Nonparametric Tree-Based Predictive Modeling of Storm Outages on an Electric Distribution Network.

This article compares two nonparametric tree-based models, quantile regression forests (QRF) and Bayesian additive regression trees (BART), for predicting storm outages on an electric distribution network in Connecticut, USA. We evaluated point estimates and prediction intervals of outage predictions for both models using high-resolution weather, infrastructure, and land use data for 89 storm events (including hurricanes, blizzards, and thunderstorms). We found that spatially BART predicted more accurate point estimates than QRF. However, QRF produced better prediction intervals for high spatial resolutions (2-km grid cells and towns), while BART predictions aggregated to coarser resolutions (divisions and service territory) more effectively. We also found that the predictive accuracy was dependent on the season (e.g., tree-leaf condition, storm characteristics), and that the predictions were most accurate for winter storms. Given the merits of each individual model, we suggest that BART and QRF be implemented together to show the complete picture of a storm's potential impact on the electric distribution network, which would allow for a utility to make better decisions about allocating prestorm resources.

Colored dissolved organic matter dynamics and anthropogenic influences in a major transboundary river and its coastal wetland.

Most transboundary rivers and their wetlands are subject to considerable anthropogenic pressures associated with multiple and often conflicting uses. In the Eastern Mediterranean such systems are also particularly vulnerable to climate change, posing additional challenges for integrated water resources management. Comprehensive measurements of the optical signature of colored dissolved organic matter (CDOM) were combined with measurements of river discharges and water physicochemical and biogeochemical properties, to assess carbon dynamics, water quality, and anthropogenic influences in a major transboundary system of the Eastern Mediterranean, the Evros (or, Марица or, Meriç) river and its Ramsar protected coastal wetland. Measurements were performed over three years, in seasons characterized by different hydrologic conditions and along transects extending more than 70 km from the freshwater end-member to two kilometers offshore in the Aegean Sea. Changes in precipitation, anthropogenic dissolved organic matter (DOM) inputs from the polluted Ergene tributary, and the irregular operation of a dam were key factors driving water quality, salinity regimes, and biogeochemical properties in the Evros delta and coastal waters. Marsh outwelling affected coastal carbon quality, but the influence of wetlands was often masked by anthropogenic DOM contributions. A distinctive five-peak CDOM fluorescence signature was characteristic of upstream anthropogenic inputs and clearly tracked the influence of freshwater discharges on water quality. Monitoring of this CDOM fluorescence footprint could have direct applications to programs focusing on water quality and environmental assessment in this and other transboundary rivers where management of water resources remains largely ineffective.

The US COVID-19 pandemic in the flood season.

Flooding displaces large populations each season, which potentially increases the exposure of the vulnerable societies. Having failed to curve down the number of people infected with COVID-19 in the first wave of the pandemic, many states in the United States (U.S.) are now at high risk of the concurrence of the two disasters. Assessing this compound risk before the country enters the flood season is of vital importance. Therefore, we provide a prompt tool to assess the compound risk of COVID-19 at the county level over the U.S. We find that (1) the number of flood insurance house claims can proxy the displaced population accurately with more spatiotemporal detail, and (2) the high-risk areas of both flooding and COVID-19 are concentrated along the southern and eastern coasts and some parts of the Mississippi River. Our findings may trigger the interest of further exploring the topics related to the concurrence of COVID-19 and flooding.

The role of climate in the trend and variability of Ethiopia's cereal crop yields.

Food security has been and will continue to be a major challenge in Ethiopia. The country's smallholder, rainfed agriculture renders its food production system extremely vulnerable to climate variability and extremes. In this study, we investigate the impact of past climate variability and change on the yields of five major cereal crops in Ethiopia-barley, maize, millet, sorghum, and wheat-during the period 1979-2014 using the Decision Support System for Agrotechnology Transfer (DSSAT) crop model. The model is calibrated at both the site and agroecological-zone scales. At the sites studied, the model results suggest that climate in the past four decades may have contributed to an increasing trend in maize yield, a decreasing trend in wheat yield, and no clear trend in the yields of barley and millet; cereal crop yield is positively correlated with growing season solar radiation and temperature, but negatively correlated with growing season precipitation. For modeled cereal crops across the nation during the study period, yield in western Ethiopia is positively correlated with solar radiation and day time temperature; in the eastern and southeastern Ethiopia where water is a limiting factor for growth, yield is positively correlated with precipitation but negatively correlated with solar radiation and both day time and night time temperature. The national average of simulated yields of most crops (except maize) showed an overall decreasing (although not statistically significant) trend induced by past climate variability and changes. Over a large portion of the highly productive areas where there is a negative correlation between yield and temperature, yield is simulated to have significantly decreased over the past four decades, an indication of adverse climate impact in the past and potential food security concern in the future.

A global distributed basin morphometric dataset.

Basin morphometry is vital information for relating storms to hydrologic hazards, such as landslides and floods. In this paper we present the first comprehensive global dataset of distributed basin morphometry at 30 arc seconds resolution. The dataset includes nine prime morphometric variables; in addition we present formulas for generating twenty-one additional morphometric variables based on combination of the prime variables. The dataset can aid different applications including studies of land-atmosphere interaction, and modelling of floods and droughts for sustainable water management. The validity of the dataset has been consolidated by successfully repeating the Hack's law.

Effect of climatic variability on childhood diarrhea and its high risk periods in northwestern parts of Ethiopia.

BACKGROUND: Increasing climate variability as a result of climate change will be one of the public health challenges to control infectious diseases in the future, particularly in sub-Saharan Africa including Ethiopia. OBJECTIVE: To investigate the effect of climate variability on childhood diarrhea (CDD) and identify high risk periods of diarrheal diseases. METHODS: The study was conducted in all districts located in three Zones (Awi, West and East Gojjam) of Amhara Region in northwestern parts of Ethiopia. Monthly CDD cases for 24 months (from July 2013 to June 2015) reported to each district health office from the routine surveillance system were used for the study. Temperature, rainfall and humidity data for each district were extracted from satellite precipitation estimates and global atmospheric reanalysis. The space-time permutation scan statistic was used to identify high risk periods of CDD. A negative binomial regression was used to investigate the relationship between cases of CDD and climate variables. Statistical analyses were conducted using SaTScan program and StataSE v. 12. RESULTS: The monthly average incidence rate of CDD was 11.4 per 1000 (95%CI 10.8-12.0) with significant variation between males [12.5 per 1000 (95%CI 11.9 to 13.2)] and females [10.2 per 1000 (95%CI 9.6 to 10.8)]. The space-time permutation scan statistic identified the most likely high risk period of CDD between March and June 2014 located in Huletej Enese district of East Gojjam Zone. Monthly average temperature and monthly average rainfall were positively associated with the rate of CDD, whereas the relative humidity was negatively associated with the rate of CDD. CONCLUSIONS: This study found that the most likely high risk period is in the beginning of the dry season. Climatic factors have an association with the occurrence of CDD. Therefore, CDD prevention and control strategy should consider local weather variations to improve programs on CDD.

A user-centered, object-oriented methodology for developing Health Information Systems: a Clinical Information System (CIS) example.

The aim of this study is to present our perspectives on healthcare analysis and design and the lessons learned from our experience with the development of a distributed, object-oriented Clinical Information System (CIS). In order to overcome known issues regarding development, implementation and finally acceptance of a CIS by the physicians we decided to develop a novel object-oriented methodology by integrating usability principles and techniques in a simplified version of a well established software engineering process (SEP), the Unified Process (UP). A multilayer architecture has been defined and implemented with the use of a vendor application framework. Our first experiences from a pilot implementation of our CIS are positive. This approach allowed us to gain a socio-technical understanding of the domain and enabled us to identify all the important factors that define both the structure and the behavior of a Health Information System.

Cavernous hemangioma of infrahyoid carotid sheath and review of the literature on carotid sheath tumors.

BACKGROUND: Carotid sheath may include a variety of lesions such as neurogenic or vascular, tumors originating from extra-adrenal chromaphil cells, squamous cell carcinomas, and lymphomas. Hemangiomas are benign congenital neoplasms, which, when located in the head and neck region, may be easily misdiagnosed due to their infrequent localization. METHODS AND RESULTS: We report an unusual case of cavernous hemangioma of the infrahyoid carotid sheath presenting as palpable mass in a 51-year-old woman with no prior medical history. A review of the literature was performed to investigate the radiological and histopathological characteristics and highlight the treatment of carotid sheath lesions. CONCLUSIONS: CT, MRI, and MR angiography would help to locate hemangiomas of carotid sheath, but only surgical excision and histopathology can reveal their true nature.