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首页> 外文期刊>Hydrology and Earth System Sciences >Climate-vegetation-soil interactions and long-term hydrologic partitioning: signatures of catchment co-evolution
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Climate-vegetation-soil interactions and long-term hydrologic partitioning: signatures of catchment co-evolution

机译:气候-土壤-土壤相互作用和长期水文分区:集水区共同演化的标志

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Budyko (1974) postulated that long-term catchment waterbalance is controlled to first order by the available water and energy. Thisleads to the interesting question of how do landscape characteristics(soils, geology, vegetation) and climate properties (precipitation,potential evaporation, number of wet and dry days) interact at the catchmentscale to produce such a simple and predictable outcome of hydrologicalpartitioning? Here we use a physically-based hydrologic model separatelyparameterized in 12 US catchments across a climate gradient to decouple theimpact of climate and landscape properties to gain insight into the role ofclimate-vegetation-soil interactions in long-term hydrologic partitioning.The 12 catchment models (with different paramterizations) are subjected tothe 12 different climate forcings, resulting in 144 10 yr modelsimulations. The results are analyzed per catchment (one catchment modelsubjected to 12 climates) and per climate (one climate filtered by 12different model parameterization), and compared to water balance predictionsbased on Budyko's hypothesis (E/P = ϕ (Ep/P); E: evaporation,P: precipitation, Ep: potential evaporation). We find significantanti-correlation between average deviations of the evaporation index (E/P)computed per catchment vs. per climate, compared to that predicted byBudyko. Catchments that on average produce more E/P have developed inclimates that on average produce less E/P, when compared to Budyko'sprediction. Water and energy seasonality could not explain theseobservations, confirming previous results reported by Potter et al. (2005).Next, we analyze which model (i.e., landscape filter) characteristicsexplain the catchment's tendency to produce more or less E/P. We find thatthe time scale that controls subsurface storage release explains theobserved trend. This time scale combines several geomorphologic andhydraulic soil properties. Catchments with relatively longer subsurfacestorage release time scales produce significantly more E/P. Vegetation inthese catchments have longer access to this additional groundwater sourceand thus are less prone to water stress. Further analysis reveals thatclimates that give rise to more (less) E/P are associated with catchmentsthat have vegetation with less (more) efficient water use parameters. Inparticular, the climates with tendency to produce more E/P have catchmentsthat have lower % root fraction and less light use efficiency. Ourresults suggest that their exists strong interactions between climate,vegetation and soil properties that lead to specific hydrologic partitioningat the catchment scale. This co-evolution of catchment vegetation and soilswith climate needs to be further explored to improve our capabilities topredict hydrologic partitioning in ungauged basins.
机译:Budyko(1974)推测,长期流域的水平衡受可用水和能源控制在第一位。这引出了一个有趣的问题,即景观特征(土壤,地质,植被)和气候特性(降水,潜在蒸发,干湿天数)如何在流域尺度上相互作用以产生如此简单且可预测的水文分区结果?在这里,我们使用一个基于物理的水文模型,该模型在12个美国流域的整个气候梯度中分别进行了参数化,以消除气候和景观属性的影响,从而深入了解气候-植被-土壤相互作用在长期水文分区中的作用.12个流域模型(具有不同的参数设置)经受12种不同的气候强迫,导致144个10年模型模拟。分析每个集水区(一个集水区模型受12个气候影响)和每个气候集(一个气候,通过12个不同模型参数化过滤的结果)的结果,并与基于Budyko假设( E / P =ϕ ( E p / P ); E :蒸发, P :沉淀, E p :潜在蒸发)。与Budyko预测的结果相比,我们发现每个流域与每个气候计算的蒸发指数( E / P )的平均偏差之间存在显着的反相关性。平均而言,集水区平均产生更多的 E / P 的情况表明,当集水区平均产生较少的 E / P 时,与Budyko的预测相比。水和能源的季节性不能解释这些观测结果,从而证实了Potter等人先前报道的结果。 (2005)。接下来,我们分析哪种模型(即景观过滤器)特征解释了流域产生或多或少的 E / P 的趋势。我们发现控制地下存储释放的时间尺度解释了观察到的趋势。该时间尺度结合了几种地貌和液压土壤特性。地下存储释放时间尺度相对较长的集水区产生更多的 E / P 。这些集水区的植被可以更长时间地使用这种额外的地下水源,因此不易受到水分胁迫。进一步的分析表明,产生更多(更少) E / P 的气候与具有较少(更多)有效用水参数的植被集水区有关。特别是倾向于产生更多 E / P 的气候集水区的根部百分含量较低,光利用效率较低。我们的结果表明,它们在气候,植被与土壤特性之间存在着强大的相互作用,从而导致在流域尺度上进行特定的水文分配。流域植被和土壤与气候的这种共同演化需要进一步探索,以提高我们预测未开垦盆地水文分区的能力。

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