Regionalization for Ungauged Catchments — Lessons Learned From a Comparative Large‐Sample Study. Issue 10 (28th September 2021)

• Record Type: Journal Article
• Authors: Pool, Sandra; Vis, Marc; Seibert, Jan
• Is Part Of: Water resources research. Volume 57:Issue 10(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-09-28
• Subjects: Ungauged catchments -- regionalization -- parameter estimation -- large‐sample data set; Hydrology -- Periodicals; 333.91
• DOI: 10.1029/2021WR030437
• Languages: English
• ISSNs: 0043-1397

Abstract

Abstract: Model parameter values for ungauged catchments can be regionalized from hydrologically similar gauged catchments. Achieving reliable and robust predictions in ungauged catchments by regionalization, however, is still a major challenge. Here, we conduct a comparative assessment of 19 regionalization approaches based on previously published literature to contribute new insights into their performance in different geographic regions. The approaches use geographical information, physical catchment attributes, hydrological signatures, or a combination thereof to select donor catchments and to subsequently transfer their entire parameter sets to the ungauged receiver catchment. Each regionalization approach was tested in a leave‐one‐out cross‐validation with a bucket‐type catchment model (the HBV model) using 671 gauged catchments in the United States with a diverse hydroclimatology. We then evaluated regionalization performance for several hydrograph aspects, compared it against calibration and regionalization benchmarks, and linked it to catchment descriptors. The results of this large‐sample regionalization study can be summarized in three major lessons: (a) Catchments can benefit from a well‐chosen regionalization approach independent of their geographic region and independent of how well they can be modeled or regionalized at best. (b) Almost perfect donors exist for most catchments and an excellent relative model performance can be reached for most catchments with current regionalization approaches. This implies that there is considerable potential for improvement in the prediction in ungauged catchments. (c) The ranking of regionalization approaches depends on how the predicted hydrographs are evaluated. These findings indicate that a multi‐criteria evaluation is essential for a robust assessment of regionalization performance. Plain Language Summary: Information on streamflow is crucial for good water resources management including the mitigation of water‐related hazards. However, for many catchments there is a lack of streamflow information. In such situations, streamflow is often estimated using hydrological models, whereby model parameterizations are transferred (i.e., regionalized) from hydrologically similar gauged catchments. Reliable estimates in data‐scarce regions are still a major challenge in hydrology despite the large number of regionalization approaches proposed in the past decades. Here, we conduct a systematic and standardized assessment of 19 existing regionalization approaches using 671 catchments in the United States. Our findings suggest that widely used regionalization approaches can result in excellent model performance for most catchments, whereby approaches considering spatial proximity and any kind of volume information are among the most promising ones. While volume information is per definition missing in ungauged catchments, it could possibly be derived from a small number of field measurements or estimated through statistical analysis. However, the most suitable approach can vary considerably among catchments, and an improved understanding of the characteristics and parameter values of great donors and their relationship to an ungauged catchment will be key to advance regionalization further. Key Points: A comparison of 19 regionalization approaches was conducted using 671 U.S. catchments and a homogenized modeling protocol Almost perfect donors exist, and excellent relative performance can be reached for most catchments with current regionalization approaches The ranking of regionalization approaches depends more on how the predicted hydrographs are evaluated than how the donors are calibrated