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Relationships Be1ween Climatic Indices and Soil

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Relationships Be1ween Climatic Indices and Soil RELATIONSHIPS BE1WEEN CLIMATIC INDICES AND SOIL PROPERTIES THAT REFLECT LEACHING AND WEATHERING IN THE NATAL MIDLANDS, AND THEIR USE IN THE ASSESSMENT OF AFFORESTATION POTENTIAL MICHAEL JOHN DONKIN Submitted in partial fulfilment of the requirements for the degr~e of Doctor of Philosophy in the Department of Agronomy, Faculty of Agriculture, University of Natal Department of Agronomy Faculty of Agriculture University of Natal Pietermaritzburg December 1991 The exclusion of the monovalent cations from the calculation of ECEC enabled an even better fit of the data. ECEC may be used to estimate MAER on well-drained sites, but, on the basis of a case study involving Acacia mearnsii, ECEC does not necessarily provide an estimation of the site index for timber, since tree growth is also dependent upon many other factors, the more so when rainfall is not limiting. ECEC is recommended as a replacement for the S-value in the South African soil classification. For well-drained soils, ECEC is highly related to climatic indices, is less susceptible to seasonal change or change by land-use practices, and it is strongly covariant with many soil properties. Its use would bring about better alignment of the South African system with other soil classifications. III DECLARATION I wish to certify that the work reported in this thesis is my own original and unaided work except where specific acknowledgement is made. Portions of this thesis have already been published as papers in the scientific literature in a form somewhat different to the form in which they are presented here. These papers are: Donkin, MoJ., 1989. The base status of soils for assessing afforestation potential: a preliminary appraisal. Proc. 9th Site and Nutrition Working Group, Sabie, May 1989, 38- 45. Donkin, MoJ. and Schulze, RoE., 1990. The determination of afforestation potential from soil property - climate relationships: I. The use of an agrohydrological model in the quantification of climate as a soil-forming factor. S. Afr. J Plant Soil, 7(4): 230-235. Donkin, MoJ. and Fey, M.V., 1991. Factor analysis of familiar properties of some Natal soils with potential for afforestation. Geoderma 48: 297-304. This thesis has not been submitted for a degree in any other university. Signed: MICHAEL JOHN nONKIN iv List of Terms and Abbreviations ACRU An agrohydrological water-budgeting model developed by the Agricultural Catchments Research Unit, Department of Agricultural Engineering, University of Natal, Pietermaritzburg. CCWR Computing Centre for Water Research CEC Cation Exchange Capacity Climofunction A functional relationship between soil properties and 'climate (Jenny, 1941). Climosequence A set of soils that differ, one from another, in certain properties as a result of climate as a soil-forming factor (Jenny, 1941). Centimoles of electrostatic charge EC Electrical conductivity ECEC Effective Cation Exchange Capacity (sum of the exchangeable bases and exchangeable acidity) EGME Ethylene glycol monoethyl ether ICFR Institute for Commercial Forestry Research, University of Natal, Pietermaritzburg. MAER Mean annual effective rainfall MAD [] Mean annual drainage [out of the B1 horizon, or the 50cm depth, as specified in square brackets] MAP Mean annual precipitation (refers to all forms of precipitation including hail and snow, and not only rainfall) S-value Sum of the exchangeable basic cations Ca2+, Mg2+, K+, Na+. SSA Specific surface area (m 2 g-l) v List of Figures and Maps Page 1 Map of the Natal midlands showing the location of sites used in the climosequence. ................ .......................... 60 2 The ACRU-2 agrohydrological modelling system: general structure (after Schulze, 1989). 63 3 Mean soil water drainage with respect to soil depth at four sites in the Natal midlands. ........................................... 68 4 Relationship between MAP and MAER for 33 sites in the Natal midlands. 69 5 Relationship between mean annual precipitation and mean annual drainage out of the B1 horizon for 33 sites in the Natal midlands. ..... 70 6 Plot of the general relationship between the degree of weathering and the degree of leaching, with the superimposed silica:sesquioxide ratio line (adapted from Crompton, 1960), for freely drained soils with limited influence of mar humus (after Young, 1976, p.74). .......... ...... 79 7 Plot of an index of the degree of leaching (S-value per unit mass of clay), against an index of the degree of weathering (silica:alumina ratio of the clay fraction, relative to the original ratio in the parent material). 93 8 The relationship between MAP and the S-value per unit mass of clay for B1 samples from 33 sites in the Natal midlands. 98 9 The relationship between MAER and the S-value per unit mass of clay for B1 samples from 33 sites in the Natal midlands. .. 100 10 The relationship between MAER and the S-value per unit mass of clay for B1 samples from 33 sites in the Natal midlands, stratified according to lithology of the parent material. .. 101 11 The relationship between MAER and exchangeable Ca2+ + Mg2 + per unit mass of clay for B1 samples from 33 sites in the Natal midlands. ... .. 103 12 The relationship between MAER and exchangeable Ca2++ Mg2 + per unit mass of soil for B1 samples from 33 sites in the Natal midlands. .. 104 13 The relationship between MAER and exchangeable Ca2+ + Mg2+ per unit mass of soil for B1 samples from 33 sites in the Natal midlands, stratified according to lithology of the parent material. ..................... 108 VI 14 The relationship between base saturation and loge(S-value per unit mass of clay) for B1 samples from 33 Natal midlands sites. .. 110 15 The relationship between MAER and base saturation for B 1 samples from 33 sites in the Natal midlands. ................................ 112 16 Base saturation versus dibasic cation saturation index for 33 B1 soils sampled at sites in the Natal midlands. .. 113 17 The relationship between MAER and dibasic cation saturation for B1 samples from 33 sites in the Natal midlands. ..................... 114 18 The relationship between MAER and pH (1M KCI) for B1 samples from 33 sites in the Natal midlands. ................................ 120 19 Relationship between cation exchange capacity of the clay fraction and mean annual rainfall for soils formed upon basalt in the Golan, Israel (after Singer, 1966). .. 124 20 The relationship between MAER and ECEC for B1 samples from 33 sites in the Natal midlands. ...................................... 126 21 Relationship between MAER and Sum of exchangeable Ca2+ + Mg2+ + acidity per unit mass of soil for B1 samples from 33 sites in the Natal midlands. .. 127 22 Relationship between MAER and Sum of exchangeable Ca2+ + Mg2+ + acidity per unit mass of soil for B1 samples from 33 sites in the Natal midlands, stratified according to lithology of the parent material. ...... 129 23 The relationship between MAER and pH4Si04 (H20) and pH4Si04 (CaCl2)· . .. 134 24 The relationship between MAER and the Si02:Al20iclay)/ Si02:Al20 3(parent material) for B1 samples from 33 sites in the Natal midlands. ............................................. " 141 25 Site index of A.mearnsii versus Sum of exchangeable Ca2+ + Mg2+ + acidity for the 80 sites with apedal chromic subsoils. .. 152 26 Site index of A.mearnsii versus Sum of exchangeable Ca2+ + Mg2+ + acidity for the restricted set of 38 sites without deep humic topsoils or diagnostic horizons signifying wetness. .......................... 153 Vll List of Tables Page 1 Degrees of leaching in upland soils, in terms of chemical properties of their B2 horizons (van der Eyk, 1965b). ....................... 44 2 A summary of sites selected in the Natal midlands. ................ 58 3 Summary of the three groups of soils used for factor analysis. 82 4 Factor analysis results showing the relative loadings of variables on 5 factors derived by varimax rotation for soil sets from Comrie, Natal midlands A horizons, and Natal midlands Bl horizons, respectively. .... 84 5 Factor analysis results showing the relative loadings of variables on 5 factors derived by varimax rotation for B2 horizon soils from the Tugela basin study. .............................................. 86 6 Factor analysis results showing the relative loadings of variables on 5 factors derived by varimax rotation for Bl soil samples taken from well- drained sites from around the Natal midlands. ...... ............. 92 Vlll ACKNOWLEDGEMENTS I wish to thank the following people and organisations: Prof. Martin Fey, Department of Agronomy, Pietermaritzburg, my supervisor, for his interest, encouragement, stimulating discussions and critical appraisals of the work. The Institute for Commercial Forestry Research (ICFR), its patrons and its staff for support for this research project. In particular I wish to thank Prof. Peter Roberts for his backing, and those persons who helped me in the laboratory: Jill Pearce, Carol Cameron, Michael Chetty, Mary Galbraith, Sally Schwabe and Neill Cameron. The interest of Dave Garbutt and the polemical discussions of Colin Smith have been invaluable. Prof. Roland Schulze, Department of Agricultural Engineering, for permission to use ACRU, an agrohydrological water-budgeting model developed by the Agricultural Catchments Research Unit, and for his valuable help in this regard. In addition, Dr. Mark Dent and staff of the Computing Centre for Water Research (CCWR), are thanked for the invaluable service that their organisation provides. The staff of the Department of Agronomy are thanked for their
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