DEVELOPMENT OF PADDY-FIELD WATER LEVEL GAGE CORRESPONDING TO A SENSOR-NETWORK

This study proposes a measurement system that comprises an e-Tape water level sensor, Arduino and XBee. The system was considered a success because of the linear relation between measured voltage signals and water depths obtained by it. This linearity was essential because Arduino does not have non-linear calculation ability. As a result, the numerical order of RMSE in measuring water depth using this system was obtained as 3.52 mm. For measuring water consumption for 1 day at the standard scale of paddy fields in Japan, water consumption can be estimated using the system below non-flowing water surfaces. However, when there is water flow, it will be difficult to estimate water consumption because discharge errors may be cumulative.

Impact of high flows of an Arctic river on ring widths of floodplain trees

The tree-ring signal for flooding along the Ob River, a large Arctic River in western Siberia, is investigated using a combination of floodplain tree-ring sites from riparian and non-riparian settings. A conceptual model is presented contrasting tree-growth responses of riparian and non-riparian trees to unusually severe flooding. A set of five riparian ( Salix and Populus) tree-ring chronologies is developed and used in combination with existing floodplain non-riparian Larix and Pinus chronologies in a binary classification tree (CT) model to classify high-flood years, defined as a Salekhard water-level gage reading in the seasonal window from May 1 to August 31 of above 470 cm for 82 or more consecutive days. Correlation and regression identifies a nonlinear relationship of riparian ring widths to discharge and flooding: higher annual discharge generally leads to higher growth, but the relationship reverses in extreme-flood years. Micrographs highlight the suppression of width and occasional distortion of cell anatomy in selected trees. CT modeling guided by cross-validation yields a CT model with a primary split on the riparian ring width and secondary split on the non-riparian ring width. The model successfully identifies four of the eight most severe high-flow years, 1934–2014. The model further identifies two years (1885 and 1914) before the start of the gaged record in 1934 as high-flow years. No appreciable difference is found in frequency of high-flow years before and after 1956, when the first major reservoirs began filling upstream of the Lower Ob. The CT modeling approach is proposed as a novel approach to dealing with nonlinearity in reconstructing flood history of Arctic rivers from tree rings.

Modeling tamping recovery of track geometry using the copula-based approach

Assessing and maintaining track geometry within acceptable limits are key components of railroad infrastructure maintenance operations. Track geometry conditions have a significant influence on rider comfort and safety. To maintain the ride quality and safety of the track, maintenance activities pertaining to track geometry, such as tamping, are performed. Tamping enhances the track geometry quality but fails to return the track geometry to an as-good-as-new condition. Majority of studies have evaluated tamping recovery using deterministic techniques, which assume that tamping recovery is dependent on the track geometry quality prior to tamping. However, they fail to capture the uncertainty of the recovery values. Probabilistic approaches are increasingly being used to account for the uncertainty but fail to model the underlying dependence between the variables, which may exhibit nonlinear dependences such as tail or asymmetric dependence. To accurately model the tamping recovery phenomenon, this research employs the copula models in combining arbitrary marginal distributions to form a joint multivariate distribution with the underlying dependence. Copula models are used to estimate the tamping recovery of track geometry parameters such as surface (longitudinal level), alignment, cross level, gage, and warp.