Hello NatCap team,
Is it logical to get negative values for HP_energy and HP_val when running valuation? I set the discount rate at 7 and timespan at 50 years.
Hello NatCap team,
I will be glad to get a response because i tried all options including manipulating fiures but i still get negative values
Hi @Safari1 -
The energy and value results are based on realized supply, which is based on water yield, so what do those results look like? Are either of their values negative?
Yes, the realised supply is in negative values. Could there be a problem somewhere?
I have been trying to find out the source of the problem. I landed on a screenshot here, which I compared with my results and realised that my precipitation is so low and so does the wateryield. I am convinced that the low precipitation is the leading cause for the the negative values, where the consumption volume is many times higher than the wateryield. I checked my precipitation input raster which i clipped from worldclim and it gives very low figures compared to the original raster. When I tried to calibrate, I realised that the mean precipitation for my catchment is around 1100mm compared to what my raster gives me. I tried different rasters from worldclim with different resolutions but there’s no significant difference. Can I take it that these results are a true definition of the catchment? This catchment has a major river with four hydropower dams. Ofcourse it could also be that water comes from the mountains.
I have attached some pics. The two legends, one is for the catchment and one is for the entire region before clipping.
Hi @Safari1 -
Can you describe the difference between “the catchment” and “the entire region before clipping”? The watershed_results shapefile has results aggregated to the watersheds that you provide as input. Does “the entire region” include the watersheds that make up “the catchment”? If so, the values in the watershed_results tables for each of these model runs should be the same for those “catchment” watersheds. For example, are the model output values for ws_id 2 (munirabad) the same in both tables?
In the first image, I do see many entries with negative rsupply and hp values. As you noted, these are places where the model calculated small wyield_vol values compared with the consumption values, so there is more consumption than water yield in these watersheds, which will lead to negative hp_energy and hp_val results.
Remember that water yield is calculated in a very simple way in this model, essentially (although not technically) precipitation minus evapotranspiration. So it’s not only low precipitation that causes low water yield values, but also high evapotranspiration.
I’ll also suggest that, although we do provide calculations for hydropower energy and value, these are VERY rough estimates, based on very simple net present value methods. If you need to calculate accurate values for real-world decision-making, make sure that you are calibrating the model against observed data, and then do the valuation outside of the model, so you can address the local context more specifically.
thanks for your response. To be specific, of the two attribute tables, mine is the top image with a lot of negative fields, and I compared with the bottom which i just download from this community plattform.
Yes, the entire region (merged) includes the watershed (precipitation_clim). I just clipped from it. I however run it too in the model and it gave me the same results just as you have put it. What puzzled me is how wateryield can be this low yet the precipitation in real world is high. And the realised supply also being negative is very unrealistic in the real world. I am trying to explore more and I have learnt something. I would be glad to learn more.
Does the precipitation raster that is used as input accurately represent the high precipitation in the real world? Even if it does, if the ET raster is also high, then a lot of that precipitation will be lost to evapotanspiration before it can be used in the realized supply calculation.
And honestly, I wouldn’t rely on the realized supply/valuation portion of this model, but recommend doing your own service/valuation analysis in post-processing. The model is extremely simple, and likely does not represent the complexities of where water comes from that is consumed in the basin. It assumes that all of the water that’s used comes from that same basin, which may or may not be reality. In this case, it sounds like the model is estimating that more water is used than is produced in this watershed, which is (unfortunately) often the case in the real world, but then the water comes from somewhere, often groundwater pumping or from a different watershed, neither of which are included in this model.
To me, this absolutely clears my doubts. I decided to drop the valuation and concentrate on biophysicals and scarcity though.