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a b s t r a c tEvapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03′N, 12°40′E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

Lamačová A., Hruška J., Krám P., Stuchlík E., Farda A., Chuman T., Fottová D. (2014): Runoff trends analysis and future projections of hydrological patterns in small forested catchments. Soil & Water Res., 9: 169-181.The aims of the present study were (i) to evaluate trends in runoff from small forested catchments of the GEOMON (GEOchemical MONitoring) network during the period 1994-2011, and (ii) to estimate the impact of anticipated climate change projected by ALADIN-Climate/CZ regional climate model coupled to ARPEGE-Climate global circulation model and forced with IPCC SRES A1B emission scenario on flow patterns in the periods 2021-2050 and 2071-2100. There were no general patterns found indicating either significant increases or decreases in runoff on either seasonal or annual levels across the investigated catchments within 1994-2011. Annual runoff is projected to decrease by 15% (2021-2050) and 35% (2071-2100) with a significant decrease in summer months and a slight increase in winter months as a result of expected climate change as simulated by the selected climate model.