Abstract:A distributed hydrological model, water and energy transfer processes (WEP) model, is developed to simulate spatially variable water and energy processes in watersheds with complex land covers. In the model, state variables include depression storage on land surfaces and canopies, soil moisture content, land surface temperature, groundwater tables and water stages in rivers, etc. The subgrid heterogeneity of land use is also taken into consideration by using the mosaic method. For hydrological processes, evapotranspiration is computed by the Penman-Monteith equation, infiltration excess during heavy rains is simulated by a generalized Green-Ampt model, whereas saturation excess during the remaining periods is obtained by doing balance analysis in unsaturated soil layers. A two-dimensional simulation of multilayered aquifers is performed for groundwater flow. Flow routing is conducted by using the kinematic wave method in a one-dimensional scheme. For energy processes, short-wave radiation is based on observation or deduced from sunshine duration, long-wave radiation is calculated according to temperatures, latent and sensible fluxes are computed by the aerodynamic method and surface temperature is solved by the force-restore method. In addition, anthropogenic components, e.g. water supply, groundwater lift, sewerage drainage and energy consumption, etc. are also taken into account. The model is applied to the Ebi River watershed (27 km 2 ) with a grid size of 50 m and a time step of 1 h. The model is verified through comparisons of simulated river discharges, groundwater levels and land surface temperatures with the observed values. A comparison between water balance at present (1993) and that in the future (2035) is also conducted. It is found that the hydrological cycle in the future can be improved through the implementation of infiltration trenches for the storm water from urban canopies.

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Since the topographical data obtained from LiDAR (Light Detection and Ranging) measurements is superior in resolution and accuracy as compared to conventional geospatial data, over the last decade aerial LiDAR (Light Detection and Ranging) has been widely used for obtaining geospatial information. However, digital terrain models made from LiDAR data retain some degree of uncertainty as a result of the measurement principles and the operational limitations of LiDAR surveying. LiDAR cannot precisely measure topographical elements such as ground undulation covered by vegetation, curbstones, etc. Such instrumental and physical uncertainties may impact an estimated result in an inundation flow simulation. Meanwhile, how much and how these topographical uncertainties affect calculated results is not understood. To evaluate the effect of topographical uncertainty on the calculated inundation flow, three representative terrains were prepared that included errors in elevation. Here, the topographical uncertainty that was introduced was generated using a fractal algorithm in order to represent the spatial structure of the elevation uncertainty. Then, inundation flows over model terrains were calculated with an unstructured finite volume flow model that solved shallow water equations. The sensitivity of the elevation uncertainty on the calculated inundated propagation, especially the local flow velocity, was evaluated. The predictability of inundation flow over complex topography is discussed, as well as its relationship to topographical features.

Abstract. Fragility curves evaluating a risk of railway embankment fill and track ballast scour were developed. To develop fragility curves, two well-documented events of singletrack railway washout during floods in Japan were investigated. Type of damage to the railway was categorized into no damage, ballast scour, and embankment scour, in order of damage severity. Railway overtopping water depth for each event was estimated based on well-documented hydrologic and hydraulic analyses. Normal and log-normal fragility curves were developed based on damage probability derived from field records and the estimated overtopping water depth. A combined ballast and embankment scour model was validated by comparing the results of previous studies and the spatial distribution of railway damage type records.

Hydrogel glucose sensors with boronic acid-based fluorescence intensity theoretically hold promise to improve in vivo continuous glucose monitoring (CGM) by facilitating long-lasting accuracy. However, these sensors generally degrade after implantation and the fluorescence intensity decreases immediately over time. Herein, we describe a hydrogel glucose sensor with in vivo stability based on boronic acid-based fluorescence intensity, integrating two antioxidant enzymes, superoxide dismutase (SOD), and catalase. These protected the arylboronic acid from being degraded by hydrogen peroxide in vitro and preserved the boronic acid-based fluorescence intensity of the hydrogel glucose sensors in rats for 28 days. These antioxidant enzymes also allowed the hydrogel glucose sensor attached to a homemade semi-implantable CGM device to trace blood glucose concentrations in rats for 5 h with the accuracy required for clinical settings. Hydrogel glucose sensors with boronic acid-based fluorescence intensity containing SOD and catalase could comprise a new strategy for in vivo CGM.