Gully erosion in South Eastern Tanzania: spatial distribution ... - Core

Z. Geomorph. N. F.

52

2

225–235

Berlin · Stuttgart

June 2008

Gully erosion in South Eastern Tanzania: spatial distribution and topographic thresholds by Wouter M. J. Achten, Stefaan Dondeyne, Samweli Mugogo, Elly Kafiriti, Jean Poesen, Jozef Deckers, and Bart Muys with 4 figures and 3 tables

Summary. Though gully erosion is often mentioned as a major process of land degradation in South Eastern Tanzania, little information is available on its distribution. The Makonde plateau and adjacent inland plains are of particular concern as they are densely populated and are major areas of cashew nuts production. The occurrence of gully erosion was assessed in 66 villages selected by stratified random sampling in an area of 13,000 km2. Difference in susceptibility to gully erosion between landscape units was assess by determining topographic threshold parameters of 22 gullies on the Makonde plateau and 14 in the inland plains. Overall, gullies are common and spread equally over the different landscape units. Their occurrence is positively associated with terrain roughness (Cramér’s V = 0.30; P = 0.05) and negatively with population density (V = 0.44; P ⬍ 0.01). On the Makonde plateau occurrence of gully erosion is associated with the presence of roads, while on the inland plains it is predominantly found in fields (V = 0.37; P ⬍ 0.05). This association is explained by the high susceptibility of the Makonde plateau to gully erosion and is due to the particular nature of its deep, highly weathered, sandy soils. Appreciating differences in susceptibility to gully erosion between landscape units is most relevant for targeting soil conservation measures. eschweizerbartxxx

Résumé. L’érosion en ravine dans le Sud Est de la Tanzanie: répartition spatiale et seuils topographiques. – Bien que l’érosion en ravine soit souvent mentionnée comme processus important de dégradation de la terre dans le Sud Est de la Tanzanie, peu d’information est disponible sur sa répartition. Le plateau Makonde et les plaines intérieures adjacentes sont d’intérêt particulier étant densément peuplé et étant l’aire principale de production des noix d’anacardier. L’occurrence de l’érosion en ravine a été évaluée dans 66 villages répartis sur une superficie de 13.000 km2 et sélectionnés par échantillonnage aléatoire stratifié. La différence de susceptibilité à l’érosion en ravine entre les unités paysagiques a été évaluée en déterminant les paramètres du seuil topographiques de l’érosion de 22 ravines sur le plateau Makonde et 14 dans les plaines intérieures. En général, l’érosion en ravine est courante et est également répartie dans les diverses unités paysagiques. Leur occurrence est positivement associée à la rugosité du terrain (V = 0.30 de Cramér; P = 0.05) et négativement avec la densité de population (V = 0.44; P ⬍ 0.01). Sur le plateau Makonde l’occurrence de l’érosion en ravine est associée aux routes, alors que sur les plaines intérieures on la trouve principalement dans les champs (V = 0.37; P ⬍ 0.05). Cette association s’explique par la susceptibilité élevée du plateau Makonde à l’érosion en ravine et est principalement due à la nature particulière de ses sols proDOI: 10.1127/0372-8854/2008/0052-0225

0372-8854/08/0225 $ 2.75 © 2008 Gebrüder Borntraeger, D-14129 Berlin · D-70176 Stuttgart

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fonds, fortement altérés et sableux. Apprécier ces différences de susceptibilité à l’érosion en ravine entre les unités paysagiques est important pour pouvoir cibler des mesures de conservation de sol.

1

Introduction

Gully erosion is the process whereby runoff water accumulates, and often recurs over short periods, in narrow channels removing the soil to considerable depths. It is one of the most important processes contributing to the sculpturing of the earth surface. Areas with high gully density can become unsuitable for agricultural land-use. Gully erosion can cause major damage to infrastructure and can cause problems by siltation of rivers and reservoirs (Poesen et al. 2003). The initiation of gullies is a threshold phenomenon occurring when, for a given catchment area, a critical slope gradient has been exceeded; or when, for a given slope, a critical catchment area has been exceeded. The critical values of slope and catchment area vary according to climate, soil, terrain and land-use (Vandekerckhove et al. 2000). Patton and Schumm (1975) formulated the relationship as S = a A– b

(1)

where S is the slope of the soil surface at the gully head, A the area of the catchment, and a and b are parameters depending on environmental characteristics. The curve defined by this equation, corresponds with threshold values for the initiation of gullies in terms of slope and catchment area. Changes in land-use will influence the formation of gully erosion by affecting the catchment area. For example, changes in field sizes may directly lead to an expansion of the catchment area, as may alteration in water runoff due to paths or roads. Because of differences in geomorphologic processes and soil properties, topographic thresholds can be expected to vary across landscape units. Insights into variation in susceptibility should be useful to target strategies for controlling or preventing gully erosion. However, relatively few field studies on gully erosion have been conducted at large spatial scales, as these can be difficult and time demanding (Poesen et al. 2003). Although gully erosion is considered a major process of land degradation in Tanzania (Majule 2004), little is known about the actual extent of the phenomenon. This study aimed at (i) assessing the occurrence of gully erosion across different landscape units, (ii) investigating relationships between the occurrence of gully erosion with geomorphologic and demographic variables, and (iii) evaluating differences between landscape units in susceptibility to gully formation. eschweizerbartxxx

Gully erosion in South Eastern Tanzania

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Materials and methods

2.1 Study area Bennett et al. (1979) mapped landscape units of South Eastern Tanzania at a reconnaissance scale (1 : 250,000). From east to west, the landscape can be divided into a narrow coastal plain, an area of large plateaux and an area of inland plains (fig. 1). This study focussed on the Makonde plateau and the adjacent inland plains, as they are the most populated, and the most important production areas for cashew nuts, one of Tanzania’s major export commodities. The Makonde plateau is part of a chain of similar plateaux, with the Rondo plateau to the north and the Mueda plateau in Mozambique to the south. Soils of the Makonde plateau are deep, highly weathered, well drained and with a sandy topsoil and sandy loam or sandy clay loam in the subsurface horizons. Soil structure is usually weakly developed. The dominant soils are Xanthic, Veti-Acric Ferralsols (Dondeyne et al. 2003). The inland plains are gently undulating with broad flat-topped interfluves and wide shallow valleys, and are derived from Precambrian Basement rocks, mostly gneiss. Soil changes reflect variations in lithology, drainage and erosional history. On the interfluvial crest, least affected by erosion, deep, highly weathered, red sandy clay loam or sandy clay soils occur (Rhodic, Veti-Acric Ferralsols). On the slopes, less weathered, often shallow, coarse textured soils occur. These can be less than a metre

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Fig. 1. Landscape units of the study area and location of the study sites (Source: adapted from Bennett et al. 1979).

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deep and as varied as Chromic Luvisols, Leptic Cambisols and Petric Plinthosols (Dondeyne et al. 2003). The climate of South Eastern Tanzania is influenced by the south-eastern trade wind in mid-year and the north-eastern trade wind during the turn of the year. Air temperatures vary little: the mean is 24.3°C in July and 27.5°C in December; mean annual air temperature is 26°C in the coastal area and 24°C in the inland areas (Bennett et al. 1979). Rainfall pattern is uni-modal, but very erratic as can be seen from table 1. The inland plains, in the rain shadow of the plateaux, have a distinct drier climate than the plateaux. Hourly rainfall records necessary to determine the rainfall erosivity are not available. Average rainfall intensity is also higher on the Makonde plateau (table 1), indicating that erosivity can be expected to be highest on the plateaux. 2.2 Field survey In a first phase, a random sample of 66 villages was selected in an area of about 13,000 km2, after stratification according to landscape units: 23 from the Makonde dissected plateau, 22 from the Makonde high plateau, and 21 from the inland plains (fig. 1). In each of these villages, representatives of the village authorities and farmers were asked whether gullies occur within the village area. If so, at least one was visited of which the geographical coordinates of the gully head was recorded using a handheld global positioning system (GPS). The location of the gully was checked to be in agricultural fields, fallow fields, bush or along roads. In a second phase, 18 of these villages were revisited to determine the slopecatchment area relationship of the gully heads, whereby not more than five gullies were studied per village. The villages were selected to be representative for the landscape units, based on the information obtained from the first phase. On the Makonde dissected plateau 15 gullies were studied, on the Makonde high plateau 7 and in the inland plains 14. The slope gradient (S) of the soil surface at the gully head was measeschweizerbartxxx

Table 1

Rainfall characteristics (mm/year) in South Eastern Tanzania. Rainfall values for a dry and wet year have a 10 year return period. Annual rainfall

Rainfall intensity

Climatic station

Dry year

Average

Wet year

Median

IQR

Makonde plateau Mtwara airport (n = 45) Newala (n = 11)

844 688

1137 1245

1429 1912

187 243

82 65

Inland plains Nachingwea (n = 14) Masasi (n= 11)

605 538

823 873

1025 1550

189 179

43 55

n = number of years of observation; Rainfall intensity = S(RM2)/RA, with RM monthly rainfall, RA annual rainfall; IQR, interquartile range (adapted from Dondeyne et al. 2003).


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ured with a clinometer over a stretch of 5 m up and 5 m down the gully head, as proposed by Nyssen et al. (2002). The surface area of the catchment was determined by walking through it and visually evaluating whether runoff water would flow to the gully head or not, while recording boundary points with a GPS. Farmers helped in the field assessment and proved to have a detailed knowledge on the local hydrography. Subsequently, using a geographic information system, the boundary points were converted to polygons for calculating the actual catchment area. 2.3 Geomorphologic characteristics River density and terrain roughness were calculated for a circle with a radius of 5 km around each of the study sites: for villages where more than one gully occurred, a gully head taken randomly; for sites where no gullies occur, the village centre was taken as a reference. The river density was calculated as the total length of rivers occurring within this area. The data was derived from the digitised drainage network taken from the landscape maps of Bennett et al. (1979). The terrain roughness was calculated as the standard deviation of the topographic elevation, but corrected for the overall slope using least square linear regression. The elevation was assessed from a digital elevation model derived from contour lines of the topographic maps (scale 1 : 50,000) with contour lines at a height interval of 15.2 m (50 feet). ArcView’s Surface Tool extension (Jenness 2004) was used for estimating the elevation of 49 points spaced on a 800 ҂ 800 m square grid with the same centre point as described above. 2.4 Demographic data

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Data on the human population per ward1 was taken from the Tanzania National Website (2003) for the 2002 census, and from the official report of the 1988 census (United Republic of Tanzania 1991). Population density was determined by linking the 2002 population data with a digital map of the wards. Differences in the population between 2002 and 1988 per ward were used to calculate the average annual population growth. Subsequently, a digital map overlay allowed linking the study sites to annual population growth rate per ward. 2.5 Data analysis ANOVA with the Fisher’s least significant difference test (LSD) was used to check if landscape units differ in terms of geomorphologic and demographic characteristics. The Cramér’s V coefficient was calculated to assess the association between gully erosion and the different landscape units, the geomorphologic variables (river density, terrain roughness) and demographic variables (population density, population growth rate). For this analysis, the continuous variables were grouped into three categories corresponding to the 1⁄3 highest, 1⁄3 medium and 1⁄3 lowest observation. The mean topographic thresholds were determined as the orthogonal linear regression

1

A ward is the smallest administrative unit in Tanzania above village level.

ab

580

B

A

A b

15.8

20.5

13.6

13.1

15.6

ab

b

b

a

26.4

B

B

A

Terrain roughness (m)

50

93

96

80

90

106

ab

a

a

a

a

A

A

A

Population density (pers/km2)

1.9%

2.2%

1.4%

1.8%

1.9%

ab

ac

ab

ab

a

Growth rate (%) 1.1%

Demography

B

B

A

* different letters indicate significant differences between the landscape units (P ⬍ 0.05); those in capital concerns the analyse with the landscape units of the plains generalised to inland plains.

b

735

730

Inland plains (n = 21) Lulindi plains (n = 6) Nachingwea-Masasi plains (n = 8) Southern Masasi plains (n = 7)

a

b

423

Makonde dissected plateau (n = 23)

a*

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898

330

Makonde high plateau (n = 22)

River density (m/km2)

Geomorphology

Summary statistics of geomorphologic and demographic characteristics around 66 observation points on the Makonde plateau and adjacent inland plains, South Eastern Tanzania.

Landscape unit

Table 2

230 W. M. J. Achten et al.

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lines between the logarithm of the slope at the gully head (S) and the logarithm of the catchment area (A), as proposed by (Vandekerckhove et al. 2000). 3

Results

The landscape units mapped by Bennett et al. (1979) and used to stratify the random sampling of the study sites clearly correspond to distinct geomorphologic characteristics (table 2). River density on the Makonde plateau is significantly smaller than that of the inland plains. The opposite is true for the terrain roughness, though the difference between the Makonde dissected plateau and inland plains is not significant, while terrain roughness of the Southern Masasi plain gets to levels comparable as to those of the Makonde high plateau. The differences between the landscape units in terms of demographic characteristics are less clear, which could be expected, as the study area was targeted at the more populated parts of South Eastern Tanzania. As in terms of geomorphologic and demographic characteristics, the differences between the Lulindi, NachingweaMasasi and Southern Masasi plains are not or hardly significant (table 2), they are further referred to as the “inland plains”. Overall, gullies are found in 73% of the visited villages (48 out of 66 villages). In percentage of occurrence there is only a small difference between the Makonde high plateau 68% (15 out of 22 villages), the Makonde dissected plateau 70% (16 out of 23 villages) and the inland plains 81% (17 out of 21 villages). Occurrence of gullies is significantly associated with terrain roughness and population density, and not with any other geomorphologic or demographic characteristics (table 3). As shown in fig. 2, occurrence of gullies is positively associated with terrain roughness, and negatively with population density. On the Makonde plateau the occurrence of gullies is however significantly associated with the presence of roads, while on the inland plains they rather occur in fields (fig. 3). For the 36 gullies studied in more detail, the relationship between slope at the gully head (S) and catchment area (A) is clearly different for the Makonde plateau and inland plains (fig. 4). The observations of the Makonde dissected plateau and eschweizerbartxxx

Table 3

Strength of association between occurrence of gully erosion and geomorphologic and demographic characteristics.

Landscape units* Major landscape unit † River density Terrain roughness Population density Population growth rate

Cramér’s V

df

0.24 0.13 0.17 0.30 0.44 0.06

4 2 2 2 2 2

P ⬍ 0.44 ⬍ 0.59 ⬍ 0.40 ⬍ 0.05 ⬍ 0.01 ⬍ 0.89

* mapping units of Bennett et al. (1979) (see also fig. 1). † Landscape units generalised to inland plains, Makonde dissected plateau and Makonde high plateau.

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Makonde high plateau, seem to represent one population as can be seen in fig. 4. The slope of the 22 gullies on Makonde plateau ranges from 0.02 to 0.36 m/m, while on the inland plains it ranges from 0.02 to 0.015 m/m. The larger variability of the slope measured at the gully head on the Makonde plateau is consistent with the higher terrain roughness as derived from the DEM. In contrast the range for the catchment area is smaller on the Makonde plateau (0.08 to 7 ha) than on the inland plains (0.05 to 18 ha). Most strikingly, the slope of the regression line on the Makonde plateau is much steeper than that for the inland plains, indicating that soils of the Makonde plateau are more susceptible to gully erosion (fig. 4).

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Fig. 2. Frequency of occurrence of gully erosion in relation to terrain roughness and population density in 66 villages South Eastern Tanzania.

Fig. 3. Relationship between occurrence of gully erosion in fields or along roads per landscape units, South Eastern Tanzania.


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Fig. 4. Average topographical threshold of 22 gullies on the Makonde plateau and 14 gullies on the inland plains in South Eastern Tanzania.

4

Discussion and Conclusions

Gully erosion is common and evenly spread across the different landscape units of South Eastern Tanzania. In contrast to the perception that gully erosion would be principally associated to roads as had been reported by Vermang (2004), this study shows that gullies are equally common in fields. Still, a distinction can be made between landscape units, as on the Makonde plateau gullies are more often associated to roads than on the inland plains (fig. 3). Values from field observations reported in literature for the slope of the regression line – the b parameter of equation 1 – typically falls within the range between 0.1 and 0.6 (Nyssen et al. 2002, Vandekerckhove et al. 2000). Compared to those values, one can conclude that soils of the Makonde plateau (with b = 0.8) are very susceptible to gully erosion. The high susceptibility for gully erosion of the Makonde plateau could partly be attributed to the more erosive rainfall (table 1), but for the major part it seems to be linked to geomorphologic characteristics in combination with the particular nature of the deep, highly weathered and sandy soils. The soils of the Makonde plateau have weakly developed structures and are generally sandy, but with distinct higher clay content in the subsoil (Dondeyne et al. 2003) which explains their high susceptibility to gully erosion. Terrain roughness as determined from the digital elevation model is highest on the Makonde high plateau (table 2) and is positively associated with the occurrence of gully erosion (fig. 2). This relationship can however be seen as both cause and consequence of gully erosion: deep gullies result in higher terrain roughness and in turn may enhance runoff processes leading to more gully erosion. The association between gully erosion and roads on the Makonde plateau is understandable when taking into account the high susceptibility of this unit as indicated by the topographic threshold. Any change in the size of the catchment area, which typically happens when roads are made, will easily lead to the formation of gullies. Reciprocally, any soil conservation measure reducing surface water runoff, eschweizerbartxxx

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can be expected to be more effective on the Makonde plateau than on the inland plains. Appreciating these differences between landscape units seems most relevant to local policy makers and rural development agencies when elaborating strategies for soil conservation. Somewhat counter intuitive is the negative association between the occurrence of gully erosion and population density. At first sight, it could be explained by the “more people, less erosion” hypothesis where population growth and agricultural intensification results in improving rather than deteriorating the use of soil and water resources (Boyd & Slaymaker 2000). In the case of South Eastern Tanzania, however, it has to be attributed to, fewer people living in areas of the drier inland plains commonly affected by gully erosion and where soils are shallow and stony. As soils of the Makonde plateau are shown to be particularly sensitive to gully erosion, this should equally be expected to be so for the similar Rondo and Mueda plateaux. Moreover, when taking into account that soils of the Makonde plateau have been shown also to be sensitive to soil acidification when sulphur is used as a fungicide in the cashew groves (Ngatunga et al. 2003), this area appears to be particular vulnerable to land degradation. Acknowledgements This study was conducted as part of the “Soil Conservation Management project, South Eastern Tanzania” (project No ZEIN2002 PR253) financed by the Ministry of Agriculture and Food Security, Tanzania with support from the Flemish Inter-University Council, Belgium. The authors like to thank Mr Laurence B. Emmanuel and Ms Elisa Mapua for their contribution in preparing the digital terrain model, Mr Musa Mapua, Mr Laurence B. Emmanuel and Mr Abdallah Nachundu for their assistance in the fieldwork. eschweizerbartxxx

References Bennett, J. G., Brown, L. C., Geddes, A. M. W., Hendy, C. R. C., Lavelle, A. M., Innes, R. R. & Sewell, L. G. (1979): Report of the Zonal Survey team phase 2. Vol. 1: The physical environment. – Project report 67, Mtwara/Lindi Regional Integrated Development Programme, Land Resources Development Centre, Surrey, 242pp. Boyd, C. & Slaymaker, T. (2000): Re-examining the “more people less erosion” hypothesis: special case or wider trend? – Natural Resource Perspectives 63: 1–6. Dondeyne, S., Ngatunga, E. L., Cools, N., Mugogo, S. & Deckers, J. (2003): Landscapes and soils of South Eastern Tanzania: their suitability for cashew. – In: Topper, C. P. & Kasuga, L. J. (eds.): Knowledge transfer for sustainable tree crop development: 229– 239; BioHybrids Agrisystems, Reading. Jenness, J. (2004): Surface Tools extension for ArcView 3.x, v. 1. 5. Jenness Enterprises. Available at http://www.jennessent.com/surface_tools.htm. (accessed 19 Aug. 2004) Majule, A. E. (2004): Gateway to land and water information: Tanzania. FAO Rome, http://www.fao.org/ag/agl/swlwpnr/reports/y_sf/z_tz/tz.htm (accessed 16 June 2005). Ngatunga, E., Dondeyne, S. & Deckers, J. (2003): Is sulphur acidifying cashew soils of South Eastern Tanzania? – Agriculture, Ecosystems and Environm. 95: 179–184. Nyssen, J., Poesen, J., Moeyersons, J., Luyten, E., Veyret-Picot, M., Deckers, J., Haile, M. & Govers, G. (2002): Impact of road building on gully erosion risk: a case study from the Northern Ethiopian Highlands. – Earth Surf. Proc. and Landf. 27: 1267–1283.


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Patton, P. C. & Schumm, S. A. (1975): Gully erosion, North-western Colorado: a threshold phenomenon. – Geology 3: 88–90. Poesen, J., Nachtergaele, J., Verstraeten, G. & Valentin, G. (2003): Gully erosion and environmental change: importance and research needs. – Catena 50: 91–133. United Republic Of Tanzania (1991): Population census. Takwimu, Bureau of Statistics, President’s Office, Planning Commissions, Dar es Salaam (volumes per administrative region). Tanzania National Website (2003): 2002 Population and housing census, available at http://www.tanzania.go.tz/census/index.html. (accessed 13 Sep. 2004) Vandekerckhove, L., Poesen, J., Oostwijk Wijdenes, D., Nachtergaele, J., Kosmas, C., Roxo, M. J. & De Figueiredo, T. (2000): Thresholds for gully initiation and sedimentation in Mediterranean Europe. – Earth Surf. Proc. and Landf. 25: 1201–1220. Vermang, J. (2004): Gully erosion on the roads of the Makonde Plateaux in Southeast Tanzania. – Master dissertation, Catholic University of Louvain, Leuven, Belgium, 133pp. Addresses of the authors: Wouter M. J. Achten, Bart Muys, Laboratory for Forest, Nature and Landscape Research, Catholic University of Leuven, Celestijnenlaan 200, B-3001 Leuven, Belgium. – Stefaan Dondeyne (Corresp. author), Chimanimani National Reserve, Ministry of Tourism, C. P. 121, Chimoio, Mozambique. E-Mail: [email protected] – Samweli Mugogo, Elly Kafiriti, Naliendele Agricultural Research Institute, PO Box 509, Mtwara, Tanzania. – Jean Poesen, Physical and Regional Geography Research Group, Catholic University of Leuven, Celestijnenlaan 200, B-3001 Leuven, Belgium. – Jozef Deckers, Laboratory for Land and Water Management, Catholic University of Leuven, Celestijnenlaan 200, B-3001 Leuven, Belgium.

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