Department of Physics, Wright State University, 3640 Colonel Glenn Highway, Dayton, OH 45435, USA.
Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089, USA.
Sci Total Environ. 2023 Jun 15;877:162905. doi: 10.1016/j.scitotenv.2023.162905. Epub 2023 Mar 16.
The relationship between carbon cycle and water demand is key to understanding global climate change, vegetation productivity, and predicting the future of water resources. The water balance, which enumerates the relative fractions of precipitation P that run off, Q, or are returned to the atmosphere through evapotranspiration, ET, links drawdown of atmospheric carbon with the water cycle through plant transpiration. Our theoretical description based on percolation theory proposes that dominant ecosystems tend to maximize drawdown of atmospheric carbon in the process of growth and reproduction, thus providing a link between carbon and water cycles. In this framework, the only parameter is the fractal dimensionality d of the root system. Values of d appear to relate to the relative roles of nutrient and water accessibility. Larger values of d lead to higher ET values. Known ranges of grassland root fractal dimensions predict reasonably the range of ET(P) in such ecosystems as a function of aridity index. Forests with shallower root systems, should be characterized by a smaller d and, therefore, ET that is a smaller fraction of P. The prediction of ET/P using the 3D percolation value of d matches rather closely results deemed typical for forests based on a phenomenology already in common use. We test predictions of Q with P against data and data summaries for sclerophyll forests in southeastern Australia and the southeastern USA. Applying PET data from a nearby site constrains the data from the USA to lie between our ET predictions for 2D and 3D root systems. For the Australian site, equating cited "losses" with PET underpredicts ET. This discrepancy is mostly removed by referring to mapped values of PET in that region. Missing in both cases is local PET variability, more important for reducing data scatter in southeastern Australia, due to the greater relief.
碳循环与水需求之间的关系是理解全球气候变化、植被生产力以及预测未来水资源的关键。水量平衡将降水 P 的相对部分进行分类,其中 Q 部分为径流量,ET 部分通过蒸散作用返回大气。水量平衡通过植物蒸腾作用将大气碳的消耗与水循环联系起来。我们基于渗流理论的理论描述表明,主要生态系统倾向于在生长和繁殖过程中最大限度地消耗大气碳,从而为碳和水循环提供了联系。在这个框架中,唯一的参数是根系的分形维数 d。d 的值似乎与养分和水分可及性的相对作用有关。较大的 d 值会导致较高的 ET 值。已知草地根系分形维数的范围可以合理地预测这些生态系统中 ET(P)的范围,其函数是干旱指数。根系较浅的森林,其 d 值应该较小,因此 ET 占 P 的比例也较小。使用 3D 渗流 d 值预测 ET/P 与已广泛使用的基于现象学的典型森林结果相当吻合。我们根据澳大利亚东南部和美国东南部的硬叶林数据和数据摘要来检验 Q 与 P 的预测值。应用附近地点的 PET 数据可以将美国的数据限制在我们为 2D 和 3D 根系系统预测的 ET 之间。对于澳大利亚的地点,将引用的“损失”与 PET 等同起来会低估 ET。通过引用该地区绘制的 PET 值,可以消除这种差异。在这两种情况下,都缺少当地的 PET 可变性,这对于减少澳大利亚东南部的数据分散更为重要,因为那里的地形起伏更大。