This document provides instructions for using the WaterBudget component in the OMS 3 console to model the water budget and simulate discharge, actual evapotranspiration, runoff, and drainage for a given area. The component solves water budget equations using inputs of rainfall, potential evapotranspiration, and other parameters. It produces time series outputs of water storage, discharge, evapotranspiration, runoff, and drainage that can be used for hydrologic modeling and forecasting. Links are provided to download necessary files and access the component's source code.
Multivariable Parametric Modeling of a Greenhouse by Minimizing the Quadratic...TELKOMNIKA JOURNAL
This paper concerns the identification of a greenhouse described in a multivariable linear system
with two inputs and two outputs (TITO). The method proposed is based on the least squares identification
method, without being less efficient, presents an iterative calculation algorithm with a reduced
computational cost. Moreover, its recursive character allows it to overcome, with a good initialization, slight
variations of parameters, inevitable in a real multivariable process. A comparison with other method s
recently proposed in the literature demonstrates the advantage of this method. Simulations obtained will be
exposed to showthe effectiveness and application of the method on multivariable systems.
Some basics and opinions about how to use the javax.measure API in backend and how to integrate it with a frontend application. Have fun and leave feedback :-)
Ill-posedness formulation of the emission source localization in the radio- d...Ahmed Ammar Rebai PhD
To contact the authors : tarek.salhi@gmail.com and ahmed.rebai2@gmail.com
In the field of radio detection in astroparticle physics, many studies have shown the strong dependence of the solution of the radio-transient sources localization problem (the radio-shower time of arrival on antennas) such solutions are purely numerical artifacts. Based on a detailed analysis of some already published results of radio-detection experiments like : CODALEMA 3 in France, AERA in Argentina and TREND in China, we demonstrate the ill-posed character of this problem in the sens of Hadamard. Two approaches have been used as the existence of solutions degeneration and the bad conditioning of the mathematical formulation problem. A comparison between experimental results and simulations have been made, to highlight the mathematical studies. Many properties of the non-linear least square function are discussed such as the configuration of the set of solutions and the bias.
Concurrent Ternary Galois-based Computation using Nano-apex Multiplexing Nibs...VLSICS Design
Novel realizations of concurrent computations utilizing three-dimensional lattice networks and their corresponding carbon-based field emission controlled switching is introduced in this article. The formalistic ternary nano-based implementation utilizes recent findings in field emission and nano applications which include carbon-based nanotubes and nanotips for three-valued lattice computing via field-emission methods. The presented work implements multi-valued Galois functions by utilizing concurrent nano-based lattice systems, which use two-to-one controlled switching via carbon-based field emission devices by using nano-apex carbon fibers and carbon nanotubes that were presented in the first part of the article. The introduced computational extension utilizing many-to-one carbon field-emission devices will be further utilized in implementing congestion-free architectures within the third part of the article. The emerging nano-based technologies form important directions in low-power compact-size regular lattice realizations, in which carbon-based devices switch less-costly and more-reliably using much less power than silicon-based devices. Applications include low-power design of VLSI circuits for signal processing and control of autonomous robots.
Thrid part of the Course "Java Open Source GIS Development - From the building blocks to extending an existing GIS application." held at the University of Potsdam in August 2011
Model predictive-fuzzy-control-of-air-ratio-for-automotive-enginespace130557
Automotive engine air-ratio plays an important role of
emissions and fuel consumption reduction while maintains
satisfactory engine power among all of the engine control variables.
Egg deposition for Bloaters, aged 3, in Lake Huron and predicting next five y...Arpan Kumar
The objective of this report is to observe any pattern or seasonality in Coregonus’ egg deposition aged 3 in Lake Huron (one of the five great lakes in North America) using time-series analysis methods and aim to predict any changes in Egg depositions for the next five years. This report will touchbase on the topics like finding a relevant model and apply suitable approaches to fit a model using visualisation and R functions for the provided dataset
It describe how to build a modelling solution with the Simple Water Budget component of JGrass-NewAGE. Se the companion documentation regarding the component itself
Production decline analysis is a traditional means of identifying well production problems and predicting well performance and life based on real production data. It uses empirical decline models that have little fundamental justifications. These models include
•
Exponential decline (constant fractional decline)
•
Harmonic decline, and
•
Hyperbolic decline.
Viene presentato e discusso (in inglese) in dettaglio l'utilizzo della piattaforma EIAGRID/SmartGEO in due casi studio significativi per le applicazioni geotecniche e ambientali. Al termine, l'utente interessato dovrebbe essere in grado di utilizzare in modo autonomo la piattaforma attraverso il portale SmartGEO.
The presentation discusses a new method for imaging seismic data that was recently implemented on the SmartGeo cloud computing portal (https://smartgeo.crs4.it/enginframe/eiagrid/eiagrid.xml). The method is particularly suited for near-surface applications such as geotechnical engineering or environmental studies. It is shown that instead of limiting the stacking velocity analysis to single Common-Midpoint-Gathers, groups of neighboring Common-Midpoint-Gathers gathers are considered to identify entire reflection surfaces in the data. As a result the extracted kinematic properties of the subsurface, e.g. wave-propagation velocities, are more reliable and the final data stacking leads to a more detailed subsurface image even in case of noisy prestack data and laterally strongly variable velocities. In the second part of the presentation, the successful application of the proposed method is discussed in a case study based on a ultra-shallow seismic SH-wave data set recorded close to Teulada, Sardinia, Italy.
An investigation into helicopter rotor blade-vortex interaction. This interaction limits a helicopter’s performance, vibrates
the rotor and fuselage, fatigues the entire aircraft, and creates noise which can be heard for great
distances.
GEOFRAME: a system for doing hydrology by computerRiccardo Rigon
GEOFRAME is the infrastructure built around JGrass, J-Hydro and the models GEOtop and NewAge which would allows to perform modern hydrology by computer
Multivariable Parametric Modeling of a Greenhouse by Minimizing the Quadratic...TELKOMNIKA JOURNAL
This paper concerns the identification of a greenhouse described in a multivariable linear system
with two inputs and two outputs (TITO). The method proposed is based on the least squares identification
method, without being less efficient, presents an iterative calculation algorithm with a reduced
computational cost. Moreover, its recursive character allows it to overcome, with a good initialization, slight
variations of parameters, inevitable in a real multivariable process. A comparison with other method s
recently proposed in the literature demonstrates the advantage of this method. Simulations obtained will be
exposed to showthe effectiveness and application of the method on multivariable systems.
Some basics and opinions about how to use the javax.measure API in backend and how to integrate it with a frontend application. Have fun and leave feedback :-)
Ill-posedness formulation of the emission source localization in the radio- d...Ahmed Ammar Rebai PhD
To contact the authors : tarek.salhi@gmail.com and ahmed.rebai2@gmail.com
In the field of radio detection in astroparticle physics, many studies have shown the strong dependence of the solution of the radio-transient sources localization problem (the radio-shower time of arrival on antennas) such solutions are purely numerical artifacts. Based on a detailed analysis of some already published results of radio-detection experiments like : CODALEMA 3 in France, AERA in Argentina and TREND in China, we demonstrate the ill-posed character of this problem in the sens of Hadamard. Two approaches have been used as the existence of solutions degeneration and the bad conditioning of the mathematical formulation problem. A comparison between experimental results and simulations have been made, to highlight the mathematical studies. Many properties of the non-linear least square function are discussed such as the configuration of the set of solutions and the bias.
Concurrent Ternary Galois-based Computation using Nano-apex Multiplexing Nibs...VLSICS Design
Novel realizations of concurrent computations utilizing three-dimensional lattice networks and their corresponding carbon-based field emission controlled switching is introduced in this article. The formalistic ternary nano-based implementation utilizes recent findings in field emission and nano applications which include carbon-based nanotubes and nanotips for three-valued lattice computing via field-emission methods. The presented work implements multi-valued Galois functions by utilizing concurrent nano-based lattice systems, which use two-to-one controlled switching via carbon-based field emission devices by using nano-apex carbon fibers and carbon nanotubes that were presented in the first part of the article. The introduced computational extension utilizing many-to-one carbon field-emission devices will be further utilized in implementing congestion-free architectures within the third part of the article. The emerging nano-based technologies form important directions in low-power compact-size regular lattice realizations, in which carbon-based devices switch less-costly and more-reliably using much less power than silicon-based devices. Applications include low-power design of VLSI circuits for signal processing and control of autonomous robots.
Thrid part of the Course "Java Open Source GIS Development - From the building blocks to extending an existing GIS application." held at the University of Potsdam in August 2011
Model predictive-fuzzy-control-of-air-ratio-for-automotive-enginespace130557
Automotive engine air-ratio plays an important role of
emissions and fuel consumption reduction while maintains
satisfactory engine power among all of the engine control variables.
Egg deposition for Bloaters, aged 3, in Lake Huron and predicting next five y...Arpan Kumar
The objective of this report is to observe any pattern or seasonality in Coregonus’ egg deposition aged 3 in Lake Huron (one of the five great lakes in North America) using time-series analysis methods and aim to predict any changes in Egg depositions for the next five years. This report will touchbase on the topics like finding a relevant model and apply suitable approaches to fit a model using visualisation and R functions for the provided dataset
It describe how to build a modelling solution with the Simple Water Budget component of JGrass-NewAGE. Se the companion documentation regarding the component itself
Production decline analysis is a traditional means of identifying well production problems and predicting well performance and life based on real production data. It uses empirical decline models that have little fundamental justifications. These models include
•
Exponential decline (constant fractional decline)
•
Harmonic decline, and
•
Hyperbolic decline.
Viene presentato e discusso (in inglese) in dettaglio l'utilizzo della piattaforma EIAGRID/SmartGEO in due casi studio significativi per le applicazioni geotecniche e ambientali. Al termine, l'utente interessato dovrebbe essere in grado di utilizzare in modo autonomo la piattaforma attraverso il portale SmartGEO.
The presentation discusses a new method for imaging seismic data that was recently implemented on the SmartGeo cloud computing portal (https://smartgeo.crs4.it/enginframe/eiagrid/eiagrid.xml). The method is particularly suited for near-surface applications such as geotechnical engineering or environmental studies. It is shown that instead of limiting the stacking velocity analysis to single Common-Midpoint-Gathers, groups of neighboring Common-Midpoint-Gathers gathers are considered to identify entire reflection surfaces in the data. As a result the extracted kinematic properties of the subsurface, e.g. wave-propagation velocities, are more reliable and the final data stacking leads to a more detailed subsurface image even in case of noisy prestack data and laterally strongly variable velocities. In the second part of the presentation, the successful application of the proposed method is discussed in a case study based on a ultra-shallow seismic SH-wave data set recorded close to Teulada, Sardinia, Italy.
An investigation into helicopter rotor blade-vortex interaction. This interaction limits a helicopter’s performance, vibrates
the rotor and fuselage, fatigues the entire aircraft, and creates noise which can be heard for great
distances.
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The ideology behind the hydrological modelling I do. It is a revisiting of part of a talk I gave at CUAHSI biennial meeting in Boulder (CO) on July 2008. It promotes the modeling-by-components paradigm
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It describes the simple water budget component of JGrass-NewAGE. Water Budget is estimatedby integrating a non-lieanr partial differential equation. Information inside.
The concepts related of the New Model of River Adige, and especially an analysys of the existing OMS components ready and their interpretation on the basis of travel time approaches
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Numerical assessment of the backward facing steps nozzleeSAT Journals
Abstract The backward facing steps nozzle (BFSN) is a flow adjustable exit area nozzle for large rocket engines. It consists of two parts, the first is a base nozzle with small area ratio and the second part is a nozzle extension with surface consists of backward facing steps. The number of steps and their heights are carefully chosen to produce controlled flow separation at steps edges that adjust the nozzle exit area at all altitudes (pressure ratios). The BFSN performance parameters are assessed in terms of thrust and side loads against the dual-bell nozzle (DBN) with the same pressure ratios and cross sectional areas. The DBN is a two-mode flow adjustable exit area nozzle for low and high altitude. Three-dimensional turbulent flow solutions are obtained for the BFSN indicating that the flow is axi-symmetric and does not generate significant side loads. Further confirmation of the axi-symmetric flow is obtained by comparing the three-dimensional flow with the two-dimensional axi-symmetric solutions. The comparison of the thrust generated over the PR range from 50 to 1500 shows that BFSN generates more uniform and higher thrust than the DBN in the intermediate pressure ratios. At PR 1500 (high altitude), the BFSN thrust is 0.28% less than the DBN. All numerical solutions are obtained using the Fluent code. Keywords: Backward facing steps nozzle, Turbulent flow in supersonic nozzle, Side load in supersonic nozzle.
Numerical analysis for two phase flow distribution headers in heat exchangerseSAT Journals
Abstract A flow header having number of multiple small branch pipes are commonly used in heat exchangers and boilers. In beginning the headers were designed based on the assumption that the fluid distribute equally to all lateral pipes. In practical situation the flow is not uniform and equal in all lateral pipes. Mal distribution of flow in heat exchangers significantly affects their performance. Non-uniform flow distribution from header to the branch pipes in a flow system will lead to 25% decrease in effectiveness of a cross flow heat exchanger. Mal distribution of flow in the header is influenced by the geometric parameters and operating conditions of the header. In this work the flow distribution among the branch pipes of dividing flow header system is analyzed for two phase flow condition. In the two phase flow condition, the effect of change in geometric cross sectional shape of the header (circular, square), inlet flow velocities are varied to find the flow mal distribution through the lateral pipes are investigated with the use of Computational Fluid Dynamics software. Keywords: circular, square headers and Computational Fluid Dynamics software. (CFD)
Simulations Of Unsteady Flow Around A Generic Pickup Truck Using Reynolds Ave...Abhishek Jain
Above Research Paper can be downloaded from www.zeusnumerix.com
The research paper aims to replicate the wind tunnel test of General Motors pick-up truck using CFD analysis. The pickup is a blunt body and simulation reveals vortex shedding from the edges of the vehicle downstream. The unsteadiness of this phenomenon is seen in the oscillation of residue. The paper shows matching of velocity magnitude downstream of the vortex. Authors - Bahram Khalighi (GM, USA), Basant Gupta et al Zeus Numerix.
Optimization Model for Refinery Hydrogen Networks Part IIJERA Editor
Petroleum refineries have many process units that consume hydrogen.These process units are distributed in different places everywhere in the refinery.In order to feed them, it is necessary to have sources capable of supplying, in amount and quality, the hydrogen that every consuming unit needs.It is also needed to have a distribution network that it is correctly designed and which operation is adjusted in an optimal manner to the changing conditions of the refinery.This involves the minimization of the cost of installation and operation of the hydrogen network.The installation cost is dominated by the amount of pipelines, compressors and purifying units; while the cost of operation is dominated by the amount of fresh hydrogen that the plant consumes.In this work a mathematical model is developed for a hydrogen network,which is adapted to the different information levels available in the different stages of design of that system.The model is currently in use in the YPFLuján de Cuyo refinery (Mendoza, Argentina). In this first part, the basic model is presented; whereas in a second part, the model is enlarged to accommodate the incorporation of purifying units and new compressors.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Nutraceutical market, scope and growth: Herbal drug technologyLokesh Patil
As consumer awareness of health and wellness rises, the nutraceutical market—which includes goods like functional meals, drinks, and dietary supplements that provide health advantages beyond basic nutrition—is growing significantly. As healthcare expenses rise, the population ages, and people want natural and preventative health solutions more and more, this industry is increasing quickly. Further driving market expansion are product formulation innovations and the use of cutting-edge technology for customized nutrition. With its worldwide reach, the nutraceutical industry is expected to keep growing and provide significant chances for research and investment in a number of categories, including vitamins, minerals, probiotics, and herbal supplements.
What is greenhouse gasses and how many gasses are there to affect the Earth.moosaasad1975
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Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
4. An Overview of Sugarcane White Leaf Disease in Vietnam.pdf
JGrass-NewAge water budget
1. Bancheri
LINKERS
JGrass-NewAge: WaterBudget component
Marialaura Bancheri
Correspondence:
marialaura.bancheri@unitn.it
Dipartimento di Ingegneria Civile
Ambientale e Meccanica, Trento,
Mesiano di Povo, Trento, IT
Full list of author information is
available at the end of the article
Abstract
These pages teach how to run the WaterBudget component inside the OMS 3
console. Some preliminary knowledge and installation of OMS is mandatory (see @Also
useful). This component deals with the water budget solution, for a defined layer. Given
the time series of the rainfall and of the potential evapotranspiration, the components
is able to estimate the water storage, to simulate the runoff and the actual
evapotranpiration for the considered layer, at different time-step. It also simulate the
possible drainage toward deeper layer. The package is perfectly integrated in the
JGrass-NewAge, and can be fed by other components, like the one providing the
potential evapotranspiration and connected to calibration algorithms. Once parameters
are assigned according to the selected model, it can be used for the forecasting water
storage in a selected point.
@Version:
0.1
@License:
GPL v. 3
@Inputs:
• Rainfall (mm);
• Potential evapotranspiration (mm);
• Discharge (if required) (m3
/s);
• Solver model (String);
• Q model (String);
• AET model (String);
• Area of the basin (A) (km2
);
• Non-linear reservoir parameter (a) (-);
• Non-linear reservoir exponent (b) (-);
• Maximum storage (mm);
• Pore volume in the root zone (nZ) (mm);
• Recharge rate (Re) (mm);
@Outputs:
• Water storage [mm];
• Total discharge [m3
/m2
];
• Actual evapotranspiration [mm];
• Quick runoff [m3
/m2
];
• Drainage from the layer [m3
/m2
].
@Doc Author: Marialaura Bancheri
@References:
• See References section below
Keywords: OMS; JGrass-NewAGE Component Description; Water budget
2. Bancheri Page 2 of 11
Code Information
Executables
This link points to the jar file that, once downloaded can be used in the OMS console:
https://github.com/GEOframeOMSProjects/OMS_Project_WB/tree/master/lib
Developer Info
This link points to useful information for the developers, i.e. information about the code
internals, algorithms and the source code
https://github.com/geoframecomponents
Also useful
To run JGrass-NewAGE it is necessary to know how to use the OMS console. Information
at: ”How to install and run the OMS console”,
https://alm.engr.colostate.edu/cb/project/oms).
JGrasstools are required for preparing some input data (information at:
http://abouthydrology.blogspot.it/2012/11/udig-jgrasstools-resources-in-italian.
html
To visualize results you need a GIS. Use your preferred GIS, following its installation
instructions. To make statistics on the results, you can probably get benefits from R:
http://www.r-project.org/ and follow its installation instruction.
To whom address questions
marialaura.bancheri@unitn.it
Authors of documentation
Marialaura Bancheri (marialaura.bancheri@unitn.it)
This documentation is released under Creative Commons 4.0 Attribution International
3. Bancheri Page 3 of 11
Component Description
This component solves the water budget, simulates the discharge and the actual evapo-
transpiration, according to the model chosen. The equation solved is:
dS(t)
dt
= J(t) − Q(t) − AET(t) (1)
where S [mm] is the water storage, J [mm] is the precipitation, Q the discharge [m3
/m2
]
and AET [mm] is the actual evapotranspiration. Both the discharge and the actual evepo-
transpiration can be given values or estimated from the S, according to different models,
i.e.:
Q(t) = aS(t)b
(2)
AET =
S(t)
Smax
ET(t) (3)
where ET is the potential evapotranspiration. Also the soil moisture can be modeled,
considering the porosity (n) and the depth of the root zone (Z). In this case, the equation
solved is:
nZ
ds(t)
dt
= J(t) − Q(t) − AET(t) (4)
The component, given the maximum recharge rate of the lower layer (Re), is also able
to estimate the drainage toward the deeper layers, eq. 5 and the direct runoff from the
considered layer, eq. 6
R(t) = min(Q(t), Re) (5)
Qquick(t) = Q(t) − R(t) (6)
Detailed Inputs description
The input file is a .csv file containing a header and one or more time series of input data,
depending on the number of stations involved. Each column of the file is associated to a
different station.
The file must have the following header:
• The first 3 rows with general information such as the date of the creation of the file
and the author;
• the fourth and fifth rows contain the IDs of the stations (e.g. station number 8:
value 8, ID, ,8);
• the sixth row contains the information about the type of the input data (in this
case, one column with the date and one column with double values);
• the seventh row specifies the date format (YYYY-MM-dd HH:mm).
All the previous information shown in the figure 1.
4. Bancheri Page 4 of 11
Figure 1 Heading of the .csv input file
Rainfall
The rainfall is given in time series of (mm) for the investigated station .
Evapotranpiration
The evapotranpiration is given in time series of (mm) for the investigated station.
Discharge
The discharge is given in time series for the investigated station in (m3
/s). The discharge
values are directly converted in to (mm), given the value of the area of the basin. This
values are needed in the case the user wants to solve the water balance only using external
values, otherwise the component simulates the discharge, using the previous models, eq.
2.
Solver model
The Solver model field is a string in which the user specifies the integrator to use of the
solution of the ODE 1. There are two options :”dp853” which is the Dormand-Prince
8(5,3) integrator and ”Eulero”, which is the Euler integrator.
Q model
The Q model field is a string in which the user specifies the model for the discharge:
”NonLinearResevoir” or ”ExternalValues”.
AET model
The AET model field is a string in which the user specifies the model for the evapotran-
spiration: ”AET” or ”ExternalValues”.
Area of the basin
A is the area of the basin expressed in (km2
).
Non-linear reservoir parameter (a)
Non-linear reservoir parameter is the a parameter in eq. 2
Non-linear reservoir exponent (b)
Non-linear reservoir exponent is the b exponent in eq. 2
Maximum storage
Maximum storage is the variable Smax in eq. 3. It is expressed in (mm)
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Pore volume in the root zone
The pore volume in the root zone is the variable nZ in eq. 4 and it is the product of the
soil porosity n and the depth of the root zone Z.
Recharge rate(mm)
The Recharge rate is the variable Re in eq. 5 and it is the maximum recharge rate towards
the lower layer.
Detailed Outputs description
Water storage
The water storage output is given as a time series at a given point. Its units are [mm].
Figure 2 shows the results of the simulation obtained using the data from a station in the
Posina river basin.
0 10000 20000 30000 40000
0.0000.0050.0100.0150.0200.0250.030
Water storage
Time[h]
S[mm]
Figure 2 Time series of water storage for a station in the Posina river basin.
Discharge
The discharge output is given as a time series at a given point. Its units are [mm3
/m2
].
Figure 3 shows the results of the discharge simulation obtained using the non linear
reservoir model.
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0 10000 20000 30000 40000
0.00.51.01.5
Discharge
Time[h]
Q[mm]
Figure 3 Time series of discharge for a station in the Posina river basin.
Actual evapotranspiration
The actual evaotranspiration output is given as a time series at a given point. Its units
are [mm]. Figure 4 shows the results of the AET simulation obtained considering it a
function of the water storage.
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0 10000 20000 30000 40000
0.00.20.40.60.81.0
Actual ET
Time[h]
AET[mm]
Figure 4 Time series of AET for a station in the Posina river basin.
Runoff
The runoff output is given as a time series at a given point. Its units are [mm]. Figure 5
shows the results of the runoff simulation, considering the maximum recharge rate of the
lower layer equal to 0.2 [mm].
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0 10000 20000 30000 40000
0.00.20.40.60.81.01.2
Runoff from the layer
Time[h]
Qquick[mm]
Figure 5 Time series of runoff for a station in the Posina river basin.
Drainage
The drainage output is given as a time series at a given point. Its units are [mm]. Figure
6 shows the results of the runoff simulation, considering the maximum recharge rate of
the lower layer equal to 0.2 [mm].
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0 10000 20000 30000 40000
0.000.050.100.150.20
Drainage toward the lower layers
Time[h]
R[mm]
Figure 6 Time series of drainage toward a deeper layer for a station in the Posina river basin.
Examples
The following .sim file is customized for the use of the WaterBudget component. The .sim
file can be downloaded from here:
https://github.com/GEOframeOMSProjects/OMS_Project_WB/tree/master/simulation
import static oms3.SimBuilder.instance as OMS3
def home = oms_prj
def startDate= "1994 -01 -01 00:00"
def endDate= "1998 -12 -31 00:00"
OMS3.sim {
resource "$oms_prj/lib/waterbudget -0.0.1 - SNAPSHOT -jar -with -
dependencies .jar"
model(while:" reader_data_J .doProcess") {
components {
" reader_data_J " "org. jgrasstools .gears.io. timedependent .
OmsTimeSeriesIteratorReader "
" reader_data_ET " "org.jgrasstools .gears.io. timedependent .
OmsTimeSeriesIteratorReader "
"ws" "waterBudget. WaterBudget "
"writer_S" "org.jgrasstools.gears.io. timedependent .
OmsTimeSeriesIteratorWriter "
"writer_Q" "org.jgrasstools.gears.io. timedependent .
OmsTimeSeriesIteratorWriter "
"writer_ET" "org. jgrasstools.gears.io. timedependent .
OmsTimeSeriesIteratorWriter "
" writer_Quick " "org.jgrasstools.gears.io. timedependent .
OmsTimeSeriesIteratorWriter "
"writer_R" "org.jgrasstools.gears.io. timedependent .
OmsTimeSeriesIteratorWriter "
}
11. Bancheri Page 11 of 11
Data and Project
The following link is for the download of the input data necessaries to execute the WB
component (as shown in the .sim file in the previous section ) :
https://github.com/GEOframeOMSProjects/OMS_Project_WB/tree/master/data
The following link is for the download of the OMS project for WB component:
https://github.com/GEOframeOMSProjects/OMS_Project_WB
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References