Energy-efficient Traffic Allocation in SDN-based Backhaul Networks: Theory and Implementation

5G networks are expected to be highly energy efficient, with a 10 times lower consumption than today’s systems. An effective way to achieve such a goal is to act on the backhaul network by controlling the nodes operational state and the allocation of traffic flows. To this end, in this paper we formulate energy-efficient flow routing on the backhaul network as an optimization problem. In light of its complexity, which impairs the solution in large-scale scenarios, we then propose a heuristic approach. Our scheme, named EMMA, aims to both turn off idle nodes and concentrate traffic on the smallest possible set of links, which in its turn increases the number of idle nodes. We implement EMMA on top of ONOS and derive experimental results by emulating the network through Mininet. Our results show that EMMA provides excellent energy saving performance, which closely approaches the optimum. In larger network scenarios, the gain in energy consumption that EMMA provides with respect to the simple benchmark where all nodes are active, is extremely high under medium-low traffic load

Corrigendum to "Assessing the potential hydrological impact of the Gibe III Dam on Lake Turkana water level using multi-source satellite data" published in Hydrol. Earth Syst. Sci., 16, 3561–3578, 2012

No abstract available

Evapotranspiration in the Nile Basin: Identifying Dynamics, Trends, and Drivers 2002-2011

Analysis of the relationship between evapotranspiration (ET) and its natural and anthropogenic drivers is critical in water-limited basins such as the Nile. The spatiotemporal relationships of ET with rainfall and vegetation dynamics in the Nile Basin during 2002–2011 were analyzed using satellite-derived data. Non-parametric statistics were used to quantify ET-rainfall interactions and trends across land cover types and subbasins. We found that 65% of the study area (2.5 million km2) showed significant (p \u3c 0.05) positive correlations between monthly ET and rainfall, whereas 7% showed significant negative correlations. As expected, positive ET-rainfall correlations were observed over natural vegetation, mixed croplands/natural vegetation, and croplands, with a few subbasin-specific exceptions. In particular, irrigated croplands, wetlands and some forests exhibited negative correlations. Trend tests revealed spatial clusters of statistically significant trends in ET (6% of study area was negative; 12% positive), vegetation greenness (24% negative; 12% positive) and rainfall (11% negative; 1% positive) during 2002–2011. The Nile Delta, Ethiopian highlands and central Uganda regions showed decline in ET while central parts of Sudan, South Sudan, southwestern Ethiopia and northeastern Uganda showed increases. Except for a decline in ET in central Uganda, the detected changes in ET (both positive and negative) were not associated with corresponding changes in rainfall. Detected declines in ET in the Nile delta and Ethiopian highlands were found to be attributable to anthropogenic land degradation, while the ET decline in central Uganda is likely caused by rainfall reduction

A Self-calibrating Runoff and Streamflow Remote Sensing Model for Ungauged Basins Using Open-access Earth Observation Data

Due to increasing pressures on water resources, there is a need to monitor regional water resource availability in a spatially and temporally explicit manner. However, for many parts of the world, there is insufficient data to quantify stream flow or ground water infiltration rates. We present the results of a pixel-based water balance formulation to partition rainfall into evapotranspiration, surface water runoff and potential ground water infiltration. The method leverages remote sensing derived estimates of precipitation, evapotranspiration, soil moisture, Leaf Area Index, and a single F coefficient to distinguish between runoff and storage changes. The study produced significant correlations between the remote sensing method and field based measurements of river flow in two Vietnamese river basins. For the Ca basin, we found R2 values ranging from 0.88–0.97 and Nash–Sutcliffe efficiency (NSE) values varying between 0.44–0.88. The R2 for the Red River varied between 0.87–0.93 and NSE values between 0.61 and 0.79. Based on these findings, we conclude that the method allows for a fast and cost-effective way to map water resource availability in basins with no gauges or monitoring infrastructure, without the need for application of sophisticated hydrological models or resource-intensive data

Assessing the potential hydrological impact of the Gibe III Dam on Lake Turkana water level using multi-source satellite data

Lake Turkana, the largest desert lake in the world, is fed by ungauged or poorly gauged river systems. To meet the demand of electricity in the East African region, Ethiopia is currently building the Gibe III hydroelectric dam on the Omo River, which supplies more than 80% of the inflows to Lake Turkana. On completion, the Gibe III dam will be the tallest dam in Africa with a height of 241 m. However, the nature of interactions and potential impacts of regulated inflows to Lake Turkana are not well understood due to its remote location and unavailability of reliable in situ datasets. In this study, we used 12 yr (1998–2009) of existing multi-source satellite and model-assimilated global weather data. We used a calibrated multi-source satellite data-driven water balance model for Lake Turkana that takes into account model routed runoff, lake/reservoir evapotranspiration, direct rain on lakes/reservoirs and releases from the dam to compute lake water levels. The model evaluates the impact of the Gibe III dam using three different approaches – a historical approach, a rainfall based approach, and a statistical approach to generate rainfall-runoff scenarios. All the approaches provided comparable and consistent results. Model results indicated that the hydrological impact of the Gibe III dam on Lake Turkana would vary with the magnitude and distribution of rainfall post-dam commencement. On average, the reservoir would take up to 8–10 months, after commencement, to reach a minimum operation level of 201 m depth of water. During the dam filling period, the lake level would drop up to 1–2 m (95% confidence) compared to the lake level modeled without the dam. The lake level variability caused by regulated inflows after the dam commissioning were found to be within the natural variability of the lake of 4.8 m. Moreover, modeling results indicated that the hydrological impact of the Gibe III dam would depend on the initial lake level at the time of dam commencement. Areas along the Lake Turkana shoreline that are vulnerable to fluctuations in lake levels due to the Gibe III dam were also identified. This study demonstrates the effectiveness of using existing multi-source satellite data in a basic modeling framework to assess the potential hydrological impact of an upstream dam on a terminal downstream lake. The results obtained from this study could also be used to evaluate alternative dam-filling scenarios and assess the potential impact of the dam on Lake Turkana under different operational strategies

Manipulation of High Spatial Resolution Aircraft Remote Sensing Data for Use in Site-Specific Farming

Three spatial data sets consisting of high spatial resolution (1 m) remote sensing images acquired in 12 spectral bands, an on-the-go yield map, and a Digital Elevation Model were co-registered and evaluated for spatial variability studies in a Geographic Information Systems environment. Separate on-the-go yield maps were developed for 3, 5, and 12 statistically significant mean yield classes. For each yield class, the corresponding mean spectral and elevation data were extracted. The relationship between mean spectral and yield data was strongly linear (r = 0.99). Also, a strong linear relationship between mean yield and elevation data (r = 0.92) was found. The relationship between the spectral and on-the-go yield data indicated the potential of remote sensing for spatial variability studies

Evaluation of the Event Driven Phenology Model Coupled with the VegET Evapotranspiration Model Through Comparisons with Reference Datasets in a Spatially Explicit Manner

A new model coupling scheme with remote sensing data assimilation was developed for estimation of daily actual evapotranspiration (ET). The scheme represents a mix of the VegET, a physically based model to estimate ET from a water balance, and an event driven phenology model (EDPM), where the EDPM is an empirically derived crop specific model capable of producing seasonal trajectories of canopy attributes. In this experiment, the scheme was deployed in a spatially explicit manner within the croplands of the Northern Great Plains. The evaluation was carried out using 2007-2009 land surface forcing data from the North American Land Data Assimilation System (NLDAS) and crop maps derived from remotely sensed data of NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). We compared the canopy parameters produced by the phenology model with normalized difference vegetation index (NDVI) data derived from the MODIS nadir bi-directional reflectance distribution function (BRDF) adjusted reflectance (NBAR) product. The expectations of the EDPM performance in prognostic mode were met, producing determination coefficient (r2) of 0.8 +/-.0.15. Model estimates of NDVI yielded root mean square error (RMSE) of 0.1 +/-.0.035 for the entire study area. Retrospective correction of canopy dynamics with MODIS NDVI brought the errors down to just below 10% of observed data range. The ET estimates produced by the coupled scheme were compared with ones from the MODIS land product suite. The expected r2=0.7 +/-.15 and RMSE = 11.2 +/-.4 mm per 8 days were met and even exceeded by the coupling scheme0 functioning in both prognostic and retrospective modes. Minor setbacks of the EDPM and VegET performance (r2 about 0.5 and additional 30 % of RMSR) were found on the peripheries of the study area and attributed to the insufficient EDPM training and to spatially varying accuracy of crop maps. Overall the experiment provided sufficient evidence of soundness and robustness of the EDPM and VegET coupling scheme, assuring its potential for spatially explicit applications

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

Evaluation of true maximal oxygen uptake based on a novel set of standardized criteria

In this study, criteria are used to identify whether a subject has elicited maximal oxygen uptake. We evaluated the validity of traditional maximal oxygen uptake criteria and propose a novel set of criteria. Twenty athletes completed a maximal oxygen uptake test, consisting of an incremental phase and a subsequent supramaximal phase to exhaustion (verification phase). Traditional and novel maximal oxygen uptake criteria were evaluated. Novel criteria were: oxygen uptake plateau defined as the difference between modelled and actual maximal oxygen uptake >50% of the regression slope of the individual oxygen uptake-workrate relationship; as in the first criterion, but for maximal verification oxygen uptake; and a difference of [less than or equal to]4 beats x [min.sup.-1] between maximal heart rate values in the 2 phases. Satisfying the traditional oxygen uptake plateau criterion was largely an artefact of the between-subject variation in the oxygen uptake-workrate relationship. Secondary criteria, supposedly an indicator of maximal effort, were often satisfied long before volitional exhaustion, even at intensities as low as 61% maximal oxygen uptake. No significant mean differences were observed between the incremental and verification phases for oxygen uptake (t = 0.4; p = 0.7) or heart rate (t = 0.8; p = 0.5). The novel oxygen uptake plateau criterion, maximal oxygen uptake verification criterion, and maximal heart rate verification criterion were satisfied by 17, 18, and 18 subjects, respectively. The small individual absolute differences in oxygen uptake between incremental and verification phases observed in most subjects provided additional confidence that maximal oxygen uptake was elicited. Current maximal oxygen uptake criteria were not valid and novel criteria should be further explored