Subject: climate data + some help Posted: 9/11/2024 Viewed: 657 times
Hello everyone,
I am currently working on a project involving a basin in Crete, Greece, and I would greatly appreciate any guidance or assistance.
I have precipitation data from four stations and am using the Simplified Rainfall-Runoff method. However, I am facing some challenges due to the uneven distribution of rainfall, which is influenced by significant elevation changes across the basin.
When I imported a NetCDF file with data from just one station, the modeled streamflow values fit my observed data very well. However, when I used precipitation data from a different station, it overestimated the streamflow. My question is: How can I solve this issue and ensure that the precipitation values are more representative so that my modeled streamflow better matches the observed data?
Additionally, my study area has a karst topography, but I do not have any groundwater model to input data from. I am unsure how to address this, as groundwater may play a significant role in the hydrology of the basin.
Finally, I am curious about how the demand sites influence the streamflow. In the Simplified Rainfall-Runoff method, the streamflow is modeled as inflow minus outflow. My understanding is that inflow comes from precipitation and outflow is largely represented by evapotranspiration (ET). I would appreciate clarification on how demand sites should be factored into the streamflow calculations.
Thank you in advance for any advice or suggestions you can provide. I look forward to hearing from anyone with experience in similar situations.
Mr. Doug Chalmers
Subject: Re: climate data + some help Posted: 9/30/2024 Viewed: 215 times
Ioulia,
Apologies for the slow response. Here are some answers to help-
Were your catchments created by catchment delineation mode with different elevation bands? If so, the climate datasets within WEAP will predict different precipitation amounts at different elevations. Consider saving a different version of your model and then using the precipitation data from the WEAP datasets. You could then look at the ratio between the different elevation bands versus the elevation of your precipitation station. For example, if the WEAP datasets say you get 1000mm/year at 250m where your observed station is location and 1500mm/year at 500m, then you could set the elevation band in your model with the NetCDF to multiply the precipitation from the station * 1.5. You can also look to literature for more information on interpolating between climate stations.
Matching your modeled to observed streamflows is a larger question of calibration, which is tricky. Resolving your precipitation will help. For information on additional fixes to calibrate, please see the Catchment Calibration chapter of our WEAP Tutorial at: https://www.weap21.org/tutorial/.
To think about the influence of karst topography, the most effective tool to help you will be local data that has studied this. If you do not have this data, you will have to rely on literature or studies that have studied basins with similar geology. The information in the Catchment Calibration tutorial mentioned above is also relevant here.
Finally, in Simplified Rainfall Runoff, the basic equation is that Runoff = Precipitation - ET. To model the effect of demands, you can either create a demand site, or right click on your catchment and select "Includes irrigation". During calibration, it will be important to re-create the historical streamflow as best you can, including any historical demands that would have occurred in the observed flow record. This is different than the natural/unimpaired flow, which would not have any human demands.
I hope this all helps. Please let me know if you'd like additional clarification.
-Doug
Ms. IOULIA KOROPTSENKO
Subject: Re: climate data + some help Posted: 10/17/2024 Viewed: 65 times
Thank you for your previous response, Doug. It has been quite helpful.
I am facing a challenge with data availability, as I have five stations in my study area, but only one provides representative data for the basin. The other four stations have significant gaps in their data records. What would be the best approach to address this issue?
Additionally, I am considering creating a groundwater node in WEAP and linking it to my catchment node via an infiltration link specifically for modeling in a karst environment. Would this approach be effective? If so, how should the amount of infiltration in karst areas be calculated, and how can I determine the portion contributing to surface runoff versus groundwater recharge in such a context?
Furthermore, we have not yet defined any karst characteristics or incorporated recharge from the springs in our model. However, the results we have obtained -- based solely on precipitation and evapotranspiration (ET) data -- yield an R^2 of 0.65. How is this possible? We also have not implemented any crop coefficient (Kc) values yet. Could you provide some insights on this?
Thank you in advance for your help
-Ioulia
Mr. Doug Chalmers
Subject: Re: climate data + some help Posted: 10/17/2024 Viewed: 52 times
Ioulia,
A lack of quality data is a common issue when building a model. As modelers, we must advocate for new studies of needed data, but while we wait we must make the best use out of the available data and make assumptions when needed.
When calibrating to flow stations, in general you should start calibrating to flow stations that are upstream and are largely unimpaired without significant human diversion. Calibrate each of those stations with the best data available and then move downstream and adjust your calibration as needed to match the downstream gauges. You will have to match the different sets of years to the different gauges depending on the data available. This is common.
Yes, I would think that a karst topography would have significant percolation to the groundwater from precipitation. A catchment node connected to a groundwater node would capture this process. You should use the soil moisture method for your non irrigated catchments and calibrate the model to match your surface flows and produce realistic patterns of the soil moisture result. Completing the calibration without good data is a common challenge. In general, the best practice is to 1. Use available local data or literature, 2. Use data or literature from a different geography, but which you think is similar to your basin, or 3. Calibrate the hydrology parameters to reproduce gauge surface flows and create a realistic pattern of soil moisture in the shallow and deep groundwater layers
Sometimes, we can reproduce observed flows, but with the model not recreating the processes in the correct way. This can happen by luck, but then your model won’t work right for other climate years. Again, check the soil moisture to see if the hydrologic processes are realistic.
Hope this helps. Calibrating hydrology without good data in areas with complicated geography is a significant challenge.
