Spatial changes in the modalities of N and P inputs in a rural river network

PII: S0043-1354(98)00187-0

Wat. Res. Vol. 33, No. 1, pp. 95±104, 1999 # 1998 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0043-1354/98 $ - see front matter

SPATIAL CHANGES IN THE MODALITIES OF N AND P INPUTS IN A RURAL RIVER NETWORK PHILIPPE VERVIER1*, ADILSON PINHEIRO{2, ANDRE FABRE3, GILLES PINAY4 and ELIANE FUSTEC5 1 CESAC, U.M.R. C 5576, CNRS/UPS, 29 rue Jeanne Marvig, F-31055 Toulouse cedex, France; IMFT, ENSEEIHT, INPT, URA 005 CNRS, AlleÂe du Professeur C. Soula, F-31400 Toulouse cedex, France; 3LET, UMR 5552, CNRS/UPS, U.P.S., Bat. IVR, 3118 route de Narbonne, F-31062 Toulouse cedex, France; 4ECOBIO, URA 1853, Universite de Rennes I, Campus de Beaulieu, F-35042 Rennes cedex, France and 5Laboratoire de GeÂologie AppliqueÂe, Universite P. et M. Curie, 4 place Jussieu, F-75252 Paris cedex, France 2

(First received January 1997; accepted in revised form April 1998) AbstractÐNitrates (NI) and total phosphorus (TP) ¯uxes were analysed in an agricultural river of southwestern France, the Save River, in order to identify their nonpoint and/or point±source origin. For this purpose, TP and NI concentrations were measured and the ¯uxes calculated along the whole river at 27 sampling sites during three di€erent seasons; Pearson correlation coecient and partial correlation were systematically calculated for each sampling period between TP or NI loads and the environmental variables; i.e. number of inhabitants, forest, crop and pasture surfaces. In Spring and Winter, concentrations and ¯uxes of NI and TP increased from the headwaters to the mouth of the Save River. During the dry season, in Summer, concentrations and ¯uxes of NI and TP were strongly in¯uenced by instream biological processes and arti®cial water supply. During wet seasons, i.e. in Winter and Spring, in spite of the same spatial dynamics of TP and NI ¯uxes, it appears that nitrate ¯uxes entering the river originated mainly from croplands (i.e. di€use pollution) whereas phosphorus ¯uxes were highly related to the number of inhabitants (i.e. point source pollution). During the rainiest season, i.e. in Spring, phosphorus ¯uxes were also related to forests which are mainly located in the steep slope upstream part of the drainage basin. # 1998 Elsevier Science Ltd. All rights reserved Key wordsÐagricultural river, point source pollution, di€use pollution, phosphorus, nitrates, partial correlation

INTRODUCTION

between the river and its drainage basin (Dillon and Kirchner, 1975; Omernik, 1976) and the role of agricultural practices (Dugdale and Dugdale, 1961; Loehr, 1974; Isenhart, 1989; Correll et al., 1992; Skaggs et al., 1994). One diculty arises from the fact that the in¯uence of the watershed on water quality of aquatic river ecosystems ¯uctuates strongly in time, since the magnitude of surface runo€ or groundwater discharge, and consequently the quantity and the quality of nutrients, may change respectively from storm¯ow to base¯ow periods (Owens et al., 1991; Skaggs et al., 1994). However, these temporal changes can only partly explain the ¯uctuations of P and N concentrations measured in streams and rivers within agricultural watersheds. Indeed, other parameters such as the soil types, the landuse, the ®eld slopes, and the storm¯ow timing can control the quantity of nutrients released by the drainage basin (Prochazkiva et al., 1991; Owens et al., 1991; Correll et al., 1992; Mulholland and Patrick, 1992; Sharpley, 1995). Moreover, nutrient loads in rivers can be in¯uenced by processes occuring within the river channel such as resuspension of instream retained phosphorus (Svendsen and Kronvang, 1993; Svendsen et al., 1995).

Di€use pollution control is nowadays an important concern, since it has been clearly identi®ed as a cause of water quality degradation both in freshwater and marine ecosystems (Monbet, 1992; Nienhuis, 1992). In that respect, nutrient, pesticides and heavy metals represent the key pollutants from which some curative action needs to be taken. Regarding nutrients, it has been demonstrated that the changes in agricultural practices in the last 50 years (use of fertilizers, simpli®cation of the landscape, mechanization, drainage) has signi®cantly contributed to increase their concentrations in surface and groundwater to such an extent that it has become detrimental to aquatic ecosystems which present evidence signs of eutrophication (Golterman and De Oude, 1991). In order to tackle this nutrient di€use pollution one needs take into account the relationships *Author to whom all correspondence should be addressed. {Present address: Instituto de Pesquisas Ambientais, Universidade Regional de Blumenau, Rua Antonio da Veiga, 140, Caixa Postal 1507, 89010-971 Blumenau, Santa Catarina, Brasil. 95

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To develop some curative strategies for aquatic ecosystems which receive nutrient pollution, it is important to identify the sources of the nutrients entering the rivers by taking into account the complexity of the watershed structure (landuse, geology, topography, . . .) which increases from upstream to downstream. However, rare are the studies in agricultural watersheds, which distinguish between the part of agricultural di€use pollution and the part of point±source pollution which can result from cities or villages (Keeney and Deluca, 1993). To face this diculty to di€erentiate these two types of source pollution, Omernik (1976) set up a data base of reference watersheds without any point±source pollution. Hence, the aim of this paper is to identify the point source or non point source origin of nitrate and total phosphorus ¯uxes in a river draining a watershed mainly devoted to agriculture.

MATERIAL AND METHODS

Site description The Save River has its source in the piedmont zone of the PyreÂneÂes mountains (southwest France) at an altitude of 600 m and joins the Garonne River after a 140 km course with an average slope of 3.6-. The 1108 km2 watershed which has a linear shape, comprises 37,315 inhabitants, which mostly live in 5 small cities (Fig. 1). The river discharge ¯uctuates strongly within a year (Fig. 2). High-water periods which are linked to precipitation and snow melting occur during Spring whereas low-water period takes place in July and August with very low discharges. In addition to these natural ¯uctuations, this ¯ow regime is strongly modi®ed by human activity; discharge during low water periods is maintained by water coming from the PyreÂneÂes mountains. This clear water is introduced near the Save River Spring and near two of its tributaries' springs via a canal (Fig. 1). Despite this arti®cial water supply of about 2 m3 sÿ1, Summer discharges can decrease up to 0.004 m3 sÿ1 100 km downstream the input since water is used for irrigation along its course.

Fig. 1. Location and description of the Save River watershed.

N and P inputs in a rural river network

97

Fig. 2. (A) Precipitation registered at Lombez city and discharge measured at the Larra gauging site from October 1988 to October 1989. (B) Discharges calculated and nitrates and total phosphorus concentrations measured at each sampling site in Winter (17/1/89), in Spring (19/4/89) and in Summer (1/8/89). Sampling strategy Three typical hydrological periods characteristics were sampled in 1989, i.e. Winter (Wi) (17/1/89), Spring (Sp) (19/4/89) and Summer (Su) (1/8/89). The Winter and Summer periods correspond to low discharges but it is important to notice that the river was fed through an arti®-

cial canal during the Summer period (Figs 1 and 2). The Spring sampling period occured during ¯oods (Fig. 2). The Save River has been divided in 27 reaches with their corresponding subwatersheds (Fig. 1). The reaches which ranged from 1 to 9 km long were delimited in their downstream part by the sampling site ``i '' and in their upstream part by the sampling site ``i ÿ 1''. Each sampling site

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located at the downstream part of each reach was considered as the outlet of the corresponding subwatershed. Upstream TP and NI-loads which refer to ¯uxes within the stream which enter in a given reach ``i '', have been calculated from the concentrations measured in the reach ``i ÿ 1''. Hence we could then calculate TP and NI ¯uxes for each of the 27 reaches.

river and the area of the corresponding subwatershed, we ®nd that this index decreases signi®cantly from upstream to downstream. Indeed the ratio is negatively correlated with the distance of the sampling sites (r = ÿ 0.65, r2=0.42, p = 0.0014).

Watershed landuse

Samples were ®ltered in the ®eld through glass ®bre ®lters (Whatman GF/C) and stored at 48C until they could be processed for nitrate (NI) analyses, within 48 h. NI concentrations were measured with a Technicon Autoanalyser (Technicon Instrument Systems, 1976). Total phosphorus (TP) concentrations were measured on un®ltered water after digestion of the total samples and using H2SO4+persulfate method (APHA, 1971). The digests were neutralised and phosphorus was determined by the ascorbic acid±molybdenum method (Murphy and Riley, 1962). Discharge was calculated at each sampling site using the discharge speci®c method (Remenieras, 1986) combined to the rainfall spatial distribution based on Thiessen polygon (Thiessen, 1911). These calculations were calibrated with the data recorded at 5 gauging sites on the Save River network, 2 on the Save River itself in Lombez (73 Km) and Larra (131 Km), and 3 corresponding to the input of the arti®cial canal in the Save River Spring, and 2 of its tributaries (the Segouade and Gesse Rivers) (Fig. 1). At each sampling site ``i'', discharge (Qi) was calculated according to the following function:

For each subwatershed (SW), surfaces of each land use category and number of inhabitants (Inh.) were determined. We identi®ed forest (For.), crop (Cro.) and pasture (Past.) which refers to the whole agricultural area minus forests and crops surfaces. Phosphorus export coecients in agricultural watersheds (U.S. EPA, 1974; Loehr, 1974; Omernik, 1976; Rast and Lee, 1983; Benneton, 1986), with main characteristics close to those of the Southwest France watersheds were used by Fabre (1993). He found that phosphorus export coecient from forest, pasture and crops in the Save River Drainage basin were respectively 0.1, 0.1 and 0.25 kg haÿ1 yÿ1 of TP, corresponding to an increase vulnerability to phosphorus loss (Sharpley, 1995; Beauchemin et al., 1996). The upstream part of the watershed is a hilly agricultural area mainly covered with forest and pastures (INSEE, 1988; MinisteÁre de l'Agriculture et des ForeÃts, 1988), while the lower part is ¯at and devoted to intensive agricultural practices (Fig. 3), mainly corn®elds which receive high quantity of fertilizers (200 kg haÿ1). Forests areas are not fertilized and pastures receive limited amount of fertilizers. It is important to note that, in a given subwatershed, the percentage of Cro. area is strongly negatively correlated with the logarithm of the slope of the river (r = ÿ 0.698, r2=0.48, p = 0.001). Areas which are heavily fertilized take place in the ¯at part of the watershed and, therefore, don't present a high risk of erosion. Due to the shape of the watershed, the subwatersheds of the down stream part of the river (i.e. from subwatershed No 17; Fig. 1) are much wider than the upstream subwatersheds. As a consequence, when we calculate a drainage basin±river connection index which corresponds to the ratio between the length of a given reach of the

Fig. 3. Longitudinal slope of each studied reach of the Save River. Percentage of For. and Cro. areas in each subwatershed.

Chemical analyses and ¯uxes calculation

Qi ˆ Qiÿ1 ‡ lateral inflow …Lin † with Lin=Qg1ÿQg2SSWi/SsW(g1;g2), where Qg1 and Qg2 are gauging stations, SSWi is subwatershed area drained at site ``i ''; SsW(g1;g2) is the subwatershed area drained between Qg1 and Qg2. In Summer, this calculation took into account the amount of water pumped for irrigation. TP and NI ¯uxes were then obtained by multiplying their concentration at a given location by the speci®c discharge. Statistical methods All the statistical calculations were performed using Systat software (Systat, 1992). Pearson correlation coecients between TP and NI loads were calculated for the three sampling periods. Pearson correlation coecients were calculated for each sampling period between TP or NI loads and the environmental variables; i.e. Inh., For., Cro. and Past. surfaces (data from MinisteÁre de l'Agriculture et des ForeÃts, 1988). In this agricultural region, 40% of people are gathered in the villages. Hence, we assumed that TP export by runo€ or sewers from villages is proportionate to the number of inhabitants, therefore we only considered Inh as population variable. Moreover, since our calculations were based on correlation between nutrient ¯uxes and environmental variables, we did not use the number of animals which was highly correlated with pasture surfaces (r = 0.946). Upstream loads (TP or NI) were also considered as environmental variables. All the correlation coecients were calculated after eliminating outliers when necessary (Hoaglin et al., 1986). The aim of these calculations was to explain the spatial and temporal ¯uctuations of TP or NI ¯uxes by these variables. But even if the Pearson correlation coecient is statistically signi®cant, it does not mean that there is a direct relation between TP or NI ¯uxes and the considered variables (King, 1969; Pringle, 1980). Therefore, to avoid possible spurious correlation and to determine relations between the dependent variables (i.e. TP-loads and NIloads) and the independent variables (i.e. forest, crop and pasture surfaces, number of inhabitants, upstream TPloads and upstream NI-loads), partial correlation (rp) was used. Partial correlation is the correlation between two

N and P inputs in a rural river network variables with either one or more of the other variables, which are called ``control variables'', held constant (King, 1969; Pringle, 1980; Kirby, 1993). Among all the partial correlation coecients calculated, we will only discuss those which modi®ed signi®cantly the correlation coecients of Pearson. The partial correlation calculations can increase, decrease or not change the statistical signi®cance between NI or TP ¯uxes and the independent variables. For each sampling period, TP-loads and NI-loads calculated at each sampling site were plotted vs the distance from the source. A two-way scatter plot was performed using the negative exponentially weighted smoothing method (Systat, 1992). This method ®ts a curve through a set of points by considering that the in¯uence of two neighbour points, decreases exponentially with their distance.

99

or dry periods since they strongly in¯uence nutrient export (Johnson et al., 1985; Smith, 1987; Cann, 1990). Discharges calculated at each sampling site increased from the source to the mouth of the river in Spring (Fig. 2). In Winter, the small discharge increase along the river corresponded to a very low supply from the drainage basin. In Summer, despite the fact that the Save River is fed through its source by an arti®cial canal (1.6 m3 sÿ1), the discharge decreased strongly up to the mouth of the river due to water extraction along the water course for irrigation purpose. Spatial and temporal ¯uctuations of TP and NI-loads

RESULTS

Precipitation and discharges During the study period, i.e. October 1988 to September 1989, precipitation was signi®cantly higher then an average year. Winter and Summer samples have been taken during low-water periods. Winter samples occurred during a low precipitation period whereas the Summer samples (1/8/89) took place during a dry period (Fig. 2). Spring sampling occured during a high ¯ow period. It is important to underline if the samples were taken during rainy

Highest ¯uxes of TP and NI loads were measured during Spring near the mouth of the river (site No. 27: TP-loads = 410 kg  dÿ1; NI-loads = 12,979 kg  dÿ1). These values were 150 times more than the highest values of NI and 30 more than the highest values of TP registered in Summer. In Winter and Spring, TP and NI loads increased from the source to the downstream part of the river (Fig. 4). During these two sampling periods TP and NI loads presented the same variations along the river course (Fig. 4). This is con®rmed by the signi®cant correlation between the same nutrient at di€erent time

Fig. 4. Nitrates and total phosphorus loads calculated at each sampling site for the three periods, i.e. Winter (17/1/89), Spring (19/4/89) and Summer (1/8/89).

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Table 1. Pearson correlation coecients between the TP and NI-Loads at the 3 sampling periods i.e. Winter (Wi), Spring (Sp) and Summer (Su) Wi TP-load Wi TP-load Sp TP-load Su TP-load Wi NI-load Sp NI-load Su NI-load

Sp TP-load

1.000

Su TP-load

Wi NI-load

ns

0.974*** 1.000

Sp NI-load

0.927*** 0.972*** 0.236ns 1.000

0.307 0.355ns 1.000

Su NI-load

0.965*** 0.991*** 0.277ns 0.984*** 1.000

ÿ0.723*** ÿ0.692*** 0.289ns ÿ0.719*** ÿ0.737*** 1.000

Signi®cance of correlation: ns = non signi®cant; * = 0.01 < p = 0.05; ** = 0.001 < p = 0.01; ***p = 0.001.

and between TP and NI for the two sampling periods (Table 1). The dynamics of TP and NI ¯uxes during Summer were very di€erent from the two other sampling periods (Fig. 4). In Summer, a slight increase was registered for TP loads from the Spring station (SW1) up to SW 20, while NI loads were relatively constant along the water course. In

the 7 most downstream sampling sites, TP and NI loads decreased strongly (Fig. 4). Despite these similar tendencies, there was no signi®cant correlation between TP and NI during Summer (Table 1). Relations between loads and the subwatersheds Whatever the season, TP and NI loads in a given stretch were highly signi®cantly correlated with

Table 2. In the left-column, Pearson correlation coecients between TP-loads or NI-loads (variables A) and the independent variables (variables B): crops, pasture and forest surfaces, number of inhabitants (Inh) and upstream loads (Up L.). In the middle-column, independent variables used as control variables for calculations of partial correlation coecients between variables A and B. In the right-column, partial correlation coecients between variables A and B by using the other independent variables as control one Pearson correlation coecients between variables A and B

Control variables used in partial correlation coecients between variables A and B

Partial correlation coecients between variables A and B rp

signi®cance

18 18 18 18 18

0.398 ÿ0.694 0.234 0.711 0.926

ns *** ns *** ***

+ + + + +

16 16 16 16 16

ÿ0.740 ÿ0.647 0.592 0.838 0.999

*** ** * *** ***

+ + + + +

+ + + + +

21 21 21 21 21

0.128 ÿ0.020 ÿ0.085 ÿ0.078 0.622

ns ns ns ns **

+ + + + +

+ + + + +

+ + + + +

18 18 18 18 18

0.706 0.180 ÿ0.269 0.118 0.991

*** ns ns ns ***

+ + + + +

+ + + + +

+ + + + +

+ + + + +

19 19 19 19 19

0.573 ÿ0.150 0.166 0.328 0.995

** ns ns ns ***

+ + + + +

+ + + + +

+ + + + +

+ + + + +

20 20 20 20 20

0.142 0.042 0.035 ÿ0.347 0.930

ns ns ns ns ***

Var A

Var B

n

r

Cro.

pasture

forest

Inh

Up L.

TP W

Cro. pasture forest Inhab Up L

24 24 24 24 24

0.240 ÿ0.034 0.159 0.393 0.904

ns ns ns ns ***

+ + + + +

+ + + + +

+ + + + +

+ + + + +

TP Sp

Cro. pasture forest Inhab Up L

22 22 22 22 22

0.353 ÿ0.139 0.182 0.403 0.993

ns ns ns ns ***

+ + + + +

+ + + + +

+ + + + +

TP Su

Cro. pasture forest Inhab Up L

27 27 27 27 27

0.303 0.068 0.006 0.123 0.654

ns ns ns ns ***

+ + + + +

+ + + + +

NI W

Cro. pasture forest Inhab Up L

24 24 24 24 24

0.499 ÿ0.061 0.248 0.675 0.988

* ns ns *** ***

+ + + + +

NI Sp

Cro. pasture forest Inhab Up L

25 25 25 25 25

0.341 0.010 0.205 0.567 0.988

ns ns ns ** ***

NI Su

Cro. pasture forest Inhab Up L

26 26 26 26 26

0.083 0.230 ÿ0.002 ÿ0.310 0.954

ns ns ns ns ***

ddl

Signi®cance of correlation: ns = non signi®cant; * = 0.01 < p = 0.05; ** = 0.001 < p = 0.01; *** = p = 0.001. Lines with bold fonts refer to signi®cant partial correlation between variables A and B.

N and P inputs in a rural river network

upstream loads (Table 2). These signi®cant and positive partial correlation indicated an expected direct relation between TP load or NI load in two successive reaches. For the other independent variables (i.e. forest, crops and pasture surfaces, number of inhabitants), correlations were not signi®cant and therefore we calculated partial correlation (Table 2). In Winter and Spring TP was only positively correlated with upstream load (Up L), but was not correlated with any other independent variable, i.e. Cro., For., Past and Inh. (Table 2). Therefore, we used partial correlation coecient (rp) to explain Loads variations with environmental variables (Table 2). There were relations between TP loads and Cro. (in Spring) or Past (in Winter and in Spring) since TP loads decreased in the river when Cro. or Past. increased (Table 2). Even if, during Spring, TP Loads increased with For. surfaces of subwatersheds, TP loads in both the seasons were highly related to the number of Inhabitants, independently of Cro., Past., For. or Up L. In Winter and Spring, NI loads were signi®cantly positively correlated with Inh. and Up L., while the relationship between NI and Cro. and TP loads was only signi®cant in Winter. However, the rp with Inh. was non signi®cant, traducing a spurious correlation between NI loads and Inh. (Table 2). In Winter and Spring, NI loads increased with an increase of crop surfaces (Table 2). This signi®cant correlation between NI loads and Cro. underlines the strong relation between crop surfaces and nitrates in the Save River. In Summer, we could not ®nd any signi®cant correlation between the nutrient loads (NI and TP) and the selected independent variables related to the drainage basin land use. Ni and TP loads in a given stretch of the river were only determined by the upstream load (Up L). Spatial and temporal ¯uctuations of TP and NI concentrations The range of TP concentrations was the same for the 3 sampled seasons while NI concentrations changed remarkably from Summer to Spring (Fig. 2). In Spring and Winter, NI and TP concentrations increased from the headwaters to the mouth of the river (Fig. 2). Despite high variations in the last part of the river course (WI 22 to WI 27), this tendency is also noticeable during Summer for TP concentrations. In Summer, NI concentrations did not present any signi®cant variation and remained at very low level compared to the other seasons (Fig. 2). DISCUSSION

In order to highlight the causes of NI and TP dynamics within the Save River, we will distinguish between the Summer sampling period on the one

101

hand, and the Winter and Spring periods on the other hand. The ®rst period was characterized by very low discharge and precipitation which limited hydraulic connections between the river and its watershed to take place while during the other periods, the catchment was hydrologically connected to the river. NI and PT dynamics in Summer During Summer, NI and TP ¯uxes decreased signi®cantly in the lower part of the river course. This phenomenon can be explained by the decrease in discharge caused by irrigation in the corn®elds of the downstream part of the Save drainage basin (Fig. 4). During this period, nitrate concentrations remained very low (less than 1.5 mg lÿ1 of N±NOÿ 3) despite the small increase along the water course. This traduces a very weak in¯uence of the Save watershed on the quality of this river. Those low nitrate concentrations can be partly explained by the fact that the Save River is supplied by water coming from the PyreÂneÂes mountains watershed containing very low nutrient concentrations (Fig. 2). Moreover, NI and TP loads were only in¯uenced by upstream loads (Table 2) indicating that the relationship between each successive subwatershed was direct without strong retention processes. However, variations of TP concentrations in the lower subwatersheds must be linked to instream processes such as retention of phosphorus in stream sediments (Pilleboue, 1987; Svendsen and Kronvang, 1993; Svendsen et al., 1995). In the Save River, these processes can be reinforced by the presence of small impoundments (water mill dams) and very low water discharges which entail suspended matter deposition. These physical factors seem to be less ecient for nitrate control (Svendsen and Kronvang, 1993). Variations of NI concentrations can be likely ascribed to internal biological processes such as quick consumption of nitrates in the periphyton by photosynthetic processes (Isenhart, 1989) and/or by microbial denitri®cation in river sediment (Cooper, 1990; Hill, 1997). NI dynamics in Winter and Spring The watershed in¯uence on the river water quality is clearly demonstrated by NI loads increase from upstream to downstream of the river course. This spatial variation which is related to the increase of crop surfaces, can be explained both by natural factors and agricultural practices. During these periods, corn production frequently leaves bare soils, which, coupled with high rainfall, particularly in Spring (Fig. 2), entails N fertilizer runo€ before plant uptake can start (Prochazkiva et al., 1991; Keeney and Deluca, 1993). Therefore, since croplands can export far more nitrogen per hectare than do forests and pastures (Correll et al., 1992), NI loads within the river increase with crop surfaces increase. Moreover, during Spring, fertilisation is

102

Philippe Vervier et al.

far more important than during other periods and can explain the fact that the highest concentrations were measured during this high water period (Fig. 2) even though nitrate concentrations can ¯uctuate during spates (Kattan et al., 1986). During the Winter sampling period, runo€ was limited due to the low precipitation (Fig. 2). Hydrological linkages between the river and the drainage basin occurred most likely through subsurface ¯ow since 68% of the irrigated surfaces are drained by buried drain tubing (MinisteÁre de l'Agriculture et des ForeÃts, 1988). According to Skaggs et al. (1994), subsurface drainage systems increase loss of nitrates and even if the groundwater aquifers are not well developed along this river valley, they exist and can release into the stream, nitrates which have in®ltrated instead of being washed out by runo€ (Owens et al., 1991) during the rainy period. These strong relationships between Cro. surfaces and NI loads are reinforced by the fact that agriculture impinges directly upon river banks along the river, limiting the natural riparian vegetation which could potentially remove nitrates from shallow groundwater (Hill, 1983; Correll et al., 1992; Haycock and Pinay, 1993; Pinay et al., 1994). TP dynamics in Winter and Spring Total phosphorus, loads and concentrations increased also from upstream to downstream of the river course (Figs 2 and 4). As for NI, an increase of TP loads cannot be restricted to discharge increase since concentrations presented the same pattern. We expected a relationship between TP loads and increase of Cro. surfaces which could act as di€use sources of TP as it is often mentioned in the literature (Burwell et al., 1975; Omernik, 1976; Nicholaichuk and Read, 1978; Wendt and Corey, 1980; Angle et al., 1984; Prochazkiva et al., 1991; Correll et al., 1992). On the contrary, during Spring, crop and pasture surfaces presented negative rp with TP loads whereas it was positive with forest surfaces and number of inhabitants (Table 2). These negative rp between TP loads and cropland surfaces in Spring, can be attributed to both landuse and agricultural practices. In the downstream part of the watershed, where the Cro. surfaces are important, runo€ of phosphorus associated to sediments, which usually dominates P export in most of the agricultural watersheds (Harms et al., 1974; Kattan et al., 1986; Pilleboue, 1987; Vaithiyanathan and Correll, 1992), was strongly limited both by the weakness of the slope which diminishes the erosion risk and by the subsurface drainage network (Skaggs et al., 1994). Negative rp between TP loads and pastures, in Spring and Winter, can be explained by the low vulnerability of grassed watersheds to P loss (Sharpley, 1995) and the presence of vegetation cover during Spring which limits runo€ and subsequently TP

export from the watersheds (Burwell et al., 1975; Nicholaichuk and Read, 1978; Wendt and Corey, 1980; Angle et al., 1984). On the contrary, the rp with forests is positive during Spring, probably because forests, which are expected to export low P ¯uxes/ha (Vaithiyanathan and Correll, 1992), are mainly distributed in the hilly upstream part of the drainage basin which present steep slope areas (Fig. 3). This relation between TP loads and forest surfaces can be linked to the fact that to a certain extent, the slope e€ect could increase phosphorus export (Ryden et al., 1973; Vighi et al., 1991), particularly during rainy periods. In the lower part of the Save River, even if forest surfaces represent roughly 30% of the watershed, they probably did not in¯uence signi®cantly TP loads and concentrations since this area is ¯at (Fig. 3) and the forest stands are very patchy, far from the river bank. Inhabitants who live mainly in the lower part of the watershed seemed to strongly in¯uence TP loads in the Save River. Indeed, there were high and signi®cant rp between TP loads and Inh. both in Spring and in Winter. It appears that TP-loads in the Save River were in¯uenced directly by non point source export from the watershed in its upstream part, i.e. the hilly part, whereas they were controlled by point sources of phosphorus in its downstream part. The unexpected negative partial correlation between TP ¯uxes and cropland surfaces could be linked to the fact that the more the cropland surfaces increased, the more the connection between subwatersheds and the river decreased, as it was shown by the negative relationship between the connection index and the distance of the sampling site. CONCLUSION

Although ¯uxes of nitrogen and phosphorus within the Save River showed the same temporal and spatial variations during Winter and Spring, i.e. rainy periods, it is obvious that their origin were di€erent. Nitrates can be clearly ascribed to agricultural di€use pollution which originated from fertilised croplands. This is in accordance with other results in similar agricultural drainage basins elsewhere in the world (Kattan et al., 1986; Correll et al., 1992; Haycock and Pinay, 1993; Keeney and Deluca, 1993; Skaggs et al., 1994). However, it is important to notice that Thomas et al. (1992) found in streams draining small agricultural watersheds that nitrate and phosphorus levels within the streams should be ascribed more to parent geology of the watersheds or to sewage from houses than to fertilizer. Our study did not con®rm this result for nitrates. Moreover, we found that phosphorus loads within the river, were strongly dependant on both the presence of the village as point source pollution in the ¯at part of the watershed and of the di€use origin of P pollution through runo€ in its hilly

N and P inputs in a rural river network

part, underlying the critical role of the drainage basin's slope. These results can be linked to the environmental European standards concerning the N and P concentrations in outlets of waste water treatment plants of cities in agricultural watersheds. In the case of the Save River, since nitrates within the river were mainly originated from croplands, tertiary treatment plant should privilege P retention. We found that the Save riverbed constitutes a sink for TP during the Summer period. However, we still lack to know if the Save sediments represent a permanent retention system or may release phosphorus either by riverbed scouring during ¯ood events or by leaching in a more soluble form such as ortho-P under anoxic conditions. AcknowledgementsÐThe authors thank the Compagnie d'AmeÂnagement des Coteaux de Gascogne which have provided the discharge data. We would like to express our gratitude to our colleagues, E. Chauvet, F. Gazelle, D. Lacaze and M. F. Patau for their ®eld and laboratory assistance. We thank Caroline Richards for editing the English text.

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