Seven Steps Into Catchments analysis by Hydrological models

 First step: Overall

Define the overall scope of the analysis. (e.g. Blöschl et al., 2019)

Document about the literature existing on the catchments. Including papers appeared in any type of studies.  Choose a large set of  performances indicators (depending on the model use and objectives) (Addor et al., 2017).  Set a strategy for assessing the results uncertainty and variability. (e.g. Clark et al., )

Second step: Geomorphology

Extract the catchment from DEM by state-of-art  analysis tools (as TauDEM or the Horton Machine Toolbox). Investigate if the surface catchment corresponds to the effective catchment (i.e. if including/excluding karst is an option). Control the surface water network extension (talk at the GSS2021). Analyze the presence and the number of lakes/reservoirs. Pay attention to endorheic catchments. Discuss the catchment connectivity.

Third step: Hydrological Data

Analyze the time series of available data and make a comparison  between rainfall and runoff amounts. Analyze any other time series or map time series, like  map of snow and evapotranspiration (Abera et al., 2017). Define the calibration set and the validation set.

Fourth step: Modelling Setup

Setup the space partitioning in hydrologic response units  (e.g. Dal Molin, 2021). Discuss the data density required (or possible) to give robust results or, viceversa, reduce your objectives to something achievable with the data available.   Choose the model among existing ones for adequacy not for legacy (Addor, 2019).  Choose a model structure as hypothesis zero (Fenicia and Kavetski, 2021, VimeoVideo).*  Setup the modelling solution (MS). Choose the better modelling structure (Clark et al., 2011).  Analyze the MS  parameters and discuss their variability.  Plan the model runs thinking to open science protocols (Hall et al., 2021). 

Fifth step: Modelling Execution

Executing the model, including discharges, snow and ET. Annotate the model performances issues. 

Sixth step: Results Delivery

Show the results appropriately (discharge analysis is not the only one quantity to watch at).  Analyze the performances of indicators. Add comments and discussion. Assess results confidence.

Seventh step: Deployment

Deploy the results for open science and public discussion (e.g. Hall et al., 2021). 

Notes

*With regards to the modelling structure, if you are using ODEs for modelling, consider a standard way to visualize and describe the model structure. As many know, the Extended Petri Net can be a sound way to do it. 

Some Slides and Videos about the above topics:

• Seven Steps in Modelling I-III Overall Analysis,, Geomorphology, The Data (Vimeo2023)
  
• (Vimeo2022)
• 4 - Modelling setup, Calibration/Validation 
• (Vimeo2022)
• 5-6-7 Executing, Delivery of the results , Preparing for Open Science 
• (Vimeo2022)

References

Abera, W., G. Formetta, and L. Brocca. 2017. “Modeling the Water Budget of the Upper Blue Nile Basin Using the JGrass-NewAge Model System and Satellite Data.” Hydrology and Earth System Sciences. http://nora.nerc.ac.uk/id/eprint/517346/.

Addor, Nans, Andrew J. Newman, Naoki Mizukami, and Martyn P. Clark. 2017. “The CAMELS Data Set: Catchment Attributes and Meteorology for Large-Sample Studies.” Hydrology and Earth System Sciences 21 (10): 5293–5313.

Addor, N., and L. A. Melsen. 2019. “Legacy, Rather Than Adequacy, Drives the Selection of Hydrological Models.” Water Resources Research 55 (1): 378–90.

Blöschl, Günter, Marc F. P. Bierkens, Antonio Chambel, Christophe Cudennec, Georgia Destouni, Aldo Fiori, James W. Kirchner, et al. 2019. “Twenty-Three Unsolved Problems in Hydrology (UPH) – a Community Perspective.” Hydrological Sciences Journal 64 (10): 1141–58.

Clark, Martyn P., Andrew G. Slater, David E. Rupp, Ross A. Woods, Jasper A. Vrugt, Hoshin V. Gupta, Thorsten Wagener, and Lauren E. Hay. 2008. “Framework for Understanding Structural Errors (FUSE): A Modular Framework to Diagnose Differences between Hydrological Models.” Water Resources Research, Water Sci. Appl., 44 (12): 2135.

Clark, Martyn P., Dmitri Kavetski, and Fabrizio Fenicia. 2011. “Pursuing the Method of Multiple Working Hypotheses for Hydrological Modeling: HYPOTHESIS TESTING IN HYDROLOGY.” Water Resources Research 47 (9). https://doi.org/10.1029/2010wr009827.

Dal Molin, Marco. 2021. “Improvement and Application of Flexible Frameworks for Modelling Regional Streamflow Variability.” Edited by Marco Schirmer Fabrizio Fenicia. Ph.D., Université de Neuchâtel.

Fenicia, Fabrizio, and Dmitri Kavetski. 2021. “Behind Every Robust Result Is a Robust Method: Perspectives from a Case Study and Publication Process in Hydrological Modelling.” Hydrological Processes 35 (8). https://doi.org/10.1002/hyp.14266.

Hall, Caitlyn A., Sheila M. Saia, Andrea L. Popp, Nilay Dogulu, Stanislaus J. Schymanski, Niels Drost, Tim van Emmerik, and Rolf Hut. 2021. “A Hydrologist’s Guide to Open Science.” Hydrol. Earth Syst. Sci. https://doi.org/10.5194/hess-2021-392.