Commentary - GALF bRgalf-dresden.de/galf/wp-content/uploads/2013/06/... · outside Europe,...

Commentary

Micha Gebel

Stefan Halbfaß

Stephan Bürger

Mario Uhlig

www.galf-dresden.de

www.viewer.stoffbilanz.de

www.stoffbilanz.de

30.01.2018

http://www.stoffbilanz.de/



Table of Contents

1 Introduction...........................................................................................................................5

2 The philosophy of the STOFFBILANZ model.......................................................................6

2.1 Principles...........................................................................................................................6

3 Water balance.......................................................................................................................8

3.1 Surface runoff....................................................................................................................8

3.2 Percolation rates..............................................................................................................10

3.2.1 Arable land, grassland, forest.......................................................................................10

3.2.2 settlement, viticulture, fruit-growing, undefined land use.............................................11

3.3 Drainage rates.................................................................................................................11

3.4 Groundwater runoff and interflow....................................................................................11

4 Soil erosion and sediment input.........................................................................................13

4.1 Soil erosion from rainfall and runoff.................................................................................13

4.2 Sediment input.................................................................................................................14

5 P-balance............................................................................................................................17

5.1 Diffuse P-input.................................................................................................................17

5.1.1 Particle-bound phosporus.............................................................................................17

5.1.2 Dissolved P-inputs........................................................................................................18

5.1.3 Further P-inputs............................................................................................................18

5.1.3.1 Diffuse sources in urban areas / settlement..............................................................18

5.1.3.2 Diffuse sources for waters and undefined land use types.........................................20

5.2 Point-related P-inputs......................................................................................................21

6 N-balance............................................................................................................................22

6.1 Diffuse N-input.................................................................................................................22

6.1.1 N-balances on arable land, grassland and viticulture, fruit-growing............................22

6.1.1.1 N-import on arable land.............................................................................................23

6.1.1.2 N-mobilisation on cropland........................................................................................23

6.1.1.3 N-immobilisation on arable land................................................................................25

6.1.1.4 N-export on arable land.............................................................................................26

6.1.1.5 Interim balance..........................................................................................................26

6.1.1.6 Interim balance on grassland....................................................................................26

6.1.1.7 Interim balance on viticulture and fruit-growing.........................................................26

6.1.2 N-balance on forest land..............................................................................................26

6.1.2.1 N net-uptake rate.......................................................................................................26

6.1.2.2 N-Immobilisation on forest land.................................................................................28

6.1.3 Atmospheric N-deposition............................................................................................28

6.1.4 Denitrification in topsoil.................................................................................................28

6.1.4.1 Arable land, grassland, fruit-growing, viticulture, settlement, undefined land use....28

6.1.4.2 Forest land.................................................................................................................29

6.1.5 Diffuse N-leaching from the rooted soil zone...............................................................30

6.1.6 N-input in surface waters from sealed areas................................................................30

6.1.7 Separation of the N-leaching to the runoff components...............................................32

6.1.8 Residence time and denitrification in the upper aquifer...............................................32

6.1.8.1 Solid rock aquifers and loose over solid rock aquifers..............................................33

6.1.8.2 Loose rock aquifers...................................................................................................34

6.1.9 Dissolved N-input from diffuse sources........................................................................35

6.1.10 Particle-bound N-input................................................................................................35

6.1.11 Total diffuse N-input....................................................................................................35

6.2 Point-related N-inputs......................................................................................................35

7 Long lasting nutrient retention in river basins.....................................................................36

7.1 Retention of phosphorus..................................................................................................36

7.1.1 Retention of phosphorus in rivers.................................................................................36

7.1.2 Retention of phosphorus in lakes and reservoirs.........................................................39

7.1.3 Calculation within the river net......................................................................................39

7.2 Retention of nitrogen.......................................................................................................39

7.2.1 Retention of nitrogen in rivers.......................................................................................39

7.2.2 Retention of nitrogen in lakes and reservoirs...............................................................40

7.2.3 Calculation within the river net......................................................................................40

8 Decision support / scenarios..............................................................................................41

9 References..........................................................................................................................42

10 Appendix...........................................................................................................................52

List of Figures

Figure 1: Sources and pathways of nutrient inputs into waters in river basins.......................5

Figure 2: The modular construction of the web based STOFFBILANZ model........................7

Figure 3: Graphical user interface of the Web based STOFFBILANZ Viewer........................8

Figure 4: Methodological approach to compute sediment input and hotspot areas.............15

Figure 5: The derivation of likeliness of connectivity in principle...........................................16

Figure 6: Derivation of the N-balance on cropland................................................................22

Figure 7: Derivation of the N-mobilisation from the organic soil matrix.................................24

Figure 8: Derivation of groundwater residence time and denitrification................................34

List of Tables

Table 1: Derivation of CN-values (medium soil moisture, 5% slope)......................................9

Table 2: Calculation of climate controlled capillary rise........................................................10

Table 3: Determination of the runoff quotient........................................................................12

Table 4: Influence of exposure and slope on the intensity of evaporation on arable land....12

Table 5: P-concentrations [mg/l] in the runoff components...................................................18

Table 6: Definition of the coefficient fs to characterize the cultivation practice.....................25

Table 7: Derivation of the weathering class on forest land...................................................27

Table 8: Derivation of the yield type on forest land...............................................................27

Table 9: Derivation of the N net-uptake on forest land..........................................................28

Table 10: Derivation of N-immobisation rate on forest land..................................................28

Table 11: Conditions of denitrification derived from the soil type..........................................29

Table 12: Derivation of the coefficient fde.............................................................................29

Table 13: Derivation of denitrification in the upper aquifer, e.g. for Saxony.........................33

Table 14: Estimation of ground water residence time (solid rock, e.g. Saxony)...................34

Table 15: Generating of parameters acc. to the LAWA-river typology e.g. for Saxony........38

Table 16: Scenario options in the STOFFBILANZ model (examples)..................................41

Table 17: Input parameters in the STOFFBILANZ model.....................................................52

Table 18: Input data of validation..........................................................................................53

Table 19: Types of fruit and prefixes.....................................................................................53

Table 20: Soil textures in the STOFFBILANZ model (comp. Ad-hoc-AG Boden, 2005).......54

Table 21: Soil types in the STOFFBILANZ model (compare Ad-hoc-AG Boden, 2005).......55

Table 22: Derivation of percolation rate SW (according to Ad-hoc AG Boden 2003)...........56

Chapter 1 : Introduction

1 Introduction

Pollution of ground and surface water from point and non-point sources via the diffe-rent input pathways are still evident in the intensively used regions in Midlle europe. Itshould be minimized in order to get a good ecological state according to the WaterFramework Directive (EU 2000).

Diffuse inputs of nitrogen (N) and phosphorus (P) in waters are realized via the diffe-rent runoff components (1). N and P are certainly different in respect to their bindingsand physical / chemical character. Dislocation of P is often determined by a particle-bound transport, which depends on soil erosion and surface runoff.

Figure 1: Sources and pathways of nutrient inputs into waters in river basins

Nitrogen is chiefly washed out as dissolved nitrate via interflow and groundwaterflow. Processes of turnover (mobilization, immobilization, denitrificaton) as well as re-sidence times of water fluxes should be taken into consideration whenever possible.

Modelling tools, like the model STOFFBILANZ, are used to generate these inputs ofsediment and nutrients in river catchments according to their origin and quantity.

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Chapter 1 : Introduction

Therfore we have to consider diffuse and point source inputs into waters as well asprocesses of retention during the residence time in groundwater and surface water.

According to the Water Framework Directive water management programs are chieflyestablished on a regional scale. Thus we have to use emission-based modellingtools, which are able to identify diffuse and point source inputs even in larger riverbasins, considering main sources, pathways and sinks in accordance to land use andlocation.

The following methods and algorithms only refer to a modelling in one year timesteps. Daily based modelling routines are also available in the STOFFBILANZapproach for evapotranspiration, and deep percolation (Crop EvapotranspirationETcadj, see Allen et al. 1998), for direct runoff (Curve Number approach, see NRCS2004, Hawkins et al. 2009), and for soil loss by stormwater runoff (USLE-M, seeKinnell 2001, Yu & Rosewell 1996), sediment input, as well as particulate P input, butnot described in detail in this commentary. All these daily based modelling was doneoutside Europe, especially in China and South-Africa (Gebel et al. 2016, 2017,Meissner et al. 2016).

2 The philosophy of the STOFFBILANZ model

2.1 Principles

The STOFFBILANZ model is a Web based tool to quantify nitrogen, phosphorus andsediment emissions in surface water. The main sources and pathways are identifiedand calculated for land use types and user specific area units. The results show thenutrient and sediment inputs according to the different areas as annual balance. Themodel mediates between a large and small scale approach and is therefore especial-ly suitable for use in the field of regional (mesoscale) river basin management. Herethe method is especially useful as a component for the realization of the EU waterframework directive.

Using scientifically validated methods in accordance to the state of the art the modelallows to generate flow and mass balances for different states of landscape and landuse (current state, target state, scenarios):

• Analysis of origin (sources)

• Analysis of pathways

• Identification of risk areas and source areas

• Aggregation at different spatial levels

To quantify diffuse nutrient and sediment loadings it is first necessary to obtain andwork up parameters of landscape, land use and farming, which are listed in 17,appendix). To compare the calculated loadings with real measured data we need in-formation to point source inputs and water quality measurements (compare 18,appendix).

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Chapter 2 : The philosophy of the STOFFBILANZ model

In order to link user friendliness, technical aspects and requirements to the river ba-sin management, GALF bR has developed the Web based model STOFFBILANZi.The Web service consists of the model itself and various tools for data import and ex-port, data analysis and visualisation. The storage of spatial and technical data isdone in a PostgreSQL / POSTGIS database. Modern web technologies enable thedevelopment of a desktop-like user interface. An important element is theimplementation of the UMN-Mapserver, which supports the dynamic visualization ofmodel data and results. Users are thus able to monitor and to evaluate theparameters and results in a cartographic mode, but also to make their own mode-lings. Statistic tools are supporting the evaluation of the model data and the compari-son of scenarios (2 and 3).

A demo version with limited functions is disposable at viewer.stoffbilanz.de (see alsowww.stoffbilanz.de).

Figure 2: The modular construction of the web based STOFFBILANZ model

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Chapter 2 : The philosophy of the STOFFBILANZ model

Figure 3: Graphical user interface of the Web based STOFFBILANZ Viewer

3 Water balance

The determination of total runoff R is realized as the sum of the runoff componentssurface runoff RO, rain discharge (runoff from sealed areas) RS, drainage rate RD,interflow RI and groundwater runoff RG:

R=RO+RD+RI+RG+RS [mm yr-1]

The determination of surface runoff and rain discharge respectively is done accordingto the modified Curve Number Method (adapted from US Soil Conservation Service1972, Halbfaß 2004). Surface runoff is only calculated for areas with a hydraulicconnection to the river net.

Interflow and groundwater runoff are calculated on the basis of percolation rates ta-king into account the runoff quotient and the sun exposure (Ad-hoc-AG Boden 2003,modified according to Röder 1997, Wessolek 1997, Wessolek et al. 2008).

Calculation of drainage rates on drained areas is similar to the determination of per-colation (Ad hoc-AG Boden 2003), whereby capillary rise is not included.

3.1 Surface runoff

The determination of the surface runoff RO and the rain discharge RV respectively isdone according to the modified Curve Number Method (adapted from US Soil Con-servation Service (SCS), 1972), which has been developed in the USA. Based onflood data and measurements of percolation in small river basins characteristics ofrunoff have been investigated considering land use, soil tillage, soil texture, soil moi-sture and intensity of rainfall. The resulting Curve number (CN) gives a measure forthe maximum storage capacity taking into account land use and preliminary rainfall

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Chapter 3 : Water balance

(indicated by three classes of soil moisture). The influence of soil characteristics onthe capacity of percolation is determined in the SCS-method considering four hydro-logical soil classes, modified for the calculation in the STOFFBILANZ model as seenin 1 (adapted from US Soil Conservation Service 1972, Halbfaß 2005).

The CN5-value will be corrected by the slope as follows:

CN slp=( (CN 5⋅e(0,00673⋅(100−CN 5 ))−CN 5)

3 )⋅(1−2⋅e(−13,86⋅slp))+CN 5

where slp is the slope [m · m-1].

The storage capacity S [mm] and the initial loss IA [mm] are determined by the follo-wing equations:

S =(1000CN−10)⋅25,4

I A=0,03⋅S

Table 1: Derivation of CN-values (medium soil moisture, 5% slope)

main form of land use soil texture (compare 20, appendix)

ss us, ls, tu, lu, su sl, ll, tl lt, ut, Hn, Hh

CN5-value

arable land (conventional) 67 78 86 89

arable land (conservation tillage) 62 73 79 80

grassland 39 61 74 80

forest 36 60 73 79

fruit-growing 36 60 73 79

viticulture 64 73 79 82

settlement 61 for unsealed areas99 for sealed area

waters -

undefined land use 80

We are calculating the mean annual surface runoff as follows below considering themean annual number of rainy days dP and the mean daily sum of rainfall Pd for theserainy days:

RO ,RS=(Pd− I A)

2

(Pd− I A+S )⋅d P [mm yr-1]

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A calculation of the surface runoff in respect of the main land use types arable land,grassland, fruit-growing, viticulture, forest and undefined land use is always done ifthe area has a hydraulic connection. The surface runoff is however not calculated onareas with a missing connection. For settlement areas a calculation of the surface ru-noff from the unsealed part RO is done, as well as a calculation of the rain dischargeRS from the sealed part.

Surface runoff is not calculated for areas with a slope more less than 0,5°, watersurfaces and drained areas respectively (siehe 3.3).

3.2 Percolation rates

3.2.1 Arable land, grassland, forest

The determination of long-year percolation rates is based on the TUB-BGR-methodo-logy, (Ad-hoc-AG Boden 2003, Wessolek et al 2008) considering a land use-specificstatistical regression (22, appendix). Parameters of land use, soil and soil water areincluded in the regression as well as the plant available soil water in the effective rootzone WV. The necessary parameters are listed below:

– soil texture in order to derive the field capacity in the effective root zone nFKWeand the climate controlled capillary rise KAkli from April to September,

– land use type (arable land, grassland, coniferous forest, decidous forest),

– climate data: potential FAO-grass reference evapotranspiration ET0, precipitationin summer Psummer and winter Pwinter.

Following the TUB-BGR-procedure percolation rate from the rooted soil zone is deri-ved from the difference of mean annual precipitation Pyear and actual evapotranspira-tion Eta in dependence on ET0 and WV.

WV is determined by KA, nFKWe, Psummer, Pyear and RO (Ad-hoc-AG Boden 2003) asfollows:

WV =nFKWe+KA+P summer⋅(1− ROP year) [mm yr-1]

The capillary rise is calculated by the following equations in 2, considering differentland use types (Ad-hoc AG Boden 2003):

Table 2: Calculation of climate controlled capillary rise

Land use type Kakli [mm a-1]

Arable landgrasslandforest

KAkli = 1,05 · ET0summer – Psummer + 0,5 · nFKWe KAkli = 1,05 · ET0summer – Psummer + 0,5 · nFKWe KAkli = 1,05 · ET0summer – Psummer + 0,5 · nFKWe

mit ET0summer = 0,72 · ET0 + 48

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The capillary rise KA is derived from Kakli as follows:

(a) KA = 0 if KAkli = 0

(b) KA = KAkli if KAmax > KAkli

(c) KA = KAmax if KAmax ≤ KAkli

The maximum capillary rise KAmax is a function of mean daily capillary rise KR [mm/d]and the corresponding mean daily lengh of time of capillary rise ta [d] (according toAd-hoc-AG Boden 2003):

KAmax=KR⋅ta [mm yr-1]

In the STOFFBILANZ model we assume that KR mainly depends on soil texture andtype of crop and is only relevant on hydromorphic soil types. Otherwise we are ne-glecting the derivation of KR.

3.2.2 settlement, viticulture, fruit-growing, undefined land use

We are calculating the percolation rate for these land use types according to Lieb-scher & Keller (1979, modified by Wendland et al. 1993):

SW =0,86⋅P year−111,6⋅(P summer

Pwinter)−120⋅log (KA+nFKWe ) [mm yr-1]

3.3 Drainage rates

The portion of drained areas Fd for arable land and grassland can be derived (accor-ding to Behrendt et al. 1999) from the soil type (SS-##, S#: 50%, GG-##, G#, HN,HH, A#: 10%). It is also possible tu use alternative procedures with a higher resoluti-on (e.g. Hirt et al. 2005) or a more sensitive dataset, if available.

The derivation of drainage rates on drained areas is similar to the determination ofpercolation, whereby capillary rise is not included in generell:

RD=Ad⋅SW

100[mm yr-1]

On drained areas we have no calculation of RG, RO and RI.

3.4 Groundwater runoff and interflow

The percolation rate is separated into the interflow RI and groundwater runoff RG ac-cording to Röder (1997), using a runoff quotient fq in dependence on the site slopeand grade of hydromorphy (3):

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Table 3: Determination of the runoff quotient

grade of hydro-morphy

slope class [°]

≤1 >1-2 >2-5 >5-10 >10-15 >15-20 >20

mgwtd1

[m]soil types

compare Tab. A5

terrestrial 1,1 1,2 1,4 1,6 1,8 2 2,3 > 1,5

F#, O#, RN, RQ,RR, RZ, D#, B#,L#, T#, C#, Y#, PP-BB

semi hydromorphic 2 2 2 2 2,1 2,3 2,3 0,8–1,5 SS-##, GG-##, A#

hydromorphic 2,5 2,5 2,5 2,5 2,5 2,5 2,5 < 0,8 S#, G#, HN, HH

The factor of sun exposure fexp (modified from Wessolek, 1997) describes the influ-ence of exposure and slope on the intensity of evaporation on arable land. Conse-quently the runoff is higher on north, north-west and north-east exposed slopes andlower on south, south-west and south-east exposures. This factor is only used for thecalculation of the groundwater runoff and the interflow from arable land (4).

Table 4: Influence of exposure and slope on the intensity of evaporation on arable land

exposure slope [°]

≤1 >1-2 >2-5 >5-10 >10-15 >15

north 1 1,03 1,06 1,13 1,2 1,32

north-east 1 1,02 1,05 1,09 1,18 1,23

north-west 1 1,02 1,05 1,09 1,18 1,23

south 1 0,97 0,94 0,89 0,79 0,72

south-west 1 0,98 0,95 0,9 0,81 0,75

south-east 1 0,98 0,95 0,9 0,81 0,75

east, west 1 1 1 1 1 1

Groundwater runoff and interflow are computed as follows, considering the portion ofdrainage Ad and the grade of sealing Aseal [%]:

RG=

SW ⋅RO⋅ f exp

P year

⋅(1− Ad

100)⋅(1− 0,75⋅Aseal

100 )f q

[mm yr-1]

RI =( f q−1)⋅RG [mm yr-1]

We assume that sealed areas have a permeability of 25%. There is no calculation ofRI and RG on drained areas.

1 mean groundwater table depth

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Chapter 4 : Soil erosion and sediment input

4 Soil erosion and sediment input

4.1 Soil erosion from rainfall and runoff

Soil erosion from rainfall and runoff is computed according to the Universal Soil LossEquation USLE (Wischmeier & Smith 1978) considering sheet and rill erosion, but nostream channel and gully erosion (compare Auerswald & Schwertmann 1988, Auers-wald 2000, Wiegand 2002).

A=R ⋅K ⋅C ⋅S⋅L⋅P

A computed soil loss per unit area [t ha-1 yr-1],R rainfall and runoff factor: the number of rainfall erosion index units, plus a

factor for runoff from snowmelt or applied water, where such runoff is significant,

K soil erodibility factor: soil loss rate per erosion index unit,L slope-length factor: ratio of soil loss from the field slope length to that from a

22 m length,S slope-steepness factor: ratio of soil loss from the field slope gradient to that

from a 9% slope,C cover and management factor: ratio of soil loss from an area with specified co

ver and management to that from an identical area in tilled, continuous fallow,P support practice factor: ratio of soil loss with a support practice like contour

disking to that with straight-row farming up and down the slope.

The C-factor is computed municipality based considering data from the agriculturalstatistic (e.g. InVeKoS-data2) according to Auerswald (2002) for arable land as fol-lows:

C=[83−1,58⋅(c+ms+ fc)+0,0082⋅(c+ms+ fc)2]⋅(1−0,03⋅ fc )+0,01⋅ fc−0,05⋅ms

with c as the portion of cereals (including rape, excluding maize) [% of cropland], msas the portion of root crops and cereals (including rape and maize) in conservation til-lage [% of cropland], fc as the portion of perennial feed cropsf several years [% ofcropland].

The coefficients c, ms and fc are computed from the agricultural statistic per munici-pality. We are able to consider 91% of the real C-factors' variance (Auerswald 2000).The methodology should not be used if a dominance of vegetables, perennial cultu-res (hop, viticulure, fruit-growing) or crop feed (> 30%) or combinations of crop feedand root crops in conservation tillage are given, because negative C-factors could becomputed. We recommend to set in an estimated value of 0,01 in these cases, whichcorresponds to a 1% soil loss of an area in tilled, continous fallow.

If we only know the shares of conservation tillage at all, but information about thecorresponding fruit types are missing, we recommend to choose a C-factor value of0,06. The recommended values for the following land use types are: 0,1 on viticulture

2 InVeKoS - Integriertes Verwaltungs- und Kontrollsystem

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and fruit-growing, 0,004 on grassland and forest. We do not calculate any C-factorson further land use types.

It should be taken into account, that the chosen size of the grid significantlyinfluences the modelling of soil loss. Larger grid sizes show a tendency tounderestimate soil loss, because the spatial variability of slope is decreasing, causedby aggregation (Wu et al. 2005).

4.2 Sediment input

Soil accumulation is close connected to soil erosion. Only a smaller part of soil loss iscarried in into surface water in larger river basins. Sediment input is often limited tosmaller areas, but can be very intensive on those „hotspot“-sites. We assume, thatapproximately 90% of the sediment input into surface water is realized on 10% of acatchment 's area (see COST Action 869 2006, Voges 1999). Driving forces are thedistances to the watercourse, transportation capacity of surface runoff and the depo-sition of soil in landscape.

Sediment loadings in watercourses may also be caused by many other factors, forexample:

– lateral or vertical erosion within watercourses,

– sediment input from urban areas / settlement (substances filtered off),

– mudflows, solifluction, gelifluction,

– sediment input from coal mining, building of roads, houses etc.

– forest routes.

Car Traffic and industrial washing off are the main sources of sediment input in urbanareas with approximately 0,2 to 1 t ha-1 yr-1. Particle-bound input is of miner importan-ce on this land use type (z.B. Carter et al. 2003, Kiehlhorn 2005, University of Wis-consin-Extension 1997). Soil losses from building-sites have been estimated up to14-18 t ha-1 a-1, filtered off substances with concentrations between 100 to 340 mg l-1

have been mentioned by Kiehlhorn (2005). In the STOFFBILANZ model we cannotconsider these sources at the moment in an adequate way.

Empirical based modellings often use the sediment delivery ratio SDR to computethe relation beteen soil erosion from rainfall and runoff and sediment input in the wa-tercourse. In the model STOFFBILANZ we use a methodology to estimate sedimentinput, which has been adapted to regional scale (Veith 2002, Halbfaß 2005, Halbfaß& Grunewald 2006, 2008, Voges 1999). Main targets are:

– the spatial differentiated computation of sediment delivery considering the main driving forces,

– the calculation of sediment input in the whole river basin,

– the computation of hotspot and source areas of sediment input in detail.

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The methodological approach is explained in 4. First we have to do a separation bet-ween connected areas and those areas, who have no hydraulic connection to theriver net using GIS-functions (Halbfaß 2006). Barriers on the flow path, like roads,railways, etc. are considered in the modelling of sediment input, non-connected are-as will be neglected.

Figure 4: Methodological approach to compute sediment input and hotspot areas

The sediment delivery ratio SDR is calculated as follows:

SDR=ҳ ⋅( sl flow)(1−P )

where ҳ is a coefficient of land use, s is the slope [m m-1], lflow is the average distanceto the watercourse [m] and P is the likeliness of connectivity3.

The coefficient ҳ is derived from the C-factor:

ҳ=1,43⋅ln (C− factor )+9,49 R²=0,89

P is calculated using the different probabilities (according to Voges 1999, see 5) forthe distance to the watercourse plFG, soil erosion pA and surface runoff pRO as follows:

(0 ≤ P ≤1)

with

P lflow=−0,1358⋅ln ( lflow)+0,9717 R²=0,94 (0 < ҳ ≤ 1000 m)

3 the likeliness of connectivity describes the probability and the intensity of an area to participate onsediment dislocations up to the watercourse (Halbfaß 2005)

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P A=0,0671⋅ln(A)+0,1557 R²=0,85 (ҳ ≥ 0,1 t ha-1 yr-1)

PRO=0,0386⋅ln (RO )+0,0994 R²=0,96 (ҳ ≥ 0,1 mm yr-1)

and:

plflow = 0 v pA = 0 v pRO = 0 --> P = 0

lflow > 1000 m --> plflow = 0 --> P = 0

A < 0,1 t ha-1 a-1 --> pA = 0 --> P = 0

RO < 0,1 mm a-1 --> pRO = 0 --> P= 0

Figure 5: The derivation of likeliness of connectivity in principle

Sediment input in the watercourses is derived as follows:

SE=SDR⋅A⋅a

where SE [t yr-1] is the use specific sediment input, A [t ha-1yr-1] is the soil erosion anda (0 ≤ a ≤ 1) is the portion of an area where a hydraulic connection is given.

Sediment hotspots are computed by an estimation formula considering the relationbetween P and SDR:

f (P)=SDR=a⋅Pb

The coefficients a and b of this function are determined by the Least Square Method.Sediment hotspot areas are defined, if the increase f'(P0) of tangent at P0 1.

P0 is derived as follows:

P0=( ( f ' (P0))(a⋅b ) )(

1(b−1) )

with f'(P0) = 1

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Chapter 5 : P-balance

5 P-balance

5.1 Diffuse P-input

The P-balancing is influenced by P-inputs, P-transformations and P-losses. A com-plete modelling of this soil-water-plant system on regional scale might be very diffi -cult, because of the physical / chemical character of phosphorus and its strong bin-ding to the sediment. P-transformations are therefore not adequately computable. Inthe STOFFBILANZ model we focuse on the derivation of particle-bound (via soil ero-sion and surface runoff) and dissolved P-losses (via percolation) considering pa-thways, sources and sinks of phosphorus in river basins. Particle bound phosphorusPPSE and dissolved P-losses DP are summarized to TPdiff:

TPdiff [ kg ha−1a−1 ]=PP SE+DP

5.1.1 Particle-bound phosporus

Particle bound P-input in surface waters PPSE are calculated for the land use typesarable land, grassland, decidous forest, coniferous forest, viticulture and fruit-growing(emmission) considering sediment input SE, nutrient enrichment ER and the P-con-tent Pt in topsoil:

PPSE [ kg ha−1a−1]=SE [ t ha−1a−1]⋅ER⋅P t [mg kg

−1]

The P-content in topsoil is derived from land use type and soil texture (e.g. accordingto Freistaat Sachsen 1999). P-contents are rather uncertain because of their sitespecific high variability (Halbfaß & Grunewald 2004).

The nutrient enrichment ER is derived from the soil loss rate A (compare Auerswald1989).

ER=2,53⋅A−0,21 R² = 0,981

Thus we have an increasing ER if soil erosion sinks, because of the selective trans-port process, prefering the dislocation of silt and clay. P is mainly adsorbed to thesesoil textures, thus we have an enrichment of sorbed substances in the sediment loadof the surface runoff in comparison to the soil (Lammers 1997). The enrichment isbased on the splash-effect of rainfall. Soil aggregates are destroyed and soil particlesare dislocated selectively. Thus enrichment ratio increases in combination with a sin-king soil loss because the portion of smaller soil particles, being dislocated, increases(Ghadiri & Rose 1991a, b). In literature we find different enrichment ratio values, cor -responding to regional characteristics up to 6,0. Mean values about 1,8 are typical forMid european conditions (Sharpley et al. 1993, Schaub & Wilke 1996, Dutt-mann1999).

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5.1.2 Dissolved P-inputs

The dissolved P-inputs DP into the tributary – for areas of arable land, grassland,fruit-growing, viticulture and decidous / coniferous forest - are caluculated as the pro-duct of the average runoff of the respective runoff component and the correspondingP- concentration in surface runoff, drain discharge, groundwater runoff and interflow.

5 shows concentration values which have been collected for Saxony using mo-nitoring data from groundwater measurements and literature data (Halbfaß 2005,Prasuhn 2003).

Table 5: P-concentrations [mg/l] in the runoff components

land use type surface runoff draindischarge

interflow groundwaterrunoff

arable land- conventionel tillage- conservation tillage

0,20,6

0,21 / 0,062

0,61 / 0,182

0,06³/ 0,01 – 0,054 0,01 – 0,055

grassland 0,8 0,8 0,06³/ 0,01 – 0,054 0,01 – 0,055

decidous / coniferous forest 0,025 - 0,01 – 0,03 0,01 – 0,035

fruit-growing 1,2 - 0,01 – 0,05 0,01 – 0,055

viticulture 0,8 - 0,01 – 0,05 0,01 – 0,055

1 soil texture ss, ls, us / 2 soil texture lt, tl, ll, sl, ut, su, lu, tu / 3 semihydromorphic and hydromorphic soils / 4 terrestric soils / 5 regional differentiated

At the moment we have a discussion about the influences of conservation tillage onP-concentrations. According to Zimmermann (2003) strong macropore fluxes arepossible on these sites, if the percolation capacity is exceeded. The risk of a P-dislo-cation via macropores even depends on many other soil characteristics. We assumethat there is no significant increasing of P-dislocation via macropore on terrestric soiltypes (compare Schmidt 2006).

5.1.3 Further P-inputs

P-inputs TPdiff, which cannot b calculated according to their pathway of input (partic-le-bound, dissolved) are summarized in the following chapter. In the modelling weuse export coefficients, which have been derived from literature.

5.1.3.1 Diffuse sources in urban areas / settlement

Diffuse sources from urban areas / settlement are considered in the modelling via thefollowing pathways using export coefficients:

• housings without a connection to a public sewage treatment plant, direct discharger to the sewage system, small sewage works possible, no cesspit

• housings without a connection to a sewage system, cesspit or a small sewage works available

• stormwater overflow discharge

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• atmospheric deposition (unsealed area)

In the estimation of diffuse inputs from housings, population equivalents in raw waterand mean values of retention are included.

P-inputs via stormwater overflow discharges are only determined on the sealed area.

For the computation of atmospheric P-deposition on unsealed areas we use a meanvalue of 0,5 kg P ha-1 yr-1. We assume additionally that only 10 % (0,05 kg P ha-1 yr-1)will be washed out into surface water because of the high P-sorption in the unsatura-ted zone.

Pathway unsealed settlement / urban area

Spatial scale: grid

Input data

• Export coefficient for P cP [kg ha-1 yr-1]

• grade of sealing Aseal [%]

• retention coefficient in soil rsoil for P 90%

• permeability of sealing: 25%

Modelling

DP urb=c P⋅( 100−r soil

100 )⋅(100−Aseal⋅0,75

100 ) [kg ha-1 yr-1]

Pathway storm water discharge

Spatial scale: grid

Input data

• export coefficient for P cP [kg ha-1 yr-1]



Modelling

DP seal=c P⋅( Aseal ⋅0,75

100 ) [kg ha-1 yr-1]

Pathway housings without a sewer system

Spatial scale: varying

Input data

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• export coefficient for P cPinh [kg inhabitants-1 yr-1]

• inhabitants ninh [-]

• grade of connection to the sewage treatment plant nSTP [%]

• portion of the inhabitants without a connection to the sewer system to the sumof inhabitants with a direct discharge and inhabitants without a connection tothe sewer system nwSTP [%]

• settlement area Aurb [ha]

Modelling

DP seal=cPinh⋅ninh⋅

100−nSTP

100⋅nwSTP

100Aurb

[kg ha-1 yr-1]

Pathway housings with a direct discharge


Input data

• export coefficienten for P cPinh [kg inhabitants-1 yr-1]





Modelling

DP seal=cPinh⋅ninh⋅

100−nSTP

100⋅100−nwSTP

100Aurb

[kg ha-1 yr-1]

Diffuse P-input TPdiff from settlement / urban area in surface waters is realized as thesum of all export coefficient of each pathway..

5.1.3.2 Diffuse sources for waters and undefined land use types

We do not make any differentiation between particle-bound and dissolved inputs onthe land use types waters and Undefined land use, because variabilities are hardly tocompute. Diffuse P-input TPdiff for undefined land use is estimated to 0,5 kg P ha-1yr-1.

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On the land use type waters we determine the diffuse phosphorus input TPdiff accor-ding to the atmospheric P-deposition, varying according to literature data from 0,04 to1,5 kg P ha-1 yr-1. We recommend to use the 0,4 value for eastern Germany regionswith precipitations about 660 mm a-1, according to Behrendt et al. (1999).

5.2 Point-related P-inputs

Besides the diffuse P-input we have an additional pollution of waters by point-relatedloadings TPpoint, which can be quantified using datasets of public and industrial sewa-ge treatment plants.

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Chapter 6 : N-balance

6 N-balance

6.1 Diffuse N-input

6.1.1 N-balances on arable land, grassland and viticulture, fruit-growing

The nitrogen balance can be computed in a simplifying way as the result of inputsand outputs being done in the present regional scale by different modelling tools(e.g. Behrendt et al. 2002, Bach et al. 2003). Processes of mobilisation and immobili-sation of nitrogen are additionally considered by applications with a more detailedsite specific view (e.g. Hülsbergen & Diepenbrock 1997, Brisson et al. 1998) In theSTOFFBILANZ model these processes are included for cropland sites using indica-tors of mineralisation and immobilsation in dependence on soil and fruit specific coef-ficients. Thus we are able to give an estimation to the status of N-humus (decreasingor increasing) in addition. Focusing on these phenomena will become more import-ant in the future because of an increasing cultivation of energy crops. Effects of spe-cial measurements like intercrop cultivation, changes in live-stock or consequencesof climate change can be computed in a more sufficient way. The different parame-ters of this „extended“ N-balancing are included in 6 (Gebel e al. 2010, 2013)

Figure 6: Derivation of the N-balance on cropland

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Calculation of input, output, mobilisation and immobilisation is derived from the follo-wing equations considering the respective spectrum of crop types:

Import=F min+ f l ⋅F org+F leg

Mobilisation= f mob⋅F org+M root+M ic+M soil [kg N ha-1 yr-1]

Immobilisation= f org ⋅F org+ I root+ I icExport=Eharv+E root

where Fmin is mineral fertilizer, Forg is farm manure, Fleg is N-fixing of legumes, Mroot is N-mobilisation from crop residues of the preliminary crop in the year of calculation, I ic is N-immobilisation by inter crops, Mic is N-mobilisation from inter crops of the previous year, Msoil is long year N-mobillsation from organic soil matrix, Eharv is harvest withdrawel of the main product, Iroot is N-immobilisation by root and by-product, Eroot is exported by-product, fl is coefficient to consider losses of Forg, fmob is the coefficient to consider N-mobilisation from Forg in the year of calculation, forg is the coefficient to determine the or-ganic part of Forg.

Information to the atmospheric deposition Natm and denitrification in topsoil Dsoil will begiven in chapter 6.1.3 and 6.1.4.

6.1.1.1 N-import on arable land

Mineral fertilizer and farm manure

Data to mineral fertilizer Fmin are given in dependence on fruit types and regional spe-cification. Farm manure Forg is determined in dependence on the regional livestockconsidering losses of storage and deposition of liquid manure and dung by the helpof a coefficient fl.

N-fixing by legumes

N-fixing rates Fleg are determined in dependence on the type of fruit and the respecti-ve yield (nach SlfL 2007).

6.1.1.2 N-mobilisation on cropland

N-mobilisation from farm manure

The N-mobilisation from the organic farm manure part is calculated via the coefficientfmob considering dung and liquid manure.

N-mobilisation from inter crops

Effects of the cultivation of inter crops of the previous year are considered by additio-nal coefficients of N-immobilisation and mobilisation. In the modelling we assumethat the N-mobilisation from inter crops in spring is about 75% of the total immobilisa-tion of the inter crops Mic in autumn / winter of the previous year (compare Schliepha-ke & Albert 2003, chapter 6.1.1.3).

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N-mobilisation from crop residues and roots

N-mobilisation from crop residues and roots Mroot are considered in the modeling ac-cording to SLfL (2007) and Arman et al. (2002).

N-mobilisation from organic soil matrix

The long time mobilisation of nitrogen from the organic soil matrix Msoil is determinedas described above (7). N-mobilisations resulting from the recent year calculation arenot included in this part of the modeling. They are calculated in addition (see Mroot).

In the framework of the development of the model STOFFBILANZ_BW in cooperationwith the authorities of the federal state of Baden-Württemberg we have modified themethodolgy to derive the N-mobilisation based on the Henin & Dupuis concept. N-mobilisation is calculated according to Mary & Guérif (1994) and Meynard et al.(1996), considering content of humus, C/N-ratio, contents of clay, lime and skeleton,average annual temperature and fruit type specific manamgement practice. Thus weget a differentiation including variabilities of soil texture and soil type specifics of N-mobilisation in an adequate way.

Figure 7: Derivation of the N-mobilisation from the organic soil matrix

First we have to determine the organic N-content in topsoil Nt using the humus con-tent chumus [%], raw density SBD [g/cm³] and C/N-ratio in topsoil as follows (Mary &Guérif 1994, Meynard et al. 1996):

N t=chumus ⋅SBD⋅3⋅10000

1,72⋅C /N [kg N ha-1 yr-1]

The potential N-mobilisation from soil matrix Msoil is determined as follows conside-ring Nt, the coefficient K2 and the content of skeleton csk in topsoil [%]:

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M soil=N t ⋅K 2⋅1,3⋅(1−csk

100) [kg N ha-1 yr-1]

The coefficient K2 is calculated by content of clay cclay and lime clime in topsoil [%] andthe average annual temperature Tavg [°C] via the coefficient ft. The intensity of farmmanure use and the frequency of an export of crop residues is taken into account foreach type of fruit via the coefficient fs to characterize the cultivation system (6,according to Arman et al. 2002, Mary & Guérif 1994, Meynard et al. 1996):

K 2=1200⋅ f s ⋅ f t

(cclay⋅10+200 )⋅(0,3⋅clime ⋅10+200)

f t=0,15⋅T avg−0.5

Table 6: Definition of the coefficient fs to characterize the cultivation practice

Crop residues being ex-ported

frequency of farm manure practice

> every 10 years every 5-10years

every 3-5 years < every 3 years

fs

… always 0,8 0,9 1 1,1

... sometimes 0,9 1 1,1 1,2

... never 1 1,1 1,2 1,3

6.1.1.3 N-immobilisation on arable land

N-immobilisation by the organic part of farm manure

We calculate the organic part of farm manure which will be included in the humus-pool in the year of calculation using the coefficient forg.

N-immobilisation by crop residues and root

The N-immobilisation in crop residues and root on arable land is given by Iroot in rela-tion to the fruit type specific yield and the coefficient of withdrawel for the by-product(SlfL 2007, LAP 2004). Crop residues being exported are excluded in the calculation(see Eroot).

N-immobilisation by inter crops

Effects of the cultivation of inter crops are considered by additionally coefficients ofN-immobilisation and mobilisation. In the modelling we assume that the N-immobili-sation by inter crops Iic in autumn / winter is about 20 kg N ha-1 yr-1 higher than the N-mobilisation in spring of the calculation year from the intercrop of the previous year.We are estimating the N-immobilisation to 80 kg N ha-1 yr-1 and the N-mobilisation to 60kg N ha-1 yr-1 respectively (see chapter 6.1.1.2, compare to Schliephake & Albert2003).

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6.1.1.4 N-export on arable land

Harvest withdrawel

The N-withdrawel by harvest is given by Eharv in relation to the fruit type specific yieldand the coefficient of withdrawel for the main product (SlfL 2007).

Crop residues being exported

This part of crop residues Eroot is considered in dependence on the fruit type specificyield, the coefficient of withdrawel for the by-product and the portion of crop residuesbeeing exported (SLfL 2007).

6.1.1.5 Interim balance

The interim balance (Nsurplus) on arable land is calculated as follows, consideringsources (input, mobilisation) and sinks (immobilisation, output):

N surplus=F+M − I−E [kg N ha-1 yr-1]

6.1.1.6 Interim balance on grassland

We calculate the interim balance (= N-surplus) on grassland as follows:

N surplus=F leg+F min+( f l− f org+ f mob)⋅F org−Eharv [kg N ha-1 yr-1]

The N-fixing of legumes on grassland is determined according to Weissbach (1995).All other parameters are derived analogous to cropland whereby we do not considerN-transformations.

6.1.1.7 Interim balance on viticulture and fruit-growing

We estimate the interim balance value (= surplus) on viticulture to 0 kg N ha-1 yr-1,.onfruit-growing areas a 10 kg N ha-1 yr-1 value is given. These values should be adaptedif necessary.

6.1.2 N-balance on forest land

6.1.2.1 N net-uptake rate

While calculating the data for forest land first the weathering class and N- net-uptakerate have to be computed. We derive the data following the critical-load-concept (ac-cording to Nagel & Gregor 1999, UBA 1996). For the use in the model STOFFBI-LANZ they have been accordingly adapted (Kaiser 2002). The weathering rate isclassified according to the soil texture and parent rock derived from the soil type (ad-apted from Nagel & Gregor 1999, 7).

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Table 7: Derivation of the weathering class on forest land

soil type

soil texture

Hn, Hh ss, ls,us, su

sl, lu ll tl tu ut lt

weathering class

HN, HH 0 0 0 0 0 0 0 0

F#, O#, RN, RQ, P#,B#, PP-BB

0 1 2 3 3 3 4 4

D#, L#, SS-##, GG-##, A#, S#, G#, T#,Y#

0 2 3 4 4 4 4 4

RR, RZ, C# 0 4 4 4 4 4 4 4

The yield type can be deduced from the weathering class while taking into considera-tion the average annual temperature as well as the average percolation rate (adaptedfrom Nagel & Gregor 1999, 8).

Table 8: Derivation of the yield type on forest land

weathering class 3 + 4 weathering class 1 + 2 weathering class 0

temperature [°C] ≥9 8 7 6 5 <5 ≥9 8 7 6 5 <5 ≥9 8 7 6 5 <5

SW [mm/ yr-1] yield type

≥1000 Ia Ia Ia I II IV I I I II III IV I I I II IV V

<1000-800 Ia Ia Ia I II IV I I I II III IV I I I II IV V

<800-600 Ia Ia I I II IV I I I II III IV I I II II IV V

<600-400 Ia I I I II IV I I II II III IV II II II III IV V

<400-200 I II II II III IV II II III III III IV II III IV IV IV V

<200 III III III II III IV III III IV IV IV IV III IV V V V V

The net removal of N on biomass (Iuptake) which is harvested can be derived from theyield type (adapted from Nagel & Gregor 1999, 9).

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Table 9: Derivation of the N net-uptake on forest land

N net-uptake rate [kg N ha-1 yr-1]

yield type decidous forest coniferous forest

Ia 15 10

I 13,5 8,5

II 11,5 6,5

III 8 5

IV 7 4

V 3,5 2

6.1.2.2 N-Immobilisation on forest land

The N-immobilisation rate Ihumus is found with the help of the average annual tempera-ture (adapted from Nagel & Gregor 1999, 10).

Table 10: Derivation of N-immobisation rate on forest land

average annual temperature [°C] ≤4 5 6 7 8 ≥9

N-immobilisation rate [kg N ha-1 yr-1] 5 4 3 2 1,5 1

6.1.3 Atmospheric N-deposition

The data of total atmospheric deposition (dry and wet) Natm are considered in the mo-delling according to land use type for each grid cell (compare Gauger et al. 2002,2008).

6.1.4 Denitrification in topsoil

6.1.4.1 Arable land, grassland, fruit-growing, viticulture, settlement, undefined land use

We calculate the denitrification of the top soil according to the method of Wendland(1992), considering the Michaelis-Menten-kinetics. Here the different parts of the in-terim balance are used. In addition to that we determine the maximum denitrificationrate as well as the coefficient K which depends on the conditions of denitrification(good / moderate / poor) and the soil type (11):

D soil [kg N ha−1a−1]=Dmax⋅

(N surplus+N atm)7,5

K +N surplus+N atm

7,5

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Table 11: Conditions of denitrification derived from the soil type

conditions of denitri-fication

Dmax [kg N ha-1 yr-1] K Bodentypen

good 50 6,7 S#, G#, HN, HH

moderate 30 4 RR, RZ, T#, D#, L#, SS-##, GG-##, C#, A#

poor 10 2,5 F#, O#, RN, RQ, P#, B#, PP-BB, UA, Y#

The conditions of denitrification in the top soil require though a more differentiatedview in addition to the values in 11. So the conditions for the soil type luvisol (L#) incombination with the soil textures ss and ls are assumed as poor (instead ofmoderate). For the soil type cambisol (B#) the conditions of denitrification of the soiltextures tl, lt and ut are categorized as moderate (instead of poor). The reason forthese differentiations is that we as well as Wendland (1992) distinguish betweencambisols that are poor in base and those that are rich in base. Areas with the abovementioned soil textures are mainly classified as cambisols rich in base. Here we alsofind particularly high field capacity values, comparatively low values of effective fieldcapacity and field capacity in the effective root depth and low kf and soil porosity va -lues, which increase denitrification. Furthermore the assessment of the conditions ofdenitrification on soils with a skeleton content higher than 30% is always changedfrom good to moderate respectively from moderate to poor. We assume that the con-ditions of denitrification in areas of settlements and in of those of viticulture are gene-rally poor independent on the soil type and the soil texture. The reason for these mo-difications is that these soils have a sufficient porosity and a greater distance togroundwater table, so that higher rates of denitrification need not be expected.

6.1.4.2 Forest land

For the land use types decidous and coniferous forest the denitrification rate is deter-mined according to the critical-load-concept (see Kaiser & Gebel 2003, adapted fromNagel & Gregor 1999). Here data for the atmospheric deposition, the N net-uptakerate Iuptake (9), the N immobilization rate Ihumus (10) and a denitrification coefficient fde

(12) are necessary:

D soil [kg N ha−1a−1]= f de⋅(N atm− I uptake− I humus)

Table 12: Derivation of the coefficient fde

soil texture ss, ls, us, su, sl, lu ll, tu tl, ut, lt Hn, Hh

fde 0,1 0,2 0,3 0,8

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6.1.5 Diffuse N-leaching from the rooted soil zone

N-leaching rate DNsoil on arable land, grassland, viticulture, fruit-growing and undefi-ned land use is determined as follows considering the interim balance, Natm and thedenitrification Dsoil:

DN soil [kg N ha−1a−1 ]=N surplus+N atm−D soil

On the land use type waters the leaching corresponds to the atmospheric deposition.

On forest land we compute the N-leaching in dependence on N net-uptake rate, N-immobilisation and denitrification as follows (according to Nagel & Gregor 1999):

DN soil [kg N ha−1a−1 ]=N atm−D soil− I uptake− I humusOn the land use type settlement the N-leaching is only calculated on the unsealedarea. We assume that the permeability on the sealed area Aseal [%] is about 75%(compare to Sukopp & Wittig 1998).

DN soil [kg N ha−1a−1 ]=(N atm−D soil)⋅(1− (0,75⋅A seal)100 )

The diffuse loadings from sealed areas DNRS are washed out directly into the tributary(see below).

6.1.6 N-input in surface waters from sealed areas

The N-inputs from the sealed area DNRS are calculated analogous to the derivation ofP-inputs.

Pathway storm water discharge

Spatial scale: grid

Input data

• export coefficient for N cN [kg ha-1 yr-1]



Modelling

DN seal=cN ⋅( Aseal⋅0,75

100 ) [kg ha-1 yr-1]

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Pathway housings without a sewer system


Input data

• export coefficient for N cNinh [kg inhabitants-1 yr-1]





Modelling

DN seal=cNinh⋅n inh⋅

100−nSTP

100⋅nwSTP

100Aurb

[kg ha-1 yr-1]

Pathway housings with a direct discharge


Input data

• export coefficient for N cNinh [kg inhabitants-1 yr-1]





Modelling

DN seal=cNinh⋅n inh⋅

100−nSTP

100⋅100−nwSTP

100Aurb

[kg ha-1 yr-1]

Diffuse N-input from sealed areas in surface waters DNRS is realized as the sum of allleachings of each pathway.

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6.1.7 Separation of the N-leaching to the runoff components

Nitrate-N being readily soluable in water is extremly apt to be washed out because ofits high mobility. The emissions from an area are transfered from the rooted soil ma-trix by the way of percolation (DNSW), drain discharge (DNRD) and the surface runoff(DNRO). We assume that for water areas the loads are only transfered by the surfacerunoff.

The partitioning of NanSW in NanRG and NanRB is done for each runoff component. Theloads for the groundwater runoff, interflow, surface runoff and drain discharge arecalculated as follows:

DN SW [kg N ha−1a−1]=DN soil⋅SW

(R−0,75⋅RS )

DN RD [kg N ha−1a−1]=DN soil⋅RD

(R−0,75⋅RS )

DN RO [kg N ha−1a−1]=DN soil ⋅RO

(R−0,75⋅RS )

DN RI [kg N ha−1a−1]=DN soil⋅RI

(R−0,75⋅RS )

DN RG [kg N ha−1a−1]=(DN SW−DN RI )⋅r gw

Residence time of groundwater runoff and denitrification in the upper aquifer is com-puted in the modelling in dependence on groundwater structure (see below). Weassume that for water areas the loads are only transfered by the surface runoff. The-refore a possible transfer of nitrogen from the water into the ground water is not ta-ken into account.

The nitrate concentration in percolation water CNO3SW is calculated according to thefollowing algorithm:

C NO3SW [mg l−1 ]=

DN SW ⋅4,43⋅100

SW

6.1.8 Residence time and denitrification in the upper aquifer

The nitrate emissions which are detectable in the surface water have reduced them-selves because of denitrification processes during the runoff passage in the ground-water system. The nitrate loss by denitrification rgw in the upper aquifer (groundwaterpath) is computed in dependence on groundwater structure. Considering half-valuetime of denitrification and residence time of groundwater, a significant reduction ofthe N-input into groundwater is possible. The detection of flow-paths and the calcula-tion of distance ground-water velocity is only possible in loose rock. Total residencetime and retention of the emitted load per grid cell is then determined on the integralinteraction of residence time and half-value time of all grid cells corresponding to theflow path until the contact to surface water is realized (compare to chapter 6.1.8.2,8).

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Flow paths and residence time are not numerically considered in regions with solidrock or loose over solid rock aquifers because of the very complex hydraulic, whichcan not be explained by the Darcy-algorithm. Thus we have to make an estimation ofthe respective values (see chapter 6.1.8.1, 13 and 14).

6.1.8.1 Solid rock aquifers and loose over solid rock aquifers

We have to estimate residence time and half-time value of denitrification in these re-gions, based on the investigations of Wendland & Kunkel (1999) and Kunkel &Wendland (1999). The methodology has exemplary been adapted by Ullrich (2006)for Saxony considering the hydro-chemical character of groundwater and present lite-rature and isotope data to groundwater dating (e.g. Schwarze 2004) (13, 14

The coefficient rgw is considered in dependence on half-value time of denitrificationand groundwater residence time (upper aquifer) as follows (Wendland & Kunkel1999, Wendland 1992):

good or moderate conditions of denitrification:

r gw=exp (−0,267⋅t gw)

poor conditions of denitrification:


denitrification might be insignificant:


Table 13: Derivation of denitrification in the upper aquifer, e.g. for Saxony

upper aquifer half-value time of de-nitrification [yr]

hydro-chemical cha-racter of groundwater

conditions of denitrifi-cation

quarternary and tertiary loose rock

ca. 1,2 bis 4 mainly reducing good or moderate

loose rock over solid rock

ca. 20 oxidising / reducing poor

limestone, conglomera-te, metamorphic, pluto-nic, volcanic, sandsto-ne, silt and clay rock

ca. 35 oxidising insignificant

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Table 14: Estimation of ground water residence time (solid rock, e.g. Saxony)

groundwater structure / soil type estimation of averagegroundwater residence time

[yr]

sandstone 20

loose rock over solid rock 15

metamorphic, plutonic 7

volcanic 6,5

limestone, conglomerate, silt- and claystone, quarternary valleys 5

soil types G#, GG-##, A#, HN 1

6.1.8.2 Loose rock aquifers

The calculation is based on a compartment model which has been developed by Uh-lig (2008) according to the WEKU-methodology (Kunkel & Wendland 1999) using amultiple-flow algorithm (8).

Necessary input data are coefficients of permeability taken from the HÜK 200, a digi-tal groundwater table of the upper aquifer, the river net and an elevation model. Weuse these data to generate the distance ground-water velocity, flow paths and thetransfers of nitrate for each grid cell of the upper aquifer. The exfiltration in surfacewater is determined on the distance between elevation model and groundwater-head.The transfer of groundwater runoff and nitrate load to the exfitration zone stops if sta-tionary conditions are fulfilled.

Figure 8: Derivation of groundwater residence time and denitrification

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Denitrification is simulated via a first order degradation, using a coefficient of degra-dation of 0,267/yr (compare to Wendland 1992).

Transport of groundwater runoff and nitrate load is realized by a multiple-flow algo-rithm (MFA). According to the hydraulic gradient, waters and loads are separated intodifferent directions. Finally we are able to compute nitrate load and nitrate concentra-tion for each grid cell up to the exfiltration zone (Uhlig et al. 2010).

6.1.9 Dissolved N-input from diffuse sources

The total dissolved N-input DNR from diffuse sources considering denitrification ingroundwater is calculated as follows:

DN R [kg N ha−1a−1]=DN RO+DN RS+DN RD+DN RI+DN RG

6.1.10 Particle-bound N-input

Besides the dissolved N-input, we can have particle-bound dislocations of nitrogenwhich are generally of miner importance. We calculate these inputs PNSE in combina-tion with the modeling of soil erosion considering the organic N-content of topsoil Nt

and the sediment input SE as follows:

PN SE [kg N ha−1a−1]=N t ⋅SE3000

6.1.11 Total diffuse N-input

The total diffuse N-input TNdiff is finally calculated as the sum of dissolved and partic-le-bound loads:

TN diff [ kg N ha−1a−1]=PN SE+DN R

6.2 Point-related N-inputs

Besides the diffuse N-input TNpoint we have an additionally pollution of waters bypoint-related loadings, which can be quantified using datasets of public and industrialsewage treatment plants.

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Chapter 7 : Long lasting nutrient retention in river basins

7 Long lasting nutrient retention in river basins

Transfer of nutrients (P, N) in catchment areas is determined on different interdepen-dent processes. Nutrient sources, pathways and sinks are controlled by catchmentcharacter, hydrology and anthropogenic input. Processes of transfer are in generalmobilisation and dislocation caused by heavy rainfalls via surface runoff and soil ero-sion (Sharpley et al. 1999), infiltration via macropores (Bundt 2000, Heathwai te u.Dils 2000), drainage, interflow and groundwater (Kronvang et al. 1997, Pudenz 1998,Chapman 2001, Jonge et al. 2004), bank erosion (Sekely et al. 2002, Zaimes et al.2005, Koch 2007), resuspension of and desorption from bottom sediments (Bowes etal. 2003, Mulholland 1992, Schulz et al. 2008), processes of biological turnover inwaters (Boulton et al. 1998, Jin et al. 2007) and nutrient inputs from point sources.

P- and N-fluxes in waters are determined by spatial and temporal dynamic (nutrientspiraling). A lot of physical and biogeochemical factors are influencing processes, nu-trient concentrations and loadings (u.a. Withers u. Jarvie 2008). Important time andspace diffenciated parameters are conditions of morphology, hydrology and meteoro-logy, bioactivity, processes in riparian zone, river bed and inundation zone and watermanagement practice (u.a. Svendsen et al. 1998, Zessner et al. 2004).

Dealing with the nutrient retention phenomenon we should take into account, thatmany effects are short time related, especially controlled by hydrological variability(flood, low water). A long lasting retention for P especially exists in flooding areasand reservoirs (Walling u. He 1994, Guhr u. Meissner 2000, Venterink et al. 2003,Withers u. Jarvie 2008). The most important N-removal is caused by denitrification inriver bed (z.B. Donner et al. 2004). At the moment there is still a lack of plausible me-thods to derive process-orientated retention rates in the meso- or macroscalecatchment modelling.

Our computation of an average long-term retention of nitrogen and phosphorus insurface waters is based on generally available data and should only be used in a re-gional river basin modeling.

7.1 Retention of phosphorus

7.1.1 Retention of phosphorus in rivers

The spatial and temporal dynamic of transformation, transport and retention of phos-phorus is generated using the spiralling concept (Newbold et al. 1983). Thus proces-sings in the river continuum are changing from source to mouth (e.g. Bowes et al.2003).

Important processes in rivers in respect to a reflection of sources and sinks are listedas follows (e.g. House 2002, Haggard u. Sharpley 2007, Withers u. Jarvie 2008):

(a) sinks

1. deposition of sediment adsorbed phosphorus on the river bed;

2. sorption of phosphorus to the bed sediment;

3. phosphorus uptake by macrophytes and algues;

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4. precipitations of phosphorus in combination with calcite, iron and hydroxidesin oxidised interstitial water.

(b) sources

1. flood related remobilisation / resuspension of phosphorus from bed and banksediments;

2. desorption and solution of phosphorus from the sediment;

3. mineralisation of organic phosphorus;

4. solution of phosphorus in reduced interstitial water.

The processes mentioned above are generally relevant as short-term or medium-ran-ge sources and sinks, controlled by the temporal dynamic of runoff (low water, flood).Long-term retention of phosphorus is chiefly relevant in the inundation zone ofrivers and in reservoirs, being controlled by sedimentation of suspended par-ticles (Walling u. He 1994, Guhr u. Meissner 2000, Venterink et al. 2003, Withers u.Jarvie 2008). P-desorption from sediment into waters is neglectable as long as the in-terstitial water is oxidised (Schonlau 2007).

The computation of phosphorus retention in the STOFFBILANZ model only consi-ders the average long-term sedimentation of suspended loads in the floodingzone of surface waters. Sorption/desorption in the flooding zone, resuspension andshort-term respectively medium-range processes are neglected.

The sedimentation areas Ai per surface water body (OWK) are generated using GIS-technologies (e.g. processing of flooding zone, elevation model, soil mapping). Ave-rage annual long-term rates of sedimentation si are defined to the LAWA-river typo-logy. For the Lower Elbe river a value of 1 mm yr-1 has been exemplarily investigated(z.B. Schwartz et al. 2004, Krüger et al. 2006). Arguments by analogy have beenused to determine sedimentation rates for smaller rivers because corresponding in-vestigations are missing. The compactness SBD is assumed to be 1,5 g/cm³ uni-formly (15).

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Table 15: Generating of parameters acc. to the LAWA-river typology e.g. for Saxony

LAWA-type

description kSTs

mm a-1SBD

g/cm³

5 silicic mountain brooks 20 to 22 0,1 1,5

6 calcaric mountain brooks 22 0,1 1,5

9 silicic mountain rivers 28 0,1 1,5

10 mountain streams 30 0,1 1,5

14 lowland brooks with sandy sediment 40 0,1 1,5

15 lowland rivers with sandy-loamy sediment 40 0,5 1,5

16 lowland brooks with gravel sediment 35 0,1 1,5

17 lowland rivers with gravel sediment 35 0,5 1,5

18 lowland brooks with silty sediment 35 0,1 1,5

20 lowland streams 40 1,0 1,5

11 brooks with organic sediment 30 0,1 1,5

19 watercourses of flatland 35 0,1 1,5

The average annual sedimentation rate being potentially deposited is determined persurface water body considering sedimentation area and rate as well as the coefficientof compactness. The retention of suspended loads in lakes and reservoirs is assu-med to be 75%. The surface water bodies are joined together by a routing from sour-ce to mouth. Thus the suspended loads of the tributaries also include the respectiveloads of the upstream residents. The suspended load is reduced by the calculatedsediment retention. The load consists of:

• sediment input caused by soil erosion from rainfall and runoff,

• sediment input via drain discharges: 50% of P-input is assumed to be particle-bound, corresponding sediment rate is derived, P-concentration in sediment:1000 mg kg-1,

• sediment input on settlement areas and undefined land use areas are estima-ted to 0,2 t ha-1 yr-1 (low limited).

In relation to the suspended load we have a potential particle-bound P-rate, consis-ting of the following components:

• particle-bound P-input, caused by sediment input via soil erosion,

• particle-bound P-input via drain discharges, assumed to be 50% of the total in-put via drain discharges,

• particle-bound P-input from settlement and undefined land use, assumed to be50% of the total input from these land use types.

The long-term average annual retention of phosphorus in the flooding zone is derivedfrom the sedimentation rate and the corresponding particle-bound P-concentration insediment per surface water body. Long-term effects of bank erosion is not included in

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the modelling as well as we have no limitation of particle-bound P-concentration inthe suspended load.

7.1.2 Retention of phosphorus in lakes and reservoirs

Retention in lakes and reservoirs rres is done according to Maniak (2005) consideringthe coefficient of phosphorus net transfer sP, average depth of the water body z andthe hydraulic residence time τ:

r res=sP

(s P+zτ)

A net transfer coefficient of 16 is given in Maniak (2005). We have made an adaptionof the net transfer coefficient for the use in saxonian reservoirs considering the inves-tigations of Frank (20074).

7.1.3 Calculation within the river net

We determine a specific retention for each surface water body (OWK). The corre-sponding load per OWK Li consists of the catchment related input within the OWKarea TPi multiplied with the specific coefficient of retention r and the sum of inputs Lj

from the upstream residents multplied with r:

Li , P=(TPdiff , point ,i+∑ L j)×(1−r )

Tributaries and upstream residents are joined by a routing.

7.2 Retention of nitrogen

7.2.1 Retention of nitrogen in rivers

The most important mechanism of nitrogen retention in surface waters is the denitrifi -cation in the contact zone of water and sediment, being controlled by hydraulic andmicro-biological processes. According to the Nutrient Spiralling – concept (StreamSolute Workshop, 1990) modelling of retention rriv of a river section is done in depen-dence on a time-specific N-uptake rate kt (biological aspect) and the water residencetime τ (hydraulic Aspect) as follows:

r riv=1−exp (−k t⋅τ )

Water residence time is derived from the river section length and the average flowvelocity with

4 Frank, S. (2007): Ermittlung und Auswertung von Stofffrachten gemäß der LAWA- Empfehlung anZu- und Abflüssen ausgewählter Talsperren und Analyse der abflusskorrigierten Standartmethode.Belegarbeit TU Dresden, Inst. f. Geographie.

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τ= lv

The flow velocity is generated in a simplified way according to Mischke et al. (2005),considering the hydraulic gradient I, discharge Q, river width w and Manning-Strickler-coefficient kST:

v=k ST ⋅( Q(k ST ⋅w ⋅√I ))(

25)⋅√I

N-uptake rate depends on the discharge according to literature data (Wollheim et al.2006). Thus we have a decreasing uptake rate with an increasing discharge, becau-se the relationship between contact zone of water and sediment and the dischargebecomes more disadvantageous. The dependency of the uptake rate to nitrate con-centration and water temperature is not considered at the moment. The implementa-tion of these parameters should be strived for in order to optimise the retention mo-delling especially for point-related inputs.

River length is derived using GIS-technologies for each surface water body (OWK).The discharge of a surface water body includes the discharges of the surface waterbodies above, thus the whole catchment is considered. The Manning-Strickler-coeffi-cient is taken from literature (LAWA-Fließgewässertypen), as well as the average ri-ver width (mapping of river structure).

7.2.2 Retention of nitrogen in lakes and reservoirs

Retention modelling in lakes and reservoirs rres is done according to Maniak (2005)considering the coefficient of nitrogen net transfer sN, average depth of the waterbody z and the hydraulic residence time τ:

r res=sN

(sN+zτ)

7.2.3 Calculation within the river net

We determine a specific retention for each surface water body (OWK). The corre-sponding load per OWK Li consists of the catchment related input within the OWKarea TNi multiplied with the specific coefficient of retention r and the sum of inputs Lj

from the upstream residents multplied with r (Halbfaß el al. 2010):

Li , N=(TN diff , point , i+∑ L j)×(1−r )

Tributaries and upstream residents are joined by a routing.

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Chapter 8 : Decision support / scenarios

8 Decision support / scenarios

There is much space to use the STOFFBILANZ modelling as a decision support toolfor river basin management as well as the defining, calculating and interpretation ofspecial scenarios in comparison is possible. A collection of scenario options, which isextendable in cooperation to the developers, is presented in 16 (see detailedinformation in Gebel et al. 2015, 2016).

Table 16: Scenario options in the STOFFBILANZ model (examples)

target parameter controlling factors

diffuse input

soil erosion / sediment input / PPSE / PNSE conservation tillage / mulch seed / direct seed

inter crop cultivation

crop sequence

eduction of slope length

structure of edges (cropland, waters)

land use change

dissolved N-input DN inter crop cultivation

mineral fertilizers / farm manure

crop sequence

organic farming

humus-N temperature (climate change)

live stock

management of by-product

management of fermenting residues (energy crops)

diffuse input on sealed areas

dissolved P-input DP/ dissolved N-input DN grade of connection to public sewage treatment plant

share of housings with direct discharge, small sewage works, cesspit

P elimination of small sewage works, sewage treatment plants

additional building of sewage treatment plants

point-related inputs

sewage treatment plants design capacity

demographic change decreasing number of inhabitants

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Chapter 8 : Decision support / scenarios

9 References

Ad-hoc-AG Boden (2003): Bodenkundliche Kartieranleitung, 5. Aufl., Hannover.

Ad-hoc-AG Boden (2003): Methodendokumentation Bodenkunde – Auswertungsver-fahren zur Beurteilung der Empfindlichkeit und Belastbarkeit von Böden. Ergän-zungsblatt zu Kennwert 4.6 Mittlere jährliche Sickerwasserrate aus dem Boden, Bun-desanstalt für Geowissenschaften und Rohstoffe (BGR), Hannover.

Akkermann, M. (2004): Beurteilung des Einflusses einer angepassten Ackernutzungauf den Hochwasserabfluss. Diss., Hannover.

Albrecht, K., Grunewald, K., Halbfaß, S. (2002): Untersuchungen von Phosphorein-trägen aus Siedlungsgebieten in Oberflächengewässer, Geoöko, 23 (4), p.269-277.

Allen, R.G., Pereira, L.S., Raes, D., Smith, M. 1998. Crop Evapotranspiration –Guidelines for computing crop water requirements, FAO Irrigation and DrainagePaper No. 56.

Arman, B.; Billen, N.; Häring, G. (2002): Ein Nährstoff macht sich vom Acker. Ökolo-gische und betriebswirtschaftliche Bewertung von Nitratverlusten und Maßnahmenzu deren Verminderung, In: Selbstverlag, Uni Hohenheim.

Auerswald, K. (1988): Predicting nutrient enrichment from long term average soilloss, Soil Techn., 2, p.271-277.

Auerswald, K. (1997): Feststofftransport in Fließgewässern. . In: Blume H.-P.; Felix-Henningsen P.; Fischer W.R.; Frede H.-G.; Horn R. Stahr K. (Hrsg.): Handbuch derBodenkunde, ecomed, Landsberg/Lech, 3. Erg. Lfg., 12 S.

Auerswald, K. (2000): Bodenerosion - Ursachen, Schutzmassnahmen und Prognose,Vorsorgender Bodenschutz, Ministerium für Umwelt und Forsten Rheinland-Pfalz,p.17-26.

Auerswald, K. (2002): Schätzung des C-Faktors aus Fruchtartenstatistiken für Acker-flächen in Gebieten mit subkontinentalem bis subatlantischem Klima nördlich der Al-pen, Landnutzung Landentwicklung, 43, p.1-5.

Auerswald, K. & Schwertmann, U. (1988): Modelle zur Erosionsvorhersage als Ent-scheidungsgrundlage des Bodenschutzes. In: Rosenkranz, D., Bachmann, G., Einse-le, G., Harreß, H.M. [Hrsg.]: Bodenschutz, Berlin, Erich Schmidt Verlag.

Auerswald, K., Weigand, S., (1999): Eintrag und Freisetzung von P durch Erosions-material in Oberflächengewässern. VDLUFA-Schriftenreihe 50/1999.

Bach, M., Grimm, M, Frede, H.G. (2003): Berechnung von Stickstoff-Flächenbilanzenfür Gemeinden – Beispiel Hessen. In Wasser & Boden, 55/7+8, 120-126.

BAW (2005): Phosphataustrag aus landwirtschaftlich genutzten Flächen in Oberös-terreich. Endbericht, Bundesamt für Wasserwirtschaft, Wien.

Behrendt, H., Kornmilch, M., Opitz, D., Schmoll, O., Scholz, G., Uebe, R. (2002):Estimation of the nutrient inputs into river systems- experiences from German rivers.In: Regional Environmental Changes 3, 107-117.

Seite 42 von 56

Chapter 9 : References

Behrendt, H.; Bach, M.; Huber, P. et al. (1999): Nährstoffbilanzierung der Flussgebie-te Deutschlands. UBA-Texte 75/99, Umweltbundesamt, Berlin.

Behrendt, H.; Opitz, D. (2000): Retention of nutrients in river systems: dependenceon specific runoff and hydrolic load. Hydrobiol., 410, 111-122.

Bohner, A. (2008): Phosphor-Pools und Phosphor-Verfügbarkeit im Grünlandbodenals Basis für Phosphor-Düngeempfehlungen. Umweltökologisches Symposium, 4./5.März 2008, Raumberg-Gumpenstein, Irdning.

Bohner, A.; Eder, G.; Schink, M. (2007): Nährstoffkreislauf und Stoffflüsse in einemGrünland-Ökosystem. 12. Gumpensteiner Lysimetertagung, 17./18. April 2007, Ird-ning, Österreich.

Boulton, A.J.; Findlay, S.; Marmonier, P.; Stanley, E.H.; Valett, H.M. (1998): Thefunctional significance of the hyporheic zone in streams and rivers. Annu. Rev. Ecol.Syst., 29, 59-81.

Bowes, M.J.; House, W.A.; Hodgkinson, R.A. (2003): Phosphorus dynamics along ariver continuum. Sci. Tot. Environ., 313, 199-212.

Bowes, M.J.; House, W.A.; Hodgkinson, R.A.; Leach, D.V. (2005): Phosphorus–discharge hysteresis during storm events along a river catchment: the River Swale,UK. Wat. Res., 39, 751-762.

Brisson, N., Mary, B., Ripoche, D., Jeuffroy, M.H., Ruget, F., Gate, P., Devienne, F.,Antonioletti, R., Durr, C., Nicoullaud, B., Beaudoin, N., Recous, S., Tayot, X., Plenet,D., Richard, G., Cellier, P., Machet, J.M., Meynard, J.M. and Delécolle, R. (1998):STICS : a generic crop simulation model with water and nitrogen balance. Applicationto wheat and maize. I. Theory and parameterization. Agronomie, 22, 1, pp. 69-92.

Bundt, M. (2000): Highways Through the Soil. Properties of Preferential Flow Pathsand Transport of Reactive Compounds. Diss., ETH Zürich.

Carter, J., Owens, P.N., Walling, D.E., Leeks, G.J.L. (2003): Fingerprinting suspen-ded sediment sources in a large urban river system, The Science of the Total Envi-ronment, 314-316, p.513-534.

Chapman, A.S.; Foster, I.D.L.; Lees, J.A.; Hodgkinson, R.A.; Jackson, R.H. (2001):Particulate phosphorus transport by sub-surface drainage from agricultural land inthe UK. Environmental significance at the catchment and national scale. Sci. Tot. En-viron., 266, 95-102.

COST Action 869 (2006): Mitigation Options for Nutrient Reduction in Surface Waterand Groundwaters, 164th CSO Meeting 29-30 March 2006, Proposal for a newCOST Action.

Demars, B. O. L.; Harper, D. M.; Pitt, J.-A.; Slaughter, R. (2005): Impact of phospho-rus control measures on in-river phosphorus retention associated with point sourcepollution. Hydrol. Earth Sys. Sci., 9, 43–55.

Diepolder, M.; Raschbacher, S. (2007): Untersuchungen zur Stickstoff-, Phosphor-und Schwefelbelastung des Sickerwassers unter Dauergrünland. 12. GumpensteinerLysimetertagung, 17./18. April 2007, Irdning, Österreich.

Seite 43 von 56


Diepolder, M.; Raschbacher, S.; Ebertseder, T. (2005): P-Austrag aus Drainagen un-ter Wirtschaftsgrünland. SuB Heft 12/05, Seite III 6-11.

Djodjic, F.; Börling, K.; Bergström, L. (2004): Phosphorus Leaching in Relation to SoilType and Soil Phosphorus Content. J. Environ. Qual. 33:678–684.

Duttmann, R. (1999): Partikuläre Stoffverlagerungen in Landschaften. Ansätze zurflächenhaften Vorhersage von Transportpfaden und Stoffumlagerungen auf verschie-denen Maßstabsebenen unter besonderer Berücksichtigung räumlich-zeitlicher Än-derungen der Bodenfeuchte, Geosynthesis 10, Universität Hannover.

EU (2000): Richtlinie 2000/60/EG des Europäischen Parlaments und des Rates vom23. Oktober 2000 zur Schaffung eines Ordnungsrahmens für Maßnahmen der Ge-meinschaft im Bereich der Wasserpolitik, Amtsblatt der Europäischen Gemeinschaftvom 22.12.2000 L 327/1.

FAO-Unesco (1974): Map of the world, Vol. 1, Legend, Paris.

Freistaat Sachsen (1999): Bodenatlas des Freistaates Sachsen, Teil 3 – Boden-messprogramm, Bodenmessnetz Raster 4 km x 4 km, Materialien zum Bodenschutz,

Freistaat Sachsen (2004): Landwirtschaftlicher Bodenschutz. Schriftenreihe derSächsischen Landesanstalt für Landwirtschaft, Heft 10 – 9. Jahrgang 2004.

Galler, J. (2006): Phosphat – Düngung und Eutrophierung. LandwirtschaftskammerSalzburg, 32p.

Gauger, T., Anshelm, F., Schuster, H., Erisman, J.W., Vermeulen, A.T., Draaijers,G.P.J., Bleeker, A., Nagel, H.D. (2002): Mapping of ecosystem specific long-termtrends in deposition loads and concentrations of air pollutants in Germany and theircomparison with Critical Loads and Critical Levels, Final Report on behalf of FederalEnvironmental Agency (Umweltbundesamt), Berlin. BMU/UBA FE-No 299 42 210.Part 1: Deposition Loads 1990-1999.

Gauger. T.; Haenel, H.-D.; Rösemann, C.; Dämmgen, U.; Bleeker, A.; Erisman, J.W.;Vermeulen, A.T. (2008): National Implementation of the UNECE Convention onLong-range Transboundary Air Pollution (Effects), Teil 1: Deposition Loads: Metho-den, Modellierung und Kartierungsergebnisse, Trends. Umweltforschungsplan desBundesministeriums für Umwelt, Naturschutz und Reaktorsicherheit, Abschlußbe-richt, FKZ 204 63 252, UBA, Dessau.

Gebel, M. (2003): Die Berücksichtigung von N-Umsatzprozessen auf Ackerflächenbei der Quantifizierung von Stickstoffeinträgen in Flussgebieten mit dem ModellSTOFFBILANZ, Geoöko, 24 (3-4), p.249-259.

Gebel, M., Halbfaß, S., Grunewald, K., Kaiser, M., Bürger, S. (2007): STOFFBILANZ– Modellerläuterung. Adresse: http://www.stoffbilanz.de

Gebel, M., Kaiser, M., Korte, S., Lambrecht, H., Finck, M. (2005): Calculation of diffu-se seepage loads of nitrogen in the Upper Rhine valley using the STOFFBILANZ mo-del, In: EWRA 6th International Conference: Sharing a common vision of our waterresources, Conference Proceedings, 1-20.

Gebel M., Halbfaß S., Bürger S., Friese H., Naumann S. (2010): Modelling ofnitrogen turnover and leaching in Saxony, Adv. Geosci., 27, 139-144

Seite 44 von 56


Gebel M., Halbfaß S., Bürger S., Lorz C. (2013): Long-term simulation of effects ofenergy crop cultivation on nitrogen leaching and surface water quality inSaxony/Germany. Reg Environ Change, 13: 249-261.

Gebel M., Meißner R., Halbfaß S., Hagenau J., Duan S. (2014): Web GIS-basedsimulation of water fluxes in the Miyun catchment area. IFOREST-BIOGEOSCIENCES AND FORESTRY, doi: 10.3832/ifor1169-007

Gebel M., Uhlig, M., Halbfass, S., Meißner R., Duan, S. (2014): Predicting erosionand sediment yield in a mesoscale basin in the semiarid monsoon regionMiyun/China. Ecological Processes, 3: 5, DOI: 10.1186/2192-1709-3-5

Gebel M., Friese, H., Kurzer H.-J. (2015): Modellgestützte Wirkungsabschätzung vonMaßnahmen zur Minderung von Phosphoreinträgen in die Gewässer. In: DWALandesverband Sachsen/Thüringen (Hrsg.): Phosphor – Problem oder Chance?Innovationen der Wasserwirtschaft, 27-36.

Gebel M., Bürger S., Halbfaß S., Uhlig M. (2016): Modellgestützte Ermittlung derNährstoffeinträge in sächsische Gewässer – Status quo und Ausblick bis 2027.Herausgeber: Sächsisches Landesamt für Umwelt, Landwirtschaft und Geologie, 102S.

Gebel M., Bürger, S., Wallace, M., Malherbe H., Vogt H., Lorz C. (2017): Simulationof land use impacts on sediment and nutrient transfer in coastal areas of WesternCape, South Africa. In: Change Adaptation Socioecol. Syst. 2017; 3: 1–17

Ghadiri, H. & Rose, C.W. (1991a): Soil processes and chemical transport. Sorbedchemical transport in overland flow. 1. A nutrient and pesticide enrichment mecha-nism, J. Environ. Qual., 20, p.628-633.

Ghadiri, H. & Rose, C.W. (1991b): Soil processes and chemical transport. Sorbedchemical transport in overland flow. 2. Enrichment ratio variation with erosion pro-cess, J. Environ. Qual., 20, p.634-641.

Guhr, H.; Meissner, R. (2000): Phosphorumsatz und -retention in Fließgewässern.DBG, Bd. 92, 163-166.

Haggard, B.E.; Sharpley, N. (2007): Phosphorus Transport in Streams: Processesand Modeling Considerations. In: Radcliffe, D.E.; Cabrera, M.L. (Ed.)(2007): Mode-ling Phosphorus in the Enviroment. CRC Press, Boca Raton, pp. 105-130.

Halbfaß (2005): Entwicklung eines GIS-gestützten Modells zur Quantifizierung diffu-ser Phosphoreinträge in Oberflächengewässer im mittleren Maßstab unter besonde-rer Berücksichtigung geoökologisch wirksamer Raumstrukturen, TU Dresden, Beiträ-ge zur Landschaftsforschung, Bd. 1, Rhombos-Verlag, Berlin.

Halbfass, S. (2005): Entwicklung eines GIS-gestützten Modells zur Quantifizierungdiffuser Phosphoreinträge in Oberflächengewässer im mittleren Maßstab unter Be-rücksichtigung geoökologisch wirksamer Raumstrukturen. Diss., Rhombos-Verlag,Bd. 1, Berlin.

Halbfaß, S. & Grunewald, K. (2004): Räumliche Variabilität der Phosphorgehalte imOberboden landwirtschaftlich genutzter Flächen in kleinen Einzugsgebieten, J. PlantNutr. Soil Sci., 166, p.197-203.

Seite 45 von 56


Halbfaß, S. & Grunewald, K. (2006): Abschätzung potenzieller Herkunftsflächen vonerosionsbedingten Stoffeinträgen in Oberflächengewässer im mittleren Maßstab,Wasserwirtschaft, 12, p.28-32.

Halbfaß, S. & Grunewald, K. (2008): Ermittlung räumlich verteilter Sediment DeliveryRatio zur Modellierung von Sedimenteinträgen in Fließgewässer im mittleren Maß-stab, Wasserwirtschaft, 3, p.31-35.

Halbfaß S., Gebel M., Bürger S. (2010): Modelling of long term nitrogen retention insurface waters, Adv. Geosci., 27, 145-148

Hawkins, R.H., Ward, T.J., Woodward, D.E., Van Mullem, J.A. 2009. Curve NumberHydrology: State of the Practice. American Society of Civil Engineers, Reston,Virginia.

Heathwaite, A.L.; Dils, R.M. (2000): Characterising phosphorus loss in surface andsubsurface hydrological pathway. Sci. Tot. Environ., 251/252, 523-538.

Hirt, U., Burghard, C.M., Hammann, T. (2005): Proportions of subsurface drainageareas - methodological study in the Middle Mulde catchment (Germany), J. Plant Nu-tr. Soil Sci., 168, p.375-385.

House, W.A. (2002): Geochemical cycling of phosphorus in rivers. App. Geochem.,18, 739-748.

Huber, B.; Winterhalter, M.; Mallen, G.; Hartmann, H.P.; Gerl, G.; Auerswald, K.;Priesack, E.; Seiler, K.-P. (2005): Wasserflüsse und wassergetragene Stoffflüsse inAgrarökosystemen. In: Osinski et al. (2005). Landwirtschaft und Umwelt – ein Span-nungsfeld. FAM, München.

Hülsbergen, K.J. & Diepenbrock, W. (1997): Das Modell REPRO zur Analyse undBewertung von Stoff- und Energieflüssen in Landwirtschaftsbetrieben. In: DBU[Hrsg.]: Umweltverträgliche Pflanzenproduktion – Indikatoren, Bilanzierungsansätzeund ihre Einbindung in Ökobilanzen, 159-185, Zeller Verlag, Osnabrück.

Jedele und Partner GmbH (2007): Ermittlung von Stofffrachten aus Abwassereinlei-tungen in Oberflächengewässer (punktuelle Einträge). Bericht, AG: Thüringer Minis-terium für Landwirtschaft, Naturschutz und Umwelt, 124pp.

Jin H.S.; Ramsey, J.B.; White, D.S. (2007): Nutrient Uptake and Retention Patternsin Two Streams with Contrasting Watershed Landuse. J. Ky. Acad. Sci., 68(1), 24-30.

Jonge, L.W.; Moldrup, P.; Rubæk, G. H.; Schelde, K. ; Djurhuus, J. (2004): ParticleLeaching and Particle-Facilitated Transport of Phosphorus at Field Scale. VadoseZone Journal 3:462–470.

Kaiser, M. & Gebel, M. (2003): Quantifizierung diffuser Stoffeinträge mit dem ModellSTOFFBILANZ in einem bewaldeten Gewässereinzugsgebiet im Mittelgebirge, Geo-öko, 24 (3-4), p.262-269.

Kielhorn, C. (2005): Massnahmen zur Reduzierung des Sedimenteintrages einesGeestgewässers am Beispiel des Börnsengrabens - Herzogtum Lauenburg, Dipl.-ar-beit, Hamburg.

Seite 46 von 56


Kinnell, P.I.A. 2001. The USLE-M and Modeling Erosion Within Catchments. In: Stott,D.E., Steinhardt G.C. (eds): Sustaining the Global Farm. Selected papers from the10th International Soil Conservation Organiza-tion on Meeting held May 24-29, 1999at Perdue University and the USDA-ARS National Soil Erosion Re-search Laboratory

Klein, J.J.M. de (2008): From ditch to delta : nutrient retention in running waters.WUR Wageningen, p. 194.

Koch, R. (2007): Uferzonen von Fließgewässern in Kleineinzugsgebieten der RegionBasel. Diss., Basel.

Kretschmar, R. (1977): Stofftransport in ländlichen Entwässerungsgräben und Vorflu-tern. Landwirtschaftliche Forschung, 3, 231-238.

Kronvang, B.; Grant, R.; Laubel, A.L. (1997): Sediment and phosphorus export froma lowland catchment: Quantification of sources. Water Air Soil Poll., 99, 465-476.

Krüger, F.; Schwartz, R.; Kunert, M.; Friese, K. (2006): Methods to calculate sedi-mentation rates of floodplain soils in the middle region of the Elbe River. Acta hydro-chim. hydrobiol., 34, 175-187.

Kunkel, R., Wendland, F. (1999): Das Weg-/Zeitverhalten des grundwasserbürtigenAbflusses im Elbeeinzugsgebie. Schriften des Forschungszentrums Jülich, ReiheUmwelt/Environment, Vol. 19.

Kunst, S., Scheer, C., Panckow, N. (2004): Signifikante Nährstoffeinträge aus derFläche, ATV-DVWK e.V., ATV-DVWK-Themen, Hennef.

Lammers, A. (1997): Phosphatformen und Phosphatfreisetzung in hochgedüngtenBöden Europas, Diss., Agrarwissenschaften München.

LAP (2004): Stickstoff-Düngeberatungssystem des Landes Baden-Württemberg –Düngeberechnung für Acker- und Sonderkulturen. Landesanstalt für PflanzenbauForchheim / Infodienst Bad.- Württemberg.

LfUG (2004): Emissionsbericht Abwasser. Bestandsaufnahme der Abwasseremissio-nen im Freistaat Sachsen. Datenstand 2001. Landesamt für Umwelt und Geologie,Dresden.

LfUG (2007): Emissionsbericht Abwasser. Zweite Bestandsaufnahme der Abwasse-remissionen im Freistaat Sachsen 2005/2006. Landesamt für Umwelt und Geologie,Dresden.

Liebscher, H.J. & Keller, R. (1979): Abfluss, In: Hydrologischer Atlas der BRD (Text-band), hrsg. i. Auftrag der Dt. Forschungsgemeinschaft, Bonn.

Maniak, U. (2005): Hydrologie und Wasserwirtschaft - Eine Einführung für Ingenieu-re, Springer, Berlin Heidelberg.

Maniak, U. (2005): Hydrologie und Wasserwirtschaft – Eine Einführung für Ingenieu-re. Springer, Berlin Heidelberg.

Marcé, R.; Armengol, J. (2009): Modeling nutrient in-stream processes at the water-shed scale using Nutrient Spiralling metrics. Hydrol. Earth Syst. Sci. Discuss., 6,501–533.

Seite 47 von 56


Mary, B. and Guérif, J. (1994): Intérêts et limites des modèles de prévision de l' évo-lution des matières organiques et de l'azote dans le sol, Cahiers Agricultures, 3, 247-257

Meissner R., Gebel M., Hagenau J., Halbfass S., Engelke P., Giessler M., Duan S.,Lu B., Wang X. (2016): WebGIS-based approach to simulate water and solute fluxesin the Miyun basin in China. In: Borchardt D., Bogardi J., Ibisch R. (Eds.): IntegratedWater Resources Management: Concept, Research and Implementation, 515-539,Springer.

Meynard, J.M. and Justes, E. and Machet, J.M. and Recous, S. (1996): Fertilisationazotée des cultures annuelles de plein champ, In: Lemaire, G. \& Nicolardot, B.(Eds.): Maitrise de l'azote dans les agro-systèmes. Les colloques de l'INRA, INRA,Reims, 183-199

Miller, R.; Peter, M.; Bräunig, A. (2007): Bodenatlas des Freistaates Sachsen Teil 4:Auswertungskarten zum Bodenschutz – Erläuterungsheft, Materialien zum Boden-schutz, hrsg. v. LfUG Sachsen

Mischke, U.; Opitz, D.(2005): Endbericht zum LAWA-Vorhaben Entwicklung einesBewertungsverfahrens für Fließgewässer mittels Phytoplankton zur Umsetzung derEU-Wasserrahmenrichtlinie. IGB, Berlin.

Mokry, M. (1999): Austrag von gelöstem Orthophosphat aus Drainagen unterschied-lich hoch mit Phosphor versorgter Ackerflächen. 8. Gumpensteiner Lysimetertagung,13. und 14. April 1999, Bundesanstalt für alpenländische Landwirtschaft Gumpen-stein, A-8952 Irdning.

Mokry, M. (2003): Makroporen-Transport von Phosphor nach Gülleausbringung aufLöß- und Tonböden. 10. Gumpensteiner Lysimetertagung, 29. und 30. April 2003,Bundesanstalt für alpenländische Landwirtschaft Gumpenstein, A-8952 Irdning.

Mulholland, P.J. (1992): Regulation of nutrient concentrations in a temperate foreststream: Roles of upland, riparian and instream processes. Limnol. Oceanogr., 37(7),1512-1526.

Nagel, H.D. & Gregor, H.D. (1999): Ökologische Belastungsgrenzen: Ein Internatio-nales Konzept für die Luftreinhaltepolitik (Critical Loads \& levels), Springer, BerlinHeidelberg.

Newbold, J.D.; Elwood, J.W.; O`Neill, R.V.; Sheldon, A.L. (1983): Phosphorus dyna-mics in a woodland stream ecosystem – A study of nutrient spiralling. Ecol. 64, 1249-1265.

Nitzsche, O.; Schmidt, W.; Richter, W. (2000): Minderung des P-Abtrags von Acker-flächen durch konservierende Bodenbearbeitung. Mitt. Dtsch. Bodenkdl. Ges., 92:178-181.

NRCS - Natural Resources Conservation Service 2004. National EngineeringHandbook Part 630 Hydrology – Estimation of Direct Runoff from Storm Rainfall,United States Department of Agriculture.

Prasuhn, V. (2003): Abschätzung der Phosphoreinträge aus diffusen Quellen in denGreifensee, FAL.

Seite 48 von 56


Prasuhn, V. (2003): Abschätzung der Phosphoreinträge aus diffusen Quellen in denGreifensee. Bericht FAL, Zürich.

Prasuhn, V. (2008): Phosphorabschwemmung von Graslandflächen in der Schweiz -Eintragspfade und Massnahmen zur Reduzierung. 2. Internationale Seenfachtagung,Bad Schussenried, 8.-9.10.2008.

Pudenz, S. (1998): Modellierung der regionalen Phosphorverlagerung im Boden undGrundwasser. Diss., TU Berlin.

Richter, D. (1995): Ergebnisse methodischer Untersuchungen zur Korrektur des sys-tematischen Messfehlers des Hellmann-Niederschlagsmessers, Berichte des Deut-schen Wetterdienstes, 194, Ofenbach.

Röder, M. (1997): Erfassung und Bewertung anthropogen bedingter Änderungen desLandschaftswasserhaushaltes - dargestellt an Beispielen aus der Westlausitz, Dis-sertation, TU Dresden.

Schäfer, M. (1999): Regionalisierte Stoffstrombilanzen in städtischen Einzugsgebie-ten - Möglichkeiten, Probleme und Schlussfolgerungen, Universität Karlsruhe, Inst. f.Siedlungswasserwirtschaft.

Schaub, D. & Wilke, B. (1996): Phosphatanreicherung bei der Bodenerosion, Mitt.Dtsch. Bodenkdl. Ges., 79, p.435-438

Schliephake, W. & Albert, E. (2003): Vermeidung von Stickstoffverlusten. Schriften-reihe der Sächsischen Landesanstalt für Landwirtschaft, Heft 9, Dresden.

Schmidt, W. (2006): Einfluss der konservierenden Bodenbearbeitung auf den Stof-faustrag über Makroporen, Sächsische Landesanstalt für Landwirtschaft, Leipzig.

Schmidt, W. (2008): Einfluss der konservierenden Bodenbearbeitung auf den Stof-faustrag über Makroporen. Sächsische Landesanstalt für Landwirtschaft, Leipzig.

Schonlau, H.U. (2007): Zeitskalenübergreifende Berücksichtigung von partikuläremStofftransport in einer Langfrist-Gewässergüteprognose für Flieÿgewässer. Diss., THAachen.

Schulz, M.; Bischoff, M.; Klasmeier, J.; Berlekamp, J.; Matthies, M. (2008): An empiri-cal regression model of soluble phosphorus retention for small pristine streams eva-luating tracer experiments. Aquat. Sci. 70, 115-122.

Schwartz, R.; Krüger, F.; Kozerski, H.P. (2004): Bilanzierung des Schwebstoffrück-halts der unteren Mittelelbe in Fluss und Aue. DGL-Tagungsbericht, Berlin, 239-244.

Schwarze, R. (2004): Regionalspezifische Analysen in der Festgesteinsregion, In:Becker, A. u. Lahmer, W. [Hrsg]: Wasser- und Nährstoffhaushalt im Elbegebiet undMöglichkeiten zur Stoffeintragsminderung. Weißensee-Verlag, Berlin, p.183-224.

Sekely, A.C.; Mulla, D.J.; Bauer, D.W. (2002): Streambank slumping and its contribu-tion to the phosphorus and suspended sediment loads of the blue earth river, minne-sota. Journal of Soil and Water Conservation September 2002 vol. 57 no. 5 243-250.

Sharpley, A.N., Daniel, T.C., Edwards, D.R. (1993): Phosphorus movement in thelandscape, J. Prod. Agri., 6 (4), p.492-500.

Seite 49 von 56


Sharpley, A.N.; Daniel, T. ; Sims, T. ; Lemunyon, J.; Stevens, R. ; Parry, R. (1999):Agricultural Phosphorus and Eutrophication. United States Department of Agriculture,Agricultural Research Service, ARS–149.

SLfL [Hrsg.](2007): Umsetzung der Düngeverordnung – Hinweise und Richtwerte fürdie Praxis. Sächsische Landesanstalt für Landwirtschaft, Dresden.

SMUL (2006): Lagebericht 2006. Kommunale Abwasserbeseitigung im FreistaatSachsen. Staatsministerium für Umwelt und Landwirtschaft, Dresden.

Strauss, P. (2008): Ackerbauliche Maßnahmen zur Reduktion von Schwebstoff- undPhosphoreintrag in Gewässer. 2. Internationale Seenfachtagung, Bad Schussenried,8.-9.10.2008.

Stream Solute Workshop (1990): Concepts and methods for assessing solutedynamics in stream ecosystems. Journal of the North American Bentological Society.Vol. 9, No. 2, 95-119.

Sukopp, H. & Wittig, R. (1998): Stadtökologie - ein Fachbuch für Studium und Praxis,Gustav Fischer Verlag, Stuttgart.

Tetzlaff, B. (2006): Die Phosphatbelastung großer Flusseinzugsgebiete aus diffusenund punktuellen Quellen. Diss., Schriften d. FZ Jülich, Reihe Umwelt, Band 65.

UBA [Hrsg.] (1996): Manual on methodologies and criteria for mapping criticallevels/loads and geographical areas where they are exceeded, Coordination Centerfor Effects and the Secretariat of the United Nations Economic Commission for Euro-pe, UBA-Texte 71/96, Berlin.

Uhlig, M. (2008): Mesoskalige Modellierung von Verweilzeiten und Nitratabbau imoberen Grundwasserleiter in einem Testgebiet in Nordsachsen. Diplomarbeit, TUDresden.

Uhlig M., Gebel M., Halbfaß S., Liedl R. (2010): Mesoskalige Modellierung dergrundwasserbürtigen Nitratbelastung von Fließgewässern. Grundwasser 15(3):163-176, Springer.

Ullrich, J. (2006): Berücksichtigung von Stickstoffumsatzprozessen im Grundwassermit dem Modell STOFFBILANZ, Dipl.-arbeit, TU Dresden.

University of Wisconsin-Extension (1997): Urban Runoff - A Source of Concern,GWQ020, Madison.

US SCS (1972): National engineering handbook (Chap 4: Hydrology, 2nd reprint),US Dept. Agriculture, Washington.

van der Lee, G. E. M.; Venterink, H.O.; Asselman, N. E. M. (2004): Nutrient retentionin floodplains of the Rhine distributaries in the Netherlands. River Res. Applic., 20,315–325.

van Es, H.M.; Schindelbeck, R.R.; Jokela, W.E. (2004): Effect of Manure ApplicationTiming, Crop, and Soil Type on Phosphorus Leaching. J. Environ. Qual. 33:1070–1080.

Veith, T.L. (2002): Agricultural BMP placement for cost-effective pollution control atthe watershed level, Virginia Polytechnic Institute and State University.

Seite 50 von 56


Venterink, H.O.; Wiegman, F.; Van der Lee, G. E. M.; Vermaat, J. E. (2003): Role ofActive Floodplains for Nutrient Retention in the River Rhine. J. Environ. Qual., 32,1430–1435.

Voges, J. (1999): Empirisches Modell für die mittlere Maßstabsebene zur GIS-ge-stützten Bestimmung der Anbindung erosionsgefährdeter Ackerflächen an Fließge-wässer, Diss. Univ. Hannover.

Walling, D.E.; He, Q. (1994): Rates of overbank sedimentation on the flood plains ofseveral British rivers during the past 100 years. Variability in Stream ans SedimentTransport, IAHS Publ., 224, 203-210.

Weißbach, F. (1995): Über die Schätzung des Beitrags der symbiontischen N2-Fixie-rung durch Weißklee zur Stickstoffbilanz von Grünlandflächen, LandbauforschungVölkenrode, 45 (2), p.67-74.

Wendland, F. (1992): Die Nitratbelastung in den Grundwasserlandschaften der altenBundesländer (BRD), Berichte aus der ökologischen Forschung, Bd. 8.

Wendland, F. & Kunkel, R. (1999): Das Nitratabbauvermögen im Grundwasser desElbeeinzugsgebietes, Schriften des Forschungszentrums Jülich, Reihe Umwelt/Envi-ronment, Bd. 13.

Wendland, F., Albert, H., Bach, M., Schmidt, R. (1993): Atlas zum Nitratstrom in derBundesrepublik Deutschland, Springer-Verlag, Berlin, Heidelberg, New York.

Wessolek, G. (1997): Abschätzung der Grundwasserneubildung von Hangstand-orten. Erstellt im Auftrag der Bundesanstalt für Geowissenschaften und Rostoffe, un-veröff., Hannover.

Wessolek, G., Duijnisveld, W.H.M., Trinks, S. (2008): Hydro-pedotransfer functions(HPTFs) for predicting annual percolation rate on a regional scale. Journal of Hydro-logy 356, 17-27.

Wiegand, U. (2002): Hydro- und geochemische Prozesse in oberflächennahen Kip-pensedimenten des Braunkohlentagebaus Zwenkau, UFZ-Bericht 6/2002.

Wischmeyer, W.H. & Smith, D.D. (1978): Predicting rainfall losses - a guide to con-servation planning, USDA Agriculture Handbook, 537, p.1-58.

Withers, P.J.A.; Jarvie, H.P. (2008): Delivery and cycling of phosphorus in rivers: Areview. Sci. Tot. Environ., 400, 379-395.

Wollheim, W.M.; Vörösmarty, C.J.; Peterson, B.J.; Seitzinger, S.P.; Hopkinson, C.S.(2006): Relationship between river size and nutrient removal. Geophysic. Res. L., 33,L06410.

Wu, S., Li, J., Huang, G. (2005): An evaluation of grid size uncertainty in empiricalsoil loss modelling with digital elevation models, Environmental Modelling and As-sessment, 10 (1), p.33-42.

Yu, B. & Rosewell, C.J. 1996. A robust estimator of the R-factor for the universal lossequation, American Soci-ety of Agricultural Engineers 0001-2351 / 96 / 3902-0559,Vol. 39(2): 559-561.

Seite 51 von 56


Zaimes, G.N.; Schultz, R.C.; Isenhart, T.M.; Mickelson, M.K.; Kovar, J.L.; Russell,J.R.; Powers, W.P. (2005): Stream bank erosion under different riparian land-usepractices in northeast Iowa. AFTA 2005 Conference Proceedings.

Zimmermann, F. (2003): Einfluss unterschiedlicher Bodenbearbeitung von Ackerflä-chen auf den sickerwassergebundenen Stofftransport – untersucht mit Hilfe von Ex-perimenten an Bodensäulen. Diplomarbeit. Universität Leipzig.

10 Appendix

Table 17: Input parameters in the STOFFBILANZ model

Parameter description

Land use type Main land use type5

Grade of sealing Aseal Grade of sealing [%]

Soil texture Main soil texture6

Soil type Main soil type7

Skeleton content csk Average content of skeleton in topsoil [%]

Pt P-content in topsoil [mg kg-1]

Content of humus chumus Content of humus in topsoil [%]

C/N-ratio C/N-ratio in topsoil

Raw density SBD Raw density [%]

slope Average slope [°]

exposure Main exposure

Precipitation in winter Pwinter Precipitation in winter (okt. - march) [mm yr-1]

Precipitation in summer Psummer Precipitation in summer (april– sept.) [mm yr-1]

ETp FAO-grass-reference precipitation [mm yr-1]

Average annual temperature Tavg Average annual temperature [°C]

Natm Atmospheric deposition (dry and wet)

elevation Average elevation [m above NN]

Distance to waters Average distance to the next tributary [m]

Hydraulic connection Hydraulic connection (GIS-preprocessing)

Rainy days Average number of rainy days with a precipitation ≥ 1mm

Mineral fertilizer Fmin Fruit type specific mineral fertilizer [kg N ha-1 yr-1)]

Farm manure Forg Farm manure [kg N ha-1 yr-1)]

yield Fruit type specific yield [dt/ha]

5 Cropland, grassland, fruit-growing, viticulture, decidous forest, coniferous forest, settlement/urbanarea, waters, undefined land use

6 According to Ad-hoc-AG Boden (2005)7 According to Ad-hoc-AG Boden (2005)

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Chapter 10 : Appendix

Table 18: Input data of validation

data description

Point-related nutrient inputs Data to public and industrial sewage treatment plants

Measured data in surface waters N- und P-loads and concentrations

Measured runoff data Discharges

Reservoirs / lakes Characterising data (e.g. mean depth, hydraulic resi-dence time)

Measured data in groundwater Nitrate concentrations in upper aquifers

Table 19: Types of fruit and prefixes

Parameter description

Winter wheat (qw) Winter wheat (14-16% crude protein)

Winter wheat (ww) Winter wheat (12% crude protein)

Winter barley (wb) Winter barley

Winter rye (wr) Winter rye, triticale

Summer cereal (sc) Summer wheat, durum wheat, oats, summer rye, summer barley, spelt

Silo maize (sm) Silomaize, corn-cob-mix

Grain maize (gm) Grain maize

Rape (r) Rape

Further oil seeds (os) Mustard, linseed

potatoe (p) Potatoe

Root crops (rc) Sugar beet

sunflower (sf) Sunflower

Grain legumes (gl) Pea, lupin, bean

Fodder legumes (fl) Clover-gras, lucerne-gras

Crop grass (cg) Cropgrass

Intensive vegetables (iv) Intensive vegetables

Virginia-tobacco (vt) Virginia-tobacco

Dark air dried tobacco, burley-tobacco (dt)

Dark air dried tobacco, burley-tobacco

strawberries (st) Strawberries

asparagus (as) Asparagus

Intensive grassland (ig) Intensive meadows, pasture, grassland

Extensive grassland (eg) Extensive meadows, meadow orchard

Fallow Fallow

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Table 20: Soil textures in the STOFFBILANZ model (comp. Ad-hoc-AG Boden, 2005)

Soil textures, used in the STOFFBILANZmodel

(prefixes, description)

Corresponding soil textures according to Ad-hoc AG Boden (2005)

(prefixes)

ss, sandy sand Ss, gS, mS, fS, ffS

ls, loamy sand Su2, Sl2, Sl3, St2

us, silty sand Su3, Su4

sl, sandy loam Slu, St3, Sl4

su, sandy silt Us, Uu

lu, loamy silt Uls, Ut2, Ut3

ll, loamy loam Ls2, Ls3, Ls4, Lt2

tu, clay silt Ut4, Lu

tl, clay loam Ts3, Ts4, Lts

ut, silty clay Tu3, Tu4, Lt3

lt, loamy clay Ts2, Tl, Tu2, Tt

Hn, low moor -

Hh, peat bog -

F#, subhydric -

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Table 21: Soil types in the STOFFBILANZ model (compare Ad-hoc-AG Boden, 2005)

Prefixes of soil types german / english

Corresponding soil types (FAO-Unesco 1974)

F# Skeleton soil

O# / I Lithosol

RN / N Leptosol

RQ / R Regosol

T# / C Chernozem

P# / P Podzol

RR, RZ / E Rendzina, calcaric regosol

D# / V Vertisol

B# / B Cambisol

PP-BB / dystric B Podzolic cambisol

L# / L, D Luvisol, Podzoluvisol

C# / R Calcaric regosol

Y# Anthrosol, rigosol

SS-## / stagnic G-B Subtype with properties of stagnic gleysol (e.g.SS-BB)

GG-## / gleyic B Subtype with properties of gleysol (e.g. GG-BB)

A# / J Fluvisol

S# / stagnic G Stagnic gleysol

G# Gleysol

HN, HH / O Histosol

J# Subhydric soil

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Table 22: Derivation of percolation rate SW (according to Ad-hoc AG Boden 2003)

Land use type WV Regression formula

Cropland

Groundwater influence > 700 mm 700 mm

SW = Pyear – ET0 x 1,05 x [0,61 x log(1/ET0) + 2,66]SW = Pyear – ET0 x [1,45 x log(nFKWe + KA + Psummer) – 3,08]x [0,61 x log(1/ET0) + 2,66]

No groundwater influence > 700 mm 700 mm

SW = Pyear – ET0 x 1,05 x [0,76 x log (1/ET0) + 3,07]SW = Pyear – ET0 x [1,45 x log(nFKWe + Psummer) – 3,08] x[0,76 x log(1/ET0) + 3,07]

Grassland




SW = Pyear – ET0 x 1,20 x [0,66 x log(1/ET0) + 2,79]SW = Pyear – ET0 x [1,79 x log(nFKWe + Psummer) – 3,89] x[0,66 x log(1/ET0) + 2,79]

Coniferous forest




SW = Pyear – ET0 x [1,30 x [0,92 x (1/ET0) + 3,52]SW = Pyear – ET0 x 1,,68 x log(nFKWe + Psummer) – 3,53] x[0,92 x log(1/ET0) + 3,52]

Decidous forest


SW = Pyear – 0,90 x ET0 x 1,30 x [0,81 x log(1/ET0) +3,20]SW = Pyear – 0,90 x ET0 x [1,68 x log(nFKWe + KA + Psummer)– 3,53] x [0,81 x log(1/ET0) + 3,20]


SW = Pyear – 0,90 x ET0 x 1,30 x [0,92 x log(1/ET0) + 3,52]SW = Pyear – 0,90 x ET0 x [1,68 x log(nFKWe + Psummer) –3,53] x [0,92 x log(1/ET0) + 3,52]

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