Physically based modeling in catchment hydrology at 50: Survey and outlook
By Claudio Paniconi, Mario Putti. 2015
301 citations recorded by the source corpus.
Integrated, process‐based numerical models in hydrology are rapidly evolving, spurred by novel theories in mathematical physics, advances in computational methods, insights from laboratory and field experiments, and the need to better understand and predict the potential impacts of population, land use, and climate change on our water resources. At the catchment scale, these simulation models are commonly based on conservation principles for surface and subsurface water flow and solute transport (e.g., the Richards, shallow water, and advection‐dispersion equations), and they require robust numerical techniques for their resolution. Traditional (and still open) challenges in developing reliable and efficient models are associated with heterogeneity and variability in parameters and state variables; nonlinearities and scale effects in process dynamics; and complex or poorly known boundary conditions and initial system states. As catchment modeling enters a highly interdisciplinary era, new challenges arise from the need to maintain physical and numerical consistency in the description of multiple processes that interact over a range of scales and across different compartments of an overall system. This paper first gives an historical overview (past 50 years) of some of the key developments in physically based hydrological modeling, emphasizing how the interplay between theory, experiments, and modeling has contributed to advancing the state of the art. The second part of the paper examines some outstanding problems in integrated catchment modeling from the perspective of recent developments in mathematical and computational science.
Subfields: Civil and Structural Engineering, Environmental Engineering, Water Science and Technology
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Citations in the corpus
- Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data (2016, background): “In addition, subsurface flow involves a number of complex sub-processes that interact in non-linear ways, which are difficult to encapsulate in current theory-based models [37].”
- HESS Opinions : The complementary merits of competing modelling philosophies in hydrology (2017, background): “…continuum are criticized for lacking a robust physical or theoretical basis and for their inability to meaningfully represent spatial patterns (e.g. Paniconi and Putti, 2015; Fatichi et al., 2016), whereas models at the high-resolution and high-complexity end are often viewed as having inferior…”
- The evolution of process-based hydrologic models: Historical challenges and the collective quest for physical realism. (2017, unknown): “The first solution, and the most obvious, is to exploit advances in massively parallel (e.g., exa-scale) computation [Kollet et al. 2010; Wood et al. 2011; Paniconi and Putti 2015; Fatichi et al. 2016].”