模拟预测气候变化对切萨皮克湾流域水流水文的影响

T. Hawkins
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引用次数: 10

摘要

一个网格模型被开发用来模拟切萨皮克湾流域的水文,切萨皮克湾是美国最大的河口。利用CMIP3和CMIP5气候预估驱动该模式评估河流流量和流域水文的变化。协议值指数表明模型性能良好。预计到2080年至2099年,年平均气温将上升1.9°C至5.4°C,流域北部夏季和秋季的升温幅度最大。预计到2080年至2099年,年总降水量将增加5.2%至15.2%,最大的增加通常发生在冬季。预计平均蒸散量和降雨量将增加,而降雪量、雪水储存量和融雪量将减少。预计在较暖的月份,地下水分会减少,补给时间会增加,在某些情况下,补给时间从未真正发生。所有346个气候预测的年径流量变化平均为0%(2020-2039)、- 1.5%(2050-2069)和- 5.1%(2080-2099)。在未来的时间段内,年径流量分别有48%、52%和60%的可能性低于基线值(1950-1999年)。极端径流预测绝大多数与分布的负端相关。径流的增加仅限于1月到3月,而且海拔较高。这项研究的新颖之处在于它使用了大量的气候模式,水文模式的网格化性质,以及对几个水文变量的模拟,所有这些都允许评估预估的不确定性和跨多个时空尺度的变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Simulating the Impacts of Projected Climate Change on Streamflow Hydrology for the Chesapeake Bay Watershed
A gridded model was developed to simulate the hydrology of the Chesapeake Bay Watershed, the largest estuary in the United States. CMIP3 and CMIP5 climate projections were used to drive the model to assess changes in streamflow and watershed-wide hydrology. Index of agreement values indicated good model performance. Annual average temperature is projected to increase 1.9°C to 5.4°C by 2080 to 2099, with the greatest warming occurring in summer and fall in the northern part of the watershed. Annual total precipitation is projected to increase between 5.2 percent and 15.2 percent by 2080 to 2099, with the largest increases generally occurring in winter. Average evapotranspiration and rainfall are projected to increase while snowfall, snow water storage, and snowmelt decrease. Subsurface moisture is projected to decrease during the warmer months and the time to recharge increases and, in some cases, never actually occurs. Changes in annual runoff for all 346 climate projections averaged 0 percent (2020–2039), –1.5 percent (2050–2069), and –5.1 percent (2080–2099). There is a 48 percent, 52 percent, and 60 percent chance, respectively, for the future time periods that annual runoff will be less than baseline values (1950–1999). Extreme runoff projections are overwhelmingly associated with the negative end of the distribution. Runoff increases are confined to January through March and to higher elevations. This study is novel in its use of a large number of climate models, the gridded nature of the hydrologic model, and the simulation of several hydrologic variables, all of which allowed for the assessment of both uncertainty in the projections and variation across multiple spatial and temporal scales.
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