Climate change over the high-mountain versus plain areas: Effects on the land surface hydrologic budget in the Alpine area and northern Italy

Abstract

Abstract. Climate change may intensify during the second half of the current century. Changes in temperature and precipitation can exert a significant impact on the regional hydrologic cycle. Because the land surface serves as the hub of interactions among the variables constituting the energy and water cycles, evaluating the land surface processes is essential to detail the future climate. In this study, we employ a trusted soil–vegetation–atmosphere transfer scheme, called the University of Torino model of land Processes Interaction with Atmosphere (UTOPIA), in offline simulations to quantify the changes in hydrologic components in the Alpine area and northern Italy, between the period of 1961–1990 and 2071–2100. The regional climate projections are obtained by the Regional Climate Model version 3 (RegCM3) via two emission scenarios – A2 and B2 from the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios. The hydroclimate projections, especially from A2, indicate that evapotranspiration generally increases, especially over the plain areas, and consequently the surface soil moisture decreases during summer, falling below the wilting point threshold for an extra month. In the high-mountain areas, due to the earlier snowmelt, the land surface becomes snowless for an additional month. The annual mean number of dry (wet) days increases remarkably (slightly), thus increasing the risk of severe droughts, and slightly increasing the risk of floods coincidently. Our results have serious implications for human life, including agricultural production, water sustainability, and general infrastructures, over the Alpine and adjacent plain areas and can be used to plan the managements of water resources, floods, irrigation, forestry, hydropower, and many other relevant activities.

Projected Changes in Soil Temperature and Surface Energy Budget Components over the Alps and Northern Italy

“…In more detail, UTOPIA was driven over each grid point using the following RegCM3 outputs: Longwave and shortwave radiation, precipitation, and the surface-level (2 m) temperature, humidity, pressure, and wind. To ensure the numerical stability of UTOPIA, all 3-hourly RegCM3 non-intermittent outputs were interpolated every hour using a cubic spline, whereas the intermittent variable, e.g., precipitation, was simply redistributed assuming a constant rate (see more details in [4]).…”

“…More specifically, we set the bottom-level depth, from layer 1 (top) to layer 10 (bottom), to 0.05, 0. 15 [4]. Despite UTOPIA possessing an internal algorithm for dealing with a non-null heat flux from the bottom, there is no similar algorithm for dealing with eventual (non-null) moisture fluxes.…”

“…We obtained the soil characteristics data from ECOCLIMAP soil texture [73,74], and used the same data for all soil profiles due to the absence of other sources of data regarding deep soil composition. In terms of vegetation, we assumed that short grasses cover the whole domain, in accordance with [4], though the tree line elevation in the Swiss Alps can reach up to 2450 m [75,76] with various types of vegetation. This assumption, i.e., having short grasses over all the domain grid points, is based on the following considerations, mainly associated with the large uncertainty in projection of future vegetation aspects: (i) RegCM3 had no dynamic vegetation parametrization and employed fixed vegetation and land use data; (ii) the grid resolution of RegCM3 was not sufficient to represent the detailed orographic features, and hence, the changes in natural vegetation and land use exerted by potential climatic variability; (iii) most hilly and plain areas are extensively used for agriculture and are subject to irrigation and thus, it is hard to predict the vegetation aspects by models based on the natural vegetation change; and (iv) vegetation dynamics are conditioned by not only climatic factors but also by artificial factors (e.g., adaptive ecosystem management [77]).…”

“…FC A2 and FC B2 were projected through the A2 and B2 emission scenarios, respectively, from the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) [78]. The analyses of the hydrologic budget components (including soil moisture, dry and wet soil indices, and snow) over the same domain and periods of our study are conducted in reference [4]. Although climate change due to anthropogenic or climate-induced sources, e.g., land-use/land-cover change, biofuel expansion and vegetation migration, have been addressed recently (e.g., references [79][80][81]), we focused on the climate projections based on the SRES A2 and B2 scenarios only.…”

“…Being proportional to ET, LHF is a key variable that links energy and hydrologic exchanges. For this reason, assessment of the soil hydrologic budget is crucial to allow correct evaluation of the energy budget components [4].…”