Confronting input, parameter, structural, and measurement uncertainty in multi-site multiple-response watershed modeling using Bayesian inferences

2012 Fall.Includes bibliographical references.Simulation modeling is arguably one of the most powerful scientific tools available to address questions, assess alternatives, and support decision making for environmental management. Watershed models are used to describe and understand hydrologic and water quality responses of land and water systems under prevailing and projected conditions. Since the promulgation of the Clean Water Act of 1972 in the United States, models are increasingly used to evaluate potential impacts of mitigation strategies and support policy instruments for pollution control such as the Total Maximum Daily Load (TMDL) program. Generation, fate, and transport of water and contaminants within watershed systems comprise a highly complex network of interactions. It is difficult, if not impossible, to capture all important processes within a modeling framework. Although critical natural processes and management actions can be resolved at varying spatial and temporal scales, simulation models will always remain an approximation of the real system. As a result, the use of models with limited knowledge of the system and model structure is fraught with uncertainty. Wresting environmental decisions from model applications must consider factors that could conspire against credible model outcomes. The main goal of this study is to develop a novel Bayesian-based computational framework for characterization and incorporation of uncertainties from forcing inputs, model parameters, model structures, and measured responses in the parameter estimation process for multisite multiple-response watershed modeling. Specifically, the following objectives are defined: (i) to evaluate the effectiveness and efficiency of different computational strategies in sampling the model parameter space; (ii) to examine the role of measured responses at various locations in the stream network as well as intra-watershed processes in enhancing the model performance credibility; (iii) to facilitate combining predictions from competing model structures; and (iv) to develop a statistically rigorous procedure for incorporation of errors from input, parameter, structural and measurement sources in the parameter estimation process. The proposed framework was applied for simulating streamflow and total nitrogen at multiple locations within a 248 square kilometer watershed in the Midwestern United States using the Soil and Water Assessment Tool (SWAT). Results underlined the importance of simultaneous treatment of all sources of uncertainty for parameter estimation. In particular, it became evident that incorporation of input uncertainties was critical for determination of model structure for runoff generation and also representation of intra-watershed processes such as denitrification rate and dominant pathways for transport of nitrate within the system. The computational framework developed in this study can be implemented to establish credibility for modeling watershed processes. More importantly, the framework can reveal how collection of data from different responses at different locations within a watershed system of interest would enhance the predictive capability of watershed models by reducing input, parametric, structural, and measurement uncertainties

Melanocortin Administration to the Ventral Tegmental Area Alters Homeostatic and Hedonic Feeding

Dopamine neurons of ventral tegmental area (VTA) are critical for control of homeostatic feeding, which relates to food intake necessary for maintaining normal physiological function. It also plays an important role in hedonic or ‘reward’ feeding. Alteration of mesolimbic dopamine pathways can change both baseline homeostatic and reward feeding. The melanocortin system of the hypothalamus also is important for control of feeding, and recently it has been shown that melanocortins can modulate the food intake by acting at dopamine pathways. Here, we tested whether injection of melanocortin receptor agonists into the VTA also affected reward feeding. Injection of melanocortin receptor agonists into the VTA decreased consumption of rewarding sucrose solutions (hedonic feeding), in addition to the expected reductions in normal chow intake (homeostatic feeding). These studies will give a better understanding of the mechanisms regulate acutely food intake and may have implication for treating obesity

An Introduction to the Hyperspace of Hargreaves-Samani Reference Evapotranspiration

Climate change has been shown to directly influence evapotranspiration, which is one of the crucial watershed processes. The common approach to its calculation is via mathematical equations, such as 1985 Hargreaves-Samani (HS85). It computes reference evapotranspiration (ETo) through three climatic variables and one constant: RA (extra-terrestrial radiation), TC (mean temperature), TR (temperature range) and KR (empirical coefficient). To make HS85 more accurate, one of its authors proposed an equation for KR as a function of TR in 2000 (HS00). Both models are 4D and their internal behaviours are difficult to understand, hence, the data driven applications prevalent among experts and managers. In this study, we introduce an innovative research by trying to respond to two questions. What are the relationships between TC and TR? What are the internal patterns of HS hyperspace (4D domain) and the changes in ETo possibilities of the two models? In the proposed approach, thresholds for the four variables are utilized to cover majority of the agroclimatic situations in the world and the hyperspace is discretized with more than 50,000 calculation nodes. The ETo results show that under various climatic conditions, the behaviour of HS is nonlinear (more for HS00) leading to an increased uncertainty particularly for data driven applications. TC and TR show patterns useful for regions with less data.This work was partially financed by (a) the Portuguese Foundation for Science and Technology (FCT) under the contract UID/ECI/04047/2013 for the Centre of Territory, Environment and Construction(CTAC) of the University of Minho, (b) project POCI-01-0145-FEDER-028247 - funded by FEDER funds throughCOMPETE2020—Programa Operacional Competitividade e Internacionalização (POCI) and by national funds (PIDDAC) through FCT/MCTES. Acknowledgments: The authors appreciate the cooperation of the Cluster computing facilities of the University of Minho developed under the Project ‘Search-ON2: Revitalization of HPC infrastructure of UMinho’ (NORTE-07-0162-FEDER-000086), co-funded by the North Portugal Regional Operational Programme (ON.2—O Novo Norte), under the National Strategic Reference Framework (NSRF), through the European Regional Development Fund (ERDF).info:eu-repo/semantics/publishedVersio

The Clinical Application of Anterolateral Thigh Flap

The anterolateral thigh flap can provide a large skin paddle nourished by a long and large-caliber pedicle and can be harvested by two-team work. Most importantly, the donor-site morbidity is minimal. However, the anatomic variations decreased its popularity. By adapting free-style flap concepts, such as preoperative mapping of the perforators and being familiar with retrograde perforator dissection, this disadvantage had been overcome gradually. Furthermore, several modifications widen its clinical applications: the fascia lata can be included for sling or tendon reconstruction, the bulkiness could be created by including vastus lateralis muscle or deepithelization of skin flap, the pliability could be increased by suprafascial dissection or primary thinning, the pedicle length could be lengthening by proximally eccentric placement of the perforator, and so forth. Combined with these technical and conceptual advancements, the anterolateral thigh flap has become the workhorse flap for soft-tissue reconstructions from head to toe

Evaluation of CFSR, TMPA 3B42 and ground-based rainfall data as input for hydrological models, in data-scarce regions: The upper Blue Nile Basin, Ethiopia

Accurate prediction of hydrological models requires accurate spatial and temporal distribution of rainfall. In developing countries, the network of observation stations for rainfall is sparse and unevenly distributed. Satellite-based products have the potential to overcome this shortcoming. The objective of this study is to compare the advantages and the limitation of commonly used high-resolution satellite rainfall products (Climate Forecast System Reanalysis (CFSR) and Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis (TMPA) 3B42 version 7) as input to hydrological models as compared to sparsely and densely populated network of rain gauges. We used two (semi-distributed) hydrological models that performed well in the Ethiopian highlands: Hydrologiska Byråns Vattenbalansavdelning (HBV) and Parameter Efficient Distributed (PED). The rainfall products were tested in two watersheds: Gilgel Abay with a relatively dense network of rain gauge stations and Main Beles with a relatively scarce network, both are located in the Upper Blue Nile Basin. The results indicated that TMPA 3B42 was not be able to capture the gauged rainfall temporal variation in both watersheds and was not tested further. CFSR over predicted the rainfall pattern slightly. Both the gauged and the CFSR reanalysis data were able to reproduce the streamflow well for both models and both watershed when calibrated separately to the discharge data. Using the calibrated model parameters of gauged rainfall dataset together with the CFSR rainfall, the stream discharge for the Gilgel Abay was reproduced well but the discharge of the Main Beles was captured poorly partly because of the poor accuracy of the gauged rainfall dataset with none of the rainfall stations located inside the watershed. HBV model performed slightly better than the PED model, but the parameter values of the PED could be identified with the features of the landscape

Evaluating hydrologic responses to soil characteristics using SWAT model in a paired-watersheds in the Upper Blue Nile Basin

Watershed responses are affected by the watershed characteristics and rainfall events. The characteristics of soil layers are among the fundamental characteristics of a watershed and they are input to hydrologic modeling similar to topography and land use/cover. Although the roles of soils have been perceived, there are limited studies that quantify the role of soil characteristics on watershed runoff responses due to the lack of field datasets. Using two adjacent watersheds (Ribb and Gumara) which have a significant different runoff response with a similar characterstics except geological settings (including soil characteristics), we studied the effects of soil characteristics on runoff and water balance. The Soil and Water Assessment Tool (SWAT) was used to simulate the surface runoff response at the outlet of the watershed and the optimal model parameters distribution was tested with a non-parametric test for similarity. Results indicated that SWAT model captured the observed flow very well with a Nash-Sutcliffe Efficiency (NSE) of greater than 0.74 and with a PBIAS of less than 10% for both calibration and validation period. The comparison of the optimal model parameter distributions of the SWAT model showed that the watershed characteristics could be uniquely defined and represented by a hydrologic model due to the differences in the soils. Using field observations and modeling experiments, this study demonstrates how sensitive watershed hydrology is to soils, emphasizing the importance of accurate soil information in hydrological modeling. We conclude that due emphasis should be given to soil information in hydrologic analysis

Application of Large-Scale, Multi-Resolution Watershed Modeling Framework Using the Hydrologic and Water Quality System (HAWQS)

In recent years, large-scale watershed modeling has been implemented broadly in the field of water resources planning and management. Complex hydrological, sediment, and nutrient processes can be simulated by sophisticated watershed simulation models for important issues such as water resources allocation, sediment transport, and pollution control. Among commonly adopted models, the Soil and Water Assessment Tool (SWAT) has been demonstrated to provide superior performance with a large amount of referencing databases. However, it is cumbersome to perform tedious initialization steps such as preparing inputs and developing a model with each changing targeted study area. In this study, the Hydrologic and Water Quality System (HAWQS) is introduced to serve as a national-scale Decision Support System (DSS) to conduct challenging watershed modeling tasks. HAWQS is a web-based DSS developed and maintained by Texas A & M University, and supported by the U.S. Environmental Protection Agency. Three different spatial resolutions of Hydrologic Unit Code (HUC8, HUC10, and HUC12) and three temporal scales (time steps in daily/monthly/annual) are available as alternatives for general users. In addition, users can specify preferred values of model parameters instead of using the pre-defined sets. With the aid of HAWQS, users can generate a preliminarily calibrated SWAT project within a few minutes by only providing the ending HUC number of the targeted watershed and the simulation period. In the case study, HAWQS was implemented on the Illinois River Basin, USA, with graphical demonstrations and associated analytical results. Scientists and/or decision-makers can take advantage of the HAWQS framework while conducting relevant topics or policies in the future

Necrotizing fasciitis in liver cirrhosis

SummaryBackgroundNecrotizing fasciitis (NF) is associated with a high mortality rate. Hepatitis is endemic in Taiwan, and liver cirrhosis is associated with the development of NF. The characteristics of these patients, however, have not been well documented or the predictors of mortality clearly identified. The purpose of this study is to identify predictors of mortality in patients with liver cirrhosis and necrotizing fasciitis.MethodsThis study was conducted at the Chi-Mei Medical Center in southern Taiwan. Demographic data, clinical characteristics, and the microorganisms responsible for NF in patients with liver cirrhosis were recorded. To identify independent predictors associated with mortality, univariate analysis followed by multivariate logistic regression modeling was performed.ResultsDuring the period 2003–2011, a total of 55 patients with liver cirrhosis and NF were treated at the Chi-Mei Medical Center. Most patients had infections by monomicrobial Gram-negative bacilli. Univariate analysis revealed that severity of liver cirrhosis, shock, band polymorphonuclear neutrophil (>10%), international normalized ratio (>1.5), serum creatinine (>2.0 mg/dL), serum albumin (<2.5 g/dL), and activated partial thromboplastin time (>60 seconds) were significantly associated with mortality. However, multivariate logistic regression analysis revealed that serum albumin of <2.5 g/dL was the only independent predictor of mortality in patients with liver cirrhosis and NF.ConclusionNF in the vast majority of cirrhotic patients was caused by Gram-negative bacilli. Hypoalbuminemia (serum albumin <2.5 g/dL) was associated with mortality in patients with liver cirrhosis and NF. Further studies are needed to assess whether resuscitation with albumin-containing solutions lowers the mortality rate in such patients

Development of a Testbench for Additive Manufacturing Data Integration, Management, and Analytics

The NIST Additive Manufacturing (AM) Data Integration Testbench is a platform designed to evaluate data models, communication methods, and data analytics for AM industrialization. This paper describes a reference framework for AM data integration, named AMIF, and the design of the testbench based on AM Integration Framework (AMIF) for testing the integration of in-process data acquisition, real-time feature extraction, process control, and predictive models under a data management system. A specification of this testbench is developed to manage and stream voluminous data captured by high-speed cameras and performing data analytics using common information models and functional interfaces. The integration of the data, models, and computer tools sends operational decisions to an AM machine in real time. On top of the real-time control functions, AM data integration with MES and ERP systems is also included using a high-performance data warehouse for long-term data archiving and metadata management. The architecture of this testbench is illustrated in this work. AMIF can guide AM practitioners and system integrators to build their integrated AM manufacturing systems for production. The NIST AM testbench’s plug-and-play features allow both internal and external researchers and developers to assess the effectiveness of their individual data models, data analytics, and decision-making algorithms on the systems engineering level.Mechanical Engineerin

Multiple models guide strategies for agricultural nutrient reductions

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/1/fee1472_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/2/fee1472-sup-0008-WebTable7.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/3/fee1472-sup-0004-WebTable3.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/4/fee1472.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/5/fee1472-sup-0006-WebTable5.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/6/fee1472-sup-0002-WebTable1.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/7/fee1472-sup-0005-WebTable4.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/8/fee1472-sup-0007-WebTable6.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/9/fee1472-sup-0003-WebTable2.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/136504/10/fee1472-sup-0001-WebFig1.pd