Using MODIS Land-Use/Land-Cover Data and Hydrological Modeling for Estimating Nutrient Concentrations - Vladimir J. Alarcon, William McAnally, Gary Ervin, Christopher Brooks
Using MODIS Land-Use/Land-Cover Data and Hydrological Modeling for Estimating Nutrient Concentrations - Vladimir J. Alarcon, William McAnally, Gary Ervin, Christopher Brooks
Presented at the 12th AGILE International Conference on Geographic Information Science
Abdulhakim Abdi and Anand Nandipati
http://www.geospatialtechnologist.com/
Mosnier - Impacts of improved transportation infrastructure on agricultural s...CIALCA
Presentation delivered at the CIALCA international conference 'Challenges and Opportunities to the agricultural intensification of the humid highland systems of sub-Saharan Africa'. Kigali, Rwanda, October 24-27 2011.
Assessment of Spatial and Temporal Variations of Soil Salinity using Remote S...Hamdi Zurqani
“The aim of this paper is to identify the change in saline soils (Sebkha) using Remote Sensing (RS) and geographic information system (GIS) techniques”.
Chemical and spectroscopy of peat from West and Central Kalimantan, Indonesia...Agriculture Journal IJOEAR
Abstract— Improving peat soil is difficult but not impossible. Managed correctly, peat can be a highly productive medium for agriculture, but drainage and cultivation can lead to irreversible peat shrinkage. Vegetational changes during the restoration of cutover peatlands leave a legacy in terms of the organic matter quality of the newly formed peat. Current efforts to restore peatlands at a large scale therefore require low cost and high throughput techniques to monitor the evolution of organic matter. In this study, we assessed the merits of using Fourier transform infrared (FTIR) spectra to predict the organic matter composition in peat samples in relation with soil peat properties, tends to to be hydrophobic, flammable.
Presented at the 12th AGILE International Conference on Geographic Information Science
Abdulhakim Abdi and Anand Nandipati
http://www.geospatialtechnologist.com/
Mosnier - Impacts of improved transportation infrastructure on agricultural s...CIALCA
Presentation delivered at the CIALCA international conference 'Challenges and Opportunities to the agricultural intensification of the humid highland systems of sub-Saharan Africa'. Kigali, Rwanda, October 24-27 2011.
Assessment of Spatial and Temporal Variations of Soil Salinity using Remote S...Hamdi Zurqani
“The aim of this paper is to identify the change in saline soils (Sebkha) using Remote Sensing (RS) and geographic information system (GIS) techniques”.
Chemical and spectroscopy of peat from West and Central Kalimantan, Indonesia...Agriculture Journal IJOEAR
Abstract— Improving peat soil is difficult but not impossible. Managed correctly, peat can be a highly productive medium for agriculture, but drainage and cultivation can lead to irreversible peat shrinkage. Vegetational changes during the restoration of cutover peatlands leave a legacy in terms of the organic matter quality of the newly formed peat. Current efforts to restore peatlands at a large scale therefore require low cost and high throughput techniques to monitor the evolution of organic matter. In this study, we assessed the merits of using Fourier transform infrared (FTIR) spectra to predict the organic matter composition in peat samples in relation with soil peat properties, tends to to be hydrophobic, flammable.
Soil Classification Using Image Processing and Modified SVM Classifierijtsrd
Recently the use of soil classification has gained more and more importance and recent direction in research works indicates that image classification of images for soil information is the preferred choice. Various methods for image classification have been developed based on different theories or models. In this study, three of these methods Maximum Likelihood classification MLC , Sub pixel classification SP and Support Vector machine SVM are used to classify a soil image into seven soil classes and the results compared. MLC and SVM are hard classification methods but SP is a soft classification. Hardening of soft classifications for accuracy determination leads to loss of information and the accuracy may not necessary represent the strength of class membership. Therefore, in the comparison of the methods, the top 20 compositions per soil class of the SP were used instead. Results from the classification, indicated that output from SP was generally poor although it performs well with soils such as forest that are homogeneous in character. Of the two hard classifiers, SVM gave a better output than MLC. Priyanka Dewangan | Vaibhav Dedhe "Soil Classification Using Image Processing and Modified SVM Classifier" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18489.pdf
Methodologies used for identifying, assessing and mapping ecosystem services are diverse and frequently inconsistent and notwithstanding the examples from available literature, evident methodological gaps are still present. This paper presents an indicator based approach to assessing and mapping the multiplicity of ecosystem services provided by soils, based on available soil data for a reference depth of 100 cm. Of operational value is the fact that, within this framework, several services can be treated and mapped simultaneously, providing an efficient tool to model the heterogeneity of different soil functions, both at local and regional scale. The methodology consists of: (i) definition of soil based eco-system services, based on available soil data and on societal demands; (ii) definition of appropriate indicators and coding; and (iii) assessment and eventually mapping of soil based multiple ecosystem services. In this work we used spatial data to characterize and model the spatial heterogeneity of provisioning and regulating soil services in the case study area of alluvial plain of Emilia Romagna (Northern Italy). In order to explicitly take into account the spatial variability and the related uncertainty, and in order to exploit at best the available information, we: (i) realised a continuous coverage of basic soil properties via geostatistical simulation conditional on available 1:50,000 soil map and land use map, and (ii) derived the relevant soil properties via locally calibrated PTFs and using other available information, such as the land capability map. Results provide new insights about the composition and interrelation of multiple soil functions and services in the region and highlight the difference between soils in term of joint services provision.
Analysis of Changing Land Use Land Cover in Salinity Affected Coastal RegionIJERA Editor
Anthropogenic activities have induced many changes in land use over a period of three decades in a salinity
affected semi-arid region of coastal Saurashtra in Gujarat. To overcome water scarcity and quality issues, efforts
have been undertaken by state authorities to conserve and effectively use surface water resource to supplement
the irrigation and domestic water requirements. Surface water schemes implemented in the area have altered the
general land use conditions. In the present study, remotely sensed data coupled with ancillary data are used for
analysing the land use-land cover change. Supervised classification and post classification techniques are
employed to classify various land use-land cover classes and to detect changes, respectively. Landscape pattern
change has been studied by analysing the spatial pattern of land use land cover classes structure. The results
show that the region has experienced significant changes over a thirty year period. Growth in agricultural
activities, policies developed to conserve freshwater runoff, and increase in built-up area, are the main driving
forces behind these changes
Measurement of Carbon content in plots under SFM and SLM in the Gran Chaco Am...ExternalEvents
This presentation was presented during the 2 Parallel session on Theme 1, Monitoring, mapping, measuring, reporting and verification (MRV) of SOC, of the Global Symposium on Soil Organic Carbon that took place in Rome 21-23 March 2017. The presentation was made by Mr. Matías Bosio, from PASCHACO - Argentina, in FAO Hq, Rome
Accounting for Carbon in Australia’s Coastal WetlandsCIFOR-ICRAF
Presented by Tertius de Kluyver (Senior Policy Analyst at the Department of the Environment of the Government of Australia) at "Steps towards Blue Carbon mitigation under NDCs in Latin America and the Caribbean - Session 2" on 23 July 2020
Watershed management: Role of Geospatial Technologyamritpaldigra30
Watershed management is the study of the relevant characteristics of a watershed which is done to enhance watershed functions that affect the plant, animal and human or other living communities within the watershed boundary.
This PPT dscribes the Role of Geospatial Technology in Watershed Management
performance evaluation and characterization of wetted soil parameters of impr...IJEAB
Field study was conducted to evaluate the emission uniformity (EU), global coefficient of variation (CGv), emitter flow variation (Qvar) and distribution uniformity (DU), and determine the wetted radius (rw) on soil surface of improvised medi-emitters installed in a tomato field. Soil water content (SWC) at four layers was determined after different periods of irrigation. Radius of wetted soil surface was determined and predicted. Irrigation frequency had no significant effect on the average discharge rate of the medi-emitters throughout the growing cycle. Average Qvar and CGv were significantly (P=0.05) influenced by the frequency of application while the EU and DU did not significantly (P=0.05) differ among the treatments. There were significant differences in the average values of SWC in different soil layers under the different periods of irrigation. Both the observed and calculated rw on the soil surface were fitted with fourth order polynomial. The model performance parameters of MAE and RMSE between the calculated and observed radii were low, indicating good prediction. Medical infusion set can successfully replace the more expensive conventional emitters for drip irrigation system.
Class Project
Mapping of Crop Residues Using Hyperspectral Data:
· Techniques and indexes for quantification,
· Data sources and
· Unsupervised classification for tillage systems
Table of contents / INDEX
Topic
Page
1.
Problem / application
3
2.
Working hypothesis
3
3.
Project outcomes
4
4.
Literature review
4
5.
Data sources
8
6.
Methods
10
7.
Results
16
8
Issues and learning
20
9
Conclusions and future works
21
10.
Annex 1. Corrected bands and columns
22
11
Annex 2. Copy of in-running matlab code for de-striping
23
12
References
25
2
1. PROBLEM / APPLICATION
Agriculture is a widespread, basic activity around the world, which main purpose is to harvest food, fiber or/and energy. After every growing season residues are left in fields. It is important to quantify the amount and cover of agricultural residues for enhancing the understanding in global biogeochemical cycles, and for applications such as their role for preventing soil erosion and their contribution in carbon sequestration. However, it is not completely understood yet how to estimate crop residues cover, their discrimination under tillage or no tillage cropping systems, and its seasonal variability as well as their temporal changes. This class project proposes to explore the estimation and mapping of crop residues by remote sensing techniques using hyperspectral image data.
2. WORKING HYPOTHESIS
Crop residues cover and amount can be accurately estimated by remote sensing techniques. A wide range of crop species and their residues can be studied in the near future and they might be even differentiated by spectral classification. Future work might include description of temporal patterns upon analyzing hyperspectral data (EO-1 Hyperion) in complement with multispectral data (Landsat 7 ETM+ and EO-1 ALI).
3
3. PROJECT OUTCOMES
This class project will generate an estimation of crop residues cover in agricultural fields in Central Indiana in Tipton County. In addition, the amount of crop residues will be approximately calculated based upon yield/residues ratio assumptions. Also, unsupervised classifications for different tillage management (two classes: tilled areas and no-tilled areas) in agricultural fields in Tipton County. Finally, by this study we expect to integrate/use three different data sources (Landsat 7 ETM+, EO-1 ALI and EO-1 Hyperion) and to calculate Cellulose Absorption Index on hyperspectral data.
4. LITERATURE REVIEW
Crop residues are any portion of crop plants that is left in the field after harvest. Crop residues cover is a relevant topic to be studied because of three main reasons: they are widespread in the landscape of agriculture in the Midwest, they represent one of the most important organic inputs for soil carbon sequestration estimating input, and also they relate to soil conservation and reduction of soil erosion (Lal, 2002 & 2004). Remote sensing techniques are also a potential fo ...
Soil Classification Using Image Processing and Modified SVM Classifierijtsrd
Recently the use of soil classification has gained more and more importance and recent direction in research works indicates that image classification of images for soil information is the preferred choice. Various methods for image classification have been developed based on different theories or models. In this study, three of these methods Maximum Likelihood classification MLC , Sub pixel classification SP and Support Vector machine SVM are used to classify a soil image into seven soil classes and the results compared. MLC and SVM are hard classification methods but SP is a soft classification. Hardening of soft classifications for accuracy determination leads to loss of information and the accuracy may not necessary represent the strength of class membership. Therefore, in the comparison of the methods, the top 20 compositions per soil class of the SP were used instead. Results from the classification, indicated that output from SP was generally poor although it performs well with soils such as forest that are homogeneous in character. Of the two hard classifiers, SVM gave a better output than MLC. Priyanka Dewangan | Vaibhav Dedhe "Soil Classification Using Image Processing and Modified SVM Classifier" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18489.pdf
Methodologies used for identifying, assessing and mapping ecosystem services are diverse and frequently inconsistent and notwithstanding the examples from available literature, evident methodological gaps are still present. This paper presents an indicator based approach to assessing and mapping the multiplicity of ecosystem services provided by soils, based on available soil data for a reference depth of 100 cm. Of operational value is the fact that, within this framework, several services can be treated and mapped simultaneously, providing an efficient tool to model the heterogeneity of different soil functions, both at local and regional scale. The methodology consists of: (i) definition of soil based eco-system services, based on available soil data and on societal demands; (ii) definition of appropriate indicators and coding; and (iii) assessment and eventually mapping of soil based multiple ecosystem services. In this work we used spatial data to characterize and model the spatial heterogeneity of provisioning and regulating soil services in the case study area of alluvial plain of Emilia Romagna (Northern Italy). In order to explicitly take into account the spatial variability and the related uncertainty, and in order to exploit at best the available information, we: (i) realised a continuous coverage of basic soil properties via geostatistical simulation conditional on available 1:50,000 soil map and land use map, and (ii) derived the relevant soil properties via locally calibrated PTFs and using other available information, such as the land capability map. Results provide new insights about the composition and interrelation of multiple soil functions and services in the region and highlight the difference between soils in term of joint services provision.
Analysis of Changing Land Use Land Cover in Salinity Affected Coastal RegionIJERA Editor
Anthropogenic activities have induced many changes in land use over a period of three decades in a salinity
affected semi-arid region of coastal Saurashtra in Gujarat. To overcome water scarcity and quality issues, efforts
have been undertaken by state authorities to conserve and effectively use surface water resource to supplement
the irrigation and domestic water requirements. Surface water schemes implemented in the area have altered the
general land use conditions. In the present study, remotely sensed data coupled with ancillary data are used for
analysing the land use-land cover change. Supervised classification and post classification techniques are
employed to classify various land use-land cover classes and to detect changes, respectively. Landscape pattern
change has been studied by analysing the spatial pattern of land use land cover classes structure. The results
show that the region has experienced significant changes over a thirty year period. Growth in agricultural
activities, policies developed to conserve freshwater runoff, and increase in built-up area, are the main driving
forces behind these changes
Analysis of Changing Land Use Land Cover in Salinity Affected Coastal Region
Similar to Using MODIS Land-Use/Land-Cover Data and Hydrological Modeling for Estimating Nutrient Concentrations - Vladimir J. Alarcon, William McAnally, Gary Ervin, Christopher Brooks
Measurement of Carbon content in plots under SFM and SLM in the Gran Chaco Am...ExternalEvents
This presentation was presented during the 2 Parallel session on Theme 1, Monitoring, mapping, measuring, reporting and verification (MRV) of SOC, of the Global Symposium on Soil Organic Carbon that took place in Rome 21-23 March 2017. The presentation was made by Mr. Matías Bosio, from PASCHACO - Argentina, in FAO Hq, Rome
Accounting for Carbon in Australia’s Coastal WetlandsCIFOR-ICRAF
Presented by Tertius de Kluyver (Senior Policy Analyst at the Department of the Environment of the Government of Australia) at "Steps towards Blue Carbon mitigation under NDCs in Latin America and the Caribbean - Session 2" on 23 July 2020
Watershed management: Role of Geospatial Technologyamritpaldigra30
Watershed management is the study of the relevant characteristics of a watershed which is done to enhance watershed functions that affect the plant, animal and human or other living communities within the watershed boundary.
This PPT dscribes the Role of Geospatial Technology in Watershed Management
performance evaluation and characterization of wetted soil parameters of impr...IJEAB
Field study was conducted to evaluate the emission uniformity (EU), global coefficient of variation (CGv), emitter flow variation (Qvar) and distribution uniformity (DU), and determine the wetted radius (rw) on soil surface of improvised medi-emitters installed in a tomato field. Soil water content (SWC) at four layers was determined after different periods of irrigation. Radius of wetted soil surface was determined and predicted. Irrigation frequency had no significant effect on the average discharge rate of the medi-emitters throughout the growing cycle. Average Qvar and CGv were significantly (P=0.05) influenced by the frequency of application while the EU and DU did not significantly (P=0.05) differ among the treatments. There were significant differences in the average values of SWC in different soil layers under the different periods of irrigation. Both the observed and calculated rw on the soil surface were fitted with fourth order polynomial. The model performance parameters of MAE and RMSE between the calculated and observed radii were low, indicating good prediction. Medical infusion set can successfully replace the more expensive conventional emitters for drip irrigation system.
Class Project
Mapping of Crop Residues Using Hyperspectral Data:
· Techniques and indexes for quantification,
· Data sources and
· Unsupervised classification for tillage systems
Table of contents / INDEX
Topic
Page
1.
Problem / application
3
2.
Working hypothesis
3
3.
Project outcomes
4
4.
Literature review
4
5.
Data sources
8
6.
Methods
10
7.
Results
16
8
Issues and learning
20
9
Conclusions and future works
21
10.
Annex 1. Corrected bands and columns
22
11
Annex 2. Copy of in-running matlab code for de-striping
23
12
References
25
2
1. PROBLEM / APPLICATION
Agriculture is a widespread, basic activity around the world, which main purpose is to harvest food, fiber or/and energy. After every growing season residues are left in fields. It is important to quantify the amount and cover of agricultural residues for enhancing the understanding in global biogeochemical cycles, and for applications such as their role for preventing soil erosion and their contribution in carbon sequestration. However, it is not completely understood yet how to estimate crop residues cover, their discrimination under tillage or no tillage cropping systems, and its seasonal variability as well as their temporal changes. This class project proposes to explore the estimation and mapping of crop residues by remote sensing techniques using hyperspectral image data.
2. WORKING HYPOTHESIS
Crop residues cover and amount can be accurately estimated by remote sensing techniques. A wide range of crop species and their residues can be studied in the near future and they might be even differentiated by spectral classification. Future work might include description of temporal patterns upon analyzing hyperspectral data (EO-1 Hyperion) in complement with multispectral data (Landsat 7 ETM+ and EO-1 ALI).
3
3. PROJECT OUTCOMES
This class project will generate an estimation of crop residues cover in agricultural fields in Central Indiana in Tipton County. In addition, the amount of crop residues will be approximately calculated based upon yield/residues ratio assumptions. Also, unsupervised classifications for different tillage management (two classes: tilled areas and no-tilled areas) in agricultural fields in Tipton County. Finally, by this study we expect to integrate/use three different data sources (Landsat 7 ETM+, EO-1 ALI and EO-1 Hyperion) and to calculate Cellulose Absorption Index on hyperspectral data.
4. LITERATURE REVIEW
Crop residues are any portion of crop plants that is left in the field after harvest. Crop residues cover is a relevant topic to be studied because of three main reasons: they are widespread in the landscape of agriculture in the Midwest, they represent one of the most important organic inputs for soil carbon sequestration estimating input, and also they relate to soil conservation and reduction of soil erosion (Lal, 2002 & 2004). Remote sensing techniques are also a potential fo ...
The performance of portable mid-infrared spectroscopy for the prediction of s...ExternalEvents
This presentation was presented during the 3 Parallel session on Theme 1, Monitoring, mapping, measuring, reporting and verification (MRV) of SOC, of the Global Symposium on Soil Organic Carbon that took place in Rome 21-23 March 2017. The presentation was made by Mr. Martin Soriano-Disla, CSIRO Land and Water - Australia, in FAO Hq, Rome
37.8 MGD Activated Sludge Wastewater Treatment Plant Field and Model Capacity...njcnews777
This paper presents results from the model capacity evaluation of an activated sludge plant at a large 37.8 MGD regional municipal wastewater treatment plant with reuse potential. The plant capacity evaluation (stress test) was performed to evaluate treatment process capacity and efficiencies as a part of the continuous improvement of the treatment plant for process optimization and maximization of flow through the plant.
Similar to Using MODIS Land-Use/Land-Cover Data and Hydrological Modeling for Estimating Nutrient Concentrations - Vladimir J. Alarcon, William McAnally, Gary Ervin, Christopher Brooks (20)
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"Analyzing and assessing ecological transition in building sustainable cities" Keynote presentation at "International Conference on Sustainable Environment and Technologies" 23 September 2022, Nicolas Tesla University Union, Belgrade, Serbia
Smart Cities: New Science for the Cities
Beniamino Murgante
School of Engineering, University of Basilicata
Lecture at the Department of Community and Regional Planning
Smart Cities course - Professor Alenka Poplin
Keynote at the 24th International Conference on Urban Planning and Regional Development in the Information Society
GeoMultimedia 2019, 2-4 April 2019
Karlsruhe Institute of Technology, Germany
Involving citizens in smart energy approaches: the experience of an energy pa...Beniamino Murgante
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Programmazione per la governance territoriale in tema di tutela della biodive...Beniamino Murgante
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Università degli Studi di Cagliari, DICAAR, sabrinalai@unica.it
RISCHIO TERRITORIALE NEL GOVERNO DEL TERRITORIO: Ricerca e formazione nelle s...Beniamino Murgante
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Alessandro Attolico, Federico Amato
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GEOGRAPHIC INFORMATION – NEED TO KNOW (GI-N2K) Towards a more demand-driven g...Beniamino Murgante
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Fino alla fine degli anni '80 un urbanista che cercava di supportare dei ragionamenti di piano con l'informatica riusciva ad ottenere, nel migliore dei casi, qualche dato statistico sulla popolazione. Con il trascorrere degli anni si è assistito ad un incremento dell'utilizzo delle tecnologie per la costruzione dei quadri conoscitivi a supporto del processo di piano, fino a raggiungere l'attuale Information Explosion Era.
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Introduzione
Andreina Maahsen-Milan
Università di Bologna
Tecnologie, Territorio, Smartness
Beniamino Murgante
Università della Basilicata
Facoltà Ingegneria Edile di Ravenna - Università di Bologna
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Using MODIS Land-Use/Land-Cover Data and Hydrological Modeling for Estimating Nutrient Concentrations - Vladimir J. Alarcon, William McAnally, Gary Ervin, Christopher Brooks
1. Using MODIS Land-Use/Land-
Cover Data and Hydrological
Modeling for Estimating Nutrient
Concentrations
Vladimir J. Alarcon, William McAnally,
Gary Ervin, Christopher Brooks
Northern Gulf Institute - GeoSystems Research Institute
Mississippi State University
2. Introduction
• United States land area: 0.9 billion hectares
– 20 percent is cropland, 26 percent permanent
grassland pasture and range land, and 28 percent
forest-use land.
– Land used for agricultural purposes in 1997 totaled
nearly 1.2 billion acres, over (52 percent of total
U.S. land area).
– Land use in the Southeastern United States is
predominantly covered by forests and agricultural
lands.
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
3. Introduction
• Water quality and flow regime influence the
ecological “health” of aquatic biota.
• In the Southeastern USA
– agricultural land use can comprise 50% or more of
land cover,
– sediment and nutrient runoff can seriously degrade
the ecological quality of aquatic environments.
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
4. Objectives
• Connecting hydrological processes to
biological system response studies in the
Upper Tombigbee watershed
– a hydrological model of the watershed was
developed.
– model development and its use for providing
stream flow, runoff, and nutrient concentrations to
establish relationships between stream
nutrients, runoff and discharge, and biotic data.
–.
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
5. Methods
• Study area:
– Upper Tombigbee
• located in Northwestern
Alabama and
Northeastern Mississippi,
USA
• Drains approximately
1390325 ha
• main contributor of flow
to the Mobile River
• approximate average
stream flow of 169 m3/s.
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
6. Methods
• Topographical data:
– USGS DEM,
• 3 arc-second (1:250,000-
scale, 300 m)
• A seamless topographical
– “mosaicking” several
DEMs that covered the
area.
• ArcInfo (GRID) was used
to fill grid cells with no-
data values (con,
focalmax, and focalmean)
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
7. Methods
• Land Use data:
– Two land use datasets
• USGS GIRAS (1986)
• NASA MODIS
MOD12Q1 (2001-2004)
– The MODIS MOD12 Q1
data was geo-processed
for the dataset to be
consistent with the USGS
GIRAS dataset (land use
categories).
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
8. Methods/Results
• Biological Data and Watershed Delineation:
– Geo-locations of field-collected data on fish and
mussel were used to delineate the watershed
under study.
• Produced sub-watersheds contained at least four
sampled species per sub-watershed
• Only samples collected during 2002-2004 and 1977-
1982 were used for these analyses, to coincide with
the GIRAS (1986) and MODIS (2001-2004) land use
data.
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
9. Methods
• Hydrological Modeling
– Hydrological Simulation Program Fortran
(HSPF).
• Simulation of non-point source watershed hydrology
and water quality.
• Time-series of meteorological/water-quality data,
land use and topographical data are used to estimate
stream flow hydrographs and polluto-graphs.
• The model simulates interception, soil moisture,
surface runoff, interflow, base flow, snowpack depth
and water content, snowmelt, evapo-transpiration,
and ground-water recharge.
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
10. Methods
• Hydrological Modeling
– Nutrients (total nitrogen, TN, and total
phosphorus, TP) concentrations were estimated
using export coefficient for the region (*).
Land use category Average TP (kg/ha- Average TN (kg/ha-
year) year)
Row Crops 4.46 16.09
Non Row Crops 1.08 5.19
Forested 0.236 2.86
Urban 1.91 9.97
Pasture 1.5 8.65
Feedlot/Manure
Storage 300.7 3110.7
Mixed Agriculture 1.134 16.53
• (*) Lin, J.P.: Review of Published Export Coefficient and Event Mean Concentration (EMC) Data.
Wetlands Regulatory Assistance Program ERDC TN-WRAP-04-3, September (2004)
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
11. Results
• Land Use:
– From 1986 to 2003
agricultural lands
increased in almost
34%, forest lands
decreased in 16%.
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
12. Results
• Hydro modeling:
– Once an optimum watershed delineation was
achieved, HSPF was launched from within BASINS
to initialize the HSPF model application for the
Upper Tombigbee watershed. The initialization was
done for each of the land use datasets used in this
study (GIRAS and MODIS). Hence, two
hydrological models were set-up with two different
time periods of simulation: 1980-1990, and 1996-
2006.
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
13. Results
• Hydro modeling:
– From delineated watershed to HSPF model
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
14. Results
• Hydro modeling: Calibrated HSPF models
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
15. Results
• Nutrient estimation Total Phosphorus
Average Maximum 3 quartile
(selected sub-basins) Sub-basin
43
GIRAS
0.43
GIRAS
2.04
GIRAS
0.62
51 1.11 5.26 1.66
54 0.80 3.75 1.12
Average Maximum 3 quartile
Sub-basin MODIS MODIS MODIS
43 0.33 2.17 0.51
51 0.88 6.09 1.17
54 0.68 4.36 1.06
Total Nitrogen
Average Maximum 3 quartile
Sub-basin GIRAS GIRAS GIRAS
43 2.30 10.91 3.32
51 4.40 20.94 6.61
54 3.53 16.65 5.00
Average Maximum 3 quartile
Sub-basin MODIS MODIS MODIS
43 1.76 11.42 2.69
51 3.42 23.70 4.55
54 2.98 19.07 4.62
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
16. Results
• Nutrient estimation (all sub-basins)
TOTAL
PHOSPHORUS
% Change
(Mg/L) Average Maximum (Maximum)
GIRAS 1.23 5.66
MODIS 1.20 7.78 37
TOTAL
NITROGEN
% Change
(Mg/L) Average Maximum Maximum
GIRAS 4.72 21.58
MODIS 4.48 28.94 34
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
17. Conclusions
• Methodology for the introduction of land use data from
MODIS MOD 12Q1 into the Hydrological Program
Fortran (HSPF) is shown to be successful.
• MODIS datasets for 2001 through 2004 were geo-
processed and the results are shown to be consistent
with historical trends in land use for the region of
Upper Tombigbee watershed.
– From 1986 to 2003 agricultural lands increased in almost
34%, forest lands decreased in 16%, and range-land almost
quadruple in size.
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
18. Conclusions
• The watershed delineation process, guided by
geographical locations of sampling points of mollusk
and fish data, allowed the generation of sub-watersheds
that captured the distribution of biological data
throughout the study area.
• A comparison of nutrient concentration values for sub-
basins 43, 51, and 54 showed:
– Average and 3rd-quartile total phosphorus (TP)
concentrations do not differ greatly when using either land
use dataset.
– Only maximum concentrations showed to have increased
from 6% to 16%.
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan
19. Conclusions
• Similarly,
– Maximum total nitrogen (TN) concentrations were found to
have increased when using MODIS land use data (with
respect to TN concentrations estimated using GIRAS land use
data). Percent increments in TN concentration values are in-
between 5% to 15%.
• For all sub-basins:
– Maximum TP and TN concentrations seem to have increased
in about 37 % and 34%, respectively, from 1986 to 2003.
– This increase in maximum nutrient concentrations seems to
correlate with the 34% increase in agricultural areas in the
Upper Tombigbee watershed, from 1986 to 2003.
ICCSA 2010 Conference, March 23-26, 2010, Fukuoka, Japan