@prefix dcat: . @prefix dct: . @prefix foaf: . @prefix xsd: . a dcat:Dataset ; dct:description """This project aimed to improve the understanding of water and salt movement in lower River Murray floodplains from River Red Gum and Black Box tree ET. This presentation provides an opportunity for salinity managers, environmental water managers, and river managers to be presented with the outcomes emerging from this research project.\r \r Background\r \r In May 2019, under the CSIRO-MDBA (Murray-Darling Basin Authority) Partnership Agreement, a project to quantify total water losses or evapotranspiration (ET) from key floodplain vegetation located over saline groundwater within the Murray-Darling Basin (MDB) began. Lack of woody vegetation ET data has been identified as a significant knowledge gap in the ability to understand and model salt mobilisation in the lower Murray. Numerical models inform management decisions by simulating the movement of water and salt within the floodplain and river channel environment. The aim of this study, therefore, was to provide robust field data of woody vegetation ET, to improve river and saline floodplain management as well as improve the accuracy of ET data used in numerical models. The field data has been used to further develop a model to predict quantified spatial monthly timeseries ET outputs from 2000 onwards, for floodplain trees across the MDB.\r \r Implications of management watering actions field locations have intentionally been selected in areas where there are predicted management actions in the future. This includes salt interception scheme manipulation to vary scheme operation, as well monitoring the influence of environmental flow actions on floodplain vegetation ET and hence response of trees to altered water availability, highlighting tree water stress changes. Sites likely to be responding to environmental flow allocations include the Bookpurnong Red Gum and Black Box, Calperum Red Gum site, Calperum Site 1 and the Lindsay flushed zone site which are likely to have benefited from the 2020 River Murray ‘southern spring flow’. The Lindsay wet site also received water in the adjacent creek in spring/summer 2020 and 2021 related to the southern spring flow. All sites were inundated with the natural River Murray flood event in the summer of 2022-23.\r \r After four years (2019-2024) of monitoring and model refinements, we can present robust data and modelling results of tree ET during managed and natural river flow events. New insights into information about groundwater extraction from tree ET processes on the floodplain will also be shared. Further information is also available in the journal article below and is freely available to access:\r \r Doody TM, Gao S, Vervoort W, Pritchard JL, Davies MJ, Nolan M, Nagler P. 2023. A river basin scale spatial model to advance understanding of riverine tree response to hydrological management. Journal of Environmental Management, 332, https://doi.org/10.1016/j.jenvman.2023.117393\r \r """ ; dct:identifier "a201d673-20b9-4140-bd87-626c268a352c" ; dct:issued "2024-10-16T01:40:15.025827"^^xsd:dateTime ; dct:modified "2024-10-17T01:01:32.798034"^^xsd:dateTime ; dct:publisher ; dct:title "Floodplain Woody Vegetation Evapotranspiration project" ; dcat:distribution , ; dcat:keyword "Basin Salinity Management 2030 strategy", "Evapotranspiration", "Knowledge priority" . a dcat:Distribution ; dct:format "MP4" ; dct:issued "2024-10-17T00:11:55.306018"^^xsd:dateTime ; dct:modified "2024-10-17T01:01:32.803577"^^xsd:dateTime ; dct:title "Outcomes presentation: Floodplain Woody Vegetation Evapotranspiration project" ; dcat:accessURL . a dcat:Distribution ; dct:description "Ecological condition continues to decline in arid and semi-arid river basins globally due to hydrological over-abstraction combined with changing climatic conditions. Whilst provision of water for the environment has been a primary approach to alleviate ecological decline, how to accurately monitor changes in riverine trees at fine spatial and temporal scales, remains a substantial challenge. This is further complicated by constantly changing water availability across expansive river basins with varying climatic zones. Within, we combine rare, fine-scale, high frequency temporal in-situ field collected data with machine learning and remote sensing, to provide a robust model that enables broadscale monitoring of physiological tree water stress response to environmental changes via actual evapotranspiration (ET). Physiological variation of Eucalyptus camaldulensis (River Red Gum) and E. largiflorens (Black Box) trees across 10 study locations in the southern Murray-Darling Basin, Australia, was captured instantaneously using sap flow sensors, substantially reducing tree response lags encountered by monitoring visual canopy changes. Actual ET measurement of both species was used to bias correct a national spatial ET product where a Random Forest model was trained using continuous timeseries of in-situ data of up to four years. Precise monthly AMLETT (Australia-wide Machine Learning ET for Trees) ET outputs in 30 m pixel resolution from 2012 to 2021, were derived by incorporating additional remote sensing layers such as soil moisture, land surface temperature, radiation and EVI and NDVI in the Random Forest model. Landsat and Sentinal-2 correlation results between in-situ ET and AMLETT ET returned R2 of 0.94 (RMSE 6.63 mm period−1) and 0.92 (RMSE 6.89 mm period−1), respectively. In comparison, correlation between in-situ ET and a national ET product returned R2 of 0.44 (RMSE 34.08 mm period−1) highlighting the need for bias correction to generate accurate absolute ET values. The AMLETT method presented here, enhances environmental management in river basins worldwide. Such robust broadscale monitoring can inform water accounting and importantly, assist decisions on where to prioritize water for the environment to restore and protect key ecological assets and preserve floodplain and riparian ecological function." ; dct:format "HTML" ; dct:issued "2024-10-16T01:42:25.260260"^^xsd:dateTime ; dct:modified "2024-10-16T01:42:25.244708"^^xsd:dateTime ; dct:title "A river basin spatial model to quantitively advance understanding of riverine tree response dynamics to water availability and hydrological management" ; dcat:accessURL . a foaf:Agent ; foaf:name "Murray-Darling Basin Authority" .