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Soil distribution in valleys according to stream order
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Catena 72 (2008) 395 – 404 www.elsevier.com/locate/catena
Soil distribution in valleys according to stream order Brice Mourier a,b,⁎, Christian Walter a , Philippe Merot a a
b
INRA Agrocampus Rennes, UMR Sol-Agronomie, Spatialisation, 65 route de Saint Brieuc CS 84215, 35042 Rennes cedex, France Centre Alpin de Recherche sur les Réseaux Trophiques et les Ecosystèmes Limniques (UMR 42 INRA/Université de Savoie), Domaine Universitaire, 73376 Le Bourget du Lac, France Received 25 October 2006; received in revised form 9 July 2007; accepted 25 July 2007
Abstract While much research has been done on predicting the occurrence of waterlogged soils in small catchments, we need to improve our knowledge of the extension of these soils in large catchments. The aim of this study is to analyse the extent of soils with redoximorphic features in the valley bottomland domain as a function of the stream order. This study concerns a 10,000 km2 catchment (River Vilaine, Armorican massif, north-western France) where valley bottomland soils commonly associated with hydromorphic characteristics cover up to 20% of the basin area. To describe the catchment organisation, we used the stream order classification of Strahler to test the behaviour of the topographic index in a large range of landscape morphological settings. Two methods were used to define the extent of the hydromorphic zone (HZ) in each valley bottomland according to stream order: (i) A field study based on mapping the HZ according to the occurrence of redoximorphic features along 60 transects; (ii) a modelling approach linking a DEMderived topographic index to the digitized stream network of the River Vilaine. In view of the topographic factors, progressive valley widening may represent an enhancing factor of HZ extent. Thus, simple topographic index modelling predicts an increase in waterlogging in high-order channel settings (orders 6–7). By contrast, field mapping suggests that HZ extent remains stable with increasing order and decreases significantly for high-order settings (orders 6–7). Therefore, topographic index modelling appears effective in upper catchment settings (1st, 2nd and 3rd order). On the contrary, modelling efficiency is limited in high-order settings where the indices prove to be inappropriate: in such contexts, interactions between adjacent hillslope and HZ are of secondary importance. Along the longitudinal profile of the catchment, soil material near the streams shifts from having a colluvial origin in low-order to an alluvial origin in high-order settings. In high-order settings, the fine-scale valley bottomland topography and the spatial organisation of deposits control waterlogging duration and possibly play a major role in HZ extent. Finally, the integration of stream order data should considerably improve the efficiency of modelling the spatial distribution of soils over large catchments. © 2007 Elsevier B.V. All rights reserved. Keywords: Redoximorphic features; Stream order; Catchment; Topographic modelling
1. Introduction The spatial extent of water-saturated soils is a key variable in the hydrological response of a catchment and, more generally, in the functioning of hydrologic systems. Surface flow depends on water infiltration conditions and vertical water movements within ⁎ Corresponding author. Centre Alpin de Recherche sur les Réseaux Trophiques et les Ecosystèmes Limniques (UMR 42 INRA/Université de Savoie), Domaine Universitaire, 73376 Le Bourget du Lac, France. Tel.: +33 4 79 75 86 37; fax: +33 4 79 75 88 80. E-mail address: [email protected] (B. Mourier). 0341-8162/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.catena.2007.07.012
the soil (Moussa and Bocquillon, 1996). Waterlogging of soils contributes to the partitioning of both water and energy involved in evapotranspiration and erosion (Wilson et al., 2004). Soil and sub-soil water accumulation can promote erosion (Western et al., 1999) even if soil saturation is not complete (Burt and Butcher, 1985). High soil water content enhances the redistribution of nutrients and sediments in the landscape (Georgakakos, 1996; Chaplot and Walter, 2003). Temporal variation of soil moisture is also a major factor in assessing the hydrological response of a surface (Gómez-Plaza et al., 2000; Wilson et al., 2004). Seasonal soil moisture variation is locally controlled by the balance between evaporation and precipitation. A catchment can be
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broadly divided into two areas, saturated and well-drained, that are separated by a boundary that varies in time (Merot et al., 2003). When water saturation of soils occurs for periods long enough to allow the development of reducing conditions, this may be recognized by the observation of a gleyic colour pattern (WRB, 2006). In this way, soil colour mottling, the presence of segregated iron and manganese (hydr)oxides and the presence of organic soil material, represent morphological indicators that allow to infer the soil water regime (Mitsch and Gosselink, 1993; WRB, 2006). Veneman et al. (1998) summarized the relationship between redoximorphic features and seasonal saturation in soils. Within a catchment, the distribution of soils with redoximorphic features is almost stable over time due to the inertia of underlying processes and the persistence of these features (Mitsch and Gosselink, 1993; Brinson, 1993). The delineation of the area within a landscape were soils are affected by redoximorphic features in the topsoil horizon (b 20 cm depth), here referred to as the Hydromorphic Zone (HZ), is therefore a major issue in soil survey studies (Soil Survey Division Staff, 1993). Due to the close relationship between topography and soil waterlogging, spatial modelling approaches based on topographic attributes have been widely developed to predict the HZ spatial distribution (McBratney et al., 2003). Local parameters such as slope, elevation, convexity, concavity and upslope drainage area, are derived from Digital Elevation Models (DEMs) and can be combined into topographic indices linked to soil waterlogging extent (Merot et al., 1995; Freer et al., 1997; Crave and Gascuel-Odoux, 1997; Rodhe and Seibert, 1999; Western et al., 1999; Chaplot et al., 2003). Beven and Kirkby (1979) established a compound topographic index, distributed over space, by determining the upslope drainage area per unit contour length (a) and local slope (tanβ) at each cell of a DEM. This topographic index (ln (a) / (tanβ)) assumes that topography is the major factor controlling the extension of waterlogging through two main processes: flow convergence and lateral drainage (Wilson et al., 2004). The increasing availability of DEMs has favoured the use of indices, although most validation studies have found that only roughly 50% of the in situ spatial variability of the HZ extent can be explained (Wilson et al., 2004). Lastly, most applications have been tested and validated in upper catchments related to 1st, 2nd or 3rd order streams according to the Strahler (1952) classification. Additional factors have been accounted to improve soil with hydromorphic characteristics prediction: (i) soil transmissivity linked to soil texture (Beven and Kirkby, 1979), and (ii) annual effective rainfall (Merot et al., 2003) to compare catchments with different climatic conditions. Several authors (Seyfried, 1998; Qiu et al., 2001; Chaplot and Walter, 2003; Fu et al., 2003; Buttle et al., 2004) emphasize the importance of soil properties, especially soil depth and abrupt textural changes, for understanding subsurface water flow that often accounts for the HZ extent. Recently, Merot et al. (2006) defined a new methodology, the PEEW approach (Potential, existing and efficient approach), which combines permanent and nonpermanent criteria to delineate wetlands. This approach account
for land use and land cover in farming zones modifying delineation and functions of wetlands. At the catchment scale, energy and material fluxes vary from the sources to the outlet zone. Specifically, the regolith (soil parent material), such as the autochthonous material or colluvial and alluvial deposits, may change downstream in the catchment and strongly affect soil water transmissivity. As a result, HZ distribution in valley bottomlands may change according to the catchment organisation. To describe the catchment organisation, stream networks are studied by order according to the Strahler (1952) index method. Stream order may be tested as an indicator for ranking sub-catchments and studying HZ extent over large areas. The aim of this study is to analyse the extent of soils with redoximorphic features in the valley bottomland domain as a function of stream order. The study takes place in the Vilaine catchment where we carried out two successive steps: (i) the in situ soil study of the extent of the HZ along 60 cross valley transects ranked by stream order (6‑16 transects by order class); (ii) the comparison of field descriptions with predictions from a topographic modelling approach based on estimations of the topographic index in the valley bottomland domain. 2. Materials and methods 2.1. Study area Study sites were chosen in the Vilaine catchment, the largest drainage basin in the Armorican Massif of western France (Fig. 1). The study area covers 10,000 km2 and exhibits a range in elevation of 305 m. Mean annual rainfall ranges from 700 to 750 mm, with considerable spatial variability owing to the large size of the catchment area. The landscape is strongly affected by agricultural activities, covering almost 62% of the total basin area. One particular aspect of land use is that valley bottomland zones are mainly used as pastures (Chaplot and Walter, 2003). Topography is generally smooth and well correlated with geological formations. Moreover, previous tectonic disturbances (Chaplot et al., 1999) and quaternary deposits (Aeolian loam, riverbank) contribute to the present-day landscape morphology. Bottomland soils are commonly associated with hydromorphic conditions and cover up to 20% of the basin area (Merot et al., 2003), which is a result of their position in the landscape (Merot et al., 1995). 2.2. Definition of stream order and modelling of HZ distribution using topographic indices Strahler (1952) indexation is preferred here to other indexation systems (Gravelius, 1914; Shreve, 1966), since previous studies have shown that modelling of the Vilaine hydrological regime is improved by integrating this descriptor of the catchment's spatial organisation (Crave, 1995; Cudennec, 2000). Stream order allows us to rank the size and the flow regime of streams. It is a measure of the position of the stream in the tributary hierarchy and is sensitive to the accuracy of the drainage pattern delineation. Strahler's (1952) stream order system is an increasingly used method for classifying stream segments based on the number of
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Fig. 1. Vilaine drainage network and location of the 30 studied transects. Streams are marked according to Strahler indexation system.
upstream tributaries. Stream order increases with catchment size, tributary number and drainage network density (Crave, 1995). Stream order and topographic index modelling were extracted from a 50-m resolution DEM and from a digitized stream network previously incorporated into ArcGIS 8.3 software (© ESRI). The maximal order for the Vilaine catchment is seven, while first-order streams represents approximately 50% of the total stream length. The compound topographic index (Beven and Kirkby, 1979) presented in the Introduction was adopted to model the HZ extent. It is mainly based on the assumption that the hydraulic gradient of the shallow water table is equal to the local topographic slope angle, tanβ. The spatial distribution of the soil moisture in a catchment is described by the so called topographic index, log(a / tanβ). a and tanβ are easily computed from a DEM. The potential soil moisture increases with the value of this index. For a rainfall depth given for the whole catchment,
the larger the drainage area and the smaller the slope are, the higher is the topographic index value and thus the probability of occurrence of high soil moisture. This index estimates the soil surface water content at all cells of the raster layer. In a later step, we assume that high values of the topographic index are linked to the presence of redoximorphic surface features. We studied the index distribution for different stream orders in the neighbourhood of streams (arranged by orders), by creating buffer zones of different widths (15, 30, 60, 90, 120, 180, 240 and 300 m) bordering the drainage network. 2.3. Field study of HZ spatial distribution along stream transects The extent of soils with hydromorphic characteristics was delineated perpendicularly to streams of the Vilaine catchment.
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30 settings were randomly selected within the catchment (Fig. 1) based on an indexed map of the stream network. Classes 4 and 5 were grouped because their cumulative lengths represent only 12% of the total length, as well as classes 6 and 7 which represent only 5%. Hence, five order classes were defined as follows: 1, 2, 3, 4–5, 6–7. At each selected site, the transect was investigated for soil morphological characteristics when the following operational conditions were satisfied: (i) good differential GPS signal reception along the whole transect in order to locate precise soil boundaries and provide an accurate topographical profile; settings with dense and high vegetation therefore had to be eliminated; (ii) uniform land use conditions not heavily modified by human activities (roads, embanking, canalization, etc.); (iii) authorisation by the land owner. Finally, each order class was represented by 6–16 transects. On each transect, the two sides of the valley were characterized separately because of the asymmetry of the hillslopes. Topographical and pedological information were collected along each transect using the following procedures (Fig. 2): (i) the topographic line was established with a Pathfinder Pro XRS GPS, giving a submeter-scale precision of geographical coordinates and elevation. Elevation data were smoothed using a 10-order spline function adjustment with an Splus 6.1 (Insightful Corporation, 2003), which enabled us to represent the general configuration of the valley; (ii) the presence or absence of redoximorphic features in the upper soil horizon (0–20 cm) was precisely located. These limits were observed by regularly spaced (10 m) soil auger profiles. When two successive profile observations were significantly different (presence or changes in intensity of soil redoximorphic features), intermediate profiles were carried out until we obtained a metre-scale precision on the limit location. Two levels of redoximorphic intensity were distinguished depending on the abundance of redoximophic features in the topsoil horizon. A Low Hydromorphic Zone (LHZ) was described when gleyic colour pattern (WRB, 2006) was present at an abundance of less than 20% of the soil matrix. A High Hydromorphic Zone (HHZ) was delineated when redoximorphic features represented more than 20% of the soil matrix. Finally, HZ was defined as the sum of HHZ and LHZ. (iii) A solum description down to 120 cm depth at a distance of 10 m from the stream was performed to characterize the soil parent material. The main substratum types encountered in the valley bottomlands were made up of colluvial, alluvial or a mixing of
colluvio-alluvial parent materials. These were distinguished according to the following criteria: vertical heterogeneity of horizon texture and organic matter content, gravel shape and stone content, local morphological aspect (Baize and Girard, 1995). The topographical form of each valley side was described using the following variables (Fig. 2): - hillslope gradient (%) calculated perpendicularly to the streamline; - bottomland gradient (%) and bottomland width (D in m), by convention both calculated at a vertical elevation of 2 m above and perpendicularly to the streamline; - width (in m) of the LHZ, HHZ and HZ domains; - elevation (E in m) above the streamline of the limit of LHZ appearance. Overall correlation between the HZ extent and topography was tested through direct comparison of HZ length to topographic attributes such as gradient (%) of the general hillslope and topographic index. Finally, the proportion of soils with redoximorphic features within the valley bottomland domain is defined by the following equation: HZ=D 2.4. Statistical comparison Topographic attributes and extents were compared for different order classes using the non-parametric Kolmogorov Smirnov two sample test. Differences were considered to be significant at the 0.05 level. Statistical comparison has been done using an Splus software package (Insightful Corporation, 2003). 3. Results 3.1. Topographic index modelling over the whole catchment according to stream order Average topographic index values vary from 9 to 20 and increase significantly with stream order (Fig. 3). The evolution of the topographic index close to streams is analogous for all orders: index values decrease with distance from the stream channel and a major drop of the index occurs at about 50 m from
Fig. 2. Schematic representation of topographical and pedological information collected from the field study. Slope A depicts pedological variables, whereas slope B illustrates topographic variables. Both pedological and topographic information were collected on each slope.
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have a significantly lower bottomland gradient than the other settings. The D domain width is a powerful descriptor of progressive valley expansion, since the value increases with the width of the valley and smoothness of slope. The median bottomland D domain extension ranges from 41 m for order 1 to 89 m for orders 6–7. According to the Kolmogorov– Smirnov test, low-orders (1–3) are significantly different from high-orders (4–6). 3.3. HZ width and near-river substratum according to stream order Fig. 3. Statistics (mean, standard error, t = 0.05) of log(a / tanβ) topographic index according to buffer width around streams indexed by their Strahler order.
streams. Index values are maximum for orders 6 and 7 and remain significantly higher up to a distance of 300 m. For lower orders, differences are significant up to 100 m. Standard deviations are generally low, but increase near the stream, particularly for high-orders. As a result, there is a positive relationship between the increasing order and index value. This trend reflects the progressive valley expansion (smoother slope and more extensive valley), and therefore the increasing potential for waterlogged areas in higher order classes. 3.2. Valley cross profiles at the study sites according to stream order Fig. 4 presents the topographical and pedological information collected along the 30 transects grouped according to Strahler stream order. Transects exhibit a marked asymmetry between the two slopes of the same valley. Within each order, we observe evidence of high topographic variability, particularly for the orders 3 and 4–5. HZ lateral extent ranges from 0 to 100 m, being more pronounced for small orders (1 and 2), and appearing well correlated with topography, particularly on smooth slopes. For high-orders (orders 6–7), the HZ extent appears more discontinuous and less correlated to topographic factors. In some specific cases, the HZ is totally absent, for example on transects T8 and T31, of orders 1 and 7, respectively, which are both located in cultivated areas: T8 is located perpendicular to a temporary stream, while T31 intersects a large valley in a smooth slope setting with systematically well-drained soils. Intense redoximorphic features (HHZ) are observed in all transects with low stream order (except T8), whereas they are not recognized in order classes 6 and 7. Generally, HHZ appears in immediate proximity to the streams and is limited to a width of less than 30 m. Table 1 reports non-parametric statistics (median and interquartile values) of the valley bottomland gradient and the valley bottomland width (D). Half-transects are ranked by Strahler order. Generally, the bottomland gradient decreases with increasing stream order. Transects with stream order 2 yield the highest median gradient values (7.5%), associated with high variability (interquartile of 5.6%). The Kolmogorov–Smirnov test shows that high-order (6–7) transects
The extent of the HZ (distinguishing two intensities of redoximorphic features) and the nature of the substratum parent material were derived from the detailed field survey (Table 2, Fig. 4). Half-transects were stratified by Strahler order. Median HZ widths range from 23 m to 63 m (for orders 6–7 and order 2, respectively) and tend to decrease with increasing valley order. This observation is significant for high-order transects (6–7). In all the transects concerned, HHZ is represented by small strips with median lengths ranging from 11 to 26 m. The HHZ width is maximal for orders 2 and 4–5, in spite of a considerable semi-interquartile range in these same orders. For order 2, the median HHZ length is 26 m, which contrasts significantly with orders 6–7 where HHZ does not appear (Table 2, Fig. 4). Concerning the nature of the near-river substratum, the colluvial and colluvio-alluvial materials occur mainly in the upper catchment. In order 1 transects, 67% of the soils are formed on colluvial material (Table 2, Fig. 4). With increasing stream order, the parent material becomes exclusively alluvial (100% for orders 4–5 and 6–7). Thus, deposits show more homogeneous spatial organisation with increasing stream order. Soils formed on colluvial (or colluvio-alluvial) deposits and long HZ strips are both located at the head of the catchment, whereas, farther downstream, the HZ length is shorter and the soils are mainly formed on alluvial deposits. 3.4. Relation between HZ width and topographic attributes Based on the 60 hillslopes studied on both sides of the streams, Fig. 5.A shows the relation between the topographic index (maximal value along the transect) and HZ width according to stream order. The large scattering of points indicates a poor correlation between topographic index value and HZ lateral length. Although low-order settings exhibit lower index values, large HZ widths may also occur in these domains. While highorder valleys (orders 6–7) are associated with high topographic index, they may have a very restricted HZ. Linear correlations between the index and HZ extent are only significant for orders 2 and 3 (R2 = 0.27 and R2 = 0.11, respectively). Therefore, in upper catchment settings, the extension of the redoximorphic zones appears partially linked to variations of the topographic index, whereas, farther downstream, topographic modelling through this index appears unable to explain HZ extent. We studied the relationship between the gradient of the hillslope gradient and HZ width (Fig. 5.B). Hillslope gradient
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Fig. 4. Topographic profiles and extension of hydromorphic soils in the 30 studied transects. Transects are grouped by orders; two levels of redoximorphic features are distinguished; stream location and origin of soil substratum are indicated.
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Table 1 Statistics (median, 25% and 75% quartiles) of bottomland topographic attributes (gradient and width) according to the Strahler order of the valley Order Sample Bottomland gradient (%) Bottomland D domain width (m) number 1 2 3 4–5 6–7
12 16 16 10 6
5.2 (4.3–7.3)a⁎ 7.5 (4.4–10.0)a 4.3 (2.6–6.6)a 3.3 (2.1–5.1)a 1.7 (1.3–2.6)b
41 (28–51)a 30 (21–77)a 34 (19–49)a 61 (35–132)b 89 (63–142)b
⁎ Medians with the same superscript letters are not significantly different (Kolmogorov–Smirnov test, P = 0.05).
Table 2 Statistics (median, 25% and 75% quartiles) of HZ and HHZ extents (in m) and proportion of colluvial or alluvial soil material next to streams Order
1 2 3 4–5 6–7
Sample number
12 16 16 10 6
HHZ width
HZ width
Colluvial soil material
(m)
(m)
(% of the study area for each order)
15 (10–24)a⁎ 26 (11–41)a 11 (0–30)b 20 (7–53)a 0 (0–0)b
36 63 25 32 23
(11–75)a (19–89)b (14–71)a (21–83)a (0–68)c
67 50 25 0 0
Alluvial soil material
33 25 63 100 100
⁎ Medians with the same superscript letters are not significantly different (Kolmogorov–Smirnov test, P = 0.05). 60 transects are considered according to stream order.
directly affects and determines the maximum HZ extent, that is to say, the HZ width decreases with increasing slope. The greatest HZ widths (N 85 m) are generally located on slopes that do not exceed 5%. Gradients over 14% prevent the HZ from extending to more than 20 m from the channel. There is a significant correlation between the HZ width and the hillslope gradient for orders 2 and 3 (R2 = 0.30 and R2 = 0.58, respectively). For higher orders, the morphological variability appears too large and no
Fig. 6. Statistics on proportion of hydromorphic soils (median, 25% and 75% quartiles) in valley bottomland classified by order. The proportion is estimated by the ratio between total surface extent of HZ and D domain. ⁎Medians with same superscript letters are not significantly different (Kolmogorov–Smirnov test, P = 0.05).
significant correlation can be estimated. Thus, we observe that the hillslope gradient is correlated with HZ width in the head catchment, but not for the highest stream orders (R2 b 0.01, R2 = 0.02 for orders 4–5 and 6–7, respectively). Fig. 6 presents the proportions of soils affected by hydromorphic conditions in valley bottomlands, where extension is estimated by the distance D (Fig. 2). A ratio (R) expresses the HZ width according to the width of the valley bottomland domain (R = HZ width /D). If the ratio is higher than 1, only soils affected by hydromorphic conditions are developed in the valley even though redoximorphic features are also observed on the hillslopes. At low R values, soils of the valley are only partially affected by hydromorphic conditions. The values of this ratio reveal a contrast between lower orders, where soils with redoximorphic features are dominant (R(1) = 1.05 and R(2) = 1.69) and higher down-catchment orders (R(6–7) = 0.3). The median R ratio globally decreases with increasing stream order, but the difference only becomes significant for orders 6–7 where welldrained soils are dominant.
Fig. 5. HZ width on slopes according to two topographic attributes: (A) calculated topographic index derived from a 50-m DEM, (B) hillslope gradient. Symbols indicate Strahler order of the stream.
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4. Discussion Through the random selection of transects over a large area, this study highlights a great variability of HZ extent in comparison with stream order. The Strahler order differentiates the morphological settings of valleys and HZ extent. With increasing order, the topographic slope decreases progressively, so the valley becomes wider even if the slopes of the same transect are often asymmetric (Fig. 4 and Table 1). When considering topographic factors alone, progressive valley expansion may represent a factor that enhances the HZ extent. The modelling of potential soil waterlogging based on the topographic indexes is the most common method for predicting soils associated with hydromorphic conditions, even if topography does not represent the key process (Grayson and Western, 2001). The prediction of HZ distribution from topographic modelling suggests an increasing potential for waterlogging in areas with higher orders (Fig. 3). As indicated by the redoximorphic features and the arrangement of deposits, there is a progressive change of soil distribution in the valley bottoms of the Vilaine catchment.
Field mapping suggests that HZ extent remains stable for order 1 to 3 and even decreases, significantly for orders 6–7 (Fig. 6 and Table 2). HZ extent is therefore not correlated with valley widening, and soils are proportionally more affected by waterlogging processes at the head of the catchment (orders 1 to 3). Moreover, the highest hydromorphic intensities (HHZ) are predominant in low-order valleys (Fig. 4, Table 2). These observations suggest that, for low-order valleys, the extension of the HZ appears correlated with the potential waterlogged areas predicted by topographic index modelling. In highorder valleys, the topographic index modelling approach appears clearly inadequate to explain HZ extent. For such areas, additional information needs to be integrated to take account of the climatic and local hydrological controls on the occurrence of HZ. In all settings, the soil materials near the stream originate from deposits of alluvial or colluvial origin, or a mixture of both. Along the catchment, we observe an increasingly welldeveloped organisation of the deposits owing to valley expansion (Figs. 4 and 7, Table 2). The soils developed on colluvial or mixed deposits are affected by hydromorphic
Fig. 7. Conceptual model of arrangement of valley bottomland systems. The origin of the deposits and the HZ extent are considered according to stream order.
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conditions and occur mainly in the upper catchment. By contrast, the soils formed alluvial deposits are generally welldrained. On a catchment area scale, the spatial organisation of the deposits therefore seems to play a major role in HZ extent. Fig. 7 summarizes these observations in an integrative framework of valley bottomland development as a function of stream order. This conceptual model takes into account the changes in the arrangement of deposits within the catchment and the evolution of HZ extent. The soils occurring in areas with stream order values of 1 to 3 are more affected by redoximorphic features. HZ is correlated with topographic attributes, and interactions between slope and HZ are predominant (Merot et al., 2006). Moreover, Chaplot (1998) shows that colluvial origin soils from the upper catchment exhibit abrupt hydrodynamic variations between horizons. Thus, the flow of soil water is modified and waterlogging is favoured (Chaplot, 1998). Topographic modelling with topographic indexes is a useful tool for predicting the HZ extent (Fig. 5) in 1st, 2nd or 3rd order catchments. By contrast, HZs are either absent close to high-order streams (6–7) or located within a few tens of meters of the channel (Fig. 4). In such settings, the HZ distribution may be due to the microtopography inherited from the ancient stream flow regime. These ancient fluvial deposits are not found in areas of low stream orders, but are abundant in high stream orders where they strongly control the HZ development. The interaction between the slope and the HZ is minor, whereas the influence of valley bottomland micro-topography is dominant. Our results suggest that the prediction of HZ using DEM with stream order stratification is validated in low-order settings (orders 1 to 3). By contrast, prediction overestimates the HZ extent in high-order settings (orders 6–7). A possible improvement of the prediction of HZ extent in orders 6–7 should consist of an integration of the origin and the organisation of the quaternary deposits. Moreover, improvement of the DEM resolution would enable to describe more precisely the complex micro-topography of the valley bottomland area. 5. Conclusion According to our study, stream order can be considered as a crucial hierarchical descriptor of the distribution pattern of soils in the valley bottomland area. Stream order enables us to compare valley morphology in a wide range of settings: from small temporary streams to high-flow-regime rivers. The spatial approach applied here to characterize HZ extent, based on topsoil-surface redoximorphic features, can be used to supplement soil moisture studies and wetlands delineation, particularly on a catchment area scale. The results of the in situ study suggest that HZ extent remains similar for orders 1 to 3 and decreases, significantly for orders 6 and 7. By contrast, the modelling approach based on the topographic index predicts high potential waterlogging in high-order channel settings (orders 6–7). The modelling efficiency is limited in high-order settings where the indices are inappropriate. In such contexts, the fine-scale bottomland topography and the spatial organisa-
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tion of ancient deposits control waterlogging duration and, as a consequence, soils with redoximorphic features. Acknowledgments The authors would like to thank G. Dutin for field assistance and providing much insight on Brittany's soils. Prof. Dr. Karl Auerswald and the two anonymous reviewers are thankfully acknowledged for their valuable comments on the early draft of this paper. M.S.N. Carpenter post-edited the English style. References Baize, D., Girard, M.C., 1995. Référenciel pédologique. INRA éditions, Versailles. Beven, K., Kirkby, M.J., 1979. A physically based, variable contributive area model of basin hydrology. Hydrol. Sci. Bull. 24, 43–69. Brinson, M., 1993. A hydrogeomorphic classification for wetlands. U.S. Army Corps of Engineers, Waterways Experiment Station, Vicksburg, MS, USA. Technical Report WRP-DE 4. Burt, T.P., Butcher, D.P., 1985. Topographic control of soil moisture distributions. J. Soil Sci. 36, 469–486. Buttle, J.M., Dillon, P.J., Eerkes, G.R., 2004. Hydrologic coupling slopes, riparian zones and streams: an example from the Canadian Shield. J. Hydrol. 287, 161–177. Chaplot, V., 1998. Organisation spatiale des sols hydromorphes de fonds de vallée. Modélisation prédictive de leur distribution. Ph.D. Thesis, Ensa Rennes, France. Chaplot, V., Walter, C., 2003. Subsurface topography to enhance the prediction of the spatial distribution of soil wetness. Hydrol. Process. 17, 2567–2580. Chaplot, V., Walter, C., Curmi, P., 1999. Cartographic arguments of a tectonic effect on regional soil distribution in the Armorican Massif. C. R. Acad. Sci. Pari 329 (7), 487–493. Chaplot, V., Van Vliet-Lanoe, B., Walter, C., Curmi, P., Cooper, M., 2003. Soil spatial distribution in the Armorican Massif, western France: effect of soilforming factors. Soil Sci. 168 (12), 856–868. Crave, A., 1995. Quantification de l'organisation des réseaux hydrodynamiques. Thèse, Géosciences Rennes. Crave, A., Gascuel-Odoux, C., 1997. The influence of topography on time and space distribution of soil surface water content. Hydrol. Process. 11, 203–210. Cudennec, C., 2000. Description mathématique de l'organisation du réseau hydrographique et modélisation hydrologique. Ph.D. Thesis, Ensa Rennes, France. Freer, J., McDonnell, J., Beven, K., Brammer, D., Burns, D., Hooper, R.P., Kendal, C., 1997. Topographic controls on subsurface storm flow at the hillslope scale for two hydrologically distinct small catchments. Hydrol. Process. 11, 1347–1352. Fu, B., Wang, J., Chen, L., Qui, Y., 2003. The effects of land use on soil moisture variation in the Danangou catchment of the Loess Plateau, China. Catena 54, 197–213. Georgakakos, K.P., 1996. Soil moisture theories and observations (special issue). J. Hydrol. 184, 131–152. Gómez-Plaza, A., Alvarez-Rogel, J., Alabaladejo, J., Castillo, V.M., 2000. Spatial patterns and temporal stability of soil moisture across a range of scales in a semi-arid environment. Hydrol. Process. 14, 1261–1277. Grayson, R., Western, A., 2001. Terrain and distribution of soil moisture. Hydrol. Process. 15, 2689–2690. Gravelius, H., 1914. Flusskunde. Goschen Verlagshandlung Berlin. In Zavoianu, I (1985). Morphometry of drainage bassins. Amsterdam, Elsevier. Insightful Corporation, 2003. S-PLUS software: S-PLUS® 6.2 for Windows Professional Edition. Insightful Corporation, Seattle. McBratney, A.B., Mendonça, Santos, M.L., Minasny, B., 2003. On digital soil mapping. Geoderma 117, 3–52.
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Merot, P., Ezzahar, B., Walter, C., Aurousseau, P., 1995. Mapping waterlogging of soils using digital terrain models. Hydrol. Process. 9, 27–34. Merot, P., Squividant, H., Hefting, M., Burt, T., Maitre, V., Kruk, M., Butturini, A., Thenail, C., Viaud, V., 2003. Testing a climato-topographic index for predicting wetlands distribution along an European climate gradient. Ecol. Model. 163, 57–71. Merot, P., Hubert-Moy, L., Gascuel-Odoux, C., Clement, B., Durand, P., Baudry, J., Thenail, C., 2006. A method for improving the management of controversial wetland. Environ. Manag. 37 (2), 258–270. Mitsch, W.J., Gosselink, J.G., 1993. Wetlands, 2nd ed. John Wiley, New York. 722 pp. Moussa, R., Bocquillon, C., 1996. Fractal analyses of tree-like channel networks from digital elevation model data. J. Hydrol. 187, 157–172. Qiu, Y., Fu, B., Wang, J., Chen, L., 2001. Soil moisture variation in relation to topography and land use in a hillslope catchment of the Loess Plateau, China. J. Hydrol. 240, 243–263. Rodhe, A., Seibert, J., 1999. Wetland occurrence in relation to topography: a test of topographic indices as moisture indicators. Agric. For. Meteorol. 98–99, 325–340.
Seyfried, M., 1998. Spatial variability constraints to modeling soil water at different scales. Geoderma 85, 231–254. Shreve, R.L., 1966. Statistical law of stream numbers. J. Geol. 74, 17–37. Soil Survey Division Staff, 1993. Soil survey manual. Soil Conservation Service U.S. Department of Agriculture Handbook, vol. 18. Strahler, A.N., 1952. Hypsometric (area-altitude) analysis of erosional topography. Geol. Soc. Amer. Bull. 63, 1117–1142. Veneman, P.M., Lindbo, D.L., Spokos, L.A., 1998. Soil moisture and redoximorphic features, a historical perspective. In: Rabenhorst, M.C., et al. (Ed.), Quantifying Soil Hydromorphology. SSSA spec. pub., vol. 54. Western, W., Grayson, R.B., Blöschl, G., Willgoose, G.R., McMahon, T.A., 1999. Observed spatial organisation of soil moisture and its relation to terrain indices. Water Resour. Res. 35, 797–810. Wilson, J.P., Western, W., Grayson, R.B., 2004. Identifying sources of variability in temporal and spatial soil moisture observations. Water Resour. Res. 40, W02507. WRB, 2006. World Reference Base for Soil Resources. World Soil Resources Reports, vol. 103. FAO, Rome.
Catena 72 (2008) 395 – 404 www.elsevier.com/locate/catena
Soil distribution in valleys according to stream order Brice Mourier a,b,⁎, Christian Walter a , Philippe Merot a a
b
INRA Agrocampus Rennes, UMR Sol-Agronomie, Spatialisation, 65 route de Saint Brieuc CS 84215, 35042 Rennes cedex, France Centre Alpin de Recherche sur les Réseaux Trophiques et les Ecosystèmes Limniques (UMR 42 INRA/Université de Savoie), Domaine Universitaire, 73376 Le Bourget du Lac, France Received 25 October 2006; received in revised form 9 July 2007; accepted 25 July 2007
Abstract While much research has been done on predicting the occurrence of waterlogged soils in small catchments, we need to improve our knowledge of the extension of these soils in large catchments. The aim of this study is to analyse the extent of soils with redoximorphic features in the valley bottomland domain as a function of the stream order. This study concerns a 10,000 km2 catchment (River Vilaine, Armorican massif, north-western France) where valley bottomland soils commonly associated with hydromorphic characteristics cover up to 20% of the basin area. To describe the catchment organisation, we used the stream order classification of Strahler to test the behaviour of the topographic index in a large range of landscape morphological settings. Two methods were used to define the extent of the hydromorphic zone (HZ) in each valley bottomland according to stream order: (i) A field study based on mapping the HZ according to the occurrence of redoximorphic features along 60 transects; (ii) a modelling approach linking a DEMderived topographic index to the digitized stream network of the River Vilaine. In view of the topographic factors, progressive valley widening may represent an enhancing factor of HZ extent. Thus, simple topographic index modelling predicts an increase in waterlogging in high-order channel settings (orders 6–7). By contrast, field mapping suggests that HZ extent remains stable with increasing order and decreases significantly for high-order settings (orders 6–7). Therefore, topographic index modelling appears effective in upper catchment settings (1st, 2nd and 3rd order). On the contrary, modelling efficiency is limited in high-order settings where the indices prove to be inappropriate: in such contexts, interactions between adjacent hillslope and HZ are of secondary importance. Along the longitudinal profile of the catchment, soil material near the streams shifts from having a colluvial origin in low-order to an alluvial origin in high-order settings. In high-order settings, the fine-scale valley bottomland topography and the spatial organisation of deposits control waterlogging duration and possibly play a major role in HZ extent. Finally, the integration of stream order data should considerably improve the efficiency of modelling the spatial distribution of soils over large catchments. © 2007 Elsevier B.V. All rights reserved. Keywords: Redoximorphic features; Stream order; Catchment; Topographic modelling
1. Introduction The spatial extent of water-saturated soils is a key variable in the hydrological response of a catchment and, more generally, in the functioning of hydrologic systems. Surface flow depends on water infiltration conditions and vertical water movements within ⁎ Corresponding author. Centre Alpin de Recherche sur les Réseaux Trophiques et les Ecosystèmes Limniques (UMR 42 INRA/Université de Savoie), Domaine Universitaire, 73376 Le Bourget du Lac, France. Tel.: +33 4 79 75 86 37; fax: +33 4 79 75 88 80. E-mail address: [email protected] (B. Mourier). 0341-8162/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.catena.2007.07.012
the soil (Moussa and Bocquillon, 1996). Waterlogging of soils contributes to the partitioning of both water and energy involved in evapotranspiration and erosion (Wilson et al., 2004). Soil and sub-soil water accumulation can promote erosion (Western et al., 1999) even if soil saturation is not complete (Burt and Butcher, 1985). High soil water content enhances the redistribution of nutrients and sediments in the landscape (Georgakakos, 1996; Chaplot and Walter, 2003). Temporal variation of soil moisture is also a major factor in assessing the hydrological response of a surface (Gómez-Plaza et al., 2000; Wilson et al., 2004). Seasonal soil moisture variation is locally controlled by the balance between evaporation and precipitation. A catchment can be
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broadly divided into two areas, saturated and well-drained, that are separated by a boundary that varies in time (Merot et al., 2003). When water saturation of soils occurs for periods long enough to allow the development of reducing conditions, this may be recognized by the observation of a gleyic colour pattern (WRB, 2006). In this way, soil colour mottling, the presence of segregated iron and manganese (hydr)oxides and the presence of organic soil material, represent morphological indicators that allow to infer the soil water regime (Mitsch and Gosselink, 1993; WRB, 2006). Veneman et al. (1998) summarized the relationship between redoximorphic features and seasonal saturation in soils. Within a catchment, the distribution of soils with redoximorphic features is almost stable over time due to the inertia of underlying processes and the persistence of these features (Mitsch and Gosselink, 1993; Brinson, 1993). The delineation of the area within a landscape were soils are affected by redoximorphic features in the topsoil horizon (b 20 cm depth), here referred to as the Hydromorphic Zone (HZ), is therefore a major issue in soil survey studies (Soil Survey Division Staff, 1993). Due to the close relationship between topography and soil waterlogging, spatial modelling approaches based on topographic attributes have been widely developed to predict the HZ spatial distribution (McBratney et al., 2003). Local parameters such as slope, elevation, convexity, concavity and upslope drainage area, are derived from Digital Elevation Models (DEMs) and can be combined into topographic indices linked to soil waterlogging extent (Merot et al., 1995; Freer et al., 1997; Crave and Gascuel-Odoux, 1997; Rodhe and Seibert, 1999; Western et al., 1999; Chaplot et al., 2003). Beven and Kirkby (1979) established a compound topographic index, distributed over space, by determining the upslope drainage area per unit contour length (a) and local slope (tanβ) at each cell of a DEM. This topographic index (ln (a) / (tanβ)) assumes that topography is the major factor controlling the extension of waterlogging through two main processes: flow convergence and lateral drainage (Wilson et al., 2004). The increasing availability of DEMs has favoured the use of indices, although most validation studies have found that only roughly 50% of the in situ spatial variability of the HZ extent can be explained (Wilson et al., 2004). Lastly, most applications have been tested and validated in upper catchments related to 1st, 2nd or 3rd order streams according to the Strahler (1952) classification. Additional factors have been accounted to improve soil with hydromorphic characteristics prediction: (i) soil transmissivity linked to soil texture (Beven and Kirkby, 1979), and (ii) annual effective rainfall (Merot et al., 2003) to compare catchments with different climatic conditions. Several authors (Seyfried, 1998; Qiu et al., 2001; Chaplot and Walter, 2003; Fu et al., 2003; Buttle et al., 2004) emphasize the importance of soil properties, especially soil depth and abrupt textural changes, for understanding subsurface water flow that often accounts for the HZ extent. Recently, Merot et al. (2006) defined a new methodology, the PEEW approach (Potential, existing and efficient approach), which combines permanent and nonpermanent criteria to delineate wetlands. This approach account
for land use and land cover in farming zones modifying delineation and functions of wetlands. At the catchment scale, energy and material fluxes vary from the sources to the outlet zone. Specifically, the regolith (soil parent material), such as the autochthonous material or colluvial and alluvial deposits, may change downstream in the catchment and strongly affect soil water transmissivity. As a result, HZ distribution in valley bottomlands may change according to the catchment organisation. To describe the catchment organisation, stream networks are studied by order according to the Strahler (1952) index method. Stream order may be tested as an indicator for ranking sub-catchments and studying HZ extent over large areas. The aim of this study is to analyse the extent of soils with redoximorphic features in the valley bottomland domain as a function of stream order. The study takes place in the Vilaine catchment where we carried out two successive steps: (i) the in situ soil study of the extent of the HZ along 60 cross valley transects ranked by stream order (6‑16 transects by order class); (ii) the comparison of field descriptions with predictions from a topographic modelling approach based on estimations of the topographic index in the valley bottomland domain. 2. Materials and methods 2.1. Study area Study sites were chosen in the Vilaine catchment, the largest drainage basin in the Armorican Massif of western France (Fig. 1). The study area covers 10,000 km2 and exhibits a range in elevation of 305 m. Mean annual rainfall ranges from 700 to 750 mm, with considerable spatial variability owing to the large size of the catchment area. The landscape is strongly affected by agricultural activities, covering almost 62% of the total basin area. One particular aspect of land use is that valley bottomland zones are mainly used as pastures (Chaplot and Walter, 2003). Topography is generally smooth and well correlated with geological formations. Moreover, previous tectonic disturbances (Chaplot et al., 1999) and quaternary deposits (Aeolian loam, riverbank) contribute to the present-day landscape morphology. Bottomland soils are commonly associated with hydromorphic conditions and cover up to 20% of the basin area (Merot et al., 2003), which is a result of their position in the landscape (Merot et al., 1995). 2.2. Definition of stream order and modelling of HZ distribution using topographic indices Strahler (1952) indexation is preferred here to other indexation systems (Gravelius, 1914; Shreve, 1966), since previous studies have shown that modelling of the Vilaine hydrological regime is improved by integrating this descriptor of the catchment's spatial organisation (Crave, 1995; Cudennec, 2000). Stream order allows us to rank the size and the flow regime of streams. It is a measure of the position of the stream in the tributary hierarchy and is sensitive to the accuracy of the drainage pattern delineation. Strahler's (1952) stream order system is an increasingly used method for classifying stream segments based on the number of
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Fig. 1. Vilaine drainage network and location of the 30 studied transects. Streams are marked according to Strahler indexation system.
upstream tributaries. Stream order increases with catchment size, tributary number and drainage network density (Crave, 1995). Stream order and topographic index modelling were extracted from a 50-m resolution DEM and from a digitized stream network previously incorporated into ArcGIS 8.3 software (© ESRI). The maximal order for the Vilaine catchment is seven, while first-order streams represents approximately 50% of the total stream length. The compound topographic index (Beven and Kirkby, 1979) presented in the Introduction was adopted to model the HZ extent. It is mainly based on the assumption that the hydraulic gradient of the shallow water table is equal to the local topographic slope angle, tanβ. The spatial distribution of the soil moisture in a catchment is described by the so called topographic index, log(a / tanβ). a and tanβ are easily computed from a DEM. The potential soil moisture increases with the value of this index. For a rainfall depth given for the whole catchment,
the larger the drainage area and the smaller the slope are, the higher is the topographic index value and thus the probability of occurrence of high soil moisture. This index estimates the soil surface water content at all cells of the raster layer. In a later step, we assume that high values of the topographic index are linked to the presence of redoximorphic surface features. We studied the index distribution for different stream orders in the neighbourhood of streams (arranged by orders), by creating buffer zones of different widths (15, 30, 60, 90, 120, 180, 240 and 300 m) bordering the drainage network. 2.3. Field study of HZ spatial distribution along stream transects The extent of soils with hydromorphic characteristics was delineated perpendicularly to streams of the Vilaine catchment.
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30 settings were randomly selected within the catchment (Fig. 1) based on an indexed map of the stream network. Classes 4 and 5 were grouped because their cumulative lengths represent only 12% of the total length, as well as classes 6 and 7 which represent only 5%. Hence, five order classes were defined as follows: 1, 2, 3, 4–5, 6–7. At each selected site, the transect was investigated for soil morphological characteristics when the following operational conditions were satisfied: (i) good differential GPS signal reception along the whole transect in order to locate precise soil boundaries and provide an accurate topographical profile; settings with dense and high vegetation therefore had to be eliminated; (ii) uniform land use conditions not heavily modified by human activities (roads, embanking, canalization, etc.); (iii) authorisation by the land owner. Finally, each order class was represented by 6–16 transects. On each transect, the two sides of the valley were characterized separately because of the asymmetry of the hillslopes. Topographical and pedological information were collected along each transect using the following procedures (Fig. 2): (i) the topographic line was established with a Pathfinder Pro XRS GPS, giving a submeter-scale precision of geographical coordinates and elevation. Elevation data were smoothed using a 10-order spline function adjustment with an Splus 6.1 (Insightful Corporation, 2003), which enabled us to represent the general configuration of the valley; (ii) the presence or absence of redoximorphic features in the upper soil horizon (0–20 cm) was precisely located. These limits were observed by regularly spaced (10 m) soil auger profiles. When two successive profile observations were significantly different (presence or changes in intensity of soil redoximorphic features), intermediate profiles were carried out until we obtained a metre-scale precision on the limit location. Two levels of redoximorphic intensity were distinguished depending on the abundance of redoximophic features in the topsoil horizon. A Low Hydromorphic Zone (LHZ) was described when gleyic colour pattern (WRB, 2006) was present at an abundance of less than 20% of the soil matrix. A High Hydromorphic Zone (HHZ) was delineated when redoximorphic features represented more than 20% of the soil matrix. Finally, HZ was defined as the sum of HHZ and LHZ. (iii) A solum description down to 120 cm depth at a distance of 10 m from the stream was performed to characterize the soil parent material. The main substratum types encountered in the valley bottomlands were made up of colluvial, alluvial or a mixing of
colluvio-alluvial parent materials. These were distinguished according to the following criteria: vertical heterogeneity of horizon texture and organic matter content, gravel shape and stone content, local morphological aspect (Baize and Girard, 1995). The topographical form of each valley side was described using the following variables (Fig. 2): - hillslope gradient (%) calculated perpendicularly to the streamline; - bottomland gradient (%) and bottomland width (D in m), by convention both calculated at a vertical elevation of 2 m above and perpendicularly to the streamline; - width (in m) of the LHZ, HHZ and HZ domains; - elevation (E in m) above the streamline of the limit of LHZ appearance. Overall correlation between the HZ extent and topography was tested through direct comparison of HZ length to topographic attributes such as gradient (%) of the general hillslope and topographic index. Finally, the proportion of soils with redoximorphic features within the valley bottomland domain is defined by the following equation: HZ=D 2.4. Statistical comparison Topographic attributes and extents were compared for different order classes using the non-parametric Kolmogorov Smirnov two sample test. Differences were considered to be significant at the 0.05 level. Statistical comparison has been done using an Splus software package (Insightful Corporation, 2003). 3. Results 3.1. Topographic index modelling over the whole catchment according to stream order Average topographic index values vary from 9 to 20 and increase significantly with stream order (Fig. 3). The evolution of the topographic index close to streams is analogous for all orders: index values decrease with distance from the stream channel and a major drop of the index occurs at about 50 m from
Fig. 2. Schematic representation of topographical and pedological information collected from the field study. Slope A depicts pedological variables, whereas slope B illustrates topographic variables. Both pedological and topographic information were collected on each slope.
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have a significantly lower bottomland gradient than the other settings. The D domain width is a powerful descriptor of progressive valley expansion, since the value increases with the width of the valley and smoothness of slope. The median bottomland D domain extension ranges from 41 m for order 1 to 89 m for orders 6–7. According to the Kolmogorov– Smirnov test, low-orders (1–3) are significantly different from high-orders (4–6). 3.3. HZ width and near-river substratum according to stream order Fig. 3. Statistics (mean, standard error, t = 0.05) of log(a / tanβ) topographic index according to buffer width around streams indexed by their Strahler order.
streams. Index values are maximum for orders 6 and 7 and remain significantly higher up to a distance of 300 m. For lower orders, differences are significant up to 100 m. Standard deviations are generally low, but increase near the stream, particularly for high-orders. As a result, there is a positive relationship between the increasing order and index value. This trend reflects the progressive valley expansion (smoother slope and more extensive valley), and therefore the increasing potential for waterlogged areas in higher order classes. 3.2. Valley cross profiles at the study sites according to stream order Fig. 4 presents the topographical and pedological information collected along the 30 transects grouped according to Strahler stream order. Transects exhibit a marked asymmetry between the two slopes of the same valley. Within each order, we observe evidence of high topographic variability, particularly for the orders 3 and 4–5. HZ lateral extent ranges from 0 to 100 m, being more pronounced for small orders (1 and 2), and appearing well correlated with topography, particularly on smooth slopes. For high-orders (orders 6–7), the HZ extent appears more discontinuous and less correlated to topographic factors. In some specific cases, the HZ is totally absent, for example on transects T8 and T31, of orders 1 and 7, respectively, which are both located in cultivated areas: T8 is located perpendicular to a temporary stream, while T31 intersects a large valley in a smooth slope setting with systematically well-drained soils. Intense redoximorphic features (HHZ) are observed in all transects with low stream order (except T8), whereas they are not recognized in order classes 6 and 7. Generally, HHZ appears in immediate proximity to the streams and is limited to a width of less than 30 m. Table 1 reports non-parametric statistics (median and interquartile values) of the valley bottomland gradient and the valley bottomland width (D). Half-transects are ranked by Strahler order. Generally, the bottomland gradient decreases with increasing stream order. Transects with stream order 2 yield the highest median gradient values (7.5%), associated with high variability (interquartile of 5.6%). The Kolmogorov–Smirnov test shows that high-order (6–7) transects
The extent of the HZ (distinguishing two intensities of redoximorphic features) and the nature of the substratum parent material were derived from the detailed field survey (Table 2, Fig. 4). Half-transects were stratified by Strahler order. Median HZ widths range from 23 m to 63 m (for orders 6–7 and order 2, respectively) and tend to decrease with increasing valley order. This observation is significant for high-order transects (6–7). In all the transects concerned, HHZ is represented by small strips with median lengths ranging from 11 to 26 m. The HHZ width is maximal for orders 2 and 4–5, in spite of a considerable semi-interquartile range in these same orders. For order 2, the median HHZ length is 26 m, which contrasts significantly with orders 6–7 where HHZ does not appear (Table 2, Fig. 4). Concerning the nature of the near-river substratum, the colluvial and colluvio-alluvial materials occur mainly in the upper catchment. In order 1 transects, 67% of the soils are formed on colluvial material (Table 2, Fig. 4). With increasing stream order, the parent material becomes exclusively alluvial (100% for orders 4–5 and 6–7). Thus, deposits show more homogeneous spatial organisation with increasing stream order. Soils formed on colluvial (or colluvio-alluvial) deposits and long HZ strips are both located at the head of the catchment, whereas, farther downstream, the HZ length is shorter and the soils are mainly formed on alluvial deposits. 3.4. Relation between HZ width and topographic attributes Based on the 60 hillslopes studied on both sides of the streams, Fig. 5.A shows the relation between the topographic index (maximal value along the transect) and HZ width according to stream order. The large scattering of points indicates a poor correlation between topographic index value and HZ lateral length. Although low-order settings exhibit lower index values, large HZ widths may also occur in these domains. While highorder valleys (orders 6–7) are associated with high topographic index, they may have a very restricted HZ. Linear correlations between the index and HZ extent are only significant for orders 2 and 3 (R2 = 0.27 and R2 = 0.11, respectively). Therefore, in upper catchment settings, the extension of the redoximorphic zones appears partially linked to variations of the topographic index, whereas, farther downstream, topographic modelling through this index appears unable to explain HZ extent. We studied the relationship between the gradient of the hillslope gradient and HZ width (Fig. 5.B). Hillslope gradient
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Fig. 4. Topographic profiles and extension of hydromorphic soils in the 30 studied transects. Transects are grouped by orders; two levels of redoximorphic features are distinguished; stream location and origin of soil substratum are indicated.
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Table 1 Statistics (median, 25% and 75% quartiles) of bottomland topographic attributes (gradient and width) according to the Strahler order of the valley Order Sample Bottomland gradient (%) Bottomland D domain width (m) number 1 2 3 4–5 6–7
12 16 16 10 6
5.2 (4.3–7.3)a⁎ 7.5 (4.4–10.0)a 4.3 (2.6–6.6)a 3.3 (2.1–5.1)a 1.7 (1.3–2.6)b
41 (28–51)a 30 (21–77)a 34 (19–49)a 61 (35–132)b 89 (63–142)b
⁎ Medians with the same superscript letters are not significantly different (Kolmogorov–Smirnov test, P = 0.05).
Table 2 Statistics (median, 25% and 75% quartiles) of HZ and HHZ extents (in m) and proportion of colluvial or alluvial soil material next to streams Order
1 2 3 4–5 6–7
Sample number
12 16 16 10 6
HHZ width
HZ width
Colluvial soil material
(m)
(m)
(% of the study area for each order)
15 (10–24)a⁎ 26 (11–41)a 11 (0–30)b 20 (7–53)a 0 (0–0)b
36 63 25 32 23
(11–75)a (19–89)b (14–71)a (21–83)a (0–68)c
67 50 25 0 0
Alluvial soil material
33 25 63 100 100
⁎ Medians with the same superscript letters are not significantly different (Kolmogorov–Smirnov test, P = 0.05). 60 transects are considered according to stream order.
directly affects and determines the maximum HZ extent, that is to say, the HZ width decreases with increasing slope. The greatest HZ widths (N 85 m) are generally located on slopes that do not exceed 5%. Gradients over 14% prevent the HZ from extending to more than 20 m from the channel. There is a significant correlation between the HZ width and the hillslope gradient for orders 2 and 3 (R2 = 0.30 and R2 = 0.58, respectively). For higher orders, the morphological variability appears too large and no
Fig. 6. Statistics on proportion of hydromorphic soils (median, 25% and 75% quartiles) in valley bottomland classified by order. The proportion is estimated by the ratio between total surface extent of HZ and D domain. ⁎Medians with same superscript letters are not significantly different (Kolmogorov–Smirnov test, P = 0.05).
significant correlation can be estimated. Thus, we observe that the hillslope gradient is correlated with HZ width in the head catchment, but not for the highest stream orders (R2 b 0.01, R2 = 0.02 for orders 4–5 and 6–7, respectively). Fig. 6 presents the proportions of soils affected by hydromorphic conditions in valley bottomlands, where extension is estimated by the distance D (Fig. 2). A ratio (R) expresses the HZ width according to the width of the valley bottomland domain (R = HZ width /D). If the ratio is higher than 1, only soils affected by hydromorphic conditions are developed in the valley even though redoximorphic features are also observed on the hillslopes. At low R values, soils of the valley are only partially affected by hydromorphic conditions. The values of this ratio reveal a contrast between lower orders, where soils with redoximorphic features are dominant (R(1) = 1.05 and R(2) = 1.69) and higher down-catchment orders (R(6–7) = 0.3). The median R ratio globally decreases with increasing stream order, but the difference only becomes significant for orders 6–7 where welldrained soils are dominant.
Fig. 5. HZ width on slopes according to two topographic attributes: (A) calculated topographic index derived from a 50-m DEM, (B) hillslope gradient. Symbols indicate Strahler order of the stream.
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4. Discussion Through the random selection of transects over a large area, this study highlights a great variability of HZ extent in comparison with stream order. The Strahler order differentiates the morphological settings of valleys and HZ extent. With increasing order, the topographic slope decreases progressively, so the valley becomes wider even if the slopes of the same transect are often asymmetric (Fig. 4 and Table 1). When considering topographic factors alone, progressive valley expansion may represent a factor that enhances the HZ extent. The modelling of potential soil waterlogging based on the topographic indexes is the most common method for predicting soils associated with hydromorphic conditions, even if topography does not represent the key process (Grayson and Western, 2001). The prediction of HZ distribution from topographic modelling suggests an increasing potential for waterlogging in areas with higher orders (Fig. 3). As indicated by the redoximorphic features and the arrangement of deposits, there is a progressive change of soil distribution in the valley bottoms of the Vilaine catchment.
Field mapping suggests that HZ extent remains stable for order 1 to 3 and even decreases, significantly for orders 6–7 (Fig. 6 and Table 2). HZ extent is therefore not correlated with valley widening, and soils are proportionally more affected by waterlogging processes at the head of the catchment (orders 1 to 3). Moreover, the highest hydromorphic intensities (HHZ) are predominant in low-order valleys (Fig. 4, Table 2). These observations suggest that, for low-order valleys, the extension of the HZ appears correlated with the potential waterlogged areas predicted by topographic index modelling. In highorder valleys, the topographic index modelling approach appears clearly inadequate to explain HZ extent. For such areas, additional information needs to be integrated to take account of the climatic and local hydrological controls on the occurrence of HZ. In all settings, the soil materials near the stream originate from deposits of alluvial or colluvial origin, or a mixture of both. Along the catchment, we observe an increasingly welldeveloped organisation of the deposits owing to valley expansion (Figs. 4 and 7, Table 2). The soils developed on colluvial or mixed deposits are affected by hydromorphic
Fig. 7. Conceptual model of arrangement of valley bottomland systems. The origin of the deposits and the HZ extent are considered according to stream order.
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conditions and occur mainly in the upper catchment. By contrast, the soils formed alluvial deposits are generally welldrained. On a catchment area scale, the spatial organisation of the deposits therefore seems to play a major role in HZ extent. Fig. 7 summarizes these observations in an integrative framework of valley bottomland development as a function of stream order. This conceptual model takes into account the changes in the arrangement of deposits within the catchment and the evolution of HZ extent. The soils occurring in areas with stream order values of 1 to 3 are more affected by redoximorphic features. HZ is correlated with topographic attributes, and interactions between slope and HZ are predominant (Merot et al., 2006). Moreover, Chaplot (1998) shows that colluvial origin soils from the upper catchment exhibit abrupt hydrodynamic variations between horizons. Thus, the flow of soil water is modified and waterlogging is favoured (Chaplot, 1998). Topographic modelling with topographic indexes is a useful tool for predicting the HZ extent (Fig. 5) in 1st, 2nd or 3rd order catchments. By contrast, HZs are either absent close to high-order streams (6–7) or located within a few tens of meters of the channel (Fig. 4). In such settings, the HZ distribution may be due to the microtopography inherited from the ancient stream flow regime. These ancient fluvial deposits are not found in areas of low stream orders, but are abundant in high stream orders where they strongly control the HZ development. The interaction between the slope and the HZ is minor, whereas the influence of valley bottomland micro-topography is dominant. Our results suggest that the prediction of HZ using DEM with stream order stratification is validated in low-order settings (orders 1 to 3). By contrast, prediction overestimates the HZ extent in high-order settings (orders 6–7). A possible improvement of the prediction of HZ extent in orders 6–7 should consist of an integration of the origin and the organisation of the quaternary deposits. Moreover, improvement of the DEM resolution would enable to describe more precisely the complex micro-topography of the valley bottomland area. 5. Conclusion According to our study, stream order can be considered as a crucial hierarchical descriptor of the distribution pattern of soils in the valley bottomland area. Stream order enables us to compare valley morphology in a wide range of settings: from small temporary streams to high-flow-regime rivers. The spatial approach applied here to characterize HZ extent, based on topsoil-surface redoximorphic features, can be used to supplement soil moisture studies and wetlands delineation, particularly on a catchment area scale. The results of the in situ study suggest that HZ extent remains similar for orders 1 to 3 and decreases, significantly for orders 6 and 7. By contrast, the modelling approach based on the topographic index predicts high potential waterlogging in high-order channel settings (orders 6–7). The modelling efficiency is limited in high-order settings where the indices are inappropriate. In such contexts, the fine-scale bottomland topography and the spatial organisa-
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