The study of the multiannual thermal dynamics of Lake Iseo, a deep lake in the Italian pre-alpine area, is presented. Inter flow was found to be the dominant river entrance mode, suggesting future susceptibility of the lake thermal structure to the overall effects of climate change expected in the upstream alpine watershed. A lake model employed the results of a long-term hydrologic model to simulate the effects of a climate change scenario on the lake ’ s thermal evolution for the period 2012 – 2050. The model predicts an overall average increase in the lake water temperature of 0.012 °C/year and a reinforced Schmidt thermal stability of the water column in the winter up to 800 J/m 2. Both these effects may further hinder the deep circulation process, which is vital for the oxygenation of deep water
Abstract. The potential impact of climate change scenarios on the runoff regime in the Italian Alpine area was investigated. A preliminary analysis of the output of three Global Circulation Models (PCM, HADCM, ECHAM) was needed to select IPCC-based scenarios for the 2000–2099 period. Two basins, 1840 and 236 km2 in size, respectively, and with different glaciated areas and storage capacity of reservoirs were selected as case studies. The PCM model, the one capable to better reproduce the observed rainfall regime in the investigated area, with the IPCC SRES A2 scenario was adopted for the meteorological forcing. On average for the two basins, an increase of annual precipitation of about 3% is expected for the 2050 scenario and should not significantly vary at the end of this century compared to present conditions. At the same time temperature should increase of 1.1°C in 2050 and 2.4°C for 2090. Because of the coarse resolution of the climate models' output, the statistics of the simulated rainy days and daily precipitation were adapted to the scale of the two selected basins using a modified version of the multiplicative cascade β-model, proposed in the literature to explain the statistics of intermittent fully developed turbulence. As regards to land cover, glaciated areas are decreased, in the future scenarios, according to the Kuhn's concept of equilibrium line adaptation to climate fluctuations. The tree-line altitude is increased, according to the observed trend since the end of the Little Ice Age: thus boundary conditions for evapotranspiration changed. The resulting meteorological variables and hydrological parameters were used to run the WATFLOOD hydrological model in order to assess the changes of runoff regimes in the two watersheds. A decrease of about 7% of annual runoff volume for the 2050 scenario and of 13% for the 2090 scenario was estimated, on average, at the outlet of the Oglio river basin, the largest one. In the smaller Lys basin, where the glaciated area is 8% of the total area, the annual runoff is foreseen to decrease by about 3% (for the 2050 scenario) and 14% at the end of this century. Also the runoff regime changes are significant, with an increase of spring melt and a decrease of summer and autumn runoff. No clear evidence is found for changes in the precipitation extremes and in the fraction of rainy days.
Soil water retention curves are a key constitutive law used to describe the physical behavior of an unsaturated soil. Various computational modeling techniques, that formulate retention curve models, are mostly based on existing soil databases, which rarely consider any effect of stress on the soil water retention. Such effects are crucial in the case of swelling soils. This study illustrates and explores the ability of computational intelligence-based genetic programming to formulate the mathematical relationship between the water content, in terms of degree of saturation, and two input variables, i.e., net stress and suction for three different soils (sand-kaolin mixture, Gaduk Silt and Firouzkouh clay). The predictions obtained from the proposed models are in good agreement with the experimental data. The parametric and sensitivity analysis conducted validates the robustness of our proposed model by unveiling important parameters and hidden non-linear relationships
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