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Hydrologic and Water Resource Modeling and Simulation - Science topic

Hydrologic and Water Resource Modeling and Simulation is a streamflow measurement and modelling, methods and research.
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There are many commonly used methods for esimtation of evapotranspiration which are based on temperature, radiation, mass and energy transfer etc. or a compbination of thse. Methods such as Penman-Monetieth, Pendman, Hargreaves, Priestley-Taylor, Thronthwaite etc. fall under these categories. What I want to know is the applicability of these methods primarily based on the climatic conditions of the area. Like whichmethod is suitable for humid conditions or arid climate? If someone asks me what method should I use to estimate the ETo for an area in Mumbai, which method should I use?
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The standard ET measurement method is the so called FAO 56-PM method. But different studies indicated the preference of other empirical methods according to the specific climatic conditions they studied, For example, based on the study of Gao et al. (2017) the Priestley-Taylor performed better in Dry climate, Hargreaves performed better in semi dry climate and Makkink methods performed best in humid climates. So it depends. It is also important to note that now a days ET could be predicted easily by machine learning algorithms.
F. Gao, G. Feng, Y. Ouyang, H. Wang, D. Fisher, A. Adeli, J. Jenkins Evaluation of reference evapotranspiration methods in arid, semiarid, and humid regions
JAWRA J. Am. Water Resour. Assoc., 53 (2017), pp. 791-808,
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Hello,
I am using MODFLOW 6 transient simulation and have the following listing file. I wonder about two of the outputs. See attached screenshot.
  1. What those STO-SS & STO-SY mean? Are these total available water in storage? is it change in storage? If so, what is the difference between in and out?
  2. What is the meaning of positive recharge in the recharge package (RCH) in the out section? I would have expected it to be equal to zero.
I will appreciate your response.
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Adil Sbai, thanks for responding. I am still not sure about recharge values as an output from the porous media - for that there is the Drainage package. I can only assume that In recharge is the flux of water fed into the model as recharge at each stress period, and the Out recharge is the flux of water that has been rejected as recharge at the same time point. Does it make any sense?
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Greeting.. suppose i'm missing continuous half hourly water table data for extended period (say a month) due to instrumentation failure, can I fill the gap using a nearby monitoring station that, from long term observation, seemingly share the same trend/fluctuation? which model is recommended that uses adjacent water table data as input? Personally, I was thinking along the route of using artificial neural network
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I have used statistics as analysis of variance to compare data and come up with relationship if it exists. But usually at the beginning, I graphically plot each data set on a time scale. Hand plotting was quite consuming, but computers and software make this easy. For exceptionally long records, I might even use a plotter to plot long periods of record, or break it up into meaningful time segments. By looking at this data visually, one can see any noticable time lags, intensity of response, compare groundwater hydrograph and recession curve responses. Sometimes the spatial response of Two separated sites will depend on the direction and speed of the storm, and this may be helpful when trying to recover data. Weather agencies may save the Doppler storm tracks. The more one knows about the individual station responses, their trends or correlation, the storm specifics (direction, speed, spatial extent, etc.), the more reliable the recovery of data can be. The visualization of time series data plot of two locations of interest in comparing, and with storm Doppler data, can be very helpful beyond just model or statistical recovery.
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(Matlab, R, Python, ...??)
taking into account the current evolution of artificial intelligence
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Alessandro Farina Makes an excellent and very important point about working in a collaborative environment. When working with colleagues or simply in a group environment, rather than alone, communication is key. To make use of the power of a group, you need to be able to communicate with each other efficiently and effectively. So to quote Alessandro:
"if your colleagues already use Matlab" {or something else}", then go with Matlab " {what they use} "since you will be able to deal problems with them and you will speed up your work."
"If you work alone because you don't have many colleagues ..." you have more freedom to choose.
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I have received data for 50+ rainfall stations in my study area. Is there any mathematical formulae which gives optimum number of rainfall stations for trend based climate change study ? All of them have missing values in them, ranging from 1% to 50%. Upto what percentage of missing values can be filled by statistical methods and how to determine the threshold limit (whether 10% or 15% or 20%). If any literature is available on this, kindly intimate me
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Interesting question, which considers two topics: the optimum number of stations and the maximum percentage of missing values.
The optimum number of rainfall stations depends on different factors, for instance the temporal resolution of the measurements (hourly, daily, monthly), the spatial variability of rainfall in a particular area and the purpose/ use of the rainfall data. Hourly measurements generally require smaller spatial scales (and hence more rainfall stations per unit area) than daily or monthly measurements. Areas with a large spatial variability in rainfall (e.g. convective rainfall, tropical areas, mountainous areas) will require more stations per unit area than areas with less spatial variability. Regarding the purpose and use of the rainfall data, it certainly will make a difference whether rainfall data are directly used (e.g. for early warning or trend analyses) or used as input in for instance a hydrological model. In the latter case, the rainfall data are filtered and spatial and temporal rainfall variability is dampened through the rainfall-runoff transformation (i.e. hydrological fluxes and water storage compartments in a catchment). See for instance these papers on appropriate spatial resolutions and number of rainfall stations: , and .
As Vishnuvardan Narayanamurthi also indicated, there is no fixed maximum percentage of missing data. Again, this depends on the spatial and (in particular) temporal variability of rainfall and the use of the data. Highly temporally variable rainfall should have less missing data than more smoothly varying rainfall. One way to look at this is to determine the temporal correlation length by constructing a temporal variogram (temporal correlation coefficient as a function of temporal lag). Temporal resolutions should be typically much smaller than the temporal correlation length and hence, filling data gaps should be done at smaller temporal scales than the temporal correlation length as well (often not much more than a (couple of) day(s) for rainfall). Obviously, when for instance rainfall trend analysis is carried out at larger spatial scales (grid scales instead of station/ point scale), temporal variability will decrease and some more missing values would be acceptable and can be interpolated/ filled in.
Good luck,
Martijn
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Four homogeneity tests, namely the Standard Normal Homogeneity Test(SNHT), Buishand Range(BR) and Pettitt test and Von-Neumann Ratio test (VNR) are applied for finding the break-point. Out of which SNHT, BR and Pettitt give the timestamp at which the break occurs whereas VNR measures the amount of inhomogeneity. Multiple papers have made the claim that "SNHT finds the break point at the beginning and end of the series whereas BR & Pettitt test finds the break point at the middle of the series."
Is there any mathematical proof behind that claim ? Is there any peer-reviewed work (Journal article) which has proved the claim or is there any paper which has crosschecked the claim ?
Let me say that I have a 100 years data, then start of the time series means whether it is the first 10 years or first 15 years or first 20 years? How to come to a conclusion ?
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Well, I do not know much about these tests you are doing. What you say in the last sentence is more related to my experience. I have prepared a paper on day temperature series and used split-line models with plateau phase followed by linear or nonlinear phase (same can be done if various trends are followed by a plateau phase as happens in Mitscherlich's diminishing returns (Exponential curve). There is also a test which helps to decide if linear trend in two sub-periods are equal or not.
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I attended a training to learn Hydrological Modelling Using SWAT, which is a widely used model, back in 2018.
We discussed about the details regarding calibration and validation of a model and were told that 7:3 is like a golden ratio for calibration and validation. Basically, if you have 10 years of observed data, you calibrate the model for 7 years and validate the same for 3 years. As a beginner in hydrological modelling back then, I engrained this piece of information in my brain.
But as I keep reading through various research materials, I have realised that there is no obvious pattern or thumb rule for this. I recently read a paper which calibrated a model for 1 year worth of observed data while validating the same for 5 years.
So I'd like to know your approach when you work with a hydrological model and the factors which influence your decisions on how much to calibrate or validate.
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Interesting question. In addition to the very useful comments and replies from colleagues, I would like to add some observations and comments. The calibration and validation strategy depends on different factors, such as the purpose of the modelling and possible final application, the availability of data and the hydroclimatological conditions in the studied catchment(s).
The modelling purpose can be very general (e.g. simulation of hydrological regime and behaviour of a catchment), specific (e.g. low flows) or supporting water systems and infrastructure design (extreme, non-observed conditions) and future impacts (e.g. due to climate change). Calibration and validation strategies for general purposes can be more straightforward by using the split-sample test and dividing the time series in two parts, indeed generally somewhat more data for calibration (e.g. 2/3) than for validation. Specific purposes and support for design and impact assessment require more tailor-made approaches showing the robustness of the model. For instance, for flood design purposes one would like to show that the calibrated model can also be used for more extreme conditions than the calibration conditions. Hence, one might select the calibration and validation periods in such a way that the validation period includes more extreme events than the calibration period. In this and similar cases a so-called differential split-sample test is therefore more appropriate. Similar reasoning applies for climate change impacts studies, where you might want to show that your model can also be used for changed climatic conditions. This can be (partly) achieved by selecting a validation period with (hydro)climatological conditions more similar to the expected changed climatic conditions than the calibration period.
Data avaliability obviously determines what is possible in the calibration and validation. When for instance streamflow data are not sufficiently available, you might look for alternative data regarding other output variables such as actual evaporation (e.g. based on satellite information) or state variables (e.g. soil moisture, snow and groundwater). Different calibration strategies for multiple variables (and objectives) are available in the literature, see for instance .
Recommended splits for calibration and validation periods (e.g. 50-50 or 70-30) will also depend on the hydroclimatological conditions in the study catchment (e.g. the occurrence of dry and wet periods) and the hydrological model used. The systematic study mentioned by Mehmet Cüneyd Demirel provides a nice example of the detemination of the optimal data length, but results obviously depend on the hydroclimatological conditions, the catchment characteristics and the model used.
Good luck,
Martijn
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  1. In non-parametric statistics, the Theil–Sen estimator is a method for robustly fitting a line to sample points in the plane (simple linear regression) by choosing the median of the slopes of all lines through pairs of points. Many journals have applied Sen slope to find the magnitude and direction of the trend
  2. It has also been called Sen's slope estimator, slope selection, the single median method, the Kendall robust line-fit method,[6] and the Kendall–Theil robust line.
  3. The major advantage of Thiel-Sen slope is that the estimator can be computed efficiently, and is insensitive to outliers. It can be significantly more accurate than non-robust simple linear regression (least squares) for skewed and heteroskedastic data, and competes well against least squares even for normally distributed data in terms of statistical power.
My question is are there any disadvantages/shortcomings of Sen's Slope? Are there any assumptions on the time series before applying it.? Is there any improved version of this method? Since the method was discovered in 1968, does there exist any literature where the power of the Sen slope is compared with other non-parametric? What inference can be made by applying Sen slope to a hydrologic time series explicitly? What about the performance of the Sen slope when applied on an autocorrelated time series like rainfall and temperature?
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Two points. The approach is pretty similar to what Boscovich proposed in the 1700s, so if dating this type of procedure you can go further back (Farebrother, R. W. (1999). Fitting linear relationships: A history of the calculus of observations
1750--1900. New York, NY: Springer.) Second point. A disadvantage is it will be slow for even medium sized n. Here is a quick coding of T-S compared with the lm function in R (which is slower for n=10 because of all the checks it does before estimating the model) and what I assume is similar to the main computation bit in it. At n=10 they are similiar-ish, but n=100 T-S is much slower (note different units).
> theilsen <- function(x,y){
+ n <- length(x) # assuming no missing
+ slopes <- {}
+ for (i in 1:(n-1))
+ for (j in (i+1):n)
+ slopes <- c(slopes, (y[i]-y[j])/(x[i]-x[j]))
+ beta1 <- median(slopes[is.finite(slopes)])
+ beta0 <- median(y - beta1*x)
+ return(list(beta0=beta0,beta1=beta1))
+ }
> lmb <- function(x,y) solve(t(x) %*% x) %*% t(x) %*% y
> library(microbenchmark)
> x <- rnorm(10); y <- rnorm(10)
> microbenchmark(theilsen(x,y),lm(x~y),lmb(x,y))
Unit: microseconds
expr min lq mean median uq max
theilsen(x, y) 249.101 271.3515 764.2949 303.4510 373.6505 42047.800
lm(x ~ y) 1222.101 1293.1510 1496.4859 1419.3010 1594.7010 5597.801
lmb(x, y) 100.001 103.3010 271.7730 120.2015 186.0010 7302.101
neval cld
100 ab
100 b
100 a
> x <- rnorm(100); y <- rnorm(100)
> microbenchmark(theilsen(x,y),lm(x~y),lmb(x,y))
Unit: microseconds
expr min lq mean median uq
theilsen(x, y) 60628.902 75446.151 91017.986 76951.5510 80715.9015
lm(x ~ y) 1187.001 1377.951 1619.025 1659.1510 1807.2015
lmb(x, y) 100.600 111.702 176.185 192.4505 215.2015
max neval cld
543952.501 100 b
2262.701 100 a
303.602 100 a
>
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I have 18 rainfall time series. On calculating the variance, it was found there was an appreciable change in the value of variance from one rainfall station to other. Parametric statistical tests are sensitive to Variance, does it mean we need to apply robust statistical tests instead of the parametric test?
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Kabbilawsh Peruvazhuthi, Generally Parametric tests are to assume equal variances across groups. You could potentially resolve issues either with some data transformation or switching to a non-parametric equivalent test.
Best !!
AN
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After running a simulation in HEC-HMS, I'm getting the following warning:
Warning 42403: Time of concentration increased by one time interval (24h) in basin X.
This is causing my simulated hydrograph peak to occur 24 hours after the observed peak.
What can I do to resolve this issue?
Thank you.
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Harsch, you need to give some more detail about your model setup in order for anybody to be able to say anything about what may be the cause of this.
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I read a thesis which used the formula v = K(S^0.5) to determine the flow velocity in a channel. The value for conveyance K was adopted from Ward and Trimble (2004) and was mentioned to be equal to 5 for a river bed composed mainly of sand and gravel. Can anybody help me find the K value for a river bed which mostly consists of boulders with patches of vegetation?
Thank you.
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Thank you everyone for replying. I had an inkling that the equation referred to the Manning's equation. That is why the thesis author using a K value of 5 by jyst looking at the channel bed surface made no sense to me. To be honest, tgat thesis smells fishy to me now.
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I have used the following parameters to simulate:
1. Loss method: SCS-CN, 2. Transform method: Clark UH, 3. Routing: Lag.
My simulated peak occurs 1 day after the observed peak.
It shows "Warning: Time of concentration increased to one time interval at subbasin X" which I'm assuming is the reason for the discrepancy.
What parameters can I adjust to shift the peak by 1 days and to esolve this error?
Thank you.
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Brahim Abdelkebir I've found that if the input time of concentration is less than your simulation time step, then it is automatically increased to match the simulation time step (24h in our cases). So you'll have to reduce the simulation time step. The output graphs will look weird but this is the only solution I could come up with.
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I want to set up a minimum amount of outflow (1500 cumecs) through a junction or reach or basin so that if the inflow there is less than the value above, it results in zero outflow. Is it possible?
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Define a reservoir, then put a pump on that and play with the rule base of the pump such that it always pumps unless (some condition you like)
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I am trying to use HEC-HMS for streamflow modelling of a river. The thing is that I have only one gauge in my study area located at the outlet of the catchment. I've been through some materials which mention that inflow data is a basic requirement. However, the gauge flow data at the data at the outlet has to be considered as outflow data if I'm not wrong. Is there any other way to go about this?
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You can use the outlet observations for calibrating the basin parameters as well as MC parameters which depend mostly on your river cross-sections. So only outlet discharge observations is enough for modeling. You have also chance to see the modeled inflows of the channels in hms and you can compare inflow and outflow hydrographs.
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I want to check the Homogeneity of a rainfall time series. So i applied the following four methods and found the time series to be non-Homogeneous
  1. Von Neumann ratioTest
  2. Buishand range test
  3. SNHT
  4. Pettitt's test
Is there any R package available in CRAN which make non-homogenous series back to homogenous ?
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Did you normalize or difference the data? If time series are rather long, you may make fractional differencing too.
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Although I check that the flow accumulation tick is OK in display options, but still there are no streams on the map...
How to fix this in order to continue watershed delineation?
best regards
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Dear Qussay
you must tick flow direction in display option to view flow streams
Best Regards
abas
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Have a nice day everyone, I've created a watershed model via WEAP software for modeling water budget of a basin. Now, I'm planning to construct another model using another software/program for modeling the same area and compare different models' performances.
Lastly, I'd like to ask you about "Pysheds" model's weaknesses and strenghts, plus I'd be so glad if you could share with me tutorials through which I can figure out basics of "Pysheds"
Thanks in advance
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IntErO model for calculation of soil erosion intensity and runoff
Dear colleague/s,
(to Ibrahim, but open to some other interested colleagues)
I am kindly inviting you to have a look at the application of my IntErO model for the calculation of soil erosion intensity and runoff (link):
IntErO model
- Free download of the software;
- Simple installation;
- Examples of applications available on the same web page (but also on RG and on www.geasci.org/Publications);
- I, as an author, am available to demonstrate how it is working.
Finally, in case you decide to compare the results received with using the IntErO with some other model/s and or measurements, I will try to arrange to finance the publication of the paper having in a team of authors two of us from my team,
Sincerely,
Velibor Spalevic
Mob/Viber/WhatsApp: +38267201222
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Grubbs's test and Dixon's test are widely applied in the field of Hydrology to detect outliers, but the drawback of these statistical tests is that it needs the dataset to be approximately normally distributed? I have rainfall data for 113 years and the dataset is non-normally distributed. What are the statistical tests for finding outliers in non-normally distributed datasets & what values should we replace in the place of Outliers?
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Hello Kabbilawsh,
If you believed your sample data accurately represented the target population, you could: (a) run a simulation study of random samples from such a population; and (b) identify exact thresholds for cases (either individual data points or sample means or medians, depending on which better fit your research situation) at whatever desired level of Type I risk you were willing to apply.
If you don't believe your sample data accurately represent the target population, you could invoke whatever distribution you believe to be plausible for the population, then proceed as above.
On the other hand, you could always construct a Chebychev confidence interval for the mean at whatever confidence level you desired, though this would then identify thresholds beyond which no more than 100 - CI% of sample means would be expected to fall, no matter what the shape of the distribution. This, of course, would apply only to samples of 2 or more cases, not to individual scores.
Good luck with your work.
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I have Monthly rainfall data from 1901-2013 for 29 stations covering the entire state of Kerala. I took the first 80% of the data for training the model and the rest 20% for validating it. I developed SARIMA monthly model for forecasting rainfall. The reviewer has asked What is the scientific basis for forecasting rainfall over a point location (station) over a longer time scale (a Month)? What was the reviewer trying to convey by this question?
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Hi Kabbilawsh,
You developed a statistical model based on the long-term observational data, which may have incorporated certain interannual variabilities intrinsic in climate system affecting the specific place. However, you have not understood what cause the interannual variabilities, or why the monthly precipitation is predictable. The reviewer would hope you to give an explanation (in discussion) about the drivers or mechanism underlying the variabilities.
Good lack.
Guoyu Ren
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Dear colleagues,
Actually, I am looking such discharge data for any stations in Sobat river basin and the White Nile basin, as well.
I will be thankful if someone can share it with me.
Regards,
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I have to implement Green Ampt Infiltration equation for daily time step with regional scale over different Land use/Land cover conditions. The Green Ampt parameters are estimated using soil properties, how the equation could be improved for different LULC conditions and what could be the effect of varying spatial and temporal resolution in model performance.
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That is a good question.
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Hi friends! I ran my project successfully, however there are some reservoirs in my basin. Hence, I have to rewrite data again and set the reservoir parameter up.
Unfortunately, I don't work and the text box show that my reservoir area and volume have to be less than a number (I showed in the picture below). Meanwhile, my real reservoirs are larger than that number.
Does anyone get the same problem with me?
Your answer will be a big help for me. So many thank!
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Alicia Chong So sorry friends, I just read your question now. I suppose that you've already known the answer. However, I write here to help the other persons who have the same question.
You can use the access function of Microsoft to open/edit/save a .dbf file.
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Hi
I'm using three different performance criteria for evaluating my model:
1.Nash–Sutcliffe (NSE)
2.Percent bias (PBIAS)
3.Root mean square error (RMSE)
You can suppose that I used a regression model to estimate a time series data such as river mean daily discharge or something like that.
But for a single model and a single dataset, we saw difference performances for each criteria.
Is this possible? I expected that all of these three criteria have same results.
You can see the variation's diagram of these criteria in appendix pic.
Thanks
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There is nothing surprising. Different criteria, different results. If these matched, would obviously be redundant (Occam).
By the way, the Nash-Sutcliff criterion is generally questioned (see https://doi.org/10.37162/2618-9631-2020-1-176-189).
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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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Is anybody familiar with AquiferWin32 ver 4.0?
I need a jump start on how to run this program, specifically how to add background in the model, add well and then run. Thanks.
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Hello, is there anyone to help me to do groundwater pumping and monitoring wells data analysis using this software? I may pay you little ....Ahsan
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I am using SWAT to simulate stream flow in a river. All the steps are performed well, but the error appears when I come up to the last one "Run SWAT". The error is released by cmd.exe as the attached photo. I do not know what kind of error is it and how I can correct it as well. Please give me any recommendations to solve this problem. Thank you very much.
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This problem occured when you make an error while you fill the Weather generator in SWAT2012.mb data base.
Re-check it your PCPstata, and dewpoint input data.
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Hi,
Except synoptic stations, does anybody know any website/software that gives the climatological data of unequipped places?
I am aware of using interpolation methods, but, I am looking for a method that extract data for a desired location numerically (like an excel format etc,.).
Thanks,
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Interesante pregunta, sería muy bueno poder acceder a sitios o software q aportaran esta información
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The parallel drainages are commonly observed over estuarine environments, flood plains and reservoirs of the area
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We also faced a similar problem in the Jhelum basin. In larger basins, you are very much right that natural drainage is not always available for stream burning. Further in our case, the pseudo drainage occurred in flat surfaces and over the lakes. For lakes, we had the lake polygon layer to burn. I think increasing the threshold is one of the viable options that does reduce such spurious drainage lines.
The solution lies in between the opinions provided by W. J. van Verseveld Richard Gloaguen Neelakantan Sajikumar
Thank you all for this wonderful knowledgeable discussion.
Regards
Gowhar Meraj
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Hello all,
i am new to water chemistry, i have been looking at trends in the water chemistry parameters, and found there is significant decreasing trend in Stream-water temperature, Ca, Mg, Na, and chloride along with discharge both in the monsoon and non-monsoon seasons.
Like From Jan 1994, Jan 1995, Jan 1996...... Jan 2018 (for Non-Monsoon period) Sept 1994, sept 1995, sept 1996...................Sept 2018 (Monsoon period)
Note- watershed (1000 km2 drainage area, Western Ghats, India) is free from dams and other water structures.
What could be possible drivers of trends in the above parameters?
Please provide your valuable suggestions.
Thanks in advance.
Regards
Rajat
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A couple of my earliest Researchgate entries and citations may be informative, even though different conditions. Many water quality parameters have influence from flow rate (discharge), and in part often due to rainfall dilution effect, runoff and movement of sediment and other non-point pollutants and nutrients during storms. You may find a hysteresis effect with markedly higher values during rising limb of hydrograph, and lower rates as hydrograph recedes. Geology and groundwater and its chemistry influences contribute to varying degrees as some streams loose water to groundwater, while others gain water inputs from groundwater for substantial periods of time. There are many books and papers on the subject, as well as professional or informational courses. It is not unusual to find these trends. Stream temperature in many locations increases in the summer growing season as more solar radiation, higher temperatures with lower streamflow often combine to elevate temperatures. Streams heavily augmented by groundwater or springflow as well as dense forest cover have substantially less effect than conditions without these benefits. In one of my studies, mountain streams without dense forest cover actually had lower winter temperatures, so forested stream buffers may have a moderating effect on temperature extremes in both summer and winter. It is highly useful to have recording water levels to estimate flow rates with time. A relative moderate expense tool for this is transducer (vented or barometric adjusted unvented). Streams with excessive sediment may contribute to transducer fouling, but properly installed, they can collect high quality data for weeks or months without service. The USGS collects flow data every 15 minutes, and appropriate for your study area. For small catchments, more frequent readings may be needed. A variety of tools or techniques are available to collect samples during storms or more routinely, if ample research funding exists.
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I am unable to find literature having acceptable rainfall performance criteria as is available for other parameters such as wind, temperature, etc. Is it correct to define a criteria based on the 90th or 95th or similar percentiles from the population of rmse, mean error values?
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Dear Researchers,
I run multiple times my SWAT-CUP SUFI2 but it is contineously giving this problem as attached in picture. Please let me know your expert opinion why I am facing this error and how to fix it.
Thanks in Anticipation.
Kind Regards
Naveed
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how to solve the SWAT_CUP error dispalyed in figure below.
with 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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I have a daily flow data at the outlet of my basin. From that data, how can i estimate base flow parameters?I am currently using constant monthly method and i am using a trial and error approach..but i want to explore other possibilities of baseflow methods such as recession baseflow for which i would beed recession constant, initial discharge and ratio to peak.. How can i estimate these parameters?
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There are many ways of estimating baseflow from measured flow data. Note that all of them are estimates; there is no way of knowing if they are right. So, one has to use the flow data to estimate baseflow parameters and then feed them into a hydrological model, HEC-HMS or some other model.
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I see huge discrepancy between researchers (difference for the same class is somewhere up to 0.2). What determines the choice of the appropriate value ? What is the role of spatial resolution of the research in this ? Thank you.
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Manning's n or roughness coefficient is actually a measure of energy or head loss along a channel reach. The roughness of the channel, bank and floodplain is a major determinant of Manning's n. However, all mechanisms that contribute to energy loss should be considered in selecting its proper value. For example, flow velocity and associated turbulence are important (e.g., if velocity is near zero, the Manning's n will be zero even when the river has high roughness). Similarly flow depth is important. So is the season (e.g., more vegetation and thus higher roughness in summer).
I think engineers should think of Manning's n as more related to energy loss under specific flow conditions than to only roughness.
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Of course there is "urban" table, but it isn't enough since I try to model large city. Especially I have problem with green areas such parks, lawns, orchards and courts. BTW, in the table there is a field "urb cn" with value always 98 - does it force CN number in HRU?
If so, is it a good idea to split landuses on urban+grass, depending on %of impervious surface?
I've chosen swat+ because of its popularity, but maybe there is a better software for hydrological modelling of urban areas?
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It depends on how you want to represent the urban. The urbca2 are the default values but if you have your own values you can change them in "SWAT2012" though the name might vary with the version. Usually default value is okay.
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I am very new in hydrodynamic modeling. Recently, I have done a simulation in SMS-SRH 2D. Now, I want to perform calibration and validation of my model. But, I have no basic on calibration and validation. Can anyone give me some documents or tutorial or guidelines on calibration and validation of numerical model which will, not only build my basic but also make me able to perform on my existing simulation?
Some specific questions:
1) What are the parameters need to be used for fine tuning of model during calibration?
2) If I have limited observed data, will model give satisfactory result?
3) During validation, shall I use different cross section of another time period for my model domain?
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Hi, you are talking of hydrodynamic mathematical 2D model. For calibration and / or verification studies, you would require a few prototype hydraulic observations, like velocities with direction, depths of flow, water levels at different locations. Corresponding discharges are of critical importance. If gauge discharge curves are available within the reach reproduced in the model, then it is of immense value.
You will require discharge hydrograph for control of discharge at the upstream end and a gauge discharge at the downstream end of the model for water level control.
As you are at the "Verification stage", it is assumed that these are already available and used for the studies.
Initially, you are required to run the model with the specified discharge values at the upstream end and water level control curve at the downstream end.
The first stage is to reproduce the average water surface slopes for the different discharge stages. For calibration of the same, the Mannings' value on n needs to be corrected / adjusted.
After getting satisfactory results, for the specific discharges (Depending up on the available prototype data) you may have to look at the flow conditions (Velocities with direction, depth of flow, etc) for the specific discharges.
Most of these verification studies are problem-dependent. Each and every parameter observed at the site may or may not be correctly reproduced all the time. A description of the modeller is many times required.
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I am looking for a hydrological model and a crop model that i can couple to predict crop yield and also to develop an improved irrigation scheduling for dry season vegetable production in a river basin in Ghana for a PhD research work. Please I need suggestions on hydrological and crop models that are available for free on the net. Thank you
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You can use Cropwhat . you can download from FAo.
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I am required to do a project where I have to calculate discharge of streams/ watersheds in a high altitude area with extremely treacherous terrain. Will it be possible to achieve this objective using GIS and remote sensing, without field observations ?
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Dear Bro. Indranil Mondal
You can
Please find the attched manual file, it will help you:
all the best
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Is there any particular rule that told us in what condition we allowed to rebuilding missing data in a synoptic station? For example, if a station has 15% missing data over 30 years, can it be filling? In other words, is there a specific rule that says up to what percent of missed data we can reconstruct it and used in drought studies? Can this data be filled in by taking a regression from the station itself, or should it be filled in by nearby stations? The time steps are in monthly. Do you have any referenced article for that?
Thank you in advanced Best Regards
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we usually use regression techniques (mostly linear) by utilizing data from the nearby or at least closest stations in columns. Moreover, for temperature data, we sometimes create random points to extract from remote sensing imagery and create a column to include the regression process. Although each process comprises uncertainty itself, we think they still represent the required climate data in case of data scarcity.
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I am new to hydrogeology but I want to understand what is required to be measured at the field or site which will form basis for MODFLOW FLEX 3D modeling.. I want to to know the specifics to be gotten at the site. The rivers, lake, recharge... where do I require resistivity, every form of measurements needed to be calculated, please I’d like to know and where I can get the information I need as well... thanks
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Dear Lawrence,
Since you are new to hydrogeology I would suggest you start with Applied Groundwater Modelling by Andreson and Woessner and Groundwater Modeling - An introduction to groundwater flow and solute transport modelling by Rausch. Also Fundamentals of groundwater modelling by Huasam Baalousha. The latter two are available on Research Gate, but the applied Groundwater Modelling good is not only a good read but a good reference.
The first question of groundwater modelling is do you need a model? Several basic calculations and analytical solutions can be better than using a groundwater model. There are good flow charts to follow in regards to the modelling process.
As you start to read you will start to realise that although modelling is data intensive, models if conceptualised correctly can be very useful even with limited data. Some of the parameters can be estimated via a literature review if not available and can be refined during the calibration process.
As Ajoy Saha said at the very least some basic geological information is a must that is followed by hydrological data and hydrogeological data (T, k, water levels etc.).
My final comment will be to kindly remember that the software is a programme that can be used once you understand how to work the programme. However successful groundwater modelling or any other modelling is dependent on you understanding the limitations of your data and the limitations of the final product.
Best Wishes,
Raoul
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Rainfall erosivity
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According our results for the Czech Republic conditions the relationship is not statistically significant. This should be always verified for local conditions. Strong statistical significance exhibits for example longitude for the Czech Republic conditions.
Best Regards.
Jiri
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I have known some physical-based models and emperical models, i.e., the original Stefan model (mainly used in permafrost regions) and its modified modes. However, I consider there would be some better methods to quantify the dynamics of frost depth in seasonal frozen soil region.
Due to the characteristics of two-way melting of the soil during the thawing period in seasonal frozen soil regions, the prediction of the frost depth during the thawing period becomes more complicated and difficult. Are there any good methods to quantify the dynamics of frost depth during thawing period?
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Thank you for sharing your latest related research, I will read it carefully!@Yijian Zeng
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Currently, the combined effect of all clouds is one of net cooling, meaning that clouds are dampening the rate of climate warming. But scientists are looking into whether clouds will have the same effect on climate as the Earth continues to warm. If the proportion of different cloud types changes, it could affect the rate of climate change because different types of clouds have different impacts on the Earth's climate. While some types of clouds help to warm the Earth, others help to cool it?
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Well,
The answer can be found in the earth's energy budget as shown in the attached figure.
Regards
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Hi, i noticed on youtube that a lot of researchers change the unit of the degree slope map to radians on raster calculator while the original formula stays in degrees. because if we work by degrees, the result will be negative values, on the other hand in radians, there will be positive values.
Best regards
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You must go through my article: " A Review of RUSLE Model".
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Raindrops falling on the soil
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Dear Mourad,
I do not think that this material exists in one of the research laboratories in Algeria. Maybe you have to look at the meteorological office. It may be equipped with such a device.
Regards
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Coefficient of determination R^2
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Coefficient of Determination and Nash-Sutcliffe Efficiency are based on least squares so give greater weight to the peaks. A high CoD can indicate the peaks fit well but not the recessions. You can get a better idea of the fit of the recessions by taking logs. There are other measures you can use if you trawl through the literature however I used a combination of NSE and logNSE to indicate the fit of my models when working on my PhD. However what value to pick is a very good question - the answer to that is dependent on so many factors and is often a case of as good as you can get given the uncertainties involved. Good luck. It is probably good practice to determine your limits of acceptability before you start to model then throw out any models that don't comply - again trawl the literature particularly the work of Keith Beven.
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We know that there are lots of tools to manage the floods. Those tools may be software tools or procedures. But have we clearly identified all the components and stakeholders in the tools?.
Then I have developed a conceptual model which consists of not only stakeholders but also the hydrology model and GIS model.
I need to confirm the model or need your observation to modify it.
Hence express your ideas on
1. Do you agree with the components identified?
2. What are the additional components to be included in the model?
Thank you
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@Rmm Pradeep
I am working as a consultant for WRD, Assam. The department receives the model outcomes (prepared by NESAC) during flood time and takes action based on it. The department was a part of the decision makers during formulation of the model and one of the end users too.
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I have eight rainfall events with length of 476 days. i want to predict the peak discharge and peak time.
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Use Microsoft Excel, which has a wide range of functiona
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I am trying to calculate the LST of three land types existing in permafrost regions of NWT, I am using Landsat-8.
Is the thermal imagery of Landsat-8 a good source for deriving LST of a local scale?
And,
I was wondering,
which time of year is the best time for this process?
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It would be a good idea to compare the interpretations based on different seasons of the year. Winter would give you an idea of where areas with limited snow cover occur, and so the ground is likely to be very cold. Areas with large amounts of snow would be possible areas of discontinuous permafrost or where if might be absent. In summer, the topography would give you a good idea of where palsas/lithalsas might be present and the vegetation tell you where peat plateaus may occur. Look up the appearance of these on aerial photography. Do not forget to carry out a thorough literature search and incorporate the results of prior field studies by others to guide your interpretations. Otherwise you my end up clashing with the results of good field and laboratory studies. Check with the appropriate Territorial government bodies who carry out these studies as well as the GSC. Also check your interpretations against the available climate data, especially mean annual freezing and thawing indices based on seasons.
Stuart.
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we are considering to develope the SUSTAIN model adding some new functions. the officia website on USEPA applied the source code of its interface and simulation engine, but it's an extension tool based on arcgis 9.3.1, we have no idea to use the dll files, got from source code, with arcgis platform.
asking for help sincerely, by a rookie.
moreover, is there any possibility to transplant this model to newer version of arcgis 10.x, that could be a "big" project which USEPA was not willing to do.
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I think SUSTAIN Was developed by a private company on behalf of the US EPA and you might be able to get specific information about modifications from them.
The SUSTAIN manual refers to the company as follows:
Tetra Tech, Inc.
10306 Eaton Place, Suite 340
Fairfax, VA 22030
And the authors on the manual included:
Leslie Shoemaker, Ph.D.
John Riverson Jr.
Khalid Alvi
Jenny X. Zhen, Ph.D., P.E.
Sabu Paul, Ph.D., P.E.
Teresa Rafi
If you can find a contact for any of these folk on researchgate, Linkedin, or elsewhere, you may get a response? I was able to talk to some people at Tetra Tech back in 2013 or so about using SUSTAIN so they may still be open to discuss how easy it might be to port the model to ArcMap 10, and/or modify functions?
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Hello all,
I am looking for Acoustic Doupler Current Profiler (ADCP) which are found to be performing well for streamflow measurement. please share experiences and suggestions for selection of appropriate ADCP for streamflow measurement.
Thanks.
Regards
Rajat
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Thanks Dr. Darren, Dr. Hening and Dr. Guilermo, for suggestions on ADCP, it will be helpful in selection of Appropriate ADCP. Shared ADCP Report is of immense help.
Regards
Rajat
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Dear Researchers,
I have created the soil user file and now working of LULC file. I have done almost all only remaining are following:
Townland and
Ruralland
Both belongs to urban landcover, so its code must come from Urban database and accordingly code ID will be assigned in the user define Land-use text file. AM I right?
Secondly, Desert, Dryland and Plaindryland I am still struggling how to replace them from the land cover closest category.
Could you please guide me how to fix these problems.
Thanks in anticipation.
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Due to environmental impacts of dams such as:
- problems for the surrounding area, for plant life,
- dams block up flowing bodies of water, such as rivers, any animals that depend on the flow to reproduce or as part of their life cycle are put in danger.
- Harm water quality and temperature.
- Block fish migration
- ...
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From the previous answers, a lot has been said regarding the potentials usefulness of dams, which is really good. I would like to adress in this answer, for the sake of discussion, some key points regarding why dams can be problematic to us.
It appears that during the past decades, wild river streams (ones that run free from headwaters to confluence) have nearly been wiped and then replaced by river dams. Fact is, dams disrupt natural systems and subsequently thwart the work of rivers. They block fish runs, seasonal flood patterns, affecting redistribution of nutrients (like marine nitrogen delivered by salmon to feed the inlands).
Dams encourage unsustainable growth, displace people, often indigenous people
Very often, dams are built through grants of institutions and rarely benefit the local people. Most of the generated hydropower (if any) is delivered to big cities, not the rural villages displaced by the dams.
Even from a design perspective, it appears dams are made to fail. A huge reservoir surfaces mean terrible annual evaporation losses. Silting is unavoidable. Even the largest reservoirs silt up. When they collapse, it is nightmarish.
Some researchers point out dams are not the solution to our energy crisis. Solar and wind can provide far more reliable, long-term energy than hydropower with far fewer environmental costs.
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What I want to know is that table value only for United State or It can be used over the any place of world?
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SCS CN Curve number method give you better result but it has some restriction it is applicable for small catchment and ungauged watershed.
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I have a Annual Rainfall time series data (1987-2017). I am determining the trend in the data using MK test. However I found that if there is a serial correlation we should go for MMK test.
Therefore I calculated correlation coefficient at different lags for the original data (upto10 lags) and found that the correlation coefficient are within the tolerance band (within upper limit and lower limit at 5 % significance level) except at lag 4 it is above Upper limit.
Does this mean the series is autocorrelated?
What is the criteria for going for MMK test?
Do we really need to perform student t test corresponding to lag 1 correlation coefficient? Is this test justifiable?
This makes me confused because at lag 1 there is no auto correlation (it is within tolerance band) however at lag 4 there is auto correlation.
So there is mismatch. Student t test would entail no autocorrelation whereas the correlation coefficient at lag 4 entails there is auto correlation.
Your help would be appreciated
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@Vasker Sharma, you can use the autocorrelation fuction syntax in R,that is acf (), assuming you have a monthly data series of a data frame called Rubi, to check for auto correlation at lag=1 in the January series of Rubi in R you type as follows;
acf (Rubi$January,lag.max=1)$acf pressing your enter key will display the autocorrelation plot at lag=1,you will clearly see the limit line marked in blue,if your output crosses the limit line in either the positive or negative side of the divide then you can say that the January series of the data frame called Rubi is statistically significant at lag=1.Modified Mann-Kendall (MMK) is then recommended,in such case i will recommend the Bias Corrected Pre-whitening (BCPW).
Best of luck
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Does anyone know how to calibrate a PR2/6 SOIL MOISTURE PROBE in the field?
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see my profile to get the publication related to the calibration.
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Hello Everyone!!
i'm working on Hydraulics particularly on Scouring,
i have Scour depth data and Parameters affecting to scour. now i would like to carryout sensitivity analysis on the parameters to predict the scour.
Currently i don't have the scour model, based on data i would like to carry out Sensitivity analysis ,
please suggest some suitable method for the sensitivity analysis.
Thank you.
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Hi Praveen,
You might have a look at the correlations between the scour depth data and the parameters. If there is a high correlation between the scour depth and a particular parameter in the data, you would expect that this high correlation is also present in a (good) model and hence the model output (scour depth) is sensitive to variations in this parameter.
Good luck,
Martijn
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Hi,
I would like to estimate very roughly the time necessary for a river to travel a long par of it's course (approximately 50km).
Sadly the course has not been studied, neither modeled, we don't know the shape and section of the river on a distance that long. Anyway we have several measurements of the river flow (middle of the river, 1 meter deep) along the river course.
We would like to reach the magnitude of residence time of water, in order to compare it with pesticides half-life in water.
Thank you for sharing your knowledge,
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Well,
Ct = C0e-kt, Where
C0 is the concentration at t = 0, that is, at the upstream boundary of the river section of interest.
Ct is the concentration after travel downstream for time t.
x distance downstream
v stream velocity , the time of travel (Residence time, when inlet=outlet) is t = x/v.
The coefficient k indicates how rapidly the pollutant disappears from the water; high k means faster disappearance. k has units of 1/time (time-1).
Regards
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I am looking for data set to develop a flood forecasting system specifically for an agriculture dominated watershed. The requirements include a) fine resolution DEM b) land use type and soil hydrologic group c) hourly/sub-hourly rainfall data for a minimum of 30 years d) hourly/sub-hourly stream flow data and e)demographic details of the area. It would be helpful if you suggest any data repository/experimental watershed for collecting the above mentioned data. I assure you that the services offered will be duly acknowledged.
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I agree with previous two answers. I must say that there is no single repository of datasets for the whole world. Most often GIS repositories are at state or country level. DEM is most commonly available GIS data. Land use could be variable in resolution depending on the country. In regions where there is no land use maps, you could use remote-sensing to define a better land cover map. Soils data is mostly FAO dataset V2, which is coarse in scale. Soil surveys with countries have better resolution. For rainfall time series, try to contact your meteorological department. You need many stations for watershed modeling. Streamflow is often used to calibrate and validate and often available only in long-term monitoring stations. Many rivers are ungauged in the world. For demographic information, census is best but is available at census district levels. If you can specify the watershed you are planning to model, I can suggest datasets better.
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We observed a huge difference between simulated and observed outflows from a catchment during a hydrological modelling exercise in HEC-HMS. The catchment contains numerous ponds and smaller lakes (of varying areal extent), lacking operational data. How can we account for the effect of these storage structures in the hydrological modelling?
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I am not totally familiar with HEC-HMS. I believe that it runs by reaches, with a stage, storage, outflow for each reach, is that correct? If so, then you need to make each reservoir along the river to to have its own stage storage outflow information. This is challenging modeling, so it will take some time to fully describe each of the reservoirs.
If you are modeling the upland runoff to HEC-HMS using the Curve Number methodology, there is a way in the method to account for the effect of reservoir storage in the sub basins. Let me know if you need some suggestions on how to do that.
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I'm looking for methods to separate different sources contributions to suspended sediment concentration / sediment yield :
Either to quantify the volume or to obtain partial concentrations of the hillslope portion or the in-chanel portion based on Time-Discharge-Concentration data series.
Most methods I find use fingerprinting, I don't have the data required for such methods. Thank you !
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Even if you ultimately want to be able to differentiate the contributions from the multiple sources of sediments without taking into account the characteristics of the watershed, a modeling approach, like the one proposed by Timothy O Randhir, could help you initially to derive a (graphical) model of your own, calibrate it, and validate it. It could be something like this:
  1. Calibrate a couple of models for specific watersheds (maybe with different types of hysteresis loops) to match the observed flow and sediment load.
  2. Take a subset of the models to compute the percent contribution from the hillslopes for a set of events.
  3. Extract meaningful statistics from the observed data (Q and C) for each of these events (e.g., precedent conditions, Q magnitude, number of peaks, storm duration, percentage difference between Q and C, lag times, etc.).
  4. Train a model (e.g., regression) that estimates the modeled percent contribution based on the extracted statistics.
  5. Test the derived (regression) model on the other subset of watersheds that were not used for its training to verify accuracy.
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R and DEM (pysical model )?
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Obviously there is difference between R and DEM (physical model).
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I have four values of discharge such as discharge value of 1, 15, 18 and 25 august. I want to construct a unit hydrograph from these values. How can I perform this?
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Actually, to built unit hydrograph need automatic water level recorded, if you have only 4 discharges for one time, you have to built rainfall prediction plan in that time to make discharge estimation in that time
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What is the main challenges in water sector based on main events? (like drought, flood, agriculture, industry, etc)
I'm looking for a framework or divide of challenges in this manner.
like we can say in agriculture main challenge could be the low efficiency of irrgation.
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Protecting water as a vulnerable resource - water saving awareness- responding to climate change impact on water – increasing water use efficiency – using the right price for water services.
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I have downloaded the data but observed that each year is given in separate files. I need to extract each year separately that is time-consuming. Does anybody know any easier way to extract data together in time series from 1961-2007 for a particular location?
Thanks,
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APHRO_MA_025deg_V1101.1951 is this a netcdf file ? it does not open by any standard netcdf reader
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Dear Researchers, I have daily flows data 1961-2015 and some of the months flows data is missing. This missing period varied; 1 mont, 1.5 months, 7 months, randomly. I would like to ask how to generate this missing data? Please share your expertise and skills. Thanks in anticipation Regards Naveed.
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Hi Naveed,
Assuming you have temperature and precipitation data, you could setup and calibrate a rainfall runoff model to predict missing flows. If instrumental data are not available, most places in the world have gridded meteorlogical data which often works better for runoff simulation than direct measurements from a met. station. You could make the met data as simple or as complex as you like, we've had surprisingly good results for most of the Indian subcontinent using a single precipitation and temperature time series to model river flows. There are a range of straight forward and easy to use rainfall runoff models. My group has had success with Jan Seibert's HBV-Light model and my PERSiST model.
Sincerely,
Martyn
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I'm dealing with a time series of stage data (water surface level) measured with a pressure transducer submerged in a river. In a an early analysis, I've found noise in the data and moved on to apply a filter (like Savitski Goulai) to smooth data since it will be used as input to a hydrological model. In a futher analysis, I've found that the noise was actually oscillations with a semi-diurnal period, i.e. approximately 12 hours, with peaks at 10:00 am and 10:00 pm, which corresponds to the peaks of barometric pressure (known as barometric tide) measured in a nearby station. Therefore, I suspect there was something wrong with the barometric compensation of the measurements. Probably I'm working with an absolute transducer, not a vented one (not sure about the source). Some compensation had to be made since stage data is not very high (as you can see in the Excel file provided).
My questions are 2:
1. Are the oscillations really the result from barometric changes in pressure and incorrect compensation from the transducer?
2. More important: is there any way, knowing the "real" closeby atmospheric pressure, to compensate and eliminate these oscillations?
Thank you in advance!
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Yes, as answered. However, during active growing season, some of the diurnal changes in small streams noticed may be due to transpiration demand by forest. I have used an Insitu sonde that was unvented, and they sold a barometer that could be installed nearby, and with it software that corrected the stream stage readings. The same would be true of well levels when using pressure transducers, adjustment for barometric pressure is needed.
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For a linked simulation-optimization modeling, how can I run the GMS (Groundwater Modeling System) software using C ++ programming commands?
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One thing you can do... If you save the native text documents while creating your model. then all the files will be saved in text document. then you can easily run modflow exe file with name in c++
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Has anyone a complete data of a coastal aquifer to simulate saltwater intrusion using GMS software?
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IN GMS there are tutorials which you can download from their official website. from there you can get a complete data set for simulation of saltwater intrusion.
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Dear Researchers,
I would like to ask that between Water Flow and Balance Simulation Model (WaSiM) and Cold Regions Hydrological Model (CRHM) which is good model in permafrost hydrology prespectve. I have to choose anyone between these two models. I am confused and not yet finally decided.
Expert opinion is highly appriciated and valuable.
Thanks in anticipation.
Regards
Naveed.
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Hi Marcos,
First of all thanks for your detailed comment.
I have contacted with the developers of CRHM and they have provided me required information which was very helpful for me to select the most appropriate model for my research scope. As long as concern about my research work, i will mainly focus on the runoff generations under changing climate from the permafrost zones due to dynamics of the Active Layer Thickness (ALT). The CRHM is better to use in the cold environments have mainly covered with snow and CRHM is applicable to the tundra or other like this environments found in Arctic, Canada and Alaska's regions.
WaSiM model simulate the dynamics of the active layer thickness more better as compared to CRHM and also gave three dimentional variations in the soil temperatures.
Therefore after review some articles and some other literature, I finally selected WaSiM. I can use CRHM if I found that I have enough time to simulate using it as well. By comparing both the model's results, I will conclude the application efficiency as well as I will be able to write some good articles.
Thanks a lot for you precios time and detailed comment.
Regards
Naveed.
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Hi,
Please let me know is this the right approach for the calibration of flow in SUFI2?
1. I should first check the performance of initial model with observed data :
i. Should I compare the simulated results given as "flow_out" in the "rch" file in SWATOUTPUT.mdb with the observed data?
ii. Should this be performed for the whole discharge period or only the period for which I intend to perform calibration?
iii. Should I compute the waterbalance before doing calibration using my first model and pleae let me know what else i should check apart from comparing the observed and simulated discharge in the first step.
2. Based upon the comparsion of simulated and observed flow I should do the regionalisation of parameters.
2. Sensitivity Analysis to find out the parameters most sentive for the watershed with regards to flow.
3. I should set the range for the parameters identified in step 3.
Can i first use the ranges provided as default in SWAT-CUP or I should set the ranges based on literature review (in case I find any). For this step I should run the simulations from 500-1000 times and check the values of Objective funcion and 95PPU and r-factor. If the ranges are satisfactory then those ranges set for the parametsr will be final otherwise i should repeat the model for another 500-1000 simulations by changing the ranges.
please correct me if my approach is wrong.