Search

Understanding the response of a catchment is a crucial problem in hydrology, with a variety of practical and theoretical implications. Dissecting the role of sub-basins is helpful both for advancing current knowledge of physical processes and for improving the implementation of simulation or forecast models. In this context, recent advancements in sensitivity analysis tools could be worthwhile for bringing out hidden dynamics otherwise not easy to distinguish in complex data driven investigations. In the present work seven feature importance measures are described and tested in a specific and simplified proof of concept case study. In practice, simulated runoff time series are generated for a watershed and its inner 15 sub-basins. A machine learning tool is calibrated using the sub-basins time series for forecasting the watershed runoff. Importance measures are applied on such synthetic hydrological scenario with the aim to investigate the role of each sub-basin in shaping the overall catchment response. This proof of concept offers a simplified representation of the complex dynamics of catchment response. The interesting result is that the discharge at the catchment outlet depends mainly on 3 sub-basins that are consistently identified by alternative sensitivity measures. The proposed approach can be extended to real applications, providing useful insights on the role of each sub-basin also analyzing more complex scenarios. [ABSTRACT FROM AUTHOR]

Soil erosion caused by intense rainfall events is one of the major problems affecting agricultural and forest ecosystems. The Universal Soil Loss Equation (USLE) is probably the most adopted approach for rainfall erosivity estimation, but in order to be properly employed it needs high resolution rainfall data which are often unavailable. In this case, empirical formulas, employing aggregated rainfall data, are commonly used. In this work, we select 12 empirical formulas for the estimation of the USLE rainfall erosivity in order to assess their reliability. Moreover, we used a Stochastic Rainfall Generator (SRG) to simulate a long and high-resolution rainfall time series with the aim of assessing its application to rainfall erosivity estimations. From the analysis, performed in the Rieti province of Central Italy, we identified three equations which seem to provide better results. Moreover, the use of the selected SRG seems promising and it could help in solving the problem of hydrological data scarcity and consequently guarantee major accuracy in soil erosion estimation. [ABSTRACT FROM AUTHOR]

One of the main signatures of short duration storms is given by Depth–Duration–Frequency (DDF) curves. In order to provide reliable estimates for small river basins or urban catchments, generally characterized by short concentration times, in this study the performances of different DDF curves proposed in literature are described and compared, in order to provide insights on the selection of the best approach in design practice, with particular reference to short durations. With this aim, 28 monitoring stations with time series of annual maximum rainfall depth characterized by sample size greater than 20 were selected in the Northern part of the Puglia region (South-Eastern Italy). In order to test the effect of the investigated DDF curves in reproducing the design peak discharge corresponding to an observed expected rainfall event, the Soil Conservation (SCS) curve number (CN) approach is exploited, generating peak discharges according to different selected combinations of the main parameters that control the critical rainfall duration. Results confirm the good reliability of the DDF curves with three parameters to adapt on short events both in terms of rainfall depth and in terms of peak discharge and, in particular, for durations up to 30 min, the three-parameter DDF curves always perform better than the two-parameter DDF. [ABSTRACT FROM AUTHOR]

• A continuous hydrologic model is tested using as input a long observed rainfall time series at 10-min resolution. • The proposed continuous model is tailored for small and ungauged basin applications. • The test results confirm that continuous models can be an appealing alternative to the event-based approach. The design hydrograph estimation in small and ungauged basins represents one of the most common practices and, yet, a challenging open research topic for hydrologists. When discharge observations are not available, the practitioner is compelled to apply empirical approaches. The rational formula is slowly disappearing, while event-based approaches are more and more widespread. A step forward is represented by continuous models that have the potential to address the major drawbacks of event-based approaches. In this work we applied a continuous model specifically designed for ungauged basins (COSMO4SUB) and tested its use in conditions where typically the rational formula and the event-based approaches are applied. Results confirm that the continuous modelling is suitable for rapid and effective design simulations supporting flood hazard modelling and mapping studies. [ABSTRACT FROM AUTHOR]