**8. Conclusion**

The implementation of the AnnAGNPS in two small agricultural watersheds (Cannata, southern Italy, and Ganspoel, central Belgium) provided interesting indications about mod‐ el's prediction capability of surface runoff, peak flow and sediment yield and thus about its applicability in the experimental conditions.

The study case of the Cannata watershed has highlighted a good prediction capability of run‐ off and erosive events, particularly for the events of highest relative magnitude (higher than 15 mm and 100 kg ha-1 respectively); a good accuracy has been achieved also for monthly runoff volumes simulation. The over-estimation of runoff volumes at yearly scale has been limited by setting up the initial CNs in the calibration phase, with mean differences between observed and simulated yearly values lower than 20%. Peak flow predictions have been satisfactory on‐ ly for the less intense events (lower than 0.3 m3 /s); the utilisation of the different synthetic hye‐ tographs available for the hydrologic sub-model has not hallowed to eliminate the high overestimation of the most intense peak flows. On the whole, the results provided by the analysis of this study case encourage further efforts in order to verify the model transferability to the cli‐ matic conditions typical of the semi-arid Mediterranean environment.

The evaluation of AnnAGNPS in the Ganspoel watershed has highlighted a good prediction capability only for the most intense runoff events (higher than 1 mm) in absence of calibra‐ tion. The prediction capability of peak flows and sediment yields have resulted instead un‐ satisfactory (as also highlighted by the low coefficients of efficiency): the poor model's sediment yield predictions reflect the unreliability of simulated values of peak flows, re‐ quired as input by the erosive sub-model.

The influence of the limited availability of geomorphologic parameters (balanced by the esti‐ mation, even reasonable, of some input parameters) as well as of hydrological observations (which even has advised against realistic calibration processes) on the model performance can not be excluded.

However, the availability of proper climatic (allowing set-up of input meteorological data) and GIS sub-routines (helping to process available DEM and themes) together with the userfriendly graphical interfaces in the model software made easy in AnnAGNPS the input data processing. In spite of the large number of input parameters required (more than 100), as for the majority of continuous, physically-based and distributed models, we have remarked a basical easiness of model implementation at the Cannata watershed, thanks to the good availability of geomorphologic and hydrologic information within the experimental data‐ base as well as the easiness of finding/measuring the majority of input parameters (e.g. me‐ teorological data, soil physical properties). Nevertheless, in some cases processing of simulated hydrologic variables resulted in a time consuming task, especially for surface run‐ off analysis at event scale.

The model performance could be further improved by optimising algorithms for water bal‐ ance of soil (in order to improve the simulation of more realistic moisture conditions) or by utilising as input the observed rainfall patterns (at hourly or sub-hourly scales) instead of the synthetic hyetographs utilised at present by AnnAGNPS. Sensitivity analyses, which would allow a more precise estimation of the input parameters to which model response is more sensitive, would be advisable for a better model implementation.

Such improvements, together further research activities aiming at model verification in dif‐ ferent environmental conditions, could enhance the model consolidation and stimulate its wider diffusion in professional activities for controlling surface runoff and soil erosion as well as planning mitigation countermeasures.
