This study tried to assess the impact of climate change on water resources of the upper Awash River sub-basin (Ethiopia) using a statistical downscaling model (SDSM). The future climatic parameters (rainfall, maximum and minimum temperatures) were generated by downscaling outputs of HadCM3 (Hadley Centre Coupled Model, version 3) general circulation model to watershed level for A2a (medium-high) and B2a (medium-low) emission scenarios at representative stations (Addis Ababa, Ginchi and Bishoftu). These SDSM generated climatic data were used to develop current/baseline period (1971-2010) and future climate change scenarios: 2020s (2011-2040), 2050s (2041-2070) and 2080s (2071-2099). The projected future rainfall and mean monthly potential evapotranspiration at these stations were weighted and fed to HBV hydrological model (Hydrologiska Byråns Vattenbalansavdelning model) for future stream flow simulation. These simulated future daily flow time series were processed to monthly, seasonal and annual time scales and the values were compared with that of base period for impact assessment. The simulation result revealed the possibility for significant mean flow reductions in the future during Summer or “Kiremt” (main rainy season) and apparent increase during “Belg” or winter (dry season). Autumn flow volume showed decreasing trend (2020s), but demonstrated increasing trend at 2050s and 2080s. A mean annual flow reduction (ranging from 13.0 to 29.4%) is also expected in the future for the three studied benchmark periods under both emission scenarios. Generally, the result signals that the water resources of upper Awash River basin will be expected to be severely affected by the changing climate. Therefore, different adaptation options should be carried out in order to reduce the likely impact and ensure water security in the sub-basin.
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Accurate gridded precipitation data with high spatial and temporal scales are required for diverse studies such as climatology, meteorology, and hydrology. Currently, one of the sources of global precipitation estimation is the satellite-based precipitation estimate products. Nonetheless, their spatial resolution is often too coarse for usage in local region and basin scales or for parameterizing of meteorological and hydrological models at regional scales. In the present paper, a reconstruction method of satellite-based monthly precipitation was developed to attain improved pixel-based precipitation data with high spatial resolution on Golestan province in Northern Iran. In this endeavor, we considered the spatially heterogeneous relationships between tropical rainfall measuring mission (TRMM) precipitation and environmental variables utilizing the moving-window regression methods, the geographically weighted regression (GWR) and the mixed geographically weighted regression (MGWR) models. By in situ observations from rain gauges in the study area, the calibration and validation were performed, and the following conclusions were derived: (1) the proposed procedure had the ability to enhance both the spatial resolution and accuracy of satellite-based precipitation estimates; (2) the monthly reconstructed precipitation using the GWR model (CC=0.69, bias=0.75) and using the MGWR model (CC=0.72, bias=0.64) outperformed the TRMM-3B43V7 data (CC=0.58, bias=0.84) against ground observations; (3) this research offered a potential solution for producing gridded precipitation estimates at high spatial resolution. remote sensing
In this paper, a comparison and evaluation of three resampling methods for gridded DEM is implemented. The evaluation was based on the results of bilinear resampling, bi-cubic and Kriging resampling methods for an experiment using both degraded and sampled datasets at 20 m and 60 m spatial resolutions. The evaluation of the algorithms was accomplished comprehensively with visual and quantitative assessments. The visual assessment process was based on direct comparison of the same topographic features in different downscaled images, scatterplots and profiles. The quantitative assessment was based on the most commonly used parameters for DEM accuracy assessment such as root mean square errors (RMSEs), linear regression parameters m and b, and correlation coefficient R. Both visual and quantitative assessment revealed greater accuracy of the Kriging over the other two conventional methods.
This paper presents analysis carried out with using data provided by the Polish system of air pollutant emissions management – the National Emission Database (NED; data from 2011), established by the National Centre for Emissions Management at the Institute of Environmental Protection – National Research Institute. The NED database was established primarily for purposes of country-level air pollutant emission management also financial matters in environmental management (environmntal taxes). The first analysis: [21] also the second [22] have shown that the data collected in the NED database can be treated as an effective, supporting device in national air pollutant emission inventory for purposes of fulfilling international obligations (i.e. UN ECE LRTAP Convention [17]). In this paper are shown selected problems with emission downscaling and disaggregation for purposes of reporting with using data on emission of nitric oxides (NOX) and sulphuric oxides (SOX) from stationary combustion sources derived from the NED database.
PL
W niniejszej pracy przedstawiono wyniki analizy danych o rocznej emisji (dane za rok 2011) tlenków azotu (NOX) oraz siarki (SOX) zgłoszonych przez operatorów stacjonarnych instalacji spalania paliw, zlokalizowanych w województwie śląskim, w ramach sprawozdawczości krajowej prowadzonej przez Instytut Ochrony Środowiska – Państwowy Instytut Badawczy, w Krajowym Ośrodku Bilansowania i Zarządzania Emisjami. Przedstawiona analiza potwierdza użyteczność krajowego systemu zarządzania emisjami w aspekcie prowadzenia analiz związanych z dysagregacją oszacowań krajowej emisji zanieczyszczeń do powietrza.
Modele hydrologiczne opad-odpływ czy rolnicze opad-plon wymagają na wejściu określony zbiór danych meteorologicznych. Problem braku takich danych bądź ich niekompletność mogą zostać rozwiązane przez uzyskanie danych syntetycznych. Jest to konieczne w badaniach nad wpływem zmian klimatu, gdzie do badań wykorzystuje się dane wygenerowane za pomocą modeli symulujących potencjalne wartości wybranych zmiennych meteorologicznych. W pracy przedstawiono proces przygotowania syntetycznych danych do modelu opad-odpływ dla aktualnych warunków klimatycznych oraz spełniających założenia scenariuszy zmiany klimatu. Przeprowadzono weryfikację uzyskanych danych generowanych. Dane zostały wykorzystane do przeprowadzenie oceny wpływ zmian klimatycznych na 2080 rok według scenariusza emisyjnego A1B oraz modelu cyrkulacyjnego HadCM3.
EN
Hydrological rainfall-runoff models and agricultural rainfall-yield need at input a specific set of meteorological data. The problem of the absence of such data or their incompleteness can be solved by synthetic data. This is necessary in studies on the effects of climate change, where the research uses data from weather generator that simulate the possible values of selected meteorological variables. The paper presents the process of preparing synthetic data for rainfall-runoff model for current climatic conditions and satisfying the assumptions of climate change scenarios. A verification of the generated data was also presented. The obtain data were used to assess the impact of climate change on the year 2080 according to the emission scenario A1B and circulation model HadCM3.
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