{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,13]],"date-time":"2026-05-13T04:32:41Z","timestamp":1778646761304,"version":"3.51.4"},"reference-count":79,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T00:00:00Z","timestamp":1605571200000},"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>Conventional calibration methods adopted in hydrological modelling are based on streamflow data measured at certain river sections. However, streamflow measurements are usually sparse and, in such instances, remote-sensing-based products may be used as an additional dataset(s) in hydrological model calibration. This study compares two main calibration approaches: (a) single variable calibration with streamflow and evapotranspiration separately, and (b) multi-variable calibration with both variables together. Here, we used remote sensing-based evapotranspiration data from Global Land Evaporation: the Amsterdam Model (GLEAM ET), and measured streamflow at four stations to calibrate a Soil and Water Assessment Tool (SWAT) and evaluate the performances for Chindwin Basin, Myanmar. Our results showed that when one variable (either streamflow or evapotranspiration) is used for calibration, it led to good performance with respect to the calibration variable but resulted in reduced performance in the other variable. In the multi-variable calibration using both streamflow and evapotranspiration, reasonable results were obtained for both variables. For example, at the basin outlet, the best NSEs (Nash-Sutcliffe Efficiencies) of streamflow and evapotranspiration on monthly time series are, respectively, 0.98 and 0.59 in the calibration with streamflow alone, and 0.69 and 0.73 in the calibration with evapotranspiration alone. Whereas, in the multi-variable calibration, the NSEs at the basin outlet are 0.97 and 0.64 for streamflow and evapotranspiration, respectively. The results suggest that the GLEAM ET data, together with streamflow data, can be used for model calibration in the study region as the simulation results show reasonable performance for streamflow with an NSE &gt; 0.85. Results also show that many different sets of parameter values (\u2018good parameter sets\u2019) can produce results comparable to the best parameter set.<\/jats:p>","DOI":"10.3390\/rs12223768","type":"journal-article","created":{"date-parts":[[2020,11,17]],"date-time":"2020-11-17T07:23:28Z","timestamp":1605597808000},"page":"3768","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":67,"title":["Hydrological Model Calibration with Streamflow and Remote Sensing Based Evapotranspiration Data in a Data Poor Basin"],"prefix":"10.3390","volume":"12","author":[{"given":"T. A. Jeewanthi G.","family":"Sirisena","sequence":"first","affiliation":[{"name":"Department of Coastal and Urban Risk and Resilience, IHE Delft Institute for Water Education, 2611 AX Delft, The Netherlands"},{"name":"Department of Water Engineering and Management, University of Twente, 7522 NB Enschede, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3259-5374","authenticated-orcid":false,"given":"Shreedhar","family":"Maskey","sequence":"additional","affiliation":[{"name":"Department of Water Resources and Ecosystems, IHE Delft Institute for Water Education, 2611 AX Delft, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6234-2063","authenticated-orcid":false,"given":"Roshanka","family":"Ranasinghe","sequence":"additional","affiliation":[{"name":"Department of Coastal and Urban Risk and Resilience, IHE Delft Institute for Water Education, 2611 AX Delft, The Netherlands"},{"name":"Department of Water Engineering and Management, University of Twente, 7522 NB Enschede, The Netherlands"},{"name":"Department of the Harbour, Coastal and Offshore Engineering at Deltares, 2600 MH Delft, The Netherlands"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,17]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Winsemius, H.C., Schaefli, B., Montanari, A., and Savenije, H.H.G. 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