The lack of understanding on the soil moisture–precipitation feedback mechanisms remains a large source of uncertainty for land–atmosphere coupled models. Previous observation-based studies on the soil moisture–precipitation feedback in Illinois have shown contradictory results. This paper extends earlier research by providing a more holistic analysis considering different scales based on an 11-yr (2003–13) hourly soil moisture dataset, which makes it possible to revisit the disputed hypothesis on the correlation between warm-season soil moisture and subsequent precipitation. This study finds a strong positive correlation between late spring/early summer state-average soil moisture at the root-zone depths and subsequent state-average summer precipitation. On the daily to weekly time scale, however, no relation is found. Moreover, regional analysis suggests that precipitation variability over central Illinois can be best explained by the soil moisture variability in northwest Illinois. Using a back-trajectory method [Water Accounting Model-2 layers (WAM-2layers)] from May to July, the evaporative sources of precipitation in Illinois are identified. The pattern of the source regions shows little interannual variability, while the strength of the sources changes significantly and the Gulf of Mexico contributes more during wet years. However, strong influences (teleconnections) of sea surface temperatures on the subsequent precipitation variability in Illinois are not found on a seasonal scale. The long time scale of the soil moisture–precipitation correlation and the weak influences of SSTs and climate indices may suggest that precipitation variability in spring/summer in Illinois is mostly related to continental-scale soil moisture–precipitation feedback.@en

The paper describes the process of induction of equations for the description of vegetation-induced roughness from several angles. Firstly, it describes two approaches for obtaining theoretically well-founded analytical expressions for vegetation resistance. The first of the two is based on simplified assumptions for the vertical flow profile through and over vegetation, whereas the second is based on an analytical solution to the momentum balance for flow through and over vegetation. In addition to analytical expressions the paper also outlines a numerical 1-DV k-¿ turbulence model which includes several important features related to influence plants exhibit on the flow. Last but not least, the paper presents a novel way of applying genetic programming to the results of the 1-DV model, in order to obtain an expression for roughness based on synthetic data. The resulting expressions are evaluated and compared with an independent data set of flume experiments.@en

GECCO-2005 A joint meeting of the fourteenth international conference on genetic algorithms ICGA-2005) and the tenth annual genetic programming conference (GP-2005). ACM Order Number 910052 7. CONCLUSIONS Four formulations for waterdepth-related resistance induced by vegetation are studied and compared. Two have been explicitly derived by a scientist building upon the extensive literature on this subject. One expression was derived by dimensionally aware genetic programming, and finally one expression was created by manually analysing and improving the genetic programming equation. It was found that the genetic programming equations were superior to the manually derived equations, both on their performance on synthetic training and laboratory testing data, and in the economy of detail that needs to be modelled. The manually found expression was found to be in good agreement with previous expressions found in the literature, and performed competitive with the detailed model that was used to generate the training data.@en