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(1)

The world in a grain of sand

Cornie van Huyssteen

The world in a grain of sand

Cornie van Huyssteen

(2)

Dedication

Dedication

My Lord and saviour

My family My mentors My colleagues My students

(3)

A grain of sand

A grain of sand

(4)

Humans classify their environment to: create order

make it more understandable aid recollection

communicate

Introduction

Introduction

(5)

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

Soil Classification

Soil Classification

(6)

Perceived hydrological order:

 red → driest

 yellow → intermediate  grey → wettest

Colour defined horizons

Colour defined horizons

dry wet red aped al B sof plin thic B yello w b row n ap edal B E ho rizon G h oriz on hem atite quar tz goet hite

(7)

Colour definitions

Colour definitions

Yellow Grey

(8)

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

Soil forms

Soil forms

(9)

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

(10)

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

(11)

Aerobic (oxidised)

Fe3+ coating Soil particle Quartz Fe3+

Anaerobic (reduced)

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

Fe determines colour

Fe determines colour

(12)

Fluvisol in Hungary (2011)

Fe determines colour

Fe determines colour

(13)

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

Reduction sequence

(14)

Stagnic colour pattern

Stagnic colour pattern

(15)

Stagnic colour pattern

Stagnic colour pattern

(16)

Stagnic colour pattern

Stagnic colour pattern

(17)

Stagnic colour pattern

Stagnic colour pattern

(18)

Gleyic colour pattern

Gleyic colour pattern

(19)

Gleyic colour pattern

Gleyic colour pattern

(20)

Munsell colour definitions

Munsell colour definitions

(21)

Weatherley

Weatherley

METHODOLOGY:

 28 profiles

• described in detail

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

 Neutron water meter measurements • weekly for six years (1997 - 2002)

(22)
(23)

Degree of water saturation (S

0.7

)

Degree of water saturation (S

0.7

)

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

(24)

AD

s>0.7

per horizon

AD

s>0.7

per horizon

re ne ye ot sp gs on gh 0 61 122 182 243 304 365 A D s> 0 .7 ( d a ys y e a r-1 ) red aped al B neoc utan ic B E h oriz ons Uns peci fied wet G h oriz ons yello w b row n ap edal B orth ic A soft plin thic B

(25)

Florisbad

Florisbad

Permanently dry Temporary wet Seasonally wet Permanently wet

0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 0.08 0.16 0.53 0.70 0.74 0.79 0.97 0.79 Top soil Wetland Zone D e gr e e o f w at er s a tu ra ti o n ( m 3 m 3 )

(26)

Florisbad

Florisbad

Permanently dry Temporary wet Seasonally wet Permanently wet 0 5 10 15 20 25 30 Top soil Wetland Zone rH rH = 2(Eh/59 + pH) Oxidised Reduced

(27)

 Hydropedology

 Wetland delineation • Urban development • Mining EIAs

 Irrigation scheduling  Water table soils

 Soil classification

Application

Application

(28)

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

Hydropedology

Hydropedology

(29)

Wetlands

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

(30)

Rift valley fever

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?

(31)

RVF sheep mortality (2010)

RVF sheep mortality (2010)

(32)

RFV study sites

RFV study sites

(33)

• – Location

• - Vector of dimension 3

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

• - Matrices • - Vectors • - Constants

• (1: Group 1 – Outbreak, 2: Group 2 – Control)  – Outbreak site

 – Control site

Prediction of RVF outbreak site

Prediction of RVF outbreak site

(34)

One Health

One Health

(35)

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.

RVF partners

RVF partners

(36)

 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

Iphakade at the UFS

Iphakade at the UFS

(37)

 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

Iphakade totals at UFS

Iphakade totals at UFS

(38)

The Future

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

(39)

The world

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

(40)

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

Conclusion

Conclusion

(41)

Thank you!

Thank you!

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