Unravelling abiotic and biotic controls on the seasonal water balance using data-driven dimensionless diagnostics
Unravelling abiotic and biotic controls on the seasonal water balance using data-driven dimensionless diagnostics
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DOI：
10.5194/hess-21-2817-2017
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发表时间：
2017-06
影响因子：
6.3
通讯作者：
S. P. Seibert;C. Jackisch;U. Ehret;L. Pfister;E. Zehe
中科院分区：
文献类型：
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作者：
S. P. Seibert;C. Jackisch;U. Ehret;L. Pfister;E. Zehe
抽象的。令人困惑的径流产生过程的多样性，以及我们对自然地理特征如何控制水的收集，储存和释放的基本水文功能的粗略理解，继续对流域水文学提出重大的研究挑战。在这里，我们提出了创新的数据驱动的诊断签名，以克服目前的现状，流域间的比较。更具体地说，我们提出了无量纲双质量曲线（dDMC），它允许在季节和年度时间尺度上的径流生成和水平衡的信息的推断。通过将植被和冬季分开，dDMC还提供了关于生物和非生物控制在季节性径流形成中的作用的信息。我们在本文中解决的一个关键方面是推导无量纲表达式的通量，确保在空间和时间的签名的可比性。我们实现这一目标，通过使用水文过程的限制因素作为缩放参考。我们表明，不同的参考导致不同的诊断。因此，我们定义了两种dDMC，使我们能够获得季节性径流系数和表征无量纲径流释放的潜在更新率的函数的土壤储存。我们预计这些签名存储控制的季节性径流形成保持不变，只要释放供应和供应存储容量的比例在不同的集水区发展类似。我们测试所提出的方法，将它们应用到一个业务数据集，包括22个集水区（12-166平方公里）从不同的环境在德国南部和水文气象数据从4个水文年。诊断是用来比较的网站，并揭示径流形成的主导控制。主要研究结果是，dDMC是有意义的签名流域径流形成在季节到年度尺度和缩放的类型强烈影响的dDMC的诊断潜力。增加生长季节和冬季之间的歧视是至关重要的，易于实现的温度指数模型。更具体地说，温度总量解释了70%以上的季节性夏季径流系数的变化。结果还表明，土壤地形指数，即地形坡度和饱和导水率的乘积，与冬季径流系数显著相关，而地形坡度和饱和导水率单独与冬季径流系数不显著相关。我们的结论是，代理梯度和阻力应被解释为一对。最后，dDMC概念揭示了夏季和冬季径流制度之间的记忆效应，这是不相关的春季之间的过渡从冬季到夏季。
Abstract. The baffling diversity of runoff generation processes, alongside our sketchy understanding of how physiographic characteristics control fundamental hydrological functions of water collection, storage, and release, continue to pose major research challenges in catchment hydrology. Here, we propose innovative data-driven diagnostic signatures for overcoming the prevailing status quo in catchment inter-comparison. More specifically, we present dimensionless double mass curves (dDMC) which allow inference of information on runoff generation and the water balance at the seasonal and annual timescales. By separating the vegetation and winter periods, dDMC furthermore provide information on the role of biotic and abiotic controls in seasonal runoff formation. A key aspect we address in this paper is the derivation of dimensionless expressions of fluxes which ensure the comparability of the signatures in space and time. We achieve this by using the limiting factors of a hydrological process as a scaling reference. We show that different references result in different diagnostics. As such we define two kinds of dDMC which allow us to derive seasonal runoff coefficients and to characterize dimensionless streamflow release as a function of the potential renewal rate of the soil storage. We expect these signatures for storage controlled seasonal runoff formation to remain invariant, as long as the ratios of release over supply and supply over storage capacity develop similarly in different catchments. We test the proposed methods by applying them to an operational data set comprising 22 catchments (12–166 km2) from different environments in southern Germany and hydrometeorological data from 4 hydrological years. The diagnostics are used to compare the sites and to reveal the dominant controls on runoff formation. The key findings are that dDMC are meaningful signatures for catchment runoff formation at the seasonal to annual scale and that the type of scaling strongly influences the diagnostic potential of the dDMC. Adding discrimination between growing season and winter period was of fundamental importance and easy to implement by means of a temperature-index model. More specifically, temperature aggregates explain over 70 % of the variability of the seasonal summer runoff coefficients. The results also show that the soil topographic index, i.e. the product of topographic gradient and saturated hydraulic conductivity, is significantly correlated with winter runoff coefficients, whereas the topographic gradient and the hydraulic conductivity alone are not. We conclude that proxies for gradients and resistances should be interpreted as a pair. Lastly, the dDMC concept reveals memory effects between summer and winter runoff regimes that are not relevant in spring between the transition from winter to summer.