Performance measurement and indicators for water supply management: review and international cases

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Climate Change and Water Resources Management: A Federal Perspective

Many challenges, including climate change, face the Nation’s water managers. The Intergovernmental Panel on Climate Change (IPCC) has provided estimates of how climate may change, but more understanding of the processes driving the changes, the sequences of the changes, and the manifestation of these global changes at different scales could be beneficial. Since the changes will likely affect fundamental drivers of the hydrological cycle, climate change may have a large impact on water resources and water resources managers. The purpose of this interagency report prepared by the U.S. Geological Survey (USGS), U.S. Army Corps of Engineers (USACE), Bureau of Reclamation (Reclamation), and National Oceanic and Atmospheric Administration (NOAA) is to explore strategies to improve water management by tracking, anticipating, and responding to climate change. The key points below briefly summarize the chapters in this report and represent underlying assumptions needed to address the many impacts of climate change.

Integration of spatial and temporal models to predict extreme water table depths

The objective of this work was to evaluate extreme water table depths in a watershed, using methods for geographical spatial data analysis. Groundwater spatio-temporal dynamics was evaluated in an outcrop of the Guarani Aquifer System. Water table depths were estimated from monitoring of water levels in 23 piezometers and time series modeling available from April 2004 to April 2011. For generation of spatial scenarios, geostatistical techniques were used, which incorporated into the prediction ancillary information related to the geomorphological patterns of the watershed, using a digital elevation model. This procedure improved estimates, due to the high correlation between water levels and elevation, and aggregated physical sense to predictions. The scenarios showed differences regarding the extreme levels - too deep or too shallow ones - and can subsidize water planning, efficient water use, and sustainable water management in the watershed.

JOB SATISFACTION: A QUALITY INDICATOR IN NURSING HUMAN RESOURCE MANAGEMENT

This descriptive study addresses the job satisfaction of nurse managers and clinical nurses working at the Hematology and Hemotherapy Services of a public hospital in Sao Paulo. The study objectives were to identify the factors that caused job satisfaction among nurse managers and clinical nurses, and support the results in the development of indicators to evaluate the quality of nursing human resource management. The components of the study were: autonomy, interaction, professional status, job requirements, organizational norms and remuneration. Participants were 44 nurses. Data were collected using a Job Satisfaction Index (JSI) questionnaire. In conclusion, this study permitted the identification of the clinical nurse group, which was the most satisfied, with a JSI of 10.5; the managerial group scored 10.0. Regarding the satisfaction levels in regards to the current activity, 88.9% of the nurse managers reported feeling satisfied, as did 90.9% of clinical nurses. For both groups, autonomy was the component with the highest level of professional satisfaction.

A resource management scenario for traditional and scientific management of pink shrimp (Farfantepenaeus paulensis) in the Patos Lagoon estuary (RS), Brazil

Abstract Background This article aims to discuss the incorporation of traditional time in the construction of a management scenario for pink shrimp in the Patos Lagoon estuary (RS), Brazil. To meet this objective, two procedures have been adopted; one at a conceptual level and another at a methodological level. At the conceptual level, the concept of traditional time as a form of traditional ecological knowledge (TEK) was adopted. Method At the methodological level, we conduct a wide literature review of the scientific knowledge (SK) that guides recommendations for pink shrimp management by restricting the fishing season in the Patos Lagoon estuary; in addition, we review the ethno-scientific literature which describes traditional calendars as a management base for artisanal fishers in the Patos Lagoon estuary. Results Results demonstrate that TEK and SK describe similar estuarine biological processes, but are incommensurable at a resource management level. On the other hand, the construction of a “management scenario” for pink shrimp is possible through the development of “criteria for hierarchies of validity” which arise from a productive dialog between SK and TEK. Conclusions The commensurable and the incommensurable levels reveal different basis of time-space perceptions between traditional ecological knowledge and scientific knowledge. Despite incommensurability at the management level, it is possible to establish guidelines for the construction of “management scenarios” and to support a co-management process.

Ultra-low power WSNs: distributed signal processing and dynamic resource management

This thesis presents several data processing and compression techniques capable of addressing the strict requirements of wireless sensor networks. After introducing a general overview of sensor networks, the energy problem is introduced, dividing the different energy reduction approaches according to the different subsystem they try to optimize. To manage the complexity brought by these techniques, a quick overview of the most common middlewares for WSNs is given, describing in detail SPINE2, a framework for data processing in the node environment. The focus is then shifted on the in-network aggregation techniques, used to reduce data sent by the network nodes trying to prolong the network lifetime as long as possible. Among the several techniques, the most promising approach is the Compressive Sensing (CS). To investigate this technique, a practical implementation of the algorithm is compared against a simpler aggregation scheme, deriving a mixed algorithm able to successfully reduce the power consumption. The analysis moves from compression implemented on single nodes to CS for signal ensembles, trying to exploit the correlations among sensors and nodes to improve compression and reconstruction quality. The two main techniques for signal ensembles, Distributed CS (DCS) and Kronecker CS (KCS), are introduced and compared against a common set of data gathered by real deployments. The best trade-off between reconstruction quality and power consumption is then investigated. The usage of CS is also addressed when the signal of interest is sampled at a Sub-Nyquist rate, evaluating the reconstruction performance. Finally the group sparsity CS (GS-CS) is compared to another well-known technique for reconstruction of signals from an highly sub-sampled version. These two frameworks are compared again against a real data-set and an insightful analysis of the trade-off between reconstruction quality and lifetime is given.

Runoff Water Quality and Pollutant Mass Loads From Extensive Green Roofs

Green roof mitigation of volume and peak flow-rate of stormwater runoff has been studied extensively. However, due to the common practice of green roof fertilization, there is the potential for introduction of nutrients into local bodies of water. Therefore, this study compares green roof runoff quality with the water quality of precipitation and runoff from a bare shingle roof. The runoff from a demonstration-scale extensive green roof was analyzed during the summer of 2011 for its effect on runoff volume and analyzed during eleven storm events in the fall and winter for concentrations of copper, cadmium, zinc, lead, nitrogen species, total nitrogen, total organic carbon, sulfate, orthophosphate, and other monovalent and divalent ions. The green roof reduced the overall volume of runoff and served as a sink for NO3 - and NH4 +. However, the green roof was also a source for the pollutants PO4 3-, SO4 2-, TOC, cations, and total nitrogen. Metals such as zinc and lead showed trends of higher mass loads in the bare roof runoff than in precipitation and green roof runoff, although results were not statistically significant. The green roof also showed trends, although also not statistically significant, of retaining cadmium and copper. With the green roof serving as a source of phosphorous species and a sink for nitrogen species, and appearing to a retain metals and total volume, the life cycle impact analysis shows minimum impacts from the green roof, when compared with precipitation and bare roof runoff, in all but fresh water eutrophication. Therefore, the best environments to install a green roof may be in coastal environments.