Sediment yield variability in Spain: a quantitative and semiqualitative analysis using reservoir sedimentation rates

Abstract

An existing dataset of area-specific sediment yield (SSY) for 60 catchments in Spain that was retrieved from sediment deposition rates in reservoirs [Avendaño Salas, C., Sanz Montero, E., Rayán, C., Gómez Montaña, 1997. Sediment yield at Spanish reservoirs and its relationship with the drainage basin area. In: Proceedings of the 19th Symposium of Large Dams, Florence, 1997. ICOLD (International Committee on Large Dams), pp. 863–874] reveals that catchment area alone explains only 17% of the variability in SSY. In this study, an attempt to explain the remaining variability in SSY was made using a quantitative and a semiqualitative approach for 22 catchments. During a field survey, the 22 selected catchments were characterised by topography, vegetation cover, lithology, shape and the presence of gullies in the broad vicinity of the reservoir. This information was used to develop a factorial scoring index model that provides a fairly accurate and reliable prediction of SSY. A classical multiple regression model using climatic, topographic and land use properties derived from regional datasets could not explain as much variance as the qualitative index model, nor did it appear to be as reliable. The same conclusion could be drawn when using the CORINE soil erosion risk map of southern Europe. The low prediction capability of the multiple regression models and the CORINE soil erosion risk map could be attributed mainly to the fact that these methods do not incorporate gully erosion and that the land cover data are not a good representation of soil cover. Both variables have been shown to be of great importance during the field surveys. Future assessments of SSY could be quickly and efficiently made using the proposed factorial scoring index model. In comparison with other models, which demand more data, the index model offers an alternative prediction tool.

Introduction

In many parts of the world, soil erosion affects the stability of ecosystems, often causing irreversible land degradation. Both on-site and off-site problems can be related to the variety of soil erosion processes. On-site effects refer mainly to a loss of agricultural and economical productivity, and to land degradation as a whole, whereas one of the most important off-site effects is certainly the sedimentation of reservoirs and their corresponding loss in water storage capacity. It is estimated that the annual loss in storage capacity of the world's reservoirs due to sediment deposition is around 0.5–1% (WCD, 2000). For many reservoirs, however, annual depletion rates are much higher and can go up to 4% or 5%, such that they lose the majority of their capacity after only 25–30 years. These high rates of storage loss pose a serious threat to the economic sustainability of the reservoir. A reduction in the volume of sediment delivered to the reservoir can be achieved by reducing soil erosion, or sediment production, as well as by minimizing the sediment delivery from the hillslopes to the rivers. On the other hand, an accurate estimate of reservoir sediment deposition rates should be made during the planning of new reservoirs.

At present, sediment yield predictions are achieved mainly through simple empirical models that relate the annual sediment delivery by a river to catchment properties, including drainage area, topography, climate and vegetation characteristics (e.g. Flaxman, 1972, Walling, 1983, Hadley et al., 1985, Onstad, 1984, Bazoffi et al., 1996, Lixian et al., 1996, Verstraeten and Poesen, 2001). Catchment area is probably the most important of all and, in many cases, it is the only explanatory variable used to predict SSY (e.g. Strand, 1975, Dendy and Bolton, 1976, Lahlou, 1988). Area-specific sediment yield (SSY) usually decreases with increasing catchment area following a power function, which can be easily explained by the theory of sediment sources and sinks (Walling, 1983). With increasing catchment area, the relative proportion of flat and gentle slopes that promote sediment deposition and, thus, act as a sediment sink (e.g. floodplains) will increase, whereas these areas will normally not contribute to sediment production such that the relative proportion of sediment sources will decrease. Such a relation may be valid for regions with homogenous land use, climate, topography and soils, and where the range in catchment areas is large. For the central Belgian Loess Belt, for instance, Verstraeten and Poesen (2001) showed that in such environmental conditions, catchment area behaves like a black box parameter. In such a case, no information about the basic variables that control soil erosion and sediment delivery within the catchment are included, and the use of such a relation for catchments with other environmental characteristics is impossible.

For two catchments with similar sizes but with contrasting climates and geomorphologies, the production and delivery of sediment may be completely different, i.e. the system is equifinal. Therefore, in regions with a large variability in climate, topography, land use and soil, a unique relation between SSY and catchment area will not be observed. This is also the case for Spain. Avendaño Salas et al. (1997) presented a dataset of SSY values for 60 catchments distributed throughout Spain, which were derived from reservoir sediment deposition records. Catchment area only explains 17% of the observed variability in SSY (Fig. 1). The relation between SSY (t km⁻¹ year⁻¹) and catchment area (A, km²) for the 60 catchments is:

$$\text{SSY}\text{=4139A}{}^{\mathrm{-0.43}}$$

with an R² value of 0.17 (model significance <1%). A large variability in SSY can be observed for catchments with similar size. For a catchment area of around 1000 km², SSY in Spain can range from 20 up to 1000 t km⁻² year⁻¹. The relation between SSY and catchment area as presented in Fig. 1 is, therefore, not a valid tool for predicting sediment deposition rates for planned reservoirs. This means that other variables need to be included in the prediction of SSY.

The objectives of this study are (1) to analyse the spatial variability in area-specific sediment yield for catchments in Spain and (2) to understand the major factors controlling this variability. This will be made first through a classical multiple regression approach whereby climate, topography and land use variables will be related to SSY. The collection of such environmental data has become easier nowadays as many global or regional environmental datasets are freely available. Lu and Higgitt (1999), for instance, have applied such datasets for analysing the sediment yield variability in the Upper Yangtze, whereas Summerfield and Hulton (1994) were the first to make use of global geophysical data to study topographic control on denudation rates in large river basins. Within this study, some of these datasets will be used as well and an evaluation of their use to examine the various controlling variables of SSY throughout Spain will be made. It was, however, also tested whether a more simple assessment of the erosional susceptibility of a catchment through short field surveys can provide as much information on the SSY compared to a lumped regression approach. For a rapid assessment of SSY, a simple geomorphic interpretation of the catchment may be accurate enough. Stocking and Elwell (1973; cited in Morgan, 1995), for instance, produced a soil erosion risk map using a factorial scoring system for Zimbabwe. Since this study explores this type of approach, 22 catchments out of the 60 catchments in the dataset of Avendaño Salas et al. (1997) were surveyed and used in this analysis.