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C-MASC 2010 Visiting Scholars !

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C-MASC had the unique privilege to host 16 scholars from around the world in 2010. They shared their knowledge and experience with us and conducted research on themes of mutual interest. Upon return to their home institution, they continue to collaborate with C-MASC.!

ENR-671

Environmental Soil

Physics

Course Objectives

The course is designed to provide a comprehensive understanding of the relationships in

basic soil physics and its applications to environment quality and sustainable use of natural

resources. The syllabus meets the curriculum needs of students in Soil Science,

Environmental Sciences, Natural Resources, Agricultural Engineering, Horticulture and

Crop Sciences, Forestry, Geology, Climatology and Civil Engineering

Learning Outcomes

1. Gain a working understanding of soil’s physical, mechanical, hydrological and

rheological properties in relation to environment quality and sustainable

management of terrestrial ecosystems.

2. Learn applications of soil physical properties and processes will be discussed with

regards to the following special topics:

(i) Greenhouse effect, global C cycle, gaseous emissions and C sequestration,

(ii) wetland management, hypoxia, drainage, irrigation and salinity,

(iii) soil erosion, land degradation and food security,

(iv) biofuels and residue management, among others.

This course in designed for undergraduate and graduate students

There are no specific pre-requisites, please contact Dr. Lal for any questions.

Instructor

Dr. R. Lal

422B Kottman Hall

292-9069

lal.1@osu.edu

Winter 2011 Room # KH 333C

(5 credit hours) Lecture: M T W F

11am-11:48am

Lab: Th 10am-12pm

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###

Q\Q#

''''''

C-MASC Presentations for SSSA Meetings "Drs. A. Kadono, S. Kumar, K. Lorenz, R. Shrestha, and D.A.N. Ussiri #!

Modelling of Soil Organic Carbon Dynamics in Grassland and Agricultural Ecosystems in Ukraine!

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Predicting Spatial Distribution of Organic Carbon Pool In Soils of Ohio Using Four

Statistical Approaches  

Sandeep  Kumar,  Ohio  State  University,  Columbus,  OH    RaPan  Lal,  The  Ohio  State  University,  Columbus,  OH    

Desheng  Liu,  Department  of  Geography,  Ohio  State  University,  Columbus,  OH  

                   

Assessment  of  spaKal  variability  of  soil  organic  carbon  (SOC)  pool  at  state  and  regional   scale   is   constrained   by   extensive   soil   sampling.   A   wide   range   of  methods   and   tools   are   thus   used   to   esKmate   the   SOC   pool   at   these   scales.  Since,   SOC   is   influenced   by   different   environmental   and   anthropogenic  variables,  and  the  interacKon  among  them.  A  bePer  esKmaKon  of  SOC  pool  can  be  made   by   considering   the   relaKonship   among   these   variables   and   by   using  geographical   informaKon   systems   (GIS)   modeling   which   can   enhance   the  understanding  of  the  global  C  cycle.  Thus,  the  specific  objecKve  of  the  study  was  to   esKmate   the   SOC   density   (C   stock   per   unit   area)   to   1-­‐m   depth   for   soils   of  Ohio.   Four   predicKve   GIS   models   used   were:   ordinary   kriging   (OK),   mulKple  linear   regression   (MLR),   regression   kriging   (RK)   and   geographically   weighted  regression   (GWR).   AnalyKcal   data   for   a   total   of   1424   soil   profiles   were  extracted,   of   which   80%   were   used   for   calibraKon   and   20%   for   validaKon.   A  total   of   20   variables   (except   in   OK)   including   terrain   aPributes,   climate   data,  bedrock  geology,  and  land  use  data  were  used  for  esKmaKng  the  SOC  density.  Four  approaches  were  compared  and  observed   that   the  GWR  provided  bePer  predicKons  with   lowest   (3.81  kg  m-­‐2)   root  mean  square  error   (RMSE)   followed  by   RK   (3.85   kg   m-­‐2),   MLR   (3.90   kg   m-­‐2),   and   OK   (4.70   kg   m-­‐2).   The   relaKve  improvement   (RI)   values   showed   that   predicKons   with   GWR,   RK   and   MLR  approaches   were   79,   53,   and   49%   higher   compared   to   those   with   OK.   Total  esKmated  SOC  pool  for  soils  in  Ohio  ranged  from  727  to  742  Tg.  The  Data  show  that  GWR  approach,  a  local  spaKal  staKsKcal  technique,  enhances  the  precision  for   predicKng   the   SOC  pool   compared   to   other   global   spaKal   techniques   (e.g.  MLR  and  RK).          

…7…  

Apex Model Simulation of Runoff and Sediment Losses From Agroforestry Buffers for Watersheds Under

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Long-Term Land-Use Effects on Soil Organic Carbon Sequestration!

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Greenhouse Gas Emissions In a No-till Chronosequence!

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Upcoming Workshops!Recarbonization of the Biosphere !

20-22 March 2011 at IASS Potsdam, Germany!

ppp pR b i i f h Bi h

Q_RQ#

In Memoriam – "George Stanley Taylor!

Q_SQ#

George Stanley Taylor (1920-2010)!!

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