Long-term effects of watershed management on surface runoff and sediment loss in the Ethiopian Highlands

Data on rainfall, runoff and sediment loss from different land use types have been collected by the Soil Conservation Research Programme in seven small catchments (73-673 hectares) throughout the Ethiopian Highlands since the early 1980s. Monitoring was carried out on a storm-to-storm basis for extended periods of 10-20 years, and the data are analysed here to assess long-term effects of changes. Soil and water conservation technologies were introduced in the early years in the catchments in view of their capacity to reduce runoff and sediment yield. Results indicate that rainfall did not substantially change over the observation periods. Land use changes and land degradation, however, altered runoff, as shown by the data from small test plots (30 m2), which were not altered by conservation measures during the monitoring periods. Sediment delivery from the catchments may have decreased due to soil and water conservation, while runoff rates did not change significantly. Extrapolation of the results in the highlands, however, showed that expansion of cultivated and grazing land induced by population growth may have increased the overall surface runoff. Watershed management in the catchments, finally, had beneficial effects on ecosystem services by reducing soil erosion, restoring soil fertility, enhancing agricultural production, and maintaining overall runoff to the benefit of lowland areas and neighbouring countries.

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.

Identification of glacial meltwater runoff in a karstic environment and its implication for present and future water availability

Glaciers all over the world are expected to continue to retreat due to the global warming throughout the 21st century. Consequently, future seasonal water availability might become scarce once glacier areas have declined below a certain threshold affecting future water management strategies. Particular attention should be paid to glaciers located in a karstic environment, as parts of the meltwater can be drained by underlying karst systems, making it difficult to assess water availability. In this study tracer experiments, karst modeling and glacier melt modeling are combined in order to identify flow paths in a high alpine, glacierized, karstic environment (Glacier de la Plaine Morte, Switzerland) and to investigate current and predict future downstream water availability. Flow paths through the karst underground were determined with natural and fluorescent tracers. Subsequently, geologic information and the findings from tracer experiments were assembled in a karst model. Finally, glacier melt projections driven with a climate scenario were performed to discuss future water availability in the area surrounding the glacier. The results suggest that during late summer glacier meltwater is rapidly drained through well-developed channels at the glacier bottom to the north of the glacier, while during low flow season meltwater enters into the karst and is drained to the south. Climate change projections with the glacier melt model reveal that by the end of the century glacier melt will be significantly reduced in the summer, jeopardizing water availability in glacier-fed karst springs.

Soil Infiltration and Wetland Treatment of Feedlot Runoff

Treating feedlot runoff using a soil infiltration area followed by a small constructed wetland can significantly reduce contaminants in the runoff. An infiltration/wetland treatment system has been monitored for three years at ISU’s Beef Nutrition Farm near Ames. Overall contaminant concentrations in the wetland effluent are typically 20% or less than the initial runoff concentrations.

Dynamic SLA management with forecasting using multi-objective optimization

Cost-efficient operation while satisfying performance and availability guarantees in Service Level Agreements (SLAs) is a challenge for Cloud Computing, as these are potentially conflicting objectives. We present a framework for SLA management based on multi-objective optimization. The framework features a forecasting model for determining the best virtual machine-to-host allocation given the need to minimize SLA violations, energy consumption and resource wasting. A comprehensive SLA management solution is proposed that uses event processing for monitoring and enables dynamic provisioning of virtual machines onto the physical infrastructure. We validated our implementation against serveral standard heuristics and were able to show that our approach is significantly better.