Nutrient Transport Modelling in the Daugava River Basin - DiVA Portal

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a) Streamflow, calibration periodb) Streamflow, validation periodReportedcm/year40353025201510505000019931994199519961997c) Nitrogen load, calibration period19981999cm/year35302520151050600001980198119821983198419851986198719881989d) Nitrogen load, validation periodModelled4000050000ton/year30000200001000020000199319941995199619971998e) Phosphorus load, calibration period1999ton/year40000300002000010000200001980198119821983198419851986198719881989f) Phosphorus load, validation period15001500ton/year1000500ton/year10005000019931994199519961997199819991980198119821983198419851986198719881989Figure 7. Reported and modelled values of yearly means of streamflow,nitrogen loads and phosphorus loads from the Daugava River for the calibration period(19932000) and the validation period (19801990).Table 2 shows a statistical summary of the comparison of observed and predictedvalues. Generally, the prediction of yearly values is a lot better than the prediction ofmonthly values. Regressions lines were made between reported and modelled values.The R 2 value of the regression of modelled and reported yearly nitrogen loads is 0.78and the corresponding slope of regression is 1.17. The R 2 value for yearly phosphorusloads is 0.5, but since the regression slope is only 0.14 the ability of the model to predictphosphorus loads must be considered to be very low. The regression slope for monthlymeans is generally much lower than for yearly means. This is due to the fact that themodel underestimates peak flows. For yearly values the impact of peak flows is not sosignificant, which is why the regression slope for yearly means is higher than formonthly means. Plots of the regressions are found in Appendix F.16
Table 2. Comparison of reported and modelled valuesCalibration period,19931999Validation period,19801989MonthlymeansYearlymeansMonthlymeansYearlymeansStream flow:Modelled mean/reported meanfor entire simulation period1 1 0.99 0.99Mean absolute percentage error 45 18 48 13Slope of regression betweenreported and modelled values0.48 1.21 0.7 1.58R 2 of regression betweenreported and modelled values0.36 0.67 0.53 0.82Nitrogen load:Modelled mean/reported meanfor entire simulation period1 1 0.67 0.67Mean absolute percentage error 59 18 44 35Slope of regression betweenreported and modelled values0.47 1.17 0.41 0.57R 2 of regression betweenreported and modelled values0.32 0.78 0.44 0.75Phosphorus load:Modelled mean/reported meanfor entire simulation period0.16 0.16 0.2 0.2Mean absolute percentage error 80 84 83 81Slope of regression betweenreported and modelled values0.016 0.14 0.18 0.24R 2 of regression betweenreported and modelled values0.006 0.5 0.18 0.47The contribution to the modelled streamflow is divided by flow from surface runoff,groundwater box 1 and groundwater box 2 respectively. In figure 8 the distribution ofthese three flows over two years is shown. Flow from groundwater box 1 is the maincontributor to streamflow. The largest flows occur during spring. Surface runoff onlyoccurs during periods of rainfall and/or snowmelt, see Appendix B. The contributionfrom groundwater box 2 is generally lower than from groundwater box 1. On the otherhand, the flow from box 2 is more constant over the year, and during fall and winter thecontribution from box 2 at times exceeds the contribution from box 1..7.6cm/day.5.4.3.2.1.Surface runoffFlow from box1Flow from box 2Jan95Jul95Jan96Jul96Figure 8. The predicted daily contribution to streamflow from surfacerunoff and groundwater box 1 and 2 and the total streamflow, 19951996.17
Page 1 and 2: UPTEC W05 009Examensarbete 20 pFebr
Page 3 and 4: Nyckelord: avrinning, näringsämne
Page 6 and 7: APPENDIX C. DETERMINATION OF POTENT
Page 8 and 9: simulation system CatchmentSim. The
Page 10 and 11: Figure 1. The hydrological part of
Page 12 and 13: TemperaturePrecipitation20.00120deg
Page 14 and 15: 3.2 MODEL DESCRIPTION3.2.1 An overv
Page 16 and 17: Groundwater discharge to the river
Page 18 and 19: Groundwater nutrient loadsThe groun
Page 20 and 21: There is therefore no guarantee tha
Page 24 and 25: 4.2 IMPACT OF THE CURVE NUMBER ON N
Page 26 and 27: the chosen value is a very rough ap
Page 28 and 29: all cultivated land will have winte
Page 30 and 31: HELCOM, 2004a. 30 years of protecti
Page 32 and 33: Appendix A. Input data and paramete
Page 34 and 35: Description of parameter/input Name
Page 36 and 37: Description of parameter/input Name
Page 38 and 39: moisture.Figure B1. Selection of cu
Page 40 and 41: wherea t = rainfall erosivity coeff
Page 42 and 43: Appendix F. Regression lines of rep

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