Thornwaite Water Balance Model: An Analysis Of Two Rainfall-Runoff Models
Two Rainfall-Runoff Models were earlier identified for application and for the generation of a more reliable discharge data. These are the Thornwaite Water Balance Model (WBM) and the IHACRES. The input requirement of both models differ. For the WBM, generation of runoff requires seven input parameters. These are the Runoff Factor (RF), Direct Runoff factor (DRF), Soil Moisture Storage Capacity (SMSC), Latitude of location, Rain Temperature Threshold, Snow Temperature Threshold and Maximum Snow Melt Rate of Snow. The IHACRES requires just the rainfall, temperature and runoff data. The models were first calibrated with known data and then more runoff data was generated using the calibrated parameters and measured values of rainfall and temperature.
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Having established the good and bad years, the rainfall and runoff data of the good years were used to calibrate the IHACRES which was subsequently used to generate a better runoff data from measured rainfall values. Data input for IHACRES were rainfall, runoff and temperature. The PC-IHACRES version 1.03 was used in this work. And Table 5.30 gives the calibration parameters for each study basin.
Based on the parameters in Table 5.30, a Matlab code was written to simulate discharge data from measured rainfall and temperature data. The resultant data are shown in Tables 5.31 to 5.35 and the graphs are in Figures 5.26 to 5.30. The Figures show measured rainfall, measured flow and the simulated flows. The instrumental variable best suited for Asa and Gongola Rivers is the exponential store and instantaneous store in parallel. This means that both rivers has the tendency for some baseflow at the control points. The other rivers are best suited for a single exponential store. This means that there is very little evidence of baseflow at the control points. The structure and parameters of the linear module of the IHACRES are determined by the store configurations. One store represented ephemeral rivers without baseflow and two store are for rivers with both baseflow and
Having established the good and bad years, the rainfall and runoff data of the good years were used to calibrate the IHACRES which was subsequently used to generate a better runoff data from measured rainfall values. Data input for IHACRES were rainfall, runoff and temperature. The PC-IHACRES version 1.03 was used in this work. And Table 5.30 gives the calibration parameters for each study basin.
Based on the parameters in Table 5.30, a Matlab code was written to simulate discharge data from measured rainfall and temperature data. The resultant data are shown in Tables 5.31 to 5.35 and the graphs are in Figures 5.26 to 5.30. The Figures show measured rainfall, measured flow and the simulated flows. The instrumental variable best suited for Asa and Gongola Rivers is the exponential store and instantaneous store in parallel. This means that both rivers has the tendency for some baseflow at the control points. The other rivers are best suited for a single exponential store. This means that there is very little evidence of baseflow at the control points. The structure and parameters of the linear module of the IHACRES are determined by the store configurations. One store represented ephemeral rivers without baseflow and two store are for rivers with both baseflow and