Modelling water use in global hydrological models: review, challenges and directions

NASA Astrophysics Data System (ADS)

Bierkens, M. F.; de Graaf, I.; Wada, Y.; Wanders, N.; Van Beek, L. P.

2017-12-01

During the late 1980s and early 1990s, awareness of the shortage of global water resources lead to the first detailed global water resources assessments using regional statistics of water use and observations of meteorological and hydrological variables. Shortly thereafter, the first macroscale hydrological models (MHM) appeared. In these models, blue water (i.e., surface water and renewable groundwater) availability was calculated by accumulating runoff over a stream network and comparing it with population densities or with estimated water demand for agriculture, industry and households. In this talk we review the evolution of human impact modelling in global land models with a focus on global water resources, touching upon developments of the last 15 years: i.e. calculating human water scarcity; estimating groundwater depletion; adding dams and reservoirs; fully integrating water use (demand, withdrawal, consumption, return flow) in the hydrology; simulating the effects of land use change. We show example studies for each of these steps. We identify We identify major challenges that hamper the further development of integrated water resources modelling. Examples of these are: 1) simulating reservoir operations; 2) including local infrastructure and redistribution; 3) using the correct allocations rules; 4) projecting future water demand and water use. For each of these challenges we signify promising directions for further research.

Meteorological satellite accomplishments

NASA Technical Reports Server (NTRS)

Allison, L. J.; Arking, A.; Bandeen, W. R.; Shenk, W. E.; Wexler, R.

1974-01-01

The various types of meteorological satellites are enumerated. Vertical sounding, parameter extraction technique, and both macroscale and mesoscale meteorological phenomena are discussed. The heat budget of the earth-atmosphere system is considered, along with ocean surface and hydrology.

Hydrologic Implications of Dynamical and Statistical Approaches to Downscaling Climate Model Outputs

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

Wood, Andrew W; Leung, Lai R; Sridhar, V

Six approaches for downscaling climate model outputs for use in hydrologic simulation were evaluated, with particular emphasis on each method's ability to produce precipitation and other variables used to drive a macroscale hydrology model applied at much higher spatial resolution than the climate model. Comparisons were made on the basis of a twenty-year retrospective (1975–1995) climate simulation produced by the NCAR-DOE Parallel Climate Model (PCM), and the implications of the comparison for a future (2040–2060) PCM climate scenario were also explored. The six approaches were made up of three relatively simple statistical downscaling methods – linear interpolation (LI), spatial disaggregationmore » (SD), and bias-correction and spatial disaggregation (BCSD) – each applied to both PCM output directly (at T42 spatial resolution), and after dynamical downscaling via a Regional Climate Model (RCM – at ½-degree spatial resolution), for downscaling the climate model outputs to the 1/8-degree spatial resolution of the hydrological model. For the retrospective climate simulation, results were compared to an observed gridded climatology of temperature and precipitation, and gridded hydrologic variables resulting from forcing the hydrologic model with observations. The most significant findings are that the BCSD method was successful in reproducing the main features of the observed hydrometeorology from the retrospective climate simulation, when applied to both PCM and RCM outputs. Linear interpolation produced better results using RCM output than PCM output, but both methods (PCM-LI and RCM-LI) lead to unacceptably biased hydrologic simulations. Spatial disaggregation of the PCM output produced results similar to those achieved with the RCM interpolated output; nonetheless, neither PCM nor RCM output was useful for hydrologic simulation purposes without a bias-correction step. For the future climate scenario, only the BCSD-method (using PCM or RCM) was able to produce hydrologically plausible results. With the BCSD method, the RCM-derived hydrology was more sensitive to climate change than the PCM-derived hydrology.« less

Evapotranspiration and runoff from large land areas: Land surface hydrology for atmospheric general circulation models

NASA Technical Reports Server (NTRS)

Famiglietti, J. S.; Wood, Eric F.

1993-01-01

A land surface hydrology parameterization for use in atmospheric GCM's is presented. The parameterization incorporates subgrid scale variability in topography, soils, soil moisture and precipitation. The framework of the model is the statistical distribution of a topography-soils index, which controls the local water balance fluxes, and is therefore taken to represent the large land area. Spatially variable water balance fluxes are integrated with respect to the topography-soils index to yield our large topography-soils distribution, and interval responses are weighted by the probability of occurrence of the interval. Grid square averaged land surface fluxes result. The model functions independently as a macroscale water balance model. Runoff ratio and evapotranspiration efficiency parameterizations are derived and are shown to depend on the spatial variability of the above mentioned properties and processes, as well as the dynamics of land surface-atmosphere interactions.

A similarity based approach to identify homogeneous regions for seasonal forecasting

NASA Astrophysics Data System (ADS)

Schick, Simon; Rössler, Ole; Weingartner, Rolf

2015-04-01

Seasonal runoff forecasting using statistical models is challenged by a large number of candidate predictors and a general weak predictor-predictand relationship. As the area of the target basin increases, often also the available data sets do, thus reinforcing the predictor selection challenge. We propose an approach which follows the idea of 'divide and conquer' as developed in computational sciences and machine learning: First, the macroscale target basin is partitioned into homogeneous regions using all its gauged mesoscale subbasins. Second, one representative subbasin per homogeneous region is identified, for which models are fitted and applied. Third, the resulting forecasts are combined at the scale of the macroscale target basin. This approach requires a suitable method to identify homogeneous regions and representative subbasins. We suggest a way based on hydrological similarity, as catchment similarity estimated with respect to physiographic-climatic descriptors does not necessarily imply similar runoff response. Each descriptor is derived from daily runoff series and aimed to reflect a specific catchment characteristic: autocorrelation coefficient, parameters of fitted Gamma distribution and low/high flow indices (based on daily runoff values) fluctuation of the standard deviation within the yearly cycle (based on weekly runoff values) dominant harmonics obtained from the discrete Fourier transform (based on monthly runoff values) long term trend (based on yearly runoff values) Where necessary, the runoff series first need to be standardized, aggregated, detrended or deseasonalized. As a preliminary study we present the results of a cluster analysis for the Swiss Rhine River as macroscale target basin, which leads to about 40 mesoscale subbasins with runoff series for the period 1991-2010. Problems we have to address include the choice of a clustering algorithm, the identification of an appropriate number of regions and the selection of representative subbasins per region. The results are finally discussed with respect to the runoff regimes as defined in the Hydrological Atlas of Switzerland.

Hydrological Validation of The Lpj Dynamic Global Vegetation Model - First Results and Required Actions

NASA Astrophysics Data System (ADS)

Haberlandt, U.; Gerten, D.; Schaphoff, S.; Lucht, W.

Dynamic global vegetation models are developed with the main purpose to describe the spatio-temporal dynamics of vegetation at the global scale. Increasing concern about climate change impacts has put the focus of recent applications on the sim- ulation of the global carbon cycle. Water is a prime driver of biogeochemical and biophysical processes, thus an appropriate representation of the water cycle is crucial for their proper simulation. However, these models usually lack thorough validation of the water balance they produce. Here we present a hydrological validation of the current version of the LPJ (Lund- Potsdam-Jena) model, a dynamic global vegetation model operating at daily time steps. Long-term simulated runoff and evapotranspiration are compared to literature values, results from three global hydrological models, and discharge observations from various macroscale river basins. It was found that the seasonal and spatial patterns of the LPJ-simulated average values correspond well both with the measurements and the results from the stand-alone hy- drological models. However, a general underestimation of runoff occurs, which may be attributable to the low input dynamics of precipitation (equal distribution within a month), to the simulated vegetation pattern (potential vegetation without anthro- pogenic influence), and to some generalizations of the hydrological components in LPJ. Future research will focus on a better representation of the temporal variability of climate forcing, improved description of hydrological processes, and on the consider- ation of anthropogenic land use.

Hybrid Multiscale Simulation of Hydrologic and Biogeochemical Processes in the River-Groundwater Interaction Zone

NASA Astrophysics Data System (ADS)

Yang, X.; Scheibe, T. D.; Chen, X.; Hammond, G. E.; Song, X.

2015-12-01

The zone in which river water and groundwater mix plays an important role in natural ecosystems as it regulates the mixing of nutrients that control biogeochemical transformations. Subsurface heterogeneity leads to local hotspots of microbial activity that are important to system function yet difficult to resolve computationally. To address this challenge, we are testing a hybrid multiscale approach that couples models at two distinct scales, based on field research at the U. S. Department of Energy's Hanford Site. The region of interest is a 400 x 400 x 20 m macroscale domain that intersects the aquifer and the river and contains a contaminant plume. However, biogeochemical activity is high in a thin zone (mud layer, <1 m thick) immediately adjacent to the river. This microscale domain is highly heterogeneous and requires fine spatial resolution to adequately represent the effects of local mixing on reactions. It is not computationally feasible to resolve the full macroscale domain at the fine resolution needed in the mud layer, and the reaction network needed in the mud layer is much more complex than that needed in the rest of the macroscale domain. Hence, a hybrid multiscale approach is used to efficiently and accurately predict flow and reactive transport at both scales. In our simulations, models at both scales are simulated using the PFLOTRAN code. Multiple microscale simulations in dynamically defined sub-domains (fine resolution, complex reaction network) are executed and coupled with a macroscale simulation over the entire domain (coarse resolution, simpler reaction network). The objectives of the research include: 1) comparing accuracy and computing cost of the hybrid multiscale simulation with a single-scale simulation; 2) identifying hot spots of microbial activity; and 3) defining macroscopic quantities such as fluxes, residence times and effective reaction rates.

Hydrologic response of Pacific Northwest river to climate change

NASA Astrophysics Data System (ADS)

Su, F.; Cuo, L.; Wu, H.; Mantua, N.; Lettenmaier, D. P.

2009-12-01

The climate of the Pacific Northwest (PNW - which we define as the Columbia River basin and watersheds draining to the Oregon and Washington coasts) is expected to warm by approximately 0.3°C per decade in the next 100 years based on the IPCC the Fourth Assessment Report (AR4) results. PNW hydrology is particularly sensitive to a warming climate because of the dominant role of snowmelt in seasonal streamflow. Timing shifts in seasonality of flows, peak discharge, and base flows will impact water resource management, regional electrical energy production, and freshwater ecosystems. In this work we update previous studies of implications of climate change on PNW hydrology using a macroscale hydrology model driven by simulations of temperature and precipitation downscaled from runs of 20 General Circulation Models (GCMs) under two emissions scenarios (lower B1 and mid-high A1B) in the 21st century. The hydrology model is implemented at 1/16th degree spatial resolution over the entire PNW. A (statistical) bias-correction and spatial disaggregation downscaling approach is used for translating the transient monthly climate model output into continuous daily forcings for the hydrologic analysis. We evaluate projected changes in snow water equivalent, seasonal streamflow, and frequency of peak low flows over a set of case study watersheds in the region. We also compare these hydrologic projections with previous analysis based on delta downscaling method over the PNW. This research is part of a project investigating climate change impacts on the future of wild Pacific salmon, and is a pilot effort to investigate the hydrologic sensitivity of salmon bearing watersheds around the entire North Pacific Rim.

The Freshwater Landscape: Lake, Wetland, and Stream Abundance and Connectivity at Macroscales

EPA Science Inventory

It is becoming increasingly recognized that inland waterbodies and their surface hydrologic connections are active components in the landscape, influencing multiple ecological processes that can propagate to broad-scale phenomena such as regional nutrient and carbon cycles and me...

Global evaluation of runoff from 10 state-of-the-art hydrological models

NASA Astrophysics Data System (ADS)

Beck, Hylke E.; van Dijk, Albert I. J. M.; de Roo, Ad; Dutra, Emanuel; Fink, Gabriel; Orth, Rene; Schellekens, Jaap

2017-06-01

Observed streamflow data from 966 medium sized catchments (1000-5000 km2) around the globe were used to comprehensively evaluate the daily runoff estimates (1979-2012) of six global hydrological models (GHMs) and four land surface models (LSMs) produced as part of tier-1 of the eartH2Observe project. The models were all driven by the WATCH Forcing Data ERA-Interim (WFDEI) meteorological dataset, but used different datasets for non-meteorologic inputs and were run at various spatial and temporal resolutions, although all data were re-sampled to a common 0. 5° spatial and daily temporal resolution. For the evaluation, we used a broad range of performance metrics related to important aspects of the hydrograph. We found pronounced inter-model performance differences, underscoring the importance of hydrological model uncertainty in addition to climate input uncertainty, for example in studies assessing the hydrological impacts of climate change. The uncalibrated GHMs were found to perform, on average, better than the uncalibrated LSMs in snow-dominated regions, while the ensemble mean was found to perform only slightly worse than the best (calibrated) model. The inclusion of less-accurate models did not appreciably degrade the ensemble performance. Overall, we argue that more effort should be devoted on calibrating and regionalizing the parameters of macro-scale models. We further found that, despite adjustments using gauge observations, the WFDEI precipitation data still contain substantial biases that propagate into the simulated runoff. The early bias in the spring snowmelt peak exhibited by most models is probably primarily due to the widespread precipitation underestimation at high northern latitudes.

Hydrological variability in the Fraser River Basin during the 20th century: A sensitivity study with the VIC model

NASA Astrophysics Data System (ADS)

Kang, D.; Gao, H.; Dery, S. J.

2012-12-01

The Variable Infiltration Capacity (VIC) model, a macroscale surface hydrology model, was applied to the Fraser River Basin (FRB) of British Columbia, Canada. Previous modeling studies have demonstrated that the FRB is a snow-dominated system but with climate change may evolve to a pluvial regime. The ultimate goal of this model application is to evaluate the changing contribution of snowmelt to streamflow in the FRB both spatially and temporally. To this end, the National Centers for Environmental Prediction (NCEP) reanalysis data combined with meteorological observations over 1953 to 2006 are used to drive the model at a resolution of 0.25°. Model simulations are first validated with daily discharge observations from the Water Survey of Canada (WSC). In addition, the snow water equivalent (SWE) results from VIC are compared with snow pillow observations from the B.C. Ministry of Environment. Then peak SWE values simulated each winter are compared with the annual runoff data to quantify the changing contribution of snowmelt to the hydrology of the FRB. With perturbed model forcings such as precipitation and air temperature, how streamflow and surface energy-mass balance are changed is evaluated. Finally, interactions between the land surface and ambient atmosphere are evaluated by analyzing VIC results such as evaporation, soil moisture, snowmelt and sensible-latent heat flux with corresponding meteorological forcings, i.e. precipitation and air temperature.

Relationship between water quality and macro-scale parameters (land use, erosion, geology, and population density) in the Siminehrood River Basin.

PubMed

Bostanmaneshrad, Farshid; Partani, Sadegh; Noori, Roohollah; Nachtnebel, Hans-Peter; Berndtsson, Ronny; Adamowski, Jan Franklin

2018-10-15

To date, few studies have investigated the simultaneous effects of macro-scale parameters (MSPs) such as land use, population density, geology, and erosion layers on micro-scale water quality variables (MSWQVs). This research focused on an evaluation of the relationship between MSPs and MSWQVs in the Siminehrood River Basin, Iran. In addition, we investigated the importance of water particle travel time (hydrological distance) on this relationship. The MSWQVs included 13 physicochemical and biochemical parameters observed at 15 stations during three seasons. Primary screening was performed by utilizing three multivariate statistical analyses (Pearson's correlation, cluster and discriminant analyses) in seven series of observed data. These series included three separate seasonal data, three two-season data, and aggregated three-season data for investigation of relationships between MSPs and MSWQVs. Coupled data (pairs of MSWQVs and MSPs) repeated in at least two out of three statistical analyses were selected for final screening. The primary screening results demonstrated significant relationships between land use and phosphorus, total solids and turbidity, erosion levels and electrical conductivity, and erosion and total solids. Furthermore, water particle travel time effects were considered through three geographical pattern definitions of distance for each MSP by using two weighting methods. To find effective MSP factors on MSWQVs, a multivariate linear regression analysis was employed. Then, preliminary equations that estimated MSWQVs were developed. The preliminary equations were modified to adaptive equations to obtain the final models. The final models indicated that a new metric, referred to as hydrological distance, provided better MSWQV estimation and water quality prediction compared to the National Sanitation Foundation Water Quality Index. Crown Copyright © 2018. Published by Elsevier B.V. All rights reserved.

What did the Romans ever do for us? Putting humans in global land models

NASA Astrophysics Data System (ADS)

Bierkens, M. F.; Wada, Y.; Dermody, B.; Van Beek, L. P.

2016-12-01

During the late 1980s and early 1990s, awareness of the shortage of global water resources lead to the first detailed global water resources assessments using regional statistics of water use and observations of meteorological and hydrological variables. Shortly thereafter, the first macroscale hydrological models (MHM) appeared. In these models, blue water (i.e., surface water and renewable groundwater) availability was calculated by accumulating runoff over a stream network and comparing it with population densities or with estimated water demand for agriculture, industry and households. In this talk we review the evolution of human impact modelling in global land models with a focus on global water resources, touching upon developments of the last 15 years: i.e. calculating human water scarcity; estimating groundwater depletion; adding dams and reservoirs; fully integrating water use (abstraction, application, consumption, return flow) in the hydrology; simulating the effects of land use change. We identify four major challenges that hamper the further development of integrated water resources modelling and thus prohibit realistic projections of the future terrestrial water cycle in the Anthropocene. These are: 1) including the ability to model infrastructural changes and measures; 2) projecting future water demand and water use and associated measures; 3) including virtual water trade; 4) including land use change and landscape change. While all these challenges will likely benefit from hydro-economics and the newly developing field of socio-hydrology, we also show that especially for challenges 3 and 4 lessons can be drawn from the (pre)historic past. To make this point we provide two case studies: one modelling the virtual water trade in the Roman Empire and one modelling human-landscape interaction in prehistoric Calabria (Italy).

Dynamical nexus of water supply, hydropower and environment based on the modeling of multiple socio-natural processes: from socio-hydrological perspective

NASA Astrophysics Data System (ADS)

Liu, D.; Wei, X.; Li, H. Y.; Lin, M.; Tian, F.; Huang, Q.

2017-12-01

In the socio-hydrological system, the ecological functions and environmental services, which are chosen to maintain, are determined by the preference of the society, which is making the trade-off among the values of riparian vegetation, fish, river landscape, water supply, hydropower, navigation and so on. As the society develops, the preference of the value will change and the ecological functions and environmental services which are chosen to maintain will change. The aim of the study is to focus on revealing the feedback relationship of water supply, hydropower and environment and the dynamical feedback mechanism at macro-scale, and to establish socio-hydrological evolution model of the watershed based on the modeling of multiple socio-natural processes. The study will aim at the Han River in China, analyze the impact of the water supply and hydropower on the ecology, hydrology and other environment elements, and study the effect on the water supply and hydropower to ensure the ecological and environmental water of the different level. Water supply and ecology are usually competitive. In some reservoirs, hydropower and ecology are synergic relationship while they are competitive in some reservoirs. The study will analyze the multiple mechanisms to implement the dynamical feedbacks of environment to hydropower, set up the quantitative relationship description of the feedback mechanisms, recognize the dominant processes in the feedback relationships of hydropower and environment and then analyze the positive and negative feedbacks in the feedback networks. The socio-hydrological evolution model at the watershed scale will be built and applied to simulate the long-term evolution processes of the watershed of the current situation. Dynamical nexus of water supply, hydropower and environment will be investigated.

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

Siranosian, Antranik Antonio; Schembri, Philip Edward; Luscher, Darby Jon

The Los Alamos National Laboratory's Weapon Systems Engineering division's Advanced Engineering Analysis group employs material constitutive models of composites for use in simulations of components and assemblies of interest. Experimental characterization, modeling and prediction of the macro-scale (i.e. continuum) behaviors of these composite materials is generally difficult because they exhibit nonlinear behaviors on the meso- (e.g. micro-) and macro-scales. Furthermore, it can be difficult to measure and model the mechanical responses of the individual constituents and constituent interactions in the composites of interest. Current efforts to model such composite materials rely on semi-empirical models in which meso-scale properties are inferredmore » from continuum level testing and modeling. The proposed approach involves removing the difficulties of interrogating and characterizing micro-scale behaviors by scaling-up the problem to work with macro-scale composites, with the intention of developing testing and modeling capabilities that will be applicable to the mesoscale. This approach assumes that the physical mechanisms governing the responses of the composites on the meso-scale are reproducible on the macro-scale. Working on the macro-scale simplifies the quantification of composite constituents and constituent interactions so that efforts can be focused on developing material models and the testing techniques needed for calibration and validation. Other benefits to working with macro-scale composites include the ability to engineer and manufacture—potentially using additive manufacturing techniques—composites that will support the application of advanced measurement techniques such as digital volume correlation and three-dimensional computed tomography imaging, which would aid in observing and quantifying complex behaviors that are exhibited in the macro-scale composites of interest. Ultimately, the goal of this new approach is to develop a meso-scale composite modeling framework, applicable to many composite materials, and the corresponding macroscale testing and test data interrogation techniques to support model calibration.« less

Five-minute, 1/2°, and 1° data sets of continental watersheds and river networks for use in regional and global hydrologic and climate system modeling studies

NASA Astrophysics Data System (ADS)

Graham, S. T.; Famiglietti, J. S.; Maidment, D. R.

1999-02-01

A major shortcoming of the land surface component in climate models is the absence of a river transport algorithm. This issue becomes particularly important in fully coupled climate system models (CSMs), where river transport is required to close and realistically represent the global water cycle. The development of a river transport algorithm requires knowledge of watersheds and river networks at a scale that is appropriate for use in CSMs. These data must be derived largely from global digital topographic information. The purpose of this paper is to describe a new data set of watersheds and river networks, which is derived primarily from the TerrainBase 5' Global DTM (digital terrain model) and the CIA World Data Bank II. These data serve as a base map for routing continental runoff to the appropriate coast and therefore into the appropriate ocean or inland sea. Using this data set, the runoff produced in any grid cell, when coupled with a routing algorithm, can easily be transported to the appropriate water body and distributed across that water body as desired. The data set includes watershed and flow direction information, as well as supporting hydrologic data at 5', 1/2°, and 1° resolutions globally. It will be useful in fully coupled land-ocean-atmosphere models, in terrestrial ecosystem models, or in stand-alone macroscale hydrologic-modeling studies.

Multi-RCM ensemble downscaling of global seasonal forecasts (MRED)

NASA Astrophysics Data System (ADS)

Arritt, R. W.

2008-12-01

The Multi-RCM Ensemble Downscaling (MRED) project was recently initiated to address the question, Can regional climate models provide additional useful information from global seasonal forecasts? MRED will use a suite of regional climate models to downscale seasonal forecasts produced by the new National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS) seasonal forecast system and the NASA GEOS5 system. The initial focus will be on wintertime forecasts in order to evaluate topographic forcing, snowmelt, and the potential usefulness of higher resolution, especially for near-surface fields influenced by high resolution orography. Each regional model will cover the conterminous US (CONUS) at approximately 32 km resolution, and will perform an ensemble of 15 runs for each year 1982-2003 for the forecast period 1 December - 30 April. MRED will compare individual regional and global forecasts as well as ensemble mean precipitation and temperature forecasts, which are currently being used to drive macroscale land surface models (LSMs), as well as wind, humidity, radiation, turbulent heat fluxes, which are important for more advanced coupled macro-scale hydrologic models. Metrics of ensemble spread will also be evaluated. Extensive analysis will be performed to link improvements in downscaled forecast skill to regional forcings and physical mechanisms. Our overarching goal is to determine what additional skill can be provided by a community ensemble of high resolution regional models, which we believe will eventually define a strategy for more skillful and useful regional seasonal climate forecasts.

Glaciers and small ice caps in the macro-scale hydrological cycle - an assessment of present conditions and future changes

NASA Astrophysics Data System (ADS)

Lammers, Richard; Hock, Regine; Prusevich, Alexander; Bliss, Andrew; Radic, Valentina; Glidden, Stanley; Grogan, Danielle; Frolking, Steve

2014-05-01

Glacier and small ice cap melt water contributions to the global hydrologic cycle are an important component of human water supply and for sea level rise. This melt water is used in many arid and semi-arid parts of the world for direct human consumption as well as indirect consumption by irrigation for crops, serving as frozen reservoirs of water that supplement runoff during warm and dry periods of summer when it is needed the most. Additionally, this melt water reaching the oceans represents a direct input to sea level rise and therefore accurate estimates of this contribution have profound economic and geopolitical implications. It has been demonstrated that, on the scale of glacierized river catchments, land surface hydrological models can successfully simulate glacier contribution to streamflow. However, at global scales, the implementation of glacier melt in hydrological models has been rudimentary or non-existent. In this study, a global glacier mass balance model is coupled with the University of New Hampshire Water Balance/Transport Model (WBM) to assess recent and projected future glacier contributions to the hydrological cycle over the global land surface (excluding the ice sheets of Greenland and Antarctica). For instance, results of WBM simulations indicate that seasonal glacier melt water in many arid climate watersheds comprises 40 % or more of their discharge. Implicitly coupled glacier and WBM models compute monthly glacier mass changes and resulting runoff at the glacier terminus for each individual glacier from the globally complete Randolph Glacier Inventory including over 200 000 glaciers. The time series of glacier runoff is aggregated over each hydrological modeling unit and delivered to the hydrological model for routing downstream and mixing with non-glacial contribution of runoff to each drainage basin outlet. WBM tracks and uses glacial and non-glacial components of the in-stream water for filling reservoirs, transfers of water between drainage basins (inter-basin hydrological transfers), and irrigation along the global system of rivers with net discharge to the ocean. Climate scenarios from global climate models prepared for IPCC AR5 are used to explore an expected range of possible future glacier outflow variability to estimate the impacts on human use of these valuable waters and their poorly understood net contribution to sea level change.

Comparing SMAP to Macro-scale and Hyper-resolution Land Surface Models over Continental U. S.

NASA Astrophysics Data System (ADS)

Pan, Ming; Cai, Xitian; Chaney, Nathaniel; Wood, Eric

2016-04-01

SMAP sensors collect moisture information in top soil at the spatial resolution of ~40 km (radiometer) and ~1 to 3 km (radar, before its failure in July 2015). Such information is extremely valuable for understanding various terrestrial hydrologic processes and their implications on human life. At the same time, soil moisture is a joint consequence of numerous physical processes (precipitation, temperature, radiation, topography, crop/vegetation dynamics, soil properties, etc.) that happen at a wide range of scales from tens of kilometers down to tens of meters. Therefore, a full and thorough analysis/exploration of SMAP data products calls for investigations at multiple spatial scales - from regional, to catchment, and to field scales. Here we first compare the SMAP retrievals to the Variable Infiltration Capacity (VIC) macro-scale land surface model simulations over the continental U. S. region at 3 km resolution. The forcing inputs to the model are merged/downscaled from a suite of best available data products including the NLDAS-2 forcing, Stage IV and Stage II precipitation, GOES Surface and Insolation Products, and fine elevation data. The near real time VIC simulation is intended to provide a source of large scale comparisons at the active sensor resolution. Beyond the VIC model scale, we perform comparisons at 30 m resolution against the recently developed HydroBloks hyper-resolution land surface model over several densely gauged USDA experimental watersheds. Comparisons are also made against in-situ point-scale observations from various SMAP Cal/Val and field campaign sites.

Comparing Macroscale and Microscale Simulations of Porous Battery Electrodes

DOE PAGES

Higa, Kenneth; Wu, Shao-Ling; Parkinson, Dilworth Y.; ...

2017-06-22

This article describes a vertically-integrated exploration of NMC electrode rate limitations, combining experiments with corresponding macroscale (macro-homogeneous) and microscale models. Parameters common to both models were obtained from experiments or based on published results. Positive electrode tortuosity was the sole fitting parameter used in the macroscale model, while the microscale model used no fitting parameters, instead relying on microstructural domains generated from X-ray microtomography of pristine electrode material held under compression while immersed in electrolyte solution (additionally providing novel observations of electrode wetting). Macroscale simulations showed that the capacity decrease observed at higher rates resulted primarily from solution-phase diffusion resistance.more » This ability to provide such qualitative insights at low computational costs is a strength of macroscale models, made possible by neglecting electrode spatial details. To explore the consequences of such simplification, the corresponding, computationally-expensive microscale model was constructed. This was found to have limitations preventing quantitatively accurate predictions, for reasons that are discussed in the hope of guiding future work. Nevertheless, the microscale simulation results complement those of the macroscale model by providing a reality-check based on microstructural information; in particular, this novel comparison of the two approaches suggests a reexamination of salt diffusivity measurements.« less

A Hydrological Modeling Framework for Flood Risk Assessment for Japan

NASA Astrophysics Data System (ADS)

Ashouri, H.; Chinnayakanahalli, K.; Chowdhary, H.; Sen Gupta, A.

2016-12-01

Flooding has been the most frequent natural disaster that claims lives and imposes significant economic losses to human societies worldwide. Japan, with an annual rainfall of up to approximately 4000 mm is extremely vulnerable to flooding. The focus of this research is to develop a macroscale hydrologic model for simulating flooding toward an improved understanding and assessment of flood risk across Japan. The framework employs a conceptual hydrological model, known as the Probability Distributed Model (PDM), as well as the Muskingum-Cunge flood routing procedure for simulating streamflow. In addition, a Temperature-Index model is incorporated to account for snowmelt and its contribution to streamflow. For an efficient calibration of the model, in terms of computational timing and convergence of the parameters, a set of A Priori parameters is obtained based on the relationships between the model parameters and the physical properties of watersheds. In this regard, we have implemented a particle tracking algorithm and a statistical model which use high resolution Digital Terrain Models to estimate different time related parameters of the model such as time to peak of the unit hydrograph. In addition, global soil moisture and depth data are used to generate A Priori estimation of maximum soil moisture capacity, an important parameter of the PDM model. Once the model is calibrated, its performance is examined during the Typhoon Nabi which struck Japan in September 2005 and caused severe flooding throughout the country. The model is also validated for the extreme precipitation event in 2012 which affected Kyushu. In both cases, quantitative measures show that simulated streamflow depicts good agreement with gauge-based observations. The model is employed to simulate thousands of possible flood events for the entire Japan which makes a basis for a comprehensive flood risk assessment and loss estimation for the flood insurance industry.

Evaluation of the land surface water budget in NCEP/NCAR and NCEP/DOE reanalyses using an off-line hydrologic model

NASA Astrophysics Data System (ADS)

Maurer, Edwin P.; O'Donnell, Greg M.; Lettenmaier, Dennis P.; Roads, John O.

2001-08-01

The ability of the National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis (NRA1) and the follow-up NCEP/Department of Energy (DOE) reanalysis (NRA2), to reproduce the hydrologic budgets over the Mississippi River basin is evaluated using a macroscale hydrology model. This diagnosis is aided by a relatively unconstrained global climate simulation using the NCEP global spectral model, and a more highly constrained regional climate simulation using the NCEP regional spectral model, both employing the same land surface parameterization (LSP) as the reanalyses. The hydrology model is the variable infiltration capacity (VIC) model, which is forced by gridded observed precipitation and temperature. It reproduces observed streamflow, and by closure is constrained to balance other terms in the surface water and energy budgets. The VIC-simulated surface fluxes therefore provide a benchmark for evaluating the predictions from the reanalyses and the climate models. The comparisons, conducted for the 10-year period 1988-1997, show the well-known overestimation of summer precipitation in the southeastern Mississippi River basin, a consistent overestimation of evapotranspiration, and an underprediction of snow in NRA1. These biases are generally lower in NRA2, though a large overprediction of snow water equivalent exists. NRA1 is subject to errors in the surface water budget due to nudging of modeled soil moisture to an assumed climatology. The nudging and precipitation bias alone do not explain the consistent overprediction of evapotranspiration throughout the basin. Another source of error is the gravitational drainage term in the NCEP LSP, which produces the majority of the model's reported runoff. This may contribute to an overprediction of persistence of surface water anomalies in much of the basin. Residual evapotranspiration inferred from an atmospheric balance of NRA1, which is more directly related to observed atmospheric variables, matches the VIC prediction much more closely than the coupled models. However, the persistence of the residual evapotranspiration is much less than is predicted by the hydrological model or the climate models.

Landslide Hazard from Coupled Inherent and Dynamic Probabilities

NASA Astrophysics Data System (ADS)

Strauch, R. L.; Istanbulluoglu, E.; Nudurupati, S. S.

2015-12-01

Landslide hazard research has typically been conducted independently from hydroclimate research. We sought to unify these two lines of research to provide regional scale landslide hazard information for risk assessments and resource management decision-making. Our approach couples an empirical inherent landslide probability, based on a frequency ratio analysis, with a numerical dynamic probability, generated by combining subsurface water recharge and surface runoff from the Variable Infiltration Capacity (VIC) macro-scale land surface hydrologic model with a finer resolution probabilistic slope stability model. Landslide hazard mapping is advanced by combining static and dynamic models of stability into a probabilistic measure of geohazard prediction in both space and time. This work will aid resource management decision-making in current and future landscape and climatic conditions. The approach is applied as a case study in North Cascade National Park Complex in northern Washington State.

Uncertainties in Hydrologic and Climate Change Impact Analysis in Major Watersheds in British Columbia, Canada

NASA Astrophysics Data System (ADS)

Bennett, K. E.; Schnorbus, M.; Werner, A. T.; Music, B.; Caya, D.; Rodenhuis, D. R.

2009-12-01

Uncertainties in the projections of future hydrologic change can be assessed using a suite of tools, thereby allowing researchers to focus on improvement to identifiable sources of uncertainty. A pareto set of optimal hydrologic parameterizations was run for three BC watersheds (Fraser, Peace and Columbia) for a range of downscaled Global Climate Model (GCM) emission scenarios to illustrate the uncertainty in hydrologic response to climate change. Results show varying responses of hydrologic regimes across geographic landscapes. Uncertainties in streamflow and water balance (runoff, evapo-transpiration, snow water equivalent, soil moisture) were analysed by forcing the Variable Infiltration Capacity (VIC) hydrologic model, run under twenty-five optimal parameter solution sets using six Bias-Corrected Statistically Downscaled (BCSD) GCM emission scenario projections for the 2050s and the 2080s. Projected changes by the 2050s include increased winter flows, increases and decreases in freshet magnitude depending on the scenario, and decreases in summer flows persisting until September. Winter runoff had the greatest range between GCM emission scenarios, while the hydrologic parameters within individual GCM emission scenarios had a winter runoff range an order of magnitude smaller. Evapo-transpiration, snow water equivalent and soil moisture exhibited a spread of ~10% or less. Streamflow changes by the 2080s lie outside the natural range of historic variability over the winter and spring. Results indicate that the changes projected between GCM emission scenarios are greater than the differences between the hydrologic model parameterizations. An alternate tool, the Canadian Regional Climate Model (CRCM) has been set up for these watersheds and various runs have been analysed to determine the range and variability present and to examine these results in comparison to the hydrologic model projections. The CRCM range and variability is an improvement over the Canadian GCM and thus requires less bias correction. However, without downscaling the CRCM results are still coarser than what is required to drive macroscale hydrologic models, such as VIC. Applying these tools has illustrated the importance of focusing on improved downscaling efforts, including downscaling CRCM results rather than CGCM data. Tools for decision-making in the face of uncertainty are emerging as a priority for the climate change impacts community, and there is a need to focus on incorporating uncertainty information along with the projection of impacts. Assessing uncertainty across a range of regimes and geographic regions can assist to identify the main sources of uncertainty and allow researchers to focus on improving those sources using more robust methodological approaches and tools.

Model study of the impacts of future climate change on the hydrology of Ganges-Brahmaputra-Meghna (GBM) basin

NASA Astrophysics Data System (ADS)

Masood, M.; Yeh, P. J.-F.; Hanasaki, N.; Takeuchi, K.

2014-06-01

The intensity, duration, and geographic extent of floods in Bangladesh mostly depend on the combined influences of three river systems, Ganges, Brahmaputra and Meghna (GBM). In addition, climate change is likely to have significant effects on the hydrology and water resources of the GBM basins and might ultimately lead to more serious floods in Bangladesh. However, the assessment of climate change impacts on basin-scale hydrology by using well-constrained hydrologic modelling has rarely been conducted for GBM basins due to the lack of data for model calibration and validation. In this study, a macro-scale hydrologic model H08 has been applied regionally over the basin at a relatively fine grid resolution (10 km) by integrating the fine-resolution (~0.5 km) DEM data for accurate river networks delineation. The model has been calibrated via analyzing model parameter sensitivity and validated based on a long-term observed daily streamflow data. The impact of climate change on not only the runoff, but also the basin-scale hydrology including evapotranspiration, soil moisture and net radiation have been assessed in this study through three time-slice experiments; present-day (1979-2003), near-future (2015-2039) and far-future (2075-2099) periods. Results shows that, by the end of 21st century (a) the entire GBM basin is projected to be warmed by ~3°C (b) the changes of mean precipitation are projected to be +14.0, +10.4, and +15.2%, and the changes of mean runoff to be +14, +15, and +18% in the Brahmaputra, Ganges and Meghna basin respectively (c) evapotranspiration is predicted to increase significantly for the entire GBM basins (Brahmaputra: +14.4%, Ganges: +9.4%, Meghna: +8.8%) due to increased net radiation (Brahmaputra: +6%, Ganges: +5.9%, Meghna: +3.3%) as well as warmer air temperature. Changes of hydrologic variables will be larger in dry season (November-April) than that in wet season (May-October). Amongst three basins, Meghna shows the largest hydrological response which indicates higher possibility of flood occurrence in this basin. The uncertainty due to the specification of key model parameters in predicting hydrologic quantities, has also been analysed explicitly in this study and found that the uncertainty in estimation of runoff, evapotranspiration and net radiation is relatively less. However, the uncertainty in estimation of soil moisture is quite large (coefficient of variation ranges from 11 to 33% for three basins). It is significant in land use management, agriculture in particular and highlights the necessity of physical observation of soil moisture.

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

DOE PAGES

Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.; ...

2017-09-14

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less

Towards improved parameterization of a macroscale hydrologic model in a discontinuous permafrost boreal forest ecosystem

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

Endalamaw, Abraham; Bolton, W. Robert; Young-Robertson, Jessica M.

Modeling hydrological processes in the Alaskan sub-arctic is challenging because of the extreme spatial heterogeneity in soil properties and vegetation communities. Nevertheless, modeling and predicting hydrological processes is critical in this region due to its vulnerability to the effects of climate change. Coarse-spatial-resolution datasets used in land surface modeling pose a new challenge in simulating the spatially distributed and basin-integrated processes since these datasets do not adequately represent the small-scale hydrological, thermal, and ecological heterogeneity. The goal of this study is to improve the prediction capacity of mesoscale to large-scale hydrological models by introducing a small-scale parameterization scheme, which bettermore » represents the spatial heterogeneity of soil properties and vegetation cover in the Alaskan sub-arctic. The small-scale parameterization schemes are derived from observations and a sub-grid parameterization method in the two contrasting sub-basins of the Caribou Poker Creek Research Watershed (CPCRW) in Interior Alaska: one nearly permafrost-free (LowP) sub-basin and one permafrost-dominated (HighP) sub-basin. The sub-grid parameterization method used in the small-scale parameterization scheme is derived from the watershed topography. We found that observed soil thermal and hydraulic properties – including the distribution of permafrost and vegetation cover heterogeneity – are better represented in the sub-grid parameterization method than the coarse-resolution datasets. Parameters derived from the coarse-resolution datasets and from the sub-grid parameterization method are implemented into the variable infiltration capacity (VIC) mesoscale hydrological model to simulate runoff, evapotranspiration (ET), and soil moisture in the two sub-basins of the CPCRW. Simulated hydrographs based on the small-scale parameterization capture most of the peak and low flows, with similar accuracy in both sub-basins, compared to simulated hydrographs based on the coarse-resolution datasets. On average, the small-scale parameterization scheme improves the total runoff simulation by up to 50 % in the LowP sub-basin and by up to 10 % in the HighP sub-basin from the large-scale parameterization. This study shows that the proposed sub-grid parameterization method can be used to improve the performance of mesoscale hydrological models in the Alaskan sub-arctic watersheds.« less

Direct numerical simulations in solid mechanics for quantifying the macroscale effects of microstructure and material model-form error

DOE PAGES

Bishop, Joseph E.; Emery, John M.; Battaile, Corbett C.; ...

2016-03-16

Two fundamental approximations in macroscale solid-mechanics modeling are (1) the assumption of scale separation in homogenization theory and (2) the use of a macroscopic plasticity material model that represents, in a mean sense, the multitude of inelastic processes occurring at the microscale. With the goal of quantifying the errors induced by these approximations on engineering quantities of interest, we perform a set of direct numerical simulations (DNS) in which polycrystalline microstructures are embedded throughout a macroscale structure. The largest simulations model over 50,000 grains. The microstructure is idealized using a randomly close-packed Voronoi tessellation in which each polyhedral Voronoi cellmore » represents a grain. An face centered cubic crystal-plasticity model is used to model the mechanical response of each grain. The overall grain structure is equiaxed, and each grain is randomly oriented with no overall texture. The detailed results from the DNS simulations are compared to results obtained from conventional macroscale simulations that use homogeneous isotropic plasticity models. The macroscale plasticity models are calibrated using a representative volume element of the idealized microstructure. Furthermore, we envision that DNS modeling will be used to gain new insights into the mechanics of material deformation and failure.« less

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.

Stochastic Models of Macroscale Quantities for the Prediction of the REV Scale for Multiphase Flow through Porous Media

NASA Astrophysics Data System (ADS)

Talbot, C.; McClure, J. E.; Armstrong, R. T.; Mostaghimi, P.; Hu, Y.; Miller, C. T.

2017-12-01

Microscale experimental and computational methods can be used to evaluate fundamental microscale mechanisms and deduce macroscale constitutive relationships and parameter values. The link between the microscale and the macroscale is especially demanding, because technical issues arise regarding the necessary scale of the system needed for a meaningful set of macroscale measures to be insensitive to the size of the system, which is known as a representative elementary volume (REV). While the REV scale is routinely determined for single-phase flow in porous media, no systematic study of the scale of a REV for the comprehensive set of macroscale measures considered here has been reported in the literature. A comprehensive set of measures of the macroscale state is developed. We further develop and apply methods to predict the REV scale and quantify the uncertainty of the estimate for this set of macroscale quantities. We model the system state in terms of standard errors of macroscale quantities as a multivariate Gaussian process dependent on the size of the domain simulated. We determine predictive distributions of function values and a posterior distributions of weights using standard kernels, as well as a kernel constructed using relationships between physical quantities. For each kernel, we discuss the decay of the mean and covariance with increasing domain size, and use cross-validation to facilitate model selection. The procedure yields a model of the domain size needed to achieve a REV with quantifiable uncertainty. We present results in the context of multiphase fluid flow through a highly resolved realization of sandstone imaged using micro-CT. A 1440x1440x4320 section of the full 2520x2520x5280 imaged medium is simulated using the lattice-Boltzmann method. We compare the fidelity of the predictive model with results obtained by an analogous approach using polynomial regression.

Virtual mission stage I: Implications of a spaceborne surface water mission

NASA Astrophysics Data System (ADS)

Clark, E. A.; Alsdorf, D. E.; Bates, P.; Wilson, M. D.; Lettenmaier, D. P.

2004-12-01

The interannual and interseasonal variability of the land surface water cycle depend on the distribution of surface water in lakes, wetlands, reservoirs, and river systems; however, measurements of hydrologic variables are sparsely distributed, even in industrialized nations. Moreover, the spatial extent and storage variations of lakes, reservoirs, and wetlands are poorly known. We are developing a virtual mission to demonstrate the feasibility of observing surface water extent and variations from a spaceborne platform. In the first stage of the virtual mission, on which we report here, surface water area and fluxes are emulated using simulation modeling over three continental scale river basins, including the Ohio River, the Amazon River and an Arctic river. The Variable Infiltration Capacity (VIC) macroscale hydrologic model is used to simulate evapotranspiration, soil moisture, snow accumulation and ablation, and runoff and streamflow over each basin at one-eighth degree resolution. The runoff from this model is routed using a linear transfer model to provide input to a much more detailed flow hydraulics model. The flow hydraulics model then routes runoff through various channel and floodplain morphologies at a 250 m spatial and 20 second temporal resolution over a 100 km by 500 km domain. This information is used to evaluate trade-offs between spatial and temporal resolutions of a hypothetical high resolution spaceborne altimeter by synthetically sampling the resultant model-predicted water surface elevations.

On Multiscale Modeling: Preserving Energy Dissipation Across the Scales with Consistent Handshaking Methods

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Bednarcyk, Brett A.; Arnold, Steven M.; Waas, Anthony M.

2013-01-01

A mesh objective crack band model was implemented within the generalized method of cells micromechanics theory. This model was linked to a macroscale finite element model to predict post-peak strain softening in composite materials. Although a mesh objective theory was implemented at the microscale, it does not preclude pathological mesh dependence at the macroscale. To ensure mesh objectivity at both scales, the energy density and the energy release rate must be preserved identically across the two scales. This requires a consistent characteristic length or localization limiter. The effects of scaling (or not scaling) the dimensions of the microscale repeating unit cell (RUC), according to the macroscale element size, in a multiscale analysis was investigated using two examples. Additionally, the ramifications of the macroscale element shape, compared to the RUC, was studied.

Scaling water and energy fluxes in climate systems - Three land-atmospheric modeling experiments

NASA Technical Reports Server (NTRS)

Wood, Eric F.; Lakshmi, Venkataraman

1993-01-01

Three numerical experiments that investigate the scaling of land-surface processes - either of the inputs or parameters - are reported, and the aggregated processes are compared to the spatially variable case. The first is the aggregation of the hydrologic response in a catchment due to rainfall during a storm event and due to evaporative demands during interstorm periods. The second is the spatial and temporal aggregation of latent heat fluxes, as calculated from SiB. The third is the aggregation of remotely sensed land vegetation and latent and sensible heat fluxes using TM data from the FIFE experiment of 1987 in Kansas. In all three experiments it was found that the surface fluxes and land characteristics can be scaled, and that macroscale models based on effective parameters are sufficient to account for the small-scale heterogeneities investigated.

Evaluating historical climate and hydrologic trends in the Central Appalachian region of the United States

NASA Astrophysics Data System (ADS)

Gaertner, B. A.; Zegre, N.

2015-12-01

Climate change is surfacing as one of the most important environmental and social issues of the 21st century. Over the last 100 years, observations show increasing trends in global temperatures and intensity and frequency of precipitation events such as flooding, drought, and extreme storms. Global circulation models (GCM) show similar trends for historic and future climate indicators, albeit with geographic and topographic variability at regional and local scale. In order to assess the utility of GCM projections for hydrologic modeling, it is important to quantify how robust GCM outputs are compared to robust historical observations at finer spatial scales. Previous research in the United States has primarily focused on the Western and Northeastern regions due to dominance of snow melt for runoff and aquifer recharge but the impact of climate warming in the mountainous central Appalachian Region is poorly understood. In this research, we assess the performance of GCM-generated historical climate compared to historical observations primarily in the context of forcing data for macro-scale hydrologic modeling. Our results show significant spatial heterogeneity of modeled climate indices when compared to observational trends at the watershed scale. Observational data is showing considerable variability within maximum temperature and precipitation trends, with consistent increases in minimum temperature. The geographic, temperature, and complex topographic gradient throughout the central Appalachian region is likely the contributing factor in temperature and precipitation variability. Variable climate changes are leading to more severe and frequent climate events such as temperature extremes and storm events, which can have significant impacts on our drinking water supply, infrastructure, and health of all downstream communities.

Nonholonomic Hamiltonian Method for Meso-macroscale Simulations of Reacting Shocks

NASA Astrophysics Data System (ADS)

Fahrenthold, Eric; Lee, Sangyup

2015-06-01

The seamless integration of macroscale, mesoscale, and molecular scale models of reacting shock physics has been hindered by dramatic differences in the model formulation techniques normally used at different scales. In recent research the authors have developed the first unified discrete Hamiltonian approach to multiscale simulation of reacting shock physics. Unlike previous work, the formulation employs reacting themomechanical Hamiltonian formulations at all scales, including the continuum. Unlike previous work, the formulation employs a nonholonomic modeling approach to systematically couple the models developed at all scales. Example applications of the method show meso-macroscale shock to detonation simulations in nitromethane and RDX. Research supported by the Defense Threat Reduction Agency.

Development and Implementation of the DTOPLATS-MP land surface model over the Continental US at 30 meters

NASA Astrophysics Data System (ADS)

Chaney, N.; Wood, E. F.

2014-12-01

The increasing accessibility of high-resolution land data (< 100 m) and high performance computing allows improved parameterizations of subgrid hydrologic processes in macroscale land surface models. Continental scale fully distributed modeling at these spatial scales is possible; however, its practicality for operational use is still unknown due to uncertainties in input data, model parameters, and storage requirements. To address these concerns, we propose a modeling framework that provides the spatial detail of a fully distributed model yet maintains the benefits of a semi-distributed model. In this presentation we will introduce DTOPLATS-MP, a coupling between the NOAH-MP land surface model and the Dynamic TOPMODEL hydrologic model. This new model captures a catchment's spatial heterogeneity by clustering high-resolution land datasets (soil, topography, and land cover) into hundreds of hydrologic similar units (HSUs). A prior DEM analysis defines the connections between each HSU. At each time step, the 1D land surface model updates each HSU; the HSUs then interact laterally via the subsurface and surface. When compared to the fully distributed form of the model, this framework allows a significant decrease in computation and storage while providing most of the same information and enabling parameter transferability. As a proof of concept, we will show how this new modeling framework can be run over CONUS at a 30-meter spatial resolution. For each catchment in the WBD HUC-12 dataset, the model is run between 2002 and 2012 using available high-resolution continental scale land and meteorological datasets over CONUS (dSSURGO, NLCD, NED, and NCEP Stage IV). For each catchment, the model is run with 1000 model parameter sets obtained from a Latin hypercube sample. This exercise will illustrate the feasibility of running the model operationally at continental scales while accounting for model parameter uncertainty.

Improved Large-Scale Inundation Modelling by 1D-2D Coupling and Consideration of Hydrologic and Hydrodynamic Processes - a Case Study in the Amazon

NASA Astrophysics Data System (ADS)

Hoch, J. M.; Bierkens, M. F.; Van Beek, R.; Winsemius, H.; Haag, A.

2015-12-01

Understanding the dynamics of fluvial floods is paramount to accurate flood hazard and risk modeling. Currently, economic losses due to flooding constitute about one third of all damage resulting from natural hazards. Given future projections of climate change, the anticipated increase in the World's population and the associated implications, sound knowledge of flood hazard and related risk is crucial. Fluvial floods are cross-border phenomena that need to be addressed accordingly. Yet, only few studies model floods at the large-scale which is preferable to tiling the output of small-scale models. Most models cannot realistically model flood wave propagation due to a lack of either detailed channel and floodplain geometry or the absence of hydrologic processes. This study aims to develop a large-scale modeling tool that accounts for both hydrologic and hydrodynamic processes, to find and understand possible sources of errors and improvements and to assess how the added hydrodynamics affect flood wave propagation. Flood wave propagation is simulated by DELFT3D-FM (FM), a hydrodynamic model using a flexible mesh to schematize the study area. It is coupled to PCR-GLOBWB (PCR), a macro-scale hydrological model, that has its own simpler 1D routing scheme (DynRout) which has already been used for global inundation modeling and flood risk assessments (GLOFRIS; Winsemius et al., 2013). A number of model set-ups are compared and benchmarked for the simulation period 1986-1996: (0) PCR with DynRout; (1) using a FM 2D flexible mesh forced with PCR output and (2) as in (1) but discriminating between 1D channels and 2D floodplains, and, for comparison, (3) and (4) the same set-ups as (1) and (2) but forced with observed GRDC discharge values. Outputs are subsequently validated against observed GRDC data at Óbidos and flood extent maps from the Dartmouth Flood Observatory. The present research constitutes a first step into a globally applicable approach to fully couple hydrologic with hydrodynamic computations while discriminating between 1D-channels and 2D-floodplains. Such a fully-fledged set-up would be able to provide higher-order flood hazard information, e.g. time to flooding and flood duration, ultimately leading to improved flood risk assessment and management at the large scale.

Advancing Climate Change and Impacts Science Through Climate Informatics

NASA Astrophysics Data System (ADS)

Lenhardt, W.; Pouchard, L. C.; King, A. W.; Branstetter, M. L.; Kao, S.; Wang, D.

2010-12-01

This poster will outline the work to date on developing a climate informatics capability at Oak Ridge National Laboratory (ORNL). The central proposition of this effort is that the application of informatics and information science to the domain of climate change science is an essential means to bridge the realm of high performance computing (HPC) and domain science. The goal is to facilitate knowledge capture and the creation of new scientific insights. For example, a climate informatics capability will help with the understanding and use of model results in domain sciences that were not originally in the scope. From there, HPC can also benefit from feedback as the new approaches may lead to better parameterization in the models. In this poster we will summarize the challenges associated with climate change science that can benefit from the systematic application of informatics and we will highlight our work to date in creating the climate informatics capability to address these types of challenges. We have identified three areas that are particularly challenging in the context of climate change science: 1) integrating model and observational data across different spatial and temporal scales, 2) model linkages, i.e. climate models linked to other models such as hydrologic models, and 3) model diagnostics. Each of these has a methodological component and an informatics component. Our project under way at ORNL seeks to develop new approaches and tools in the context of linking climate change and water issues. We are basing our work on the following four use cases: 1) Evaluation/test of CCSM4 biases in hydrology (precipitation, soil water, runoff, river discharge) over the Rio Grande Basin. User: climate modeler. 2) Investigation of projected changes in hydrology of Rio Grande Basin using the VIC (Variable Infiltration Capacity Macroscale) Hydrologic Model. User: watershed hydrologist/modeler. 3) Impact of climate change on agricultural productivity of the Rio Grande Basin. User: climate impact scientist, agricultural economist. 4) Renegotiation of the 1944 “Treaty for the Utilization of Waters of the Colorado and Tijuana Rivers and of the Rio Grande”. User: A US State Department analyst or their counterpart in Mexico.

Pan-Arctic river discharge: Prioritizing monitoring of future climate change hot spots

NASA Astrophysics Data System (ADS)

Bring, Arvid; Shiklomanov, Alexander; Lammers, Richard B.

2017-01-01

The Arctic freshwater cycle is changing rapidly, which will require adequate monitoring of river flows to detect, observe, and understand changes and provide adaptation information. There has, however, been little detail about where the greatest flow changes are projected, and where monitoring therefore may need to be strengthened. In this study, we used a set of recent climate model runs and an advanced macro-scale hydrological model to analyze how flows across the continental pan-Arctic are projected to change and where the climate models agree on significant changes. We also developed a method to identify where monitoring stations should be placed to observe these significant changes, and compared this set of suggested locations with the existing network of monitoring stations. Overall, our results reinforce earlier indications of large increases in flow over much of the Arctic, but we also identify some areas where projections agree on significant changes but disagree on the sign of change. For monitoring, central and eastern Siberia, Alaska, and central Canada are hot spots for the highest changes. To take advantage of existing networks, a number of stations across central Canada and western and central Siberia could form a prioritized set. Further development of model representation of high-latitude hydrology would improve confidence in the areas we identify here. Nevertheless, ongoing observation programs may consider these suggested locations in efforts to improve monitoring of the rapidly changing Arctic freshwater cycle.

Pan-Arctic River Discharge: Where Can We Improve Monitoring of Future Change?

NASA Astrophysics Data System (ADS)

Bring, A.; Shiklomanov, A. I.; Lammers, R. B.

2016-12-01

The Arctic freshwater cycle is changing rapidly, which will require adequate monitoring of river flow to detect, observe and understand changes and provide adaptation information. There has however been little detail about where the greatest flow changes are projected, and where monitoring therefore may need to be strengthened. In this study, we used a set of recent climate model runs and an advanced macro-scale hydrological model to analyze how flows across the continental pan-Arctic are projected to change, and where the climate models agree on significant changes. We also developed a method to identify where monitoring stations should be placed to observe these significant changes, and compared this set of suggested locations with the existing network of monitoring stations. Overall, our results reinforce earlier indications of large increases in flow over much of the Arctic, but we also identify some areas where projections agree on significant changes but disagree on the sign of change. For monitoring, central and eastern Siberia, Alaska and central Canada are hot spots for the highest changes. To take advantage of existing networks, a number of stations across central Canada and western and central Siberia could form a prioritized set. Further development of model representation of high-latitude hydrology would improve confidence in the areas we identify here. Nevertheless, ongoing observation programs may consider these suggested locations in efforts to improve monitoring of the rapidly changing Arctic freshwater cycle.

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

Bishop, Joseph E.; Emery, John M.; Battaile, Corbett C.

Two fundamental approximations in macroscale solid-mechanics modeling are (1) the assumption of scale separation in homogenization theory and (2) the use of a macroscopic plasticity material model that represents, in a mean sense, the multitude of inelastic processes occurring at the microscale. With the goal of quantifying the errors induced by these approximations on engineering quantities of interest, we perform a set of direct numerical simulations (DNS) in which polycrystalline microstructures are embedded throughout a macroscale structure. The largest simulations model over 50,000 grains. The microstructure is idealized using a randomly close-packed Voronoi tessellation in which each polyhedral Voronoi cellmore » represents a grain. An face centered cubic crystal-plasticity model is used to model the mechanical response of each grain. The overall grain structure is equiaxed, and each grain is randomly oriented with no overall texture. The detailed results from the DNS simulations are compared to results obtained from conventional macroscale simulations that use homogeneous isotropic plasticity models. The macroscale plasticity models are calibrated using a representative volume element of the idealized microstructure. Furthermore, we envision that DNS modeling will be used to gain new insights into the mechanics of material deformation and failure.« less

Micro and Macroscale Drivers of Nutrient Concentrations in Urban Streams in South, Central and North America.

PubMed

Loiselle, Steven A; Gasparini Fernandes Cunha, Davi; Shupe, Scott; Valiente, Elsa; Rocha, Luciana; Heasley, Eleanore; Belmont, Patricia Pérez; Baruch, Avinoam

Global metrics of land cover and land use provide a fundamental basis to examine the spatial variability of human-induced impacts on freshwater ecosystems. However, microscale processes and site specific conditions related to bank vegetation, pollution sources, adjacent land use and water uses can have important influences on ecosystem conditions, in particular in smaller tributary rivers. Compared to larger order rivers, these low-order streams and rivers are more numerous, yet often under-monitored. The present study explored the relationship of nutrient concentrations in 150 streams in 57 hydrological basins in South, Central and North America (Buenos Aires, Curitiba, São Paulo, Rio de Janeiro, Mexico City and Vancouver) with macroscale information available from global datasets and microscale data acquired by trained citizen scientists. Average sub-basin phosphate (P-PO4) concentrations were found to be well correlated with sub-basin attributes on both macro and microscales, while the relationships between sub-basin attributes and nitrate (N-NO3) concentrations were limited. A phosphate threshold for eutrophic conditions (>0.1 mg L-1 P-PO4) was exceeded in basins where microscale point source discharge points (eg. residential, industrial, urban/road) were identified in more than 86% of stream reaches monitored by citizen scientists. The presence of bankside vegetation covaried (rho = -0.53) with lower phosphate concentrations in the ecosystems studied. Macroscale information on nutrient loading allowed for a strong separation between basins with and without eutrophic conditions. Most importantly, the combination of macroscale and microscale information acquired increased our ability to explain sub-basin variability of P-PO4 concentrations. The identification of microscale point sources and bank vegetation conditions by citizen scientists provided important information that local authorities could use to improve their management of lower order river ecosystems.

Micro and Macroscale Drivers of Nutrient Concentrations in Urban Streams in South, Central and North America

PubMed Central

Loiselle, Steven A.; Gasparini Fernandes Cunha, Davi; Shupe, Scott; Valiente, Elsa; Rocha, Luciana; Heasley, Eleanore; Belmont, Patricia Pérez; Baruch, Avinoam

2016-01-01

Global metrics of land cover and land use provide a fundamental basis to examine the spatial variability of human-induced impacts on freshwater ecosystems. However, microscale processes and site specific conditions related to bank vegetation, pollution sources, adjacent land use and water uses can have important influences on ecosystem conditions, in particular in smaller tributary rivers. Compared to larger order rivers, these low-order streams and rivers are more numerous, yet often under-monitored. The present study explored the relationship of nutrient concentrations in 150 streams in 57 hydrological basins in South, Central and North America (Buenos Aires, Curitiba, São Paulo, Rio de Janeiro, Mexico City and Vancouver) with macroscale information available from global datasets and microscale data acquired by trained citizen scientists. Average sub-basin phosphate (P-PO4) concentrations were found to be well correlated with sub-basin attributes on both macro and microscales, while the relationships between sub-basin attributes and nitrate (N-NO3) concentrations were limited. A phosphate threshold for eutrophic conditions (>0.1 mg L-1 P-PO4) was exceeded in basins where microscale point source discharge points (eg. residential, industrial, urban/road) were identified in more than 86% of stream reaches monitored by citizen scientists. The presence of bankside vegetation covaried (rho = –0.53) with lower phosphate concentrations in the ecosystems studied. Macroscale information on nutrient loading allowed for a strong separation between basins with and without eutrophic conditions. Most importantly, the combination of macroscale and microscale information acquired increased our ability to explain sub-basin variability of P-PO4 concentrations. The identification of microscale point sources and bank vegetation conditions by citizen scientists provided important information that local authorities could use to improve their management of lower order river ecosystems. PMID:27662192

Good coupling for the multiscale patch scheme on systems with microscale heterogeneity

NASA Astrophysics Data System (ADS)

Bunder, J. E.; Roberts, A. J.; Kevrekidis, I. G.

2017-05-01

Computational simulation of microscale detailed systems is frequently only feasible over spatial domains much smaller than the macroscale of interest. The 'equation-free' methodology couples many small patches of microscale computations across space to empower efficient computational simulation over macroscale domains of interest. Motivated by molecular or agent simulations, we analyse the performance of various coupling schemes for patches when the microscale is inherently 'rough'. As a canonical problem in this universality class, we systematically analyse the case of heterogeneous diffusion on a lattice. Computer algebra explores how the dynamics of coupled patches predict the large scale emergent macroscale dynamics of the computational scheme. We determine good design for the coupling of patches by comparing the macroscale predictions from patch dynamics with the emergent macroscale on the entire domain, thus minimising the computational error of the multiscale modelling. The minimal error on the macroscale is obtained when the coupling utilises averaging regions which are between a third and a half of the patch. Moreover, when the symmetry of the inter-patch coupling matches that of the underlying microscale structure, patch dynamics predicts the desired macroscale dynamics to any specified order of error. The results confirm that the patch scheme is useful for macroscale computational simulation of a range of systems with microscale heterogeneity.

Monte Carlo sensitivity analysis of land surface parameters using the Variable Infiltration Capacity model

NASA Astrophysics Data System (ADS)

Demaria, Eleonora M.; Nijssen, Bart; Wagener, Thorsten

2007-06-01

Current land surface models use increasingly complex descriptions of the processes that they represent. Increase in complexity is accompanied by an increase in the number of model parameters, many of which cannot be measured directly at large spatial scales. A Monte Carlo framework was used to evaluate the sensitivity and identifiability of ten parameters controlling surface and subsurface runoff generation in the Variable Infiltration Capacity model (VIC). Using the Monte Carlo Analysis Toolbox (MCAT), parameter sensitivities were studied for four U.S. watersheds along a hydroclimatic gradient, based on a 20-year data set developed for the Model Parameter Estimation Experiment (MOPEX). Results showed that simulated streamflows are sensitive to three parameters when evaluated with different objective functions. Sensitivity of the infiltration parameter (b) and the drainage parameter (exp) were strongly related to the hydroclimatic gradient. The placement of vegetation roots played an important role in the sensitivity of model simulations to the thickness of the second soil layer (thick2). Overparameterization was found in the base flow formulation indicating that a simplified version could be implemented. Parameter sensitivity was more strongly dictated by climatic gradients than by changes in soil properties. Results showed how a complex model can be reduced to a more parsimonious form, leading to a more identifiable model with an increased chance of successful regionalization to ungauged basins. Although parameter sensitivities are strictly valid for VIC, this model is representative of a wider class of macroscale hydrological models. Consequently, the results and methodology will have applicability to other hydrological models.

Integrated Hydro-geomorphological Monitoring System of the Upper Bussento river basin (Cilento and Vallo Diano Geopark, S-Italy)

NASA Astrophysics Data System (ADS)

Guida, D.; Cuomo, A.; Longobardi, A.; Villani, P.; Guida, M.; Guadagnuolo, D.; Cestari, A.; Siervo, V.; Benevento, G.; Sorvino, S.; Doto, R.; Verrone, M.; De Vita, A.; Aloia, A.; Positano, P.

2012-04-01

The Mediterranean river ecosystem functionings are supported by river-aquifer interactions. The assessment of their ecological services requires interdisciplinary scientific approaches, integrate monitoring systems and inter-institutional planning and management. This poster illustrates the Hydro-geomorphological Monitoring System build-up in the Upper Bussento river basin by the University of Salerno, in agreement with the local Basin Autorities and in extension to the other river basins located in the Cilento and Vallo Diano National Park (southern Italy), recently accepted in the European Geopark Network. The Monitoring System is based on a hierarchical Hydro-geomorphological Model (HGM), improved in a multiscale, nested and object-oriented Hydro-geomorphological Informative System (HGIS, Figure 1). Hydro-objects are topologically linked and functionally bounded by Hydro-elements at various levels of homogeneity (Table 1). Spatial Hydro-geomorpho-system, HG-complex and HG-unit support respectively areal Hydro-objects, as basin, sector and catchment and linear Hydro-objects, as river, segment, reach and section. Runoff initiation points, springs, disappearing points, junctions, gaining and water losing points complete the Hydro-systems. An automatic procedure use the Pfafstetter coding to hierarchically divide a terrain into arbitrarily small hydro-geomorphological units (basin, interfluve, headwater and no-contribution areas, each with a unique label with hierarchical topological properties. To obtain a hierarchy of hydro-geomorphological units, the method is then applied recursively on each basin and interbasin, and labels of the subdivided regions are appended to the existing label of the original region. The monitoring stations are ranked consequently in main, secondary, temporary and random and located progressively at the points or sections representative for the hydro-geomorphological responses by validation control and modeling calibration. The datasets are organized into a relational geodatabase supporting tracer testings, space-time analysis and hydrological modeling. At the moment, three main station for hourly streamflow measurements are located at the terminal sections of the main basin and the two main sub-basin; secondary stations for weekly discharge measurements are located along the Upper Bussento river segment, upstream and downstream of each river reach or tributary catchments or karst spring inflow. Temporary stations are located in the representative sections of the catchments to detect stream flow losses into alluvial beds or experimental parcels in the bare karst and forested sandstone headwaters. Streamflow measurements are combined with geochemical survey and water sampling for Radon activity concentration measurements. Results of measurement campains in Radon space-time distribution within the basin are given in other contribution of same EGU session. Monitoring results confirm the hourly, daily, weekly and monthly hydrological data and validate outcomes of semi-distributed hydrological models based on previously time series, allowing both academic consultants and institutional subject to extend the Integrated Hydro-geomorphological Monitoring System to the surrounding drainage areas of the Cilento and Vallo di Diano Geopark. Keywords: River-aquifer interaction, Upper Bussento river basin, monitoring system, hydro-geomorphology, semi-distributed hydrological model. Table 1: Comparative, hierarchical Hydro-morpho-climate entities Hierarchy levelArea (Km2) Scale Orography Entity Climate Entity Morfological Entity Areal Drainage Entity Linear Drainage Entity VIII 106 1:15E6 Orogen Macroscale α Morphological Region Hydrological Region VII 105 1:10E6 Chain Sistem Macroscale β Morphological Province Hydrological Province VI 104 1:5E5 Chain Mesoscale α Morphological Sistem Basin River V 103 1:2,5E5Chain Segment Mesoscale β Morphological Sub-systemSub-Basin Torrent IV 100 1:1,0E5Orographic Group Mesoscale γ Morphological Complex Basin Sector Mid Order Channel/ Segment III 10 1: 5E4 Orographic System Microscale αMorphological Unit Watershed Low Order Channel/ Reach II 1 1:2,5E3Orographic ComplexMicroscale βMorphological ComponentCatchment Transient Channel/ Pool I 10-2 1:5E3 Orographic Unit Microscale γMorphological Element Hollow Zero Order Channel PIC

Projecting Climate Change Impacts on Wildfire Probabilities

NASA Astrophysics Data System (ADS)

Westerling, A. L.; Bryant, B. P.; Preisler, H.

2008-12-01

We present preliminary results of the 2008 Climate Change Impact Assessment for wildfire in California, part of the second biennial science report to the California Climate Action Team organized via the California Climate Change Center by the California Energy Commission's Public Interest Energy Research Program pursuant to Executive Order S-03-05 of Governor Schwarzenegger. In order to support decision making by the State pertaining to mitigation of and adaptation to climate change and its impacts, we model wildfire occurrence monthly from 1950 to 2100 under a range of climate scenarios from the Intergovernmental Panel on Climate Change. We use six climate change models (GFDL CM2.1, NCAR PCM1, CNRM CM3, MPI ECHAM5, MIROC3.2 med, NCAR CCSM3) under two emissions scenarios--A2 (C02 850ppm max atmospheric concentration) and B1(CO2 550ppm max concentration). Climate model output has been downscaled to a 1/8 degree (~12 km) grid using two alternative methods: a Bias Correction and Spatial Donwscaling (BCSD) and a Constructed Analogues (CA) downscaling. Hydrologic variables have been simulated from temperature, precipitation, wind and radiation forcing data using the Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model. We model wildfire as a function of temperature, moisture deficit, and land surface characteristics using nonlinear logistic regression techniques. Previous work on wildfire climatology and seasonal forecasting has demonstrated that these variables account for much of the inter-annual and seasonal variation in wildfire. The results of this study are monthly gridded probabilities of wildfire occurrence by fire size class, and estimates of the number of structures potentially affected by fires. In this presentation we will explore the range of modeled outcomes for wildfire in California, considering the effects of emissions scenarios, climate model sensitivities, downscaling methods, hydrologic simulations, statistical model specifications for california wildfire, and their intersection with a range of development scenarios for California.

Understanding macroscale invasion patterns and processes with FIA data

Treesearch

Songlin Fei; Basil V. Iannone III; Christopher M. Oswalt; Qinfeng Guo; Kevin M. Potter; Sonja N. Oswalt; Bryan C. Pijanowski; Gabriela C. Nunez-Mir

2015-01-01

Using empirical data from FIA, we modeled invasion richness and invasion prevalence as functions of 22 factors reflective of propagule pressure and/or habitat invasibility across the continental US. Our statistical models suggest that both propagule pressure and habitat invasibility contribute to macroscale patterns of forest plant invasions. Our investigation provides...

Evaluating a Local Ensemble Transform Kalman Filter snow cover data assimilation method to estimate SWE within a high-resolution hydrologic modeling framework across Western US mountainous regions

NASA Astrophysics Data System (ADS)

Oaida, C. M.; Andreadis, K.; Reager, J. T., II; Famiglietti, J. S.; Levoe, S.

2017-12-01

Accurately estimating how much snow water equivalent (SWE) is stored in mountainous regions characterized by complex terrain and snowmelt-driven hydrologic cycles is not only greatly desirable, but also a big challenge. Mountain snowpack exhibits high spatial variability across a broad range of spatial and temporal scales due to a multitude of physical and climatic factors, making it difficult to observe or estimate in its entirety. Combing remotely sensed data and high resolution hydrologic modeling through data assimilation (DA) has the potential to provide a spatially and temporally continuous SWE dataset at horizontal scales that capture sub-grid snow spatial variability and are also relevant to stakeholders such as water resource managers. Here, we present the evaluation of a new snow DA approach that uses a Local Ensemble Transform Kalman Filter (LETKF) in tandem with the Variable Infiltration Capacity macro-scale hydrologic model across the Western United States, at a daily temporal resolution, and a horizontal resolution of 1.75 km x 1.75 km. The LETKF is chosen for its relative simplicity, ease of implementation, and computational efficiency and scalability. The modeling/DA system assimilates daily MODIS Snow Covered Area and Grain Size (MODSCAG) fractional snow cover over, and has been developed to efficiently calculate SWE estimates over extended periods of time and covering large regional-scale areas at relatively high spatial resolution, ultimately producing a snow reanalysis-type dataset. Here we focus on the assessment of SWE produced by the DA scheme over several basins in California's Sierra Nevada Mountain range where Airborne Snow Observatory data is available, during the last five water years (2013-2017), which include both one of the driest and one of the wettest years. Comparison against such a spatially distributed SWE observational product provides a greater understanding of the model's ability to estimate SWE and SWE spatial variability, and highlights under which conditions snow cover DA can add value in estimating SWE.

Impacts of Climate Change on Stream Temperatures in the Clearwater River, Idaho

NASA Astrophysics Data System (ADS)

Yearsley, J. R.; Chegwidden, O.; Nijssen, B.

2016-12-01

Dworshak Dam in northern Idaho impounds the waters of the North Fork of the Clearwater River, creating a reservoir of approximately 4.278 km3 at full pool elevation. The dam's primary purpose is for flood control and hydroelectric power generation. It also provides important water quality benefits by releasing cold water into the Clearwater River during the summer when conditions become critical for migrating endangered species of salmon. Changes in the climate may have an impact on the ability of Dworshak Dam and Reservoir to provide these benefits. To investigate the potential for extreme outcomes that would limit cold water releases from Dworshak Reservoir and compromise the fishery, we implemented a system of hydrologic and water temperature models that simulate daily-averaged water temperatures in both the riverine and reservoir environments. We used the macroscale hydrologic model, VIC, to simulate land surface water and energy fluxes, the one-dimensional, time-dependent stream temperature model, RBM, to simulate river temperatures and a modified version of CEQUAL-W2 to simulate water temperatures in Dworshak Reservoir. A long-term hydrologically based gridded data set of meteorological forcing provided the input for comparing model results with available observations of flow and water temperature. For purposes of investigating the impacts of climate change, we used the results from ten of the most recent Climate Model Intercomparison Project (CMIP5) climate change models scenarios in conjunction with the estimates of anthropogenic inputs of climate change gases from two representative concentration pathways (RCP). We compared the simulated results associated with a range of outcomes at critical river locations from the climate scenarios with existing conditions assuming that the reservoir would be operated under a rule curve based on the average reservoir elevation for the period 2006-2015 rule curve and for power demands represented by that same period.

A hydroclimatological approach to predicting regional landslide probability using Landlab

NASA Astrophysics Data System (ADS)

Strauch, Ronda; Istanbulluoglu, Erkan; Nudurupati, Sai Siddhartha; Bandaragoda, Christina; Gasparini, Nicole M.; Tucker, Gregory E.

2018-02-01

We develop a hydroclimatological approach to the modeling of regional shallow landslide initiation that integrates spatial and temporal dimensions of parameter uncertainty to estimate an annual probability of landslide initiation based on Monte Carlo simulations. The physically based model couples the infinite-slope stability model with a steady-state subsurface flow representation and operates in a digital elevation model. Spatially distributed gridded data for soil properties and vegetation classification are used for parameter estimation of probability distributions that characterize model input uncertainty. Hydrologic forcing to the model is through annual maximum daily recharge to subsurface flow obtained from a macroscale hydrologic model. We demonstrate the model in a steep mountainous region in northern Washington, USA, over 2700 km2. The influence of soil depth on the probability of landslide initiation is investigated through comparisons among model output produced using three different soil depth scenarios reflecting the uncertainty of soil depth and its potential long-term variability. We found elevation-dependent patterns in probability of landslide initiation that showed the stabilizing effects of forests at low elevations, an increased landslide probability with forest decline at mid-elevations (1400 to 2400 m), and soil limitation and steep topographic controls at high alpine elevations and in post-glacial landscapes. These dominant controls manifest themselves in a bimodal distribution of spatial annual landslide probability. Model testing with limited observations revealed similarly moderate model confidence for the three hazard maps, suggesting suitable use as relative hazard products. The model is available as a component in Landlab, an open-source, Python-based landscape earth systems modeling environment, and is designed to be easily reproduced utilizing HydroShare cyberinfrastructure.

QUANTIFYING THE MICROMECHANICAL EFFECTS OF VARIABLE CEMENT IN GRANULAR POROUS MEDIA

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

Boutt, David F; Goodwin, Laurel B

2010-03-01

The mechanical and hydrologic behavior of clastic rocks and sediments is fundamentally controlled by variables such as grain size and shape, sorting, grain and cement mineralogy, porosity, and %cement - parameters that are not used directly in field-scale models of coupled flow and deformation. To improve our understanding of the relationship between these micromechanical properties and bulk behavior we focused on (1) relating detailed, quantitative characterization of the grain-pore systems to both hydrologic and mechanical properties of a suite of variably quartz-cemented quartz arenite samples and (2) the use of a combination of discrete element method (DEM) and poroelastic modelsmore » parameterized by data from the natural samples to isolate and compare the influence of changes in the mechanical and hydrologic properties of granular porous media due to changes in degree of cementation. Quartz overgrowths, the most common form of authigenic cements in sandstones, are responsible for significant porosity and permeability reduction. The distribution of quartz overgrowths is controlled by available pore space and the crystallographic orientations of individual quartz grains. Study of the St. Peter Sandstone allowed evaluation of the relative effects of quartz cementation and compaction on final grain and pore morphology, showing that progressive quartz cementation modifies the grain framework in consistent, predictable ways. Detailed microstructural characterization and multiple regression analyses show that with progressive diagenesis, the number and length of grain contacts increases as the number of pores increases, the number of large, well-connected pores decreases, and pores become rounder. These changes cause a decrease in pore size variability that leads to a decrease in bulk permeability and both stiffening and strengthening of the grain framework. The consistent nature of these changes allows us to predict variations in hydrologic and mechanical properties with progressive diagenesis, and explore the impact of these changes on aquifer behavior. Several examples of this predictive capability are offered. In one application, data from natural sandstones are used to calibrate the proportionality constant of the Kozeny- Carman relationship, improving the ability to predict permeability in quartz-cemented quartz arenites. In another, the bond-to-grain ratio (BGR) is used to parameterize a discrete element model with data acquired from sandstone samples. The DEM results provide input to poroelastic models used to explore the hydrologic, mechanical, and coupled hydrologic and mechanical response of the sandstone to pumping stresses. This modeling exercise shows that at the macroscale, changes in mechanical and hydrologic properties directly influence the magnitude and area of aquifer deformation. The significant difference in sensitivity of the system to the mechanical properties alone versus its sensitivity to coupled mechanical and hydrologic properties demonstrates the importance of including hydrologic properties that are adjusted for changes in cementation in fluid storage and deformation studies. The large magnitude of radial deformation compared to vertical deformation in these models emphasizes the importance of considering three dimensional deformation in fluid flow and deformation studies.« less

A first large-scale flood inundation forecasting model

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

Schumann, Guy J-P; Neal, Jeffrey C.; Voisin, Nathalie

2013-11-04

At present continental to global scale flood forecasting focusses on predicting at a point discharge, with little attention to the detail and accuracy of local scale inundation predictions. Yet, inundation is actually the variable of interest and all flood impacts are inherently local in nature. This paper proposes a first large scale flood inundation ensemble forecasting model that uses best available data and modeling approaches in data scarce areas and at continental scales. The model was built for the Lower Zambezi River in southeast Africa to demonstrate current flood inundation forecasting capabilities in large data-scarce regions. The inundation model domainmore » has a surface area of approximately 170k km2. ECMWF meteorological data were used to force the VIC (Variable Infiltration Capacity) macro-scale hydrological model which simulated and routed daily flows to the input boundary locations of the 2-D hydrodynamic model. Efficient hydrodynamic modeling over large areas still requires model grid resolutions that are typically larger than the width of many river channels that play a key a role in flood wave propagation. We therefore employed a novel sub-grid channel scheme to describe the river network in detail whilst at the same time representing the floodplain at an appropriate and efficient scale. The modeling system was first calibrated using water levels on the main channel from the ICESat (Ice, Cloud, and land Elevation Satellite) laser altimeter and then applied to predict the February 2007 Mozambique floods. Model evaluation showed that simulated flood edge cells were within a distance of about 1 km (one model resolution) compared to an observed flood edge of the event. Our study highlights that physically plausible parameter values and satisfactory performance can be achieved at spatial scales ranging from tens to several hundreds of thousands of km2 and at model grid resolutions up to several km2. However, initial model test runs in forecast mode revealed that it is crucial to account for basin-wide hydrological response time when assessing lead time performances notwithstanding structural limitations in the hydrological model and possibly large inaccuracies in precipitation data.« less

Infrastructure Upgrades to Support Model Longevity and New Applications: The Variable Infiltration Capacity Model Version 5.0 (VIC 5.0)

NASA Astrophysics Data System (ADS)

Nijssen, B.; Hamman, J.; Bohn, T. J.

2015-12-01

The Variable Infiltration Capacity (VIC) model is a macro-scale semi-distributed hydrologic model. VIC development began in the early 1990s and it has been used extensively, applied from basin to global scales. VIC has been applied in a many use cases, including the construction of hydrologic data sets, trend analysis, data evaluation and assimilation, forecasting, coupled climate modeling, and climate change impact analysis. Ongoing applications of the VIC model include the University of Washington's drought monitor and forecast systems, and NASA's land data assimilation systems. The development of VIC version 5.0 focused on reconfiguring the legacy VIC source code to support a wider range of modern modeling applications. The VIC source code has been moved to a public Github repository to encourage participation by the model development community-at-large. The reconfiguration has separated the physical core of the model from the driver, which is responsible for memory allocation, pre- and post-processing and I/O. VIC 5.0 includes four drivers that use the same physical model core: classic, image, CESM, and Python. The classic driver supports legacy VIC configurations and runs in the traditional time-before-space configuration. The image driver includes a space-before-time configuration, netCDF I/O, and uses MPI for parallel processing. This configuration facilitates the direct coupling of streamflow routing, reservoir, and irrigation processes within VIC. The image driver is the foundation of the CESM driver; which couples VIC to CESM's CPL7 and a prognostic atmosphere. Finally, we have added a Python driver that provides access to the functions and datatypes of VIC's physical core from a Python interface. This presentation demonstrates how reconfiguring legacy source code extends the life and applicability of a research model.

On the consistency of scale among experiments, theory, and simulation

DOE PAGES

McClure, James E.; Dye, Amanda L.; Miller, Cass T.; ...

2017-02-20

As a tool for addressing problems of scale, we consider an evolving approach known as the thermodynamically constrained averaging theory (TCAT), which has broad applicability to hydrology. We consider the case of modeling of two-fluid-phase flow in porous media, and we focus on issues of scale as they relate to various measures of pressure, capillary pressure, and state equations needed to produce solvable models. We apply TCAT to perform physics-based data assimilation to understand how the internal behavior influences the macroscale state of two-fluid porous medium systems. A microfluidic experimental method and a lattice Boltzmann simulation method are used to examinemore » a key deficiency associated with standard approaches. In a hydrologic process such as evaporation, the water content will ultimately be reduced below the irreducible wetting-phase saturation determined from experiments. This is problematic since the derived closure relationships cannot predict the associated capillary pressures for these states. Here, we demonstrate that the irreducible wetting-phase saturation is an artifact of the experimental design, caused by the fact that the boundary pressure difference does not approximate the true capillary pressure. Using averaging methods, we compute the true capillary pressure for fluid configurations at and below the irreducible wetting-phase saturation. Results of our analysis include a state function for the capillary pressure expressed as a function of fluid saturation and interfacial area.« less

On the consistency of scale among experiments, theory, and simulation

NASA Astrophysics Data System (ADS)

McClure, James E.; Dye, Amanda L.; Miller, Cass T.; Gray, William G.

2017-02-01

As a tool for addressing problems of scale, we consider an evolving approach known as the thermodynamically constrained averaging theory (TCAT), which has broad applicability to hydrology. We consider the case of modeling of two-fluid-phase flow in porous media, and we focus on issues of scale as they relate to various measures of pressure, capillary pressure, and state equations needed to produce solvable models. We apply TCAT to perform physics-based data assimilation to understand how the internal behavior influences the macroscale state of two-fluid porous medium systems. A microfluidic experimental method and a lattice Boltzmann simulation method are used to examine a key deficiency associated with standard approaches. In a hydrologic process such as evaporation, the water content will ultimately be reduced below the irreducible wetting-phase saturation determined from experiments. This is problematic since the derived closure relationships cannot predict the associated capillary pressures for these states. We demonstrate that the irreducible wetting-phase saturation is an artifact of the experimental design, caused by the fact that the boundary pressure difference does not approximate the true capillary pressure. Using averaging methods, we compute the true capillary pressure for fluid configurations at and below the irreducible wetting-phase saturation. Results of our analysis include a state function for the capillary pressure expressed as a function of fluid saturation and interfacial area.

Modeling surface water dynamics in the Amazon Basin using MOSART-Inundation v1.0: Impacts of geomorphological parameters and river flow representation

DOE PAGES

Luo, Xiangyu; Li, Hong -Yi; Leung, L. Ruby; ...

2017-03-23

In the Amazon Basin, floodplain inundation is a key component of surface water dynamics and plays an important role in water, energy and carbon cycles. The Model for Scale Adaptive River Transport (MOSART) was extended with a macroscale inundation scheme for representing floodplain inundation. The extended model, named MOSART-Inundation, was used to simulate surface hydrology of the entire Amazon Basin. Previous hydrologic modeling studies in the Amazon Basin identified and addressed a few challenges in simulating surface hydrology of this basin, including uncertainties of floodplain topography and channel geometry, and the representation of river flow in reaches with mild slopes.more » This study further addressed four aspects of these challenges. First, the spatial variability of vegetation-caused biases embedded in the HydroSHEDS digital elevation model (DEM) data was explicitly addressed. A vegetation height map of about 1 km resolution and a land cover dataset of about 90 m resolution were used in a DEM correction procedure that resulted in an average elevation reduction of 13.2 m for the entire basin and led to evident changes in the floodplain topography. Second, basin-wide empirical formulae for channel cross-sectional dimensions were refined for various subregions to improve the representation of spatial variability in channel geometry. Third, the channel Manning roughness coefficient was allowed to vary with the channel depth, as the effect of riverbed resistance on river flow generally declines with increasing river size. Lastly, backwater effects were accounted for to better represent river flow in mild-slope reaches. The model was evaluated against in situ streamflow records and remotely sensed Envisat altimetry data and Global Inundation Extent from Multi-Satellites (GIEMS) inundation data. In a sensitivity study, seven simulations were compared to evaluate the impacts of the five modeling aspects addressed in this study. The comparisons showed that representing floodplain inundation could significantly improve the simulated streamflow and river stages. Refining floodplain topography, channel geometry and Manning roughness coefficients, as well as accounting for backwater effects had notable impacts on the simulated surface water dynamics in the Amazon Basin. As a result, the understanding obtained in this study could be helpful in improving modeling of surface hydrology in basins with evident inundation, especially at regional to continental scales.« less

Modeling surface water dynamics in the Amazon Basin using MOSART-Inundation v1.0: Impacts of geomorphological parameters and river flow representation

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

Luo, Xiangyu; Li, Hong -Yi; Leung, L. Ruby

In the Amazon Basin, floodplain inundation is a key component of surface water dynamics and plays an important role in water, energy and carbon cycles. The Model for Scale Adaptive River Transport (MOSART) was extended with a macroscale inundation scheme for representing floodplain inundation. The extended model, named MOSART-Inundation, was used to simulate surface hydrology of the entire Amazon Basin. Previous hydrologic modeling studies in the Amazon Basin identified and addressed a few challenges in simulating surface hydrology of this basin, including uncertainties of floodplain topography and channel geometry, and the representation of river flow in reaches with mild slopes.more » This study further addressed four aspects of these challenges. First, the spatial variability of vegetation-caused biases embedded in the HydroSHEDS digital elevation model (DEM) data was explicitly addressed. A vegetation height map of about 1 km resolution and a land cover dataset of about 90 m resolution were used in a DEM correction procedure that resulted in an average elevation reduction of 13.2 m for the entire basin and led to evident changes in the floodplain topography. Second, basin-wide empirical formulae for channel cross-sectional dimensions were refined for various subregions to improve the representation of spatial variability in channel geometry. Third, the channel Manning roughness coefficient was allowed to vary with the channel depth, as the effect of riverbed resistance on river flow generally declines with increasing river size. Lastly, backwater effects were accounted for to better represent river flow in mild-slope reaches. The model was evaluated against in situ streamflow records and remotely sensed Envisat altimetry data and Global Inundation Extent from Multi-Satellites (GIEMS) inundation data. In a sensitivity study, seven simulations were compared to evaluate the impacts of the five modeling aspects addressed in this study. The comparisons showed that representing floodplain inundation could significantly improve the simulated streamflow and river stages. Refining floodplain topography, channel geometry and Manning roughness coefficients, as well as accounting for backwater effects had notable impacts on the simulated surface water dynamics in the Amazon Basin. As a result, the understanding obtained in this study could be helpful in improving modeling of surface hydrology in basins with evident inundation, especially at regional to continental scales.« less

Climate Change Impacts on River Temperature in the Southeastern United States: A Case Study of the Tennessee River Basin

NASA Astrophysics Data System (ADS)

Cheng, Y.; Niemeyer, R. J.; Mao, Y.; Yearsley, J. R.; Nijssen, B.

2016-12-01

In the coming decades, climate change and population growth are expected to affect water and energy supply as well as demand in the southeastern United States. Changes in temperature and precipitation impact river flow and stream temperature with implications for hydropower generation, industrial and municipal water supply, cooling for thermo-electric power plants, agricultural irrigation, ecosystem functions and flood control. At the same time, water and energy demand are expected to change in response to temperature increase, population growth and changing crop water requirements. As part of a multi-institution study of the food-energy-water nexus in the southeastern U.S., we are developing coupled hydrological and stream temperature models that will be linked to water resources, power systems and crop models at a later stage. Here we evaluate the ability of our system to simulate water supply and stream temperature in the Tennessee River Basin using the Variable Infiltration Capacity (VIC) macroscale hydrology model coupled to the River Basin Model (RBM), a 1-D semi-Lagrangian river temperature model, which has recently been expanded with a two-layer reservoir temperature model. Simulations with VIC-RBM were performed for the Tennessee River Basin at 1/8-degree spatial resolution and a temporal resolution of 1 day or less. Reservoir releases were prescribed based on historic operating rules. In future iterations, these releases will be modeled directly by a water resources model that incorporates flood control, and power and agricultural water demands. We compare simulated flows, as well as stream and reservoir temperatures with observed flows and temperatures throughout the basin. In preparation for later stages of the project, we also perform a set of climate change sensitivity experiments to evaluate how changes in climate may impact river and reservoir temperature.

Implications of GRACE Satellite Gravity Measurements for Diverse Hydrological Applications

NASA Astrophysics Data System (ADS)

Yirdaw-Zeleke, Sitotaw

Soil moisture plays a major role in the hydrologic water balance and is the basis for most hydrological models. It influences the partitioning of energy and moisture inputs at the land surface. Because of its importance, it has been used as a key variable for many hydrological studies such as flood forecasting, drought studies and the determination of groundwater recharge. Therefore, spatially distributed soil moisture with reasonable temporal resolution is considered a valuable source of information for hydrological model parameterization and validation. Unfortunately, soil moisture is difficult to measure and remains essentially unmeasured over spatial and temporal scales needed for a number of hydrological model applications. In 2002, the Gravity Recovery And Climate Experiment (GRACE) satellite platform was launched to measure, among other things, the gravitational field of the earth. Over its life span, these orbiting satellites have produced time series of mass changes of the earth-atmosphere system. The subsequent outcome of this, after integration over a number of years, is a time series of highly refined images of the earth's mass distribution. In addition to quantifying the static distribution of mass, the month-to-month variation in the earth's gravitational field are indicative of the integrated value of the subsurface total water storage for specific catchments. Utilization of these natural changes in the earth's gravitational field entails the transformation of the derived GRACE geopotential spherical harmonic coefficients into spatially varying time series estimates of total water storage. These remotely sensed basin total water storage estimates can be routinely validated against independent estimates of total water storage from an atmospheric-based water balance approach or from well calibrated macroscale hydrologic models. The hydrological relevance and implications of remotely estimated GRACE total water storage over poorly gauged, wetland-dominated watershed as well as over a deltaic region underlain by a thick sand aquifer in Western Canada are the focus of this thesis. The domain of the first case study was the Mackenzie River Basin wherein the GRACE total water storage estimates were successfully inter-compared and validated with the atmospheric based water balance. These were then used to assess the WAT-CLASS hydrological model estimates of total water storage. The outcome of this inter-comparison revealed the potential application of the GRACE-based approach for the closure of the hydrological water balance of the Mackenzie River Basin as well as a dependable source of data for the calibration of traditional hydrological models. The Mackenzie River Basin result led to a second case study where the GRACE-based total water storage was validated using storage estimated from the atmospheric-based water balance P--E computations in conjunction with the measured streamflow records for the Saskatchewan River Basin at its Grand Rapids outlet in Manitoba. The fallout from this comparison was then applied to the characterization of the Prairie-wide 2002/2003 drought enabling the development of a new drought index now known as the Total Storage Deficit Index (TSDI). This study demonstrated the potential application of the GRACE-based technique as a tool for drought characterization in the Canadian Prairies. Finally, the hydroinformatic approach based on the artificial neural network (ANN) enabled the downscaling of the groundwater component from the total water storage estimate from the remote sensing satellite, GRACE. This was subsequently explored as an alternate source of calibration and validation for a hydrological modeling application over the Assiniboine Delta Aquifer in Manitoba. Interestingly, a high correlation exists between the simulated groundwater storage from the coupled hydrological model, CLM-PF and the downscaled groundwater time series storage from the remote sensing satellite GRACE over this 4,000 km2 deltaic basin in Canada.

Global-scale regionalization of hydrological model parameters using streamflow data from many small catchments

NASA Astrophysics Data System (ADS)

Beck, Hylke; de Roo, Ad; van Dijk, Albert; McVicar, Tim; Miralles, Diego; Schellekens, Jaap; Bruijnzeel, Sampurno; de Jeu, Richard

2015-04-01

Motivated by the lack of large-scale model parameter regionalization studies, a large set of 3328 small catchments (< 10000 km2) around the globe was used to set up and evaluate five model parameterization schemes at global scale. The HBV-light model was chosen because of its parsimony and flexibility to test the schemes. The catchments were calibrated against observed streamflow (Q) using an objective function incorporating both behavioral and goodness-of-fit measures, after which the catchment set was split into subsets of 1215 donor and 2113 evaluation catchments based on the calibration performance. The donor catchments were subsequently used to derive parameter sets that were transferred to similar grid cells based on a similarity measure incorporating climatic and physiographic characteristics, thereby producing parameter maps with global coverage. Overall, there was a lack of suitable donor catchments for mountainous and tropical environments. The schemes with spatially-uniform parameter sets (EXP2 and EXP3) achieved the worst Q estimation performance in the evaluation catchments, emphasizing the importance of parameter regionalization. The direct transfer of calibrated parameter sets from donor catchments to similar grid cells (scheme EXP1) performed best, although there was still a large performance gap between EXP1 and HBV-light calibrated against observed Q. The schemes with parameter sets obtained by simultaneously calibrating clusters of similar donor catchments (NC10 and NC58) performed worse than EXP1. The relatively poor Q estimation performance achieved by two (uncalibrated) macro-scale hydrological models suggests there is considerable merit in regionalizing the parameters of such models. The global HBV-light parameter maps and ancillary data are freely available via http://water.jrc.ec.europa.eu.

Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources

NASA Astrophysics Data System (ADS)

Wada, Y.; Wisser, D.; Bierkens, M. F. P.

2014-01-01

To sustain growing food demand and increasing standard of living, global water withdrawal and consumptive water use have been increasing rapidly. To analyze the human perturbation on water resources consistently over large scales, a number of macro-scale hydrological models (MHMs) have been developed in recent decades. However, few models consider the interaction between terrestrial water fluxes, and human activities and associated water use, and even fewer models distinguish water use from surface water and groundwater resources. Here, we couple a global water demand model with a global hydrological model and dynamically simulate daily water withdrawal and consumptive water use over the period 1979-2010, using two re-analysis products: ERA-Interim and MERRA. We explicitly take into account the mutual feedback between supply and demand, and implement a newly developed water allocation scheme to distinguish surface water and groundwater use. Moreover, we include a new irrigation scheme, which works dynamically with a daily surface and soil water balance, and incorporate the newly available extensive Global Reservoir and Dams data set (GRanD). Simulated surface water and groundwater withdrawals generally show good agreement with reported national and subnational statistics. The results show a consistent increase in both surface water and groundwater use worldwide, with a more rapid increase in groundwater use since the 1990s. Human impacts on terrestrial water storage (TWS) signals are evident, altering the seasonal and interannual variability. This alteration is particularly large over heavily regulated basins such as the Colorado and the Columbia, and over the major irrigated basins such as the Mississippi, the Indus, and the Ganges. Including human water use and associated reservoir operations generally improves the correlation of simulated TWS anomalies with those of the GRACE observations.

Global Modeling of Withdrawal, Allocation and Consumptive Use of Surface Water and Groundwater Resources

NASA Astrophysics Data System (ADS)

Wada, Y.; Wisser, D.; Bierkens, M. F.

2014-12-01

To sustain growing food demand and increasing standard of living, global water withdrawal and consumptive water use have been increasing rapidly. To analyze the human perturbation on water resources consistently over large scales, a number of macro-scale hydrological models (MHMs) have been developed in recent decades. However, few models consider the interaction between terrestrial water fluxes, and human activities and associated water use, and even fewer models distinguish water use from surface water and groundwater resources. Here, we couple a global water demand model with a global hydrological model and dynamically simulate daily water withdrawal and consumptive water use over the period 1979-2010, using two re-analysis products: ERA-Interim and MERRA. We explicitly take into account the mutual feedback between supply and demand, and implement a newly developed water allocation scheme to distinguish surface water and groundwater use. Moreover, we include a new irrigation scheme, which works dynamically with a daily surface and soil water balance, and incorporate the newly available extensive global reservoir data set (GRanD). Simulated surface water and groundwater withdrawals generally show good agreement with reported national and sub-national statistics. The results show a consistent increase in both surface water and groundwater use worldwide, with a more rapid increase in groundwater use since the 1990s. Human impacts on terrestrial water storage (TWS) signals are evident, altering the seasonal and inter-annual variability. This alteration is particularly large over heavily regulated basins such as the Colorado and the Columbia, and over the major irrigated basins such as the Mississippi, the Indus, and the Ganges. Including human water use and associated reservoir operations generally improves the correlation of simulated TWS anomalies with those of the GRACE observations.

Auditory Mechanics of the Tectorial Membrane and the Cochlear Spiral

PubMed Central

Gavara, Núria; Manoussaki, Daphne; Chadwick, Richard S.

2012-01-01

Purpose of review This review is timely and relevant since new experimental and theoretical findings suggest that cochlear mechanics from the nanoscale to the macroscale are affected by mechanical properties of the tectorial membrane and the spiral shape. Recent findings Main tectorial membrane themes covered are i) composition and morphology, ii) nanoscale mechanical interactions with the outer hair cell bundle, iii) macroscale longitudinal coupling, iv) fluid interaction with inner hair cell bundles, v) macroscale dynamics and waves. Main cochlear spiral themes are macroscale low-frequency energy focusing and microscale organ of Corti shear gain. Implications Findings from new experimental and theoretical models reveal exquisite sensitivity of cochlear mechanical performance to tectorial membrane structural organization, mechanics, and its positioning with respect to hair bundles. The cochlear spiral geometry is a major determinant of low frequency hearing. Suggestions are made for future research directions. PMID:21785353

Determination of macro-scale soil properties from pore-scale structures: model derivation.

PubMed

Daly, K R; Roose, T

2018-01-01

In this paper, we use homogenization to derive a set of macro-scale poro-elastic equations for soils composed of rigid solid particles, air-filled pore space and a poro-elastic mixed phase. We consider the derivation in the limit of large deformation and show that by solving representative problems on the micro-scale we can parametrize the macro-scale equations. To validate the homogenization procedure, we compare the predictions of the homogenized equations with those of the full equations for a range of different geometries and material properties. We show that the results differ by [Formula: see text] for all cases considered. The success of the homogenization scheme means that it can be used to determine the macro-scale poro-elastic properties of soils from the underlying structure. Hence, it will prove a valuable tool in both characterization and optimization.

A systematic multiscale modeling and experimental approach to protect grain boundaries in magnesium alloys from corrosion

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

Horstemeyer, Mark R.; Chaudhuri, Santanu

2015-09-30

A multiscale modeling Internal State Variable (ISV) constitutive model was developed that captures the fundamental structure-property relationships. The macroscale ISV model used lower length scale simulations (Butler-Volmer and Electronics Structures results) in order to inform the ISVs at the macroscale. The chemomechanical ISV model was calibrated and validated from experiments with magnesium (Mg) alloys that were investigated under corrosive environments coupled with experimental electrochemical studies. Because the ISV chemomechanical model is physically based, it can be used for other material systems to predict corrosion behavior. As such, others can use the chemomechanical model for analyzing corrosion effects on their designs.

Improving Forecasts of Cumulus: An Intersection of the Renewable Energy and Climate Science Communities

NASA Astrophysics Data System (ADS)

Berg, L. K.; Gustafson, W. I., Jr.; Kassianov, E.; Long, C. N.

2015-12-01

Accurate forecasts of broken cloud fields and their associated impact on the downwelling solar irradiance has remained a challenge to the renewable energy industry. Likewise, shallow cumulus play an important role in the Earth's radiation budget and hydrologic cycle and are of interest to the weather forecasting and climate science communities. The main challenge associated with predicting these clouds are their relatively small size (on the order of a kilometer or less) relative to the model grid spacing. Recently, however, there have been significant efforts put into improving forecasts of shallow clouds and the associated temporal and spatial variability of the solar irradiance that they induce. As an example of these efforts, we will describe recent modifications to the standard Kain-Fritsch parameterization as applied within the Weather Research and Forecasting (WRF) model that are designed to improve predictions of the macroscale and microscale structure of shallow cumulus. These modifications are shown to lead to a realistic increase in the simulated cloud fraction and associated decrease in the solar irradiance. We will evaluate our results using data collected at the Department of Energy's Atmospheric Radiation Measurement (ARM) Southern Great Plains site, which is located in north-central Oklahoma. Our team has analyzed over 5 years of data collected at this site to document the macroscale structure of the clouds (including cloud fraction, cloud-base and cloud-top height) as well as their impact on the downwelling shortwave and longwave irradiance. One particularly interesting impact of shallow cumuli is the enhancement of the diffuse radiation, such that during periods in which the sun is not blocked, the observed irradiance can be significantly larger than the corresponding clear sky case. To date, this feature is not accurately represented by models that apply the plane-parallel assumption applied in the standard radiation parameterizations.

Landslide Hazard Probability Derived from Inherent and Dynamic Determinants

NASA Astrophysics Data System (ADS)

Strauch, Ronda; Istanbulluoglu, Erkan

2016-04-01

Landslide hazard research has typically been conducted independently from hydroclimate research. We unify these two lines of research to provide regional scale landslide hazard information for risk assessments and resource management decision-making. Our approach combines an empirical inherent landslide probability with a numerical dynamic probability, generated by combining routed recharge from the Variable Infiltration Capacity (VIC) macro-scale land surface hydrologic model with a finer resolution probabilistic slope stability model run in a Monte Carlo simulation. Landslide hazard mapping is advanced by adjusting the dynamic model of stability with an empirically-based scalar representing the inherent stability of the landscape, creating a probabilistic quantitative measure of geohazard prediction at a 30-m resolution. Climatology, soil, and topography control the dynamic nature of hillslope stability and the empirical information further improves the discriminating ability of the integrated model. This work will aid resource management decision-making in current and future landscape and climatic conditions. The approach is applied as a case study in North Cascade National Park Complex, a rugged terrain with nearly 2,700 m (9,000 ft) of vertical relief, covering 2757 sq km (1064 sq mi) in northern Washington State, U.S.A.

Multi-scale streamflow variability responses to precipitation over the headwater catchments in southern China

NASA Astrophysics Data System (ADS)

Niu, Jun; Chen, Ji; Wang, Keyi; Sivakumar, Bellie

2017-08-01

This paper examines the multi-scale streamflow variability responses to precipitation over 16 headwater catchments in the Pearl River basin, South China. The long-term daily streamflow data (1952-2000), obtained using a macro-scale hydrological model, the Variable Infiltration Capacity (VIC) model, and a routing scheme, are studied. Temporal features of streamflow variability at 10 different timescales, ranging from 6 days to 8.4 years, are revealed with the Haar wavelet transform. The principal component analysis (PCA) is performed to categorize the headwater catchments with the coherent modes of multi-scale wavelet spectra. The results indicate that three distinct modes, with different variability distributions at small timescales and seasonal scales, can explain 95% of the streamflow variability. A large majority of the catchments (i.e. 12 out of 16) exhibit consistent mode feature on multi-scale variability throughout three sub-periods (1952-1968, 1969-1984, and 1985-2000). The multi-scale streamflow variability responses to precipitation are identified to be associated with the regional flood and drought tendency over the headwater catchments in southern China.

Regionalization of meso-scale physically based nitrogen modeling outputs to the macro-scale by the use of regression trees

NASA Astrophysics Data System (ADS)

Künne, A.; Fink, M.; Kipka, H.; Krause, P.; Flügel, W.-A.

2012-06-01

In this paper, a method is presented to estimate excess nitrogen on large scales considering single field processes. The approach was implemented by using the physically based model J2000-S to simulate the nitrogen balance as well as the hydrological dynamics within meso-scale test catchments. The model input data, the parameterization, the results and a detailed system understanding were used to generate the regression tree models with GUIDE (Loh, 2002). For each landscape type in the federal state of Thuringia a regression tree was calibrated and validated using the model data and results of excess nitrogen from the test catchments. Hydrological parameters such as precipitation and evapotranspiration were also used to predict excess nitrogen by the regression tree model. Hence they had to be calculated and regionalized as well for the state of Thuringia. Here the model J2000g was used to simulate the water balance on the macro scale. With the regression trees the excess nitrogen was regionalized for each landscape type of Thuringia. The approach allows calculating the potential nitrogen input into the streams of the drainage area. The results show that the applied methodology was able to transfer the detailed model results of the meso-scale catchments to the entire state of Thuringia by low computing time without losing the detailed knowledge from the nitrogen transport modeling. This was validated with modeling results from Fink (2004) in a catchment lying in the regionalization area. The regionalized and modeled excess nitrogen correspond with 94%. The study was conducted within the framework of a project in collaboration with the Thuringian Environmental Ministry, whose overall aim was to assess the effect of agro-environmental measures regarding load reduction in the water bodies of Thuringia to fulfill the requirements of the European Water Framework Directive (Bäse et al., 2007; Fink, 2006; Fink et al., 2007).

Dynamic Data-Driven Reduced-Order Models of Macroscale Quantities for the Prediction of Equilibrium System State for Multiphase Porous Medium Systems

NASA Astrophysics Data System (ADS)

Talbot, C.; McClure, J. E.; Armstrong, R. T.; Mostaghimi, P.; Hu, Y.; Miller, C. T.

2017-12-01

Microscale simulation of multiphase flow in realistic, highly-resolved porous medium systems of a sufficient size to support macroscale evaluation is computationally demanding. Such approaches can, however, reveal the dynamic, steady, and equilibrium states of a system. We evaluate methods to utilize dynamic data to reduce the cost associated with modeling a steady or equilibrium state. We construct data-driven models using extensions to dynamic mode decomposition (DMD) and its connections to Koopman Operator Theory. DMD and its variants comprise a class of equation-free methods for dimensionality reduction of time-dependent nonlinear dynamical systems. DMD furnishes an explicit reduced representation of system states in terms of spatiotemporally varying modes with time-dependent oscillation frequencies and amplitudes. We use DMD to predict the steady and equilibrium macroscale state of a realistic two-fluid porous medium system imaged using micro-computed tomography (µCT) and simulated using the lattice Boltzmann method (LBM). We apply Koopman DMD to direct numerical simulation data resulting from simulations of multiphase fluid flow through a 1440x1440x4320 section of a full 1600x1600x5280 realization of imaged sandstone. We determine a representative set of system observables via dimensionality reduction techniques including linear and kernel principal component analysis. We demonstrate how this subset of macroscale quantities furnishes a representation of the time-evolution of the system in terms of dynamic modes, and discuss the selection of a subset of DMD modes yielding the optimal reduced model, as well as the time-dependence of the error in the predicted equilibrium value of each macroscale quantity. Finally, we describe how the above procedure, modified to incorporate methods from compressed sensing and random projection techniques, may be used in an online fashion to facilitate adaptive time-stepping and parsimonious storage of system states over time.

Three centuries of dual pressure from land use and climate change on the biosphere

NASA Astrophysics Data System (ADS)

Ostberg, Sebastian; Schaphoff, Sibyll; Lucht, Wolfgang; Gerten, Dieter

2015-04-01

Human land use and anthropogenic climate change (CC) are placing mounting pressure on natural ecosystems worldwide, with impacts on biodiversity, water resources, nutrient and carbon cycles. Here, we present a quantitative macro-scale comparative analysis of the separate and joint dual impacts of land use and land cover change (LULCC) and CC on the terrestrial biosphere during the last ca. 300 years, based on simulations with a dynamic global vegetation model and an aggregated metric of simultaneous biogeochemical, hydrological and vegetation-structural shifts. We find that by the beginning of the 21st century LULCC and CC have jointly caused major shifts on more than 90% of all areas now cultivated, corresponding to 26% of the land area. CC has exposed another 26% of natural ecosystems to moderate or major shifts. Within three centuries, the impact of LULCC on landscapes has increased 13-fold. Within just one century, CC effects have caught up with LULCC effects.

Molecular shear heating and vortex dynamics in thermostatted two dimensional Yukawa liquids

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

Gupta, Akanksha; Ganesh, Rajaraman, E-mail: ganesh@ipr.res.in; Joy, Ashwin

2016-07-15

It is well known that two-dimensional macroscale shear flows are susceptible to instabilities leading to macroscale vortical structures. The linear and nonlinear fate of such a macroscale flow in a strongly coupled medium is a fundamental problem. A popular example of a strongly coupled medium is a dusty plasma, often modelled as a Yukawa liquid. Recently, laboratory experiments and molecular dynamics (MD) studies of shear flows in strongly coupled Yukawa liquids indicated the occurrence of strong molecular shear heating, which is found to reduce the coupling strength exponentially leading to the destruction of macroscale vorticity. To understand the vortex dynamicsmore » of strongly coupled molecular fluids undergoing macroscale shear flows and molecular shear heating, MD simulation has been performed, which allows the macroscopic vortex dynamics to evolve, while at the same time “removes” the microscopically generated heat without using the velocity degrees of freedom. We demonstrate that by using a configurational thermostat in a novel way, the microscale heat generated by shear flow can be thermostatted out efficiently without compromising the large scale vortex dynamics. In the present work, using MD simulations, a comparative study of shear flow evolution in Yukawa liquids in the presence and absence of molecular or microscopic heating is presented for a prototype shear flow, namely, Kolmogorov flow.« less

Development of Joint Climate and Discharge Projections for the International Rhine River Basin - the CHR RheinBlick2050 Project

NASA Astrophysics Data System (ADS)

Görgen, K.; Pfister, L.

2008-12-01

The anticipated climate change will lead to modified hydro-meteorological regimes that influence discharge behaviour and hydraulics of rivers. This has variable impacts on managed (anthropogenic) and unmanaged (natural) systems, depending on their sensitivity and vulnerability (ecology, economy, infrastructure, transport, energy production, water management, etc.). Decision makers in these contexts need adequate adaptation strategies to minimize adverse effects of climate change, i.e. an improved knowledge on the potential impacts including uncertainties means an extension of the informed options open to users. The goal of the highly applied study presented here is the development of joint, consistent climate and discharge projections for the international Rhine River catchments (Switzerland, France, Germany, Netherlands) in order to assess future changes of hydro-meteorological regimes in the meso- and macroscale Rhine River catchments and to derive and improve the understanding of such impacts on hydrologic and hydraulic processes. The RheinBlick2050 project is an international effort initiated by the International Commission for the Hydrology of the Rhine Basin (CHR) in close cooperation with the International Commission for the Protection of the Rhine. The core experiment design foresees a data-synthesis, multi-model approach where (transient) (bias- corrected) regional climate change projections are used as forcing data for existing calibrated hydrological (and hydraulic) models at a daily temporal resolution over mesoscale catchments of the Rhine River. Mainly for validation purposes, hydro-meteorological observations from national weather services are compiled into a new consistent 5 km x 5 km reference dataset from 1961 to 2005. RCM data are mainly used from the ENSEMBLES project and other existing dynamical downscaling model runs to derive probabilistic ensembles and thereby also access uncertainties on a regional scale. A benchmarking is helping to identify those atmospheric forcing data that ideally suit the needs for the subsequent hydrological model runs with the LARSIM and HBV models and evaluate those simulations too. As a result, usable information and quantifiable statements (e.g. extreme value statistics, uncertainty assessment, validation), that might form the basis for further planning or policy relevant decisions, are to be derived. Our analyses are highly influenced by the requirements of the potential users and stakeholders from government agencies who shall make use of the data and results. Here we present first results of the application of the complete data processing and modelling chain towards discharge projections on a subset of input data, albeit still without any bias correction applied to the meteorological forcing data.

Computational Design of Materials: Planetary Entry to Electric Aircraft and Beyond

NASA Technical Reports Server (NTRS)

Thompson, Alexander; Lawson, John W.

2014-01-01

NASA's projects and missions push the bounds of what is possible. To support the agency's work, materials development must stay on the cutting edge in order to keep pace. Today, researchers at NASA Ames Research Center perform multiscale modeling to aid the development of new materials and provide insight into existing ones. Multiscale modeling enables researchers to determine micro- and macroscale properties by connecting computational methods ranging from the atomic level (density functional theory, molecular dynamics) to the macroscale (finite element method). The output of one level is passed on as input to the next level, creating a powerful predictive model.

Impacts on Water Management and Crop Production of Regional Cropping System Adaptation to Climate Change

NASA Astrophysics Data System (ADS)

Zhong, H.; Sun, L.; Tian, Z.; Liang, Z.; Fischer, G.

2014-12-01

China is one of the most populous and fast developing countries, also faces a great pressure on grain production and food security. Multi-cropping system is widely applied in China to fully utilize agro-climatic resources and increase land productivity. As the heat resource keep improving under climate warming, multi-cropping system will also shifting northward, and benefit crop production. But water shortage in North China Plain will constrain the adoption of new multi-cropping system. Effectiveness of multi-cropping system adaptation to climate change will greatly depend on future hydrological change and agriculture water management. So it is necessary to quantitatively express the water demand of different multi-cropping systems under climate change. In this paper, we proposed an integrated climate-cropping system-crops adaptation framework, and specifically focused on: 1) precipitation and hydrological change under future climate change in China; 2) the best multi-cropping system and correspondent crop rotation sequence, and water demand under future agro-climatic resources; 3) attainable crop production with water constraint; and 4) future water management. In order to obtain climate projection and precipitation distribution, global climate change scenario from HADCAM3 is downscaled with regional climate model (PRECIS), historical climate data (1960-1990) was interpolated from more than 700 meteorological observation stations. The regional Agro-ecological Zone (AEZ) model is applied to simulate the best multi-cropping system and crop rotation sequence under projected climate change scenario. Finally, we use the site process-based DSSAT model to estimate attainable crop production and the water deficiency. Our findings indicate that annual land productivity may increase and China can gain benefit from climate change if multi-cropping system would be adopted. This study provides a macro-scale view of agriculture adaptation, and gives suggestions to national agriculture adaptation strategy decisions.

On the role of "internal variability" on soil erosion assessment

NASA Astrophysics Data System (ADS)

Kim, Jongho; Ivanov, Valeriy; Fatichi, Simone

2017-04-01

Empirical data demonstrate that soil loss is highly non-unique with respect to meteorological or even runoff forcing and its frequency distributions exhibit heavy tails. However, all current erosion assessments do not describe the large associated uncertainties of temporal erosion variability and make unjustified assumptions by relying on central tendencies. Thus, the predictive skill of prognostic models and reliability of national-scale assessments have been repeatedly questioned. In this study, we attempt to reveal that the high variability in soil losses can be attributed to two sources: (1) 'external variability' referring to the uncertainties originating at macro-scale, such as climate, topography, and land use, which has been extensively studied; (2) 'geomorphic internal variability' referring to the micro-scale variations of pedologic properties (e.g., surface erodibility in soils with multi-sized particles), hydrologic properties (e.g., soil structure and degree of saturation), and hydraulic properties (e.g., surface roughness and surface topography). Using data and a physical hydraulic, hydrologic, and erosion and sediment transport model, we show that the geomorphic internal variability summarized by spatio-temporal variability in surface erodibility properties is a considerable source of uncertainty in erosion estimates and represents an overlooked but vital element of geomorphic response. The conclusion is that predictive frameworks of soil erosion should embed stochastic components together with deterministic assessments, if they do not want to largely underestimate uncertainty. Acknowledgement: This study was supported by the Basic Science Research Program of the National Research Foundation of Korea funded by the Ministry of Education (2016R1D1A1B03931886).

Using Discrete Event Simulation for Programming Model Exploration at Extreme-Scale: Macroscale Components for the Structural Simulation Toolkit (SST).

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

Wilke, Jeremiah J; Kenny, Joseph P.

2015-02-01

Discrete event simulation provides a powerful mechanism for designing and testing new extreme- scale programming models for high-performance computing. Rather than debug, run, and wait for results on an actual system, design can first iterate through a simulator. This is particularly useful when test beds cannot be used, i.e. to explore hardware or scales that do not yet exist or are inaccessible. Here we detail the macroscale components of the structural simulation toolkit (SST). Instead of depending on trace replay or state machines, the simulator is architected to execute real code on real software stacks. Our particular user-space threading frameworkmore » allows massive scales to be simulated even on small clusters. The link between the discrete event core and the threading framework allows interesting performance metrics like call graphs to be collected from a simulated run. Performance analysis via simulation can thus become an important phase in extreme-scale programming model and runtime system design via the SST macroscale components.« less

Medium range flood forecasts at global scale

NASA Astrophysics Data System (ADS)

Voisin, N.; Wood, A. W.; Lettenmaier, D. P.; Wood, E. F.

2006-12-01

While weather and climate forecast methods have advanced greatly over the last two decades, this capability has yet to be evidenced in mitigation of water-related natural hazards (primarily floods and droughts), especially in the developing world. Examples abound of extreme property damage and loss of life due to floods in the underdeveloped world. For instance, more than 4.5 million people were affected by the July 2000 flooding of the Mekong River and its tributaries in Cambodia, Vietnam, Laos and Thailand. The February- March 2000 floods in the Limpopo River of Mozambique caused extreme disruption to that country's fledgling economy. Mitigation of these events through advance warning has typically been modest at best. Despite the above noted improvement in weather and climate forecasts, there is at present no system for forecasting of floods globally, notwithstanding that the potential clearly exists. We describe a methodology that is eventually intended to generate global flood predictions routinely. It draws heavily from the experimental North American Land Data Assimilation System (NLDAS) and the companion Global Land Data Assimilation System (GLDAS) for development of nowcasts, and the University of Washington Experimental Hydrologic Prediction System to develop ensemble hydrologic forecasts based on Numerical Weather Prediction (NWP) models which serve both as nowcasts (and hence reduce the need for in situ precipitation and other observations in parts of the world where surface networks are critically deficient) and provide forecasts for lead times as long as fifteen days. The heart of the hydrologic modeling system is the University of Washington/Princeton University Variable Infiltration Capacity (VIC) macroscale hydrology model. In the prototype (tested using retrospective data), VIC is driven globally up to the time of forecast with daily ERA40 precipitation (rescaled on a monthly basis to a station-based global climatology), ERA40 wind, and ERA40 average surface air temperature (with temperature ranges adjusted to a station-based climatology). In the retrospective forecasting mode, VIC is driven by global NCEP ensemble 15-day reforecasts provided by Tom Hamill (NOAA/ERL), bias corrected with respect to the adjusted ERA40 data and further downscaled spatially using higher spatial resolution Global Precipitation Climatology Project (GPCP) 1dd daily precipitation. Downward solar and longwave radiation, surface relative humidity, and other model forcings are derived from relationships with the daily temperature range during both the retrospective (spinup) and forecast period. The initial system is implemented globally at one-half degree spatial resolution. We evaluate model performance retrospectively for predictions of major floods for the Oder River in 1997, the Mekong River in 2000 and the Limpopo River in 2000.

Role of pseudo-turbulent stresses in shocked particle clouds and construction of surrogate models for closure

NASA Astrophysics Data System (ADS)

Sen, O.; Gaul, N. J.; Davis, S.; Choi, K. K.; Jacobs, G.; Udaykumar, H. S.

2018-05-01

Macroscale models of shock-particle interactions require closure terms for unresolved solid-fluid momentum and energy transfer. These comprise the effects of mean as well as fluctuating fluid-phase velocity fields in the particle cloud. Mean drag and Reynolds stress equivalent terms (also known as pseudo-turbulent terms) appear in the macroscale equations. Closure laws for the pseudo-turbulent terms are constructed in this work from ensembles of high-fidelity mesoscale simulations. The computations are performed over a wide range of Mach numbers ( M) and particle volume fractions (φ ) and are used to explicitly compute the pseudo-turbulent stresses from the Favre average of the velocity fluctuations in the flow field. The computed stresses are then used as inputs to a Modified Bayesian Kriging method to generate surrogate models. The surrogates can be used as closure models for the pseudo-turbulent terms in macroscale computations of shock-particle interactions. It is found that the kinetic energy associated with the velocity fluctuations is comparable to that of the mean flow—especially for increasing M and φ . This work is a first attempt to quantify and evaluate the effect of velocity fluctuations for problems of shock-particle interactions.

Role of pseudo-turbulent stresses in shocked particle clouds and construction of surrogate models for closure

NASA Astrophysics Data System (ADS)

Sen, O.; Gaul, N. J.; Davis, S.; Choi, K. K.; Jacobs, G.; Udaykumar, H. S.

2018-02-01

Macroscale models of shock-particle interactions require closure terms for unresolved solid-fluid momentum and energy transfer. These comprise the effects of mean as well as fluctuating fluid-phase velocity fields in the particle cloud. Mean drag and Reynolds stress equivalent terms (also known as pseudo-turbulent terms) appear in the macroscale equations. Closure laws for the pseudo-turbulent terms are constructed in this work from ensembles of high-fidelity mesoscale simulations. The computations are performed over a wide range of Mach numbers (M) and particle volume fractions (φ ) and are used to explicitly compute the pseudo-turbulent stresses from the Favre average of the velocity fluctuations in the flow field. The computed stresses are then used as inputs to a Modified Bayesian Kriging method to generate surrogate models. The surrogates can be used as closure models for the pseudo-turbulent terms in macroscale computations of shock-particle interactions. It is found that the kinetic energy associated with the velocity fluctuations is comparable to that of the mean flow—especially for increasing M and φ . This work is a first attempt to quantify and evaluate the effect of velocity fluctuations for problems of shock-particle interactions.

Data-Science Analysis of the Macro-scale Features Governing the Corrosion to Crack Transition in AA7050-T7451

NASA Astrophysics Data System (ADS)

Co, Noelle Easter C.; Brown, Donald E.; Burns, James T.

2018-05-01

This study applies data science approaches (random forest and logistic regression) to determine the extent to which macro-scale corrosion damage features govern the crack formation behavior in AA7050-T7451. Each corrosion morphology has a set of corresponding predictor variables (pit depth, volume, area, diameter, pit density, total fissure length, surface roughness metrics, etc.) describing the shape of the corrosion damage. The values of the predictor variables are obtained from white light interferometry, x-ray tomography, and scanning electron microscope imaging of the corrosion damage. A permutation test is employed to assess the significance of the logistic and random forest model predictions. Results indicate minimal relationship between the macro-scale corrosion feature predictor variables and fatigue crack initiation. These findings suggest that the macro-scale corrosion features and their interactions do not solely govern the crack formation behavior. While these results do not imply that the macro-features have no impact, they do suggest that additional parameters must be considered to rigorously inform the crack formation location.

Development of a Digital Aquifer Permeability Map for the ...

EPA Pesticide Factsheets

Researchers at the U.S. Environmental Protection Agency’s Western Ecology Division have been developing hydrologic landscape maps for selected U.S. states in an effort to create a method to identify the intrinsic watershed attributes of landscapes in regions with little data. Each hydrologic landscape unit is assigned a categorical value from five key indices of macro-scale hydrologic behavior, including annual climate, climate seasonality, aquifer permeability, terrain, and soil permeability. The aquifer permeability index requires creation of a from-scratch dataset for each state. The permeability index for the Pacific Southwest (California, Nevada, and Arizona) expands and modifies the permeability index for the Pacific Northwest (Oregon, Washington, and Idaho), which preceded it. The permeability index was created by assigning geologic map units to one of 18 categories with presumed similar values of permeability to create a hydrolithologic map. The hydrolithologies were then further categorized into permeability index classifications of high, low, unknown and surface water. Unconsolidated, carbonate, volcanic, and undifferentiated units are classified more conservatively to better address uncertainty in source data. High vs. low permeability classifications are assigned qualitatively but follow a threshold guideline of 8.5x10-2 m/day hydraulic conductivity. Estimates of permeability from surface lithology is the current best practice for broad-sca

Multiscale Modeling and Uncertainty Quantification for Nuclear Fuel Performance

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

Estep, Donald; El-Azab, Anter; Pernice, Michael

2017-03-23

In this project, we will address the challenges associated with constructing high fidelity multiscale models of nuclear fuel performance. We (*) propose a novel approach for coupling mesoscale and macroscale models, (*) devise efficient numerical methods for simulating the coupled system, and (*) devise and analyze effective numerical approaches for error and uncertainty quantification for the coupled multiscale system. As an integral part of the project, we will carry out analysis of the effects of upscaling and downscaling, investigate efficient methods for stochastic sensitivity analysis of the individual macroscale and mesoscale models, and carry out a posteriori error analysis formore » computed results. We will pursue development and implementation of solutions in software used at Idaho National Laboratories on models of interest to the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program.« less

The Critical Role of the Routing Scheme in Simulating Peak River Discharge in Global Hydrological Models

NASA Technical Reports Server (NTRS)

Zhao, Fang; Veldkamp, Ted I. E.; Frieler, Katja; Schewe, Jacob; Ostberg, Sebastian; Willner, Sven; Schauberger, Bernhard; Gosling, Simon N.; Schmied, Hannes Muller; Portmann, Felix T.;

Spatial distribution of diesel transit bus emissions and urban populations: implications of coincidence and scale on exposure.

PubMed

Gouge, Brian; Ries, Francis J; Dowlatabadi, Hadi

2010-09-15

Macroscale emissions modeling approaches have been widely applied in impact assessments of mobile source emissions. However, these approaches poorly characterize the spatial distribution of emissions and have been shown to underestimate emissions of some pollutants. To quantify the implications of these limitations on exposure assessments, CO, NO(X), and HC emissions from diesel transit buses were estimated at 50 m intervals along a bus rapid transit route using a microscale emissions modeling approach. The impacted population around the route was estimated using census, pedestrian count and transit ridership data. Emissions exhibited significant spatial variability. In intervals near major intersections and bus stops, emissions were 1.6-3.0 times higher than average. The coincidence of these emission hot spots and peaks in pedestrian populations resulted in a 20-40% increase in exposure compared to estimates that assumed homogeneous spatial distributions of emissions and/or populations along the route. An additional 19-30% increase in exposure resulted from the underestimate of CO and NO(X) emissions by macroscale modeling approaches. The results of this study indicate that macroscale modeling approaches underestimate exposure due to poor characterization of the influence of vehicle activity on the spatial distribution of emissions and total emissions.

From the Nano- to the Macroscale - Bridging Scales for the Moving Contact Line Problem

NASA Astrophysics Data System (ADS)

Nold, Andreas; Sibley, David; Goddard, Benjamin; Kalliadasis, Serafim; Complex Multiscale Systems Team

2016-11-01

The moving contact line problem remains an unsolved fundamental problem in fluid mechanics. At the heart of the problem is its multiscale nature: a nanoscale region close to the solid boundary where the continuum hypothesis breaks down, must be resolved before effective macroscale parameters such as contact line friction and slip can be obtained. To capture nanoscale properties very close to the contact line and to establish a link to the macroscale behaviour, we employ classical density-functional theory (DFT), in combination with extended Navier-Stokes-like equations. Using simple models for viscosity and slip at the wall, we compare our computations with the Molecular Kinetic Theory, by extracting the contact line friction, depending on the imposed temperature of the fluid. A key fluid property captured by DFT is the fluid layering at the wall-fluid interface, which has a large effect on the shearing properties of a fluid. To capture this crucial property, we propose an anisotropic model for the viscosity, which also allows us to scrutinize the effect of fluid layering on contact line friction.

A Generalized Subsurface Flow Parameterization Considering Subgrid Spatial Variability of Recharge and Topography

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

Huang, Maoyi; Liang, Xu; Leung, Lai R.

2008-12-05

Subsurface flow is an important hydrologic process and a key component of the water budget, especially in humid regions. In this study, a new subsurface flow formulation is developed that incorporates spatial variability of both topography and recharge. It is shown through theoretical derivation and case studies that the power law and exponential subsurface flow parameterizations and the parameterization proposed by Woods et al.[1997] are all special cases of the new formulation. The subsurface flows calculated using the new formulation compare well with values derived from observations at the Tulpehocken Creek and Walnut Creek watersheds. Sensitivity studies show that whenmore » the spatial variability of topography or recharge, or both is increased, the subsurface flows increase at the two aforementioned sites and the Maimai hillslope. This is likely due to enhancement of interactions between the groundwater table and the land surface that reduce the flow path. An important conclusion of this study is that the spatial variability of recharge alone, and/or in combination with the spatial variability of topography can substantially alter the behaviors of subsurface flows. This suggests that in macroscale hydrologic models or land surface models, subgrid variations of recharge and topography can make significant contributions to the grid mean subsurface flow and must be accounted for in regions with large surface heterogeneity. This is particularly true for regions with humid climate and relatively shallow groundwater table where the combined impacts of spatial variability of recharge and topography are shown to be more important. For regions with arid climate and relatively deep groundwater table, simpler formulations, especially the power law, for subsurface flow can work well, and the impacts of subgrid variations of recharge and topography may be ignored.« less

Analysis of the mechanical behavior of a titanium scaffold with a repeating unit-cell substructure.

PubMed

Ryan, Garrett; McGarry, Patrick; Pandit, Abhay; Apatsidis, Dimitrios

2009-08-01

Titanium scaffolds with controlled microarchitecture have been developed for load bearing orthopedic applications. The controlled microarchitecture refers to a repeating array of unit-cells, composed of sintered titanium powder, which make up the scaffold structure. The objective of this current research was to characterize the mechanical performance of three scaffolds with increasing porosity, using finite element analysis (FEA) and to compare the results with experimental data. Scaffolds were scanned using microcomputed tomography and FEA models were generated from the resulting computer models. Macroscale and unit-cell models of the scaffolds were created. The material properties of the sintered titanium powders were first evaluated in mechanical tests and the data used in the FEA. The macroscale and unit-cell FEA models proved to be a good predictor of Young's modulus and yield strength. Although macroscale models showed similar failure patterns and an expected trend in UCS, strain at UCS did not compare well with experimental data. Since a rapid prototyping method was used to create the scaffolds, the original CAD geometries of the scaffold were also evaluated using FEA but they did not reflect the mechanical properties of the physical scaffolds. This indicates that at present, determining the actual geometry of the scaffold through computed tomography imaging is important. Finally, a fatigue analysis was performed on the scaffold to simulate the loading conditions it would experience as a spinal interbody fusion device.

Micro- and macroscale coefficients of friction of cementitious materials

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

Lomboy, Gilson; Sundararajan, Sriram, E-mail: srirams@iastate.edu; Wang, Kejin

2013-12-15

Millions of metric tons of cementitious materials are produced, transported and used in construction each year. The ease or difficulty of handling cementitious materials is greatly influenced by the material friction properties. In the present study, the coefficients of friction of cementitious materials were measured at the microscale and macroscale. The materials tested were commercially-available Portland cement, Class C fly ash, and ground granulated blast furnace slag. At the microscale, the coefficient of friction was determined from the interaction forces between cementitious particles using an Atomic Force Microscope. At the macroscale, the coefficient of friction was determined from stresses onmore » bulk cementitious materials under direct shear. The study indicated that the microscale coefficient of friction ranged from 0.020 to 0.059, and the macroscale coefficient of friction ranged from 0.56 to 0.75. The fly ash studied had the highest microscale coefficient of friction and the lowest macroscale coefficient of friction. -- Highlights: •Microscale (interparticle) coefficient of friction (COF) was determined with AFM. •Macroscale (bulk) COF was measured under direct shear. •Fly ash had the highest microscale COF and the lowest macroscale COF. •Portland cement against GGBFS had the lowest microscale COF. •Portland cement against Portland cement had the highest macroscale COF.« less

Simulating the Snow Water Equivalent and its changing pattern over Nepal

NASA Astrophysics Data System (ADS)

Niroula, S.; Joseph, J.; Ghosh, S.

2016-12-01

Snow fall in the Himalayan region is one of the primary sources of fresh water, which accounts around 10% of total precipitation of Nepal. Snow water is an intricate variable in terms of its global and regional estimates whose complexity is favored by spatial variability linked with rugged topography. The study is primarily focused on simulation of Snow Water Equivalent (SWE) by the use of a macroscale hydrologic model, Variable Infiltration Capacity (VIC). As whole Nepal including its Himalayas lies under the catchment of Ganga River in India, contributing at least 40% of annual discharge of Ganges, this model was run in the entire watershed that covers part of Tibet and Bangladesh as well. Meteorological inputs for 29 years (1979-2007) are drawn from ERA-INTERIM and APHRODITE dataset for horizontal resolution of 0.25 degrees. The analysis was performed to study temporal variability of SWE in the Himalayan region of Nepal. The model was calibrated by observed stream flows of the tributaries of the Gandaki River in Nepal which ultimately feeds river Ganga. Further, the simulated SWE is used to estimate stream flow in this river basin. Since Nepal has a greater snow cover accumulation in monsoon season than in winter at high altitudes, seasonality fluctuations in SWE affecting the stream flows are known. The model provided fair estimates of SWE and stream flow as per statistical analysis. Stream flows are known to be sensitive to the changes in snow water that can bring a negative impact on power generation in a country which has huge hydroelectric potential. In addition, our results on simulated SWE in second largest snow-fed catchment of the country will be helpful for reservoir management, flood forecasting and other water resource management issues. Keywords: Hydrology, Snow Water Equivalent, Variable Infiltration Capacity, Gandaki River Basin, Stream Flow

Biology meets physics: Reductionism and multi-scale modeling of morphogenesis.

PubMed

Green, Sara; Batterman, Robert

2017-02-01

A common reductionist assumption is that macro-scale behaviors can be described "bottom-up" if only sufficient details about lower-scale processes are available. The view that an "ideal" or "fundamental" physics would be sufficient to explain all macro-scale phenomena has been met with criticism from philosophers of biology. Specifically, scholars have pointed to the impossibility of deducing biological explanations from physical ones, and to the irreducible nature of distinctively biological processes such as gene regulation and evolution. This paper takes a step back in asking whether bottom-up modeling is feasible even when modeling simple physical systems across scales. By comparing examples of multi-scale modeling in physics and biology, we argue that the "tyranny of scales" problem presents a challenge to reductive explanations in both physics and biology. The problem refers to the scale-dependency of physical and biological behaviors that forces researchers to combine different models relying on different scale-specific mathematical strategies and boundary conditions. Analyzing the ways in which different models are combined in multi-scale modeling also has implications for the relation between physics and biology. Contrary to the assumption that physical science approaches provide reductive explanations in biology, we exemplify how inputs from physics often reveal the importance of macro-scale models and explanations. We illustrate this through an examination of the role of biomechanical modeling in developmental biology. In such contexts, the relation between models at different scales and from different disciplines is neither reductive nor completely autonomous, but interdependent. Copyright © 2016 Elsevier Ltd. All rights reserved.

Turbulence modeling and combustion simulation in porous media under high Peclet number

NASA Astrophysics Data System (ADS)

Moiseev, Andrey A.; Savin, Andrey V.

2018-05-01

Turbulence modelling in porous flows and burning still remains not completely clear until now. Undoubtedly, conventional turbulence models must work well under high Peclet numbers when porous channels shape is implemented in details. Nevertheless, the true turbulent mixing takes place at micro-scales only, and the dispersion mixing works at macro-scales almost independent from true turbulence. The dispersion mechanism is characterized by the definite space scale (scale of the porous structure) and definite velocity scale (filtration velocity). The porous structure is stochastic one usually, and this circumstance allows applying the analogy between space-time-stochastic true turbulence and the dispersion flow which is stochastic in space only, when porous flow is simulated at the macro-scale level. Additionally, the mentioned analogy allows applying well-known turbulent combustion models in simulations of porous combustion under high Peclet numbers.

Effects of Climate Change on Extreme Streamflow Risks in the Olympic National Park

NASA Astrophysics Data System (ADS)

Tohver, I. M.; Lee, S.; Hamlet, A.

2011-12-01

Conventionally, natural resource management practices are designed within the framework that past conditions serve as a baseline for future conditions. However, the warmer future climate projected for the Pacific Northwest will alter the region's flood and low flow risks, posing considerable challenges to resource managers in the Olympic National Forest (ONF) and Olympic National Park (ONP). Shifts in extreme streamflow will influence two key management objectives in the ONF and ONP: the protection of wildlife and the maintenance of road infrastructure. The ONF is charged with managing habitat for species listed under the Endangered Species Act (ESA), and with maintaining the network of forest roads and culverts. Climate-induced increases in flood severity will introduce additional challenges in road and culvert design. Furthermore, the aging road infrastructure and more extreme summer low flows will compromise aquatic habitats, intrinsic to the health of threatened and endangered fish species listed under the ESA. Current practice uses estimates of Q100 (or the peak flow with an estimated 100 year return frequency) as the standard metric for stream crossing design. Simple regression models relating annual precipitation and basin area to Q100 are used in the design process. Low flow estimates are based on historical streamflow data to calculate the 7-day consecutive lowest flow with a 10-year return interval, or 7Q10. Under the projections a changing climate, these methods for estimating extreme flows are ill equipped to capture the complex and spatially varying effects of seasonal changes in temperature, precipitation, and snowpack on extreme flow risk. As an alternative approach, this study applies a physically-based hydrologic model to estimate historical and future flood risk at 1/16th degree (latitude/longitude) resolution (about 32 km2). We downscaled climate data derived from 10 global climate models to use as input for the Variable Infiltration Capacity (VIC) model, a macro-scale hydrologic model, which simulates various hydrologic variables at a daily time step. Using the VIC estimates for baseflow and run-off, we calculated Q100 and 7Q10 for the historical period and under two emission scenarios, A1B and B1, at three future time intervals: the 2020s, the 2040s and the 2080s. We also calculated Q100 and 7Q10 at the spatial scale of the 12-digit hydrologic unit codes (HUCs) as delineated by the United States Geologic Survey. The results demonstrate the sensitivity of snowpack at mid-elevation basins to a warmer climate, resulting in more severe winter flooding and lower streamflows in the summertime. These ensemble estimates of extreme streamflows will serve as a tool for management practices by providing high-resolution maps of changing risk over the ONF and ONP.

Tracking interface and common curve dynamics for two-fluid flow in porous media

DOE PAGES

Mcclure, James E.; Miller, Cass T.; Gray, W. G.; ...

2016-04-29

Pore-scale studies of multiphase flow in porous medium systems can be used to understand transport mechanisms and quantitatively determine closure relations that better incorporate microscale physics into macroscale models. Multiphase flow simulators constructed using the lattice Boltzmann method provide a means to conduct such studies, including both the equilibrium and dynamic aspects. Moving, storing, and analyzing the large state space presents a computational challenge when highly-resolved models are applied. We present an approach to simulate multiphase flow processes in which in-situ analysis is applied to track multiphase flow dynamics at high temporal resolution. We compute a comprehensive set of measuresmore » of the phase distributions and the system dynamics, which can be used to aid fundamental understanding and inform closure relations for macroscale models. The measures computed include microscale point representations and macroscale averages of fluid saturations, the pressure and velocity of the fluid phases, interfacial areas, interfacial curvatures, interface and common curve velocities, interfacial orientation tensors, phase velocities and the contact angle between the fluid-fluid interface and the solid surface. Test cases are studied to validate the approach and illustrate how measures of system state can be obtained and used to inform macroscopic theory.« less

Integrated Modeling to Assess the Impacts of Changes in Climate and Socio Economics on Agriculture in the Columbia River Basin

NASA Astrophysics Data System (ADS)

Rajagopalan, K.; Chinnayakanahalli, K.; Adam, J. C.; Malek, K.; Nelson, R.; Stockle, C.; Brady, M.; Dinesh, S.; Barber, M. E.; Yorgey, G.; Kruger, C.

2012-12-01

The objective of this work is to assess the impacts of climate change and socio economics on agriculture in the Columbia River basin (CRB) in the Pacific Northwest region of the U.S. and a portion of Southwestern Canada. The water resources of the CRB are managed to satisfy multiple objectives including agricultural withdrawal, which is the largest consumptive user of CRB water with 14,000 square kilometers of irrigated area. Agriculture is an important component of the region's economy, with an annual value over 5 billion in Washington State alone. Therefore, the region is relevant for applying a modeling framework that can aid agriculture decision making in the context of a changing climate. To do this, we created an integrated biophysical and socio-economic regional modeling framework that includes human and natural systems. The modeling framework captures the interactions between climate, hydrology, crop growth dynamics, water management and socio economics. The biophysical framework includes a coupled macro-scale physically-based hydrology model (the Variable Infiltration Capacity, VIC model), and crop growth model (CropSyst), as well as a reservoir operations simulation model. Water rights data and instream flow target requirements are also incorporated in the model to simulate the process of curtailment during water shortage. The economics model informs the biophysical model of the short term agricultural producer response to water shortage as well as the long term agricultural producer response to domestic growth and international trade in terms of an altered cropping pattern. The modeling framework was applied over the CRB for the historical period 1976-2006 and compared to a future 30-year period centered on the 2030s. Impacts of climate change on irrigation water availability, crop irrigation demand, frequency of curtailment, and crop yields are quantified and presented. Sensitivity associated with estimates of water availability, irrigation demand, crop yields, unmet demand and available instream flows due to climate inputs, hydrology and crop model parameterization, water management assumptions, model integration assumptions, as well as multiple socio economic alternatives are also presented. Compared to historical conditions, for the 2030s time period, our results show an average additional irrigation water demand requirement of 370 million cubic meters in the CRB, an increased frequency of curtailment and a revenue impact between 70 and $150 million resulting from adverse crop yield impacts due to curtailment in the state of Washington. The impacts vary spatially and some of the CRB tributary watersheds are impacted more than others, e.g., unmet demand in the Yakima River basin is expected to increase by 50%. Increased irrigation demand, coupled with decreased seasonal supply poses difficult water resources management questions in the region.

Numerical study of multiscale compaction-initiated detonation

NASA Astrophysics Data System (ADS)

Gambino, J. R.; Schwendeman, D. W.; Kapila, A. K.

2018-02-01

A multiscale model of heterogeneous condensed-phase explosives is examined computationally to determine the course of transient events following the application of a piston-driven stimulus. The model is a modified version of that introduced by Gonthier (Combust Sci Technol 175(9):1679-1709, 2003. https://doi.org/10.1080/00102200302373) in which the explosive is treated as a porous, compacting medium at the macro-scale and a collection of closely packed spherical grains capable of undergoing reaction and diffusive heat transfer at the meso-scale. A separate continuum description is ascribed to each scale, and the two scales are coupled together in an energetically consistent manner. Following piston-induced compaction, localized energy deposition at the sites of intergranular contact creates hot spots where reaction begins preferentially. Reaction progress at the macro-scale is determined by the spatial average of that at the grain scale. A parametric study shows that combustion at the macro-scale produces an unsteady detonation with a cyclical character, in which the lead shock loses strength and is overtaken by a stronger secondary shock generated in the partially reacted material behind it. The secondary shock in turn becomes the new lead shock and the process repeats itself.

Methane Emissions From Western Siberian Wetlands: Heterogeneity and Sensitivity to Climate Change

NASA Astrophysics Data System (ADS)

Bohn, T. J.; Lettenmaier, D. P.; Podest, E.; McDonald, K. C.; Sathulur, K.; Bowling, L. C.; Friborg, T.

2007-12-01

Prediction of methane emissions from high-latitude wetlands is important given concerns about their sensitivity to a warming climate. As a basis for prediction of wetland methane emissions at regional scales, we have coupled the Variable Infiltration Capacity macroscale hydrological model (VIC) with the Biosphere-Energy-Transfer- Hydrology terrestrial ecosystem model (BETHY) and a wetland methane emissions model to make large-scale estimates of methane emissions as a function of soil temperature, water table depth, and net primary productivity (NPP), with a parameterization of the sub-grid heterogeneity of the water table depth based on topographic wetness index. Using landcover classifications derived from L-band satellite synthetic aperture radar imagery, we simulated methane emissions for the Chaya River basin in western Siberia, an area that includes the Bakchar Bog, for a retrospective baseline period of 1980-1999, and evaluated their sensitivity to increases in temperature of 0-5 °C and increases in precipitation of 0-15%. The interactions of temperature and precipitation, through their effects on the water table depth, play an important role in determining methane emissions from these wetlands. The balance between these effects varies spatially, and their net effect depends in part on sub- grid topographic heterogeneity. Higher temperatures alone increase methane production in saturated areas, but cause those saturated areas to shrink in extent, resulting in a net reduction in methane emissions. Higher precipitation alone raises water tables and expands the saturated area, resulting in a net increase in methane emissions. Combining a temperature increase of 3 °C and an increase of 10% in precipitation, to represent the climate conditions likely in western Siberia at the end of this century, results in roughly a doubling of annual methane emissions. This work was carried out at the University of Washington, at Purdue University, and at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

Bottom-up modeling of damage in heterogeneous quasi-brittle solids

NASA Astrophysics Data System (ADS)

Rinaldi, Antonio

2013-03-01

The theoretical modeling of multisite cracking in quasi-brittle materials is a complex damage problem, hard to model with traditional methods of fracture mechanics due to its multiscale nature and to strain localization induced by microcracks interaction. Macroscale "effective" elastic models can be conveniently applied if a suitable Helmholtz free energy function is identified for a given material scenario. Del Piero and Truskinovsky (Continuum Mech Thermodyn 21:141-171, 2009), among other authors, investigated macroscale continuum solutions capable of matching—in a top-down view—the phenomenology of the damage process for quasi-brittle materials regardless of the microstructure. On the contrary, this paper features a physically based solution method that starts from the direct consideration of the microscale properties and, in a bottom-up view, recovers a continuum elastic description. This procedure is illustrated for a simple one-dimensional problem of this type, a bar modeled stretched by an axial displacement, where the bar is modeled as a 2D random lattice of decohesive spring elements of finite strength. The (microscale) data from simulations are used to identify the "exact" (macro-) damage parameter and to build up the (macro-) Helmholtz function for the equivalent elastic model, bridging the macroscale approach by Del Piero and Truskinovsky. The elastic approach, coupled with microstructural knowledge, becomes a more powerful tool to reproduce a broad class of macroscopic material responses by changing the convexity-concavity of the Helmholtz energy. The analysis points out that mean-field statistics are appropriate prior to damage localization but max-field statistics are better suited in the softening regime up to failure, where microstrain fluctuation needs to be incorporated in the continuum model. This observation is of consequence to revise mean-field damage models from literature and to calibrate Nth gradient continuum models.

A grain boundary damage model for delamination

NASA Astrophysics Data System (ADS)

Messner, M. C.; Beaudoin, A. J.; Dodds, R. H.

2015-07-01

Intergranular failure in metallic materials represents a multiscale damage mechanism: some feature of the material microstructure triggers the separation of grain boundaries on the microscale, but the intergranular fractures develop into long cracks on the macroscale. This work develops a multiscale model of grain boundary damage for modeling intergranular delamination—a failure of one particular family of grain boundaries sharing a common normal direction. The key feature of the model is a physically-consistent and mesh independent, multiscale scheme that homogenizes damage at many grain boundaries on the microscale into a single damage parameter on the macroscale to characterize material failure across a plane. The specific application of the damage framework developed here considers delamination failure in modern Al-Li alloys. However, the framework may be readily applied to other metals or composites and to other non-delamination interface geometries—for example, multiple populations of material interfaces with different geometric characteristics.

Multi-Scale Modeling of Liquid Phase Sintering Affected by Gravity: Preliminary Analysis

NASA Technical Reports Server (NTRS)

Olevsky, Eugene; German, Randall M.

2012-01-01

A multi-scale simulation concept taking into account impact of gravity on liquid phase sintering is described. The gravity influence can be included at both the micro- and macro-scales. At the micro-scale, the diffusion mass-transport is directionally modified in the framework of kinetic Monte-Carlo simulations to include the impact of gravity. The micro-scale simulations can provide the values of the constitutive parameters for macroscopic sintering simulations. At the macro-scale, we are attempting to embed a continuum model of sintering into a finite-element framework that includes the gravity forces and substrate friction. If successful, the finite elements analysis will enable predictions relevant to space-based processing, including size and shape and property predictions. Model experiments are underway to support the models via extraction of viscosity moduli versus composition, particle size, heating rate, temperature and time.

Modeling non-equilibrium mass transport in biologically reactive porous media

NASA Astrophysics Data System (ADS)

Davit, Yohan; Debenest, Gérald; Wood, Brian D.; Quintard, Michel

2010-09-01

We develop a one-equation non-equilibrium model to describe the Darcy-scale transport of a solute undergoing biodegradation in porous media. Most of the mathematical models that describe the macroscale transport in such systems have been developed intuitively on the basis of simple conceptual schemes. There are two problems with such a heuristic analysis. First, it is unclear how much information these models are able to capture; that is, it is not clear what the model's domain of validity is. Second, there is no obvious connection between the macroscale effective parameters and the microscopic processes and parameters. As an alternative, a number of upscaling techniques have been developed to derive the appropriate macroscale equations that are used to describe mass transport and reactions in multiphase media. These approaches have been adapted to the problem of biodegradation in porous media with biofilms, but most of the work has focused on systems that are restricted to small concentration gradients at the microscale. This assumption, referred to as the local mass equilibrium approximation, generally has constraints that are overly restrictive. In this article, we devise a model that does not require the assumption of local mass equilibrium to be valid. In this approach, one instead requires only that, at sufficiently long times, anomalous behaviors of the third and higher spatial moments can be neglected; this, in turn, implies that the macroscopic model is well represented by a convection-dispersion-reaction type equation. This strategy is very much in the spirit of the developments for Taylor dispersion presented by Aris (1956). On the basis of our numerical results, we carefully describe the domain of validity of the model and show that the time-asymptotic constraint may be adhered to even for systems that are not at local mass equilibrium.

Shear behavior of thermoformed woven-textile thermoplastic prepregs: An analysis combining bias-extension test and X-ray microtomography

NASA Astrophysics Data System (ADS)

Gassoumi, M.; Rolland du Roscoat, S.; Casari, P.; Dumont, P. J. J.; Orgéas, L.; Jacquemin, F.

2017-10-01

Thermoforming allows the manufacture of structural parts for the automotive and aeronautical domains using long fiber thermoplastic prepregs with short cycle times. During this operation, several sheets of molten prepregs are stacked and subjected to large macroscale strains, mainly via in-plane shear, out-of-plane consolidation or dilatation, and bending of the fibrous reinforcement. These deformation modes and the related meso and microstructure evolutions are still poorly understood. However, they can drastically alter the end-use macroscale properties of fabricated parts. To better understand these phenomena, bias extension tests were performed using specimens made of several stacked layers of glass woven fabrics and polyamide matrix. The macroscale shear behavior of these prepregs was investigated at various temperatures. A multiscale analysis of deformed samples was performed using X-ray microtomography images of the deformed specimens acquired at two different spatial resolutions. The low-resolution images were used to analyze the deformation mechanisms and the structural characteristics of prepregs at the macroscale and bundle scales. It was possible to analyze the 3D shapes of deformed samples and, in particular, the spatial variations of their thickness so as to quantify the out-of-plane dilatancy or consolidation phenomena induced by the in-plane shear of prepregs. At a lower scale, the analysis of the high-resolution images showed that these mechanisms were accompanied by the growth of pores and the deformation of fiber bundles. The orientation of the fiber bundles and its through-thickness evolution were measured along the weft and warp directions in the deformed samples, allowing the relevance of geometrical models currently used to analyze bias extension tests to be discussed. Results can be used to enhance the current rheological models for the prediction of thermoforming of thermoplastic prepregs.

A novel physical eco-hydrological model concept for preferential flow based on experimental applications.

NASA Astrophysics Data System (ADS)

Jackisch, Conrad; van Schaik, Loes; Graeff, Thomas; Zehe, Erwin

2014-05-01

Preferential flow through macropores often determines hydrological characteristics - especially regarding runoff generation and fast transport of solutes. Macropore settings may yet be very different in nature and dynamics, depending on their origin. While biogenic structures follow activity cycles (e.g. earth worms) and population conditions (e.g. roots), pedogenic and geogenic structures may depend on water stress (e.g. cracks) or large events (e.g. flushed voids between skeleton and soil pipes) or simply persist (e.g. bedrock interface). On the one hand, such dynamic site characteristics can be observed in seasonal changes in its reaction to precipitation. On the other hand, sprinkling experiments accompanied by tracers or time-lapse 3D Ground-Penetrating-Radar are suitable tools to determine infiltration patterns and macropore configuration. However, model representation of the macropore-matrix system is still problematic, because models either rely on effective parameters (assuming well-mixed state) or on explicit advection strongly simplifying or neglecting interaction with the diffusive flow domain. Motivated by the dynamic nature of macropores, we present a novel model approach for interacting diffusive and advective water, solutes and energy transport in structured soils. It solely relies on scale- and process-aware observables. A representative set of macropores (data from sprinkling experiments) determines the process model scale through 1D advective domains. These are connected to a 2D matrix domain which is defined by pedo-physical retention properties. Water is represented as particles. Diffusive flow is governed by a 2D random walk of these particles while advection may take place in the macropore domain. Macropore-matrix interaction is computed as dissipation of the advective momentum of a particle by its experienced drag from the matrix domain. Through a representation of matrix and macropores as connected diffusive and advective domains for water transport we open up double domain concepts linking porescale physics to preferential macroscale fingerprints without effective parameterisation or mixing assumptions. Moreover, solute transport, energy balance aspects and lateral heterogeneity in soil moisture distribution are intrinsically captured. In addition, macropore and matrix domain settings may change over time based on physical and stochastic observations. The representativity concept allows scaleability from plotscale to the lower mesoscale.

Quantifying the impact of material-model error on macroscale quantities-of-interest using multiscale a posteriori error-estimation techniques

DOE PAGES

Brown, Judith A.; Bishop, Joseph E.

2016-07-20

An a posteriori error-estimation framework is introduced to quantify and reduce modeling errors resulting from approximating complex mesoscale material behavior with a simpler macroscale model. Such errors may be prevalent when modeling welds and additively manufactured structures, where spatial variations and material textures may be present in the microstructure. We consider a case where a <100> fiber texture develops in the longitudinal scanning direction of a weld. Transversely isotropic elastic properties are obtained through homogenization of a microstructural model with this texture and are considered the reference weld properties within the error-estimation framework. Conversely, isotropic elastic properties are considered approximatemore » weld properties since they contain no representation of texture. Errors introduced by using isotropic material properties to represent a weld are assessed through a quantified error bound in the elastic regime. Lastly, an adaptive error reduction scheme is used to determine the optimal spatial variation of the isotropic weld properties to reduce the error bound.« less

Scaling, soil moisture and evapotranspiration in runoff models

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1993-01-01

The effects of small-scale heterogeneity in land surface characteristics on the large-scale fluxes of water and energy in the land-atmosphere system has become a central focus of many of the climatology research experiments. The acquisition of high resolution land surface data through remote sensing and intensive land-climatology field experiments (like HAPEX and FIFE) has provided data to investigate the interactions between microscale land-atmosphere interactions and macroscale models. One essential research question is how to account for the small scale heterogeneities and whether 'effective' parameters can be used in the macroscale models. To address this question of scaling, the probability distribution for evaporation is derived which illustrates the conditions for which scaling should work. A correction algorithm that may appropriate for the land parameterization of a GCM is derived using a 2nd order linearization scheme. The performance of the algorithm is evaluated.

Modeling & processing of ceramic and polymer precursor ceramic matrix composite materials

NASA Astrophysics Data System (ADS)

Wang, Xiaolin

Synthesis and processing of novel materials with various advanced approaches have attracted much attention of engineers and scientists for the past thirty years. Many advanced materials display a number of exceptional properties and can be produced with different novel processing techniques. For example, AlN is a promising candidate for electronic, optical and opto-electronic applications due to its high thermal conductivity, high electrical resistivity, high acoustic wave velocity and large band gap. Large bulk AlN crystal can be produced by sublimation of AlN powder. Novel nonostructured multicomponent refractory metal-based ceramics (carbides, borides and nitrides) show a lot of exceptional mechanical, thermal and chemical properties, and can be easily produced by pyrolysis of suitable preceramic precursors mixed with metal particles. The objective of this work is to study sublimation and synthesis of AlN powder, and synthesis of SiC-based metal ceramics. For AlN sublimation crystal growth, we will focus on modeling the processes in the powder source that affect significantly the sublimation growth as a whole. To understand the powder porosity evolution and vapor transport during powder sublimation, the interplay between vapor transport and powder sublimation will be studied. A physics-based computational model will be developed considering powder sublimation and porosity evolution. Based on the proposed model, the effect of a central hole in the powder on the sublimation rate is studied and the result is compared to the case of powder without a hole. The effect of hole size on the sublimation rate will be studied. The effects of initial porosity, particle size and driving force on the sublimation rate are also studied. Moreover, the optimal growth condition for large diameter crystal quality and high growth rate will be determined. For synthesis of SiC-based metal ceramics, we will focus on developing a multi-scale process model to describe the dynamic behavior of filler particle reaction, microstructure evolution, at the microscale as well as transient fluid flow, heat transfer, and species transport at the macroscale. The model comprises of (i) a microscale model and (ii) a macroscale transport model, and aims to provide optimal conditions for the fabrication process of the ceramics. The porous media macroscale model for SiC-based metal-ceramic materials processing will be developed to understand the thermal polymer pyrolysis, chemical reaction of active fillers and transport phenomena in the porous media. The macroscale model will include heat and mass transfer, curing, pyrolysis, chemical reaction and crystallization in a mixture of preceramic polymers and submicron/nano-sized metal particles of uranium, zirconium, niobium, or hafnium. The effects of heating rate, sample size, size and volume ratio of the metal particles on the reaction rate and product uniformity will be studied. The microscale model will be developed for modeling the synthesis of SiC matrix and metal particles. The macroscale model provides thermal boundary conditions to the microscale model. The microscale model applies to repetitive units in the porous structure and describes mass transport, composition changes and motion of metal particles. The unit-cell is the representation unit of the source material, and it consists of several metal particles, SiC matrix and other components produced from the synthesis process. The reactions between different components, the microstructure evolution of the product will be considered. The effects of heating rate and metal particle size on species uniformity and microstructure are investigated.

What is the importance of climate model bias when projecting the impacts of climate change on land surface processes?

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

Liu, M. L.; Rajagopalan, K.; Chung, S. H.

2014-05-16

Regional climate change impact (CCI) studies have widely involved downscaling and bias-correcting (BC) Global Climate Model (GCM)-projected climate for driving land surface models. However, BC may cause uncertainties in projecting hydrologic and biogeochemical responses to future climate due to the impaired spatiotemporal covariance of climate variables and a breakdown of physical conservation principles. Here we quantify the impact of BC on simulated climate-driven changes in water variables(evapotranspiration, ET; runoff; snow water equivalent, SWE; and water demand for irrigation), crop yield, biogenic volatile organic compounds (BVOC), nitric oxide (NO) emissions, and dissolved inorganic nitrogen (DIN) export over the Pacific Northwest (PNW)more » Region. We also quantify the impacts on net primary production (NPP) over a small watershed in the region (HJ Andrews). Simulation results from the coupled ECHAM5/MPI-OM model with A1B emission scenario were firstly dynamically downscaled to 12 km resolutions with WRF model. Then a quantile mapping based statistical downscaling model was used to downscale them into 1/16th degree resolution daily climate data over historical and future periods. Two series climate data were generated according to the option of bias-correction (i.e. with bias-correction (BC) and without bias-correction, NBC). Impact models were then applied to estimate hydrologic and biogeochemical responses to both BC and NBC meteorological datasets. These im20 pact models include a macro-scale hydrologic model (VIC), a coupled cropping system model (VIC-CropSyst), an ecohydrologic model (RHESSys), a biogenic emissions model (MEGAN), and a nutrient export model (Global-NEWS). Results demonstrate that the BC and NBC climate data provide consistent estimates of the climate-driven changes in water fluxes (ET, runoff, and water demand), VOCs (isoprene and monoterpenes) and NO emissions, mean crop yield, and river DIN export over the PNW domain. However, significant differences rise from projected SWE, crop yield from dry lands, and HJ Andrews’s ET between BC and NBC data. Even though BC post-processing has no significant impacts on most of the studied variables when taking PNW as a whole, their effects have large spatial variations and some local areas are substantially influenced. In addition, there are months during which BC and NBC post-processing produces significant differences in projected changes, such as summer runoff. Factor-controlled simulations indicate that BC post-processing of precipitation and temperature both substantially contribute to these differences at region scales. We conclude that there are trade-offs between using BC climate data for offline CCI studies vs. direct modeled climate data. These trade-offs should be considered when designing integrated modeling frameworks for specific applications; e.g., BC may be more important when considering impacts on reservoir operations in mountainous watersheds than when investigating impacts on biogenic emissions and air quality (where VOCs are a primary indicator).« less

An new MHD/kinetic model for exploring energetic particle production in macro-scale systems

NASA Astrophysics Data System (ADS)

Drake, J. F.; Swisdak, M.; Dahlin, J. T.

2017-12-01

A novel MHD/kinetic model is being developed to explore magneticreconnection and particle energization in macro-scale systems such asthe solar corona and the outer heliosphere. The model blends the MHDdescription with a macro-particle description. The rationale for thismodel is based on the recent discovery that energetic particleproduction during magnetic reconnection is controlled by Fermireflection and Betatron acceleration and not parallel electricfields. Since the former mechanisms are not dependent on kineticscales such as the Debye length and the electron and ion inertialscales, a model that sheds these scales is sufficient for describingparticle acceleration in macro-systems. Our MHD/kinetic model includesmacroparticles laid out on an MHD grid that are evolved with the MHDfields. Crucially, the feedback of the energetic component on the MHDfluid is included in the dynamics. Thus, energy of the total system,the MHD fluid plus the energetic component, is conserved. The systemhas no kinetic scales and therefore can be implemented to modelenergetic particle production in macro-systems with none of theconstraints associated with a PIC model. Tests of the new model insimple geometries will be presented and potential applications will bediscussed.

Design-based modeling of magnetically actuated soft diaphragm materials

NASA Astrophysics Data System (ADS)

Jayaneththi, V. R.; Aw, K. C.; McDaid, A. J.

2018-04-01

Magnetic polymer composites (MPC) have shown promise for emerging biomedical applications such as lab-on-a-chip and implantable drug delivery. These soft material actuators are capable of fast response, large deformation and wireless actuation. Existing MPC modeling approaches are computationally expensive and unsuitable for rapid design prototyping and real-time control applications. This paper proposes a macro-scale 1-DOF model capable of predicting force and displacement of an MPC diaphragm actuator. Model validation confirmed both blocked force and displacement can be accurately predicted in a variety of working conditions i.e. different magnetic field strengths, static/dynamic fields, and gap distances. The contribution of this work includes a comprehensive experimental investigation of a macro-scale diaphragm actuator; the derivation and validation of a new phenomenological model to describe MPC actuation; and insights into the proposed model’s design-based functionality i.e. scalability and generalizability in terms of magnetic filler concentration and diaphragm diameter. Due to the lumped element modeling approach, the proposed model can also be adapted to alternative actuator configurations, and thus presents a useful tool for design, control and simulation of novel MPC applications.

Communication: Diverse nanoscale cluster dynamics: Diffusion of 2D epitaxial clusters

NASA Astrophysics Data System (ADS)

Lai, King C.; Evans, James W.; Liu, Da-Jiang

2017-11-01

The dynamics of nanoscale clusters can be distinct from macroscale behavior described by continuum formalisms. For diffusion of 2D clusters of N atoms in homoepitaxial systems mediated by edge atom hopping, macroscale theory predicts simple monotonic size scaling of the diffusion coefficient, DN ˜ N-β, with β = 3/2. However, modeling for nanoclusters on metal(100) surfaces reveals that slow nucleation-mediated diffusion displaying weak size scaling β < 1 occurs for "perfect" sizes Np = L2 and L(L+1) for integer L = 3,4,… (with unique square or near-square ground state shapes), and also for Np+3, Np+4,…. In contrast, fast facile nucleation-free diffusion displaying strong size scaling β ≈ 2.5 occurs for sizes Np+1 and Np+2. DN versus N oscillates strongly between the slowest branch (for Np+3) and the fastest branch (for Np+1). All branches merge for N = O(102), but macroscale behavior is only achieved for much larger N = O(103). This analysis reveals the unprecedented diversity of behavior on the nanoscale.

Computer modelling of cyclic deformation of high-temperature materials. Technical progress report, 16 November 1992-15 February 1993

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

Duesbery, M.S.

1993-02-26

This program aims at improving current methods of lifetime assessment by building in the characteristics of the micro-mechanisms known to be responsible for damage and failure. The broad approach entails the integration and, where necessary, augmentation of the micro-scale research results currently available in the literature into a macro-scale model with predictive capability. In more detail, the program will develop a set of hierarchically structured models at different length scales, from atomic to macroscopic, at each level taking as parametric input the results of the model at the next smaller scale. In this way the known microscopic properties can bemore » transported by systematic procedures to the unknown macro-scale region. It may not be possible to eliminate empiricism completely, because some of the quantities involved cannot yet be estimated to the required degree of precision. In this case the aim will be at least to eliminate functional empiricism.« less

Water condensation: a multiscale phenomenon.

PubMed

Jensen, Kasper Risgaard; Fojan, Peter; Jensen, Rasmus Lund; Gurevich, Leonid

2014-02-01

The condensation of water is a phenomenon occurring in multiple situations in everyday life, e.g., when fog is formed or when dew forms on the grass or on windows. This means that this phenomenon plays an important role within the different fields of science including meteorology, building physics, and chemistry. In this review we address condensation models and simulations with the main focus on heterogeneous condensation of water. The condensation process is, at first, described from a thermodynamic viewpoint where the nucleation step is described by the classical nucleation theory. Further, we address the shortcomings of the thermodynamic theory in describing the nucleation and emphasize the importance of nanoscale effects. This leads to the description of condensation from a molecular viewpoint. Also presented is how the nucleation can be simulated by use of molecular models, and how the condensation process is simulated on the macroscale using computational fluid dynamics. Finally, examples of hybrid models combining molecular and macroscale models for the simulation of condensation on a surface are presented.

Investigation of Micro- and Macro-Scale Transport Processes for Improved Fuel Cell Performance

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

Gu, Wenbin

2014-08-29

This report documents the work performed by General Motors (GM) under the Cooperative agreement No. DE-EE0000470, “Investigation of Micro- and Macro-Scale Transport Processes for Improved Fuel Cell Performance,” in collaboration with the Penn State University (PSU), University of Tennessee Knoxville (UTK), Rochester Institute of Technology (RIT), and University of Rochester (UR) via subcontracts. The overall objectives of the project are to investigate and synthesize fundamental understanding of transport phenomena at both the macro- and micro-scales for the development of a down-the-channel model that accounts for all transport domains in a broad operating space. GM as a prime contractor focused onmore » cell level experiments and modeling, and the Universities as subcontractors worked toward fundamental understanding of each component and associated interface.« less

Mechanical response of common millet (Panicum miliaceum) seeds under quasi-static compression: Experiments and modeling.

PubMed

Hasseldine, Benjamin P J; Gao, Chao; Collins, Joseph M; Jung, Hyun-Do; Jang, Tae-Sik; Song, Juha; Li, Yaning

2017-09-01

The common millet (Panicum miliaceum) seedcoat has a fascinating complex microstructure, with jigsaw puzzle-like epidermis cells articulated via wavy intercellular sutures to form a compact layer to protect the kernel inside. However, little research has been conducted on linking the microstructure details with the overall mechanical response of this interesting biological composite. To this end, an integrated experimental-numerical-analytical investigation was conducted to both characterize the microstructure and ascertain the microscale mechanical properties and to test the overall response of kernels and full seeds under macroscale quasi-static compression. Scanning electron microscopy (SEM) was utilized to examine the microstructure of the outer seedcoat and nanoindentation was performed to obtain the material properties of the seedcoat hard phase material. A multiscale computational strategy was applied to link the microstructure to the macroscale response of the seed. First, the effective anisotropic mechanical properties of the seedcoat were obtained from finite element (FE) simulations of a microscale representative volume element (RVE), which were further verified from sophisticated analytical models. Then, macroscale FE models of the individual kernel and full seed were developed. Good agreement between the compression experiments and FE simulations were obtained for both the kernel and the full seed. The results revealed the anisotropic property and the protective function of the seedcoat, and showed that the sutures of the seedcoat play an important role in transmitting and distributing loads in responding to external compression. Copyright © 2017 Elsevier Ltd. All rights reserved.

The Role of Water Governance and Irrigation Technologies in Regional-Scale Water Use and Consumption in the US West

NASA Astrophysics Data System (ADS)

Lammers, R. B.; Grogan, D. S.; Frolking, S. E.; Proussevitch, A. A.; Zuidema, S.; Fowler, L.; Caccese, R. T.; Peklak, D. L.; Fisher-Vanden, K.

2017-12-01

Water management in the Western USA is challenged by the demands of an increased population, ecological needs and changing values for water use, and a broadening of variability in climate, which together have created physical limits on water availability. The management of scarce water resources in this region is strictly constrained by the current legal structure (prior appropriation water rights) on one hand, and on the other assisted by the development of new, efficient water delivery and application technologies. Therefore, critical components for a complete understanding of the hydrological landscape include the institutions governing water rights, the technologies used for the highly water consumptive agricultural sector, and the role institutions and technologies play in altering when and where water is used and consumed by humans or reserved for the environment. To explore the sensitivities of water availability within the human-physical system, we present a method to incorporate water rights allocated under the prior appropriation doctrine for the western U.S. into the University of New Hampshire macro-scale Water Balance Model to capture the essential structure of these rights and their impacts on different economic sectors in Idaho and across the US West. In addition to legal structures, new irrigation technologies also alter the efficiency and timing of water use. We assess the impacts of a variety of technologies for both the delivery of water to the agricultural fields and the application methods for bringing water to the crops on consumptive and non-consumptive agricultural water use. We explore the impacts relative to natural climate variability, investigate the role that return flows from different agricultural technologies have on regional water balance, and examine the sensitivity of the entire system to extremes such as extended drought. These methods are sufficiently generalizable to be used by other hydrological models.

Multiscale Modeling of Cell Interaction in Angiogenesis: From the Micro- to Macro-scale

NASA Astrophysics Data System (ADS)

Pillay, Samara; Maini, Philip; Byrne, Helen

Solid tumors require a supply of nutrients to grow in size. To this end, tumors induce the growth of new blood vessels from existing vasculature through the process of angiogenesis. In this work, we use a discrete agent-based approach to model the behavior of individual endothelial cells during angiogenesis. We incorporate crowding effects through volume exclusion, motility of cells through biased random walks, and include birth and death processes. We use the transition probabilities associated with the discrete models to determine collective cell behavior, in terms of partial differential equations, using a Markov chain and master equation framework. We find that the cell-level dynamics gives rise to a migrating cell front in the form of a traveling wave on the macro-scale. The behavior of this front depends on the cell interactions that are included and the extent to which volume exclusion is taken into account in the discrete micro-scale model. We also find that well-established continuum models of angiogenesis cannot distinguish between certain types of cell behavior on the micro-scale. This may impact drug development strategies based on these models.

Sensitivity of River Runoff in Bhutan to Changes in Precipitation and Temperature

NASA Astrophysics Data System (ADS)

Sonessa, M. Y.; Nijssen, B.; Dorji, C.; Wangmo, D.; Lettenmaier, D. P.; Richey, J. E.

2013-12-01

In the past decades there has been increasing concern about the potential effects of climate change on runoff and water resources all over the world under different conditions. Various studies have indicated that climate change will have an impact on runoff and stream flow. Bhutan is one of the countries in the Hindu Kush-Himalayan region which shows more warming than the global average. The Variable Infiltration Capacity (VIC) model, a macroscale hydrological model, was used to assess the hydrology of the country and the potential impacts of climate change on water availability. Precipitation and temperature were perturbed to study the runoff sensitivity to temperature and precipitation changes. The VIC model was run at 1/24° latitude-longitude resolution. The modeled mean annual runoff elasticity which measures fractional change in annual runoff divided by fractional change in annual precipitation ranges from 1.08 to 2.16. The elasticity value is lower for higher reference precipitations and vice versa. The runoff sensitivity to temperature represents the percentage change in annual runoff per 1°C change in temperature. Runoff sensitivities are negative and range from -1.36%/°C to -1.70%/°C. Spatially, both greater elasticity and sensitivity occur towards the northern part of the country where elevation is more than 5000 m above sea level. Based on the coupled model inter-comparison project phase five (CMIP5) average model results, both precipitation and temperature are predicted to increase in Bhutan in the 21st century. Annually, P is expected to increase by 0.45 to 8.7% under RCP4.5 emission scenario and 1.95 to 14.26% under RCP8.5 emission. The mean annual temperature increment ranges from +1.1 to +2.6°C under RCP4.5 and +1.2 to +4.5°C under RCP8.5 emission scenario. These changes in precipitation and temperature are expected to result in runoff changes ranging from -1.0 to +14.3% and +2.2 to +23.1% increments under RCP4.5 and RCP8.5 emission scenarios, respectively, with the increment getting bigger towards the end of the century. Keywords: Climate change; runoff elasticity; runoff sensitivity; Bhutan.

"Climate change impact on water resources - a challenge for IWRM". BRAHMATWINN - Twinning European and South Asian River Basins to enhance capacity and implement adaptive management approaches

NASA Astrophysics Data System (ADS)

Bartosch, A.; Pechstädt, J.; Müller Schmied, H.; Flügel, W.-A.

2009-04-01

BRAHMATWINN addresses climate change impact of the hydrology of two macro-scale river basins having headwaters in alpine mountain massifs. The project will elaborate on the consequential vulnerability of present IWRM and river basin management that have been persistent in these basins during the past decades and will develop tested approaches and technologies for adaptive IWRM and resilience. The overall objective of BRAHMATWINN is to enhance and improve capacity to carry out a harmonized integrated water resources management (IWRM) approach as addressed by the European Water Initiative (EWI) in headwater river systems of alpine mountain massifs in respect to impacts from likely climate change, and to transfer professional IWRM expertise, approaches and tools based on case studies carried out in twinning European and Asian river basins, the Upper Danube River Basin (UDRB) and the Upper Brahmaputra River Basin (UBRB). Sustainable IWRM in river basins of such kind face common problems: (i) floods e.g. during spring melt or heavy storms and droughts during summer; (ii) competing water demands for agriculture, hydropower, rural, urban and industrial development, and the environment; (iii) pollution from point as well as diffuse sources; and (iv) socio-economic and legal issues related to water allocation. Besides those common topics both basins also differ in other issues requiring the adaptation of the IWRM tools; these are for example climate conditions, the density of monitoring network, political framework and trans-boundary conflicts. An IWRM has to consider all water-related issues like the securing of water supply for the population in sufficient quantity and quality, the protection of the ecological function of water bodies and it has to consider the probability of natural hazards like floods and droughts. Furthermore the resource water should be threatened in a way that the needs of future generations can be satisfied. Sustainable development is one of the main characteristics of an IWRM. An analysis of present IWRM practices and strategies in the basins and test sites, as well as an analysis of water administration, related organizations and water laws was conducted in the frame of the project to evaluate the status of water management in the regions and develop approaches to enhance the situation and to transfer professional IWRM expertise. For investigating the actual status of the system and its development in the past a thorough system analysis was conducted as the fundament for further activities. With the knowledge of the historical development of climate conditions, runoff regime, glacier development and similar basin-related information it is possible to extrapolate the system response for future developments. One approach of the system analysis is the delineation of hydrological response units (HRUs). "Hydrological response units are distributed, heterogeneously structured entities having a common climate, land use and underlying pedo-topo-geological associations controlling their hydrological dynamics" (FLÜGEL 1995, Hydrological Processes, Vol.9, 423-436). HRUs can be used as model entities to simulate the hydrology of the basin using a distributive hydrological modeling system. The hydrologic modeling is the next logical step after the HRU delineation. The novel hydrological model JAMS/J2000g, developed at the Friedrich-Schiller-University of Jena, was used for this purpose. For managing data (time series, GIS-data and documents) within the BRAHMATWINN project, a River Basin Information System (RBIS) was developed. In addition, RBIS provides the technical basis of a decision support system. For this challenge, the frontend offers different analysis functions. The structure of the web application RBIS consists of several components. One element is responsible for application administration tasks, e.g. the access management. Another component was constructed as a variable number of application modules plus a shared management for metadata, following the ISO 19115 standard, including specific extensions for each application module. Available modules are RBISts for the management of time series data, RBISdoc for the management of documents and RBISmap for the management and visualization of GIS data. BRAHMATWINN will considerably enhance the state-of-the-art in alpine mountain IWRM, mitigation of likely climate change scenarios and aspects of trans-boundary conflict management. By providing an innovative IWRMS toolset comprising the hydrological model, the presented web based information system, and a decision support component the outcomes of the project will be applicable for other river basins of this kind world wide.

Communication: Diverse nanoscale cluster dynamics: Diffusion of 2D epitaxial clusters

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

Lai, King C.; Evans, James W.; Liu, Da -Jiang

The dynamics of nanoscale clusters can be distinct from macroscale behavior described by continuum formalisms. For diffusion of 2D clusters of N atoms in homoepitaxial systems mediated by edge atom hopping, macroscale theory predicts simple monotonic size scaling of the diffusion coefficient, D N ~ N –β, with β = 3/2. However, modeling for nanoclusters on metal(100) surfaces reveals that slow nucleation-mediated diffusion displaying weak size scaling β < 1 occurs for “perfect” sizes N p = L 2 and L(L+1) for integer L = 3,4,… (with unique square or near-square ground state shapes), and also for N p+3, Nmore » p+4,…. In contrast, fast facile nucleation-free diffusion displaying strong size scaling β ≈ 2.5 occurs for sizes N p+1 and N p+2. D N versus N oscillates strongly between the slowest branch (for N p+3) and the fastest branch (for N p+1). All branches merge for N = O(10 2), but macroscale behavior is only achieved for much larger N = O(10 3). Here, this analysis reveals the unprecedented diversity of behavior on the nanoscale.« less

Communication: Diverse nanoscale cluster dynamics: Diffusion of 2D epitaxial clusters

DOE PAGES

Lai, King C.; Evans, James W.; Liu, Da -Jiang

2017-11-27

The dynamics of nanoscale clusters can be distinct from macroscale behavior described by continuum formalisms. For diffusion of 2D clusters of N atoms in homoepitaxial systems mediated by edge atom hopping, macroscale theory predicts simple monotonic size scaling of the diffusion coefficient, D N ~ N –β, with β = 3/2. However, modeling for nanoclusters on metal(100) surfaces reveals that slow nucleation-mediated diffusion displaying weak size scaling β < 1 occurs for “perfect” sizes N p = L 2 and L(L+1) for integer L = 3,4,… (with unique square or near-square ground state shapes), and also for N p+3, Nmore » p+4,…. In contrast, fast facile nucleation-free diffusion displaying strong size scaling β ≈ 2.5 occurs for sizes N p+1 and N p+2. D N versus N oscillates strongly between the slowest branch (for N p+3) and the fastest branch (for N p+1). All branches merge for N = O(10 2), but macroscale behavior is only achieved for much larger N = O(10 3). Here, this analysis reveals the unprecedented diversity of behavior on the nanoscale.« less

MODELING OF MACROSCALE AGRICULTURAL ELEMENTS IN PESTICIDE EXPOSURE

EPA Science Inventory

Yuma County, Arizona, is the site of year around agriculture. To understand the role of agricultural pesticide exposures experienced by children, urinary metabolite concentrations were compared with agricultural use of pesticides. The urinary metabolite and household data wer...

Development of Macroscale Models of UO 2 Fuel Sintering and Densification using Multiscale Modeling and Simulation

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

Greenquist, Ian; Tonks, Michael

2016-10-01

Light water reactor fuel pellets are fabricated using sintering to final densities of 95% or greater. During reactor operation, the porosity remaining in the fuel after fabrication decreases further due to irradiation-assisted densification. While empirical models have been developed to describe this densification process, a mechanistic model is needed as part of the ongoing work by the NEAMS program to develop a more predictive fuel performance code. In this work we will develop a phase field model of sintering of UO 2 in the MARMOT code, and validate it by comparing to published sintering data. We will then add themore » capability to capture irradiation effects into the model, and use it to develop a mechanistic model of densification that will go into the BISON code and add another essential piece to the microstructure-based materials models. The final step will be to add the effects of applied fields, to model field-assisted sintering of UO 2. The results of the phase field model will be validated by comparing to data from field-assisted sintering. Tasks over three years: 1. Develop a sintering model for UO 2 in MARMOT 2. Expand model to account for irradiation effects 3. Develop a mechanistic macroscale model of densification for BISON« less

General predictive model of friction behavior regimes for metal contacts based on the formation stability and evolution of nanocrystalline surface films.

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

Argibay, Nicolas; Cheng, Shengfeng; Sawyer, W. G.

2015-09-01

The prediction of macro-scale friction and wear behavior based on first principles and material properties has remained an elusive but highly desirable target for tribologists and material scientists alike. Stochastic processes (e.g. wear), statistically described parameters (e.g. surface topography) and their evolution tend to defeat attempts to establish practical general correlations between fundamental nanoscale processes and macro-scale behaviors. We present a model based on microstructural stability and evolution for the prediction of metal friction regimes, founded on recently established microstructural deformation mechanisms of nanocrystalline metals, that relies exclusively on material properties and contact stress models. We show through complementary experimentalmore » and simulation results that this model overcomes longstanding practical challenges and successfully makes accurate and consistent predictions of friction transitions for a wide range of contact conditions. This framework not only challenges the assumptions of conventional causal relationships between hardness and friction, and between friction and wear, but also suggests a pathway for the design of higher performance metal alloys.« less

Continuum-Kinetic Models and Numerical Methods for Multiphase Applications

NASA Astrophysics Data System (ADS)

Nault, Isaac Michael

This thesis presents a continuum-kinetic approach for modeling general problems in multiphase solid mechanics. In this context, a continuum model refers to any model, typically on the macro-scale, in which continuous state variables are used to capture the most important physics: conservation of mass, momentum, and energy. A kinetic model refers to any model, typically on the meso-scale, which captures the statistical motion and evolution of microscopic entitites. Multiphase phenomena usually involve non-negligible micro or meso-scopic effects at the interfaces between phases. The approach developed in the thesis attempts to combine the computational performance benefits of a continuum model with the physical accuracy of a kinetic model when applied to a multiphase problem. The approach is applied to modeling a single particle impact in Cold Spray, an engineering process that intimately involves the interaction of crystal grains with high-magnitude elastic waves. Such a situation could be classified a multiphase application due to the discrete nature of grains on the spatial scale of the problem. For this application, a hyper elasto-plastic model is solved by a finite volume method with approximate Riemann solver. The results of this model are compared for two types of plastic closure: a phenomenological macro-scale constitutive law, and a physics-based meso-scale Crystal Plasticity model.

Climate Change Impacts on Stream Temperature in Regulated River Systems: A Case Study in the Southeastern United States

NASA Astrophysics Data System (ADS)

Cheng, Y.; Niemeyer, R. J.; Zhang, X.; Yearsley, J. R.; Voisin, N.; Nijssen, B.

2017-12-01

Climate change and associated changes in air temperature and precipitation are projected to impact natural water resources quantity, quality and timing. In the past century, over 280 major dams were built in the Southeastern United States (SEUS) (GRanD database). Regulation of the river system greatly alters natural streamflow as well as stream temperature. Understanding the impacts of climate change on regulated systems, particularly within the context of the Clean Water Act, can inform stakeholders how to maintain and adapt water operations (e.g. regulation, withdrawals). In this study, we use a new modeling framework to study climate change impacts on stream temperatures of a regulated river system. We simulate runoff with the Variable Infiltration Capacity (VIC) macroscale hydrological model, regulated streamflow and reservoir operations with a large-scale river routing-reservoir model (MOSART-WM), and stream temperature using the River Basin Model (RBM). We enhanced RBM with a two-layer thermal stratification reservoir module. This modeling framework captures both the impact of reservoir regulation on streamflow and the reservoir stratification effects on downstream temperatures. We evaluate changes in flow and stream temperatures based on climate projections from two representative concentration pathways (RCPs; RCP4.5 and RCP8.5) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We simulate river temperature with meteorological forcings that have been downscaled with the Multivariate Constructed Analogs (MACA) method. We are specifically interested in analyzing extreme periods during which stream temperature exceeds water quality standards. In this study, we focus on identifying whether these extreme temperature periods coincide with low flows, and whether the frequency and duration of these operationally-relevant periods will increase under future climate change.

An Emerging Role for Numerical Modelling in Wildfire Behavior Research: Explorations, Explanations, and Hypothesis Development

NASA Astrophysics Data System (ADS)

Linn, R.; Winterkamp, J.; Canfield, J.; Sauer, J.; Dupuy, J. L.; Finney, M.; Hoffman, C.; Parsons, R.; Pimont, F.; Sieg, C.; Forthofer, J.

2014-12-01

The human capacity for altering the water cycle has been well documented and given the expected change due to population, income growth, biofuels, climate, and associated land use change, there remains great uncertainty in both the degree of increased pressure on land and water resources and in our ability to adapt to these changes. Alleviating regional shortages in water supply can be carried out in a spatial hierarchy through i) direct trade of water between all regions, ii) development of infrastructure to improve water availability within regions (e.g. impounding rivers), iii) via inter-basin hydrological transfer between neighboring regions and, iv) via virtual water trade. These adaptation strategies can be managed via market trade in water and commodities to identify those strategies most likely to be adopted. This work combines the physically-based University of New Hampshire Water Balance Model (WBM) with the macro-scale Purdue University Simplified International Model of agricultural Prices Land use and the Environment (SIMPLE) to explore the interaction of supply and demand for fresh water globally. In this work we use a newly developed grid cell-based version of SIMPLE to achieve a more direct connection between the two modeling paradigms of physically-based models with optimization-driven approaches characteristic of economic models. We explore questions related to the global and regional impact of water scarcity and water surplus on the ability of regions to adapt to future change. Allowing for a variety of adaptation strategies such as direct trade of water and expanding the built water infrastructure, as well as indirect trade in commodities, will reduce overall global water stress and, in some regions, significantly reduce their vulnerability to these future changes.

Global modeling of withdrawal, allocation and consumptive use of surface water and groundwater resources

NASA Astrophysics Data System (ADS)

Wada, Y.; Wisser, D.; Bierkens, M. F. P.

2013-02-01

To sustain growing food demand and increasing standard of living, global water withdrawal and consumptive water use have been increasing rapidly. To analyze the human perturbation on water resources consistently over a large scale, a number of macro-scale hydrological models (MHMs) have been developed over the recent decades. However, few models consider the feedback between water availability and water demand, and even fewer models explicitly incorporate water allocation from surface water and groundwater resources. Here, we integrate a global water demand model into a global water balance model, and simulate water withdrawal and consumptive water use over the period 1979-2010, considering water allocation from surface water and groundwater resources and explicitly taking into account feedbacks between supply and demand, using two re-analysis products: ERA-Interim and MERRA. We implement an irrigation water scheme, which works dynamically with daily surface and soil water balance, and include a newly available extensive reservoir data set. Simulated surface water and groundwater withdrawal show generally good agreement with available reported national and sub-national statistics. The results show a consistent increase in both surface water and groundwater use worldwide, but groundwater use has been increasing more rapidly than surface water use since the 1990s. Human impacts on terrestrial water storage (TWS) signals are evident, altering the seasonal and inter-annual variability. The alteration is particularly large over the heavily regulated basins such as the Colorado and the Columbia, and over the major irrigated basins such as the Mississippi, the Indus, and the Ganges. Including human water use generally improves the correlation of simulated TWS anomalies with those of the GRACE observations.

Chondrocyte Deformations as a Function of Tibiofemoral Joint Loading Predicted by a Generalized High-Throughput Pipeline of Multi-Scale Simulations

PubMed Central

Sibole, Scott C.; Erdemir, Ahmet

2012-01-01

Cells of the musculoskeletal system are known to respond to mechanical loading and chondrocytes within the cartilage are not an exception. However, understanding how joint level loads relate to cell level deformations, e.g. in the cartilage, is not a straightforward task. In this study, a multi-scale analysis pipeline was implemented to post-process the results of a macro-scale finite element (FE) tibiofemoral joint model to provide joint mechanics based displacement boundary conditions to micro-scale cellular FE models of the cartilage, for the purpose of characterizing chondrocyte deformations in relation to tibiofemoral joint loading. It was possible to identify the load distribution within the knee among its tissue structures and ultimately within the cartilage among its extracellular matrix, pericellular environment and resident chondrocytes. Various cellular deformation metrics (aspect ratio change, volumetric strain, cellular effective strain and maximum shear strain) were calculated. To illustrate further utility of this multi-scale modeling pipeline, two micro-scale cartilage constructs were considered: an idealized single cell at the centroid of a 100×100×100 μm block commonly used in past research studies, and an anatomically based (11 cell model of the same volume) representation of the middle zone of tibiofemoral cartilage. In both cases, chondrocytes experienced amplified deformations compared to those at the macro-scale, predicted by simulating one body weight compressive loading on the tibiofemoral joint. In the 11 cell case, all cells experienced less deformation than the single cell case, and also exhibited a larger variance in deformation compared to other cells residing in the same block. The coupling method proved to be highly scalable due to micro-scale model independence that allowed for exploitation of distributed memory computing architecture. The method’s generalized nature also allows for substitution of any macro-scale and/or micro-scale model providing application for other multi-scale continuum mechanics problems. PMID:22649535

Climate change impact on hydroclimate regimes and extremes over Andean basins in the central-southern Chile

NASA Astrophysics Data System (ADS)

Bozkurt, Deniz; Rojas, Maisa; Valdivieso, Jonás; Falvey, Mark

2015-04-01

We have assessed the impact of projected increases in temperature and decreased precipitation on variability and potential changes in hydroclimate regimes and extremes over Andean basins in the central-southern Chile (~30-40S). The altitude of the southern Andes in the study area has an average altitude of 5000 m in the north that decreases to 3000 m at the southern edge. Climatically the region has a Mediterranean-like climate with mainly winter precipitation that gradually increases southwards, from around 300 mm/yr to 1000 mm/yr. The region is home to most of the population in Chile (~10 mil. inhabitants), it has fertile and productive agriculture land, as well as hydro-electrical power plants. During the 20th Century the region has experienced a decreasing precipitation trend imbedded in important interannual and decadal scale variability. We have used gridded observed daily precipitation and temperatures to drive and validate the VIC macro-scale model over the region of interest at 0.25 x 0.25 degree resolution. Historical (1960-2005) and projected (RCP8.5, 2006-2099) daily precipitation and temperatures from 28 CMIP5 models are adjusted via a transfer function based on the gridded observed daily precipitation and temperature data. Adjusted time series are then used to drive the VIC model in order to present climate change projections. The hydrological model simulations foresee that drying is robust in the models and total annual runoff will decrease in the future (40-45% by the end of the century). Center timing of runoff tends to shift to earlier days (3-5 weeks by the end of the century). In some areas over the Andes winter runoff is projected to increase due to upward movement of zero isotherm. Moreover, reductions in the amount of snowpack and accelerated snowmelt lead to more pronounced increase in winter evapotranspiration over the same areas. The simulated 12-months Standardized Runoff Index (SRI) clearly shows severe persistent hydrological droughts without (or a few) wet spell interruptions by the end of the century. On the other hand, probability density function of annual maximum runoff over high elevations (>1000 m) and higher interannual variability of 3-months SRI indicate a possible increase in the probability of flood events.

A hierarchical perspective of plant diversity

USGS Publications Warehouse

Sarr, Daniel; Hibbs, D.E.; Huston, M.

2005-01-01

Predictive models of plant diversity have typically focused on either a landscapea??s capacity for richness (equilibrium models), or on the processes that regulate competitive exclusion, and thus allow species to coexist (nonequilibrium models). Here, we review the concepts and purposes of a hierarchical, multiscale model of the controls of plant diversity that incorporates the equilibrium model of climatic favorability at macroscales, nonequilibrium models of competition at microscales, and a mixed model emphasizing environmental heterogeneity at mesoscales. We evaluate the conceptual model using published data from three spatially nested datasets: (1) a macroscale analysis of ecoregions in the continental and western U.S.; (2) a mesoscale study in California; and (3) a microscale study in the Siskiyou Mountains of Oregon and California. At the macroscale (areas from 3889 km2 to 638,300 km2), climate (actual evaporation) was a strong predictor of tree diversity (R2 = 0.80), as predicted by the conceptual model, but area was a better predictor for vascular plant diversity overall (R2 = 0.38), which suggests different types of plants differ in their sensitivity to climatic controls. At mesoscales (areas from 1111 km2 to 15,833 km2 ), climate was still an important predictor of richness (R2 = 0.52), but, as expected, topographic heterogeneity explained an important share of the variance (R2 = 0.19), showed positive correlations with diversity of trees, shrubs, and annual and perennial herbs, and was the primary predictor of shrub and annual plant species richness. At microscales (0.1 ha plots), spatial patterns of diversity showed a clear unimodal pattern along a climatea??driven productivity gradient and a negative relationship with soil fertility. The strong decline in understory and total diversity at the most productive sites suggests that competitive controls, as predicted, can override climatic controls at this scale. We conclude that this hierarchical, multiscale model provides a sound basis to understand and analyze plant species diversity. Specifically, future research should employ the principles in this paper to explore climatic controls on species richness of different life forms, better quantify environmental heterogeneity in landscapes, and analyze how these largea??scale factors interact with local nonequilibrium dynamics to maintain plant diversity.

Understanding fast macroscale fracture from microcrack post mortem patterns

PubMed Central

Guerra, Claudia; Scheibert, Julien; Bonamy, Daniel; Dalmas, Davy

2012-01-01

Dynamic crack propagation drives catastrophic solid failures. In many amorphous brittle materials, sufficiently fast crack growth involves small-scale, high-frequency microcracking damage localized near the crack tip. The ultrafast dynamics of microcrack nucleation, growth, and coalescence is inaccessible experimentally and fast crack propagation was therefore studied only as a macroscale average. Here, we overcome this limitation in polymethylmethacrylate, the archetype of brittle amorphous materials: We reconstruct the complete spatiotemporal microcracking dynamics, with micrometer/nanosecond resolution, through post mortem analysis of the fracture surfaces. We find that all individual microcracks propagate at the same low, load-independent velocity. Collectively, the main effect of microcracks is not to slow down fracture by increasing the energy required for crack propagation, as commonly believed, but on the contrary to boost the macroscale velocity through an acceleration factor selected on geometric grounds. Our results emphasize the key role of damage-related internal variables in the selection of macroscale fracture dynamics. PMID:22203962

The sense and non-sense of plot-scale, catchment-scale, continental-scale and global-scale hydrological modelling

NASA Astrophysics Data System (ADS)

Bronstert, Axel; Heistermann, Maik; Francke, Till

2017-04-01

Hydrological models aim at quantifying the hydrological cycle and its constituent processes for particular conditions, sites or periods in time. Such models have been developed for a large range of spatial and temporal scales. One must be aware that the question which is the appropriate scale to be applied depends on the overall question under study. Therefore, it is not advisable to give a general applicable guideline on what is "the best" scale for a model. This statement is even more relevant for coupled hydrological, ecological and atmospheric models. Although a general statement about the most appropriate modelling scale is not recommendable, it is worth to have a look on what are the advantages and the shortcomings of micro-, meso- and macro-scale approaches. Such an appraisal is of increasing importance, since increasingly (very) large / global scale approaches and models are under operation and therefore the question arises how far and for what purposes such methods may yield scientifically sound results. It is important to understand that in most hydrological (and ecological, atmospheric and other) studies process scale, measurement scale, and modelling scale differ from each other. In some cases, the differences between theses scales can be of different orders of magnitude (example: runoff formation, measurement and modelling). These differences are a major source of uncertainty in description and modelling of hydrological, ecological and atmospheric processes. Let us now summarize our viewpoint of the strengths (+) and weaknesses (-) of hydrological models of different scales: Micro scale (e.g. extent of a plot, field or hillslope): (+) enables process research, based on controlled experiments (e.g. infiltration; root water uptake; chemical matter transport); (+) data of state conditions (e.g. soil parameter, vegetation properties) and boundary fluxes (e.g. rainfall or evapotranspiration) are directly measurable and reproducible; (+) equations based on first principals, partly pde-type, are available for several processes (but not for all), because measurement and modelling scale are compatible (-) the spatial model domain are hardly representative for larger spatial entities, including regions for which water resources management decisions are to be taken; straightforward upsizing is also limited by data availability and computational requirements. Meso scale (e.g. extent of a small to large catchment or region): (+) the spatial extent of the model domain has approximately the same extent as the regions for which water resources management decisions are to be taken. I.e., such models enable water resources quantification at the scale of most water management decisions; (+) data of some state conditions (e.g. vegetation cover, topography, river network and cross sections) are available; (+) data of some boundary fluxes (in particular surface runoff / channel flow) are directly measurable with mostly sufficient certainty; (+) equations, partly based on simple water budgeting, partly variants of pde-type equations, are available for most hydrological processes. This enables the construction of meso-scale distributed models reflecting the spatial heterogeneity of regions/landscapes; (-) process scale, measurement scale, and modelling scale differ from each other for a number of processes, e.g., such as runoff generation; (-) the process formulation (usually derived from micro-scale studies) cannot directly be transferred to the modelling domain. Upscaling procedures for this purpose are not readily and generally available. Macro scale (e.g. extent of a continent up to global): (+) the spatial extent of the model may cover the whole Earth. This enables an attractive global display of model results; (+) model results might be technically interchangeable or at least comparable with results from other global models, such as global climate models; (-) process scale, measurement scale, and modelling scale differ heavily from each other for all hydrological and associated processes; (-) the model domain and its results are not representative regions for which water resources management decisions are to be taken. (-) both state condition and boundary flux data are hardly available for the whole model domain. Water management data and discharge data from remote regions are particular incomplete / unavailable for this scale. This undermines the model's verifiability; (-) since process formulation and resulting modelling reliability at this scale is very limited, such models can hardly show any explanatory skills or prognostic power; (-) since both the entire model domain and the spatial sub-units cover large areas, model results represent values averaged over at least the spatial sub-unit's extent. In many cases, the applied time scale implies a long-term averaging in time, too. We emphasize the importance to be aware of the above mentioned strengths and weaknesses of those scale-specific models. (Many of the) results of the current global model studies do not reflect such limitations. In particular, we consider the averaging over large model entities in space and/or time inadequate. Many hydrological processes are of a non-linear nature, including threshold-type behaviour. Such features cannot be reflected by such large scale entities. The model results therefore can be of little or no use for water resources decisions and/or even misleading for public debates or decision making. Some rather newly developed sustainability concepts, e.g. "Planetary Boundaries" in which humanity may "continue to develop and thrive for generations to come" are based on such global-scale approaches and models. However, many of the major problems regarding sustainability on Earth, e.g. water scarcity, do not exhibit on a global but on a regional scale. While on a global scale water might look like being available in sufficient quantity and quality, there are many regions where water problems already have very harmful or even devastating effects. Therefore, it is the challenge to derive models and observation programmes for regional scales. In case a global display is desired future efforts should be directed towards the development of a global picture based on a mosaic of regional sound assessments, rather than "zooming into" the results of large-scale simulations. Still, a key question remains to be discussed, i.e. for which purpose models at this (global) scale can be used.

Trade in water and commodities as adaptations to global change

NASA Astrophysics Data System (ADS)

Lammers, R. B.; Hertel, T. W.; Prousevitch, A.; Baldos, U. L. C.; Frolking, S. E.; Liu, J.; Grogan, D. S.

2015-12-01

The human capacity for altering the water cycle has been well documented and given the expected change due to population, income growth, biofuels, climate, and associated land use change, there remains great uncertainty in both the degree of increased pressure on land and water resources and in our ability to adapt to these changes. Alleviating regional shortages in water supply can be carried out in a spatial hierarchy through i) direct trade of water between all regions, ii) development of infrastructure to improve water availability within regions (e.g. impounding rivers), iii) via inter-basin hydrological transfer between neighboring regions and, iv) via virtual water trade. These adaptation strategies can be managed via market trade in water and commodities to identify those strategies most likely to be adopted. This work combines the physically-based University of New Hampshire Water Balance Model (WBM) with the macro-scale Purdue University Simplified International Model of agricultural Prices Land use and the Environment (SIMPLE) to explore the interaction of supply and demand for fresh water globally. In this work we use a newly developed grid cell-based version of SIMPLE to achieve a more direct connection between the two modeling paradigms of physically-based models with optimization-driven approaches characteristic of economic models. We explore questions related to the global and regional impact of water scarcity and water surplus on the ability of regions to adapt to future change. Allowing for a variety of adaptation strategies such as direct trade of water and expanding the built water infrastructure, as well as indirect trade in commodities, will reduce overall global water stress and, in some regions, significantly reduce their vulnerability to these future changes.

Multiscale modeling of porous ceramics using movable cellular automaton method

NASA Astrophysics Data System (ADS)

Smolin, Alexey Yu.; Smolin, Igor Yu.; Smolina, Irina Yu.

2017-10-01

The paper presents a multiscale model for porous ceramics based on movable cellular automaton method, which is a particle method in novel computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the unique position in space. As a result, we get the average values of Young's modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behavior at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via effective properties determined earliar. If the pore size distribution function of the material has N maxima we need to perform computations for N-1 levels in order to get the properties step by step from the lowest scale up to the macroscale. The proposed approach was applied to modeling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behavior of the model sample at the macroscale.

Spatial-pattern-induced evolution of a self-replicating loop network.

PubMed

Suzuki, Keisuke; Ikegami, Takashi

2006-01-01

We study a system of self-replicating loops in which interaction rules between individuals allow competition that leads to the formation of a hypercycle-like network. The main feature of the model is the multiple layers of interaction between loops, which lead to both global spatial patterns and local replication. The network of loops manifests itself as a spiral structure from which new kinds of self-replicating loops emerge at the boundaries between different species. In these regions, larger and more complex self-replicating loops live for longer periods of time, managing to self-replicate in spite of their slower replication. Of particular interest is how micro-scale interactions between replicators lead to macro-scale spatial pattern formation, and how these macro-scale patterns in turn perturb the micro-scale replication dynamics.

Non-equilibrium effects of diatomic and polyatomic gases on the shock-vortex interaction based on the second-order constitutive model of the Boltzmann-Curtiss equation

NASA Astrophysics Data System (ADS)

Singh, S.; Karchani, A.; Myong, R. S.

2018-01-01

The rotational mode of molecules plays a critical role in the behavior of diatomic and polyatomic gases away from equilibrium. In order to investigate the essence of the non-equilibrium effects, the shock-vortex interaction problem was investigated by employing an explicit modal discontinuous Galerkin method. In particular, the first- and second-order constitutive models for diatomic and polyatomic gases derived rigorously from the Boltzmann-Curtiss kinetic equation were solved in conjunction with the physical conservation laws. As compared with a monatomic gas, the non-equilibrium effects result in a substantial change in flow fields in both macroscale and microscale shock-vortex interactions. Specifically, the computational results showed three major effects of diatomic and polyatomic gases on the shock-vortex interaction: (i) the generation of the third sound waves and additional reflected shock waves with strong and enlarged expansion, (ii) the dominance of viscous vorticity generation, and (iii) an increase in enstrophy with increasing bulk viscosity, related to the rotational mode of gas molecules. Moreover, it was shown that there is a significant discrepancy in flow fields between the microscale and macroscale shock-vortex interactions in diatomic and polyatomic gases. The quadrupolar acoustic wave source structures, which are typically observed in macroscale shock-vortex interactions, were not found in any microscale shock-vortex interactions. The physics of the shock-vortex interaction was also investigated in detail to examine vortex deformation and evolution dynamics over an incident shock wave. A comparative study of first- and second-order constitutive models was also conducted for the enstrophy and dissipation rate. Finally, the study was extended to the shock-vortex pair interaction case to examine the effects of pair interaction on vortex deformation and evolution dynamics.

A novel method of multi-scale simulation of macro-scale deformation and microstructure evolution on metal forming

NASA Astrophysics Data System (ADS)

Huang, Shiquan; Yi, Youping; Li, Pengchuan

2011-05-01

In recent years, multi-scale simulation technique of metal forming is gaining significant attention for prediction of the whole deformation process and microstructure evolution of product. The advances of numerical simulation at macro-scale level on metal forming are remarkable and the commercial FEM software, such as Deform2D/3D, has found a wide application in the fields of metal forming. However, the simulation method of multi-scale has little application due to the non-linearity of microstructure evolution during forming and the difficulty of modeling at the micro-scale level. This work deals with the modeling of microstructure evolution and a new method of multi-scale simulation in forging process. The aviation material 7050 aluminum alloy has been used as example for modeling of microstructure evolution. The corresponding thermal simulated experiment has been performed on Gleeble 1500 machine. The tested specimens have been analyzed for modeling of dislocation density, nucleation and growth of recrystallization(DRX). The source program using cellular automaton (CA) method has been developed to simulate the grain nucleation and growth, in which the change of grain topology structure caused by the metal deformation was considered. The physical fields at macro-scale level such as temperature field, stress and strain fields, which can be obtained by commercial software Deform 3D, are coupled with the deformed storage energy at micro-scale level by dislocation model to realize the multi-scale simulation. This method was explained by forging process simulation of the aircraft wheel hub forging. Coupled the results of Deform 3D with CA results, the forging deformation progress and the microstructure evolution at any point of forging could be simulated. For verifying the efficiency of simulation, experiments of aircraft wheel hub forging have been done in the laboratory and the comparison of simulation and experiment result has been discussed in details.

Investigating Deformation and Mesoscale Void Creation in HMX Based Composites using Tomography Based Grain Scale Finite Element Modeling

NASA Astrophysics Data System (ADS)

Walters, David J.; Luscher, Darby J.; Manner, Virginia; Yeager, John D.; Patterson, Brian M.

2017-06-01

The microstructure of plastic bonded explosives (PBXs) significantly affects their macroscale mechanical characteristics. Imaging and modeling of the mesoscale constituents allows for a detailed examination of the deformation of mechanically loaded PBXs. In this study, explosive composites, formulated with HMX crystals and various HTPB based polymer binders have been imaged using micro Computed Tomography (μCT). Cohesive parameters for simulation of the crystal/binder interface are determined by comparing numerical and experimental results of the delamination of a polymer bound bi-crystal system. Similarly, polycrystalline samples are discretized into a finite element mesh using the mesoscale geometry captured by in-situ μCT imaging. Experimentally, increasing the stiffness of the HTPB binder in the polycrystalline system resulted in a transition from ductile flow with little crystal/binder delamination to brittle behavior with increased void creation along the interfaces. Simulating the macroscale compression of these samples demonstrates the effects that the mesoscale geometry, cohesive properties, and binder stiffness have on the creation and distribution of interfacial voids. Understanding void nucleation is critical for modeling damage in these complex materials.

Multiscale Mechanical Characterization of Biomimetic Physically Associating Gels

DTIC Science & Technology

2006-09-01

work, a ballistic gelatin and two styrene- isoprene triblock copolymer gels are tested and compared using both macroscale and microscale measurements... isoprene triblock copolymer gels are tested and compared using both macroscale and microscale measurements. A methodology is presented to conduct

Systems and Methods for Implementing Bulk Metallic Glass-Based Macroscale Compliant Mechanisms

NASA Technical Reports Server (NTRS)

Hofmann, Douglas C. (Inventor); Agnes, Gregory (Inventor)

2017-01-01

Systems and methods in accordance with embodiments of the invention implement bulk metallic glass-based macroscale compliant mechanisms. In one embodiment, a bulk metallic glass-based macroscale compliant mechanism includes: a flexible member that is strained during the normal operation of the compliant mechanism; where the flexible member has a thickness of 0.5 mm; where the flexible member comprises a bulk metallic glass-based material; and where the bulk metallic glass-based material can survive a fatigue test that includes 1000 cycles under a bending loading mode at an applied stress to ultimate strength ratio of 0.25.

Some surprising manifestations of charged particle dynamics in a magnetic field

NASA Astrophysics Data System (ADS)

Varma, Ram K.

2010-08-01

We present here some very unusual experimental results on the dynamics of charged particle in a magnetic field which cannot be comprehended in terms of the Lorentz dynamics regarded, as per the current conceptual framework, as the appropriate one for the macro-scale description. Astonishingly, these results have been shown to be manifestations of a novel macro-scale quantum structure, designated as ‘transition amplitude wave’ (TAW), riding with the guiding centre trajectory, which is generated in the latter trajectory in consequence of the scattering of the particle with a fixed scattering centre. One set of observed results is thus identified as matter wave interference effects on the macro-scale attributable to this entity. The other enigmatic observation demonstrates the detection of a curl-free magnetic vector potential on the macro-scale, which is also shown to be a consequence of the TAW embedded in the Lorentz trajectory. These enigmatic results thus point to the unravelling of a new concept of a ‘dressed’ Lorentz trajectory—dressed with the TAW—accountable for these results, as against the ‘bare’ trajectory. These results and the formalism which enables one to comprehend them have led to the emergence of a new class of phenomena which display quantum properties on the macro-scale.

Optimal lattice-structured materials

DOE PAGES

Messner, Mark C.

2016-07-09

This paper describes a method for optimizing the mesostructure of lattice-structured materials. These materials are periodic arrays of slender members resembling efficient, lightweight macroscale structures like bridges and frame buildings. Current additive manufacturing technologies can assemble lattice structures with length scales ranging from nanometers to millimeters. Previous work demonstrates that lattice materials have excellent stiffness- and strength-to-weight scaling, outperforming natural materials. However, there are currently no methods for producing optimal mesostructures that consider the full space of possible 3D lattice topologies. The inverse homogenization approach for optimizing the periodic structure of lattice materials requires a parameterized, homogenized material model describingmore » the response of an arbitrary structure. This work develops such a model, starting with a method for describing the long-wavelength, macroscale deformation of an arbitrary lattice. The work combines the homogenized model with a parameterized description of the total design space to generate a parameterized model. Finally, the work describes an optimization method capable of producing optimal mesostructures. Several examples demonstrate the optimization method. One of these examples produces an elastically isotropic, maximally stiff structure, here called the isotruss, that arguably outperforms the anisotropic octet truss topology.« less

Effective equations governing an active poroelastic medium

PubMed Central

2017-01-01

In this work, we consider the spatial homogenization of a coupled transport and fluid–structure interaction model, to the end of deriving a system of effective equations describing the flow, elastic deformation and transport in an active poroelastic medium. The ‘active’ nature of the material results from a morphoelastic response to a chemical stimulant, in which the growth time scale is strongly separated from other elastic time scales. The resulting effective model is broadly relevant to the study of biological tissue growth, geophysical flows (e.g. swelling in coals and clays) and a wide range of industrial applications (e.g. absorbant hygiene products). The key contribution of this work is the derivation of a system of homogenized partial differential equations describing macroscale growth, coupled to transport of solute, that explicitly incorporates details of the structure and dynamics of the microscopic system, and, moreover, admits finite growth and deformation at the pore scale. The resulting macroscale model comprises a Biot-type system, augmented with additional terms pertaining to growth, coupled to an advection–reaction–diffusion equation. The resultant system of effective equations is then compared with other recent models under a selection of appropriate simplifying asymptotic limits. PMID:28293138

Estimates of Annual Climatic Water Need in Introductory Geography

ERIC Educational Resources Information Center

Currey, Donald R.

1976-01-01

This paper compares briefly, within the regional context of the western United States, several of the more readily adoptable models that are being used or could be used to provide estimates of annual climatic water need appropriate to macroscale applications in introductory geography courses. (Author)

Simulation of synthetic gecko arrays shearing on rough surfaces

PubMed Central

Gillies, Andrew G.; Fearing, Ronald S.

2014-01-01

To better understand the role of surface roughness and tip geometry in the adhesion of gecko synthetic adhesives, a model is developed that attempts to uncover the relationship between surface feature size and the adhesive terminal feature shape. This model is the first to predict the adhesive behaviour of a plurality of hairs acting in shear on simulated rough surfaces using analytically derived contact models. The models showed that the nanoscale geometry of the tip shape alters the macroscale adhesion of the array of fibres by nearly an order of magnitude, and that on sinusoidal surfaces with amplitudes much larger than the nanoscale features, spatula-shaped features can increase adhesive forces by 2.5 times on smooth surfaces and 10 times on rough surfaces. Interestingly, the summation of the fibres acting in concert shows behaviour much more complex that what could be predicted with the pull-off model of a single fibre. Both the Johnson–Kendall–Roberts and Kendall peel models can explain the experimentally observed frictional adhesion effect previously described in the literature. Similar to experimental results recently reported on the macroscale features of the gecko adhesive system, adhesion drops dramatically when surface roughness exceeds the size and spacing of the adhesive fibrillar features. PMID:24694893

Modeling of Multiphase Flow through Thin Porous Layers: Application to a Polymer Electrolyte Fuel Cell (PEFC)

NASA Astrophysics Data System (ADS)

Qin, C.; Hassanizadeh, S.

2013-12-01

Multiphase flow and species transport though thin porous layers are encountered in a number of industrial applications, such as fuel cells, filters, and hygiene products. Based on some macroscale models like the Darcy's law, to date, the modeling of flow and transport through such thin layers has been mostly performed in 3D discretized domains with many computational cells. But, there are a number of problems with this approach. First, a proper representative elementary volume (REV) is not defined. Second, one needs to discretize a thin porous medium into computational cells whose size may be comparable to the pore sizes. This suggests that the traditional models are not applicable to such thin domains. Third, the interfacial conditions between neighboring layers are usually not well defined. Last, 3D modeling of a number of interacting thin porous layers often requires heavy computational efforts. So, to eliminate the drawbacks mentioned above, we propose a new approach to modeling multilayers of thin porous media as 2D interacting continua (see Fig. 1). Macroscale 2D governing equations are formulated in terms of thickness-averaged material properties. Also, the exchange of thermodynamic properties between neighboring layers is described by thickness-averaged quantities. In Comparison to previous macroscale models, our model has the distinctive advantages of: (1) it is rigorous thermodynamics-based model; (2) it is formulated in terms of thickness-averaged material properties which are easily measureable; and (3) it reduces 3D modeling to 2D leading to a very significant reduction of computation efforts. As an application, we employ the new approach in the study of liquid water flooding in the cathode of a polymer electrolyte fuel cell (PEFC). To highlight the advantages of the present model, we compare the results of water distribution with those obtained from the traditional 3D Darcy-based modeling. Finally, it is worth noting that, for specific case studies, a number of material properties in the model need to be determined experimentally, such as mass and heat exchange coefficients between neighboring layers. Fig. 1: Schematic representation of three thin porous layers, which may exchange mass, momentum, and energy. Also, a typical averaging domain (REV) is shown. Note that the layer thickness and thus the REV height can be spatially variable. Also, in reality, the layers are tightly stacked and there is no gap between them.

A Technique for Mapping Characteristic Lengths to Preserve Energy Dissipated via Strain Softening in a Multiscale Analysis

NASA Technical Reports Server (NTRS)

Pineda, Evan J.; Bednarcyk, Brett A.; Arnold, Steven M.

2014-01-01

It is often advantageous to account for the microstructure of the material directly using multiscale modeling. For computational tractability, an idealized repeating unit cell (RUC) is used to capture all of the pertinent features of the microstructure. Typically, the RUC is dimensionless and depends only on the relative volume fractions of the different phases in the material. This works well for non-linear and inelastic behavior exhibiting a positive-definite constitutive response. Although, once the material exhibits strain softening, or localization, a mesh objective failure theories, such as smeared fracture theories, nodal and element enrichment theories (XFEM), cohesive elements or virtual crack closure technique (VCCT), can be utilized at the microscale, but the dimensions of the RUC must then be defined. One major challenge in multiscale progressive damage modeling is relating the characteristic lengths across the scales in order to preserve the energy that is dissipated via localization at the microscale. If there is no effort to relate the size of the macroscale element to the microscale RUC, then the energy that is dissipated will remain mesh dependent at the macroscale, even if it is regularized at the microscale. Here, a technique for mapping characteristic lengths across the scales is proposed. The RUC will be modeled using the generalized method of cells (GMC) micromechanics theory, and local failure in the matrix constituent subcells will be modeled using the crack band theory. The subcell characteristic lengths used in the crack band calculations will be mapped to the macroscale finite element in order to regularize the local energy in a manner consistent with the global length scale. Examples will be provided with and without the regularization, and they will be compared to a baseline case where the size and shape of the element and RUC are coincident (ensuring energy is preserved across the scales).

Evaluation and Validation of a TCAT Model to Describe Non-Dilute Flow and Species Transport in Porous Media

NASA Astrophysics Data System (ADS)

Weigand, T. M.; Harrison, E.; Miller, C. T.

2017-12-01

A thermodynamically constrained averaging theory (TCAT) model has been developed to simulate non-dilute flow and species transport in porous media. This model has the advantages of a firm connection between the microscale, or pore scale, and the macroscale; a thermodynamically consistent basis; the explicit inclusion of dissipative terms that arise from spatial gradients in pressure and chemical activity; and the ability to describe both high and low concentration displacement. The TCAT model has previously been shown to provide excellent agreement for a set of laboratory data and outperformed existing macroscale models that have been used for non-dilute flow and transport. The examined experimental dataset consisted of stable brine displacements for a large range of fluid properties. This dataset however only examined one type of porous media and had a fixed flow rate for all experiments. In this work, the TCAT model is applied to a dataset that consists of two different porous media types, constant head and flow rate conditions, varying resident fluid concentrations, and internal probes that measured the pressure and salt mass fraction. Parameter estimation is performed on a subset of the experimental data for the TCAT model as well as other existing non-dilute flow and transport models. The optimized parameters are then used for forward simulations and the accuracy of the models is compared.

Averaging Theory for Description of Environmental Problems: What Have We Learned?

PubMed Central

Miller, Cass T.; Schrefler, Bernhard A.

2012-01-01

Advances in Water Resources has been a prime archival source for implementation of averaging theories in changing the scale at which processes of importance in environmental modeling are described. Thus in celebration of the 35th year of this journal, it seems appropriate to assess what has been learned about these theories and about their utility in describing systems of interest. We review advances in understanding and use of averaging theories to describe porous medium flow and transport at the macroscale, an averaged scale that models spatial variability, and at the megascale, an integral scale that only considers time variation of system properties. We detail physical insights gained from the development and application of averaging theory for flow through porous medium systems and for the behavior of solids at the macroscale. We show the relationship between standard models that are typically applied and more rigorous models that are derived using modern averaging theory. We discuss how the results derived from averaging theory that are available can be built upon and applied broadly within the community. We highlight opportunities and needs that exist for collaborations among theorists, numerical analysts, and experimentalists to advance the new classes of models that have been derived. Lastly, we comment on averaging developments for rivers, estuaries, and watersheds. PMID:23393409

Multiscale finite element modeling of sheet molding compound (SMC) composite structure based on stochastic mesostructure reconstruction

DOE PAGES

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin; ...

2018-03-15

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less

A predictive parameter estimation approach for the thermodynamically constrained averaging theory applied to diffusion in porous media

NASA Astrophysics Data System (ADS)

Valdes-Parada, F. J.; Ostvar, S.; Wood, B. D.; Miller, C. T.

2017-12-01

Modeling of hierarchical systems such as porous media can be performed by different approaches that bridge microscale physics to the macroscale. Among the several alternatives available in the literature, the thermodynamically constrained averaging theory (TCAT) has emerged as a robust modeling approach that provides macroscale models that are consistent across scales. For specific closure relation forms, TCAT models are expressed in terms of parameters that depend upon the physical system under study. These parameters are usually obtained from inverse modeling based upon either experimental data or direct numerical simulation at the pore scale. Other upscaling approaches, such as the method of volume averaging, involve an a priori scheme for parameter estimation for certain microscale and transport conditions. In this work, we show how such a predictive scheme can be implemented in TCAT by studying the simple problem of single-phase passive diffusion in rigid and homogeneous porous media. The components of the effective diffusivity tensor are predicted for several porous media by solving ancillary boundary-value problems in periodic unit cells. The results are validated through a comparison with data from direct numerical simulation. This extension of TCAT constitutes a useful advance for certain classes of problems amenable to this estimation approach.

Multiscale finite element modeling of sheet molding compound (SMC) composite structure based on stochastic mesostructure reconstruction

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

Chen, Zhangxing; Huang, Tianyu; Shao, Yimin

Predicting the mechanical behavior of the chopped carbon fiber Sheet Molding Compound (SMC) due to spatial variations in local material properties is critical for the structural performance analysis but is computationally challenging. Such spatial variations are induced by the material flow in the compression molding process. In this work, a new multiscale SMC modeling framework and the associated computational techniques are developed to provide accurate and efficient predictions of SMC mechanical performance. The proposed multiscale modeling framework contains three modules. First, a stochastic algorithm for 3D chip-packing reconstruction is developed to efficiently generate the SMC mesoscale Representative Volume Element (RVE)more » model for Finite Element Analysis (FEA). A new fiber orientation tensor recovery function is embedded in the reconstruction algorithm to match reconstructions with the target characteristics of fiber orientation distribution. Second, a metamodeling module is established to improve the computational efficiency by creating the surrogates of mesoscale analyses. Third, the macroscale behaviors are predicted by an efficient multiscale model, in which the spatially varying material properties are obtained based on the local fiber orientation tensors. Our approach is further validated through experiments at both meso- and macro-scales, such as tensile tests assisted by Digital Image Correlation (DIC) and mesostructure imaging.« less

Development and Validation of Spatially Explicit Habitat Models for Cavity-nesting Birds in Fishlake National Forest, Utah

Treesearch

Randall A., Jr. Schultz; Thomas C., Jr. Edwards; Gretchen G. Moisen; Tracey S. Frescino

2005-01-01

The ability of USDA Forest Service Forest Inventory and Analysis (FIA) generated spatial products to increase the predictive accuracy of spatially explicit, macroscale habitat models was examined for nest-site selection by cavity-nesting birds in Fishlake National Forest, Utah. One FIA-derived variable (percent basal area of aspen trees) was significant in the habitat...

Hydrological climate change projections for Central America

NASA Astrophysics Data System (ADS)

Hidalgo, Hugo G.; Amador, Jorge A.; Alfaro, Eric J.; Quesada, Beatriz

2013-07-01

Runoff climate change projections for the 21st century were calculated from a suite of 30 General Circulation Model (GCM) simulations for the A1B emission scenario in a 0.5° × 0.5° grid over Central America. The GCM data were downscaled using a version of the Bias Correction and Spatial Downscaling (BCSD) method and then used in the Variable Infiltration Capacity (VIC) macroscale hydrological model. The VIC model showed calibration skill in Honduras, Nicaragua, Costa Rica and Panama, but the results for some of the northern countries (Guatemala, El Salvador and Belize) and for the Caribbean coast of Central America was not satisfactory. Bias correction showed to remove effectively the biases in the GCMs. Results of the projected climate in the 2050-2099 period showed median significant reductions in precipitation (as much as 5-10%) and runoff (as much as 10-30%) in northern Central America. Therefore in this sub-region the prevalence of severe drought may increase significantly in the future under this emissions scenario. Northern Central America could warm as much as 3 °C during 2050-2099 and southern Central America could reach increases as much as 4 °C during the same period. The projected dry pattern over Central America is consistent with a southward displacement of the Intertropical Convergence Zone (ITCZ). In addition, downscaling of the NCEP/NCAR Reanalysis data from 1948 to 2012 and posterior run in VIC, for two locations in the northern and southern sub-regions of Central America, suggested that the annual runoff has been decreasing since ca. 1980, which is consistent with the sign of the runoff changes of the GCM projections. However, the Reanalysis 1980-2012 drying trends are generally much stronger than the corresponding GCM trends. Among the possible reasons for that discrepancy are model deficiencies, amplification of the trends due to constructive interference with natural modes of variability in the Reanalysis data, errors in the Reanalysis (modeled) precipitation data, and that the drying signal is more pronounced than predicted by the emissions scenario used. A few studies show that extrapolations of future climate from paleoclimatic indicators project a wetter climate in northern Central America, which is inconsistent with the modeling results presented here. However, these types of extrapolations should be done with caution, as the future climate responds to an extra forcing mechanism (anthropogenic) that was not present prehistorically and therefore the response could also be different than in the past.

Hydrological modelling in forested systems | Science ...

EPA Pesticide Factsheets

This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological processes. The focus of this chapter is on process-based models and approaches, specifically 'forest hydrology models'; that is, physically based simulation tools that quantify compartments of the forest hydrological cycle. Physically based models can be considered those that describe the conservation of mass, momentum and/or energy. The purpose of this chapter is to provide a brief overview of forest hydrology modeling approaches for answering important global research and management questions. The focus of this chapter is on process-based models and approaches, specifically “forest hydrology models”, i.e., physically-based simulation tools that quantify compartments of the forest hydrological cycle.

Integrated detection of fractures and caves in carbonate fractured-vuggy reservoirs based on seismic data and well data

NASA Astrophysics Data System (ADS)

Cao, Zhanning; Li, Xiangyang; Sun, Shaohan; Liu, Qun; Deng, Guangxiao

2018-04-01

Aiming at the prediction of carbonate fractured-vuggy reservoirs, we put forward an integrated approach based on seismic and well data. We divide a carbonate fracture-cave system into four scales for study: micro-scale fracture, meso-scale fracture, macro-scale fracture and cave. Firstly, we analyze anisotropic attributes of prestack azimuth gathers based on multi-scale rock physics forward modeling. We select the frequency attenuation gradient attribute to calculate azimuth anisotropy intensity, and we constrain the result with Formation MicroScanner image data and trial production data to predict the distribution of both micro-scale and meso-scale fracture sets. Then, poststack seismic attributes, variance, curvature and ant algorithms are used to predict the distribution of macro-scale fractures. We also constrain the results with trial production data for accuracy. Next, the distribution of caves is predicted by the amplitude corresponding to the instantaneous peak frequency of the seismic imaging data. Finally, the meso-scale fracture sets, macro-scale fractures and caves are combined to obtain an integrated result. This integrated approach is applied to a real field in Tarim Basin in western China for the prediction of fracture-cave reservoirs. The results indicate that this approach can well explain the spatial distribution of carbonate reservoirs. It can solve the problem of non-uniqueness and improve fracture prediction accuracy.

Assessing Potential Implications of Climate Change for Long-Term Water Resources Planning in the Colorado River Basin, Texas

NASA Astrophysics Data System (ADS)

Munevar, A.; Butler, S.; Anderson, R.; Rippole, J.

2008-12-01

While much of the focus on climate change impacts to water resources in the western United States has been related to snow-dominated watersheds, lower elevation basins such as the Colorado River Basin in Texas are dependent on rainfall as the predominant form of precipitation and source of supply. Water management in these basins has evolved to adapt to extreme climatic and hydrologic variability, but the impact of climate change is potentially more acute due to rapid runoff response and subsequent greater soil moisture depletion during the dry seasons. The Lower Colorado River Authority (LCRA) - San Antonio Water System (SAWS) Water Project is being studied to conserve water, develop conjunctive groundwater supplies, and capture excess and unused river flows to meet future water needs for two neighboring regions in Texas. Agricultural and other rural water needs would be met on a more reliable basis in the lower Colorado River Basin through water conservation, surface water development and limited groundwater production. Surface water would be transferred to the San Antonio area to meet municipal needs in quantities still being evaluated. Detailed studies are addressing environmental, agricultural, socioeconomic, and engineering aspects of the project. Key planning activities include evaluating instream flow criteria, water quality, bay freshwater inflow criteria, surface water availability and operating approaches, agricultural conservation measures, groundwater availability, and economics. Models used to estimate future water availability and environmental flow requirements have been developed largely based on historical observed hydrologic data. This is a common approach used by water planners as well as by many regulatory agencies for permit review. In view of the project's 80-yr planning horizon, contractual obligations, comments from the Science Review Panel, and increased public and regulatory awareness of climate change issues, the project team is exploring climate change projections and methods to assess potential impacts over the project's expected life. Following an initial qualitative risk assessment, quantitative climate scenarios were developed based on multiple coupled atmosphere-ocean general circulation model (AOGCM) simulations under a range of global emission scenarios. Projected temperature and precipitation changes were evaluated from 112 downscaled AOGCM projections. A Four scenarios were selected for detailed hydrologic evaluations using the Variable Infiltration Capacity (VIC) macroscale model. A quantile mapping procedure was applied to map future climatological period change statistics onto the long-term natural climate variability in the observed record. Simulated changes in runoff, river flow, evaporation, and evapotranspiration are used to generate adjustments to historical hydrology for assessment of potential changes to surface water availability, river water quality, riverine habitat, and Bay health. Projected temperature, precipitation, and atmospheric CO2 concentrations are used to estimate changes in agricultural demand. Sea level rise scenarios that include trends in Gulf Coast shelf subsidence are combined with changes in inflows to evaluate increased coastal erosion, upland migration of the estuary, and changes to the salinity regime. Results of the scenario-based analyses are being considered in the development of adaptive management strategies for future operations of the system and the proposed project.

A Raman chemical imaging system for detection of contaminants in food

NASA Astrophysics Data System (ADS)

Chao, Kaunglin; Qin, Jianwei; Kim, Moon S.; Mo, Chang Yeon

2011-06-01

This study presented a preliminary investigation into the use of macro-scale Raman chemical imaging for the screening of dry milk powder for the presence of chemical contaminants. Melamine was mixed into dry milk at concentrations (w/w) of 0.2%, 0.5%, 1.0%, 2.0%, 5.0%, and 10.0% and images of the mixtures were analyzed by a spectral information divergence algorithm. Ammonium sulfate, dicyandiamide, and urea were each separately mixed into dry milk at concentrations of (w/w) of 0.5%, 1.0%, and 5.0%, and an algorithm based on self-modeling mixture analysis was applied to these sample images. The contaminants were successfully detected and the spatial distribution of the contaminants within the sample mixtures was visualized using these algorithms. Although further studies are necessary, macro-scale Raman chemical imaging shows promise for use in detecting contaminants in food ingredients and may also be useful for authentication of food ingredients.

The Effect of Scale Dependent Discretization on the Progressive Failure of Composite Materials Using Multiscale Analyses

NASA Technical Reports Server (NTRS)

Ricks, Trenton M.; Lacy, Thomas E., Jr.; Pineda, Evan J.; Bednarcyk, Brett A.; Arnold, Steven M.

2013-01-01

A multiscale modeling methodology, which incorporates a statistical distribution of fiber strengths into coupled micromechanics/ finite element analyses, is applied to unidirectional polymer matrix composites (PMCs) to analyze the effect of mesh discretization both at the micro- and macroscales on the predicted ultimate tensile (UTS) strength and failure behavior. The NASA code FEAMAC and the ABAQUS finite element solver were used to analyze the progressive failure of a PMC tensile specimen that initiates at the repeating unit cell (RUC) level. Three different finite element mesh densities were employed and each coupled with an appropriate RUC. Multiple simulations were performed in order to assess the effect of a statistical distribution of fiber strengths on the bulk composite failure and predicted strength. The coupled effects of both the micro- and macroscale discretizations were found to have a noticeable effect on the predicted UTS and computational efficiency of the simulations.

Analytical and Computational Modeling of Mechanical Waves in Microscale Granular Crystals: Nonlinearity and Rotational Dynamics

NASA Astrophysics Data System (ADS)

Wallen, Samuel P.

Granular media are one of the most common, yet least understood forms of matter on earth. The difficulties in understanding the physics of granular media stem from the fact that they are typically heterogeneous and highly disordered, and the grains interact via nonlinear contact forces. Historically, one approach to reducing these complexities and gaining new insight has been the study of granular crystals, which are ordered arrays of similarly-shaped particles (typically spheres) in Hertzian contact. Using this setting, past works explored the rich nonlinear dynamics stemming from contact forces, and proposed avenues where such granular crystals could form designer, dynamically responsive materials, which yield beneficial functionality in dynamic regimes. In recent years, the combination of self-assembly fabrication methods and laser ultrasonic experimental characterization have enabled the study of granular crystals at microscale. While our intuition may suggest that these microscale granular crystals are simply scaled-down versions of their macroscale counterparts, in fact, the relevant physics change drastically; for example, short-range adhesive forces between particles, which are negligible at macroscale, are several orders of magnitude stronger than gravity at microscale. In this thesis, we present recent advances in analytical and computational modeling of microscale granular crystals, in particular concerning the interplay of nonlinearity, shear interactions, and particle rotations, which have previously been either absent, or included separately at macroscale. Drawing inspiration from past works on phononic crystals and nonlinear lattices, we explore problems involving locally-resonant metamaterials, nonlinear localized modes, amplitude-dependent energy partition, and other rich dynamical phenomena. This work enhances our understanding of microscale granular media, which may find applicability in fields such as ultrasonic wave tailoring, signal processing, shock and vibration mitigation, and powder processing.

Visualization and Interactivity in the Teaching of Chemistry to Science and Non-Science Students

ERIC Educational Resources Information Center

Venkataraman, Bhawani

2009-01-01

A series of interactive, instructional units have been developed that integrate computational molecular modelling and visualization to teach fundamental chemistry concepts and the relationship between the molecular and macro-scales. The units span the scale from atoms, small molecules to macromolecular systems, and introduce many of the concepts…

The Analog Atomic Force Microscope: Measuring, Modeling, and Graphing for Middle School

ERIC Educational Resources Information Center

Goss, Valerie; Brandt, Sharon; Lieberman, Marya

2013-01-01

using an analog atomic force microscope (A-AFM) made from a cardboard box and mailing tubes. Varying numbers of ping pong balls inside the tubes mimic atoms on a surface. Students use a dowel to make macroscale measurements similar to those of a nanoscale AFM tip as it…

Meso-scopic Densification in Brittle Granular Materials

NASA Astrophysics Data System (ADS)

Neal, William; Appleby-Thomas, Gareth; Collins, Gareth

2013-06-01

Particulate materials are ideally suited to shock absorbing applications due to the large amounts of energy required to deform their inherently complex meso-structure. Significant effort is being made to improve macro-scale material models to represent these atypical materials. On the long road towards achieving this capability, an important milestone would be to understand how particle densification mechanisms are affected by loading rate. In brittle particulate materials, the majority of densification is caused by particle fracture. Macro-scale quasi-static and dynamic compaction curves have been measured that show good qualitative agreement. There are, however, some differences that appear to be dependent on the loading rate that require further investigation. This study aims to investigate the difference in grain-fracture behavior between the quasi-static and shock loading response of brittle glass microsphere beds using a combination of quasi-static and dynamic loading techniques. Results from pressure-density measurements, sample recovery, and meso-scale hydrocode models (iSALE, an in-house simulation package) are discussed to explain the differences in particle densification mechanisms between the two loading rate regimes. Gratefully funded by AWE.plc.

Environmental drivers defining linkages among life-history traits: mechanistic insights from a semiterrestrial amphipod subjected to macroscale gradients.

PubMed

Gómez, Julio; Barboza, Francisco R; Defeo, Omar

2013-10-01

Determining the existence of interconnected responses among life-history traits and identifying underlying environmental drivers are recognized as key goals for understanding the basis of phenotypic variability. We studied potentially interconnected responses among senescence, fecundity, embryos size, weight of brooding females, size at maturity and sex ratio in a semiterrestrial amphipod affected by macroscale gradients in beach morphodynamics and salinity. To this end, multiple modelling processes based on generalized additive mixed models were used to deal with the spatio-temporal structure of the data obtained at 10 beaches during 22 months. Salinity was the only nexus among life-history traits, suggesting that this physiological stressor influences the energy balance of organisms. Different salinity scenarios determined shifts in the weight of brooding females and size at maturity, having consequences in the number and size of embryos which in turn affected sex determination and sex ratio at the population level. Our work highlights the importance of analysing field data to find the variables and potential mechanisms that define concerted responses among traits, therefore defining life-history strategies.

Multiscale Simulation of Porous Ceramics Based on Movable Cellular Automaton Method

NASA Astrophysics Data System (ADS)

Smolin, A.; Smolin, I.; Eremina, G.; Smolina, I.

2017-10-01

The paper presents a model for simulating mechanical behaviour of multiscale porous ceramics based on movable cellular automaton method, which is a novel particle method in computational mechanics of solid. The initial scale of the proposed approach corresponds to the characteristic size of the smallest pores in the ceramics. At this scale, we model uniaxial compression of several representative samples with an explicit account of pores of the same size but with the random unique position in space. As a result, we get the average values of Young’s modulus and strength, as well as the parameters of the Weibull distribution of these properties at the current scale level. These data allow us to describe the material behaviour at the next scale level were only the larger pores are considered explicitly, while the influence of small pores is included via the effective properties determined at the previous scale level. If the pore size distribution function of the material has N maxima we need to perform computations for N - 1 levels in order to get the properties from the lowest scale up to the macroscale step by step. The proposed approach was applied to modelling zirconia ceramics with bimodal pore size distribution. The obtained results show correct behaviour of the model sample at the macroscale.

MICRO-SCALE CFD MODELING OF OSCILLATING FLOW IN A REGENERATOR

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

Cheadle, M. J.; Nellis, G. F.; Klein, S. A.

2010-04-09

Regenerator models used by designers are macro-scale models that do not explicitly consider interactions between the fluid and the solid matrix. Rather, the heat transfer coefficient and pressure drop are calculated using correlations for Nusselt number and friction factor. These correlations are typically based on steady flow data. The error associated with using steady flow correlations to characterize the oscillatory flow that is actually present in the regenerator is not well understood. Oscillating flow correlations based on experimental data do exist in the literature; however, these results are often conflicting. This paper uses a micro-scale computational fluid dynamic (CFD) modelmore » of a unit-cell of a regenerator matrix to determine the conditions for which oscillating flow affects friction factor. These conditions are compared to those found in typical pulse tube regenerators to determine whether oscillatory flow is of practical importance. CFD results clearly show a transition Valensi number beyond which oscillating flow significantly increases the friction factor. This transition Valensi number increases with Reynolds number. Most practical pulse tube regenerators will operate below this Valensi transition number and therefore this study suggests that the effect of flow oscillation on pressure drop can be neglected in macro-scale regenerator models.« less

Line-scan macro-scale Raman chemical imaging for authentication of powdered foods and ingredients

USDA-ARS?s Scientific Manuscript database

Adulteration and fraud for powdered foods and ingredients are rising food safety risks that threaten consumers’ health. In this study, a newly developed line-scan macro-scale Raman imaging system using a 5 W 785 nm line laser as excitation source was used to authenticate the food powders. The system...

Comprehensive Representation of Hydrologic and Geomorphic Process Coupling in Numerical Models: Internal Dynamics and Basin Evolution

NASA Astrophysics Data System (ADS)

Istanbulluoglu, E.; Vivoni, E. R.; Ivanov, V. Y.; Bras, R. L.

2005-12-01

Landscape morphology has an important control on the spatial and temporal organization of basin hydrologic response to climate forcing, affecting soil moisture redistribution as well as vegetation function. On the other hand, erosion, driven by hydrology and modulated by vegetation, produces landforms over geologic time scales that reflect characteristic signatures of the dominant land forming process. Responding to extreme climate events or anthropogenic disturbances of the land surface, infrequent but rapid forms of erosion (e.g., arroyo development, landsliding) can modify topography such that basin hydrology is significantly influenced. Despite significant advances in both hydrologic and geomorphic modeling over the past two decades, the dynamic interactions between basin hydrology, geomorphology and terrestrial ecology are not adequately captured in current model frameworks. In order to investigate hydrologic-geomorphic-ecologic interactions at the basin scale we present initial efforts in integrating the CHILD landscape evolution model (Tucker et al. 2001) with the tRIBS hydrology model (Ivanov et al. 2004), both developed in a common software environment. In this talk, we present preliminary results of the numerical modeling of the coupled evolution of basin hydro-geomorphic response and resulting landscape morphology in two sets of examples. First, we discuss the long-term evolution of both the hydrologic response and the resulting basin morphology from an initially uplifted plateau. In the second set of modeling experiments, we implement changes in climate and land-use to an existing topography and compare basin hydrologic response to the model results when landscape form is fixed (e.g. no coupling between hydrology and geomorphology). Model results stress the importance of internal basin dynamics, including runoff generation mechanisms and hydrologic states, in shaping hydrologic response as well as the importance of employing comprehensive conceptualizations of hydrology in modeling landscape evolution.

Multi-model approach to assess the impact of climate change on runoff

NASA Astrophysics Data System (ADS)

Dams, J.; Nossent, J.; Senbeta, T. B.; Willems, P.; Batelaan, O.

2015-10-01

The assessment of climate change impacts on hydrology is subject to uncertainties related to the climate change scenarios, stochastic uncertainties of the hydrological model and structural uncertainties of the hydrological model. This paper focuses on the contribution of structural uncertainty of hydrological models to the overall uncertainty of the climate change impact assessment. To quantify the structural uncertainty of hydrological models, four physically based hydrological models (SWAT, PRMS and a semi- and fully distributed version of the WetSpa model) are set up for a catchment in Belgium. Each model is calibrated using four different objective functions. Three climate change scenarios with a high, mean and low hydrological impact are statistically perturbed from a large ensemble of climate change scenarios and are used to force the hydrological models. This methodology allows assessing and comparing the uncertainty introduced by the climate change scenarios with the uncertainty introduced by the hydrological model structure. Results show that the hydrological model structure introduces a large uncertainty on both the average monthly discharge and the extreme peak and low flow predictions under the climate change scenarios. For the low impact climate change scenario, the uncertainty range of the mean monthly runoff is comparable to the range of these runoff values in the reference period. However, for the mean and high impact scenarios, this range is significantly larger. The uncertainty introduced by the climate change scenarios is larger than the uncertainty due to the hydrological model structure for the low and mean hydrological impact scenarios, but the reverse is true for the high impact climate change scenario. The mean and high impact scenarios project increasing peak discharges, while the low impact scenario projects increasing peak discharges only for peak events with return periods larger than 1.6 years. All models suggest for all scenarios a decrease of the lowest flows, except for the SWAT model with the mean hydrological impact climate change scenario. The results of this study indicate that besides the uncertainty introduced by the climate change scenarios also the hydrological model structure uncertainty should be taken into account in the assessment of climate change impacts on hydrology. To make it more straightforward and transparent to include model structural uncertainty in hydrological impact studies, there is a need for hydrological modelling tools that allow flexible structures and methods to validate model structures in their ability to assess impacts under unobserved future climatic conditions.

Detecting climate change oriented and human induced changes in stream temperature across the Southeastern U.S.

NASA Astrophysics Data System (ADS)

Zhang, X.; Voisin, N.; Cheng, Y.; Niemeyer, R. J.; Nijssen, B.; Yearsley, J. R.; Zhou, T.

2017-12-01

In many areas, climate change is expected to alter the flow regime and increase stream temperature, especially during summer low flow periods. During these low flow periods, water management increases flows in order to sustain human activities such as water for irrigation and hydroelectric power generation. Water extraction from rivers during warm season can increase stream temperature while reservoir regulation may cool downstream river temperatures by releasing cool water from deep layers. Thus, it is reasonable to hypothesize that water management changes the sensitivity of the stream temperature regime to climate change when compared to unmanaged resources. The time of emergence of change refers to the point in time when observations, or model simulations, show statistically significant changes from a given baseline period, i.e. above natural variability. Here we aim to address two questions by investigating the time of emergence of changes in stream temperature in the southeastern United States: what is the sensitivity of stream temperature under regulated flow conditions to climate change and what is the contribution of water management in increasing or decreasing stream temperature sensitivity to climate change. We simulate regulated flow by using runoff from the Variable Infiltration Capacity (VIC) macroscale hydrological model as input into a large scale river routing and reservoir model MOSART-WM. The River Basin Model (RBM), a distributed stream temperature model, includes a two-layer thermal stratification module to simulate stream temperature in regulated river systems. We evaluate the timing of emergence of changes in flow and stream temperature based on climate projections from two representative concentration pathways (RCPs; RCP4.5 and RCP8.5) from the Coupled Model Intercomparison Project Phase 5 (CMIP5). We analyze the difference in emergence of change between natural and regulated streamflow. Insights will be provided toward applications for multiple sectors of activities including electrical resources adequacy studies over the southeastern U.S.

Advancing the Implementation of Hydrologic Models as Web-based Applications

NASA Astrophysics Data System (ADS)

Dahal, P.; Tarboton, D. G.; Castronova, A. M.

2017-12-01

Advanced computer simulations are required to understand hydrologic phenomenon such as rainfall-runoff response, groundwater hydrology, snow hydrology, etc. Building a hydrologic model instance to simulate a watershed requires investment in data (diverse geospatial datasets such as terrain, soil) and computer resources, typically demands a wide skill set from the analyst, and the workflow involved is often difficult to reproduce. This work introduces a web-based prototype infrastructure in the form of a web application that provides researchers with easy to use access to complete hydrological modeling functionality. This includes creating the necessary geospatial and forcing data, preparing input files for a model by applying complex data preprocessing, running the model for a user defined watershed, and saving the results to a web repository. The open source Tethys Platform was used to develop the web app front-end Graphical User Interface (GUI). We used HydroDS, a webservice that provides data preparation processing capability to support backend computations used by the app. Results are saved in HydroShare, a hydrologic information system that supports the sharing of hydrologic data, model and analysis tools. The TOPographic Kinematic APproximation and Integration (TOPKAPI) model served as the example for which we developed a complete hydrologic modeling service to demonstrate the approach. The final product is a complete modeling system accessible through the web to create input files, and run the TOPKAPI hydrologic model for a watershed of interest. We are investigating similar functionality for the preparation of input to Regional Hydro-Ecological Simulation System (RHESSys). Key Words: hydrologic modeling, web services, hydrologic information system, HydroShare, HydroDS, Tethys Platform

Subcellular Electrical Measurements as a Function of Wood Moisture Content

Treesearch

Samuel L. Zelinka; José L. Colon Quintana; Samuel V. Glass; Joseph E. Jakes; Alex C. Wiedenhoeft

2015-01-01

The percolation model developed by Zelinka et al. was based upon macroscale measurements of the electrical conductivity and implicitly treats the wood material as homogenous. The transport mechanism proposed by Jakes et al. depends upon a moisture induced glass transition occurring in the hemicelluloses. This theory suggests that there are likely differences in the...

Multi-scale heat and mass transfer modelling of cell and tissue cryopreservation

PubMed Central

Xu, Feng; Moon, Sangjun; Zhang, Xiaohui; Shao, Lei; Song, Young Seok; Demirci, Utkan

2010-01-01

Cells and tissues undergo complex physical processes during cryopreservation. Understanding the underlying physical phenomena is critical to improve current cryopreservation methods and to develop new techniques. Here, we describe multi-scale approaches for modelling cell and tissue cryopreservation including heat transfer at macroscale level, crystallization, cell volume change and mass transport across cell membranes at microscale level. These multi-scale approaches allow us to study cell and tissue cryopreservation. PMID:20047939

The correlation between gelatin macroscale differences and nanoparticle properties: providing insight into biopolymer variability.

PubMed

Stevenson, André T; Jankus, Danny J; Tarshis, Max A; Whittington, Abby R

2018-05-21

From therapeutic delivery to sustainable packaging, manipulation of biopolymers into nanostructures imparts biocompatibility to numerous materials with minimal environmental pollution during processing. While biopolymers are appealing natural based materials, the lack of nanoparticle (NP) physicochemical consistency has decreased their nanoscale translation into actual products. Insights regarding the macroscale and nanoscale property variation of gelatin, one of the most common biopolymers already utilized in its bulk form, are presented. Novel correlations between macroscale and nanoscale properties were made by characterizing similar gelatin rigidities obtained from different manufacturers. Samples with significant differences in clarity, indicating sample purity, obtained the largest deviations in NP diameter. Furthermore, a statistically significant positive correlation between macroscale molecular weight dispersity and NP diameter was determined. New theoretical calculations proposing the limited number of gelatin chains that can aggregate and subsequently get crosslinked for NP formation were presented as one possible reason to substantiate the correlation analysis. NP charge and crosslinking extent were also related to diameter. Lower gelatin sample molecular weight dispersities produced statistically smaller average diameters (<75 nm), and higher average electrostatic charges (∼30 mV) and crosslinking extents (∼95%), which were independent of gelatin rigidity, conclusions not shown in the literature. This study demonstrates that the molecular weight composition of the starting material is one significant factor affecting gelatin nanoscale properties and must be characterized prior to NP preparation. Identifying gelatin macroscale and nanoscale correlations offers a route toward greater physicochemical property control and reproducibility of new NP formulations for translation to industry.

Mapping (un)certainties in the sign of hydrological projections

NASA Astrophysics Data System (ADS)

Melsen, Lieke; Addor, Nans; Mizukami, Naoki; Newman, Andrew; Torfs, Paul; Clark, Martyn; Uijlenhoet, Remko; Teuling, Ryan

2017-04-01

While hydrological projections are of vital importance, particularly for water infrastructure design and food production, they are also prone to different sources of uncertainty. Using a multi-model set-up we investigated the uncertainty in hydrological projections for the period 2070-2100 associated with the parameterization of hydrological models, hydrological model structure, and General Circulation Models (GCMs) needed to force the hydrological model, for 605 basins throughout the contiguous United States. The use of such a large sample of basins gave us the opportunity to recognize spatial patterns in the results, and to attribute the uncertainty to particular hydrological processes. We investigated the sign of the projected change in mean annual runoff. The parameterization influenced the sign of change in 5 to 34% of the basins, depending on the hydrological model and GCM forcing. The hydrological model structure led to uncertainty in the sign of the change in 13 to 26% of the basins, depending on GCM forcing. This uncertainty could largely be attributed to the conceptualization of snow processes in the hydrological models. In 14% of the basins, none of the hydrological models was behavioural, which could be related to catchments with high aridity and intermittent flow behaviour. In 41 to 69% of the basins, the sign of the change was uncertain due to GCM forcing, which could be attributed to disagreement among the climate models regarding the projected change in precipitation. The results demonstrate that even the sign of change in mean annual runoff is highly uncertain in the majority of the investigated basins. If we want to use hydrological projections for water management purposes, including the design of water infrastructure, we clearly need to increase our understanding of climate and hydrological processes and their feedbacks.

Macroscale Transformation Optics Enabled by Photoelectrochemical Etching.

PubMed

Barth, David S; Gladden, Christopher; Salandrino, Alessandro; O'Brien, Kevin; Ye, Ziliang; Mrejen, Michael; Wang, Yuan; Zhang, Xiang

2015-10-28

Photoelectrochemical etching of silicon can be used to form lateral refractive index gradients for transformation optical devices. This technique allows the fabrication of macroscale devices with large refractive index gradients. Patterned porous layers can also be lifted from the substrate and transferred to other materials, creating more possibilities for novel devices. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Nondestructive chemical imaging of wood at the micro-scale: advanced technology to complement macro-scale evaluations

Treesearch

Barbara L. Illman; Julia Sedlmair; Miriam Unger; Carol Hirschmugl

2013-01-01

Chemical images help understanding of wood properties, durability, and cell wall deconstruction for conversion of lignocellulose to biofuels, nanocellulose and other value added chemicals in forest biorefineries. We describe here a new method for nondestructive chemical imaging of wood and wood-based materials at the micro-scale to complement macro-scale methods based...

An extremely simple macroscale electronic skin realized by deep machine learning.

PubMed

Sohn, Kee-Sun; Chung, Jiyong; Cho, Min-Young; Timilsina, Suman; Park, Woon Bae; Pyo, Myungho; Shin, Namsoo; Sohn, Keemin; Kim, Ji Sik

2017-09-11

Complicated structures consisting of multi-layers with a multi-modal array of device components, i.e., so-called patterned multi-layers, and their corresponding circuit designs for signal readout and addressing are used to achieve a macroscale electronic skin (e-skin). In contrast to this common approach, we realized an extremely simple macroscale e-skin only by employing a single-layered piezoresistive MWCNT-PDMS composite film with neither nano-, micro-, nor macro-patterns. It is the deep machine learning that made it possible to let such a simple bulky material play the role of a smart sensory device. A deep neural network (DNN) enabled us to process electrical resistance change induced by applied pressure and thereby to instantaneously evaluate the pressure level and the exact position under pressure. The great potential of this revolutionary concept for the attainment of pressure-distribution sensing on a macroscale area could expand its use to not only e-skin applications but to other high-end applications such as touch panels, portable flexible keyboard, sign language interpreting globes, safety diagnosis of social infrastructures, and the diagnosis of motility and peristalsis disorders in the gastrointestinal tract.

Race and Space in the 1990s: Changes in the Geographic Scale of Racial Residential Segregation, 1990-2000

PubMed Central

Reardon, Sean F.; Farrell, Chad R.; Matthews, Stephen A.; O'Sullivan, David; Bischoff, Kendra; Firebaugh, Glenn

2014-01-01

We use newly developed methods of measuring spatial segregation across a range of spatial scales to assess changes in racial residential segregation patterns in the 100 largest U.S. metropolitan areas from 1990 to 2000. Our results point to three notable trends in segregation from 1990 to 2000: 1) Hispanic-white and Asian-white segregation levels increased at both micro- and macro-scales; 2) black-white segregation declined at a micro-scale, but was unchanged at a macro-scale; and 3) for all three racial groups and for almost all metropolitan areas, macro-scale segregation accounted for more of the total metropolitan area segregation in 2000 than in 1990. Our examination of the variation in these trends among the metropolitan areas suggests that Hispanic-white and Asian-white segregation changes have been driven largely by increases in macro-scale segregation resulting from the rapid growth of the Hispanic and Asian populations in central cities. The changes in black-white segregation, in contrast, appear to be driven by the continuation of a 30-year trend in declining micro-segregation, coupled with persistent and largely stable patterns of macro-segregation. PMID:19569292

Scale effect challenges in urban hydrology highlighted with a distributed hydrological model

NASA Astrophysics Data System (ADS)

Ichiba, Abdellah; Gires, Auguste; Tchiguirinskaia, Ioulia; Schertzer, Daniel; Bompard, Philippe; Ten Veldhuis, Marie-Claire

2018-01-01

Hydrological models are extensively used in urban water management, development and evaluation of future scenarios and research activities. There is a growing interest in the development of fully distributed and grid-based models. However, some complex questions related to scale effects are not yet fully understood and still remain open issues in urban hydrology. In this paper we propose a two-step investigation framework to illustrate the extent of scale effects in urban hydrology. First, fractal tools are used to highlight the scale dependence observed within distributed data input into urban hydrological models. Then an intensive multi-scale modelling work is carried out to understand scale effects on hydrological model performance. Investigations are conducted using a fully distributed and physically based model, Multi-Hydro, developed at Ecole des Ponts ParisTech. The model is implemented at 17 spatial resolutions ranging from 100 to 5 m. Results clearly exhibit scale effect challenges in urban hydrology modelling. The applicability of fractal concepts highlights the scale dependence observed within distributed data. Patterns of geophysical data change when the size of the observation pixel changes. The multi-scale modelling investigation confirms scale effects on hydrological model performance. Results are analysed over three ranges of scales identified in the fractal analysis and confirmed through modelling. This work also discusses some remaining issues in urban hydrology modelling related to the availability of high-quality data at high resolutions, and model numerical instabilities as well as the computation time requirements. The main findings of this paper enable a replacement of traditional methods of model calibration by innovative methods of model resolution alteration based on the spatial data variability and scaling of flows in urban hydrology.

Hydrological modelling in forested systems

EPA Science Inventory

This chapter provides a brief overview of forest hydrology modelling approaches for answering important global research and management questions. Many hundreds of hydrological models have been applied globally across multiple decades to represent and predict forest hydrological p...

Nanowire active-matrix circuitry for low-voltage macroscale artificial skin.

PubMed

Takei, Kuniharu; Takahashi, Toshitake; Ho, Johnny C; Ko, Hyunhyub; Gillies, Andrew G; Leu, Paul W; Fearing, Ronald S; Javey, Ali

2010-10-01

Large-scale integration of high-performance electronic components on mechanically flexible substrates may enable new applications in electronics, sensing and energy. Over the past several years, tremendous progress in the printing and transfer of single-crystalline, inorganic micro- and nanostructures on plastic substrates has been achieved through various process schemes. For instance, contact printing of parallel arrays of semiconductor nanowires (NWs) has been explored as a versatile route to enable fabrication of high-performance, bendable transistors and sensors. However, truly macroscale integration of ordered NW circuitry has not yet been demonstrated, with the largest-scale active systems being of the order of 1 cm(2) (refs 11,15). This limitation is in part due to assembly- and processing-related obstacles, although larger-scale integration has been demonstrated for randomly oriented NWs (ref. 16). Driven by this challenge, here we demonstrate macroscale (7×7 cm(2)) integration of parallel NW arrays as the active-matrix backplane of a flexible pressure-sensor array (18×19 pixels). The integrated sensor array effectively functions as an artificial electronic skin, capable of monitoring applied pressure profiles with high spatial resolution. The active-matrix circuitry operates at a low operating voltage of less than 5 V and exhibits superb mechanical robustness and reliability, without performance degradation on bending to small radii of curvature (2.5 mm) for over 2,000 bending cycles. This work presents the largest integration of ordered NW-array active components, and demonstrates a model platform for future integration of nanomaterials for practical applications.

Improving student comprehension of the interconnectivity of the hydrologic cycle with a novel 'hydrology toolbox', integrated watershed model, and companion textbook

NASA Astrophysics Data System (ADS)

Huning, L. S.; Margulis, S. A.

2013-12-01

Concepts in introductory hydrology courses are often taught in the context of process-based modeling that ultimately is integrated into a watershed model. In an effort to reduce the learning curve associated with applying hydrologic concepts to real-world applications, we developed and incorporated a 'hydrology toolbox' that complements a new, companion textbook into introductory undergraduate hydrology courses. The hydrology toolbox contains the basic building blocks (functions coded in MATLAB) for an integrated spatially-distributed watershed model that makes hydrologic topics (e.g. precipitation, snow, radiation, evaporation, unsaturated flow, infiltration, groundwater, and runoff) more user-friendly and accessible for students. The toolbox functions can be used in a modular format so that students can study individual hydrologic processes and become familiar with the hydrology toolbox. This approach allows such courses to emphasize understanding and application of hydrologic concepts rather than computer coding or programming. While topics in introductory hydrology courses are often introduced and taught independently or semi-independently, they are inherently interconnected. These toolbox functions are therefore linked together at the end of the course to reinforce a holistic understanding of how these hydrologic processes are measured, interconnected, and modeled. They are integrated into a spatially-distributed watershed model or numerical laboratory where students can explore a range of topics such as rainfall-runoff modeling, urbanization, deforestation, watershed response to changes in parameters or forcings, etc. Model output can readily be visualized and analyzed by students to understand watershed response in a real river basin or a simple 'toy' basin. These tools complement the textbook, each of which has been well received by students in multiple hydrology courses with various disciplinary backgrounds. The same governing equations that students have studied in the textbook and used in the toolbox have been encapsulated in the watershed model. Therefore, the combination of the hydrology toolbox, integrated watershed model, and textbook tends to eliminate the potential disconnect between process-based modeling and an 'off-the-shelf' watershed model.

Wetland Hydrology | Science Inventory | US EPA

EPA Pesticide Factsheets

This chapter discusses the state of the science in wetland hydrology by touching upon the major hydraulic and hydrologic processes in these complex ecosystems, their measurement/estimation techniques, and modeling methods. It starts with the definition of wetlands, their benefits and types, and explains the role and importance of hydrology on wetland functioning. The chapter continues with the description of wetland hydrologic terms and related estimation and modeling techniques. The chapter provides a quick but valuable information regarding hydraulics of surface and subsurface flow, groundwater seepage/discharge, and modeling groundwater/surface water interactions in wetlands. Because of the aggregated effects of the wetlands at larger scales and their ecosystem services, wetland hydrology at the watershed scale is also discussed in which we elaborate on the proficiencies of some of the well-known watershed models in modeling wetland hydrology. This chapter can serve as a useful reference for eco-hydrologists, wetland researchers and decision makers as well as watershed hydrology modelers. In this chapter, the importance of hydrology for wetlands and their functional role are discussed. Wetland hydrologic terms and the major components of water budget in wetlands and how they can be estimated/modeled are also presented. Although this chapter does not provide a comprehensive coverage of wetland hydrology, it provides a quick understanding of the basic co

Uncertainty Propagation of Non-Parametric-Derived Precipitation Estimates into Multi-Hydrologic Model Simulations

NASA Astrophysics Data System (ADS)

Bhuiyan, M. A. E.; Nikolopoulos, E. I.; Anagnostou, E. N.

2017-12-01

Quantifying the uncertainty of global precipitation datasets is beneficial when using these precipitation products in hydrological applications, because precipitation uncertainty propagation through hydrologic modeling can significantly affect the accuracy of the simulated hydrologic variables. In this research the Iberian Peninsula has been used as the study area with a study period spanning eleven years (2000-2010). This study evaluates the performance of multiple hydrologic models forced with combined global rainfall estimates derived based on a Quantile Regression Forests (QRF) technique. In QRF technique three satellite precipitation products (CMORPH, PERSIANN, and 3B42 (V7)); an atmospheric reanalysis precipitation and air temperature dataset; satellite-derived near-surface daily soil moisture data; and a terrain elevation dataset are being utilized in this study. A high-resolution, ground-based observations driven precipitation dataset (named SAFRAN) available at 5 km/1 h resolution is used as reference. Through the QRF blending framework the stochastic error model produces error-adjusted ensemble precipitation realizations, which are used to force four global hydrological models (JULES (Joint UK Land Environment Simulator), WaterGAP3 (Water-Global Assessment and Prognosis), ORCHIDEE (Organizing Carbon and Hydrology in Dynamic Ecosystems) and SURFEX (Stands for Surface Externalisée) ) to simulate three hydrologic variables (surface runoff, subsurface runoff and evapotranspiration). The models are forced with the reference precipitation to generate reference-based hydrologic simulations. This study presents a comparative analysis of multiple hydrologic model simulations for different hydrologic variables and the impact of the blending algorithm on the simulated hydrologic variables. Results show how precipitation uncertainty propagates through the different hydrologic model structures to manifest in reduction of error in hydrologic variables.

Microbial control of mineral–groundwater equilibria:Macroscale to microscale

USGS Publications Warehouse

Bennett, Philip C.; Hiebert, Franz K.; Roger, Jennifer Roberts

2000-01-01

macroscaleprocesses that perturb general groundwater chemistry and therefore mineral–water equilibria; and microscale interactions, where attached organisms locally perturb mineral–water equilibria, potentially releasing limiting trace nutrients from the dissolving mineral.In the contaminated unconfined glacio-fluvial aquifer near Bemidji, Minnesota, USA, carbonate chemistry is influenced primarily at the macroscale. Under oxic conditions, respiration by native aerobic heterotrophs produces excess carbon dioxide that promotes calcite and dolomite dissolution. Aerobic microorganisms do not colonize dolomite surfaces and few occur on calcite. Within the anoxic groundwater, calcite overgrowths form on uncolonized calcite cleavage surfaces, possibly due to the consumption of acidity by dissimilatory iron-reducing bacteria. As molecular oxygen concentration increases downgradient of the oil pool, aerobes again dominate and residual hydrocarbons and ferrous iron are oxidized, resulting in macroscale carbonate-mineral dissolution and iron precipitation.

Impact of a statistical bias correction on the projected simulated hydrological changes obtained from three GCMs and two hydrology models

NASA Astrophysics Data System (ADS)

Hagemann, Stefan; Chen, Cui; Haerter, Jan O.; Gerten, Dieter; Heinke, Jens; Piani, Claudio

2010-05-01

Future climate model scenarios depend crucially on their adequate representation of the hydrological cycle. Within the European project "Water and Global Change" (WATCH) special care is taken to couple state-of-the-art climate model output to a suite of hydrological models. This coupling is expected to lead to a better assessment of changes in the hydrological cycle. However, due to the systematic model errors of climate models, their output is often not directly applicable as input for hydrological models. Thus, the methodology of a statistical bias correction has been developed, which can be used for correcting climate model output to produce internally consistent fields that have the same statistical intensity distribution as the observations. As observations, global re-analysed daily data of precipitation and temperature are used that are obtained in the WATCH project. We will apply the bias correction to global climate model data of precipitation and temperature from the GCMs ECHAM5/MPIOM, CNRM-CM3 and LMDZ-4, and intercompare the bias corrected data to the original GCM data and the observations. Then, the orginal and the bias corrected GCM data will be used to force two global hydrology models: (1) the hydrological model of the Max Planck Institute for Meteorology (MPI-HM) consisting of the Simplified Land surface (SL) scheme and the Hydrological Discharge (HD) model, and (2) the dynamic vegetation model LPJmL operated by the Potsdam Institute for Climate Impact Research. The impact of the bias correction on the projected simulated hydrological changes will be analysed, and the resulting behaviour of the two hydrology models will be compared.

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

PubMed

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

2003-01-01

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

Investigation of shear damage considering the evolution of anisotropy

NASA Astrophysics Data System (ADS)

Kweon, S.

2013-12-01

The damage that occurs in shear deformations in view of anisotropy evolution is investigated. It is widely believed in the mechanics research community that damage (or porosity) does not evolve (increase) in shear deformations since the hydrostatic stress in shear is zero. This paper proves that the above statement can be false in large deformations of simple shear. The simulation using the proposed anisotropic ductile fracture model (macro-scale) in this study indicates that hydrostatic stress becomes nonzero and (thus) porosity evolves (increases or decreases) in the simple shear deformation of anisotropic (orthotropic) materials. The simple shear simulation using a crystal plasticity based damage model (meso-scale) shows the same physics as manifested in the above macro-scale model that porosity evolves due to the grain-to-grain interaction, i.e., due to the evolution of anisotropy. Through a series of simple shear simulations, this study investigates the effect of the evolution of anisotropy, i.e., the rotation of the orthotropic axes onto the damage (porosity) evolution. The effect of the evolutions of void orientation and void shape onto the damage (porosity) evolution is investigated as well. It is found out that the interaction among porosity, the matrix anisotropy and void orientation/shape plays a crucial role in the ductile damage of porous materials.

Components for Atomistic-to-Continuum Multiscale Modeling of Flow in Micro- and Nanofluidic Systems

DOE PAGES

Adalsteinsson, Helgi; Debusschere, Bert J.; Long, Kevin R.; ...

2008-01-01

Micro- and nanofluidics pose a series of significant challenges for science-based modeling. Key among those are the wide separation of length- and timescales between interface phenomena and bulk flow and the spatially heterogeneous solution properties near solid-liquid interfaces. It is not uncommon for characteristic scales in these systems to span nine orders of magnitude from the atomic motions in particle dynamics up to evolution of mass transport at the macroscale level, making explicit particle models intractable for all but the simplest systems. Recently, atomistic-to-continuum (A2C) multiscale simulations have gained a lot of interest as an approach to rigorously handle particle-levelmore » dynamics while also tracking evolution of large-scale macroscale behavior. While these methods are clearly not applicable to all classes of simulations, they are finding traction in systems in which tight-binding, and physically important, dynamics at system interfaces have complex effects on the slower-evolving large-scale evolution of the surrounding medium. These conditions allow decomposition of the simulation into discrete domains, either spatially or temporally. In this paper, we describe how features of domain decomposed simulation systems can be harnessed to yield flexible and efficient software for multiscale simulations of electric field-driven micro- and nanofluidics.« less

Drivers of Non-Native Aquatic Species Invasions across the ...

EPA Pesticide Factsheets

Background/Question/Methods Mapping the geographic distribution of non-native aquatic species is a critically important precursor to understanding the anthropogenic and environmental factors that drive freshwater biological invasions. Such efforts are often limited to local scales and/or to a single taxa, missing the opportunity to observe and understand the drivers of macroscale invasion patterns at sub-continental or continental scales. Here we map the distribution of exotic freshwater species richness across the continental United States using publicly accessible species occurrence data (e.g GBIF) and investigate the role of human activity in driving macroscale patterns of aquatic invasion. Using a dasymetric model of human population density and a spatially explicit model of recreational freshwater fishing demand, we analyzed the effect of these metrics of human influence on non-native aquatic species richness at the watershed scale, while controlling for spatial and sampling bias. We also assessed the effects that a temporal mismatch between occurrence data (collected since 1815) and cross-sectional predictors (developed using 2010 data) may have on model fit. Results/Conclusions Our results indicated that non-native aquatic species richness exhibits a highly patchy distribution, with hotspots in the Northeast, Great Lakes, Florida, and human population centers on the Pacific coast. These richness patterns are correlated with population density, but are m

Escape of a knot from a DNA molecule in flow

NASA Astrophysics Data System (ADS)

Renner, Benjamin; Doyle, Patrick

2014-03-01

Macroscale knots are an everyday occurrence when trying to unravel an unorganized flexible string (e.g. an iPhone cord taken out of your pocket). In nature, knots are found in proteins and viral capsid DNA, and the properties imbued by their topologies are thought to have biological significance. Unlike their macroscale counterparts, thermal fluctuations greatly influence the dynamics of polymer knots. Here, we use Brownian Dynamics simulations to study knot diffusion along a linear polymer chain. The model is parameterized to dsDNA, a model polymer used in previous simulation and experimental studies of knot dynamics. We have used this model to study the process of knot escape and transport along a dsDNA strand extended by an elongational flow. For a range of knot topologies and flow strengths, we show scalings that result in collapse of the data onto a master curve. We show a topologically mediated mode of transport coincides with observed differences in rates of knot transport, and we provide a simple mechanistic explanation for its effect. We anticipate these results will build on the growing body of fundamental studies of knotted polymers and inform future experimental study. This work is supported by the Singapore-MIT Alliance for Research and Technology (SMART) and National Science Foundation (NSF) grant CBET-0852235.

An assessment of irrigation needs and crop yield for the United States under potential climate changes

USGS Publications Warehouse

Brumbelow, Kelly; Georgakakos, Aris P.

2000-01-01

Past assessments of climate change on U.S. agriculture have mostly focused on changes in crop yield. Few studies have included the entire conterminous U.S., and few studies have assessed changing irrigation requirements. None have included the effects of changing soil moisture characteristics as determined by changing climatic forcing. This study assesses changes in irrigation requirements and crop yields for five crops in the areas of the U.S. where they have traditionally been grown. Physiologically-based crop models are used to incorporate inputs of climate, soils, agricultural management, and drought stress tolerance. Soil moisture values from a macroscale hydrologic model run under a future climate scenario are used to initialize soil moisture content at the beginning of each growing season. Historical crop yield data is used to calibrate model parameters and determine locally acceptable drought stress as a management parameter. Changes in irrigation demand and crop yield are assessed for both means and extremes by comparing results for atmospheric forcing close to the present climate with those for a future climate scenario. Assessments using the Canadian Center for Climate Modeling and Analysis General Circulation Model (CGCM1) indicate greater irrigation demands in the southern U.S. and decreased irrigation demands in the northern and western U.S. Crop yields typically increase except for winter wheat in the southern U.S. and corn. Variability in both irrigation demands and crop yields increases in most cases. Assessment results for the CGCM1 climate scenario are compared to those for the Hadley Centre for Climate Prediction and Research GCM (HadCM2) scenario for southwestern Georgia. The comparison shows significant differences in irrigation and yield trends, both in magnitude and direction. The differences reflect the high forecast uncertainty of current GCMs. Nonetheless, both GCMs indicate higher variability in future climatic forcing and, consequently, in the response of agricultural systems.

Coupling of the simultaneous heat and water model with a distributed hydrological model and evaluation of the combined model in a cold region watershed

USDA-ARS?s Scientific Manuscript database

To represent the effects of frozen soil on hydrology in cold regions, a new physically based distributed hydrological model has been developed by coupling the simultaneous heat and water model (SHAW) with the geomorphology based distributed hydrological model (GBHM), under the framework of the water...

Quantifying and Generalizing Hydrologic Responses to Dam Regulation using a Statistical Modeling Approach

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

McManamay, Ryan A

2014-01-01

Despite the ubiquitous existence of dams within riverscapes, much of our knowledge about dams and their environmental effects remains context-specific. Hydrology, more than any other environmental variable, has been studied in great detail with regard to dam regulation. While much progress has been made in generalizing the hydrologic effects of regulation by large dams, many aspects of hydrology show site-specific fidelity to dam operations, small dams (including diversions), and regional hydrologic regimes. A statistical modeling framework is presented to quantify and generalize hydrologic responses to varying degrees of dam regulation. Specifically, the objectives were to 1) compare the effects ofmore » local versus cumulative dam regulation, 2) determine the importance of different regional hydrologic regimes in influencing hydrologic responses to dams, and 3) evaluate how different regulation contexts lead to error in predicting hydrologic responses to dams. Overall, model performance was poor in quantifying the magnitude of hydrologic responses, but performance was sufficient in classifying hydrologic responses as negative or positive. Responses of some hydrologic indices to dam regulation were highly dependent upon hydrologic class membership and the purpose of the dam. The opposing coefficients between local and cumulative-dam predictors suggested that hydrologic responses to cumulative dam regulation are complex, and predicting the hydrology downstream of individual dams, as opposed to multiple dams, may be more easy accomplished using statistical approaches. Results also suggested that particular contexts, including multipurpose dams, high cumulative regulation by multiple dams, diversions, close proximity to dams, and certain hydrologic classes are all sources of increased error when predicting hydrologic responses to dams. Statistical models, such as the ones presented herein, show promise in their ability to model the effects of dam regulation effects at large spatial scales as to generalize the directionality of hydrologic responses.« less

Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

NASA Astrophysics Data System (ADS)

Prudhomme, C.; Haxton, T.; Crooks, S.; Jackson, C.; Barkwith, A.; Williamson, J.; Kelvin, J.; Mackay, J.; Wang, L.; Young, A.; Watts, G.

2012-12-01

The dataset Future Flows Hydrology was developed as part of the project "Future Flows and Groundwater Levels" to provide a consistent set of transient daily river flow and monthly groundwater levels projections across England, Wales and Scotland to enable the investigation of the role of climate variability on river flow and groundwater levels nationally and how this may change in the future. Future Flows Hydrology is derived from Future Flows Climate, a national ensemble projection derived from the Hadley Centre's ensemble projection HadRM3-PPE to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications. Three hydrological models and one groundwater level model were used to derive Future Flows Hydrology, with 30 river sites simulated by two hydrological models to enable assessment of hydrological modelling uncertainty in studying the impact of climate change on the hydrology. Future Flows Hydrology contains an 11-member ensemble of transient projections from January 1951 to December 2098, each associated with a single realisation from a different variant of HadRM3 and a single hydrological model. Daily river flows are provided for 281 river catchments and monthly groundwater levels at 24 boreholes as .csv files containing all 11 ensemble members. When separate simulations are done with two hydrological models, two separate .csv files are provided. Because of potential biases in the climate-hydrology modelling chain, catchment fact sheets are associated with each ensemble. These contain information on the uncertainty associated with the hydrological modelling when driven using observed climate and Future Flows Climate for a period representative of the reference time slice 1961-1990 as described by key hydrological statistics. Graphs of projected changes for selected hydrological indicators are also provided for the 2050s time slice. Limitations associated with the dataset are provided, along with practical recommendation of use. Future Flows Hydrology is freely available for non-commercial use under certain licensing conditions. For each study site, catchment averages of daily precipitation and monthly potential evapotranspiration, used to drive the hydrological models, are made available, so that hydrological modelling uncertainty under climate change conditions can be explored further. doi:10.5285/f3723162-4fed-4d9d-92c6-dd17412fa37b.

Future Flows Hydrology: an ensemble of daily river flow and monthly groundwater levels for use for climate change impact assessment across Great Britain

NASA Astrophysics Data System (ADS)

Prudhomme, C.; Haxton, T.; Crooks, S.; Jackson, C.; Barkwith, A.; Williamson, J.; Kelvin, J.; Mackay, J.; Wang, L.; Young, A.; Watts, G.

2013-03-01

The dataset Future Flows Hydrology was developed as part of the project "Future Flows and Groundwater Levels'' to provide a consistent set of transient daily river flow and monthly groundwater level projections across England, Wales and Scotland to enable the investigation of the role of climate variability on river flow and groundwater levels nationally and how this may change in the future. Future Flows Hydrology is derived from Future Flows Climate, a national ensemble projection derived from the Hadley Centre's ensemble projection HadRM3-PPE to provide a consistent set of climate change projections for the whole of Great Britain at both space and time resolutions appropriate for hydrological applications. Three hydrological models and one groundwater level model were used to derive Future Flows Hydrology, with 30 river sites simulated by two hydrological models to enable assessment of hydrological modelling uncertainty in studying the impact of climate change on the hydrology. Future Flows Hydrology contains an 11-member ensemble of transient projections from January 1951 to December 2098, each associated with a single realisation from a different variant of HadRM3 and a single hydrological model. Daily river flows are provided for 281 river catchments and monthly groundwater levels at 24 boreholes as .csv files containing all 11 ensemble members. When separate simulations are done with two hydrological models, two separate .csv files are provided. Because of potential biases in the climate-hydrology modelling chain, catchment fact sheets are associated with each ensemble. These contain information on the uncertainty associated with the hydrological modelling when driven using observed climate and Future Flows Climate for a period representative of the reference time slice 1961-1990 as described by key hydrological statistics. Graphs of projected changes for selected hydrological indicators are also provided for the 2050s time slice. Limitations associated with the dataset are provided, along with practical recommendation of use. Future Flows Hydrology is freely available for non-commercial use under certain licensing conditions. For each study site, catchment averages of daily precipitation and monthly potential evapotranspiration, used to drive the hydrological models, are made available, so that hydrological modelling uncertainty under climate change conditions can be explored further. doi:10.5285/f3723162-4fed-4d9d-92c6-dd17412fa37b

Workshop summary: Physical properties of gas hydrate-bearing sediment

USGS Publications Warehouse

Waite, William F.; Santamarina, J.C.

2008-01-01

A wide range of particle and pore scale phenomena, often coupled, determines the macro-scale response of gas-hydrate bearing sediment to changes in mechanical, thermal, or chemical conditions. Predicting this macro-scale response is critical for applications such as optimizing the production of methane from gas-hydrate deposits, or determining the role of gas hydrates in global carbon cycling and climate change.

Macroscale intraspecific variation and environmental heterogeneity: analysis of cold and warm zone abundance, mortality, and regeneration distributions of four eastern US tree species

Treesearch

Anantha M. Prasad

2015-01-01

I test for macroscale intraspecific variation of abundance, mortality, and regeneration of four eastern US tree species (Tsuga canadensis, Betula lenta, Liriodendron tulipifera, and Quercus prinus) by splitting them into three climatic zones based on plant hardiness zones (PHZs). The primary goals of the analysis are to assess the...

Multi-model ensemble hydrological simulation using a BP Neural Network for the upper Yalongjiang River Basin, China

NASA Astrophysics Data System (ADS)

Li, Zhanjie; Yu, Jingshan; Xu, Xinyi; Sun, Wenchao; Pang, Bo; Yue, Jiajia

2018-06-01

Hydrological models are important and effective tools for detecting complex hydrological processes. Different models have different strengths when capturing the various aspects of hydrological processes. Relying on a single model usually leads to simulation uncertainties. Ensemble approaches, based on multi-model hydrological simulations, can improve application performance over single models. In this study, the upper Yalongjiang River Basin was selected for a case study. Three commonly used hydrological models (SWAT, VIC, and BTOPMC) were selected and used for independent simulations with the same input and initial values. Then, the BP neural network method was employed to combine the results from the three models. The results show that the accuracy of BP ensemble simulation is better than that of the single models.

A finite-element model for moving contact line problems in immiscible two-phase flow

NASA Astrophysics Data System (ADS)

Kucala, Alec

2017-11-01

Accurate modeling of moving contact line (MCL) problems is imperative in predicting capillary pressure vs. saturation curves, permeability, and preferential flow paths for a variety of applications, including geological carbon storage (GCS) and enhanced oil recovery (EOR). The macroscale movement of the contact line is dependent on the molecular interactions occurring at the three-phase interface, however most MCL problems require resolution at the meso- and macro-scale. A phenomenological model must be developed to account for the microscale interactions, as resolving both the macro- and micro-scale would render most problems computationally intractable. Here, a model for the moving contact line is presented as a weak forcing term in the Navier-Stokes equation and applied directly at the location of the three-phase interface point. The moving interface is tracked with the level set method and discretized using the conformal decomposition finite element method (CDFEM), allowing for the surface tension and the wetting model to be computed at the exact interface location. A variety of verification test cases for simple two- and three-dimensional geometries are presented to validate the current MCL model, which can exhibit grid independence when a proper scaling for the slip length is chosen. Sandia National Laboratories is a multi-mission laboratory managed and operated by National Technology and Engineering Solutions of Sandia, LLC., a wholly owned subsidiary of Honeywell International, Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA-0003525.

Description of the National Hydrologic Model for use with the Precipitation-Runoff Modeling System (PRMS)

USGS Publications Warehouse

Regan, R. Steven; Markstrom, Steven L.; Hay, Lauren E.; Viger, Roland J.; Norton, Parker A.; Driscoll, Jessica M.; LaFontaine, Jacob H.

2018-01-08

This report documents several components of the U.S. Geological Survey National Hydrologic Model of the conterminous United States for use with the Precipitation-Runoff Modeling System (PRMS). It provides descriptions of the (1) National Hydrologic Model, (2) Geospatial Fabric for National Hydrologic Modeling, (3) PRMS hydrologic simulation code, (4) parameters and estimation methods used to compute spatially and temporally distributed default values as required by PRMS, (5) National Hydrologic Model Parameter Database, and (6) model extraction tool named Bandit. The National Hydrologic Model Parameter Database contains values for all PRMS parameters used in the National Hydrologic Model. The methods and national datasets used to estimate all the PRMS parameters are described. Some parameter values are derived from characteristics of topography, land cover, soils, geology, and hydrography using traditional Geographic Information System methods. Other parameters are set to long-established default values and computation of initial values. Additionally, methods (statistical, sensitivity, calibration, and algebraic) were developed to compute parameter values on the basis of a variety of nationally-consistent datasets. Values in the National Hydrologic Model Parameter Database can periodically be updated on the basis of new parameter estimation methods and as additional national datasets become available. A companion ScienceBase resource provides a set of static parameter values as well as images of spatially-distributed parameters associated with PRMS states and fluxes for each Hydrologic Response Unit across the conterminuous United States.

Two-scale modeling of joining of the aluminum alloys by a cohesive zone element technique

NASA Astrophysics Data System (ADS)

Zuo, Yinan; Wulfinghoff, Stephan; Reese, Stefanie

2016-10-01

The roll bonding of aluminum sheets is numerically investigated. In the first part of the paper, a cohesive zone element formulation in the framework of zero-thickness interface elements is developed. Based on a traction-separation law, this enables the modeling of bonding and debonding on both macroscale and microscale. Simulations on microscale are done to show the mechanism of bonding and the influence of different factors on the bonding strength.

Coupled Crop/Hydrology Model to Estimate Expanded Irrigation Impact on Water Resources

NASA Astrophysics Data System (ADS)

Handyside, C. T.; Cruise, J.

2017-12-01

A coupled agricultural and hydrologic systems model is used to examine the environmental impact of irrigation in the Southeast. A gridded crop model for the Southeast is used to determine regional irrigation demand. This irrigation demand is used in a regional hydrologic model to determine the hydrologic impact of irrigation. For the Southeast to maintain/expand irrigated agricultural production and provide adaptation to climate change and climate variability it will require integrated agricultural and hydrologic system models that can calculate irrigation demand and the impact of the this demand on the river hydrology. These integrated models can be used as (1) historical tools to examine vulnerability of expanded irrigation to past climate extremes (2) future tools to examine the sustainability of expanded irrigation under future climate scenarios and (3) a real-time tool to allow dynamic water resource management. Such tools are necessary to assure stakeholders and the public that irrigation can be carried out in a sustainable manner. The system tools to be discussed include a gridded version of the crop modeling system (DSSAT). The gridded model is referred to as GriDSSAT. The irrigation demand from GriDSSAT is coupled to a regional hydrologic model developed by the Eastern Forest Environmental Threat Assessment Center of the USDA Forest Service) (WaSSI). The crop model provides the dynamic irrigation demand which is a function of the weather. The hydrologic model includes all other competing uses of water. Examples of use the crop model coupled with the hydrologic model include historical analyses which show the change in hydrology as additional acres of irrigated land are added to water sheds. The first order change in hydrology is computed in terms of changes in the Water Availability Stress Index (WASSI) which is the ratio of water demand (irrigation, public water supply, industrial use, etc.) and water availability from the hydrologic model. Also, statistics such as the number of times certain WASSI thresholds are exceeded are calculated to show the impact of expanded irrigation during times of hydrologic drought and the coincident use of water by other sectors. Also, integrated downstream impacts of irrigation are also calculated through changes in flows through the whole river systems.

Modeling the effect of land use change on hydrology of a forested watershed in coastal South Carolina.

Treesearch

Zhaohua Dai; Devendra M. Amatya; Ge Sun; Changsheng Li; Carl C. Trettin; Harbin Li

2009-01-01

Since hydrology is one of main factors controlling wetland functions, hydrologic models are useful for evaluating the effects of land use change on we land ecosystems. We evaluated two process-based hydrologic models with...

Linking microstructural evolution and macro-scale friction behavior in metals [Predicting the friction behavior of metals using a microstructural evolution model

DOE PAGES

Argibay, N.; Chandross, M.; Cheng, S.; ...

2016-11-21

A correlation is established between the macro-scale friction regimes of metals and a transition between two dominant atomistic mechanisms of deformation. Metals tend to exhibit bi-stable friction behavior—low and converging or high and diverging. These general trends in behavior are shown to be largely explained using a simplified model based on grain size evolution, as a function of contact stress and temperature, and are demonstrated for self-mated pure copper and gold sliding contacts. Specifically, the low-friction regime (where µ < 0.5) is linked to the formation of ultra-nanocrystalline surface films (10–20 nm), driving toward shear accommodation by grain boundary sliding.more » Above a critical combination of stress and temperature—demonstrated to be a material property—shear accommodation transitions to dislocation dominated plasticity and high friction, with µ > 0.5. We utilize a combination of experimental and computational methods to develop and validate the proposed structure–property relationship. As a result, this quantitative framework provides a shift from phenomenological to mechanistic and predictive fundamental understanding of friction for crystalline materials, including engineering alloys.« less

A "total parameter estimation" method in the varification of distributed hydrological models

NASA Astrophysics Data System (ADS)

Wang, M.; Qin, D.; Wang, H.

2011-12-01

Conventionally hydrological models are used for runoff or flood forecasting, hence the determination of model parameters are common estimated based on discharge measurements at the catchment outlets. With the advancement in hydrological sciences and computer technology, distributed hydrological models based on the physical mechanism such as SWAT, MIKESHE, and WEP, have gradually become the mainstream models in hydrology sciences. However, the assessments of distributed hydrological models and model parameter determination still rely on runoff and occasionally, groundwater level measurements. It is essential in many countries, including China, to understand the local and regional water cycle: not only do we need to simulate the runoff generation process and for flood forecasting in wet areas, we also need to grasp the water cycle pathways and consumption process of transformation in arid and semi-arid regions for the conservation and integrated water resources management. As distributed hydrological model can simulate physical processes within a catchment, we can get a more realistic representation of the actual water cycle within the simulation model. Runoff is the combined result of various hydrological processes, using runoff for parameter estimation alone is inherits problematic and difficult to assess the accuracy. In particular, in the arid areas, such as the Haihe River Basin in China, runoff accounted for only 17% of the rainfall, and very concentrated during the rainy season from June to August each year. During other months, many of the perennial rivers within the river basin dry up. Thus using single runoff simulation does not fully utilize the distributed hydrological model in arid and semi-arid regions. This paper proposed a "total parameter estimation" method to verify the distributed hydrological models within various water cycle processes, including runoff, evapotranspiration, groundwater, and soil water; and apply it to the Haihe river basin in China. The application results demonstrate that this comprehensive testing method is very useful in the development of a distributed hydrological model and it provides a new way of thinking in hydrological sciences.

Effective properties of a fly ash geopolymer: Synergistic application of X-ray synchrotron tomography, nanoindentation, and homogenization models

DOE PAGES

Das, Sumanta; Yang, Pu; Singh, Sudhanshu S.; ...

2015-09-02

Microstructural and micromechanical investigation of a fly ash-based geopolymer using: (i) synchrotron x-ray tomography (XRT) to determine the volume fraction and tortuosity of pores that are influential in fluid transport, (ii) mercury intrusion porosimetry (MIP) to capture the volume fraction of smaller pores, (iii) scanning electron microscopy (SEM) combined with multi-label thresholding to identify and characterize the solid phases in the microstructure, and (iv) nanoindentation to determine the component phase elastic properties using statistical deconvolution, is reported in this paper. The phase volume fractions and elastic properties are used in multi-step mean field homogenization (Mori- Tanaka and double inclusion) modelsmore » to determine the homogenized macroscale elastic modulus of the composite. The homogenized elastic moduli are in good agreement with the flexural elastic modulus determined on macroscale paste beams. As a result, the combined use of microstructural and micromechanical characterization tools at multiple scales provides valuable information towards the material design of fly ash geopolymers.« less

Effect of friction on vibrotactile sensation of normal and dehydrated skin.

PubMed

Chen, S; Ge, S; Tang, W; Zhang, J

2016-02-01

Vibrotactile sensation mediated is highly dependent on surface mechanical and frictional properties. Dehydration of skin could change these properties. To investigate the relationship between friction and vibrotactile sensation of normal and dehydrated skin. Vibrations were firstly measured during surface exploration using a biomimetic sensor. Piglet skin was used as human skin model to study frictional properties for both normal and dehydrated skin using an atomic force microscope on nanoscale and a pin-on-disk tribometer on macroscale. Effect of vibrational frequency on friction and vibrotactile perception was also observed on nano and macro scale for normal and dehydrated skin. The result indicated that dehydrated skin was less sensitive than normal skin. The coefficient of friction of dehydrated skin is smaller than that of normal skin on both nano and macro scale. The coefficient of friction increases as increasing scanning frequencies. There is a positive correlation between coefficient of friction and vibrotactile sensation on nanoscale and macroscale. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Assimilation of remote sensing observations into a continuous distributed hydrological model: impacts on the hydrologic cycle

NASA Astrophysics Data System (ADS)

Laiolo, Paola; Gabellani, Simone; Campo, Lorenzo; Cenci, Luca; Silvestro, Francesco; Delogu, Fabio; Boni, Giorgio; Rudari, Roberto

2015-04-01

The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce in-situ data. This work investigates the impact of the assimilation of different remote sensing products on the hydrological cycle by using a continuous physically based distributed hydrological model. Three soil moisture products derived by ASCAT (Advanced SCATterometer) are used to update the model state variables. The satellite-derived products are assimilated into the hydrological model using different assimilation techniques: a simple nudging and the Ensemble Kalman Filter. Moreover two assimilation strategies are evaluated to assess the impact of assimilating the satellite products at model spatial resolution or at the satellite scale. The experiments are carried out for three Italian catchments on multi year period. The benefits on the model predictions of discharge, LST, evapotranspiration and soil moisture dynamics are tested and discussed.

Jump-Diffusion models and structural changes for asset forecasting in hydrology

NASA Astrophysics Data System (ADS)

Tranquille Temgoua, André Guy; Martel, Richard; Chang, Philippe J. J.; Rivera, Alfonso

2017-04-01

Impacts of climate change on surface water and groundwater are of concern in many regions of the world since water is an essential natural resource. Jump-Diffusion models are generally used in economics and other related fields but not in hydrology. The potential application could be made for hydrologic data series analysis and forecast. The present study uses Jump-Diffusion models by adding structural changes to detect fluctuations in hydrologic processes in relationship with climate change. The model implicitly assumes that modifications in rivers' flowrates can be divided into three categories: (a) normal changes due to irregular precipitation events especially in tropical regions causing major disturbance in hydrologic processes (this component is modelled by a discrete Brownian motion); (b) abnormal, sudden and non-persistent modifications in hydrologic proceedings are handled by Poisson processes; (c) the persistence of hydrologic fluctuations characterized by structural changes in hydrological data related to climate variability. The objective of this paper is to add structural changes in diffusion models with jumps, in order to capture the persistence of hydrologic fluctuations. Indirectly, the idea is to observe if there are structural changes of discharge/recharge over the study area, and to find an efficient and flexible model able of capturing a wide variety of hydrologic processes. Structural changes in hydrological data are estimated using the method of nonlinear discrete filters via Method of Simulated Moments (MSM). An application is given using sensitive parameters such as baseflow index and recession coefficient to capture discharge/recharge. Historical dataset are examined by the Volume Spread Analysis (VSA) to detect real time and random perturbations in hydrologic processes. The application of the method allows establishing more accurate hydrologic parameters. The impact of this study is perceptible in forecasting floods and groundwater recession. Keywords: hydrologic processes, Jump-Diffusion models, structural changes, forecast, climate change

Upscaling from research watersheds: an essential stage of trustworthy general-purpose hydrologic model building

NASA Astrophysics Data System (ADS)

McNamara, J. P.; Semenova, O.; Restrepo, P. J.

2011-12-01

Highly instrumented research watersheds provide excellent opportunities for investigating hydrologic processes. A danger, however, is that the processes observed at a particular research watershed are too specific to the watershed and not representative even of the larger scale watershed that contains that particular research watershed. Thus, models developed based on those partial observations may not be suitable for general hydrologic use. Therefore demonstrating the upscaling of hydrologic process from research watersheds to larger watersheds is essential to validate concepts and test model structure. The Hydrograph model has been developed as a general-purpose process-based hydrologic distributed system. In its applications and further development we evaluate the scaling of model concepts and parameters in a wide range of hydrologic landscapes. All models, either lumped or distributed, are based on a discretization concept. It is common practice that watersheds are discretized into so called hydrologic units or hydrologic landscapes possessing assumed homogeneous hydrologic functioning. If a model structure is fixed, the difference in hydrologic functioning (difference in hydrologic landscapes) should be reflected by a specific set of model parameters. Research watersheds provide the possibility for reasonable detailed combining of processes into some typical hydrologic concept such as hydrologic units, hydrologic forms, and runoff formation complexes in the Hydrograph model. And here by upscaling we imply not the upscaling of a single process but upscaling of such unified hydrologic functioning. The simulation of runoff processes for the Dry Creek research watershed, Idaho, USA (27 km2) was undertaken using the Hydrograph model. The information on the watershed was provided by Boise State University and included a GIS database of watershed characteristics and a detailed hydrometeorological observational dataset. The model provided good simulation results in terms of runoff and variable states of soil and snow over a simulation period 2000 - 2009. The parameters of the model were hand-adjusted based on rational sense, observational data and available understanding of underlying processes. For the first run some processes as riparian vegetation impact on runoff and streamflow/groundwater interaction were handled in a conceptual way. It was shown that the use of Hydrograph model which requires modest amount of parameter calibration may serve also as a quality control for observations. Based on the obtained parameters values and process understanding at the research watershed the model was applied to the larger scale watersheds located in similar environment - the Boise River at South Fork (1660 km2) and Twin Springs (2155 km2). The evaluation of the results of such upscaling will be presented.

Development of a biosphere hydrological model considering vegetation dynamics and its evaluation at basin scale under climate change

NASA Astrophysics Data System (ADS)

Li, Qiaoling; Ishidaira, Hiroshi

2012-01-01

SummaryThe biosphere and hydrosphere are intrinsically coupled. The scientific question is if there is a substantial change in one component such as vegetation cover, how will the other components such as transpiration and runoff generation respond, especially under climate change conditions? Stand-alone hydrological models have a detailed description of hydrological processes but do not sufficiently parameterize vegetation as a dynamic component. Dynamic global vegetation models (DGVMs) are able to simulate transient structural changes in major vegetation types but do not simulate runoff generation reliably. Therefore, both hydrological models and DGVMs have their limitations as well as advantages for addressing this question. In this study a biosphere hydrological model (LPJH) is developed by coupling a prominent DGVM (Lund-Postdam-Jena model referred to as LPJ) with a stand-alone hydrological model (HYMOD), with the objective of analyzing the role of vegetation in the hydrological processes at basin scale and evaluating the impact of vegetation change on the hydrological processes under climate change. The application and validation of the LPJH model to four basins representing a variety of climate and vegetation conditions shows that the performance of LPJH is much better than that of the original LPJ and is similar to that of stand-alone hydrological models for monthly and daily runoff simulation at the basin scale. It is argued that the LPJH model gives more reasonable hydrological simulation since it considers both the spatial variability of soil moisture and vegetation dynamics, which make the runoff generation mechanism more reliable. As an example, it is shown that changing atmospheric CO 2 content alone would result in runoff increases in humid basins and decreases in arid basins. Theses changes are mainly attributable to changes in transpiration driven by vegetation dynamics, which are not simulated in stand-alone hydrological models. Therefore LPJH potentially provides a powerful tool for simulating vegetation response to climate changes in the biosphere hydrological cycle.

An Educational Model for Hands-On Hydrology Education

NASA Astrophysics Data System (ADS)

AghaKouchak, A.; Nakhjiri, N.; Habib, E. H.

2014-12-01

This presentation provides an overview of a hands-on modeling tool developed for students in civil engineering and earth science disciplines to help them learn the fundamentals of hydrologic processes, model calibration, sensitivity analysis, uncertainty assessment, and practice conceptual thinking in solving engineering problems. The toolbox includes two simplified hydrologic models, namely HBV-EDU and HBV-Ensemble, designed as a complement to theoretical hydrology lectures. The models provide an interdisciplinary application-oriented learning environment that introduces the hydrologic phenomena through the use of a simplified conceptual hydrologic model. The toolbox can be used for in-class lab practices and homework assignments, and assessment of students' understanding of hydrological processes. Using this modeling toolbox, students can gain more insights into how hydrological processes (e.g., precipitation, snowmelt and snow accumulation, soil moisture, evapotranspiration and runoff generation) are interconnected. The educational toolbox includes a MATLAB Graphical User Interface (GUI) and an ensemble simulation scheme that can be used for teaching more advanced topics including uncertainty analysis, and ensemble simulation. Both models have been administered in a class for both in-class instruction and a final project, and students submitted their feedback about the toolbox. The results indicate that this educational software had a positive impact on students understanding and knowledge of hydrology.

Research on Multi Hydrological Models Applicability and Modelling Data Uncertainty Analysis for Flash Flood Simulation in Hilly Area

NASA Astrophysics Data System (ADS)

Ye, L.; Wu, J.; Wang, L.; Song, T.; Ji, R.

2017-12-01

Flooding in small-scale watershed in hilly area is characterized by short time periods and rapid rise and recession due to the complex underlying surfaces, various climate type and strong effect of human activities. It is almost impossible for a single hydrological model to describe the variation of flooding in both time and space accurately for all the catchments in hilly area because the hydrological characteristics can vary significantly among different catchments. In this study, we compare the performance of 5 hydrological models with varying degrees of complexity for simulation of flash flood for 14 small-scale watershed in China in order to find the relationship between the applicability of the hydrological models and the catchments characteristics. Meanwhile, given the fact that the hydrological data is sparse in hilly area, the effect of precipitation data, DEM resolution and their interference on the uncertainty of flood simulation is also illustrated. In general, the results showed that the distributed hydrological model (HEC-HMS in this study) performed better than the lumped hydrological models. Xinajiang and API models had good simulation for the humid catchments when long-term and continuous rainfall data is provided. Dahuofang model can simulate the flood peak well while the runoff generation module is relatively poor. In addition, the effect of diverse modelling data on the simulations is not simply superposed, and there is a complex interaction effect among different modelling data. Overall, both the catchment hydrological characteristics and modelling data situation should be taken into consideration in order to choose the suitable hydrological model for flood simulation for small-scale catchment in hilly area.

Modeling Materials: Design for Planetary Entry, Electric Aircraft, and Beyond

NASA Technical Reports Server (NTRS)

Thompson, Alexander; Lawson, John W.

2014-01-01

NASA missions push the limits of what is possible. The development of high-performance materials must keep pace with the agency's demanding, cutting-edge applications. Researchers at NASA's Ames Research Center are performing multiscale computational modeling to accelerate development times and further the design of next-generation aerospace materials. Multiscale modeling combines several computationally intensive techniques ranging from the atomic level to the macroscale, passing output from one level as input to the next level. These methods are applicable to a wide variety of materials systems. For example: (a) Ultra-high-temperature ceramics for hypersonic aircraft-we utilized the full range of multiscale modeling to characterize thermal protection materials for faster, safer air- and spacecraft, (b) Planetary entry heat shields for space vehicles-we computed thermal and mechanical properties of ablative composites by combining several methods, from atomistic simulations to macroscale computations, (c) Advanced batteries for electric aircraft-we performed large-scale molecular dynamics simulations of advanced electrolytes for ultra-high-energy capacity batteries to enable long-distance electric aircraft service; and (d) Shape-memory alloys for high-efficiency aircraft-we used high-fidelity electronic structure calculations to determine phase diagrams in shape-memory transformations. Advances in high-performance computing have been critical to the development of multiscale materials modeling. We used nearly one million processor hours on NASA's Pleiades supercomputer to characterize electrolytes with a fidelity that would be otherwise impossible. For this and other projects, Pleiades enables us to push the physics and accuracy of our calculations to new levels.

Development of efficient and cost-effective distributed hydrological modeling tool MWEasyDHM based on open-source MapWindow GIS

NASA Astrophysics Data System (ADS)

Lei, Xiaohui; Wang, Yuhui; Liao, Weihong; Jiang, Yunzhong; Tian, Yu; Wang, Hao

2011-09-01

Many regions are still threatened with frequent floods and water resource shortage problems in China. Consequently, the task of reproducing and predicting the hydrological process in watersheds is hard and unavoidable for reducing the risks of damage and loss. Thus, it is necessary to develop an efficient and cost-effective hydrological tool in China as many areas should be modeled. Currently, developed hydrological tools such as Mike SHE and ArcSWAT (soil and water assessment tool based on ArcGIS) show significant power in improving the precision of hydrological modeling in China by considering spatial variability both in land cover and in soil type. However, adopting developed commercial tools in such a large developing country comes at a high cost. Commercial modeling tools usually contain large numbers of formulas, complicated data formats, and many preprocessing or postprocessing steps that may make it difficult for the user to carry out simulation, thus lowering the efficiency of the modeling process. Besides, commercial hydrological models usually cannot be modified or improved to be suitable for some special hydrological conditions in China. Some other hydrological models are open source, but integrated into commercial GIS systems. Therefore, by integrating hydrological simulation code EasyDHM, a hydrological simulation tool named MWEasyDHM was developed based on open-source MapWindow GIS, the purpose of which is to establish the first open-source GIS-based distributed hydrological model tool in China by integrating modules of preprocessing, model computation, parameter estimation, result display, and analysis. MWEasyDHM provides users with a friendly manipulating MapWindow GIS interface, selectable multifunctional hydrological processing modules, and, more importantly, an efficient and cost-effective hydrological simulation tool. The general construction of MWEasyDHM consists of four major parts: (1) a general GIS module for hydrological analysis, (2) a preprocessing module for modeling inputs, (3) a model calibration module, and (4) a postprocessing module. The general GIS module for hydrological analysis is developed on the basis of totally open-source GIS software, MapWindow, which contains basic GIS functions. The preprocessing module is made up of three submodules including a DEM-based submodule for hydrological analysis, a submodule for default parameter calculation, and a submodule for the spatial interpolation of meteorological data. The calibration module contains parallel computation, real-time computation, and visualization. The postprocessing module includes model calibration and model results spatial visualization using tabular form and spatial grids. MWEasyDHM makes it possible for efficient modeling and calibration of EasyDHM, and promises further development of cost-effective applications in various watersheds.

Development of a distributed biosphere hydrological model and its evaluation with the Southern Great Plains Experiments (SGP97 and SGP99)

USDA-ARS?s Scientific Manuscript database

A distributed biosphere hydrological model, the so called water and energy budget-based distributed hydrological model (WEB-DHM), has been developed by fully coupling a biosphere scheme (SiB2) with a geomorphology-based hydrological model (GBHM). SiB2 describes the transfer of turbulent fluxes (ener...

Hydrological excitation of polar motion by different variables of the GLDAS models

NASA Astrophysics Data System (ADS)

Wińska, Małgorzata; Nastula, Jolanta

Continental hydrological loading, by land water, snow, and ice, is an element that is strongly needed for a full understanding of the excitation of polar motion. In this study we compute different estimations of hydrological excitation functions of polar motion (Hydrological Angular Momentum - HAM) using various variables from the Global Land Data Assimilation System (GLDAS) models of land hydrosphere. The main aim of this study is to show the influence of different variables for example: total evapotranspiration, runoff, snowmelt, soil moisture to polar motion excitations in annual and short term scale. In our consideration we employ several realizations of the GLDAS model as: GLDAS Common Land Model (CLM), GLDAS Mosaic Model, GLDAS National Centers for Environmental Prediction/Oregon State University/Air Force/Hydrologic Research Lab Model (Noah), GLDAS Variable Infiltration Capacity (VIC) Model. Hydrological excitation functions of polar motion, both global and regional, are determined by using selected variables of these GLDAS realizations. First we compare a timing, spectra and phase diagrams of different regional and global HAMs with each other. Next, we estimate, the hydrological signal in geodetically observed polar motion excitation by subtracting the atmospheric -- AAM (pressure + wind) and oceanic -- OAM (bottom pressure + currents) contributions. Finally, the hydrological excitations are compared to these hydrological signal in observed polar motion excitation series. The results help us understand which variables of considered hydrological models are the most important for the polar motion excitation and how well we can close polar motion excitation budget in the seasonal and inter-annual spectral ranges.

Using Non-linear Homogenization to Improve the Performance of Macroscopic Damage Models of Trabecular Bone.

PubMed

Levrero-Florencio, Francesc; Pankaj, Pankaj

2018-01-01

Realistic macro-level finite element simulations of the mechanical behavior of trabecular bone, a cellular anisotropic material, require a suitable constitutive model; a model that incorporates the mechanical response of bone for complex loading scenarios and includes post-elastic phenomena, such as plasticity (permanent deformations) and damage (permanent stiffness reduction), which bone is likely to experience. Some such models have been developed by conducting homogenization-based multiscale finite element simulations on bone micro-structure. While homogenization has been fairly successful in the elastic regime and, to some extent, in modeling the macroscopic plastic response, it has remained a challenge with respect to modeling damage. This study uses a homogenization scheme to upscale the damage behavior from the tissue level (microscale) to the organ level (macroscale) and assesses the suitability of different damage constitutive laws. Ten cubic specimens were each subjected to 21 strain-controlled load cases for a small range of macroscopic post-elastic strains. Isotropic and anisotropic criteria were considered, density and fabric relationships were used in the formulation of the damage law, and a combined isotropic/anisotropic law with tension/compression asymmetry was formulated, based on the homogenized results, as a possible alternative to the currently used single scalar damage criterion. This computational study enhances the current knowledge on the macroscopic damage behavior of trabecular bone. By developing relationships of damage progression with bone's micro-architectural indices (density and fabric) the study also provides an aid for the creation of more precise macroscale continuum models, which are likely to improve clinical predictions.

The case for applying tissue engineering methodologies to instruct human organoid morphogenesis.

PubMed

Marti-Figueroa, Carlos R; Ashton, Randolph S

2017-05-01

Three-dimensional organoids derived from human pluripotent stem cell (hPSC) derivatives have become widely used in vitro models for studying development and disease. Their ability to recapitulate facets of normal human development during in vitro morphogenesis produces tissue structures with unprecedented biomimicry. Current organoid derivation protocols primarily rely on spontaneous morphogenesis processes to occur within 3-D spherical cell aggregates with minimal to no exogenous control. This yields organoids containing microscale regions of biomimetic tissues, but at the macroscale (i.e. 100's of microns to millimeters), the organoids' morphology, cytoarchitecture, and cellular composition are non-biomimetic and variable. The current lack of control over in vitro organoid morphogenesis at the microscale induces aberrations at the macroscale, which impedes realization of the technology's potential to reproducibly form anatomically correct human tissue units that could serve as optimal human in vitro models and even transplants. Here, we review tissue engineering methodologies that could be used to develop powerful approaches for instructing multiscale, 3-D human organoid morphogenesis. Such technological mergers are critically needed to harness organoid morphogenesis as a tool for engineering functional human tissues with biomimetic anatomy and physiology. Human PSC-derived 3-D organoids are revolutionizing the biomedical sciences. They enable the study of development and disease within patient-specific genetic backgrounds and unprecedented biomimetic tissue microenvironments. However, their uncontrolled, spontaneous morphogenesis at the microscale yields inconsistences in macroscale organoid morphology, cytoarchitecture, and cellular composition that limits their standardization and application. Integration of tissue engineering methods with organoid derivation protocols could allow us to harness their potential by instructing standardized in vitro morphogenesis to generate organoids with biomimicry at all scales. Such advancements would enable the use of organoids as a basis for 'next-generation' tissue engineering of functional, anatomically mimetic human tissues and potentially novel organ transplants. Here, we discuss critical aspects of organoid morphogenesis where application of innovative tissue engineering methodologies would yield significant advancement towards this goal. Copyright © 2017. Published by Elsevier Ltd.

Evaluation of Hydrologic Simulations Developed Using Multi-Model Synthesis and Remotely-Sensed Data within a Portfolio of Calibration Strategies

NASA Astrophysics Data System (ADS)

Lafontaine, J.; Hay, L.; Markstrom, S. L.

2016-12-01

The United States Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the conterminous United States (CONUS). As many stream reaches in the CONUS are either not gaged, or are substantially impacted by water use or flow regulation, ancillary information must be used to determine reasonable parameter estimations for streamflow simulations. Hydrologic models for 1,576 gaged watersheds across the CONUS were developed to test the feasibility of improving streamflow simulations linking physically-based hydrologic models with remotely-sensed data products (i.e. snow water equivalent). Initially, the physically-based models were calibrated to measured streamflow data to provide a baseline for comparison across multiple calibration strategy tests. In addition, not all ancillary datasets are appropriate for application to all parts of the CONUS (e.g. snow water equivalent in the southeastern U.S., where snow is a rarity). As it is not expected that any one data product or model simulation will be sufficient for representing hydrologic behavior across the entire CONUS, a systematic evaluation of which data products improve hydrologic simulations for various regions across the CONUS was performed. The resulting portfolio of calibration strategies can be used to guide selection of an appropriate combination of modeled and measured information for hydrologic model development and calibration. In addition, these calibration strategies have been developed to be flexible so that new data products can be assimilated. This analysis provides a foundation to understand how well models work when sufficient streamflow data are not available and could be used to further inform hydrologic model parameter development for ungaged areas.

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

On the Hydrologic Adjustment of Climate-Model Projections: The Potential Pitfall of Potential Evapotranspiration

USGS Publications Warehouse

Milly, Paul C.D.; Dunne, Krista A.

2011-01-01

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement ("downscaling"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median -11%) caused by the hydrologic model’s apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen–Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors’ findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climate-change impacts on water.

Design and Implementation of Hydrologic Process Knowledge-base Ontology: A case study for the Infiltration Process

NASA Astrophysics Data System (ADS)

Elag, M.; Goodall, J. L.

2013-12-01

Hydrologic modeling often requires the re-use and integration of models from different disciplines to simulate complex environmental systems. Component-based modeling introduces a flexible approach for integrating physical-based processes across disciplinary boundaries. Several hydrologic-related modeling communities have adopted the component-based approach for simulating complex physical systems by integrating model components across disciplinary boundaries in a workflow. However, it is not always straightforward to create these interdisciplinary models due to the lack of sufficient knowledge about a hydrologic process. This shortcoming is a result of using informal methods for organizing and sharing information about a hydrologic process. A knowledge-based ontology provides such standards and is considered the ideal approach for overcoming this challenge. The aims of this research are to present the methodology used in analyzing the basic hydrologic domain in order to identify hydrologic processes, the ontology itself, and how the proposed ontology is integrated with the Water Resources Component (WRC) ontology. The proposed ontology standardizes the definitions of a hydrologic process, the relationships between hydrologic processes, and their associated scientific equations. The objective of the proposed Hydrologic Process (HP) Ontology is to advance the idea of creating a unified knowledge framework for components' metadata by introducing a domain-level ontology for hydrologic processes. The HP ontology is a step toward an explicit and robust domain knowledge framework that can be evolved through the contribution of domain users. Analysis of the hydrologic domain is accomplished using the Formal Concept Approach (FCA), in which the infiltration process, an important hydrologic process, is examined. Two infiltration methods, the Green-Ampt and Philip's methods, were used to demonstrate the implementation of information in the HP ontology. Furthermore, a SPARQL service is provided for semantic-based querying of the ontology.

Hierarchical Co-Assembly Enhanced Direct Ink Writing.

PubMed

Li, Longyu; Zhang, Pengfei; Zhang, Zhiyun; Lin, Qianming; Wu, Yuyang; Cheng, Alexander; Lin, Yunxiao; Thompson, Christina M; Smaldone, Ronald A; Ke, Chenfeng

2018-04-23

Integrating intelligent molecular systems into 3D printing materials and transforming their molecular functions to the macroscale with controlled superstructures will unleash great potential for the development of smart materials. Compared to macromolecular 3D printing materials, self-assembled small-molecule-based 3D printing materials are very rare owing to the difficulties of facilitating 3D printability as well as preserving their molecular functions macroscopically. Herein, we report a general approach for the integration of functional small molecules into 3D printing materials for direct ink writing through the introduction of a supramolecular template. A variety of inorganic and organic small-molecule-based inks were 3D-printed, and their superstructures were refined by post-printing hierarchical co-assembly. Through spatial and temporal control of individual molecular events from the nano- to the macroscale, fine-tuned macroscale features were successfully installed in the monoliths. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Virtual hydrology observatory: an immersive visualization of hydrology modeling

NASA Astrophysics Data System (ADS)

Su, Simon; Cruz-Neira, Carolina; Habib, Emad; Gerndt, Andreas

2009-02-01

The Virtual Hydrology Observatory will provide students with the ability to observe the integrated hydrology simulation with an instructional interface by using a desktop based or immersive virtual reality setup. It is the goal of the virtual hydrology observatory application to facilitate the introduction of field experience and observational skills into hydrology courses through innovative virtual techniques that mimic activities during actual field visits. The simulation part of the application is developed from the integrated atmospheric forecast model: Weather Research and Forecasting (WRF), and the hydrology model: Gridded Surface/Subsurface Hydrologic Analysis (GSSHA). Both the output from WRF and GSSHA models are then used to generate the final visualization components of the Virtual Hydrology Observatory. The various visualization data processing techniques provided by VTK are 2D Delaunay triangulation and data optimization. Once all the visualization components are generated, they are integrated into the simulation data using VRFlowVis and VR Juggler software toolkit. VR Juggler is used primarily to provide the Virtual Hydrology Observatory application with fully immersive and real time 3D interaction experience; while VRFlowVis provides the integration framework for the hydrologic simulation data, graphical objects and user interaction. A six-sided CAVETM like system is used to run the Virtual Hydrology Observatory to provide the students with a fully immersive experience.

A question driven socio-hydrological modeling process

NASA Astrophysics Data System (ADS)

Garcia, M.; Portney, K.; Islam, S.

2016-01-01

Human and hydrological systems are coupled: human activity impacts the hydrological cycle and hydrological conditions can, but do not always, trigger changes in human systems. Traditional modeling approaches with no feedback between hydrological and human systems typically cannot offer insight into how different patterns of natural variability or human-induced changes may propagate through this coupled system. Modeling of coupled human-hydrological systems, also called socio-hydrological systems, recognizes the potential for humans to transform hydrological systems and for hydrological conditions to influence human behavior. However, this coupling introduces new challenges and existing literature does not offer clear guidance regarding model conceptualization. There are no universally accepted laws of human behavior as there are for the physical systems; furthermore, a shared understanding of important processes within the field is often used to develop hydrological models, but there is no such consensus on the relevant processes in socio-hydrological systems. Here we present a question driven process to address these challenges. Such an approach allows modeling structure, scope and detail to remain contingent on and adaptive to the question context. We demonstrate the utility of this process by revisiting a classic question in water resources engineering on reservoir operation rules: what is the impact of reservoir operation policy on the reliability of water supply for a growing city? Our example model couples hydrological and human systems by linking the rate of demand decreases to the past reliability to compare standard operating policy (SOP) with hedging policy (HP). The model shows that reservoir storage acts both as a buffer for variability and as a delay triggering oscillations around a sustainable level of demand. HP reduces the threshold for action thereby decreasing the delay and the oscillation effect. As a result, per capita demand decreases during periods of water stress are more frequent but less drastic and the additive effect of small adjustments decreases the tendency of the system to overshoot available supplies. This distinction between the two policies was not apparent using a traditional noncoupled model.

Simulating hydrological processes of a typical small mountainous catchment in Tibetan Plateau

NASA Astrophysics Data System (ADS)

Xu, Y. P.; Bai, Z.; Fu, Q.; Pan, S.; Zhu, C.

2017-12-01

Water cycle of small watersheds with seasonal/permanent frozen soil and snow pack in Tibetan Plateau is seriously affected by climate change. The objective of this study is to find out how much and in what way the frozen soil and snow pack will influence the hydrology of small mountainous catchments in cold regions and how can the performance of simulation by a distributed hydrological model be improved. The Dong catchment, a small catchment located in Tibetan Plateau, is used as a case study. Two measurement stations are set up to collect basic meteorological and hydrological data for the modeling purpose. Annual and interannual variations of runoff indices are first analyzed based on historic data series. The sources of runoff in dry periods and wet periods are analyzed respectively. Then, a distributed hydrology soil vegetation model (DHSVM) is adopted to simulate the hydrological process of Dong catchment based on limited data set. Global sensitivity analysis is applied to help determine the important processes of the catchment. Based on sensitivity analysis results, the Epsilon-Dominance Non-Dominated Sorted Genetic Algorithm II (ɛ-NSGAII) is finally added into the hydrological model to calibrate the hydrological model in a multi-objective way and analyze the performance of DHSVM model. The performance of simulation is evaluated with several evaluation indices. The final results show that frozen soil and snow pack do play an important role in hydrological processes in cold mountainous region, in particular in dry periods without precipitation, while in wet periods precipitation is often the main source of runoff. The results also show that although the DHSVM hydrological model has the potential to model the hydrology well in small mountainous catchments with very limited data in Tibetan Plateau, the simulation of hydrology in dry periods is not very satisfactory due to the model's insufficiency in simulating seasonal frozen soil.

Improving National Water Modeling: An Intercomparison of two High-Resolution, Continental Scale Models, CONUS-ParFlow and the National Water Model

NASA Astrophysics Data System (ADS)

Tijerina, D.; Gochis, D.; Condon, L. E.; Maxwell, R. M.

2017-12-01

Development of integrated hydrology modeling systems that couple atmospheric, land surface, and subsurface flow is growing trend in hydrologic modeling. Using an integrated modeling framework, subsurface hydrologic processes, such as lateral flow and soil moisture redistribution, are represented in a single cohesive framework with surface processes like overland flow and evapotranspiration. There is a need for these more intricate models in comprehensive hydrologic forecasting and water management over large spatial areas, specifically the Continental US (CONUS). Currently, two high-resolution, coupled hydrologic modeling applications have been developed for this domain: CONUS-ParFlow built using the integrated hydrologic model ParFlow and the National Water Model that uses the NCAR Weather Research and Forecasting hydrological extension package (WRF-Hydro). Both ParFlow and WRF-Hydro include land surface models, overland flow, and take advantage of parallelization and high-performance computing (HPC) capabilities; however, they have different approaches to overland subsurface flow and groundwater-surface water interactions. Accurately representing large domains remains a challenge considering the difficult task of representing complex hydrologic processes, computational expense, and extensive data needs; both models have accomplished this, but have differences in approach and continue to be difficult to validate. A further exploration of effective methodology to accurately represent large-scale hydrology with integrated models is needed to advance this growing field. Here we compare the outputs of CONUS-ParFlow and the National Water Model to each other and with observations to study the performance of hyper-resolution models over large domains. Models were compared over a range of scales for major watersheds within the CONUS with a specific focus on the Mississippi, Ohio, and Colorado River basins. We use a novel set of approaches and analysis for this comparison to better understand differences in process and bias. This intercomparison is a step toward better understanding how much water we have and interactions between surface and subsurface. Our goal is to advance our understanding and simulation of the hydrologic system and ultimately improve hydrologic forecasts.

Stress enhanced calcium kinetics in a neuron.

PubMed

Kant, Aayush; Bhandakkar, Tanmay K; Medhekar, Nikhil V

2018-02-01

Accurate modeling of the mechanobiological response of a Traumatic Brain Injury is beneficial toward its effective clinical examination, treatment and prevention. Here, we present a stress history-dependent non-spatial kinetic model to predict the microscale phenomena of secondary insults due to accumulation of excess calcium ions (Ca[Formula: see text]) induced by the macroscale primary injuries. The model is able to capture the experimentally observed increase and subsequent partial recovery of intracellular Ca[Formula: see text] concentration in response to various types of mechanical impulses. We further establish the accuracy of the model by comparing our predictions with key experimental observations.

Multiscale Modeling of Carbon Fiber Reinforced Polymer (CFRP) for Integrated Computational Materials Engineering Process

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

Gao, Jiaying; Liang, Biao; Zhang, Weizhao

In this work, a multiscale modeling framework for CFRP is introduced to study hierarchical structure of CFRP. Four distinct scales are defined: nanoscale, microscale, mesoscale, and macroscale. Information at lower scales can be passed to higher scale, which is beneficial for studying effect of constituents on macroscale part’s mechanical property. This bottom-up modeling approach enables better understanding of CFRP from finest details. Current study focuses on microscale and mesoscale. Representative volume element is used at microscale and mesoscale to model material’s properties. At microscale, unidirection CFRP (UD) RVE is used to study properties of UD. The UD RVE can bemore » modeled with different volumetric fraction to encounter non-uniform fiber distribution in CFRP part. Such consideration is important in modeling uncertainties at microscale level. Currently, we identified volumetric fraction as the only uncertainty parameters in UD RVE. To measure effective material properties of UD RVE, periodic boundary conditions (PBC) are applied to UD RVE to ensure convergence of obtained properties. Properties of UD is directly used at mesoscale woven RVE modeling, where each yarn is assumed to have same properties as UD. Within woven RVE, there can be many potential uncertainties parameters to consider for a physical modeling of CFRP. Currently, we will consider fiber misalignment within yarn and angle between wrap and weft yarns. PBC is applied to woven RVE to calculate its effective material properties. The effect of uncertainties are investigated quantitatively by Gaussian process. Preliminary results of UD and Woven study are analyzed for efficacy of the RVE modeling. This work is considered as the foundation for future multiscale modeling framework development for ICME project.« less

Hydrologic filtering of fish life history strategies across the United States: implications for stream flow alteration

DOE PAGES

McManamay, Ryan A.; Frimpong, Emmanuel A.

2015-01-01

Lotic fish have developed life history strategies adapted to the natural variation in stream flow regimes. The natural timing, duration, and magnitude of flow events has contributed to the diversity, production, and composition of fish assemblages over time. Studies evaluating the role of hydrology in structuring fish assemblages have been more common at the local or regional scale with very few studies conducted at the continental scale. Furthermore, quantitative linkages between natural hydrologic patterns and fish assemblages are rarely used to make predictions of ecological consequences of hydrologic alterations. We ask two questions: (1) what is the relative role ofmore » hydrology in structuring fish assemblages at large scales? and (2) can relationships between fish assemblages and natural hydrology be utilized to predict fish assemblage responses to hydrologic disturbance? We developed models to relate fish life histories and reproductive strategies to landscape and hydrologic variables separately and then combined. Models were then used to predict the ecological consequences of altered hydrology due to dam regulation. Although hydrology plays a considerable role in structuring fish assemblages, the performance of models using only hydrologic variables was lower than that of models constructed using landscape variables. Isolating the relative importance of hydrology in structuring fish assemblages at the continental scale is difficult since hydrology is interrelated to many landscape factors. By applying models to dam-regulated hydrologic data, we observed some consistent predicted responses in fish life history strategies and modes of reproduction. In agreement with existing literature, equilibrium strategists are predicted to increase following dam regulation, whereas opportunistic and periodic species are predicted to decrease. In addition, dam regulation favors the selection of reproductive strategies with extended spawning seasons and preference for stable conditions.« less

Hydrologic filtering of fish life history strategies across the United States: implications for stream flow alteration

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

McManamay, Ryan A.; Frimpong, Emmanuel A.

Lotic fish have developed life history strategies adapted to the natural variation in stream flow regimes. The natural timing, duration, and magnitude of flow events has contributed to the diversity, production, and composition of fish assemblages over time. Studies evaluating the role of hydrology in structuring fish assemblages have been more common at the local or regional scale with very few studies conducted at the continental scale. Furthermore, quantitative linkages between natural hydrologic patterns and fish assemblages are rarely used to make predictions of ecological consequences of hydrologic alterations. We ask two questions: (1) what is the relative role ofmore » hydrology in structuring fish assemblages at large scales? and (2) can relationships between fish assemblages and natural hydrology be utilized to predict fish assemblage responses to hydrologic disturbance? We developed models to relate fish life histories and reproductive strategies to landscape and hydrologic variables separately and then combined. Models were then used to predict the ecological consequences of altered hydrology due to dam regulation. Although hydrology plays a considerable role in structuring fish assemblages, the performance of models using only hydrologic variables was lower than that of models constructed using landscape variables. Isolating the relative importance of hydrology in structuring fish assemblages at the continental scale is difficult since hydrology is interrelated to many landscape factors. By applying models to dam-regulated hydrologic data, we observed some consistent predicted responses in fish life history strategies and modes of reproduction. In agreement with existing literature, equilibrium strategists are predicted to increase following dam regulation, whereas opportunistic and periodic species are predicted to decrease. In addition, dam regulation favors the selection of reproductive strategies with extended spawning seasons and preference for stable conditions.« less

On the hydrologic adjustment of climate-model projections: The potential pitfall of potential evapotranspiration

USGS Publications Warehouse

Milly, P.C.D.; Dunne, K.A.

2011-01-01

Hydrologic models often are applied to adjust projections of hydroclimatic change that come from climate models. Such adjustment includes climate-bias correction, spatial refinement ("downscaling"), and consideration of the roles of hydrologic processes that were neglected in the climate model. Described herein is a quantitative analysis of the effects of hydrologic adjustment on the projections of runoff change associated with projected twenty-first-century climate change. In a case study including three climate models and 10 river basins in the contiguous United States, the authors find that relative (i.e., fractional or percentage) runoff change computed with hydrologic adjustment more often than not was less positive (or, equivalently, more negative) than what was projected by the climate models. The dominant contributor to this decrease in runoff was a ubiquitous change in runoff (median 211%) caused by the hydrologic model's apparent amplification of the climate-model-implied growth in potential evapotranspiration. Analysis suggests that the hydrologic model, on the basis of the empirical, temperature-based modified Jensen-Haise formula, calculates a change in potential evapotranspiration that is typically 3 times the change implied by the climate models, which explicitly track surface energy budgets. In comparison with the amplification of potential evapotranspiration, central tendencies of other contributions from hydrologic adjustment (spatial refinement, climate-bias adjustment, and process refinement) were relatively small. The authors' findings highlight the need for caution when projecting changes in potential evapotranspiration for use in hydrologic models or drought indices to evaluate climatechange impacts on water. Copyright ?? 2011, Paper 15-001; 35,952 words, 3 Figures, 0 Animations, 1 Tables.

Modeling Pre- and Post- Wildfire Hydrologic Response to Vegetation Change in the Valles Caldera National Preserve, NM

NASA Astrophysics Data System (ADS)

Gregory, A. E.; Benedict, K. K.; Zhang, S.; Savickas, J.

2017-12-01

Large scale, high severity wildfires in forests have become increasingly prevalent in the western United States due to fire exclusion. Although past work has focused on the immediate consequences of wildfire (ie. runoff magnitude and debris flow), little has been done to understand the post wildfire hydrologic consequences of vegetation regrowth. Furthermore, vegetation is often characterized by static parameterizations within hydrological models. In order to understand the temporal relationship between hydrologic processes and revegetation, we modularized and partially automated the hydrologic modeling process to increase connectivity between remotely sensed data, the Virtual Watershed Platform (a data management resource, called the VWP), input meteorological data, and the Precipitation-Runoff Modeling System (PRMS). This process was used to run simulations in the Valles Caldera of NM, an area impacted by the 2011 Las Conchas Fire, in PRMS before and after the Las Conchas to evaluate hydrologic process changes. The modeling environment addressed some of the existing challenges faced by hydrological modelers. At present, modelers are somewhat limited in their ability to push the boundaries of hydrologic understanding. Specific issues faced by modelers include limited computational resources to model processes at large spatial and temporal scales, data storage capacity and accessibility from the modeling platform, computational and time contraints for experimental modeling, and the skills to integrate modeling software in ways that have not been explored. By taking an interdisciplinary approach, we were able to address some of these challenges by leveraging the skills of hydrologic, data, and computer scientists; and the technical capabilities provided by a combination of on-demand/high-performance computing, distributed data, and cloud services. The hydrologic modeling process was modularized to include options for distributing meteorological data, parameter space experimentation, data format transformation, looping, validation of models and containerization for enabling new analytic scenarios. The user interacts with the modules through Jupyter Notebooks which can be connected to an on-demand computing and HPC environment, and data services built as part of the VWP.

Improving Evapotranspiration Estimates Using Multi-Platform Remote Sensing

NASA Astrophysics Data System (ADS)

Knipper, Kyle; Hogue, Terri; Franz, Kristie; Scott, Russell

2016-04-01

Understanding the linkages between energy and water cycles through evapotranspiration (ET) is uniquely challenging given its dependence on a range of climatological parameters and surface/atmospheric heterogeneity. A number of methods have been developed to estimate ET either from primarily remote-sensing observations, in-situ measurements, or a combination of the two. However, the scale of many of these methods may be too large to provide needed information about the spatial and temporal variability of ET that can occur over regions with acute or chronic land cover change and precipitation driven fluxes. The current study aims to improve the spatial and temporal variability of ET utilizing only satellite-based observations by incorporating a potential evapotranspiration (PET) methodology with satellite-based down-scaled soil moisture estimates in southern Arizona, USA. Initially, soil moisture estimates from AMSR2 and SMOS are downscaled to 1km through a triangular relationship between MODIS land surface temperature (MYD11A1), vegetation indices (MOD13Q1/MYD13Q1), and brightness temperature. Downscaled soil moisture values are then used to scale PET to actual ET (AET) at a daily, 1km resolution. Derived AET estimates are compared to observed flux tower estimates, the North American Land Data Assimilation System (NLDAS) model output (i.e. Variable Infiltration Capacity (VIC) Macroscale Hydrologic Model, Mosiac Model, and Noah Model simulations), the Operational Simplified Surface Energy Balance Model (SSEBop), and a calibrated empirical ET model created specifically for the region. Preliminary results indicate a strong increase in correlation when incorporating the downscaling technique to original AMSR2 and SMOS soil moisture values, with the added benefit of being able to decipher small scale heterogeneity in soil moisture (riparian versus desert grassland). AET results show strong correlations with relatively low error and bias when compared to flux tower estimates. In addition, AET results show improved bias to those reported by SSEBop, with similar correlations and errors when compared to the empirical ET model. Spatial patterns of estimated AET display patterns representative of the basin's elevation and vegetation characteristics, with improved spatial resolution and temporal heterogeneity when compared to previous models.

Acting, predicting and intervening in a socio-hydrological world

NASA Astrophysics Data System (ADS)

Lane, S. N.

2014-03-01

This paper asks a simple question: if humans and their actions co-evolve with hydrological systems (Sivapalan et al., 2012), what is the role of hydrological scientists, who are also humans, within this system? To put it more directly, as traditionally there is a supposed separation of scientists and society, can we maintain this separation as socio-hydrologists studying a socio-hydrological world? This paper argues that we cannot, using four linked sections. The first section draws directly upon the concern of science-technology studies to make a case to the (socio-hydrological) community that we need to be sensitive to constructivist accounts of science in general and socio-hydrology in particular. I review three positions taken by such accounts and apply them to hydrological science, supported with specific examples: (a) the ways in which scientific activities frame socio-hydrological research, such that at least some of the knowledge that we obtain is constructed by precisely what we do; (b) the need to attend to how socio-hydrological knowledge is used in decision-making, as evidence suggests that hydrological knowledge does not flow simply from science into policy; and (c) the observation that those who do not normally label themselves as socio-hydrologists may actually have a profound knowledge of socio-hydrology. The second section provides an empirical basis for considering these three issues by detailing the history of the practice of roughness parameterisation, using parameters like Manning's n, in hydrological and hydraulic models for flood inundation mapping. This history sustains the third section that is a more general consideration of one type of socio-hydrological practice: predictive modelling. I show that as part of a socio-hydrological analysis, hydrological prediction needs to be thought through much more carefully: not only because hydrological prediction exists to help inform decisions that are made about water management; but also because those predictions contain assumptions, the predictions are only correct in so far as those assumptions hold, and for those assumptions to hold, the socio-hydrological system (i.e. the world) has to be shaped so as to include them. Here, I add to the "normal" view that ideally our models should represent the world around us, to argue that for our models (and hence our predictions) to be valid, we have to make the world look like our models. Decisions over how the world is modelled may transform the world as much as they represent the world. Thus, socio-hydrological modelling has to become a socially accountable process such that the world is transformed, through the implications of modelling, in a fair and just manner. This leads into the final section of the paper where I consider how socio-hydrological research may be made more socially accountable, in a way that is both sensitive to the constructivist critique (Sect. 1), but which retains the contribution that hydrologists might make to socio-hydrological studies. This includes (1) working with conflict and controversy in hydrological science, rather than trying to eliminate them; (2) using hydrological events to avoid becoming locked into our own frames of explanation and prediction; (3) being empirical and experimental but in a socio-hydrological sense; and (4) co-producing socio-hydrological predictions. I will show how this might be done through a project that specifically developed predictive models for making interventions in river catchments to increase high river flow attenuation. Therein, I found myself becoming detached from my normal disciplinary networks and attached to the co-production of a predictive hydrological model with communities normally excluded from the practice of hydrological science.

The application of remote sensing to the development and formulation of hydrologic planning models

NASA Technical Reports Server (NTRS)

Fowler, T. R.; Castruccio, P. A.; Loats, H. L., Jr.

1977-01-01

The development of a remote sensing model and its efficiency in determining parameters of hydrologic models are reviewed. Procedures for extracting hydrologic data from LANDSAT imagery, and the visual analysis of composite imagery are presented. A hydrologic planning model is developed and applied to determine seasonal variations in watershed conditions. The transfer of this technology to a user community and contract arrangements are discussed.

Scatter of fatigue data owing to material microscopic effects

NASA Astrophysics Data System (ADS)

Tang, XueSong

2014-01-01

A common phenomenon of fatigue test data reported in the open literature such as S-N curves exhibits the scatter of points for a group of same specimens under the same loading condition. The reason is well known that the microstructure is different from specimen to specimen even in the same group. Specifically, a fatigue failure process is a multi-scale problem so that a fatigue failure model should have the ability to take the microscopic effect into account. A physically-based trans-scale crack model is established and the analytical solution is obtained by coupling the micro- and macro-scale. Obtained is the trans-scale stress intensity factor as well as the trans-scale strain energy density (SED) factor. By taking this trans-scale SEDF as a key controlling parameter for the fatigue crack propagation from micro- to macro-scale, a trans-scale fatigue crack growth model is proposed in this work which can reflect the microscopic effect and scale transition in a fatigue process. The fatigue test data of aluminum alloy LY12 plate specimens is chosen to check the model. Two S-N experimental curves for cyclic stress ratio R=0.02 and R=0.6 are selected. The scattering test data points and two S-N curves for both R=0.02 and R=0.6 are exactly re-produced by application of the proposed model. It is demonstrated that the proposed model is able to reflect the multiscaling effect in a fatigue process. The result also shows that the microscopic effect has a pronounced influence on the fatigue life of specimens.

Genetic Programming for Automatic Hydrological Modelling

NASA Astrophysics Data System (ADS)

Chadalawada, Jayashree; Babovic, Vladan

2017-04-01

One of the recent challenges for the hydrologic research community is the need for the development of coupled systems that involves the integration of hydrologic, atmospheric and socio-economic relationships. This poses a requirement for novel modelling frameworks that can accurately represent complex systems, given, the limited understanding of underlying processes, increasing volume of data and high levels of uncertainity. Each of the existing hydrological models vary in terms of conceptualization and process representation and is the best suited to capture the environmental dynamics of a particular hydrological system. Data driven approaches can be used in the integration of alternative process hypotheses in order to achieve a unified theory at catchment scale. The key steps in the implementation of integrated modelling framework that is influenced by prior understanding and data, include, choice of the technique for the induction of knowledge from data, identification of alternative structural hypotheses, definition of rules, constraints for meaningful, intelligent combination of model component hypotheses and definition of evaluation metrics. This study aims at defining a Genetic Programming based modelling framework that test different conceptual model constructs based on wide range of objective functions and evolves accurate and parsimonious models that capture dominant hydrological processes at catchment scale. In this paper, GP initializes the evolutionary process using the modelling decisions inspired from the Superflex framework [Fenicia et al., 2011] and automatically combines them into model structures that are scrutinized against observed data using statistical, hydrological and flow duration curve based performance metrics. The collaboration between data driven and physical, conceptual modelling paradigms improves the ability to model and manage hydrologic systems. Fenicia, F., D. Kavetski, and H. H. Savenije (2011), Elements of a flexible approach for conceptual hydrological modeling: 1. Motivation and theoretical development, Water Resources Research, 47(11).

Designing hydrologic monitoring networks to maximize predictability of hydrologic conditions in a data assimilation system: a case study from South Florida, U.S.A

NASA Astrophysics Data System (ADS)

Flores, A. N.; Pathak, C. S.; Senarath, S. U.; Bras, R. L.

2009-12-01

Robust hydrologic monitoring networks represent a critical element of decision support systems for effective water resource planning and management. Moreover, process representation within hydrologic simulation models is steadily improving, while at the same time computational costs are decreasing due to, for instance, readily available high performance computing resources. The ability to leverage these increasingly complex models together with the data from these monitoring networks to provide accurate and timely estimates of relevant hydrologic variables within a multiple-use, managed water resources system would substantially enhance the information available to resource decision makers. Numerical data assimilation techniques provide mathematical frameworks through which uncertain model predictions can be constrained to observational data to compensate for uncertainties in the model forcings and parameters. In ensemble-based data assimilation techniques such as the ensemble Kalman Filter (EnKF), information in observed variables such as canal, marsh and groundwater stages are propagated back to the model states in a manner related to: (1) the degree of certainty in the model state estimates and observations, and (2) the cross-correlation between the model states and the observable outputs of the model. However, the ultimate degree to which hydrologic conditions can be accurately predicted in an area of interest is controlled, in part, by the configuration of the monitoring network itself. In this proof-of-concept study we developed an approach by which the design of an existing hydrologic monitoring network is adapted to iteratively improve the predictions of hydrologic conditions within an area of the South Florida Water Management District (SFWMD). The objective of the network design is to minimize prediction errors of key hydrologic states and fluxes produced by the spatially distributed Regional Simulation Model (RSM), developed specifically to simulate the hydrologic conditions in several intensively managed and hydrologically complex watersheds within the SFWMD system. In a series of synthetic experiments RSM is used to generate the notionally true hydrologic state and the relevant observational data. The EnKF is then used as the mechanism to fuse RSM hydrologic estimates with data from the candidate network. The performance of the candidate network is measured by the prediction errors of the EnKF estimates of hydrologic states, relative to the notionally true scenario. The candidate network is then adapted by relocating existing observational sites to unobserved areas where predictions of local hydrologic conditions are most uncertain and the EnKF procedure repeated. Iteration of the monitoring network continues until further improvements in EnKF-based predictions of hydrologic conditions are negligible.

Detecting and modelling structures on the micro and the macro scales: Assessing their effects on solute transport behaviour

NASA Astrophysics Data System (ADS)

Haslauer, C. P.; Bárdossy, A.; Sudicky, E. A.

2017-09-01

This paper demonstrates quantitative reasoning to separate the dataset of spatially distributed variables into different entities and subsequently characterize their geostatistical properties, properly. The main contribution of the paper is a statistical based algorithm that matches the manual distinction results. This algorithm is based on measured data and is generally applicable. In this paper, it is successfully applied at two datasets of saturated hydraulic conductivity (K) measured at the Borden (Canada) and the Lauswiesen (Germany) aquifers. The boundary layer was successfully delineated at Borden despite its only mild heterogeneity and only small statistical differences between the divided units. The methods are verified with the more heterogeneous Lauswiesen aquifer K data-set, where a boundary layer has previously been delineated. The effects of the macro- and the microstructure on solute transport behaviour are evaluated using numerical solute tracer experiments. Within the microscale structure, both Gaussian and non-Gaussian models of spatial dependence of K are evaluated. The effects of heterogeneity both on the macro- and the microscale are analysed using numerical tracer experiments based on four scenarios: including or not including the macroscale structures and optimally fitting a Gaussian or a non-Gaussian model for the spatial dependence in the micro-structure. The paper shows that both micro- and macro-scale structures are important, as in each of the four possible geostatistical scenarios solute transport behaviour differs meaningfully.

Influence of the Aral Sea negative water balance on its seasonal circulation and ventilation patterns: use of a 3d hydrodynamic model.

NASA Astrophysics Data System (ADS)

Sirjacobs, D.; Grégoire, M.; Delhez, E.; Nihoul, J.

2003-04-01

Within the context of the EU INCO-COPERNICUS program "Desertification in the Aral Sea Region: A study of the Natural and Anthropogenic Impacts" (Contract IAC2-CT-2000-10023), a large-scale 3D hydrodynamic model was adapted to address specifically the macroscale processes affecting the Aral Sea water circulation and ventilation. The particular goal of this research is to simulate the effect of lasting negative water balance on the 3D seasonal circulation, temperature, salinity and water-mixing fields of the Aral Sea. The original Aral Sea seasonal hydrodynamism is simulated with the average seasonal forcings corresponding to the period from 1956 to 1960. This first investigation concerns a period of relative stability of the water balance, before the beginning of the drying process. The consequences of the drying process on the hydrodynamic of the Sea will be studied by comparing this first results with the simulation representing the average situation for the years 1981 to 1985, a very low river flow period. For both simulation periods, the forcing considered are the seasonal fluctuations of wind fields, precipitation, evaporation, river discharge and salinity, cloud cover, air temperature and humidity. The meteorological forcings were adapted to the common optimum one-month temporal resolution of the available data sets. Monthly mean kinetic energy flux and surface tensions were calculated from daily ECMWF wind data. Monthly in situ precipitation, surface air temperature and humidity fields were interpolated from data obtained from the Russian Hydrological and Meteorological Institute. Monthly water discharge and average salinity of the river water were considered for both Amu Darya and Syr Darya river over each simulation periods. The water mass conservation routines allowed the simulation of a changing coastline by taking into account local drying and flooding events of particular grid points. Preliminary barotropic runs were realised (for the 1951-1960 situation, before drying up began) in order to get a first experience of the behaviour of the hydrodynamic model. These first runs provide results about the evolution of the following state variables: elevation of the sea surface, 3D fields of vertical and horizontal flows, 2D fields of average horizontal flows and finally the 3D fields of turbulent kinetic energy. The mean seasonal salinity and temperature fields (in-situ data gathered by the Russian Hydrological and Meteorological Institute) are available for the two simulated periods and will allow a first validation of the hydrodynamic model. Various satellites products were identified, collected and processed in the frame of this research project and will be used for the validation of the model outputs. Seasonal level changes measurements derived from water table change will serve for water balance validation and sea surface temperature for hydrodynamics validation.

Probabilistic flood inundation prediction within a coupled hydrodynamic, distributed hydrologic modeling framework

NASA Astrophysics Data System (ADS)

Adams, T. E.

2016-12-01

Accurate and timely predictions of the lateral exent of floodwaters and water level depth in floodplain areas are critical globally. This paper demonstrates the coupling of hydrologic ensembles, derived from the use of numerical weather prediction (NWP) model forcings as input to a fully distributed hydrologic model. Resulting ensemble output from the distributed hydrologic model are used as upstream flow boundaries and lateral inflows to a 1-D hydrodynamic model. An example is presented for the Potomac River in the vicinity of Washington, DC (USA). The approach taken falls within the broader goals of the Hydrologic Ensemble Prediction EXperiment (HEPEX).

Observational breakthroughs lead the way to improved hydrological predictions

NASA Astrophysics Data System (ADS)

Lettenmaier, Dennis P.

2017-04-01

New data sources are revolutionizing the hydrological sciences. The capabilities of hydrological models have advanced greatly over the last several decades, but until recently model capabilities have outstripped the spatial resolution and accuracy of model forcings (atmospheric variables at the land surface) and the hydrologic state variables (e.g., soil moisture; snow water equivalent) that the models predict. This has begun to change, as shown in two examples here: soil moisture and drought evolution over Africa as predicted by a hydrology model forced with satellite-derived precipitation, and observations of snow water equivalent at very high resolution over a river basin in California's Sierra Nevada.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

Uncertainty in impact studies arises both from Global Climate Models (GCM), emission projections, statistical downscaling, Regional Climate Models (RCM), hydrological models and calibration techniques (Refsgaard et al. 2013). Some of these uncertainties have been evaluated several times in the literature; however few studies have investigated the effect of hydrological model choice on the assessment results (Boorman & Sefton 1997; Jiang et al. 2007; Bastola et al. 2011). These studies have found that model choice results in large differences, up to 70%, in the predicted discharge changes depending on the climate input. The objective of the study is to investigate the impact of climate change on hydrology of the Odense catchment, Denmark both in response to (a) different climate projections (GCM-RCM combinations); (b) different hydrological models and (c) different land use scenarios. This includes: 1. Separation of the climate model signal; the hydrological model signal and the land use signal 2. How do the different hydrological components react under different climate and land use conditions for the different models 3. What land use scenario seems to provide the best adaptation for the challenges of the different future climate change scenarios from a hydrological perspective? Four climate models from the ENSEMBLES project (Hewitt & Griggs 2004): ECHAM5 - HIRHAM5, ECHAM5 - RCA3, ARPEGE - RM5.1 and HadCM3 - HadRM3 are used, assessing the climate change impact in three periods: 1991-2010 (present), 2041-2060 (near future) and 2081-2100 (far future). The four climate models are used in combination with three hydrological models with different conceptual layout: NAM, SWAT and MIKE SHE. Bastola, S., C. Murphy and J. Sweeney (2011). "The role of hydrological modelling uncertainties in climate change impact assessments of Irish river catchments." Advances in Water Resources 34: 562-576. Boorman, D. B. and C. E. M. Sefton (1997). "Recognising the uncertainty in the quantification of the effects of climate change on hydrological response." Climate Change 35: 415-434. Hewitt, C. D. and D. J. Griggs (2004). "Ensembles-based predictions of climate changes and their impacts." Eos, Transactions American Geophysical Union 85: 1-566. Jiang, T., Y. D. Chen, C. Xu, X. Chen, X. Chen and V. P. Singh (2007). "Comparison of hydrological impacts of climate change simulated by six hydrological models in the Dongjiang Basin, South China." Journal of hydrology 336: 316-333. Refsgaard, J. C., K. Arnbjerg-Nielsen, M. Drews, K. Halsnæs, E. Jeppesen, H. Madsen, A. Markandya, J. E. Olesen, J. R. Porter and J. H. Christensen (2013). "The role of uncertainty in climate change adaptation strategies - A Danish water management example." Mitigation and Adaptation Strategies for Global Change 18: 337-359.

Feedback Loop of Data Infilling Using Model Result of Actual Evapotranspiration from Satellites and Hydrological Model

NASA Astrophysics Data System (ADS)

Murdi Hartanto, Isnaeni; Alexandridis, Thomas K.; van Andel, Schalk Jan; Solomatine, Dimitri

2014-05-01

Using satellite data in a hydrological model has long been occurring in modelling of hydrological processes, as a source of low cost regular data. The methods range from using satellite products as direct input, model validation, and data assimilation. However, the satellite data frequently face the missing value problem, whether due to the cloud cover or the limited temporal coverage. The problem could seriously affect its usefulness in hydrological model, especially if the model uses it as direct input, so data infilling becomes one of the important parts in the whole modelling exercise. In this research, actual evapotranspiration product from satellite is directly used as input into a spatially distributed hydrological model, and validated by comparing the catchment's end discharge with measured data. The instantaneous actual evapotranspiration is estimated from MODIS satellite images using a variation of the energy balance model for land (SEBAL). The eight-day cumulative actual evapotranspiration is then obtained by a temporal integration that uses the reference evapotranspiration calculated from meteorological data [1]. However, the above method cannot fill in a cell if the cell is constantly having no-data value during the eight-day periods. The hydrological model requires full set of data without no-data cells, hence, the no-data cells in the satellite's evapotranspiration map need to be filled in. In order to fills the no-data cells, an output of hydrological model is used. The hydrological model is firstly run with reference evapotranspiration as input to calculate discharge and actual evapotranspiration. The no-data cells in the eight-day cumulative map from the satellite are then filled in with the output of the first run of hydrological model. The final data is then used as input in a hydrological model to calculate discharge, thus creating a loop. The method is applied in the case study of Rijnland, the Netherlands where in the winter, cloud cover is persistent and leads to many no-data cells in the satellite products. The Rijnland area is a low-lying area with tight water system control. The satellite data is used as input in a SIMGRO model, a spatially distributed hydrological model that is able to handle the controlled water system and that is suitable for the low-lying areas in the Netherlands. The application in the Rijnland area gives overall a good result of total discharge. By using the method, the hydrological model is improved in term of spatial hydrological state, where the original model is only calibrated to discharge in one location. [1] Alexandridis, T.K., Cherif, I., Chemin, Y., Silleos, G.N., Stavrinos, E. & Zalidis, G.C. (2009). Integrated Methodology for Estimating Water Use in Mediterranean Agricultural Areas. Remote Sensing. 1

Incorporating groundwater flow into the WEPP model

Treesearch

William Elliot; Erin Brooks; Tim Link; Sue Miller

2010-01-01

The water erosion prediction project (WEPP) model is a physically-based hydrology and erosion model. In recent years, the hydrology prediction within the model has been improved for forest watershed modeling by incorporating shallow lateral flow into watershed runoff prediction. This has greatly improved WEPP's hydrologic performance on small watersheds with...

Materials-by-design: computation, synthesis, and characterization from atoms to structures

NASA Astrophysics Data System (ADS)

Yeo, Jingjie; Jung, Gang Seob; Martín-Martínez, Francisco J.; Ling, Shengjie; Gu, Grace X.; Qin, Zhao; Buehler, Markus J.

2018-05-01

In the 50 years that succeeded Richard Feynman’s exposition of the idea that there is ‘plenty of room at the bottom’ for manipulating individual atoms for the synthesis and manufacturing processing of materials, the materials-by-design paradigm is being developed gradually through synergistic integration of experimental material synthesis and characterization with predictive computational modeling and optimization. This paper reviews how this paradigm creates the possibility to develop materials according to specific, rational designs from the molecular to the macroscopic scale. We discuss promising techniques in experimental small-scale material synthesis and large-scale fabrication methods to manipulate atomistic or macroscale structures, which can be designed by computational modeling. These include recombinant protein technology to produce peptides and proteins with tailored sequences encoded by recombinant DNA, self-assembly processes induced by conformational transition of proteins, additive manufacturing for designing complex structures, and qualitative and quantitative characterization of materials at different length scales. We describe important material characterization techniques using numerous methods of spectroscopy and microscopy. We detail numerous multi-scale computational modeling techniques that complements these experimental techniques: DFT at the atomistic scale; fully atomistic and coarse-grain molecular dynamics at the molecular to mesoscale; continuum modeling at the macroscale. Additionally, we present case studies that utilize experimental and computational approaches in an integrated manner to broaden our understanding of the properties of two-dimensional materials and materials based on silk and silk-elastin-like proteins.

Electrical conductivity modeling and experimental study of densely packed SWCNT networks.

PubMed

Jack, D A; Yeh, C-S; Liang, Z; Li, S; Park, J G; Fielding, J C

2010-05-14

Single-walled carbon nanotube (SWCNT) networks have become a subject of interest due to their ability to support structural, thermal and electrical loadings, but to date their application has been hindered due, in large part, to the inability to model macroscopic responses in an industrial product with any reasonable confidence. This paper seeks to address the relationship between macroscale electrical conductivity and the nanostructure of a dense network composed of SWCNTs and presents a uniquely formulated physics-based computational model for electrical conductivity predictions. The proposed model incorporates physics-based stochastic parameters for the individual nanotubes to construct the nanostructure such as: an experimentally obtained orientation distribution function, experimentally derived length and diameter distributions, and assumed distributions of chirality and registry of individual CNTs. Case studies are presented to investigate the relationship between macroscale conductivity and nanostructured variations in the bulk stochastic length, diameter and orientation distributions. Simulation results correspond nicely with those available in the literature for case studies of conductivity versus length and conductivity versus diameter. In addition, predictions for the increasing anisotropy of the bulk conductivity as a function of the tube orientation distribution are in reasonable agreement with our experimental results. Examples are presented to demonstrate the importance of incorporating various stochastic characteristics in bulk conductivity predictions. Finally, a design consideration for industrial applications is discussed based on localized network power emission considerations and may lend insight to the design engineer to better predict network failure under high current loading applications.

Multi-scale analysis of the effect of nano-filler particle diameter on the physical properties of CAD/CAM composite resin blocks.

PubMed

Yamaguchi, Satoshi; Inoue, Sayuri; Sakai, Takahiko; Abe, Tomohiro; Kitagawa, Haruaki; Imazato, Satoshi

2017-05-01

The objective of this study was to assess the effect of silica nano-filler particle diameters in a computer-aided design/manufacturing (CAD/CAM) composite resin (CR) block on physical properties at the multi-scale in silico. CAD/CAM CR blocks were modeled, consisting of silica nano-filler particles (20, 40, 60, 80, and 100 nm) and matrix (Bis-GMA/TEGDMA), with filler volume contents of 55.161%. Calculation of Young's moduli and Poisson's ratios for the block at macro-scale were analyzed by homogenization. Macro-scale CAD/CAM CR blocks (3 × 3 × 3 mm) were modeled and compressive strengths were defined when the fracture loads exceeded 6075 N. MPS values of the nano-scale models were compared by localization analysis. As the filler size decreased, Young's moduli and compressive strength increased, while Poisson's ratios and MPS decreased. All parameters were significantly correlated with the diameters of the filler particles (Pearson's correlation test, r = -0.949, 0.943, -0.951, 0.976, p < 0.05). The in silico multi-scale model established in this study demonstrates that the Young's moduli, Poisson's ratios, and compressive strengths of CAD/CAM CR blocks can be enhanced by loading silica nanofiller particles of smaller diameter. CAD/CAM CR blocks by using smaller silica nano-filler particles have a potential to increase fracture resistance.

Electrical conductivity of nanocomposites based on carbon nanotubes: a 3D multiscale modeling approach

NASA Astrophysics Data System (ADS)

Grabowski, Krzysztof; Zbyrad, Paulina; Staszewski, Wieslaw J.; Uhl, Tadeusz; Wiatr, Kazimierz; Packo, Pawel

2016-04-01

Remarkable electrical properties of carbon nanotubes (CNT) have lead to increased interest in studying CNT- based devices. Many of current researches are devoted to using all kinds of carbon nanomaterials in the con- struction of sensory elements. One of the most common applications is the development of high performance, large scale sensors. Due to the remarkable conductivity of CNT's such devices represent very high sensitivity. However, there are no sufficient tools for studying and designing such sensors. The main objective of this paper is to develop and validate a multiscale numerical model for a carbon nanotubes based sensor. The device utilises the change of electrical conductivity of a nanocomposite material under applied deformation. The nanocomposite consists of a number of CNTs dispersed in polymer matrix. The paper is devoted to the analysis of the impact of spatial distribution of carbon nanotubes in polymer matrix on electrical conductivity of the sensor. One of key elements is also to examine the impact of strain on electric charge ow in such anisotropic composite structures. In the following work a multiscale electro-mechanical model for CNT - based nanocomposites is proposed. The model comprises of two length scales, namely the meso- and the macro-scale for mechanical and electrical domains. The approach allows for evaluation of macro-scale mechanical response of a strain sensor. Electrical properties of polymeric material with certain CNT fractions were derived considering electrical properties of CNTs, their contact and the tunnelling effect.

Hydrologic Process-oriented Optimization of Electrical Resistivity Tomography

NASA Astrophysics Data System (ADS)

Hinnell, A.; Bechtold, M.; Ferre, T. A.; van der Kruk, J.

2010-12-01

Electrical resistivity tomography (ERT) is commonly used in hydrologic investigations. Advances in joint and coupled hydrogeophysical inversion have enhanced the quantitative use of ERT to construct and condition hydrologic models (i.e. identify hydrologic structure and estimate hydrologic parameters). However the selection of which electrical resistivity data to collect and use is often determined by a combination of data requirements for geophysical analysis, intuition on the part of the hydrogeophysicist and logistical constraints of the laboratory or field site. One of the advantages of coupled hydrogeophysical inversion is the direct link between the hydrologic model and the individual geophysical data used to condition the model. That is, there is no requirement to collect geophysical data suitable for independent geophysical inversion. The geophysical measurements collected can be optimized for estimation of hydrologic model parameters rather than to develop a geophysical model. Using a synthetic model of drip irrigation we evaluate the value of individual resistivity measurements to describe the soil hydraulic properties and then use this information to build a data set optimized for characterizing hydrologic processes. We then compare the information content in the optimized data set with the information content in a data set optimized using a Jacobian sensitivity analysis.

Improving Hydrological Simulations by Incorporating GRACE Data for Parameter Calibration

NASA Astrophysics Data System (ADS)

Bai, P.

2017-12-01

Hydrological model parameters are commonly calibrated by observed streamflow data. This calibration strategy is questioned when the modeled hydrological variables of interest are not limited to streamflow. Well-performed streamflow simulations do not guarantee the reliable reproduction of other hydrological variables. One of the reasons is that hydrological model parameters are not reasonably identified. The Gravity Recovery and Climate Experiment (GRACE) satellite-derived total water storage change (TWSC) data provide an opportunity to constrain hydrological model parameterizations in combination with streamflow observations. We constructed a multi-objective calibration scheme based on GRACE-derived TWSC and streamflow observations, with the aim of improving the parameterizations of hydrological models. The multi-objective calibration scheme was compared with the traditional single-objective calibration scheme, which is based only on streamflow observations. Two monthly hydrological models were employed on 22 Chinese catchments with different hydroclimatic conditions. The model evaluation was performed using observed streamflows, GRACE-derived TWSC, and evapotranspiraiton (ET) estimates from flux towers and from the water balance approach. Results showed that the multi-objective calibration provided more reliable TWSC and ET simulations without significant deterioration in the accuracy of streamflow simulations than the single-objective calibration. In addition, the improvements of TWSC and ET simulations were more significant in relatively dry catchments than in relatively wet catchments. This study highlights the importance of including additional constraints besides streamflow observations in the parameter estimation to improve the performances of hydrological models.

Modeling the investment casting of a titanium crown.

PubMed

Atwood, R C; Lee, P D; Curtis, R V; Maijer, D M

2007-01-01

The objective of this study was to apply computational modeling tools to assist in the design of titanium dental castings. The tools developed should incorporate state-of-the-art micromodels to predict the depth to which the mechanical properties of the crown are affected by contamination from the mold. The model should also be validated by comparison of macro- and micro-defects found in a typical investment cast titanium tooth crown. Crowns were hand-waxed and investment cast in commercial purity grade 1 (CP-1) titanium by a commercial dental laboratory. The castings were analyzed using X-ray microtomography (XMT). Following sectioning, analysis continued with optical and scanning electron microscopy, and microhardness testing. An in-house cellular-automata solidification and finite-difference diffusion program was coupled with a commercial casting program to model the investment casting process. A three-dimensional (3D) digital image generated by X-ray tomography was used to generate an accurate geometric representation of a molar crown casting. Previously reported work was significantly expanded upon by including transport of dissolved oxygen and impurity sources upon the arbitrarily shaped surface of the crown, and improved coupling of micro- and macro-scale simulations. Macroscale modeling was found to be sufficient to accurately predict the location of the large internal porosity. These are shrinkage pores located in the thick sections of the cusp. The model was used to determine the influence of sprue design on the size and location of these pores. Combining microscale with macroscale modeling allowed the microstructure and depth of contamination to be predicted qualitatively. This combined model predicted a surprising result--the dissolution of silicon from the mold into the molten titanium is sufficient to depress the freezing point of the liquid metal such that the crown solidifies the subsurface. Solidification then progresses inwards and back out to the surface through the silicon-enriched near-surface layer. The microstructure and compositional analysis of the near-surface region are consistent with this prediction. A multiscale model was developed and validated, which can be used to design CP-Ti dental castings to minimize both macro- and micro-defects, including shrinkage porosity, grain size and the extent of surface contamination due to reaction with the mold material. The model predicted the surprising result that the extent of Si contamination from the mold was sufficient to suppress the liquidus temperature to the extent that the surface (to a depth of approximately 100 microm) of the casting solidifies after the bulk. This significantly increases the oxygen pickup, thereby increasing the depth of formation of alpha casing. The trend towards mold materials with reduced Si in order to produce easier-to-finish titanium castings is a correct approach.

Spatial calibration and temporal validation of flow for regional scale hydrologic modeling

USDA-ARS?s Scientific Manuscript database

Physically based regional scale hydrologic modeling is gaining importance for planning and management of water resources. Calibration and validation of such regional scale model is necessary before applying it for scenario assessment. However, in most regional scale hydrologic modeling, flow validat...

A Community Data Model for Hydrologic Observations

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Horsburgh, J. S.; Zaslavsky, I.; Maidment, D. R.; Valentine, D.; Jennings, B.

2006-12-01

The CUAHSI Hydrologic Information System project is developing information technology infrastructure to support hydrologic science. Hydrologic information science involves the description of hydrologic environments in a consistent way, using data models for information integration. This includes a hydrologic observations data model for the storage and retrieval of hydrologic observations in a relational database designed to facilitate data retrieval for integrated analysis of information collected by multiple investigators. It is intended to provide a standard format to facilitate the effective sharing of information between investigators and to facilitate analysis of information within a single study area or hydrologic observatory, or across hydrologic observatories and regions. The observations data model is designed to store hydrologic observations and sufficient ancillary information (metadata) about the observations to allow them to be unambiguously interpreted and used and provide traceable heritage from raw measurements to usable information. The design is based on the premise that a relational database at the single observation level is most effective for providing querying capability and cross dimension data retrieval and analysis. This premise is being tested through the implementation of a prototype hydrologic observations database, and the development of web services for the retrieval of data from and ingestion of data into the database. These web services hosted by the San Diego Supercomputer center make data in the database accessible both through a Hydrologic Data Access System portal and directly from applications software such as Excel, Matlab and ArcGIS that have Standard Object Access Protocol (SOAP) capability. This paper will (1) describe the data model; (2) demonstrate the capability for representing diverse data in the same database; (3) demonstrate the use of the database from applications software for the performance of hydrologic analysis across different observation types.

Hydrologic connectivity: Quantitative assessments of hydrologic-enforced drainage structures in an elevation model

USGS Publications Warehouse

Poppenga, Sandra K.; Worstell, Bruce B.

2016-01-01

Elevation data derived from light detection and ranging present challenges for hydrologic modeling as the elevation surface includes bridge decks and elevated road features overlaying culvert drainage structures. In reality, water is carried through these structures; however, in the elevation surface these features impede modeled overland surface flow. Thus, a hydrologically-enforced elevation surface is needed for hydrodynamic modeling. In the Delaware River Basin, hydrologic-enforcement techniques were used to modify elevations to simulate how constructed drainage structures allow overland surface flow. By calculating residuals between unfilled and filled elevation surfaces, artificially pooled depressions that formed upstream of constructed drainage structure features were defined, and elevation values were adjusted by generating transects at the location of the drainage structures. An assessment of each hydrologically-enforced drainage structure was conducted using field-surveyed culvert and bridge coordinates obtained from numerous public agencies, but it was discovered the disparate drainage structure datasets were not comprehensive enough to assess all remotely located depressions in need of hydrologic-enforcement. Alternatively, orthoimagery was interpreted to define drainage structures near each depression, and these locations were used as reference points for a quantitative hydrologic-enforcement assessment. The orthoimagery-interpreted reference points resulted in a larger corresponding sample size than the assessment between hydrologic-enforced transects and field-surveyed data. This assessment demonstrates the viability of rules-based hydrologic-enforcement that is needed to achieve hydrologic connectivity, which is valuable for hydrodynamic models in sensitive coastal regions. Hydrologic-enforced elevation data are also essential for merging with topographic/bathymetric elevation data that extend over vulnerable urbanized areas and dynamic coastal regions.

Hydrological Modeling in the Bull Run Watershed in Support of a Piloting Utility Modeling Applications (PUMA) Project

NASA Astrophysics Data System (ADS)

Nijssen, B.; Chiao, T. H.; Lettenmaier, D. P.; Vano, J. A.

2016-12-01

Hydrologic models with varying complexities and structures are commonly used to evaluate the impact of climate change on future hydrology. While the uncertainties in future climate projections are well documented, uncertainties in streamflow projections associated with hydrologic model structure and parameter estimation have received less attention. In this study, we implemented and calibrated three hydrologic models (the Distributed Hydrology Soil Vegetation Model (DHSVM), the Precipitation-Runoff Modeling System (PRMS), and the Variable Infiltration Capacity model (VIC)) for the Bull Run watershed in northern Oregon using consistent data sources and best practice calibration protocols. The project was part of a Piloting Utility Modeling Applications (PUMA) project with the Portland Water Bureau (PWB) under the umbrella of the Water Utility Climate Alliance (WUCA). Ultimately PWB would use the model evaluation to select a model to perform in-house climate change analysis for Bull Run Watershed. This presentation focuses on the experimental design of the comparison project, project findings and the collaboration between the team at the University of Washington and at PWB. After calibration, the three models showed similar capability to reproduce seasonal and inter-annual variations in streamflow, but differed in their ability to capture extreme events. Furthermore, the annual and seasonal hydrologic sensitivities to changes in climate forcings differed among models, potentially attributable to different model representations of snow and vegetation processes.

On the use of three hydrological models as hypotheses to investigate the behaviour of a small Mediterranean catchment

NASA Astrophysics Data System (ADS)

Ruiz Pérez, Guiomar; Latron, Jérôme; Llorens, Pilar; Gallart, Francesc; Francés, Félix

2017-04-01

Selecting an adequate hydrological model is the first step to carry out a rainfall-runoff modelling exercise. A hydrological model is a hypothesis of catchment functioning, encompassing a description of dominant hydrological processes and predicting how these processes interact to produce the catchment's response to external forcing. Current research lines emphasize the importance of multiple working hypotheses for hydrological modelling instead of only using a single model. In line with this philosophy, here different hypotheses were considered and analysed to simulate the nonlinear response of a small Mediterranean catchment and to progress in the analysis of its hydrological behaviour. In particular, three hydrological models were considered representing different potential hypotheses: two lumped models called LU3 and LU4, and one distributed model called TETIS. To determine how well each specific model performed and to assess whether a model was more adequate than another, we raised three complementary tests: one based on the analysis of residual errors series, another based on a sensitivity analysis and the last one based on using multiple evaluation criteria associated to the concept of Pareto frontier. This modelling approach, based on multiple working hypotheses, helped to improve our perceptual model of the catchment behaviour and, furthermore, could be used as a guidance to improve the performance of other environmental models.

Shrink-swell behavior of soil across a vertisol catena

USDA-ARS?s Scientific Manuscript database

Shrinking and swelling of soils and the associated formation and closing of cracks can vary spatially within the smallest hydrologic unit subdivision utilized in surface hydrology models. Usually in the application of surface hydrology models, cracking is not considered to vary within a hydrologic u...

Functional adaptation of crustacean exoskeletal elements through structural and compositional diversity: a combined experimental and theoretical study.

PubMed

Fabritius, Helge-Otto; Ziegler, Andreas; Friák, Martin; Nikolov, Svetoslav; Huber, Julia; Seidl, Bastian H M; Ruangchai, Sukhum; Alagboso, Francisca I; Karsten, Simone; Lu, Jin; Janus, Anna M; Petrov, Michal; Zhu, Li-Fang; Hemzalová, Pavlína; Hild, Sabine; Raabe, Dierk; Neugebauer, Jörg

2016-09-09

The crustacean cuticle is a composite material that covers the whole animal and forms the continuous exoskeleton. Nano-fibers composed of chitin and protein molecules form most of the organic matrix of the cuticle that, at the macroscale, is organized in up to eight hierarchical levels. At least two of them, the exo- and endocuticle, contain a mineral phase of mainly Mg-calcite, amorphous calcium carbonate and phosphate. The high number of hierarchical levels and the compositional diversity provide a high degree of freedom for varying the physical, in particular mechanical, properties of the material. This makes the cuticle a versatile material ideally suited to form a variety of skeletal elements that are adapted to different functions and the eco-physiological strains of individual species. This review presents our recent analytical, experimental and theoretical studies on the cuticle, summarising at which hierarchical levels structure and composition are modified to achieve the required physical properties. We describe our multi-scale hierarchical modeling approach based on the results from these studies, aiming at systematically predicting the structure-composition-property relations of cuticle composites from the molecular level to the macro-scale. This modeling approach provides a tool to facilitate the development of optimized biomimetic materials within a knowledge-based design approach.

Subdivision of Texas watersheds for hydrologic modeling.

DOT National Transportation Integrated Search

2009-06-01

The purpose of this report is to present a set of findings and examples for subdivision of watersheds for hydrologic modeling. Three approaches were used to examine the impact of watershed subdivision on modeled hydrologic response: (1) An equal-area...

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 study establish the feasibility and importance of including influential point detection diagnostics as a standard tool in hydrological model calibration. They provide the hydrologist with important information on whether model calibration is susceptible to a small number of highly influent data points. This enables the hydrologist to make a more informed decision of whether to (1) remove/retain the calibration data; (2) adjust the calibration strategy and/or hydrological model to reduce the susceptibility of model predictions to a small number of influential observations.

Cyberinfrastructure to Support Collaborative and Reproducible Computational Hydrologic Modeling

NASA Astrophysics Data System (ADS)

Goodall, J. L.; Castronova, A. M.; Bandaragoda, C.; Morsy, M. M.; Sadler, J. M.; Essawy, B.; Tarboton, D. G.; Malik, T.; Nijssen, B.; Clark, M. P.; Liu, Y.; Wang, S. W.

2017-12-01

Creating cyberinfrastructure to support reproducibility of computational hydrologic models is an important research challenge. Addressing this challenge requires open and reusable code and data with machine and human readable metadata, organized in ways that allow others to replicate results and verify published findings. Specific digital objects that must be tracked for reproducible computational hydrologic modeling include (1) raw initial datasets, (2) data processing scripts used to clean and organize the data, (3) processed model inputs, (4) model results, and (5) the model code with an itemization of all software dependencies and computational requirements. HydroShare is a cyberinfrastructure under active development designed to help users store, share, and publish digital research products in order to improve reproducibility in computational hydrology, with an architecture supporting hydrologic-specific resource metadata. Researchers can upload data required for modeling, add hydrology-specific metadata to these resources, and use the data directly within HydroShare.org for collaborative modeling using tools like CyberGIS, Sciunit-CLI, and JupyterHub that have been integrated with HydroShare to run models using notebooks, Docker containers, and cloud resources. Current research aims to implement the Structure For Unifying Multiple Modeling Alternatives (SUMMA) hydrologic model within HydroShare to support hypothesis-driven hydrologic modeling while also taking advantage of the HydroShare cyberinfrastructure. The goal of this integration is to create the cyberinfrastructure that supports hypothesis-driven model experimentation, education, and training efforts by lowering barriers to entry, reducing the time spent on informatics technology and software development, and supporting collaborative research within and across research groups.

WEB-DHM: A distributed biosphere hydrological model developed by coupling a simple biosphere scheme with a hillslope hydrological model

USDA-ARS?s Scientific Manuscript database

The coupling of land surface models and hydrological models potentially improves the land surface representation, benefiting both the streamflow prediction capabilities as well as providing improved estimates of water and energy fluxes into the atmosphere. In this study, the simple biosphere model 2...

An integrated crop and hydrologic modeling system to estimate hydrologic impacts of crop irrigation demands

Treesearch

R.T. McNider; C. Handyside; K. Doty; W.L. Ellenburg; J.F. Cruise; J.R. Christy; D. Moss; V. Sharda; G. Hoogenboom; Peter Caldwell

2015-01-01

The present paper discusses a coupled gridded crop modeling and hydrologic modeling system that can examine the benefits of irrigation and costs of irrigation and the coincident impact of the irrigation water withdrawals on surface water hydrology. The system is applied to the Southeastern U.S. The system tools to be discussed include a gridded version (GriDSSAT) of...

iTree-Hydro: Snow hydrology update for the urban forest hydrology model

Treesearch

Yang Yang; Theodore A. Endreny; David J. Nowak

2011-01-01

This article presents snow hydrology updates made to iTree-Hydro, previously called the Urban Forest Effects—Hydrology model. iTree-Hydro Version 1 was a warm climate model developed by the USDA Forest Service to provide a process-based planning tool with robust water quantity and quality predictions given data limitations common to most urban areas. Cold climate...

Modeling non-linear growth responses to temperature and hydrology in wetland trees

NASA Astrophysics Data System (ADS)

Keim, R.; Allen, S. T.

2016-12-01

Growth responses of wetland trees to flooding and climate variations are difficult to model because they depend on multiple, apparently interacting factors, but are a critical link in hydrological control of wetland carbon budgets. To more generally understand tree growth to hydrological forcing, we modeled non-linear responses of tree ring growth to flooding and climate at sub-annual time steps, using Vaganov-Shashkin response functions. We calibrated the model to six baldcypress tree-ring chronologies from two hydrologically distinct sites in southern Louisiana, and tested several hypotheses of plasticity in wetlands tree responses to interacting environmental variables. The model outperformed traditional multiple linear regression. More importantly, optimized response parameters were generally similar among sites with varying hydrological conditions, suggesting generality to the functions. Model forms that included interacting responses to multiple forcing factors were more effective than were single response functions, indicating the principle of a single limiting factor is not correct in wetlands and both climatic and hydrological variables must be considered in predicting responses to hydrological or climate change.

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

NASA Astrophysics Data System (ADS)

Kirchner, James W.

2006-03-01

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

Attaining insight into interactions between hydrologic model parameters and geophysical attributes for national-scale model parameter estimation

NASA Astrophysics Data System (ADS)

Mizukami, N.; Clark, M. P.; Newman, A. J.; Wood, A.; Gutmann, E. D.

2017-12-01

Estimating spatially distributed model parameters is a grand challenge for large domain hydrologic modeling, especially in the context of hydrologic model applications such as streamflow forecasting. Multi-scale Parameter Regionalization (MPR) is a promising technique that accounts for the effects of fine-scale geophysical attributes (e.g., soil texture, land cover, topography, climate) on model parameters and nonlinear scaling effects on model parameters. MPR computes model parameters with transfer functions (TFs) that relate geophysical attributes to model parameters at the native input data resolution and then scales them using scaling functions to the spatial resolution of the model implementation. One of the biggest challenges in the use of MPR is identification of TFs for each model parameter: both functional forms and geophysical predictors. TFs used to estimate the parameters of hydrologic models typically rely on previous studies or were derived in an ad-hoc, heuristic manner, potentially not utilizing maximum information content contained in the geophysical attributes for optimal parameter identification. Thus, it is necessary to first uncover relationships among geophysical attributes, model parameters, and hydrologic processes (i.e., hydrologic signatures) to obtain insight into which and to what extent geophysical attributes are related to model parameters. We perform multivariate statistical analysis on a large-sample catchment data set including various geophysical attributes as well as constrained VIC model parameters at 671 unimpaired basins over the CONUS. We first calibrate VIC model at each catchment to obtain constrained parameter sets. Additionally, parameter sets sampled during the calibration process are used for sensitivity analysis using various hydrologic signatures as objectives to understand the relationships among geophysical attributes, parameters, and hydrologic processes.

A framework for human-hydrologic system model development integrating hydrology and water management: application to the Cutzamala water system in Mexico

NASA Astrophysics Data System (ADS)

Wi, S.; Freeman, S.; Brown, C.

2017-12-01

This study presents a general approach to developing computational models of human-hydrologic systems where human modification of hydrologic surface processes are significant or dominant. A river basin system is represented by a network of human-hydrologic response units (HHRUs) identified based on locations where river regulations happen (e.g., reservoir operation and diversions). Natural and human processes in HHRUs are simulated in a holistic framework that integrates component models representing rainfall-runoff, river routing, reservoir operation, flow diversion and water use processes. We illustrate the approach in a case study of the Cutzamala water system (CWS) in Mexico, a complex inter-basin water transfer system supplying the Mexico City Metropolitan Area (MCMA). The human-hydrologic system model for CWS (CUTZSIM) is evaluated in terms of streamflow and reservoir storages measured across the CWS and to water supplied for MCMA. The CUTZSIM improves the representation of hydrology and river-operation interaction and, in so doing, advances evaluation of system-wide water management consequences under altered climatic and demand regimes. The integrated modeling framework enables evaluation and simulation of model errors throughout the river basin, including errors in representation of the human component processes. Heretofore, model error evaluation, predictive error intervals and the resultant improved understanding have been limited to hydrologic processes. The general framework represents an initial step towards fuller understanding and prediction of the many and varied processes that determine the hydrologic fluxes and state variables in real river basins.

Diagnosing the impact of alternative calibration strategies on coupled hydrologic models

NASA Astrophysics Data System (ADS)

Smith, T. J.; Perera, C.; Corrigan, C.

2017-12-01

Hydrologic models represent a significant tool for understanding, predicting, and responding to the impacts of water on society and society on water resources and, as such, are used extensively in water resources planning and management. Given this important role, the validity and fidelity of hydrologic models is imperative. While extensive focus has been paid to improving hydrologic models through better process representation, better parameter estimation, and better uncertainty quantification, significant challenges remain. In this study, we explore a number of competing model calibration scenarios for simple, coupled snowmelt-runoff models to better understand the sensitivity / variability of parameterizations and its impact on model performance, robustness, fidelity, and transferability. Our analysis highlights the sensitivity of coupled snowmelt-runoff model parameterizations to alterations in calibration approach, underscores the concept of information content in hydrologic modeling, and provides insight into potential strategies for improving model robustness / fidelity.

On the information content of hydrological signatures and their relationship to catchment attributes

NASA Astrophysics Data System (ADS)

Addor, Nans; Clark, Martyn P.; Prieto, Cristina; Newman, Andrew J.; Mizukami, Naoki; Nearing, Grey; Le Vine, Nataliya

2017-04-01

Hydrological signatures, which are indices characterizing hydrologic behavior, are increasingly used for the evaluation, calibration and selection of hydrological models. Their key advantage is to provide more direct insights into specific hydrological processes than aggregated metrics (e.g., the Nash-Sutcliffe efficiency). A plethora of signatures now exists, which enable characterizing a variety of hydrograph features, but also makes the selection of signatures for new studies challenging. Here we propose that the selection of signatures should be based on their information content, which we estimated using several approaches, all leading to similar conclusions. To explore the relationship between hydrological signatures and the landscape, we extended a previously published data set of hydrometeorological time series for 671 catchments in the contiguous United States, by characterizing the climatic conditions, topography, soil, vegetation and stream network of each catchment. This new catchment attributes data set will soon be in open access, and we are looking forward to introducing it to the community. We used this data set in a data-learning algorithm (random forests) to explore whether hydrological signatures could be inferred from catchment attributes alone. We find that some signatures can be predicted remarkably well by random forests and, interestingly, the same signatures are well captured when simulating discharge using a conceptual hydrological model. We discuss what this result reveals about our understanding of hydrological processes shaping hydrological signatures. We also identify which catchment attributes exert the strongest control on catchment behavior, in particular during extreme hydrological events. Overall, climatic attributes have the most significant influence, and strongly condition how well hydrological signatures can be predicted by random forests and simulated by the hydrological model. In contrast, soil characteristics at the catchment scale are not found to be significant predictors by random forests, which raises questions on how to best use soil data for hydrological modeling, for instance for parameter estimation. We finally demonstrate that signatures with high spatial variability are poorly captured by random forests and model simulations, which makes their regionalization delicate. We conclude with a ranking of signatures based on their information content, and propose that the signatures with high information content are best suited for model calibration, model selection and understanding hydrologic similarity.

A methodology for long range prediction of air transportation

NASA Technical Reports Server (NTRS)

Ayati, M. B.; English, J. M.

1980-01-01

The paper describes the methodology for long-time projection of aircraft fuel requirements. A new concept of social and economic factors for future aviation industry which provides an estimate of predicted fuel usage is presented; it includes air traffic forecasts and lead times for producing new engines and aircraft types. An air transportation model is then developed in terms of an abstracted set of variables which represent the entire aircraft industry on a macroscale. This model was evaluated by testing the required output variables from a model based on historical data over the past decades.

One-day offset in daily hydrologic modeling: An exploration of the issue in automatic model calibration

USDA-ARS?s Scientific Manuscript database

The literature of daily hydrologic modelling illustrates that daily simulation models are incapable of accurately representing hydrograph timing due to relationships between precipitation and watershed hydrologic response. For watersheds with a time of concentration less than 24 hrs and a late day p...

Interfacial separation of a mature biofilm from a glass surface - A combined experimental and cohesive zone modelling approach.

PubMed

Safari, Ashkan; Tukovic, Zeljko; Cardiff, Philip; Walter, Maik; Casey, Eoin; Ivankovic, Alojz

2016-02-01

A good understanding of the mechanical stability of biofilms is essential for biofouling management, particularly when mechanical forces are used. Previous biofilm studies lack a damage-based theoretical model to describe the biofilm separation from a surface. The purpose of the current study was to investigate the interfacial separation of a mature biofilm from a rigid glass substrate using a combined experimental and numerical modelling approach. In the current work, the biofilm-glass interfacial separation process was investigated under tensile and shear stresses at the macroscale level, known as modes I and II failure mechanisms respectively. The numerical simulations were performed using a Finite Volume (FV)-based simulation package (OpenFOAM®) to predict the separation initiation using the cohesive zone model (CZM). Atomic force microscopy (AFM)-based retraction curve was used to obtain the separation properties between the biofilm and glass colloid at microscale level, where the CZM parameters were estimated using the Johnson-Kendall-Roberts (JKR) model. In this study CZM is introduced as a reliable method for the investigation of interfacial separation between a biofilm and rigid substrate, in which a high local stress at the interface edge acts as an ultimate stress at the crack tip.This study demonstrated that the total interfacial failure energy measured at the macroscale, was significantly higher than the pure interfacial separation energy obtained by AFM at the microscale, indicating a highly ductile deformation behaviour within the bulk biofilm matrix. The results of this study can significantly contribute to the understanding of biofilm detachments. Copyright © 2015 Elsevier Ltd. All rights reserved.

Multiscale mechanics of the lateral pressure effect on enhancing the load transfer between polymer coated CNTs.

PubMed

Yazdandoost, Fatemeh; Mirzaeifar, Reza; Qin, Zhao; Buehler, Markus J

2017-05-04

While individual carbon nanotubes (CNTs) are known as one of the strongest fibers ever known, even the strongest fabricated macroscale CNT yarns and fibers are still significantly weaker than individual nanotubes. The loss in mechanical properties is mainly because the deformation mechanism of CNT fibers is highly governed by the weak shear strength corresponding to sliding of nanotubes on each other. Adding polymer coating to the bundles, and twisting the CNT yarns to enhance the intertube interactions are both efficient methods to improve the mechanical properties of macroscale yarns. Here, we perform molecular dynamics (MD) simulations to unravel the unknown deformation mechanism in the intertube polymer chains and also local deformations of the CNTs at the atomistic scale. Our results show that the lateral pressure can have both beneficial and adverse effects on shear strength of polymer coated CNTs, depending on the local deformations at the atomistic scale. In this paper we also introduce a bottom-up bridging strategy between a full atomistic model and a coarse-grained (CG) model. Our trained CG model is capable of incorporating the atomistic scale local deformations of each CNT to the larger scale collect behavior of bundles, which enables the model to accurately predict the effect of lateral pressure on larger CNT bundles and yarns. The developed multiscale CG model is implemented to study the effect of lateral pressure on the shear strength of straight polymer coated CNT yarns, and also the effect of twisting on the pull-out force of bundles in spun CNT yarns.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Climate change: evaluating your local and regional water resources

USGS Publications Warehouse

Flint, Lorraine E.; Flint, Alan L.; Thorne, James H.

2015-01-01

The BCM is a fine-scale hydrologic model that uses detailed maps of soils, geology, topography, and transient monthly or daily maps of potential evapotranspiration, air temperature, and precipitation to generate maps of recharge, runoff, snow pack, actual evapotranspiration, and climatic water deficit. With these comprehensive environmental inputs and experienced scientific analysis, the BCM provides resource managers with important hydrologic and ecologic understanding of a landscape or basin at hillslope to regional scales. The model is calibrated using historical climate and streamflow data over the range of geologic materials specific to an area. Once calibrated, the model is used to translate climate-change data into hydrologic responses for a defined landscape, to provide managers an understanding of potential ecological risks and threats to water supplies and managed hydrologic systems. Although limited to estimates of unimpaired hydrologic conditions, estimates of impaired conditions, such as agricultural demand, diversions, or reservoir outflows can be incorporated into the calibration of the model to expand its utility. Additionally, the model can be linked to other models, such as groundwater-flow models (that is, MODFLOW) or the integrated hydrologic model (MF-FMP), to provide information about subsurface hydrologic processes. The model can be applied at a relatively small scale, but also can be applied to large-scale national and international river basins.

Microhabitats in the tropics buffer temperature in a globally coherent manner

PubMed Central

Scheffers, Brett R.; Evans, Theodore A.; Williams, Stephen E.; Edwards, David P.

2014-01-01

Vegetated habitats contain a variety of fine-scale features that can ameliorate temperate extremes. These buffered microhabitats may be used by species to evade extreme weather and novel climates in the future. Yet, the magnitude and extent of this buffering on a global scale remains unknown. Across all tropical continents and using 36 published studies, we assessed temperature buffering from within microhabitats across various habitat strata and structures (e.g. soil, logs, epiphytes and tree holes) and compared them to non-buffered macro-scale ambient temperatures (the thermal control). Microhabitats buffered temperature by 3.9°C and reduced maximum temperatures by 3.5°C. Buffering was most pronounced in tropical lowlands where temperatures were most variable. With the expected increase in extreme weather events, microhabitats should provide species with a local layer of protection that is not captured by traditional climate assessments, which are typically derived from macro-scale temperatures (e.g. satellites). Our data illustrate the need for a next generation of predictive models that account for species' ability to move within microhabitats to exploit favourable buffered microclimates. PMID:25540160

Probing Dynamics in Granular Media of Contrasting Geometries via X-Ray Phase Contrast Imaging and PDV

NASA Astrophysics Data System (ADS)

Crum, Ryan; Pagan, Darren; Lind, Jon; Homel, Michael; Hurley, Ryan; Herbold, Eric; Akin, Minta

Granular systems are ubiquitous in our everyday world and play a central role in many dynamic scientific problems including mine blasting, projectile penetration, astrophysical collisions, explosions, and dynamic compaction. An understanding of granular media's behavior under various loading conditions is an ongoing scientific grand challenge. This is partly due to the intricate interplay between material properties, loading conditions, grain geometry, and grain connectivity. Previous dynamic studies in granular media predominantly utilize the macro-scale analyses VISAR or PDV, diagnostics that are not sensitive to the many degrees of freedom and their interactions, focusing instead on their aggregate effect. Results of a macro-scale analysis leave the principal interactions of these degrees of freedom too entangled to elucidate. To isolate the significance of grain geometry, this study probes various geometries of granular media subjected to gas gun generated waves via in-situ X-ray analysis. Analyses include evaluating displacement fields, grain fracture, inter- and intra-granular densification, and wave front motion. Phase Contrast Imaging (PCI) and PDV analyses feed directly into our concurrent meso-scale granular media modeling efforts to enhance our predictive capabilities.

Harvesting liquid from unsaturated vapor - nanoflows induced by capillary condensation

NASA Astrophysics Data System (ADS)

Vincent, Olivier; Marguet, Bastien; Stroock, Abraham

2016-11-01

A vapor, even subsaturated, can spontaneously form liquid in nanoscale spaces. This process, known as capillary condensation, plays a fundamental role in various contexts, such as the formation of clouds or the dynamics of hydrocarbons in the geological subsurface. However, large uncertainties remain on the thermodynamics and fluid mechanics of the phenomenon, due to experimental challenges as well as outstanding questions about the validity of macroscale physics at the nanometer scale. We studied experimentally the spatio-temporal dynamics of water condensation in a model nanoporous medium (pore radius 2 nm), taking advantage of the color change of the material upon hydration. We found that at low relative humidities (< 60 % RH), capillary condensation progressed in a diffusive fashion, while it occurred through a well-defined capillary-viscous imbibition front at > 60 % RH, driven by a balance between the pore capillary pressure and the condensation stress given by Kelvin equation. Further analyzing the imbibition dynamics as a function of saturation allowed us to extract detailed information about the physics of nano-confined fluids. Our results suggest excellent extension of macroscale fluid dynamics and thermodynamics even in pores 10 molecules in diameter.

Micro- to macroscale perspectives on space plasmas

NASA Technical Reports Server (NTRS)

Eastman, Timothy E.

1993-01-01

The Earth's magnetosphere is the most accessible of natural collisionless plasma environments; an astrophysical plasma 'laboratory'. Magnetospheric physics has been in an exploration phase since its origin 35 years ago but new coordinated, multipoint observations, theory, modeling, and simulations are moving this highly interdisciplinary field of plasma science into a new phase of synthesis and understanding. Plasma systems are ones in which binary collisions are relatively negligible and collective behavior beyond the microscale emerges. Most readily accessible natural plasma systems are collisional and nearest-neighbor classical interactions compete with longer-range plasma effects. Except for stars, most space plasmas are collisionless, however, and the effects of electrodynamic coupling dominate. Basic physical processes in such collisionless plasmas occur at micro-, meso-, and macroscales that are not merely reducible to each other in certain crucial ways as illustrated for the global coupling of the Earth's magnetosphere and for the nonlinear dynamics of charged particle motion in the magnetotail. Such global coupling and coherence makes the geospace environment, the domain of solar-terrestrial science, the most highly coupled of all physical geospheres.

Mapping (dis)agreement in hydrologic projections

NASA Astrophysics Data System (ADS)

Melsen, Lieke A.; Addor, Nans; Mizukami, Naoki; Newman, Andrew J.; Torfs, Paul J. J. F.; Clark, Martyn P.; Uijlenhoet, Remko; Teuling, Adriaan J.

2018-03-01

Hydrologic projections are of vital socio-economic importance. However, they are also prone to uncertainty. In order to establish a meaningful range of storylines to support water managers in decision making, we need to reveal the relevant sources of uncertainty. Here, we systematically and extensively investigate uncertainty in hydrologic projections for 605 basins throughout the contiguous US. We show that in the majority of the basins, the sign of change in average annual runoff and discharge timing for the period 2070-2100 compared to 1985-2008 differs among combinations of climate models, hydrologic models, and parameters. Mapping the results revealed that different sources of uncertainty dominate in different regions. Hydrologic model induced uncertainty in the sign of change in mean runoff was related to snow processes and aridity, whereas uncertainty in both mean runoff and discharge timing induced by the climate models was related to disagreement among the models regarding the change in precipitation. Overall, disagreement on the sign of change was more widespread for the mean runoff than for the discharge timing. The results demonstrate the need to define a wide range of quantitative hydrologic storylines, including parameter, hydrologic model, and climate model forcing uncertainty, to support water resource planning.

Thermo-Oxidative Induced Damage in Polymer Composites: Microstructure Image-Based Multi-Scale Modeling and Experimental Validation

NASA Astrophysics Data System (ADS)

Hussein, Rafid M.; Chandrashekhara, K.

2017-11-01

A multi-scale modeling approach is presented to simulate and validate thermo-oxidation shrinkage and cracking damage of a high temperature polymer composite. The multi-scale approach investigates coupled transient diffusion-reaction and static structural at macro- to micro-scale. The micro-scale shrinkage deformation and cracking damage are simulated and validated using 2D and 3D simulations. Localized shrinkage displacement boundary conditions for the micro-scale simulations are determined from the respective meso- and macro-scale simulations, conducted for a cross-ply laminate. The meso-scale geometrical domain and the micro-scale geometry and mesh are developed using the object oriented finite element (OOF). The macro-scale shrinkage and weight loss are measured using unidirectional coupons and used to build the macro-shrinkage model. The cross-ply coupons are used to validate the macro-shrinkage model by the shrinkage profiles acquired using scanning electron images at the cracked surface. The macro-shrinkage model deformation shows a discrepancy when the micro-scale image-based cracking is computed. The local maximum shrinkage strain is assumed to be 13 times the maximum macro-shrinkage strain of 2.5 × 10-5, upon which the discrepancy is minimized. The microcrack damage of the composite is modeled using a static elastic analysis with extended finite element and cohesive surfaces by considering the modulus spatial evolution. The 3D shrinkage displacements are fed to the model using node-wise boundary/domain conditions of the respective oxidized region. Microcrack simulation results: length, meander, and opening are closely matched to the crack in the area of interest for the scanning electron images.

Multi-site calibration, validation, and sensitivity analysis of the MIKE SHE Model for a large watershed in northern China

Treesearch

S. Wang; Z. Zhang; G. Sun; P. Strauss; J. Guo; Y. Tang; A. Yao

2012-01-01

Model calibration is essential for hydrologic modeling of large watersheds in a heterogeneous mountain environment. Little guidance is available for model calibration protocols for distributed models that aim at capturing the spatial variability of hydrologic processes. This study used the physically-based distributed hydrologic model, MIKE SHE, to contrast a lumped...

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.

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.

A RETROSPECTIVE ANALYSIS OF MODEL UNCERTAINTY FOR FORECASTING HYDROLOGIC CHANGE

EPA Science Inventory

GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...

The Impact of Microwave-Derived Surface Soil Moisture on Watershed Hydrological Modeling

NASA Technical Reports Server (NTRS)

ONeill, P. E.; Hsu, A. Y.; Jackson, T. J.; Wood, E. F.; Zion, M.

1997-01-01

The usefulness of incorporating microwave-derived soil moisture information in a semi-distributed hydrological model was demonstrated for the Washita '92 experiment in the Little Washita River watershed in Oklahoma. Initializing the hydrological model with surface soil moisture fields from the ESTAR airborne L-band microwave radiometer on a single wet day at the start of the study period produced more accurate model predictions of soil moisture than a standard hydrological initialization with streamflow data over an eight-day soil moisture drydown.

Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

NASA Astrophysics Data System (ADS)

Qi, W.; Zhang, C.; Fu, G.; Sweetapple, C.; Zhou, H.

2016-02-01

The applicability of six fine-resolution precipitation products, including precipitation radar, infrared, microwave and gauge-based products, using different precipitation computation recipes, is evaluated using statistical and hydrological methods in northeastern China. In addition, a framework quantifying uncertainty contributions of precipitation products, hydrological models, and their interactions to uncertainties in ensemble discharges is proposed. The investigated precipitation products are Tropical Rainfall Measuring Mission (TRMM) products (TRMM3B42 and TRMM3B42RT), Global Land Data Assimilation System (GLDAS)/Noah, Asian Precipitation - Highly-Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and a Global Satellite Mapping of Precipitation (GSMAP-MVK+) product. Two hydrological models of different complexities, i.e. a water and energy budget-based distributed hydrological model and a physically based semi-distributed hydrological model, are employed to investigate the influence of hydrological models on simulated discharges. Results show APHRODITE has high accuracy at a monthly scale compared with other products, and GSMAP-MVK+ shows huge advantage and is better than TRMM3B42 in relative bias (RB), Nash-Sutcliffe coefficient of efficiency (NSE), root mean square error (RMSE), correlation coefficient (CC), false alarm ratio, and critical success index. These findings could be very useful for validation, refinement, and future development of satellite-based products (e.g. NASA Global Precipitation Measurement). Although large uncertainty exists in heavy precipitation, hydrological models contribute most of the uncertainty in extreme discharges. Interactions between precipitation products and hydrological models can have the similar magnitude of contribution to discharge uncertainty as the hydrological models. A better precipitation product does not guarantee a better discharge simulation because of interactions. It is also found that a good discharge simulation depends on a good coalition of a hydrological model and a precipitation product, suggesting that, although the satellite-based precipitation products are not as accurate as the gauge-based products, they could have better performance in discharge simulations when appropriately combined with hydrological models. This information is revealed for the first time and very beneficial for precipitation product applications.

Evaluation of potential impacts of climate change and water management on streamflow in the Rovuma River, Mozambique and Tanzania

NASA Astrophysics Data System (ADS)

Minihane, M.; Lettenmaier, D. P.

2012-12-01

Economic development and public health are tied to water resources development in many parts of the world. Effective use of water management infrastructure investments requires projections of future climatic and water use conditions. This is particularly true in developing countries. We explore in this work water resource availability in the Rovuma River, which lies in a sparsely-populated region of southeastern Africa, on the border of Mozambique and Tanzania. While there are only limited documented observations of flow of the Rovuma River and it's tributaries, particularly in recent years, there is widespread interest in development of the water resources of the region. The national governments are interested in hydropower potential while private companies, many of them large multinational organizations, have started irrigation programs to increase agricultural output. While the Mozambique and Tanzania governments have a joint agreement over the river development, there is a need to assess both current and potential future water resource conditions in the basin. The sustainability of these developments, however, may be affected by climate change. Here we quantify potential changes in streamflow in the Rovuma River under dry and wet climate projection scenarios using the delta method and the Variable Infiltration Capacity (VIC) macro-scale hydrology model. We then evaluate streamflow changes relative to water withdrawals required for a range of irrigated agriculture scenarios. Our analysis is intended to be a starting point for planners to consider potential impacts of both streamflow withdrawal permits (for irrigated agriculture) and future uncertain climate conditions.

Inter-sectoral comparison of model uncertainty of climate change impacts in Africa

NASA Astrophysics Data System (ADS)

van Griensven, Ann; Vetter, Tobias; Piontek, Franzisca; Gosling, Simon N.; Kamali, Bahareh; Reinhardt, Julia; Dinkneh, Aklilu; Yang, Hong; Alemayehu, Tadesse

2016-04-01

We present the model results and their uncertainties of an inter-sectoral impact model inter-comparison initiative (ISI-MIP) for climate change impacts in Africa. The study includes results on hydrological, crop and health aspects. The impact models used ensemble inputs consisting of 20 time series of daily rainfall and temperature data obtained from 5 Global Circulation Models (GCMs) and 4 Representative concentration pathway (RCP). In this study, we analysed model uncertainty for the Regional Hydrological Models, Global Hydrological Models, Malaria models and Crop models. For the regional hydrological models, we used 2 African test cases: the Blue Nile in Eastern Africa and the Niger in Western Africa. For both basins, the main sources of uncertainty are originating from the GCM and RCPs, while the uncertainty of the regional hydrological models is relatively low. The hydrological model uncertainty becomes more important when predicting changes on low flows compared to mean or high flows. For the other sectors, the impact models have the largest share of uncertainty compared to GCM and RCP, especially for Malaria and crop modelling. The overall conclusion of the ISI-MIP is that it is strongly advised to use ensemble modeling approach for climate change impact studies throughout the whole modelling chain.

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

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

Implications of the methodological choices for hydrologic portrayals of climate change over the contiguous United States: Statistically downscaled forcing data and hydrologic models

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Gutmann, Ethan D.; Mendoza, Pablo A.; Newman, Andrew J.; Nijssen, Bart; Livneh, Ben; Hay, Lauren E.; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

Continental-domain assessments of climate change impacts on water resources typically rely on statistically downscaled climate model outputs to force hydrologic models at a finer spatial resolution. This study examines the effects of four statistical downscaling methods [bias-corrected constructed analog (BCCA), bias-corrected spatial disaggregation applied at daily (BCSDd) and monthly scales (BCSDm), and asynchronous regression (AR)] on retrospective hydrologic simulations using three hydrologic models with their default parameters (the Community Land Model, version 4.0; the Variable Infiltration Capacity model, version 4.1.2; and the Precipitation–Runoff Modeling System, version 3.0.4) over the contiguous United States (CONUS). Biases of hydrologic simulations forced by statistically downscaled climate data relative to the simulation with observation-based gridded data are presented. Each statistical downscaling method produces different meteorological portrayals including precipitation amount, wet-day frequency, and the energy input (i.e., shortwave radiation), and their interplay affects estimations of precipitation partitioning between evapotranspiration and runoff, extreme runoff, and hydrologic states (i.e., snow and soil moisture). The analyses show that BCCA underestimates annual precipitation by as much as −250 mm, leading to unreasonable hydrologic portrayals over the CONUS for all models. Although the other three statistical downscaling methods produce a comparable precipitation bias ranging from −10 to 8 mm across the CONUS, BCSDd severely overestimates the wet-day fraction by up to 0.25, leading to different precipitation partitioning compared to the simulations with other downscaled data. Overall, the choice of downscaling method contributes to less spread in runoff estimates (by a factor of 1.5–3) than the choice of hydrologic model with use of the default parameters if BCCA is excluded.

Improved Ground Hydrology Calculations for Global Climate Models (GCMs): Soil Water Movement and Evapotranspiration.

NASA Astrophysics Data System (ADS)

Abramopoulos, F.; Rosenzweig, C.; Choudhury, B.

1988-09-01

A physically based ground hydrology model is developed to improve the land-surface sensible and latent heat calculations in global climate models (GCMs). The processes of transpiration, evaporation from intercepted precipitation and dew, evaporation from bare soil, infiltration, soil water flow, and runoff are explicitly included in the model. The amount of detail in the hydrologic calculations is restricted to a level appropriate for use in a GCM, but each of the aforementioned processes is modeled on the basis of the underlying physical principles. Data from the Goddard Institute for Space Studies (GISS) GCM are used as inputs for off-line tests of the ground hydrology model in four 8° × 10° regions (Brazil, Sahel, Sahara, and India). Soil and vegetation input parameters are calculated as area-weighted means over the 8° × 10° gridhox. This compositing procedure is tested by comparing resulting hydrological quantities to ground hydrology model calculations performed on the 1° × 1° cells which comprise the 8° × 10° gridbox. Results show that the compositing procedure works well except in the Sahel where lower soil water levels and a heterogeneous land surface produce more variability in hydrological quantities, indicating that a resolution better than 8° × 10° is needed for that region. Modeled annual and diurnal hydrological cycles compare well with observations for Brazil, where real world data are available. The sensitivity of the ground hydrology model to several of its input parameters was tested; it was found to be most sensitive to the fraction of land covered by vegetation and least sensitive to the soil hydraulic conductivity and matric potential.

Development of Hydro-Informatic Modelling System and its Application

NASA Astrophysics Data System (ADS)

Wang, Z.; Liu, C.; Zheng, H.; Zhang, L.; Wu, X.

2009-12-01

The understanding of hydrological cycle is the core of hydrology and the scientific base of water resources management. Meanwhile, simulation of hydrological cycle has long been regarded as an important tool for the assessment, utilization and protection of water resources. In this paper, a new tool named Hydro-Informatic Modelling System (HIMS) has been developed and introduced with case studies in the Yellow River Basin in China and 331 catchments in Australia. The case studies showed that HIMS can be employed as an integrated platform for hydrological simulation in different regions. HIMS is a modular based framework of hydrological model designed for different utilization such as flood forecasting, water resources planning and evaluating hydrological impacts of climate change and human activities. The unique of HIMS is its flexibility in providing alternative modules in the simulation of hydrological cycle, which successfully overcome the difficulties in the availability of input data, the uncertainty of parameters, and the difference of rainfall-runoff processes. The modular based structure of HIMS makes it possible for developing new hydrological models by the users.

Hydrodynamic modeling of laser interaction with micro-structured targets

DOE PAGES

Velechovsky, Jan; Limpouch, Jiri; Liska, Richard; ...

2016-08-03

A model is developed for numerical simulations of laser absorption in plasmas made of porous materials, with particular interest in low-density foams. Laser absorption is treated on two spatial scales simultaneously. At the microscale, the expansion of a thin solid pore wall is modeled in one dimension and the information obtained is used in the macroscale fluid simulations for the description of the plasma homogenization behind the ionization front. This two-scale laser absorption model is implemented in the arbitrary Lagrangian–Eulerian hydrocode PALE. In conclusion, the numerical simulations of laser penetration into low-density foams compare favorably with published experimental data.

Comparisons of regional Hydrological Angular Momentum (HAM) of the different models

NASA Astrophysics Data System (ADS)

Nastula, J.; Kolaczek, B.; Popinski, W.

2006-10-01

In the paper hydrological excitations of the polar motion (HAM) were computed from various hydrological data series (NCEP, ECMWF, CPC water storage and LaD World Simulations of global continental water). HAM series obtained from these four models and the geodetic excitation function GEOD computed from the polar motion COMB03 data were compared in the seasonal spectral band. The results show big differences of these hydrological excitation functions as well as of their spectra in the seasonal spectra band. Seasonal oscillations of the global geophysical excitation functions (AAM + OAM + HAM) in all cases besides the NCEP/NCAR model are smaller than the geodetic excitation function. It means that these models need further improvement and perhaps not only hydrological models need improvements.

Meshing complex macro-scale objects into self-assembling bricks

PubMed Central

Hacohen, Adar; Hanniel, Iddo; Nikulshin, Yasha; Wolfus, Shuki; Abu-Horowitz, Almogit; Bachelet, Ido

2015-01-01

Self-assembly provides an information-economical route to the fabrication of objects at virtually all scales. However, there is no known algorithm to program self-assembly in macro-scale, solid, complex 3D objects. Here such an algorithm is described, which is inspired by the molecular assembly of DNA, and based on bricks designed by tetrahedral meshing of arbitrary objects. Assembly rules are encoded by topographic cues imprinted on brick faces while attraction between bricks is provided by embedded magnets. The bricks can then be mixed in a container and agitated, leading to properly assembled objects at high yields and zero errors. The system and its assembly dynamics were characterized by video and audio analysis, enabling the precise time- and space-resolved characterization of its performance and accuracy. Improved designs inspired by our system could lead to successful implementation of self-assembly at the macro-scale, allowing rapid, on-demand fabrication of objects without the need for assembly lines. PMID:26226488

Accelerating advances in continental domain hydrologic modeling

USGS Publications Warehouse

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

2015-01-01

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

Pursuing realistic hydrologic model under SUPERFLEX framework in a semi-humid catchment in China

NASA Astrophysics Data System (ADS)

Wei, Lingna; Savenije, Hubert H. G.; Gao, Hongkai; Chen, Xi

2016-04-01

Model realism is pursued perpetually by hydrologists for flood and drought prediction, integrated water resources management and decision support of water security. "Physical-based" distributed hydrologic models are speedily developed but they also encounter unneglectable challenges, for instance, computational time with low efficiency and parameters uncertainty. This study step-wisely tested four conceptual hydrologic models under the framework of SUPERFLEX in a small semi-humid catchment in southern Huai River basin of China. The original lumped FLEXL has hypothesized model structure of four reservoirs to represent canopy interception, unsaturated zone, subsurface flow of fast and slow components and base flow storage. Considering the uneven rainfall in space, the second model (FLEXD) is developed with same parameter set for different rain gauge controlling units. To reveal the effect of topography, terrain descriptor of height above the nearest drainage (HAND) combined with slope is applied to classify the experimental catchment into two landscapes. Then the third one (FLEXTOPO) builds different model blocks in consideration of the dominant hydrologic process corresponding to the topographical condition. The fourth one named FLEXTOPOD integrating the parallel framework of FLEXTOPO in four controlled units is designed to interpret spatial variability of rainfall patterns and topographic features. Through pairwise comparison, our results suggest that: (1) semi-distributed models (FLEXD and FLEXTOPOD) taking precipitation spatial heterogeneity into account has improved model performance with parsimonious parameter set, and (2) hydrologic model architecture with flexibility to reflect perceived dominant hydrologic processes can include the local terrain circumstances for each landscape. Hence, the modeling actions are coincided with the catchment behaviour and close to the "reality". The presented methodology is regarding hydrologic model as a tool to test our hypothesis and deepen our understanding of hydrologic processes, which will be helpful to improve modeling realism.

Hydrological system dynamics of glaciated Karnali River Basin Nepal Himalaya using J2000 Hydrological model

NASA Astrophysics Data System (ADS)

Khatiwada, K. R.; Nepal, S.; Panthi, J., Sr.; Shrestha, M.

2015-12-01

Hydrological modelling plays an important role in understanding hydrological processes of a catchment. In the context of climate change, the understanding of hydrological characteristic of the catchment is very vital to understand how the climate change will affect the hydrological regime. This research facilitates in better understanding of the hydrological system dynamics of a himalayan mountainous catchment in western Nepal. The Karnali River, longest river flowing inside Nepal, is one of the three major basins of Nepal, having the area of 45269 sq. km. is unique. The basin has steep topography and high mountains to the northern side. The 40% of the basin is dominated by forest land while other land cover are: grass land, bare rocky land etc. About 2% of the areas in basin is covered by permanent glacier apart from that about 12% of basin has the snow and ice cover. There are 34 meteorological stations distributed across the basin. A process oriented distributed J2000 hydrologial model has been applied to understand the hydrological system dynamics. The model application provides distributed output of various hydrological components. The J2000 model applies Hydrological Response Unit (HRU) as a modelling entity. With 6861 HRU and 1010 reaches, the model was calibrated (1981-1999) and validated (2000-2004) at a daily scale using split-sample test. The model is able to capture the overall hydrological dynamics well. The rising limbs and recession limbs are simulated equally and with satisfactory ground water conditions. Based on the graphical and statistical evaluation of the model performance the model is able to simulate hydrological processes fairly well. Calibration shows that Nash Sutcliffe efficiency is 0.91, coefficient of determination is 0.92 Initial observation shows that during the pre-monsoon season(March to May) the glacial runoff is 25% of the total discharge while in the monsoon(June to September) season it is only 13%. The surface runoff contributed about 40%, 20% in subsurface while there is about 13% in the base flow. For better understanding and interpretation of the area there is still need of further coherent research and analysis for land use change and future climate change impact in the glaciered alpine catchment of Himalayan region.

Hydrological modeling in forested systems

Treesearch

H.E. Golden; G.R. Evenson; S. Tian; Devendra Amatya; Ge Sun

2015-01-01

Characterizing and quantifying interactions among components of the forest hydrological cycle is complex and usually requires a combination of field monitoring and modelling approaches (Weiler and McDonnell, 2004; National Research Council, 2008). Models are important tools for testing hypotheses, understanding hydrological processes and synthesizing experimental data...

Snow hydrology in a general circulation model

NASA Technical Reports Server (NTRS)

Marshall, Susan; Roads, John O.; Glatzmaier, Gary

1994-01-01

A snow hydrology has been implemented in an atmospheric general circulation model (GCM). The snow hydrology consists of parameterizations of snowfall and snow cover fraction, a prognostic calculation of snow temperature, and a model of the snow mass and hydrologic budgets. Previously, only snow albedo had been included by a specified snow line. A 3-year GCM simulation with this now more complete surface hydrology is compared to a previous GCM control run with the specified snow line, as well as with observations. In particular, the authors discuss comparisons of the atmospheric and surface hydrologic budgets and the surface energy budget for U.S. and Canadian areas. The new snow hydrology changes the annual cycle of the surface moisture and energy budgets in the model. There is a noticeable shift in the runoff maximum from winter in the control run to spring in the snow hydrology run. A substantial amount of GCM winter precipitation is now stored in the seasonal snowpack. Snow cover also acts as an important insulating layer between the atmosphere and the ground. Wintertime soil temperatures are much higher in the snow hydrology experiment than in the control experiment. Seasonal snow cover is important for dampening large fluctuations in GCM continental skin temperature during the Northern Hemisphere winter. Snow depths and snow extent show good agreement with observations over North America. The geographic distribution of maximum depths is not as well simulated by the model due, in part, to the coarse resolution of the model. The patterns of runoff are qualitatively and quantitatively similar to observed patterns of streamflow averaged over the continental United States. The seasonal cycles of precipitation and evaporation are also reasonably well simulated by the model, although their magnitudes are larger than is observed. This is due, in part, to a cold bias in this model, which results in a dry model atmosphere and enhances the hydrologic cycle everywhere.

Five Guidelines for Selecting Hydrological Signatures

NASA Astrophysics Data System (ADS)

McMillan, H. K.; Westerberg, I.; Branger, F.

2017-12-01

Hydrological signatures are index values derived from observed or modeled series of hydrological data such as rainfall, flow or soil moisture. They are designed to extract relevant information about hydrological behavior, such as to identify dominant processes, and to determine the strength, speed and spatiotemporal variability of the rainfall-runoff response. Hydrological signatures play an important role in model evaluation. They allow us to test whether particular model structures or parameter sets accurately reproduce the runoff generation processes within the watershed of interest. Most modeling studies use a selection of different signatures to capture different aspects of the catchment response, for example evaluating overall flow distribution as well as high and low flow extremes and flow timing. Such studies often choose their own set of signatures, or may borrow subsets of signatures used in multiple other works. The link between signature values and hydrological processes is not always straightforward, leading to uncertainty and variability in hydrologists' signature choices. In this presentation, we aim to encourage a more rigorous approach to hydrological signature selection, which considers the ability of signatures to represent hydrological behavior and underlying processes for the catchment and application in question. To this end, we propose a set of guidelines for selecting hydrological signatures. We describe five criteria that any hydrological signature should conform to: Identifiability, Robustness, Consistency, Representativeness, and Discriminatory Power. We describe an example of the design process for a signature, assessing possible signature designs against the guidelines above. Due to their ubiquity, we chose a signature related to the Flow Duration Curve, selecting the FDC mid-section slope as a proposed signature to quantify catchment overall behavior and flashiness. We demonstrate how assessment against each guideline could be used to compare or choose between alternative signature definitions. We believe that reaching a consensus on selection criteria for hydrological signatures will assist modelers to choose between competing signatures, facilitate comparison between hydrological studies, and help hydrologists to fully evaluate their models.

Testing the Structure of Hydrological Models using Genetic Programming

NASA Astrophysics Data System (ADS)

Selle, B.; Muttil, N.

2009-04-01

Genetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that genetic programming can be used to test the structure hydrological models and to identify dominant processes in hydrological systems. To test this, genetic programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, water table depths and water ponding times during surface irrigation. Using genetic programming, a simple model of deep percolation was consistently evolved in multiple model runs. This simple and interpretable model confirmed the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that genetic programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

On the importance of methods in hydrological modelling. Perspectives from a case study

NASA Astrophysics Data System (ADS)

Fenicia, Fabrizio; Kavetski, Dmitri

2017-04-01

The hydrological community generally appreciates that developing any non-trivial hydrological model requires a multitude of modelling choices. These choices may range from a (seemingly) straightforward application of mass conservation, to the (often) guesswork-like selection of constitutive functions, parameter values, etc. The application of a model itself requires a myriad of methodological choices - the selection of numerical solvers, objective functions for model calibration, validation approaches, performance metrics, etc. Not unreasonably, hydrologists embarking on ever ambitious projects prioritize hydrological insight over the morass of methodological choices. Perhaps to emphasize "ideas" over "methods", some journals have even reduced the fontsize of the methodology sections of its articles. However, the very nature of modelling is that seemingly routine methodological choices can significantly affect the conclusions of case studies and investigations - making it dangerous to skimp over methodological details in an enthusiastic rush towards the next great hydrological idea. This talk shares modelling insights from a hydrological study of a 300 km2 catchment in Luxembourg, where the diversity of hydrograph dynamics observed at 10 locations begs the question of whether external forcings or internal catchment properties act as dominant controls on streamflow generation. The hydrological insights are fascinating (at least to us), but in this talk we emphasize the impact of modelling methodology on case study conclusions and recommendations. How did we construct our prior set of hydrological model hypotheses? What numerical solver was implemented and why was an objective function based on Bayesian theory deployed? And what would have happened had we omitted model cross-validation, or not used a systematic hypothesis testing approach?

An ensemble approach to assess hydrological models' contribution to uncertainties in the analysis of climate change impact on water resources

NASA Astrophysics Data System (ADS)

Velázquez, J. A.; Schmid, J.; Ricard, S.; Muerth, M. J.; Gauvin St-Denis, B.; Minville, M.; Chaumont, D.; Caya, D.; Ludwig, R.; Turcotte, R.

2012-06-01

Over the recent years, several research efforts investigated the impact of climate change on water resources for different regions of the world. The projection of future river flows is affected by different sources of uncertainty in the hydro-climatic modelling chain. One of the aims of the QBic3 project (Québec-Bavarian International Collaboration on Climate Change) is to assess the contribution to uncertainty of hydrological models by using an ensemble of hydrological models presenting a diversity of structural complexity (i.e. lumped, semi distributed and distributed models). The study investigates two humid, mid-latitude catchments with natural flow conditions; one located in Southern Québec (Canada) and one in Southern Bavaria (Germany). Daily flow is simulated with four different hydrological models, forced by outputs from regional climate models driven by a given number of GCMs' members over a reference (1971-2000) and a future (2041-2070) periods. The results show that the choice of the hydrological model does strongly affect the climate change response of selected hydrological indicators, especially those related to low flows. Indicators related to high flows seem less sensitive on the choice of the hydrological model. Therefore, the computationally less demanding models (usually simple, lumped and conceptual) give a significant level of trust for high and overall mean flows.

Some thoughts on building, evaluating and constraining hydrologic models from catchment to continental scales

NASA Astrophysics Data System (ADS)

Wagener, Thorsten

2017-04-01

We increasingly build and apply hydrologic models that simulate systems beyond the catchment scale. Such models run at regional, national or even continental scales. They therefore offer opportunities for new scientific insights, for example by enabling comparative hydrology or connectivity studies, and for water management, where we might better understand changes to water resources from larger scale activities like agriculture or from hazards such as droughts. However, these models also require us to rethink how we build and evaluate them given that some of the unsolved problems from the catchment scale have not gone away. So what role should such models play in scientific advancement in hydrology? What problems do we still have to resolve before they can fulfill their role? What opportunities for solving these problems are there, but have not yet been utilized? I will provide some thoughts on these issues in the context of the IAHS Panta Rhei initiative and the scientific challenges it has set out for hydrology (Montanari et al., 2013, Hydrological Sciences Journal; McMillan et al., 2016, Hydrological Sciences Journal).

Choices Matter, but How Do We Model Them?

NASA Astrophysics Data System (ADS)

Brelsford, C.; Dumas, M.

2017-12-01

Quantifying interactions between social systems and the physical environment we live within has long been a major scientific challenge. Humans have had such a large influence on our environment that it is no longer reasonable to consider the behavior of an ecological or hydrological system from a purely `physical' perspective: imagining a system that excludes the influence of human choices and behavior. Understanding the role that human social choices play in the energy water nexus is crucial for developing accurate models in that space. The relatively new field of socio-hydrology is making progress towards understanding the role humans play in hydrological systems. While this fact is now widely recognized across the many academic fields that study water systems, we have yet to develop a coherent set of theories for how to model the behavior of these complex and highly interdependent socio-hydrological systems. How should we conceptualize hydrological systems as socio-ecological systems (i.e. system with variables, states, parameters, actors who can control certain variables and a sense of the desirability of states) within which the rigorous study of feedbacks becomes possible? This talk reviews the state of knowledge of how social decisions around water consumption, allocation, and transport influence and are influenced by the physical hydrology that water also moves within. We cover recent papers in socio-hydrology, engineering, water law, and institutional analysis. There have been several calls within socio-hydrology to model human social behavior endogenously along with the hydrology. These improvements are needed across a range of spatial and temporal scales. We suggest two potential strategies for coupled models that allow endogenous water consumption behavior: a social first model which looks for empirical relationships between water consumption and allocation choices and the hydrological state, and a hydrology first model in which we look for regularities in how water regimes influence behavior, regional economies, or allocation institutions.

Internal Catchment Process Simulation in a Snow-Dominated Basin: Performance Evaluation with Spatiotemporally Variable Runoff Generation and Groundwater Dynamics

NASA Astrophysics Data System (ADS)

Kuras, P. K.; Weiler, M.; Alila, Y.; Spittlehouse, D.; Winkler, R.

2006-12-01

Hydrologic models have been increasingly used in forest hydrology to overcome the limitations of paired watershed experiments, where vegetative recovery and natural variability obscure the inferences and conclusions that can be drawn from such studies. Models, however, are also plagued by uncertainty stemming from a limited understanding of hydrological processes in forested catchments and parameter equifinality is a common concern. This has created the necessity to improve our understanding of how hydrological systems work, through the development of hydrological measures, analyses and models that address the question: are we getting the right answers for the right reasons? Hence, physically-based, spatially-distributed hydrologic models should be validated with high-quality experimental data describing multiple concurrent internal catchment processes under a range of hydrologic regimes. The distributed hydrology soil vegetation model (DHSVM) frequently used in forest management applications is an example of a process-based model used to address the aforementioned circumstances, and this study takes a novel approach at collectively examining the ability of a pre-calibrated model application to realistically simulate outlet flows along with the spatial-temporal variation of internal catchment processes including: continuous groundwater dynamics at 9 locations, stream and road network flow at 67 locations for six individual days throughout the freshet, and pre-melt season snow distribution. Model efficiency was improved over prior evaluations due to continuous efforts in improving the quality of meteorological data in the watershed. Road and stream network flows were very well simulated for a range of hydrological conditions, and the spatial distribution of the pre-melt season snowpack was in general agreement with observed values. The model was effective in simulating the spatial variability of subsurface flow generation, except at locations where strong stream-groundwater interactions existed, as the model is not capable of simulating such processes and subsurface flows always drain to the stream network. The model has proven overall to be quite capable in realistically simulating internal catchment processes in the watershed, which creates more confidence in future model applications exploring the effects of various forest management scenarios on the watershed's hydrological processes.

Correcting Inadequate Model Snow Process Descriptions Dramatically Improves Mountain Hydrology Simulations

NASA Astrophysics Data System (ADS)

Pomeroy, J. W.; Fang, X.

2014-12-01

The vast effort in hydrology devoted to parameter calibration as a means to improve model performance assumes that the models concerned are not fundamentally wrong. By focussing on finding optimal parameter sets and ascribing poor model performance to parameter or data uncertainty, these efforts may fail to consider the need to improve models with more intelligent descriptions of hydrological processes. To test this hypothesis, a flexible physically based hydrological model including a full suite of snow hydrology processes as well as warm season, hillslope and groundwater hydrology was applied to Marmot Creek Research Basin, Canadian Rocky Mountains where excellent driving meteorology and basin biophysical descriptions exist. Model parameters were set from values found in the basin or from similar environments; no parameters were calibrated. The model was tested against snow surveys and streamflow observations. The model used algorithms that describe snow redistribution, sublimation and forest canopy effects on snowmelt and evaporative processes that are rarely implemented in hydrological models. To investigate the contribution of these processes to model predictive capability, the model was "falsified" by deleting parameterisations for forest canopy snow mass and energy, blowing snow, intercepted rain evaporation, and sublimation. Model falsification by ignoring forest canopy processes contributed to a large increase in SWE errors for forested portions of the research basin with RMSE increasing from 19 to 55 mm and mean bias (MB) increasing from 0.004 to 0.62. In the alpine tundra portion, removing blowing processes resulted in an increase in model SWE MB from 0.04 to 2.55 on north-facing slopes and -0.006 to -0.48 on south-facing slopes. Eliminating these algorithms degraded streamflow prediction with the Nash Sutcliffe efficiency dropping from 0.58 to 0.22 and MB increasing from 0.01 to 0.09. These results show dramatic model improvements by including snow redistribution and melt processes associated with wind transport and forest canopies. As most hydrological models do not currently include these processes, it is suggested that modellers first improve the realism of model structures before trying to optimise what are inherently inadequate simulations of hydrology.

Hydrologic characteristics of freshwater mussel habitat: novel insights from modeled flows

USGS Publications Warehouse

Drew, C. Ashton; Eddy, Michele; Kwak, Thomas J.; Cope, W. Gregory; Augspurger, Tom

2018-01-01

The ability to model freshwater stream habitat and species distributions is limited by the spatially sparse flow data available from long-term gauging stations. Flow data beyond the immediate vicinity of gauging stations would enhance our ability to explore and characterize hydrologic habitat suitability. The southeastern USA supports high aquatic biodiversity, but threats, such as landuse alteration, climate change, conflicting water-resource demands, and pollution, have led to the imperilment and legal protection of many species. The ability to distinguish suitable from unsuitable habitat conditions, including hydrologic suitability, is a key criterion for successful conservation and restoration of aquatic species. We used the example of the critically endangered Tar River Spinymussel (Parvaspina steinstansana) and associated species to demonstrate the value of modeled flow data (WaterFALL™) to generate novel insights into population structure and testable hypotheses regarding hydrologic suitability. With ordination models, we: 1) identified all catchments with potentially suitable hydrology, 2) identified 2 distinct hydrologic environments occupied by the Tar River Spinymussel, and 3) estimated greater hydrological habitat niche breadth of assumed surrogate species associates at the catchment scale. Our findings provide the first demonstrated application of complete, continuous, regional modeled hydrologic data to freshwater mussel distribution and management. This research highlights the utility of modeling and data-mining methods to facilitate further exploration and application of such modeled environmental conditions to inform aquatic species management. We conclude that such an approach can support landscape-scale management decisions that require spatial information at fine resolution (e.g., enhanced National Hydrology Dataset catchments) and broad extent (e.g., multiple river basins).

Simulated discharge trends indicate robustness of hydrological models in a changing climate

NASA Astrophysics Data System (ADS)

Addor, Nans; Nikolova, Silviya; Seibert, Jan

2016-04-01

Assessing the robustness of hydrological models under contrasted climatic conditions should be part any hydrological model evaluation. Robust models are particularly important for climate impact studies, as models performing well under current conditions are not necessarily capable of correctly simulating hydrological perturbations caused by climate change. A pressing issue is the usually assumed stationarity of parameter values over time. Modeling experiments using conceptual hydrological models revealed that assuming transposability of parameters values in changing climatic conditions can lead to significant biases in discharge simulations. This raises the question whether parameter values should to be modified over time to reflect changes in hydrological processes induced by climate change. Such a question denotes a focus on the contribution of internal processes (i.e., catchment processes) to discharge generation. Here we adopt a different perspective and explore the contribution of external forcing (i.e., changes in precipitation and temperature) to changes in discharge. We argue that in a robust hydrological model, discharge variability should be induced by changes in the boundary conditions, and not by changes in parameter values. In this study, we explore how well the conceptual hydrological model HBV captures transient changes in hydrological signatures over the period 1970-2009. Our analysis focuses on research catchments in Switzerland undisturbed by human activities. The precipitation and temperature forcing are extracted from recently released 2km gridded data sets. We use a genetic algorithm to calibrate HBV for the whole 40-year period and for the eight successive 5-year periods to assess eventual trends in parameter values. Model calibration is run multiple times to account for parameter uncertainty. We find that in alpine catchments showing a significant increase of winter discharge, this trend can be captured reasonably well with constant parameter values over the whole reference period. Further, preliminary results suggest that some trends in parameter values do not reflect changes in hydrological processes, as reported by others previously, but instead might stem from a modeling artifact related to the parameterization of evapotranspiration, which is overly sensitive to temperature increase. We adopt a trading-space-for-time approach to better understand whether robust relationships between parameter values and forcing can be established, and to critically explore the rationale behind time-dependent parameter values in conceptual hydrological models.

Publishing and sharing of hydrologic models through WaterHUB

NASA Astrophysics Data System (ADS)

Merwade, V.; Ruddell, B. L.; Song, C.; Zhao, L.; Kim, J.; Assi, A.

2011-12-01

Most hydrologists use hydrologic models to simulate the hydrologic processes to understand hydrologic pathways and fluxes for research, decision making and engineering design. Once these tasks are complete including publication of results, the models generally are not published or made available to the public for further use and improvement. Although publication or sharing of models is not required for journal publications, sharing of models may open doors for new collaborations, and avoids duplication of efforts if other researchers are interested in simulating a particular watershed for which a model already exists. For researchers, who are interested in sharing models, there are limited avenues to publishing their models to the wider community. Towards filling this gap, a prototype cyberinfrastructure (CI), called WaterHUB, is developed for sharing hydrologic data and modeling tools in an interactive environment. To test the utility of WaterHUB for sharing hydrologic models, a system to publish and share SWAT (Soil Water Assessment Tool) is developed. Users can utilize WaterHUB to search and download existing SWAT models, and also upload new SWAT models. Metadata such as the name of the watershed, name of the person or agency who developed the model, simulation period, time step, and list of calibrated parameters also published with individual model.

Event-based hydrological modeling for detecting dominant hydrological process and suitable model strategy for semi-arid catchments

NASA Astrophysics Data System (ADS)

Huang, Pengnian; Li, Zhijia; Chen, Ji; Li, Qiaoling; Yao, Cheng

2016-11-01

To simulate the hydrological processes in semi-arid areas properly is still challenging. This study assesses the impact of different modeling strategies on simulating flood processes in semi-arid catchments. Four classic hydrological models, TOPMODEL, XINANJIANG (XAJ), SAC-SMA and TANK, were selected and applied to three semi-arid catchments in North China. Based on analysis and comparison of the simulation results of these classic models, four new flexible models were constructed and used to further investigate the suitability of various modeling strategies for semi-arid environments. Numerical experiments were also designed to examine the performances of the models. The results show that in semi-arid catchments a suitable model needs to include at least one nonlinear component to simulate the main process of surface runoff generation. If there are more than two nonlinear components in the hydrological model, they should be arranged in parallel, rather than in series. In addition, the results show that the parallel nonlinear components should be combined by multiplication rather than addition. Moreover, this study reveals that the key hydrological process over semi-arid catchments is the infiltration excess surface runoff, a non-linear component.

From micro-scale 3D simulations to macro-scale model of periodic porous media

NASA Astrophysics Data System (ADS)

Crevacore, Eleonora; Tosco, Tiziana; Marchisio, Daniele; Sethi, Rajandrea; Messina, Francesca

2015-04-01

In environmental engineering, the transport of colloidal suspensions in porous media is studied to understand the fate of potentially harmful nano-particles and to design new remediation technologies. In this perspective, averaging techniques applied to micro-scale numerical simulations are a powerful tool to extrapolate accurate macro-scale models. Choosing two simplified packing configurations of soil grains and starting from a single elementary cell (module), it is possible to take advantage of the periodicity of the structures to reduce the computation costs of full 3D simulations. Steady-state flow simulations for incompressible fluid in laminar regime are implemented. Transport simulations are based on the pore-scale advection-diffusion equation, that can be enriched introducing also the Stokes velocity (to consider the gravity effect) and the interception mechanism. Simulations are carried on a domain composed of several elementary modules, that serve as control volumes in a finite volume method for the macro-scale method. The periodicity of the medium involves the periodicity of the flow field and this will be of great importance during the up-scaling procedure, allowing relevant simplifications. Micro-scale numerical data are treated in order to compute the mean concentration (volume and area averages) and fluxes on each module. The simulation results are used to compare the micro-scale averaged equation to the integral form of the macroscopic one, making a distinction between those terms that could be computed exactly and those for which a closure in needed. Of particular interest it is the investigation of the origin of macro-scale terms such as the dispersion and tortuosity, trying to describe them with micro-scale known quantities. Traditionally, to study the colloidal transport many simplifications are introduced, such those concerning ultra-simplified geometry that usually account for a single collector. Gradual removal of such hypothesis leads to a detailed description of colloidal transport mechanisms. Starting from nearly realistic 3D geometries, the ultimate purpose of this work is that of develop an improved understanding of the fate of colloidal particles through, for example, an accurate description of the deposition efficiency, in order design efficient remediation techniques. G. Boccardo, D.L. Marchisio, R.Sethi, Journal of colloid and interface science, Vol 417C, pp 227-237, 2014 M. Icardi, G. Boccardo, D.L. Marchisio, T. Tosco, R.Sethi, Physical Review E - Statistical, Nonlinear, and Soft Matter Physics, 2014 S. Torkzaban, S.S. Tazehkand, S.L. Walker, S.A. Bradford, Water resources research, Vol 44, 2008 S.M. Hassanizadeh, Adv in Water Resources, Vol. 2, pp 131-144, 1979 S. Whitaker, AIChE Journal, Vol. 13 No. 3, pp 420-428, May 1967

HYDROLOGIC MODEL UNCERTAINTY ASSOCIATED WITH SIMULATING FUTURE LAND-COVER/USE SCENARIOS: A RETROSPECTIVE ANALYSIS

EPA Science Inventory

GIS-based hydrologic modeling offers a convenient means of assessing the impacts associated with land-cover/use change for environmental planning efforts. Alternative future scenarios can be used as input to hydrologic models and compared with existing conditions to evaluate pot...

Integration of remote sensing and hydrologic modeling through multi-disciplinary semiarid field campaigns: Moonsoon 1990, Walnut Gulch 1992, and SALSA-MEX

NASA Technical Reports Server (NTRS)

Moran, M. S.; Goodrich, D. C.; Kustas, W. P.

1994-01-01

A research and modeling strategy is presented for development of distributed hydrologic models given by a combination of remotely sensed and ground based data. In support of this strategy, two experiments Moonsoon'90 and Walnut Gulch'92 were conducted in a semiarid rangeland southeast of Tucson, Arizona, (U.S.) and a third experiment, the SALSA-MEX (Semi Arid Land Surface Atmospheric Mountain Experiment) was proposed. Results from the Moonsoon'90 experiment substantially advanced the understanding of the hydrologic and atmospheric fluxes in an arid environment and provided insight into the use of remote sensing data for hydrologic modeling. The Walnut Gulch'92 experiment addressed the seasonal hydrologic dynamics of the region and the potential of combined optical microwave remote sensing for hydrologic applications. SALSA-MEX will combine measurements and modeling to study hydrologic processes influenced by surrounding mountains, such as enhanced precipitation, snowmelt and recharge to ground water aquifers. The results from these experiments, along with the extensive experimental data bases, should aid the research community in large scale modeling of mass and energy exchanges across the soil-plant-atmosphere interface.

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.

Simulating Fire Disturbance and Plant Mortality Using Antecedent Eco-hydrological Conditions to Inform a Physically Based Combustion Model

NASA Astrophysics Data System (ADS)

Atchley, A. L.; Linn, R.; Middleton, R. S.; Runde, I.; Coon, E.; Michaletz, S. T.

2016-12-01

Wildfire is a complex agent of change that both affects and depends on eco-hydrological systems, thereby constituting a tightly linked system of disturbances and eco-hydrological conditions. For example, structure, build-up, and moisture content of fuel are dependent on eco-hydrological regimes, which impacts fire spread and intensity. Fire behavior, on the other hand, determines the severity and extent of eco-hydrological disturbance, often resulting in a mosaic of untouched, stressed, damaged, or completely destroyed vegetation within the fire perimeter. This in turn drives new eco-hydrological system behavior. The cycles of disturbance and recovery present a complex evolving system with many unknowns especially in the face of climate change that has implications for fire risk, water supply, and forest composition. Physically-based numerical experiments that attempt to capture the complex linkages between eco-hydrological regimes that affect fire behavior and the echo-hydrological response from those fire disturbances help build the understanding required to project how fire disturbance and eco-hydrological conditions coevolve over time. Here we explore the use of FIRETEC—a physically-based 3D combustion model that solves conservation of mass, momentum, energy, and chemical species—to resolve fire spread over complex terrain and fuel structures. Uniquely, we couple a physically-based plant mortality model with FIRETEC and examine the resultant hydrologic impact. In this proof of concept demonstration we spatially distribute fuel structure and moisture content based on the eco-hydrological condition to use as input for FIRETEC. The fire behavior simulation then produces localized burn severity and heat injures which are used as input to a spatially-informed plant mortality model. Ultimately we demonstrate the applicability of physically-based models to explore integrated disturbance and eco-hydrologic response to wildfire behavior and specifically map how fire spread and intensity is affect by the antecedent eco-hydrological condition, which then affects the resulting tree mortality patterns.

Quantifying Direct and Indirect Impact of Future Climate on Sub-Arctic Hydrology

NASA Astrophysics Data System (ADS)

Endalamaw, A. M.; Bolton, W. R.; Young-Robertson, J. M.; Morton, D.; Hinzman, L. D.

2016-12-01

Projected future climate will have a significant impact on the hydrology of interior Alaskan sub-arctic watersheds, directly though the changes in precipitation and temperature patterns, and indirectly through the cryospheric and ecological impacts. Although the latter is the dominant factor controlling the hydrological processes in the interior Alaska sub-arctic, it is often overlooked in many climate change impact studies. In this study, we aim to quantify and compare the direct and indirect impact of the projected future climate on the hydrology of the interior Alaskan sub-arctic watersheds. The Variable Infiltration Capacity (VIC) meso-scale hydrological model will be implemented to simulate the hydrological processes, including runoff, evapotranspiration, and soil moisture dynamics in the Chena River Basin (area = 5400km2), located in the interior Alaska sub-arctic region. Permafrost and vegetation distribution will be derived from the Geophysical Institute Permafrost Lab (GIPL) model and the Lund-Potsdam-Jena Dynamic Global Model (LPJ) model, respectively. All models will be calibrated and validated using historical data. The Scenario Network for Alaskan and Arctic Planning (SNAP) 5-model average projected climate data products will be used as forcing data for each of these models. The direct impact of climate change on hydrology is estimated using surface parameterization derived from the present day permafrost and vegetation distribution, and future climate forcing from SNAP projected climate data products. Along with the projected future climate, outputs of GIPL and LPJ will be incorporated into the VIC model to estimate the indirect and overall impact of future climate on the hydrology processes in the interior Alaskan sub-arctic watersheds. Finally, we will present the potential hydrological and ecological changes by the end of the 21st century.

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.

Multi-scale finite element model of growth plate damage during the development of slipped capital femoral epiphysis.

PubMed

Farzaneh, S; Paseta, O; Gómez-Benito, M J

2015-04-01

Slipped capital femoral epiphysis (SCFE) is one of the most common disorders of adolescent hips. A number of works have related the development of SCFE to mechanical factors. Due to the difficulty of diagnosing SCFE in its early stages, the disorder often progresses over time, resulting in serious side effects. Therefore, the development of a tool to predict the initiation of damage in the growth plate is needed. Because the growth plate is a heterogeneous structure, to develop a precise and reliable model, it is necessary to consider this structure from both macro- and microscale perspectives. Thus, the main objective of this work is to develop a numerical multi-scale model that links damage occurring at the microscale to damage occurring at the macroscale. The use of this model enables us to predict which regions of the growth plate are at high risk of damage. First, we have independently analyzed the microscale to simulate the microstructure under shear and tensile tests to calibrate the damage model. Second, we have employed the model to simulate damage occurring in standardized healthy and affected femurs during the heel-strike stage of stair climbing. Our results indicate that on the macroscale, damage is concentrated in the medial region of the growth plate in both healthy and affected femurs. Furthermore, damage to the affected femur is greater than damage to the healthy femur from both the micro- and macrostandpoints. Maximal damage is observed in territorial matrices. Furthermore, simulations illustrate that little damage occurs in the reserve zone. These findings are consistent with previous findings reported in well-known experimental works.

Optimizing Discharge Capacity of Li-O 2 Batteries by Design of Air-Electrode Porous Structure: Multifidelity Modeling and Optimization

DOE PAGES

Pan, Wenxiao; Yang, Xiu; Bao, Jie; ...

2017-01-01

We develop a new mathematical framework to study the optimal design of air electrode microstructures for lithium-oxygen (Li-O2) batteries. It can eectively reduce the number of expensive experiments for testing dierent air-electrodes, thereby minimizing the cost in the design of Li-O2 batteries. The design parameters to characterize an air-electrode microstructure include the porosity, surface-to-volume ratio, and parameters associated with the pore-size distribution. A surrogate model (also known as response surface) for discharge capacity is rst constructed as a function of these design parameters. The surrogate model is accurate and easy to evaluate such that an optimization can be performed basedmore » on it. In particular, a Gaussian process regression method, co-kriging, is employed due to its accuracy and eciency in predicting high-dimensional responses from a combination of multidelity data. Specically, a small amount of data from high-delity simulations are combined with a large number of data obtained from computationally ecient low-delity simulations. The high-delity simulation is based on a multiscale modeling approach that couples the microscale (pore-scale) and macroscale (device-scale) models. Whereas, the low-delity simulation is based on an empirical macroscale model. The constructed response surface provides quantitative understanding and prediction about how air electrode microstructures aect the discharge performance of Li-O2 batteries. The succeeding sensitivity analysis via Sobol indices and optimization via genetic algorithm ultimately oer a reliable guidance on the optimal design of air electrode microstructures. The proposed mathematical framework can be generalized to investigate other new energy storage techniques and materials.« less

Optimizing Discharge Capacity of Li-O 2 Batteries by Design of Air-Electrode Porous Structure: Multifidelity Modeling and Optimization

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

Pan, Wenxiao; Yang, Xiu; Bao, Jie

We develop a new mathematical framework to study the optimal design of air electrode microstructures for lithium-oxygen (Li-O2) batteries. It can eectively reduce the number of expensive experiments for testing dierent air-electrodes, thereby minimizing the cost in the design of Li-O2 batteries. The design parameters to characterize an air-electrode microstructure include the porosity, surface-to-volume ratio, and parameters associated with the pore-size distribution. A surrogate model (also known as response surface) for discharge capacity is rst constructed as a function of these design parameters. The surrogate model is accurate and easy to evaluate such that an optimization can be performed basedmore » on it. In particular, a Gaussian process regression method, co-kriging, is employed due to its accuracy and eciency in predicting high-dimensional responses from a combination of multidelity data. Specically, a small amount of data from high-delity simulations are combined with a large number of data obtained from computationally ecient low-delity simulations. The high-delity simulation is based on a multiscale modeling approach that couples the microscale (pore-scale) and macroscale (device-scale) models. Whereas, the low-delity simulation is based on an empirical macroscale model. The constructed response surface provides quantitative understanding and prediction about how air electrode microstructures aect the discharge performance of Li-O2 batteries. The succeeding sensitivity analysis via Sobol indices and optimization via genetic algorithm ultimately oer a reliable guidance on the optimal design of air electrode microstructures. The proposed mathematical framework can be generalized to investigate other new energy storage techniques and materials.« less

Diagnosing hydrological limitations of a Land Surface Model: application of JULES to a deep-groundwater chalk basin

NASA Astrophysics Data System (ADS)

Le Vine, N.; Butler, A.; McIntyre, N.; Jackson, C.

2015-08-01

Land Surface Models (LSMs) are prospective starting points to develop a global hyper-resolution model of the terrestrial water, energy and biogeochemical cycles. However, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. A diagnostic approach to model evaluation is taken here that exploits hydrological expert knowledge to detect LSM inadequacies through consideration of the major behavioural functions of a hydrological system: overall water balance, vertical water redistribution in the unsaturated zone, temporal water redistribution and spatial water redistribution over the catchment's groundwater and surface water systems. Three types of information are utilised to improve the model's hydrology: (a) observations, (b) information about expected response from regionalised data, and (c) information from an independent physics-based model. The study considers the JULES (Joint UK Land Environmental Simulator) LSM applied to a deep-groundwater chalk catchment in the UK. The diagnosed hydrological limitations and the proposed ways to address them are indicative of the challenges faced while transitioning to a global high resolution model of the water cycle.

Diagnosing hydrological limitations of a land surface model: application of JULES to a deep-groundwater chalk basin

NASA Astrophysics Data System (ADS)

Le Vine, N.; Butler, A.; McIntyre, N.; Jackson, C.

2016-01-01

Land surface models (LSMs) are prospective starting points to develop a global hyper-resolution model of the terrestrial water, energy, and biogeochemical cycles. However, there are some fundamental limitations of LSMs related to how meaningfully hydrological fluxes and stores are represented. A diagnostic approach to model evaluation and improvement is taken here that exploits hydrological expert knowledge to detect LSM inadequacies through consideration of the major behavioural functions of a hydrological system: overall water balance, vertical water redistribution in the unsaturated zone, temporal water redistribution, and spatial water redistribution over the catchment's groundwater and surface-water systems. Three types of information are utilized to improve the model's hydrology: (a) observations, (b) information about expected response from regionalized data, and (c) information from an independent physics-based model. The study considers the JULES (Joint UK Land Environmental Simulator) LSM applied to a deep-groundwater chalk catchment in the UK. The diagnosed hydrological limitations and the proposed ways to address them are indicative of the challenges faced while transitioning to a global high resolution model of the water cycle.

Stream Discharge and Evapotranspiration Responses to Climate Change and Their Associated Uncertainties in a Large Semi-Arid Basin

NASA Astrophysics Data System (ADS)

Bassam, S.; Ren, J.

2017-12-01

Predicting future water availability in watersheds is very important for proper water resources management, especially in semi-arid regions with scarce water resources. Hydrological models have been considered as powerful tools in predicting future hydrological conditions in watershed systems in the past two decades. Streamflow and evapotranspiration are the two important components in watershed water balance estimation as the former is the most commonly-used indicator of the overall water budget estimation, and the latter is the second biggest component of water budget (biggest outflow from the system). One of the main concerns in watershed scale hydrological modeling is the uncertainties associated with model prediction, which could arise from errors in model parameters and input meteorological data, or errors in model representation of the physics of hydrological processes. Understanding and quantifying these uncertainties are vital to water resources managers for proper decision making based on model predictions. In this study, we evaluated the impacts of different climate change scenarios on the future stream discharge and evapotranspiration, and their associated uncertainties, throughout a large semi-arid basin using a stochastically-calibrated, physically-based, semi-distributed hydrological model. The results of this study could provide valuable insights in applying hydrological models in large scale watersheds, understanding the associated sensitivity and uncertainties in model parameters, and estimating the corresponding impacts on interested hydrological process variables under different climate change scenarios.

Development and testing of watershed-scale models for poorly drained soils

Treesearch

Glenn P. Fernandez; George M. Chescheir; R. Wayne Skaggs; Devendra M. Amatya

2005-01-01

Watershed-scale hydrology and water quality models were used to evaluate the crrmulative impacts of land use and management practices on dowrzstream hydrology and nitrogen loading of poorly drained watersheds. Field-scale hydrology and nutrient dyyrutmics are predicted by DRAINMOD in both models. In the first model (DRAINMOD-DUFLOW), field-scale predictions are coupled...

The application of remote sensing to the development and formulation of hydrologic planning models

NASA Technical Reports Server (NTRS)

Castruccio, P. A.; Loats, H. L., Jr.; Fowler, T. R.

1976-01-01

A hydrologic planning model is developed based on remotely sensed inputs. Data from LANDSAT 1 are used to supply the model's quantitative parameters and coefficients. The use of LANDSAT data as information input to all categories of hydrologic models requiring quantitative surface parameters for their effects functioning is also investigated.

Adequacy of satellite derived rainfall data for stream flow modeling

USGS Publications Warehouse

Artan, G.; Gadain, Hussein; Smith, Jodie; Asante, Kwasi; Bandaragoda, C.J.; Verdin, J.P.

2007-01-01

Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated. ?? Springer Science+Business Media, Inc. 2007.

The benefits of daily data and scale up issues in hydrologic models-SWAT and CRAFT

NASA Astrophysics Data System (ADS)

Huang, Yumei; Quinn, Paul; Liang, Qiuhua; Adams, Russell

2017-04-01

When modelling the flow pathways for nutrient transport, the lack of good data and limitation of data resolution become the key cause of low quality output in various hydrologic models. The scale of catchment being studied would present the main issues of the sensitivity and uncertainty expected on the hydrologic modelling. Equally, the time step chosen is also important to nutrient dynamics. This study aims to evaluate the benefits of using both monthly and daily data in hydrologic models, and to address the issues of catchment scale when using the two hydrologic models, the Soil and Water Assessment Tool (SWAT), and Catchment Runoff Attenuation Flux Tool (CRAFT), by comparing the difference between SWAT and CRAFT in flow pathways and sediment transport. The models are different in terms of complexity, therefore the poster will discuss the strengths and weakness of the models. Also we can show the problems of calibration and how the models can be used to support catchment modelling.

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. 2; Aggregation

NASA Technical Reports Server (NTRS)

Schamschula, Marius; Crosson, William L.; Inguva, Ramarao; Yates, Thomas; Laymen, Charles A.; Caulfield, John

1998-01-01

This is a follow up on the preceding presentation by Crosson. The grid size for remote microwave measurements is much coarser than the hydrological model computational grids. To validate the hydrological models with measurements we propose mechanisms to aggregate the hydrological model outputs for soil moisture to allow comparison with measurements. Weighted neighborhood averaging methods are proposed to facilitate the comparison. We will also discuss such complications as misalignment, rotation and other distortions introduced by a generalized sensor image.

Simultaneous Semi-Distributed Model Calibration Guided by ...

EPA Pesticide Factsheets

Modelling approaches to transfer hydrologically-relevant information from locations with streamflow measurements to locations without such measurements continues to be an active field of research for hydrologists. The Pacific Northwest Hydrologic Landscapes (PNW HL) provide a solid conceptual classification framework based on our understanding of dominant processes. A Hydrologic Landscape code (5 letter descriptor based on physical and climatic properties) describes each assessment unit area, and these units average area 60km2. The core function of these HL codes is to relate and transfer hydrologically meaningful information between watersheds without the need for streamflow time series. We present a novel approach based on the HL framework to answer the question “How can we calibrate models across separate watersheds simultaneously, guided by our understanding of dominant processes?“. We should be able to apply the same parameterizations to assessment units of common HL codes if 1) the Hydrologic Landscapes contain hydrologic information transferable between watersheds at a sub-watershed-scale and 2) we use a conceptual hydrologic model and parameters that reflect the hydrologic behavior of a watershed. In this study, This work specifically tests the ability or inability to use HL-codes to inform and share model parameters across watersheds in the Pacific Northwest. EPA’s Western Ecology Division has published and is refining a framework for defining la

A new fit-for-purpose model testing framework: Decision Crash Tests

NASA Astrophysics Data System (ADS)

Tolson, Bryan; Craig, James

2016-04-01

Decision-makers in water resources are often burdened with selecting appropriate multi-million dollar strategies to mitigate the impacts of climate or land use change. Unfortunately, the suitability of existing hydrologic simulation models to accurately inform decision-making is in doubt because the testing procedures used to evaluate model utility (i.e., model validation) are insufficient. For example, many authors have identified that a good standard framework for model testing called the Klemes Crash Tests (KCTs), which are the classic model validation procedures from Klemeš (1986) that Andréassian et al. (2009) rename as KCTs, have yet to become common practice in hydrology. Furthermore, Andréassian et al. (2009) claim that the progression of hydrological science requires widespread use of KCT and the development of new crash tests. Existing simulation (not forecasting) model testing procedures such as KCTs look backwards (checking for consistency between simulations and past observations) rather than forwards (explicitly assessing if the model is likely to support future decisions). We propose a fundamentally different, forward-looking, decision-oriented hydrologic model testing framework based upon the concept of fit-for-purpose model testing that we call Decision Crash Tests or DCTs. Key DCT elements are i) the model purpose (i.e., decision the model is meant to support) must be identified so that model outputs can be mapped to management decisions ii) the framework evaluates not just the selected hydrologic model but the entire suite of model-building decisions associated with model discretization, calibration etc. The framework is constructed to directly and quantitatively evaluate model suitability. The DCT framework is applied to a model building case study on the Grand River in Ontario, Canada. A hypothetical binary decision scenario is analysed (upgrade or not upgrade the existing flood control structure) under two different sets of model building decisions. In one case, we show the set of model building decisions has a low probability to correctly support the upgrade decision. In the other case, we show evidence suggesting another set of model building decisions has a high probability to correctly support the decision. The proposed DCT framework focuses on what model users typically care about: the management decision in question. The DCT framework will often be very strict and will produce easy to interpret results enabling clear unsuitability determinations. In the past, hydrologic modelling progress has necessarily meant new models and model building methods. Continued progress in hydrologic modelling requires finding clear evidence to motivate researchers to disregard unproductive models and methods and the DCT framework is built to produce this kind of evidence. References: Andréassian, V., C. Perrin, L. Berthet, N. Le Moine, J. Lerat, C. Loumagne, L. Oudin, T. Mathevet, M.-H. Ramos, and A. Valéry (2009), Crash tests for a standardized evaluation of hydrological models. Hydrology and Earth System Sciences, 13, 1757-1764. Klemeš, V. (1986), Operational testing of hydrological simulation models. Hydrological Sciences Journal, 31 (1), 13-24.

DRAINMOD-FOREST: Integrated modeling of hydrology, soil carbon and nitrogen dynamics, and plant growth for drained forests

Treesearch

Shiying Tian; Mohamed A. Youssef; R. Wayne Skaggs; Devendra M. Amatya; G.M. Chescheir

2012-01-01

We present a hybrid and stand-level forest ecosystem model, DRAINMOD-FOREST, for simulating the hydrology, carbon (C) and nitrogen (N) dynamics, and tree growth for drained forest lands under common silvicultural practices. The model was developed by linking DRAINMOD, the hydrological model, and DRAINMOD-N II, the soil C and N dynamics model, to a forest growth model,...

Teaching geographical hydrology in a non-stationary world

NASA Astrophysics Data System (ADS)

Hendriks, Martin R.; Karssenberg, Derek

2010-05-01

Understanding hydrological processes in a non-stationary world requires knowledge of hydrological processes and their interactions. Also, one needs to understand the (non-linear) relations between the hydrological system and other parts of our Earth system, such as the climate system, the socio-economic system, and the ecosystem. To provide this knowledge and understanding we think that three components are essential when teaching geographical hydrology. First of all, a student needs to acquire a thorough understanding of classical hydrology. For this, knowledge of the basic hydrological equations, such as the energy equation (Bernoulli), flow equation (Darcy), continuity (or water balance) equation is needed. This, however, is not sufficient to make a student fully understand the interactions between hydrological compartments, or between hydrological subsystems and other parts of the Earth system. Therefore, secondly, a student also needs to be knowledgeable of methods by which the different subsystems can be coupled; in general, numerical models are used for this. A major disadvantage of numerical models is their complexity. A solution may be to use simpler models, provided that a student really understands how hydrological processes function in our real, non-stationary world. The challenge for a student then lies in understanding the interactions between the subsystems, and to be able to answer questions such as: what is the effect of a change in vegetation or land use on runoff? Thirdly, knowledge of field hydrology is of utmost importance. For this a student needs to be trained in the field. Fieldwork is very important as a student is confronted in the field with spatial and temporal variability, as well as with real life uncertainties, rather than being lured into believing the world as presented in hydrological textbooks and models, e.g. the world under study is homogeneous, isotropic, or lumped (averaged). Also, students in the field learn to plan and cooperate. Besides fieldwork, a student should also learn to make use of the many available data sets, such as google earth, or as provided by remote sensing, or automatic data loggers. In our opinion the following sequence of activities should be applied for a student to attain a desirable working knowledge level. As mentioned earlier, a student first of all needs to have sufficient classical hydrological knowledge. After this a student should be educated in using simple models, in which field knowledge is incorporated. After this, a student should learn how to build models for solving typical hydrological problems. Modelling is especially worthwhile when the model is applied to a known area, as this certifies integration of fieldwork and modelling activities. To learn how to model, tailored courses with software that provides a set of easily learned functions to match the student's conceptual thought processes are needed. It is not easy to bring theoretical, field, and modelling knowledge together, and a pitfall may be the lack of knowledge of one or more of the above. Also, a student must learn to be able to deal with uncertainties in data and models, and must be trained to deal with unpredictability. Therefore, in our opinion a modern student should strive to become an integrating specialist in all of the above mentioned fields if we are to take geographical hydrology to a higher level and if we want to come to grips with it in a non-stationary world. A student must learn to think and act in an integrative way, and for this combining classical hydrology, field hydrology and modelling at a high education level in our hydrology curricula, in our opinion, is the way to proceed.

Watershed Modeling Applications with the Open-Access Modular Distributed Watershed Educational Toolbox (MOD-WET) and Introductory Hydrology Textbook

NASA Astrophysics Data System (ADS)

Huning, L. S.; Margulis, S. A.

2014-12-01

Traditionally, introductory hydrology courses focus on hydrologic processes as independent or semi-independent concepts that are ultimately integrated into a watershed model near the end of the term. When an "off-the-shelf" watershed model is introduced in the curriculum, this approach can result in a potential disconnect between process-based hydrology and the inherent interconnectivity of processes within the water cycle. In order to curb this and reduce the learning curve associated with applying hydrologic concepts to complex real-world problems, we developed the open-access Modular Distributed Watershed Educational Toolbox (MOD-WET). The user-friendly, MATLAB-based toolbox contains the same physical equations for hydrological processes (i.e. precipitation, snow, radiation, evaporation, unsaturated flow, infiltration, groundwater, and runoff) that are presented in the companion e-textbook (http://aqua.seas.ucla.edu/margulis_intro_to_hydro_textbook.html) and taught in the classroom. The modular toolbox functions can be used by students to study individual hydrologic processes. These functions are integrated together to form a simple spatially-distributed watershed model, which reinforces a holistic understanding of how hydrologic processes are interconnected and modeled. Therefore when watershed modeling is introduced, students are already familiar with the fundamental building blocks that have been unified in the MOD-WET model. Extensive effort has been placed on the development of a highly modular and well-documented code that can be run on a personal computer within the commonly-used MATLAB environment. MOD-WET was designed to: 1) increase the qualitative and quantitative understanding of hydrological processes at the basin-scale and demonstrate how they vary with watershed properties, 2) emphasize applications of hydrologic concepts rather than computer programming, 3) elucidate the underlying physical processes that can often be obscured with a complicated "off-the-shelf" watershed model in an introductory hydrology course, and 4) reduce the learning curve associated with analyzing meaningful real-world problems. The open-access MOD-WET and e-textbook have already been successfully incorporated within our undergraduate curriculum.

Hydrological Modeling in Alaska with WRF-Hydro

NASA Astrophysics Data System (ADS)

Elmer, N. J.; Zavodsky, B.; Molthan, A.

2017-12-01

The operational National Water Model (NWM), implemented in August 2016, is an instantiation of the Weather Research and Forecasting hydrological extension package (WRF-Hydro). Currently, the NWM only covers the contiguous United States, but will be expanded to include an Alaska domain in the future. It is well known that Alaska presents several hydrological modeling challenges, including unique arctic/sub-arctic hydrological processes not observed elsewhere in the United States and a severe lack of in-situ observations for model initialization. This project sets up an experimental version of WRF-Hydro in Alaska mimicking the NWM to gauge the ability of WRF-Hydro to represent hydrological processes in Alaska and identify model calibration challenges. Recent and upcoming launches of hydrology-focused NASA satellite missions such as the Soil Moisture Active Passive (SMAP) and Surface Water Ocean Topography (SWOT) expand the spatial and temporal coverage of observations in Alaska, so this study also lays the groundwork for assimilating these NASA datasets into WRF-Hydro in the future.

Teaching hydrological modelling as a subsidiary subject

NASA Astrophysics Data System (ADS)

Hörmann, G.; Schmalz, B.; Fohrer, N.

2009-04-01

The department of hydrology and water resources management is part of the Ecology Center of Kiel University, an interdisciplinary research organization. We teach hydrology for geographers, biologists, agricultural engineers and ecologists. Hydrological modeling is part of the curriculum since 1988. It has moved from the subject for specialists to a basic component of all hydrological courses. During the first year, we focussed on in-depth teaching of theory and practice of one big model, but the students found it hard to follow and beyond practical problems. During the last years we switched to a broader, but more shallow policy. Modeling is now part of nearly all courses, but remains limited to mostly 2-4 days of teaching. We now present only very basic theory and leave it to the students to discover the details during the practical work with pre-installed data sets. The poster shows how the models SWAT, Hydrus, Coupmodel, SIMPEL and PC-Raster are embedded in the hydrological curriculum and what kind of problems we experienced in teaching.

Multiple model analysis with discriminatory data collection (MMA-DDC): A new method for improving measurement selection

NASA Astrophysics Data System (ADS)

Kikuchi, C.; Ferre, P. A.; Vrugt, J. A.

2011-12-01

Hydrologic models are developed, tested, and refined based on the ability of those models to explain available hydrologic data. The optimization of model performance based upon mismatch between model outputs and real world observations has been extensively studied. However, identification of plausible models is sensitive not only to the models themselves - including model structure and model parameters - but also to the location, timing, type, and number of observations used in model calibration. Therefore, careful selection of hydrologic observations has the potential to significantly improve the performance of hydrologic models. In this research, we seek to reduce prediction uncertainty through optimization of the data collection process. A new tool - multiple model analysis with discriminatory data collection (MMA-DDC) - was developed to address this challenge. In this approach, multiple hydrologic models are developed and treated as competing hypotheses. Potential new data are then evaluated on their ability to discriminate between competing hypotheses. MMA-DDC is well-suited for use in recursive mode, in which new observations are continuously used in the optimization of subsequent observations. This new approach was applied to a synthetic solute transport experiment, in which ranges of parameter values constitute the multiple hydrologic models, and model predictions are calculated using likelihood-weighted model averaging. MMA-DDC was used to determine the optimal location, timing, number, and type of new observations. From comparison with an exhaustive search of all possible observation sequences, we find that MMA-DDC consistently selects observations which lead to the highest reduction in model prediction uncertainty. We conclude that using MMA-DDC to evaluate potential observations may significantly improve the performance of hydrologic models while reducing the cost associated with collecting new data.

Computer modelling of cyclic deformation of high-temperature materials. Progress report

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

Duesbery, M.S.; Louat, N.P.

1992-11-16

Current methods of lifetime assessment leave much to be desired. Typically, the expected life of a full-scale component exposed to a complex environment is based upon empirical interpretations of measurements performed on microscopic samples in controlled laboratory conditions. Extrapolation to the service component is accomplished by scaling laws which, if used at all, are empirical; little or no attention is paid to synergistic interactions between the different components of the real environment. With the increasingly hostile conditions which must be faced in modern aerospace applications, improvement in lifetime estimation is mandated by both cost and safety considerations. This program aimsmore » at improving current methods of lifetime assessment by building in the characteristics of the micro-mechanisms known to be responsible for damage and failure. The broad approach entails the integration and, where necessary, augmentation of the micro-scale research results currently available in the literature into a macro-scale model with predictive capability. In more detail, the program will develop a set of hierarchically structured models at different length scales, from atomic to macroscopic, at each level taking as parametric input the results of the model at the next smaller scale. In this way the known microscopic properties can be transported by systematic procedures to the unknown macro-scale region. It may not be possible to eliminate empiricism completely, because some of the quantities involved cannot yet be estimated to the required degree of precision. In this case the aim will be at least to eliminate functional empiricism.« less

Findings and Challenges in Fine-Resolution Large-Scale Hydrological Modeling

NASA Astrophysics Data System (ADS)

Her, Y. G.

2017-12-01

Fine-resolution large-scale (FL) modeling can provide the overall picture of the hydrological cycle and transport while taking into account unique local conditions in the simulation. It can also help develop water resources management plans consistent across spatial scales by describing the spatial consequences of decisions and hydrological events extensively. FL modeling is expected to be common in the near future as global-scale remotely sensed data are emerging, and computing resources have been advanced rapidly. There are several spatially distributed models available for hydrological analyses. Some of them rely on numerical methods such as finite difference/element methods (FDM/FEM), which require excessive computing resources (implicit scheme) to manipulate large matrices or small simulation time intervals (explicit scheme) to maintain the stability of the solution, to describe two-dimensional overland processes. Others make unrealistic assumptions such as constant overland flow velocity to reduce the computational loads of the simulation. Thus, simulation efficiency often comes at the expense of precision and reliability in FL modeling. Here, we introduce a new FL continuous hydrological model and its application to four watersheds in different landscapes and sizes from 3.5 km2 to 2,800 km2 at the spatial resolution of 30 m on an hourly basis. The model provided acceptable accuracy statistics in reproducing hydrological observations made in the watersheds. The modeling outputs including the maps of simulated travel time, runoff depth, soil water content, and groundwater recharge, were animated, visualizing the dynamics of hydrological processes occurring in the watersheds during and between storm events. Findings and challenges were discussed in the context of modeling efficiency, accuracy, and reproducibility, which we found can be improved by employing advanced computing techniques and hydrological understandings, by using remotely sensed hydrological observations such as soil moisture and radar rainfall depth and by sharing the model and its codes in public domain, respectively.

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.

Advancing Tissue Engineering: A Tale of Nano-, Micro-, and Macroscale Integration.

PubMed

Leijten, Jeroen; Rouwkema, Jeroen; Zhang, Yu Shrike; Nasajpour, Amir; Dokmeci, Mehmet Remzi; Khademhosseini, Ali

2016-04-27

Tissue engineering has the potential to revolutionize the health care industry. Delivering on this promise requires the generation of efficient, controllable and predictable implants. The integration of nano- and microtechnologies into macroscale regenerative biomaterials plays an essential role in the generation of such implants, by enabling spatiotemporal control of the cellular microenvironment. Here we review the role, function and progress of a wide range of nano- and microtechnologies that are driving the advancements in the field of tissue engineering. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A method for coupling a parameterization of the planetary boundary layer with a hydrologic model

NASA Technical Reports Server (NTRS)

Lin, J. D.; Sun, Shu Fen

1986-01-01

Deardorff's parameterization of the planetary boundary layer is adapted to drive a hydrologic model. The method converts the atmospheric conditions measured at the anemometer height at one site to the mean values in the planetary boundary layer; it then uses the planetary boundary layer parameterization and the hydrologic variables to calculate the fluxes of momentum, heat and moisture at the atmosphere-land interface for a different site. A simplified hydrologic model is used for a simulation study of soil moisture and ground temperature on three different land surface covers. The results indicate that this method can be used to drive a spatially distributed hydrologic model by using observed data available at a meteorological station located on or nearby the site.

Sensitivity of effective rainfall amount to land use description using GIS tool. Case of a small mediterranean catchment

NASA Astrophysics Data System (ADS)

Payraudeau, S.; Tournoud, M. G.; Cernesson, F.

Distributed modelling in hydrology assess catchment subdivision to take into account physic characteristics. In this paper, we test the effect of land use aggregation scheme on catchment hydrological response. Evolution of intra-subcatchment land use is studied using statistic and entropy methods. The SCS-CN method is used to calculate effective rainfall which is here assimilated to hydrological response. Our purpose is to determine the existence of a critical threshold-area appropriate for the application of hydrological modelling. Land use aggregation effects on effective rainfall is assessed on small mediterranean catchment. The results show that land use aggregation and land use classification type have significant effects on hydrological modelling and in particular on effective rainfall modelling.

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

PubMed

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

2017-06-01

Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalize community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water plant functional group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 687 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed that models achieved acceptable predictive performance, with correct classification rates in the range 0.68-0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales. © 2017 by the Ecological Society of America.

Data Services in Support of High Performance Computing-Based Distributed Hydrologic Models

NASA Astrophysics Data System (ADS)

Tarboton, D. G.; Horsburgh, J. S.; Dash, P. K.; Gichamo, T.; Yildirim, A. A.; Jones, N.

2014-12-01

We have developed web-based data services to support the application of hydrologic models on High Performance Computing (HPC) systems. The purposes of these services are to provide hydrologic researchers, modelers, water managers, and users access to HPC resources without requiring them to become HPC experts and understanding the intrinsic complexities of the data services, so as to reduce the amount of time and effort spent in finding and organizing the data required to execute hydrologic models and data preprocessing tools on HPC systems. These services address some of the data challenges faced by hydrologic models that strive to take advantage of HPC. Needed data is often not in the form needed by such models, requiring researchers to spend time and effort on data preparation and preprocessing that inhibits or limits the application of these models. Another limitation is the difficult to use batch job control and queuing systems used by HPC systems. We have developed a REST-based gateway application programming interface (API) for authenticated access to HPC systems that abstracts away many of the details that are barriers to HPC use and enhances accessibility from desktop programming and scripting languages such as Python and R. We have used this gateway API to establish software services that support the delineation of watersheds to define a modeling domain, then extract terrain and land use information to automatically configure the inputs required for hydrologic models. These services support the Terrain Analysis Using Digital Elevation Model (TauDEM) tools for watershed delineation and generation of hydrology-based terrain information such as wetness index and stream networks. These services also support the derivation of inputs for the Utah Energy Balance snowmelt model used to address questions such as how climate, land cover and land use change may affect snowmelt inputs to runoff generation. To enhance access to the time varying climate data used to drive hydrologic models, we have developed services to downscale and re-grid nationally available climate analysis data from systems such as NLDAS and MERRA. These cases serve as examples for how this approach can be extended to other models to enhance the use of HPC for hydrologic modeling.

Insights on the impact of systematic model errors on data assimilation performance in changing catchments

NASA Astrophysics Data System (ADS)

Pathiraja, S.; Anghileri, D.; Burlando, P.; Sharma, A.; Marshall, L.; Moradkhani, H.

2018-03-01

The global prevalence of rapid and extensive land use change necessitates hydrologic modelling methodologies capable of handling non-stationarity. This is particularly true in the context of Hydrologic Forecasting using Data Assimilation. Data Assimilation has been shown to dramatically improve forecast skill in hydrologic and meteorological applications, although such improvements are conditional on using bias-free observations and model simulations. A hydrologic model calibrated to a particular set of land cover conditions has the potential to produce biased simulations when the catchment is disturbed. This paper sheds new light on the impacts of bias or systematic errors in hydrologic data assimilation, in the context of forecasting in catchments with changing land surface conditions and a model calibrated to pre-change conditions. We posit that in such cases, the impact of systematic model errors on assimilation or forecast quality is dependent on the inherent prediction uncertainty that persists even in pre-change conditions. Through experiments on a range of catchments, we develop a conceptual relationship between total prediction uncertainty and the impacts of land cover changes on the hydrologic regime to demonstrate how forecast quality is affected when using state estimation Data Assimilation with no modifications to account for land cover changes. This work shows that systematic model errors as a result of changing or changed catchment conditions do not always necessitate adjustments to the modelling or assimilation methodology, for instance through re-calibration of the hydrologic model, time varying model parameters or revised offline/online bias estimation.

Real-time hydrological early warning system at national scale for surface water and groundwater with stakeholder involvement

NASA Astrophysics Data System (ADS)

He, X.; Stisen, S.; Henriksen, H. J.

2015-12-01

Hydrological models are important tools to support decision making in water resource management in the past few decades. Nowadays, frequent occurrence of extreme hydrological events has put focus on development of real-time hydrological modeling and forecasting systems. Among the various types of hydrological models, it is only the rainfall-runoff models for surface water that are commonly used in the online real-time fashion; and there is never a tradition to use integrated hydrological models for both surface water and groundwater with large scale perspective. At the Geological Survey of Denmark and Greenland (GEUS), we have setup and calibrated an integrated hydrological model that covers the entire nation, namely the DK-model. So far, the DK-model has only been used in offline mode for historical and future scenario simulations. Therefore, challenges arise when operating the DK-model in real-time mode due to lack of technical experiences and stakeholder awareness. In the present study, we try to demonstrate the process of bringing the DK-model online while actively involving the opinions of the stakeholders. Although the system is not yet fully operational, a prototype has been finished and presented to the stakeholders which can simulate groundwater levels, streamflow and water content in the root zone with a lead time of 48 hours and refreshed every 6 hours. The active involvement of stakeholders has provided very valuable insights and feedbacks for future improvements.

Coupling a distributed hydrological model with detailed forest structural information for large-scale global change impact assessment

NASA Astrophysics Data System (ADS)

Eisner, Stephanie; Huang, Shaochun; Majasalmi, Titta; Bright, Ryan; Astrup, Rasmus; Beldring, Stein

2017-04-01

Forests are recognized for their decisive effect on landscape water balance with structural forest characteristics as stand density or species composition determining energy partitioning and dominant flow paths. However, spatial and temporal variability in forest structure is often poorly represented in hydrological modeling frameworks, in particular in regional to large scale hydrological modeling and impact analysis. As a common practice, prescribed land cover classes (including different generic forest types) are linked to parameter values derived from literature, or parameters are determined by calibration. While national forest inventory (NFI) data provide comprehensive, detailed information on hydrologically relevant forest characteristics, their potential to inform hydrological simulation over larger spatial domains is rarely exploited. In this study we present a modeling framework that couples the distributed hydrological model HBV with forest structural information derived from the Norwegian NFI and multi-source remote sensing data. The modeling framework, set up for the entire of continental Norway at 1 km spatial resolution, is explicitly designed to study the combined and isolated impacts of climate change, forest management and land use change on hydrological fluxes. We use a forest classification system based on forest structure rather than biomes which allows to implicitly account for impacts of forest management on forest structural attributes. In the hydrological model, different forest classes are represented by three parameters: leaf area index (LAI), mean tree height and surface albedo. Seasonal cycles of LAI and surface albedo are dynamically simulated to make the framework applicable under climate change conditions. Based on a hindcast for the pilot regions Nord-Trøndelag and Sør-Trøndelag, we show how forest management has affected regional hydrological fluxes during the second half of the 20th century as contrasted to climate variability.

A blueprint for using climate change predictions in an eco-hydrological study

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.

2009-12-01

There is a growing interest to extend climate change predictions to smaller, catchment-size scales and identify their implications on hydrological and ecological processes. Small scale processes are, in fact, expected to mediate climate changes, producing local effects and feedbacks that can interact with the principal consequences of the change. This is particularly applicable, when a complex interaction, such as the inter-relationship between the hydrological cycle and vegetation dynamics, is considered. This study presents a blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the catchment scale. Climate conditions, present or future, are imposed through input hydrometeorological variables for hydrological and eco-hydrological models. These variables are simulated with an hourly weather generator as an outcome of a stochastic downscaling technique. The generator is parameterized to reproduce the climate of southwestern Arizona for present (1961-2000) and future (2081-2100) conditions. The methodology provides the capability to generate ensemble realizations for the future that take into account the heterogeneous nature of climate predictions from different models. The generated time series of meteorological variables for the two scenarios corresponding to the current and mean expected future serve as input to a coupled hydrological and vegetation dynamics model, “Tethys-Chloris”. The hydrological model reproduces essential components of the land-surface hydrological cycle, solving the mass and energy budget equations. The vegetation model parsimoniously parameterizes essential plant life-cycle processes, including photosynthesis, phenology, carbon allocation, and tissue turnover. The results for the two mean scenarios are compared and discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity The need to account for uncertainties in projections of future climate is discussed and a methodology for propagating these uncertainties into the probability density functions of changes in eco-hydrological variables is presented.

Sensitivity of river fishes to climate change: The role of hydrological stressors on habitat range shifts.

PubMed

Segurado, Pedro; Branco, Paulo; Jauch, Eduardo; Neves, Ramiro; Ferreira, M Teresa

2016-08-15

Climate change will predictably change hydrological patterns and processes at the catchment scale, with impacts on habitat conditions for fish. The main goal of this study is to assess how shifts in fish habitat favourability under climate change scenarios are affected by hydrological stressors. The interplay between climate and hydrological stressors has important implications in river management under climate change because management actions to control hydrological parameters are more feasible than controlling climate. This study was carried out in the Tamega catchment of the Douro basin. A set of hydrological stressor variables were generated through a process-based modelling based on current climate data (2008-2014) and also considering a high-end future climate change scenario. The resulting parameters, along with climatic and site-descriptor variables were used as explanatory variables in empirical habitat models for nine fish species using boosted regression trees. Models were calibrated for the whole Douro basin using 254 fish sampling sites and predictions under future climate change scenarios were made for the Tamega catchment. Results show that models using climatic variables but not hydrological stressors produce more stringent predictions of future favourability, predicting more distribution contractions or stronger range shifts. The use of hydrological stressors strongly influences projections of habitat favourability shifts; the integration of these stressors in the models thinned shifts in range due to climate change. Hydrological stressors were retained in the models for most species and had a high importance, demonstrating that it is important to integrate hydrology in studies of impacts of climate change on freshwater fishes. This is a relevant result because it means that management actions to control hydrological parameters in rivers will have an impact on the effects of climate change and may potentially be helpful to mitigate its negative effects on fish populations and assemblages. Copyright © 2016 Elsevier B.V. All rights reserved.

Open source data assimilation framework for hydrological modeling

NASA Astrophysics Data System (ADS)

Ridler, Marc; Hummel, Stef; van Velzen, Nils; Katrine Falk, Anne; Madsen, Henrik

2013-04-01

An open-source data assimilation framework is proposed for hydrological modeling. Data assimilation (DA) in hydrodynamic and hydrological forecasting systems has great potential to improve predictions and improve model result. The basic principle is to incorporate measurement information into a model with the aim to improve model results by error minimization. Great strides have been made to assimilate traditional in-situ measurements such as discharge, soil moisture, hydraulic head and snowpack into hydrologic models. More recently, remotely sensed data retrievals of soil moisture, snow water equivalent or snow cover area, surface water elevation, terrestrial water storage and land surface temperature have been successfully assimilated in hydrological models. The assimilation algorithms have become increasingly sophisticated to manage measurement and model bias, non-linear systems, data sparsity (time & space) and undetermined system uncertainty. It is therefore useful to use a pre-existing DA toolbox such as OpenDA. OpenDA is an open interface standard for (and free implementation of) a set of tools to quickly implement DA and calibration for arbitrary numerical models. The basic design philosophy of OpenDA is to breakdown DA into a set of building blocks programmed in object oriented languages. To implement DA, a model must interact with OpenDA to create model instances, propagate the model, get/set variables (or parameters) and free the model once DA is completed. An open-source interface for hydrological models exists capable of all these tasks: OpenMI. OpenMI is an open source standard interface already adopted by key hydrological model providers. It defines a universal approach to interact with hydrological models during simulation to exchange data during runtime, thus facilitating the interactions between models and data sources. The interface is flexible enough so that models can interact even if the model is coded in a different language, represent processes from a different domain or have different spatial and temporal resolutions. An open source framework that bridges OpenMI and OpenDA is presented. The framework provides a generic and easy means for any OpenMI compliant model to assimilate observation measurements. An example test case will be presented using MikeSHE, and OpenMI compliant fully coupled integrated hydrological model that can accurately simulate the feedback dynamics of overland flow, unsaturated zone and saturated zone.

Fallon, Nevada FORGE Thermal-Hydrological-Mechanical Models

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

Blankenship, Doug; Sonnenthal, Eric

Archive contains thermal-mechanical simulation input/output files. Included are files which fall into the following categories: ( 1 ) Spreadsheets with various input parameter calculations ( 2 ) Final Simulation Inputs ( 3 ) Native-State Thermal-Hydrological Model Input File Folders ( 4 ) Native-State Thermal-Hydrological-Mechanical Model Input Files ( 5 ) THM Model Stimulation Cases See 'File Descriptions.xlsx' resource below for additional information on individual files.

Human impact parameterization in global hydrological models improves estimates of monthly discharges and hydrological extremes: a multi-model validation study

NASA Astrophysics Data System (ADS)

Veldkamp, Ted; Ward, Philip; de Moel, Hans; Aerts, Jeroen; Muller Schmied, Hannes; Portmann, Felix; Zhao, Fang; Gerten, Dieter; Masaki, Yoshimitsu; Pokhrel, Yadu; Satoh, Yusuke; Gosling, Simon; Zaherpour, Jamal; Wada, Yoshihide

2017-04-01

Human impacts on freshwater resources and hydrological features form the core of present-day water related hazards, like flooding, droughts, water scarcity, and water quality issues. Driven by the societal and scientific needs to correctly model such water related hazards a fair amount of resources has been invested over the past decades to represent human activities and their interactions with the hydrological cycle in global hydrological models (GHMs). Use of these GHMs - including the human dimension - is widespread, especially in water resources research. Evaluation or comparative assessments of the ability of such GHMs to represent real-world hydrological conditions are, unfortunately, however often limited to (near-)natural river basins. Such studies are, therefore, not able to test the model representation of human activities and its associated impact on estimates of freshwater resources or assessments of hydrological extremes. Studies that did perform a validation exercise - including the human dimension and looking into managed catchments - either focused only on one hydrological model, and/or incorporated only a few data points (i.e. river basins) for validation. To date, a comprehensive comparative analysis that evaluates whether and where incorporating the human dimension actually improves the performance of different GHMs with respect to their representation of real-world hydrological conditions and extremes is missing. The absence of such study limits the potential benchmarking of GHMs and their outcomes in hydrological hazard and risk assessments significantly, potentially hampering incorporation of GHMs and their modelling results in actual policy making and decision support with respect to water resources management. To address this issue, we evaluate in this study the performance of five state-of-the-art GHMs that include anthropogenic activities in their modelling scheme, with respect to their representation of monthly discharges and hydrological extremes. To this end, we compared their monthly discharge simulations under a naturalized and a time-dependent human impact simulation, with monthly GRDC river discharge observations of 2,412 stations over the period 1971-2010. Evaluation metrics that were used to assess the performance of the GHMs included the modified Kling-Gupta Efficiency index, and its individual parameters describing the linear correlation coefficient, the bias ratio, and the variability ratio, as well as indicators for hydrological extremes (Q90, Q10). Our results show that inclusion of anthropogenic activities in the modelling framework generally enhances the overall performance of the GHMs studied, mainly driven by bias-improvements, and to a lesser extent due to changes in modelled hydrological variability. Whilst the inclusion of anthropogenic activities takes mainly effect in the managed catchments, a significant share of the (near-)natural catchments is influenced as well. To get estimates of hydrological extremes right, especially when looking at low-flows, inclusion of human activities is paramount. Whilst high-flow estimates are mainly decreased, impact of human activities on low-flows is ambiguous, i.e. due to the relative importance of the timing of return flows and reservoir operations. Even with inclusion of the human dimension we find, nevertheless, a persistent overestimation of hydrological extremes across all models, which should be accounted for in future assessments.

Modeling the hydrologic impacts of forest harvesting on Florida flatwoods

Treesearch

Ge Sun; Hans Rierkerk; Nicholas B. Comerford

1998-01-01

The great temporal and spatial variability of pine flatwoods hydrology suggests traditional short-term field methods may not be effective in evaluating the hydrologic effects of forest management. The flatwoods model was developed, calibrated and validated specifically for the cypress wetland-pine upland landscape. The model was applied to two typical flatwoods sites...

Overall uncertainty study of the hydrological impacts of climate change for a Canadian watershed

NASA Astrophysics Data System (ADS)

Chen, Jie; Brissette, FrançOis P.; Poulin, Annie; Leconte, Robert

2011-12-01

General circulation models (GCMs) and greenhouse gas emissions scenarios (GGES) are generally considered to be the two major sources of uncertainty in quantifying the climate change impacts on hydrology. Other sources of uncertainty have been given less attention. This study considers overall uncertainty by combining results from an ensemble of two GGES, six GCMs, five GCM initial conditions, four downscaling techniques, three hydrological model structures, and 10 sets of hydrological model parameters. Each climate projection is equally weighted to predict the hydrology on a Canadian watershed for the 2081-2100 horizon. The results show that the choice of GCM is consistently a major contributor to uncertainty. However, other sources of uncertainty, such as the choice of a downscaling method and the GCM initial conditions, also have a comparable or even larger uncertainty for some hydrological variables. Uncertainties linked to GGES and the hydrological model structure are somewhat less than those related to GCMs and downscaling techniques. Uncertainty due to the hydrological model parameter selection has the least important contribution among all the variables considered. Overall, this research underlines the importance of adequately covering all sources of uncertainty. A failure to do so may result in moderately to severely biased climate change impact studies. Results further indicate that the major contributors to uncertainty vary depending on the hydrological variables selected, and that the methodology presented in this paper is successful at identifying the key sources of uncertainty to consider for a climate change impact study.

Hydrologic modeling strategy for the Islamic Republic of Mauritania, Africa

USGS Publications Warehouse

Friedel, Michael J.

2008-01-01

The government of Mauritania is interested in how to maintain hydrologic balance to ensure a long-term stable water supply for minerals-related, domestic, and other purposes. Because of the many complicating and competing natural and anthropogenic factors, hydrologists will perform quantitative analysis with specific objectives and relevant computer models in mind. Whereas various computer models are available for studying water-resource priorities, the success of these models to provide reliable predictions largely depends on adequacy of the model-calibration process. Predictive analysis helps us evaluate the accuracy and uncertainty associated with simulated dependent variables of our calibrated model. In this report, the hydrologic modeling process is reviewed and a strategy summarized for future Mauritanian hydrologic modeling studies.

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

NASA Technical Reports Server (NTRS)

Liu, Yuqiong; Weerts, A.; Clark, M.; Hendricks Franssen, H.-J; Kumar, S.; Moradkhani, H.; Seo, D.-J.; Schwanenberg, D.; Smith, P.; van Dijk, A. I. J. M.;

An approach to measure parameter sensitivity in watershed ...

EPA Pesticide Factsheets

Hydrologic responses vary spatially and temporally according to watershed characteristics. In this study, the hydrologic models that we developed earlier for the Little Miami River (LMR) and Las Vegas Wash (LVW) watersheds were used for detail sensitivity analyses. To compare the relative sensitivities of the hydrologic parameters of these two models, we used Normalized Root Mean Square Error (NRMSE). By combining the NRMSE index with the flow duration curve analysis, we derived an approach to measure parameter sensitivities under different flow regimes. Results show that the parameters related to groundwater are highly sensitive in the LMR watershed, whereas the LVW watershed is primarily sensitive to near surface and impervious parameters. The high and medium flows are more impacted by most of the parameters. Low flow regime was highly sensitive to groundwater related parameters. Moreover, our approach is found to be useful in facilitating model development and calibration. This journal article describes hydrological modeling of climate change and land use changes on stream hydrology, and elucidates the importance of hydrological model construction in generating valid modeling results.

On how to avoid input and structural uncertainties corrupt the inference of hydrological parameters using a Bayesian framework

NASA Astrophysics Data System (ADS)

Hernández, Mario R.; Francés, Félix

2015-04-01

One phase of the hydrological models implementation process, significantly contributing to the hydrological predictions uncertainty, is the calibration phase in which values of the unknown model parameters are tuned by optimizing an objective function. An unsuitable error model (e.g. Standard Least Squares or SLS) introduces noise into the estimation of the parameters. The main sources of this noise are the input errors and the hydrological model structural deficiencies. Thus, the biased calibrated parameters cause the divergence model phenomenon, where the errors variance of the (spatially and temporally) forecasted flows far exceeds the errors variance in the fitting period, and provoke the loss of part or all of the physical meaning of the modeled processes. In other words, yielding a calibrated hydrological model which works well, but not for the right reasons. Besides, an unsuitable error model yields a non-reliable predictive uncertainty assessment. Hence, with the aim of prevent all these undesirable effects, this research focuses on the Bayesian joint inference (BJI) of both the hydrological and error model parameters, considering a general additive (GA) error model that allows for correlation, non-stationarity (in variance and bias) and non-normality of model residuals. As hydrological model, it has been used a conceptual distributed model called TETIS, with a particular split structure of the effective model parameters. Bayesian inference has been performed with the aid of a Markov Chain Monte Carlo (MCMC) algorithm called Dream-ZS. MCMC algorithm quantifies the uncertainty of the hydrological and error model parameters by getting the joint posterior probability distribution, conditioned on the observed flows. The BJI methodology is a very powerful and reliable tool, but it must be used correctly this is, if non-stationarity in errors variance and bias is modeled, the Total Laws must be taken into account. The results of this research show that the application of BJI with a GA error model outperforms the hydrological parameters robustness (diminishing the divergence model phenomenon) and improves the reliability of the streamflow predictive distribution, in respect of the results of a bad error model as SLS. Finally, the most likely prediction in a validation period, for both BJI+GA and SLS error models shows a similar performance.

Alternative spatial configurations to reflect landscape structure in a hydrological model: SUMMA applications to the Reynolds Creek Watershed and the Columbia River Basin

NASA Astrophysics Data System (ADS)

Nijssen, Bart; Clark, Martyn; Mizukami, Naoki; Chegwidden, Oriana

2016-04-01

Most existing hydrological models use a fixed representation of landscape structure. For example, high-resolution, spatially-distributed models may use grid cells that exchange moisture through the saturated subsurface or may divide the landscape into hydrologic response units that only exchange moisture through surface channels. Alternatively, many regional models represent the landscape through coarse elements that do not model any moisture exchange between these model elements. These spatial organizations are often represented at a low-level in the model code and its data structures, which makes it difficult to evaluate different landscape representations using the same hydrological model. Instead, such experimentation requires the use of multiple, different hydrological models, which in turn complicates the analysis, because differences in model outcomes are no longer constrained by differing spatial representations. This inflexibility in the representation of landscape structure also limits a model's capability for scaling local processes to regional outcomes. In this study, we used the Structure for Unifying Multiple Modeling Alternatives (SUMMA) to evaluate different model spatial configurations to represent landscape structure and to evaluate scaling behavior. SUMMA can represent the moisture exchange between arbitrarily shaped landscape elements in a number of different ways, while using the same model parameterizations for vertical fluxes. This allows us to isolate the effects of changes in landscape representations on modeled hydrological fluxes and states. We examine the effects of spatial configuration in Reynolds Creek, Idaho, USA, which is a research watershed with gaged areas from 1-20 km2. We then use the same modeling system to evaluate scaling behavior in simulated hydrological fluxes in the Columbia River Basin, Pacific Northwest, USA. This basin drains more than 500,000 km2 and includes the Reynolds Creek Watershed.

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

The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

NASA Astrophysics Data System (ADS)

Clark, Martyn P.; Bierkens, Marc F. P.; Samaniego, Luis; Woods, Ross A.; Uijlenhoet, Remko; Bennett, Katrina E.; Pauwels, Valentijn R. N.; Cai, Xitian; Wood, Andrew W.; Peters-Lidard, Christa D.

2017-07-01

The diversity in hydrologic models has historically led to great controversy on the correct approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this paper, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We illustrate how modeling advances have been made by groups using models of different type and complexity, and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.

The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

NASA Astrophysics Data System (ADS)

Clark, M. P.; Nijssen, B.; Wood, A.; Mizukami, N.; Newman, A. J.

2017-12-01

The diversity in hydrologic models has historically led to great controversy on the "correct" approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. In this paper, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We illustrate how modeling advances have been made by groups using models of different type and complexity, and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.

Hydrologic Design in the Anthropocene

NASA Astrophysics Data System (ADS)

Vogel, R. M.; Farmer, W. H.; Read, L.

2014-12-01

In an era dubbed the Anthropocene, the natural world is being transformed by a myriad of human influences. As anthropogenic impacts permeate hydrologic systems, hydrologists are challenged to fully account for such changes and develop new methods of hydrologic design. Deterministic watershed models (DWM), which can account for the impacts of changes in land use, climate and infrastructure, are becoming increasing popular for the design of flood and/or drought protection measures. As with all models that are calibrated to existing datasets, DWMs are subject to model error or uncertainty. In practice, the model error component of DWM predictions is typically ignored yet DWM simulations which ignore model error produce model output which cannot reproduce the statistical properties of the observations they are intended to replicate. In the context of hydrologic design, we demonstrate how ignoring model error can lead to systematic downward bias in flood quantiles, upward bias in drought quantiles and upward bias in water supply yields. By reincorporating model error, we document how DWM models can be used to generate results that mimic actual observations and preserve their statistical behavior. In addition to use of DWM for improved predictions in a changing world, improved communication of the risk and reliability is also needed. Traditional statements of risk and reliability in hydrologic design have been characterized by return periods, but such statements often assume that the annual probability of experiencing a design event remains constant throughout the project horizon. We document the general impact of nonstationarity on the average return period and reliability in the context of hydrologic design. Our analyses reveal that return periods do not provide meaningful expressions of the likelihood of future hydrologic events. Instead, knowledge of system reliability over future planning horizons can more effectively prepare society and communicate the likelihood of future hydrologic events of interest.

Sources of uncertainty in hydrological climate impact assessment: a cross-scale study

NASA Astrophysics Data System (ADS)

Hattermann, F. F.; Vetter, T.; Breuer, L.; Su, Buda; Daggupati, P.; Donnelly, C.; Fekete, B.; Flörke, F.; Gosling, S. N.; Hoffmann, P.; Liersch, S.; Masaki, Y.; Motovilov, Y.; Müller, C.; Samaniego, L.; Stacke, T.; Wada, Y.; Yang, T.; Krysnaova, V.

2018-01-01

Climate change impacts on water availability and hydrological extremes are major concerns as regards the Sustainable Development Goals. Impacts on hydrology are normally investigated as part of a modelling chain, in which climate projections from multiple climate models are used as inputs to multiple impact models, under different greenhouse gas emissions scenarios, which result in different amounts of global temperature rise. While the goal is generally to investigate the relevance of changes in climate for the water cycle, water resources or hydrological extremes, it is often the case that variations in other components of the model chain obscure the effect of climate scenario variation. This is particularly important when assessing the impacts of relatively lower magnitudes of global warming, such as those associated with the aspirational goals of the Paris Agreement. In our study, we use ANOVA (analyses of variance) to allocate and quantify the main sources of uncertainty in the hydrological impact modelling chain. In turn we determine the statistical significance of different sources of uncertainty. We achieve this by using a set of five climate models and up to 13 hydrological models, for nine large scale river basins across the globe, under four emissions scenarios. The impact variable we consider in our analysis is daily river discharge. We analyze overall water availability and flow regime, including seasonality, high flows and low flows. Scaling effects are investigated by separately looking at discharge generated by global and regional hydrological models respectively. Finally, we compare our results with other recently published studies. We find that small differences in global temperature rise associated with some emissions scenarios have mostly significant impacts on river discharge—however, climate model related uncertainty is so large that it obscures the sensitivity of the hydrological system.

Nano-metrology and terrain modelling - convergent practice in surface characterisation

USGS Publications Warehouse

Pike, R.J.

2000-01-01

The quantification of magnetic-tape and disk topography has a macro-scale counterpart in the Earth sciences - terrain modelling, the numerical representation of relief and pattern of the ground surface. The two practices arose independently and continue to function separately. This methodological paper introduces terrain modelling, discusses its similarities to and differences from industrial surface metrology, and raises the possibility of a unified discipline of quantitative surface characterisation. A brief discussion of an Earth-science problem, subdividing a heterogeneous terrain surface from a set of sample measurements, exemplifies a multivariate statistical procedure that may transfer to tribological applications of 3-D metrological height data.

The HYPE Open Source Community

NASA Astrophysics Data System (ADS)

Strömbäck, Lena; Arheimer, Berit; Pers, Charlotta; Isberg, Kristina

2013-04-01

The Hydrological Predictions for the Environment (HYPE) model is a dynamic, semi-distributed, process-based, integrated catchment model (Lindström et al., 2010). It uses well-known hydrological and nutrient transport concepts and can be applied for both small and large scale assessments of water resources and status. In the model, the landscape is divided into classes according to soil type, vegetation and altitude. The soil representation is stratified and can be divided in up to three layers. Water and substances are routed through the same flow paths and storages (snow, soil, groundwater, streams, rivers, lakes) considering turn-over and transformation on the way towards the sea. In Sweden, the model is used by water authorities to fulfil the Water Framework Directive and the Marine Strategy Framework Directive. It is used for characterization, forecasts, and scenario analyses. Model data can be downloaded for free from three different HYPE applications: Europe (www.smhi.se/e-hype), Baltic Sea basin (www.smhi.se/balt-hype), and Sweden (vattenweb.smhi.se) The HYPE OSC (hype.sourceforge.net) is an open source initiative under the Lesser GNU Public License taken by SMHI to strengthen international collaboration in hydrological modelling and hydrological data production. The hypothesis is that more brains and more testing will result in better models and better code. The code is transparent and can be changed and learnt from. New versions of the main code will be delivered frequently. The main objective of the HYPE OSC is to provide public access to a state-of-the-art operational hydrological model and to encourage hydrologic expertise from different parts of the world to contribute to model improvement. HYPE OSC is open to everyone interested in hydrology, hydrological modelling and code development - e.g. scientists, authorities, and consultancies. The HYPE Open Source Community was initiated in November 2011 by a kick-off and workshop with 50 eager participants from twelve different countries. In beginning of 2013 we will release a new version of the code featuring new and better modularization, corresponding to hydrological processes which will make the code easier to understand and further develop. During 2013 we also plan a new workshop and HYPE course for everyone interested in the community. Lindström, G., Pers, C.P., Rosberg, R., Strömqvist, J., Arheimer, B. 2010. Development and test of the HYPE (Hydrological Predictions for the Environment) model - A water quality model for different spatial scales. Hydrology Research 41.3-4:295-319

Hydrology under change: an evaluation protocol to investigate how hydrological models deal with changing catchments

Treesearch

G. Thirel; V. Andreassian; C. Perrin; J.-N. Audouy; L. Berthet; Pamela Edwards; N. Folton; C. Furusho; A. Kuentz; J. Lerat; G. Lindstrom; E. Martin; T. Mathevet; R. Merz; J. Parajka; D. Ruelland; J. Vaze

2015-01-01

Testing hydrological models under changing conditions is essential to evaluate their ability to cope with changing catchments and their suitability for impact studies. With this perspective in mind, a workshop dedicated to this issue was held at the 2013 General Assembly of the International Association of Hydrological Sciences (IAHS) in Göteborg, Sweden, in July 2013...

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

Atomistic modeling of dropwise condensation

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

Sikarwar, B. S., E-mail: bssikarwar@amity.edu; Singh, P. L.; Muralidhar, K.

The basic aim of the atomistic modeling of condensation of water is to determine the size of the stable cluster and connect phenomena occurring at atomic scale to the macroscale. In this paper, a population balance model is described in terms of the rate equations to obtain the number density distribution of the resulting clusters. The residence time is taken to be large enough so that sufficient time is available for all the adatoms existing in vapor-phase to loose their latent heat and get condensed. The simulation assumes clusters of a given size to be formed from clusters of smallermore » sizes, but not by the disintegration of the larger clusters. The largest stable cluster size in the number density distribution is taken to be representative of the minimum drop radius formed in a dropwise condensation process. A numerical confirmation of this result against predictions based on a thermodynamic model has been obtained. Results show that the number density distribution is sensitive to the surface diffusion coefficient and the rate of vapor flux impinging on the substrate. The minimum drop radius increases with the diffusion coefficient and the impinging vapor flux; however, the dependence is weak. The minimum drop radius predicted from thermodynamic considerations matches the prediction of the cluster model, though the former does not take into account the effect of the surface properties on the nucleation phenomena. For a chemically passive surface, the diffusion coefficient and the residence time are dependent on the surface texture via the coefficient of friction. Thus, physical texturing provides a means of changing, within limits, the minimum drop radius. The study reveals that surface texturing at the scale of the minimum drop radius does not provide controllability of the macro-scale dropwise condensation at large timescales when a dynamic steady-state is reached.« less

Quasi-static incremental behavior of granular materials: Elastic-plastic coupling and micro-scale dissipation

NASA Astrophysics Data System (ADS)

Kuhn, Matthew R.; Daouadji, Ali

2018-05-01

The paper addresses a common assumption of elastoplastic modeling: that the recoverable, elastic strain increment is unaffected by alterations of the elastic moduli that accompany loading. This assumption is found to be false for a granular material, and discrete element (DEM) simulations demonstrate that granular materials are coupled materials at both micro- and macro-scales. Elasto-plastic coupling at the macro-scale is placed in the context of thermomechanics framework of Tomasz Hueckel and Hans Ziegler, in which the elastic moduli are altered by irreversible processes during loading. This complex behavior is explored for multi-directional loading probes that follow an initial monotonic loading. An advanced DEM model is used in the study, with non-convex non-spherical particles and two different contact models: a conventional linear-frictional model and an exact implementation of the Hertz-like Cattaneo-Mindlin model. Orthotropic true-triaxial probes were used in the study (i.e., no direct shear strain), with tiny strain increments of 2 ×10-6 . At the micro-scale, contact movements were monitored during small increments of loading and load-reversal, and results show that these movements are not reversed by a reversal of strain direction, and some contacts that were sliding during a loading increment continue to slide during reversal. The probes show that the coupled part of a strain increment, the difference between the recoverable (elastic) increment and its reversible part, must be considered when partitioning strain increments into elastic and plastic parts. Small increments of irreversible (and plastic) strain and contact slipping and frictional dissipation occur for all directions of loading, and an elastic domain, if it exists at all, is smaller than the strain increment used in the simulations.

Effects of DEM source and resolution on WEPP hydrologic and erosion simulation: A case study of two forest watersheds in northern Idaho

Treesearch

J. X. Zhang; J. Q. Wu; K. Chang; W. J. Elliot; S. Dun

2009-01-01

The recent modification of the Water Erosion Prediction Project (WEPP) model has improved its applicability to hydrology and erosion modeling in forest watersheds. To generate reliable topographic and hydrologic inputs for the WEPP model, carefully selecting digital elevation models (DEMs) with appropriate resolution and accuracy is essential because topography is a...

Hydrogeology, hydrologic effects of development, and simulation of groundwater flow in the Borrego Valley, San Diego County, California

USGS Publications Warehouse

Faunt, Claudia C.; Stamos, Christina L.; Flint, Lorraine E.; Wright, Michael T.; Burgess, Matthew K.; Sneed, Michelle; Brandt, Justin; Martin, Peter; Coes, Alissa L.

2015-11-24

This report documents and presents (1) an analysis of the conceptual model, (2) a description of the hydrologic features, (3) a compilation and analysis of water-quality data, (4) the measurement and analysis of land subsidence by using geophysical and remote sensing techniques, (5) the development and calibration of a two-dimensional borehole-groundwater-flow model to estimate aquifer hydraulic conductivities, (6) the development and calibration of a three-dimensional (3-D) integrated hydrologic flow model, (7) a water-availability analysis with respect to current climate variability and land use, and (8) potential future management scenarios. The integrated hydrologic model, referred to here as the “Borrego Valley Hydrologic Model” (BVHM), is a tool that can provide results with the accuracy needed for making water-management decisions, although potential future refinements and enhancements could further improve the level of spatial and temporal resolution and model accuracy. Because the model incorporates time-varying inflows and outflows, this tool can be used to evaluate the effects of temporal changes in recharge and pumping and to compare the relative effects of different water-management scenarios on the aquifer system. Overall, the development of the hydrogeologic and hydrologic models, data networks, and hydrologic analysis provides a basis for assessing surface and groundwater availability and potential water-resource management guidelines.

Nucleation, aggregative growth and detachment of metal nanoparticles during electrodeposition at electrode surfaces.

PubMed

Lai, Stanley C S; Lazenby, Robert A; Kirkman, Paul M; Unwin, Patrick R

2015-02-01

The nucleation and growth of metal nanoparticles (NPs) on surfaces is of considerable interest with regard to creating functional interfaces with myriad applications. Yet, key features of these processes remain elusive and are undergoing revision. Here, the mechanism of the electrodeposition of silver on basal plane highly oriented pyrolytic graphite (HOPG) is investigated as a model system at a wide range of length scales, spanning electrochemical measurements from the macroscale to the nanoscale using scanning electrochemical cell microscopy (SECCM), a pipette-based approach. The macroscale measurements show that the nucleation process cannot be modelled as either truly instantaneous or progressive, and that step edge sites of HOPG do not play a dominant role in nucleation events compared to the HOPG basal plane, as has been widely proposed. Moreover, nucleation numbers extracted from electrochemical analysis do not match those determined by atomic force microscopy (AFM). The high time and spatial resolution of the nanoscale pipette set-up reveals individual nucleation and growth events at the graphite basal surface that are resolved and analysed in detail. Based on these results, corroborated with complementary microscopy measurements, we propose that a nucleation-aggregative growth-detachment mechanism is an important feature of the electrodeposition of silver NPs on HOPG. These findings have major implications for NP electrodeposition and for understanding electrochemical processes at graphitic materials generally.

On the Usefulness of Hydrologic Landscapes for Hydrologic Modeling and Water Management

EPA Science Inventory

Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...

On the Usefulness of Hydrologic Landscapes on Hydrologic Model calibration and Selection

EPA Science Inventory

Hydrologic Landscapes (HLs) are units that can be used in aggregate to describe the watershed-scale hydrologic response of an area through use of physical and climatic properties. The HL assessment unit is a useful classification tool to relate and transfer hydrologically meaning...

Testing the Hydrological Coherence of High-Resolution Gridded Precipitation and Temperature Data Sets

NASA Astrophysics Data System (ADS)

Laiti, L.; Mallucci, S.; Piccolroaz, S.; Bellin, A.; Zardi, D.; Fiori, A.; Nikulin, G.; Majone, B.

2018-03-01

Assessing the accuracy of gridded climate data sets is highly relevant to climate change impact studies, since evaluation, bias correction, and statistical downscaling of climate models commonly use these products as reference. Among all impact studies those addressing hydrological fluxes are the most affected by errors and biases plaguing these data. This paper introduces a framework, coined Hydrological Coherence Test (HyCoT), for assessing the hydrological coherence of gridded data sets with hydrological observations. HyCoT provides a framework for excluding meteorological forcing data sets not complying with observations, as function of the particular goal at hand. The proposed methodology allows falsifying the hypothesis that a given data set is coherent with hydrological observations on the basis of the performance of hydrological modeling measured by a metric selected by the modeler. HyCoT is demonstrated in the Adige catchment (southeastern Alps, Italy) for streamflow analysis, using a distributed hydrological model. The comparison covers the period 1989-2008 and includes five gridded daily meteorological data sets: E-OBS, MSWEP, MESAN, APGD, and ADIGE. The analysis highlights that APGD and ADIGE, the data sets with highest effective resolution, display similar spatiotemporal precipitation patterns and produce the largest hydrological efficiency indices. Lower performances are observed for E-OBS, MESAN, and MSWEP, especially in small catchments. HyCoT reveals deficiencies in the representation of spatiotemporal patterns of gridded climate data sets, which cannot be corrected by simply rescaling the meteorological forcing fields, as often done in bias correction of climate model outputs. We recommend this framework to assess the hydrological coherence of gridded data sets to be used in large-scale hydroclimatic studies.

Stochastic Simulation and Forecast of Hydrologic Time Series Based on Probabilistic Chaos Expansion

NASA Astrophysics Data System (ADS)

Li, Z.; Ghaith, M.

2017-12-01

Hydrological processes are characterized by many complex features, such as nonlinearity, dynamics and uncertainty. How to quantify and address such complexities and uncertainties has been a challenging task for water engineers and managers for decades. To support robust uncertainty analysis, an innovative approach for the stochastic simulation and forecast of hydrologic time series is developed is this study. Probabilistic Chaos Expansions (PCEs) are established through probabilistic collocation to tackle uncertainties associated with the parameters of traditional hydrological models. The uncertainties are quantified in model outputs as Hermite polynomials with regard to standard normal random variables. Sequentially, multivariate analysis techniques are used to analyze the complex nonlinear relationships between meteorological inputs (e.g., temperature, precipitation, evapotranspiration, etc.) and the coefficients of the Hermite polynomials. With the established relationships between model inputs and PCE coefficients, forecasts of hydrologic time series can be generated and the uncertainties in the future time series can be further tackled. The proposed approach is demonstrated using a case study in China and is compared to a traditional stochastic simulation technique, the Markov-Chain Monte-Carlo (MCMC) method. Results show that the proposed approach can serve as a reliable proxy to complicated hydrological models. It can provide probabilistic forecasting in a more computationally efficient manner, compared to the traditional MCMC method. This work provides technical support for addressing uncertainties associated with hydrological modeling and for enhancing the reliability of hydrological modeling results. Applications of the developed approach can be extended to many other complicated geophysical and environmental modeling systems to support the associated uncertainty quantification and risk analysis.

The critical role of uncertainty in projections of hydrological extremes

NASA Astrophysics Data System (ADS)

Meresa, Hadush K.; Romanowicz, Renata J.

2017-08-01

This paper aims to quantify the uncertainty in projections of future hydrological extremes in the Biala Tarnowska River at Koszyce gauging station, south Poland. The approach followed is based on several climate projections obtained from the EURO-CORDEX initiative, raw and bias-corrected realizations of catchment precipitation, and flow simulations derived using multiple hydrological model parameter sets. The projections cover the 21st century. Three sources of uncertainty are considered: one related to climate projection ensemble spread, the second related to the uncertainty in hydrological model parameters and the third related to the error in fitting theoretical distribution models to annual extreme flow series. The uncertainty of projected extreme indices related to hydrological model parameters was conditioned on flow observations from the reference period using the generalized likelihood uncertainty estimation (GLUE) approach, with separate criteria for high- and low-flow extremes. Extreme (low and high) flow quantiles were estimated using the generalized extreme value (GEV) distribution at different return periods and were based on two different lengths of the flow time series. A sensitivity analysis based on the analysis of variance (ANOVA) shows that the uncertainty introduced by the hydrological model parameters can be larger than the climate model variability and the distribution fit uncertainty for the low-flow extremes whilst for the high-flow extremes higher uncertainty is observed from climate models than from hydrological parameter and distribution fit uncertainties. This implies that ignoring one of the three uncertainty sources may cause great risk to future hydrological extreme adaptations and water resource planning and management.

An approach to measure parameter sensitivity in watershed hydrological modelling

EPA Science Inventory

Hydrologic responses vary spatially and temporally according to watershed characteristics. In this study, the hydrologic models that we developed earlier for the Little Miami River (LMR) and Las Vegas Wash (LVW) watersheds were used for detail sensitivity analyses. To compare the...

Simultaneous Semi-Distributed Model Calibration Guided by Hydrologic Landscapes in the Pacific Northwest, USA

EPA Science Inventory

Modelling approaches to transfer hydrologically-relevant information from locations with streamflow measurements to locations without such measurements continues to be an active field of research for hydrologists. The Pacific Northwest Hydrologic Landscapes (PNW HL) provide a sol...

Delineating floodplain and upload areas for hydrologic models: A comparison of methods

USDA-ARS?s Scientific Manuscript database

A spatially distributed representation of basin hydrology and transport processes in eco-hydrological models facilitates the identification of critical source areas and the placement of management and conservation measures. Floodplains are critical landscape features that differ from neighboring up...

Stimulation from Simulation? A Teaching Model of Hillslope Hydrology for Use on Microcomputers.

ERIC Educational Resources Information Center

Burt, Tim; Butcher, Dave

1986-01-01

The design and use of a simple computer model which simulates a hillslope hydrology is described in a teaching context. The model shows a relatively complex environmental system can be constructed on the basis of a simple but realistic theory, thus allowing students to simulate the hydrological response of real hillslopes. (Author/TRS)

Use of high resolution remotely sensed evapotranspiration retrievals for calibration of a process-based hydrologic model in data-poor basins

USDA-ARS?s Scientific Manuscript database

Calibration of process-based hydrologic models is a challenging task in data-poor basins, where monitored hydrologic data are scarce. In this study, we present a novel approach that benefits from remotely sensed evapotranspiration (ET) data to calibrate a complex watershed model, namely the Soil and...

Hydrologic Evaluation of Landfill Performance (HELP) Model: B (Set Includes, A- User's Guide for Version 3 w/disks, B-Engineering Documentation for Version 3

EPA Science Inventory

The Hydrologic Evaluation of Landfill Performance (HELP) computer program is a quasi-two-dimensional hydrologic model of water movement across, into, through and out of landfills. The model accepts weather, soil and design data. Landfill systems including various combinations o...

Exploration of warm-up period in conceptual hydrological modelling

NASA Astrophysics Data System (ADS)

Kim, Kue Bum; Kwon, Hyun-Han; Han, Dawei

2018-01-01

One of the important issues in hydrological modelling is to specify the initial conditions of the catchment since it has a major impact on the response of the model. Although this issue should be a high priority among modelers, it has remained unaddressed by the community. The typical suggested warm-up period for the hydrological models has ranged from one to several years, which may lead to an underuse of data. The model warm-up is an adjustment process for the model to reach an 'optimal' state, where internal stores (e.g., soil moisture) move from the estimated initial condition to an 'optimal' state. This study explores the warm-up period of two conceptual hydrological models, HYMOD and IHACRES, in a southwestern England catchment. A series of hydrologic simulations were performed for different initial soil moisture conditions and different rainfall amounts to evaluate the sensitivity of the warm-up period. Evaluation of the results indicates that both initial wetness and rainfall amount affect the time required for model warm up, although it depends on the structure of the hydrological model. Approximately one and a half months are required for the model to warm up in HYMOD for our study catchment and climatic conditions. In addition, it requires less time to warm up under wetter initial conditions (i.e., saturated initial conditions). On the other hand, approximately six months is required for warm-up in IHACRES, and the wet or dry initial conditions have little effect on the warm-up period. Instead, the initial values that are close to the optimal value result in less warm-up time. These findings have implications for hydrologic model development, specifically in determining soil moisture initial conditions and warm-up periods to make full use of the available data, which is very important for catchments with short hydrological records.

Improving evapotranspiration processes in distrubing hydrological models using Remote Sensing derived ET products.

NASA Astrophysics Data System (ADS)

Abitew, T. A.; van Griensven, A.; Bauwens, W.

2015-12-01

Evapotranspiration is the main process in hydrology (on average around 60%), though has not received as much attention in the evaluation and calibration of hydrological models. In this study, Remote Sensing (RS) derived Evapotranspiration (ET) is used to improve the spatially distributed processes of ET of SWAT model application in the upper Mara basin (Kenya) and the Blue Nile basin (Ethiopia). The RS derived ET data is obtained from recently compiled global datasets (continuously monthly data at 1 km resolution from MOD16NBI,SSEBop,ALEXI,CMRSET models) and from regionally applied Energy Balance Models (for several cloud free days). The RS-RT data is used in different forms: Method 1) to evaluate spatially distributed evapotransiration model resultsMethod 2) to calibrate the evotranspiration processes in hydrological modelMethod 3) to bias-correct the evapotranpiration in hydrological model during simulation after changing the SWAT codesAn inter-comparison of the RS-ET products shows that at present there is a significant bias, but at the same time an agreement on the spatial variability of ET. The ensemble mean of different ET products seems the most realistic estimation and was further used in this study.The results show that:Method 1) the spatially mapped evapotranspiration of hydrological models shows clear differences when compared to RS derived evapotranspiration (low correlations). Especially evapotranspiration in forested areas is strongly underestimated compared to other land covers.Method 2) Calibration allows to improve the correlations between the RS and hydrological model results to some extent.Method 3) Bias-corrections are efficient in producing (sesonal or annual) evapotranspiration maps from hydrological models which are very similar to the patterns obtained from RS data.Though the bias-correction is very efficient, it is advised to improve the model results by better representing the ET processes by improved plant/crop computations, improved agricultural management practices or by providing improved meteorological data.

Testing the structure of a hydrological model using Genetic Programming

NASA Astrophysics Data System (ADS)

Selle, Benny; Muttil, Nitin

2011-01-01

SummaryGenetic Programming is able to systematically explore many alternative model structures of different complexity from available input and response data. We hypothesised that Genetic Programming can be used to test the structure of hydrological models and to identify dominant processes in hydrological systems. To test this, Genetic Programming was used to analyse a data set from a lysimeter experiment in southeastern Australia. The lysimeter experiment was conducted to quantify the deep percolation response under surface irrigated pasture to different soil types, watertable depths and water ponding times during surface irrigation. Using Genetic Programming, a simple model of deep percolation was recurrently evolved in multiple Genetic Programming runs. This simple and interpretable model supported the dominant process contributing to deep percolation represented in a conceptual model that was published earlier. Thus, this study shows that Genetic Programming can be used to evaluate the structure of hydrological models and to gain insight about the dominant processes in hydrological systems.

Model Calibration in Watershed Hydrology

NASA Technical Reports Server (NTRS)

Yilmaz, Koray K.; Vrugt, Jasper A.; Gupta, Hoshin V.; Sorooshian, Soroosh

2009-01-01

Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must, therefore, be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. This Chapter reviews the current state-of-the-art of model calibration in watershed hydrology with special emphasis on our own contributions in the last few decades. We discuss the historical background that has led to current perspectives, and review different approaches for manual and automatic single- and multi-objective parameter estimation. In particular, we highlight the recent developments in the calibration of distributed hydrologic models using parameter dimensionality reduction sampling, parameter regularization and parallel computing.

Uncertainty of a hydrological climate change impact assessment - Is it really all about climate uncertainty?

NASA Astrophysics Data System (ADS)

Honti, Mark; Reichert, Peter; Scheidegger, Andreas; Stamm, Christian

2013-04-01

Climate change impact assessments have become more and more popular in hydrology since the middle 1980's with another boost after the publication of the IPCC AR4 report. During hundreds of impact studies a quasi-standard methodology emerged, which is mainly shaped by the growing public demand for predicting how water resources management or flood protection should change in the close future. The ``standard'' workflow considers future climate under a specific IPCC emission scenario simulated by global circulation models (GCMs), possibly downscaled by a regional climate model (RCM) and/or a stochastic weather generator. The output from the climate models is typically corrected for bias before feeding it into a calibrated hydrological model, which is run on the past and future meteorological data to analyse the impacts of climate change on the hydrological indicators of interest. The impact predictions are as uncertain as any forecast that tries to describe the behaviour of an extremely complex system decades into the future. Future climate predictions are uncertain due to the scenario uncertainty and the GCM model uncertainty that is obvious on finer resolution than continental scale. Like in any hierarchical model system, uncertainty propagates through the descendant components. Downscaling increases uncertainty with the deficiencies of RCMs and/or weather generators. Bias correction adds a strong deterministic shift to the input data. Finally the predictive uncertainty of the hydrological model ends the cascade that leads to the total uncertainty of the hydrological impact assessment. There is an emerging consensus between many studies on the relative importance of the different uncertainty sources. The prevailing perception is that GCM uncertainty dominates hydrological impact studies. There are only few studies, which found that the predictive uncertainty of hydrological models can be in the same range or even larger than climatic uncertainty. We carried out a climate change impact assessment and estimated the relative importance of the uncertainty sources. The study was performed on 2 small catchments in the Swiss Plateau with a lumped conceptual rainfall runoff model. In the climatic part we applied the standard ensemble approach to quantify uncertainty but in hydrology we used formal Bayesian uncertainty assessment method with 2 different likelihood functions. One was a time-series error model that was able to deal with the complicated statistical properties of hydrological model residuals. The second was a likelihood function for the flow quantiles directly. Due to the better data coverage and smaller hydrological complexity in one of our test catchments we had better performance from the hydrological model and thus could observe that the relative importance of different uncertainty sources varied between sites, boundary conditions and flow indicators. The uncertainty of future climate was important, but not dominant. The deficiencies of the hydrological model were on the same scale, especially for the sites and flow components where model performance for the past observations was further from optimal (Nash-Sutcliffe index = 0.5 - 0.7). The overall uncertainty of predictions was well beyond the expected change signal even for the best performing site and flow indicator.

Effects of different regional climate model resolution and forcing scales on projected hydrologic changes

NASA Astrophysics Data System (ADS)

Mendoza, Pablo A.; Mizukami, Naoki; Ikeda, Kyoko; Clark, Martyn P.; Gutmann, Ethan D.; Arnold, Jeffrey R.; Brekke, Levi D.; Rajagopalan, Balaji

2016-10-01

We examine the effects of regional climate model (RCM) horizontal resolution and forcing scaling (i.e., spatial aggregation of meteorological datasets) on the portrayal of climate change impacts. Specifically, we assess how the above decisions affect: (i) historical simulation of signature measures of hydrologic behavior, and (ii) projected changes in terms of annual water balance and hydrologic signature measures. To this end, we conduct our study in three catchments located in the headwaters of the Colorado River basin. Meteorological forcings for current and a future climate projection are obtained at three spatial resolutions (4-, 12- and 36-km) from dynamical downscaling with the Weather Research and Forecasting (WRF) regional climate model, and hydrologic changes are computed using four different hydrologic model structures. These projected changes are compared to those obtained from running hydrologic simulations with current and future 4-km WRF climate outputs re-scaled to 12- and 36-km. The results show that the horizontal resolution of WRF simulations heavily affects basin-averaged precipitation amounts, propagating into large differences in simulated signature measures across model structures. The implications of re-scaled forcing datasets on historical performance were primarily observed on simulated runoff seasonality. We also found that the effects of WRF grid resolution on projected changes in mean annual runoff and evapotranspiration may be larger than the effects of hydrologic model choice, which surpasses the effects from re-scaled forcings. Scaling effects on projected variations in hydrologic signature measures were found to be generally smaller than those coming from WRF resolution; however, forcing aggregation in many cases reversed the direction of projected changes in hydrologic behavior.

From local hydrological process analysis to regional hydrological model application in Benin: Concept, results and perspectives

NASA Astrophysics Data System (ADS)

Bormann, H.; Faß, T.; Giertz, S.; Junge, B.; Diekkrüger, B.; Reichert, B.; Skowronek, A.

This paper presents the concept, first results and perspectives of the hydrological sub-project of the IMPETUS-Benin project which is part of the GLOWA program funded by the German ministry of education and research. In addition to the research concept, first results on field hydrology, pedology, hydrogeology and hydrological modelling are presented, focusing on the understanding of the actual hydrological processes. For analysing the processes a 30 km 2 catchment acting as a super test site was chosen which is assumed to be representative for the entire catchment of about 15,000 km 2. First results of the field investigations show that infiltration, runoff generation and soil erosion strongly depend on land cover and land use which again influence the soil properties significantly. A conceptual hydrogeological model has been developed summarising the process knowledge on runoff generation and subsurface hydrological processes. This concept model shows a dominance of fast runoff components (surface runoff and interflow), a groundwater recharge along preferential flow paths, temporary interaction between surface and groundwater and separate groundwater systems on different scales (shallow, temporary groundwater on local scale and permanent, deep groundwater on regional scale). The findings of intensive measurement campaigns on soil hydrology, groundwater dynamics and soil erosion have been integrated into different, scale-dependent hydrological modelling concepts applied at different scales in the target region (upper Ouémé catchment in Benin, about 15,000 km 2). The models have been applied and successfully validated. They will be used for integrated scenario analyses in the forthcoming project phase to assess the impacts of global change on the regional water cycle and on typical problem complexes such as food security in West African countries.

Using Unsupervised Learning to Unlock the Potential of Hydrologic Similarity

NASA Astrophysics Data System (ADS)

Chaney, N.; Newman, A. J.

2017-12-01

By clustering environmental data into representative hydrologic response units (HRUs), hydrologic similarity aims to harness the covariance between a system's physical environment and its hydrologic response to create reduced-order models. This is the primary approach through which sub-grid hydrologic processes are represented in large-scale models (e.g., Earth System Models). Although the possibilities of hydrologic similarity are extensive, its practical implementations have been limited to 1-d bins of oversimplistic metrics of hydrologic response (e.g., topographic index)—this is a missed opportunity. In this presentation we will show how unsupervised learning is unlocking the potential of hydrologic similarity; clustering methods enable generalized frameworks to effectively and efficiently harness the petabytes of global environmental data to robustly characterize sub-grid heterogeneity in large-scale models. To illustrate the potential that unsupervised learning has towards advancing hydrologic similarity, we introduce a hierarchical clustering algorithm (HCA) that clusters very high resolution (30-100 meters) elevation, soil, climate, and land cover data to assemble a domain's representative HRUs. These HRUs are then used to parameterize the sub-grid heterogeneity in land surface models; for this study we use the GFDL LM4 model—the land component of the GFDL Earth System Model. To explore HCA and its impacts on the hydrologic system we use a ¼ grid cell in southeastern California as a test site. HCA is used to construct an ensemble of 9 different HRU configurations—each configuration has a different number of HRUs; for each ensemble member LM4 is run between 2002 and 2014 with a 26 year spinup. The analysis of the ensemble of model simulations show that: 1) clustering the high-dimensional environmental data space leads to a robust representation of the role of the physical environment in the coupled water, energy, and carbon cycles at a relatively low number of HRUs; 2) the reduced-order model with around 300 HRUs effectively reproduces the fully distributed model simulation (30 meters) with less than 1/1000 of computational expense; 3) assigning each grid cell of the fully distributed grid to an HRU via HCA enables novel visualization methods for large-scale models—this has significant implications for how these models are applied and evaluated. We will conclude by outlining the potential that this work has within operational prediction systems including numerical weather prediction, Earth System models, and Early Warning systems.

Hydrologic Impacts of Climate Change: Quantification of Uncertainties (Alexander von Humboldt Medal Lecture)

NASA Astrophysics Data System (ADS)

Mujumdar, Pradeep P.

2014-05-01

Climate change results in regional hydrologic change. The three prominent signals of global climate change, viz., increase in global average temperatures, rise in sea levels and change in precipitation patterns convert into signals of regional hydrologic change in terms of modifications in water availability, evaporative water demand, hydrologic extremes of floods and droughts, water quality, salinity intrusion in coastal aquifers, groundwater recharge and other related phenomena. A major research focus in hydrologic sciences in recent years has been assessment of impacts of climate change at regional scales. An important research issue addressed in this context deals with responses of water fluxes on a catchment scale to the global climatic change. A commonly adopted methodology for assessing the regional hydrologic impacts of climate change is to use the climate projections provided by the General Circulation Models (GCMs) for specified emission scenarios in conjunction with the process-based hydrologic models to generate the corresponding hydrologic projections. The scaling problem arising because of the large spatial scales at which the GCMs operate compared to those required in distributed hydrologic models, and their inability to satisfactorily simulate the variables of interest to hydrology are addressed by downscaling the GCM simulations to hydrologic scales. Projections obtained with this procedure are burdened with a large uncertainty introduced by the choice of GCMs and emission scenarios, small samples of historical data against which the models are calibrated, downscaling methods used and other sources. Development of methodologies to quantify and reduce such uncertainties is a current area of research in hydrology. In this presentation, an overview of recent research carried out by the author's group on assessment of hydrologic impacts of climate change addressing scale issues and quantification of uncertainties is provided. Methodologies developed with conditional random fields, Dempster-Shafer theory, possibility theory, imprecise probabilities and non-stationary extreme value theory are discussed. Specific applications on uncertainty quantification in impacts on streamflows, evaporative water demands, river water quality and urban flooding are presented. A brief discussion on detection and attribution of hydrologic change at river basin scales, contribution of landuse change and likely alterations in return levels of hydrologic extremes is also provided.

Detecting hydrological changes through conceptual model

NASA Astrophysics Data System (ADS)

Viola, Francesco; Caracciolo, Domenico; Pumo, Dario; Francipane, Antonio; Valerio Noto, Leonardo

2015-04-01

Natural changes and human modifications in hydrological systems coevolve and interact in a coupled and interlinked way. If, on one hand, climatic changes are stochastic, non-steady, and affect the hydrological systems, on the other hand, human-induced changes due to over-exploitation of soils and water resources modifies the natural landscape, water fluxes and its partitioning. Indeed, the traditional assumption of static systems in hydrological analysis, which has been adopted for long time, fails whenever transient climatic conditions and/or land use changes occur. Time series analysis is a way to explore environmental changes together with societal changes; unfortunately, the not distinguishability between causes restrict the scope of this method. In order to overcome this limitation, it is possible to couple time series analysis with an opportune hydrological model, such as a conceptual hydrological model, which offers a schematization of complex dynamics acting within a basin. Assuming that model parameters represent morphological basin characteristics and that calibration is a way to detect hydrological signature at a specific moment, it is possible to argue that calibrating the model over different time windows could be a method for detecting potential hydrological changes. In order to test the capabilities of a conceptual model in detecting hydrological changes, this work presents different "in silico" experiments. A synthetic-basin is forced with an ensemble of possible future scenarios generated with a stochastic weather generator able to simulate steady and non-steady climatic conditions. The experiments refer to Mediterranean climate, which is characterized by marked seasonality, and consider the outcomes of the IPCC 5th report for describing climate evolution in the next century. In particular, in order to generate future climate change scenarios, a stochastic downscaling in space and time is carried out using realizations of an ensemble of General Circulation Models (GCMs) for the future scenarios 2046-2065 and 2081-2100. Land use changes (i.e., changes in the fraction of impervious area due to increasing urbanization) are explicitly simulated, while the reference hydrological responses are assessed by the spatially distributed, process-based hydrological model tRIBS, the TIN-based Real-time Integrated Basin Simulator. Several scenarios have been created, describing hypothetical centuries with steady conditions, climate change conditions, land use change conditions and finally complex conditions involving both transient climatic modifications and gradual land use changes. A conceptual lumped model, the EHSM (EcoHydrological Streamflow Model) is calibrated for the above mentioned scenarios with regard to different time-windows. The calibrated parameters show high sensitivity to anthropic variations in land use and/or climatic variability. Land use changes are clearly visible from parameters evolution especially when steady climatic conditions are considered. When the increase in urbanization is coupled with rainfall reduction the ability to detect human interventions through the analysis of conceptual model parameters is weakened.

Using aerial images for establishing a workflow for the quantification of water management measures

NASA Astrophysics Data System (ADS)

Leuschner, Annette; Merz, Christoph; van Gasselt, Stephan; Steidl, Jörg

2017-04-01

Quantified landscape characteristics, such as morphology, land use or hydrological conditions, play an important role for hydrological investigations as landscape parameters directly control the overall water balance. A powerful assimilation and geospatial analysis of remote sensing datasets in combination with hydrological modeling allows to quantify landscape parameters and water balances efficiently. This study focuses on the development of a workflow to extract hydrologically relevant data from aerial image datasets and derived products in order to allow an effective parametrization of a hydrological model. Consistent and self-contained data source are indispensable for achieving reasonable modeling results. In order to minimize uncertainties and inconsistencies, input parameters for modeling should be extracted from one remote-sensing dataset mainly if possbile. Here, aerial images have been chosen because of their high spatial and spectral resolution that permits the extraction of various model relevant parameters, like morphology, land-use or artificial drainage-systems. The methodological repertoire to extract environmental parameters range from analyses of digital terrain models, multispectral classification and segmentation of land use distribution maps and mapping of artificial drainage-systems based on spectral and visual inspection. The workflow has been tested for a mesoscale catchment area which forms a characteristic hydrological system of a young moraine landscape located in the state of Brandenburg, Germany. These dataset were used as input-dataset for multi-temporal hydrological modelling of water balances to detect and quantify anthropogenic and meteorological impacts. ArcSWAT, as a GIS-implemented extension and graphical user input interface for the Soil Water Assessment Tool (SWAT) was chosen. The results of this modeling approach provide the basis for anticipating future development of the hydrological system, and regarding system changes for the adaption of water resource management decisions.

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

Macroscale and Nanoscale Morphology Evolution during in Situ Spray Coating of Titania Films for Perovskite Solar Cells.

PubMed

Su, Bo; Caller-Guzman, Herbert A; Körstgens, Volker; Rui, Yichuan; Yao, Yuan; Saxena, Nitin; Santoro, Gonzalo; Roth, Stephan V; Müller-Buschbaum, Peter

2017-12-20

Mesoporous titania is a cheap and widely used material for photovoltaic applications. To enable a large-scale fabrication and a controllable pore size, we combined a block copolymer-assisted sol-gel route with spray coating to fabricate titania films, in which the block copolymer polystyrene-block-poly(ethylene oxide) (PS-b-PEO) is used as a structure-directing template. Both the macroscale and nanoscale are studied. The kinetics and thermodynamics of the spray deposition processes are simulated on a macroscale, which shows a good agreement with the large-scale morphology of the spray-coated films obtained in practice. On the nanoscale, the structure evolution of the titania films is probed with in situ grazing incidence small-angle X-ray scattering (GISAXS) during the spray process. The changes of the PS domain size depend not only on micellization but also on solvent evaporation during the spray coating. Perovskite (CH 3 NH 3 PbI 3 ) solar cells (PSCs) based on sprayed titania film are fabricated, which showcases the suitability of spray-deposited titania films for PSCs.

Effect of spherical Au nanoparticles on nanofriction and wear reduction in dry and liquid environments

PubMed Central

Maharaj, Dave

2012-01-01

Summary Nano-object additives are used in tribological applications as well as in various applications in liquids requiring controlled manipulation and targeting. On the macroscale, nanoparticles in solids and liquids have been shown to reduce friction and wear. On the nanoscale, atomic force microscopy (AFM) studies have been performed in single- and multiple-nanoparticle contact, in dry environments, to characterize friction forces and wear. However, limited studies in submerged liquid environments have been performed and further studies are needed. In this paper, spherical Au nanoparticles were studied for their effect on friction and wear under dry conditions and submerged in water. In single-nanoparticle contact, individual nanoparticles, deposited on silicon, were manipulated with a sharp tip and the friction force was determined. Multiple-nanoparticle contact sliding experiments were performed on nanoparticle-coated silicon with a glass sphere. Wear tests were performed on the nanoscale with AFM as well as on the macroscale by using a ball-on-flat tribometer to relate friction and wear reduction on the nanoscale and macroscale. Results indicate that the addition of Au nanoparticles reduces friction and wear. PMID:23213639

Modeling the Hydrological Regime of Turkana Lake (Kenya, Ethiopia) by Combining Spatially Distributed Hydrological Modeling and Remote Sensing Datasets

NASA Astrophysics Data System (ADS)

Anghileri, D.; Kaelin, A.; Peleg, N.; Fatichi, S.; Molnar, P.; Roques, C.; Longuevergne, L.; Burlando, P.

2017-12-01

Hydrological modeling in poorly gauged basins can benefit from the use of remote sensing datasets although there are challenges associated with the mismatch in spatial and temporal scales between catchment scale hydrological models and remote sensing products. We model the hydrological processes and long-term water budget of the Lake Turkana catchment, a transboundary basin between Kenya and Ethiopia, by integrating several remote sensing products into a spatially distributed and physically explicit model, Topkapi-ETH. Lake Turkana is the world largest desert lake draining a catchment of 145'500 km2. It has three main contributing rivers: the Omo river, which contributes most of the annual lake inflow, the Turkwel river, and the Kerio rivers, which contribute the remaining part. The lake levels have shown great variations in the last decades due to long-term climate fluctuations and the regulation of three reservoirs, Gibe I, II, and III, which significantly alter the hydrological seasonality. Another large reservoir is planned and may be built in the next decade, generating concerns about the fate of Lake Turkana in the long run because of this additional anthropogenic pressure and increasing evaporation driven by climate change. We consider different remote sensing datasets, i.e., TRMM-V7 for precipitation, MERRA-2 for temperature, as inputs to the spatially distributed hydrological model. We validate the simulation results with other remote sensing datasets, i.e., GRACE for total water storage anomalies, GLDAS-NOAH for soil moisture, ERA-Interim/Land for surface runoff, and TOPEX/Poseidon for satellite altimetry data. Results highlight how different remote sensing products can be integrated into a hydrological modeling framework accounting for their relative uncertainties. We also carried out simulations with the artificial reservoirs planned in the north part of the catchment and without any reservoirs, to assess their impacts on the catchment hydrological regime and the Lake Turkana level variability.

Stress-dependent grain size evolution of nanocrystalline Ni-W and its impact on friction behavior

DOE PAGES

Argibay, N.; Furnish, T. A.; Boyce, B. L.; ...

2016-06-07

The friction behavior of ultra-nanocrystalline Ni-W coatings was investigated. A critical stress threshold was identified below which friction remained low, and above which a time-dependent evolution toward higher friction behavior occurred. Founded on established plasticity models we propose a correlation between surface grain size and applied stress that can be used to predict the critical stress separating the two friction regimes. Lastly, this interpretation of plasticity models suggests that macro-scale low and high friction regimes are respectively associated with the nano-scale mechanisms of grain boundary and dislocation-mediated plasticity.

Hydrologic consistency as a basis for assessing complexity of monthly water balance models for the continental United States

NASA Astrophysics Data System (ADS)

Martinez, Guillermo F.; Gupta, Hoshin V.

2011-12-01

Methods to select parsimonious and hydrologically consistent model structures are useful for evaluating dominance of hydrologic processes and representativeness of data. While information criteria (appropriately constrained to obey underlying statistical assumptions) can provide a basis for evaluating appropriate model complexity, it is not sufficient to rely upon the principle of maximum likelihood (ML) alone. We suggest that one must also call upon a "principle of hydrologic consistency," meaning that selected ML structures and parameter estimates must be constrained (as well as possible) to reproduce desired hydrological characteristics of the processes under investigation. This argument is demonstrated in the context of evaluating the suitability of candidate model structures for lumped water balance modeling across the continental United States, using data from 307 snow-free catchments. The models are constrained to satisfy several tests of hydrologic consistency, a flow space transformation is used to ensure better consistency with underlying statistical assumptions, and information criteria are used to evaluate model complexity relative to the data. The results clearly demonstrate that the principle of consistency provides a sensible basis for guiding selection of model structures and indicate strong spatial persistence of certain model structures across the continental United States. Further work to untangle reasons for model structure predominance can help to relate conceptual model structures to physical characteristics of the catchments, facilitating the task of prediction in ungaged basins.

Quantifying the sources of uncertainty in an ensemble of hydrological climate-impact projections

NASA Astrophysics Data System (ADS)

Aryal, Anil; Shrestha, Sangam; Babel, Mukand S.

2018-01-01

The objective of this paper is to quantify the various sources of uncertainty in the assessment of climate change impact on hydrology in the Tamakoshi River Basin, located in the north-eastern part of Nepal. Multiple climate and hydrological models were used to simulate future climate conditions and discharge in the basin. The simulated results of future climate and river discharge were analysed for the quantification of sources of uncertainty using two-way and three-way ANOVA. The results showed that temperature and precipitation in the study area are projected to change in near- (2010-2039), mid- (2040-2069) and far-future (2070-2099) periods. Maximum temperature is likely to rise by 1.75 °C under Representative Concentration Pathway (RCP) 4.5 and by 3.52 °C under RCP 8.5. Similarly, the minimum temperature is expected to rise by 2.10 °C under RCP 4.5 and by 3.73 °C under RCP 8.5 by the end of the twenty-first century. Similarly, the precipitation in the study area is expected to change by - 2.15% under RCP 4.5 and - 2.44% under RCP 8.5 scenarios. The future discharge in the study area was projected using two hydrological models, viz. Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center's Hydrologic Modelling System (HEC-HMS). The SWAT model projected discharge is expected to change by small amount, whereas HEC-HMS model projected considerably lower discharge in future compared to the baseline period. The results also show that future climate variables and river hydrology contain uncertainty due to the choice of climate models, RCP scenarios, bias correction methods and hydrological models. During wet days, more uncertainty is observed due to the use of different climate models, whereas during dry days, the use of different hydrological models has a greater effect on uncertainty. Inter-comparison of the impacts of different climate models reveals that the REMO climate model shows higher uncertainty in the prediction of precipitation and, consequently, in the prediction of future discharge and maximum probable flood.

The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

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

Clark, Martyn P.; Bierkens, Marc F. P.; Samaniego, Luis

The diversity in hydrologic models has historically led to great controversy on the correct approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. Here, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We also illustrate how modeling advances have been made by groups using models of different type and complexity,more » and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.« less

The evolution of process-based hydrologic models: historical challenges and the collective quest for physical realism

DOE PAGES

Clark, Martyn P.; Bierkens, Marc F. P.; Samaniego, Luis; ...

2017-07-11

The diversity in hydrologic models has historically led to great controversy on the correct approach to process-based hydrologic modeling, with debates centered on the adequacy of process parameterizations, data limitations and uncertainty, and computational constraints on model analysis. Here, we revisit key modeling challenges on requirements to (1) define suitable model equations, (2) define adequate model parameters, and (3) cope with limitations in computing power. We outline the historical modeling challenges, provide examples of modeling advances that address these challenges, and define outstanding research needs. We also illustrate how modeling advances have been made by groups using models of different type and complexity,more » and we argue for the need to more effectively use our diversity of modeling approaches in order to advance our collective quest for physically realistic hydrologic models.« less

Storm water infiltration in a monitored green roof for hydrologic restoration.

PubMed

Palla, A; Sansalone, J J; Gnecco, I; Lanza, L G

2011-01-01

The objectives of this study are to provide detailed information about green roof performance in the Mediterranean climate (retained volume, peak flow reduction, runoff delay) and to identify a suitable modelling approach for describing the associated hydrologic response. Data collected during a 13-month monitoring campaign and a seasonal monitoring campaign (September-December 2008) at the green roof experimental site of the University of Genova (Italy) are presented together with results obtained in quantifying the green roof hydrologic performance. In order to examine the green roof hydrologic response, the SWMS_2D model, that solves the Richards' equation for two-dimensional saturated-unsaturated water flow, has been implemented. Modelling results confirm the suitability of the SWMS_2D model to properly describe the hydrologic response of the green roofs. The model adequately reproduces the hydrographs; furthermore, the predicted soil water content profile generally matches the observed values along a vertical profile where measurements are available.

Global change and terrestrial hydrology - A review

NASA Technical Reports Server (NTRS)

Dickinson, Robert E.

1991-01-01

This paper reviews the role of terrestrial hydrology in determining the coupling between the surface and atmosphere. Present experience with interactive numerical simulation is discussed and approaches to the inclusion of land hydrology in global climate models ae considered. At present, a wide range of answers as to expected changes in surface hydrology is given by nominally similar models. Studies of the effects of tropical deforestation and global warming illustrate this point.

Hydrological responses to dynamically and statistically downscaled climate model output

USGS Publications Warehouse

Wilby, R.L.; Hay, L.E.; Gutowski, W.J.; Arritt, R.W.; Takle, E.S.; Pan, Z.; Leavesley, G.H.; Clark, M.P.

2000-01-01

Daily rainfall and surface temperature series were simulated for the Animas River basin, Colorado using dynamically and statistically downscaled output from the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis. A distributed hydrological model was then applied to the downscaled data. Relative to raw NCEP output, downscaled climate variables provided more realistic stimulations of basin scale hydrology. However, the results highlight the sensitivity of modeled processes to the choice of downscaling technique, and point to the need for caution when interpreting future hydrological scenarios.

Critical zone evolution and the origins of organised complexity in watersheds

NASA Astrophysics Data System (ADS)

Harman, C.; Troch, P. A.; Pelletier, J.; Rasmussen, C.; Chorover, J.

2012-04-01

The capacity of the landscape to store and transmit water is the result of a historical trajectory of landscape, soil and vegetation development, much of which is driven by hydrology itself. Progress in geomorphology and pedology has produced models of surface and sub-surface evolution in soil-mantled uplands. These dissected, denuding modeled landscapes are emblematic of the kinds of dissipative self-organized flow structures whose hydrologic organization may also be understood by low-dimensional hydrologic models. They offer an exciting starting-point for examining the mapping between the long-term controls on landscape evolution and the high-frequency hydrologic dynamics. Here we build on recent theoretical developments in geomorphology and pedology to try to understand how the relative rates of erosion, sediment transport and soil development in a landscape determine catchment storage capacity and the relative dominance of runoff process, flow pathways and storage-discharge relationships. We do so by using a combination of landscape evolution models, hydrologic process models and data from a variety of sources, including the University of Arizona Critical Zone Observatory. A challenge to linking the landscape evolution and hydrologic model representations is the vast differences in the timescales implicit in the process representations. Furthermore the vast array of processes involved makes parameterization of such models an enormous challenge. The best data-constrained geomorphic transport and soil development laws only represent hydrologic processes implicitly, through the transport and weathering rate parameters. In this work we propose to avoid this problem by identifying the relationship between the landscape and soil evolution parameters and macroscopic climate and geological controls. These macroscopic controls (such as the aridity index) have two roles: 1) they express the water and energy constraints on the long-term evolution of the landscape system, and 2) they bound the range of plausible short-term hydroclimatic regimes that may drive a particular landscape's hydrologic dynamics. To ensure that the hydrologic dynamics implicit in the evolutionary parameters are compatible with the dynamics observed in the hydrologic modeling, a set of consistency checks based on flow process dominance are developed.

The implementation and validation of improved landsurface hydrology in an atmospheric general circulation model

NASA Technical Reports Server (NTRS)

Johnson, Kevin D.; Entekhabi, Dara; Eagleson, Peter S.

1991-01-01

Landsurface hydrological parameterizations are implemented in the NASA Goddard Institute for Space Studies (GISS) General Circulation Model (GCM). These parameterizations are: (1) runoff and evapotranspiration functions that include the effects of subgrid scale spatial variability and use physically based equations of hydrologic flux at the soil surface, and (2) a realistic soil moisture diffusion scheme for the movement of water in the soil column. A one dimensional climate model with a complete hydrologic cycle is used to screen the basic sensitivities of the hydrological parameterizations before implementation into the full three dimensional GCM. Results of the final simulation with the GISS GCM and the new landsurface hydrology indicate that the runoff rate, especially in the tropics is significantly improved. As a result, the remaining components of the heat and moisture balance show comparable improvements when compared to observations. The validation of model results is carried from the large global (ocean and landsurface) scale, to the zonal, continental, and finally the finer river basin scales.

Review article: Hydrological modeling in glacierized catchments of central Asia - status and challenges

NASA Astrophysics Data System (ADS)

Chen, Yaning; Li, Weihong; Fang, Gonghuan; Li, Zhi

2017-02-01

Meltwater from glacierized catchments is one of the most important water supplies in central Asia. Therefore, the effects of climate change on glaciers and snow cover will have increasingly significant consequences for runoff. Hydrological modeling has become an indispensable research approach to water resources management in large glacierized river basins, but there is a lack of focus in the modeling of glacial discharge. This paper reviews the status of hydrological modeling in glacierized catchments of central Asia, discussing the limitations of the available models and extrapolating these to future challenges and directions. After reviewing recent efforts, we conclude that the main sources of uncertainty in assessing the regional hydrological impacts of climate change are the unreliable and incomplete data sets and the lack of understanding of the hydrological regimes of glacierized catchments of central Asia. Runoff trends indicate a complex response to changes in climate. For future variation of water resources, it is essential to quantify the responses of hydrologic processes to both climate change and shrinking glaciers in glacierized catchments, and scientific focus should be on reducing uncertainties linked to these processes.

Advancing Collaboration through Hydrologic Data and Model Sharing

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Examination of Soil Moisture Retrieval Using SIR-C Radar Data and a Distributed Hydrological Model

NASA Technical Reports Server (NTRS)

Hsu, A. Y.; ONeill, P. E.; Wood, E. F.; Zion, M.

1997-01-01

A major objective of soil moisture-related hydrological-research during NASA's SIR-C/X-SAR mission was to determine and compare soil moisture patterns within humid watersheds using SAR data, ground-based measurements, and hydrologic modeling. Currently available soil moisture-inversion methods using active microwave data are only accurate when applied to bare and slightly vegetated surfaces. Moreover, as the surface dries down, the number of pixels that can provide estimated soil moisture by these radar inversion methods decreases, leading to less accuracy and, confidence in the retrieved soil moisture fields at the watershed scale. The impact of these errors in microwave- derived soil moisture on hydrological modeling of vegetated watersheds has yet to be addressed. In this study a coupled water and energy balance model operating within a topographic framework is used to predict surface soil moisture for both bare and vegetated areas. In the first model run, the hydrological model is initialized using a standard baseflow approach, while in the second model run, soil moisture values derived from SIR-C radar data are used for initialization. The results, which compare favorably with ground measurements, demonstrate the utility of combining radar-derived surface soil moisture information with basin-scale hydrological modeling.

Integrating macro and micro scale approaches in the agent-based modeling of residential dynamics

NASA Astrophysics Data System (ADS)

Saeedi, Sara

2018-06-01

With the advancement of computational modeling and simulation (M&S) methods as well as data collection technologies, urban dynamics modeling substantially improved over the last several decades. The complex urban dynamics processes are most effectively modeled not at the macro-scale, but following a bottom-up approach, by simulating the decisions of individual entities, or residents. Agent-based modeling (ABM) provides the key to a dynamic M&S framework that is able to integrate socioeconomic with environmental models, and to operate at both micro and macro geographical scales. In this study, a multi-agent system is proposed to simulate residential dynamics by considering spatiotemporal land use changes. In the proposed ABM, macro-scale land use change prediction is modeled by Artificial Neural Network (ANN) and deployed as the agent environment and micro-scale residential dynamics behaviors autonomously implemented by household agents. These two levels of simulation interacted and jointly promoted urbanization process in an urban area of Tehran city in Iran. The model simulates the behavior of individual households in finding ideal locations to dwell. The household agents are divided into three main groups based on their income rank and they are further classified into different categories based on a number of attributes. These attributes determine the households' preferences for finding new dwellings and change with time. The ABM environment is represented by a land-use map in which the properties of the land parcels change dynamically over the simulation time. The outputs of this model are a set of maps showing the pattern of different groups of households in the city. These patterns can be used by city planners to find optimum locations for building new residential units or adding new services to the city. The simulation results show that combining macro- and micro-level simulation can give full play to the potential of the ABM to understand the driving mechanism of urbanization and provide decision-making support for urban management.

Benchmarking hydrological model predictive capability for UK River flows and flood peaks.

NASA Astrophysics Data System (ADS)

Lane, Rosanna; Coxon, Gemma; Freer, Jim; Wagener, Thorsten

2017-04-01

Data and hydrological models are now available for national hydrological analyses. However, hydrological model performance varies between catchments, and lumped, conceptual models are not able to produce adequate simulations everywhere. This study aims to benchmark hydrological model performance for catchments across the United Kingdom within an uncertainty analysis framework. We have applied four hydrological models from the FUSE framework to 1128 catchments across the UK. These models are all lumped models and run at a daily timestep, but differ in the model structural architecture and process parameterisations, therefore producing different but equally plausible simulations. We apply FUSE over a 20 year period from 1988-2008, within a GLUE Monte Carlo uncertainty analyses framework. Model performance was evaluated for each catchment, model structure and parameter set using standard performance metrics. These were calculated both for the whole time series and to assess seasonal differences in model performance. The GLUE uncertainty analysis framework was then applied to produce simulated 5th and 95th percentile uncertainty bounds for the daily flow time-series and additionally the annual maximum prediction bounds for each catchment. The results show that the model performance varies significantly in space and time depending on catchment characteristics including climate, geology and human impact. We identify regions where models are systematically failing to produce good results, and present reasons why this could be the case. We also identify regions or catchment characteristics where one model performs better than others, and have explored what structural component or parameterisation enables certain models to produce better simulations in these catchments. Model predictive capability was assessed for each catchment, through looking at the ability of the models to produce discharge prediction bounds which successfully bound the observed discharge. These results improve our understanding of the predictive capability of simple conceptual hydrological models across the UK and help us to identify where further effort is needed to develop modelling approaches to better represent different catchment and climate typologies.

Improving flood forecasting capability of physically based distributed hydrological model by parameter optimization

NASA Astrophysics Data System (ADS)

Chen, Y.; Li, J.; Xu, H.

2015-10-01

Physically based distributed hydrological models discrete the terrain of the whole catchment into a number of grid cells at fine resolution, and assimilate different terrain data and precipitation to different cells, and are regarded to have the potential to improve the catchment hydrological processes simulation and prediction capability. In the early stage, physically based distributed hydrological models are assumed to derive model parameters from the terrain properties directly, so there is no need to calibrate model parameters, but unfortunately, the uncertanties associated with this model parameter deriving is very high, which impacted their application in flood forecasting, so parameter optimization may also be necessary. There are two main purposes for this study, the first is to propose a parameter optimization method for physically based distributed hydrological models in catchment flood forecasting by using PSO algorithm and to test its competence and to improve its performances, the second is to explore the possibility of improving physically based distributed hydrological models capability in cathcment flood forecasting by parameter optimization. In this paper, based on the scalar concept, a general framework for parameter optimization of the PBDHMs for catchment flood forecasting is first proposed that could be used for all PBDHMs. Then, with Liuxihe model as the study model, which is a physically based distributed hydrological model proposed for catchment flood forecasting, the improverd Particle Swarm Optimization (PSO) algorithm is developed for the parameter optimization of Liuxihe model in catchment flood forecasting, the improvements include to adopt the linear decreasing inertia weight strategy to change the inertia weight, and the arccosine function strategy to adjust the acceleration coefficients. This method has been tested in two catchments in southern China with different sizes, and the results show that the improved PSO algorithm could be used for Liuxihe model parameter optimization effectively, and could improve the model capability largely in catchment flood forecasting, thus proven that parameter optimization is necessary to improve the flood forecasting capability of physically based distributed hydrological model. It also has been found that the appropriate particle number and the maximum evolution number of PSO algorithm used for Liuxihe model catchment flood forcasting is 20 and 30, respectively.

Understanding the Impacts of Climate Change and Land Use Dynamics Using a Fully Coupled Hydrologic Feedback Model between Surface and Subsurface Systems

NASA Astrophysics Data System (ADS)

Park, C.; Lee, J.; Koo, M.

2011-12-01

Climate is the most critical driving force of the hydrologic system of the Earth. Since the industrial revolution, the impacts of anthropogenic activities to the Earth environment have been expanded and accelerated. Especially, the global emission of carbon dioxide into the atmosphere is known to have significantly increased temperature and affected the hydrologic system. Many hydrologists have contributed to the studies regarding the climate change on the hydrologic system since the Intergovernmental Panel on Climate Change (IPCC) was created in 1988. Among many components in the hydrologic system groundwater and its response to the climate change and anthropogenic activities are not fully understood due to the complexity of subsurface conditions between the surface and the groundwater table. A new spatio-temporal hydrologic model has been developed to estimate the impacts of climate change and land use dynamics on the groundwater. The model consists of two sub-models: a surface model and a subsurface model. The surface model involves three surface processes: interception, runoff, and evapotranspiration, and the subsurface model does also three subsurface processes: soil moisture balance, recharge, and groundwater flow. The surface model requires various input data including land use, soil types, vegetation types, topographical elevations, and meteorological data. The surface model simulates daily hydrological processes for rainfall interception, surface runoff varied by land use change and crop growth, and evapotranspiration controlled by soil moisture balance. The daily soil moisture balance is a key element to link two sub-models as it calculates infiltration and groundwater recharge by considering a time delay routing through a vadose zone down to the groundwater table. MODFLOW is adopted to simulate groundwater flow and interaction with surface water components as well. The model is technically flexible to add new model or modify existing model as it is developed with an object-oriented language - Python. The model also can easily be localized by simple modification of soil and crop properties. The actual application of the model after calibration was successful and results showed reliable water balance and interaction between the surface and subsurface hydrologic systems.

Generalized Likelihood Uncertainty Estimation (GLUE) Using Multi-Optimization Algorithm as Sampling Method

NASA Astrophysics Data System (ADS)

Wang, Z.

2015-12-01

For decades, distributed and lumped hydrological models have furthered our understanding of hydrological system. The development of hydrological simulation in large scale and high precision elaborated the spatial descriptions and hydrological behaviors. Meanwhile, the new trend is also followed by the increment of model complexity and number of parameters, which brings new challenges of uncertainty quantification. Generalized Likelihood Uncertainty Estimation (GLUE) has been widely used in uncertainty analysis for hydrological models referring to Monte Carlo method coupled with Bayesian estimation. However, the stochastic sampling method of prior parameters adopted by GLUE appears inefficient, especially in high dimensional parameter space. The heuristic optimization algorithms utilizing iterative evolution show better convergence speed and optimality-searching performance. In light of the features of heuristic optimization algorithms, this study adopted genetic algorithm, differential evolution, shuffled complex evolving algorithm to search the parameter space and obtain the parameter sets of large likelihoods. Based on the multi-algorithm sampling, hydrological model uncertainty analysis is conducted by the typical GLUE framework. To demonstrate the superiority of the new method, two hydrological models of different complexity are examined. The results shows the adaptive method tends to be efficient in sampling and effective in uncertainty analysis, providing an alternative path for uncertainty quantilization.

Modeling hydrology and in-stream transport on drained forested lands in coastal Carolinas, U.S.A.

Treesearch

Devendra Amatya

2005-01-01

This study summarizes the successional development and testing of forest hydrologic models based on DRAINMOD that predicts the hydrology of low-gradient poorly drained watersheds as affected by land management and climatic variation. The field scale (DRAINLOB) and watershed-scale in-stream routing (DRAINWAT) models were successfully tested with water table and outflow...

A comparison of MIKE SHE and DRAINMOD for modeling forested wetland hydrology in coastal South Carolina, USA

Treesearch

Zhaohua Dai; Devendra M. Amatya; Ge Sun; Carl C. Trettin; Changsheng Li; Harbin Li

2010-01-01

Models are widely used to assess hydrologic impacts of land-management, land-use change and climate change. Two hydrologic models with different spatial scales, MIKE SHE (spatially distributed, watershed-scale) and DRAINMOD (lumped, fieldscale), were compared in terms of their performance in predicting stream flow and water table depth in a first-order forested...

Bi-criteria evaluation of the MIKE SHE model for a forested watershed on the South Carolina coastal plain

Treesearch

Z. Dai; C. Li; C. Trettin; G. Sun; D. Amatya; H. Li

2010-01-01

Hydrological models are important tools for effective management, conservation and restoration of forested wetlands. The objective of this study was to test a distributed hydrological model, MIKE SHE, by using bi-criteria (i.e., two measurable variables, streamflow and water table depth) to describe the hydrological processes in a forested watershed that is...

Simulation of hydrologic influences on wetland ecosystem succession. Master's thesis

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

Pompilio, R.A.

1994-09-01

This research focuses on the development of a simulation model to determine the affects of hydrological influences on a wetland ecosystem. The model allows perturbations to the inputs of various wetland data which in turn, influences the successional development of the ecosystem. This research consisted of converting a grassland ecosystem model to one which simulates wetland conditions. The critical factor in determining the success of wetland creation is the hydrology of the system. There are four of the areas of the original model which are affected by the hydrology. The model measures the health or success of the ecosystem throughmore » the measurement of the systems gross plant production, the respiration and the net primary production of biomass. Altering the auxiliary variables of water level and the rate of flow through the system explicitly details the affects hydrologic influences on those production rates. Ten case tests depicting exogenous perturbations of the hydrology were run to identify these affects. Although the tests dealt with the fluctuation of water through the system, any one of the auxiliary variables in the model could be changed to reflect site specific data. Productivity, Hazardous material management, Hazardous material pharmacy.« less

Tracking unaccounted water use in data sparse arid environment

NASA Astrophysics Data System (ADS)

Hafeez, M. M.; Edraki, M.; Ullah, M. K.; Chemin, Y.; Sixsmith, J.; Faux, R.

2009-12-01

Hydrological knowledge of irrigated farms within the inundation plains of the Murray Darling Basin (MDB) is very limited in quality and reliability of the observation network that has been declining rapidly over the past decade. This paper focuses on Land Surface Diversions (LSD) that encompass all forms of surface water diversion except the direct extraction of water from rivers, watercourses and lakes by farmers for the purposes of irrigation and stock and domestic supply. Its accurate measurement is very challenging, due to the practical difficulties associated with separating the different components of LSD and estimating them accurately for a large catchment. The inadequacy of current methods of measuring and monitoring LSD poses severe limitations on existing and proposed policies for managing such diversions. It is commonly believed that LSD comprises 20-30% of total diversions from river valleys in the MDB areas. But, scientific estimates of LSD do not exist, because they were considered unimportant prior the onset of recent draught in Australia. There is a need to develop hydrological water balance models through the coupling of hydrological variables derived from on ground hydrological measurements and remote sensing techniques to accurately model LSD. Typically, the hydrological water balance components for farm/catchment scale models includes: irrigation inflow, outflow, rainfall, runoff, evapotranspiration, soil moisture change and deep percolation. The actual evapotranspiration (ETa) is the largest and single most important component of hydrological water balance model. An accurate quantification of all components of hydrological water balance model at farm/catchment scale is of prime importance to estimate the volume of LSD. A hydrological water balance model is developed to calculate LSD at 6 selected pilot farms. The catchment hydrological water balance model is being developed by using selected parameters derived from hydrological water balance model at farm scale. LSD results obtained through the modelling process have been compared with LSD estimates measured with the ground observed data at 6 pilot farms. The differences between the values are between 3 to 5 percent of the water inputs which is within the confidence limit expected from such analysis. Similarly, the LSD values at the catchment scale have been estimated with a great confidence. The hydrological water balance models at farm and catchment scale provide reliable quantification of LSD. Improved LSD estimates can guide water management decisions at farm to catchment scale and could be instrumental for enhancing the integrity of the water allocation process and making them fairer and equitable across stakeholders.

Microhabitats in the tropics buffer temperature in a globally coherent manner.

PubMed

Scheffers, Brett R; Evans, Theodore A; Williams, Stephen E; Edwards, David P

2014-12-01

Vegetated habitats contain a variety of fine-scale features that can ameliorate temperate extremes. These buffered microhabitats may be used by species to evade extreme weather and novel climates in the future. Yet, the magnitude and extent of this buffering on a global scale remains unknown. Across all tropical continents and using 36 published studies, we assessed temperature buffering from within microhabitats across various habitat strata and structures (e.g. soil, logs, epiphytes and tree holes) and compared them to non-buffered macro-scale ambient temperatures (the thermal control). Microhabitats buffered temperature by 3.9 °C and reduced maximum temperatures by 3.5 °C. Buffering was most pronounced in tropical lowlands where temperatures were most variable. With the expected increase in extreme weather events, microhabitats should provide species with a local layer of protection that is not captured by traditional climate assessments, which are typically derived from macro-scale temperatures (e.g. satellites). Our data illustrate the need for a next generation of predictive models that account for species' ability to move within microhabitats to exploit favourable buffered microclimates. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

How the morphology of dusts influences packing density in small solar system bodies

NASA Astrophysics Data System (ADS)

Zangmeister, C.; Radney, J. G.; Zachariah, M. R.

2014-12-01

Large planetary seedlings, comets, and nanoscale soot particles are made from rigid, aggregated subunits that are compacted under low compression into larger structures spanning over 10 orders of magnitude in dimensional space. Here, we demonstrate that the packing density (Φf) of compacted rigid aggregates is independent of spatial scale for systems under weak compaction, a regime that includes small solar system bodies. The Φf of rigid aggregated structures across 6 orders of magnitude were measured using nanoscale spherical soot aerosol composed of aggregates with ≈ 17 nm monomeric subunits and aggregates made from uniform monomeric 6 mm spherical subunits at the macroscale. We find Φf = 0.36 ± 0.02 at both the nano- and macroscale. These values are remarkably similar to qf observed for comet nuclei and measured values of other rigid aggregated systems across a wide variety of spatial and formative conditions. We present a packing model that incorporates the aggregate morphology and show that Φf is independent of both monomer and aggregate size. These observations suggest thatqf of rigid aggregates is independent of spatial dimension across varied formative conditions ranging from interstellar space to pharmaceutical manufacturing.

Causal Scale of Rotors in a Cardiac System

NASA Astrophysics Data System (ADS)

Ashikaga, Hiroshi; Prieto-Castrillo, Francisco; Kawakatsu, Mari; Dehghani, Nima

2018-04-01

Rotors of spiral waves are thought to be one of the potential mechanisms that maintain atrial fibrillation (AF). However, disappointing clinical outcomes of rotor mapping and ablation to eliminate AF raise a serious doubt on rotors as a macro-scale mechanism that causes the micro-scale behavior of individual cardiomyocytes to maintain spiral waves. In this study, we aimed to elucidate the causal relationship between rotors and spiral waves in a numerical model of cardiac excitation. To accomplish the aim, we described the system in a series of spatiotemporal scales by generating a renormalization group, and evaluated the causal architecture of the system by quantifying causal emergence. Causal emergence is an information-theoretic metric that quantifies emergence or reduction between micro- and macro-scale behaviors of a system by evaluating effective information at each scale. We found that the cardiac system with rotors has a spatiotemporal scale at which effective information peaks. A positive correlation between the number of rotors and causal emergence was observed only up to the scale of peak causation. We conclude that rotors are not the universal mechanism to maintain spiral waves at all spatiotemporal scales. This finding may account for the conflicting benefit of rotor ablation in clinical studies.

A Novel Macroscale Acoustic Device for Blood Filtration.

PubMed

Dutra, Brian; Carmen Mora, Maria; Gerhardson, Tyler I; Sporbert, Brianna; Dufresne, Alexandre; Bittner, Katharine R; Lovewell, Carolanne; Rust, Michael J; Tirabassi, Michael V; Masi, Louis; Lipkens, Bart; Kennedy, Daniel R

2018-03-01

Retransfusion of a patient's own shed blood during cardiac surgery is attractive since it reduces the need for allogeneic transfusion, minimizes cost, and decreases transfusion related morbidity. Evidence suggests that lipid micro-emboli associated with the retransfusion of the shed blood are the predominant causes of the neurocognitive disorders. We have developed a novel acoustophoretic filtration system that can remove lipids from blood at clinically relevant flow rates. Unlike other acoustophoretic separation systems, this ultrasound technology works at the macroscale, and is therefore able to process larger flow rates than typical micro-electromechanical system (MEMS) scale acoustophoretic separation devices. In this work, we have first demonstrated the systematic design of the acoustic device and its optimization, followed by examining the feasibility of the device to filter lipids from the system. Then, we demonstrate the effects of the acoustic waves on the shed blood; examining hemolysis using both haptoglobin formation and lactate dehydrogenase release, as well as the potential of platelet aggregation or inflammatory cascade activation. Finally, in a porcine surgical model, we determined the potential viability of acoustic trapping as a blood filtration technology, as the animal responded to redelivered blood by increasing both systemic and mean arterial blood pressure.

Diagnosis of the hydrology of a small Arctic basin at the tundra-taiga transition using a physically based hydrological model

NASA Astrophysics Data System (ADS)

Krogh, Sebastian A.; Pomeroy, John W.; Marsh, Philip

2017-07-01

A better understanding of cold regions hydrological processes and regimes in transitional environments is critical for predicting future Arctic freshwater fluxes under climate and vegetation change. A physically based hydrological model using the Cold Regions Hydrological Model platform was created for a small Arctic basin in the tundra-taiga transition region. The model represents snow redistribution and sublimation by wind and vegetation, snowmelt energy budget, evapotranspiration, subsurface flow through organic terrain, infiltration to frozen soils, freezing and thawing of soils, permafrost and streamflow routing. The model was used to reconstruct the basin water cycle over 28 years to understand and quantify the mass fluxes controlling its hydrological regime. Model structure and parameters were set from the current understanding of Arctic hydrology, remote sensing, field research in the basin and region, and calibration against streamflow observations. Calibration was restricted to subsurface hydraulic and storage parameters. Multi-objective evaluation of the model using observed streamflow, snow accumulation and ground freeze/thaw state showed adequate simulation. Significant spatial variability in the winter mass fluxes was found between tundra, shrubs and forested sites, particularly due to the substantial blowing snow redistribution and sublimation from the wind-swept upper basin, as well as sublimation of canopy intercepted snow from the forest (about 17% of snowfall). At the basin scale, the model showed that evapotranspiration is the largest loss of water (47%), followed by streamflow (39%) and sublimation (14%). The models streamflow performance sensitivity to a set of parameter was analysed, as well as the mean annual mass balance uncertainty associated with these parameters.

Combining Empirical and Stochastic Models for Extreme Floods Estimation

NASA Astrophysics Data System (ADS)

Zemzami, M.; Benaabidate, L.

2013-12-01

Hydrological models can be defined as physical, mathematical or empirical. The latter class uses mathematical equations independent of the physical processes involved in the hydrological system. The linear regression and Gradex (Gradient of Extreme values) are classic examples of empirical models. However, conventional empirical models are still used as a tool for hydrological analysis by probabilistic approaches. In many regions in the world, watersheds are not gauged. This is true even in developed countries where the gauging network has continued to decline as a result of the lack of human and financial resources. Indeed, the obvious lack of data in these watersheds makes it impossible to apply some basic empirical models for daily forecast. So we had to find a combination of rainfall-runoff models in which it would be possible to create our own data and use them to estimate the flow. The estimated design floods would be a good choice to illustrate the difficulties facing the hydrologist for the construction of a standard empirical model in basins where hydrological information is rare. The construction of the climate-hydrological model, which is based on frequency analysis, was established to estimate the design flood in the Anseghmir catchments, Morocco. The choice of using this complex model returns to its ability to be applied in watersheds where hydrological information is not sufficient. It was found that this method is a powerful tool for estimating the design flood of the watershed and also other hydrological elements (runoff, volumes of water...).The hydrographic characteristics and climatic parameters were used to estimate the runoff, water volumes and design flood for different return periods.

The Canadian Hydrological Model (CHM): A multi-scale, variable-complexity hydrological model for cold regions

NASA Astrophysics Data System (ADS)

Marsh, C.; Pomeroy, J. W.; Wheater, H. S.

2016-12-01

There is a need for hydrological land surface schemes that can link to atmospheric models, provide hydrological prediction at multiple scales and guide the development of multiple objective water predictive systems. Distributed raster-based models suffer from an overrepresentation of topography, leading to wasted computational effort that increases uncertainty due to greater numbers of parameters and initial conditions. The Canadian Hydrological Model (CHM) is a modular, multiphysics, spatially distributed modelling framework designed for representing hydrological processes, including those that operate in cold-regions. Unstructured meshes permit variable spatial resolution, allowing coarse resolutions at low spatial variability and fine resolutions as required. Model uncertainty is reduced by lessening the necessary computational elements relative to high-resolution rasters. CHM uses a novel multi-objective approach for unstructured triangular mesh generation that fulfills hydrologically important constraints (e.g., basin boundaries, water bodies, soil classification, land cover, elevation, and slope/aspect). This provides an efficient spatial representation of parameters and initial conditions, as well as well-formed and well-graded triangles that are suitable for numerical discretization. CHM uses high-quality open source libraries and high performance computing paradigms to provide a framework that allows for integrating current state-of-the-art process algorithms. The impact of changes to model structure, including individual algorithms, parameters, initial conditions, driving meteorology, and spatial/temporal discretization can be easily tested. Initial testing of CHM compared spatial scales and model complexity for a spring melt period at a sub-arctic mountain basin. The meshing algorithm reduced the total number of computational elements and preserved the spatial heterogeneity of predictions.

Assessment of NASA's Physiographic and Meteorological Datasets as Input to HSPF and SWAT Hydrological Models

NASA Technical Reports Server (NTRS)

Alacron, Vladimir J.; Nigro, Joseph D.; McAnally, William H.; OHara, Charles G.; Engman, Edwin Ted; Toll, David

2011-01-01

This paper documents the use of simulated Moderate Resolution Imaging Spectroradiometer land use/land cover (MODIS-LULC), NASA-LIS generated precipitation and evapo-transpiration (ET), and Shuttle Radar Topography Mission (SRTM) datasets (in conjunction with standard land use, topographical and meteorological datasets) as input to hydrological models routinely used by the watershed hydrology modeling community. The study is focused in coastal watersheds in the Mississippi Gulf Coast although one of the test cases focuses in an inland watershed located in northeastern State of Mississippi, USA. The decision support tools (DSTs) into which the NASA datasets were assimilated were the Soil Water & Assessment Tool (SWAT) and the Hydrological Simulation Program FORTRAN (HSPF). These DSTs are endorsed by several US government agencies (EPA, FEMA, USGS) for water resources management strategies. These models use physiographic and meteorological data extensively. Precipitation gages and USGS gage stations in the region were used to calibrate several HSPF and SWAT model applications. Land use and topographical datasets were swapped to assess model output sensitivities. NASA-LIS meteorological data were introduced in the calibrated model applications for simulation of watershed hydrology for a time period in which no weather data were available (1997-2006). The performance of the NASA datasets in the context of hydrological modeling was assessed through comparison of measured and model-simulated hydrographs. Overall, NASA datasets were as useful as standard land use, topographical , and meteorological datasets. Moreover, NASA datasets were used for performing analyses that the standard datasets could not made possible, e.g., introduction of land use dynamics into hydrological simulations

A sensitivity analysis of regional and small watershed hydrologic models

NASA Technical Reports Server (NTRS)

Ambaruch, R.; Salomonson, V. V.; Simmons, J. W.

1975-01-01

Continuous simulation models of the hydrologic behavior of watersheds are important tools in several practical applications such as hydroelectric power planning, navigation, and flood control. Several recent studies have addressed the feasibility of using remote earth observations as sources of input data for hydrologic models. The objective of the study reported here was to determine how accurately remotely sensed measurements must be to provide inputs to hydrologic models of watersheds, within the tolerances needed for acceptably accurate synthesis of streamflow by the models. The study objective was achieved by performing a series of sensitivity analyses using continuous simulation models of three watersheds. The sensitivity analysis showed quantitatively how variations in each of 46 model inputs and parameters affect simulation accuracy with respect to five different performance indices.

A dynamic nitrogen budget model of a Pacific Northwest salt ...

EPA Pesticide Factsheets

The role of salt marshes as either nitrogen sinks or sources in relation to their adjacent estuaries has been a focus of ecosystem service research for many decades. The complex hydrology of these systems is driven by tides, upland surface runoff, precipitation, evapotranspiration, and groundwater inputs, all of which can vary significantly on timescales ranging from sub-daily to seasonal. Additionally, many of these hydrologic drivers may vary with a changing climate. Due to this temporal variation in hydrology, it is difficult to represent salt marsh nitrogen budgets as steady-state models. A dynamic nitrogen budget model that varies based on hydrologic conditions may more accurately describe the role of salt marshes in nitrogen cycling. In this study we aim to develop a hydrologic model that is coupled with a process-based nitrogen model to simulate nitrogen dynamics at multiple temporal scales. To construct and validate our model we will use hydrologic and nitrogen species data collected from 2010 to present, from a 1.8 hectare salt marsh in the Yaquina Estuary, OR, USA. Hydrologic data include water table levels at two transects, upland tributary flow, tidal channel stage and flow, and vertical hydraulic head gradients. Nitrogen pool data include concentrations of nitrate and ammonium in porewater, tidal channel water, and extracted from soil cores. Nitrogen flux data include denitrification rates, nitrogen concentrations in upland runoff, and tida

Ensemble catchment hydrological modelling for climate change impact analysis

NASA Astrophysics Data System (ADS)

Vansteenkiste, Thomas; Ntegeka, Victor; Willems, Patrick

2014-05-01

It is vital to investigate how the hydrological model structure affects the climate change impact given that future changes not in the range for which the models were calibrated or validated are likely. Thus an ensemble modelling approach which involves a diversity of models with different structures such as spatial resolutions and process descriptions is crucial. The ensemble modelling approach was applied to a set of models: from the lumped conceptual models NAM, PDM and VHM, an intermediate detailed and distributed model WetSpa, to the highly detailed and fully distributed model MIKE-SHE. Explicit focus was given to the high and low flow extremes. All models were calibrated for sub flows and quick flows derived from rainfall and potential evapotranspiration (ETo) time series. In general, all models were able to produce reliable estimates of the flow regimes under the current climate for extreme peak and low flows. An intercomparison of the low and high flow changes under changed climatic conditions was made using climate scenarios tailored for extremes. Tailoring was important for two reasons. First, since the use of many scenarios was not feasible it was necessary to construct few scenarios that would reasonably represent the range of extreme impacts. Second, scenarios would be more informative as changes in high and low flows would be easily traced to changes of ETo and rainfall; the tailored scenarios are constructed using seasonal changes that are defined using different levels of magnitude (high, mean and low) for rainfall and ETo. After simulation of these climate scenarios in the five hydrological models, close agreement was found among the models. The different models predicted similar range of peak flow changes. For the low flows, however, the differences in the projected impact range by different hydrological models was larger, particularly for the drier scenarios. This suggests that the hydrological model structure is critical in low flow predictions, more than in high flow conditions. Hence, the mechanism of the slow flow component simulation requires further attention. It is concluded that a multi-model ensemble approach where different plausible model structures are applied, is extremely useful. It improves the reliability of climate change impact results and allows decision making to be based on uncertainty assessment that includes model structure related uncertainties. References: Ntegeka, V., Baguis, P., Roulin, E., Willems, P., 2014. Developing tailored climate change scenarios for hydrological impact assessments. Journal of Hydrology, 508C, 307-321 Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Willems, P., De Smedt, F., Batelaan, O., 2013. Climate change impact on river flows and catchment hydrology: a comparison of two spatially distributed models. Hydrological Processes, 27(25), 3649-3662. Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., Van Steenbergen, N., De Smedt, F., Batelaan, O., Pereira, F., Willems, P., 2014. Intercomparison of five lumped and distributed models for catchment runoff and extreme flow simulation. Journal of Hydrology, in press. Vansteenkiste, Th., Tavakoli, M., Ntegeka, V., De Smedt, F., Batelaan, O., Pereira, F., Willems, P., 2014. Intercomparison of climate scenario impact predictions by a lumped and distributed model ensemble. Journal of Hydrology, in revision.

Inspiring a Broader Socio-Hydrological Negotiation Approach With Interdisciplinary Field-Based Experience

NASA Astrophysics Data System (ADS)

Massuel, S.; Riaux, J.; Molle, F.; Kuper, M.; Ogilvie, A.; Collard, A.-L.; Leduc, C.; Barreteau, O.

2018-04-01

Socio-hydrology advanced the field of hydrology by considering humans and their activities as part of the water cycle, rather than as external drivers. Models are used to infer reproducible trends in human interactions with water resources. However, defining and handling water problems in this way may restrict the scope of such modeling approaches. We propose an interdisciplinary socio-hydrological approach to overcome this limit and complement modeling approaches. It starts from concrete field-based situations, combines disciplinary as well as local knowledge on water-society relationships, with the aim of broadening the hydrocentric analysis and modeling of water systems. The paper argues that an analysis of social dynamics linked to water is highly complementary to traditional hydrological tools but requires a negotiated and contextualized interdisciplinary approach to the representation and analysis of socio-hydro systems. This reflection emerged from experience gained in the field where a water-budget modeling framework failed to adequately incorporate the multiplicity of (nonhydrological) factors that determine the volumes of withdrawals for irrigation. The pathway subsequently explored was to move away from the hydrologic view of the phenomena and, in collaboration with social scientists, to produce a shared conceptualization of a coupled human-water system through a negotiated approach. This approach changed the way hydrological research issues were addressed and limited the number of strong assumptions needed for simplification in modeling. The proposed socio-hydrological approach led to a deeper understanding of the mechanisms behind local water-related problems and to debates on the interactions between social and political decisions and the dynamics of these problems.

The Hydrological Sensitivity to Global Warming and Solar Geoengineering Derived from Thermodynamic Constraints

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

Kleidon, Alex; Kravitz, Benjamin S.; Renner, Maik

2015-01-16

We derive analytic expressions of the transient response of the hydrological cycle to surface warming from an extremely simple energy balance model in which turbulent heat fluxes are constrained by the thermodynamic limit of maximum power. For a given magnitude of steady-state temperature change, this approach predicts the transient response as well as the steady-state change in surface energy partitioning and the hydrologic cycle. We show that the transient behavior of the simple model as well as the steady state hydrological sensitivities to greenhouse warming and solar geoengineering are comparable to results from simulations using highly complex models. Many ofmore » the global-scale hydrological cycle changes can be understood from a surface energy balance perspective, and our thermodynamically-constrained approach provides a physically robust way of estimating global hydrological changes in response to altered radiative forcing.« less

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

USDA-ARS?s Scientific Manuscript database

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

Evaluation of uncertainty in capturing the spatial variability and magnitudes of extreme hydrological events for the uMngeni catchment, South Africa

NASA Astrophysics Data System (ADS)

Kusangaya, Samuel; Warburton Toucher, Michele L.; van Garderen, Emma Archer

2018-02-01

Downscaled General Circulation Models (GCMs) output are used to forecast climate change and provide information used as input for hydrological modelling. Given that our understanding of climate change points towards an increasing frequency, timing and intensity of extreme hydrological events, there is therefore the need to assess the ability of downscaled GCMs to capture these extreme hydrological events. Extreme hydrological events play a significant role in regulating the structure and function of rivers and associated ecosystems. In this study, the Indicators of Hydrologic Alteration (IHA) method was adapted to assess the ability of simulated streamflow (using downscaled GCMs (dGCMs)) in capturing extreme river dynamics (high and low flows), as compared to streamflow simulated using historical climate data from 1960 to 2000. The ACRU hydrological model was used for simulating streamflow for the 13 water management units of the uMngeni Catchment, South Africa. Statistically downscaled climate models obtained from the Climate System Analysis Group at the University of Cape Town were used as input for the ACRU Model. Results indicated that, high flows and extreme high flows (one in ten year high flows/large flood events) were poorly represented both in terms of timing, frequency and magnitude. Simulated streamflow using dGCMs data also captures more low flows and extreme low flows (one in ten year lowest flows) than that captured in streamflow simulated using historical climate data. The overall conclusion was that although dGCMs output can reasonably be used to simulate overall streamflow, it performs poorly when simulating extreme high and low flows. Streamflow simulation from dGCMs must thus be used with caution in hydrological applications, particularly for design hydrology, as extreme high and low flows are still poorly represented. This, arguably calls for the further improvement of downscaling techniques in order to generate climate data more relevant and useful for hydrological applications such as in design hydrology. Nevertheless, the availability of downscaled climatic output provide the potential of exploring climate model uncertainties in different hydro climatic regions at local scales where forcing data is often less accessible but more accurate at finer spatial scales and with adequate spatial detail.

Modelling of in-stream nitrogen and phosphorus concentrations using different sampling strategies for calibration data

NASA Astrophysics Data System (ADS)

Jomaa, Seifeddine; Jiang, Sanyuan; Yang, Xiaoqiang; Rode, Michael

2016-04-01

It is known that a good evaluation and prediction of surface water pollution is mainly limited by the monitoring strategy and the capability of the hydrological water quality model to reproduce the internal processes. To this end, a compromise sampling frequency, which can reflect the dynamical behaviour of leached nutrient fluxes responding to changes in land use, agriculture practices and point sources, and appropriate process-based water quality model are required. The objective of this study was to test the identification of hydrological water quality model parameters (nitrogen and phosphorus) under two different monitoring strategies: (1) regular grab-sampling approach and (2) regular grab-sampling with additional monitoring during the hydrological events using automatic samplers. First, the semi-distributed hydrological water quality HYPE (Hydrological Predictions for the Environment) model was successfully calibrated (1994-1998) for discharge (NSE = 0.86), nitrate-N (lowest NSE for nitrate-N load = 0.69), particulate phosphorus and soluble phosphorus in the Selke catchment (463 km2, central Germany) for the period 1994-1998 using regular grab-sampling approach (biweekly to monthly for nitrogen and phosphorus concentrations). Second, the model was successfully validated during the period 1999-2010 for discharge, nitrate-N, particulate-phosphorus and soluble-phosphorus (lowest NSE for soluble phosphorus load = 0.54). Results, showed that when additional sampling during the events with random grab-sampling approach was used (period 2011-2013), the hydrological model could reproduce only the nitrate-N and soluble phosphorus concentrations reasonably well. However, when additional sampling during the hydrological events was considered, the HYPE model could not represent the measured particulate phosphorus. This reflects the importance of suspended sediment during the hydrological events increasing the concentrations of particulate phosphorus. The HYPE model could reproduce the total phosphorus during the period 2011-2013 only when the sediment transport-related model parameters was re-identified again considering the automatic sampling during the high-flow conditions.

Use of hydrologic and hydrodynamic modeling for ecosystem restoration

USGS Publications Warehouse

Obeysekera, J.; Kuebler, L.; Ahmed, S.; Chang, M.-L.; Engel, V.; Langevin, C.; Swain, E.; Wan, Y.

2011-01-01

Planning and implementation of unprecedented projects for restoring the greater Everglades ecosystem are underway and the hydrologic and hydrodynamic modeling of restoration alternatives has become essential for success of restoration efforts. In view of the complex nature of the South Florida water resources system, regional-scale (system-wide) hydrologic models have been developed and used extensively for the development of the Comprehensive Everglades Restoration Plan. In addition, numerous subregional-scale hydrologic and hydrodynamic models have been developed and are being used for evaluating project-scale water management plans associated with urban, agricultural, and inland costal ecosystems. The authors provide a comprehensive summary of models of all scales, as well as the next generation models under development to meet the future needs of ecosystem restoration efforts in South Florida. The multiagency efforts to develop and apply models have allowed the agencies to understand the complex hydrologic interactions, quantify appropriate performance measures, and use new technologies in simulation algorithms, software development, and GIS/database techniques to meet the future modeling needs of the ecosystem restoration programs. Copyright ?? 2011 Taylor & Francis Group, LLC.

OHD/HL - Staff

Science.gov Websites

Laboratory Branches Hydrologic Software Engineering Branch (HSEB) Hydrologic Science and Modeling Branch (HSMB) General Info Publications Documentation Software Standard and Guidelines Contact Us HL Staff resources and services. Staff Directory Chief, Hydrology Laboratory; Chief, Hydrologic Software Engineering

Tracer-aided modelling to explore non-linearities in flow paths, hydrological connectivity and faecal contamination risk

NASA Astrophysics Data System (ADS)

Neill, A. J.; Tetzlaff, D.; Strachan, N.; Soulsby, C.

2016-12-01

The non-linearities of runoff generation processes are strongly influenced by the connectivity of hillslopes and channel networks, particularly where overland flow is an important runoff mechanism. Despite major advances in understanding hydrological connectivity and runoff generation, the role of connectivity in the contamination of potable water supplies by faecal pathogens from grazing animals remains unclear. This is a water quality issue with serious implications for public health. Here, we sought to understand the dynamics of hydrological connectivity, flow paths and linked faecal pathogen transport in a montane catchment in Scotland with high deer populations. We firstly calibrated, within an uncertainty framework, a parsimonious tracer-aided hydrological model to daily discharge and stream isotope data. The model, developed on the basis of past empirical and tracer studies, conceptualises the catchment as three interacting hydrological source areas (dynamic saturation zone, dynamic hillslope, and groundwater) for which water fluxes, water ages and storage-based connectivity can be simulated. We next coupled several faecal indicator organism (FIO; a common indicator of faecal pathogen contamination) behaviour and transport schemes to the robust hydrological models. A further calibration was then undertaken based on the ability of each coupled model to simulate daily FIO concentrations. This gave us a final set of coupled behavioural models from which we explored how in-stream FIO dynamics could be related to the changing connectivity between the three hydrological source areas, flow paths, water ages and consequent dominant runoff generation processes. We found that high levels of FIOs were transient and episodic, and strongly correlated with periods of high connectivity through overland flow. This non-linearity in connectivity and FIO flux was successfully captured within our dynamic, tracer-aided hydrological model.

Determining hydrological changes in a small Arctic treeline basin using cold regions hydrological modelling and a pseudo-global warming approach

NASA Astrophysics Data System (ADS)

Krogh, S. A.; Pomeroy, J. W.

2017-12-01

Increasing temperatures are producing higher rainfall ratios, shorter snow-covered periods, permafrost thaw, more shrub coverage, more northerly treelines and greater interaction between groundwater and surface flow in Arctic basins. How these changes will impact the hydrology of the Arctic treeline environment represents a great challenge. To diagnose the future hydrology along the current Arctic treeline, a physically based cold regions model was used to simulate the hydrology of a small basin near Inuvik, Northwest Territories, Canada. The hydrological model includes hydrological processes such as snow redistribution and sublimation by wind, canopy interception of snow/rain and sublimation/evaporation, snowmelt energy balance, active layer freeze/thaw, infiltration into frozen and unfrozen soils, evapotranspiration, horizontal flow through organic terrain and snowpack, subsurface flow and streamflow routing. The model was driven with weather simulated by a high-resolution (4 km) numerical weather prediction model under two scenarios: (1) control run, using ERA-Interim boundary conditions (2001-2013) and (2) future, using a Pseudo-Global Warming (PGW) approach based on the RCP8.5 projections perturbing the control run. Transient changes in vegetation based on recent observations and ecological expectations were then used to re-parameterise the model. Historical hydrological simulations were validated against daily streamflow, snow water equivalent and active layer thickness records, showing the model's suitability in this environment. Strong annual warming ( 6 °C) and more precipitation ( 20%) were simulated by the PGW scenario, with winter precipitation and fall temperature showing the largest seasonal increase. The joint impact of climate and transient vegetation changes on snow accumulation and redistribution, evapotranspiration, active layer development, runoff generation and hydrograph characteristics are analyzed and discussed.

The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

NASA Astrophysics Data System (ADS)

Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.

2014-08-01

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.

A Dynamic Hydrology-Critical Zone Framework for Rainfall-triggered Landslide Hazard Prediction

NASA Astrophysics Data System (ADS)

Dialynas, Y. G.; Foufoula-Georgiou, E.; Dietrich, W. E.; Bras, R. L.

2017-12-01

Watershed-scale coupled hydrologic-stability models are still in their early stages, and are characterized by important limitations: (a) either they assume steady-state or quasi-dynamic watershed hydrology, or (b) they simulate landslide occurrence based on a simple one-dimensional stability criterion. Here we develop a three-dimensional landslide prediction framework, based on a coupled hydrologic-slope stability model and incorporation of the influence of deep critical zone processes (i.e., flow through weathered bedrock and exfiltration to the colluvium) for more accurate prediction of the timing, location, and extent of landslides. Specifically, a watershed-scale slope stability model that systematically accounts for the contribution of driving and resisting forces in three-dimensional hillslope segments was coupled with a spatially-explicit and physically-based hydrologic model. The landslide prediction framework considers critical zone processes and structure, and explicitly accounts for the spatial heterogeneity of surface and subsurface properties that control slope stability, including soil and weathered bedrock hydrological and mechanical characteristics, vegetation, and slope morphology. To test performance, the model was applied in landslide-prone sites in the US, the hydrology of which has been extensively studied. Results showed that both rainfall infiltration in the soil and groundwater exfiltration exert a strong control on the timing and magnitude of landslide occurrence. We demonstrate the extent to which three-dimensional slope destabilizing factors, which are modulated by dynamic hydrologic conditions in the soil-bedrock column, control landslide initiation at the watershed scale.

Hydrological and geomorphological controls of malaria transmission

NASA Astrophysics Data System (ADS)

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

2013-01-01

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

Remote sensing applications to hydrologic modeling

NASA Technical Reports Server (NTRS)

Dozier, J.; Estes, J. E.; Simonett, D. S.; Davis, R.; Frew, J.; Marks, D.; Schiffman, K.; Souza, M.; Witebsky, E.

1977-01-01

An energy balance snowmelt model for rugged terrain was devised and coupled to a flow model. A literature review of remote sensing applications to hydrologic modeling was included along with a software development outline.

Hydrological signal in polar motion excitation from a combination of geophysical and gravimetric series

NASA Astrophysics Data System (ADS)

Nastula, Jolanta; Winska, Malgorzata; Salstein, David A.

2015-08-01

One can estimate the hydrological signal in polar motion excitation as a residual, namely the difference between observed geodetic excitation functions (Geodetic Angular Momentum, GAM) and the sum of Atmospheric Angular Momentum (AAM) and Oceanic Angular Momentum (OAM).The aim of this study is to find the optimal model and results for hydrological excitation functions in terms of their agreement with the computed difference between GAM and atmospheric and oceanic signals.The atmospheric and oceanic model-based data that we use in this study are the geophysical excitation functions of AAM, OAM available from the Special Bureaus for the Atmosphere and Oceans of the Geophysical Global Fluids Center (GGFC) of the International Earth Rotation and Reference Systems Service (IERS). For the atmosphere and ocean, these functions are based on the mass and motion fields of the fluids.Global models of land hydrology are used to estimate hydrological excitation functions of polar motion (Hydrological Angular Momentum - HAM). These HAM series are the mass of water substance determined from the various types of land-based hydrological reservoirs. In addition the HAM are estimated from spherical harmonic coefficients of the Earth’s gravity field. We use several sets of degree-2, order-1 harmonics of the Earth’s gravity field, derived from the Gravity Recovery and Climate Experiment (GRACE), Satellite Laser Ranging (SLR), and Global Navigation Satellite Systems (GNSS) data.Finally, these several different HAM series are used to determine the best model of hydrological excitation of polar motion. The model is found by looking for the combination of these series that fits the geodetic residuals using the least-square method.In addition, we will access model results from the Coupled Model Intercomparison Project, fifth experiment (CMIP-5) to examine atmospheric excitations from the twentieth century and estimates for the twenty-first century to see the possible signals and trends of these excitation series to help understand the potential range in the derived of hydrological excitation results.

ERM model analysis for adaptation to hydrological model errors

NASA Astrophysics Data System (ADS)

Baymani-Nezhad, M.; Han, D.

2018-05-01

Hydrological conditions are changed continuously and these phenomenons generate errors on flood forecasting models and will lead to get unrealistic results. Therefore, to overcome these difficulties, a concept called model updating is proposed in hydrological studies. Real-time model updating is one of the challenging processes in hydrological sciences and has not been entirely solved due to lack of knowledge about the future state of the catchment under study. Basically, in terms of flood forecasting process, errors propagated from the rainfall-runoff model are enumerated as the main source of uncertainty in the forecasting model. Hence, to dominate the exciting errors, several methods have been proposed by researchers to update the rainfall-runoff models such as parameter updating, model state updating, and correction on input data. The current study focuses on investigations about the ability of rainfall-runoff model parameters to cope with three types of existing errors, timing, shape and volume as the common errors in hydrological modelling. The new lumped model, the ERM model, has been selected for this study to evaluate its parameters for its use in model updating to cope with the stated errors. Investigation about ten events proves that the ERM model parameters can be updated to cope with the errors without the need to recalibrate the model.

Flexibility on storage-release based distributed hydrologic modeling with object-oriented approach

USDA-ARS?s Scientific Manuscript database

With the availability of advanced hydrologic data in the public domain such as remotely sensed and climate change scenario data, there is a need for a modeling framework that is capable of using these data to simulate and extend hydrologic processes with multidisciplinary approaches for sustainable ...

Floods in a changing climate

Treesearch

Theresa K. Andersen; Marshall J. Shepherd

2013-01-01

Atmospheric warming and associated hydrological changes have implications for regional flood intensity and frequency. Climate models and hydrological models have the ability to integrate various contributing factors and assess potential changes to hydrology at global to local scales through the century. This survey of floods in a changing climate reviews flood...

Bayesian inference of the groundwater depth threshold in a vegetation dynamic model: a case study, lower reach, Tarim River

USDA-ARS?s Scientific Manuscript database

The responses of eco-hydrological systems to anthropogenic and natural disturbances have attracted much attention in recent years. The coupling and simulating feedback between hydrological and ecological components have been realized in several recently developed eco-hydrological models. However, li...

Intercomparison of Multiscale Modeling Approaches in Simulating Subsurface Flow and Transport

NASA Astrophysics Data System (ADS)

Yang, X.; Mehmani, Y.; Barajas-Solano, D. A.; Song, H. S.; Balhoff, M.; Tartakovsky, A. M.; Scheibe, T. D.

2016-12-01

Hybrid multiscale simulations that couple models across scales are critical to advance predictions of the larger system behavior using understanding of fundamental processes. In the current study, three hybrid multiscale methods are intercompared: multiscale loose-coupling method, multiscale finite volume (MsFV) method and multiscale mortar method. The loose-coupling method enables a parallel workflow structure based on the Swift scripting environment that manages the complex process of executing coupled micro- and macro-scale models without being intrusive to the at-scale simulators. The MsFV method applies microscale and macroscale models over overlapping subdomains of the modeling domain and enforces continuity of concentration and transport fluxes between models via restriction and prolongation operators. The mortar method is a non-overlapping domain decomposition approach capable of coupling all permutations of pore- and continuum-scale models with each other. In doing so, Lagrange multipliers are used at interfaces shared between the subdomains so as to establish continuity of species/fluid mass flux. Subdomain computations can be performed either concurrently or non-concurrently depending on the algorithm used. All the above methods have been proven to be accurate and efficient in studying flow and transport in porous media. However, there has not been any field-scale applications and benchmarking among various hybrid multiscale approaches. To address this challenge, we apply all three hybrid multiscale methods to simulate water flow and transport in a conceptualized 2D modeling domain of the hyporheic zone, where strong interactions between groundwater and surface water exist across multiple scales. In all three multiscale methods, fine-scale simulations are applied to a thin layer of riverbed alluvial sediments while the macroscopic simulations are used for the larger subsurface aquifer domain. Different numerical coupling methods are then applied between scales and inter-compared. Comparisons are drawn in terms of velocity distributions, solute transport behavior, algorithm-induced numerical error and computing cost. The intercomparison work provides support for confidence in a variety of hybrid multiscale methods and motivates further development and applications.

Nonlinear Micromorphic Continuum Mechanics and Finite Strain Elastoplasticity

DTIC Science & Technology

2010-11-01

phenomenology at the micro and macroscales. More micromechanical analysis and experimental data are necessary to determine the microplasticity ...129) ᾱ∇χ L̄ = H̄∇χZ̄χ ,L̄ (130) where ˙̄γ∇χ is the microplastic gradient multiplier. 40 Remark 3. The main advantage to defining constitutively the...for macro and microplasticity (F̄ χ and Ḡχ with similar functional form as F̄ and Ḡ), but this is only for the example model presented here. It is

Towards methodical modelling: Differences between the structure and output dynamics of multiple conceptual models

NASA Astrophysics Data System (ADS)

Knoben, Wouter; Woods, Ross; Freer, Jim

2016-04-01

Conceptual hydrologic models consist of a certain arrangement of spatial and temporal dynamics consisting of stores, fluxes and transformation functions, depending on the modeller's choices and intended use. They have the advantages of being computationally efficient, being relatively easy model structures to reconfigure and having relatively low input data demands. This makes them well-suited for large-scale and large-sample hydrology, where appropriately representing the dominant hydrologic functions of a catchment is a main concern. Given these requirements, the number of parameters in the model cannot be too high, to avoid equifinality and identifiability issues. This limits the number and level of complexity of dominant hydrologic processes the model can represent. Specific purposes and places thus require a specific model and this has led to an abundance of conceptual hydrologic models. No structured overview of these models exists and there is no clear method to select appropriate model structures for different catchments. This study is a first step towards creating an overview of the elements that make up conceptual models, which may later assist a modeller in finding an appropriate model structure for a given catchment. To this end, this study brings together over 30 past and present conceptual models. The reviewed model structures are simply different configurations of three basic model elements (stores, fluxes and transformation functions), depending on the hydrologic processes the models are intended to represent. Differences also exist in the inner workings of the stores, fluxes and transformations, i.e. the mathematical formulations that describe each model element's intended behaviour. We investigate the hypothesis that different model structures can produce similar behavioural simulations. This can clarify the overview of model elements by grouping elements which are similar, which can improve model structure selection.

Hydrological model uncertainty due to spatial evapotranspiration estimation methods

NASA Astrophysics Data System (ADS)

Yu, Xuan; Lamačová, Anna; Duffy, Christopher; Krám, Pavel; Hruška, Jakub

2016-05-01

Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03‧N, 12°40‧E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

Towards an integrated model of floodplain hydrology representing feedbacks and anthropogenic effects

NASA Astrophysics Data System (ADS)

Andreadis, K.; Schumann, G.; Voisin, N.; O'Loughlin, F.; Tesfa, T. K.; Bates, P.

2017-12-01

The exchange of water between hillslopes, river channels and floodplain can be quite complex and the difficulty in capturing the mechanisms behind it is exacerbated by the impact of human activities such as irrigation and reservoir operations. Although there has been a vast body of work on modeling hydrological processes, most of the resulting models have been limited with regards to aspects of the coupled human-natural system. For example, hydrologic models that represent processes such as evapotranspiration, infiltration, interception and groundwater dynamics often neglect anthropogenic effects or do not adequately represent the inherently two-dimensional floodplain flow. We present an integrated modeling framework that is comprised of the Variable Infiltration Capacity (VIC) hydrology model, the LISFLOOD-FP hydrodynamic model, and the Water resources Management (WM) model. The VIC model solves the energy and water balance over a gridded domain and simulates a number of hydrologic features such as snow, frozen soils, lakes and wetlands, while also representing irrigation demand from cropland areas. LISFLOOD-FP solves an approximation of the Saint-Venant equations to efficiently simulate flow in river channels and the floodplain. The implementation of WM accommodates a variety of operating rules in reservoirs and withdrawals due to consumptive demands, allowing the successful simulation of regulated flow. The models are coupled so as to allow feedbacks between their corresponding processes, therefore providing the ability to test different hypotheses about the floodplain hydrology of large-scale basins. We test this integrated framework over the Zambezi River basin by simulating its hydrology from 2000-2010, and evaluate the results against remotely sensed observations. Finally, we examine the sensitivity of streamflow and water inundation to changes in reservoir operations, precipitation and temperature.

Using the cloud to speed-up calibration of watershed-scale hydrologic models (Invited)

NASA Astrophysics Data System (ADS)

Goodall, J. L.; Ercan, M. B.; Castronova, A. M.; Humphrey, M.; Beekwilder, N.; Steele, J.; Kim, I.

2013-12-01

This research focuses on using the cloud to address computational challenges associated with hydrologic modeling. One example is calibration of a watershed-scale hydrologic model, which can take days of execution time on typical computers. While parallel algorithms for model calibration exist and some researchers have used multi-core computers or clusters to run these algorithms, these solutions do not fully address the challenge because (i) calibration can still be too time consuming even on multicore personal computers and (ii) few in the community have the time and expertise needed to manage a compute cluster. Given this, another option for addressing this challenge that we are exploring through this work is the use of the cloud for speeding-up calibration of watershed-scale hydrologic models. The cloud used in this capacity provides a means for renting a specific number and type of machines for only the time needed to perform a calibration model run. The cloud allows one to precisely balance the duration of the calibration with the financial costs so that, if the budget allows, the calibration can be performed more quickly by renting more machines. Focusing specifically on the SWAT hydrologic model and a parallel version of the DDS calibration algorithm, we show significant speed-up time across a range of watershed sizes using up to 256 cores to perform a model calibration. The tool provides a simple web-based user interface and the ability to monitor the calibration job submission process during the calibration process. Finally this talk concludes with initial work to leverage the cloud for other tasks associated with hydrologic modeling including tasks related to preparing inputs for constructing place-based hydrologic models.

A comparison of hydrological deformation using GPS and global hydrological model for the Eurasian plate

NASA Astrophysics Data System (ADS)

Li, Zhen; Yue, Jianping; Li, Wang; Lu, Dekai; Li, Xiaogen

2017-08-01

The 0.5° × 0.5° gridded hydrological loading from Global Land Surface Discharge Model (LSDM) mass distributions is adopted for 32 GPS sites on the Eurasian plate from January 2010 to January 2014. When the heights of these sites that have been corrected for the effects of non-tidal atmospheric and ocean loading are adjusted by the hydrological loading deformation, more than one third of the root-mean-square (RMS) values of the GPS height variability become larger. After analyzing the results by continuous wavelet transform (CWT) and wavelet transform coherence (WTC), we confirm that hydrological loading primarily contributes to the annual variations in GPS heights. Further, the cross wavelet transform (XWT) is used to investigate the relative phase between the time series of GPS heights and hydrological deformation, and it is indicated that the annual oscillations in the two time series are physically related for some sites; other geophysical effect, GPS systematic errors and hydrological modeling errors could result in the phase asynchrony between GPS and hydrological loading signals for the other sites. Consequently, the phase asynchrony confirms that the annual fluctuations in GPS observations result from a combination of geophysical signals and systematic errors.

A Conceptual Model for Evaluating Hydrologic Connectivity in Geographically Isolated Wetlands

EPA Science Inventory

Knowledge about hydrologic connectivity between aquatic resources is critical to understanding and managing watershed hydrology and to the legal status of those resources. In particular, information is needed on the hydrologic connectivity and effects of geographically isolated ...

Linking statistically-and physically-based models for improved streamflow simulation in gaged and ungaged watersheds

Treesearch

Jacob LaFontaine; Lauren Hay; Stacey Archfield; William Farmer; Julie Kiang

2016-01-01

The U.S. Geological Survey (USGS) has developed a National Hydrologic Model (NHM) to support coordinated, comprehensive and consistent hydrologic model development, and facilitate the application of hydrologic simulations within the continental US. The portion of the NHM located within the Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO LCC) is...

A Conceptual Approach to Assimilating Remote Sensing Data to Improve Soil Moisture Profile Estimates in a Surface Flux/Hydrology Model. 3; Disaggregation

NASA Technical Reports Server (NTRS)

Caulfield, John; Crosson, William L.; Inguva, Ramarao; Laymon, Charles A.; Schamschula, Marius

1998-01-01

This is a followup on the preceding presentation by Crosson and Schamschula. The grid size for remote microwave measurements is much coarser than the hydrological model computational grids. To validate the hydrological models with measurements we propose mechanisms to disaggregate the microwave measurements to allow comparison with outputs from the hydrological models. Weighted interpolation and Bayesian methods are proposed to facilitate the comparison. While remote measurements occur at a large scale, they reflect underlying small-scale features. We can give continuing estimates of the small scale features by correcting the simple 0th-order, starting with each small-scale model with each large-scale measurement using a straightforward method based on Kalman filtering.

Using Advances in Research on Louisiana Coastal Restoration and Protection to Develop Undergraduate Hydrology Education Experiences Delivered via a Web Interface

NASA Astrophysics Data System (ADS)

Bodin, M.; Habib, E. H.; Meselhe, E. A.; Visser, J.; Chimmula, S.

2014-12-01

Utilizing advances in hydrologic research and technology, learning modules can be developed to deliver visual, case-based, data and simulation driven educational experiences. This paper focuses on the development of web modules based on case studies in Coastal Louisiana, one of three ecosystems that comprise an ongoing hydrology education online system called HydroViz. The Chenier Plain ecosystem in Coastal Louisiana provides an abundance of concepts and scenarios appropriate for use in many undergraduate water resource and hydrology curricula. The modules rely on a set of hydrologic data collected within the Chenier Plain along with inputs and outputs of eco-hydrology and vegetation-change simulation models that were developed to analyze different restoration and protection projects within the 2012 Louisiana Costal Master Plan. The modules begin by investigating the basic features of the basin and it hydrologic characteristics. The eco-hydrology model is then introduced along with its governing equations, numerical solution scheme and how it represents the study domain. Concepts on water budget in a coastal basin are then introduced using the simulation model inputs, outputs and boundary conditions. The complex relationships between salinity, water level and vegetation changes are then investigated through the use of the simulation models and associated field data. Other student activities focus on using the simulation models to evaluate tradeoffs and impacts of actual restoration and protection projects that were proposed as part of 2012 Louisiana Master Plan. The hands-on learning activities stimulate student learning of hydrologic and water management concepts by providing real-world context and opportunity to build fundamental knowledge as well as practical skills. The modules are delivered through a carefully designed user interface using open source and free technologies which enable wide dissemination and encourage adaptation by others.

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

NASA Technical Reports Server (NTRS)

Adler, Robert F.; Hong, Yang; Huffman, George J.

2006-01-01

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

Balancing model complexity and measurements in hydrology

NASA Astrophysics Data System (ADS)

Van De Giesen, N.; Schoups, G.; Weijs, S. V.

2012-12-01

The Data Processing Inequality implies that hydrological modeling can only reduce, and never increase, the amount of information available in the original data used to formulate and calibrate hydrological models: I(X;Z(Y)) ≤ I(X;Y). Still, hydrologists around the world seem quite content building models for "their" watersheds to move our discipline forward. Hydrological models tend to have a hybrid character with respect to underlying physics. Most models make use of some well established physical principles, such as mass and energy balances. One could argue that such principles are based on many observations, and therefore add data. These physical principles, however, are applied to hydrological models that often contain concepts that have no direct counterpart in the observable physical universe, such as "buckets" or "reservoirs" that fill up and empty out over time. These not-so-physical concepts are more like the Artificial Neural Networks and Support Vector Machines of the Artificial Intelligence (AI) community. Within AI, one quickly came to the realization that by increasing model complexity, one could basically fit any dataset but that complexity should be controlled in order to be able to predict unseen events. The more data are available to train or calibrate the model, the more complex it can be. Many complexity control approaches exist in AI, with Solomonoff inductive inference being one of the first formal approaches, the Akaike Information Criterion the most popular, and Statistical Learning Theory arguably being the most comprehensive practical approach. In hydrology, complexity control has hardly been used so far. There are a number of reasons for that lack of interest, the more valid ones of which will be presented during the presentation. For starters, there are no readily available complexity measures for our models. Second, some unrealistic simplifications of the underlying complex physics tend to have a smoothing effect on possible model outcomes, thereby preventing the most obvious results of over-fitting. Thirdly, dependence within and between time series poses an additional analytical problem. Finally, there are arguments to be made that the often discussed "equifinality" in hydrological models is simply a different manifestation of the lack of complexity control. In turn, this points toward a general idea, which is actually quite popular in sciences other than hydrology, that additional data gathering is a good way to increase the information content of our descriptions of hydrological reality.

Global operational hydrological forecasts through eWaterCycle

NASA Astrophysics Data System (ADS)

van de Giesen, Nick; Bierkens, Marc; Donchyts, Gennadii; Drost, Niels; Hut, Rolf; Sutanudjaja, Edwin

2015-04-01

Central goal of the eWaterCycle project (www.ewatercycle.org) is the development of an operational hyper-resolution hydrological global model. This model is able to produce 14 day ensemble forecasts based on a hydrological model and operational weather data (presently NOAA's Global Ensemble Forecast System). Special attention is paid to prediction of situations in which water related issues are relevant, such as floods, droughts, navigation, hydropower generation, and irrigation stress. Near-real time satellite data will be assimilated in the hydrological simulations, which is a feature that will be presented for the first time at EGU 2015. First, we address challenges that are mainly computer science oriented but have direct practical hydrological implications. An important feature in this is the use of existing standards and open-source software to the maximum extent possible. For example, we use the Community Surface Dynamics Modeling System (CSDMS) approach to coupling models (Basic Model Interface (BMI)). The hydrological model underlying the project is PCR-GLOBWB, built by Utrecht University. This is the motor behind the predictions and state estimations. Parts of PCR-GLOBWB have been re-engineered to facilitate running it in a High Performance Computing (HPC) environment, run parallel on multiple nodes, as well as to use BMI. Hydrological models are not very CPU intensive compared to, say, atmospheric models. They are, however, memory hungry due to the localized processes and associated effective parameters. To accommodate this memory need, especially in an ensemble setting, a variation on the traditional Ensemble Kalman Filter was developed that needs much less on-chip memory. Due to the operational nature, the coupling of the hydrological model with hydraulic models is very important. The idea is not to run detailed hydraulic routing schemes over the complete globe but to have on-demand simulation prepared off-line with respect to topography and parameterizations. This allows for very detailed simulations at hectare to meter scales, where and when this is needed. At EGU 2015, the operational global eWaterCycle model will be presented for the first time, including forecasts at high resolution, the innovative data assimilation approach, and on-demand coupling with hydraulic models.

Development of the Hydrological-Ecological Integrated watershed Flow Model (HEIFLOW): an application to the Heihe River Basin

NASA Astrophysics Data System (ADS)

Tian, Y.; Zheng, Y.; Zheng, C.; Han, F., Sr.

2017-12-01

Physically based and fully-distributed integrated hydrological models (IHMs) can quantitatively depict hydrological processes, both surface and subsurface, with sufficient spatial and temporal details. However, the complexity involved in pre-processing data and setting up models seriously hindered the wider application of IHMs in scientific research and management practice. This study introduces our design and development of Visual HEIFLOW, hereafter referred to as VHF, a comprehensive graphical data processing and modeling system for integrated hydrological simulation. The current version of VHF has been structured to accommodate an IHM named HEIFLOW (Hydrological-Ecological Integrated watershed-scale FLOW model). HEIFLOW is a model being developed by the authors, which has all typical elements of physically based and fully-distributed IHMs. It is based on GSFLOW, a representative integrated surface water-groundwater model developed by USGS. HEIFLOW provides several ecological modules that enable to simulate growth cycle of general vegetation and special plants (maize and populus euphratica). VHF incorporates and streamlines all key steps of the integrated modeling, and accommodates all types of GIS data necessary to hydrological simulation. It provides a GIS-based data processing framework to prepare an IHM for simulations, and has functionalities to flexibly display and modify model features (e.g., model grids, streams, boundary conditions, observational sites, etc.) and their associated data. It enables visualization and various spatio-temporal analyses of all model inputs and outputs at different scales (i.e., computing unit, sub-basin, basin, or user-defined spatial extent). The above system features, as well as many others, can significantly reduce the difficulty and time cost of building and using a complex IHM. The case study in the Heihe River Basin demonstrated the applicability of VHF for large scale integrated SW-GW modeling. Visualization and spatial-temporal analysis of the modeling results by HEIFLOW greatly facilitates our understanding on the complicated hydrologic cycle and relationship among the hydrological and ecological variables in the study area, and provides insights into the regional water resources management.

Hetero-cellular prototyping by synchronized multi-material bioprinting for rotary cell culture system.

PubMed

Snyder, Jessica; Son, Ae Rin; Hamid, Qudus; Wu, Honglu; Sun, Wei

2016-01-13

Bottom-up tissue engineering requires methodological progress of biofabrication to capture key design facets of anatomical arrangements across micro, meso and macro-scales. The diffusive mass transfer properties necessary to elicit stability and functionality require hetero-typic contact, cell-to-cell signaling and uniform nutrient diffusion. Bioprinting techniques successfully build mathematically defined porous architecture to diminish resistance to mass transfer. Current limitations of bioprinted cell assemblies include poor micro-scale formability of cell-laden soft gels and asymmetrical macro-scale diffusion through 3D volumes. The objective of this work is to engineer a synchronized multi-material bioprinter (SMMB) system which improves the resolution and expands the capability of existing bioprinting systems by packaging multiple cell types in heterotypic arrays prior to deposition. This unit cell approach to arranging multiple cell-laden solutions is integrated with a motion system to print heterogeneous filaments as tissue engineered scaffolds and nanoliter droplets. The set of SMMB process parameters control the geometric arrangement of the combined flow's internal features and constituent material's volume fractions. SMMB printed hepatocyte-endothelial laden 200 nl droplets are cultured in a rotary cell culture system (RCCS) to study the effect of microgravity on an in vitro model of the human hepatic lobule. RCCS conditioning for 48 h increased hepatocyte cytoplasm diameter 2 μm, increased metabolic rate, and decreased drug half-life. SMMB hetero-cellular models present a 10-fold increase in metabolic rate, compared to SMMB mono-culture models. Improved bioprinting resolution due to process control of cell-laden matrix packaging as well as nanoliter droplet printing capability identify SMMB as a viable technique to improve in vitro model efficacy.

Development of a high temporal-spatial resolution vehicle emission inventory based on NRT traffic data and its impact on air pollution in Beijing - Part 1: Development and evaluation of vehicle emission inventory

NASA Astrophysics Data System (ADS)

Jing, B. Y.; Wu, L.; Mao, H. J.; Gong, S. L.; He, J. J.; Zou, C.; Song, G. H.; Li, X. Y.; Wu, Z.

2015-10-01

As the ownership of vehicles and frequency of utilization increase, vehicle emissions have become an important source of air pollution in Chinese cities. An accurate emission inventory for on-road vehicles is necessary for numerical air quality simulation and the assessment of implementation strategies. This paper presents a bottom-up methodology based on the local emission factors, complemented with the widely used emission factors of Computer Programme to Calculate Emissions from Road Transport (COPERT) model and near real time (NRT) traffic data on road segments to develop a high temporal-spatial resolution vehicle emission inventory (HTSVE) for the urban Beijing area. To simulate real-world vehicle emissions accurately, the road has been divided into segments according to the driving cycle (traffic speed) on this road segment. The results show that the vehicle emissions of NOx, CO, HC and PM were 10.54 × 104, 42.51 × 104 and 2.13 × 104 and 0.41 × 104 Mg, respectively. The vehicle emissions and fuel consumption estimated by the model were compared with the China Vehicle Emission Control Annual Report and fuel sales thereafter. The grid-based emissions were also compared with the vehicular emission inventory developed by the macro-scale approach. This method indicates that the bottom-up approach better estimates the levels and spatial distribution of vehicle emissions than the macro-scale method, which relies on more information. Additionally, the on-road vehicle emission inventory model and control effect assessment system in Beijing, a vehicle emission inventory model, was established based on this study in a companion paper (He et al., 2015).

The HYPE Open Source Community

NASA Astrophysics Data System (ADS)

Strömbäck, L.; Pers, C.; Isberg, K.; Nyström, K.; Arheimer, B.

2013-12-01

The Hydrological Predictions for the Environment (HYPE) model is a dynamic, semi-distributed, process-based, integrated catchment model. It uses well-known hydrological and nutrient transport concepts and can be applied for both small and large scale assessments of water resources and status. In the model, the landscape is divided into classes according to soil type, vegetation and altitude. The soil representation is stratified and can be divided in up to three layers. Water and substances are routed through the same flow paths and storages (snow, soil, groundwater, streams, rivers, lakes) considering turn-over and transformation on the way towards the sea. HYPE has been successfully used in many hydrological applications at SMHI. For Europe, we currently have three different models; The S-HYPE model for Sweden; The BALT-HYPE model for the Baltic Sea; and the E-HYPE model for the whole Europe. These models simulate hydrological conditions and nutrients for their respective areas and are used for characterization, forecasts, and scenario analyses. Model data can be downloaded from hypeweb.smhi.se. In addition, we provide models for the Arctic region, the Arab (Middle East and Northern Africa) region, India, the Niger River basin, the La Plata Basin. This demonstrates the applicability of the HYPE model for large scale modeling in different regions of the world. An important goal with our work is to make our data and tools available as open data and services. For this aim we created the HYPE Open Source Community (OSC) that makes the source code of HYPE available for anyone interested in further development of HYPE. The HYPE OSC (hype.sourceforge.net) is an open source initiative under the Lesser GNU Public License taken by SMHI to strengthen international collaboration in hydrological modeling and hydrological data production. The hypothesis is that more brains and more testing will result in better models and better code. The code is transparent and can be changed and learnt from. New versions of the main code are delivered frequently. HYPE OSC is open to everyone interested in hydrology, hydrological modeling and code development - e.g. scientists, authorities, and consultancies. By joining the HYPE OSC you get access a state-of-the-art operational hydrological model. The HYPE source code is designed to efficiently handle large scale modeling for forecast, hindcast and climate applications. The code is under constant development to improve the hydrological processes, efficiency and readability. In the beginning of 2013 we released a version with new and better modularization based on hydrological processes. This will make the code easier to understand and further develop for a new user. An important challenge in this process is to produce code that is easy for anyone to understand and work with, but still maintain the properties that make the code efficient enough for large scale applications. Input from the HYPE Open Source Community is an important source for future improvements of the HYPE model. Therefore, by joining the community you become an active part of the development, get access to the latest features and can influence future versions of the model.

Parallel computing method for simulating hydrological processesof large rivers under climate change

NASA Astrophysics Data System (ADS)

Wang, H.; Chen, Y.

2016-12-01

Climate change is one of the proverbial global environmental problems in the world.Climate change has altered the watershed hydrological processes in time and space distribution, especially in worldlarge rivers.Watershed hydrological process simulation based on physically based distributed hydrological model can could have better results compared with the lumped models.However, watershed hydrological process simulation includes large amount of calculations, especially in large rivers, thus needing huge computing resources that may not be steadily available for the researchers or at high expense, this seriously restricted the research and application. To solve this problem, the current parallel method are mostly parallel computing in space and time dimensions.They calculate the natural features orderly thatbased on distributed hydrological model by grid (unit, a basin) from upstream to downstream.This articleproposes ahigh-performancecomputing method of hydrological process simulation with high speedratio and parallel efficiency.It combinedthe runoff characteristics of time and space of distributed hydrological model withthe methods adopting distributed data storage, memory database, distributed computing, parallel computing based on computing power unit.The method has strong adaptability and extensibility,which means it canmake full use of the computing and storage resources under the condition of limited computing resources, and the computing efficiency can be improved linearly with the increase of computing resources .This method can satisfy the parallel computing requirements ofhydrological process simulation in small, medium and large rivers.