358 research outputs found

    Performance of GloFAS Flood Forecasts using proxy data in Uganda

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    Capabilities to forecast fluvial flooding are not equality spread across the globe and forecasting systems are especially limited in flood-prone low-income countries (Revilla Romero et al., 2014). The availability of higher spatial and temporal resolution remote sensing data and the increase in post processing technology have opened opportunities for fluvial forecasting at a continental and global scale (Emerton et al., 2016a) (Revilla-Romero et al., 2015). This means flood forecasts are available for regions where previously there were no forecasting capabilities. The availability of flood forecasts for flood-prone low-income countries does not directly lead to action being taken in case of flooding. The forecast based financing program of the Red Cross Climate Centre enables early action to be taken using probabilistic forecast information, with the aim of reducing the impacts of flooding (Coughlan de Perez et al 2015). The program uses a combination of forecast models including the Global Flood Awareness System (GLoFAS) and is active in multiple location including Tongo, Peru and Uganda. There are many factors at play to create an effective early warning system, including the performance of the forecast. Analysing the performance of forecasts is essential for the further improvement and development of an effective early warning system. However, in low-income countries with a low data availability this is a major challenge. This poster shows the performance of the GloFAS forecast using proxy flood event data in the North East of Uganda and poses the question: “How can the performance of forecasts be analysed when data is limited and uncertain?”

    Estimating flood forecast performance using inundation data in Soroti, Uganda

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    This work explores the question “How can data on flood extents derived from Earth Observations (EO) be used to assess the performance of a global flood forecasting model in the ungauged catchment of the Okere and Okok Rivers in Uganda?”. The Global Flood Awareness System (GloFAS), jointly developed by the European Commission and the European Centre for Medium-Range Weather Forecasts (ECMWF), is a global hydrological forecast and monitoring system. In many parts of sub-Saharan Africa the performance of GloFAS has not been assessed. GloFAS is being used in some parts of Uganda to forecast floods. Recently Africa Risk Capacity has been developing a pan-African flood model for use in underpinning parametric flood insurance. The African Flood Extent Depiction Model (AFED) is a daily depiction of temporarily flooded areas everywhere in Africa over the past 20 years. The AFED uses satellite remote sensing from microwave sensors to map floods. The AFED data set was used to assess the performance of GloFAS for two rivers in Uganda. The AFED flood data consists of a flooded fraction per pixel which ranges from 0 to 1. This is not directly comparable to the river discharges produced by the GloFAS flood forecasting model. In order to compare both datasets and assess GloFAS’s performance, the following steps were taken: Extracting the flooded fraction of the Okok and Okere Rivers. Five methods were explored: Flooded fraction of the most downstream pixel; Catchment average flooded fraction for all non-zero pixels; Maximum flooded fraction in catchment; Number of pixels that are non-zero in the catchment; Sum of flooded fraction of all the pixels in the catchment. Comparing the recorded floods derived from newspaper articles with the EO data to establish if the AFED captures the flooding of the Okok and Okere Rivers. Establishing the range of the flood fraction that signifies flooding in recorded events. Extracting flood events using the peaks of the AFED data and the range of flooding from step 3. Assessing the performance of GloFAS and calculating its skill scores using this extended flood events. Results show that AFED data successfully identifies flooding for the two rivers and can be used to assess GloFAS’s performance

    Sulfur gases produced by the decomposition of sulfide minerals: Application to geochemical exploration

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    We have evaluated the potential application of sulfur gas analysis to exploration for buried sulfide mineral deposits by: (1) calculating by use of equilibrium thermodynamics, the relative abundances of gases that should be given off by decomposing sulfide minerals; and (2) determining experimentally the abundances of gases that are actually given off. The calculations indicate that the gases that should be given off by decomposing sulfide minerals are (in order of decreasing abundance) H2S, COS, CS2, CH3SH, (CH3)2S2 or SO2 or S2 (depending on Eh and pH). In contrast, our experiments show that decomposing sulfide minerals evolve only CS2 and COS, in order of decreasing abundance. Pyrite produces the largest amounts of sulfur gas. Moist (rather than saturated) and non-sterile (rather than sterile) conditions enhance gas generation from pyrite, although no large difference appeared between sterile and non-sterile experiments for other sulfide minerals. These experiments indicate that the sulfur gases CS2 and COS could be useful indicators of buried metal sulfide deposits.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/23777/1/0000015.pd
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