assessment of landscape sensitivity of the semiarid krom … · freieuniversitätberlin...

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Freie Universität Berlin Department of Earth Sciences Physical Geography Working Group Schütt The Krom Antonies Catchment I It is semiarid ( ¯ x = 490 mm) with reliable winter rainfalls. I The catchment is characterized by agroindustrial fruit and vegetable production – mostly grapes and potatoes. I The stream’s lower course is seasonal, the upstream tributaries are perennial. Round-the-year water availability is granted by excessive groundwater pumping and storage. Figure 1: Overview map of Western Cape and the Krom Antonies River Catchment [1, 2]. SPEI The Standardized Precipitation-Evapotranspiration Index (SPEI)[3] makes use of a simple log-logistic distribution of D i = P i - PET i where D is the difference between precipitation (P) and potential evapotranspiration (PET). The more distant from 0 the more extreme the climate event. Values between 1 and -1 are considered to represent normal conditions. Droughts & Wet Spells Figure 2: SPEI using a 24 month time scale for a 64 year time series. Data Source: [4] I Droughts and humid phases occur in cycles. I The winter months tend to prevalent above normal rainfalls. I Very humid phases do not occur during winter rain. I No severe droughts are shown on a two-year time scale. I Light drought conditions appear in all seasons. Table 1: Absolute Frequencies. Humid Drought very light normal light severe Jan 2 7 43 12 0 Feb 3 6 45 13 0 Mar 2 9 40 13 0 Apr 0 12 40 12 0 May 0 11 41 12 0 Jun 0 10 42 12 0 Jul 0 13 37 14 0 Aug 0 13 39 12 0 Sep 1 9 41 13 0 Oct 1 8 44 11 0 Nov 1 6 46 10 0 Dec 1 7 45 11 0 Landuse & Landcover I Major fractions (> 2 3) are not used. I Intensive agroindustry only in minor shares of the catchment (<3 %). I As a rule of thumb: »The further away from the stream, the less intensive the water use.« I Open Water is exclusively from artificial water storage dams. I Pasture, Barren and Fallow are in parts indistinguishable. I Wetland classes always related to the stream and/or water storage facilities I All Forest is man-made. Open Water Low Intensity Residual Barren Evergreen Forest Shrubland Orchards & Vineyards Grassland Pasture Fallow Woody Wetlands Herbaceous Wetlands 0 5 10 15 20 25 30 35 40 prop. [%] Figure 3: Classes after [5] Magnitude-Frequency-Analysis The recurrence interval (RI) of daily rainfall values shows a log-linear relationship of the rainfall values (r) and their descending rang position (N) [6]. RI = N + 1 r 0 500 1000 1500 0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000 22000 Distance [m] Elevation [m] Riviera Kromvlei Piketberg Piketberg Mountains NW SE Figure 4: Transect of the weather stations across the mountains. 0 25 50 75 100 125 Daily Rainfall [mm] 1 7 14 28 50 100 200 365 1 4 7 1013 Recurrence in Years Recurrence in Days P = RI -14.85 log10 19.38 Riviera n = 4394 days 0 25 50 75 100 125 Daily Rainfall [mm] 1 7 14 28 50 100 200 1 4 7 912 Recurrence in Years Recurrence in Days P = RI -30.75 log10 34.05 Kromvlei n = 4049 days 0 10 20 30 40 Daily Rainfall [mm] 1 7 14 28 50 100 200 365 1 3 457 Recurrence in Years Recurrence in Days P = RI -7.58 log10 10.85 Piketberg n = 2282 days Figure 6: MFA along a Transect. Data Source: [7, 8] I Piketberg station strongly differs from the others. Rainfall amount is generally lower and less frequently. I Kromvlei and Riviera show similar scales, but differing slopes and intersects reveal spatially heterogeneous rainfall events. I The frequencies of rainfalls are much higher than outside the valley, which is interpreted as a result of orographic rainfalls from the Westerlies and the valley’s topographic configuration. Unit Stream Power Erosion Deposition USPED [9] makes use of the transport capacity (T) limitation of soils and sediments to estimate potential erosion and deposition based on (R)USLE parameters, via T = LS × K × R × C × P. Spatial Subfactors LS (log-scaled) -10 -5 0 5 10 15 20 Figure 7: Slope Length & Steepness K [t ha h (ha MJ mm) -1 ] 0 0.1 0.2 0.3 0.4 0.5 Figure 8: Soil Erodibility C 0.6 0.5 0.4 0.3 0.2 0.1 0 Figure 9: Cover- Management Factor I Most of the LS values are reasonable, only the extreme values – located in v-shaped valleys and (perennial) streams – cause the LS factor to be exaggerated. LS is processed with the upslope contributing area (A) and slope (β ) – LS = A m (sin β ) n . Rill-interrill (m) affects the values extraordinarily (Fig. 11). I The eastern mountain range is geologically older and thus more erodible than the rest. Therefore K values are increased. I Vast areas are occupied by sparse or patchy vegetation. That leads to a generally low protection against erosive rainfalls. Only some minor regions in the lower course show favorable values. Rainfall-Runoff Erosivity 0 30 60 90 120 150 180 210 240 270 R factor [MJ mm h -1 ha -1 ] 0 10 20 30 40 50 60 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Daily Precipitation [mm] x Figure 10: Daily rainfall distribution and the corresponding R factor for Riviera station. Data Source: [7] Erosion & Deposition m = 1.6 Krom Antonies 0 5 10 15 20 extreme severe very severe severe high moderate low very low very low low - moderate high Share [%] Deposition Erosion Distribution of Classes (m = 1.6) m = 1.0 m = 1.2 Figure 11: Potential erosion/deposition. Classes after [10, 11] I The valley bottom is relatively stable. I The surrounding slopes are very prone to erosive processes. I Overshooting values – especially upstream – result from highly concentrated streamflow (Fig. 12) and need to be reclassified so these values must be seen as trends. I The most determining factor is the topography. Landuse and sediment properties are of minor importance. Figure 12: Stabilized Gully (N. Anselm 2014) Conclusions I The valley is blessed with a topographically and thus climatologically favored location. I Rainfalls occur temporally and spatially highly variable, in parts they fail. Their erosivity is most of the year negligible – only four months per year the values are excessive. I Climatic stresses (e.g. droughts) are intrinsic part of that environment. I Only very small fractions of arable land are used (ground-)water intensive. The majority is barren/unused. I The main trigger for potential erosion and deposition are the topography and rainfalls. Using USPED in this environment reveals LS and the rill-interrill ratio m as extremely sensitive. References [1] J. J. Danielson et al. Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010). USGS Open File Report 2011-1073. Reston, 2011. URL: http://pubs.usgs.gov/of/2011/1073/pdf/of2011-1073.pdf (visited on 09/12/2014). [2] T. G. Farr et al. “The Shuttle Radar Topography Mission”. In: Reviews of Geophysics 45.2 (June 2007), RG2004. [3] S. M. Vicente-Serrano et al. “A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index”. In: Journal of Climate 23.7 (2010), pp. 1696–1718. [4] Y. Fan et al. “A global monthly land surface air temperature analysis for 1948–present”. In: Journal of Geophysical Research: Atmospheres 113.D1 (Jan. 2008), p. D01103. [5] United States Department of the Interior et al. NLCD 92 Land Cover Class Definitions. 2014. URL: http://landcover.usgs.gov/classes.php (visited on 03/28/2014). [6] F. Ahnert. “Untersuchungen über das Morphoklima und die Morphologie des Inselberggebietes von Machakos, Kenia”. In: Catena Supplement 2 (1982), pp. 1–72. [7] Agricultural Research Council et al. AgroClimatology Programme. Pretoria, 2014. [8] Karsten Group. Karsten Group. 2015. URL: http://www.karsten.co.za/ (visited on 02/22/2015). [9] H. Mitasova et al. “Modelling topographic potential for erosion and deposition using GIS”. In: International journal of geographical information systems 10.5 (1996), pp. 629–641. [10] J. M. van der Knijff et al. “Soil Erosion risk Assessment in Italy”. In: Man and Soil at the Third Millennium. Ed. by J. L. Rubio et al. Vol. 2. Logroño., 2002, pp. 1903 –1917. [11] P. Borrelli. “Risk assessment of human-induced accelerated soil erosion processes in the intermountain watersheds of Central Italy”. PhD thesis. Freie Universität Berlin, Germany, 2011. Contact: M. Sc. Norbert Anselm Malteserstr. 74 – 100, G113 12249 Berlin [email protected] In cooperation with: Funded by:

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Page 1: Assessment of Landscape Sensitivity of the semiarid Krom … · FreieUniversitätBerlin DepartmentofEarthSciences PhysicalGeography WorkingGroupSchütt Assessment of Landscape Sensitivity

Freie Universität BerlinDepartment of Earth SciencesPhysical GeographyWorking Group Schütt

Assessment of Landscape Sensitivity of the semiarid Krom AntoniesRiver Catchment, Western Cape, South Africa

Norbert Anselm

The Krom Antonies Catchment

I It is semiarid (x̄ = 490mm) with reliable winter rainfalls.IThe catchment is characterized by agroindustrial fruit andvegetable production – mostly grapes and potatoes.

IThe stream’s lower course is seasonal, the upstream tributariesare perennial. Round-the-year water availability is granted byexcessive groundwater pumping and storage.

Figure 1: Overview map of Western Cape and the KromAntonies River Catchment [1, 2].

SPEIThe Standardized Precipitation-Evapotranspiration Index(SPEI)[3] makes use of a simple log-logistic distribution ofDi = Pi − PETi where D is the difference between precipitation(P) and potential evapotranspiration (PET).The more distant from 0 the more extreme the climate event.Values between 1 and −1 are considered to represent normalconditions.

Droughts & Wet Spells

Figure 2: SPEI using a 24 month time scale for a 64 year timeseries. Data Source: [4]IDroughts and humid phasesoccur in cycles.

IThe winter months tend toprevalent above normalrainfalls.

I Very humid phases do notoccur during winter rain.

INo severe droughts areshown on a two-year timescale.

I Light drought conditionsappear in all seasons.

Table 1: Absolute Frequencies.Humid Drought

very light normal light severeJan 2 7 43 12 0Feb 3 6 45 13 0Mar 2 9 40 13 0Apr 0 12 40 12 0May 0 11 41 12 0Jun 0 10 42 12 0Jul 0 13 37 14 0Aug 0 13 39 12 0Sep 1 9 41 13 0Oct 1 8 44 11 0Nov 1 6 46 10 0Dec 1 7 45 11 0

Landuse & Landcover

IMajor fractions (> 2⁄3) are not used.I Intensive agroindustry only in minorshares of the catchment (<3%).

I As a rule of thumb: »The furtheraway from the stream, the lessintensive the water use.«

IOpen Water is exclusively fromartificial water storage dams.

I Pasture, Barren and Fallow are inparts indistinguishable.

IWetland classes always related tothe stream and/or water storagefacilities

I All Forest is man-made.

Open WaterLow Intensity ResidualBarrenEvergreen ForestShrublandOrchards & VineyardsGrasslandPastureFallowWoody WetlandsHerbaceous Wetlands

0

5

10

15

20

25

30

35

40

prop. [%]

Figure 3: Classes after [5]

Magnitude-Frequency-Analysis

The recurrence interval (RI) of daily rainfall values shows alog-linear relationship of the rainfall values (r) and theirdescending rang position (N) [6].

RI =N + 1

r

0

500

1000

1500

0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000 22000Distance [m]

Ele

vation

[m

]

●Riviera Kromvlei Piketberg

PiketbergMountains

NW SE

Figure 4: Transect of the weather stations across the mountains.

●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●●0

25

50

75

100

125

Dai

ly R

ainf

all [

mm

]

1 7 14 28 50 100 200 365

1 4 7 1013

Recurrence in Years

Recurrence in Days

P = RI −14.85 log10 19.38Riviera

n = 4394 days

●●

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25

50

75

100

125

Dai

ly R

ainf

all [

mm

]

1 7 14 28 50 100 200

1 4 7 9 12Recurrence in Years

Recurrence in Days

P = RI −30.75 log10 34.05Kromvlei

n = 4049 days

●●●

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10

20

30

40

Dai

ly R

ainf

all [

mm

]

1 7 14 28 50 100 200 365

1 3 4 5 7

Recurrence in Years

Recurrence in Days

P = RI −7.58 log10 10.85Piketberg

n = 2282 days

Figure 6: MFA along a Transect. Data Source: [7, 8]

I Piketberg station strongly differs from the others. Rainfallamount is generally lower and less frequently.

IKromvlei and Riviera show similar scales, but differing slopesand intersects reveal spatially heterogeneous rainfall events.

IThe frequencies of rainfalls are much higher than outside thevalley, which is interpreted as a result of orographic rainfallsfrom the Westerlies and the valley’s topographic configuration.

Unit Stream Power Erosion Deposition

USPED [9] makes use of the transport capacity (T) limitation ofsoils and sediments to estimate potential erosion and depositionbased on (R)USLE parameters, via T = LS× K× R× C× P.

Spatial Subfactors

LS (log−scaled)

−10−5

05

101520

Figure 7: SlopeLength & Steepness

K [t ha h (ha MJ mm)−1]

0

0.1

0.2

0.3

0.4

0.5

Figure 8: SoilErodibility

C

0.60.50.40.30.20.1

0

Figure 9: Cover-Management Factor

IMost of the LS values are reasonable, only the extreme values –located in v-shaped valleys and (perennial) streams – cause theLS factor to be exaggerated. LS is processed with the upslopecontributing area (A) and slope (β) – LS = Am(sin β)n.Rill-interrill (m) affects the values extraordinarily (Fig. 11).

IThe eastern mountain range is geologically older and thus moreerodible than the rest. Therefore K values are increased.

I Vast areas are occupied by sparse or patchy vegetation. Thatleads to a generally low protection against erosive rainfalls. Onlysome minor regions in the lower course show favorable values.

Rainfall-Runoff Erosivity

0

30

60

90

120

150

180

210

240

270

R factor [M

J mm

h−

1 ha−

1]

●●

●●

●●

●●

●●●

●●

●●

●●

●●

●●

●●●

0

10

20

30

40

50

60

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Dai

ly P

reci

pita

tion

[m

m]

●●

● ● ●●

● ● ●

● x

Figure 10: Daily rainfall distribution and the corresponding Rfactor for Riviera station. Data Source: [7]

Erosion & Deposition

m = 1.6

Krom Antonies 0 5 10 15 20

extreme severevery severe

severehigh

moderatelow

very lowvery low

low − moderatehigh

Share [%]

Deposition

Erosion

Distribution of Classes (m = 1.6)

m = 1.0 m = 1.2

Figure 11: Potential erosion/deposition. Classes after [10, 11]

IThe valley bottom is relatively stable.IThe surrounding slopes are veryprone to erosive processes.

IOvershooting values – especiallyupstream – result from highlyconcentrated streamflow (Fig. 12)and need to be reclassified so thesevalues must be seen as trends.

IThe most determining factor is thetopography. Landuse and sedimentproperties are of minor importance. Figure 12: Stabilized

Gully (N. Anselm 2014)

Conclusions

IThe valley is blessed with a topographically and thusclimatologically favored location.

I Rainfalls occur temporally and spatially highly variable, in partsthey fail. Their erosivity is most of the year negligible – onlyfour months per year the values are excessive.

I Climatic stresses (e.g. droughts) are intrinsic part of thatenvironment.

IOnly very small fractions of arable land are used (ground-)waterintensive. The majority is barren/unused.

IThe main trigger for potential erosion and deposition are thetopography and rainfalls. Using USPED in this environmentreveals LS and the rill-interrill ratio m as extremely sensitive.

References[1] J. J. Danielson et al. Global Multi-resolution Terrain Elevation Data 2010 (GMTED2010). USGS Open

File Report 2011-1073. Reston, 2011. URL:http://pubs.usgs.gov/of/2011/1073/pdf/of2011-1073.pdf (visited on 09/12/2014).

[2] T. G. Farr et al. “The Shuttle Radar Topography Mission”. In: Reviews of Geophysics 45.2 (June 2007),RG2004.

[3] S. M. Vicente-Serrano et al. “A Multiscalar Drought Index Sensitive to Global Warming: TheStandardized Precipitation Evapotranspiration Index”. In: Journal of Climate 23.7 (2010),pp. 1696–1718.

[4] Y. Fan et al. “A global monthly land surface air temperature analysis for 1948–present”. In: Journal ofGeophysical Research: Atmospheres 113.D1 (Jan. 2008), p. D01103.

[5] United States Department of the Interior et al. NLCD 92 Land Cover Class Definitions. 2014. URL:http://landcover.usgs.gov/classes.php (visited on 03/28/2014).

[6] F. Ahnert. “Untersuchungen über das Morphoklima und die Morphologie des Inselberggebietes vonMachakos, Kenia”. In: Catena Supplement 2 (1982), pp. 1–72.

[7] Agricultural Research Council et al. AgroClimatology Programme. Pretoria, 2014.[8] Karsten Group. Karsten Group. 2015. URL: http://www.karsten.co.za/ (visited on 02/22/2015).[9] H. Mitasova et al. “Modelling topographic potential for erosion and deposition using GIS”. In:

International journal of geographical information systems 10.5 (1996), pp. 629–641.[10] J. M. van der Knijff et al. “Soil Erosion risk Assessment in Italy”. In: Man and Soil at the Third

Millennium. Ed. by J. L. Rubio et al. Vol. 2. Logroño., 2002, pp. 1903 –1917.[11] P. Borrelli. “Risk assessment of human-induced accelerated soil erosion processes in the intermountain

watersheds of Central Italy”. PhD thesis. Freie Universität Berlin, Germany, 2011.

,

Contact:M.Sc. Norbert AnselmMalteserstr. 74 – 100, G11312249 [email protected]

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