Article

Using monthly weather statistics to generate daily data in a SWAT model application to West Africa

Swiss Federal Institute of Aquatic Science and Technology (Eawag), Überlandstrasse 133, P.O. Box 611, 8600 Dübendorf, Switzerland
Ecological Modelling (Impact Factor: 2.33). 03/2007; 201(3-4):301-311. DOI: 10.1016/j.ecolmodel.2006.09.028

ABSTRACT Most hydrologic models require daily weather data to run. While this information may be abundant in some parts of the world, in most parts such data is not available on daily basis. Distributed hydrologic models are particularly adversely affected by the lack of daily data or the existence of very inaccurate data as they impart large uncertainties to the model prediction. In this study we developed a daily weather generator algorithm (dGen) that uses the currently available 0.5° monthly weather statistics from the Climatic Research Unit (CRU). We tested dGen in two ways. First, we made a direct comparison of the measured and generated precipitation and maximum–minimum temperatures by looking at some long-term statistics in a few stations in West Africa. Second, we ran the model “Soil and Water Assessment Tool” (SWAT) with dGen-generated and measured daily weather data to simulate 25 years of annual and monthly river discharges at some gauging stations. The simulated river discharges were then compared with the measured ones. It was seen that using the dGen-simulated daily weather data resulted in a much better match with the measured discharge data than the measured daily weather data in combination with the SWAT internal weather generator WXGEN. WXGEN is used in SWAT to fill missing data using monthly statistics, which must be calculated from the existing daily data. For annual and monthly hydrological simulations, dGen-generated daily rainfall and temperature data appears to have a high degree of reliability.

19 Followers
 · 
1,345 Views
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Unmitigated anthropogenic climate change is set to exacerbate current stresses on water resources management and creates the need to develop strategies to face climate change impacts on water resources, especially in the long term. Insufficient information on possible impacts on water availability limits the organization and promotion of efforts to adapt and improve the resilience and efficiency of water systems. To document the potential impacts of climate change in the region of Mendoza, Argentina, we perform a hydrological modeling of the Mendoza River watershed using a SWAT model and project climate change scenarios to observe hydrological changes. The results show the impact of higher temperature on glaciers as river flow increases due to glacier melting; at the same time, runoff decreases as precipitation is reduced. Furthermore, the runoff timing is shifted and an earlier melting becomes more important in more pronounced climate change scenarios. Scenarios show a reduction in water availability that ranges between 1 and 10%. An additional scenario under stronger climate change conditions without glaciers data shows a reduction of the river flow by up to 11.8%. This scenario would correspond to a future situation in which glaciers have completely melted. These situations would imply a reduction in the water availability and the possibility of future unsatisfied water uses, in particular for irrigation, which received most of the available water in Mendoza, on which agricultural activities and regional economy depends.
    Environmental Science & Policy 11/2014; 43. DOI:10.1016/j.envsci.2014.01.002 · 3.51 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Climatic balance of the Earth, global warming and climate change are the most important phenomena in this century. One of the valid empirical methods to establish a quantitative measure of the relationship of temperature and rainfall is index of aridity developed by De Martonne. In this research, three future periods were considered and De Martonne's method is chosen to categorise climate. The spatial effect of climate change on climatic classification for the periods is investigated. Urmia Lake basin is taken as a case study using downscaled output of HadCM3 model, created by Climate Research Unit (CRU) Institute. Considering this matter that AOGCMs have a high uncertainty, a new methodology and spatial downscaling are utilised. As the final results show, the climate of basin in future has a high sensitivity to climate change. Grouping the scenarios indicates a conversion in main climate of the basin from semi-arid climate to arid one.
    01/2013; 3(2):128 - 140. DOI:10.1504/IJHST.2013.057625
  • Source
    Water Resources Management 10/2012; DOI:10.1007/s11269-012-0099-9 · 2.46 Impact Factor

Preview

Download
100 Downloads
Available from