Supplementary Information
Quantifying nitrogen leaching from diffuse agricultural and forest sources in a large heterogeneous catchment
Jiří Kopáček, Josef Hejzlar, Maximilian Posch
Part SI-1: Details to section “Site description and data sources”
Upper Vltava river catchment
This part summarizes details on the current land-use characteristics of the upper Vltava river catchment and their historical development. The boundaries of the administrative South Bohemian District refer to its area prior to 2000, when it consisted of 8 shires: České Budějovice, Český Krumlov, Jindřichův Hradec, Písek, Prachatice, Strakonice, Tábor, and Pelhřimov.
Fig. SI-1. Catchment of the upper Vltava river (grey area) and boundary of the administrative South Bohemian District (solid line) and their location in Europe. Numbers and abbreviations indicate the locations of hydrological stations and forested sub-catchments, respectively, used in this study (for details on their names, location, and elevation see Tables SI-3 and SI-5).
Table SI-1. Reservoirs and the largest fishpond (Rožmberk) in the upperVltava catchment (Broža et al., 2001).
Reservoir / Stream / Year of filling / Volume / Area / Mean depthmillion m3 / km2 / m
Rožmberk / Lužnice / 1590 / 13.8 / 4.89 / 2.8
Husinec / Blanice / 1939 / 5.6 / 0.57 / 9.9
Slapy / Vltava / 1957 / 269.3 / 13.92 / 19.3
Lipno I / Vltava / 1960 / 306.0 / 48.70 / 6.3
Lipno II / Vltava / 1960 / 1.7 / 0.45 / 3.8
Kamýk / Vltava / 1963 / 12.8 / 1.95 / 6.6
Orlík / Vltava / 1963 / 716.5 / 27.32 / 26.2
Římov / Malše / 1978 / 33.6 / 2.11 / 15.9
Humenice / Stropnice / 1988 / 0.8 / 0.15 / 5.4
Hněvkovice / Vltava / 1991 / 22.2 / 3.12 / 7.1
Part SI-2: Details to section “Site description and data sources”
Trends in agriculture (upper Vltava catchment and Czech Republic, 1950–2010)
Part SI-3: Details to section “Site description and data sources”
Nitrogen in organic fertilizers and biofixation of N2
Organic fertilizers – Annual amounts of organic fertilizers and associated N applied to the agricultural land of the upper Vltava catchment were calculated on the basis of annual numbers of dairy cows and other cattle, pigs, horses, sheep, goats, and poultry (Statistical Yearbooks of the Czech Republic), data on their production of manure and slurry, the respective N concentrations in these products, and losses during storage prior to application (Bouwman et. al. 1997; Smil 1999). We set the annual N production per animal head according to Smil (1999) as follows: 80, 50, 35, 10, 5, 0.3 kg N head–1 yr–1 for dairy cows, other cattle, pigs, horses, sheep (and goats), and poultry, respectively. The average N losses to the atmosphere were set according to Bouwman et. al. (1997) and Smil (1999) at 36% for cows, pigs, and poultry, and at 28% for horses, sheep, and goats. The resulting N fertilization rate of agricultural land, associated with organic fertilizers, increased from ~33 to 42 kg ha–1 yr–1 between 1959 and the late 1980s, and then declined to 21 kg ha–1 yr–1 in 2010 (Fig. SI-2E).
We checked this calculation using another approach, based on available statistical data on manure, liquid manure, and slurry production and application in the South Bohemian district and the average N concentrations in organic fertilizers in the CzechRepublic (Vostal and Matousch 1988). The calculation was based on animal units (AU = 500 kg of live animal weight; i.e., one cow or horse = 1 AU, one pig = 0.2 AU, one sheep or goat = 0.15 AU, and poultry = 0.004 AU). Numbers of AU varied between 0.54 and 1.11 ha–1 on an agricultural land area basis between 1959 and 2010 (following general trends in livestock production; Fig. SI-3), with cattle, pigs, poultry, and other livestock (horses, sheep, and goats) contributing 69–80%, 13–24%, 1.5–5%, and 1.5–8%, respectively. Statistical data on manure, liquid manure, and slurry production and application in the South Bohemian district were available for the 2000s (Statistical Yearbooks of the CzechRepublic). The average concentrations of N in these fertilizers were set as follows: 0.50% in manure, 0.21% in liquid manure, and 0.41% in slurry; all these concentrations included corrections for an average N loss to the atmosphere during storage and application of organic fertilizers (Vostal and Matousch 1988). The average N concentration in slurry was calculated as mass-weighted mean of the respective cattle, pig, and poultry contribution to the total slurry production in the Czech Republic (44, 47, and 9%) and their average N concentrations (0.29, 0.44, and 0.88% after correction for the N losses) (Vostal and Matousch 1988). Using these data, we calculated an annual average amount of N applied to agricultural land in organic fertilizers per one AU (41 kg AU–1 yr–1), and this value was kept constant for the whole 1959–2010 period due to the absence of more detailed historical data on N concentrations in manure and slurry. This calculation resulted in similar values of average N dose applied to agricultural land in the South Bohemian district with organic fertilizers as were those based on calculation according to Smil (1999) (Fig. SI-2E), with the respective results of 27 vs. 25 kg ha–1 yr–1 in the 2000s and 44 vs. 41 kg ha–1 yr–1 in the 1980s. Moreover, the calculated N inputs in organic fertilizers to the study agricultural land are reasonably close to their average for the whole CzechRepublic, estimated for the 1980s by Vostal and Matousch (1988) at 40 kg ha–1 yr–1.
Biofixation of atmospheric N2 – Significant quantities of Nr are introduced to the agricultural land via biological N fixation (BNF). The most important part of BNF is associated with symbiosis of the genus Rhizobium with leguminous plants, and its rate varies considerably within and among legume types (Galloway et al. 1995; Smil 1999). The commonly used averages of the areal BNF rates are 40, 150, 200, 50, and 5 kg ha–1 yr–1 for lentils, clover, lucerne (alfalfa), legume-grass mixtures, and grass at pastures (Vostal and Matousch 1988; Smil 1999). The amount of N biofixation is usually estimated from the legume cultivation area and the areal BNF rates of individual leguminous plants. The net soil enrichment with the fixed N is, however, lower than the total N fixation, because most of the aboveground biomass is harvested and used as fodder for livestock. A part of this aboveground N comes back to soils later in the form of manure and slurry. Not to include this N input to the agricultural land twice (in both BNF and organic fertilizers) we estimated the net areal N enrichment of soils from BNF by a plant i (NABNFi, kg ha–1 yr–1) as:
(SI-1)
where Mi (Mg ha–1) is the areal mass of roots and post-harvest residue of the plant i, Ci (kg Mg–1) the average N concentration in the plant, Pi the proportion of N in the plant originating from BNF, and Ti (yr) the average time of plant breeding in a field prior to its replacement with another crop. We used 1 year for legumes and annual fodder crops and 2 years for perennial fodder crops (red clover, lucerne, clover-grass, and lucerne-grass). The Mi, Ci, and Pivalues come from Baier and Baierová (1985) and Vostal and Matousch (1988) and are based on studies and measurements performed in the CzechRepublic in the early 1980s (Table SI-2).
Since the annual per hectare yields of fodder exhibited a large variability (e.g., 4.6–11.8, 4.9–11.6, and 2.4–6.1 Mg of hay ha–1 yr–1 for red clover, lucerne, and hay on meadows, respectively) during the study in both long-term and inter-annual pattern, we did not calculate the net annual N biofixation on an areal basis, but on the basis of annual harvest. The average rate of soil N enrichment related to the mass unit of harvested plant i (Fi, kg Mg–1 yr–1) was calculated as Fi = NABNFi/Yi, where Yi (Mg ha–1) was the average annual per hectare yield (in the form of hay in the case of fodder) of the respective plant in the Czech Republic in 1980–1985, i.e., in the same period for which the Mi and Ci values are relevant. The resulting Fi factors varied between 0.5 and 12.7 kg Mg–1 yr–1 for hay on meadows and annual clover, respectively (Table SI-2), and were kept constant for the whole study period. Then, the annual net enrichment of agricultural land with the fixed N (NBNFy, kg ha–1 yr–1) was calculated from the harvest of individual plants (Hi,y, Mg) and total agricultural land area (AAL,y, ha) in the study catchment in a year of interest (y):
(SI-2)
The average net enrichment of agricultural land by N biofixation was dominated (91–98%) by fodder production in the upper Vltava catchment throughout the study period; it increased from ~3 to 7 kg ha–1 yr–1 between 1959 and the 1980s, and then declined to 2 kg ha–1 yr–1 in 2010 (Fig. SI-2E).
Table SI-2. Mean values used for calculating net soil N enrichment by biofixation in the upper Vltava catchment by major leguminous species (Baier and Baierová 1985; Vostal and Matousch 1988; Statistical Yearbooks of the Czech Republic).
Plant (i) / Yi / Mi / Ci / Ti / Pi / BNF / NABNFi / FiMg ha–1 / Mg ha–1 / g kg–1 / yr / kg ha–1 yr–1 / kg ha–1 yr–1 / kg Mg–1 yr–1
Legumes / 2.3 / 2.7 / 16 / 1 / 0.50 / 39 / 21 / 9.4
Annual mixed fodder / 3.4 / 2.4 / 13 / 1 / 0.66 / 51 / 21 / 6.1
Annual clover / 5.5 / 2.9 / 32 / 1 / 0.75 / 202 / 70 / 12.7
Red clover / 10.6 / 5.6 / 23 / 2 / 0.75 / 284 / 49 / 4.6
Lucerne / 10.1 / 6.7 / 24 / 2 / 0.75 / 300 / 60 / 6.0
Other perennial fodder crops / 7.8 / 5.6 / 14 / 2 / 0.30 / 58 / 12 / 1.5
Hay on meadows / 5.4 / 4.4 / 12 / 2 / 0.10 / 11 / 3 / 0.5
Abbreviations: Yi = average annual per hectare yield of plant i (in the form of hay for fodder) in 1980–1985, Mi = areal yield of roots and post-harvest residue of the plant i in the early 1980s, Ci = N concentration in the plant i, Pi = proportion of N in the plant i originating from BNF, BNF = total biological N fixation by plant i, NABNFi = net areal N enrichment of soils from BNF by a plant i, Fi = average rate of soil N enrichment due to production of mass unit of plant i. Other perennial fodder crops includeclover-grass and lucerne-grass.
Part SI-4: Details to section “Hydrological and chemical data”
Hydrological stations and forested sub-catchments used in this study
Table SI-3. Catchment runoff measured at 39 hydrological stations in the upper Vltava catchment from 2000–2009.
River/Station / AC(km2) / E (m) / Catchment runoff (m yr-1)No / 2000 / 2001 / 2002 / 2003 / 2004 / 2005 / 2006 / 2007 / 2008 / 2009
1 / Bezdrevský potok/Netolice / 79 / 586 / 0.10 / 0.13 / 0.73 / 0.18 / 0.16 / 0.14 / 0.16 / 0.16 / 0.11 / 0.31
2 / Blanice/Heřmaň / 843 / 603 / 0.12 / 0.11 / 0.45 / 0.14 / 0.17 / 0.21 / 0.26 / 0.13 / 0.12 / 0.27
3 / Černá/Líčov / 127 / 801 / 0.21 / 0.33 / 0.72 / 0.22 / 0.36 / 0.56 / 0.53 / 0.31 / 0.28 / 0.64
4 / Černovický potok/Tučapy / 102 / 569 / 0.20 / 0.24 / 0.39 / 0.15 / 0.21 / 0.20 / 0.29 / 0.15 / 0.19 / 0.22
5 / Křemelná/Stodůlky / 135 / 992 / 0.82 / 0.75 / 1.47 / 0.55 / 0.73 / 0.90 / 1.04 / 0.96 / 0.91 / 0.95
6 / Křemžský potok/Brloh / 41 / 766 / 0.12 / 0.15 / 0.89 / 0.22 / 0.19 / 0.17 / 0.19 / 0.21 / 0.19 / 0.46
7 / Lomnice/D. Ostrovec / 390 / 510 / 0.11 / 0.13 / 0.39 / 0.12 / 0.15 / 0.16 / 0.18 / 0.06 / 0.08 / 0.12
8 / Lužnice/Koloděje / 4221 / 521 / 0.12 / 0.15 / 0.41 / 0.12 / 0.19 / 0.20 / 0.31 / 0.12 / 0.12 / 0.21
9 / Lužnice/Bechyně / 4056 / 524 / 0.13 / 0.16 / 0.42 / 0.13 / 0.20 / 0.21 / 0.33 / 0.13 / 0.12 / 0.22
10 / Lužnice/Klenovice / 3153 / 532 / 0.13 / 0.16 / 0.44 / 0.13 / 0.21 / 0.22 / 0.34 / 0.13 / 0.12 / 0.24
11 / Lužnice/nad Zl. Stokou / 937 / 590 / 0.12 / 0.20 / 0.49 / 0.13 / 0.24 / 0.23 / 0.39 / 0.17 / 0.14 / 0.29
12 / Lužnice/Nová Ves / 604 / 626 / 0.13 / 0.24 / 0.65 / 0.15 / 0.29 / 0.31 / 0.52 / 0.29 / 0.21 / 0.24
13 / Malše/Roudné / 962 / 622 / 0.11 / 0.14 / 0.51 / 0.14 / 0.20 / 0.25 / 0.30 / 0.13 / 0.13 / 0.32
14 / Malše/Římov / 494 / 710 / 0.12 / 0.15 / 0.54 / 0.15 / 0.21 / 0.29 / 0.29 / 0.15 / 0.15 / 0.32
15 / Malše/Kaplice / 258 / 721 / 0.19 / 0.25 / 0.59 / 0.19 / 0.29 / 0.39 / 0.32 / 0.22 / 0.23 / 0.39
16 / Malše/Pořešín / 437 / 731 / 0.20 / 0.26 / 0.61 / 0.19 / 0.30 / 0.40 / 0.40 / 0.21 / 0.23 / 0.39
17 / Malše/Leopoldschlag / 98 / 820 / 0.23 / 0.30 / 0.67 / 0.22 / 0.34 / 0.45 / 0.45 / 0.24 / 0.26 / 0.44
18 / Nežárka/Lásenice / 684 / 576 / 0.22 / 0.26 / 0.42 / 0.16 / 0.23 / 0.22 / 0.31 / 0.17 / 0.17 / 0.24
19 / Ostružná/Kolínec / 92 / 754 / 0.30 / 0.32 / 0.71 / 0.26 / 0.33 / 0.40 / 0.51 / 0.42 / 0.34 / 0.54
20 / Otava/Písek / 2914 / 644 / 0.23 / 0.21 / 0.58 / 0.20 / 0.26 / 0.30 / 0.36 / 0.27 / 0.23 / 0.35
21 / Otava/Strakonice / 1719 / 704 / 0.31 / 0.28 / 0.68 / 0.24 / 0.31 / 0.37 / 0.44 / 0.37 / 0.31 / 0.46
22 / Otava/Katovice / 1134 / 730 / 0.38 / 0.35 / 0.76 / 0.27 / 0.35 / 0.42 / 0.50 / 0.42 / 0.37 / 0.51
23 / Otava/Sušice / 534 / 916 / 0.62 / 0.57 / 1.13 / 0.42 / 0.56 / 0.69 / 0.81 / 0.71 / 0.68 / 0.77
24 / Otava/Rejštejn / 334 / 1017 / 0.89 / 0.81 / 1.60 / 0.59 / 0.79 / 0.98 / 1.08 / 1.04 / 1.02 / 1.10
25 / Polečnice/Český Krumlov / 198 / 700 / 0.10 / 0.12 / 0.72 / 0.18 / 0.15 / 0.14 / 0.16 / 0.17 / 0.16 / 0.25
26 / Skalice/Varvažov / 367 / 521 / 0.09 / 0.12 / 0.28 / 0.11 / 0.12 / 0.13 / 0.21 / 0.09 / 0.07 / 0.12
27 / Skřemelice/Hoheneich / 237 / 576 / 0.13 / 0.21 / 0.54 / 0.15 / 0.26 / 0.25 / 0.37 / 0.17 / 0.13 / 0.29
28 / Smutná/Rataje / 218 / 524 / 0.17 / 0.19 / 0.32 / 0.12 / 0.17 / 0.17 / 0.25 / 0.14 / 0.09 / 0.13
29 / Spůlka/Bohumilice / 105 / 806 / 0.27 / 0.21 / 0.80 / 0.25 / 0.38 / 0.39 / 0.51 / 0.36 / 0.19 / 0.41
30 / Stropnice/Pašinovice / 400 / 539 / 0.10 / 0.14 / 0.51 / 0.14 / 0.19 / 0.23 / 0.32 / 0.12 / 0.12 / 0.33
31 / Stropnice/Horní Stropnice / 25 / 686 / 0.18 / 0.25 / 0.89 / 0.25 / 0.33 / 0.40 / 0.56 / 0.21 / 0.20 / 0.58
32 / Studená Vltava/Černý Kříž / 106 / 925 / 0.58 / 0.41 / 0.88 / 0.40 / 0.54 / 0.66 / 0.87 / 0.91 / 1.00 / 0.60
33 / Teplá Vltava/Chlum u Volar / 348 / 940 / 0.60 / 0.42 / 0.92 / 0.42 / 0.56 / 0.68 / 0.70 / 0.58 / 0.49 / 0.65
34 / Teplá Vltava/Lenora / 176 / 1011 / 0.71 / 0.50 / 1.09 / 0.50 / 0.66 / 0.81 / 0.71 / 0.53 / 0.52 / 0.73
35 / Vltava/České Budějovice / 2850 / 719 / 0.25 / 0.22 / 0.62 / 0.25 / 0.25 / 0.32 / 0.36 / 0.26 / 0.26 / 0.37
36 / Vltava/Březí / 1828 / 779 / 0.32 / 0.27 / 0.69 / 0.31 / 0.28 / 0.36 / 0.40 / 0.33 / 0.33 / 0.41
37 / Vltava/Spolí / 1341 / 827 / 0.32 / 0.26 / 0.59 / 0.30 / 0.27 / 0.36 / 0.39 / 0.31 / 0.32 / 0.38
38 / Volyňka/Nemětice / 379 / 723 / 0.19 / 0.14 / 0.55 / 0.17 / 0.26 / 0.27 / 0.35 / 0.33 / 0.18 / 0.40
39 / Vydra/Modrava / 90 / 1140 / 1.30 / 1.19 / 2.34 / 0.87 / 1.16 / 1.43 / 1.55 / 1.46 / 1.29 / 1.38
Abbreviations: AC: catchment area; E: areal average elevation of the catchment.
Table SI-4. Annual average discharge of the Vltava river at Slapy Reservoir during 1959–2010.
Year / m3 s–1 / Year / m3 s–1 / Year / m3 s–1 / Year / m3 s–1 / Year / m3 s–11959 / 79.0 / 1970 / 96.2 / 1981 / 106 / 1992 / 67.7 / 2003 / 73.6
1960 / 96.0 / 1971 / 59.8 / 1982 / 89.2 / 1993 / 73.4 / 2004 / 75.5
1961 / 79.0 / 1972 / 66.5 / 1983 / 75.9 / 1994 / 66.3 / 2005 / 93.2
1962 / 87.6 / 1973 / 59.2 / 1984 / 55.4 / 1995 / 91.6 / 2006 / 127
1963 / 44.6 / 1974 / 106 / 1985 / 73.8 / 1996 / 110 / 2007 / 64.1
1964 / 65.7 / 1975 / 105 / 1986 / 89.0 / 1997 / 84.9 / 2008 / 61.4
1965 / 159 / 1976 / 84.9 / 1987 / 124 / 1998 / 59.0 / 2009 / 97.8
1966 / 128 / 1977 / 123 / 1988 / 102 / 1999 / 62.3 / 2010 / 102
1967 / 107 / 1978 / 81.6 / 1989 / 66.8 / 2000 / 68.9 / Minimum / 44.6
1968 / 67.2 / 1979 / 127 / 1990 / 57.0 / 2001 / 69.2 / Maximum / 189.0
1969 / 60.3 / 1980 / 124 / 1991 / 60.1 / 2002 / 189 / Average / 87.3
Table SI-5. Forest lakes and streams analyzed for NO3– concentrations in the upper Vltava catchment and its surrounding. For site locations see Fig. SI-1. Abbreviation: p = potok (stream).
Abbre-viation / Site / River catchment / Eleva-tion / Observations / Average NO3-N concentration (µg l–1)1935-1937 / 1959-1961 / 1976-1980 / 1985-1990 / 1995-2000 / 2001-2010
SU / Sudoměřice / Košínský p. / 487 / 2000 / 310
LE / Letny / Trnavá / 662 / 2002 / 1430
HA / Hartvíkov / Bělá / 676 / 2002 / 1500
KL / Klepná / Černá / 733 / 2008–2010 / 406
MA / Malonty / Kamenice / 747 / 1996, 2002, 2005 / 993
TI / Tisový p. / Černá / 811 / 2002, 2005 / 361
KR / Krakovický p. / Zdíkovský p. / 834 / 2002, 2005, 2008–2010 / 678
KA / Kabelský p. / Malše / 852 / 2002, 2005 / 740 / 391
CN1) / ČernéLake / Úhlava / 1008 / 1936, 1959–1961, 1978–2010 / < 10 / 690 / 1670 / 1618 / 1268 / 1138
CT1) / ČertovoLake / Řezná / 1028 / 1937, 1960, 1984–2010 / < 10 / 340 / 830 / 1200 / 773 / 680
PL1) / PlešnéLake / Vltava / 1090 / 1935, 1961, 1984–2010 / < 10 / 280 / 885 / 526 / 1305
1)The Bohemian Forest lakes. Data refer to NO3-N concentrations in their inlets and were either directly measured (1998–2010) or recalculated from in-lake concentrations, using the average in-lake nitrate removal of 29% in the CN and CT lakes and 50% in the PL lake.
Analytical methods used for determination of N forms in 1959–2010 – Concentrations of NO3– have been determined after reduction to nitrite with alkaline hydrazine according to Procházková (1959) since 1959 and by ionic chromatography (IC) since 1996. Because both methods provided almost identical values (e.g., 23851 vs. 24351 in 1996), the data based on IC method have been used in the long-term trend since 1996 even though data on both methods are available. Concentrations of NH4+ were determined by nesslerization of the distillate at pH ~7.8 in 1959–1963 (for details see Procházková 1977), then by the NH4-specific (rubazoic acid) method (Procházková 1964) till 1992, and finally by its modified version, excluding the original extraction step (Kopáček and Procházková 1993) in the 1992–2010 period. Comparability of the latter two methods was successfully proved, but NH4-N concentrations prior to 1964 could be partly overestimated (Kopáček and Procházková 1993). This potential error is, however, negligible for the purpose of this study. Concentrations of NO2– have been determined spectrophotometrically according to Bendschneider and Robinson (1952) since 1961. Concentrations of total organic N (TON, the difference between the respective Kjeldahl N and NH4-N) have been determined since 1959 by Kjeldahl digestion according to Procházková (1960), with 25–50 ml of samples previously evaporated with sulphuric acid to obtain a detection limit of ~25µgl–1.
Part SI-5: Details to section “Mass balance”
Nitrate retention in water bodies and relationship between elevation and catchment runoff
Empirical equation (3) by Seitzinger et al. (2002) was developed for lakes and streams and relates the in-lake N removal (rN) to water residence time. We tested the reliability of this equation in the upper Vltava catchment by comparing measured and computed rN data for 9 water bodies with available mass budged studies on in-lake NO3– removal: one fish pond – Rožmberk (2000–2007), three forest lakes – Plešné and Čertovo (2000–2011) and Černé (2000), three reservoirs in the study catchment – Lipno (1991–1993, 1999), Slapy (2004–2006), and Římov (1998–1999), and two reservoirs in the neighboring catchment – Švihov (1994–1995) and Němčice (1988, 1999–2000). Data sources: Kopáček et al. (2001; 2004; 2006a,b), Hejzlar et al. (2006) and Hejzlar and Kopáček (unpubl. data). The available measured and computed rN values were averaged for each water body. The relationship between the average measured and computed rN values was close, with the computed values being on average higher by ~8% (Fig. SI-4).
Part SI-6: Details to section “Mass balance”
Terrestrial nitrogen export from forest areas (EFO) in the upper Vltava catchment
Time series of average N concentrations in the forest streams (CFO) – Data on NO3– concentrations in the Bohemian Forest lakes [Černé (CN), Čertovo (CT), and Plešné (PL)] prior to 1990 are from Jírovec and Jírovcová (1937), Veselý (1994), Veselý et al. (1998), and Procházková and Blažka (1999), and are based on 1–4 samples per year. All N forms have been determined in 4-month to 2-week intervals in the lakes and their inlets since 1990 and 1998, respectively (Kopáček et al. 2001; 2006a,b; and unpubl. data). Analytical methods used for NO3– determinations in the 1930s were checked and found to be reasonably reliable (Veselý and Majer 1992). Other N analyses were performed with methods identical to those used for the Slapy Reservoir. Annual average N concentrations were obtained for individual lakes as discharge-weighted means for years with monthly or more frequent samplings (Kopáček et al. 2006a,b), and as arithmetical means of all available data for years with less frequent sampling. The in-lake NO3– concentrations did not, however, represent the real NO3– export from the lake catchments, but the nitrate remaining in the lakes after its partial removal by denitrification and assimilation. Detailed mass budget studies for 1998–2010 showed that the net in-lake NO3– removal averaged 29% in the CN and CT lakes and 50% in the more phosphorus rich (and productive) PL lake (Kopáček et al. 2001; 2004; 2006a,b; and unpubl. data). We used these removal percentages to calculate annual average concentrations of NO3– in the lake inlets (first-order forest streams); and we kept them constant for the whole study period, i.e. assumed stable efficiency of the in-lake processes to remove NO3–. For example, the annual average NO3– concentration in the CT inlets (CINLET) was calculated from their in-lake concentrations (CLAKE) as CINLET=CLAKE/(1–29/100), except for 1998–2010, when they were measured directly.
Part SI-7: Details to section “Mass balance”
Nitrogen fluxes in waste waters (EWW) in the upper Vltava catchment
Annual fluxes of N entering the surface waters with waste waters (EWW,y) were estimated on the basis of annual data on population, proportion of inhabitants attached to municipal sewerage systems, proportion of waste waters treated in waste water treatment plants (Fig. SI-6), and the efficiency of their technologies in year y (equation SI-3):
(SI-3)
where PN (g capita–1 day–1) is a daily per capita production of N, X is number of inhabitants not attached to sewerage systems (XNA,y) and attached to sewerage systems without and with waste water treatment plants (i.e., attached but untreated, XAU,y; and attached and treated XAT,y) in the study catchment, and f (%) is the treatment efficiency of the respective sanitary systems to remove N (i.e., fNA,y, fAU, and fAT,y).
The per capita N production was set to 15 g capita–1 day–1 on the basis of a mass budget study (Hejzlar et al. 2010) in the study catchment, and was kept constant for the whole period. This number is in the middle of range of total per capita N production (12–18 g capita–1 day–1) in the Czech Republic, which consists of a constant physiological N production of 12 g capita–1 day–1 and the N production from food industry, which increases from 2 to 6 g capita–1 day–1 with increasing settlement size between 10,000 and 100,000 inhabitants (Nesměrák 1996). A similar per capita N production (11–18 g capita1 day–1) was reported for Germany (Ryding and Rast 1989; Behrendt et al. 2000). The XNA,y, XAU,y, and XAT,y values were calculated on the basis of annual statistical data (Fig. SI-7). The efficiency of individual sanitary systems and technologies (mechanical purification, biological treatment, denitrification) of waste water treatment plants was reviewed in the literature (Ryding and Rast 1989; Nesměrák 1996; Behrendt et al. 2000) and estimated on the basis of monitoring of waste water treatment plants (Just et al. 1996; Hejzlar et al. 2010) and operational evidence of sewerage systems and waste water treatment plants in the administrative South Bohemian district (ČEVAK 2010) as follows:
(i) Just et al. (1996) estimated that 25% of the anthropogenic N production of inhabitants not attached to sewerage systems reached surface waters in the Želivka catchment (Czech Republic) from small villages (<500 inhabitants) in 1995. Consequently, we set the fNA,y value to 75% in 1995–2010. The relatively high export of anthropogenic N to surface waters from settlements without sewerage systems resulted from a previous (1950–1980) development of water supply networks and sanitary systems (conversion of latrines to flush toilets, increasing number of automatic washing machines), which was faster than construction of new sewerage systems. The increasing volumes of waste waters originally collected in cesspools (which were hauled away seasonally) were drained to ditches and irrigation sewage disposals, or simply leaked through the cesspool walls. Due to a lack of direct measurements, we set historical fNA,y values to 90% and 80% in 1950 and 1960, respectively. The fNA,y values in 1951–1959 and 1961–1994 periods were then obtained by linear interpolation.
(ii) The efficiency of sewerage systems without waste water treatment plant was set to 10% and this fAU was used constant for the whole study period. In this case, we assumed only mechanical purification of sewage in domestic septic tanks, which removed only ~10% of total N input (Behrendt et al. 2000), prior to entering the sewerage system.
(iii) The efficiency of sewerage systems with waste water treatment plants depends on time and was based on the development of treatment technologies. The individual fAT,y values were set to 30% (Behrendt et al. 2000) prior to 1985, when only biological treatment was used, and 68% since 2005, when a large proportion of waste waters has been already treated using a denitrification step. The latter fAT,y efficiency factor was based on a mass balance study of nutrient sources in the upper Vltava catchment (Hejzlar et al. 2010) and was similar to those used in other studies (e.g., 45–75% in Germany; Ryding and Rast 1989; Behrendt et al. 2000). The fAT,y values for 1986–2004 were linearly interpolated between 30% and 68% as a correction for a continual improvement and increasing efficiency of waste water treatment plants to remove N in this period.