Andrea S. Kishné, Cristine L. S. Morgan

Slides:



Advertisements
Similar presentations
Monitoring soil mineral nitrogen concentration in Germany: Preliminary results and some methodical challenges P. Schweigert* and R.R. van der Ploeg Institute.
Advertisements

The Effects of Site and Soil on Fertilizer Response of Coastal Douglas-fir K.M. Littke, R.B. Harrison, and D.G. Briggs University of Washington Coast Fertilization.
Quantifying soil carbon and nitrogen under different types of vegetation cover using near infrared-spectroscopy: a case study from India J. Dinakaran*and.
Nitrogen and Biomass Content, and Nitrogen and Water Uptake Parameters of Citrus Grown on Sandy Soils in Central Florida Ph.D. Exit Seminar Soil and Water.
Scaling and Assimilation of Soil Moisture and Streamflow (SASMAS): project overview and preliminary results G Willgoose (U. Leeds, UK), H Hemakumara (U.
Development of Remote Sensing-based Predictive Models for the Management of Taste and Odor Events in Kansas Reservoirs Dr. Mark Jakubauskas Kansas Biological.
Pollinator Diversity in a Bunchgrass Prairie Melissa McKenney Dr. Sujaya Rao, Dept. Crop and Soil Science Dr. Sandy DeBano, Dept. Fish and Wildlife.
Soil-mediated effects of a CO 2 gradient on grassland productivity: Interactions with resources and species change. Philip A. Fay USDA-ARS Grassland, Soil,
Alberta Rainfall-Runoff Analysis September, 2002.
EXAMPLE 2 Interpret a box-and-whisker plot PRECIPITATION The box-and-whisker plots below show the normal precipitation (in inches) each month in Dallas.
Aim: How to Read a Topographic Map
Assessment of Flow Paths in Upland Areas and Vegetated Buffers August 2, 2004 I.J. Kim, S.L. Hutchinson, and J.M.S. Hutchinson* The department of Biological.
Effects of hillslope terracing on productivity and soil properties in semi-arid Ponderosa Pine habitat in Western Montana L. Cerise¹ ², D.S. Page-Dumroese¹,
Identifying Soil Types using Soil moisture data CVEN 689 BY Uday Sant April 26, 2004.
N ON- P OINT S OURCE P OLLUTION Analysis and Prediction in ArcView David Munn Texas A&M University/Dept. of Civil Engineering CVEN 689 Applications of.
Flood Forecasting February 11th, 2015
Geog 100 Themes in World Geography Dr. Julie Cidell Fall 2004 Section 7.
Evapotranspiration Controllers in Florida
PALMS: Precision Agricultural-Landscape Modeling System Precision modeling to provide decision support for farmers PALMS is software designed to provide.
Economic Cooperation Organization Training Course on “Drought and Desertification” Alanya Facilities, Antalya, TURKEY presented by Ertan TURGU from Turkish.
Validation of AMSR-E Soil Moisture Estimation in Mongolia and A Renewal Plan of Ground-based Monitoring Instruments Ichirow Kaihotsu (Hiroshima University)
Jaco van der Gaast The Winand Staring Centre, P.O. Box 125, 6700 AC Wageningen, The Netherlands 1 Water Management Tools Jaco van der Gaast The Winand.
Initial Results on Soil Quality by Victor B. Ella Professor, UPLB
A Statistical Comparison of Weather Stations in Carberry, Manitoba, Canada.
Effects of various soil amendments on soil test P values David Brauer, Glen Aiken, Dan Pote ARS/USDA, Booneville AR S.J. Livingston, L.D. Norton ARS/USDA,
Digital Terrain Analysis and Simulation Modeling to Assess Spatial Variability of Soil Water Balance B. Basso J.T. Ritchie J.C. Gallant Dipartimento di.
Assessment of Hydrology of Bhutan What would be the impacts of changes in agriculture (including irrigation) and forestry practices on local and regional.
Consideration of Drainage Ditches and Sediment Rating Curve on SWAT Model Performance A.M. Sadeghi *1, A.M. Sexton 1, G.W. McCarty 1, M.W. Lang 3,1, W.D.
An Application of Field Monitoring Data in Estimating Optimal Planting Dates of Cassava in Upper Paddy Field in Northeast Thailand Meeting Notes.
Evaluation of climate change impact on soil and snow processes in small watersheds of European part of Russia using various scenarios of climate Lebedeva.
The University of Mississippi Geoinformatics Center NASA MRC RPC – 11 July 2007 Greg Easson, Ph.D. Robert Holt, Ph.D. A. K. M. Azad Hossain University.
Effects of Forest Management Practices on Carbon Storage Coeli M. Hoover USDA Forest Service, Northern Research Station Forest PLUS, Washington DC December.
Results of Long-Term Experiments With Conservation Tillage in Austria Introduction On-site and off-site damages of soil erosion cause serious problems.
Understanding Hydro-geochemical Process Coupling at the Susquehanna Shale Hills Critical Zone Observatory (SSHCZO) Using RT-Flux-PIHM: an integrated hydrological-reactive.
Travis D. Miller Department of Soil and Crop Sciences Texas AgriLife Extension Service The 2011 drought situation: July, 2011 Travis D. Miller Professor,
2013 NUE Conference Des Moines, Iowa August 5-7 Jacob T. Bushong.
Remote sensing for surface water hydrology RS applications for assessment of hydrometeorological states and fluxes –Soil moisture, snow cover, snow water.
Using GIS to estimate the volume of snow and water in a drainage basin Todd Rayne and Dave Tewksbury Hamilton College Clinton, New York.
DRAINMOD APPLICATION ABE 527 Computer Models in Environmental and Natural Resources.
Measuring Soil Bulk Density by Using Vibration-induced Conductivity Fluctuation A. Sz. Kishné, C. L.S. Morgan Dept. of Soil and Crop Sciences, Texas A&M.
Spatial interpolation of Daily temperatures using an advection scheme Kwang Soo Kim.
ELECTRICAL RESISTIVITY SOUNDING TO STUDY WATER CONTENT DISTRIBUTION IN HETEROGENEOUS SOILS 1 University of Maryland, College Park MD; 2 BA/ANRI/EMSL, USDA-ARS,
Climate Sensitivity of Thinleaf Alder Growth in Interior Alaska: Implications for N-Fixation Inputs to River Floodplains Dana Nossov 1,2, Roger Ruess 1,
ESTIMATING EARTHWORK DR. Nabil Dmaidi.
WP coordinator meeting June 17/ WP3 progress report.
Modeling CO 2 emissions in Prairie Pothole Region using DNDC model and remotely sensed data Zhengpeng Li 1, Shuguang Liu 2, Robert Gleason 3, Zhengxi Tan.
Impact of the changes of prescribed fire emissions on regional air quality from 2002 to 2050 in the southeastern United States Tao Zeng 1,3, Yuhang Wang.
Treatment Plots Plot conditions for treatments studied at time of sampling. Bole-only without vegetation control BO-VC Total Tree Plus with vegetation.
P B Hunukumbura1 S B Weerakoon1
Ground-based energy flux measurements for calibration of the Advanced Thermal and Land Application Sensor (ATLAS) 1 Eric W. Harmsen and Richard Díaz Román,
1. Session Goals 2 __________________________________________ FAMINE EARLY WARNING SYSTEMS NETWORK Understand use of the terms climatology and variability.
Temporal and Spatial Influences of Juglands nigra and Gleditsia triacanthos on Soil Indicators in a Southern Appalachian Silvopasture Study Area By Scott.
Geospatial Hydrology Group
Mapping Variations in Crop Growth Using Satellite Data
Term Project Presentation
AIM AIM point-scale plot-scale hillslope-scale
An Integrated Approach for Subsidence Monitoring and Sinkhole Formation in the Karst Terrain of Dougherty County, Georgia Matthew Cahalan1 and Adam Milewski1.
What is Conservation Agriculture ?
Distribution and characterization of soil organic carbon under different ecosystems of Red and Laterite zone of West Bengal  P. K. Patra, Sajal Saha*,
Height and Pressure Test for Improving Spray Application
Qing Zhu1, Henry Lin1, Xiaobo Zhou1, J.A. Doolittle2 and Jun Zhang1
Anticipating Impacts of AWM Interventions
C. Kallenbach1. , W. Horwath1, Z. Kabir1, J. Mitchell2, D
Jili Qu Department of Environmental and Architectural College
Analysis of influencing factors on Budyko parameter and the application of Budyko framework in future runoff change projection EGU Weiguang Wang.
Using GIS to Evaluate Water-Level Changes in Gillespie, Co. Texas:
Impact of prolonged soil moisture deficit on grassland biomass production John Hottenstein Mentors: Susan Moran, USDA – Agricultural Research Service Guillermo.
University of Washington Center for Science in the Earth System
Using Soil Moisture and Matric Potential Observations to Identify Subsurface Convergent Flow Pathways Qing Zhu, Henry Lin, and Xiaobo Zhou Dept . Crop.
Infrastructure planning and management
Presentation transcript:

Spatial and Temporal Changes of Crack Formation of a Vertisol in the Texas Gulf Coast Prairie Andrea S. Kishné, Cristine L. S. Morgan Dept. Soil & Crop Sciences Texas A&M University, TX,USA Wesley L. Miller USDA Natural Resources Conservation Service, Victoria,TX,USA

Research Objectives Overall objective: Quantify soil cracking processes to improve landscape hydrology models and USDA classification of Vertisols Specific objective: Analyze the relationships among microtopography, soil moisture, and spatial, temporal variation of crack patterns in a Vertisol on the Texas Gulf Coast Prairie. Houston Victoria Study site

Piezometers Laewest Fine, smectitic, hyperthermic Typic Hapluderts Soil moisture samples: @ 10, 25, 50, 75 & 100 cm depth

Scanned and Rectified Study period: 1989 - 1998 42 crack diagrams Scanning with 157 pixels/cm 18 dates of soil moisture Elevation measurements 10 m Crack width categories, cm ≤ 0.5 0.5 ≤ 1.0 1.0 ≤ 2.0 2.0 ≤ 5.0 5.0 ≤ 7.0 10 m 10 m 10 m

Digitized Crack width categories, cm ≤ 0.5 0.5 ≤ 1.0 1.0 ≤ 2.0 ≤ 0.5 0.5 ≤ 1.0 1.0 ≤ 2.0 2.0 ≤ 5.0 5 .0 ≤ 7.0 10 m

Crack Area Density for 100 m2 Below normal yearly precipitation Normal yearly precipitation 0.02 Above normal yearly precipitation Area density m2 m-2 0.01 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 Total Crack Area Density for 100 m2 over Time

Digital Elevation Model Discretized thin plate spline Cell size: 5 cm RMSE: 1.3 mm, n=148 Contours 12.40 m 12.35 m 12.30 m 12.25 m 12.20 m Calcareous puff 10 m

Slope 9 – 17 % 7 – 9 % 5 – 7 % 3 – 5 % 0 – 3 % Contours 12.20 m

Microhigh (38%) Microslope (43 %) Microlow (19 %) Contours, m 12.40 12.35 12.30 12.25 12.20 10 m

Polylines Clipped by Micro-topo

Crack Area Density Micro-highs Microhighs Microslopes Microlows 0.05 Area density m2 m-2 0.03 Indicates month of July 0.01 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998

Micro-topography Crack Area 3.0 Microhighs 0.12 Microslopes Crack area m2 2.0 Microlows 0.08 1.0 0.04 1 10 20 1 10 20 30 40 Sorted by Total Crack Area

Crack Density vs. Moisture Content 2 0.04 0-10 cm Micro-highs N = 18 Micro-lows Line density m m-2 1 Area density m2 m-2 0.02 0.15 0.30 0.45 0.15 0.30 0.45 Moisture content, kg kg-1

Monitoring Line Density Increased Decreased Unchanged 10 m Line density (m m-2) on 06/02/98 Line density (m m-2) on 07/20/98

Conclusions 1. Crack development starts on microhighs. 2. Crack density is greater on microhighs than on microlows at the same soil moisture content. 3. In 1998 crack density increased on micro-highs and decreased on microslopes and microlows.

Current Research Analyze crack width and depth relationship to model crack volume Develop empirical model between daily PET and crack development Evaluate criteria of cumulative open crack periods in normal precipitation years for Usterts and Uderts in Soil Taxonomy Compare the cracking sub-model of process-based landscape model to the measured crack data

Acknowledgements USDA-Natural Resources Conservation Service Texas Agricultural Experiment Station Dr. Raghavan Srinivasan and Todd Snelgrove at the Texas A & M University Spatial Sciences Laboratory