Team: Francisco Contreras, Carlos Lechuga and Martin Merino Objectives: 1) reproduce our previous best classification of the coasts of Mexico in terms.

Slides:

Advertisements

Similar presentations

BY PAT AND CONNOR INDIA. SIZE AND LAND USAGE Area: 3,287,263 sq. kilometers 7 th largest country in the world About 7,000 km of coastline Arable land.

Advertisements

Simone Bizzi In collaboration with: Dr Andrea Nardini Technical Director of CIRF (Italian Centre for River Restoration) Model and evaluate geomorphology.

Developing Modeling Tools in Support of Nutrient Reduction Policies Randy Mentz Adam Freihoefer, Trip Hook, & Theresa Nelson Water Quality Modeling Technical.

Carbon Monitoring of Agricultural Lands: Developing a Globally Consistent Estimate of Carbon Stocks and Fluxes Julie Wolf 1, Stephen Ogle 2 and Tris West.

Forecasting impact of climate change on runoff coefficient in Limpopo basin using ANN MARCH , 2004AF_42 DAKAR WORKSHOP WELCOME TO THE SECOND AIACC.

Dr. Martin T. Auer Michigan Tech Department of Civil & Environmental Engineering Surface Water Supply.

Dr. Martin T. Auer Michigan Tech Department of Civil & Environmental Engineering Surface Water Supply.

53rd ANNUAL MEETING OF THE ARIZONA-NEVADA ACADEMY OF SCIENCE UNIVERSITY OF ARIZONA TUCSON, AZ APRIL 4, rd ANNUAL MEETING OF THE ARIZONA-NEVADA ACADEMY.

Hydrologic Cycle and Watersheds. Hydrologic Cycle Components Precipitation Infiltration Percolation Runoff Evapotranspiration.

LOICZ II The next Generation of Global Coastal Change Science Land-Ocean interactions across multiple interfaces A core project of the International.

Presented by Jason Afinowicz Biological and Agricultural Engineering Department, Texas A&M University CVEN 689 Applications of GIS to Civil Engineering.

Estimating Global Inventory-Based Net Carbon Exchange from Agricultural Lands for Use in the NASA Flux Pilot Study Julie Wolf, Yannick Le Page and Tris.

What do you see in this image? How was this image taken?

Climatic variability, land-cover change, and forest hydrology in the Pacific Northwest David W. Peterson JISAO Climate Impacts Group Forest Hydrology.

Urban and rural areas An introduction. What is an urban area? built-up area.

What is Water Cycle? It is the flow/movement and storage of water in and between the atmosphere, the lithosphere, the hydrosphere & the biosphere It also.

The Important Big Book of The Regions of California Electronic Big Book Adaptation 2012 By Ms. Mary Ann Rechtfertig Previously Adapted by Melinda Rader.

Living Things and the Environment. ECOLOGYECOLOGYECOLOGYECOLOGY.

Hydrogeodesy: Can it help to reach the Millennium Development Goal for Water in Africa? Norman L. Miller IGCP 565 Fifth Annual Workshop October 2012.

Team: Andrea Claassen and Thomas Bales FR 5262, 12/13/2011 Instructor: Joe Knight.

Basso, B. and J. T. Ritchie Simulating crop growth and biogeochemical fluxes in response to land management using the SALUS model. Pages

Coasts Characteristics of US coastlines. Coastal Waters Classification of coastal waters Adjacent to land (to edge of continental shelf) Influenced by.

Unit 2: Cells Chapter 3: Cells, The Basic Units of Life Lesson 3.3: Organization of Life.

Flux tower representativeness >croplands< news from the workbench Martin Wattenbach Astley Hastings Pete Smith.

May 6, 2015 Huidae Cho Water Resources Engineer, Dewberry Consultants

TREND IN SALINITY OF THE WATERS OF THE CENTRAL- WEST-NORTH AFRICAN OCEANIC I ZONE (ZONE 12). (A PILOT STUDY) S. Duadze.

Biophysical and Socioeconomic Assessments: The LOICZ* Approach Liana Talaue-McManus Rosenstiel School of Marine and Atmospheric Science University of Miami.

Tides. Tides The rise and fall of the ocean water levels along the coast are called tides. The amount of water in the ocean doesn’t change but moves in.

EEA 2006 Accounts Update Tables. PART 1 Table 1.1: Classifying land cover and land cover change for land accounting.

LOICZVIEW clustering tool applied to the European North Atlantic coastal zone Linking typology clustering to river N and P loads to the NA Ocean The Hague,

New Mexico Pilot Study: Salt Creek and White Mountain Wilderness areas Prepared by: Ilias Kavouras, Vic Etyemezian, Jin Xu, Dave DuBois, Marc Pitchford.

Food Systems in the Coastal Zone: A LOICZ Perspective L. Talaue-McManus Rosenstiel School of Marine & Atmospheric Science University of Miami.

Bluff! A Game and Study Guide All In One!. Rules In turn, each team will be asked a question. Team members who know the answer will stand up. The other.

Basic Hydrology & Hydraulics: DES 601 Module 6 Regional Analysis.

Runoff Overview Tom Hopson.

Dr. Monia Santini University of Tuscia and CMCC CMCC Annual Meeting

California Water Briefing APRIL 2006 Department of Water Resources.

The Regions of California Electronic Big Book Adaptation 2012 By Ms. Mary Ann Rechtfertig and Laura Barnett Previously Adapted by Melinda Rader Modified.

Recent SeaWiFS view of the forest fires over Alaska Gene Feldman, NASA GSFC, Laboratory for Hydrospheric Processes, Office for Global Carbon Studies

Implementing Probabilistic Climate Outlooks within a Seasonal Hydrologic Forecast System Andy Wood and Dennis P. Lettenmaier Department of Civil and Environmental.

Geography Starter  Use the chart on page 110 to answer the following questions: 1. What is the literacy rate for the USA? 2. What is the population of.

California Geologic Regions and Hazards: Follow-Up Presentation Created by the Natomas High School / Inderkum High School Science Lesson Study Team 2005.

Georgia Agricultural Curriculum Office June 2011.

HOW DOES THE LAND- BASED PORTION OF THE HYDROLOGIC CYCLE WORK?

HOW DOES THE LAND- BASED PORTION OF THE HYDROLOGIC CYCLE WORK?

Organisms and Their Environment. What is Ecology? Ecology is the study of interactions among organisms and their environments Ecologists study relationships.

Chapter 9, Section 5 Ocean Resources LT: I will describe how humans use resources from the ocean and how humans impact the ocean.

The Natural Regions of Texas

'. \s\s I. '.. '... · \ \ \,, I.

Investigating Environments

Biochemistry: Water Part 1

Ch. 8 Estimating with Confidence

Nueces River Basin By Jason Jenkins.

GIS Aspect We used GIS to extract the watershed basin we were going to focus on so that we could obtain the NLCD landcover data for the catchments the.

U.S. GEOGRAPHY.

Watersheds and Drainage Basins

ચાલો માટી વિશે જાણીએ All About Soil.

Biochemistry: Water Part 1

Classification Vocab.

' '· \ ·' ,,,,

To what extent are the water and carbon cycles linked?

Population and Community 3rd Grade Science – SOL 3.6

Biochemistry: Water Part 1

To what extent are the water and carbon cycles linked?

Biochemistry: Water Part 1

Sustainable use of ecosystem services in Europe’s regions

Linking typology clustering to river N and P loads to the NA Ocean

Biochemistry: Water Part 1

Biochemistry: Water Part 1

Presentation transcript:

Team: Francisco Contreras, Carlos Lechuga and Martin Merino Objectives: 1) reproduce our previous best classification of the coasts of Mexico in terms of LOICZ’s objectives 2) try it with the world coastline

We chose three kind of proxies and the parameters that could work for each case: As runoff proxies:Precip, ann mean Runoff, annual mean * Basin Runoff Soil Carbonate C, As geomorphic proxies: CZ Bath/Elev, std dev of SS2 value Ocean Bath, mean SS2 value Land Elev, mean G30 value Land Elev, std dev of G30 values * Cell Landcover, % Water Basin Landcover, % Water As C, N, P, flux proxies: Soil Organic C, Cell Landcover, % Cropland * Cell Landcover, % Grassland Cell Landcover, % Urban and Built-up Population, 30' cell total Basin Landcover, % Cropland Basin Landcover, % Grassland Basin Landcover, % Urban and Built-up Basin Population

Results: 1) We could get a typology that reproduces our previous classification target 2) However, variability was still present within our types, as most were represented by cells of two clusters

Cluster:Cluster 0: low STDDEV_G30VALUE, low RUNOFF_TOTAL_ANN, low CELL_PERCNT_CROPLAND Cluster 1: high STDDEV_G30VALUE, low RUNOFF_TOTAL_ANN Cluster 2: medium CELL_PERCNT_CROPLAND, low RUNOFF_TOTAL_ANN ValueStd Dev% PopulatedValueStd Dev% PopulatedValueStd Dev% Populated Archetype Point: Points Per Cluster: STDDEV_G30VALUE: RUNOFF_TOTAL_ANN: CELL_PERCNT_CROPLAND: Cluster:Cluster 3: low RUNOFF_TOTAL_ANN, low CELL_PERCNT_CROPLAND Cluster 4: medium STDDEV_G30VALUE, low RUNOFF_TOTAL_ANN, low CELL_PERCNT_CROPLAND Cluster 5: medium RUNOFF_TOTAL_ANN, low CELL_PERCNT_CROPLAND ValueStd Dev% PopulatedValueStd Dev% PopulatedValueStd Dev% Populated Archetype Point: Points Per Cluster: STDDEV_G30VALUE: RUNOFF_TOTAL_ANN: CELL_PERCNT_CROPLAND: Cluster:Cluster 6: high CELL_PERCNT_CROPLAND, low RUNOFF_TOTAL_ANN Cluster 7: high RUNOFF_TOTAL_ANN Cluster 8: low CELL_PERCNT_CROPLAND, low RUNOFF_TOTAL_ANN ValueStd Dev% PopulatedValueStd Dev% PopulatedValueStd Dev% Populated Archetype Point: Points Per Cluster: STDDEV_G30VALUE: RUNOFF_TOTAL_ANN: CELL_PERCNT_CROPLAND: Cluster:Cluster 9: low STDDEV_G30VALUE, low RUNOFF_TOTAL_ANN, low CELL_PERCNT_CROPLAND ValueStd Dev% Populated Archetype Point: Points Per Cluster: STDDEV_G30VALUE: RUNOFF_TOTAL_ANN: CELL_PERCNT_CROPLAND: Entire Set ValueStd DevMinMax Archetype Point: Points Per Cluster: STDDEV_G30VALUE: RUNOFF_TOTAL_ANN: CELL_PERCNT_CROPLAND: