Global Croplands and Their Water Use for Food Security in the Twenty-first Century

Global climate change is putting unprecedented pressure on global croplands and their water use, vital for ensuring future food security for the world's rapidly expanding human population. The end of the green green revolution (productivity per unit of land) era has meant declining global per capita agricultural production requiring immediate policy responses to safeguard food security amidst global climate change and economic turbulence. Above all, global croplands are water guzzlers, consuming between 60-90% of all human water use. With increasing urbanization, industrialization, and other demands (e.g., bio-fuels) on water there is increasing pressure to reduce agricultural water use by producing more food from existing or even reduced: (a) areas of croplands (more crop per unit area); and (b) quantities of water (more crop per unit of water). Given this background, a critical and urgent question facing humanity in the twenty-first century is, how can we continue to feed the World's ballooning populations in the twenty-first century in a scenario where croplands are decreasing (e.g., taken away for bio-fuels, urbanization), and water use is increasing (e.g., as a result of increasing temperature in a changing climate)?. Our team will look into new and emerging strategies for increasing agricultural productivity which will consider and analyze: i) growing more of crops that consume less water (e.g., more wheat, less rice); ii) increasing water use efficiency leading to a blue revolution ("more crop per drop"; see Liu et al., 2008); iii) educating people to eat less water-consuming food (e.g., more vegetables and grains, less meat; more local and seasonal foods); and iv) emphasizing rainfed crop productivity to reduce stress on water-intensive irrigated croplands (FAO, 2009, Thenkabail, 2010, Thenkabail et al., 2010).

To address the above questions adequately and find solid scientific solutions, we need to fill an existing knowledge gap: the precise estimation of global croplands, their water use, and their locations. At present, the best available data only provide coarse resolution global cropland maps (e.g., Thenkabail et al., 2009a, Thenkabail et al., 2009b, Ramankutty et al., 2008, Goldewijk, 2009, Portman et al., 2009, Ozdogan and Gutman, 2008, Siebert et al., 2006) which have huge uncertainties in: (a) estimating cropland areas, crop types, cropping intensities, and their precise location, and (b) differentiating irrigated areas from rainfed areas. So, the critical questions that will be asked and answered by the 11 leading global researchers on the topic @ the Powell Center will be to carefully consider how we can identify, conceptualize, develop and recommend (by reviewing ongoing work, brainstorming new pathways, creating a knowledge warehouse through series of publications in top journals) methods and techniques for consistent and unbiased estimates of agricultural croplands over space and time by (a) accounting for watering sources (e.g., irrigated, rainfed, other land use/ land cover (LULC)) of croplands, (b) elaborating on cropping intensities over a year, particularly in parts of the world where two or three crops may be grown in one year, but where cropping intensities are not known or recorded in secondary statistics; (c) defining the actual area and spatial distribution of croplands in the world; (d) determining change in croplands extent or intensity (e.g., expansion of croplands into natural vegetation, reduction due to urbanization and biofuels, change in intensity of cropping); and (e) assessing accuracies, errors, and uncertainties.







Publication(s):

Global Food Security Analysis-Support Data at 30 Meters (GFSAD30) Project



Thenkabail, P.S. (2012). Global croplands and their water use for food security in the twenty-first century. Photogrammetric Engineering & Remote Sensing, 78(8), 797-798.



Thenkabail, P.S., Knox, J.W., Ozdogan, M.; Gumma, M.K., Congalton, R.G., Wu, Z., Milesi, C., Finkral, A., Marshall, M., Mariotto, I., You, S., Giri, C., and Nagler, P. (2012). Assessing future risks to agricultural productivity, water resources and food security: How can remote sensing help? Photogrammetric Engineering and Remote Sensing, Special Issue: Global Cropland, 78(8), 773-782.



Thenkabail, P.S., Mariotto, I., Gumma, M.K., Middleton, E.M., Landis, and D.R., Huemmrich, F.K. (2013). Selection of hyperspectral narrowbands (HNBs) and composition of hyperspectral twoband vegetation indices (HVIs) for biophysical characterization and discrimination of crop types using field reflectance and Hyperion/EO-1 data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol. 6, No. 2, April 2013 doi: 10.1109/JSTARS.2013.2252601



Thenkabail, P.S., and Wu, Z. (2012). An Automated Cropland Classification Algorithm (ACCA) for Tajikstan by Combining Landsat, MODIS, and Secondary Data: Remote Sensing, 4(10), 2890-2918. doi: 10.3390/rs4102890