Science topic

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
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Dear All,
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.
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Special emphasis on PMF model.
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Quality and cost are directly impacted by measurement uncertainty. Many industries including research, manufacturing, finance, and healthcare rely on reports that contain quantitative data from measurement results. Product quality, experiment results, financial decisions, and medical diagnosis can all be directly impacted by errors introduced from the omission of measurement uncertainty. Without awareness or consideration of the impact measurement uncertainty has on quality, the greater the probability of increased operating costs and failure rates.
Measurement uncertainty is critical to risk assessment and decision making. Organizations make decisions every day based on reports containing quantitative measurement data. If measurement results are not accurate, then decision risks increase.
The need for increased accuracy is not as important as the need to measure quality. Accuracy should only be adequate enough to effectively satisfy each organizations established requirements.
The measurement of uncertainty is not an easy task. The following link address the steps of measurement of uncertainty
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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:
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Excellent question flagged here. Would be eager to know more.
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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.
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I think mike she will be best suited for integrated hydro metrological and water quality modelling purpose
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Dear All
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.
Kind regards
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Some forecasting methods such as orrelation analysis, group comparison, single regressionanalysis, multiple regression analysis, time-series analysis, input–output analysis, and system dynamics. Among these methods,regression analysis is widely used to forecast MSW generationdue to its mature theory and simple algorithms .Several literature have shown better results using time-seriesanalysis which appears to be the most appropriate forecastingmethod considering seasonal impacts . However, this requires a large number of data to pro-vide accurate forecasting in short term period .
In waste management perspective, time-seriesanalysis leads to lack of power of generalization and intellectualvalues, while factor analysis can explain the changes of MSW char-acteristics associated with influencing variables .Recently, Artificial Neural Network (ANN) has been shown having great ulitity.... Grey model has been implementedsuccessfully to forecast for long-term periods with higher accuracy than conventional time series analyses and ANN . Based on enclosed PDFs.
Please have a look at some of these PDFs.......
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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.
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please check the below links, may help
Regards
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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.
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Hi James. Here we need a single accuracy assessment criteria to compare overall performance of models with different inputs and modeling time periods.
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In the field of environmental modelling, who is the end user of a model? The person/group who made it or others?
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I want to express my humble opinion to Dr. Muhammad Anwar Iqbal on his interesting question.
Before talking about my personal experience related to the mathematical model, I would like to appreciate prof. Tom Koch and prof. Olivier Serrat for their s deeply thoughts that are reflected in their answers.
In 2007, the university refused my proposal for my desertion until I have designed and wrote the mathematical model. The chair of the committee considered the mathematical model as a core request. Writing that model has cost me an extra year of hard work.
Now, I believe that this model is an integral aspect of linking the conceptual framework or theoretical framework to practice. Without this model, bridging the gap between theory and practice is very difficult.
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Which specific environmental problems can be accessed or solved by environmental modeling?
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Evens Emmanuel thank you for useful information provided.
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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.
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The medium spatial resolution images could be used to capture the Ecological state of the Lake.
Examples of these are , the Landsat (TM, ETM+, OLI), ASTER (LIB, LIT), Sentinel-2, etc.
I have attached the (Spatial and Spectral band ) information of the above listed satellite images. Please see attached. You would find it helpful.
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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
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I would like to participate but the call for abstract page clearly stated 'All scientific staff and students of TU Vienna are cordially invited to participate in this event'. There is no sign for inviting external participants, could you clarify?
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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.
Thanks.
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Do you have an example you can share? Thanks in advance.
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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
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Yah really used full software to use it in hydrological fields like flood forecasting.
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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.
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Hi Kate.
You can contact the developer John for LEACHM directly.
John is very nice. He is active and doing volunteer work now although retired at Flinders University years ago. Here is his email: john.hutson@flinders.edu.au
Cheers
Rose
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- path planning robot simulation .
- 3D map environment model / robot workspace.
- mobile robot will autonomously navigate.
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Hello Ariff,
This choise it's up to you. There are lots of 3D environments and simulations such as Gazebo, MatterPort, MINOS, CHALET, THOR and Gibson. I have been studying on Gibson Environment based on pybullet. I can recommend it to you.
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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?
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Here, there are various libraries available to implement on the iris data set
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Hello friends!
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!
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Seems to me that you don't have 1500 "time series", you have 5 time series of ~300 samples each (though 10 years of monthly samples comes to ~120 samples, if my math is right). Vegetation phenology at a time "t" will be a function of your environmental variables AND vegetation status during previous times (t-1, t-2...). This time-dependence is where ARIMA models will be helpful: Rainfall in one season will affect vegetation in another season, etc. Seasonal Mann-Kendall analysis may be useful for comparing seasonal variability, too.
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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?.
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Vit Mateju , Nafees Mohammad, Mahmood M. Barbooti , Omar Ali Al-Khashman Mala Babagana Gutti and @ thanks very much for your reply, thinking on your countries of origen, would you agree with William McMinn that :
  • "A basic minimum would be Soil fraction OM, silt/clay content, Hg, Cd, Cr (3 + 6), Ni, (phytotoxicity Zn, Cu) , Pb with speciated PAH's or to recuce costs simply look at BaP ehich accounts for 96.8% of the toxicity for the whole group of PAH (unpublished work by Health Protection Agency UK 2003). Cation exchange capacity would also be useful.
  • Effectively you could apply the regional risk apprroach as outlined in REACH"
?
On the other hand, regarding about what to measure?, the remediation work would be to safeguard the ecosystem and therefore it would be important to measure Bioavailability and model the possible flow in the system, otherwise the toxicity and risk assestment wont be realistic. Moreover, even when toxic substances are on the natural level for a region, that does not mean they are not a danger.
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In your study area what is the most useful environment model? How would we teach undergraduate students about environment modelling at University?
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Environmental modelling is a broad subject. At the undergraduate level, I believe one should give a broad panoramic of the field and make emphasis in teaching the methodology and the process. A couple of really good books that I have used in my courses that satisfy these requirements are:
I hope this help!
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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..
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you can see that on average it takes 88 days from submission to first decision.
Some journals do not provide this type of statistics and for such journals you can download some random articles and compare submission date with acceptance date. This will give you an idea about the how long it use to take. If a journal does not publish submission date and acceptance date it is a strong indication that the quality of the journal is below common standards.
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Hi everyone
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?
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Models of any kind are either research/simulation models or predictive/forecast models or hybrid. GCM's have only a small amount of predictive value, depending in part on what variables they are used to forecast and for how long into the future. On the other hand, I think we need to learn to use the valuable information they give us about plausibility of future scenarios. Single predictive runs, and especially ensemble predictive runs, can tell us that a period of increased precipitation in one region may be very plausible, or very implausible, or somewhere in between. Such "predictions" are more reliable than a literal reading of one forecast for a single variable, a single year, and a single site, which should almost never be taken literally.
As a society, we need to have contingency plans for all plausible futures. This may sound undesirable difficult, but it is reality. We plan baby clothing before we know the gender of a child; we plan how to spend a salary even before we are offered the job; we invest in international moves before we have a visa. So the wise citizens of Tabriz are well advised to keep both their umbrellas and their cricket sets. I'd be nervous to give up either one in our changeable climate system.
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Hello everyone,
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?
Thank you,
Yi
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I would highly recommend that you look into the method described in the following paper:
The authors managed to supplement relatively sparse routine monitoring data with data on land use (such as from https://landcover.usgs.gov/) and satellite data (from NASA's MODIS https://modis.gsfc.nasa.gov/) to generate very good quality exposure data. This hybrid approach would be ideal for your purposes and would not necessitate collection of new data. The method requires skills in GIS and statistical programming using R.
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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.
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Kindly may check those papers:
Lal, R. (2004). Soil carbon sequestration impacts on global climate change and food security. science, 304(5677), 1623-1627.
Lal, R. (2004). Soil carbon sequestration to mitigate climate change. Geoderma, 123(1), 1-22.
Best
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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?
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Pretty old question, but maybe it's still worth adding to the comments given so far:
Type of weights: Spatial weights form a crucial part in estimating spatial autocorrelation. The choice of weights depends on a range of factors like the type of spatial behaviour you assume in the analysed process, the type of data you have at hand, the scale of your process, etc. Thus, there is no easy answer regarding an appropriate choice of weigths and it is ultimately up to a specific analytical task.
Software/different p-values: I'm not familiar with ape but have used spdep. spdep allows you to calculate distance-based weights. The function dnearneigh gives you binary weights indicating whether neighbours are located at a disc of radius dmax (dmin is also possible). If you need something like IDW weights, then you need to do some (not too extensive) R programming indeed, but it is still possible. In addition, spdep also provides functionality for creating k-nearest-neighbour weights through knearneigh.
Inference about Moran's I: There are two ways of drawing inference about Moran's I. One is called the Normal assumption (N), the other one is based on Randomisations (R). The N assumption is based on the so-called Pitman-Koopmans theorem that roughly states that Moran's I is independent of its denominator under iid normal variates. This assumption allows you to evaluate p-values of Moran's I from a normal distribution regardless of sample size, but under the (somewhat strict) assumption of normality. This is obviously a very efficient way of assessing p-values. In contrast, the R assumption is based on a permutation argument that assumes random reallocations of your values within the fixed set of spatial units. Therefore, the R assumption is a non-parametric one. While N is based on sampling with replacement, R corresponds to sampling without replacement, causing statistical power to be lower (because your decision is based on less information content). In the latter case you would construct a bootstrap from recurrently calculating Moran's I a certain number of times. The (pseudo) p-values are then assessed from that bootstrap distribution. However, even under R, Moran's I converges to normality rather quickly (though this is also influenced by the layout of your spatial units/geographic region). A valuable source for this is the series of seminal books published by Cliff and Ord (1973, 1981).
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Dear All,
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?
Thank you
(1) Keppler F, Hamilton JTG, Brass M et al (2006) Methane emissions from terrestrial plants under aerobic conditions. Nature 439, 187-191.
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Dear Aleksander,
I did a PhD on the ethylene production of Phaseolus Vulgaris L. and Marchantia Polymorpha L.
With the technique I used, I could measure methane, ethylene, ethane and propane as low molecular weight hydrocarbons at the sub-ppb level using a cryogenic pre-concentration technique. The plants were monitored in an open flow system, with very low backgrounds of the chemical species mentioned. The only hydrocarbon which was measurable with this system is ethylene, no methane, ethane or propane which were below the detection level of the measuring system (0.01 ppbv). It should be mentioned that I always removed the soil when I measured the plants in this system whereby the plants were watered with a glassfiber sheet substrate. If the soil was not removed some other of the hydrocarbons popped up above their detection limits.
It is my conviction that a large majority of plants do not emit methane, but when the soils wherein they grow are measured along with the plants growing on them, methane is bound to be measured as well.
Hence, methane is emitted by soils and not by the plants growing in these soils. Only the separate measurement of soil and plant has corroborated this finding, as I did in my PhD.
Hence, the measuring method has to be critically evaluated on the presence of soil in the measurement protocol or not!
Best regards,
Frank
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Dear researchers
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.
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I think response of @Mariel Gullian Klanian settles your first question. As for forecasting heavy metal concentration in other species using model results, presumably of another species, I think it may be possible but a bit tricky. Tricky because different species assimilate heavy metals differently. I think it is possible to do this within congenerics. It may be tricky and complex if you want to cross genus.
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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?
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Thanks a lot, my friend. A hug, C.
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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?
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Lack of adequate fundings, manpower & proper management and lack of awareness amongst some of the visitors are the major causes for deterioration of the existing historical botanical gardens.
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I need mesophyll conductance of corn for run an environmental model. How can I find this?
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Please let me know if the following reference/site is helpful to you:
 
Plant, Cell & EnvironmentExplore this journal >
Explore this journal >
Previous article in issue: Cryptochrome 1 regulates growth and development in Brassica through alteration in the expression of genes involved in light, phytohormone and stress signalling Previous article in issue: Cryptochrome 1 regulates growth and development in Brassica through alteration in the expression of genes involved in light, phytohormone and stress signalling
Next article in issue: Enhancement of root hydraulic conductivity by methyl jasmonate and the role of calcium and abscisic acid in this process Next article in issue: Enhancement of root hydraulic conductivity by methyl jasmonate and the role of calcium and abscisic acid in this process
View  issue TOC
Volume 37, Issue 4
April 2014
Pages 978–994
Original ArticleAsymmetrical effects of mesophyll conductance on fundamental photosynthetic parameters and their relationships estimated from leaf gas exchange measurements
Please see attached file:
Dennis
Dennis Mazur
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Mathematical Modelling
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I am enclosing our recently published work on the said topic. Hope it will be useful to you
Best wishes
Dr CS
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Any relative information concerning analysis for small data (except for linear regression,clustering & principal component analysis is appreciated )
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Dear Asmae,
ANNs are useful when:
  • There is no alternative direct (batch) optimization method  (such as multilinear regression),
  • The data model optimization problem is nonlinear.
Because ANNs often require iterative optimization methods that are time-consuming and may be sub-optimal (local minima).
Nevertheless, neural networks can address small datasets. But take care not to overfit your data in any case! To this end, prefer incremental learning methods. Follow:
Best Regards
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From the watershed and sediment management point of view, which aspects and effective factors of Functional and Structural sediment connectivity should be paid attention?
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Dear Robert,
Thank you for your explanation. I agree with your view. But there is one thing which need to be paid attention. Generally we think that functional connectivity is depends on the structural connectivity but I think some sediment transport processes (such as Sediment Storage or Sediment Redistribution) are due to of inconsistency between structural and functional connectivity.
I would like to know what you and other readers think about this matter.
Best wishes,
Saeed
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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.
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Both US EPA and the US Army (Dugway Proving Ground in Utah) have conducted extensive urban dispersion modelling studies with both real and modelled buildings. 
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Air quality modeling will vary with the geographical locations as the primary pollutants will vary. How could we generalize a model for the same?
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This is a vague question; air quality--and some accompanying meteorological data for selected pollutants in the US--data are available at epa.gov/outdoor-air-quality data.  This site have both "raw" data, formatted data, and data reports.  The raw data should be available on a site-specific basis, but I have not checked.  Generally there is a lag time of a year in putting the information on the web, but otherwise it can be obtained for many years on a site-specific basis. 
There are scores--probably thousands--of statistical and/or chemical/physical models used to estimate ambient air quality, depending upon the pollutant of interest, its "averaging time," its modeling domain, epoch, and receptors of interest.  See the above answers.
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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:
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Thanks, Heather! 
Unfortunately, I am not including grasslands. In this case, we are focusing only on perennial food or bioenergy crops. But I will check the methods of your paper, they are very interesting! and I may need to carry our a similar approach in the future (nice paper!).
Regards,
Alicia
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difference between stella and vensim?
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It's depends on features you want for the software. Let me know your purpose.
For educational purpose, both softwares (Vensim and Stella) are very good but I recommend you test INSIGHT MAKER because it's free, friendly, web hosted and very easy to use.
For a complete comparison table of SD software, please visit:
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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.
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Okay, I found Ritchie and spencer article. If you are interested in knowing about that, here is the link: http://admn502a2010a01.pbworks.com/f/wk_9_Richie_Spencer_Qualitative_data_analysis_for_applied_policy_research.pdf 
best!
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Assuming you have access to all kind of data, or if you don't have it, you can generate it.
e.g.
- national sales statistics of pesticides
- quantitative measurements of pesticide residues in water
- interviews with farmers expieriencing symptoms of pesticide poisoning
- farmer mental model analysis
etc.
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Hope this publication will also be useful.  It looks at a different dimension of pesticide use - which is self-poisoning using pesticides. 
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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.
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Thank you for your answer, however I should make my question more accurate: I am looking to such study in the framework of urban flood modelling.
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any one would like to answer, is there any precise and modeled equation which can predict the vertical distribution of soil moisture.
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prediction of soil moisture in cropped and uncropped soils has been thoroughly worked out, in most of crop growth models, eg DSSAT, INFOCROP, APESIM, which covers all the water balance components as well also deals with water stress effects for crop growth. FAO bulleting on water requirements of crops AND swot and SWATRE models take the soil water balance components. You can pl go through the google, you may go through GOOGLE Search engine and can get link with these models. These models primarily assumes freely draining situations and considers moisture redistribution after rainfall and irrigation events in 24 hours cycle and do not consider the inter-layer moisture movement under unsaturated environments, eg upward water flows in shallow ground waters etc. Some researchers worked on capillary contributions from shallow water table depths eg SAWAH model (HFM ten Berge et al., from Wageningen group) in this regard and but not commonly used but very important and there is a need to take it forward for strong calibration and validation for addressing these situations , regards
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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?
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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.
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Thanks for much to all for the responses, really helpful!
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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.
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Zoubair
Thanks.
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What are the main differences and similarities between Functional and Structural sediment connectivity?
Can we say they are acting in watersheds independently?
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Hello Saeed,
You can think of 'structural' features as elements that exist in the landscape or environment, even when there is no runoff or sediment transport (i.e. during dry weather). They might include the location and dimensions of patches of bedrock outctop, or patches of plants, or gullies, rills, roads, bunds, etc. 'Functional' connectivity means how the connectivity actually operates when the system is transporting water and sediment. This would clearly depend on things like the length of time rain lasts, how intense the rain is, how wet the soil might already have been when rain began. Structural connectivity in general would only change relatively slowly, but the 'functional' connectivity could change from minute-to-minute or over hours.
Hope this helps,
best wishes
David
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Satellite, flux towers, transpiration from plants can be one of them. The comparisons and dependency of these methods will improve my knowledge.
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Actually, I want to integrate the socio-economic data with the spatial data. I am looking for some precise models or methods.
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There are a number of books, the most important, which was applied for wetland restauration in LOwer Danube is a book written/edited by Edward Maultby, University of Liverpool. In addition, EPA (USA has a very good methdology as well) look at their web sites. For Maultby's book look for the chapters of the book, which were all published as articles and you will probably find them on ebscohost or any online library.
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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?
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Salmatta, Please have a look at a paper on impact of urbanization in one of my attached papers. Another paper describes the water balance procedure in a river basin. In your type of work, possibly you need to estimate future demand of water vis-a-vis population rise. But, first of all you have to assess if climate change has any impact on ground water regime, and if yes, how much. MODFLOW may help you with this. As part of adaptation strategies, you have to focus on demand-side management within the legal framework of the urban area you are working for. Good luck with your work!! 
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Dear Friends
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.
Yours sincerely
Bagher
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Dear Virendra and Omar
Thank you for your kind attention, actually you are really right.
Today's, the urban pollution is the most important environmental issues which directly affected the human being's life. 
Regards
Bagher
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Dear all,
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?
Best regards,
Sandy
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Richardo, 
You must change your ENMtools settings as similar as the tutorial (ENMtools option > show Maxent GUI &  Large file overlap/breath = yes).
Also, define the environmental layer path exactly.
Hope this help.
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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
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paper attached.
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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. 
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I very much agree with Sebastian Sauve. Fortunately, there are several equilibrium sampling techniques available that easily can measure freely dissolved concentrations of PCBs down to the pg/L level and some even down to the fg/L level. So when using one of the sensitive methods you are definetly able to detect the PCBs and likley even able to quantify freely dissolved concentrations of several PCB congeners. Here is an example of a very sensitive method that was applied to measure freely dissolved concentrations of PCBs in sediment:
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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.
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Hi Meran, I am not sure if you refer to Van der Waals surface area. In case it is, you can find it in chemical compounds database as for example "molinistincts". That´s the one I use in my study as molecular descriptor. Or what do you need it for? Maybe it would be useful to understand what you refer to.
Best regards
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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.
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The following minimum meteorological data requirements be established for
regulatory applications of AERMOD:
1. Data must be laterally and vertically representative. Representativeness should be
judged independently for each variable.
2. Surface characteristics around the meteorological site must be similar to the surface
characteristics within the modeling domain.
3. Surface characteristics around the meteorological site should be used as input for
AERMOD.
4. Adequately representative data for each of the following variables constitutes the
minimum set of meteorological variables that AERMOD requires for a regulatory
application:
i. Wind speed (at least one level between 7 times the surface roughness and 100 meters)
ii. Wind direction
iii. Ambient temperature (between the surface roughness height and 100 meters)
iv. Cloud cover
v. Morning radiosonde observation
vi. Surface roughness
vii.Bowen ratio
viii. Albedo
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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?
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Yes. Environmental harm fees/taxes should be strictly imposed so that industries/companies would make an effort to reduce the wastes they produce. They become more accountable to the their contribution to alarming rate of environmental pollution. The money/tax collected should be used for rehabilitation and conservation projects as to mitigate the effects of climate change
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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)
3. SIMDualKc
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. 
Thanks!
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Dear Sabrija Cadro, 
sorry but the web link within LEAF was disrupted. We are now trying to solve it and in the next few days it will be available for downloads.
In the meanwhile you may download the WinISAREG model and users manual using the following link
In what concerns the GISAREG application unfortunately it is not available since the language used to develop it (ArcView 3.2) is out of date and does not work in the current versions of windows.
An updated version of the SIMDualKc model (October 2016) is available at
if you have any doubt do not hesitate in contacting
best regards
Paula Paredes
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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 !
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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
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we built a new gridded data set for Africa at the 1/2 square degree (similar to CRU)
it is the website where we show the metadata behind the grids
monthly grids from January 1940 to December 1999.
Data available on demand, and soon available for free on the same website
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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?)
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The Club of Rome essentially did what you are asking for in its 1972 publication, "The Limits to Growth", by modelling a number of different scenarios. The results only of these scenarios were shown in a series of graphs, but not the underlying structure of the models. However, the structure of these models and subsequent models can be viewed and run using dynamic simulation software. One free software package is Vensim PLE. When using Vensim PLE (and other similar software) a conceptual model is first developed graphically using symbols for stocks, flows, and linkages. The direction of influence (positive and negative feedbacks) are then added. Quantification of influence is established by using equations and the model is then validated by comparing simulations against historical data and making necessary adjustments to the model. The validated model can then be used to create different scenarios by using slide controls to change the values of various parameters in the model. I recommend John Sterman's book "Business Dynamics: Systems Thinking and Modeling for a Complex World".
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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.
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Another problem comes in testing your model(s) against data. The more variables you have in your model, the more variables you'll need to test against to see if the model's good and so the more independent samples you'll need.
I like to read simple, mechanistic models because they are transparent. I am a bit suspect of big complicated models, mostly since so much is "hidden" -- assumptions and mechanics  -- making understanding and so evaluation tough. 
Your main challenge ,Xiaofeng Xu, is to make the model realistic enough for you (including using data to test assumptions and predictions) and simple enough to be understood, believed, and accepted by others.
Maybe we need and optimization meta-model for modeling!
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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. 
My questions:
  1. 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?
  2. Is there any other alternatives beside bootstrapping? Does using the total least squares method instead of ordinary least squares applicable in this situation?
Thanks!
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The attached paper may be of assistance. Best Wishes.
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Hi all,
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 ?
Kind regards.
Evans, E.
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Thank you!
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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.
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Upendra-
I'm not entirely sure what type of modelling you're considering, but at its most basic level, DZ data is typically analyzed in terms of "known" source areas.  To the degree that you know the age distribution and relative zircon fertility of the orogen, you presumably could fashion basic models to assess the relative probability of which components are contributing grains to the foreland basin through time.  This could be useful if the data record a distinct unroofing sequence.  There are many examples of this approach--one that comes to mind is Lawton et al. (2010) in Geology.
Good luck!
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Dear Researchers
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 
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Heiarchial cluster analysis, component analysis can be done to study the direct and the indirect interaction and interrealtion between the zooplankton community and the fish growth rate.... SPSS and SYSTAT can be used for the same...
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These days I'm searching for a software to model Pollutant transport in rivers.I would be gratefull if you could help me!
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hspf
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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.
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Ahmad thank you. I tried loading asciis of worldclim data in the projection (with all environmental settings and masks done using my area of study) following this manual and I still didn't succeed. 
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VGPM- Vertically Generalized Production Model
SeaBAM model
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I might suggest some absorption-based approaches, especially for coastal area, here are two examples:
Smyth, T. J., G. H. Tilstone and S. B. Groom (2005). "Integration of radiative transfer into satellite models of ocean primary production." J. Geophys. Res. 110: C0014.
Barnes, M. K., G. H. Tilstone, T. Smyth, D. J. Suggett, R. Astoreca, C. Lancelot and J. C. Kromkamp (2014). "Absorption-based algorithm of primary production for coastal waters for total and size-fractionated phytoplankton." Mar. Ecol. Prog. Ser. 504: 73-89.
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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!
Benjamin
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It will be better if you just tell the specific objectives and your target.
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Based on landfill characteristics and waste composition, the CO2 emission is quantified. How can the model be validated?
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Do you have any measurement data for "traditional" model validation? If not, there are numerous other validation methods, however less precise and less credible, e.g. different kind of reviews or face validation. If you have limited access of measurement data you may want to estimate the impact of uncertainties embedded in your model (inputs, parameters, model form uncertainty, numerical uncertainty). If so, you may apply some structured method for Uncertainty Quantification. See e.g. the comprehensive framework for UQ proposed by Roy and Oberkampf:
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I explore generalized parameters of aquatic ecosystems to assess the evolution of their state under anthropogenic effect. What parameters are preferable?
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I would add remote sensing data (satellite imaging for chlorophyll biomass, water turbidity) and atmosphere/water CO2 exchange.
Best regards,
Remi
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i want to put some modeling related to DO and BOD with reference physio-chemical parameters.  
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If it's surface water quality modeling in which you're interested, you will find a great deal of help at EPA's ORD Exposure Assessment Models Web site
Regards, John Yearsley
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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.
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If you want numbers with any meaning you have to dry it first.  Since you do not know how much water you have in the suspension, you can not correct to dry weight.  
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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
easily.
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