Drought Monitoring and Assessment: Remote Sensing and Modeling Approaches for the Famine Early Warning Systems Network

Drought monitoring is an essential component of drought risk management. It is usually carried out using drought indices/indicators that are continuous functions of rainfall and other hydrometeorological variables. This chapter presents a few examples of how remote sensing and hydrologic modeling techniques are being used to generate a suite of drought monitoring indicators at dekadal (10-day), monthly, seasonal, and annual time scales for several selected regions around the world. Satellite-based rainfall estimates are being used to produce drought indicators such as standardized precipitation index, dryness indicators, and start of season analysis. The Normalized Difference Vegetation Index is being used to monitor vegetation condition. Several satellite data products are combined using agrohydrologic models to produce multiple short- and long-term indicators of droughts. All the data sets are being produced and updated in near-real time to provide information about the onset, progression, extent, and intensity of drought conditions. The data and products produced are available for download from the Famine Early Warning Systems Network (FEWS NET) data portal at http:// earlywarning.usgs.gov. The availability of timely information and products support the decision-making processes in drought-related hazard assessment, monitoring, and management with the FEWS NET. The drought-hazard monitoring approach perfected by the U.S. Geological Survey for FEWS NET through the integration of satellite data and hydrologic modeling can form the basis for similar decision support systems. Such systems can operationally produce reliable and useful regional information that is relevant for local, district-level decision making

Past, present and future of information and knowledge sharing in the construction industry: Towards semantic service-based e-construction

The paper reviews product data technology initiatives in the construction sector and provides a synthesis of related ICT industry needs. A comparison between (a) the data centric characteristics of Product Data Technology (PDT) and (b) ontology with a focus on semantics, is given, highlighting the pros and cons of each approach. The paper advocates the migration from data-centric application integration to ontology-based business process support, and proposes inter-enterprise collaboration architectures and frameworks based on semantic services, underpinned by ontology-based knowledge structures. The paper discusses the main reasons behind the low industry take up of product data technology, and proposes a preliminary roadmap for the wide industry diffusion of the proposed approach. In this respect, the paper stresses the value of adopting alliance-based modes of operation

Deletion of IL-4Rα on CD4 T Cells Renders BALB/c Mice Resistant to Leishmania major Infection

Effector responses induced by polarized CD4(+) T helper 2 (Th2) cells drive nonhealing responses in BALB/c mice infected with Leishmania major. Th2 cytokines IL-4 and IL-13 are known susceptibility factors for L. major infection in BALB/c mice and induce their biological functions through a common receptor, the IL-4 receptor α chain (IL-4Rα). IL-4Rα–deficient BALB/c mice, however, remain susceptible to L. major infection, indicating that IL-4/IL-13 may induce protective responses. Therefore, the roles of polarized Th2 CD4(+) T cells and IL-4/IL-13 responsiveness of non-CD4(+) T cells in inducing nonhealer or healer responses have yet to be elucidated. CD4(+) T cell–specific IL-4Rα (Lck(cre)IL-4Rα(−/lox)) deficient BALB/c mice were generated and characterized to elucidate the importance of IL-4Rα signaling during cutaneous leishmaniasis in the absence of IL-4–responsive CD4(+) T cells. Efficient deletion was confirmed by loss of IL-4Rα expression on CD4(+) T cells and impaired IL-4–induced CD4(+) T cell proliferation and Th2 differentiation. CD8(+), γδ(+), and NK–T cells expressed residual IL-4Rα, and representative non–T cell populations maintained IL-4/IL-13 responsiveness. In contrast to IL-4Rα(−/lox) BALB/c mice, which developed ulcerating lesions following infection with L. major, Lck(cre)IL-4Rα(−/lox) mice were resistant and showed protection to rechallenge, similar to healer C57BL/6 mice. Resistance to L. major in Lck(cre)IL-4Rα(−/lox) mice correlated with reduced numbers of IL-10–secreting cells and early IL-12p35 mRNA induction, leading to increased delayed type hypersensitivity responses, interferon-γ production, and elevated ratios of inducible nitric oxide synthase mRNA/parasite, similar to C57BL/6 mice. These data demonstrate that abrogation of IL-4 signaling in CD4(+) T cells is required to transform nonhealer BALB/c mice to a healer phenotype. Furthermore, a beneficial role for IL-4Rα signaling in L. major infection is revealed in which IL-4/IL-13–responsive non-CD4(+) T cells induce protective responses

Trends in Virtual Water Export from the High Plains, 1950-2010

Water and land are both essential to humans in order to produce food. Over the last century the human population grew rapidly and with it the demand for food. One consequence is an amplified demand for water, which may cause an increase in water scarcity. A possible solution is to import virtual water, all water consumed by a product during production and processing. The United States is one of the major net exporters of virtual water because of the trade of agricultural products. The High Plains region in the central United States has experienced large land use change during the last 150 years, from grassland to one of the country’s main agricultural areas. One driver was water provided by the High Plains aquifer. The purpose of this thesis was to investigate the correlation between this land use change and virtual water exports from the area. This required quantification of the virtual water exports from the study area by volume and region for the selected commodities of wheat, corn, beef, and milk. Virtual water export is a product of the water footprint, and the export quantity and was estimated from 1950 to 2011. The water footprint was calculated using evapotranspiration estimated using the Soil Conservation Service Blaney-Criddle method and output quantity (yield, mass of product). The reported export data had limited temporal availability and limitations. Thus, a method was developed to estimate export data. Mexico was the largest importer of virtual water for corn, beef, and milk, while Egypt was the largest importer of virtual water for wheat. Further analysis showed an increase in virtual water export since 1950. The correlation between land use change and virtual water export was strong (R2 = 0.8). In conclusion, virtual water export is one driver for land use change in the High Plains. The projected increase of exports from the region will contribute to more land use change related to food production. This could increase the risk of water scarcity in the region. Therefore, importing countries have an impact on water and land use in the High Plains

Illuminating Inuit life at Double Mer Point: the excavation of an 18th-century communal winter house

This thesis focuses on the excavation of an 18th-century Inuit winter sod house located at Double Mer Point (GbBo-2) in Hamilton Inlet, Labrador. Hamilton Inlet has long been considered a vital region for understanding the Labrador Inuit and their relationships with Europeans in the 18th century, yet archaeological investigation has been limited. Merchants from Quebec established trading posts in Hamilton Inlet in the 18th century, providing a regular local source of goods for Inuit living in the region. As operations grew at these posts, more Europeans came to work and settle in the area, creating a unique interaction sphere with great potential for economic benefit to both parties, as well as very real challenges. The complete excavation of a small communal house in a larger settlement and examination of the material culture within provides an opportunity to examine the role of communal houses in this time of dramatic change

Remote Sensing of Evapotranspiration for Operational Drought Monitoring Using Principles of Water and Energy Balance

Evapotranspiration (ET) is an important component of the hydrologic budget because it reflects the exchange of mass and energy between the soil–water–vegetation system and the atmosphere. Prevailing weather conditions influence potential or reference ET through variables such as radiation, temperature, wind, and relativity humidity. In addition to these weather variables, actual ET (ETa) is also affected by land cover type and condition, as well as soil moisture. The dependence of ETa on land cover and soil moisture, and its direct relationship with carbon dioxide assimilation in plants, makes it an important variable for monitoring drought, crop yield, and biomass—a critical capability for decision makers interested in food security, grain markets, water allocation, and carbon sequestration (Bastiaanssen et al., 2005). Because ET can be difficult to measure accurately, especially at large spatial scales, several different hydrologic modeling techniques have been developed to estimate ETa using satellite remote sensing. In general, the ET modeling techniques can be grouped into two broad classes that include models based on surface energy balance (e.g., Bastiaanssen et al., 1998; Su et al., 2005; Allen et al., 2007; Anderson et al., 2007; Senay et al., 2007) and water balance (e.g., Allen et al., 1998, Senay, 2008) principles. While water balance models focus on tracking the pathways and magnitude of rainfall in the soil–vegetation system, most remote sensing energy balance models use land surface temperature (LST) as a primary constraint in partitioning radiant energy available at the surface between heat and water fluxes

Linked energy data: Enabling monitoring and decision support for improved energy management

This paper shows how the European Odysseus project [6] reduces energy/CO2 by improved decision making based on multi-level, semantic, energy configuration/monitoring data fully based on open standards (W3C Linked Data approach / Semantic Web technology) and an open source semantic server (Apache Marmotta) implementing those standards. © 2015 IEEE