MICROWAVE REMOTE SENSING IN HYDROLOGY

• Sponsoring Institution: State Agricultural Experiment Station
• Project Status: COMPLETE
• Funding Source: STATE
• Reporting Frequency: Annual
• Accession No.: 0201924
• Project Start Date: Mar 1, 2004
• Project End Date: Sep 30, 2008
• Program Code: [(N/A)]- (N/A)

Recipient Organization
UNIVERSITY OF FLORIDA
G022 MCCARTY HALL
GAINESVILLE,FL 32611

Performing Department
AGRICULTURAL & BIOLOGICAL ENGINEERING

Non Technical Summary
We must understand water on the earth's surface, particularly water stored in the soil to accurately predict weather patterns and short-term climate change. The National Climatic Data Center reports that extremes of weather, such as floods, droughts, hurricanes, and ice storms result in about 485 deaths per year and cause average damage of about $10 billion per year in the US. Weather forecasters missed predicting severe flooding in the US Midwest in 1993 that resulted in a loss of $26.7 billion in crops and personal property, not to mention the invaluable loss of 48 lives. If accurate measures of soil moisture had been available, the weather forecasters would have predicted the flood and damage could have been minimized. Accurate information on soil moisture also helps farmers to choose crop varieties for their farm, decide when to plant, irrigate, fertilize, and harvest, and predict crop yield. Information regarding soil moisture is also used by hydrologists and environmentalists to predict the flows of contaminants into streams, rivers and groundwater that affect our drinking water supply. Currently we have no operational method to routinely provide weather forecasters, farmers, hydrologists, and environmentalists with accurate estimates of stored water at either local or regional scales. The purpose of this research is to use microwave remote sensing to improve estimates of water and energy fluxes at the land-atmosphere interface by the Soil-Vegetation-Atmosphere Transfer (SVAT) and crop growth models.

Animal Health Component

10%

Research Effort Categories

Basic

20%

Applied

10%

Developmental

70%

Classification

Knowledge Area (KA)	Subject of Investigation (SOI)	Field of Science (FOS)	Percent
102	1480	2020	25%
102	1480	2050	25%
102	1719	2020	25%
102	1719	2050	25%

Knowledge Area
102 - Soil, Plant, Water, Nutrient Relationships;

Subject Of Investigation
1480 - Sweetcorn; 1719 - Cotton, other;

Field Of Science
2020 - Engineering; 2050 - Hydrology;

Keywords

soil moisture

evapotranspiration

recharge

microwaves

remote sensing

hydrology

water flow

energy flow

atmosphere

land

growth models

data analysis

subsurface flow

sweetcorn

cotton

agricultural engineering

micrometeorology

vegetation

soil properties

soil plant water relations

life cycle

vadose zone

crop growth

canopy

crop yields

algorithms

predictive models

Goals / Objectives
Objective 1: To conduct a comprehensive field experiment for two growing seasons of cotton and corn to measure Micrometeorological conditions, vegetation and soil properties, and microwave brightness temperatures. Objective 2: To develop a passive microwave brightness model at 6.9 GHz that characterizes emission, absorption, and scattering from the cotton and corn throughout its entire life cycle. Objective 3: To develop a process-based dynamic SVAT model that simulates coupled energy and moisture fluxes from the top of the canopy through the vadose zone, as well as crop growth and development during the entire growing season of cotton and corn. Objective 4: To develop an algorithm to assimilate Tb, and other biophysical observations with the SVAT-MB model predictions to improve soil moisture, ET, recharge, and crop yield estimate.

Project Methods
Because microwave brightness temperature (Tb) is sensitive to moisture and temperature distribution in vegetation and the top few centimeters of soil, it can be physically correlated to ET and moisture in the root-zone, important for crop water requirements and groundwater recharge, via an integrated SVAT-Microwave Brightness (MB) model. To understand this relationship between Tb and ET, we need to understand the processes that contribute to the brightness signatures of specific terrains during their growth cycles through a radiative transfer model and to study the relationship of these signatures to water dynamics in landscape , i.e. we first need to solve the forward problem. Once we have a forward SVAT-MB model that links ET and moisture estimates with Tb, we can then assimilate the microwave observations into the SVAT-MB model to improve estimation of ET and recharge fluxes by the model. Here, we propose to extend the understanding and interpretation of microwave brightness signatures, as correlated to ET and recharge, in a dominant row-crops grown in the southern U.S., viz., corn and cotton. Specifically, we propose to solve the forward problem of estimating brightness temperatures at 6.9 GHz, corresponding to the lowest frequency of the newly launched Advanced Microwave Scanning Radiometer (AMSR), for the full growing season using an integrated SVAT-MB models for corn and cotton grown in the north-central Florida. The model will be calibrated/validated using data from field experiments conducted at the UF/IFAS Plant Science Research and Education Unit (PSREU), Citra, Florida. Finally, an assimilation algorithm will be developed to allow remotely sensed microwave brightness temperatures, observed during the subsequent growing seasons, to be used in the SVAT-MB models to improve ET and recharge estimates. The data from the second growing season will be used for further forward model validation and field-testing of the assimilation algorithms. This research utilizes the sensitivity of Tb to near-surface soil moisture for assimilating observed brightness in an SVAT-MB model to improve its predictions for ET and recharge.

Progress 03/01/04 to 09/30/08

Outputs
OUTPUTS: 1. Conducted six field experiments, viz., Microwave Water and Energy Balance Experiments (MicroWEXs), as tabled below: MicroWEX Crop Year URL for Data Report 1 Cotton 2003 http://edis.ifas.ufl.edu/AE288 2 Corn 2004 http://edis.ifas.ufl.edu/AE360 3 Cotton 2004 http://edis.ifas.ufl.edu/AE361 4 Corn 2005 http://edis.ifas.ufl.edu/AE362 5 Corn 2006 http://edis.ifas.ufl.edu/AE407 6 Cotton 2006 http://edis.ifas.ufl.edu/AE409 These experiments provide one of the most detailed, high temporal resolution datasets for different components of the energy (heat) and water balance at the land surface and in the vadose zone and for remotely sensed observations at the microwave wavelengths. We have completed data analyses and field observation reports (as web-based documents). The observations from the MicroWEXs have been used for development and calibration of the land surface models (LSMs), crop growth models (CGMs), and microwave remote sensing algorithms (MRS). The LSMs simulate 1-D coupled water and heat transport in the vegetation and the root zone and estimate water and energy fluxes at the land surface. Accurate estimation of these fluxes is important for predictions of weather and near-term climate, for crop growth and yield forecasting, and ecosystem productivity. The CGMs simulate growth and development in crops and estimate harvest and yield. The MRS algorithms predict the microwave signature of the land cover (crop field, in our study) using the fluxes estimated by the LSMs. The microwave signatures of land covers are highly sensitive to the water and temperature distribution in vegetation and soil. Thus, microwave observations from space can provide information regarding soil water. 2. Developed, calibrated the integrated LSM-CGM-MRS models for corn and cotton to be able to use microwave observations to improve estimates of root zone soil moisture during the entire growing season, and hence land surface fluxes through data assimilation. In this project, the LSM model is the Land Surface Process model, the CGM is the Decision Support System for Agrotechnology Transfer, and the MRS is the Microwave Brightness model. 3. Developed and tested data assimilation algorithms for assimilation of in situ soil moisture and microwave observations from the MicroWEXs in the integrated models and quantify the errors in the estimation of root zone soil moisture and land surface fluxes. 4. Developed curves for crop water use for sweet corn and cotton grown in North Central Florida. 5. Three courses were developed: ABE 4034/ABE6035 - Remote Sensing in Engineering and ABE6037 Remote Sensing in Hydrology. These courses provide the upper-division undergraduate and graduate students the science and engineering principles underlying remote sensing and its various applications in hydrology, agriculture and other fields. 6. This project has resulted in students graduating with 1PhD and 5 Masters Degrees. Ten undergraduate students were mentored during this project, two of whom were through the UF/IFAS Summer Internship Program and one was through the University Scholars Program. PARTICIPANTS: Project investigators: Jasmeet Judge (PI); Wendy Graham (Co-PI), James Jones (Co-PI) Graduate student assistants: Joaquin Casanova, Kai-Jen Tien, Tzy-Yun Lin, Mi-Young Jang, Roufan Yang, Fei Yan, Divya Aggrawal, Maninder Singh. Undergraduate student assistants: Marisa Gedney, Heather Enos, Blaire Colvin, Michael Garcia, Masashige Taguchi, Joaquin Casanova, Yananayi Chipangura, Tarek Saleh, Alexandra Lee TARGET AUDIENCES: The project benefited the agricultural and the remote sensing researchers in utilizing state-of-the are remote sensing technology to improve quantification of Land surface fluxes such at Evapotranspiration, and soil water in the root zone. The research has resulted in 1PhD and 5 Masters students and 21 publications. PROJECT MODIFICATIONS: Nothing significant to report during this reporting period.

Impacts
Understanding water stored in the root-zone is an important agricultural issue. This amount affects irrigation scheduling, local and regional weather patterns, and crop growth. As part of this study, we use the state of the art remote sensing technologies along with crop-simulation and hydrology model to improve our understanding of water movement in the root-zone, and to understand how novel microwave observations can improve the root zone estimates from the models. Outcomes of the research activities have provided insights into model integration and calibration. The MicroWEXs datasets are rare and several collaborations with scientists from other disciplines and other universities have resulted from these datasets. We have used the UF High Performance Computing Center to calibrate our coupled LSP-DSSAT model. We have developed and tested methodology to assimilate in situ soil moisture observations and remotely sensed microwave observations to improve predictions of root-zone soil water in the models

Publications

• Lizaso, J.I., K..J.Boote, C.M. Cherr, J.M.S. Scholberg, J.J. Casanova, J. Judge, J.W. Jones, and G. Hoogenboom, Developing a sweet corn simulation model to predict fresh market yield and quality of ears, J. Amer. Soc. Hort. Sci., 132, pp 415-422, 2007.
• Tien, K.J., R.D DeRoo, and J. Judge, Comparison of different microwave radiometric calibration techniques,IEEE Geosci. Remote Sensing Letters, 4(1), pp 83-87, 2007.
• Yan, F, H.H. Han, R. Yang, J. Casanova, J. Judge, J.M. Jacobs, O. Lanni, and L.W. Miller, Field observations during the sixth Microwave, Water, and Energy Balance Experiment (MicroWEX-6): from June 19 through November 30, 2006, Circular no. 1515, UF/IFAS, EDIS Web site, http://edis.ifas.ufl.edu/AE409, 2007.
• Casanova, J., F. Yan, J. Judge, K.J. Tien, L.W. Miller, and O. Lanni, Field observations during the fifth Microwave, Water, and Energy Balance Experiment (MicroWEX-5): from March 9 through May 26, 2006, Circular no. 1514, UF/IFAS, EDIS Web site, http://edis.ifas.ufl.edu/AE407, 2007.
• Tien K.J. and J.Judge, Radiometric sensitivity to moisture changes in growing cotton, App. Engineering in Agric, 22(6), pp 843-850, 2006.
• Whitfield, B.F., J. Jacobs, and J. Judge, and, Intercomparison study of the land surface process model and the common land model for a prairie wetland in Florida, J. Hydrometeor, 7(6), pp 1247-1258, 2006.
• Casanova, J.J., J. Judge, and J.W. Jones, Calibration of CERES-Maize crop growth model for linkage with microwave remote sensing model, Trans. of Ameri. Soc. Agri. Eng., 49(3), pp 783-792, 2006.
• Casanova, J.J., J. Judge, and M.Y. Jang, Vertical distribution of moisture in a growing sweet corn canopy during MicroWEX-4, Circular No. 1492, UF/IFAS, EDIS Web site, http://edis.ifas.ufl.edu/AE395, 2006.
• Casanova, J.J., J. Judge, and M.Y. Jang, Transmission of microwaves through corn canopy, In Proceedings of IEEE International Geoscience and Remote Sensing Symposium, doi 10.1109/IGARSS.2006.524, pp 2025-2027, 2006.
• Tien, K.J., J. Judge, L.W. Miller, and O. Lanni, Field data report for the first Microwave, Water, and Energy Balance Experiment (MicroWEX-1) conducted during the cotton season in 2003, Circular no 1470, UF/IFAS, EDIS Web site, http://edis.ifas.ufl.edu/AE288, 2005.
• Judge, J. J. Casanova, T.Y. Lin, K.J. Tien, M.Y. Jang, O. Lanni, and L.W. Miller, Field observations during the second Microwave, Water, and Energy Balance Experiment (MicroWEX-2): from March 17 through June 3, 2004, Circular no. 1480, UF/IFAS, EDIS Web site, http://edis.ifas.ufl.edu/AE360, 2005
• Lin, T.Y., J. Judge, K.J. Tien, M.Y. Jang, J. Casanova, O. Lanni, L.W. Miller, and F. Yan, Field observations during the third Microwave, Water, and Energy Balance Experiment (MicroWEX-3): June 16 through December 21, 2004, Circular no. 1481, UF/IFAS, EDIS Web site, http://edis.ifas.ufl.edu/AE361, 2005.
• Guha A., J.M. Jacobs, T.J. Jackson, M.H. Cosh, E.C. Hsu, and J. Judge, Soil moisture mapping using ESTAR under dry conditions from the Southern Great Plains Experiment (SGP99), IEEE Trans. GeoSci. Remote Sensing, 41(10) Part 2, pp 2392-2397, 2003.
• Casanova, J., T.Y. Lin, M.Y. Jang, K.J. Tien, J. Judge, O. Lanni, and L.W. Miller, Field observations during the fourth Microwave, Water, and Energy Balance Experiment (MicroWEX-4): March 10 through June 14, 2005, Circular no. 1482, UF/IFAS, EDIS Web site, http://edis.ifas.ufl.edu/AE362, 2005.
• Jang, M.Y., K.J. Tien, J. Casanova, and J. Judge, Measurements of soil surface roughness during the fourth Microwave, Water, and Energy Balance Experiment: April 18 through June 13, 2005, Circular no. 1483, UF/IFAS, EDIS Web site, http://edis.ifas.ufl.edu/AE363, 2005.
• Judge, J., and J.D. Leary, Department-Specific Mentoring Network for Women Students in Engineering, In Proceedings of 35th ASEE/IEEE Frontiers in Education Conference, Paper No. 1311, 2005.
• Ritchie, J., C.H. Porter, J. Judge, J.W. Jones, and A.A. Suleiman, Extension of an existing model for soil water evaporation and redistribution under high water content conditions, Soil Sci. Soc. Am. J., 73, doi:10.2136/sssaj2007.0325, pp 792-801, 2009.
• He, J., M.D. Dukes, J.W. Jones, W. D. Graham, and J. Judge, Applying glue for estimating Ceres-Maize genetic and soil parameters for sweet corn production, Trans. Ameri. Soc. Agri. Biol. Eng, 52(6), 1907-1921, 2009.
• Casanova, J., and J. Judge, Estimation of energy and moisture fluxes for dynamic vegetation using coupled SVAT and crop-growth models, Wat. Res. Research, 44, W07415, doi:10.1029/2007WR006503, 2008.
• Judge, J., A.W. England, J.R. Metcalfe, D. McNichol, and B.E. Goodison, Calibration of an integrated land surface process and radiobrightness (LSP/R) model during summertime, Adv. in Water Resources, 31(1), pp. 189-202, 2008.\
• Judge J., Microwave remote sensing of soil water: Recent advances and issues, Invited paper, Trans. of Ameri. Soc. Agri. Eng, Centennial Edition, 50(5), pp 1645-1649, 2007.
• Casanova, J. and J. Judge, Modeling transmission of microwaves through dynamic vegetation, IEEE Trans. Geosci. Remote Sensing, 45(10), pp 3145-3149, 2007.

Progress 10/01/06 to 09/30/07

Outputs
OUTPUTS: 1. Completed data analyses and field observation reports (as web-based documents) for six Microwave Water and Energy Balance Experiments. These experiments are: MicroWEX Crop Year URL for Data Report 1 Cotton 2003 http://edis.ifas.ufl.edu/AE288 2 Corn 2004 http://edis.ifas.ufl.edu/AE360 3 Cotton 2004 http://edis.ifas.ufl.edu/AE361 4 Corn 2005 http://edis.ifas.ufl.edu/AE362 5 Corn 2006 http://edis.ifas.ufl.edu/AE407 6 Cotton 2006 http://edis.ifas.ufl.edu/AE409 These experiments provided one of the most detailed datasets for different components of the energy and water balance at the land surface and in the vadose zone and for remotely sensed observations at the microwave wavelengths. These datasets are rare and several collaborations with scientists from other disciplines have been started. In our research, the data are being used for calibration and validation of hydrology, crop, and remote sensing algorithms for growing vegetation. Other scientists are using the data for conducting inter-model comparisons and for improving of crop/soil parameterizations in their models. 2.Developed and calibrated coupled hydrology (Land Surface Process - LSP) and crop (DSSAT) model. The coupled model provides predictions of water stored in the root-zone in addition to crop growth parameters such as LAI, biomass, and yield during the growing season. The coupling methodology benefits from decades of advances in disciplinary fields of hydrology and crop modeling. 3.Developed curves for crop water use for sweet corn and cotton grown in North Central Florida. PARTICIPANTS: One student graduated with a Masters, Fei Yan. He is now enrolled in a doctoral program at the University of Texas at Austin.

Impacts
Understanding water stored in the root-zone is an important agricultural issue. This amount affects irrigation scheduling, local and regional weather patterns, and crop growth. As part of this study, we are using state of the art remote sensing technologies along with crop-simulation and hydrology model to improve our understanding of water movement in the root-zone. Outcomes of the research activities conducted this year provided insights into model development and calibration. We used UF High Performance Computing Center to calibrate our coupled LSP-DSSAT model. Efforts are underway to develop novel methodologies to assimilate remotely sensed observations to improve predictions of root-zone soil water in the models.

Publications

• Lizaso, J.I., K..J.Boote, C.M. Cherr, J.M.S. Scholberg, J.J. Casanova, J. Judge, J.W. Jones, and G. Hoogenboom, Developing a sweet corn simulation model to predict fresh market yield and quality of ears, J. Amer. Soc. Hort. Sci., 132, pp 415-422, 2007.
• Tien, K.J., R.D DeRoo, and J. Judge, Comparison of different microwave radiometric calibration techniques, IEEE Geosci. Remote Sensing Letters, 4(1), pp 83-87, 2007.
• Yan, F, H.H. Han, R. Yang, J. Casanova, J. Judge, J.M. Jacobs, O. Lanni, and L.W. Miller, Field observations during the sixth Microwave, Water, and Energy Balance Experiment (MicroWEX-6): from June 19 through November 30, 2006, Circular no. 1515, UF/IFAS, EDIS Web site, http://edis.ifas.ufl.edu/AE409, 2007.
• Judge J., Microwave remote sensing of soil water: Recent advances and issues, Invited paper, Trans. of Ameri. Soc. Agri. Eng Centennial Edition, 50(5), pp 1645-1649, 2007.
• Casanova, J. and J. Judge, Modeling transmission of microwaves through dynamic vegetation, IEEE Trans. Geosci. Remote Sensing, 45(10), pp 3145-3149, 2007.
• Casanova, J., F. Yan, J. Judge, K.J. Tien, L.W. Miller, and O. Lanni, Field observations during the fifth Microwave, Water, and Energy Balance Experiment (MicroWEX-5): from March 9 through May 26, 2006, Circular no. 1514, UF/IFAS, EDIS Web site, http://edis.ifas.ufl.edu/AE407, 2007.

Progress 10/01/05 to 09/30/06

Outputs
1. Completed two extensive field experiments. The MicroWEX-5 was conducted from March through May during the growing season of corn and MicroWEX-6 was conducted from June through December during the growing season of cotton. These experiments provided one of the most detailed datasets for different components of the energy and water balance at the land surface and in the vadose zone and for remotely sensed observations at the microwave wavelengths. The datasets will be used for calibration and validation of hydrology, crop, and remote sensing algorithms. 2. Microwave emission model for the entire growing season of cotton has been developed. 3. Linkage of the hydrology model with the crop model for corn has been completed. 4. Linkage of the hydrology model with the crop model for cotton is in progress.

Impacts
Understanding water stored in the root-zone is an important agricultural issue. This amount affects irrigation scheduling, local and regional weather patterns, and crop growth. As part of this study, we are using state of the art remote sensing technologies along with crop-simulation and hydrology model to improve our understanding of water movement in the root-zone. The research is highly interdisciplinary and involves expertise from three different disciplines.

Publications

• Casanova, J.J., J. Judge, and J.W. Jones, 2006, Calibration of CERES-Maize crop growth model for linkage with microwave remote sensing model, Trans. of Ameri. Soc. Agri. Eng., 49(3), pp XX
• Tien, K.J. and J. Judge, 2006. Sensitivity of passive microwave observations to soil moisture for growing vegetation, Applied Engineering in Agriculture, 22(6), pp 843-850.
• Whitfield, B., J. Jacobs, and J. Judge, 2006. Intercomparison Study of the Land Surface Process Model and the Common Land Model for a Prairie Wetland in Florida, Journal of Hydrometeorology, 7(6), pp 1247-1258.
• J. Casanova, J Judge, and MY Jang, 2006. Vertical distribution of moisture in a growing sweet corn canopy during MicroWEX-4, EDIS Circulation number 1492.

Progress 10/01/04 to 09/30/05

Outputs
1. Completed experimental reports for three extensive field experiments at the Plant Science Research and Education unit. 2. Crop model for corn has been calibrated using the MicroWEX-2 dataset and the results were presented at the ASAE National Conference in July, 2005. Refereed publication is in review. 3. Linkage of the hydrology model with the Crop model for corn is in progress. The results will be presented at the AGU international conference and a refereed publication will be submitted.

Impacts
Understanding water stored in the root-zone is an important agricultural issue. This amount affects irrigation scheduling, local and regional weather patterns, and crop growth. As part of this study, we are using state of the art remote sensing technologies along with crop-simulation and hydrology model to improve our understanding of water movement in the root-zone. The research is highly interdisciplinary and involved expertise from three different disciplines.

Publications

• Whitfield, B., J. Jacobs, and J. Judge, 2006. Calibration of SVAT models for prairie wetlands in Florida, submitted to Journal of Hydromet.
• Judge, J., J. Casanova, T.Y. Lin, MY Jang, KC Tien, L Miller, and O Lanni, 2006. Field observations during MicroWEX-2, EDIS Circulation number 1480.
• TYLin, J. Casanova, Judge, J., MY Jang, KC Tien, L. Miller and O Lanni, 2006 Field observations during MicroWEX-3, EDIS Circulation number 1481
• Casanova J., TY Lin, Judge, J., MY Jang, KC Tien, L. Miller, and O. Lanni, 2006. Field observations during MicroWEX-4, EDIS Circulation number 1482
• Jang, MY, J. Casanova, TY Lin, J. Judge, KC Tien, L. Miller, and O. Lanni, 2006. Soil surface roughness measurements during MicroWEX-4, EDIS Circulation number 1483.
• Casanova, J.J., J. Judge, and J.W. Jones, 2006, Calibration of CERES-Maize crop growth model for linkage with microwave remote sensing model, submitted to Trans. of Ameri. Soc. Agri. Eng..
• Tien, K.J., J. Judge, and R.D DeRoo, 2006 Comparison of different microwave radiometric calibration techniques, submitted to IEEE Trans. Geosci. Remote Sensing .
• Tien, K.J. and J. Judge, 2006. Microwave remote sensing signatures of a growing cotton, submitted to Applied Engineering in Agriculture.