Nutrient Transport Modelling in the Daugava River Basin - DiVA Portal

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the chosen value is a very rough approximation. The value of rainfall erosivity islikewise an approximation and the sediment delivery ratio is an extrapolation sincevalues were not given for watersheds as large as the Daugava basin. All together, thepredicted erosion may be considerably erroneous. Never the less, a more probableexplanation for the underestimation of phosphorus loads is that the reported values ofpoint source phosphorus loads in the basin are a lot less than the actual value and thatphosphorus from septic systems, which are not included in the modelling, contributessubstantially to the total load. According to HELCOM (2004b), about 70 % of diffusephosphorus loads to the Gulf of Riga origin from other sources than agriculture andforestry, for instance from septic systems. Looking at Daugava the figure is probablysomething similar since water from the Daugava is the main contributor to the Gulf ofRiga. Gren et al. (1997) state that the lack of sewage treatment in the Gulf of Rigaregion contributes to very large input of phosphorus to the sea. Since agriculture andforestry are the main sources of phosphorus according to the model and since septicsystems are not included it is therefore not surprising that the model fails to predictphosphorus loads.An indication of point source phosphorus pollution is that concentrations are higher atlower flows and lower at higher flows. In figure 11 the observed phosphorusconcentration and streamflow are displayed.Stream flowPhosphorus concentrationStreamflow (cm/month)1210864200.140.120.10.080.060.040.020Phosphorus concentration (mg/l)Apr80Apr81Apr82Apr83Apr84Apr85Apr86Apr87Apr88Apr89Apr90Apr91Apr92Apr93Apr94Apr95Apr96Apr97Apr98Apr9919802000.Figure 11. Reported streamflow and phosphorus concentration,It seems like the peaks in phosphorus concentration occur at low flows which could bean indication of point sources of phosphorus, but in order to say something definitelyone would need to conduct a statistical analysis of the two time series.Of the parameters used in the sensitivity analysis the nitrogen concentration ingroundwater box 1 is the one that affects average loads the most. This is not surprisingsince streamflow mainly consists of water from groundwater box 1. It is thereforeimportant to calibrate this parameter carefully. The impact of the recession coefficientsand the coefficient determining flow between the two groundwater boxes appears to bevery small, looking at the result of the sensitivity analysis. The reason for this is thesmall difference between the nitrogen concentration in the two boxes (1 and 1.3 mg/l,respectively). With a more pronounced difference in concentration between the boxesthe impact on the nitrogen load of the recession coefficients and the coefficientdetermining flow between the two boxes would have been greater.20
The choice of curve numbers that determine surface runoff has a great impact on thenutrient source apportionment. Since no data were available on site specific nutrientcontributions from different land uses, it was not possible to calibrate the curve numbersin order to fit observed apportionments. The values suggested in the manual for theoriginal GWLF (Dai et al., 2001) are developed for North American conditions and it isdifficult to say much about their relevance in this area. It is important to be consistentwhen choosing curve numbers in the rest of the Baltic Sea basin and to bear in mind thatthe source apportionment from different land uses contains substantial uncertainties.When looking at the source apportionment it should be remembered that only surfacerunoff and erosion is included; nutrient contributions from the groundwater flow is notconsidered. Due to nitrogen leakage a substantial part of nitrogen in agricultural soilswill be transported down to the groundwater and thus result in increased nitrogenconcentrations. The total nitrogen load is thus largely affected by nitrogen from thegroundwater. Thus, the actual contribution from agricultural land is greater than what issuggested by the source apportionment analysis.In a drainage basin as large as Daugava the amount of nitrogen that is lost on the way tothe sea is substantial, but nitrogen retention is not included in the model. The retentionaffects the model calibration in such a way that the calibrated groundwater nitrogenconcentrations are lower than they would have been, had retention not existed. Thegroundwater nitrogen concentration in the model is thus probably lower than in reality.The inability of the model to estimate nitrogen retention might affect the usefulness ofthe model for scenario analysis. For example, the construction of wetlands may helpdecrease nitrogen loads from water passing through the wetland since nitrogen is lost bydenitrification. In this way, wetlands can help decrease nitrogen loads from for instanceagricultural lands. But in the GWLF the nitrogen load from agriculture will not beaffected by the increase in wetland areas. Also, since retention is not included in themodel, the impact of land anywhere in the basin will have the same impact, a situationthat is unlikely to occur in reality.The quality of data is of major importance for the result of any modelling. In theDaugava basin it is difficult to find reliable data. The reported streamflow and nutrientloads can also be questioned. Little information is given regarding what reported dataare observed and what are calculated. In order for modelling results of nutrient flowsfrom the entire Baltic Sea basin to be trustworthy more reliable data are thereforeneeded. It is of utmost importance that such data are easily accessed and homogenous inorder to support sustainable water management in the Baltic Sea Region (Hannerz et al.2005).In order to use the GWLF for longterm prediction of nutrient loads, modifications ofthe model are suggested. For instance, nutrient concentrations should be variable withtime. For simulations over short time periods it is probable that the groundwaterconcentration remains more or less the same. However, considering long time spans orperiods with sudden changes in management, like for instance the collapse of the SovietUnion and its agricultural policy, it is not likely that the groundwater concentration willbe constant. As stated above, it must be remembered that the model is static in thissense. Another change that could be made is to divide the existing land cover categoriesinto several subcategories depending on more sitespecific land use. As an example,presently it would be impossible to handle a future scenario where a certain fraction of21
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 22 and 23: a) Streamflow, calibration periodb)
Page 24 and 25: 4.2 IMPACT OF THE CURVE NUMBER ON N
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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