Modelling water and chemical transport in large undisturbed soil cores using HYDRUS-2D

Soil Research ◽  
2006 ◽  
Vol 44 (1) ◽  
pp. 27 ◽  
Author(s):  
I. R. Phillips

The ability of HYDRUS-2D (HYDRUS) to simulate water and chemical transport in large, undisturbed cores of a Vertosol and a Podosol soil was investigated. Parameters required by HYDRUS for simulating water and chemical transport, and nitrogen transformation, were obtained from previously published laboratory studies. HYDRUS simulated the measured cumulative drainage and cumulative chloride (Cl–) leaching behaviour very closely for both soil types, and also provided a very good description of coupled nitrogen transformation (conversion of ammonium to nitrate) and leaching (coefficient of model efficiency ∼1). There was little correlation between measured and predicted potassium (K+) leaching from the Podosol, suggesting that the mathematical equations governing the transport of reactive chemicals did not adequately reflect K+ behaviour in this coarse-textured soil. The reason for this discrepancy is unclear but may have been related to the use of sorption parameters obtained from batch rather than miscible displacement techniques, or mechanisms controlling K+ sorption were not well represented by the general non-linear sorption equation used by HYDRUS. The ability of HYDRUS to accurately simulate water and non-reactive chemical transport agrees with previous studies; however, more investigation into its suitability for predicting the movement reactive chemicals in soil is warranted.

2020 ◽  
Vol 34 (05) ◽  
pp. 9490-9497
Author(s):  
Ke Yuan ◽  
Dafang He ◽  
Zhuoren Jiang ◽  
Liangcai Gao ◽  
Zhi Tang ◽  
...  

Mathematical equations are an important part of dissemination and communication of scientific information. Students, however, often feel challenged in reading and understanding math content and equations. With the development of the Web, students are posting their math questions online. Nevertheless, constructing a concise math headline that gives a good description of the posted detailed math question is nontrivial. In this study, we explore a novel summarization task denoted as geNerating A concise Math hEadline from a detailed math question (NAME). Compared to conventional summarization tasks, this task has two extra and essential constraints: 1) Detailed math questions consist of text and math equations which require a unified framework to jointly model textual and mathematical information; 2) Unlike text, math equations contain semantic and structural features, and both of them should be captured together. To address these issues, we propose MathSum, a novel summarization model which utilizes a pointer mechanism combined with a multi-head attention mechanism for mathematical representation augmentation. The pointer mechanism can either copy textual tokens or math tokens from source questions in order to generate math headlines. The multi-head attention mechanism is designed to enrich the representation of math equations by modeling and integrating both its semantic and structural features. For evaluation, we collect and make available two sets of real-world detailed math questions along with human-written math headlines, namely EXEQ-300k and OFEQ-10k. Experimental results demonstrate that our model (MathSum) significantly outperforms state-of-the-art models for both the EXEQ-300k and OFEQ-10k datasets.


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