Other Resources

Key WP documents

• Mul, M., Karimi, P., Coerver, H.M., Pareeth, S., Rebelo, L.M., (2020). Water Productivity and Water Accounting Methodology Manual. Project report, IHE Delft Institute for Water Education, The Netherlands and the International Water Management Institute, Sri Lanka.
• Chukalla, A.D., Mul, M., Tran, B., and Karimi, P. (2020): Standardized protocol for land and water productivity analyses using WaPOR (v1.1). Zenodo. http://doi.org/10.5281/zenodo.4641360
• FAO and IHE Delft, 2019. WaPOR Quality Assessment – technical report on the data quality of the WaPOR Database version 1.0. FAO report, Rome, Italy 
• Molden, D., and Sakthivadivel, R. (1999). Water Accounting to Assess Use and Productivity of Water. International Journal of Water Resources Development 15 (1-2): 55–71.

WP Methodologies

• Chukalla, A.D., Mul, M.L., van der Zaag, P., van Halsema, G., Mubaya, E., Muchanga, E., den Besten, N., and Karimi, P., 2021. A Framework for Irrigation Performance Assessment Using WaPOR data: The case of a Sugarcane Estate in Mozambique, Hydrology and Earth System Sciences, 26, 2759–2778
• Blatchford, M.L., Karimi, P., Bastiaanssen, W.G.M. and Nouri, H., 2018. From global goals to local gains—A framework for crop water productivity. ISPRS international journal of geo-information, 7(11), p.414.
• Bastiaanssen, W.G.M., and Steduto, P. (2016). The Water Productivity Score (WPS) at Global and Regional Level: Methodology and First Results from Remote Sensing Measurements of Wheat, Rice and Maize. Science of the Total Environment. 

WP Applications

• Servia, H., Pareeth, S., Michailovsky, C.I., de Fraiture, C. and Karimi, P., 2022. Operational framework to predict field level crop biomass using remote sensing and data driven models. International Journal of Applied Earth Observation and Geoinformation, 108, p.102725.
• Karimi, P., Bongani, B., Blatchford, M. and de Fraiture, C., 2019. Global satellite-based ET products for the local level irrigation management: An application of irrigation performance assessment in the Sugarbelt of Swaziland. Remote sensing, 11(6), p.705.
• Safi, A.R., Karimi, P., Mul, M., Chukalla, A., de Fraiture, C., 2022. Translating open-source remote sensing data to crop water improvement actions. Agricultural Water Management, 261, 107373

WP reports

• van Steenbergen, F., Mulder, E., Bremer, K., Mul, M., Chukalla, A., Chevalking, S., Deligianni, A., van der Pluijm, L., Deribe, M., 2022. Compendium of Approaches to Improve Water Productivity. Water-PIP technical report series. IHE Delft Institute for Water Education, Delft, the Netherlands.
• Karimi, P., Pareeth, S. 2020. Remote Sensing Based Water Productivity Assessment – NLBC, Karnataka, India. Project report, IHE Delft Institute for Water Education, The Netherlands.
• Chukalla, A.D., Mul, M., van Halsema, G., van der Zaag, P., Uyttendaele, T., Karimi, P., 2020. Water Productivity Analyses Using WaPOR Database. A Case Study in Xinavane, Mozambique. Water-PIP technical report series. IHE Delft Institute for Water Education, Delft, the Netherlands
• Michailovsky, C., Pareeth, S., Karimi, P., Mul, M., 2020. Water Accounting and Productivity for the Selenge River Basin, Mongolia. Project report, IHE Delft Institute for Water Education, The Netherlands.