Hi Raphael,

Thank you for your time, I am intending to use a distributed model. What I am trying to say is that I know that rain gauges get different amounts of rainfall depending on the the relative distance of the typhoon from that gauge and how fast that typhoon is moving (and the duration of the typhoon). Now obviously, these gauges will have different data. What I am trying to push through is using these data from these gauges as data for my catchment model. I wanna correlated these data into a single input but i dont know how. (I'm thinking of just interpolating the data, dependent on how far these gauges are from my catchment model but i'm not sure how to and if it is the best method)

If I understand well, you want to reconstruct rainfall spatial distribution to some extend and use it as a input for your hydrological model. How to do it (and if it make sense to do it) depends both on a spatial scale you are working at and requirements on temporal resolution of input data. E.g. if you want data of one minute temporal resolution and your RGs are 10 km from each other, they will be probably completely decorrelated and any interpolation does not make much sense. Can you specify these details?

Hi Raphael,

I am just trying to get distributed precipitation data for my flood model and once that's achieved, I want to simulate a flood in my model, I can get data of that passing typhoon for my model though. 

Hi Martin,

Yes, my 3 gauges are 10-15 kilometers part, i am planning on simulating a typhoon passage of 6-24 hours. The thing is, I want to model a flood based on an actual passage of the typhoon through that catchment basin and compare it the actual flood reports.  (in the figure below, the ones marked in red are the RG's and the white one is the catchment basin

The above figure shows that your data is too sparse and your catchment to be modeled is very big.At what time interval your rain gauges measured rainfall data?.You may not get accurate results with data from only three points.

I agree with Puppala that RG data is really sparse. If you cannot get more rainfall data I would suggest not to do any interpolation but assign to subcatchments rain rates from nearest rain gauge. Thiessen polygons can be used to decide which subcatchments should be assigned to which RG. Interpolation makes sense only if RG data are correlated. And I doubt that you find stronger correlation for high res. rainfall data (time step 1, 5 or 10 min) which would be appropriate for modelling runoff in urban area.

I fully agree with Martin's comment.Interpolating data for big catchment with just three points is meaningless.

I agree with all comments above. I would mention also another thing. It is not clear how your catchment is defined. However, it seems to me that you are either going to model very small area limited by Marikina River, Pasig River and Mangahan Floodway or the whole catchment of Marikina River. In both cases, RGs are located outside your area of interest and it means that you would not interpolate any data but extrapolate. It would be a problem even in case of a catchment between your RGs (which would be a case of interpolation) but I'm almost sure that you cannot get reasonable results in case of extrapolation due to high spatial variability of such event. As mentioned above, you would need more detailed data.

Hi Guian Carlo,

I also have this problem. if you solved this problem, please help me.

thank you

Dr.Guian,Your question is not clear.What I understood is that you want to correlate rainfall at three locations to runoff amount of the catchment.We donot know the area of the catchment.whether the 3 locations can be representative of the catchment or not is not known.in addition to rainfall other factors such antecedent soil moisture,land cover,slope etc.Instead of simple correlations you can try hydrological models