CMRSET (CSIRO MODIS ReScaled EvapoTranspiration) monthly actual evapotranspiration (ETa) estimates at 500 m resolution for the canal commands in the Indus Basin Irrigated System (IBIS) in Pakistan from March 2000 to December 2018

Brief description

Monthly actual evapotranspiration (ETa) computed with the CMRSET model at 500 m resolution. The monthly data spans from March 2000 to December 2018. The data is geographically limited to the area subtended by the 48 main canal commands in the IBIS. The data was produced to support water resources assessments and the IBIS water balance (see e.g. Ahmad et al., 2020). The format is in unsigned 16 bit integer GeoTIFF in the WGS 1984 World Mercator projected coordinate system and uses a scaling factor of 100 (i.e. divide by 100 to obtain ETa in mm per month).
Lineage: ETa estimates for the IBIS were computed on a 10-day basis via the CMRSET ETa model 2a (Guerschman et al., 2009), from 24 February 2000 to 31 December 2018 (Peña-Arancibia et al., 2020) and then aggregated to monthly. The parameters used had the following values: Kc_max=1.00, a=14.42, α=2.701, b=2.086, β=0.953. The IBIS ETa estimates used 10-day cloud free EVI and GVMI composites obtained via Google Earth Engine (Gorelick et al., 2017) from the daily Moderate Resolution Imaging Spectroradiometer (MODIS) surface spectral reflectance product (MOD09GA collection 6, Vermote and Wolfe, 2015) to obtain a crop factor which is the scaled by reference evapotranspiration (ET0). ET0 was estimated using the Hargreaves (1974) equation from a combination of local gridded ~2.5 km temperature analysis and post-processed GLDAS ~25 km reanalysis data (see Peña-Arancibia et al., 2020 for details; Rodell et al., 2004).

References

Ahmad, M. D., J. L. Peña Arancibia, J. P. Stewart, and J. M. Kirby (2020), Water balance trends in irrigated canal commands and its implications for sustainable water management in Pakistan: Evidence from 1981 to 2012, Agricultural Water Management, http://doi.org/10.1016/j.agwat.2020.106648
Cheema, M. J. M. (2012), Understanding water resources conditions in data scarce river basins using intelligent pixel information: Transboundary Indus Basin, Technische Universiteit Delft,http://resolver.tudelft.nl/uuid:7b569411-9934-4b23-b631-36a58f60363f, last access: July 2020.
Gorelick, N., M. Hancher, M. Dixon, S. Ilyushchenko, D. Thau, and R. Moore (2017), Google Earth Engine: Planetary-scale geospatial analysis for everyone, Remote Sensing of Environment, 202, 18-27, http://doi.org/10.1016/j.rse.2017.06.031
Guerschman, J. P., A. I. J. M. Van Dijk, G. Mattersdorf, J. Beringer, L. B. Hutley, R. Leuning, R. C. Pipunic, and B. S. Sherman (2009), Scaling of potential evapotranspiration with MODIS data reproduces flux observations and catchment water balance observations across Australia, Journal of Hydrology, 369(1-2), 107-119, http://doi.org/10.1016/j.jhydrol.2009.02.013
Hargreaves, G. H. (1974), Estimation of Potential and Crop Evapotranspiration, Transactions of the ASAE, 17(4), 701-704, http://doi.org/10.13031/2013.30184
Peña-Arancibia, J. L., M. D. Ahmad, J. M. Kirby, and M. J. M. Cheema (2020), Remotely sensed time-series (2000‒2018) estimation of evapotranspiration in the Indus Basin: Implementation, evaluation and analysis 34 pp, CSIRO, Australia, https://publications.csiro.au/publications/#publication/PIcsiro:EP20787, last access: July 2020.
Rodell, M., et al. (2004), The global land data assimilation system, Bulletin of the American Meteorological Society, 85(3), http://doi.org/10.1175/bams-85-3-381
Vermote, E., and R. Wolfe (2015), MOD09GA MODIS/Terra Surface Reflectance Daily L2G Global 1km and 500m SIN Grid V006 [Data set].