Summary
This paper investigates how the temporal granularity of input data influences the fidelity of process-based hydrological models when simulating extreme water flux events in grassland systems. Using field-scale observations, the authors examine whether coarser temporal resolution (e.g. daily versus sub-hourly) systematically biases predictions of peak flows or drought conditions. The findings suggest implications for model validation and the design of field monitoring networks in agricultural water management.
UK applicability
The study's focus on grassland hydrology is directly applicable to UK lowland pasture systems, where temporal data resolution remains a practical constraint in field-scale monitoring. Results may inform the design of hydrological monitoring networks and model-based water management strategies across UK agricultural catchments.
Key measures
Water flux extremes; temporal resolution of hydrological forcing data; model simulation accuracy; field-scale grassland hydrology
Outcomes reported
The study examined how different temporal resolutions of input data affect the accuracy of process-based hydrological model simulations, specifically for water flux extremes at a grassland field site. The research measured model sensitivity to data aggregation and its implications for predicting water flow dynamics.
Topic tags
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