Environmental Modeling - Science topic
Tools to advance the science and improve decision making with respect to resource and environmental issues, with emphasis on interdisciplinarity and the development of generic frameworks and methodologies which integrate models and software tools across issues, scales, disciplines and stakeholders.
Questions related to Environmental Modeling
I'm presently learning out to implement reinforcement learning using matlab/python.
Please, if i have multiple discreet actions space as my action, how can I specify the discreet range for each actions using "rlfinitespec function" in matlab and "Discreet" in python.
Thanks for your consideration.
In the computer modeling and simulation of floatovoltaic systems in marine environments or freshwater reservoirs, a floating PV photovoltaic array performance model and simulation need to characterize the FSPV or FPV irrigation reservoir water evaporation benefits in sustainability assessment for sustainable development energy projects. Quantifying evaporative water-saving is a key project viability metric in a techno-economic model for FPV hydropower hybrid performance models for hydroelectric facilities, or to estimate floating PV array operating temperature or floating PV module internal cell temperature changes in comparative studies for floating FPV and ground-mounted PV or GPV.
Computer estimation of evaporation from a water surface of a water basin or wastewater basin is often calculated in Matlab or Python through mathematical evaporation models, by using parameters such as solar radiation, air temperature, humidity, water temperature, wind velocity, etc. While various applications and modifications of the Penman method, Penman-Monteith equations or Priestley-Taylor evaporation rates are used to predict or determine evapotranspiration rates in various solar water pond cover configurations, and PV floater design types as a sustainability indicator.
However, most water surface modeling or reservoir evaporation methodologies seem to be based on average daily solar irradiation rates, meaning real-time simulation model predictions need to be adapted to account for more instantaneous hour-to-hour solar irradiation data model inputs, ambient temperature variations, wind variations, airmass, relative humidity, water temperature or weather prediction data obtained from remote sensing and weather prediction data.
In a recent publication (link below) on environmental impact assessment of floating solar PV, we propose a method to time-normalize the hourly predictions of floating solar PV evaporation rates in a water-energy-land-food nexus metric, but would like to know from researchers and scientists if literature is available to discuss other scientific data engineering options for hour-to-hour or even-minute-to-minute evaporation rate estimations on open water surfaces as a means to quantify the evaporation savings of an FPV prototype in a real-time simulation model:
Conference Paper Assessment of the evaporation rate in reservoir partially co...
I wanted to ask that if we have to develop a modelling tool to anticipate the impacts of weather extreme events on the water quality of a lake but the amount of information collected in the field is scarce. What kind of models would be better to use and which are the natural processes we should include in the models. Please guide me briefly if possible.
I'm wondering what are some of the well-established methods of forecasting future waste generation (bottom ash in particular)? I'm attempting a time decision frame of 30 years.
I'm familiar with population-based projection models as well as some attempts to use machine learning techniques which is sometime hard to follow.
Thank you very much.
In order to reintroduction of a RET(basically Endangered/Endemic) species different environmental software are used. Its used for finding suitable habitats of a particular species. It has been noticed many publication published in a highly reputed journal as well. I guess, highly skilled/train personal is required to operate and analysis of the same.
I want to run 5 different models to estimate stream flow. In order to optimize the characteristics of these models I use Taguchi method. So I have to run different models according to the Taguchi orthogonal array. Therefore, I have different models with different inputs and different data lengths. For example the first test is: using rainfall and temperature in ANFIS model with 2 year data length, while the second test is: using rainfall, temperature and discharge for previous day in SVR model with 10 year data length. So, the inputs, Data length and model type is changing in these tests. What is the best performance evaluation criterion for this study? NRMSE can be a good criterion because it normalizes the RMSE and in this way, it removes the effect of data range.
Now, I want to know if there is any better solution for this problem.
Good day, senior colleagues, I need your help/ suggestions has to which spatial resolution satellite imageries/sensors can be your used to capture Lake ecological states. Also, if you could suggest a strong research methodology/ reading material regarding this, would go a long way.
Thank you everyone, in anticipation for your suggestions.
6th Vienna young Scientists Symposium, TU Wien (Vienna University of Technology), Austria
June 25-26, 2020
Consisting of four mini-symposia, the symposium has an overall theme of "Technology, Science, and Design for a Sustainable World". The themes of the mini-symposia are:
• Innovative Materials and Green Chemistry
• Energy and Resource Engineering
• Sustainable Buildings, Cities and Infrastructures
• Environmental Analysis and Modeling
Abstract submission deadline: March 15, 2020
"The purpose of the innovative platform Vienna young Scientists Symposium (VSS) is to enhance the interdisciplinary professional exchange between members of the TU Wien." "All scientific staff and students of TU Vienna are cordially invited to participate in this event as speakers."
More information at: https://vss.tuwien.ac.at/home/EN/
#VSS2020 #TUWien #scientists #symposium #technology #science #design #sustainableworld #sustainability #innovation #materialsscience #greenchemistry #energy #resourceefficiency #sustainablearchitecture #sustainablebuilding #sustainablecities #sustainableinfrastructure #architecture #urbanplanning #urbandesign #civilengineering #climatechange #research #environmentalanalysis #environmentalmodeling
Are you implementing any software quality assurance controls if you are developing or using software as part of your modeling effort?
We also use software controls for environmental modelling so I am interested if you have any information on this topic for comparison.
The last version of TOPKAPI ( (TOPographic Kinematic APproximation and Integration) Distributed Hydrological Model, called TOPKAPI-eXtended or TOPKAPI-X, free software and open source.
MAIN MODIFICATIONS IN TOPKAPI - eXtended Model:
1.- Introduction of an 8-DIRECTIONS drainage network
2.- ADDITIONAL SOIL RESPONSE in order to reproduce different hydrological situations. Two soil layers
3.- Addition of an infiltration module based on the GREEN-AMPT MODEL, to reproduce hortonian processes
4.- Introduction of two coefficients to take into account the sun height with respect to the cell aspect for the RADIATION ASSESSMENT and ALBEDO
5.- Addition of a GROUNDWATER MODEL based on the cellular automa: full 2-D IFD (integrated finite difference) groundwater model
6.- Development a powerful graphical interface linked to GIS
7.- Development of module adapter for DELFT-FEWS (Deltares) for operational hydrology and flood forecasting
I have just completed a year-long experiment to assess soil leaching using sealed columns. I would like to assess the likely retention of nutrients in the leachate through plant activity and I have come across a model call LEACHM. However, I don’t know how to access the model and would be grateful for any advice on this or other models that might be appropriate.
- path planning robot simulation .
- 3D map environment model / robot workspace.
- mobile robot will autonomously navigate.
I have never used a modeling software and now I find myself in a research work that has to do with environmental modelling. Will using SOM be a good option for me in terms of mapping out infectious disease clusters (spatial temporal modelling)? Is it easy to learn how to use it? How can I get the software?
I am working with a multivariate time series, in a monthly basis over 10 years. In short, my response variable (Y) is the NDVI vegetation index, which I want to relate to environmental variables (precipitation, soil moisture, etc).
We are analysing 5 vegetation types and, for each one, we have 300 samples. So, there are 1500 time series.
More specifically, my research questions are:
1) Can we distinguish these vegetations using time series?
2) What are the best model to explain the NDVI variation over time for each one?
3) What environmental variables are more related to NDVI variation for each type of vegetation?
My technical question is:
What is the best approach to handle with this data? Can you suggest any method?
For now, i'm relying on the book "Time series analysis and its applications", by Shumway & Stoffer.
Thanks in advance!
A first step to remediating soil pollution is for us to aware of it, mapping the sources and understanding the possible paths of pollution and the dynamic in the ecosystem. In order to make the mapping of soil pollution, it would be necessary to check the contamination levels. However many countries in the developing world do not count with all the instrumentation and techniques. It is clear to me that pH, redox potential, electrical conductivity, macro and micro components, hydrology conditions, type of soil, OM %, etc would allow knowing the conditions in which the pollutants would be metabolized and ultimately present toxicity.
My question is limited to your own experience and your own country. What seems to be the most important soil pollutants for which to be a concern (namely POPs, harmful metal/metaloid chemical species, microorganisms, etc), which techniques and instrumentation would be recommended?
Reporting content that is normalized or not? bio available content? etc. What are your ideas in this respect?
For instance, would GC-MS be capable to identify and quantify POPs of your concern? which software do you use on your own facilities to model this pollutant?. What about ICP or AA for metal/metaloid conc? Do you use some kits for this instead?. Do you use a soil Standard Reference Material?.
I submitted some months ago and I would like to know the duration of peer review.. My paper is still under review and I would like to know if it is normal..
I have an article that will be published soon. In this paper, precipitation is predicted by MPI-ESM-MR model in Tabriz (The largest city in northwestern Iran). The results showed that, according to the both RCP4.5 and RCP8.5 scenarios, the winter precipitation will be increase over the three future periods (2021-2040, 2041-2060 and 2061-2080). Even in the RCP4.5 scenario, the trend will be ascending. While Tabriz's winter precipitation trend is descending in the base period until 2015! It seems to be a contradiction. This means that over the next three years, the winter precipitation will suddenly rise! Is this possible?? What's your opinion?
My work project involve assessing impact of school environment and on student's respiratory health using state-wide data. One of the exposure I am interested in is the traffic related exposure near school. As I am working with a state-wide data, setting up monitors to measure target pollutants (e.g. NOx, black carbon) is not a choice for me.
From literature, I saw some choices below:
1) Proximity (e.g. any roads within 500m of school, or add up all length of road within 500m of school)
2) Traffic activity (e.g. AADT/distance from road to school)
3) Modeling the traffic related pollutants
Personally, I prefer the 3rd choice but I couldn't find existing models with accessible SAS/R code/software. If you have modeled traffic related pollutants before, could you please let me know what software/tool you used? Or if there is any modeled traffic related pollutants data available for NYS?
I just started reading about carbon sequestration and I want to do a project in it (Specifically using Lattice Boltzmann Modelling)
In order to start, I need some references and papers to go through.
Your inputs are welcomed.
Elith and Leathwick (2009) recommended the Moran's I to testing for spatial patterns in raw data and residuals. I read many literature regarding this and many packages in R, but could not perform this test. Can anyone help me with detail method in data preparation for Moran's I test for raw dataset and model residual?
not only in all known to me textbooks, but also in my academic environment, plants are only discussed as carbon sinks and therefore planting forests is said to be one of the main strategies to reverse or reduce some effects of climate change.
But: About 10 years ago a german team from MPI published - and that seemed to be a shock for some climate researchers - that plants (especially forests) are able to produce tremendous amounts of methane under "normal" aerobic conditions autonomously (1). There were even attempts to link the ending phase of the ice ages with forest growth in the way that besides volcanic or solar activity forests were responsible for the warm up (and not vice versa).
Still in any lectures at my institution only common methane sources (microbes, anaerobic environments as bogs and swamps, cattles, humans,...) are discussed with students while - as said - plants are only considered as carbon sinks.
How so? Do you know something about the latest discoveries in this field (maybe i missed some relevant publications)? Are plants excluded as methane sources because of new investigations? Or is it an open (and not well known) problem that is not recognized broadly by environmental scientists?
(1) Keppler F, Hamilton JTG, Brass M et al (2006) Methane emissions from terrestrial plants under aerobic conditions. Nature 439, 187-191.
I have time series heavy metal concentration data in fish mussel, surrounding water and sediment. What kind of analysis do you suggest for modelling relation between heavy metals concentration in fish mussel, surrounding water and sediment? Is it possible to forecast heavy metals concentration in other fish species based on model results?
any advice and suggestions will be greatly appreciated.
I have been interested in environmental modeling, especially models of ecological succession. However, whenever I see studies involving models of Markov chains type, there is no description of how the transition matrix of probabilities has been actually obtained. Would anyone guide me in this regard?
I have visited many historical botanical gardens, but I think that the situation is not one of the best, what are the most serious concerns that face the existence of these botanical gardens? how could the experience of a very expert curator help new botanical gardens to survive?
Any relative information concerning analysis for small data (except for linear regression,clustering & principal component analysis is appreciated )
From the watershed and sediment management point of view, which aspects and effective factors of Functional and Structural sediment connectivity should be paid attention?
Modelling pollutant dispersion in urban centers need street level meteorological data. Whereas much of the research in this field is carriedout using met data from stations far away from study area or with general meteorological details.
Are there any urban air pollutant studies conducted using street level met data by considering the canyon effects of buildings.
Air quality modeling will vary with the geographical locations as the primary pollutants will vary. How could we generalize a model for the same?
I am looking for data contribution and collaboration. If you have some data, you can be involved in this exciting project:
Project goal: We aim to develop a comprehensible model to estimate soil organic carbon changes under perennial crops. Both food and bioenergy crop. Global study.
Methods: Meta-analysis, Inferential Statistics, Environmental Modeling, Advanced Statistical Modeling, Climate Modelling
Project information is here:
Dear all, do you know reference on hydrological modeling with InVEST, by using the Seasonal Water Yield module?
Framework Analysis was developed by Krueger (1994). Ritchie and Spencer (1994) added to this framework five interconnected stages under which the explanatory stage- in my research- operates.
Assuming you have access to all kind of data, or if you don't have it, you can generate it.
- national sales statistics of pesticides
- quantitative measurements of pesticide residues in water
- interviews with farmers expieriencing symptoms of pesticide poisoning
- farmer mental model analysis
Does anyone know a documented test (published with all needed information to reproduce it) including precipitation over an urban area with buildings? Such a test might be physical and/or numerical.
The aim is to characterize a modelling tool using a known test.
Thanks in advance for your answers.
I am using CASES/ExternE external costs of power generation and adapting it for Pakistan using scaling factor, due to non-availability of data regarding Pakistan. Can you suggest any other methods to adapt data from one region to another?
I am studying as part of a dissertation metal concentrations in urban river systems to look at urban runoff. There are 5 sites (different river systems) dotted around the city sampled 6 times (contrasting dry periods and rain periods). Other parameters are gathered such as pH, O2, conductivity ect to also I guess correlate with the concentrations.
What stats would you suggest on this data.
I am trying to simulate a model for line source emission for an area of grid 1 x 1 km2. Kindly help me with a solution how to feed input for line source emission in my model.
What are the main differences and similarities between Functional and Structural sediment connectivity?
Can we say they are acting in watersheds independently?
Satellite, flux towers, transpiration from plants can be one of them. The comparisons and dependency of these methods will improve my knowledge.
Actually, I want to integrate the socio-economic data with the spatial data. I am looking for some precise models or methods.
My research is modeling the vulnerabilities of groundwater to contamination from diffuse pollution waste water sources under the impacts of seasonal variations in an urban setting.
The project aims to use MODFLOW (example simulate groundwater flow through the urban catchment area for different precipitation and abstraction scenarios) to assess the influence of climate change impacts on groundwater and also propose optimal adaptation strategies. My major concern is that the study area lacks sufficient data for such calibration. Could you suggest some reasonable assumptions and range of scenarios, please?
I study on the pollutant source identification in the urban area. I am going to recommend the possible solutions to the reduction of the Water, Air, Soil, Groundwater, Noise and Electromagnetic Waves pollutants effects, separately.
Is there any practical solutions to the mentioned pollutant effect reduction?
For an example, how can be reduced the air pollution in the populated urban area?
I wonder if anybody will be shared own experience in this regards.
I am new in ENMTools and feel confused about identity test.
After perform identity test, how to make a identity test plot like the one in user manual ver1.3 page 17.
I now know the null distribution data is in the "sorted csv" file.
But, I do not know how (where) to find the value of red arrow.
Can somebody explain me how to make a identity test plot like the one in user manual?
Many people are interested in finding a model to estimate total suspended solids in water bodies.What is the application of these TSS ? I am aware that this is an indicator of water clarity. But as peoples are more interested to know TSS concentration , I just want to know whether that is useful in any environmental modeling or any other type o of research. If anyone has any idea or good literature please suggest.
thank you in advance
if detections in the wastewater stream are in the range of 1-8 nanograms/Liter. Several different PCB congeners have been detected in the wastewater.
Hello dear friends,
Do you know how can I measure "Minimum Projection Area" of 4n-Nonylphenol? I could not find this value in literature. Do you know it?
Many thanks in advance.
I know about different meteorological parameters required to run AERMOD such as wind speed and direction, temp etc. To run AERMET, do we require the current year met data or we can use previous year met data? Any reference or research paper will be helpful.
In Delhi, quality of air went to alarmingly toxic after the functions of Deepavali (Divali) when crackers are used at most by the people. This created 'zero visibility' even in day up to several days.
People with affordable income started to use air purifiers. But what can those people do who are not financially able to afford that. Why such people should suffer.
Is it not better that people making pollution should pay?
Government can charge on the basis of exhausted gases, chemicals etc. in the environment after a certain level. The collections should be paid on the maintaining healthy environment.
How do you think on this issue?
Anybody knows where and how I can download (or even buy) this software:
1. WINISAREG (wich should include: EVAP56 and KCISA)
2. GISAREG (for use in GIS environment)
WINISAREG is water balance models for simulating crop irrigation requirements based on FAO 56 methodology. It was developed in 2003 by L.S. Pereira and others.
At this page is a link (https://www.isa.ulisboa.pt/en/leaf/downloads) for software download but it doesn't work.
Of course, there is an option to contact authors. I did that, no answer.
Questionnaire is carried out in order to develop my master thesis: The impact of user-defined parameters on DEM accuracy. By using feedbacks from the users who works with DEMs the conclusion about users perception of the importance of user-defined parameters in digital terrain modelling will be performed.
Thanks in advance to all !
I am doing a study on drought in the Sahel using the CDI tool from FAO-SWALIM, I aim to use historical GHCN station data however I am struggling to download and assimilate station data. I've looked at getting data from climate explorer, the NOAA GHCN website and others, however getting data for the Sahel area seems patch.
- What source would you recommend for downloading GHCN data, that would allow me to select a specific area and time period, whilst weeding out incomplete records?
- How would you go about getting vegetation NVDI data that i can then match to stations? At the moment I am considering using the AFDM tool.
Many thanks, apologies if these seem fairly simple however I am quite new to this process
Currently, I try to visualize knowledge about sustainable behaviour. I.e., I'd like to construct diagrams showing (primary causal) argumentations about why certain behaviours are (un-)sustainable. It would be an aim, to visualize the consequences of our actions and their environmental and societal impacts and to encourage discussions about the underlying argumentations, based on these visual representations. Ideally, such diagrams could be developed cooperatively.
Does anyone know about related work?
Does anyone even know about the existence of such "sustainability knowledge modelling languages"?
(Or do you think, the idea to visualize such sustainability-knowledge would be unproductive?)
It has been a debate for long time, development of ecosystem models should toward simpler or more mechanistic?
Seems the modelers have a keen interest in developing mechanistic models to incorporate more processes to include more feedbacks in the system, while non-modelers do not like the complex mathematical equations.
I understand the Fixed X assumption is one of the main assumptions in regression. Typically this assumption tends to be violated when modelling environmental data because X is rarely known or determined before the experiment.
- Bootstrapping is a common alternative to overcome the violation, but do I use it as a hypothesis test or just to calculate the confidence interval?
- Is there any other alternatives beside bootstrapping? Does using the total least squares method instead of ordinary least squares applicable in this situation?
happy Research year 2016.
I am interested in numerical Ecology, I found out a very interesting book of P Legendre, L Legendre. I wish to know if there is a French Edition of this book.
Numerical Ecology, Second Edition (Developments in Environmental Modelling) Legendre, P.; Legendre, L. Publisher: Elsevier Science, 1998 ?
Is there any Model developed for the interpretation of the Detritus on foreland basin's provenance by using the DZ U-Pb geochronological data? I have DZ U-Pb data and want to extrapolate it in modelling, if available.
I had 3 data group. environmental data (Temperature, Oxygen, pH, EC and Turbidity), zooplankton community and growth rate of a fish. All data belonged to a one pool. Now I tried to find a best model to describe the relationship between number of zoopnaktons, environmental data and growth rate of the fish. what is best statistical method? Is GLM applicable?
Thanks for your help
These days I'm searching for a software to model Pollutant transport in rivers.I would be gratefull if you could help me!
I have presence data and Environmental data in SWD and would like to run Maxent model and project to worldclim data which are in raster tiff format. Is this possible? kindly share with me how I can do this.
I am working on identify which explanatory variables could be interesting to add in a mechanistic model on soil carbon dynamic.
I am able to calibrate a simple model on experimental data from several sites. This model is like an average model without explanatory variables and so don't simulate the variability existing between the different sites. I have some informations about the different sites (soil properties) which could improve the predictive quality of my model.
I can estimate the MSEP of the "average" model and I'd like to estimate the population part (lambda) of the MSEP decomposition according to Bunke and Droge (1984) or Wallach and Goffinet (1987). This part represent the minimum MSEP we can get with the explanatory variables present in the model. The bigger this part is (relatively to the MSEP) the most we have to add explanatory variables to improve the predictive quality of the model. This term depends on how much the predicted variable (y) varies for fixed values of the explanatory variables (X) in the model : lambda=E[var(y|X)].
I found that when the explanatory variables are categorial, we can estimate lambda by the mean square error of the residuals of a linear model between y and X which seems logical for me. I first thought that we can do it the same way with continuous explanatory variables but I doubt now because of the linear hypothesis which can be a contribution of the squared biais part of the MSEP decomposition (Delta).
Have you any suggestions of how I estimate the lambda part of the MSEP decomposition?
Thanks for the help!
I explore generalized parameters of aquatic ecosystems to assess the evolution of their state under anthropogenic effect. What parameters are preferable?
I have 10 or more g TSS or 7 VSS in my sample of waste activated sludge. Now I am using digestion for Total phosphorus, I do not want to dry it in oven, rather I want to use it in its original form so I want to know how can we use it on dry mass basis.
In protocol they used 3g of dry mass basis.
I have a model in the form of:
y ~ A + B + random=~1|C + random= ~1|D, family=poisson, data=data)
I recently saw a thread on grokbase that suggested;
lme and, by extension, glmmPQL do not handle crossed random effects
You must create a factor of the same length as y, A, B, C, and D with
a single level
const = factor(rep(1, length(y)))
then use the non-obvious formulation
glmmPQL(y ~ A + B, random = list(const = pdBlocked(pdIdent(~ C - 1),
pdIdent(~ D - 1))))
When I run this script however – I get the output :
Error in pdConstruct.pdBlocked(object, form = form, nam = nam, data = data, :
'form' must be a list