{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,26]],"date-time":"2026-02-26T13:45:56Z","timestamp":1772113556573,"version":"3.50.1"},"reference-count":64,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2022,7,30]],"date-time":"2022-07-30T00:00:00Z","timestamp":1659139200000},"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>We analyzed chlorophyll-a (chl-a) concentrations in shallow, turbid Utah Lake using Landsat data from 1984 to 2021. Utah Lake is ~40 km by 21 km, has a surface area of ~390 km2, an average depth of ~3 m, and loses ~50% of inflow to evaporation. This limits spatial mixing, allowing us to evaluate impacts on smaller lake regions. We evaluated long-term trends at the pixel level and for areas related to boundary conditions. We created 17 study areas based on differences in shoreline development and nutrient inflows. We expected impacted areas to exhibit increasing chl-a trends, as population growth and development in the Utah Lake watershed have been significant. We used the non-parametric Mann\u2013Kendall test to evaluate trends. The majority of the lake exhibited decreasing trends, with a few pixels in Provo and Goshen Bays exhibiting slight increasing or no trends. We estimated trend magnitudes using Sen\u2019s slope and fitted linear regression models. Trend magnitudes in all pixels (and regions), both decreasing and increasing, were small; with the largest decreasing and increasing trends being about \u22120.05 and \u22120.005 \u00b5g\/L\/year, and about 0.1 and 0.005 \u00b5g\/L\/year for the Sen\u2019s slope and linear regression slope, respectively. Over the ~40 year-period, this would result in average decreases of 2 to 0.2 \u00b5g\/L or increases of 4 and 0.2 \u00b5g\/L. All the areas exhibited decreasing trends, but the monthly trends in some areas exhibited no trends rather than decreasing trends. Monthly trends for some areas showed some indications that algal blooms are occurring earlier, though evidence is inconclusive. We found essentially no change in algal concentrations in Utah Lake at either the pixel level or for the analysis regions since the 1980\u2032s; despite significant population expansion; increased nutrient inflows; and land-use changes. This result matches prior research and supports the hypothesis that algal growth in Utah Lake is not limited by direct nutrient inflows but limited by other factors.<\/jats:p>","DOI":"10.3390\/rs14153664","type":"journal-article","created":{"date-parts":[[2022,8,1]],"date-time":"2022-08-01T04:04:00Z","timestamp":1659326640000},"page":"3664","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":16,"title":["A Spatial Long-Term Trend Analysis of Estimated Chlorophyll-a Concentrations in Utah Lake Using Earth Observation Data"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4408-8986","authenticated-orcid":false,"given":"Kaylee Brook","family":"Tanner","sequence":"first","affiliation":[{"name":"Department of Civil and Construction Engineering, Brigham Young University, Provo, UT 84602, USA"}]},{"given":"Anna Catherine","family":"Cardall","sequence":"additional","affiliation":[{"name":"Department of Civil and Construction Engineering, Brigham Young University, Provo, UT 84602, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2781-0738","authenticated-orcid":false,"given":"Gustavious Paul","family":"Williams","sequence":"additional","affiliation":[{"name":"Department of Civil and Construction Engineering, Brigham Young University, Provo, UT 84602, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,7,30]]},"reference":[{"key":"ref_1","unstructured":"Williams, G.P. 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