{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T21:50:38Z","timestamp":1780523438197,"version":"3.54.1"},"reference-count":69,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2020,7,4]],"date-time":"2020-07-04T00:00:00Z","timestamp":1593820800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Traditional watershed modeling often overlooks the role of vegetation dynamics. There is also little quantitative evidence to suggest that increased physical realism of vegetation dynamics in process-based models improves hydrology and water quality predictions simultaneously. In this study, we applied a modified Soil and Water Assessment Tool (SWAT) to quantify the extent of improvements that the assimilation of remotely sensed Leaf Area Index (LAI) would convey to streamflow, soil moisture, and nitrate load simulations across a 16,860 km2 agricultural watershed in the midwestern United States. We modified the SWAT source code to automatically override the model\u2019s built-in semiempirical LAI with spatially distributed and temporally continuous estimates from Moderate Resolution Imaging Spectroradiometer (MODIS). Compared to a \u201cbasic\u201d traditional model with limited spatial information, our LAI assimilation model (i) significantly improved daily streamflow simulations during medium-to-low flow conditions, (ii) provided realistic spatial distributions of growing season soil moisture, and (iii) substantially reproduced the long-term observed variability of daily nitrate loads. Further analysis revealed that the overestimation or underestimation of LAI imparted a proportional cascading effect on how the model partitions hydrologic fluxes and nutrient pools. As such, assimilation of MODIS LAI data corrected the model\u2019s LAI overestimation tendency, which led to a proportionally increased rootzone soil moisture and decreased plant nitrogen uptake. With these new findings, our study fills the existing knowledge gap regarding vegetation dynamics in watershed modeling and confirms that assimilation of MODIS LAI data in watershed models can effectively improve both hydrology and water quality predictions.<\/jats:p>","DOI":"10.3390\/rs12132148","type":"journal-article","created":{"date-parts":[[2020,7,6]],"date-time":"2020-07-06T09:49:11Z","timestamp":1594028951000},"page":"2148","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":53,"title":["Watershed Modeling with Remotely Sensed Big Data: MODIS Leaf Area Index Improves Hydrology and Water Quality Predictions"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2302-1421","authenticated-orcid":false,"given":"Adnan","family":"Rajib","sequence":"first","affiliation":[{"name":"Department of Environmental Engineering, Frank H. Dotterweich College of Engineering, Texas A&amp;M University, 917 W Ave B, Kingsville, TX 78363, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"I Luk","family":"Kim","sequence":"additional","affiliation":[{"name":"Rosen Center for Advanced Computing, Purdue University, West Lafayette, IN 47907, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5501-9444","authenticated-orcid":false,"given":"Heather E.","family":"Golden","sequence":"additional","affiliation":[{"name":"U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH 45220, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0066-8919","authenticated-orcid":false,"given":"Charles R.","family":"Lane","sequence":"additional","affiliation":[{"name":"U.S. Environmental Protection Agency, Office of Research and Development, Cincinnati, OH 45220, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8797-9482","authenticated-orcid":false,"given":"Sujay V.","family":"Kumar","sequence":"additional","affiliation":[{"name":"NASA Goddard Space Flight Center, Hydrological Sciences Laboratory, Greenbelt, MD 20771, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiqiang","family":"Yu","sequence":"additional","affiliation":[{"name":"Civica Infrastructure Inc., Vaughan, ON L6A 4P5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Saranya","family":"Jeyalakshmi","sequence":"additional","affiliation":[{"name":"Department of Civil and Environmental Engineering, University of Windsor, ON N9B 3P4, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2465","DOI":"10.1098\/rspa.2002.0986","article-title":"Towards a Coherent Philosophy for Environmental Modelling","volume":"458","author":"Beven","year":"2002","journal-title":"Royal Soc."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"6534","DOI":"10.1029\/2018WR023692","article-title":"Information Theory for Model Diagnostics: Structural Error is Indicated by Trade-Off Between Functional and Predictive Performance","volume":"55","author":"Ruddell","year":"2019","journal-title":"Water Resour. 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