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: 2.32). 03/2007; 201(3-4):301-311. DOI: 10.1016/j.ecolmodel.2006.09.028


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.

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    • "). A weather generator developed by [36] was used to fill the gaps due to missing data. Daily river discharge values for Kajang streamflow station were obtained from the Department of Irrigation and Drainage (DID) Malaysia. "

    02/2016; 8(2):132-136. DOI:10.7763/IJET.2016.V8.872
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    • "The weather variables used in this study are daily precipitation, minimum, and maximum air temperature for the period 1976 to 2010. A weather generator developed by (Schuol and Abbaspour, 2007 "
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    ABSTRACT: Hydrologic models are particularly useful tools in enabling the modeler to investigate many practical and significant issues that arise during planning, design, operation, and management of water resources systems. Distributedmodels should pass through a careful calibration procedure before they are utilized as the process of decision-making aids in the planning and administration of water resources. Although manual approaches are still repeatedly used for calibration, they are tedious, time-consuming and have the need of experienced personnel. This paper describes a semi-automatic approach for calibrating long term daily streamflow periods estimated by the Soil and Water Assessment Tool (SWAT) hydrological model. Optimization of three different sets of spatial input parameters were tested using SUFI-2 algorithms by firstly focusing on the sets of the groundwater inputs parameter. The second set is for the soil input parameters and the final set consists of 21 SWAT input parameters that reflect sensitivity on the streamflow simulation. For Langat river basin, the, and CN2.mgt were found to be most sensitive input parameters. SOL_AWC.sol was established to be the most sensitive to soil input parameter and followed by SOL_BD.sol and SOL_K.sol. On the final sets, it was shown that the three input parameters of OV_N.hru, SL_SUBBSN.hru, and HRU_SLP.hru were included as sensitive parameters in addition to the previous parameters. The next step should be conducting a long-term continuous hydrological modeling into SWAT 2012 model with all the selected sensitive SWAT input parameters in order to finalize the objective functions for the watershed.
    Journal of Engineering and Applied Sciences 08/2015; 10(15):6628-6633. · 0.38 Impact Factor
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    • "For the climate data, we used the monthly gridded climate data (potential evapotranspiration and precipitation) from the CRU TS 3.1 dataset (Harris et al., 2013). The CRU data have already been used in many studies on climate and hydrological modeling in the region (Paturel et al., 2010, 1995; Schuol and Abbaspour, 2007). In addition to the physical characteristics of the watersheds, two main climate characteristics (Table 1) are considered: the annual rainfall and the annual potential evapotranspiration. "
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    ABSTRACT: Hydrological observation networks in the West African region are not denseand reliable. Furthermore, the few available discharge data often present significant gaps.The Volta basin, the second largest transboundary basin in the region, is a typical exampleof a basin with inadequate hydrological In this study, a prediction approach to determine monthly discharge inungauged watersheds is developed. The approach is based on the calibration of two con-ceptual models for gauged watersheds and an estimation of models’ parameters from thephysical and climatic characteristics of the watersheds. The models’ parameters were deter-mined for each ungauged watershed through two different methods: the multiple linearregressions and the kriging method. The two methods were first validated on five gaugedwatersheds and then applied to the three ungauged watersheds. The application of the two hydrological models onthe eight watersheds helped to produce relevant monthly runoff and to establish the annualhydrological balances from 1970 to 2000 for both gauged and ungauged watersheds. Thedeveloped method in this study could therefore help estimate runoff time series, which areof crucial importance when it comes to design hydraulic structures such as small reservoirs.
    Journal of Hydrology: Regional Studies 08/2015; 4(B):386-397. DOI:10.1016/j.ejrh.2015.07.007
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