9 - Appendix 305 APPENDIX

Transcription

1 35 APPENDIX A Soil data B AML scripts to calculate relief parameters C Pedotransfer functions D Environmental factors E Regression equations to calculate maps of soil properties F Analysis of regression residuals G Maps of soil properties H PESERA parameters and results

2 36 9 Appendix The appendices A, B and E are provided electronically on the attached CD. Fig. D.1: Frequency distribution of sample and population for the climatic variables. 39 Fig. D.2: Fig. D.3: Percentage of catchment surface (population) and soil profiles (sample) per vegetation unit. 39 Percentage of catchment surface (population) and soil profiles (sample) per simplified vegetation unit. 31 Fig. D.4: Frequency distribution of sample and population for the metric relief parameters. 311 Fig. D.5: Percentage of catchment surface population and soil profiles sample per relief unit. 312 Fig. D.6: Percentage of catchment surface (population) and soil profiles (sample) per geological unit. 313 Fig. F.1: Frequency distribution of the regression residuals. 315 Fig. F.2: Distribution of the residuals per biogeographic region. 316 Fig. F.3: Distribution of the residuals of soil hydraulic properties per biogeographic region. 318 Fig. G.1: Soil depth [cm]. 321 Fig. G.2: Depth of the first (left) and second (right) layer [cm]. 322 Fig. G.3: Skeleton content of the first (left) and second (right) layer []. 323 Fig. G.4: Texture of the first (left) and second (right) layer [US texture class]. 324 Fig. G.5: CaCO3 content of the first (left) and second (right) layer []. 325 Fig. G.6: Organic carbon content of the first (left) and second (right) layer []. 326 Fig. G.7: Nitrogen content of the first (left) and second (right) layer []. 327 Fig. G.8: ph value of the second layer. 328 Fig. G.9: Saturated hydraulic conductivity of the first (left) and second (right) layer [cm/d]. 329 Fig. G.1: Field capacity of the first (left) and second (right) layer []. 33 Fig. G.11: Field capacity of the first (left) and second (right) layer [mm]. 331 Fig. G.12: Permanent wilting point of the first (left) and second (right) layer []. 332 Fig. G.13: Permanent wilting point of the first (left) and second (right) layer [mm]. 333 Fig. G.14: Available water capacity of the first (left) and second (right) layer []. 334 Fig. G.15: Available water capacity of the first (left) and second (right) layer [mm]. 335

3 37 Fig. G.16: Maps of soil properties aggregated to 84 soil classes for the application in the SWAT model. 336 Fig. H.1: Standard deviation of elevation in a radius of 3 km. 337 Fig. H.2: Soil sensitivity towards crusting. 338 Fig. H.3: Soil erodibility. 339 Fig. H.4: Effective soil water storage capacity. 34 Fig. H.5: Soil hydrological scale depth. 341 Fig. H.6: Land use classes for the PESERA model. 342 Fig. H.7: Sediment delivery ratio calculated from the DEM of the upper Drâa catchment. 343 Fig. H.8: Fig. H.9: Change in vegetation cover relative to the REMO ref simulation modelled by PESERA under global change scenarios for the biogeographic regions (see fig. 3.13). 344 Change in actual evapotranspiration relative to the REMO ref simulation modelled by PESERA under global change scenarios for the biogeographic regions (see fig. 3.13). 344 Fig. H.1: Change in runoff relative to the REMO ref simulation modelled by PESERA under global change scenarios for the biogeographic regions (see fig. 3.13). 345 Fig. H.11: Change in groundwater recharge relative to the REMO ref simulation modelled by PESERA under global change scenarios for the biogeographic regions (see fig. 3.13). 345 Fig. H.12: Change in erosion rate relative to the REMO ref simulation modelled by PESERA under global change scenarios for the biogeographic regions (see fig. 3.13). 346 Table D.1: Comparison of the frequency distribution of sample and population for the climatic variables. 39 Table D.2: Comparison of the frequency distribution of sample and population for the metric relief variables. 31 Table F.1: Results of the Kolmogorov Smirnov test for normal distribution of the regression residuals. 315 Table F.2: Highest bivariate correlation coefficient between residuals and the corresponding metric explaining variable and highest r² F value for the corresponding nominal explaining variable. 316 Table F.3: Mean and Standard Deviation (SD) of the measured soil properties (all horizons) per biogeographic region. 32

4 38 Appendix C: Applied pedotransfer functions following RAWLS & BRAKENSIEK (1985) K s = 24 * exp ( * τ * clay * sand us² * clay² * τ² * sand us * τ * sand us² * τ² * clay² * τ² * sand us² * clay * clay² * τ * sand us² * τ -.35 * clay² * sand us) Θ s = * sand us * clay * τ * clay² * sand us * τ * clay * τ -.96 * clay² * τ * τ² * sand us * τ² * clay Θ r = * sand us * clay * τ * clay² * sand us * τ * clay² * τ² * clay² * τ * τ² * clay λ = exp ( * sand us * τ * sand us² * clay² * τ² * sand us * τ * sand us² * τ² * clay² * τ² * sand us² * clay * clay² * τ * τ² * clay) Ψ b = exp ( * clay * τ * clay² * sand us * τ * clay * τ * sand us² * τ² * clay² * τ² * sand us² * clay * clay² * τ * sand us² * τ +.54 * clay² * sand us * τ² * clay) α = 1 / Ψ b n = λ + 1 m = 1 1/n clay = clay content [ by weight] (< 2 μm) sand us = sand content [ by weight] (5 μm - 2 μm) = saturated hydraulic conductivity [cm/day] K s τ = porosity [cm 3 /cm 3 ] Θ s = water content at saturation [cm 3 /cm 3 ] Θ r = residual water content [cm 3 /cm 3 ] λ = pore size distribution [dimensionless] Ψ b = bubbling pressure = air entry pressure (hpa) α, n, m = parameters for adjusting the Van Genuchten - retention curve To account for the soil skeleton content, Θ s, Θ r, and Ks are corrected as shown below (following BRAKENSIEK & RAWLS, 1994). K s_skel = if ((skel w *.1 / 4) < 1) then (1 - skel w *.1) * K s ) else (1 - skel w *.1) / (1 - ( skel w *.1) / 4) * K s ) Θ s_skel = Θ s * (1 -.1 * skel v ) Θ r_skel = Θ r * (1 -.1 * skel v ) K s_skel = saturated hydraulic conductivity incorporating skeleton content [cm/day] Θ s_skel = water content at saturation incorporating skeleton content [cm 3 /cm 3 ] Θ r_skel = residual water content incorporating skeleton content [cm 3 /cm 3 ] skel v = skeleton content [vol.-] skel w = skeleton content [weight-] fc = ((Θ r_skel + (Θ s_skel - Θ r_skel )) / ((1 + α * ) n ) m * 1 pwp = ((Θ r_skel + (Θ s_skel - Θ r_skel )) / ((1 + α * ) n ) m * 1 fc = water content at field capacity [Vol.-] pwp = water content at permanent wilting point [Vol.-]

5 39 Appendix D: Environmental factors Table D.1: Comparison of the frequency distribution of sample and population for the climatic variables. Temperature Precipitation Extreme Differences Positive.5.9 Negative Kolmogorov-Smirnov Z Asymptotic Significance.5.52 Sample Population Sample Population Temperature Precipitation Fig. D.1: Frequency distribution of sample and population for the climatic variables Clay Silt Sand Other Dense Sparse Vegetation: Depth of Soil Vegetation: Texture of Soil Vegetation: CaCO 3 content of Soil Deep Shallow Other High Medium Low Free Other High Medium + Oases Low Very Low High + Oases Medium Low Very Low Vegetation: Skeleton content of Soil Vegetation: organic matter version 1 Vegetation: organic matter version 2 Fig. D.2: Percentage of catchment surface (population) and soil profiles (sample) per vegetation unit.

6 Artemisia Thorny Cushion Shrub Oromediterranean Hamada Semi-Desert Rock Dunes Salt Vegetation Wadi Tamarisk Trees Mountain Wadi Oases Fig. D.3: Percentage of catchment surface (population) and soil profiles (sample) per simplified vegetation unit. Table D.2 - part I: Comparison of the frequency distribution of sample and population for the metric relief variables. X Y Elevation Aspect West Extreme Differences Positive Negative Kolmogorov-Smirnov Z Asymptotic Significance <.1 < North Slope Curvature Plan. Curv. Prof. Curv. Extreme Differences Positive Negative Kolmogorov-Smirnov Z Asymptotic Significance < Min. Curv. Max. Curv. Tan. Curv. CS Upslope A. Extreme Differences Positive Negative Kolmogorov-Smirnov Z Asymptotic Significance RE 3 RE 9 RE 3 Min. HS Max. HS Extreme Differences Positive Negative Kolmogorov-Smirnov Z Asymptotic Significance Mean HS TWI TSI TCI SPI Extreme Differences Positive Negative Kolmogorov-Smirnov Z Asymptotic Significance

7 311 Table D.2 - part II: Comparison of the frequency distribution of sample and population for the metric relief variables. SLF RPI ZIM RPI TWI Extreme Differences Positive Negative Kolmogorov-Smirnov Z Asymptotic Significance Abbreviations cf. Table 4.5 Plan. / Prof. / Min. / Max. / Tan. Curv. = planform / profile / minimum / maximum / tangential curvature HS = Hillshade RE = relief energy Sample Population Sample Population Sample Population Aspect Slope Curvature Planform Curv. Profile Curv. Minimum Curv. Maximum Curv. West North X Y Elevation ,9 -,6 -,3,,3, , -,5,,5 1, 1, , -,8 -,6 -,4 -,2,,2, , -,5,,5 1, 1, Sample Population Sample Population Sample Population Tangential Curv. CS -,6 -,4 -,2,,2,4,6, ,2 -,2 -,1,,,,1 E 2E7 4E7 6E7 8E7 1E8 1E8 1E8 E 5E9 1E1 2E1 2E1 2E1 3E1 Upslope Areas Fig. D.4 - part I: Frequency distribution of sample and population for the metric relief parameters.

8 312 Sample Population Sample Population Sample Population Relief Energy 3 Relief Energy Relief Energy 3 Min. Hillshade Max. Hillshade Mean Hillshade RPI TWI SPI SLF RPI ZIM TWI TSI TCI , -,5,,5 1, -1, -,5,,5 1, -1, -,5,,5 1, -1, -,5,,5 1, Fig. D.4 - part II: Frequency distribution of sample and population for the metric relief parameters Plains Hills High Hills High Plains Hills Hills Plains Hills Plains Hills Plains Plains Tablelands Plains with Hills or Open Hills and Hills and Macro landform: Brabyn 8 landforms Macro landform: Brabyn 7 classes Macro landform: Dikau Fig. D.5 - part I: Percentage of catchment surface population and soil profiles sample per relief unit.

9 Channel Toeslope Footslope Backslope Shoulder Interfluve 25 Valley Slope Ridge Plain Convergent Footslope Level Footslope Divergent Footslope Convergent Backslope Level Backslope Divergent Backslope Convergent Shoulder Level Shoulder Divergent Shoulder Hillslope Position PAR Hillslope Position ZIM Hillslope Position PEN Depression Hill Concave Saddle Positive Difference Curvature Convex Saddle Depression Landunit SHA Hill Concave Saddle Negative Difference Curvature Convex Saddle Convergent Accelerating Convergent Decelerating Divergent Accelerating Landunits TRO Divergent Decelerating C- Depression concave C- Saddle C-Hill Landunits GAU convex C- Saddle Annotation: For abbreviations cf. table 4.5 Convex Converging Prolated Converging Concave Converging Convex Parallel Prolated Parallel Concave Parallel Convex Diverging Prolated Diverging Concave Diverging Landunit SCH Fig. D.5 - part II: Percentage of catchment surface (population) and soil profiles (sample) per relief unit Neogenic Mesozoic Palaeozoic Proterozoic Sediment Consolidated Sediment Rock Magmatic Rock Metamorphic Rock Siliceous Siliceous, Carbonatic Carbonatic Sulfatic, Halitic Stratigraphical Era Type of Rock Geochemical Type of Rock Fig. D.6 - part I: Percentage of catchment surface (population) and soil profiles (sample) per geological unit.

10 Very Low Low Medium High Unconsolidated Limestone Schist Sandstone Siltstone Crystalline Rocks Resistance to Weathering Lithology Fig. D.6 - part II: Percentage of catchment surface (population) and soil profiles (sample) per geologocal unit.

11 315 Appendix F: Analyses of regression residuals Table F.1: Results of the Kolmogorov Smirnov test for normal distribution of the regression residuals. profile depth 1 st depth 1 st skeleton 1 st sand 1 st silt Extreme Differences Positive Negative Kolmogorov-Smirnov Z Asymptotic Significance.22 <.1 < st clay 1 st CaCO 3 1 st OC 1 st nitrogen 2 nd depth Extreme Differences Positive Negative Kolmogorov-Smirnov Z Asymptotic Significance nd skeleton 2 nd sand 2 nd silt 2 nd clay 2 nd CaCO 3 Extreme Differences Positive Negative Kolmogorov-Smirnov Z Asymptotic Significance.3.3 <.1 < nd OC 2 nd nitrogen 2 nd ph Extreme Differences Positive Negative Kolmogorov-Smirnov Z Asymptotic Significance < Profile depth 1 st depth 1 st skeleton 1 st sand 1 st silt 1 st clay 1 st CaCO 3 1 st OC 1 st nitrogen 2 nd depth 2 nd skeleton 2 nd sand 2 nd silt 2 nd clay 2 nd CaCO 3 2 nd OC 2 nd nitrogen 2 nd ph Fig. F.1: Frequency distribution of the regression residuals.

12 316 Table F.2: Highest bivariate correlation coefficient between residuals and the corresponding metric explaining variable and highest r² F value for the corresponding nominal explaining variable. 1 st layer 2 nd layer Highest Pearson r Corresponding Metric Co- Variable Highest r² F Corresponding Nominal Co- Variable Soil Depth [cm].7 x coordinate.21 Lithology (5) Depth [] <.1 elevation.43 Vegetation Skeleton [] -.12 DV (ZIM).61 PEN Sand [].91 elevation.89 Geochemical Type of Rock (5) Silt [].142 y coordinate.75 SHA Clay [] x coordinate.38 SCH Carbonate [].121 precip.33 Type of Rock (2) Organic Carbon [].174 precip.99 SHA Nitrogen [].125 precip.87 SHA Depth [] precip.39 Vegetation Skeleton [].5 DR (TWI).65 SHA Sand [].2 precip.99 SHA Silt [].21 precip.111 SHA Clay [].55 x coordinate.64 PEN Carbonate [] -.55 predicted 1 st CaCO Organic Carbon [].57 precip.8 Vegetation Nitrogen [].236 upslope area (mean).37 SCH ph.231 x coordinate.19 Vegetation n = 73 n = 41 n = 46 n = 49 n = 73 n = 41 n = 46 n = 49 n = 73 n = 4 n = 46 n = 5 Soil Depth 1 st Depth 1 st Stone n = 73 n = 4 n = 45 n = 5 1 st Sand -8 n = 73 n = 4 n = 45 n = 5 1 st Silt -4 n = 73 n = 4 n = 45 n = 5 1 st Clay Fig. F.2 - part I: Distribution of the residuals per biogeographic region.

13 n = 73 n = 4 n = 46 n = 5-2 n = 73 n = 4 n = 46 n = n = 73 n = 4 n = 46 n = 5 1 st CaCO 3 1 st OC 1 st Nitrogen n = 66 n = 39 n = 32 n = 46-6 n = 65 n = 38 n = 3 n = 45 n = 64 n = 38 n = 29 n = 45 2 nd Depth 2 nd Stone 2 nd Sand n = 73 n = 38 n = 29 n = 45-2 n = 73 n = 38 n = 29 n = 45-4 n = 65 n = 38 n = 3 n = 45 2 nd Silt 2 nd Clay 2 nd CaCO n = 65 n = 38 n = 29 n = n = 65 n = 38 n = 29 n = 45 n = 65 n = 38 n = 3 n = 45 2 nd OC 2 nd Nitrogen 2 nd ph Fig. F.2 - part II: Distribution of the residuals per biogeographic region.

14 n = 71 n = 4 n = 45 n = 5-5 n = 71 n = 4 n = 45 n = 5-1 n = 71 n = 4 n = 45 n = 5 1 st K s 1 st K s skeleton 1 st FC [] Fig. A-4.6.2: Distribution of the residuals per biogeographic region part II n = 71 n = 4 n = 45 n = 5-2 n = 71 n = 4 n = 45 n = 48-6 n = 71 n = 4 n = 45 n = 5 1 st FC [] skeleton 1 st FC [mm] skeleton 1 st PWP [] n = 71 n = 4 n = 45 n = 5-1 n = 71 n = 4 n = 45 n = 48-4 n = 71 n = 4 n = 45 n = 5 1 st PWP [] skeleton 1 st PWP [mm] skeleton 1 st AWC [] n = 71 n = 4 n = 45 n = 5-1 n = 71 n = 4 n = 45 n = 48 1 st AWC [] skeleton 1 st AWC [mm] skeleton Fig. F.3 - part I: Distribution of the residuals of soil hydraulic properties per biogeographic region.

15 n = 63 n = 38 n = 29 n = 45-1 n = 62 n = 38 n = 29 n = 45 2 nd K s 2 nd K s skeleton 2 nd FC [] -1 n = 63 n = 38 n = 29 n = n = 62 n = 38 n = 29 n = 45-2 n = 62 n = 38 n = 29 n = 43-1 n = 63 n = 38 n = 29 n = 45 2 nd FC [] skeleton 2 nd FC [mm] skeleton 2 nd PWP [] n = 62 n = 38 n = 29 n = 45-1 n = 62 n = 38 n = 29 n = 43-8 n = 63 n = 38 n = 29 n = 45 2 nd PWP [] skeleton 2 nd PWP [mm] skeleton 2 nd AWC [] n = 62 n = 38 n = 29 n = 45 2 nd AWC [] skeleton 2 nd AWC [mm] skeleton -1 n = 62 n = 38 n = 29 n = 43 Fig. F.3 - part II: Distribution of the residuals of soil hydraulic properties per biogeographic region.

16 32 Table F.3: Mean and Standard Deviation (SD) of the measured soil properties (all horizons) per biogeographic region. Mean SD Mean SD Mean SD Mean SD Soil Depth Horizon Deth Skeleton content Sand Silt Clay Carbonate Organic Carbon Nitrogen ph

17 Appendix G: Maps of soil properties Fig. G.1: Soil depth [cm]. 321

18 Fig. G.2: Depth of the first (left) and second (right) layer [cm]. 322

19 Fig. G.3: Skeleton content of the first (left) and second (right) layer []. 323

20 Fig. G.4: Texture of the first (left) and second (right) layer [US texture class]. 324

21 Fig. G.5: CaCO3 content of the first (left) and second (right) layer []. 325

22 Fig. G.6: Organic carbon content of the first (left) and second (right) layer []. 326

23 Fig. G.7: Nitrogen content of the first (left) and second (right) layer []. 327

24 Fig. G.8: ph value of the second layer. 328

25 Fig. G.9: Saturated hydraulic conductivity of the first (left) and second (right) layer [cm/d]. 329

26 Fig. G.1: Field capacity of the first (left) and second (right) layer []. 33

27 Fig. G.11: Field capacity of the first (left) and second (right) layer [mm]. 331

28 Fig. G.12: Permanent wilting point of the first (left) and second (right) layer []. 332

29 Fig. G.13: Permanent wilting point of the first (left) and second (right) layer [mm]. 333

30 334 Fig. G.14: Available water capacity of the first (left) and second (right) layer [].

31 Fig. G.15: Available water capacity of the first (left) and second (right) layer [mm]. 335

32 336 Fig. G.16: Maps of soil properties aggregated to 84 soil classes for the application in the SWAT model.

33 Appendix H: PESERA parameters and results Fig. H.1: Standard deviation of elevation in a radius of 3 km. 337

34 338 Fig. H.2: Soil sensitivity towards crusting.

35 Fig. H.3: Soil erodibility. 339

36 34 Fig. H.4: Effective soil water storage capacity.

37 Fig. H.5: Soil hydrological scale depth. 341

38 342 Fig. H.6: Land use classes for the PESERA model.

39 Fig. H.7: Sediment delivery ratio calculated from the DEM of the upper Drâa catchment. 343

40 344 Fig. H.8: Change in vegetation cover relative to the REMOref simulation modelled by PESERA under global change scenarios for the biogeographic regions (see fig. 3.13). Fig. H.9: Change in actual evapotranspiration relative to the REMOref simulation modelled by PESERA under global change scenarios for the biogeographic regions (see fig. 3.13).

41 345 Fig. H.1: Change in runoff relative to the REMOref simulation modelled by PESERA under global change scenarios for the biogeographic regions (see fig. 3.13). Fig. H.11: Change in groundwater recharge relative to the REMOref simulation modelled by PESERA under global change scenarios for the biogeographic regions (see fig. 3.13).

42 346 Fig. H.12: Change in erosion rate relative to the REMOref simulation modelled by PESERA under global change scenarios for the biogeographic regions (see fig. 3.13).