Science.gov

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. 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.

  4. 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.

  5. 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.

  6. Seasonal Hydrologic Predictability: Sources and Limitations

    NASA Astrophysics Data System (ADS)

    Lettenmaier, D. P.

    2015-12-01

    I first review sources of predictability in seasonal hydrological forecasts. Recent work shows that at short lead times (typically up to a few months), hydrologic forecast skill is mostly controlled by hydrologic initial conditions (primarily soil moisture and where and when relevant, snow water storage), but at longer lead times, climate forecast skill dominates. Unfortunately, aside from a few special situations, climate forecast skill for lead times beyond about a month is minimal. Therefore, for practical purposes, hydrological initial conditions are the primary source of hydrological forecast skill. This is the premise of the widely used Ensemble Streamflow Prediction (ESP) method. I also investigate barriers to the use of seasonal hydrological forecasts in water resource systems operation. I review in particular work approximately a decade ago by Maurer, which casts light on the potential for improved reservoir system operations through improved forecasts as a function of the usable reservoir storage relative to the mean annual inflow, relative to the simplest forecast (climatology). In general, the potential economic benefits of improved forecasts are largest for relatively small reservoirs.

  7. 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.

  8. 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.

  9. 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.

  10. 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).

  11. 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). PMID:26667914

  12. 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

  13. 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

  14. Hydrologic Predictions in the Anthropocene: A Research Framework Based on a Co-evolutionary Socio-hydrologic Perspective

    NASA Astrophysics Data System (ADS)

    Sivapalan, M.; Bloeschl, G.

    2012-12-01

    The world is facing a water management crisis, in the context of fast rising demand for water due to growth of human populations and changing lifestyles, and depletion of freshwater resources. In many parts of the world, poor distribution of freshwater in relation to demand is already the cause of serious water scarcity, exacerbated by climate change. Cumulatively, these result in increased human appropriation of water resources, significant modification of landscapes, and a strong human imprint on water cycle dynamics from local to global scales. Hydrologic predictions in such a fast changing environment face significant challenges. Traditional models for predictions treat the hydrologic system as a simple input-output system, and propagate variability of external inputs or disturbances through the various hydrologic subsystems, but assuming stationarity. However, in a fast changing world, none of the subsystems can be assumed to be stationary, but as co-evolving parts of a complex system. The role of humans takes on an important role, which can no longer be assumed to independent of the natural system. We need new socio-hydrologic frameworks to observe, monitor, understand and predict the co-evolution of coupled human-natural systems. In this talk, using examples from one or more real-world settings (from Australia and Europe) involving human interactions with hydrologic systems, we will present new theoretical frameworks that should be adopted to advance the emergent new sub-discipline of socio-hydrology. The proposed research agenda is organized under (i) process socio-hydrology, (ii) comparative socio-hydrology, and (iii) historical socio-hydrology.

  15. 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.

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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.

  3. Comparing Sediment Yield Predictions from Different Hydrologic Modeling Schemes

    NASA Astrophysics Data System (ADS)

    Dahl, T. A.; Kendall, A. D.; Hyndman, D. W.

    2015-12-01

    Sediment yield, or the delivery of sediment from the landscape to a river, is a difficult process to accurately model. It is primarily a function of hydrology and climate, but influenced by landcover and the underlying soils. These additional factors make it much more difficult to accurately model than water flow alone. It is not intuitive what impact different hydrologic modeling schemes may have on the prediction of sediment yield. Here, two implementations of the Modified Universal Soil Loss Equation (MUSLE) are compared to examine the effects of hydrologic model choice. Both the Soil and Water Assessment Tool (SWAT) and the Landscape Hydrology Model (LHM) utilize the MUSLE for calculating sediment yield. SWAT is a lumped parameter hydrologic model developed by the USDA, which is commonly used for predicting sediment yield. LHM is a fully distributed hydrologic model developed primarily for integrated surface and groundwater studies at the watershed to regional scale. SWAT and LHM models were developed and tested for two large, adjacent watersheds in the Great Lakes region; the Maumee River and the St. Joseph River. The models were run using a variety of single model and ensemble downscaled climate change scenarios from the Coupled Model Intercomparison Project 5 (CMIP5). The initial results of this comparison are discussed here.

  4. 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.

  5. Hydrologic predictions on ungauged catchments using deterministic distributed modelling system

    NASA Astrophysics Data System (ADS)

    Tachecí, Pavel; Kimlová, Martina

    2010-05-01

    There is a need for warning system giving prediction of flash-flood risk conditions with sufficient advance even in source areas and in small tributaries catchments. New approach is based on combination of numerical weather prediction (NWP) model, radar or rain gauge data with distributed hydrologic mathematical model of particular area. Set of newly developed tools, customized for particular use in the Czech Hydrometeorological Institute (CHMI) environment enhance import of data and presentation of results. This forecast system focuses on hydrological modelling of running water balance in spatially distributed manner. Its computation is repeated day-to-day. Six models of particular basins (800 - 4000 km2), representing different conditions across the Czech Republic territory were calibrated and validated successfully. The Sázava river basin model (4.000 km2) is used for regular testing operation in CHMI Forecast centre since October 2007. Basic size of grid cells used in models is 300x300 m, basic time step of forecast is 1 day, but can be refined according to the input data. Water balance is computed using simplified 2-layer method for unsaturated zone, 2D approximation of Boussinesq equation for saturated zone, diffusion equation for overland flow and 1D kinematic equation for river flow (MIKE 11 model). The whole process of input data processing, model simulation and result generation may be run automatically or in step-by step mode via simple graphical user interface. Three types of input data are supported: •time series (temperature and precipitation) measured at observation stations and stored in CHMI database •radar data products (precipitation intensity field) •results of ALADIN weather forecast model (temperature and precipitation field). For forecast purposes, reference evapotranspiration is approximated according relationship to air temperature for every computational grid cell. The user may choose area (catchment) to be processed and period of

  6. Remote sensing of vegetation ecophysiological function for improved hydrologic prediction

    NASA Astrophysics Data System (ADS)

    Drewry, D.; Ruddell, B. L.

    2014-12-01

    Land surface hydrology in vegetated landscapes is strongly controlled by ecophysiological function. The coupling between photosynthesis, stomatal dynamics and leaf energy balance fundamentally links the hydrologic and carbon cycles, and provides a basis for examining the utility of observations of functional plant traits for hydrologic prediction. Here we explore the potential of solar induced fluorescence (SIF) and thermal infrared (TIR) remote sensing observations to improve the accuracy and reduce the uncertainty in hydrologic prediction. While SIF represents an emission of radiation associated with photosynthesis, TIR provides information on foliage temperature and is related to stomatal function and water stress. A set of remote observing system simulation experiments are conducted to quantify the value of remotely sensed observations of SIF and TIR when assimilated into a detailed vegetation biophysical model. The MLCan model discretizes a dense plant canopy to resolve vertical variation in photosynthesis, water vapor and energy exchange. Here we present extensions to MLCan that allow for direct computation of the canopy emission of both SIF and TIR. The detailed representation of the physical environment and biological functioning of structurally complex canopies makes MLCan an ideal simulation tool for exploring the impact of these two unique, and potentially synergistic observables. This work specifically addresses remote sensing capabilities on both recently launched (OCO-2) and near-term (ECOSTRESS) satellite platforms. We contrast the information gained through the assimilation of SIF and TIR observations to that of the assimilation of data related to physical states such as soil moisture and leaf area index.

  7. Predicting Soil Biological and Physical Properties Using Hydrological Properties

    NASA Astrophysics Data System (ADS)

    Geiger, L.; Hofmockel, K.; Kaleita, A.; Hargreaves, S.

    2012-12-01

    Soil biological and chemical properties vary at different spatial scales, which make predicting processes associated with these properties difficult. However, soil biological and chemical properties are important to fertility and ecosystem functioning. In this study, we used a Self Organizing Map (SOM) to determine whether soil hydrological characteristics can be used to characterize the distribution of a suite of soil biological and chemical properties. From a row crop field in south-central Iowa, we generated 36 sampling locations via a SOM, which were grouped into three categories according to hydrological properties by the SOM. Soil samples were then analyzed for microbial biomass, carbon and nitrogen mineralization potential, and organic and inorganic pools of carbon and nitrogen. We found that sampling locations in category 1 (potholes and toe slopes) had greater microbial biomass, total carbon, total nitrogen, and extractable organic carbon than compared locations in the two well-drained categories. Nitrogen and carbon mineralization and inorganic nitrogen pools did not differ significantly among the categories. These results demonstrate that hydrological characteristics can be used to predict relatively stable biological and chemical soil properties. However, prediction of nitrogen and carbon fluxes remains a challenge.

  8. Assessing predictability of a hydrological stochastic-dynamical system

    NASA Astrophysics Data System (ADS)

    Gelfan, Alexander

    2014-05-01

    The water cycle includes the processes with different memory that creates potential for predictability of hydrological system based on separating its long and short memory components and conditioning long-term prediction on slower evolving components (similar to approaches in climate prediction). In the face of the Panta Rhei IAHS Decade questions, it is important to find a conceptual approach to classify hydrological system components with respect to their predictability, define predictable/unpredictable patterns, extend lead-time and improve reliability of hydrological predictions based on the predictable patterns. Representation of hydrological systems as the dynamical systems subjected to the effect of noise (stochastic-dynamical systems) provides possible tool for such conceptualization. A method has been proposed for assessing predictability of hydrological system caused by its sensitivity to both initial and boundary conditions. The predictability is defined through a procedure of convergence of pre-assigned probabilistic measure (e.g. variance) of the system state to stable value. The time interval of the convergence, that is the time interval during which the system losses memory about its initial state, defines limit of the system predictability. The proposed method was applied to assess predictability of soil moisture dynamics in the Nizhnedevitskaya experimental station (51.516N; 38.383E) located in the agricultural zone of the central European Russia. A stochastic-dynamical model combining a deterministic one-dimensional model of hydrothermal regime of soil with a stochastic model of meteorological inputs was developed. The deterministic model describes processes of coupled heat and moisture transfer through unfrozen/frozen soil and accounts for the influence of phase changes on water flow. The stochastic model produces time series of daily meteorological variables (precipitation, air temperature and humidity), whose statistical properties are similar

  9. Predicting Hydrologic Response Through a Pooled Watershed Knowledge Base: A Hierarchical Bayesian Approach

    NASA Astrophysics Data System (ADS)

    Smith, T. J.; Marshall, L. A.; Sharma, A.

    2011-12-01

    Hydrologic modelers are confronted with the challenge of producing estimates of the uncertainty associated with model predictions across a wide array of watersheds, often under very limited data conditions. Statistical methods for hydrologic modeling have evolved rapidly over the recent past in response to these challenges, from improved strategies to both estimate optimal parameter values and predictive uncertainty to approaches that aim to link model parameters to watershed characteristics and allow parameters to be transferred to data-poor watersheds. However, despite the advances that have been made in the application of such statistical tools there remains significant work to be done, particularly regarding the quantification/transfer of predictive uncertainty at/to data-limited locations. Here, we present a hierarchical Bayesian modeling technique referred to as Bayes Empirical Bayes (BEB) as a means of addressing the difficulties in making reliable hydrologic predictions under uncertainty in data-limited watersheds. The BEB technique utilizes formal hierarchical Bayesian analysis (specifically the resultant posterior probability distributions for each estimated model parameter) to pool information from auxiliary watersheds to generate informed probability distributions for each parameter at a data-limited watershed of interest. The application of such a method has thus far been untested in hydrologic applications but has been used more extensively in ecological studies. This technique represents a significant departure from earlier attempts to make predictions in data-limited watersheds in both its usage of available data and its ability to simultaneously quantify predictive uncertainty directly. By utilizing the Bayesian toolkit under a hierarchical approach, information available from auxiliary watersheds can be integrated and summarized into the prediction at the site of interest.

  10. 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

  11. 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

  12. 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

  13. The efficacy of calibrating hydrologic model using remotely sensed evapotranspiration and soil moisture for streamflow prediction

    NASA Astrophysics Data System (ADS)

    Kunnath-Poovakka, A.; Ryu, D.; Renzullo, L. J.; George, B.

    2016-04-01

    Calibration of spatially distributed hydrologic models is frequently limited by the availability of ground observations. Remotely sensed (RS) hydrologic information provides an alternative source of observations to inform models and extend modelling capability beyond the limits of ground observations. This study examines the capability of RS evapotranspiration (ET) and soil moisture (SM) in calibrating a hydrologic model and its efficacy to improve streamflow predictions. SM retrievals from the Advanced Microwave Scanning Radiometer-EOS (AMSR-E) and daily ET estimates from the CSIRO MODIS ReScaled potential ET (CMRSET) are used to calibrate a simplified Australian Water Resource Assessment - Landscape model (AWRA-L) for a selection of parameters. The Shuffled Complex Evolution Uncertainty Algorithm (SCE-UA) is employed for parameter estimation at eleven catchments in eastern Australia. A subset of parameters for calibration is selected based on the variance-based Sobol' sensitivity analysis. The efficacy of 15 objective functions for calibration is assessed based on streamflow predictions relative to control cases, and relative merits of each are discussed. Synthetic experiments were conducted to examine the effect of bias in RS ET observations on calibration. The objective function containing the root mean square deviation (RMSD) of ET result in best streamflow predictions and the efficacy is superior for catchments with medium to high average runoff. Synthetic experiments revealed that accurate ET product can improve the streamflow predictions in catchments with low average runoff.

  14. On wireless sensing networks in hydrology: from observation to prediction

    NASA Astrophysics Data System (ADS)

    Vereecken, H.; Bogena, H. R.; Huisman, J. A.; Wei, Q.; Fang, Z.; Vanderborght, J.; Kollet, S. J.

    2015-12-01

    The use of wireless sensor networks (WSN) has gained increasing attention in the field of hydrology, because WSNs offer a unique potential to monitor the spatial and temporal dynamics of soil moisture at scales beyond the field scale. In addition, they provide unique opportunities for the validation of numerical models, hydrogeophysical measurement techniques, as well as for the calibration and validation of remotely sensed soil moisture data. In this presentation, we will discuss results of temporal and spatially resolved measurements of soil moisture using WSNs installed in two different small-scale catchments under forest (Wüstebach, Germany) and grassland (Rollesbroich, Germany). In combination with measurements of hydrological fluxes, we were able to close the water balance of the Wüstebach catchment up to 3% of the yearly rainfall. In addition, changes between wet and dry states of the catchment could be observed and related to a critical soil moisture content. Using stochastic analysis of water flow in the unsaturated zone and pedotransfer functions, we were able to predict subgrid variability of soil moisture. This framework also allowed deriving the spatial variability of soil hydraulic parameters using the relationship between the variance of soil moisture and its mean soil water content. Finally, soil moisture data from the WSN in the Wüstebach catchment were used to validate a detailed hydrologic model of the catchment using empirical orthogonal functions and coherence wavelet analysis. Further development of wireless sensing technologies will include the monitoring of soil moisture potential and biogeochemical properties such as redox potential.

  15. 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

  16. 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

  17. How do I know if my forecasts are better? Using benchmarks in hydrological ensemble prediction

    NASA Astrophysics Data System (ADS)

    Pappenberger, F.; Ramos, M. H.; Cloke, H. L.; Wetterhall, F.; Alfieri, L.; Bogner, K.; Mueller, A.; Salamon, P.

    2015-03-01

    The skill of a forecast can be assessed by comparing the relative proximity of both the forecast and a benchmark to the observations. Example benchmarks include climatology or a naïve forecast. Hydrological ensemble prediction systems (HEPS) are currently transforming the hydrological forecasting environment but in this new field there is little information to guide researchers and operational forecasters on how benchmarks can be best used to evaluate their probabilistic forecasts. In this study, it is identified that the forecast skill calculated can vary depending on the benchmark selected and that the selection of a benchmark for determining forecasting system skill is sensitive to a number of hydrological and system factors. A benchmark intercomparison experiment is then undertaken using the continuous ranked probability score (CRPS), a reference forecasting system and a suite of 23 different methods to derive benchmarks. The benchmarks are assessed within the operational set-up of the European Flood Awareness System (EFAS) to determine those that are 'toughest to beat' and so give the most robust discrimination of forecast skill, particularly for the spatial average fields that EFAS relies upon. Evaluating against an observed discharge proxy the benchmark that has most utility for EFAS and avoids the most naïve skill across different hydrological situations is found to be meteorological persistency. This benchmark uses the latest meteorological observations of precipitation and temperature to drive the hydrological model. Hydrological long term average benchmarks, which are currently used in EFAS, are very easily beaten by the forecasting system and the use of these produces much naïve skill. When decomposed into seasons, the advanced meteorological benchmarks, which make use of meteorological observations from the past 20 years at the same calendar date, have the most skill discrimination. They are also good at discriminating skill in low flows and for all

  18. Assessing hydrologic prediction uncertainty resulting from soft land cover classification

    NASA Astrophysics Data System (ADS)

    Loosvelt, Lien; De Baets, Bernard; Pauwels, Valentijn R. N.; Verhoest, Niko E. C.

    2014-09-01

    For predictions in ungauged basins (PUB), environmental data is generally not available and needs to be inferred by indirect means. Existing technologies such as remote sensing are valuable tools for estimating the lacking data, as these technologies become more widely available and have a high areal coverage. However, indirect estimates of the environmental characteristics are prone to uncertainty. Hence, an improved understanding of the quality of the estimates and the development of methods for dealing with their associated uncertainty are essential to evolve towards accurate PUB. In this study, the impact of the uncertainty associated with the classification of land cover based on multi-temporal SPOT imagery, resulting from the use of the Random Forests classifier, on the predictions of the hydrologic model TOPLATS is investigated through a Monte Carlo simulation. The results show that the predictions of evapotranspiration, runoff and baseflow are hardly affected by the classification uncertainty when area-averaged predictions are intended, implying that uncertainty propagation is only advisable in case a spatial distribution of the predictions is relevant for decision making or is coupled to other spatially distributed models. Based on the resulting uncertainty map, guidelines for additional data collection are formulated in order to reduce the uncertainty for future model applications. Because a Monte Carlo-based uncertainty analysis is computationally very demanding, especially when complex models are involved, we developed a fast indicative uncertainty assessment method that allows for generating proxies of the Monte Carlo-based result in terms of the mean prediction and its associated uncertainty based on a single model evaluation. These proxies are shown to perform well and provide a good indication of the impact of classification uncertainty on the prediction result.

  19. 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.

  20. 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.

  1. 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)

  2. 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

  3. An Integrated Multiscale Approach to River Flood Prediction Using a Land-Surface Hydrology Model

    NASA Astrophysics Data System (ADS)

    Mackey, B. P.; Barros, A. P.; Krishnamurti, T. N.

    2005-05-01

    This work outlines and demonstrates a comprehensive hydrometeorological flood forecasting system that is interdisciplinary in nature, multiscale in its approach, and state-of-the-art in its use of forecasting techniques. This integrated approach links both meteorological and hydrological tools in order to realize a more accurate prediction of major flood events three to six days in advance. One focus is on a new non-linear method to improve global multi-model superensemble precipitation forecasts with an emphasis on successful prediction of intense rain areas. On average, the skill from such a technique is higher and the bias lower than any of the individual member models, and the overall character of the precipitation distribution is maintained through the 5-day forecast period. In addition, global and nested regional spectral models are integrated in hindcast mode. Output from such models as well as from the superensemble is used as forcing input to a physically-based, spatially-distributed hydrology model in order to predict streamflow response during selected flood events. In this terrestrial hydrology prediction system, a dynamical water routing scheme and other physical parameterizations are used in conjunction with a 3-D hydrologic model that keeps track of surface water and energy budgets, including surface-subsurface interactions, groundwater and hydraulic river routing. Experiments are run for the Limpopo River basin in southeastern Africa, where massive flooding occurred in both years 2000 and 2001. An important intermediate step in this process is the downscaling of the precipitation forecasts from the course resolution atmospheric models to the much finer resolution (1 to 10 km) required by the hydrology model. For this purpose, we examined the space-time scaling behavior of simulated precipitation fields from the NWP models at different resolutions and devised a simple physically-based multifractal downscaling algorithm that relies on the scaling

  4. Multi-scale Characterization and Prediction of Coupled Subsurface Biogeochemical-Hydrological Processes

    SciTech Connect

    Hubbard, Susan; Williams, Ken; Steefel, Carl; Banfield, Jill; Long, Phil; Slater, Lee; Pride, Steve; Jinsong Chen

    2006-06-01

    To advance solutions needed for remediation of DOE contaminated sites, approaches are needed that can elucidate and predict reactions associated with coupled biological, geochemical, and hydrological processes over a variety of spatial scales and in heterogeneous environments. Our previous laboratory experimental experiments, which were conducted under controlled and homogeneous conditions, suggest that geophysical methods have the potential for elucidating system transformations that often occur during remediation. Examples include tracking the onset and aggregation of precipitates associated with sulfate reduction using seismic and complex resistivity methods (Williams et al., 2005; Ntarlagiannis et al., 2005) as well as estimating the volume of evolved gas associated with denitrification using radar velocity. These exciting studies illustrated that geophysical responses correlated with biogeochemical changes, but also that multiple factors could impact the geophysical signature and thus a better understanding as well as integration tools were needed to advance the techniques to the point where they can be used to provide quantitative estimates of system transformations.

  5. 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.

  6. Estimation of Predictive Hydrological Uncertainty using Quantile Regression

    NASA Astrophysics Data System (ADS)

    Weerts, A.; Winsemius, H.; Verkade, J.

    2010-12-01

    A technique is presented for assessing the predictive uncertainty of rainfall-runoff and hydraulic forecasts that conditions forecasts uncertainty on the forecasted value itself, based on retrospective quantile regression of hindcasted water level forecasts and forecast errors. To test the robustness of the method, a number of retrospective forecasts for different catchments across England and Wales having different size and hydrological characteristics have been used to derive in a probabilistic sense the relation between simulated values of discharges and water levels, and matching errors. From this study, we can conclude that using quantile regression for estimating forecast errors conditional on the forecasted water levels provides an extremely simple, efficient and robust means for uncertainty estimation of deterministic forecasts. Validation of quantile regression method for water level forecasts at Welshbridge (2077) for the November 2009 flood events for 12, 24, 36 and 48 hours leadtimes. The darkgrey area represents the 50% confidence interval and the lightgrey area represents the 90% confidence interval, the black dashed line the 50% estimate, and the black dots the observations. Reliability plot for the validation period 2008&2009 for water level forecasts at location Buttington (2176)

  7. 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.

  8. 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)

  9. 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...

  10. 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.

  11. 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

  12. Advances in Modeling of Coupled Hydrologic-Socioeconomic Systems

    NASA Astrophysics Data System (ADS)

    Amadio, Mattia; Mysiak, Jaroslav; Pecora, Silvano; Agnetti, Alberto

    2013-04-01

    River flooding is the most common natural disaster in Europe, causing deaths and huge amount of economic losses. Disastrous flood events are often related to extreme meteorological conditions; therefore, climate change is expected to have an important influence over the intensity and frequency of major floods. While approximated large-scale assessments of flood risk scenarios have been carried out, the knowledge of the effects at smaller scales is poor or incomplete, with few localized studies. Also, the methods are still coarse and uneven. The approach of this study starts from the definition of the risk paradigm and the elaboration of local climatic scenarios to track a methodology aimed at elaborating and combining the three elements concurring to the determination of risk: hydrological hazard, value exposure and vulnerability. First, hydrological hazard scenarios are provided by hydrological and hydrodynamic models, used in to a flood forecasting system capable to define "what-if" scenario in a flexible way. These results are then integrated with land-use data (exposure) and depth-damage functions (vulnerability) in a GIS environment, to assess the final risk value (potential flood damage) and visualize it in form of risk maps. In this paper results from a pilot study in the Polesine area are presented, where four simulated levee breach scenarios are compared. The outcomes of the analysis may be instrumental to authorities to increase the knowledge of possible direct losses and guide decision making and planning processes also. As future perspective, the employed methodology can also be extended at the basin scale through integration with the existent flood warning system to gain a real-time estimate of floods direct costs.

  13. 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…

  14. 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

  15. 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

  16. Predicting pesticide concentrations in river water with a hydrologically calibrated basin-scale runoff model.

    PubMed

    Matsui, Y; Itoshiro, S; Buma, M; Matsushita, T; Hosogoe, K; Yuasa, A; Shinoda, S; Inoue, T

    2002-01-01

    Hydrological diffuse pollution models require calibration before they can be used to make accurate long-term predictions for a range of hydrological and meteorological conditions. As such, the applicability of the models to the dispersion of new pesticides is limited due to the lack of calibration data. In this study, the performance of a GIS-based basin-scale runoff model for predicting the concentrations of paddy-farming pesticides in river water was examined when calibrated using hydrological data alone, without optimization based on empirical pesticide concentration data. The prediction accuracy on a daily or hourly scale was somewhat unsatisfactory due to inevitable compromises concerning rice farming schedules. However, the month-averaged pesticide concentrations were satisfactorily accurate; more than 50% of predicted values were between half and twice the observed values, considering the deficiencies of the input data, particularly for pesticide usage, which may include up to 50% error.

  17. 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.

  18. Predictive markers in advanced renal cell carcinoma.

    PubMed

    Michaelson, M Dror; Stadler, Walter M

    2013-08-01

    Predictive markers of response to therapy are increasingly important in advanced renal cell carcinoma (RCC) due to the proliferation of treatment options in recent years. Different types of potential predictive markers may include clinical, toxicity-based, serum, tissue, and radiologic biomarkers. Clinical factors are commonly used in overall prognostic models of RCC but have limited utility in predicting response to therapy. Correlation between development of particular toxicities and response to therapy has been noted, such as the correlation between hypertension and response to angiogenesis-targeted therapy. Serum and tissue biomarkers will be covered in detail elsewhere, but factors such as serum lactate dehydrogenase (LDH) and circulating cytokines show promise in this regard. Finally, baseline or early treatment radiology studies may have predictive ability for longer term efficacy, with most studies to date focusing on functional imaging modalities such as positron emission tomography (PET) scans, dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI), and DCE ultrasound (US). The ultimate goal of developing predictive biomarkers is to enable rational and personalized treatment strategies for patients with advanced RCC. PMID:23972709

  19. 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.

    2013-06-01

    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. 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.

  20. 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.

  1. 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...

  2. 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.

  3. Information content of prior hydrological knowledge in EGU visitors for streamflow prediction

    NASA Astrophysics Data System (ADS)

    Weijs, Steven

    2014-05-01

    Citizens living in flood-prone areas sometimes outperform hydrological models in terms of flood prediction. An interesting question is whether this is due to more access to information, more prior knowledge or better pattern recognition capabilities. In this interactive pico presentation, we plan to quantify the information content of the prior hydrological knowledge present in the brains of members of the audience, by making them participate in a probabilistic prediction game and comparing their performance to hydrologically ignorant computer-based time series prediction models. Results will be analysed in an information-theoretical perspective, where we will try to reverse engineer the best performing forecasters (without physical contact; the software, not the hardware).

  4. Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Laiolo, P.; Gabellani, S.; Campo, L.; Silvestro, F.; Delogu, F.; Rudari, R.; Pulvirenti, L.; Boni, G.; Fascetti, F.; Pierdicca, N.; Crapolicchio, R.; Hasenauer, S.; Puca, S.

    2016-06-01

    The reliable estimation of hydrological variables in space and time is of fundamental importance in operational hydrology to improve the flood predictions and hydrological cycle description. Nowadays remotely sensed data can offer a chance to improve hydrological models especially in environments with scarce ground based data. The aim of this work is to update the state variables of a physically based, distributed and continuous hydrological model using four different satellite-derived data (three soil moisture products and a land surface temperature measurement) and one soil moisture analysis to evaluate, even with a non optimal technique, the impact on the hydrological cycle. The experiments were carried out for a small catchment, in the northern part of Italy, for the period July 2012-June 2013. The products were pre-processed according to their own characteristics and then they were assimilated into the model using a simple nudging technique. The benefits on the model predictions of discharge were tested against observations. The analysis showed a general improvement of the model discharge predictions, even with a simple assimilation technique, for all the assimilation experiments; the Nash-Sutcliffe model efficiency coefficient was increased from 0.6 (relative to the model without assimilation) to 0.7, moreover, errors on discharge were reduced up to the 10%. An added value to the model was found in the rainfall season (autumn): all the assimilation experiments reduced the errors up to the 20%. This demonstrated that discharge prediction of a distributed hydrological model, which works at fine scale resolution in a small basin, can be improved with the assimilation of coarse-scale satellite-derived data.

  5. Seamless hydrological predictions for a monsoon driven catchment in North-East India

    NASA Astrophysics Data System (ADS)

    Köhn, Lisei; Bürger, Gerd; Bronstert, Axel

    2016-04-01

    Improving hydrological forecasting systems on different time scales is interesting and challenging with regards to humanitarian as well as scientific aspects. In meteorological research, short-, medium-, and long-term forecasts are now being merged to form a system of seamless weather and climate predictions. Coupling of these meteorological forecasts with a hydrological model leads to seamless predictions of streamflow, ranging from one day to a season. While there are big efforts made to analyse the uncertainties of probabilistic streamflow forecasts, knowledge of the single uncertainty contributions from meteorological and hydrological modeling is still limited. The overarching goal of this project is to gain knowledge in this subject by decomposing and quantifying the overall predictive uncertainty into its single factors for the entire seamless forecast horizon. Our study area is the Mahanadi River Basin in North-East India, which is prone to severe floods and droughts. Improved streamflow forecasts on different time scales would contribute to early flood warning as well as better water management operations in the agricultural sector. Because of strong inter-annual monsoon variations in this region, which are, unlike the mid-latitudes, partly predictable from long-term atmospheric-oceanic oscillations, the Mahanadi catchment represents an ideal study site. Regionalized precipitation forecasts are obtained by applying the method of expanded downscaling to the ensemble prediction systems of ECMWF and NCEP. The semi-distributed hydrological model HYPSO-RR, which was developed in the Eco-Hydrological Simulation Environment ECHSE, is set up for several sub-catchments of the Mahanadi River Basin. The model is calibrated automatically using the Dynamically Dimensioned Search algorithm, with a modified Nash-Sutcliff efficiency as objective function. Meteorological uncertainty is estimated from the existing ensemble simulations, while the hydrological uncertainty is

  6. Using site-specific soil samples as a substitution for improved hydrological and nonpoint source predictions.

    PubMed

    Chen, Lei; Wang, Guobo; Zhong, Yucen; Zhao, Xin; Shen, Zhenyao

    2016-08-01

    Soil databases are one of the most important inputs for watershed models, and the quality of soil properties affects how well a model performs. The objectives of this study were to (1) quantify the sensitivity of model outputs to soil properties and to (2) use site-specific soil properties as a substitution for more accurate hydrological and nonpoint source (H/NPS) predictions. Soil samples were collected from a typical mountainous watershed in China, and the impacts of soil sample parameters on H/NPS predictions were quantified using the Soil and Water Assessment Tool (SWAT). The most sensitive parameters related to predicting flow, sediment, and total phosphorus (TP) mainly were the soil hydrological, the channel erosion processes, and the initial soil chemical environment, respectively. When the site-specific soil properties were used, the uncertainties (coefficient of variation) related to predicting the hydrology, sediment and TP decreased by 75∼80 %, 75∼84 %, and 46∼61 %, respectively. Based on changes in the Nash-Sutcliff coefficient, the model performance improved by 4.9 and 19.45 % for the hydrological and sediment model, accordingly. However, site-specific soil properties did not contribute to better TP predictions because of the high spatial variability of the soil P concentrations across the large watershed. Thus, although site-specific soil samples can be used to obtain more accurate H/NPS predictions, more sampling sites are required to apply this method in large watersheds. PMID:27146539

  7. Using site-specific soil samples as a substitution for improved hydrological and nonpoint source predictions.

    PubMed

    Chen, Lei; Wang, Guobo; Zhong, Yucen; Zhao, Xin; Shen, Zhenyao

    2016-08-01

    Soil databases are one of the most important inputs for watershed models, and the quality of soil properties affects how well a model performs. The objectives of this study were to (1) quantify the sensitivity of model outputs to soil properties and to (2) use site-specific soil properties as a substitution for more accurate hydrological and nonpoint source (H/NPS) predictions. Soil samples were collected from a typical mountainous watershed in China, and the impacts of soil sample parameters on H/NPS predictions were quantified using the Soil and Water Assessment Tool (SWAT). The most sensitive parameters related to predicting flow, sediment, and total phosphorus (TP) mainly were the soil hydrological, the channel erosion processes, and the initial soil chemical environment, respectively. When the site-specific soil properties were used, the uncertainties (coefficient of variation) related to predicting the hydrology, sediment and TP decreased by 75∼80 %, 75∼84 %, and 46∼61 %, respectively. Based on changes in the Nash-Sutcliff coefficient, the model performance improved by 4.9 and 19.45 % for the hydrological and sediment model, accordingly. However, site-specific soil properties did not contribute to better TP predictions because of the high spatial variability of the soil P concentrations across the large watershed. Thus, although site-specific soil samples can be used to obtain more accurate H/NPS predictions, more sampling sites are required to apply this method in large watersheds.

  8. 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

  9. 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

  10. Hydrologic Information Science (Invited)

    NASA Astrophysics Data System (ADS)

    Maidment, D. R.

    2009-12-01

    The CUAHSI Hydrologic Information System is intended to advance hydrologic science through better capacity to access and organize hydrologic information, as described by Tarboton et al. (2009), in this session. This development may help to create a new branch of hydrologic science, namely hydrologic information science, which is that branch of hydrologic science which deals with the organization, analysis and synthesis of hydrologic information. There are several parts of this body of information: time series data on water observations at point locations that describe the flow, level, and quality of water; GIS data that describe the watersheds, aquifers, streams, waterbodies, wells and other water features of the landscape; remote sensing data that measure distributed properties such as rainfall intensity and land surface temperature; climate grids that describe current and predict climate conditions, and information from hydrologic simulation models. Taken together, these various forms of information can be considered as a description of a set of hydrologic fields that are groups of variables distributed over a domain of time and space. The fundamental principles of hydrologic information science need to be formulated around the representation of hydrologic fields, and the interaction of one form of field with another. In particular, what is needed are insights as to how to define transformations of hydrologic fields which link information at different spatial scales, and which support interpolation of information simultaneously in space and time.

  11. Predicting hydrological signatures in ungauged catchments using spatial interpolation, index model, and rainfall-runoff modelling

    NASA Astrophysics Data System (ADS)

    Zhang, Yongqiang; Vaze, Jai; Chiew, Francis H. S.; Teng, Jin; Li, Ming

    2014-09-01

    Understanding a catchment's behaviours in terms of its underlying hydrological signatures is a fundamental task in surface water hydrology. It can help in water resource management, catchment classification, and prediction of runoff time series. This study investigated three approaches for predicting six hydrological signatures in southeastern Australia. These approaches were (1) spatial interpolation with three weighting schemes, (2) index model that estimates hydrological signatures using catchment characteristics, and (3) classical rainfall-runoff modelling. The six hydrological signatures fell into two categories: (1) long-term aggregated signatures - annual runoff coefficient, mean of log-transformed daily runoff, and zero flow ratio, and (2) signatures obtained from daily flow metrics - concavity index, seasonality ratio of runoff, and standard deviation of log-transformed daily flow. A total of 228 unregulated catchments were selected, with half the catchments randomly selected as gauged (or donors) for model building and the rest considered as ungauged (or receivers) to evaluate performance of the three approaches. The results showed that for two long-term aggregated signatures - the log-transformed daily runoff and runoff coefficient, the index model and rainfall-runoff modelling performed similarly, and were better than the spatial interpolation methods. For the zero flow ratio, the index model was best and the rainfall-runoff modelling performed worst. The other three signatures, derived from daily flow metrics and considered to be salient flow characteristics, were best predicted by the spatial interpolation methods of inverse distance weighting (IDW) and kriging. Comparison of flow duration curves predicted by the three approaches showed that the IDW method was best. The results found here provide guidelines for choosing the most appropriate approach for predicting hydrological behaviours at large scales.

  12. Extending medium-range predictability of extreme hydrological events in Europe.

    PubMed

    Lavers, David A; Pappenberger, Florian; Zsoter, Ervin

    2014-01-01

    Widespread flooding occurred across northwest Europe during the winter of 2013/14, resulting in large socioeconomic damages. In the historical record, extreme hydrological events have been connected with intense water vapour transport. Here we show that water vapour transport has higher medium-range predictability compared with precipitation in the winter 2013/14 forecasts from the European Centre for Medium-Range Weather Forecasts. Applying the concept of potential predictability, the transport is found to extend the forecast horizon by 3 days in some European regions. Our results suggest that the breakdown in precipitation predictability is due to uncertainty in the horizontal mass convergence location, an essential mechanism for precipitation generation. Furthermore, the predictability increases with larger spatial averages. Given the strong association between precipitation and water vapour transport, especially for extreme events, we conclude that the higher transport predictability could be used as a model diagnostic to increase preparedness for extreme hydrological events.

  13. A spatially consistent seamless predictions of continental-scale hydrologic fluxes and states

    NASA Astrophysics Data System (ADS)

    Kumar, Rohini; Mai, Juliane; Rakovec, Oldrich; Zink, Matthias; Cuntz, Matthias; Thober, Stephan; Attinger, Sabine; Schroen, Martin; Schaefer, David; Samaniego, Luis

    2016-04-01

    One of the major challenges in the contemporary hydrology is to establish a continental-scale hydrologic model that can provide spatially consistent, seamless prediction of hydrologic fluxes and states to better characterise extreme events like floods and droughts. This requires, among other things, 1) a robust parameterization technique that allows the model to seamlessly operate across a range of spatial resolutions and 2) an efficient parameter estimation technique to derive a representative set of spatially consistent model parameters that avoid inconsistencies in simulated hydrologic fields (e.g., soil moisture). In this study, we demostrate the applicability of a mesoscale hydrologic model parameterized using a multiscale regionalization technique to derive daily gridded fields of hydrologic fluxes/states over the Pan-EU domain since 1950. A multi-basin parameter estimation (MBE) strategy that utilizes observed streamflows from a set of hydrologically diverse basins is introduced to infer a representative set of regional calibration parameters which is applicable over the entire domain. We tested three sampling schemes to select a set of calibration basins incremented sequentially from 2 to 20 basins, based on the 1) random selection procedure, 2) gradient along the hydro-climatic regimes, and 3) diversity in hydro-climatic and basin physiographical properties (e.g., terrain, soil, land cover properties). Results of the MBE approach are contrasted against the benchmark at-site calibration strategy across 400 EU basins varying from approximately 100 to 500,000 km2. At-site calibrated parameters performed best for site-specific streamflow predictions, but their transferability to other sites resulted in poor performance. Moreover, the at-site calibration strategy generated a patchy, spatially inconsistent distribution of parameter fields that further induced large discontinuities in simulated hydrologic fields of soil moisture among other sates/fluxes. These

  14. 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 ...

  15. 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...

  16. 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...

  17. 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...

  18. Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction

    NASA Astrophysics Data System (ADS)

    Xuan, Y.; Cluckie, I. D.; Wang, Y.

    2009-03-01

    Advances in mesoscale numerical weather predication make it possible to provide rainfall forecasts along with many other data fields at increasingly higher spatial resolutions. It is currently possible to incorporate high-resolution NWPs directly into flood forecasting systems in order to obtain an extended lead time. It is recognised, however, that direct application of rainfall outputs from the NWP model can contribute considerable uncertainty to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be magnified by the scaling process. As the ensemble weather forecast has become operationally available, it is of particular interest to the hydrologist to investigate both the potential and implication of ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. In this paper, we employ a distributed hydrological model to analyse the performance of the ensemble flow forecasts based on the ensemble rainfall inputs from a short-range high-resolution mesoscale weather model. The results show that: (1) The hydrological model driven by QPF can produce forecasts comparable with those from a raingauge-driven one; (2) The ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast itself; and (3) the uncertainties as well as systematic biases are sometimes significant and, as such, extra effort needs to be made to improve the quality of such a system.

  19. Uncertainty analysis of hydrological ensemble forecasts in a distributed model utilising short-range rainfall prediction

    NASA Astrophysics Data System (ADS)

    Cluckie, I. D.; Xuan, Y.; Wang, Y.

    2006-10-01

    Advances in meso-scale numerical weather predication make it possible to provide rainfall forecasts along with many other data fields at increasingly higher spatial resolutions. It is currently possible to incorporate high-resolution NWPs directly into flood forecasting systems in order to obtain an extended lead time. It is recognised, however, that direct application of rainfall outputs from the NWP model can contribute considerable uncertainty to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be magnified by the scaling process. As the ensemble weather forecast has become operationally available, it is of particular interest to the hydrologist to investigate both the potential and implication of ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. In this paper, we employ a distributed hydrological model to analyse the performance of the ensemble flow forecasts based on the ensemble rainfall inputs from a short-range high-resolution mesoscale weather model. The results show that: (1) The hydrological model driven by QPF can produce forecasts comparable with those from a raingauge-driven one; (2) The ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast itself; and (3) the uncertainties as well as systematic biases are sometimes significant and, as such, extra effort needs to be made to improve the quality of such a system.

  20. 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

  1. 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

  2. Constraining geostatistical models with hydrological data to improve prediction realism

    NASA Astrophysics Data System (ADS)

    Demyanov, V.; Rojas, T.; Christie, M.; Arnold, D.

    2012-04-01

    Geostatistical models reproduce spatial correlation based on the available on site data and more general concepts about the modelled patters, e.g. training images. One of the problem of modelling natural systems with geostatistics is in maintaining realism spatial features and so they agree with the physical processes in nature. Tuning the model parameters to the data may lead to geostatistical realisations with unrealistic spatial patterns, which would still honour the data. Such model would result in poor predictions, even though although fit the available data well. Conditioning the model to a wider range of relevant data provide a remedy that avoid producing unrealistic features in spatial models. For instance, there are vast amounts of information about the geometries of river channels that can be used in describing fluvial environment. Relations between the geometrical channel characteristics (width, depth, wave length, amplitude, etc.) are complex and non-parametric and are exhibit a great deal of uncertainty, which is important to propagate rigorously into the predictive model. These relations can be described within a Bayesian approach as multi-dimensional prior probability distributions. We propose a way to constrain multi-point statistics models with intelligent priors obtained from analysing a vast collection of contemporary river patterns based on previously published works. We applied machine learning techniques, namely neural networks and support vector machines, to extract multivariate non-parametric relations between geometrical characteristics of fluvial channels from the available data. An example demonstrates how ensuring geological realism helps to deliver more reliable prediction of a subsurface oil reservoir in a fluvial depositional environment.

  3. 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.

  4. 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.

  5. Improved Hydrological Predictions by the Coupling of Land-Surface-Atmosphere Processes

    NASA Astrophysics Data System (ADS)

    Larsen, M. A.; Refsgaard, J.; Jensen, K. H.; Christensen, J. H.; Butts, M. B.; Drews, M.

    2012-12-01

    The study is a part of the Danish HYACINTS project (www.hyacints.dk). A part of the study involves the development of a fully dynamic coupling between the HIRHAM regional climate model (Danish Meteorological Institute) and the MIKE SHE hydrological model (DHI / Geological Survey of Denmark and Greenland). A main expectation of the coupled setup is improved hydrological predictions. As climate models generally include only a simplistic hydrological description, the improvements are expected as a result of higher detail and resolution in soil water and water table depths as generated in the hydrological model component. Equally, the hydrological model may benefit from the horizontal redistribution of sensible energy made possible through the climate model. In the preparation of the coupling, the optimal setup of the climate model component is assessed among eight simulations with varying domain sizes and resolutions. Similarly the hydrological model is parameterized by upscaling from autocalibration results performed against field measurements at distinct surfaces within the catchment. The coupled climate model domain is covering an area of 4000x2800 km in 11 km resolution over northern Europe forced by ERA-Interim reanalysis data at the boundaries. The coupled hydrological model catchment is located at the approximate climate model domain center in the Western part of Denmark covering an area of 2500 km2. The effect of the coupling is tested using a 1 year period by running the model in two versions; a fully coupled setup and a traditional passive one-way setup using HIRHAM output as MIKE SHE input. Validation variables include evapotranspiration, sensible heat flux and soil moisture.

  6. 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.

  7. 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.

  8. Empirical Hydrologic Predictions for Southwestern Poland and Their Relation to Enso Teleconnections

    NASA Astrophysics Data System (ADS)

    Niedzielski, Tomasz

    2010-01-01

    Recent investigations confirm meaningful but weak teleconnections between the El Niño/Southern Oscillation (ENSO) and hydrology in some European regions. In particular, this finding holds for Polish riverflows in winter and early spring as inferred from integrating numerous geodetic, geophysical and hydrologic time series. The purpose of this study is to examine whether such remote teleconnections may have an influence on hydrologic forecasting. The daily discharge time series from southwestern (SW) Poland spanning the time interval from 1971 to 2006 are examined. A few winter and spring peak flows are considered and the issue of their predictability using empirical forecasting is addressed. Following satisfactory prediction performance reported elsewhere, the multivariate autoregressive method is used and its modification based on the finite impulse response filtering is proposed. The initial phases of peak flows are rather acceptably forecasted but the accuracy of predictions in the vicinity of local maxima of the hydrographs is poorer. It has been hypothesized that ENSO signal slightly influences the predictability of winter and early spring floods in SW Poland. The predictions of flood wave maxima are the most accurate for floods preceded by normal states, less accurate for peak flows after La Niño episodes and highly inaccurate for peak flows preceded by El Niño events. Such a finding can be interpreted in terms of intermittency. Before peak flows preceded by El Niño there are temporarily persistent low flows followed by a consecutive melting leading to a considerable intermittency and hence to difficulties in forecasting. Before peak flows preceded by La Niño episodes there exist ENSO-related positive temperature and precipitation anomalies in SW Poland causing lower, but still considerable, intermittency and thus better, but not entirely correct, predictability of hydrologic time series.

  9. 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.

  10. 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.

  11. 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

  12. Wavelet based error correction and predictive uncertainty of a hydrological forecasting system

    NASA Astrophysics Data System (ADS)

    Bogner, Konrad; Pappenberger, Florian; Thielen, Jutta; de Roo, Ad

    2010-05-01

    River discharge predictions most often show errors with scaling properties of unknown source and statistical structure that degrade the quality of forecasts. This is especially true for lead-time ranges greater then a few days. Since the European Flood Alert System (EFAS) provides discharge forecasts up to ten days ahead, it is necessary to take these scaling properties into consideration. For example the range of scales for the error that occurs at the spring time will be caused by long lasting snowmelt processes, and is by far larger then the error, that appears during the summer period and is caused by convective rain fields of short duration. The wavelet decomposition is an excellent way to provide the detailed model error at different levels in order to estimate the (unobserved) state variables more precisely. A Vector-AutoRegressive model with eXogenous input (VARX) is fitted for the different levels of wavelet decomposition simultaneously and after predicting the next time steps ahead for each scale, a reconstruction formula is applied to transform the predictions in the wavelet domain back to the original time domain. The Bayesian Uncertainty Processor (BUP) developed by Krzysztofowicz is an efficient method to estimate the full predictive uncertainty, which is derived by integrating the hydrological model uncertainty and the meteorological input uncertainty. A hydrological uncertainty processor has been applied to the error corrected discharge series at first in order to derive the predictive conditional distribution under the hypothesis that there is no input uncertainty. The uncertainty of the forecasted meteorological input forcing the hydrological model is derived from the combination of deterministic weather forecasts and ensemble predictions systems (EPS) and the Input Processor maps this input uncertainty into the output uncertainty under the hypothesis that there is no hydrological uncertainty. The main objective of this Bayesian forecasting system

  13. 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

  14. 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

  15. 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

  16. Patterns of Hydrologic Sensitivity to Climate in the Western US: Implications for Future Predictions

    NASA Astrophysics Data System (ADS)

    Safeeq, M.; Grant, G.

    2015-12-01

    A key challenge for resource and land managers is predicting the consequences of climate warming on streamflow and water resources. During the last century in the western United States, significant reductions in snowpack and earlier snowmelt have led to an increase in the fraction of annual streamflow during winter and a decline in the summer. However, this increase and decrease in streamflow is mediated by the climate and landscape. Here we explore key landscape and climate metrics for interpreting hydrologic sensitivity to climate using observed flow from a range of watersheds across the western United States. Our results indicate that the recession constant and fraction of precipitation falling as snow are the two primary controls on hydrologic sensitivity to climate in this region. Dry season flows in watersheds that drain slowly from deep groundwater and receive precipitation as snow are most sensitive to climate warming. In terms of peak flow, watersheds are most sensitivity to the consistency (i.e. signal-to-noise ratio) in fraction of precipitation falling as snow. Our results also indicate that not all trends in western United States are associated with changes in snowpack dynamics; we observe declining flow in late fall and winter in rain-dominated watersheds as well. These empirical findings support both theory and hydrologic modeling and have implications for how hydrologic sensitivity to climate change is evaluated and interpreted across broad regions.

  17. Predicting glacio-hydrologic change in the headwaters of the Zongo River, Cordillera Real, Bolivia

    DOE PAGES

    Frans, Chris; Istanbulluoglu, Erkan; Lettenmaier, Dennis; Naz, Bibi S.; Clarke, Garry K. C.; Condom, Thomas; Burns, Pat; Nolin, Anne W.

    2015-11-19

    In many partially glacierized watersheds glacier recession driven by a warming climate could lead to complex patterns of streamflow response over time, often marked with rapid increases followed by sharp declines, depending on initial glacier ice cover and rate of climate change. Capturing such "phases'' of hydrologic response is critical in regions where communities rely on glacier meltwater, particularly during low flows. In this study, we investigate glacio-hydrologic response in the headwaters of the Zongo River, Bolivia, under climate change using a distributed glacio-hydrological model over the period of 1987-2100. Model predictions are evaluated through comparisons with satellite-derived glacier extentmore » estimates, glacier surface velocity, in situ glacier mass balance, surface energy flux, and stream discharge measurements. Historically (1987-2010) modeled glacier melt accounts for 27% of annual runoff, and 61% of dry season (JJA) runoff on average. During this period the relative glacier cover was observed to decline from 35 to 21% of the watershed. In the future, annual and dry season discharge is projected to decrease by 4% and 27% by midcentury and 25% and 57% by the end of the century, respectively, following the loss of 81% of the ice in the watershed. Modeled runoff patterns evolve through the interplay of positive and negative trends in glacier melt and increased evapotranspiration as the climate warms. Sensitivity analyses demonstrate that the selection of model surface energy balance parameters greatly influences the trajectory of hydrological change projected during the first half of the 21st century. In conclusion, these model results underscore the importance of coupled glacio-hydrology modeling.« less

  18. Predicting glacio-hydrologic change in the headwaters of the Zongo River, Cordillera Real, Bolivia

    SciTech Connect

    Frans, Chris; Istanbulluoglu, Erkan; Lettenmaier, Dennis; Naz, Bibi S.; Clarke, Garry K. C.; Condom, Thomas; Burns, Pat; Nolin, Anne W.

    2015-11-19

    In many partially glacierized watersheds glacier recession driven by a warming climate could lead to complex patterns of streamflow response over time, often marked with rapid increases followed by sharp declines, depending on initial glacier ice cover and rate of climate change. Capturing such "phases'' of hydrologic response is critical in regions where communities rely on glacier meltwater, particularly during low flows. In this study, we investigate glacio-hydrologic response in the headwaters of the Zongo River, Bolivia, under climate change using a distributed glacio-hydrological model over the period of 1987-2100. Model predictions are evaluated through comparisons with satellite-derived glacier extent estimates, glacier surface velocity, in situ glacier mass balance, surface energy flux, and stream discharge measurements. Historically (1987-2010) modeled glacier melt accounts for 27% of annual runoff, and 61% of dry season (JJA) runoff on average. During this period the relative glacier cover was observed to decline from 35 to 21% of the watershed. In the future, annual and dry season discharge is projected to decrease by 4% and 27% by midcentury and 25% and 57% by the end of the century, respectively, following the loss of 81% of the ice in the watershed. Modeled runoff patterns evolve through the interplay of positive and negative trends in glacier melt and increased evapotranspiration as the climate warms. Sensitivity analyses demonstrate that the selection of model surface energy balance parameters greatly influences the trajectory of hydrological change projected during the first half of the 21st century. In conclusion, these model results underscore the importance of coupled glacio-hydrology modeling.

  19. Predicting glacio-hydrologic change in the headwaters of the Zongo River, Cordillera Real, Bolivia

    NASA Astrophysics Data System (ADS)

    Frans, Chris; Istanbulluoglu, Erkan; Lettenmaier, Dennis P.; Naz, Bibi S.; Clarke, Garry K. C.; Condom, Thomas; Burns, Pat; Nolin, Anne W.

    2015-11-01

    In many partially glacierized watersheds glacier recession driven by a warming climate could lead to complex patterns of streamflow response over time, often marked with rapid increases followed by sharp declines, depending on initial glacier ice cover and rate of climate change. Capturing such "phases" of hydrologic response is critical in regions where communities rely on glacier meltwater, particularly during low flows. In this paper, we investigate glacio-hydrologic response in the headwaters of the Zongo River, Bolivia, under climate change using a distributed glacio-hydrological model over the period of 1987-2100. Model predictions are evaluated through comparisons with satellite-derived glacier extent estimates, glacier surface velocity, in situ glacier mass balance, surface energy flux, and stream discharge measurements. Historically (1987-2010) modeled glacier melt accounts for 27% of annual runoff, and 61% of dry season (JJA) runoff on average. During this period the relative glacier cover was observed to decline from 35 to 21% of the watershed. In the future, annual and dry season discharge is projected to decrease by 4% and 27% by midcentury and 25% and 57% by the end of the century, respectively, following the loss of 81% of the ice in the watershed. Modeled runoff patterns evolve through the interplay of positive and negative trends in glacier melt and increased evapotranspiration as the climate warms. Sensitivity analyses demonstrate that the selection of model surface energy balance parameters greatly influences the trajectory of hydrological change projected during the first half of the 21st century. These model results underscore the importance of coupled glacio-hydrology modeling.

  20. 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.

  1. 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.

  2. 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.

  3. The utility of satellite precipitation products for hydrologic prediction in topographically complex regions: The Chehalis River Basin, WA as a case study

    NASA Astrophysics Data System (ADS)

    Cao, Q.; Mehran, A.; Lettenmaier, D. P.; Mass, C.; Johnson, N.

    2015-12-01

    Accurate measurements of precipitation are of great importance in hydrologic predictions especially for floods, which are a pervasive natural hazard. One of the primary objectives of Global Precipitation Measurement (GPM) mission is to provide a basis for hydrologic predictions using satellite sensors. A major advance in GPM relative to the Tropical Rainfall Measuring Mission (TRMM) is that it observes atmospheric river (AR) events, most of which have landfall too far north to be tracked by TRMM. These events are responsible for most major floods along the U.S. West Coast. We address the question of whether, for hydrologic modeling purposes, it is better to use precipitation products derived directly from GPM and/or other precipitation fields from weather models that have assimilated satellite data. Our overall strategy is to compare different methods for prediction of flood and/or high flow events by different forcings on the hydrologic model. We examine four different configurations of the Distroibute Hydrology Soil Vegetation Model (DHSVM) over the Chehalis River Basin that use a) precipitation forcings based on gridded station data; b) precipitation forcings based on NWS WSR-88D data, c) forcings based from short-term precipitation forecasts using the Weather Research and Forecasting (WRF) mesoscale atmospheric model, and d) satellite-based precipitation estimates (TMPA and IMERG). We find that in general, biases in the radar and satellite products result in much larger errors than with either gridded station data or WRF forcings, but if these biases are removed, comparable performance in flood predictions can be achieved by Satellite-based precipitation estimates (TMPA and IMERG).

  4. Estimation of predictive hydrologic uncertainty using the quantile regression and UNEEC methods and their comparison on contrasting catchments

    NASA Astrophysics Data System (ADS)

    Dogulu, N.; López López, P.; Solomatine, D. P.; Weerts, A. H.; Shrestha, D. L.

    2015-07-01

    In operational hydrology, estimation of the predictive uncertainty of hydrological models used for flood modelling is essential for risk-based decision making for flood warning and emergency management. In the literature, there exists a variety of methods analysing and predicting uncertainty. However, studies devoted to comparing the performance of the methods in predicting uncertainty are limited. This paper focuses on the methods predicting model residual uncertainty that differ in methodological complexity: quantile regression (QR) and UNcertainty Estimation based on local Errors and Clustering (UNEEC). The comparison of the methods is aimed at investigating how well a simpler method using fewer input data performs over a more complex method with more predictors. We test these two methods on several catchments from the UK that vary in hydrological characteristics and the models used. Special attention is given to the methods' performance under different hydrological conditions. Furthermore, normality of model residuals in data clusters (identified by UNEEC) is analysed. It is found that basin lag time and forecast lead time have a large impact on the quantification of uncertainty and the presence of normality in model residuals' distribution. In general, it can be said that both methods give similar results. At the same time, it is also shown that the UNEEC method provides better performance than QR for small catchments with the changing hydrological dynamics, i.e. rapid response catchments. It is recommended that more case studies of catchments of distinct hydrologic behaviour, with diverse climatic conditions, and having various hydrological features, be considered.

  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. Hydrologic Sensitivity Indices to Predict Changes Caused by Mountain Pine Beetle Mortality in Ungauged Basins

    NASA Astrophysics Data System (ADS)

    Rosin, K.; Weiler, M.

    2006-12-01

    In British Columbia, Canada, the mountain pine beetle (MPB) has developed into a real threat for forestry since it has infested 8.5 million hectares and destroyed 411 million cubic feet of lodgepole pines. The Forest Service estimates that 80 percent of the pines in central British Columbia will be dead in about seven years, what might have a notable impact on the hydrology of this region. As a matter of fact, there are hardly neither discharge gauges nor meteorological stations in the most affected areas. In order to predict the changes of the catchment hydrology resulting from MPB mortality, we have developed the Sensitive Area Mapping Model (SAMM). In SAMM the assessed basins are categorized according to their hydrologic sensitivity - into different runoff generation indices. The general idea behind this approach is, that due to the spatial variability of the impact of MPB mortality and subsequent forest management, there are sub-basins within a larger watershed that are more sensitive to changes than others; consequently they will respond hydrologically different. Therefore, sensitivity indices should be able to show, which areas rapidly convey runoff to a stream channel. Consequently, five runoff processes indices are spatially defined: Infiltration excess overland flow (categorized by fire history, soil compaction and road density of a region), saturation excess overland flow (categorized by elevation difference to stream, contributing area and hydrogeology), shallow subsurface flow (categorization by soil-bedrock interface permeability, soil depth, slope, parent material, distance to stream), deep subsurface flow (categorized by permeability of bedrock, soil depth, quaternary geology, distance to stream) and channel interception (precipitation that falls directly into the stream channel and lakes). The indices are computed using province-wide GIS data such as maps of the stream network, third order watersheds boundaries, digital elevation model, land use and

  9. Predicting hydrologic response through a hierarchical catchment knowledgebase: A Bayes empirical Bayes approach

    NASA Astrophysics Data System (ADS)

    Smith, Tyler; Marshall, Lucy; Sharma, Ashish

    2014-02-01

    Making useful Predictions in Ungauged Basins is an incredibly difficult task given the limitations of hydrologic models to represent physical processes appropriately across the heterogeneity within and among different catchments. Here, we introduce a new method for this challenge, Bayes empirical Bayes, that allows for the statistical pooling of information from multiple donor catchments and provides the ability to transfer parametric distributions rather than single parameter sets to the ungauged catchment. Further, the methodology provides an efficient framework with which to formally assess predictive uncertainty at the ungauged catchment. We investigated the utility of the methodology under both synthetic and real data conditions, and with respect to its sensitivity to the number and quality of the donor catchments used. This study highlighted the ability of the hierarchical Bayes empirical Bayes approach to produce expected outcomes in both the synthetic and real data applications. The method was found to be sensitive to the quality (hydrologic similarity) of the donor catchments used. Results were less sensitive to the number of donor catchments, but indicated that predictive uncertainty was best constrained with larger numbers of donor catchments (but still adequate with fewer donors).

  10. A radar-based hydrological model for flash flood prediction in the dry regions of Israel

    NASA Astrophysics Data System (ADS)

    Ronen, Alon; Peleg, Nadav; Morin, Efrat

    2014-05-01

    Flash floods are floods which follow shortly after rainfall events, and are among the most destructive natural disasters that strike people and infrastructures in humid and arid regions alike. Using a hydrological model for the prediction of flash floods in gauged and ungauged basins can help mitigate the risk and damage they cause. The sparsity of rain gauges in arid regions requires the use of radar measurements in order to get reliable quantitative precipitation estimations (QPE). While many hydrological models use radar data, only a handful do so in dry climate. This research presents a robust radar-based hydro-meteorological model built specifically for dry climate. Using this model we examine the governing factors of flash floods in the arid and semi-arid regions of Israel in particular and in dry regions in general. The hydrological model built is a semi-distributed, physically-based model, which represents the main hydrological processes in the area, namely infiltration, flow routing and transmission losses. Three infiltration functions were examined - Initial & Constant, SCS-CN and Green&Ampt. The parameters for each function were found by calibration based on 53 flood events in three catchments, and validation was performed using 55 flood events in six catchments. QPE were obtained from a C-band weather radar and adjusted using a weighted multiple regression method based on a rain gauge network. Antecedent moisture conditions were calculated using a daily recharge assessment model (DREAM). We found that the SCS-CN infiltration function performed better than the other two, with reasonable agreement between calculated and measured peak discharge. Effects of storm characteristics were studied using synthetic storms from a high resolution weather generator (HiReS-WG), and showed a strong correlation between storm speed, storm direction and rain depth over desert soils to flood volume and peak discharge.

  11. 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.

  12. Predicted Hydrological Impacts of Climate Change for Harp Lake and Catchment, South- Central Ontario

    NASA Astrophysics Data System (ADS)

    Yao, H.

    2009-05-01

    Potential hydrological impacts of two climate change scenarios were analyzed for a typical inland lake (Harp Lake) and its catchment in the boreal ecozone of Ontario, Canada. The first scenario was created by extrapolation of long-term trends of monthly temperature and precipitation over a 129-year data record, into a future target year 2050. This scenario predicts a slight temperature increase (0.6 0C per 50 years on average) in each of 12 months and a slight increase in monthly precipitation (on average 2.8 mm/m per 50 years). The second scenario was based on a Canadian general circulation model (GCM) prediction, which predicts larger changes and more differences among months. It predicts that the temperature of each month would increase in 2050 by 3.1 0C on average, and monthly precipitation would increase or decrease depending on the month by 1.7 mm/m on average compared to the present. The hydrological responses of the catchment and the lake were calculated using a USGS catchment water balance model and a proposed lake water balance model respectively, and the two models were calibrated with 26-years of hydrological and meteorological data from the Harp catchment. The USGS model has six parameters which were calibrated. Model-estimated runoff and observed runoff have a high correlation coefficient of 0.88. The model was then used to calculate catchment's responses in evapotranspiration and runoff under each of the two climate change scenarios. The lake's water balance model includes a relationship of lake outflow and inflow (i.e. catchment runoff) which was regressed using the 26-year data for each month, and a monthly water budget accounting. The change of lake-water level within a month was calculated as the difference of input term (precipitation, inflow) and output term (outflow, evaporation). The first scenario with a warmer and wetter climate predicted a smaller magnitude of hydrological impact than the second scenario. The first scenario showed an

  13. Substrate Deformation Predicts Neuronal Growth Cone Advance

    PubMed Central

    Athamneh, Ahmad I.M.; Cartagena-Rivera, Alexander X.; Raman, Arvind; Suter, Daniel M.

    2015-01-01

    Although pulling forces have been observed in axonal growth for several decades, their underlying mechanisms, absolute magnitudes, and exact roles are not well understood. In this study, using two different experimental approaches, we quantified retrograde traction force in Aplysia californica neuronal growth cones as they develop over time in response to a new adhesion substrate. In the first approach, we developed a novel method, to our knowledge, for measuring traction forces using an atomic force microscope (AFM) with a cantilever that was modified with an Aplysia cell adhesion molecule (apCAM)-coated microbead. In the second approach, we used force-calibrated glass microneedles coated with apCAM ligands to guide growth cone advance. The traction force exerted by the growth cone was measured by monitoring the microneedle deflection using an optical microscope. Both approaches showed that Aplysia growth cones can develop traction forces in the 100–102 nN range during adhesion-mediated advance. Moreover, our results suggest that the level of traction force is directly correlated to the stiffness of the microneedle, which is consistent with a reinforcement mechanism previously observed in other cell types. Interestingly, the absolute level of traction force did not correlate with growth cone advance toward the adhesion site, but the amount of microneedle deflection did. In cases of adhesion-mediated growth cone advance, the mean needle deflection was 1.05 ± 0.07 μm. By contrast, the mean deflection was significantly lower (0.48 ± 0.06 μm) when the growth cones did not advance. Our data support a hypothesis that adhesion complexes, which can undergo micron-scale elastic deformation, regulate the coupling between the retrogradely flowing actin cytoskeleton and apCAM substrates, stimulating growth cone advance if sufficiently abundant. PMID:26445437

  14. Estimation of predictive hydrologic uncertainty using quantile regression and UNEEC methods and their comparison on contrasting catchments

    NASA Astrophysics Data System (ADS)

    Dogulu, N.; López López, P.; Solomatine, D. P.; Weerts, A. H.; Shrestha, D. L.

    2014-09-01

    In operational hydrology, estimation of predictive uncertainty of hydrological models used for flood modelling is essential for risk based decision making for flood warning and emergency management. In the literature, there exists a variety of methods analyzing and predicting uncertainty. However, case studies comparing performance of these methods, most particularly predictive uncertainty methods, are limited. This paper focuses on two predictive uncertainty methods that differ in their methodological complexity: quantile regression (QR) and UNcertainty Estimation based on local Errors and Clustering (UNEEC), aiming at identifying possible advantages and disadvantages of these methods (both estimating residual uncertainty) based on their comparative performance. We test these two methods on several catchments (from UK) that vary in its hydrological characteristics and models. Special attention is given to the errors for high flow/water level conditions. Furthermore, normality of model residuals is discussed in view of clustering approach employed within the framework of UNEEC method. It is found that basin lag time and forecast lead time have great impact on quantification of uncertainty (in the form of two quantiles) and achievement of normality in model residuals' distribution. In general, uncertainty analysis results from different case studies indicate that both methods give similar results. However, it is also shown that UNEEC method provides better performance than QR for small catchments with changing hydrological dynamics, i.e. rapid response catchments. We recommend that more case studies of catchments from regions of distinct hydrologic behaviour, with diverse climatic conditions, and having various hydrological features be tested.

  15. 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

  16. Assessing the impacts of precipitation bias on distributed hydrologic model calibration and prediction accuracy

    NASA Astrophysics Data System (ADS)

    Looper, Jonathan P.; Vieux, Baxter E.; Moreno, Maria A.

    2012-02-01

    SummaryPhysics-based distributed (PBD) hydrologic models predict runoff throughout a basin using the laws of conservation of mass and momentum, and benefit from more accurate and representative precipitation input. V flo™ is a gridded distributed hydrologic model that predicts runoff and continuously updates soil moisture. As a participating model in the second Distributed Model Intercomparison Project (DMIP2), V flo™ is applied to the Illinois and Blue River basins in Oklahoma. Model parameters are derived from geospatial data for initial setup, and then adjusted to reproduce the observed flow under continuous time-series simulations and on an event basis. Simulation results demonstrate that certain runoff events are governed by saturation excess processes, while in others, infiltration-rate excess processes dominate. Streamflow prediction accuracy is enhanced when multi-sensor precipitation estimates (MPE) are bias corrected through re-analysis of the MPE provided in the DMIP2 experiment, resulting in gauge-corrected precipitation estimates (GCPE). Model calibration identified a set of parameters that minimized objective functions for errors in runoff volume and instantaneous discharge. Simulated streamflow for the Blue and Illinois River basins, have Nash-Sutcliffe efficiency coefficients between 0.61 and 0.68, respectively, for the 1996-2002 period using GCPE. The streamflow prediction accuracy improves by 74% in terms of Nash-Sutcliffe efficiency when GCPE is used during the calibration period. Without model calibration, excellent agreement between hourly simulated and observed discharge is obtained for the Illinois, whereas in the Blue River, adjustment of parameters affecting both saturation and infiltration-rate excess processes were necessary. During the 1996-2002 period, GCPE input was more important than model calibration for the Blue River, while model calibration proved more important for the Illinois River. During the verification period (2002

  17. Application of a global hydrologic prediction system to the Zambezi River Basin (Invited)

    NASA Astrophysics Data System (ADS)

    Voisin, N.; Pappenberger, F.; Buizza, R.; Lettenmaier, D. P.

    2010-12-01

    We evaluate a 10-day globally applicable flood prediction scheme over the Zambezi River basin for the period 2003-2007. The hydrological core of the scheme is the Variable Infiltration Capacity (VIC) hydrology model, which we forced with the European Centre for Medium Range Weather Forecasts (ECMWF) temperature and wind analyses, and the near real-time Tropical Rainfall Monitoring Mission (TRMM) precipitation product (3B42RT) up to the day of forecast. During the forecast period, the VIC model was forced with calibrated and downscaled 10-day forecasts from the ECMWF ensemble prediction system (EPS). We also tested a parallel setup where the EPS ensemble forecasts were interpolated to the 0.25 degree spatial resolution of the hydrology model. Each set of forecasts was extended by 5 days using monthly mean climatological variables and zero precipitation in order to account for the effect of initial conditions (the EPS was extended to 15 days only in 2006). The 15-day spatially distributed ensemble runoff forecasts were then routed to several locations in the basin. Surrogates for observed daily runoff and streamflow were provided by the reference run, i.e. the VIC simulations forced with ECMWF analysis fields and TRMM precipitation. Mean forecast errors and skills for the two sets of ensemble forecasts are evaluated with respect to the reference on a seasonal basis, and are compared to previous results from a similarly designed study over the Ohio River Basin. The influence on forecast accuracy of basin drainage area, hydroclimatic diversity within the basin, and storm type on forecast skill scores is evaluated.

  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. Predicting impact factor one year in advance.

    PubMed

    Ketcham, Catherine M

    2007-06-01

    The first impact factor (IF) to reflect the sole efforts of a new editorial team occurs 4 years into what is usually a 5-year editorship, owing to the lag times of: paper accrual and publication, accumulation of citations in derivative literature, and compiling of such citations by the Thomson ISI Web of Knowledge service. Through weekly collection of citation data from the Web of Science over the past 2 years, we now demonstrate that the evolution of IF can be tracked weekly over the course of a calendar year, enabling prediction of the next year's IF beginning at the middle of the previous year. The methodology used to track the developing IF for Lab Invest is presented in this study and a prediction made for the 2006 IF, along with IF predictions for other general pathology journals (American Journal of Pathology, Journal of Pathology, Modern Pathology, American Journal of Surgical Pathology, and Human Pathology). Despite the fact that the 2006 IF for Lab Invest will not be issued until June 2007, it became apparent as early as July 2006 that the Lab Invest IF would be greatly improved over 2004 and 2005 by a predicted 0.5 units. However, as important as IF can be to a journal, it is vital not to let IF considerations influence every aspect of the editors' decisions. Rather, the significance of early prediction lies in earlier validation of editorial policies for journal management as a whole, and reassurance that the philosophy for journal operations is on track.

  20. Using a Dynamic Hydrology Model To Predict Mosquito Abundances in Flood and Swamp Water

    PubMed Central

    Stieglitz, Marc; Stark, Colin; Le Blancq, Sylvie; Cane, Mark

    2002-01-01

    We modeled surface wetness at high resolution, using a dynamic hydrology model, to predict flood and swamp water mosquito abundances. Historical meteorologic data, as well as topographic, soil, and vegetation data, were used to model surface wetness and identify potential fresh and swamp water breeding habitats in two northern New Jersey watersheds. Surface wetness was positively associated with the subsequent abundance of the dominant floodwater mosquito species, Aedes vexans, and the swamp water species, Anopheles walkeri. The subsequent abundance of Culex pipiens, a species that breeds in polluted, eutrophic waters, was negatively correlated with local modeled surface wetness. These associations permit real-time monitoring and forecasting of these floodwater and nonfloodwater species at high spatial and temporal resolution. These predictions will enable public health agencies to institute control measures before the mosquitoes emerge as adults, when their role as transmitters of disease comes into play. PMID:11749741

  1. Using a dynamic hydrology model to predict mosquito abundances in flood and swamp water.

    PubMed

    Shaman, Jeffrey; Stieglitz, Marc; Stark, Colin; Le Blancq, Sylvie; Cane, Mark

    2002-01-01

    We modeled surface wetness at high resolution, using a dynamic hydrology model, to predict flood and swamp water mosquito abundances. Historical meteorologic data, as well as topographic, soil, and vegetation data, were used to model surface wetness and identify potential fresh and swamp water breeding habitats in two northern New Jersey watersheds. Surface wetness was positively associated with the subsequent abundance of the dominant floodwater mosquito species, Aedes vexans, and the swamp water species, Anopheles walkeri. The subsequent abundance of Culex pipiens, a species that breeds in polluted, eutrophic waters, was negatively correlated with local modeled surface wetness. These associations permit real-time monitoring and forecasting of these floodwater and nonfloodwater species at high spatial and temporal resolution. These predictions will enable public health agencies to institute control measures before the mosquitoes emerge as adults, when their role as transmitters of disease comes into play.

  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. 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

  4. Hydrologic Forecasting at the US National Weather Service in the 21st Century: Transition from the NWS River Forecast System (NWSRFS) to the Community Hydrologic Prediction System (CHPS)

    NASA Astrophysics Data System (ADS)

    Restrepo, Pedro; Roe, Jon; Dietz, Christine; Werner, Micha; Gijsbers, Peter; Hartman, Robert; Opitz, Harold; Olsen, Billy; Halquist, John; Shedd, Robert

    2010-05-01

    The US National Weather Service developed the River Forecast System (NWSRFS) since the 1970s as the platform for performing hydrologic forecasts. The system, originally developed for the computers of that era, was optimized for speed of execution and compact and fast data storage and retrieval. However, with modern computers those features became less of a driver, and, instead, the ability to maintain and transition of new developments in data and modeling research into operations have become the top system priorities for hydrologic forecasting software applications. To address those two new priorities, and to allow the hydrologic research community at large to be able to contribute models and forecasting techniques, the National Weather Service proposed the development of the Community Hydrologic Prediction System (CHPS). CHPS must be sufficiently flexible not only to ensure current operational models and data remain available, but also to integrate readily modeling approaches and data from the wider community of practitioners and scientists involved in hydro-meteorological forecasting. Portability considerations require the computational infrastructure to be programmed in a language such as Java, and data formats conform to open standards such as XML. After examining a number of potential candidates, the NWS settled on the Delft Flood Early Warning System (Delft FEWS) from Deltares as the basis for CHPS, since it shares the basic design characteristics, the underlying community philosophy and was being successfully used in operations in several countries. This paper describes the characteristics of CHPS and the transition path to make it operational and available to the community.

  5. 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

  6. 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

  7. Advancing monthly streamflow prediction accuracy of CART models using ensemble learning paradigms

    NASA Astrophysics Data System (ADS)

    Erdal, Halil Ibrahim; Karakurt, Onur

    2013-01-01

    SummaryStreamflow forecasting is one of the most important steps in the water resources planning and management. Ensemble techniques such as bagging, boosting and stacking have gained popularity in hydrological forecasting in the recent years. The study investigates the potential usage of two ensemble learning paradigms (i.e., bagging; stochastic gradient boosting) in building classification and regression trees (CARTs) ensembles to advance the streamflow prediction accuracy. The study, initially, investigates the use of classification and regression trees for monthly streamflow forecasting and employs a support vector regression (SVR) model as the benchmark model. The analytic results indicate that CART outperforms SVR in both training and testing phases. Although the obtained results of CART model in training phase are considerable, it is not in testing phase. Thus, to optimize the prediction accuracy of CART for monthly streamflow forecasting, we incorporate bagging and stochastic gradient boosting which are rooted in same philosophy, advancing the prediction accuracy of weak learners. Comparing with the results of bagged regression trees (BRTs) and stochastic gradient boosted regression trees (GBRTs) models possess satisfactory monthly streamflow forecasting performance than CART and SVR models. Overall, it is found that ensemble learning paradigms can remarkably advance the prediction accuracy of CART models in monthly streamflow forecasting.

  8. 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.

  9. [Advance in researches on the effect of forest on hydrological process].

    PubMed

    Zhang, Zhiqiang; Yu, Xinxiao; Zhao, Yutao; Qin, Yongsheng

    2003-01-01

    According to the effects of forest on hydrological process, forest hydrology can be divided into three related aspects: experimental research on the effects of forest changing on hydrological process quantity and water quality; mechanism study on the effects of forest changing on hydrological cycle, and establishing and exploitating physical-based distributed forest hydrological model for resource management and engineering construction. Orientation experiment research can not only support the first-hand data for forest hydrological model, but also make clear the precipitation-runoff mechanisms. Research on runoff mechanisms can be valuable for the exploitation and improvement of physical based hydrological models. Moreover, the model can also improve the experimental and runoff mechanism researches. A review of above three aspects are summarized in this paper.

  10. Predicting Malignancy in Thyroid Nodules: Molecular Advances

    PubMed Central

    Melck, Adrienne L.; Yip, Linwah

    2016-01-01

    Over the last several years, a clearer understanding of the genetic alterations underlying thyroid carcinogenesis has developed. This knowledge can be utilized to tackle one of the greatest challenges facing thyroidologists: management of the indeterminate thyroid nodule. Despite the accuracy of fine needle aspiration cytology, many patients undergo invasive surgery in order to determine if a follicular or Hurthle cell neoplasm is malignant, and better diagnostic tools are required. A number of biomarkers have recently been studied and show promise in this setting. In particular, BRAF, RAS, PAX8-PPARγ, microRNAs and loss of heterozygosity have each been demonstrated as useful molecular tools for predicting malignancy and can thereby guide decisions regarding surgical management of nodular thyroid disease. This review summarizes the current literature surrounding each of these markers and highlights our institution’s prospective analysis of these markers and their subsequent incorporation into our management algorithms for thyroid nodules. PMID:21818817

  11. 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.

  12. Advances in tilt rotor noise prediction

    NASA Astrophysics Data System (ADS)

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

    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.

  13. Seasonal streamflow prediction by a combined climate-hydrologic system for river basins of Taiwan

    NASA Astrophysics Data System (ADS)

    Kuo, Chun-Chao; Gan, Thian Yew; Yu, Pao-Shan

    2010-06-01

    SummaryA combined, climate-hydrologic system with three components to predict the streamflow of two river basins of Taiwan at one season (3-month) lead time for the NDJ and JFM seasons was developed. The first component consists of the wavelet-based, ANN-GA model (Artificial Neural Network calibrated by Genetic Algorithm) which predicts the seasonal rainfall by using selected sea surface temperature (SST) as predictors, given that SST are generally predictable by climate models up to 6-month lead time. For the second component, three disaggregation models, Valencia and Schaake (VS), Lane, and Canonical Random Cascade Model (CRCM), were tested to compare the accuracy of seasonal rainfall disaggregated by these three models to 3-day time scale rainfall data. The third component consists of the continuous rainfall-runoff model modified from HBV (called the MHBV) and calibrated by a global optimization algorithm against the observed rainfall and streamflow data of the Shihmen and Tsengwen river basins of Taiwan. The proposed system was tested, first by disaggregating the predicted seasonal rainfall of ANN-GA to rainfall of 3-day time step using the Lane model; then the disaggregated rainfall data was used to drive the calibrated MHBV to predict the streamflow for both river basins at 3-day time step up to a season's lead time. Overall, the streamflow predicted by this combined system for the NDJ season, which is better than that of the JFM season, will be useful for the seasonal planning and management of water resources of these two river basins of Taiwan.

  14. Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 2: Application

    NASA Astrophysics Data System (ADS)

    Elshorbagy, A.; Corzo, G.; Srinivasulu, S.; Solomatine, D. P.

    2010-10-01

    In this second part of the two-part paper, the data driven modeling (DDM) experiment, presented and explained in the first part, is implemented. Inputs for the five case studies (half-hourly actual evapotranspiration, daily peat soil moisture, daily till soil moisture, and two daily rainfall-runoff datasets) are identified, either based on previous studies or using the mutual information content. Twelve groups (realizations) were randomly generated from each dataset by randomly sampling without replacement from the original dataset. Neural networks (ANNs), genetic programming (GP), evolutionary polynomial regression (EPR), Support vector machines (SVM), M5 model trees (M5), K-nearest neighbors (K-nn), and multiple linear regression (MLR) techniques are implemented and applied to each of the 12 realizations of each case study. The predictive accuracy and uncertainties of the various techniques are assessed using multiple average overall error measures, scatter plots, frequency distribution of model residuals, and the deterioration rate of prediction performance during the testing phase. Gamma test is used as a guide to assist in selecting the appropriate modeling technique. Unlike two nonlinear soil moisture case studies, the results of the experiment conducted in this research study show that ANNs were a sub-optimal choice for the actual evapotranspiration and the two rainfall-runoff case studies. GP is the most successful technique due to its ability to adapt the model complexity to the modeled data. EPR performance could be close to GP with datasets that are more linear than nonlinear. SVM is sensitive to the kernel choice and if appropriately selected, the performance of SVM can improve. M5 performs very well with linear and semi linear data, which cover wide range of hydrological situations. In highly nonlinear case studies, ANNs, K-nn, and GP could be more successful than other modeling techniques. K-nn is also successful in linear situations, and it should

  15. Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 2: Application

    NASA Astrophysics Data System (ADS)

    Elshorbagy, A.; Corzo, G.; Srinivasulu, S.; Solomatine, D. P.

    2009-11-01

    In this second part of the two-part paper, the data driven modeling (DDM) experiment, presented and explained in the first part, is implemented. Inputs for the five case studies (half-hourly actual evapotranspiration, daily peat soil moisture, daily till soil moisture, and two daily rainfall-runoff datasets) are identified, either based on previous studies or using the mutual information content. Twelve groups (realizations) were randomly generated from each dataset by randomly sampling without replacement from the original dataset. Neural networks (ANNs), genetic programming (GP), evolutionary polynomial regression (EPR), Support vector machines (SVM), M5 model trees (M5), K nearest neighbors (K-nn), and multiple linear regression (MLR) techniques are implemented and applied to each of the 12 realizations of each case study. The predictive accuracy and uncertainties of the various techniques are assessed using multiple average overall error measures, scatter plots, frequency distribution of model residuals, and the deterioration rate of prediction performance during the testing phase. Gamma test is used as a guide to assist in selecting the appropriate modeling technique. Unlike the two nonlinear soil moisture case studies, the results of the experiment conducted in this research study show that ANNs were a sub-optimal choice for the actual evapotranspiration and the two rainfall-runoff case studies. GP is the most successful technique due to its ability to adapt the model complexity to the modeled data. EPR performance could be close to GP with datasets that are more linear than nonlinear. SVM is sensitive to the kernel choice and if appropriately selected, the performance of SVM can improve. M5 performs very well with linear and semi linear data, which cover wide range of hydrological situations. In highly nonlinear case studies, ANNs, K-nn, and GP could be more successful than other modeling techniques. K-nn is also successful in linear situations, and it

  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. 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.

  19. Evaluating the impacts of soil data on hydrological and nonpoint source pollution prediction.

    PubMed

    Chen, Lei; Wang, Guobo; Zhong, Yucen; Shen, Zhenyao

    2016-09-01

    Soil data are one key input for most hydrological and nonpoint source (H/NPS) models, and quantifying the error transmission from soil data to H/NPS predictions is of great importance. In this study, two typical soil datasets were compared using the Soil and Water Assessment Tool (SWAT) in a typical mountainous watershed, the Three Gorges Reservoir Region, China. Besides, the effects of soil data resolution were evaluated, and the error transmission from soil data to watershed management strategy was assessed. The results indicate that model outputs are not sensitive to changes of soil data resolution but the choice of soil data greatly impacts the application of watershed models, in terms of the goodness-of-fit indicator, predicted data and related uncertainty. This soil data-induced error would be inevitably magnified from the flow simulation to the NPS prediction stage. This study could indicate that the choice of soil data will lead to significant differences in management schemes for specific pollution periods. These results provide information on the impacts of soil data on the functionality of watershed models and valuable information for the appropriateness of each soil database.

  20. Upper Limits of Predictability in Long-Range Climate/Hydrologic Forecasts

    NASA Technical Reports Server (NTRS)

    Koster, R. D.; Suarez, M. J.; Heiser, M.

    1998-01-01

    The accurate forecasting of el nino or la nina conditions in the tropical Pacific can potentially lead to valuable predictions of hydrological anomalies over land at seasonal to interannual timescales. Even with highly accurate earth system models, though, our ability to generate these continental forecasts will always be limited by the chaotic nature of the atmospheric circulation. The nature of this fundamental limitation is explored through the use of 16-member ensembles of multi-decade GCM simulations. In each simulation of the first ensemble, sea surface temperatures (SSTs) are given the same realistic interannual variations over a 45-year period, and land surface state is allowed to evolve with that of the atmosphere. Analysis of the results shows that the SSTs control the temporal organization of continental precipitation anomalies to a significant extent in the tropics and to a much smaller extent in midlatitudes. In each simulation of the second ensemble, we prescribe SSTs as before, but we also prescribe interannual variations in the low frequency component of evaporation efficiency over land. Thus, in the second ensemble, we effectively make the extreme assumption that surface boundary conditions across the globe are perfectly predictable, and we quantify the consistency with which the atmosphere (particularly precipitation) responds to these boundary conditions. The resulting "absolute upper limit" on the predictability of precipitation is found to be quite high in the tropics yet only moderate in many midlatitude regions.

  1. 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

    2015-01-01

    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.

  2. 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

  3. 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.

  4. 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

  5. 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.

  6. 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

  7. 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

  8. [Research advances in dynamic mechanism and its simulation of eco-hydrological process in forest catchment].

    PubMed

    Diao, Yiwei; Pei, Tiefan

    2004-12-01

    Hydrological process is the key link between climatic fluctuations and ecologic dynamics of forests at spatial and temporal scales. To some extent, global climate change and large-scale human's activities will impact the spatial-temporal changes of eco-hydrological process in forest catchments in the future. Therefore, researches on the dynamic mechanism of eco-hydrological processes in forest catchments play a crucial role in understanding and controlling the rational use of ecological resources, resuming regional ecology, and sustainable development in economy. This paper described the interception, evapotranspiration and rainfall-runoff of forest ecological system and their effects on hydrological process. The spatial structure of soil moisture and its evolution with time were also the cause and consequence of forest. The spatial-temporal interaction between hydrologic and ecologic dynamics, the application of distributed hydrological model, and the eco-hydrological dynamics and cybernetics of forest would be the most exciting frontiers of the relative researches in the future. PMID:15825459

  9. Incorporating multi-platform remote sensing products for prediction of post-fire hydrologic recovery

    NASA Astrophysics Data System (ADS)

    Kinoshita, A. M.; Hogue, T. S.; Kim, J.

    2011-12-01

    Wildfires are increasing in intensity and size across the western US, and more than half of the 20 largest fires in California have occurred within the last decade. Development in southern California has increased and as a result many homes at the wildland-urban interface (WUI) are affected by fire events themselves and post-fire processes. Current management efforts are mostly concentrated around immediate post-fire effects (first storm season); however, burned systems are often altered for prolonged periods of time, creating long-term concerns for downstream communities at the WUI. Previous work in two southern Californian watersheds, City Creek and Devil Canyon, shows lack of vegetation recovery and significant changes in annual and seasonal discharge for the post-fire study period (seven years). Applying remotely sensed data streams enhances monitoring of large and ungauged burned areas at high spatial and temporal resolutions. The goal of the current study is to integrate remote sensing data from multiple satellite platforms to improve prediction of the spatial and temporal variability of key hydrological variables controlling post-fire response. Remote sensing data streams from Moderate-resolution Imaging Spectroradiometer (MODIS) and Landsat are used to derive a range of land surface parameters and evaluate ecosystem and hydrologic recovery for the Arroyo Seco, an urban-fringe watershed in southern California burned by the 2009 Station Fire. A UCLA remotely-sensed evapotranspiration (ET) product is used to provide insight on vegetation growth and plant water availability. A UCLA MODIS-AMSR-E soil moisture product is used to evaluate the spatial variability of post-fire surface soil moisture and coupled storm runoff response. A range of other parameters, surface temperature, albedo and vegetation indices, are also evaluated to provide insight on the spatial variability of watershed recovery. Predicting the short and long-term risks of post-fire floods, debris

  10. 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.

  11. 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 Central

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

    2008-01-01

    Monitoring and simulating urban sprawl and its effects on land-use patterns and hydrological processes in urbanized watersheds are essential in land-use and water-resource planning and management. This study applies a novel framework to the urban growth model Slope, Land use, Excluded land, Urban extent, Transportation, and Hillshading (SLEUTH) and land-use change with the Conversion of Land use and its Effects (CLUE-s) model using historical SPOT images to predict urban sprawl in the Paochiao watershed in Taipei County, Taiwan. The historical and predicted land-use data was input into Patch Analyst to obtain landscape metrics. This data was also input to the Generalized Watershed Loading Function (GWLF) model to analyze the effects of future urban sprawl on the land-use patterns and watershed hydrology. The landscape metrics of the historical SPOT images show that land-use patterns changed between 1990–2000. The SLEUTH model accurately simulated historical land-use patterns and urban sprawl in the Paochiao watershed, and simulated future clustered land-use patterns (2001–2025). The CLUE-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 SLEUTH and CLUE-s models show the significant impact urban sprawl will have on land-use patterns in the Paochiao watershed. The historical and predicted land-use patterns in the watershed tended to fragment, had regular shapes and interspersion patterns, but were relatively less isolated in 2001–2025 and less interspersed from 2005–2025 compared with land-use pattern in 1990. During the study, the variability and magnitude of hydrological components based on the historical and predicted land-use patterns were cumulatively affected by urban sprawl in the watershed; specifically, surface runoff increased significantly by 22.0% and baseflow decreased by 18.0% during 1990–2025. The proposed approach is an

  12. 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...

  13. Advanced flood forecasting in Alpine watersheds by coupling meteorological observations and forecasts with a distributed hydrological model

    NASA Astrophysics Data System (ADS)

    Jasper, Karsten; Gurtz, Joachim; Lang, Herbert

    2002-10-01

    Flood forecasting may be improved by coupling atmospheric and hydrological models. To investigate the current potential of such an approach in complex mountain watersheds, the authors carried out a number of combined high-resolution one-way driven model experiments to generate runoff hydrographs for seven extreme flood events which occurred in the Lago Maggiore basin between 1993 and 2000. The Alpine Ticino-Verzasca-Maggia basin (2627 km 2) is located directly to the south of the main Alpine ridge embracing a great part of the drainage area of Lago Maggiore. For this basin, the grid-based hydrological catchment model WaSiM-ETH was employed to determine the continuous runoff hydrographs. In the model experiments, two different sets of meteorological input data were used: (1) surface observation data from station measurements and from weather radar, and (2) forecast data from five different high-resolution numerical weather prediction (NWP) models with grid cell sizes between 2 and 14 km. This paper presents and compares selected results of these flood runoff simulations with particular attention to the experimental design of the model coupling. The configuration and initialization of the hydrological model runs are outlined as well as the down-scale techniques which proved to provide an adequate spatial interpolation of the meteorological variables onto the 500 m×500 m grid of the hydrological model. In order to evaluate the various hydrological model results as generated from the different outputs from the five NWP models, some coupled experiments with 'non-standard' NWP model outputs have been carried out. In particular, the results of these sensitivity studies point to inherent limits of high-resolution flood runoff predictions in complex mountain terrain.

  14. A study on WRF radar data assimilation for hydrological rainfall prediction

    NASA Astrophysics Data System (ADS)

    Liu, J.; Bray, M.; Han, D.

    2013-08-01

    Mesoscale numerical weather prediction (NWP) models are gaining more attention in providing high-resolution rainfall forecasts at the catchment scale for real-time flood forecasting. The model accuracy is however negatively affected by the "spin-up" effect and errors in the initial and lateral boundary conditions. Synoptic studies in the meteorological area have shown that the assimilation of operational observations, especially the weather radar data, can improve the reliability of the rainfall forecasts from the NWP models. This study aims at investigating the potential of radar data assimilation in improving the NWP rainfall forecasts that have direct benefits for hydrological applications. The Weather Research and Forecasting (WRF) model is adopted to generate 10 km rainfall forecasts for a 24 h storm event in the Brue catchment (135.2 km2) located in southwest England. Radar reflectivity from the lowest scan elevation of a C-band weather radar is assimilated by using the three-dimensional variational (3D-Var) data-assimilation technique. Considering the unsatisfactory quality of radar data compared to the rain gauge observations, the radar data are assimilated in both the original form and an improved form based on a real-time correction ratio developed according to the rain gauge observations. Traditional meteorological observations including the surface and upper-air measurements of pressure, temperature, humidity and wind speed are also assimilated as a bench mark to better evaluate and test the potential of radar data assimilation. Four modes of data assimilation are thus carried out on different types/combinations of observations: (1) traditional meteorological data; (2) radar reflectivity; (3) corrected radar reflectivity; (4) a combination of the original reflectivity and meteorological data; and (5) a combination of the corrected reflectivity and meteorological data. The WRF rainfall forecasts before and after different modes of data assimilation are

  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. 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.

  19. 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.

  20. 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...

  1. Advancing Satellite-Based Flood Prediction in Complex Terrain Using High-Resolution Numerical Weather Prediction

    NASA Astrophysics Data System (ADS)

    Zhang, X.; Anagnostou, E. N.; Nikolopoulos, E. I.; Bartsotas, N. S.

    2015-12-01

    Floods constitute one of the most significant and frequent natural hazard in mountainous regions. Satellite-based precipitation products offer in many cases the only available source of QPE. However, satellite-based QPE over complex terrain suffer from significant bias that limits their applicability for hydrologic modeling. In this work we investigate the potential of a new correction procedure, which involves the use of high-resolution numerical weather prediction (NWP) model simulations to adjust satellite QPE. Adjustment is based on the pdf matching of satellite and NWP (used as reference) precipitation distribution. The impact of correction procedure on simulating the hydrologic response is examined for 15 storm events that generated floods over the mountainous Upper Adige region of Northern Italy. Atmospheric simulations were performed at 1-km resolution from a state-of-the-art atmospheric model (RAMS/ICLAMS). The proposed error correction procedure was then applied on the widely used TRMM 3B42 satellite precipitation product and the evaluation of the correction was based on independent in situ precipitation measurements from a dense rain gauge network (1 gauge / 70 km2) available in the study area. Satellite QPE, before and after correction, are used to simulate flood response using ARFFS (Adige River Flood Forecasting System), a semi-distributed hydrologic model, which is used for operational flood forecasting in the region. Results showed that bias in satellite QPE before correction was significant and had a tremendous impact on the simulation of flood peak, however the correction procedure was able to reduce bias in QPE and therefore improve considerably the simulated flood hydrograph.

  2. Predicting the acceptance of advanced rider assistance systems.

    PubMed

    Huth, Véronique; Gelau, Christhard

    2013-01-01

    The strong prevalence of human error as a crash causation factor in motorcycle accidents calls for countermeasures that help tackling this issue. Advanced rider assistance systems pursue this goal, providing the riders with support and thus contributing to the prevention of crashes. However, the systems can only enhance riding safety if the riders use them. For this reason, acceptance is a decisive aspect to be considered in the development process of such systems. In order to be able to improve behavioural acceptance, the factors that influence the intention to use the system need to be identified. This paper examines the particularities of motorcycle riding and the characteristics of this user group that should be considered when predicting the acceptance of advanced rider assistance systems. Founded on theories predicting behavioural intention, the acceptance of technologies and the acceptance of driver support systems, a model on the acceptance of advanced rider assistance systems is proposed, including the perceived safety when riding without support, the interface design and the social norm as determinants of the usage intention. Since actual usage cannot be measured in the development stage of the systems, the willingness to have the system installed on the own motorcycle and the willingness to pay for the system are analyzed, constituting relevant conditions that allow for actual usage at a later stage. Its validation with the results from user tests on four advanced rider assistance systems allows confirming the social norm and the interface design as powerful predictors of the acceptance of ARAS, while the extent of perceived safety when riding without support did not have any predictive value in the present study.

  3. 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).

  4. 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.

  5. Predictive Understanding of Seasonal Hydrological Dynamics under Climate and Land Use-Land Cover Change

    NASA Astrophysics Data System (ADS)

    Batra, N.; Yang, Y. E.; Choi, H. I.; Kumar, P.; Cai, X.; Fraiture, C. D.

    2008-12-01

    Water has always been and will continue to be an important factor in agricultural production and any alteration in the seasonal distribution of water availability due to climate and land use-land cover change (LULCC) will significantly impact the future production. To achieve the ecologic, economic and social objectives of sustainability, physical understanding of the linkages between climatic changes, LULCC and hydrological response is required. Aided by satellite data, modeling and understanding of the interactions between physical processes of the climate system and society, more reliable regional LULCC and climate change projections are now available. However, resulting quantitative projection of changes on the regional scale hydrological components at the seasonal time scale are sparse. This study attempts to quantify the seasonal hydrological response due to projected LULCC and climate change scenario of Intergovernmental Panel on Climate Change (IPCC) in different hydro-climatic regions of the world. The Common Land Model (CLM) is used for global assessment of future hydrologic response with the development of a consistent global GIS based database for the surface boundary conditions and meteorological forcing of the model. Future climate change projections are derived from the IPCC Fourth Assessment Report: Working Group I - The Physical Science Basis. The study is performed over nine river basins selected from Asia, Africa and North America to present the broad climatic and landscape controls on the seasonal hydrological dynamics. Future changes in water availability are quite evident from our results based upon changes in the volume and seasonality of precipitation, runoff and evapotranspiration. Severe water scarcity is projected to occur in certain seasons which may not be known through annual estimates. Knowledge of the projected seasonal hydrological response can be effectively used for developing adaptive management strategies for the sustainability

  6. Development and application of a conceptual hydrologic model to predict soil salinity within modern Tunisian oases

    NASA Astrophysics Data System (ADS)

    Askri, Brahim; Bouhlila, Rachida; Job, Jean Olivier

    2010-01-01

    SummaryIn modern oases situated in the south of Tunisia, secondary salination of irrigated lands is a crucial problem. The visible salt deposits and soil salination processes are the consequence of several factors including the excessive use of saline irrigation water, seepage from earthen canal systems, inefficient irrigation practices and inadequate drainage. Understanding the mechanism of the secondary salination is of interest in order to maintain existing oases, and thus ensure the sustainability of date production in this part of the country. Therefore, a conceptual, daily, semi-distributed hydrologic model (OASIS_MOD) was developed to analyse the impact of irrigation management on the water table fluctuation, soil salinity and drain discharge, and to evaluate measures to control salinity within an oasis ecosystem. The basic processes incorporated in the model are irrigation, infiltration, percolation to the shallow groundwater, soil evaporation, crop transpiration, groundwater flow, capillary rise flux, and drain discharge. OASIS_MOD was tested with data collected in a parcel of farmland situated in the Segdoud oasis, in the south-west of Tunisia. The calibration results showed that groundwater levels were simulated with acceptable accuracy, since the differences between the simulated and measured values are less than 0.22 m. However, the model under-predicted some water table peaks when irrigation occurs due to inconsistencies in the irrigation water data. The validation results showed that deviations between observed and simulated groundwater levels have increased to about 0.5 m due to under-estimation of groundwater inflow from an upstream palm plantation. A long-term simulation scenario revealed that the soil salinity and groundwater level have three types of variability in time: a daily variability due to irrigation practices, seasonal fluctuation due to climatic conditions and annual variability explained by the increase in cultivated areas. The

  7. 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

    ... From the Federal Register Online via the Government Publishing Office DEPARTMENT OF HEALTH AND 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...

  8. 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.

  9. Ancient numerical daemons of conceptual hydrological modeling: 2. Impact of time stepping schemes on model analysis and prediction

    NASA Astrophysics Data System (ADS)

    Kavetski, Dmitri; Clark, Martyn P.

    2010-10-01

    Despite the widespread use of conceptual hydrological models in environmental research and operations, they remain frequently implemented using numerically unreliable methods. This paper considers the impact of the time stepping scheme on model analysis (sensitivity analysis, parameter optimization, and Markov chain Monte Carlo-based uncertainty estimation) and prediction. It builds on the companion paper (Clark and Kavetski, 2010), which focused on numerical accuracy, fidelity, and computational efficiency. Empirical and theoretical analysis of eight distinct time stepping schemes for six different hydrological models in 13 diverse basins demonstrates several critical conclusions. (1) Unreliable time stepping schemes, in particular, fixed-step explicit methods, suffer from troublesome numerical artifacts that severely deform the objective function of the model. These deformations are not rare isolated instances but can arise in any model structure, in any catchment, and under common hydroclimatic conditions. (2) Sensitivity analysis can be severely contaminated by numerical errors, often to the extent that it becomes dominated by the sensitivity of truncation errors rather than the model equations. (3) Robust time stepping schemes generally produce "better behaved" objective functions, free of spurious local optima, and with sufficient numerical continuity to permit parameter optimization using efficient quasi Newton methods. When implemented within a multistart framework, modern Newton-type optimizers are robust even when started far from the optima and provide valuable diagnostic insights not directly available from evolutionary global optimizers. (4) Unreliable time stepping schemes lead to inconsistent and biased inferences of the model parameters and internal states. (5) Even when interactions between hydrological parameters and numerical errors provide "the right result for the wrong reason" and the calibrated model performance appears adequate, unreliable

  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. 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.

  12. Application of current and future satellite missions to hydrologic prediction in transboundary rivers

    NASA Astrophysics Data System (ADS)

    Biancamaria, S.; Clark, E.; Lettenmaier, D. P.

    2010-12-01

    More than 256 major global river basins, which cover about 45% of the continental land surface, are shared among two or more countries. The flow of such a large part of the global runoff across international boundaries has led to tension in many cases between upstream and downstream riparian countries. Among many examples, this is the case of the Ganges and the Brahmaputra Rivers, which cross the boundary between India and Bangladesh. Hydrological data (river discharge, reservoir storage) are viewed as sensitive by India (the upstream country) and are therefore not shared with Bangladesh, which can only monitor river discharge and water depth at the international border crossing. These measurements only allow forecasting of floods in the interior and southern portions of the country two to three days in advance. These forecasts are not long enough either for agricultural water management purposes (for which knowledge of upstream reservoir storage is essential) or for disaster preparedness purposes. Satellite observations of river spatial extent, surface slope, reservoir area and surface elevation have the potential to make tremendous changes in management of water within the basins. In this study, we examine the use of currently available satellite measurements (in India) and in-situ measurements in Bangladesh to increase forecast lead time in the Ganges and Brahmaputra Rivers. Using nadir altimeters, we find that it is possible to forecast the discharge of the Ganges River at the Bangladesh border with lead time 3 days and mean absolute error of around 25%. On the Ganges River, 2-day forecasts are possible with a mean absolute error of around 20%. When combined with optical/infra-red MODIS images, it is possible to map water elevations along the river and its floodplain upstream of the boundary, and to compute water storage. However, the high frequency of clouds in this region results in relatively large errors in the water mask. Due to the nadir altimeter

  13. 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.

  14. Toward improving the reliability of hydrologic prediction: Model structure uncertainty and its quantification using ensemble-based genetic programming framework

    NASA Astrophysics Data System (ADS)

    Parasuraman, Kamban; Elshorbagy, Amin

    2008-12-01

    Uncertainty analysis is starting to be widely acknowledged as an integral part of hydrological modeling. The conventional treatment of uncertainty analysis in hydrologic modeling is to assume a deterministic model structure, and treat its associated parameters as imperfectly known, thereby neglecting the uncertainty associated with the model structure. In this paper, a modeling framework that can explicitly account for the effect of model structure uncertainty has been proposed. The modeling framework is based on initially generating different realizations of the original data set using a non-parametric bootstrap method, and then exploiting the ability of the self-organizing algorithms, namely genetic programming, to evolve their own model structure for each of the resampled data sets. The resulting ensemble of models is then used to quantify the uncertainty associated with the model structure. The performance of the proposed modeling framework is analyzed with regards to its ability in characterizing the evapotranspiration process at the Southwest Sand Storage facility, located near Ft. McMurray, Alberta. Eddy-covariance-measured actual evapotranspiration is modeled as a function of net radiation, air temperature, ground temperature, relative humidity, and wind speed. Investigating the relation between model complexity, prediction accuracy, and uncertainty, two sets of experiments were carried out by varying the level of mathematical operators that can be used to define the predictand-predictor relationship. While the first set uses just the additive operators, the second set uses both the additive and the multiplicative operators to define the predictand-predictor relationship. The results suggest that increasing the model complexity may lead to better prediction accuracy but at an expense of increasing uncertainty. Compared to the model parameter uncertainty, the relative contribution of model structure uncertainty to the predictive uncertainty of a model is

  15. 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.

  16. Nitrate reduction in geologically heterogeneous catchments--a framework for assessing the scale of predictive capability of hydrological models.

    PubMed

    Refsgaard, Jens Christian; Auken, Esben; Bamberg, Charlotte A; Christensen, Britt S B; Clausen, Thomas; Dalgaard, Esben; Effersø, Flemming; Ernstsen, Vibeke; Gertz, Flemming; Hansen, Anne Lausten; He, Xin; Jacobsen, Brian H; Jensen, Karsten Høgh; Jørgensen, Flemming; Jørgensen, Lisbeth Flindt; Koch, Julian; Nilsson, Bertel; Petersen, Christian; De Schepper, Guillaume; Schamper, Cyril; Sørensen, Kurt I; Therrien, Rene; Thirup, Christian; Viezzoli, Andrea

    2014-01-15

    In order to fulfil the requirements of the EU Water Framework Directive nitrate load from agricultural areas to surface water in Denmark needs to be reduced by about 40%. The regulations imposed until now have been uniform, i.e. the same restrictions for all areas independent of the subsurface conditions. Studies have shown that on a national basis about 2/3 of the nitrate leaching from the root zone is reduced naturally, through denitrification, in the subsurface before reaching the streams. Therefore, it is more cost-effective to identify robust areas, where nitrate leaching through the root zone is reduced in the saturated zone before reaching the streams, and vulnerable areas, where no subsurface reduction takes place, and then only impose regulations/restrictions on the vulnerable areas. Distributed hydrological models can make predictions at grid scale, i.e. at much smaller scale than the entire catchment. However, as distributed models often do not include local scale hydrogeological heterogeneities, they are typically not able to make accurate predictions at scales smaller than they are calibrated. We present a framework for assessing nitrate reduction in the subsurface and for assessing at which spatial scales modelling tools have predictive capabilities. A new instrument has been developed for airborne geophysical measurements, Mini-SkyTEM, dedicated to identifying geological structures and heterogeneities with horizontal and lateral resolutions of 30-50 m and 2m, respectively, in the upper 30 m. The geological heterogeneity and uncertainty are further analysed by use of the geostatistical software TProGS by generating stochastic geological realisations that are soft conditioned against the geophysical data. Finally, the flow paths within the catchment are simulated by use of the MIKE SHE hydrological modelling system for each of the geological models generated by TProGS and the prediction uncertainty is characterised by the variance between the

  17. 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

  18. 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...

  19. 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

  20. 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.

  1. 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.

  2. Testing the Hydrological Landscape Unit Classification System and Other Terrain Analysis Measures for Predicting Low-Flow Nitrate and Chloride in Watersheds

    NASA Astrophysics Data System (ADS)

    Poor, Cara J.; McDonnell, Jeffrey J.; Bolte, John

    2008-11-01

    Elevated nitrate concentrations in streamwater are a major environmental management problem. While land use exerts a large control on stream nitrate, hydrology often plays an equally important role. To date, predictions of low-flow nitrate in ungauged watersheds have been poor because of the difficulty in describing the uniqueness of watershed hydrology over large areas. Clearly, hydrologic response varies depending on the states and stocks of water, flow pathways, and residence times. How to capture the dominant hydrological controls that combine with land use to define streamwater nitrate concentration is a major research challenge. This paper tests the new Hydrologic Landscape Regions (HLRs) watershed classification scheme of Wolock and others (Environmental Management 34:S71-S88, 2004) to address the question: Can HLRs be used as a way to predict low-flow nitrate? We also test a number of other indexes including inverse-distance weighting of land use and the well-known topographic index (TI) to address the question: How do other terrain and land use measures compare to HLR in terms of their ability to predict low-flow nitrate concentration? We test this for 76 watersheds in western Oregon using the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program and Regional Environmental Monitoring and Assessment Program data. We found that HLRs did not significantly improve nitrate predictions beyond the standard TI and land-use metrics. Using TI and inverse-distance weighting did not improve nitrate predictions; the best models were the percentage land use—elevation models. We did, however, see an improvement of chloride predictions using HLRs, TI, and inverse-distance weighting; adding HLRs and TI significantly improved model predictions and the best models used inverse-distance weighting and elevation. One interesting result of this study is elevation consistently predicted nitrate better than TI or the hydrologic classification

  3. Streamflow predictions in regulated river systems: hydrological non-stationarity versus anthropogenic water use

    NASA Astrophysics Data System (ADS)

    Dutta, D.; Kim, S.; Vaze, J.; Hughes, J.

    2015-06-01

    Streamflow in a regulated river system is highly influenced by storage regulations and anthropogenic water use in addition to climate variability. Thus, changes in climate-streamflow relationships and dominant hydrological processes over time are difficult to quantify in a regulated system without partitioning influence of storage regulation and anthropogenic water uses. This requires a robust regulated river system model, which takes into consideration of both hydrological and man-made flow regulation processes, as well as anthropogenic water uses. In this study, a newly developed large-scale river system model (called "AWRA-R") was used to assess the influence of both anthropogenic and climate variability/change on streamflow non-stationarity in the Murray Darling Basin (MDB). MDB is one of the highly regulated basins in Australia with multiple large and small storages developed primarily for supplying water to irrigated agriculture. The modelling was undertaken for the period of 1950-2010, which includes rapid water resources development and both wet and dry climate. The AWRA-R model was calibrated for a reasonably long period and then, validated on an independent period. The calibrated parameters were used to simulate streamflow under current and pre-development conditions to analyse the streamflow variability and influence of climate variability and anthropogenic development on streamflow trend. This paper briefly introduces the model and the method used for assessing streamflow variability under natural and developed conditions and presents the results and findings.

  4. 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

  5. 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...

  6. 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

  7. Prediction of concurrent chemoradiotherapy outcome in advanced oropharyngeal cancer

    PubMed Central

    HASEGAWA, MASAHIRO; MAEDA, HIROYUKI; DENG, ZEYI; KIYUNA, ASANORI; GANAHA, AKIRA; YAMASHITA, YUKASHI; MATAYOSHI, SEN; AGENA, SHINYA; TOITA, TAKAFUMI; UEHARA, TAKAYUKI; SUZUKI, MIKIO

    2014-01-01

    The aim of this study was to investigate human papillomavirus (HPV) infection as a predictor of concurrent chemoradiotherapy (CCRT) response and indicator of planned neck dissection (PND) for patients with advanced oropharyngeal squamous cell carcinoma (OPSCC; stage III/IV). Overall, 39 OPSCC patients (32 men, 7 women; median age 61 years, range 39–79 years) were enrolled. The primary lesion and whole neck were irradiated up to 50.4 Gy, and subsequently the primary site and metastatic lymph nodes were boosted with a further 16.2 Gy. Although several chemotherapy regimens were employed, 82.1% of OPSCC patients received the combination of nedaplatin and 5-fluorouracil. HPV-related OPSCC (16 cases) was defined as both HPV DNA-positive status by polymerase chain reaction and p16INK4a overexpression by immunohistochemistry. Patients with N2 and N3 disease received PND 2–3 months after CCRT completion. Compared to non-responders, CCRT responders showed significantly lower nodal stage (N0 to N2b) and HPV-positive status in univariate analysis. Patients with HPV-related OPSCC had longer time to treatment failure (TTF) than those with HPV-unrelated OPSCC (p=0.040). Three-year TTF was 81.3 and 47.8% in the HPV-related and HPV-unrelated groups, respectively. There were also significant differences in disease-free survival (DFS) between the two OPSCC patient groups (p=0.042). Three-year DFS was 93.8 and 66.7% in patients with HPV-related and HPV-unrelated OPSCC, respectively. Multivariate logistic analysis showed a lower risk of TTF event occurrence in HPV-related OPSCC (p=0.041) than in HPV-unrelated OPSCC. Thus, HPV testing in addition to nodal stage was useful for predicting CCRT response, especially in advanced OPSCC. Because patients who received PND showed moderate locoregional control, PND is an effective surgical procedure for controlling neck lesions in patients with advanced HPV-unrelated disease. PMID:24969413

  8. 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...

  9. On the optimal design of experiments for conceptual and predictive discrimination of hydrologic system models

    NASA Astrophysics Data System (ADS)

    Kikuchi, C. P.; Ferré, T. P. A.; Vrugt, J. A.

    2015-06-01

    Experimental design and data collection constitute two main steps of the iterative research cycle (aka the scientific method). To help evaluate competing hypotheses, it is critical to ensure that the experimental design is appropriate and maximizes information retrieval from the system of interest. Scientific hypothesis testing is implemented by comparing plausible model structures (conceptual discrimination) and sets of predictions (predictive discrimination). This research presents a new Discrimination-Inference (DI) methodology to identify prospective data sets highly suitable for either conceptual or predictive discrimination. The DI methodology uses preposterior estimation techniques to evaluate the expected change in the conceptual or predictive probabilities, as measured by the Kullback-Leibler divergence. We present two case studies with increasing complexity to illustrate implementation of the DI for maximizing information withdrawal from a system of interest. The case studies show that highly informative data sets for conceptual discrimination are in general those for which between-model (conceptual) uncertainty is large relative to the within-model (parameter) uncertainty, and the redundancy between individual measurements in the set is minimized. The optimal data set differs if predictive, rather than conceptual, discrimination is the experimental design objective. Our results show that DI analyses highlight measurements that can be used to address critical uncertainties related to the prediction of interest. Finally, we find that the optimal data set for predictive discrimination is sensitive to the predictive grouping definition in ways that are not immediately apparent from inspection of the model structure and parameter values.

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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.

  15. 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.

  16. 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

  17. Modeling present hydrological conditions as a key to predict the future - results from a case study of a periglacial catchment in Greenland

    NASA Astrophysics Data System (ADS)

    Johansson, E.; Lindborg, T.; Berglund, S.

    2015-12-01

    The routing of water through periglacial landscapes is closely connected to the presence of permafrost, and freezing and thawing processes. To predict responses in the landscape to climate driven changes, we need to better understand the present day hydrology. The present hydrological processes, and the uncertainties in the data used to describe them, must be investigated and understood before we can develop models describing possible future conditions. In this work we have studied the hydrology of a catchment in the Kangerlussuaq region, Greenland. Johansson et al. (2015) presented a hydrological model of the catchment based on a new hydrological and meteorological data set from the catchment area. The present water balance was quantified, and the spatial and seasonal dynamics of the main hydrological fluxes were presented. It was shown that the model was able to reproduce the measured lake level dynamics and the measured components of the water balance. Based on this work we have used the numerical model to investigate the sensitivity in hydrological responses to different meteorological, geological and geometrical model input data. The aim with this study is to investigate the importance of the use of local data, but also to highlight the importance of present day site understanding when developing and applying the model for predicting responses to a changing climate. The results show that the site specific model is highly sensitive to the meteorological input data. Driving the model with precipitation data from a meteorological station only 30 km away from the catchment instead of local data from the studied catchment, or using local precipitation data not corrected for wind and adhesion losses, resulted in large discrepancies between measured and calculated lake levels. The modelled intra-annual dynamics of the active layer groundwater was shown to be sensitive both to the applied soil temperatures but also to the active layer depth and sediment stratigraphy.

  18. 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.

  19. 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...

  20. Uncertainty Analysis of the Ensemble Hydrological Forecasts in the Coupled Meteorological-Hydrological Modelling Environment

    NASA Astrophysics Data System (ADS)

    Xuan, Y.; Cluckie, I. D.

    2006-12-01

    The advances in meso-scale numerical weather predication render hydrologists the capability to incorporate high-resolution NWP directly into flood forecasting systems in order to obtain an extended lead time. However, such a direct application of rainfall outputs from the NWP model can contribute considerable uncertainties to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be highlighted by the scaling process. In this research, the ensemble hydrological forecasts driven by the ensemble weather prediction are investigated in an effort trying to understand both the potential and the implication of the ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. A data-rich catchment facilitated with dense rainguage network as well as high resolution weather radar was chosen to run the ensemble hydrological simulations of a distributed hydrological model driven by the high resolution NWP predictions. The uncertainties of the amount and the location/timing of the rainfall prediction are discussed whith the results showing that: (1) the hydrological model driven by the short-range NWP can produce forecasts comparable with those from a raingauge-driven one; (2) the ensemble hydrological forecast is able to disseminate abundant information with regard to the nature of the weather system and the confidence of the forecast itself; and (3) the uncertainties as well as systematical biases sometimes are significantly large and, as such, extra efforts need to be made to improve the quality of such a system.

  1. Recent advances towards a theory of catchment hydrologic transport: age-ranked storage and the Ω-functions

    NASA Astrophysics Data System (ADS)

    Harman, C. J.

    2014-12-01

    Models that faithfully represent spatially-integrated hydrologic transport through the critical zone at sub-watershed scales are essential building blocks for large-scale models of land use and climate controls on non-point source contaminant delivery. A particular challenge facing these models is the need to represent the delay between inputs of soluble contaminants (such as nitrate) at the field scale, and the solute load that appears in streams. Recent advances in the theory of time-variable transit time distributions (e.g. Botter et al., GRL 38(L11403), 2011) have provided a rigorous framework for representing conservative solute transport and its coupling to hydrologic variability and partitioning. Here I will present a reformulation of this framework that offers several distinct advantages over existing formulations: 1) the derivation of the governing conservation equation is simple and intuitive, 2) the closure relations are expressed in a convenient and physically meaningful way as probability distributions Ω(ST)Omega(S_T) over the storage ranked by age STS_T, and 3) changes in transport behavior determined by storage-dependent dilution and flow-path dynamics (as distinct from those due only to changes in the rates and partitioning of water flux) are completely encapsulated by these probability distributions. The framework has been implemented to model to the rich dataset of long-term stream and precipitation chloride from the Plynlimon watershed in Wales, UK. With suitable choices for the functional form of the closure relationships, only a small number of free parameters are required to reproduce the observed chloride dynamics as well as previous models with many more parameters, including reproducing the observed fractal 1/f filtering of the streamflow chloride variability. The modeled transport dynamics are sensitive to the input precipitation variability and water balance partitioning to evapotranspiration. Apparent storage-dependent age

  2. 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

  3. 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.

  4. Three-dimensional prediction of soil physical, chemical, and hydrological properties in a forested catchment of the Santa Catalina CZO

    NASA Astrophysics Data System (ADS)

    Shepard, C.; Holleran, M.; Lybrand, R. A.; Rasmussen, C.

    2014-12-01

    in each cluster calculated. Mass-preserving splines combined with stepwise regressions are an effective tool for predicting soil physical, chemical, and hydrological properties with depth, enhancing our understanding of the critical zone.

  5. 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.

  6. 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.

  7. Testing a distributed hydrological model to predict scenarios of extreme events on a marginal olive orchard microcatchment

    NASA Astrophysics Data System (ADS)

    Guzmán, Enrique; Aguilar, Cristina; Taguas, Encarnación V.

    2014-05-01

    Olive groves constitute a traditional Mediterranean crop and thus, an important source of income to these regions and a crucial landscape component. Despite its importance, most of the olive groves in the region of Andalusia, Southern Spain, are located in sloping areas, which implies a significant risk of erosion. The combination of data and models allow enhancing the knowledge about processes taking place in these areas as well as the prediction of future scenarios. This aspect might be essential to plan soil protection strategies within a context of climate change where the IPCC estimates a significant increase of soil aridity and torrential events by the end of the century. The objective of this study is to estimate the rainfall-runoff-sediment dynamics in a microcatchment olive grove with the aid of a physically-based distributed hydrological model in order to evaluate the effect of extreme events on runoff and erosion. This study will allow to improve land-use and management planning activities in similar areas. In addition, the scale of the study (microcatchment) will allow to contrast the results in larger areas such as catchment regional spatial scales.

  8. 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.

  9. Advances and computational tools towards predictable design in biological engineering.

    PubMed

    Pasotti, Lorenzo; Zucca, Susanna

    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.

  10. Hydrologic modeling to predict performance of shallow land burial cover designs at the Los Alamos National Laboratory

    SciTech Connect

    Nyhan, J.W.

    1989-03-01

    The water balance relationships of two shallow land burial (SLB) cover configurations were studied using a hydrologic model in a preliminary attempt to design waste disposal site covers for successful long-term closure at Los Alamos. Burial site performance requirements for site closure are first discussed, along with the role of hydrologic models in assessing the dynamics of the hydrology of the SLB cover. The calibration of a hydrologic model using field data from two SLB cover designs is then described, followed by an analysis of long-term climatic model input parameters across Los Alamos National Laboratory. These two calibrated models are then used to evaluate the influence of vegetation, precipitation, and runoff curve number on the design of SLB covers within Los Alamos county. Future directions of field research efforts and subsequent hydrologic modeling activities were recommended in terms of their usefulness for waste management decisions to be made at Los Alamos. 24 refs., 17 figs., 9 tabs.

  11. 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.

  12. 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…

  13. 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…

  14. 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…

  15. Development of pre-processing method for use of meteorological ensemble predictions as input to hydrological models: case study of the Huai River Basin, China

    NASA Astrophysics Data System (ADS)

    Song, W.; Xu, X.; Duan, Q.; van Andel, S. J.; Lobbrecht, A. H.; Solomatine, D. P.

    2012-04-01

    Hydrological models are run with precipitation and other meteorological data as input. With adequate spatial and temporal coverage, observed meteorological data is more reliable and more accurate for hydrological models, conventionally. However, when an early warning with several days ahead needs to be provided (for example for flood forecasts) in many cases Numerical Weather Prediction (NWP) has to be used. Hydro-meteorological forecasters and researchers aim to understand and minimize the forecast uncertainties. This research's focus is on testing existing methods and/or developing new methods to improve the integration between meteorological models and hydrological models. The output of the fixed version of the NCEP GFS meteorological ensemble prediction system for the Huai river basin is used in this research with the lead time of 1 to 15 days. There are a number of pre-processing methods to be tested, such as Quantile-to-Quantile correction methods, Analog methods, and Logistic regression. Apart from a single method, a multi-methods system could be developed as well - employing BMA, ANN or other model combinational algorithms. Furthermore, the processed ensemble meteorological data can be fed into hydrological models to generate ensemble discharge forecasts. Performance of this approach is tested by comparing its output with ensemble discharge forecasts on the basis of the raw meteorological ensemble forecast input.

  16. 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.

  17. 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.

  18. 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...

  19. 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.

  20. 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

  1. 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.

  2. 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.

  3. Predicting foraging wading bird populations in Everglades National Park from seasonal hydrologic statistics under different management scenarios

    NASA Astrophysics Data System (ADS)

    Kwon, Hyun-Han; Lall, Upmanu; Engel, Vic

    2011-09-01

    The ability to map relationships between ecological outcomes and hydrologic conditions in the Everglades National Park (ENP) is a key building block for their restoration program, a primary goal of which is to improve conditions for wading birds. This paper presents a model linking wading bird foraging numbers to hydrologic conditions in the ENP. Seasonal hydrologic statistics derived from a single water level recorder are well correlated with water depths throughout most areas of the ENP, and are effective as predictors of wading bird numbers when using a nonlinear hierarchical Bayesian model to estimate the conditional distribution of bird populations. Model parameters are estimated using a Markov chain Monte Carlo (MCMC) procedure. Parameter and model uncertainty is assessed as a byproduct of the estimation process. Water depths at the beginning of the nesting season, the average dry season water level, and the numbers of reversals from the dry season recession are identified as significant predictors, consistent with the hydrologic conditions considered important in the production and concentration of prey organisms in this system. Long-term hydrologic records at the index location allow for a retrospective analysis (1952-2006) of foraging bird numbers showing low frequency oscillations in response to decadal fluctuations in hydroclimatic conditions. Simulations of water levels at the index location used in the Bayesian model under alternative water management scenarios allow the posterior probability distributions of the number of foraging birds to be compared, thus providing a mechanism for linking management schemes to seasonal rainfall forecasts.

  4. 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.

  5. 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.

  6. Incorporating Satellite Remote Sensing Data into Hydrologic Models: Towards Improved Performance in Modeling the Past and Reduced Uncertainty in Predicting the Future

    NASA Astrophysics Data System (ADS)

    Parr, D.; Wang, G.

    2014-12-01

    In many regions of the worlds, studies of past hydrological variability have to rely on hydrological models either because river gauge measurement is not available or because measurements do not reflect the natural flow due to water diversion or reservoir regulation. However, results from these studies are subject to major uncertainty related to the challenges in quantifying vegetation conditions and evapotranspiration, both of which are important for surface water and energy budgets. This study incorporates satellite remote sensing data for ET and vegetation into the VIC model to improve the model performance in simulating the surface water budget, hydrological seasonality, and timing of hydrological extremes. Using the Connecticut River Basin as an example, and driven with the NASA NLDAS-2 meteorological forcing data, the VIC model has been modified to read in LAI and ET data derived from MODIS among others. The MODIS LAI data provides VIC with the inter-annually varying seasonal cycle of vegetation, and the MODIS ET data replaces the model simulated ET. The data-enhanced model performs significantly better in simulating river discharge, its magnitude, seasonality, timing, soil moisture and its temporal variation. Incorporation of the ET data led to an increase of stream flow correlations between model and observations on the daily and biweekly temporal scales, and the seasonality is better represented on a monthly scale with particular magnitude improvements during the summer when ET is greatest. Incorporation of the LAI data led to improved simulation of inter-annual variability. This joint application of remote sensing and modeling helps quantify the extent to which remote sensing data improves model performance, facilitates a more accurate understanding and attribution of past hydrological variability/changes, and helps characterize the range of model-related uncertainties in future predictions.

  7. Examining the Role Played by Meteorological Ensemble Forecasts, Ensemble Kalman Filter Streamflow Assimilation, and Multiple Hydrological Models within a Prediction System Accounting for Three Sources of Uncertainty

    NASA Astrophysics Data System (ADS)

    Anctil, F.; Thiboult, A.; Boucher, M. A.

    2015-12-01

    Building a hydrological ensemble prediction system (H-EPS) from an operational deterministic one may look like an easy task. Indeed, one has only to issue many forecasts at each time step instead of a single one. The problem gets much more complicated when that same person seeks the predictive distribution to be interpretable (reliable). This presentation examine the role played by meteorological ensemble forecasts (meteorological uncertainty), Ensemble Kalman Filter (EnKF) streamflow assimilation (initial conditions uncertainty), and multiple hydrological models (structural uncertainty), combined in a nearly reliable H-EPS. The EnKF is shown to contribute largely to the ensemble accuracy and dispersion, indicating that the initial condition uncertainty is dominant. However, it fails to maintain the required dispersion throughout the entire forecast horizon and needs to be supported by a multimodel approach to take into account structural uncertainty. Moreover, the multimodel approach contributes to improve the general forecasting performance and prevents from falling into the model selection pitfall since models differ strongly in their ability. Finally, the use of probabilistic meteorological forcing was found to contribute mostly to long lead time reliability. The H-EPS was implemented on 38 catchments (Québec, Canada) characterized by a dominant spring freshet and tested for 9-day ahead forecasts over a 2-year period. Twenty lumped hydrological models, chosen for their structural and conceptual diversity, were available to the project as well as ECMWF probabilistic meteorological weather forecasts.

  8. 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

  9. 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

  10. Advance prediction of hypotension at cesarean delivery under spinal anesthesia.

    PubMed

    Kinsella, S M; Norris, M C

    1996-01-01

    Cardiovascular responses to supine inferior vena cava compression might predict hypotension risk during elective cesarean delivery using spinal anesthesia. In this pilot study we investigated 27 women before operation by taking blood pressure and heart rate measurements for 5 min in the left lateral position, 5 min supine, and then performed one further reading in the left lateral position and one sitting. Anesthesia with hyperbaric bupivacaine was rigorously standardised. A pre-operative 'supine stress test', combining an increase in maternal heart rate of greater than 10 beats/min or leg flexion movements while supine, was analysed. A positive supine stress test (SST) was 4.1 times more frequent in those with severe systolic hypotension below 70% of baseline (12 out of 16 women) than in those without (2 out of 11 women), with a sensitivity of 75% (95% C.I. 48% to 93%) and specificity of 82% (95% C.I. 48% to 98%). A positive test was associated with twice as much vasopressor use as a negative test (30.7 +/-/14.5 mg versus 13.5 +/-/ 9.9 mg; P = 0.0014). Unlike the SST, cardiovascular responses to the change from recumbent to sitting (tilt test) were not useful as a predictor of hypotension.

  11. Advance prediction of hypotension at cesarean delivery under spinal anesthesia.

    PubMed

    Kinsella, S M; Norris, M C

    1996-01-01

    Cardiovascular responses to supine inferior vena cava compression might predict hypotension risk during elective cesarean delivery using spinal anesthesia. In this pilot study we investigated 27 women before operation by taking blood pressure and heart rate measurements for 5 min in the left lateral position, 5 min supine, and then performed one further reading in the left lateral position and one sitting. Anesthesia with hyperbaric bupivacaine was rigorously standardised. A pre-operative 'supine stress test', combining an increase in maternal heart rate of greater than 10 beats/min or leg flexion movements while supine, was analysed. A positive supine stress test (SST) was 4.1 times more frequent in those with severe systolic hypotension below 70% of baseline (12 out of 16 women) than in those without (2 out of 11 women), with a sensitivity of 75% (95% C.I. 48% to 93%) and specificity of 82% (95% C.I. 48% to 98%). A positive test was associated with twice as much vasopressor use as a negative test (30.7 +/-/14.5 mg versus 13.5 +/-/ 9.9 mg; P = 0.0014). Unlike the SST, cardiovascular responses to the change from recumbent to sitting (tilt test) were not useful as a predictor of hypotension. PMID:15321375

  12. Integration of small run-of-river and solar power: The hydrological regime prediction/assessment accuracy

    NASA Astrophysics Data System (ADS)

    Francois, Baptiste; Creutin, Jean-Dominique; Hingray, Benoit; Zoccatelli, Davide

    2014-05-01

    The possibility to achieved a high integration of climate related energies (i.e. run-of-river-, wind- and solar- energies) depends on the possibility to balance the potentially large deviations between the related intermittent productions and the variable demand using storage facilities such as water storage in accumulation dams. These deviations depend obviously on how energy sources co-fluctuate in time among themselves and with the demand as well. Balancing hydropower system design as well as their operational planning requires the estimation of these co-fluctuations, resulting from both, space and time weather structures/patterns and watershed features (e.g. area, altitude range, geological basement …). The co-fluctuations between intermittent energy sources can be estimated from observed time series when available or from time series obtained from simulation models when not or when different contexts have to be considered (e.g. climate change and/or intermittent energy development). The simulation models were classically developed and evaluated for the prediction of each energy source individually. The ability of the models to simulate relevant levels of co-fluctuations is however to our knowledge not really considered. This issue is however critical and should also require thorough attention. This work focuses on run-of-river and solar- power interaction assessment. The study area is located in Italy where run-of-river power plants, mainly located on small river tributaries, represent almost 43 % of the hydropower production with only 27 % of the installed hydro-capacity (in 2011). Solar power generation is available from observed time series at different locations over the region but there is no systematic measurement of water discharges over the considered river tributaries and discharges have to be reconstituted from simulations. The absence of discharge measures makes also impossible to calibrate hydrological model at each power plant location. We thus

  13. A Pilot Cyberinfrastructure for Hydrology Cyberlearning

    NASA Astrophysics Data System (ADS)

    Ruddell, Benjamin; Merwade, Venkatesh; Wagener, Thorsten

    2010-05-01

    The geoscience educational agenda in hydrology involves teaching the description, explanation, and prediction of the occurrence, distribution and movement of water in nature. Hydrology is conventionally taught on a chalkboard using the fundamental physical laws of mass, momentum and energy. However, the connections between theoretical concepts are easier to understand when the cause-effect relationships are demonstrated through visual experimentation with models and real-world data. The last decade has produced a revolution in the availability of observational data, hydrological models, and the geoinformatic software necessary to process complex datasets. These advances can bring into the classroom the exploratory modeling and data analysis methods that were once available only to specialists. Unfortunately, several practical problems have prevented the widespread adoption of the latest data analysis and modeling tools for hydrology education by teachers and researchers. These include steep technology learning curves (specialized curricula written by experts are needed for software training), rapid technology turnover (curricula must be updated very frequently, making it difficult for educators to keep current), and the lack of an organized community cyberinfrastructure for the dissemination and publication of the latest tools and curricula (causing duplication of effort by educators, and limiting the adoption of technology). Our objective is to dramatically increase the incorporation of exploratory data analysis and modeling tools within the hydrology and geoscience education classroom, beginning in the University, and moving toward primary and secondary education applications. We developing a cyberinfrastructure to support open community development and dissemination of a data-driven curriculum for hydrology and the geosciences. A modular pilot curriculum is being developed to teach data access, analysis, and modeling and visualization using case studies for

  14. 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

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  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. 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.

  7. The Potential Response of Aquatic Biodiversity in the Midwestern United States to Predicted Changes in Climate Based On Output From Landscape Scale Hydrologic Models

    NASA Astrophysics Data System (ADS)

    Knouft, J.; Chien, H.

    2012-12-01

    North America contains the highest diversity of temperate aquatic species on Earth. However, aquatic ecosystems, particularly rivers and streams, are experiencing a variety of anthropogenic impacts, including the ongoing effects of changes in climate. Unfortunately, our understanding of the potential responses of aquatic taxa to variation in climate is limited, particularly across broad geographic regions. At the landscape scale, the interactions of climate and landuse/landcover can have significant impacts on the hydrologic characteristics of aquatic ecosystems, which should have a direct influence on the distribution and persistence of aquatic species. Consequently, the ability to predict spatial variation in streamflow at landscape scales is essential to understanding the potential impacts of changes in climate on these ecosystems in the coming century. The goal of this study is to assess the potential impacts of climate change on streamflow in watersheds located in the Midwestern United States, primarily in Illinois. In-stream hydrologic data are then integrated with species distribution data (fishes, crayfishes, and mussels) and an ecological niche modeling algorithm to predict the potential impact of changes in streamflow on species distributions. A distributed hydrologic model, the Soil and Water Assessment Tool (SWAT), was calibrated and validated using a multi-gauge landscape-scale approach. The potential impacts of climate changes on water resources were assessed through the validated SWAT model, which includes weather data predictions from a variety of global climate models (GCM). Predictions based on future climate scenarios generally indicate that total annual streamflow will decrease in the future compared with recent streamflow (1991-1999). Seasonal streamflow patterns in the future are predicted to change in terms of increased streamflow in the winter but decreased streamflow in the summer, yet intra-annual variability in streamflow will tend to

  8. 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

  9. Application of a GIS-based distributed hydrology model for prediction of forest harvest effects on peak stream flow in the Pacific Northwest

    NASA Astrophysics Data System (ADS)

    Storck, Pascal; Bowling, Laura; Wetherbee, Paul; Lettenmaier, Dennis

    1998-05-01

    Spatially distributed rainfall-runoff models, made feasible by the widespread availability of land surface characteristics data (especially digital topography), and the evolution of high power desktop workstations, are particularly useful for assessment of the hydrological effects of land surface change. Three examples are provided of the use of the Distributed Hydrology-Soil-Vegetation Model (DHSVM) to assess the hydrological effects of logging in the Pacific Northwest. DHSVM provides a dynamic representation of the spatial distribution of soil moisture, snow cover, evapotranspiration and runoff production, at the scale of digital topographic data (typically 30-100 m). Among the hydrological concerns that have been raised related to forest harvest in the Pacific Northwest are increases in flood peaks owing to enhanced rain-on-snow and spring radiation melt response, and the effects of forest roads. The first example is for two rain-on-snow floods in the North Fork Snoqualmie River during November 1990 and December 1989. Predicted maximum vegetation sensitivities (the difference between predicted peaks for all mature vegetation compared with all clear-cut) showed a 31% increase in the peak runoff for the 1989 event and a 10% increase for the larger 1990 event. The main reason for the difference in response can be traced to less antecedent low elevation snow during the 1990 event. The second example is spring snowmelt runoff for the Little Naches River, Washington, which drains the east slopes of the Washington Cascades. Analysis of spring snowmelt peak runoff during May 1993 and April 1994 showed that, for current vegetation relative to all mature vegetation, increases in peak spring stream flow of only about 3% should have occurred over the entire basin. However, much larger increases (up to 30%) would occur for a maximum possible harvest scenario, and in a small headwaters catchment, whose higher elevation leads to greater snow coverage (and, hence, sensitivity

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

    PubMed Central

    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

    2016-01-01

    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. PMID:27527370

  11. The Experimental Hydrology Wiki

    NASA Astrophysics Data System (ADS)

    Blume, Theresa; van Meerveld, Ilja; Graeff, Thomas

    2013-04-01

    The "Experimental Hydrology Wiki" is a forum for hydrologists to learn about, recommend, question and discuss new and established, basic and advanced methods and equipment for hydrological research. As a database of "lessons learned" it does not only contain short descriptions of specific experimental equipment but also information on encountered errors and problems and recommendations on how to deal with them. This makes valuable personal field experience accessible to a wider audience. The Wiki allows experimentalists to share and find solutions for common problems and thus helps us in not making the same mistakes others have made before us. At the same time modellers can use this platform to find information on sources of error and uncertainty in the data they use for model validation and calibration. The general idea and layout of the Experimental Hydrology Wiki is presented here along with an invitation to all experimental hydrologists to contribute their knowledge and experiences! http://www.experimental- hydrology.net/

  12. Influence of simulation time-step (temporal-scale) on optimal parameter estimation and runoff prediction performance in hydrological modeling

    NASA Astrophysics Data System (ADS)

    Loizu, Javier; Álvarez-Mozos, Jesús; Casalí, Javier; Goñi, Mikel

    2015-04-01

    Nowadays, most hydrological catchment models are designed to allow their use for streamflow simulation at different time-scales. While this permits models to be applied for broader purposes, it can also be a source of error in hydrological processes simulation at catchment scale. Those errors seem not to affect significantly simple conceptual models, but this flexibility may lead to large behavior errors in physically based models. Equations used in processes such as those related to soil moisture time-variation are usually representative at certain time-scales but they may not characterize properly water transfer in soil layers at larger scales. This effect is especially relevant as we move from detailed hourly scale to daily time-step, which are common time scales used at catchment streamflow simulation for different research and management practices purposes. This study aims to provide an objective methodology to identify the degree of similarity of optimal parameter values when hydrological catchment model calibration is developed at different time-scales. Thus, providing information for an informed discussion of physical parameter significance on hydrological models. In this research, we analyze the influence of time scale simulation on: 1) the optimal values of six highly sensitive parameters of the TOPLATS model and 2) the streamflow simulation efficiency, while optimization is carried out at different time scales. TOPLATS (TOPMODEL-based Land-Atmosphere Transfer Scheme) has been applied on its lumped version on three catchments of varying size located in northern Spain. The model has its basis on shallow groundwater gradients (related to local topography) that set up spatial patterns of soil moisture and are assumed to control infiltration and runoff during storm events and evaporation and drainage in between storm events. The model calculates the saturated portion of the catchment at each time step based on Topographical Index (TI) intervals. Surface

  13. Computational methods in the prediction of advanced subsonic and supersonic propeller induced noise: ASSPIN users' manual

    NASA Technical Reports Server (NTRS)

    Dunn, M. H.; Tarkenton, G. M.

    1992-01-01

    This document describes the computational aspects of propeller noise prediction in the time domain and the use of high speed propeller noise prediction program ASSPIN (Advanced Subsonic and Supersonic Propeller Induced Noise). These formulations are valid in both the near and far fields. Two formulations are utilized by ASSPIN: (1) one is used for subsonic portions of the propeller blade; and (2) the second is used for transonic and supersonic regions on the blade. Switching between the two formulations is done automatically. ASSPIN incorporates advanced blade geometry and surface pressure modelling, adaptive observer time grid strategies, and contains enhanced numerical algorithms that result in reduced computational time. In addition, the ability to treat the nonaxial inflow case has been included.

  14. 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.

  15. 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.

  16. Measured and predicted rotor performance for the SERI advanced wind turbine blades

    NASA Astrophysics Data System (ADS)

    Tangler, J.; Smith, B.; Kelley, N.; Jager, D.

    1992-02-01

    Measured and predicted rotor performance for the Solar Energy Research Institute (SERI) advanced wind turbine blades were compared to assess the accuracy of predictions and to identify the sources of error affecting both predictions and measurements. An awareness of these sources of error contributes to improved prediction and measurement methods that will ultimately benefit future rotor design efforts. Propeller/vane anemometers were found to underestimate the wind speed in turbulent environments such as the San Gorgonio Pass wind farm area. Using sonic or cup anemometers, good agreement was achieved between predicted and measured power output for wind speeds up to 8 m/sec. At higher wind speeds an optimistic predicted power output and the occurrence of peak power at wind speeds lower than measurements resulted from the omission of turbulence and yaw error. In addition, accurate two-dimensional (2-D) airfoil data prior to stall and a post stall airfoil data synthesization method that reflects three-dimensional (3-D) effects were found to be essential for accurate performance prediction.

  17. Comparison of Advection–Diffusion Models and Neural Networks for Prediction of Advanced Water Treatment Effluent

    PubMed Central

    Mortula, Mohammed Maruf; Abdalla, Jamal; Ghadban, Ahmad A.

    2012-01-01

    Abstract An artificial neural network (ANN) can help in the prediction of advanced water treatment effluent and thus facilitate design practices. In this study, sets of 225 experimental data were obtained from a wastewater treatment process for the removal of phosphorus using oven-dried alum residuals in fixed-bed adsorbers. Five input variables (pH, initial phosphorus concentration, wastewater flow rate, porosity, and time) were used to test the efficiency of phosphorus removal at different times, and ANNs were then used to predict the effluent phosphorus concentration. Results of experiments that were conducted for different values of the input parameters made up the data used to train and test a multilayer perceptron using the back-propagation algorithm of the ANN. Values predicted by the ANN and the experimentally measured values were compared, and the accuracy of the ANN was evaluated. When ANN results were compared to the experimental results, it was concluded that the ANN results were accurate, especially during conditions of high phosphorus concentration. While the ANN model was able to predict the breakthrough point with good accuracy, the conventional advection–diffusion equation was not as accurate. A parametric study conducted to examine the effect of the initial pH and initial phosphorus concentration on the effluent phosphorus concentration at different times showed that lower influent pH values are the most suitable for this advanced treatment system. PMID:22783063

  18. Verification of precipitation forecasts from two numerical weather prediction models in the Middle Atlantic Region of the USA: A precursory analysis to hydrologic forecasting

    NASA Astrophysics Data System (ADS)

    Siddique, Ridwan; Mejia, Alfonso; Brown, James; Reed, Seann; Ahnert, Peter

    2015-10-01

    Accurate precipitation forecasts are required for accurate flood forecasting. The structures of different precipitation forecasting systems are constantly evolving, with improvements in forecasting techniques, increases in spatial and temporal resolution, improvements in model physics and numerical techniques, and better understanding of, and accounting for, predictive uncertainty. Hence, routine verification is necessary to understand the quality of forecasts as inputs to hydrologic modeling. In this study, we verify precipitation forecasts from the National Centers for Environmental Prediction (NCEP) 11-member Global Ensemble Forecast System Reforecast version 2 (GEFSRv2), as well as the 21-member Short Range Ensemble Forecast (SREF) system. Specifically, basin averaged precipitation forecasts are verified for different basin sizes (spatial scales) in the operating domain of the Middle Atlantic River Forecast Center (MARFC), using multi-sensor precipitation estimates (MPEs) as the observed data. The quality of the ensemble forecasts is evaluated conditionally upon precipitation amounts, forecast lead times, accumulation periods, and seasonality using different verification metrics. Overall, both GEFSRv2 and SREF tend to overforecast light to moderate precipitation and underforecast heavy precipitation. In addition, precipitation forecasts from both systems become increasingly reliable with increasing basin size and decreasing precipitation threshold, and the 24-hourly forecasts show slightly better skill than the 6-hourly forecasts. Both systems show a strong seasonal trend, characterized by better skill during the cool season than the warm season. Ultimately, the verification results lead to guidance on the expected quality of the precipitation forecasts, together with an assessment of their relative quality and unique information content, which is useful and necessary for their application in hydrologic forecasting.

  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. 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.

  1. 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.

  2. Sexual selection predicts advancement of avian spring migration in response to climate change

    PubMed Central

    Spottiswoode, Claire N; Tøttrup, Anders P; Coppack, Timothy

    2006-01-01

    Global warming has led to earlier spring arrival of migratory birds, but the extent of this advancement varies greatly among species, and it remains uncertain to what degree these changes are phenotypically plastic responses or microevolutionary adaptations to changing environmental conditions. We suggest that sexual selection could help to understand this variation, since early spring arrival of males is favoured by female choice. Climate change could weaken the strength of natural selection opposing sexual selection for early migration, which would predict greatest advancement in species with stronger female choice. We test this hypothesis comparatively by investigating the degree of long-term change in spring passage at two ringing stations in northern Europe in relation to a synthetic estimate of the strength of female choice, composed of degree of extra-pair paternity, relative testes size and degree of sexually dichromatic plumage colouration. We found that species with a stronger index of sexual selection have indeed advanced their date of spring passage to a greater extent. This relationship was stronger for the changes in the median passage date of the whole population than for changes in the timing of first-arriving individuals, suggesting that selection has not only acted on protandrous males. These results suggest that sexual selection may have an impact on the responses of organisms to climate change, and knowledge of a species' mating system might help to inform attempts at predicting these. PMID:17015341

  3. 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

  4. 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

  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. Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

    PubMed Central

    Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

    2015-01-01

    Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC. PMID:26420960

  7. 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. PMID:22299108

  8. Predictive biomarkers of sorafenib efficacy in advanced hepatocellular carcinoma: Are we getting there?

    PubMed

    Shao, Yu-Yun; Hsu, Chih-Hung; Cheng, Ann-Lii

    2015-09-28

    Sorafenib is the current standard treatment for advanced hepatocellular carcinoma (HCC), but its efficacy is modest with low response rates and short response duration. Predictive biomarkers for sorafenib efficacy are necessary. However, efforts to determine biomarkers for sorafenib have led only to potential candidates rather than clinically useful predictors. Studies based on patient cohorts identified the potential of blood levels of angiopoietin-2, hepatocyte growth factor, insulin-like growth factor-1, and transforming growth factor-β1 for predicting sorafenib efficacy. Alpha-fetoprotein response, dynamic contrast-enhanced magnetic resonance imaging, and treatment-related side effects may serve as early surrogate markers. Novel approaches based on super-responders or experimental mouse models may provide new directions in biomarker research. These studies identified tumor amplification of FGF3/FGF4 or VEGFA and tumor expression of phospho-Mapk14 and phospho-Atf2 as possible predictive markers that await validation. A group effort that considers various prognostic factors and proper collection of tumor tissues before treatment is imperative for the success of future biomarker research in advanced HCC.

  9. 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.

  10. 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

  11. Simulation studies of the impact of advanced observing systems on numerical weather prediction

    NASA Technical Reports Server (NTRS)

    Atlas, R.; Kalnay, E.; Susskind, J.; Reuter, D.; Baker, W. E.; Halem, M.

    1984-01-01

    To study the potential impact of advanced passive sounders and lidar temperature, pressure, humidity, and wind observing systems on large-scale numerical weather prediction, a series of realistic simulation studies between the European Center for medium-range weather forecasts, the National Meteorological Center, and the Goddard Laboratory for Atmospheric Sciences is conducted. The project attempts to avoid the unrealistic character of earlier simulation studies. The previous simulation studies and real-data impact tests are reviewed and the design of the current simulation system is described. Consideration is given to the simulation of observations of space-based sounding systems.

  12. Snow and Glacier Hydrology

    NASA Astrophysics Data System (ADS)

    Brubaker, Kaye

    The study of snow and ice is rich in both fundamental science and practical applications. Snow and Glacier Hydrology offers something for everyone, from resource practitioners in regions where water supply depends on seasonal snow pack or glaciers, to research scientists seeking to understand the role of the solid phase in the water cycle and climate. The book is aimed at the advanced undergraduate or graduate-level student. A perusal of online documentation for snow hydrology classes suggests that there is currently no single text or reference book on this topic in general use. Instructors rely on chapters from general hydrology texts or operational manuals, collections of journal papers, or their own notes. This variety reflects the fact that snow and ice regions differ in climate, topography, language, water law, hazards, and resource use (hydropower, irrigation, recreation). Given this diversity, producing a universally applicable book is a challenge.

  13. Hydrological minimal model for fire regime assessment in Mediterranean ecosystem

    NASA Astrophysics Data System (ADS)

    Ursino, N.; Rulli, M. C.

    2012-04-01

    A new model for Mediterranean forest fire regime assessment is presented and discussed. The model is based on the experimental evidence that fire is due to both hydrological and ecological processes and the relative role of fuel load versus fuel moisture is an important driver in fire ecology. Diverse scenarios are analyzed where either the hydrological forcing or the feedback between fire and hydrological characterization of the site is changed. The model outcome demonstrates that the two way interaction between hydrological processes, biology and fire regime drives the ecosystem toward a typical fire regime that may be altered either by an evolution of the biological characterization of the site or by a change of the hydrological forcing. This tenet implies that not every fire regime is compatible with the ecohydrological characterization of the site under study. This means that natural (non antropogenic) fire cannot be modeled as an arbitrary external forcing because the coupled hydrological and biological processes determines its statistical characterization, and conversely, the fire regime affects the soil moisture availability and the outcome of different species competition under possible water stress. The new modelling approach presented here, when provided by a proper model parameterization, can advance the capability in predicting and managing fires in ecosystems influenced by climate and land use changes.

  14. A proposed predictive model for advanced fibrosis in patients with chronic hepatitis B and its validation.

    PubMed

    Nishikawa, Hiroki; Hasegawa, Kunihiro; Ishii, Akio; Takata, Ryo; Enomoto, Hirayuki; Yoh, Kazunori; Kishino, Kyohei; Shimono, Yoshihiro; Iwata, Yoshinori; Nakano, Chikage; Nishimura, Takashi; Aizawa, Nobuhiro; Sakai, Yoshiyuki; Ikeda, Naoto; Takashima, Tomoyuki; Iijima, Hiroko; Nishiguchi, Shuhei

    2016-08-01

    We created a predictive model using serum-based biomarkers for advanced fibrosis (F3 or more) in patients with chronic hepatitis B (CHB) and to confirm the accuracy in an independent cohort.A total of 249 CHB patients were analyzed. To achieve our study aim, a training group (n = 125) and a validation group (n = 124) were formed. In the training group, parameters related to the presence of advanced fibrosis in univariate and multivariate analyses were examined, and a formula for advanced fibrosis was created. Next, we verified the applicability of the predictive model in the validation group.Multivariate analysis identified that gamma-glutamyl transpeptidase (GGT, P = 0.0343) and platelet count (P = 0.0034) were significant predictors of the presence of advanced fibrosis, while Wisteria floribunda agglutinin-positive Mac-2-binding protein (WFA-M2BP, P = 0.0741) and hyaluronic acid (P = 0.0916) tended to be significant factors. Using these 4 parameters, we created the following formula: GMPH score = -0.755 - (0.015 × GGT) - (0.268 × WFA-M2BP) + (0.167 × platelet count) + (0.003 × hyaluronic acid). In 8 analyzed variables (WFA-M2BP, aspartate aminotransferase-to-platelet ratio index, FIB-4 index, prothrombin time, platelet count, hyaluronic acid, Forns index, and GMPH score), GMPH score had the highest area under the receiver operating characteristic (AUROC) curve for advanced fibrosis with a value of 0.8064 in the training group and in the validation group, GMPH score also had the highest AUROC (0.7782). In all subgroup analyses of the hepatitis B virus (HBV) status (HB surface antigen quantification, HBV-DNA quantification, and HBe antigen seropositivity), GMPH score in F3 or F4 was significantly lower than that in F0 to F2. In the above mentioned 8 variables, differences between the liver fibrosis stages (F0 to F1 vs F2, F2 vs F3, F3 vs F4, F0 to F1 vs F3, F0 to F1 vs F4, and F2 vs F4) for the entire

  15. A proposed predictive model for advanced fibrosis in patients with chronic hepatitis B and its validation

    PubMed Central

    Nishikawa, Hiroki; Hasegawa, Kunihiro; Ishii, Akio; Takata, Ryo; Enomoto, Hirayuki; Yoh, Kazunori; Kishino, Kyohei; Shimono, Yoshihiro; Iwata, Yoshinori; Nakano, Chikage; Nishimura, Takashi; Aizawa, Nobuhiro; Sakai, Yoshiyuki; Ikeda, Naoto; Takashima, Tomoyuki; Iijima, Hiroko; Nishiguchi, Shuhei

    2016-01-01

    Abstract We created a predictive model using serum-based biomarkers for advanced fibrosis (F3 or more) in patients with chronic hepatitis B (CHB) and to confirm the accuracy in an independent cohort. A total of 249 CHB patients were analyzed. To achieve our study aim, a training group (n = 125) and a validation group (n = 124) were formed. In the training group, parameters related to the presence of advanced fibrosis in univariate and multivariate analyses were examined, and a formula for advanced fibrosis was created. Next, we verified the applicability of the predictive model in the validation group. Multivariate analysis identified that gamma-glutamyl transpeptidase (GGT, P = 0.0343) and platelet count (P = 0.0034) were significant predictors of the presence of advanced fibrosis, while Wisteria floribunda agglutinin-positive Mac-2-binding protein (WFA+-M2BP, P = 0.0741) and hyaluronic acid (P = 0.0916) tended to be significant factors. Using these 4 parameters, we created the following formula: GMPH score = −0.755 − (0.015 × GGT) − (0.268 × WFA+-M2BP) + (0.167 × platelet count) + (0.003 × hyaluronic acid). In 8 analyzed variables (WFA+-M2BP, aspartate aminotransferase-to-platelet ratio index, FIB-4 index, prothrombin time, platelet count, hyaluronic acid, Forns index, and GMPH score), GMPH score had the highest area under the receiver operating characteristic (AUROC) curve for advanced fibrosis with a value of 0.8064 in the training group and in the validation group, GMPH score also had the highest AUROC (0.7782). In all subgroup analyses of the hepatitis B virus (HBV) status (HB surface antigen quantification, HBV-DNA quantification, and HBe antigen seropositivity), GMPH score in F3 or F4 was significantly lower than that in F0 to F2. In the above mentioned 8 variables, differences between the liver fibrosis stages (F0 to F1 vs F2, F2 vs F3, F3 vs F4, F0 to F1 vs F3, F0 to F1 vs F4, and F2 vs

  16. 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.

  17. Predictive and preventive strategies to advance the treatments of cardiovascular and cerebrovascular diseases: the Ukrainian context

    PubMed Central

    2012-01-01

    Despite great efforts in treatments of cardiovascular diseases, the field requires innovative strategies because of high rates of morbidity, mortality and disability, indicating evident deficits in predictive vascular diagnosis and individualized treatment approaches. Talking about the vascular system, currently, physicians are not provided with integrated medical approaches to diagnose and treat vascular diseases. Only an individual global approach to the analysis of all segments in the vascular system of a patient allows finding the optimal way for vascular disease treatment. As for the existing methodology, there is a dominance of static methods such as X-ray contrast angiography and magnetic resonance imaging in angiomode. Taking into account the world experience, this article deals with innovative strategies, aiming at predictive diagnosis in vascular system, personalization of the biomedical treatment approaches, and targeted prevention of individual patient cohorts. Clinical examples illustrate the advances in corresponding healthcare sectors. Recommendations are provided to promote the field. PMID:23083430

  18. 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.

  19. 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

  20. Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

    NASA Astrophysics Data System (ADS)

    Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

    2015-12-01

    Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we

  1. Snow depth estimation, structure, prediction, and hydrologic modeling at the kilometer scale in the Colorado Rocky Mountains

    NASA Astrophysics Data System (ADS)

    McCreight, James L.

    Research focuses on observing and predicting spatial distribution of snow depth at the kilometer scale. Observation of spatial snow depth distribution is considered by its estimation from random, sparse observations and important factors affecting this estimation. Predicting spatial distribution of both snow depth and melt rates begins from simple hypothesis wherein the spatial distribution of snow depth is structured by the spatial distribution of controlling variables. Predictions made by this structured view are evaluated in spatial modeling of peak-accumulation snow depth and applied to spatial distribution of a point-scale, temperature-index model of snowmelt runoff using minimal parameter complexity. High-resolution light detection and ranging (LiDAR) measurements provide a rich backdrop for understanding estimation from sparse observations and developing our structured view of snow distribution. The data are used to illuminate the effects of sample size on estimation skill, the uncertainty in estimation due to random sampling, the effect of model resolution on estimation skill, and the difference between cross-validated skill and skill based on the entire distribution. None of these topics have previously been explored in the literature. The effect of predictor quality is also investigated. LiDAR derived predictors are compared to readily available predictors downloaded from the internet. Hierarchical cluster analysis is used to decompose spatial non-stationarity of snow depth and results match qualitative understanding of the spatial distribution of physical controls. The same methodology is then used to decompose spatial non-stationarity of physical controls and infer patterns of snow depth distribution independent of observations. Even when using readily-available predictors, predicted patterns require at least 100--200 observations to be matched by standard estimation methods. Predicted patterns are then applied to formulate a parameterized spatial

  2. A Model to Predict Nitrogen Losses in Advanced Soil-Based Wastewater Treatment Systems

    NASA Astrophysics Data System (ADS)

    Morales, I.; Cooper, J.; Loomis, G.; Kalen, D.; Amador, J.; Boving, T. B.

    2014-12-01

    Most of the non-point source Nitrogen (N) load in rural areas is attributed to onsite wastewater treatment systems (OWTS). Nitrogen compounds are considered environmental pollutants because they deplete the oxygen availability in water bodies and produce eutrophication. The objective of this study was to simulate the fate and transport of Nitrogen in OWTS. The commercially-available 2D/3D HYDRUS software was used to develop a transport and fate model. Experimental data from a laboratory meso-cosm study included the soil moisture content, NH4 and NO3- data. That data set was used to calibrate the model. Three types of OWTS were simulated: (1) pipe-and-stone (P&S), (2) advanced soil drainfields, pressurized shallow narrow drainfield (SND) and (3) Geomat (GEO), a variation of SND. To better understand the nitrogen removal mechanism and the performance of OWTS technologies, replicate (n = 3) intact soil mesocosms were used with 15N-labelled nitrogen inputs. As a result, it was estimated that N removal by denitrification was predominant in P&S. However, it is suggested that N was removed by nitrification in SND and GEO. The calibrated model was used to estimate Nitrogen fluxes for both conventional and advanced OWTS. Also, the model predicted the N losses from nitrification and denitrification in all OWTS. These findings help to provide practitioners with guidelines to estimate N removal efficiencies for OWTS, and predict N loads and spatial distribution for identifying non-point sources.

  3. Plasma genetic and genomic abnormalities predict treatment response and clinical outcome in advanced prostate cancer

    PubMed Central

    Du, Meijun; Dittmar, Rachel L.; Lee, Adam; Nandy, Debashis; Yuan, Tiezheng; Guo, Yongchen; Wang, Yuan; Tschannen, Michael R.; Worthey, Elizabeth; Jacob, Howard; See, William; Kilari, Deepak; Wang, Xuexia; Hovey, Raymond L.; Huang, Chiang-Ching; Wang, Liang

    2015-01-01

    Liquid biopsies, examinations of tumor components in body fluids, have shown promise for predicting clinical outcomes. To evaluate tumor-associated genomic and genetic variations in plasma cell-free DNA (cfDNA) and their associations with treatment response and overall survival, we applied whole genome and targeted sequencing to examine the plasma cfDNAs derived from 20 patients with advanced prostate cancer. Sequencing-based genomic abnormality analysis revealed locus-specific gains or losses that were common in prostate cancer, such as 8q gains, AR amplifications, PTEN losses and TMPRSS2-ERG fusions. To estimate tumor burden in cfDNA, we developed a Plasma Genomic Abnormality (PGA) score by summing the most significant copy number variations. Cox regression analysis showed that PGA scores were significantly associated with overall survival (p < 0.04). After androgen deprivation therapy or chemotherapy, targeted sequencing showed significant mutational profile changes in genes involved in androgen biosynthesis, AR activation, DNA repair, and chemotherapy resistance. These changes may reflect the dynamic evolution of heterozygous tumor populations in response to these treatments. These results strongly support the feasibility of using non-invasive liquid biopsies as potential tools to study biological mechanisms underlying therapy-specific resistance and to predict disease progression in advanced prostate cancer. PMID:25915538

  4. Can primary optimal cytoreduction be predicted in advanced epithelial ovarian cancer preoperatively?

    PubMed Central

    2010-01-01

    Introduction Prediction of optimal cytoreduction in patients with advanced epithelial ovarian caner preoperatively. Methods Patients with advanced epithelial ovarian cancer who underwent surgery for the first time from Jan. to June 2008 at gynecologic oncology ward of TUMS (Tehran University of Medical Sciences) were eligible for this study. The possibility of predicting primary optimal cytoreduction considering multiple variables was evaluated. Variables were peritoneal carcinomatosis, serum CA125, ascites, pleural effusion, physical status and imaging findings. Univariate comparisons of patients underwent suboptimal cytoreduction carried out using Fisher's exact test for each of the potential predictors. The wilcoxon rank sum test was used to compare variables between patients with optimal versus suboptimal cytoreduction. Results 41 patients met study inclusion criteria. Statistically significant association was noted between peritoneal carcinomatosis and suboptimal cytoreduction. There were no statistically significant differences between physical status, pleural effusion, imaging findings, serum CA125 and ascites of individuals with optimal cytoreduction compared to those with suboptimal cytoreduction. Conclusions Because of small populations in our study the results are not reproducible in alternate populations. Only the patient who is most unlikely to undergo optimal cytoreduction should be offered neoadjuvant chemotherapy, unless her medical condition renders her unsuitable for primary surgery. PMID:20170515

  5. 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.

  6. 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.

  7. 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

  8. 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

  9. 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.

  10. Early Identification of Students Predicted to Enroll in Advanced, Upper-Level High School Courses: An Examination of Validity

    ERIC Educational Resources Information Center

    DeRose, Diego S.; Clement, Russell W.

    2011-01-01

    Broward County Public Schools' Research Services department uses logistic regression analysis to compute an indicator to predict student enrollment in advanced high school courses, for students entering ninth grade for the first time. This prediction indicator, along with other student characteristics, supports high school guidance staffs in…

  11. Advances in Rosetta structure prediction for difficult molecular-replacement problems

    SciTech Connect

    DiMaio, Frank

    2013-11-01

    Modeling advances using Rosetta structure prediction to aid in solving difficult molecular-replacement problems are discussed. Recent work has shown the effectiveness of structure-prediction methods in solving difficult molecular-replacement problems. The Rosetta protein structure modeling suite can aid in the solution of difficult molecular-replacement problems using templates from 15 to 25% sequence identity; Rosetta refinement guided by noisy density has consistently led to solved structures where other methods fail. In this paper, an overview of the use of Rosetta for these difficult molecular-replacement problems is provided and new modeling developments that further improve model quality are described. Several variations to the method are introduced that significantly reduce the time needed to generate a model and the sampling required to improve the starting template. The improvements are benchmarked on a set of nine difficult cases and it is shown that this improved method obtains consistently better models in less running time. Finally, strategies for best using Rosetta to solve difficult molecular-replacement problems are presented and future directions for the role of structure-prediction methods in crystallography are discussed.

  12. 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.

  13. An open framework for hydrological data assimilation

    NASA Astrophysics Data System (ADS)

    Madsen, H.; Ridler, M. E.; Velzen, N. V.; Hummel, S.; Sandholt, I.; Falk, A. K.; Heemink, A.

    2013-12-01

    Accurate and reliable real-time hydrological forecasts are essential for protection against water-related hazards, operation of infrastructure, and water resources management. Recent advances in radar rainfall estimation and forecasting, numerical weather predictions, satellite and in-situ monitoring, and faster computing facilities are opening up new opportunities in real-time hydrological forecasting. More effective use of the different information sources via data assimilation will provide the basis for producing more accurate and more reliable forecasts. In this regard, development and implementation of robust and computationally efficient data assimilation algorithms that are feasible for real-time applications remains one of the key challenges. Thus far, many of the efforts on implementation of data assimilation in hydrological modeling have been model specific. This requires access to as well as an in-depth knowledge of the numerical core of the models. A means to deal with the interaction between model and data assimilation algorithm in a more generic way is the use of the Open Model Interface (OpenMI). This open source standard interface allows models to exchange data during runtime, thus transforming a complex numerical model to a plug and play like component. For data assimilation, the OpenDA data assimilation toolbox is an open interface standard that includes a set of tools, assimilation algorithms, and numerical techniques to quickly implement data assimilation in numerical models. This paper presents a new generic data assimilation framework that uses OpenMI to interface models within OpenDA. This enables the many OpenMI hydrological models already available access to a robust and flexible data assimilation library. A synthetic test case is presented that highlights the potential of this new framework. An ensemble based Kalman filter is demonstrated for assimilation of groundwater levels in the MIKE SHE distributed and integrated hydrological

  14. Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 1: Concepts and methodology

    NASA Astrophysics Data System (ADS)

    Elshorbagy, A.; Corzo, G.; Srinivasulu, S.; Solomatine, D. P.

    2009-11-01

    A comprehensive data driven modeling experiment is presented in two-part paper. In this first part, an extensive data-driven modeling experiment is proposed. The most important concerns regarding the way data driven modeling (DDM) techniques and data were handled, compared, and evaluated, and the basis on which findings and conclusions were drawn are discussed. A concise review of key articles that presented comparisons among various DDM techniques is presented. Six DDM techniques, namely, neural networks, genetic programming, evolutionary polynomial regression, support vector machines, M5 model trees, and K-nearest neighbors are proposed and explained. Multiple linear regression and naïve models are also suggested as baseline for comparison with the various techniques. Five datasets from Canada and Europe representing evapotranspiration, upper and lower layer soil moisture content, and rainfall-runoff process are described and proposed for the modeling experiment. Twelve different realizations (groups) from each dataset are created by a procedure involving random sampling. Each group contains three subsets; training, cross-validation, and testing. Each modeling technique is proposed to be applied to each of the 12 groups of each dataset. This way, both predictive accuracy and uncertainty of the modeling techniques can be evaluated. The implementation of the modeling techniques, results and analysis, and the findings of the modeling experiment are deferred to the second part of this paper.

  15. Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 1: Concepts and methodology

    NASA Astrophysics Data System (ADS)

    Elshorbagy, A.; Corzo, G.; Srinivasulu, S.; Solomatine, D. P.

    2010-10-01

    A comprehensive data driven modeling experiment is presented in a two-part paper. In this first part, an extensive data-driven modeling experiment is proposed. The most important concerns regarding the way data driven modeling (DDM) techniques and data were handled, compared, and evaluated, and the basis on which findings and conclusions were drawn are discussed. A concise review of key articles that presented comparisons among various DDM techniques is presented. Six DDM techniques, namely, neural networks, genetic programming, evolutionary polynomial regression, support vector machines, M5 model trees, and K-nearest neighbors are proposed and explained. Multiple linear regression and naïve models are also suggested as baseline for comparison with the various techniques. Five datasets from Canada and Europe representing evapotranspiration, upper and lower layer soil moisture content, and rainfall-runoff process are described and proposed, in the second paper, for the modeling experiment. Twelve different realizations (groups) from each dataset are created by a procedure involving random sampling. Each group contains three subsets; training, cross-validation, and testing. Each modeling technique is proposed to be applied to each of the 12 groups of each dataset. This way, both prediction accuracy and uncertainty of the modeling techniques can be evaluated. The description of the datasets, the implementation of the modeling techniques, results and analysis, and the findings of the modeling experiment are deferred to the second part of this paper.

  16. 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.

  17. 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

  18. 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.

  19. Prediction of response to preoperative chemoradiotherapy and establishment of individualized therapy in advanced rectal cancer.

    PubMed

    Nakao, Toshihiro; Iwata, Takashi; Hotchi, Masanori; Yoshikawa, Kozo; Higashijima, Jun; Nishi, Masaaki; Takasu, Chie; Eto, Shohei; Teraoku, Hiroki; Shimada, Mitsuo

    2015-10-01

    Preoperative chemoradiotherapy (CRT) has become the standard treatment for patients with locally advanced rectal cancer. However, no specific biomarker has been identified to predict a response to preoperative CRT. The aim of the present study was to assess the gene expression patterns of patients with advanced rectal cancer to predict their responses to preoperative CRT. Fifty-nine rectal cancer patients were subjected to preoperative CRT. Patients were randomly assigned to receive CRT with tegafur/gimeracil/oteracil (S-1 group, n=30) or tegafur-uracil (UFT group, n=29). Gene expression changes were studied with cDNA and miRNA microarray. The association between gene expression and response to CRT was evaluated. cDNA microarray showed that 184 genes were significantly differentially expressed between the responders and the non‑responders in the S-1 group. Comparatively, 193 genes were significantly differentially expressed in the responders in the UFT group. TBX18 upregulation was common to both groups whereas BTNL8, LOC375010, ADH1B, HRASLS2, LOC284232, GCNT3 and ALDH1A2 were significantly differentially lower in both groups when compared with the non-responders. Using miRNA microarray, we found that 7 and 16 genes were significantly differentially expressed between the responders and non-responders in the S-1 and UFT groups, respectively. miR-223 was significantly higher in the responders in the S-1 group and tended to be higher in the responders in the UFT group. The present study identified several genes likely to be useful for establishing individualized therapies for patients with rectal cancer.

  20. Surprise Questions for Survival Prediction in Patients With Advanced Cancer: A Multicenter Prospective Cohort Study

    PubMed Central

    Hamano, Jun; Morita, Tatsuya; Inoue, Satoshi; Ikenaga, Masayuki; Matsumoto, Yoshihisa; Sekine, Ryuichi; Yamaguchi, Takashi; Hirohashi, Takeshi; Tajima, Tsukasa; Tatara, Ryohei; Watanabe, Hiroaki; Otani, Hiroyuki; Takigawa, Chizuko; Matsuda, Yoshinobu; Nagaoka, Hiroka; Mori, Masanori; Yamamoto, Naoki; Shimizu, Mie; Sasara, Takeshi

    2015-01-01

    Background. Predicting the short-term survival in cancer patients is an important issue for patients, family, and oncologists. Although the prognostic accuracy of the surprise question has value in 1-year mortality for cancer patients, the prognostic value for short-term survival has not been formally assessed. The primary aim of the present study was to assess the prognostic value of the surprise question for 7-day and 30-day survival in patients with advanced cancer. Patients and Methods. The present multicenter prospective cohort study was conducted in Japan from September 2012 through April 2014, involving 16 palliative care units, 19 hospital-based palliative care teams, and 23 home-based palliative care services. Results. We recruited 2,425 patients and included 2,361 for analysis: 912 from hospital-based palliative care teams, 895 from hospital palliative care units, and 554 from home-based palliative care services. The sensitivity, specificity, positive predictive value, and negative predictive value of the 7-day survival surprise question were 84.7% (95% confidence interval [CI], 80.7%–88.0%), 68.0% (95% CI, 67.3%–68.5%), 30.3% (95% CI, 28.9%–31.5%), and 96.4% (95% CI, 95.5%–97.2%), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value for the 30-day surprise question were 95.6% (95% CI, 94.4%–96.6%), 37.0% (95% CI, 35.9%–37.9%), 57.6% (95% CI, 56.8%–58.2%), and 90.4% (95% CI, 87.7%–92.6%), respectively. Conclusion. Surprise questions are useful for screening patients for short survival. However, the high false-positive rates do not allow clinicians to provide definitive prognosis prediction. Implications for Practice: The findings of this study indicate that clinicians can screen patients for 7- or 30-day survival using surprise questions with 90% or more sensitivity. Clinicians cannot provide accurate prognosis estimation, and all patients will not always die within the defined periods. The

  1. 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.

  2. Can functional gene abundance predict N-fluxes? Examples from a well-studied hydrological flow path in a forested watershed in SW China

    NASA Astrophysics Data System (ADS)

    Liu, Binbin; Muzammil, Bushra; Dörsch, Peter; Zhu, Jing; Mulder, Jan; Frostegård, Åsa

    2014-05-01

    Edaphic, climatic and management factors shape soil microbial communities taxonomically and functionally, resulting in spatial separation of nitrogen (N) oxidation and reduction processes along hydrological flowpaths. In a recent study, we investigated N-cycling processes and N2O emissions along a mesic hillslope (HS) and a hydrologically connected groundwater discharge zone (GDZ) in a forested headwater catchment dominated by acid soils (pH 4.0 - 4.5) in subtropical China (Chongqing). The watershed receives 50 kg N ha-1 a-1 through atmogenic deposition (2/3 as ammonium), most of which is removed before discharge. Surprisingly, N2O emissions were found to be greatest on the well-drained HS, whereas a drop of NO3- concentrations along the flow path indicated that N removal was highest in the moist GDZ. Nitrification was assumed to be none-limiting as the total flux of NO3- leaving the hill slope soils roughly equalled the input of NH4+. To understand watershed N-cycling and removal in more detail, we studied the abundance of functional genes involved in ammonium oxidation (amoA of AOB and AOA), nitrite oxidation (nxrB) and denitrification (nirK, nirS, nosZ) in top soils from 8 locations along the flow path spanning from the hilltop to the outlet of the GDZ. 16S rRNA gene abundance was assessed as a general marker for bacterial abundance. All genes showed highest abundance per gram soil in the heavily disturbed GDZ (formerly cultivated terraces), despite lower soil organic carbon content (1-4% w/w as opposed to 10-20% w/w in HS topsoil) and periodically stagnant conditions due to high water tables after monsoonal rainfalls. Ratios of nosZ/nirS+nirK, commonly used to predict denitrification product stoichiometry (N2O/N2), yielded counterintuitive results with higher values for HS than for GDZ. However, comparing nir gene with 16S rRNA gene abundance revealed that denitrifiers accounted for up to 10% of the bacterial community in the GDZ soils whereas this value was

  3. Ductile damage prediction in metal forming processes: Advanced modeling and numerical simulation

    NASA Astrophysics Data System (ADS)

    Saanouni, K.

    2013-05-01

    This paper describes the needs required in modern virtual metal forming including both sheet and bulk metal forming of mechanical components. These concern the advanced modeling of thermo-mechanical behavior including the multiphysical phenomena and their interaction or strong coupling, as well as the associated numerical aspects using fully adaptive simulation strategies. First a survey of advanced constitutive equations accounting for the main thermomechanical phenomena as the thermo-elasto-plastic finite strains with isotropic and kinematic hardenings fully coupled with ductile damage will be presented. Only the macroscopic phenomenological approach with state variables (monoscale approach) will be discussed in the general framework of the rational thermodynamics for generalized micromorphic continua. The micro-macro (multi-scales approach) in the framework of polycrystalline inelasticity is not presented here for the sake of shortness but will be presented during the oral presentation. The main numerical aspects related to the resolution of the associated initial and boundary value problem will be outlined. A fully adaptive numerical methodology will be briefly described and some numerical examples will be given in order to show the high predictive capabilities of this adaptive methodology for virtual metal forming simulations.

  4. [Plasma Biomarkers as Predictive Factors for Advanced Hepatocellular Carcinoma with Sorafenib].

    PubMed

    Shiozawa, Kazue; Watanabe, Manabu; Ikehara, Takashi; Matsukiyo, Yasushi; Kogame, Michio; Shinohara, Mie; Kikuchi, Yoshinori; Igarashi, Yoshinori; Sumino, Yasukiyo

    2016-07-01

    We examined plasma biomarkers as predictive factors for advanced hepatocellular carcinoma(ad-HCC)patients treated with sorafenib. We analyzed a-fetoprotein(AFP), AFP-L3, des-g-carboxy prothrombin(DCP), neutrophil-to-lymphocyte ratio(NLR), platelet-to-lymphocyte ratio(PLR), and vascular endothelial growth factor(VEGF)before sorafenib therapy, and changes in AFP-L3, NLR, PLR, and VEGF 1 month after sorafenib therapy in 16 patients. High AFP-L3(hazard ratio: 1.058, 95%CI: 1.019-1.098, p=0.003)and high NLR(hazard ratio: 1.475, 95%CI: 1.045-2.082, p=0.027)were significantly associated with poor prognosis in ad-HCC patients treated with sorafenib. There were no significant differences in changes in AFP-L3, NLR, PLR, and VEGF 1 month after sorafenib therapy. We suggest that AFP-L3 and NLR levels before sorafenib therapy in patients with ad-HCC are an important predictive factor for the therapeutic effect of sorafenib and patient survival. PMID:27431630

  5. Longitudinal Temporal and Probabilistic Prediction of Survival in a Cohort of Patients With Advanced Cancer

    PubMed Central

    Perez-Cruz, Pedro E.; dos Santos, Renata; Silva, Thiago Buosi; Crovador, Camila Souza; Nascimento, Maria Salete de Angelis; Hall, Stacy; Fajardo, Julieta; Bruera, Eduardo; Hui, David

    2014-01-01

    Context Survival prognostication is important during end-of-life. The accuracy of clinician prediction of survival (CPS) over time has not been well characterized. Objectives To examine changes in prognostication accuracy during the last 14 days of life in a cohort of patients with advanced cancer admitted to two acute palliative care units and to compare the accuracy between the temporal and probabilistic approaches. Methods Physicians and nurses prognosticated survival daily for cancer patients in two hospitals until death/discharge using two prognostic approaches: temporal and probabilistic. We assessed accuracy for each method daily during the last 14 days of life comparing accuracy at day −14 (baseline) with accuracy at each time point using a test of proportions. Results 6718 temporal and 6621 probabilistic estimations were provided by physicians and nurses for 311 patients, respectively. Median (interquartile range) survival was 8 (4, 20) days. Temporal CPS had low accuracy (10–40%) and did not change over time. In contrast, probabilistic CPS was significantly more accurate (p<.05 at each time point) but decreased close to death. Conclusion Probabilistic CPS was consistently more accurate than temporal CPS over the last 14 days of life; however, its accuracy decreased as patients approached death. Our findings suggest that better tools to predict impending death are necessary. PMID:24746583

  6. 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.

  7. 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.

  8. Advances and applications of binding affinity prediction methods in drug discovery.

    PubMed

    Parenti, Marco Daniele; Rastelli, Giulio

    2012-01-01

    Nowadays, the improvement of R&D productivity is the primary commitment in pharmaceutical research, both in big pharma and smaller biotech companies. To reduce costs, to speed up the discovery process and to increase the chance of success, advanced methods of rational drug design are very helpful, as demonstrated by several successful applications. Among these, computational methods able to predict the binding affinity of small molecules to specific biological targets are of special interest because they can accelerate the discovery of new hit compounds. Here we provide an overview of the most widely used methods in the field of binding affinity prediction, as well as of our own work in developing BEAR, an innovative methodology specifically devised to overtake some limitations in existing approaches. The BEAR method was successfully validated against different biological targets, and proved its efficacy in retrieving active compounds from virtual screening campaigns. The results obtained so far indicate that BEAR may become a leading tool in the drug discovery pipeline. We primarily discuss advantages and drawbacks of each technique and show relevant examples and applications in drug discovery.

  9. 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

  10. Including the dynamic relationship between climatic variables and leaf area index in a hydrological model to improve streamflow prediction under a changing climate

    NASA Astrophysics Data System (ADS)

    Tesemma, Z. K.; Wei, Y.; Peel, M. C.; Western, A. W.

    2015-06-01

    Anthropogenic climate change is projected to enrich the atmosphere with carbon dioxide, change vegetation dynamics and influence the availability of water at the catchment scale. This study combines a nonlinear model for estimating changes in leaf area index (LAI) due to climatic fluctuations with the variable infiltration capacity (VIC) hydrological model to improve catchment streamflow prediction under a changing climate. The combined model was applied to 13 gauged sub-catchments with different land cover types (crop, pasture and tree) in the Goulburn-Broken catchment, Australia, for the "Millennium Drought" (1997-2009) relative to the period 1983-1995, and for two future periods (2021-2050 and 2071-2100) and two emission scenarios (Representative Concentration Pathway (RCP) 4.5 and RCP8.5) which were compared with the baseline historical period of 1981-2010. This region was projected to be warmer and mostly drier in the future as predicted by 38 Coupled Model Intercomparison Project Phase 5 (CMIP5) runs from 15 global climate models (GCMs) and for two emission scenarios. The results showed that during the Millennium Drought there was about a 29.7-66.3 % reduction in mean annual runoff due to reduced precipitation and increased temperature. When drought-induced changes in LAI were included, smaller reductions in mean annual runoff of between 29.3 and 61.4 % were predicted. The proportional increase in runoff due to modeling LAI was 1.3-10.2 % relative to not including LAI. For projected climate change under the RCP4.5 emission scenario, ignoring the LAI response to changing climate could lead to a further reduction in mean annual runoff of between 2.3 and 27.7 % in the near-term (2021-2050) and 2.3 to 23.1 % later in the century (2071-2100) relative to modeling the dynamic response of LAI to precipitation and temperature changes. Similar results (near-term 2.5-25.9 % and end of century 2.6-24.2 %) were found for climate change under the RCP8.5 emission scenario

  11. 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

  12. Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios: the example of a small Mediterranean agro-watershed.

    PubMed

    Kourgialas, Nektarios N; Dokou, Zoi; Karatzas, George P

    2015-05-01

    The purpose of this study was to create a modeling management tool for the simulation of extreme flow events under current and future climatic conditions. This tool is a combination of different components and can be applied in complex hydrogeological river basins, where frequent flood and drought phenomena occur. The first component is the statistical analysis of the available hydro-meteorological data. Specifically, principal components analysis was performed in order to quantify the importance of the hydro-meteorological parameters that affect the generation of extreme events. The second component is a prediction-forecasting artificial neural network (ANN) model that simulates, accurately and efficiently, river flow on an hourly basis. This model is based on a methodology that attempts to resolve a very difficult problem related to the accurate estimation of extreme flows. For this purpose, the available measurements (5 years of hourly data) were divided in two subsets: one for the dry and one for the wet periods of the hydrological year. This way, two ANNs were created, trained, tested and validated for a complex Mediterranean river basin in Crete, Greece. As part of the second management component a statistical downscaling tool was used for the creation of meteorological data according to the higher and lower emission climate change scenarios A2 and B1. These data are used as input in the ANN for the forecasting of river flow for the next two decades. The final component is the application of a meteorological index on the measured and forecasted precipitation and flow data, in order to assess the severity and duration of extreme events. PMID:25710600

  13. Statistical analysis and ANN modeling for predicting hydrological extremes under climate change scenarios: the example of a small Mediterranean agro-watershed.

    PubMed

    Kourgialas, Nektarios N; Dokou, Zoi; Karatzas, George P

    2015-05-01

    The purpose of this study was to create a modeling management tool for the simulation of extreme flow events under current and future climatic conditions. This tool is a combination of different components and can be applied in complex hydrogeological river basins, where frequent flood and drought phenomena occur. The first component is the statistical analysis of the available hydro-meteorological data. Specifically, principal components analysis was performed in order to quantify the importance of the hydro-meteorological parameters that affect the generation of extreme events. The second component is a prediction-forecasting artificial neural network (ANN) model that simulates, accurately and efficiently, river flow on an hourly basis. This model is based on a methodology that attempts to resolve a very difficult problem related to the accurate estimation of extreme flows. For this purpose, the available measurements (5 years of hourly data) were divided in two subsets: one for the dry and one for the wet periods of the hydrological year. This way, two ANNs were created, trained, tested and validated for a complex Mediterranean river basin in Crete, Greece. As part of the second management component a statistical downscaling tool was used for the creation of meteorological data according to the higher and lower emission climate change scenarios A2 and B1. These data are used as input in the ANN for the forecasting of river flow for the next two decades. The final component is the application of a meteorological index on the measured and forecasted precipitation and flow data, in order to assess the severity and duration of extreme events.

  14. 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).

  15. 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.

  16. Arctic hydrology and meteorology

    SciTech Connect

    Kane, D.L.

    1988-01-01

    The behavior of arctic ecosystems is directly related to the ongoing physical processes of heat and mass transfer. Furthermore, this system undergoes very large fluctuations in the surface energy balance. The buffering effect of both snow and the surface organic soils can be seen by looking at the surface and 40 cm soil temperatures. The active layer, that surface zone above the permafrost table, is either continually freezing or thawing. A large percentage of energy into and out of a watershed must pass through this thin veneer that we call the active layer. Likewise, most water entering and leaving the watershed does so through the active layer. To date, we have been very successful at monitoring the hydrology of Imnavait Creek with special emphasis on the active layer processes. The major contribution of this study is that year-round hydrologic data are being collected. An original objective of our study was to define how the thermal and moisture regimes within the active layer change during an annual cycle under natural conditions, and then to define how the regime will be impacted by some imposed terrain alteration. Our major analysis of the hydrologic data sets for Imnavait Creek have been water balance evaluations for plots during snowmelt, water balance for the watershed during both rainfall and snowmelt, and the application of a hydrologic model to predict the Imnavait Creek runoff events generated by both snowmelt and rainfall.

  17. 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

  18. Using Daily GCM Rainfall for Crop Yield Predictions: Advances and Challenges

    NASA Astrophysics Data System (ADS)

    Ines, A. M.; Hansen, J. W.; Robertson, A. W.; Baethgen, W.; Sun, L.; Indeje, M.

    2010-12-01

    Global climate models (GCMs) are promising for crop yield predictions not only because of their ability to simulate seasonal climate in advance of the growing season but also of their ability to simulate long-term climate changes. Despite this potential, a lot of challenges exist in using directly raw GCM data to crop models. First, because of the spatial scale mismatch between GCMs and crop models (10^2 km vs. 10^1 m), and second, due to biases and temporal structure mismatches in daily GCM rainfall relative to station observations. Crop growth is very sensitive to daily variations of rainfall thus any mismatch in daily rainfall statistics could adversely impact simulation of crop yields. In view of this, a lot of efforts have been made to correct biases in daily GCM rainfall relative to the climatology of a station or set of stations, and recently on some attempts to correct time structure in climate model rainfall. Here, we will present some advances in tailoring daily GCM rainfall for crop yield predictions and discuss some challenges underlying those methods. Specifically, we will present an improved nested GCM bias correction-stochastic disaggregation (BC-DisAg) method for improving the use of daily GCM rainfall for crop simulations and show some testing and evaluation results in different regions (Northeastern Kenya, Uruguay, Southern and Northeast Brazil). We also examined several ways of weighting GCM grid cells to better summarize their information contents for the nested approach, including inverse-distance weighting, arithmetic averaging, multiple linear regression and genetic algorithms. Finally, we will show a comparison between the GCM bias correction and Model Output Statistics (MOS)-correction downscaling in one of the selected sites at Katumani, Kenya. Our results showed that there is a significant improvement in the simulation of yields if the GCM bias correction (BC) is nested with stochastic disaggregation than just BC alone because of the

  19. In-Service Design & Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation

    SciTech Connect

    G. R. Odette; G. E. Lucas

    2005-11-15

    This final report on "In-Service Design & Performance Prediction of Advanced Fusion Material Systems by Computational Modeling and Simulation" (DE-FG03-01ER54632) consists of a series of summaries of work that has been published, or presented at meetings, or both. It briefly describes results on the following topics: 1) A Transport and Fate Model for Helium and Helium Management; 2) Atomistic Studies of Point Defect Energetics, Dynamics and Interactions; 3) Multiscale Modeling of Fracture consisting of: 3a) A Micromechanical Model of the Master Curve (MC) Universal Fracture Toughness-Temperature Curve Relation, KJc(T - To), 3b) An Embrittlement DTo Prediction Model for the Irradiation Hardening Dominated Regime, 3c) Non-hardening Irradiation Assisted Thermal and Helium Embrittlement of 8Cr Tempered Martensitic Steels: Compilation and Analysis of Existing Data, 3d) A Model for the KJc(T) of a High Strength NFA MA957, 3e) Cracked Body Size and Geometry Effects of Measured and Effective Fracture Toughness-Model Based MC and To Evaluations of F82H and Eurofer 97, 3-f) Size and Geometry Effects on the Effective Toughness of Cracked Fusion Structures; 4) Modeling the Multiscale Mechanics of Flow Localization-Ductility Loss in Irradiation Damaged BCC Alloys; and 5) A Universal Relation Between Indentation Hardness and True Stress-Strain Constitutive Behavior. Further details can be found in the cited references or presentations that generally can be accessed on the internet, or provided upon request to the authors. Finally, it is noted that this effort was integrated with our base program in fusion materials, also funded by the DOE OFES.

  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. 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.

  2. 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. PMID:23159421

  3. 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. PMID:26065331

  4. 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.

  5. 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.

  6. 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...

  7. 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.

  8. Derivation and validation of a prediction rule for estimating advanced colorectal neoplasm risk in average-risk Chinese.

    PubMed

    Cai, Quan-Cai; Yu, En-Da; Xiao, Yi; Bai, Wen-Yuan; Chen, Xing; He, Li-Ping; Yang, Yu-Xiu; Zhou, Ping-Hong; Jiang, Xue-Liang; Xu, Hui-Min; Fan, Hong; Ge, Zhi-Zheng; Lv, Nong-Hua; Huang, Zhi-Gang; Li, You-Ming; Ma, Shu-Ren; Chen, Jie; Li, Yan-Qing; Xu, Jian-Ming; Xiang, Ping; Yang, Li; Lin, Fu-Lin; Li, Zhao-Shen

    2012-03-15

    No prediction rule is currently available for advanced colorectal neoplasms, defined as invasive cancer, an adenoma of 10 mm or more, a villous adenoma, or an adenoma with high-grade dysplasia, in average-risk Chinese. In this study between 2006 and 2008, a total of 7,541 average-risk Chinese persons aged 40 years or older who had complete colonoscopy were included. The derivation and validation cohorts consisted of 5,229 and 2,312 persons, respectively. A prediction rule was developed from a logistic regression model and then internally and externally validated. The prediction rule comprised 8 variables (age, sex, smoking, diabetes mellitus, green vegetables, pickled food, fried food, and white meat), with scores ranging from 0 to 14. Among the participants with low-risk (≤3) or high-risk (>3) scores in the validation cohort, the risks of advanced neoplasms were 2.6% and 10.0% (P < 0.001), respectively. If colonoscopy was used only for persons with high risk, 80.3% of persons with advanced neoplasms would be detected while the number of colonoscopies would be reduced by 49.2%. The prediction rule had good discrimination (area under the receiver operating characteristic curve = 0.74, 95% confidence interval: 0.70, 0.78) and calibration (P = 0.77) and, thus, provides accurate risk stratification for advanced neoplasms in average-risk Chinese. PMID:22328705

  9. 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...

  10. Development of a Measure for Predicting Learning Advancement through Cooperative Education: Reliability and Validity of the PLACE Scale.

    ERIC Educational Resources Information Center

    Parks, Donald K.; Onwuegbuzie, Anthony J.; Cash, Shannon H.

    2001-01-01

    Exploratory factor analysis of data from 2,309 cooperative education students tested a measure of co-op outcomes. Three factors were identified: work skills development, career development, and academic functions. The Predicting Learner Advancement through Cooperative Education Scale appeared to have good psychometric properties. (Contains 27…

  11. 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.

  12. 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

  13. Abs-initio, Predictive Calculations for Optoelectronic and Advanced Materials Research

    NASA Astrophysics Data System (ADS)

    Bagayoko, Diola

    2010-10-01

    Most density functional theory (DFT) calculations find band gaps that are 30-50 percent smaller than the experimental ones. Some explanations of this serious underestimation by theory include self-interaction and the derivative discontinuity of the exchange correlation energy. Several approaches have been developed in the search for a solution to this problem. Most of them entail some modification of DFT potentials. The Green function and screened Coulomb approximation (GWA) is a non-DFT formalism that has led to some improvements. Despite these efforts, the underestimation problem has mostly persisted in the literature. Using the Rayleigh theorem, we describe a basis set and variational effect inherently associated with calculations that employ a linear combination of atomic orbitals (LCAO) in a variational approach of the Rayleigh-Ritz type. This description concomitantly shows a source of large underestimation errors in calculated band gaps, i.e., an often dramatic lowering of some unoccupied energies on account of the Rayleigh theorem as opposed to a physical interaction. We present the Bagayoko, Zhao, and Williams (BZW) method [Phys. Rev. B 60, 1563 (1999); PRB 74, 245214 (2006); and J. Appl. Phys. 103, 096101 (2008)] that systematically avoids this effect and leads (a) to DFT and LDA calculated band gaps of semiconductors in agreement with experiment and (b) theoretical predictions of band gaps that are confirmed by experiment. Unlike most calculations, BZW computations solve, self-consistently, a system of two coupled equations. DFT-BZW calculated effective masses and optical properties (dielectric functions) also agree with measurements. We illustrate ten years of success of the BZW method with its results for GaN, C, Si, 3C-SIC, 4H-SiC, ZnO, AlAs, Ge, ZnSe, w-InN, c-InN, InAs, CdS, AlN and nanostructures. We conclude with potential applications of the BZW method in optoelectronic and advanced materials research.

  14. 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.

  15. 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.

  16. 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.

  17. 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. PMID:21537597

  18. Predicting Advanced Placement Examination Success from FCAT Scores. Research Brief. Volume 0709

    ERIC Educational Resources Information Center

    Froman, Terry; Brown, Shelly; Tirado, Arleti

    2008-01-01

    Advanced Placement courses are offered at M-DCPS for students to acquire college credit or advanced college academic standing. A system has been developed in the past by the College Board to use the PSAT for 10th grade students to estimate their potential for AP Examination success. The same test has recently been applied in this district to 9th…

  19. Katul Receives 2012 Hydrologic Sciences Award: Citation

    NASA Astrophysics Data System (ADS)

    Parlange, Marc B.

    2013-10-01

    I am delighted to present Professor Gabriel Katul of Duke University with the 2012 Hydrologic Sciences Award. He has made massive contributions to the understanding and prediction of hydrology, and it is for his work that we (Professors Poporato, Hornberger, Rinaldo, Rodriguez-Iturbe, Brutsaert, and Raupach) nominated him.

  20. 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

  1. Hydrology team

    NASA Technical Reports Server (NTRS)

    Ragan, R.

    1982-01-01

    General problems faced by hydrologists when using historical records, real time data, statistical analysis, and system simulation in providing quantitative information on the temporal and spatial distribution of water are related to the limitations of these data. Major problem areas requiring multispectral imaging-based research to improve hydrology models involve: evapotranspiration rates and soil moisture dynamics for large areas; the three dimensional characteristics of bodies of water; flooding in wetlands; snow water equivalents; runoff and sediment yield from ungaged watersheds; storm rainfall; fluorescence and polarization of water and its contained substances; discriminating between sediment and chlorophyll in water; role of barrier island dynamics in coastal zone processes; the relationship between remotely measured surface roughness and hydraulic roughness of land surfaces and stream networks; and modeling the runoff process.

  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. 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.

  5. Paleoflood hydrology: Origin, progress, prospects

    NASA Astrophysics Data System (ADS)

    Baker, Victor R.

    2008-10-01

    From an origin in diverse studies of flood geomorphology and Quaternary geology, paleoflood hydrology emerged as a geophysical and an applied hydrological science during the 1970s and 1980s. Since acquiring its formal name in 1982, the most productive approach in paleoflood hydrology has become energy-based inverse hydraulic modeling of discrete paleoflood events, recorded in appropriate settings as slackwater deposits and other paleostage indicators (SWD-PSI), or as various threshold indicators of non-exceedence. Technological advances, particularly in hydraulic modeling and geochronology, were instrumental in moving the discipline to its present status. The most recent advances include (1) new techniques for the accurate geochronology of flood sediments, notably TAMS radiocarbon analyses and OSL dating, and (2) the phenomenal increase in computer power that allows complex hydraulic calculations to become feasible for routine studies. From its initial demonstration in the southwestern United States, SWD-PSI paleoflood hydrology proved its widespread applicability to various landscape environments. Particularly important studies have been accomplished in Australia, China, India, Israel, South Africa, Spain, and Thailand. Paleoflood hydrology has also generated its share of controversy, in part because of the differing viewpoints and attitudes of the two scientific traditions from which it emerged: Quaternary geology/geomorphology versus applied hydrologic/hydraulic engineering. Nevertheless, the future growth of the discipline is assured, given the rapid pace of discoveries that it engenders. Indeed, so many international studies exist that it is appropriate to pursue global syntheses to address interesting and timely questions of extreme flood phenomena in relation to global climatic change.

  6. 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.

  7. 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).

  8. 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.

  9. 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

  10. 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.

  11. 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

    2015-01-01

    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

  12. 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

  13. An Integrated Theory for Predicting the Hydrothermomechanical Response of Advanced Composite Structural Components

    NASA Technical Reports Server (NTRS)

    Chamis, C. C.; Lark, R. F.; Sinclair, J. H.

    1977-01-01

    An integrated theory is developed for predicting the hydrothermomechanical (HDTM) response of fiber composite components. The integrated theory is based on a combined theoretical and experimental investigation. In addition to predicting the HDTM response of components, the theory is structured to assess the combined hydrothermal effects on the mechanical properties of unidirectional composites loaded along the material axis and off-axis, and those of angleplied laminates. The theory developed predicts values which are in good agreement with measured data at the micromechanics, macromechanics, laminate analysis and structural analysis levels.

  14. 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.

  15. How Prognostic and Predictive Biomarkers Are Transforming Our Understanding and Management of Advanced Gastric Cancer

    PubMed Central

    Mulder, Karen; Spratlin, Jennifer

    2014-01-01

    Background. Gastric cancer (GC) is the second leading cause of cancer death worldwide. GC is a heterogeneous disease in terms of histology, anatomy, and epidemiology. There is also wide variability in how GC is treated in both the resectable and unresectable settings. Identification of prognostic and predictive biomarkers is critical to help direct and tailor therapy for this deadly disease. Methods. A literature search was done using Medline and MeSH terms for GC and predictive biomarkers and prognostic biomarkers. The search was limited to human subjects and the English language. There was no limit on dates. Published data and unpublished abstracts with clinical relevance were included. Results. Many potential prognostic and predictive biomarkers have been assessed for GC, some of which are becoming practice changing. This review is focused on clinically relevant biomarkers, including EGFR, HER2, various markers of angiogenesis, proto-oncogene MET, and the mammalian target of rapamycin. Conclusion. GC is a deadly and heterogeneous disease for which biomarkers are beginning to change our understanding of prognosis and management. The recognition of predictive biomarkers, such as HER2 and vascular endothelial growth factor, has been an exciting development in the management of GC, validating the use of targeted drugs trastuzumab and ramucirumab. MET is another potential predictive marker that may be targeted in GC with drugs such as rilotumumab, foretinib, and crizotinib. Further identification and validation of prognostic and predictive biomarkers has the potential transform how this deadly disease is managed. PMID:25142842

  16. Improving standard practices for prediction in ungauged basins: Bayesian approach

    NASA Astrophysics Data System (ADS)

    Prieto, Cristina; Le-Vine, Nataliya; García, Eduardo; Medina, Raúl

    2015-04-01

    In hydrological modelling, the prediction of flows in ungauged basins is still a defiance. Among the different alternatives to quantify and reduce the uncertainty in the predictions, a Bayesian framework has proven to be advantageous. This framework allows flow prediction in ungauged basins based on regionalised hydrological indices. Being grounded on probability theory, the procedure requires a number of assumptions and decisions to be made. Among the most important ones are 1) selection of representative hydrological signatures, 2) selection of regionalization model functional form, and 3) a 'perfect' model/ input assumption. The contribution of this research is to address these three assumptions. First, to reduce an extensive set of available hydrological signatures we select a compact orthogonal set of information pieces using Principal Component Analysis. This advances the standard practice of semi-empirical selection of individual hydrological signatures. Second, we use functional-form-assumption-free Random Forests to regionalize the selected information. This allows the traditional assumption of linear regression between catchment properties and characteristics of hydrological response to be relaxes. And third, we propose utilizing non-traditional metrics to flag-up possible model/ input errors: Bayes' Factor and a newly-proposed 'Suitability' test. This addresses the typical non-realistic assumption that model is 'perfect' and the input is noise-free. The proposed methodological developments are illustrated for the empirical challenge of flow prediction in rivers in Northern Spain.

  17. 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.

  18. Hydrological research in Ethiopia

    NASA Astrophysics Data System (ADS)

    Gebremichael, M.

    2012-12-01

    Almost all major development problems in Ethiopia are water-related: food insecurity, low economic development, recurrent droughts, disastrous floods, poor health conditions, and low energy condition. In order to develop and manage existing water resources in a sustainable manner, knowledge is required about water availability, water quality, water demand in various sectors, and the impacts of water resource projects on health and the environment. The lack of ground-based data has been a major challenge for generating this knowledge. Current advances in remote sensing and computer simulation technology could provide alternative source of datasets. In this talk, I will present the challenges and opportunities in using remote sensing datasets and hydrological models in regions such as Africa where ground-based datasets are scarce.

  19. 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.

  20. 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.

  1. Advancing decadal-scale climate prediction in the North Atlantic sector.

    PubMed

    Keenlyside, N S; Latif, M; Jungclaus, J; Kornblueh, L; Roeckner, E

    2008-05-01

    The climate of the North Atlantic region exhibits fluctuations on decadal timescales that have large societal consequences. Prominent examples include hurricane activity in the Atlantic, and surface-temperature and rainfall variations over North America, Europe and northern Africa. Although these multidecadal variations are potentially predictable if the current state of the ocean is known, the lack of subsurface ocean observations that constrain this state has been a limiting factor for realizing the full skill potential of such predictions. Here we apply a simple approach-that uses only sea surface temperature (SST) observations-to partly overcome this difficulty and perform retrospective decadal predictions with a climate model. Skill is improved significantly relative to predictions made with incomplete knowledge of the ocean state, particularly in the North Atlantic and tropical Pacific oceans. Thus these results point towards the possibility of routine decadal climate predictions. Using this method, and by considering both internal natural climate variations and projected future anthropogenic forcing, we make the following forecast: over the next decade, the current Atlantic meridional overturning circulation will weaken to its long-term mean; moreover, North Atlantic SST and European and North American surface temperatures will cool slightly, whereas tropical Pacific SST will remain almost unchanged. Our results suggest that global surface temperature may not increase over the next decade, as natural climate variations in the North Atlantic and tropical Pacific temporarily offset the projected anthropogenic warming.

  2. Global warming and the hydrologic cycle

    NASA Astrophysics Data System (ADS)

    Loaiciga, Hugo A.; Valdes, Juan B.; Vogel, Richard; Garvey, Jeff; Schwarz, Harry

    1996-01-01

    Starting with a review of the basic processes that govern greenhouse warming, we have demonstrated that the hydrologic cycle plays a key role in the heat balance of the Earth's surface—atmosphere system. Through the water and other climatic feedbacks, the hydrologic cycle is shown to be a key factor in the climate's evolution as greenhouse gases continue to build up in the atmosphere. This paper examines the current predictive capability of general circulation models linked with macroscale and landscape-scale hydrologic models that simulate regional and local hydrologic regimes under global warming scenarios. Issues concerning hydrologic model calibration and validation in the context of climate change are addressed herein. It is shown that the natural uncertainty in hydrologic regimes in the present climate introduces a signal-to-noise interpretation problem for discerning greenhouse-induced variations in regional hydrologic regimes. Simulations of river basins by means of macroscale hydrologic models nested within general circulation models have been implemented in a few selected cases. From the perspective of water resources management, such simulations, carried out in detail under greenhouse-warming scenarios in midlatitudinal basins of the United States, predict shorter winter seasons, larger winter floods, drier and more frequent summer weather, and overall enhanced and protracted hydrologic variability. All these predictions point to potentially worsening conditions for flood control, water storage, and water supply in areas of semiarid midlatitudinal climate currently dependent of spring snowmelt. Little information of this type is currently available for other areas of the world. Practice of sound water resources engineering principles ought to be adequate to cope with additional hydrologic uncertainty that might arise from global warming.

  3. 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.

  4. Development of Predictive Models of Advanced Propulsion Concepts for Low Cost Space Transportation

    NASA Technical Reports Server (NTRS)

    Morrell, Michael Randy

    2002-01-01

    This final report presents the Graduate Student Research Program (GSRP) work Mr. Morrell was able to complete as a summer intern at NASA MSFS during the summer of 2001, and represents work completed from inception through project termination. The topics include: 1) NASA TD40 Organization; 2) Combustion Physics Lab; 3) Advanced Hydrocarbon Fuels; 4) GSRP Summer Tasks; 5) High Pressure Facility Installation; 6) High Pressure Combustion Issues; 7) High Energy Density Matter (HEDM) Hydrocarbons; and 8) GSRP Summer Intern Summary.

  5. 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.

  6. 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

  7. 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.

  8. 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

  9. 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.

  10. 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.

  11. 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.

  12. Advanced turboprop noise prediction: Development of a code at NASA Langley based on recent theoretical results

    NASA Technical Reports Server (NTRS)

    Farassat, F.; Dunn, M. H.; Padula, S. L.

    1986-01-01

    The development of a high speed propeller noise prediction code at Langley Research Center is described. The code utilizes two recent acoustic formulations in the time domain for subsonic and supersonic sources. The structure and capabilities of the code are discussed. Grid size study for accuracy and speed of execution on a computer is also presented. The code is tested against an earlier Langley code. Considerable increase in accuracy and speed of execution are observed. Some examples of noise prediction of a high speed propeller for which acoustic test data are available are given. A brisk derivation of formulations used is given in an appendix.

  13. 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

  14. 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.

  15. 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.

  16. 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

  17. Sensor-model prediction, monitoring and in-situ control of liquid RTM advanced fiber architecture composite processing

    NASA Astrophysics Data System (ADS)

    Kranbuehl, D.; Kingsley, P.; Hart, S.; Loos, A.; Hasko, G.; Dexter, B.

    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. 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.

  19. Global hydrology 2015: State, trends, and directions

    NASA Astrophysics Data System (ADS)

    Bierkens, Marc F. P.

    2015-07-01

    Global hydrology has come a long way since the first introduction of the primitive land surface model of Manabe (1969) and the declaration of the "Emergence of Global Hydrology" by Eagleson (1986). Hydrological submodels of varying complexity are now part of global climate models, of models calculating global terrestrial carbon sequestration, of earth system models, and even of integrated assessment models. This paper reviews the current state of global hydrological modeling, discusses past and recent developments, and extrapolates these to future challenges and directions. First, established domains of global hydrological model applications are discussed, in terms of societal and science questions posed, the type of models developed, and recent advances therein. Next, a genealogy of global hydrological models is given. After reviewing recent efforts to connect model components from different domains, new domains are identified where global hydrology is now starting to become an integral part of the analyses. Finally, inspired by these new domains of application, persistent and emerging challenges are identified as well as the directions global hydrology is likely to take in the coming decade and beyond.

  20. 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...

  1. 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.

  2. In silico assessment of the acute toxicity of chemicals: recent advances and new model for multitasking prediction of toxic effect.

    PubMed

    Kleandrova, Valeria V; Luan, Feng; Speck-Planche, Alejandro; Cordeiro, M Natália D S

    2015-01-01

    The assessment of acute toxicity is one of the most important stages to ensure the safety of chemicals with potential applications in pharmaceutical sciences, biomedical research, or any other industrial branch. A huge and indiscriminate number of toxicity assays have been carried out on laboratory animals. In this sense, computational approaches involving models based on quantitative-structure activity/toxicity relationships (QSAR/QSTR) can help to rationalize time and financial costs. Here, we discuss the most significant advances in the last 6 years focused on the use of QSAR/QSTR models to predict acute toxicity of drugs/chemicals in laboratory animals, employing large and heterogeneous datasets. The advantages and drawbacks of the different QSAR/QSTR models are analyzed. As a contribution to the field, we introduce the first multitasking (mtk) QSTR model for simultaneous prediction of acute toxicity of compounds by considering different routes of administration, diverse breeds of laboratory animals, and the reliability of the experimental conditions. The mtk-QSTR model was based on artificial neural networks (ANN), allowing the classification of compounds as toxic or non-toxic. This model correctly classified more than 94% of the 1646 cases present in the whole dataset, and its applicability was demonstrated by performing predictions of different chemicals such as drugs, dietary supplements, and molecules which could serve as nanocarriers for drug delivery. The predictions given by the mtk-QSTR model are in very good agreement with the experimental results. PMID:25694074

  3. In silico assessment of the acute toxicity of chemicals: recent advances and new model for multitasking prediction of toxic effect.

    PubMed

    Kleandrova, Valeria V; Luan, Feng; Speck-Planche, Alejandro; Cordeiro, M Natália D S

    2015-01-01

    The assessment of acute toxicity is one of the most important stages to ensure the safety of chemicals with potential applications in pharmaceutical sciences, biomedical research, or any other industrial branch. A huge and indiscriminate number of toxicity assays have been carried out on laboratory animals. In this sense, computational approaches involving models based on quantitative-structure activity/toxicity relationships (QSAR/QSTR) can help to rationalize time and financial costs. Here, we discuss the most significant advances in the last 6 years focused on the use of QSAR/QSTR models to predict acute toxicity of drugs/chemicals in laboratory animals, employing large and heterogeneous datasets. The advantages and drawbacks of the different QSAR/QSTR models are analyzed. As a contribution to the field, we introduce the first multitasking (mtk) QSTR model for simultaneous prediction of acute toxicity of compounds by considering different routes of administration, diverse breeds of laboratory animals, and the reliability of the experimental conditions. The mtk-QSTR model was based on artificial neural networks (ANN), allowing the classification of compounds as toxic or non-toxic. This model correctly classified more than 94% of the 1646 cases present in the whole dataset, and its applicability was demonstrated by performing predictions of different chemicals such as drugs, dietary supplements, and molecules which could serve as nanocarriers for drug delivery. The predictions given by the mtk-QSTR model are in very good agreement with the experimental results.

  4. 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

  5. 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!

  6. Advanced Predictive Model and Real-World Results for Medium Concentration CPV

    NASA Astrophysics Data System (ADS)

    Karney, Bruce; Finot, Marc

    2011-12-01

    Skyline Solar has developed a novel medium concentration PV product. The system is a linear concentrator that tracks the sun with a 1-axis horizontal tracker. Reflectors are used to concentrate sunlight 7-50x using non-imaging optics. The receivers use Silicon cells and passive cooling. The product's design has been guided by a detailed Performance Prediction Tool (PPT) that relates component characteristics and climate data to the overall energy production. In contrast with other tools, the PPT captures the non-linearity of conditions such as weather, system architecture (stringing, shadow management) and the value of energy as a function of time of day and season. This paper describes the key elements of the PPT and compares its predictions to real-world results from different locations with significantly different DNI. Moderate DNI sites are San Jose, California and Kona, Hawaii. The higher DNI site is Nipton, California (DNI ˜7.2). Skyline's PPT accurately predicts the energy harvest for two Skyline Solar systems including the HGS 1000 and the new Skyline Solar X14 System.

  7. 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. PMID:27532883

  8. 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

  9. 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.

  10. 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

  11. Ensemble seasonal hydrological forecasting at the pan-European scale

    NASA Astrophysics Data System (ADS)

    Pechlivanidis, Ilias; Spångmyr, Henrik; Bosshard, Thomas; Gustafsson, David; Olsson, Jonas

    2015-04-01

    Recent advances in understanding and forecasting of climate and climate change have resulted into skillful and useful meteorological predictions, which can consequently increase the confidence of hydrological prognosis and awareness from an end-user perspective. However, the majority of seasonal impact modelling has commonly been conducted at only one or a limited number of basins limiting the need to understand large systems which are heavily influenced by human activities. In here, we complement the "deep" knowledge from basin based modelling using large scale multi-basin modelling, which is capable of representing human influences (i.e. irrigation, reservoirs and groundwater use). We analyse the seasonal predictive skill along Europe's hydro-climatic gradient using the pan-European E-HYPE v3.0 multi-basin hydrological model. Forcing data (mean daily precipitation and temperature) are derived from the WFDEI product for the period 1979-2010 and used to initialise the hydrological model (level in surface water, i.e. reservoirs, lakes and wetlands, soil moisture, snow depth). Re-forecast forcing data (daily mean precipitation and temperature for the period 1981-2010) from ECMWF's System 4 (15 members initialised every month) are firstly bias corrected using a modified version of the Distribution Based Scaling (DBS) method to account for drifting conditioning the bias correction on the lead month, and further used to drive E-HYPE. The predictive skill of river runoff for a number of European basins is assessed on seasonal timescales. Seasonal re-forecasts are evaluated with respect to their accuracy against observed impact variables, i.e. streamflow, at different space and time-scales; the value of the predictions are assessed using various performance metrics. Verification points (around 2600 stations) are used to represent various climatologies, soil-types, land uses, altitudes and basin scales within Europe. We finally identify regions of similar hydrological

  12. 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.

  13. Predictive and prognostic biomarkers for neoadjuvant chemoradiotherapy in locally advanced rectal cancer.

    PubMed

    Lim, S H; Chua, W; Henderson, C; Ng, W; Shin, J-S; Chantrill, L; Asghari, R; Lee, C S; Spring, K J; de Souza, P

    2015-10-01

    Locally advanced rectal cancer is regularly treated with trimodality therapy consisting of neoadjuvant chemoradiation, surgery and adjuvant chemotherapy. There is a need for biomarkers to assess treatment response, and aid in stratification of patient risk to adapt and personalise components of the therapy. Currently, pathological stage and tumour regression grade are used to assess response. Experimental markers include proteins involved in cell proliferation, apoptosis, angiogenesis, the epithelial to mesenchymal transition and microsatellite instability. As yet, no single marker is sufficiently robust to have clinical utility. Microarrays that screen a tumour for multiple promising candidate markers, gene expression and microRNA profiling will likely have higher yield and it is expected that a combination or panel of markers would prove most useful. Moving forward, utilising serial samples of circulating tumour cells or circulating nucleic acids can potentially allow us to demonstrate tumour heterogeneity, document mutational changes and subsequently measure treatment response. PMID:26032919

  14. 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.

  15. The Climate Variability & Predictability (CVP) Program at NOAA - DYNAMO Recent Project Advancements

    NASA Astrophysics Data System (ADS)

    Lucas, S. E.; Todd, J. F.; Higgins, W.

    2013-12-01

    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 Geosphere-Biosphere Programme (IGBP), and the U.S. Global Change Research Program (USGCRP). The CVP program sits within the Earth System Science (ESS) Division at NOAA's Climate Program Office. Dynamics of the Madden-Julian Oscillation (DYNAMO): The Indian Ocean is one of Earth's most sensitive regions because the interactions between ocean and atmosphere there have a discernable effect on global climate patterns. The tropical weather that brews in that region can move eastward along the equator and reverberate around the globe, shaping weather and climate in far-off places. The vehicle for this variability is a phenomenon called the Madden-Julian Oscillation, or MJO. The MJO, which originates over the Indian Ocean roughly every 30 to 90 days, is known to influence the Asian and Australian monsoons. It can also enhance hurricane activity in the northeast Pacific and Gulf of Mexico, trigger torrential rainfall along the west coast of North America, and affect the onset of El Niño. CVP-funded scientists participated in the DYNAMO field campaign in 2011-12. Results from this international campaign are expected to improve researcher's insights into this influential phenomenon. A better understanding of the processes governing MJO is an essential step toward

  16. Hydrological and geomorphological controls of malaria transmission

    NASA Astrophysics Data System (ADS)

    Smith, M. W.; Macklin, M. G.; Thomas, C. J.

    2013-01-01

    Malaria risk is linked inextricably to the hydrological and geomorphological processes that form vector breeding sites. Yet environmental controls of malaria transmission are often represented by temperature and rainfall amounts, ignoring hydrological and geomorphological influences altogether. Continental-scale studies incorporate hydrology implicitly through simple minimum rainfall thresholds, while community-scale coupled hydrological and entomological models do not represent the actual diversity of the mosquito vector breeding sites. The greatest range of malaria transmission responses to environmental factors is observed at the catchment scale where seemingly contradictory associations between rainfall and malaria risk can be explained by hydrological and geomorphological processes that govern surface water body formation and persistence. This paper extends recent efforts to incorporate ecological factors into malaria-risk models, proposing that the same detailed representation be afforded to hydrological and, at longer timescales relevant for predictions of climate change impacts, geomorphological processes. We review existing representations of environmental controls of malaria and identify a range of hydrologically distinct vector breeding sites from existing literature. We illustrate the potential complexity of interactions among hydrology, geomorphology and vector breeding sites by classifying a range of water bodies observed in a catchment in East Africa. Crucially, the mechanisms driving surface water body formation and destruction must be considered explicitly if we are to produce dynamic spatial models of malaria risk at catchment scales.

  17. 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.

  18. 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

    2016-01-01

    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

  19. 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

  20. 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.

  1. 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.

  2. 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.

  3. [Advance in researches on vegetation cover and management factor in the soil erosion prediction model].

    PubMed

    Zhang, Yan; Yuan, Jianping; Liu, Baoyuan

    2002-08-01

    Vegetation cover and land management are the main limiting factors of soil erosion, and quantitative evaluation on the effect of different vegetation on soil erosion is essential to land use and soil conservation planning. The vegetation cover and management factor (C) in the universal soil loss equation (USLE) is an index to evaluate this effect, which has been studied deeply and used widely. However, the C factor study is insufficient in China. In order to strengthen the research of C factor, this paper reviewed the developing progress of C factor, and compared the methods of estimating C value in different USLE versions. The relative studies in China were also summarized from the aspects of vegetation canopy coverage, soil surface cover, and root density. Three problems in C factor study were pointed out. The authors suggested that cropland C factor research should be furthered, and its methodology should be unified in China to represent reliable C values for soil loss prediction and conservation planning.

  4. Application of neural networks to prediction of advanced composite structures mechanical response and behavior

    NASA Technical Reports Server (NTRS)

    Cios, K. J.; Vary, A.; Berke, L.; Kautz, H. E.

    1992-01-01

    Two types of neural networks were used to evaluate acousto-ultrasonic (AU) data for material characterization and mechanical reponse prediction. The neural networks included a simple feedforward network (backpropagation) and a radial basis functions network. Comparisons of results in terms of accuracy and training time are given. Acousto-ultrasonic (AU) measurements were performed on a series of tensile specimens composed of eight laminated layers of continuous, SiC fiber reinforced Ti-15-3 matrix. The frequency spectrum was dominated by frequencies of longitudinal wave resonance through the thickness of the specimen at the sending transducer. The magnitude of the frequency spectrum of the AU signal was used for calculating a stress-wave factor based on integrating the spectral distribution function and used for comparison with neural networks results.

  5. Advanced Prediction of Tool Wear by Taking the Load History into Consideration

    NASA Astrophysics Data System (ADS)

    Ersoy, K.; Nuernberg, G.; Herrmann, G.; Hoffmann, H.

    2007-04-01

    A disadvantage of the conventional methods of simulating the wear occurring in deep drawing processes is that the wear coefficient, and thus wear too, is considered to be constant along loading duration, which, in case of deep drawing, corresponds to sliding distance and number of punch strokes. However, in reality, it is a known fact that wear development is not constant over time. In former studies, the authors presented a method, which makes it possible to consider the number of punch strokes in the simulation of wear. Another enhancement of this method is introduced in this paper. It is proposed to consider wear as a function of wear work instead of the number of punch strokes. Using this approach, the wear coefficients are implemented as a function of wear work and fully take into account the load history of the respective node. This enhancement makes it possible to apply the variable wear coefficients to completely different geometries, where one punch stroke involves different sliding distance or pressure values than the experiments with which the wear coefficients were determined. In this study, deep drawing experiments with a cylindrical cup geometry were carried out, in which the characteristic wear coefficient values as well as their gradients along the life cycle were determined. In this case, the die was produced via rapid tooling techniques. The prediction of tool wear is carried out with REDSY, a wear simulation software which was developed at the Institute of Metal Forming and Casting, TU-Muenchen. The wear predictions made by this software are based on the results of a conventional deep drawing simulation. For the wear modelling a modified Archard model was used.

  6. 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

  7. 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.

  8. Godunov-Based Model of Swash Zone Dynamics to Advance Coastal Flood Prediction

    NASA Astrophysics Data System (ADS)

    Shakeri Majd, M.; Sanders, B. F.

    2012-12-01

    Urbanized lowlands in southern California are defended against coastal flooding by sandy beaches that dynamically adjust to changes in water level and wave conditions, particularly during storm events. Recent research has shown that coastal flood impacts are scaled by the volume of beach overtopping flows, and an improved characterization of dynamic overtopping rates is needed to improve coastal flood forecasting (Gallien et al. 2012). However, uncertainty in the beach slope and height makes it difficult to predict the onset of overtopping and the magnitude of resulting flooding. That is, beaches may evolve significantly over a storm event. Sallenger (Sallenger, 2000) describes Impact Levels to distinguish different impact regimes (swash, collision, overwash and inundation) on dunes and barrier islands. Our goal is to model processes in different regimes as was described by him. Godunov-based models adopt a depth-integrated, two-phase approach and the shallow-water hypothesis to resolve flow and sediment transport in a tightly coupled manner that resolves shocks in the air/fluid and fluid/sediment interface. These models are best known in the context of debris flow modeling where the ability to predict the flow of highly concentrated sediment/fluid mixtures is required. Here, the approach is directed at the swash zone. Existing Godunov-based models are reviewed and shown to have drawbacks relative to wetting and drying and "avalanching"—important processes in the swash zone. This nonphysical erosion can be described as the natural tendency of the schemes to smear out steep bed slopes. To denote and reduce these numerical errors, new numerical methods are presented to address these limitations and the resulting model is applied to a set of laboratory-scale test problems. The shallow-water hypothesis limits the applicability of the model to the swash zone, so it is forced by a time series of water level and cross-shore velocity that accounts for surf zone wave

  9. 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

  10. Recent advances in computational predictions of NMR parameters for the structure elucidation of carbohydrates: methods and limitations.

    PubMed

    Toukach, Filip V; Ananikov, Valentine P

    2013-11-01

    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.

  11. Predictive biomarkers in advance of a companion drug: ahead of their time?

    PubMed

    Kelley, Robin K; Atreya, Chloe; Venook, Alan P; Febbo, Phillip G

    2012-03-01

    Because of a surge in molecular testing capabilities concurrent with the rising numbers of targeted therapies in clinical development, the commercial use of predictive biomarkers before clinical validation is available is a topic of growing relevance to medical oncologists. Increasingly, patients will present questions about, requests for, and results from commercial biomarker tests for their oncologists to address. The sheer numbers of tests reaching the market, along with forecasted American Medical Association reforms in current procedural terminology coding and increasing FDA oversight of in vitro companion diagnostic device development, are likely to draw intense scrutiny to the regulation of commercial molecular testing in the near future, which will also require clinicians to remain abreast of the level of clinical validation of the biomarker tests available in practice. In addition to the direct risks of novel biomarker testing, including financial cost and ethical issues, the indirect risks encompass those associated with any clinical decision based on the biomarker test results. A great need exists for comprehensive and dynamic practice guidelines for all types of biomarker testing according to tumor type. PMID:22393192

  12. The Fitness Landscape of HIV-1 Gag: Advanced Modeling Approaches and Validation of Model Predictions by In Vitro Testing

    PubMed Central

    Omarjee, Saleha; Walker, Bruce D.; Chakraborty, Arup; Ndung'u, Thumbi

    2014-01-01

    Viral immune evasion by sequence variation is a major hindrance to HIV-1 vaccine design. To address this challenge, our group has developed a computational model, rooted in physics, that aims to predict the fitness landscape of HIV-1 proteins in order to design vaccine immunogens that lead to impaired viral fitness, thus blocking viable escape routes. Here, we advance the computational models to address previous limitations, and directly test model predictions against in vitro fitness measurements of HIV-1 strains containing multiple Gag mutations. We incorporated regularization into the model fitting procedure to address finite sampling. Further, we developed a model that accounts for the specific identity of mutant amino acids (Potts model), generalizing our previous approach (Ising model) that is unable to distinguish between different mutant amino acids. Gag mutation combinations (17 pairs, 1 triple and 25 single mutations within these) predicted to be either harmful to HIV-1 viability or fitness-neutral were introduced into HIV-1 NL4-3 by site-directed mutagenesis and replication capacities of these mutants were assayed in vitro. The predicted and measured fitness of the corresponding mutants for the original Ising model (r = −0.74, p = 3.6×10−6) are strongly correlated, and this was further strengthened in the regularized Ising model (r = −0.83, p = 3.7×10−12). Performance of the Potts model (r = −0.73, p = 9.7×10−9) was similar to that of the Ising model, indicating that the binary approximation is sufficient for capturing fitness effects of common mutants at sites of low amino acid diversity. However, we show that the Potts model is expected to improve predictive power for more variable proteins. Overall, our results support the ability of the computational models to robustly predict the relative fitness of mutant viral strains, and indicate the potential value of this approach for understanding viral immune evasion

  13. Executive Summary of the 2015 ISCD Position Development Conference on Advanced Measures From DXA and QCT: Fracture Prediction Beyond BMD.

    PubMed

    Shepherd, John A; Schousboe, John T; Broy, Susan B; Engelke, Klaus; Leslie, William D

    2015-01-01

    There have been many scientific advances in fracture risk prediction beyond bone density. The International Society for Clinical Densitometry (ISCD) convened a Position Development Conference (PDC) on the use of dual-energy X-ray absorptiometry beyond measurement of bone mineral density for fracture risk assessment, including trabecular bone score and hip geometry measures. Previously, no guidelines for nonbone mineral density DXA measures existed. Furthermore, there have been advances in the analysis of quantitative computed tomography (QCT) including finite element analysis, QCT of the hip, DXA-equivalent hip measurements, and opportunistic screening that were not included in the previous ISCD positions. The topics and questions for consideration were developed by the ISCD Board of Directors and the Scientific Advisory Committee and were designed to address the needs of clinical practitioners. Three task forces were created and asked to conduct comprehensive literature reviews to address specific questions. The task forces included participants from many countries and a variety of interests including academic institutions and private health care delivery organizations. Representatives from industry participated as consultants to the task forces. Task force reports with proposed position statements were then presented to an international panel of experts with backgrounds in bone densitometry. The PDC was held in Chicago, Illinois, USA, contemporaneously with the Annual Meeting of the ISCD, February 26 through February 28, 2015. This Executive Summary describes the methodology of the 2015 PDC on advanced measures from DXA and QCT and summarizes the approved official positions. Six separate articles in this issue will detail the rationale, discussion, and additional research topics for each question the task forces addressed.

  14. 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.

  15. The value of lactate dehydrogenase serum levels as a prognostic and predictive factor for advanced pancreatic cancer patients receiving sorafenib

    PubMed Central

    Faloppi, Luca; Bianconi, Maristella; Giampieri, Riccardo; Sobrero, Alberto; Labianca, Roberto; Ferrari, Daris; Barni, Sandro; Aitini, Enrico; Zaniboni, Alberto; Boni, Corrado; Caprioni, Francesco; Mosconi, Stefania; Fanello, Silvia; Berardi, Rossana; Bittoni, Alessandro; Andrikou, Kalliopi; Cinquini, Michela; Torri, Valter; Scartozzi, Mario; Cascinu, Stefano

    2015-01-01

    Although lactate dehydrogenase (LDH) serum levels, indirect markers of angiogenesis, are associated with a worse outcome in several tumours, their prognostic value is not defined in pancreatic cancer. Moreover, high levels are associated even with a lack of efficacy of tyrosine kinase inhibitors, contributing to explain negative results in clinical trials. We assessed the role of LDH in advanced pancreatic cancer receiving sorafenib. Seventy-one of 114 patients included in the randomised phase II trial MAPS (chemotherapy plus or not sorafenib) and with available serum LDH levels, were included in this analysis. Patients were categorized according to serum LDH levels (LDH ≤vs.> upper normal rate). A significant difference was found in progression free survival (PFS) and in overall survival (OS) between patients with LDH values under or above the cut-off (PFS: 5.2 vs. 2.7 months, p = 0.0287; OS: 10.7 vs. 5.9 months, p = 0.0021). After stratification according to LDH serum levels and sorafenib treatment, patients with low LDH serum levels treated with sorafenib showed an advantage in PFS (p = 0.05) and OS (p = 0.0012). LDH appears to be a reliable parameter to assess the prognosis of advanced pancreatic cancer patients, and it may be a predictive parameter to select patients candidate to receive sorafenib. PMID:26397228

  16. The value of lactate dehydrogenase serum levels as a prognostic and predictive factor for advanced pancreatic cancer patients receiving sorafenib.

    PubMed

    Faloppi, Luca; Bianconi, Maristella; Giampieri, Riccardo; Sobrero, Alberto; Labianca, Roberto; Ferrari, Daris; Barni, Sandro; Aitini, Enrico; Zaniboni, Alberto; Boni, Corrado; Caprioni, Francesco; Mosconi, Stefania; Fanello, Silvia; Berardi, Rossana; Bittoni, Alessandro; Andrikou, Kalliopi; Cinquini, Michela; Torri, Valter; Scartozzi, Mario; Cascinu, Stefano

    2015-10-27

    Although lactate dehydrogenase (LDH) serum levels, indirect markers of angiogenesis, are associated with a worse outcome in several tumours, their prognostic value is not defined in pancreatic cancer. Moreover, high levels are associated even with a lack of efficacy of tyrosine kinase inhibitors, contributing to explain negative results in clinical trials. We assessed the role of LDH in advanced pancreatic cancer receiving sorafenib. Seventy-one of 114 patients included in the randomised phase II trial MAPS (chemotherapy plus or not sorafenib) and with available serum LDH levels, were included in this analysis. Patients were categorized according to serum LDH levels (LDH ≤ vs.> upper normal rate). A significant difference was found in progression free survival (PFS) and in overall survival (OS) between patients with LDH values under or above the cut-off (PFS: 5.2 vs. 2.7 months, p = 0.0287; OS: 10.7 vs. 5.9 months, p = 0.0021). After stratification according to LDH serum levels and sorafenib treatment, patients with low LDH serum levels treated with sorafenib showed an advantage in PFS (p = 0.05) and OS (p = 0.0012). LDH appears to be a reliable parameter to assess the prognosis of advanced pancreatic cancer patients, and it may be a predictive parameter to select patients candidate to receive sorafenib. PMID:26397228

  17. Oscillations in land surface hydrological cycle

    NASA Astrophysics Data System (ADS)

    Labat, D.

    2006-02-01

    Hydrological cycle is the perpetual movement of water throughout the various component of the global Earth's system. Focusing on the land surface component of this cycle, the determination of the succession of dry and humid periods is of high importance with respect to water resources management but also with respect to global geochemical cycles. This knowledge requires a specified estimation of recent fluctuations of the land surface cycle at continental and global scales. Our approach leans towards a new estimation of freshwater discharge to oceans from 1875 to 1994 as recently proposed by Labat et al. [Labat, D., Goddéris, Y., Probst, JL, Guyot, JL, 2004. Evidence for global runoff increase related to climate warming. Advances in Water Resources, 631-642]. Wavelet analyses of the annual freshwater discharge time series reveal an intermittent multiannual variability (4- to 8-y, 14- to 16-y and 20- to 25-y fluctuations) and a persistent multidecadal 30- to 40-y variability. Continent by continent, reasonable relationships between land-water cycle oscillations and climate forcing (such as ENSO, NAO or sea surface temperature) are proposed even though if such relationships or correlations remain very complex. The high intermittency of interannual oscillations and the existence of persistent multidecadal fluctuations make prediction difficult for medium-term variability of droughts and high-flows, but lead to a more optimistic diagnostic for long-term fluctuations prediction.

  18. 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

  19. 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

  20. 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

  1. The CUAHSI Community Hydrologic Information System

    NASA Astrophysics Data System (ADS)

    Tarboton, D. G.; Maidment, D. R.; Zaslavsky, I.; Ames, D. P.; Goodall, J. L.; Hooper, R. P.; Horsburgh, J. S.

    2011-12-01

    Hydrologic information is collected by many individuals and organizations in government and academia for many purposes, including general monitoring of the condition of the water environment and specific investigations of hydrologic processes. Comprehensive understanding of hydrology requires integration of this information from multiple sources. The Consortium of Universities for the Advancement of Hydrologic Science, Inc. (CUAHSI) has developed a Hydrologic Information System (HIS) to provide better access to data by enabling the publication, cataloging, discovery and retrieval of hydrologic data using web services. This paper describes HIS capability developed to promote data sharing and interoperability in the Hydrologic Sciences with the purpose of enabling hydrologic analyses that integrate data from multiple sources. The CUAHSI HIS is an Internet based system comprised of hydrologic databases and servers connected through web services as well as software for data publication, discovery and access. The system that has been developed provides new opportunities for the water research community to approach the management, publication, and analysis of their data systematically. The system's flexibility in storing and enabling public access to similarly formatted data and metadata has created a community data resource from public and academic data that might otherwise have been confined to the private files of agencies or individual investigators. Additionally, HIS provides an analysis environment within which data from multiple sources can be discovered, accessed and integrated. The CUAHSI HIS serves as a prototype for the infrastructure to support a network of large scale environmental observatories or research watersheds, and indeed, components of the CUAHSI HIS have now been adopted or modified for use within the Critical Zone Observatory (CZO) network. Software and further information may be obtained from http://his.cuahsi.org.

  2. 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 understand the climatology of optical turbulence at such locations. In many cases, it is impractical and expensive to setup instrumentation to characterize the climatology of OT, so numerical simulations become a less expensive and convenient alternative. The strength of OT is characterized by the refractive index structure function Cn2, which in turn is used to calculate atmospheric seeing parameters. While attempts have been made to characterize Cn2 using empirical models, Cn2 can be calculated more directly from Numerical Weather Prediction (NWP) simulations using pressure, temperature, thermal stability, vertical wind shear, turbulent Prandtl number, and turbulence kinetic energy (TKE). In this work we use the Weather Research and Forecast (WRF) NWP model to generate Cn2 climatologies in the planetary boundary layer and free atmosphere, allowing for both point-to-point and ground-to-space seeing estimates of the Fried Coherence length (ro) and other seeing parameters. Simulations are performed using a multi-node linux cluster using the Intel chip architecture. The WRF model is configured to run at 1km horizontal resolution and centered on the Mauna Loa Observatory (MLO) of the Big Island. The vertical resolution varies from 25 meters in the boundary layer to 500 meters in the stratosphere. The model top is 20 km. The Mellor-Yamada-Janjic (MYJ) TKE scheme has been modified to diagnose the turbulent Prandtl number as a function of the Richardson number, following observations by Kondo and others. This modification

  3. New hydrology bibliography available

    NASA Astrophysics Data System (ADS)

    Calder, Jan R.

    Hydrotitles is the first bibliography to be published specifically covering hydrology and hydrology-related sciences. With the increasing numbers of journals and publications in this area, Hydrotitles fills a long-felt need for assistance in guiding the practitioner through the mass of literature to publications that are relevant to his or her needs. The bimonthly publication is published by Geosystems (P.O. Box 40, Didcot, Oxon OX11 9BX, United Kingdom; ISSN 0953-7589, $150 per year.)Entries are arranged by a subject hierarchy according to Geosaurus, Geosystem's thesaurus of geoscience. The main subject headings are hydrology; hydrogeology; hydraulics; experimental hydrology and hydrometry; numerical hydrology; hydrogeochemistry; water quality, treatment, supply and management; environmental hydrology, water pollution and acid rain; fluvial geomorphology; glaciology; climate change; energy; equipment; computer methods; policy and law; limnology; and engineering. There follows a locational index, a stratigraphical index, a geographical index, and an author index.

  4. Predictions in ungauged basins - where do we stand?

    NASA Astrophysics Data System (ADS)

    Blöschl, Günter

    2016-05-01

    The spatial dimensions of water management heavily rely on accurate hydrological estimates in the landscape. This has exactly been the focus of the Predictions in Ungauged Basins (PUB) initiative of the IAHS. The initiative has significantly advanced the science by furthering process understanding and estimation methods, and by synthesising the knowledge across processes, places and scales. Ongoing research on PUB is increasingly treating water management as an intrinsic part of the hydrological cycle and is developing processes understanding and methods to account for the feedbacks between humans and water in the landscape.

  5. Advanced glycation end products and their circulating receptors predict cardiovascular disease mortality in older community-dwelling women

    PubMed Central

    Semba, Richard D.; Ferrucci, Luigi; Sun, Kai; Beck, Justine; Dalal, Mansi; Varadhan, Ravi; Walston, Jeremy; Guralnik, Jack M.; Fried, Linda P.

    2008-01-01

    Objective To characterize the relationship between advanced glycation end products (AGEs) and circulating receptors for AGEs (RAGE) with cardiovascular disease mortality. Methods The relationships between serum AGEs, total RAGE (sRAGE), and endogenous secretory RAGE (esRAGE), and mortality were characterized in 559 community-dwelling women, ≥65 years, in Baltimore, Maryland. Results During 4.5 years of follow-up, 123 (22%) women died, of whom 54 died with cardiovascular disease. The measure of serum AGEs was carboxymethyl-lysine (CML), a dominant AGE. Serum CML predicted cardiovascular disease mortality (Hazards Ratio [H.R.] for highest versus lower three quartiles 1.94, 95% Confidence Interval [C.I.] 1.08-3.48, P = 0.026), after adjusting for age, race, body mass index, and renal insufficiency. Serum sRAGE (ng/mL) and esRAGE (ng/mL) predicted cardiovascular disease mortality (H.R. per 1 Standard Deviation [S.D.] 1.27, 95% C.I. 0.98-1.65, P = 0.07; H.R. 1.28, 95% C.I. 1.02-1.63, P = 0.03), after adjusting for the same covariates. Among non-diabetic women, serum CML, sRAGE, and esRAGE, respectively, predicted cardiovascular disease mortality (H.R. for highest versus lower three quartiles, 2.29, 95% C.I. 1.21-4.34, P = 0.01; H.R. per 1 S.D., 1.24, 95% C.I. 0.92-1.65, P = 0.16; H.R. per 1 S.D. 1.45, 95% C.I. 1.08-1.93, P = 0.01), after adjusting for the same covariates. Conclusions High circulating AGEs and RAGE predict cardiovascular disease mortality among older community-dwelling women. AGEs are a potential target for interventions, as serum AGEs can be lowered by change in dietary pattern and pharmacological treatment. PMID:19448391

  6. Prognostic and Predictive Value of Baseline and Posttreatment Molecular Marker Expression in Locally Advanced Rectal Cancer Treated With Neoadjuvant Chemoradiotherapy

    SciTech Connect

    Bertolini, Federica . E-mail: bertolini.federica@policlinico.mo.it; Bengala, Carmelo; Losi, Luisa; Pagano, Maria; Iachetta, Francesco; Dealis, Cristina; Jovic, Gordana; Depenni, Roberta; Zironi, Sandra; Falchi, Anna Maria; Luppi, Gabriele; Conte, Pier Franco

    2007-08-01

    Purpose: To evaluate expression of a panel of molecular markers, including p53, p21, MLH1, MSH2, MIB-1, thymidylate synthase, epidermal growth factor receptor (EGFR), and tissue vascular endothelial growth factor (VEGF), before and after treatment in patients treated with neoadjuvant chemoradiotherapy for locally advanced rectal cancer, to correlate the constitutive profile and dynamics of expression with pathologic response and outcome. Methods and Materials: Expression of biomarkers was evaluated by immunohistochemistry in tumor samples from 91 patients with clinical Stage II and III rectal cancer treated with preoperative pelvic radiotherapy (50 Gy) plus concurrent 5-fluorouracil by continuous intravenous infusion. Results: A pathologic complete remission was observed in 14 patients (15.4%). Patients with MLH1-positive tumors had a higher pathologic complete response rate (24.3% vs. 9.4%; p = 0.055). Low expression of constitutive p21, absence of EGFR expression after chemoradiotherapy, and high Dworak's tumor regression grade (TRG) were significantly associated with improved disease-free survival and overall survival. A high MIB-1 value after chemoradiotherapy was significantly associated with worse overall survival. Multivariate analysis confirmed the prognostic value of constitutive p21 expression as well as EGFR expression and MIB-1 value after chemoradiotherapy among patients not achieving TRG 3-4. Conclusions: In our study, we observed the independent prognostic value of EGFR expression after chemoradiotherapy on disease-free survival. Moreover, our study suggests that a constitutive high p21 expression and a high MIB-1 value after neoadjuvant chemoradiotherapy treatment could predict worse outcome in locally advanced rectal cancer.

  7. Primary Tumor Necrosis Predicts Distant Control in Locally Advanced Soft-Tissue Sarcomas After Preoperative Concurrent Chemoradiotherapy

    SciTech Connect

    MacDermed, Dhara M.; Miller, Luke L.; Peabody, Terrance D.; Simon, Michael A.; Luu, Hue H.; Haydon, Rex C.; Montag, Anthony G.; Undevia, Samir D.

    2010-03-15

    Purpose: Various neoadjuvant approaches have been evaluated for the treatment of locally advanced soft-tissue sarcomas. This retrospective study describes a uniquely modified version of the Eilber regimen developed at the University of Chicago. Methods and Materials: We treated 34 patients (28 Stage III and 6 Stage IV) with locally advanced soft-tissue sarcomas of an extremity between 1995 and 2008. All patients received preoperative therapy including ifosfamide (2.5 g/m2 per day for 5 days) with concurrent radiation (28 Gy in 3.5-Gy daily fractions), sandwiched between various chemotherapy regimens. Postoperatively, 47% received further adjuvant chemotherapy. Results: Most tumors (94%) were Grade 3, and all were T2b, with a median size of 10.3 cm. Wide excision was performed in 29 patients (85%), and 5 required amputation. Of the resected tumor specimens, 50% exhibited high (>=90%) treatment-induced necrosis and 11.8% had a complete pathologic response. Surgical margins were negative in all patients. The 5-year survival rate was 42.3% for all patients and 45.2% for Stage III patients. For limb-preservation patients, the 5-year local control rate was 89.0% and reoperation was required for wound complications in 17.2%. The 5-year freedom-from-distant metastasis rate was 53.4% (Stage IV patients excluded), and freedom from distant metastasis was superior if treatment-induced tumor necrosis was 90% or greater (84.6% vs. 19.9%, p = 0.02). Conclusions: This well-tolerated concurrent chemoradiotherapy approach yields excellent rates of limb preservation and local control. The resulting treatment-induced necrosis rates are predictive of subsequent metastatic risk, and this information may provide an opportunity to guide postoperative systemic therapies.

  8. 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...

  9. 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.

  10. Hydrologic issues associated with nuclear waste repositories

    NASA Astrophysics Data System (ADS)

    Tsang, Chin-Fu; Neretnieks, Ivars; Tsang, Yvonne

    2015-09-01

    Significant progress in hydrology, especially in subsurface flow and solute transport, has been made over the last 35 years because of sustained interest in underground nuclear waste repositories. The present paper provides an overview of the key hydrologic issues involved, and to highlight advances in their understanding and treatment because of these efforts. The focus is not on the development of radioactive waste repositories and their safety assessment, but instead on the advances in hydrologic science that have emerged from such studies. Work and results associated with three rock types, which are being considered to host the repositories, are reviewed, with a different emphasis for each rock type. The first rock type is fractured crystalline rock, for which the discussion will be mainly on flow and transport in saturated fractured rock. The second rock type is unsaturated tuff, for which the emphasis will be on flow from the shallow subsurface through the unsaturated zone to the repository. The third rock type is clay-rich formations, whose permeability is very low in an undisturbed state. In this case, the emphasis will be on hydrologic issues that arise from mechanical and thermal disturbances; i.e., on the relevant coupled thermo-hydro-mechanical processes. The extensive research results, especially those from multiyear large-scale underground research laboratory investigations, represent a rich body of information and data that can form the basis for further development in the related areas of hydrologic research.

  11. Temperature and Material Flow Prediction in Friction-Stir Spot Welding of Advanced High-Strength Steel

    SciTech Connect

    Miles, Michael; Karki, U.; Hovanski, Yuri

    2014-10-01

    Friction-stir spot welding (FSSW) has been shown to be capable of joining advanced high-strength steel, with its flexibility in controlling the heat of welding and the resulting microstructure of the joint. This makes FSSW a potential alternative to resistance spot welding if tool life is sufficiently high, and if machine spindle loads are sufficiently low that the process can be implemented on an industrial robot. Robots for spot welding can typically sustain vertical loads of about 8 kN, but FSSW at tool speeds of less than 3000 rpm cause loads that are too high, in the range of 11–14 kN. Therefore, in the current work, tool speeds of 5000 rpm were employed to generate heat more quickly and to reduce welding loads to acceptable levels. Si3N4 tools were used for the welding experiments on 1.2-mm DP 980 steel. The FSSW process was modeled with a finite element approach using the Forge* software. An updated Lagrangian scheme with explicit time integration was employed to predict the flow of the sheet material, subjected to boundary conditions of a rotating tool and a fixed backing plate. Material flow was calculated from a velocity field that is two-dimensional, but heat generated by friction was computed by a novel approach, where the rotational velocity component imparted to the sheet by the tool surface was included in the thermal boundary conditions. An isotropic, viscoplastic Norton-Hoff law was used to compute the material flow stress as a function of strain, strain rate, and temperature. The model predicted welding temperatures to within percent, and the position of the joint interface to within 10 percent, of the experimental results.

  12. Data Access System for Hydrology

    NASA Astrophysics Data System (ADS)

    Whitenack, T.; Zaslavsky, I.; Valentine, D.; Djokic, D.

    2007-12-01

    As part of the CUAHSI HIS (Consortium of Universities for the Advancement of Hydrologic Science, Inc., Hydrologic Information System), the CUAHSI HIS team has developed Data Access System for Hydrology or DASH. DASH is based on commercial off the shelf technology, which has been developed in conjunction with a commercial partner, ESRI. DASH is a web-based user interface, developed in ASP.NET developed using ESRI ArcGIS Server 9.2 that represents a mapping, querying and data retrieval interface over observation and GIS databases, and web services. This is the front end application for the CUAHSI Hydrologic Information System Server. The HIS Server is a software stack that organizes observation databases, geographic data layers, data importing and management tools, and online user interfaces such as the DASH application, into a flexible multi- tier application for serving both national-level and locally-maintained observation data. The user interface of the DASH web application allows online users to query observation networks by location and attributes, selecting stations in a user-specified area where a particular variable was measured during a given time interval. Once one or more stations and variables are selected, the user can retrieve and download the observation data for further off-line analysis. The DASH application is highly configurable. The mapping interface can be configured to display map services from multiple sources in multiple formats, including ArcGIS Server, ArcIMS, and WMS. The observation network data is configured in an XML file where you specify the network's web service location and its corresponding map layer. Upon initial deployment, two national level observation networks (USGS NWIS daily values and USGS NWIS Instantaneous values) are already pre-configured. There is also an optional login page which can be used to restrict access as well as providing a alternative to immediate downloads. For large request, users would be notified via

  13. 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…

  14. 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,…

  15. Improving USGS National Hydrologic Model Parameterization with Satellite-Based Phenology Products

    NASA Astrophysics Data System (ADS)

    Micheletty, P. D.; Hogue, T. S.; Hay, L.; Markstrom, S. L.; Regan, R. S.

    2014-12-01

    Hydrologists and water resource engineers are simulating hydrologic processes at the continental scale assisted by the advancement of high-performance computing and the accessibility of large-scale climate and hydrologic datasets. The United States Geological Survey (USGS) is developing a National Hydrologic Model (NHM) that supports coordinated, comprehensive, and consistent hydrologic model development and simulations of the conterminous United States (CONUS). The goal of this project is to improve model parameterization and ultimately streamflow predictions across the CONUS using remotely sensed data products. The current work will specifically improve estimates of the growing season in the NHM through the integration of satellite-based phenology products developed at the USGS Earth Resources Observation and Science (EROS) Center. Currently, the NHM defines the growing season using one of three temperature-index methods: 1) first and last freezing air temperatures; 2) temperature threshold for a specified begin and end month; and 3) dynamic specification. The USGS/EROS RSP products are based on a timeseries analysis of the normalized difference vegetation index (NDVI) from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors. Using the phenological metrics derived from AVHRR, we define a new growing season parameter set for the CONUS from 1989 to 2013, which ultimately will enhance estimations of daily transpiration rates throughout the model domain. Using default temperature-index based estimates of growing season and RSP derived estimates, we provide statistical evaluation and comparison of the NHM simulations related to growing season. The RSP growing season dates may improve model hydrologic simulations especially in drought periods when water availability, demand, and usage are critical, or in areas where the temperature-index based growing season estimates lack skill, such as some

  16. Environmental Observatories and Hydrologic Modeling

    NASA Astrophysics Data System (ADS)

    Hooper, R. P.; Duncan, J. M.

    2006-12-01

    During the past several years, the environmental sciences community has been attempting to design large- scale obsevatories that will transform the science. A watershed-based observatory has emerged as an effective landscape unit for a broad range of environmental sciences and engineering. For an effective observatory, modeling is a central requirement because models are precise statements of the hypothesized conceptual organization of watersheds and of the processes believed to be controlling hydrology of the watershed. Furthermore, models can serve to determine the value of existing data and the incremental value of any additional data to be collected. Given limited resources, such valuation is mandatory for an objective design of an observatory. Modeling is one part of a "digital watershed" that must be constructed for any observatory, a concept that has been developed by the CUAHSI Hydrologic Information Systems project. A digital watershed has three functions. First, it permits assembly of time series (such as stream discharge or precipitation measurements), static spatial coverages (such as topography), and dynamic fields (such as precipitation radar and other remotely sensed data). Second, based upon this common data description, a digital observatory permits multiple conceptualizations of the observatory to be created and to be stored. These conceptualizations could range from lumped box-and-arrow watershed models, to semi-distributed topographically based models, to three-dimensional finite element models. Finally, each conceptualization can lead to multiple models--that is, a set of equations that quantitatively describe hydrologic (or biogeochemical or geomorphologic) processes through libraries of tools that can be linked as workflow sequences. The advances in cyberinfrastructure that allow the storage of multiple conceptualizations and multiple model formulations of these conceptualizations promise to accelerate advances in environmental science both

  17. Significance of hydrological model choice and land use changes when doing climate change impact assessment

    NASA Astrophysics Data System (ADS)

    Bjørnholt Karlsson, Ida; Obel Sonnenborg, Torben; Refsgaard, Jens Christian; Høgh Jensen, Karsten

    2014-05-01

    Uncertainty in impact studies arises both from Global Climate Models (GCM), emission projections, statistical downscaling, Regional Climate Models (RCM), hydrological models and calibration techniques (Refsgaard et al. 2013). Some of these uncertainties have been evaluated several times in the literature; however few studies have investigated the effect of hydrological model choice on the assessment results (Boorman & Sefton 1997; Jiang et al. 2007; Bastola et al. 2011). These studies have found that model choice results in large differences, up to 70%, in the predicted discharge changes depending on the climate input. The objective of the study is to investigate the impact of climate change on hydrology of the Odense catchment, Denmark both in response to (a) different climate projections (GCM-RCM combinations); (b) different hydrological models and (c) different land use scenarios. This includes: 1. Separation of the climate model signal; the hydrological model signal and the land use signal 2. How do the different hydrological components react under different climate and land use conditions for the different models 3. What land use scenario seems to provide the best adaptation for the challenges of the different future climate change scenarios from a hydrological perspective? Four climate models from the ENSEMBLES project (Hewitt & Griggs 2004): ECHAM5 - HIRHAM5, ECHAM5 - RCA3, ARPEGE - RM5.1 and HadCM3 - HadRM3 are used, assessing the climate change impact in three periods: 1991-2010 (present), 2041-2060 (near future) and 2081-2100 (far future). The four climate models are used in combination with three hydrological models with different conceptual layout: NAM, SWAT and MIKE SHE. Bastola, S., C. Murphy and J. Sweeney (2011). "The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments." Advances in Water Resources 34: 562-576. Boorman, D. B. and C. E. M. Sefton (1997). "Recognising the uncertainty in the

  18. Hydrologic Ontology for the Web

    NASA Astrophysics Data System (ADS)

    Bermudez, L. E.; Piasecki, M.

    2003-12-01

    This poster presents the conceptual development of a Hydrologic Ontology for the Web (HOW) that will facilitate data sharing among the hydrologic community. Hydrologic data is difficult to share because of its predicted vast increase in data volume, the availability of new measurement technologies and the heterogeneity of information systems used to produced, store, retrieved and used the data. The augmented capacity of the Internet and the technologies recommended by the W3C, as well as metadata standards provide sophisticated means to make data more usable and systems to be more integrated. Standard metadata is commonly used to solve interoperability issues. For the hydrologic field an explicit metadata standard does not exist, but one could be created extending metadata standards such as the FGDC-STD-001-1998 or ISO 19115. Standard metadata defines a set of elements required to describe data in a consistent manner, and their domains are sometimes restricted by a finite set of values or controlled vocabulary (e.g. code lists in ISO/DIS 19115). This controlled vocabulary is domain specific varying from one information community to another, allowing dissimilar descriptions to similar data sets. This issue is sometimes called semantic non-interoperability or semantic heterogeneity, and it is usually the main problem when sharing data. Explicit domain ontologies could be created to provide semantic interoperability among heterogeneous information communities. Domain ontologies supply the values for restricted domains of some elements in the metadata set and the semantic mapping with other domain ontologies. To achieve interoperability between applications that exchange machine-understandable information on the Web, metadata is expressed using Resource Description Framework (RDF) and domain ontologies are expressed using the Ontology Web Language (OWL), which is also based on RDF. A specific OWL ontology for hydrology is HOW. HOW presents, using a formal syntax, the

  19. Modelling the hydrological cycle in assessments of climate change

    NASA Technical Reports Server (NTRS)

    Rind, D.; Rosenzweig, C.; Goldberg, R.

    1992-01-01

    The predictions of climate change studies depend crucially on the hydrological cycles embedded in the different models used. It is shown here that uncertainties in hydrological processes and inconsistencies in both climate and impact models limit confidence in current assessments of climate change. A future course of action to remedy this problem is suggested.

  20. The Western States Water Mission: A Hyper-Resolution Hydrological Modeling and Data Integration Platform

    NASA Astrophysics Data System (ADS)

    Famiglietti, James; Basilio, Ralph; Trangsrud, Amy; Andreadis, Kostas; Cricthon, Dan; David, Cedric; Farr, Thomas; Malhotra, Shan; Neff, Kirstin; Reager, John

    2016-04-01

    Hydrological remote sensing has advanced significantly over the last decade, and will continue to grow with number of recent and near-future launched. Arguably, a platform for synthesizing remote observations is an important step towards improved modeling, understanding and prediction of terrestrial hydrology. In this presentation we describe the new NASA Western States Water Mission, a high-resolution, catchment-based modeling and data assimilation platform implemented for the western United States. Model structure will be described, as well as early results that include assimilation of satellite snow observations. A key feature of model development has been its treatment as a 'flight project' which enables leveraging of important NASA systems engineering and project management expertise.