pressure in many parts of the world are the defining societal challenges for hydrology in the 21st century. A review of the existing literature shows that these challenges and their educational consequences for hydrology were foreseeable and were even predicted by some. However, surveys of the current educational basis for hydrology also clearly demonstrate that hydrology education is not yet ready to prepare students to deal with these challenges. We present our own vision of the necessary evolution of hydrology education, which we implemented in the Modular Curriculum for Hydrologic Advancement (MOCHA). The MOCHA project is directly aimed at developing a community-driven basis for hydrology education. In this paper we combine literature review, community survey, discussion and assessment to provide a holistic baseline for the future of hydrology education. The ultimate objective of our educational initiative is to enable educators to train a new generation of "renaissance hydrologists," who can master the holistic nature of our field and of the problems we encounter.

  3. Acting, predicting and intervening in a socio-hydrological world

    NASA Astrophysics Data System (ADS)

    Lane, S. N.

    2014-03-01

    This paper asks a simple question: if humans and their actions co-evolve with hydrological systems (Sivapalan et al., 2012), what is the role of hydrological scientists, who are also humans, within this system? To put it more directly, as traditionally there is a supposed separation of scientists and society, can we maintain this separation as socio-hydrologists studying a socio-hydrological world? This paper argues that we cannot, using four linked sections. The first section draws directly upon the concern of science-technology studies to make a case to the (socio-hydrological) community that we need to be sensitive to constructivist accounts of science in general and socio-hydrology in particular. I review three positions taken by such accounts and apply them to hydrological science, supported with specific examples: (a) the ways in which scientific activities frame socio-hydrological research, such that at least some of the knowledge that we obtain is constructed by precisely what we do; (b) the need to attend to how socio-hydrological knowledge is used in decision-making, as evidence suggests that hydrological knowledge does not flow simply from science into policy; and (c) the observation that those who do not normally label themselves as socio-hydrologists may actually have a profound knowledge of socio-hydrology. The second section provides an empirical basis for considering these three issues by detailing the history of the practice of roughness parameterisation, using parameters like Manning's n, in hydrological and hydraulic models for flood inundation mapping. This history sustains the third section that is a more general consideration of one type of socio-hydrological practice: predictive modelling. I show that as part of a socio-hydrological analysis, hydrological prediction needs to be thought through much more carefully: not only because hydrological prediction exists to help inform decisions that are made about water management; but also because

  4. Challenges and Opportunities for Hydrology Education in a Changing World - The Modular Curriculum for Hydrologic Advancement

    NASA Astrophysics Data System (ADS)

    McGlynn, Brian; Wagener, Thorsten; Marshall, Lucy; McGuire, Kevin; Meixner, Thomas; Weiler, Markus; Gooseff, Michael; Kelleher, Christa; Gregg, Susan

    2010-05-01

    ‘It takes a village to raise a child', but who does it take to educate a hydrologist who can solve today's and tomorrow's problems? Hydrology is inherently an interdisciplinary science, and therefore requires interdisciplinary training. We believe that the demands on current and future hydrologists will continue to increase, while training at undergraduate and graduate levels has not kept pace. How do we, as university faculty, educate hydrologists capable of solving complex problems in an interdisciplinary environment considering that current educators have often been taught in narrow traditional disciplines? We suggest a unified community effort to change the way that hydrologists are educated. The complexity of the task is ever increasing. Analysis techniques and tools required for solving emerging problems have to evolve away from focusing mainly on the analysis of past behavior because baselines are shifting as the world changes. The difficulties of providing an appropriate education are also increasing, especially given the growing demands on faculty time. To support hydrology educators and improve hydrology education, we have started a faculty community of educators (REACH) and implemented the Modular Curriculum for Hydrologic Advancement (MOCHA, http://www.mocha.psu.edu/). The goal of this effort is to support hydrology faculty as they educate hydrologists that can solve interdisciplinary problems that go far beyond the traditional disciplinary biased hydrology education most of us have experienced as students. Our current objective is to create an evolving core curriculum for university hydrology education, based on modern pedagogical standards, freely available to and developed and reviewed by the worldwide hydrologic community. We seek to establish an online faculty learning community for hydrology education and capacity building. In this presentation we discuss the results of a recent survey on current hydrology education (to compare with the state of

  5. Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Weerts, A. H.; Clark, M.; Hendricks Franssen, H.-J.; Kumar, S.; Moradkhani, H.; Seo, D.-J.; Schwanenberg, D.; Smith, P.; van Dijk, A. I. J. M.; van Velzen, N.; He, M.; Lee, H.; Noh, S. J.; Rakovec, O.; Restrepo, P.

    2012-03-01

    Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented into operational forecast systems to improve the skill of forecasts to better inform real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, The Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical considerations in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modelling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers

  6. Advancing data assimilation in operational hydrologic forecasting: progresses, challenges, and emerging opportunities

    NASA Astrophysics Data System (ADS)

    Liu, Y.; Weerts, A. H.; Clark, M.; Hendricks Franssen, H.-J.; Kumar, S.; Moradkhani, H.; Seo, D.-J.; Schwanenberg, D.; Smith, P.; van Dijk, A. I. J. M.; van Velzen, N.; He, M.; Lee, H.; Noh, S. J.; Rakovec, O.; Restrepo, P.

    2012-10-01

    Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, the Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical aspects in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA

  7. Advancing Data Assimilation in Operational Hydrologic Forecasting: Progresses, Challenges, and Emerging Opportunities

    NASA Technical Reports Server (NTRS)

    Liu, Yuqiong; Weerts, A.; Clark, M.; Hendricks Franssen, H.-J; Kumar, S.; Moradkhani, H.; Seo, D.-J.; Schwanenberg, D.; Smith, P.; van Dijk, A. I. J. M.; van Velzen, N.; He, M.; Lee, H.; Noh, S. J.; Rakovec, O.; Restrepo, P.

    2012-01-01

    Data assimilation (DA) holds considerable potential for improving hydrologic predictions as demonstrated in numerous research studies. However, advances in hydrologic DA research have not been adequately or timely implemented in operational forecast systems to improve the skill of forecasts for better informed real-world decision making. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. The need for effective DA of useful hydrologic data into the forecast process has become increasingly recognized in recent years. This motivated a hydrologic DA workshop in Delft, the Netherlands in November 2010, which focused on advancing DA in operational hydrologic forecasting and water resources management. As an outcome of the workshop, this paper reviews, in relevant detail, the current status of DA applications in both hydrologic research and operational practices, and discusses the existing or potential hurdles and challenges in transitioning hydrologic DA research into cost-effective operational forecasting tools, as well as the potential pathways and newly emerging opportunities for overcoming these challenges. Several related aspects are discussed, including (1) theoretical or mathematical aspects in DA algorithms, (2) the estimation of different types of uncertainty, (3) new observations and their objective use in hydrologic DA, (4) the use of DA for real-time control of water resources systems, and (5) the development of community-based, generic DA tools for hydrologic applications. It is recommended that cost-effective transition of hydrologic DA from research to operations should be helped by developing community-based, generic modeling and DA tools or frameworks, and through fostering collaborative efforts among hydrologic modellers, DA

  8. Advances in Data Assimilation for Operational Hydrologic Forecasting

    NASA Astrophysics Data System (ADS)

    Weerts, Albrecht; Liu, Yuqiong

    2011-02-01

    International Workshop on Data Assimilation for Operational Hydrologic Forecasting and Water Resources Management; Delft, Netherlands, 1-3 November 2010 ; The abundance of new hydrologic observations (in situ or remotely sensed) in the past couple of decades has stimulated a great deal of research into the use of these observations for improved hydrologic predictions via model-data infusion applications. Generally speaking, however, hydrologic data assimilation (DA) as an objective tool for reducing predictive uncertainty is not yet technically ready for operational hydrologic forecasting and water resources management. This is due in part to a lack of mechanisms to properly quantify the uncertainty in observations and forecast models in real-time forecasting situations and to conduct the merging of data and models in a way that is adequately efficient and transparent to operational forecasters. Nevertheless, the need for effective assimilation of useful data into the forecast process is increasing. Within the framework of the Hydrologic Ensemble Prediction Experiment (HEPEX; http://www.hepex.org/), a workshop was held in the Netherlands. The overall goal of the workshop was to develop and foster community-based efforts for collaborative research, development, and synthesis of techniques and tools for hydrologic data assimilation and for the cost-effective transition of these techniques and tools from research to operations.

  9. Acting, predicting and intervening in a socio-hydrological world

    NASA Astrophysics Data System (ADS)

    Lane, S. N.

    2013-08-01

    This paper asks a simple question: if humans and their actions co-evolve with hydrological systems (Sivapalan and Blöschl, 2012), what is the role of those humans who are simultaneously hydrological scientists, bound up within this system? To put it more directly, can we, as socio-hydrologists study the socio-hydrological world in isolation from that world in a way that mirrors the supposed separation between scientists and society? I answer this question, in the negative, from three linked perspectives. The first draws directly upon science-technology studies to make a case to the (socio-hydrological) community that we need to be sensitive to constructivist accounts of science in general and hydrology in particular. I review three positions taken by such accounts and apply them to hydrological science, supported with specific examples: (a) the philosophical critique of the claimed abstraction of scientists and scientific activity from the socio-hydrological world; (b) the way in which hydrological science is embedded in wider societal decision-making; and (c) the recognition that socio-hydrological knowledge is much more distributed than we as (socio-)hydrologists commonly recognise. For the second perspective, I consider predictive modelling as a socio-hydrological practice. I draw upon wider studies of the practice of modelling, coupled to empirical evidence for one element of hydrological modelling, roughness parameterisation, to consider how it is that socio-hydrological modellers come to believe in the predictive models that they use. This will show that if predictive modelling is to be more than analytical, that if it is to effect more sustainable socio-hydrological futures, then we need to rethink the basic tenets of how we practice predictive modelling. These first two perspectives are themselves, in combination, analytical, prone to the criticism that they cause us to degenerate into an "anything goes" relationship with the world around us. Thus, in a

  10. Hydrological partitioning in the critical zone: Recent advances and opportunities for developing transferable understanding of water cycle dynamics

    NASA Astrophysics Data System (ADS)

    Brooks, Paul D.; Chorover, Jon; Fan, Ying; Godsey, Sarah E.; Maxwell, Reed M.; McNamara, James P.; Tague, Christina

    2015-09-01

    Hydrology is an integrative discipline linking the broad array of water-related research with physical, ecological, and social sciences. The increasing breadth of hydrological research, often where subdisciplines of hydrology partner with related sciences, reflects the central importance of water to environmental science, while highlighting the fractured nature of the discipline itself. This lack of coordination among hydrologic subdisciplines has hindered the development of hydrologic theory and integrated models capable of predicting hydrologic partitioning across time and space. The recent development of the concept of the critical zone (CZ), an open system extending from the top of the canopy to the base of groundwater, brings together multiple hydrological subdisciplines with related physical and ecological sciences. Observations obtained by CZ researchers provide a diverse range of complementary process and structural data to evaluate both conceptual and numerical models. Consequently, a cross-site focus on "critical zone hydrology" has potential to advance the discipline of hydrology and to facilitate the transition of CZ observatories into a research network with immediate societal relevance. Here we review recent work in catchment hydrology and hydrochemistry, hydrogeology, and ecohydrology that highlights a common knowledge gap in how precipitation is partitioned in the critical zone: "how is the amount, routing, and residence time of water in the subsurface related to the biogeophysical structure of the CZ?" Addressing this question will require coordination among hydrologic subdisciplines and interfacing sciences, and catalyze rapid progress in understanding current CZ structure and predicting how climate and land cover changes will affect hydrologic partitioning.

  11. Predicting Epileptic Seizures in Advance

    PubMed Central

    Moghim, Negin; Corne, David W.

    2014-01-01

    Epilepsy is the second most common neurological disorder, affecting 0.6–0.8% of the world's population. In this neurological disorder, abnormal activity of the brain causes seizures, the nature of which tend to be sudden. Antiepileptic Drugs (AEDs) are used as long-term therapeutic solutions that control the condition. Of those treated with AEDs, 35% become resistant to medication. The unpredictable nature of seizures poses risks for the individual with epilepsy. It is clearly desirable to find more effective ways of preventing seizures for such patients. The automatic detection of oncoming seizures, before their actual onset, can facilitate timely intervention and hence minimize these risks. In addition, advance prediction of seizures can enrich our understanding of the epileptic brain. In this study, drawing on the body of work behind automatic seizure detection and prediction from digitised Invasive Electroencephalography (EEG) data, a prediction algorithm, ASPPR (Advance Seizure Prediction via Pre-ictal Relabeling), is described. ASPPR facilitates the learning of predictive models targeted at recognizing patterns in EEG activity that are in a specific time window in advance of a seizure. It then exploits advanced machine learning coupled with the design and selection of appropriate features from EEG signals. Results, from evaluating ASPPR independently on 21 different patients, suggest that seizures for many patients can be predicted up to 20 minutes in advance of their onset. Compared to benchmark performance represented by a mean S1-Score (harmonic mean of Sensitivity and Specificity) of 90.6% for predicting seizure onset between 0 and 5 minutes in advance, ASPPR achieves mean S1-Scores of: 96.30% for prediction between 1 and 6 minutes in advance, 96.13% for prediction between 8 and 13 minutes in advance, 94.5% for prediction between 14 and 19 minutes in advance, and 94.2% for prediction between 20 and 25 minutes in advance. PMID:24911316

  12. A seasonal hydrologic ensemble prediction system for water resource management

    NASA Astrophysics Data System (ADS)

    Luo, L.; Wood, E. F.

    2006-12-01

    A seasonal hydrologic ensemble prediction system, developed for the Ohio River basin, has been improved and expanded to several other regions including the Eastern U.S., Africa and East Asia. The prediction system adopts the traditional Extended Streamflow Prediction (ESP) approach, utilizing the VIC (Variable Infiltration Capacity) hydrological model as the central tool for producing ensemble prediction of soil moisture, snow and streamflow with lead times up to 6-month. VIC is forced by observed meteorology to estimate the hydrological initial condition prior to the forecast, but during the forecast period the atmospheric forcing comes from statistically downscaled, seasonal forecast from dynamic climate models. The seasonal hydrologic ensemble prediction system is currently producing realtime seasonal hydrologic forecast for these regions on a monthly basis. Using hindcasts from a 19-year period (1981-1999), during which seasonal hindcasts from NCEP Climate Forecast System (CFS) and European Union DEMETER project are available, we evaluate the performance of the forecast system over our forecast regions. The evaluation shows that the prediction system using the current forecast approach is able to produce reliable and accurate precipitation, soil moisture and streamflow predictions. The overall skill is much higher then the traditional ESP. In particular, forecasts based on multiple climate model forecast are more skillful than single model-based forecast. This emphasizes the significant need for producing seasonal climate forecast with multiple climate models for hydrologic applications. Forecast from this system is expected to provide very valuable information about future hydrologic states and associated risks for end users, including water resource management and financial sectors.

  13. Advances in borehole geophysics for hydrology

    SciTech Connect

    Nelson, P.H.

    1982-01-01

    Borehole geophysical methods provide vital subsurface information on rock properties, fluid movement, and the condition of engineered borehole structures. Within the first category, salient advances include the continuing improvement of the borehole televiewer, refinement of the electrical conductivity dipmeter for fracture characterization, and the development of a gigahertz-frequency electromagnetic propagation tool for water saturation measurements. The exploration of the rock mass between boreholes remains a challenging problem with high potential; promising methods are now incorporating high-density spatial sampling and sophisticated data processing. Flow-rate measurement methods appear adequate for all but low-flow situations. At low rates the tagging method seems the most attractive. The current exploitation of neutron-activation techniques for tagging means that the wellbore fluid itself is tagged, thereby eliminating the mixing of an alien fluid into the wellbore. Another method uses the acoustic noise generated by flow through constrictions and in and behind casing to detect and locate flaws in the production system. With the advent of field-recorded digital data, the interpretation of logs from sedimentary sequences is now reaching a sophisticated level with the aid of computer processing and the application of statistical methods. Lagging behind are interpretive schemes for the low-porosity, fracture-controlled igneous and metamorphic rocks encountered in the geothermal reservoirs and in potential waste-storage sites. Progress is being made on the general problem of fracture detection by use of electrical and acoustical techniques, but the reliable definition of permeability continues to be an elusive goal.

  14. Ensemble prediction and data assimilation for operational hydrology

    NASA Astrophysics Data System (ADS)

    Seo, Dong-Jun; Liu, Yuqiong; Moradkhani, Hamid; Weerts, Albrecht

    2014-11-01

    Ensemble methodologies are fast gaining popularity and acceptance as a new paradigm for operational hydrologic forecasting and risk-based water resources management. This trend reflects the recognition that there will always be significant uncertainties in hydrologic predictions due to limited predictability in atmospheric forcings, errors in model structures, initial condition, parameters and states, and unknown/unknowable human control of the hydrologic cycle (Krzysztofowicz, 1999; Seo et al., 2006; Liu and Gupta, 2007; Todini, 2008; Weerts et al., 2011; DeChant and Moradkhani, 2011; Madadgar et al., 2014), that quantification of source-specific uncertainty affords cost-effective improvement of the forecast system and process (Demargne et al. 2014; Verkade et al., 2013; Moradkhani et al., 2012), and that ensemble approaches allow objective utilization of multiple sources of data and models that are very often complementary (Georgakakos et al. 2004; Parrish et al., 2012).

  15. Evaluation of Community Land Model Hydrologic Predictions

    NASA Astrophysics Data System (ADS)

    Li, K. Y.; Lettenmaier, D. P.; Bohn, T.; Delire, C.

    2005-12-01

    Confidence in representation and parameterization of land surface processes in coupled land-atmosphere models is strongly dependent on a diversity of opportunities for model testing, since such coupled models are usually intended for application in a wide range of conditions (regional models) or globally. Land surface models have been increasing in complexity over the past decade, which has increased the demands on data sets appropriate for model testing and evaluation. In this study, we compare the performance of two commonly used land surface schemes - the Variable Infiltration Capacity (VIC) and Community Land Model (CLM) with respect to their ability to reproduce observed water and energy fluxes in off-line tests for two large river basins with contrasting hydroclimatic conditions spanning the range from temperate continental to arctic, and for five point (column flux) sites spanning the range from tropical to arctic. The two large river basins are the Arkansas-Red in U.S. southern Great Plains, and the Torne-Kalix in northern Scandinavia. The column flux evaluations are for a tropical forest site at Reserva Jaru (ABRACOS) in Brazil, a prairie site (FIFE) near Manhattan, Kansas in the central U.S., a soybean site at Caumont (HAPEX-Monbilhy) in France, a meadow site at Cabauw in the Netherlands, and a small grassland catchment at Valday, Russia. The results indicate that VIC can reasonably well capture the land surface biophysical processes, while CLM is somewhat less successful. We suggest changes to the CLM parameterizations that would improve its general performance with respect to its representation of land surface hydrologic processes.

  16. On the sources of hydrological prediction uncertainty in the Amazon

    NASA Astrophysics Data System (ADS)

    Paiva, R. C. D.; Collischonn, W.; Bonnet, M. P.; Gonçalves, L. G. G.

    2012-03-01

    Recent extreme events in the Amazon River basin and the vulnerability of local population motivate the development of hydrological forecast systems (HFSs) using process based models for this region. In this direction, the knowledge of the source of errors in HFSs may guide the choice on improving model structure, model forcings or developing data assimilation (DA) systems for estimation of initial model states. We evaluate the relative importance of hydrologic initial conditions (ICs) and model meteorological forcings (MFs) errors (precisely precipitation) as sources of stream flow forecast uncertainty in the Amazon River basin. We used a hindcast approach developed by Wood and Lettenmaier (2008) that contrasts Ensemble Streamflow Prediction (ESP) and a reverse Ensemble Streamflow Prediction (reverse-ESP). Simulations were performed using the physically-based and distributed hydrological model MGB-IPH, comprising surface energy and water balance, soil water, river and floodplain hydrodynamics processes. Model was forced using TRMM 3B42 precipitation estimates. Results show that uncertainty on initial conditions play an important role for discharge predictability even for large lead times (~1 to 3 months) on main Amazonian Rivers. ICs of surface waters state variables are the major source of hydrological forecast uncertainty, mainly in rivers with low slope and large floodplains. ICs of groundwater state variables are important mostly during low flow period and southeast part of the Amazon, where lithology and the strong rainfall seasonality with a marked dry season may be the explaining factors. Analyses indicate that hydrological forecasts based on a hydrological model forced with historical meteorological data and optimal initial conditions, may be feasible. Also, development of DA methods is encouraged for this region.

  17. Can assimilation of crowdsourced data in hydrological modelling improve flood prediction?

    NASA Astrophysics Data System (ADS)

    Mazzoleni, Maurizio; Verlaan, Martin; Alfonso, Leonardo; Monego, Martina; Norbiato, Daniele; Ferri, Miche; Solomatine, Dimitri P.

    2017-02-01

    Monitoring stations have been used for decades to properly measure hydrological variables and better predict floods. To this end, methods to incorporate these observations into mathematical water models have also been developed. Besides, in recent years, the continued technological advances, in combination with the growing inclusion of citizens in participatory processes related to water resources management, have encouraged the increase of citizen science projects around the globe. In turn, this has stimulated the spread of low-cost sensors to allow citizens to participate in the collection of hydrological data in a more distributed way than the classic static physical sensors do. However, two main disadvantages of such crowdsourced data are the irregular availability and variable accuracy from sensor to sensor, which makes them challenging to use in hydrological modelling. This study aims to demonstrate that streamflow data, derived from crowdsourced water level observations, can improve flood prediction if integrated in hydrological models. Two different hydrological models, applied to four case studies, are considered. Realistic (albeit synthetic) time series are used to represent crowdsourced data in all case studies. In this study, it is found that the data accuracies have much more influence on the model results than the irregular frequencies of data availability at which the streamflow data are assimilated. This study demonstrates that data collected by citizens, characterized by being asynchronous and inaccurate, can still complement traditional networks formed by few accurate, static sensors and improve the accuracy of flood forecasts.

  18. Reducing uncertainty in predictions in ungauged basins by combining hydrologic indices regionalization and multiobjective optimization

    NASA Astrophysics Data System (ADS)

    Zhang, Zhenxing; Wagener, Thorsten; Reed, Patrick; Bhushan, Rashi

    2008-12-01

    Approaches to predictions in ungauged basins have so far mainly focused on a priori parameter estimates from physical watershed characteristics or on the regionalization of model parameters. Recent studies suggest that the regionalization of hydrologic indices (e.g., streamflow characteristics) provides an additional way to extrapolate information about the expected watershed response to ungauged locations for use in continuous watershed modeling. This study contributes a novel multiobjective framework for identifying behavioral parameter ensembles for ungauged basins using suites of regionalized hydrologic indices. The new formulation enables the use of multiobjective optimization algorithms for the identification of model ensembles for predictions in ungauged basins for the first time. Application of the new formulation to 30 watersheds located in England and Wales and comparison of the results with a Monte Carlo approach demonstrate that the new formulation will significantly advance our ability to reduce the uncertainty of predictions in ungauged basins.

  19. ARCHES: Advancing Research & Capacity in Hydrologic Education and Science

    NASA Astrophysics Data System (ADS)

    Milewski, A.; Fryar, A. E.; Durham, M. C.; Schroeder, P.; Agouridis, C.; Hanley, C.; Rotz, R. R.

    2013-12-01

    Educating young scientists and building capacity on a global scale is pivotal towards better understanding and managing our water resources. Based on this premise the ARCHES (Advancing Research & Capacity in Hydrologic Education and Science) program has been established. This abstract provides an overview of the program, links to access information, and describes the activities and outcomes of student participants from the Middle East and North Africa. The ARCHES program (http://arches.wrrs.uga.edu) is an integrated hydrologic education approach using online courses, field programs, and various hands-on workshops. The program aims to enable young scientists to effectively perform the high level research that will ultimately improve quality of life, enhance science-based decision making, and facilitate collaboration. Three broad, interlinked sets of activities are incorporated into the ARCHES program: (A1) the development of technical expertise, (A2) the development of professional contacts and skills, and (A3) outreach and long-term sustainability. The development of technical expertise (A1) is implemented through three progressive instructional sections. Section 1: Students were guided through a series of online lectures and exercises (Moodle: http://wrrs.uga.edu/moodle) covering three main topics (Remote Sensing, GIS, and Hydrologic Modeling). Section 2: Students participated in a hands-on workshop hosted at the University of Georgia's Water Resources and Remote Sensing Laboratory (WRRSL). Using ENVI, ArcGIS, and ArcSWAT, students completed a series of lectures and real-world applications (e.g., Development of Hydrologic Models). Section 3: Students participated in field studies (e.g., measurements of infiltration, recharge, streamflow, and water-quality parameters) conducted by U.S. partners and international collaborators in the participating countries. The development of professional contacts and skills (A2) was achieved through the promotion of networking

  20. Improving predictive certainty and system understanding with watershed hydrology models

    NASA Astrophysics Data System (ADS)

    Kelleher, C.; McGlynn, B. L.; Wagener, T.

    2015-12-01

    Modeling at the intersection of climate variability and hydrology is complicated by uncertainties that make predicting physical behavior a challenge. Environmental models used to simulate how climate will impact hydrology are typically complex, demand many spatial and temporal data inputs, contain numerous parameters, and can be computationally expensive. Distributed models in particular complicate the assessment of how uncertainty in the model framework, inputs, parameters, and observations impact predictive uncertainty. In addition, future climate perturbations may alter the magnitude of these uncertainties. Here, we focus on model parameters as a key source of uncertainty. Identifying those model parameters that most influence the predictions at a particular place can reduce a complex, multidimensional problem to a simpler form. We demonstrate how sensitivity analysis in the absence of observational streamflow can be used to identify sensitive model parameters by conditioning a model on climate data and a priori parameter ranges. We apply this approach to five headwater catchments in the Tenderfoot Creek Experimental Forest located in central Montana using the Distributed Hydrology-Soil-Vegetation Model. Across these five sub-catchments, climate clearly organizes parameter sensitivities. To further explore the relationship between parameter sensitivities and climate, we assess how parameter sensitivities change when meteorological forcing data is perturbed to reflect natural variability at the site. This general approach can support uncertainty reduction. However, parameter equifinality will still impact finer scale predictions of any environmental variable in space and time. As such, improving our certainty in environmental predictions should evaluate point predictions as well as simulations of internal catchment behavior, and must not only rely on our use of computational methods but on our basic understanding of system functioning.

  1. Advancing reservoir operation description in physically based hydrological models

    NASA Astrophysics Data System (ADS)

    Anghileri, Daniela; Giudici, Federico; Castelletti, Andrea; Burlando, Paolo

    2016-04-01

    Last decades have seen significant advances in our capacity of characterizing and reproducing hydrological processes within physically based models. Yet, when the human component is considered (e.g. reservoirs, water distribution systems), the associated decisions are generally modeled with very simplistic rules, which might underperform in reproducing the actual operators' behaviour on a daily or sub-daily basis. For example, reservoir operations are usually described by a target-level rule curve, which represents the level that the reservoir should track during normal operating conditions. The associated release decision is determined by the current state of the reservoir relative to the rule curve. This modeling approach can reasonably reproduce the seasonal water volume shift due to reservoir operation. Still, it cannot capture more complex decision making processes in response, e.g., to the fluctuations of energy prices and demands, the temporal unavailability of power plants or varying amount of snow accumulated in the basin. In this work, we link a physically explicit hydrological model with detailed hydropower behavioural models describing the decision making process by the dam operator. In particular, we consider two categories of behavioural models: explicit or rule-based behavioural models, where reservoir operating rules are empirically inferred from observational data, and implicit or optimization based behavioural models, where, following a normative economic approach, the decision maker is represented as a rational agent maximising a utility function. We compare these two alternate modelling approaches on the real-world water system of Lake Como catchment in the Italian Alps. The water system is characterized by the presence of 18 artificial hydropower reservoirs generating almost 13% of the Italian hydropower production. Results show to which extent the hydrological regime in the catchment is affected by different behavioural models and reservoir

  2. Advances in river ice hydrology 1999-2003

    NASA Astrophysics Data System (ADS)

    Morse, Brian; Hicks, Faye

    2005-01-01

    In the period 1999 to 2003, river ice has continued to have important socio-economic impacts in Canada and other Nordic countries. Concurrently, there have been many important advances in all areas of Canadian research into river ice engineering and hydrology. For example: (1) River ice processes were highlighted in two special journal issues (Canadian Journal of Civil Engineering in 2003 and Hydrological Processes in 2002) and at five conferences (Canadian Committee on River Ice Processes and the Environment in 1999, 2001 and 2003, and International Association of Hydraulic Research in 2000 and 2002). (2) A number of workers have clearly advanced our understanding of river ice processes by bringing together disparate information in comprehensive review articles. (3) There have been significant advances in river ice modelling. For example, both one-dimensional (e.g. RIVICE, RIVJAM, ICEJAM, HEC-RAS, etc.) and two-dimensional (2-D; www.river2d.ca) public-domain ice-jam models are now available. Work is ongoing to improve RIVER2D, and a commercial 2-D ice-process model is being developed. (4) The 1999-2003 period is notable for the number of distinctly hydrological and ecological studies. On the quantitative side, many are making efforts to determine streamflow during the winter period. On the ecological side, some new publications have addressed the link to water quality (temperature, dissolved oxygen, nutrients and pollutants), and others have dealt with sediment transport and geomorphology (particularly as it relates to break-up), stream ecology (plants, food cycle, etc.) and fish habitat.There is the growing recognition, that these types of study require collaborative efforts. In our view, the main areas requiring further work are: (1) to interface geomorphological and habitat models with quantitative river ice hydrodynamic models; (2) to develop a manager's toolbox (database management, remote sensing, forecasting, intervention methodologies, etc.) to enable

  3. Multifractal prediction of hydrological extremes and the RIO research program

    NASA Astrophysics Data System (ADS)

    Tchiguirinskaia, I.; Schertzer, D. J.; Hubert, P.; Bendjoudi, H.; Lovejoy, S.

    2004-05-01

    One of the main research themes of the current RIO (Risque Inondation / Flood Risk) program of the Ministry of Environment in France is the prediction of extreme hydrological events and the development of new tools for their prediction, prevention and alert. Deterministic models based on various physical and/or statistical approaches are still not capable to capture the phenomena of extreme precipitation and floods. It is well known that one of the main difficulties for the description of hydro-meteorological extremes is the colossal variability of their intensities over a wide range of space-time scales. To contribute to the RIO program, our group uses the multifractal framework not only to explain the power-law fall-off of probability distributions for hydrological-meteorological extremes, but also to explore a link between the observed variability and the underlying physics. We analyze space-time distributions of precipitation and discharges over widely different hydrological regions. A multifractal data analysis performed in the space-time domain produces - amongst other results - a physically-based tool for the clear distinction and multifractal description of flash-floods. We illustrate these methods on two recent flooding events in France: the Abbeville phreatic floods in 2001 and the flash floods in Gard in 2002.

  4. Uncertainty of hydrological signatures predicted for ungauged basins

    NASA Astrophysics Data System (ADS)

    Westerberg, Ida; Coxon, Gemma; Wagener, Thorsten; McMillan, Hilary; Montanari, Alberto; Castellarin, Attilio; Freer, Jim

    2015-04-01

    Reliable information about the hydrological behaviour of an ungauged catchment is needed for a wide range of water resource management decisions, and it has been a central topic of research in hydrology for the last decade through the Predictions in Ungauged Basins initiative. Such information derived as an index value from observed data in a gauged basin is known as a hydrological signature, and has been used in a variety of studies for, e.g., change detection, model calibration and diagnostic model-structural evaluation. When signature values are predicted for ungauged catchments, they are not only affected by uncertainties in the regionalisation procedure, but also by uncertainties in the observed data for the gauged catchments used for the prediction. In this study we investigated a method for regionalisation of hydrological signatures to ungauged catchments that accounted for both of these uncertainty sources. This also enabled us to assess the role of the different uncertainty sources in defining the overall regionalisation uncertainty - e.g. for what signatures and conditions are the data uncertainties more important than the regionalisation uncertainties and vice versa? The study was made using an extensive dataset of catchments in England and Wales, incorporating gauging (stage-discharge) data from all the discharge stations. The uncertainties were assessed within a Monte Carlo framework that incorporated different types of uncertainties in the data as well as uncertainties in the regionalisation procedure. The regionalisation results had a high reliability when the gauged discharge uncertainties were accounted for. The magnitude of the gauged uncertainty was often larger than the differences between deterministic gauged and regionalised values, which shows that deterministic comparisons are insufficient for evaluation of regionalisation results. The results were better for medium and high-flow signatures than for low-flow signatures. The data

  5. Advancing Drought Understanding, Monitoring and Prediction

    NASA Technical Reports Server (NTRS)

    Mariotti, Annarita; Schubert, Siegfried D.; Mo, Kingtse; Peters-Lidard, Christa; Wood, Andy; Pulwarty, Roger; Huang, Jin; Barrie, Dan

    2013-01-01

    Having the capacity to monitor droughts in near-real time and providing accurate drought prediction from weeks to seasons in advance can greatly reduce the severity of social and economic damage caused by drought, a leading natural hazard for North America. The congressional mandate to establish the National Integrated Drought Information System (NIDIS; Public Law 109-430) in 2006 was a major impulse to develop, integrate, and provide drought information to meet the challenges posed by this hazard. Significant progress has been made on many fronts. On the research front, efforts by the broad scientific community have resulted in improved understanding of North American droughts and improved monitoring and forecasting tools. We now have a better understanding of the droughts of the twentieth century including the 1930s "Dust Bowl"; we have developed a broader array of tools and datasets that enhance the official North American Drought Monitor based on different methodologies such as state-of-the-art land surface modeling (e.g., the North American Land Data Assimilation System) and remote sensing (e.g., the evaporative stress index) to better characterize the occurrence and severity of drought in its multiple manifestations. In addition, we have new tools for drought prediction [including the new National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2, for operational prediction and an experimental National Multimodel Ensemble] and have explored diverse methodologies including ensemble hydrologic prediction approaches. Broad NIDIS-inspired progress is influencing the development of a Global Drought Information System (GDIS) under the auspices of the World Climate Research Program. Despite these advances, current drought monitoring and forecasting capabilities still fall short of users' needs, especially the need for skillful and reliable drought forecasts at regional and local scales. To tackle this outstanding challenging problem

  6. Hydrology

    ERIC Educational Resources Information Center

    Sharp, John M., Jr.

    1978-01-01

    The past year saw a re-emphasis on the practical aspects of hydrology due to regional drought patterns, urban flooding, and agricultural and energy demands on water resources. Highlights of hydrologic symposia, publications, and events are included. (MA)

  7. Global scale hydrology - Advances in land surface modeling

    SciTech Connect

    Wood, E.F. )

    1991-01-01

    Research into global scale hydrology is an expanding area that includes researchers from the meteorology, climatology, ecology and hydrology communities. This paper reviews research in this area carried out in the United States during the last IUGG quadrennial period of 1987-1990. The review covers the representation of land-surface hydrologic processes for general circulation models (GCMs), sensitivity analysis of these representations on global hydrologic fields like precipitation, regional studies of climate that have global hydrologic implications, recent field studies and experiments whose aims are the improved understanding of land surface-atmospheric interactions, and the use of remotely sensed data for the further understanding of the spatial variability of surface hydrologic processes that are important at regional and global climate scales. 76 refs.

  8. Impact of modellers' decisions on hydrological a priori predictions

    NASA Astrophysics Data System (ADS)

    Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

    2014-06-01

    In practice, the catchment hydrologist is often confronted with the task of predicting discharge without having the needed records for calibration. Here, we report the discharge predictions of 10 modellers - using the model of their choice - for the man-made Chicken Creek catchment (6 ha, northeast Germany, Gerwin et al., 2009b) and we analyse how well they improved their prediction in three steps based on adding information prior to each following step. The modellers predicted the catchment's hydrological response in its initial phase without having access to the observed records. They used conceptually different physically based models and their modelling experience differed largely. Hence, they encountered two problems: (i) to simulate discharge for an ungauged catchment and (ii) using models that were developed for catchments, which are not in a state of landscape transformation. The prediction exercise was organized in three steps: (1) for the first prediction the modellers received a basic data set describing the catchment to a degree somewhat more complete than usually available for a priori predictions of ungauged catchments; they did not obtain information on stream flow, soil moisture, nor groundwater response and had therefore to guess the initial conditions; (2) before the second prediction they inspected the catchment on-site and discussed their first prediction attempt; (3) for their third prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step (1). Here, we detail the modeller's assumptions and decisions in accounting for the various processes. We document the prediction progress as well as the learning process resulting from the availability of added information. For the second and third steps, the progress in prediction quality is evaluated in relation to individual modelling experience and costs of

  9. Toward an Online Community of Educators: The Modular Curriculum for Hydrologic Advancement (MOCHA)

    NASA Astrophysics Data System (ADS)

    Kelleher, C.; Wagener, T.; Gooseff, M. N.; Gregg, S.; McGlynn, B. L.; Sharma, P.; Meixner, T.; Marshall, L. A.; McGuire, K. J.; Weiler, M.

    2009-12-01

    The field of hydrology encompasses a wide range of departments and disciplines, ranging from civil engineering to geography to geosciences. As a consequence, in-class hydrology education is often strongly biased towards the background of a single instructor, limiting the educational experience of the students and not allowing for a holistic approach to hydrology education. Recently established, the Modular Curriculum for Hydrologic Advancement (MOCHA) creates an online community of hydrologists from a range of backgrounds and disciplines to define the boundaries of an unbiased hydrology education and to jointly develop resources to overcome previous instructional limitations (http://www.mocha.psu.edu/). Our first objective is to create an evolving core curriculum for hydrology education freely available to, developed, evolved and reviewed by the worldwide hydrologic community. On a larger scale, we hope to raise the standard of hydrology education and to foster international collaboration and exchange. Our work began with an initial survey including over 100 hydrology educators to assess the state of current hydrology education. Based on the survey results, the MOCHA project was designed and implemented, and initial teaching material and pedagogical guidelines for good practice in teaching were prepared. This past fall and spring, we piloted the website and teaching material across several universities. The web-based MOCHA project has recently been opened to solicit contributions from the global hydrology community. Our presentation will focus on the overall vision behind MOCHA, lessons learned from our initial piloting, and current steps to achieve our vision.

  10. Statistical procedures for evaluating daily and monthly hydrologic model predictions

    USGS Publications Warehouse

    Coffey, M.E.; Workman, S.R.; Taraba, J.L.; Fogle, A.W.

    2004-01-01

    The overall study objective was to evaluate the applicability of different qualitative and quantitative methods for comparing daily and monthly SWAT computer model hydrologic streamflow predictions to observed data, and to recommend statistical methods for use in future model evaluations. Statistical methods were tested using daily streamflows and monthly equivalent runoff depths. The statistical techniques included linear regression, Nash-Sutcliffe efficiency, nonparametric tests, t-test, objective functions, autocorrelation, and cross-correlation. None of the methods specifically applied to the non-normal distribution and dependence between data points for the daily predicted and observed data. Of the tested methods, median objective functions, sign test, autocorrelation, and cross-correlation were most applicable for the daily data. The robust coefficient of determination (CD*) and robust modeling efficiency (EF*) objective functions were the preferred methods for daily model results due to the ease of comparing these values with a fixed ideal reference value of one. Predicted and observed monthly totals were more normally distributed, and there was less dependence between individual monthly totals than was observed for the corresponding predicted and observed daily values. More statistical methods were available for comparing SWAT model-predicted and observed monthly totals. The 1995 monthly SWAT model predictions and observed data had a regression Rr2 of 0.70, a Nash-Sutcliffe efficiency of 0.41, and the t-test failed to reject the equal data means hypothesis. The Nash-Sutcliffe coefficient and the R r2 coefficient were the preferred methods for monthly results due to the ability to compare these coefficients to a set ideal value of one.

  11. Impact of modellers' decisions on hydrological a priori predictions

    NASA Astrophysics Data System (ADS)

    Holländer, H. M.; Bormann, H.; Blume, T.; Buytaert, W.; Chirico, G. B.; Exbrayat, J.-F.; Gustafsson, D.; Hölzel, H.; Krauße, T.; Kraft, P.; Stoll, S.; Blöschl, G.; Flühler, H.

    2013-07-01

    The purpose of this paper is to stimulate a re-thinking of how we, the catchment hydrologists, could become reliable forecasters. A group of catchment modellers predicted the hydrological response of a man-made 6 ha catchment in its initial phase (Chicken Creek) without having access to the observed records. They used conceptually different model families. Their modelling experience differed largely. The prediction exercise was organized in three steps: (1) for the 1st prediction modellers received a basic data set describing the internal structure of the catchment (somewhat more complete than usually available to a priori predictions in ungauged catchments). They did not obtain time series of stream flow, soil moisture or groundwater response. (2) Before the 2nd improved prediction they inspected the catchment on-site and attended a workshop where the modellers presented and discussed their first attempts. (3) For their improved 3rd prediction they were offered additional data by charging them pro forma with the costs for obtaining this additional information. Holländer et al. (2009) discussed the range of predictions obtained in step 1. Here, we detail the modeller's decisions in accounting for the various processes based on what they learned during the field visit (step 2) and add the final outcome of step 3 when the modellers made use of additional data. We document the prediction progress as well as the learning process resulting from the availability of added information. For the 2nd and 3rd step, the progress in prediction quality could be evaluated in relation to individual modelling experience and costs of added information. We learned (i) that soft information such as the modeller's system understanding is as important as the model itself (hard information), (ii) that the sequence of modelling steps matters (field visit, interactions between differently experienced experts, choice of model, selection of available data, and methods for parameter guessing

  12. Recent developments for the advancement of hydrological modeling

    NASA Astrophysics Data System (ADS)

    Ehret, Uwe

    2016-04-01

    This talk will consist of three parts: In the first, I will pick up the major questions formulated in the session outline (theories to support hydrological model development, representation of emergent behavior, optimality principles and landscape structure in models, approaches for model evaluation and selection) and present and discuss recent examples for each. In the second part, I will reflect on what the consideration of the above desirables implies for the way we should structure and implement hydrological models. Finally, I will illustrate the latter point with examples from the CAOS model (a mesoscale hydrological model currently under construction in the framework of the Catchments As Organized Systems research group).

  13. Passive microwave (SSM/I) satellite predictions of valley glacier hydrology, Matanuska Glacier, Alaska

    USGS Publications Warehouse

    Kopczynski, S.E.; Ramage, J.; Lawson, D.; Goetz, S.; Evenson, E.; Denner, J.; Larson, G.

    2008-01-01

    We advance an approach to use satellite passive microwave observations to track valley glacier snowmelt and predict timing of spring snowmelt-induced floods at the terminus. Using 37 V GHz brightness temperatures (Tb) from the Special Sensor Microwave hnager (SSM/I), we monitor snowmelt onset when both Tb and the difference between the ascending and descending overpasses exceed fixed thresholds established for Matanuska Glacier. Melt is confirmed by ground-measured air temperature and snow-wetness, while glacier hydrologic responses are monitored by a stream gauge, suspended-sediment sensors and terminus ice velocity measurements. Accumulation area snowmelt timing is correlated (R2 = 0.61) to timing of the annual snowmelt flood peak and can be predicted within ??5 days. Copyright 2008 by the American Geophysical Union.

  14. Recent advances in nonparametric function estimation: Hydrologic applications

    NASA Astrophysics Data System (ADS)

    Lall, U.

    1995-07-01

    Nonparametric function estimation refers to methods that strive to approximate a target function locally, i.e., using data from a "small" neighborhood of the point of estimate. "Weak" assumptions, such as continuity of the target function and its differentiability to some order in the neighborhood, rather than an a priori assumption of the global form (e.g., linear or quadratic) of the entire target function are used. Traditionally, parametric assumptions (e.g., hydraulic conductivity is log normally distributed, floods follow a log Pearson III (LP3) distribution, annual stream flow is either log normal or gamma distributed, daily rainfall amounts are exponentially distributed, and the variograms of spatial hydrologic data follow a power law) have dominated statistical hydrologic estimation. Applications of nonparametric methods to some classical problems (frequency analysis, classification, spatial surface fitting, trend analysis, time series forecasting and simulation) of stochastic hydrology are reviewed.

  15. Improved understanding and prediction of the hydrologic response of highly urbanized catchments through development of the Illinois Urban Hydrologic Model

    NASA Astrophysics Data System (ADS)

    Cantone, Joshua; Schmidt, Arthur

    2011-08-01

    What happens to the rain in highly urbanized catchments? That is the question that urban hydrologists must ask themselves when trying to integrate the hydrologic and hydraulic processes that affect the hydrologic response of urban catchments. The Illinois Urban Hydrologic Model (IUHM) has been developed to help answer this question and improve understanding and prediction of hydrologic response in highly urbanized catchments. Urban catchments are significantly different than natural watersheds, but there are similarities that allow features of the pioneering geomorphologic instantaneous unit hydrograph concept developed for natural watersheds to be adapted to the urban setting. This probabilistically based approach is a marked departure from the traditional deterministic models used to design and simulate urban sewer systems and does not have the burdensome input data requirements that detailed deterministic models possess. Application of IUHM to the CDS-51 catchment located in the village of Dolton, Illinois, highlights the model's ability to predict the hydrologic response of the catchment as well as the widely accepted SWMM model and is in accordance with observed data recorded by the United States Geological Survey. In addition, the unique structure and organization of urban sewer networks make it possible to characterize a set of ratios for urban catchments that allow IUHM to be applied when detailed input data are not available.

  16. Advancing Collaboration through Hydrologic Data and Model Sharing

    NASA Astrophysics Data System (ADS)

    Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Band, L. E.; Merwade, V.; Couch, A.; Hooper, R. P.; Maidment, D. R.; Dash, P. K.; Stealey, M.; Yi, H.; Gan, T.; Castronova, A. M.; Miles, B.; Li, Z.; Morsy, M. M.

    2015-12-01

    HydroShare is an online, collaborative system for open sharing of hydrologic data, analytical tools, and models. It supports the sharing of and collaboration around "resources" which are defined primarily by standardized metadata, content data models for each resource type, and an overarching resource data model based on the Open Archives Initiative's Object Reuse and Exchange (OAI-ORE) standard and a hierarchical file packaging system called "BagIt". HydroShare expands the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated to include geospatial and multidimensional space-time datasets commonly used in hydrology. HydroShare also includes new capability for sharing models, model components, and analytical tools and will take advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. It also supports web services and server/cloud based computation operating on resources for the execution of hydrologic models and analysis and visualization of hydrologic data. HydroShare uses iRODS as a network file system for underlying storage of datasets and models. Collaboration is enabled by casting datasets and models as "social objects". Social functions include both private and public sharing, formation of collaborative groups of users, and value-added annotation of shared datasets and models. The HydroShare web interface and social media functions were developed using the Django web application framework coupled to iRODS. Data visualization and analysis is supported through the Tethys Platform web GIS software stack. Links to external systems are supported by RESTful web service interfaces to HydroShare's content. This presentation will introduce the HydroShare functionality developed to date and describe ongoing development of functionality to support collaboration and integration of data and models.

  17. Hydrology

    ERIC Educational Resources Information Center

    Sharp, John M.

    1977-01-01

    Lists many recent research projects in hydrology, including flow in fractured media, improvements in remote-sensing techniques, effects of urbanization on water resources, and developments in drainage basins. (MLH)

  18. Application of quantitative precipitation forecasting and precipitation ensemble prediction for hydrological forecasting

    NASA Astrophysics Data System (ADS)

    Tao, P.; Tie-Yuan, S.; Zhi-Yuan, Y.; Jun-Chao, W.

    2015-05-01

    The precipitation in the forecast period influences flood forecasting precision, due to the uncertainty of the input to the hydrological model. Taking the ZhangHe basin as the example, the research adopts the precipitation forecast and ensemble precipitation forecast product of the AREM model, uses the Xin Anjiang hydrological model, and tests the flood forecasts. The results show that the flood forecast result can be clearly improved when considering precipitation during the forecast period. Hydrological forecast based on Ensemble Precipitation prediction gives better hydrological forecast information, better satisfying the need for risk information for flood prevention and disaster reduction, and has broad development opportunities.

  19. Hydrology

    USGS Publications Warehouse

    Eisenbies, Mark H.; Hughes, W. Brian

    2000-01-01

    Hydrologic process are the main determinants of the type of wetland located on a site. Precipitation, groundwater, or flooding interact with soil properties and geomorphic setting to yield a complex matrix of conditions that control groundwater flux, water storage and discharge, water chemistry, biotic productivity, biodiversity, and biogeochemical cycling. Hydroperiod affects many abiotic factors that in turn determine plant and animal species composition, biodiversity, primary and secondary productivity, accumulation, of organic matter, and nutrient cycling. Because the hydrologic regime has a major influence on wetland functioning, understanding how hydrologic changes influence ecosystem processes is essential, especially in light of the pressures placed on remaining wetlands by society's demands for water resources and by potential global changes in climate.

  20. Demasking the integrated value of discharge - Advanced sensitivity analysis on the components of hydrological models

    NASA Astrophysics Data System (ADS)

    Guse, Björn; Pfannerstill, Matthias; Gafurov, Abror; Fohrer, Nicola; Gupta, Hoshin

    2016-04-01

    The hydrologic response variable most often used in sensitivity analysis is discharge which provides an integrated value of all catchment processes. The typical sensitivity analysis evaluates how changes in the model parameters affect the model output. However, due to discharge being the aggregated effect of all hydrological processes, the sensitivity signal of a certain model parameter can be strongly masked. A more advanced form of sensitivity analysis would be achieved if we could investigate how the sensitivity of a certain modelled process variable relates to the changes in a parameter. Based on this, the controlling parameters for different hydrological components could be detected. Towards this end, we apply the approach of temporal dynamics of parameter sensitivity (TEDPAS) to calculate the daily sensitivities for different model outputs with the FAST method. The temporal variations in parameter dominance are then analysed for both the modelled hydrological components themselves, and also for the rates of change (derivatives) in the modelled hydrological components. The daily parameter sensitivities are then compared with the modelled hydrological components using regime curves. Application of this approach shows that when the corresponding modelled process is investigated instead of discharge, we obtain both an increased indication of parameter sensitivity, and also a clear pattern showing how the seasonal patterns of parameter dominance change over time for each hydrological process. By relating these results with the model structure, we can see that the sensitivity of model parameters is influenced by the function of the parameter. While capacity parameters show more sensitivity to the modelled hydrological component, flux parameters tend to have a higher sensitivity to rates of change in the modelled hydrological component. By better disentangling the information hidden in the discharge values, we can use sensitivity analyses to obtain a clearer signal

  1. Timing and Prediction of Climate Change and Hydrological Impacts: Periodicity in Natural Variations

    EPA Science Inventory

    Hydrological impacts from climate change are of principal interest to water resource policy-makers and practicing engineers, and predictive climatic models have been extensively investigated to quantify the impacts. In palaeoclmatic investigations, climate proxy evidence has une...

  2. Snow multivariable data assimilation for hydrological predictions in mountain areas

    NASA Astrophysics Data System (ADS)

    Piazzi, Gaia; Campo, Lorenzo; Gabellani, Simone; Rudari, Roberto; Castelli, Fabio; Cremonese, Edoardo; Morra di Cella, Umberto; Stevenin, Hervé; Ratto, Sara Maria

    2016-04-01

    The seasonal presence of snow on alpine catchments strongly impacts both surface energy balance and water resource. Thus, the knowledge of the snowpack dynamics is of critical importance for several applications, such as water resource management, floods prediction and hydroelectric power production. Several independent data sources provide information about snowpack state: ground-based measurements, satellite data and physical models. Although all these data types are reliable, each of them is affected by specific flaws and errors (respectively dependency on local conditions, sensor biases and limitations, initialization and poor quality forcing data). Moreover, there are physical factors that make an exhaustive reconstruction of snow dynamics complicated: snow intermittence in space and time, stratification and slow phenomena like metamorphism processes, uncertainty in snowfall evaluation, wind transportation, etc. Data Assimilation (DA) techniques provide an objective methodology to combine observational and modeled information to obtain the most likely estimate of snowpack state. Indeed, by combining all the available sources of information, the implementation of DA schemes can quantify and reduce the uncertainties of the estimations. This study presents SMASH (Snow Multidata Assimilation System for Hydrology), a multi-layer snow dynamic model, strengthened by a robust multivariable data assimilation algorithm. The model is physically based on mass and energy balances and can be used to reproduce the main physical processes occurring within the snowpack: accumulation, density dynamics, melting, sublimation, radiative balance, heat and mass exchanges. The model is driven by observed forcing meteorological data (air temperature, wind velocity, relative air humidity, precipitation and incident solar radiation) to provide a complete estimate of snowpack state. The implementation of an Ensemble Kalman Filter (EnKF) scheme enables to assimilate simultaneously ground

  3. Developing predictive insight into changing water systems: use-inspired hydrologic science for the Anthropocene

    NASA Astrophysics Data System (ADS)

    Thompson, S. E.; Sivapalan, M.; Harman, C. J.; Srinivasan, V.; Hipsey, M. R.; Reed, P.; Montanari, A.; Blöschl, G.

    2013-12-01

    Globally, many different kinds of water resources management issues call for policy- and infrastructure-based responses. Yet responsible decision-making about water resources management raises a fundamental challenge for hydrologists: making predictions about water resources on decadal- to century-long timescales. Obtaining insight into hydrologic futures over 100 yr timescales forces researchers to address internal and exogenous changes in the properties of hydrologic systems. To do this, new hydrologic research must identify, describe and model feedbacks between water and other changing, coupled environmental subsystems. These models must be constrained to yield useful insights, despite the many likely sources of uncertainty in their predictions. Chief among these uncertainties are the impacts of the increasing role of human intervention in the global water cycle - a defining challenge for hydrology in the Anthropocene. Here we present a research agenda that proposes a suite of strategies to address these challenges from the perspectives of hydrologic science research. The research agenda focuses on the development of co-evolutionary hydrologic modeling to explore coupling across systems, and to address the implications of this coupling on the long-time behavior of the coupled systems. Three research directions support the development of these models: hydrologic reconstruction, comparative hydrology and model-data learning. These strategies focus on understanding hydrologic processes and feedbacks over long timescales, across many locations, and through strategic coupling of observational and model data in specific systems. We highlight the value of use-inspired and team-based science that is motivated by real-world hydrologic problems but targets improvements in fundamental understanding to support decision-making and management. Fully realizing the potential of this approach will ultimately require detailed integration of social science and physical science

  4. Hydrological-niche models predict water plant functional group distributions in diverse wetland types.

    PubMed

    Deane, David C; Nicol, Jason M; Gehrig, Susan L; Harding, Claire; Aldridge, Kane T; Goodman, Abigail M; Brookes, Justin D

    2017-03-06

    Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial-scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalise community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water-plant-functional-group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 697 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed models achieved acceptable predictive performance, with correct classification rates in the range 0.68 - 0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales. This article is protected by copyright. All rights reserved.

  5. Predicting Career Advancement with Structural Equation Modelling

    ERIC Educational Resources Information Center

    Heimler, Ronald; Rosenberg, Stuart; Morote, Elsa-Sofia

    2012-01-01

    Purpose: The purpose of this paper is to use the authors' prior findings concerning basic employability skills in order to determine which skills best predict career advancement potential. Design/methodology/approach: Utilizing survey responses of human resource managers, the employability skills showing the largest relationships to career…

  6. Assessing the role of land surface hydrology model initializations in the simulation and prediction of North American Monsoon precipitation character

    NASA Astrophysics Data System (ADS)

    Gochis, D.; Vivoni, E.; Yu, W.; Tewari, M.; Xiang, T.

    2013-05-01

    Land surface hydrology has been implicated as an active participant in the initiation of atmospheric convection under certain conditions. What is less clear is how terrestrial hydrologic variability, superimposed on complex terrain regions, modifies background circulation structures such as mountain valley and mountain plain flows. Additionally, there is considerable uncertainty as to how selection of land surface model spin-up decisions, influence the simulation and prediction of important precipitation characteristics such as occurrence, intensity and spatial extent. This study examines, in detail how decisions in the model spin-up process, such as selection of physics, land surface parameters and offline forcing data affect simulation and prediction quality. The Advanced Weather Research and Forecasting Model (WRF-ARW) was applied at a 4km grid spacing in seasonal simulation and prediction modes for the summer of 2004. We present the results in the context of assessing the influence of land surface hydrologic forcing versus various possible states of atmospheric conditions including a priori moisture availability and stability. Model results are validated using hydro-meteorological data collected as part of the 2004 North American Monsoon Experiment. Emphasis of the analyses is placed on diagnosing key variables and threshold values for the initiation and growth of convective cloud cover and precipitation in the mountainous and coastal plain regions of northwest Mexico. We conclude the presentation with a set of recommendations for future observational activities which may have the potential to reduce model initialization errors and improve forecast skill.

  7. On the prediction of the Toce alpine basin floods with distributed hydrologic models

    NASA Astrophysics Data System (ADS)

    Montaldo, Nicola; Ravazzani, Giovanni; Mancini, Marco

    2007-02-01

    With the objective of improving flood predictions, in recent years sophisticated continuous hydrologic models that include complex land-surface sub-models have been developed. This has produced a significant increase in parameterization; consequently, applications of distributed models to ungauged basins lacking specific data from field campaigns may become redundant.The objective of this paper is to produce a parsimonious and robust distributed hydrologic model for flood predictions in Italian alpine basins. Application is made to the Toce basin (area 1534 km2). The Toce basin was a case study of the RAPHAEL European Union research project, during which a comprehensive set of hydrologic, meteorological and physiographic data were collected, including the hydrologic analysis of the 1996-1997 period. Two major floods occurred during this period. We compare the FEST04 event model (which computes rainfall abstraction and antecedent soil moisture conditions through the simple Soil Conservation Service curve number method) and two continuous hydrologic models, SDM and TDM (which differ in soil water balance scheme, and base flow and runoff generation computations).The simple FEST04 event model demonstrated good performance in the prediction of the 1997 flood, but shows limits in the prediction of the long and moderate 1996 flood. More robust predictions are obtained with the parsimonious SDM continuous hydrologic model, which uses a simple one-layer soil water balance model and an infiltration excess mechanism for runoff generation, and demonstrates good performance in both long-term runoff modelling and flood predictions. Instead, the use of a more sophisticated continuous hydrologic model, the TDM, that simulates soil moisture dynamics in two layers of soil, and computes runoff and base flow using some TOPMODEL concepts, does not seem to be advantageous for this alpine basin. Copyright

  8. Advances in variable selection methods II: Effect of variable selection method on classification of hydrologically similar watersheds in three Mid-Atlantic ecoregions

    EPA Science Inventory

    Hydrological flow predictions in ungauged and sparsely gauged watersheds use regionalization or classification of hydrologically similar watersheds to develop empirical relationships between hydrologic, climatic, and watershed variables. The watershed classifications may be based...

  9. An Integrated Hydrologic Bayesian Multi-Model Combination Framework: Confronting Input, parameter and model structural uncertainty in Hydrologic Prediction

    SciTech Connect

    Ajami, N K; Duan, Q; Sorooshian, S

    2006-05-05

    This paper presents a new technique--Integrated Bayesian Uncertainty Estimator (IBUNE) to account for the major uncertainties of hydrologic rainfall-runoff predictions explicitly. The uncertainties from the input (forcing) data--mainly the precipitation observations and from the model parameters are reduced through a Monte Carlo Markov Chain (MCMC) scheme named Shuffled Complex Evolution Metropolis (SCEM) algorithm which has been extended to include a precipitation error model. Afterwards, the Bayesian Model Averaging (BMA) scheme is employed to further improve the prediction skill and uncertainty estimation using multiple model output. A series of case studies using three rainfall-runoff models to predict the streamflow in the Leaf River basin, Mississippi are used to examine the necessity and usefulness of this technique. The results suggests that ignoring either input forcings error or model structural uncertainty will lead to unrealistic model simulations and their associated uncertainty bounds which does not consistently capture and represent the real-world behavior of the watershed.

  10. Predictive Dynamic Security Assessment through Advanced Computing

    SciTech Connect

    Huang, Zhenyu; Diao, Ruisheng; Jin, Shuangshuang; Chen, Yousu

    2014-11-30

    Abstract— Traditional dynamic security assessment is limited by several factors and thus falls short in providing real-time information to be predictive for power system operation. These factors include the steady-state assumption of current operating points, static transfer limits, and low computational speed. This addresses these factors and frames predictive dynamic security assessment. The primary objective of predictive dynamic security assessment is to enhance the functionality and computational process of dynamic security assessment through the use of high-speed phasor measurements and the application of advanced computing technologies for faster-than-real-time simulation. This paper presents algorithms, computing platforms, and simulation frameworks that constitute the predictive dynamic security assessment capability. Examples of phasor application and fast computation for dynamic security assessment are included to demonstrate the feasibility and speed enhancement for real-time applications.

  11. On the Impact of Uncertainty in Initial Conditions of Hydrologic Models on Prediction

    NASA Astrophysics Data System (ADS)

    Razavi, S.; Sheikholeslami, R.

    2015-12-01

    Determining the initial conditions for predictive models remains a challenge due to the uncertainty in measurement/identification of the state variables at the scale of interest. However, the characterization of uncertainty in initial conditions has arguably attracted less attention compared with other sources of uncertainty in hydrologic modelling (e.g, parameter, data, and structural uncertainty). This is perhaps because it is commonly believed that: (1) hydrologic systems (relatively rapidly) forget their initial conditions over time, and (2) other sources of uncertainty (e.g., in data) are dominant. This presentation revisits the basic principles of the theory of nonlinear dynamical systems in the context of hydrologic systems. Through simple example case studies, we demonstrate how and under what circumstances different hydrologic processes represent a range of attracting limit sets in their evolution trajectory in state space over time, including fixed points, limit cycles (periodic behaviour), torus (quasi-periodic behaviour), and strange attractors (chaotic behaviour). Furthermore, the propagation (or dissipation) of uncertainty in initial conditions of several hydrologic models through time, under any of the possible attracting limit sets, is investigated. This study highlights that there are definite situations in hydrology where uncertainty in initial conditions remains of significance. The results and insights gained have important implications for hydrologic modelling under non-stationarity in climate and environment.

  12. Reducing hydrologic model uncertainty in monthly streamflow predictions using multimodel combination

    NASA Astrophysics Data System (ADS)

    Li, Weihua; Sankarasubramanian, A.

    2012-12-01

    Model errors are inevitable in any prediction exercise. One approach that is currently gaining attention in reducing model errors is by combining multiple models to develop improved predictions. The rationale behind this approach primarily lies on the premise that optimal weights could be derived for each model so that the developed multimodel predictions will result in improved predictions. A new dynamic approach (MM-1) to combine multiple hydrological models by evaluating their performance/skill contingent on the predictor state is proposed. We combine two hydrological models, "abcd" model and variable infiltration capacity (VIC) model, to develop multimodel streamflow predictions. To quantify precisely under what conditions the multimodel combination results in improved predictions, we compare multimodel scheme MM-1 with optimal model combination scheme (MM-O) by employing them in predicting the streamflow generated from a known hydrologic model (abcd model orVICmodel) with heteroscedastic error variance as well as from a hydrologic model that exhibits different structure than that of the candidate models (i.e., "abcd" model or VIC model). Results from the study show that streamflow estimated from single models performed better than multimodels under almost no measurement error. However, under increased measurement errors and model structural misspecification, both multimodel schemes (MM-1 and MM-O) consistently performed better than the single model prediction. Overall, MM-1 performs better than MM-O in predicting the monthly flow values as well as in predicting extreme monthly flows. Comparison of the weights obtained from each candidate model reveals that as measurement errors increase, MM-1 assigns weights equally for all the models, whereas MM-O assigns higher weights for always the best-performing candidate model under the calibration period. Applying the multimodel algorithms for predicting streamflows over four different sites revealed that MM-1 performs

  13. Predicting the natural flow regime: Models for assessing hydrological alteration in streams

    USGS Publications Warehouse

    Carlisle, D.M.; Falcone, J.; Wolock, D.M.; Meador, M.R.; Norris, R.H.

    2010-01-01

    Understanding the extent to which natural streamflow characteristics have been altered is an important consideration for ecological assessments of streams. Assessing hydrologic condition requires that we quantify the attributes of the flow regime that would be expected in the absence of anthropogenic modifications. The objective of this study was to evaluate whether selected streamflow characteristics could be predicted at regional and national scales using geospatial data. Long-term, gaged river basins distributed throughout the contiguous US that had streamflow characteristics representing least disturbed or near pristine conditions were identified. Thirteen metrics of the magnitude, frequency, duration, timing and rate of change of streamflow were calculated using a 20-50 year period of record for each site. We used random forests (RF), a robust statistical modelling approach, to develop models that predicted the value for each streamflow metric using natural watershed characteristics. We compared the performance (i.e. bias and precision) of national- and regional-scale predictive models to that of models based on landscape classifications, including major river basins, ecoregions and hydrologic landscape regions (HLR). For all hydrologic metrics, landscape stratification models produced estimates that were less biased and more precise than a null model that accounted for no natural variability. Predictive models at the national and regional scale performed equally well, and substantially improved predictions of all hydrologic metrics relative to landscape stratification models. Prediction error rates ranged from 15 to 40%, but were 25% for most metrics. We selected three gaged, non-reference sites to illustrate how predictive models could be used to assess hydrologic condition. These examples show how the models accurately estimate predisturbance conditions and are sensitive to changes in streamflow variability associated with long-term land-use change. We also

  14. Development of a coupled hydrological-geotechnical framework for rainfall-induced landslides prediction

    NASA Astrophysics Data System (ADS)

    He, Xiaogang; Hong, Yang; Vergara, Humberto; Zhang, Ke; Kirstetter, Pierre-Emmanuel; Gourley, Jonathan J.; Zhang, Yu; Qiao, Gang; Liu, Chun

    2016-12-01

    In this paper, we propose a new coupled hydrological-geotechnical model called CRESLIDE (Coupled Routing and Excess Storage and SLope-Infiltration-Distributed Equilibrium), which can alleviate the chronic flaws of landslides simulation and prediction. CRESLIDE is designed to improve the original landslides model (SLIDE) through the coupling of hydrological model (CREST) and to deliver an integrated system for predicting storm-triggered landslides. This coupled system is implemented and evaluated in Macon County, North Carolina, where Hurricane Ivan triggered widespread landslides in September 2004 during the hurricane season. Model simulations from CRESLIDE show its reliability to predict landslides occurrence (location and timing). Receiver Operating Characteristic (ROC) analysis demonstrates that the coupled system (CRESLIDE) has higher specificity (94.10%) and higher sensitivity (11.36%) compared to the original SLIDE model (specificity = 93.32%, sensitivity = 10.23%) and a well-known landslide model (TRIGRS, whose sensitivity is 6.98%). This improved predictive performance demonstrates the advantage of coupling hydrological and geotechnical models with a more realistic representation of infiltration. It warrants a better depiction of the spatial and temporal dependence of hydrological and geotechnical processes in the course of the rainfall-triggered landslide event. This kind of model integration is useful for landslides prediction and early warning.

  15. Satellite Remote Sensing and Hydrological Modeling for Flood Inundation Mapping in Lake Victoria Basin: Implications for Hydrologic Prediction in Ungauged Basins

    NASA Astrophysics Data System (ADS)

    Khan, S. I.; Hong, Y.; Wang, J.; Yilmaz, K. K.; Gourley, J. J.; Adler, R. F.; Brakenridge, G. R.; Policelli, F.; Habib, S.; Irwin, D.

    2009-12-01

    Floods are among the most catastrophic natural disasters around the globe impacting human lives and infrastructure. Implementation of a flood prediction system can potentially reduce these losses. Typically, the set up and calibration of a hydrologic model requires in situ observations (e.g. rain gauges and stream gauges). Satellite remote sensing data have emerged as viable alternatives or supplements to in situ observations due to their coverage over ungauged regions. The focus of this study is to utilize the best available satellite products and integrate them in a state-of-the-art hydrologic model to characterize the spatial extent of flooding and associated hazards over sparsely-gauged or ungauged basins. This study presents a methodology based entirely on satellite remote sensing data to calibrate a hydrologic model, simulate the spatial extent of flooding, and evaluate the probability of detecting inundated areas. A raster-based distributed hydrologic model, CREST, was implemented for the Nzoia basin, a sub-basin of Lake Victoria (Africa). MODIS- and ASTER-based flood inundation maps were retrieved over the region and used to benchmark the distributed hydrologic model simulations of streamflow and inundation areas. The analysis showed the applicability of integrating satellite data products as input for a distributed hydrological model as well as direct estimation of flood extent maps. The quantification of flooding spatial extent through orbital sensors can help to evaluate hydrologic models and hence potentially improve hydrologic prediction and flood management strategies in ungauged catchments.

  16. Predicting hydrological response to forest changes by simple statistical models: the selection of the best indicator of forest changes with a hydrological perspective

    NASA Astrophysics Data System (ADS)

    Ning, D.; Zhang, M.; Ren, S.; Hou, Y.; Yu, L.; Meng, Z.

    2017-01-01

    Forest plays an important role in hydrological cycle, and forest changes will inevitably affect runoff across multiple spatial scales. The selection of a suitable indicator for forest changes is essential for predicting forest-related hydrological response. This study used the Meijiang River, one of the headwaters of the Poyang Lake as an example to identify the best indicator of forest changes for predicting forest change-induced hydrological responses. Correlation analysis was conducted first to detect the relationships between monthly runoff and its predictive variables including antecedent monthly precipitation and indicators for forest changes (forest coverage, vegetation indices including EVI, NDVI, and NDWI), and by use of the identified predictive variables that were most correlated with monthly runoff, multiple linear regression models were then developed. The model with best performance identified in this study included two independent variables -antecedent monthly precipitation and NDWI. It indicates that NDWI is the best indicator of forest change in hydrological prediction while forest coverage, the most commonly used indicator of forest change is insignificantly related to monthly runoff. This highlights the use of vegetation index such as NDWI to indicate forest changes in hydrological studies. This study will provide us with an efficient way to quantify the hydrological impact of large-scale forest changes in the Meijiang River watershed, which is crucial for downstream water resource management and ecological protection in the Poyang Lake basin.

  17. Stochastic Residual-Error Analysis For Estimating Hydrologic Model Predictive Uncertainty

    EPA Science Inventory

    A hybrid time series-nonparametric sampling approach, referred to herein as semiparametric, is presented for the estimation of model predictive uncertainty. The methodology is a two-step procedure whereby a distributed hydrologic model is first calibrated, then followed by brute ...

  18. Improving hydrologic predictions of a catchment model via assimilation of surface soil moisture

    Technology Transfer Automated Retrieval System (TEKTRAN)

    This paper examines the potential for improving Soil and Water Assessment Tool (SWAT) hydrologic predictions within the 341 km2 Cobb Creek Watershed in southwestern Oklahoma through the assimilation of surface soil moisture observations using an Ensemble Kalman filter (EnKF). In a series of synthet...

  19. Diagnosis of streamflow prediction skills in Oregon using Hydrologic Landscape Classification

    EPA Science Inventory

    A complete understanding of why rainfall-runoff models provide good streamflow predictions at catchments in some regions, but fail to do so in other regions, has still not been achieved. Here, we argue that a hydrologic classification system is a robust conceptual tool that is w...

  20. Use of hydrologic landscape classification to diagnose streamflow predictability in Oregon

    EPA Science Inventory

    We implement a spatially lumped rainfall-runoff model to predict daily streamflow at 88 catchments within Oregon, USA and analyze its performance within the context of Oregon Hydrologic Landscapes (OHL) classification. OHL classification is used to characterize the physio-climat...

  1. New Hydrologic Insights to Advance Geophysical Investigation of the Unsaturated Zone

    NASA Astrophysics Data System (ADS)

    Nimmo, J. R.; Perkins, K. S.

    2015-12-01

    Advances in hydrology require information from the unsaturated zone, especially for problems related to groundwater contamination, water-supply sustainability, and ecohydrology. Unsaturated-zone processes are notoriously difficult to quantify; soils and rocks are visually opaque, spatially variable in the extreme, and easily disturbed by instrument installation. Thus there is great value in noninvasive techniques that produce water-related data of high density in space and time. Methods based on resistivity and electromagnetic waves have already produced significant new understanding of percolation processes, root-zone water retention, influences of evapotranspiration on soil-water, and effects of preferential flow. Further developments are underway for such purposes as noninvasive application to greater depths, increased resolution, adaptation for lab-scale experiments, and calibration in heterogeneous media. Beyond these, however, there is need for a stronger marriage of hydrologic and geophysical knowledge and perspective. Possible means to greater and faster progress include: Apply the latest hydrologic understanding, both pore-scale and macroscopic, to the detection of preferential flow paths and their degree of activation. In the continuing advancement of hardware and techniques, draw creatively from developments in such fields as high-energy physics, medical imaging, astrogeology, high-tech semiconductors, and bioinstrumentation. Sidestep the imaging process where possible to measure essential properties and fluxes more directly. Pose questions that have a strong end-use character, like "how does storm intensity relate to aquifer recharge rate" rather than "what is the shape of the wetting front". The greatest advances in geophysical investigation of the unsaturated zone will come from methods informed by the latest understanding of unsaturated systems and processes, and aimed as directly as possible at the answers to important hydrologic questions.

  2. Advancements in predictive plasma formation modeling

    NASA Astrophysics Data System (ADS)

    Purvis, Michael A.; Schafgans, Alexander; Brown, Daniel J. W.; Fomenkov, Igor; Rafac, Rob; Brown, Josh; Tao, Yezheng; Rokitski, Slava; Abraham, Mathew; Vargas, Mike; Rich, Spencer; Taylor, Ted; Brandt, David; Pirati, Alberto; Fisher, Aaron; Scott, Howard; Koniges, Alice; Eder, David; Wilks, Scott; Link, Anthony; Langer, Steven

    2016-03-01

    We present highlights from plasma simulations performed in collaboration with Lawrence Livermore National Labs. This modeling is performed to advance the rate of learning about optimal EUV generation for laser produced plasmas and to provide insights where experimental results are not currently available. The goal is to identify key physical processes necessary for an accurate and predictive model capable of simulating a wide range of conditions. This modeling will help to drive source performance scaling in support of the EUV Lithography roadmap. The model simulates pre-pulse laser interaction with the tin droplet and follows the droplet expansion into the main pulse target zone. Next, the interaction of the expanded droplet with the main laser pulse is simulated. We demonstrate the predictive nature of the code and provide comparison with experimental results.

  3. Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model

    NASA Astrophysics Data System (ADS)

    Ragettli, S.; Pellicciotti, F.; Immerzeel, W. W.; Miles, E. S.; Petersen, L.; Heynen, M.; Shea, J. M.; Stumm, D.; Joshi, S.; Shrestha, A.

    2015-04-01

    The hydrology of high-elevation watersheds of the Hindu Kush-Himalaya region (HKH) is poorly known. The correct representation of internal states and process dynamics in glacio-hydrological models can often not be verified due to missing in situ measurements. We use a new set of detailed ground data from the upper Langtang valley in Nepal to systematically guide a state-of-the art glacio-hydrological model through a parameter assigning process with the aim to understand the hydrology of the catchment and contribution of snow and ice processes to runoff. 14 parameters are directly calculated on the basis of local data, and 13 parameters are calibrated against 5 different datasets of in situ or remote sensing data. Spatial fields of debris thickness are reconstructed through a novel approach that employs data from an Unmanned Aerial Vehicle (UAV), energy balance modeling and statistical techniques. The model is validated against measured catchment runoff (Nash-Sutcliffe efficiency 0.87) and modeled snow cover is compared to Landsat snow cover. The advanced representation of processes allowed assessing the role played by avalanching for runoff for the first time for a Himalayan catchment (5% of annual water inputs to the hydrological system are due to snow redistribution) and to quantify the hydrological significance of sub-debris ice melt (9% of annual water inputs). Snowmelt is the most important contributor to total runoff during the hydrological year 2012/2013 (representing 40% of all sources), followed by rainfall (34%) and ice melt (26%). A sensitivity analysis is used to assess the efficiency of the monitoring network and identify the timing and location of field measurements that constrain model uncertainty. The methodology to set up a glacio-hydrological model in high-elevation regions presented in this study can be regarded as a benchmark for modelers in the HKH seeking to evaluate their calibration approach, their experimental setup and thus to reduce the

  4. Program plan and summary, remote fluvial experimental (REFLEX) series: Research experiments using advanced remote sensing technologies with emphasis on hydrologic transport, and hydrologic-ecologic interactions

    SciTech Connect

    Wobber, F.J.

    1986-10-01

    This document describes research designed to evaluate advanced remote sensing technologies for environmental research. A series of Remote Fluvial Experiments (REFLEX) - stressing new applications of remote sensing systems and use of advanced digital analysis methods - are described. Program strategy, experiments, research areas, and future initiatives are summarized. The goals of REFLEX are: (1) to apply new and developing aerial and satellite remote sensing technologies - including both advanced sensor systems and digital/optical processing - for interdisciplinary scientific experiments in hydrology and to hydrologic/ecologic interactions; (2) to develop new concepts for processing and analyzing remote sensing data for general scientific application; and (3) to demonstrate innovative analytical technologies that advance the state of the art in applying information from remote sensing systems, for example, supercomputer processing and analysis.

  5. Hydrological states and fluxes in terrestrial systems: from observation to prediction (John Dalton Medal Lecture)

    NASA Astrophysics Data System (ADS)

    Vereecken, Harry

    2016-04-01

    Quantification and prediction of hydrological processes requires information on the spatial and temporal distribution of soil water fluxes and soil water content. The access to spatially and temporally highly resolved soil water content and fluxes is needed to adequately test hydrological hypotheses and to validate hydrological models. In this presentation we will discuss new developments for the determination of soil water content and quantification and prediction of hydrological fluxes based on hydrogeophysical measurement techniques and novel ground- and satellite based sensing platforms. At the field scale, ground penetrating radar and passive microwave methods are presently being developed which provide the possibility to map soil water content with a high spatial and temporal resolution, also in the subsurface environment. Recent developments show that the application of full wave form inversion methods is a unique technique to derive soil water and soil hydraulic parameters from on- and off-ground systems with high spatial resolution. At the small catchment scale, wireless sensor networks are presently being developed providing soil moisture content values with a high spatial and temporal resolution. Stochastic theories have been used to interpret the relationship between average soil water content and its standard deviation. Cosmic ray sensors are presently being deployed within the TERENO observatories. These sensors provide soil moisture content values with a high temporal resolution at a scale of one to two hundred meters, thereby bridging the gap between local scale measurements and remote sensing platforms. Cosmic ray probes are extremely valuable for the determination of soil water content in agriculturally managed soils. Data assimilation methods provide a unique approach to fully exploit the value of spatially and temporally highly resolved soil water content measurements and states of the terrestrial system for the prediction of hydrological fluxes

  6. A Hierarchical Approach Embedding Hydrologic and Population Modeling for a West Nile Virus Vector Prediction

    NASA Astrophysics Data System (ADS)

    Jian, Y.; Silvestri, S.; Marani, M.; Saltarin, A.; Chillemi, G.

    2012-12-01

    We applied a hierarchical state space model to predict the abundance of Cx.pipiens (a West Nile Virus vector) in the Po River Delta Region, Northeastern Italy. The study area has large mosquito abundance, due to a favorable environment and climate as well as dense human population. Mosquito data were collected on a weekly basis at more than 20 sites from May to September in 2010 and 2011. Cx.pipiens was the dominant species in our samples, accounting for about 90% of the more than 300,000 total captures. The hydrological component of the model accounted for evapotranspiration, infiltration and deep percolation to infer, in a 0D context, the local dynamics of soil moisture as a direct exogenous forcing of mosquito dynamics. The population model had a Gompertz structure, which included exogenous meteorological forcings and delayed internal dynamics. The models were coupled within a hierarchical statistical structure to overcome the relatively short length of the samples by exploiting the large number of concurrent observations available. The results indicated that Cx.pipiens abundance had significant density dependence at 1 week lag, which approximately matched its development time from larvae to adult. Among the exogenous controls, temperature, daylight hours, and soil moisture explained most of the dynamics. Longer daylight hours and lower soil moisture values resulted in higher abundance. The negative correlation of soil moisture and mosquito population can be explained with the abundance of water in the region (e.g. due to irrigation) and the preference for eutrophic habitats by Cx.pipien. Variations among sites were explained by land use factors as represented by distance to the nearest rice field and NDVI values: the carrying capacity decreased with increased distance to the nearest rice filed, while the maximum growth rate was positively related with NDVI. The model shows a satisfactory performance in predicting (potentially one week in advance) mosquito

  7. SWAT Ungauged: Hydrological Budget and Crop Yield Predictions in the Upper Mississippi River Basin

    SciTech Connect

    R. Srinivasan,; X. Zhang,; J. Arnold,

    2010-01-01

    Physically based, distributed hydrologic models are increasingly used in assessments of water resources, best management practices, and climate and land use changes. Model performance evaluation in ungauged basins is an important research topic. In this study, we propose a framework for developing Soil and Water Assessment Tool (SWAT) input data, including hydrography, terrain, land use, soil, tile, weather, and management practices, for the Upper Mississippi River basin (UMRB). We also present a performance evaluation of SWAT hydrologic budget and crop yield simulations in the UMRB without calibration. The uncalibrated SWAT model ably predicts annual streamflow at 11 USGS gauges and crop yield at a four-digit hydrologic unit code (HUC) scale. For monthly streamflow simulation, the performance of SWAT is marginally poor compared with that of annual flow, which may be due to incomplete information about reservoirs and dams within the UMRB. Further validation shows that SWAT can predict base flow contribution ratio reasonably well. Compared with three calibrated SWAT models developed in previous studies of the entire UMRB, the uncalibrated SWAT model presented here can provide similar results. Overall, the SWAT model can provide satisfactory predictions on hydrologic budget and crop yield in the UMRB without calibration. The results emphasize the importance and prospects of using accurate spatial input data for the physically based SWAT model. This study also examines biofuel-biomass production by simulating all agricultural lands with switchgrass, producing satisfactory results in estimating biomass availability for biofuel production.

  8. Extending data worth methods to select multiple observations targeting specific hydrological predictions of interest

    NASA Astrophysics Data System (ADS)

    Vilhelmsen, Troels N.; Ferré, Ty P. A.

    2016-04-01

    Hydrological models are often developed to forecasting future behavior in response due to natural or human induced changes in stresses affecting hydrologic systems. Commonly, these models are conceptualized and calibrated based on existing data/information about the hydrological conditions. However, most hydrologic systems lack sufficient data to constrain models with adequate certainty to support robust decision making. Therefore, a key element of a hydrologic study is the selection of additional data to improve model performance. Given the nature of hydrologic investigations, it is not practical to select data sequentially, i.e. to choose the next observation, collect it, refine the model, and then repeat the process. Rather, for timing and financial reasons, measurement campaigns include multiple wells or sampling points. There is a growing body of literature aimed at defining the expected data worth based on existing models. However, these are almost all limited to identifying single additional observations. In this study, we present a methodology for simultaneously selecting multiple potential new observations based on their expected ability to reduce the uncertainty of the forecasts of interest. This methodology is based on linear estimates of the predictive uncertainty, and it can be used to determine the optimal combinations of measurements (location and number) established to reduce the uncertainty of multiple predictions. The outcome of the analysis is an estimate of the optimal sampling locations; the optimal number of samples; as well as a probability map showing the locations within the investigated area that are most likely to provide useful information about the forecasting of interest.

  9. Can citizen-based observations be assimilated in hydrological models to improve flood prediction?

    NASA Astrophysics Data System (ADS)

    Mazzoleni, Maurizio; Alfonso, Leonardo; Solomatine, Dimitri P.

    2015-04-01

    In the recent years, the continued technological improvement has stimulated the spread of low-cost sensors that can be used to measure hydrological variables by citizens in a more spatially distributed way than classic static physical sensors. However, such measurements have the main characteristics to have irregular arrival time and variable uncertainty. This study presents a Kalman filter based method to integrate citizen-based observations into hydrological models in order to improve flood prediction. The methodology is applied in the Brue catchment, South West of England. In order to estimate the response of the catchment to a given flood event, a lumped conceptual hydrological model is implemented. The measured precipitation values are used as perfect forecast input in the hydrological model. Synthetic streamflow values are used in this study due to the fact that citizen-based observations coming at irregular time steps are not available. The results of this study pointed out how increasing the number of uncertain citizen-based observations within two model time steps can improve the model accuracy leading to a better flood forecast. Therefore, observations uncertainty influences the model accuracy more than the irregular moments in which the streamflow observations are assimilated into the hydrological model. This study is part of the FP7 European Project WeSenseIt Citizen Water Observatory (http://wesenseit.eu/).

  10. Advances in Frozen Ground Studies and Understanding its Role in the Hydrological Cycle

    NASA Astrophysics Data System (ADS)

    Zhang, T.

    2004-05-01

    Significant advances in frozen ground studies have been achieved over the past several decades. Knowledge and information on frozen ground would improve our understanding in local, regional, and global water cycle over the cold regions/cold seasons. Permafrost regions occupy approximately 24 percent of the land area in the Northern Hemisphere. The total volume of the excess ground ice contained in the ice-rich permafrost ranges from about 10,800 to 35,460 cubic kilometers or about 2.7 to 8.8 cm sea-level equivalent. Permafrost limits the amount of subsurface water storage and infiltration that can occur, leading to wet soils and standing surface water, unusual for a region with limited precipitation. Observational evidence indicates that permafrost warming and thawing in the Northern Hemisphere have occurred over the past several decades. Active layer thickness has increased and depth of seasonally frozen ground has decreased significantly in the Russian Arctic and Subarctic. Thickening of the active layer and melting of the excess ground ice may partly contribute to the increase of runoff over the Russian Arctic drainage basin. Increase in active layer thickness may also delay the active layer freeze-up date, possibly leading to the increase in winter river runoff. On average, nearly 50 percent of the land surface in the Northern Hemisphere experiences freeze/thaw cycles that last from a few days to several months with thickness up to several meters. The existence of a thin frozen layer near the surface essentially decouples moisture exchange between the atmosphere and deeper soils. Knowing whether the soil is frozen is important in predicting spring surface runoff and soil moisture reserve in northern United States. Coupling of soil freezing and thawing processes into the hydrological model improves the model prediction on river runoff significantly. The timing, duration, areal extent,frequency, and thickness of the near-surface soil freeze/thaw cycle have

  11. Getting the right answers for the right reasons: Linking measurements, analyses, and models to advance the science of hydrology

    NASA Astrophysics Data System (ADS)

    Kirchner, James W.

    2006-03-01

    The science of hydrology is on the threshold of major advances, driven by new hydrologic measurements, new methods for analyzing hydrologic data, and new approaches to modeling hydrologic systems. Here I suggest several promising directions forward, including (1) designing new data networks, field observations, and field experiments, with explicit recognition of the spatial and temporal heterogeneity of hydrologic processes, (2) replacing linear, additive "black box" models with "gray box" approaches that better capture the nonlinear and non-additive character of hydrologic systems, (3) developing physically based governing equations for hydrologic behavior at the catchment or hillslope scale, recognizing that they may look different from the equations that describe the small-scale physics, (4) developing models that are minimally parameterized and therefore stand some chance of failing the tests that they are subjected to, and (5) developing ways to test models more comprehensively and incisively. I argue that scientific progress will mostly be achieved through the collision of theory and data, rather than through increasingly elaborate and parameter-rich models that may succeed as mathematical marionettes, dancing to match the calibration data even if their underlying premises are unrealistic. Thus advancing the science of hydrology will require not only developing theories that get the right answers but also testing whether they get the right answers for the right reasons.

  12. A simple hydrologic model for rapid prediction of runoff from ungauged coastal catchments

    NASA Astrophysics Data System (ADS)

    Wan, Yongshan; Konyha, Kenneth

    2015-09-01

    We developed a lumped conceptual rainfall-runoff model for rapid prediction of runoff generated in the unique hydrological setting with flat terrain, sandy soils, high groundwater table, and a dense drainage canal network in south Florida. The model is conceptualized as rainfall and evapotranspiration filling and emptying the root zone and excess rainfall recharging three storage zones. Outflows from these storage zones, routed with parallel arrangement of three linear reservoirs, represent different flow components of catchment runoff, i.e., slow drainage (shallow subsurface flow), medium drainage (interflow and saturation excess overland flow), and fast drainage (direct runoff from impervious urban areas or from water table management in agricultural land). The model is parsimonious with eight model parameters along with two optional water management parameters. A regionalization study was conducted through model parameterization to achieve target hydrological behavior of typical land uses, which are the most significant basin descriptor affecting catchment hydrology in south Florida. Cross validation with 16 gauged basins dominated by urban, agricultural, and natural lands, respectively, indicated that the model provides an effective tool for rapid prediction of runoff in ungauged basins using the regionalized model parameters. A case study is presented, involving application of the model to support real-time adaptive management to hydrological operations for protection of estuarine ecosystems.

  13. Predicting changes in hydrologic retention in an evolving semi-arid alluvial stream

    USGS Publications Warehouse

    Harvey, J.W.; Conklin, M.H.; Koelsch, R.S.

    2003-01-01

    Hydrologic retention of solutes in hyporheic zones or other slowly moving waters of natural channels is thought to be a significant control on biogeochemical cycling and ecology of streams. To learn more about factors affecting hydrologic retention, we repeated stream-tracer injections for 5 years in a semi-arid alluvial stream (Pinal Creek, Ariz.) during a period when streamflow was decreasing, channel width increasing, and coverage of aquatic macrophytes expanding. Average stream velocity at Pinal Creek decreased from 0.8 to 0.2 m/s, average stream depth decreased from 0.09 to 0.04 m, and average channel width expanded from 3 to 13 m. Modeling of tracer experiments indicated that the hydrologic retention factor (Rh), a measure of the average time that solute spends in storage per unit length of downstream transport, increased from 0.02 to 8 s/m. At the same time the ratio of cross-sectional area of storage zones to main channel cross-sectional area (As/A) increased from 0.2 to 0.8 m2/m2, and average water residence time in storage zones (ts) increased from 5 to 24 min. Compared with published data from four other streams in the US, Pinal Creek experienced the greatest change in hydrologic retention for a given change in streamflow. The other streams differed from Pinal Creek in that they experienced a change in streamflow between tracer experiments without substantial geomorphic or vegetative adjustments. As a result, a regression of hydrologic retention on streamflow developed for the other streams underpredicted the measured increases in hydrologic retention at Pinal Creek. The increase in hydrologic retention at Pinal Creek was more accurately predicted when measurements of the Darcy-Weisbach friction factor were used (either alone or in addition to streamflow) as a predictor variable. We conclude that relatively simple measurements of channel friction are useful for predicting the response of hydrologic retention in streams to major adjustments in channel

  14. Predicting Hydrological Drought: Relative Contributions of Soil Moisture and Snow Information to Seasonal Streamflow Prediction Skill

    NASA Technical Reports Server (NTRS)

    Koster, R.; Mahanama, S.; Livneh, B.; Lettenmaier, D.; Reichle, R.

    2011-01-01

    in this study we examine how knowledge of mid-winter snow accumulation and soil moisture conditions contribute to our ability to predict streamflow months in advance. A first "synthetic truth" analysis focuses on a series of numerical experiments with multiple sophisticated land surface models driven with a dataset of observations-based meteorological forcing spanning multiple decades and covering the continental United States. Snowpack information by itself obviously contributes to the skill attained in streamflow prediction, particularly in the mountainous west. The isolated contribution of soil moisture information, however, is found to be large and significant in many areas, particularly in the west but also in region surrounding the Great Lakes. The results are supported by a supplemental, observations-based analysis using (naturalized) March-July streamflow measurements covering much of the western U.S. Additional forecast experiments using start dates that span the year indicate a strong seasonality in the skill contributions; soil moisture information, for example, contributes to kill at much longer leads for forecasts issued in winter than for those issued in summer.

  15. Evaluation of real-time hydrometeorological ensemble prediction on hydrologic scales in Northern California

    NASA Astrophysics Data System (ADS)

    Georgakakos, Konstantine P.; Graham, Nicholas E.; Modrick, Theresa M.; Murphy, Michael J.; Shamir, Eylon; Spencer, Cristopher R.; Sperfslage, Jason A.

    2014-11-01

    The paper presents an evaluation of real time ensemble forecasts produced during 2010-2012 by the demonstration project INFORM (Integrated Forecast and Reservoir Management) in Northern California. In addition, the innovative elements of the forecast component of the INFORM project are highlighted. The forecast component is designed to dynamically downscale operational multi-lead ensemble forecasts from the Global Ensemble Forecast System (GEFS) and the Climate Forecast system (CFS) of the National Centers of Environmental Prediction (NCEP), and to use adaptations of the operational hydrologic models of the US National Weather Service California Nevada River Forecast Center to provide ensemble reservoir inflow forecasts in real time. A full-physics 10-km resolution (10 km on the side) mesoscale model was implemented for the ensemble prediction of surface precipitation and temperature over the domain of Northern California with lead times out to 16 days with 6-hourly temporal resolution. An intermediate complexity regional model with a 10 km resolution was implemented to downscale the NCEP CFS ensemble forecasts for lead times out to 41.5 days. Methodologies for precipitation and temperature model forecast adjustment to comply with the corresponding observations were formulated and tested as regards their effectiveness for improving the ensemble predictions of these two variables and also for improving reservoir inflow forecasts. The evaluation is done using the real time databases of INFORM and concerns the snow accumulation and melt seasons. Performance is measured by metrics that range from those that use forecast means to those that use the entire forecast ensemble. The results show very good skill in forecasting precipitation and temperature over the subcatchments of the INFORM domain out to a week in advance for all basins, models and seasons. For temperature, in some cases, non-negligible skill has been obtained out to four weeks for the melt season

  16. A probabilistic prediction network for hydrological drought identification and environmental flow assessment

    NASA Astrophysics Data System (ADS)

    Liu, Zhiyong; Törnros, Tobias; Menzel, Lucas

    2016-08-01

    A general probabilistic prediction network is proposed for hydrological drought examination and environmental flow assessment. This network consists of three major components. First, we present the joint streamflow drought indicator (JSDI) to describe the hydrological dryness/wetness conditions. The JSDI is established based on a high-dimensional multivariate probabilistic model. In the second part, a drought-based environmental flow assessment method is introduced, which provides dynamic risk-based information about how much flow (the environmental flow target) is required for drought recovery and its likelihood under different hydrological drought initial situations. The final part involves estimating the conditional probability of achieving the required environmental flow under different precipitation scenarios according to the joint dependence structure between streamflow and precipitation. Three watersheds from different countries (Germany, China, and the United States) with varying sizes from small to large were used to examine the usefulness of this network. The results show that the JSDI can provide an assessment of overall hydrological dryness/wetness conditions and performs well in identifying both drought onset and persistence. This network also allows quantitative prediction of targeted environmental flow required for hydrological drought recovery and estimation of the corresponding likelihood. Moreover, the results confirm that the general network can estimate the conditional probability associated with the required flow under different precipitation scenarios. The presented methodology offers a promising tool for water supply planning and management and for drought-based environmental flow assessment. The network has no restrictions that would prevent it from being applied to other basins worldwide.

  17. Threshold behavior in hydrological systems and geo-ecosystems: manifestations, controls and implications for predictability

    NASA Astrophysics Data System (ADS)

    Zehe, E.; Sivapalan, M.

    2008-11-01

    The aim of this paper is to provide evidence that the dynamics of hydrological systems and geo-ecosystems is often influenced by threshold behavior at a variety of space and time scales. Based on well known characteristics of elementary threshold phenomena we suggest criteria for detecting threshold behavior in hydrological systems. The most important one is intermittence of phenomena, i.e. the rapid switching of related state variables/fluxes from zero to finite values, or existence of behavior regimes where the same process/response appears qualitatively differently at the macroscopic level. From the literature we present several examples for intermittent hydrological phenomena, ranging from overland flow generation in different landscapes, including the effects of hydrophobicity, to soil water flow occurring in the matrix continuum or via preferential pathways, including the case of cracking soils, nonlinear subsurface stormflow response of hillslopes during severe rainfall events, and long-term catchment flooding responses. Since threshold phenomena are often associated with environmental hazards such as floods, soil erosion, and contamination of shallow groundwater resources, we discuss common difficulties that complicate predictions of whether or not they might even occur. Predicting the onset of threshold phenomena requires a thorough understanding of the underlying controls. Through examples we illustrate that threshold behavior in hydrological systems can manifest at (a) the process level, (b) the response level, and (c) the functional level, and explain that the complexity of the underlying controls and of the interacting phenomena that determine threshold behavior become increasingly complex at the higher levels. Finally we provide evidence from field observations and model predictions that show that within an "unstable range" of system states "close" to a threshold, it is difficult to predict whether or not the system will switch behavior, for instance

  18. The state of the art of flood forecasting - Hydrological Ensemble Prediction Systems

    NASA Astrophysics Data System (ADS)

    Thielen-Del Pozo, J.; Pappenberger, F.; Salamon, P.; Bogner, K.; Burek, P.; de Roo, A.

    2010-09-01

    Flood forecasting systems form a key part of ‘preparedness' strategies for disastrous floods and provide hydrological services, civil protection authorities and the public with information of upcoming events. Provided the warning leadtime is sufficiently long, adequate preparatory actions can be taken to efficiently reduce the impacts of the flooding. Because of the specific characteristics of each catchment, varying data availability and end-user demands, the design of the best flood forecasting system may differ from catchment to catchment. However, despite the differences in concept and data needs, there is one underlying issue that spans across all systems. There has been an growing awareness and acceptance that uncertainty is a fundamental issue of flood forecasting and needs to be dealt with at the different spatial and temporal scales as well as the different stages of the flood generating processes. Today, operational flood forecasting centres change increasingly from single deterministic forecasts to probabilistic forecasts with various representations of the different contributions of uncertainty. The move towards these so-called Hydrological Ensemble Prediction Systems (HEPS) in flood forecasting represents the state of the art in forecasting science, following on the success of the use of ensembles for weather forecasting (Buizza et al., 2005) and paralleling the move towards ensemble forecasting in other related disciplines such as climate change predictions. The use of HEPS has been internationally fostered by initiatives such as "The Hydrologic Ensemble Prediction Experiment" (HEPEX), created with the aim to investigate how best to produce, communicate and use hydrologic ensemble forecasts in hydrological short-, medium- und long term prediction of hydrological processes. The advantages of quantifying the different contributions of uncertainty as well as the overall uncertainty to obtain reliable and useful flood forecasts also for extreme events

  19. Towards a Predictive Theory of Malaria: Connections to Spatio-temporal Variability of Climate and Hydrology

    NASA Astrophysics Data System (ADS)

    Endo, N.; Eltahir, E. A. B.

    2015-12-01

    Malaria transmission is closely linked to climatology, hydrology, environment, and the biology of local vectors. These factors interact with each other and non-linearly influence malaria transmission dynamics, making prediction and prevention challenging. Our work attempts to find a universality in the multi-dimensional system of malaria transmission and to develop a theory to predict emergence of malaria given a limited set of environmental and biological inputs.A credible malaria transmission dynamics model, HYDREMATS (Bomblies et al., 2008), was used under hypothetical settings to investigate the role of spatial and temporal distribution of vector breeding pools. HYDREMATS is a mechanistic model and capable of simulating the basic reproduction rate (Ro) without bold assumptions even under dynamic conditions. The spatial distribution of pools is mainly governed by hydrological factors; the impact of pool persistence and rainy season length on malaria transmission were investigated. Also analyzed was the impact of the temporal distribution of pools relative to human houses. We developed non-dimensional variables combining the hydrological and biological parameters. Simulated values of Ro from HYDREMATS are presented in a newly-introduced non-dimensional plane, which leads to a some-what universal theory describing the condition for sustainable malaria transmission. The findings were tested against observations both from the West Africa and the Ethiopian Highland, representing diverse hydroclimatological conditions. Predicated Ro values from the theory over the two regions are in good agreement with the observed malaria transmission data.

  20. On the validity of first-order prediction limits for conceptual hydrologic models

    NASA Astrophysics Data System (ADS)

    Kuczera, George

    1988-11-01

    First-order analysis is a powerful method for evaluating the effect of parameter uncertainty propagating through a conceptual hydrologic model. However, its validity rests on the strong assumption that a first-order approximation is valid over the region of parameter space where there is significant parameter uncertainty. It is suggested that Beale's nonlinearity measure be used to check this assumption. This measure is based on the discrepancy between actual and linearized response for parameters randomly sampled from the surface of the 90% confidence ellipsoid. Examples involving two nonlinear conceptual models demonstrate that model nonlinearity is very much application-dependent, highlighting the need to compute Beale's nonlinearity measure in all model applications. Uncertainty in hydrologic response is induced not only by parameter uncertainty propagating through the model, but also by natural uncertainty arising from model and measurement error. Approximate prediction limits based on both parameter and natural uncertainty, are developed in a regression context, which employs an error model consistent with the residual characteristics found in conceptual hydrologic model applications. An example involving an eight-parameter streamflow yield model demonstrates dominance of natural over parameter uncertainty, emphasizing the need to include both forms of uncertainty when computing prediction limits.

  1. Agricultural soil moisture experiment, Colby, Kansas 1978: Measured and predicted hydrological properties of the soil

    NASA Technical Reports Server (NTRS)

    Arya, L. M. (Principal Investigator)

    1980-01-01

    Predictive procedures for developing soil hydrologic properties (i.e., relationships of soil water pressure and hydraulic conductivity to soil water content) are presented. Three models of the soil water pressure-water content relationship and one model of the hydraulic conductivity-water content relationship are discussed. Input requirements for the models are indicated, and computational procedures are outlined. Computed hydrologic properties for Keith silt loam, a soil typer near Colby, Kansas, on which the 1978 Agricultural Soil Moisture Experiment was conducted, are presented. A comparison of computed results with experimental data in the dry range shows that analytical models utilizing a few basic hydrophysical parameters can produce satisfactory data for large-scale applications.

  2. Can ENSO teleconnections be exploited for seasonal hydrological prediction in the Western U.S.

    NASA Astrophysics Data System (ADS)

    Lettenmaier, Dennis

    2016-04-01

    El Nino is perhaps the strongest teleconnection in the extratropics. The current El Nino event is thought to be the strongest in the instrumental record. We use a set of ten grouped climate and snow water equivalent (SWE) stations distributed across the western U.S. to evaluate how well the U.S. National Multimodel Ensemble (NMME) seasonal climate forecast system is able to exploit ENSO signals. We do so through a comparison of stratified Ensemble Hydrologic Prediction (ESP), in which hydrological forcings for the VIC model are subselected from prior El Nino years, with NMME seasonal forecasts for the same years. We also evaluate the skill of both methods for point forecasts of SWE and accumulated winter (Nov-Mar) precipitation and average winter temperature for winter 2015-2016, and for SWE at the 10 forecast points for Apr 1, 2016.

  3. Use of different sampling schemes in machine learning-based prediction of hydrological models' uncertainty

    NASA Astrophysics Data System (ADS)

    Kayastha, Nagendra; Solomatine, Dimitri; Lal Shrestha, Durga; van Griensven, Ann

    2013-04-01

    In recent years, a lot of attention in the hydrologic literature is given to model parameter uncertainty analysis. The robustness estimation of uncertainty depends on the efficiency of sampling method used to generate the best fit responses (outputs) and on ease of use. This paper aims to investigate: (1) how sampling strategies effect the uncertainty estimations of hydrological models, (2) how to use this information in machine learning predictors of models uncertainty. Sampling of parameters may employ various algorithms. We compared seven different algorithms namely, Monte Carlo (MC) simulation, generalized likelihood uncertainty estimation (GLUE), Markov chain Monte Carlo (MCMC), shuffled complex evolution metropolis algorithm (SCEMUA), differential evolution adaptive metropolis (DREAM), partical swarm optimization (PSO) and adaptive cluster covering (ACCO) [1]. These methods were applied to estimate uncertainty of streamflow simulation using conceptual model HBV and Semi-distributed hydrological model SWAT. Nzoia catchment in West Kenya is considered as the case study. The results are compared and analysed based on the shape of the posterior distribution of parameters, uncertainty results on model outputs. The MLUE method [2] uses results of Monte Carlo sampling (or any other sampling shceme) to build a machine learning (regression) model U able to predict uncertainty (quantiles of pdf) of a hydrological model H outputs. Inputs to these models are specially identified representative variables (past events precipitation and flows). The trained machine learning models are then employed to predict the model output uncertainty which is specific for the new input data. The problem here is that different sampling algorithms result in different data sets used to train such a model U, which leads to several models (and there is no clear evidence which model is the best since there is no basis for comparison). A solution could be to form a committee of all models U and

  4. Weather Prediction Improvement Using Advanced Satellite Technology

    NASA Technical Reports Server (NTRS)

    Einaudi, Franco; Uccellini, L.; Purdom, J.; Rogers, D.; Gelaro, R.; Dodge, J.; Atlas, R.; Lord, S.

    2001-01-01

    We discuss in this paper some of the problems that exist today in the fall utilization of satellite data to improve weather forecasts and we propose specific recommendations to solve them. This discussion can be viewed as an aspect of the general debate on how best to organize the transition from research to operational satellites and how to evaluate the impact of a research instrument on numerical weather predictions. A method for providing this transition is offered by the National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP). This mission will bridge the time between the present NOAA and Department of Defense (DOD) polar orbiting missions and the initiation of the converged NPOESS series and will evaluate some of the Earth Observing System (EOS) instruments as appropriate for operational missions. Thus, this mission can be viewed as an effort to meet the operational requirements of NOAA and DOD and the research requirements of NASA. More generally, however, it can be said that the process of going from the conception of new, more advanced instruments to their operational implementation and full utilization by the weather forecast communities is not optimal. Instruments developed for research purposes may have insufficient funding to explore their potential operational capabilities. Furthermore, instrument development programs designed for operational satellites typically have insufficient funding for assimilation algorithms needed to transform the satellite observations into data that can be used by sophisticated global weather forecast models. As a result, years often go by before satellite data are efficiently used for operational forecasts. NASA and NOAA each have unique expertise in the design of satellite instruments, their use for basic and applied research and their utilization in weather and climate research. At a time of limited resources, the two agencies must combine their efforts to work toward common

  5. Reducing Uncertainties of Hydrologic Model Predictions Using a New Ensemble Pre-Processing Approach

    NASA Astrophysics Data System (ADS)

    Khajehei, S.; Moradkhani, H.

    2015-12-01

    Ensemble Streamflow Prediction (ESP) was developed to characterize the uncertainty in hydrologic predictions. However, ESP outputs are still prone to bias due to the uncertainty in the forcing data, initial condition, and model structure. Among these, uncertainty in forcing data has a major impact on the reliability of hydrologic simulations/forecasts. Major steps have been taken in generating less uncertain precipitation forecasts such as the Ensemble Pre-Processing (EPP) to achieve this goal. EPP is introduced as a statistical procedure based on the bivariate joint distribution between observation and forecast to generate ensemble climatologic forecast from single-value forecast. The purpose of this study is to evaluate the performance of pre-processed ensemble precipitation forecast in generating ensemble streamflow predictions. Copula functions used in EPP, model the multivariate joint distribution between univariate variables with any level of dependency. Accordingly, ESP is generated by employing both raw ensemble precipitation forecast as well as pre-processed ensemble precipitation. The ensemble precipitation forecast is taken from Climate Forecast System (CFS) generated by National Weather Service's (NWS) National Centers for Environmental Prediction (NCEP) models. Study is conducted using the precipitation Runoff Modeling System (PRMS) over two basins in the Pacific Northwest USA for the period of 1979 to 2013. Results reveal that applying this new EPP will lead to reduction of uncertainty and overall improvement in the ESP.

  6. Predictive occurrence models for coastal wetland plant communities: delineating hydrologic response surfaces with multinomial logistic regression

    USGS Publications Warehouse

    Snedden, Gregg A.; Steyer, Gregory D.

    2013-01-01

    Understanding plant community zonation along estuarine stress gradients is critical for effective conservation and restoration of coastal wetland ecosystems. We related the presence of plant community types to estuarine hydrology at 173 sites across coastal Louisiana. Percent relative cover by species was assessed at each site near the end of the growing season in 2008, and hourly water level and salinity were recorded at each site Oct 2007–Sep 2008. Nine plant community types were delineated with k-means clustering, and indicator species were identified for each of the community types with indicator species analysis. An inverse relation between salinity and species diversity was observed. Canonical correspondence analysis (CCA) effectively segregated the sites across ordination space by community type, and indicated that salinity and tidal amplitude were both important drivers of vegetation composition. Multinomial logistic regression (MLR) and Akaike's Information Criterion (AIC) were used to predict the probability of occurrence of the nine vegetation communities as a function of salinity and tidal amplitude, and probability surfaces obtained from the MLR model corroborated the CCA results. The weighted kappa statistic, calculated from the confusion matrix of predicted versus actual community types, was 0.7 and indicated good agreement between observed community types and model predictions. Our results suggest that models based on a few key hydrologic variables can be valuable tools for predicting vegetation community development when restoring and managing coastal wetlands.

  7. Impact of time-variable vegetation on accuracy of rapid hydrologic predictions

    NASA Astrophysics Data System (ADS)

    Stec, Magdalena; Niedzielski, Tomasz

    2016-04-01

    It is crucial to identify the processes that impact errors of hydrologic forecasts. Since existence of vegetation and its ability to store precipitation is an important element of water distribution in the catchment, especially at the beginning of a rainfall event, it may be considered as one of the processes influencing skills of hydrological forecasts. The main objective of the study is to verify the hypothesis that water level predictions are controlled by vegetation dynamics in the contributing mountainous basins. The analysis is conducted for the upper Nysa Klodzka catchment with the outlet in Bardo (SW Poland). The basin includes a mid-mountain abasement covered with crops, while surrounding medium-altitude mountain ranges are mainly covered with forests. We focus on the entire year, from autumn 2013 to summer 2014. Herein, we analyze prediction errors and efficiency measures of hydrologic forecasts provided by two stochastic models - uni- and multivariate autoregressive models as well as their two-model ensemble prediction. In addition, we use the satellite-derived Leaf Area Index (LAI) images from the Moderate Resolution Imaging Spectroradiometer (MODIS). Hydrological prognoses are derived by the HydroProg real-time rapid forecasting system, built at the University of Wroclaw (Poland) in frame of the research project 2011/01/D/ST10/04171 of the National Science Centre of Poland. Correlation analysis between the plant maximum water storage capacity and prediction error/skill statistics (mean absolute error, root mean square error, Nash-Sutcliffe efficiency , index of agreement) is conducted. To cope with small sample size, the bootstrap simulation is performed. We conclude that there is a strong negative association between mean or median prediction errors and vegetation state for all meteorological seasons of a year. This result implies that basins with higher interception potential are more vulnerable to forecast inaccuracy than those with sparse natural

  8. Combining meteorological ensemble prediction, data assimilation and hydrological multimodel to reduce and untangle sources of uncertainty

    NASA Astrophysics Data System (ADS)

    Thiboult, Antoine; Anctil, François; Boucher, Marie-Amélie

    2015-04-01

    Hydrological ensemble prediction systems offer the possibility to dynamically assess forecast uncertainty. An ensemble may be issued wherever the uncertainty is situated along the meteorological chain. We commonly identify three main sources of uncertainty: meteorological forcing, hydrological initial conditions, and structural and parameter uncertainty. To address these uncertainties, different techniques have been developed. Meteorological ensemble prediction systems gained in popularity among researchers and operational forecasters as it allows to account for forcing uncertainties. Many data assimilation techniques have been applied to hydrology to reinitialize model states in order to issue more accurate and sharper predictive density functions. At last, multimodel simulation allows to get away from the quest of single best parameter and structure pitfall. The knowledge about these individual techniques is getting extensive and many individual applications can be found in the literature. Even though they proved to improve upon traditional forecasting, they frequently fail to issue fully reliable hydrological forecast as all sources of uncertainty are not tackled. Therefore, an improvement can be obtained in combining them, as it provides a more comprehensive handling of errors. Moreover, using these techniques separately or in combination allows to issue more reliable forecasts but also to identify explicitly the amount of total uncertainty that each technique accounts for. At the end, these sources of error can be characterized in terms of magnitude and lead time influence. As these techniques are frequently used alone, they are usually tuned to perform individually. To reach optimal performance, they should be set jointly. Among them, the data assimilation technique offers a large flexibility in its setting and therefore requires a proper setting considering the other ensemble techniques used. This question is also raised for the hydrological model selection

  9. Delineation of homogenous regions using hydrological variables predicted by projection pursuit regression

    NASA Astrophysics Data System (ADS)

    Durocher, Martin; Chebana, Fateh; Ouarda, Taha B. M. J.

    2016-11-01

    This study investigates the utilization of hydrological information in regional flood frequency analysis (RFFA) to enforce desired properties for a group of gauged stations. Neighbourhoods are particular types of regions that are centred on target locations. A challenge for using neighbourhoods in RFFA is that hydrological information is not available at target locations and cannot be completely replaced by the available physiographical information. Instead of using the available physiographic characteristics to define the centre of a target location, this study proposes to introduce estimates of reference hydrological variables to ensure a better homogeneity. These reference variables represent nonlinear relations with the site characteristics obtained by projection pursuit regression, a nonparametric regression method. The resulting neighbourhoods are investigated in combination with commonly used regional models: the index-flood model and regression-based models. The complete approach is illustrated in a real-world case study with gauged sites from the southern part of the province of Québec, Canada, and is compared with the traditional approaches such as region of influence and canonical correlation analysis. The evaluation focuses on the neighbourhood properties as well as prediction performances, with special attention devoted to problematic stations. Results show clear improvements in neighbourhood definitions and quantile estimates.

  10. Use of radar rainfall estimates in hydrological models: an assessment of predictive uncertainty

    NASA Astrophysics Data System (ADS)

    Borga, M.

    2003-04-01

    Radar estimates of rainfall are being increasingly applied to flood forecasting applications. Errors are inherent both in the process of estimating rainfall from radar and in the modelling of the rainfall-runoff transformation. This paper addresses the problem of evaluating the impact of the rainfall-runoff model parameter uncertainty on the propagation of radar errors trough the hydrological model. Model parameter uncertainty is explicitly accounted for by use of the GLUE (Generalized Likelihood Uncertainty Estimation; Beven and Binley, 1992). The GLUE procedure is used in this study as a means of hydrological model comparison using different rainfall input, provided by dense rain gage networks and by radar estimates according to various processing scenarios. The uncertainty assessment is carried out here through application of radar-estimated precipitation to a lumped rainfall-runoff model for the Brue catchment, a medium-sized watershed located in Somerset, south-west England. The analysis framework allows to evaluate both the wideness of the uncertainty limits and the percentage of observations included in the limits, with varying the behavioural threshold. This helps to assess the impact of radar rainfall errors on the output of a hydrological model previously conditioned using rainfall data from a dense raingauge network. The evaluation is reported in terms of both structural validity and predictive capability of the resulting model output. Several features are worth summarising here. Runoff simulations appear very sensitive to the impact of errors related to variability of reflectivity with height, which dominate the radar error structure. The runoff model defined by using unadjusted radar estimates for higher beam elevations is structurally invalid due to poorly defined input data. Results show the critical importance of proper adjustment of radar estimates. Uncertainty affecting runoff predictions from adjusted radar data are close to those generated by

  11. Probabilistic prediction of hydrologic drought using a conditional probability approach based on the meta-Gaussian model

    NASA Astrophysics Data System (ADS)

    Hao, Zengchao; Hao, Fanghua; Singh, Vijay P.; Sun, Alexander Y.; Xia, Youlong

    2016-11-01

    Prediction of drought plays an important role in drought preparedness and mitigation, especially because of large impacts of drought and increasing demand for water resources. An important aspect for improving drought prediction skills is the identification of drought predictability sources. In general, a drought originates from precipitation deficit and thus the antecedent meteorological drought may provide predictive information for other types of drought. In this study, a hydrological drought (represented by Standardized Runoff Index (SRI)) prediction method is proposed based on the meta-Gaussian model taking into account the persistence and its prior meteorological drought condition (represented by Standardized Precipitation Index (SPI)). Considering the inherent nature of standardized drought indices, the meta-Gaussian model arises as a suitable model for constructing the joint distribution of multiple drought indices. Accordingly, the conditional distribution of hydrological drought can be derived analytically, which enables the probabilistic prediction of hydrological drought in the target period and uncertainty quantifications. Based on monthly precipitation and surface runoff of climate divisions of Texas, U.S., 1-month and 2-month lead predictions of hydrological drought are illustrated and compared to the prediction from Ensemble Streamflow Prediction (ESP). Results, based on 10 climate divisions in Texas, show that the proposed meta-Gaussian model provides useful drought prediction information with performance depending on regions and seasons.

  12. Predictive Models of the Hydrological Regime of Unregulated Streams in Arizona

    USGS Publications Warehouse

    Anning, David W.; Parker, John T.C.

    2009-01-01

    Three statistical models were developed by the U.S. Geological Survey in cooperation with the Arizona Department of Environmental Quality to improve the predictability of flow occurrence in unregulated streams throughout Arizona. The models can be used to predict the probabilities of the hydrological regime being one of four categories developed by this investigation: perennial, which has streamflow year-round; nearly perennial, which has streamflow 90 to 99.9 percent of the year; weakly perennial, which has streamflow 80 to 90 percent of the year; or nonperennial, which has streamflow less than 80 percent of the year. The models were developed to assist the Arizona Department of Environmental Quality in selecting sites for participation in the U.S. Environmental Protection Agency's Environmental Monitoring and Assessment Program. One model was developed for each of the three hydrologic provinces in Arizona - the Plateau Uplands, the Central Highlands, and the Basin and Range Lowlands. The models for predicting the hydrological regime were calibrated using statistical methods and explanatory variables of discharge, drainage-area, altitude, and location data for selected U.S. Geological Survey streamflow-gaging stations and a climate index derived from annual precipitation data. Models were calibrated on the basis of streamflow data from 46 stations for the Plateau Uplands province, 82 stations for the Central Highlands province, and 90 stations for the Basin and Range Lowlands province. The models were developed using classification trees that facilitated the analysis of mixed numeric and factor variables. In all three models, a threshold stream discharge was the initial variable to be considered within the classification tree and was the single most important explanatory variable. If a stream discharge value at a station was below the threshold, then the station record was determined as being nonperennial. If, however, the stream discharge was above the threshold

  13. Improving hydrologic predictions of a catchment model via assimilation of surface soil moisture

    NASA Astrophysics Data System (ADS)

    Chen, Fan; Crow, Wade T.; Starks, Patrick J.; Moriasi, Daniel N.

    2011-04-01

    This paper examines the potential for improving Soil and Water Assessment Tool (SWAT) hydrologic predictions of root-zone soil moisture, evapotranspiration, and stream flow within the 341 km 2 Cobb Creek Watershed in southwestern Oklahoma through the assimilation of surface soil moisture observations using an Ensemble Kalman filter (EnKF). In a series of synthetic twin experiments assimilating surface soil moisture is shown to effectively update SWAT upper-layer soil moisture predictions and provide moderate improvement to lower layer soil moisture and evapotranspiration estimates. However, insufficient SWAT-predicted vertical coupling results in limited updating of deep soil moisture, regardless of the SWAT parameterization chosen for root-water extraction. Likewise, a real data assimilation experiment using ground-based soil moisture observations has only limited success in updating upper-layer soil moisture and is generally unsuccessful in enhancing SWAT stream flow predictions. Comparisons against ground-based observations suggest that SWAT significantly under-predicts the magnitude of vertical soil water coupling at the site, and this lack of coupling impedes the ability of the EnKF to effectively update deep soil moisture, groundwater flow and surface runoff. The failed attempt to improve stream flow prediction is also attributed to the inability of the EnKF to correct for existing biases in SWAT-predicted stream flow components.

  14. Predicting current and future peatmoss drought stress: Impact of hydrological complexity

    NASA Astrophysics Data System (ADS)

    Nijp, Jelmer; Metselaar, Klaas; Limpens, Juul; Teutschbein, Claudia; Peichl, Matthias; Nilsson, Mats; Berendse, Frank; van der Zee, Sjoerd

    2016-04-01

    Northern peatlands sequester enormous amounts of carbon and therefore represent a carbon store of global importance. The vegetation in northern peatlands is dominated by peat-forming bryophytes of the genus Sphagnum. The growth of this carbon fixer, and hence its carbon uptake, strongly depends on the moisture availability in the living moss layer, which is a function of both water table and rewetting by rain. Peatland hydrology models are used to predict how changes in climate may modify the future water balance of peatmoss carpets and influence associated carbon and energy balances. These models, however, differ considerably in the number and type of processes included, which will have yet unknown consequences for peatland drought predictions in a future climate. Here, we assessed the importance of rainwater storage and peat volume change for predicting peatmoss drought projections in northern peatlands using an ensemble of downscaled, bias-corrected climate scenarios for current (1991 - 2020) and future (2061 - 2090) climate. Peatmoss drought projections were compared among four model variants with or without rainwater storage in the peatmoss carpet and peat volume change, which are considered as two important hydrological feedbacks controlling moss moisture availability. The performance of the four model variants was assessed using field data from a site in northern Sweden (Degerö Stormyr, 64°N 19°E). Our results show that adding rainwater storage in the moss layer as well as peat volume change significantly improved model performance; the most complex model had best model performance. Compared to the reference model, including both model extensions reduced the predicted drought frequency experienced by peatmoss with around 50%. Moreover, projected climate change is expected to reduce predicted peatmoss drought stress with about 20% for the studied site. In conclusion, this study shows that including rainwater storage in the peatmoss layer and/or peat volume

  15. An Integrated Bayesian Uncertainty Estimator: fusion of Input, Parameter and Model Structural Uncertainty Estimation in Hydrologic Prediction System

    NASA Astrophysics Data System (ADS)

    Ajami, N. K.; Duan, Q.; Sorooshian, S.

    2005-12-01

    To-date single conceptual hydrologic models often applied to interpret physical processes within a watershed. Nevertheless hydrologic models regardless of their sophistication and complexity are simplified representation of the complex, spatially distributed and highly nonlinear real world system. Consequently their hydrologic predictions contain considerable uncertainty from different sources including: hydrometeorological forcing inputs, boundary/initial conditions, model structure, model parameters which need to be accounted for. Thus far the effort has gone to address these sources of uncertainty explicitly, making an implicit assumption that uncertainties from different sources are additive. Nevertheless because of the nonlinear nature of the hydrologic systems, it is not feasible to account for these uncertainties independently. Here we present the Integrated Bayesian Uncertainty Estimator (IBUNE) which accounts for total uncertainties from all major sources: inputs forcing, model structure, model parameters. This algorithm explores multi-model framework to tackle model structural uncertainty while using the Bayesian rules to estimate parameter and input uncertainty within individual models. Three hydrologic models including SACramento Soil Moisture Accounting (SAC-SMA) model, Hydrologic model (HYMOD) and Simple Water Balance (SWB) model were considered within IBUNE framework for this study. The results which are presented for the Leaf River Basin, MS, indicates that IBUNE gives a better quantification of uncertainty through hydrological modeling processes, therefore provide more reliable and less bias prediction with realistic uncertainty boundaries.

  16. Recent Advances in Predictive (Machine) Learning

    SciTech Connect

    Friedman, J

    2004-01-24

    Prediction involves estimating the unknown value of an attribute of a system under study given the values of other measured attributes. In prediction (machine) learning the prediction rule is derived from data consisting of previously solved cases. Most methods for predictive learning were originated many years ago at the dawn of the computer age. Recently two new techniques have emerged that have revitalized the field. These are support vector machines and boosted decision trees. This paper provides an introduction to these two new methods tracing their respective ancestral roots to standard kernel methods and ordinary decision trees.

  17. Sharp landscape features and their role in predictive hydrology and geomorphology

    NASA Astrophysics Data System (ADS)

    Belmont, P.; Foufoula, E.; Passalacqua, P.

    2012-12-01

    Sharp topographic features often represent critical boundaries, or discontinuities, in hydrologic and geomorphic processes. Many such features are found in the proximity of actively evolving river channels (e.g., small knickpoints, steep channel banks, natural levees, scroll bars, and floodplain microtopography). While these features are often overlooked in hydro-geomorphic modeling, they can be used as indicators of channel dynamics. The increasing availability and quality of high-resolution topography data provides new opportunities to utilize these sharp features to interpret geomorphic processes and identify critical process-boundaries. However, sophisticated and automated techniques are needed for delineation and measurement of these sharp features over spatially extensive areas (i.e., entire channel-floodplain networks). Further, these features occur at scales much smaller than the grid scale of predictive hydrologic and morphodynamic models, raising the need for sub-grid scale parameterizations, or closures. In this work we present such techniques and use the Minnesota River Basin (MRB) as a prototype system to investigate the distinct assemblages of sharp features that exist in different geomorphic environments, connect them to the processes responsible for their formation, and propose ways for incorporating them in hydro-geomorphologic modeling. The MRB is a predominantly agricultural watershed with pervasive human modifications, an accelerating hydrologic cycle, a uniquely dynamic geologic history, and severe impairments for sediment and eutrophication. The MRB channel-floodplain network exhibits an exceptionally broad range of geomorphic environments, including rapidly meandering, incising, and aggrading reaches, making it an ideal location to study the linkages between form and process. Specific challenges are discussed in deriving sub-grid scale closures that implicitly account for these sharp features and developments needed for increased prediction

  18. Value of medium range weather forecasts in the improvement of seasonal hydrologic prediction skill

    SciTech Connect

    Shukla, Shraddhanand; Voisin, Nathalie; Lettenmaier, D. P.

    2012-08-15

    We investigated the contribution of medium range weather forecasts with lead times up to 14 days to seasonal hydrologic prediction skill over the Conterminous United States (CONUS). Three different Ensemble Streamflow Prediction (ESP)-based experiments were performed for the period 1980-2003 using the Variable Infiltration Capacity (VIC) hydrology model to generate forecasts of monthly runoff and soil moisture (SM) at lead-1 (first month of the forecast period) to lead-3. The first experiment (ESP) used a resampling from the retrospective period 1980-2003 and represented full climatological uncertainty for the entire forecast period. In the second and third experiments, the first 14 days of each ESP ensemble member were replaced by either observations (perfect 14-day forecast) or by a deterministic 14-day weather forecast. We used Spearman rank correlations of forecasts and observations as the forecast skill score. We estimated the potential and actual improvement in baseline skill as the difference between the skill of experiments 2 and 3 relative to ESP, respectively. We found that useful runoff and SM forecast skill at lead-1 to -3 months can be obtained by exploiting medium range weather forecast skill in conjunction with the skill derived by the knowledge of initial hydrologic conditions. Potential improvement in baseline skill by using medium range weather forecasts, for runoff (SM) forecasts generally varies from 0 to 0.8 (0 to 0.5) as measured by differences in correlations, with actual improvement generally from 0 to 0.8 of the potential improvement. With some exceptions, most of the improvement in runoff is for lead-1 forecasts, although some improvement in SM was achieved at lead-2.

  19. Advanced technology wind shear prediction system evaluation

    NASA Technical Reports Server (NTRS)

    Gering, Greg

    1992-01-01

    The program overviews: (1) American Airline (AA)/Turbulence Prediction Systems (TPS), which have installed forward looking infrared predictive windshear system on 3 MD-80 aircraft; (2) AA/TPS AWAS III evaluation, which is a joint effort and is installed in the noise landing gear (NLG) area and a data recorder installed in the E/E compartment.

  20. Assessment of hydrological model predictive ability given multiple conceptual geological models

    NASA Astrophysics Data System (ADS)

    Seifert, Dorte; Sonnenborg, Torben O.; Refsgaard, Jens Christian; HøJberg, Anker L.; Troldborg, Lars

    2012-06-01

    In this study six hydrological models that only differ with respect to their conceptual geological models are established for a 465 km2 area. The performances of the six models are evaluated in differential split-sample tests against a unique data set with well documented groundwater head and discharge data for different periods with different groundwater abstractions. The calibration results of the six models are comparable, with no model being superior to the others. Though, the six models make very different predictions of changes in groundwater head and discharges as a response to changes in groundwater abstraction. This confirms the utmost importance of the conceptual geological model for making predictions of variables and conditions beyond the calibration situation. In most cases the observed changes in hydraulic head and discharge are within the range of the changes predicted by the six models implying that a multiple modeling approach can be useful in obtaining more robust assessments of likely prediction errors. We conclude that the use of multiple models appear to be a good alternative to traditional differential split-sample schemes. A model averaging analysis shows that model weights estimated from model performance in the calibration or validation situation in many cases are not optimal for making other predictions. Hence, the critical assumption that is always made in model averaging, namely that the model weights derived from the calibration situation are also optimal for model predictions, cannot be assumed to be generally valid.

  1. Predicting success on the Advanced Placement Biology Examination

    NASA Astrophysics Data System (ADS)

    Shepherd, Lesa Hanlin

    Four hundred sixty students in four public high schools were used as subjects to determine which of eleven academic and demographic factors studied were significant predictors of success for the Advanced Placement Biology Examination. Factors studied were attendance, class rank, gender, grade level at the time of the examination, grade point average, level of prerequisite biology course, number of Advanced Placement Examinations taken in the year prior to the Advanced Placement Biology Examination, number of Advanced Placement Examinations taken in the same year as the Advanced Placement Biology Examination, proposed major in college, race, and SAT mathematics, verbal, and combined score. Significant relationships were found to exist between the Advanced Placement Biology Examination score and attendance, class rank, gender, grade level at the time of the Advanced Placement Biology Examination, grade point average, number of Advanced Placement Examinations taken in the year prior to the Advanced Placement Biology Examination, number of Advanced Placement Examinations taken in the same year as the Advanced Placement Biology Examination, race, and SAT scores. Significant relationships were not found to exist between Advanced Placement Biology Examination score and level prerequisite biology course and Advanced Placement Biology Examination score and proposed major in college. A multiple regression showed the best combination of predictors to be attendance, SAT verbal score, and SAT mathematics score. Discriminant analysis showed the variables in this study to be good predictors of whether the student would pass the Advanced Placement Biology Examination (score a 3, 4, or 5) or fail the Advanced Placement Biology Examination (score a 1 or 2). These results demonstrated that significant predictors for the Advanced Placement Biology Examination do exist and can be used to assist in the prediction of scores, prediction of passing or failing, the identification of

  2. Tuning stochastic matrix models with hydrologic data to predict the population dynamics of a riverine fish

    USGS Publications Warehouse

    Sakaris, P.C.; Irwin, E.R.

    2010-01-01

    We developed stochastic matrix models to evaluate the effects of hydrologic alteration and variable mortality on the population dynamics of a lotie fish in a regulated river system. Models were applied to a representative lotic fish species, the flathead catfish (Pylodictis olivaris), for which two populations were examined: a native population from a regulated reach of the Coosa River (Alabama, USA) and an introduced population from an unregulated section of the Ocmulgee River (Georgia, USA). Size-classified matrix models were constructed for both populations, and residuals from catch-curve regressions were used as indices of year class strength (i.e., recruitment). A multiple regression model indicated that recruitment of flathead catfish in the Coosa River was positively related to the frequency of spring pulses between 283 and 566 m3/s. For the Ocmulgee River population, multiple regression models indicated that year class strength was negatively related to mean March discharge and positively related to June low flow. When the Coosa population was modeled to experience five consecutive years of favorable hydrologic conditions during a 50-year projection period, it exhibited a substantial spike in size and increased at an overall 0.2% annual rate. When modeled to experience five years of unfavorable hydrologic conditions, the Coosa population initially exhibited a decrease in size but later stabilized and increased at a 0.4% annual rate following the decline. When the Ocmulgee River population was modeled to experience five years of favorable conditions, it exhibited a substantial spike in size and increased at an overall 0.4% annual rate. After the Ocmulgee population experienced five years of unfavorable conditions, a sharp decline in population size was predicted. However, the population quickly recovered, with population size increasing at a 0.3% annual rate following the decline. In general, stochastic population growth in the Ocmulgee River was more

  3. Multi-variable evaluation of hydrological model predictions for a headwater basin in the Canadian Rocky Mountains

    NASA Astrophysics Data System (ADS)

    Fang, X.; Pomeroy, J. W.; Ellis, C. R.; MacDonald, M. K.; DeBeer, C. M.; Brown, T.

    2012-11-01

    One of the purposes of the Cold Regions Hydrological Modelling platform (CRHM) is to diagnose inadequacies in the understanding of the hydrological cycle and its simulation. A physically based hydrological model including a full suite of snow and cold regions hydrology processes as well as warm season, hillslope and groundwater hydrology was developed in CRHM for application in the Marmot Creek Research Basin (~ 9.4km2), located in the Front Ranges of Canadian Rocky Mountains. Parameters were selected from digital elevation model, forest, soil and geological maps, and from the results of many cold regions hydrology studies in the region and elsewhere. Non-calibrated simulations were conducted for six hydrological years during 2005-2011 and were compared with detailed field observations of several hydrological cycle components. Results showed good model performance for snow accumulation and snowmelt compared to the field observations for four seasons during 2007-2011, with a small bias and normalized root mean square difference (NRMSD) ranging from 40 to 42% for the subalpine conifer forests and from 31 to 67% for the alpine tundra and tree-line larch forest environments. Overestimation or underestimation of the peak SWE ranged from 1.6 to 29%. Simulations matched well with the observed unfrozen moisture fluctuation in the top soil layer at a lodgepole pine site during 2006-2011, with a NRMSD ranging from 17% to 39%, but with consistent overestimation of 7 to 34%. Evaluations of seasonal streamflow during 2006-2011 revealed the model generally predicted well compared to observations at the basin scale, with a NRMSD of 77% and small model bias (6%), but at the sub-basin scale NRMSD were larger, ranging from 86 to 106%; though overestimation or underestimation for the cumulative seasonal discharge was within 24%. Timing of discharge was better predicted at the Marmot Creek basin outlet having a Nash-Sutcliffe efficiency (NSE) of 0.31 compared to the outlets of the sub

  4. Multi-variable evaluation of hydrological model predictions for a headwater basin in the Canadian Rocky Mountains

    NASA Astrophysics Data System (ADS)

    Fang, X.; Pomeroy, J. W.; Ellis, C. R.; MacDonald, M. K.; DeBeer, C. M.; Brown, T.

    2013-04-01

    One of the purposes of the Cold Regions Hydrological Modelling platform (CRHM) is to diagnose inadequacies in the understanding of the hydrological cycle and its simulation. A physically based hydrological model including a full suite of snow and cold regions hydrology processes as well as warm season, hillslope and groundwater hydrology was developed in CRHM for application in the Marmot Creek Research Basin (~ 9.4 km2), located in the Front Ranges of the Canadian Rocky Mountains. Parameters were selected from digital elevation model, forest, soil, and geological maps, and from the results of many cold regions hydrology studies in the region and elsewhere. Non-calibrated simulations were conducted for six hydrological years during the period 2005-2011 and were compared with detailed field observations of several hydrological cycle components. The results showed good model performance for snow accumulation and snowmelt compared to the field observations for four seasons during the period 2007-2011, with a small bias and normalised root mean square difference (NRMSD) ranging from 40 to 42% for the subalpine conifer forests and from 31 to 67% for the alpine tundra and treeline larch forest environments. Overestimation or underestimation of the peak SWE ranged from 1.6 to 29%. Simulations matched well with the observed unfrozen moisture fluctuation in the top soil layer at a lodgepole pine site during the period 2006-2011, with a NRMSD ranging from 17 to 39%, but with consistent overestimation of 7 to 34%. Evaluations of seasonal streamflow during the period 2006-2011 revealed that the model generally predicted well compared to observations at the basin scale, with a NRMSD of 60% and small model bias (1%), while at the sub-basin scale NRMSDs were larger, ranging from 72 to 76%, though overestimation or underestimation for the cumulative seasonal discharge was within 29%. Timing of discharge was better predicted at the Marmot Creek basin outlet, having a Nash

  5. Quantifying uncertainties in streamflow predictions through signature based inference of hydrological model parameters

    NASA Astrophysics Data System (ADS)

    Fenicia, Fabrizio; Reichert, Peter; Kavetski, Dmitri; Albert, Calro

    2016-04-01

    The calibration of hydrological models based on signatures (e.g. Flow Duration Curves - FDCs) is often advocated as an alternative to model calibration based on the full time series of system responses (e.g. hydrographs). Signature based calibration is motivated by various arguments. From a conceptual perspective, calibration on signatures is a way to filter out errors that are difficult to represent when calibrating on the full time series. Such errors may for example occur when observed and simulated hydrographs are shifted, either on the "time" axis (i.e. left or right), or on the "streamflow" axis (i.e. above or below). These shifts may be due to errors in the precipitation input (time or amount), and if not properly accounted in the likelihood function, may cause biased parameter estimates (e.g. estimated model parameters that do not reproduce the recession characteristics of a hydrograph). From a practical perspective, signature based calibration is seen as a possible solution for making predictions in ungauged basins. Where streamflow data are not available, it may in fact be possible to reliably estimate streamflow signatures. Previous research has for example shown how FDCs can be reliably estimated at ungauged locations based on climatic and physiographic influence factors. Typically, the goal of signature based calibration is not the prediction of the signatures themselves, but the prediction of the system responses. Ideally, the prediction of system responses should be accompanied by a reliable quantification of the associated uncertainties. Previous approaches for signature based calibration, however, do not allow reliable estimates of streamflow predictive distributions. Here, we illustrate how the Bayesian approach can be employed to obtain reliable streamflow predictive distributions based on signatures. A case study is presented, where a hydrological model is calibrated on FDCs and additional signatures. We propose an approach where the likelihood

  6. Predicting RNA structure: advances and limitations.

    PubMed

    Hofacker, Ivo L; Lorenz, Ronny

    2014-01-01

    RNA secondary structures can be predicted using efficient algorithms. A widely used software package implementing a large number of computational methods is the ViennaRNA Package. This chapter describes how to use programs from the ViennaRNA Package to perform common tasks such as prediction of minimum free-energy structures, suboptimal structures, or base pairing probabilities, and generating secondary structure plots with reliability annotation. Moreover, we present recent methods to assess the folding kinetics of an RNA via 2D projections of the energy landscape, identification of local minima and energy barriers, or simulation of RNA folding as a Markov process.

  7. Radar monitoring of hydrology in Maryland's forested coastal plain wetlands: Implications for predicted climate change and improved mapping

    NASA Astrophysics Data System (ADS)

    Weiner Lang, Megan

    Wetlands provide important services to society but Mid-Atlantic wetlands are at high risk for loss, with forested wetlands being especially vulnerable. Hydrology (flooding and soil moisture) controls wetland function and extent but it may be altered due to changes in climate and anthropogenic influence. Wetland hydrology must better understood in order to predict and mitigate the impact of these changes. Broad-scale forested wetland hydrology is difficult to monitor using ground-based and traditional remote sensing methods. C-band synthetic aperture radar (SAR) data could improve the capability to monitor forested wetland hydrology but the abilities and limitations of these data need further investigation. This study examined: (1) the link between climate and wetland hydrology; (2) the ability of ENVISAT SAR (C-HH and C-VV) data to monitor inundation and soil moisture in forested wetlands; (3) limitations inherent to C-band data (incidence angle, polarization, and phenology) when monitoring forested wetland hydrology; and (4) the accuracy of forested wetland maps produced using SAR data. The study was primarily conducted near the Patuxent River in Maryland but the influence of incidence angle was considered along the Roanoke River in North Carolina. This study showed: (1) climate was highly correlated with wetland inundation; (2) significant differences in C-VV and C-HH backscatter existed between forested areas of varying hydrology (uplands and wetlands) throughout the year; (3) C-HH backscatter was better correlated to hydrology than C-VV backscatter; (4) correlations were stronger during the leaf-off season; (5) the difference in backscatter between flooded and non-flooded areas did not sharply decline with incidence angle, as predicted; and (6) maps produced using SAR data had relatively high accuracy levels. Based on these findings, I concluded that hydrology is influenced by climate at the study site, and C-HH data should be able to monitor changes in

  8. Numerical daemons in hydrological modeling: Effects on uncertainty assessment, sensitivity analysis and model predictions

    NASA Astrophysics Data System (ADS)

    Kavetski, D.; Clark, M. P.; Fenicia, F.

    2011-12-01

    Hydrologists often face sources of uncertainty that dwarf those normally encountered in many engineering and scientific disciplines. Especially when representing large scale integrated systems, internal heterogeneities such as stream networks, preferential flowpaths, vegetation, etc, are necessarily represented with a considerable degree of lumping. The inputs to these models are themselves often the products of sparse observational networks. Given the simplifications inherent in environmental models, especially lumped conceptual models, does it really matter how they are implemented? At the same time, given the complexities usually found in the response surfaces of hydrological models, increasingly sophisticated analysis methodologies are being proposed for sensitivity analysis, parameter calibration and uncertainty assessment. Quite remarkably, rather than being caused by the model structure/equations themselves, in many cases model analysis complexities are consequences of seemingly trivial aspects of the model implementation - often, literally, whether the start-of-step or end-of-step fluxes are used! The extent of problems can be staggering, including (i) degraded performance of parameter optimization and uncertainty analysis algorithms, (ii) erroneous and/or misleading conclusions of sensitivity analysis, parameter inference and model interpretations and, finally, (iii) poor reliability of a calibrated model in predictive applications. While the often nontrivial behavior of numerical approximations has long been recognized in applied mathematics and in physically-oriented fields of environmental sciences, it remains a problematic issue in many environmental modeling applications. Perhaps detailed attention to numerics is only warranted for complicated engineering models? Would not numerical errors be an insignificant component of total uncertainty when typical data and model approximations are present? Is this really a serious issue beyond some rare isolated

  9. Bayesian Analysis Diagnostics: Diagnosing Predictive and Parameter Uncertainty for Hydrological Models

    NASA Astrophysics Data System (ADS)

    Thyer, Mark; Kavetski, Dmitri; Evin, Guillaume; Kuczera, George; Renard, Ben; McInerney, David

    2015-04-01

    All scientific and statistical analysis, particularly in natural sciences, is based on approximations and assumptions. For example, the calibration of hydrological models using approaches such as Nash-Sutcliffe efficiency and/or simple least squares (SLS) objective functions may appear to be 'assumption-free'. However, this is a naïve point of view, as SLS assumes that the model residuals (residuals=observed-predictions) are independent, homoscedastic and Gaussian. If these assumptions are poor, parameter inference and model predictions will be correspondingly poor. An essential step in model development is therefore to verify the assumptions and approximations made in the modeling process. Diagnostics play a key role in verifying modeling assumptions. An important advantage of the formal Bayesian approach is that the modeler is required to make the assumptions explicit. Specialized diagnostics can then be developed and applied to test and verify their assumptions. This paper presents a suite of statistical and modeling diagnostics that can be used by environmental modelers to test their modeling calibration assumptions and diagnose model deficiencies. Three major types of diagnostics are presented: Residual Diagnostics Residual diagnostics are used to test whether the assumptions of the residual error model within the likelihood function are compatible with the data. This includes testing for statistical independence, homoscedasticity, unbiasedness, Gaussianity and any distributional assumptions. Parameter Uncertainty and MCMC Diagnostics An important part of Bayesian analysis is assess parameter uncertainty. Markov Chain Monte Carlo (MCMC) methods are a powerful numerical tool for estimating these uncertainties. Diagnostics based on posterior parameter distributions can be used to assess parameter identifiability, interactions and correlations. This provides a very useful tool for detecting and remedying model deficiencies. In addition, numerical diagnostics are

  10. High-speed limnology: using advanced sensors to investigate spatial variability in biogeochemistry and hydrology.

    PubMed

    Crawford, John T; Loken, Luke C; Casson, Nora J; Smith, Colin; Stone, Amanda G; Winslow, Luke A

    2015-01-06

    Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h(-1)) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial-aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

  11. High-speed limnology: Using advanced sensors to investigate spatial variability in biogeochemistry and hydrology

    USGS Publications Warehouse

    Crawford, John T.; Loken, Luke C.; Casson, Nora J.; Smith, Collin; Stone, Amanda G.; Winslow, Luke A.

    2015-01-01

    Advanced sensor technology is widely used in aquatic monitoring and research. Most applications focus on temporal variability, whereas spatial variability has been challenging to document. We assess the capability of water chemistry sensors embedded in a high-speed water intake system to document spatial variability. This new sensor platform continuously samples surface water at a range of speeds (0 to >45 km h–1) resulting in high-density, mesoscale spatial data. These novel observations reveal previously unknown variability in physical, chemical, and biological factors in streams, rivers, and lakes. By combining multiple sensors into one platform, we were able to detect terrestrial–aquatic hydrologic connections in a small dystrophic lake, to infer the role of main-channel vs backwater nutrient processing in a large river and to detect sharp chemical changes across aquatic ecosystem boundaries in a stream/lake complex. Spatial sensor data were verified in our examples by comparing with standard lab-based measurements of selected variables. Spatial fDOM data showed strong correlation with wet chemistry measurements of DOC, and optical NO3 concentrations were highly correlated with lab-based measurements. High-frequency spatial data similar to our examples could be used to further understand aquatic biogeochemical fluxes, ecological patterns, and ecosystem processes, and will both inform and benefit from fixed-site data.

  12. Robust quantitative parameter estimation by advanced CMP measurements for vadose zone hydrological studies

    NASA Astrophysics Data System (ADS)

    Koyama, C.; Wang, H.; Khuut, T.; Kawai, T.; Sato, M.

    2015-12-01

    Soil moisture plays a crucial role in the understanding of processes in the vadose zone hydrology. In the last two decades ground penetrating radar (GPR) has been widely discussed has nondestructive measurement technique for soil moisture data. Especially the common mid-point (CMP) technique, which has been used in both seismic and GPR surveys to investigate the vertical velocity profiles, has a very high potential for quantitaive obervsations from the root zone to the ground water aquifer. However, the use is still rather limited today and algorithms for robust quantitative paramter estimation are lacking. In this study we develop an advanced processing scheme for operational soil moisture reetrieval at various depth. Using improved signal processing, together with a semblance - non-normalized cross-correlation sum combined stacking approach and the Dix formula, the interval velocities for multiple soil layers are obtained from the RMS velocities allowing for more accurate estimation of the permittivity at the reflecting point. Where the presence of a water saturated layer, like a groundwater aquifer, can be easily identified by its RMS velocity due to the high contrast compared to the unsaturated zone. By using a new semi-automated measurement technique the acquisition time for a full CMP gather with 1 cm intervals along a 10 m profile can be reduced significantly to under 2 minutes. The method is tested and validated under laboratory conditions in a sand-pit as well as on agricultural fields and beach sand in the Sendai city area. Comparison between CMP estimates and TDR measurements yield a very good agreement with RMSE of 1.5 Vol.-%. The accuracy of depth estimation is validated with errors smaller than 2%. Finally, we demonstrate application of the method in a test site in semi-arid Mongolia, namely the Orkhon River catchment in Bulgan, using commercial 100 MHz and 500 MHz RAMAC GPR antennas. The results demonstrate the suitability of the proposed method for

  13. Hydrologic monitoring in 1-km2 headwater catchments in Sierra Nevada forests for predictive modeling of hydrologic response to forest treatments across 140-km2 firesheds

    NASA Astrophysics Data System (ADS)

    Saksa, P. C.; Bales, R. C.; Conklin, M. H.; Martin, S. E.; Rice, R.

    2010-12-01

    As part of the Sierra Nevada Adaptive Management Project, an eight-year study designed to measure the impacts of forest treatments (thinning, mastication, controlled burns) on multiple forest attributes, four headwater catchments were established to provide data on hydrologic response to treatments. These 1-km2 study catchments are each sited within 40-100 km2 firesheds, which in this case largely follow watershed boundaries, and which are the larger study areas for informing adaptive management of approximately 3,000 km2 of mixed-conifer forest in California’s central and southern Sierra Nevada. The aim of the hydrologic design was to put in place a ground-based monitoring network that would measure hydrologic attributes at representative locations, and when combined with remotely sensed data, provide a basis for predictive modeling of the larger study area. The selected locations employ instrument clusters, or groupings of instruments in a compact arrangement, to maximize the number of measurements possible and accessibility to the monitoring sites. The two study firesheds , located in the Tahoe and Sierra National Forests, cover a total of about 140-km2. Within each fireshed, two meteorological stations were placed near 1650-m and 2150-m, spanning the precipitation gradient from lower-elevation rain-dominated to higher-elevation snow-dominated systems. Two headwater streams draining approximately 1-km2 are monitored for stage, discharge, electrical conductivity, and sediment movement. Additionally, instrument nodes to monitor temperature, snow depth and soil moisture are installed within 0.5-1 km of the outlet and meterological stations. These nodes were placed to monitor end members of aspect, slope, elevation and canopy cover, which set the boundaries for the model outputs. High-resolution LiDAR provides the topographic and distributed vegetation characteristics, which are combined with field surveys and standard soils information to define the modeling

  14. Predicting Production Costs for Advanced Aerospace Vehicles

    NASA Technical Reports Server (NTRS)

    Bao, Han P.; Samareh, J. A.; Weston, R. P.

    2002-01-01

    For early design concepts, the conventional approach to cost is normally some kind of parametric weight-based cost model. There is now ample evidence that this approach can be misleading and inaccurate. By the nature of its development, a parametric cost model requires historical data and is valid only if the new design is analogous to those for which the model was derived. Advanced aerospace vehicles have no historical production data and are nowhere near the vehicles of the past. Using an existing weight-based cost model would only lead to errors and distortions of the true production cost. This paper outlines the development of a process-based cost model in which the physical elements of the vehicle are soared according to a first-order dynamics model. This theoretical cost model, first advocated by early work at MIT, has been expanded to cover the basic structures of an advanced aerospace vehicle. Elemental costs based on the geometry of the design can be summed up to provide an overall estimation of the total production cost for a design configuration. This capability to directly link any design configuration to realistic cost estimation is a key requirement for high payoff MDO problems. Another important consideration in this paper is the handling of part or product complexity. Here the concept of cost modulus is introduced to take into account variability due to different materials, sizes, shapes, precision of fabrication, and equipment requirements. The most important implication of the development of the proposed process-based cost model is that different design configurations can now be quickly related to their cost estimates in a seamless calculation process easily implemented on any spreadsheet tool.

  15. Coupling crop growth and hydrologic models to predict crop yield with spatial analysis technologies

    NASA Astrophysics Data System (ADS)

    Jia, Yangwen; Shen, Suhui; Niu, Cunwen; Qiu, Yaqin; Wang, Hao; Liu, Yu

    2011-01-01

    This paper analyzes climate change impact on crop yield of winter wheat, a main crop in the water-stressed Haihe River Basin in North China. An integrated analysis was carried out by coupling the World Food Studies (WOFOST) crop growth model and the distributed hydrological model describing the water and energy transfer processes in large river basins (WEP-L). Various spatial analysis technologies, including remote sensing and geographical information system, were woven together to support model calibration and validation. The WOFOST model was calibrated and validated using the winter wheat data collected in two successive years. Effort was then extended to calibrate and validate the WEP-L distributed hydrologic model for the whole basin. Such an effort was collectively supported by using the remote sensing evapotranspiration and biomass data, the in situ river flow data, and the wheat yield statistical data. With this integration, the wheat yield from 2010 to 2030 can be predicted under the given climate change impact corresponding to Intergovernmental Panel on Climate Change A1B, A2, and B1 scenarios. Given the prescribed climate change scenarios, at the basin-scale, the winter wheat yield may increase in terms of the annual average; however, the long-term trend is geared toward a decreasing yield with significant fluctuations. The colder hilly areas with current lower yield may significantly increase due to possible future temperature rise while the warmer plain areas with current higher yield may slightly increase or decrease. Despite the data collected thus far, it is evident that further studies are needed to reduce the uncertainties of these predictions of climate change effect on winter wheat grain yield.

  16. Evaluation of Hydrologic Models to Predict Sediment Export With Changing Land Use in Leeward Hawaiian Watersheds

    NASA Astrophysics Data System (ADS)

    Falinski, K. A.; Oleson, K.; Nielson, J.

    2014-12-01

    Land-based sediments are a key threat to shallow coral reef ecosystems in Hawaii. Estimating sediment export is a critical step to being able to connect future land use changes with changes in sediment released to the coastal zone. However, empirically- and process-based hydrological models have proven difficult to adapt to Hawaii's geography, adding significant uncertainty to using available decision support tools. Four soil loss and sediment yield models, InVEST, N-SPECT, SWAT and GSSHA, were compared. Data including precipitation, flow discharge, and suspended sediment concentration were compiled from four leeward watersheds in the Hawaiian Islands. These were combined with the most recently available GIS data on soils, rainfall, land use and 10-m elevation. Results show that annual sediment export is typically underpredicted by an order of magnitude in the models. Moreover, soil loss predictions are spatially incongruent with field observations. Model results overestimate soil loss in the steep forested zones, where field observations show source material to be limited, and are not able to adequately capture human- and animal-disturbed material that connects hydrologically with the stream network. We suggest that the differences stem from a mismatch of processes that source sediments, including stream channel erosion and storage and shallow landslides, which are not included in all the models that are typically used for decision support. Moreover, different modeling platforms use different transport equations, which have not been validated for steep, mountainous watersheds. Changes in land use, such as new developments or cover crops, are obscured by models which consider steeply-sloped areas to be the primary source of sediment. The comparison suggests that decision support tools for Hawaii need a different approach for predicting sediment export with changing land use.

  17. Verification of ECMWF monthly forecasts for the use in hydrological predictions

    NASA Astrophysics Data System (ADS)

    Monhart, Samuel; Spirig, Christoph; Bhend, Jonas; Liniger, Mark A.; Bogner, Konrad; Schär, Christoph

    2016-04-01

    In recent years, sub-seasonal forecasts have received increasing attention. These forecasts with a time horizon of 2 to 6 weeks bridge the gap between operational weather forecasts and seasonal predictions. Different sectors (e.g. agriculture, energy, warnings systems) show high demand in seamless forecasts from days to seasons. Within the HEPS4Power project we aim at developing a hydrometeorological end-to-end ensemble prediction system for several catchments in the Swiss Alps. In order to use the monthly forecast in hydrological modeling, we first explore the performance of the meteorological forecasts separately. This framework allows also an assessment of different bias correction and downscaling techniques. Such a post-processing will be important to couple the hydrological model to the meteorological model data. We verified the ECMWF extended-range forecast against approximately 1000 observational time series of ECA&D across Europe. To do so, we made use of 20 years of hindcasts of the forecasting system that was operational from May 2014 to April 2015 (cycle 40r1), yielding an analysis period of May 1995 to June 2014. This unique data set is large enough to stratify the performance of the monthly forecasting system with season and region. Weekly temperature and precipitation of both raw hindcasts and post-processed hindcasts were analyzed. Various skill metrics (RPSS, CRPSS, ROCSS) characterizing different aspects of forecast quality were computed using climatology as a benchmark. Overall, skillful forecasts were found in some regions and seasons up to three weeks of lead time in case of temperature and up to two weeks for precipitation, respectively. Bias-corrections allowed to enhance forecast skill in the first two weeks for most of the stations. Spatial and seasonal differences in skill were found both for temperature and precipitation, with winter forecasts generally being better than those of other seasons. Geographically, forecasts tend to show higher

  18. Recent scientific advances in the use of radar in scientific hydrology

    NASA Technical Reports Server (NTRS)

    Engman, Edwin T.

    1993-01-01

    The data needs in scientific hydrology involve measurements of system states and fluxes. The microwave region is particularly well suited for measuring the system states of soil moisture and snow and the major flux into the earth as rainfall. This paper discusses the unique data needs of hydrology and presents some recent examples from AIRSAR experiments.

  19. Perface: Research advances in vadose zone hydrology throughsimulations with the TOUGH codes

    SciTech Connect

    Finsterle, Stefan; Oldenburg, Curtis M.

    2004-07-12

    Numerical simulators are playing an increasingly important role in advancing our fundamental understanding of hydrological systems. They are indispensable tools for managing groundwater resources, analyzing proposed and actual remediation activities at contaminated sites, optimizing recovery of oil, gas, and geothermal energy, evaluating subsurface structures and mining activities, designing monitoring systems, assessing the long-term impacts of chemical and nuclear waste disposal, and devising improved irrigation and drainage practices in agricultural areas, among many other applications. The complexity of subsurface hydrology in the vadose zone calls for sophisticated modeling codes capable of handling the strong nonlinearities involved, the interactions of coupled physical, chemical and biological processes, and the multiscale heterogeneities inherent in such systems. The papers in this special section of ''Vadose Zone Journal'' are illustrative of the enormous potential of such numerical simulators as applied to the vadose zone. The papers describe recent developments and applications of one particular set of codes, the TOUGH family of codes, as applied to nonisothermal flow and transport in heterogeneous porous and fractured media (http://www-esd.lbl.gov/TOUGH2). The contributions were selected from presentations given at the TOUGH Symposium 2003, which brought together developers and users of the TOUGH codes at the Lawrence Berkeley National Laboratory (LBNL) in Berkeley, California, for three days of information exchange in May 2003 (http://www-esd.lbl.gov/TOUGHsymposium). The papers presented at the symposium covered a wide range of topics, including geothermal reservoir engineering, fracture flow and vadose zone hydrology, nuclear waste disposal, mining engineering, reactive chemical transport, environmental remediation, and gas transport. This Special Section of ''Vadose Zone Journal'' contains revised and expanded versions of selected papers from the

  20. Advances in tilt rotor noise prediction

    NASA Technical Reports Server (NTRS)

    George, A. R.; Coffen, C. D.; Ringler, T. D.

    1992-01-01

    The two most serious tilt rotor external noise problems, hover noise and blade-vortex interaction noise, are studied. The results of flow visualization and inflow velocity measurements document a complex, recirculating highly unsteady and turbulent flow due to the rotor-wing-body interactions characteristic of tilt rotors. The wing under the rotor is found to obstruct the inflow, causing a deficit in the inflow velocities over the inboard region of the rotor. Discrete frequency harmonic thickness and loading noise mechanisms in hover are examined by first modeling tilt rotor hover aerodynamics and then applying various noise prediction methods using the WOPWOP code. The analysis indicates that the partial ground plane created by the wing below the rotor results in a primary sound source for hover.

  1. Hydrology of the North Cascades region, Washington: 2. A proposed hydrometeorological streamflow prediction method

    USGS Publications Warehouse

    Tangborn, Wendell V.; Rasmussen, Lowell A.

    1976-01-01

    . This contribution decreases to nearly zero during the summer and then rises slightly for late summer predictions. The reason for the smaller than expected effect of summer precipitation is thought to be due to the compensating effect of increased evaporative losses and increased infiltration when precipitation is greater than normal during the summer months. The error caused by the beginning winter month (assumed to be October in this study) not coinciding with the time of minimum storage was examined; it appears that October may be the best average beginning winter month for most drainages but that a more detailed study is needed. The optimum beginning of the winter season appears to vary from August to October when individual years are examined. These results demonstrate that standard precipitation and runoff measurements in the North Cascades region are adequate for constructing a predictive hydrologic model. This model can be used to make streamflow predictions that compare favorably with current multiple regression methods based on mountain snow surveys. This method has the added advantages of predicting the space and time distributions of storage and summer runoff.

  2. A Primer In Advanced Fatigue Life Prediction Methods

    NASA Technical Reports Server (NTRS)

    Halford, Gary R.

    2000-01-01

    Metal fatigue has plagued structural components for centuries, and it remains a critical durability issue in today's aerospace hardware. This is true despite vastly improved and advanced materials, increased mechanistic understanding, and development of accurate structural analysis and advanced fatigue life prediction tools. Each advance is quickly taken advantage of to produce safer, more reliable more cost effective, and better performing products. In other words, as the envelop is expanded, components are then designed to operate just as close to the newly expanded envelop as they were to the initial one. The problem is perennial. The economic importance of addressing structural durability issues early in the design process is emphasized. Tradeoffs with performance, cost, and legislated restrictions are pointed out. Several aspects of structural durability of advanced systems, advanced materials and advanced fatigue life prediction methods are presented. Specific items include the basic elements of durability analysis, conventional designs, barriers to be overcome for advanced systems, high-temperature life prediction for both creep-fatigue and thermomechanical fatigue, mean stress effects, multiaxial stress-strain states, and cumulative fatigue damage accumulation assessment.

  3. Hydrological Aspects of Weather Prediction and Flood Warnings: Report of the Ninth Prospectus Development Team of the U.S. Weather Research Program

    USGS Publications Warehouse

    Droegemeier, K.K.; Smith, J.D.; Businger, S.; Doswell, C.; Doyle, J.; Duffy, C.; Foufoula-Georgiou, E.; Graziano, T.; James, L.D.; Krajewski, V.; LeMone, M.; Lettenmaier, D.; Mass, C.; Pielke, R.; Ray, P.; Rutledge, S.; Schaake, J.; Zipser, E.

    2000-01-01

    Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists - in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems - to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research

  4. Hydrological Aspects of Weather Prediction and Flood Warnings: Report of the Ninth Prospectus Development Team of the U.S. Weather Research Program.

    NASA Astrophysics Data System (ADS)

    Droegemeier, K. K.; Smith, J. D.; Businger, S.; Doswell, C., III; Doyle, J.; Duffy, C.; Foufoula-Georgiou, E.; Graziano, T.; James, L. D.; Krajewski, V.; Lemone, M.; Lettenmaier, D.; Mass, C.; Pielke, R., Sr.; Ray, P.; Rutledge, S.; Schaake, J.; Zipser, E.

    2000-11-01

    Among the many natural disasters that disrupt human and industrial activity in the United States each year, including tornadoes, hurricanes, extreme temperatures, and lightning, floods are among the most devastating and rank second in the loss of life. Indeed, the societal impact of floods has increased during the past few years and shows no sign of abating. Although the scientific questions associated with flooding and its accurate prediction are many and complex, an unprecedented opportunity now exists-in light of new observational and computing systems and infrastructures, a much improved understanding of small-scale meteorological and hydrological processes, and the availability of sophisticated numerical models and data assimilation systems-to attack the flood forecasting problem in a comprehensive manner that will yield significant new scientific insights and corresponding practical benefits. The authors present herein a set of recommendations for advancing our understanding of floods via the creation of natural laboratories situated in a variety of local meteorological and hydrological settings. Emphasis is given to floods caused by convection and cold season events, fronts and extratropical cyclones, orographic forcing, and hurricanes and tropical cyclones following landfall. Although the particular research strategies applied within each laboratory setting will necessarily vary, all will share the following principal elements: (a) exploitation of those couplings important to flooding that exist between meteorological and hydrological processes and models; (b) innovative use of operational radars, research radars, satellites, and rain gauges to provide detailed spatial characterizations of precipitation fields and rates, along with the use of this information in hydrological models and for improving and validating microphysical algorithms in meteorological models; (c) comparisons of quantitative precipitation estimation algorithms from both research

  5. Predictive control of water distribution in the Dutch National Hydrological Instrument (NHI)

    NASA Astrophysics Data System (ADS)

    Talsma, J.; Patzke, S.; Becker, B. P. J.; Schwanenberg, D.; Jansen, M.

    2012-04-01

    In the Netherlands, water is extracted from rivers, lakes and canals for drinking water supply as well as industrial, agricultural and environmental water demands. These water extractions must be managed in such a way that constraints such as water quality, safety and minimum water levels for navigation are maintained as long as possible. The National Hydrological Instrument (NHI) has been developed for modeling the water distribution in the Netherlands and supporting the development of water management strategies. It is also integrated into the national Dutch forecasting system for predicting dry periods and their impacts on water supply, agriculture, aquatic ecosystems and navigation. With such setup, the NHI will be a fundamental tool for drought forecast in the Netherlands. The NHI consists of a groundwater model (MODFLOW), an unsaturated zone model (Metaswap) and surface water models which interact with each other in every time step via an OpenMI interface. The surface water models consist of a hydrological model MOZART for representing the regional catchments and computing a desired water demand, a SOBEK open channel flow model for flow routing in the network of the larger rivers, lakes and canals, and a real-time control component (RTC-Tools). The latter links the water demand generated by MOZART to the availably supply in the network for generating optimum water allocation policies within the prediction horizon of 10 days of the operational forecasting system. The approach relies on predictive control consisting of a simplified internal model of the network within a system-wide optimization algorithm. In a period of water shortages, the user can refine the water allocation by defining specific objectives and related priorities. Finally, the optimum water extractions from RTC-Tools are passed back to MOZART and SOBEK as allocated values. The RTC-Tools integration into the NHI is an ongoing activity. We present the new functionality based on a pilot system

  6. GIS-based prediction of stream chemistry using landscape composition, wet areas, and hydrological flow pathways

    NASA Astrophysics Data System (ADS)

    Tiwari, Tejshree; Lidman, Fredrik; Laudon, Hjalmar; Lidberg, William; Ågren, Anneli M.

    2017-01-01

    Landscape morphology exerts strong, scale-dependent controls on stream hydrology and biogeochemistry in heterogeneous catchments. We applied three descriptors of landscape structure at different spatial scales based on new geographic information system tools to predict variability in stream concentrations for a wide range of solutes (Al, Ba, Be, Ca, Fe, K, Mg, Na, S, Si, Sr, Sc, Co, Cr, Ni, Cu, As, Se, Rb, Y, Cd, Sb, Cs, La, Pb, Th, U, DOC, and Cl) using a linear regression analysis. Results showed that less reactive elements, which can be expected to behave more conservatively in the landscape (e.g., Na, K, Ca, Mg, Cl, and Si), generally were best predicted from the broader-scale description of landscape composition (areal coverage of peat, tills, and sorted sediments). These results highlight the importance of mineral weathering as a source of some elements, which was best captured by landscape-scale descriptors of catchment structure. By contrast, more nonconservative elements (e.g., DOC, Al, Cd, Cs, Co, Th, Y, and U), were best predicted by defining wet areas and/or flow path lengths of different patches in the landscape. This change in the predictive models reflect the importance of peat deposits, such as organic-rich riparian zones and mire ecosystems, which are favorable environments for biogeochemical reactions of more nonconservative elements. As such, using this understanding of landscape influences on stream chemistry can provide improved mitigation strategies and management plans that specifically target source areas, so as to minimize mobilization of undesired elements into streams.

  7. Hydrologic Connections and Landscape Metrics to Advance Ecosystem Goods and Services in Tampa Bay Watershed

    EPA Science Inventory

    Understanding the hydrological characteristics of coastal wetlands across land use gradients ranging from natural to urban to agricultural is important for significantly enhancing our ability to utilize environmental data in interpreting ecosystem condition and processes. Here we...

  8. Predicting debris flow occurrence in Eastern Italian Alps based on hydrological and geomorphological modelling

    NASA Astrophysics Data System (ADS)

    Nikolopoulos, Efthymios I.; Borga, Marco; Destro, Elisa; Marchi, Lorenzo

    2015-04-01

    Most of the work so far on the prediction of debris flow occurrence is focused on the identification of critical rainfall conditions. However, findings in the literature have shown that critical rainfall thresholds cannot always accurately identify debris flow occurrence, leading to false detections (positive or negative). One of the main reasons for this limitation is attributed to the fact that critical rainfall thresholds do not account for the characteristics of underlying land surface (e.g. geomorphology, moisture conditions, sediment availability, etc), which are strongly related to debris flow triggering. In addition, in areas where debris flows occur predominantly as a result of channel bed failure (as in many Alpine basins), the triggering factor is runoff, which suggests that identification of critical runoff conditions for debris flow prediction is more pertinent than critical rainfall. The primary objective of this study is to investigate the potential of a triggering index (TI), which combines variables related to runoff generation and channel morphology, for predicting debris flows occurrence. TI is based on a threshold criterion developed on past works (Tognacca et al., 2000; Berti and Simoni, 2005; Gregoretti and Dalla Fontana, 2008) and combines information on unit width peak flow, local channel slope and mean grain size. Estimation of peak discharge is based on the application of a distributed hydrologic model, while local channel slope is derived from a high-resolution (5m) DEM. Scaling functions of peak flows and channel width with drainage area are adopted since it is not possible to measure channel width or simulate peak flow at all channel nodes. TI values are mapped over the channel network thus allowing spatially distributed prediction but instead of identifying debris flow occurrence on single points, we identify their occurrence with reference to the tributary catchment involved. Evaluation of TI is carried out for five different basins

  9. Implications of hydrologic predictability for the development of a global drought information system

    NASA Astrophysics Data System (ADS)

    Lettenmaier, D. P.

    2014-12-01

    Drought information systems consist of two key elements: nowcasts; essentially maps that identify the locations of areas currently in drought and the severity thereof as related to an historical record; and drought forecasts, which predict the best understanding of the evolution of drought, along with the uncertainty of those predictions. Because drought nowcasts are only meaningful if current conditions are related to an historical period, stable quality controlled historical space-time records of key drought variables are essential. Generally, these include surface meteorological conditions, such as surface air temperature and precipitation, and other land surface variables, such as downward shortwave and longwave radiation, which typically are derived from more commonly measured variables, such as the daily temperature and temperature range. I discuss our experience in constructing such records, both across the continental U.S. where we have the luxury of relatively lengthy and high quality meteorological and climate records, and globally, where attaining statistical stability of constructed historical records is more challenging. In the case of agricultural (soil moisture) and hydrological (runoff) droughts, the key drought variables usually must be derived from land surface models (LSMs) forced by precipitation, surface air temperature, humidity, surface wind, and downward shortwave and longwave radiation. Clearly, the statistical stability of derived soil moisture and runoff depend on stability of the LSM forcings, and I discuss some experiences and issues in our development of a prototype global drought information system GDIS. With respect to drought forecasts, skill derives either from a) persistence in the land surface initial states, primarily soil moisture and snow; and b) skill in prediction of the LSM forcings (most importantly, precipitation). I review recent work that shows the relative influence of these two sources of drought forecast skill, as

  10. Comparison of three methods for the optimal allocation of hydrological model participation in an Ensemble Prediction System

    NASA Astrophysics Data System (ADS)

    Brochero, D.; Anctil, F.; Gagné, C.

    2012-04-01

    Today, the availability of the Meteorological Ensemble Prediction Systems (MEPS) and its subsequent coupling with multiple hydrological models offer the possibility of building Hydrological Ensemble Prediction Systems (HEPS) consisting of a large number of members. However, this task is complex both in terms of the coupling of information and of the computational time, which may create an operational barrier. The evaluation of the prominence of each hydrological members can be seen as a non-parametric post-processing stage that seeks finding the optimal participation of the hydrological models (in a fashion similar to the Bayesian model averaging technique), maintaining or improving the quality of a probabilistic forecasts based on only x members drawn from a super ensemble of d members, thus allowing the reduction of the task required to issue the probabilistic forecast. The main objective of the current work consists in assessing the degree of simplification (reduction of the number of hydrological members) that can be achieved with a HEPS configured using 16 lumped hydrological models driven by the 50 weather ensemble forecasts from the European Centre for Medium-range Weather Forecasts (ECMWF), i.e. an 800-member HEPS. In a previous work (Brochero et al., 2011a, b), we demonstrated that the proportion of members allocated to each hydrological model is a sufficient criterion to reduce the number of hydrological members while improving the balance of the scores, taking into account interchangeability of the ECMWF MEPS. Here, we compare the proportion of members allocated to each hydrological model derived from three non-parametric techniques: correlation analysis of hydrological members, Backward Greedy Selection (BGS) and Nondominated Sorting Genetic Algorithm (NSGA II). The last two techniques allude to techniques developed in machine learning, in a multicriteria framework exploiting the relationship between bias, reliability, and the number of members of the

  11. Advanced propeller noise prediction in the time domain

    NASA Technical Reports Server (NTRS)

    Farassat, F.; Dunn, M. H.; Spence, P. L.

    1992-01-01

    The time domain code ASSPIN gives acousticians a powerful technique of advanced propeller noise prediction. Except for nonlinear effects, the code uses exact solutions of the Ffowcs Williams-Hawkings equation with exact blade geometry and kinematics. By including nonaxial inflow, periodic loading noise, and adaptive time steps to accelerate computer execution, the development of this code becomes complete.

  12. Stream network geomorphology mediates predicted vulnerability of anadromous fish habitat to hydrologic change in southeast Alaska.

    PubMed

    Sloat, Matthew R; Reeves, Gordon H; Christiansen, Kelly R

    2017-02-01

    In rivers supporting Pacific salmon in southeast Alaska, USA, regional trends toward a warmer, wetter climate are predicted to increase mid- and late-21st-century mean annual flood size by 17% and 28%, respectively. Increased flood size could alter stream habitats used by Pacific salmon for reproduction, with negative consequences for the substantial economic, cultural, and ecosystem services these fish provide. We combined field measurements and model simulations to estimate the potential influence of future flood disturbance on geomorphic processes controlling the quality and extent of coho, chum, and pink salmon spawning habitat in over 800 southeast Alaska watersheds. Spawning habitat responses varied widely across watersheds and among salmon species. Little variation among watersheds in potential spawning habitat change was explained by predicted increases in mean annual flood size. Watershed response diversity was mediated primarily by topographic controls on stream channel confinement, reach-scale geomorphic associations with spawning habitat preferences, and complexity in the pace and mode of geomorphic channel responses to altered flood size. Potential spawning habitat loss was highest for coho salmon, which spawn over a wide range of geomorphic settings, including steeper, confined stream reaches that are more susceptible to streambed scour during high flows. We estimated that 9-10% and 13-16% of the spawning habitat for coho salmon could be lost by the 2040s and 2080s, respectively, with losses occurring primarily in confined, higher-gradient streams that provide only moderate-quality habitat. Estimated effects were lower for pink and chum salmon, which primarily spawn in unconfined floodplain streams. Our results illustrate the importance of accounting for valley and reach-scale geomorphic features in watershed assessments of climate vulnerability, especially in topographically complex regions. Failure to consider the geomorphic context of stream

  13. Predictive Biomarkers to Chemoradiation in Locally Advanced Rectal Cancer

    PubMed Central

    Conde-Muíño, Raquel; Cuadros, Marta; Zambudio, Natalia; Segura-Jiménez, Inmaculada; Cano, Carlos; Palma, Pablo

    2015-01-01

    There has been a high local recurrence rate in rectal cancer. Besides improvements in surgical techniques, both neoadjuvant short-course radiotherapy and long-course chemoradiation improve oncological results. Approximately 40–60% of rectal cancer patients treated with neoadjuvant chemoradiation achieve some degree of pathologic response. However, there is no effective method of predicting which patients will respond to neoadjuvant treatment. Recent studies have evaluated the potential of genetic biomarkers to predict outcome in locally advanced rectal adenocarcinoma treated with neoadjuvant chemoradiation. The articles produced by the PubMed search were reviewed for those specifically addressing a genetic profile's ability to predict response to neoadjuvant treatment in rectal cancer. Although tissue gene microarray profiling has led to promising data in cancer, to date, none of the identified signatures or molecular markers in locally advanced rectal cancer has been successfully validated as a diagnostic or prognostic tool applicable to routine clinical practice. PMID:26504848

  14. Predictive Biomarkers to Chemoradiation in Locally Advanced Rectal Cancer.

    PubMed

    Conde-Muíño, Raquel; Cuadros, Marta; Zambudio, Natalia; Segura-Jiménez, Inmaculada; Cano, Carlos; Palma, Pablo

    2015-01-01

    There has been a high local recurrence rate in rectal cancer. Besides improvements in surgical techniques, both neoadjuvant short-course radiotherapy and long-course chemoradiation improve oncological results. Approximately 40-60% of rectal cancer patients treated with neoadjuvant chemoradiation achieve some degree of pathologic response. However, there is no effective method of predicting which patients will respond to neoadjuvant treatment. Recent studies have evaluated the potential of genetic biomarkers to predict outcome in locally advanced rectal adenocarcinoma treated with neoadjuvant chemoradiation. The articles produced by the PubMed search were reviewed for those specifically addressing a genetic profile's ability to predict response to neoadjuvant treatment in rectal cancer. Although tissue gene microarray profiling has led to promising data in cancer, to date, none of the identified signatures or molecular markers in locally advanced rectal cancer has been successfully validated as a diagnostic or prognostic tool applicable to routine clinical practice.

  15. Prediction of future hydrological regimes in poorly gauged high altitude basins: the case study of the upper Indus, Pakistan

    NASA Astrophysics Data System (ADS)

    Bocchiola, D.; Diolaiuti, G.; Soncini, A.; Mihalcea, C.; D'Agata, C.; Mayer, C.; Lambrecht, A.; Rosso, R.; Smiraglia, C.

    2011-04-01

    In the mountain regions of the Hindu Kush, Karakoram and Himalaya (HKH) the "third polar ice cap" of our planet, glaciers play the role of "water towers" by providing significant amount of melt water, especially in the dry season, essential for agriculture, drinking purposes, and hydropower production. Recently, most glaciers in the HKH have been retreating and losing mass, mainly due to significant regional warming, thus calling for assessment of future water resources availability for populations down slope. However, hydrology of these high altitude catchments is poorly studied and little understood. Most such catchments are poorly gauged, thus posing major issues in flow prediction therein, and representing in facts typical grounds of application of PUB concepts, where simple and portable hydrological modeling based upon scarce data amount is necessary for water budget estimation, and prediction under climate change conditions. In this preliminarily study, future (2060) hydrological flows in a particular watershed (Shigar river at Shigar, ca. 7000 km2), nested within the upper Indus basin and fed by seasonal melt from major glaciers, are investigated. The study is carried out under the umbrella of the SHARE-Paprika project, aiming at evaluating the impact of climate change upon hydrology of the upper Indus river. We set up a minimal hydrological model, tuned against a short series of observed ground climatic data from a number of stations in the area, in situ measured ice ablation data, and remotely sensed snow cover data. The future, locally adjusted, precipitation and temperature fields for the reference decade 2050-2059 from CCSM3 model, available within the IPCC's panel, are then fed to the hydrological model. We adopt four different glaciers' cover scenarios, to test sensitivity to decreased glacierized areas. The projected flow duration curves, and some selected flow descriptors are evaluated. The uncertainty of the results is then addressed, and use of

  16. Prediction of future hydrological regimes in poorly gauged high altitude basins: the case study of the upper Indus, Pakistan

    NASA Astrophysics Data System (ADS)

    Bocchiola, D.; Diolaiuti, G.; Soncini, A.; Mihalcea, C.; D'Agata, C.; Mayer, C.; Lambrecht, A.; Rosso, R.; Smiraglia, C.

    2011-07-01

    In the mountain regions of the Hindu Kush, Karakoram and Himalaya (HKH) the "third polar ice cap" of our planet, glaciers play the role of "water towers" by providing significant amount of melt water, especially in the dry season, essential for agriculture, drinking purposes, and hydropower production. Recently, most glaciers in the HKH have been retreating and losing mass, mainly due to significant regional warming, thus calling for assessment of future water resources availability for populations down slope. However, hydrology of these high altitude catchments is poorly studied and little understood. Most such catchments are poorly gauged, thus posing major issues in flow prediction therein, and representing in fact typical grounds of application of PUB concepts, where simple and portable hydrological modeling based upon scarce data amount is necessary for water budget estimation, and prediction under climate change conditions. In this preliminarily study, future (2060) hydrological flows in a particular watershed (Shigar river at Shigar, ca. 7000 km2), nested within the upper Indus basin and fed by seasonal melt from major glaciers, are investigated. The study is carried out under the umbrella of the SHARE-Paprika project, aiming at evaluating the impact of climate change upon hydrology of the upper Indus river. We set up a minimal hydrological model, tuned against a short series of observed ground climatic data from a number of stations in the area, in situ measured ice ablation data, and remotely sensed snow cover data. The future, locally adjusted, precipitation and temperature fields for the reference decade 2050-2059 from CCSM3 model, available within the IPCC's panel, are then fed to the hydrological model. We adopt four different glaciers' cover scenarios, to test sensitivity to decreased glacierized areas. The projected flow duration curves, and some selected flow descriptors are evaluated. The uncertainty of the results is then addressed, and use of the

  17. Integrating understanding of hydrology, geomorphology and ecology to better predict periphyton abundance in New Zealand rivers

    NASA Astrophysics Data System (ADS)

    Hoyle, Jo; Kilroy, Cathy; Hicks, Murray

    2015-04-01

    Periphyton (the algae dominated community that grows on the bed of rivers) provide a rich food source for the upper trophic levels of stream ecosystems and can also provide an important ecological service by removing dissolved nutrients and contaminants from the flow. However, in excess, periphyton can have negative effects on habitat quality, water chemistry and biodiversity, and can reduce recreation and aesthetic values. The abundance of periphyton in rivers is influenced by a number of factors, but the two key factors that can be directly influenced by human activities are flow regime and nutrient concentrations. River managers in New Zealand are required to set objectives for periphyton abundance that meet or exceed national bottom lines, and they then need to set limits on freshwater quality and quantity in their region to ensure these objectives are met. Consequently, the ability to predict periphyton abundance under different conditions is crucial for management of rivers to protect ecological and other values. Establishing quantitative relationships between periphyton abundance, hydrologic regimes and nutrient concentrations has proven to be difficult but remains an urgent priority in New Zealand. A common index for predicting periphyton abundance has been the frequency of floods greater than 3 times the median flow (FRE3), and this has been successful on a regional average but can be quite unreliable on a site-specific basis. This stems largely from our limited ability to transform flow data into ecologically meaningful physical processes that directly affect periphyton removal (e.g., drag, abrasion, bed movement). The research we will present examines whether geomorphic variables, such as frequency of bed movement, are useful co-predictors in periphyton abundance-flow-nutrient relationships. We collected data on channel topography and bed material size for 20 reaches in the Manawatu-Wanganui Region which have at least 5 years of flow, nutrient

  18. Sustainable co-evolution of society, ecology and hydrology: forward-looking modelling and prediction of the ecosystem and hydrology of the Lake of Monate - Italy

    NASA Astrophysics Data System (ADS)

    Montanari, Alberto; Attilio, Castellarin; Cervi, Federico

    2016-04-01

    The catchment of the Lake of Monate, in Northern Italy, is a unique example of sustainable and long-term co-evolution of society, exploitation of environmental resources, ecology and hydrology. The catchment is intensively managed since Roman times for the extraction of limestone and the whole basin area was intensively urbanized in recent times, so that the lake is now placed within a profoundly impacted environment. Notwithstanding the above relevant anthropogenic activity, the ecosystem of the lake is still very close to pristine conditions, therefore offering unique research opportunities. Sustainable co-evolution was ensured by the absence of significant surface inflows to the lake, which is mainly alimented by groundwater flows, and a wise and forward looking land use planning and management since ancient times. Today, the increasing pace of limestone extraction, and consequent land recovery, as well as urbanization, poses the need for an improved understanding of sustainability, to support long term prediction and planning. The target is to ensure that the ecosystemic value of the lake is preserved for the benefit of future generations and societal development. The above need calls for improved modelling tools where the co-evolution of society, ecology and hydrology is modelled by focusing on the time scales of the related interactions and the planning horizon. A theoretical framework will be presented to identify the above relevant scales and to properly incorporate the feedbacks between human activity and natural systems.

  19. Remote sensing inputs to landscape models which predict future spatial land use patterns for hydrologic models

    NASA Technical Reports Server (NTRS)

    Miller, L. D.; Tom, C.; Nualchawee, K.

    1977-01-01

    A tropical forest area of Northern Thailand provided a test case of the application of the approach in more natural surroundings. Remote sensing imagery subjected to proper computer analysis has been shown to be a very useful means of collecting spatial data for the science of hydrology. Remote sensing products provide direct input to hydrologic models and practical data bases for planning large and small-scale hydrologic developments. Combining the available remote sensing imagery together with available map information in the landscape model provides a basis for substantial improvements in these applications.

  20. Hydrology and Human Health: Predicting Cholera Outbreaks using Remote Sensing Data

    NASA Astrophysics Data System (ADS)

    Jutla, A. S.; Akanda, A. S.; Islam, S.

    2010-12-01

    Cholera bacteria survive and thrive in two distinctively different environments: the micro- and the macro-environmental processes that vary over a range of spatial and temporal scales. While micro-environmental conditions are necessary for maintaining epidemic conditions, macro-environmental conditions set the stage for initial outbreak and endemicity of the disease. As macro-environmental processes provide natural ecological niche for V. cholerae and there is powerful evidence of new biotypes emerging, it is unlikely that cholera will be fully eradicated, a condition which necessitates exploration of alternate means to develop prediction mechanism for cholera outbreaks. Satellite remote sensing data provides reliable estimates of plankton abundance through chlorophyll content which then can be used to understand cholera - chlorophyll relationships. However, the functional nature of association of cholera incidence with chlorophyll and its predictive capabilities are not well understood. Here we show that cholera outbreaks in Bengal Delta can be predicted two to three months in advance with an overall prediction accuracy of greater than 80% using combination of satellite derived chlorophyll and air temperature. Such high prediction accuracy is achievable because the two seasonal peaks of cholera in Bengal Delta are controlled by two distinctive macro-environmental processes. We have found that interannual variability of pre- monsoonal cholera outbreaks is intricately linked with coastal plankton through a cascade of hydro-coastal processes. Post- monsoonal cholera outbreaks, on the other hand, are related with wide spreading flooding and subsequent breakdown of the sanitary conditions. Our results demonstrate that satellite data, with a careful choice of space and time scales, can be very effective to develop a cholera prediction model for the Bengal delta with several months lead time. We anticipate that our modeling framework will provide essential lead time for

  1. Predictable elastomeric impressions in advanced fixed prosthodontics: a comprehensive review.

    PubMed

    Lee, E A

    1999-05-01

    Despite advances in dental material technology, the predictable procurement of accurate impressions for the fabrication of complex fixed prosthodontic restorations remains an elusive objective. The technical challenges and potential negative sequelae are exponentially magnified in advanced applications that involve multiple abutments and preparatory phases. A protocol for consistently achieving accurate impressions with the use of polyether impression materials and automatic instrumentation is presented and illustrated with multiple clinical examples. The technique is capable of yielding reliable results in extensive cases and requires minimal support from auxiliary personnel.

  2. Predictable elastomeric impressions in advanced fixed prosthodontics: a comprehensive review.

    PubMed

    Lee, Ernesto A

    2007-10-01

    Despite advances in dental material technology, the predictable procurement of accurate impressions for the fabrication of complex fixed prosthodontic restorations remains an elusive objective. The technical challenges and potential negative sequelae are exponentially magnified in advanced applications that involve multiple abutments and preparatory phases. A protocol for consistently achieving accurate impressions with the use of various impression materials and automatic instrumentation is presented and illustrated with multiple clinical examples. The technique is capable of yielding reliable results in extensive cases and requires minimal support from auxiliary personnel.

  3. PREDICTIVE UNCERTAINTY IN HYDROLOGIC AND WATER QUALITY MODELING: APPROACHES, APPLICATION TO ENVIRONMENTAL MANAGEMENT, AND FUTURE CHALLENGES

    EPA Science Inventory

    Extant process-based hydrologic and water quality models are indispensable to water resources planning and environmental management. However, models are only approximations of real systems and often calibrated with incomplete and uncertain data. Reliable estimates, or perhaps f...

  4. Development of Advanced Eco-hydrologic and Biogeochemical Coupling Model to Re-evaluate Greenhouse Gas Budget of Biosphere

    NASA Astrophysics Data System (ADS)

    Nakayama, T.; Maksyutov, S. S.

    2015-12-01

    Inland waters including rivers, lakes, and groundwater are suggested to act as a transport pathway for water and dissolved substances, and play some role in continental biogeochemical cycling (Cole et al., 2007; Battin et al., 2009). The authors have developed process-based National Integrated Catchment-based Eco-hydrology (NICE) model (2014, 2015, etc.), which includes feedback between hydrologic-geomorphic-ecological processes. In this study, NICE was further developed to couple with various biogeochemical cycle models in biosphere, those for water quality in aquatic ecosystems, and those for carbon weathering. The NICE-biogeochemical coupling model incorporates connectivity of the biogeochemical cycle accompanied by hydrologic cycle between surface water and groundwater, hillslopes and river networks, and other intermediate regions. The model also includes reaction between inorganic and organic carbons, and its relation to nitrogen and phosphorus in terrestrial-aquatic continuum. The coupled model showed to improve the accuracy of inundation stress mechanism such as photosynthesis and primary production, which attributes to improvement of CH4 flux in wetland sensitive to fluctuations of shallow groundwater. The model also simulated CO2 evasion from inland water in global scale, and was relatively in good agreement in empirical relation (Aufdenkampe et al., 2011) which has relatively an uncertainty in the calculated flux because of pCO2 data missing in some region and effect of small tributaries, etc. Further, the model evaluated how the expected CO2 evasion might change as inland waters become polluted with nutrients and eutrophication increases from agriculture and urban areas (Pacheco et al., 2013). This advanced eco-hydrologic and biogeochemical coupling model would play important role to re-evaluate greenhouse gas budget of the biosphere, and to bridge gap between top-down and bottom-up approaches (Battin et al., 2009; Regnier et al., 2013).

  5. Multi-objective optimization of empirical hydrological model for streamflow prediction

    NASA Astrophysics Data System (ADS)

    Guo, Jun; Zhou, Jianzhong; Lu, Jiazheng; Zou, Qiang; Zhang, Huajie; Bi, Sheng

    2014-04-01

    Traditional calibration of hydrological models is performed with a single objective function. Practical experience with the calibration of hydrologic models reveals that single objective functions are often inadequate to properly measure all of the characteristics of the hydrologic system. To circumvent this problem, in recent years, a lot of studies have looked into the automatic calibration of hydrological models with multi-objective functions. In this paper, the multi-objective evolution algorithm MODE-ACM is introduced to solve the multi-objective optimization of hydrologic models. Moreover, to improve the performance of the MODE-ACM, an Enhanced Pareto Multi-Objective Differential Evolution algorithm named EPMODE is proposed in this research. The efficacy of the MODE-ACM and EPMODE are compared with two state-of-the-art algorithms NSGA-II and SPEA2 on two case studies. Five test problems are used as the first case study to generate the true Pareto front. Then this approach is tested on a typical empirical hydrological model for monthly streamflow forecasting. The results of these case studies show that the EPMODE, as well as MODE-ACM, is effective in solving multi-objective problems and has great potential as an efficient and reliable algorithm for water resources applications.

  6. Life Prediction of Fretting Fatigue with Advanced Surface Treatments (Preprint)

    DTIC Science & Technology

    2006-05-01

    surfaces and not the fretting pads. The chosen coatings included DLC, Ni-B, Molybdenum, and Nitride. These 4 coatings, their application to the titanium ...Article Preprint 5a. CONTRACT NUMBER In-house 5b. GRANT NUMBER 4 . TITLE AND SUBTITLE LIFE PREDICTION OF FRETTING FATIGUE WITH ADVANCED SURFACE...TREATMENTS (PREPRINT) 5c. PROGRAM ELEMENT NUMBER N/A 5d. PROJECT NUMBER M02R 5e. TASK NUMBER 30 6 . AUTHOR(S) Patrick J. Golden and Michael

  7. Evaluation of SCaMPR Satellite QPEs for Operational Hydrologic Prediction

    NASA Astrophysics Data System (ADS)

    LEE, H.; Zhang, Y.; Seo, D.; Kitzmiller, D. H.; Kuligowski, R. J.; Corby, R.

    2011-12-01

    National Weather Service (NWS) River Forecast Centers (RFCs) use rain gauge or radar-gauge multi-sensor quantitative precipitation estimates (QPEs) as the primary rainfall input to their operational hydrologic models. In areas with poor radar and rain gauge coverage, satellite-based QPEs are a potential alternative. In this work, we evaluated the utility of satellite-based QPEs produced via the Self-Calibrating Multivariate Precipitation Retrieval (SCaMPR) algorithm for operational hydrologic modeling for a set of basins in Texas and Louisiana for the period of 2000-7. First, we assessed the relative accuracy of two sets of SCaMPR QPEs versus gauge-only QPE, with operational multi-sensor QPEs as the reference. One set used only operational polar orbiting satellite microwave input as the predictors, the other included Tropical Rainfall Measuring Mission (TRMM) rain rates in the calibration process. We then performed hydrologic simulations using these QPEs and evaluated the simulations. Results indicated that a) SCaMPR QPEs showed better/worse skill than the gauge-only QPEs in resolving heavy precipitation at 1-h/24-h time intervals in terms of Critical Success Index (CSI); b) SCaMPR QPEs underperformed gauge-only QPEs in simulating flood events; and c) ingesting TRMM rainfall rates helped enhance the hydrologic utility of SCaMPR QPE, by mitigating the positive bias of SCaMPR QPEs, elevating the detection rates of heavy rainfall, and improving the simulation of flood discharge. Our findings suggest that the superior performance of gauge-only QPEs versus SCaMPR in hydrologic simulations is tied to its better accuracy at 24-h scale. The implication of the scale dependence in the relative performance of SCaMPR QPEs to their potential hydrologic utility is discussed.

  8. An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): assessing the added value of probabilistic forecasts

    NASA Astrophysics Data System (ADS)

    Addor, N.; Jaun, S.; Fundel, F.; Zappa, M.

    2012-04-01

    The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS) was launched operationally in 2008. This model chain relies on deterministic (COSMO-7) and probabilistic (COSMO-LEPS) atmospheric forecasts, which are used to force a semi-distributed hydrological model (PREVAH) coupled to a hydraulic model (FLORIS). The resulting hydrological forecasts are eventually communicated to the stakeholders involved in the Sihl discharge management. This fully operational setting provides a real framework with which we assessed the potential of deterministic and probabilistic discharge forecasts for flood mitigation. To study the suitability of HEPS for small-scale basins and to quantify the added value conveyed by the probability information, a 31-month reforecast was produced for the Sihl catchment (336 km2). Several metrics support the conclusion that the performance gain is of up to 2 days lead time for the catchment considered. Brier skill scores show that probabilistic hydrological forecasts outperform their deterministic counterparts for all the lead times and event intensities considered. The small size of the Sihl catchment does not prevent skillful discharge forecasts, but makes them particularly dependent on correct precipitation forecasts. Our evaluation stresses that the capacity of the model to provide confident and reliable mid-term probability forecasts for high discharges is limited. We finally highlight challenges for making decisions on the basis of hydrological predictions, and discuss the need for a tool to be used in addition to forecasts to compare the different mitigation actions possible in the Sihl catchment.

  9. Estimating observing locations for advancing beyond the winter predictability barrier of Indian Ocean dipole event predictions

    NASA Astrophysics Data System (ADS)

    Feng, Rong; Duan, Wansuo; Mu, Mu

    2017-02-01

    In this paper, we explored potential observing locations (i.e., the sensitive areas) of positive Indian Ocean dipole (IOD) events to advance beyond the winter predictability barrier (WPB) using the geophysical fluid dynamics laboratory climate model version 2p1 (GFDL CM2p1). The sensitivity analysis is conducted through perfect model predictability experiments, in which the model is assumed to be perfect and so any prediction errors are caused by initial errors. The results show that the initial errors with an east-west dipole pattern are more likely to result in a significant WPB than spatially correlated noises; the areas where the large values of the dipole pattern initial errors are located have great effects on prediction uncertainties in winter and provide useful information regarding the sensitive areas. Further, the prediction uncertainties in winter are more sensitive to the initial errors in the subsurface large value areas than to those in the surface large value areas. The results indicate that the subsurface large value areas are sensitive areas for advancing beyond the WPB of IOD predictions and if we carry out intensive observations across these areas, the prediction errors in winter may be largely reduced. This will lead to large improvements in the skill of wintertime IOD event forecasts.

  10. Developing soil erodibility prediction equations for the Rangeland Hydrology and Erosion Model (RHEM)

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Soil erodibility is a key factor for estimating soil erosion using physically based models. In this study, a new parameterization approach for estimating erodibility was developed for the Rangeland Hydrology and Erosion Model (RHEM). The approach uses empirical equations that were developed by apply...

  11. Predicting binary merger event rates for advanced LIGO/Virgo

    NASA Astrophysics Data System (ADS)

    Holz, Daniel; Belczynski, Chris; O'Shaughnessy, Richard; Bulik, Tomek; LIGO Collaboration

    2016-03-01

    We discuss estimates of the rates of mergers of binary systems composed of neutron stars and/or stellar mass black holes. We use the StarTrack population synthesis code, and make predictions for the detection rate of compact binary coalescences with the advanced LIGO/Virgo gravitational wave detectors. Because these instruments are sensitive to massive (M > 20M⊙) stellar-mass binary black holes mergers out to high redshift (z > 1), we discuss the cosmological effects which must be taken into account when calculating LIGO detection rates, including a generalization of the calculation of the ``peanut factor'' and the sensitive time-volume.

  12. Uncertainty in Predicted Neighborhood-Scale Green Stormwater Infrastructure Performance Informed by field monitoring of Hydrologic Abstractions

    NASA Astrophysics Data System (ADS)

    Smalls-Mantey, L.; Jeffers, S.; Montalto, F. A.

    2013-12-01

    Human alterations to the environment provide infrastructure for housing and transportation but have drastically changed local hydrology. Excess stormwater runoff from impervious surfaces generates erosion, overburdens sewer infrastructure, and can pollute receiving bodies. Increased attention to green stormwater management controls is based on the premise that some of these issues can be mitigated by capturing or slowing the flow of stormwater. However, our ability to predict actual green infrastructure facility performance using physical or statistical methods needs additional validation, and efforts to incorporate green infrastructure controls into hydrologic models are still in their infancy stages. We use more than three years of field monitoring data to derive facility specific probability density functions characterizing the hydrologic abstractions provided by a stormwater treatment wetland, streetside bioretention facility, and a green roof. The monitoring results are normalized by impervious area treated, and incorporated into a neighborhood-scale agent model allowing probabilistic comparisons of the stormwater capture outcomes associated with alternative urban greening scenarios. Specifically, we compare the uncertainty introduced into the model by facility performance (as represented by the variability in the abstraction), to that introduced by both precipitation variability, and spatial patterns of emergence of different types of green infrastructure. The modeling results are used to update a discussion about the potential effectiveness of urban green infrastructure implementation plans.

  13. Advances in the assessment and prediction of interpersonal violence.

    PubMed

    Mills, Jeremy F

    2005-02-01

    This article underscores the weakness of clinical judgment as a mechanism for prediction with examples from other areas in the psychological literature. Clinical judgment has as its Achilles'heel the reliance on a person to incorporate multiple pieces of information while overcoming human judgment errors--a feat insurmountable thus far. The actuarial approach to risk assessment has overcome many of the weaknesses of clinical judgment and has been shown to be a much superior method. Nonetheless, the static/historical nature of the risk factors associated with most actuarial approaches is limiting. Advances in risk prediction will be found in part in the development of dynamic actuarial instruments that will measure both static/historical and changeable risk factors. The dynamic risk factors can be reevaluated on an ongoing basis, and it is proposed that the level of change in dynamic factors necessary to represent a significant change in overall risk will be an interactive function with static risk factors.

  14. The prediction of transonic loading on advancing helicopter rotors

    NASA Technical Reports Server (NTRS)

    Strawn, R. C.; Tung, C.

    1986-01-01

    Two different schemes are presented for including the effect of rotor wakes on the finie-difference prediction of rotor loads. The first formulation includes wake effects by means of a blade-surface inflow specification. This approach is sufficiently simple to permit coupling of a full-potential finite-difference rotor code to a comprehensive integral model for the rotor wake and blade motion. The coupling involves a transfer of appropriate loads and inflow data between the two computer codes. Results are compared with experimental data for two advancing rotor cases. The second rotor-wake modeling scheme is a split potential formulation for computing unsteady blade-vortex interactions. Discrete vortex fields are introduced into a three-dimensional, conservative, full-potential rotor code. Computer predictions are compared with two experimental blade-vortex interaction cases.

  15. The prediction of transonic loading advancing helicopter rotors

    NASA Technical Reports Server (NTRS)

    Strawn, R.; Tung, C.

    1986-01-01

    Two different schemes are presented for including the effect of rotor wakes on the finite-difference prediction of rotor loads. The first formulation includes wake effects by means of a blade-surface inflow specification. This approach is sufficiently simple to permit coupling of a full-potential finite-difference rotor code to a comprehensive integral model for the rotor wake and blade motion. The coupling involves a transfer of appropriate loads and inflow data between the two computer codes. Results are compared with experimental data for two advancing rotor cases. The second rotor wake modeling scheme in this paper is a split potential formulation for computing unsteady blade-vortex interactions. Discrete vortex fields are introduced into a three-dimensional, conservative, full-potential rotor code. Computer predictions are compared with two experimental blade-vortex interaction cases.

  16. Monitoring and Predicting Land-use Changes and the Hydrology of the Urbanized Paochiao Watershed in Taiwan Using Remote Sensing Data, Urban Growth Models and a Hydrological Model.

    PubMed

    Lin, Yu-Pin; Lin, Yun-Bin; Wang, Yen-Tan; Hong, Nien-Ming

    2008-02-04

    Monitoring and simulating urban sprawl and its effects on land-use patterns andhydrological processes in urbanized watersheds are essential in land-use and waterresourceplanning and management. This study applies a novel framework to the urbangrowth model Slope, Land use, Excluded land, Urban extent, Transportation, andHillshading (SLEUTH) and land-use change with the Conversion of Land use and itsEffects (CLUE-s) model using historical SPOT images to predict urban sprawl in thePaochiao watershed in Taipei County, Taiwan. The historical and predicted land-use datawas input into Patch Analyst to obtain landscape metrics. This data was also input to theGeneralized Watershed Loading Function (GWLF) model to analyze the effects of futureurban sprawl on the land-use patterns and watershed hydrology. The landscape metrics ofthe historical SPOT images show that land-use patterns changed between 1990-2000. TheSLEUTH model accurately simulated historical land-use patterns and urban sprawl in thePaochiao watershed, and simulated future clustered land-use patterns (2001-2025). TheCLUE-s model also simulated land-use patterns for the same period and yielded historical trends in the metrics of land-use patterns. The land-use patterns predicted by the SLEUTHand CLUE-s models show the significant impact urban sprawl will have on land-usepatterns in the Paochiao watershed. The historical and predicted land-use patterns in thewatershed tended to fragment, had regular shapes and interspersion patterns, but wererelatively less isolated in 2001-2025 and less interspersed from 2005-2025 compared withland-use pattern in 1990. During the study, the variability and magnitude of hydrologicalcomponents based on the historical and predicted land-use patterns were cumulativelyaffected by urban sprawl in the watershed; specifically, surface runoff increasedsignificantly by 22.0% and baseflow decreased by 18.0% during 1990-2025. The proposedapproach is an effective means of enhancing land

  17. Combining natural and man-made DNA tracers to advance understanding of hydrologic flow pathway evolution

    NASA Astrophysics Data System (ADS)

    Dahlke, H. E.; Walter, M. T.; Lyon, S. W.; Rosqvist, G. N.

    2014-12-01

    Identifying and characterizing the sources, pathways and residence times of water and associated constituents is critical to developing improved understanding of watershed-stream connections and hydrological/ecological/biogeochemical models. To date the most robust information is obtained from integrated studies that combine natural tracers (e.g. isotopes, geochemical tracers) with controlled chemical tracer (e.g., bromide, dyes) or colloidal tracer (e.g., carboxilated microspheres, tagged clay particles, microorganisms) applications. In the presented study we explore how understanding of sources and flow pathways of water derived from natural tracer studies can be improved and expanded in space and time by simultaneously introducing man-made, synthetic DNA-based microtracers. The microtracer used were composed of polylactic acid (PLA) microspheres into which short strands of synthetic DNA and paramagnetic iron oxide nanoparticles are incorporated. Tracer experiments using both natural tracers and the DNA-based microtracers were conducted in the sub-arctic, glacierized Tarfala (21.7 km2) catchment in northern Sweden. Isotopic hydrograph separations revealed that even though storm runoff was dominated by pre-event water the event water (i.e. rainfall) contributions to streamflow increased throughout the summer season as glacial snow cover decreased. This suggests that glaciers are a major source of the rainwater fraction in streamflow. Simultaneous injections of ten unique DNA-based microtracers confirmed this hypothesis and revealed that the transit time of water traveling from the glacier surface to the stream decreased fourfold over the summer season leading to instantaneous rainwater contributions during storm events. These results highlight that integrating simultaneous tracer injections (injecting tracers at multiple places at one time) with traditional tracer methods (sampling multiple times at one place) rather than using either approach in isolation can

  18. ASRM radiation and flowfield prediction status. [Advanced Solid Rocket Motor plume radiation prediction

    NASA Technical Reports Server (NTRS)

    Reardon, J. E.; Everson, J.; Smith, S. D.; Sulyma, P. R.

    1991-01-01

    Existing and proposed methods for the prediction of plume radiation are discussed in terms of their application to the NASA Advanced Solid Rocket Motor (ASRM) and Space Shuttle Main Engine (SSME) projects. Extrapolations of the Solid Rocket Motor (SRM) are discussed with respect to preliminary predictions of the primary and secondary radiation environments. The methodology for radiation and initial plume property predictions are set forth, including a new code for scattering media and independent secondary source models based on flight data. The Monte Carlo code employs a reverse-evaluation approach which traces rays back to their point of absorption in the plume. The SRM sea-level plume model is modified to account for the increased radiation in the ASRM plume due to the ASRM's propellant chemistry. The ASRM cycle-1 environment predictions are shown to identify a potential reason for the shutdown spike identified with pre-SRM staging.

  19. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    NASA Technical Reports Server (NTRS)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This paper presents recent thermal model results of the Advanced Stirling Radioisotope Generator (ASRG). The three-dimensional (3D) ASRG thermal power model was built using the Thermal Desktop(trademark) thermal analyzer. The model was correlated with ASRG engineering unit test data and ASRG flight unit predictions from Lockheed Martin's (LM's) I-deas(trademark) TMG thermal model. The auxiliary cooling system (ACS) of the ASRG is also included in the ASRG thermal model. The ACS is designed to remove waste heat from the ASRG so that it can be used to heat spacecraft components. The performance of the ACS is reported under nominal conditions and during a Venus flyby scenario. The results for the nominal case are validated with data from Lockheed Martin. Transient thermal analysis results of ASRG for a Venus flyby with a representative trajectory are also presented. In addition, model results of an ASRG mounted on a Cassini-like spacecraft with a sunshade are presented to show a way to mitigate the high temperatures of a Venus flyby. It was predicted that the sunshade can lower the temperature of the ASRG alternator by 20 C for the representative Venus flyby trajectory. The 3D model also was modified to predict generator performance after a single Advanced Stirling Convertor failure. The geometry of the Microtherm HT insulation block on the outboard side was modified to match deformation and shrinkage observed during testing of a prototypic ASRG test fixture by LM. Test conditions and test data were used to correlate the model by adjusting the thermal conductivity of the deformed insulation to match the post-heat-dump steady state temperatures. Results for these conditions showed that the performance of the still-functioning inboard ACS was unaffected.

  20. An eco-hydrological approach to predicting regional vegetation and groundwater response to ecological water convergence in dryland riparian ecosystems

    Technology Transfer Automated Retrieval System (TEKTRAN)

    To improve the management strategy of riparian restoration, better understanding of the dynamic of eco-hydrological system and its feedback between hydrological and ecological components are needed. The fully distributed eco-hydrological model coupled with a hydrology component was developed based o...

  1. Integrating weather and climate predictions for seamless hydrologic ensemble forecasting: A case study in the Yalong River basin

    NASA Astrophysics Data System (ADS)

    Ye, Aizhong; Deng, Xiaoxue; Ma, Feng; Duan, Qingyun; Zhou, Zheng; Du, Chao

    2017-04-01

    Despite the tremendous improvement made in numerical weather and climate models over the recent years, the forecasts generated by those models still cannot be used directly for hydrological forecasting. A post-processor like the Ensemble Pre-Processor (EPP) developed by U.S. National Weather Service must be used to remove various biases and to extract useful predictive information from those forecasts. In this paper, we investigate how different designs of canonical events in the EPP can help post-process precipitation forecasts from the Global Ensemble Forecast System (GEFS) and Climate Forecast System Version 2 (CFSv2). The use of canonical events allow those products to be linked seamlessly and then the post-processed ensemble precipitation forecasts can be generated using the Schaake Shuffle procedure. We used the post-processed ensemble precipitation forecasts to drive a distributed hydrological model to obtain ensemble streamflow forecasts and evaluated those forecasts against the observed streamflow. We found that the careful design of canonical events can help extract more useful information, especially when up-to-date observed precipitation is used to setup the canonical events. We also found that streamflow forecasts using post-processed precipitation forecasts have longer lead times and higher accuracy than streamflow forecasts made by traditional Extend Streamflow Prediction (ESP) and the forecasts based on original GEFS and CFSv2 precipitation forecasts.

  2. Prediction of Coupled Thermal, Hydrological and Chemical Processes at the Proposed Yucca Mountain Nuclear Waste Repository: An Integrated Approach

    SciTech Connect

    N. Spycher; E. Sonnenthal; T. Kneafsey; P. Dobson

    2003-10-17

    An integrated modeling approach was developed to investigate long-term coupled thermal, hydrological, and chemical (THC) processes that could take place around nuclear waste emplacement tunnels (drifts). The approach involves the development of process models, followed by numerical implementation and validation against field and laboratory experiments before conducting long-term predictive simulations. An outcome of this work was the refinement and validation of an existing reactive transport numerical code for applications specific to the geologic storage of nuclear waste. The model was applied to the case of the proposed high-level nuclear waste repository at Yucca Mountain, Nevada, to evaluate the chemistry of waters potentially seeping into drifts and the effect of water-rock interaction on long-term hydrological behavior around the repository. At liquid saturations significantly larger than residual, no extreme pH or salinity values were predicted. Mineral precipitation around drifts consists mainly of silica with minor calcite, trace zeolites and clays. The effect of mineral precipitation on flow depends largely on initial fracture porosity, and results in negligible to significant diversion of percolation around the drift. Further analyses of model uncertainty are under way to improve confidence in model results.

  3. COLLABORATIVE RESEARCH: TOWARDS ADVANCED UNDERSTANDING AND PREDICTIVE CAPABILITY OF CLIMATE CHANGE IN THE ARCTIC USING A HIGH-RESOLUTION REGIONAL ARCTIC CLIMATE SYSTEM MODEL

    SciTech Connect

    Gutowski, William J.

    2013-02-07

    The motivation for this project was to advance the science of climate change and prediction in the Arctic region. Its primary goals were to (i) develop a state-of-the-art Regional Arctic Climate system Model (RACM) including high-resolution atmosphere, land, ocean, sea ice and land hydrology components and (ii) to perform extended numerical experiments using high performance computers to minimize uncertainties and fundamentally improve current predictions of climate change in the northern polar regions. These goals were realized first through evaluation studies of climate system components via one-way coupling experiments. Simulations were then used to examine the effects of advancements in climate component systems on their representation of main physics, time-mean fields and to understand variability signals at scales over many years. As such this research directly addressed some of the major science objectives of the BER Climate Change Research Division (CCRD) regarding the advancement of long-term climate prediction.

  4. Advanced karst hydrological and contaminant monitoring techniques for real-time and high resolution applications

    Technology Transfer Automated Retrieval System (TEKTRAN)

    In telogenetic and soil-mantled karst aquifers, the movement of autogenic recharge through the epikarstic zone and into the regional aquifer can be a complex process and have implications for flooding, groundwater contamination, and other difficult to capture processes. Recent advances in instrument...

  5. Predicting the Hydrologic Response of the Columbia River System to Climate Change

    NASA Astrophysics Data System (ADS)

    Chegwidden, O.; Hamman, J.; Xiao, M.; Ishottama, F.; Lee, S. Y.; Stumbaugh, M. R.; Mote, P.; Lettenmaier, D. P.; Nijssen, B.

    2014-12-01

    The Columbia River, located in the northwestern United States with headwaters in Canada (Pacific Northwest), is intensely managed for hydropower generation, irrigation, flood control, ecosystem services (particularly salmonids), navigation, and recreation. Effects of anthropogenic climate change already manifest themselves in the Pacific Northwest through reduced winter snow accumulation at lower elevations and earlier spring melt. As the climate warms, the Columbia River, whose flow regime is heavily dependent on seasonal snow melt, is likely to experience significant changes in the timing of its seasonal hydrograph and possibly in total flow volume. We report on a new study co-funded by the Bonneville Power Administration to update and enhance an existing climate change streamflow data set developed by the University of Washington Climate Impacts Group in 2009-2010. Our new study is based on the RCP4.5 and RCP8.5 climate projections from the Coupled Model Intercomparison Project Version 5 (CMIP5). In contrast to earlier studies, we are using a suite of three hydrologic models, the Variable Infiltration Capacity (VIC) model, the Unified Land Model and the Precipitation Runoff Modeling System, each implemented at 1/16 degree (~6 km) over the Pacific Northwest. In addition, we will use multiple statistical downscaling methods based on the output from a subset of 10 CMIP5 global climate models (GCMs). The use of multiple hydrologic models, downscaling methods and GCMs is motivated by the need to assess the impact of methodological choices in the modeling process on projected changes in Columbia River flows. We discuss the implementation of the three hydrologic models as well as our development of a glacier model for VIC, which is intended to better represent the effects of climate change on streamflows from the Columbia River headwaters region. Finally, we report on our application of a new auto-calibration method that uses an inverse routing scheme to develop

  6. Prediction of Corrosion of Advanced Materials and Fabricated Components

    SciTech Connect

    A. Anderko; G. Engelhardt; M.M. Lencka; M.A. Jakab; G. Tormoen; N. Sridhar

    2007-09-29

    The goal of this project is to provide materials engineers, chemical engineers and plant operators with a software tool that will enable them to predict localized corrosion of process equipment including fabricated components as well as base alloys. For design and revamp purposes, the software predicts the occurrence of localized corrosion as a function of environment chemistry and assists the user in selecting the optimum alloy for a given environment. For the operation of existing plants, the software enables the users to predict the remaining life of equipment and help in scheduling maintenance activities. This project combined fundamental understanding of mechanisms of corrosion with focused experimental results to predict the corrosion of advanced, base or fabricated, alloys in real-world environments encountered in the chemical industry. At the heart of this approach is the development of models that predict the fundamental parameters that control the occurrence of localized corrosion as a function of environmental conditions and alloy composition. The fundamental parameters that dictate the occurrence of localized corrosion are the corrosion and repassivation potentials. The program team, OLI Systems and Southwest Research Institute, has developed theoretical models for these parameters. These theoretical models have been applied to predict the occurrence of localized corrosion of base materials and heat-treated components in a variety of environments containing aggressive and non-aggressive species. As a result of this project, a comprehensive model has been established and extensively verified for predicting the occurrence of localized corrosion as a function of environment chemistry and temperature by calculating the corrosion and repassivation potentials.To support and calibrate the model, an experimental database has been developed to elucidate (1) the effects of various inhibiting species as well as aggressive species on localized corrosion of nickel

  7. An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios

    NASA Astrophysics Data System (ADS)

    Addor, N.; Jaun, S.; Fundel, F.; Zappa, M.

    2011-07-01

    The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS) was launched operationally in 2008. This model chain relies on limited-area atmospheric forecasts provided by the deterministic model COSMO-7 and the probabilistic model COSMO-LEPS. These atmospheric forecasts are used to force a semi-distributed hydrological model (PREVAH), coupled to a hydraulic model (FLORIS). The resulting hydrological forecasts are eventually communicated to the stakeholders involved in the Sihl discharge management. This fully operational setting provides a real framework with which to compare the potential of deterministic and probabilistic discharge forecasts for flood mitigation. To study the suitability of HEPS for small-scale basins and to quantify the added-value conveyed by the probability information, a reforecast was made for the period June 2007 to December 2009 for the Sihl catchment (336 km2). Several metrics support the conclusion that the performance gain can be of up to 2 days lead time for the catchment considered. Brier skill scores show that overall COSMO-LEPS-based hydrological forecasts outperforms their COSMO-7-based counterparts for all the lead times and event intensities considered. The small size of the Sihl catchment does not prevent skillful discharge forecasts, but makes them particularly dependent on correct precipitation forecasts, as shown by comparisons with a reference run driven by observed meteorological parameters. Our evaluation stresses that the capacity of the model to provide confident and reliable mid-term probability forecasts for high discharges is limited. The two most intense events of the study period are investigated utilising a novel graphical representation of probability forecasts, and are used to generate high discharge

  8. An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios

    NASA Astrophysics Data System (ADS)

    Addor, N.; Jaun, S.; Zappa, M.

    2011-01-01

    The Sihl River flows through Zurich, Switzerland's most populated city, for which it represents the largest flood threat. To anticipate extreme discharge events and provide decision support in case of flood risk, a hydrometeorological ensemble prediction system (HEPS) was launched operationally in 2008. This models chain relies on limited-area atmospheric forecasts provided by the deterministic model COSMO-7 and the probabilistic model COSMO-LEPS. These atmospheric forecasts are used to force a semi-distributed hydrological model (PREVAH), coupled to a hydraulic model (FLORIS). The resulting hydrological forecasts are eventually communicated to the stakeholders involved in the Sihl discharge management. This fully operational setting provides a real framework to compare the potential of deterministic and probabilistic discharge forecasts for flood mitigation. To study the suitability of HEPS for small-scale basins and to quantify the added-value conveyed by the probability information, a reforecast was made for the period June 2007 to December 2009 for the Sihl catchment (336 km2). Several metrics support the conclusion that the performance gain can be of up to 2 days lead time for the catchment considered. Brier skill scores show that COSMO-LEPS-based hydrological forecasts overall outperform their COSMO-7 based counterparts for all the lead times and event intensities considered. The small size of the Sihl catchment does not prevent skillful discharge forecasts, but makes them particularly dependent on correct precipitation forecasts, as shown by comparisons with a reference run driven by observed meteorological parameters. Our evaluation stresses that the capacity of the model to provide confident and reliable mid-term probability forecasts for high discharges is limited. The two most intense events of the study period are investigated utilising a novel graphical representation of probability forecasts and used to generate high discharge scenarios. They

  9. Advances in Remote Sensing for Assessing High Altitude Glacio-Hydrology - with a Focus on High Mountain Asia

    NASA Astrophysics Data System (ADS)

    Bolch, T.

    2014-12-01

    Meltwater released by glaciers can be of high importance for the overall run-off and thus affect society and development of mountainous regions and their forelands. However, glaciers are mostly located in harsh and remote environment and detailed in-situ measurements are impossible or limited to few glaciers. This lack of measurements of glacier characteristics (e.g. area, debris cover, flow) and mass budgets hampers a correct glacio-hydrologic modelling and representation of processes in advanced simulation models. Remote sensing has been proven a powerful tool in providing essential data to fill this gap. The most basic information in this respect is the location and area of the glaciers. A global and some regional inventories exist, but the uncertainties and differences among them are high, especially with respect to the upper accumulation area and debris cover. I here present a multi-method approach to map glaciers more precisely based on remote sensing data and combining image ratioing (using visible, infrared and thermal bands), micro-wave coherence images, terrain analysis, differencing of digital elevation models (DEMs) and, if available, high resolution images. DEM differencing is used to provide region-wide mass balance assessments, but volume to mass conversion and data voids introduce uncertainties. For High Mountain Asia (HMA), a crucial region in terms of water resources and glacier changes, most studies concentrate on the period after the year 2000 with the SRTM-DEM as baseline data set. However, declassified satellite data from the 1960s and 1970s also exist and allowed to extend the data record back in time for several regions in HMA. Using an example from an ice-covered area of ~5000 km² in the Aksu-Tarim catchment in Central Tien Shan the importance of remote sensing for glacio-hydrological modelling is shown. This is especially true for debris-covered and surge-type glaciers whose reaction to climate is still not fully understood. Therefore

  10. Use of the data depth function to differentiate between case of interpolation and extrapolation in hydrological model prediction

    NASA Astrophysics Data System (ADS)

    Singh, Shailesh Kumar; McMillan, Hilary; Bárdossy, András

    2013-01-01

    SummaryHydrological models are subject to significant sources of uncertainty including input data, model structure and parameter uncertainty. A key requirement for an operational flow forecasting model is therefore to give accurate estimates of model uncertainty. This estimate is often presented in terms of confidence bounds. The quality and quantity of observed rainfall and flow data available for calibration has a great influence on the identification of hydrological model parameters, and hence the model error distribution and width of the confidence bounds. The information contained in the observed time series is not uniformly distributed, and may not represent all types of behaviour or activation of flow pathways that could occur in the catchment. A model calibrated with data from a given time period could therefore perform well or poorly when evaluated over a new time period, depending on the information content and variability of the calibration data, in relation to the validation period. Our hypothesis is that we can improve the estimate of hydrological predictive uncertainty, based on our knowledge of the range of data available for calibration. If the characteristics of the validation data are similar in information content and variability to those in the calibration period, we term this an "interpolation case", and expect the model errors during calibration to be similar to those in validation. Otherwise, it is an "extrapolation case", where we may expect model errors to be greater. In this study, we developed an algorithm to differentiate cases of 'interpolation' versus 'extrapolation' in the prediction time period. The algorithm is based on the concept of 'data depth', i.e. the location of new data in relation to the convex hull of the calibration data set. Using a case study, we calculated uncertainty bounds for the predictive time period using methods with/without differentiation of interpolation and extrapolation cases. The performance of the

  11. Prediction of soil stability and erosion in semiarid regions using numerical hydrological model (MCAT) and airborne hyperspectral imagery

    NASA Astrophysics Data System (ADS)

    Brook, Anna; Wittenberg, Lea

    2015-04-01

    Long-term environmental monitoring is addressed to identify physical and biological changes and progresses taking place in the ecosystem. This basic action of landscape monitoring is an essential part of the systematic long-term surveillance, aiming to evaluate, assess and predict the spatial change and progresses. Indeed, it provides a context for wide range of diverse studies and research frameworks from regional or global scale. Spatial-temporal trends and changes at various scales (massive to less certain) require establishing consistent baseline data over time. One of the spatial cases of landscape monitoring is dedicated to soil formation and pedological progresses. It is previously acknowledged that changes in soil affect the functionality of the environment, so monitoring changes recently become important cause considerable resources in areas such as environmental management, sustainability services, and protecting the environment healthy. Given the above, it can be concluded that monitoring changes in the base for sustainable development. The hydrological response of bare soils and watersheds in semiarid regions to intense rainfall events is known to be complex due to multiply physical and structural impacts and feedbacks. As a result, the comprehensive evaluations of mathematical models including detailed consideration of uncertainties in the modeling of hydrological and environmental systems are of increasing importance. The presented method incorporates means of remote sensing data, hydrological and climate data and implementing dedicated and integrative Monte Carlo Analysis Toolbox (MCAT) model for semiarid region. Complexity of practical models to represent spatial systems requires an extensive understanding of the spatial phenomena, while providing realistic balance of sensitivity and corresponding uncertainty levels. Nowadays a large number of dedicated mathematical models applied to assess environmental hydrological process. Among the most

  12. A Hydrological Model for Predicting the Effects of Dams on the Shoreline Vegetation of Lakes and Reservoirs

    PubMed

    Hill; Keddy; Wisheu

    1998-09-01

    / The species richness of shoreline vegetation of unregulated lakes in Nova Scotia, Canada, is known to increase as a function of catchment area, a topographic variable governing water level fluctuations. Predictions based on catchment area however, fail to account for richness patterns at the margins of lakes enlarged by dams. Here, we compare the vegetation and hydrological regimes of regulated and unregulated systems. Hydrological regimes of regulated systems deviated from natural systems of similar catchment area by being either hypovariable or hypervariable for both within-year and among-year fluctuations in water level. Plant communities of dammed systems were less diverse, contained more exotic species, and were, with one exception, devoid of rare shoreline herbs. Data from "recovering," or previously dammed systems indicated that shoreline communities can be restored upon return of the appropriate hydrological regime. Using observed within-year and among-year water level fluctuation data, we propose a general model for the maintenance or restoration of diverse herbaceous wetlands on shorelines of temperate lakes or reservoirs. Managers can manipulate the within-year water level variation within prescribed limits (1-2 m), while ensuring that among-year variation (SD of summer levels) is less than 25% of within-year variation. This preliminary model is based on data from low-fertility, temperate lakes in river systems. To calibrate the model, plant community data from other regions are needed, as are long-term water-level data for unregulated lakes, data which are essential but largely lacking in many areas.KEY WORDS: Catchment area; Regulated lakes; Shoreline restoration; Rare plants; Exotic plants; Diversity

  13. Development and Testing of Improved Techniques for Modeling the Hydrologic Cycle in a Mesoscale Weather Prediction System

    DTIC Science & Technology

    1993-12-14

    Normalized difference vegetation index ( NDVI ) measurements from the NOAA Advanced Very High Resolution Radiometer (AVHRR) and radiant surface temperature...produce optimum fields of surface humidity and temperature. One facet involves using radar data to predict the correct locatban, timing and intensity... timing of convection. The model is usually statically initialized with convectional rawinsonde data, but the large distance between the rawinsonde

  14. Predicting phosphorus dynamics in complex terrains using a variable source area hydrology model

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Prediction of phosphorus (P) loss from agricultural watersheds depends on accurately representing the processes governing P loss from agricultural watersheds and the particular transport factors facilitating loss. The Soil and Water Assessment Tool (SWAT), a model commonly used to predict runoff an...

  15. New Approaches to Assessing and Predicting the Hydrologic Impacts of Urban Disturbance Using Isotopes and Transit Time Analysis

    NASA Astrophysics Data System (ADS)

    Soulsby, C.; Geris, J.; Birkel, C.; Tetzlaff, D.

    2015-12-01

    Urbanization is an abrupt hydrological disturbance that affects large parts of the world. For ameliorative management, an understanding of how flow partitioning and storage dynamics are affected is crucial, yet this remains limited. This reflects the lack of integrated monitoring and modelling frameworks for characterizing these hydrological response dynamics to incremental urban development. Here we use a coupled flow-isotope model to assess the impacts of urbanisation (~20%) on stream water age distributions in an 8 km2 catchment. A conceptual runoff model was used with flux tracking to estimate the time-varying age of stream water at the outlet and both urban and non-urban sub-catchments over a 3 year period. Combined objective functions of both flow and isotope metric constrained model structures, improved calibration and aided model evaluation. Specifically, we explored (1) the age distribution of stream water draining urban and non-urban areas, (2) the integrated effect of these different land uses at larger catchment scales, and (3) how the modelling can predict the impacts on the stream water age of future urbanization proposals. The results showed that stream water draining the most urbanized tributary was youngest with a mean transit time (MTT) of < 6 months compared with ~18 months in the non-urban tributary. For the catchment outlet, the MTT was around 9 months. Here, the response of urban areas dominated smaller and moderate events, but rural contributions dominated during the wettest periods, giving a bi-modal distribution of water ages. Predictions for planned developments in the area indicated that just a 5% increase in urban area would give dramatic reductions in MTTs that can propagate to the larger catchment scale. This novel approach offers a framework for understanding the cumulative impacts of disturbances on streams. It can also contribute to the design of more sustainable urban water design in terms of targeted restriction of rapid water

  16. A two-model hydrologic ensemble prediction of hydrograph: case study from the upper Nysa Klodzka river basin (SW Poland)

    NASA Astrophysics Data System (ADS)

    Niedzielski, Tomasz; Mizinski, Bartlomiej

    2016-04-01

    The HydroProg system has been elaborated in frame of the research project no. 2011/01/D/ST10/04171 of the National Science Centre of Poland and is steadily producing multimodel ensemble predictions of hydrograph in real time. Although there are six ensemble members available at present, the longest record of predictions and their statistics is available for two data-based models (uni- and multivariate autoregressive models). Thus, we consider 3-hour predictions of water levels, with lead times ranging from 15 to 180 minutes, computed every 15 minutes since August 2013 for the Nysa Klodzka basin (SW Poland) using the two approaches and their two-model ensemble. Since the launch of the HydroProg system there have been 12 high flow episodes, and the objective of this work is to present the performance of the two-model ensemble in the process of forecasting these events. For a sake of brevity, we limit our investigation to a single gauge located at the Nysa Klodzka river in the town of Klodzko, which is centrally located in the studied basin. We identified certain regular scenarios of how the models perform in predicting the high flows in Klodzko. At the initial phase of the high flow, well before the rising limb of hydrograph, the two-model ensemble is found to provide the most skilful prognoses of water levels. However, while forecasting the rising limb of hydrograph, either the two-model solution or the vector autoregressive model offers the best predictive performance. In addition, it is hypothesized that along with the development of the rising limb phase, the vector autoregression becomes the most skilful approach amongst the scrutinized ones. Our simple two-model exercise confirms that multimodel hydrologic ensemble predictions cannot be treated as universal solutions suitable for forecasting the entire high flow event, but their superior performance may hold only for certain phases of a high flow.

  17. Advances in Data Assimilation and Weather Prediction Using TRMM Observations

    NASA Technical Reports Server (NTRS)

    Atlas, Robert (Technical Monitor); Hou, Arthur Y.; Zhang, Sara; daSilvia, Arlindo; Li, Jui-Lin; Zhang, Minghua

    2002-01-01

    Understanding the Earth's climate and how it responds to climate perturbations requires knowledge of how atmospheric moisture, clouds, latent heating, the large-scale circulation and energy fluxes vary with changing climatic conditions. The physical process linking these climate elements is precipitation. Accurate knowledge of how precipitation varies in space and time and how it couples with other atmospheric variables is essential for understanding the global water and energy cycle. In recent years, TRMM data products have played a key role in advancing the field of data assimilation to provide better global analyses for climate research and numerical weather prediction. TRMM research has demonstrated the effectiveness of microwave-based rainfall and total precipitable water (TPW) observations in improving the quality of assimilated datasets and upgrading forecast skills. TRMM latent heating products have also stimulated experimentation with innovative techniques to use this type of information to improve global analyses. We discuss strategies of assimilating TRMM observations at NASA s Data Assimilation Office and present results on the impact assimilating TRMM data on the Goddard Earth Observing System (GEOS) analyses and forecast capabilities.

  18. Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care

    Cancer.gov

    Cancer Pharmacogenomics: Integrating Discoveries in Basic, Clinical and Population Sciences to Advance Predictive Cancer Care, a 2010 workshop sponsored by the Epidemiology and Genomics Research Program.

  19. An Efficient Scaling Technique For Predicting Fine Resolution Terrestrial Hydrologic And Carbon Dynamics

    NASA Astrophysics Data System (ADS)

    Pau, G. S. H.; Shen, C.; Riley, W. J.

    2015-12-01

    Limited computational resources typically limit the spatial resolution of watershed-scale hydrologic-biogeochemical models, thus necessitating the upscaling of topographic, biotic, and abiotic parameters. Upscaled models, however, may not capture nonlinear interactions between processes accurately, leading to significant biases in the solutions. In this presentation, we consider a sampling-based scaling approach that maps coarse-resolution solutions to the high-resolution solutions. The approach, called Proper Orthogonal Decomposition Mapping Method (PODMM), trains a reduced order model with coarse- and fine- solutions, here obtained using a high-resolution watershed-scale model. The model, PAWS+CLM, is a quasi-3D watershed model that has been validated against observations in many temperate watersheds; here we applied PAWS+CLM to construct coarse- (7 km) and fine- (200m) resolution simulations for the Clinton River basin in Michigan, USA. After the training stage, subsequent fine-resolution solutions were approximated based only on coarse-resolution solutions and the ROM, leading to significant computational speedup. We demonstrate that fine-resolution soil moisture, latent heat flux, and net primary production are accurately reproduced, with up to 80% bias reduction compared to solutions obtained using coarse-resolution model. In addition, the subgrid distributions of the ROM solutions closely resemble those obtained using the fine-resolution model. This method can potentially bridge the intrinsic difference in scales between different processes by allowing efficient upscaling and downscaling of spatial solutions.

  20. Improving the representation of hydrologic processes in Earth System Models

    SciTech Connect

    Clark, Martyn P.; Fan, Ying; Lawrence, David M.; Adam, Jennifer C.; Bolster, Diogo; Gochis, David J.; Hooper, Richard P.; Kumar, Mukesh; Leung, L. Ruby; Mackay, D. Scott; Maxwell, Reed M.; Shen, Chaopeng; Swenson, Sean C.; Zeng, Xubin

    2015-08-21

    Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale models, such as the land components of Earth System Models (ESMs), do not yet represent the terrestrial water cycle in a fully integrated manner or resolve the finer-scale processes that can dominate large-scale water budgets. This paper reviews the current representation of hydrologic processes in ESMs and identifies the key opportunities for improvement. This review suggests that (1) the development of ESMs has not kept pace with modeling advances in hydrology, both through neglecting key processes (e.g., groundwater) and neglecting key aspects of spatial variability and hydrologic connectivity; and (2) many modeling advances in hydrology can readily be incorporated into ESMs and substantially improve predictions of the water cycle. Accelerating modeling advances in ESMs requires comprehensive hydrologic benchmarking activities, in order to systematically evaluate competing modeling alternatives, understand model weaknesses, and prioritize model development needs. This demands stronger collaboration, both through greater engagement of hydrologists in ESM development and through more detailed evaluation of ESM processes in research watersheds. Advances in the representation of hydrologic process in ESMs can substantially improve energy, carbon and nutrient cycle prediction capabilities through the fundamental role the water cycle plays in regulating these cycles.

  1. Life prediction methodology for ceramic components of advanced heat engines. Phase 1: Volume 1, Final report

    SciTech Connect

    Cuccio, J.C.; Brehm, P.; Fang, H.T.

    1995-03-01

    Emphasis of this program is to develop and demonstrate ceramics life prediction methods, including fast fracture, stress rupture, creep, oxidation, and nondestructive evaluation. Significant advancements were made in these methods and their predictive capabilities successfully demonstrated.

  2. Integrated Hydrologic Validation to Improve Physical Precipitation Retrievals for GPM

    NASA Astrophysics Data System (ADS)

    Peters-Lidard, C. D.; Harrison, K. W.; Tian, Y.; Kumar, S.

    2011-12-01

    One of the five scientific objectives for GPM is to "Improve hydrological modeling and prediction", including advancing prediction skill for high-impact hazards such as floods, droughts, landslides and landfalling hurricanes. Given the focus on land hydrology, and the range of hydrologic regimes targeted by GPM, it follows that a hydrologically-oriented ground validation program that covers these regimes from both the physical retrieval and the hydrological prediction perspectives is required for the successful application of GPM to land hydrology. In order to investigate the robustness of both hydrologic model predictions and physical precipitation retrievals, this talk will present recent evaluations of skill in land surface hydrologic models forced with TRMM-era multisensor products, with and without land data assimilation. In addition to LSM skill, we will also demonstrate how physical precipitation retrievals can be supported by land surface emissivity and temperature estimates obtained by coupling microwave emission models (e.g., the Joint Center for Satellite Data Assimilation Community Radiative Transfer Model CRTM and the European Center for Medium-Range Weather Forecasting's Community Microwave Emission Model CMEM) to the land surface models in the Land Information System (LIS; http://lis.gsfc.nasa.gov). Evaluation at multiple frequencies, with and without land data assimilation, demonstrates the critical impact of certain real-time ancillary data (e.g., snow cover) on the microwave background states required for physical retrievals.

  3. Neighbourhood selection for local modelling and prediction of hydrological time series

    NASA Astrophysics Data System (ADS)

    Jayawardena, A. W.; Li, W. K.; Xu, P.

    2002-02-01

    The prediction of a time series using the dynamical systems approach requires the knowledge of three parameters; the time delay, the embedding dimension and the number of nearest neighbours. In this paper, a new criterion, based on the generalized degrees of freedom, for the selection of the number of nearest neighbours needed for a better local model for time series prediction is presented. The validity of the proposed method is examined using time series, which are known to be chaotic under certain initial conditions (Lorenz map, Henon map and Logistic map), and real hydro meteorological time series (discharge data from Chao Phraya river in Thailand, Mekong river in Thailand and Laos, and sea surface temperature anomaly data). The predicted results are compared with observations, and with similar predictions obtained by using arbitrarily fixed numbers of neighbours. The results indicate superior predictive capability as measured by the mean square errors and coefficients of variation by the proposed approach when compared with the traditional approach of using a fixed number of neighbours.

  4. Predicted hydrologic effects of pumping from the Lichterman Well Field in the Memphis Area, Tennessee

    USGS Publications Warehouse

    Nyman, Dale J.

    1965-01-01

    The Lichterman well field is scheduled to go into operation early in 1965 to supplement the municipal water-supply system for the city of Memphis, Tenn. Although the initial rate of withdrawal from the well field will be about 8 mgd (million gallons per day), the ultimate design capacity of the field is 20 mgd. A study of sand samples, drillers' logs, and geophysical logs collected during preliminary test drilling at the site for the Lichterman well field was used as a basis for defining three zones of sand favorable for the construction of high-capacity (1,000 gallons per minute or more) water wells. The three zones occur in the '500-foot' sand and are here designated (in descending order) as zone A, zone B, and zone C. The depth to the top of these zones below land surface has the following ranges: zone A, 125 to 225 feet; zone B, 200 to 350 feet; and zone C, 700 to 775 feet. Zones A and B range from 0 to 100 feet in thickness, and zone C ranges from 10 to 100 feet in thickness. Within the well field proper these zones are expected to react to the stress of pumping as separate hydrologic units, but outside the well field the three zones are expected to react as a single hydrologic unit. The '500-foot' sand in the Germantown-Collierville area is recharged chiefly by precipitation on the outcrop area of the sand to the east, but the evidence indicates that additional recharge is entering the aquifer from the Wolf River. In spite of this additional recharge, water levels in the '500-foot' sand are declining at an average rate of about two-thirds of a foot per year, owing to municipal and industrial pumpage in the Memphis area. However, this decline is not expected to alter the excellent quality of the water in the '500-foot' sand at the site of the Lichterman well field. Pumping in the Lichterman well field will create a cone of depression in the free-water (piezometric) surface of the '500-foot' sand. The decline in water levels will be directly proportional to the

  5. Design storm prediction and hydrologic modeling using a web-GIS approach on a free-software platform

    NASA Astrophysics Data System (ADS)

    Castrogiovanni, E. M.; La Loggia, G.; Noto, L. V.

    2005-09-01

    The aim of this work has been to implement a set of procedures useful to automatise the evaluation, the design storm prediction and the flood discharge associated with a selected risk level. For this purpose a Geographic Information System has been implemented using Grass 5.0. One of the main topics of such a system is a georeferenced database of the highest intensity rainfalls and their assigned duration recorded in Sicily. This database contains the main characteristics for more than 250 raingauges, as well as the values of intense rainfall events recorded by these raingauges. These data are managed through the combined use of the PostgreSQL and GRASS-GIS 5.0 databases. Some of the best-known probability distributions have been implemented within the Geographical Information System in order to determine the point and/or areal rain values once duration and return period have been defined. The system also includes a hydrological module necessary to compute the probable flow, for a selected risk level, at points chosen by the user. A peculiarity of the system is the possibility to querying the model using a web-interface. The assumption is that the rising needs of geographic information, and dealing with the rising importance of peoples participation in the decision process, requires new forms for the diffusion of territorial data. Furthermore, technicians as well as public administrators needs to get customized and specialist data to support planning, particularly in emergencies. In this perspective a Web-interface has been developed for the hydrologic system. The aim is to allow remote users to access a centralized database and processing-power to serve the needs of knowledge without complex hardware/software infrastructures.

  6. Hydrologic modeling as a predictive basis for ecological restoration of salt marshes

    USGS Publications Warehouse

    Roman, C.T.; Garvine, R.W.; Portnoy, J.W.

    1995-01-01

    Roads, bridges, causeways, impoundments, and dikes in the coastal zone often restrict tidal flow to salt marsh ecosystems. A dike with tide control structures, located at the mouth of the Herring River salt marsh estuarine system (Wellfleet, Massachusetts) since 1908, has effectively restricted tidal exchange, causing changes in marsh vegetation composition, degraded water quality, and reduced abundance of fish and macroinvertebrate communities. Restoration of this estuary by reintroduction of tidal exchange is a feasible management alternative. However, restoration efforts must proceed with caution as residential dwellings and a golf course are located immediately adjacent to and in places within the tidal wetland. A numerical model was developed to predict tide height levels for numerous alternative openings through the Herring River dike. Given these model predictions and knowledge of elevations of flood-prone areas, it becomes possible to make responsible decisions regarding restoration. Moreover, tidal flooding elevations relative to the wetland surface must be known to predict optimum conditions for ecological recovery. The tide height model has a universal role, as demonstrated by successful application at a nearby salt marsh restoration site in Provincetown, Massachusetts. Salt marsh restoration is a valuable management tool toward maintaining and enhancing coastal zone habitat diversity. The tide height model presented in this paper will enable both scientists and resource professionals to assign a degree of predictability when designing salt marsh restoration programs.

  7. Leveraging simultaneous SMOS and ASCAT soil moisture products for enhanced hydrologic prediction

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Runoff predictions obtained from rainfall runoff model are typically degraded for a wide variety of error sources including the inaccurate specification of pre-storm soil moisture conditions (determining infiltration capacity) and random error in rainfall inputs (especially in areas of a world lacki...

  8. An integrated tool for real time prediction of hydrological response of steep-slopes in shallow pyroclastic deposits

    NASA Astrophysics Data System (ADS)

    Damiano, E.; Giorgio, M.; Greco, R.; Guida, A.; Netti, N.; Olivares, L.; Savastano, V.

    2012-04-01

    A large part of the mountains of Campania, in southern Italy, are interested by catastrophic flowslides triggered by heavy rainfalls. The slopes are covered by shallow deposits of loose pyroclastic soils in unsaturated conditions, which equilibrium is assured by the contribution of apparent cohesion due to soil suction. Hence, a key tool for the prediction of slope stability is the short-term forecasting of intense and persistent rainfall events and the subsequent analysis of the hydrological response of the shallow covers during such events. To this aim a numerical tool, is presented, consisting of a module for stochastic short-term rainfall prediction and 3D finite volumes model of infiltration and seepage through porous medium, provided with a geotechnical module for slope stability analysis. The presented predictor of rainfall evolution consists of an event based stochastic model, allowing formulating real time predictions of the future evolution of a storm, conditioned to the observed part of the storm. The 3D code (I-MOD3D) was calibrated through back-analysis of infiltration tests on slope model (Olivares et al. 2009) and of in situ suction measurements (Olivares and Damiano, 2007) collected in a instrumented site on a slope where recently a catastrophic flowslide occurred. The calibrated model has been applied to real time predictions of the slope response during some observed storms, showing the reliability of the results of the proposed model, which may represent a useful tool for decision making to implement early warning systems. Olivares L. and Damiano E. (2007). Post-failure mechanics of landslides: laboratory investigation of flowslides in pyroclastic soils. Journal of Geotechnical and Geoenvironmental Engineering ASCE, 133(1): 51-62 Olivares L., Damiano E, Greco R, Zeni L, Picarelli L, Minardo A, Guida A, Bernini R (2009). An Instrumented Flume to Investigate the Mechanics of Rainfall-Induced Landslides in Unsaturated Granular Soils. GEOTECHNICAL

  9. Weather radar rainfall data in urban hydrology

    NASA Astrophysics Data System (ADS)

    Thorndahl, Søren; Einfalt, Thomas; Willems, Patrick; Ellerbæk Nielsen, Jesper; ten Veldhuis, Marie-Claire; Arnbjerg-Nielsen, Karsten; Rasmussen, Michael R.; Molnar, Peter

    2017-03-01

    Application of weather radar data in urban hydrological applications has evolved significantly during the past decade as an alternative to traditional rainfall observations with rain gauges. Advances in radar hardware, data processing, numerical models, and emerging fields within urban hydrology necessitate an updated review of the state of the art in such radar rainfall data and applications. Three key areas with significant advances over the past decade have been identified: (1) temporal and spatial resolution of rainfall data required for different types of hydrological applications, (2) rainfall estimation, radar data adjustment and data quality, and (3) nowcasting of radar rainfall and real-time applications. Based on these three fields of research, the paper provides recommendations based on an updated overview of shortcomings, gains, and novel developments in relation to urban hydrological applications. The paper also reviews how the focus in urban hydrology research has shifted over the last decade to fields such as climate change impacts, resilience of urban areas to hydrological extremes, and online prediction/warning systems. It is discussed how radar rainfall data can add value to the aforementioned emerging fields in current and future applications, but also to the analysis of integrated water systems.

  10. 76 FR 52954 - Workshop: Advancing Research on Mixtures; New Perspectives and Approaches for Predicting Adverse...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-08-24

    ... HUMAN SERVICES Workshop: Advancing Research on Mixtures; New Perspectives and Approaches for Predicting... ``Advancing Research on Mixtures: New Perspectives and Approaches for Predicting Adverse Human Health Effects....niehs.nih.gov/conferences/dert/mixtures/ . The deadline to register for this workshop is...

  11. Prediction of surface flow hydrology and sediment retention upslope of a vetiver buffer strip

    NASA Astrophysics Data System (ADS)

    Hussein, Janet; Yu, Bofu; Ghadiri, Hossein; Rose, Calvin

    2007-05-01

    SummaryVegetated buffer strips are widely used to reduce fluxes of eroding soil and associated chemicals, from hillslopes into waterways. Sediment retention by buffers is time-dependent, with its effectiveness changing with the deposition process. Our research focuses on settling of sediment upslope of stiff grass buffers at three slopes, under subcritical flow conditions. A new model is developed which couples the hydraulics, sediment deposition and subsequent adjustment to topography in order to predict water and sediment profiles upslope of a buffer with time. Experiments to test the model were carried out in the Griffith University Tilting-Flume Simulated Rainfall facility using subcritical flows at 1%, 3% and 5% slopes. Water and sediment profiles were measured at different times as Vertisol sediment was introduced upslope of a vetiver grass strip. A region of increased flow depth (backwater) was produced upslope of the strip which increased in depth and decreased in length with increasing slope. Backwater height could be predicted from flow rates and thus could be used as an input for the model in the absence of experimental data. As slope increased, sediment was deposited closer to the grass strip, moving into the grass strip itself at 5% slope. The grass strip was less effective in reducing sediment in the outflow as slope increased and differences between slopes were significant. Model prediction of water and sediment profiles compared reasonably well with measured data, giving low root mean square errors and high coefficients of model efficiency. Masses of deposited sediment were generally simulated within 20% of measured values. However, simulated particle size distributions of deposited sediment were less accurate.

  12. Lifetime prediction modeling of airfoils for advanced power generation

    NASA Astrophysics Data System (ADS)

    Karaivanov, Ventzislav Gueorguiev

    The use of gases produced from coal as a turbine fuel offers an attractive means for efficiently generating electric power from our Nation's most abundant fossil fuel resource. The oxy-fuel and hydrogen-fired turbine concepts promise increased efficiency and low emissions on the expense of increased turbine inlet temperature (TIT) and different working fluid. Developing the turbine technology and materials is critical to the creation of these near-zero emission power generation technologies. A computational methodology, based on three-dimensional finite element analysis (FEA) and damage mechanics is presented for predicting the evolution of creep and fatigue in airfoils. We took a first look at airfoil thermal distributions in these advanced turbine systems based on CFD analysis. The damage mechanics-based creep and fatigue models were implemented as user modified routine in commercial package ANSYS. This routine was used to visualize the creep and fatigue damage evolution over airfoils for hydrogen-fired and oxy-fuel turbines concepts, and regions most susceptible to failure were indentified. Model allows for interaction between creep and fatigue damage thus damage due to fatigue and creep processes acting separately in one cycle will affect both the fatigue and creep damage rates in the next cycle. Simulation results were presented for various thermal conductivity of the top coat. Surface maps were created on the airfoil showing the development of the TGO scale and the Al depletion of the bond coat. In conjunction with model development, laboratory-scale experimental validation was executed to evaluate the influence of operational compressive stress levels on the performance of the TBC system. TBC coated single crystal coupons were exposed isothermally in air at 900, 1000, 1100oC with and without compressive load. Exposed samples were cross-sectioned and evaluated with scanning electron microscope (SEM). Performance data was collected based on image analysis

  13. Thermal Model Predictions of Advanced Stirling Radioisotope Generator Performance

    NASA Technical Reports Server (NTRS)

    Wang, Xiao-Yen J.; Fabanich, William Anthony; Schmitz, Paul C.

    2014-01-01

    This presentation describes the capabilities of three-dimensional thermal power model of advanced stirling radioisotope generator (ASRG). The performance of the ASRG is presented for different scenario, such as Venus flyby with or without the auxiliary cooling system.

  14. Hydrology and Change (Invited)

    NASA Astrophysics Data System (ADS)

    Koutsoyiannis, D.

    2009-12-01

    Since “panta rhei” was pronounced by Heraclitus, hydrology and the objects it studies, such as rivers and lakes, offer grounds to observe and understand change and flux. Change occurs on all time scales, from minute to geological, but our limited senses and life span, as well as the short time window of instrumental observations, restrict our perception to the most apparent daily to yearly variations. As a result, our typical modelling practices assume that natural changes are just a short-term “noise” superimposed to the daily and annual cycles in a scene that is static and invariant in the long run. According to this perception, only an exceptional and extraordinary forcing can produce a long-term change. The hydrologist H. E. Hurst, studying the long flow records of the Nile and other geophysical time series, was the first to observe a natural behaviour, named after him, related to multi-scale change, as well as its implications in engineering designs. Essentially, this behaviour manifests that long-term changes are much more frequent and intense than commonly perceived and, simultaneously, that the future states are much more uncertain and unpredictable on long time horizons than implied by standard approaches. Due to its close relationship with engineering design, hydrology has always been concerned with long-term predictions. Hydrologists understood early that deterministic predictions for typical design horizons of 50-100 years are hopeless and appreciated the usefulness of probabilistic approaches. Yet, during the last two decades, hydrology, following other geophysical disciplines, changed perspective and invested its hopes in deterministic descriptions and models. In particular, climate model outputs have been assumed to represent the future of hydrological inputs for the next 50-100 years. However, recent comparisons of climate model results with long historical records for local to sub-continental spatial scales show that these models are not

  15. Capability of passive microwave and SNODAS SWE estimates for hydrologic predictions in selected U.S. watersheds

    NASA Astrophysics Data System (ADS)

    Vuyovich, C.; Jacobs, J. M.

    2013-12-01

    In the United States, a dedicated system of snow measurement stations (SNOTEL) and snowpack modeling products (SNODAS) are available to estimate the snow water equivalent (SWE) throughout the winter seasons. Even in the U.S., water resource management is hampered by limited snow data in certain regions, as evident by the 2011 Missouri Basin flooding due in large part to the significant Plains snowpack. In other regions of the world that depend on snowmelt for water resources, snow data can be scarce, and these regions are vulnerable to drought or flood conditions. Satellite data could potentially provide important information in under-sampled areas. Passive microwave data have shown some skill in estimating SWE in several regions of the United States, as compared with the SNODAS spatially distributed estimates. However, the SNODAS product contains greater uncertainty in regions with limited observations or that experience wind redistribution of snow. This study evaluates SWE estimates from AMSR-E and SSM/I satellites, and the SNODAS product, in several watersheds throughout the United States by comparison with discharge data. Watersheds large enough to be appropriate for passive microwave resolution were selected from the Hydro-Climatic Data Network (HCDN), which identifies watersheds with minimal human impacts to stream flow. A water balance analysis was conducted to determine the predictive capability of passive microwave for hydrological applications.

  16. Advanced System-Level Reliability Analysis and Prediction with Field Data Integration

    DTIC Science & Technology

    2011-09-01

    innovative life prediction methodologies that incorporate emerging probabilistic lifing techniques as well as advanced physics-of- failure...often based on simplifying assumptions and their predictions may suffer from different sources of uncertainty. For instance, one source of...system level, most modeling approaches focus on life prediction for single components and fail to account for the interdependencies that may result

  17. Prediction in cases with superposition of different hydrological phenomena, such as from weather "cold drops

    NASA Astrophysics Data System (ADS)

    Anton, J. M.; Grau, J. B.; Tarquis, A. M.; Andina, D.; Sanchez, M. E.

    2012-04-01

    The authors have been involved in Model Codes for Construction prior to Eurocodes now Euronorms, and in a Drainage Instruction for Roads for Spain that adopted a prediction model from BPR (Bureau of Public Roads) of USA to take account of evident regional differences in Iberian Peninsula and Spanish Isles, and in some related studies. They used Extreme Value Type I (Gumbell law) models, with independent actions in superposition; this law was also adopted then to obtain maps of extreme rains by CEDEX. These methods could be extrapolated somehow with other extreme values distributions, but the first step was useful to set valid superposition schemas for actions in norms. As real case, in East of Spain rain comes usually extensively from normal weather perturbations, but in other cases from "cold drop" local high rains of about 400mm in a day occur, causing inundations and in cases local disasters. The city of Valencia in East of Spain was inundated at 1,5m high from a cold drop in 1957, and the river Turia formerly through that city was just later diverted some kilometers to South in a wider canal. With Gumbell law the expected intensity grows with time for occurrence, indicating a value for each given "return period", but the increasing speed grows with the "annual dispersion" of the Gumbell law, and some rare dangerous events may become really very possible in periods of many years. That can be proved with relatively simple models, e.g. with Extreme Law type I, and they could be made more precise or discussed. Such effects were used for superposition of actions on a structure for Model Codes, and may be combined with hydraulic effects, e.g. for bridges on rivers. These different Gumbell laws, or other extreme laws, with different dispersion may occur for marine actions of waves, earthquakes, tsunamis, and maybe for human perturbations, that could include industrial catastrophes, or civilization wars if considering historical periods.

  18. Predicting Performance in Technical Preclinical Dental Courses Using Advanced Simulation.

    PubMed

    Gottlieb, Riki; Baechle, Mary A; Janus, Charles; Lanning, Sharon K

    2017-01-01

    The aim of this study was to investigate whether advanced simulation parameters, such as simulation exam scores, number of student self-evaluations, time to complete the simulation, and time to complete self-evaluations, served as predictors of dental students' preclinical performance. Students from three consecutive classes (n=282) at one U.S. dental school completed advanced simulation training and exams within the first four months of their dental curriculum. The students then completed conventional preclinical instruction and exams in operative dentistry (OD) and fixed prosthodontics (FP) courses, taken during the first and second years of dental school, respectively. Two advanced simulation exam scores (ASES1 and ASES2) were tested as predictors of performance in the two preclinical courses based on final course grades. ASES1 and ASES2 were found to be predictors of OD and FP preclinical course grades. Other advanced simulation parameters were not significantly related to grades in the preclinical courses. These results highlight the value of an early psychomotor skills assessment in dentistry. Advanced simulation scores may allow early intervention in students' learning process and assist in efficient allocation of resources such as faculty coverage and tutor assignment.

  19. Regional aspects of the North American land surface: Atmosphere interactions and their contributions to the variability and predictability of the regional hydrologic cycle

    NASA Astrophysics Data System (ADS)

    Luo, Yan

    In this study, we investigate the pathways responsible for soil moisture-precipitation interactions and the mechanisms for soil moisture memory at regional scales through analysis of NCEP's North American Regional Reanalysis dataset, which is derived from a system using the mesoscale Eta model coupled with Noah land surface model. The consideration of the relative availability of water and energy leads to the relative strengths of land-atmosphere interaction and soil moisture memory, which are related to the predictability of the regional hydrologic cycle. The seasonal and geographical variations in estimated interaction and memory may establish the relative predictability among the North American basins. The potential for seasonal predictability of the regional hydrologic cycle is conditioned by the foreknowledge of the land surface soil state, which contributes significantly to summer precipitation: (i) The precipitation variability and predictability by strong land-atmosphere interactions are most important in the monsoon regions of Mexico; (ii) Although strong in interactions, the poor soil moisture memory in the Colorado basin and the western part of the Mississippi basin lowers the predictability; (iii) The Columbia basin and the eastern part of the Mississippi basin also stand out as low predictability basins, in that they have good soil moisture memory, but weak strength in interactions, limiting their predictabilities. Our analysis has revealed a highly physically and statistically consistent picture, providing solid support to studies of predictability based on model simulations.

  20. Use of oxygen-18 and deuterium to assess the hydrology of groundwater-lake systems: Chapter 3: Advances in chemistry

    USGS Publications Warehouse

    Krabbenhoft, David P.; Bowser, Carl J.; Kendall, Carol; Gat, Joel

    2009-01-01

    A thorough understanding of a lake's hydrology is essential for many lake studies. In some situations the interactions between groundwater systems and lakes are complex; in other cases the hydrology of a multilake system needs to be quantified. In such places, stable isotopes offer an alternative to the more traditional piezometer networks, which are costly to install and time-consuming to maintain. The stable-isotope mass-balance relations presented here can be used to estimate groundwater exchange rates for individual lakes and geographically clustered lakes. These relations also can be used to estimate other hydrological factors, such as average relative humidity. In places where the groundwater system is unstable (e.g., where flow reversals occur), natural solute tracers may provide a better alternative than stable isotopes for estimating rates of groundwater flow to and from lakes.

  1. Advances and Computational Tools towards Predictable Design in Biological Engineering

    PubMed Central

    2014-01-01

    The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated. PMID:25161694

  2. Advanced GIS Exercise: Predicting Rainfall Erosivity Index Using Regression Analysis

    ERIC Educational Resources Information Center

    Post, Christopher J.; Goddard, Megan A.; Mikhailova, Elena A.; Hall, Steven T.

    2006-01-01

    Graduate students from a variety of agricultural and natural resource fields are incorporating geographic information systems (GIS) analysis into their graduate research, creating a need for teaching methodologies that help students understand advanced GIS topics for use in their own research. Graduate-level GIS exercises help students understand…

  3. Factors that Predict Who Takes Advanced Courses in Cognitive Therapy

    ERIC Educational Resources Information Center

    Pehlivanidis, Artemios

    2007-01-01

    Training in Cognitive Therapy (CT) includes theoretical and didactic components combined with clinical supervision. An introductory course in CT might satisfy training needs in psychotherapy and help in the selection of those trainees who wish to continue to an advanced training level. Predictors of success at such an introductory course have been…

  4. Perceptions and Predictions of Expertise in Advanced Musical Learners

    ERIC Educational Resources Information Center

    Papageorgi, Ioulia; Creech, Andrea; Haddon, Elizabeth; Morton, Frances; De Bezenac, Christophe; Himonides, Evangelos; Potter, John; Duffy, Celia; Whyton, Tony; Welch, Graham

    2010-01-01

    The aim of this article was to compare musicians' views on (a) the importance of musical skills and (b) the nature of expertise. Data were obtained from a specially devised web-based questionnaire completed by advanced musicians representing four musical genres (classical, popular, jazz, Scottish traditional) and varying degrees of professional…

  5. firestar--advances in the prediction of functionally important residues.

    PubMed

    Lopez, Gonzalo; Maietta, Paolo; Rodriguez, Jose Manuel; Valencia, Alfonso; Tress, Michael L

    2011-07-01

    firestar is a server for predicting catalytic and ligand-binding residues in protein sequences. Here, we present the important developments since the first release of firestar. Previous versions of the server required human interpretation of the results; the server is now fully automatized. firestar has been implemented as a web service and can now be run in high-throughput mode. Prediction coverage has been greatly improved with the extension of the FireDB database and the addition of alignments generated by HHsearch. Ligands in FireDB are now classified for biological relevance. Many of the changes have been motivated by the critical assessment of techniques for protein structure prediction (CASP) ligand-binding prediction experiment, which provided us with a framework to test the performance of firestar. URL: http://firedb.bioinfo.cnio.es/Php/FireStar.php.

  6. PREDICTIVE UNCERTAINTY IN HYDROLOGIC AND WATER QUALITY MODELING: APPROACHES, APPLICATION TO ENVIRONMENTAL MANAGEMENT, AND FUTURE CHALLENGES (PRESENTATION)

    EPA Science Inventory

    Extant process-based hydrologic and water quality models are indispensable to water resources planning and environmental management. However, models are only approximations of real systems and often calibrated with incomplete and uncertain data. Reliable estimates, or perhaps f...

  7. Advancements in decadal climate predictability: The role of nonoceanic drivers

    NASA Astrophysics Data System (ADS)

    Bellucci, A.; Haarsma, R.; Bellouin, N.; Booth, B.; Cagnazzo, C.; Hurk, B.; Keenlyside, N.; Koenigk, T.; Massonnet, F.; Materia, S.; Weiss, M.

    2015-06-01

    We review recent progress in understanding the role of sea ice, land surface, stratosphere, and aerosols in decadal-scale predictability and discuss the perspectives for improving the predictive capabilities of current Earth system models (ESMs). These constituents have received relatively little attention because their contribution to the slow climatic manifold is controversial in comparison to that of the large heat capacity of the oceans. Furthermore, their initialization as well as their representation in state-of-the-art climate models remains a challenge. Numerous extraoceanic processes that could be active over the decadal range are proposed. Potential predictability associated with the aforementioned, poorly represented, and scarcely observed constituents of the climate system has been primarily inspected through numerical simulations performed under idealized experimental settings. The impact, however, on practical decadal predictions, conducted with realistically initialized full-fledged climate models, is still largely unexploited. Enhancing initial-value predictability through an improved model initialization appears to be a viable option for land surface, sea ice, and, marginally, the stratosphere. Similarly, capturing future aerosol emission storylines might lead to an improved representation of both global and regional short-term climatic changes. In addition to these factors, a key role on the overall predictive ability of ESMs is expected to be played by an accurate representation of processes associated with specific components of the climate system. These act as "signal carriers," transferring across the climatic phase space the information associated with the initial state and boundary forcings, and dynamically bridging different (otherwise unconnected) subsystems. Through this mechanism, Earth system components trigger low-frequency variability modes, thus extending the predictability beyond the seasonal scale.

  8. Advances in fatigue life prediction methodology for metallic materials

    NASA Technical Reports Server (NTRS)

    Newman, J. C., Jr.

    1992-01-01

    The capabilities of a plasticity-induced crack-closure model to predict small- and large-crack growth rates, and in some cases total fatigue life, for four aluminum alloys and three titanium alloys under constant-amplitude, variable-amplitude, and spectrum loading are described. Equations to calculate a cyclic-plastic-zone corrected effective stress-intensity factor range from a cyclic J-integral and crack-closure analysis of large cracks were reviewed. The effective stress-intensity factor range against crack growth rate relations were used in the closure model to predict small- and large-crack growth under variable-amplitude and spectrum loading. Using the closure model and microstructural features, a total fatigue life prediction method is demonstrated for three aluminum alloys under various load histories.

  9. Finding diversity for building one-day ahead Hydrological Ensemble Prediction System based on artificial neural network stacks

    NASA Astrophysics Data System (ADS)

    Brochero, Darwin; Anctil, Francois; Gagné, Christian; López, Karol

    2013-04-01

    In this study, we addressed the application of Artificial Neural Networks (ANN) in the context of Hydrological Ensemble Prediction Systems (HEPS). Such systems have become popular in the past years as a tool to include the forecast uncertainty in the decision making process. HEPS considers fundamentally the uncertainty cascade model [4] for uncertainty representation. Analogously, the machine learning community has proposed models of multiple classifier systems that take into account the variability in datasets, input space, model structures, and parametric configuration [3]. This approach is based primarily on the well-known "no free lunch theorem" [1]. Consequently, we propose a framework based on two separate but complementary topics: data stratification and input variable selection (IVS). Thus, we promote an ANN prediction stack in which each predictor is trained based on input spaces defined by the IVS application on different stratified sub-samples. All this, added to the inherent variability of classical ANN optimization, leads us to our ultimate goal: diversity in the prediction, defined as the complementarity of the individual predictors. The stratification application on the 12 basins used in this study, which originate from the second and third workshop of the MOPEX project [2], shows that the informativeness of the data is far more important than the quantity used for ANN training. Additionally, the input space variability leads to ANN stacks that outperform an ANN stack model trained with 100% of the available information but with a random selection of dataset used in the early stopping method (scenario R100P). The results show that from a deterministic view, the main advantage focuses on the efficient selection of the training information, which is an equally important concept for the calibration of conceptual hydrological models. On the other hand, the diversity achieved is reflected in a substantial improvement in the scores that define the

  10. RNA Structure: Advances and Assessment of 3D Structure Prediction.

    PubMed

    Miao, Zhichao; Westhof, Eric

    2017-03-30

    Biological functions of RNA molecules are dependent upon sustained specific three-dimensional (3D) structures of RNA, with or without the help of proteins. Understanding of RNA structure is frequently based on 2D structures, which describe only the Watson-Crick (WC) base pairs. Here, we hierarchically review the structural elements of RNA and how they contribute to RNA 3D structure. We focus our analysis on the non-WC base pairs and on RNA modules. Several computer programs have now been designed to predict RNA modules. We describe the RNA-Puzzles initiative, which is a community-wide, blind assessment of RNA 3D structure prediction programs to determine the capabilities and bottlenecks of current predictions. The assessment metrics used in RNA-Puzzles are briefly described. The detection of RNA 3D modules from sequence data and their automatic implementation belong to the current challenges in RNA 3D structure prediction. Expected final online publication date for the Annual Review of Biophysics Volume 46 is May 20, 2017. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

  11. Advances in Modeling Streambank Stability by Incorporating the Mechanical and Hydrologic Effects of Woody and Herbaceous Riparian Vegetation

    NASA Astrophysics Data System (ADS)

    Simon, A.; Collison, A. J.

    2001-12-01

    Sediment is one of the principle pollutants of surface waters of the United States. Sediment derived from streambanks by mass failure is a significant contributor to water-quality and land management problems. Accurately modeling streambank stability and potential mitigation strategies using riparian vegetation involves quantifying the hydrologic and mechanical factors that control the driving and resisting forces imposed by bank material, ground and surface water and the vegetation. Stabilization of streambanks using riparian vegetation offers numerous potential benefits and some potential problems that are related to mechanical and hydrological effects that are rarely quantified. In this study mechanical reinforcement of various woody and herbaceous riparian species is quantified with in situ, field measurements of root tensile strength, root sizes and root distribution that are used to calculate increases in soil cohesion. Hydrological effects of vegetation are monitored at the Goodwin Creek Experimental Watershed, Mississippi using interception plots and tensiometers under three vegetative covers: cropped grass `control' cover, clumps of eastern gamma grass, and a deciduous woody-vegetation stand. The ARS Bank-Stability Model which accounts for complex bank geometries, up to five soil layers, positive and negative pore-water pressures and confining pressure due to streamflow is used to evaluate the effectiveness of various vegetative treatments based on the field data. The model is used to evaluate the individual and combined effects of vegetation on streambank stability. On April 4 th 2000 prolonged rainfall at the field site caused bank failure at the control cover plot, providing useful validation data for the analysis. The resulting factor of safety (Fs) values (incorporating both hydrological and mechanical effects) were 1.04, 1.64 and 2.18, respectively. Results show that the main contribution of the woody-vegetation to bank stability during the study

  12. Broadband noise - Its prediction and likely importance for advanced propfans

    NASA Astrophysics Data System (ADS)

    Knowles, K.

    1986-07-01

    A comparison of published experimental results and analytical results on broadband noise evaluations for rotating many-bladed propellers has been conducted to assess the importance of broadband noise in the perceived noise (PN) level of propfans. It is concluded that, in cruise conditions, the tone noise dominates the broadband noise of typical propfans by 8 dB. As the speed is reduced, and the values of forward Mach number and helical tip Mach number are reduced, the tones fall more rapidly than the broadband component until, at approach conditions, the broadband noise is dominant by 8 to 16 PNdB. A survey of the state-of-the-art of broadband noise prediction suggests that the broadband noise can be predicted to within 5 dB.

  13. Early Prediction of Lupus Nephritis Using Advanced Proteomics

    DTIC Science & Technology

    2009-06-01

    nephritis from non inflammatory nephropathies with similar urinary findings. 1.2: Validation of NGAL as a biomarker for predicting SLE disease...R01-DK-069749, R01-DK-53289, P50-DK-52612, and R21-DK-070163 from the National Institute of Diabetes and Digestive and Kidney Diseases) and by the...significant, and P values less than 0.1 were reported to show trends. RESULTS Baseline patient characteristics and treatments . Table 1 summarizes the

  14. Life prediction of advanced materials for gas turbine application

    SciTech Connect

    Zamrik, S.Y.; Ray, A.; Koss, D.A.

    1995-10-01

    Most of the studies on the low cycle fatigue life prediction have been reported under isothermal conditions where the deformation of the material is strain dependent. In the development of gas turbines, components such as blades and vanes are exposed to temperature variations in addition to strain cycling. As a result, the deformation process becomes temperature and strain dependent. Therefore, the life of the component becomes sensitive to temperature-strain cycling which produces a process known as {open_quotes}thermomechanical fatigue, or TMF{close_quotes}. The TMF fatigue failure phenomenon has been modeled using conventional fatigue life prediction methods, which are not sufficiently accurate to quantitatively establish an allowable design procedure. To add to the complexity of TMF life prediction, blade and vane substrates are normally coated with aluminide, overlay or thermal barrier type coatings (TBC) where the durability of the component is dominated by the coating/substrate constitutive response and by the fatigue behavior of the coating. A number of issues arise from TMF depending on the type of temperature/strain phase cycle: (1) time-dependent inelastic behavior can significantly affect the stress response. For example, creep relaxation during a tensile or compressive loading at elevated temperatures leads to a progressive increase in the mean stress level under cyclic loading. (2) the mismatch in elastic and thermal expansion properties between the coating and the substrate can lead to significant deviations in the coating stress levels due to changes in the elastic modulii. (3) the {open_quotes}dry{close_quotes} corrosion resistance coatings applied to the substrate may act as primary crack initiation sites. Crack initiation in the coating is a function of the coating composition, its mechanical properties, creep relaxation behavior, thermal strain range and the strain/temperature phase relationship.

  15. Toward high-resolution flash flood prediction in large urban areas - Analysis of sensitivity to spatiotemporal resolution of rainfall input and hydrologic modeling

    NASA Astrophysics Data System (ADS)

    Rafieeinasab, Arezoo; Norouzi, Amir; Kim, Sunghee; Habibi, Hamideh; Nazari, Behzad; Seo, Dong-Jun; Lee, Haksu; Cosgrove, Brian; Cui, Zhengtao

    2015-12-01

    Urban flash flooding is a serious problem in large, highly populated areas such as the Dallas-Fort Worth Metroplex (DFW). Being able to monitor and predict flash flooding at a high spatiotemporal resolution is critical to providing location-specific early warnings and cost-effective emergency management in such areas. Under the idealized conditions of perfect models and precipitation input, one may expect that spatiotemporal specificity and accuracy of the model output improve as the resolution of the models and precipitation input increases. In reality, however, due to the errors in the precipitation input, and in the structures, parameters and states of the models, there are practical limits to the model resolution. In this work, we assess the sensitivity of streamflow simulation in urban catchments to the spatiotemporal resolution of precipitation input and hydrologic modeling to identify the resolution at which the simulation errors may be at minimum given the quality of the precipitation input and hydrologic models used, and the response time of the catchment. The hydrologic modeling system used in this work is the National Weather Service (NWS) Hydrology Laboratory's Research Distributed Hydrologic Model (HLRDHM) applied at spatiotemporal resolutions ranging from 250 m to 2 km and from 1 min to 1 h applied over the Cities of Fort Worth, Arlington and Grand Prairie in DFW. The high-resolution precipitation input is from the DFW Demonstration Network of the Collaborative Adaptive Sensing of the Atmosphere (CASA) radars. For comparison, the NWS Multisensor Precipitation Estimator (MPE) product, which is available at a 4-km 1-h resolution, was also used. The streamflow simulation results are evaluated for 5 urban catchments ranging in size from 3.4 to 54.6 km2 and from about 45 min to 3 h in time-to-peak in the Cities of Fort Worth, Arlington and Grand Prairie. The streamflow observations used in evaluation were obtained from water level measurements via rating

  16. Early Prediction of Lupus Nephritis Using Advanced Proteomics

    DTIC Science & Technology

    2012-06-01

    non inflammatory nephropathies with similar urinary findings. 1.2: Validation of NGAL as a biomarker for predicting SLE disease activity and course...Devarajan’s work was supported by the NIH (grants R01-DK-069749, R01-DK-53289, P50-DK-52612, and R21-DK-070163 from the National Institute of Diabetes and... treatments . Table 1 summarizes the characteristics of the 111 pa- tients included in the study. Their mean SD age was 15.9 3.4 years, and the

  17. Toward improved durability in advanced combustors and turbines: Progress in the prediction of thermomechanical loads

    NASA Technical Reports Server (NTRS)

    Sokolowski, Daniel E.; Ensign, C. Robert

    1986-01-01

    NASA is sponsoring the Turbine Engine Hot Section Technology (HOST) Project to address the need for improved durability in advanced combustors and turbines. Analytical and experimental activities aimed at more accurate prediction of the aerothermal environment, the thermomechanical loads, the material behavior and structural responses to such loading, and life predictions for high temperature cyclic operation have been underway for several years and are showing promising results. Progress is reported in the development of advanced instrumentation and in the improvement of combustor aerothermal and turbine heat transfer models that will lead to more accurate prediction of thermomechanical loads.

  18. Predicting the relativistic periastron advance of a binary without curving spacetime

    NASA Astrophysics Data System (ADS)

    Friedman, Y.; Livshitz, S.; Steiner, J. M.

    2017-01-01

    Relativistic Newtonian dynamics, the simple model used previously for predicting accurately the anomalous precession of Mercury, is now applied to predict the periastron advance of a binary. The classical treatment of a binary as a two-body problem is modified to account for the influence of the gravitational potential on spacetime. Without curving spacetime, the model predicts the identical equation for the relativistic periastron advance as the post-Newtonian approximation of the general relativity formalism thereby providing further substantiation of this model.

  19. The evolution of root-zone moisture capacities after deforestation: a step towards hydrological predictions under change?

    NASA Astrophysics Data System (ADS)

    Nijzink, Remko; Hutton, Christopher; Pechlivanidis, Ilias; Capell, René; Arheimer, Berit; Freer, Jim; Han, Dawei; Wagener, Thorsten; McGuire, Kevin; Savenije, Hubert; Hrachowitz, Markus

    2016-12-01

    The core component of many hydrological systems, the moisture storage capacity available to vegetation, is impossible to observe directly at the catchment scale and is typically treated as a calibration parameter or obtained from a priori available soil characteristics combined with estimates of rooting depth. Often this parameter is considered to remain constant in time. Using long-term data (30-40 years) from three experimental catchments that underwent significant land cover change, we tested the hypotheses that: (1) the root-zone storage capacity significantly changes after deforestation, (2) changes in the root-zone storage capacity can to a large extent explain post-treatment changes to the hydrological regimes and that (3) a time-dynamic formulation of the root-zone storage can improve the performance of a hydrological model.A recently introduced method to estimate catchment-scale root-zone storage capacities based on climate data (i.e. observed rainfall and an estimate of transpiration) was used to reproduce the temporal evolution of root-zone storage capacity under change. Briefly, the maximum deficit that arises from the difference between cumulative daily precipitation and transpiration can be considered as a proxy for root-zone storage capacity. This value was compared to the value obtained from four different conceptual hydrological models that were calibrated for consecutive 2-year windows.It was found that water-balance-derived root-zone storage capacities were similar to the values obtained from calibration of the hydrological models. A sharp decline in root-zone storage capacity was observed after deforestation, followed by a gradual recovery, for two of the three catchments. Trend analysis suggested hydrological recovery periods between 5 and 13 years after deforestation. In a proof-of-concept analysis, one of the hydrological models was adapted to allow dynamically changing root-zone storage capacities, following the observed changes due to

  20. StreamFlow 1.0: an extension to the spatially distributed snow model Alpine3D for hydrological modelling and deterministic stream temperature prediction

    NASA Astrophysics Data System (ADS)

    Gallice, Aurélien; Bavay, Mathias; Brauchli, Tristan; Comola, Francesco; Lehning, Michael; Huwald, Hendrik

    2016-12-01

    Climate change is expected to strongly impact the hydrological and thermal regimes of Alpine rivers within the coming decades. In this context, the development of hydrological models accounting for the specific dynamics of Alpine catchments appears as one of the promising approaches to reduce our uncertainty of future mountain hydrology. This paper describes the improvements brought to StreamFlow, an existing model for hydrological and stream temperature prediction built as an external extension to the physically based snow model Alpine3D. StreamFlow's source code has been entirely written anew, taking advantage of object-oriented programming to significantly improve its structure and ease the implementation of future developments. The source code is now publicly available online, along with a complete documentation. A special emphasis has been put on modularity during the re-implementation of StreamFlow, so that many model aspects can be represented using different alternatives. For example, several options are now available to model the advection of water within the stream. This allows for an easy and fast comparison between different approaches and helps in defining more reliable uncertainty estimates of the model forecasts. In particular, a case study in a Swiss Alpine catchment reveals that the stream temperature predictions are particularly sensitive to the approach used to model the temperature of subsurface flow, a fact which has been poorly reported in the literature to date. Based on the case study, StreamFlow is shown to reproduce hourly mean discharge with a Nash-Sutcliffe efficiency (NSE) of 0.82 and hourly mean temperature with a NSE of 0.78.

  1. The accuracy of clinicians' predictions of survival in advanced cancer: a review.

    PubMed

    Cheon, Stephanie; Agarwal, Arnav; Popovic, Marko; Milakovic, Milica; Lam, Michael; Fu, Wayne; DiGiovanni, Julia; Lam, Henry; Lechner, Breanne; Pulenzas, Natalie; Chow, Ronald; Chow, Edward

    2016-01-01

    The process of formulating an accurate survival prediction is often difficult but important, as it influences the decisions of clinicians, patients, and their families. The current article aims to review the accuracy of clinicians' predictions of survival (CPS) in advanced cancer patients. A literature search of Cochrane CENTRAL, EMBASE, and MEDLINE was conducted to identify studies that reported clinicians' prediction of survival in advanced cancer patients. Studies were included if the subjects consisted of advanced cancer patients and the data reported on the ability of clinicians to predict survival, with both estimated and observed survival data present. Studies reporting on the ability of biological and molecular markers to predict survival were excluded. Fifteen studies that met the inclusion and exclusion criteria were identified. Clinicians in five studies underestimated patients' survival (estimated to observed survival ratio between 0.5 and 0.92). In contrast, 12 studies reported clinicians' overestimation of survival (ratio between 1.06 and 6). CPS in advanced cancer patients is often inaccurate and overestimated. Given these findings, clinicians should be aware of their tendency to be overoptimistic. Further investigation of predictive patient and clinician characteristics is warranted to improve clinicians' ability to predict survival.

  2. Modelling Aerodynamically Generated Sound: Recent Advances in Rotor Noise Prediction

    NASA Technical Reports Server (NTRS)

    Brentner, Kenneth S.

    2000-01-01

    A great deal of progress has been made in the modeling of aerodynamically generated sound for rotors over the past decade. The Ffowcs Williams-Hawkings (FW-H ) equation has been the foundation for much of the development. Both subsonic and supersonic quadrupole noise formulations have been developed for the prediction of high-speed impulsive noise. In an effort to eliminate the need to compute the quadrupole contribution, the FW-H has also been utilized on permeable surfaces surrounding all physical noise sources. Comparison of the Kirchhoff formulation for moving surfaces with the FW-H equation have shown that the Kirchhoff formulation for moving surfaces can give erroneous results for aeroacoustic problems.

  3. Recent advances using rodent models for predicting human allergenicity

    SciTech Connect

    Knippels, Leon M.J. . E-mail: Knippels@voeding.tno.nl; Penninks, Andre H.

    2005-09-01

    The potential allergenicity of newly introduced proteins in genetically engineered foods has become an important safety evaluation issue. However, to evaluate the potential allergenicity and the potency of new proteins in our food, there are still no widely accepted and reliable test systems. The best-known allergy assessment proposal for foods derived from genetically engineered plants was the careful stepwise process presented in the so-called ILSI/IFBC decision tree. A revision of this decision tree strategy was proposed by a FAO/WHO expert consultation. As prediction of the sensitizing potential of the novel introduced protein based on animal testing was considered to be very important, animal models were introduced as one of the new test items, despite the fact that non of the currently studied models has been widely accepted and validated yet. In this paper, recent results are summarized of promising models developed in rat and mouse.

  4. Investigation of advanced UQ for CRUD prediction with VIPRE.

    SciTech Connect

    Eldred, Michael Scott

    2011-09-01

    This document summarizes the results from a level 3 milestone study within the CASL VUQ effort. It demonstrates the application of 'advanced UQ,' in particular dimension-adaptive p-refinement for polynomial chaos and stochastic collocation. The study calculates statistics for several quantities of interest that are indicators for the formation of CRUD (Chalk River unidentified deposit), which can lead to CIPS (CRUD induced power shift). Stochastic expansion methods are attractive methods for uncertainty quantification due to their fast convergence properties. For smooth functions (i.e., analytic, infinitely-differentiable) in L{sup 2} (i.e., possessing finite variance), exponential convergence rates can be obtained under order refinement for integrated statistical quantities of interest such as mean, variance, and probability. Two stochastic expansion methods are of interest: nonintrusive polynomial chaos expansion (PCE), which computes coefficients for a known basis of multivariate orthogonal polynomials, and stochastic collocation (SC), which forms multivariate interpolation polynomials for known coefficients. Within the DAKOTA project, recent research in stochastic expansion methods has focused on automated polynomial order refinement ('p-refinement') of expansions to support scalability to higher dimensional random input spaces [4, 3]. By preferentially refining only in the most important dimensions of the input space, the applicability of these methods can be extended from O(10{sup 0})-O(10{sup 1}) random variables to O(10{sup 2}) and beyond, depending on the degree of anisotropy (i.e., the extent to which randominput variables have differing degrees of influence on the statistical quantities of interest (QOIs)). Thus, the purpose of this study is to investigate the application of these adaptive stochastic expansion methods to the analysis of CRUD using the VIPRE simulation tools for two different plant models of differing random dimension, anisotropy, and

  5. Global-Scale Hydrology: Simple Characterization of Complex Simulation

    NASA Technical Reports Server (NTRS)

    Koster, Randal D.

    1999-01-01

    Atmospheric general circulation models (AGCMS) are unique and valuable tools for the analysis of large-scale hydrology. AGCM simulations of climate provide tremendous amounts of hydrological data with a spatial and temporal coverage unmatched by observation systems. To the extent that the AGCM behaves realistically, these data can shed light on the nature of the real world's hydrological cycle. In the first part of the seminar, I will describe the hydrological cycle in a typical AGCM, with some emphasis on the validation of simulated precipitation against observations. The second part of the seminar will focus on a key goal in large-scale hydrology studies, namely the identification of simple, overarching controls on hydrological behavior hidden amidst the tremendous amounts of data produced by the highly complex AGCM parameterizations. In particular, I will show that a simple 50-year-old climatological relation (and a recent extension we made to it) successfully predicts, to first order, both the annual mean and the interannual variability of simulated evaporation and runoff fluxes. The seminar will conclude with an example of a practical application of global hydrology studies. The accurate prediction of weather statistics several months in advance would have tremendous societal benefits, and conventional wisdom today points at the use of coupled ocean-atmosphere-land models for such seasonal-to-interannual prediction. Understanding the hydrological cycle in AGCMs is critical to establishing the potential for such prediction. Our own studies show, among other things, that soil moisture retention can lead to significant precipitation predictability in many midlatitude and tropical regions.

  6. Multimodel hydrologic ensemble predictions of peak flows: lessons learned from the real-time experiment in the upper Nysa Klodzka basin (SW Poland)

    NASA Astrophysics Data System (ADS)

    Niedzielski, Tomasz; Mizinski, Bartlomiej

    2015-04-01

    The novel system for issuing the real-time warnings against hydrologic hazards, known as HydroProg (research project no. 2011/01/D/ST10/04171 of the National Science Centre of Poland), has been implemented in the upper Nysa Klodzka basin (SW Poland). The system itself works like a bridge between automatic hydrometeorological observational networks and numerous hydrologic models. Its main objective is to automatically produce and publish flood warnings on a basis of prognoses of river stages calculated from dissimilar models and - most importantly - their multimodel ensembles which are computed in real time within HydroProg. The implementation in question for the upper Nysa Klodzka basin is abbreviated as HydroProg-Klodzko, and is feasible due to the partnership with Klodzko County which maintains the Local System for Flood Monitoring (Lokalny System Oslony Przeciwpowodziowej - LSOP). The HydroProg-Klodzko prototype is continuously, i.e. with 15-minute update, calculating multimodel hydrologic ensemble predictions and publishing them along with prognoses corresponding to individual ensemble members (www.klodzko.hydroprog.uni.wroc.pl). The real-time HydroProg-Klodzko experiment provided us with a valuable database of predictions as well as their errors and performance characteristics. At present, six hydrologic models participate in the experiment, however two of them (multi- and univariate autoregressive time series models) work uninterruptedly since the launch of the system in August 2013. The present study focuses on the detailed characterization of the real-time performance of the two models in predicting a few significant peak flows that occurred over the entire year of the experiment. In particular, we show how the two models can be weighted to produce skilful multimodel ensemble prognoses of river stages during peak flows. We identify phases of a peak flow in which, in order to improve the predictive skills, one should switch between individual models and

  7. Advancing alternatives analysis: The role of predictive toxicology in selecting safer chemical products and processes.

    PubMed

    Malloy, Timothy; Zaunbrecher, Virginia; Beryt, Elizabeth; Judson, Richard; Tice, Raymond; Allard, Patrick; Blake, Ann; Cote, Ila; Godwin, Hilary; Heine, Lauren; Kerzic, Patrick; Kostal, Jakub; Marchant, Gary; McPartland, Jennifer; Moran, Kelly; Nel, Andre; Oguseitan, Oladele; Rossi, Mark; Thayer, Kristina; Tickner, Joel; Whittaker, Margaret; Zarker, Ken

    2017-03-01

    Alternatives analysis (AA) is a method used in regulation and product design to identify, assess, and evaluate the safety and viability of potential substitutes for hazardous chemicals. It requires toxicological data for the existing chemical and potential alternatives. Predictive toxicology uses in silico and in vitro approaches, computational models, and other tools to expedite toxicological data generation in more cost-effective manner than traditional approaches. This article briefly reviews the challenges associated with using predictive toxicology in regulatory AA, then presents four recommendations for its advancement. It recommends using case studies to advance the integration of predictive toxicology into AA; adopting a stepwise process to employing predicative toxicology in AA beginning with prioritization of chemicals of concern; leveraging existing resources to advance the integration of predictive toxicology into the practice of AA, and supporting trans-disciplinary efforts. The further incorporation of predictive toxicology into AA would advance the ability of companies and regulators to select alternatives to harmful ingredients, and potentially increase the use of predictive toxicology in regulation more broadly. This article is protected by copyright. All rights reserved.

  8. Parameterization of Natural Depressions in Distributed Hydrologic Models: Implications for Scaling up Predictions of Sediment and Nutrient Yields in Ungauged Agricultural Watersheds

    NASA Astrophysics Data System (ADS)

    Chien, H.; Mackay, S.; Cabot, P. E.; Karthikeyan, K.

    2005-12-01

    Digital Elevation Models (DEMs) are widely used in distributed hydrologic modeling. In general, interior depressions within catchments are viewed as errors in the DEM, even though they are hydrologically significant features. Natural depressions in catchments are capable of trapping surface runoff and associated sediment, but they are difficult to identify and represent, especially in ungauged basins. We examined the errors associated with the removal of such depressions on predictions from hydrologic models, Soil and Water Assessment Tool (SWAT) and Agricultural Policy/Environmental eXtender (APEX). Automated water and sediment samplers were installed in the outlets of three natural depressions in a small catchment in the North Fork of Pheasant Branch watershed in Dane County, Wisconsin, to collect surface runoff and sediment yields for the period 2003-2004. The data showed that when daily precipitation is over 26 mm, surface runoff with suspended sediment overtops the depressions. SWAT and APEX were calibrated to this data to examine the influence of nested depressions on sediment yields. The hypothesis addressed in this study is: sediment transport parameters can be used as proxies for the functioning of surface depression and to obtain the correct sediment response. The alternative is to explicitly prescribe depressions as reservoirs with more geometric details of depressions if the hypothesis failed. Initial model results showed that the adjustment of sediment transport parameters mimics the response of the depressions and significantly reduces sediment yields. Implications of a simple proxy of sediment deposition for scaling to larger, ungauged basins will be discussed.

  9. Evaluation and development of hydrological parameterisations for the atmosphere, ocean and land surface coupled model developed by the UK Environmental Prediction (UKEP) Prototype project

    NASA Astrophysics Data System (ADS)

    Martinez-de la Torre, Alberto; Blyth, Eleanor; Ashton, Heather; Lewis, Huw

    2016-04-01

    The UKEP project brings together atmosphere, ocean and land surface models and scientist to build a coupled prediction system for the UK at 1.5 km scale. JULES (Joint UK Land-Environment Simulator) is the land surface model that generates runoff and simulates soil hydrology within the coupled prediction system. Here we present an evaluation of JULES performance at producing river flow for 13 selected catchments in Great Britain, where we use daily river flow observations at the catchment outlets. The evaluation is based on the Nush-Sutcliffe metric and bias. Results suggest that the inclusion of a new linear topographic slope dependency in the S0 parameter of the PDM (Probability Distributed Model, scheme that generates saturation excess runoff at the land surface when the soil water storage reaches S0), improves results for all catchments, constraining the surface runoff production for flatter catchments during rainy episodes. The new hydrological configuration developed offline using the JULES model has been implemented in the coupled prediction system for an intense winter storm case study. We found significant changes in accumulated runoff and total column soil moisture, and results consistent with the offline experiments with an increase in surface runoff on the high slopes of Scotland.

  10. Assessing Hydrological Extreme Events with Geospatial Data and Models

    NASA Astrophysics Data System (ADS)

    Vivoni, Enrique R.; Grimaldi, Salvatore; Nardi, Fernando; Ivanov, Valeriy Y.; Castelli, Fabio; Bras, Rafael L.; Ubertini, Lucio

    2004-09-01

    Prediction of river basin hydrological response to extreme meteorological events is a primary concern in areas with frequent flooding, landslides, and debris flows. Natural hydrogeological disasters in many regions lead to extensive property damage, impact on societal activities, and loss of life. Hydrologists have a long history of assessing and predicting hydrologic hazards through the combined use of field observations, monitoring networks, remote sensing, and numerical modeling. Nevertheless, the integration of field data and computer models has yet to result in prediction systems that capture space-time interactions between meteorological forcing, land surface characteristics, and the internal hydrological response in river basins. Capabilities for assessing hydrologic extreme events are greatly enhanced via the use of geospatial data sets describing watershed properties such as topography, channel structure, soils, vegetation, and geological features. Recent advances in managing, processing, and visualizing cartographic data with geographic information systems (GIS) have enabled their direct use in spatially distributed hydrological models. In a distributed model application, geospatial data sets can be used to establish the model domain, specify boundary and initial conditions, determine the spatial variation of parameter values, and provide the spatial model forcing. By representing a watershed through a set of discrete elements, distributed models simulate water, energy, and mass transport in a landscape and provide estimates of the spatial pattern of hydrologic states, fluxes, and pathways.

  11. Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

    PubMed Central

    Qin, Changbo; Jia, Yangwen; Su, Z.(Bob); Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

    2008-01-01

    This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems. PMID:27879946

  12. Assessment of Evolving TRMM-Based Real-Time Precipitation Estimation Methods and Their Impacts on Hydrologic Prediction in a High-Latitude Basin

    NASA Technical Reports Server (NTRS)

    Yong, Bin; Hong, Yang; Ren, Li-Liang; Gourley, Jonathan; Huffman, George J.; Chen, Xi; Wang, Wen; Khan, Sadiq I.

    2013-01-01

    The real-time availability of satellite-derived precipitation estimates provides hydrologists an opportunity to improve current hydrologic prediction capability for medium to large river basins. Due to the availability of new satellite data and upgrades to the precipitation algorithms, the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis real-time estimates (TMPA-RT) have been undergoing several important revisions over the past ten years. In this study, the changes of the relative accuracy and hydrologic potential of TMPA-RT estimates over its three major evolving periods were evaluated and inter-compared at daily, monthly and seasonal scales in the high-latitude Laohahe basin in China. Assessment results show that the performance of TMPA-RT in terms of precipitation estimation and streamflow simulation was significantly improved after 3 February 2005. Overestimation during winter months was noteworthy and consistent, which is suggested to be a consequence from interference of snow cover to the passive microwave retrievals. Rainfall estimated by the new version 6 of TMPA-RT starting from 1 October 2008 to present has higher correlations with independent gauge observations and tends to perform better in detecting rain compared to the prior periods, although it suffers larger mean error and relative bias. After a simple bias correction, this latest dataset of TMPA-RT exhibited the best capability in capturing hydrologic response among the three tested periods. In summary, this study demonstrated that there is an increasing potential in the use of TMPA-RT in hydrologic streamflow simulations over its three algorithm upgrade periods, but still with significant challenges during the winter snowing events.

  13. Time Changes of the European Gravity Field from GRACE: A Comparison with Ground Measurements from Superconducting Gravimeters and with Hydrology Model Predictions

    NASA Technical Reports Server (NTRS)

    Hinderer, J.; Lemoine, Frank G.; Crossley, D.; Boy, J.-P.

    2004-01-01

    We investigate the time-variable gravity changes in Europe retrieved from the initial GRACE monthly solutions spanning a 18 month duration from April 2002 to October 2003. Gravity anomaly maps are retrieved in Central Europe from the monthly satellite solutions we compare the fields according to various truncation levels (typically between degree 10 and 20) of the initial fields (expressed in spherical harmonics to degree 120). For these different degrees, an empirical orthogonal function (EOF) decomposition of the time-variable gravity field leads us to its main spatial and temporal characteristics. We show that the dominant signal is found to be annual with an amplitude and a phase both in agreement with predictions in Europe modeled using snow and soil-moisture variations from recent hydrology models. We compare these GRACE gravity field changes to surface gravity observations from 6 superconducting gravimeters of the GGP (Global Geodynamics Project) European sub-network, with a special attention to loading corrections. Initial results suggest that all 3 data sets (GRACE, hydrology and GGP) are responding to annual changes in near-surface water in Europe of a few microGal (at length scales of approx.1000 km) that show a high value in winter and a summer minimum. We also point out that the GRACE gravity field evolution seems to indicate that there is a trend in gravity between summer 2002 and summer 2003 which can be related to the 2003 heatwave in Europe and its hydrological consequences (drought). Despite the limited time span of our analysis and the uncertainties in retrieving a regional solution from the network of gravimeters, the calibration and validation aspects of the GRACE data processing based on the annual hydrology cycle in Europe are in progress.

  14. Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation.

    PubMed

    Qin, Changbo; Jia, Yangwen; Su, Z; Zhou, Zuhao; Qiu, Yaqin; Suhui, Shen

    2008-07-29

    This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km2. A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems.

  15. Classification of simulated and actual NOAA-6 AVHRR data for hydrologic land-surface feature definition. [Advanced Very High Resolution Radiometer

    NASA Technical Reports Server (NTRS)

    Ormsby, J. P.

    1982-01-01

    An examination of the possibilities of using Landsat data to simulate NOAA-6 Advanced Very High Resolution Radiometer (AVHRR) data on two channels, as well as using actual NOAA-6 imagery, for large-scale hydrological studies is presented. A running average was obtained of 18 consecutive pixels of 1 km resolution taken by the Landsat scanners were scaled up to 8-bit data and investigated for different gray levels. AVHRR data comprising five channels of 10-bit, band-interleaved information covering 10 deg latitude were analyzed and a suitable pixel grid was chosen for comparison with the Landsat data in a supervised classification format, an unsupervised mode, and with ground truth. Landcover delineation was explored by removing snow, water, and cloud features from the cluster analysis, and resulted in less than 10% difference. Low resolution large-scale data was determined useful for characterizing some landcover features if weekly and/or monthly updates are maintained.

  16. Urinary π-glutathione S-transferase Predicts Advanced Acute Kidney Injury Following Cardiovascular Surgery.

    PubMed

    Shu, Kai-Hsiang; Wang, Chih-Hsien; Wu, Che-Hsiung; Huang, Tao-Min; Wu, Pei-Chen; Lai, Chien-Heng; Tseng, Li-Jung; Tsai, Pi-Ru; Connolly, Rory; Wu, Vin-Cent

    2016-08-16

    Urinary biomarkers augment the diagnosis of acute kidney injury (AKI), with AKI after cardiovascular surgeries being a prototype of prognosis scenario. Glutathione S-transferases (GST) were evaluated as biomarkers of AKI. Urine samples were collected in 141 cardiovascular surgical patients and analyzed for urinary alpha-(α-) and pi-(π-) GSTs. The outcomes of advanced AKI (KDIGO stage 2, 3) and all-cause in-patient mortality, as composite outcome, were recorded. Areas under the receiver operator characteristic (ROC) curves and multivariate generalized additive model (GAM) were applied to predict outcomes. Thirty-eight (26.9%) patients had AKI, while 12 (8.5%) were with advanced AKI. Urinary π-GST differentiated patients with/without advanced AKI or composite outcome after surgery (p < 0.05 by generalized estimating equation). Urinary π-GST predicted advanced AKI at 3 hrs post-surgery (p = 0.033) and composite outcome (p = 0.009), while the corresponding ROC curve had AUC of 0.784 and 0.783. Using GAM, the cutoff value of 14.7 μg/L for π-GST showed the best performance to predict composite outcome. The addition of π-GST to the SOFA score improved risk stratification (total net reclassification index = 0.47). Thus, urinary π-GST levels predict advanced AKI or hospital mortality after cardiovascular surgery and improve in SOFA outcome assessment specific to AKI.

  17. Predicting the type, location and magnitude of geomorphic responses to dam removal: Role of hydrologic and geomorphic constraints

    NASA Astrophysics Data System (ADS)

    Gartner, John D.; Magilligan, Francis J.; Renshaw, Carl E.

    2015-12-01

    thousands of dams likely to be considered for removal or repair in the coming decades, this study helps to advance predictions of the geomorphic response to dam removal and contributes to a broader understanding of the variability in both style and timing of fluvial responses to disturbances.

  18. The hydrologic laboratory

    USGS Publications Warehouse

    Johnson, A.I.

    1963-01-01

    The knowledge of soil and rock testing, including the application of the test or analysis data to field problems, is still in its infancy. By learning more about the basic laws and principles of nature we can more accurately predict hydrologic phenomena of the future, as well as solve more efficiently the hydrologic problems of the present Our reservoir of fundamental facts and basic knowledge has been, and can be even more fully, increased by the analysis and research work of the Hydrologic Laboratory.

  19. Using hydrological data to assess the impact of a change to the parameterization of surface fluxes over water in a numerical weather prediction system

    NASA Astrophysics Data System (ADS)

    Fortin, V.; Deacu, D.; Klyszejko, E.; Vaillancourt, P. A.

    2012-12-01

    The Canadian Meteorological Center (CMC) uses the Global Environmental Multiscale (GEM) model in different configurations to provide numerical guidance for lead times of one day to two weeks, at horizontal scales varying from 2.5 km to 60 km depending on lead time. 48h forecasts are provided by its Regional Deterministic Prediction System (RDPS), which has a horizontal resolution of 15 km over North America. In June 2012, evaluation of a 10 km configuration of the RDPS was initiated at CMC. This configuration includes changes to the parameterization of surface fluxes over water, as it was diagnosed that heat fluxes over water are overestimated by the operational system, leading in particular to an overprediction of precipitation downstream of water bodies in unstable conditions during cold months. The same parameterization was also implemented in the MESH surface and hydrology model, in order to be able to perform offline sensitivity tests. Observations of streamflow and water levels in the Great Lakes watershed were used to identify the GEM model deficiency, and propose an improved parameterization. In addition to having the desired effect of reducing heat fluxes predicted by GEM, and thus precipitation, the changes have led to significant improvement to predictions of net basin supply for the Great Lakes obtained with the MESH hydrological modelling system. Average latent heat flux [W/m2] for winter 2011. Top left: 24h forecast from control run. Top right: 24h forecast from new prediction system. Bottom: verifying analysis (OAflux) Average sensible heat flux [W/m2] for winter 2011. Top left: 24h forecast from control run. Top right: 24h forecast from new prediction system. Bottom: verifying analysis (OAflux)

  20. Using discharge data to reduce structural deficits in a hydrological model with a Bayesian inference approach and the implications for the prediction of critical source areas

    NASA Astrophysics Data System (ADS)

    Frey, M. P.; Stamm, C.; Schneider, M. K.; Reichert, P.

    2011-12-01

    A distributed hydrological model was used to simulate the distribution of fast runoff formation as a proxy for critical source areas for herbicide pollution in a small agricultural catchment in Switzerland. We tested to what degree predictions based on prior knowledge without local measurements could be improved upon relying on observed discharge. This learning process consisted of five steps: For the prior prediction (step 1), knowledge of the model parameters was coarse and predictions were fairly uncertain. In the second step, discharge data were used to update the prior parameter distribution. Effects of uncertainty in input data and model structure were accounted for by an autoregressive error model. This step decreased the width of the marginal distributions of parameters describing the lower boundary (percolation rates) but hardly affected soil hydraulic parameters. Residual analysis (step 3) revealed model structure deficits. We modified the model, and in the subsequent Bayesian updating (step 4) the widths of the posterior marginal distributions were reduced for most parameters compared to those of the prior. This incremental procedure led to a strong reduction in the uncertainty of the spatial prediction. Thus, despite only using spatially integrated data (discharge), the spatially distributed effect of the improved model structure can be expected to improve the spatially distributed predictions also. The fifth step consisted of a test with independent spatial data on herbicide losses and revealed ambiguous results. The comparison depended critically on the ratio of event to preevent water that was discharged. This ratio cannot be estimated from hydrological data only. The results demonstrate that the value of local data is strongly dependent on a correct model structure. An iterative procedure of Bayesian updating, model testing, and model modification is suggested.

  1. Positive impact of the new 5-layer soil-hydrology scheme on seasonal prediction skill of 2-meter air temperatures over Europe

    NASA Astrophysics Data System (ADS)

    Bunzel, Felix; Müller, Wolfgang; Stacke, Tobias; Hagemann, Stefan; Dobrynin, Mikhail; Baehr, Johanna; Fröhlich, Kristina

    2016-04-01

    Recent studies show that the initialization of soil moisture has the potential to improve the skill of seasonal predictions with coupled climate models. Particularly, soil-moisture memory in the root zone is found to affect the predictability of surface state variables. However, in order to simulate the connection between root-zone soil-moisture and the near-surface atmospheric state realistically, the soil-hydrology scheme implemented in a coupled climate model requires a certain level of complexity. In this study, we first compare the quality of soil-moisture simulation in full-field assimilation experiments performed with the Max Planck Institute Earth System Model (MPI-ESM) in two different setups, one using the old bucket-type soil scheme and one using the new 5-layer soil-hydrology scheme. We find soil moisture to be more realistically simulated when MPI-ESM is used with the new 5-layer soil scheme. In a second step, from each of the two assimilation experiments a set of seasonal hindcast simulations is started. Each hindcast set consists of 10-member ensembles initialized on 1 May and 1 November each year within 1981-2012 with a hindcast length of 6 months each. We find the new 5-layer soil-hydrology scheme to improve the hindcast skill of both summer and winter 2-meter air temperatures over Europe compared to the old bucket-type soil scheme. In order to find possible sources for the improvement, land-atmosphere coupling is analyzed in the two hindcast sets, and a potential link to the atmospheric blocking frequency is investigated.

  2. Application of infinite model predictive control methodology to other advanced controllers.

    PubMed

    Abu-Ayyad, M; Dubay, R; Hernandez, J M

    2009-01-01

    This paper presents an application of most recent developed predictive control algorithm an infinite model predictive control (IMPC) to other advanced control schemes. The IMPC strategy was derived for systems with different degrees of nonlinearity on the process gain and time constant. Also, it was shown that IMPC structure uses nonlinear open-loop modeling which is conducted while closed-loop control is executed every sampling instant. The main objective of this work is to demonstrate that the methodology of IMPC can be applied to other advanced control strategies making the methodology generic. The IMPC strategy was implemented on several advanced controllers such as PI controller using Smith-Predictor, Dahlin controller, simplified predictive control (SPC), dynamic matrix control (DMC), and shifted dynamic matrix (m-DMC). Experimental work using these approaches combined with IMPC was conducted on both single-input-single-output (SISO) and multi-input-multi-output (MIMO) systems and compared with the original forms of these advanced controllers. Computer simulations were performed on nonlinear plants demonstrating that the IMPC strategy can be readily implemented on other advanced control schemes providing improved control performance. Practical work included real-time control applications on a DC motor, plastic injection molding machine and a MIMO three zone thermal system.

  3. Data Mining and Predictive Modeling in Institutional Advancement: How Ten Schools Found Success. Technical Report

    ERIC Educational Resources Information Center

    Luperchio, Dan

    2009-01-01

    This technical report, produced in partnership by the Council for Advancement and Support of Education (CASE) and SPSS Inc., explores the promise of data mining alumni records at educational institutions. Working with individual alumni records from The Johns Hopkins Zanvyl Krieger School of Arts and Sciences, a predictive regression model is…

  4. The development of a sub-daily gridded rainfall product to improve hydrological predictions in Great Britain

    NASA Astrophysics Data System (ADS)

    Quinn, Niall; Freer, Jim; Coxon, Gemma; O'Loughlin, Fiachra; Woods, Ross; Liguori, Sara

    2015-04-01

    In Great Britain and many other regions of the world, flooding resulting from short duration, high intensity rainfall events can lead to significant economic losses and fatalities. At present, such extreme events are often poorly evaluated using hydrological models due, in part, to their rarity and relatively short duration and a lack of appropriate data. Such storm characteristics are not well represented by daily rainfall records currently available using volumetric gauges and/or derived gridded products. This research aims to address this important data gap by developing a sub-daily gridded precipitation product for Great Britain. Our focus is to better understand these storm events and some of the challenges and uncertainties in quantifying such data across catchment scales. Our goal is to both improve such rainfall characterisation and derive an input to drive hydrological model simulations. Our methodology involves the collation, error checking, and spatial interpolation of approximately 2000 rain gauges located across Great Britain, provided by the Scottish Environment Protection Agency (SEPA) and the Environment Agency (EA). Error checking was conducted over the entirety of the TBR data available, utilising a two stage approach. First, rain gauge data at each site were examined independently, with data exceeding reasonable thresholds marked as suspect. Second, potentially erroneous data were marked using a neighbourhood analysis approach whereby measurements at a given gauge were deemed suspect if they did not fall within defined bounds of measurements at neighbouring gauges. A total of eight error checks were conducted. To provide the user with the greatest flexibility possible, the error markers associated with each check have been recorded at every site. This approach aims to enable the user to choose which checks they deem most suitable for a particular application. The quality assured TBR dataset was then spatially interpolated to produce a national

  5. Genomic Prediction of Seed Quality Traits Using Advanced Barley Breeding Lines

    PubMed Central

    Nielsen, Nanna Hellum; Jahoor, Ahmed; Jensen, Jens Due; Orabi, Jihad; Cericola, Fabio; Edriss, Vahid; Jensen, Just

    2016-01-01

    Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines) are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families. PMID:27783639

  6. Efficient Use of Prior Information to Calibrate the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) Hydrology Model

    DTIC Science & Technology

    2014-09-01

    Gridded Surface Subsurface Hydrologic Analysis (GSSHA) Hydrology Model by Brian E. Skahill and Charles W. Downer PURPOSE: The purpose of this... Hydrologic Analysis (GSSHA) model. These new capabilities enable the incorporation of soft data, or prior information (i.e., extra observations which...traditional hydrologic simulation models (viz., lumped and semidistributed model structures). Such models have the potential to predict with greater

  7. Intermediate-term prediction in advance of the Loma Prieta earthquake

    SciTech Connect

    Keilis-Borok, V.I.; Kossobokov, V.; Rotvain, I. ); Knopoff, L. )

    1990-08-01

    The Loma Prieta earthquake of October 17, 1989 was predicted by the use of two pattern recognition algorithms, CN and M8. The prediction with algorithm CN was that an earthquake with magnitude greater than or equal to 6.4 was expected to occur in a roughly four year interval staring in midsummer 1986 in a polygonal spatial window of approximate average dimensions 600 {times} 450 km, encompassing Northern California and Northern Nevada. The prediction with algorithm M8 was that an earthquake with magnitude greater than or equal to 7.0 was expected to occur within 5 to 7 years after 1985, in a spatial window of approximate average dimensions 800 {times} 560 km. The predictions were communicated in advance of the earthquake. In previous, mainly retrospective applications of these algorithms, successful predictions occurred in about 80% of the cases.

  8. Recent Advances in Quantifying Hydrological Processes Linking Water, Carbon, and Energy Exports into Coastal Margins Along the Arctic Land-Sea Boundary

    NASA Astrophysics Data System (ADS)

    Rawlins, M. A.

    2014-12-01

    The high northern latitudes have experienced rapid warming in recent decades with projections of larger increases likely by the end of this century. Warming permafrost and an acceleration of the arctic freshwater cycle are among the myriad interconnected changes taking place that have the potential to impact ecosystems throughout the pan-Arctic. The Arctic Ocean receives a disproportionately large amount of global freshwater runoff and as such near-shore coastal margins along the arctic land-sea boundary are strongly influenced by riverine freshwater discharge. Alterations in hydrological flows driven by a changing climate and other perturbations, therefore, are likely to impact the biology and biogeochemistry of arctic coastal margins. Advances have been made in the quantification of water, carbon, and materials transports with recent studies documenting significant changes in exports of quantities such as dissolved organic carbon from large rivers, linked in turn to changes in landscape characteristics and hydrological flow rates. Here key measured data sets, derived empirical relationships, and the resulting pan-Arctic estimates for several constituents are described for the major arctic rivers and full pan-Arctic basin. Complementary estimates from a process-based model are presented, illustrating the potential for leveraging measured data to derive more accurate flows at basin and continental scales. A series of retrospective model simulations point to an increasing influence of river-borne heat transport on ice melt in coastal margins. Case studies of large freshwater anomalies provide a framework for understanding connections between river discharge and the biology and biogeochemistry of arctic coastal margins.

  9. Accurate and efficient prediction of fine-resolution hydrologic and carbon dynamic simulations from coarse-resolution models

    NASA Astrophysics Data System (ADS)

    Pau, George Shu Heng; Shen, Chaopeng; Riley, William J.; Liu, Yaning

    2016-02-01

    The topography, and the biotic and abiotic parameters are typically upscaled to make watershed-scale hydrologic-biogeochemical models computationally tractable. However, upscaling procedure can produce biases when nonlinear interactions between different processes are not fully captured at coarse resolutions. Here we applied the Proper Orthogonal Decomposition Mapping Method (PODMM) to downscale the field solutions from a coarse (7 km) resolution grid to a fine (220 m) resolution grid. PODMM trains a reduced-order model (ROM) with coarse-resolution and fine-resolution solutions, here obtained using PAWS+CLM, a quasi-3-D watershed processes model that has been validated for many temperate watersheds. Subsequent fine-resolution solutions were approximated based only on coarse-resolution solutions and the ROM. The approximation errors were efficiently quantified using an error estimator. By jointly estimating correlated variables and temporally varying the ROM parameters, we further reduced the approximation errors by up to 20%. We also improved the method's robustness by constructing multiple ROMs using different set of variables, and selecting the best approximation based on the error estimator. The ROMs produced accurate downscaling of soil moisture, latent heat flux, and net primary production with O(1000) reduction in computational cost. The subgrid distributions were also nearly indistinguishable from the ones obtained using the fine-resolution model. Compared to coarse-resolution solutions, biases in upscaled ROM solutions were reduced by up to 80%. This method has the potential to help address the long-standing spatial scaling problem in hydrology and enable long-time integration, parameter estimation, and stochastic uncertainty analysis while accurately representing the heterogeneities.

  10. Formability Prediction of Advanced High Strength Steel with a New Ductile Fracture Criterion

    NASA Astrophysics Data System (ADS)

    Lou, Yanshan; Lim, Sungjun; Huh, Jeehyang; Huh, Hoon

    2011-08-01

    A ductile fracture criterion is newly proposed to accurately predict forming limit diagrams (FLD) of sheet metals. The new ductile fracture criterion is based on the effect of the non-dimensional stress triaxiality, the stress concentration factor and the effective plastic strain on the nucleation, growth and coalescence of voids. The new ductile fracture criterion has been applied to estimate the formability of four kind advanced high strength steels (AHSS): DP780, DP980, TRIP590, and TWIP980. FLDs predicted are compared with experimental results and those predicted by other ductile fracture criteria. The comparison demonstrates that FLDs predicted by the new ductile fracture criterion are in better agreement with experimental FLDs than those predicted by other ductile fracture criteria. The better agreement of FLDs predicted by the new ductile fracture criterion is because conventional ductile fracture criteria were proposed for fracture prediction in bulk metal forming while the new one is proposed to predict the onset of fracture in sheet metal forming processes.

  11. Development of advanced structural analysis methodologies for predicting widespread fatigue damage in aircraft structures

    NASA Technical Reports Server (NTRS)

    Harris, Charles E.; Starnes, James H., Jr.; Newman, James C., Jr.

    1995-01-01

    NASA is developing a 'tool box' that includes a number of advanced structural analysis computer codes which, taken together, represent the comprehensive fracture mechanics capability required to predict the onset of widespread fatigue damage. These structural analysis tools have complementary and specialized capabilities ranging from a finite-element-based stress-analysis code for two- and three-dimensional built-up structures with cracks to a fatigue and fracture analysis code that uses stress-intensity factors and material-property data found in 'look-up' tables or from equations. NASA is conducting critical experiments necessary to verify the predictive capabilities of the codes, and these tests represent a first step in the technology-validation and industry-acceptance processes. NASA has established cooperative programs with aircraft manufacturers to facilitate the comprehensive transfer of this technology by making these advanced structural analysis codes available to industry.

  12. Using the Storm Water Management Model to predict urban headwater stream hydrological response to climate and land cover change

    NASA Astrophysics Data System (ADS)

    Wu, J. Y.; Thompson, J. R.; Kolka, R. K.; Franz, K. J.; Stewart, T. W.

    2013-06-01

    Streams are natural features in urban landscapes that can provide ecosystem services for urban residents. However, urban streams are under increasing pressure caused by multiple anthropogenic impacts, including increases in human population and associated impervious surface area, and accelerated climate change. The ability to anticipate these changes and better understand their effects on streams is important for developing and implementing strategies to mitigate potentially negative effects. In this study, stream flow was monitored during April-November (2011 and 2012), and the data were used to apply the Storm Water Management Model (SWMM) for five urban watersheds in central Iowa, USA representing a gradient of percent impervious surface (IS, ranging from 5.3 to 37.1%). A set of three scenarios was designed to quantify hydrological responses to independent and combined effects of climate change (18% increase in precipitation), and land cover change (absolute increases between 5.2 and 17.1%, based on separate projections of impervious surfaces for the five watersheds) for the year 2040 compared to a current condition simulation. An additional set of three scenarios examined stream response to different distributions of land cover change within a single watershed. Hydrological responses were quantified using three indices: unit-area peak discharge, flashiness (R-B Index), and runoff ratio. Stream hydrology was strongly affected by watershed percent IS. For the current condition simulation, values for all three indices were five to seven times greater in the most developed watershed compared to the least developed watershed. The climate change scenario caused a 20.8% increase in unit-area peak discharge on average across the five watersheds compared to the current condition simulation. The land cover change scenario resulted in large increases for all three indices: 49.5% for unit-area peak discharge, 39.3% for R-B Index, and 73.9% for runoff ratio, on average, for

  13. Using the Storm Water Management Model to predict urban headwater stream hydrological response to climate and land cover change

    NASA Astrophysics Data System (ADS)

    Wu, J. Y.; Thompson, J. R.; Kolka, R. K.; Franz, K. J.; Stewart, T. W.

    2013-12-01

    Streams are natural features in urban landscapes that can provide ecosystem services for urban residents. However, urban streams are under increasing pressure caused by multiple anthropogenic impacts, including increases in human population and associated impervious surface area, and accelerated climate change. The ability to anticipate these changes and better understand their effects on streams is important for developing and implementing strategies to mitigate potentially negative effects. In this study, stream flow was monitored during April-November (2011 and 2012), and the data were used to apply the Storm Water Management Model (SWMM) for five urban watersheds in central Iowa, USA, representing a gradient of percent impervious surface (IS, ranging from 5.3 to 37.1%). A set of three scenarios was designed to quantify hydrological responses to independent and combined effects of climate change (18% increase in precipitation), and land cover change (absolute increases between 5.2 and 17.1%, based on separate projections of impervious surfaces for the five watersheds) for the year 2040 compared to a current condition simulation. An additional set of three scenarios examined stream response to different distributions of land cover change within a single watershed. Hydrological responses were quantified using three indices: unit-area peak discharge, flashiness (R-B Index; Richards-Baker Index), and runoff ratio. Stream hydrology was strongly affected by watershed percent IS. For the current condition simulation, values for all three indices were five to seven times greater in the most developed watershed compared to the least developed watershed. The climate change scenario caused a 20.8% increase in unit-area peak discharge on average across the five watersheds compared to the current condition simulation. The land cover change scenario resulted in large increases for all three indices: 49.5% for unit-area peak discharge, 39.3% for R-B Index, and 73.9% for runoff

  14. Improved NASA-ANOPP Noise Prediction Computer Code for Advanced Subsonic Propulsion Systems

    NASA Technical Reports Server (NTRS)

    Kontos, K. B.; Janardan, B. A.; Gliebe, P. R.

    1996-01-01

    Recent experience using ANOPP to predict turbofan engine flyover noise suggests that it over-predicts overall EPNL by a significant amount. An improvement in this prediction method is desired for system optimization and assessment studies of advanced UHB engines. An assessment of the ANOPP fan inlet, fan exhaust, jet, combustor, and turbine noise prediction methods is made using static engine component noise data from the CF6-8OC2, E(3), and QCSEE turbofan engines. It is shown that the ANOPP prediction results are generally higher than the measured GE data, and that the inlet noise prediction method (Heidmann method) is the most significant source of this overprediction. Fan noise spectral comparisons show that improvements to the fan tone, broadband, and combination tone noise models are required to yield results that more closely simulate the GE data. Suggested changes that yield improved fan noise predictions but preserve the Heidmann model structure are identified and described. These changes are based on the sets of engine data mentioned, as well as some CFM56 engine data that was used to expand the combination tone noise database. It should be noted that the recommended changes are based on an analysis of engines that are limited to single stage fans with design tip relative Mach numbers greater than one.

  15. Climate sensitivity runs and regional hydrologic modeling for predicting the response of the greater Florida Everglades ecosystem to climate change.

    PubMed

    Obeysekera, Jayantha; Barnes, Jenifer; Nungesser, Martha

    2015-04-01

    It is important to understand the vulnerability of the water management system in south Florida and to determine the resilience and robustness of greater Everglades restoration plans under future climate change. The current climate models, at both global and regional scales, are not ready to deliver specific climatic datasets for water resources investigations involving future plans and therefore a scenario based approach was adopted for this first study in restoration planning. We focused on the general implications of potential changes in future temperature and associated changes in evapotranspiration, precipitation, and sea levels at the regional boundary. From these, we developed a set of six climate and sea level scenarios, used them to simulate the hydrologic response of the greater Everglades region including agricultural, urban, and natural areas, and compared the results to those from a base run of current conditions. The scenarios included a 1.5 °C increase in temperature, ±10 % change in precipitation, and a 0.46 m (1.5 feet) increase in sea level for the 50-year planning horizon. The results suggested that, depending on the rainfall and temperature scenario, there would be significant changes in water budgets, ecosystem performance, and in water supply demands met. The increased sea level scenarios also show that the ground water levels would increase significantly with associated implications for flood protection in the urbanized areas of southeastern Florida.

  16. Advanced Numerical Prediction and Modeling of Tropical Cyclones Using WRF-NMM modeling system

    NASA Astrophysics Data System (ADS)

    Gopalakrishnan, S. G.; Rogers, R. F.; Marks, F. D.; Atlas, R.

    2007-12-01

    Dramatic improvement in tropical cyclone track forecasts have occurred through advancements in high quality observations, high speed computers and improvements in dynamical models. Similar advancements now need to be made for tropical cyclone intensity, structure and rainfall prediction. The Weather Research Forecasting Model (WRF) is a general purpose, multi-institutional mesoscale modeling system. A version of the WRF model called the HWRF/WRF-NMM modeling system, developed at the National Center for Environmental Protection (NCEP) was recently adopted for hurricane forecasting (Gopalakrishnan et al, 2006) by the National Hurricane Center (NHC). At the Hurricane Research Division (HRD/AOML/OAR) we are developing and further advancing a research version of this modeling system. This work is done in collaboration with the Developmental Test bed Center (DTC), Boulder, CO, Global Systems division (GSD/ESRL/OAR), Boulder, CO, The Air Resources Laboratory (ARL/OAR), Washington, D.C., the U.S. university community, the Indian Institute of Technology, IIT.Delhi, India, and the India Meteorological Department, New Delhi, India Our modeling effort includes advancing the WRF system for Ensemble Hurricane Forecasting, advancing our understanding of Ensemble-vs- High Resolution Forecasting of Hurricanes, advancing WRF/WRF-NMM with better analysis techniques (e.g. Four Dimensional Data Assimilation) for improving forecasts and above all, advancing our understanding of hurricane processes using a high resolution numerical modeling approach. Examples of some of these applications will be shown here. Reference: NCEP's Two-way-Interactive-Moving-Nest NMM-WRF modeling system for Hurricane Forecasting, S.G. Gopalakrishnan, N. Surgi, R. Tuleya, and Z. Janjic 27th Conference on Hurricanes and Tropical Meteorology, 24- 28 April 2006, Monterey, California.

  17. Hydrologic impacts of thawing permafrost—A review

    USGS Publications Warehouse

    Walvoord, Michelle Ann; Kurylyk, Barret L.

    2016-01-01

    Where present, permafrost exerts a primary control on water fluxes, flowpaths, and distribution. Climate warming and related drivers of soil thermal change are expected to modify the distribution of permafrost, leading to changing hydrologic conditions, including alterations in soil moisture, connectivity of inland waters, streamflow seasonality, and the partitioning of water stored above and below ground. The field of permafrost hydrology is undergoing rapid advancement with respect to multiscale observations, subsurface characterization, modeling, and integration with other disciplines. However, gaining predictive capability of the many interrelated consequences of climate change is a persistent challenge due to several factors. Observations of hydrologic change have been causally linked to permafrost thaw, but applications of process-based models needed to support and enhance the transferability of empirical linkages have often been restricted to generalized representations. Limitations stem from inadequate baseline permafrost and unfrozen hydrogeologic characterization, lack of historical data, and simplifications in structure and process representation needed to counter the high computational demands of cryohydrogeologic simulations. Further, due in part to the large degree of subsurface heterogeneity of permafrost landscapes and the nonuniformity in thaw patterns and rates, associations between various modes of permafrost thaw and hydrologic change are not readily scalable; even trajectories of change can differ. This review highlights promising advances in characterization and modeling of permafrost regions and presents ongoing research challenges toward projecting hydrologic and ecologic consequences of permafrost thaw at time and spatial scales that are useful to managers and researchers.

  18. Unsteady blade-surface pressures on a large-scale advanced propeller: Prediction and data

    NASA Technical Reports Server (NTRS)

    Nallasamy, M.; Groeneweg, J. F.

    1990-01-01

    An unsteady 3-D Euler analysis technique is employed to compute the flow field of an advanced propeller operating at an angle of attack. The predicted blade pressure waveforms are compared with wind tunnel data at two Mach numbers, 0.5 and 0.2. The inflow angle is three degrees. For an inflow Mach number of 0.5, the predicted pressure response is in fair agreement with data: the predicted phases of the waveforms are in close agreement with data while the magnitudes are underpredicted. At the low Mach number of 0.2 (takeoff), the numerical solution shows the formation of a leading edge vortex which is in qualitative agreement with measurements. However, the highly nonlinear pressure response measured on the blade suction surface is not captured in the present inviscid analysis.

  19. Unsteady blade surface pressures on a large-scale advanced propeller - Prediction and data

    NASA Technical Reports Server (NTRS)

    Nallasamy, M.; Groeneweg, J. F.

    1990-01-01

    An unsteady three dimensional Euler analysis technique is employed to compute the flowfield of an advanced propeller operating at an angle of attack. The predicted blade pressure waveforms are compared with wind tunnel data at two Mach numbers, 0.5 and 0.2. The inflow angle is three degrees. For an inflow Mach number of 0.5, the predicted pressure response is in fair agreement with data: the predicted phases of the waveforms are in close agreement with data while the magnitudes are underpredicted. At the low Mach number of 0.2 (take-off) the numerical solution shows the formation of a leading edge vortex which is in qualitative agreement with measurements. However, the highly nonlinear pressure response measured on the blade suction surface is not captured in the present inviscid analysis.

  20. Long-lead station-scale prediction of hydrological droughts in South Korea based on bivariate pattern-based downscaling

    NASA Astrophysics Data System (ADS)

    Sohn, Soo-Jin; Tam, Chi-Yung

    2016-05-01

    Capturing climatic variations in boreal winter to spring (December-May) is essential for properly predicting droughts in South Korea. This study investigates the variability and predictability of the South Korean climate during this extended season, based on observations from 60 station locations and multi-model ensemble (MME) hindcast experiments (1983/1984-2005/2006) archived at the APEC Climate Center (APCC). Multivariate empirical orthogonal function (EOF) analysis results based on observations show that the first two leading modes of winter-to-spring precipitation and temperature variability, which together account for ~80 % of the total variance, are characterized by regional-scale anomalies covering the whole South Korean territory. These modes were also closely related to some of the recurrent large-scale circulation changes in the northern hemisphere during the same season. Consistent with the above, examination of the standardized precipitation evapotranspiration index (SPEI) indicates that drought conditions in South Korea tend to be accompanied by regional-to-continental-scale circulation anomalies over East Asia to the western north Pacific. Motivated by the aforementioned findings on the spatial-temporal coherence among station-scale precipitation and temperature anomalies, a new bivariate and pattern-based downscaling method was developed. The novelty of this method is that precipitation and temperature data were first filtered using multivariate EOFs to enhance their spatial-temporal coherence, before being linked to large-scale circulation variables using canonical correlation analysis (CCA). To test its applicability and to investigate its related potential predictability, a perfect empirical model was first constructed with observed datasets as predictors. Next, a model output statistics (MOS)-type hybrid dynamical-statistical model was developed, using products from nine one-tier climate models as inputs. It was found that, with model sea

  1. Assessing the impact of land use change on hydrology by ensemble modelling (LUCHEM) II: Ensemble combinations and predictions

    USGS Publications Warehouse

    Viney, N.R.; Bormann, H.; Breuer, L.; Bronstert, A.; Croke, B.F.W.; Frede, H.; Graff, T.; Hubrechts, L.; Huisman, J.A.; Jakeman, A.J.; Kite, G.W.; Lanini, J.; Leavesley, G.; Lettenmaier, D.P.; Lindstrom, G.; Seibert, J.; Sivapalan, M.; Willems, P.

    2009-01-01

    This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9-year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles, in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in

  2. Assessment of potential for small hydro/solar power integration in a mountainous, data sparse region: the role of hydrological prediction accuracy

    NASA Astrophysics Data System (ADS)

    Borga, Marco; Francois, Baptiste; Creutin, Jean-Dominique; Hingray, Benoit; Zoccatelli, Davide; Tardivo, Gianmarco

    2015-04-01

    In many parts of the world, integration of small hydropower and solar/wind energy sources along river systems is examined as a way to meet pressing renewable energy targets. Depending on the space and time scales considered, hydrometeorological variability may synchronize or desynchronize solar/wind, runoff and the demand opening the possibility to use their complementarity to smooth the intermittency of each individual energy source. Rivers also provide important ecosystem services, including the provision of high quality downstream water supply and the maintenance of in-stream habitats. With future supply and demand of water resources both impacted by environmental change, a good understanding of the potential for the integration among hydropower and solar/wind energy sources in often sparsely gauged catchments is important. In such cases, where complex data-demanding models may be inappropriate, there is a need for simple conceptual modelling approaches that can still capture the main features of runoff generation and artificial regulation processes. In this work we focus on run-of-the-river and solar-power interaction assessment. In order to catch the three key cycles of the load fluctuation - daily, weekly and seasonal, the time step used in the study is the hourly resolution. We examine the performance of a conceptual hydrological model which includes facilities to model dam regulation and diversions and hydrological modules to account for the effect of glaciarised catchments. The model is applied to catchments of the heavily regulated Upper Adige river system (6900 km2), Eastern Italian Alps, which has a long history of hydropower generation. The model is used to characterize and predict the natural flow regime, assess the regulation impacts, and simulate co-fluctuations between run-of- the-river and solar power. The results demonstrates that the simple, conceptual modelling approach developed here can capture the main hydrological and regulation processes

  3. Solid phase evolution in the Biosphere 2 hillslope experiment as predicted by modeling of hydrologic and geochemical fluxes

    SciTech Connect

    Dontsova, K.; Steefel, C.I.; Desilets, S.; Thompson, A.; Chorover, J.

    2009-07-15

    A reactive transport geochemical modeling study was conducted to help predict the mineral transformations occurring over a ten year time-scale that are expected to impact soil hydraulic properties in the Biosphere 2 (B2) synthetic hillslope experiment. The modeling sought to predict the rate and extent of weathering of a granular basalt (selected for hillslope construction) as a function of climatic drivers, and to assess the feedback effects of such weathering processes on the hydraulic properties of the hillslope. Flow vectors were imported from HYDRUS into a reactive transport code, CrunchFlow2007, which was then used to model mineral weathering coupled to reactive solute transport. Associated particle size evolution was translated into changes in saturated hydraulic conductivity using Rosetta software. We found that flow characteristics, including velocity and saturation, strongly influenced the predicted extent of incongruent mineral weathering and neo-phase precipitation on the hillslope. Results were also highly sensitive to specific surface areas of the soil media, consistent with surface reaction controls on dissolution. Effects of fluid flow on weathering resulted in significant differences in the prediction of soil particle size distributions, which should feedback to alter hillslope hydraulic conductivities.

  4. Comparison of two imaging programs in predicting the soft tissue changes with mandibular advancement surgery.

    PubMed

    Ravindranath, Sneha; Krishnaswamy, Nathamuni Rengarajan; Sundaram, Venkateswaran

    2011-01-01

    Establishing common objectives and expectations concerning the outcome of proposed surgical orthodontic therapy is a crucial part of the treatment planning process, which has been greatly simplified by imaging software. The purpose of this study was to investigate the reliability of two surgical imaging programs--Dolphin Imaging 10 and Vistadent OC--in simulating the actual outcome of mandibular advancement surgery by using a visual analog scale (VAS) judged by a panel of orthodontists, oral surgeons, and laypersons. The predictions were also analyzed with soft tissue cephalometric evaluation. The results of the study showed that in predicting the surgical outcome evaluated by the VAS, both programs received a mean rating of fair. One was marginally superior for the overall assessment among all three panelist groups. Region-wise, rating indicated the lower lip region to be the least accurate, and the submental region received the highest scores. The soft tissue cephalometric parameters showed minimal differences except for the lower lip parameters. Thus, Dolphin Imaging 10 and Vistadent OC are reliable in predicting mandibular advancement surgical outcomes with inaccuracies chiefly in the lower lip region.

  5. Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

    NASA Technical Reports Server (NTRS)

    Wilson, Scott D.; Reid, Terry V.; Schifer, Nicholas A.; Briggs, Maxwell H.

    2012-01-01

    The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two high-efficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical power output for a given net heat input. Microporous bulk insulation is used in the ground support test hardware to minimize the loss of thermal energy from the electric heat source to the environment. The insulation package is characterized before operation to predict how much heat will be absorbed by the convertor and how much will be lost to the environment during operation. In an effort to validate these predictions, numerous tasks have been performed, which provided a more accurate value for net heat input into the ASCs. This test and modeling effort included: (a) making thermophysical property measurements of test setup materials to provide inputs to the numerical models, (b) acquiring additional test data that was collected during convertor tests to provide numerical models with temperature profiles of the test setup via thermocouple and infrared measurements, (c) using multidimensional numerical models (computational fluid dynamics code) to predict net heat input of an operating convertor, and (d) using validation test hardware to provide direct comparison of numerical results and validate the multidimensional numerical models used to predict convertor net heat input. This effort produced high fidelity ASC net heat input predictions, which were successfully validated using

  6. Hillslope hydrology and stability

    USGS Publications Warehouse

    Lu, Ning; Godt, Jonathan

    2012-01-01

    Landslides are caused by a failure of the mechanical balance within hillslopes. This balance is governed by two coupled physical processes: hydrological or subsurface flow and stress. The stabilizing strength of hillslope materials depends on effective stress, which is diminished by rainfall. This book presents a cutting-edge quantitative approach to understanding hydro-mechanical processes across variably saturated hillslope environments and to the study and prediction of rainfall-induced landslides. Topics covered include historic synthesis of hillslope geomorphology and hydrology, total and effective stress distributions, critical reviews of shear strength of hillslope materials and different bases for stability analysis. Exercises and homework problems are provided for students to engage with the theory in practice. This is an invaluable resource for graduate students and researchers in hydrology, geomorphology, engineering geology, geotechnical engineering and geomechanics and for professionals in the fields of civil and environmental engineering and natural hazard analysis.

  7. Using prediction uncertainty analysis to design hydrologic monitoring networks: Example applications from the Great Lakes water availability pilot project

    USGS Publications Warehouse

    Fienen, Michael N.; Doherty, John E.; Hunt, Randall J.; Reeves, Howard W.

    2010-01-01

    The importance of monitoring networks for resource-management decisions is becoming more recognized, in both theory and application. Quantitative computer models provide a science-based framework to evaluate the efficacy and efficiency of existing and possible future monitoring networks. In the study described herein, two suites of tools were used to evaluate the worth of new data for specific predictions, which in turn can support efficient use of resources needed to construct a monitoring network. The approach evaluates the uncertainty of a model prediction and, by using linear propagation of uncertainty, estimates how much uncertainty could be reduced if the model were calibrated with addition information (increased a priori knowledge of parameter values or new observations). The theoretical underpinnings of the two suites of tools addressing this technique are compared, and their application to a hypothetical model based on a local model inset into the Great Lakes Water Availability Pilot model are described. Results show that meaningful guidance for monitoring network design can be obtained by using the methods explored. The validity of this guidance depends substantially on the parameterization as well; hence, parameterization must be considered not only when designing the parameter-estimation paradigm but also-importantly-when designing the prediction-uncertainty paradigm.

  8. Plasma mRNA as liquid biopsy predicts chemo-sensitivity in advanced gastric cancer patients.

    PubMed

    Shen, Jie; Kong, Weiwei; Wu, Yuanna; Ren, Haozhen; Wei, Jia; Yang, Yang; Yang, Yan; Yu, Lixia; Guan, Wenxian; Liu, Baorui

    2017-01-01

    Predictive biomarkers based individualized chemotherapy can improve efficacy. However, for those advanced patients, it may be impossible to obtain the tissues from operation. Tissues from biopsy may not be always enough for gene detection. Thus, biomarker from blood could be a non-invasive and useful tool to provide real-time information in the procedure of treatment. To further understand the role of plasma mRNA in chemo-efficiency prediction, several mRNA expression levels were assessed in plasma and paired tumor tissues from 133 locally advanced gastric cancer patients (stage III), and mRNA levels were correlated with chemosensitivity to docetaxel, pemetrexed, platinum, and irinotecan. mRNA expression level in 64 advanced gastric cancer patients (stage IV) was also examined (55 in test group, and 9 in control), and chemotherapy in the test group were given according to the plasma gene detection. As a result, in the 133 patients with locally advanced gastric cancer (Stage III), correlations were observed between the mRNA expression of plasma/tumor BRCA1 levels and docetaxel sensitivity (P<0.001), plasma/tumor TS and pemetrexed sensitivity (P<0.001), plasma/tumor BRCA1 and platinum sensitivity (plasma, P=0.016; tumor, P<0.001), and plasma/tumor TOPO1 and irinotecan sensitivity (plasma, P=0.015; tumor, P=0.011). Among another 64 patients with advanced cancer (Stage IV), the median OS of test group was 15.5m (95% CI=10.1 to 20.9m), the PFS was 9.1m (95% CI=8.0 to 10.2m), which were significant longer than the control (P=0.047 for OS, P=0.038 for PFS). The mortality risk was higher in the control than patients treated according to the plasma gene detection (HR in the control=2.34, 95% CI=0.93 to 5.88, P=0.071). Plasma mRNA as liquid biopsy could be ideal recourse for examination to predict chemo-sensitivity in gastric cancer.

  9. Plasma mRNA as liquid biopsy predicts chemo-sensitivity in advanced gastric cancer patients

    PubMed Central

    Shen, Jie; Kong, Weiwei; Wu, Yuanna; Ren, Haozhen; Wei, Jia; Yang, Yang; Yang, Yan; Yu, Lixia; Guan, Wenxian; Liu, Baorui

    2017-01-01

    Predictive biomarkers based individualized chemotherapy can improve efficacy. However, for those advanced patients, it may be impossible to obtain the tissues from operation. Tissues from biopsy may not be always enough for gene detection. Thus, biomarker from blood could be a non-invasive and useful tool to provide real-time information in the procedure of treatment. To further understand the role of plasma mRNA in chemo-efficiency prediction, several mRNA expression levels were assessed in plasma and paired tumor tissues from 133 locally advanced gastric cancer patients (stage III), and mRNA levels were correlated with chemosensitivity to docetaxel, pemetrexed, platinum, and irinotecan. mRNA expression level in 64 advanced gastric cancer patients (stage IV) was also examined (55 in test group, and 9 in control), and chemotherapy in the test group were given according to the plasma gene detection. As a result, in the 133 patients with locally advanced gastric cancer (Stage III), correlations were observed between the mRNA expression of plasma/tumor BRCA1 levels and docetaxel sensitivity (P<0.001), plasma/tumor TS and pemetrexed sensitivity (P<0.001), plasma/tumor BRCA1 and platinum sensitivity (plasma, P=0.016; tumor, P<0.001), and plasma/tumor TOPO1 and irinotecan sensitivity (plasma, P=0.015; tumor, P=0.011). Among another 64 patients with advanced cancer (Stage IV), the median OS of test group was 15.5m (95% CI=10.1 to 20.9m), the PFS was 9.1m (95% CI=8.0 to 10.2m), which were significant longer than the control (P=0.047 for OS, P=0.038 for PFS). The mortality risk was higher in the control than patients treated according to the plasma gene detection (HR in the control=2.34, 95% CI=0.93 to 5.88, P=0.071). Plasma mRNA as liquid biopsy could be ideal recourse for examination to predict chemo-sensitivity in gastric cancer.

  10. Development of a constitutive model for creep and life prediction of advanced silicon nitride ceramics

    SciTech Connect

    Ding, J.L.; Liu, K.C.; Brinkman, C.R.

    1992-12-31

    A constitutive model capable of describing deformation and predicting rupture life was developed for high temperature ceramic materials under general thermal-mechanical loading conditions. The model was developed based on the deformation and fracture behavior observed from a systematic experimental study on an advanced silicon nitride (Si{sub 3}N{sub 4}) ceramic material. Validity of the model was evaluated with reference to creep and creep rupture data obtained under constant and stepwise-varied loading conditions, including the effects of annealing on creep and creep rupture behavior.

  11. Watershed hydrology, network allometry and ecosystem structure

    NASA Astrophysics Data System (ADS)

    Rinaldo, A.

    2003-04-01

    The lecture covers recent advances relevant to watershed hydrology, in particular derived from the realm of data now available, covering a wide range of scales and objectively collected and analyzed. It is intended to summarize results that are, in the lecturer's opinion, crucial to our current understanding of a variety of issues. Key among them, landscape evolution models, models of the hydrologic response and, indeed a scientific challenge, ecosystem structure. In particular, a new allometric scaling law for loopless networks, confirmed through studies on rivers, exact network results and computer simulations, offers unique insight on a variety of phenomena, ranging from the ubiquity of the 'quarter-power' law in biology to the origin of scaling size spectra in marine microbial ecosystems, to the proper geomorphological description of a river basin and its hydrological implications. In a sense, networks are a byproduct of the hydrologic dynamics, and indeed can be shown to be related to ecosystem structure. Si parva licet, I will provide evidence suggesting that ensemble averaging of the allometric property (where individual realizations are different networks) leads to results in excellent accord with the known limit scaling of efficient and compact networks with remarkably little scatter with implications of somewhat general character. Such results complement recent work suggesting that scaling features are quite robust to geometrical fluctuations of network properties. Finally, I shall gather from the morphological analysis on river networks the potential for predicting the main characters of the hydrologic response in ungauged basins - a task of practical nature with many social implications, possibly relevant to the Session's aims.

  12. Multiscale Modeling of Advanced Materials for Damage Prediction and Structural Health Monitoring

    NASA Astrophysics Data System (ADS)

    Borkowski, Luke

    Advanced aerospace materials, including fiber reinforced polymer and ceramic matrix composites, are increasingly being used in critical and demanding applications, challenging the current damage prediction, detection, and quantification methodologies. Multiscale computational models offer key advantages over traditional analysis techniques and can provide the necessary capabilities for the development of a comprehensive virtual structural health monitoring (SHM) framework. Virtual SHM has the potential to drastically improve the design and analysis of aerospace components through coupling the complementary capabilities of models able to predict the initiation and propagation of damage under a wide range of loading and environmental scenarios, simulate interrogation methods for damage detection and quantification, and assess the health of a structure. A major component of the virtual SHM framework involves having micromechanics-based multiscale composite models that can provide the elastic, inelastic, and damage behavior of composite material systems under mechanical and thermal loading conditions and in the presence of microstructural complexity and variability. Quantification of the role geometric and architectural variability in the composite microstructure plays in the local and global composite behavior is essential to the development of appropriate scale-dependent unit cells and boundary conditions for the multiscale model. Once the composite behavior is predicted and variability effects assessed, wave-based SHM simulation models serve to provide knowledge on the probability of detection and characterization accuracy of damage present in the composite. The research presented in this dissertation provides the foundation for a comprehensive SHM framework for advanced aerospace materials. The developed models enhance the prediction of damage formation as a result of ceramic matrix composite processing, improve the understanding of the effects of architectural and

  13. A hybrid numerical technique for predicting the aerodynamic and acoustic fields of advanced turboprops

    NASA Technical Reports Server (NTRS)

    Homicz, G. F.; Moselle, J. R.

    1985-01-01

    A hybrid numerical procedure is presented for the prediction of the aerodynamic and acoustic performance of advanced turboprops. A hybrid scheme is proposed which in principle leads to a consistent simultaneous prediction of both fields. In the inner flow a finite difference method, the Approximate-Factorization Alternating-Direction-Implicit (ADI) scheme, is used to solve the nonlinear Euler equations. In the outer flow the linearized acoustic equations are solved via a Boundary-Integral Equation (BIE) method. The two solutions are iteratively matched across a fictitious interface in the flow so as to maintain continuity. At convergence the resulting aerodynamic load prediction will automatically satisfy the appropriate free-field boundary conditions at the edge of the finite difference grid, while the acoustic predictions will reflect the back-reaction of the radiated field on the magnitude of the loading source terms, as well as refractive effects in the inner flow. The equations and logic needed to match the two solutions are developed and the computer program implementing the procedure is described. Unfortunately, no converged solutions were obtained, due to unexpectedly large running times. The reasons for this are discussed and several means to alleviate the situation are suggested.

  14. A prospective study of the efficacy of magnetic resonance spectroscopy imaging for predicting locally advanced prostate cancer

    PubMed Central

    Razi, Ali; Parizi, Mehdi Kardoust; Kazemeini, Seid Mohammad; Abedi, Akbar

    2015-01-01

    Objective: To evaluate the efficacy of magnetic resonance spectroscopy imaging (MRSI) for predicting locally advanced prostate cancer (PC). Materials and methods: Between April 2009 and July 2012, 80 consecutive patients with clinically localized PC had undergone endorectal MRSI before radical retropubic prostatectomy. Clinicopathological parameters, including age, preoperative prostate-specific antigen (PSA), Gleason score (GS) at biopsy, perinural invasion at biopsy, prostate weight at surgery, GS of surgical specimen, and pathological staging were recorded. The MRSI findings were compared with the histopathological findings of the radical prostatectomy. The diagnostic accuracy measures consisting of sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) of MRSI, and other variables in the diagnosis of locally advanced PC (Pathology Stages pT3a, pT3b, or pT4) were evaluated. Results: Sensitivity, specificity, PPV, and NPV of MRSI in detecting locally advanced PC is 42.4%, 93.6%, 82.3%, and 69.8%, respectively [area under the receiver operating characteristic (ROC) curve=0.658, p value <0.0001]. MRSI, cancer-positive core percentage at biopsy, and GS at biopsy are more accurate factors among all the predictive variables in predicting locally advanced PC. Conclusion: MRSI may be considered as a complementary diagnostic modality with high specificity and moderate sensitivity in predicting locally advanced PC. Combination of this modality with other predictive factors helps the surgeon and patient to select an appropriate treatment strategy. PMID:26328204

  15. CUAHSI Hydrologic Information System and its role in hydrologic observatories

    NASA Astrophysics Data System (ADS)

    Maidment, D.; Helly, J. J.; Graham, W.; Kruger, A.; Kumar, P.; Lakshmi, V.; Lettenmaier, D.; Zheng, C.; Lall, U.; Piasecki, M.; Duffy, C.

    2003-12-01

    The Hydrologic Information System component of CUAHSI focuses on building a hydrologic information system to support the advancement of hydrologic science. This system is intended to help with rapidly acquiring diverse geospatial and temporal hydrologic datasets, integrating them into a hydrologic data model or framework describing a region, and supporting analysis, modeling and visualization of the movement of water and the transport of constituents through that region. In addition, the system will feature interfaces for advanced technologies like knowledge discovery in databases (KDD) and also provide a comprehensive metadata description including a hydrologic ontology (HOW) for integration with the Semantic Web. The prototype region is the Neuse river basin in North Carolina. A "digital watershed" is to be built for this basin to help formulate and test the hydrologic data model at a range of spatial scales, from the scale of the whole basin down to the scale of individual experimental sites. This data model will be further developed and refined as additional hydrologic observatories are selected by CUAHSI. This will result in a consistent means for the characterization and comparison of processes in different geographic regions of the nation using a common data framework. The HIS will also provide a generalized digital library capability to manage collections of thematically-organized data from primary sources as well as derived analytical results in the form of data publications. The HIS will be designed from the beginning as an open federation of observatory-based collections that are interoperable with other data and digital library systems. The CUAHSI Hydrologic Information System project involves collaboration among several CUAHSI member institutions, with the San Diego Supercomputer Center serving as the technology partner to facilitate the development of a prototype system.

  16. Assessing the model performance of an integrated hydrological and biogeochemical model for discharge and nitrate load predictions

    NASA Astrophysics Data System (ADS)

    Pohlert, T.; Breuer, L.; Huisman, J. A.; Frede, H.-G.

    2007-03-01

    In this study, we evaluate the performance of the SWAT-N model, a modified version of the widely used SWAT version, for discharge and nitrate predictions at the mesoscale Dill catchment (Germany) for a 5-year period. The underlying question is, whether the model efficiency is sufficient for scenario analysis of land-use changes on both water quantity and quality. The Shuffled Complex Evolution (SCE-UA) algorithm is used to calibrate the model for daily discharge at the catchments outlet. Model performance is assessed with a split-sampling as well as a proxy-basin test using recorded hydrographs of four additional gauges located within the catchment. The efficiency regarding nitrate load simulation is assessed without further calibration on a daily, log-daily, weekly, and monthly basis as compared to observations derived from an intensive sampling campaign conducted at the catchments outlet. A new approach is employed to test the spatial consistency of the model, where simulated longitudinal profiles of nitrate concentrations were compared with observed longitudinal profiles. It is concluded that the model efficiency of SWAT-N is sufficient for the assessment of scenarios for daily discharge predictions. SWAT-N can be employed without further calibration for nitrate load simulations on both a weekly and monthly basis with an acceptable degree of accuracy. However, the model efficiency for daily nitrate load is insufficient, which can be attributed to both data uncertainty (i.e. point-source effluents and actual farming practise) as well as structural errors. The simulated longitudinal profiles meet the observations reasonably well, which suggests that the model is spatially consistent.

  17. Assessing the model performance of an integrated hydrological and biogeochemical model for discharge and nitrate load predictions

    NASA Astrophysics Data System (ADS)

    Pohlert, T.; Breuer, L.; Huisman, J. A.; Frede, H.-G.

    2006-09-01

    In this study, we evaluate the performance of the SWAT-N model, a modified version of the widely used SWAT version, for discharge and nitrate predictions at the mesoscale Dill catchment for a 5-year period. The underlying question is, whether the model efficiency is sufficient for scenario analysis of land-use changes on both water quantity and quality. The Shuffled Complex Evolution (SCE-UA) algorithm is used to calibrate the model for daily discharge at the catchments outlet. Model performance is assessed with a split-sampling as well as a proxy-basin test using recorded hydrographs of four additional gauges located within the catchment. The efficiency regarding nitrate load simulation is assessed without further calibration on a daily, log-daily, weekly, and monthly basis as compared to observations derived from an intensive sampling campaign conducted at the catchments outlet. A new approach is employed to test the spatial consistency of the model, where simulated longitudinal profiles of nitrate concentrations were compared with observed longitudinal profiles. It is concluded that the model efficiency of SWAT-N is sufficient for the assessment of scenarios for daily discharge predictions. SWAT-N can be employed without further calibration for nitrate load simulations on both a weekly and monthly basis with an acceptable degree of accuracy. However, the model efficiency for daily nitrate load is insufficient, which can be attributed to both data uncertainty (i.e. point-source effluents and actual farming practise) as well as structural errors. The simulated longitudinal profiles meet the observations reasonably well, which suggests that the model is spatially consistent.

  18. Predictive Factors of Tumor Response After Neoadjuvant Chemoradiation for Locally Advanced Rectal Cancer

    SciTech Connect

    Moureau-Zabotto, Laurence; Farnault, Bertrand; de Chaisemartin, Cecile; Esterni, Benjamin; Lelong, Bernard; Viret, Frederic; Giovannini, Marc; Monges, Genevieve; Delpero, Jean-Robert; Bories, Erwan; Turrini, Olivier; Viens, Patrice; Salem, Naji

    2011-06-01

    Purpose: Neoadjuvant chemoradiation followed by surgery is the standard of care for locally advanced rectal cancer. The aim of this study was to correlate tumor response to survival and to identify predictive factors for tumor response after chemoradiation. Methods and Materials: From 1998 to 2008, 168 patients with histologically proven locally advanced adenocarcinoma treated by preoperative chemoradiation before total mesorectal excision were retrospectively studied. They received a radiation dose of 45 Gy with a concomitant 5-fluorouracil (5-FU)-based chemotherapy. Analysis of tumor response was based on lowering of the T stage between pretreatment endorectal ultrasound and pathologic specimens. Overall and progression-free survival rates were correlated with tumor response. Tumor response was analyzed with predictive factors. Results: The median follow-up was 34 months. Five-year disease-free survival and overall survival rates were, of 44.4% and 74.5% in the whole population, 83.4% and 83.4%, respectively, in patients with pathological complete response, 38.6% and 71.9%, respectively, in patients with tumor downstaging, and 29.1and 58.9% respectively, in patients with absence of response. A pretreatment carcinoembryonic antigen (CEA) level of <5 ng/ml was significantly independently associated with pathologic complete tumor response (p = 0.019). Pretreatment small tumor size (p = 0.04), pretreatment CEA level of <5 ng/ml (p = 0.008), and chemotherapy with capecitabine (vs. 5-FU) (p = 0.04) were significantly associated with tumor downstaging. Conclusions: Downstaging and complete response after CRT improved progression-free survival and overall survival of locally advanced rectal adenocarcinoma. In multivariate analysis, a pretreatment CEA level of <5 ng/ml was associated with complete tumor response. Thus, small tumor size, a pretreatment CEA level of < 5ng/ml, and use of capecitabine were associated with tumor downstaging.

  19. Satellite-derived potential evapotranspiration for distributed hydrologic runoff modeling

    NASA Astrophysics Data System (ADS)

    Spies, R. R.; Franz, K. J.; Bowman, A.; Hogue, T. S.; Kim, J.

    2012-12-01

    Distributed models have the ability of incorporating spatially variable data, especially high resolution forcing inputs such as precipitation, temperature and evapotranspiration in hydrologic modeling. Use of distributed hydrologic models for operational streamflow prediction has been partially hindered by a lack of readily available, spatially explicit input observations. Potential evapotranspiration (PET), for example, is currently accounted for through PET input grids that are based on monthly climatological values. The goal of this study is to assess the use of satellite-based PET estimates that represent the temporal and spatial variability, as input to the National Weather Service (NWS) Hydrology Laboratory Research Distributed Hydrologic Model (HL-RDHM). Daily PET grids are generated for six watersheds in the upper Mississippi River basin using a method that applies only MODIS satellite-based observations and the Priestly Taylor formula (MODIS-PET). The use of MODIS-PET grids will be tested against the use of the current climatological PET grids for simulating basin discharge. Gridded surface temperature forcing data are derived by applying the inverse distance weighting spatial prediction method to point-based station observations from the Automated Surface Observing System (ASOS) and Automated Weather Observing System (AWOS). Precipitation data are obtained from the Climate Prediction Center's (CPC) Climatology-Calibrated Precipitation Analysis (CCPA). A-priori gridded parameters for the Sacramento Soil Moisture Accounting Model (SAC-SMA), Snow-17 model, and routing model are initially obtained from the Office of Hydrologic Development and further calibrated using an automated approach. The potential of the MODIS-PET to be used in an operational distributed modeling system will be assessed with the long-term goal of promoting research to operations transfers and advancing the science of hydrologic forecasting.

  20. The Use of Remote Sensing for Monitoring, Prediction, and Management of Hydrologic, Agricultural, and Ecological Processes in the Northern Great Plains

    NASA Technical Reports Server (NTRS)

    Farwell, Sherry O.; DeTroye, Diane (Technical Monitor)

    2002-01-01

    The NASA-EPSCoR program in South Dakota is focused on the enhancement of NASA-related research in earth system science and corresponding infrastructure development to support this theme. Hence, the program has adopted a strategy that keys on research projects that: a) establish quantitative links between geospatial information technologies and fundamental climatic and ecosystem processes in the Northern Great Plains (NGP) and b) develop and use coupled modeling tools, which can be initialized by data from combined satellite and surface measurements, to provide reliable predictions and management guidance for hydrologic, agricultural, and ecological systems of the NGP. Building a partnership network that includes both internal and external team members is recognized as an essential element of the SD NASA-EPSCoR program. Hence, promoting and tracking such linkages along with their relevant programmatic consequences are used as one metric to assess the program's progress and success. This annual report first summarizes general activities and accomplishments, and then provides progress narratives for the two separate, yet related research projects that are essential components of the SD NASA-EPSCoR program.

  1. Advance Prediction of the March 11, 2011 Great East Japan Earthquake: A Missed Opportunity for Disaster Preparedness

    NASA Astrophysics Data System (ADS)

    Davis, C. A.; Keilis-Borok, V. I.; Kossobokov, V. G.; Soloviev, A.

    2012-12-01

    There was a missed opportunity for implementing important disaster preparedness measures following an earthquake prediction that was announced as an alarm in mid-2001. This intermediate-term middle-range prediction was the initiation of a chain of alarms that successfully detected the time, region, and magnitude range for the magnitude 9.0 March 11, 2011 Great East Japan Earthquake. The prediction chains were made using an algorithm called M8 and is the latest of many predictions tested worldwide for more than 25 years, the results of which show at least a 70% success rate. The earthquake detection could have been utilized to implement measures and improve earthquake preparedness in advance; unfortunately this was not done, in part due to the predictions' limited distribution and the lack of applying existing methods for using intermediate-term predictions to make decisions for taking action. The resulting earthquake and induced tsunami caused tremendous devastation to north-east Japan. Methods that were known in advance of the predication and further advanced during the prediction timeframe are presented in a scenario describing some possibilities on how the 2001 prediction may have been utilized to reduce significant damage, including damage to the Fukushima nuclear power plant, and to show prudent cost-effective actions can be taken if the prediction certainty is known, but not necessarily high. The purpose of this presentation is to show how the prediction information can be strategically used to enhance disaster preparedness and reduce future impacts from the world's largest earthquakes.

  2. Predictive Modeling of Estrogen Receptor Binding Agents Using Advanced Cheminformatics Tools and Massive Public Data

    PubMed Central

    Ribay, Kathryn; Kim, Marlene T.; Wang, Wenyi; Pinolini, Daniel; Zhu, Hao

    2016-01-01

    Estrogen receptors (ERα) are a critical target for drug design as well as a potential source of toxicity when activated unintentionally. Thus, evaluating potential ERα binding agents is critical in both drug discovery and chemical toxicity areas. Using computational tools, e.g., Quantitative Structure-Activity Relationship (QSAR) models, can predict potential ERα binding agents before chemical synthesis. The purpose of this project was to develop enhanced predictive models of ERα binding agents by utilizing advanced cheminformatics tools that can integrate publicly available bioassay data. The initial ERα binding agent data set, consisting of 446 binders and 8307 non-binders, was obtained from the Tox21 Challenge project organized by the NIH Chemical Genomics Center (NCGC). After removing the duplicates and inorganic compounds, this data set was used to create a training set (259 binders and 259 non-binders). This training set was used to develop QSAR models using chemical descriptors. The resulting models were then used to predict the binding activity of 264 external compounds, which were available to us after the models were developed. The cross-validation results of training set [Correct Classification Rate (CCR) = 0.72] were much higher than the external predictivity of the unknown compounds (CCR = 0.59). To improve the conventional QSAR models, all compounds in the training set were used to search PubChem and generate a profile of their biological responses across thousands of bioassays. The most important bioassays were prioritized to generate a similarity index that was used to calculate the biosimilarity score between each two compounds. The nearest neighbors for each compound within the set were then identified and its ERα binding potential was predicted by its nearest neighbors in the training set. The hybrid model performance (CCR = 0.94 for cross validation; CCR = 0.68 for external prediction) showed significant improvement over the original QSAR

  3. The Platte River Hydrologic Observatory (PRIVHO)

    NASA Astrophysics Data System (ADS)

    Harvey, F.; Ramirez, J. A.; Thurow, T. L.

    2004-12-01

    The Platte River Hydrologic Observatory (PRIVHO), located within the Platte River Basin, of the U.S. central Great Plains, affords excellent interdisciplinary and multi-disciplinary research opportunities for scientists to examine the impacts of scaling, to investigate forcing feedbacks and coupling of various interconnected hydrological, geological, climatological and biological systems, and to test the applicability and limits of prediction in keeping with all five of CUAHSI's priority science criteria; linking hydrologic and biogeochemical cycles, sustainability of water resources, hydrologic and ecosystem interactions, hydrologic extremes, and fate and transport of contaminants. In addition, PRIVHO is uniquely positioned to investigate many human dimension questions such as those related to interstate and intrastate conflicts over water use, evolution of water policy and law in the wake of advancing science, societal and economic changes that are driven by water use, availability and management, and human impacts on climate and land use changes. The Platte River traverses several important environmental gradients, including temperature and precipitation-to-evaporation ratio, is underlain by the High Plains Aquifer under much of its reach, crosses a number of terrestrial ecoregions, and in central Nebraska, serves as a vital link in the Central Flyway, providing habitat for 300 species of migratory birds and many threatened or endangered species. The Platte River flows through metropolitan, urban and agricultural settings and is impacted by both point and non-point pollution. The Platte River is one of the most over-appropriated rivers in the country with 15 major dams, hundreds of small reservoirs, and thousands of irrigation wells. The river provides municipal and industrial water supplies for about 3.5 million people, irrigation water for millions of acres of farmland, and generates millions of dollars of hydroelectric power. PRIVHO will allow researchers to

  4. A satellite based scheme for predicting the effects of land cover change on local microclimate and surface hydrology: Development of an operational regional planning tool

    NASA Astrophysics Data System (ADS)

    Arthur, Sandra Traci

    Humans have diverse goals for their use of land: mining, water supply, aesthetic enjoyment, recreation, transportation, housing, etc. Any individual living within an actively developing community can look back in time and note how, perhaps slowly but nonetheless dramatically, the total land area dedicated to human use has increased. As our society's basic functioning intensifies, the disappearance of "free" open space is apparent---today, even conservation areas are carefully designated, mapped and controlled. This transition in land use is a result of many individual decisions that occur throughout space and time, often with little concern for the potential impacts on the local environment. Two specific environmental components---the microclimate and surface hydrology---are the focus of this thesis. This study, as well as related tools and bodies of knowledge, should be used to broaden the scientific basis behind land use management decisions. It will be shown that development can induce predictable changes in measures of the local radiant surface temperature and evapotranspiration fraction---as long as certain features of the development are known. Specifically, the vegetation changes that accompany the development must be noted, as well as the initial climatic state of the land parcel. Additionally, plots of runoff vs. rainfall for gauged basins will be interpreted in terms of the proportion of the basin contributing to a storm event's runoff signal. For a particular basin, four distinct runoff responses, separated by season and antecedent moisture conditions, will be distinguished. The response for the non-summer months under typical antecedent moisture conditions will be shown to be the most representative of and responsive to a basin's land use patterns. A scheme that makes use of satellite-derived land cover patterns and other physical attributes of the basin in order to determine this particular runoff response will be presented. The Soil Conservation

  5. Comparison of the Berg Balance Scale and Fullerton Advanced Balance Scale to predict falls in community-dwelling adults

    PubMed Central

    Jeon, Yong-Jin; Kim, Gyoung-Mo

    2017-01-01

    [Purpose] The purpose of this study was to investigate and compare the predictive properties of Berg Balance Scale and Fullerton Advanced Balance Scales, in a group of independently-functioning community dwelling older adults. [Subjects and Methods] Ninety-seven community-dwelling older adults (male=39, female=58) who were capable of walking independently on assessment were included in this study. A binary logistic regression analysis of the Berg Balance Scale and Fullerton Advanced Balance Scale scores was used to investigate a predictive model for fall risk. A receiver operating characteristic analysis was conducted for each, to determine the cut-off for optimal levels of sensitivity and specificity. [Results] The overall prediction success rate was 89.7%; the total Berg Balance Scale and Fullerton Advanced Balance Scale scores were significant in predicting fall risk. Receiver operating characteristic analysis determined that a cut-off score of 40 out of 56 on the Berg Balance Scale produced the highest sensitivity (0.82) and specificity (0.67), and a cut-off score of 22 out of 40 on the Fullerton Advanced Balance Scale produced the highest sensitivity (0.85) and specificity (0.65) in predicting faller status. [Conclusion] The Berg Balance Scale and Fullerton Advanced Balance Scales can predict fall risk, when used for independently-functioning community-dwelling older adults. PMID:28265146

  6. Comparison of the Berg Balance Scale and Fullerton Advanced Balance Scale to predict falls in community-dwelling adults.

    PubMed

    Jeon, Yong-Jin; Kim, Gyoung-Mo

    2017-02-01

    [Purpose] The purpose of this study was to investigate and compare the predictive properties of Berg Balance Scale and Fullerton Advanced Balance Scales, in a group of independently-functioning community dwelling older adults. [Subjects and Methods] Ninety-seven community-dwelling older adults (male=39, female=58) who were capable of walking independently on assessment were included in this study. A binary logistic regression analysis of the Berg Balance Scale and Fullerton Advanced Balance Scale scores was used to investigate a predictive model for fall risk. A receiver operating characteristic analysis was conducted for each, to determine the cut-off for optimal levels of sensitivity and specificity. [Results] The overall prediction success rate was 89.7%; the total Berg Balance Scale and Fullerton Advanced Balance Scale scores were significant in predicting fall risk. Receiver operating characteristic analysis determined that a cut-off score of 40 out of 56 on the Berg Balance Scale produced the highest sensitivity (0.82) and specificity (0.67), and a cut-off score of 22 out of 40 on the Fullerton Advanced Balance Scale produced the highest sensitivity (0.85) and specificity (0.65) in predicting faller status. [Conclusion] The Berg Balance Scale and Fullerton Advanced Balance Scales can predict fall risk, when used for independently-functioning community-dwelling older adults.

  7. The prediction of the building precision in the Laser Engineered Net Shaping process using advanced networks

    NASA Astrophysics Data System (ADS)

    Lu, Z. L.; Li, D. C.; Lu, B. H.; Zhang, A. F.; Zhu, G. X.; Pi, G.

    2010-05-01

    Laser Engineered Net Shaping (LENS) is an advanced manufacturing technology, but it is difficult to control the depositing height (DH) of the prototype because there are many technology parameters influencing the forming process. The effect of main parameters (laser power, scanning speed and powder feeding rate) on the DH of single track is firstly analyzed, and then it shows that there is the complex nonlinear intrinsic relationship between them. In order to predict the DH, the back propagation (BP) based network improved with Adaptive learning rate and Momentum coefficient (AM) algorithm, and the least square support vector machine (LS-SVM) network are both adopted. The mapping relationship between above parameters and the DH is constructed according to training samples collected by LENS experiments, and then their generalization ability, function-approximating ability and real-time are contrastively investigated. The results show that although the predicted result by the BP-AM approximates the experimental result, above performance index of the LS-SVM are better than those of the BP-AM. Finally, high-definition thin-walled parts of AISI316L are successfully fabricated. Hence, the LS-SVM network is more suitable for the prediction of the DH.

  8. In silico ADMET prediction: recent advances, current challenges and future trends.

    PubMed

    Cheng, Feixiong; Li, Weihua; Liu, Guixia; Tang, Yun

    2013-01-01

    There are numerous small molecular compounds around us to affect our health, such as drugs, pesticides, food additives, industrial chemicals, and environmental pollutants. Over decades, properties related to absorption, distribution, metabolism, excretion, and toxicity (ADMET) have become one of the most important issues to assess the effects or risks of these compounds on human body. Recent high-rate drug withdrawals increase the pressure on regulators and pharmaceutical industry to improve preclinical safety testing. Since in vivo and in vitro evaluations are costly and laborious, in silico techniques have been widely used to estimate these properties. In this review, we would briefly describe the recent advances of in silico ADMET prediction, with emphasis on substructure pattern recognition method that we developed recently. Challenges and limitations in the area of in silico ADMET prediction were further discussed, such as application domain of models, models validation techniques, and global versus local models. At last, several new promising research directions were provided, such as computational systems toxicology (toxicogenomics), data-integration and meta-decision making systems, which could be used for systemic in silico ADMET prediction in drug discovery and hazard risk assessment.

  9. Regional Arctic System Model (RASM): A Tool to Address the U.S. Priorities and Advance Capabilities for Arctic Climate Modeling and Prediction

    NASA Astrophysics Data System (ADS)

    Maslowski, W.; Roberts, A.; Cassano, J. J.; Gutowski, W. J., Jr.; Nijssen, B.; Osinski, R.; Zeng, X.; Brunke, M.; Duvivier, A.; Hamman, J.; Hossainzadeh, S.; Hughes, M.; Seefeldt, M. W.

    2015-12-01

    The Arctic is undergoing some of the most coordinated rapid climatic changes currently occurring anywhere on Earth, including the retreat of the perennial sea ice cover, which integrates forcing by, exchanges with and feedbacks between atmosphere, ocean and land. While historical reconstructions from Earth System Models (ESMs) are in broad agreement with these changes, the rate of change in ESMs generally remains outpaced by observations. Reasons for that relate to a combination of coarse resolution, inadequate parameterizations, under-represented processes and a limited knowledge of physical interactions. We demonstrate the capability of the Regional Arctic System Model (RASM) in addressing some of the ESM limitations in simulating observed variability and trends in arctic surface climate. RASM is a high resolution, pan-Arctic coupled climate model with the sea ice and ocean model components configured at an eddy-permitting resolution of 1/12o and the atmosphere and land hydrology model components at 50 km resolution, which are all coupled at 20-minute intervals. RASM is an example of limited-area, process-resolving, fully coupled ESM, which due to the constraints from boundary conditions facilitates detailed comparisons with observational statistics that are not possible with ESMs. The overall goal of RASM is to address key requirements published in the Navy Arctic Roadmap: 2014-2030 and in the Implementation Plan for the National Strategy for the Arctic Region, regarding the need for advanced modeling capabilities for operational forecasting and strategic climate predictions through 2030. The main science objectives of RASM are to advance understanding and model representation of critical physical processes and feedbacks of importance to sea ice thickness and area distribution. RASM results are presented to quantify relative contributions by (i) resolved processes and feedbacks as well as (ii) sensitivity to space dependent sub-grid parameterizations to better

  10. Seasonal forecasting of global hydrologic extremes using the North American Multi-model Ensemble system

    NASA Astrophysics Data System (ADS)

    Wood, Eric F.; Yuan, Xing; Roundy, Joshua K.; Sheffield, Justin

    2015-04-01

    Seasonal hydrologic extremes in the form of droughts and wet spells have devastating impacts on human and natural systems. Improving our understanding and predictive capability of hydrologic extremes, and facilitating adaptations through establishing climate service systems at regional to global scales, are among the grand challenges proposed by the World Climate Research Programme (WCRP), and are the core themes of the Regional Hydroclimate Projects (RHP) under the Global Energy and Water Exchanges Project (GEWEX). An experimental global seasonal hydrologic forecasting system has been developed, which is based on coupled climate forecast models participating in the North American Multi-Model Ensemble (NMME) project and an advanced land surface hydrologic model. The system is evaluated over major GEWEX/RHP river basins by comparing with Ensemble Streamflow Prediction (ESP). The multi-model seasonal forecast system provides higher detectability for soil moisture droughts, more reliable low and high flow ensemble forecasts, and better "real-time" prediction for the 2012 North American extreme drought. The association of the onset of extreme hydrologic events with oceanic and land precursors is also investigated based on the joint distribution of forecasts and observations. Climate models have a higher probability of missing the onset of hydrologic extremes when there is no oceanic precursor. But oceanic precursor alone is insufficient to guarantee a correct forecast, a land precursor is also critical in avoiding a false alarm for forecasting extremes. This study is targeted at providing the scientific underpinning for the predictability of hydrologic extremes over GEWEX/RHP basins, and serves as a prototype for seasonal hydrologic forecasts within the Global Framework for Climate Services (GFCS).

  11. Arctic hydrology and meteorology

    SciTech Connect

    Kane, D.L.

    1989-01-01

    To date, five years of hydrologic and meteorologic data have been collected at Imnavait Creek near Toolik Lake, Alaska. This is the most complete set of field data of this type collected in the Arctic of North America. These data have been used in process-oriented research to increase our understanding of atmosphere/hydrosphere/biosphere/lithosphere interactions. Basically, we are monitoring heat and mass transfer between various spheres to quantify rates. These could be rates of mass movement such as hillslope flow or rates of heat transfer for active layer thawing or combined heat and mass processes such as evapotranspiration. We have utilized a conceptual model to predict hydrologic processes. To test the success of this model, we are comparing our predicted rates of runoff and snowmelt to measured valves. We have also used a surface energy model to simulate active layer temperatures. The final step in this modeling effort to date was to predict what impact climatic warming would have on active layer thicknesses and how this will influence the hydrology of our research watershed by examining several streambeds.

  12. PNW Hydrologic Landscape Class

    EPA Pesticide Factsheets

    Work has been done to expand the hydrologic landscapes (HLs) concept and to develop an approach for using it to address streamflow vulnerability from climate change. This work has included development of the HL classification framework and its application to Oregon, use of the HL classes to predict where a simple lumped hydrologic model accurately predicts daily streamflow, use of HL information to model the presence of cold-water patches at tributary confluences, and combining Oregon HL results with temperature and precipitation predictions to examine how HLs would vary as a result of climate change. As a part of the current work, the HL approach has been expanded to the Pacific Northwest (Oregon, Washington, and Idaho) based on a revision of the approach that makes it more broadly applicable. This revised approach has several advantages compared with the original approach: it is not limited to areas that have an aquifer permeability map; it uses a flexible approach to converting a nationally available geospatial dataset into assessment units; and it is more robust. These improvements should allow the revised HL approach to be applied more often in situations requiring hydrologic classification, and allow greater confidence in results. This effort paves the way for a climate change analysis for the Pacific Northwest that is currently underway, as well as expansion into the southwest (California, Arizona, and Nevada). This dataset contains a high resolutio

  13. Prediction and preliminary standardization of fire debris constituents with the advanced distillation curve method.

    PubMed

    Bruno, Thomas J; Lovestead, Tara M; Huber, Marcia L

    2011-01-01

    The recent National Academy of Sciences report on forensic sciences states that the study of fire patterns and debris in arson fires is in need of additional work and eventual standardization. We discuss a recently introduced method that can provide predicted evaporation patterns for ignitable liquids as a function of temperature. The method is a complex fluid analysis protocol, the advanced distillation curve approach, featuring a composition explicit data channel for each distillate fraction (for qualitative, quantitative, and trace analysis), low uncertainty temperature measurements that are thermodynamic state points that can be modeled with an equation of state, consistency with a century of historical data, and an assessment of the energy content of each distillate fraction. We discuss the application of the method to kerosenes and gasolines and outline how expansion of the scope of fluids to other ignitable liquids can benefit the criminalist in the analysis of fire debris for arson.

  14. Edge Fracture Prediction ofTraditional and Advanced Trimming Processes for AA6111-T4 Sheets

    SciTech Connect

    Hu, Xiaohua; Choi, Kyoo Sil; Sun, Xin; Golovashchenko, Segey F.

    2014-02-15

    This work examines the traditional and advanced trimming of AA6111-T4 aluminum sheets with finite element simulations. The Rice-Tracy damage model is used for the simulation with damage parameters estimated from experimental observation of grain aspect ratio near the fracture surface of trimmed parts. Fine meshes at the shearing zone, adaptive meshing, and adaptive contact techniques are used to accurately capture the contact interactions between the sharp corner of the trimming tools and the blank to be trimmed. To the knowledge of the authors, these are the first trimming simulations that can predict the effects of shearing clearance on burr heights with quantitative accuracy for AA6111-T4 aluminum sheets. In addition, the models have also accurately reproduced the crack initiation site as well as burr and sliver formation mechanisms observed experimentally.

  15. Predicting Inner Heliospheric Solar Wind Conditions in Advance of Solar Probe Plus

    NASA Astrophysics Data System (ADS)

    Case, A. W.; Kasper, J. C.; Korreck, K. E.; Stevens, M. L.; Cohen, O.; Salem, C. S.; Halekas, J. S.; Larson, D. E.; Maruca, B. A.

    2012-12-01

    In advance of the upcoming inner heliospheric missions (Solar Orbiter and Solar Probe Plus) it is vital to have an accurate prediction of the range of solar wind conditions that occur between 9.5Rs and 0.7AU. These conditions will place constraints on instrument design and the operational modes that are used. In this paper, we discuss and compare different methods of predicting the solar wind bulk plasma parameters. One method uses observed 1AU conditions observed with the Wind spacecraft combined with scaling laws derived from Helios observations. We extend this simple model by using a more realistic solar wind velocity profile in addition to the Wind and Helios observations. Another method uses 3D MHD simulations from which solar wind conditions along a spacecraft trajectory can be extracted. We discuss some implications of these models in the design of the Solar Wind Electrons Alphas and Protons investigation, a suite of solar wind instruments being designed to fly on Solar Probe Plus.

  16. Investigation to advance prediction techniques of the low-speed aerodynamics of V/STOL aircraft

    NASA Technical Reports Server (NTRS)

    Maskew, B.; Strash, D.; Nathman, J.; Dvorak, F. A.

    1985-01-01

    A computer program, VSAERO, has been applied to a number of V/STOL configurations with a view to advancing prediction techniques for the low-speed aerodynamic characteristics. The program couples a low-order panel method with surface streamline calculation and integral boundary layer procedures. The panel method--which uses piecewise constant source and doublet panels-includes an iterative procedure for wake shape and models boundary layer displacement effect using the source transpiration technique. Certain improvements to a basic vortex tube jet model were installed in the code prior to evaluation. Very promising results were obtained for surface pressures near a jet issuing at 90 deg from a flat plate. A solid core model was used in the initial part of the jet with a simple entrainment model. Preliminary representation of the downstream separation zone significantly improve the correlation. The program accurately predicted the pressure distribution inside the inlet on the Grumman 698-411 design at a range of flight conditions. Furthermore, coupled viscous/potential flow calculations gave very close correlation with experimentally determined operational boundaries dictated by the onset of separation inside the inlet. Experimentally observed degradation of these operational boundaries between nacelle-alone tests and tests on the full configuration were also indicated by the calculation. Application of the program to the General Dynamics STOL fighter design were equally encouraging. Very close agreement was observed between experiment and calculation for the effects of power on pressure distribution, lift and lift curve slope.

  17. Advanced error-prediction LDPC with temperature compensation for highly reliable SSDs

    NASA Astrophysics Data System (ADS)

    Tokutomi, Tsukasa; Tanakamaru, Shuhei; Iwasaki, Tomoko Ogura; Takeuchi, Ken

    2015-09-01

    To improve the reliability of NAND Flash memory based solid-state drives (SSDs), error-prediction LDPC (EP-LDPC) has been proposed for multi-level-cell (MLC) NAND Flash memory (Tanakamaru et al., 2012, 2013), which is effective for long retention times. However, EP-LDPC is not as effective for triple-level cell (TLC) NAND Flash memory, because TLC NAND Flash has higher error rates and is more sensitive to program-disturb error. Therefore, advanced error-prediction LDPC (AEP-LDPC) has been proposed for TLC NAND Flash memory (Tokutomi et al., 2014). AEP-LDPC can correct errors more accurately by precisely describing the error phenomena. In this paper, the effects of AEP-LDPC are investigated in a 2×nm TLC NAND Flash memory with temperature characterization. Compared with LDPC-with-BER-only, the SSD's data-retention time is increased by 3.4× and 9.5× at room-temperature (RT) and 85 °C, respectively. Similarly, the acceptable BER is increased by 1.8× and 2.3×, respectively. Moreover, AEP-LDPC can correct errors with pre-determined tables made at higher temperatures to shorten the measurement time before shipping. Furthermore, it is found that one table can cover behavior over a range of temperatures in AEP-LDPC. As a result, the total table size can be reduced to 777 kBytes, which makes this approach more practical.

  18. Assessing Impacts of Landuse Changes on Hydrology for the Upper San Pedro Watershed

    EPA Science Inventory

    The assessment of landuse changes on hydrology is essential for the development of sustainable water resource strategies. Specifically, understanding how each land use influences hydrological processes will greatly improve predictability of hydrological consequences to landuse ch...

  19. Advancing representation of hydrologic processes in the Soil and Water Assessment Tool (SWAT) through integration of the TOPographic MODEL (TOPMODEL) features

    USGS Publications Warehouse

    Chen, J.; Wu, Y.

    2012-01-01

    This paper presents a study of the integration of the Soil and Water Assessment Tool (SWAT) model and the TOPographic MODEL (TOPMODEL) features for enhancing the physical representation of hydrologic processes. In SWAT, four hydrologic processes, which are surface runoff, baseflow, groundwater re-evaporation and deep aquifer percolation, are modeled by using a group of empirical equations. The empirical equations usually constrain the simulation capability of relevant processes. To replace these equations and to model the influences of topography and water table variation on streamflow generation, the TOPMODEL features are integrated into SWAT, and a new model, the so-called SWAT-TOP, is developed. In the new model, the process of deep aquifer percolation is removed, the concept of groundwater re-evaporation is refined, and the processes of surface runoff and baseflow are remodeled. Consequently, three parameters in SWAT are discarded, and two new parameters to reflect the TOPMODEL features are introduced. SWAT-TOP and SWAT are applied to the East River basin in South China, and the results reveal that, compared with SWAT, the new model can provide a more reasonable simulation of the hydrologic processes of surface runoff, groundwater re-evaporation, and baseflow. This study evidences that an established hydrologic model can be further improved by integrating the features of another model, which is a possible way to enhance our understanding of the workings of catchments.

  20. Advancing representation of hydrologic processes in the Soil and Water Assessment Tool (SWAT) through integration of the TOPographic MODEL (TOPMODEL) features

    NASA Astrophysics Data System (ADS)

    Chen, Ji; Wu, Yiping

    2012-02-01

    SummaryThis paper presents a study of the integration of the Soil and Water Assessment Tool (SWAT) model and the TOPographic MODEL (TOPMODEL) features for enhancing the physical representation of hydrologic processes. In SWAT, four hydrologic processes, which are surface runoff, baseflow, groundwater re-evaporation and deep aquifer percolation, are modeled by using a group of empirical equations. The empirical equations usually constrain the simulation capability of relevant processes. To replace these equations and to model the influences of topography and water table variation on streamflow generation, the TOPMODEL features are integrated into SWAT, and a new model, the so-called SWAT-TOP, is developed. In the new model, the process of deep aquifer percolation is removed, the concept of groundwater re-evaporation is refined, and the processes of surface runoff and baseflow are remodeled. Consequently, three parameters in SWAT are discarded, and two new parameters to reflect the TOPMODEL features are introduced. SWAT-TOP and SWAT are applied to the East River basin in South China, and the results reveal that, compared with SWAT, the new model can provide a more reasonable simulation of the hydrologic processes of surface runoff, groundwater re-evaporation, and baseflow. This study evidences that an established hydrologic model can be further improved by integrating the features of another model, which is a possible way to enhance our understanding of the workings of catchments.

  1. Advances in monitoring dynamic hydrologic conditions in the vadose zone through automated high-resolution ground-penetrating radar imaging and analysis

    NASA Astrophysics Data System (ADS)

    Mangel, Adam R.

    This body of research focuses on resolving physical and hydrological heterogeneities in the subsurface with ground-penetrating radar (GPR). Essentially, there are two facets of this research centered on the goal of improving the collective understanding of unsaturated flow processes: i) modifications to commercially available equipment to optimize hydrologic value of the data and ii) the development of novel methods for data interpretation and analysis in a hydrologic context given the increased hydrologic value of the data. Regarding modifications to equipment, automation of GPR data collection substantially enhances our ability to measure changes in the hydrologic state of the subsurface at high spatial and temporal resolution (Chapter 1). Additionally, automated collection shows promise for quick high-resolution mapping of dangerous subsurface targets, like unexploded ordinance, that may have alternate signals depending on the hydrologic environment (Chapter 5). Regarding novel methods for data inversion, dispersive GPR data collected during infiltration can constrain important information about the local 1D distribution of water in waveguide layers (Chapters 2 and 3), however, more data is required for reliably analyzing complicated patterns produced by the wetting of the soil. In this regard, data collected in 2D and 3D geometries can further illustrate evidence of heterogeneous flow, while maintaining the content for resolving wave velocities and therefore, water content. This enables the use of algorithms like reflection tomography, which show the ability of the GPR data to independently resolve water content distribution in homogeneous soils (Chapter 5). In conclusion, automation enables the non-invasive study of highly dynamic hydrologic processes by providing the high resolution data required to interpret and resolve spatial and temporal wetting patterns associated with heterogeneous flow. By automating the data collection, it also allows for the novel

  2. Development and Application of Advanced Weather Prediction Technologies for the Wind Energy Industry (Invited)

    NASA Astrophysics Data System (ADS)

    Mahoney, W. P.; Wiener, G.; Liu, Y.; Myers, W.; Johnson, D.

    2010-12-01

    Wind energy decision makers are required to make critical judgments on a daily basis with regard to energy generation, distribution, demand, storage, and integration. Accurate knowledge of the present and future state of the atmosphere is vital in making these decisions. As wind energy portfolios expand, this forecast problem is taking on new urgency because wind forecast inaccuracies frequently lead to substantial economic losses and constrain the national expansion of renewable energy. Improved weather prediction and precise spatial analysis of small-scale weather events are crucial for renewable energy management. In early 2009, the National Center for Atmospheric Research (NCAR) began a collaborative project with Xcel Energy Services, Inc. to perform research and develop technologies to improve Xcel Energy's ability to increase the amount of wind energy in their generation portfolio. The agreement and scope of work was designed to provide highly detailed, localized wind energy forecasts to enable Xcel Energy to more efficiently integrate electricity generated from wind into the power grid. The wind prediction technologies are designed to help Xcel Energy operators make critical decisions about powering down traditional coal and natural gas-powered plants when sufficient wind energy is predicted. The wind prediction technologies have been designed to cover Xcel Energy wind resources spanning a region from Wisconsin to New Mexico. The goal of the project is not only to improve Xcel Energy’s wind energy prediction capabilities, but also to make technological advancements in wind and wind energy prediction, expand our knowledge of boundary layer meteorology, and share the results across the renewable energy industry. To generate wind energy forecasts, NCAR is incorporating observations of current atmospheric conditions from a variety of sources including satellites, aircraft, weather radars, ground-based weather stations, wind profilers, and even wind sensors on

  3. Impact of land surface conditions on the predictability of hydrologic processes and mountain-valley circulations in the North American Monsoon region

    NASA Astrophysics Data System (ADS)

    Xiang, T.; Vivoni, E. R.; Gochis, D. J.; Mascaro, G.

    2015-12-01

    Heterogeneous land surface conditions are essential components of land-atmosphere interactions in regions of complex terrain and have the potential to affect convective precipitation formation. Yet, due to their high complexity, hydrologic processes over mountainous regions are not well understood, and are usually parameterized in simple ways within coupled land-atmosphere modeling frameworks. With the improving model physics and spatial resolution of numerical weather prediction models, there is an urgent need to understand how land surface processes affect local and regional meteorological processes. In the North American Monsoon (NAM) region, the summer rainy season is accompanied by a dramatic greening of mountain ecosystems that adds spatiotemporal variability in vegetation which is anticipated to impact the conditions leading to convection, mountain-valley circulations and mesoscale organization. In this study, we present results from a detailed analysis of a high-resolution (1 km) land surface model, Noah-MP, in a large, mountainous watershed of the NAM region - the Rio Sonora (21,264 km2) in Mexico. In addition to capturing the spatial variations in terrain and soil distributions, recently-developed features in Noah-MP allow the model to read time-varying vegetation parameters derived from remotely-sensed vegetation indices; however, this new implementation has not been fully evaluated. Therefore, we assess the simulated spatiotemporal fields of soil moisture, surface temperature and surface energy fluxes through comparisons to remote sensing products and results from coarser land surface models obtained from the North American Land Data Assimilation System. We focus attention on the impact of vegetation changes along different elevation bands on the diurnal cycle of surface energy fluxes to provide a baseline for future analyses of mountain-valley circulations using a coupled land-atmosphere modeling system. Our study also compares limited streamflow

  4. Hydrological cycle.

    PubMed

    Gonçalves, H C; Mercante, M A; Santos, E T

    2011-04-01

    The Pantanal hydrological cycle holds an important meaning in the Alto Paraguay Basin, comprising two areas with considerably diverse conditions regarding natural and water resources: the Plateau and the Plains. From the perspective of the ecosystem function, the hydrological flow in the relationship between plateau and plains is important for the creation of reproductive and feeding niches for the regional biodiversity. In general, river declivity in the plateau is 0.6 m/km while declivity on the plains varies from 0.1 to 0.3 m/km. The environment in the plains is characteristically seasonal and is home to an exuberant and abundant diversity of species, including some animals threatened with extinction. When the flat surface meets the plains there is a diminished water flow on the riverbeds and, during the rainy season the rivers overflow their banks, flooding the lowlands. Average annual precipitation in the Basin is 1,396 mm, ranging from 800 mm to 1,600 mm, and the heaviest rainfall occurs in the plateau region. The low drainage capacity of the rivers and lakes that shape the Pantanal, coupled with the climate in the region, produce very high evaporation: approximately 60% of all the waters coming from the plateau are lost through evaporation. The Alto Paraguay Basin, including the Pantanal, while boasting an abundant availability of water resources, also has some spots with water scarcity in some sub-basins, at different times of the year. Climate conditions alone are not enough to explain the differences observed in the Paraguay River regime and some of its tributaries. The complexity of the hydrologic regime of the Paraguay River is due to the low declivity of the lands that comprise the Mato Grosso plains and plateau (50 to 30 cm/km from east to west and 3 to 1.5 cm/km from north to south) as well as the area's dimension, which remains periodically flooded with a large volume of water.

  5. Research Area 3 - Mathematical Sciences: Multiscale Modeling of the Mechanics of Advanced Energetic Materials Relevant to Detonation Prediction

    DTIC Science & Technology

    2015-08-24

    new energetic materials with enhanced energy release rates and reduced sensitivity to unintentional detonation . The following results have been...Mechanics of Advanced Energetic Materials Relevant to Detonation Prediction The views, opinions and/or findings contained in this report are those of the...modeling, molecular simulations, detonation prediction REPORT DOCUMENTATION PAGE 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 10. SPONSOR/MONITOR’S

  6. The role of advanced reactive surface area characterization in improving predictions of mineral reaction rates

    NASA Astrophysics Data System (ADS)

    Beckingham, L. E.; Zhang, S.; Mitnick, E.; Cole, D. R.; Yang, L.; Anovitz, L. M.; Sheets, J.; Swift, A.; Kneafsey, T. J.; Landrot, G.; Mito, S.; Xue, Z.; Steefel, C. I.; DePaolo, D. J.; Ajo Franklin, J. B.

    2014-12-01

    Geologic sequestration of CO2 in deep sedimentary formations is a promising means of mitigating carbon emissions from coal-fired power plants but the long-term fate of injected CO2 is challenging to predict. Reactive transport models are used to gain insight over long times but rely on laboratory determined mineral reaction rates that have been difficult to extrapolate to field systems. This, in part, is due to a lack of understanding of mineral reactive surface area. Many models use an arbitrary approximation of reactive surface area, applying orders of magnitude scaling factors to measured BET or geometric surface areas. Recently, a few more sophisticated approaches have used 2D and 3D image analyses to determine mineral-specific reactive surface areas that account for the accessibility of minerals. However, the ability of these advanced surface area estimates to improve predictions of mineral reaction rates has yet to be determined. In this study, we fuse X-ray microCT, SEM QEMSCAN, XRD, SANS, and SEM-FIB analysis to determine mineral-specific accessible reactive surface areas for a core sample from the Nagaoka pilot CO2 injection site (Japan). This sample is primarily quartz, plagioclase, smectite, K-feldspar, and pyroxene. SEM imaging shows abundant smectite cement and grain coatings that decrease the fluid accessibility of other minerals. However, analysis of FIB-SEM images reveals that smectite nano-pores are well connected such that access to underlying minerals is not occluded by smectite coatings. Mineral-specific accessible surfaces are determined, accounting for the connectivity of the pore space with and without connected smectite nano-pores. The large-scale impact of variations in accessibility and dissolution rates are then determined through continuum scale modeling using grid-cell specific information on accessible surface areas. This approach will be compared with a traditional continuum scale model using mineral abundances and common surface area

  7. A Priori Attitudes Predict Amniocentesis Uptake in Women of Advanced Maternal Age: A Pilot Study.

    PubMed

    Grinshpun-Cohen, Julia; Miron-Shatz, Talya; Rhee-Morris, Laila; Briscoe, Barbara; Pras, Elon; Towner, Dena

    2015-01-01

    Amniocentesis is an invasive procedure performed during pregnancy to determine, among other things, whether the fetus has Down syndrome. It is often preceded by screening, which gives a probabilistic risk assessment. Thus, ample information is conveyed to women with the goal to inform their decisions. This study examined the factors that predict amniocentesis uptake among pregnant women of advanced maternal age (older than 35 years old at the time of childbirth). Participants filled out a questionnaire regarding risk estimates, demographics, and attitudes on screening and pregnancy termination before their first genetic counseling appointment and were followed up to 24 weeks of gestation. Findings show that women's decisions are not always informed by screening results or having a medical indication. Psychological factors measured at the beginning of pregnancy: amniocentesis risk tolerance, pregnancy termination tolerance, and age risk perception affected amniocentesis uptake. Although most women thought that screening for Down syndrome risk would inform their decision, they later stated other reasons for screening, such as preparing for the possibility of a child with special needs. Findings suggest that women's decisions regarding amniocentesis are driven not only by medical factors, but also by a priori attitudes. The authors believe that these should be addressed in the dialogue on women's informed use of prenatal tests.

  8. Methodological advances in predicting flow-induced dynamics of plants using mechanical-engineering theory.

    PubMed

    de Langre, Emmanuel

    2012-03-15

    The modeling of fluid-structure interactions, such as flow-induced vibrations, is a well-developed field of mechanical engineering. Many methods exist, and it seems natural to apply them to model the behavior of plants, and potentially other cantilever-like biological structures, under flow. Overcoming this disciplinary divide, and the application of such models to biological systems, will significantly advance our understanding of ecological patterns and processes and improve our predictive capabilities. Nonetheless, several methodological issues must first be addressed, which I describe here using two practical examples that have strong similarities: one from agricultural sciences and the other from nuclear engineering. Very similar issues arise in both: individual and collective behavior, small and large space and time scales, porous modeling, standard and extreme events, trade-off between the surface of exchange and individual or collective risk of damage, variability, hostile environments and, in some aspects, evolution. The conclusion is that, although similar issues do exist, which need to be exploited in some detail, there is a significant gap that requires new developments. It is obvious that living plants grow in and adapt to their environment, which certainly makes plant biomechanics fundamentally distinct from classical mechanical engineering. Moreover, the selection processes in biology and in human engineering are truly different, making the issue of safety different as well. A thorough understanding of these similarities and differences is needed to work efficiently in the application of a mechanistic approach to ecology.

  9. Predicting compliance for mandible advancement splint therapy in 96 obstructive sleep apnea patients.

    PubMed

    Ingman, Tuula; Arte, Sirpa; Bachour, Adel; Bäck, Leif; Mäkitie, Antti

    2013-12-01

    The treatment of choice in obstructive sleep apnea (OSA) is continuous positive airway pressure (CPAP). Mandible advancement splint (MAS) offers an option for patients with mild or moderate OSA, who refuse or are unable to tolerate CPAP. The aim of the study was to find predictive factors in OSA for MAS therapy. The study group comprised 96 consecutive OSA patients who were sent for MAS therapy during 2008. Data were collected on the patients' general and dental condition, diagnosis, and treatment for OSA. Panoramic and cephalometric radiographs were analysed. The treatment compliance rate and problems with the use of the MAS were recorded. This rate was 57% and the significant affecting factors were protrusion of the mandible with MAS during the adaptation to the appliance as well as shorter maxillary and mandible lengths. The compliance of the MAS therapy was best in patients with short maxilla and mandible, which should be taken into consideration when planning MAS therapy for OSA patients. Finally, a sleep study should be part of the follow-up in this patient population.

  10. Soft tissue profile changes following mandibular advancement surgery: predictability and long-term outcome.

    PubMed

    Mobarak, K A; Espeland, L; Krogstad, O; Lyberg, T

    2001-04-01

    The objectives of this cephalometric study were to assess long-term changes in the soft tissue profile following mandibular advancement surgery and to investigate the relationship between soft tissue and hard tissue movements. The sample consisted of 61 patients treated consecutively for mandibular retrognathism with orthodontic therapy combined with bilateral sagittal split osteotomy and rigid fixation. Lateral cephalograms were taken on 6 occasions: immediately before surgery, immediately after surgery, 2 and 6 months after surgery, and 1 and 3 years after surgery. Postsurgical changes in the upper and the lower lips and the mentolabial fold were more pronounced among low-angle cases compared with high-angle cases. In accordance with other studies, the soft tissue chin and the mentolabial fold were generally found to follow their underlying skeletal structures in a 1:1 ratio. Because of the strong influence skeletal relapse has on soft tissue profile changes, alternative ratios of soft tissue-to-hard tissue movement that accounted for mean relapse were also generated. It is suggested that if a more realistic long-term prediction of the postsurgical soft tissue profile is desirable, then ratios incorporating mean relapse should be used rather than estimates based on a 1:1 relationship.

  11. Accuracy of three-dimensional soft tissue predictions in orthognathic surgery after Le Fort I advancement osteotomies.

    PubMed

    Ullah, R; Turner, P J; Khambay, B S

    2015-02-01

    Prediction of postoperative facial appearance after orthognathic surgery can be used for communication, managing patients' expectations,avoiding postoperative dissatisfaction and exploring different treatment options. We have assessed the accuracy of 3dMD Vultus in predicting the final 3-dimensional soft tissue facial morphology after Le Fort I advancement osteotomy. We retrospectively studied 13 patients who were treated with a Le Fort I advancement osteotomy alone. We used routine cone-beam computed tomographic (CT) images taken immediately before and a minimum of 6 months after operation, and 3dMD Vultus to virtually reposition the preoperative maxilla and mandible in their post operative positions to generate a prediction of what the soft tissue would look like. Segmented anatomical areas of the predicted mesh were then compared with the actual soft tissue. The means of the absolute distance between the 90th percentile of the mesh points for each region were calculated, and a one-sample Student's t test was used to calculate if the difference differed significantly from 3 mm.The differences in the mean absolute distances between the actual soft tissue and the prediction were significantly below 3 mm for all segmented anatomical areas (p < 0.001), and ranged from 0.65 mm (chin) to 1.17 mm (upper lip). 3dMD Vultus produces clinically satisfactory 3-dimensional facial soft tissue predictions after Le Fort I advancement osteotomy. The mass-spring model for prediction seems to be able to predict the position of the lip and chin, but its ability to predict nasal and paranasal areas could be improved.

  12. APPLICATION OF ADVANCED IN VITRO TECHNIQUES TO MEASURE, UNDERSTAND AND PREDICT THE KINETICS AND MECHANISMS OF XENOBIOTIC METABOLISM

    EPA Science Inventory

    We have developed a research program in metabolism that involves numerous collaborators across EPA as well as other federal and academic labs. A primary goal is to develop and apply advanced in vitro techniques to measure, understand and predict the kinetics and mechanisms of xen...

  13. A risk score for the prediction of advanced age-related macular degeneration: Development and validation in 2 prospective cohorts

    Technology Transfer Automated Retrieval System (TEKTRAN)

    We aimed to develop an eye specific model which used readily available information to predict risk for advanced age-related macular degeneration (AMD). We used the Age-Related Eye Disease Study (AREDS) as our training dataset, which consisted of the 4,507 participants (contributing 1,185 affected v...

  14. Understanding hydrological extremes in the Anthropocene

    NASA Astrophysics Data System (ADS)

    Mård, Johanna; Di Baldassarre, Giuliano

    2016-04-01

    Hydrological extremes, from floods to droughts, pose one of the greatest challenges of the 21st century. Many of these challenges are associated with societal interactions with water, as people control or impact hydrological systems in a multitude of ways while they are also being affected and shaped by hydrological extremes, depending on their response to drought and flood events. However, the fact that the human and natural components of freshwater systems interact and co-evolve over time is often not taken into account. There is a need to study the two-way coupling between hydrology and society within a more comprehensive framework for hydrological extremes to anticipate future trajectories in a rapidly changing world. We present an interdisciplinary framework (and concepts) to identify internal controlling variables, processes and feedbacks, and the external system drivers and disturbances of the coupled human-water system with regard to hydrological extremes. To achieve this, the study (i) synthesizes existing research on coupled human-water system focusing on floods and droughts, (ii) analyzes hydrological extremes that have already occurred and their spatiotemporal patterns to investigate what patterns are observed in different regions of the world, and (iii) systematically describe the observed hydrological extremes, their causes and the interactions and feedbacks between hydrology and society. Advancing our understanding of mechanisms and feedbacks driving hydrological extremes is essential to better anticipate how the coupled human-water system will respond to future environmental change.

  15. Development of Computational Capabilities to Predict the Corrosion Wastage of Boiler Tubes in Advanced Combustion Systems

    SciTech Connect

    Kung, Steven; Rapp, Robert

    2014-08-31

    coal-fired boilers resulting from the coexistence of sulfur and chlorine in the fuel. A new corrosion mechanism, i.e., “Active Sulfidation Corrosion Mechanism,” has been proposed to account for the accelerated corrosion wastage observed on the furnace walls of utility boilers burning coals containing sulfur and chlorine. In addition, a second corrosion mechanism, i.e., “Active Sulfide-to-Oxide Corrosion Mechanism,” has been identified to account for the rapid corrosion attack on superheaters and reheaters. Both of the newly discovered corrosion mechanisms involve the formation of iron chloride (FeCl2) vapor from iron sulfide (FeS) and HCl, followed by the decomposition of FeCl2 via self-sustaining cycling reactions. For higher alloys containing sufficient chromium, the attack on superheaters and reheaters is dominated by Hot Corrosion in the presence of a fused salt. Furthermore, two stages of the hot corrosion mechanism have been identified and characterized in detail. The initiation of hot corrosion attack induced by molten sulfate leads to Stage 1 “acidic” fluxing and re-precipitation of the protective scale formed initially on the deposit-covered alloy surfaces. Once the protective scale is penetrated, Stage 2 Hot Corrosion is initiated, which is dominated by “basic” fluxing and re-precipitation of the scale in the fused salt. Based on the extensive corrosion information generated from this project, corrosion modeling was performed using non-linear regression analysis. As a result of the modeling efforts, two predictive equations have been formulated, one for furnace walls and the other for superheaters and reheaters. These first-of-the-kind equations can be used to estimate the corrosion rates of boiler tubes based on coal chemistry, alloy compositions, and boiler operating conditions for advanced boiler systems.

  16. Optimal Use Of Spatial Variability And Complex Dynamics In Hydrology: Are We There Yet?

    NASA Astrophysics Data System (ADS)

    Foufoula-Georgiou, Efi

    Hydrologic Science has witnessed significant technological advances over the last decade: many more observations have become available from remote sensors and computer power has quadrupled. One would expect then, that advances in hydrologic understanding and prediction accuracy have been commensurate with these develop- ments. But is this really so? Have we used the information empowerment with the same ingenuity as our predecessors showed to compensate for lack of information? They advanced conceptual modeling, lumped parameterization and calibration tech- niques to improve predictions. Have we, in turn, advanced our methodologies enough to deal with detailed information of process variability, interaction of processes across scales, complexity, and uncertainties? And equally important, do we have adequate methodologies to judge the degree of our progress? Hydrologic Science is now at the forefront of Earth Sciences. There are pressing questions for the new generation to ad- dress and new approaches to learning from data, modeling and assessing predictability might be in order. This talk will address some of these issues.

  17. Attribution of hydrologic trends using integrated hydrologic and economic models

    NASA Astrophysics Data System (ADS)

    Maneta, M. P.; Brugger, D. R.; Silverman, N. L.

    2014-12-01

    Hydrologic change has been detected in many regions of the world in the form of trends in annual streamflows, varying depths to the regional water table, or other alterations of the hydrologic balance. Most models used to investigate these changes implement sophisticated descriptions of the physical system but use simplified descriptions of the socioeconomic system. These simplifications come in the form of prescribed water diversions and land use change scenarios, which provide little insight into coupled natural-human systems and have limited predictive capabilities. We present an integrated model that adds realism to the description of the hydrologic system in agricultural regions by incorporating a component that updates the allocation of land and water to crops in response to hydroclimatic (water available) and economic conditions (prices of commodities and agricultural inputs). This component assumes that farmers allocate resources to maximize their net revenues, thus justifying the use of optimality conditions to constrain the parameters of an empirical production function that captures the economic behavior of farmers. Because the model internalizes the feedback between climate, agricultural markets, and farming activity into the hydrologic system, it can be used to understand to what extent human economic activity can exacerbate or buffer the regional hydrologic impacts of climate change in agricultural regions. It can also help in the attribution of causes of hydrologic change. These are important issues because local policy and management cannot solve climate change, but they can address land use and agricultural water use. We demonstrate the model in a case study.

  18. Interleukin-22 predicts severity and death in advanced liver cirrhosis: a prospective cohort study

    PubMed Central

    2012-01-01

    Background Interleukin-22 (IL-22), recently identified as a crucial parameter of pathology in experimental liver damage, may determine survival in clinical end-stage liver disease. Systematic analysis of serum IL-22 in relation to morbidity and mortality of patients with advanced liver cirrhosis has not been performed so far. Methods This is a prospective cohort study including 120 liver cirrhosis patients and 40 healthy donors to analyze systemic levels of IL-22 in relation to survival and hepatic complications. Results A total of 71% of patients displayed liver cirrhosis-related complications at study inclusion. A total of 23% of the patients died during a mean follow-up of 196 ± 165 days. Systemic IL-22 was detectable in 74% of patients but only in 10% of healthy donors (P < 0.001). Elevated levels of IL-22 were associated with ascites (P = 0.006), hepatorenal syndrome (P < 0.0001), and spontaneous bacterial peritonitis (P = 0.001). Patients with elevated IL-22 (>18 pg/ml, n = 57) showed significantly reduced survival compared to patients with regular (≤18 pg/ml) levels of IL-22 (321 days versus 526 days, P = 0.003). Other factors associated with reduced overall survival were high CRP (≥2.9 mg/dl, P = 0.005, hazard ratio (HR) 0.314, confidence interval (CI) (0.141 to 0.702)), elevated serum creatinine (P = 0.05, HR 0.453, CI (0.203 to 1.012)), presence of liver-related complications (P = 0.028, HR 0.258, CI (0.077 to 0.862)), model of end stage liver disease (MELD) score ≥20 (P = 0.017, HR 0.364, CI (0.159 to 0.835)) and age (P = 0.011, HR 0.955, CI (0.922 to 0.989)). Adjusted multivariate Cox proportional-hazards analysis identified elevated systemic IL-22 levels as independent predictors of reduced survival (P = 0.007, HR 0.218, CI (0.072 to 0.662)). Conclusions In patients with liver cirrhosis, elevated systemic IL-22 levels are predictive for reduced survival independently from age, liver-related complications, CRP, creatinine and the MELD score. Thus

  19. Testing earthquake prediction algorithms: Statistically significant advance prediction of the largest earthquakes in the Circum-Pacific, 1992-1997

    USGS Publications Warehouse

    Kossobokov, V.G.; Romashkova, L.L.; Keilis-Borok, V. I.; Healy, J.H.

    1999-01-01

    Algorithms M8 and MSc (i.e., the Mendocino Scenario) were used in a real-time intermediate-term research prediction of the strongest earthquakes in the Circum-Pacific seismic belt. Predictions are made by M8 first. Then, the areas of alarm are reduced by MSc at the cost that some earthquakes are missed in the second approximation of prediction. In 1992-1997, five earthquakes of magnitude 8 and above occurred in the test area: all of them were predicted by M8 and MSc identified correctly the locations of four of them. The space-time volume of the alarms is 36% and 18%, correspondingly, when estimated with a normalized product measure of empirical distribution of epicenters and uniform time. The statistical significance of the achieved results is beyond 99% both for M8 and MSc. For magnitude 7.5 + , 10 out of 19 earthquakes were predicted by M8 in 40% and five were predicted by M8-MSc in 13% of the total volume considered. This implies a significance level of 81% for M8 and 92% for M8-MSc. The lower significance levels might result from a global change in seismic regime in 1993-1996, when the rate of the largest events has doubled and all of them become exclusively normal or reversed faults. The predictions are fully reproducible; the algorithms M8 and MSc in complete formal definitions were published before we started our experiment [Keilis-Borok, V.I., Kossobokov, V.G., 1990. Premonitory activation of seismic flow: Algorithm M8, Phys. Earth and Planet. Inter. 61, 73-83; Kossobokov, V.G., Keilis-Borok, V.I., Smith, S.W., 1990. Localization of intermediate-term earthquake prediction, J. Geophys. Res., 95, 19763-19772; Healy, J.H., Kossobokov, V.G., Dewey, J.W., 1992. A test to evaluate the earthquake prediction algorithm, M8. U.S. Geol. Surv. OFR 92-401]. M8 is available from the IASPEI Software Library [Healy, J.H., Keilis-Borok, V.I., Lee, W.H.K. (Eds.), 1997. Algorithms for Earthquake Statistics and Prediction, Vol. 6. IASPEI Software Library]. ?? 1999 Elsevier

  20. Hydrologic Observatories: Design, Operation, and the Neuse Basin Prototype

    NASA Astrophysics Data System (ADS)

    Reckhow, K.; Band, L.

    2003-12-01

    Hydrologic observatories are conceived as major research facilities that will be available to the full hydrologic community, to facilitate comprehensive, cross-disciplinary and multi-scale measurements necessary to address the current and next generation of critical science and management issues. A network of hydrologic observatories is proposed that both develop national comparable, multidisciplinary data sets and provide study areas to allow scientists, through their own creativity, to make scientific breakthroughs that would be impossible without the proposed observatories. The core objective of an observatory is to improve predictive understanding of the flow paths, fluxes, and residence times of water, sediment and nutrients (the "core data") across a range of spatial and temporal scales across `interfaces'. To assess attainment of this objective, a benchmark will be established in the first year, and evaluated periodically. The benchmark should provide an estimate of prediction uncertainty at points in the stream across scale; the general principle is that predictive understanding must be demonstrated internal to the catchment as well as its outlet. The core data will be needed for practically any hydrologic study, yet absence of these data has been a barrier to larger scale studies in the past. However, advancement of hydrologic science facilitated by the network of hydrologic observatories is expected to focus on a set of science drivers, drawn from the major scientific questions posed by the set of NRC reports and refined into CUAHSI themes. These hypotheses will be tested at all observatories and will be used in the design to ensure the sufficiency of the data set. To make the observatories a national (and international) resource, a key aspect of the operation is the support of remote PI's. This support will include a resident staff of scientists and technicians on the order of 10 FTE's, availability of dormitory, laboratory, workshop space for all

  1. Advancing the predictive capability for pedestal structure through experiment and modeling

    NASA Astrophysics Data System (ADS)

    Hughes, Jerry

    2012-10-01

    Prospects for predictive capability of the edge pedestal in magnetic fusion devices have been dramatically enhanced due to recent research, which was conducted jointly by the US experimental and theory communities. Studies on the C-Mod, DIII-D and NSTX devices have revealed common features, including an upper limit on pedestal pressure in ELMy H-mode determined by instability to peeling-ballooning modes (PBMs), and pedestal width which scales approximately as βpol^1/2. The width dependence is consistent with a pedestal regulated by kinetic ballooning modes (KBMs). Signatures of KBMs have been actively sought both in experimental fluctuation measurements and in gyrokinetic simulations of the pedestal, with encouraging results. Studies of the temporal evolution of the pedestal during the ELM cycle reveal a tendency for the pressure gradient to saturate in advance of the ELM, with a steady growth in the pedestal width occurring prior to the ELM crash, which further supports a model for KBMs and PBMs working together to set the pedestal structure. Such a model, EPED, reproduces the pedestal height and width to better than 20% accuracy on existing devices over a range of more than 20 in pedestal pressure. Additional transport processes are assessed for their impact on pedestal structure, in particular the relative variation of the temperature and density pedestals due, for example, to differences in edge neutral sources. Such differences are observed in dimensionlessly matched discharges on C-Mod and DIII-D, despite their having similar calculated MHD stability and similar edge fluctuations. In certain high performance discharges, such as EDA H-mode, QH-mode and I-mode, pedestal relaxation is accomplished by continuous edge fluctuations, avoiding peeling-ballooning instabilities and associated ELMs. Progress in understanding these regimes will be reported.

  2. Hydrologic Design in the Anthropocene

    NASA Astrophysics Data System (ADS)

    Vogel, R. M.; Farmer, W. H.; Read, L.

    2014-12-01

    In an era dubbed the Anthropocene, the natural world is being transformed by a myriad of human influences. As anthropogenic impacts permeate hydrologic systems, hydrologists are challenged to fully account for such changes and develop new methods of hydrologic design. Deterministic watershed models (DWM), which can account for the impacts of changes in land use, climate and infrastructure, are becoming increasing popular for the design of flood and/or drought protection measures. As with all models that are calibrated to existing datasets, DWMs are subject to model error or uncertainty. In practice, the model error component of DWM predictions is typically ignored yet DWM simulations which ignore model error produce model output which cannot reproduce the statistical properties of the observations they are intended to replicate. In the context of hydrologic design, we demonstrate how ignoring model error can lead to systematic downward bias in flood quantiles, upward bias in drought quantiles and upward bias in water supply yields. By reincorporating model error, we document how DWM models can be used to generate results that mimic actual observations and preserve their statistical behavior. In addition to use of DWM for improved predictions in a changing world, improved communication of the risk and reliability is also needed. Traditional statements of risk and reliability in hydrologic design have been characterized by return periods, but such statements often assume that the annual probability of experiencing a design event remains constant throughout the project horizon. We document the general impact of nonstationarity on the average return period and reliability in the context of hydrologic design. Our analyses reveal that return periods do not provide meaningful expressions of the likelihood of future hydrologic events. Instead, knowledge of system reliability over future planning horizons can more effectively prepare society and communicate the likelihood

  3. Comparison of global optimization approaches for robust calibration of hydrologic model parameters

    NASA Astrophysics Data System (ADS)

    Jung, I. W.

    2015-12-01

    Robustness of the calibrated parameters of hydrologic models is necessary to provide a reliable prediction of future performance of watershed behavior under varying climate conditions. This study investigated calibration performances according to the length of calibration period, objective functions, hydrologic model structures and optimization methods. To do this, the combination of three global optimization methods (i.e. SCE-UA, Micro-GA, and DREAM) and four hydrologic models (i.e. SAC-SMA, GR4J, HBV, and PRMS) was tested with different calibration periods and objective functions. Our results showed that three global optimization methods provided close calibration performances under different calibration periods, objective functions, and hydrologic models. However, using the agreement of index, normalized root mean square error, Nash-Sutcliffe efficiency as the objective function showed better performance than using correlation coefficient and percent bias. Calibration performances according to different calibration periods from one year to seven years were hard to generalize because four hydrologic models have different levels of complexity and different years have different information content of hydrological observation. Acknowledgements This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

  4. Early skin toxicity predicts better outcomes, and early tumor shrinkage predicts better response after cetuximab treatment in advanced colorectal cancer.

    PubMed

    Kogawa, T; Doi, A; Shimokawa, M; Fouad, T M; Osuga, T; Tamura, F; Mizushima, T; Kimura, T; Abe, S; Ihara, H; Kukitsu, T; Sumiyoshi, T; Yoshizaki, N; Hirayama, M; Sasaki, T; Kawarada, Y; Kitashiro, S; Okushiba, S; Kondo, H; Tsuji, Y

    2015-03-01

    Cetuximab-containing treatments for metastatic colorectal cancer have been shown to have higher overall response rates and longer progression-free and overall survival than other systemic therapies. Cetuximab-related manifestations, including severe skin toxicity and early tumor shrinkage, have been shown to be predictors of response to cetuximab. We hypothesized that early skin toxicity is a predictor of response and better outcomes in patients with advanced colorectal carcinoma. We retrospectively evaluated 62 patients with colorectal adenocarcinoma who had unresectable tumors and were treated with cetuximab in our institution. Skin toxicity grade was evaluated on each treatment day. Tumor size was evaluated using computed tomography prior to treatment and 4-8 weeks after the start of treatment with cetuximab.Patients with early tumor shrinkage after starting treatment with cetuximab had a significantly higher overall response rate (P = 0.0001). Patients with early skin toxicity showed significantly longer overall survival (P = 0.0305), and patients with higher skin toxicity grades had longer progression-free survival (P = 0.0168).We have shown that early tumor shrinkage, early onset of skin toxicity, and high skin toxicity grade are predictors of treatment efficacy and/or outcome in patients with advanced colorectal carcinoma treated with cetuximab.

  5. Hydrologic applications of weather radar

    NASA Astrophysics Data System (ADS)

    Seo, Dong-Jun; Habib, Emad; Andrieu, Hervé; Morin, Efrat

    2015-12-01

    By providing high-resolution quantitative precipitation information (QPI), weather radars have revolutionized hydrology in the last two decades. With the aid of GIS technology, radar-based quantitative precipitation estimates (QPE) have enabled routine high-resolution hydrologic modeling in many parts of the world. Given the ever-increasing need for higher-resolution hydrologic and water resources information for a wide range of applications, one may expect that the use of weather radar will only grow. Despite the tremendous progress, a number of significant scientific, technological and engineering challenges remain to realize its potential. New challenges are also emerging as new areas of applications are discovered, explored and pursued. The purpose of this special issue is to provide the readership with some of the latest advances, lessons learned, experiences gained, and science issues and challenges related to hydrologic applications of weather radar. The special issue features 20 contributions on various topics which reflect the increasing diversity as well as the areas of focus in radar hydrology today. The contributions may be grouped as follows: Radar QPE (Kwon et al.; Hall et al.; Chen and Chandrasekar; Seo and Krajewski; Sandford).

  6. Grid computing technology for hydrological applications

    NASA Astrophysics Data System (ADS)

    Lecca, G.; Petitdidier, M.; Hluchy, L.; Ivanovic, M.; Kussul, N.; Ray, N.; Thieron, V.

    2011-06-01

    SummaryAdvances in e-Infrastructure promise to revolutionize sensing systems and the way in which data are collected and assimilated, and complex water systems are simulated and visualized. According to the EU Infrastructure 2010 work-programme, data and compute infrastructures and their underlying technologies, either oriented to tackle scientific challenges or complex problem solving in engineering, are expected to converge together into the so-called knowledge infrastructures, leading to a more effective research, education and innovation in the next decade and beyond. Grid technology is recognized as a fundamental component of e-Infrastructures. Nevertheless, this emerging paradigm highlights several topics, including data management, algorithm optimization, security, performance (speed, throughput, bandwidth, etc.), and scientific cooperation and collaboration issues that require further examination to fully exploit it and to better inform future research policies. The paper illustrates the results of six different surface and subsurface hydrology applications that have been deployed on the Grid. All the applications aim to answer to strong requirements from the Civil Society at large, relatively to natural and anthropogenic risks. Grid technology has been successfully tested to improve flood prediction, groundwater resources management and Black Sea hydrological survey, by providing large computing resources. It is also shown that Grid technology facilitates e-cooperation among partners by means of services for authentication and authorization, seamless access to distributed data sources, data protection and access right, and standardization.

  7. The predictive value of MRI in detecting thyroid gland invasion in patients with advanced laryngeal or hypopharyngeal carcinoma.

    PubMed

    Lin, Peiliang; Huang, Xiaoming; Zheng, Chushan; Cai, Qian; Guan, Zhong; Liang, Faya; Zheng, Yiqing

    2017-01-01

    The aim of this study was to evaluate the predictive value of magnetic resonance imaging (MRI) in detecting thyroid gland invasion (TGI) in patients with advanced laryngeal or hypopharyngeal carcinoma. In a retrospective chart review, 41 patients with advanced laryngeal or hypopharyngeal carcinoma underwent MRI scan before total laryngectomy and ipsilateral or bilateral thyroidectomy during the past 5 years. The MRI findings were compared with the postoperative pathological results. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were calculated. Among the 41 patients, 3 had thyroid gland invasion in postoperative pathological results. MRI correctly predicted the absence of TGI in 37 of 38 patients and TGI in all 3 patients. The sensitivity, specificity, PPV, and NPV of MRI were 100.0, 97.4, 75.0, and 100 %, respectively, with the diagnostic accuracy of 97.6 %. In consideration of the high negative predictive value of MRI, it may help surgeons selectively preserve thyroid gland in total laryngectomy and reduce the incidence of hypothyroidism and hypoparathyroidism postoperatively.

  8. Predicted reliability of aerospace electronics: Application of two advanced probabilistic concepts

    NASA Astrophysics Data System (ADS)

    Suhir, E.

    Two advanced probabilistic design-for-reliability (PDfR) concepts are addressed and discussed in application to the prediction, quantification and assurance of the aerospace electronics reliability: 1) Boltzmann-Arrhenius-Zhurkov (BAZ) model, which is an extension of the currently widely used Arrhenius model and, in combination with the exponential law of reliability, enables one to obtain a simple, easy-to-use and physically meaningful formula for the evaluation of the probability of failure (PoF) of a material or a device after the given time in operation at the given temperature and under the given stress (not necessarily mechanical), and 2) Extreme Value Distribution (EVD) technique that can be used to assess the number of repetitive loadings that result in the material/device degradation and eventually lead to its failure by closing, in a step-wise fashion, the gap between the bearing capacity (stress-free activation energy) of the material or the device and the demand (loading). It is shown that the material degradation (aging, damage accumulation, flaw propagation, etc.) can be viewed, when BAZ model is considered, as a Markovian process, and that the BAZ model can be obtained as the ultimate steady-state solution to the well-known Fokker-Planck equation in the theory of Markovian processes. It is shown also that the BAZ model addresses the worst, but a reasonably conservative, situation. It is suggested therefore that the transient period preceding the condition addressed by the steady-state BAZ model need not be accounted for in engineering evaluations. However, when there is an interest in understanding the transient degradation process, the obtained solution to the Fokker-Planck equation can be used for this purpose. As to the EVD concept, it attributes the degradation process to the accumulation of damages caused by a train of repetitive high-level loadings, while loadings of levels that are considerably lower than their extreme values do not contribute

  9. Prediction of helicopter rotor discrete frequency noise: A computer program incorporating realistic blade motions and advanced acoustic formulation

    NASA Technical Reports Server (NTRS)

    Brentner, K. S.

    1986-01-01

    A computer program has been developed at the Langley Research Center to predict the discrete frequency noise of conventional and advanced helicopter rotors. The program, called WOPWOP, uses the most advanced subsonic formulation of Farassat that is less sensitive to errors and is valid for nearly all helicopter rotor geometries and flight conditions. A brief derivation of the acoustic formulation is presented along with a discussion of the numerical implementation of the formulation. The computer program uses realistic helicopter blade motion and aerodynamic loadings, input by the user, for noise calculation in the time domain. A detailed definition of all the input variables, default values, and output data is included. A comparison with experimental data shows good agreement between prediction and experiment; however, accurate aerodynamic loading is needed.

  10. Predicting Violence Among Forensic-Correctional Populations: The Past 2 Decades of Advancements and Future Endeavors

    ERIC Educational Resources Information Center

    Loza, Wagdy; Dhaliwal, Gurmeet K.

    2005-01-01

    Research on violence prediction during the past 2 decades has evolved appreciably in terms of depicting determinants of violence and developing psychometrically sound actuarial measures to predict the probability of future violent behavior. This article provides a brief synopsis of information on predicting violence gained in the past 2 decades,…

  11. Characterizing the Hypermutated Subtype of Advanced Prostate Cancer as a Predictive Biomarker for Precision Medicine

    DTIC Science & Technology

    2015-10-01

    hypermutated advanced prostate cancers. Using a targeted deep sequencing assay that includes intronic and flanking regions we discovered DNA mismatch...subtype of advanced prostate cancer, most likely mutations in DNA mismatch repair genes. To test this hypothesis we performed targeted deep ...have adapted the mSINGS method to both the BROCA and UW-OncoPlex genomic deep sequencing platforms to accurately detect both phenotypic MSI and

  12. Nonstationary Approaches to Hydrologic Design

    NASA Astrophysics Data System (ADS)

    Vogel, Richard; Hecht, Jory; Read, Laura

    2014-05-01

    We introduce a generalized framework for evaluating the risk, reliability and return period of hydrologic events in a nonstationary world. A heteroscedastic regression model is introduced as an elegant and general framework for modeling trends in the mean and/or variance of hydrologic records using ordinary least squares regression methods. A regression approach to modeling trends has numerous advantages over other methods including: (1) ease of application, (2) considers linear or nonlinear trends, (3) graphical display of trends, (4) analytical estimate of the power of the trend test and prediction intervals associated with trend extrapolation. Traditional statements of risk, reliability and return periods which assume that the annual probability of a flood event remains constant throughout the project horizon are revised to include the impacts of trends in the mean and/or variance of hydrologic records. Our analyses reveal that in a nonstationary world, meaningful expressions of the likelihood of future hydrologic events are unlikely to result from knowledge of return periods whereas knowledge of system reliability over future planning horizons can effectively communicate the likelihood of future hydrologic events of interest.

  13. Towards tracer-aided spatially distributed models of catchment storage and mixing to predict non-stationary hydrologic and biogeochemical response

    NASA Astrophysics Data System (ADS)

    Soulsby, Chris; van Huijgevoort, Marjolein; Dick, Jonathan; Birkel, Christian; Tetzlaff, Doerthe

    2016-04-01

    To develop a spatially distributed understanding of the linkages between storage dynamics, mixing processes and non-stationary watershed response we have used diverse, intensive data sets collected in a small montane catchment to both inform and test hydrological and water quality models. At the core of these efforts has been the use of ~6 years of daily isotope data in precipitation and stream flow to inform the calibration and testing of coupled flow-tracer models that constrain storage estimates, mixing processes and hydrologic fluxes in the dominant landscape units as well as simulating discharge and stream isotopes. LiDAR surveys have been used to extend this approach using a high resolution DTM to facilitate a Spatially distributed Tracer-Aided Rainfall-Runoff model (STARR). This provides a flexible, generic approach that allows us to track and visualise aggregated storage changes, mixing processes, and the fluxes and age distribution of water across spatio-temporal scales. The modelling framework provides a basis for assessing the effects of hydroclimatic variability on the non-stationary nature of catchment hydrological function by simulating the spatial variation in tracer composition of different source waters and flow paths. This is tested against extensive (over 120 sites) synoptic surveys of multiple-tracers in soil water, groundwater and stream water repeated under contrasting states of catchment storage when different flow paths are activated. The modelling approach can reproduce the major spatio-temporal differences in isotopes, dissolved organic (DOC) and alkalinity reasonably well and thus, has potential to be adapted for biogeochemical modelling. This potential is explored in relation to daily DOC simulations over prolonged (2 year) periods. The transferability of the modelling approach to other sites is also tested.

  14. How to predict hydrological effects of local land use change: how the vegetation parameterisation for short rotation coppices influences model results

    NASA Astrophysics Data System (ADS)

    Richter, F.; Döring, C.; Jansen, M.; Panferov, O.; Spank, U.; Bernhofer, C.

    2015-01-01

    Among the different bioenergy sources short rotation coppices (SRC) with poplar and willow trees are one of the mostly promising options in Europe. SRC not only provide woody biomass, but often additional ecosystem services. One known shortcoming is the possible negative effect on groundwater recharge, caused by potentially higher rates of evapotranspiration compared to annual crops. An assessment of land use change by means of hydrological models and taking into account the changing climate can help to minimize negative and maximize positive ecological effects at regional and local scales, e.g. to regional climate and/or to adjacent ecosystems. The present study implemented the hydrological model system WaSim for such assessment. The hydrological analysis requires the adequate description of the vegetation cover to simulate the processes like soil evaporation, interception evaporation and transpiration. The uncertainties in the vegetation parameterisations might result in implausible model results. The present study shows that leaf area index (LAI), stomatal resistance (Rsc) as well as the beginning and length of the growing season are the sensitive parameters when investigating the effects of an enhanced cultivation of SRC on water budget or on groundwater recharge. Mostly sensitive is the description of the beginning of the growing season. When this estimation is wrong, the accuracy of LAI and Rsc description plays a minor role. The analyses done here illustrate that the use of locally measured vegetation parameters like maximal LAI and meteorological variables like air temperature, to estimate the beginning of the growing season, produce better results than literature data or data from remote network stations. However the direct implementation of locally measured or literature data on e.g. stomatal resistance is not always advisable. The adjustment of locally vegetation parameterisation shows the best model evaluation. Additionally the adjusted course of LAI

  15. Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

    NASA Technical Reports Server (NTRS)

    Wilson, Scott D.; Reid, Terry; Schifer, Nicholas; Briggs, Maxwell

    2011-01-01

    Past methods of predicting net heat input needed to be validated. Validation effort pursued with several paths including improving model inputs, using test hardware to provide validation data, and validating high fidelity models. Validation test hardware provided direct measurement of net heat input for comparison to predicted values. Predicted value of net heat input was 1.7 percent less than measured value and initial calculations of measurement uncertainty were 2.1 percent (under review). Lessons learned during validation effort were incorporated into convertor modeling approach which improved predictions of convertor efficiency.

  16. Hydrologic modeling in a marsh-mangrove ecotone: Predicting wetland surface water and salinity response to restoration in the Ten Thousand Islands region of Florida, USA

    USGS Publications Warehouse

    Michot, B.D.; Meselhe, E.A.; Krauss, Ken W.; Shrestha, Surendra; From, Andrew S.; Patino, Eduardo

    2017-01-01

    At the fringe of Everglades National Park in southwest Florida, United States, the Ten Thousand Islands National Wildlife Refuge (TTINWR) habitat has been heavily affected by the disruption of natural freshwater flow across the Tamiami Trail (U.S. Highway 41). As the Comprehensive Everglades Restoration Plan (CERP) proposes to restore the natural sheet flow from the Picayune Strand Restoration Project area north of the highway, the impact of planned measures on the hydrology in the refuge needs to be taken into account. The objective of this study was to develop a simple, computationally efficient mass balance model to simulate the spatial and temporal patterns of water level and salinity within the area of interest. This model could be used to assess the effects of the proposed management decisions on the surface water hydrological characteristics of the refuge. Surface water variations are critical to the maintenance of wetland processes. The model domain is divided into 10 compartments on the basis of their shared topography, vegetation, and hydrologic characteristics. A diversion of +10% of the discharge recorded during the modeling period was simulated in the primary canal draining the Picayune Strand forest north of the Tamiami Trail (Faka Union Canal) and this discharge was distributed as overland flow through the refuge area. Water depths were affected only modestly. However, in the northern part of the refuge, the hydroperiod, i.e., the duration of seasonal flooding, was increased by 21 days (from 115 to 136 days) for the simulation during the 2008 wet season, with an average water level rise of 0.06 m. The average salinity over a two-year period in the model area just south of Tamiami Trail was reduced by approximately 8 practical salinity units (psu) (from 18 to 10 psu), whereas the peak dry season average was reduced from 35 to 29 psu (by 17%). These salinity reductions were even larger with greater flow diversions (+20%). Naturally, the reduction

  17. Advanced Methods for Determining Prediction Uncertainty in Model-Based Prognostics with Application to Planetary Rovers

    NASA Technical Reports Server (NTRS)

    Daigle, Matthew J.; Sankararaman, Shankar

    2013-01-01

    Prognostics is centered on predicting the time of and time until adverse events in components, subsystems, and systems. It typically involves both a state estimation phase, in which the current health state of a system is identified, and a prediction phase, in which the state is projected forward in time. Since prognostics is mainly a prediction problem, prognostic approaches cannot avoid uncertainty, which arises due to several sources. Prognostics algorithms must both characterize this uncertainty and incorporate it into the predictions so that informed decisions can be made about the system. In this paper, we describe three methods to solve these problems, including Monte Carlo-, unscented transform-, and first-order reliability-based methods. Using a planetary rover as a case study, we demonstrate and compare the different methods in simulation for battery end-of-discharge prediction.

  18. Novel Pretreatment Scoring Incorporating C-reactive Protein to Predict Overall Survival in Advanced Hepatocellular Carcinoma with Sorafenib Treatment

    PubMed Central

    Nakanishi, Hiroyuki; Kurosaki, Masayuki; Tsuchiya, Kaoru; Yasui, Yutaka; Higuchi, Mayu; Yoshida, Tsubasa; Komiyama, Yasuyuki; Takaura, Kenta; Hayashi, Tsuguru; Kuwabara, Konomi; Nakakuki, Natsuko; Takada, Hitomi; Ueda, Masako; Tamaki, Nobuharu; Suzuki, Shoko; Itakura, Jun; Takahashi, Yuka; Izumi, Namiki

    2016-01-01

    Objectives This study aimed to build a prediction score of prognosis for patients with advanced hepatocellular carcinoma (HCC) after sorafenib treatment. Methods A total of 165 patients with advanced HCC who were treated with sorafenib were analyzed. Readily available baseline factors were used to establish a scoring system for the prediction of survival. Results The median survival time (MST) was 14.2 months. The independent prognostic factors were C-reactive protein (CRP) <1.0 mg/dL [hazard ratio (HR) =0.51], albumin >3.5 g/dL (HR =0.55), alpha-fetoprotein <200 ng/mL (HR =0.45), and a lack of major vascular invasion (HR =0.39). Each of these factors had a score of 1, and after classifying the patients into five groups, the total scores ranged from 0 to 4. Higher scores were linked to significantly longer survival (p<0.0001). Twenty-nine patients (17.6%) with a score of 4 had a MST as long as 36.5 months, whereas MST was as short as 2.4 and 3.7 months for seven (4.2%) and 22 (13.3%) patients with scores of 0 and 1, respectively. Conclusions A novel prognostic scoring system, which includes the CRP level, has the ability to stratify the prognosis of patients with advanced stage HCC after treatment with sorafenib. PMID:27781198

  19. CLEANER-Hydrologic Observatory Joint Science Plan

    NASA Astrophysics Data System (ADS)

    Welty, C.; Dressler, K.; Hooper, R.

    2005-12-01

    The CLEANER-Hydrologic Observatory* initiative is a distributed network for research on complex environmental systems that focuses on the intersecting water-related issues of both the CUAHSI and CLEANER communities. It emphasizes research on the nation's water resources related to human-dominated natural and built environments. The network will be comprised of: interacting field sites with an integrated cyberinfrastructure; a centralized technical resource staff and management infrastructure to support interdisciplinary research through data collection from advanced sensor systems, data mining and aggregation from multiple sources and databases; cyber-tools for analysis, visualization, and predictive multi-scale modeling that is dynamically driven. As such, the network will transform 21st century workforce development in the water-related intersection of environmental science and engineering, as well as enable substantial educational and engagement opportunities for all age levels. The scientific goal and strategic intent of the CLEANER-Hydrologic Observatory Network is to transform our understanding of the earth's water cycle and associated biogeochemical cycles across spatial and temporal scales-enabling quantitative forecasts of critical water-related processes, especially those that affect and are affected by human activities. This strategy will develop scientific and engineering tools that will enable more effective adaptive approaches for resource management. The need for the network is based on three critical deficiencies in current abilities to understand large-scale environmental processes and thereby develop more effective management strategies. First we lack basic data and the infrastructure to collect them at the needed resolution. Second, we lack the means to integrate data across scales from different media (paper records, electronic worksheets, web-based) and sources (observations, experiments, simulations). Third, we lack sufficiently accurate

  20. How the Young Hydrologic Society can rejuvenate hydrology

    NASA Astrophysics Data System (ADS)

    van Emmerik, T. H.; Berghuijs, W. R.; Smoorenburg, M.; Harrigan, S.; Muller, H.; Dugge, J.

    2013-12-01

    The hydrologic community aims to understand the complex movement, distribution and quality of water around the world. Especially with climate change, suppressed food security and environmental degradation, hydrologists play an important role in sustainable water resources management. To achieve this, worldwide collaboration between researchers is a crucial necessity. For example, IAHS' "Predictions in Ungauged Basins (PUB)" and "Panta Rei" initiatives have shown that working together leads to fruitful results. However, hydrology struggles to unify, with its different research perspectives, myriad of organizations and diverse array of focus areas. Furthermore, within the active hydrologic community, young scientists are underrepresented and often not well connected. Active involvement of those who will deal with tomorrow's water issues is the key to building bridges between generations and the variety of hydrologic research fields. Therefore, the Young Hydrologic Society (YHS) was founded with the following goal: 'Bringing young scientists from around the world together to contribute to the scientific and organizational unification of the global hydrologic community' To realize this, YHS has set itself 4 main objectives: - Function as the link between existing and future student initiatives within the major organizations (e.g. EGU, AGU, IAHS, etc.), - Connect early career scientists (e.g. MSc, PhD, Post-Doc) at an early stage in their career, - Stimulate bottom-up research initiatives, - Create a voice of the young hydrologists in the global scientific debate. YHS is already supported by some of the world's most prominent hydrologists and organizations. But, to make YHS a real success, we need you to spread the word and get involved in the YHS initiative. Get connected, get inspired and get involved!

  1. Predicting SAT Performance from Advanced Course Content and Timing of Matriculation

    ERIC Educational Resources Information Center

    Patterson, Jonathan Sparks

    2012-01-01

    As record numbers of students are applying to selective colleges and universities, students are attempting to set themselves apart from their peers by taking rigorous advanced courses in high school. The race for improving a student's academic record has resulted in more and more students taking these courses earlier and earlier in their high…

  2. Earthquake prediction

    NASA Technical Reports Server (NTRS)

    Turcotte, Donald L.

    1991-01-01

    The state of the art in earthquake prediction is discussed. Short-term prediction based on seismic precursors, changes in the ratio of compressional velocity to shear velocity, tilt and strain precursors, electromagnetic precursors, hydrologic phenomena, chemical monitors, and animal behavior is examined. Seismic hazard assessment is addressed, and the applications of dynamical systems to earthquake prediction are discussed.

  3. Understanding, management and modelling of urban hydrology and its consequences for receiving waters: A state of the art

    NASA Astrophysics Data System (ADS)

    Fletcher, T. D.; Andrieu, H.; Hamel, P.

    2013-01-01

    Urban hydrology has evolved to improve the way urban runoff is managed for flood protection, public health and environmental protection. There have been significant recent advances in the measurement and prediction of urban rainfall, with technologies such as radar and microwave networks showing promise. The ability to predict urban hydrology has also evolved, to deliver models suited to the small temporal and spatial scales typical of urban and peri-urban applications. Urban stormwater management increasingly consider the needs of receiving environments as well as those of humans. There is a clear trend towards approaches that attempt to restore pre-development flow-regimes and water quality, with an increasing recognition that restoring a more natural water balance benefits not only the environment, but enhances the liveability of the urban landscape. Once regarded only as a nuisance, stormwater is now increasingly regarded as a resource. Despite the advances, many important challenges in urban hydrology remain. Further research into the spatio-temporal dynamics of urban rainfall is required to improve short-term rainfall prediction. The performance of stormwater technologies in restoring the water balance and in removing emerging priority pollutants remain poorly quantified. All of these challenges are overlaid by the uncertainty of climate change, which imposes a requirement to ensure that stormwater management systems are adaptable and resilient to changes. Urban hydrology will play a critical role in addressing these challenges.

  4. Advances and Challenges In Uncertainty Quantification with Application to Climate Prediction, ICF design and Science Stockpile Stewardship

    NASA Astrophysics Data System (ADS)

    Klein, R.; Woodward, C. S.; Johannesson, G.; Domyancic, D.; Covey, C. C.; Lucas, D. D.

    2012-12-01

    Uncertainty Quantification (UQ) is a critical field within 21st century simulation science that resides at the very center of the web of emerging predictive capabilities. The science of UQ holds the promise of giving much greater meaning to the results of complex large-scale simulations, allowing for quantifying and bounding uncertainties. This powerful capability will yield new insights into scientific predictions (e.g. Climate) of great impact on both national and international arenas, allow informed decisions on the design of critical experiments (e.g. ICF capsule design, MFE, NE) in many scientific fields, and assign confidence bounds to scientifically predictable outcomes (e.g. nuclear weapons design). In this talk I will discuss a major new strategic initiative (SI) we have developed at Lawrence Livermore National Laboratory to advance the science of Uncertainty Quantification at LLNL focusing in particular on (a) the research and development of new algorithms and methodologies of UQ as applied to multi-physics multi-scale codes, (b) incorporation of these advancements into a global UQ Pipeline (i.e. a computational superstructure) that will simplify user access to sophisticated tools for UQ studies as well as act as a self-guided, self-adapting UQ engine for UQ studies on extreme computing platforms and (c) use laboratory applications as a test bed for new algorithms and methodologies. The initial SI focus has been on applications for the quantification of uncertainty associated with Climate prediction, but the validated UQ methodologies we have developed are now being fed back into Science Based Stockpile Stewardship (SSS) and ICF UQ efforts. To make advancements in several of these UQ grand challenges, I will focus in talk on the following three research areas in our Strategic Initiative: Error Estimation in multi-physics and multi-scale codes ; Tackling the "Curse of High Dimensionality"; and development of an advanced UQ Computational Pipeline to enable

  5. Ideal MHD Stability Prediction and Required Power for EAST Advanced Scenario

    NASA Astrophysics Data System (ADS)

    Chen, Junjie; Li, Guoqiang; Qian, Jinping; Liu, Zixi

    2012-11-01

    The Experimental Advanced Superconducting Tokamak (EAST) is the first fully superconducting tokamak with a D-shaped cross-sectional plasma presently in operation. The ideal magnetohydrodynamic (MHD) stability and required power for the EAST advanced tokamak (AT) scenario with negative central shear and double transport barrier (DTB) are investigated. With the equilibrium code TOQ and stability code GATO, the ideal MHD stability is analyzed. It is shown that a moderate ratio of edge transport barriers' (ETB) height to internal transport barriers' (ITBs) height is beneficial to ideal MHD stability. The normalized beta βN limit is about 2.20 (without wall) and 3.70 (with ideal wall). With the scaling law of energy confinement time, the required heating power for EAST AT scenario is calculated. The total heating power Pt increases as the toroidal magnetic field BT or the normalized beta βN is increased.

  6. Application of Advanced Methods to Predict Grid to Rod Fretting in PWRs

    SciTech Connect

    Karoutas, Zeses; Roger, Lu Y.; Yan, J.; Krammen, M.A.; Sham, Sam

    2012-01-01

    Advanced modeling and simulation methods are being developed as part of the US Department of Energy sponsored Nuclear Energy Modeling and Simulation Hub called CASL (Consortium for Advanced Simulation of LWRs). The key participants of the CASL team include Oak Ridge National Laboratory (lead), Idaho National Laboratory, Sandia National Laboratories, Los Alamos National Laboratory, Massachusetts Institute of Technology, North Carolina State University, University of Michigan, Electric Power Research Institute, Tennessee Valley Authority and Westinghouse Electric Corporation. One of the key objectives of the CASL program is to develop multi-physics methods and tools which evaluate neutronic, thermal-hydraulic, structural mechanics and nuclear fuel rod performance in rod bundles to support power uprates, increased burnup/cycle length and life extension for US nuclear plants.

  7. Introduction to hydrology

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Hydrology deals with the occurrence, movement, and storage of water in the Earth system. Hydrologic science comprises understanding the underlying physical and stochastic processes involved and estimating the quantity and quality of water in the various phases and stores. The study of hydrology als...

  8. Advancing viral RNA structure prediction: measuring the thermodynamics of pyrimidine-rich internal loops.

    PubMed

    Phan, Andy; Mailey, Katherine; Sakai, Jessica; Gu, Xiaobo; Schroeder, Susan J

    2017-02-17

    Accurate thermodynamic parameters improve RNA structure predictions and thus accelerate understanding of RNA function and the identification of RNA drug binding sites. Many viral RNA structures, such as internal ribosome entry sites, have internal loops and bulges that are potential drug target sites. Current models used to predict internal loops are biased towards small, symmetric purine loops, and thus poorly predict asymmetric, pyrimidine-rich loops with more than 6 nucleotides that occur frequently in viral RNA. This paper presents new thermodynamic data for 40 pyrimidine loops, many of which can form UU or protonated CC base pairs. Protonated cytosine and uracil base pairs stabilize asymmetric internal loops. Accurate prediction rules are presented that account for all thermodynamic measurements of RNA asymmetric internal loops. New loop initiation terms for loops with more than 6 nucleotides are presented that do not follow previous assumptions that increasing asymmetry destabilizes loops. Since the last 2004 update, 126 new loops with asymmetry or sizes greater than 2x2 have been measured (Mathews 2004). These new measurements significantly deepen and diversify the thermodynamic database for RNA. These results will help better predict internal loops that are larger, pyrimidine-rich, and occur within viral structures such as internal ribosome entry sites.

  9. Advanced validation of CFD-FDTD combined method using highly applicable solver for reentry blackout prediction

    NASA Astrophysics Data System (ADS)

    Takahashi, Yusuke

    2016-01-01

    An analysis model of plasma flow and electromagnetic waves around a reentry vehicle for radio frequency blackout prediction during aerodynamic heating was developed in this study. The model was validated based on experimental results from the radio attenuation measurement program. The plasma flow properties, such as electron number density, in the shock layer and wake region were obtained using a newly developed unstructured grid solver that incorporated real gas effect models and could treat thermochemically non-equilibrium flow. To predict the electromagnetic waves in plasma, a frequency-dependent finite-difference time-domain method was used. Moreover, the complicated behaviour of electromagnetic waves in the plasma layer during atmospheric reentry was clarified at several altitudes. The prediction performance of the combined model was evaluated with profiles and peak values of the electron number density in the plasma layer. In addition, to validate the models, the signal losses measured during communication with the reentry vehicle were directly compared with the predicted results. Based on the study, it was suggested that the present analysis model accurately predicts the radio frequency blackout and plasma attenuation of electromagnetic waves in plasma in communication.

  10. Life prediction methodology for ceramic components of advanced vehicular heat engines: Volume 1. Final report

    SciTech Connect

    Khandelwal, P.K.; Provenzano, N.J.; Schneider, W.E.

    1996-02-01

    One of the major challenges involved in the use of ceramic materials is ensuring adequate strength and durability. This activity has developed methodology which can be used during the design phase to predict the structural behavior of ceramic components. The effort involved the characterization of injection molded and hot isostatic pressed (HIPed) PY-6 silicon nitride, the development of nondestructive evaluation (NDE) technology, and the development of analytical life prediction methodology. Four failure modes are addressed: fast fracture, slow crack growth, creep, and oxidation. The techniques deal with failures initiating at the surface as well as internal to the component. The life prediction methodology for fast fracture and slow crack growth have been verified using a variety of confirmatory tests. The verification tests were conducted at room and elevated temperatures up to a maximum of 1371 {degrees}C. The tests involved (1) flat circular disks subjected to bending stresses and (2) high speed rotating spin disks. Reasonable correlation was achieved for a variety of test conditions and failure mechanisms. The predictions associated with surface failures proved to be optimistic, requiring re-evaluation of the components` initial fast fracture strengths. Correlation was achieved for the spin disks which failed in fast fracture from internal flaws. Time dependent elevated temperature slow crack growth spin disk failures were also successfully predicted.

  11. Life prediction methodology for ceramic components of advanced heat engines. Phase 1: Volume 2, Appendices

    SciTech Connect

    1995-03-01

    This volume presents the following appendices: ceramic test specimen drawings and schematics, mixed-mode and biaxial stress fracture of structural ceramics for advanced vehicular heat engines (U. Utah), mode I/mode II fracture toughness and tension/torsion fracture strength of NT154 Si nitride (Brown U.), summary of strength test results and fractography, fractography photographs, derivations of statistical models, Weibull strength plots for fast fracture test specimens, and size functions.

  12. OSMOSE an experimental program for improving neutronic predictions of advanced nuclear fuels.

    SciTech Connect

    Klann, R. T.; Aliberti, G.; Zhong, Z.; Graczyk, D.; Loussi, A.; Nuclear Engineering Division; Commissariat a l Energie Atomique

    2007-10-18

    This report describes the technical results of tasks and activities conducted in FY07 to support the DOE-CEA collaboration on the OSMOSE program. The activities are divided into five high-level tasks: reactor modeling and pre-experiment analysis, sample fabrication and analysis, reactor experiments, data treatment and analysis, and assessment for relevance to high priority advanced reactor programs (such as GNEP and Gen-IV).

  13. Advancing hydrometeorological prediction capabilities through standards-based cyberinfrastructure development: The community WRF-Hydro modeling system

    NASA Astrophysics Data System (ADS)

    gochis, David; Parodi, Antonio; Hooper, Rick; Jha, Shantenu; Zaslavsky, Ilya

    2013-04-01

    The need for improved assessments and predictions of many key environmental variables is driving a multitude of model development efforts in the geosciences. The proliferation of weather and climate impacts research is driving a host of new environmental prediction model development efforts as society seeks to understand how climate does and will impact key societal activities and resources and, in turn, how human activities influence climate and the environment. This surge in model development has highlighted the role of model coupling as a fundamental activity itself and, at times, a significant bottleneck in weather and climate impacts research. This talk explores some of the recent activities and progress that has been made in assessing the attributes of various approaches to the coupling of physics-based process models for hydrometeorology. One example modeling system that is emerging from these efforts is the community 'WRF-Hydro' modeling system which is based on the modeling architecture of the Weather Research and Forecasting (WRF). An overview of the structural components of WRF-Hydro will be presented as will results from several recent applications which include the prediction of flash flooding events in the Rocky Mountain Front Range region of the U.S. and along the Ligurian coastline in the northern Mediterranean. Efficient integration of the coupled modeling system with distributed infrastructure for collecting and sharing hydrometeorological observations is one of core themes of the work. Specifically, we aim to demonstrate how data management infrastructures used in the US and Europe, in particular data sharing technologies developed within the CUAHSI Hydrologic Information System and UNIDATA, can interoperate based on international standards for data discovery and exchange, such as standards developed by the Open Geospatial Consortium and adopted by GEOSS. The data system we envision will help manage WRF-Hydro prediction model data flows, enabling

  14. [Clinical application value of prognostic nutritional index for predicting survival in patients with advanced non-small cell lung cancer].

    PubMed

    Xu, W J; Kang, Y M; Zhou, L; Chen, F F; Song, Y H; Zhang, C Q

    2017-02-23

    Objective: To explore the clinical application value of prognostic nutritional index(PNI) for predicting overall survival(OS) in patients with advanced non-small cell lung cancer (NSCLC). Methods: 123 patients with histologically confirmed non-small cell lung cancer were enrolled in this study, and their clinical and laboratory data were reviewed. The PNI was calculated as 10×serum albumin value+ 5×total lymphocyte countin peripheral blood.Univariate and multivariate analyses were used to identify the potential prognostic factors for advanced NSCLC. Results: PNI of the 123 NSCLC patients was 46.24±6.56. PNI was significantly associated with age, weight loss and pleural effusion (P<0.05). However, it showed no relationship with sex, smoking, hemoptysis, chest pain, dyspnea, histological type, clinical stage, and administration of chemotherapy (P>0.05). The median OS of the 123 patients was 19.5 months. The median OS in the higher PNI group (PNI≥46.24) and lower PNI group(PNI<46.24) were 25.2 months and 16.4 months, respectively.The 1-year survival rates were 80.6% and 63.9%, and 2-year survival rates were 54.8% and 19.6%, respectively (P<0.01). Univariate analysis showed that PNI, age, dyspnea, and weight loss were related to the OS of the advanced NSCLC patients (P<0.05). Multivariate analysis identified PNI as an independent prognostic factor for OS of advanced NSCLC (P<0.001). Conclusion: PNI can be easily calculated, and may be used as a relatively new prognostic indicator for advanced NSCLC in clinical practice.

  15. Strengthening sociometric prediction: scientific advances in the assessment of children's peer relations.

    PubMed

    DeRosier, Melissa E; Thomas, James M

    2003-01-01

    This study assessed the strength of sociometric classification in the prediction of concurrent sociobehavioral adjustment. Differential adjustment for subgroups of unclassified children were also examined. Participants were 881 fifth graders (ages 9 to 12). Classification strength (CS) and unclassified subgroups were determined through newly developed algorithms. CS added significantly to the prediction of all areas of adjustment. For example, highly rejected children were at extreme risk for victimization whereas highly controversial children were most likely to be bullies and relationally aggressive. Unclassified subgroups were found to exhibit adjustment problems mirroring those of their extreme status group counterparts. Findings support that increasing the sensitivity of sociometric measurement results in both greater predictive strength and enhanced understanding of underlying social processes.

  16. Predicted and measured boundary layer refraction for advanced turboprop propeller noise

    NASA Technical Reports Server (NTRS)

    Dittmar, James H.; Krejsa, Eugene A.

    1990-01-01

    Currently, boundary layer refraction presents a limitation to the measurement of forward arc propeller noise measured on an acoustic plate in the NASA Lewis 8- by 6-Foot Supersonic Wind Tunnel. The use of a validated boundary layer refraction model to adjust the data could remove this limitation. An existing boundary layer refraction model is used to predict the refraction for cases where boundary layer refraction was measured. In general, the model exhibits the same qualitative behavior as the measured refraction. However, the prediction method does not show quantitative agreement with the data. In general, it overpredicts the amount of refraction for the far forward angles at axial Mach number of 0.85 and 0.80 and underpredicts the refraction at axial Mach numbers of 0.75 and 0.70. A more complete propeller source description is suggested as a way to improve the prediction method.

  17. Sensor-model prediction, monitoring and in-situ control of liquid RTM advanced fiber architecture composite processing

    NASA Technical Reports Server (NTRS)

    Kranbuehl, D.; Kingsley, P.; Hart, S.; Loos, A.; Hasko, G.; Dexter, B.

    1992-01-01

    In-situ frequency dependent electromagnetic sensors (FDEMS) and the Loos resin transfer model have been used to select and control the processing properties of an epoxy resin during liquid pressure RTM impregnation and cure. Once correlated with viscosity and degree of cure the FDEMS sensor monitors and the RTM processing model predicts the reaction advancement of the resin, viscosity and the impregnation of the fabric. This provides a direct means for predicting, monitoring, and controlling the liquid RTM process in-situ in the mold throughout the fabrication process and the effects of time, temperature, vacuum and pressure. Most importantly, the FDEMS-sensor model system has been developed to make intelligent decisions, thereby automating the liquid RTM process and removing the need for operator direction.

  18. NASA University Research Centers Technical Advances in Aeronautics, Space Sciences and Technology, Earth Systems Sciences, Global Hydrology, and Education. Volumes 2 and 3

    NASA Technical Reports Server (NTRS)

    Coleman, Tommy L. (Editor); White, Bettie (Editor); Goodman, Steven (Editor); Sakimoto, P. (Editor); Randolph, Lynwood (Editor); Rickman, Doug (Editor)

    1998-01-01

    This volume chronicles the proceedings of the 1998 NASA University Research Centers Technical Conference (URC-TC '98), held on February 22-25, 1998, in Huntsville, Alabama. The University Research Centers (URCS) are multidisciplinary research units established by NASA at 11 Historically Black Colleges or Universities (HBCU's) and 3 Other Minority Universities (OMU's) to conduct research work in areas of interest to NASA. The URC Technical Conferences bring together the faculty members and students from the URC's with representatives from other universities, NASA, and the aerospace industry to discuss recent advances in their fields.

  19. Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances

    PubMed Central

    Abut, Fatih; Akay, Mehmet Fatih

    2015-01-01

    Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R) and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance. PMID:26346869

  20. A hybrid approach to advancing quantitative prediction of tissue distribution of basic drugs in human

    SciTech Connect

    Poulin, Patrick; Ekins, Sean; Theil, Frank-Peter

    2011-01-15

    A general toxicity of basic drugs is related to phospholipidosis in tissues. Therefore, it is essential to predict the tissue distribution of basic drugs to facilitate an initial estimate of that toxicity. The objective of the present study was to further assess the original prediction method that consisted of using the binding to red blood cells measured in vitro for the unbound drug (RBCu) as a surrogate for tissue distribution, by correlating it to unbound tissue:plasma partition coefficients (Kpu) of several tissues, and finally to predict volume of distribution at steady-state (V{sub ss}) in humans under in vivo conditions. This correlation method demonstrated inaccurate predictions of V{sub ss} for particular basic drugs that did not follow the original correlation principle. Therefore, the novelty of this study is to provide clarity on the actual hypotheses to identify i) the impact of pharmacological mode of action on the generic correlation of RBCu-Kpu, ii) additional mechanisms of tissue distribution for the outlier drugs, iii) molecular features and properties that differentiate compounds as outliers in the original correlation analysis in order to facilitate its applicability domain alongside the properties already used so far, and finally iv) to present a novel and refined correlation method that is superior to what has been previously published for the prediction of human V{sub ss} of basic drugs. Applying a refined correlation method after identifying outliers would facilitate the prediction of more accurate distribution parameters as key inputs used in physiologically based pharmacokinetic (PBPK) and phospholipidosis models.

  1. Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances.

    PubMed

    Abut, Fatih; Akay, Mehmet Fatih

    2015-01-01

    Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R) and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance.

  2. Predicting Cost/Reliability/Maintainability of Advanced General Aviation Avionics Equipment

    NASA Technical Reports Server (NTRS)

    Davis, M. R.; Kamins, M.; Mooz, W. E.

    1978-01-01

    A methodology is provided for assisting NASA in estimating the cost, reliability, and maintenance (CRM) requirements for general avionics equipment operating in the 1980's. Practical problems of predicting these factors are examined. The usefulness and short comings of different approaches for modeling coast and reliability estimates are discussed together with special problems caused by the lack of historical data on the cost of maintaining general aviation avionics. Suggestions are offered on how NASA might proceed in assessing cost reliability CRM implications in the absence of reliable generalized predictive models.

  3. Advanced Models and Controls for Prediction and Extension of Battery Lifetime (Presentation)

    SciTech Connect

    Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Pesaran, A.

    2014-02-01

    Predictive models of capacity and power fade must consider a multiplicity of degradation modes experienced by Li-ion batteries in the automotive environment. Lacking accurate models and tests, lifetime uncertainty must presently be absorbed by overdesign and excess warranty costs. To reduce these costs and extend life, degradation models are under development that predict lifetime more accurately and with less test data. The lifetime models provide engineering feedback for cell, pack and system designs and are being incorporated into real-time control strategies.

  4. LiverTox: Advanced QSAR and Toxicogeomic Software for Hepatotoxicity Prediction

    SciTech Connect

    Lu, P-Y.; Yuracko, K.

    2011-02-25

    YAHSGS LLC and Oak Ridge National Laboratory (ORNL) established a CRADA in an attempt to develop a predictive system using a pre-existing ORNL computational neural network and wavelets format. This was in the interest of addressing national needs for toxicity prediction system to help overcome the significant drain of resources (money and time) being directed toward developing chemical agents for commerce. The research project has been supported through an STTR mechanism and funded by the National Institute of Environmental Health Sciences beginning Phase I in 2004 (CRADA No. ORNL-04-0688) and extending Phase II through 2007 (ORNL NFE-06-00020). To attempt the research objectives and aims outlined under this CRADA, state-of-the-art computational neural network and wavelet methods were used in an effort to design a predictive toxicity system that used two independent areas on which to base the system’s predictions. These two areas were quantitative structure-activity relationships and gene-expression data obtained from microarrays. A third area, using the new Massively Parallel Signature Sequencing (MPSS) technology to assess gene expression, also was attempted but had to be dropped because the company holding the rights to this promising MPSS technology went out of business. A research-scale predictive toxicity database system called Multi-Intelligent System for Toxicogenomic Applications (MISTA) was developed and its feasibility for use as a predictor of toxicological activity was tested. The fundamental focus of the CRADA was an attempt and effort to operate the MISTA database using the ORNL neural network. This effort indicated the potential that such a fully developed system might be used to assist in predicting such biological endpoints as hepatotoxcity and neurotoxicity. The MISTA/LiverTox approach if eventually fully developed might also be useful for automatic processing of microarray data to predict modes of action. A technical paper describing the

  5. Multiaxial deformation and life prediction model and experimental data for advanced silicon nitride ceramics

    SciTech Connect

    Ding, J.L.; Liu, K.C.; Brinkman, C.R.

    1993-06-01

    This paper summarizes recent experimental results on creep and creep rupture behavior of a commercial grade of Si{sub 3}N{sub 4} ceramic in the temperature range of 1150 to 1300C obtained at ORNL; and introduces a tentative multiaxial deformation and life prediction model for ceramic materials under general thermomechanical loadings. Issues related to the possible standardization of the data analysis methodology and possible future research needs for high temperature structural ceramics in the area of development of data base and life prediction methodology are also discussed.

  6. Neoadjuvant treatment for advanced esophageal cancer: response assessment before surgery and how to predict response to chemoradiation before starting treatment

    PubMed Central

    Hölscher, Arnulf H.; Schmidt, Matthias; Warnecke-Eberz, Ute

    2015-01-01

    Patients with advanced esophageal cancer (T3-4, N) have a poor prognosis. Chemoradiation or chemotherapy before esophagectomy with adequate lymphadenectomy is the standard treatment for patients with resectable advanced esophageal carcinoma. However, only patients with major histopathologic response (regression to less than 10% of the primary tumor) after preoperative treatment will have a prognostic benefit of preoperative chemoradiation. Using current therapy regimens about 40% to 50% of the patients show major histopathological response. The remaining cohort does not benefit from this neoadjuvant approach but might benefit from earlier surgical resection. Therefore, it is an aim to develop tools for response prediction before starting the treatment and for early response assessment identifying responders. The current review discusses the different imaging techniques and the most recent studies about molecular markers for early response prediction. The results show that [18F]-fluorodeoxyglucose-positron emission tomography (FDG-PET) has a good sensitivity but the specificity is not robust enough for routine clinical use. Newer positron emission tomography detector technology, the combination of FDG-PET with computed tomography, additional evaluation criteria and standardization of evaluation may improve the predictive value. There exist a great number of retrospective studies using molecular markers for prediction of response. Until now the clinical use is missing. But the results of first prospective studies are promising. A future perspective may be the combination of imaging technics and special molecular markers for individualized therapy. Another aspect is the response assessment after finishing neoadjuvant treatment protocol. The different clinical methods are discussed. The results show that until now no non-invasive method is valid enough to assess complete histopathological response. PMID:26157318

  7. MODELING AND ANALYSIS OF GLOBAL AND REGIONAL HYDROLOGIC PROCESSES AND APPROPRIATE CONSERVATION OF MOIST ENTROPY

    SciTech Connect

    Donald Johnson, Todd Schaack

    2007-06-08

    The research supported by DOE funding addressed the fundamental issues of understanding and modeling of hydrologic processes in relation to regional and global climate change. The emphasis of this research effort was on the application of isentropic modeling and analysis to advance the accuracy of the simulation of all aspects of the hydrologic cycle including clouds and thus the climate state regionally and globally. Simulation of atmospheric hydrologic processes by the UW hybrid isentropic coordinate models provided fundamental insight into global monsoonal circulations, and regional energy exchange in relation to the atmospheric hydrologic cycle. Inter-comparison of UW hybrid model simulations with those from the NCAR Community Climate Model and other climate and numerical weather prediction (NWP) models investigated the increased accuracies gained in modeling long-range transport in isentropic coordinates and isolated differences in modeling of the climate state. The inter-comparisons demonstrated advantages in the simulation of the transport of the hydrologic components of the climate system and provided insight into the more general problems of simulating hydrologic processes, aerosols and chemistry for climate. This research demonstrated the viability of the UW isentropic-eta model for long-term integration for climate and climate change studies and documented that no insurmountable barriers exist to simulation of climate utilizing hybrid isentropic coordinate models. The results provide impetus for continued development of hybrid isentropic coordinate models as a means to advance accuracies in the simulation of global and regional climate in relation to transport and the planetary distribution of heat sources and sinks.

  8. Advances in Toxico-Cheminformatics: Supporting a New Paradigm for Predictive Toxicology

    EPA Science Inventory

    EPA’s National Center for Computational Toxicology is building capabilities to support a new paradigm for toxicity screening and prediction through the harnessing of legacy toxicity data, creation of data linkages, and generation of new high-throughput screening (HTS) data. The D...

  9. Development of advanced stability theory suction prediction techniques for laminar flow control. [on swept wings

    NASA Technical Reports Server (NTRS)

    Srokowski, A. J.

    1978-01-01

    The problem of obtaining accurate estimates of suction requirements on swept laminar flow control wings was discussed. A fast accurate computer code developed to predict suction requirements by integrating disturbance amplification rates was described. Assumptions and approximations used in the present computer code are examined in light of flow conditions on the swept wing which may limit their validity.

  10. The Climate Variability & Predictability (CVP) Program at NOAA - Recent Program Advancements

    NASA Astrophysics Data System (ADS)

    Lucas, S. E.; Todd, J. F.

    2015-12-01

    The Climate Variability & Predictability (CVP) Program supports research aimed at providing process-level understanding of the climate system through observation, modeling, analysis, and field studies. This vital knowledge is needed to improve climate models and predictions so that scientists can better anticipate the impacts of future climate variability and change. To achieve its mission, the CVP Program supports research carried out at NOAA and other federal laboratories, NOAA Cooperative Institutes, and academic institutions. The Program also coordinates its sponsored projects with major national and international scientific bodies including the World Climate Research Programme (WCRP), the International and U.S. Climate Variability and Predictability (CLIVAR/US CLIVAR) Program, and the U.S. Global Change Research Program (USGCRP). The CVP program sits within NOAA's Climate Program Office (http://cpo.noaa.gov/CVP). The CVP Program currently supports multiple projects in areas that are aimed at improved representation of physical processes in global models. Some of the topics that are currently funded include: i) Improved Understanding of Intraseasonal Tropical Variability - DYNAMO field campaign and post -field projects, and the new climate model improvement teams focused on MJO processes; ii) Climate Process Teams (CPTs, co-funded with NSF) with projects focused on Cloud macrophysical parameterization and its application to aerosol indirect effects, and Internal-Wave Driven Mixing in Global Ocean Models; iii) Improved Understanding of Tropical Pacific Processes, Biases, and Climatology; iv) Understanding Arctic Sea Ice Mechanism and Predictability;v) AMOC Mechanisms and Decadal Predictability Recent results from CVP-funded projects will be summarized. Additional information can be found at http://cpo.noaa.gov/CVP.

  11. Assessment of Hydrologic Response to Variable Precipitation Forcing: Russian River Case Study

    NASA Astrophysics Data System (ADS)

    Cifelli, R.; Hsu, C.; Johnson, L. E.

    2014-12-01

    NOAA Hydrometeorology Testbed (HMT) activities in California have involved deployment of advanced sensor networks to better track atmospheric river (AR) dynamics and inland penetration of high water vapor air masses. Numerical weather prediction models and decision support tools have been developed to provide forecasters a better basis for forecasting heavy precipitation and consequent flooding. The HMT also involves a joint project with California Department of Water Resources (CA-DWR) and the Scripps Institute for Oceanography (SIO) as part of CA-DWR's Enhanced Flood Response and Emergency Preparedness (EFREP) program. The HMT activities have included development and calibration of a distributed hydrologic model, the NWS Office of Hydrologic Development's (OHD) Research Distributed Hydrologic Model (RDHM), to prototype the distributed approach for flood and other water resources applications. HMT has applied RDHM to the Russian-Napa watersheds for research assessment of gap-filling weather radars for precipitation and hydrologic forecasting and for establishing a prototype to inform both the NWS Monterey Forecast Office and the California Nevada River Forecast Center (CNRFC) of RDHM capabilities. In this presentation, a variety of precipitation forcings generated with and without gap filling radar and rain gauge data are used as input to RDHM to assess the hydrologic response for selected case study events. Both the precipitation forcing and hydrologic model are run at different spatial and temporal resolution in order to examine the sensitivity of runoff to the precipitation inputs. Based on the timing of the events and the variations of spatial and temporal resolution, the parameters which dominate the hydrologic response are identified. The assessment is implemented at two USGS stations (Ukiah near Russian River and Austin Creek near Cazadero) that are minimally influenced by managed flows and objective evaluation can thus be derived. The results are assessed

  12. Improving predictions of the effects of extreme events, land use, and climate change on the hydrology of watersheds in the Philippines

    NASA Astrophysics Data System (ADS)

    Benavidez, Rubianca; Jackson, Bethanna; Maxwell, Deborah; Paringit, Enrico

    2016-05-01

    Due to its location within the typhoon belt, the Philippines is vulnerable to tropical cyclones that can cause destructive floods. Climate change is likely to exacerbate these risks through increases in tropical cyclone frequency and intensity. To protect populations and infrastructure, disaster risk management in the Philippines focuses on real-time flood forecasting and structural measures such as dikes and retaining walls. Real-time flood forecasting in the Philippines mostly utilises two models from the Hydrologic Engineering Center (HEC): the Hydrologic Modeling System (HMS) for watershed modelling, and the River Analysis System (RAS) for inundation modelling. This research focuses on using non-structural measures for flood mitigation, such as changing land use management or watershed rehabilitation. This is being done by parameterising and applying the Land Utilisation and Capability Indicator (LUCI) model to the Cagayan de Oro watershed (1400 km2) in southern Philippines. The LUCI model is capable of identifying areas providing ecosystem services such as flood mitigation and agricultural productivity, and analysing trade-offs between services. It can also assess whether management interventions could enhance or degrade ecosystem services at fine spatial scales. The LUCI model was used to identify areas within the watershed that are providing flood mitigating services and areas that would benefit from management interventions. For the preliminary comparison, LUCI and HEC-HMS were run under the same scenario: baseline land use and the extreme rainfall event of Typhoon Bopha. The hydrographs from both models were then input to HEC-RAS to produce inundation maps. The novelty of this research is two-fold: (1) this type of ecosystem service modelling has not been carried out in the Cagayan de Oro watershed; and (2) this is the first application of the LUCI model in the Philippines. Since this research is still ongoing, the results presented in this paper are

  13. Functional imaging using computational fluid dynamics to predict treatment success of mandibular advancement devices in sleep-disordered breathing.

    PubMed

    De Backer, J W; Vanderveken, O M; Vos, W G; Devolder, A; Verhulst, S L; Verbraecken, J A; Parizel, P M; Braem, M J; Van de Heyning, P H; De Backer, W A

    2007-01-01

    Mandibular advancement devices (MADs) have emerged as a popular alternative for the treatment of sleep-disordered breathing. These devices bring the mandibula forward in order to increase upper airway (UA) volume and prevent total UA collapse during sleep. However, the precise mechanism of action appears to be quite complex and is not yet completely understood; this might explain interindividual variation in treatment success. We examined whether an UA model, that combines imaging techniques and computational fluid dynamics (CFD), allows for a prediction of the treatment outcome with MADs. Ten patients that were treated with a custom-made mandibular advancement device (MAD), underwent split-night polysomnography. The morning after the sleep study, a low radiation dose CT scan was scheduled with and without the MAD. The CT examinations allowed for a comparison between the change in UA volume and the anatomical characteristics through the conversion to three-dimensional computer models. Furthermore, the change in UA resistance could be calculated through flow simulations with CFD. Boundary conditions for the model such as mass flow rate and pressure distributions were obtained during the split-night polysomnography. Therefore, the flow modeling was based on a patient specific geometry and patient specific boundary conditions. The results indicated that a decrease in UA resistance and an increase in UA volume correlate with both a clinical and an objective improvement. The results of this pilot study suggest that the outcome of MAD treatment can be predicted using the described UA model.

  14. Application of Multivariable Model Predictive Advanced Control for a 2×310T/H CFB Boiler Unit

    NASA Astrophysics Data System (ADS)

    Weijie, Zhao; Zongllao, Dai; Rong, Gou; Wengan, Gong

    When a CFB boiler is in automatic control, there are strong interactions between various process variables and inverse response characteristics of bed temperature control target. Conventional Pill control strategy cannot deliver satisfactory control demand. Kalman wave filter technology is used to establish a non-linear combustion model, based on the CFB combustion characteristics of bed fuel inventory, heating values, bed lime inventory and consumption. CFB advanced combustion control utilizes multivariable model predictive control technology to optimize primary and secondary air flow, bed temperature, air flow, fuel flow and heat flux. In addition to providing advanced combustion control to 2×310t/h CFB+1×100MW extraction condensing turbine generator unit, the control also provides load allocation optimization and advanced control for main steam pressure, combustion and temperature. After the successful implementation, under 10% load change, main steam pressure varied less than ±0.07MPa, temperature less than ±1°C, bed temperature less than ±4°C, and air flow (O2) less than ±0.4%.

  15. Towards Reproducibility in Computational Hydrology

    NASA Astrophysics Data System (ADS)

    Hutton, Christopher; Wagener, Thorsten; Freer, Jim; Han, Dawei

    2016-04-01

    The ability to reproduce published scientific findings is a foundational principle of scientific research. Independent observation helps to verify the legitimacy of individual findings; build upon sound observations so that we can evolve hypotheses (and models) of how catchments function; and move them from specific circumstances to more general theory. The rise of computational research has brought increased focus on the issue of reproducibility across the broader scientific literature. This is because publications based on computational research typically do not contain sufficient information to enable the results to be reproduced, and therefore verified. Given the rise of computational analysis in hydrology over the past 30 years, to what extent is reproducibility, or a lack thereof, a problem in hydrology? Whilst much hydrological code is accessible, the actual code and workflow that produced and therefore documents the provenance of published scientific findings, is rarely available. We argue that in order to advance and make more robust the process of hypothesis testing and knowledge creation within the computational hydrological community, we need to build on from existing open data initiatives and adopt common standards and infrastructures to: first make code re-useable and easy to find through consistent use of metadata; second, publish well documented workflows that combine re-useable code together with data to enable published scientific findings to be reproduced; finally, use unique persistent identifiers (e.g. DOIs) to reference re-useable and reproducible code, thereby clearly showing the provenance of published scientific findings. Whilst extra effort is require to make work reproducible, there are benefits to both the individual and the broader community in doing so, which will improve the credibility of the science in the face of the need for societies to adapt to changing hydrological environments.

  16. MGMT expression levels predict disease stabilisation, progression-free and overall survival in patients with advanced melanomas treated with DTIC.

    PubMed

    Busch, Christian; Geisler, Jürgen; Lillehaug, Johan R; Lønning, Per Eystein

    2010-07-01

    Metastatic melanoma responds poorly to systemic treatment. We report the results of a prospective single institution study evaluating O(6)-methylguanine-DNA methyltransferase (MGMT) status as a potential predictive and/or prognostic marker among patients treated with dacarbazine (DTIC) 800-1000 mg/m(2) monotherapy administered as a 3-weekly schedule for advanced malignant melanomas. The study was approved by the Regional Ethical Committee. Surgical biopsies from metastatic or loco-regional deposits obtained prior to DTIC treatment were snap-frozen immediately upon removal and stored in liquid nitrogen up to processing. Median time from enrolment to end of follow-up was 67 months. MGMT expression levels evaluated by qRT-PCR correlated significantly to DTIC benefit (CR/PR/SD; p=0.005), time to progression (TTP) (p=0.005) and overall survival (OS) (p=0.003). MGMT expression also correlated to Breslow thickness in the primary tumour (p=0.014). While MGMT promoter hypermethylation correlated to MGMT expression, MGMT promoter hypermethylation did not correlate to treatment benefit, TTP or OS, suggesting that other factors may be critical in determining MGMT expression levels in melanomas. In a Cox proportional regression analysis, serum lactate dehydrogenase (LDH, p<0.001), MGMT expression (p=0.022) and p16(INK4a) expression (p=0.037) independently predicted OS, while TTP correlated to DTIC benefit after 6 weeks only (p=0.001). Our data reveal MGMT expression levels to be associated with disease stabilisation and prognosis in patients receiving DTIC monotherapy for advanced melanoma. The role of MGMT expression as a predictor to DTIC sensitivity versus a general prognostic factor in advanced melanomas warrants further evaluation.

  17. Advances in CFD Prediction of Shock Wave Turbulent Boundary Layer Interactions

    DTIC Science & Technology

    2006-01-01

    on the Baldwin and Lomax [151] algebraic turbulence model. Fig. 58 from Panaras [150] includes all the critical elements of the swept shock/turbulent...pitot pressure, yaw angle and surface pressure are predictable with reasonable accuracy using algebraic or two-equation turbulence models, however the...calculations they tested algebraic turbulence models and the k−² model, integrated to the wall or employing the wall-function technique. They have found

  18. Advanced Control Filtering and Prediction for Phased Arrays in Directed Energy Systems

    DTIC Science & Technology

    2014-07-31

    SIMULINK model for prediction and feedback control of a phase ramp. Mirror represented by integrator with sample time tsim. The model shown has a...and simulating the closed-loop system in SIMULINK . Approved for public release; distribution unlimited 3 4.0 RESULTS AND DISCUSSION 4.1...although this measurement probably is not necessary. 4.2 Simulation Model There are three differences between the current SIMULINK model and the

  19. Advanced Durability Analysis. Volume 2. Analytical Predictions, Test Results and Analytical Correlations

    DTIC Science & Technology

    1989-02-27

    used for the back-extrapolation. Recommendations for durability analysis are as follows: (1) define the equivalent initial flaw size distribution ...WAFXHR4 Data Set) for Cumulative Distribution of Service Time to Reach Crack Size x1 -0.59" Based on DCGA- DCGA. xiv List of Figures (Continued) Fiaur. ag ...be used to make predictions for the probability bf crack exceedance at any service time, 7’ , and the cumulative distribution of service time to

  20. From spatially variable streamflow to distributed hydrological models: Analysis of key modeling decisions

    NASA Astrophysics Data System (ADS)

    Fenicia, Fabrizio; Kavetski, Dmitri; Savenije, Hubert H. G.; Pfister, Laurent

    2016-02-01

    This paper explores the development and application of distributed hydrological models, focusing on the key decisions of how to discretize the landscape, which model structures to use in each landscape element, and how to link model parameters across multiple landscape elements. The case study considers the Attert catchment in Luxembourg—a 300 km2 mesoscale catchment with 10 nested subcatchments that exhibit clearly different streamflow dynamics. The research questions are investigated using conceptual models applied at hydrologic response unit (HRU) scales (1-4 HRUs) on 6 hourly time steps. Multiple model structures are hypothesized and implemented using the SUPERFLEX framework. Following calibration, space/time model transferability is tested using a split-sample approach, with evaluation criteria including streamflow prediction error metrics and hydrological signatures. Our results suggest that: (1) models using geology-based HRUs are more robust and capture the spatial variability of streamflow time series and signatures better than models using topography-based HRUs; this finding supports the hypothesis that, in the Attert, geology exerts a stronger control than topography on streamflow generation, (2) streamflow dynamics of different HRUs can be represented using distinct and remarkably simple model structures, which can be interpreted in terms of the perceived dominant hydrologic processes in each geology type, and (3) the same maximum root zone storage can be used across the three dominant geological units with no loss in model transferability; this finding suggests that the partitioning of water between streamflow and evaporation in the study area is largely independent of geology and can be used to improve model parsimony. The modeling methodology introduced in this study is general and can be used to advance our broader understanding and prediction of hydrological behavior, including the landscape characteristics that control hydrologic response, the

  1. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

    PubMed

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets.

  2. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science

    PubMed Central

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets. PMID:27532883

  3. Myopodin methylation is a prognostic biomarker and predicts antiangiogenic response in advanced kidney cancer.

    PubMed

    Pompas-Veganzones, N; Sandonis, V; Perez-Lanzac, Alberto; Beltran, M; Beardo, P; Juárez, A; Vazquez, F; Cozar, J M; Alvarez-Ossorio, J L; Sanchez-Carbayo, Marta

    2016-10-01

    Myopodin is a cytoskeleton protein that shuttles to the nucleus depending on the cellular differentiation and stress. It has shown tumor suppressor functions. Myopodin methylation status was useful for staging bladder and colon tumors and predicting clinical outcome. To our knowledge, myopodin has not been tested in kidney cancer to date. The purpose of this study was to evaluate whether myopodin methylation status could be clinically useful in renal cancer (1) as a prognostic biomarker and 2) as a predictive factor of response to antiangiogenic therapy in patients with metastatic disease. Methylation-specific polymerase chain reactions (MS-PCR) were used to evaluate myopodin methylation in 88 kidney tumors. These belonged to patients with localized disease and no evidence of disease during follow-up (n = 25) (group 1), and 63 patients under antiangiogenic therapy (sunitinib, sorafenib, pazopanib, and temsirolimus), from which group 2 had non-metastatic disease at diagnosis (n = 32), and group 3 showed metastatic disease at diagnosis (n = 31). Univariate and multivariate Cox analyses were utilized to assess outcome and response to antiangiogenic agents taking progression, disease-specific survival, and overall survival as clinical endpoints. Myopodin was methylated in 50 out of the 88 kidney tumors (56.8 %). Among the 88 cases analyzed, 10 of them recurred (11.4 %), 51 progressed (57.9 %), and 40 died of disease (45.4 %). Myopodin methylation status correlated to MSKCC Risk score (p = 0.050) and the presence of distant metastasis (p = 0.039). Taking all patients, an unmethylated myopodin identified patients with shorter progression-free survival, disease-specific survival, and overall survival. Using also in univariate and multivariate models, an unmethylated myopodin predicted response to antiangiogenic therapy (groups 2 and 3) using progression-free survival, disease-specific, and overall survival as clinical endpoints. Myopodin was revealed

  4. Predicting early brain metastases based on clinicopathological factors and gene expression analysis in advanced HER2-positive breast cancer patients.

    PubMed

    Duchnowska, Renata; Jassem, Jacek; Goswami, Chirayu Pankaj; Dundar, Murat; Gökmen-Polar, Yesim; Li, Lang; Woditschka, Stephan; Biernat, Wojciech; Sosińska-Mielcarek, Katarzyna; Czartoryska-Arłukowicz, Bogumiła; Radecka, Barbara; Tomasevic, Zorica; Stępniak, Piotr; Wojdan, Konrad; Sledge, George W; Steeg, Patricia S; Badve, Sunil

    2015-03-01

    The overexpression or amplification of the human epidermal growth factor receptor 2 gene (HER2/neu) is associated with high risk of brain metastasis (BM). The identification of patients at highest immediate risk of BM could optimize screening and facilitate interventional trials. We performed gene expression analysis using complementary deoxyribonucleic acid-mediated annealing, selection, extension and ligation and real-time quantitative reverse transcription PCR (qRT-PCR) in primary tumor samples from two independent cohorts of advanced HER2 positive breast cancer patients. Additionally, we analyzed predictive relevance of clinicopathological factors in this series. Study group included discovery Cohort A (84 patients) and validation Cohort B (75 patients). The only independent variables associated with the development of early BM in both cohorts were the visceral location of first distant relapse [Cohort A: hazard ratio (HR) 7.4, 95 % CI 2.4-22.3; p < 0.001; Cohort B: HR 6.1, 95 % CI 1.5-25.6; p = 0.01] and the lack of trastuzumab administration in the metastatic setting (Cohort A: HR 5.0, 95 % CI 1.4-10.0; p = 0.009; Cohort B: HR 10.0, 95 % CI 2.0-100.0; p = 0.008). A profile including 13 genes was associated with early (≤36 months) symptomatic BM in the discovery cohort. This was refined by qRT-PCR to a 3-gene classifier (RAD51, HDGF, TPR) highly predictive of early BM (HR 5.3, 95 % CI 1.6-16.7; p = 0.005; multivariate analysis). However, predictive value of the classifier was not confirmed in the independent validation Cohort B. The presence of visceral metastases and the lack of trastuzumab administration in the metastatic setting apparently increase the likelihood of early BM in advanced HER2-positive breast cancer.

  5. Tumor size and lymph node status determined by imaging are reliable factors for predicting advanced cervical cancer prognosis.

    PubMed

    Kyung, Min Sun; Kim, Hong Bae; Seoung, Jung Yeob; Choi, In Young; Joo, Young Soo; Lee, Me Yeon; Kang, Jung Bae; Park, Young Han

    2015-05-01

    The aim of the present study was to investigate the prognostic role of a number of clinical factors in advanced cervical cancer patients. Patients (n=157) with stage IIA-IIB cervical cancer treated at four Hallym Medical Centers in South Korea (Hallym University Sacred Heart Hospital; Kangnam Sacred Heart Hospital; Chuncheon Sacred Heart Hospital; and Kangdong Sacred Heart Hospital) between 2006 and 2010 were retrospectively enrolled. Univariate analysis identified significant predictive values in the following eight factors: i) Cancer stage (P<0.0001); ii) tumor size (≤4 vs. 4-6 cm, P=0.0147; and ≤4 vs. >6 cm, P<0.0001); iii) serum squamous cell carcinoma antigen level (≤2 vs. >15 ng/ml; P=0.0291); iv) lower third vaginal involvement (P<0.0001); v) hydronephrosis (P=0.0003); vi) bladder/rectum involvement (P=0.0015); vii) pelvic (P=0.0017) or para-aortic (P=0.0019) lymph node (LN) metastasis detected by imaging vs. no metastasis; and viii) pelvic LN metastasis identified by pathological analysis (P=0.0289). Furthermore, multivariate analysis determined that tumor size (≤4 vs. 4-6 cm, P=0.0371; and ≤4 vs. >6 cm, P=0.0024) and pelvic LN metastasis determined by imaging vs. no metastasis (P=0.0499) were independent predictive variables. Therefore, tumor size and pelvic LN metastasis measured by imaging were independent predictive factors for the prognosis of advanced cervical cancer. These factors may provide more clinically significant prognostic information compared with the currently used International Federation of Gynecology and Obstetrics staging system.

  6. Prediction of Unsteady Blade Surface Pressures on an Advanced Propeller at an Angle of Attack

    NASA Technical Reports Server (NTRS)

    Nallasamy, M.; Groeneweg, J. F.

    1989-01-01

    The numerical solution of the unsteady, three-dimensional, Euler equations is considered in order to obtain the blade surface pressures of an advanced propeller at an angle of attack. The specific configuration considered is the SR7L propeller at cruise conditions with a 4.6 deg inflow angle corresponding to the plus 2 deg nacelle tilt of the Propeller Test Assessment (PTA) flight test condition. The results indicate nearly sinusoidal response of the blade loading, with angle of attack. For the first time, detailed variations of the chordwise loading as a function of azimuthal angle are presented. It is observed that the blade is lightly loaded for part of the revolution and shocks appear from hub to about 80 percent radial station for the highly loaded portion of the revolution.

  7. Prediction of unsteady blade surface pressures on an advanced propeller at an angle of attack

    NASA Technical Reports Server (NTRS)

    Nallasamy, M.; Groeneweg, J. F.

    1989-01-01

    The paper considers the numerical solution of the unsteady, three-dimensional, Euler equations to obtain the blade surface pressures of an advanced propeller at an angle of attack. The specific configuration considered is the SR7L propeller at cruise conditions with a 4.6 deg inflow angle corresponding to the +2 deg nacelle tilt of the Propeller Test Assessment (PTA) flight test condition. The results indicate nearly sinusoidal response of the blade loading, with angle of attack. For the first time, detailed variations of the chordwise loading as a function of azimuthal angle are presented. It is observed that the blade is lightly loaded for part of the revolution and shocks appear from hub to about 80 percent radial station for the highly loaded portion of the revolution.

  8. Performance Prediction for a Hockey-Puck Silicon Crystal Monochromator at the Advanced Photon Source

    NASA Astrophysics Data System (ADS)

    Liu, Zunping; Rosenbaum, Gerd; Navrotski, Gary

    2014-03-01

    One of the Key Performance Parameters of the upgrade of the Advanced Photon Source (APS) is the increase of the storage ring current from 100 to 150 mA. In order to anticipate the impact of this increased heat load on the X-ray optics of the beamlines, the APS has implemented a systematic review, by means of finite element analysis and computational fluid dynamics, of the thermal performance of the different types of monochromators installed at the highest-heat-load insertion device beamlines. We present here simulations of the performance of a directly liquid nitrogen-cooled silicon crystal, the hockey-puck design. Calculations of the temperature and slope error at multiple ring currents under multiple operational conditions, including the influence of power, cooling, and diffraction surface thickness are included.

  9. CEP55 overexpression predicts poor prognosis in patients with locally advanced esophageal squamous cell carcinoma

    PubMed Central

    Jiang, Wenpeng; Wang, Zhou; Jia, Yang

    2017-01-01

    Development of esophageal squamous cell carcinoma (ESCC) involves alterations in multiple genes with corresponding proteins. Recent studies have demonstrated that centrosomal protein 55 (CEP55) shares certain features with oncogenes, and CEP55 overexpression is associated with the development and progression of malignant tumors. The present study aimed to analyze, for the first time, whether CEP55 expression is related to clinicopothalogic features in the esophageal squamous cell carcinoma (ESCC), as well as patient survival. A total of 110 patients with mid-thoracic ESCC who suffered from Ivor-Lewis were enrolled. The CEP55 expression profile of these patients in tumour tissues and corresponding healthy esophageal mucosa (CHEM) was detected by immunohistochemistry and semi-quantitative reverse transcription-polymerase chain reaction analyses. Correlations between CEP55 expression and clinicopathological factors were analyzed using χ2 test. The log-rank test was employed to calculate survival rate. A Cox regression multivariate analysis was performed to determine independent prognostic factors. The results demonstrated that CEP55 expression in ESCC was significantly higher than that of CHEM (P<0.001). Overexpression of CEP55 was significantly associated with differentiation degree (P=0.022), T stage (P=0.019), lymph node metastasis (P=0.033), clinicopathological staging (P=0.002) and tumor recurrence (P=0.021) in locally advanced ESCC patients. In addition, CEP55 overexpression was significantly associated with reduced overall survival of patients after surgery (P=0.012). The 5-year survival rate of patients without CEP55 overexpression was significantly higher than that of patients with CEP55 overexpression (P=0.012). Therefore, these findings suggest that CEP55 overexpression correlates with poor prognosis in locally advanced ESCC patients. PMID:28123547

  10. An advanced system model for the prediction of the clinical task performance of radiographic systems

    NASA Astrophysics Data System (ADS)

    Töpfer, Karin; Keelan, Brian W.; Sugiro, Francisca

    2007-03-01

    A flexible software tool was developed that combines predictive models for detector noise and blur with image simulation and an improved human observer model to predict the clinical task performance of existing and future radiographic systems. The model starts with high-fidelity images from a database and mathematical models of common disease features, which may be added to the images at desired contrast levels. These images are processed through the entire imaging chain including capture, the detector, image processing, and hardcopy or softcopy display. The simulated images and the viewing conditions are passed to a human observer model, which calculates the detectability index d' of the signal (disease or target feature). The visual model incorporates a channelized Hotelling observer with a luminance-dependent contrast sensitivity function and two types of internal visual system noise (intrinsic and image background-induced). It was optimized based on three independent human observer studies of target detection, and is able to predict d' over a wide range of viewing conditions, background complexities, and target spatial frequency content. A more intuitive metric of system performance, Task-Specific Detective Efficiency (TSDE), is defined to indicate how much detector improvements would translate to better radiologist performance. The TSDE is calculated as the squared ratio of d' for a system with the actual detector and a hypothetical system containing an ideal detector. A low TSDE, e.g., 5% for the detection of 0.1 mm microcalcifications in typical mammography systems, indicates that improvements in the detector characteristics are likely to translate to better detection performance. The TSDE of lung nodule detection is as high as 75% even with the detective quantum efficiency (DQE) of the detector not exceeding 24%. Applications of the model to system optimizations for flat-panel detectors, in mammography and dual energy digital radiography, are discussed.

  11. Advanced Train and Traffic Control Based on Prediction of Train Movement

    NASA Astrophysics Data System (ADS)

    Hiraguri, Shigeto; Hirao, Yuji; Watanabe, Ikuo; Tomii, Norio; Hase, Shinichi

    Trains are often forced to decelerate or stop between stations on commuter lines due to the delay of the preceding train. If a train stops between stations, both the travel time and the interval between trains will increase. This situation has an adverse effect on energy consumption. To solve this problem, we propose a new train control method based on the prediction of train movement and data communications between railway sub-systems. Computer simulations are carried out to verify the effect of the proposed method. As a result, it has been proved that the new method reduces the train stopping time between stations and the electric energy consumption at substations.

  12. Prediction of Dynamic Stall Characteristics Using Advanced Non-Linear Panel Methods.

    DTIC Science & Technology

    1984-04-04

    three- dimensional method , incorporating the techniques that are being examined in the two-dimensional pilot code. r.• - t... . .. -..-. .°.- S °"°"° I...RD-Ai48 453 PREDICTION OF DYNAMIC STRLL CHARACTERISTICS USING 1/1 RDVRNCED NON-LINERR PAN..(U) ANALYTICAL METHODS INC REDMOND WA B MRSKEW ET AL. 84...1 2.0 micROCOPY RESOLUTION TEST CHART hAyl0#dM. @UAU M STAUIOAPOI A VOSR-TR 84.0 97 5 Analytical methods Report 8406 FINAL REPORT Tw. ’ PREDICITON OF

  13. Usefulness of human epididymis protein 4 in predicting cytoreductive surgical outcomes for advanced ovarian tubal and peritoneal carcinoma

    PubMed Central

    Tang, Zhijian; Chang, Xiaohong; Ye, Xue; Li, Yi; Cheng, Hongyan

    2015-01-01

    Objective Human epididymis protein 4 (HE4) is a promising biomarker of epithelial ovarian cancer (EOC). But its role in assessing the primary optimal debulking (OD) of EOC remains unknown. The purpose of this study is to elucidate the ability of preoperative HE4 in predicting the primary cytoreductive outcomes in advanced EOC, tubal or peritoneal carcinoma. Methods We reviewed the records of 90 patients with advanced ovarian, tubal or peritoneal carcinoma who underwent primary cytoreduction at the Department of Obstetrics and Gynecology of Peking University People’s Hospital between November 2005 and October 2010. Preoperative serum HE4 and CA125 levels were detected with EIA kit. A receiver operating characteristic (ROC) curve was used to determine the most useful HE4 cut-off value. Logistic regression analysis was performed to identify significant preoperative clinical characteristics to predict optimal primary cytoreduction. Results OD was achieved in 47.7% (43/48) of patients. The median preoperative HE4 level for patients with OD vs. suboptimal debulking was 423 and 820 pmol/L, respectively (P<0.001). The areas under the ROC curve for HE4 and CA125 were 0.716 and 0.599, respectively (P=0.080). The most useful HE4 cut-off value was 473 pmol/L. Suboptimal cytoreduction was obtained in 66.7% (38/57) of cases with HE4 ≥473 pmol/L compared with only 27.3% (9/33) of cases with HE4 <473 pmol/L. At this threshold, the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for diagnosing suboptimal debulking were 81%, 56%, 67%, and 73%, respectively. Logistic regression analysis showed that the patients with HE4 ≥473 pmol/L were less likely to achieve OD (odds ratio =5.044, P=0.002). Conclusions Preoperative serum HE4 may be helpful to predict whether optimal cytoreductive surgery could be obtained or whether extended cytoreduction would be needed by an interdisciplinary team. PMID:26157328

  14. MicroRNA-31 Emerges as a Predictive Biomarker of Pathological Response and Outcome in Locally Advanced Rectal Cancer.

    PubMed

    Caramés, Cristina; Cristobal, Ion; Moreno, Víctor; Marín, Juan P; González-Alonso, Paula; Torrejón, Blanca; Minguez, Pablo; Leon, Ana; Martín, José I; Hernández, Roberto; Pedregal, Manuel; Martín, María J; Cortés, Delia; García-Olmo, Damian; Fernández, María J; Rojo, Federico; García-Foncillas, Jesús

    2016-06-03

    Neoadjuvant chemoradiotherapy (CRT) followed by total mesorectal excision has emerged as the standard treatment for locally advanced rectal cancer (LARC) patients. However, many cases do not respond to neoadjuvant CRT, suffering unnecessary toxicities and surgery delays. Thus, identification of predictive biomarkers for neoadjuvant CRT is a current clinical need. In the present study, microRNA-31 expression was measured in formalin-fixed paraffin-embedded (FFPE) biopsies from 78 patients diagnosed with LARC who were treated with neoadjuvant CRT. Then, the obtained results were correlated with clinical and pathological characteristics and outcome. High microRNA-31 (miR-31) levels were found overexpressed in 34.2% of cases. Its overexpression significantly predicted poor pathological response (p = 0.018) and worse overall survival (OS) (p = 0.008). The odds ratio for no pathological response among patients with miR-31 overexpression was 0.18 (Confidence Interval = 0.06 to 0.57; p = 0.003). Multivariate analysis corroborated the clinical impact of miR-31 in determining pathological response to neoadjuvant CRT as well as OS. Altogether, miR-31 quantification emerges as a novel valuable clinical tool to predict both pathological response and outcome in LARC patients.

  15. MicroRNA-31 Emerges as a Predictive Biomarker of Pathological Response and Outcome in Locally Advanced Rectal Cancer

    PubMed Central

    Caramés, Cristina; Cristobal, Ion; Moreno, Víctor; Marín, Juan P.; González-Alonso, Paula; Torrejón, Blanca; Minguez, Pablo; Leon, Ana; Martín, José I.; Hernández, Roberto; Pedregal, Manuel; Martín, María J.; Cortés, Delia; García-Olmo, Damian; Fernández, María J.; Rojo, Federico; García-Foncillas, Jesús

    2016-01-01

    Neoadjuvant chemoradiotherapy (CRT) followed by total mesorectal excision has emerged as the standard treatment for locally advanced rectal cancer (LARC) patients. However, many cases do not respond to neoadjuvant CRT, suffering unnecessary toxicities and surgery delays. Thus, identification of predictive biomarkers for neoadjuvant CRT is a current clinical need. In the present study, microRNA-31 expression was measured in formalin-fixed paraffin-embedded (FFPE) biopsies from 78 patients diagnosed with LARC who were treated with neoadjuvant CRT. Then, the obtained results were correlated with clinical and pathological characteristics and outcome. High microRNA-31 (miR-31) levels were found overexpressed in 34.2% of cases. Its overexpression significantly predicted poor pathological response (p = 0.018) and worse overall survival (OS) (p = 0.008). The odds ratio for no pathological response among patients with miR-31 overexpression was 0.18 (Confidence Interval = 0.06 to 0.57; p = 0.003). Multivariate analysis corroborated the clinical impact of miR-31 in determining pathological response to neoadjuvant CRT as well as OS. Altogether, miR-31 quantification emerges as a novel valuable clinical tool to predict both pathological response and outcome in LARC patients. PMID:27271609

  16. A model to predict deflection of bevel-tipped active needle advancing in soft tissue.

    PubMed

    Datla, Naresh V; Konh, Bardia; Honarvar, Mohammad; Podder, Tarun K; Dicker, Adam P; Yu, Yan; Hutapea, Parsaoran

    2014-03-01

    Active needles are recently being developed to improve steerability and placement accuracy for various medical applications. These active needles can bend during insertion by actuators attached to their bodies. The bending of active needles enables them to be steered away from the critical organs on the way to target and accurately reach target locations previously unachievable with conventional rigid needles. These active needles combined with an asymmetric bevel-tip can further improve their steerability. To optimize the design and to develop accurate path planning and control algorithms, there is a need to develop a tissue-needle interaction model. This work presents an energy-based model that predicts needle deflection of active bevel-tipped needles when inserted into the tissue. This current model was based on an existing energy-based model for bevel-tipped needles, to which work of actuation was included in calculating the system energy. The developed model was validated with needle insertion experiments with a phantom material. The model predicts needle deflection reasonably for higher diameter needles (11.6% error), whereas largest error was observed for the smallest needle diameter (24.7% error).

  17. Large-scale hydrological modelling by using modified PUB recommendations: the India-HYPE case

    NASA Astrophysics Data System (ADS)

    Pechlivanidis, I. G.; Arheimer, B.

    2015-11-01

    The scientific initiative Prediction in Ungauged Basins (PUB) (2003-2012 by the IAHS) put considerable effort into improving the reliability of hydrological models to predict flow response in ungauged rivers. PUB's collective experience advanced hydrologic science and defined guidelines to make predictions in catchments without observed runoff data. At present, there is a raised interest in applying catchment models to large domains and large data samples in a multi-basin manner, to explore emerging spatial patterns or learn from comparative hydrology. However, such modelling involves additional sources of uncertainties caused by the inconsistency between input data sets, i.e. particularly regional and global databases. This may lead to inaccurate model parameterisation and erroneous process understanding. In order to bridge the gap between the best practices for flow predictions in single catchments and multi-basins at the large scale, we present a further developed and slightly modified version of the recommended best practices for PUB by Takeuchi et al. (2013). By using examples from a recent HYPE (Hydrological Predictions for the Environment) hydrological model set-up across 6000 subbasins for the Indian subcontinent, named India-HYPE v1.0, we explore the PUB recommendations, identify challenges and recommend ways to overcome them. We describe the work process related to (a) errors and inconsistencies in global databases, unknown human impacts, and poor data quality; (b) robust approaches to identify model parameters using a stepwise calibration approach, remote sensing data, expert knowledge, and catchment similarities; and (c) evaluation based on flow signatures and performance metrics, using both multiple criteria and multiple variables, and independent gauges for "blind tests". The results show that despite the strong physiographical gradient over the subcontinent, a single model can describe the spatial variability in dominant hydrological processes at the

  18. Recovery Act. Development and Validation of an Advanced Stimulation Prediction Model for Enhanced Geothermal System

    SciTech Connect

    Gutierrez, Marte

    2016-12-31

    The research project aims to develop and validate an advanced computer model that can be used in the planning and design of stimulation techniques to create engineered reservoirs for Enhanced Geothermal Systems. The specific objectives of the proposal are to: 1) Develop a true three-dimensional hydro-thermal fracturing simulator that is particularly suited for EGS reservoir creation. 2) Perform laboratory scale model tests of hydraulic fracturing and proppant flow/transport using a polyaxial loading device, and use the laboratory results to test and validate the 3D simulator. 3) Perform discrete element/particulate modeling of proppant transport in hydraulic fractures, and use the results to improve understand of proppant flow and transport. 4) Test and validate the 3D hydro-thermal fracturing simulator against case histories of EGS energy production. 5) Develop a plan to commercialize the 3D fracturing and proppant flow/transport simulator. The project is expected to yield several specific results and benefits. Major technical products from the proposal include: 1) A true-3D hydro-thermal fracturing computer code that is particularly suited to EGS, 2) Documented results of scale model tests on hydro-thermal fracturing and fracture propping in an analogue crystalline rock, 3) Documented procedures and results of discrete element/particulate modeling of flow and transport of proppants for EGS applications, and 4) Database of monitoring data, with focus of Acoustic Emissions (AE) from lab scale modeling and field case histories of EGS reservoir creation.

  19. Recovery Act. Development and Validation of an Advanced Stimulation Prediction Model for Enhanced Geothermal Systems

    SciTech Connect

    Gutierrez, Marte

    2013-12-31

    This research project aims to develop and validate an advanced computer model that can be used in the planning and design of stimulation techniques to create engineered reservoirs for Enhanced Geothermal Systems. The specific objectives of the proposal are to; Develop a true three-dimensional hydro-thermal fracturing simulator that is particularly suited for EGS reservoir creation; Perform laboratory scale model tests of hydraulic fracturing and proppant flow/transport using a polyaxial loading device, and use the laboratory results to test and validate the 3D simulator; Perform discrete element/particulate modeling of proppant transport in hydraulic fractures, and use the results to improve understand of proppant flow and transport; Test and validate the 3D hydro-thermal fracturing simulator against case histories of EGS energy production; and Develop a plan to commercialize the 3D fracturing and proppant flow/transport simulator. The project is expected to yield several specific results and benefits. Major technical products from the proposal include; A true-3D hydro-thermal fracturing computer code that is particularly suited to EGS; Documented results of scale model tests on hydro-thermal fracturing and fracture propping in an analogue crystalline rock; Documented procedures and results of discrete element/particulate modeling of flow and transport of proppants for EGS applications; and Database of monitoring data, with focus of Acoustic Emissions (AE) from lab scale modeling and field case histories of EGS reservoir creation.

  20. Advances and challenges in biomarker development for type 1 diabetes prediction and prevention using omic technologies

    PubMed Central

    Carey, Colleen; Purohit, Sharad; She, Jin-Xiong

    2010-01-01

    Importance of the field Biomarkers are essential for the identification of high risk children as well as monitoring of prevention outcomes for type 1 diabetes (T1D). Areas covered in this review This review discusses progress, opportunities and challenges in biomarker discovery and validation using high throughput genomic, transcriptomic and proteomic technologies. The authors also suggest potential solutions to deal with the current challenges. What the reader will gain Readers will gain an overview of the current status on T1D biomarkers, an integrated review of three omic technologies, their applications and limitations for biomarker discovery and validation, and a critical discussion of the major issues encountered in biomarker development. Take home message Better biomarkers are still urgently needed for T1D prediction and prevention. The high throughput omic technologies offer great opportunities but also face significant challenges that have to be solved before their potential for biomarker development is fully realized. PMID:20885991

  1. Correlation of predicted and measured thermal stresses on an advanced aircraft structure with similar materials

    NASA Technical Reports Server (NTRS)

    Jenkins, J. M.

    1979-01-01

    A laboratory heating test simulating hypersonic heating was conducted on a heat-sink type structure to provide basic thermal stress measurements. Six NASTRAN models utilizing various combinations of bar, shear panel, membrane, and plate elements were used to develop calculated thermal stresses. Thermal stresses were also calculated using a beam model. For a given temperature distribution there was very little variation in NASTRAN calculated thermal stresses when element types were interchanged for a given grid system. Thermal stresses calculated for the beam model compared similarly to the values obtained for the NASTRAN models. Calculated thermal stresses compared generally well to laboratory measured thermal stresses. A discrepancy of signifiance occurred between the measured and predicted thermal stresses in the skin areas. A minor anomaly in the laboratory skin heating uniformity resulted in inadequate temperature input data for the structural models.

  2. Predictive biomarkers for response to therapy in advanced colorectal/rectal adenocarcinoma.

    PubMed

    Kapur, Payal

    2012-01-01

    Over the past couple of decades, with discovery of novel targeted therapies, and expansion of our understanding of the molecular biology of rectal cancer, there has been an emergence of a wide variety of therapeutic options designed to facilitate a personalized approach for the treatment of this malignancy. A plethora of new prognostic and predictive single genes and proteins are being discovered that may reflect susceptibility and/or resistance to therapy. Pathologic complete response rates occur in 10-16% of patients and have been shown to correlate with both disease-free and overall survival. However, the response to neoadjuvant therapy remains variable and unpredictable. In this review, some of these novel markers are discussed for their potential use as pharmacogenetic predictors for specific therapy, drug toxicity, and disease outcome.

  3. How to predict hydrological effects of local land use change: how the vegetation parameterisation for short rotation coppices influences model results

    NASA Astrophysics Data System (ADS)

    Richter, F.; Döring, C.; Jansen, M.; Panferov, O.; Spank, U.; Bernhofer, C.

    2015-08-01

    Among the different bioenergy sources, short rotation coppices (SRC) with poplar and willow trees are one of the promising options in Europe. SRC provide not only woody biomass but also additional ecosystem services. However, a known shortcoming is the potentially lower groundwater recharge caused by the potentially higher evapotranspiration demand compared to annual crops. The complex feedbacks between vegetation cover and water cycle can be only correctly assessed by application of well-parameterised and calibrated numerical models. In the present study, the hydrological model system WaSim (Wasserhaushalts-Simulations-Model) is implemented for assessment of the water balance. The focus is the analysis of simulation uncertainties caused by the use of guidelines or transferred parameter sets from scientific literature compared to "actual" parameterisations derived from local measurements of leaf area index (LAI), stomatal resistance (Rsc) and date of leaf unfolding (LU). The analysis showed that uncertainties in parameterisation of vegetation lead to implausible model results. LAI, Rsc and LU are the most sensitive plant physiological parameters concerning the effects of enhanced SRC cultivation on water budget or groundwater recharge. Particularly sensitive is the beginning of the growing season, i.e. LU. When this estimation is wrong, the accuracy of LAI and Rsc description plays a minor role. Our analyses illustrate that the use of locally measured vegetation parameters, like maximal LAI, and meteorological variables, like air temperature, to estimate LU give better results than literature data or data from remote network stations. However, the direct implementation of locally measured data is not always advisable or possible. Regarding Rsc, the adjustment of local measurements gives the best model evaluation. For local and accurate studies, measurements of model sensitive parameters like LAI, Rsc and LU are valuable information. The derivation of these model

  4. Recent advances in computational predictions of NMR parameters for the structure elucidation of carbohydrates: methods and limitations.

    PubMed

    Toukach, Filip V; Ananikov, Valentine P

    2013-11-07

    All living systems are comprised of four fundamental classes of macromolecules--nucleic acids, proteins, lipids, and carbohydrates (glycans). Glycans play a unique role of joining three principal hierarchical levels of the living world: (1) the molecular level (pathogenic agents and vaccine recognition by the immune system, metabolic pathways involving saccharides that provide cells with energy, and energy accumulation via photosynthesis); (2) the nanoscale level (cell membrane mechanics, structural support of biomolecules, and the glycosylation of macromolecules); (3) the microscale and macroscale levels (polymeric materials, such as cellulose, starch, glycogen, and biomass). NMR spectroscopy is the most powerful research approach for getting insight into the solution structure and function of carbohydrates at all hierarchical levels, from monosaccharides to oligo- and polysaccharides. Recent progress in computational procedures has opened up novel opportunities to reveal the structural information available in the NMR spectra of saccharides and to advance our understanding of the corresponding biochemical processes. The ability to predict the molecular geometry and NMR parameters is crucial for the elucidation of carbohydrate structures. In the present paper, we review the major NMR spectrum simulation techniques with regard to chemical shifts, coupling constants, relaxation rates and nuclear Overhauser effect prediction applied to the three levels of glycomics. Outstanding development in the related fields of genomics and proteomics has clearly shown that it is the advancement of research tools (automated spectrum analysis, structure elucidation, synthesis, sequencing and amplification) that drives the large challenges in modern science. Combining NMR spectroscopy and the computational analysis of structural information encoded in the NMR spectra reveals a way to the automated elucidation of the structure of carbohydrates.

  5. Pre-adjuvant chemotherapy leukocyte count may predict the outcome for advanced gastric cancer after radical resection.

    PubMed

    Pei, Dong; Zhu, Fang; Chen, Xiaofeng; Qian, Jing; He, Shaohua; Qian, Yingying; Shen, Hua; Liu, Yiqian; Xu, Jiali; Shu, Yongqian

    2014-03-01

    Gastric cancer (GC) has a high morbidity worldwide each year especially in China and advanced GC is well known with poor prognosis, for which surgical resection combine adjuvant chemotherapy is the optimal choice for therapy. Leukocyte is an important index during the treatment for its influence on drugs' dosage and tolerance. Therefore, peripheral blood leukocyte and its subsets during adjuvant chemotherapy may have great clinical value for predicting prognostic. In this retrospective study, we showed the distribution of white blood cell and its subsets in the baseline period before adjuvant chemotherapy in 399 patients who underwent radical resection for advanced GC from January 1, 2008 to August 31, 2012. We investigated the relationship between leukocyte count and overall survival (OS) as well as disease-free survival (DFS). In these patients, females were more likely to have less white blood cells after operation (P=0.016). Patients with pre-chemotherapy leukocyte count less than 4×10(9)/L got worse DFS (P=0.028) and OS (P=0.016). In multivariate analysis, tumor size ≥ 6cm (P=0.033), TNM stage IV (P=0.024), vascular or nerval invasion (P=0.005) and leukocyte count less than 4.0×10(9)/L (P=0.019) was associated with poor DFS. TNM stage IV (P=0.008), vascular or nerval invasion (P=0.001) and lower leukocyte count (P=0.045) were independent risk factors for poor OS. Taken together, our findings suggest that pre-adjuvant chemotherapy peripheral blood leukocyte count correlates with clinical outcome of patients with advanced GC after radical resection.

  6. HPV Genotypes Predict Survival Benefits From Concurrent Chemotherapy and Radiation Therapy in Advanced Squamous Cell Carcinoma of the Cervix

    SciTech Connect

    Wang, Chun-Chieh; Lai, Chyong-Huey; Huang, Yi-Ting; Chao, Angel; Chou, Hung-Hsueh; Hong, Ji-Hong

    2012-11-15

    Purpose: To study the prognostic value of human papillomavirus (HPV) genotypes in patients with advanced cervical cancer treated with radiation therapy (RT) alone or concurrent chemoradiation therapy (CCRT). Methods and Materials: Between August 1993 and May 2000, 327 patients with advanced squamous cell carcinoma of the cervix (International Federation of Gynecology and Obstetrics stage III/IVA or stage IIB with positive lymph nodes) were eligible for this study. HPV genotypes were determined using the Easychip Registered-Sign HPV genechip. Outcomes were analyzed using Kaplan-Meier survival analysis and the Cox proportional hazards model. Results: We detected 22 HPV genotypes in 323 (98.8%) patients. The leading 4 types were HPV16, 58, 18, and 33. The 5-year overall and disease-specific survival estimates for the entire cohort were 41.9% and 51.4%, respectively. CCRT improved the 5-year disease-specific survival by an absolute 9.8%, but this was not statistically significant (P=.089). There was a significant improvement in disease-specific survival in the CCRT group for HPV18-positive (60.9% vs 30.4%, P=.019) and HPV58-positive (69.3% vs 48.9%, P=.026) patients compared with the RT alone group. In contrast, the differences in survival with CCRT compared with RT alone in the HPV16-positive and HPV-33 positive subgroups were not statistically significant (P=.86 and P=.53, respectively). An improved disease-specific survival was observed for CCRT treated patients infected with both HPV16 and HPV18, but these differenced also were not statistically significant. Conclusions: The HPV genotype may be a useful predictive factor for the effect of CCRT in patients with advanced squamous cell carcinoma of the cervix. Verifying these results in prospective trials could have an impact on tailoring future treatment based on HPV genotype.

  7. Correcting Unintended Perturbation Biases in Hydrologic Data Assimilation Using the Ensemble Kalman Filter

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Recent advances in hydrologic data assimilation have demonstrated the value of remotely sensed surface soil moisture in improving forecasts of key hydrologic variables such as root-zone soil moisture and surface runoff. In hydrologic data assimilation, the ensemble Kalman filter (EnKF) provides a ro...

  8. Advanced Procedures for Long-Term Creep Data Prediction for 2.25 Chromium Steels

    NASA Astrophysics Data System (ADS)

    Whittaker, Mark T.; Wilshire, Brian

    2013-01-01

    A critical review of recent creep studies concluded that traditional approaches such as steady-state behavior, power law equations, and the view that diffusional creep mechanisms are dominant at low stresses should be seriously reconsidered. Specifically, creep strain rate against time curves show that a decaying primary rate leads into an accelerating tertiary stage, giving a minimum rather than a secondary period. Conventional steady-state mechanisms should therefore be abandoned in favor of an understanding of the processes governing strain accumulation and the damage phenomena causing tertiary creep and fracture. Similarly, creep always takes place by dislocation processes, with no change to diffusional creep mechanisms with decreasing stress, negating the concept of deformation mechanism maps. Alternative descriptions are then provided by normalizing the applied stress through the ultimate tensile stress and yield stress at the creep temperature. In this way, the resulting Wilshire equations allow accurate prediction of 100,00 hours of creep data using only property values from tests lasting 5000 hours for a series of 2.25 chromium steels, namely grades 22, 23, and 24.

  9. Predictive transport simulations of real-time profile control in JET advanced tokamak plasmas

    NASA Astrophysics Data System (ADS)

    Tala, T.; Laborde, L.; Mazon, D.; Moreau, D.; Corrigan, G.; Crisanti, F.; Garbet, X.; Heading, D.; Joffrin, E.; Litaudon, X.; Parail, V.; Salmi, A.; EFDA-JET workprogramme, contributors to the

    2005-09-01

    Predictive, time-dependent transport simulations with a semi-empirical plasma model have been used in closed-loop simulations to control the q-profile and the strength and location of the internal transport barrier (ITB). Five transport equations (Te, Ti, q, ne, vΦ) are solved, and the power levels of lower hybrid current drive, NBI and ICRH are calculated in a feedback loop determined by the feedback controller matrix. The real-time control (RTC) technique and algorithms used in the transport simulations are identical to those implemented and used in JET experiments (Laborde L. et al 2005 Plasma Phys. Control. Fusion 47 155 and Moreau D. et al 2003 Nucl. Fusion 43 870). The closed-loop simulations with RTC demonstrate that varieties of q-profiles and pressure profiles in the ITB can be achieved and controlled simultaneously. The simulations also showed that with the same RTC technique as used in JET experiments, it is possible to sustain the q-profiles and pressure profiles close to their set-point profiles for longer than the current diffusion time. In addition, the importance of being able to handle the multiple time scales to control the location and strength of the ITB is pointed out. Several future improvements and perspectives of the RTC scheme are presented.

  10. Immunohistochemical prediction of lapatinib efficacy in advanced HER2-positive breast cancer patients

    PubMed Central

    Duchnowska, Renata; Wysocki, Piotr J.; Korski, Konstanty; Czartoryska-Arłukowicz, Bogumiła; Niwińska, Anna; Orlikowska, Marlena; Radecka, Barbara; Studziński, Maciej; Demlova, Regina; Ziółkowska, Barbara; Merdalska, Monika; Hajac, Łukasz; Myśliwiec, Paulina; Zuziak, Dorota; Dębska-Szmich, Sylwia; Lang, Istvan; Foszczyńska-Kłoda, Małgorzata; Karczmarek-Borowska, Bożenna; Żawrocki, Anton; Kowalczyk, Anna; Biernat, Wojciech; Jassem, Jacek

    2016-01-01

    Molecular mechanisms of lapatinib resistance in breast cancer are not well understood. The aim of this study was to correlate expression of selected proteins involved in ErbB family signaling pathways with clinical efficacy of lapatinib. Study group included 270 HER2-positive advanced breast cancer patients treated with lapatinib and capecitabine. Immunohistochemical expression of phosphorylated adenosine monophosphate-activated protein (p-AMPK), mitogen-activated protein kinase (p-MAPK), phospho (p)-p70S6K, cyclin E, phosphatase and tensin homolog were analyzed in primary breast cancer samples. The best discriminative value for progression-free survival (PFS) was established for each biomarker and subjected to multivariate analysis. At least one biomarker was determined in 199 patients. Expression of p-p70S6K was independently associated with longer (HR 0.45; 95% CI: 0.25–0.81; p = 0.009), and cyclin E with shorter PFS (HR 1.83; 95% CI: 1.06–3.14; p = 0.029). Expression of p-MAPK (HR 1.61; 95% CI 1.13–2.29; p = 0.009) and cyclin E (HR 2.99; 95% CI: 1.29–6.94; p = 0.011) was correlated with shorter, and expression of estrogen receptor (HR 0.65; 95% CI 0.43–0.98; p = 0.041) with longer overall survival. Expression of p-AMPK negatively impacted response to treatment (HR 3.31; 95% CI 1.48–7.44; p = 0.004) and disease control (HR 3.07; 95% CI 1.25–7.58; p = 0.015). In conclusion: the efficacy of lapatinib seems to be associated with the activity of downstream signaling pathways – AMPK/mTOR and Ras/Raf/MAPK. Further research is warranted to assess the clinical utility of these data and to determine a potential role of combining lapatinib with MAPK pathway inhibitors. PMID:26623720

  11. Hydrology Domain Cyberinfrastructures: Successes, Challenges, and Opportunities

    NASA Astrophysics Data System (ADS)

    Horsburgh, J. S.

    2015-12-01

    Anticipated changes to climate, human population, land use, and urban form will alter the hydrology and availability of water within the water systems on which the world's population relies. Understanding the effects of these changes will be paramount in sustainably managing water resources, as well as maintaining associated capacity to provide ecosystem services (e.g., regulating flooding, maintaining instream flow during dry periods, cycling nutrients, and maintaining water quality). It will require better information characterizing both natural and human mediated hydrologic systems and enhanced ability to generate, manage, store, analyze, and share growing volumes of observational data. Over the past several years, a number of hydrology domain cyberinfrastructures have emerged or are currently under development that are focused on providing integrated access to and analysis of data for cross-domain synthesis studies. These include the Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) Hydrologic Information System (HIS), the Critical Zone Observatory Information System (CZOData), HyroShare, the BiG CZ software system, and others. These systems have focused on sharing, integrating, and analyzing hydrologic observations data. This presentation will describe commonalities and differences in the cyberinfrastructure approaches used by these projects and will highlight successes and lessons learned in addressing the challenges of big and complex data. It will also identify new challenges and opportunities for next generation cyberinfrastructure and a next generation of cyber-savvy scientists and engineers as developers and users.

  12. Predictive value of advanced glycation end products for the development of post-infarction heart failure: a preliminary report

    PubMed Central

    2012-01-01

    Background Since post-infarction heart failure (HF) determines a great morbidity and mortality, and given the physiopathology implications of advanced glycation end products (AGE) in the genesis of myocardial dysfunction, it was intended to analyze the prognostic value of these molecules in order to predict post-infarction HF development. Methods A prospective clinical study in patients after first acute coronary syndrome was conducted. The follow-up period was consisted in 1 year. In 194 patients consecutively admitted in the coronary unit for myocardial infarct fluorescent AGE levels were measured. The association between glycaemic parameters and the development of post-infarction HF were analyzed in those patients. Finally, we identified the variables with independent predictor value by performing a multivariate analysis of Hazard ratio for Cox regression. Results Eleven out of 194 patients (5.6%) developed HF during follow-up (median: 1.0 years [0.8 - 1.5 years]). Even though basal glucose, fructosamine and glycated haemoglobin were significant predictive factors in the univariate analysis, after being adjusted by confounding variables and AGE they lost their statistical signification. Only AGE (Hazard Ratio 1.016, IC 95%: 1.006-1.026; p<0,001), together with NT-proBNP and the infarct extension were predictors for post-infarction HF development, where AGE levels over the median value 5-fold increased the risk of HF development during follow-up. Conclusions AGE are an independent marker of post-infarction HF development risk. PMID:22909322

  13. Neoadjuvant chemotherapy in women with large and locally advanced breast cancer: chemoresistance and prediction of response to drug therapy.

    PubMed

    Chuthapisith, S; Eremin, J M; El-Sheemy, M; Eremin, O

    2006-08-01

    Patients with large and locally advanced breast cancer (LLABC) present with a therapeutic challenge and undergo multimodality treatment. Many such patients receive neoadjuvant chemotherapy (NAC) prior to surgery. However, a number of these patients do not respond well to NAC and only a percentage (usually less than 30%) obtains a complete or optimal response. A range of mechanisms are believed to be involved in this chemoresistance, including ATP binding cassette (ABC) transporter overexpression, dysregulation of apoptosis and possibly increased numbers of cancer stem cells. The chemoresistant processes may be due to more than one mechanism. The ability to predict a response to NAC would be beneficial, targeting expensive and toxic drug treatment to those likely to respond and providing a therapeutic strategy for further post-operative chemotherapy. Currently, many biomarkers have been studied with a view to establishing a predictor of response. However, no single biomarker appears to be effective. Genomics is a novel biotechnological process which is being used to predict response to drug therapy; this work is currently at an early stage of development

  14. Hydrologic Services Course.

    ERIC Educational Resources Information Center

    National Oceanic and Atmospheric Administration (DOC), Rockville, MD. National Weather Service.

    A course to develop an understanding of the scope of water resource activities, of the need for forecasting, of the National Weather Service's role in hydrology, and of the proper procedures to follow in fulfilling this role is presented. The course is one of self-help, guided by correspondence. Nine lessons are included: (1) Hydrology in the…

  15. Hands-On Hydrology

    ERIC Educational Resources Information Center

    Mathews, Catherine E.; Monroe, Louise Nelson

    2004-01-01

    A professional school and university collaboration enables elementary students and their teachers to explore hydrology concepts and realize the beneficial functions of wetlands. Hands-on experiences involve young students in determining water quality at field sites after laying the groundwork with activities related to the hydrologic cycle,…

  16. Seeking parsimony in hydrology and water resources technology

    NASA Astrophysics Data System (ADS)

    Koutsoyiannis, D.

    2009-04-01

    The principle of parsimony, also known as the principle of simplicity, the principle of economy and Ockham's razor, advises scientists to prefer the simplest theory among those that fit the data equally well. In this, it is an epistemic principle but reflects an ontological characterization that the universe is ultimately parsimonious. Is this principle useful and can it really be reconciled with, and implemented to, our modelling approaches of complex hydrological systems, whose elements and events are extraordinarily numerous, different and unique? The answer underlying the mainstream hydrological research of the last two decades seems to be negative. Hopes were invested to the power of computers that would enable faithful and detailed representation of the diverse system elements and the hydrological processes, based on merely "first principles" and resulting in "physically-based" models that tend to approach in complexity the real world systems. Today the account of such research endeavour seems not positive, as it did not improve model predictive capacity and processes comprehension. A return to parsimonious modelling seems to be again the promising route. The experience from recent research and from comparisons of parsimonious and complicated models indicates that the former can facilitate insight and comprehension, improve accuracy and predictive capacity, and increase efficiency. In addition - and despite aspiration that "physically based" models will have lower data requirements and, even, they ultimately become "data-free" - parsimonious models require fewer data to achieve the same accuracy with more complicated models. Naturally, the concepts that reconcile the simplicity of parsimonious models with the complexity of hydrological systems are probability theory and statistics. Probability theory provides the theoretical basis for moving from a microscopic to a macroscopic view of phenomena, by mapping sets of diverse elements and events of hydrological

  17. Numerical Simulations of Optical Turbulence Using an Advanced Atmospheric Prediction Model: Implications for Adaptive Optics Design

    NASA Astrophysics Data System (ADS)

    Alliss, R.

    2014-09-01

    Optical turbulence (OT) acts to distort light in the atmosphere, degrading imagery from astronomical telescopes and reducing the data quality of optical imaging and communication links. Some of the degradation due to turbulence can be corrected by adaptive optics. However, the severity of optical turbulence, and thus the amount of correction required, is largely dependent upon the turbulence at the location of interest. Therefore, it is vital to unders