S Jacqueminet

K Kermadi

T Michel

C Joliveau

E Dodane

Volte

Mériem Labbas
email: meriem.labbas@irstea.fr

; Flora Branger

Isabelle Braud

Sven Kralisch

Christine Jacqueminet

Saïda Kermadi

; Kristell

Thierry Joliveau

Clément Dodane

Emmanuelle Volte

Multi-scale approach to assess the impacts of land use evolution and rainwater management practices on the hydrology of periurban catchments : application to the Yzeron catchment (150 km2)

 Periurban catchments = combination of natural areas, rural areas with dispersed settlements and urban areas mostly covered by built zones and spots of natural surfaces  especially affected due to fast anthropogenic modifications (Braud et al., 2013).

 General guideline: European Water Framework Directive (2000) and Floods

Directive (2007)  integrated and sustainable solutions needed to reduce flooding risks and river pollution at catchment scale.

 Our objective: Quantify the impact of urbanization and stormwater management on the long-term hydrological cycle of medium-sized periurban watersheds.

• DEVELOPMENT OF A PERIURBAN MODEL J2000P

 The hydrological distributed model J2000:

process-oriented / fully distributed / irregular meshes based on the HRU concept (Fig. 7) open source / modular based on JAMS framework (Kralisch et al., 2007 ; Multi-scale approach to assess the impacts of land use evolution and rainwater management practices on the hydrology of periurban catchments. Application to the Yzeron catchment (150 km 2 ).

Approche multi-échelles pour étudier les impacts de l'évolution de l'occupation du sol et de la gestion des eaux pluviales sur l'hydrologie de bassins versants périurbains. Application au bassin de l'Yzeron (150 km2).

• CASE STUDY

 Hydro-meteorological monitoring since the 1990's (OTHU, Fig. 4).

Mean annual rainfall ≈ 830 mm.

 Steep slopes upstream (Fig. 4) + low soil water storage capacity  quick Mediterranean-type floods  Fast growing urbanization led to an increase of impervious areas since 1980's. In 2008, the catchment was covered by 25% of impervious surfaces, 42% of agricultural areas and 33% of forests (Fig. 5).

 In urban areas: rainwater is mainly directed to the waste water treatment plant (WWTP) outside of the basin using combined sewer network (Fig. 6).

• CONCLUSIONS AND PERSPECTIVES

 The daily J2000 model is an appropriate simulation tool for studying the water balance of the Yzeron catchment. To model periurban hydrology, structure and parameters need to be adapted  model J2000P.

 Although no comparison with measured sewer runoff and overflow data was made yet to assess the model performance, it can be concluded that the model reproduces qualitatively well the expected urban behavior of the catchment.

 Ongoing work focus on the HRUs delineation which has to take into account the different hydrological objects in periurban areas and their optional connections to the rainwater system. More studies have also to be conducted on the routing inside the HRUs.

• Acknowledgments and bibliography  The simulations mostly overestimate the runoff (Fig. 13) because of a low simulated evapotranspiration which seems to be limited by a small soil water availability. At present, the most important peak events (April, Nov., Dec.) are not well estimated by the model.

 The simulation of the sewer network decreases the river runoff as expected (Fig. 13). The introduction of SOD generates occasional overflows from the sewer to the river.

 The sewer flow is affected by the presence of SOD (Fig. 14). Overflows happen for almost all the SODs (Fig. 15) and some can really impact the environment (polluted water), especially during low flow periods.

-Water flow paths modifications  explicit description of the sewer network + HRU outflows connected to the sewer and river networks (Fig. 9)

-Overflows from the sewer to the river  implementation of a Sewer Overflow Device (SOD) module (Fig. 10)

-Spatialization of the infiltration coefficient (one value for each HRU) Mériem Labbas 1 ; Flora Branger 1 ; Isabelle Braud 1 ; Sven Kralisch 2 ; Christine Jacqueminet 3 ; Saïda Kermadi 3 ; Kristell Michel 3 ; Thierry Joliveau 4 ; Clément Dodane 4 ; Emmanuelle Volte 5

ABSTRACT

The anthropogenic influence or "artificialization" generated by land use evolution and water flow paths modifications induces changes in the hydrology of watersheds. To help stakeholders to assess the vulnerability of their territory by addressing different rainwater management and planning issues, a methodology based on a multi-scale distributed hydrological modelling approach is proposed.

The objective is to quantify the impact of ongoing urbanization and stormwater management on the long-term hydrological cycle of a medium-sized watershed (150 km 2 ). The described method relies on several tools and data: a distributed hydrological model adapted to the characteristics of periurban areas, land use and land cover maps from different dates (past, present, future) and information about rainwater management collected from local authorities. The case study area is the Yzeron periurban catchment, located near Lyon (France).

KEYWORDS

Distributed hydrological modelling, long term water balance, land use change, rainwater management.

INTRODUCTION

Many studies showed the impact of artificialization on hydrology and ecology (Leopold, 1968;Walsh et al., 2005). Growing urbanization increases the imperviousness of previously natural or agricultural surfaces. The evolution of rainwater management leads to the development of artificial channels such as sewer networks, roads and ditches. In addition, some sustainable drainage systems such as infiltration ditches and retention basins are set up to slow down surface runoff. Sewer overflow devices are installed in combined sewer systems and deliver water, often polluted, to the river. All of these anthropogenic modifications influence the natural water flow paths and the water balance of catchments. As a result, several authors report an increase of surface runoff, a rise of storm peak flows and flood magnitude, a reduction of groundwater recharge and increasing water pollution (O'Loughlin et al., 1996 ;Beighley and Moglen, 2002 ;Burns et al., 2005, etc.).

Medium-sized periurban catchments (~ 100-150 km 2 ) are particularly subjected to fast anthropogenic modifications (Braud et al., 2013). These catchments consist of a combination of natural areas, rural areas with dispersed villages and urban areas mostly covered by built zones and spots of natural surfaces. Their boundaries are not so easy to define as they depend on both topography and rainwater management (Jankowfsky et al., 2012). In the context of the European Water Framework Directive ( 2000) and the Floods Directive ( 2007), extensive knowledge of the long-term hydrological dynamics of periurban catchments is required in order to find integrated and perennial solutions to reduce flooding and river pollution at the scale of urban conglomerations or whole catchments.

Distributed hydrological modelling is a well-recognized tool to quantify the anthropogenic alterations of the water cycle of medium-sized catchments and thus to develop rainwater management solutions at the appropriate scale. As they can take into account the heterogeneity of periurban areas, distributed models allow the determination of the main origins of water flow and the localization of the areas vulnerable to flooding and pollution. Long-term simulations provide an appraisal of river regime changes and allow the evaluation of potential scenarios for future actions. However, the temporal dynamics and the spatial scale of hydrological processes in urban and rural areas are very different and the complex interaction of both land use types is thus not easily modelled. Many hydrological models exist and most of them are designed either for urban or rural areas. In general, urban models focus on the hydraulic routing inside sewer systems and rural models on runoff generation. Few models are especially dedicated to medium-sized periurban catchments, although they are required in order to quantify the impact of modifications of land use and rainwater management on the hydrological cycle over a long time period. To address this question, we propose a methodology based on a multi-scale distributed modelling approach. We first describe the general concepts of the method.

Then, we present one application to the Yzeron catchment study area, with an adapted model called J2000P, and the first results obtained in the framework of this on-going project.

CONCEPTS AND METHODOLOGY

In order to model both urban and rural water cycles at medium scales, the main elements existing in periurban areas and defined by a kind of land use and rainwater management must be first identified as well as the dominant hydrological processes they generate. This demands for a global understanding and formalizing of small-scaled (few ha to few km 2 ) periurban hydrological processes which are then to be organized into a hierarchy. To model the long-term hydrology of medium-scaled periurban catchments, an appropriate model has to be developed or an existing one should be adapted. This model has to take into account the main elements and processes identified during the previous steps, at the appropriate temporal and spatial scales. To assess the ability of the model to simulate the long-term periurban hydrology, the model has to be evaluated using observed data.

Then, it can be used for evaluating the impacts of different past and future hydrological management scenarios, based on collected knowledge of land use/land cover and rainwater management practices.

Defining a "periurban typology"

Water production and routing depend on land use and rainwater management practices. To identify the main hydrological elements that influence the hydrological processes and should be represented in the model, we propose to establish a land use and rainwater management typology, based on the analysis of the available information for different dates. This "periurban typology" has to take into account the different types of land use such as forests, agricultural areas, large properties, farms, dense urban city centres, residential buildings, industrial areas, etc. According to their typical rainwater management practices (combined sewer system, rainwater network, agricultural drainage, combination of different techniques, no rainwater management, etc.), these types of land use are grouped together or are separated to obtain classes of similar hydrological properties (runoff generation and runoff connectivity): impervious surfaces connected to the sewer network, to the river, to a storage or to a permable surface, pervious surfaces, etc.

Thereafter, this classification is used for the construction of hydrological response units (HRUs;Flügel, 1995). These units represent "hydrologically homogeneous" areas characterized by a similar hydrological process response to climatic input. The runoff generation is related to physical parameters depending not only on land use and rainwater management practices but also on geologic and pedologic characteristics. The knowledge of these properties allows the assessment of the partition between the interception, the evapotranspiration, the infiltration and the runoff components of each HRU. Due to their ability to route generated runoff to different neighbouring elements, HRUs are an appropriate representation to take into account the modification of water flow paths by artificial channels in periurban catchments. According to its land use and rainwater management, each HRU can be connected to the river network, the sewer system or a neighbouring element in different ways.

For instance, to calculate the surface runoff produced by one HRU and identify its receivers, one needs to know both the percentage of impervious surfaces and the percentage of these surfaces connected to an artificial drainage system. Finally, different kinds of HRUs are obtained. For example, a HRU made up of dense urban areas connected to combined sewer networks produces mainly surface runoff and clear water infiltration into the sewer network. Then, depending on whether or not the waste water treatment plant is within the catchment, the water balance is modified. Another HRU made up of residential areas connected to a separated sewer network can transfer its runoff more or less directly to the river depending on its rainwater management.

Process representation using a multi-scale approach

The second step of the method aims at improving the representation of hydrological periurban processes to model the long-term regime of medium-sized periurban catchments. To simplify the complexity of the hydrological processes occurring at the scale of medium catchments, small-scaled hydrological processes are identified and organized into a hierarchy. Only the main processes are to be implemented at the larger target scale. For this purpose, the results of existing detailed hydrological simulations, obtained at smaller scales (districts or small-sized catchments) and described in the literature are analyzed and synthesized. In particular, two detailed models have been already identified: URBS and PUMMA.

URBS is an object-oriented model (Rodriguez et al., 2008) which describes the runoff generation using a detailed spatial description of urban areas. The sewer system and each cadastral unit, including their buildings, gardens and adjacent streets, are represented explicitly. A module describing sustainable rainwater systems was also implemented. This model is used to assess the modification of water pathways due to the introduction of sewer networks. It was already applied to two small catchments, Gohards (180 ha) and Rezé (5 ha), France. The second model is the distributed PUMMA model (Jankowfsky, 2011) which uses an object-oriented and modular approach to describe periurban areas. It consists of a combination of two models within a modelling framework : URBS for the modelling of urban objects and BVFT (Bassin Versant Fontaine du Theil, Branger, 2007) for the modelling of rural objects such as agricultural fields and forested areas. PUMMA was already applied to the Chaudanne catchment (4.1 km 2 ) located in the Yzeron catchment, France. The results of long-term simulations on this catchment already showed the importance of urban influenced processes on the hydrological response, in particular surface runoff generation on impervious and natural urban areas and infiltration into the sewer system. The connection of urban areas to the natural river was also pointed out to be a key parameter for periurban catchments modelling.

After this understanding step, the dominant hydrological processes and objects defined during the previous steps have to be implemented in a larger scaled model. This model has to be able to simulate the modifications caused by urban areas on runoff generation and water routing. For example, Braud et al. (2013) showed that a periurban catchment of 150 km 2 can have a response time of 12 hours. So, in order to better represent the faster responses of urban areas, the modelling time step has to be less than one day. Branger et al. (2013) found that the simulation of the water balance of the same catchment with a distributed model resulted in an overestimation of the discharge in urbanized subcatchments. The absence of sewer representation and an overestimation of the runoff coefficients were assumed to be mainly responsible for these results and thus should be changed. Finally, the representation of hydrological processes must also be thought depending on the periurban topology. As mentioned before, each HRU represents specific hydrological properties. The dominant processes occurring within these units depend on their percentage of imperviousness, vegetation, type of drainage and also on the connection of the different land uses to the routing channels. This last point must be taken into account in the model.

Model set up and evaluation

In distributed modelling, the first step consists of the spatial discretization required by the selected model. Here, we propose a discretization based on the HRU concept and the periurban typology established previously. The delineation of each HRU depends on the land use, rainwater management, soil, geology, aspect and slope criteria of the study catchment. The connections between HRUs, the river network and the sewer networks can be determined in reference to the rainwater management so that the topology can take into account the modifications of water flow paths caused by artificial channel networks. For this purpose, the periurban catchment delineation method of Jankowfsky et al. (2012) can be used. It takes into account both topography and water flow path modifications due to the sewer system to define catchments boundaries. This method was already applied to the Yzeron catchment for the delineation of artificial and natural subcatchments (Branger et al., 2012;2013). The HRU segmentation has also to be adapted to the simulation time step and the identified dominant processes. The second step is the specification of model parameters based on the existing information. As there is a close relationship between parameter values and the available measured data, an additional calibration of model parameters is not necessary (Branger et al., 2013).

Then, the model's ability to simulate the most important hydrological processes within the catchment must be assessed. The verification can be done based on present land use and rainwater management state, using several years of climate forcing time series. For a better evaluation, the simulation results are compared with observed discharge at different nested gauging stations located along the natural and artificial channel networks. A set of performance indicators can be used to quantify these results and hydrological signatures can be extracted from the hydrological series to characterize the global regime, high flows, low flows and seasonal flows (Braud et al., 2013).

Finally, once the model is validated, it can be used to test the effects of different past and future land use and rainwater management scenarios on the catchment hydrology. These scenarios can be built based on land use maps and the analysis of the evolution of rainwater management. Different assumptions about the rainwater management can also be used to build scenarios of potential future development. Depending on the density of impervious areas, various hypotheses concerning the presence or absence of combined and rainwater sewer systems, as well as the existence of sustainable drainage systems, can be tested. To assess the hydrological impacts of these scenarios, different model output variables are of interest: evapotranspiration and water soil storage, total discharge and its components (surface runoff, interflow, base flow) at the artificial and natural outlets of the whole catchment or various subcatchments. Flow separation hydrographs and filtering methods (Willems, 2009) can be used to compare the simulated and observed components of the urban and rural flows.

APPLICATION SITE AND AVAILABLE DATA

Presentation of the Yzeron catchment

The method is applied to the medium-sized Yzeron catchment (150 km 2 ), located in the Southwest of Lyon, France (Figure 1). This catchment is representative for French periurban areas and is characterized by a contrasted topography and a changing land-use. Upstream, the hills culminating at 917 meters are mainly covered by forests on steep slopes. The middle part consists of urban nuclei surrounded by grassland and cultivated lands. Downstream, there are densely urbanized zones and the altitude reaches 162 meters at the outlet of the catchment, the Rhône river. Since the 1980's, a fast growing of urbanization has been observed at small urban centres and along the road networks (Cottet, 2005 ;Gnouma, 2006;Radojevic et al., 2010). The analysis of digitized aerial photographs and satellite images showed an increase of impervious areas (Kermadi et al., 2013). The catchment is also characterized by a limited soil water storage capacity due to its geology: crystalline rock (granite and gneiss) in the western part and alluvial and glacier formations in the eastern part. The climate is temperate, with continental and Mediterranean influences. The watershed receives annually about 830 mm of precipitation (www.meteofrance.fr, 2012). Due to steep slopes upstream and a low soil water storage capacity, quick Mediterranean-type floods can occur and impact the urbanized areas downstream.

The Yzeron catchment is a part of the Field Observatory for Urban Water Management (OTHU, 2012).

As such, it is very well-documented over a long time period.

Hydrological and meteorological data

A network of measurement stations was set up over the catchment providing quite long time series of both precipitation and discharge (Figure 1). Four rain gauges monitoring precipitation with a 6 min time

GIS data and urban database

A digital elevation model (DEM) from BDTopo®IGN is available with a 25 m resolution. A geological map of the region at the 1:50000 scale was digitized by Gnouma (2006). The pedological map comes from the French DONESOL programme (SIRA, 2012). The French national database BDCarthage provided maps of the river network. In the framework of the AVuPUR (Assessing the Vulnerability of Peri-Urban Rivers) project (Braud et al., 2010), past, present and future land use maps from 1945 to 2030 were produced using different remote sensing images: BDOrtho®IGN aerial photographs, QuickBird satellite images and Spot satellite images (Jacqueminet et al., 2013), and territorial prospective (Dodane et al., 2010). Land use maps are available for 1945, 1970, 1990 and 2008 and land cover maps for 1990, 1999, 2008 (Figure 2). In 2008, the catchment was covered by 25 % of impervious surfaces, 42 % of agricultural areas and 33 % of forests. Maps of future land use scenarios provide different perspectives of urbanization. The maps of the sewer networks were obtained from local authorities (Grand Lyon and SIAHVY, Figure 3). The associated data are the localization of sewer pipes and pumping stations, the flow directions, the type of pipes (combined or separate systems for waste water and rainwater) and their diameter, and the localization of waste water treatment plants (WWTP). There are two local WWTP within the basin, in the municipalities of Yzeron (since 2011) and Saint-Laurent-de-Vaux (since 2012), but most of the rainwater collected by combined sewer systems goes to a WWTP outside of the catchment (Pierre-Bénite).

Elements on rainwater management

From the information that could already be gathered, the rainwater management of the Yzeron catchment is divided into three zones: the eastern part managed by the local authority Grand Lyon (GL), the western part managed by the sanitation syndicate SIAHVY and some municipalities which keep their rainwater responsibility (e.g., programming and financing of rehabilitation works). In urban areas, rainwater is in most cases directed to the WWTP using Combined Sewer System (CSS). In some places, the houses are not connected to a sewer system and infiltrate their rainwater directly on-site. The rainwater management is mainly influenced by the policy of GL which manages the principal drain of the sewage disposal and the main WWTP at Pierre-Bénite. An agreement made between the GL and the cities in the catchment sets a theoretical maximum discharge which passes through the main drain (for e.g., 110 L/s for Brindas and 90 L/s for Vaugneray). Since 1995, GL has been carrying out an active rainwater management policy which is followed by almost each local authority of the different cities of the catchment. It recommends that all rainwater falling on a newly built place should not reach a sewer system. In most cases, it is advised to let the rainwater infiltrate on-site using a retention basin or a seepage well. If this is not possible, which can be the case on the Yzeron catchment where the soil water storage is very limited, the rainwater can be connected to a natural or separate network after retention (e.g. underground tank). The acceptable discharges are 10 L/s/ha in case of a disposal into a ditch or a separate sewer system and 5 L/s/ha in case of a disposal into a combined sewer system. In the old sewer systems, retention basins and SODs were installed. Finally, a project of a rainwater tax has been studied by GL in order to encourage industrial and private owners to disconnect their rainwater from the CSS. This is still not implemented but it offers various guidelines for the design of future rainwater management scenarios.

MODELLING TOOL AND FIRST RESULTS

Model choice

The model chosen for the application of the method described in section 2 is a periurban version of the J2000 model (Krause et al., 2006), called J2000P. J2000 is a modular, open-source model available through the JAMS modelling framework (Kralisch et al., 2007). It is thus freely available, new simulation components can be easily developed and integrated to adapt the model to the requirements of periurban catchments (see Section 4.3). J2000 is a fully-distributed hydrological model, which was developed for continuous long-term modelling of meso-and macro-scale rural catchments. It simulates hydrological processes on irregular meshes based on the concept of HRUs.

As mentioned in section 2.3, the HRU discretization allows to cope with the heterogeneity of urban areas and in particular with the fact that flows are not only governed by topography but also by artificial networks (sewer, ditches, roads, etc.). Up to now, J2000 has been mainly used at a daily time step but the model can be run at any fixed time step.

Water production and routing in J2000

In J2000, hydrological processes are simulated on irregular HRUs. Five main components describe the following physical processes: interception, evapotranspiration, infiltration/surface runoff partition, soil diffusion and percolation, groundwater flow and stream flow (Figure 4). At each time step, the model simulates these processes for each HRU. The outflows are then routed laterally to the connected neighbouring HRU or river reach, according to the topology. The infiltration/surface runoff partition is controlled by the surface sealed grade, the average soil saturation of the HRU and a maximum infiltration rate. A depression storage can slow down surface runoff water before it reaches the HRU's outlet. Infiltrating water is distributed to two soil reservoirs with different porosities: the middle pore storage (MPS) and the large pore storage (LPS). Water can percolate into two groundwater compartments with different sizes and recession constants, characterized by quick and slow reactions. Thus, four runoff contributions are calculated: surface runoff (RD1), interflow (RD2), quick base flow (RG1) and slow base flow (RG2). Once they have reached the stream, these runoff components are transferred from one river reach to the other using a simplified kinematic wave approach in the flow routing module. Other components provide functions for the regionalization of climate data and the calculation of potential evapotranspiration (PET). To take into account the local context and the available data, a simplified J2000 version with only one groundwater storage was already applied to the Yzeron catchment. The components for PET calculation were removed and a crop coefficient component was developed to use ET0 time series, modulated according to the vegetation phenological development, as input data (Branger et al., 2012(Branger et al., , 2013)). The development of J2000P is based on this version.

First steps towards the J2000P periurban model

Hourly simulations

The simplified version of J2000, applied without calibration, was already evaluated and validated at the daily time step, leading to a satisfactory simulation of the long-term variations of discharge, including the seasonal variations of base flow (Branger et al., 2012(Branger et al., , 2013)). Subcatchments are used as HRUs (Figure 5) and the parameterization of the model is based on available information. For example, land use was re-classified into 5 classes (Figure 5) and average vegetation parameters (leaf area index, crop coefficient, root depth) were assigned for each class, according to FAO (1998) and Ecoclimap database (Masson et al., 2003). The infiltration is characterized by impervious rates derived from land cover maps (Jacqueminet et al., 2013, Branger et al., 2013).

However, in urban areas where hydrological responses are quicker than in rural areas, a sub-daily time step can significantly improve the simulation of periurban hydrological processes. As J2000 had not been thoroughly tested at the hourly time step before, a few adaptations were necessary. We present here the first results of the comparison of hourly and daily simulations conducted with this version of J2000. The simulations, based on the 2008 land use, were conducted over a thirteen-year period (1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010), using the year 1997 as warming period. We used the same parameter values as for the daily simulation, except that we adapted the values of time step dependent parameters. In order to compare the simulated and observed discharges, a set of performance indicators was calculated for the time period 1998-2010: the classical Nash-Sutcliffe (NS) efficiency to characterize high flows, the root mean square error (RMSE) to quantify the mean error in discharge and the bias and absolute bias (Abias) to evaluate the mass balance (Table 1). For the hourly simulation, the NS is calculated based on the daily average of hourly discharges. But, even in that case, the NS are less good for the hourly simulations which might be caused by a higher overestimation and quicker dynamics of the hourly discharge. In fact, the results of maximum and mean discharges and the analysis of the discharge evolution reflect quicker and higher reaction of the hourly discharges in response to a more noisy rain signal (see an example on Figure 6). Figure 7 and bias results show that the model tends to overestimate the discharge at the outlet and that the overestimation is higher for the hourly simulation. This can be explained by the general water balance with a higher interannual mean soil saturation (0.39) and actual evapotranspiration (AET) response (73% in percentage of rain) for the daily simulation (Figure 8). For the hourly simulations, the AET (68 % in percentage of rain) seems to be limited by a smaller soil water availability (mean soil saturation equals to 0.33). The analysis of MPS and LPS behaviours shows a quicker decrease of the amount of stored water simulated by the hourly model before the dry season. This is reflected in the relative contributions of the discharge components, also influenced by the time step change.

Concerning the groundwater, the hourly model simulates higher base flow (Figure 9) which is mainly governed by water availability. As there is less AET generated by the hourly model, higher base flow is produced. However, the base flow contribution also involves time-dependent parameters whose sensitivity must be analyzed more in depth (e.g.; a percolation rate).

Implementation of a sewer network

In order to better take into account rainwater management, an explicit representation of sewer networks is implemented in the J2000P model. It receives urban rainwater coming from impervious surfaces connected to a sewer system and delivers this water to a separate outlet or directly to the river in case of sewer overflow device (SOD) outflows. Technically, a new network made of sewer reaches is added (similarly to the river network already implemented) and a SOD module is developed. Then, as one HRU can have rural and urban fractions which can be drained differently, the model is modified to offer the possibility to assign several outlets to one HRU. In particular, different proportions of the outflows of each HRU can go to the sewer network, a neighbouring HRU and the river network.

As shown in Figure 10, the spatial routing scheme of J2000P is modified as compared to the previous version of J2000. Each sewer reach connected to the river by a SOD is characterized by a threshold and pipe dimensions. If the water height inside a sewer reach connected to a SOD is above its threshold, the excess water goes into the river. A combination of weir and orifice equations is chosen to calculate the discharge (Figure 11). In case of a rainwater system, there is a direct connection of the outlet of the sewer system to the river. Up to now, we first validated a test model with two parallel rivers (and thus two outlets) that were fed upstream using a test data set. The SOD module was also developed and validated with another test model made of two parallel reaches and one SOD, also fed using a test signal.

CONCLUSION

The methodology described in this paper consists of a multiscale approach which focuses on the understanding and the formalizing of dominant periurban hydrological processes from small scales (few ha to few km 2 ) to larger scales (~ 150 km 2 ). The objectives are to 1) simulate both urban and rural hydrological processes and 2) test the effects of different hydrological scenarios on the long-term hydrology of medium-sized periurban catchments. For the application of the method, we chose the medium-scaled catchment of Yzeron as it is subjected to a fast progression of urbanization since the eighties and has been monitored for a long time period. For the modelling, J2000 already appeared to be an appropriate simulation tool for the water balance study of the Yzeron catchment without any calibration. As it was not designed especially for periurban areas, its structure and parameters need to be adapted. For this purpose, two first adaptations of J2000 were proposed here: time step decrease and implementation of a sewer network, leading to the development of the J2000P periurban version of J2000. The first results of the hourly simulation are presented but a further sensitivity analysis has still to be done. Concerning the implementation of the sewer network, it was validated on a test case and the next step consists in testing it on the whole catchment, thanks to the available map of the sewer system.

Ongoing work will focus on a better representation of urban hydrological processes. A major step is the HRU's delineation which takes into account the different hydrological objects in periurban areas and their optional connection to the rainwater system. This delineation will hopefully improve the modelling of the water routing from upstream to downstream with the modifications generated by the artificial channels. More studies have also to be conducted on the routing inside the HRUs: the rural and the urban parts of the HRUs do not route the water in the same time and the routing depends on the distance of the different objects from the outlet of the HRU. Different methods can be tested to simulate the intra-HRU routing: sub-grid variability or average calculation. Further effort needs to be spent on the calculation of runoff coefficients. Once the model performance is validated, it will allow a better representation of historic and actual conditions. For water managers, it can be an interesting tool for testing projections of future urban development, not only for extreme conditions but also for long term and continuous periods.



  Growing urbanization  increasing water pollution (a), increase of surface runoff, rise of storm peak flows and flood magnitude (b), reduction of groundwater recharge and erosion (c).

  Fig. 8) long-term continuous simulation with fixed time steps • FIRST APPLICATION  Sewer network and SOD parameterization: 110 sewer reaches (Fig. 11): roughness=100, slope=1%,width=0.4m . 29 SOD: threshold = 50cm  First assumption: in urban HRU, connection of all impervious surfaces to the sewer  Climatic forcing: uniform hourly ET0 calculated from SAFRAN reanalysis (Vidal et al., 2010), hourly rainfall regionalized using 7 gauges. Simulations performed for the 1997-2010 period (1997 as warming-up period) .

Figure 4 :

 4 Figure 4: Situation map of the Yzeron and Taffignon catchments with indications of topography, impervious areas and measurement network.

Figure 5 :

 5 Figure 5: 2008 land use map of the Yzeron catchment derived from very high resolution satellite images (Jacqueminet et al., 2013).

Figure

  Figure 6: Current rainwater management map derived from local authorities data (Grand Lyon, SIAHVY).

Figure 9 :

 9 Figure 9: Routing in J2000P. Addition of a sewer network. Some SODs can connect sewer reaches to river reaches.

Figure 8 :

 8 Figure 8: Physical processes and runoff contributions simulated at each time step and for each HRU.

Figure 7 :

 7 Figure 7: HRU concept (Flügel, 1995).

Figure

  Figure 12: Land use based on remote sensing images (Jacqueminet et al., 2013).Re-classification into 5 classes.

Figure 10 :

 10 Figure 10: Concept of the SOD module.

Figure 13 :

 13 Figure 13: Mean interannual monthly river runoff at Taffignon between 1998 and 2010.

Figure 15 :

 15 Figure 15: Mean interannual volume from SODs (m 3 /year).

Figure 14 :

 14 Figure 14: Mean interannual monthly sewer runoff at Taffignon between 1998 and 2010.

Figure

  Figure 1: Aggregated land use map (2008) Figure 2: Reclassified 2008 land use map with the k-means method (k=5)

Figure 1 :

 1 Figure 1 : Situation map of the Yzeron and Taffignon catchments with indications of topography, river networks, urbanized areas (roads and built areas), rain and discharge gauges. The borders of the Yzeron catchment match the topographical borders derived from the DEM whereas the delineation of the Taffignon catchment also takes into account the modification of water flow paths due to stormwater and combined sewer systems.

  step have been managed by the Grand Lyon since 1985. Since 1997, Irstea manages complementary rain gauges using a variable time step. The streamflow measurement follows a strategy of nested subcatchments from 2 km 2 to 129 km 2 , with varying land-uses. Discharge stations are maintained by DREAL Rhône Alpes and Irstea, and provide data with a variable time step at different subcatchments, some of them nested, since 1970. In addition, discharge data coming from the outlets of sewer overflow devices have been collected by Irstea since 2001 in the Chaudanne subcatchment and by the SIAHVY, an association of municipalities monitoring sewer networks, since 2010. The climatic data were derived from the SAFRAN reanalysis database (Vidal et al., 2010) provided by Météo-France over a 8*8 km 2 grid from 1970 to 2011 at an hourly time step. This data set is used for the computation of the reference evapotranspiration (ET0) following the FAO (1998) method.

Figure 2 :

 2 Figure 2 : Land cover map provided by the analysis of SPOT images (2008).

Figure 3 :

 3 Figure 3 : Map of the present rainwater management on the Yzeron catchment.

Figure 4 :

 4 Figure 4: Physical processes and runoff contributions simulated for each HRU.

Figure 5 :

 5 Figure 5: HRU delineation and land use classification derived from remote sensing images.

Figure 8 :

 8 Figure 8: Comparison between daily and hourly evapotranspiration (ET) results.

Figure 9 :

 9 Figure 9 : Comparison of interannual monthly mean hourly and daily base flow.

Figure 6 :

 6 Figure 6: Hourly (black) and daily (red) simulated surface runoff over one hydrological year. The hourly rain is drawn in grey

Figure 7 :

 7 Figure 7: Comparison of interannual monthly mean hourly and daily simulated discharges and observed discharges at the outlet of the catchment.

Figure

  Figure 10 : Spatial routing scheme of J2000P.

Figure 11 :

 11 Figure 11 : Outline of the functioning of a SOD. The SOD is parameterized by its height Hp and width Wp.

1

  Irstea, Lyon UR HHLY (corresponding author: meriem.labbas@irstea.fr). 2 Department of Geoinformatics, University of Jena, Löbdergraben 32, 07743 Jena, Allemagne. 3 Université de Lyon, UMR CNRS EVS, 18 Rue Chevreul, 69363 Lyon Cedex 7, France. 4 Université de Saint-Etienne, UFR SHS, 33, Rue du 11 Novembre, 42023 Saint-Etienne Cedex 2, France. 5 Grand Lyon, Direction de l'eau, Unité Etudes générales et modélisation, 117 boulevard Marius Vivier Merle, 69003 Lyon, France.

Table 1 :

 1 Set of performance indicators based on daily (D) and hourly (H) simulations over the period 1998-2010, at the catchment outlet (Taffignon). For the hourly simulation, the indicators were calculated based on the daily average of the hourly discharge.

		NS [-]	RMSE [m 3 /s]	Bias [%]	Abias [%]	Qmean [m 3 /s]	Qmax [m 3 /s]
	D	0.46	1.06	38	74	0.86	45.2
	H	0.17	1.31	68	98	1.04	60.4

ACKNOWLEDGEMENTS

Some of the data used in this study are taken from the ANR VMCS AVuPUR project (contract ANR-07-VULN-01) and OTHU. The study is conducted under the EC2CO BVPU/ROSENHY project.

catchment, France. Proceedings of the iEMSs 2012 International Congress, Leipzig, Germany. Branger, F., Kermadi, S., Jacqueminet, C., Michel, K., Labbas, M., Krause, P., Kralisch, S., Braud, I., (2013).

Assessment of the influence of land use data on the hydrology of a periurban catchment using a distributed modelling approach, Journal of Hydrology, in revision. Braud, I. et al. (2010). The AVuPUR project (Assessing the Vulnerabiliy of Peri-Urbans Rivers) : experimental set up, modelling strategy and first results, Proceedings of the 7th Novatech 2010 Conference, June 28-July 1 2010, Lyon, France, 10pp. http://hal.archives-ouvertes.fr/hal-00527564_v1/ Braud, I., Breil, P., Thollet, F., Lagouy, M., Branger, F., Jacqueminet, C., Kermadi, S., Michel, K., (2013).

Evidence of the impact of urbanization on the hydrological regime of a medium-sized periurban catchment in France, Journal of Hydrology, 485, 5-23. Burns, D., Vitvar, T., McDonnell, J., Hassett, J., Duncan, J. and Kendall, C. (2005). Effects of suburban development on runoff generation in the Croton River basin, New York, USA. J. of H., 311(1-4):266-281. Cottet, M. (2005). Evolution de l'occupation du sol dans le bassin versant de l'Yzeron au cours du XXème sicècle: premiers éléments pour un diagnostic hydrologique. Université Jean Moulin, Lyon III, Lyon. Dodane, C., Joliveau, T., Honegger, A. and Molines, N. (2010). Simuler les changements d'occupation du sol à l'horizon 2030. CNRS UMR EVS, Atelier Yzeron. FAO (1998). Crop Evaporation -Guidelines for computing crop water requirements. Irrigation and Drainage paper n°56, FAO, Rome. Flügel, W. . (1995). Delineating hydrological response units by geographical information system analyses for regional hydrological modelling using PRMS/MMS in the drainage basin of the river Brol, Germany. Hydrological Processes, 9(3-4):423-436. Gnouma, R. (2006). Aide à la calibration d'un modèle hydrologique distribué au moyen d'une analyse des processus hydrologiques: application au bassin versant de l'Yzeron. INSA, Lyon, France, 448 pp. Grand Lyon. (2006). Aménagement et eaux pluviales sur le territoire du Grand Lyon, Guide pratique. Jacqueminet C., Kermadi S., Michel K., Béal D., Branger F., Jankowsky S., Braud I., (2013). Land cover mapping using aerial and VHR satellite images for distributed hydrological modelling of periurban catchments: application to the Yzeron catchment (Lyon, France), Journal of Hydrology, 485, 68-83. Jankowfsky, S. ( 2011). Understanding and modelling of hydrological processes in small peri-urban catchments using an object-oriented and modular distributed approach. Application to the Chaudanne and Mercier subcatchments, France. UJF, Grenoble, France, 321 pp. http://tel.archives-ouvertes.fr/tel-00721988 Jankowfsky, S., Branger, F., Braud, I., Gironás, J. and Rodriguez, F. (2012). Comparison of catchment and network delineation approaches in complex suburban environments: application to the Chaudanne catchment, France. Hydrol. Process. doi: 10.1002/hyp.9506 . Kermadi, S., Braud, I., Jacqueminet, C., Branger, F., Renard, F., Michel, K., (2013). Quels liens entre climatologie, occupation des sols et inondations dans le bassin versant de l'Yzeron (ouest Lyonnais) ? Apport de l'analyse conjointe de données hydroclimatiques et d'images satellitaires très haute résolution, Climatologie, in press. Kralisch, S., Krause, P., Fink, M., Fischer, C. and Flügel, W.-A (2007). Component based environmental modelling using the JAMS framework, in L. Oxley & D. Kulasiri, Eds., MODSIM 2007, pp. 812-818. Krause, P., Bäse, F., Bende-Michl, U., Fink, M., Flügel, W. and Pfenning, B.(2006) Multiscale investigations in a mesoscale catchment -hydrological modelling in the Gera catchment, Advances in Geosciences, 9, 53-61. Leopold, L. (1968). Hydrology for urban landplanning-A guidebook on the hydrologic effects of urban land use.

U.S. Geological Survey Circular 554. Masson, V., Champeaux, J.L., Chauvin, F., Meriguet, C., Lacaze, R., (2003). A global database of land surface parameters at 1-km resolutionin meteorological and climate models. J. Climate, 16(9), 1261-1282. O'Loughlin, G., Huber, W. and Chocat, B. (1996). Rainfall-runoff processes and modelling. Journal of Hydraulic Research, 34(6):733-751. OTHU (2012). http://www.graie.org/othu/. Consulted on 2012/10/23. Radojevic, B., Breil, P. and Chocat, B. (2010). Assessing impact of global change on flood regimes. International Journal of Climate Change Strategies and Management, 2(2), 167-179. Rodriguez, F., Andrieu, H. and Morena, F. (2008). A distributed hydrological model for urbanized areas -model development and application to case studies. J Hydrol, 351(3-4):268-287. SIRA (2012). Sol Info Rhône-Alpes, -http://www.rhone-alpes.chambagri.fr/sira/. Consulted on 2010/09/16. Vidal, J.P., Martin, E., Franchisteguy, L., Baillon, M. and Soubeyroux, J.M. (2010). A 50-year high-resolution atmospheric reanalysis over France with the SAFRAN system. Int J Climatol, 30(11), 1627-1644. Walsh, C. J., Fletcher, T. D. and Ladson, A. R. (2005). Stream restoration in urban catchments through redesigning stormwater systems : looking to the catchment to save the stream. Journal of the North American Benthological Society, 24(3):690-705. Willems, P. (2009). A time series tool to support the multi-criteria performance evaluation of rainfall runoff models.

Environmental Modelling and Software, 24(3):311-321.

LIST OF REFERENCES

 Beighley, R. E. and Moglen, G. E. (2002). Trend assessment in rainfall-runoff behavior in urbanizing watersheds.

Journal of Hydrologic Engineering, 7(1):27-34.

Branger, F. (2007). Utilisation d'une plate-forme de modélisation environnementale pour représenter le rôle d'aménagements hydro-agricoles sur les flux d'eau et de pesticides. Application au bassin versant de la

Fontaine du Theil (Ille-et-Vilaine). Université Joseph Fourier, Grenoble I, Grenoble, France. Branger F., Kermadi S., Krause P., Labbas, M., Jacqueminet, C., Michel, K., Braud, I. and Kralisch, S. (2012),

Investigating the impact of two decades of urbanization on the water balance of the Yzeron peri-urban


Samantha Bailey
email: samantha.bailey@irstea.fr

Fabrice Requier

Benoît Nusillard

Stuart P M Roberts

Simon G Potts

Christophe Bouget

Distance from forest edge affects bee pollinators in oilseed rape fields

Keywords: Andrena, bee dispersal, ecosystem service, foraging range, Nomada, partial habitats, wild bees

). Synthesis and Applications. This study provides one of the first examples in temperate ecosystems of how forest edges may actually act as a reservoir of potential pollinators and directly benefit agricultural crops by providing nesting or mating sites for important early spring pollinators. Policymakers and land managers should take forest edges into account and encourage their protection in the agricultural matrix to promote wild bees and their pollination services.

Introduction

Pollinators play an important functional role in most terrestrial ecosystems and provide a key ecosystem service [START_REF] Ashman | Pollen limitation of plant reproduction: ecological and evolutionary causes and consequences[END_REF]). Insects, particularly bees, are the primary pollinators for the majority of the world's angiosperms [START_REF] Ollerton | Overplaying the role of honey bees as pollinators: a comment on Aebi and Neumann (2011)[END_REF]. Without this service, many interconnected species and processes functioning within both wild and agricultural ecosystems could collapse [START_REF] Kearns | Endangered mutualisms: the conservation of plant-pollinator interactions[END_REF]. Brassica napus (oilseed rape, OSR) represents the most widespread entomophilous crop in France with almost 1.5 Mha in 2010 (FAOSTAT August 10th, 2012). Results differ between varieties, but even though it seems that OSR produces 70% of its fruits through self-pollination (Downey et al. 1970 in Mesquida and[START_REF] Mesquida | Pollination of male-fertile and male-sterile winter rapeseed (Brassica-napus L var Oleifera Metzger) by the honey bee (Apis-mellifica L) -Effects on phenology and yield[END_REF], native bees are also known to contribute to its pollination [START_REF] Morandin | Wild bee abundance and seed production in conventional, organic, and genetically modified canola[END_REF][START_REF] Jauker | Pollination efficiency of wild bees and hoverflies provided to oilseed rape[END_REF]. Bee pollination leads to improved yields (Steffan-Dewenter 2003b;[START_REF] Sabbahi | Influence of honey bee (Hymenoptera: Apidae) density on the production of canola (Crucifera: Brassicacae)[END_REF] and to a shorter blooming period [START_REF] Sabbahi | Does the honeybee (Hymenoptera: Apidae) reduce the blooming period of canola?[END_REF], thus increasing the crop's market value [START_REF] Bommarco | Insect pollination enhances seed yield, quality, and market value in oilseed rape[END_REF]. The most widely used species in crop pollination is the honeybee (Apis mellifera L) which is sometimes assumed to be sufficient for worldwide crop pollination [START_REF] Aebi | Endosymbionts and honey bee colony losses?[END_REF]. However, this assertion has been questioned by different authors [START_REF] Ollerton | Overplaying the role of honey bees as pollinators: a comment on Aebi and Neumann (2011)[END_REF], and several studies show that many wild bees are also efficient pollinators of crops [START_REF] Klein | Importance of pollinators in changing landscapes for world crops[END_REF][START_REF] Winfree | Wild bee pollinators provide the majority of crop visitation across land-use gradients in New Jersey and Pennsylvania, USA[END_REF][START_REF] Breeze | Pollination services in the UK: how important are honeybees?[END_REF]. Recently, [START_REF] Garibaldi | Wild pollinators enhance fruit set of crops regardless of honey bee abundance[END_REF] found positive associations of fruit set with wild-insect visits to flowers in 41 crop systems worldwide. They demonstrate that honeybees do not maximize pollination, nor can they fully replace the contributions of diverse, wild-insect assemblages to fruit set for a broad range of crops and agricultural practices on all continents with farmland. Unfortunately, not only are honey bees declining due to a variety of different causes [START_REF] Vanengelsdorp | Colony collapse disorder: a descriptive study[END_REF], wild bee populations are also dwindling [START_REF] Potts | Global pollinator declines: trends, impacts and drivers[END_REF]. Their decline has been documented in two Western European countries (Britain and the Netherlands) by comparing data obtained before and after 1980 [START_REF] Biesmeijer | Parallel declines in pollinators and insect-pollinated plants in Britain and the Netherlands[END_REF]). These losses have mostly been attributed to the use of agrochemicals, the increase in monocultures, the loss of seminatural habitat and deforestation [START_REF] Steffan-Dewenter | Scale-dependent effects of landscape context on three pollinator guilds[END_REF][START_REF] Steffan-Dewenter | The interplay of pollinator diversity, pollination services and landscape change[END_REF][START_REF] Brittain | The potential impacts of insecticides on the life-history traits of bees and the consequences for pollination[END_REF].

Several studies have shown the importance of natural or seminatural habitats in sustaining pollinator populations or pollination services close to fruit crops (Steffan-Dewenter 2003a; [START_REF] Kremen | The area requirements of an ecosystem service: crop pollination by native bee communities in California[END_REF]Greenleaf and Kremen 2006a;[START_REF] Carvalheiro | Pollination services decline with distance from natural habitat even in biodiversity-rich areas[END_REF]. [START_REF] Morandin | Pollinators provide economic incentive to preserve natural land in agroecosystems[END_REF] presented a cost-benefit model that estimates profit in OSR agroecosystems with different proportions of uncultivated land. They calculated that yield and profit could be maximized with 30% of the land left uncultivated within 750 m of field edges. Other studies have demonstrated a negative impact of the distance from forests on pollination services or bee abundance and richness both in tropical ecosystems [START_REF] De Marco | Services performed by the ecosystem: forest remnants influence agricultural cultures' pollination and production[END_REF][START_REF] Blanche | Proximity to rainforest enhances pollination and fruit set in orchards[END_REF][START_REF] Chacoff | Edge effects on flower-visiting insects in grapefruit plantations bordering premontane subtropical forest[END_REF] and in temperate ecosystems [START_REF] Hawkins | Factors affecting the yield of seed produced by different varieties of red clover[END_REF][START_REF] Taki | Landscape effects of forest loss in a pollination system[END_REF][START_REF] Arthur | Influence of woody vegetation on pollinator densities in oilseed Brassica fields in an Australian temperate landscape[END_REF][START_REF] Watson | Forested landscapes promote richness and abundance of native bees (Hymenoptera: Apoidea: Anthophila) in Wisconsin apple orchards[END_REF].

These studies all suggest that natural or seminatural habitats are important sources of pollinators, probably because they provide "partial habitats" [START_REF] Westrich | Habitat requirements of central European bees and the problems of partial habitats[END_REF]) such as complementary mating, foraging, nesting, and nesting materials sites that bees need to complete their life cycle. In this study, we focused on the effect of distance to forest edge on bee assemblages in OSR ecosystems. Forest edges could provide one or more important partial habitats for different bee species in agricultural landscapes, in particular when associated with a massflowering crop such as OSR [START_REF] Le Feon | Solitary bee abundance and species richness in dynamic agricultural landscapes[END_REF]. For example, the availability of untilled soil and dead branches might provide ground-nesting and cavity-nesting bee species with numerous nesting sites. Moreover, during spring at least, the understory and the forest edge can provide cover containing flowering plants and wild trees such as Prunus spp, Castanea sativa, or Salix spp and thereby allow bees to find alternative floral resources.

During spring 2010 and 2011, in two areas in France, we examined wild bee abundance and taxa richness both along forest edges and inside OSR fields at different distances from the forest. Like other taxa, bees respond to environmental variables according to their biologic traits that determine access and requirements for nesting, mating, and forage resources, species mobility or physiological tolerance. Specifically, we hypothesized that (1) bee abundance, species richness, and composition of bee communities within the crop field are dependent on the distance from the forest edge (where complementary floral resources, nesting sites, shelters, etc. can be found) and on the orientation of the forest edge; (2) the identity of bees in the crop is related to their foraging range which we measured with the ITD (Inter-Tegular distance); (3) the forest edge may be the nesting or mating sites for cavity-nesting or ground-nesting bees such as Osmia spp or Andrena spp which are important groups of potential early spring pollinators for OSR.

Materials and Methods

Study sites

The field work was conducted in 2010 near Orleans, France (latitude 47.8537191, longitude 2.7499075), and in 2011 in the same area and in addition, near Toulouse, France (latitude 43.3030938, longitude 0.9914780). These two study areas are 700 km from each other. In 2010, we selected eight fields sown with B. napus and in 2011, a total of ten fields in both areas (Fig. 2). The 28 fields were selected with at least one of their sides directly adjacent to a forest with indigenous deciduous tree species (mainly Quercus, Carpinus and Populus spp.). We classified 11 forest edges as "cold orientation" (northern and eastern exposure) and 17 forest edges as "warm orientation" (southern and western exposure) according to the amount of Celsius degree they received during the day. The fields we selected in 2010 and 2011 had forest edges of at least 100 m in length. In 2010, we had two study point distances from forest edge, 50 m and 200 m. Our 200-m study points were distant from other edges by at least 200 m. In 2011, we also had two study point distances from forest edge, 10 m and the further one varied from 30 to 230 m (Fig. 3).

Bee sampling

We used yellow pan traps to sample bees, while the OSR was in bloom; this is a common passive sampling method (Dafni et al. 2005in Westphal et al. 2008). The traps were plastic bowls (approximately 30 cm in diameter and 23 cm in height) with an UV-reflecting paint (S.P.R.L, Spray-color 18 133UK, Brussels, Belgium) sprayed on the inside. They were mounted on wooden poles at vegetation height [START_REF] Westphal | Measuring bee diversity in different European habitats and biogeographical regions[END_REF]) and filled with approximately 2.4 L of water, 0.6 L of monopropylene glycol for conservation, and a few drops of liquid soap to lower surface tension, and then were exposed for 15 days during the blooming period. In 2010, we placed two pan traps at each distance from forest edge: 0 m (forest edge), 50 m, and 200 m into the crop. In 2011, we placed one pan trap at each distance: 0 m (forest edge), 10 m, and a third location varying between 30 and 230 m into the crop. Collected specimens were stored in a freezer, then dried, mounted, and identified to the species level when possible. Some specimens could only be determined to the genus (Nomada, Sphecodes) or subgenus (Micrandrena) level. The specimens were also separated into males and females.

Data analysis

Hypothesis 1: bee abundance, species richness, and composition of bee communities within the crop field are dependent on the distance from the forest edge and forest edge orientation

We constructed generalized additive mixed models (R; mgcv package) to test our hypotheses about total bee abundance and bee species richness as a function of distance and orientation (2-level categorical variable specifying a cold or warm orientation). In addition to the interaction between distance and orientation, we included year (n = 2) and field area (n = 2) as additional fixed effects and the field identity (n = 28) as a random effect. Residuals analyses motivated us to use a Poisson distribution for the abundance and a normal distribution for the species richness (Table 1). In our analysis of species richness, we also included total abundance as a covariate.

To examine how the composition of the bee community varied with distance and orientation, we used canonical analysis of principal coordinates (CAP) (R package: vegan, function: capscale; R Core Team 2012). This method allowed us to quantify and test the individual contribution of qualitative variables (year, geographic area, field, and orientation) and the quantitative variable (distance) to variations in total assemblage composition. We used the Jaccard similarity index and carried out an inertia partitioning to estimate the total variance in assemblage composition, total constrained inertia (i.e., explained by all the variables included in the model), and the relative individual contribution of each variable to the constrained inertia [START_REF] Anderson | Canonical analysis of principal coordinates: a useful method of constrained ordination for ecology[END_REF].

Hypothesis 2: the identity of bees in the crop is related to their foraging range To examine how bee identity varied with distance and orientation of forest edge, we examined how the mean female ITD (Inter-Tegular distance: the distance between the bases of the two wings) varied with distance and orientation. As above, we modeled the mean female ITD using a generalized additive mixed model. In addition to the interaction between distance and orientation, we included year (n = 2) and field area (n = 2) as additional fixed effects and the field identity (n = 28) as a random effect. We used a normal distribution and we also included total abundance as a covariate. Only females and traps with at least two specimens were included in this analysis (2 traps were therefore excluded). Males were not included in the analysis of mean ITD because they do not take care of brood so they do not collect pollen; their principal requirement is finding females with which to mate. On the contrary, females take care of the brood so they must find appropriate nesting sites and supply the larvae with food. Moreover, females exhibit central-place foraging, so they actively travel from crop to nest. They are the actual OSR pollinators. The parasites Bombus (Psithyrus), Nomada, and Sphecodes were not included in the analysis of the mean ITD because they also do not take care of their broods; their presence or movements may be more linked to their nest host [START_REF] Williams | Ecological and life-history traits predict bee species responses to environmental disturbances[END_REF].

Hypothesis 3: the forest edge may be the nesting or mating sites for cavity-nesting or ground-nesting bees To estimate the importance of forest edge for groundor cavity-nesting bees, we constructed a generalized additive mixed model as above. We focused only on the Andrena responses because (1) other groups such as the cavity-nesting bees (Osmia spp) were probably underestimated because of the sampling method used [START_REF] Westphal | Measuring bee diversity in different European habitats and biogeographical regions[END_REF][START_REF] Sobek | Canopy vs. understory: does tree diversity affect bee and wasp communities and their natural enemies across forest strata? For[END_REF]); (2) Andrena were the only taxa whose males and parasites had already emerged and could be used as indirect indicators of nesting or mating sites; and (3) other studies in similar areas had already shown that Andrena are important visitors to B. napus [START_REF] Delbrassine | Contribution a l' etude de la pollinisation du colza Brassica napus L; var oleifera (Moench) Delile en Belgique[END_REF][START_REF] Le Feon | Solitary bee abundance and species richness in dynamic agricultural landscapes[END_REF].

We investigated the response of Andrena females and males separately. For Andrena females, our model contained the interaction between distance and orientation, and we included year (n = 2) and field area (n = 2) as additional fixed effects and the field identity (n = 28) as a random effect. Residuals analysis suggested a Poisson distribution. For the analysis of Andrena males, we further included a factor structuring the variance of error using the "weights" distribution function (varpower). In this case, we used a Gaussian distribution (Table 1).

Finally, for this hypothesis, we also examined the response of the Andrena cleptoparasites, Nomada, using the same model structure as for Andrena males.

Results

A total of 4594 individuals representing 83 taxa from 6 families, and 12 genera were recorded. The most abundant families were Halictidae (49.1% of total abundance, 31 species) and Andrenidae (39.5% of total abundance, 36 species). Their parasites, Sphecodes (12 specimens) and Nomada (191 specimens, 101 females, 90 males), respectively, represented 4.4% of the total abundance. The Apidae (Apis and Bombus spp.) family represented only 5.7% of total abundance. Furthermore, all Bombus spp. were queens indicating that colonies had not yet been established at the time of the study. The Bombus parasites (Bombus (Psithyrus) rupestris, Bombus (Psithyrus) sylvestris, and Bombus (Psithyrus) vestalis) with a total of 27 specimens accounted for 0.6% of total abundance. Females for all taxa combined represented 89.1% of total abundance with 4095 specimens, and males only 10.9% (499 specimens) with Andrena and Nomada males making up, respectively, 74.5% and 18% of male abundance (Fig. 4). Halictidae and Apidae males emerge later and were therefore absent in our samples.

Hypothesis 1: bee abundance, species richness and composition of bee communities within the crop field are dependent on the distance from the forest edge and forest edge orientation Distance had a significant negative effect on total abundance and richness (Table 1). The orientation of forest edge and its interaction with distance had no significant effect on total abundance, richness, abundance of Andrena males and females mean ITD (Table 1). We observed a positive effect of the interaction between cold Table 1. Estimates (AE SE) of ecological effects from generalized additive mixed-effect models for bee abundance, species richness, mean female ITD, Andrena females and males, and Nomada.

Probability (P) of a significant difference between values is indicated by NS, not significant,*P < 0.05. **P < 0.01. ***P < 0.001. orientation and distance on Andrena females and Nomada abundance. In other words, we observed a decrease in Andrena females and Nomada abundance with increasing distance from warm edges. Conversely, we observed an increase in Andrena females and Nomada abundance with increasing distance from cold edges (Data S1). However, for the Nomada, the model did not describe the data very well.

Inertia partitioning by CAP (canonical analysis of principal coordinates) showed that distance provided the second largest contribution to the variance in bee assemblages (29.4%), the first explanatory variable being the field ID (48.8%). Distance and field ID were the only significant variables with an independent contribution; the others had only joint contributions (Table 2).

Hypothesis 2: the identity of bees in the crop is related to their foraging range Distance had a significant positive effect on mean female ITD (Fig. 5). In other words, the further away collected bees were from the edge, the larger they were (Table 1).

Hypothesis 3: forest edge as nesting or mating sites for Andrena For the Andrena, both females and males were negatively affected by longer distances. Nomada were also apparently negatively affected by longer distances; however, the model did not describe the data very well (Table 1). Even so, we decided to retain this model because of the high proportion of Nomada present at forest edges (81.7% of their total abundance).

Discussion

Hypothesis 1: bee abundance, species richness, and composition of bee communities within the crop field are dependent on the distance from the forest edge and forest edge orientation Multiple points are plotted as "sunflowers" with multiple leaves ("petals") such that overplotting is visualized.

(A) (B) (C) (D) (E) (F)
In our study, we found a negative effect of distance from forest edge on bee abundance and richness. Distance also greatly affected assemblage composition. Our results provide evidence that distance strongly determines the spatial distribution of bees in the OSR field. In a metaanalysis, [START_REF] Ricketts | Landscape effects on crop pollination services: are there general patterns?[END_REF] showed that native pollinator visitation rate drops to 50% of the maximum at a location 668 m away from natural habitats. Some other studies focusing on the effect of forest on bee visits or pollination services are consistent with these results (e.g., [START_REF] Hawkins | Factors affecting the yield of seed produced by different varieties of red clover[END_REF][START_REF] De Marco | Services performed by the ecosystem: forest remnants influence agricultural cultures' pollination and production[END_REF][START_REF] Chacoff | Edge effects on flower-visiting insects in grapefruit plantations bordering premontane subtropical forest[END_REF]. Together with ours, these studies highlight that forest edges are likely to be a pollinator source for different crops. Indeed, forest edges present a complex vertical structure and undisturbed soil offering shelter for all bees and a wide range of nesting sites for both cavity-and ground-nesting bee. In addition, they provide a diversity of floral resources throughout the bees' activity period. Finally, these studies also suggest that the pollination of the mass-flowering crop, OSR, could be negatively affected by too great distance from the forest [START_REF] Morandin | Wild bee abundance and seed production in conventional, organic, and genetically modified canola[END_REF], unless the few species that venture farther afield can provide on their own the supplementary pollination necessary for the crop.

We also observed a positive effect of the interaction between cold orientation and distance on Andrena females and Nomada abundance. This is consistent with the ecological requirements of solitary bees; they are thermophilous insects so they prefer warm exposed sites for foraging. They may therefore travel further into the field to forage in well-exposed areas. Moreover, rapeseed flowering could be sparse and occurs later along cold forest edges. In that case, bees would probably forage further into the crop where better exposure has encouraged more abundant floral resources.

Hypothesis 2: the identity of bees in the crop is related to their foraging range In contrast to [START_REF] Lentini | Supporting wild pollinators in a temperate agricultural landscape: maintaining mosaics of natural features and production[END_REF], we found that larger female bees were found in the fields further from the forest edge. However, all the fields in Lentini et al.'s study contained small untilled areas that could have provided alternative nectar sources or nesting sites and acted as local population sources within the otherwise homogeneous fields. [START_REF] Arthur | Influence of woody vegetation on pollinator densities in oilseed Brassica fields in an Australian temperate landscape[END_REF] also presumed that the absence of an edge effect on solitary bees in OSR might indicate that some bees were nesting inside the crop fields, with minimum tillage technique ground nesting may be possible. In our study, we assumed that: (i) the recorded taxa could not nest in the field itself as mechanical tillage was carried out at least once a year and (ii) some taxa must have covered distances of up to 230 m to reach the OSR field from their nesting sites on the forest edge. We hypothesized that females would be distributed according to their foraging range, calculated by measuring their ITD [START_REF] Greenleaf | Bee foraging ranges and their relationship to body size[END_REF]). In our study, we found that mean ITD increased with distance from forest edge. Overall, we found that distance was the second most important explanatory factor for the variance in bee communities. For large taxa, the higher energy consumption required to fly further may well be compensated for by less competition for forage resources. The social taxa, Bombus spp. and A. mellifera, may benefit even more than solitary taxa from the lower competition in the center of the plot because they need to store large amounts of resources to start colonies [START_REF] Herrmann | Genetic diversity and mass resources promote colony size and forager densities of a social bee (Bombus pascuorum) in agricultural landscapes[END_REF][START_REF] Westphal | Mass flowering oilseed rape improves early colony growth but not sexual reproduction of bumblebees[END_REF]. Additionally, the decline in total bee abundance with increasing distance into the OSR field may reflect a dilution effect: pollinators in the middle of the field have more flowers to choose from away from the forest edge [START_REF] Arthur | Influence of woody vegetation on pollinator densities in oilseed Brassica fields in an Australian temperate landscape[END_REF]. Indeed, even though several species of solitary bees have been found to be able to return from distances of up to 400 meters [START_REF] Zurbuchen | Maximum foraging ranges in solitary bees: only few individuals have the capability to cover long foraging distances[END_REF], the smaller species' foraging ranges probably remain rather limited if resources are abundant nearby. This could result in a negative impact on pollination efficiency far from the forest edge with a decrease in interspecific interactions (Greenleaf and Kremen 2006b).

Hypothesis 3: forest edge as nesting or mating sites for Andrena

Wild bee nests are difficult to locate in the field [START_REF] Waters | Testing a detection dog to locate bumblebee colonies and estimate nest density[END_REF], unless a very limited area is intensively studied. Therefore, we decided to use the distribution patterns of males and nest parasites as general indicators of the areas likely to be used by Andrena for nesting or mating; indeed, these two groups' activity is mostly, although not exclusively, focused around nesting or mating sites rather than forage sites [START_REF] Eickwort | Foraging and matingbehavior in Apoidea[END_REF]. Andrena males patrol areas, marking vegetation with mandibular gland secretions around the nesting sites of females or their food plants [START_REF] Tengo | Odor-released behavior in Andrena male bees (Apoidea, Hymenoptera)[END_REF][START_REF] Ayasse | Mating behavior and chemical communication in the order Hymenoptera[END_REF] or actively search for receptive females at emergence sites [START_REF] Butler | Sex attraction in Andrena flavipes Panzer (Hymenoptera: Apidae), with some observations on nest-site restriction[END_REF][START_REF] Tengo | Odor-released behavior in Andrena male bees (Apoidea, Hymenoptera)[END_REF]. The reproductive success of Nomada depends on the capacity of females to find host nests and gain entry into them [START_REF] Tengo | Cleptoparasitism and odor mimetism in beesdo Nomada males imitate odor of Andrena females?[END_REF][START_REF] Cane | Olfactory evaluation of Andrena host nest suitability by kleptoparasitic Nomada bees (Hymenoptera, Apoidea)[END_REF]). In our study, the preference shown by both Andrena males and their cleptoparasites for forest edges indicates suitable nesting, or at least mating sites, for some abundant Andrena species and their parasites. This is consistent with [START_REF] Calabuig | Solitary bees and bumble bees in a Danish agricultural landscape[END_REF] who found that the abundance of males and inquilines was significantly higher along forest edges than along several of the other linear habitats tested. Moreover, we observed that several abundant females (A haemorrhoa, A nitida, A nigroaenea, and A cineraria) occurred at different distances, while their males were most abundant along forest edges. Therefore, forest edges may not just be "partial habitats"; they could be a population sources for potential pollinators to OSR fields.

Implications for bee conservation and agricultural landscape management

The main objective of this study was to assess whether forest edges are an important partial habitat for potential OSR pollinators. Our results clearly support this assumption. We found that the forest edge is likely to be a nesting site and/or mating site for an important group of pollinating bees, the Andrenidae. Furthermore, the forest edge is a potential foraging site for all bees because of the early spring-flowering trees or forbs it contains. Therefore, taking into account, the proportion of forest edges around a field could be an indirect way to measure direct factors such as food availability or the presence of suitable pollinator nesting sites and/or mating sites in a landscape [START_REF] Roulston | The role of resources and risks in regulating wild bee populations[END_REF], at least during spring. We also show that forest edge value may vary depending on microclimatic conditions such as the amount of sunlight it receives. We therefore recommend that future studies include forest edges and seasonality as explanatory variables to explain bee abundance or richness in a given landscape.

The decrease in pollinators with distance seems to be caused by flight costs as indicated by the mean increase in bee size with distance. Therefore, preserving untilled conservation land inside crop fields may be a way to offset the absence of bees in large fields with distant forest edges [START_REF] Lentini | Supporting wild pollinators in a temperate agricultural landscape: maintaining mosaics of natural features and production[END_REF]. [START_REF] Brosi | Optimal design of agricultural landscapes for pollination services[END_REF] proposed a model farm configuration that would maximize crop yield; the highest-yield farm designs were those with a relatively small area of pollination reservoirs, suggesting a conservation strategy of small parcels of service-providing habitat interspersed throughout working landscapes. However, small pollination reservoirs are probably not complete habitats in themselves, so this farm design is likely to be dependent on bee flight range and their ability to disperse throughout the crop matrix [START_REF] Bommarco | Dispersal capacity and diet breadth modify the response of wild bees to habitat loss[END_REF]. All these results suggest that forest edges are important sources of pollinators because they provide different "partial habitats" for bees [START_REF] Westrich | Habitat requirements of central European bees and the problems of partial habitats[END_REF]. However, forest edges need to be spatially well integrated into the agricultural matrix: (i) to promote bee populations, (ii) to ensure pollination services, and (iii) to enhance opportunities for colonization via connecting habitats [START_REF] Steffan-Dewenter | Scale-dependent effects of landscape context on three pollinator guilds[END_REF]. Unfortunately, trees are often negatively perceived by farmers because they compete with crops for sunlight, nutrients, or water [START_REF] Huth | Regional differences in tree-crop competition due to soil, climate and management[END_REF]). Yet, studies show that forest edges or trees may provide several additional ecosystems services such as pest control [START_REF] Bianchi | Landscape factors affecting the control of Mamestra brassicae by natural enemies in Brussels sprout[END_REF][START_REF] Stutz | Effects of the landscape context on aphid-ant-predator interactions on cherry trees[END_REF], soil quality improvement, water regulation [START_REF] Tsonkova | Ecological benefits provided by alley cropping systems for production of woody biomass in the temperate region: a review[END_REF], and wind breaks [START_REF] Brandle | Windbreaks in North American Agricultural Systems[END_REF]). The loss in crop yield induced by forest edges should therefore be weighed up against the potential ecological benefits gained. We recommend that forest edges should be included in agro-environmental schemes and "green belt networks" (http://www.legrenelle-environnement.fr/ spip.php, MEEDDM 2010) to promote bee populations, bee biodiversity, and diverse ecosystem services. We also recommend that forest edges should be associated with other agro-environmental schemes, such as fallow land or hedgerows, to supply partial habitats for different bee species throughout the bees' seasonal activity [START_REF] Hannon | Hedgerows in an agri-natural landscape: potential habitat value for native bees[END_REF][START_REF] Lye | Assessing the value of Rural Stewardship schemes for providing foraging resources and nesting habitat for bumblebee queens (Hymenoptera: Apidae)[END_REF]).

Figure 1 .

 1 Figure 1. Left, a Nomada sp male; right, an Andrena sp male.

Figure 2 .

 2 Figure 2. Location of study areas and spatial arrangement of our sampling design.

Figure 3 .

 3 Figure 3. Design used to survey bees in oilseed rape crops at different distances from the forest edge. Circles represent yellow pan traps.

Figure 4 .

 4 Figure 4. Abundance as a function of distance from the forest edge for different bee groups. We show absence and presence values and use different scales on Y-axes for clarity.Multiple points are plotted as "sunflowers" with multiple leaves ("petals") such that overplotting is visualized.

Figure 5 .

 5 Figure 5. Fitted GAMM model of the response of female mean ITD including distance, year, female abundance, and geographic coordinates as fixed factors and geographic area and field as random factors.

Table 2 .

 2 Results of the canonical analysis of principal coordinates on the bee assemblage for the five factors.

		Total inertia	Pr (>F)	% constraint inertia	% own contribution	% joint contribution
	Field ID	70.54	0.005	48.8	13.1	86.9
	Distance	42.55	0.005	29.4	15.7	84.3
	Area	20.29	0.005	14.0	0.0	100.0
	Year	8.69	0.005	6.0	0.0	100.0
	Orientation	2.56	0.067	1.8	0.0	100.0
	Residuals	8.64

ª 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

ª 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.

Acknowledgments

We greatly thank Eric Dufrêne, David Genoud, S ebastien Patiny, Alain Pauly, Pierre Rasmont, Micka€ el Terz€ o, and Erwin Scheuchl for bee identification, Julien Fleury, Nicolas Lagarde, and Carl Moliard who took part in data collection and in specimen preparation before identification and Annie Ouin, Marc Deconchat, J erôme Willm, Phillippe Caniot, Bruno Dumora, and Martin Vigan for their data collection in the South of France. We also thank Philip Roche, Micka€ el Terz€ o, Micka€ el Henry, Serge Gadoum, Eric Dufrêne, and Emilie Andrieu for discussions on the project. We are also grateful to the landowners who granted us access to their land and Vicki Moore for checking the English language. Andrew Bates, Andrew Beckerman, and an anonymous reviewer significantly helped us to improve the manuscript. The contributions by S.G.P and S.P.M.R were supported by the STEP project (Status and Trends of European Pollinators, Grant no. 244090 -STEP -CP -FP). This research was funded by the French Ministry in Charge of the Ecology through the BGF program (convention Bilisse 10-MBGD-BGF-4-CVS-084, no CHORUS 2100215042). Part of this work was also funded by two grants from Irstea and the "Conseil Regional du Centre".

Funding Information

This research was funded by the French Ministry in Charge of the Ecology through the BGF program (convention Bilisse 10-MBGD-BGF-4-CVS-084, no CHORUS 2100215042). Part of this work was also funded by two grants from Irstea and the "Conseil Regional du Centre".

Conflict of Interest

None declared.

Supporting Information

Additional Supporting Information may be found in the online version of this article: Data S1. Fitted GAMM model of the response of total abundance, richness, mean female ITD, Andrena female abundance, Andrena male abundance and total Nomada abundance as a function of distance from the forest edge for the two qualitative variables "cold" and "warm" orientation.