The world in a grain of sand

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The world in a grain of sand

Cornie van Huyssteen

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Dedication

My Lord and saviour My family

My mentors My colleagues My students

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A grain of sand

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Humans classify their environment to: create order

make it more understandable aid recollection

communicate

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International systems:

§ USDA Soil Taxonomy

§ World Reference Base for Soil Resources

National system:

§ Soil Classification: A Taxonomic System for South Africa

• Colour defined horizons: – grey E horizon

– yellow brown apedal B horizon – red apedal B horizon

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Perceived hydrological order:

§ red → driest

§ yellow → intermediate

§ grey → wettest

Colour defined horizons

dry wet red aped al B soft plin thic B yello w b row n ap edal B E ho rizon G hor izon hem atite qua rtz goet hite

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Colour definitions

Yellow Grey

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P204 (Longlands) P226 (Kroonstad) P210 (Bloemdal)

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Aerobic respiration CO₂ + 4e- _{+ 4H}+ CH₂O + H₂O O₂ + 4e- _{+ 4H}+ 2 H₂O energy organic matter

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Anaerobic respiration CO₂ + 4e- _{+ 4H}+ CH₂O + H₂O Fe₂O₃ + 2e- _{+ 6H}+ 2Fe2+ _{+ 3H} 2O less energy (insoluble) (soluble) organic matter

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Aerobic (oxidised)

Fe3+ _coating Soil particle Quartz Fe3+

Anaerobic (reduced)

Soil particle Fe2+ Fe2+ Fe2+ Fe2+ Fe2+

Fe determines colour

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Fluvisol in Hungary (2011)

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Oxygen reduction 4e- _{+ 4H}+ _{+ O} 2 ↔ 2H2O (+500 mV) Denitrification 10e- _{+ 12H}+ _{+ 2NO} 3- ↔ N2 + 6H2O (+350 mV) Manganese reduction 2e- _{+ 4H}+ _{+ MnO} 2 ↔ Mn2+ + 2H2O (+300 mV) Iron reduction 2e- _{+ 6H}+ _{+ Fe} 2O3 ↔ 2Fe2+ + 3H2O (+200 mV) Sulphate reduction 8e- _{+ 10H}+ _{+ SO} 42- ↔ H2S + 4H2O (-75 mV)

Swamp gas production

8e- _{+ 8H}+ _{+ CO} 2 ↔ CH4 + 2H2O (-185 mV) H₂ formation 2e- _{+ 2H}+ _{↔ H} 2 (-185 mV)

Reduction sequence

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Stagnic colour pattern

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Stagnic colour pattern

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Stagnic colour pattern

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Gleyic colour pattern

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Munsell colour definitions

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Weatherley

METHODOLOGY:

§ 28 profiles

• described in detail

• sampled & analysed in 100 mm intervals • bulk density & porosity

§ Neutron water meter measurements

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Degree of water saturation (S

_0.7

)

Air 10 % Water 90 % Air 30 % 70 % Water Air Water 20 % 80 %

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AD

_s>0.7

per horizon

0 61 122 182 243 304 365 re ne ye ot sp gs on gh AD s> 0 .7 (d ay s ye ar -1 ) red apedal B neoc utani cB E ho rizon s Unsp ecifi ed we t G ho rizon s yello w b row n apedal B orthi c A soft plint hic B

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Florisbad

0,08 0,16 0,53 0,70 0,74 0,79 0,97 0,79 0,0 0,1 0,2 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0

Permanently dry Temporary wet Seasonally wet Permanently wet

Degr ee of w at er sa tu ra tio n (m 3 m 3 ) Wetland Zone Topsoil Subsoil

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Florisbad

0 5 10 15 20 25 30

Permanently dry Temporary wet Seasonally wet Permanently wet

rH Wetland Zone Topsoil Subsoil rH = 2(Eh/59 + pH) Oxidised Reduced

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§ Hydropedology

§ Wetland delineation

• Urban development • Mining EIAs

§ Irrigation scheduling

§ Water table soils

§ Soil classification

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Midslope Footslope Valley bottom Hu We Ka A Midslope Valley bottom Footslope Hu We Ka B

Hydropedology

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Wetlands

§ Saturated with water in growing season

• Determines vegetation type

• Leads to distinct soil morphology – Termed redox morphology

• Evidence of saturation in rooting depth – Grey soil matrix colours

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Rift valley fever

Viral zoonotic disease

Affects domestic and wild animals and humans Outbreaks every ca. 10 years

§ Aligned to rainfall cycle?

Transmitted by infected Aedes mosquitos

High abortion and mortality rates in livestock Virus estivates in mosquito larvae in wetlands?

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§ !_"#(%_&) = −2 + %_&,-_"%_& + %_&,/_" + 0_" • 1 – Location

• %_& - Vector of dimension 3

– log (sol. Ca), square root (exch. K), square root (med. sand) – From stepwise procedure

• -_" - Matrices

• /_" - Vectors

• 0_" - Constants

• 2 = 1,2 (1: Group 1 – Outbreak, 2: Group 2 – Control)

§ !₅#(%_&) > !_##(%_&) – Outbreak site

§ !₅#_(%

&) < !##(%&) – Control site

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This project is sponsored by the U.S. Department of Defense, Defense Threat Reduction Agency. The content of the information does not necessarily reflect the position or the policy of the federal government, and no official endorsement should be inferred.

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§ Since 2009

§ Initiated at UFS by Marian Tredoux

§ Initially collaboration between Germany & SA

§ Funded in SA by DST

§ Administrated by Prof. Maarten de Witt (NMU)

§ Disbursed to various university collaborators

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§ ca. R14 100 000 over 10 years

§ 6 Departments

§ 17 Lecturers

§ 180 students

§ Focus on Hons., M.Sc. & Ph.D. students

§ Approximately:

• 50% black; 50% white • 40% female; 60% male

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The Future

• To propose ancillary criteria to relate SAT to WRB • To modify SAT diagnostics to better relate to WRB • To propose morphological diagnostics for the WRB

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The world

Wageningen 1995 Yakutsk 2013 Rome 2013 Florianapolis 2013 Texas A&M 2012 Lincoln 2012 Potsdam 2012 _Wroclaw 2011 Brisbane 2010 Trondheim 2010 Gödöllő 2010 Santiago 2008 State College 2006 Philadelphia 2006 Petrosavodsk 2004 Walvis Bay 2002 San Diego 1998 Rio 2018 Torun 2018 Blacksburg 2018 Tallinn 2017 Minneapolis 2015 Jeju 2014 Wexford 2014 Ulm 2013 Cluj 2018

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Soil colour:

§ reflects soil hydrology

§ can therefore be used to infer water behaviour

§ applied in:

• hydropedology

• wetland delineation • irrigation scheduling • water table soils

• soil classification

Must be willing to see the world in a grain of sand

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