The types of data and models used within the hydrologic science community are diverse. New repositories have succeeded in making data and models more accessible, but are, in most cases, limited to particular types or classes of data or models and also lack the type of collaborative and iterative functionality needed to enable shared data collection and modeling workflows. File sharing systems currently used within many scientific communities for private sharing of preliminary and intermediate data and modeling products do not support collaborative data capture, description, visualization, and annotation. In this article, we cast hydrologic datasets and models as “social objects” that can be published, collaborated around, annotated, discovered, and accessed. This article describes the generic data model and content packaging scheme for diverse hydrologic datasets and models used by a new hydrologic collaborative environment called HydroShare to enable storage, management, sharing, publication, and annotation of the diverse types of data and models used by hydrologic scientists. The flexibility of HydroShare's data model and packaging scheme is demonstrated using multiple hydrologic data and model use cases that highlight its features.

Abstract-We present the Networked InfoMechanical System for Planar Translation, which is a novel two-degree-of-freedom (2-DOF) cable-driven robot with self-calibration and online driftcorrection capabilities. This system is intended for actuated sensing applications in aquatic environments. The actuation redundancy resulting from in-plane translation driven by four cables results in an infinite set of tension distributions, thus requiring realtime computation of optimal tension distributions. To this end, we have implemented a highly efficient, iterative linear programming solver, which requires a very small number of iterations to converge to the optimal value. In addition, two novel self-calibration methods have been developed that leverage the robot's actuation redundancy. The first uses an incremental displacement, or jitter method, whereas the second uses variations in cable tensions to determine end-effector location. We also propose a novel leastsquares drift-detection algorithm, which enables the robot to detect long-term drift. Combined with self-calibration capabilities, this drift-monitoring algorithm enables long-term autonomous operation. To verify the performance of our algorithms, we have performed extensive experiments in simulation and on a real system.

Increasing demands on water supplies, non-point source pollution, and water quality-based ecological concerns all point to the need for observing stream flow perturbations and pollutant discharges at higher resolution than was practical in the past. This work presents a rapidly deployable Networked Infomechanical System (NIMS RD) technology for observing spatiotemporal hydraulic and chemical properties across stream channels.NIMS RD is comprised of two supporting towers and a suspension cable delivering power and Internet connectivity for controlling and actuating the tram-like NIMS unit. The NIMS unit is capable of raising and lowering a payload of sensors, allowing a preprogrammed or data-actuated adaptive scan to be completed across a stream channel.In this work, NIMS RD is demonstrated in two relevant cases: (1) elucidating spatiotemporal variations in nutrients and other biologically significant stream constituents in Medea Creek, a small urban stream in Southern California, and (2) using high resolution synoptic sampling of steady velocity and salinity distributions across the San Joaquin River in Central California to provide quantitative salt load estimates. For Medea Creek, temperature and specific conductivity (SC) exhibited varying cross-sectional patterns throughout each of three 24-hour scans carried out over three summer months. Both temperature and SC displayed repeating sinusoidal diel fluctuations independent of the spatial variation. For each of the months the cross-sectional variation was lower during the 2 late nighttime and morning hours than during the afternoon and early nighttime hours. For the San Joaquin River, high resolution velocity distributions from NIMS RD were successfully reproduced in separate deployments, and quantitatively matched stage-based volumetric flow rates at the site. The product of the velocity and associated SC distributions yielded total salt load estimates similar to report values, but no basis for direct comparison was available.