Questions related to Rainfall Runoff Modelling
I am going to derive the precipitation data from NETCDF files of CMIP5 GCMs in order to forecast precipitation after doing Bias Correction with Quantile Mapping as a downscaling method. In the literature that some of the bests are attached, the nearest neighborhood and Inverse Distance Method are highly recommended.
The nearest neighbour give the average value of the grid to each point located in the grid as a simple method. According to the attached paper (drought-assessment-based-on-m...) the author claimed that the NN method is better than other methods such as IDM because:
"The major reason is that we intended to preserve the
original climate signal of the GCMs even though the large grid spacing.
Involving more GCM grid cell data on the interpolation procedure
(as in Inverse Distance Weighting–IDW) may result to significant
information dilution, or signal cancellation between two or more grid
cell data from GCM outputs."
But in my opinion maybe the IDM is a better choice because I think as the estimates of subgrid-scale values are generally not provided and the other attached paper (1-s2.0-S00221...) is a good instance for its efficiency.
I would appreciate if someone can answer this question with an evidence. Which interpolation method do you recommend for interpolation of GCM cmip5 outputs?
Thank you in advance.
My study area is extremely large (multiple valleys) and precipitation is close to zero. Streams are often dry, but runoff almost solely comes from glacier melt and is heterogenous throughout the valleys. I have extracted stream boundaries for hundreds of basins using a machine learning algorithm and I can get channel geometry such as width/depth/cross sectional area (at any point along the stream), wetted perimeter etc. Is there any way I can get approximate velocity, discharge, etc at bankfull using stream geometry and a corresponding DEM? Maybe using slope and geometry?
any one know about how to prepare intensity duration frequency curve for estimation of peak flow for rainfall runoff modeling for ungauged watershed
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.
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?
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?
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?
After running a simulationa and comparing the simulated discharge with Observed discharge the values of Nash Sutcliffe coefficient has been -40.473, and after optimizing the value comes out to be -8.216. Which steps can i take to have NSE to 0.65-0.80.
Which factors can i optimize.
I am doing uncertainty in rainfall runoff model ("hbv") and wants to get optimal value of parameter, but the difficulty is the selection of the likelihood function? (the cod in Rstudio and interpretation)
I am a hydrologist and want to model baseflow (i.e. surface-water groundwater interactions) via the development of a numerical groundwater model (GW model). One of the critical input parameters for the development of the GW model is the hydrogeology of the catchment in question.
Bore-well lithology datasets required for preparation of hydrogeology map or Fence Diagram is very limited (2 borewell logs only), Since, my study area lies in the headwater mountainous region. I am planning to do an electrical resistivity survey for mapping the hydro-geology of the basin in the catchment area of 102 Km2. I have a few questions, in planning Electrical survey in the basin-
1. What could be the optimum number of resistivity profiles required for appropriate representation of hydrogeology of the basin?
2. How to identify the most appropriate locations for Electrical resistivity profiling representative of the basin under consideration?
I request you all to give suggestions in this respect.
During calibration of a hydrological model using synthetic data, I was trying to add Gaussian noise to the simulated streamflow data. But many streamflow values are near to and equal to zero, if I add a Gaussian noise with certain standard deviation (lets' say 10%), it will make many data values negative. But streamflow data values as negative will be invalid.
Could anyone please suggest how should I proceed ? Also, cite studies which supports that method.
- Which is the correct order in Data-processing of rainfall time series- Homogeneity test followed outlier detection & treatment (OR) Outlier detection & treatment followed by Homogeneity test?
- I have monthly rainfall data for 113 years. I am planning to run four homogeneity test- Buishand range test (BRT), Standard normal homogeneity test(SNHT), Von-Neumann Ratio (VNR) and Pettitt.
- Which is the appropriate method for identifying outliers in a non-normal distribution ?
- Should the descriptive statistics(DS) and Exploratory data analysis (EDA) should be conducted before (or) after treating the outlier? (or) a comparison should be made in the EDA & DS before and after treating the outlier
I have been trying to find out length of longest flow path, through GIS but it is always giving me the vlaue of 0.29 whereas my study area is 6896 km2. How to solve this problem.
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
I am looking for modelling tools that are capable of simulating the impacts of green infrastructure.
I was thinking about applying the downscaling statistical methods on GPM using the MODIS cloud level 2 . However, I am not sure about it from the prospective of its validity on arid or semi arid areas with low number of observations for instance.
I am trying to run the CESM model, in order to evaluate teleconnection in a rising temperature levels, in low-mid atmosphere conditions and the rainfall patterns in the Andes of South America.
But, I am newbie in this, so I am having some troubles indeed, when I execute the ./create_newcase this command does not create a new folder into my directory, I was finding out what I did wrong but I am lost
Can anyone help with this one?
Thanks a lot!
I am trying to run the CESM-atm model, but I don't get where is the path for the data, I am attaching an image of what must be the structure of the path.
By the way, I am running this model in my personal lap, so I had to do the porting proccess before, so I don't think that would be really the problem here.
Could anyone explain me what I must do for downloading the data for the model?
Thanks a lot!
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.
i wish to know how to decide whether we need to use MIKE Basin for a particular catchment or do we need to use MIKE Rainfall Runoff model NAM.
I want to work with HEC-HMS on rainfall-runoff simulation & when I wanted to build the catchment polygon layer, I faced the error that says:
"the system cannot find the file specified"
I searched a lot but I didn't find the way for my problem.
NOTE: The catchment grid layer has been built successfully, but when I checked it's file in the saving path, it had only 8 items, but the other layers had 9 items in their files.
It didn't have the log file, but the other layers had the log file. My system RAM isn't full.
What do you suggest for my problem?
We are aware that a shift in monsoon peak discharge may have an adverse impact on several water-based applications such as agriculture, dam operations, etc. E.g.
I'm having a hard time using TopoIndex (which is the first step). It keeps on getting an error which says that the corrections did not converge (regardless of how many iterations). Any troubleshooting tips?
Is there any way to calibrate a rainfall-runoff model with Hec-Hms anything other than discharge? The thing is I don’t have continuous discharge data availability. But I have water level and cross-section data. Is there any way to calibrate through water level? It's important for the thesis project I'm working on.
Because I see that to estimate soil loss throught USLE, RUSLE models, some researchers use models that are not compatible with the study region?
My study area of rainfall-runoff modelling is in mountainous region and has snow cover. There is about 10 percent snowmelt contribution to the discharge of the river i am modelling. How can I include snowmelt parameters to enhance my study? any tutorials on snowmelt modleing in hec hms would be welcome..Thanks in advance
I am doing my project work in snowmelt runoff modelling. I have collected a Matlab code which I found very difficult to understand due to its complexity.
Hi all, i'm trying to implement the SM2RAIN algorithm in python for estimating precipitation in USA based on soil moisture observations, i started by gathering data on county level.
I used " NASA_USDA/HSL/soil_moisture" for the SM observations, basically the SURFACE SOIL MOISTURE (ranges from 0 to 25mm), the temporal resolution is 3 days (the lowest available one)
For the precipitation, i used "IDAHO_EPSCOR/GRIDMET" for daily observation, i resamplead the data to 3 day accumulated values.
I implement the algorithm using this code freely available on github " https://github.com/IRPIhydrology/sm2rain/blob/master/sm2rain/algorithm.py ".
I normalized the surface soil moisture values and got started with on county (320 observation)
I used the pearson's correlation R and RMSE as metrics for evaluating the output of the model.
The calibration process was processed on the whole dataset
The issue is that i'm getting a low R value (below 50%), and the simulated precipitation always has the same pattern as the soil moisture.
the simulated precipitation cannot catch the hight values of observed precipitation as you see in the attached file (orange color: observed precipitation/ blue color simulated precipitation [only 30 points in the graph]
Did i choose the correct soil moisture variable ?
it is normal that simulated precipitation has the same pattern as the soil moisture ?
Any tips or suggestions are appreciated.
Thanks in advance.
I have downloaded the MSWEP sub-daily rainfall data (3-hourly data 0.1 degree resolution). I used MATLAB to convert it and obtained a table of dimensions 1800 x 3600 for a specific date. I am unable to understand how to interpret the resulting table. I am assuming the rows and columns represent latitude and longitude intervals. But I am not entirely sure of what the range is. I am a litle confused about how to interpret this. Any tips regarding this will be helpful!
I have prepared rainfall datasets for SWAT MODEL using 0.25 degree IMD long term gridded rainfall data,
but as I am using it in the model, it is rounding off the co-ordinates value.
eg:- for the latitude 19.75 and longitude 78.50, the name given to the file is PY1975X7850,
but in the textinout folder, the .pcp file for precipitation is rounding off the coordinates to 19.8 and 78.5.
If it is taking co-ordinate values to 1st decimal place only, then can't we use the 0.25 degree rainfall data in the input?
also it is not displaying the input data in the same format.
Kindly, refer to the attached video to understand the query.
Any valuable suggestions are highly appreciated.
I am doing a small research to review the water related open source tools / software (e.g FREEWAT).
if you have used/developed/ heard of similar tools,please share it with me ?
Thanks in advance
I am new to HEC HMS. and i am thinking to perform rainfall runoff modelling of a basin near my area using HEC HMS. The data i have is rainfall time series data and flow data of my outlet point. I want to estimate the discharge and compare the discharge obtained from the model to that of the real observed data..how can i perform the modelling without using soil data as i dont have any soil data or soil classification data of my region (for SCS CN method)?
Hi. I need an open source QGIS friendly software to model runoff in a big basin in Africa (17.000 km2). I know how to do it in Hec-Hms but it seams a bit amateur, because the choice of CN depends on user criterion. I would prefer to use a software that use DEM to calculate runoff. In the other hand, and as far as I know, Hec-GeoHMS works only with ArcGIS. Am I right?
Can someone tell me the pros and cons of IHACRES, TOPMODEL and EPA BASINS/HSPF ?
Here is the FAO Dependable Rain Method to computes MONTHLY effective rainfall
Pe = 0.8 P - 25 if P > 75 mm/month
Pe = 0.6 P - 10 if P < 75 mm/month
Where Pe is the monthly effective rainfall and P is the monthly rainfall
If I want to use the same formula to compute DAILY rather than Monthly Rainfall, can I do that?
DailyPe = 0.8 DailyP - 25 if daily P >2.5mm/day (or 75 mm/30 days)
DailyPe = 0.6 DailyP - 10 if daily P < 2.5mm/day (or 75mm/30 days)
Where DailyPe is the daily effective rainfall and DailyP is the daily rainfall.
See ⬇️, the upper bar has darker colours for larger errors, does it help the assessment of the agreement of obs (green) vs sim (red)?
Ex using different 🛰️ 🌧️ products, including #SM2RAIN https://www.earth-syst-sci-data.net/11/1583/2019/
I want to run a runoff simulation in a catchment and almost finished my model in python but, my concern is how to measure the impacts of an increase in 20% of the rainfall in the catchment. Should I increase the original rainfall dataset by 20%? or should I code the increasing part independently?
Thank you very much for your help.
i'm predicting the future rainfall using SDSM Software.
while calibrating (Period 1970 to 2000) the model for, conditional monthly frequency, SDSM is giving an error says " An error has occurred- please check all the selections. overflow has occurred ".
checked for the Predictand length it looks perfect for 366 days a year setting.
Predictors are Canadian Based NCEP-NCAR (1961 to 2005) of the box (27x , 41y) seems correct, all the variables appears while calibrating.
not able to Debug please do help.
check the Attachment for the error message.
I have a question for all the soil scientists and geo-hydrologists around.
We want to model the runoff behaviour of a couple of watersheds where some soil and water conservation measures will be implemented (something like small trenches to retain runoff).
Our model is something simple and we are building it for an area with little data available (thus the need to stay simple). We want to roughly estimate how much additional water (runoff and direct rainfall) can be captured by the soil and water conservation structures. The model is a simple water balance for which we need infiltration values (measured with mini disk infiltrometer), which in turns is influenced by soil texture.
We have collected quite a number of samples at surface (0 to 20 cm) and subsurface (20-50 cm) for this. Here is my question for you:
When on a budget constrain, which depth would you prioritize to characterize texture - surface or sub-surface?
Our gut feeling is to prioritize the surface samples, but i would love the opinion of some scientists with hands on experience (possibly with some references to prove the point).
Any thought on this would be much appreciated!
Thanks a lot everyone,
It can be lumped to a catchment level (with average rainfall and % of land cover types e.g. forest, agriculture, urban) or raster cell based. I agree that, there are many other factors such as topography, soil type, evaporation/evapotranspiration, distance to reach as well as daily/event rainfall distribution that influences the river discharge. But at the moment, the purpose is to compare the net change in river discharge (or runoff) in relation to change in rainfall and/or land use land cover only without needing to specify other information.
I tried the Soil curve number method using land cover and hydrologic soil group, but found it not suitable for monthly or annual data as the response for various amount of rainfall differ a lot and it is aimed for event level runoff estimation.
Thanks a lot for the help
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
I have a question about your work (Fuzzy Logic).
In forecasting something using FIS toolbox (in matlab) how to use previous output (T-1) as one of inputs?
I am trying to calibrate a hydrologic model for a large watershed in central Mexico(Lerma). I found several stream gages in the watershed, but hourly streamflow data from the gages is not consistently available till 2018. Also, I haven't been able to find any historical rainfall data. To collaborate my model, I need both rainfall & runoff data.
Can someone suggest any source to download rainfall and runoff data for the central Mexico-Conauga?
I would truly appreciate any help.
What data do we need?
I got 35 years of daily data of rainfall and river discharge.
I am working on this project for my final year research project in civil engineering.
The soil erosion rate level is different across the region, what is the acceptable erosion risk level for construction activity ? Any reference or comparison between country or region ?
Hi, I am working on road improve project in Africa Region. Of course we are going to project main road and its infrastructure system. We are developing main drainage and support drainage systems. Because of project site morphologic and climate conditions, runoff harvesting is main issue for our project. We will use roadside drains, outfall chanel, ponds in our project. I'm wonder what you think about following topics:
- How do you think we should calculate ponds-outfall channel shapes, lengths, diameters ?
- How do you think we should solve complex interaction between culvert or pipe structure under road and roadside drains (ponds-outfall channel) ?
Can anyone guide me how to use SCE-UA to get the optimized value of parameters, especially parameters from rainfall runoff model. I found one SCE-UA script written in matlab language, however, I can't find any part of the script is related to parameter of model.
As part of my research, I am modelling runoff discharge on a rural watershed. I would like to activate Land Use Update with SWAT. I am using ArcGIS 10.3.1 with ArcSWAT, along with SWATCUP 5.1.6 for automatic calibration. I used SWAT LUU tool (see https://saraswat-swat.rcac.purdue.edu/swatluu) to prepare inputs lup.dat and relevant files for 3 differents land use scenerios (2004, 2009 and 2017). My simulation goes from 2004 to 2017, with one year warm up (2004).
I noticed that when I run SWAT-CUP, it seems to find lup.dat, since deleting any of the associated *.dat files containing HRU fractions (HRU_FR) values returns an error. However, during the auto-calibration process, *.hru files are constantly edited, but their HRU_FR (first line) does not change. As such, it seems that land use update does not work.
Are there any recommended guidelines or anything I have missed ? In case any information is needed upon this, I would be glad to provided them. Thanks in advance.
Over the years, there have been numerous techniques developed to analyse baseflow recession as well as derive a recession constant, K (Hall, 1968, Vogel & Kroll, 1996; Kienzle, 2006; Dijk, 2010; Beck et al., 2013).
How you do select the range (start and end points) on the recession limb to derive the recession constant / do recession analysis?
Why did you use that rule? How is it advantageous over the others?
Is there any way to compute effective rainfall in Australia ? Like the the SCS-CN method for the US. It has to be specific to Australia, preferably from observation/experimentation in the field (empirical equation). I am looking for something different from the Dependable Rain (FAO) or the USDA soil conservation service.
I'm searching for some softwares (or methods) that can help me to model the fate of pharmaceuticals (or pesticides/chemicals) from runoff in agricultural soil.
I tried to use RZWQM and PRZM but without satisfying results; other ideas?
we are doing rainfall runoff mdelling Using SWAT.
we have two gauging sites where levels are measured.
one locations is weir and another one is controll crossestion.
both the locations are very close to sea. levels measured at both the sites are affected by the sea level variations.
i would like to correct these levels before using it for callibration and validation (we have stage disgharge relationship to convert levels into discharge) .
Note: we dont have the sea levels data.
Dear All Prof, lecturer, and researcher. I am Ali Rahmat, Master student of Gifu University. I am in confuse condition, I get home work from my supervisor to separate direct runoff and baseflow but I only have total runoff (water discharge). I try to approach used electric conductivity and water temperature data but still can not prediction when direct runoff stop.
Did any equation to prediction direct runoff and baseflow? or another technic to separate?
Thank you very much
I'm currently trying to study the flash flood risks in an ungauged area. Is there a recommended way to calculate the daily accumulated rainfall data in a certain location using satellites like TRMM ?
Hello! I am working on the project" Rainfall Runoff Modelling on Mahi lower sub basin".I want to calculate runoff but i got only Daily Rainfall data & other meteorological data of various rainguage stations.so from this data how can i calculate the runoff? can anyone help me please.