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Evaluation of future hydrological cycle under climate change scenarios in a mesoscale Alpine watershed of Italy

机译：在意大利中型高山流域气候变化情景下对未来水文循环的评估

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We investigate future (2045-2054) hydrological cycle of the snow fed Oglio (‰1800 km2) Alpine watershed in Northern Italy. A Stochastic Space Random Cascade (SSRC) approach is used to downscale future precipitation from three general circulation models, GCMs (PCM, CCSM3, and HadCM3) available within the IPCC's data base and chosen for this purpose based upon previous studies. We then downscale temperature output from the GCMs to obtain temperature fields for the area. We also consider a projected scenario based upon trends locally observed in former studies, LOC scenario. Then, we feed the downscaled fields to a minimal hydrological model to build future hydrological scenarios. We provide projected flow duration curves and selected flow descriptors, giving indication of expected modified (against control run for 1990-1999) regime of low flows and droughts and flood hazard, and thus evaluate modified peak floods regime through indexed flood. We then assess the degree of uncertainty, or spread, of the projected water resources scenarios by feeding the hydrological model with ensembles projections consistent with our deterministic (GCMs + LOC) scenarios, and we evaluate the significance of the projected flow variables against those observed in the control run. The climate scenarios from the adopted GCMs differ greatly from one another with respect to projected precipitation amount and temperature regimes, and so do the projected hydrological scenarios. A relatively good agreement is found upon prospective shrinkage and shorter duration of the seasonal snow cover due to increased temperature patterns, and upon prospective increase of hydrological losses, i.e. evapotranspiration, for the same reason. However, precipitation patterns are less consistent, because HadCM3 and PCM models project noticeably increased precipitation for 2045-2054, whereas CCSM3 provides decreased precipitation patterns therein. The LOC scenario instead displays unchanged precipitation. The ensemble simulations indicate that several projected flow variables under the considered scenarios are significantly different from their control run counterparts, and also that snow cover seems to significantly decrease in duration and depth. The proposed hydrological scenarios eventually provide a what-if analysis, giving a broad view of the possible expected impacts of climate change within the Italian Alps, necessary to trigger the discussion about future adaptation strategies.
机译：我们调查了意大利北部以积雪为食的奥格里奥（‰1800 km2）高山流域的未来（2045-2054）水文循环。随机空间随机串级（SSRC）方法用于降低IPCC数据库中可用的三个通用环流模型GCM（PCM，CCSM3和HadCM3）的未来降水量，并根据先前的研究为此目的进行了选择。然后，我们缩小GCM的温度输出，以获取该区域的温度场。我们还根据以前研究中本地观察到的趋势（LOC情景）考虑了一个预测的情景。然后，我们将缩小的字段馈入最小水文模型，以建立未来的水文情景。我们提供了预计的流量持续时间曲线和选定的流量描述符，给出了预期的低流量，干旱和洪水灾害改良（相对于1990-1999年控制运行）方案的指示，从而通过索引洪水评估了改良峰值洪涝方案。然后，我们通过向水文模型提供符合我们确定性（GCMs + LOC）情景的集合预测，来评估预计水资源情景的不确定性或扩散程度，并评估预测流量变量相对于观测到的变量的重要性。控制运行。在预测的降水量和温度状况方面，采用的GCM产生的气候情景彼此之间有很大的不同，预计的水文情景也是如此。由于相同的原因，在预期的收缩和由于温度升高引起的季节性积雪持续时间较短，以及预期的水文损失（即蒸散）增加方面，发现了相对较好的协议。但是，降水模式的一致性较差，因为HadCM3和PCM模型预测2045-2054年降水会显着增加，而CCSM3的降水模式将减少。相反，LOC场景显示不变的降水量。整体模拟表明，在所考虑的情景下，几个预计的流量变量与控制运行的变量明显不同，而且积雪的持续时间和深度似乎明显减少。拟议的水文情景最终提供了假设分析，从而广泛地揭示了意大利阿尔卑斯山内气候变化可能产生的预期影响，这是引发有关未来适应战略讨论的必要条件。

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