Leveraging Remote Sensing, Land Surface Modeling and Ground-based Observations ... Variables within Heterogeneous Agricultural Landscapes
Hydrology and Remote Sensing Laboratory
2013 Annual Report
1a. Objectives (from AD-416):
Objective 1: Develop and verify new observational tools (both remote sensing- and ground observation-based) and scaling techniques for characterizing water balance components, from plot (~10 m) to regional scales (~100 km). Objective 2: Develop remote sensing and modeling approaches for monitoring the magnitude of agricultural drought and its subsequent impact on agricultural crop condition and yield. Objective 3: Develop remote sensing and modeling approaches for characterizing the multi-scale impacts of conservation practices on water quality variables.
1b. Approach (from AD-416):
Ground measurements, remote sensing observations, and modeling each provide a partial description of hydrologic variables required at different spatial scales for agricultural applications. This project seeks to integrate these various sources of information into true multi-scale assessments and leverage their mutual strengths.
3. Progress Report:
First year progress was dominated by data collection/processing activities and the development of suitable evaluation strategies for benchmarking anticipated future improvements in remote sensing, modeling and data assimilation approaches. Examples include the completion of an extensive validation exercise for satellite-based surface energy flux estimates and a detailed examination of ground-based instrumentation required for the validation of satellite-based surface soil moisture retrievals. In addition, new verification techniques were developed for evaluating remote sensing retrievals over data-poor areas lacking extensive ground instrumentation. These milestones represent important prerequisites for follow-on activities aimed at improving our ability to track the storage and flux of water through agricultural landscapes.
Agricultural drought monitoring is another key component of the project. In particular, there is an emphasis on the development of improved drought-monitoring approaches which integrate visible, near-infrared, thermal, and microwave remote-sensing resources. Such integrative research requires the acquisition and processing of multiple (large-scale) satellite- and ground-based data sets. To address this need, a number of important data acquisition and processing tasks were completed over the past year. Once in place, these data sets will allow us to look for better ways to integrate disparate remote sensing products into a unified drought product.
The same is true for projects focused on improving water quality monitoring. In particular, significant time and resources have been dedicated to collecting datasets required to benchmark expected future improvements in combined modeling/remote sensing approaches for monitoring water quality and the impact of conservation practices within the Chesapeake Bay Watershed.
Cosh, M.H., Evett, S.R., McKee, L.G. 2012. Surface soil water content spatial organization within irrigated and non-irrigated agricultural fields. Advances in Water Resources. 50:55-61.
Kustas, W.P., Alfieri, J.G., Anderson, M.C., Colaizzi, P.D., Prueger, J.H., Evett, S.R., Neale, C.M., French, A.N., Hipps, L.E., Chavez, J.L., Copeland, K.S., Howell, T.A. 2012. Evaluating the two-source energy balance model using local thermal and surface flux observations in a strongly advective irrigated agricultural area. Advances in Water Resources. 50:120-133.
Gao, F.N., Eric, B.U., Ma, R., Weng, Q., Masek, J.G., Chen, J., Pan, Y., Song, C. 2012. Mapping impervious surface expansion using medium resolution satellite image time series: A case study in Yangtze river delta, China. International Journal of Remote Sensing. 33:7609-7628.
Alfieri, J.G., Kustas, W.P., Prueger, J.H., Hipps, L.E., Evett, S.R., Basara, J., Neale, C., French, A.N., Colaizzi, P.D., Agam, N., Chavez, J., Howell, T.A. 2012. On the discrepancy between eddy covariance and lysimetry-based surface flux measurements under strongly advective conditions. Advances in Water Resources. 50:62-78.
Anderson, M.C., Kustas, W.P., Alfieri, J.G., Gao, F.N., Hain, C., Prueger, J.H., Evett, S.R., Colaizzi, P.D., Howell, T.A., Chavez, J. 2012. Mapping daily evapotranspiration at Landsat spatial scales during the BEAREX'08 field campaign. Advances in Water Resources. 50:162-177.
Crow, W.T., Gupta, S.V., Bolten, J. 2012. On the utility of land surface models for agricultural drought monitoring. Hydrology and Earth System Sciences. 16(9):3451-2460.
Crow, W.T., Wagner, W., Naeimi, V. 2010. The impact of radar incidence angle on soil moisture retrieval skill. Geoscience and Remote Sensing Letters. 7(3):501-505.
Heathman, G.C., Cosh, M.H., Merwade, V., Han, E. 2012. Multi-scale temporal stability analysis of surface and subsurface soil moisture within the Upper Cedar Creek Watershed, Indiana. Catena. 95:91-103.
Lang, M.W., McCarty, G.W., Osterling, R.A. 2012. Topographic indices for improved mapping of forested wetlands. Wetlands. 33:141-155.
French, A.N., Alfieri, J.G., Kustas, W.P., Prueger, J.H., Hipps, L.E., Chavez Eguez, J.L., Evett, S.R., Howell, T.A., Gowda, P., Hunsaker, D.J., Thorp, K.R. 2012. Estimation of surface energy fluxes using surface renewal and flux variance techniques over an advective irrigated agricultural site. Advances in Water Resources. 50:91-105. doi:10.1016/j.advwatres.2012.07.007.
Cammalleri, C., Anderson, M.C., Ciraolo, G., D'Urso, G., Kustas, W.P., La Loggia, G., Minacapilli, M. 2012. Practical applications of the remote sensing-based two-source algorithm for mapping surface energy fluxes without in-situ air temperature observations. Remote Sensing of Environment. 124:502-515.
Yilmaz, M.T., Crow, W.T., Anderson, M.C., Hain, C. 2012. An objective methodology for merging satellite and model-based soil moisture products. Water Resources Research. DOI:10.1029/2011WR011682.
Chen, F., Crow, W.T., Holmes, T.R. 2012. Improving long-term, retrospective precipitation datasets using satellite-based surface soil moisture retrievals and the soil moisture analysis rainfall tool (SMART). Journal of Applied Remote Sensing (JARS). 6(1):603-604.
Holmes, T.R., Crow, W.T., Yilmaz, M.T., Jackson, T.J. 2012. Enhancing model-based land surface temperature estimates using multi-platform microwave remote sensing products. Journal of Geophysical Research Atmospheres. 11:577-591.
Entekhabi, D., Reichle, R.H., Crow, W.T., Koster, R.D. 2010. Performance metrics for soil moisture retrievals and applications requirements. Journal of Hydrometeorology. 11:832-840.
Heathman, G.C., Cosh, M.H., Han, E., Jackson, T.J., McKee, L.G., McAfee, S.J. 2012. Field scale spatiotemporal analysis of surface soil moisture for evaluating point-scale in situ networks. Geoderma. 170:195-205.
Nearing, G.S., Crow, W.T., Thorp, K.R., Moran, M.S., Reichle, R., Gupta, H.V. 2012. Assimilating remote sensing observations of leaf area index and soil moisture for wheat yield estimates: An observing system simulation experiment. Water Resources Research. 48 W05525.
Evett, S.R., Kustas, W.P., Gowda, P., Anderson, M.C., Prueger, J.H., Howell, T.A. 2012. Overview of the Bushland Evapotranspiration and Agricultural Remote sensing experiment 2008 (BEAREX08): A field experiment evaluating methods for quantifying ET at multiple scales. Advances in Water Resources. 50:4-19. http://dx.doi.org/10.1016/j.advwatres.2012.03.010.
Colaizzi, P.D., Kustas, W.P., Anderson, M.C., Agam, N., Tolk, J.A., Evett, S.R., Howell, T.A., Gowda, P., O'Shaughnessy, S.A. 2012. Two-source energy balance model estimates of evapotranspiration using component and composite surface temperatures. Advances in Water Resources. 50:134-151. http://dx.doi.org/10.1016/j.advwatres.2012.06.004.
Agam, N., Evett, S.R., Tolk, J.A., Kustas, W.P., Colaizzi, P.D., Alfieri, J.G., McKee, L.G., Copeland, K.S., Howell, T.A., Chavez, J.L. 2012. Evaporative loss from irrigated interrows in a highly advective semi-arid agricultural area. Advances in Water Resources. 50:20-30.
Agam, N., Kustas, W.P., Evett, S.R., Colaizzi, P.D., Cosh, M.H., McKee, L.G. 2012. Soil heat flux variability influenced by row direction in irrigated cotton. Advances in Water Resources. 50:31-40.
Evett, S.R., Agam, N., Kustas, W.P., Colaizzi, P.D., Schwartz, R.C. 2012. Soil profile method for soil thermal diffusivity, conductivity and heat flux: Comparison to soil heat flux plates. Advances in Water Resources. 50:41-54. http://dx.doi.org/10.1016/j.advwatres.2012.04.012.
Hain, C., Crow, W.T., Anderson, M.C., Mecikalski, J. 2012. An EnKF dual assimilation of thermal-infrared and microwave satellite observations of soil moisture into the Noah land surface model. Water Resources Research. DOI: 10.1029/2011WR011268.
Neale, C., Geli, H., Kustas, W.P., Alfieri, J.G., Gowda, P., Evett, S.R., Prueger, J.H., Hipps, L.E., Dulaney, W.P., Chavez, J., French, A.N., Howell, T.A. 2012. Soil water content estimation using a remote sensing based hybrid evapotranspiration modeling approach. Advances in Water Resources. 50:152-161.
Bertoldi, G., Kustas, W.P., Albertson, J.D. 2013. Evaluating source area contributions from aircraft flux measurements over heterogeneous land cover by large eddy simulation. Boundary Layer Meteorology. 147:261-279.
Scanlon, T.M., Kustas, W.P. 2012. Partitioning evapotranspiration using an eddy covariance-based technique: Improved assessment of soil moisture and land-atmosphere exchange dynamics. Vadose Zone Journal. 11:3.
Yilmaz, M.T., Crow, W.T. 2013. The optimality of potential rescaling approaches in land data assimilation. Journal of Hydrometeorology. 14:650-660.
Bolten, J., Crow, W.T. 2012. Improved prediction of quasi-global vegetation conditions using remotely-sensed surface soil moisture. Geophysical Research Letters. 39(19):L19406.
Mladenova, I., Jackson, T.J., Bindlish, R., Henlsey, S. 2013. Incidence angle normalization of radar backscatter data. IEEE Transactions on Geoscience and Remote Sensing. 51:1791-1804.
Du, D., Jackson, T.J., Bindlish, R., Cosh, M.H., Li, L., Hornbuckle, B., Kabela, E. 2012. Effect of dew on aircraft-based passive microwave observations over an agricultural domain. Journal of Applied Remote Sensing (JARS). DOI: 10.1117/1.JRS.6.063571.
Reichle, R.H., Bosilovich, M.G., Crow, W.T., Koster, R.D., Kumar, S.V., Mahanama, S.P., Zaitchik, B.F. 2009. Recent advances in land data assimilation at the NASA Global Modeling and Assimilation Office. In: Pard, S.K., editor. Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications. London, United Kingdom: Springer-Verland. p. 407-428.
Kumar, A., Chen, F., Niyogi, D., Alfieri, J.G., Ek, M.B., Mitchell, K. 2011. Evaluation of a photosyntheses-based canopy resistance formulation in the Noah Land-surface model. Boundary Layer Meteorology. 138:263-284.
Magagi, R., Berg, A., Goita, K., Belair, S., Jackson, T.J., Toth, B., Walker, A., Mcnairn, H., O'Neil, P.E., Moghaddam, M., Gherboudj, I., Colliander, A., Cosh, M.H. 2013. Canadian experiment for soil moisture in 2010 (CanEx-SM10): Overview and preliminary results. IEEE Transactions on Geoscience and Remote Sensing. 51:347-363.