Congenital syphilis is a rare and serious disease that, although preventable, continues to be a major healthcare problem. Its clinical spectrum ranges from an asymptomatic infection to fulminating sepsis or death. A diagnosis of congenital syphilis was made in an 8-week-old infant whose mother had adequate prenatal care. We present the clinical and histopathologic findings of this uncommon congenital disease.

We present the development and testing of a web application called the historical validation tool (HVT) that processes and visualizes observed and simulated historical stream discharge data from the global GEOGloWS ECMWF streamflow services (GESS), performs seasonally adjusted bias correction, computes goodness-of-fit metrics, and performs forward bias correction on subsequent forecasts. The HVT corrects GESS output at a local scale using a technique that identifies and corrects model bias using observed hydrological data that are accessed using web services. HVT evaluates the performance of the GESS historic simulation data and provides more accurate historic simulation and bias-corrected forecast data. The HVT also allows users of the GEOGloWS historical streamflow data to use local observed data to both validate and improve the accuracy of local streamflow predictions. We developed the HVT using Tethys Platform, an open-source web application development framework. HVT presents data visualization using web mapping services and data plotting in the web map interface while functions related to bias correction, metrics reporting, and data generation for statistical analysis are computed by the back end. We present five case studies using the HVT in Australia, Brazil, Colombia, the Dominican Republic, and Peru. In these case studies, in addition to presenting the application, we evaluate the accuracy of the method we implemented in the HVT for bias correction. These case studies show that the HVT bias correction in Brazil, Colombia, and Peru results in significant improvement in historic simulation across the countries, while bias correction only resulted in marginal historic simulation improvements in Australia and the Dominican Republic. The HVT web application allows users to use local data to adjust global historical simulation and forecasts and validate the results, making the GESS modeling results more useful at a local scale.

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We present the design and development of an open-source web application called Water Data Explorer (WDE), designed to retrieve water resources observation and model data from data catalogs that follow the WaterOneFlow and WaterML Service-Oriented Architecture standards. WDE is a fully customizable web application built using the Tethys Platform development environment. As it is open source, it can be deployed on the web servers of international government agencies, non-governmental organizations, research teams, and others. Water Data Explorer provides uniform access to international data catalogs, such as the Consortium of Universities for the Advancement of Hydrologic Science (CUAHSI) Hydrologic Information System (HIS) and the World Meteorological Organization (WMO) Hydrological Observing System (WHOS), as well as to local data catalogs that support the WaterOneFlow and WaterML standards. WDE supports data discovery, visualization, downloading, and basic data interpolation. It can be customized for different regions by modifying the user interface (i.e., localization), as well as by including pre-defined data catalogs and data sources. Access to WDE functionality is provided by a new open-source Python package called “Pywaterml” which provides programmable access to WDE methods to discover, visualize, download, and interpolate data. We present two case studies that access the CUAHSI HIS and WHOS catalogs and demonstrate regional customization, data discovery from WaterOneFlow web services, data visualization of time series observations, and data downloading.

The Hindu Kush Himalayan region is extremely susceptible to periodic monsoon floods. Early warning systems with the ability to predict floods in advance can benefit tens of millions of people living in the region. Two web-based flood forecasting tools (ECMWF-SPT and HIWAT-SPT) are therefore developed and deployed jointly by SERVIR-HKH and NASA-AST to provide early warning to Bangladesh, Bhutan, and Nepal. ECMWF-SPT provides ensemble forecast up to 15-day lead time, whereas HIWAT-SPT provides deterministic forecast up to 3-day lead time covering almost 100% of the rivers. Hydrological models in conjunction with forecast validation contribute not only to advancing the processes of a forecasting system, but also objectively assess the joint distribution of forecasts and observations in quantifying forecast accuracy. The validation of forecast products has emerged as a priority need to evaluate the worth of the predictive information in terms of quality and consistency. This paper describes the effort made in developing the hydrological forecast systems, the current state of the flood forecast services, and the performance of the forecast evaluation. Both tools are validated using a selection of appropriate metrics in measurement in both probabilistic and deterministic space. The numerical metrics are further complemented by graphical representations of scores and probabilities. It was found that the models had a good performance in capturing high flood events. The evaluation across multiple locations indicates that the model performance and forecast goodness are variable on spatiotemporal scale. The resulting information is used to support good decision-making in risk and resource management.