Approximation of Nash equilibria and the network community structure detection problem

PubMed Central

2017-01-01

Game theory based methods designed to solve the problem of community structure detection in complex networks have emerged in recent years as an alternative to classical and optimization based approaches. The Mixed Nash Extremal Optimization uses a generative relation for the characterization of Nash equilibria to identify the community structure of a network by converting the problem into a non-cooperative game. This paper proposes a method to enhance this algorithm by reducing the number of payoff function evaluations. Numerical experiments performed on synthetic and real-world networks show that this approach is efficient, with results better or just as good as other state-of-the-art methods. PMID:28467496

Local Nash Equilibrium in Social Networks

PubMed Central

Zhang, Yichao; Aziz-Alaoui, M. A.; Bertelle, Cyrille; Guan, Jihong

2014-01-01

Nash equilibrium is widely present in various social disputes. As of now, in structured static populations, such as social networks, regular, and random graphs, the discussions on Nash equilibrium are quite limited. In a relatively stable static gaming network, a rational individual has to comprehensively consider all his/her opponents' strategies before they adopt a unified strategy. In this scenario, a new strategy equilibrium emerges in the system. We define this equilibrium as a local Nash equilibrium. In this paper, we present an explicit definition of the local Nash equilibrium for the two-strategy games in structured populations. Based on the definition, we investigate the condition that a system reaches the evolutionary stable state when the individuals play the Prisoner's dilemma and snow-drift game. The local Nash equilibrium provides a way to judge whether a gaming structured population reaches the evolutionary stable state on one hand. On the other hand, it can be used to predict whether cooperators can survive in a system long before the system reaches its evolutionary stable state for the Prisoner's dilemma game. Our work therefore provides a theoretical framework for understanding the evolutionary stable state in the gaming populations with static structures. PMID:25169150

Congestion schemes and Nash equilibrium in complex networks

NASA Astrophysics Data System (ADS)

Almendral, Juan A.; López, Luis; Cholvi, Vicent; Sanjuán, Miguel A. F.

2005-09-01

Whenever a common resource is scarce, a set of rules are needed to share it in a fairly way. However, most control schemes assume that users will behave in a cooperative way, without taking care of guaranteeing that they will not act in a selfish manner. Then, a fundamental issue is to evaluate the impact of cheating. From the point of view of game theory, a Nash equilibrium implies that nobody can take advantage by unilaterally deviating from this stable state, even in the presence of selfish users. In this paper we prove that any efficient Nash equilibrium strongly depends on the number of users, if the control scheme policy does not record their previous behavior. Since this is a common pattern in real situations, this implies that the system would be always out of equilibrium. Consequently, this result proves that, in practice, oblivious control schemes must be improved to cope with selfish users.

How Do Doctors Diagnose NAFLD and NASH?

MedlinePlus

... NAFLD and NASH, such as overweight or obesity insulin resistance high levels of triglycerides or abnormal levels of ... NASH, such as an enlarged liver signs of insulin resistance such as darkened skin patches over your knuckles, ...

The Hopeful Traveler Jay Bryan Nash.

ERIC Educational Resources Information Center

Jessup, Harvey M., Comp.

This book is one of a series of publications preserving the best writing and speeches of outstanding leaders of the American Alliance for Health, Physical Education, Recreation and Dance. Jay Bryan Nash was one of the founders of the Alliance. The speeches and essays by Nash in this collection are, for the most part, appearing in published form…

NARSTO SOS99NASH WIND PROFILER DATA

Atmospheric Science Data Center

2018-04-16

NARSTO SOS99NASH WIND PROFILER DATA Project Title:  NARSTO ... Platform:  Ground Station Instrument:  Wind Profiler Location:  Nashville, Tennessee Spatial ... Data Guide Documents:  SOS99Nash Wind Profiler Guide Related Data:  Southern Oxidants ...

Jay B. Nash.

ERIC Educational Resources Information Center

Jable, J. Thomas

1985-01-01

Jay B. Nash's accomplishments and professional service have long been recognized by physical educators. This article examines the major forces and events that made him one of the most important leaders in American physical education. (MT)

Phosphorus component in AnnAGNPS

USGS Publications Warehouse

Yuan, Y.; Bingner, R.L.; Theurer, F.D.; Rebich, R.A.; Moore, P.A.

2005-01-01

The USDA Annualized Agricultural Non-Point Source Pollution model (AnnAGNPS) has been developed to aid in evaluation of watershed response to agricultural management practices. Previous studies have demonstrated the capability of the model to simulate runoff and sediment, but not phosphorus (P). The main purpose of this article is to evaluate the performance of AnnAGNPS on P simulation using comparisons with measurements from the Deep Hollow watershed of the Mississippi Delta Management Systems Evaluation Area (MDMSEA) project. A sensitivity analysis was performed to identify input parameters whose impact is the greatest on P yields. Sensitivity analysis results indicate that the most sensitive variables of those selected are initial soil P contents, P application rate, and plant P uptake. AnnAGNPS simulations of dissolved P yield do not agree well with observed dissolved P yield (Nash-Sutcliffe coefficient of efficiency of 0.34, R2 of 0.51, and slope of 0.24); however, AnnAGNPS simulations of total P yield agree well with observed total P yield (Nash-Sutcliffe coefficient of efficiency of 0.85, R2 of 0.88, and slope of 0.83). The difference in dissolved P yield may be attributed to limitations in model simulation of P processes. Uncertainties in input parameter selections also affect the model's performance.

Pre-Collegiate Teachers and Gary Nash

ERIC Educational Resources Information Center

Sesso, Gloria

2009-01-01

In this article, the author recalls the time she met Gary Nash at UCLA on July 13, 1992, when they began the work of creating the National Standards in History. Professor Nash was the leader in the development of the United States History Standards. In creating the Standards, they were to focus on Historical Thinking. They needed to organize the…

Pathophysiology of NASH: perspectives for a targeted treatment

PubMed Central

Marra, Fabio; Lotersztajn, Sophie

2013-01-01

Non alcoholic steatohepatitis (NASH) is the more severe form of nonalcoholic fatty liver disease. In NASH, fatty liver, hepatic inflammation, hepatocyte injury and fibrogenesis are associated, and thi condition may eventually lead to cirrhosis. Current treatment of NASH relies on the reduction of body weight and increase in physical activity, but there is no pharmacologic treatment approved as yet. Emerging data indicate that NASH progression results from parallel events originating from the liver as well as from the adipose tissue, the gut and the gastrointestinal tract. Thus, dysfunction of the adipose tissue through enhanced flow of free fatty acids and release of adipocytokines, and alterations in the gut microbiome generate proinflammatory signals that underly NASH progression. Additional ‘extrahepatic hits’ include dietary factors and gastrointestinal hormones. Within the liver, hepatocyte apoptosis, ER stress and oxidative stress are key contributors to hepatocellular injury. In addition, lipotoxic mediators and danger signals activate Kupffer cells which initiate and perpetuate the inflammatory response by releasing inflammatory mediators that contribute to inflammatory cell recruitment and development of fibrosis. Inflammatory and fibrogenic mediators include chemokines, the cannabinoid system, the inflammasome and activation of pattern-recognition receptors. Here we review the major mechanisms leading to appearance and progression of NASH, focusing on both extrahepatic signals and local inflammatory mechanisms, in an effort to identify the most promising molecular targets for the treatment of this condition. PMID:23394092

Nash equilibrium and evolutionary dynamics in semifinalists' dilemma.

PubMed

Baek, Seung Ki; Son, Seung-Woo; Jeong, Hyeong-Chai

2015-04-01

We consider a tournament among four equally strong semifinalists. The players have to decide how much stamina to use in the semifinals, provided that the rest is available in the final and the third-place playoff. We investigate optimal strategies for allocating stamina to the successive matches when players' prizes (payoffs) are given according to the tournament results. From the basic assumption that the probability to win a match follows a nondecreasing function of stamina difference, we present symmetric Nash equilibria for general payoff structures. We find three different phases of the Nash equilibria in the payoff space. First, when the champion wins a much bigger payoff than the others, any pure strategy can constitute a Nash equilibrium as long as all four players adopt it in common. Second, when the first two places are much more valuable than the other two, the only Nash equilibrium is such that everyone uses a pure strategy investing all stamina in the semifinal. Third, when the payoff for last place is much smaller than the others, a Nash equilibrium is formed when every player adopts a mixed strategy of using all or none of its stamina in the semifinals. In a limiting case that only last place pays the penalty, this mixed-strategy profile can be proved to be a unique symmetric Nash equilibrium, at least when the winning probability follows a Heaviside step function. Moreover, by using this Heaviside step function, we study the tournament by using evolutionary replicator dynamics to obtain analytic solutions, which reproduces the corresponding Nash equilibria on the population level and gives information on dynamic aspects.

Nash equilibrium and evolutionary dynamics in semifinalists' dilemma

NASA Astrophysics Data System (ADS)

Baek, Seung Ki; Son, Seung-Woo; Jeong, Hyeong-Chai

2015-04-01

We consider a tournament among four equally strong semifinalists. The players have to decide how much stamina to use in the semifinals, provided that the rest is available in the final and the third-place playoff. We investigate optimal strategies for allocating stamina to the successive matches when players' prizes (payoffs) are given according to the tournament results. From the basic assumption that the probability to win a match follows a nondecreasing function of stamina difference, we present symmetric Nash equilibria for general payoff structures. We find three different phases of the Nash equilibria in the payoff space. First, when the champion wins a much bigger payoff than the others, any pure strategy can constitute a Nash equilibrium as long as all four players adopt it in common. Second, when the first two places are much more valuable than the other two, the only Nash equilibrium is such that everyone uses a pure strategy investing all stamina in the semifinal. Third, when the payoff for last place is much smaller than the others, a Nash equilibrium is formed when every player adopts a mixed strategy of using all or none of its stamina in the semifinals. In a limiting case that only last place pays the penalty, this mixed-strategy profile can be proved to be a unique symmetric Nash equilibrium, at least when the winning probability follows a Heaviside step function. Moreover, by using this Heaviside step function, we study the tournament by using evolutionary replicator dynamics to obtain analytic solutions, which reproduces the corresponding Nash equilibria on the population level and gives information on dynamic aspects.

Nash equilibrium strategy in the deregulated power industry and comparing its lost welfare with Iran wholesale electricity market

NASA Astrophysics Data System (ADS)

Mousavi, Seyed Hosein; Nazemi, Ali; Hafezalkotob, Ashkan

2016-09-01

With the increasing use of different types of auctions in market designing, modeling of participants' behaviors to evaluate the market structure is one of the main discussions in the studies related to the deregulated power industries. In this article, we apply an approach of the optimal bidding behavior to the Iran wholesale electricity market as a restructured electric power industry and model how the participants of the market bid in the spot electricity market. The problem is formulated analytically using the Nash equilibrium concept composed of large numbers of players having discrete and very large strategy spaces. Then, we compute and draw supply curve of the competitive market in which all generators' proposed prices are equal to their marginal costs and supply curve of the real market in which the pricing mechanism is pay-as-bid. We finally calculate the lost welfare or inefficiency of the Nash equilibrium and the real market by comparing their supply curves with the competitive curve. We examine 3 cases on November 24 (2 cases) and July 24 (1 case), 2012. It is observed that in the Nash equilibrium on November 24 and demand of 23,487 MW, there are 212 allowed plants for the first case (plants are allowed to choose any quantity of generation except one of them that should be equal to maximum Power) and the economic efficiency or social welfare of Nash equilibrium is 2.77 times as much as the real market. In addition, there are 184 allowed plants for the second case (plants should offer their maximum power with different prices) and the efficiency or social welfare of Nash equilibrium is 3.6 times as much as the real market. On July 24 and demand of 42,421 MW, all 370 plants should generate maximum energy due to the high electricity demand that the economic efficiency or social welfare of the Nash equilibrium is about 2 times as much as the real market.

Near-Nash targeting strategies for heterogeneous teams of autonomous combat vehicles

NASA Astrophysics Data System (ADS)

Galati, David G.; Simaan, Marwan A.

2008-04-01

Military strategists are currently seeking methodologies to control large numbers of autonomous assets. Automated planners based upon the Nash equilibrium concept in non-zero sum games are one option. Because such planners inherently consider possible adversarial actions, assets are able to adapt to, and to some extent predict, potential enemy actions. However, these planners must function properly both in cases in which a pure Nash strategy does not exist and in scenarios possessing multiple Nash equilibria. Another issue that needs to be overcome is the scalability of the Nash equilibrium. That is, as the dimensionality of the problem increases, the Nash strategies become unfeasible to compute using traditional methodologies. In this paper we introduce the concept of near-Nash strategies as a mechanism to overcome these difficulties. We then illustrate this concept by deriving the near-Nash strategies and using these strategies as the basis for an intelligent battle plan for heterogeneous teams of autonomous combat air vehicles in the Multi-Team Dynamic Weapon Target Assignment model.

Quantum Nash Equilibria and Quantum Computing

NASA Astrophysics Data System (ADS)

Fellman, Philip Vos; Post, Jonathan Vos

In 2004, At the Fifth International Conference on Complex Systems, we drew attention to some remarkable findings by researchers at the Santa Fe Institute (Sato, Farmer and Akiyama, 2001) about hitherto unsuspected complexity in the Nash Equilibrium. As we progressed from these findings about heteroclinic Hamiltonians and chaotic transients hidden within the learning patterns of the simple rock-paper-scissors game to some related findings on the theory of quantum computing, one of the arguments we put forward was just as in the late 1990's a number of new Nash equilibria were discovered in simple bi-matrix games (Shubik and Quint, 1996; Von Stengel, 1997, 2000; and McLennan and Park, 1999) we would begin to see new Nash equilibria discovered as the result of quantum computation. While actual quantum computers remain rather primitive (Toibman, 2004), and the theory of quantum computation seems to be advancing perhaps a bit more slowly than originally expected, there have, nonetheless, been a number of advances in computation and some more radical advances in an allied field, quantum game theory (Huberman and Hogg, 2004) which are quite significant. In the course of this paper we will review a few of these discoveries and illustrate some of the characteristics of these new "Quantum Nash Equilibria". The full text of this research can be found at http://necsi.org/events/iccs6/viewpaper.php?id-234

Quantum gambling based on Nash-equilibrium

NASA Astrophysics Data System (ADS)

Zhang, Pei; Zhou, Xiao-Qi; Wang, Yun-Long; Liu, Bi-Heng; Shadbolt, Pete; Zhang, Yong-Sheng; Gao, Hong; Li, Fu-Li; O'Brien, Jeremy L.

2017-06-01

The problem of establishing a fair bet between spatially separated gambler and casino can only be solved in the classical regime by relying on a trusted third party. By combining Nash-equilibrium theory with quantum game theory, we show that a secure, remote, two-party game can be played using a quantum gambling machine which has no classical counterpart. Specifically, by modifying the Nash-equilibrium point we can construct games with arbitrary amount of bias, including a game that is demonstrably fair to both parties. We also report a proof-of-principle experimental demonstration using linear optics.

Non-alcoholic steatohepatitis (NASH) in patients with polycystic ovarian syndrome (PCOS).

PubMed

Hossain, Noreen; Stepanova, Maria; Afendy, Arian; Nader, Fatema; Younossi, Youssef; Rafiq, Nila; Goodman, Zachary; Younossi, Zobair M

2011-04-01

Both non-alcoholic steatohepatitis (NASH) and polycystic ovary syndrome (PCOS) are associated with metabolic syndrome (MS) and insulin resistance (IR). Except for a few case reports, there are no systematic assessments of NASH in PCOS patients. To determine the prevalence of NASH and independent factors associated with NASH in a cohort of patients with documented PCOS. Patients with established diagnosis of PCOS and matched controls (matched for gender, age, and body mass index (BMI)) were included in the study. Causes of other liver diseases were systematically excluded by clinical and laboratory tests. Excessive alcohol use was defined as alcohol consumption of greater than 10 g/day. All liver biopsies were read by a single pathologist blinded to the clinical data. Histologic NASH was defined as steatosis with lobular inflammation and ballooning degeneration of hepatocytes with or without Mallory-Denk bodies or pericellular fibrosis. Univariate and multivariate analyses with logistic regression were performed to compare PCOS to matched controls. Sixty-six patients were included in the study (34 PCOS and 32 matched controls). Of PCOS patients, 73% had a liver biopsy while 78% of the matched controls had a liver biopsy. In comparing PCOS patients to the matched controls, clinical (BMI, waist circumference, type 2 diabetes, MS, or its components, any alcohol consumption in the prior year, ethnic background, age, gender, etc.) and laboratory data (aminotransferases, ferritin, glucose, etc.) were not significantly different (p > 0.05). However, PCOS patients tended to have more histologic NASH on their liver biopsies (44.0% vs. 20.8%, p = 0.08). Independent predictors of histologic NASH in PCOS patients were elevated aspartate aminotransferase (AST), high triglycerides and small amounts of alcohol consumption (p = 0.019, 10-fold cross-validated AUC = 0.80, 95% CI = 0.56-0.94). Although about half of PCOS patients did not report any alcohol consumption, 50% did report

Assessment of Spatial Transferability of Process-Based Hydrological Model Parameters in Two Neighboring Catchments in the Himalayan Region

NASA Astrophysics Data System (ADS)

Nepal, S.

2016-12-01

The spatial transferability of the model parameters of the process-oriented distributed J2000 hydrological model was investigated in two glaciated sub-catchments of the Koshi river basin in eastern Nepal. The basins had a high degree of similarity with respect to their static landscape features. The model was first calibrated (1986-1991) and validated (1992-1997) in the Dudh Koshi sub-catchment. The calibrated and validated model parameters were then transferred to the nearby Tamor catchment (2001-2009). A sensitivity and uncertainty analysis was carried out for both sub-catchments to discover the sensitivity range of the parameters in the two catchments. The model represented the overall hydrograph well in both sub-catchments, including baseflow and medium range flows (rising and recession limbs). The efficiency results according to both Nash-Sutcliffe and the coefficient of determination was above 0.84 in both cases. The sensitivity analysis showed that the same parameter was most sensitive for Nash-Sutcliffe (ENS) and Log Nash-Sutcliffe (LNS) efficiencies in both catchments. However, there were some differences in sensitivity to ENS and LNS for moderate and low sensitive parameters, although the majority (13 out of 16 for ENS and 16 out of 16 for LNS) had a sensitivity response in a similar range. A generalized likelihood uncertainty estimation (GLUE) result suggest that most of the time the observed runoff is within the parameter uncertainty range, although occasionally the values lie outside the uncertainty range, especially during flood peaks and more in the Tamor. This may be due to the limited input data resulting from the small number of precipitation stations and lack of representative stations in high-altitude areas, as well as to model structural uncertainty. The results indicate that transfer of the J2000 parameters to a neighboring catchment in the Himalayan region with similar physiographic landscape characteristics is viable. This indicates the

Development of a novel diagnostic algorithm to predict NASH in HCV-positive patients.

PubMed

Gallotta, Andrea; Paneghetti, Laura; Mrázová, Viera; Bednárová, Adriana; Kružlicová, Dáša; Frecer, Vladimir; Miertus, Stanislav; Biasiolo, Alessandra; Martini, Andrea; Pontisso, Patrizia; Fassina, Giorgio

2018-05-01

Non-alcoholic steato-hepatitis (NASH) is a severe disease characterised by liver inflammation and progressive hepatic fibrosis, which may progress to cirrhosis and hepatocellular carcinoma. Clinical evidence suggests that in hepatitis C virus patients steatosis and NASH are associated with faster fibrosis progression and hepatocellular carcinoma. A safe and reliable non-invasive diagnostic method to detect NASH at its early stages is still needed to prevent progression of the disease. We prospectively enrolled 91 hepatitis C virus-positive patients with histologically proven chronic liver disease: 77 patients were included in our study; of these, 10 had NASH. For each patient, various clinical and serological variables were collected. Different algorithms combining squamous cell carcinoma antigen-immunoglobulin-M (SCCA-IgM) levels with other common clinical data were created to provide the probability of having NASH. Our analysis revealed a statistically significant correlation between the histological presence of NASH and SCCA-IgM, insulin, homeostasis model assessment, haemoglobin, high-density lipoprotein and ferritin levels, and smoke. Compared to the use of a single marker, algorithms that combined four, six or seven variables identified NASH with higher accuracy. The best diagnostic performance was obtained with the logistic regression combination, which included all seven variables correlated with NASH. The combination of SCCA-IgM with common clinical data shows promising diagnostic performance for the detection of NASH in hepatitis C virus patients.

Simulation of agricultural non-point source pollution in Xichuan by using SWAT model

NASA Astrophysics Data System (ADS)

Xing, Linan; Zuo, Jiane; Liu, Fenglin; Zhang, Xiaohui; Cao, Qiguang

2018-02-01

This paper evaluated the applicability of using SWAT to access agricultural non-point source pollution in Xichuan area. In order to build the model, DEM, soil sort and land use map, climate monitoring data were collected as basic database. The SWAT model was calibrated and validated for the SWAT was carried out using streamflow, suspended solids, total phosphorus and total nitrogen records from 2009 to 2011. Errors, coefficient of determination and Nash-Sutcliffe coefficient were considered to evaluate the applicability. The coefficient of determination were 0.96, 0.66, 0.55 and 0.66 for streamflow, SS, TN, and TP, respectively. Nash-Sutcliffe coefficient were 0.93, 0.5, 0.52 and 0.63, respectively. The results all meet the requirements. It suggested that the SWAT model can simulate the study area.

A novel diagnostic biomarker panel for obesity-related nonalcoholic steatohepatitis (NASH).

PubMed

Younossi, Zobair M; Jarrar, Mohammed; Nugent, Clare; Randhawa, Manpreet; Afendy, Mariam; Stepanova, Maria; Rafiq, Nila; Goodman, Zachary; Chandhoke, Vikas; Baranova, Ancha

2008-11-01

Within the spectrum of nonalcoholic fatty liver disease (NAFLD), only patients with nonalcoholic steatohepatitis (NASH) show convincing evidence for progression. To date, liver biopsy remains the gold standard for the diagnosis of NASH; however, liver biopsy is expensive and associated with a small risk, emphasizing the urgent need for noninvasive diagnostic biomarkers. Recent findings suggest a role for apoptosis and adipocytokines in the pathogenesis of NASH. The aim of this study was to develop a noninvasive diagnostic biomarker for NASH. The study included 101 patients with liver biopsies who were tested with enzyme-linked immunosorbent assay (ELISA)-based assays. Of these, 69 were included in the biomarker development set and 32 were included in the biomarker validation set. Clinical data and serum samples were collected at the time of biopsy. Fasting serum samples were assayed for adiponectin, resistin, insulin, glucose, TNF-alpha, IL-6, IL-8, cytokeratin CK-18 (M65 antigen), and caspase-cleaved CK-18 (M30 antigen). Data analysis revealed that the levels of M30 antigen (cleaved CK-18) predicted histological NASH with 70% sensitivity and 83.7% specificity and area under the curve (AUC) = 0.711, p < 10(-4), whereas the predictive value of the levels of intact CK-18 (M65) was higher (63.6% sensitivity and 89.4% specificity and AUC = 0.814, p < 10(-4)). Histological NASH could be predicted by a combination of Cleaved CK-18, a product of the subtraction of Cleaved CK-18 level from intact CK-18 level, serum adiponectin, and serum resistin with a sensitivity of 95.45% sensitivity, specificity of 70.21%, and AUC of 0.908 (p < 10(-4)). Blinded validation of this model confirmed its reliability for separating NASH from simple steatosis. Four ELISA-based tests were combined to form a simple diagnostic biomarker for NASH.

The Nash Equilibrium Revisited: Chaos and Complexity Hidden in Simplicity

NASA Astrophysics Data System (ADS)

Fellman, Philip V.

The Nash Equilibrium is a much discussed, deceptively complex, method for the analysis of non-cooperative games (McLennan and Berg, 2005). If one reads many of the commonly available definitions the description of the Nash Equilibrium is deceptively simple in appearance. Modern research has discovered a number of new and important complex properties of the Nash Equilibrium, some of which remain as contemporary conundrums of extraordinary difficulty and complexity (Quint and Shubik, 1997). Among the recently discovered features which the Nash Equilibrium exhibits under various conditions are heteroclinic Hamiltonian dynamics, a very complex asymptotic structure in the context of two-player bi-matrix games and a number of computationally complex or computationally intractable features in other settings (Sato, Akiyama and Farmer, 2002). This paper reviews those findings and then suggests how they may inform various market prediction strategies.

Navigable networks as Nash equilibria of navigation games.

PubMed

Gulyás, András; Bíró, József J; Kőrösi, Attila; Rétvári, Gábor; Krioukov, Dmitri

2015-07-03

Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network.

Enhancement of a parsimonious water balance model to simulate surface hydrology in a glacierized watershed

USGS Publications Warehouse

Valentin, Melissa M.; Viger, Roland J.; Van Beusekom, Ashley E.; Hay, Lauren E.; Hogue, Terri S.; Foks, Nathan Leon

2018-01-01

The U.S. Geological Survey monthly water balance model (MWBM) was enhanced with the capability to simulate glaciers in order to make it more suitable for simulating cold region hydrology. The new model, MWBMglacier, is demonstrated in the heavily glacierized and ecologically important Copper River watershed in Southcentral Alaska. Simulated water budget components compared well to satellite‐based observations and ground measurements of streamflow, evapotranspiration, snow extent, and total water storage, with differences ranging from 0.2% to 7% of the precipitation flux. Nash Sutcliffe efficiency for simulated and observed streamflow was greater than 0.8 for six of eight stream gages. Snow extent matched satellite‐based observations with Nash Sutcliffe efficiency values of greater than 0.89 in the four Copper River ecoregions represented. During the simulation period 1949 to 2009, glacier ice melt contributed 25% of total runoff, ranging from 12% to 45% in different tributaries, and glacierized area was reduced by 6%. Statistically significant (p < 0.05) decreasing and increasing trends in annual glacier mass balance occurred during the multidecade cool and warm phases of the Pacific Decadal Oscillation, respectively, reinforcing the link between climate perturbations and glacier mass balance change. The simulations of glaciers and total runoff for a large, remote region of Alaska provide useful data to evaluate hydrologic, cryospheric, ecologic, and climatic trends. MWBM glacier is a valuable tool to understand when, and to what extent, streamflow may increase or decrease as glaciers respond to a changing climate.

Heat transfer analysis of cylindrical anaerobic reactors with different sizes: a heat transfer model.

PubMed

Liu, Jiawei; Zhou, Xingqiu; Wu, Jiangdong; Gao, Wen; Qian, Xu

2017-10-01

The temperature is the essential factor that influences the efficiency of anaerobic reactors. During the operation of the anaerobic reactor, the fluctuations of ambient temperature can cause a change in the internal temperature of the reactor. Therefore, insulation and heating measures are often used to maintain anaerobic reactor's internal temperature. In this paper, a simplified heat transfer model was developed to study heat transfer between cylindrical anaerobic reactors and their surroundings. Three cylindrical reactors of different sizes were studied, and the internal relations between ambient temperature, thickness of insulation, and temperature fluctuations of the reactors were obtained at different reactor sizes. The model was calibrated by a sensitivity analysis, and the calibrated model was well able to predict reactor temperature. The Nash-Sutcliffe model efficiency coefficient was used to assess the predictive power of heat transfer models. The Nash coefficients of the three reactors were 0.76, 0.60, and 0.45, respectively. The model can provide reference for the thermal insulation design of cylindrical anaerobic reactors.

Non-Alcoholic Steatohepatitis (NASH): Risk Factors in Morbidly Obese Patients

PubMed Central

Losekann, Alexandre; Weston, Antonio C.; de Mattos, Angelo A.; Tovo, Cristiane V.; de Carli, Luis A.; Espindola, Marilia B.; Pioner, Sergio R.; Coral, Gabriela P.

2015-01-01

The aim was to investigate the prevalence of non-alcoholic steatohepatitis (NASH) and risk factors for hepatic fibrosis in morbidly obese patients submitted to bariatric surgery. This retrospective study recruited all patients submitted to bariatric surgery from January 2007 to December 2012 at a reference attendance center of Southern Brazil. Clinical and biochemical data were studied as a function of the histological findings of liver biopsies done during the surgery. Steatosis was present in 226 (90.4%) and NASH in 176 (70.4%) cases. The diagnosis of cirrhosis was established in four cases (1.6%) and fibrosis in 108 (43.2%). Risk factors associated with NASH at multivariate analysis were alanine aminotransferase (ALT) >1.5 times the upper limit of normal (ULN); glucose ≥ 126 mg/dL and triglycerides ≥ 150 mg/dL. All patients with ALT ≥1.5 times the ULN had NASH. When the presence of fibrosis was analyzed, ALT > 1.5 times the ULN and triglycerides ≥ 150 mg/dL were risk factors, furthermore, there was an increase of 1% in the prevalence of fibrosis for each year of age increase. Not only steatosis, but NASH is a frequent finding in MO patients. In the present study, ALT ≥ 1.5 times the ULN identifies all patients with NASH, this finding needs to be further validated in other studies. Moreover, the presence of fibrosis was associated with ALT, triglycerides and age, identifying a subset of patients with more severe disease. PMID:26512661

Controversies in the Diagnosis and Management of NAFLD and NASH.

PubMed

Rinella, Mary E; Loomba, Rohit; Caldwell, Stephen H; Kowdley, Kris; Charlton, Michael; Tetri, Brent; Harrison, Stephen A

2014-04-01

Nonalcoholic fatty liver disease (NAFLD) is recognized as the most common cause of chronic liver disease in the United States. Nonalcoholic steatohepatitis (NASH) occurs in a subset of patients with NAFLD and is characterized by the presence of hepa-tocellular injury, which is progressive in a substantial proportion of cases and can lead to cirrhosis and all of its complications. Although the diagnosis of NAFLD can be made through imaging studies or liver biopsy, the diagnosis of NASH still requires histologic confirmation. Liver biopsy should be performed in the presence of risk factors for advanced disease. Measures aimed at promoting weight loss, a healthier lifestyle, and optimization of metabolic risk factors remain the cornerstone of management of NAFLD. Therapeutic agents that are presently considered the most promising in NAFLD are effective in less than 50% of patients. Among patients with biopsy-proven NASH, treatment with pharmacologic agents should be considered; however, the role of specific agents in NASH still needs further study. Despite a wealth of research over the past 15 years, many controversies remain with respect to the diagnosis and management of NAFLD and NASH as well as the influence of alcohol on liver disease progression in these patients.

Navigable networks as Nash equilibria of navigation games

PubMed Central

Gulyás, András; Bíró, József J.; Kőrösi, Attila; Rétvári, Gábor; Krioukov, Dmitri

2015-01-01

Common sense suggests that networks are not random mazes of purposeless connections, but that these connections are organized so that networks can perform their functions well. One function common to many networks is targeted transport or navigation. Here, using game theory, we show that minimalistic networks designed to maximize the navigation efficiency at minimal cost share basic structural properties with real networks. These idealistic networks are Nash equilibria of a network construction game whose purpose is to find an optimal trade-off between the network cost and navigability. We show that these skeletons are present in the Internet, metabolic, English word, US airport, Hungarian road networks, and in a structural network of the human brain. The knowledge of these skeletons allows one to identify the minimal number of edges, by altering which one can efficiently improve or paralyse navigation in the network. PMID:26138277

Nash Receives 2004 David Perlman Award for Excellence in Science Writing

NASA Astrophysics Data System (ADS)

Elmer-DeWitt, Philip; Nash, J. Madeleine

2004-07-01

J. Madeleine Nash received the David Perlman Award for Excellence in Science Writing at the AGU Joint Assembly Honors Ceremony, which was held on 19 May 2004, in Montreal, Canada. Nash was honored for ``Fireproofing the Forests,'' an article that appeared in the 18 August 2003 edition of Time Magazine. ``It is an honor to present AGU's 2004 David Perlman Award to Madeleine Nash, a senior contributor to Time Magazine and, if I may say so, one of the great science writers of her generation.''

A novel role of astrocyte elevated gene-1 (AEG-1) in regulating nonalcoholic steatohepatitis (NASH).

PubMed

Srivastava, Jyoti; Robertson, Chadia L; Ebeid, Kareem; Dozmorov, Mikhail; Rajasekaran, Devaraja; Mendoza, Rachel; Siddiq, Ayesha; Akiel, Maaged A; Jariwala, Nidhi; Shen, Xue-Ning; Windle, Jolene J; Subler, Mark A; Mukhopadhyay, Nitai D; Giashuddin, Shah; Ghosh, Shobha; Lai, Zhao; Chen, Yidong; Fisher, Paul B; Salem, Aliasger K; Sanyal, Arun J; Sarkar, Devanand

2017-08-01

Nonalcoholic steatohepatitis (NASH) is the most prevalent cause of chronic liver disease in the Western world. However, an optimum therapy for NASH is yet to be established, mandating more in-depth investigation into the molecular pathogenesis of NASH to identify novel regulatory molecules and develop targeted therapies. Here, we unravel a unique function of astrocyte elevated gene-1(AEG-1)/metadherin in NASH using a transgenic mouse with hepatocyte-specific overexpression of AEG-1 (Alb/AEG-1) and a conditional hepatocyte-specific AEG-1 knockout mouse (AEG-1 ΔHEP ). Alb/AEG-1 mice developed spontaneous NASH whereas AEG-1 ΔHEP mice were protected from high-fat diet (HFD)-induced NASH. Intriguingly, AEG-1 overexpression was observed in livers of NASH patients and wild-type (WT) mice that developed steatosis upon feeding HFD. In-depth molecular analysis unraveled that inhibition of peroxisome proliferator-activated receptor alpha activity resulting in decreased fatty acid β-oxidation, augmentation of translation of fatty acid synthase resulting in de novo lipogenesis, and increased nuclear factor kappa B-mediated inflammation act in concert to mediate AEG-1-induced NASH. Therapeutically, hepatocyte-specific nanoparticle-delivered AEG-1 small interfering RNA provided marked protection from HFD-induced NASH in WT mice. AEG-1 might be a key molecule regulating initiation and progression of NASH. AEG-1 inhibitory strategies might be developed as a potential therapeutic intervention in NASH patients. (Hepatology 2017;66:466-480). © 2017 by the American Association for the Study of Liver Diseases.

Uniqueness of Nash equilibrium in vaccination games.

PubMed

Bai, Fan

2016-12-01

One crucial condition for the uniqueness of Nash equilibrium set in vaccination games is that the attack ratio monotonically decreases as the vaccine coverage level increasing. We consider several deterministic vaccination models in homogeneous mixing population and in heterogeneous mixing population. Based on the final size relations obtained from the deterministic epidemic models, we prove that the attack ratios can be expressed in terms of the vaccine coverage levels, and also prove that the attack ratios are decreasing functions of vaccine coverage levels. Some thresholds are presented, which depend on the vaccine efficacy. It is proved that for vaccination games in homogeneous mixing population, there is a unique Nash equilibrium for each game.

Calibration of HEC-Ras hydrodynamic model using gauged discharge data and flood inundation maps

NASA Astrophysics Data System (ADS)

Tong, Rui; Komma, Jürgen

2017-04-01

The estimation of flood is essential for disaster alleviation. Hydrodynamic models are implemented to predict the occurrence and variance of flood in different scales. In practice, the calibration of hydrodynamic models aims to search the best possible parameters for the representation the natural flow resistance. Recent years have seen the calibration of hydrodynamic models being more actual and faster following the advance of earth observation products and computer based optimization techniques. In this study, the Hydrologic Engineering River Analysis System (HEC-Ras) model was set up with high-resolution digital elevation model from Laser scanner for the river Inn in Tyrol, Austria. 10 largest flood events from 19 hourly discharge gauges and flood inundation maps were selected to calibrate the HEC-Ras model. Manning roughness values and lateral inflow factors as parameters were automatically optimized with the Shuffled complex with Principal component analysis (SP-UCI) algorithm developed from the Shuffled Complex Evolution (SCE-UA). Different objective functions (Nash-Sutcliffe model efficiency coefficient, the timing of peak, peak value and Root-mean-square deviation) were used in single or multiple way. It was found that the lateral inflow factor was the most sensitive parameter. SP-UCI algorithm could avoid the local optimal and achieve efficient and effective parameters in the calibration of HEC-Ras model using flood extension images. As results showed, calibration by means of gauged discharge data and flood inundation maps, together with objective function of Nash-Sutcliffe model efficiency coefficient, was very robust to obtain more reliable flood simulation, and also to catch up with the peak value and the timing of peak.

Comparison between two statistically based methods, and two physically based models developed to compute daily mean streamflow at ungaged locations in the Cedar River Basin, Iowa

USGS Publications Warehouse

Linhart, S. Mike; Nania, Jon F.; Christiansen, Daniel E.; Hutchinson, Kasey J.; Sanders, Curtis L.; Archfield, Stacey A.

2013-01-01

A variety of individuals from water resource managers to recreational users need streamflow information for planning and decisionmaking at locations where there are no streamgages. To address this problem, two statistically based methods, the Flow Duration Curve Transfer method and the Flow Anywhere method, were developed for statewide application and the two physically based models, the Precipitation Runoff Modeling-System and the Soil and Water Assessment Tool, were only developed for application for the Cedar River Basin. Observed and estimated streamflows for the two methods and models were compared for goodness of fit at 13 streamgages modeled in the Cedar River Basin by using the Nash-Sutcliffe and the percent-bias efficiency values. Based on median and mean Nash-Sutcliffe values for the 13 streamgages the Precipitation Runoff Modeling-System and Soil and Water Assessment Tool models appear to have performed similarly and better than Flow Duration Curve Transfer and Flow Anywhere methods. Based on median and mean percent bias values, the Soil and Water Assessment Tool model appears to have generally overestimated daily mean streamflows, whereas the Precipitation Runoff Modeling-System model and statistical methods appear to have underestimated daily mean streamflows. The Flow Duration Curve Transfer method produced the lowest median and mean percent bias values and appears to perform better than the other models.

Mixed Nash equilibria in Eisert-Lewenstein-Wilkens (ELW) games

NASA Astrophysics Data System (ADS)

Bolonek-Lasoń, Katarzyna; Kosiński, Piotr

2017-01-01

The classification of all mixed Nash equilibria for the original ELW game is presented. It is based on the quaternionic form of the game proposed by Landsburg (Proc. Am. Math. Soc. 139 (2011), 4423; Rochester Working Paper No 524 (2006); Wiley Encyclopedia of Operations Research and Management Science (Wiley and Sons, New York, (2011)). This approach allows to reduce the problem of finding the Nash equilibria to relatively simple analysis of the extrema of certain quadratic forms.

A Tribute to Gary Nash

ERIC Educational Resources Information Center

Jason-Fives, Alli

2009-01-01

In this article, the author gives tribute to Gary Nash, a brilliant scholar, an award-winning professor, a prolific writer, a true humanitarian, and a revered historian. She honors him for his work with public school teachers. He has provided the educational support, encouragement, and motivation behind the importance of teaching history. Here,…

Serum uric acid concentrations and fructose consumption are independently associated with NASH in children and adolescents.

PubMed

Mosca, Antonella; Nobili, Valerio; De Vito, Rita; Crudele, Annalisa; Scorletti, Eleonora; Villani, Alberto; Alisi, Anna; Byrne, Christopher D

2017-05-01

Recent research has suggested that dietary fructose intake may increase serum uric acid (UA) concentrations. Both UA concentration and fructose consumption maybe also increase in NAFLD. It is not known whether dietary fructose consumption and UA concentration are independently associated with non-alcoholic steatohepatitis (NASH). Our aim was to investigate the factors associated with NASH in children and adolescents with proven NAFLD, and to test whether UA concentrations and fructose consumption are independently associated with NASH. Obese children with NAFLD were studied (n=271). NASH was diagnosed by a NAFLD activity score ⩾5 and the fatty liver inhibition of progression (FLIP) algorithm. Fructose consumption (g/day) was assessed by food frequency questionnaire, and UA (mg/dl) was measured in serum. Binary logistic regression with adjustment for covariates and potential confounders was undertaken to test factors independently associated with NASH. NASH occurred in 37.6% of patients. Hyperuricaemia (UA ⩾5.9mg/dl) was present in 47% of patients with NASH compared with 29.7% of non-NASH patients (p=0.003). Both UA concentration (OR=2.488, 95% CI: 1.87-2.83, p=0.004) and fructose consumption (OR=1.612, 95% CI 1.25-1.86, p=0.001) were independently associated with NASH, after adjustment for multiple (and all) measured confounders. Fructose consumption was independently associated with hyperuricaemia (OR=2.021, 95% CI: 1.66-2.78, p=0.01). These data were confirmed using the FLIP algorithm. Both dietary fructose consumption and serum UA concentrations are independently associated with NASH. Fructose consumption was the only factor independently associated with serum UA concentration. Currently, it is not known whether dietary fructose consumption and uric acid (UA) concentration are linked with non-alcoholic steatohepatitis (NASH) in children and adolescents. Our aim was to test whether UA concentrations and fructose consumption are independently associated with

NASH is an Inflammatory Disorder: Pathogenic, Prognostic and Therapeutic Implications

PubMed Central

van Rooyen, Derrick; Gan, Lay; Chitturi, Shivrakumar

2012-01-01

While non-alcoholic fatty liver disease (NAFLD) is highly prevalent (15% to 45%) in modern societies, only 10% to 25% of cases develop hepatic fibrosis leading to cirrhosis, end-stage liver disease or hepatocellular carcinoma. Apart from pre-existing fibrosis, the strongest predictor of fibrotic progression in NAFLD is steatohepatitis or non-alcoholic steatohepatitis (NASH). The critical features other than steatosis are hepatocellular degeneration (ballooning, Mallory hyaline) and mixed inflammatory cell infiltration. While much is understood about the relationship of steatosis to metabolic factors (over-nutrition, insulin resistance, hyperglycemia, metabolic syndrome, hypoadiponectinemia), less is known about inflammatory recruitment, despite its importance for the perpetuation of liver injury and fibrogenesis. In this review, we present evidence that liver inflammation has prognostic significance in NAFLD. We then consider the origins and components of liver inflammation in NASH. Hepatocytes injured by toxic lipid molecules (lipotoxicity) play a central role in the recruitment of innate immunity involving Toll-like receptors (TLRs), Kupffer cells (KCs), lymphocytes and neutrophils and possibly inflammasome. The key pro-inflammatory signaling pathways in NASH are nuclear factor-kappa B (NF-κB) and c-Jun N-terminal kinase (JNK). The downstream effectors include adhesion molecules, chemokines, cytokines and the activation of cell death pathways leading to apoptosis. The upstream activators of NF-κB and JNK are more contentious and may depend on the experimental model used. TLRs are strong contenders. It remains possible that inflammation in NASH originates outside the liver and in the gut microbiota that prime KC/TLR responses, inflamed adipose tissue and circulating inflammatory cells. We briefly review these mechanistic considerations and project their implications for the effective treatment of NASH. PMID:22570745

Gender difference in NASH susceptibility: Roles of hepatocyte Ikkβ and Sult1e1

PubMed Central

Matsushita, Noriko; Hassanein, Mohamed T.; Martinez-Clemente, Marcos; Lazaro, Raul; French, Samuel W.; Xie, Wen; Lai, Keane; Karin, Michael; Tsukamoto, Hidekazu

2017-01-01

Myeloid cell and hepatocyte IKKβ may mediate the genesis of obesity and insulin resistance in mice fed high fat diet. However, their gender-specific roles in the pathogenesis of non-alcoholic steatohepatitis (NASH) are not known. Here we demonstrate myeloid IKKβ deficiency prevents Western diet-induced obesity and visceral adiposity in females but not in males, and attenuates hyperglycemia, global IR, and NASH in both genders. In contrast, all metabolic sequela including NASH are aggravated by hepatocyte IKKβ deficiency (IkbkbΔhep) in male but not female mice. Gene profiling identifies sulfotransferase family 1E (Sult1e1), which encodes a sulfotransferase E1 responsible for inactivation of estrogen, as a gene upregulated in NASH in both genders and most conspicuously in male IkbkbΔhep mice having worst NASH and lowest plasma estradiol levels. LXRα is enriched to LXRE on Sult1e1 promoter in male WT and IkbkbΔhep mice with NASH, and a Sult1e1 promoter activity is increased by LXRα and its ligand and augmented by expression of a S32A mutant of IκBα. These results demonstrate striking gender differences in regulation by IKKβ of high cholesterol saturated fat diet-induced metabolic changes including NASH and suggest hepatocyte IKKβ is protective in male due at least in part to its ability to repress LXR-induced Sult1e1. Our findings also raise a caution for systemic IKK inhibition for the treatment of NASH as it may exacerbate the disease in male patients. PMID:28797077

Nonalcoholic steatohepatitis (NASH) after pancreaticoduodenectomy: association of pancreatic exocrine deficiency and infection.

PubMed

Murata, Yasuhiro; Mizuno, Shugo; Kato, Hiroyuki; Kishiwada, Masashi; Ohsawa, Ichiro; Hamada, Takashi; Usui, Masanobu; Sakurai, Hiroyuki; Tabata, Masami; Nishimura, Keisuke; Fukutome, Kazuo; Isaji, Shuji

2011-08-01

Previous clinical study has demonstrated that 30-40% of patients undergoing pancreaticoduodenectomy (PD) developed hepatic steatosis. However, nonalcoholic steatohepatitis (NASH) is a little-known complication after PD. Recently we encountered two patients with PD who later developed NASH diagnosed by liver biopsy. Case 1 was a 79-year-old woman who underwent PD for intraductal papillary mucinous neoplasm (IPMN). She had postoperative severe diarrhea due to pseudomembranous enterocolitis. Severe liver dysfunction was observed on the 31st postoperative day. Abdominal computed tomography (CT) on the 32nd day showed remarkably decreased hepatic CT value of 6 HU. Immediate liver biopsy revealed NASH (Brunt criteria: grade 2, stage 2). Case 2 was a 71-year-old woman who underwent PD for IPMN. Liver biopsy on 70th postoperative day, which was performed for assessment of moderate liver dysfunction and decreased hepatic CT value of 44 HU, demonstrated simple steatosis. In the 21st postoperative month, she developed severe urinary tract infection together with marked liver dysfunction. Immediate liver biopsy revealed NASH (Brunt criteria: grade 1, stage 1). For each patient, treatment of infection and high-dose pancreatic enzyme supplements improved liver dysfunction and liver steatosis. Clinical features of our cases seem to support the current leading hypothesis of the pathogenesis of NASH, i.e., the two-hit theory.

Water extract of Vitis coignetiae Pulliat leaves attenuates oxidative stress and inflammation in progressive NASH rats.

PubMed

Pak, Wing; Takayama, Fusako; Hasegawa, Azusa; Mankura, Mitsumasa; Egashira, Toru; Ueki, Keiji; Nakamoto, Kazuo; Kawasaki, Hiromu; Mori, Akitane

2012-01-01

This study aimed to investigate the therapeutic effects of the water extract of leaves of Vitis coignetiae Pulliat (VCPL) on nonalcoholic steatohepatitis (NASH) with advanced fibrosis, as our previous study exhibited its preventive effect on NASH. The NASH animal model [PCT/JP2007/52477] was prepared by loading recurrent and intermittent hypoxemia stress to a rat with fatty liver, which resembled the condition occurring in patients with obstructive sleep apnea (OSA) and fatty liver, who have a high incidence of NASH. Intermittent hypoxemia stress is regarded as a condition similar to warm ischemia followed by re-oxygenation, which induces oxidative stress (OS). The daily 100 or 300 mg/kg VCPL administrations were performed for 3 weeks perorally beginning at the time of detection of advanced liver fibrosis. The therapeutic efficacy of VCPL on NASH was demonstrated by the reduction of the leakage of hepato-biliary enzymes and the amelioration of liver fibrosis. The OS elevation in NASH rats was measured based on the derivation of reactive oxygen species from liver mitochondrial energy metabolism and on the decrease in plasma SOD-like activity. The aggravation of inflammatory responses was demonstrated by the neutrophil infiltration (elevated myeloperoxidase activity) and the progression of fibrosis in the livers of NASH rats. In addition, the NASH rats without VCPL treatment also exhibited activation of nuclear factor-κB, a key factor in the link between oxidative stress and inflammation. All of these changes were reduced dose-dependently by the VCPL administration. These findings indicate that VCPL may improve hepatic fibrosis or at least suppress the progression of NASH, by breaking the crosstalk between OS and inflammation.

Enhanced free cholesterol, SREBP-2 and StAR expression in human NASH.

PubMed

Caballero, Francisco; Fernández, Anna; De Lacy, Antonio M; Fernández-Checa, Jose C; Caballería, Juan; García-Ruiz, Carmen

2009-04-01

Non-alcoholic fatty liver disease (NAFLD) pathogenesis remains unknown. Due to the emerging role of free cholesterol (FC) in NAFLD, our aim was to examine the correlation between FC accumulation in patients with NAFLD and the expression of enzymes that regulate cholesterol homeostasis. Filipin staining, indicative of FC accumulation, and real-time PCR analyses were performed in 31 NAFLD patients and in seven controls. All NASH patients (n=14) and 4 out of 17 patients with steatosis exhibited filipin staining compared to controls (0 out of 7 subjects with normal liver histology and BMI). Sterol regulatory element-binding protein-2 (SREBP-2) mRNA levels were 7- and 3-fold higher in NASH and steatosis patients, respectively, compared to controls. Since hydroxymethylglutaryl-CoA (HMG-CoA) reductase is the key enzyme in cholesterol synthesis and transcriptionally controlled by SREBP-2 we measured its mRNA levels, being 3- to 4-fold higher in NAFLD compared to controls, without any difference between NASH and steatosis patients. Fatty acid synthase (FAS) and SREBP-1c expression were not significantly induced in NAFLD, while ATP-binding cassette sub-family G member 1 (ABCG1), a transporter involved in cholesterol egress, and acyl-CoA-cholesterol acyltransferase mRNA levels were modestly increased (1.5- to 2.5-fold, p<0.05), regardless of fibrosis. Interestingly, mRNA levels of steroidogenic acute regulatory protein (StAR), a mitochondrial-cholesterol transporting polypeptide, increased 7- and 15-fold in steatosis and NASH patients, respectively, compared to controls. FC increases in NASH and correlates with SREBP-2 induction. Moreover, StAR overexpression in NASH suggests that mitochondrial FC may be a player in disease progression and a novel target for intervention.

Hepatic FTO expression is increased in NASH and its silencing attenuates palmitic acid-induced lipotoxicity.

PubMed

Lim, Andrea; Zhou, Jin; Sinha, Rohit A; Singh, Brijesh K; Ghosh, Sujoy; Lim, Kiat-Hon; Chow, Pierce Kah-Hoe; Woon, Esther C Y; Yen, Paul M

2016-10-21

Non-alcoholic steatohepatitis (NASH) is one of the most common causes of liver failure worldwide. It is characterized by excess fat accumulation, inflammation, and increased lipotoxicity in hepatocytes. Currently, there are limited treatment options for NASH due to lack of understanding of its molecular etiology. In the present study, we demonstrate that the expression of fat mass and obesity associated gene (FTO) is significantly increased in the livers of NASH patients and in a rodent model of NASH. Furthermore, using human hepatic cells, we show that genetic silencing of FTO protects against palmitate-induced oxidative stress, mitochondrial dysfunction, ER stress, and apoptosis in vitro. Taken together, our results show that FTO may have a deleterious role in hepatic cells during lipotoxic conditions, and strongly suggest that up-regulation of FTO may contribute to the increased liver damage in NASH. Copyright © 2016 Elsevier Inc. All rights reserved.

Overexpression of the Vitronectin V10 Subunit in Patients with Nonalcoholic Steatohepatitis: Implications for Noninvasive Diagnosis of NASH.

PubMed

Del Ben, Maria; Overi, Diletta; Polimeni, Licia; Carpino, Guido; Labbadia, Giancarlo; Baratta, Francesco; Pastori, Daniele; Noce, Valeria; Gaudio, Eugenio; Angelico, Francesco; Mancone, Carmine

2018-02-18

Nonalcoholic steatohepatitis (NASH) is the critical stage of nonalcoholic fatty liver disease (NAFLD). The persistence of necroinflammatory lesions and fibrogenesis in NASH is the leading cause of liver cirrhosis and, ultimately, hepatocellular carcinoma. To date, the histological examination of liver biopsies, albeit invasive, remains the means to distinguish NASH from simple steatosis (NAFL). Therefore, a noninvasive diagnosis by serum biomarkers is eagerly needed. Here, by a proteomic approach, we analysed the soluble low-molecular-weight protein fragments flushed out from the liver tissue of NAFL and NASH patients. On the basis of the assumption that steatohepatitis leads to the remodelling of the liver extracellular matrix (ECM), NASH-specific fragments were in silico analysed for their involvement in the ECM molecular composition. The 10 kDa C-terminal fragment of the ECM protein vitronectin (VTN) was then selected as a promising circulating biomarker in discriminating NASH. The analysis of sera of patients provided these major findings: the circulating VTN fragment (i) is overexpressed in NASH patients and positively correlates with the NASH activity score (NAS); (ii) originates from the disulfide bond reduction between the V10 and the V65 subunits. In conclusion, V10 determination in the serum could represent a reliable tool for the noninvasive discrimination of NASH from simple steatosis.

Evolving Concepts in the Pathogenesis of NASH: Beyond Steatosis and Inflammation

PubMed Central

Peverill, William; Powell, Lawrie W.; Skoien, Richard

2014-01-01

Non-alcoholic steatohepatitis (NASH) is characterised by hepatic steatosis and inflammation and, in some patients, progressive fibrosis leading to cirrhosis. An understanding of the pathogenesis of NASH is still evolving but current evidence suggests multiple metabolic factors critically disrupt homeostasis and induce an inflammatory cascade and ensuing fibrosis. The mechanisms underlying these changes and the complex inter-cellular interactions that mediate fibrogenesis are yet to be fully elucidated. Lipotoxicity, in the setting of excess free fatty acids, obesity, and insulin resistance, appears to be the central driver of cellular injury via oxidative stress. Hepatocyte apoptosis and/or senescence contribute to activation of the inflammasome via a variety of intra- and inter-cellular signalling mechanisms leading to fibrosis. Current evidence suggests that periportal components, including the ductular reaction and expansion of the hepatic progenitor cell compartment, may be involved and that the Th17 response may mediate disease progression. This review aims to provide an overview of the pathogenesis of NASH and summarises the evidence pertaining to key mechanisms implicated in the transition from steatosis and inflammation to fibrosis. Currently there are limited treatments for NASH although an increasing understanding of its pathogenesis will likely improve the development and use of interventions in the future. PMID:24830559

Sorafenib prevents liver fibrosis in a non-alcoholic steatohepatitis (NASH) rodent model

PubMed Central

Stefano, J.T.; Pereira, I.V.A.; Torres, M.M.; Bida, P.M.; Coelho, A.M.M.; Xerfan, M.P.; Cogliati, B.; Barbeiro, D.F.; Mazo, D.F.C.; Kubrusly, M.S.; D'Albuquerque, L.A.C.; Souza, H.P.; Carrilho, F.J.; Oliveira, C.P.

2015-01-01

Liver fibrosis occurring as an outcome of non-alcoholic steatohepatitis (NASH) can precede the development of cirrhosis. We investigated the effects of sorafenib in preventing liver fibrosis in a rodent model of NASH. Adult Sprague-Dawley rats were fed a choline-deficient high-fat diet and exposed to diethylnitrosamine for 6 weeks. The NASH group (n=10) received vehicle and the sorafenib group (n=10) received 2.5 mg·kg-1·day-1 by gavage. A control group (n=4) received only standard diet and vehicle. Following treatment, animals were sacrificed and liver tissue was collected for histologic examination, mRNA isolation, and analysis of mitochondrial function. Genes related to fibrosis (MMP9, TIMP1, TIMP2), oxidative stress (HSP60, HSP90, GST), and mitochondrial biogenesis (PGC1α) were evaluated by real-time quantitative polymerase chain reaction (RT-qPCR). Liver mitochondrial oxidation activity was measured by a polarographic method, and cytokines by enzyme-linked immunosorbent assay (ELISA). Sorafenib treatment restored mitochondrial function and reduced collagen deposition by nearly 63% compared to the NASH group. Sorafenib upregulated PGC1α and MMP9 and reduced TIMP1 and TIMP2 mRNA and IL-6 and IL-10 protein expression. There were no differences in HSP60, HSP90 and GST expression. Sorafenib modulated PGC1α expression, improved mitochondrial respiration and prevented collagen deposition. It may, therefore, be useful in the treatment of liver fibrosis in NASH. PMID:25714891

Gary Nash: Repairing a Necessary Connection

ERIC Educational Resources Information Center

Bender, Thomas

2009-01-01

In this essay, the author comments on the life and the contributions of author Gary Nash. Everyone is thanking him for his remarkable engagement with the schools, as a writer of outstanding textbooks and materials for teachers developed through his work as director of the Center for Teaching History in the Schools, and, of course, the National…

NLRP3 inflammasome blockade reduces liver inflammation and fibrosis in experimental NASH in mice.

PubMed

Mridha, Auvro R; Wree, Alexander; Robertson, Avril A B; Yeh, Matthew M; Johnson, Casey D; Van Rooyen, Derrick M; Haczeyni, Fahrettin; Teoh, Narci C-H; Savard, Christopher; Ioannou, George N; Masters, Seth L; Schroder, Kate; Cooper, Matthew A; Feldstein, Ariel E; Farrell, Geoffrey C

2017-05-01

NOD-like receptor protein 3 (NLRP3) inflammasome activation occurs in Non-alcoholic fatty liver disease (NAFLD). We used the first small molecule NLRP3 inhibitor, MCC950, to test whether inflammasome blockade alters inflammatory recruitment and liver fibrosis in two murine models of steatohepatitis. We fed foz/foz and wild-type mice an atherogenic diet for 16weeks, gavaged MCC950 or vehicle until 24weeks, then determined NAFLD phenotype. In mice fed an methionine/choline deficient (MCD) diet, we gavaged MCC950 or vehicle for 6weeks and determined the effects on liver fibrosis. In vehicle-treated foz/foz mice, hepatic expression of NLRP3, pro-IL-1β, active caspase-1 and IL-1β increased at 24weeks, in association with cholesterol crystal formation and NASH pathology; plasma IL-1β, IL-6, MCP-1, ALT/AST all increased. MCC950 treatment normalized hepatic caspase 1 and IL-1β expression, plasma IL-1β, MCP-1 and IL-6, lowered ALT/AST, and reduced the severity of liver inflammation including designation as NASH pathology, and liver fibrosis. In vitro, cholesterol crystals activated Kupffer cells and macrophages to release IL-1β; MCC950 abolished this, and the associated neutrophil migration. MCD diet-fed mice developed fibrotic steatohepatitis; MCC950 suppressed the increase in hepatic caspase 1 and IL-1β, lowered numbers of macrophages and neutrophils in the liver, and improved liver fibrosis. MCC950, an NLRP3 selective inhibitor, improved NAFLD pathology and fibrosis in obese diabetic mice. This is potentially attributable to the blockade of cholesterol crystal-mediated NLRP3 activation in myeloid cells. MCC950 reduced liver fibrosis in MCD-fed mice. Targeting NLRP3 is a logical direction in pharmacotherapy of NASH. Fatty liver disease caused by being overweight with diabetes and a high risk of heart attack, termed non-alcoholic steatohepatitis (NASH), is the most common serious liver disease with no current treatment. There could be several causes of inflammation

Simulation of daily streamflows at gaged and ungaged locations within the Cedar River Basin, Iowa, using a Precipitation-Runoff Modeling System model

USGS Publications Warehouse

Christiansen, Daniel E.

2012-01-01

The U.S. Geological Survey, in cooperation with the Iowa Department of Natural Resources, conducted a study to examine techniques for estimation of daily streamflows using hydrological models and statistical methods. This report focuses on the use of a hydrologic model, the U.S. Geological Survey's Precipitation-Runoff Modeling System, to estimate daily streamflows at gaged and ungaged locations. The Precipitation-Runoff Modeling System is a modular, physically based, distributed-parameter modeling system developed to evaluate the impacts of various combinations of precipitation, climate, and land use on surface-water runoff and general basin hydrology. The Cedar River Basin was selected to construct a Precipitation-Runoff Modeling System model that simulates the period from January 1, 2000, to December 31, 2010. The calibration period was from January 1, 2000, to December 31, 2004, and the validation periods were from January 1, 2005, to December 31, 2010 and January 1, 2000 to December 31, 2010. A Geographic Information System tool was used to delineate the Cedar River Basin and subbasins for the Precipitation-Runoff Modeling System model and to derive parameters based on the physical geographical features. Calibration of the Precipitation-Runoff Modeling System model was completed using a U.S. Geological Survey calibration software tool. The main objective of the calibration was to match the daily streamflow simulated by the Precipitation-Runoff Modeling System model with streamflow measured at U.S. Geological Survey streamflow gages. The Cedar River Basin daily streamflow model performed with a Nash-Sutcliffe efficiency ranged from 0.82 to 0.33 during the calibration period, and a Nash-Sutcliffe efficiency ranged from 0.77 to -0.04 during the validation period. The Cedar River Basin model is meeting the criteria of greater than 0.50 Nash-Sutcliffe and is a good fit for streamflow conditions for the calibration period at all but one location, Austin, Minnesota

Grace Nash: Nine Decades of Graceful Teaching.

ERIC Educational Resources Information Center

Cole, Judith

2000-01-01

Provides information on the life of Grace Nash, an influential educator and pioneer of Orff Schulwerk in the United States, focusing on issues such as her young life, experience as a prisoner-of-war, development of her interest in the Orff, Kodaly, and Laban methods, and her own work. Offers selected resources. (CMK)

Hydrological Modelling using HEC-HMS for Flood Risk Assessment of Segamat Town, Malaysia

NASA Astrophysics Data System (ADS)

Romali, N. S.; Yusop, Z.; Ismail, A. Z.

2018-03-01

This paper presents an assessment of the applicability of using Hydrologic Modelling System developed by the Hydrologic Engineering Center (HEC-HMS) for hydrological modelling of Segamat River. The objective of the model application is to assist in the assessment of flood risk by providing the peak flows of 2011 Segamat flood for the generation of flood mapping of Segamat town. The capability of the model was evaluated by comparing the historical observed data with the simulation results of the selected flood events. The model calibration and validation efficiency was verified using Nash-Sutcliffe model efficiency coefficient. The results demonstrate the interest to implement the hydrological model for assessing flood risk where the simulated peak flow result is in agreement with historical observed data. The model efficiency of the calibrated and validated exercises is 0.90 and 0.76 respectively, which is acceptable.

Memories of Gary Nash over Five Decades

ERIC Educational Resources Information Center

Mellor, Ronald

2009-01-01

It is as a longtime client, softball teammate, colleague, traveling companion, and friend that the author writes this article to honor Gary Nash. He has known him in varied guises in five different decades, and on five continents, with Africa coming in 2009. In this article, the author recalls some of his memories of Gary over five decades.

Pharmacological cholesterol lowering reverses fibrotic NASH in obese, diabetic mice with metabolic syndrome.

PubMed

Van Rooyen, Derrick M; Gan, Lay T; Yeh, Matthew M; Haigh, W Geoffrey; Larter, Claire Z; Ioannou, George; Teoh, Narci C; Farrell, Geoffrey C

2013-07-01

We have recently showed that hyperinsulinemia promotes hepatic free cholesterol (FC) accumulation in obese, insulin-resistant Alms1 mutant (foz/foz) mice with NASH. Here we tested whether cholesterol-lowering drugs reduce stress-activated c-Jun N-terminal kinase (JNK) activation, hepatocyte injury/apoptosis, inflammation, and fibrosis in this metabolic syndrome NASH model. Female foz/foz and WT mice were fed HF (0.2% cholesterol) 16 weeks, before adding ezetimibe (5 mg/kg), atorvastatin (20 mg/kg), or both to diet, another 8 weeks. Hepatic lipidomic analysis, ALT, liver histology, Sirius Red morphometry, hepatic mRNA and protein expression and immunohistochemistry (IHC) for apoptosis (M30), macrophages (F4/80), and polymorphs (myeloperoxidase) were determined. In mice with NASH, ezetimibe/atorvastatin combination normalized hepatic FC but did not alter saturated free fatty acids (FFA) and had minimal effects on other lipids; ezetimibe and atorvastatin had similar but less profound effects. Pharmacological lowering of FC abolished JNK activation, improved serum ALT, apoptosis, liver inflammation/NAFLD activity score, designation as "NASH", macrophage chemotactic protein-1 expression, reduced macrophage and polymorph populations, and liver fibrosis. Cholesterol lowering with ezetimibe/atorvastatin combination reverses hepatic FC but not saturated FFA accumulation. This dampens JNK activation, ALT release, hepatocyte apoptosis, and inflammatory recruitment, with reversal of steatohepatitis pathology and liver fibrosis. Ezetimibe/statin combination is a potent, mechanism-based treatment that could reverse NASH and liver fibrosis. Copyright © 2013 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Beyond Reasonable Doubt: Who Is the Culprit in Lipotoxicity in NAFLD/NASH?

PubMed Central

Arteel, Gavin E.

2016-01-01

BACKGROUND & AIMS Type 2 diabetes and nonalcoholic steatohepatitis (NASH) are associated with insulin resistance and disordered cholesterol homeostasis. We investigated the basis for hepatic cholesterol accumulation with insulin resistance and its relevance to the pathogenesis of NASH. METHODS Alms1 mutant (foz/foz) and wild-type NOD.B10 mice were fed high-fat diets that contained varying percentages of cholesterol; hepatic lipid pools and pathways of cholesterol turnover were determined. Hepatocytes were exposed to insulin concentrations that circulate in diabetic foz/foz mice. RESULTS Hepatic cholesterol accumulation was attributed to up-regulation of low-density lipoprotein receptor via activation of sterol regulatory element binding protein 2 (SREBP-2), reduced biotransformation to bile acids, and suppression of canalicular pathways for cholesterol and bile acid excretion in bile. Exposing primary hepatocytes to concentrations of insulin that circulate in diabetic Alms1 mice replicated the increases in SREBP-2 and low-density lipoprotein receptor and suppression of bile salt export pump. Removing cholesterol from diet prevented hepatic accumulation of free cholesterol and NASH; increasing dietary cholesterol levels exacerbated hepatic accumulation of free cholesterol, hepatocyte injury or apoptosis, macrophage recruitment, and liver fibrosis. CONCLUSIONS In obese, diabetic mice, hyperinsulinemia alters nuclear transcriptional regulators of cholesterol homeostasis, leading to hepatic accumulation of free cholesterol; the resulting cytotoxicity mediates transition of steatosis to NASH. PMID:22422583

Single non-invasive model to diagnose non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH).

PubMed

Otgonsuren, Munkhzul; Estep, Michael J; Hossain, Nayeem; Younossi, Elena; Frost, Spencer; Henry, Linda; Hunt, Sharon; Fang, Yun; Goodman, Zachary; Younossi, Zobair M

2014-12-01

Non-alcoholic steatohepatitis (NASH) is the progressive form of non-alcoholic fatty liver disease (NAFLD). A liver biopsy is considered the "gold standard" for diagnosing/staging NASH. Identification of NAFLD/NASH using non-invasive tools is important for intervention. The study aims were to: develop/validate the predictive performance of a non-invasive model (index of NASH [ION]); assess the performance of a recognized non-invasive model (fatty liver index [FLI]) compared with ION for NAFLD diagnosis; determine which non-invasive model (FLI, ION, or NAFLD fibrosis score [NFS]) performed best in predicting age-adjusted mortality. From the National Health and Nutrition Examination Survey III database, anthropometric, clinical, ultrasound, laboratory, and mortality data were obtained (n = 4458; n = 861 [19.3%] NAFLD by ultrasound) and used to develop the ION model, and then to compare the ION and FLI models for NAFLD diagnosis. For validation and diagnosis of NASH, liver biopsy data were used (n = 152). Age-adjusted Cox proportional hazard modeling estimated the association among the three non-invasive tests (FLI, ION, and NFS) and mortality. FLI's threshold score > 60 and ION's threshold score > 22 had similar specificity (FLI = 80% vs ION = 82%) for NAFLD diagnosis; FLI < 30 (80% sensitivity) and ION < 11 (81% sensitivity) excluded NAFLD. An ION score > 50 predicted histological NASH (92% specificity); the FLI model did not predict NASH or mortality. The ION model was best in predicting cardiovascular/diabetes-related mortality; NFS predicted overall or diabetes-related mortality. The ION model was superior in predicting NASH and mortality compared with the FLI model. Studies are needed to validate ION. © 2014 Journal of Gastroenterology and Hepatology Foundation and Wiley Publishing Asia Pty Ltd.

Distributed Nash Equilibrium Seeking for Generalized Convex Games with Shared Constraints

NASA Astrophysics Data System (ADS)

Sun, Chao; Hu, Guoqiang

2018-05-01

In this paper, we deal with the problem of finding a Nash equilibrium for a generalized convex game. Each player is associated with a convex cost function and multiple shared constraints. Supposing that each player can exchange information with its neighbors via a connected undirected graph, the objective of this paper is to design a Nash equilibrium seeking law such that each agent minimizes its objective function in a distributed way. Consensus and singular perturbation theories are used to prove the stability of the system. A numerical example is given to show the effectiveness of the proposed algorithms.

Long term highly saturated fat diet does not induce NASH in Wistar rats

PubMed Central

Romestaing, Caroline; Piquet, Marie-Astrid; Bedu, Elodie; Rouleau, Vincent; Dautresme, Marianne; Hourmand-Ollivier, Isabelle; Filippi, Céline; Duchamp, Claude; Sibille, Brigitte

2007-01-01

Background Understanding of nonalcoholic steatohepatitis (NASH) is hampered by the lack of a suitable model. Our aim was to investigate whether long term high saturated-fat feeding would induce NASH in rats. Methods 21 day-old rats fed high fat diets for 14 weeks, with either coconut oil or butter, and were compared with rats feeding a standard diet or a methionine choline-deficient (MCD) diet, a non physiological model of NASH. Results MCDD fed rats rapidly lost weight and showed NASH features. Rats fed coconut (86% of saturated fatty acid) or butter (51% of saturated fatty acid) had an increased caloric intake (+143% and +30%). At the end of the study period, total lipid ingestion in term of percentage of energy intake was higher in both coconut (45%) and butter (42%) groups than in the standard (7%) diet group. No change in body mass was observed as compared with standard rats at the end of the experiment. However, high fat fed rats were fattier with enlarged white and brown adipose tissue (BAT) depots, but they showed no liver steatosis and no difference in triglyceride content in hepatocytes, as compared with standard rats. Absence of hepatic lipid accumulation with high fat diets was not related to a higher lipid oxidation by isolated hepatocytes (unchanged ketogenesis and oxygen consumption) or hepatic mitochondrial respiration but was rather associated with a rise in BAT uncoupling protein UCP1 (+25–28% vs standard). Conclusion Long term high saturated fat feeding led to increased "peripheral" fat storage and BAT thermogenesis but did not induce hepatic steatosis and NASH. PMID:17313679

Gary Nash: Preeminent Scholar and Committed Educator

ERIC Educational Resources Information Center

Symcox, Linda

2009-01-01

The author has known Gary Nash as a friend since 1969, but she only began to work with him as a colleague in 1989, when he invited her to join the National Center for History in the Schools (NCHS) as it was just forming. During the seven years she spent as Assistant and then Associate Director of the NCHS, they shared the extraordinary experience…

Nash Equilibria in Noncooperative Predator-Prey Games

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ramos, Angel Manuel; Roubicek, Tomas

2007-09-15

A noncooperative game governed by a distributed-parameter predator-prey system is considered, assuming that two players control initial conditions for predator and prey, respectively. Existence of a Nash equilibrium is shown under the condition that the desired population profiles and the environmental carrying capacity for the prey are sufficiently small. A conceptual approximation algorithm is proposed and analyzed. Finally, numerical simulations are performed, too.

Assessment of runoff and sediment yields using the AnnAGNPS model in a Three-Gorge watershed of China.

PubMed

Hua, Lizhong; He, Xiubin; Yuan, Yongping; Nan, Hongwei

2012-05-01

Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs) and/or conservation programs have been adopted. Watershed models, such as the Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS), have been developed to aid in the evaluation of watershed response to watershed management practices. The model has been applied worldwide and proven to be a very effective tool in identifying the critical areas which had serious erosion, and in aiding in decision-making processes for adopting BMPs and/or conservation programs so that cost/benefit can be maximized and non-point source pollution control can be achieved in the most efficient way. The main goal of this study was to assess the characteristics of soil erosion, sediment and sediment delivery of a watershed so that effective conservation measures can be implemented. To achieve the overall objective of this study, all necessary data for the 4,184 km(2) Daning River watershed in the Three-Gorge region of the Yangtze River of China were assembled. The model was calibrated using observed monthly runoff from 1998 to 1999 (Nash-Sutcliffe coefficient of efficiency of 0.94 and R(2) of 0.94) and validated using the observed monthly runoff from 2003 to 2005 (Nash-Sutcliffe coefficient of efficiency of 0.93 and R(2) of 0.93). Additionally, the model was validated using annual average sediment of 2000-2002 (relative error of -0.34) and 2003-2004 (relative error of 0.18) at Wuxi station. Post validation simulation showed that approximately 48% of the watershed was under the soil loss tolerance released by the Ministry of Water Resources of China (500 t·km(-2)·y(-1)). However, 8% of the watershed had soil erosion of exceeding 5,000 t·km(-2)·y(-1). Sloping areas and low coverage areas are the main source of soil loss in the

Progression and Regression of Hepatic Lesions in a Mouse Model of NASH Induced by Dietary Intervention and Its Implications in Pharmacotherapy.

PubMed

Ding, Zhi-Ming; Xiao, Yue; Wu, Xikun; Zou, Haixia; Yang, Shurong; Shen, Yiyun; Xu, Juehua; Workman, Heather C; Usborne, Amy L; Hua, Haiqing

2018-01-01

Understanding of the temporal changes of hepatic lesions in the progression and regression of non-alcoholic steatohepatitis (NASH) is vital to elucidation of the pathogenesis of NASH, and critical to the development of a strategy for NASH pharmacotherapy. There are challenges in studying hepatic lesion progression and regression in NASH patients due to the slow development of NASH in humans, one being the requirement for multiple biopsies during the longitudinal follow-up. Here we studied lesion progression and regression in the diet-induced animal model of NASH by application or removal of the pathogenic diet for multiple time periods. Male C57BL/6 mice fed Western diet developed progressive hepatic steatosis/macrovesicular vacuolation, inflammation, and hepatocyte degeneration, as well as perisinusoidal fibrosis and occasionally portal fibrosis as early as 2 months after initiation of the Western diet. In the same period, the mice exhibited elevated ALT (alanine aminotransferase) and AST (aspartate aminotransferase) enzyme activities, CK18 (cytokeratin-18), PIIINP (N-terminal propeptide of type III collagen), and TIMP-1 (tissue inhibitor of metalloproteinase-1). Hepatic steatosis diminished rapidly when the Western diet was replaced by normal rodent chow diet and hepatic inflammation and hepatocyte degeneration were also reduced. Interestingly, perisinusoidal fibrosis and portal fibrosis regressed 8 months after chow diet replacement. To understand pharmacotherapy for NASH, mice with established NASH hepatic lesions were treated with either FXR agonist obeticholic acid (Ocaliva), or CCR2/5 antagonist Cenicriviroc. Similar to the diet replacement, metabolic modulator Ocaliva markedly reduced steatosis/macrovesicular vacuolation, hepatic inflammation, and hepatocyte degeneration effectively, but exhibited no significant effect on liver fibrosis. Anti-inflammation drug Cenicriviroc, on the other hand, markedly decreased inflammation and hepatocyte degeneration, and

Gut microbiome composition in lean patients with NASH is associated with liver damage independent of caloric intake: A prospective pilot study.

PubMed

Duarte, S M B; Stefano, J T; Miele, L; Ponziani, F R; Souza-Basqueira, M; Okada, L S R R; de Barros Costa, F G; Toda, K; Mazo, D F C; Sabino, E C; Carrilho, F J; Gasbarrini, A; Oliveira, C P

2018-04-01

The aim of the study was to compare the gut microbiomes from obese and lean patients with or without NASH to outline phenotypic differences. We performed a cross-sectional pilot study comprising biopsy-proven NASH patients grouped according to BMI. Microbiome DNA was extracted from stool samples, and PCR amplification was performed using primers for the V4 region of the 16S rRNA gene. The amplicons were sequenced using the Ion PGM Torrent platform, and data were analyzed using QIIME software. Macronutrient consumption was analyzed by a 7-day food record. Liver fibrosis ≥ F2 was associated with increased abundance of Lactobacilli (p = 0.0007). NASH patients showed differences in Faecalibacterium, Ruminococcus, Lactobacillus and Bifidobacterium abundance compared with the control group. Lean NASH patients had a 3-fold lower abundance of Faecalibacterium and Ruminococcus (p = 0.004), obese NASH patients were enriched in Lactobacilli (p = 0.002), and overweight NASH patients had reduced Bifidobacterium (p = 0.018). Moreover, lean NASH patients showed a deficiency in Lactobacillus compared with overweight and obese NASH patients. This group also appeared similar to the control group with regard to gut microbiome alpha diversity. Although there were qualitative differences between lean NASH and overweight/obese NASH, they were not statistically significant (p = 0.618). The study limitations included a small sample size, a food questionnaire that collected only qualitative and semi-quantitative data, and variations in group gender composition that may influence differences in FXR signaling, bile acids metabolism and the composition of gut microbiota. Our preliminary finding of a different pathogenetic process in lean NASH patients needs to be confirmed by larger studies, including those with patient populations stratified by sex and dietary habits. Copyright © 2017 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the

Nash equilibrium in differential games and the construction of the programmed iteration method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Averboukh, Yurii V

This work is devoted to the study of nonzero-sum differential games. The set of payoffs in a situation of Nash equilibrium is examined. It is shown that the set of payoffs in a situation of Nash equilibrium coincides with the set of values of consistent functions which are fixed points of the program absorption operator. A condition for functions to be consistent is given in terms of the weak invariance of the graph of the functions under a certain differential inclusion. Bibliography: 18 titles.

Surviving History: Gary Nash and the National Standards

ERIC Educational Resources Information Center

Bingham, Marjorie

2009-01-01

In this article, the author recalls the first time she met Gary Nash. He came to speak at a Bradley Commission meeting and she was rather surprised to see him appear and to find out that he, along with Charlotte Crabtree, was involved in a National Center for History. She gives three reasons for her surprise which she thinks may tell aspects of…

A Graphical Analysis of the Cournot-Nash and Stackelberg Models.

ERIC Educational Resources Information Center

Fulton, Murray

1997-01-01

Shows how the Cournot-Nash and Stackelberg equilibria can be represented in the familiar supply-demand graphical framework, allowing a direct comparison with the monopoly, competitive, and industrial organization models. This graphical analysis is represented throughout the article. (MJP)

Factors predicting non-alcoholic steatohepatitis (NASH) and advanced fibrosis in patients with non-alcoholic fatty liver disease (NAFLD).

PubMed

Tasneem, Abbas Ali; Luck, Nasir Hassan; Majid, Zain

2018-04-01

Introduction To determine the factors predicting non-alcoholic steatohepatitis (NASH) and advanced fibrosis in patients with non-alcoholic fatty liver disease (NAFLD). Methodology All patients aged >18 years and having a fatty liver on abdominal ultrasound (US), presenting from January 2011 to January 2017, were included. A liver biopsy was performed on all the patients. Results Of 96 patients undergoing liver biopsy for non-alcoholic fatty liver disease (NAFLD), 76 (79.2%) were men. On liver US, diffuse fatty liver (DFL) was noted in 68 (70.8%) patients. Liver biopsy showed non-alcoholic steatohepatitis (NASH) in 78 (81.3%) patients. Factors associated with NASH were male gender, body mass index (BMI) > 27 kg/m 2 , DFL and raised alanine aminotransferase (ALT). A GULAB score (based on gender, US liver findings, lipid (fasting) levels, ALT level and BMI) of ≥5 predicted NASH with 82.05% sensitivity. Factors associated with advanced fibrosis in NAFLD were age >40 years, diabetes mellitus, AST/ALT ratio > 1 and raised GGT. Conclusion NASH is common in patients with male gender, high BMI, DFL on liver US, raised ALT and GULAB score ≥5.

Development and application of a catchment scale pesticide fate and transport model for use in drinking water risk assessment.

PubMed

Pullan, S P; Whelan, M J; Rettino, J; Filby, K; Eyre, S; Holman, I P

2016-09-01

This paper describes the development and application of IMPT (Integrated Model for Pesticide Transport), a parameter-efficient tool for predicting diffuse-source pesticide concentrations in surface waters used for drinking water supply. The model was applied to a small UK headwater catchment with high frequency (8h) pesticide monitoring data and to five larger catchments (479-1653km(2)) with sampling approximately every 14days. Model performance was good for predictions of both flow (Nash Sutcliffe Efficiency generally >0.59 and PBIAS <10%) and pesticide concentrations, although low sampling frequency in the larger catchments is likely to mask the true episodic nature of exposure. The computational efficiency of the model, along with the fact that most of its parameters can be derived from existing national soil property data mean that it can be used to rapidly predict pesticide exposure in multiple surface water resources to support operational and strategic risk assessments. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Critical Realism and Statistical Methods--A Response to Nash

ERIC Educational Resources Information Center

Scott, David

2007-01-01

This article offers a defence of critical realism in the face of objections Nash (2005) makes to it in a recent edition of this journal. It is argued that critical and scientific realisms are closely related and that both are opposed to statistical positivism. However, the suggestion is made that scientific realism retains (from statistical…

Follow-up CT findings of tamoxifen-induced non-alcoholic steatohepatitis (NASH) of breast cancer patients treated with bezafibrate.

PubMed

Ogawa, Yasuhiro; Murata, Yoriko; Saibara, Toshiji; Nishioka, Akihito; Kariya, Shinji; Yoshida, Shoji

2003-01-01

One-third of the breast cancer patients who underwent tamoxifen intake showed less than 0.9 of their liver/spleen CT (computed tomography) ratio on their annual CT study, and were diagnosed as having fatty liver (hepatic steatosis). Among them, patients who showed a lower liver/spleen CT ratio of less than 0.5 were recommended to undergo needle biopsy of the liver in order to obtain histopathological confirmation of non-alcoholic steatohepatitis (NASH), with 15 patients undergoing needle biopsy of the liver. As a result, 14 out of the 15 patients were diagnosed as having NASH, and these patients were additionally administered bezafibrate in order to prevent possible progressive changes of NASH into liver cirrhosis. In this study, we show the changes of follow-up CT findings of 6 patients with histopathologically-proven NASH who continued to undergo bezafibrate intake after the diagnosis of NASH. Two patients showed almost complete improvement as indicated by the liver/spleen CT ratio several months after completion of a tamoxifen intake of 5 years, and another 3 showed partial improvement on their liver/spleen CT ratio by bezafibrate intake in spite of continuing tamoxifen intake. Another patient with diabetes mellitus (type II) showed a continually decreasing liver/spleen CT ratio during adjuvant tamoxifen in spite of bezafibrate intake. Therefore, we concluded that the progression of NASH could be prevented by bezafibrate without any interruption of adjuvant tamoxifen treatment. For patients with diabetes mellitus, critical follow-up using CT study and laboratory tests is considered essential.

Application of dimensionless sediment rating curves to predict suspended-sediment concentrations, bedload, and annual sediment loads for rivers in Minnesota

USGS Publications Warehouse

Ellison, Christopher A.; Groten, Joel T.; Lorenz, David L.; Koller, Karl S.

2016-10-27

-of-fit that included proximity of the model(s) fitted line to the 95-percent confidence intervals of the site-specific model, Nash-Sutcliffe Efficiency values, model biases, and deviation of annual sediment loads from each model to the annual sediment loads calculated from measured data.Composite plots comparing Pagosa Springs DSRCs, Minnesota DSRCs, site-specific regression models, and measured data indicated that regionally developed DSRCs (Minnesota DSRC models) more closely approximated measured data for nearly every site. Pagosa Springs DSRC models had markedly larger exponents (slopes) when compared to the Minnesota DSRC models and the site-specific regression models, and over-represent SSC and bedload at streamflows exceeding bankfull. The Nash-Sutcliffe Efficiency values for the Minnesota DSRC model for suspended-sediment concentrations closely matched Nash-Sutcliffe Efficiency values of the site-specific regression models for 12 out of 16 sites. Nash-Sutcliffe Efficiency values associated with Minnesota DSRCs were greater than those associated with Pagosa Springs DSRCs for every site except the Whitewater River near Beaver, Minnesota site. Pagosa Springs DSRC models were less accurate than the mean of the measured data at predicting SSC values for one-half of the sites for good/fair stability sites and one-half of the sites for poor stability sites. Relative model biases were calculated and determined to be substantial (greater than 5 percent) for Pagosa Springs and Minnesota models, with Minnesota models having a lower mean model bias. For predicted annual suspended-sediment loads (SSL), the Minnesota DSRC models for good/fair and poor stream stability sites more closely approximated the annual SSLs calculated from the measured data as compared to the Pagosa Springs DSRC model.Results of data analyses indicate that DSRC models developed using data collected in Minnesota were more effective at compensating for differences in individual stream characteristics across a

Kupffer Cells Undergo Fundamental Changes during the Development of Experimental NASH and Are Critical in Initiating Liver Damage and Inflammation

PubMed Central

Reid, D. T.; Reyes, J. L.; McDonald, B. A.; Vo, T.; Reimer, R. A.; Eksteen, B.

2016-01-01

Non-alcoholic fatty liver disease has become the leading liver disease in North America and is associated with the progressive inflammatory liver disease non-alcoholic steatohepatitis (NASH). Considerable effort has been made to understand the role of resident and recruited macrophage populations in NASH however numerous questions remain. Our goal was to characterize the dynamic changes in liver macrophages during the initiation of NASH in a murine model. Using the methionine-choline deficient diet we found that liver-resident macrophages, Kupffer cells were lost early in disease onset followed by a robust infiltration of Ly-6C+ monocyte-derived macrophages that retained a dynamic phenotype. Genetic profiling revealed distinct patterns of inflammatory gene expression between macrophage subsets. Only early depletion of liver macrophages using liposomal clodronate prevented the development of NASH in mice suggesting that Kupffer cells are critical for the orchestration of inflammation during experimental NASH. Increased understanding of these dynamics may allow us to target potentially harmful populations whilst promoting anti-inflammatory or restorative populations to ultimately guide the development of effective treatment strategies. PMID:27454866

 The product of triglycerides and glucose as biomarker for screening simple steatosis and NASH in asymptomatic women.

PubMed

Simental-Mendía, Luis E; Simental-Mendía, Esteban; Rodríguez-Hernández, Heriberto; Rodríguez-Morán, Martha; Guerrero-Romero, Fernando

2016-01-01

 Introduction and aim. Given that early identification of non-alcoholic fatty liver disease (NAFLD) is an important issue for primary prevention of hepatic disease, the objectives of this study were to evaluate the efficacy of the product of triglyceride and glucose levels (TyG) for screening simple steatosis and non-alcoholic steatohepatitis (NASH) in asymptomatic women, and to compare its efficacy vs. other biomarkers for recognizing NAFLD. Asymptomatic women aged 20 to 65 years were enrolled into a cross-sectional study. The optimal values of TyG, for screening simple steatosis and NASH were established on a Receiver Operating Characteristic scatter plot; the sensitivity, specificity, and likelihood ratios of TyG index were estimated versus liver biopsy. According sensitivity and specificity, the efficacy of TyG was compared versus the well-known clinical biomarkers for recognizing NAFLD. A total of 50 asymptomatic women were enrolled. The best cutoff point of TyG for screening simple steatosis was 4.58 (sensitivity 0.94, specificity 0.69); in addition, the best cutoff point of TyG index for screening NASH was 4.59 (sensitivity 0.87, specificity 0.69). The positive and negative likelihood ratios were 3.03 and 0.08 for simple steatosis, and 2.80 and 0.18 for NASH. As compared versus SteatoTest, NashTest, Fatty liver index, and Algorithm, the TyG showed to be the best test for screening. TyG has high sensitivity and low negative likelihood ratio; as compared with other clinical biomarkers, the TyG showed to be the best test for screening simple steatosis and NASH.

Information Structures in Nash and Leader-Follower Strategies.

DTIC Science & Technology

1981-01-01

OICkASSIPICATION/ OOWNGRAOING IS. OISTNIIIUTION STATEMINT (ao tD. esPort ) * Approved for public release; distribution unlimited. 17. DISTRIBUTION STATEMENT...problems and two market models of duopoly ith this type of information structure are extensively analyzed and examined. DO jAN7, 1473 EDIION OF NV SS IS...information 3 structure is employed in both Nash games and optimal coordination problems and two market models of duopoly with this type of information

On Nash Equilibrium and Evolutionarily Stable States That Are Not Characterised by the Folk Theorem

PubMed Central

Li, Jiawei; Kendall, Graham

2015-01-01

In evolutionary game theory, evolutionarily stable states are characterised by the folk theorem because exact solutions to the replicator equation are difficult to obtain. It is generally assumed that the folk theorem, which is the fundamental theory for non-cooperative games, defines all Nash equilibria in infinitely repeated games. Here, we prove that Nash equilibria that are not characterised by the folk theorem do exist. By adopting specific reactive strategies, a group of players can be better off by coordinating their actions in repeated games. We call it a type-k equilibrium when a group of k players coordinate their actions and they have no incentive to deviate from their strategies simultaneously. The existence and stability of the type-k equilibrium in general games is discussed. This study shows that the sets of Nash equilibria and evolutionarily stable states have greater cardinality than classic game theory has predicted in many repeated games. PMID:26288088

Remediating Language Deficient/Dyslexic College Students: An Interview with Robert Nash.

ERIC Educational Resources Information Center

Lundquist, Arlene J.; Nash, Robert

1988-01-01

Robert Nash responds to questions concerning his personal and professional background, the Simultaneous Multisensory Instructional Procedure for Teaching the Complete Sound Structure of the Language, problems associated with dyslexia, the social/emotional impact of learning disabilities, and the University of Wisconsin's Project Success for…

77 FR 10553 - Match-E-Be-Nash-She-Wish Band of Pottawatomi Indians (Gun Lake)-Amendment to Liquor Beverage...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-22

... DEPARTMENT OF THE INTERIOR Bureau of Indian Affairs Match-E-Be-Nash-She-Wish Band of Pottawatomi Indians (Gun Lake)-- Amendment to Liquor Beverage Control Ordinance AGENCY: Bureau of Indian Affairs, Interior. ACTION: Notice SUMMARY: This notice publishes the amendments to the Match-E-Be-Nash- She-Wish...

Cholesterol-lowering drugs cause dissolution of cholesterol crystals and disperse Kupffer cell crown-like structures during resolution of NASH.

PubMed

Ioannou, George N; Van Rooyen, Derrick M; Savard, Christopher; Haigh, W Geoffrey; Yeh, Matthew M; Teoh, Narci C; Farrell, Geoffrey C

2015-02-01

Cholesterol crystals form within hepatocyte lipid droplets in human and experimental nonalcoholic steatohepatitis (NASH) and are the focus of crown-like structures (CLSs) of activated Kupffer cells (KCs). Obese, diabetic Alms1 mutant (foz/foz) mice were a fed high-fat (23%) diet containing 0.2% cholesterol for 16 weeks and then assigned to four intervention groups for 8 weeks: a) vehicle control, b) ezetimibe (5 mg/kg/day), c) atorvastatin (20 mg/kg/day), or d) ezetimibe and atorvastatin. Livers of vehicle-treated mice developed fibrosing NASH with abundant cholesterol crystallization within lipid droplets calculated to extend over 3.3% (SD, 2.2%) of liver surface area. Hepatocyte lipid droplets with prominent cholesterol crystallization were surrounded by TNFα-positive (activated) KCs forming CLSs (≥ 3 per high-power field). KCs that formed CLSs stained positive for NLRP3, implicating activation of the NLRP3 inflammasome in response to cholesterol crystals. In contrast, foz/foz mice treated with ezetimibe and atorvastatin showed near-complete resolution of cholesterol crystals [0.01% (SD, 0.02%) of surface area] and CLSs (0 per high-power field), with amelioration of fibrotic NASH. Ezetimibe or atorvastatin alone had intermediate effects on cholesterol crystallization, CLSs, and NASH. These findings are consistent with a causative link between exposure of hepatocytes and KCs to cholesterol crystals and with the development of NASH possibly mediated by NLRP3 activation.

Models for estimating daily rainfall erosivity in China

NASA Astrophysics Data System (ADS)

Xie, Yun; Yin, Shui-qing; Liu, Bao-yuan; Nearing, Mark A.; Zhao, Ying

2016-04-01

The rainfall erosivity factor (R) represents the multiplication of rainfall energy and maximum 30 min intensity by event (EI30) and year. This rainfall erosivity index is widely used for empirical soil loss prediction. Its calculation, however, requires high temporal resolution rainfall data that are not readily available in many parts of the world. The purpose of this study was to parameterize models suitable for estimating erosivity from daily rainfall data, which are more widely available. One-minute resolution rainfall data recorded in sixteen stations over the eastern water erosion impacted regions of China were analyzed. The R-factor ranged from 781.9 to 8258.5 MJ mm ha-1 h-1 y-1. A total of 5942 erosive events from one-minute resolution rainfall data of ten stations were used to parameterize three models, and 4949 erosive events from the other six stations were used for validation. A threshold of daily rainfall between days classified as erosive and non-erosive was suggested to be 9.7 mm based on these data. Two of the models (I and II) used power law functions that required only daily rainfall totals. Model I used different model coefficients in the cool season (Oct.-Apr.) and warm season (May-Sept.), and Model II was fitted with a sinusoidal curve of seasonal variation. Both Model I and Model II estimated the erosivity index for average annual, yearly, and half-month temporal scales reasonably well, with the symmetric mean absolute percentage error MAPEsym ranging from 10.8% to 32.1%. Model II predicted slightly better than Model I. However, the prediction efficiency for the daily erosivity index was limited, with the symmetric mean absolute percentage error being 68.0% (Model I) and 65.7% (Model II) and Nash-Sutcliffe model efficiency being 0.55 (Model I) and 0.57 (Model II). Model III, which used the combination of daily rainfall amount and daily maximum 60-min rainfall, improved predictions significantly, and produced a Nash-Sutcliffe model efficiency

Assessment of Runoff and Sediment Yields Using the AnnAGNPS Model in a Three-Gorge Watershed of China

PubMed Central

Hua, Lizhong; He, Xiubin; Yuan, Yongping; Nan, Hongwei

2012-01-01

Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs) and/or conservation programs have been adopted. Watershed models, such as the Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS), have been developed to aid in the evaluation of watershed response to watershed management practices. The model has been applied worldwide and proven to be a very effective tool in identifying the critical areas which had serious erosion, and in aiding in decision-making processes for adopting BMPs and/or conservation programs so that cost/benefit can be maximized and non-point source pollution control can be achieved in the most efficient way. The main goal of this study was to assess the characteristics of soil erosion, sediment and sediment delivery of a watershed so that effective conservation measures can be implemented. To achieve the overall objective of this study, all necessary data for the 4,184 km2 Daning River watershed in the Three-Gorge region of the Yangtze River of China were assembled. The model was calibrated using observed monthly runoff from 1998 to 1999 (Nash-Sutcliffe coefficient of efficiency of 0.94 and R2 of 0.94) and validated using the observed monthly runoff from 2003 to 2005 (Nash-Sutcliffe coefficient of efficiency of 0.93 and R2 of 0.93). Additionally, the model was validated using annual average sediment of 2000–2002 (relative error of −0.34) and 2003–2004 (relative error of 0.18) at Wuxi station. Post validation simulation showed that approximately 48% of the watershed was under the soil loss tolerance released by the Ministry of Water Resources of China (500 t·km−2·y−1). However, 8% of the watershed had soil erosion of exceeding 5,000 t·km−2·y−1. Sloping areas and low coverage areas are the main source of soil loss in the

Non-Alcoholic Fatty Liver Disease (NAFLD) and Non-Alcoholic Steatohepatitis (NASH) in HIV.

PubMed

Rockstroh, Jürgen Kurt

2017-04-01

Abnormal liver enzymes (LE) are common in patients infected with the human immunodeficiency virus (HIV) even in the absence of viral hepatitis or alcohol abuse. With availability of antiretroviral combination therapy, life expectancy has improved dramatically and as a consequence the spectrum of liver disease is changing. Increased reports on the development of non-alcoholic fatty liver disease (NAFLD) or non-alcoholic steatohepatitis (NASH) in HIV coinfected patients raise questions around prevalence, clinical manifestations, and clinical outcome of these liver diseases in HIV coinfection. Moreover, the potential impact of combination antiretroviral therapy as well as direct HIV effects on the emergence of non-alcoholic fatty liver disease needs to be explored. This review summarizes the recent literature on NAFLD and NASH in HIV.

Optimization, Monotonicity and the Determination of Nash Equilibria — An Algorithmic Analysis

NASA Astrophysics Data System (ADS)

Lozovanu, D.; Pickl, S. W.; Weber, G.-W.

2004-08-01

This paper is concerned with the optimization of a nonlinear time-discrete model exploiting the special structure of the underlying cost game and the property of inverse matrices. The costs are interlinked by a system of linear inequalities. It is shown that, if the players cooperate, i.e., minimize the sum of all the costs, they achieve a Nash equilibrium. In order to determine Nash equilibria, the simplex method can be applied with respect to the dual problem. An introduction into the TEM model and its relationship to an economic Joint Implementation program is given. The equivalence problem is presented. The construction of the emission cost game and the allocation problem is explained. The assumption of inverse monotony for the matrices leads to a new result in the area of such allocation problems. A generalization of such problems is presented.

NASH resolution is associated with improvements in HDL and triglyceride levels but not improvement in LDL or non-HDL-C levels.

PubMed

Corey, K E; Vuppalanchi, R; Wilson, L A; Cummings, O W; Chalasani, N

2015-02-01

Nonalcoholic steatohepatitis (NASH) is associated with dyslipidemia and cardiovascular disease (CVD). To determine the relationship between resolution of NASH and dyslipidemia. Individuals in the Pioglitazone vs. Vitamin E vs. Placebo for the Treatment of Nondiabetic Patients with Nonalcoholic Steatohepatitis (PIVENS) trial with paired liver biopsies and fasting lipid levels were included (N = 222). In the PIVENS trial individuals were randomised to pioglitazone 30 mg, vitamin E 800 IU or placebo for 96 weeks. Change in lipid levels at 96 weeks was compared between those with and without NASH resolution. Dyslipidemia at baseline was frequent, with low high-density lipoprotein (HDL) (<40 mg/dL in men or <50 mg/dL in women) in 63%, hypertriglyceridaemia (≥150 mg/dL) in 46%, hypercholesterolaemia (≥200 mg/dL) in 47% and triglycerides (TG)/HDL >5.0 in 25%. Low-density lipoprotein (LD) ≥160 mg/dL was found in 16% and elevated non-HDL cholesterol (non-HDL-C) (≥130 mg/dL) in 73%. HDL increased with NASH resolution but decreased in those without resolution (2.9 mg/dL vs. -2.5 mg/dL, P < 0.001). NASH resolution was associated with significant decreases in TG and TG/HDL ratio compared to those without resolution (TG: -21.1 vs. -2.3 mg/dL, P = 0.03 and TG/HDL: -0.7 vs. 0.1, P = 0.003). Non-HDL-C, LDL and cholesterol decreased over 96 weeks in both groups, but there was no significant difference between groups. Treatment group did not impact lipids. NASH resolution is associated with improvements in TG and HDL but not in other cardiovascular disease risk factors including LDL and non-HDL-C levels. Individuals with resolution of NASH may still be at increased risk of cardiovascular disease. ClinicalTrials.gov identifier: NCT00063622. © 2014 John Wiley & Sons Ltd.

Applicability of TOPMODEL in the mountainous catchments in the upper Nysa Kłodzka river basin (SW Poland)

NASA Astrophysics Data System (ADS)

Jeziorska, Justyna; Niedzielski, Tomasz

2018-03-01

River basins located in the Central Sudetes (SW Poland) demonstrate a high vulnerability to flooding. Four mountainous basins and the corresponding outlets have been chosen for modeling the streamflow dynamics using TOPMODEL, a physically based semi-distributed topohydrological model. The model has been calibrated using the Monte Carlo approach—with discharge, rainfall, and evapotranspiration data used to estimate the parameters. The overall performance of the model was judged by interpreting the efficiency measures. TOPMODEL was able to reproduce the main pattern of the hydrograph with acceptable accuracy for two of the investigated catchments. However, it failed to simulate the hydrological response in the remaining two catchments. The best performing data set obtained Nash-Sutcliffe efficiency of 0.78. This data set was chosen to conduct a detailed analysis aiming to estimate the optimal timespan of input data for which TOPMODEL performs best. The best fit was attained for the half-year time span. The model was validated and found to reveal good skills.

A fractional factorial probabilistic collocation method for uncertainty propagation of hydrologic model parameters in a reduced dimensional space

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Huang, W.; Fan, Y. R.; Li, Z.

2015-10-01

In this study, a fractional factorial probabilistic collocation method is proposed to reveal statistical significance of hydrologic model parameters and their multi-level interactions affecting model outputs, facilitating uncertainty propagation in a reduced dimensional space. The proposed methodology is applied to the Xiangxi River watershed in China to demonstrate its validity and applicability, as well as its capability of revealing complex and dynamic parameter interactions. A set of reduced polynomial chaos expansions (PCEs) only with statistically significant terms can be obtained based on the results of factorial analysis of variance (ANOVA), achieving a reduction of uncertainty in hydrologic predictions. The predictive performance of reduced PCEs is verified by comparing against standard PCEs and the Monte Carlo with Latin hypercube sampling (MC-LHS) method in terms of reliability, sharpness, and Nash-Sutcliffe efficiency (NSE). Results reveal that the reduced PCEs are able to capture hydrologic behaviors of the Xiangxi River watershed, and they are efficient functional representations for propagating uncertainties in hydrologic predictions.

Efficacy of docosahexaenoic acid-choline-vitamin E in paediatric NASH: a randomized controlled clinical trial.

PubMed

Zöhrer, Evelyn; Alisi, Anna; Jahnel, Jörg; Mosca, Antonella; Della Corte, Claudia; Crudele, Annalisa; Fauler, Günter; Nobili, Valerio

2017-09-01

Nonalcoholic steatohepatitis (NASH), a progressive form of nonalcoholic fatty liver disease, is one of the most common hepatic diseases in children. We conducted a randomized controlled clinical trial on children with biopsy-proven NASH based on a combinatorial nutritional approach compared with placebo. Participants were assigned to lifestyle modification plus placebo or lifestyle modification plus a mix containing docosahexaenoic acid, choline, and vitamin E (DHA-CHO-VE). Forty children and adolescents participated in the entire trial. The primary outcome was the improvement of liver hyperechogenicity. Secondary outcomes included alterations of alanine aminotransferase (ALT) and other metabolic parameters. Furthermore, changes of serum bile acids (BA) and plasma fibroblast growth factor 19 (FGF19) levels were evaluated as inverse biomarkers of disease severity. At the end of the study, we observed a significant decrease in severe steatosis in the treatment group (50% to 5%, p = 0.001). Furthermore, although the anthropometric and biochemical measurements in the placebo and DHA-CHO-VE groups were comparable at baseline, at the end of the study ALT and fasting glucose levels improved only in the treatment group. Finally, we found that BA levels were not influenced whereas FGF19 levels were significantly increased by DHA-CHO-VE. The results suggest that a combination of DHA, VE, and CHO could improve steatosis and reduce ALT and glucose levels in children with NASH. However, further studies are needed to assess the impact of a DHA and VE combination on repair of liver damage in paediatric NASH.

Ensemble hydrological forecast efficiency evolution over various issue dates and lead-time: case study for the Cheboksary reservoir (Volga River)

NASA Astrophysics Data System (ADS)

Gelfan, Alexander; Moreido, Vsevolod

2017-04-01

Ensemble hydrological forecasting allows for describing uncertainty caused by variability of meteorological conditions in the river basin for the forecast lead-time. At the same time, in snowmelt-dependent river basins another significant source of uncertainty relates to variability of initial conditions of the basin (snow water equivalent, soil moisture content, etc.) prior to forecast issue. Accurate long-term hydrological forecast is most crucial for large water management systems, such as the Cheboksary reservoir (the catchment area is 374 000 sq.km) located in the Middle Volga river in Russia. Accurate forecasts of water inflow volume, maximum discharge and other flow characteristics are of great value for this basin, especially before the beginning of the spring freshet season that lasts here from April to June. The semi-distributed hydrological model ECOMAG was used to develop long-term ensemble forecast of daily water inflow into the Cheboksary reservoir. To describe variability of the meteorological conditions and construct ensemble of possible weather scenarios for the lead-time of the forecast, two approaches were applied. The first one utilizes 50 weather scenarios observed in the previous years (similar to the ensemble streamflow prediction (ESP) procedure), the second one uses 1000 synthetic scenarios simulated by a stochastic weather generator. We investigated the evolution of forecast uncertainty reduction, expressed as forecast efficiency, over various consequent forecast issue dates and lead time. We analyzed the Nash-Sutcliffe efficiency of inflow hindcasts for the period 1982 to 2016 starting from 1st of March with 15 days frequency for lead-time of 1 to 6 months. This resulted in the forecast efficiency matrix with issue dates versus lead-time that allows for predictability identification of the basin. The matrix was constructed separately for observed and synthetic weather ensembles.

The Combination of Blueberry Juice and Probiotics Ameliorate Non-Alcoholic Steatohepatitis (NASH) by Affecting SREBP-1c/PNPLA-3 Pathway via PPAR-α.

PubMed

Ren, Tingting; Zhu, Juanjuan; Zhu, Lili; Cheng, Mingliang

2017-02-27

Nonalcoholic steatohepatitis (NASH) is liver inflammation and a major threat to public health. Several pharmaceutical agents have been used for NASH therapy but their high-rate side effects limit the use. Blueberry juice and probiotics (BP) have anti-inflammation and antibacterial properties, and may be potential candidates for NASH therapy. To understand the molecular mechanism, Sprague Dawley rats were used to create NASH models and received different treatments. Liver tissues were examined using HE (hematoxylin and eosin) and ORO (Oil Red O) stain, and serum biochemical indices were measured. The levels of peroxisome proliferators-activated receptor (PPAR)-α, sterol regulatory element binding protein-1c (SREBP-1c), Patatin-like phospholipase domain-containing protein 3 (PNPLA-3), inflammatory cytokines and apoptosis biomarkers in liver tissues were measured by qRT-PCR and Western blot. HE and ORO analysis indicated that the hepatocytes were seriously damaged with more and larger lipid droplets in NASH models while BP reduced the number and size of lipid droplets ( p < 0.05). Meanwhile, BP increased the levels of SOD (superoxide dismutase), GSH (reduced glutathione) and HDL-C (high-density lipoprotein cholesterol), and reduced the levels of AST (aspartate aminotransferase), ALT (alanine aminotransferase), TG (triglycerides), LDL-C (low-density lipoprotein cholesterol) and MDA (malondialdehyde) in NASH models ( p < 0.05). BP increased the level of PPAR-α (Peroxisome proliferator-activated receptor α), and reduced the levels of SREBP-1c (sterol regulatory element binding protein-1c) and PNPLA-3 (Patatin-like phospholipase domain-containing protein 3) ( p < 0.05). BP reduced hepatic inflammation and apoptosis by affecting IL-6 (interleukin 6), TNF-α (Tumor necrosis factor α), caspase-3 and Bcl-2 in NASH models. Furthermore, PPAR-α inhibitor increased the level of SREBP-1c and PNPLA-3. Therefore, BP prevents NASH progression by affecting SREBP-1c/PNPLA-3

TLR9 is up-regulated in human and murine NASH: pivotal role in inflammatory recruitment and cell survival.

PubMed

Mridha, Auvro R; Haczeyni, Fahrettin; Yeh, Matthew M; Haigh, W Geoffrey; Ioannou, George N; Barn, Vanessa; Ajamieh, Hussam; Adams, Leon; Hamdorf, Jeffrey M; Teoh, Narci C; Farrell, Geoffrey C

2017-08-15

Background and aims : TLR9 deletion protects against steatohepatitis due to choline-amino acid depletion and high-fat diet. We measured TLR9 in human non-alcoholic steatohepatitis (NASH) livers, and tested whether TLR9 mediates inflammatory recruitment in three murine models of non-alcoholic fatty liver disease (NAFLD). Methods : We assayed TLR mRNA in liver biopsies from bariatric surgery patients. Wild-type ( Wt ), appetite-dysregulated Alms1 mutant (foz/foz), Tlr9 -/- , and Tlr9 -/- foz/foz C57BL6/J mice and bone marrow (BM) chimeras were fed 0.2% cholesterol, high-fat, high sucrose (atherogenic[Ath]) diet or chow, and NAFLD activity score (NAS)/NASH pathology, macrophage/neutrophil infiltration, cytokines/chemokines, and cell death markers measured in livers. Results : Hepatic TLR9 and TLR4 mRNA were increased in human NASH but not simple steatosis, and in Ath-fed foz/foz mice with metabolic syndrome-related NASH. Ath-fed Tlr9 -/- mice showed simple steatosis and less Th1 cytokines than Wt. Tlr9 -/- foz/foz mice were obese and diabetic, but necroinflammatory changes were less severe than Tlr9 +/+ .foz/foz mice. TLR9-expressing myeloid cells were critical for Th1 cytokine production in BM chimeras. BM macrophages from Tlr9 -/- mice showed M2 polarization, were resistant to M1 activation by necrotic hepatocytes/other pro-inflammatory triggers, and provoked less neutrophil chemotaxis than Wt Livers from Ath-fed Tlr9 -/- mice appeared to exhibit more markers of necroptosis [receptor interacting protein kinase (RIP)-1, RIP-3, and mixed lineage kinase domain-like protein (MLKL)] than Wt , and ∼25% showed portal foci of mononuclear cells unrelated to NASH pathology. Our novel clinical data and studies in overnutrition models, including those with diabetes and metabolic syndrome, clarify TLR9 as a pro-inflammatory trigger in NASH. This response is mediated via M1-macrophages and neutrophil chemotaxis. © 2017 The Author(s). Published by Portland Press Limited on

Geometry of Cournot-Nash Equilibrium with Application to Commons and Anticommons

ERIC Educational Resources Information Center

D'Agata, Antonio

2010-01-01

The author develops a simple geometric analysis of Cournot-Nash equilibrium in the price-quantity space by exploiting the economic content of the first-order condition. The approach makes it clear that strategic interdependency in oligopoly originates from externalities among producers. This explains why cartels are unstable and casts oligopoly…

Challenges and Management of Liver Cirrhosis: Practical Issues in the Therapy of Patients with Cirrhosis due to NAFLD and NASH.

PubMed

Traussnigg, Stefan; Kienbacher, Christian; Halilbasic, Emina; Rechling, Christian; Kazemi-Shirazi, Lili; Hofer, Harald; Munda, Petra; Trauner, Michael

2015-01-01

Nonalcoholic fatty liver disease (NAFLD) is the hepatic manifestation of the metabolic syndrome and comprises a liver disease spectrum ranging from steatosis to nonalcoholic steatohepatitis (NASH) with risk of progression to liver cirrhosis and hepatocellular carcinoma (HCC). Associated metabolic conditions and comorbidities such as obesity, diabetes and cardiovascular diseases are common and require concerted management. Adiponutrin (PNPLA3) variants may help to identify NAFLD patients at higher risk for liver disease progression towards advanced fibrosis and HCC. The therapeutic options in NAFLD/NASH include lifestyle modification, pharmacological treatment, bariatric surgery for patients with morbid obesity and treatment of complications of liver cirrhosis and HCC, including liver transplantation. Insulin sensitizers and antioxidative treatment strategies with vitamin E are among the best-established pharmacological approaches, but both drugs have long-term safety issues and there is limited evidence in cirrhotic patients. Treatment of concomitant/underlying metabolic conditions with statins or metformin may also have beneficial effects on portal hypertension, complications of liver cirrhosis and HCC prevention. The bile acid receptor FXR may be a promising novel therapeutic target for the treatment of NAFLD/NASH, fibrosis and portal hypertension, but the prognostic implications of associated changes in low- and high-density lipoprotein cholesterol require further studies. Morbidly obese NASH patients can benefit from bariatric surgery which may reduce liver fibrosis but carries a risk of decompensation in patients with advanced liver cirrhosis. When carefully selected, patients with NASH cirrhosis undergoing liver transplantation have a good outcome. This review summarizes recent progress in the management of patients with liver cirrhosis due to NASH. © 2015 S. Karger AG, Basel.

Cholesterol-lowering drugs cause dissolution of cholesterol crystals and disperse Kupffer cell crown-like structures during resolution of NASH

PubMed Central

Ioannou, George N.; Van Rooyen, Derrick M.; Savard, Christopher; Haigh, W. Geoffrey; Yeh, Matthew M.; Teoh, Narci C.; Farrell, Geoffrey C.

2015-01-01

Cholesterol crystals form within hepatocyte lipid droplets in human and experimental nonalcoholic steatohepatitis (NASH) and are the focus of crown-like structures (CLSs) of activated Kupffer cells (KCs). Obese, diabetic Alms1 mutant (foz/foz) mice were a fed high-fat (23%) diet containing 0.2% cholesterol for 16 weeks and then assigned to four intervention groups for 8 weeks: a) vehicle control, b) ezetimibe (5 mg/kg/day), c) atorvastatin (20 mg/kg/day), or d) ezetimibe and atorvastatin. Livers of vehicle-treated mice developed fibrosing NASH with abundant cholesterol crystallization within lipid droplets calculated to extend over 3.3% (SD, 2.2%) of liver surface area. Hepatocyte lipid droplets with prominent cholesterol crystallization were surrounded by TNFα-positive (activated) KCs forming CLSs (≥3 per high-power field). KCs that formed CLSs stained positive for NLRP3, implicating activation of the NLRP3 inflammasome in response to cholesterol crystals. In contrast, foz/foz mice treated with ezetimibe and atorvastatin showed near-complete resolution of cholesterol crystals [0.01% (SD, 0.02%) of surface area] and CLSs (0 per high-power field), with amelioration of fibrotic NASH. Ezetimibe or atorvastatin alone had intermediate effects on cholesterol crystallization, CLSs, and NASH. These findings are consistent with a causative link between exposure of hepatocytes and KCs to cholesterol crystals and with the development of NASH possibly mediated by NLRP3 activation. PMID:25520429

Clinical Model for NASH and Advanced Fibrosis in Adult Patients With Diabetes and NAFLD: Guidelines for Referral in NAFLD

PubMed Central

Bazick, Jessica; Donithan, Michele; Neuschwander-Tetri, Brent A.; Kleiner, David; Brunt, Elizabeth M.; Wilson, Laura; Doo, Ed; Lavine, Joel; Tonascia, James

2015-01-01

OBJECTIVE Approximately 18 million people in the U.S. have coexisting type 2 diabetes and nonalcoholic fatty liver disease (NAFLD). It is not known who among these patients has nonalcoholic steatohepatitis (NASH) with advanced fibrosis. Therefore, we aimed to determine factors that are associated with both NASH and advanced fibrosis in patients with diabetes and NAFLD in order to identify who should be prioritized for referral to a hepatologist for further diagnostic evaluation and treatment. RESEARCH DESIGN AND METHODS This study was derived from the NASH Clinical Research Network studies and included 1,249 patients with biopsy-proven NAFLD (including a model development cohort of 346 patients and an independent validation cohort of 100 patients with type 2 diabetes as defined by the American Diabetes Association criteria). Outcome measures were presence of NASH or advanced fibrosis (stage 3 or 4) using cross-validated, by jackknife method, multivariable-adjusted area under the receiver operating characteristic curve (AUROC) and 95% CI. RESULTS The mean ± SD age and BMI of patients with diabetes and NAFLD was 52.5 ± 10.3 years and 35.8 ± 6.8 kg/m2, respectively. The prevalence of NASH and advanced fibrosis was 69.2% and 41.0%, respectively. The model for NASH included white race, BMI, waist, alanine aminotransferase (ALT), Aspartate aminotransferase (AST), albumin, HbA1c, HOMA of insulin resistance, and ferritin with an AUROC of 0.80 (95% CI 0.75–0.84, P = 0.007). The specificity, sensitivity, negative predictive values (NPVs), and positive predictive values (PPVs) were 90.0%, 56.8%, 47.7%, and 93.2%, respectively, and the model correctly classified 67% of patients as having NASH. The model for predicting advanced fibrosis included age, Hispanic ethnicity, BMI, waist-to-hip ratio, hypertension, ALT-to-AST ratio, alkaline phosphatase, isolated abnormal alkaline phosphatase, bilirubin (total and direct), globulin, albumin, serum insulin, hematocrit

Characterizing the Nash equilibria of three-player Bayesian quantum games

NASA Astrophysics Data System (ADS)

Solmeyer, Neal; Balu, Radhakrishnan

2017-05-01

Quantum games with incomplete information can be studied within a Bayesian framework. We analyze games quantized within the EWL framework [Eisert, Wilkens, and Lewenstein, Phys Rev. Lett. 83, 3077 (1999)]. We solve for the Nash equilibria of a variety of two-player quantum games and compare the results to the solutions of the corresponding classical games. We then analyze Bayesian games where there is uncertainty about the player types in two-player conflicting interest games. The solutions to the Bayesian games are found to have a phase diagram-like structure where different equilibria exist in different parameter regions, depending both on the amount of uncertainty and the degree of entanglement. We find that in games where a Pareto-optimal solution is not a Nash equilibrium, it is possible for the quantized game to have an advantage over the classical version. In addition, we analyze the behavior of the solutions as the strategy choices approach an unrestricted operation. We find that some games have a continuum of solutions, bounded by the solutions of a simpler restricted game. A deeper understanding of Bayesian quantum game theory could lead to novel quantum applications in a multi-agent setting.

Role of white adipose lipolysis in the development of NASH induced by methionine-and choline-deficient diet

PubMed Central

Tanaka, Naoki; Takahashi, Shogo; Fang, Zhong-Ze; Matsubara, Tsutomu; Krausz, Kristopher W.; Qu, Aijuan; Gonzalez, Frank J.

2014-01-01

Methionine- and choline-deficient diet (MCD) is a model for nonalcoholic steatohepatitis (NASH) in rodents. However, the mechanism of NASH development by dietary methionine/choline deficiency remains undetermined. To elucidate the early metabolic changes associated with MCD-NASH, serum metabolomic analysis was performed using mice treated with MCD and control diet for three days and one week, revealing significant increases in oleic and linoleic acids after MCD treatment. These increases were correlated with reduced body weight and white adipose tissue (WAT) mass, increased phosphorylation of hormone-sensitive lipase, and up-regulation of genes encoding carboxylesterase 3 and β2-adrenergic receptor in WAT, indicating accelerated lipolysis in adipocytes. The changes in serum fatty acids and WAT by MCD treatment were reversed by methionine supplementation, and similar alterations were detected in mice fed a methionine-deficient diet (MD), thus demonstrating that dietary methionine deficiency enhances lipolysis in WAT. MD treatment decreased glucose and increased fibroblast growth factor 21 in serum, thus exhibiting a similar metabolic phenotype as the fasting response. Comparison between MCD and choline-deficient diet (CD) treatments suggested that the addition of MD-induced metabolic alterations, such as WAT lipolysis, to CD-induced hepatic steatosis promotes liver injury. Collectively, these results demonstrate an important role for dietary methionine deficiency and WAT lipolysis in the development of MCD-NASH. PMID:25178843

Efficiency and formalism of quantum games

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, C.F.; Johnson, Neil F.

We show that quantum games are more efficient than classical games and provide a saturated upper bound for this efficiency. We also demonstrate that the set of finite classical games is a strict subset of the set of finite quantum games. Our analysis is based on a rigorous formulation of quantum games, from which quantum versions of the minimax theorem and the Nash equilibrium theorem can be deduced.

Satellite based Global Flood Detection System - strengths and limitations

NASA Astrophysics Data System (ADS)

Revilla-Romero, Beatriz; Salamon, Peter; Thielen, Jutta; De Groeve, Tom; Zajac, Zuzanna

2014-05-01

One of the main problems for global hydrological models is that for many regions only very limited or no observational data for a model assessment is available. This problem could be overcome with filling the gaps using information derived from satellite observations. Thus, an evaluation of the remote sensing signal of the Global Flood Detection System (GFDS) against observed discharge data was performed in order to test the use of this data in sparsely gauged river basins. The study was carried out at 398 locations near the main rivers and in Africa, Asia, Europe, North America and South America. After evaluating different methodologies for extracting the satellite signal, a temporal (4 days) and spatial (4 GFDS pixels) average was chosen to proceed with the analysis. For the 340 stations with a concurrent time series longer than seven years for both, the signal and the in situ observed discharge (obtained mainly from the Global Runoff Data Centre), a calibration based on monthly linear models was carried out. The validation was executed and several skill scores were calculated such as the R2, Nash-Sutcliffe (NSE), and Root Mean Square Error (RMSE). It is important to highlight that, for this study, 230 stations globally had Nash-Sutcliffe efficient score higher than zero, indicating that for specific conditions the satellite signal as used in GFDS can fill the gaps where observations are not available. For example, several locations in African catchments have good performance as in the Niger, Volta and Zambezi for which Nash-Sutcliffe is greater than 0.75. It is known that a number of factors affect total upwelling microwave brightness from a mixed water and land surface measured by a single image pixel. Aiming to better understand how some features of the sites could affect the satellite signal and the correlation with in situ observations, apart from the dependency on the river geometry, a multivariate analysis was carried out between the skill scores (NSE and

The Combination of Blueberry Juice and Probiotics Ameliorate Non-Alcoholic Steatohepatitis (NASH) by Affecting SREBP-1c/PNPLA-3 Pathway via PPAR-α

PubMed Central

Ren, Tingting; Zhu, Juanjuan; Zhu, Lili; Cheng, Mingliang

2017-01-01

Nonalcoholic steatohepatitis (NASH) is liver inflammation and a major threat to public health. Several pharmaceutical agents have been used for NASH therapy but their high-rate side effects limit the use. Blueberry juice and probiotics (BP) have anti-inflammation and antibacterial properties, and may be potential candidates for NASH therapy. To understand the molecular mechanism, Sprague Dawley rats were used to create NASH models and received different treatments. Liver tissues were examined using HE (hematoxylin and eosin) and ORO (Oil Red O) stain, and serum biochemical indices were measured. The levels of peroxisome proliferators-activated receptor (PPAR)-α, sterol regulatory element binding protein-1c (SREBP-1c), Patatin-like phospholipase domain-containing protein 3 (PNPLA-3), inflammatory cytokines and apoptosis biomarkers in liver tissues were measured by qRT-PCR and Western blot. HE and ORO analysis indicated that the hepatocytes were seriously damaged with more and larger lipid droplets in NASH models while BP reduced the number and size of lipid droplets (p < 0.05). Meanwhile, BP increased the levels of SOD (superoxide dismutase), GSH (reduced glutathione) and HDL-C (high-density lipoprotein cholesterol), and reduced the levels of AST (aspartate aminotransferase), ALT (alanine aminotransferase), TG (triglycerides), LDL-C (low-density lipoprotein cholesterol) and MDA (malondialdehyde) in NASH models (p < 0.05). BP increased the level of PPAR-α (Peroxisome proliferator-activated receptor α), and reduced the levels of SREBP-1c (sterol regulatory element binding protein-1c) and PNPLA-3 (Patatin-like phospholipase domain-containing protein 3) (p < 0.05). BP reduced hepatic inflammation and apoptosis by affecting IL-6 (interleukin 6), TNF-α (Tumor necrosis factor α), caspase-3 and Bcl-2 in NASH models. Furthermore, PPAR-α inhibitor increased the level of SREBP-1c and PNPLA-3. Therefore, BP prevents NASH progression by affecting SREBP-1c/PNPLA-3 pathway

A longitudinal study of whole body, tissue, and cellular physiology in a mouse model of fibrosing NASH with high fidelity to the human condition.

PubMed

Krishnan, Anuradha; Abdullah, Tasduq Sheikh; Mounajjed, Taofic; Hartono, Stella; McConico, Andrea; White, Thomas; LeBrasseur, Nathan; Lanza, Ian; Nair, Sreekumaran; Gores, Gregory; Charlton, Michael

2017-06-01

The sequence of events that lead to inflammation and fibrosing nonalcoholic steatohepatitis (NASH) is incompletely understood. Hence, we investigated the chronology of whole body, tissue, and cellular events that occur during the evolution of diet-induced NASH. Male C57Bl/6 mice were assigned to a fast-food (FF; high calorie, high cholesterol, high fructose) or standard-chow (SC) diet over a period of 36 wk. Liver histology, body composition, mitochondrial respiration, metabolic rate, gene expression, and hepatic lipid content were analyzed. Insulin resistance [homeostasis model assessment-insulin resistance (HOMA-IR)] increased 10-fold after 4 wk. Fibrosing NASH was fully established by 16 wk. Total hepatic lipids increased by 4 wk and remained two- to threefold increased throughout. Hepatic triglycerides declined from sixfold increase at 8 wk to threefold increase by 36 wk. In contrast, hepatic cholesterol levels steadily increased from baseline at 8 wk to twofold by 36 wk. The hepatic immune cell population altered over time with macrophages persisting beyond 16 wk. Mitochondrial oxygen flux rates of FF mice diet were uniformly lower with all the tested substrates (13-276 pmol·s -1 ·ml -1 per unit citrate synthase) than SC mice (17-394 pmol·s -1 ·ml -1 per unit citrate synthase) and was accompanied by decreased mitochondrial:nuclear gene copy number ratios after 4 wk. Metabolic rate was lower in FF mice. Mitochondrial glutathione was significantly decreased at 24 wk in FF mice. Expression of dismutases and catalase was also decreased in FF mice. The evolution of NASH in the FF diet-induced model is multiphasic, particularly in terms of hepatic lipid composition. Insulin resistance precedes hepatic inflammation and fibrosis. Mitochondrial dysfunction and depletion occur after the histological features of NASH are apparent. Collectively, these observations provide a unique overview of the sequence of changes that coevolve with the histological evolution of

Clinical Model for NASH and Advanced Fibrosis in Adult Patients With Diabetes and NAFLD: Guidelines for Referral in NAFLD.

PubMed

Bazick, Jessica; Donithan, Michele; Neuschwander-Tetri, Brent A; Kleiner, David; Brunt, Elizabeth M; Wilson, Laura; Doo, Ed; Lavine, Joel; Tonascia, James; Loomba, Rohit

2015-07-01

Approximately 18 million people in the U.S. have coexisting type 2 diabetes and nonalcoholic fatty liver disease (NAFLD). It is not known who among these patients has nonalcoholic steatohepatitis (NASH) with advanced fibrosis. Therefore, we aimed to determine factors that are associated with both NASH and advanced fibrosis in patients with diabetes and NAFLD in order to identify who should be prioritized for referral to a hepatologist for further diagnostic evaluation and treatment. This study was derived from the NASH Clinical Research Network studies and included 1,249 patients with biopsy-proven NAFLD (including a model development cohort of 346 patients and an independent validation cohort of 100 patients with type 2 diabetes as defined by the American Diabetes Association criteria). Outcome measures were presence of NASH or advanced fibrosis (stage 3 or 4) using cross-validated, by jackknife method, multivariable-adjusted area under the receiver operating characteristic curve (AUROC) and 95% CI. The mean ± SD age and BMI of patients with diabetes and NAFLD was 52.5 ± 10.3 years and 35.8 ± 6.8 kg/m(2), respectively. The prevalence of NASH and advanced fibrosis was 69.2% and 41.0%, respectively. The model for NASH included white race, BMI, waist, alanine aminotransferase (ALT), Aspartate aminotransferase (AST), albumin, HbA1c, HOMA of insulin resistance, and ferritin with an AUROC of 0.80 (95% CI 0.75-0.84, P = 0.007). The specificity, sensitivity, negative predictive values (NPVs), and positive predictive values (PPVs) were 90.0%, 56.8%, 47.7%, and 93.2%, respectively, and the model correctly classified 67% of patients as having NASH. The model for predicting advanced fibrosis included age, Hispanic ethnicity, BMI, waist-to-hip ratio, hypertension, ALT-to-AST ratio, alkaline phosphatase, isolated abnormal alkaline phosphatase, bilirubin (total and direct), globulin, albumin, serum insulin, hematocrit, international normalized ratio, and platelet count with

The Scale Effects of Engineered Inlets in Urban Hydrologic Processes

NASA Astrophysics Data System (ADS)

Shevade, L.; Montalto, F. A.

2017-12-01

Runoff from urban surfaces is typically captured by engineered inlets for conveyance to receiving water bodies or treatment plants. Normative hydrologic and hydraulic (H&H) modeling tools generally assume 100% efficient inlets, though observations by the authors suggest this assumption is invalid. The discrepancy is key since the more efficiently the inlet, the more linearly hydrologic processes scale with catchment area. Using several years of remote sensing, the observed efficiencies of urban green infrastructure (GI) facility inlets in New York City are presented, as a function of the morphological and climatological properties of their catchments and events. The rainfall-runoff response is modeled with EPA to assess the degree of inaccuracy that the assumption of efficient inlets introduces in block and neighborhood-scale simulations. Next, an algorithm is presented that incorporates inlet efficiency into SWMM and the improved predictive skill evaluated using Nash-Sutcliffe and root-mean-square error (RMSE). The results are used to evaluate the extent to which decentralized green stormwater management facilities positioned at the low points of urban catchments ought to be designed with larger capacities than their counterparts located further upslope.

A long-acting FGF21 alleviates hepatic steatosis and inflammation in NASH mice partly through an FGF21- adiponectin- IL17A axis.

PubMed

Bao, Lichen; Yin, Jun; Gao, Wen; Wang, Qun; Yao, Wenbing; Gao, Xiangdong

2018-06-02

NASH is the most severe form of NAFLD and is a serious public health problem around the world. There are currently no approved treatments for NASH. FGF21 has recently emerged as a promising drug candidate for metabolic diseases. However, the challenges in developing FGF21 as a novel medicine include its short plasma half-life and poor drug-like properties. Here, we explored the therapeutic effects of PsTag600-FGF21, an engineered long-acting FGF21 fusion protein, in NASH mice and revealed some of the mechanisms responsible for this activity. A long-acting FGF21 was prepared by genetic fusion with a 600 residues polypeptide (PsTag600). We conducted our studies using a choline-deficient high-fat diet (CD-HFD) induced NASH mouse model. In NASH mice, the effects on body weight, insulin sensitivity, inflammation and levels of hormones and metabolites were studied first. We further investigated whether PsTag600-FGF21 attenuated inflammation through the Th17-IL17A axis and the associated mechanisms. PsTag600-FGF21 dose-dependently reduced body weight, blood glucose, insulin and lipid levels and reversed hepatic steatosis. PsTag600-FGF21 enhanced fatty acid activation and mitochondrial β-oxidation in the liver. The profound reduction in hepatic inflammation in NASH mice was associated with PsTag600-FGF21 inhibition of IL17A expression in Th17 cells. Furthermore, PsTag600-FGF21 depended on adiponectin to exert its suppression effects on Th17 cell differentiation and IL17A expression. Our data begin to uncover the indirect mechanism by which PsTag600-FGF21 suppresses hepatic inflammation and further suggest that PsTag600-FGF21 could be an effective approach in NASH treatment. This article is protected by copyright. All rights reserved.

Nash Equilibria in Theory of Reasoned Action

NASA Astrophysics Data System (ADS)

Almeida, Leando; Cruz, José; Ferreira, Helena; Pinto, Alberto Adrego

2009-08-01

Game theory and Decision Theory have been applied to many different areas such as Physics, Economics, Biology, etc. In its application to Psychology, we introduce, in the literature, a Game Theoretical Model of Planned Behavior or Reasoned Action by establishing an analogy between two specific theories. In this study we take in account that individual decision-making is an outcome of a process where group decisions can determine individual probabilistic behavior. Using Game Theory concepts, we describe how intentions can be transformed in behavior and according to the Nash Equilibrium, this process will correspond to the best individual decision/response taking in account the collective response. This analysis can be extended to several examples based in the Game Theoretical Model of Planned Behavior or Reasoned Action.

Nash Equilibrium of Social-Learning Agents in a Restless Multiarmed Bandit Game.

PubMed

Nakayama, Kazuaki; Hisakado, Masato; Mori, Shintaro

2017-05-16

We study a simple model for social-learning agents in a restless multiarmed bandit (rMAB). The bandit has one good arm that changes to a bad one with a certain probability. Each agent stochastically selects one of the two methods, random search (individual learning) or copying information from other agents (social learning), using which he/she seeks the good arm. Fitness of an agent is the probability to know the good arm in the steady state of the agent system. In this model, we explicitly construct the unique Nash equilibrium state and show that the corresponding strategy for each agent is an evolutionarily stable strategy (ESS) in the sense of Thomas. It is shown that the fitness of an agent with ESS is superior to that of an asocial learner when the success probability of social learning is greater than a threshold determined from the probability of success of individual learning, the probability of change of state of the rMAB, and the number of agents. The ESS Nash equilibrium is a solution to Rogers' paradox.

Screening for therapeutic trials and treatment indication in clinical practice: MACK-3, a new blood test for the diagnosis of fibrotic NASH.

PubMed

Boursier, J; Anty, R; Vonghia, L; Moal, V; Vanwolleghem, T; Canivet, C M; Michalak, S; Bonnafous, S; Michielsen, P; Oberti, F; Iannelli, A; Van Gaal, L; Patouraux, S; Blanchet, O; Verrijken, A; Gual, P; Rousselet, M-C; Driessen, A; Hunault, G; Bertrais, S; Tran, A; Calès, P; Francque, S

2018-05-01

The composite histological endpoint comprising nonalcoholic steatohepatitis (NASH) and NAFLD activity score ≥4 and advanced fibrosis (F ≥ 2) ("fibrotic NASH") is becoming an important diagnostic target in NAFLD: it is currently used to select patients for inclusion in phase III therapeutic trials and will ultimately be used to indicate treatment in clinical practice once the new drugs are approved. To develop a new blood test specifically dedicated for this new diagnostic target of interest. Eight Hundred and forty-six biopsy-proven NAFLD patients from three centres (Angers, Nice, Antwerp) were randomised into derivation and validation sets. The blood fibrosis tests BARD, NFS and FIB4 had poor accuracy for fibrotic NASH with respective AUROC: 0.566 ± 0.023, 0.654 ± 0.023, 0.732 ± 0.021. In the derivation set, fibrotic NASH was independently predicted by AST, HOMA and CK18; all three were combined in the new blood test MACK-3 (hoMa, Ast, CK18) for which 90% sensitivity and 95% specificity cut-offs were calculated. In the validation set, MACK-3 had a significantly higher AUROC (0.847 ± 0.030, P ≤ 0.002) than blood fibrosis tests. Using liver biopsy in the grey zone between the two cut-offs (36.0% of the patients), MACK-3 provided excellent accuracy for the diagnosis of fibrotic NASH with 93.3% well-classified patients, sensitivity: 90.0%, specificity: 94.2%, positive predictive value: 81.8% and negative predictive value: 97.0%. The new blood test MACK-3 accurately diagnoses fibrotic NASH. This new test will facilitate patient screening and inclusion in NAFLD therapeutic trials and will enable the identification of patients who will benefit from the treatments once approved. © 2018 John Wiley & Sons Ltd.

Design and rationale for a real-world observational cohort of patients with nonalcoholic fatty liver disease: The TARGET-NASH study.

PubMed

Barritt, A S; Gitlin, Norman; Klein, Samuel; Lok, Anna S; Loomba, Rohit; Malahias, Laura; Powell, Margaret; Vos, Miriam B; Weiss, L Michael; Cusi, Kenneth; Neuschwander-Tetri, Brent A; Sanyal, Arun

2017-10-01

Nonalcoholic fatty liver disease (NAFLD) is highly prevalent and can lead to cirrhosis, hepatocellular carcinoma, and end-stage liver disease. NAFLD comprises the spectrum from simple steatosis (nonalcoholic fatty liver, NAFL), to steatosis with inflammation (nonalcoholic steatohepatitis, NASH). Current primary therapy recommended for NAFLD is weight loss induced by lifestyle modification. The difficulty in achieving this has led to robust pharmacological therapy development. While new drugs may show efficacy in selected phase II/III clinical trial populations, their real-world effectiveness is unknown. TARGET-NASH is a 5-year, longitudinal, observational study of patients with NAFLD designed to evaluate the effectiveness of clinical practice interventions and provide practical information unobtainable in registration trials. A biological specimen repository is included in TARGET-NASH for translational studies of genomics and biomarkers of disease activity. Patients are enrolling at adult and pediatric sites representing multiple specialties. All patients being managed for NAFLD are eligible, whereas those in other NASH registries or clinical trials will be excluded. Enrolled patients range in age from 6 and up and will have 3years of clinical data reviewed. Patient comorbidities, concomitant medications, disease progression and off-label interventions will be assessed, and adverse outcomes, monitored. Confirming the use, safety and effectiveness of NAFLD interventions in children and adults and establishing pragmatic methods of assessing disease progression under real-world conditions are key study outcomes. Ultimately, TARGET-NASH will establish a large, diverse registry of NAFLD patients at academic and community practices to be leveraged to improve health and reduce development of cirrhosis and hepatocellular carcinoma. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparison of infiltration models in NIT Kurukshetra campus

NASA Astrophysics Data System (ADS)

Singh, Balraj; Sihag, Parveen; Singh, Karan

2018-05-01

The aim of the present investigation is to evaluate the performance of infiltration models used to calculate the infiltration rate of the soils. Ten different locations were chosen to measure the infiltration rate in NIT Kurukshetra. The instrument used for the experimentation was double ring infiltrometer. Some of the popular infiltration models like Horton's, Philip's, Modified Philip's and Green-Ampt were fitted with infiltration test data and performance of the models was determined using Nash-Sutcliffe efficiency (NSE), coefficient of correlation (C.C) and Root mean square error (RMSE) criteria. The result suggests that Modified Philip's model is the most accurate model where values of C.C, NSE and RMSE vary from 0.9947-0.9999, 0.9877-0.9998 to 0.1402-0.6913 (mm/h), respectively. Thus, this model can be used to synthetically produce infiltration data in the absence of infiltration data under the same conditions.

HCV genotype 3 and squamous cell carcinoma antigen (SCCA)-IgM are independently associated with histological features of NASH in HCV-infected patients.

PubMed

Martini, A; Fattovich, G; Guido, M; Bugianesi, E; Biasiolo, A; Ieluzzi, D; Gallotta, A; Fassina, G; Merkel, C; Gatta, A; Negro, F; Pontisso, P

2015-10-01

Nonalcoholic steatohepatitis (NASH) enhances the risk of progressive liver disease. In chronic hepatitis C (CHC), liver steatosis is frequent, especially in genotype 3, but its clinical significance is debated. As squamous cell carcinoma antigen (SCCA)-IgM has been associated with advanced liver disease and risk of tumour development, we evaluated its occurrence in CHC and the possible relation with NASH at liver biopsy. Using a validated ELISA, serum SCCA-IgM was measured in 91 patients with CHC at the time of liver biopsy performed before antiviral treatment, at the end of treatment and 6 months thereafter, and in 93 HCV-negative patients with histological diagnosis of nonalcoholic fatty liver disease, as controls. SCCA-IgM was detected in 33% of CHC patients and in 4% of controls. This biomarker was found more elevated in CHC patients with histological NASH, and at multivariate analysis, SCCA-IgM and HCV genotype 3 were independently associated with NASH [OR (95% CI): 6.94 (1.21-40) and 27.02 (4.44-166.6)]. As predictors of NASH, HCV genotype 3 and SCCA-IgM had a specificity and a sensitivity of 97% and 44%, and of 95% and 27%, respectively. PPV and NPV were 80% and 86% for HCV genotype 3 vs 73% and 72% for SCCA-IgM. In patients with sustained virologic response to therapy, SCCA-IgM levels decreased significantly, while these remained unchanged in nonresponders. In conclusion, SCCA-IgM is detectable in one-third of patients with CHC and significantly correlates with histological NASH. © 2015 John Wiley & Sons Ltd.

Obeticholic acid raises LDL-cholesterol and reduces HDL-cholesterol in the Diet-Induced NASH (DIN) hamster model.

PubMed

Briand, François; Brousseau, Emmanuel; Quinsat, Marjolaine; Burcelin, Rémy; Sulpice, Thierry

2018-01-05

The use of rat and mouse models limits the translation to humans for developing novel drugs targeting nonalcoholic steatohepatitis (NASH). Obeticholic acid (OCA) illustrates this limitation since its dyslipidemic effect in humans cannot be observed in these rodents. Conversely, Golden Syrian hamsters have a lipoprotein metabolism mimicking human dyslipidemia since it does express the cholesteryl ester transfer protein (CETP). We therefore developed a Diet-Induced NASH (DIN) hamster model and evaluated the impact of OCA. Compared with chow fed controls, hamsters fed for 20 weeks with a free-choice (FC) diet, developed obesity, insulin resistance, dyslipidemia and NASH (microvesicular steatosis, inflammation, hepatocyte ballooning and perisinusoidal to bridging fibrosis). After 20 weeks of diet, FC fed hamsters were treated without or with obeticholic acid (15mg/kg/day) for 5 weeks. Although a non-significant trend towards higher dietary caloric intake was observed, OCA significantly lowered body weight after 5 weeks of treatment. OCA significantly increased CETP activity and LDL-C levels by 20% and 27%, and reduced HDL-C levels by 20%. OCA blunted hepatic gene expression of Cyp7a1 and Cyp8b1 and reduced fecal bile acids mass excretion by 64% (P < 0.05). Hamsters treated with OCA showed a trend towards higher scavenger receptor Class B type I (SR-BI) and lower LDL-receptor hepatic protein expression. OCA reduced NAS score for inflammation (P < 0.01) and total NAS score, although not significantly. Compared to mouse and rat models, the DIN hamster replicates benefits and side effects of OCA as observed in humans, and should be useful for evaluating novel drugs targeting NASH. Copyright © 2017 Elsevier B.V. All rights reserved.

Wavelet-based multiscale performance analysis: An approach to assess and improve hydrological models

NASA Astrophysics Data System (ADS)

Rathinasamy, Maheswaran; Khosa, Rakesh; Adamowski, Jan; ch, Sudheer; Partheepan, G.; Anand, Jatin; Narsimlu, Boini

2014-12-01

The temporal dynamics of hydrological processes are spread across different time scales and, as such, the performance of hydrological models cannot be estimated reliably from global performance measures that assign a single number to the fit of a simulated time series to an observed reference series. Accordingly, it is important to analyze model performance at different time scales. Wavelets have been used extensively in the area of hydrological modeling for multiscale analysis, and have been shown to be very reliable and useful in understanding dynamics across time scales and as these evolve in time. In this paper, a wavelet-based multiscale performance measure for hydrological models is proposed and tested (i.e., Multiscale Nash-Sutcliffe Criteria and Multiscale Normalized Root Mean Square Error). The main advantage of this method is that it provides a quantitative measure of model performance across different time scales. In the proposed approach, model and observed time series are decomposed using the Discrete Wavelet Transform (known as the à trous wavelet transform), and performance measures of the model are obtained at each time scale. The applicability of the proposed method was explored using various case studies-both real as well as synthetic. The synthetic case studies included various kinds of errors (e.g., timing error, under and over prediction of high and low flows) in outputs from a hydrologic model. The real time case studies investigated in this study included simulation results of both the process-based Soil Water Assessment Tool (SWAT) model, as well as statistical models, namely the Coupled Wavelet-Volterra (WVC), Artificial Neural Network (ANN), and Auto Regressive Moving Average (ARMA) methods. For the SWAT model, data from Wainganga and Sind Basin (India) were used, while for the Wavelet Volterra, ANN and ARMA models, data from the Cauvery River Basin (India) and Fraser River (Canada) were used. The study also explored the effect of the

High-fat, high-fructose, high-cholesterol feeding causes severe NASH and cecal microbiota dysbiosis in juvenile Ossabaw swine.

PubMed

Panasevich, M R; Meers, G M; Linden, M A; Booth, F W; Perfield, J W; Fritsche, K L; Wankhade, Umesh D; Chintapalli, Sree V; Shankar, K; Ibdah, J A; Rector, R S

2018-01-01

Pediatric obesity and nonalcoholic steatohepatitis (NASH) are on the rise in industrialized countries, yet our ability to mechanistically examine this relationship is limited by the lack of a suitable higher animal models. Here, we examined the effects of high-fat, high-fructose corn syrup, high-cholesterol Western-style diet (WD)-induced obesity on NASH and cecal microbiota dysbiosis in juvenile Ossabaw swine. Juvenile female Ossabaw swine (5 wk old) were fed WD (43.0% fat; 17.8% high-fructose corn syrup; 2% cholesterol) or low-fat diet (CON/lean; 10.5% fat) for 16 wk ( n = 6 each) or 36 wk ( n = 4 each). WD-fed pigs developed obesity, dyslipidemia, and systemic insulin resistance compared with CON pigs. In addition, obese WD-fed pigs developed severe NASH, with hepatic steatosis, hepatocyte ballooning, inflammatory cell infiltration, and fibrosis after 16 wk, with further exacerbation of histological inflammation and fibrosis after 36 wk of WD feeding. WD feeding also resulted in robust cecal microbiota changes including increased relative abundances of families and genera in Proteobacteria ( P < 0.05) (i.e., Enterobacteriaceae, Succinivibrionaceae, and Succinivibrio) and LPS-containing Desulfovibrionaceae and Desulfovibrio and a greater ( P < 0.05) predicted microbial metabolic function for LPS biosynthesis, LPS biosynthesis proteins, and peptidoglycan synthesis compared with CON-fed pigs. Overall, juvenile Ossabaw swine fed a high-fat, high-fructose, high-cholesterol diet develop obesity and severe microbiota dysbiosis with a proinflammatory signature and a NASH phenotype directly relevant to the pediatric/adolescent and young adult population.

Foraging swarms as Nash equilibria of dynamic games.

PubMed

Özgüler, Arif Bülent; Yildiz, Aykut

2014-06-01

The question of whether foraging swarms can form as a result of a noncooperative game played by individuals is shown here to have an affirmative answer. A dynamic game played by N agents in 1-D motion is introduced and models, for instance, a foraging ant colony. Each agent controls its velocity to minimize its total work done in a finite time interval. The game is shown to have a unique Nash equilibrium under two different foraging location specifications, and both equilibria display many features of a foraging swarm behavior observed in biological swarms. Explicit expressions are derived for pairwise distances between individuals of the swarm, swarm size, and swarm center location during foraging.

Transforming the Ordinary into Extraordinary: Gary Nash and the Visions of History

ERIC Educational Resources Information Center

Vigilante, David

2009-01-01

Through his long career, Gary Nash has been a pioneer in opening the often-stuffy chambers of academia. He has shown a devotion to K-12 teachers throughout the nation and has ventured into their classrooms to observe, to teach, and, yes, to learn. It is all too rare for a noted historian, famous for his many seminal works, to roll up his sleeves…

A Differential Evolution Algorithm Based on Nikaido-Isoda Function for Solving Nash Equilibrium in Nonlinear Continuous Games

PubMed Central

He, Feng; Zhang, Wei; Zhang, Guoqiang

2016-01-01

A differential evolution algorithm for solving Nash equilibrium in nonlinear continuous games is presented in this paper, called NIDE (Nikaido-Isoda differential evolution). At each generation, parent and child strategy profiles are compared one by one pairwisely, adapting Nikaido-Isoda function as fitness function. In practice, the NE of nonlinear game model with cubic cost function and quadratic demand function is solved, and this method could also be applied to non-concave payoff functions. Moreover, the NIDE is compared with the existing Nash Domination Evolutionary Multiplayer Optimization (NDEMO), the result showed that NIDE was significantly better than NDEMO with less iterations and shorter running time. These numerical examples suggested that the NIDE method is potentially useful. PMID:27589229

High prevalence of normal serum albumin in NASH patients with ascites: a retrospective analysis.

PubMed

Sourianarayanane, Achuthan; O'Shea, Robert S; Barnes, David S; McCullough, Arthur J

2013-06-01

Ascites usually occurs in the setting of end-stage liver disease and low serum albumin and is associated with increased mortality. However, some patients develop ascites despite normal serum albumin (NSA), when a higher portal pressure and/or enhanced renal sodium retention would be expected. This study investigated the relationship between the hepatic venous pressure gradient (HVPG) and serum albumin in ascitic patients with different etiologies of cirrhosis and mortality. Records of all patients with non-malignant ascites who underwent HVPG measurement from 2005 to 2009 were reviewed. One hundred and thirty-eight 138 patients met inclusion criteria; 18.8% had NSA. No difference in sodium excretion or diuretic use was noted in patients with and without NSA. NASH patients were more likely to have a NSA (34.2% vs 12.4%; P=0.001) as well as lower HVPG (15 vs 17.9 mmHg; P=0.009) compared to other etiologies. MELD and HVPG predicted overall survival. However, mortality did not differ by disease etiology, though NASH patients had lower CTP (7.6 vs 8.5; P<0.001) and MELD (15.6 vs 18.1; P=0.09) scores, particularly among patients who died. In patients with ascites and NSA, there were no increase in HVPG or urinary sodium retention. NASH patients with ascites had lower HVPG and a higher prevalence of NSA. They also had a higher mortality relative to MELD and CTP scores in other patients. In these patients, mechanisms other than portal and oncotic pressures and sodium retention play a role in ascites development, and increase mortality rate when complicated by low albumin. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

Role of adipose tissue in methionine-choline-deficient model of non-alcoholic steatohepatitis (NASH).

PubMed

Jha, Pooja; Knopf, Astrid; Koefeler, Harald; Mueller, Michaela; Lackner, Carolin; Hoefler, Gerald; Claudel, Thierry; Trauner, Michael

2014-07-01

Methionine-choline-deficient (MCD) diet is a widely used dietary model of non-alcoholic steatohepatitis (NASH) in rodents. However, the contribution of adipose tissue to MCD-induced steatosis, and inflammation as features of NASH are not fully understood. The goal of this study was to elucidate the role of adipose tissue fatty acid (FA) metabolism, adipogenesis, lipolysis, inflammation and subsequent changes in FA profiles in serum and liver in the pathogenesis of steatohepatitis. We therefore fed ob/ob mice with control or MCD diet for 5 weeks. MCD-feeding increased adipose triglyceride lipase and hormone sensitive lipase activities in all adipose depots which may be attributed to increased systemic FGF21 levels. The highest lipase enzyme activity was exhibited by visceral WAT. Non-esterified fatty acid (NEFA)-18:2n6 was the predominantly elevated FA species in serum and liver of MCD-fed ob/ob mice, while overall serum total fatty acid (TFA) composition was reduced. In contrast, an overall increase of all FA species from TFA pool was found in liver, reflecting the combined effects of increased FA flux to liver, decreased FA oxidation and decrease in lipase activity in liver. NAFLD activity score was increased in liver, while WAT showed no changes and BAT showed even reduced inflammation. This study demonstrates a key role for adipose tissue lipases in the pathogenesis of NASH and provides a comprehensive lipidomic profiling of NEFA and TFA homeostasis in serum and liver. Our findings provide novel mechanistic insights for the role of WAT in progression of MCD-induced liver injury. Copyright © 2014. Published by Elsevier B.V.

Efficient Nash Equilibrium Resource Allocation Based on Game Theory Mechanism in Cloud Computing by Using Auction

PubMed Central

Nezarat, Amin; Dastghaibifard, GH

2015-01-01

One of the most complex issues in the cloud computing environment is the problem of resource allocation so that, on one hand, the cloud provider expects the most profitability and, on the other hand, users also expect to have the best resources at their disposal considering the budget constraints and time. In most previous work conducted, heuristic and evolutionary approaches have been used to solve this problem. Nevertheless, since the nature of this environment is based on economic methods, using such methods can decrease response time and reducing the complexity of the problem. In this paper, an auction-based method is proposed which determines the auction winner by applying game theory mechanism and holding a repetitive game with incomplete information in a non-cooperative environment. In this method, users calculate suitable price bid with their objective function during several round and repetitions and send it to the auctioneer; and the auctioneer chooses the winning player based the suggested utility function. In the proposed method, the end point of the game is the Nash equilibrium point where players are no longer inclined to alter their bid for that resource and the final bid also satisfies the auctioneer’s utility function. To prove the response space convexity, the Lagrange method is used and the proposed model is simulated in the cloudsim and the results are compared with previous work. At the end, it is concluded that this method converges to a response in a shorter time, provides the lowest service level agreement violations and the most utility to the provider. PMID:26431035

Efficient Nash Equilibrium Resource Allocation Based on Game Theory Mechanism in Cloud Computing by Using Auction.

PubMed

Nezarat, Amin; Dastghaibifard, G H

2015-01-01

One of the most complex issues in the cloud computing environment is the problem of resource allocation so that, on one hand, the cloud provider expects the most profitability and, on the other hand, users also expect to have the best resources at their disposal considering the budget constraints and time. In most previous work conducted, heuristic and evolutionary approaches have been used to solve this problem. Nevertheless, since the nature of this environment is based on economic methods, using such methods can decrease response time and reducing the complexity of the problem. In this paper, an auction-based method is proposed which determines the auction winner by applying game theory mechanism and holding a repetitive game with incomplete information in a non-cooperative environment. In this method, users calculate suitable price bid with their objective function during several round and repetitions and send it to the auctioneer; and the auctioneer chooses the winning player based the suggested utility function. In the proposed method, the end point of the game is the Nash equilibrium point where players are no longer inclined to alter their bid for that resource and the final bid also satisfies the auctioneer's utility function. To prove the response space convexity, the Lagrange method is used and the proposed model is simulated in the cloudsim and the results are compared with previous work. At the end, it is concluded that this method converges to a response in a shorter time, provides the lowest service level agreement violations and the most utility to the provider.

Estimating suspended sediment using acoustics in a fine-grained riverine system, Kickapoo Creek at Bloomington, Illinois

USGS Publications Warehouse

Manaster, Amanda D.; Domanski, Marian M.; Straub, Timothy D.; Boldt, Justin A.

2016-08-18

Acoustic technologies have the potential to be used as a surrogate for measuring suspended-sediment concentration (SSC). This potential was examined in a fine-grained (97-100 percent fines) riverine system in central Illinois by way of installation of an acoustic instrument. Acoustic data were collected continuously over the span of 5.5 years. Acoustic parameters were regressed against SSC data to determine the accuracy of using acoustic technology as a surrogate for measuring SSC in a fine-grained riverine system. The resulting regressions for SSC and sediment acoustic parameters had coefficients of determination ranging from 0.75 to 0.97 for various events and configurations. The overall Nash-Sutcliffe model-fit efficiency was 0.95 for the 132 observed and predicted SSC values determined using the sediment acoustic parameter regressions. The study of using acoustic technologies as a surrogate for measuring SSC in fine-grained riverine systems is ongoing. The results at this site are promising in the realm of surrogate technology.

Improving the Performance of Temperature Index Snowmelt Model of SWAT by Using MODIS Land Surface Temperature Data

PubMed Central

Yang, Yan; Onishi, Takeo; Hiramatsu, Ken

2014-01-01

Simulation results of the widely used temperature index snowmelt model are greatly influenced by input air temperature data. Spatially sparse air temperature data remain the main factor inducing uncertainties and errors in that model, which limits its applications. Thus, to solve this problem, we created new air temperature data using linear regression relationships that can be formulated based on MODIS land surface temperature data. The Soil Water Assessment Tool model, which includes an improved temperature index snowmelt module, was chosen to test the newly created data. By evaluating simulation performance for daily snowmelt in three test basins of the Amur River, performance of the newly created data was assessed. The coefficient of determination (R 2) and Nash-Sutcliffe efficiency (NSE) were used for evaluation. The results indicate that MODIS land surface temperature data can be used as a new source for air temperature data creation. This will improve snow simulation using the temperature index model in an area with sparse air temperature observations. PMID:25165746

Nonalcoholic steatohepatitic (NASH) mice are protected from higher hepatotoxicity of acetaminophen upon induction of PPAR{alpha} with clofibrate

DOE Office of Scientific and Technical Information (OSTI.GOV)

Donthamsetty, Shashikiran; Bhave, Vishakha S.; Mitra, Mayurranjan S.

2008-08-01

The objective was to investigate if the hepatotoxic sensitivity in nonalcoholic steatohepatitic mice to acetaminophen (APAP) is due to downregulation of nuclear receptor PPAR{alpha} via lower cell division and tissue repair. Male Swiss Webster mice fed methionine and choline deficient diet for 31 days exhibited NASH. On the 32nd day, a marginally toxic dose of APAP (360 mg/kg, ip) yielded 70% mortality in steatohepatitic mice, while all non steatohepatitic mice receiving the same dose survived. {sup 14}C-APAP covalent binding, CYP2E1 protein, and enzyme activity did not differ from the controls, obviating increased APAP bioactivation as the cause of amplified APAPmore » hepatotoxicity. Liver injury progressed only in steatohepatitic livers between 6 and 24 h. Cell division and tissue repair assessed by {sup 3}H-thymidine incorporation and PCNA were inhibited only in the steatohepatitic mice given APAP suggesting that higher sensitivity of NASH liver to APAP-induced hepatotoxicity was due to lower tissue repair. The hypothesis that impeded liver tissue repair in steatohepatitic mice was due to downregulation of PPAR{alpha} was tested. PPAR{alpha} was downregulated in NASH. To investigate whether downregulation of PPAR{alpha} in NASH is the critical mechanism of compromised liver tissue repair, PPAR{alpha} was induced in steatohepatitic mice with clofibrate (250 mg/kg for 3 days, ip) before injecting APAP. All clofibrate pretreated steatohepatitic mice receiving APAP exhibited lower liver injury, which did not progress and the mice survived. The protection was not due to lower bioactivation of APAP but due to higher liver tissue repair. These findings suggest that inadequate PPAR{alpha} expression in steatohepatitic mice sensitizes them to APAP hepatotoxicity.« less

Branched-chain amino acids alleviate hepatic steatosis and liver injury in choline-deficient high-fat diet induced NASH mice.

PubMed

Honda, Takashi; Ishigami, Masatoshi; Luo, Fangqiong; Lingyun, Ma; Ishizu, Yoji; Kuzuya, Teiji; Hayashi, Kazuhiko; Nakano, Isao; Ishikawa, Tetsuya; Feng, Guo-Gang; Katano, Yoshiaki; Kohama, Tomoya; Kitaura, Yasuyuki; Shimomura, Yoshiharu; Goto, Hidemi; Hirooka, Yoshiki

2017-04-01

For successful treatment for nonalcoholic steatohepatitis (NASH), it may be important to treat the individual causative factors. At present, however, there is no established treatment for this disease. Branched-chain amino acids (BCAAs) have been used to treat patients with decompensated cirrhosis. In order to elucidate the mechanisms responsible for the effects of BCAAs on hepatic steatosis and disease progression, we investigated the effects of BCAA supplementation in mice fed a choline-deficient high-fat diet (CDHF), which induces NASH. Male mice were divided into four groups that received (1) choline-sufficient high fat (HF) diet (HF-control), (2) HF plus 2% BCAA in drinking water (HF-BCAA), (3) CDHF diet (CDHF-control), or (4) CDHF-BCAA for 8weeks. We monitored liver injury, hepatic steatosis and cholesterol, gene expression related to lipid metabolism, and hepatic fat accumulation. Serum alanine aminotransferase (ALT) levels and hepatic triglyceride (TG) were significantly elevated in CDHF-control relative to HF-control. Liver histopathology revealed severe steatosis, inflammation, and pericellular fibrosis in CDHF-control, confirming the NASH findings. Serum ALT levels and hepatic TG and lipid droplet areas were significantly lower in CDHF-BCAA than in CDHF-control. Gene expression and protein level of fatty acid synthase (FAS), which catalyzes the final step in fatty acid biosynthesis, was significantly decreased in CDHF-BCAA than in CDHF-control (P<0.05). Moreover, hepatic total and free cholesterol of CDHF-BCAA was significantly lower than those of CDHF-control. BCAA can alleviate hepatic steatosis and liver injury associated with NASH by suppressing FAS gene expression and protein levels. Copyright © 2017 Elsevier Inc. All rights reserved.

Induction of steatohepatitis (NASH) with insulin resistance in wildtype B6 mice by a western-type diet containing soybean oil and cholesterol.

PubMed

Henkel, Janin; Coleman, Charles Dominic; Schraplau, Anne; Jӧhrens, Korinna; Weber, Daniela; Castro, José Pedro; Hugo, Martin; Schulz, Tim Julius; Krämer, Stephanie; Schürmann, Annette; Püschel, Gerhard Paul

2017-03-21

Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are hepatic manifestations of the metabolic syndrome. Many currently used animal models of NAFLD/NASH lack clinical features of either NASH or metabolic syndrome such as hepatic inflammation and fibrosis (e.g. high-fat diets) or overweight and insulin resistance (e.g. methionine-choline-deficient diets) or they are based on monogenetic defects (e.g. ob/ob mice). In the current study, a western-type diet containing soybean oil with high n 6-PUFA and 0.75% cholesterol (SOD+Cho) induced steatosis, inflammation and fibrosis accompanied by hepatic lipid peroxidation and oxidative stress in livers of C57BL/6-mice which in addition showed increased weight gain and insulin resistance, thus displaying a phenotype closely resembling all clinical features of NASH in patients with metabolic syndrome. In striking contrast a soybean oil-containing western-type diet without cholesterol (SOD) induced only mild steatosis but neither hepatic inflammation nor fibrosis, weight gain or insulin resistance. Another high-fat diet mainly consisting of lard and supplemented with fructose in drinking water (LAD+Fru) resulted in more prominent weight gain, insulin resistance and hepatic steatosis than SOD+Cho but livers were devoid of inflammation and fibrosis. Although both LAD+Fru- and SOD+Cho-fed animals had high plasma cholesterol, liver cholesterol was elevated only in SOD+Cho animals. Cholesterol induced expression of chemotactic and inflammatory cytokines in cultured Kupffer cells and rendered hepatocytes more susceptible to apoptosis. Summarizing, dietary cholesterol in SOD+Cho diet may trigger hepatic inflammation and fibrosis. SOD+Cho-fed animals may be a useful disease model displaying many clinical features of patients with the metabolic syndrome and NASH.

Sensitivity of New England Stream Temperatures to Air Temperature and Precipitation Under Projected Climate

NASA Astrophysics Data System (ADS)

Huang, T.; Samal, N. R.; Wollheim, W. M.; Stewart, R. J.; Zuidema, S.; Prousevitch, A.; Glidden, S.

2015-12-01

The thermal response of streams and rivers to changing climate will influence aquatic habitat. This study examines the impact that changing climate has on stream temperatures in the Merrimack River, NH/MA USA using the Framework for Aquatic Modeling in the Earth System (FrAMES), a spatially distributed river network model driven by air temperature, air humidity, wind speed, precipitation, and solar radiation. Streamflow and water temperatures are simulated at a 45-second (latitude x longitude) river grid resolution for 135 years under historical and projected climate variability. Contemporary streamflow (Nash-Sutcliffe Coefficient = 0.77) and river temperatures (Nash-Sutcliffe Coefficient = 0.89) matched at downstream USGS gauge data well. A suite of model runs were made in combination with uniformly increased daily summer air temperatures by 2oC, 4 oC and 6 oC as well as adjusted precipitation by -40%, -30%, -20%, -10% and +10% as a sensitivity analysis to explore a broad range of potential future climates. We analyzed the summer stream temperatures and the percent of river length unsuitable for cold to warm water fish habitats. Impacts are greatest in large rivers due to the accumulation of river temperature warming throughout the entire river network. Cold water fish (i.e. brook trout) are most strongly affected while, warm water fish (i.e. largemouth bass) aren't expected to be impacted. The changes in stream temperatures under various potential climate scenarios will provide a better understanding of the specific impact that air temperature and precipitation have on aquatic thermal regimes and habitat.

75 FR 41518 - Match-E-Be-Nash-She-Wish (Gun Lake) Tribe Liquor Control Ordinance

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-16

... ethyl alcohol, hydrated oxide of ethyl, or spirit of wine, commonly produced by the fermentation or... benefit of the Tribe. (j) ``Tribe'' means the Match-E-Be-Nash-She-Wish Band of Pottawatomi Indians of... and wine shall be purchased from distributors licensed by the Michigan Liquor Control Commission. (f...

Genetic Predisposition in NAFLD and NASH: Impact on Severity of Liver Disease and Response to Treatment

PubMed Central

Dongiovanni, Paola; Anstee, Quentin M; Valenti, Luca

2013-01-01

Liver fat deposition related to systemic insulin resistance defines non-alcoholic fatty liver disease (NAFLD) which, when associated with oxidative hepatocellular damage, inflammation, and activation of fibrogenesis, i.e. non-alcoholic steatohepatitis (NASH), can progress towards cirrhosis and hepatocellular carcinoma. Due to the epidemic of obesity, NAFLD is now the most frequent liver disease and the leading cause of altered liver enzymes in Western countries. Epidemiological, familial, and twin studies provide evidence for an element of heritability of NAFLD. Genetic modifiers of disease severity and progression have been identified through genome-wide association studies. These include the Patatin-like phosholipase domain-containing 3 (PNPLA3) gene variant I148M as a major determinant of inter-individual and ethnicity-related differences in hepatic fat content independent of insulin resistance and serum lipid concentration. Association studies confirm that the I148M polymorphism is also a strong modifier of NASH and progressive hepatic injury. Furthermore, a few large multicentre case-control studies have demonstrated a role for genetic variants implicated in insulin signalling, oxidative stress, and fibrogenesis in the progression of NAFLD towards fibrosing NASH, and confirm that hepatocellular fat accumulation and insulin resistance are key operative mechanisms closely involved in the progression of liver damage. It is now important to explore the molecular mechanisms underlying these associations between gene variants and progressive liver disease, and to evaluate their impact on the response to available therapies. It is hoped that this knowledge will offer further insights into pathogenesis, suggest novel therapeutic targets, and could help guide physicians towards individualised therapy that improves clinical outcome. PMID:23394097

Effects of n-3 fish oil on metabolic and histological parameters in NASH: a double-blind, randomized, placebo-controlled trial.

PubMed

Argo, Curtis K; Patrie, James T; Lackner, Carolin; Henry, Thomas D; de Lange, Eduard E; Weltman, Arthur L; Shah, Neeral L; Al-Osaimi, Abdullah M; Pramoonjago, Patcharin; Jayakumar, Saumya; Binder, Lukas P; Simmons-Egolf, Winsor D; Burks, Sandra G; Bao, Yongde; Taylor, Ann Gill; Rodriguez, Jessica; Caldwell, Stephen H

2015-01-01

This study's aim was to assess the histological and metabolic effects of n-3 polyunsaturated fatty acids (PUFAs) vs. placebo while adjusting for the impact of age and weight change in NASH patients. (ClinicalTrials.gov: NCT00681408). Forty-one subjects with non-cirrhotic NASH were enrolled, and 34 completed the study. 17 received n-3 fish oil 3000 mg/day and 17 received placebo daily for 1 year with typical counselling on caloric intake and physical activity for all subjects. N-3- and placebo-treated groups showed no significant difference for the primary end point of NASH activity score (NAS) reduction ⩾ 2 points without fibrosis progression after adjustment for known covariates (n-3, 4/17 (23.5%); placebo, 3/17, (17.6%), p = 0.99). Among subjects with increased or stable weight, n-3 subjects showed a larger decrease in liver fat content by MRI than placebo-treated subjects (p = 0.014 for 2nd quartile, p = 0.003 for 3rd quartile of weight change). N-3 treatment showed significant fat reduction on the paired analysis of image-assisted fat morphometry regardless of weight loss or gain. Exercise capacity remained markedly reduced in all subjects. No independent effects on markers of hepatocyte injury or insulin sensitivity indices were observed. N-3 PUFAs at 3000 mg/day for one year did not lead to an improvement in the primary outcome of histological activity in NASH patients (⩾ 2 point NAS reduction). N-3 led to reduced liver fat by multiple measures. Other metabolic effects were not seen, although no detrimental effects were apparent. Whether longer duration, higher dose, or different composition of n-3 therapy would lead to additional benefits is uncertain. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Modulatory role of Co-enzyme Q10 on methionine and choline deficient diet-induced non-alcoholic steatohepatitis (NASH) in albino rats.

PubMed

Saleh, Dalia O; Ahmed, Rania F; Amin, Mohamed M

2017-03-01

The present study aimed to evaluate the hepato-protective and neuro-protective activity of Co-enzyme Q10 (CoQ10) on non-alcoholic steatohepatitis (NASH) in albino rats induced by methionine and choline-deficient (MCD) diet. Rats were fed an MCD diet for 8 weeks to induce non-alcoholic steatohepatitis. CoQ10 (10 mg/(kg·day) -1 ) was orally administered for 2 consecutive weeks. Twenty-four hours after the last dose of the drug, the behavioral test, namely the activity cage test, was performed and the activity counts were recorded. Serum alanine transaminase, aspartate aminotransferase, alkaline phosphatase, gamma-glutamyl transferase, total/direct bilirubin, and albumin were valued to assess liver function. Moreover, hepatic cytokines interleukin-6 as well as its modulator nuclear factor kappa-light-chain-enhancer of activated B cells were determined. In addition, brain biomarkers, viz ammonia, nitric oxide, and brain-derived neurotrophic factor (BDNF), were measured as they are reliable indices to assess brain damage. Histopathological and immunohistochemical examination of brain proliferating cell nuclear antigen in brain and liver tissues were also evaluated. Results revealed that MCD-induced NASH showed impairment in the liver functions with an increase in the liver inflammatory markers. Moreover, NASH resulted in pronounced brain dysfunction as evidenced by hyper-locomotor activity, a decrease in the BDNF level, as well as an increase in the brain nitric oxide and ammonia contents. Oral treatment of MCD-diet-fed rats with CoQ10 for 14 days showed a marked improvement in all the assigned parameters. Finally, it can be concluded that CoQ10 has a hepatoprotective and neuroprotective role in MCD-diet-induced NASH in rats.

Using the nonlinear aquifer storage-discharge relationship to simulate the base flow of glacier- and snowmelt-dominated basins in northwest China

NASA Astrophysics Data System (ADS)

Gan, R.; Luo, Y.

2013-09-01

Base flow is an important component in hydrological modeling. This process is usually modeled by using the linear aquifer storage-discharge relation approach, although the outflow from groundwater aquifers is nonlinear. To identify the accuracy of base flow estimates in rivers dominated by snowmelt and/or glacier melt in arid and cold northwestern China, a nonlinear storage-discharge relationship for use in SWAT (Soil Water Assessment Tool) modeling was developed and applied to the Manas River basin in the Tian Shan Mountains. Linear reservoir models and a digital filter program were used for comparisons. Meanwhile, numerical analysis of recession curves from 78 river gauge stations revealed variation in the parameters of the nonlinear relationship. It was found that the nonlinear reservoir model can improve the streamflow simulation, especially for low-flow period. The higher Nash-Sutcliffe efficiency, logarithmic efficiency, and volumetric efficiency, and lower percent bias were obtained when compared to the one-linear reservoir approach. The parameter b of the aquifer storage-discharge function varied mostly between 0.0 and 0.1, which is much smaller than the suggested value of 0.5. The coefficient a of the function is related to catchment properties, primarily the basin and glacier areas.

Iterative algorithms for computing the feedback Nash equilibrium point for positive systems

NASA Astrophysics Data System (ADS)

Ivanov, I.; Imsland, Lars; Bogdanova, B.

2017-03-01

The paper studies N-player linear quadratic differential games on an infinite time horizon with deterministic feedback information structure. It introduces two iterative methods (the Newton method as well as its accelerated modification) in order to compute the stabilising solution of a set of generalised algebraic Riccati equations. The latter is related to the Nash equilibrium point of the considered game model. Moreover, we derive the sufficient conditions for convergence of the proposed methods. Finally, we discuss two numerical examples so as to illustrate the performance of both of the algorithms.

Development and evaluation of a reservoir model for the Chain of Lakes in Illinois

USGS Publications Warehouse

Domanski, Marian M.

2017-01-27

Forecasts of flows entering and leaving the Chain of Lakes reservoir on the Fox River in northeastern Illinois are critical information to water-resource managers who determine the optimal operation of the dam at McHenry, Illinois, to help minimize damages to property and loss of life because of flooding on the Fox River. In 2014, the U.S. Geological Survey; the Illinois Department of Natural Resources, Office of Water Resources; and National Weather Service, North Central River Forecast Center began a cooperative study to develop a system to enable engineers and planners to simulate and communicate flows and to prepare proactively for precipitation events in near real time in the upper Fox River watershed. The purpose of this report is to document the development and evaluation of the Chain of Lakes reservoir model developed in this study.The reservoir model for the Chain of Lakes was developed using the Hydrologic Engineering Center–Reservoir System Simulation program. Because of the complex relation between the dam headwater and reservoir pool elevations, the reservoir model uses a linear regression model that relates dam headwater elevation to reservoir pool elevation. The linear regression model was developed using 17 U.S. Geological Survey streamflow measurements, along with the gage height in the reservoir pool and the gage height at the dam headwater. The Nash-Sutcliffe model efficiency coefficients for all three linear regression model variables ranged from 0.90 to 0.98.The reservoir model performance was evaluated by graphically comparing simulated and observed reservoir pool elevation time series during nine periods of high pool elevation. In addition, the peak elevations during these time periods were graphically compared to the closest-in-time observed pool elevation peak. The mean difference in the simulated and observed peak elevations was -0.03 feet, with a standard deviation of 0.19 feet. The Nash-Sutcliffe coefficient for peak prediction was

Strain dependence of diet-induced NASH and liver fibrosis in obese mice is linked to diabetes and inflammatory phenotype.

PubMed

Farrell, Geoffrey C; Mridha, Auvro R; Yeh, Matthew M; Arsov, Todor; Van Rooyen, Derrick M; Brooling, John; Nguyen, Tori; Heydet, Deborah; Delghingaro-Augusto, Viviane; Nolan, Christopher J; Shackel, Nicholas A; McLennan, Susan V; Teoh, Narci C; Larter, Claire Z

2014-08-01

Obese Alms1 mutant (foz/foz) NOD.B10 mice develop diabetes and fibrotic NASH when fed high-fat(HF) diet. To establish whether diabetes or obesity is more closely associated with NASH fibrosis, we compared diabetic foz/foz C57BL6/J with non-diabetic foz/foz BALB/c mice. We also determined hepatic cytokines, growth factors and related profibrotic pathways. Male and female foz/foz BALB/c and C57BL6/J mice were fed HF or chow for 24 weeks before determining metabolic indices, liver injury, cytokines, growth factors, pathology/fibrosis and matrix deposition pathways. All foz/foz mice were obese. Hepatomegaly, hyperinsulinemia, hyperglycaemia and hypoadiponectinaemia occurred only in foz/foz C57BL6/J mice, whereas foz/foz BALB/c formed more adipose. Serum ALT, steatosis, ballooning, liver inflammation and NAFLD activity score were worse in C57BL6/J mice. In HF-fed mice, fibrosis was severe in foz/foz C57BL6/J, appreciable in WT C57BL6/J, but absent in foz/foz BALB/c mice. Hepatic mRNA expression of TNF-α, IL-12, IL-4, IL-10 was increased (but not IFN-γ, IL-1β, IL-17A), and IL-4:IFN-γ ratio (indicating Th-2 predominance) was higher in HF-fed foz/foz C57BL6/J than BALB/c mice. In livers of HF-fed foz/foz C57BL6/J mice, TGF-β was unaltered but PDGFα and CTGF were increased in association with enhanced α-SMA, CD147and MMP activity. In mice with equivalent genetic/dietary obesity, NASH development is linked to strain differences in hyperinsulinaemia and hyperglycaemia inversely related to lipid partitioning between adipose and liver. Diabetes-mediated CTGF-regulation of MMPs as well as cytokines/growth factors (Th-2 cytokine predominant, PDGFα, not TGF-β) mobilized in the resultant hepatic necroinflammatory change may contribute to strain differences in NASH fibrosis. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Multifunctional Effects of a Small-Molecule STAT3 Inhibitor on NASH and Hepatocellular Carcinoma in Mice.

PubMed

Jung, Kwang Hwa; Yoo, Wonbeak; Stevenson, Heather L; Deshpande, Dipti; Shen, Hong; Gagea, Mihai; Yoo, Suk-Young; Wang, Jing; Eckols, T Kris; Bharadwaj, Uddalak; Tweardy, David J; Beretta, Laura

2017-09-15

Purpose: The incidence of hepatocellular carcinoma is increasing in the United States, and liver cancer is the second leading cause of cancer-related mortality worldwide. Nonalcoholic steatohepatitis (NASH) is becoming an important risk for hepatocellular carcinoma, and most patients with hepatocellular carcinoma have underlying liver cirrhosis and compromised liver function, which limit treatment options. Thus, novel therapeutic strategies to prevent or treat hepatocellular carcinoma in the context of NASH and cirrhosis are urgently needed. Experimental Design: Constitutive activation of STAT3 is frequently detected in hepatocellular carcinoma tumors. STAT3 signaling plays a pivotal role in hepatocellular carcinoma survival, growth, angiogenesis, and metastasis. We identified C188-9, a novel small-molecule STAT3 inhibitor using computer-aided rational drug design. In this study, we evaluated the therapeutic potential of C188-9 for hepatocellular carcinoma treatment and prevention. Results: C188-9 showed antitumor activity in vitro in three hepatocellular carcinoma cell lines. In mice with hepatocyte-specific deletion of Pten (Hep Pten - mice), C188-9 treatment blocked hepatocellular carcinoma tumor growth, reduced tumor development, and reduced liver steatosis, inflammation, and bile ductular reactions, resulting in improvement of the pathological lesions of NASH. Remarkably, C188-9 also greatly reduced liver injury in these mice as measured by serum aspartate aminotransferase and alanine transaminase levels. Analysis of gene expression showed that C188-9 treatment of Hep Pten - mice resulted in inhibition of signaling pathways downstream of STAT3, STAT1, TREM-1, and Toll-like receptors. In contrast, C188-9 treatment increased liver specification and differentiation gene pathways. Conclusions: Our results suggest that C188-9 should be evaluated further for the treatment and/or prevention of hepatocellular carcinoma. Clin Cancer Res; 23(18); 5537-46. ©2017 AACR

Efficiency in evolutionary games: Darwin, Nash and the secret handshake.

PubMed

Robson, A J

1990-06-07

This paper considers any evolutionary game possessing several evolutionarily stable strategies, or ESSs, with differing payoffs. A mutant is introduced which will "destroy" any ESS which yields a lower payoff than another. This mutant possesses a costless signal and also conditions on the presence of this signal in each opponent. The mutant then can protect itself against a population playing an inefficient ESS by matching this against these non-signalers. At the same time, the mutants can achieve the more efficient ESS against the signaling mutant population itself. This construction is illustrated by means of the simplest possible example, a co-ordination game. The one-shot prisoner's dilemma is used to illustrate how a superior outcome which is not induced by an ESS may be temporarily but not permanently attained. In the case of the repeated prisoner's dilemma, the present argument seems to render the "evolution of co-operation" ultimately inevitable.

Midkine Increases Diagnostic Yield in AFP Negative and NASH-Related Hepatocellular Carcinoma

PubMed Central

Vongsuvanh, Roslyn; van der Poorten, David; Iseli, Tristan; Strasser, Simone I.; McCaughan, Geoffrey W.; George, Jacob

2016-01-01

Robust biomarkers for population-level hepatocellular carcinoma (HCC) surveillance are lacking. We compared serum midkine (MDK), dickkopf-1 (DKK1), osteopontin (OPN) and AFP for HCC diagnosis in 86 HCC patients matched to 86 cirrhotics, 86 with chronic liver disease (CLD) and 86 healthy controls (HC). Based on the performance of each biomarker, we assessed a separate longitudinal cohort of 28 HCC patients, at and before cancer diagnosis. Serum levels of MDK and OPN were higher in HCC patients compared to cirrhosis, CLD and HC groups. DKK1 was not different between cases and controls. More than half of HCC patients had normal AFP. In this AFP-negative HCC cohort, 59.18% (n = 29/49) had elevated MDK, applying the optimal cut-off of 0.44 ng/ml. Using AFP ≥ 20 IU/ml or MDK ≥ 0.44 ng/ml, a significantly greater number (76.7%; n = 66/86) of HCC cases were detected. The area under the receiver operating curve for MDK was superior to AFP and OPN in NASH-HCC diagnosis. In the longitudinal cohort, MDK was elevated in 15/28 (54%) of HCC patients at diagnosis, of whom 67% had elevated MDK 6 months prior. Conclusion: AFP and MDK have a complementary role in HCC detection. MDK increases the diagnostic yield in AFP-negative HCC and has greater diagnostic performance than AFP, OPN and DKK-1 in the diagnosis of NASH-HCC. Additionally, MDK has a promising role in the pre-clinical diagnosis of HCC. PMID:27219517

A Comprehensive Snow Density Model for Integrating Lidar-Derived Snow Depth Data into Spatial Snow Modeling

NASA Astrophysics Data System (ADS)

Marks, D. G.; Kormos, P.; Johnson, M.; Bormann, K. J.; Hedrick, A. R.; Havens, S.; Robertson, M.; Painter, T. H.

2017-12-01

Lidar-derived snow depths when combined with modeled or estimated snow density can provide reliable estimates of the distribution of SWE over large mountain areas. Application of this approach is transforming western snow hydrology. We present a comprehensive approach toward modeling bulk snow density that is reliable over a vast range of weather and snow conditions. The method is applied and evaluated over mountainous regions of California, Idaho, Oregon and Colorado in the western US. Simulated and measured snow density are compared at fourteen validation sites across the western US where measurements of snow mass (SWE) and depth are co-located. Fitting statistics for ten sites from three mountain catchments (two in Idaho, one in California) show an average Nash-Sutcliff model efficiency coefficient of 0.83, and mean bias of 4 kg m-3. Results illustrate issues associated with monitoring snow depth and SWE and show the effectiveness of the model, with a small mean bias across a range of snow and climate conditions in the west.

A comparative study of shallow groundwater level simulation with three time series models in a coastal aquifer of South China

NASA Astrophysics Data System (ADS)

Yang, Q.; Wang, Y.; Zhang, J.; Delgado, J.

2017-05-01

Accurate and reliable groundwater level forecasting models can help ensure the sustainable use of a watershed's aquifers for urban and rural water supply. In this paper, three time series analysis methods, Holt-Winters (HW), integrated time series (ITS), and seasonal autoregressive integrated moving average (SARIMA), are explored to simulate the groundwater level in a coastal aquifer, China. The monthly groundwater table depth data collected in a long time series from 2000 to 2011 are simulated and compared with those three time series models. The error criteria are estimated using coefficient of determination ( R 2), Nash-Sutcliffe model efficiency coefficient ( E), and root-mean-squared error. The results indicate that three models are all accurate in reproducing the historical time series of groundwater levels. The comparisons of three models show that HW model is more accurate in predicting the groundwater levels than SARIMA and ITS models. It is recommended that additional studies explore this proposed method, which can be used in turn to facilitate the development and implementation of more effective and sustainable groundwater management strategies.

Variable complexity online sequential extreme learning machine, with applications to streamflow prediction

NASA Astrophysics Data System (ADS)

Lima, Aranildo R.; Hsieh, William W.; Cannon, Alex J.

2017-12-01

In situations where new data arrive continually, online learning algorithms are computationally much less costly than batch learning ones in maintaining the model up-to-date. The extreme learning machine (ELM), a single hidden layer artificial neural network with random weights in the hidden layer, is solved by linear least squares, and has an online learning version, the online sequential ELM (OSELM). As more data become available during online learning, information on the longer time scale becomes available, so ideally the model complexity should be allowed to change, but the number of hidden nodes (HN) remains fixed in OSELM. A variable complexity VC-OSELM algorithm is proposed to dynamically add or remove HN in the OSELM, allowing the model complexity to vary automatically as online learning proceeds. The performance of VC-OSELM was compared with OSELM in daily streamflow predictions at two hydrological stations in British Columbia, Canada, with VC-OSELM significantly outperforming OSELM in mean absolute error, root mean squared error and Nash-Sutcliffe efficiency at both stations.

Modeling seasonal water balance based on catchments' hedging strategy on evapotranspiration for climate seasonality

NASA Astrophysics Data System (ADS)

Wu, S.; Zhao, J.; Wang, H.

2017-12-01

This paper develops a seasonal water balance model based on the hypothesis that natural catchments utilize hedging strategy on evapotranspiration for climate seasonality. According to the monthly aridity index, one year is split into wet season and dry season. A seasonal water balance model is developed by analogy to a two-stage reservoir operation model, in which seasonal rainfall infiltration, evapotranspiration and saturation-excess runoff is corresponding to the inflow, release and surplus of the catchment system. Then the optimal hedging between wet season and dry season evapotranspiration is analytically derived with marginal benefit principle. Water budget data sets of 320 catchments in the United States covering the period from 1980 to 2010 are used to evaluate the performance of this model. The Nash-Sutcliffe Efficiency coefficient for evapotranspiration is higher than 0.5 in 84% of the study catchments; while the runoff is 87%. This paper validates catchments' hedging strategy on evapotranspiration for climate seasonality and shows its potential application for seasonal water balance, which is valuable for water resources planning and management.

2020s scenario analysis of nutrient load in the Mekong River Basin using a distributed hydrological model.

PubMed

Yoshimura, Chihiro; Zhou, Maichun; Kiem, Anthony S; Fukami, Kazuhiko; Prasantha, Hapuarachchi H A; Ishidaira, Hiroshi; Takeuchi, Kuniyoshi

2009-10-01

A distributed hydrological model, YHyM, was integrated with the export coefficient concept and applied to simulate the nutrient load in the Mekong River Basin. In the validation period (1992-1999), Nash-Sutcliffe efficiency was 76.4% for discharge, 65.9% for total nitrogen, and 45.3% for total phosphorus at Khong Chiam. Using the model, scenario analysis was then performed for the 2020s taking into account major anthropogenic factors: climate change, population, land cover, fertilizer use, and industrial waste water. The results show that the load at Kompong Cham in 2020s is 6.3 x 10(4)tN a(-1) (+13.0% compared to 1990s) and 4.3 x 10(3)tP a(-1) (+24.7%). Overall, the noticeable nutrient sources are cropland in the middle region and urban load in the lower region. The installation of waste water treatment plants in urban areas possibly cut 60.6%N and 19.9%P of the estimated increase in the case without any treatment.

Parameter regionalization of a monthly water balance model for the conterminous United States

NASA Astrophysics Data System (ADS)

Bock, Andrew R.; Hay, Lauren E.; McCabe, Gregory J.; Markstrom, Steven L.; Atkinson, R. Dwight

2016-07-01

A parameter regionalization scheme to transfer parameter values from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash-Sutcliffe efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.

Parameter regionalization of a monthly water balance model for the conterminous United States

NASA Astrophysics Data System (ADS)

Bock, A. R.; Hay, L. E.; McCabe, G. J.; Markstrom, S. L.; Atkinson, R. D.

2015-09-01

A parameter regionalization scheme to transfer parameter values and model uncertainty information from gaged to ungaged areas for a monthly water balance model (MWBM) was developed and tested for the conterminous United States (CONUS). The Fourier Amplitude Sensitivity Test, a global-sensitivity algorithm, was implemented on a MWBM to generate parameter sensitivities on a set of 109 951 hydrologic response units (HRUs) across the CONUS. The HRUs were grouped into 110 calibration regions based on similar parameter sensitivities. Subsequently, measured runoff from 1575 streamgages within the calibration regions were used to calibrate the MWBM parameters to produce parameter sets for each calibration region. Measured and simulated runoff at the 1575 streamgages showed good correspondence for the majority of the CONUS, with a median computed Nash-Sutcliffe Efficiency coefficient of 0.76 over all streamgages. These methods maximize the use of available runoff information, resulting in a calibrated CONUS-wide application of the MWBM suitable for providing estimates of water availability at the HRU resolution for both gaged and ungaged areas of the CONUS.

High-fat, high-fructose, high-cholesterol feeding causes severe NASH and cecal microbiota dysbiosis in juvenile Ossabaw swine

USDA-ARS?s Scientific Manuscript database

Pediatric obesity and nonalcoholic steatohepatitis (NASH) are on the rise in industrialized countries, yet our ability to mechanistically examine this relationship is limited by the lack of a suitable higher animal models. Here, we examined the effects of high-fat, high-fructose corn syrup, high-cho...

Spontaneous Time Symmetry Breaking in System with Mixed Strategy Nash Equilibrium: Evidences in Experimental Economics Data

NASA Astrophysics Data System (ADS)

Wang, Zhijian; Xu, Bin; Zhejiang Collaboration

2011-03-01

In social science, laboratory experiment with human subjects' interaction is a standard test-bed for studying social processes in micro level. Usually, as in physics, the processes near equilibrium are suggested as stochastic processes with time-reversal symmetry (TRS). To the best of our knowledge, near equilibrium, the breaking time symmetry, as well as the existence of robust time anti-symmetry processes, has not been reported clearly in experimental economics till now. By employing Markov transition method to analysis the data from human subject 2x2 Games with wide parameters and mixed Nash equilibrium, we study the time symmetry of the social interaction process near Nash equilibrium. We find that, the time symmetry is broken, and there exists a robust time anti-symmetry processes. We also report the weight of the time anti-symmetry processes in the total processes of each the games. Evidences in laboratory marketing experiments, at the same time, are provided as one-dimension cases. In these cases, time anti-symmetry cycles can also be captured. The proposition of time anti-symmetry processes is small, but the cycles are distinguishable.

Quantitative imaging of fibrotic and morphological changes in liver of non-alcoholic steatohepatitis (NASH) model mice by second harmonic generation (SHG) and auto-fluorescence (AF) imaging using two-photon excitation microscopy (TPEM).

PubMed

Yamamoto, Shin; Oshima, Yusuke; Saitou, Takashi; Watanabe, Takao; Miyake, Teruki; Yoshida, Osamu; Tokumoto, Yoshio; Abe, Masanori; Matsuura, Bunzo; Hiasa, Yoichi; Imamura, Takeshi

2016-12-01

Non-alcoholic steatohepatitis (NASH) is a common liver disorder caused by fatty liver. Because NASH is associated with fibrotic and morphological changes in liver tissue, a direct imaging technique is required for accurate staging of liver tissue. For this purpose, in this study we took advantage of two label-free optical imaging techniques, second harmonic generation (SHG) and auto-fluorescence (AF), using two-photon excitation microscopy (TPEM). Three-dimensional ex vivo imaging of tissues from NASH model mice, followed by image processing, revealed that SHG and AF are sufficient to quantitatively characterize the hepatic capsule at an early stage and parenchymal morphologies associated with liver disease progression, respectively.

A model for water discharge based on energy consumption data (WATEN).

NASA Astrophysics Data System (ADS)

Moyano, María Carmen; Tornos, Lucía; Juana, Luis

2014-05-01

As the need for water conservation is becoming a major water concern, a lumped model entitled WATEN has been proposed to analyse the water balance in the B-XII Irrigation Sector of the Lower Guadalquivir Irrigated Area, one of the largest irrigated areas in Spain. The aim of this work is to approach the hydrological study of an irrigation district lacking of robust data in such a manner that the water balance is performed from less to more process complexity. WATEN parameters are the total and readily available moisture in the soil, a fix percentage for effective precipitation, and the irrigation efficiency. The Sector presents six different drainage pumping stations, with particular pumping groups and with no water flow measurement devices. Energy consumption depends on the working pumping stations and groups, and on the variable water level to discharge. Energy consumed in the drainage pumping stations has been used for calibration The study has relied on two monthly series of data: the volume of drainage obtained from the model and the energy consumed in the pumping stations. A double mass analysis has permitted the detection of data tendencies. The two resulting series of data have been compared to assess model performance, particularly the Pearson's product moment correlation coefficient and the Nash-Sutcliffe coefficient of efficiency, e2, determined for monthly data and for annual and monthly average data. For model calibration, we have followed a classical approach based on objective functions optimization, and a robust approach based on Markov chain Monte Carlo simulation process, driven in a similar manner to genetic algorithms, entitled Parameters Estimation on Driven Trials (PEDT), and aiming to reduce computational requirements. WATEN has been parameterised maintaining its physical and conceptual rationality. The study approach is outlined as a progressive introduction of data. In this manner, we can observe its effect on the studied objective

Factors Controlling Sediment Load in The Central Anatolia Region of Turkey: Ankara River Basin

NASA Astrophysics Data System (ADS)

Duru, Umit; Wohl, Ellen; Ahmadi, Mehdi

2017-05-01

Better understanding of the factors controlling sediment load at a catchment scale can facilitate estimation of soil erosion and sediment transport rates. The research summarized here enhances understanding of correlations between potential control variables on suspended sediment loads. The Soil and Water Assessment Tool was used to simulate flow and sediment at the Ankara River basin. Multivariable regression analysis and principal component analysis were then performed between sediment load and controlling variables. The physical variables were either directly derived from a Digital Elevation Model or from field maps or computed using established equations. Mean observed sediment rate is 6697 ton/year and mean sediment yield is 21 ton/y/km² from the gage. Soil and Water Assessment Tool satisfactorily simulated observed sediment load with Nash-Sutcliffe efficiency, relative error, and coefficient of determination ( R²) values of 0.81, -1.55, and 0.93, respectively in the catchment. Therefore, parameter values from the physically based model were applied to the multivariable regression analysis as well as principal component analysis. The results indicate that stream flow, drainage area, and channel width explain most of the variability in sediment load among the catchments. The implications of the results, efficient siltation management practices in the catchment should be performed to stream flow, drainage area, and channel width.

On the assimilation set-up of ASCAT soil moisture data for improving streamflow catchment simulation

NASA Astrophysics Data System (ADS)

Loizu, Javier; Massari, Christian; Álvarez-Mozos, Jesús; Tarpanelli, Angelica; Brocca, Luca; Casalí, Javier

2018-01-01

Assimilation of remotely sensed surface soil moisture (SSM) data into hydrological catchment models has been identified as a means to improve streamflow simulations, but reported results vary markedly depending on the particular model, catchment and assimilation procedure used. In this study, the influence of key aspects, such as the type of model, re-scaling technique and SSM observation error considered, were evaluated. For this aim, Advanced SCATterometer ASCAT-SSM observations were assimilated through the ensemble Kalman filter into two hydrological models of different complexity (namely MISDc and TOPLATS) run on two Mediterranean catchments of similar size (750 km2). Three different re-scaling techniques were evaluated (linear re-scaling, variance matching and cumulative distribution function matching), and SSM observation error values ranging from 0.01% to 20% were considered. Four different efficiency measures were used for evaluating the results. Increases in Nash-Sutcliffe efficiency (0.03-0.15) and efficiency indices (10-45%) were obtained, especially when linear re-scaling and observation errors within 4-6% were considered. This study found out that there is a potential to improve streamflow prediction through data assimilation of remotely sensed SSM in catchments of different characteristics and with hydrological models of different conceptualizations schemes, but for that, a careful evaluation of the observation error and re-scaling technique set-up utilized is required.

Artificial intelligence models for predicting the performance of biological wastewater treatment plant in the removal of Kjeldahl Nitrogen from wastewater

NASA Astrophysics Data System (ADS)

Manu, D. S.; Thalla, Arun Kumar

2017-11-01

The current work demonstrates the support vector machine (SVM) and adaptive neuro-fuzzy inference system (ANFIS) modeling to assess the removal efficiency of Kjeldahl Nitrogen of a full-scale aerobic biological wastewater treatment plant. The influent variables such as pH, chemical oxygen demand, total solids (TS), free ammonia, ammonia nitrogen and Kjeldahl Nitrogen are used as input variables during modeling. Model development focused on postulating an adaptive, functional, real-time and alternative approach for modeling the removal efficiency of Kjeldahl Nitrogen. The input variables used for modeling were daily time series data recorded at wastewater treatment plant (WWTP) located in Mangalore during the period June 2014-September 2014. The performance of ANFIS model developed using Gbell and trapezoidal membership functions (MFs) and SVM are assessed using different statistical indices like root mean square error, correlation coefficients (CC) and Nash Sutcliff error (NSE). The errors related to the prediction of effluent Kjeldahl Nitrogen concentration by the SVM modeling appeared to be reasonable when compared to that of ANFIS models with Gbell and trapezoidal MF. From the performance evaluation of the developed SVM model, it is observed that the approach is capable to define the inter-relationship between various wastewater quality variables and thus SVM can be potentially applied for evaluating the efficiency of aerobic biological processes in WWTP.

Mixed-strategy Nash equilibrium for a discontinuous symmetric N-player game

NASA Astrophysics Data System (ADS)

Hilhorst, H. J.; Appert-Rolland, C.

2018-03-01

We consider a game in which each player must find a compromise between more daring strategies that carry a high risk for him to be eliminated, and more cautious ones that, however, reduce his final score. For two symmetric players this game was originally formulated in 1961 by Dresher, who modeled a duel between two opponents. The game has also been of interest in the description of athletic competitions. We extend here the two-player game to an arbitrary number N of symmetric players. We show that there is a mixed-strategy Nash equilibrium and find its exact analytic expression, which we analyze in particular in the limit of large N, where mean-field behavior occurs. The original game with N  =  2 arises as a singular limit of the general case.

The Mathematics of Aggregation, Interdependence, Organizations and Systems of Nash Equilibria (NE): A Replacement for Game Theory

DTIC Science & Technology

2011-06-01

there a free-market economist in the House?, American Journal of Economics and Sociology, 66(2): 309-334. Jasny, B. R., Zahn, L.M., & Marshall, E...1   The Mathematics of Aggregation, Interdependence, Organizations and Systems of Nash equilibria (NE): A replacement for Game Theory...level data to group, organization and systems levels, making it one of social science’s biggest challenges, if not the most important (Giles, 2011). For

Adaptive Parameter Optimization of a Grid-based Conceptual Hydrological Model

NASA Astrophysics Data System (ADS)

Samaniego, L.; Kumar, R.; Attinger, S.

2007-12-01

). The main difference with the standard SA is the parameter search routine which uses adaptive heuristic rules to improve its efficiency. These rules are based on the relative behavior of the efficiency criteria. The efficiency of the model is evaluated with the Nash-Sutcliffe efficiency coefficient (NS) and the RMSE obtained for various short and long term runoff characteristics such as daily flows; semiannual high and low flow characteristics such as total drought duration frequency of high flows; and annual specific discharge at various gauging stations. Additionally, the parameter search was constrained with the 95% confidence bands of the runoff characteristics mentioned above. The proposed method was calibrated in the Upper Neckar River basin covering an area of approximately 4000~km2 during the period from 1961 to 1993. The spatial and temporal resolutions used were a grid size of (1000 × 1000)~m and 12~h intervals respectively. The results of the study indicate significant improvement in model performance (e.g. Nash-Sutcliffe of various runoff characteristics ~ 0.8) and a significant reduction in computational burden of at least 25%.

Seasonal precipitation forecasting for the Melbourne region using a Self-Organizing Maps approach

NASA Astrophysics Data System (ADS)

Pidoto, Ross; Wallner, Markus; Haberlandt, Uwe

2017-04-01

The Melbourne region experiences highly variable inter-annual rainfall. For close to a decade during the 2000s, below average rainfall seriously affected the environment, water supplies and agriculture. A seasonal rainfall forecasting model for the Melbourne region based on the novel approach of a Self-Organizing Map has been developed and tested for its prediction performance. Predictor variables at varying lead times were first assessed for inclusion within the model by calculating their importance via Random Forests. Predictor variables tested include the climate indices SOI, DMI and N3.4, in addition to gridded global sea surface temperature data. Five forecasting models were developed: an annual model and four seasonal models, each individually optimized for performance through Pearson's correlation r and the Nash-Sutcliffe Efficiency. The annual model showed a prediction performance of r = 0.54 and NSE = 0.14. The best seasonal model was for spring, with r = 0.61 and NSE = 0.31. Autumn was the worst performing seasonal model. The sea surface temperature data contributed fewer predictor variables compared to climate indices. Most predictor variables were supplied at a minimum lead, however some predictors were found at lead times of up to a year.

A glacier runoff extension to the Precipitation Runoff Modeling System

USGS Publications Warehouse

Van Beusekom, Ashley E.; Viger, Roland

2016-01-01

A module to simulate glacier runoff, PRMSglacier, was added to PRMS (Precipitation Runoff Modeling System), a distributed-parameter, physical-process hydrological simulation code. The extension does not require extensive on-glacier measurements or computational expense but still relies on physical principles over empirical relations as much as is feasible while maintaining model usability. PRMSglacier is validated on two basins in Alaska, Wolverine, and Gulkana Glacier basin, which have been studied since 1966 and have a substantial amount of data with which to test model performance over a long period of time covering a wide range of climatic and hydrologic conditions. When error in field measurements is considered, the Nash-Sutcliffe efficiencies of streamflow are 0.87 and 0.86, the absolute bias fractions of the winter mass balance simulations are 0.10 and 0.08, and the absolute bias fractions of the summer mass balances are 0.01 and 0.03, all computed over 42 years for the Wolverine and Gulkana Glacier basins, respectively. Without taking into account measurement error, the values are still within the range achieved by the more computationally expensive codes tested over shorter time periods.

A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series

NASA Astrophysics Data System (ADS)

Wang, Wen-Chuan; Chau, Kwok-Wing; Cheng, Chun-Tian; Qiu, Lin

2009-08-01

SummaryDeveloping a hydrological forecasting model based on past records is crucial to effective hydropower reservoir management and scheduling. Traditionally, time series analysis and modeling is used for building mathematical models to generate hydrologic records in hydrology and water resources. Artificial intelligence (AI), as a branch of computer science, is capable of analyzing long-series and large-scale hydrological data. In recent years, it is one of front issues to apply AI technology to the hydrological forecasting modeling. In this paper, autoregressive moving-average (ARMA) models, artificial neural networks (ANNs) approaches, adaptive neural-based fuzzy inference system (ANFIS) techniques, genetic programming (GP) models and support vector machine (SVM) method are examined using the long-term observations of monthly river flow discharges. The four quantitative standard statistical performance evaluation measures, the coefficient of correlation ( R), Nash-Sutcliffe efficiency coefficient ( E), root mean squared error (RMSE), mean absolute percentage error (MAPE), are employed to evaluate the performances of various models developed. Two case study river sites are also provided to illustrate their respective performances. The results indicate that the best performance can be obtained by ANFIS, GP and SVM, in terms of different evaluation criteria during the training and validation phases.

Estimating daily time series of streamflow using hydrological model calibrated based on satellite observations of river water surface width: Toward real world applications.

PubMed

Sun, Wenchao; Ishidaira, Hiroshi; Bastola, Satish; Yu, Jingshan

2015-05-01

Lacking observation data for calibration constrains applications of hydrological models to estimate daily time series of streamflow. Recent improvements in remote sensing enable detection of river water-surface width from satellite observations, making possible the tracking of streamflow from space. In this study, a method calibrating hydrological models using river width derived from remote sensing is demonstrated through application to the ungauged Irrawaddy Basin in Myanmar. Generalized likelihood uncertainty estimation (GLUE) is selected as a tool for automatic calibration and uncertainty analysis. Of 50,000 randomly generated parameter sets, 997 are identified as behavioral, based on comparing model simulation with satellite observations. The uncertainty band of streamflow simulation can span most of 10-year average monthly observed streamflow for moderate and high flow conditions. Nash-Sutcliffe efficiency is 95.7% for the simulated streamflow at the 50% quantile. These results indicate that application to the target basin is generally successful. Beyond evaluating the method in a basin lacking streamflow data, difficulties and possible solutions for applications in the real world are addressed to promote future use of the proposed method in more ungauged basins. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

Evaluation of stream water quality data generated from MODIS images in modeling total suspended solid emission to a freshwater lake.

PubMed

Ayana, Essayas K; Worqlul, Abeyou W; Steenhuis, Tammo S

2015-08-01

Modeling of suspended sediment emission into freshwater lakes is challenging due to data gaps in developing countries. Existing models simulate sediment concentration at a gauging station upstream and none of these studies had modeled total suspended solids (TSS) emissions by inflowing rivers to freshwater lakes as there are no TSS measurements at the river mouth in the upper Blue Nile basin. In this study a 10year TSS time series data generated from remotely sensed MODIS/Terra images using established empirical relationship is applied to calibrate and validate a hydrology model for Lake Tana in Upper Blue Nile Basin. The result showed that at a monthly time scale TSS at the river mouth can be replicated with Nash-Sutcliffe efficiency (NS) of 0.34 for calibration and 0.21 for validation periods. Percent bias (PBIAS) and ratio of the root-mean-square error to the standard deviation of measured data (RSR) are all within range. Given the inaccessibility and costliness to measure TSS at river mouths to a lake the results found here are considered useful for suspended sediment budget studies in water bodies of the basin. Copyright © 2015 Elsevier B.V. All rights reserved.

CHIP−/−-Mouse Liver: Adiponectin-AMPK-FOXO-Activation Overrides CYP2E1-Elicited JNK1-Activation, Delaying Onset of NASH: Therapeutic Implications

PubMed Central

Kim, Sung-Mi; Grenert, James P.; Patterson, Cam; Correia, Maria Almira

2016-01-01

Genetic ablation of C-terminus of Hsc70-interacting protein (CHIP) E3 ubiquitin-ligase impairs hepatic cytochrome P450 CYP2E1 degradation. Consequent CYP2E1 gain of function accelerates reactive O2 species (ROS) production, triggering oxidative/proteotoxic stress associated with sustained activation of c-Jun NH2-terminal kinase (JNK)-signaling cascades, pro-inflammatory effectors/cytokines, insulin resistance, progressive hepatocellular ballooning and microvesicular steatosis. Despite this, little evidence of nonalcoholic fatty liver disease (NAFLD)/nonalcoholic steatohepatitis (NASH) was found in CHIP−/−-mice over the first 8–9-months of life. We herein document that this lack of tissue injury is largely due to the concurrent up-regulation and/or activation of the adiponectin-5′-AMP-activated protein kinase (AMPK)-forkhead box O (FOXO)-signaling axis stemming from at the least three synergistic features: Up-regulated expression of adipose tissue adiponectin and its hepatic adipoR1/adipoR2 receptors, stabilization of hepatic AMPKα1-isoform, identified herein for the first time as a CHIP-ubiquitination substrate (unlike its AMPKα2-isoform), as well as nuclear stabilization of FOXOs, well-known CHIP-ubiquitination targets. Such beneficial predominance of the adiponectin-AMPK-FOXO-signaling axis over the sustained JNK-elevation and injurious insulin resistance in CHIP−/−-livers apparently counteracts/delays rapid progression of the hepatic microvesicular steatosis to the characteristic macrovesicular steatosis observed in clinical NASH and/or rodent NASH-models. PMID:27406999

Analysis of one dimension migration law from rainfall runoff on urban roof

NASA Astrophysics Data System (ADS)

Weiwei, Chen

2017-08-01

Research was taken on the hydrology and water quality process in the natural rain condition and water samples were collected and analyzed. The pollutant were included SS, COD and TN. Based on the mass balance principle, one dimension migration model was built for the rainfall runoff pollution in surface. The difference equation was developed according to the finite difference method, by applying the Newton iteration method for solving it. The simulated pollutant concentration process was in consistent with the measured value on model, and Nash-Sutcliffe coefficient was higher than 0.80. The model had better practicability, which provided evidence for effectively utilizing urban rainfall resource, non-point source pollution of making management technologies and measures, sponge city construction, and so on.

Factors Controlling Sediment Load in The Central Anatolia Region of Turkey: Ankara River Basin.

PubMed

Duru, Umit; Wohl, Ellen; Ahmadi, Mehdi

2017-05-01

Better understanding of the factors controlling sediment load at a catchment scale can facilitate estimation of soil erosion and sediment transport rates. The research summarized here enhances understanding of correlations between potential control variables on suspended sediment loads. The Soil and Water Assessment Tool was used to simulate flow and sediment at the Ankara River basin. Multivariable regression analysis and principal component analysis were then performed between sediment load and controlling variables. The physical variables were either directly derived from a Digital Elevation Model or from field maps or computed using established equations. Mean observed sediment rate is 6697 ton/year and mean sediment yield is 21 ton/y/km² from the gage. Soil and Water Assessment Tool satisfactorily simulated observed sediment load with Nash-Sutcliffe efficiency, relative error, and coefficient of determination (R²) values of 0.81, -1.55, and 0.93, respectively in the catchment. Therefore, parameter values from the physically based model were applied to the multivariable regression analysis as well as principal component analysis. The results indicate that stream flow, drainage area, and channel width explain most of the variability in sediment load among the catchments. The implications of the results, efficient siltation management practices in the catchment should be performed to stream flow, drainage area, and channel width.

Coupling the NASA-CASA ecosystem model with a hydrologic routing algorithm for improved water management in Yosemite National Park

NASA Astrophysics Data System (ADS)

Teaby, A.; Johnson, E. R.; Griffin, M.; Carrillo, C.; Kannan, T.; Shupe, J. W.; Schmidt, C.

2013-12-01

Historic trends reveal extreme precipitation variability within the Yosemite National Park (YNP) geographic region. While California obtains greater than half of its annual water supply from the Sierra Nevada, snowpack, precipitation, and runoff can fluctuate between less than 50% and greater than 200% of climatological averages. Advances in hydrological modeling are crucial to improving water-use efficiency at the local, state, and national levels. The NASA Carnegie Ames Stanford Approach (CASA) is a global simulation model that combines multi-year satellite, climate, and other land surface databases to estimate biosphere-atmosphere exchange of energy, water, and trace gases from plants and soils. By coupling CASA with a Hydrological Routing Algorithm known as HYDRA, it is possible to calculate current water availability and observe hydrological trends within YNP. Satellite-derived inputs such as surface evapotranspiration, temperature, precipitation, land cover, and elevation were included to create a valuable decision support tool for YNP's water resource managers. These results will be of enhanced importance given current efforts to restore 81 miles of the Merced River within the park's boundary. Validations of model results were conducted using in situ stream gage measurements. The model accurately simulated observed streamflow values, achieving a relatively strong Nash-Sutcliffe model efficiency coefficient. This geospatial assessment provides a standardized method which may be repeated in both national and international water-stressed regions.

Hydrological Modeling of the Jiaoyi Watershed (China) Using HSPF Model

PubMed Central

Yan, Chang-An; Zhang, Wanchang; Zhang, Zhijie

2014-01-01

A watershed hydrological model, hydrological simulation program-Fortran (HSPF), was applied to simulate the spatial and temporal variation of hydrological processes in the Jiaoyi watershed of Huaihe River Basin, the heaviest shortage of water resources and polluted area in China. The model was calibrated using the years 2001–2004 and validated with data from 2005 to 2006. Calibration and validation results showed that the model generally simulated mean monthly and daily runoff precisely due to the close matching hydrographs between simulated and observed runoff, as well as the excellent evaluation indicators such as Nash-Sutcliffe efficiency (NSE), coefficient of correlation (R 2), and the relative error (RE). The similar simulation results between calibration and validation period showed that all the calibrated parameters had a certain representation in Jiaoyi watershed. Additionally, the simulation in rainy months was more accurate than the drought months. Another result in this paper was that HSPF was also capable of estimating the water balance components reasonably and realistically in space through the whole watershed. The calibrated model can be used to explore the effects of climate change scenarios and various watershed management practices on the water resources and water environment in the basin. PMID:25013863

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.

Hourly predictive Levenberg-Marquardt ANN and multi linear regression models for predicting of dew point temperature

NASA Astrophysics Data System (ADS)

Zounemat-Kermani, Mohammad

2012-08-01

In this study, the ability of two models of multi linear regression (MLR) and Levenberg-Marquardt (LM) feed-forward neural network was examined to estimate the hourly dew point temperature. Dew point temperature is the temperature at which water vapor in the air condenses into liquid. This temperature can be useful in estimating meteorological variables such as fog, rain, snow, dew, and evapotranspiration and in investigating agronomical issues as stomatal closure in plants. The availability of hourly records of climatic data (air temperature, relative humidity and pressure) which could be used to predict dew point temperature initiated the practice of modeling. Additionally, the wind vector (wind speed magnitude and direction) and conceptual input of weather condition were employed as other input variables. The three quantitative standard statistical performance evaluation measures, i.e. the root mean squared error, mean absolute error, and absolute logarithmic Nash-Sutcliffe efficiency coefficient ( {| {{{Log}}({{NS}})} |} ) were employed to evaluate the performances of the developed models. The results showed that applying wind vector and weather condition as input vectors along with meteorological variables could slightly increase the ANN and MLR predictive accuracy. The results also revealed that LM-NN was superior to MLR model and the best performance was obtained by considering all potential input variables in terms of different evaluation criteria.

Climate change impact assessment on hydrology of a small watershed using semi-distributed model

NASA Astrophysics Data System (ADS)

Pandey, Brij Kishor; Gosain, A. K.; Paul, George; Khare, Deepak

2017-07-01

This study is an attempt to quantify the impact of climate change on the hydrology of Armur watershed in Godavari river basin, India. A GIS-based semi-distributed hydrological model, soil and water assessment tool (SWAT) has been employed to estimate the water balance components on the basis of unique combinations of slope, soil and land cover classes for the base line (1961-1990) and future climate scenarios (2071-2100). Sensitivity analysis of the model has been performed to identify the most critical parameters of the watershed. Average monthly calibration (1987-1994) and validation (1995-2000) have been performed using the observed discharge data. Coefficient of determination (R2), Nash-Sutcliffe efficiency (ENS) and root mean square error (RMSE) were used to evaluate the model performance. Calibrated SWAT setup has been used to evaluate the changes in water balance components of future projection over the study area. HadRM3, a regional climatic data, have been used as input of the hydrological model for climate change impact studies. In results, it was found that changes in average annual temperature (+3.25 °C), average annual rainfall (+28 %), evapotranspiration (28 %) and water yield (49 %) increased for GHG scenarios with respect to the base line scenario.

Temporal dynamics of catchment transit times from stable isotope data

NASA Astrophysics Data System (ADS)

Klaus, Julian; Chun, Kwok P.; McGuire, Kevin J.; McDonnell, Jeffrey J.

2015-06-01

Time variant catchment transit time distributions are fundamental descriptors of catchment function but yet not fully understood, characterized, and modeled. Here we present a new approach for use with standard runoff and tracer data sets that is based on tracking of tracer and age information and time variant catchment mixing. Our new approach is able to deal with nonstationarity of flow paths and catchment mixing, and an irregular shape of the transit time distribution. The approach extracts information on catchment mixing from the stable isotope time series instead of prior assumptions of mixing or the shape of transit time distribution. We first demonstrate proof of concept of the approach with artificial data; the Nash-Sutcliffe efficiencies in tracer and instantaneous transit times were >0.9. The model provides very accurate estimates of time variant transit times when the boundary conditions and fluxes are fully known. We then tested the model with real rainfall-runoff flow and isotope tracer time series from the H.J. Andrews Watershed 10 (WS10) in Oregon. Model efficiencies were 0.37 for the 18O modeling for a 2 year time series; the efficiencies increased to 0.86 for the second year underlying the need of long time tracer time series with a long overlap of tracer input and output. The approach was able to determine time variant transit time of WS10 with field data and showed how it follows the storage dynamics and related changes in flow paths where wet periods with high flows resulted in clearly shorter transit times compared to dry low flow periods.

Computing daily mean streamflow at ungaged locations in Iowa by using the Flow Anywhere and Flow Duration Curve Transfer statistical methods

USGS Publications Warehouse

Linhart, S. Mike; Nania, Jon F.; Sanders, Curtis L.; Archfield, Stacey A.

2012-01-01

-mean-square error ranged from 13.0 to 5.3 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.80 to 0.40. Percent-bias values ranged from 25.4 to 4.0 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.35. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.86 to 0.56. For the streamgage with the best agreement between observed and estimated streamflow, higher streamflows appear to be underestimated. For the streamgage with the worst agreement between observed and estimated streamflow, low flows appear to be overestimated whereas higher flows seem to be underestimated. Estimated cumulative streamflows for the period October 1, 2004, to September 30, 2009, are underestimated by -25.8 and -7.4 percent for the closest and poorest comparisons, respectively. For the Flow Duration Curve Transfer method, results of the validation study conducted by using the same six streamgages show that differences between the root-mean-square error and the mean absolute error ranged from 437 to 93.9 ft3/s, with the larger value signifying a greater occurrence of outliers between observed and estimated streamflows. Root-mean-square-error values ranged from 906 to 169 ft3/s. Values of the percent root-mean-square-error ranged from 67.0 to 25.6 percent. The logarithm (base 10) streamflow percent root-mean-square error ranged from 12.5 to 4.4 percent. Root-mean-square-error observations standard-deviation-ratio values ranged from 0.79 to 0.40. Percent-bias values ranged from 22.7 to 0.94 percent. Untransformed streamflow Nash-Sutcliffe efficiency values ranged from 0.84 to 0.38. The logarithm (base 10) streamflow Nash-Sutcliffe efficiency values ranged from 0.89 to 0.48. For the streamgage with the closest agreement between observed and estimated streamflow, there is relatively good agreement between observed and estimated streamflows. For the streamgage with the poorest agreement between observed and

Increased Tim-3 expression alleviates liver injury by regulating macrophage activation in MCD-induced NASH mice.

PubMed

Du, Xianhong; Wu, Zhuanchang; Xu, Yong; Liu, Yuan; Liu, Wen; Wang, Tixiao; Li, Chunyang; Zhang, Cuijuan; Yi, Fan; Gao, Lifen; Liang, Xiaohong; Ma, Chunhong

2018-05-07

As an immune checkpoint, Tim-3 plays roles in the regulation of both adaptive and innate immune cells including macrophages and is greatly involved in chronic liver diseases. However, the precise roles of Tim-3 in nonalcoholic steatohepatitis (NASH) remain unstated. In the current study, we analyzed Tim-3 expression on different subpopulations of liver macrophages and further investigated the potential roles of Tim-3 on hepatic macrophages in methionine and choline-deficient diet (MCD)-induced NASH mice. The results of flow cytometry demonstrated the significantly increased expression of Tim-3 on all detected liver macrophage subsets in MCD mice, including F4/80 + CD11b + , F4/80 + CD68 + , and F4/80 + CD169 + macrophages. Remarkably, Tim-3 knockout (KO) significantly accelerated MCD-induced liver steatosis, displaying higher serum ALT, larger hepatic vacuolation, more liver lipid deposition, and more severe liver fibrosis. Moreover, compared with wild-type C57BL/6 mice, Tim-3 KO MCD mice demonstrated an enhanced expression of NOX2, NLRP3, and caspase-1 p20 together with increased generation of IL-1β and IL-18 in livers. In vitro studies demonstrated that Tim-3 negatively regulated the production of reactive oxygen species (ROS) and related downstream pro-inflammatory cytokine secretion of IL-1β and IL-18 in macrophages. Exogenous administration of N-Acetyl-L-cysteine (NAC), a small molecular inhibitor of ROS, remarkably suppressed caspase-1 p20 expression and IL-1β and IL-18 production in livers of Tim-3 KO mice, thus significantly reducing the severity of steatohepatitis induced by MCD. In conclusion, Tim-3 is a promising protector in MCD-induced steatohepatitis by controlling ROS and the associated pro-inflammatory cytokine production in macrophages.

Linear genetic programming application for successive-station monthly streamflow prediction

NASA Astrophysics Data System (ADS)

Danandeh Mehr, Ali; Kahya, Ercan; Yerdelen, Cahit

2014-09-01

In recent decades, artificial intelligence (AI) techniques have been pronounced as a branch of computer science to model wide range of hydrological phenomena. A number of researches have been still comparing these techniques in order to find more effective approaches in terms of accuracy and applicability. In this study, we examined the ability of linear genetic programming (LGP) technique to model successive-station monthly streamflow process, as an applied alternative for streamflow prediction. A comparative efficiency study between LGP and three different artificial neural network algorithms, namely feed forward back propagation (FFBP), generalized regression neural networks (GRNN), and radial basis function (RBF), has also been presented in this study. For this aim, firstly, we put forward six different successive-station monthly streamflow prediction scenarios subjected to training by LGP and FFBP using the field data recorded at two gauging stations on Çoruh River, Turkey. Based on Nash-Sutcliffe and root mean squared error measures, we then compared the efficiency of these techniques and selected the best prediction scenario. Eventually, GRNN and RBF algorithms were utilized to restructure the selected scenario and to compare with corresponding FFBP and LGP. Our results indicated the promising role of LGP for successive-station monthly streamflow prediction providing more accurate results than those of all the ANN algorithms. We found an explicit LGP-based expression evolved by only the basic arithmetic functions as the best prediction model for the river, which uses the records of the both target and upstream stations.

Development and comparison of Bayesian modularization method in uncertainty assessment of hydrological models

NASA Astrophysics Data System (ADS)

Li, L.; Xu, C.-Y.; Engeland, K.

2012-04-01

With respect to model calibration, parameter estimation and analysis of uncertainty sources, different approaches have been used in hydrological models. Bayesian method is one of the most widely used methods for uncertainty assessment of hydrological models, which incorporates different sources of information into a single analysis through Bayesian theorem. However, none of these applications can well treat the uncertainty in extreme flows of hydrological models' simulations. This study proposes a Bayesian modularization method approach in uncertainty assessment of conceptual hydrological models by considering the extreme flows. It includes a comprehensive comparison and evaluation of uncertainty assessments by a new Bayesian modularization method approach and traditional Bayesian models using the Metropolis Hasting (MH) algorithm with the daily hydrological model WASMOD. Three likelihood functions are used in combination with traditional Bayesian: the AR (1) plus Normal and time period independent model (Model 1), the AR (1) plus Normal and time period dependent model (Model 2) and the AR (1) plus multi-normal model (Model 3). The results reveal that (1) the simulations derived from Bayesian modularization method are more accurate with the highest Nash-Sutcliffe efficiency value, and (2) the Bayesian modularization method performs best in uncertainty estimates of entire flows and in terms of the application and computational efficiency. The study thus introduces a new approach for reducing the extreme flow's effect on the discharge uncertainty assessment of hydrological models via Bayesian. Keywords: extreme flow, uncertainty assessment, Bayesian modularization, hydrological model, WASMOD

Development of Semi-distributed ecohydrological model in the Rio Grande De Manati River Basin, Puerto Rico

NASA Astrophysics Data System (ADS)

Setegn, S. G.; Ortiz, J.; Melendez, J.; Barreto, M.; Torres-Perez, J. L.; Guild, L. S.

2015-12-01

There are limited studies in Puerto Rico that shows the water resources availability and variability with respect to changing climates and land use. The main goal of the HICE-PR (Human Impacts to Coastal Ecosystems in Puerto Rico (HICE-PR): the Río Loco Watershed (southwest coast PR) project which was funded by NASA is to evaluate the impacts of land use/land cover changes on the quality and extent of coastal and marine ecosystems (CMEs) in two priority watersheds in Puerto Rico (Manatí and Guánica).The main objective of this study is to set up a physically based spatially distributed hydrological model, Soil and Water Assessment Tool (SWAT) for the analysis of hydrological processes in the Rio Grande de Manati river basin. SWAT (soil and water assessment tool) is a spatially distributed watershed model developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds. For efficient use of distributed models for hydrological and scenario analysis, it is important that these models pass through a careful calibration and uncertainty analysis. The model was calibrated and validated using Sequential Uncertainty Fitting (SUFI-2) calibration and uncertainty analysis algorithms. The model evaluation statistics for streamflows prediction shows that there is a good agreement between the measured and simulated flows that was verified by coefficients of determination and Nash Sutcliffe efficiency greater than 0.5. Keywords: Hydrological Modeling; SWAT; SUFI-2; Rio Grande De Manati; Puerto Rico

Impact of the calibration period on the conceptual rainfall-runoff model parameter estimates

NASA Astrophysics Data System (ADS)

Todorovic, Andrijana; Plavsic, Jasna

2015-04-01

A conceptual rainfall-runoff model is defined by its structure and parameters, which are commonly inferred through model calibration. Parameter estimates depend on objective function(s), optimisation method, and calibration period. Model calibration over different periods may result in dissimilar parameter estimates, while model efficiency decreases outside calibration period. Problem of model (parameter) transferability, which conditions reliability of hydrologic simulations, has been investigated for decades. In this paper, dependence of the parameter estimates and model performance on calibration period is analysed. The main question that is addressed is: are there any changes in optimised parameters and model efficiency that can be linked to the changes in hydrologic or meteorological variables (flow, precipitation and temperature)? Conceptual, semi-distributed HBV-light model is calibrated over five-year periods shifted by a year (sliding time windows). Length of the calibration periods is selected to enable identification of all parameters. One water year of model warm-up precedes every simulation, which starts with the beginning of a water year. The model is calibrated using the built-in GAP optimisation algorithm. The objective function used for calibration is composed of Nash-Sutcliffe coefficient for flows and logarithms of flows, and volumetric error, all of which participate in the composite objective function with approximately equal weights. Same prior parameter ranges are used in all simulations. The model is calibrated against flows observed at the Slovac stream gauge on the Kolubara River in Serbia (records from 1954 to 2013). There are no trends in precipitation nor in flows, however, there is a statistically significant increasing trend in temperatures at this catchment. Parameter variability across the calibration periods is quantified in terms of standard deviations of normalised parameters, enabling detection of the most variable parameters

Development, Testing, and Psychometric Qualities of the Nash Duty to Care Scale for Disaster Response.

PubMed

Nash, Tracy Jeanne

2017-08-01

Although nurses struggle with the decision to report for work during disaster events, there are no instruments to measure nurses' duty to care for disaster situations. The purpose of this study was to describe the development, testing, and psychometric qualities of the Nash Duty to Care Scale. A convenience sample of 409 registered nurses were recruited from 3 universities in the United States. Exploratory factor analysis resulted in a 19-item, 4-factor model explaining 67.34% of the variance. Internal consistency reliability was supported by Cronbach's alpha ranging from .81 to .91 for the 4-factor subscales and .92 for the total scale. The psychometrically sound instrument for measuring nurses' perceived duty to care for disasters is applicable to contemporary nursing practice, institutional disaster management plans, and patient health outcomes worldwide.

Strategic trade between two regions with partial local consumer protection - General setup and nash equilibria

NASA Astrophysics Data System (ADS)

Iordanov, Iordan V.; Vassilev, Andrey A.

2017-12-01

We construct a model of the trade relations between two regions for the case when the trading entities (consumers) compete for a scarce good and there is an element of strategic interdependence in the trading process. Additionally, local consumers enjoy partial protection in the form of guaranteed access to a part of the locally-supplied quantity of the good. The model is formulated for the general asymmetric case, where the two regions differ in terms of parameters such as income, size of the local market supply, degree of protection and transportation costs. For this general model we establish the existence of Nash equilibria and obtain their form as a function of the model parameters, producing a typology of the equilibria. This is a required step in order to rigorously study various types of price dynamics for the model.

Development of genetic algorithm-based optimization module in WHAT system for hydrograph analysis and model application

NASA Astrophysics Data System (ADS)

Lim, Kyoung Jae; Park, Youn Shik; Kim, Jonggun; Shin, Yong-Chul; Kim, Nam Won; Kim, Seong Joon; Jeon, Ji-Hong; Engel, Bernard A.

2010-07-01

Many hydrologic and water quality computer models have been developed and applied to assess hydrologic and water quality impacts of land use changes. These models are typically calibrated and validated prior to their application. The Long-Term Hydrologic Impact Assessment (L-THIA) model was applied to the Little Eagle Creek (LEC) watershed and compared with the filtered direct runoff using BFLOW and the Eckhardt digital filter (with a default BFI max value of 0.80 and filter parameter value of 0.98), both available in the Web GIS-based Hydrograph Analysis Tool, called WHAT. The R2 value and the Nash-Sutcliffe coefficient values were 0.68 and 0.64 with BFLOW, and 0.66 and 0.63 with the Eckhardt digital filter. Although these results indicate that the L-THIA model estimates direct runoff reasonably well, the filtered direct runoff values using BFLOW and Eckhardt digital filter with the default BFI max and filter parameter values do not reflect hydrological and hydrogeological situations in the LEC watershed. Thus, a BFI max GA-Analyzer module (BFI max Genetic Algorithm-Analyzer module) was developed and integrated into the WHAT system for determination of the optimum BFI max parameter and filter parameter of the Eckhardt digital filter. With the automated recession curve analysis method and BFI max GA-Analyzer module of the WHAT system, the optimum BFI max value of 0.491 and filter parameter value of 0.987 were determined for the LEC watershed. The comparison of L-THIA estimates with filtered direct runoff using an optimized BFI max and filter parameter resulted in an R2 value of 0.66 and the Nash-Sutcliffe coefficient value of 0.63. However, L-THIA estimates calibrated with the optimized BFI max and filter parameter increased by 33% and estimated NPS pollutant loadings increased by more than 20%. This indicates L-THIA model direct runoff estimates can be incorrect by 33% and NPS pollutant loading estimation by more than 20%, if the accuracy of the baseflow

Battle for Climate and Scarcity Rents: Beyond the Linear-Quadratic Case.

PubMed

Kagan, Mark; van der Ploeg, Frederick; Withagen, Cees

Industria imports oil, produces final goods and wishes to mitigate global warming. Oilrabia exports oil and buys final goods from the other country. Industria uses the carbon tax to impose an import tariff on oil and steal some of Oilrabia's scarcity rent. Conversely, Oilrabia has monopoly power and sets the oil price to steal some of Industria's climate rent. We analyze the relative speeds of oil extraction and carbon accumulation under these strategic interactions for various production function specifications and compare these with the efficient and competitive outcomes. We prove that for the class of HARA production functions, the oil price is initially higher and subsequently lower in the open-loop Nash equilibrium than in the efficient outcome. The oil extraction rate is thus initially too low and in later stages too high. The HARA class includes linear, loglinear and semi-loglinear demand functions as special cases. For non-HARA production functions, Oilrabia may in the open-loop Nash equilibrium initially price oil lower than the efficient level, thus resulting in more oil extraction and climate damages. We also contrast the open-loop Nash and efficient outcomes numerically with the feedback Nash outcomes. We find that the optimal carbon tax path in the feedback Nash equilibrium is flatter than in the open-loop Nash equilibrium. It turns out that for certain demand functions using the carbon tax as an import tariff may hurt consumers' welfare as the resulting user cost of oil is so high that the fall in welfare wipes out the gain from higher tariff revenues.

The Effect of Metformin and Standard Therapy Versus Standard Therapy Alone in Nondiabetic Patients with Insulin Resistance and Nonalcoholic Steatohepatitis (NASH): A Pilot Trial

DTIC Science & Technology

2009-01-01

histology in nondiabetic patients with insulin resistance and NASH. Decrease in BMI through diet and exercise significantly improved HOMA - IR scores, serum...BMI through diet and exercise significantly improved HOMA - IR scores, serum aminotransferases and liver histology. 15. SUBJECT TERMS 16. SECURITY...insulin resistance (or HOMA - IR ) score was calculated using the formula: fasting insulin (mIU/ml) fasting glu- cose (mg/dl)/405 [Matthews et al. 1985

Seasonal drought ensemble predictions based on multiple climate models in the upper Han River Basin, China

NASA Astrophysics Data System (ADS)

Ma, Feng; Ye, Aizhong; Duan, Qingyun

2017-03-01

An experimental seasonal drought forecasting system is developed based on 29-year (1982-2010) seasonal meteorological hindcasts generated by the climate models from the North American Multi-Model Ensemble (NMME) project. This system made use of a bias correction and spatial downscaling method, and a distributed time-variant gain model (DTVGM) hydrologic model. DTVGM was calibrated using observed daily hydrological data and its streamflow simulations achieved Nash-Sutcliffe efficiency values of 0.727 and 0.724 during calibration (1978-1995) and validation (1996-2005) periods, respectively, at the Danjiangkou reservoir station. The experimental seasonal drought forecasting system (known as NMME-DTVGM) is used to generate seasonal drought forecasts. The forecasts were evaluated against the reference forecasts (i.e., persistence forecast and climatological forecast). The NMME-DTVGM drought forecasts have higher detectability and accuracy and lower false alarm rate than the reference forecasts at different lead times (from 1 to 4 months) during the cold-dry season. No apparent advantage is shown in drought predictions during spring and summer seasons because of a long memory of the initial conditions in spring and a lower predictive skill for precipitation in summer. Overall, the NMME-based seasonal drought forecasting system has meaningful skill in predicting drought several months in advance, which can provide critical information for drought preparedness and response planning as well as the sustainable practice of water resource conservation over the basin.

A simple analytical infiltration model for short-duration rainfall

NASA Astrophysics Data System (ADS)

Wang, Kaiwen; Yang, Xiaohua; Liu, Xiaomang; Liu, Changming

2017-12-01

Many infiltration models have been proposed to simulate infiltration process. Different initial soil conditions and non-uniform initial water content can lead to infiltration simulation errors, especially for short-duration rainfall (SHR). Few infiltration models are specifically derived to eliminate the errors caused by the complex initial soil conditions. We present a simple analytical infiltration model for SHR infiltration simulation, i.e., Short-duration Infiltration Process model (SHIP model). The infiltration simulated by 5 models (i.e., SHIP (high) model, SHIP (middle) model, SHIP (low) model, Philip model and Parlange model) were compared based on numerical experiments and soil column experiments. In numerical experiments, SHIP (middle) and Parlange models had robust solutions for SHR infiltration simulation of 12 typical soils under different initial soil conditions. The absolute values of percent bias were less than 12% and the values of Nash and Sutcliffe efficiency were greater than 0.83. Additionally, in soil column experiments, infiltration rate fluctuated in a range because of non-uniform initial water content. SHIP (high) and SHIP (low) models can simulate an infiltration range, which successfully covered the fluctuation range of the observed infiltration rate. According to the robustness of solutions and the coverage of fluctuation range of infiltration rate, SHIP model can be integrated into hydrologic models to simulate SHR infiltration process and benefit the flood forecast.

Linking Stream Dissolved Oxygen with the Dynamic Environmental Drivers across the Pacific Coast of U.S.A.

NASA Astrophysics Data System (ADS)

Araya, F. Z.; Abdul-Aziz, O. I.

2017-12-01

This study utilized a systematic data analytics approach to determine the relative linkages of stream dissolved oxygen (DO) with the hydro-climatic and biogeochemical drivers across the U.S. Pacific Coast. Multivariate statistical techniques of Pearson correlation matrix, principal component analysis, and factor analysis were applied to a complex water quality dataset (1998-2015) at 35 water quality monitoring stations of USGS NWIS and EPA STORET. Power-law based partial least squares regression (PLSR) models with a bootstrap Monte Carlo procedure (1000 iterations) were developed to reliably estimate the relative linkages by resolving multicollinearity (Nash-Sutcliffe Efficiency, NSE = 0.50-0.94). Based on the dominant drivers, four environmental regimes have been identified and adequately described the system-data variances. In Pacific North West and Southern California, water temperature was the most dominant driver of DO in majority of the streams. However, in Central and Northern California, stream DO was controlled by multiple drivers (i.e., water temperature, pH, stream flow, and total phosphorus), exhibiting a transitional environmental regime. Further, total phosphorus (TP) appeared to be the limiting nutrient for most streams. The estimated linkages and insights would be useful to identify management priorities to achieve healthy coastal stream ecosystems across the Pacific Coast of U.S.A. and similar regions around the world. Keywords: Data analytics, water quality, coastal streams, dissolved oxygen, environmental regimes, Pacific Coast, United States.

Effect of Using Extreme Years in Hydrologic Model Calibration Performance

NASA Astrophysics Data System (ADS)

Goktas, R. K.; Tezel, U.; Kargi, P. G.; Ayvaz, T.; Tezyapar, I.; Mesta, B.; Kentel, E.

2017-12-01

Hydrological models are useful in predicting and developing management strategies for controlling the system behaviour. Specifically they can be used for evaluating streamflow at ungaged catchments, effect of climate change, best management practices on water resources, or identification of pollution sources in a watershed. This study is a part of a TUBITAK project named "Development of a geographical information system based decision-making tool for water quality management of Ergene Watershed using pollutant fingerprints". Within the scope of this project, first water resources in Ergene Watershed is studied. Streamgages found in the basin are identified and daily streamflow measurements are obtained from State Hydraulic Works of Turkey. Streamflow data is analysed using box-whisker plots, hydrographs and flow-duration curves focusing on identification of extreme periods, dry or wet. Then a hydrological model is developed for Ergene Watershed using HEC-HMS in the Watershed Modeling System (WMS) environment. The model is calibrated for various time periods including dry and wet ones and the performance of calibration is evaluated using Nash-Sutcliffe Efficiency (NSE), correlation coefficient, percent bias (PBIAS) and root mean square error. It is observed that calibration period affects the model performance, and the main purpose of the development of the hydrological model should guide calibration period selection. Acknowledgement: This study is funded by The Scientific and Technological Research Council of Turkey (TUBITAK) under Project Number 115Y064.

Regional flow duration curves: Geostatistical techniques versus multivariate regression

USGS Publications Warehouse

Pugliese, Alessio; Farmer, William H.; Castellarin, Attilio; Archfield, Stacey A.; Vogel, Richard M.

2016-01-01

A period-of-record flow duration curve (FDC) represents the relationship between the magnitude and frequency of daily streamflows. Prediction of FDCs is of great importance for locations characterized by sparse or missing streamflow observations. We present a detailed comparison of two methods which are capable of predicting an FDC at ungauged basins: (1) an adaptation of the geostatistical method, Top-kriging, employing a linear weighted average of dimensionless empirical FDCs, standardised with a reference streamflow value; and (2) regional multiple linear regression of streamflow quantiles, perhaps the most common method for the prediction of FDCs at ungauged sites. In particular, Top-kriging relies on a metric for expressing the similarity between catchments computed as the negative deviation of the FDC from a reference streamflow value, which we termed total negative deviation (TND). Comparisons of these two methods are made in 182 largely unregulated river catchments in the southeastern U.S. using a three-fold cross-validation algorithm. Our results reveal that the two methods perform similarly throughout flow-regimes, with average Nash-Sutcliffe Efficiencies 0.566 and 0.662, (0.883 and 0.829 on log-transformed quantiles) for the geostatistical and the linear regression models, respectively. The differences between the reproduction of FDC's occurred mostly for low flows with exceedance probability (i.e. duration) above 0.98.

Development of seasonal flow outlook model for Ganges-Brahmaputra Basins in Bangladesh

NASA Astrophysics Data System (ADS)

Hossain, Sazzad; Haque Khan, Raihanul; Gautum, Dilip Kumar; Karmaker, Ripon; Hossain, Amirul

2016-10-01

Bangladesh is crisscrossed by the branches and tributaries of three main river systems, the Ganges, Bramaputra and Meghna (GBM). The temporal variation of water availability of those rivers has an impact on the different water usages such as irrigation, urban water supply, hydropower generation, navigation etc. Thus, seasonal flow outlook can play important role in various aspects of water management. The Flood Forecasting and Warning Center (FFWC) in Bangladesh provides short term and medium term flood forecast, and there is a wide demand from end-users about seasonal flow outlook for agricultural purposes. The objective of this study is to develop a seasonal flow outlook model in Bangladesh based on rainfall forecast. It uses European Centre for Medium-Range Weather Forecasts (ECMWF) seasonal precipitation, temperature forecast to simulate HYDROMAD hydrological model. Present study is limited for Ganges and Brahmaputra River Basins. ARIMA correction is applied to correct the model error. The performance of the model is evaluated using coefficient of determination (R2) and Nash-Sutcliffe Efficiency (NSE). The model result shows good performance with R2 value of 0.78 and NSE of 0.61 for the Brahmaputra River Basin, and R2 value of 0.72 and NSE of 0.59 for the Ganges River Basin for the period of May to July 2015. The result of the study indicates strong potential to make seasonal outlook to be operationalized.

Statistical downscaling rainfall using artificial neural network: significantly wetter Bangkok?

NASA Astrophysics Data System (ADS)

Vu, Minh Tue; Aribarg, Thannob; Supratid, Siriporn; Raghavan, Srivatsan V.; Liong, Shie-Yui

2016-11-01

Artificial neural network (ANN) is an established technique with a flexible mathematical structure that is capable of identifying complex nonlinear relationships between input and output data. The present study utilizes ANN as a method of statistically downscaling global climate models (GCMs) during the rainy season at meteorological site locations in Bangkok, Thailand. The study illustrates the applications of the feed forward back propagation using large-scale predictor variables derived from both the ERA-Interim reanalyses data and present day/future GCM data. The predictors are first selected over different grid boxes surrounding Bangkok region and then screened by using principal component analysis (PCA) to filter the best correlated predictors for ANN training. The reanalyses downscaled results of the present day climate show good agreement against station precipitation with a correlation coefficient of 0.8 and a Nash-Sutcliffe efficiency of 0.65. The final downscaled results for four GCMs show an increasing trend of precipitation for rainy season over Bangkok by the end of the twenty-first century. The extreme values of precipitation determined using statistical indices show strong increases of wetness. These findings will be useful for policy makers in pondering adaptation measures due to flooding such as whether the current drainage network system is sufficient to meet the changing climate and to plan for a range of related adaptation/mitigation measures.

Hydrologic Evaluation of TRMM Multisatellite Precipitation Analysis for Nanliu River Basin in Humid Southwestern China.

PubMed

Zhao, Yinjun; Xie, Qiongying; Lu, Yuan; Hu, Baoqing

2017-06-01

The accuracy of Tropical Rainfall Measuring Mission (TRMM) multi-satellite precipitation analysis (TMPA) daily accumulated precipitation products (3B42RTV7 and 3B42V7) was evaluated for a small basin (the Nanliu river basin). A direct comparison was performed against gauge observations from a period of 9 years (2000-2009) at temporal and spatial scales. The results show that the temporal-spatial precipitation characteristics of the Nanliu river basin are highly consistent with 3B42V7 relative to 3B42RTV7, with higher correlation coefficient (CC) approximately 0.9 at all temporal scales except for the daily scale and a lower relative bias percentage. 3B42V7 slightly overestimates precipitation at all temporal scales except the yearly scale; it slightly underestimates the precipitation at the daily spatial scale. The results also reveal that the precision of TMPA products increases with longer time-aggregated data, and the detection capability of daily TMPA precipitation products are enhanced by augmentation with daily precipitation rates. In addition, daily TMPA products were input into the Xin'anjiang hydrologic model; the results show that 3B42V7-based simulated outputs were well in line with actual stream flow observations, with a high CC (0.90) and Nash-Sutcliffe efficiency coefficient (NSE, 0.79), and the results adequately captured the pattern of the observed flow curve.

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Artan, Guleid A.; Tokar, S.A.; Gautam, D.K.; Bajracharya, S.R.; Shrestha, M.S.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.

A mathematical model for the transfer of soil solutes to runoff under water scouring.

PubMed

Yang, Ting; Wang, Quanjiu; Wu, Laosheng; Zhang, Pengyu; Zhao, Guangxu; Liu, Yanli

2016-11-01

The transfer of nutrients from soil to runoff often causes unexpected pollution in water bodies. In this study, a mathematical model that relates to the detachment of soil particles by water flow and the degree of mixing between overland flow and soil nutrients was proposed. The model assumes that the mixing depth is an integral of average water flow depth, and it was evaluated by experiments with three water inflow rates to bare soil surfaces and to surfaces with eight treatments of different stone coverages. The model predicted outflow rates were compared with the experimentally observed data to test the accuracy of the infiltration parameters obtained by curve fitting the models to the data. Further analysis showed that the comprehensive mixing coefficient (ke) was linearly correlated with Reynolds' number Re (R(2)>0.9), and this relationship was verified by comparing the simulated potassium concentration and cumulative mass with observed data, respectively. The best performance with the bias error analysis (Nash Sutcliffe coefficient of efficiency (NS), relative error (RE) and the coefficient of determination (R(2))) showed that the predicted data by the proposed model was in good agreement with the measured data. Thus the model can be used to guide soil-water and fertilization management to minimize nutrient runoff from cropland. Copyright © 2016 Elsevier B.V. All rights reserved.

Using machine learning for real-time estimates of snow water equivalent in the watersheds of Afghanistan

NASA Astrophysics Data System (ADS)

Bair, Edward H.; Abreu Calfa, Andre; Rittger, Karl; Dozier, Jeff

2018-05-01

In the mountains, snowmelt often provides most of the runoff. Operational estimates use imagery from optical and passive microwave sensors, but each has its limitations. An accurate approach, which we validate in Afghanistan and the Sierra Nevada USA, reconstructs spatially distributed snow water equivalent (SWE) by calculating snowmelt backward from a remotely sensed date of disappearance. However, reconstructed SWE estimates are available only retrospectively; they do not provide a forecast. To estimate SWE throughout the snowmelt season, we consider physiographic and remotely sensed information as predictors and reconstructed SWE as the target. The period of analysis matches the AMSR-E radiometer's lifetime from 2003 to 2011, for the months of April through June. The spatial resolution of the predictions is 3.125 km, to match the resolution of a microwave brightness temperature product. Two machine learning techniques - bagged regression trees and feed-forward neural networks - produced similar mean results, with 0-14 % bias and 46-48 mm RMSE on average. Nash-Sutcliffe efficiencies averaged 0.68 for all years. Daily SWE climatology and fractional snow-covered area are the most important predictors. We conclude that these methods can accurately estimate SWE during the snow season in remote mountains, and thereby provide an independent estimate to forecast runoff and validate other methods to assess the snow resource.

Model Performance Evaluation and Scenario Analysis ...

EPA Pesticide Factsheets

This tool consists of two parts: model performance evaluation and scenario analysis (MPESA). The model performance evaluation consists of two components: model performance evaluation metrics and model diagnostics. These metrics provides modelers with statistical goodness-of-fit measures that capture magnitude only, sequence only, and combined magnitude and sequence errors. The performance measures include error analysis, coefficient of determination, Nash-Sutcliffe efficiency, and a new weighted rank method. These performance metrics only provide useful information about the overall model performance. Note that MPESA is based on the separation of observed and simulated time series into magnitude and sequence components. The separation of time series into magnitude and sequence components and the reconstruction back to time series provides diagnostic insights to modelers. For example, traditional approaches lack the capability to identify if the source of uncertainty in the simulated data is due to the quality of the input data or the way the analyst adjusted the model parameters. This report presents a suite of model diagnostics that identify if mismatches between observed and simulated data result from magnitude or sequence related errors. MPESA offers graphical and statistical options that allow HSPF users to compare observed and simulated time series and identify the parameter values to adjust or the input data to modify. The scenario analysis part of the too

Predicting Hydrologic Function With Aquatic Gene Fragments

NASA Astrophysics Data System (ADS)

Good, S. P.; URycki, D. R.; Crump, B. C.

2018-03-01

Recent advances in microbiology techniques, such as genetic sequencing, allow for rapid and cost-effective collection of large quantities of genetic information carried within water samples. Here we posit that the unique composition of aquatic DNA material within a water sample contains relevant information about hydrologic function at multiple temporal scales. In this study, machine learning was used to develop discharge prediction models trained on the relative abundance of bacterial taxa classified into operational taxonomic units (OTUs) based on 16S rRNA gene sequences from six large arctic rivers. We term this approach "genohydrology," and show that OTU relative abundances can be used to predict river discharge at monthly and longer timescales. Based on a single DNA sample from each river, the average Nash-Sutcliffe efficiency (NSE) for predicted mean monthly discharge values throughout the year was 0.84, while the NSE for predicted discharge values across different return intervals was 0.67. These are considerable improvements over predictions based only on the area-scaled mean specific discharge of five similar rivers, which had average NSE values of 0.64 and -0.32 for seasonal and recurrence interval discharge values, respectively. The genohydrology approach demonstrates that genetic diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.

Estimating groundwater levels using system identification models in Nzhelele and Luvuvhu areas, Limpopo Province, South Africa

NASA Astrophysics Data System (ADS)

Makungo, Rachel; Odiyo, John O.

2017-08-01

This study was focused on testing the ability of a coupled linear and non-linear system identification model in estimating groundwater levels. System identification provides an alternative approach for estimating groundwater levels in areas that lack data required by physically-based models. It also overcomes the limitations of physically-based models due to approximations, assumptions and simplifications. Daily groundwater levels for 4 boreholes, rainfall and evaporation data covering the period 2005-2014 were used in the study. Seventy and thirty percent of the data were used to calibrate and validate the model, respectively. Correlation coefficient (R), coefficient of determination (R2), root mean square error (RMSE), percent bias (PBIAS), Nash Sutcliffe coefficient of efficiency (NSE) and graphical fits were used to evaluate the model performance. Values for R, R2, RMSE, PBIAS and NSE ranged from 0.8 to 0.99, 0.63 to 0.99, 0.01-2.06 m, -7.18 to 1.16 and 0.68 to 0.99, respectively. Comparisons of observed and simulated groundwater levels for calibration and validation runs showed close agreements. The model performance mostly varied from satisfactory, good, very good and excellent. Thus, the model is able to estimate groundwater levels. The calibrated models can reasonably capture description between input and output variables and can, thus be used to estimate long term groundwater levels.

Decomposition of the Mean Squared Error and NSE Performance Criteria: Implications for Improving Hydrological Modelling

NASA Technical Reports Server (NTRS)

Gupta, Hoshin V.; Kling, Harald; Yilmaz, Koray K.; Martinez-Baquero, Guillermo F.

2009-01-01

The mean squared error (MSE) and the related normalization, the Nash-Sutcliffe efficiency (NSE), are the two criteria most widely used for calibration and evaluation of hydrological models with observed data. Here, we present a diagnostically interesting decomposition of NSE (and hence MSE), which facilitates analysis of the relative importance of its different components in the context of hydrological modelling, and show how model calibration problems can arise due to interactions among these components. The analysis is illustrated by calibrating a simple conceptual precipitation-runoff model to daily data for a number of Austrian basins having a broad range of hydro-meteorological characteristics. Evaluation of the results clearly demonstrates the problems that can be associated with any calibration based on the NSE (or MSE) criterion. While we propose and test an alternative criterion that can help to reduce model calibration problems, the primary purpose of this study is not to present an improved measure of model performance. Instead, we seek to show that there are systematic problems inherent with any optimization based on formulations related to the MSE. The analysis and results have implications to the manner in which we calibrate and evaluate environmental models; we discuss these and suggest possible ways forward that may move us towards an improved and diagnostically meaningful approach to model performance evaluation and identification.

Performance of the general circulation models in simulating temperature and precipitation over Iran

NASA Astrophysics Data System (ADS)

Abbasian, Mohammadsadegh; Moghim, Sanaz; Abrishamchi, Ahmad

2018-03-01

General Circulation Models (GCMs) are advanced tools for impact assessment and climate change studies. Previous studies show that the performance of the GCMs in simulating climate variables varies significantly over different regions. This study intends to evaluate the performance of the Coupled Model Intercomparison Project phase 5 (CMIP5) GCMs in simulating temperature and precipitation over Iran. Simulations from 37 GCMs and observations from the Climatic Research Unit (CRU) were obtained for the period of 1901-2005. Six measures of performance including mean bias, root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), linear correlation coefficient (r), Kolmogorov-Smirnov statistic (KS), Sen's slope estimator, and the Taylor diagram are used for the evaluation. GCMs are ranked based on each statistic at seasonal and annual time scales. Results show that most GCMs perform reasonably well in simulating the annual and seasonal temperature over Iran. The majority of the GCMs have a poor skill to simulate precipitation, particularly at seasonal scale. Based on the results, the best GCMs to represent temperature and precipitation simulations over Iran are the CMCC-CMS (Euro-Mediterranean Center on Climate Change) and the MRI-CGCM3 (Meteorological Research Institute), respectively. The results are valuable for climate and hydrometeorological studies and can help water resources planners and managers to choose the proper GCM based on their criteria.

Parameter Identification and Uncertainty Analysis for Visual MODFLOW based Groundwater Flow Model in a Small River Basin, Eastern India

NASA Astrophysics Data System (ADS)

Jena, S.

2015-12-01

The overexploitation of groundwater resulted in abandoning many shallow tube wells in the river Basin in Eastern India. For the sustainability of groundwater resources, basin-scale modelling of groundwater flow is essential for the efficient planning and management of the water resources. The main intent of this study is to develope a 3-D groundwater flow model of the study basin using the Visual MODFLOW package and successfully calibrate and validate it using 17 years of observed data. The sensitivity analysis was carried out to quantify the susceptibility of aquifer system to the river bank seepage, recharge from rainfall and agriculture practices, horizontal and vertical hydraulic conductivities, and specific yield. To quantify the impact of parameter uncertainties, Sequential Uncertainty Fitting Algorithm (SUFI-2) and Markov chain Monte Carlo (MCMC) techniques were implemented. Results from the two techniques were compared and the advantages and disadvantages were analysed. Nash-Sutcliffe coefficient (NSE) and coefficient of determination (R2) were adopted as two criteria during calibration and validation of the developed model. NSE and R2 values of groundwater flow model for calibration and validation periods were in acceptable range. Also, the MCMC technique was able to provide more reasonable results than SUFI-2. The calibrated and validated model will be useful to identify the aquifer properties, analyse the groundwater flow dynamics and the change in groundwater levels in future forecasts.

Cement kiln dust (CKD)-filter sand permeable reactive barrier for the removal of Cu(II) and Zn(II) from simulated acidic groundwater.

PubMed

Sulaymon, Abbas H; Faisal, Ayad A H; Khaliefa, Qusey M

2015-10-30

The hydraulic conductivity and breakthrough curves of copper and zinc contaminants were measured in a set of continuous column experiments for 99 days using cement kiln dust (CKD)-filter sand as the permeable reactive barrier. The results of these experiments proved that the weight ratios of the cement kiln dust-filter sand (10:90 and 20:80) are adequate in preventing the loss of reactivity and hydraulic conductivity and, in turn, avoiding reduction in the groundwater flow. These results reveal a decrease in the hydraulic conductivity, which can be attributed to an accumulation of most of the quantity of the contaminant masses in the first sections of the column bed. Breakthrough curves for the description of the temporal contaminant transport within the barrier were found to be more representative by the Belter-Cussler-Hu and Yan models based on the coefficient of determination and Nash-Sutcliffe efficiency. The longevity of the barrier was simulated for the field scale, based on the laboratory column tests and the values verified that cement kiln dust can be effectively used in the future, as the reactive material in permeable reactive barrier technology. These results signify that the longevity of the barrier is directly proportional to its thickness and inversely to the percentage of the CKD used. Copyright © 2015 Elsevier B.V. All rights reserved.

Fuzzy rule-based forecast of meteorological drought in western Niger

NASA Astrophysics Data System (ADS)

Abdourahamane, Zakari Seybou; Acar, Reşat

2018-01-01

Understanding the causes of rainfall anomalies in the West African Sahel to effectively predict drought events remains a challenge. The physical mechanisms that influence precipitation in this region are complex, uncertain, and imprecise in nature. Fuzzy logic techniques are renowned to be highly efficient in modeling such dynamics. This paper attempts to forecast meteorological drought in Western Niger using fuzzy rule-based modeling techniques. The 3-month scale standardized precipitation index (SPI-3) of four rainfall stations was used as predictand. Monthly data of southern oscillation index (SOI), South Atlantic sea surface temperature (SST), relative humidity (RH), and Atlantic sea level pressure (SLP), sourced from the National Oceanic and Atmosphere Administration (NOAA), were used as predictors. Fuzzy rules and membership functions were generated using fuzzy c-means clustering approach, expert decision, and literature review. For a minimum lead time of 1 month, the model has a coefficient of determination R 2 between 0.80 and 0.88, mean square error (MSE) below 0.17, and Nash-Sutcliffe efficiency (NSE) ranging between 0.79 and 0.87. The empirical frequency distributions of the predicted and the observed drought classes are equal at the 99% of confidence level based on two-sample t test. Results also revealed the discrepancy in the influence of SOI and SLP on drought occurrence at the four stations while the effect of SST and RH are space independent, being both significantly correlated (at α < 0.05 level) to the SPI-3. Moreover, the implemented fuzzy model compared to decision tree-based forecast model shows better forecast skills.

Changes in the flood frequency in the Mahanadi basin under observed and projected future climate

NASA Astrophysics Data System (ADS)

Modi, P. A.; Lakshmi, V.; Mishra, V.

2017-12-01

The Mahanadi river basin is vulnerable to multiple types of extreme events due to its topography and river networks. These extreme events are not efficiently captured by the current LSMs partly due to lack of spatial hydrological data and uncertainty in the models. This study compares and evaluates the hydrologic simulations of the recently developed community Noah model with multi-parameterization options which is an upgradation of baseline Noah LSM. The model is calibrated and validated for the Mahanadi river basin and is driven by major atmospheric forcing from the Indian Meteorological Department (IMD), Global Precipitation Measurement (GPM), Tropical rainfall Measurement Mission (TRMM) and Multi-Source Weighted-Ensemble Precipitation (MSWEP designed for hydrological modeling) precipitation datasets along with some additional forcing derived from the VIC model at 0.25-degree spatial resolution. The Noah-MP LSM is calibrated using observed daily streamflow data from 1978-1989 (India-WRIS) at the gauge stations with least human interventions with a Nash Sutcliffe Efficiency higher than 0.60. Noah MP was calibrated using different schemes for runoff with variation in all parameters sensitive to surface and sub-surface runoff. Streamflow routing was performed using a stand-alone model (VIC model) to route daily model runoff at required gauge station. Surface runoff is mainly affected by the uncertainties in major atmospheric forcing and highly sensitive parameters pertaining to soil properties. Noah MP is validated using observed streamflow from 1975-2010 which indicates the consistency of streamflow with the historical observations (NSE>0.65) thus indicating an increase in probability of future flood events.

Instantaneous-to-daily GPP upscaling schemes based on a coupled photosynthesis-stomatal conductance model: correcting the overestimation of GPP by directly using daily average meteorological inputs.

PubMed

Wang, Fumin; Gonsamo, Alemu; Chen, Jing M; Black, T Andrew; Zhou, Bin

2014-11-01

Daily canopy photosynthesis is usually temporally upscaled from instantaneous (i.e., seconds) photosynthesis rate. The nonlinear response of photosynthesis to meteorological variables makes the temporal scaling a significant challenge. In this study, two temporal upscaling schemes of daily photosynthesis, the integrated daily model (IDM) and the segmented daily model (SDM), are presented by considering the diurnal variations of meteorological variables based on a coupled photosynthesis-stomatal conductance model. The two models, as well as a simple average daily model (SADM) with daily average meteorological inputs, were validated using the tower-derived gross primary production (GPP) to assess their abilities in simulating daily photosynthesis. The results showed IDM closely followed the seasonal trend of the tower-derived GPP with an average RMSE of 1.63 g C m(-2) day(-1), and an average Nash-Sutcliffe model efficiency coefficient (E) of 0.87. SDM performed similarly to IDM in GPP simulation but decreased the computation time by >66%. SADM overestimated daily GPP by about 15% during the growing season compared to IDM. Both IDM and SDM greatly decreased the overestimation by SADM, and improved the simulation of daily GPP by reducing the RMSE by 34 and 30%, respectively. The results indicated that IDM and SDM are useful temporal upscaling approaches, and both are superior to SADM in daily GPP simulation because they take into account the diurnally varying responses of photosynthesis to meteorological variables. SDM is computationally more efficient, and therefore more suitable for long-term and large-scale GPP simulations.

Prediction of dissolved oxygen concentration in hypoxic river systems using support vector machine: a case study of Wen-Rui Tang River, China.

PubMed

Ji, Xiaoliang; Shang, Xu; Dahlgren, Randy A; Zhang, Minghua

2017-07-01

Accurate quantification of dissolved oxygen (DO) is critically important for managing water resources and controlling pollution. Artificial intelligence (AI) models have been successfully applied for modeling DO content in aquatic ecosystems with limited data. However, the efficacy of these AI models in predicting DO levels in the hypoxic river systems having multiple pollution sources and complicated pollutants behaviors is unclear. Given this dilemma, we developed a promising AI model, known as support vector machine (SVM), to predict the DO concentration in a hypoxic river in southeastern China. Four different calibration models, specifically, multiple linear regression, back propagation neural network, general regression neural network, and SVM, were established, and their prediction accuracy was systemically investigated and compared. A total of 11 hydro-chemical variables were used as model inputs. These variables were measured bimonthly at eight sampling sites along the rural-suburban-urban portion of Wen-Rui Tang River from 2004 to 2008. The performances of the established models were assessed through the mean square error (MSE), determination coefficient (R 2 ), and Nash-Sutcliffe (NS) model efficiency. The results indicated that the SVM model was superior to other models in predicting DO concentration in Wen-Rui Tang River. For SVM, the MSE, R 2 , and NS values for the testing subset were 0.9416 mg/L, 0.8646, and 0.8763, respectively. Sensitivity analysis showed that ammonium-nitrogen was the most significant input variable of the proposal SVM model. Overall, these results demonstrated that the proposed SVM model can efficiently predict water quality, especially for highly impaired and hypoxic river systems.

Hydrologic modeling of Guinale River Basin using HEC-HMS and synthetic aperture radar

NASA Astrophysics Data System (ADS)

Bien, Ferdinand E.; Plopenio, Joanaviva C.

2017-09-01

This paper presents the methods and results of hydrologic modeling of Guinale river basin through the use of HEC-HMS software and Synthetic Aperture Radar Digital Elevation Model (SAR DEM). Guinale River Basin is located in the province of Albay, Philippines which is one of the river basins covered by the Ateneo de Naga University (ADNU) Phil-LiDAR 1. This research project was funded by the Department of Science and Technology (DOST) through the Philippine Council for Industry, Energy and Emerging Technology Research and Development (PCIEERD). Its objectives are to simulate the hydrologic model of Guinale River basin using HEC-HMS software and SAR DEM. Its basin covers an area of 165.395 sq.km. and the hydrologic model was calibrated using the storm event typhoon Nona (international name Melor). Its parameter had undergone a series of optimization processes of HEC-HMS software in order to produce an acceptable level of model efficiency. The Nash-Sutcliffe (E), Percent Bias and Standard Deviation Ratio were used to measure the model efficiency, giving values of 0.880, 0.260 and 0.346 respectively which resulted to a "very good" performance rating of the model. The flood inundation model was simulated using Legazpi Rainfall Intensity Duration Frequency Curves (RIDF) and HEC-RAS software developed by the US Army corps of Engineers (USACE). This hydrologic model will provide the Municipal Disaster Risk Reduction Management Office (MDRRMO), Local Government units (LGUs) and the community a tool for the prediction of runoff in the area.

Research on the response of the water sources to the climatic change in Shiyang River Basin

NASA Astrophysics Data System (ADS)

Jin, Y. Z.; Zeng, J. J.; Hu, X. Q.; Sun, D. Y.; Song, Z. F.; Zhang, Y. L.; Lu, S. C.; Cui, Y. Q.

2017-08-01

The influence of the future climate change to the water resource will directly pose some impact on the watershed management planning and administrative strategies of Shiyang River Basin. With the purpose of exploring the influence of climate change to the runoff, this paper set Shiyang River as the study area and then established a SWAT basin hydrological model based on the data such as DEM, land use, soil, climate hydrology and so on. Besides, algorithm of SUFI2 embedded in SWAT-CUP software is adopted. The conclusion shows that SWAT Model can simulate the runoff process of Nanying River well. During the period of model verification and simulation, the runoff Nash-Sutcliffe efficient coefficient of the verification and simulation is 0.76 and 0.72 separately. The relative error between the simulation and actual measurement and the model efficient coefficient are both within the scope of acceptance, which means that the SWAT hydrological model can be properly applied into the runoff simulation of Shiyang River Basin. Meantime, analysis on the response of the water resources to the climate change in Shiyang River Basin indicates that the impact of climate change on runoff is remarkable under different climate change situations and the annual runoff will be greatly decreased as the precipitation falls and the temperature rises. Influence of precipitation to annual runoff is greater than that of temperature. Annual runoff differs obviously under different climate change situations. All in all, this paper tries to provide some technical assistance for the water sources development and utilization assessment and optimal configuration.

From rationality to cooperativeness: The totally mixed Nash equilibrium in Markov strategies in the iterated Prisoner's Dilemma.

PubMed

Menshikov, Ivan S; Shklover, Alexsandr V; Babkina, Tatiana S; Myagkov, Mikhail G

2017-01-01

In this research, the social behavior of the participants in a Prisoner's Dilemma laboratory game is explained on the basis of the quantal response equilibrium concept and the representation of the game in Markov strategies. In previous research, we demonstrated that social interaction during the experiment has a positive influence on cooperation, trust, and gratefulness. This research shows that the quantal response equilibrium concept agrees only with the results of experiments on cooperation in Prisoner's Dilemma prior to social interaction. However, quantal response equilibrium does not explain of participants' behavior after social interaction. As an alternative theoretical approach, an examination was conducted of iterated Prisoner's Dilemma game in Markov strategies. We built a totally mixed Nash equilibrium in this game; the equilibrium agrees with the results of the experiments both before and after social interaction.

Water temperature of streams in the Cook Inlet basin, Alaska, and implications of climate change

USGS Publications Warehouse

Kyle, Rebecca E.; Brabets, Timothy P.

2001-10-02

Water-temperature data from 32 sites in the Cook Inlet Basin, south-central Alaska, indicate various trends that depend on watershed characteristics. Basins with 25 percent or more of their area consisting of glaciers have the coldest water temperatures during the open-water season, mid-May to mid-October. Streams and rivers that drain lowlands have the warmest water temperatures. A model that uses air temperature as input to predict water temperature as output was utilized to simulate future trends in water temperature based on increased air temperatures due to climate warming. Based on the Nash-Sutcliffe coefficient, the model produced acceptable results for 27 sites. For basins with more than 25 percent glacial coverage, the model was not as accurate. Results indicate that 15 sites had a predicted water-temperature change of 3 degrees Celsius or more, a magnitude of change that is considered significant for the incidence of disease in fish populations.

MRI and MRE for non-invasive quantitative assessment of hepatic steatosis and fibrosis in NAFLD and NASH: Clinical trials to clinical practice

PubMed Central

Dulai, Parambir S.; Sirlin, Claude B.; Loomba, Rohit

2016-01-01

Nonalcoholic fatty liver disease (NAFLD) represents one of the most common causes of chronic liver disease, and its prevalence is rising worldwide. The occurrence of nonalcoholic steatohepatitis (NASH) is associated with a substantial increase in disease related morbidity and mortality. Accordingly, there has been a surge of innovation surrounding drug development in an effort to off-set the natural progression and long-term risks of this disease. Disease assessment within clinical trials and clinical practice for NAFLD is currently done with liver biopsies. Liver biopsy-based assessments, however, remain imprecise and are not without cost or risk. This carries significant implications for the feasibility and costs of bringing therapeutic interventions to market. A need therefore arises for reliable and highly accurate surrogate end-points that can be used in phase 2 and 3 clinical trials to reduce trial size requirements and costs, while improving feasibility and ease of implementation in clinical practice. Significant advances have now been made in magnetic resonance technology, and magnetic resonance imaging (MRI) and elastrography (MRE) have been demonstrated to be highly accurate diagnostic tools for the detection of hepatic steatosis and fibrosis. In this review article, we will summarize the currently available evidence regarding the use of MRI and MRE among NAFLD patients, and the evolving role these surrogate biomarkers will play in the rapidly advancing arena of clinical trials in NASH and hepatic fibrosis. Furthermore, we will highlight how these tools can be readily applied to routine clinical practice, where the growing burden of NAFLD will need to be met with enhanced monitoring algorithms. PMID:27312947

On the Fair Division of Multiple Stochastic Pies to Multiple Agents within the Nash Bargaining Solution

PubMed Central

Karmperis, Athanasios C.; Aravossis, Konstantinos; Tatsiopoulos, Ilias P.; Sotirchos, Anastasios

2012-01-01

The fair division of a surplus is one of the most widely examined problems. This paper focuses on bargaining problems with fixed disagreement payoffs where risk-neutral agents have reached an agreement that is the Nash-bargaining solution (NBS). We consider a stochastic environment, in which the overall return consists of multiple pies with uncertain sizes and we examine how these pies can be allocated with fairness among agents. Specifically, fairness is based on the Aristotle’s maxim: “equals should be treated equally and unequals unequally, in proportion to the relevant inequality”. In this context, fairness is achieved when all the individual stochastic surplus shares which are allocated to agents are distributed in proportion to the NBS. We introduce a novel algorithm, which can be used to compute the ratio of each pie that should be allocated to each agent, in order to ensure fairness within a symmetric or asymmetric NBS. PMID:23024752

Coupling HYDRUS-1D Code with PA-DDS Algorithms for Inverse Calibration

NASA Astrophysics Data System (ADS)

Wang, Xiang; Asadzadeh, Masoud; Holländer, Hartmut

2017-04-01

Numerical modelling requires calibration to predict future stages. A standard method for calibration is inverse calibration where generally multi-objective optimization algorithms are used to find a solution, e.g. to find an optimal solution of the van Genuchten Mualem (VGM) parameters to predict water fluxes in the vadose zone. We coupled HYDRUS-1D with PA-DDS to add a new, robust function for inverse calibration to the model. The PA-DDS method is a recently developed multi-objective optimization algorithm, which combines Dynamically Dimensioned Search (DDS) and Pareto Archived Evolution Strategy (PAES). The results were compared to a standard method (Marquardt-Levenberg method) implemented in HYDRUS-1D. Calibration performance is evaluated using observed and simulated soil moisture at two soil layers in the Southern Abbotsford, British Columbia, Canada in the terms of the root mean squared error (RMSE) and the Nash-Sutcliffe Efficiency (NSE). Results showed low RMSE values of 0.014 and 0.017 and strong NSE values of 0.961 and 0.939. Compared to the results by the Marquardt-Levenberg method, we received better calibration results for deeper located soil sensors. However, VGM parameters were similar comparing with previous studies. Both methods are equally computational efficient. We claim that a direct implementation of PA-DDS into HYDRUS-1D should reduce the computation effort further. This, the PA-DDS method is efficient for calibrating recharge for complex vadose zone modelling with multiple soil layer and can be a potential tool for calibration of heat and solute transport. Future work should focus on the effectiveness of PA-DDS for calibrating more complex versions of the model with complex vadose zone settings, with more soil layers, and against measured heat and solute transport. Keywords: Recharge, Calibration, HYDRUS-1D, Multi-objective Optimization

A comparative analysis of 9 multi-model averaging approaches in hydrological continuous streamflow simulation

NASA Astrophysics Data System (ADS)

Arsenault, Richard; Gatien, Philippe; Renaud, Benoit; Brissette, François; Martel, Jean-Luc

2015-10-01

This study aims to test whether a weighted combination of several hydrological models can simulate flows more accurately than the models taken individually. In addition, the project attempts to identify the most efficient model averaging method and the optimal number of models to include in the weighting scheme. In order to address the first objective, streamflow was simulated using four lumped hydrological models (HSAMI, HMETS, MOHYSE and GR4J-6), each of which were calibrated with three different objective functions on 429 watersheds. The resulting 12 hydrographs (4 models × 3 metrics) were weighted and combined with the help of 9 averaging methods which are the simple arithmetic mean (SAM), Akaike information criterion (AICA), Bates-Granger (BGA), Bayes information criterion (BICA), Bayesian model averaging (BMA), Granger-Ramanathan average variant A, B and C (GRA, GRB and GRC) and the average by SCE-UA optimization (SCA). The same weights were then applied to the hydrographs in validation mode, and the Nash-Sutcliffe Efficiency metric was measured between the averaged and observed hydrographs. Statistical analyses were performed to compare the accuracy of weighted methods to that of individual models. A Kruskal-Wallis test and a multi-objective optimization algorithm were then used to identify the most efficient weighted method and the optimal number of models to integrate. Results suggest that the GRA, GRB, GRC and SCA weighted methods perform better than the individual members. Model averaging from these four methods were superior to the best of the individual members in 76% of the cases. Optimal combinations on all watersheds included at least one of each of the four hydrological models. None of the optimal combinations included all members of the ensemble of 12 hydrographs. The Granger-Ramanathan average variant C (GRC) is recommended as the best compromise between accuracy, speed of execution, and simplicity.

A Bidding Methodology by Nash Equilibrium for Finite Generators Participating in Imperfect Electricity Markets

NASA Astrophysics Data System (ADS)

Satyaramesh, P. V.

2014-01-01

This paper presents an application of finite n-person non-cooperative game theory for analyzing bidding strategies of generators in a deregulated energy marketplace with Pool Bilateral contracts so as to maximize their net profits. A new methodology to build bidding methodology for generators participating in oligopoly electricity market has been proposed in this paper. It is assumed that each generator bids a supply function. This methodology finds out the coefficients in the supply function of generators in order to maximize benefits in an environment of competing rival bidders. A natural choice for developing strategies is Nash Equilibrium (NE) model incorporating mixed strategies, for solving the bidding problem of electrical market. Associated optimal profits are evaluated for a combination of set of pure strategies of bidding of generators, and payoff matrix has been constructed. The optimal payoff is calculated by using NE. An attempt has also been made to minimize the gap between the optimal payoff and the payoff obtained by a possible mixed strategies combination. The algorithm is coded in MATLAB. A numerical example is used to illustrate the essential features of the approach and the results are proved to be the optimal values.

Gd-EOB-DTPA-enhanced-MR imaging in the inflammation stage of nonalcoholic steatohepatitis (NASH) in mice.

PubMed

Yamada, Tomomi; Obata, Atsushi; Kashiwagi, Yuto; Rokugawa, Takemi; Matsushima, Shuuichi; Hamada, Tadateru; Watabe, Hiroshi; Abe, Kohji

2016-07-01

The purpose of this study is to investigate the correlation between the liver kinetics of gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) and liver histopathology in a mouse model of NASH by using dynamic contrast-enhanced MRI. Twenty male C57/BL6 mice aged 8weeks were fed a methionine-choline-deficient (MCD) diet for 2, 4 and 6weeks (MCD groups: MCD 2w, 4w, or 6w). Gd-EOB-DTPA-enhanced MR imaging of the liver was performed at 2, 4 and 6weeks after the MCD feeding. The signal intensity of the liver was obtained from dynamic MR images and relative enhancement (RE), and the time to maximum RE (Tmax) and half-life of elimination RE (T1/2) were calculated. After MRI scan, histopathological scores of hepatic steatosis and inflammation and blood biochemistry data, such as aspartate aminotransferase (AST) and alanine aminotransferase (ALT) levels, were obtained. Plasma AST and ALT levels were significantly increased in mice fed MCD. Histopathological scores indicated that steatohepatitis progressed with the MCD feeding period from 2 to 6weeks, but significant fibrosis was observed only in mice fed MCD for 6weeks. Gd-EOB-DTPA-enhanced MRI showed that Tmax was significantly prolonged in the livers of the 6-week group compared to the control group (control, 4.0±0.7min; MCD 6w, 12.1±1.6min), although there was no alteration in the 2- and 4-week groups. T1/2 was significantly prolonged in mice fed MCD for 4 and 6weeks compared to the control group (control, 19.9±2.0min; MCD 4w, 46.7±8.7min; MCD 6w, 65.4±8.8min). The parameters of Gd-EOB-DTPA kinetics (Tmax and T1/2) in the liver were positively correlated with the liver histopathological score (steatosis vs Tmax, rho=0.69, P=0.0007; inflammation vs Tmax, rho=0.66, P=0.00155; steatosis vs T1/2, rho=0.77, P<0.0001; inflammation vs T1/2, rho=0.73, P=0.0003). The liver kinetics of Gd-EOB-DTPA correlated well with the inflammation score in the mouse model of NASH, suggesting the possibility of

From rationality to cooperativeness: The totally mixed Nash equilibrium in Markov strategies in the iterated Prisoner’s Dilemma

PubMed Central

Myagkov, Mikhail G.

2017-01-01

In this research, the social behavior of the participants in a Prisoner's Dilemma laboratory game is explained on the basis of the quantal response equilibrium concept and the representation of the game in Markov strategies. In previous research, we demonstrated that social interaction during the experiment has a positive influence on cooperation, trust, and gratefulness. This research shows that the quantal response equilibrium concept agrees only with the results of experiments on cooperation in Prisoner’s Dilemma prior to social interaction. However, quantal response equilibrium does not explain of participants’ behavior after social interaction. As an alternative theoretical approach, an examination was conducted of iterated Prisoner's Dilemma game in Markov strategies. We built a totally mixed Nash equilibrium in this game; the equilibrium agrees with the results of the experiments both before and after social interaction. PMID:29190280

Automation of Endmember Pixel Selection in SEBAL/METRIC Model

NASA Astrophysics Data System (ADS)

Bhattarai, N.; Quackenbush, L. J.; Im, J.; Shaw, S. B.

2015-12-01

The commonly applied surface energy balance for land (SEBAL) and its variant, mapping evapotranspiration (ET) at high resolution with internalized calibration (METRIC) models require manual selection of endmember (i.e. hot and cold) pixels to calibrate sensible heat flux. Current approaches for automating this process are based on statistical methods and do not appear to be robust under varying climate conditions and seasons. In this paper, we introduce a new approach based on simple machine learning tools and search algorithms that provides an automatic and time efficient way of identifying endmember pixels for use in these models. The fully automated models were applied on over 100 cloud-free Landsat images with each image covering several eddy covariance flux sites in Florida and Oklahoma. Observed land surface temperatures at automatically identified hot and cold pixels were within 0.5% of those from pixels manually identified by an experienced operator (coefficient of determination, R2, ≥ 0.92, Nash-Sutcliffe efficiency, NSE, ≥ 0.92, and root mean squared error, RMSE, ≤ 1.67 K). Daily ET estimates derived from the automated SEBAL and METRIC models were in good agreement with their manual counterparts (e.g., NSE ≥ 0.91 and RMSE ≤ 0.35 mm day-1). Automated and manual pixel selection resulted in similar estimates of observed ET across all sites. The proposed approach should reduce time demands for applying SEBAL/METRIC models and allow for their more widespread and frequent use. This automation can also reduce potential bias that could be introduced by an inexperienced operator and extend the domain of the models to new users.

Application of SPHY model for Understanding the Hydrological Regime of Tamor River, Nepal

NASA Astrophysics Data System (ADS)

Vaidya, A.; Kayastha, R. B.

2017-12-01

With the changing climate the hydrology of the rivers are also changing so to understand the actual impacts hydrological modelling plays a very vital role. In this study a distributed SPHY model is used in Tamor River basin located in the eastern part of Nepal to estimate the snow and glacier melt contribution in the discharge. The model calculates the each component of water balance equation in each grid cell of the basin and routes it to the outlet point. The model simulates the daily discharge for both calibration (2002-2005) and validation year (2006-2010) competently with coefficient of determination (R2) 0.78 and 0.76 and Nash-Sutcliffe Efficiency (NSE) 0.73 and 0.7, respectively. The model simulates the low flow with high efficiency whereas high flows are under estimated. The snow and glacier melt contribution in the river discharge is 20% for both calibration and validation year. The precipitation and temperature data for CMIP5 RCP4.5 and RCP8.5 scenarios after bias correction are used to simulate the projected discharge for period (2020-2099). The average discharge of the period is 170.21 m3 s-1 and 188.45 m3 s-1 for RCP4.5 and RCP8.5 respectively. The average contribution of snow and glacier melt in the discharge for the whole period (2020-2099) is similar to the calibration and validation year but decadal analysis shows that the contribution is highest in the midst of the period and again decreasing towards the end for both scenarios. The findings of the study indicate further monitoring and modeling is necessary to get better grasp of the subject.

Stepwise sensitivity analysis from qualitative to quantitative: Application to the terrestrial hydrological modeling of a Conjunctive Surface-Subsurface Process (CSSP) land surface model

NASA Astrophysics Data System (ADS)

Gan, Yanjun; Liang, Xin-Zhong; Duan, Qingyun; Choi, Hyun Il; Dai, Yongjiu; Wu, Huan

2015-06-01

An uncertainty quantification framework was employed to examine the sensitivities of 24 model parameters from a newly developed Conjunctive Surface-Subsurface Process (CSSP) land surface model (LSM). The sensitivity analysis (SA) was performed over 18 representative watersheds in the contiguous United States to examine the influence of model parameters in the simulation of terrestrial hydrological processes. Two normalized metrics, relative bias (RB) and Nash-Sutcliffe efficiency (NSE), were adopted to assess the fit between simulated and observed streamflow discharge (SD) and evapotranspiration (ET) for a 14 year period. SA was conducted using a multiobjective two-stage approach, in which the first stage was a qualitative SA using the Latin Hypercube-based One-At-a-Time (LH-OAT) screening, and the second stage was a quantitative SA using the Multivariate Adaptive Regression Splines (MARS)-based Sobol' sensitivity indices. This approach combines the merits of qualitative and quantitative global SA methods, and is effective and efficient for understanding and simplifying large, complex system models. Ten of the 24 parameters were identified as important across different watersheds. The contribution of each parameter to the total response variance was then quantified by Sobol' sensitivity indices. Generally, parameter interactions contribute the most to the response variance of the CSSP, and only 5 out of 24 parameters dominate model behavior. Four photosynthetic and respiratory parameters are shown to be influential to ET, whereas reference depth for saturated hydraulic conductivity is the most influential parameter for SD in most watersheds. Parameter sensitivity patterns mainly depend on hydroclimatic regime, as well as vegetation type and soil texture. This article was corrected on 26 JUN 2015. See the end of the full text for details.

Estimation of Groundwater Recharge in a Japanese Headwater Area by Intensive Collaboration of Field Survey and Modelling Work

NASA Astrophysics Data System (ADS)

Yano, S.; Kondo, H.; Tawara, Y.; Yamada, T.; Mori, K.; Yoshida, A.; Tada, K.; Tsujimura, M.; Tokunaga, T.

2017-12-01

It is important to understand groundwater systems, including their recharge, flow, storage, discharge, and withdrawal, so that we can use groundwater resources efficiently and sustainably. To examine groundwater recharge, several methods have been discussed based on water balance estimation, in situ experiments, and hydrological tracers. However, few studies have developed a concrete framework for quantifying groundwater recharge rates in an undefined area. In this study, we established a robust method to quantitatively determine water cycles and estimate the groundwater recharge rate by combining the advantages of field surveys and model simulations. We replicated in situ hydrogeological observations and three-dimensional modeling in a mountainous basin area in Japan. We adopted a general-purpose terrestrial fluid-flow simulator (GETFLOWS) to develop a geological model and simulate the local water cycle. Local data relating to topology, geology, vegetation, land use, climate, and water use were collected from the existing literature and observations to assess the spatiotemporal variations of the water balance from 2011 to 2013. The characteristic structures of geology and soils, as found through field surveys, were parameterized for incorporation into the model. The simulated results were validated using observed groundwater levels and resulted in a Nash-Sutcliffe Model Efficiency Coefficient of 0.92. The results suggested that local groundwater flows across the watershed boundary and that the groundwater recharge rate, defined as the flux of water reaching the local unconfined groundwater table, has values similar to the level estimated in the `the lower soil layers on a long-term basis. This innovative method enables us to quantify the groundwater recharge rate and its spatiotemporal variability with high accuracy, which contributes to establishing a foundation for sustainable groundwater management.

Ranking streamflow model performance based on Information theory metrics

NASA Astrophysics Data System (ADS)

Martinez, Gonzalo; Pachepsky, Yakov; Pan, Feng; Wagener, Thorsten; Nicholson, Thomas

2016-04-01

The accuracy-based model performance metrics not necessarily reflect the qualitative correspondence between simulated and measured streamflow time series. The objective of this work was to use the information theory-based metrics to see whether they can be used as complementary tool for hydrologic model evaluation and selection. We simulated 10-year streamflow time series in five watersheds located in Texas, North Carolina, Mississippi, and West Virginia. Eight model of different complexity were applied. The information-theory based metrics were obtained after representing the time series as strings of symbols where different symbols corresponded to different quantiles of the probability distribution of streamflow. The symbol alphabet was used. Three metrics were computed for those strings - mean information gain that measures the randomness of the signal, effective measure complexity that characterizes predictability and fluctuation complexity that characterizes the presence of a pattern in the signal. The observed streamflow time series has smaller information content and larger complexity metrics than the precipitation time series. Watersheds served as information filters and and streamflow time series were less random and more complex than the ones of precipitation. This is reflected the fact that the watershed acts as the information filter in the hydrologic conversion process from precipitation to streamflow. The Nash Sutcliffe efficiency metric increased as the complexity of models increased, but in many cases several model had this efficiency values not statistically significant from each other. In such cases, ranking models by the closeness of the information-theory based parameters in simulated and measured streamflow time series can provide an additional criterion for the evaluation of hydrologic model performance.

Integrated water system simulation by considering hydrological and biogeochemical processes: model development, with parameter sensitivity and autocalibration

NASA Astrophysics Data System (ADS)

Zhang, Y. Y.; Shao, Q. X.; Ye, A. Z.; Xing, H. T.; Xia, J.

2016-02-01

Integrated water system modeling is a feasible approach to understanding severe water crises in the world and promoting the implementation of integrated river basin management. In this study, a classic hydrological model (the time variant gain model: TVGM) was extended to an integrated water system model by coupling multiple water-related processes in hydrology, biogeochemistry, water quality, and ecology, and considering the interference of human activities. A parameter analysis tool, which included sensitivity analysis, autocalibration and model performance evaluation, was developed to improve modeling efficiency. To demonstrate the model performances, the Shaying River catchment, which is the largest highly regulated and heavily polluted tributary of the Huai River basin in China, was selected as the case study area. The model performances were evaluated on the key water-related components including runoff, water quality, diffuse pollution load (or nonpoint sources) and crop yield. Results showed that our proposed model simulated most components reasonably well. The simulated daily runoff at most regulated and less-regulated stations matched well with the observations. The average correlation coefficient and Nash-Sutcliffe efficiency were 0.85 and 0.70, respectively. Both the simulated low and high flows at most stations were improved when the dam regulation was considered. The daily ammonium-nitrogen (NH4-N) concentration was also well captured with the average correlation coefficient of 0.67. Furthermore, the diffuse source load of NH4-N and the corn yield were reasonably simulated at the administrative region scale. This integrated water system model is expected to improve the simulation performances with extension to more model functionalities, and to provide a scientific basis for the implementation in integrated river basin managements.

Green-Ampt approximations: A comprehensive analysis

NASA Astrophysics Data System (ADS)

Ali, Shakir; Islam, Adlul; Mishra, P. K.; Sikka, Alok K.

2016-04-01

Green-Ampt (GA) model and its modifications are widely used for simulating infiltration process. Several explicit approximate solutions to the implicit GA model have been developed with varying degree of accuracy. In this study, performance of nine explicit approximations to the GA model is compared with the implicit GA model using the published data for broad range of soil classes and infiltration time. The explicit GA models considered are Li et al. (1976) (LI), Stone et al. (1994) (ST), Salvucci and Entekhabi (1994) (SE), Parlange et al. (2002) (PA), Barry et al. (2005) (BA), Swamee et al. (2012) (SW), Ali et al. (2013) (AL), Almedeij and Esen (2014) (AE), and Vatankhah (2015) (VA). Six statistical indicators (e.g., percent relative error, maximum absolute percent relative error, average absolute percent relative errors, percent bias, index of agreement, and Nash-Sutcliffe efficiency) and relative computer computation time are used for assessing the model performance. Models are ranked based on the overall performance index (OPI). The BA model is found to be the most accurate followed by the PA and VA models for variety of soil classes and infiltration periods. The AE, SW, SE, and LI model also performed comparatively better. Based on the overall performance index, the explicit models are ranked as BA > PA > VA > LI > AE > SE > SW > ST > AL. Results of this study will be helpful in selection of accurate and simple explicit approximate GA models for solving variety of hydrological problems.

Ensemble forecasting of short-term system scale irrigation demands using real-time flow data and numerical weather predictions

NASA Astrophysics Data System (ADS)

Perera, Kushan C.; Western, Andrew W.; Robertson, David E.; George, Biju; Nawarathna, Bandara

2016-06-01

Irrigation demands fluctuate in response to weather variations and a range of irrigation management decisions, which creates challenges for water supply system operators. This paper develops a method for real-time ensemble forecasting of irrigation demand and applies it to irrigation command areas of various sizes for lead times of 1 to 5 days. The ensemble forecasts are based on a deterministic time series model coupled with ensemble representations of the various inputs to that model. Forecast inputs include past flow, precipitation, and potential evapotranspiration. These inputs are variously derived from flow observations from a modernized irrigation delivery system; short-term weather forecasts derived from numerical weather prediction models and observed weather data available from automatic weather stations. The predictive performance for the ensemble spread of irrigation demand was quantified using rank histograms, the mean continuous rank probability score (CRPS), the mean CRPS reliability and the temporal mean of the ensemble root mean squared error (MRMSE). The mean forecast was evaluated using root mean squared error (RMSE), Nash-Sutcliffe model efficiency (NSE) and bias. The NSE values for evaluation periods ranged between 0.96 (1 day lead time, whole study area) and 0.42 (5 days lead time, smallest command area). Rank histograms and comparison of MRMSE, mean CRPS, mean CRPS reliability and RMSE indicated that the ensemble spread is generally a reliable representation of the forecast uncertainty for short lead times but underestimates the uncertainty for long lead times.

Data for Figures in Rainfall-induced release of microbes from manure: model development, parameter estimation, and uncertainty evaluation on small plots

EPA Pesticide Factsheets

? Figure 1. Ratio of cumulative released cells to cells initially present in the manure at Week 0 as they vary by time, manure type and age, microbe, and Event (i.e., season). The 95% confidence intervals of the observed median number of cells in microbial runoff are shown as the shaded area.? Figure 2. Typical observed and simulated cumulative microbial runoff for Plots A403 and C209 with individual plot calibration.? Figure 3. Observed versus simulated microbial runoff associated with the Approach 1, adjusted for cumulative results by manure type and Event. Results accounted for counts associated with field monitoring time intervals described in Section 2.1 Field method. NS=Nash-Sutcliffe modeling efficiency, EC=E. coli, En=enterococci, FC= fecal coliforms.? Figure 4. Ratio of cumulative released cells/mass to cells/mass initially present in the aged manure by time and component (e.g., microbe) for solid manure (a) and (b), and amended, dry litter, and slurry manure (c). Solid lines (Equation (11) correspond to values in Table 3 for solid manure, and dry litter and slurry manure, respectively: (a) uses individual b values, and (b) and (c) use the combined values for b. Bounds of first and third quartiles associated with the present study??s results for cattle. Bounds of first and third quartiles associated with the present study??s results for poultry and swine. The full color versions of all figures are available in the online version of this paper, at ht

Performance of complex snow cover descriptions in a distributed hydrological model system: A case study for the high Alpine terrain of the Berchtesgaden Alps.

PubMed

Warscher, M; Strasser, U; Kraller, G; Marke, T; Franz, H; Kunstmann, H

2013-05-01

[1] Runoff generation in Alpine regions is typically affected by snow processes. Snow accumulation, storage, redistribution, and ablation control the availability of water. In this study, several robust parameterizations describing snow processes in Alpine environments were implemented in a fully distributed, physically based hydrological model. Snow cover development is simulated using different methods from a simple temperature index approach, followed by an energy balance scheme, to additionally accounting for gravitational and wind-driven lateral snow redistribution. Test site for the study is the Berchtesgaden National Park (Bavarian Alps, Germany) which is characterized by extreme topography and climate conditions. The performance of the model system in reproducing snow cover dynamics and resulting discharge generation is analyzed and validated via measurements of snow water equivalent and snow depth, satellite-based remote sensing data, and runoff gauge data. Model efficiency (the Nash-Sutcliffe coefficient) for simulated runoff increases from 0.57 to 0.68 in a high Alpine headwater catchment and from 0.62 to 0.64 in total with increasing snow model complexity. In particular, the results show that the introduction of the energy balance scheme reproduces daily fluctuations in the snowmelt rates that trace down to the channel stream. These daily cycles measured in snowmelt and resulting runoff rates could not be reproduced by using the temperature index approach. In addition, accounting for lateral snow transport changes the seasonal distribution of modeled snowmelt amounts, which leads to a higher accuracy in modeling runoff characteristics.

Quantifying shallow subsurface water and heat dynamics using coupled hydrological-thermal-geophysical inversion

DOE PAGES

Tran, Anh Phuong; Dafflon, Baptiste; Hubbard, Susan S.; ...

2016-04-25

Improving our ability to estimate the parameters that control water and heat fluxes in the shallow subsurface is particularly important due to their strong control on recharge, evaporation and biogeochemical processes. The objectives of this study are to develop and test a new inversion scheme to simultaneously estimate subsurface hydrological, thermal and petrophysical parameters using hydrological, thermal and electrical resistivity tomography (ERT) data. The inversion scheme-which is based on a nonisothermal, multiphase hydrological model-provides the desired subsurface property estimates in high spatiotemporal resolution. A particularly novel aspect of the inversion scheme is the explicit incorporation of the dependence of themore » subsurface electrical resistivity on both moisture and temperature. The scheme was applied to synthetic case studies, as well as to real datasets that were autonomously collected at a biogeochemical field study site in Rifle, Colorado. At the Rifle site, the coupled hydrological-thermal-geophysical inversion approach well predicted the matric potential, temperature and apparent resistivity with the Nash-Sutcliffe efficiency criterion greater than 0.92. Synthetic studies found that neglecting the subsurface temperature variability, and its effect on the electrical resistivity in the hydrogeophysical inversion, may lead to an incorrect estimation of the hydrological parameters. The approach is expected to be especially useful for the increasing number of studies that are taking advantage of autonomously collected ERT and soil measurements to explore complex terrestrial system dynamics.« less

Modelling sheet erosion on steep slopes in the loess region of China

NASA Astrophysics Data System (ADS)

Wu, Bing; Wang, Zhanli; Zhang, Qingwei; Shen, Nan; Liu, June

2017-10-01

The relationship of sheet erosion rate (SE), slope gradient (S) and rainfall intensity (I), and hydraulic parameters, such as flow velocity (V), shear stress (τ), stream power (Ω) and unit stream power (P), was investigated to derive an accurate experimental model. The experiment was conducted at slopes of 12.23%, 17.63%, 26.8%, 36.4%, 40.4% and 46.63% under I of 48, 60, 90, 120, 138 and 150 mm h-1, respectively, using simulated rainfall. Results showed that sheet erosion rate increased as a power function with rainfall intensity and slope gradient with R2 = 0.95 and Nash-Sutcliffe model efficiency (NSE) = 0.87. Sheet erosion rate was more sensitive to rainfall intensity than to slope gradient. It increased as a power function with flow velocity, which was satisfactory for predicting sheet erosion rate with R2 = 0.95 and NSE = 0.81. Shear stress and stream power could be used to predict sheet erosion rate accurately with a linear function equation. Stream power (R2 = 0.97, NSE = 0.97) was a better predictor of sheet erosion rather than shear stress (R2 = 0.90, NSE = 0.89). However, a prediction based on unit stream power was poor. The new equation (i.e. SE = 7.5 ×1012S1.43I3.04 and SE = 0.06 Ω - 0.0003 and SE = 0.011 τ - 0.01) would improve water erosion estimation on loess hillslopes of China.

Examining dynamic interactions among experimental factors influencing hydrologic data assimilation with the ensemble Kalman filter

NASA Astrophysics Data System (ADS)

Wang, S.; Huang, G. H.; Baetz, B. W.; Cai, X. M.; Ancell, B. C.; Fan, Y. R.

2017-11-01

The ensemble Kalman filter (EnKF) is recognized as a powerful data assimilation technique that generates an ensemble of model variables through stochastic perturbations of forcing data and observations. However, relatively little guidance exists with regard to the proper specification of the magnitude of the perturbation and the ensemble size, posing a significant challenge in optimally implementing the EnKF. This paper presents a robust data assimilation system (RDAS), in which a multi-factorial design of the EnKF experiments is first proposed for hydrologic ensemble predictions. A multi-way analysis of variance is then used to examine potential interactions among factors affecting the EnKF experiments, achieving optimality of the RDAS with maximized performance of hydrologic predictions. The RDAS is applied to the Xiangxi River watershed which is the most representative watershed in China's Three Gorges Reservoir region to demonstrate its validity and applicability. Results reveal that the pairwise interaction between perturbed precipitation and streamflow observations has the most significant impact on the performance of the EnKF system, and their interactions vary dynamically across different settings of the ensemble size and the evapotranspiration perturbation. In addition, the interactions among experimental factors vary greatly in magnitude and direction depending on different statistical metrics for model evaluation including the Nash-Sutcliffe efficiency and the Box-Cox transformed root-mean-square error. It is thus necessary to test various evaluation metrics in order to enhance the robustness of hydrologic prediction systems.

Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin

USGS Publications Warehouse

Shrestha, M.S.; Artan, G.A.; Bajracharya, S.R.; Gautam, D.K.; Tokar, S.A.

2011-01-01

In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32000km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC-RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC-RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC-RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction. ?? 2011 The Authors. Journal of Flood Risk Management ?? 2011 The Chartered Institution of Water and Environmental Management.

Hydrograph matching method for measuring model performance

NASA Astrophysics Data System (ADS)

Ewen, John

2011-09-01

SummaryDespite all the progress made over the years on developing automatic methods for analysing hydrographs and measuring the performance of rainfall-runoff models, automatic methods cannot yet match the power and flexibility of the human eye and brain. Very simple approaches are therefore being developed that mimic the way hydrologists inspect and interpret hydrographs, including the way that patterns are recognised, links are made by eye, and hydrological responses and errors are studied and remembered. In this paper, a dynamic programming algorithm originally designed for use in data mining is customised for use with hydrographs. It generates sets of "rays" that are analogous to the visual links made by the hydrologist's eye when linking features or times in one hydrograph to the corresponding features or times in another hydrograph. One outcome from this work is a new family of performance measures called "visual" performance measures. These can measure differences in amplitude and timing, including the timing errors between simulated and observed hydrographs in model calibration. To demonstrate this, two visual performance measures, one based on the Nash-Sutcliffe Efficiency and the other on the mean absolute error, are used in a total of 34 split-sample calibration-validation tests for two rainfall-runoff models applied to the Hodder catchment, northwest England. The customised algorithm, called the Hydrograph Matching Algorithm, is very simple to apply; it is given in a few lines of pseudocode.

Quantifying the Uncertainty in Streamflow Predictions Using Swat for Brazos-Colorado Coastal Watershed, Texas

NASA Astrophysics Data System (ADS)

Mandal, D.; Bhatia, N.; Srivastav, R. K.

2016-12-01

Soil Water Assessment Tool (SWAT) is one of the most comprehensive hydrologic models to simulate streamflow for a watershed. The two major inputs for a SWAT model are: (i) Digital Elevation Models (DEM), and (ii) Land Use and Land Cover Maps (LULC). This study aims to quantify the uncertainty in streamflow predictions using SWAT for San Bernard River in Brazos-Colorado coastal watershed, Texas, by incorporating the respective datasets from different sources: (i) DEM data will be obtained from ASTER GDEM V2, GMTED2010, NHD DEM, and SRTM DEM datasets with ranging resolution from 1/3 arc-second to 30 arc-second, and (ii) LULC data will be obtained from GLCC V2, MRLC NLCD2011, NOAA's C-CAP, USGS GAP, and TCEQ databases. Weather variables (Precipitation and Max-Min Temperature at daily scale) will be obtained from National Climatic Data Centre (NCDC) and SWAT in-built STASGO tool will be used to obtain the soil maps. The SWAT model will be calibrated using SWAT-CUP SUFI-2 approach and its performance will be evaluated using the statistical indices of Nash-Sutcliffe efficiency (NSE), ratio of Root-Mean-Square-Error to standard deviation of observed streamflow (RSR), and Percent-Bias Error (PBIAS). The study will help understand the performance of SWAT model with varying data sources and eventually aid the regional state water boards in planning, designing, and managing hydrologic systems.

Regional prediction of basin-scale brown trout habitat suitability

NASA Astrophysics Data System (ADS)

Ceola, S.; Pugliese, A.

2014-09-01

In this study we propose a novel method for the estimation of ecological indices describing the habitat suitability of brown trout (Salmo trutta). Traditional hydrological tools are coupled with an innovative regional geostatistical technique, aiming at the prediction of the brown trout habitat suitability index where partial or totally ungauged conditions occur. Several methods for the assessment of ecological indices are already proposed in the scientific literature, but the possibility of exploiting a geostatistical prediction model, such as Topological Kriging, has never been investigated before. In order to develop a regional habitat suitability model we use the habitat suitability curve, obtained from measured data of brown trout adult individuals collected in several river basins across the USA. The Top-kriging prediction model is then employed to assess the spatial correlation between upstream and downstream habitat suitability indices. The study area is the Metauro River basin, located in the central part of Italy (Marche region), for which both water depth and streamflow data were collected. The present analysis focuses on discharge values corresponding to the 0.1-, 0.5-, 0.9-empirical quantiles derived from flow-duration curves available for seven gauging stations located within the study area, for which three different suitability indices (i.e. ψ10, ψ50 and ψ90) are evaluated. The results of this preliminary analysis are encouraging showing Nash-Sutcliffe efficiencies equal to 0.52, 0.65, and 0.69, respectively.

Development and comparison in uncertainty assessment based Bayesian modularization method in hydrological modeling

NASA Astrophysics Data System (ADS)

Li, Lu; Xu, Chong-Yu; Engeland, Kolbjørn

2013-04-01

SummaryWith respect to model calibration, parameter estimation and analysis of uncertainty sources, various regression and probabilistic approaches are used in hydrological modeling. A family of Bayesian methods, which incorporates different sources of information into a single analysis through Bayes' theorem, is widely used for uncertainty assessment. However, none of these approaches can well treat the impact of high flows in hydrological modeling. This study proposes a Bayesian modularization uncertainty assessment approach in which the highest streamflow observations are treated as suspect information that should not influence the inference of the main bulk of the model parameters. This study includes a comprehensive comparison and evaluation of uncertainty assessments by our new Bayesian modularization method and standard Bayesian methods using the Metropolis-Hastings (MH) algorithm with the daily hydrological model WASMOD. Three likelihood functions were used in combination with standard Bayesian method: the AR(1) plus Normal model independent of time (Model 1), the AR(1) plus Normal model dependent on time (Model 2) and the AR(1) plus Multi-normal model (Model 3). The results reveal that the Bayesian modularization method provides the most accurate streamflow estimates measured by the Nash-Sutcliffe efficiency and provide the best in uncertainty estimates for low, medium and entire flows compared to standard Bayesian methods. The study thus provides a new approach for reducing the impact of high flows on the discharge uncertainty assessment of hydrological models via Bayesian method.

Assessing the relative importance of parameter and forcing uncertainty and their interactions in conceptual hydrological model simulations

NASA Astrophysics Data System (ADS)

Mockler, E. M.; Chun, K. P.; Sapriza-Azuri, G.; Bruen, M.; Wheater, H. S.

2016-11-01

Predictions of river flow dynamics provide vital information for many aspects of water management including water resource planning, climate adaptation, and flood and drought assessments. Many of the subjective choices that modellers make including model and criteria selection can have a significant impact on the magnitude and distribution of the output uncertainty. Hydrological modellers are tasked with understanding and minimising the uncertainty surrounding streamflow predictions before communicating the overall uncertainty to decision makers. Parameter uncertainty in conceptual rainfall-runoff models has been widely investigated, and model structural uncertainty and forcing data have been receiving increasing attention. This study aimed to assess uncertainties in streamflow predictions due to forcing data and the identification of behavioural parameter sets in 31 Irish catchments. By combining stochastic rainfall ensembles and multiple parameter sets for three conceptual rainfall-runoff models, an analysis of variance model was used to decompose the total uncertainty in streamflow simulations into contributions from (i) forcing data, (ii) identification of model parameters and (iii) interactions between the two. The analysis illustrates that, for our subjective choices, hydrological model selection had a greater contribution to overall uncertainty, while performance criteria selection influenced the relative intra-annual uncertainties in streamflow predictions. Uncertainties in streamflow predictions due to the method of determining parameters were relatively lower for wetter catchments, and more evenly distributed throughout the year when the Nash-Sutcliffe Efficiency of logarithmic values of flow (lnNSE) was the evaluation criterion.

Accessing the capability of TRMM 3B42 V7 to simulate streamflow during extreme rain events: Case study for a Himalayan River Basin

NASA Astrophysics Data System (ADS)

Kumar, Brijesh; Lakshmi, Venkat

2018-03-01

The paper examines the quality of Tropical Rainfall Monitoring Mission (TRMM) 3B42 V7 precipitation product to simulate the streamflow using Soil Water Assessment Tool (SWAT) model for various rainfall intensities over the Himalayan region. The SWAT model has been set up for Gandak River Basin with 41 sub-basins and 420 HRUs. Five stream gauge locations are used to simulate the streamflow for a time span of 10 years (2000-2010). Daily streamflow for the simulation period is collected from Central Water Commission (CWC), India and Department of Hydrology and Meteorology (DHM), Nepal. The simulation results are found good in terms of Nash-Sutcliffe efficiency (NSE) {>}0.65, coefficient of determination (R2) {>}0.67 and Percentage Bias (PBIAS){<}15%, at each stream gauge sites. Thereafter, we have calculated the PBIAS and RMSE-observations standard deviation ratio (RSR) statistics between TRMM simulated and observed streamflow for various rainfall intensity classes, viz., light ({<}7.5 mm/d), moderate (7.5 to 35.4 mm/d), heavy (35.5 to 124.4 mm/d) and extremely heavy ({>}124.4 mm/d). The PBIAS and RSR show that TRMM simulated streamflow is suitable for moderate to heavy rainfall intensities. However, it does not perform well for light- and extremely-heavy rainfall intensities. The finding of the present work is useful for the problems related to water resources management, irrigation planning and hazard analysis over the Himalayan regions.

Implementation and evaluation of a monthly water balance model over the US on an 800 m grid

USGS Publications Warehouse

Hostetler, Steven W.; Alder, Jay R.

2016-01-01

We simulate the 1950–2010 water balance for the conterminous U.S. (CONUS) with a monthly water balance model (MWBM) using the 800 m Parameter-elevation Regression on Independent Slopes Model (PRISM) data set as model input. We employed observed snow and streamflow data sets to guide modification of the snow and potential evapotranspiration components in the default model and to evaluate model performance. Based on various metrics and sensitivity tests, the modified model yields reasonably good simulations of seasonal snowpack in the West (range of bias of ±50 mm at 68% of 713 SNOTEL sites), the gradients and magnitudes of actual evapotranspiration, and runoff (median correlation of 0.83 and median Nash-Sutcliff efficiency of 0.6 between simulated and observed annual time series at 1427 USGS gage sites). The model generally performs well along the Pacific Coast, the high elevations of the Basin and Range and over the Midwest and East, but not as well over the dry areas of the Southwest and upper Plains regions due, in part, to the apportioning of direct versus delayed runoff. Sensitivity testing and application of the MWBM to simulate the future water balance at four National Parks when driven by 30 climate models from the Climate Model Intercomparison Program Phase 5 (CMIP5) demonstrate that the model is useful for evaluating first-order, climate driven hydrologic change on monthly and annual time scales.

Comparison between satellite precipitation product and observation rain gauges in the Red-Thai Binh River Basin

NASA Astrophysics Data System (ADS)

Lakshmi, V.; Le, M. H.; Sutton, J. R. P.; Bui, D. D.; Bolten, J. D.

2017-12-01

The Red-ThaiBinh River is the second largest river in Vietnam in terms of economic impact and is home to around 29 million people. The river has been facing challenges for water resources allocation, which require reliable and routine hydrological assessments. However, hydrological analysis is difficult due to insufficient spatial coverage by rain gauges. Satellite-based precipitation estimates are a promising alternative with high-resolution in both time and space. This study aims at investigating the uncertainties in satellite-based precipitation product TRMM 3B42 v7.0 by comparing them against in-situ measurements over the Red-ThaiBinh River basin. The TRMM 3B42 v7.0 are assessed in terms of seasonal, monthly and daily variations over a 17-year period (1998 - 2014). Preliminary results indicate that at a daily scale, except for low Mean Bias Error (MBE), satellite based rainfall product has weak relationship with ground observation data, indicating by average performance of 0.326 and -0.485 for correlation coefficient and Nash Sutcliffe Efficiency (NSE), respectively. At monthly scale, we observe that the TRMM 3B42 v7.0 has higher correlation with the correlation increased significantly to 0.863 and NSE of 0.522. By analyzing wet season (May - October) and dry season (November - April) separately we find that the correlation between the TRMM 3B42 v7.0 with ground observations were higher for wet season than the dry season.

TOPMODEL simulations of streamflow and depth to water table in Fishing Brook Watershed, New York, 2007-09

USGS Publications Warehouse

Nystrom, Elizabeth A.; Burns, Douglas A.

2011-01-01

TOPMODEL uses a topographic wetness index computed from surface-elevation data to simulate streamflow and subsurface-saturation state, represented by the saturation deficit. Depth to water table was computed from simulated saturation-deficit values using computed soil properties. In the Fishing Brook Watershed, TOPMODEL was calibrated to the natural logarithm of streamflow at the study area outlet and depth to water table at Sixmile Wetland using a combined multiple-objective function. Runoff and depth to water table responded differently to some of the model parameters, and the combined multiple-objective function balanced the goodness-of-fit of the model realizations with respect to these parameters. Results show that TOPMODEL reasonably simulated runoff and depth to water table during the study period. The simulated runoff had a Nash-Sutcliffe efficiency of 0.738, but the model underpredicted total runoff by 14 percent. Depth to water table computed from simulated saturation-deficit values matched observed water-table depth moderately well; the root mean squared error of absolute depth to water table was 91 millimeters (mm), compared to the mean observed depth to water table of 205 mm. The correlation coefficient for temporal depth-to-water-table fluctuations was 0.624. The variability of the TOPMODEL simulations was assessed using prediction intervals grouped using the combined multiple-objective function. The calibrated TOPMODEL results for the entire study area were applied to several subwatersheds within the study area using computed hydrogeomorphic properties of the subwatersheds.

Computationally inexpensive identification of noninformative model parameters by sequential screening

NASA Astrophysics Data System (ADS)

Cuntz, Matthias; Mai, Juliane; Zink, Matthias; Thober, Stephan; Kumar, Rohini; Schäfer, David; Schrön, Martin; Craven, John; Rakovec, Oldrich; Spieler, Diana; Prykhodko, Vladyslav; Dalmasso, Giovanni; Musuuza, Jude; Langenberg, Ben; Attinger, Sabine; Samaniego, Luis

2015-08-01

Environmental models tend to require increasing computational time and resources as physical process descriptions are improved or new descriptions are incorporated. Many-query applications such as sensitivity analysis or model calibration usually require a large number of model evaluations leading to high computational demand. This often limits the feasibility of rigorous analyses. Here we present a fully automated sequential screening method that selects only informative parameters for a given model output. The method requires a number of model evaluations that is approximately 10 times the number of model parameters. It was tested using the mesoscale hydrologic model mHM in three hydrologically unique European river catchments. It identified around 20 informative parameters out of 52, with different informative parameters in each catchment. The screening method was evaluated with subsequent analyses using all 52 as well as only the informative parameters. Subsequent Sobol's global sensitivity analysis led to almost identical results yet required 40% fewer model evaluations after screening. mHM was calibrated with all and with only informative parameters in the three catchments. Model performances for daily discharge were equally high in both cases with Nash-Sutcliffe efficiencies above 0.82. Calibration using only the informative parameters needed just one third of the number of model evaluations. The universality of the sequential screening method was demonstrated using several general test functions from the literature. We therefore recommend the use of the computationally inexpensive sequential screening method prior to rigorous analyses on complex environmental models.

Computationally inexpensive identification of noninformative model parameters by sequential screening

NASA Astrophysics Data System (ADS)

Mai, Juliane; Cuntz, Matthias; Zink, Matthias; Thober, Stephan; Kumar, Rohini; Schäfer, David; Schrön, Martin; Craven, John; Rakovec, Oldrich; Spieler, Diana; Prykhodko, Vladyslav; Dalmasso, Giovanni; Musuuza, Jude; Langenberg, Ben; Attinger, Sabine; Samaniego, Luis

2016-04-01

Environmental models tend to require increasing computational time and resources as physical process descriptions are improved or new descriptions are incorporated. Many-query applications such as sensitivity analysis or model calibration usually require a large number of model evaluations leading to high computational demand. This often limits the feasibility of rigorous analyses. Here we present a fully automated sequential screening method that selects only informative parameters for a given model output. The method requires a number of model evaluations that is approximately 10 times the number of model parameters. It was tested using the mesoscale hydrologic model mHM in three hydrologically unique European river catchments. It identified around 20 informative parameters out of 52, with different informative parameters in each catchment. The screening method was evaluated with subsequent analyses using all 52 as well as only the informative parameters. Subsequent Sobol's global sensitivity analysis led to almost identical results yet required 40% fewer model evaluations after screening. mHM was calibrated with all and with only informative parameters in the three catchments. Model performances for daily discharge were equally high in both cases with Nash-Sutcliffe efficiencies above 0.82. Calibration using only the informative parameters needed just one third of the number of model evaluations. The universality of the sequential screening method was demonstrated using several general test functions from the literature. We therefore recommend the use of the computationally inexpensive sequential screening method prior to rigorous analyses on complex environmental models.

Predicting hydrologic function with the streamwater mircobiome

NASA Astrophysics Data System (ADS)

Good, S. P.; URycki, D. R.; Crump, B. C.

2017-12-01

Recent advances in microbiology allow for rapid and cost-effective determination of the presence of a nearly limitless number of bacterial (and other) species within a water sample. Here, we posit that the quasi-unique taxonomic composition of the aquatic microbiome is an emergent property of a catchment that contains information about hydrologic function at multiple temporal and spatial scales, and term this approach `genohydrolgy.' As first a genohydrology case study, we show that the relative abundance of bacterial species within different operational taxonomic units (OTUs) from six large arctic rivers can be used to predict river discharge at monthly and longer timescales. Using only OTU abundance information and a machine-learning algorithm trained on OTU and discharge data from the other five rivers, our genohydrology approach is able to predict mean monthly discharge values throughout the year with an average Nash-Sutcliffe efficiency (NSE) of 0.50, while the recurrence interval of extreme flows at longer times scales in these rivers was predicted with an NSE of 0.04. This approach demonstrates considerable improvement over prediction of these quantities in each river based only on discharge data from the other five (our null hypothesis), which had average NSE values of -1.19 and -5.50 for the seasonal and recurrence interval discharge values, respectively. Overall the genohydrology approach demonstrates that bacterial diversity within the aquatic microbiome is a large and underutilized data resource with benefits for prediction of hydrologic function.

Modelling runoff on ceramic tile roofs using the kinematic wave equations

NASA Astrophysics Data System (ADS)

Silveira, Alexandre; Abrantes, João; de Lima, João; Lira, Lincoln

2016-04-01

Rainwater harvesting is a water saving alternative strategy that presents many advantages and can provide solutions to address major water resources problems, such as fresh water scarcity, urban stream degradation and flooding. In recent years, these problems have become global challenges, due to climatic change, population growth and increasing urbanisation. Generally, roofs are the first to come into contact with rainwater; thus, they are the best candidates for rainwater harvesting. In this context, the correct evaluation of roof runoff quantity and quality is essential to effectively design rainwater harvesting systems. Despite this, many studies usually focus on the qualitative aspects in detriment of the quantitative aspects. Laboratory studies using rainfall simulators have been widely used to investigate rainfall-runoff processes. These studies enabled a detailed exploration and systematic replication of a large range of hydrologic conditions, such as rainfall spatial and temporal characteristics, providing for a fast way to obtain precise and consistent data that can be used to calibrate and validate numerical models. This study aims to evaluate the performance of a kinematic wave based numerical model in simulating runoff on sloping roofs, by comparing the numerical results with the ones obtained from laboratory rainfall simulations on a real-scale ceramic tile roof (Lusa tiles). For all studied slopes, simulated discharge hydrographs had a good adjust to observed ones. Coefficient of determination and Nash-Sutcliffe efficiency values were close to 1.0. Particularly, peak discharges, times to peak and peak durations were very well simulated.

Modelling the effect of fire frequency on runoff and erosion in north-central Portugal using the revised Morgan-Morgan-Finney

NASA Astrophysics Data System (ADS)

Hosseini, Mohammadreza; Nunes, João Pedro; González Pelayo, Oscar; Keizer, Jan Jacob; Ritsema, Coen; Geissen, Violette

2017-04-01

Models can be valuable for foreseeing the hydrological effects of fires and to plan and execute post-fire management alternatives. In this study, the revised Morgan-Morgan-Finney (MMF) model was utilized to simulate runoff and soil erosion in recently burned maritime pine plantations with different fire regimes, in a wet Mediterranean area of north-central Portugal. The MMF model was adjusted for burned zones in order to accommodate seasonal patterns in runoff and soil erosion, attributed to changes in soil water repellency and vegetation recovery. The model was then assessed by applying it for a sum of 18 experimental micro-plots (0.25 m2) at 9 1x-burnt and 9 4x-burnt slopes, using both literature-based and calibrated parameters, with the collected data used to assess the robustness of each parameterization. The estimate of erosion was more exact than that of runoff, with a general Nash-Sutcliffe efficiency of 0.54. Slope angle and the soil's effective hydrological depth (which relies on upon vegetation and additionally crop cover) were found to be the primary parameters enhancing model results, and different hydrological depths were expected to separate between the two differentiating fire regimes. This relative analysis demonstrated that most existing benchmark parameters can be utilized to apply MMF in burnt pine regions with moderate severity to support post-fire management; however it also showed that further endeavours ought to concentrate on mapping soil depth and vegetation cover to enhance these simulations.

Comparison of Precipitation from Gauge and Tropical Rainfall Measurement Mission (TRMM) for River Basins of India

NASA Astrophysics Data System (ADS)

Mondal, A.; Chandniha, S. K.; Lakshmi, V.; Kundu, S.; Hashemi, H.

2017-12-01

This study compares the monthly precipitation from the gridded rain gauge data collected by India Meteorological Department (IMD) and the retrievals from the Tropical Rainfall Measurement Mission (TRMM) for the river basins of India using the TRMM Multisatellite Precipitation Analysis (TMPA) version 7 (V7). The IMD and TMPA datasets have the same spatial resolution (0.25°×0.25°) and extend from 1998 to 2013. The TRMM data accuracy for the river basins is assessed by comparison with IMD using root mean square error (RMSE), normalized mean square error (NMSE), Nash-Sutcliffe coefficient (NASH) and correlation coefficient (CC) methods. The Mann-Kendall (MK) and modified Mann-Kendall (MMK) tests have been applied for analyzing the data trend, and the change has been detected by Sen's Slope using both data sets for annual and seasonal time periods. The change in intensity of precipitation is estimated by percentage for comparing actual differences in various river basins. Variation in precipitation is high (>100 mm represents >15% of average annual precipitation) in Brahmaputra, rivers draining into Myanmar (RDM), rivers draining into Bangladesh (RDB), east flowing rivers between Mahanadi and Godavari (EMG), east flowing rivers between Pennar and Cauvery (EPC), Cauvery and Tapi. The NASH and CC values vary between 0.80 to 0.98 and 0.87 to 0.99 in all river basins except area of north Ladakh not draining into Indus (NLI) and east flowing rivers south of Cauvery (ESC), while RMSE and NMSE vary from 15.95 to 101.68 mm and 2.66 to 58.38 mm, respectively. The trends for TMPA and IMD datasets from 1998 to 2013 are quite similar in MK (except 4 river basins) and MMK (except 3 river basins). The estimated results imply that the TMPA precipitation show good agreement and can be used in climate studies and hydrological simulations in locations/river basins where the number of rain gauge stations is not adequate to quantify the spatial variability of precipitation. Keywords

Confidence intervals in Flow Forecasting by using artificial neural networks

NASA Astrophysics Data System (ADS)

Panagoulia, Dionysia; Tsekouras, George

2014-05-01

variable of different ANN structures [3]. The performance of each ANN structure is evaluated by the voting analysis based on eleven criteria, which are the root mean square error (RMSE), the correlation index (R), the mean absolute percentage error (MAPE), the mean percentage error (MPE), the mean percentage error (ME), the percentage volume in errors (VE), the percentage error in peak (MF), the normalized mean bias error (NMBE), the normalized root mean bias error (NRMSE), the Nash-Sutcliffe model efficiency coefficient (E) and the modified Nash-Sutcliffe model efficiency coefficient (E1). The next day flow for the test set is calculated using the best ANN structure's model. Consequently, the confidence intervals of various confidence levels for training, evaluation and test sets are compared in order to explore the generalisation dynamics of confidence intervals from training and evaluation sets. [1] H.S. Hippert, C.E. Pedreira, R.C. Souza, "Neural networks for short-term load forecasting: A review and evaluation," IEEE Trans. on Power Systems, vol. 16, no. 1, 2001, pp. 44-55. [2] G. J. Tsekouras, N.E. Mastorakis, F.D. Kanellos, V.T. Kontargyri, C.D. Tsirekis, I.S. Karanasiou, Ch.N. Elias, A.D. Salis, P.A. Kontaxis, A.A. Gialketsi: "Short term load forecasting in Greek interconnected power system using ANN: Confidence Interval using a novel re-sampling technique with corrective Factor", WSEAS International Conference on Circuits, Systems, Electronics, Control & Signal Processing, (CSECS '10), Vouliagmeni, Athens, Greece, December 29-31, 2010. [3] D. Panagoulia, I. Trichakis, G. J. Tsekouras: "Flow Forecasting via Artificial Neural Networks - A Study for Input Variables conditioned on atmospheric circulation", European Geosciences Union, General Assembly 2012 (NH1.1 / AS1.16 - Extreme meteorological and hydrological events induced by severe weather and climate change), Vienna, Austria, 22-27 April 2012.

University of California, Davis | Division of Cancer Prevention

Cancer.gov

Member Information Dr. Julie L. Sutcliffe Laboratory websiteshttps://bme.ucdavis.edu/sutcliffe/ http://www.ucdmc.ucdavis.edu/publish/providerbio/search/21751 https://bme.ucdavis.edu/people/departmental-faculty/julie-sutcliffe/ |

Evolution of wealth in a non-conservative economy driven by local Nash equilibria.

PubMed

Degond, Pierre; Liu, Jian-Guo; Ringhofer, Christian

2014-11-13

We develop a model for the evolution of wealth in a non-conservative economic environment, extending a theory developed in Degond et al. (2014 J. Stat. Phys. 154, 751-780 (doi:10.1007/s10955-013-0888-4)). The model considers a system of rational agents interacting in a game-theoretical framework. This evolution drives the dynamics of the agents in both wealth and economic configuration variables. The cost function is chosen to represent a risk-averse strategy of each agent. That is, the agent is more likely to interact with the market, the more predictable the market, and therefore the smaller its individual risk. This yields a kinetic equation for an effective single particle agent density with a Nash equilibrium serving as the local thermodynamic equilibrium. We consider a regime of scale separation where the large-scale dynamics is given by a hydrodynamic closure with this local equilibrium. A class of generalized collision invariants is developed to overcome the difficulty of the non-conservative property in the hydrodynamic closure derivation of the large-scale dynamics for the evolution of wealth distribution. The result is a system of gas dynamics-type equations for the density and average wealth of the agents on large scales. We recover the inverse Gamma distribution, which has been previously considered in the literature, as a local equilibrium for particular choices of the cost function. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Establishment and application of the estimation model for pollutant concentrfation in agriculture drain

NASA Astrophysics Data System (ADS)

Li, Qiangkun; Hu, Yawei; Jia, Qian; Song, Changji

2018-02-01

It is the key point of quantitative research on agricultural non-point source pollution load, the estimation of pollutant concentration in agricultural drain. In the guidance of uncertainty theory, the synthesis of fertilization and irrigation is used as an impulse input to the farmland, meanwhile, the pollutant concentration in agricultural drain is looked as the response process corresponding to the impulse input. The migration and transformation of pollutant in soil is expressed by Inverse Gaussian Probability Density Function. The law of pollutants migration and transformation in soil at crop different growth periods is reflected by adjusting parameters of Inverse Gaussian Distribution. Based on above, the estimation model for pollutant concentration in agricultural drain at field scale was constructed. Taking the of Qing Tong Xia Irrigation District in Ningxia as an example, the concentration of nitrate nitrogen and total phosphorus in agricultural drain was simulated by this model. The results show that the simulated results accorded with measured data approximately and Nash-Sutcliffe coefficients were 0.972 and 0.964, respectively.

Deduction of reservoir operating rules for application in global hydrological models

NASA Astrophysics Data System (ADS)

Coerver, Hubertus M.; Rutten, Martine M.; van de Giesen, Nick C.

2018-01-01

A big challenge in constructing global hydrological models is the inclusion of anthropogenic impacts on the water cycle, such as caused by dams. Dam operators make decisions based on experience and often uncertain information. In this study information generally available to dam operators, like inflow into the reservoir and storage levels, was used to derive fuzzy rules describing the way a reservoir is operated. Using an artificial neural network capable of mimicking fuzzy logic, called the ANFIS adaptive-network-based fuzzy inference system, fuzzy rules linking inflow and storage with reservoir release were determined for 11 reservoirs in central Asia, the US and Vietnam. By varying the input variables of the neural network, different configurations of fuzzy rules were created and tested. It was found that the release from relatively large reservoirs was significantly dependent on information concerning recent storage levels, while release from smaller reservoirs was more dependent on reservoir inflows. Subsequently, the derived rules were used to simulate reservoir release with an average Nash-Sutcliffe coefficient of 0.81.

Network formation: neighborhood structures, establishment costs, and distributed learning.

PubMed

Chasparis, Georgios C; Shamma, Jeff S

2013-12-01

We consider the problem of network formation in a distributed fashion. Network formation is modeled as a strategic-form game, where agents represent nodes that form and sever unidirectional links with other nodes and derive utilities from these links. Furthermore, agents can form links only with a limited set of neighbors. Agents trade off the benefit from links, which is determined by a distance-dependent reward function, and the cost of maintaining links. When each agent acts independently, trying to maximize its own utility function, we can characterize “stable” networks through the notion of Nash equilibrium. In fact, the introduced reward and cost functions lead to Nash equilibria (networks), which exhibit several desirable properties such as connectivity, bounded-hop diameter, and efficiency (i.e., minimum number of links). Since Nash networks may not necessarily be efficient, we also explore the possibility of “shaping” the set of Nash networks through the introduction of state-based utility functions. Such utility functions may represent dynamic phenomena such as establishment costs (either positive or negative). Finally, we show how Nash networks can be the outcome of a distributed learning process. In particular, we extend previous learning processes to so-called “state-based” weakly acyclic games, and we show that the proposed network formation games belong to this class of games.

Nash points, Ky Fan inequality and equilibria of abstract economies in Max-Plus and -convexity

NASA Astrophysics Data System (ADS)

Briec, Walter; Horvath, Charles

2008-05-01

-convexity was introduced in [W. Briec, C. Horvath, -convexity, Optimization 53 (2004) 103-127]. Separation and Hahn-Banach like theorems can be found in [G. Adilov, A.M. Rubinov, -convex sets and functions, Numer. Funct. Anal. Optim. 27 (2006) 237-257] and [W. Briec, C.D. Horvath, A. Rubinov, Separation in -convexity, Pacific J. Optim. 1 (2005) 13-30]. We show here that all the basic results related to fixed point theorems are available in -convexity. Ky Fan inequality, existence of Nash equilibria and existence of equilibria for abstract economies are established in the framework of -convexity. Monotone analysis, or analysis on Maslov semimodules [V.N. Kolokoltsov, V.P. Maslov, Idempotent Analysis and Its Applications, Math. Appl., volE 401, Kluwer Academic, 1997; V.P. Litvinov, V.P. Maslov, G.B. Shpitz, Idempotent functional analysis: An algebraic approach, Math. Notes 69 (2001) 696-729; V.P. Maslov, S.N. Samborski (Eds.), Idempotent Analysis, Advances in Soviet Mathematics, Amer. Math. Soc., Providence, RI, 1992], is the natural framework for these results. From this point of view Max-Plus convexity and -convexity are isomorphic Maslov semimodules structures over isomorphic semirings. Therefore all the results of this paper hold in the context of Max-Plus convexity.

Estimation of Flow Duration Curve for Ungauged Catchments using Adaptive Neuro-Fuzzy Inference System and Map Correlation Method: A Case Study from Turkey

NASA Astrophysics Data System (ADS)

Kentel, E.; Dogulu, N.

2015-12-01

In Turkey the experience and data required for a hydrological model setup is limited and very often not available. Moreover there are many ungauged catchments where there are also many planned projects aimed at utilization of water resources including development of existing hydropower potential. This situation makes runoff prediction at locations with lack of data and ungauged locations where small hydropower plants, reservoirs, etc. are planned an increasingly significant challenge and concern in the country. Flow duration curves have many practical applications in hydrology and integrated water resources management. Estimation of flood duration curve (FDC) at ungauged locations is essential, particularly for hydropower feasibility studies and selection of the installed capacities. In this study, we test and compare the performances of two methods for estimating FDCs in the Western Black Sea catchment, Turkey: (i) FDC based on Map Correlation Method (MCM) flow estimates. MCM is a recently proposed method (Archfield and Vogel, 2010) which uses geospatial information to estimate flow. Flow measurements of stream gauging stations nearby the ungauged location are the only data requirement for this method. This fact makes MCM very attractive for flow estimation in Turkey, (ii) Adaptive Neuro-Fuzzy Inference System (ANFIS) is a data-driven method which is used to relate FDC to a number of variables representing catchment and climate characteristics. However, it`s ease of implementation makes it very useful for practical purposes. Both methods use easily collectable data and are computationally efficient. Comparison of the results is realized based on two different measures: the root mean squared error (RMSE) and the Nash-Sutcliffe Efficiency (NSE) value. Ref: Archfield, S. A., and R. M. Vogel (2010), Map correlation method: Selection of a reference streamgage to estimate daily streamflow at ungaged catchments, Water Resour. Res., 46, W10513, doi:10.1029/2009WR008481.

Application of artificial intelligence to estimate the reference evapotranspiration in sub-humid Doon valley

NASA Astrophysics Data System (ADS)

Nema, Manish K.; Khare, Deepak; Chandniha, Surendra K.

2017-11-01

Estimation of evapotranspiration (ET) is an essential component of the hydrologic cycle, which is also requisite for efficient irrigation water management planning and hydro-meteorological studies at both the basin and catchment scales. There are about twenty well-established methods available for ET estimation which depends upon various meteorological parameters and assumptions. Most of these methods are physically based and need a variety of input data. The FAO-56 Penman-Monteith method (PM) for estimating reference evapotranspiration (ET0) is recommend for irrigation scheduling worldwide, because PM generally yields the best results under various climatic conditions. This study investigates the abilities of artificial neural networks (ANN) to improve the accuracy of monthly evaporation estimation in sub-humid climatic region of Dehradun. In the first part of the study, different ANN models, comprising various combinations of training function and number of neutrons were developed to estimate the ET0 and it has been compared with the Penman-Monteith (PM) ET0 as the ideal (observed) ET0. Various statistical approaches were considered to estimate the model performance, i.e. Coefficient of Correlation ( r), Sum of Squared Errors, Root Mean Square Error, Nash-Sutcliffe Efficiency Index (NSE) and Mean Absolute Error. The ANN model with Levenberg-Marquardt training algorithm, single hidden layer and nine number of neutron schema was found the best predicting capabilities for the study station with Coefficient of Correlation ( r) and NSE value of 0.996 and 0.991 for calibration period and 0.990 and 0.980 for validation period, respectively. In the subsequent part of the study, the trend analysis of ET0 time series revealed a rising trend in the month of March, and a falling trend during June to November, except August, with more than 90% significance level and the annual declining rate was found to 1.49 mm per year.

The impact of lake and reservoir parameterization on global streamflow simulation.

PubMed

Zajac, Zuzanna; Revilla-Romero, Beatriz; Salamon, Peter; Burek, Peter; Hirpa, Feyera A; Beck, Hylke

2017-05-01

Lakes and reservoirs affect the timing and magnitude of streamflow, and are therefore essential hydrological model components, especially in the context of global flood forecasting. However, the parameterization of lake and reservoir routines on a global scale is subject to considerable uncertainty due to lack of information on lake hydrographic characteristics and reservoir operating rules. In this study we estimated the effect of lakes and reservoirs on global daily streamflow simulations of a spatially-distributed LISFLOOD hydrological model. We applied state-of-the-art global sensitivity and uncertainty analyses for selected catchments to examine the effect of uncertain lake and reservoir parameterization on model performance. Streamflow observations from 390 catchments around the globe and multiple performance measures were used to assess model performance. Results indicate a considerable geographical variability in the lake and reservoir effects on the streamflow simulation. Nash-Sutcliffe Efficiency (NSE) and Kling-Gupta Efficiency (KGE) metrics improved for 65% and 38% of catchments respectively, with median skill score values of 0.16 and 0.2 while scores deteriorated for 28% and 52% of the catchments, with median values -0.09 and -0.16, respectively. The effect of reservoirs on extreme high flows was substantial and widespread in the global domain, while the effect of lakes was spatially limited to a few catchments. As indicated by global sensitivity analysis, parameter uncertainty substantially affected uncertainty of model performance. Reservoir parameters often contributed to this uncertainty, although the effect varied widely among catchments. The effect of reservoir parameters on model performance diminished with distance downstream of reservoirs in favor of other parameters, notably groundwater-related parameters and channel Manning's roughness coefficient. This study underscores the importance of accounting for lakes and, especially, reservoirs and

Estimating catchment-scale groundwater dynamics from recession analysis - enhanced constraining of hydrological models

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Mengistu, Zelalem

2016-12-01

In this study, we propose a new formulation of subsurface water storage dynamics for use in rainfall-runoff models. Under the assumption of a strong relationship between storage and runoff, the temporal distribution of catchment-scale storage is considered to have the same shape as the distribution of observed recessions (measured as the difference between the log of runoff values). The mean subsurface storage is estimated as the storage at steady state, where moisture input equals the mean annual runoff. An important contribution of the new formulation is that its parameters are derived directly from observed recession data and the mean annual runoff. The parameters are hence estimated prior to model calibration against runoff. The new storage routine is implemented in the parameter parsimonious distance distribution dynamics (DDD) model and has been tested for 73 catchments in Norway of varying size, mean elevation and landscape type. Runoff simulations for the 73 catchments from two model structures (DDD with calibrated subsurface storage and DDD with the new estimated subsurface storage) were compared. Little loss in precision of runoff simulations was found using the new estimated storage routine. For the 73 catchments, an average of the Nash-Sutcliffe efficiency criterion of 0.73 was obtained using the new estimated storage routine compared with 0.75 using calibrated storage routine. The average Kling-Gupta efficiency criterion was 0.80 and 0.81 for the new and old storage routine, respectively. Runoff recessions are more realistically modelled using the new approach since the root mean square error between the mean of observed and simulated recession characteristics was reduced by almost 50 % using the new storage routine. The parameters of the proposed storage routine are found to be significantly correlated to catchment characteristics, which is potentially useful for predictions in ungauged basins.

Estimating catchment scale groundwater dynamics from recession analysis - enhanced constraining of hydrological models

NASA Astrophysics Data System (ADS)

Skaugen, T.; Mengistu, Z.

2015-10-01

In this study we propose a new formulation of subsurface water storage dynamics for use in rainfall-runoff models. Under the assumption of a strong relationship between storage and runoff, the temporal distribution of storage is considered to have the same shape as the distribution of observed recessions (measured as the difference between the log of runoff values). The mean subsurface storage is estimated as the storage at steady-state, where moisture input equals the mean annual runoff. An important contribution of the new formulation is that its parameters are derived directly from observed recession data and the mean annual runoff and hence estimated prior to calibration. Key principles guiding the evaluation of the new subsurface storage routine have been (a) to minimize the number of parameters to be estimated through the, often arbitrary fitting to optimize runoff predictions (calibration) and (b) maximize the range of testing conditions (i.e. large-sample hydrology). The new storage routine has been implemented in the already parameter parsimonious Distance Distribution Dynamics (DDD) model and tested for 73 catchments in Norway of varying size, mean elevations and landscape types. Runoff simulations for the 73 catchments from two model structures; DDD with calibrated subsurface storage and DDD with the new estimated subsurface storage were compared. No loss in precision of runoff simulations was found using the new estimated storage routine. For the 73 catchments, an average of the Nash-Sutcliffe Efficiency criterion of 0.68 was found using the new estimated storage routine compared with 0.66 using calibrated storage routine. The average Kling-Gupta Efficiency criterion was 0.69 and 0.70 for the new and old storage routine, respectively. Runoff recessions are more realistically modelled using the new approach since the root mean square error between the mean of observed and simulated recessions was reduced by almost 50 % using the new storage routine.

Parameter sensitivity analysis and optimization for a satellite-based evapotranspiration model across multiple sites using Moderate Resolution Imaging Spectroradiometer and flux data

NASA Astrophysics Data System (ADS)

Zhang, Kun; Ma, Jinzhu; Zhu, Gaofeng; Ma, Ting; Han, Tuo; Feng, Li Li

2017-01-01

Global and regional estimates of daily evapotranspiration are essential to our understanding of the hydrologic cycle and climate change. In this study, we selected the radiation-based Priestly-Taylor Jet Propulsion Laboratory (PT-JPL) model and assessed it at a daily time scale by using 44 flux towers. These towers distributed in a wide range of ecological systems: croplands, deciduous broadleaf forest, evergreen broadleaf forest, evergreen needleleaf forest, grasslands, mixed forests, savannas, and shrublands. A regional land surface evapotranspiration model with a relatively simple structure, the PT-JPL model largely uses ecophysiologically-based formulation and parameters to relate potential evapotranspiration to actual evapotranspiration. The results using the original model indicate that the model always overestimates evapotranspiration in arid regions. This likely results from the misrepresentation of water limitation and energy partition in the model. By analyzing physiological processes and determining the sensitive parameters, we identified a series of parameter sets that can increase model performance. The model with optimized parameters showed better performance (R2 = 0.2-0.87; Nash-Sutcliffe efficiency (NSE) = 0.1-0.87) at each site than the original model (R2 = 0.19-0.87; NSE = -12.14-0.85). The results of the optimization indicated that the parameter β (water control of soil evaporation) was much lower in arid regions than in relatively humid regions. Furthermore, the optimized value of parameter m1 (plant control of canopy transpiration) was mostly between 1 to 1.3, slightly lower than the original value. Also, the optimized parameter Topt correlated well to the actual environmental temperature at each site. We suggest that using optimized parameters with the PT-JPL model could provide an efficient way to improve the model performance.

Earthworms and tree roots: A model study of the effect of preferential flow paths on runoff generation and groundwater recharge in steep, saprolitic, tropical lowland catchments

NASA Astrophysics Data System (ADS)

Cheng, Yanyan; Ogden, Fred L.; Zhu, Jianting

2017-07-01

Preferential flow paths (PFPs) affect the hydrological response of humid tropical catchments but have not received sufficient attention. We consider PFPs created by tree roots and earthworms in a near-surface soil layer in steep, humid, tropical lowland catchments and hypothesize that observed hydrological behaviors can be better captured by reasonably considering PFPs in this layer. We test this hypothesis by evaluating the performance of four different physically based distributed model structures without and with PFPs in different configurations. Model structures are tested both quantitatively and qualitatively using hydrological, geophysical, and geochemical data both from the Smithsonian Tropical Research Institute Agua Salud Project experimental catchment(s) in Central Panama and other sources in the literature. The performance of different model structures is evaluated using runoff Volume Error and three Nash-Sutcliffe efficiency measures against observed total runoff, stormflows, and base flows along with visual comparison of simulated and observed hydrographs. Two of the four proposed model structures which include both lateral and vertical PFPs are plausible, but the one with explicit simulation of PFPs performs the best. A small number of vertical PFPs that fully extend below the root zone allow the model to reasonably simulate deep groundwater recharge, which plays a crucial role in base flow generation. Results also show that the shallow lateral PFPs are the main contributor to the observed high flow characteristics. Their number and size distribution are found to be more important than the depth distribution. Our model results are corroborated by geochemical and geophysical observations.

Influence of three common calibration metrics on the diagnosis of climate change impacts on water resources

NASA Astrophysics Data System (ADS)

Seiller, G.; Roy, R.; Anctil, F.

2017-04-01

Uncertainties associated to the evaluation of the impacts of climate change on water resources are broad, from multiple sources, and lead to diagnoses sometimes difficult to interpret. Quantification of these uncertainties is a key element to yield confidence in the analyses and to provide water managers with valuable information. This work specifically evaluates the influence of hydrological modeling calibration metrics on future water resources projections, on thirty-seven watersheds in the Province of Québec, Canada. Twelve lumped hydrologic models, representing a wide range of operational options, are calibrated with three common objective functions derived from the Nash-Sutcliffe efficiency. The hydrologic models are forced with climate simulations corresponding to two RCP, twenty-nine GCM from CMIP5 (Coupled Model Intercomparison Project phase 5) and two post-treatment techniques, leading to future projections in the 2041-2070 period. Results show that the diagnosis of the impacts of climate change on water resources are quite affected by the hydrologic models selection and calibration metrics. Indeed, for the four selected hydrological indicators, dedicated to water management, parameters from the three objective functions can provide different interpretations in terms of absolute and relative changes, as well as projected changes direction and climatic ensemble consensus. The GR4J model and a multimodel approach offer the best modeling options, based on calibration performance and robustness. Overall, these results illustrate the need to provide water managers with detailed information on relative changes analysis, but also absolute change values, especially for hydrological indicators acting as security policy thresholds.

An ensemble-based dynamic Bayesian averaging approach for discharge simulations using multiple global precipitation products and hydrological models

NASA Astrophysics Data System (ADS)

Qi, Wei; Liu, Junguo; Yang, Hong; Sweetapple, Chris

2018-03-01

Global precipitation products are very important datasets in flow simulations, especially in poorly gauged regions. Uncertainties resulting from precipitation products, hydrological models and their combinations vary with time and data magnitude, and undermine their application to flow simulations. However, previous studies have not quantified these uncertainties individually and explicitly. This study developed an ensemble-based dynamic Bayesian averaging approach (e-Bay) for deterministic discharge simulations using multiple global precipitation products and hydrological models. In this approach, the joint probability of precipitation products and hydrological models being correct is quantified based on uncertainties in maximum and mean estimation, posterior probability is quantified as functions of the magnitude and timing of discharges, and the law of total probability is implemented to calculate expected discharges. Six global fine-resolution precipitation products and two hydrological models of different complexities are included in an illustrative application. e-Bay can effectively quantify uncertainties and therefore generate better deterministic discharges than traditional approaches (weighted average methods with equal and varying weights and maximum likelihood approach). The mean Nash-Sutcliffe Efficiency values of e-Bay are up to 0.97 and 0.85 in training and validation periods respectively, which are at least 0.06 and 0.13 higher than traditional approaches. In addition, with increased training data, assessment criteria values of e-Bay show smaller fluctuations than traditional approaches and its performance becomes outstanding. The proposed e-Bay approach bridges the gap between global precipitation products and their pragmatic applications to discharge simulations, and is beneficial to water resources management in ungauged or poorly gauged regions across the world.

Impacts of precipitation and potential evapotranspiration patterns on downscaling soil moisture in regions with large topographic relief

NASA Astrophysics Data System (ADS)

Cowley, Garret S.; Niemann, Jeffrey D.; Green, Timothy R.; Seyfried, Mark S.; Jones, Andrew S.; Grazaitis, Peter J.

2017-02-01

Soil moisture can be estimated at coarse resolutions (>1 km) using satellite remote sensing, but that resolution is poorly suited for many applications. The Equilibrium Moisture from Topography, Vegetation, and Soil (EMT+VS) model downscales coarse-resolution soil moisture using fine-resolution topographic, vegetation, and soil data to produce fine-resolution (10-30 m) estimates of soil moisture. The EMT+VS model performs well at catchments with low topographic relief (≤124 m), but it has not been applied to regions with larger ranges of elevation. Large relief can produce substantial variations in precipitation and potential evapotranspiration (PET), which might affect the fine-resolution patterns of soil moisture. In this research, simple methods to downscale temporal average precipitation and PET are developed and included in the EMT+VS model, and the effects of spatial variations in these variables on the surface soil moisture estimates are investigated. The methods are tested against ground truth data at the 239 km2 Reynolds Creek watershed in southern Idaho, which has 1145 m of relief. The precipitation and PET downscaling methods are able to capture the main features in the spatial patterns of both variables. The space-time Nash-Sutcliffe coefficients of efficiency of the fine-resolution soil moisture estimates improve from 0.33 to 0.36 and 0.41 when the precipitation and PET downscaling methods are included, respectively. PET downscaling provides a larger improvement in the soil moisture estimates than precipitation downscaling likely because the PET pattern is more persistent through time, and thus more predictable, than the precipitation pattern.

Climate-driven disturbances in the San Juan River sub-basin of the Colorado River

NASA Astrophysics Data System (ADS)

Bennett, Katrina E.; Bohn, Theodore J.; Solander, Kurt; McDowell, Nathan G.; Xu, Chonggang; Vivoni, Enrique; Middleton, Richard S.

2018-01-01

Accelerated climate change and associated forest disturbances in the southwestern USA are anticipated to have substantial impacts on regional water resources. Few studies have quantified the impact of both climate change and land cover disturbances on water balances on the basin scale, and none on the regional scale. In this work, we evaluate the impacts of forest disturbances and climate change on a headwater basin to the Colorado River, the San Juan River watershed, using a robustly calibrated (Nash-Sutcliffe efficiency 0.76) hydrologic model run with updated formulations that improve estimates of evapotranspiration for semi-arid regions. Our results show that future disturbances will have a substantial impact on streamflow with implications for water resource management. Our findings are in contradiction with conventional thinking that forest disturbances reduce evapotranspiration and increase streamflow. In this study, annual average regional streamflow under the coupled climate-disturbance scenarios is at least 6-11 % lower than those scenarios accounting for climate change alone; for forested zones of the San Juan River basin, streamflow is 15-21 % lower. The monthly signals of altered streamflow point to an emergent streamflow pattern related to changes in forests of the disturbed systems. Exacerbated reductions of mean and low flows under disturbance scenarios indicate a high risk of low water availability for forested headwater systems of the Colorado River basin. These findings also indicate that explicit representation of land cover disturbances is required in modeling efforts that consider the impact of climate change on water resources.

Excavating black hole continuum spectrum: Possible signatures of scalar hairs and of higher dimensions

NASA Astrophysics Data System (ADS)

Banerjee, Indrani; Chakraborty, Sumanta; SenGupta, Soumitra

2017-10-01

Continuum spectrum from black hole accretion disc holds enormous information regarding the strong gravity regime around the black hole and hence about the nature of gravitational interaction in extreme situations. Since in such strong gravity regime the dynamics of gravity should be modified from the Einstein-Hilbert one, its effect should be imprinted on the continuum spectrum originating from the black hole accretion. To explore the effects of these alternative theories on the black hole continuum spectrum in an explicit manner, we have discussed three alternative gravitational models having their origin in three distinct paradigms—(a) higher dimensions, (b) higher curvature gravity, and (c) generalized Horndeski theories. All of them can have signatures sculptured on the black hole continuum spectrum, distinct from the standard general relativistic scenario. Interestingly all these models exhibit black hole solutions with tidal charge parameter which in these alternative gravity scenarios can become negative, in sharp contrast with the Reissner-Nordström black hole. Using the observational data of optical luminosity for eighty Palomer Green quasars we have illustrated that the difference between the theoretical estimates and the observational results gets minimized for negative values of the tidal charge parameter. As a quantitative estimate of this result we concentrate on several error estimators, including reduced χ2 , Nash-Sutcliffe efficiency, index of agreement etc. Remarkably, all of them indicates a negative value of the tidal charge parameter, signaling the possibility of higher dimensions as well as scalar charge at play in those high gravity regimes.

Adequacy of TRMM satellite rainfall data in driving the SWAT modeling of Tiaoxi catchment (Taihu lake basin, China)

NASA Astrophysics Data System (ADS)

Li, Dan; Christakos, George; Ding, Xinxin; Wu, Jiaping

2018-01-01

Spatial rainfall data is an essential input to Distributed Hydrological Models (DHM), and a significant contributor to hydrological model uncertainty. Model uncertainty is higher when rain gauges are sparse, as is often the case in practice. Currently, satellite-based precipitation products increasingly provide an alternative means to ground-based rainfall estimates, in which case a rigorous product assessment is required before implementation. Accordingly, the twofold objective of this work paper was the real-world assessment of both (a) the Tropical Rainfall Measuring Mission (TRMM) rainfall product using gauge data, and (b) the TRMM product's role in forcing data for hydrologic simulations in the area of the Tiaoxi catchment (Taihu lake basin, China). The TRMM rainfall products used in this study are the Version-7 real-time 3B42RT and the post-real-time 3B42. It was found that the TRMM rainfall data showed a superior performance at the monthly and annual scales, fitting well with surface observation-based frequency rainfall distributions. The Nash-Sutcliffe Coefficient of Efficiency (NSCE) and the relative bias ratio (BIAS) were used to evaluate hydrologic model performance. The satisfactory performance of the monthly runoff simulations in the Tiaoxi study supports the view that the implementation of real-time 3B42RT allows considerable room for improvement. At the same time, post-real-time 3B42 can be a valuable tool of hydrologic modeling, water balance analysis, and basin water resource management, especially in developing countries or at remote locations in which rainfall gauges are scarce.

Climate change impacts under CMIP5 RCP scenarios on water resources of the Kelantan River Basin, Malaysia

NASA Astrophysics Data System (ADS)

Tan, Mou Leong; Ibrahim, Ab Latif; Yusop, Zulkifli; Chua, Vivien P.; Chan, Ngai Weng

2017-06-01

This study aims to evaluate the potential impacts of climate change on water resources of the Kelantan River Basin in north-eastern Peninsular Malaysia using the Soil and Water Assessment Tool (SWAT) model. Thirty-six downscaled climate projections from five General Circulation Models (GCMs) under the three Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 scenarios for the periods of 2015-2044 and 2045-2074 were incorporated into the calibrated SWAT model. Differences of these scenarios were calculated by comparing to the 1975-2004 baseline period. Overall, the SWAT model performed well in monthly streamflow simulation, with the Nash-Sutcliffe efficiency values of 0.75 and 0.63 for calibration and validation, respectively. Based on the ensemble of five GCMs, the annual rainfall and maximum temperature are projected to increase by 1.2-8.7% and 0.6-2.1 °C, respectively. This corresponds to the increases in the annual streamflow (14.6-27.2%), evapotranspiration (0.3-2.7%), surface runoff (46.8-90.2%) and water yield (14.2-26.5%) components. The study shows an increase of monthly rainfall during the wet season, and decrease during the dry season. Therefore, the monthly streamflow and surface runoff are likely to increase significantly in November, December and January. In addition, slight decreases in the monthly water yield are found between June and October (1.9-8.9%) during the 2015-2044 period. These findings could act as a scientific reference to develop better climate adaptation strategies.

Analysis of the hydrological response of a distributed physically-based model using post-assimilation (EnKF) diagnostics of streamflow and in situ soil moisture observations

NASA Astrophysics Data System (ADS)

Trudel, Mélanie; Leconte, Robert; Paniconi, Claudio

2014-06-01

Data assimilation techniques not only enhance model simulations and forecast, they also provide the opportunity to obtain a diagnostic of both the model and observations used in the assimilation process. In this research, an ensemble Kalman filter was used to assimilate streamflow observations at a basin outlet and at interior locations, as well as soil moisture at two different depths (15 and 45 cm). The simulation model is the distributed physically-based hydrological model CATHY (CATchment HYdrology) and the study site is the Des Anglais watershed, a 690 km2 river basin located in southern Quebec, Canada. Use of Latin hypercube sampling instead of a conventional Monte Carlo method to generate the ensemble reduced the size of the ensemble, and therefore the calculation time. Different post-assimilation diagnostics, based on innovations (observation minus background), analysis residuals (observation minus analysis), and analysis increments (analysis minus background), were used to evaluate assimilation optimality. An important issue in data assimilation is the estimation of error covariance matrices. These diagnostics were also used in a calibration exercise to determine the standard deviation of model parameters, forcing data, and observations that led to optimal assimilations. The analysis of innovations showed a lag between the model forecast and the observation during rainfall events. Assimilation of streamflow observations corrected this discrepancy. Assimilation of outlet streamflow observations improved the Nash-Sutcliffe efficiencies (NSE) between the model forecast (one day) and the observation at both outlet and interior point locations, owing to the structure of the state vector used. However, assimilation of streamflow observations systematically increased the simulated soil moisture values.

Application of Water Evaluation and Planning Model for Integrated Water Resources Management: Case Study of Langat River Basin, Malaysia

NASA Astrophysics Data System (ADS)

Leong, W. K.; Lai, S. H.

2017-06-01

Due to the effects of climate change and the increasing demand on water, sustainable development in term of water resources management has become a major challenge. In this context, the application of simulation models is useful to duel with the uncertainty and complexity of water system by providing stakeholders with the best solution. This paper outlines an integrated management planning network is developed based on Water Evaluation and Planning (WEAP) to evaluate current and future water management system of Langat River Basin, Malaysia under various scenarios. The WEAP model is known as an integrated decision support system investigate major stresses on demand and supply in terms of water availability in catchment scale. In fact, WEAP is applicable to simulate complex systems including various sectors within a single catchment or transboundary river system. To construct the model, by taking account of the Langat catchment and the corresponding demand points, we defined the hydrological model into 10 sub-hydrological catchments and 17 demand points included the export of treated water to the major cities outside the catchment. The model is calibrated and verified by several quantitative statistics (coefficient of determination, R2; Nash-Sutcliffe efficiency, NSE and Percent bias, PBIAS). The trend of supply and demand in the catchment is evaluated under three scenarios to 2050, 1: Population growth rate, 2: Demand side management (DSM) and 3: Combination of DSM and reduce non-revenue water (NRW). Results show that by reducing NRW and proper DSM, unmet demand able to reduce significantly.

Improvement and comparison of likelihood functions for model calibration and parameter uncertainty analysis within a Markov chain Monte Carlo scheme

NASA Astrophysics Data System (ADS)

Cheng, Qin-Bo; Chen, Xi; Xu, Chong-Yu; Reinhardt-Imjela, Christian; Schulte, Achim

2014-11-01

In this study, the likelihood functions for uncertainty analysis of hydrological models are compared and improved through the following steps: (1) the equivalent relationship between the Nash-Sutcliffe Efficiency coefficient (NSE) and the likelihood function with Gaussian independent and identically distributed residuals is proved; (2) a new estimation method of the Box-Cox transformation (BC) parameter is developed to improve the effective elimination of the heteroscedasticity of model residuals; and (3) three likelihood functions-NSE, Generalized Error Distribution with BC (BC-GED) and Skew Generalized Error Distribution with BC (BC-SGED)-are applied for SWAT-WB-VSA (Soil and Water Assessment Tool - Water Balance - Variable Source Area) model calibration in the Baocun watershed, Eastern China. Performances of calibrated models are compared using the observed river discharges and groundwater levels. The result shows that the minimum variance constraint can effectively estimate the BC parameter. The form of the likelihood function significantly impacts on the calibrated parameters and the simulated results of high and low flow components. SWAT-WB-VSA with the NSE approach simulates flood well, but baseflow badly owing to the assumption of Gaussian error distribution, where the probability of the large error is low, but the small error around zero approximates equiprobability. By contrast, SWAT-WB-VSA with the BC-GED or BC-SGED approach mimics baseflow well, which is proved in the groundwater level simulation. The assumption of skewness of the error distribution may be unnecessary, because all the results of the BC-SGED approach are nearly the same as those of the BC-GED approach.

Evaluation of the APEX Model to Simulate Runoff Quality from Agricultural Fields in the Southern Region of the United States.

PubMed

Ramirez-Avila, John J; Radcliffe, David E; Osmond, Deanna; Bolster, Carl; Sharpley, Andrew; Ortega-Achury, Sandra L; Forsberg, Adam; Oldham, J Larry

2017-11-01

The Agricultural Policy Environmental eXtender (APEX) model has been widely applied to assess phosphorus (P) loss in runoff water and has been proposed as a model to support practical decisions regarding agricultural P management, as well as a model to evaluate tools such as the P Index. The aim of this study is to evaluate the performance of APEX to simulate P losses from agricultural systems to determine its potential use for refinement or replacement of the P Index in the southern region of the United States. Uncalibrated and calibrated APEX model predictions were compared against measured water quality data from row crop fields in North Carolina and Mississippi and pasture fields in Arkansas and Georgia. Calibrated models satisfactorily predicted event-based surface runoff volumes at all sites (Nash-Sutcliffe efficiency [NSE] > 0.47, |percent bias [PBIAS]| < 34) except Arkansas (NSE < 0.11, |PBIAS| < 50) but did not satisfactory simulate sediment, dissolved P, or total P losses in runoff water. The APEX model tended to underestimate dissolved and total P losses from fields where manure was surface applied. The model also overestimated sediments and total P loads during irrigation events. We conclude that the capability of APEX to predict sediment and P losses is limited, and consequently so is the potential for using APEX to make P management recommendations to improve P Indices in the southern United States. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Multisite Evaluation of APEX for Water Quality: I. Best Professional Judgment Parameterization.

PubMed

Baffaut, Claire; Nelson, Nathan O; Lory, John A; Senaviratne, G M M M Anomaa; Bhandari, Ammar B; Udawatta, Ranjith P; Sweeney, Daniel W; Helmers, Matt J; Van Liew, Mike W; Mallarino, Antonio P; Wortmann, Charles S

2017-11-01

The Agricultural Policy Environmental eXtender (APEX) model is capable of estimating edge-of-field water, nutrient, and sediment transport and is used to assess the environmental impacts of management practices. The current practice is to fully calibrate the model for each site simulation, a task that requires resources and data not always available. The objective of this study was to compare model performance for flow, sediment, and phosphorus transport under two parameterization schemes: a best professional judgment (BPJ) parameterization based on readily available data and a fully calibrated parameterization based on site-specific soil, weather, event flow, and water quality data. The analysis was conducted using 12 datasets at four locations representing poorly drained soils and row-crop production under different tillage systems. Model performance was based on the Nash-Sutcliffe efficiency (NSE), the coefficient of determination () and the regression slope between simulated and measured annualized loads across all site years. Although the BPJ model performance for flow was acceptable (NSE = 0.7) at the annual time step, calibration improved it (NSE = 0.9). Acceptable simulation of sediment and total phosphorus transport (NSE = 0.5 and 0.9, respectively) was obtained only after full calibration at each site. Given the unacceptable performance of the BPJ approach, uncalibrated use of APEX for planning or management purposes may be misleading. Model calibration with water quality data prior to using APEX for simulating sediment and total phosphorus loss is essential. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Estimation of surface water storage in the Congo Basin

NASA Astrophysics Data System (ADS)

O'Loughlin, F.; Neal, J. C.; Schumann, G.; Beighley, E.; Bates, P. D.

2015-12-01

For many large river basins, especially in Africa, the lack of access to in-situ measurements, and the large areas involved, make modelling of water storage and runoff difficult. However, remote sensing datasets are useful alternative sources of information, which overcome these issues. In this study, we focus on the Congo Basin and, in particular, the cuvette central. Despite being the second largest river basin on earth and containing a large percentage of the world's tropical wetlands and forest, little is known about this basin's hydrology. Combining discharge estimates from in-situ measurements and outputs from a hydrological model, we build the first large-scale hydrodynamic model for this region to estimate the volume of water stored in the corresponding floodplains and to investigate how important these floodplains are to the behaviour of the overall system. This hydrodynamic model covers an area over 1.6 million square kilometres and 13 thousand kilometres of rivers and is calibrated to water surface heights at 33 virtual gauging stations obtained from ESA's Envisat satellite. Our results show that the use of different sources of discharge estimations and calibration via Envisat observations can produce accurate water levels and downstream discharges. Our model produced un-biased (bias =-0.08 m), sub-metre Root Mean Square Error (RMSE =0.862 m) with a Nash-Sutcliffe efficiency greater than 80% (NSE =0.81). The spatial-temporal variations in our simulated inundated areas are consistent with the pattern obtained from satellites. Overall, we find a high correlation coefficient (R =0.88) between our modelled inundated areas and those estimated from satellites.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Comparison of model performance and simulated water balance using NASIM and SWAT for the Wupper River Basin, Germany

NASA Astrophysics Data System (ADS)

Lorza, Paula; Nottebohm, Martin; Scheibel, Marc; aus der Beek, Tim

2017-04-01

Under the framework of the Horizon 2020 project BINGO (Bringing INnovation to onGOing water management), climate change impacts on the water cycle in the Wupper catchment area are being studied. With this purpose, a set of hydrological models in NASIM and SWAT have been set up, calibrated, and validated for past conditions using available data. NASIM is a physically-based, lumped, hydrological model based on the water balance equation. For the upper part of the Dhünn catchment area - Wupper River's main tributary - a SWAT model was also implemented. Observed and simulated discharge by NASIM and SWAT for the drainage area upstream of Neumühle hydrometric station (close to Große Dhünn reservoir's inlet) are compared. Comparison of simulated water balance for several hydrological years between the two models is also carried out. While NASIM offers high level of detail for modelling of complex urban areas and the possibility of entering precipitation time series at fine temporal resolution (e.g. minutely data), SWAT enables to study long-term impacts offering a huge variety of input and output variables including different soil properties, vegetation and land management practices. Beside runoff, also sediment and nutrient transport can be simulated. For most calculations, SWAT operates on a daily time step. The objective of this and future work is to determine catchment responses on different meteorological events and to study parameter sensitivity of stationary inputs such as soil parameters, vegetation or land use. Model performance is assessed with different statistical metrics (relative volume error, coefficient of determination, and Nash-Sutcliffe Efficiency).

Soil salinisation and irrigation management of date palms in a Saharan environment.

PubMed

Haj-Amor, Zied; Ibrahimi, Mohamed-Khaled; Feki, Nissma; Lhomme, Jean-Paul; Bouri, Salem

2016-08-01

The continuance of agricultural production in regions of the world with chronic water shortages depends upon understanding how soil salinity is impacted by irrigation practises such as water salinity, irrigation frequency and amount of irrigation. A two-year field study was conducted in a Saharan oasis of Tunisia (Lazala Oasis) to determine how the soil electrical conductivity was affected by irrigation of date palms with high saline water. The study area lacked a saline shallow water table. Field results indicate that, under current irrigation practises, soil electrical conductivity can build up to levels which exceed the salt tolerance of date palm trees. The effects of irrigation practises on the soil electrical conductivity were also evaluated using model simulations (HYDRUS-1D) of various irrigation regimes with different frequencies, different amounts of added water and different water salinities. The comparison between the simulated and observed results demonstrated that the model gave an acceptable estimation of water and salt dynamics in the soil profile, as indicated by the small values of root mean square error (RMSE) and the high values of the Nash-Sutcliffe model efficiency coefficient (NSE). The simulations demonstrated that, under field conditions without saline shallow groundwater, saline irrigation water can be used to maintain soil electrical conductivity and soil water content at safe levels (soil electrical conductivity <4 dS m(-1) and soil water content >0.04 cm(3) cm(-3)) if frequent irrigations with small amounts of water (90 % of the evapotranspiration requirements) were applied throughout the year.

Generation of common coefficients to estimate global solar radiation over different locations of India

NASA Astrophysics Data System (ADS)

Samanta, Suman; Patra, Pulak Kumar; Banerjee, Saon; Narsimhaiah, Lakshmi; Sarath Chandran, M. A.; Vijaya Kumar, P.; Bandyopadhyay, Sanjib

2018-06-01

In developing countries like India, global solar radiation (GSR) is measured at very few locations due to non-availability of radiation measuring instruments. To overcome the inadequacy of GSR measurements, scientists developed many empirical models to estimate location-wise GSR. In the present study, three simple forms of Angstrom equation [Angstrom-Prescott (A-P), Ogelman, and Bahel] were used to estimate GSR at six geographically and climatologically different locations across India with an objective to find out a set of common constants usable for whole country. Results showed that GSR values varied from 9.86 to 24.85 MJ m-2 day-1 for different stations. It was also observed that A-P model showed smaller errors than Ogelman and Bahel models. All the models well estimated GSR, as the 1:1 line between measured and estimated values showed Nash-Sutcliffe efficiency (NSE) values ≥ 0.81 for all locations. Measured data of GSR pooled over six selected locations was analyzed to obtain a new set of constants for A-P equation which can be applicable throughout the country. The set of constants (a = 0.29 and b = 0.40) was named as "One India One Constant (OIOC)," and the model was named as "MOIOC." Furthermore, the developed constants are validated statistically for another six locations of India and produce close estimation. High R 2 values (≥ 76%) along with low mean bias error (MBE) ranging from - 0.64 to 0.05 MJ m-2 day-1 revealed that the new constants are able to predict GSR with lesser percentage of error.

Similarity-based multi-model ensemble approach for 1-15-day advance prediction of monsoon rainfall over India

NASA Astrophysics Data System (ADS)

Jaiswal, Neeru; Kishtawal, C. M.; Bhomia, Swati

2018-04-01

The southwest (SW) monsoon season (June, July, August and September) is the major period of rainfall over the Indian region. The present study focuses on the development of a new multi-model ensemble approach based on the similarity criterion (SMME) for the prediction of SW monsoon rainfall in the extended range. This approach is based on the assumption that training with the similar type of conditions may provide the better forecasts in spite of the sequential training which is being used in the conventional MME approaches. In this approach, the training dataset has been selected by matching the present day condition to the archived dataset and days with the most similar conditions were identified and used for training the model. The coefficients thus generated were used for the rainfall prediction. The precipitation forecasts from four general circulation models (GCMs), viz. European Centre for Medium-Range Weather Forecasts (ECMWF), United Kingdom Meteorological Office (UKMO), National Centre for Environment Prediction (NCEP) and China Meteorological Administration (CMA) have been used for developing the SMME forecasts. The forecasts of 1-5, 6-10 and 11-15 days were generated using the newly developed approach for each pentad of June-September during the years 2008-2013 and the skill of the model was analysed using verification scores, viz. equitable skill score (ETS), mean absolute error (MAE), Pearson's correlation coefficient and Nash-Sutcliffe model efficiency index. Statistical analysis of SMME forecasts shows superior forecast skill compared to the conventional MME and the individual models for all the pentads, viz. 1-5, 6-10 and 11-15 days.

Improvement of suspended sediment concentration estimation for the Yarlung Zangbo river

NASA Astrophysics Data System (ADS)

Zeng, C.; Zhang, F.

2017-12-01

Suspended sediment load of a river represents integrated results of soil erosion, ecosystem variation and landform change occurring within basin over a specified period. Accurate estimation of suspended sediment concentration is important for calculating suspended sediment load, therefore is helpful for evaluating the impact of natural and anthropogenic factors on earth system processes under the background of global climate change. However, long-term observation of suspended sediment concentration usually very difficult in harsh condition areas e.g. rivers on the Tibet Plateau. This study proposed two sediment rating curve subdivision methods, the flood rank method and suspended sediment concentration stages method, to improve the estimations of daily suspended sediment concentration of the Yarlung Zangbo river during 2007 to 2009. The flood rank method, hypothesized that the higher water flow with larger erosive power can mobilize sediment sources not available during lower flows, suitable for application where sediments were mainly transported by first few flood events. The suspended sediment concentration stages method, assumed that precipitation is the dominating driving force of sediment erosion and transport processes during the flooding periods, suitable for application where soil erosion was closely related to precipitation events. Compared to traditional sediment rating curve and subdivision methods, results showed that the proposed methods can improve suspended sediment concentration and subsequent suspended sediment load estimations in the middle reach of the Yarlung Zangbo river with higher coefficients of determination (R2) and Nash-Sutcliffe efficiency coefficients (NSE), and yielded smaller bias (BIAS) and root-mean-square errors (RMSE). This study can provide guidelines for regional ecological and environmental management.

Uncertainty analysis of hydrological modeling in a tropical area using different algorithms

NASA Astrophysics Data System (ADS)

Rafiei Emam, Ammar; Kappas, Martin; Fassnacht, Steven; Linh, Nguyen Hoang Khanh

2018-01-01

Hydrological modeling outputs are subject to uncertainty resulting from different sources of errors (e.g., error in input data, model structure, and model parameters), making quantification of uncertainty in hydrological modeling imperative and meant to improve reliability of modeling results. The uncertainty analysis must solve difficulties in calibration of hydrological models, which further increase in areas with data scarcity. The purpose of this study is to apply four uncertainty analysis algorithms to a semi-distributed hydrological model, quantifying different source of uncertainties (especially parameter uncertainty) and evaluate their performance. In this study, the Soil and Water Assessment Tools (SWAT) eco-hydrological model was implemented for the watershed in the center of Vietnam. The sensitivity of parameters was analyzed, and the model was calibrated. The uncertainty analysis for the hydrological model was conducted based on four algorithms: Generalized Likelihood Uncertainty Estimation (GLUE), Sequential Uncertainty Fitting (SUFI), Parameter Solution method (ParaSol) and Particle Swarm Optimization (PSO). The performance of the algorithms was compared using P-factor and Rfactor, coefficient of determination (R 2), the Nash Sutcliffe coefficient of efficiency (NSE) and Percent Bias (PBIAS). The results showed the high performance of SUFI and PSO with P-factor>0.83, R-factor <0.56 and R 2>0.91, NSE>0.89, and 0.18

Using oceanic-atmospheric oscillations for long lead time streamflow forecasting

NASA Astrophysics Data System (ADS)

Kalra, Ajay; Ahmad, Sajjad

2009-03-01

We present a data-driven model, Support Vector Machine (SVM), for long lead time streamflow forecasting using oceanic-atmospheric oscillations. The SVM is based on statistical learning theory that uses a hypothesis space of linear functions based on Kernel approach and has been used to predict a quantity forward in time on the basis of training from past data. The strength of SVM lies in minimizing the empirical classification error and maximizing the geometric margin by solving inverse problem. The SVM model is applied to three gages, i.e., Cisco, Green River, and Lees Ferry in the Upper Colorado River Basin in the western United States. Annual oceanic-atmospheric indices, comprising Pacific Decadal Oscillation (PDO), North Atlantic Oscillation (NAO), Atlantic Multidecadal Oscillation (AMO), and El Nino-Southern Oscillations (ENSO) for a period of 1906-2001 are used to generate annual streamflow volumes with 3 years lead time. The SVM model is trained with 86 years of data (1906-1991) and tested with 10 years of data (1992-2001). On the basis of correlation coefficient, root means square error, and Nash Sutcliffe Efficiency Coefficient the model shows satisfactory results, and the predictions are in good agreement with measured streamflow volumes. Sensitivity analysis, performed to evaluate the effect of individual and coupled oscillations, reveals a strong signal for ENSO and NAO indices as compared to PDO and AMO indices for the long lead time streamflow forecast. Streamflow predictions from the SVM model are found to be better when compared with the predictions obtained from feedforward back propagation artificial neural network model and linear regression.

Topographic Controls on Soil Carbon Distribution in Iowa Croplands, USA

NASA Astrophysics Data System (ADS)

McCarty, Greg; Li, Xia

2017-04-01

Topography is a key factor affecting soil organic carbon (SOC) redistribution (erosion or deposition) because it influences several hydrological indices including soil moisture dynamics, runoff velocity and acceleration, and flow divergence and convergence. In this study, we examined the relationship between 15 topographic metrics derived from Light Detection and Ranging (Lidar) data and SOC redistribution in agricultural fields. We adopted the fallout 137Cesium (137Cs) technique to estimate SOC redistribution rates across 560 sampling plots in Iowa. Then, using stepwise ordinarily least square regression (SOLSR) and stepwise principle component analysis (SPCA), topography-based SOC models were developed to simulate spatial patterns of SOC content and redistribution. Results suggested that erosion and deposition of topsoil SOC were regulated by topography with SOC gain in lowland areas and SOC loss in sloping areas. Topographic wetness index (TWI) and slope were the most influential variables controlling SOC content and redistribution. The topography-based models exhibited good performances in simulating SOC content and redistribution across two crop sites with intensive samplings. SPCA models had slightly lower coefficients of determination and Nash-Sutcliffe efficiency values compared to SOLSR models at the field scale. However, significantly SPCA outperformed SOLAR in predicting SOC redistribution patterns at the watershed scale. Results of this study suggest that the topography-based SPCA model was more robust for scaling up models to the watershed scale because SPCA models may better represent the landscapes and are less subject to over fitting. This work suggests an improved method to sample and characterize landscapes for better prediction of soil property distribution.

Precipitation projections under GCMs perspective and Turkish Water Foundation (TWF) statistical downscaling model procedures

NASA Astrophysics Data System (ADS)

Dabanlı, İsmail; Şen, Zekai

2018-04-01

The statistical climate downscaling model by the Turkish Water Foundation (TWF) is further developed and applied to a set of monthly precipitation records. The model is structured by two phases as spatial (regional) and temporal downscaling of global circulation model (GCM) scenarios. The TWF model takes into consideration the regional dependence function (RDF) for spatial structure and Markov whitening process (MWP) for temporal characteristics of the records to set projections. The impact of climate change on monthly precipitations is studied by downscaling Intergovernmental Panel on Climate Change-Special Report on Emission Scenarios (IPCC-SRES) A2 and B2 emission scenarios from Max Plank Institute (EH40PYC) and Hadley Center (HadCM3). The main purposes are to explain the TWF statistical climate downscaling model procedures and to expose the validation tests, which are rewarded in same specifications as "very good" for all stations except one (Suhut) station in the Akarcay basin that is in the west central part of Turkey. Eventhough, the validation score is just a bit lower at the Suhut station, the results are "satisfactory." It is, therefore, possible to say that the TWF model has reasonably acceptable skill for highly accurate estimation regarding standard deviation ratio (SDR), Nash-Sutcliffe efficiency (NSE), and percent bias (PBIAS) criteria. Based on the validated model, precipitation predictions are generated from 2011 to 2100 by using 30-year reference observation period (1981-2010). Precipitation arithmetic average and standard deviation have less than 5% error for EH40PYC and HadCM3 SRES (A2 and B2) scenarios.

A data-driven SVR model for long-term runoff prediction and uncertainty analysis based on the Bayesian framework

NASA Astrophysics Data System (ADS)

Liang, Zhongmin; Li, Yujie; Hu, Yiming; Li, Binquan; Wang, Jun

2017-06-01

Accurate and reliable long-term forecasting plays an important role in water resources management and utilization. In this paper, a hybrid model called SVR-HUP is presented to predict long-term runoff and quantify the prediction uncertainty. The model is created based on three steps. First, appropriate predictors are selected according to the correlations between meteorological factors and runoff. Second, a support vector regression (SVR) model is structured and optimized based on the LibSVM toolbox and a genetic algorithm. Finally, using forecasted and observed runoff, a hydrologic uncertainty processor (HUP) based on a Bayesian framework is used to estimate the posterior probability distribution of the simulated values, and the associated uncertainty of prediction was quantitatively analyzed. Six precision evaluation indexes, including the correlation coefficient (CC), relative root mean square error (RRMSE), relative error (RE), mean absolute percentage error (MAPE), Nash-Sutcliffe efficiency (NSE), and qualification rate (QR), are used to measure the prediction accuracy. As a case study, the proposed approach is applied in the Han River basin, South Central China. Three types of SVR models are established to forecast the monthly, flood season and annual runoff volumes. The results indicate that SVR yields satisfactory accuracy and reliability at all three scales. In addition, the results suggest that the HUP cannot only quantify the uncertainty of prediction based on a confidence interval but also provide a more accurate single value prediction than the initial SVR forecasting result. Thus, the SVR-HUP model provides an alternative method for long-term runoff forecasting.

Verification of Advances in a Coupled Snow-runoff Modeling Framework for Operational Streamflow Forecasts

NASA Astrophysics Data System (ADS)

Barik, M. G.; Hogue, T. S.; Franz, K. J.; He, M.

2011-12-01

The National Oceanic and Atmospheric Administration's (NOAA's) River Forecast Centers (RFCs) issue hydrologic forecasts related to flood events, reservoir operations for water supply, streamflow regulation, and recreation on the nation's streams and rivers. The RFCs use the National Weather Service River Forecast System (NWSRFS) for streamflow forecasting which relies on a coupled snow model (i.e. SNOW17) and rainfall-runoff model (i.e. SAC-SMA) in snow-dominated regions of the US. Errors arise in various steps of the forecasting system from input data, model structure, model parameters, and initial states. The goal of the current study is to undertake verification of potential improvements in the SNOW17-SAC-SMA modeling framework developed for operational streamflow forecasts. We undertake verification for a range of parameters sets (i.e. RFC, DREAM (Differential Evolution Adaptive Metropolis)) as well as a data assimilation (DA) framework developed for the coupled models. Verification is also undertaken for various initial conditions to observe the influence of variability in initial conditions on the forecast. The study basin is the North Fork America River Basin (NFARB) located on the western side of the Sierra Nevada Mountains in northern California. Hindcasts are verified using both deterministic (i.e. Nash Sutcliffe efficiency, root mean square error, and joint distribution) and probabilistic (i.e. reliability diagram, discrimination diagram, containing ratio, and Quantile plots) statistics. Our presentation includes comparison of the performance of different optimized parameters and the DA framework as well as assessment of the impact associated with the initial conditions used for streamflow forecasts for the NFARB.

Determination of the optimal training principle and input variables in artificial neural network model for the biweekly chlorophyll-a prediction: a case study of the Yuqiao Reservoir, China.

PubMed

Liu, Yu; Xi, Du-Gang; Li, Zhao-Liang

2015-01-01

Predicting the levels of chlorophyll-a (Chl-a) is a vital component of water quality management, which ensures that urban drinking water is safe from harmful algal blooms. This study developed a model to predict Chl-a levels in the Yuqiao Reservoir (Tianjin, China) biweekly using water quality and meteorological data from 1999-2012. First, six artificial neural networks (ANNs) and two non-ANN methods (principal component analysis and the support vector regression model) were compared to determine the appropriate training principle. Subsequently, three predictors with different input variables were developed to examine the feasibility of incorporating meteorological factors into Chl-a prediction, which usually only uses water quality data. Finally, a sensitivity analysis was performed to examine how the Chl-a predictor reacts to changes in input variables. The results were as follows: first, ANN is a powerful predictive alternative to the traditional modeling techniques used for Chl-a prediction. The back program (BP) model yields slightly better results than all other ANNs, with the normalized mean square error (NMSE), the correlation coefficient (Corr), and the Nash-Sutcliffe coefficient of efficiency (NSE) at 0.003 mg/l, 0.880 and 0.754, respectively, in the testing period. Second, the incorporation of meteorological data greatly improved Chl-a prediction compared to models solely using water quality factors or meteorological data; the correlation coefficient increased from 0.574-0.686 to 0.880 when meteorological data were included. Finally, the Chl-a predictor is more sensitive to air pressure and pH compared to other water quality and meteorological variables.

Potential of vetiver (vetiveria zizanioides (L.) Nash) for phytoremediation of petroleum hydrocarbon-contaminated soils in Venezuela.

PubMed

Brandt, Regine; Merkl, Nicole; Schultze-Kraft, Rainer; Infante, Carmen; Broll, Gabriele

2006-01-01

Venezuela is one of the largest oil producers in the world. For the rehabilitation of oil-contaminated sites, phytoremediation represents a promising technology whereby plants are used to enhance biodegradation processes in soil. A greenhouse study was conducted to determine the tolerance of vetiver (Vetiveria zizanioides (L.) Nash) to a Venezuelan heavy crude oil in soil. Additionally, the plant's potential for stimulating the biodegradation processes of petroleum hydrocarbons was tested under the application of two fertilizer levels. In the presence of contaminants, biomass and plant height were significantly reduced. As for fertilization, the lower fertilizer level led to higher biomass production. The specific root surface area was reduced under the effects of petroleum. However, vetiver was found to tolerate crude-oil contamination in a concentration of 5% (w/w). Concerning total oil and grease content in soil, no significant decrease under the influence of vetiver was detected when compared to the unplanted control. Thus, there was no evidence of vetiver enhancing the biodegradation of crude oil in soil under the conditions of this trial. However, uses of vetiver grass in relation to petroleum-contaminated soils are promising for amelioration of slightly polluted sites, to allow other species to get established and for erosion control.

Roles of ER, SRC-1, and CBP Phosphorylation in Estrogen Receptor-Regulated Gene Expression

DTIC Science & Technology

1999-06-01

J. S. Sutcliff, P. Fang, R. J. Galjaard, Y. H. Jiang, C. S. localization of three repair genes: the xeroderma pigmentosum group C gene Benton, J. M...receptor-mediated scription efficiency, a central DNA-binding domain, which me- transcription; SRC-1, p300/CBP, and RAC3/ACTR/AIB1 pos - diates receptor

Utility of the ELF Test for Detecting Steatohepatitis in Morbid Obese Patients with Suspicion of Nonalcoholic Fatty Liver Disease.

PubMed

López, Iria Cebreiros; Aroca, Florentina Guzmán; Bernal, Maria Dolores Frutos; Mompeán, Juan Antonio Luján; Bernal, Águeda Bas; Martínez, Antonio Miguel Hernández; Barba, Enrique Martínez; Velasco, Jose Antonio Noguera; Paricio, Pascual Parilla

2017-09-01

Morbid obese patients have a high rate of nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH). NASH is related to the progression and poor evolution of chronic hepatopathy in NAFLD, so that its detection makes it possible to identify the subjects who are most at risk in order to prioritize treatment. The ELF test (Enhanced Liver Fibrosis test; Siemens Diagnostics, NY, USA) has been assessed for its capacity to detect fibrosis in patients with NAFLD, but its capacity for diagnosing NASH has not been checked. Our objective is to determine the utility of the ELF test for detecting NASH in morbid obese patients with suspected NAFLD. ELF values were determined in a cohort of obese patients who underwent bariatric surgery with suspected NAFLD. Liver biopsy was used as the reference standard. The values of ELF were significantly higher in patients with NASH (p = 0.002) and in those who presented with metabolic syndrome (p = 0.047). An ELF cut-off point of 8.72 allows the detection of patients with NASH with a sensitivity of 71.4% and a specificity of 74.1% (AUC = 0.742, p = 0.002). The ELF test is efficient for the identification of obese patients with NAFLD and early signs of steatohepatitis and fibrosis.

Modeling Nitrogen Dynamics in a Waste Stabilization Pond System Using Flexible Modeling Environment with MCMC.

PubMed

Mukhtar, Hussnain; Lin, Yu-Pin; Shipin, Oleg V; Petway, Joy R

2017-07-12

This study presents an approach for obtaining realization sets of parameters for nitrogen removal in a pilot-scale waste stabilization pond (WSP) system. The proposed approach was designed for optimal parameterization, local sensitivity analysis, and global uncertainty analysis of a dynamic simulation model for the WSP by using the R software package Flexible Modeling Environment (R-FME) with the Markov chain Monte Carlo (MCMC) method. Additionally, generalized likelihood uncertainty estimation (GLUE) was integrated into the FME to evaluate the major parameters that affect the simulation outputs in the study WSP. Comprehensive modeling analysis was used to simulate and assess nine parameters and concentrations of ON-N, NH₃-N and NO₃-N. Results indicate that the integrated FME-GLUE-based model, with good Nash-Sutcliffe coefficients (0.53-0.69) and correlation coefficients (0.76-0.83), successfully simulates the concentrations of ON-N, NH₃-N and NO₃-N. Moreover, the Arrhenius constant was the only parameter sensitive to model performances of ON-N and NH₃-N simulations. However, Nitrosomonas growth rate, the denitrification constant, and the maximum growth rate at 20 °C were sensitive to ON-N and NO₃-N simulation, which was measured using global sensitivity.

Evaluation of different parameterizations of the spatial heterogeneity of subsurface storage capacity for hourly runoff simulation in boreal mountainous watershed

NASA Astrophysics Data System (ADS)

Hailegeorgis, Teklu T.; Alfredsen, Knut; Abdella, Yisak S.; Kolberg, Sjur

2015-03-01

Identification of proper parameterizations of spatial heterogeneity is required for precipitation-runoff models. However, relevant studies with a specific aim at hourly runoff simulation in boreal mountainous catchments are not common. We conducted calibration and evaluation of hourly runoff simulation in a boreal mountainous watershed based on six different parameterizations of the spatial heterogeneity of subsurface storage capacity for a semi-distributed (subcatchments hereafter called elements) and distributed (1 × 1 km2 grid) setup. We evaluated representation of element-to-element, grid-to-grid, and probabilistic subcatchment/subbasin, subelement and subgrid heterogeneities. The parameterization cases satisfactorily reproduced the streamflow hydrographs with Nash-Sutcliffe efficiency values for the calibration and validation periods up to 0.84 and 0.86 respectively, and similarly for the log-transformed streamflow up to 0.85 and 0.90. The parameterizations reproduced the flow duration curves, but predictive reliability in terms of quantile-quantile (Q-Q) plots indicated marked over and under predictions. The simple and parsimonious parameterizations with no subelement or no subgrid heterogeneities provided equivalent simulation performance compared to the more complex cases. The results indicated that (i) identification of parameterizations require measurements from denser precipitation stations than what is required for acceptable calibration of the precipitation-streamflow relationships, (ii) there is challenges in the identification of parameterizations based on only calibration to catchment integrated streamflow observations and (iii) a potential preference for the simple and parsimonious parameterizations for operational forecast contingent on their equivalent simulation performance for the available input data. In addition, the effects of non-identifiability of parameters (interactions and equifinality) can contribute to the non-identifiability of the

Comprehensive Performance Evaluation for Hydrological and Nutrients Simulation Using the Hydrological Simulation Program–Fortran in a Mesoscale Monsoon Watershed, China

PubMed Central

Luo, Chuan; Jiang, Kaixia; Wan, Rongrong; Li, Hengpeng

2017-01-01

The Hydrological Simulation Program–Fortran (HSPF) is a hydrological and water quality computer model that was developed by the United States Environmental Protection Agency. Comprehensive performance evaluations were carried out for hydrological and nutrient simulation using the HSPF model in the Xitiaoxi watershed in China. Streamflow simulation was calibrated from 1 January 2002 to 31 December 2007 and then validated from 1 January 2008 to 31 December 2010 using daily observed data, and nutrient simulation was calibrated and validated using monthly observed data during the period from July 2009 to July 2010. These results of model performance evaluation showed that the streamflows were well simulated over the study period. The determination coefficient (R2) was 0.87, 0.77 and 0.63, and the Nash-Sutcliffe coefficient of efficiency (Ens) was 0.82, 0.76 and 0.65 for the streamflow simulation in annual, monthly and daily time-steps, respectively. Although limited to monthly observed data, satisfactory performance was still achieved during the quantitative evaluation for nutrients. The R2 was 0.73, 0.82 and 0.92, and the Ens was 0.67, 0.74 and 0.86 for nitrate, ammonium and orthophosphate simulation, respectively. Some issues may affect the application of HSPF were also discussed, such as input data quality, parameter values, etc. Overall, the HSPF model can be successfully used to describe streamflow and nutrients transport in the mesoscale watershed located in the East Asian monsoon climate area. This study is expected to serve as a comprehensive and systematic documentation of understanding the HSPF model for wide application and avoiding possible misuses. PMID:29257117

In quest of axionic hairs in quasars

NASA Astrophysics Data System (ADS)

Banerjee, Indrani; Mandal, Bhaswati; SenGupta, Soumitra

2018-03-01

The presence of axionic field can provide plausible explanation to several long standing problems in physics such as dark matter and dark energy. The pseudo-scalar axion whose derivative corresponds to the Hodge dual of the Kalb-Ramond field strength in four dimensions plays crucial roles in explaining several astrophysical and cosmological observations. Therefore, the detection of axionic hairs/Kalb-Ramond field which appears as closed string excitations in the heterotic string spectrum may provide a profound insight to our understanding of the current universe. The current level of precision achieved in solar-system based tests employed to test general relativity, is not sufficient to detect the presence of axion. However, the near horizon regime of quasars where the curvature effects are maximum seems to be a natural laboratory to probe such additions to the matter sector. The continuum spectrum emitted from the accretion disk around quasars encapsulates the imprints of the background spacetime and hence acts as a storehouse of information regarding the nature of gravitational interaction in extreme situations. The surfeit of data available in the electromagnetic domain provides a further motivation to explore such systems. Using the optical data for eighty Palomar Green quasars we demonstrate that the theoretical estimates of optical luminosity explain the observations best when the axionic field is assumed to be absent. However, axion which violates the energy condition seems to be favored by observations which has several interesting consequences. Error estimators, including reduced χ2, Nash-Sutcliffe efficiency, index of agreement and modified versions of the last two are used to solidify our conclusion and the implications of our result are discussed.

Linking river, floodplain, and vadose zone hydrology to improve restoration of a coastal river affected by saltwater intrusion.

PubMed

Kaplan, D; Muñoz-Carpena, R; Wan, Y; Hedgepeth, M; Zheng, F; Roberts, R; Rossmanith, R

2010-01-01

Floodplain forests provide unique ecological structure and function, which are often degraded or lost when watershed hydrology is modified. Restoration of damaged ecosystems requires an understanding of surface water, groundwater, and vadose (unsaturated) zone hydrology in the floodplain. Soil moisture and porewater salinity are of particular importance for seed germination and seedling survival in systems affected by saltwater intrusion but are difficult to monitor and often overlooked. This study contributes to the understanding of floodplain hydrology in one of the last bald cypress [Taxodium distichum (L.) Rich.] floodplain swamps in southeast Florida. We investigated soil moisture and porewater salinity dynamics in the floodplain of the Loxahatchee River, where reduced freshwater flow has led to saltwater intrusion and a transition to salt-tolerant, mangrove-dominated communities. Twenty-four dielectric probes measuring soil moisture and porewater salinity every 30 min were installed along two transects-one in an upstream, freshwater location and one in a downstream tidal area. Complemented by surface water, groundwater, and meteorological data, these unique 4-yr datasets quantified the spatial variability and temporal dynamics of vadose zone hydrology. Results showed that soil moisture can be closely predicted based on river stage and topographic elevation (overall Nash-Sutcliffe coefficient of efficiency = 0.83). Porewater salinity rarely exceeded tolerance thresholds (0.3125 S m(-1)) for bald cypress upstream but did so in some downstream areas. This provided an explanation for observed vegetation changes that both surface water and groundwater salinity failed to explain. The results offer a methodological and analytical framework for floodplain monitoring in locations where restoration success depends on vadose zone hydrology and provide relationships for evaluating proposed restoration and management scenarios for the Loxahatchee River.

Statistical and Hydrological evaluation of precipitation forecasts from IMD MME and ECMWF numerical weather forecasts for Indian River basins

NASA Astrophysics Data System (ADS)

Mohite, A. R.; Beria, H.; Behera, A. K.; Chatterjee, C.; Singh, R.

2016-12-01

Flood forecasting using hydrological models is an important and cost-effective non-structural flood management measure. For forecasting at short lead times, empirical models using real-time precipitation estimates have proven to be reliable. However, their skill depreciates with increasing lead time. Coupling a hydrologic model with real-time rainfall forecasts issued from numerical weather prediction (NWP) systems could increase the lead time substantially. In this study, we compared 1-5 days precipitation forecasts from India Meteorological Department (IMD) Multi-Model Ensemble (MME) with European Center for Medium Weather forecast (ECMWF) NWP forecasts for over 86 major river basins in India. We then evaluated the hydrologic utility of these forecasts over Basantpur catchment (approx. 59,000 km2) of the Mahanadi River basin. Coupled MIKE 11 RR (NAM) and MIKE 11 hydrodynamic (HD) models were used for the development of flood forecast system (FFS). RR model was calibrated using IMD station rainfall data. Cross-sections extracted from SRTM 30 were used as input to the MIKE 11 HD model. IMD started issuing operational MME forecasts from the year 2008, and hence, both the statistical and hydrologic evaluation were carried out from 2008-2014. The performance of FFS was evaluated using both the NWP datasets separately for the year 2011, which was a large flood year in Mahanadi River basin. We will present figures and metrics for statistical (threshold based statistics, skill in terms of correlation and bias) and hydrologic (Nash Sutcliffe efficiency, mean and peak error statistics) evaluation. The statistical evaluation will be at pan-India scale for all the major river basins and the hydrologic evaluation will be for the Basantpur catchment of the Mahanadi River basin.

Assessing the Hydrologic Performance of the EPA's Nonpoint Source Water Quality Assessment Decision Support Tool Using North American Land Data Assimilation System (Products)

NASA Technical Reports Server (NTRS)

Lee, S.; Ni-Meister, W.; Toll, D.; Nigro, J.; Guiterrez-Magness, A.; Engman, T.

2010-01-01

The accuracy of streamflow predictions in the EPA's BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. The North American Land Data Assimilation System (NLDAS) data with high spatial and temporal resolutions provide an alternative to the NOAA National Climatic Data Center (NCDC)'s station data. This study assessed the improvement of streamflow prediction of the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS using the NLDAS 118 degree hourly precipitation and evapotranspiration estimates in seven watersheds of the Chesapeake Bay region. Our results demonstrated consistent improvements of daily streamflow predictions in five of the seven watersheds when NLDAS precipitation and evapotranspiration data was incorporated into BASINS. The improvement of using the NLDAS data is significant when watershed's meteorological station is either far away or not in a similar climatic region. When the station is nearby, using the NLDAS data produces similar results. The correlation coefficients of the analyses using the NLDAS data were greater than 0.8, the Nash-Sutcliffe (NS) model fit efficiency greater than 0.6, and the error in the water balance was less than 5%. Our analyses also showed that the streamflow improvements were mainly contributed by the NLDAS's precipitation data and that the improvement from using NLDAS's evapotranspiration data was not significant; partially due to the constraints of current BASINS-HSPF settings. However, NLDAS's evapotranspiration data did improve the baseflow prediction. This study demonstrates the NLDAS data has the potential to improve stream flow predictions, thus aid the water quality assessment in the EPA nonpoint water quality assessment decision tool.

Mathematical modeling of olive mill waste composting process.

PubMed

Vasiliadou, Ioanna A; Muktadirul Bari Chowdhury, Abu Khayer Md; Akratos, Christos S; Tekerlekopoulou, Athanasia G; Pavlou, Stavros; Vayenas, Dimitrios V

2015-09-01

The present study aimed at developing an integrated mathematical model for the composting process of olive mill waste. The multi-component model was developed to simulate the composting of three-phase olive mill solid waste with olive leaves and different materials as bulking agents. The modeling system included heat transfer, organic substrate degradation, oxygen consumption, carbon dioxide production, water content change, and biological processes. First-order kinetics were used to describe the hydrolysis of insoluble organic matter, followed by formation of biomass. Microbial biomass growth was modeled with a double-substrate limitation by hydrolyzed available organic substrate and oxygen using Monod kinetics. The inhibitory factors of temperature and moisture content were included in the system. The production and consumption of nitrogen and phosphorous were also included in the model. In order to evaluate the kinetic parameters, and to validate the model, six pilot-scale composting experiments in controlled laboratory conditions were used. Low values of hydrolysis rates were observed (0.002841/d) coinciding with the high cellulose and lignin content of the composting materials used. Model simulations were in good agreement with the experimental results. Sensitivity analysis was performed and the modeling efficiency was determined to further evaluate the model predictions. Results revealed that oxygen simulations were more sensitive on the input parameters of the model compared to those of water, temperature and insoluble organic matter. Finally, the Nash and Sutcliff index (E), showed that the experimental data of insoluble organic matter (E>0.909) and temperature (E>0.678) were better simulated than those of water. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comparison of HSPF and PRMS model simulated flows using different temporal and spatial scales in the Black Hills, South Dakota

USGS Publications Warehouse

Chalise, D. R.; Haj, Adel E.; Fontaine, T.A.

2018-01-01

The hydrological simulation program Fortran (HSPF) [Hydrological Simulation Program Fortran version 12.2 (Computer software). USEPA, Washington, DC] and the precipitation runoff modeling system (PRMS) [Precipitation Runoff Modeling System version 4.0 (Computer software). USGS, Reston, VA] models are semidistributed, deterministic hydrological tools for simulating the impacts of precipitation, land use, and climate on basin hydrology and streamflow. Both models have been applied independently to many watersheds across the United States. This paper reports the statistical results assessing various temporal (daily, monthly, and annual) and spatial (small versus large watershed) scale biases in HSPF and PRMS simulations using two watersheds in the Black Hills, South Dakota. The Nash-Sutcliffe efficiency (NSE), Pearson correlation coefficient (r">rr), and coefficient of determination (R2">R2R2) statistics for the daily, monthly, and annual flows were used to evaluate the models’ performance. Results from the HSPF models showed that the HSPF consistently simulated the annual flows for both large and small basins better than the monthly and daily flows, and the simulated flows for the small watershed better than flows for the large watershed. In comparison, the PRMS model results show that the PRMS simulated the monthly flows for both the large and small watersheds better than the daily and annual flows, and the range of statistical error in the PRMS models was greater than that in the HSPF models. Moreover, it can be concluded that the statistical error in the HSPF and the PRMSdaily, monthly, and annual flow estimates for watersheds in the Black Hills was influenced by both temporal and spatial scale variability.

Effects of uncertainties in hydrological modelling. A case study of a mountainous catchment in Southern Norway

NASA Astrophysics Data System (ADS)

Engeland, Kolbjørn; Steinsland, Ingelin; Johansen, Stian Solvang; Petersen-Øverleir, Asgeir; Kolberg, Sjur

2016-05-01

In this study, we explore the effect of uncertainty and poor observation quality on hydrological model calibration and predictions. The Osali catchment in Western Norway was selected as case study and an elevation distributed HBV-model was used. We systematically evaluated the effect of accounting for uncertainty in parameters, precipitation input, temperature input and streamflow observations. For precipitation and temperature we accounted for the interpolation uncertainty, and for streamflow we accounted for rating curve uncertainty. Further, the effects of poorer quality of precipitation input and streamflow observations were explored. Less information about precipitation was obtained by excluding the nearest precipitation station from the analysis, while reduced information about the streamflow was obtained by omitting the highest and lowest streamflow observations when estimating the rating curve. The results showed that including uncertainty in the precipitation and temperature inputs has a negligible effect on the posterior distribution of parameters and for the Nash-Sutcliffe (NS) efficiency for the predicted flows, while the reliability and the continuous rank probability score (CRPS) improves. Less information in precipitation input resulted in a shift in the water balance parameter Pcorr, a model producing smoother streamflow predictions, giving poorer NS and CRPS, but higher reliability. The effect of calibrating the hydrological model using streamflow observations based on different rating curves is mainly seen as variability in the water balance parameter Pcorr. When evaluating predictions, the best evaluation scores were not achieved for the rating curve used for calibration, but for rating curves giving smoother streamflow observations. Less information in streamflow influenced the water balance parameter Pcorr, and increased the spread in evaluation scores by giving both better and worse scores.

Integrating a reservoir regulation scheme into a spatially distributed hydrological model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Gang; Gao, Huilin; Naz, Bibi S.

2016-12-01

During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, natural streamflow timing and magnitude have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land use/land cover and climate changes. To understand the fine scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is of desire. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrologymore » Soil Vegetation Model (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM model was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficients of determination (R2) and the Nash-Sutcliff Efficiency (NSE) are 0.85 and 0.75, respectively. These results suggest that this reservoir module has promise for use in sub-monthly hydrological simulations. Enabled with the new reservoir component, the DHSVM model provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.« less

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.

Distributed Modelling of Stormflow Generation: Assessing the Effect of Ground Cover

NASA Astrophysics Data System (ADS)

Jarihani, B.; Sidle, R. C.; Roth, C. H.; Bartley, R.; Wilkinson, S. N.

2017-12-01

Understanding the effects of grazing management and land cover changes on surface hydrology is important for water resources and land management. A distributed hydrological modelling platform, wflow, (that was developed as part of Deltares's OpenStreams project) is used to assess the effect of land management practices on runoff generation processes. The model was applied to Weany Creek, a small catchment (13.6 km2) of the Burdekin Basin, North Australia, which is being studied to understand sources of sediment and nutrients to the Great Barrier Reef. Satellite and drone-based ground cover data, high resolution topography from LiDAR, soil properties, and distributed rainfall data were used to parameterise the model. Wflow was used to predict total runoff, peak runoff, time of rise, and lag time for several events of varying magnitudes and antecedent moisture conditions. A nested approach was employed to calibrate the model by using recorded flow hydrographs at three scales: (1) a hillslope sub-catchment: (2) a gullied sub-catchment; and the 13.6 km2 catchment outlet. Model performance was evaluated by comparing observed and predicted stormflow hydrograph attributes using the Nash Sutcliffe efficiency metric. By using a nested approach, spatiotemporal patterns of overland flow occurrence across the catchment can also be evaluated. The results show that a process-based distributed model can be calibrated to simulate spatial and temporal patterns of runoff generation processes, to help identify dominant processes which may be addressed by land management to improve rainfall retention. The model will be used to assess the effects of ground cover changes due to management practices in grazed lands on storm runoff.

Relative Linkages of Stream Dissolved Oxygen with the Hydroclimatic and Biogeochemical Drivers across the Gulf Coast of U.S.A.

NASA Astrophysics Data System (ADS)

Gebreslase, A. K.; Abdul-Aziz, O. I.

2017-12-01

Dynamics of coastal stream water quality is influenced by a multitude of interacting environmental drivers. A systematic data analytics approach was employed to determine the relative linkages of stream dissolved oxygen (DO) with the hydroclimatic and biogeochemical variables across the Gulf Coast of U.S.A. Multivariate pattern recognition techniques of PCA and FA, alongside Pearson's correlation matrix, were utilized to examine the interrelation of variables at 36 water quality monitoring stations from USGS NWIS and EPA STORET databases. Power-law based partial least square regression models with a bootstrap Monte Carlo procedure (1000 iterations) were developed to estimate the relative linkages of dissolved oxygen with the hydroclimatic and biogeochemical variables by appropriately resolving multicollinearity (Nash-Sutcliffe efficiency = 0.58-0.94). Based on the dominant drivers, stations were divided into four environmental regimes. Water temperature was the dominant driver of DO in the majority of streams, representing most the northern part of Gulf Coast states. However, streams in the southern part of Texas and Florida showed a dominant pH control on stream DO. Further, streams representing the transition zone of the two environmental regimes showed notable controls of multiple drivers (i.e., water temperature, stream flow, and specific conductance) on the stream DO. The data analytics research provided profound insight to understand the dynamics of stream DO with the hydroclimatic and biogeochemical variables. The knowledge can help water quality managers in formulating plans for effective stream water quality and watershed management in the U.S. Gulf Coast. Keywords Data analytics, coastal streams, relative linkages, dissolved oxygen, environmental regimes, Gulf Coast, United States.

Representing uncertainty in objective functions: extension to include the influence of serial correlation

NASA Astrophysics Data System (ADS)

Croke, B. F.

2008-12-01

The role of performance indicators is to give an accurate indication of the fit between a model and the system being modelled. As all measurements have an associated uncertainty (determining the significance that should be given to the measurement), performance indicators should take into account uncertainties in the observed quantities being modelled as well as in the model predictions (due to uncertainties in inputs, model parameters and model structure). In the presence of significant uncertainty in observed and modelled output of a system, failure to adequately account for variations in the uncertainties means that the objective function only gives a measure of how well the model fits the observations, not how well the model fits the system being modelled. Since in most cases, the interest lies in fitting the system response, it is vital that the objective function(s) be designed to account for these uncertainties. Most objective functions (e.g. those based on the sum of squared residuals) assume homoscedastic uncertainties. If model contribution to the variations in residuals can be ignored, then transformations (e.g. Box-Cox) can be used to remove (or at least significantly reduce) heteroscedasticity. An alternative which is more generally applicable is to explicitly represent the uncertainties in the observed and modelled values in the objective function. Previous work on this topic addressed the modifications to standard objective functions (Nash-Sutcliffe efficiency, RMSE, chi- squared, coefficient of determination) using the optimal weighted averaging approach. This paper extends this previous work; addressing the issue of serial correlation. A form for an objective function that includes serial correlation will be presented, and the impact on model fit discussed.

Agricultural Policy Environmental eXtender Simulation of Three Adjacent Row-Crop Watersheds in the Claypan Region.

PubMed

Anomaa Senaviratne, G M M M; Udawatta, Ranjith P; Baffaut, Claire; Anderson, Stephen H

2013-01-01

The Agricultural Policy Environmental Extender (APEX) model is used to evaluate best management practices on pollutant loading in whole farms or small watersheds. The objectives of this study were to conduct a sensitivity analysis to determine the effect of model parameters on APEX output and use the parameterized, calibrated, and validated model to evaluate long-term benefits of grass waterways. The APEX model was used to model three (East, Center, and West) adjacent field-size watersheds with claypan soils under a no-till corn ( L.)/soybean [ (L.) Merr.] rotation. Twenty-seven parameters were sensitive for crop yield, runoff, sediment, nitrogen (dissolved and total), and phosphorous (dissolved and total) simulations. The model was calibrated using measured event-based data from the Center watershed from 1993 to 1997 and validated with data from the West and East watersheds. Simulated crop yields were within ±13% of the measured yield. The model performance for event-based runoff was excellent, with calibration and validation > 0.9 and Nash-Sutcliffe coefficients (NSC) > 0.8, respectively. Sediment and total nitrogen calibration results were satisfactory for larger rainfall events (>50 mm), with > 0.5 and NSC > 0.4, but validation results remained poor, with NSC between 0.18 and 0.3. Total phosphorous was well calibrated and validated, with > 0.8 and NSC > 0.7, respectively. The presence of grass waterways reduced annual total phosphorus loadings by 13 to 25%. The replicated study indicates that APEX provides a convenient and efficient tool to evaluate long-term benefits of conservation practices. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Does the uncertainty in the representation of terrestrial water flows affect precipitation predictability? A WRF-Hydro ensemble analysis for Central Europe

NASA Astrophysics Data System (ADS)

Arnault, Joel; Rummler, Thomas; Baur, Florian; Lerch, Sebastian; Wagner, Sven; Fersch, Benjamin; Zhang, Zhenyu; Kerandi, Noah; Keil, Christian; Kunstmann, Harald

2017-04-01

Precipitation predictability can be assessed by the spread within an ensemble of atmospheric simulations being perturbed in the initial, lateral boundary conditions and/or modeled processes within a range of uncertainty. Surface-related processes are more likely to change precipitation when synoptic forcing is weak. This study investigates the effect of uncertainty in the representation of terrestrial water flows on precipitation predictability. The tools used for this investigation are the Weather Research and Forecasting (WRF) model and its hydrologically-enhanced version WRF-Hydro, applied over Central Europe during April-October 2008. The WRF grid is that of COSMO-DE, with a resolution of 2.8 km. In WRF-Hydro, the WRF grid is coupled with a sub-grid at 280 m resolution to resolve lateral terrestrial water flows. Vertical flow uncertainty is considered by modifying the parameter controlling the partitioning between surface runoff and infiltration in WRF, and horizontal flow uncertainty is considered by comparing WRF with WRF-Hydro. Precipitation predictability is deduced from the spread of an ensemble based on three turbulence parameterizations. Model results are validated with E-OBS precipitation and surface temperature, ESA-CCI soil moisture, FLUXNET-MTE surface evaporation and GRDC discharge. It is found that the uncertainty in the representation of terrestrial water flows is more likely to significantly affect precipitation predictability when surface flux spatial variability is high. In comparison to the WRF ensemble, WRF-Hydro slightly improves the adjusted continuous ranked probability score of daily precipitation. The reproduction of observed daily discharge with Nash-Sutcliffe model efficiency coefficients up to 0.91 demonstrates the potential of WRF-Hydro for flood forecasting.

The Water Availability Tool for Environmental Resources (WATER): A Water-Budget Modeling Approach for Managing Water-Supply Resources in Kentucky - Phase I: Data Processing, Model Development, and Application to Non-Karst Areas

USGS Publications Warehouse

Williamson, Tanja N.; Odom, Kenneth R.; Newson, Jeremy K.; Downs, Aimee C.; Nelson, Hugh L.; Cinotto, Peter J.; Ayers, Mark A.

2009-01-01

The Water Availability Tool for Environmental Resources (WATER) was developed in cooperation with the Kentucky Division of Water to provide a consistent and defensible method of estimating streamflow and water availability in ungaged basins. WATER is process oriented; it is based on the TOPMODEL code and incorporates historical water-use data together with physiographic data that quantitatively describe topography and soil-water storage. The result is a user-friendly decision tool that can estimate water availability in non-karst areas of Kentucky without additional data or processing. The model runs on a daily time step, and critical source data include a historical record of daily temperature and precipitation, digital elevation models (DEMs), the Soil Survey Geographic Database (SSURGO), and historical records of water discharges and withdrawals. The model was calibrated and statistically evaluated for 12 basins by comparing the estimated discharge to that observed at U.S. Geological Survey streamflow-gaging stations. When statistically evaluated over a 2,119-day time period, the discharge estimates showed a bias of -0.29 to 0.42, a root mean square error of 1.66 to 5.06, a correlation of 0.54 to 0.85, and a Nash-Sutcliffe Efficiency of 0.26 to 0.72. The parameter and input modifications that most significantly improved the accuracy and precision of streamflow-discharge estimates were the addition of Next Generation radar (NEXRAD) precipitation data, a rooting depth of 30 centimeters, and a TOPMODEL scaling parameter (m) derived directly from SSURGO data that was multiplied by an adjustment factor of 0.10. No site-specific optimization was used.

The Spontaneous Ray Log: A New Aid for Constructing Pseudo-Synthetic Seismograms

NASA Astrophysics Data System (ADS)

Quadir, Adnan; Lewis, Charles; Rau, Ruey-Juin

2018-02-01

Conventional synthetic seismograms for hydrocarbon exploration combine the sonic and density logs, whereas pseudo-synthetic seismograms are constructed with a density log plus a resistivity, neutron, gamma ray, or rarely a spontaneous potential log. Herein, we introduce a new technique for constructing a pseudo-synthetic seismogram by combining the gamma ray (GR) and self-potential (SP) logs to produce the spontaneous ray (SR) log. Three wells, each of which consisted of more than 1000 m of carbonates, sandstones, and shales, were investigated; each well was divided into 12 Groups based on formation tops, and the Pearson product-moment correlation coefficient (PCC) was calculated for each "Group" from each of the GR, SP, and SR logs. The highest PCC-valued log curves for each Group were then combined to produce a single log whose values were cross-plotted against the reference well's sonic ITT values to determine a linear transform for producing a pseudo-sonic (PS) log and, ultimately, a pseudo-synthetic seismogram. The range for the Nash-Sutcliffe efficiency (NSE) acceptable value for the pseudo-sonic logs of three wells was 78-83%. This technique was tested on three wells, one of which was used as a blind test well, with satisfactory results. The PCC value between the composite PS (SR) log with low-density correction and the conventional sonic (CS) log was 86%. Because of the common occurrence of spontaneous potential and gamma ray logs in many of the hydrocarbon basins of the world, this inexpensive and straightforward technique could hold significant promise in areas that are in need of alternate ways to create pseudo-synthetic seismograms for seismic reflection interpretation.

Impacts of spatial resolution and representation of flow connectivity on large-scale simulation of floods

NASA Astrophysics Data System (ADS)

Mateo, Cherry May R.; Yamazaki, Dai; Kim, Hyungjun; Champathong, Adisorn; Vaze, Jai; Oki, Taikan

2017-10-01

Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large- to global-scale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

Is there a `universal' dynamic zero-parameter hydrological model? Evaluation of a dynamic Budyko model in US and India

NASA Astrophysics Data System (ADS)

Patnaik, S.; Biswal, B.; Sharma, V. C.

2017-12-01

River flow varies greatly in space and time, and the single biggest challenge for hydrologists and ecologists around the world is the fact that most rivers are either ungauged or poorly gauged. Although it is relatively easier to predict long-term average flow of a river using the `universal' zero-parameter Budyko model, lack of data hinders short-term flow prediction at ungauged locations using traditional hydrological models as they require observed flow data for model calibration. Flow prediction in ungauged basins thus requires a dynamic 'zero-parameter' hydrological model. One way to achieve this is to regionalize a dynamic hydrological model's parameters. However, a regionalization method based zero-parameter dynamic hydrological model is not `universal'. An alternative attempt was made recently to develop a zero-parameter dynamic model by defining an instantaneous dryness index as a function of antecedent rainfall and solar energy inputs with the help of a decay function and using the original Budyko function. The model was tested first in 63 US catchments and later in 50 Indian catchments. The median Nash-Sutcliffe efficiency (NSE) was found to be close to 0.4 in both the cases. Although improvements need to be incorporated in order to use the model for reliable prediction, the main aim of this study was to rather understand hydrological processes. The overall results here seem to suggest that the dynamic zero-parameter Budyko model is `universal.' In other words natural catchments around the world are strikingly similar to each other in the way they respond to hydrologic inputs; we thus need to focus more on utilizing catchment similarities in hydrological modelling instead of over parameterizing our models.

Improved Algorithm of SCS-CN Model Parameters in Typical Inland River Basin in Central Asia

NASA Astrophysics Data System (ADS)

Wang, Jin J.; Ding, Jian L.; Zhang, Zhe; Chen, Wen Q.

2017-02-01

Rainfall-runoff relationship is the most important factor for hydrological structures, social and economic development on the background of global warmer, especially in arid regions. The aim of this paper is find the suitable method to simulate the runoff in arid area. The Soil Conservation Service Curve Number (SCS-CN) is the most popular and widely applied model for direct runoff estimation. In this paper, we will focus on Wen-quan Basin in source regions of Boertala River. It is a typical valley of inland in Central Asia. First time to use the 16m resolution remote sensing image about high-definition earth observation satellite “Gaofen-1” to provide a high degree accuracy data for land use classification determine the curve number. Use surface temperature/vegetation index (TS/VI) construct 2D scatter plot combine with the soil moisture absorption balance principle calculate the moisture-holding capacity of soil. Using original and parameter algorithm improved SCS-CN model respectively to simulation the runoff. The simulation results show that the improved model is better than original model. Both of them in calibration and validation periods Nash-Sutcliffe efficiency were 0.79, 0.71 and 0.66,038. And relative error were3%, 12% and 17%, 27%. It shows that the simulation accuracy should be further improved and using remote sensing information technology to improve the basic geographic data for the hydrological model has the following advantages: 1) Remote sensing data having a planar characteristic, comprehensive and representative. 2) To get around the bottleneck about lack of data, provide reference to simulation the runoff in similar basin conditions and data-lacking regions.

Ecologically-focused Calibration of Hydrological Models for Environmental Flow Applications

NASA Astrophysics Data System (ADS)

Adams, S. K.; Bledsoe, B. P.

2015-12-01

Hydrologic alteration resulting from watershed urbanization is a common cause of aquatic ecosystem degradation. Developing environmental flow criteria for urbanizing watersheds requires quantitative flow-ecology relationships that describe biological responses to streamflow alteration. Ideally, gaged flow data are used to develop flow-ecology relationships; however, biological monitoring sites are frequently ungaged. For these ungaged locations, hydrologic models must be used to predict streamflow characteristics through calibration and testing at gaged sites, followed by extrapolation to ungaged sites. Physically-based modeling of rainfall-runoff response has frequently utilized "best overall fit" calibration criteria, such as the Nash-Sutcliffe Efficiency (NSE), that do not necessarily focus on specific aspects of the flow regime relevant to biota of interest. This study investigates the utility of employing flow characteristics known a priori to influence regional biological endpoints as "ecologically-focused" calibration criteria compared to traditional, "best overall fit" criteria. For this study, 19 continuous HEC-HMS 4.0 models were created in coastal southern California and calibrated to hourly USGS streamflow gages with nearby biological monitoring sites using one "best overall fit" and three "ecologically-focused" criteria: NSE, Richards-Baker Flashiness Index (RBI), percent of time when the flow is < 1 cfs (%<1), and a Combined Calibration (RBI and %<1). Calibrated models were compared using calibration accuracy, environmental flow metric reproducibility, and the strength of flow-ecology relationships. Results indicate that "ecologically-focused" criteria can be calibrated with high accuracy and may provide stronger flow-ecology relationships than "best overall fit" criteria, especially when multiple "ecologically-focused" criteria are used in concert, despite inabilities to accurately reproduce additional types of ecological flow metrics to which the

Testing the Wisconsin Phosphorus Index with year-round, field-scale runoff monitoring.

PubMed

Good, Laura W; Vadas, Peter; Panuska, John C; Bonilla, Carlos A; Jokela, William E

2012-01-01

The Wisconsin Phosphorus Index (WPI) is one of several P indices in the United States that use equations to describe actual P loss processes. Although for nutrient management planning the WPI is reported as a dimensionless whole number, it is calculated as average annual dissolved P (DP) and particulate P (PP) mass delivered per unit area. The WPI calculations use soil P concentration, applied manure and fertilizer P, and estimates of average annual erosion and average annual runoff. We compared WPI estimated P losses to annual P loads measured in surface runoff from 86 field-years on crop fields and pastures. As the erosion and runoff generated by the weather in the monitoring years varied substantially from the average annual estimates used in the WPI, the WPI and measured loads were not well correlated. However, when measured runoff and erosion were used in the WPI field loss calculations, the WPI accurately estimated annual total P loads with a Nash-Sutcliffe Model Efficiency (NSE) of 0.87. The DP loss estimates were not as close to measured values (NSE = 0.40) as the PP loss estimates (NSE = 0.89). Some errors in estimating DP losses may be unavoidable due to uncertainties in estimating on-farm manure P application rates. The WPI is sensitive to field management that affects its erosion and runoff estimates. Provided that the WPI methods for estimating average annual erosion and runoff are accurately reflecting the effects of management, the WPI is an accurate field-level assessment tool for managing runoff P losses. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Coupled Surface and Groundwater Hydrological Modeling in a Changing Climate.

PubMed

Sridhar, Venkataramana; Billah, Mirza M; Hildreth, John W

2017-11-09

Many current watershed modeling efforts now incorporate surface water and groundwater for managing water resources since the exchanges between groundwater and surface water need a special focus considering the changing climate. The influence of groundwater dynamics on water and energy balance components is investigated in the Snake River Basin (SRB) by coupling the Variable Infiltration Capacity (VIC) and MODFLOW models (VIC-MF) for the period of 1986 through 2042. A 4.4% increase in base flows and a 10.3% decrease in peak flows are estimated by VIC-MF compared to the VIC model in SRB. The VIC-MF model shows significant improvement in the streamflow simulation (Nash-Sutcliffe efficiency [NSE] of 0.84) at King Hill, where the VIC model could not capture the effect of spring discharge in the streamflow simulation (NSE of -0.30); however, the streamflow estimates show an overall decreasing trend. Two climate scenarios representing median and high radiative-forcings such as representative concentration pathways 4.5 and 8.5 show an average increase in the water table elevations between 2.1 and 2.6 m (6.9 and 8.5 feet) through the year 2042. The spatial patterns of these exchanges show a higher groundwater elevation of 15 m (50 feet) in the downstream area and a lower elevation of up to 3 m (10 feet) in the upstream area. Broadly, this study supports results of previous work demonstrating that integrated assessment of groundwater-surface water enables stakeholders to balance pumping, recharge and base flow needs and to manage the watersheds that are subjected to human pressures more sustainably. © 2017, National Ground Water Association.

Coupled long term simulation of reach scale water and heat fluxes across the river groundwater interface and hyporheic temperature dynamics

NASA Astrophysics Data System (ADS)

Munz, Matthias; Oswald, Sascha E.; Schmidt, Christian

2017-04-01

Flow pattern and seasonal as well as diurnal temperature variations control ecological and biogeochemical conditions in hyporheic sediments. In particular, hyporheic temperatures have a great impact on many microbial processes. In this study we used 3-D coupled water flow and heat transport simulations applying the HydroGeoSphere code in combination with high frequent observations of hydraulic heads and temperatures for quantifying reach scale water and heat flux across the river groundwater interface and hyporheic temperature dynamics of a lowland gravel-bed river. The magnitude and dynamics of simulated temperatures matched the observed with an average mean absolute error of 0.7 °C and an average Nash Sutcliffe Efficiency of 0.87. Our results highlight that the average temperature in the hyporheic zone follows the temperature in the river which is characterized by distinct seasonal and daily temperature cycles. Individual hyporheic flow path temperature substantially varies around the average hyporheic temperature. Hyporheic flow path temperature was found to strongly depend on the flow path residence time and the temperature gradient between river and groundwater; that is, in winter the average flow path temperature of long flow paths is potentially higher compared to short flow paths. Based on the simulation results we derived a general empirical relationship, estimating the influence of hyporheic flow path residence time on hyporheic flow path temperature. Furthermore we used an empirical temperature relationship between effective temperature and respiration rate to estimate the influence of hyporheic flow path residence time and temperature on hyporheic oxygen consumption. This study highlights the relation between complex hyporheic temperature patterns, hyporheic residence times and their implications on temperature sensitive biogeochemical processes.

Coupled Long-Term Simulation of Reach-Scale Water and Heat Fluxes Across the River-Groundwater Interface for Retrieving Hyporheic Residence Times and Temperature Dynamics

NASA Astrophysics Data System (ADS)

Munz, Matthias; Oswald, Sascha E.; Schmidt, Christian

2017-11-01

Flow patterns in conjunction with seasonal and diurnal temperature variations control ecological and biogeochemical conditions in hyporheic sediments. In particular, hyporheic temperatures have a great impact on many temperature-sensitive microbial processes. In this study, we used 3-D coupled water flow and heat transport simulations applying the HydroGeoSphere code in combination with high-resolution observations of hydraulic heads and temperatures to quantify reach-scale water and heat flux across the river-groundwater interface and hyporheic temperature dynamics of a lowland gravel bed river. The model was calibrated in order to constrain estimates of the most sensitive model parameters. The magnitude and variations of the simulated temperatures matched the observed ones, with an average mean absolute error of 0.7°C and an average Nash Sutcliffe efficiency of 0.87. Our results indicate that nonsubmerged streambed structures such as gravel bars cause substantial thermal heterogeneity within the saturated sediment at the reach scale. Individual hyporheic flow path temperatures strongly depend on the flow path residence time, flow path depth, river, and groundwater temperature. Variations in individual hyporheic flow path temperatures were up to 7.9°C, significantly higher than the daily average (2.8°C), but still lower than the average seasonal hyporheic temperature difference (19.2°C). The distribution between flow path temperatures and residence times follows a power law relationship with exponent of about 0.37. Based on this empirical relation, we further estimated the influence of hyporheic flow path residence time and temperature on oxygen consumption which was found to partly increase by up to 29% in simulations.

Relative Linkages of Chlorophyll-a with the Hydroclimatic and Biogeochemical Variables across the Continental U.S. (CONUS)

NASA Astrophysics Data System (ADS)

Ahmed, M. H.; Abdul-Aziz, O. I.

2017-12-01

Chlorophyll-a (Chl-a) is a key indicator for stream water quality and ecological health. The characterization of interplay between Chl-a and its numerous hydroclimatic and biogeochemical drivers is complex, and often involves multicollinear datasets. A systematic data analytics methodology was employed to determine the relative linkages of stream Chl-a with its dynamic environmental drivers at 50 stream water quality monitoring stations across the continental U.S. Multivariate statistical techniques of principal component analysis (PCA) and factor analysis (FA), in concert with Pearson correlation analysis, were applied to evaluate interrelationships among hydroclimatic, biogeochemical, and biological variables. Power-law based partial least square regression (PLSR) models were developed with a bootstrap Monte Carlo procedure (1000 iterations) to reliably estimate the comparative linkages of Chl-a by resolving multicollinearity in the data matrices (Nash-Sutcliff efficiency = 0.50-87). The data analytics suggested four environmental regimes of stream Chl-a, as dominated by nutrient, climate, redox, and hydro-atmospheric contributions, respectively. Total phosphorous (TP) was the most dominant driver of stream Chl-a in the nutrient controlled regime. Water temperature demonstrated the strongest control of Chl-a in the climate-dominated regime. Furthermore, pH and stream flow were found to be the most important drivers of Chl-a in the redox and hydro-atmospheric component dominated regimes, respectively. The research led to a significant reduction of dimensionality in the large data matrices, providing quantitative and qualitative insights on the dynamics of stream Chl-a. The findings would be useful to manage stream water quality and ecosystem health in the continental U.S. and around the world under a changing climate and environment.

Free internet datasets for streamflow modelling using SWAT in the Johor river basin, Malaysia

NASA Astrophysics Data System (ADS)

Tan, M. L.

2014-02-01

Streamflow modelling is a mathematical computational approach that represents terrestrial hydrology cycle digitally and is used for water resources assessment. However, such modelling endeavours require a large amount of data. Generally, governmental departments produce and maintain these data sets which make it difficult to obtain this data due to bureaucratic constraints. In some countries, the availability and quality of geospatial and climate datasets remain a critical issue due to many factors such as lacking of ground station, expertise, technology, financial support and war time. To overcome this problem, this research used public domain datasets from the Internet as "input" to a streamflow model. The intention is simulate daily and monthly streamflow of the Johor River Basin in Malaysia. The model used is the Soil and Water Assessment Tool (SWAT). As input free data including a digital elevation model (DEM), land use information, soil and climate data were used. The model was validated by in-situ streamflow information obtained from Rantau Panjang station for the year 2006. The coefficient of determination and Nash-Sutcliffe efficiency were 0.35/0.02 for daily simulated streamflow and 0.92/0.21 for monthly simulated streamflow, respectively. The results show that free data can provide a better simulation at a monthly scale compared to a daily basis in a tropical region. A sensitivity analysis and calibration procedure should be conducted in order to maximize the "goodness-of-fit" between simulated and observed streamflow. The application of Internet datasets promises an acceptable performance of streamflow modelling. This research demonstrates that public domain data is suitable for streamflow modelling in a tropical river basin within acceptable accuracy.

Predicting long-term streamflow variability in moist eucalypt forests using forest growth models and a sapwood area index

NASA Astrophysics Data System (ADS)

Jaskierniak, D.; Kuczera, G.; Benyon, R.

2016-04-01

A major challenge in surface hydrology involves predicting streamflow in ungauged catchments with heterogeneous vegetation and spatiotemporally varying evapotranspiration (ET) rates. We present a top-down approach for quantifying the influence of broad-scale changes in forest structure on ET and hence streamflow. Across three catchments between 18 and 100 km2 in size and with regenerating Eucalyptus regnans and E. delegatensis forest, we demonstrate how variation in ET can be mapped in space and over time using LiDAR data and commonly available forest inventory data. The model scales plot-level sapwood area (SA) to the catchment-level using basal area (BA) and tree stocking density (N) estimates in forest growth models. The SA estimates over a 69 year regeneration period are used in a relationship between SA and vegetation induced streamflow loss (L) to predict annual streamflow (Q) with annual rainfall (P) estimates. Without calibrating P, BA, N, SA, and L to Q data, we predict annual Q with R2 between 0.68 and 0.75 and Nash Sutcliffe efficiency (NSE) between 0.44 and 0.48. To remove bias, the model was extended to allow for runoff carry-over into the following year as well as minor correction to rainfall bias, which produced R2 values between 0.72 and 0.79, and NSE between 0.70 and 0.79. The model under-predicts streamflow during drought periods as it lacks representation of ecohydrological processes that reduce L with either reduced growth rates or rainfall interception during drought. Refining the relationship between sapwood thickness and forest inventory variables is likely to further improve results.

Simulation of green roof runoff under different substrate depths and vegetation covers by coupling a simple conceptual and a physically based hydrological model.

PubMed

Soulis, Konstantinos X; Valiantzas, John D; Ntoulas, Nikolaos; Kargas, George; Nektarios, Panayiotis A

2017-09-15

In spite of the well-known green roof benefits, their widespread adoption in the management practices of urban drainage systems requires the use of adequate analytical and modelling tools. In the current study, green roof runoff modeling was accomplished by developing, testing, and jointly using a simple conceptual model and a physically based numerical simulation model utilizing HYDRUS-1D software. The use of such an approach combines the advantages of the conceptual model, namely simplicity, low computational requirements, and ability to be easily integrated in decision support tools with the capacity of the physically based simulation model to be easily transferred in conditions and locations other than those used for calibrating and validating it. The proposed approach was evaluated with an experimental dataset that included various green roof covers (either succulent plants - Sedum sediforme, or xerophytic plants - Origanum onites, or bare substrate without any vegetation) and two substrate depths (either 8 cm or 16 cm). Both the physically based and the conceptual models matched very closely the observed hydrographs. In general, the conceptual model performed better than the physically based simulation model but the overall performance of both models was sufficient in most cases as it is revealed by the Nash-Sutcliffe Efficiency index which was generally greater than 0.70. Finally, it was showcased how a physically based and a simple conceptual model can be jointly used to allow the use of the simple conceptual model for a wider set of conditions than the available experimental data and in order to support green roof design. Copyright © 2017 Elsevier Ltd. All rights reserved.

Integrating a reservoir regulation scheme into a spatially distributed hydrological model

DOE PAGES

Zhao, Gang; Gao, Huili; Naz, Bibi S; ...

2016-10-14

During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, timing and magnitude of natural streamflows have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land-use/land-cover and climate changes. To understand the fine-scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is desired. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrology Soil Vegetation Modelmore » (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficient of determination (R 2) and the Nash-Sutcliff Efficiency (NSE) were 0.85 and 0.75, respectively. These results suggest that this reservoir module holds promise for use in sub-monthly hydrological simulations. Furthermore, with the new reservoir component, the DHSVM provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.« less

Integrating a reservoir regulation scheme into a spatially distributed hydrological model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Gang; Gao, Huili; Naz, Bibi S

During the past several decades, numerous reservoirs have been built across the world for a variety of purposes such as flood control, irrigation, municipal/industrial water supplies, and hydropower generation. Consequently, timing and magnitude of natural streamflows have been altered significantly by reservoir operations. In addition, the hydrological cycle can be modified by land-use/land-cover and climate changes. To understand the fine-scale feedback between hydrological processes and water management decisions, a distributed hydrological model embedded with a reservoir component is desired. In this study, a multi-purpose reservoir module with predefined complex operational rules was integrated into the Distributed Hydrology Soil Vegetation Modelmore » (DHSVM). Conditional operating rules, which are designed to reduce flood risk and enhance water supply reliability, were adopted in this module. The performance of the integrated model was tested over the upper Brazos River Basin in Texas, where two U.S. Army Corps of Engineers reservoirs, Lake Whitney and Aquilla Lake, are located. The integrated DHSVM was calibrated and validated using observed reservoir inflow, outflow, and storage data. The error statistics were summarized for both reservoirs on a daily, weekly, and monthly basis. Using the weekly reservoir storage for Lake Whitney as an example, the coefficient of determination (R 2) and the Nash-Sutcliff Efficiency (NSE) were 0.85 and 0.75, respectively. These results suggest that this reservoir module holds promise for use in sub-monthly hydrological simulations. Furthermore, with the new reservoir component, the DHSVM provides a platform to support adaptive water resources management under the impacts of evolving anthropogenic activities and substantial environmental changes.« less

Comprehensive evaluation of Ensemble Multi-Satellite Precipitation Dataset using the Dynamic Bayesian Model Averaging scheme over the Tibetan plateau

NASA Astrophysics Data System (ADS)

Ma, Yingzhao; Yang, Yuan; Han, Zhongying; Tang, Guoqiang; Maguire, Lane; Chu, Zhigang; Hong, Yang

2018-01-01

The objective of this study is to comprehensively evaluate the new Ensemble Multi-Satellite Precipitation Dataset using the Dynamic Bayesian Model Averaging scheme (EMSPD-DBMA) at daily and 0.25° scales from 2001 to 2015 over the Tibetan Plateau (TP). Error analysis against gauge observations revealed that EMSPD-DBMA captured the spatiotemporal pattern of daily precipitation with an acceptable Correlation Coefficient (CC) of 0.53 and a Relative Bias (RB) of -8.28%. Moreover, EMSPD-DBMA outperformed IMERG and GSMaP-MVK in almost all metrics in the summers of 2014 and 2015, with the lowest RB and Root Mean Square Error (RMSE) values of -2.88% and 8.01 mm/d, respectively. It also better reproduced the Probability Density Function (PDF) in terms of daily rainfall amount and estimated moderate and heavy rainfall better than both IMERG and GSMaP-MVK. Further, hydrological evaluation with the Coupled Routing and Excess STorage (CREST) model in the Upper Yangtze River region indicated that the EMSPD-DBMA forced simulation showed satisfying hydrological performance in terms of streamflow prediction, with Nash-Sutcliffe coefficient of Efficiency (NSE) values of 0.82 and 0.58, compared to gauge forced simulation (0.88 and 0.60) at the calibration and validation periods, respectively. EMSPD-DBMA also performed a greater fitness for peak flow simulation than a new Multi-Source Weighted-Ensemble Precipitation Version 2 (MSWEP V2) product, indicating a promising prospect of hydrological utility for the ensemble satellite precipitation data. This study belongs to early comprehensive evaluation of the blended multi-satellite precipitation data across the TP, which would be significant for improving the DBMA algorithm in regions with complex terrain.

Evaluating Snow Data Assimilation Framework for Streamflow Forecasting Applications Using Hindcast Verification

NASA Astrophysics Data System (ADS)

Barik, M. G.; Hogue, T. S.; Franz, K. J.; He, M.

2012-12-01

Snow water equivalent (SWE) estimation is a key factor in producing reliable streamflow simulations and forecasts in snow dominated areas. However, measuring or predicting SWE has significant uncertainty. Sequential data assimilation, which updates states using both observed and modeled data based on error estimation, has been shown to reduce streamflow simulation errors but has had limited testing for forecasting applications. In the current study, a snow data assimilation framework integrated with the National Weather System River Forecasting System (NWSRFS) is evaluated for use in ensemble streamflow prediction (ESP). Seasonal water supply ESP hindcasts are generated for the North Fork of the American River Basin (NFARB) in northern California. Parameter sets from the California Nevada River Forecast Center (CNRFC), the Differential Evolution Adaptive Metropolis (DREAM) algorithm and the Multistep Automated Calibration Scheme (MACS) are tested both with and without sequential data assimilation. The traditional ESP method considers uncertainty in future climate conditions using historical temperature and precipitation time series to generate future streamflow scenarios conditioned on the current basin state. We include data uncertainty analysis in the forecasting framework through the DREAM-based parameter set which is part of a recently developed Integrated Uncertainty and Ensemble-based data Assimilation framework (ICEA). Extensive verification of all tested approaches is undertaken using traditional forecast verification measures, including root mean square error (RMSE), Nash-Sutcliffe efficiency coefficient (NSE), volumetric bias, joint distribution, rank probability score (RPS), and discrimination and reliability plots. In comparison to the RFC parameters, the DREAM and MACS sets show significant improvement in volumetric bias in flow. Use of assimilation improves hindcasts of higher flows but does not significantly improve performance in the mid flow and

Comprehensive Performance Evaluation for Hydrological and Nutrients Simulation Using the Hydrological Simulation Program-Fortran in a Mesoscale Monsoon Watershed, China.

PubMed

Li, Zhaofu; Luo, Chuan; Jiang, Kaixia; Wan, Rongrong; Li, Hengpeng

2017-12-19

The Hydrological Simulation Program-Fortran (HSPF) is a hydrological and water quality computer model that was developed by the United States Environmental Protection Agency. Comprehensive performance evaluations were carried out for hydrological and nutrient simulation using the HSPF model in the Xitiaoxi watershed in China. Streamflow simulation was calibrated from 1 January 2002 to 31 December 2007 and then validated from 1 January 2008 to 31 December 2010 using daily observed data, and nutrient simulation was calibrated and validated using monthly observed data during the period from July 2009 to July 2010. These results of model performance evaluation showed that the streamflows were well simulated over the study period. The determination coefficient ( R ²) was 0.87, 0.77 and 0.63, and the Nash-Sutcliffe coefficient of efficiency (Ens) was 0.82, 0.76 and 0.65 for the streamflow simulation in annual, monthly and daily time-steps, respectively. Although limited to monthly observed data, satisfactory performance was still achieved during the quantitative evaluation for nutrients. The R ² was 0.73, 0.82 and 0.92, and the Ens was 0.67, 0.74 and 0.86 for nitrate, ammonium and orthophosphate simulation, respectively. Some issues may affect the application of HSPF were also discussed, such as input data quality, parameter values, etc. Overall, the HSPF model can be successfully used to describe streamflow and nutrients transport in the mesoscale watershed located in the East Asian monsoon climate area. This study is expected to serve as a comprehensive and systematic documentation of understanding the HSPF model for wide application and avoiding possible misuses.

How would peak rainfall intensity affect runoff predictions using conceptual water balance models?

NASA Astrophysics Data System (ADS)

Yu, B.

2015-06-01

Most hydrological models use continuous daily precipitation and potential evapotranspiration for streamflow estimation. With the projected increase in mean surface temperature, hydrological processes are set to intensify irrespective of the underlying changes to the mean precipitation. The effect of an increase in rainfall intensity on the long-term water balance is, however, not adequately accounted for in the commonly used hydrological models. This study follows from a previous comparative analysis of a non-stationary daily series of stream flow of a forested watershed (River Rimbaud) in the French Alps (area = 1.478 km2) (1966-2006). Non-stationarity in the recorded stream flow occurred as a result of a severe wild fire in 1990. Two daily models (AWBM and SimHyd) were initially calibrated for each of three distinct phases in relation to the well documented land disturbance. At the daily and monthly time scales, both models performed satisfactorily with the Nash-Sutcliffe coefficient of efficiency (NSE) varying from 0.77 to 0.92. When aggregated to the annual time scale, both models underestimated the flow by about 22% with a reduced NSE at about 0.71. Exploratory data analysis was undertaken to relate daily peak hourly rainfall intensity to the discrepancy between the observed and modelled daily runoff amount. Preliminary results show that the effect of peak hourly rainfall intensity on runoff prediction is insignificant, and model performance is unlikely to improve when peak daily precipitation is included. Trend analysis indicated that the large decrease of precipitation when daily precipitation amount exceeded 10-20 mm may have contributed greatly to the decrease in stream flow of this forested watershed.

Anopheles atroparvus density modeling using MODIS NDVI in a former malarious area in Portugal.

PubMed

Lourenço, Pedro M; Sousa, Carla A; Seixas, Júlia; Lopes, Pedro; Novo, Maria T; Almeida, A Paulo G

2011-12-01

Malaria is dependent on environmental factors and considered as potentially re-emerging in temperate regions. Remote sensing data have been used successfully for monitoring environmental conditions that influence the patterns of such arthropod vector-borne diseases. Anopheles atroparvus density data were collected from 2002 to 2005, on a bimonthly basis, at three sites in a former malarial area in Southern Portugal. The development of the Remote Vector Model (RVM) was based upon two main variables: temperature and the Normalized Differential Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite. Temperature influences the mosquito life cycle and affects its intra-annual prevalence, and MODIS NDVI was used as a proxy for suitable habitat conditions. Mosquito data were used for calibration and validation of the model. For areas with high mosquito density, the model validation demonstrated a Pearson correlation of 0.68 (p<0.05) and a modelling efficiency/Nash-Sutcliffe of 0.44 representing the model's ability to predict intra- and inter-annual vector density trends. RVM estimates the density of the former malarial vector An. atroparvus as a function of temperature and of MODIS NDVI. RVM is a satellite data-based assimilation algorithm that uses temperature fields to predict the intra- and inter-annual densities of this mosquito species using MODIS NDVI. RVM is a relevant tool for vector density estimation, contributing to the risk assessment of transmission of mosquito-borne diseases and can be part of the early warning system and contingency plans providing support to the decision making process of relevant authorities. © 2011 The Society for Vector Ecology.

Epilepsy management in older people: Lessons from National Audit of Seizure management in Hospitals (NASH).

PubMed

Ziso, B; Dixon, P A; Marson, A G

2017-08-01

Epilepsy is the third most common diagnosis in older people, however management in this group remains variable. National Audit of Seizure management in Hospitals (NASH) set out to assess care provided to patients attending hospitals in England following a seizure. 154 Emergency Departments (EDs) across the UK took part. 1256 patients aged 60 years or over were included for analysis (median age 74 years, 54% men). 51% were known to have epilepsy, 17% had history of previous seizure or blackout and 32% presented with a suspected first seizure. 14% of older patients with epilepsy were not on treatment, 59% were on monotherapy. Sodium valproate was the most commonly used antiepileptic, 28%. 35% of patients with epilepsy, aged 60 and over, had a CT during admission compared to only 17% of those under 60. 80% of patients aged 60 and over presenting with a likely first seizure were admitted to hospital, compared to 65% of those under 60. 34% of those with suspected first seizure were referred to a neurologist on discharge compared to 68% of patients under the age of 60. 52% of 60-69year olds with a suspected first seizure were referred to neurology compared to 25% of patients aged 80-89. Older patients presenting with seizures are more likely to be admitted to hospital and have imaging. They are less likely to be referred to specialist services on discharge. There appears to be significant disparity in patient age and rate of referral. Crown Copyright © 2017. Published by Elsevier Ltd. All rights reserved.

On a numerical solving of random generated hexamatrix games

NASA Astrophysics Data System (ADS)

Orlov, Andrei; Strekalovskiy, Alexander

2016-10-01

In this paper, we develop a global search method for finding a Nash equilibrium in a hexamatrix game (polymatrix game of three players). The method, on the one hand, is based on the equivalence theorem of the problem of finding a Nash equilibrium in the game and a special mathematical optimization problem, and, on the other hand, on the usage of Global Search Theory for solving the latter problem. The efficiency of this approach is demonstrated by the results of computational testing.

Nash and integrated solutions in a just-in-time seller-buyer supply chain with buyer's ordering cost reductions

NASA Astrophysics Data System (ADS)

Lou, Kuo-Ren; Wang, Lu

2016-05-01

The seller frequently offers the buyer trade credit to settle the purchase amount. From the seller's prospective, granting trade credit increases not only the opportunity cost (i.e., the interest loss on the buyer's purchase amount during the credit period) but also the default risk (i.e., the rate that the buyer will be unable to pay off his/her debt obligations). On the other hand, granting trade credit increases sales volume and revenue. Consequently, trade credit is an important strategy to increase seller's profitability. In this paper, we assume that the seller uses trade credit and number of shipments in a production run as decision variables to maximise his/her profit, while the buyer determines his/her replenishment cycle time and capital investment as decision variables to reduce his/her ordering cost and achieve his/her maximum profit. We then derive non-cooperative Nash solution and cooperative integrated solution in a just-in-time inventory system, in which granting trade credit increases not only the demand but also the opportunity cost and default risk, and the relationship between the capital investment and the ordering cost reduction is logarithmic. Then, we use a software to solve and compare these two distinct solutions. Finally, we use sensitivity analysis to obtain some managerial insights.

Auction-based distributed efficient economic operations of microgrid systems

NASA Astrophysics Data System (ADS)

Zou, Suli; Ma, Zhongjing; Liu, Xiangdong

2014-12-01

This paper studies the economic operations of the microgrid in a distributed way such that the operational schedule of each of the units, like generators, load units, storage units, etc., in a microgrid system, is implemented by autonomous agents. We apply and generalise the progressive second price (PSP) auction mechanism which was proposed by Lazar and Semret to efficiently allocate the divisible network resources. Considering the economic operation for the microgrid systems, the generators play as sellers to supply energy and the load units play as the buyers to consume energy, while a storage unit, like battery, super capacitor, etc., may transit between buyer and seller, such that it is a buyer when it charges and becomes a seller when it discharges. Furthermore in a connected mode, each individual unit competes against not only the other individual units in the microgrid but also the exogenous main grid possessing fixed electricity price and infinite trade capacity; that is to say, the auctioneer assigns the electricity among all individual units and the main grid with respect to the submitted bid strategies of all individual units in the microgrid in an economic way. Due to these distinct characteristics, the underlying auction games are distinct from those studied in the literature. We show that under mild conditions, the efficient economic operation strategy is a Nash equilibrium (NE) for the PSP auction games, and propose a distributed algorithm under which the system can converge to an NE. We also show that the performance of worst NE can be bounded with respect to the system parameters, say the energy trading price with the main grid, and based upon that, the implemented NE is unique and efficient under some conditions.

Advanced oil recovery technologies for improved recovery from slope basin clastic reservoirs, Nash Draw Brushy Canyon Pool, Eddy County, NM. Second annual technical progress report, October 1, 1996--September 30, 1997

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1998-09-01

The Nash Draw Brushy Canyon Pool in Eddy County, New Mexico is a field demonstration in the US Department of Energy Class III Program. Advanced reservoir characterization techniques are being used at the Nash Draw project to develop reservoir management strategies for optimizing oil recovery from this Delaware reservoir. Analysis, interpretation, and integration of recently acquired geological, geophysical, and engineering data revealed that the initial reservoir description was too simplistic to capture the critical features of this complex formation. As a result of the analysis, a proposed pilot area was reconsidered. Comparison of seismic data and engineering data have shownmore » evidence of discontinuities in the area surrounding the proposed injector. Analysis of the 3-D seismic has shown that wells in the proposed pilot are in an area of poor quality amplitude development. The implication is that since amplitude attenuation is a function of porosity, then this is not the best area to be attempting a pilot pressure maintenance project. Because the original pilot area appears to be compartmentalized, the lateral continuity between the pilot wells could be reduced. The 3-D seismic interpretation indicates other areas may be better suited for the initial pilot area. Therefore, the current focus has shifted more to targeted drilling, and the pilot injection will be considered in a more continuous area of the NDP in the future. Results of reservoir simulation studies indicate that pressure maintenance should be started early when reservoir pressure is still high.« less

Fracture propagation through a layered shale and limestone sequence at Nash Point, South Wales: Implications on the development of fracture networks in layered sequences

NASA Astrophysics Data System (ADS)

Forbes Inskip, N.; Meredith, P. G.; Gudmundsson, A.

2017-12-01

While considerable effort has been expended on the study of fracture propagation in rocks in recent years, our understanding of how fractures propagate through sedimentary rocks composed of layers with different mechanical and elastic properties remains poor. Yet the mechanical layering is a key parameter controlling the propagation of fractures in sedimentary sequences. Here we report measurements of the contrasting properties of the Lower Lias at Nash Point, South Wales, which comprises a sequence of interbedded shale and limestone layers, and how those properties influence fracture propagation. The static Young's modulus (Estat) of both rock types has been measured parallel and normal to bedding. The shale is highly anisotropic, with Estat varying from 2.4 GPa, in the bedding-normal orientation, to 7.9 GPa, in the bedding-parallel orientation, yielding an anisotropy of 107%. By contrast the limestone has a very low anisotropy of 8%, with Estat values varying from 28.5 GPa, in the bedding-normal orientation, to 26.3 GPa in the bedding-parallel orientation. It follows that for a vertical fracture propagating in this sequence the modulus contrast is by a factor of about 12. This is important because the contrast in elastic properties is a key factor in controlling whether fractures arrest, deflect, or propagate across interfaces between layers in a sequence. Preliminary numerical modelling results (using a finite element modelling software) of induced fractures at Nash Point demonstrate a rotation of the maximum principal compressive stress across interfaces but also the concentration of tensile stress within the more competent (high Estat) limestone layers. The tensile strength (σT), using the Brazil-disk technique, and fracture toughness (KIc), using the semi-circular bend methodology, of both rock types have been measured. Measurements were made in the three principal orientations relative to bedding, Arrester, Divider, and Short-Transverse, and also at 15�

Modeling actual evapotranspiration with routine meteorological variables in the data-scarce region of the Tibetan Plateau: Comparisons and implications

NASA Astrophysics Data System (ADS)

Ma, Ning; Zhang, Yinsheng; Xu, Chong-Yu; Szilagyi, Jozsef

2015-08-01

Quantitative estimation of actual evapotranspiration (ETa) by in situ measurements and mathematical modeling is a fundamental task for physical understanding of ETa as well as the feedback mechanisms between land and the ambient atmosphere. However, the ETa information in the Tibetan Plateau (TP) has been greatly impeded by the extremely sparse ground observation network in the region. Approaches for estimating ETa solely from routine meteorological variables are therefore important for investigating spatiotemporal variations of ETa in the data-scarce region of the TP. Motivated by this need, the complementary relationship (CR) and Penman-Monteith approaches were evaluated against in situ measurements of ETa on a daily basis in an alpine steppe region of the TP. The former includes the Nonlinear Complementary Relationship (Nonlinear-CR) as well as the Complementary Relationship Areal Evapotranspiration (CRAE) models, while the latter involves the Katerji-Perrier and the Todorovic models. Results indicate that the Nonlinear-CR, CRAE, and Katerji-Perrier models are all capable of efficiently simulating daily ETa, provided their parameter values were appropriately calibrated. The Katerji-Perrier model performed best since its site-specific parameters take the soil water status into account. The Nonlinear-CR model also performed well with the advantage of not requiring the user to choose between a symmetric and asymmetric CR. The CRAE model, even with a relatively low Nash-Sutcliffe efficiency (NSE) value, is also an acceptable approach in this data-scarce region as it does not need information of wind speed and ground surface conditions. In contrast, application of the Todorovic model was found to be inappropriate in the dry regions of the TP due to its significant overestimation of ETa as it neglects the effect of water stress on the bulk surface resistance. Sensitivity analysis of the parameter values demonstrated the relative importance of each parameter in the

Parameter transferability within homogeneous regions and comparisons with predictions from a priori parameters in the eastern United States

NASA Astrophysics Data System (ADS)

Chouaib, Wafa; Alila, Younes; Caldwell, Peter V.

2018-05-01

The need for predictions of flow time-series persists at ungauged catchments, motivating the research goals of our study. By means of the Sacramento model, this paper explores the use of parameter transfer within homogeneous regions of similar climate and flow characteristics and makes comparisons with predictions from a priori parameters. We assessed the performance using the Nash-Sutcliffe (NS), bias, mean monthly hydrograph and flow duration curve (FDC). The study was conducted on a large dataset of 73 catchments within the eastern US. Two approaches to the parameter transferability were developed and evaluated; (i) the within homogeneous region parameter transfer using one donor catchment specific to each region, (ii) the parameter transfer disregarding the geographical limits of homogeneous regions, where one donor catchment was common to all regions. Comparisons between both parameter transfers enabled to assess the gain in performance from the parameter regionalization and its respective constraints and limitations. The parameter transfer within homogeneous regions outperformed the a priori parameters and led to a decrease in bias and increase in efficiency reaching a median NS of 0.77 and a NS of 0.85 at individual catchments. The use of FDC revealed the effect of bias on the inaccuracy of prediction from parameter transfer. In one specific region, of mountainous and forested catchments, the prediction accuracy of the parameter transfer was less satisfactory and equivalent to a priori parameters. In this region, the parameter transfer from the outsider catchment provided the best performance; less-biased with smaller uncertainty in medium flow percentiles (40%-60%). The large disparity of energy conditions explained the lack of performance from parameter transfer in this region. Besides, the subsurface stormflow is predominant and there is a likelihood of lateral preferential flow, which according to its specific properties further explained the reduced

Man vs. Machine: An interactive poll to evaluate hydrological model performance of a manual and an automatic calibration

NASA Astrophysics Data System (ADS)

Wesemann, Johannes; Burgholzer, Reinhard; Herrnegger, Mathew; Schulz, Karsten

2017-04-01

In recent years, a lot of research in hydrological modelling has been invested to improve the automatic calibration of rainfall-runoff models. This includes for example (1) the implementation of new optimisation methods, (2) the incorporation of new and different objective criteria and signatures in the optimisation and (3) the usage of auxiliary data sets apart from runoff. Nevertheless, in many applications manual calibration is still justifiable and frequently applied. The hydrologist performing the manual calibration, with his expert knowledge, is able to judge the hydrographs simultaneously concerning details but also in a holistic view. This integrated eye-ball verification procedure available to man can be difficult to formulate in objective criteria, even when using a multi-criteria approach. Comparing the results of automatic and manual calibration is not straightforward. Automatic calibration often solely involves objective criteria such as Nash-Sutcliffe Efficiency Coefficient or the Kling-Gupta-Efficiency as a benchmark during the calibration. Consequently, a comparison based on such measures is intrinsically biased towards automatic calibration. Additionally, objective criteria do not cover all aspects of a hydrograph leaving questions concerning the quality of a simulation open. This contribution therefore seeks to examine the quality of manually and automatically calibrated hydrographs by interactively involving expert knowledge in the evaluation. Simulations have been performed for the Mur catchment in Austria with the rainfall-runoff model COSERO using two parameter sets evolved from a manual and an automatic calibration. A subset of resulting hydrographs for observation and simulation, representing the typical flow conditions and events, will be evaluated in this study. In an interactive crowdsourcing approach experts attending the session can vote for their preferred simulated hydrograph without having information on the calibration method that

Hydrologic Modeling and Parameter Estimation under Data Scarcity for Java Island, Indonesia

NASA Astrophysics Data System (ADS)

Yanto, M.; Livneh, B.; Rajagopalan, B.; Kasprzyk, J. R.

2015-12-01

The Indonesian island of Java is routinely subjected to intense flooding, drought and related natural hazards, resulting in severe social and economic impacts. Although an improved understanding of the island's hydrology would help mitigate these risks, data scarcity issues make the modeling challenging. To this end, we developed a hydrological representation of Java using the Variable Infiltration Capacity (VIC) model, to simulate the hydrologic processes of several watersheds across the island. We measured the model performance using Nash-Sutcliffe Efficiency (NSE) at monthly time step. Data scarcity and quality issues for precipitation and streamflow warranted the application of a quality control procedure to data ensure consistency among watersheds resulting in 7 watersheds. To optimize the model performance, the calibration parameters were estimated using Borg Multi Objective Evolutionary Algorithm (Borg MOEA), which offers efficient searching of the parameter space, adaptive population sizing and local optima escape facility. The result shows that calibration performance is best (NSE ~ 0.6 - 0.9) in the eastern part of the domain and moderate (NSE ~ 0.3 - 0.5) in the western part of the island. The validation results are lower (NSE ~ 0.1 - 0.5) and (NSE ~ 0.1 - 0.4) in the east and west, respectively. We surmise that the presence of outliers and stark differences in the climate between calibration and validation periods in the western watersheds are responsible for low NSE in this region. In addition, we found that approximately 70% of total errors were contributed by less than 20% of total data. The spatial variability of model performance suggests the influence of both topographical and hydroclimatic controls on the hydrological processes. Most watersheds in eastern part perform better in wet season and vice versa for the western part. This modeling framework is one of the first attempts at comprehensively simulating the hydrology in this maritime, tropical

Sensitivity and Uncertainty Analysis for Streamflow Prediction Using Different Objective Functions and Optimization Algorithms: San Joaquin California

NASA Astrophysics Data System (ADS)

Paul, M.; Negahban-Azar, M.

2017-12-01

- r2, Nash-Sutcliffe efficiency- NSE, percent bias- PBIAS, and Kling-Gupta efficiency- KGE). The preliminary results showed that using the SUFI-2 algorithm with the objective function NSE and KGE has improved significantly the calibration (e.g. R2 and NSE is found 0.52 and 0.47 respectively for daily streamflow calibration).

Multivariate time series modeling of short-term system scale irrigation demand

NASA Astrophysics Data System (ADS)

Perera, Kushan C.; Western, Andrew W.; George, Biju; Nawarathna, Bandara

2015-12-01

Travel time limits the ability of irrigation system operators to react to short-term irrigation demand fluctuations that result from variations in weather, including very hot periods and rainfall events, as well as the various other pressures and opportunities that farmers face. Short-term system-wide irrigation demand forecasts can assist in system operation. Here we developed a multivariate time series (ARMAX) model to forecast irrigation demands with respect to aggregated service points flows (IDCGi, ASP) and off take regulator flows (IDCGi, OTR) based across 5 command areas, which included area covered under four irrigation channels and the study area. These command area specific ARMAX models forecast 1-5 days ahead daily IDCGi, ASP and IDCGi, OTR using the real time flow data recorded at the service points and the uppermost regulators and observed meteorological data collected from automatic weather stations. The model efficiency and the predictive performance were quantified using the root mean squared error (RMSE), Nash-Sutcliffe model efficiency coefficient (NSE), anomaly correlation coefficient (ACC) and mean square skill score (MSSS). During the evaluation period, NSE for IDCGi, ASP and IDCGi, OTR across 5 command areas were ranged 0.98-0.78. These models were capable of generating skillful forecasts (MSSS ⩾ 0.5 and ACC ⩾ 0.6) of IDCGi, ASP and IDCGi, OTR for all 5 lead days and IDCGi, ASP and IDCGi, OTR forecasts were better than using the long term monthly mean irrigation demand. Overall these predictive performance from the ARMAX time series models were higher than almost all the previous studies we are aware. Further, IDCGi, ASP and IDCGi, OTR forecasts have improved the operators' ability to react for near future irrigation demand fluctuations as the developed ARMAX time series models were self-adaptive to reflect the short-term changes in the irrigation demand with respect to various pressures and opportunities that farmers' face, such as

Autocalibration of a one-dimensional hydrodynamic-ecological model (DYRESM 4.0-CAEDYM 3.1) using a Monte Carlo approach: simulations of hypoxic events in a polymictic lake

NASA Astrophysics Data System (ADS)

Luo, Liancong; Hamilton, David; Lan, Jia; McBride, Chris; Trolle, Dennis

2018-03-01

Automated calibration of complex deterministic water quality models with a large number of biogeochemical parameters can reduce time-consuming iterative simulations involving empirical judgements of model fit. We undertook autocalibration of the one-dimensional hydrodynamic-ecological lake model DYRESM-CAEDYM, using a Monte Carlo sampling (MCS) method, in order to test the applicability of this procedure for shallow, polymictic Lake Rotorua (New Zealand). The calibration procedure involved independently minimizing the root-mean-square error (RMSE), maximizing the Pearson correlation coefficient (r) and Nash-Sutcliffe efficient coefficient (Nr) for comparisons of model state variables against measured data. An assigned number of parameter permutations was used for 10 000 simulation iterations. The "optimal" temperature calibration produced a RMSE of 0.54 °C, Nr value of 0.99, and r value of 0.98 through the whole water column based on comparisons with 540 observed water temperatures collected between 13 July 2007 and 13 January 2009. The modeled bottom dissolved oxygen concentration (20.5 m below surface) was compared with 467 available observations. The calculated RMSE of the simulations compared with the measurements was 1.78 mg L-1, the Nr value was 0.75, and the r value was 0.87. The autocalibrated model was further tested for an independent data set by simulating bottom-water hypoxia events from 15 January 2009 to 8 June 2011 (875 days). This verification produced an accurate simulation of five hypoxic events corresponding to DO < 2 mg L-1 during summer of 2009-2011. The RMSE was 2.07 mg L-1, Nr value 0.62, and r value of 0.81, based on the available data set of 738 days. The autocalibration software of DYRESM-CAEDYM developed here is substantially less time-consuming and more efficient in parameter optimization than traditional manual calibration which has been the standard tool practiced for similar complex water quality models.

Auto-calibration of a one-dimensional hydrodynamic-ecological model using a Monte Carlo approach: simulation of hypoxic events in a polymictic lake

NASA Astrophysics Data System (ADS)

Luo, L.

2011-12-01

Automated calibration of complex deterministic water quality models with a large number of biogeochemical parameters can reduce time-consuming iterative simulations involving empirical judgements of model fit. We undertook auto-calibration of the one-dimensional hydrodynamic-ecological lake model DYRESM-CAEDYM, using a Monte Carlo sampling (MCS) method, in order to test the applicability of this procedure for shallow, polymictic Lake Rotorua (New Zealand). The calibration procedure involved independently minimising the root-mean-square-error (RMSE), maximizing the Pearson correlation coefficient (r) and Nash-Sutcliffe efficient coefficient (Nr) for comparisons of model state variables against measured data. An assigned number of parameter permutations was used for 10,000 simulation iterations. The 'optimal' temperature calibration produced a RMSE of 0.54 °C, Nr-value of 0.99 and r-value of 0.98 through the whole water column based on comparisons with 540 observed water temperatures collected between 13 July 2007 - 13 January 2009. The modeled bottom dissolved oxygen concentration (20.5 m below surface) was compared with 467 available observations. The calculated RMSE of the simulations compared with the measurements was 1.78 mg L-1, the Nr-value was 0.75 and the r-value was 0.87. The autocalibrated model was further tested for an independent data set by simulating bottom-water hypoxia events for the period 15 January 2009 to 8 June 2011 (875 days). This verification produced an accurate simulation of five hypoxic events corresponding to DO < 2 mg L-1 during summer of 2009-2011. The RMSE was 2.07 mg L-1, Nr-value 0.62 and r-value of 0.81, based on the available data set of 738 days. The auto-calibration software of DYRESM-CAEDYM developed here is substantially less time-consuming and more efficient in parameter optimisation than traditional manual calibration which has been the standard tool practiced for similar complex water quality models.

Evaluating the robustness of conceptual rainfall-runoff models under climate variability in northern Tunisia

NASA Astrophysics Data System (ADS)

Dakhlaoui, H.; Ruelland, D.; Tramblay, Y.; Bargaoui, Z.

2017-07-01

To evaluate the impact of climate change on water resources at the catchment scale, not only future projections of climate are necessary but also robust rainfall-runoff models that must be fairly reliable under changing climate conditions. The aim of this study was thus to assess the robustness of three conceptual rainfall-runoff models (GR4j, HBV and IHACRES) on five basins in northern Tunisia under long-term climate variability, in the light of available future climate scenarios for this region. The robustness of the models was evaluated using a differential split sample test based on a climate classification of the observation period that simultaneously accounted for precipitation and temperature conditions. The study catchments include the main hydrographical basins in northern Tunisia, which produce most of the surface water resources in the country. A 30-year period (1970-2000) was used to capture a wide range of hydro-climatic conditions. The calibration was based on the Kling-Gupta Efficiency (KGE) criterion, while model transferability was evaluated based on the Nash-Sutcliffe efficiency criterion and volume error. The three hydrological models were shown to behave similarly under climate variability. The models simulated the runoff pattern better when transferred to wetter and colder conditions than to drier and warmer ones. It was shown that their robustness became unacceptable when climate conditions involved a decrease of more than 25% in annual precipitation and an increase of more than +1.75 °C in annual mean temperatures. The reduction in model robustness may be partly due to the climate dependence of some parameters. When compared to precipitation and temperature projections in the region, the limits of transferability obtained in this study are generally respected for short and middle term. For long term projections under the most pessimistic emission gas scenarios, the limits of transferability are generally not respected, which may hamper the

Discharge data assimilation in a distributed hydrologic model for flood forecasting purposes

NASA Astrophysics Data System (ADS)

Ercolani, G.; Castelli, F.

2017-12-01

Flood early warning systems benefit from accurate river flow forecasts, and data assimilation may improve their reliability. However, the actual enhancement that can be obtained in the operational practice should be investigated in detail and quantified. In this work we assess the benefits that the simultaneous assimilation of discharge observations at multiple locations can bring to flow forecasting through a distributed hydrologic model. The distributed model, MOBIDIC, is part of the operational flood forecasting chain of Tuscany Region in Central Italy. The assimilation system adopts a mixed variational-Monte Carlo approach to update efficiently initial river flow, soil moisture, and a parameter related to runoff production. The evaluation of the system is based on numerous hindcast experiments of real events. The events are characterized by significant rainfall that resulted in both high and relatively low flow in the river network. The area of study is the main basin of Tuscany Region, i.e. Arno river basin, which extends over about 8300 km2 and whose mean annual precipitation is around 800 mm. Arno's mainstream, with its nearly 240 km length, passes through major Tuscan cities, as Florence and Pisa, that are vulnerable to floods (e.g. flood of November 1966). The assimilation tests follow the usage of the model in the forecasting chain, employing the operational resolution in both space and time (500 m and 15 minutes respectively) and releasing new flow forecasts every 6 hours. The assimilation strategy is evaluated in respect to open loop simulations, i.e. runs that do not exploit discharge observations through data assimilation. We compare hydrographs in their entirety, as well as classical performance indexes, as error on peak flow and Nash-Sutcliffe efficiency. The dependence of performances on lead time and location is assessed. Results indicate that the operational forecasting chain can benefit from the developed assimilation system, although with a

Leaf gas exchange of Andropogon gerardii Vitman, Panicum virgatum L., and Sorghastrum nutans (L.) Nash in a tallgrass prairie

NASA Technical Reports Server (NTRS)

Polley, H. W.; Norman, J. M.; Arkebauer, T. J.; Walter-Shea, E. A.; Greegor, D. H., Jr.; Bramer, B.

1992-01-01

Net CO2 assimilation as a function of internal CO2 and stomatal conductance to water vapor were measured on blades of the C4 grasses Andropogon gerardii Vitman, Panicum virgatrum L., and Sorghastrum nutans (L.) Nash in northeast Kansas over two growing seasons to determine the comparative physiological responses of these dominant grasses of the tallgrass prairie to environmental variables. The response of dark respiration to temperature and of net assimilation to CO2 concentration and absorbed quantum flux differed little among species. A. gerardii had lower potential photosynthetic rates at internal CO2 concentrations below saturation than P. virgatum and S. nutans, but net assimilation under ambient conditions was similar in the three species. Net assimilation and both the initial slope of assimilation versus internal CO2 curves and the maximum potential assimilation rate decreased as leaf water potential declined in blades of A. gerardii and S. nutans. Changes in assimilation capacity were paralleled by changes in stomatal conductance that were similar in all three species. The strong correlations among processes regulating leaf CO2 assimilation and transpiration in A. gerardii, P. virgatum, and S. nutans suggest that the processes are tightly and similarly coupled in these grasses over a wide range of environmental conditions encountered in the tallgrass prairie.

Aeromagnetic Surveying with a Rotary-Wing Unmanned Aircraft System: A Case Study from a Zinc Deposit in Nash Creek, New Brunswick, Canada

NASA Astrophysics Data System (ADS)

Cunningham, Michael; Samson, Claire; Wood, Alan; Cook, Ian

2017-12-01

Unmanned aircraft systems (UASs) have been under rapid development for applications in the mineral exploration industry, mainly for aeromagnetic surveying. They provide improved detection of smaller, deeper and weaker magnetic targets. A traditional system flying an altitude of 100 m above ground level (AGL) can detect a spherical ore body with a radius of 16 m and a magnetic susceptibility of 10-4 buried at a depth of 40 m. A UAS flying at an altitude of 50 or 2 m AGL would require the radius to be 11 or 5 m, respectively. A demonstration survey was performed using the SkyLance rotary-wing UAS instrumented with a cesium vapour magnetometer in Nash Creek, New Brunswick, Canada. The UAS flew over a zinc deposit featuring three magnetic anomalies. It acquired repeatable data that compared well with upward continuation maps of ground magnetic data. Dykes or faults that are dipping eastward at 25° and are approximately 1.5 m wide fit the observed response of the three anomalies captured on the UAS magnetic data.

An optimized Nash nonlinear grey Bernoulli model based on particle swarm optimization and its application in prediction for the incidence of Hepatitis B in Xinjiang, China.

PubMed

Zhang, Liping; Zheng, Yanling; Wang, Kai; Zhang, Xueliang; Zheng, Yujian

2014-06-01

In this paper, by using a particle swarm optimization algorithm to solve the optimal parameter estimation problem, an improved Nash nonlinear grey Bernoulli model termed PSO-NNGBM(1,1) is proposed. To test the forecasting performance, the optimized model is applied for forecasting the incidence of hepatitis B in Xinjiang, China. Four models, traditional GM(1,1), grey Verhulst model (GVM), original nonlinear grey Bernoulli model (NGBM(1,1)) and Holt-Winters exponential smoothing method, are also established for comparison with the proposed model under the criteria of mean absolute percentage error and root mean square percent error. The prediction results show that the optimized NNGBM(1,1) model is more accurate and performs better than the traditional GM(1,1), GVM, NGBM(1,1) and Holt-Winters exponential smoothing method. Copyright © 2014. Published by Elsevier Ltd.

Multifactor analysis and simulation of the surface runoff and soil infiltration at different slope gradients

NASA Astrophysics Data System (ADS)

Huang, J.; Kang, Q.; Yang, J. X.; Jin, P. W.

2017-08-01

The surface runoff and soil infiltration exert significant influence on soil erosion. The effects of slope gradient/length (SG/SL), individual rainfall amount/intensity (IRA/IRI), vegetation cover (VC) and antecedent soil moisture (ASM) on the runoff depth (RD) and soil infiltration (INF) were evaluated in a series of natural rainfall experiments in the South of China. RD is found to correlate positively with IRA, IRI, and ASM factors and negatively with SG and VC. RD decreased followed by its increase with SG and ASM, it increased with a further decrease with SL, exhibited a linear growth with IRA and IRI, and exponential drop with VC. Meanwhile, INF exhibits a positive correlation with SL, IRA and IRI and VC, and a negative one with SG and ASM. INF was going up and then down with SG, linearly rising with SL, IRA and IRI, increasing by a logit function with VC, and linearly falling with ASM. The VC level above 60% can effectively lower the surface runoff and significantly enhance soil infiltration. Two RD and INF prediction models, accounting for the above six factors, were constructed using the multiple nonlinear regression method. The verification of those models disclosed a high Nash-Sutcliffe coefficient and low root-mean-square error, demonstrating good predictability of both models.

Runoff prediction using rainfall data from microwave links: Tabor case study.

PubMed

Stransky, David; Fencl, Martin; Bares, Vojtech

2018-05-01

Rainfall spatio-temporal distribution is of great concern for rainfall-runoff modellers. Standard rainfall observations are, however, often scarce and/or expensive to obtain. Thus, rainfall observations from non-traditional sensors such as commercial microwave links (CMLs) represent a promising alternative. In this paper, rainfall observations from a municipal rain gauge (RG) monitoring network were complemented by CMLs and used as an input to a standard urban drainage model operated by the water utility of the Tabor agglomeration (CZ). Two rainfall datasets were used for runoff predictions: (i) the municipal RG network, i.e. the observation layout used by the water utility, and (ii) CMLs adjusted by the municipal RGs. The performance was evaluated in terms of runoff volumes and hydrograph shapes. The use of CMLs did not lead to distinctively better predictions in terms of runoff volumes; however, CMLs outperformed RGs used alone when reproducing a hydrograph's dynamics (peak discharges, Nash-Sutcliffe coefficient and hydrograph's rising limb timing). This finding is promising for number of urban drainage tasks working with dynamics of the flow. Moreover, CML data can be obtained from a telecommunication operator's data cloud at virtually no cost. That makes their use attractive for cities unable to improve their monitoring infrastructure for economic or organizational reasons.

An Improved Approach for Estimating Daily Net Radiation over the Heihe River Basin

PubMed Central

Wu, Bingfang; Liu, Shufu; Zhu, Weiwei; Yan, Nana; Xing, Qiang; Tan, Shen

2017-01-01

Net radiation plays an essential role in determining the thermal conditions of the Earth’s surface and is an important parameter for the study of land-surface processes and global climate change. In this paper, an improved satellite-based approach to estimate the daily net radiation is presented, in which sunshine duration were derived from the geostationary meteorological satellite (FY-2D) cloud classification product, the monthly empirical as and bs Angstrom coefficients for net shortwave radiation were calibrated by spatial fitting of the ground data from 1997 to 2006, and the daily net longwave radiation was calibrated with ground data from 2007 to 2010 over the Heihe River Basin in China. The estimated daily net radiation values were validated against ground data for 12 months in 2008 at four stations with different underlying surface types. The average coefficient of determination (R2) was 0.8489, and the averaged Nash-Sutcliffe equation (NSE) was 0.8356. The close agreement between the estimated daily net radiation and observations indicates that the proposed method is promising, especially given the comparison between the spatial distribution and the interpolation of sunshine duration. Potential applications include climate research, energy balance studies and the estimation of global evapotranspiration. PMID:28054976

An Improved Approach for Estimating Daily Net Radiation over the Heihe River Basin.

PubMed

Wu, Bingfang; Liu, Shufu; Zhu, Weiwei; Yan, Nana; Xing, Qiang; Tan, Shen

2017-01-04

Net radiation plays an essential role in determining the thermal conditions of the Earth's surface and is an important parameter for the study of land-surface processes and global climate change. In this paper, an improved satellite-based approach to estimate the daily net radiation is presented, in which sunshine duration were derived from the geostationary meteorological satellite (FY-2D) cloud classification product, the monthly empirical a s and b s Angstrom coefficients for net shortwave radiation were calibrated by spatial fitting of the ground data from 1997 to 2006, and the daily net longwave radiation was calibrated with ground data from 2007 to 2010 over the Heihe River Basin in China. The estimated daily net radiation values were validated against ground data for 12 months in 2008 at four stations with different underlying surface types. The average coefficient of determination ( R ²) was 0.8489, and the averaged Nash-Sutcliffe equation ( NSE ) was 0.8356. The close agreement between the estimated daily net radiation and observations indicates that the proposed method is promising, especially given the comparison between the spatial distribution and the interpolation of sunshine duration. Potential applications include climate research, energy balance studies and the estimation of global evapotranspiration.

Linear Modeling and Evaluation of Controls on Flow Response in Western Post-Fire Watersheds

NASA Astrophysics Data System (ADS)

Saxe, S.; Hogue, T. S.; Hay, L.

2015-12-01

This research investigates the impact of wildfires on watershed flow regimes throughout the western United States, specifically focusing on evaluation of fire events within specified subregions and determination of the impact of climate and geophysical variables in post-fire flow response. Fire events were collected through federal and state-level databases and streamflow data were collected from U.S. Geological Survey stream gages. 263 watersheds were identified with at least 10 years of continuous pre-fire daily streamflow records and 5 years of continuous post-fire daily flow records. For each watershed, percent changes in runoff ratio (RO), annual seven day low-flows (7Q2) and annual seven day high-flows (7Q10) were calculated from pre- to post-fire. Numerous independent variables were identified for each watershed and fire event, including topographic, land cover, climate, burn severity, and soils data. The national watersheds were divided into five regions through K-clustering and a lasso linear regression model, applying the Leave-One-Out calibration method, was calculated for each region. Nash-Sutcliffe Efficiency (NSE) was used to determine the accuracy of the resulting models. The regions encompassing the United States along and west of the Rocky Mountains, excluding the coastal watersheds, produced the most accurate linear models. The Pacific coast region models produced poor and inconsistent results, indicating that the regions need to be further subdivided. Presently, RO and HF response variables appear to be more easily modeled than LF. Results of linear regression modeling showed varying importance of watershed and fire event variables, with conflicting correlation between land cover types and soil types by region. The addition of further independent variables and constriction of current variables based on correlation indicators is ongoing and should allow for more accurate linear regression modeling.

Estimation of daily mean streamflow for ungaged stream locations in the Delaware River Basin, water years 1960–2010

USGS Publications Warehouse

Stuckey, Marla H.

2016-06-09

The ability to characterize baseline streamflow conditions, compare them with current conditions, and assess effects of human activities on streamflow is fundamental to water-management programs addressing water allocation, human-health issues, recreation needs, and establishment of ecological flow criteria. The U.S. Geological Survey, through the National Water Census, has developed the Delaware River Basin Streamflow Estimator Tool (DRB-SET) to estimate baseline (minimally altered) and altered (affected by regulation, diversion, mining, or other anthropogenic activities) and altered streamflow at a daily time step for ungaged stream locations in the Delaware River Basin for water years 1960–2010. Daily mean baseline streamflow is estimated by using the QPPQ method to equate streamflow expressed as a percentile from the flow-duration curve (FDC) for a particular day at an ungaged stream location with the percentile from a FDC for the same day at a hydrologically similar gaged location where streamflow is measured. Parameter-based regression equations were developed for 22 exceedance probabilities from the FDC for ungaged stream locations in the Delaware River Basin. Water use data from 2010 is used to adjust the baseline daily mean streamflow generated from the QPPQ method at ungaged stream locations in the Delaware River Basin to reflect current, or altered, conditions. To evaluate the effectiveness of the overall QPPQ method contained within DRB-SET, a comparison of observed and estimated daily mean streamflows was performed for 109 reference streamgages in and near the Delaware River Basin. The Nash-Sutcliffe efficiency (NSE) values were computed as a measure of goodness of fit. The NSE values (using log10 streamflow values) ranged from 0.22 to 0.98 (median of 0.90) for 45 streamgages in the Upper Delaware River Basin and from -0.37 to 0.98 (median of 0.79) for 41 streamgages in the Lower Delaware River Basin.

Spatial and temporal variability of groundwater recharge in Geba basin, Northern Ethiopia

NASA Astrophysics Data System (ADS)

Yenehun, Alemu; Walraevens, Kristine; Batelaan, Okke

2017-10-01

WetSpa, a physically based, spatially distributed watershed model, has been used to study the spatial and temporal variation of recharge in the Geba basin, Northern Ethiopia. The model covers an area of about 4, 249 km2 and integrates elevation, soil and land-use data, hydrometeorological and river discharge data. The Geba basin has a highly variable topography ranging from 1000 to 3280 m with an average slope of 12.9%. The area is characterized by a distinct wet and long dry season with a mean annual precipitation of 681 mm and temperatures ranging between 6.5 °C and 32 °C. The model was simulated on daily basis for nearly four years (January 1, 2000 to December 18, 2003). It resulted in a good agreement between measured and simulated streamflow hydrographs with Nash-Sutcliffe efficiency of almost 70% and 85% for, respectively, the calibration and validation. The water balance terms show very strong spatial and temporal variability, about 3.8% of the total precipitation is intercepted by the plant canopy; 87.5% infiltrates into the soil (of which 13% percolates, 2.7% flows laterally off and 84.2% evapotranspired from the root zone), and 7.2% is surface runoff. The mean annual recharge varies from about 45 mm (2003) to 208 mm (2001), with average of 98.6 mm/yr. On monthly basis, August has the maximum (73 mm) and December the lowest (0.1 mm) recharge. The mean annual groundwater recharge spatially varies from 0 to 371 mm; mainly controlled by the distribution of rainfall amount, followed by soil and land-use, and to a certain extent, slope. About 21% of Geba has a recharge larger than 120 mm and 1% less than 5 mm.

Simulation of streamflow and the effects of brush management on water yields in the upper Guadalupe River watershed, south-central Texas, 1995-2010

USGS Publications Warehouse

Bumgarner, Johnathan R.; Thompson, Florence E.

2012-01-01

The U.S. Geological Survey, in cooperation with the Texas State Soil and Water Conservation Board and the Upper Guadalupe River Authority, developed and calibrated a Soil and Water Assessment Tool watershed model of the upper Guadalupe River watershed in south-central Texas to simulate streamflow and the effects of brush management on water yields in the watershed and to Canyon Lake for 1995-2010. Model simulations were done to quantify the possible change in water yield of individual subbasins in the upper Guadalupe River watershed as a result of the replacement of ashe juniper (Juniperus ashei) with grasslands. The simulation results will serve as a tool for resource managers to guide their brush-management efforts. Model hydrology was calibrated with streamflow data collected at the U.S. Geological Survey streamflow-gaging station 08167500 Guadalupe River near Spring Branch, Tex., for 1995-2010. Simulated monthly streamflow showed very good agreement with measured monthly streamflow: a percent bias of -5, a coefficient of determination of 0.91, and a Nash-Sutcliffe coefficient of model efficiency of 0.85. Modified land-cover input datasets were generated for the model in order to simulate the replacement of ashe juniper with grasslands in 23 brush-management subbasins in the watershed. Each of the 23 simulations showed an increase in simulated water yields in the targeted subbasins and to Canyon Lake. The simulated increases in average annual water yields in the subbasins ranged from 6,370 to 119,000 gallons per acre of ashe juniper replaced with grasslands with an average of 38,900 gallons. The simulated increases in average annual water yields to Canyon Lake from upstream subbasins ranged from 6,640 to 72,700 gallons per acre of ashe juniper replaced with grasslands with an average of 34,700 gallons.

A modification of the Regional Nutrient Management model (ReNuMa) to identify long-term changes in riverine nitrogen sources

NASA Astrophysics Data System (ADS)

Hu, Minpeng; Liu, Yanmei; Wang, Jiahui; Dahlgren, Randy A.; Chen, Dingjiang

2018-06-01

Source apportionment is critical for guiding development of efficient watershed nitrogen (N) pollution control measures. The ReNuMa (Regional Nutrient Management) model, a semi-empirical, semi-process-oriented model with modest data requirements, has been widely used for riverine N source apportionment. However, the ReNuMa model contains limitations for addressing long-term N dynamics by ignoring temporal changes in atmospheric N deposition rates and N-leaching lag effects. This work modified the ReNuMa model by revising the source code to allow yearly changes in atmospheric N deposition and incorporation of N-leaching lag effects into N transport processes. The appropriate N-leaching lag time was determined from cross-correlation analysis between annual watershed individual N source inputs and riverine N export. Accuracy of the modified ReNuMa model was demonstrated through analysis of a 31-year water quality record (1980-2010) from the Yongan watershed in eastern China. The revisions considerably improved the accuracy (Nash-Sutcliff coefficient increased by ∼0.2) of the modified ReNuMa model for predicting riverine N loads. The modified model explicitly identified annual and seasonal changes in contributions of various N sources (i.e., point vs. nonpoint source, surface runoff vs. groundwater) to riverine N loads as well as the fate of watershed anthropogenic N inputs. Model results were consistent with previously modeled or observed lag time length as well as changes in riverine chloride and nitrate concentrations during the low-flow regime and available N levels in agricultural soils of this watershed. The modified ReNuMa model is applicable for addressing long-term changes in riverine N sources, providing decision-makers with critical information for guiding watershed N pollution control strategies.

An ensemble-ANFIS based uncertainty assessment model for forecasting multi-scalar standardized precipitation index

NASA Astrophysics Data System (ADS)

Ali, Mumtaz; Deo, Ravinesh C.; Downs, Nathan J.; Maraseni, Tek

2018-07-01

Forecasting drought by means of the World Meteorological Organization-approved Standardized Precipitation Index (SPI) is considered to be a fundamental task to support socio-economic initiatives and effectively mitigating the climate-risk. This study aims to develop a robust drought modelling strategy to forecast multi-scalar SPI in drought-rich regions of Pakistan where statistically significant lagged combinations of antecedent SPI are used to forecast future SPI. With ensemble-Adaptive Neuro Fuzzy Inference System ('ensemble-ANFIS') executed via a 10-fold cross-validation procedure, a model is constructed by randomly partitioned input-target data. Resulting in 10-member ensemble-ANFIS outputs, judged by mean square error and correlation coefficient in the training period, the optimal forecasts are attained by the averaged simulations, and the model is benchmarked with M5 Model Tree and Minimax Probability Machine Regression (MPMR). The results show the proposed ensemble-ANFIS model's preciseness was notably better (in terms of the root mean square and mean absolute error including the Willmott's, Nash-Sutcliffe and Legates McCabe's index) for the 6- and 12- month compared to the 3-month forecasts as verified by the largest error proportions that registered in smallest error band. Applying 10-member simulations, ensemble-ANFIS model was validated for its ability to forecast severity (S), duration (D) and intensity (I) of drought (including the error bound). This enabled uncertainty between multi-models to be rationalized more efficiently, leading to a reduction in forecast error caused by stochasticity in drought behaviours. Through cross-validations at diverse sites, a geographic signature in modelled uncertainties was also calculated. Considering the superiority of ensemble-ANFIS approach and its ability to generate uncertainty-based information, the study advocates the versatility of a multi-model approach for drought-risk forecasting and its prime importance

Bayesian integration of flux tower data into a process-based simulator for quantifying uncertainty in simulated output

NASA Astrophysics Data System (ADS)

Raj, Rahul; van der Tol, Christiaan; Hamm, Nicholas Alexander Samuel; Stein, Alfred

2018-01-01

Parameters of a process-based forest growth simulator are difficult or impossible to obtain from field observations. Reliable estimates can be obtained using calibration against observations of output and state variables. In this study, we present a Bayesian framework to calibrate the widely used process-based simulator Biome-BGC against estimates of gross primary production (GPP) data. We used GPP partitioned from flux tower measurements of a net ecosystem exchange over a 55-year-old Douglas fir stand as an example. The uncertainties of both the Biome-BGC parameters and the simulated GPP values were estimated. The calibrated parameters leaf and fine root turnover (LFRT), ratio of fine root carbon to leaf carbon (FRC : LC), ratio of carbon to nitrogen in leaf (C : Nleaf), canopy water interception coefficient (Wint), fraction of leaf nitrogen in RuBisCO (FLNR), and effective soil rooting depth (SD) characterize the photosynthesis and carbon and nitrogen allocation in the forest. The calibration improved the root mean square error and enhanced Nash-Sutcliffe efficiency between simulated and flux tower daily GPP compared to the uncalibrated Biome-BGC. Nevertheless, the seasonal cycle for flux tower GPP was not reproduced exactly and some overestimation in spring and underestimation in summer remained after calibration. We hypothesized that the phenology exhibited a seasonal cycle that was not accurately reproduced by the simulator. We investigated this by calibrating the Biome-BGC to each month's flux tower GPP separately. As expected, the simulated GPP improved, but the calibrated parameter values suggested that the seasonal cycle of state variables in the simulator could be improved. It was concluded that the Bayesian framework for calibration can reveal features of the modelled physical processes and identify aspects of the process simulator that are too rigid.

A novel integrated modelling framework to assess the impacts of climate and socio-economic drivers on land use and water quality.

PubMed

Zessner, Matthias; Schönhart, Martin; Parajka, Juraj; Trautvetter, Helene; Mitter, Hermine; Kirchner, Mathias; Hepp, Gerold; Blaschke, Alfred Paul; Strenn, Birgit; Schmid, Erwin

2017-02-01

Changes in climatic conditions will directly affect the quality and quantity of water resources. Further on, they will affect them indirectly through adaptation in land use which ultimately influences diffuse nutrient emissions to rivers and therefore potentially the compliance with good ecological status according to the EU Water Framework Directive (WFD). We present an integrated impact modelling framework (IIMF) to track and quantify direct and indirect pollution impacts along policy-economy-climate-agriculture-water interfaces. The IIMF is applied to assess impacts of climatic and socio-economic drivers on agricultural land use (crop choices, farming practices and fertilization levels), river flows and the risk for exceedance of environmental quality standards for determination of the ecological water quality status in Austria. This article also presents model interfaces as well as validation procedures and results of single models and the IIMF with respect to observed state variables such as land use, river flow and nutrient river loads. The performance of the IIMF for calculations of river nutrient loads (120 monitoring stations) shows a Nash-Sutcliffe Efficiency of 0.73 for nitrogen and 0.51 for phosphorus. Most problematic is the modelling of phosphorus loads in the alpine catchments dominated by forests and mountainous landscape. About 63% of these catchments show a deviation between modelled and observed loads of 30% and more. In catchments dominated by agricultural production, the performance of the IIMF is much better as only 30% of cropland and 23% of permanent grassland dominated areas have a deviation of >30% between modelled and observed loads. As risk of exceedance of environmental quality standards is mainly recognized in catchments dominated by cropland, the IIMF is well suited for assessing the nutrient component of the WFD ecological status. Copyright © 2016 British Geological Survey, NERC. Published by Elsevier B.V. All rights reserved.

Simulating high frequency water quality monitoring data using a catchment runoff attenuation flux tool (CRAFT).

PubMed

Adams, Russell; Quinn, Paul F; Perks, Matthew; Barber, Nicholas J; Jonczyk, Jennine; Owen, Gareth J

2016-12-01

High resolution water quality data has recently become widely available from numerous catchment based monitoring schemes. However, the models that can reproduce time series of concentrations or fluxes have not kept pace with the advances in monitoring data. Model performance at predicting phosphorus (P) and sediment concentrations has frequently been poor with models not fit for purpose except for predicting annual losses. Here, the data from the Eden Demonstration Test Catchments (DTC) project have been used to calibrate the Catchment Runoff Attenuation Flux Tool (CRAFT), a new, parsimonious model developed with the aim of modelling both the generation and attenuation of nutrients and sediments in small to medium sized catchments. The CRAFT has the ability to run on an hourly timestep and can calculate the mass of sediments and nutrients transported by three flow pathways representing rapid surface runoff, fast subsurface drainage and slow groundwater flow (baseflow). The attenuation feature of the model is introduced here; this enables surface runoff and contaminants transported via this pathway to be delayed in reaching the catchment outlet. It was used to investigate some hypotheses of nutrient and sediment transport in the Newby Beck Catchment (NBC) Model performance was assessed using a suite of metrics including visual best fit and the Nash-Sutcliffe efficiency. It was found that this approach for water quality models may be the best assessment method as opposed to using a single metric. Furthermore, it was found that, when the aim of the simulations was to reproduce the time series of total P (TP) or total reactive P (TRP) to get the best visual fit, that attenuation was required. The model will be used in the future to explore the impacts on water quality of different mitigation options in the catchment; these will include attenuation of surface runoff. Copyright © 2016 Elsevier B.V. All rights reserved.

Predicting Phosphorus Dynamics Across Physiographic Regions Using a Mixed Hortonian Non-Hortonian Hydrology Model

NASA Astrophysics Data System (ADS)

Collick, A.; Easton, Z. M.; Auerbach, D.; Buchanan, B.; Kleinman, P. J. A.; Fuka, D.

2017-12-01

Predicting phosphorus (P) loss from agricultural watersheds depends on accurate representation of the hydrological and chemical processes governing P mobility and transport. In complex landscapes, P predictions are complicated by a broad range of soils with and without restrictive layers, a wide variety of agricultural management, and variable hydrological drivers. The Soil and Water Assessment Tool (SWAT) is a watershed model commonly used to predict runoff and non-point source pollution transport, but is commonly only used with Hortonian (traditional SWAT) or non-Hortonian (SWAT-VSA) initializations. Many shallow soils underlain by a restricting layer commonly generate saturation excess runoff from variable source areas (VSA), which is well represented in a re-conceptualized version, SWAT-VSA. However, many watersheds exhibit traits of both infiltration excess and saturation excess hydrology internally, based on the hydrologic distance from the stream, distribution of soils across the landscape, and characteristics of restricting layers. The objective of this research is to provide an initial look at integrating distributed predictive capabilities that consider both Hortonian and Non-Hortonian solutions simultaneously within a single SWAT-VSA initialization. We compare results from all three conceptual watershed initializations against measured surface runoff and stream P loads and to highlight the model's ability to drive sub-field management of P. All three initializations predict discharge similarly well (daily Nash-Sutcliffe Efficiencies above 0.5), but the new conceptual SWAT-VSA initialization performed best in predicting P export from the watershed, while also identifying critical source areas - those areas generating large runoff and P losses at the sub field level. These results support the use of mixed Hortonian non-Hortonian SWAT-VSA initializations in predicting watershed-scale P losses and identifying critical source areas of P loss in landscapes

Simulation of streamflow in the Pleasant, Narraguagus, Sheepscot, and Royal Rivers, Maine, using watershed models

USGS Publications Warehouse

Dudley, Robert W.; Nielsen, Martha G.

2011-01-01

The U.S. Geological Survey (USGS) began a study in 2008 to investigate anticipated changes in summer streamflows and stream temperatures in four coastal Maine river basins and the potential effects of those changes on populations of endangered Atlantic salmon. To achieve this purpose, it was necessary to characterize the quantity and timing of streamflow in these rivers by developing and evaluating a distributed-parameter watershed model for a part of each river basin by using the USGS Precipitation-Runoff Modeling System (PRMS). The GIS (geographic information system) Weasel, a USGS software application, was used to delineate the four study basins and their many subbasins, and to derive parameters for their geographic features. The models were calibrated using a four-step optimization procedure in which model output was evaluated against four datasets for calibrating solar radiation, potential evapotranspiration, annual and seasonal water balances, and daily streamflows. The calibration procedure involved thousands of model runs that used the USGS software application Luca (Let us calibrate). Luca uses the Shuffled Complex Evolution (SCE) global search algorithm to calibrate the model parameters. The calibrated watershed models performed satisfactorily, in that Nash-Sutcliffe efficiency (NSE) statistic values for the calibration periods ranged from 0.59 to 0.75 (on a scale of negative infinity to 1) and NSE statistic values for the evaluation periods ranged from 0.55 to 0.73. The calibrated watershed models simulate daily streamflow at many locations in each study basin. These models enable natural resources managers to characterize the timing and amount of streamflow in order to support a variety of water-resources efforts including water-quality calculations, assessments of water use, modeling of population dynamics and migration of Atlantic salmon, modeling and assessment of habitat, and simulation of anticipated changes to streamflow and water temperature

A simple metric to predict stream water quality from storm runoff in an urban watershed.

PubMed

Easton, Zachary M; Sullivan, Patrick J; Walter, M Todd; Fuka, Daniel R; Petrovic, A Martin; Steenhuis, Tammo S

2010-01-01

The contribution of runoff from various land uses to stream channels in a watershed is often speculated and used to underpin many model predictions. However, these contributions, often based on little or no measurements in the watershed, fail to appropriately consider the influence of the hydrologic location of a particular landscape unit in relation to the stream network. A simple model was developed to predict storm runoff and the phosphorus (P) status of a perennial stream in an urban watershed in New York State using the covariance structure of runoff from different landscape units in the watershed to predict runoff in time. One hundred and twenty-seven storm events were divided into parameterization (n = 85) and forecasting (n = 42) data sets. Runoff, dissolved P (DP), and total P (TP) were measured at nine sites distributed among three land uses (high maintenance, unmaintained, wooded), three positions in the watershed (near the outlet, midwatershed, upper watershed), and in the stream at the watershed outlet. The autocorrelation among runoff and P concentrations from the watershed landscape units (n = 9) and the covariance between measurements from the landscape units and measurements from the stream were calculated and used to predict the stream response. Models, validated using leave-one-out cross-validation and a forecasting method, were able to correctly capture temporal trends in streamflow and stream P chemistry (Nash-Sutcliffe efficiencies, 0.49-0.88). The analysis suggests that the covariance structure was consistent for all models, indicating that the physical processes governing runoff and P loss from these landscape units were stationary in time and that landscapes located in hydraulically active areas have a direct hydraulic link to the stream. This methodology provides insight into the impact of various urban landscape units on stream water quantity and quality.

Validation of a national hydrological model

NASA Astrophysics Data System (ADS)

McMillan, H. K.; Booker, D. J.; Cattoën, C.

2016-10-01

Nationwide predictions of flow time-series are valuable for development of policies relating to environmental flows, calculating reliability of supply to water users, or assessing risk of floods or droughts. This breadth of model utility is possible because various hydrological signatures can be derived from simulated flow time-series. However, producing national hydrological simulations can be challenging due to strong environmental diversity across catchments and a lack of data available to aid model parameterisation. A comprehensive and consistent suite of test procedures to quantify spatial and temporal patterns in performance across various parts of the hydrograph is described and applied to quantify the performance of an uncalibrated national rainfall-runoff model of New Zealand. Flow time-series observed at 485 gauging stations were used to calculate Nash-Sutcliffe efficiency and percent bias when simulating between-site differences in daily series, between-year differences in annual series, and between-site differences in hydrological signatures. The procedures were used to assess the benefit of applying a correction to the modelled flow duration curve based on an independent statistical analysis. They were used to aid understanding of climatological, hydrological and model-based causes of differences in predictive performance by assessing multiple hypotheses that describe where and when the model was expected to perform best. As the procedures produce quantitative measures of performance, they provide an objective basis for model assessment that could be applied when comparing observed daily flow series with competing simulated flow series from any region-wide or nationwide hydrological model. Model performance varied in space and time with better scores in larger and medium-wet catchments, and in catchments with smaller seasonal variations. Surprisingly, model performance was not sensitive to aquifer fraction or rain gauge density.

SWAT use of gridded observations for simulating runoff - a Vietnam river basin study

NASA Astrophysics Data System (ADS)

Vu, M. T.; Raghavan, S. V.; Liong, S. Y.

2011-12-01

Many research studies that focus on basin hydrology have used the SWAT model to simulate runoff. One common practice in calibrating the SWAT model is the application of station data rainfall to simulate runoff. But over regions lacking robust station data, there is a problem of applying the model to study the hydrological responses. For some countries and remote areas, the rainfall data availability might be a constraint due to many different reasons such as lacking of technology, war time and financial limitation that lead to difficulty in constructing the runoff data. To overcome such a limitation, this research study uses some of the available globally gridded high resolution precipitation datasets to simulate runoff. Five popular gridded observation precipitation datasets: (1) Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources (APHRODITE), (2) Tropical Rainfall Measuring Mission (TRMM), (3) Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN), (4) Global Precipitation Climatology Project (GPCP), (5) modified Global Historical Climatology Network version 2 (GHCN2) and one reanalysis dataset National Centers for Environment Prediction/National Center for Atmospheric Research (NCEP/NCAR) are used to simulate runoff over the Dakbla River (a small tributary of the Mekong River) in Vietnam. Wherever possible, available station data are also used for comparison. Bilinear interpolation of these gridded datasets is used to input the precipitation data at the closest grid points to the station locations. Sensitivity Analysis and Auto-calibration are performed for the SWAT model. The Nash-Sutcliffe Efficiency (NSE) and Coefficient of Determination (R2) indices are used to benchmark the model performance. This entails a good understanding of the response of the hydrological model to different datasets and a quantification of the uncertainties in these datasets. Such a

Assessment of surface water resources availability using catchment modelling and the results of tracer studies in the mesoscale Migina Catchment, Rwanda

NASA Astrophysics Data System (ADS)

Munyaneza, O.; Mukubwa, A.; Maskey, S.; Uhlenbrook, S.; Wenninger, J.

2014-12-01

In the present study, we developed a catchment hydrological model which can be used to inform water resources planning and decision making for better management of the Migina Catchment (257.4 km2). The semi-distributed hydrological model HEC-HMS (Hydrologic Engineering Center - the Hydrologic Modelling System) (version 3.5) was used with its soil moisture accounting, unit hydrograph, liner reservoir (for baseflow) and Muskingum-Cunge (river routing) methods. We used rainfall data from 12 stations and streamflow data from 5 stations, which were collected as part of this study over a period of 2 years (May 2009 and June 2011). The catchment was divided into five sub-catchments. The model parameters were calibrated separately for each sub-catchment using the observed streamflow data. Calibration results obtained were found acceptable at four stations with a Nash-Sutcliffe model efficiency index (NS) of 0.65 on daily runoff at the catchment outlet. Due to the lack of sufficient and reliable data for longer periods, a model validation was not undertaken. However, we used results from tracer-based hydrograph separation from a previous study to compare our model results in terms of the runoff components. The model performed reasonably well in simulating the total flow volume, peak flow and timing as well as the portion of direct runoff and baseflow. We observed considerable disparities in the parameters (e.g. groundwater storage) and runoff components across the five sub-catchments, which provided insights into the different hydrological processes on a sub-catchment scale. We conclude that such disparities justify the need to consider catchment subdivisions if such parameters and components of the water cycle are to form the base for decision making in water resources planning in the catchment.

Estimating drain flow from measured water table depth in layered soils under free and controlled drainage

NASA Astrophysics Data System (ADS)

Saadat, Samaneh; Bowling, Laura; Frankenberger, Jane; Kladivko, Eileen

2018-01-01

Long records of continuous drain flow are important for quantifying annual and seasonal changes in the subsurface drainage flow from drained agricultural land. Missing data due to equipment malfunction and other challenges have limited conclusions that can be made about annual flow and thus nutrient loads from field studies, including assessments of the effect of controlled drainage. Water table depth data may be available during gaps in flow data, providing a basis for filling missing drain flow data; therefore, the overall goal of this study was to examine the potential to estimate drain flow using water table observations. The objectives were to evaluate how the shape of the relationship between drain flow and water table height above drain varies depending on the soil hydraulic conductivity profile, to quantify how well the Hooghoudt equation represented the water table-drain flow relationship in five years of measured data at the Davis Purdue Agricultural Center (DPAC), and to determine the impact of controlled drainage on drain flow using the filled dataset. The shape of the drain flow-water table height relationship was found to depend on the selected hydraulic conductivity profile. Estimated drain flow using the Hooghoudt equation with measured water table height for both free draining and controlled periods compared well to observed flow with Nash-Sutcliffe Efficiency values above 0.7 and 0.8 for calibration and validation periods, respectively. Using this method, together with linear regression for the remaining gaps, a long-term drain flow record for a controlled drainage experiment at the DPAC was used to evaluate the impacts of controlled drainage on drain flow. In the controlled drainage sites, annual flow was 14-49% lower than free drainage.

Estimating the terrestrial N processes in subtropical mountainous forestry catchment through INCA-N: A case study in FuShan catchment, Taiwan

NASA Astrophysics Data System (ADS)

Lu, Meng-Chang; Huang, -Chuan, Jr.; Chang, Chung-Te; Shih, Yu-Ting; Lin, Teng-Chiu

2016-04-01

The riverine DIN is a crucial indicator for eutrophication in river network. The riverine DIN export in Taiwan is featured by the extremely high yield, ~3800 kg-N km-2yr-1, nearly 20-fold than the global average, showing the interesting terrestrial N process yet rarely documented. In this study we collected the DIN samples in rainwater, soil water, and stream water in a mountainous forest watershed, FuShan experimental forest watershed 1 (WS1) which is a natural broadleaf forest without human activities. Based on the intensive observations, we applied the INCA-N to simulate the riverine DIN response and thus estimate the terrestrial N processes in a global synthesis. The result showed that both discharge and DIN yield were simulated well with the average Nash-Sutcliffe efficiency coefficient of 0.83 and 0.76 , respectively. Among all N processes, N uptake, mineralization, nitrification, denitrfication, and immobilization are significantly positive correlated with soil moisture (R2>0.99), which indicates that soil moisture greatly influences N cycle processes. The average rate of mineralization and nitrification in wet years are consistent with documented values, whereas the rates in dry years are lower than the observations. Despite the high nitrification rate, the secondary forest may uptake abundant N indicating the plant uptake, which responds for removing considerable nitrate, is a controlling factor in forest ecosystem. Our simulated denitrification rate falls between the documented rates of temperate forest and agricultural area, and that may be affected by the high N-deposition in Taiwan. Simulated in-stream denitrification rate is less than 10% of the rate in soil, and is a little lower than that in temperate forest. This preliminary simulation provides an insightful guide to establish the monitoring programme and improve the understanding of N cycle in subtropical.

A model for the spatial distribution of snow water equivalent parameterized from the spatial variability of precipitation

NASA Astrophysics Data System (ADS)

Skaugen, Thomas; Weltzien, Ingunn H.

2016-09-01

Snow is an important and complicated element in hydrological modelling. The traditional catchment hydrological model with its many free calibration parameters, also in snow sub-models, is not a well-suited tool for predicting conditions for which it has not been calibrated. Such conditions include prediction in ungauged basins and assessing hydrological effects of climate change. In this study, a new model for the spatial distribution of snow water equivalent (SWE), parameterized solely from observed spatial variability of precipitation, is compared with the current snow distribution model used in the operational flood forecasting models in Norway. The former model uses a dynamic gamma distribution and is called Snow Distribution_Gamma, (SD_G), whereas the latter model has a fixed, calibrated coefficient of variation, which parameterizes a log-normal model for snow distribution and is called Snow Distribution_Log-Normal (SD_LN). The two models are implemented in the parameter parsimonious rainfall-runoff model Distance Distribution Dynamics (DDD), and their capability for predicting runoff, SWE and snow-covered area (SCA) is tested and compared for 71 Norwegian catchments. The calibration period is 1985-2000 and validation period is 2000-2014. Results show that SDG better simulates SCA when compared with MODIS satellite-derived snow cover. In addition, SWE is simulated more realistically in that seasonal snow is melted out and the building up of "snow towers" and giving spurious positive trends in SWE, typical for SD_LN, is prevented. The precision of runoff simulations using SDG is slightly inferior, with a reduction in Nash-Sutcliffe and Kling-Gupta efficiency criterion of 0.01, but it is shown that the high precision in runoff prediction using SD_LN is accompanied with erroneous simulations of SWE.

Looking beyond general metrics for model comparison - lessons from an international model intercomparison study

NASA Astrophysics Data System (ADS)

de Boer-Euser, Tanja; Bouaziz, Laurène; De Niel, Jan; Brauer, Claudia; Dewals, Benjamin; Drogue, Gilles; Fenicia, Fabrizio; Grelier, Benjamin; Nossent, Jiri; Pereira, Fernando; Savenije, Hubert; Thirel, Guillaume; Willems, Patrick

2017-01-01

International collaboration between research institutes and universities is a promising way to reach consensus on hydrological model development. Although model comparison studies are very valuable for international cooperation, they do often not lead to very clear new insights regarding the relevance of the modelled processes. We hypothesise that this is partly caused by model complexity and the comparison methods used, which focus too much on a good overall performance instead of focusing on a variety of specific events. In this study, we use an approach that focuses on the evaluation of specific events and characteristics. Eight international research groups calibrated their hourly model on the Ourthe catchment in Belgium and carried out a validation in time for the Ourthe catchment and a validation in space for nested and neighbouring catchments. The same protocol was followed for each model and an ensemble of best-performing parameter sets was selected. Although the models showed similar performances based on general metrics (i.e. the Nash-Sutcliffe efficiency), clear differences could be observed for specific events. We analysed the hydrographs of these specific events and conducted three types of statistical analyses on the entire time series: cumulative discharges, empirical extreme value distribution of the peak flows and flow duration curves for low flows. The results illustrate the relevance of including a very quick flow reservoir preceding the root zone storage to model peaks during low flows and including a slow reservoir in parallel with the fast reservoir to model the recession for the studied catchments. This intercomparison enhanced the understanding of the hydrological functioning of the catchment, in particular for low flows, and enabled to identify present knowledge gaps for other parts of the hydrograph. Above all, it helped to evaluate each model against a set of alternative models.

Linking land-use type and stream water quality using spatial data of fecal indicator bacteria and heavy metals in the Yeongsan river basin.

PubMed

Kang, Joo-Hyon; Lee, Seung Won; Cho, Kyung Hwa; Ki, Seo Jin; Cha, Sung Min; Kim, Joon Ha

2010-07-01

This study reveals land-use factors that explain stream water quality during wet and dry weather conditions in a large river basin using two different linear models-multiple linear regression (MLR) models and constrained least squares (CLS) models. Six land-use types and three topographical parameters (size, slope, and permeability) of the watershed were incorporated into the models as explanatory variables. The suggested models were then demonstrated using a digitized elevation map in conjunction with the land-use and the measured concentration data for Escherichia coli (EC), Enterococci bacteria (ENT), and six heavy metal species collected monthly during 2007-2008 at 50 monitoring sites in the Yeongsan Watershed, Korea. The results showed that the MLR models can be a powerful tool for predicting the average concentrations of pollutants in stream water (the Nash-Sutcliffe (NS) model efficiency coefficients ranged from 0.67 to 0.95). On the other hand, the CLS models, with moderately good prediction performance (the NS coefficients ranged 0.28-0.85), were more suitable for quantifying contributions of respective land-uses to the stream water quality. The CLS models suggested that industrial and urban land-uses are major contributors to the stream concentrations of EC and ENT, whereas agricultural, industrial, and mining areas were significant sources of many heavy metal species. In addition, the slope, size, and permeability of the watershed were found to be important factors determining the extent of the contribution from each land-use type to the stream water quality. The models proposed in this paper can be considered useful tools for developing land cover guidelines and for prioritizing locations for implementing management practices to maintain stream water quality standard in a large river basin. Copyright 2010 Elsevier Ltd. All rights reserved.

A pollution fate and transport model application in a semi-arid region: Is some number better than no number?

PubMed

Özcan, Zeynep; Başkan, Oğuz; Düzgün, H Şebnem; Kentel, Elçin; Alp, Emre

2017-10-01

Fate and transport models are powerful tools that aid authorities in making unbiased decisions for developing sustainable management strategies. Application of pollution fate and transport models in semi-arid regions has been challenging because of unique hydrological characteristics and limited data availability. Significant temporal and spatial variability in rainfall events, complex interactions between soil, vegetation and topography, and limited water quality and hydrological data due to insufficient monitoring network make it a difficult task to develop reliable models in semi-arid regions. The performances of these models govern the final use of the outcomes such as policy implementation, screening, economical analysis, etc. In this study, a deterministic distributed fate and transport model, SWAT, is applied in Lake Mogan Watershed, a semi-arid region dominated by dry agricultural practices, to estimate nutrient loads and to develop the water budget of the watershed. To minimize the discrepancy due to limited availability of historical water quality data extensive efforts were placed in collecting site-specific data for model inputs such as soil properties, agricultural practice information and land use. Moreover, calibration parameter ranges suggested in the literature are utilized during calibration in order to obtain more realistic representation of Lake Mogan Watershed in the model. Model performance is evaluated using comparisons of the measured data with 95%CI for the simulated data and comparison of unit pollution load estimations with those provided in the literature for similar catchments, in addition to commonly used evaluation criteria such as Nash-Sutcliffe simulation efficiency, coefficient of determination and percent bias. These evaluations demonstrated that even though the model prediction power is not high according to the commonly used model performance criteria, the calibrated model may provide useful information in the comparison of the

Hydrological and sedimentation implications of landscape changes in a Himalayan catchment due to bioenergy cropping

NASA Astrophysics Data System (ADS)

Remesan, Renji; Holman, Ian; Janes, Victoria

2015-04-01

There is a global effort to focus on the development of bioenergy and energy cropping, due to the generally increasing demand for crude oil, high oil price volatility and climate change mitigation challenges. Second generation energy cropping is expected to increase greatly in India as the Government of India has recently approved a national policy of 20 % biofuel blending by 2017; furthermore, the country's biomass based power generation potential is estimated as around ~24GW and large investments are expected in coming years to increase installed capacity. In this study, we have modelled the environmental influences (e.g.: hydrology and sediment) of scenarios of increased biodiesel cropping (Jatropha curcas) using the Soil and Water Assessment Tool (SWAT) in a northern Indian river basin. SWAT has been applied to the River Beas basin, using daily Tropical Rainfall Measuring Mission (TRMM) precipitation and NCEP Climate Forecast System Reanalysis (CFSR) meteorological data to simulate the river regime and crop yields. We have applied Sequential Uncertainty Fitting Ver. 2 (SUFI-2) to quantify the parameter uncertainty of the stream flow modelling. The model evaluation statistics for daily river flows at the Jwalamukhi and Pong gauges show good agreement with measured flows (Nash Sutcliffe efficiency of 0.70 and PBIAS of 7.54 %). The study has applied two land use change scenarios of (1) increased bioenergy cropping in marginal (grazing) lands in the lower and middle regions of catchment (2) increased bioenergy cropping in low yielding areas of row crops in the lower and middle regions of the catchment. The presentation will describe the improved understanding of the hydrological, erosion and sediment delivery and food production impacts arising from the introduction of a new cropping variety to a marginal area; and illustrate the potential prospects of bioenergy production in Himalayan valleys.

Calibration of the APEX Model to Simulate Management Practice Effects on Runoff, Sediment, and Phosphorus Loss.

PubMed

Bhandari, Ammar B; Nelson, Nathan O; Sweeney, Daniel W; Baffaut, Claire; Lory, John A; Senaviratne, Anomaa; Pierzynski, Gary M; Janssen, Keith A; Barnes, Philip L

2017-11-01

Process-based computer models have been proposed as a tool to generate data for Phosphorus (P) Index assessment and development. Although models are commonly used to simulate P loss from agriculture using managements that are different from the calibration data, this use of models has not been fully tested. The objective of this study is to determine if the Agricultural Policy Environmental eXtender (APEX) model can accurately simulate runoff, sediment, total P, and dissolved P loss from 0.4 to 1.5 ha of agricultural fields with managements that are different from the calibration data. The APEX model was calibrated with field-scale data from eight different managements at two locations (management-specific models). The calibrated models were then validated, either with the same management used for calibration or with different managements. Location models were also developed by calibrating APEX with data from all managements. The management-specific models resulted in satisfactory performance when used to simulate runoff, total P, and dissolved P within their respective systems, with > 0.50, Nash-Sutcliffe efficiency > 0.30, and percent bias within ±35% for runoff and ±70% for total and dissolved P. When applied outside the calibration management, the management-specific models only met the minimum performance criteria in one-third of the tests. The location models had better model performance when applied across all managements compared with management-specific models. Our results suggest that models only be applied within the managements used for calibration and that data be included from multiple management systems for calibration when using models to assess management effects on P loss or evaluate P Indices. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

Multisite Evaluation of APEX for Water Quality: II. Regional Parameterization.

PubMed

Nelson, Nathan O; Baffaut, Claire; Lory, John A; Anomaa Senaviratne, G M M M; Bhandari, Ammar B; Udawatta, Ranjith P; Sweeney, Daniel W; Helmers, Matt J; Van Liew, Mike W; Mallarino, Antonio P; Wortmann, Charles S

2017-11-01

Phosphorus (P) Index assessment requires independent estimates of long-term average annual P loss from fields, representing multiple climatic scenarios, management practices, and landscape positions. Because currently available measured data are insufficient to evaluate P Index performance, calibrated and validated process-based models have been proposed as tools to generate the required data. The objectives of this research were to develop a regional parameterization for the Agricultural Policy Environmental eXtender (APEX) model to estimate edge-of-field runoff, sediment, and P losses in restricted-layer soils of Missouri and Kansas and to assess the performance of this parameterization using monitoring data from multiple sites in this region. Five site-specific calibrated models (SSCM) from within the region were used to develop a regionally calibrated model (RCM), which was further calibrated and validated with measured data. Performance of the RCM was similar to that of the SSCMs for runoff simulation and had Nash-Sutcliffe efficiency (NSE) > 0.72 and absolute percent bias (|PBIAS|) < 18% for both calibration and validation. The RCM could not simulate sediment loss (NSE < 0, |PBIAS| > 90%) and was particularly ineffective at simulating sediment loss from locations with small sediment loads. The RCM had acceptable performance for simulation of total P loss (NSE > 0.74, |PBIAS| < 30%) but underperformed the SSCMs. Total P-loss estimates should be used with caution due to poor simulation of sediment loss. Although we did not attain our goal of a robust regional parameterization of APEX for estimating sediment and total P losses, runoff estimates with the RCM were acceptable for P Index evaluation. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America, Inc.

A new approach to predict soil temperature under vegetated surfaces.

PubMed

Dolschak, Klaus; Gartner, Karl; Berger, Torsten W

2015-12-01

In this article, the setup and the application of an empirical model, based on Newton's law of cooling, capable to predict daily mean soil temperature ( T soil ) under vegetated surfaces, is described. The only input variable, necessary to run the model, is a time series of daily mean air temperature. The simulator employs 9 empirical parameters, which were estimated by inverse modeling. The model, which primarily addresses forested sites, incorporates the effect of snow cover and soil freezing on soil temperature. The model was applied to several temperate forest sites, managing the split between Central Europe (Austria) and the United States (Harvard Forest, Massachusetts; Hubbard Brook, New Hampshire), aiming to cover a broad range of site characteristics. Investigated stands differ fundamentally in stand composition, elevation, exposition, annual mean temperature, precipitation regime, as well as in the duration of winter snow cover. At last, to explore the limits of the formulation, the simulator was applied to non-forest sites (Illinois), where soil temperature was recorded under short cut grass. The model was parameterized, specifically to site and measurement depth. After calibration of the model, an evaluation was performed, using ~50 % of the available data. In each case, the simulator was capable to deliver a feasible prediction of soil temperature in the validation time interval. To evaluate the practical suitability of the simulator, the minimum amount of soil temperature point measurements, necessary to yield expedient model performance was determined. In the investigated case 13-20 point observations, uniformly distributed within an 11-year timeframe, have been proven sufficient to yield sound model performance (root mean square error <0.9 °C, Nash-Sutcliffe efficiency >0.97). This makes the model suitable for the application on sites, where the information on soil temperature is discontinuous or scarce.

Minimum forest cover required for sustainable water flow regulation of a watershed: a case study in Jambi Province, Indonesia

NASA Astrophysics Data System (ADS)

Tarigan, Suria; Wiegand, Kerstin; Sunarti; Slamet, Bejo

2018-01-01

In many tropical regions, the rapid expansion of monoculture plantations has led to a sharp decline in forest cover, potentially degrading the ability of watersheds to regulate water flow. Therefore, regional planners need to determine the minimum proportion of forest cover that is required to support adequate ecosystem services in these watersheds. However, to date, there has been little research on this issue, particularly in tropical areas where monoculture plantations are expanding at an alarming rate. Therefore, in this study, we investigated the influence of forest cover and oil palm (Elaeis guineensis) and rubber (Hevea brasiliensis) plantations on the partitioning of rainfall into direct runoff and subsurface flow in a humid, tropical watershed in Jambi Province, Indonesia. To do this, we simulated streamflow with a calibrated Soil and Water Assessment Tool (SWAT) model and observed several watersheds to derive the direct runoff coefficient (C) and baseflow index (BFI). The model had a strong performance, with Nash-Sutcliffe efficiency values of 0.80-0.88 (calibration) and 0.80-0.85 (validation) and percent bias values of -2.9-1.2 (calibration) and 7.0-11.9 (validation). We found that the percentage of forest cover in a watershed was significantly negatively correlated with C and significantly positively correlated with BFI, whereas the rubber and oil palm plantation cover showed the opposite pattern. Our findings also suggested that at least 30 % of the forest cover was required in the study area for sustainable ecosystem services. This study provides new adjusted crop parameter values for monoculture plantations, particularly those that control surface runoff and baseflow processes, and it also describes the quantitative association between forest cover and flow indicators in a watershed, which will help regional planners in determining the minimum proportion of forest and the maximum proportion of plantation to ensure that a watershed can provide

Application of flood-intensity-duration curve, rainfall-intensity-duration curve and time of concentration to analyze the pattern of storms and their corresponding floods for the natural flood events

NASA Astrophysics Data System (ADS)

Kim, Nam Won; Shin, Mun-Ju; Lee, Jeong Eun

2016-04-01

The analysis of storm effects on floods is essential step for designing hydraulic structure and flood plain. There are previous studies for analyzing the relationship between the storm patterns and peak flow, flood volume and durations for various sizes of the catchments, but they are not enough to analyze the natural storm effects on flood responses quantitatively. This study suggests a novel method of quantitative analysis using unique factors extracted from the time series of storms and floods to investigate the relationship between natural storms and their corresponding flood responses. We used a distributed rainfall-runoff model of Grid based Rainfall-runoff Model (GRM) to generate the simulated flow and areal rainfall for 50 catchments in Republic of Korea size from 5.6 km2 to 1584.2 km2, which are including overlapped dependent catchments and non-overlapped independent catchments. The parameters of the GRM model were calibrated to get the good model performances of Nash-Sutcliffe efficiency. Then Flood-Intensity-Duration Curve (FIDC) and Rainfall-Intensity-Duration Curve (RIDC) were generated by Flood-Duration-Frequency and Intensity-Duration-Frequency methods respectively using the time series of hydrographs and hyetographs. Time of concentration developed for the Korea catchments was used as a consistent measure to extract the unique factors from the FIDC and RIDC over the different size of catchments. These unique factors for the storms and floods were analyzed against the different size of catchments to investigate the natural storm effects on floods. This method can be easily used to get the intuition of the natural storm effects with various patterns on flood responses. Acknowledgement This research was supported by a grant (11-TI-C06) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Precipitation Data Merging over Mountainous Areas Using Satellite Estimates and Sparse Gauge Observations (PDMMA-USESGO) for Hydrological Modeling — A Case Study over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Yang, Z.; Hsu, K. L.; Sorooshian, S.; Xu, X.

2017-12-01

Precipitation in mountain regions generally occurs with high-frequency-intensity, whereas it is not well-captured by sparsely distributed rain-gauges imposing a great challenge on water management. Satellite-based Precipitation Estimation (SPE) provides global high-resolution alternative data for hydro-climatic studies, but are subject to considerable biases. In this study, a model named PDMMA-USESGO for Precipitation Data Merging over Mountainous Areas Using Satellite Estimates and Sparse Gauge Observations is developed to support precipitation mapping and hydrological modeling in mountainous catchments. The PDMMA-USESGO framework includes two calculating steps—adjusting SPE biases and merging satellite-gauge estimates—using the quantile mapping approach, a two-dimensional Gaussian weighting scheme (considering elevation effect), and an inverse root mean square error weighting method. The model is applied and evaluated over the Tibetan Plateau (TP) with the PERSIANN-CCS precipitation retrievals (daily, 0.04°×0.04°) and sparse observations from 89 gauges, for the 11-yr period of 2003-2013. To assess the data merging effects on streamflow modeling, a hydrological evaluation is conducted over a watershed in southeast TP based on the Soil and Water Assessment Tool (SWAT). Evaluation results indicate effectiveness of the model in generating high-resolution-accuracy precipitation estimates over mountainous terrain, with the merged estimates (Mer-SG) presenting consistently improved correlation coefficients, root mean square errors and absolute mean biases from original satellite estimates (Ori-CCS). It is found the Mer-SG forced streamflow simulations exhibit great improvements from those simulations using Ori-CCS, with coefficient of determination (R2) and Nash-Sutcliffe efficiency reach to 0.8 and 0.65, respectively. The presented model and case study serve as valuable references for the hydro-climatic applications using remote sensing-gauge information in

Sensitivity of different satellites gridded data over Brahmaputra Basin byusing Soil and Water Assessment Tool (SWAT)

NASA Astrophysics Data System (ADS)

Paul, S.; Pradhanang, S. M.; Islam, A. S.

2016-12-01

More than half a billion people of India, China, Nepal, Bangladesh and Bhutan are dependent on the water resources of the Brahmaputra river. With climatic and anthropogenic change of this basin region is becoming a cause of concern for future water management and sharing with transboundary riparian nations. To address such issues, robust watershed runoff modeling of the basin is essential. Soil and Water Assessment Tool (SWAT) is a widely used semi-distributed watershed model that is capable of analyzing surface runoff, stream flow, water yield, sediment and nutrient transport in a large river basin such as Brahmaputra, but the performance of runoff the model depends on the accuracy of input precipitation datasets. But for a transboundary basin like Brahmaputra, precipitation gauge data from upstream areas is either not available or not accessible to the scientific communities. Satellite rainfall products are very effective where radar datasets are absent and conventional rain gauges are sparse. However, the sensitivity of the SWAT model to different satellite data products as well as hydrologic parameters for the Brahmaputra Basin are largely unknown. Thus in this study, a comparative analysis with different satellite data product has been made to assess the runoff using SWAT model. Here, datafrom three sources: TRMM, APHRDOTIE and GPCP were used as input precipitation satellite data set and ERA-Interim was used as input temperature dataset from 1998 to 2009. The main methods used in modeling the hydrologic processes in SWAT were curve number method for runoff estimating, Penman-Monteith method for PET and Muskingum method for channel routing. Our preliminary results have revealed thatthe TRMM data product is more accurate than APHRODITE and GPCP for runoff analysis. The coefficient of determination (R2) and Nash-Sutcliffe efficiencies for both calibration and validation period from TRMM data are 0.83 and 0.72, respectively.

Sensitivity of Different Satellites Gridded data over Brahmaputra Basin by using Soil and Water Assessment Tool (SWAT)

NASA Astrophysics Data System (ADS)

Paul, S.; Islam, A. S.; Hasan, M. A.

2015-12-01

More than half a billion people of India, China, Nepal, Bangladesh and Bhutan are directly or indirectly dependent on the water resources of the Brahmaputrariver. With climatic and anthropogenic change of this basin region is becoming a cause of concern for future water management and sharing with transboundary riparian nations. To address such issues, robust watershed runoff modeling of the basin is essential. Soil and Water Assessment Tool (SWAT) is a widely used semi-distributed watershed model that is capable of analyzing surface runoff, stream flow, water yield,sediment and nutrienttransport in a large river basin such as Brahmaputra, but the performance of runoff the model depends on the accuracy of input precipitation datasets. But for a transboundary basin like Brahmaputra, precipitation gauge data from upstream areas is either not available or not accessible to the scientific communities.Satellite rainfall products are very effective where radar datasets are absent and conventional rain gauges are sparse. However, the sensitivity of the SWAT model to different satellite data products as well as hydrologic parameters for the Brahmaputra Basin are largely unknown. Thus in this study, a comparative analysis with different satellite data product has been made to assess the runoff using SWAT model. Here, data from three sources: TRMM, APHRDOTIE and GPCP were used as input precipitation satellite data set and ERA-Interim was used as input temperature dataset from 1998 to 2009. The main methods used in modeling the hydrologic processes in SWAT were curve number method for runoff estimating, Penman-Monteith method for PET and Muskingum method for channel routing. Our preliminary results have revealed thatthe TRMM data product is more accurate than APHRODITE and GPCP for runoff analysis. The coefficient of determination (R2) and Nash-Sutcliffe efficiencies for both calibration and validation period from TRMM data are 0.83 and 0.72, respectively.

Performance of MODIS satellite and mesoscale model based land surface temperature for soil moisture deficit estimation using Neural Network

NASA Astrophysics Data System (ADS)

Srivastava, Prashant K.; Petropoulos, George P.; Gupta, Manika; Islam, Tanvir

2015-04-01

Soil Moisture Deficit (SMD) is a key variable in the water and energy exchanges that occur at the land-surface/atmosphere interface. Monitoring SMD is an alternate method of irrigation scheduling and represents the use of the suitable quantity of water at the proper time by combining measurements of soil moisture deficit. In past it is found that LST has a strong relation to SMD, which can be estimated by MODIS or numerical weather prediction model such as WRF (Weather Research and Forecasting model). By looking into the importance of SMD, this work focused on the application of Artificial Neural Network (ANN) for evaluating its capabilities towards SMD estimation using the LST data estimated from MODIS and WRF mesoscale model. The benchmark SMD estimated from Probability Distribution Model (PDM) over the Brue catchment, Southwest of England, U.K. is used for all the calibration and validation experiments. The performances between observed and simulated SMD are assessed in terms of the Nash-Sutcliffe Efficiency (NSE), the Root Mean Square Error (RMSE) and the percentage of bias (%Bias). The application of the ANN confirmed a high capability WRF and MODIS LST for prediction of SMD. Performance during the ANN calibration and validation showed a good agreement between benchmark and estimated SMD with MODIS LST information with significantly higher performance than WRF simulated LST. The work presented showed the first comprehensive application of LST from MODIS and WRF mesoscale model for hydrological SMD estimation, particularly for the maritime climate. More studies in this direction are recommended to hydro-meteorological community, so that useful information will be accumulated in the technical literature domain for different geographical locations and climatic conditions. Keyword: WRF, Land Surface Temperature, MODIS satellite, Soil Moisture Deficit, Neural Network

Probabilistic inference of ecohydrological parameters using observations from point to satellite scales

NASA Astrophysics Data System (ADS)

Bassiouni, Maoya; Higgins, Chad W.; Still, Christopher J.; Good, Stephen P.

2018-06-01

Vegetation controls on soil moisture dynamics are challenging to measure and translate into scale- and site-specific ecohydrological parameters for simple soil water balance models. We hypothesize that empirical probability density functions (pdfs) of relative soil moisture or soil saturation encode sufficient information to determine these ecohydrological parameters. Further, these parameters can be estimated through inverse modeling of the analytical equation for soil saturation pdfs, derived from the commonly used stochastic soil water balance framework. We developed a generalizable Bayesian inference framework to estimate ecohydrological parameters consistent with empirical soil saturation pdfs derived from observations at point, footprint, and satellite scales. We applied the inference method to four sites with different land cover and climate assuming (i) an annual rainfall pattern and (ii) a wet season rainfall pattern with a dry season of negligible rainfall. The Nash-Sutcliffe efficiencies of the analytical model's fit to soil observations ranged from 0.89 to 0.99. The coefficient of variation of posterior parameter distributions ranged from < 1 to 15 %. The parameter identifiability was not significantly improved in the more complex seasonal model; however, small differences in parameter values indicate that the annual model may have absorbed dry season dynamics. Parameter estimates were most constrained for scales and locations at which soil water dynamics are more sensitive to the fitted ecohydrological parameters of interest. In these cases, model inversion converged more slowly but ultimately provided better goodness of fit and lower uncertainty. Results were robust using as few as 100 daily observations randomly sampled from the full records, demonstrating the advantage of analyzing soil saturation pdfs instead of time series to estimate ecohydrological parameters from sparse records. Our work combines modeling and empirical approaches in

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

NASA Astrophysics Data System (ADS)

Jiao, Yang; Lei, Huimin; Yang, Dawen; Huang, Maoyi; Liu, Dengfeng; Yuan, Xing

2017-08-01

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965-1969) from -0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010-2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.

Simulation of Water Quality in the Tull Creek and West Neck Creek Watersheds, Currituck Sound Basin, North Carolina and Virginia

USGS Publications Warehouse

Garcia, Ana Maria

2009-01-01

A study of the Currituck Sound was initiated in 2005 to evaluate the water chemistry of the Sound and assess the effectiveness of management strategies. As part of this study, the Soil and Water Assessment Tool (SWAT) model was used to simulate current sediment and nutrient loadings for two distinct watersheds in the Currituck Sound basin and to determine the consequences of different water-quality management scenarios. The watersheds studied were (1) Tull Creek watershed, which has extensive row-crop cultivation and artificial drainage, and (2) West Neck Creek watershed, which drains urban areas in and around Virginia Beach, Virginia. The model simulated monthly streamflows with Nash-Sutcliffe model efficiency coefficients of 0.83 and 0.76 for Tull Creek and West Neck Creek, respectively. The daily sediment concentration coefficient of determination was 0.19 for Tull Creek and 0.36 for West Neck Creek. The coefficient of determination for total nitrogen was 0.26 for both watersheds and for dissolved phosphorus was 0.4 for Tull Creek and 0.03 for West Neck Creek. The model was used to estimate current (2006-2007) sediment and nutrient yields for the two watersheds. Total suspended-solids yield was 56 percent lower in the urban watershed than in the agricultural watershed. Total nitrogen export was 45 percent lower, and total phosphorus was 43 percent lower in the urban watershed than in the agricultural watershed. A management scenario with filter strips bordering the main channels was simulated for Tull Creek. The Soil and Water Assessment Tool model estimated a total suspended-solids yield reduction of 54 percent and total nitrogen and total phosphorus reductions of 21 percent and 29 percent, respectively, for the Tull Creek watershed.

A method for deterministic statistical downscaling of daily precipitation at a monsoonal site in Eastern China

NASA Astrophysics Data System (ADS)

Liu, Yonghe; Feng, Jinming; Liu, Xiu; Zhao, Yadi

2017-12-01

Statistical downscaling (SD) is a method that acquires the local information required for hydrological impact assessment from large-scale atmospheric variables. Very few statistical and deterministic downscaling models for daily precipitation have been conducted for local sites influenced by the East Asian monsoon. In this study, SD models were constructed by selecting the best predictors and using generalized linear models (GLMs) for Feixian, a site in the Yishu River Basin and Shandong Province. By calculating and mapping Spearman rank correlation coefficients between the gridded standardized values of five large-scale variables and daily observed precipitation, different cyclonic circulation patterns were found for monsoonal precipitation in summer (June-September) and winter (November-December and January-March); the values of the gridded boxes with the highest absolute correlations for observed precipitation were selected as predictors. Data for predictors and predictands covered the period 1979-2015, and different calibration and validation periods were divided when fitting and validating the models. Meanwhile, the bootstrap method was also used to fit the GLM. All the above thorough validations indicated that the models were robust and not sensitive to different samples or different periods. Pearson's correlations between downscaled and observed precipitation (logarithmically transformed) on a daily scale reached 0.54-0.57 in summer and 0.56-0.61 in winter, and the Nash-Sutcliffe efficiency between downscaled and observed precipitation reached 0.1 in summer and 0.41 in winter. The downscaled precipitation partially reflected exact variations in winter and main trends in summer for total interannual precipitation. For the number of wet days, both winter and summer models were able to reflect interannual variations. Other comparisons were also made in this study. These results demonstrated that when downscaling, it is appropriate to combine a correlation

SnowCloud - a Framework to Predict Streamflow in Snowmelt-dominated Watersheds Using Cloud-based Computing

NASA Astrophysics Data System (ADS)

Sproles, E. A.; Crumley, R. L.; Nolin, A. W.; Mar, E.; Lopez-Moreno, J. J.

2017-12-01

Streamflow in snowy mountain regions is extraordinarily challenging to forecast, and prediction efforts are hampered by the lack of timely snow data—particularly in data sparse regions. SnowCloud is a prototype web-based framework that integrates remote sensing, cloud computing, interactive mapping tools, and a hydrologic model to offer a new paradigm for delivering key data to water resource managers. We tested the skill of SnowCloud to forecast monthly streamflow with one month lead time in three snow-dominated headwaters. These watersheds represent a range of precipitation/runoff schemes: the Río Elqui in northern Chile (200 mm/yr, entirely snowmelt); the John Day River, Oregon, USA (635 mm/yr, primarily snowmelt); and the Río Aragon in the northern Spain (850 mm/yr, snowmelt dominated). Model skill corresponded to snowpack contribution with Nash-Sutcliffe Efficiencies of 0.86, 0.52, and 0.21 respectively. SnowCloud does not require the user to possess advanced programming skills or proprietary software. We access NASA's MOD10A1 snow cover product to calculate the snow metrics globally using Google Earth Engine's geospatial analysis and cloud computing service. The analytics and forecast tools are provided through a web-based portal that requires only internet access and minimal training. To test the efficacy of SnowCloud we provided the tools and a series of tutorials in English and Spanish to water resource managers in Chile, Spain, and the United States. Participants assessed their user experience and provided feedback, and the results of our multi-cultural assessment are also presented. While our results focus on SnowCloud, they outline methods to develop cloud-based tools that function effectively across cultures and languages. Our approach also addresses the primary challenges of science-based computing; human resource limitations, infrastructure costs, and expensive proprietary software. These challenges are particularly problematic in developing

Integration of SRTM and TRMM date into the GIS-based hydrological model for the purpose of flood modelling

NASA Astrophysics Data System (ADS)

Akbari, A.; Abu Samah, A.; Othman, F.

2012-04-01

Due to land use and climate changes, more severe and frequent floods occur worldwide. Flood simulation as the first step in flood risk management can be robustly conducted with integration of GIS, RS and flood modeling tools. The primary goal of this research is to examine the practical use of public domain satellite data and GIS-based hydrologic model. Firstly, database development process is described. GIS tools and techniques were used in the light of relevant literature to achieve the appropriate database. Watershed delineation and parameterizations were carried out using cartographic DEM derived from digital topography at a scale of 1:25 000 with 30 m cell size and SRTM elevation data at 30 m cell size. The SRTM elevation dataset is evaluated and compared with cartographic DEM. With the assistance of statistical measures such as Correlation coefficient (r), Nash-Sutcliffe efficiency (NSE), Percent Bias (PBias) or Percent of Error (PE). According to NSE index, SRTM-DEM can be used for watershed delineation and parameterization with 87% similarity with Topo-DEM in a complex and underdeveloped terrains. Primary TRMM (V6) data was used as satellite based hytograph for rainfall-runoff simulation. The SCS-CN approach was used for losses and kinematic routing method employed for hydrograph transformation through the reaches. It is concluded that TRMM estimates do not give adequate information about the storms as it can be drawn from the rain gauges. Event-based flood modeling using HEC-HMS proved that SRTM elevation dataset has the ability to obviate the lack of terrain data for hydrologic modeling where appropriate data for terrain modeling and simulation of hydrological processes is unavailable. However, TRMM precipitation estimates failed to explain the behavior of rainfall events and its resultant peak discharge and time of peak.

Development and application of a large scale river system model for National Water Accounting in Australia

NASA Astrophysics Data System (ADS)

Dutta, Dushmanta; Vaze, Jai; Kim, Shaun; Hughes, Justin; Yang, Ang; Teng, Jin; Lerat, Julien

2017-04-01

Existing global and continental scale river models, mainly designed for integrating with global climate models, are of very coarse spatial resolutions and lack many important hydrological processes, such as overbank flow, irrigation diversion, groundwater seepage/recharge, which operate at a much finer resolution. Thus, these models are not suitable for producing water accounts, which have become increasingly important for water resources planning and management at regional and national scales. A continental scale river system model called Australian Water Resource Assessment River System model (AWRA-R) has been developed and implemented for national water accounting in Australia using a node-link architecture. The model includes major hydrological processes, anthropogenic water utilisation and storage routing that influence the streamflow in both regulated and unregulated river systems. Two key components of the model are an irrigation model to compute water diversion for irrigation use and associated fluxes and stores and a storage-based floodplain inundation model to compute overbank flow from river to floodplain and associated floodplain fluxes and stores. The results in the Murray-Darling Basin shows highly satisfactory performance of the model with median daily Nash-Sutcliffe Efficiency (NSE) of 0.64 and median annual bias of less than 1% for the period of calibration (1970-1991) and median daily NSE of 0.69 and median annual bias of 12% for validation period (1992-2014). The results have demonstrated that the performance of the model is less satisfactory when the key processes such as overbank flow, groundwater seepage and irrigation diversion are switched off. The AWRA-R model, which has been operationalised by the Australian Bureau of Meteorology for continental scale water accounting, has contributed to improvements in the national water account by substantially reducing accounted different volume (gain/loss).

A comparative study of artificial neural network, adaptive neuro fuzzy inference system and support vector machine for forecasting river flow in the semiarid mountain region

NASA Astrophysics Data System (ADS)

He, Zhibin; Wen, Xiaohu; Liu, Hu; Du, Jun

2014-02-01

Data driven models are very useful for river flow forecasting when the underlying physical relationships are not fully understand, but it is not clear whether these data driven models still have a good performance in the small river basin of semiarid mountain regions where have complicated topography. In this study, the potential of three different data driven methods, artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for forecasting river flow in the semiarid mountain region, northwestern China. The models analyzed different combinations of antecedent river flow values and the appropriate input vector has been selected based on the analysis of residuals. The performance of the ANN, ANFIS and SVM models in training and validation sets are compared with the observed data. The model which consists of three antecedent values of flow has been selected as the best fit model for river flow forecasting. To get more accurate evaluation of the results of ANN, ANFIS and SVM models, the four quantitative standard statistical performance evaluation measures, the coefficient of correlation (R), root mean squared error (RMSE), Nash-Sutcliffe efficiency coefficient (NS) and mean absolute relative error (MARE), were employed to evaluate the performances of various models developed. The results indicate that the performance obtained by ANN, ANFIS and SVM in terms of different evaluation criteria during the training and validation period does not vary substantially; the performance of the ANN, ANFIS and SVM models in river flow forecasting was satisfactory. A detailed comparison of the overall performance indicated that the SVM model performed better than ANN and ANFIS in river flow forecasting for the validation data sets. The results also suggest that ANN, ANFIS and SVM method can be successfully applied to establish river flow with complicated topography forecasting models in the semiarid mountain regions.

Hydroclimatic influences on non-stationary transit time distributions in a boreal headwater catchment

NASA Astrophysics Data System (ADS)

Peralta-Tapia, A.; Soulsby, C.; Tetzlaff, D.; Sponseller, R.; Bishop, K.; Laudon, H.

2016-12-01

Understanding how water moves through catchments - from the time it enters as precipitation to when it exits via streamflow - is of fundamental importance to understanding hydrological and biogeochemical processes. A basic descriptor of this routing is the Transit Time Distribution (TTD) which is derived from the input-output behavior of conservative tracers, the mean of which represents the average time elapsed between water molecules entering and exiting a flow system. In recent decades, many transit time studies have been conducted, but few of these have focused on snow-dominated catchments. We assembled a 10-year time series of isotopic data (δ18O and δ2H) for precipitation and stream water to estimate the characteristics of the transit time distribution in a boreal catchment in northern Sweden. We applied lumped parameter models using a gamma distribution to calculate the Mean Transit Time (MTT) of water over the entire period of record and to evaluate how inter-annual differences in transit times relate to hydroclimatic variability. The best fit MTT for the complete 10-year period was 650 days (Nash-Sutcliff Efficiency = 0.65), while the best fit inter-annual MTT ranged from 300 days up to 1200 days. Whilst there was a weak negative correlation between mean annual total precipitation and the annual MTT, this relationship was stronger (r2 = 0.53, p = 0.02) for the annual rain water input. This strong connection between the MTT and annual rainfall, rather than snowmelt, has strong implications for understanding future hydrological and biogeochemical processes in boreal regions, given that predicted warmer winters would translate into a greater proportion of precipitation falling as rain and thus shorter MTT in catchments. Such a change could have direct implications for the export of solutes and pollutants.

Groundwater flux estimation in streams: A thermal equilibrium approach

NASA Astrophysics Data System (ADS)

Zhou, Yan; Fox, Garey A.; Miller, Ron B.; Mollenhauer, Robert; Brewer, Shannon

2018-06-01

Stream and groundwater interactions play an essential role in regulating flow, temperature, and water quality for stream ecosystems. Temperature gradients have been used to quantify vertical water movement in the streambed since the 1960s, but advancements in thermal methods are still possible. Seepage runs are a method commonly used to quantify exchange rates through a series of streamflow measurements but can be labor and time intensive. The objective of this study was to develop and evaluate a thermal equilibrium method as a technique for quantifying groundwater flux using monitored stream water temperature at a single point and readily available hydrological and atmospheric data. Our primary assumption was that stream water temperature at the monitored point was at thermal equilibrium with the combination of all heat transfer processes, including mixing with groundwater. By expanding the monitored stream point into a hypothetical, horizontal one-dimensional thermal modeling domain, we were able to simulate the thermal equilibrium achieved with known atmospheric variables at the point and quantify unknown groundwater flux by calibrating the model to the resulting temperature signature. Stream water temperatures were monitored at single points at nine streams in the Ozark Highland ecoregion and five reaches of the Kiamichi River to estimate groundwater fluxes using the thermal equilibrium method. When validated by comparison with seepage runs performed at the same time and reach, estimates from the two methods agreed with each other with an R2 of 0.94, a root mean squared error (RMSE) of 0.08 (m/d) and a Nash-Sutcliffe efficiency (NSE) of 0.93. In conclusion, the thermal equilibrium method was a suitable technique for quantifying groundwater flux with minimal cost and simple field installation given that suitable atmospheric and hydrological data were readily available.

DOE Office of Scientific and Technical Information (OSTI.GOV)

A. M. Sexton,; A. M. Sadeghi,; X. Zhang,

The value of watershed-scale, hydrologic and water quality models to ecosystem management is increasingly evident as more programs adopt these tools to evaluate the effectiveness of different management scenarios and their impact on the environment. Quality of precipitation data is critical for appropriate application of watershed models. In small watersheds, where no dense rain gauge network is available, modelers are faced with a dilemma to choose between different data sets. In this study, we used the German Branch (GB) watershed (~50 km 2), which is included in the USDA Conservation Effects Assessment Project (CEAP), to examine the implications of usingmore » surface rain gauge and next-generation radar (NEXRAD) precipitation data sets on the performance of the Soil and Water Assessment Tool (SWAT). The GB watershed is located in the Coastal Plain of Maryland on the eastern shore of Chesapeake Bay. Stream flow estimation results using surface rain gauge data seem to indicate the importance of using rain gauges within the same direction as the storm pattern with respect to the watershed. In the absence of a spatially representative network of rain gauges within the watershed, NEXRAD data produced good estimates of stream flow at the outlet of the watershed. Three NEXRAD datasets, including (1)*non-corrected (NC), (2) bias-corrected (BC), and (3) inverse distance weighted (IDW) corrected NEXRAD data, were produced. Nash-Sutcliffe efficiency coefficients for daily stream flow simulation using these three NEXRAD data ranged from 0.46 to 0.58 during calibration and from 0.68 to 0.76 during validation. Overall, correcting NEXRAD with rain gauge data is promising to produce better hydrologic modeling results. Given the multiple precipitation datasets and corresponding simulations, we explored the combination of the multiple simulations using Bayesian model averaging.« less

How well do terrestrial biosphere models simulate coarse-scale runoff in the contiguous United States?

DOE PAGES

Schwalm, C.; Huntzinger, Deborah N.; Cook, Robert B.; ...

2015-03-11

Significant changes in the water cycle are expected under current global environmental change. Robust assessment of present-day water cycle dynamics at continental to global scales is confounded by shortcomings in the observed record. Modeled assessments also yield conflicting results which are linked to differences in model structure and simulation protocol. Here we compare simulated gridded (1 spatial resolution) runoff from six terrestrial biosphere models (TBMs), seven reanalysis products, and one gridded surface station product in the contiguous United States (CONUS) from 2001 to 2005. We evaluate the consistency of these 14 estimates with stream gauge data, both as depleted flowmore » and corrected for net withdrawals (2005 only), at the CONUS and water resource region scale, as well as examining similarity across TBMs and reanalysis products at the grid cell scale. Mean runoff across all simulated products and regions varies widely (range: 71 to 356 mm yr(-1)) relative to observed continental-scale runoff (209 or 280 mm yr(-1) when corrected for net withdrawals). Across all 14 products 8 exhibit Nash-Sutcliffe efficiency values in excess of 0.8 and three are within 10% of the observed value. Region-level mismatch exhibits a weak pattern of overestimation in western and underestimation in eastern regions although two products are systematically biased across all regions and largely scales with water use. Although gridded composite TBM and reanalysis runoff show some regional similarities, individual product values are highly variable. At the coarse scales used here we find that progress in better constraining simulated runoff requires standardized forcing data and the explicit incorporation of human effects (e.g., water withdrawals by source, fire, and land use change). (C) 2015 Elsevier B.V. All rights reserved.« less

Impacts of Land Use Change on the Natural Flow Regime: A Case Study in the Meramec River Watershed in Eastern Missouri, USA

NASA Astrophysics Data System (ADS)

Wu, C. L.; Knouft, J.; Chu, M.

2017-12-01

The natural flow regime within a watershed can be considered as the expected temporal patterns of streamflow variation in the absence of human impacts. While ecosystems have evolved to function under these conditions, the natural flow regime of most rivers has been significantly altered by human activities. Land use change, including the development of agriculture and urbanization, is a primary cause of the loss of natural flow regimes. These changes have altered discharge volume, timing, and variability, and consequently affected the structure and functioning of river ecosystems. The Meramec River watershed is located in east central Missouri and changes in land use have been the primary factor impacting flow regimes across the watershed. In this study, a watershed model, the Soil and Water Assessment Tool (SWAT), was developed to simulate a long-term time series of streamflow (1978-2014) within the watershed. Model performance was evaluated using statistical metrics and graphical technique including R-squared, Nash-Sutcliffe efficiency, cumulative error, and 1:1-ratio comparison between observed and simulated variables. The calibrated and validated SWAT model was then used to quantify the responses of the watershed when it was a forested natural landscape. An Indicator of Hydrologic Alteration (IHA) approach was applied to characterize the flow regime under the current landcover conditions as well as the simulated natural flow regime under the no land use change scenario. Differences in intra- and inter-annual ecologically relevant flow metrics were then compared using SWAT model outputs in conjunction with the IHA approach based on model outputs from current and no land use change conditions. This study provides a watershed-scale understanding of effects of land use change on a river's flow variability and provides a framework for the development of restoration plans for heavily altered watersheds.

Measuring and Modeling Suspended Sediment and Nutrient Yields from a Mixed-Land-Use Watershed of the Central U.S.

NASA Astrophysics Data System (ADS)

Zeiger, S. J.; Hubbart, J. A.

2016-12-01

A nested-scale watershed study design was used to monitor water quantity and quality of an impaired 3rd order stream in a rapidly urbanizing mixed-land-use watershed of the central USA. Grab samples were collected at each gauging site (n=836 samples x 5 gauging sites) and analyzed for suspended sediment, total phosphorus, and inorganic nitrogen species during the four year study period (2010 - 2013). Observed data were used to quantify relationships between climate, land use and pollutant loading. Additionally, Soil and Water Assessment Tool (SWAT) estimates of monthly stream flow, suspended sediment, total phosphorus, nitrate, nitrite, and ammonium were validated. Total annual precipitation ranged from approximately 650 mm during 2012 (extreme drought year) to 1350 mm during 2010 (record setting wet year) which caused significant (p<0.05) differences in annual pollutant yields (i.e. loads per unit area) that ranged from 115 to 174%. Multiple linear regression analyses showed significant (p<0.05) relationships between pollutant loading, annual total precipitation (positive correlate), urban land use (positive correlate), forested land use (negative correlate), and wetland land use (negative correlate). Results from SWAT model performance assessment indicated calibration was necessary to achieve Nash-Sutcliff Efficiency (NSE) values greater than 0.05 for monthly pollutant loads. Calibrating the SWAT model to multiple gauging sites within the watershed improved estimates of monthly stream flow (NSE=0.83), and pollutant loads (NSE>0.78). However, nitrite and ammonium loads were underestimated by more than four orders of magnitude (NSE<-0.16) indicating a critical need for improved nutrient cycling and routing routines. Results highlight the need for sampling regimens that capture the variability of climate and flow mediated pollutant transport, and the benefits of calibrating the SWAT model to multiple gauging sites in mixed-land-use watersheds.

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiao, Yang; Lei, Huimin; Yang, Dawen

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of ecohydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of themore » Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from 0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.« less

Evaluation of acidity estimation methods for mine drainage, Pennsylvania, USA.

PubMed

Park, Daeryong; Park, Byungtae; Mendinsky, Justin J; Paksuchon, Benjaphon; Suhataikul, Ratda; Dempsey, Brian A; Cho, Yunchul

2015-01-01

Eighteen sites impacted by abandoned mine drainage (AMD) in Pennsylvania were sampled and measured for pH, acidity, alkalinity, metal ions, and sulfate. This study compared the accuracy of four acidity calculation methods with measured hot peroxide acidity and identified the most accurate calculation method for each site as a function of pH and sulfate concentration. Method E1 was the sum of proton and acidity based on total metal concentrations; method E2 added alkalinity; method E3 also accounted for aluminum speciation and temperature effects; and method E4 accounted for sulfate speciation. To evaluate errors between measured and predicted acidity, the Nash-Sutcliffe efficiency (NSE), the coefficient of determination (R (2)), and the root mean square error to standard deviation ratio (RSR) methods were applied. The error evaluation results show that E1, E2, E3, and E4 sites were most accurate at 0, 9, 4, and 5 of the sites, respectively. Sites where E2 was most accurate had pH greater than 4.0 and less than 400 mg/L of sulfate. Sites where E3 was most accurate had pH greater than 4.0 and sulfate greater than 400 mg/L with two exceptions. Sites where E4 was most accurate had pH less than 4.0 and more than 400 mg/L sulfate with one exception. The results indicate that acidity in AMD-affected streams can be accurately predicted by using pH, alkalinity, sulfate, Fe(II), Mn(II), and Al(III) concentrations in one or more of the identified equations, and that the appropriate equation for prediction can be selected based on pH and sulfate concentration.

Fitting rainfall interception models to forest ecosystems of Mexico

NASA Astrophysics Data System (ADS)

Návar, José

2017-05-01

Models that accurately predict forest interception are essential both for water balance studies and for assessing watershed responses to changes in land use and the long-term climate variability. This paper compares the performance of four rainfall interception models-the sparse Gash (1995), Rutter et al. (1975), Liu (1997) and two new models (NvMxa and NvMxb)-using data from four spatially extensive, structurally diverse forest ecosystems in Mexico. Ninety-eight case studies measuring interception in tropical dry (25), arid/semi-arid (29), temperate (26), and tropical montane cloud forests (18) were compiled and analyzed. Coefficients derived from raw data or published statistical relationships were used as model input to evaluate multi-storm forest interception at the case study scale. On average empirical data showed that, tropical montane cloud, temperate, arid/semi-arid and tropical dry forests intercepted 14%, 18%, 22% and 26% of total precipitation, respectively. The models performed well in predicting interception, with mean deviations between measured and modeled interception as a function of total precipitation (ME) generally <5.8% and Nash-Sutcliffe efficiency E estimators >0.66. Model fitting precision was dependent on the forest ecosystem. Arid/semi-arid forests exhibited the smallest, while tropical montane cloud forest displayed the largest ME deviations. Improved agreement between measured and modeled data requires modification of in-storm evaporation rate in the Liu; the canopy storage in the sparse Gash model; and the throughfall coefficient in the Rutter and the NvMx models. This research concludes on recommending the wide application of rainfall interception models with some caution as they provide mixed results. The extensive forest interception data source, the fitting and testing of four models, the introduction of a new model, and the availability of coefficient values for all four forest ecosystems are an important source of information and

Assessment of Seasonal Water Balance Components over India Using Macroscale Hydrological Model

NASA Astrophysics Data System (ADS)

Joshi, S.; Raju, P. V.; Hakeem, K. A.; Rao, V. V.; Yadav, A.; Issac, A. M.; Diwakar, P. G.; Dadhwal, V. K.

2016-12-01

Hydrological models provide water balance components which are useful for water resources assessment and for capturing the seasonal changes and impact of anthropogenic interventions and climate change. The study under description is a national level modeling framework for country India using wide range of geo-spatial and hydro-meteorological data sets for estimating daily Water Balance Components (WBCs) at 0.15º grid resolution using Variable Infiltration Capacity model. The model parameters were optimized through calibration of model computed stream flow with field observed yielding Nash-Sutcliffe efficiency between 0.5 to 0.7. The state variables, evapotranspiration (ET) and soil moisture were also validated, obtaining R2 values of 0.57 and 0.69, respectively. Using long-term meteorological data sets, model computation were carried to capture hydrological extremities. During 2013, 2014 and 2015 monsoon seasons, WBCs were estimated and were published in web portal with 2-day time lag. In occurrence of disaster events, weather forecast was ingested, high surface runoff zones were identified for forewarning and disaster preparedness. Cumulative monsoon season rainfall of 2013, 2014 and 2015 were 105, 89 and 91% of long period average (LPA) respectively (Source: India Meteorological Department). Analysis of WBCs indicated that corresponding seasonal surface runoff was 116, 81 and 86% LPA and evapotranspiration was 109, 104 and 90% LPA. Using the grid-wise data, the spatial variation in WBCs among river basins/administrative regions was derived to capture the changes in surface runoff, ET between the years and in comparison with LPA. The model framework is operational and is providing periodic account of national level water balance fluxes which are useful for quantifying spatial and temporal variation in basin/sub-basin scale water resources, periodical water budgeting to form vital inputs for studies on water resources and climate change.

The Worst-Case Weighted Multi-Objective Game with an Application to Supply Chain Competitions.

PubMed

Qu, Shaojian; Ji, Ying

2016-01-01

In this paper, we propose a worst-case weighted approach to the multi-objective n-person non-zero sum game model where each player has more than one competing objective. Our "worst-case weighted multi-objective game" model supposes that each player has a set of weights to its objectives and wishes to minimize its maximum weighted sum objectives where the maximization is with respect to the set of weights. This new model gives rise to a new Pareto Nash equilibrium concept, which we call "robust-weighted Nash equilibrium". We prove that the robust-weighted Nash equilibria are guaranteed to exist even when the weight sets are unbounded. For the worst-case weighted multi-objective game with the weight sets of players all given as polytope, we show that a robust-weighted Nash equilibrium can be obtained by solving a mathematical program with equilibrium constraints (MPEC). For an application, we illustrate the usefulness of the worst-case weighted multi-objective game to a supply chain risk management problem under demand uncertainty. By the comparison with the existed weighted approach, we show that our method is more robust and can be more efficiently used for the real-world applications.

Energy-efficient downlink resource management in self-organized OFDMA-based two-tier femtocell networks

NASA Astrophysics Data System (ADS)

Shahid, Adnan; Aslam, Saleem; Kim, Hyung Seok; Lee, Kyung-Geun

2015-12-01

Femtocell is a novel technology that is used for escalating indoor coverage as well as the capacity of traditional cellular networks. However, interference is the limiting factor for performance improvement due to co-channel deployment between macrocells and femtocells. The traditional network planning is not feasible because of the random deployment of femtocells. Therefore, self-organization approaches are the key to having successful deployment of femtocells. This study presents the joint resource block (RB) and power allocation task for the two-tier femtocell network in a self-organizing manner, with the concern to minimizing the impact of interference and maximizing the energy efficiency. In this study, we analyze the performance of the system in terms of the energy efficiency, which is composed of both the transmission and circuit power. Most of the previous studies investigate the performance regarding the throughput requirement of the two-tier femtocell network while the energy efficiency aspect is largely ignored. Here, the joint allocation task is modeled as a non-cooperative game which is demonstrated to exhibit pure and unique Nash equilibrium. In order to reduce the complexity of the proposed non-cooperative game, the joint RB and power allocation task is divided into two subproblems: an RB allocation and a particle swarm optimization-based power allocation. The analysis of the proposed game is carried out in terms of not only energy efficiency but also throughput. With practical 3rd Generation Partnership Project (3GPP) Long-Term Evolution (LTE) parameters, the simulation results illustrate the superior performance of the proposed game as compared to the traditional methods. Also, the comparison is carried out with the joint allocation scheme which only considers the throughput as the objective function. The results illustrate that significant performance improvement is achieved in terms of energy efficiency with slight loss in the throughput. The

A multi-objective model for closed-loop supply chain optimization and efficient supplier selection in a competitive environment considering quantity discount policy

NASA Astrophysics Data System (ADS)

Jahangoshai Rezaee, Mustafa; Yousefi, Samuel; Hayati, Jamileh

2017-06-01

Supplier selection and allocation of optimal order quantity are two of the most important processes in closed-loop supply chain (CLSC) and reverse logistic (RL). So that providing high quality raw material is considered as a basic requirement for a manufacturer to produce popular products, as well as achieve more market shares. On the other hand, considering the existence of competitive environment, suppliers have to offer customers incentives like discounts and enhance the quality of their products in a competition with other manufacturers. Therefore, in this study, a model is presented for CLSC optimization, efficient supplier selection, as well as orders allocation considering quantity discount policy. It is modeled using multi-objective programming based on the integrated simultaneous data envelopment analysis-Nash bargaining game. In this study, maximizing profit and efficiency and minimizing defective and functions of delivery delay rate are taken into accounts. Beside supplier selection, the suggested model selects refurbishing sites, as well as determining the number of products and parts in each network's sector. The suggested model's solution is carried out using global criteria method. Furthermore, based on related studies, a numerical example is examined to validate it.

The Worst-Case Weighted Multi-Objective Game with an Application to Supply Chain Competitions

PubMed Central

Qu, Shaojian; Ji, Ying

2016-01-01

In this paper, we propose a worst-case weighted approach to the multi-objective n-person non-zero sum game model where each player has more than one competing objective. Our “worst-case weighted multi-objective game” model supposes that each player has a set of weights to its objectives and wishes to minimize its maximum weighted sum objectives where the maximization is with respect to the set of weights. This new model gives rise to a new Pareto Nash equilibrium concept, which we call “robust-weighted Nash equilibrium”. We prove that the robust-weighted Nash equilibria are guaranteed to exist even when the weight sets are unbounded. For the worst-case weighted multi-objective game with the weight sets of players all given as polytope, we show that a robust-weighted Nash equilibrium can be obtained by solving a mathematical program with equilibrium constraints (MPEC). For an application, we illustrate the usefulness of the worst-case weighted multi-objective game to a supply chain risk management problem under demand uncertainty. By the comparison with the existed weighted approach, we show that our method is more robust and can be more efficiently used for the real-world applications. PMID:26820512

Efficient data communication protocols for wireless networks

NASA Astrophysics Data System (ADS)

Zeydan, Engin

In this dissertation, efficient decentralized algorithms are investigated for cost minimization problems in wireless networks. For wireless sensor networks, we investigate both the reduction in the energy consumption and throughput maximization problems separately using multi-hop data aggregation for correlated data in wireless sensor networks. The proposed algorithms exploit data redundancy using a game theoretic framework. For energy minimization, routes are chosen to minimize the total energy expended by the network using best response dynamics to local data. The cost function used in routing takes into account distance, interference and in-network data aggregation. The proposed energy-efficient correlation-aware routing algorithm significantly reduces the energy consumption in the network and converges in a finite number of steps iteratively. For throughput maximization, we consider both the interference distribution across the network and correlation between forwarded data when establishing routes. Nodes along each route are chosen to minimize the interference impact in their neighborhood and to maximize the in-network data aggregation. The resulting network topology maximizes the global network throughput and the algorithm is guaranteed to converge with a finite number of steps using best response dynamics. For multiple antenna wireless ad-hoc networks, we present distributed cooperative and regret-matching based learning schemes for joint transmit beanformer and power level selection problem for nodes operating in multi-user interference environment. Total network transmit power is minimized while ensuring a constant received signal-to-interference and noise ratio at each receiver. In cooperative and regret-matching based power minimization algorithms, transmit beanformers are selected from a predefined codebook to minimize the total power. By selecting transmit beamformers judiciously and performing power adaptation, the cooperative algorithm is shown to

Equivalent survival following liver transplantation in patients with non-alcoholic steatohepatitis compared with patients with other liver diseases.

PubMed

Kennedy, Christopher; Redden, David; Gray, Stephen; Eckhoff, Devin; Massoud, Omar; McGuire, Brendan; Alkurdi, Basem; Bloomer, Joseph; DuBay, Derek A

2012-09-01

Orthotopic liver transplantation (LT) in non-alcoholic steatohepatitis (NASH) is increasing in parallel with the obesity epidemic. This study retrospectively reviewed the clinical outcomes of LTs in NASH (n = 129) and non-NASH (n = 775) aetiologies carried out at a single centre between 1999 and 2009. Rates of 1-, 3- and 5-year overall survival in NASH (90%, 88% and 85%, respectively) were comparable with those in non-NASH (92%, 86% and 80%, respectively) patients. Mortality within 4 months of LT was twice as high in NASH as in non-NASH patients (8.5% vs. 4.2%; P = 0.04). Compared with non-NASH patients, post-LT mortality in NASH patients was more commonly caused by infectious (38% vs. 26%; P < 0.05) or cardiac (19% vs. 7%; P < 0.05) aetiologies. Five-year survival was lower in NASH patients with a high-risk phenotype (age >60 years, body mass index >30 kg/m(2), with hypertension and diabetes) than in NASH patients without these characteristics (72% vs. 87%; P = 0.02). Subgroup analyses revealed that 5-year overall survival in NASH was equivalent to that in Laennec's cirrhosis (85% vs. 80%; P 0.87), but lower than that in cirrhosis of cryptogenic aetiology (85% vs. 96%; P = 0.04). Orthotopic LT in NASH was associated with increased early postoperative mortality, but 1-, 3- and 5-year overall survival rates were equivalent to those in non-NASH patients. © 2012 International Hepato-Pancreato-Biliary Association.

Simulation of California's Major Reservoirs Outflow Using Data Mining Technique

NASA Astrophysics Data System (ADS)

Yang, T.; Gao, X.; Sorooshian, S.

2014-12-01

The reservoir's outflow is controlled by reservoir operators, which is different from the upstream inflow. The outflow is more important than the reservoir's inflow for the downstream water users. In order to simulate the complicated reservoir operation and extract the outflow decision making patterns for California's 12 major reservoirs, we build a data-driven, computer-based ("artificial intelligent") reservoir decision making tool, using decision regression and classification tree approach. This is a well-developed statistical and graphical modeling methodology in the field of data mining. A shuffled cross validation approach is also employed to extract the outflow decision making patterns and rules based on the selected decision variables (inflow amount, precipitation, timing, water type year etc.). To show the accuracy of the model, a verification study is carried out comparing the model-generated outflow decisions ("artificial intelligent" decisions) with that made by reservoir operators (human decisions). The simulation results show that the machine-generated outflow decisions are very similar to the real reservoir operators' decisions. This conclusion is based on statistical evaluations using the Nash-Sutcliffe test. The proposed model is able to detect the most influential variables and their weights when the reservoir operators make an outflow decision. While the proposed approach was firstly applied and tested on California's 12 major reservoirs, the method is universally adaptable to other reservoir systems.

Impact of Climate Variability and Landscape Patterns on Water Budget and Nutrient Loads in a Peri-urban Watershed: A Coupled Analysis Using Process-based Hydrological Model and Landscape Indices.

PubMed

Li, Chongwei; Zhang, Yajuan; Kharel, Gehendra; Zou, Chris B

2018-06-01

Nutrient discharge into peri-urban streams and reservoirs constitutes a significant pressure on environmental management, but quantitative assessment of non-point source pollution under climate variability in fast changing peri-urban watersheds is challenging. Soil and Water Assessment Tool (SWAT) was used to simulate water budget and nutrient loads for landscape patterns representing a 30-year progression of urbanization in a peri-urban watershed near Tianjin metropolis, China. A suite of landscape pattern indices was related to nitrogen (N) and phosphorous (P) loads under dry and wet climate using CANOCO redundancy analysis. The calibrated SWAT model was adequate to simulate runoff and nutrient loads for this peri-urban watershed, with Nash-Sutcliffe coefficient (NSE) and coefficient of determination (R 2 ) > 0.70 and percentage bias (PBIAS) between -7 and +18 for calibration and validation periods. With the progression of urbanization, forest remained the main "sink" landscape while cultivated and urban lands remained the main "source" landscapes with the role of orchard and grassland being uncertain and changing with time. Compared to 1984, the landscape use pattern in 2013 increased nutrient discharge by 10%. Nutrient loads modelled under wet climate were 3-4 times higher than that under dry climate for the same landscape pattern. Results indicate that climate change could impose a far greater impact on runoff and nutrient discharge in a peri-urban watershed than landscape pattern change.

A two-phase copula entropy-based multiobjective optimization approach to hydrometeorological gauge network design

NASA Astrophysics Data System (ADS)

Xu, Pengcheng; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi; Liu, Jiufu; Zou, Ying; He, Ruimin

2017-12-01

Hydrometeorological data are needed for obtaining point and areal mean, quantifying the spatial variability of hydrometeorological variables, and calibration and verification of hydrometeorological models. Hydrometeorological networks are utilized to collect such data. Since data collection is expensive, it is essential to design an optimal network based on the minimal number of hydrometeorological stations in order to reduce costs. This study proposes a two-phase copula entropy- based multiobjective optimization approach that includes: (1) copula entropy-based directional information transfer (CDIT) for clustering the potential hydrometeorological gauges into several groups, and (2) multiobjective method for selecting the optimal combination of gauges for regionalized groups. Although entropy theory has been employed for network design before, the joint histogram method used for mutual information estimation has several limitations. The copula entropy-based mutual information (MI) estimation method is shown to be more effective for quantifying the uncertainty of redundant information than the joint histogram (JH) method. The effectiveness of this approach is verified by applying to one type of hydrometeorological gauge network, with the use of three model evaluation measures, including Nash-Sutcliffe Coefficient (NSC), arithmetic mean of the negative copula entropy (MNCE), and MNCE/NSC. Results indicate that the two-phase copula entropy-based multiobjective technique is capable of evaluating the performance of regional hydrometeorological networks and can enable decision makers to develop strategies for water resources management.

Utilization of Expert Knowledge in a Multi-Objective Hydrologic Model Automatic Calibration Process

NASA Astrophysics Data System (ADS)

Quebbeman, J.; Park, G. H.; Carney, S.; Day, G. N.; Micheletty, P. D.

2016-12-01

Spatially distributed continuous simulation hydrologic models have a large number of parameters for potential adjustment during the calibration process. Traditional manual calibration approaches of such a modeling system is extremely laborious, which has historically motivated the use of automatic calibration procedures. With a large selection of model parameters, achieving high degrees of objective space fitness - measured with typical metrics such as Nash-Sutcliffe, Kling-Gupta, RMSE, etc. - can easily be achieved using a range of evolutionary algorithms. A concern with this approach is the high degree of compensatory calibration, with many similarly performing solutions, and yet grossly varying parameter set solutions. To help alleviate this concern, and mimic manual calibration processes, expert knowledge is proposed for inclusion within the multi-objective functions, which evaluates the parameter decision space. As a result, Pareto solutions are identified with high degrees of fitness, but also create parameter sets that maintain and utilize available expert knowledge resulting in more realistic and consistent solutions. This process was tested using the joint SNOW-17 and Sacramento Soil Moisture Accounting method (SAC-SMA) within the Animas River basin in Colorado. Three different elevation zones, each with a range of parameters, resulted in over 35 model parameters simultaneously calibrated. As a result, high degrees of fitness were achieved, in addition to the development of more realistic and consistent parameter sets such as those typically achieved during manual calibration procedures.

Simulation of Nitrogen and Phosphorus Load Runoff by a GIS-based Distributed Model for Chikugo River Watershed

NASA Astrophysics Data System (ADS)

Iseri, Haruka; Hiramatsu, Kazuaki; Harada, Masayoshi

A distributed model was developed in order to simulate the process of nitrogen and phosphorus load runoff in the semi-urban watershed of the Chikugo River, Japan. A grid of cells 1km in size was laid over the study area, and several input variables for each cell area including DEM, land use and statistical data were extracted by GIS. In the process of water runoff, hydrograph calculated at Chikugo Barrage was in close agreement with the observed one, which achieved Nash-Sutcliffe coefficient of 0.90. In addition, the model simulated reasonably well the movement of TN and TP at each station. The model was also used to analyze three scenarios based on the watershed management: (1) reduction of nutrient loads from livestock farm, (2) improvement of septic tanks' wastewater treatment system and (3) application of purification function of paddy fields. As a result, effectiveness of management strategy in each scenario depended on land use patterns. The reduction rates of nutrient load effluent in scenarios (1) and (3) were higher than that in scenario (2). The present result suggests that an appropriate management of livestock farm together with the effective use of paddy environment would have significant effects on the reduction of nutrient loads. A suitable management strategy should be planned based on the land use pattern in the watershed.

The best alternative for estimating reference crop evapotranspiration in different sub-regions of mainland China.

PubMed

Peng, Lingling; Li, Yi; Feng, Hao

2017-07-14

Reference crop evapotranspiration (ET o ) is a critically important parameter for climatological, hydrological and agricultural management. The FAO56 Penman-Monteith (PM) equation has been recommended as the standardized ET o (ET o,s ) equation, but it has a high requirements of climatic data. There is a practical need for finding a best alternative method to estimate ET o in the regions where full climatic data are lacking. A comprehensive comparison for the spatiotemporal variations, relative errors, standard deviations and Nash-Sutcliffe efficacy coefficients of monthly or annual ET o,s and ET o,i (i = 1, 2, …, 10) values estimated by 10 selected methods (i.e., Irmak et al., Makkink, Priestley-Taylor, Hargreaves-Samani, Droogers-Allen, Berti et al., Doorenbos-Pruitt, Wright and Valiantzas, respectively) using data at 552 sites over 1961-2013 in mainland China. The method proposed by Berti et al. (2014) was selected as the best alternative of FAO56-PM because it was simple in computation process, only utilized temperature data, had generally good accuracy in describing spatiotemporal characteristics of ET o,s in different sub-regions and mainland China, and correlated linearly to the FAO56-PM method very well. The parameters of the linear correlations between ET o of the two methods are calibrated for each site with the smallest determination of coefficient being 0.87.

Impact of Climate Variability and Landscape Patterns on Water Budget and Nutrient Loads in a Peri-urban Watershed: A Coupled Analysis Using Process-based Hydrological Model and Landscape Indices

NASA Astrophysics Data System (ADS)

Li, Chongwei; Zhang, Yajuan; Kharel, Gehendra; Zou, Chris B.

2018-06-01

Nutrient discharge into peri-urban streams and reservoirs constitutes a significant pressure on environmental management, but quantitative assessment of non-point source pollution under climate variability in fast changing peri-urban watersheds is challenging. Soil and Water Assessment Tool (SWAT) was used to simulate water budget and nutrient loads for landscape patterns representing a 30-year progression of urbanization in a peri-urban watershed near Tianjin metropolis, China. A suite of landscape pattern indices was related to nitrogen (N) and phosphorous (P) loads under dry and wet climate using CANOCO redundancy analysis. The calibrated SWAT model was adequate to simulate runoff and nutrient loads for this peri-urban watershed, with Nash-Sutcliffe coefficient (NSE) and coefficient of determination ( R 2) > 0.70 and percentage bias (PBIAS) between -7 and +18 for calibration and validation periods. With the progression of urbanization, forest remained the main "sink" landscape while cultivated and urban lands remained the main "source" landscapes with the role of orchard and grassland being uncertain and changing with time. Compared to 1984, the landscape use pattern in 2013 increased nutrient discharge by 10%. Nutrient loads modelled under wet climate were 3-4 times higher than that under dry climate for the same landscape pattern. Results indicate that climate change could impose a far greater impact on runoff and nutrient discharge in a peri-urban watershed than landscape pattern change.

Streamflow characteristics from modelled runoff time series: Importance of calibration criteria selection

USGS Publications Warehouse

Poole, Sandra; Vis, Marc; Knight, Rodney; Seibert, Jan

2017-01-01

Ecologically relevant streamflow characteristics (SFCs) of ungauged catchments are often estimated from simulated runoff of hydrologic models that were originally calibrated on gauged catchments. However, SFC estimates of the gauged donor catchments and subsequently the ungauged catchments can be substantially uncertain when models are calibrated using traditional approaches based on optimization of statistical performance metrics (e.g., Nash–Sutcliffe model efficiency). An improved calibration strategy for gauged catchments is therefore crucial to help reduce the uncertainties of estimated SFCs for ungauged catchments. The aim of this study was to improve SFC estimates from modeled runoff time series in gauged catchments by explicitly including one or several SFCs in the calibration process. Different types of objective functions were defined consisting of the Nash–Sutcliffe model efficiency, single SFCs, or combinations thereof. We calibrated a bucket-type runoff model (HBV – Hydrologiska Byråns Vattenavdelning – model) for 25 catchments in the Tennessee River basin and evaluated the proposed calibration approach on 13 ecologically relevant SFCs representing major flow regime components and different flow conditions. While the model generally tended to underestimate the tested SFCs related to mean and high-flow conditions, SFCs related to low flow were generally overestimated. The highest estimation accuracies were achieved by a SFC-specific model calibration. Estimates of SFCs not included in the calibration process were of similar quality when comparing a multi-SFC calibration approach to a traditional model efficiency calibration. For practical applications, this implies that SFCs should preferably be estimated from targeted runoff model calibration, and modeled estimates need to be carefully interpreted.

How far can we go in hydrological modelling without any knowledge of runoff formation processes?

NASA Astrophysics Data System (ADS)

Ayzel, Georgy

2016-04-01

Hydrological modelling is a challenging scientific issue for the last 50 years and tend to be it further because of the highest level of runoff formation processes complexity at the different spatio-temporal scales. Enormous number of modelling-related papers have submitted to the top-ranked journals every year, but in this publication speed race authors have pay increasing attention to the models and data they use by itself rather than underlying watershed processes. Great community effort of the free and open-source models sharing with high availability of hydrometeorological data sources led to conceptual shifting paradigm of hydrological science to the technical-oriented direction. In the third-world countries this shifting is more clear by the reason of field studies absence and obligatory requirement of practical significance of the research supported by the government funds. As a result we get a state of hydrological modelling discipline closer to the aim of high Nash-Sutcliffe efficiency (NSE) achievement rather than watershed processes understanding. Both lumped physically-based land-surface model SWAP (Soil Water - Atmosphere - Plants) and SCE-UA (Shuffled Complex Evolution method developed at The University of Arizona) technique for robust model parameters search were used for the runoff modelling of 323 MOPEX watersheds. No one special data analysis and expert knowledge-based decisions were not performed. Median value of NSE is 0.652 and 90% of watersheds have efficiency bigger than 0.5. Thus without any information of particular features of each watershed satisfactory modelling results were obtained. To prove our conclusions we build cutting-edge conceptual rainfall-runoff model based on decision trees and adaptive boosting machine learning algorithms for the one small watershed in USA. No one special data analysis or feature engineering was not performed too. Obtained results demonstrate great model prediction power both for learning and testing

Identifying influential data points in hydrological model calibration and their impact on streamflow predictions

NASA Astrophysics Data System (ADS)

Wright, David; Thyer, Mark; Westra, Seth

2015-04-01

Highly influential data points are those that have a disproportionately large impact on model performance, parameters and predictions. However, in current hydrological modelling practice the relative influence of individual data points on hydrological model calibration is not commonly evaluated. This presentation illustrates and evaluates several influence diagnostics tools that hydrological modellers can use to assess the relative influence of data. The feasibility and importance of including influence detection diagnostics as a standard tool in hydrological model calibration is discussed. Two classes of influence diagnostics are evaluated: (1) computationally demanding numerical "case deletion" diagnostics; and (2) computationally efficient analytical diagnostics, based on Cook's distance. These diagnostics are compared against hydrologically orientated diagnostics that describe changes in the model parameters (measured through the Mahalanobis distance), performance (objective function displacement) and predictions (mean and maximum streamflow). These influence diagnostics are applied to two case studies: a stage/discharge rating curve model, and a conceptual rainfall-runoff model (GR4J). Removing a single data point from the calibration resulted in differences to mean flow predictions of up to 6% for the rating curve model, and differences to mean and maximum flow predictions of up to 10% and 17%, respectively, for the hydrological model. When using the Nash-Sutcliffe efficiency in calibration, the computationally cheaper Cook's distance metrics produce similar results to the case-deletion metrics at a fraction of the computational cost. However, Cooks distance is adapted from linear regression with inherit assumptions on the data and is therefore less flexible than case deletion. Influential point detection diagnostics show great potential to improve current hydrological modelling practices by identifying highly influential data points. The findings of this

Estimation of water table level and nitrate pollution based on geostatistical and multiple mass transport models

NASA Astrophysics Data System (ADS)

Matiatos, Ioannis; Varouhakis, Emmanouil A.; Papadopoulou, Maria P.

2015-04-01

As the sustainable use of groundwater resources is a great challenge for many countries in the world, groundwater modeling has become a very useful and well established tool for studying groundwater management problems. Based on various methods used to numerically solve algebraic equations representing groundwater flow and contaminant mass transport, numerical models are mainly divided into Finite Difference-based and Finite Element-based models. The present study aims at evaluating the performance of a finite difference-based (MODFLOW-MT3DMS), a finite element-based (FEFLOW) and a hybrid finite element and finite difference (Princeton Transport Code-PTC) groundwater numerical models simulating groundwater flow and nitrate mass transport in the alluvial aquifer of Trizina region in NE Peloponnese, Greece. The calibration of groundwater flow in all models was performed using groundwater hydraulic head data from seven stress periods and the validation was based on a series of hydraulic head data for two stress periods in sufficient numbers of observation locations. The same periods were used for the calibration of nitrate mass transport. The calibration and validation of the three models revealed that the simulated values of hydraulic heads and nitrate mass concentrations coincide well with the observed ones. The models' performance was assessed by performing a statistical analysis of these different types of numerical algorithms. A number of metrics, such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Bias, Nash Sutcliffe Model Efficiency (NSE) and Reliability Index (RI) were used allowing the direct comparison of models' performance. Spatiotemporal Kriging (STRK) was also applied using separable and non-separable spatiotemporal variograms to predict water table level and nitrate concentration at each sampling station for two selected hydrological stress periods. The predictions were validated using the respective measured values. Maps of water table

A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition

PubMed Central

Zhang, Xike; Zhang, Qiuwen; Zhang, Gui; Nie, Zhiping; Gui, Zifan; Que, Huafei

2018-01-01

Daily land surface temperature (LST) forecasting is of great significance for application in climate-related, agricultural, eco-environmental, or industrial studies. Hybrid data-driven prediction models using Ensemble Empirical Mode Composition (EEMD) coupled with Machine Learning (ML) algorithms are useful for achieving these purposes because they can reduce the difficulty of modeling, require less history data, are easy to develop, and are less complex than physical models. In this article, a computationally simple, less data-intensive, fast and efficient novel hybrid data-driven model called the EEMD Long Short-Term Memory (LSTM) neural network, namely EEMD-LSTM, is proposed to reduce the difficulty of modeling and to improve prediction accuracy. The daily LST data series from the Mapoling and Zhijiang stations in the Dongting Lake basin, central south China, from 1 January 2014 to 31 December 2016 is used as a case study. The EEMD is firstly employed to decompose the original daily LST data series into many Intrinsic Mode Functions (IMFs) and a single residue item. Then, the Partial Autocorrelation Function (PACF) is used to obtain the number of input data sample points for LSTM models. Next, the LSTM models are constructed to predict the decompositions. All the predicted results of the decompositions are aggregated as the final daily LST. Finally, the prediction performance of the hybrid EEMD-LSTM model is assessed in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), Pearson Correlation Coefficient (CC) and Nash-Sutcliffe Coefficient of Efficiency (NSCE). To validate the hybrid data-driven model, the hybrid EEMD-LSTM model is compared with the Recurrent Neural Network (RNN), LSTM and Empirical Mode Decomposition (EMD) coupled with RNN, EMD-LSTM and EEMD-RNN models, and their comparison results demonstrate that the hybrid EEMD-LSTM model performs better than the other five

Effect of formal and informal likelihood functions on uncertainty assessment in a single event rainfall-runoff model

NASA Astrophysics Data System (ADS)

Nourali, Mahrouz; Ghahraman, Bijan; Pourreza-Bilondi, Mohsen; Davary, Kamran

2016-09-01

In the present study, DREAM(ZS), Differential Evolution Adaptive Metropolis combined with both formal and informal likelihood functions, is used to investigate uncertainty of parameters of the HEC-HMS model in Tamar watershed, Golestan province, Iran. In order to assess the uncertainty of 24 parameters used in HMS, three flood events were used to calibrate and one flood event was used to validate the posterior distributions. Moreover, performance of seven different likelihood functions (L1-L7) was assessed by means of DREAM(ZS)approach. Four likelihood functions, L1-L4, Nash-Sutcliffe (NS) efficiency, Normalized absolute error (NAE), Index of agreement (IOA), and Chiew-McMahon efficiency (CM), is considered as informal, whereas remaining (L5-L7) is represented in formal category. L5 focuses on the relationship between the traditional least squares fitting and the Bayesian inference, and L6, is a hetereoscedastic maximum likelihood error (HMLE) estimator. Finally, in likelihood function L7, serial dependence of residual errors is accounted using a first-order autoregressive (AR) model of the residuals. According to the results, sensitivities of the parameters strongly depend on the likelihood function, and vary for different likelihood functions. Most of the parameters were better defined by formal likelihood functions L5 and L7 and showed a high sensitivity to model performance. Posterior cumulative distributions corresponding to the informal likelihood functions L1, L2, L3, L4 and the formal likelihood function L6 are approximately the same for most of the sub-basins, and these likelihood functions depict almost a similar effect on sensitivity of parameters. 95% total prediction uncertainty bounds bracketed most of the observed data. Considering all the statistical indicators and criteria of uncertainty assessment, including RMSE, KGE, NS, P-factor and R-factor, results showed that DREAM(ZS) algorithm performed better under formal likelihood functions L5 and L7

A Novel Hybrid Data-Driven Model for Daily Land Surface Temperature Forecasting Using Long Short-Term Memory Neural Network Based on Ensemble Empirical Mode Decomposition.

PubMed

Zhang, Xike; Zhang, Qiuwen; Zhang, Gui; Nie, Zhiping; Gui, Zifan; Que, Huafei

2018-05-21

Daily land surface temperature (LST) forecasting is of great significance for application in climate-related, agricultural, eco-environmental, or industrial studies. Hybrid data-driven prediction models using Ensemble Empirical Mode Composition (EEMD) coupled with Machine Learning (ML) algorithms are useful for achieving these purposes because they can reduce the difficulty of modeling, require less history data, are easy to develop, and are less complex than physical models. In this article, a computationally simple, less data-intensive, fast and efficient novel hybrid data-driven model called the EEMD Long Short-Term Memory (LSTM) neural network, namely EEMD-LSTM, is proposed to reduce the difficulty of modeling and to improve prediction accuracy. The daily LST data series from the Mapoling and Zhijaing stations in the Dongting Lake basin, central south China, from 1 January 2014 to 31 December 2016 is used as a case study. The EEMD is firstly employed to decompose the original daily LST data series into many Intrinsic Mode Functions (IMFs) and a single residue item. Then, the Partial Autocorrelation Function (PACF) is used to obtain the number of input data sample points for LSTM models. Next, the LSTM models are constructed to predict the decompositions. All the predicted results of the decompositions are aggregated as the final daily LST. Finally, the prediction performance of the hybrid EEMD-LSTM model is assessed in terms of the Mean Square Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Root Mean Square Error (RMSE), Pearson Correlation Coefficient (CC) and Nash-Sutcliffe Coefficient of Efficiency (NSCE). To validate the hybrid data-driven model, the hybrid EEMD-LSTM model is compared with the Recurrent Neural Network (RNN), LSTM and Empirical Mode Decomposition (EMD) coupled with RNN, EMD-LSTM and EEMD-RNN models, and their comparison results demonstrate that the hybrid EEMD-LSTM model performs better than the other five

Fena Valley Reservoir watershed and water-balance model updates and expansion of watershed modeling to southern Guam

USGS Publications Warehouse

Rosa, Sarah N.; Hay, Lauren E.

2017-12-01

In 2014, the U.S. Geological Survey, in cooperation with the U.S. Department of Defense’s Strategic Environmental Research and Development Program, initiated a project to evaluate the potential impacts of projected climate-change on Department of Defense installations that rely on Guam’s water resources. A major task of that project was to develop a watershed model of southern Guam and a water-balance model for the Fena Valley Reservoir. The southern Guam watershed model provides a physically based tool to estimate surface-water availability in southern Guam. The U.S. Geological Survey’s Precipitation Runoff Modeling System, PRMS-IV, was used to construct the watershed model. The PRMS-IV code simulates different parts of the hydrologic cycle based on a set of user-defined modules. The southern Guam watershed model was constructed by updating a watershed model for the Fena Valley watersheds, and expanding the modeled area to include all of southern Guam. The Fena Valley watershed model was combined with a previously developed, but recently updated and recalibrated Fena Valley Reservoir water-balance model.Two important surface-water resources for the U.S. Navy and the citizens of Guam were modeled in this study; the extended model now includes the Ugum River watershed and improves upon the previous model of the Fena Valley watersheds. Surface water from the Ugum River watershed is diverted and treated for drinking water, and the Fena Valley watersheds feed the largest surface-water reservoir on Guam. The southern Guam watershed model performed “very good,” according to the criteria of Moriasi and others (2007), in the Ugum River watershed above Talofofo Falls with monthly Nash-Sutcliffe efficiency statistic values of 0.97 for the calibration period and 0.93 for the verification period (a value of 1.0 represents perfect model fit). In the Fena Valley watershed, monthly simulated streamflow volumes from the watershed model compared reasonably well with the

Questionnaire survey on lifestyle of patients with nonalcoholic steatohepatitis

PubMed Central

Noto, Haruka; Tokushige, Katsutoshi; Hashimoto, Etsuko; Taniai, Makiko; Shiratori, Keiko

2014-01-01

Lack of exercise and excessive food intake are known to be the important causes of nonalcoholic steatohepatitis (NASH). To elucidate the relationship between lifestyle and NASH, we surveyed exercise and dietary habits, comparing them among 171 biopsy-proven NASH patients, 29 nonalcoholic fatty liver (NAFL) patients and 49 normal subjects. Dietary habits including the duration of dinner time, amount of rice at dinner, and weekly frequencies of meat, fries, Chinese noodles, sweets, and instant food consumption were significantly different in male NASH patients compared to normal male subjects. In women, differences were seen in the amount of rice at dinner, frequency of eating out, and proclivity for sweets. In male NASH patients, the frequency of physical exercise was significantly lower. The lifestyle tendencies of NASH were almost similar to those of NAFL. In the comparison between obese NASH and non-obese NASH, no clear lifestyle differences were found. In conclusion, the most striking result of this survey was that the lifestyle of males contributed significantly to the development of NASH. These results point to treatment of NASH in males. In female NASH patients, lifestyle differences were minimal, and the effects of other factors such as genetic background will need to be investigated. PMID:25411525

Questionnaire survey on lifestyle of patients with nonalcoholic steatohepatitis.

PubMed

Noto, Haruka; Tokushige, Katsutoshi; Hashimoto, Etsuko; Taniai, Makiko; Shiratori, Keiko

2014-11-01

Lack of exercise and excessive food intake are known to be the important causes of nonalcoholic steatohepatitis (NASH). To elucidate the relationship between lifestyle and NASH, we surveyed exercise and dietary habits, comparing them among 171 biopsy-proven NASH patients, 29 nonalcoholic fatty liver (NAFL) patients and 49 normal subjects. Dietary habits including the duration of dinner time, amount of rice at dinner, and weekly frequencies of meat, fries, Chinese noodles, sweets, and instant food consumption were significantly different in male NASH patients compared to normal male subjects. In women, differences were seen in the amount of rice at dinner, frequency of eating out, and proclivity for sweets. In male NASH patients, the frequency of physical exercise was significantly lower. The lifestyle tendencies of NASH were almost similar to those of NAFL. In the comparison between obese NASH and non-obese NASH, no clear lifestyle differences were found. In conclusion, the most striking result of this survey was that the lifestyle of males contributed significantly to the development of NASH. These results point to treatment of NASH in males. In female NASH patients, lifestyle differences were minimal, and the effects of other factors such as genetic background will need to be investigated.

Non-alcoholic fatty liver disease - histological scoring systems: a large cohort single-center, evaluation study.

PubMed

Rastogi, Archana; Shasthry, Saggere Muralikrishna; Agarwal, Ayushi; Bihari, Chhagan; Jain, Priyanka; Jindal, Ankur; Sarin, Shiv

2017-11-01

Non-alcoholic fatty liver disease (NAFLD) is an increasingly common cause of chronic liver disease. Till date, liver biopsy remains the gold standard for identification and quantification of the wide histological spectra of NAFLD. Histological scorings are very useful and widely applied for the diagnosis and management in clinical trials and follow-up studies of non-alcoholic steatohepatitis (NASH). However, in view of scarce published literature, there is a need to evaluate them in large cohort of NAFLD. This study was aimed to evaluate the two histological scoring systems (NAS-CRN, SAF) in the diagnosis of NAFLD and to assess the role of histological characteristics as injury markers in NAFLD. Retrospective histological study of liver biopsies of 1000 patients diagnosed as NAFLD, between 2010 and 2016, was conducted. Histopathologic evaluation and semiquantiative scoring based on NAS-CRN and SAF algorithm and their correlation with serum aminotransferase and fibrosis were performed. Liver biopsies were classified according to the NAS-CRN scoring, as NAS <3 (not NASH) in 72 (7.2%), NAS 3-4 (borderline NASH) in 310 (31%), and NAS ≥5 (definite NASH) in 618 (61.8%), and SAF classified 117 (11.7%) not NASH and 883 (88.3%) definite NASH. There was excellent concordance for definite NASH and not NASH; however, 88.06% of borderline NASH was classified as NASH by SAF. 76.39% by NAS and 78.63% by SAF algorithm who were diagnosed as not NASH showed the presence of fibrosis; however, higher stages of fibrosis were significantly more prevalent in definite NASH, excluding burnt-out cirrhosis. Serum ALT was significantly associated with increasing stages of fibrosis (p < 0.001) and the three categories (not NASH, borderline NASH, and definite NASH) when classified as with/without fibrosis (p < 0.001). Steatosis of higher grades, more ballooned cells, and more foci of Lobular Inflammation were found in significantly higher proportion of patients with NASH (p < 0

Molecular Approach to Hypothalamic Rhythms: Isolation of Novel Indoleamine Receptor Genes

DTIC Science & Technology

1993-03-14

well PCR Cloning, Library Screening, and Sequence Analysis. as the lateral geniculate and superior colliculus. Serotonergic Poly(A)-enriched RNA was...CAMP, one negatively (G) and one positively (Gs). The latter is a candidate for the serotonin receptor that mediates phase advances in circadian rhythms...Texas (Sutcliffe, Erlander) Concepts in Biology and Medicine, Scripps Faculty Lecture Series (Sutcliffe) Advances in the Pharmacology and Clinical

Association of coffee and caffeine consumption with fatty liver disease, nonalcoholic steatohepatitis, and degree of hepatic fibrosis.

PubMed

Molloy, Jeffrey W; Calcagno, Christopher J; Williams, Christopher D; Jones, Frances J; Torres, Dawn M; Harrison, Stephen A

2012-02-01

Coffee caffeine consumption (CC) is associated with reduced hepatic fibrosis in patients with chronic liver diseases, such as hepatitis C. The association of CC with nonalcoholic fatty liver disease (NAFLD) has not been established. The aim of this study was to correlate CC with the prevalence and severity of NAFLD. Patients involved in a previously published NAFLD prevalence study, as well as additional NASH patients identified in the Brooke Army Medical Center Hepatology clinic, were queried about their caffeine intake. A validated questionnaire for CC was utilized to assess for a relationship between caffeine and four groups: ultrasound negative (controls), bland steatosis/not-NASH, NASH stage 0-1, and NASH stage 2-4. A total of 306 patients responded to the CC questionnaire. Average milligrams of total caffeine/coffee CC per day in controls, bland steatosis/not-NASH, NASH stage 0-1, and NASH stage 2-4 were 307/228, 229/160, 351/255, and 252/152, respectively. When comparing patients with bland steatosis/not-NASH to those with NASH stage 0-1, there was a significant difference in CC between the two groups (P = 0.005). Additionally, when comparing patients with NASH stage 0-1 to those with NASH stage 2-4, there was a significant difference in coffee CC (P = 0.016). Spearman's rank correlation analysis further supported a negative relationship between coffee CC and hepatic fibrosis (r = -0.215; P = 0.035). Coffee CC is associated with a significant reduction in risk of fibrosis among NASH patients. Copyright © 2011 American Association for the Study of Liver Diseases.

Altered Bile Acid Metabolome in Patients with Nonalcoholic Steatohepatitis.

PubMed

Ferslew, Brian C; Xie, Guoxiang; Johnston, Curtis K; Su, Mingming; Stewart, Paul W; Jia, Wei; Brouwer, Kim L R; Barritt, A Sidney

2015-11-01

The prevalence of nonalcoholic fatty liver disease (NAFLD) and steatohepatitis (NASH) is increasing at an alarming rate. The role of bile acids in the development and progression of NAFLD to NASH and cirrhosis is poorly understood. This study aimed to quantify the bile acid metabolome in healthy subjects and patients with non-cirrhotic NASH under fasting conditions and after a standardized meal. Liquid chromatography tandem mass spectroscopy was used to quantify 30 serum and 16 urinary bile acids from 15 healthy volunteers and 7 patients with biopsy-confirmed NASH. Bile acid concentrations were measured at two fasting and four post-prandial time points following a high-fat meal to induce gallbladder contraction and bile acid reabsorption from the intestine. Patients with NASH had significantly higher total serum bile acid concentrations than healthy subjects under fasting conditions (2.2- to 2.4-fold increase in NASH; NASH 2595-3549 µM and healthy 1171-1458 µM) and at all post-prandial time points (1.7- to 2.2-fold increase in NASH; NASH 4444-5898 µM and healthy 2634-2829 µM). These changes were driven by increased taurine- and glycine-conjugated primary and secondary bile acids. Patients with NASH exhibited greater variability in their fasting and post-prandial bile acid profile. Results indicate that patients with NASH have higher fasting and post-prandial exposure to bile acids, including the more hydrophobic and cytotoxic secondary species. Increased bile acid exposure may be involved in liver injury and the pathogenesis of NAFLD and NASH.

Prevalence and predictors of nonalcoholic steatohepatitis in obese patients undergoing bariatric surgery: a Department of Defense experience.

PubMed

Reha, Jeffrey L; Lee, Sukhyung; Hofmann, Luke J

2014-06-01

Nonalcoholic steatohepatitis (NASH) is a silent liver disease that can lead to inflammation and subsequent scaring. If left untreated, cirrhosis may ensue. Morbidly obese patients are at an increased risk of NASH. We report the prevalence and predictors of NASH in patients undergoing morbid obesity surgery. A retrospective review was conducted on morbidly obese patients undergoing weight reduction surgery from September 2005 through December 2008. A liver biopsy was performed at the time of surgery. Patients who had a history of hepatitis infection or previous alcohol dependency were excluded. Prevalence of NASH was studied. Predictors of NASH among clinical and biochemical variables were analyzed using multivariate regression analysis. One hundred thirteen patients were analyzed (84% female; mean age, 42.6 ± 11.4 years; mean body mass index, 45.1 ± 5.7 kg/m(2)). Sixty-one patients had systemic hypertension (54%) and 35 patients had diabetes (31%). The prevalence of NASH in this study population was 35 per cent (40 of 113). An additional 59 patients (52%) had simple steatosis without NASH. Only 14 patients had normal liver histology. On multivariate analysis, only elevated aspartate aminotransferase (AST) (greater than 41 IU/L) was the independent predictor for NASH (odds ratio, 5.85; confidence interval, 1.06 to 32.41). Patient age, body mass index, hypertension, diabetes, hypercholesterolemia, and abnormal alanine aminotransferase did not predict NASH. NASH is a common finding in obese population. Abnormal AST was the only predictive factor for NASH.

Power-efficient distributed resource allocation under goodput QoS constraints for heterogeneous networks

NASA Astrophysics Data System (ADS)

Andreotti, Riccardo; Del Fiorentino, Paolo; Giannetti, Filippo; Lottici, Vincenzo

2016-12-01

This work proposes a distributed resource allocation (RA) algorithm for packet bit-interleaved coded OFDM transmissions in the uplink of heterogeneous networks (HetNets), characterized by small cells deployed over a macrocell area and sharing the same band. Every user allocates its transmission resources, i.e., bits per active subcarrier, coding rate, and power per subcarrier, to minimize the power consumption while both guaranteeing a target quality of service (QoS) and accounting for the interference inflicted by other users transmitting over the same band. The QoS consists of the number of information bits delivered in error-free packets per unit of time, or goodput (GP), estimated at the transmitter by resorting to an efficient effective SNR mapping technique. First, the RA problem is solved in the point-to-point case, thus deriving an approximate yet accurate closed-form expression for the power allocation (PA). Then, the interference-limited HetNet case is examined, where the RA problem is described as a non-cooperative game, providing a solution in terms of generalized Nash equilibrium. Thanks to the closed-form of the PA, the solution analysis is based on the best response concept. Hence, sufficient conditions for existence and uniqueness of the solution are analytically derived, along with a distributed algorithm capable of reaching the game equilibrium.

Application of Shuffled Frog Leaping Algorithm and Genetic Algorithm for the Optimization of Urban Stormwater Drainage

NASA Astrophysics Data System (ADS)

Kumar, S.; Kaushal, D. R.; Gosain, A. K.

2017-12-01

Urban hydrology will have an increasing role to play in the sustainability of human settlements. Expansion of urban areas brings significant changes in physical characteristics of landuse. Problems with administration of urban flooding have their roots in concentration of population within a relatively small area. As watersheds are urbanized, infiltration decreases, pattern of surface runoff is changed generating high peak flows, large runoff volumes from urban areas. Conceptual rainfall-runoff models have become a foremost tool for predicting surface runoff and flood forecasting. Manual calibration is often time consuming and tedious because of the involved subjectivity, which makes automatic approach more preferable. The calibration of parameters usually includes numerous criteria for evaluating the performances with respect to the observed data. Moreover, derivation of objective function assosciat6ed with the calibration of model parameters is quite challenging. Various studies dealing with optimization methods has steered the embracement of evolution based optimization algorithms. In this paper, a systematic comparison of two evolutionary approaches to multi-objective optimization namely shuffled frog leaping algorithm (SFLA) and genetic algorithms (GA) is done. SFLA is a cooperative search metaphor, stimulated by natural memetics based on the population while, GA is based on principle of survival of the fittest and natural evolution. SFLA and GA has been employed for optimizing the major parameters i.e. width, imperviousness, Manning's coefficient and depression storage for the highly urbanized catchment of Delhi, India. The study summarizes the auto-tuning of a widely used storm water management model (SWMM), by internal coupling of SWMM with SFLA and GA separately. The values of statistical parameters such as, Nash-Sutcliffe efficiency (NSE) and Percent Bias (PBIAS) were found to lie within the acceptable limit, indicating reasonably good model performance

The importance of parameterization when simulating the hydrologic response of vegetative land-cover change

NASA Astrophysics Data System (ADS)

White, Jeremy; Stengel, Victoria; Rendon, Samuel; Banta, John

2017-08-01

Computer models of hydrologic systems are frequently used to investigate the hydrologic response of land-cover change. If the modeling results are used to inform resource-management decisions, then providing robust estimates of uncertainty in the simulated response is an important consideration. Here we examine the importance of parameterization, a necessarily subjective process, on uncertainty estimates of the simulated hydrologic response of land-cover change. Specifically, we applied the soil water assessment tool (SWAT) model to a 1.4 km2 watershed in southern Texas to investigate the simulated hydrologic response of brush management (the mechanical removal of woody plants), a discrete land-cover change. The watershed was instrumented before and after brush-management activities were undertaken, and estimates of precipitation, streamflow, and evapotranspiration (ET) are available; these data were used to condition and verify the model. The role of parameterization in brush-management simulation was evaluated by constructing two models, one with 12 adjustable parameters (reduced parameterization) and one with 1305 adjustable parameters (full parameterization). Both models were subjected to global sensitivity analysis as well as Monte Carlo and generalized likelihood uncertainty estimation (GLUE) conditioning to identify important model inputs and to estimate uncertainty in several quantities of interest related to brush management. Many realizations from both parameterizations were identified as behavioral in that they reproduce daily mean streamflow acceptably well according to Nash-Sutcliffe model efficiency coefficient, percent bias, and coefficient of determination. However, the total volumetric ET difference resulting from simulated brush management remains highly uncertain after conditioning to daily mean streamflow, indicating that streamflow data alone are not sufficient to inform the model inputs that influence the simulated outcomes of brush

Evaluation of sub daily satellite rainfall estimates through flash flood modelling in the Lower Middle Zambezi Basin

NASA Astrophysics Data System (ADS)

Matingo, Thomas; Gumindoga, Webster; Makurira, Hodson

2018-05-01

Flash floods are experienced almost annually in the ungauged Mbire District of the Middle Zambezi Basin. Studies related to hydrological modelling (rainfall-runoff) and flood forecasting require major inputs such as precipitation which, due to shortage of observed data, are increasingly using indirect methods for estimating precipitation. This study therefore evaluated performance of CMORPH and TRMM satellite rainfall estimates (SREs) for 30 min, 1 h, 3 h and daily intensities through hydrologic and flash flood modelling in the Lower Middle Zambezi Basin for the period 2013-2016. On a daily timestep, uncorrected CMORPH and TRMM show Probability of Detection (POD) of 61 and 59 %, respectively, when compared to rain gauge observations. The best performance using Correlation Coefficient (CC) was 70 and 60 % on daily timesteps for CMORPH and TRMM, respectively. The best RMSE for CMORPH was 0.81 % for 30 min timestep and for TRMM was 2, 11 % on 3 h timestep. For the year 2014 to 2015, the HEC-HMS (Hydrological Engineering Centre-Hydrological Modelling System) daily model calibration Nash Sutcliffe efficiency (NSE) for Musengezi sub catchment was 59 % whilst for Angwa it was 55 %. Angwa sub-catchment daily NSE results for the period 2015-2016 was 61 %. HEC-RAS flash flood modeling at 100, 50 and 25 year return periods for Angwa sub catchment, inundated 811 and 867 ha for TRMM rainfall simulated discharge at 3 h and daily timesteps, respectively. For CMORPH generated rainfall, the inundation was 818, 876, 890 and 891 ha at daily, 3 h, 1 h and 30 min timesteps. The 30 min time step for CMORPH effectively captures flash floods with the measure of agreement between simulated flood extent and ground control points of 69 %. For TRMM, the 3 h timestep effectively captures flash floods with coefficient of 67 %. The study therefore concludes that satellite products are most effective in capturing localized hydrological processes such as flash floods for sub-daily rainfall

Response of non-point source pollutant loads to climate change in the Shitoukoumen reservoir catchment.

PubMed

Zhang, Lei; Lu, Wenxi; An, Yonglei; Li, Di; Gong, Lei

2012-01-01

The impacts of climate change on streamflow and non-point source pollutant loads in the Shitoukoumen reservoir catchment are predicted by combining a general circulation model (HadCM3) with the Soil and Water Assessment Tool (SWAT) hydrological model. A statistical downscaling model was used to generate future local scenarios of meteorological variables such as temperature and precipitation. Then, the downscaled meteorological variables were used as input to the SWAT hydrological model calibrated and validated with observations, and the corresponding changes of future streamflow and non-point source pollutant loads in Shitoukoumen reservoir catchment were simulated and analyzed. Results show that daily temperature increases in three future periods (2010-2039, 2040-2069, and 2070-2099) relative to a baseline of 1961-1990, and the rate of increase is 0.63°C per decade. Annual precipitation also shows an apparent increase of 11 mm per decade. The calibration and validation results showed that the SWAT model was able to simulate well the streamflow and non-point source pollutant loads, with a coefficient of determination of 0.7 and a Nash-Sutcliffe efficiency of about 0.7 for both the calibration and validation periods. The future climate change has a significant impact on streamflow and non-point source pollutant loads. The annual streamflow shows a fluctuating upward trend from 2010 to 2099, with an increase rate of 1.1 m(3) s(-1) per decade, and a significant upward trend in summer, with an increase rate of 1.32 m(3) s(-1) per decade. The increase in summer contributes the most to the increase of annual load compared with other seasons. The annual NH (4) (+) -N load into Shitoukoumen reservoir shows a significant downward trend with a decrease rate of 40.6 t per decade. The annual TP load shows an insignificant increasing trend, and its change rate is 3.77 t per decade. The results of this analysis provide a scientific basis for effective support of decision

Predicting nitrate discharge dynamics in mesoscale catchments using the lumped StreamGEM model and Bayesian parameter inference

NASA Astrophysics Data System (ADS)

Woodward, Simon James Roy; Wöhling, Thomas; Rode, Michael; Stenger, Roland

2017-09-01

The common practice of infrequent (e.g., monthly) stream water quality sampling for state of the environment monitoring may, when combined with high resolution stream flow data, provide sufficient information to accurately characterise the dominant nutrient transfer pathways and predict annual catchment yields. In the proposed approach, we use the spatially lumped catchment model StreamGEM to predict daily stream flow and nitrate concentration (mg L-1 NO3-N) in four contrasting mesoscale headwater catchments based on four years of daily rainfall, potential evapotranspiration, and stream flow measurements, and monthly or daily nitrate concentrations. Posterior model parameter distributions were estimated using the Markov Chain Monte Carlo sampling code DREAMZS and a log-likelihood function assuming heteroscedastic, t-distributed residuals. Despite high uncertainty in some model parameters, the flow and nitrate calibration data was well reproduced across all catchments (Nash-Sutcliffe efficiency against Log transformed data, NSL, in the range 0.62-0.83 for daily flow and 0.17-0.88 for nitrate concentration). The slight increase in the size of the residuals for a separate validation period was considered acceptable (NSL in the range 0.60-0.89 for daily flow and 0.10-0.74 for nitrate concentration, excluding one data set with limited validation data). Proportions of flow and nitrate discharge attributed to near-surface, fast seasonal groundwater and slow deeper groundwater were consistent with expectations based on catchment geology. The results for the Weida Stream in Thuringia, Germany, using monthly as opposed to daily nitrate data were, for all intents and purposes, identical, suggesting that four years of monthly nitrate sampling provides sufficient information for calibration of the StreamGEM model and prediction of catchment dynamics. This study highlights the remarkable effectiveness of process based, spatially lumped modelling with commonly available monthly

Temperature-based modeling of reference evapotranspiration using several artificial intelligence models: application of different modeling scenarios

NASA Astrophysics Data System (ADS)

Sanikhani, Hadi; Kisi, Ozgur; Maroufpoor, Eisa; Yaseen, Zaher Mundher

2018-02-01

The establishment of an accurate computational model for predicting reference evapotranspiration (ET0) process is highly essential for several agricultural and hydrological applications, especially for the rural water resource systems, water use allocations, utilization and demand assessments, and the management of irrigation systems. In this research, six artificial intelligence (AI) models were investigated for modeling ET0 using a small number of climatic data generated from the minimum and maximum temperatures of the air and extraterrestrial radiation. The investigated models were multilayer perceptron (MLP), generalized regression neural networks (GRNN), radial basis neural networks (RBNN), integrated adaptive neuro-fuzzy inference systems with grid partitioning and subtractive clustering (ANFIS-GP and ANFIS-SC), and gene expression programming (GEP). The implemented monthly time scale data set was collected at the Antalya and Isparta stations which are located in the Mediterranean Region of Turkey. The Hargreaves-Samani (HS) equation and its calibrated version (CHS) were used to perform a verification analysis of the established AI models. The accuracy of validation was focused on multiple quantitative metrics, including root mean squared error (RMSE), mean absolute error (MAE), correlation coefficient (R 2), coefficient of residual mass (CRM), and Nash-Sutcliffe efficiency coefficient (NS). The results of the conducted models were highly practical and reliable for the investigated case studies. At the Antalya station, the performance of the GEP and GRNN models was better than the other investigated models, while the performance of the RBNN and ANFIS-SC models was best compared to the other models at the Isparta station. Except for the MLP model, all the other investigated models presented a better performance accuracy compared to the HS and CHS empirical models when applied in a cross-station scenario. A cross-station scenario examination implies the

Evaluating watershed protection programs in New York City's Cannonsville Reservoir source watershed using SWAT-HS

NASA Astrophysics Data System (ADS)

Hoang, L.; Mukundan, R.; Moore, K. E.; Owens, E. M.; Steenhuis, T. S.

2017-12-01

New York City (NYC)'s reservoirs supply over one billion gallons of drinking water each day to over nine million consumers in NYC and upstate communities. The City has invested more than $1.5 billion in watershed protection programs to maintain a waiver from filtration for the Catskill and Delaware Systems. In the last 25 years, the NYC Department of Environmental Protection (NYCDEP) has implemented programs in cooperation with upstate communities that include nutrient management, crop rotations, improvement of barnyards and manure storage, implementing tertiary treatment for Phosphorus (P) in wastewater treatment plants, and replacing failed septic systems in an effort to reduce P loads to water supply reservoirs. There have been several modeling studies evaluating the effect of agricultural Best Management Practices (BMPs) on P control in the Cannonsville watershed in the Delaware System. Although these studies showed that BMPs would reduce dissolved P losses, they were limited to farm-scale or watershed-scale estimates of reduction factors without consideration of the dynamic nature of overland flow and P losses from variable source areas. Recently, we developed the process-based SWAT-Hillslope (SWAT-HS) model, a modified version of the Soil and Water Assessment Tool (SWAT) that can realistically predict variable source runoff processes. The objective of this study is to use the SWAT-HS model to evaluate watershed protection programs addressing both point and non-point sources of P. SWAT-HS predicts streamflow very well for the Cannonsville watershed with a daily Nash Sutcliffe Efficiency (NSE) of 0.85 at the watershed outlet and NSE values ranging from 0.56 - 0.82 at five other locations within the watershed. Based on good hydrological prediction, we applied the model to predict P loads using detailed P inputs that change over time due to the implementation of watershed protection programs. Results from P model predictions provide improved projections of P

Improving operational flood ensemble prediction by the assimilation of satellite soil moisture: comparison between lumped and semi-distributed schemes

NASA Astrophysics Data System (ADS)

Alvarez-Garreton, C.; Ryu, D.; Western, A. W.; Su, C.-H.; Crow, W. T.; Robertson, D. E.; Leahy, C.

2014-09-01

Assimilation of remotely sensed soil moisture data (SM-DA) to correct soil water stores of rainfall-runoff models has shown skill in improving streamflow prediction. In the case of large and sparsely monitored catchments, SM-DA is a particularly attractive tool. Within this context, we assimilate active and passive satellite soil moisture (SSM) retrievals using an ensemble Kalman filter to improve operational flood prediction within a large semi-arid catchment in Australia (>40 000 km2). We assess the importance of accounting for channel routing and the spatial distribution of forcing data by applying SM-DA to a lumped and a semi-distributed scheme of the probability distributed model (PDM). Our scheme also accounts for model error representation and seasonal biases and errors in the satellite data. Before assimilation, the semi-distributed model provided more accurate streamflow prediction (Nash-Sutcliffe efficiency, NS = 0.77) than the lumped model (NS = 0.67) at the catchment outlet. However, this did not ensure good performance at the "ungauged" inner catchments. After SM-DA, the streamflow ensemble prediction at the outlet was improved in both the lumped and the semi-distributed schemes: the root mean square error of the ensemble was reduced by 27 and 31%, respectively; the NS of the ensemble mean increased by 7 and 38%, respectively; the false alarm ratio was reduced by 15 and 25%, respectively; and the ensemble prediction spread was reduced while its reliability was maintained. Our findings imply that even when rainfall is the main driver of flooding in semi-arid catchments, adequately processed SSM can be used to reduce errors in the model soil moisture, which in turn provides better streamflow ensemble prediction. We demonstrate that SM-DA efficacy is enhanced when the spatial distribution in forcing data and routing processes are accounted for. At ungauged locations, SM-DA is effective at improving streamflow ensemble prediction, however, the updated

Understanding seasonal variability of uncertainty in hydrological prediction

NASA Astrophysics Data System (ADS)

Li, M.; Wang, Q. J.

2012-04-01

Understanding uncertainty in hydrological prediction can be highly valuable for improving the reliability of streamflow prediction. In this study, a monthly water balance model, WAPABA, in a Bayesian joint probability with error models are presented to investigate the seasonal dependency of prediction error structure. A seasonal invariant error model, analogous to traditional time series analysis, uses constant parameters for model error and account for no seasonal variations. In contrast, a seasonal variant error model uses a different set of parameters for bias, variance and autocorrelation for each individual calendar month. Potential connection amongst model parameters from similar months is not considered within the seasonal variant model and could result in over-fitting and over-parameterization. A hierarchical error model further applies some distributional restrictions on model parameters within a Bayesian hierarchical framework. An iterative algorithm is implemented to expedite the maximum a posterior (MAP) estimation of a hierarchical error model. Three error models are applied to forecasting streamflow at a catchment in southeast Australia in a cross-validation analysis. This study also presents a number of statistical measures and graphical tools to compare the predictive skills of different error models. From probability integral transform histograms and other diagnostic graphs, the hierarchical error model conforms better to reliability when compared to the seasonal invariant error model. The hierarchical error model also generally provides the most accurate mean prediction in terms of the Nash-Sutcliffe model efficiency coefficient and the best probabilistic prediction in terms of the continuous ranked probability score (CRPS). The model parameters of the seasonal variant error model are very sensitive to each cross validation, while the hierarchical error model produces much more robust and reliable model parameters. Furthermore, the result of the

Spatial and Temporal Dynamics of the Leaf Area Index of the Caatinga Biome

NASA Astrophysics Data System (ADS)

Alves Rodrigues Pinheiro, Everton; de Jong van Lier, Quirijn; Metselaar, Klaas

2015-04-01

Leaf Area Index (LAI) is an important characteristic of ecosystems with a prominent role in processes such as transpiration, photosynthesis and interception. The Caatinga biome is a unique semiarid ecosystem ocurring in a specific region of Brazil. An important main feature of this biome is the leaf shedding and regenerative capacity of its species. The aim of this study was to quantify both spatial and temporal dynamics of the LAI of the Caatinga biome in the Aiuaba Experimental Basin, an integrally-preserved Caatinga reserve, coordinates 6°42'S; 40°17'W. The research site (12 km2) was divided into three main Soil and Vegatation Associations (SVA). For each SVA the soil type and root depth are respectively, Acrisol -0.8 m, Luvisol - 0.6 m and Regosol - 0.4 m. The LAI was estimated by SEBAL algorithm applied to eleven satellite images from Landsat 5. The values of LAI estimated by SEBAL were correlated to the mean soil water content of the 15 days previous to the satellite image date. Eight images were used to generate a simple regression model, yielding a range of coefficient of determination from 0.89 to 0.92. Three other images were used to validate the equations. The Nash-Sutcliffe efficiency coefficient ranged from 0.76 to 0.94. Using the validated correlations, the LAI was calculated over the time for each of the three SVA, from 2004 to 2012. For SVA1, SVA2 and SVA3, the avarage values of LAI during the rainy season were 0.97, 1.12 and 1.07, respectively. During the dry season, the mean values were 0.15 for SVA1 and 0.11 for SVA2 and SVA3. The vegetation showed abrupt LAI changes, and the average previous 15 days soil water content was a good indicator for this. The study has shown that the maximum LAI was relatively stable over the years, occurring between March and April. The spatial behavior of LAI appeared to be similar, independently of the soil type and root depth.

Spatial extrapolation of lysimeter results using thermal infrared imaging

NASA Astrophysics Data System (ADS)

Voortman, B. R.; Bosveld, F. C.; Bartholomeus, R. P.; Witte, J. P. M.

2016-12-01

Measuring evaporation (E) with lysimeters is costly and prone to numerous errors. By comparing the energy balance and the remotely sensed surface temperature of lysimeters with those of the undisturbed surroundings, we were able to assess the representativeness of lysimeter measurements and to quantify differences in evaporation caused by spatial variations in soil moisture content. We used an algorithm (the so called 3T model) to spatially extrapolate the measured E of a reference lysimeter based on differences in surface temperature, net radiation and soil heat flux. We tested the performance of the 3T model on measurements with multiple lysimeters (47.5 cm inner diameter) and micro lysimeters (19.2 cm inner diameter) installed in bare sand, moss and natural dry grass. We developed different scaling procedures using in situ measurements and remotely sensed surface temperatures to derive spatially distributed estimates of Rn and G and explored the physical soundness of the 3T model. Scaling of Rn and G considerably improved the performance of the 3T model for the bare sand and moss experiments (Nash-Sutcliffe efficiency (NSE) increasing from 0.45 to 0.89 and from 0.81 to 0.94, respectively). For the grass surface, the scaling procedures resulted in a poorer performance of the 3T model (NSE decreasing from 0.74 to 0.70), which was attributed to effects of shading and the difficulty to correct for differences in emissivity between dead and living biomass. The 3T model is physically unsound if the field scale average air temperature, measured at an arbitrarily chosen reference height, is used as input to the model. The proposed measurement system is relatively cheap, since it uses a zero tension (freely draining) lysimeter which results are extrapolated by the 3T model to the unaffected surroundings. The system is promising for bridging the gap between ground observations and satellite based estimates of E.

Modeling spray drift and runoff-related inputs of pesticides to receiving water.

PubMed

Zhang, Xuyang; Luo, Yuzhou; Goh, Kean S

2018-03-01

Pesticides move to surface water via various pathways including surface runoff, spray drift and subsurface flow. Little is known about the relative contributions of surface runoff and spray drift in agricultural watersheds. This study develops a modeling framework to address the contribution of spray drift to the total loadings of pesticides in receiving water bodies. The modeling framework consists of a GIS module for identifying drift potential, the AgDRIFT model for simulating spray drift, and the Soil and Water Assessment Tool (SWAT) for simulating various hydrological and landscape processes including surface runoff and transport of pesticides. The modeling framework was applied on the Orestimba Creek Watershed, California. Monitoring data collected from daily samples were used for model evaluation. Pesticide mass deposition on the Orestimba Creek ranged from 0.08 to 6.09% of applied mass. Monitoring data suggests that surface runoff was the major pathway for pesticide entering water bodies, accounting for 76% of the annual loading; the rest 24% from spray drift. The results from the modeling framework showed 81 and 19%, respectively, for runoff and spray drift. Spray drift contributed over half of the mass loading during summer months. The slightly lower spray drift contribution as predicted by the modeling framework was mainly due to SWAT's under-prediction of pesticide mass loading during summer and over-prediction of the loading during winter. Although model simulations were associated with various sources of uncertainties, the overall performance of the modeling framework was satisfactory as evaluated by multiple statistics: for simulation of daily flow, the Nash-Sutcliffe Efficiency Coefficient (NSE) ranged from 0.61 to 0.74 and the percent bias (PBIAS) < 28%; for daily pesticide loading, NSE = 0.18 and PBIAS = -1.6%. This modeling framework will be useful for assessing the relative exposure from pesticides related to spray drift and runoff in

Patterns and predictability in the intra-annual organic carbon variability across the boreal and hemiboreal landscape

USGS Publications Warehouse

Hytteborn, Julia K.; Temnerud, Johan; Alexander, Richard B.; Boyer, Elizabeth W.; Futter, Martyn N.; Fröberg, Mats; Dahné, Joel; Bishop, Kevin H.

2015-01-01

Factors affecting total organic carbon (TOC) concentrations in 215 watercourses across Sweden were investigated using parameter parsimonious regression approaches to explain spatial and temporal variabilities of the TOC water quality responses. We systematically quantified the effects of discharge, seasonality, and long-term trend as factors controlling intra-annual (among year) and inter-annual (within year) variabilities of TOC by evaluating the spatial variability in model coefficients and catchment characteristics (e.g. land cover, retention time, soil type).Catchment area (0.18–47,000 km2) and land cover types (forests, agriculture and alpine terrain) are typical for the boreal and hemiboreal zones across Fennoscandia. Watercourses had at least 6 years of monthly water quality observations between 1990 and 2010. Statistically significant models (p < 0.05) describing variation of TOC in streamflow were identified in 209 of 215 watercourses with a mean Nash-Sutcliffe efficiency index of 0.44. Increasing long-term trends were observed in 149 (70%) of the watercourses, and intra-annual variation in TOC far exceeded inter-annual variation. The average influences of the discharge and seasonality terms on intra-annual variations in daily TOC concentration were 1.4 and 1.3 mg l− 1 (13 and 12% of the mean annual TOC), respectively. The average increase in TOC was 0.17 mg l− 1 year− 1 (1.6% year− 1).Multivariate regression with over 90 different catchment characteristics explained 21% of the spatial variation in the linear trend coefficient, less than 20% of the variation in the discharge coefficient and 73% of the spatial variation in mean TOC. Specific discharge, water residence time, the variance of daily precipitation, and lake area, explained 45% of the spatial variation in the amplitude of the TOC seasonality.Because the main drivers of temporal variability in TOC are seasonality and discharge, first-order estimates of the influences of

Impacts of climate change on current methodologies for flood risk analysis: Watershed-scale analyses using the Soil and Water Assessment Tool (SWAT)

NASA Astrophysics Data System (ADS)

Spellman, P.; Griffis, V. W.; LaFond, K.

2013-12-01

A changing climate brings about new challenges for flood risk analysis and water resources planning and management. Current methods for estimating flood risk in the US involve fitting the Pearson Type III (P3) probability distribution to the logarithms of the annual maximum flood (AMF) series using the method of moments. These methods are employed under the premise of stationarity, which assumes that the fitted distribution is time invariant and variables affecting stream flow such as climate do not fluctuate. However, climate change would bring about shifts in meteorological forcings which can alter the summary statistics (mean, variance, skew) of flood series used for P3 parameter estimation, resulting in erroneous flood risk projections. To ascertain the degree to which future risk may be misrepresented by current techniques, we use climate scenarios generated from global climate models (GCMs) as input to a hydrological model to explore how relative changes to current climate affect flood response for watersheds in the northeastern United States. The watersheds were calibrated and run on a daily time step using the continuous, semi-distributed, process based Soil and Water Assessment Tool (SWAT). Nash Sutcliffe Efficiency (NSE), RMSE to Standard Deviation ratio (RSR) and Percent Bias (PBIAS) were all used to assess model performance. Eight climate scenarios were chosen from GCM output based on relative precipitation and temperature changes from the current climate of the watershed and then further bias-corrected. Four of the scenarios were selected to represent warm-wet, warm-dry, cool-wet and cool-dry future climates, and the other four were chosen to represent more extreme, albeit possible, changes in precipitation and temperature. We quantify changes in response by comparing the differences in total mass balance and summary statistics of the logarithms of the AMF series from historical baseline values. We then compare forecasts of flood quantiles from fitting

The Evolution of Remotely Sensed Precipitation Products for Hydrological Applications with a Focus on the Tropical Rainfall Measurement Mission (TRMM)

NASA Astrophysics Data System (ADS)

Tobin, K. J.; Bennett, M.

2012-12-01

This study examines the evolution of how remotely sensed precipitation products have impacted hydrologic modeling from six basins across the continental United States. Precipitation products include both ground-based (Multisensor Precipitation Estimator - MPE) and space-based products. Two space-based products are from the Tropical Rainfall Measurement Mission (TRMM) and include the real-time TRMM Multi-Satellite Precipitation Analysis (TMPA-RT) and TRMM 3B42 Research product. Precipitation products are compared between early (2004-2008) and late (2008-2010) periods. Additionally, version 6 and the new version 7 of these TRMM products are examined. Watersheds examined were moderately large (1000 to 1,000 square kilometers) and included the San Pedro (Arizona), Cimarron (Oklahoma); Alapaha (Georgia), mid-Nueces (Texas), San Casimiro (Texas), and the mid-Rio Grande basins, which is a bi-national basin that spans the Texas-Mexico border. Precipitation products are used to drive streamflow simulations using the Soil Water Assessment Tool (SWAT). The main results of this study concludes that MPE is a mature remote sensing product that generally supports superior hydrologic simulations based on standard performance metrics such as mass balance error, Nash-Sutcliffe efficiency coefficient, and coefficient of persistence. TRMM products support acceptable simulations and have improved in performance between early and late periods for TMPA-RT (both versions) and version 6 of TRMM 3B42 Research in five out of the six basins examined. This improvement is related to modification of TRMM in January 2009 with the addition of more satellite data and a climatologic bias correction, which greatly improves the real-time TMPA-RT product. Conversely, version 7 of the TRMM 3B42 Research has a positive bias compared to version 6, which is translated into poorer hydrological simulations of streamflow. Future research is urgently needed to determine if the issues observed in this study are

Effects of spatial orientation of prairie vegetation in an agricultural landscape on curve number values

NASA Astrophysics Data System (ADS)

Franz, K.; Dziubanski, D.; Helmers, M. J.

2015-12-01

The simplicity of the Curve Number (CN) method, which summarizes an area's hydrologic soil group, land cover, treatment, and hydrologic condition into a single number, make it a consistently popular choice for modelers. When multiple land cover types are present, a weighted average of the CNs is used. However, the weighted CN does not account for the spatial distribution of different land cover types within the watershed. To overcome this limitation, it becomes necessary to discretize the model into homogenous subunits, perhaps even to the hillslope scale, leading to a more complex model application. The objective of this study is to empirically derive CN values that reflect the effects of placements of native prairie vegetation (NPV) within agricultural landscapes. We derived CN values using precipitation and runoff data from (May 1 - Sept 30 over a 7 year period (2008 - 2014) for 9 ephemeral watersheds in Iowa (USA) ranging from 0.47 to 3.19 ha. The watersheds were planted with varying extents of NPV (0%, 10%, 20%) in different watershed positions (footslope vs. contour strips), with the rest of the watershed as row crop. The derived CN values from watersheds with all row crop were consistent with published values and watersheds with NPV had an average CN reduction of 6.4%, with a maximum reduction of 11.6%. Four of the six sites with treatment had a lower CN than one calculated using a weighted average of look-up values, indicating that accounting for placement of vegetation within the landscape is important for modeling runoff with the CN method. The derived CNs were verified using the leave-one-year-out method (computing CN using data from 6 of the 7 years, and then estimating runoff on the seventh year with that CN). Nash-Sutcliffe Efficiency (NSE) values for the estimated runoff typically ranged from 0.4-0.6. Our results suggest that the new CNs could confidently be used in future modeling studies to explore the hydrologic impacts of the NPV treatments at

CMIP5 ensemble-based spatial rainfall projection over homogeneous zones of India

NASA Astrophysics Data System (ADS)

Akhter, Javed; Das, Lalu; Deb, Argha

2017-09-01

Performances of the state-of-the-art CMIP5 models in reproducing the spatial rainfall patterns over seven homogeneous rainfall zones of India viz. North Mountainous India (NMI), Northwest India (NWI), North Central India (NCI), Northeast India (NEI), West Peninsular India (WPI), East Peninsular India (EPI) and South Peninsular India (SPI) have been assessed using different conventional performance metrics namely spatial correlation (R), index of agreement (d-index), Nash-Sutcliffe efficiency (NSE), Ratio of RMSE to the standard deviation of the observations (RSR) and mean bias (MB). The results based on these indices revealed that majority of the models are unable to reproduce finer-scaled spatial patterns over most of the zones. Thereafter, four bias correction methods i.e. Scaling, Standardized Reconstruction, Empirical Quantile Mapping and Gamma Quantile Mapping have been applied on GCM simulations to enhance the skills of the GCM projections. It has been found that scaling method compared to other three methods shown its better skill in capturing mean spatial patterns. Multi-model ensemble (MME) comprising 25 numbers of better performing bias corrected (Scaled) GCMs, have been considered for developing future rainfall patterns over seven zones. Models' spread from ensemble mean (uncertainty) has been found to be larger in RCP 8.5 than RCP4.5 ensemble. In general, future rainfall projections from RCP 4.5 and RCP 8.5 revealed an increasing rainfall over seven zones during 2020s, 2050s, and 2080s. The maximum increase has been found over southwestern part of NWI (12-30%), northwestern part of WPI (3-30%), southeastern part of NEI (5-18%) and northern and eastern part of SPI (6-24%). However, the contiguous region comprising by the southeastern part of NCI and northeastern part of EPI, may experience slight decreasing rainfall (about 3%) during 2020s whereas the western part of NMI may also receive around 3% reduction in rainfall during both 2050s and 2080s.

Testing the skill of numerical hydraulic modeling to simulate spatiotemporal flooding patterns in the Logone floodplain, Cameroon

NASA Astrophysics Data System (ADS)

Fernández, Alfonso; Najafi, Mohammad Reza; Durand, Michael; Mark, Bryan G.; Moritz, Mark; Jung, Hahn Chul; Neal, Jeffrey; Shastry, Apoorva; Laborde, Sarah; Phang, Sui Chian; Hamilton, Ian M.; Xiao, Ningchuan

2016-08-01

Recent innovations in hydraulic modeling have enabled global simulation of rivers, including simulation of their coupled wetlands and floodplains. Accurate simulations of floodplains using these approaches may imply tremendous advances in global hydrologic studies and in biogeochemical cycling. One such innovation is to explicitly treat sub-grid channels within two-dimensional models, given only remotely sensed data in areas with limited data availability. However, predicting inundated area in floodplains using a sub-grid model has not been rigorously validated. In this study, we applied the LISFLOOD-FP hydraulic model using a sub-grid channel parameterization to simulate inundation dynamics on the Logone River floodplain, in northern Cameroon, from 2001 to 2007. Our goal was to determine whether floodplain dynamics could be simulated with sufficient accuracy to understand human and natural contributions to current and future inundation patterns. Model inputs in this data-sparse region include in situ river discharge, satellite-derived rainfall, and the shuttle radar topography mission (SRTM) floodplain elevation. We found that the model accurately simulated total floodplain inundation, with a Pearson correlation coefficient greater than 0.9, and RMSE less than 700 km2, compared to peak inundation greater than 6000 km2. Predicted discharge downstream of the floodplain matched measurements (Nash-Sutcliffe efficiency of 0.81), and indicated that net flow from the channel to the floodplain was modeled accurately. However, the spatial pattern of inundation was not well simulated, apparently due to uncertainties in SRTM elevations. We evaluated model results at 250, 500 and 1000-m spatial resolutions, and found that results are insensitive to spatial resolution. We also compared the model output against results from a run of LISFLOOD-FP in which the sub-grid channel parameterization was disabled, finding that the sub-grid parameterization simulated more realistic

Improved regional-scale groundwater representation by the coupling of the mesoscale Hydrologic Model (mHM v5.7) to the groundwater model OpenGeoSys (OGS)

NASA Astrophysics Data System (ADS)

Jing, Miao; Heße, Falk; Kumar, Rohini; Wang, Wenqing; Fischer, Thomas; Walther, Marc; Zink, Matthias; Zech, Alraune; Samaniego, Luis; Kolditz, Olaf; Attinger, Sabine

2018-06-01

Most large-scale hydrologic models fall short in reproducing groundwater head dynamics and simulating transport process due to their oversimplified representation of groundwater flow. In this study, we aim to extend the applicability of the mesoscale Hydrologic Model (mHM v5.7) to subsurface hydrology by coupling it with the porous media simulator OpenGeoSys (OGS). The two models are one-way coupled through model interfaces GIS2FEM and RIV2FEM, by which the grid-based fluxes of groundwater recharge and the river-groundwater exchange generated by mHM are converted to fixed-flux boundary conditions of the groundwater model OGS. Specifically, the grid-based vertical reservoirs in mHM are completely preserved for the estimation of land-surface fluxes, while OGS acts as a plug-in to the original mHM modeling framework for groundwater flow and transport modeling. The applicability of the coupled model (mHM-OGS v1.0) is evaluated by a case study in the central European mesoscale river basin - Nägelstedt. Different time steps, i.e., daily in mHM and monthly in OGS, are used to account for fast surface flow and slow groundwater flow. Model calibration is conducted following a two-step procedure using discharge for mHM and long-term mean of groundwater head measurements for OGS. Based on the model summary statistics, namely the Nash-Sutcliffe model efficiency (NSE), the mean absolute error (MAE), and the interquartile range error (QRE), the coupled model is able to satisfactorily represent the dynamics of discharge and groundwater heads at several locations across the study basin. Our exemplary calculations show that the one-way coupled model can take advantage of the spatially explicit modeling capabilities of surface and groundwater hydrologic models and provide an adequate representation of the spatiotemporal behaviors of groundwater storage and heads, thus making it a valuable tool for addressing water resources and management problems.

Assessing the Impact of Climate Change on Extreme Streamflow and Reservoir Operation for Nuuanu Watershed, Oahu, Hawaii

NASA Astrophysics Data System (ADS)

Leta, O. T.; El-Kadi, A. I.; Dulaiova, H.

2016-12-01

Extreme events, such as flooding and drought, are expected to occur at increased frequencies worldwide due to climate change influencing the water cycle. This is particularly critical for tropical islands where the local freshwater resources are very sensitive to climate. This study examined the impact of climate change on extreme streamflow, reservoir water volume and outflow for the Nuuanu watershed, using the Soil and Water Assessment Tool (SWAT) model. Based on the sensitive parameters screened by the Latin Hypercube-One-factor-At-a-Time (LH-OAT) method, SWAT was calibrated and validated to daily streamflow using the SWAT Calibration and Uncertainty Program (SWAT-CUP) at three streamflow gauging stations. Results showed that SWAT adequately reproduced the observed daily streamflow hydrographs at all stations. This was verified with Nash-Sutcliffe Efficiency that resulted in acceptable values of 0.58 to 0.88, whereby more than 90% of observations were bracketed within 95% model prediction uncertainty interval for both calibration and validation periods, signifying the potential applicability of SWAT for future prediction. The climate change impact on extreme flows, reservoir water volume and outflow was assessed under the Representative Concentration Pathways of 4.5 and 8.5 scenarios. We found wide changes in extreme peak and low flows ranging from -44% to 20% and -50% to -2%, respectively, compared to baseline. Consequently, the amount of water stored in Nuuanu reservoir will be decreased up to 27% while the corresponding outflow rates are expected to decrease up to 37% relative to the baseline. In addition, the stored water and extreme flows are highly sensitive to rainfall change when compared to temperature and solar radiation changes. It is concluded that the decrease in extreme low and peak flows can have serious consequences, such as flooding, drought, with detrimental effects on riparian ecological functioning. This study's results are expected to aid in

Application of Temperature Index Model to Assess the Future Hydrological Regime of the Glacierized Catchments in Nepal.

NASA Astrophysics Data System (ADS)

Kayastha, R.; Kayastha, R. B.

2017-12-01

Unavailability of hydro meteorological data in the Himalayan regions is challenging on understanding the flow regimes. Temperature index model is simple yet the powerful glacio-hydrological model to simulate the discharge in the glacierized basin. Modified Positive Degree Day (MPDD) Model Version 2.0 is a grid-ded based semi distributed model with baseflow module is a robust melt modelling tools to estimate the discharge. MPDD model uses temperature and precipitation as a forcing datasets to simulate the discharge and also to obtain the snowmelt, icemelt, rain and baseflow contribution on total discharge. In this study two glacierized, Marsyangdi and Langtang catchment were investigated for the future hydrological regimes. Marsyangdi encompasses an area of 4026.19 sq. km with 20% glaciated area, whereas Langtang catchment with area of 354.64 sq. km with 36% glaciated area is studied to examine for the future climatic scenarios. The model simulates discharge well for the observed period; (1992-1998) in Marsyangdi and from (2007-2013) in Langtang catchment. The Nash-Sutcliffe Efficiency (NSE) for the both catchment were above 0.75 with the volume difference less than - 8 %. The snow and ice melts contribution in Marsyangdi were 4.7% and 10.2% whereas in Langtang the contribution is 15.3% and 23.4%, respectively. Rain contribution ( 40%) is higher than the baseflow contribution in total discharge in both basins. The future river discharge is also predicted using the future climate data from the regional climate models (RCMs) of CORDEX South Asia experiments for the medium stabilization scenario RCP4.5 and very high radiative forcing scenario RCP8.5 after bias correction. The projected future discharge of both catchment shows slightly increase in both scenarios with increase of snow and ice melt contribution on discharge. The result generated from the model can be utilized to understand the future hydrological regimes of the glacierized catchment also the impact of

Accuracy of topographic index models at identifying ephemeral gully trajectories on agricultural fields

NASA Astrophysics Data System (ADS)

Sheshukov, Aleksey Y.; Sekaluvu, Lawrence; Hutchinson, Stacy L.

2018-04-01

Topographic index (TI) models have been widely used to predict trajectories and initiation points of ephemeral gullies (EGs) in agricultural landscapes. Prediction of EGs strongly relies on the selected value of critical TI threshold, and the accuracy depends on topographic features, agricultural management, and datasets of observed EGs. This study statistically evaluated the predictions by TI models in two paired watersheds in Central Kansas that had different levels of structural disturbances due to implemented conservation practices. Four TI models with sole dependency on topographic factors of slope, contributing area, and planform curvature were used in this study. The observed EGs were obtained by field reconnaissance and through the process of hydrological reconditioning of digital elevation models (DEMs). The Kernel Density Estimation analysis was used to evaluate TI distribution within a 10-m buffer of the observed EG trajectories. The EG occurrence within catchments was analyzed using kappa statistics of the error matrix approach, while the lengths of predicted EGs were compared with the observed dataset using the Nash-Sutcliffe Efficiency (NSE) statistics. The TI frequency analysis produced bi-modal distribution of topographic indexes with the pixels within the EG trajectory having a higher peak. The graphs of kappa and NSE versus critical TI threshold showed similar profile for all four TI models and both watersheds with the maximum value representing the best comparison with the observed data. The Compound Topographic Index (CTI) model presented the overall best accuracy with NSE of 0.55 and kappa of 0.32. The statistics for the disturbed watershed showed higher best critical TI threshold values than for the undisturbed watershed. Structural conservation practices implemented in the disturbed watershed reduced ephemeral channels in headwater catchments, thus producing less variability in catchments with EGs. The variation in critical thresholds for all

Surface-water and karst groundwater interactions and streamflow-response simulations of the karst-influenced upper Lost River watershed, Orange County, Indiana

USGS Publications Warehouse

Bayless, E. Randall; Cinotto, Peter J.; Ulery, Randy L.; Taylor, Charles J.; McCombs, Gregory K.; Kim, Moon H.; Nelson, Hugh L.

2014-01-01

The U.S. Geological Survey (USGS), in cooperation with the U.S. Army Corps of Engineers (USACE) and the Indiana Office of Community and Rural Affairs (OCRA), conducted a study of the upper Lost River watershed in Orange County, Indiana, from 2012 to 2013. Streamflow and groundwater data were collected at 10 data-collection sites from at least October 2012 until April 2013, and a preliminary Water Availability Tool for Environmental Resources (WATER)-TOPMODEL based hydrologic model was created to increase understanding of the complex, karstic hydraulic and hydrologic system present in the upper Lost River watershed, Orange County, Ind. Statistical assessment of the optimized hydrologic-model results were promising and returned correlation coefficients for simulated and measured stream discharge of 0.58 and 0.60 and Nash-Sutcliffe efficiency values of 0.56 and 0.39 for USGS streamflow-gaging stations 03373530 (Lost River near Leipsic, Ind.), and 03373560 (Lost River near Prospect, Ind.), respectively. Additional information to refine drainage divides is needed before applying the model to the entire karst region of south-central Indiana. Surface-water and groundwater data were used to tentatively quantify the complex hydrologic processes taking place within the watershed and provide increased understanding for future modeling and management applications. The data indicate that during wet-weather periods and after certain intense storms, the hydraulic capacity of swallow holes and subsurface conduits is overwhelmed with excess water that flows onto the surface in dry-bed relic stream channels and karst paleovalleys. Analysis of discharge data collected at USGS streamflow-gaging station 03373550 (Orangeville Rise, at Orangeville, Ind.), and other ancillary data-collection sites in the watershed, indicate that a bounding condition is likely present, and drainage from the underlying karst conduit system is potentially limited to near 200 cubic feet per second. This

Monthly paleostreamflow reconstruction from annual tree-ring chronologies

NASA Astrophysics Data System (ADS)

Stagge, J. H.; Rosenberg, D. E.; DeRose, R. J.; Rittenour, T. M.

2018-02-01

Paleoclimate reconstructions are increasingly used to characterize annual climate variability prior to the instrumental record, to improve estimates of climate extremes, and to provide a baseline for climate-change projections. To date, paleoclimate records have seen limited engineering use to estimate hydrologic risks because water systems models and managers usually require streamflow input at the monthly scale. This study explores the hypothesis that monthly streamflows can be adequately modeled by statistically decomposing annual flow reconstructions. To test this hypothesis, a multiple linear regression model for monthly streamflow reconstruction is presented that expands the set of predictors to include annual streamflow reconstructions, reconstructions of global circulation, and potential differences among regional tree-ring chronologies related to tree species and geographic location. This approach is used to reconstruct 600 years of monthly streamflows at two sites on the Bear and Logan rivers in northern Utah. Nash-Sutcliffe Efficiencies remain above zero (0.26-0.60) for all months except April and Pearson's correlation coefficients (R) are 0.94 and 0.88 for the Bear and Logan rivers, respectively, confirming that the model can adequately reproduce monthly flows during the reference period (10/1942 to 9/2015). Incorporating a flexible transition between the previous and concurrent annual reconstructed flows was the most important factor for model skill. Expanding the model to include global climate indices and regional tree-ring chronologies produced smaller, but still significant improvements in model fit. The model presented here is the only approach currently available to reconstruct monthly streamflows directly from tree-ring chronologies and climate reconstructions, rather than using resampling of the observed record. With reasonable estimates of monthly flow that extend back in time many centuries, water managers can challenge systems models with a

Land use change impacts on water quality in three lake winnipeg watersheds.

PubMed

Yang, Qi; Leon, Luis F; Booty, William G; Wong, Isaac W; McCrimmon, Craig; Fong, Phil; Michiels, Patsy; Vanrobaeys, Jason; Benoy, Glenn

2014-09-01

Lake Winnipeg eutrophication results from excess nutrient loading due to agricultural activities across the watershed. Estimating nonpoint-source pollution and the mitigation effects of beneficial management practices (BMPs) is an important step in protecting the water quality of streams and receiving waters. The use of computer models to systematically compare different landscapes and agricultural systems across the Red-Assiniboine basin has not been attempted at watersheds of this size in Manitoba. In this study, the Soil and Water Assessment Tool was applied and calibrated for three pilot watersheds of the Lake Winnipeg basin. Monthly flow calibration yielded overall satisfactory Nash-Sutcliffe efficiency (NSE), with values above 0.7 for all simulations. Total phosphorus (TP) calibration NSE ranged from 0.64 to 0.76, total N (TN) ranged from 0.22 to 0.75, and total suspended solids (TSS) ranged from 0.29 to 0.68. Based on the assessment of the TP exceedance levels from 1993 to 2007, annual loads were above proposed objectives for the three watersheds more than half of the time. Four BMP scenarios based on land use changes were studied in the watersheds: annual cropland to hay land (ACHL), wetland restoration (WR), marginal annual cropland conversion to hay land (MACHL), and wetland restoration on marginal cropland (WRMAC). Of these land use change scenarios, ACHL had the greatest impact: TSS loads were reduced by 33 to 65%, TN by 58 to 82%, and TP by 38 to 72% over the simulation period. By analyzing unit area and percentage of load reduction, the results indicate that the WR and WRMAC scenarios had a significant impact on water quality in high loading zones in the three watersheds. Such reductions of sediment, N, and P are possible through land use change scenarios, suggesting that land conservation should be a key component of any Lake Winnipeg restoration strategy. Copyright © by the American Society of Agronomy, Crop Science Society of America, and Soil

Looking beyond general metrics for model evaluation - lessons from an international model intercomparison study

NASA Astrophysics Data System (ADS)

Bouaziz, Laurène; de Boer-Euser, Tanja; Brauer, Claudia; Drogue, Gilles; Fenicia, Fabrizio; Grelier, Benjamin; de Niel, Jan; Nossent, Jiri; Pereira, Fernando; Savenije, Hubert; Thirel, Guillaume; Willems, Patrick

2016-04-01

International collaboration between institutes and universities is a promising way to reach consensus on hydrological model development. Education, experience and expert knowledge of the hydrological community have resulted in the development of a great variety of model concepts, calibration methods and analysis techniques. Although comparison studies are very valuable for international cooperation, they do often not lead to very clear new insights regarding the relevance of the modelled processes. We hypothesise that this is partly caused by model complexity and the used comparison methods, which focus on a good overall performance instead of focusing on specific events. We propose an approach that focuses on the evaluation of specific events. Eight international research groups calibrated their model for the Ourthe catchment in Belgium (1607 km2) and carried out a validation in time for the Ourthe (i.e. on two different periods, one of them on a blind mode for the modellers) and a validation in space for nested and neighbouring catchments of the Meuse in a completely blind mode. For each model, the same protocol was followed and an ensemble of best performing parameter sets was selected. Signatures were first used to assess model performances in the different catchments during validation. Comparison of the models was then followed by evaluation of selected events, which include: low flows, high flows and the transition from low to high flows. While the models show rather similar performances based on general metrics (i.e. Nash-Sutcliffe Efficiency), clear differences can be observed for specific events. While most models are able to simulate high flows well, large differences are observed during low flows and in the ability to capture the first peaks after drier months. The transferability of model parameters to neighbouring and nested catchments is assessed as an additional measure in the model evaluation. This suggested approach helps to select, among competing

Sierra Nevada snowpack and runoff prediction integrating basin-wide wireless-sensor network data

NASA Astrophysics Data System (ADS)

Yoon, Y.; Conklin, M. H.; Bales, R. C.; Zhang, Z.; Zheng, Z.; Glaser, S. D.

2016-12-01

We focus on characterizing snowpack and estimating runoff from snowmelt in high elevation area (>2100 m) in Sierra Nevada for daily (for use in, e.g. flood and hydropower forecasting), seasonal (supply prediction), and decadal (long-term planning) time scale. Here, basin-wide wireless-sensor network data (ARHO, http://glaser.berkeley.edu/wsn/) is integrated into the USGS Precipitation-Runoff Modeling System (PRMS), and a case study of the American River basin is presented. In the American River basin, over 140 wireless sensors have been planted in 14 sites considering elevation gradient, slope, aspect, and vegetation density, which provides spatially distributed snow depth, temperature, solar radiation, and soil moisture from 2013. 800 m daily gridded dataset (PRISM) is used as the climate input for the PRMS. Model parameters are obtained from various sources (e.g., NLCD 2011, SSURGO, and NED) with a regionalization method and GIS analysis. We use a stepwise framework for a model calibration to improve model performance and localities of estimates. For this, entire basin is divided into 12 subbasins that include full natural flow measurements. The study period is between 1982 and 2014, which contains three major storm events and recent severe drought. Simulated snow depth and snow water equivalent (SWE) are initially compared with the water year 2014 ARHO observations. The overall results show reasonable agreements having the Nash-Sutcliffe efficiency coefficient (NS) of 0.7, ranged from 0.3 to 0.86. However, the results indicate a tendency to underestimate the SWE in a high elevation area compared with ARHO observations, which is caused by the underestimated PRISM precipitation data. Precipitation at gauge-sparse regions (e.g., high elevation area), in general, cannot be well represented in gridded datasets. Streamflow estimates of the basin outlet have NS of 0.93, percent bias of 7.8%, and normalized root mean square error of 3.6% for the monthly time scale.

Design of Environmental Flows Below Diversion Hydropower Dams: Is There Benefit to Advanced Streamflow Prediction in Sparse Data Landscapes?

NASA Astrophysics Data System (ADS)

Kibler, K. M.; Alipour, M.

2017-12-01

Diversion hydropower has been shown to significantly alter river flow regimes by dewatering diversion bypass reaches. Data scarcity is one of the foremost challenges to establishing environmental flow regimes below diversion hydropower dams, especially in regions of sparse hydro-meteorological observation. Herein, we test two prediction strategies for generating daily flows in rivers developed with diversion hydropower: a catchment similarity model, and a rainfall-runoff model selected by multi-objective optimization based on soft data. While both methods are designed for ungauged rivers embedded within large regions of sparse hydrologic observation, one is more complex and computationally-intensive. The objective of this study is to assess the benefit of using complex modeling tools in data-sparse landscapes to support design of environmental flow regimes. Models were tested in gauged catchments and then used to simulate a 28-year record of daily flows in 32 ungauged rivers. After perturbing flows with the hydropower diversion, we detect alteration using Indicators of Hydrologic Alteration (IHA) metrics and compare outcomes of the two modeling approaches. The catchment similarity model simulates low flows well (Nash-Sutcliff efficiency (NSE) = 0.91), but poorly represents moderate to high flows (overall NSE = 0.25). The multi-objective rainfall-runoff model performs well overall (NSE = 0.72). Both models agree that flow magnitudes and variability consistently decrease following diversion as temporally-dynamic flows are replaced by static minimal flows. Mean duration of events sustained below the pre-diversion Q75 and mean hydrograph rise and fall rates increase. While we see broad areas of agreement, significant effects and thresholds vary between models, particularly in the representation of moderate flows. Thus, use of simplified streamflow models may bias detected alterations or inadequately characterize pre-regulation flow regimes, providing inaccurate

Stream-flow forecasting using extreme learning machines: A case study in a semi-arid region in Iraq

NASA Astrophysics Data System (ADS)

Yaseen, Zaher Mundher; Jaafar, Othman; Deo, Ravinesh C.; Kisi, Ozgur; Adamowski, Jan; Quilty, John; El-Shafie, Ahmed

2016-11-01

Monthly stream-flow forecasting can yield important information for hydrological applications including sustainable design of rural and urban water management systems, optimization of water resource allocations, water use, pricing and water quality assessment, and agriculture and irrigation operations. The motivation for exploring and developing expert predictive models is an ongoing endeavor for hydrological applications. In this study, the potential of a relatively new data-driven method, namely the extreme learning machine (ELM) method, was explored for forecasting monthly stream-flow discharge rates in the Tigris River, Iraq. The ELM algorithm is a single-layer feedforward neural network (SLFNs) which randomly selects the input weights, hidden layer biases and analytically determines the output weights of the SLFNs. Based on the partial autocorrelation functions of historical stream-flow data, a set of five input combinations with lagged stream-flow values are employed to establish the best forecasting model. A comparative investigation is conducted to evaluate the performance of the ELM compared to other data-driven models: support vector regression (SVR) and generalized regression neural network (GRNN). The forecasting metrics defined as the correlation coefficient (r), Nash-Sutcliffe efficiency (ENS), Willmott's Index (WI), root-mean-square error (RMSE) and mean absolute error (MAE) computed between the observed and forecasted stream-flow data are employed to assess the ELM model's effectiveness. The results revealed that the ELM model outperformed the SVR and the GRNN models across a number of statistical measures. In quantitative terms, superiority of ELM over SVR and GRNN models was exhibited by ENS = 0.578, 0.378 and 0.144, r = 0.799, 0.761 and 0.468 and WI = 0.853, 0.802 and 0.689, respectively and the ELM model attained lower RMSE value by approximately 21.3% (relative to SVR) and by approximately 44.7% (relative to GRNN). Based on the findings of this

Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM). I: Model intercomparison with current land use

USGS Publications Warehouse

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

2009-01-01

This paper introduces the project on 'Assessing the impact of land use change on hydrology by ensemble modeling (LUCHEM)' that aims at investigating the envelope of predictions on changes in hydrological fluxes due to land use change. As part of a series of four papers, this paper outlines the motivation and setup of LUCHEM, and presents a model intercomparison for the present-day simulation results. Such an intercomparison provides a valuable basis to investigate the effects of different model structures on model predictions and paves the ground for the analysis of the performance of multi-model ensembles and the reliability of the scenario predictions in companion papers. In this study, we applied a set of 10 lumped, semi-lumped and fully distributed hydrological models that have been previously used in land use change studies to the low mountainous Dill catchment, Germany. Substantial differences in model performance were observed with Nash-Sutcliffe efficiencies ranging from 0.53 to 0.92. Differences in model performance were attributed to (1) model input data, (2) model calibration and (3) the physical basis of the models. The models were applied with two sets of input data: an original and a homogenized data set. This homogenization of precipitation, temperature and leaf area index was performed to reduce the variation between the models. Homogenization improved the comparability of model simulations and resulted in a reduced average bias, although some variation in model data input remained. The effect of the physical differences between models on the long-term water balance was mainly attributed to differences in how models represent evapotranspiration. Semi-lumped and lumped conceptual models slightly outperformed the fully distributed and physically based models. This was attributed to the automatic model calibration typically used for this type of models. Overall, however, we conclude that there was no superior model if several measures of model

Simulation of runoff and nutrient export from a typical small watershed in China using the Hydrological Simulation Program-Fortran.

PubMed

Li, Zhaofu; Liu, Hongyu; Luo, Chuan; Li, Yan; Li, Hengpeng; Pan, Jianjun; Jiang, Xiaosan; Zhou, Quansuo; Xiong, Zhengqin

2015-05-01

The Hydrological Simulation Program-Fortran (HSPF), which is a hydrological and water-quality computer model that was developed by the United States Environmental Protection Agency, was employed to simulate runoff and nutrient export from a typical small watershed in a hilly eastern monsoon region of China. First, a parameter sensitivity analysis was performed to assess how changes in the model parameters affect runoff and nutrient export. Next, the model was calibrated and validated using measured runoff and nutrient concentration data. The Nash-Sutcliffe efficiency (E NS ) values of the yearly runoff were 0.87 and 0.69 for the calibration and validation periods, respectively. For storms runoff events, the E NS values were 0.93 for the calibration period and 0.47 for the validation period. Antecedent precipitation and soil moisture conditions can affect the simulation accuracy of storm event flow. The E NS values for the total nitrogen (TN) export were 0.58 for the calibration period and 0.51 for the validation period. In addition, the correlation coefficients between the observed and simulated TN concentrations were 0.84 for the calibration period and 0.74 for the validation period. For phosphorus export, the E NS values were 0.89 for the calibration period and 0.88 for the validation period. In addition, the correlation coefficients between the observed and simulated orthophosphate concentrations were 0.96 and 0.94 for the calibration and validation periods, respectively. The nutrient simulation results are generally satisfactory even though the parameter-lumped HSPF model cannot represent the effects of the spatial pattern of land cover on nutrient export. The model parameters obtained in this study could serve as reference values for applying the model to similar regions. In addition, HSPF can properly describe the characteristics of water quantity and quality processes in this area. After adjustment, calibration, and validation of the parameters, the HSPF

Pan evaporation prediction using a hybrid multilayer perceptron-firefly algorithm (MLP-FFA) model: case study in North Iran

NASA Astrophysics Data System (ADS)

Ghorbani, M. A.; Deo, Ravinesh C.; Yaseen, Zaher Mundher; H. Kashani, Mahsa; Mohammadi, Babak

2017-08-01

An accurate computational approach for the prediction of pan evaporation over daily time horizons is a useful decisive tool in sustainable agriculture and hydrological applications, particularly in designing the rural water resource systems, water use allocations, utilization and demand assessments, and the management of irrigation systems. In this study, a hybrid predictive model (Multilayer Perceptron-Firefly Algorithm (MLP-FFA)) based on the FFA optimizer that is embedded within the MLP technique is developed and evaluated for its suitability for the prediction of daily pan evaporation. To develop the hybrid MLP-FFA model, the pan evaporation data measured between 2012 and 2014 for two major meteorological stations (Talesh and Manjil) located at Northern Iran are employed to train and test the predictive model. The ability of the hybrid MLP-FFA model is compared with the traditional MLP and support vector machine (SVM) models. The results are evaluated using five performance criteria metrics: root mean square error (RMSE), mean absolute error (MAE), Nash-Sutcliffe efficiency (NS), and the Willmott's Index (WI). Taylor diagrams are also used to examine the similarity between the observed and predicted pan evaporation data in the test period. Results show that an optimal MLP-FFA model outperforms the MLP and SVM model for both tested stations. For Talesh, a value of WI = 0.926, NS = 0.791, and RMSE = 1.007 mm day-1 is obtained using MLP-FFA model, compared with 0.912, 0.713, and 1.181 mm day-1 (MLP) and 0.916, 0.726, and 1.153 mm day-1 (SVM), whereas for Manjil, a value of WI = 0.976, NS = 0.922, and 1.406 mm day-1 is attained that contrasts 0.972, 0.901, and 1.583 mm day-1 (MLP) and 0.971, 0.893, and 1.646 mm day-1 (SVM). The results demonstrate the importance of the Firefly Algorithm applied to improve the performance of the MLP-FFA model, as verified through its better predictive performance compared to the MLP and SVM model.

Impact of climate change on river discharge in the Teteriv River basin (Ukraine)

NASA Astrophysics Data System (ADS)

Didovets, Iulii; Lobanova, Anastasia; Krysanova, Valentina; Snizhko, Sergiy; Bronstert, Axel

2016-04-01

The problem of water resources availability in the climate change context arises now in many countries. Ukraine is characterized by a relatively low availability of water resources compared to other countries. It is the 111th among 152 countries by the amount of domestic water resources available per capita. To ensure socio-economic development of the region and to adapt to climate change, a comprehensive assessment of potential changes in qualitative and quantitative characteristics of water resources in the region is needed. The focus of our study is the Teteriv River basin located in northern Ukraine within three administrative districts covering the area of 15,300 km2. The Teteriv is the right largest tributary of the Dnipro River, which is the fourth longest river in Europe. The water resources in the region are intensively used in industry, communal infrastructure, and agriculture. This is evidenced by a large number of dams and industrial objects which have been constructed from the early 20th century. For success of the study, it was necessary to apply a comprehensive hydrological model, tested in similar natural conditions. Therefore, an eco-hydrological model SWIM with the daily time step was applied, as this model was used previously for climate impact assessment in many similar river basins on the European territory. The model was set up, calibrated and validated for the gauge Ivankiv located close to the outlet of the Teteriv River. The Nash-Sutcliffe efficiency coefficient for the calibration period is 0.79 (0.86), and percent bias is 4,9% (-3.6%) with the daily (monthly) time step. The future climate scenarios were selected from the IMPRESSIONS (Impacts and Risks from High-End Scenarios: Strategies for Innovative Solutions, www.impressions-project.eu) project, which developed 7 climate scenarios under RCP4.5 and RCP8.5 based on GCMs and downscaled using RCMs. The results of climate impact assessment for the Teteriv River basin will be presented.

ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO2, water, and energy fluxes on daily to annual scales

NASA Astrophysics Data System (ADS)

Qiu, Chunjing; Zhu, Dan; Ciais, Philippe; Guenet, Bertrand; Krinner, Gerhard; Peng, Shushi; Aurela, Mika; Bernhofer, Christian; Brümmer, Christian; Bret-Harte, Syndonia; Chu, Housen; Chen, Jiquan; Desai, Ankur R.; Dušek, Jiří; Euskirchen, Eugénie S.; Fortuniak, Krzysztof; Flanagan, Lawrence B.; Friborg, Thomas; Grygoruk, Mateusz; Gogo, Sébastien; Grünwald, Thomas; Hansen, Birger U.; Holl, David; Humphreys, Elyn; Hurkuck, Miriam; Kiely, Gerard; Klatt, Janina; Kutzbach, Lars; Largeron, Chloé; Laggoun-Défarge, Fatima; Lund, Magnus; Lafleur, Peter M.; Li, Xuefei; Mammarella, Ivan; Merbold, Lutz; Nilsson, Mats B.; Olejnik, Janusz; Ottosson-Löfvenius, Mikaell; Oechel, Walter; Parmentier, Frans-Jan W.; Peichl, Matthias; Pirk, Norbert; Peltola, Olli; Pawlak, Włodzimierz; Rasse, Daniel; Rinne, Janne; Shaver, Gaius; Schmid, Hans Peter; Sottocornola, Matteo; Steinbrecher, Rainer; Sachs, Torsten; Urbaniak, Marek; Zona, Donatella; Ziemblinska, Klaudia

2018-02-01

Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 = 0.76; Nash-Sutcliffe modeling efficiency, MEF = 0.76) and ecosystem respiration (ER, r2 = 0.78, MEF = 0.75), with lesser accuracy for latent heat fluxes (LE, r2 = 0.42, MEF = 0.14) and and net ecosystem CO2 exchange (NEE, r2 = 0.38, MEF = 0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57-0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 < 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.

Field-scale prediction of enhanced DNAPL dissolution based on partitioning tracers.

PubMed

Wang, Fang; Annable, Michael D; Jawitz, James W

2013-09-01

The equilibrium streamtube model (EST) has demonstrated the ability to accurately predict dense nonaqueous phase liquid (DNAPL) dissolution in laboratory experiments and numerical simulations. Here the model is applied to predict DNAPL dissolution at a tetrachloroethylene (PCE)-contaminated dry cleaner site, located in Jacksonville, Florida. The EST model is an analytical solution with field-measurable input parameters. Measured data from a field-scale partitioning tracer test were used to parameterize the EST model and the predicted PCE dissolution was compared to measured data from an in-situ ethanol flood. In addition, a simulated partitioning tracer test from a calibrated, three-dimensional, spatially explicit multiphase flow model (UTCHEM) was also used to parameterize the EST analytical solution. The EST ethanol prediction based on both the field partitioning tracer test and the simulation closely matched the total recovery well field ethanol data with Nash-Sutcliffe efficiency E=0.96 and 0.90, respectively. The EST PCE predictions showed a peak shift to earlier arrival times for models based on either field-measured or simulated partitioning tracer tests, resulting in poorer matches to the field PCE data in both cases. The peak shifts were concluded to be caused by well screen interval differences between the field tracer test and ethanol flood. Both the EST model and UTCHEM were also used to predict PCE aqueous dissolution under natural gradient conditions, which has a much less complex flow pattern than the forced-gradient double five spot used for the ethanol flood. The natural gradient EST predictions based on parameters determined from tracer tests conducted with a complex flow pattern underestimated the UTCHEM-simulated natural gradient total mass removal by 12% after 170 pore volumes of water flushing indicating that some mass was not detected by the tracers likely due to stagnation zones in the flow field. These findings highlight the important

Field-scale prediction of enhanced DNAPL dissolution based on partitioning tracers

NASA Astrophysics Data System (ADS)

Wang, Fang; Annable, Michael D.; Jawitz, James W.

2013-09-01

The equilibrium streamtube model (EST) has demonstrated the ability to accurately predict dense nonaqueous phase liquid (DNAPL) dissolution in laboratory experiments and numerical simulations. Here the model is applied to predict DNAPL dissolution at a tetrachloroethylene (PCE)-contaminated dry cleaner site, located in Jacksonville, Florida. The EST model is an analytical solution with field-measurable input parameters. Measured data from a field-scale partitioning tracer test were used to parameterize the EST model and the predicted PCE dissolution was compared to measured data from an in-situ ethanol flood. In addition, a simulated partitioning tracer test from a calibrated, three-dimensional, spatially explicit multiphase flow model (UTCHEM) was also used to parameterize the EST analytical solution. The EST ethanol prediction based on both the field partitioning tracer test and the simulation closely matched the total recovery well field ethanol data with Nash-Sutcliffe efficiency E = 0.96 and 0.90, respectively. The EST PCE predictions showed a peak shift to earlier arrival times for models based on either field-measured or simulated partitioning tracer tests, resulting in poorer matches to the field PCE data in both cases. The peak shifts were concluded to be caused by well screen interval differences between the field tracer test and ethanol flood. Both the EST model and UTCHEM were also used to predict PCE aqueous dissolution under natural gradient conditions, which has a much less complex flow pattern than the forced-gradient double five spot used for the ethanol flood. The natural gradient EST predictions based on parameters determined from tracer tests conducted with a complex flow pattern underestimated the UTCHEM-simulated natural gradient total mass removal by 12% after 170 pore volumes of water flushing indicating that some mass was not detected by the tracers likely due to stagnation zones in the flow field. These findings highlight the important

Modeling phosphorus losses from soils amended with cattle manures and chemical fertilizers.

PubMed

Wang, Zhaozhi; Zhang, T Q; Tan, C S; Vadas, P; Qi, Z M; Wellen, C

2018-05-22

While applied manure/fertilizer is an important source of P loss in surface runoff, few models simulate the direct transfer of phosphorus (P) from soil-surface-applied manure/fertilizer to surface runoff. The SurPhos model was tested with 2008-2010 growing season daily surface runoff data from clay loam experimental plots subject to different manure/fertilizer applications. Model performance was evaluated on the basis of the coefficient of determination (R 2 ), Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), and the ratio of the root mean square error to the standard deviation of observed values (RSR). The model offered an acceptable performance in simulating soil labile P dynamics (R 2  = 0.75, NSE = 0.55, PBIAS = 10.43%, and RSR = 0.67) and dissolved reactive P (DRP) loss in surface runoff (R 2  ≥ 0.74 and NSE ≥ 0.69) for both solid and liquid cattle manure, as well as inorganic fertilizer. Simulated direct P loss in surface runoff from solid and liquid cattle manure accounted for 39% and 40% of total growing season DRP losses in surface runoff. To compensate for the unavailability of daily surface runoff observations under snow melt condition, the whole four years' (2008-2011) daily surface runoff predicted by EPIC (Environmental Policy Integrated Climate) was used as SurPhos input. The accuracy of simulated DRP loss in surface runoff under the different manure/fertilizer treatments was acceptable (R 2  ≥ 0.55 and NSE ≥ 0.50). For the solid cattle manure treatment, of all annual DRP losses, 19% were derived directly from the manure. Beyond offering a reliable prediction of manure/fertilizer P loss in surface runoff, SurPhos quantified different sources of DRP loss and dynamic labile P in soil, allowing a better critical assessment of different P management measures' effectiveness in mitigating DRP losses. Copyright © 2018 Elsevier B.V. All rights reserved.

National Audit of Seizure management in Hospitals (NASH): results of the national audit of adult epilepsy in the UK

PubMed Central

Dixon, Peter A; Kirkham, Jamie J; Marson, Anthony G; Pearson, Mike G

2015-01-01

Objectives About 100 000 people present to hospitals each year in England with an epileptic seizure. How they are managed is unknown; thus, the National Audit of Seizure management in Hospitals (NASH) set out to assess prior care, management of the acute event and follow-up of these patients. This paper describes the data from the second audit conducted in 2013. Setting 154 emergency departments (EDs) across the UK. Participants Data from 4544 attendances (median age of 45 years, 57% men) showed that 61% had a prior diagnosis of epilepsy, 12% other neurological problems and 22% were first seizure cases. Each ED identified 30 consecutive adult cases presenting due to a seizure. Primary and secondary outcome measures Details were recorded of the patient's prior care, management at hospital and onward referral to neurological specialists onto an online database. Descriptive results are reported at national level. Results Of those with epilepsy, 498 (18%) were on no antiepileptic drug therapy and 1330 (48%) were on monotherapy. Assessments were often incomplete and witness histories were sought in only 759 (75%) of first seizure patients, 58% were seen by a senior doctor and 57% were admitted. For first seizure patients, advice on further seizure management was given to 264 (27%) and only 55% were referred to a neurologist or epilepsy specialist. For each variable, there was wide variability among sites that was not explicable. For the sites who partook in both audits, there was a trend towards better care in 2013, but this was small and dwarfed by the intersite variability. Conclusions These results have parallels with the Sentinel Audit of Stroke performed a decade earlier. There is wide intersite variability in care covering the entire care pathway, and a need for better organised and accessible care for these patients. PMID:25829372

The effect of cocoa supplementation on hepatic steatosis, reactive oxygen species and LFABP in a rat model of NASH

PubMed Central

2011-01-01

Background Non alcoholic steatohepatitis is hypothesised to develop via a mechanism involving fat accumulation and oxidative stress. The current study aimed to investigate if an increase in oxidative stress was associated with changes in the expression of liver fatty acid binding protein in a rat model of non alcoholic steatohepatitis and whether cocoa supplementation attenuated those changes. Methods Female Sprague Dawley rats were fed a high fat control diet, a high fat methionine choline deficient diet, or one of four 12.5% cocoa supplementation regimes in combination with the high fat methionine choline deficient diet. Results Liver fatty acid binding protein mRNA and protein levels were reduced in the liver of animals with fatty liver disease when compared to controls. Increased hepatic fat content was accompanied by higher levels of oxidative stress in animals with fatty liver disease when compared to controls. An inverse association was found between the levels of hepatic liver fatty acid binding protein and the level of hepatic oxidative stress in fatty liver disease. Elevated NADPH oxidase protein levels were detected in the liver of animals with increased severity in inflammation and fibrosis. Cocoa supplementation was associated with partial attenuation of these pathological changes, although the severity of liver disease induced by the methionine choline deficient diet prevented complete reversal of any disease associated changes. Red blood cell glutathione was increased by cocoa supplementation, whereas liver glutathione was reduced by cocoa compared to methionine choline deficient diet fed animals. Conclusion These findings suggest a potential role for liver fatty acid binding protein and NADPH oxidase in the development of non alcoholic steatohepatitis. Furthermore, cocoa supplementation may have be of therapeutic benefit in less sever forms of NASH. PMID:22081873

Levels of metacaspase1 and chaperones related to protein quality control in alcoholic and nonalcoholic steatohepatitis.

PubMed

Mendoza, Alejandro S; Dorce, Jacques; Peng, Yue; French, Barbara A; Tillman, Brittany; Li, Jun; French, Samuel W

2015-02-01

Efficient management of misfolded or aggregated proteins in ASH and NASH is crucial for continued hepatic viability. Cellular protein quality control systems play an important role in the pathogenesis and progression of ASH and NASH. In a recent study, elevated Mca1 expression counteracted aggregation and accumulation of misfolded proteins and extended the life span of the yeast Saccharomyces cerevisiae (Hill et al, 2014). Mca1 may also associate with Ssa1 and Hsp104 in disaggregation and fragmentation of aggregated proteins and their subsequent degradation through the ER-associated degradation (ERAD) pathway. If degradation is not available, protection of the cellular environment from a misfolded protein is accomplished by its sequestration into two distinct inclusion bodies (Kaganovich et al., 2008) called the JUNQ (JUxta Nuclear Quality control compartment) and the IPOD (Insoluble Protein Deposit). Mca1, Hsp104, Hsp40, Ydj1, Ssa1, VCP/p97, and p62 all play important roles in protein quality control systems. This study aims to measure the expression of Mca1 and related chaperones involved in protein quality control in alcoholic steatohepatitis (ASH), and nonalcoholic steatohepatitis (NASH) compared with normal control liver biopsies. Mca1, Hsp104, Hsp40, Ydj1, Ssa1, VCP/p97, and p62 expressions were measured in three to six formalin-fixed paraffin embedded ASH and NASH liver biopsies and control normal liver specimens by immunofluorescence staining and quantified by immunofluorescence intensity. Mca1, Hsp104, Ydj1 and p62 were significantly upregulated compared to control (p<0.05) in ASH specimens. Hsp40 and VCP/p97 were also uptrending in ASH. In NASH, the only significant difference was the increased expression of Hsp104 compared to control (p<0.05). Ssa1 levels were uptrending in both ASH and NASH specimens. The upregulation of Mca1, Hsp104, Ydj1 and p62 in ASH may be elicited as a response to the chronic exposure of the hepatocytes to the toxicity of alcohol

[Prevalence of non-alcoholic fatty liver disease in a population with elevated transaminases and level of accuracy of the diagnosis in Primary Care].

PubMed

Samperio-González, María Amelia; Selvi-Blasco, Marta; Manzano-Montero, Mónica; Méndez-Gómez, Judit; Gil-Prades, Montserrat; Azagra, Rafael

2016-05-01

Nonalcoholic fatty liver disease (NAFLD) is the most common cause of elevated transaminases in adults. Determine the prevalence of NASH in patients with sustained hypertransaminasemia, and Know the adequacy of the registered in Primary Care (AP) diagnosis. 1) Cross-sectional study with a random sample of patients with elevated alanine aminotransferase (ALT) held (ALT> 32 for ≥6 months), ruling out other causes of liver disease, according to clinical, laboratory and ultrasound scan criteria in AP and 2) cross-sectional description of all cases diagnosed with NASH recorded (K76 - ICD10) with diagnostic adequacy analysis according to standard criteria. 290 patients were analyzed: 76 were diagnosed as NASH (26.1%), 44 women (57.9%). Multivariate analysis adjusted for age and sex showed no association between NASH and male gender (OR: 0.5; CI95%: 0.3-0.9), diabetes mellitus (DM) (OR: 2.42; CI95%: 1.2-4.9) and hypertension blood pressure (HBP) (OR: 3.07; CI 95% 1.6-5.6). Of the 209 diagnosed with NASH record: 51 (24.4%) met the criteria for NASH. The rest had insufficient records. 53.1% lacked sustained hypertransaminasemia; 48% of viral serology; 11% supported and 53.1% abdominal ultrasound registration of alcohol. Severe NASH is frequent among patients with sustained hypertransaminasemia. The DM and hypertension significantly increase the risk of NASH. The diagnosis of NASH is recorded without considering all criteria and mainly NASH made by ultrasonography. They should unify diagnostic criteria in the register of NASH. Copyright © 2015 Elsevier España, S.L.U. All rights reserved.

Identification of novel noninvasive markers for diagnosing nonalcoholic steatohepatitis and related fibrosis by data mining.

PubMed

Yoshimura, Keito; Okanoue, Takeshi; Ebise, Hayao; Iwasaki, Tsuyoshi; Mizuno, Masayuki; Shima, Toshihide; Ichihara, Junji; Yamazaki, Kazuto

2016-02-01

It is important that patients with nonalcoholic steatohepatitis (NASH) are diagnosed and treated early to prevent serious complications, such as liver cirrhosis or hepatocellular carcinoma. However, current methods for NASH diagnosis are invasive given that they rely on liver biopsy, making early diagnosis difficult. In this study, we developed novel noninvasive markers for the diagnosis of NASH and NASH-related fibrosis. A total of 132 Japanese patients with nonalcoholic fatty liver disease were included in this study. Blood samples were collected, and 261 biomolecules were quantified in serum. Using cluster and pathway analyses, we identified biomolecule modules connected to biological events that occur with disease progression to NASH. The modules were used as variables for diagnosis, leading to a NASH diagnostic marker associated with two biological events, that is, protective response to hepatic steatosis and hepatitis-causing innate immune response. Regarding the NASH-related fibrosis marker, immunological responses to hepatocyte injury were identified as a biological event. To develop diagnostic markers for NASH and NASH-related fibrosis, specific biomolecules were selected from each biomolecule module. The former marker was obtained by averaging the levels of four biomolecules, whereas the latter was obtained by averaging the levels of two biomolecules. Both markers achieved a diagnostic accuracy of almost 0.9 of the area under the receiver operating characteristic curve, and the latter exhibited equivalent performance in an independent group of 62 prospectively recruited patients. We developed highly accurate markers for the diagnosis of both NASH and NASH-related fibrosis (i.e., FM-NASH index and FM-fibro index, respectively). These markers may be used as an alternative diagnostic tool to liver biopsy. © 2015 by the American Association for the Study of Liver Diseases.

EXTENDING THE REALM OF OPTIMIZATION FOR COMPLEX SYSTEMS: UNCERTAINTY, COMPETITION, AND DYNAMICS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shanbhag, Uday V; Basar, Tamer; Meyn, Sean

Research reported addressed these topics: the development of analytical and algorithmic tools for distributed computation of Nash equilibria; synchronization in mean-field oscillator games, with an emphasis on learning and efficiency analysis; questions that combine learning and computation; questions including stochastic and mean-field games; modeling and control in the context of power markets.

Prevalence and Outcome of Nonalcoholic Fatty Liver Disease in Adolescents and Young Adults Undergoing Weight Loss Surgery

PubMed Central

Corey, Kathleen E.; Stanley, Takara L.; Misdraji, Joseph; Scirica, Christina; Pratt, Janey; Hoppin, Alison; Misra, Madhusmita

2014-01-01

We evaluated the prevalence of NAFLD (nonalcoholic fatty liver disease) and NASH (nonalcoholic steatohepatitis) in 27 adolescents referred for weight loss surgery (WLS). On biopsy 18 patients (66.7%) had NAFLD, and of those, 10 patients (37.0%) had NASH and 11 (40.7%) had fibrosis. Insulin, HbA1C and homeostatic model assessment of insulin resistance (HOMA-IR) were significantly higher in patients with NASH than those without NASH. Following WLS, 40% of NASH patients had persistently elevated aminotransferase levels despite weight loss. We found that NASH is underdiagnosed in adolescents referred for WLS and hyperinsulinemia, HOMA-IR and HbA1c can aid in identifying high-risk patients. PMID:24677740

Simulation of the hydraulic performance of highway filter drains through laboratory models and stormwater management tools.

PubMed

Sañudo-Fontaneda, Luis A; Jato-Espino, Daniel; Lashford, Craig; Coupe, Stephen J

2017-05-23

Road drainage is one of the most relevant assets in transport infrastructure due to its inherent influence on traffic management and road safety. Highway filter drains (HFDs), also known as "French Drains", are the main drainage system currently in use in the UK, throughout 7000 km of its strategic road network. Despite being a widespread technique across the whole country, little research has been completed on their design considerations and their subsequent impact on their hydraulic performance, representing a gap in the field. Laboratory experiments have been proven to be a reliable indicator for the simulation of the hydraulic performance of stormwater best management practices (BMPs). In addition to this, stormwater management tools (SMT) have been preferentially chosen as a design tool for BMPs by practitioners from all over the world. In this context, this research aims to investigate the hydraulic performance of HFDs by comparing the results from laboratory simulation and two widely used SMT such as the US EPA's stormwater management model (SWMM) and MicroDrainage®. Statistical analyses were applied to a series of rainfall scenarios simulated, showing a high level of accuracy between the results obtained in laboratory and using SMT as indicated by the high and low values of the Nash-Sutcliffe and R 2 coefficients and root-mean-square error (RMSE) reached, which validated the usefulness of SMT to determine the hydraulic performance of HFDs.

On approaches to analyze the sensitivity of simulated hydrologic fluxes to model parameters in the community land model

DOE PAGES

Bao, Jie; Hou, Zhangshuan; Huang, Maoyi; ...

2015-12-04

Here, effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash-Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalizedmore » linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.« less

LIS-HYMAP coupled Hydrological Modeling in the Nile River Basin and the Greater Horn of Africa

NASA Astrophysics Data System (ADS)

Jung, H. C.; Getirana, A.; Policelli, F. S.

2015-12-01

Water scarcity and resources in Africa have been exacerbated by periodic droughts and floods. However, few studies show the quantitative analysis of water balance or basin-scale hydrological modeling in Northeast Africa. The NASA Land Information System (LIS) is implemented to simulate land surface processes in the Nile River Basin and the Greater Horn of Africa. In this context, the Noah land surface model (LSM) and the Hydrological Modeling and Analysis Platform (HYMAP) are used to reproduce the water budget and surface water (rivers and floodplains) dynamics in that region. The Global Data Assimilation System (GDAS) meteorological dataset is used to force the system . Due to the unavailability of recent ground-based observations, satellite data are considered to evaluate first model outputs. Water levels at 10 Envisat virtual stations and water discharges at a gauging station are used to provide model performance coefficients (e.g. Nash-Sutcliffe, delay index, relative error). We also compare the spatial and temporal variations of flooded areas from the model with the Global Inundation Extent from Multi-Satellites (GIEMS) and the Alaska Satellite Facility (ASF)'s MEaSUREs Wetland data. Finally, we estimate surface water storage variations using a hypsographic curve approach with Shuttle Radar Topography Mission (SRTM) topographic data and evaluate the model-derived water storage changes in both river and floodplain. This study demonstrates the feasibility of using LIS-HYMAP coupled modeling to support seasonal forecast methods for prediction of decision-relevant metrics of hydrologic extremes.

Effectiveness of SWAT in characterizing the watershed hydrology in the snowy-mountainous Lower Bear Malad River (LBMR) watershed in Box Elder County, Utah

NASA Astrophysics Data System (ADS)

Salha, A. A.; Stevens, D. K.

2015-12-01

Distributed watershed models are essential for quantifying sediment and nutrient loads that originate from point and nonpoint sources. Such models are primary means towards generating pollutant estimates in ungaged watersheds and respond well at watershed scales by capturing the variability in soils, climatic conditions, land uses/covers and management conditions over extended periods of time. This effort evaluates the performance of the Soil and Water Assessment Tool (SWAT) model as a watershed level tool to investigate, manage, and characterize the transport and fate of nutrients in Lower Bear Malad River (LBMR) watershed (Subbasin HUC 16010204) in Utah. Water quality concerns have been documented and are primarily attributed to high phosphorus and total suspended sediment concentrations caused by agricultural and farming practices along with identified point sources (WWTPs). Input data such as Digital Elevation Model (DEM), land use/Land cover (LULC), soils, and climate data for 10 years (2000-2010) is utilized to quantify the LBMR streamflow. Such modeling is useful in developing the required water quality regulations such as Total Maximum Daily Loads (TMDL). Measured concentrations of nutrients were closely captured by simulated monthly nutrient concentrations based on the R2 and Nash- Sutcliffe fitness criteria. The model is expected to be able to identify contaminant non-point sources, identify areas of high pollution risk, locate optimal monitoring sites, and evaluate best management practices to cost-effectively reduce pollution and improve water quality as required by the LBMR watershed's TMDL.

Estimating hydrologic budgets for six Persian Gulf watersheds, Iran

NASA Astrophysics Data System (ADS)

Hosseini, Majid; Ghafouri, Mohammad; Tabatabaei, MahmoudReza; Goodarzi, Masoud; Mokarian, Zeinab

2017-10-01

Estimation of the major components of the hydrologic budget is important for determining the impacts on the water supply and quality of either planned or proposed land management projects, vegetative changes, groundwater withdrawals, and reservoir management practices and plans. As acquisition of field data is costly and time consuming, models have been created to test various land use practices and their concomitant effects on the hydrologic budget of watersheds. To simulate such management scenarios realistically, a model should be able to simulate the individual components of the hydrologic budget. The main objective of this study is to perform the SWAT2012 model for estimation of hydrological budget in six subbasin of Persian Gulf watershed; Golgol, Baghan, Marghab Shekastian, Tangebirim and Daragah, which are located in south and south west of Iran during 1991-2009. In order to evaluate the performance of the model, hydrological data, soil map, land use map and digital elevation model (DEM) are obtained and prepared for each catchment to run the model. SWAT-CUP with SUFI2 program was used for simulation, uncertainty and validation with 95 Percent Prediction Uncertainty. Coefficient of determination ( R 2) and Nash-Sutcliffe coefficient (NS) were used for evaluation of the model simulation results. Comparison of measured and predicted values demonstrated that each component of the model gave reasonable output and that the interaction among components was realistic. The study has produced a technique with reliable capability for annual and monthly water budget components in Persian Gulf watershed.

Improving Alpine Streamflow Simulations by Incorporation of Evapotranspiration and Soil Moisture Data

NASA Astrophysics Data System (ADS)

Tobin, K. J.; Bennett, M. E.

2017-12-01

Over the last decade autocalibration routines have become commonplace in watershed modeling. This approach is most often used to simulate a streamflow at a basin's outlet. In alpine settings spring/early summer snowmelt is by far the dominant signal in this system. Therefore, there is great potential for a modeled watershed to underperform during other times of the year. This tendency has been noted in many prior studies. In this work, the Soil and Water Assessment Tool (SWAT) model was autocalibrated with the SUFI-2 routine. Two mountainous watersheds from Idaho and Utah were examined. In this study, the basins were calibrated on a monthly satellite based on the MODIS 16A2 product. The gridded MODIS product was ideally suited to derive an estimate of ET on a subbasin basis. Soil moisture data was derived from extrapolation of in situ sites from the SNOwpack TELemetry (SNOTEL) network. Previous work has indicated that in situ soil moisture can be applied to derive an estimate at a significant distance (>30 km) away from the in situ site. Optimized ET and soil moisture parameter values were then applied to streamflow simulations. Preliminary results indicate improved streamflow performance both during calibration (2005-2011) and validation (2012-2014) periods. Streamflow performance was monitored with not only standard objective metrics (bias and Nash Sutcliffe coefficients) but also improved baseflow accuracy, demonstrating the utility of this approach in improving watershed modeling fidelity outside the main snowmelt season.

Data assimilation in integrated hydrological modelling in the presence of observation bias

NASA Astrophysics Data System (ADS)

Rasmussen, J.; Madsen, H.; Jensen, K. H.; Refsgaard, J. C.

2015-08-01

The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both stream flow and groundwater modeling. The Colored Noise Kalman filter (ColKF) and the Separate bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman Filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved stream flow modeling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modeling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behavior and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

Data assimilation in integrated hydrological modelling in the presence of observation bias

NASA Astrophysics Data System (ADS)

Rasmussen, Jørn; Madsen, Henrik; Høgh Jensen, Karsten; Refsgaard, Jens Christian

2016-05-01

The use of bias-aware Kalman filters for estimating and correcting observation bias in groundwater head observations is evaluated using both synthetic and real observations. In the synthetic test, groundwater head observations with a constant bias and unbiased stream discharge observations are assimilated in a catchment-scale integrated hydrological model with the aim of updating stream discharge and groundwater head, as well as several model parameters relating to both streamflow and groundwater modelling. The coloured noise Kalman filter (ColKF) and the separate-bias Kalman filter (SepKF) are tested and evaluated for correcting the observation biases. The study found that both methods were able to estimate most of the biases and that using any of the two bias estimation methods resulted in significant improvements over using a bias-unaware Kalman filter. While the convergence of the ColKF was significantly faster than the convergence of the SepKF, a much larger ensemble size was required as the estimation of biases would otherwise fail. Real observations of groundwater head and stream discharge were also assimilated, resulting in improved streamflow modelling in terms of an increased Nash-Sutcliffe coefficient while no clear improvement in groundwater head modelling was observed. Both the ColKF and the SepKF tended to underestimate the biases, which resulted in drifting model behaviour and sub-optimal parameter estimation, but both methods provided better state updating and parameter estimation than using a bias-unaware filter.

Application of the Soil and Water Assessment Tool (SWAT) to predict the impact of best management practices in Jatigede Catchment Area

NASA Astrophysics Data System (ADS)

Ridwansyah, Iwan; Fakhrudin, M.; Wibowo, Hendro; Yulianti, Meti

2018-02-01

Cimanuk watershed is one of the national priority watersheds for rehabilitation considering its critical condition. In this area, Jatigede Reservoir operates, which is the second largest reservoir in Indonesia, after Jatiluhur Reservoir. The reservoir performs several functions, including flood control, irrigation for 90.000 ha of rice fields, water supply of 3.500 litres per second, and power generation of 110 MW. In 2004 the Jatigede Reservoir catchment area had a critical land area of 40.875 ha (28% of the catchment area). The sedimentation rate in Cimanuk River at Eretan station shows a high rate (5.32 mm/year), which potentially decreases the function of Jatigede Reservoir. Therefore, a strategy of Best Management Practice’s (BMP’s) is required to mitigate the problem by using SWAT hydrology modelling. The aim of this study is to examine the impact of BMP’s on surface runoff and sediment yield in Jatigede Reservoir Catchment Area. Simulations were conducted using land use in 2011. The results of this study suggest that SWAT model is considered as a reasonable modelling of BMP’s simulation concerning Nash-Sutcliffe Coefficients (0.71). The simulation is using terraces, silt pit, and dam trenches as BMP’s techniques. The BMP’s application can reduce surface runoff from 99.7 mm to 75.8 mm, and decrease sediment yield from 61.9 ton/ha/year to 40.8 ton/ha/year.

The Continuous Monitoring of Flash Flood Velocity Field based on an Automated LSPIV System

NASA Astrophysics Data System (ADS)

Li, W.; Ran, Q.; Liao, Q.

2014-12-01

Large-scale particle image velocimetry (LSPIV) is a non-intrusive tool for flow velocity field measurement and has more advantages against traditional techniques, with its applications on river, lake and ocean, especially under extreme conditions. An automated LSPIV system is presented in this study, which can be easily set up and executed for continuous monitoring of flash flood. The experiment site is Longchi village, Sichuan Province, where 8.0 magnitude earthquake occurred in 2008 and debris flow happens every year since then. The interest of area is about 30m*40m of the channel which has been heavily destroyed by debris flow. Series of videos obtained during the flood season indicates that flood outbreaks after rainstorm just for several hours. Measurement is complete without being influenced by this extreme weather condition and results are more reliable and accurate due to high soil concentration. Compared with direct measurement by impellor flow meter, we validated that LSPIV works well at mountain stream, with index of 6.7% (Average Relative Error) and 95% (Nash-Sutcliffe Coefficient). On Jun 26, the maximum flood surface velocity reached 4.26 m/s, and the discharge based on velocity-area method was also decided. Overall, this system is safe, non-contact and can be adjusted according to our requirement flexibly. We can get valuable data of flood which is scarce before, which will make a great contribution to the analysis of flood and debris flow mechanism.

Climate response of the soil nitrogen cycle in three forest types of a headwater Mediterranean catchment

NASA Astrophysics Data System (ADS)

Lupon, Anna; Gerber, Stefan; Sabater, Francesc; Bernal, Susana

2015-05-01

Future changes in climate may affect soil nitrogen (N) transformations, and consequently, plant nutrition and N losses from terrestrial to stream ecosystems. We investigated the response of soil N cycling to changes in soil moisture, soil temperature, and precipitation across three Mediterranean forest types (evergreen oak, beech, and riparian) by fusing a simple process-based model (which included climate modifiers for key soil N processes) with measurements of soil organic N content, mineralization, nitrification, and concentration of ammonium and nitrate. The model describes sources (atmospheric deposition and net N mineralization) and sinks (plant uptake and hydrological losses) of inorganic N from and to the 0-10 cm soil pool as well as net nitrification. For the three forest types, the model successfully recreated the magnitude and temporal pattern of soil N processes and N concentrations (Nash-Sutcliffe coefficient = 0.49-0.96). Changes in soil water availability drove net N mineralization and net nitrification at the oak and beech forests, while temperature and precipitation were the strongest climatic factors for riparian soil N processes. In most cases, net N mineralization and net nitrification showed a different sensitivity to climatic drivers (temperature, soil moisture, and precipitation). Our model suggests that future climate change may have a minimal effect on the soil N cycle of these forests (<10% change in mean annual rates) because positive warming and negative drying effects on the soil N cycle may counterbalance each other.

Dendritic cells limit fibroinflammatory injury in nonalcoholic steatohepatitis in mice.

PubMed

Henning, Justin R; Graffeo, Christopher S; Rehman, Adeel; Fallon, Nina C; Zambirinis, Constantinos P; Ochi, Atsuo; Barilla, Rocky; Jamal, Mohsin; Deutsch, Michael; Greco, Stephanie; Ego-Osuala, Melvin; Bin-Saeed, Usama; Rao, Raghavendra S; Badar, Sana; Quesada, Juan P; Acehan, Devrim; Miller, George

2013-08-01

Nonalcoholic steatohepatitis (NASH) is the most common etiology of chronic liver dysfunction in the United States and can progress to cirrhosis and liver failure. Inflammatory insult resulting from fatty infiltration of the liver is central to disease pathogenesis. Dendritic cells (DCs) are antigen-presenting cells with an emerging role in hepatic inflammation. We postulated that DCs are important in the progression of NASH. We found that intrahepatic DCs expand and mature in NASH liver and assume an activated immune phenotype. However, rather than mitigating the severity of NASH, DC depletion markedly exacerbated intrahepatic fibroinflammation. Our mechanistic studies support a regulatory role for DCs in NASH by limiting sterile inflammation through their role in the clearance of apoptotic cells and necrotic debris. We found that DCs limit CD8(+) T-cell expansion and restrict Toll-like receptor expression and cytokine production in innate immune effector cells in NASH, including Kupffer cells, neutrophils, and inflammatory monocytes. Consistent with their regulatory role in NASH, during the recovery phase of disease, ablation of DC populations results in delayed resolution of intrahepatic inflammation and fibroplasia. Our findings support a role for DCs in modulating NASH. Targeting DC functional properties may hold promise for therapeutic intervention in NASH. Copyright © 2013 American Association for the Study of Liver Diseases.

Mechanism of the development of nonalcoholic steatohepatitis after pancreaticoduodenectomy.

PubMed

Nagaya, Tadanobu; Tanaka, Naoki; Kimura, Takefumi; Kitabatake, Hiroyuki; Fujimori, Naoyuki; Komatsu, Michiharu; Horiuchi, Akira; Yamaura, Takahiro; Umemura, Takeji; Sano, Kenji; Gonzalez, Frank J; Aoyama, Toshifumi; Tanaka, Eiji

2015-06-01

It is recognized that nonalcoholic fatty liver disease (NAFLD), including nonalcoholic steatohepatitis (NASH), may develop after pancreaticoduodenectomy (PD). However, the mechanism of NASH development remains unclear. This study aimed to examine the changes in gene expression associated with NASH occurrence following PD. The expression of genes related to fatty acid/triglyceride (FA/TG) metabolism and inflammatory signaling was examined using liver samples obtained from 7 post-PD NASH patients and compared with 6 healthy individuals and 32 conventional NASH patients. The livers of post-PD NASH patients demonstrated significant up-regulation of the genes encoding CD36, FA-binding proteins 1 and 4, acetyl-coenzyme A carboxylase α, diacylglycerol acyltransferase 2, and peroxisome proliferator-activated receptor (PPAR) γ compared with normal and conventional NASH livers. Although serum apolipoprotein B (ApoB) and TG were decreased in post-PD NASH patients, the mRNAs of ApoB and microsomal TG transfer protein were robustly increased, indicating impaired TG export from the liver as very-low-density lipoprotein (VLDL). Additionally, elevated mRNA levels of myeloid differentiation primary response 88 and superoxide dismutases in post-PD NASH livers suggested significant activation of innate immune response and augmentation of oxidative stress generation. Enhanced FA uptake into hepatocytes and lipogenesis, up-regulation of PPARγ, and disruption of VLDL excretion into the circulation are possible mechanisms of steatogenesis after PD. These results provide a basis for understanding the pathogenesis of NAFLD/NASH following PD.

Expression of cytokine signaling genes in morbidly obese patients with non-alcoholic steatohepatitis and hepatic fibrosis.

PubMed

Estep, J Michael; Baranova, Ancha; Hossain, Noreen; Elariny, Hazem; Ankrah, Kathy; Afendy, Arian; Chandhoke, Vikas; Younossi, Zobair M

2009-05-01

White adipose tissue (WAT) from visceral adiposity plays an important role in the pathogenesis of non-alcoholic steatohepatitis (NASH). Development of NASH and its progression to fibrosis is partially due to cytokines and adipokines produced by WAT. The aim of this study was to assess the association of hepatic fibrosis and NASH by evaluating the intrinsic differences in the inflammatory cytokine signaling in the visceral adipose tissue obtained from morbidly obese patients. We used targeted microarrays representing human genes involved in the inflammatory and fibrogenic reactions to profile visceral adipose samples of 15 well-matched NASH patients with and without fibrosis. Additionally, visceral adipose samples were subjected to real-time polymerase chain reaction profiling of 84 inflammations related genes. Eight genes (CCL2, CCL4, CCL18, CCR1, IL10RB, IL15RA, and LTB) were differentially expressed in NASH with fibrosis. Additionally, an overlapping but distinct list of the differentially expressed genes were found in NASH with type II diabetes (DM; IL8, BLR1, IL2RA, CD40LG, IL1RN, IL15RA, and CCL4) as compared to NASH without DM. Inflammatory cytokines are differentially expressed in the adipose tissue of NASH with fibrosis, as well in NASH with DM. These findings point at the interaction of adipose inflammatory cytokines, DM, hepatic fibrosis in NASH, and its progression to cirrhosis and end-stage liver disease.

Paraoxonase 1 and oxidative stress in paediatric non-alcoholic steatohepatitis.

PubMed

Desai, Sonal; Baker, Susan S; Liu, Wensheng; Moya, Diana A; Browne, Richard W; Mastrandrea, Lucy; Baker, Robert D; Zhu, Lixin

2014-01-01

Non-alcoholic steatohepatitis (NASH) in children is a significant public health concern. Oxidative stress is an important component in the pathophysiology of NASH. Several enzymatic antioxidant mechanisms protect the liver from oxidative injury. Examination of the expression of these enzymes in NASH livers may provide insight on the roles for these antioxidant mechanisms in the pathophysiology of NASH. The mRNA expression of catalase, glutathione peroxidase 1 (GPX1), glutathione reductase (GSR), paraoxonase 1 (PON1) and other reactive oxygen species-related genes was evaluated by microarray and quantitative real-time PCR analyses. The PON1 protein levels were evaluated in liver and serum by Western blot analyses. Serum enzymatic activities of GPX, GSR and PON1 (paraoxonase and arylesterase activities) were examined. NASH livers exhibited elevated mRNA expression of catalase and PON1, but not GPX1 or GSR. No difference in serum GPX or GSR activity was detected between NASH patients and controls. Elevated expression of PON1 mRNA and protein was detected in NASH livers, but serum PON1 protein and activities were not elevated. Elevated expression of catalase and PON1 suggests protective roles for these antioxidants in NASH livers. Given the importance of oxidative stress in the pathophysiology of NASH, future studies focusing on these enzymes could identify important targets for therapeutic or preventive interventions for NASH patients. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Anisotropic and heterogeneous mechanical properties of a stratified shale/limestone sequence at Nash Point, South Wales: A case study for hydraulic fracture propagation through a layered medium

NASA Astrophysics Data System (ADS)

Forbes Inskip, Nathaniel; Meredith, Philip; Gudmundsson, Agust

2016-04-01

While considerable effort has been expended on the study of fracture propagation in rocks in recent years, our understanding of how fractures propagate through layered sedimentary rocks with different mechanical and elastic properties remains poorly constrained. Yet this is a key issue controlling the propagation of both natural and anthropogenic hydraulic fractures in layered sequences. Here we report measurements of the contrasting mechanical and elastic properties of the Lower Lias at Nash Point, South Wales, which comprises an interbedded sequence of shale and limestone layers, and how those properties may influence fracture propagation. Elastic properties of both materials have been characterised via ultrasonic wave velocity measurements as a function of azimuth on samples cored both normal and parallel to bedding. The shale is highly anisotropic, with P-wave velocities varying from 2231 to 3890 m s-1, giving an anisotropy of ~55%. By contrast, the limestone is essentially isotropic, with a mean P-wave velocity of 5828 m s-1 and an anisotropy of ~2%. The dynamic Young's modulus of the shale, calculated from P- and S-wave velocity data, is also anisotropic with a value of 36 GPa parallel to bedding and 12 GPa normal to bedding. The modulus of the limestone is again isotropic with a value of 80 GPa. It follows that for a vertical fracture propagating (i.e. normal to bedding) the modulus contrast is 6.6. This is important because the contrast in elastic properties is a key factor in controlling whether fractures arrest, deflect, or propagate across interfaces between layers in a sequence. There are three principal mechanisms by which a fracture may deflect across or along an interface, namely: Cook-Gordon debonding, stress barrier, and elastic mismatch. Preliminary numerical modelling results (using a Finite Element Modelling software) of induced fractures at Nash Point suggest that all three are important. The results demonstrate a rotation of the maximum

Metabolism dysregulation induces a specific lipid signature of nonalcoholic steatohepatitis in patients

PubMed Central

Chiappini, Franck; Coilly, Audrey; Kadar, Hanane; Gual, Philippe; Tran, Albert; Desterke, Christophe; Samuel, Didier; Duclos-Vallée, Jean-Charles; Touboul, David; Bertrand-Michel, Justine; Brunelle, Alain; Guettier, Catherine; Le Naour, François

2017-01-01

Nonalcoholic steatohepatitis (NASH) is a condition which can progress to cirrhosis and hepatocellular carcinoma. Markers for NASH diagnosis are still lacking. We performed a comprehensive lipidomic analysis on human liver biopsies including normal liver, nonalcoholic fatty liver and NASH. Random forests-based machine learning approach allowed characterizing a signature of 32 lipids discriminating NASH with 100% sensitivity and specificity. Furthermore, we validated this signature in an independent group of NASH patients. Then, metabolism dysregulations were investigated in both patients and murine models. Alterations of elongase and desaturase activities were observed along the fatty acid synthesis pathway. The decreased activity of the desaturase FADS1 appeared as a bottleneck, leading upstream to an accumulation of fatty acids and downstream to a deficiency of long-chain fatty acids resulting to impaired phospholipid synthesis. In NASH, mass spectrometry imaging on tissue section revealed the spreading into the hepatic parenchyma of selectively accumulated fatty acids. Such lipids constituted a highly toxic mixture to human hepatocytes. In conclusion, this study characterized a specific and sensitive lipid signature of NASH and positioned FADS1 as a significant player in accumulating toxic lipids during NASH progression. PMID:28436449