## Methods and Data
### Data Sources and Processing  
The AWAP datasets concern the terrestrial water balance across continental Australia and are developed by the Australian Water Availability Project (AWAP, [[http://www.csiro.au/awap](http://www.csiro.au/awap)]([http://www.csiro.au/awap](http://www.csiro.au/awap))) Team and the CSIRO Marine and Atmospheric Research using the WaterDyn model. They include a long-term historical monthly time series (data set \"Run 26m\", 1900 to 2017) of the conventional water balance components at a spatial resolution of 0.05\({}^{\circ}\)[24]. These datasets have been widely used in research on water resource management in Australia and can be viewed as referenced or observational data to evaluate the other types of water balance components [25]. The water balance components (in mm mon\({}^{-1}\)) of the MRC from 2001 to 2016, including precipitation, ET, runoff, and soil water storage changes were obtained from these datasets. The four other ET products selected for comparative analysis include ET from CSIRO, GLDAS, MODIS, and TerraClimate. The CSIRO ET is a monthly global ET product developed by the CSIRO [26]. The estimates are computed through the observation-driven Penman-Monteith-Leuning (PML) model. The GLDAS ET is the GLDAS-2.1 ET product, which is one of two components of the GLDAS Version 2 (GLDAS-2) dataset and is developed with the advanced land surface modeling and data assimilation techniques utilising satellite and ground-based observational data products [27]. The MODIS ET is the MOD16A2 Version 6 Evapotranspiration/Latent Heat Flux product and is an 8-day composite product produced at 500-metrepixel resolution [28]. The algorithm used for the MOD16 data product collection is based on the logic of the Penman-Monteith equation, which includes inputs of daily meteorological reanalysis data along with MODIS remotely sensed data products such as vegetation property dynamics, albedo, and land cover. The TerraClimate ET is the actual evapotranspiration of TerraClimate dataset and is derived using a one-dimensional soil water balance model [29]. TerraClimate is a dataset of monthly climate and climatic water balance for global terrestrial surfaces. It uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser spatial resolution of 2.5\({}^{\circ}\). Other data used in this study include irrigation information, ecosystem data, and land cover data. The irrigation information was obtained from farm survey reports from ABARE, which is the only national farm survey information source in Australia. As one of the most important indicators of ecosystem function and closely related to water use, the GPP was selected for ecosystem assessment. The GPP data is the MOD17A3 V055 product, which provides information about annual GPP at 1 km pixel resolution [30]. In addition, we used the current release of the second version of the Dynamic Land Cover Dataset (DLCDv2.1) as a basis for water balance analyses [21]. The land cover classification scheme conforms to the 2007 International Standards Organisation (ISO) land cover standard (19144-2). Figure 2: The location of the Murrumbidgee River catchment (MRC) and its topography and land cover. In this dataset Australian land covers are clustered into 22 classes, ranging from cultivated and managed land cover to natural land cover. The data presents land cover information for every 250 m by 250 m area of the country at a two-year interval. In accord with our research aim in this study, we combined these 22 land cover types into 7 types: bare surface, water bodies/wet land, irrigated agriculture, rain-fed agriculture, grassland, forest, and urban area. Then, we uniformly resampled and adjusted resolution of the spatial data (except AWAP data set and CSIRO ET) to 500 m and projection and temporal resolutions (annual and monthly) to make the data products comparable using the Google Earth Engine (GEE).