article published yes Björn Guse author Simone Fatichi author cf8e546b-a9b0-11f0-a43b-aa89ed1b56d6 Shervan Gharari author Lieke A. Melsen author Model fidelity and accuracy in process representations have been the crux of scientific hydrological modeling, creating a pressing need for a better linkage between the development of hydrological models and the growing number of data sources and measurement techniques. Improved representation of process dynamics in hydrological models can provide new insights into complex hydrological systems and point out less understood natural phenomena that need further investigation. This special issue includes contributions that offer potential solutions and strategies to improve and test the representation of hydrological processes. We have organized the special issue contributions into four topical categories: (a) Beyond streamflow, which looks into the power of complementary data sources in addition to traditionally used streamflow for process inference. (b) Challenge of subsurface hydrology, that reflects on lesser understood processes under the surface and their impact on the model structure. (c) Evaporation in hydrological modeling, linking ecological aspects to the hydrological functioning of the natural system. Finally, (d) top down vs. bottom up modeling approaches, relied upon for process representation analysis. The special issue and our reflection on the contributions present a snapshot of ongoing efforts for integrating new concepts, knowledge, and data in process representation in hydrological models. American Geophysical Union2021 eng 0043-1397 1944-797310.1029/2021wr030661 5711 yes Guse, Björn, et al. “Advancing Process Representation in Hydrological Models: Integrating New Concepts, Knowledge, and Data.” <i>Water Resources Research</i>, vol. 57, no. 11, e2021WR030661, American Geophysical Union, 2021, doi:<a href="https://doi.org/10.1029/2021wr030661">10.1029/2021wr030661</a>. Guse, B., Fatichi, S., Gharari, S., &#38; Melsen, L. A. (2021). Advancing process representation in hydrological models: Integrating new concepts, knowledge, and data. <i>Water Resources Research</i>. American Geophysical Union. <a href="https://doi.org/10.1029/2021wr030661">https://doi.org/10.1029/2021wr030661</a> B. Guse, S. Fatichi, S. Gharari, and L. A. Melsen, “Advancing process representation in hydrological models: Integrating new concepts, knowledge, and data,” <i>Water Resources Research</i>, vol. 57, no. 11. American Geophysical Union, 2021. Guse B, Fatichi S, Gharari S, Melsen LA. Advancing process representation in hydrological models: Integrating new concepts, knowledge, and data. <i>Water Resources Research</i>. 2021;57(11). doi:<a href="https://doi.org/10.1029/2021wr030661">10.1029/2021wr030661</a> Guse, Björn, Simone Fatichi, Shervan Gharari, and Lieke A. Melsen. “Advancing Process Representation in Hydrological Models: Integrating New Concepts, Knowledge, and Data.” <i>Water Resources Research</i>. American Geophysical Union, 2021. <a href="https://doi.org/10.1029/2021wr030661">https://doi.org/10.1029/2021wr030661</a>. B. Guse, S. Fatichi, S. Gharari, L.A. Melsen, Water Resources Research 57 (2021). Guse B, Fatichi S, Gharari S, Melsen LA. 2021. Advancing process representation in hydrological models: Integrating new concepts, knowledge, and data. Water Resources Research. 57(11), e2021WR030661. 224522026-07-27T12:30:23Z2026-07-30T09:15:11Z