Large-scale land restoration improved drought resilience in Ethiopia’s degraded watersheds

  • Sutton, P. C., Anderson, S. J., Costanza, R. & Kubiszewski, I. The ecological economics of land degradation: impacts on ecosystem service values. Ecol. Econ. 126, 182–192 (2016).

    Article 

    Google Scholar
     

  • Burrell, A. L., Evans, J. P. & De Kauwe, M. G. Anthropogenic climate change has driven over 5 million km2 of drylands towards desertification. Nat. Commun. 11, 3853 (2020).

    CAS 
    Article 

    Google Scholar
     

  • Reynolds, J. F. et al. Global desertification: building a science for dryland development. Science 316, 847–651 (2007).

    CAS 
    Article 

    Google Scholar
     

  • Nkonya, E. et al. in Economics of Land Degradation and Improvement—A Global Assessment for Sustainable Development (eds Nkonya, E. et al.) 117–165 (Springer, 2016).

  • Barbier, E. B. & Hochard, J. P. Does land degradation increase poverty in developing countries? PloS ONE 11, e0152973 (2016).

    Article 

    Google Scholar
     

  • Chonabayashi, S., Jithitikulchai, T. & Qu, Y. Does agricultural diversification build economic resilience to drought and flood? Evidence from poor households in Zambia. Afr. J. Agric. Resour. Econ. 15, 65–80 (2020).


    Google Scholar
     

  • Sustainable Land Management: Challenges, Opportunities and Trade-offs (World Bank, 2006).

  • Sustainable Land Management and Restoration in the Middle East and North Africa Region—Issues, Challenges, and Recommendations (World Bank, 2019).

  • Schmidt, E. & Tadesse, F. The impact of sustainable land management on household crop production in the Blue Nile Basin, Ethiopia. Land Degrad. Dev. 30, 777–787 (2018).

    Article 

    Google Scholar
     

  • Gashaw, T., Bantider, A. & G/Silassie, H. Land degradation in Ethiopia: causes, impacts and rehabilitation techniques. J. Environ. Earth Sci. 4, 98–104 (2014).


    Google Scholar
     

  • The Cost of Land Degradation in Ethiopia: A Review of Past Studies (World Bank, 2007).

  • Agriculture, Forestry, and Fishing, Value Added (% of GDP)—Ethiopia (World Bank, accessed 11 March 2021); https://data.worldbank.org/indicator/NV.AGR.TOTL.ZS?locations=ET

  • Rural Population (% of Total Population)—Ethiopia (World Bank, accessed 11 March 2021); https://data.worldbank.org/indicator/SP.RUR.TOTL.ZS?locations=ET

  • Gessesse, G. D., Tamene, L., Abera, W., Amede, T. & A, W. Effects of land management practices and land cover types on soil loss and crop productivity in Ethiopia: a review. Int. Soil Water Conserv. Res. 9, 544–554 (2021).

    Article 

    Google Scholar
     

  • Abera, W. et al. Characterizing and evaluating the impacts of national land restoration initiatives on ecosystem services in Ethiopia. Land Degrad. Dev. 31, 37–52 (2019).

    Article 

    Google Scholar
     

  • Project Appraisal Document on a Proposed Grant in the Amount US$20.0 Million and a Proposed Grant from the Global Environmental Facility Trust Fund in the Amount of US$9.0 Million to the Federal Democratic Republic of Ethiopia for a Sustainable Land Management Project Report No. 42927-ET (World Bank, 2008).

  • Project Appraisal Document on a Proposed Credit in the Amount of SDR32.6 Million and a Proposed Grant from the Global Environment Facility Trust Fund in the Amount of US$8.33 Million and a Proposed Grant from the Least Developed Countries Fund Trust Fund in the Amount of US$4.62 Million and a Proposed Grant from the Ethiopia Sustainable Land Management Project Trust Fund in the Amount of US$42.65 Million to the Federal Democratic Republic of Ethiopia for a Sustainable Land Management Project II (SLMP-2) Report No. PAD525 (World Bank, 2013).

  • Implementation Completion and Results Report (IDA-H3770 TF-92320) on a Grant in the Amount of SDR12.5 Million (US$20.0 Million Equivalent) and a Global Environmental Facility Grant in the Amount of US$9.0 Million to the Federal Democratic Republic of Ethiopia for a Sustainable Land Management Project Report No. ICR3074 (World Bank, 2014).

  • Implementation Completion and Results Report (IDA-53180/TF15838/TF15868/TF15869) on a Credit in the Amount of SDR32.6 Million (US$50 Million Equivalent) and a Grant from the Global Environment Facility Trust Fund in the Amount of US$8.33 Million and a Grant from the Least Developed Countries Fund Trust Fund in the Amount of US$4.62 Million and a Grant from the Ethiopia Sustainable Land Management Project Trust Fund (Norway) in the Amount of US$42.65 Million to the Federal Democratic Republic of Ethiopia for a Sustainable Land Management Project Report No. ICR00004449 (World Bank, 2019).

  • Huete, A. et al. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sens. Environ. 83, 195–213 (2002).

    Article 

    Google Scholar
     

  • Li, X. & Xiao, J. Mapping photosynthesis solely from solar-induced chlorophyll fluorescence: a global, fine-resolution dataset of gross primary production derived from OCO-2. Remote Sens. 11, 2563 (2019).

    Article 

    Google Scholar
     

  • Rouse, J. W., Haas, R. H., Schell, J. A. & Deering, D. W. Monitoring vegetation systems in the Great Plains with ERTA. In Proc. Third Earth Reserves Technology Satellite Symposium (eds Freden, S. C. et al.) 309–317 (NASA, 1974).

  • Tucker, C. J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sens. Environ. 8, 127–150 (1979).

    Article 

    Google Scholar
     

  • Song, X. P. et al. Global land change from 1982 to 2016. Nature 560, 639–643 (2018).

    CAS 
    Article 

    Google Scholar
     

  • Anderson, W. & Johnson, T. in Economics of Land Degradation and Improvement—A Global Assessment for Sustainable Development (eds Nkonya, E. et al.) 85–116 (Springer, 2016).

  • De Jong, R., De Bruin, S., Schaepman, M. & Dent, D. Quantitative mapping of global land degradation using Earth observations. Int. J. Remote Sens. 32, 6823–6853 (2008).

    Article 

    Google Scholar
     

  • Bai, C. G., Dent, D. L., Olsson, L. & Schaepman, M. E. Proxy global assessment of land degradation. Soil Use Manage. 24, 223–234 (2008).

    Article 

    Google Scholar
     

  • Frankenberg, C. et al. New global observations of the terrestrial carbon cycle from GOSAT: patterns of plant fluorescence with gross primary productivity. Geophys. Res. Lett. 38, L17706 (2011).

    Article 

    Google Scholar
     

  • Joiner, J. et al. First observations of global and seasonal terrestrial chlorophyll fluorescence from space. Biogeosciences 8, 637–651 (2011).

    CAS 
    Article 

    Google Scholar
     

  • Mohammed, G. H. et al. Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress. Remote Sens. Environ. 231, 111177 (2019).

    Article 

    Google Scholar
     

  • Porcar-Castell, A. et al. Linking chlorophyll a fluorescence to photosynthesis for remote sensing applications: mechanisms and challenges. J. Exp. Bot. 65, 4065–4095 (2014).

    CAS 
    Article 

    Google Scholar
     

  • Gu, L., Han, J., Wood, J. D., Chang, C. Y. & Sun, Y. Sun-induced Chl fluorescence and its importance for biophysical modeling of photosynthesis based on light reactions. N. Phytol. 223, 1179–1191 (2019).

    CAS 
    Article 

    Google Scholar
     

  • Guanter, L. et al. Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence. Proc. Natl Acad. Sci. USA 111, E1327–E1333 (2014).

    CAS 

    Google Scholar
     

  • Joiner, J. et al. Global monitoring of terrestrial chlorophyll fluorescence from moderate-spectral-resolution near-infrared satellite measurements: methodology, simulations, and application to GOME-2. Atmos. Meas. Tech. 6, 2803–2823 (2013).

    Article 

    Google Scholar
     

  • Sun, Y. et al. OCO-2 advances photosynthesis observation from space via solar-induced chlorophyll fluorescence. Science 358, eaam5747 (2017).

    Article 

    Google Scholar
     

  • Sun, Y. et al. Overview of solar-induced chlorophyll fluorescence (SIF) from the Orbiting Carbon Observatory-2: Retrieval, cross-mission comparison, and global monitoring for GPP. Remote Sens. Environ. 209, 808–823 (2018).

    Article 

    Google Scholar
     

  • Guan, K. et al. Improving the monitoring of crop productivity using spaceborne solar-induced fluorescence. Glob. Change Biol. 22, 716–726 (2016).

    Article 

    Google Scholar
     

  • He, L. et al. From the ground to space: using solar-induced chlorophyll fluorescence to estimate crop productivity. Geophys. Res. Lett. 47, e2020GL087474 (2020).


    Google Scholar
     

  • Ali, D. A., Deininger, K. & Monchuk, D. Using satellite imagery to assess impacts of soil and water conservation measures: evidence from Ethiopia’s Tana-Beles watershed. Ecol. Econ. 169, 106512 (2020).

    Article 

    Google Scholar
     

  • Climate Data: Standardized Precipitation Index (SPI) (NCAR, accessed 15 September 2021); https://climatedataguide.ucar.edu/climate-data/standardized-precipitation-index-spi

  • East Africa: Ethiopia (FEWS NET, accessed 12 January 2021); https://fews.net/east-africa/ethiopia

  • Agricultural Sample Survey 2012/13 (2005 E.C) Volume V, Report on Area and Production of Belg Season Crops for Private Peasant Holdings (Federal Democratic Republic of Ethiopia Central Statistical Agency, 2013).

  • Agricultural Sample Survey 2007/08 (2000 E.C) Volume V, Report on Area and Production of Belg Season Crops for Private Peasant Holdings (Federal Democratic Republic of Ethiopia Central Statistical Agency, 2008).

  • Wen, J. et al. A framework for harmonizing multiple satellite instruments to generate a long-term global high spatial-resolution solar-induced chlorophyll fluorescence (SIF). Remote Sens. Environ. 239, 111644 (2020).

    Article 

    Google Scholar
     

  • Ethiopia Sentinel2 Land Use Land Cover 2016 (RCMRD, 2018); http://geoportal.rcmrd.org/layers/servir%3Aethiopia_sentinel2_lulc2016

  • Burke, M., Driscoll, A., Lobell, D. B. & Ermon, S. Using satellite imagery to understand and promote sustainable development. Science 371, eabe8628 (2021).

    CAS 
    Article 

    Google Scholar
     

  • Lobell, D. B., Thau, D., Seifert, C., Engle, E. & Little, B. A scalable satellite-based crop yield mapper. Remote Sens. Environ. 164, 324–333 (2015).

    Article 

    Google Scholar
     

  • Lobell, D. B. et al. Eyes in the sky, boots on the ground: assessing satellite- and ground-based approaches to crop yield measurement and analysis. Am. J. Agric. Econon. 102, 202–219 (2019).

  • Li, X. & J, X. A global, 0.05-degree product of solar-induced chlorophyll fluorescence derived from OCO-2, MODIS, and reanalysis data. Remote Sens. 11, 517 (2019).

    Article 

    Google Scholar
     

  • Funk, C. C. et al. A Quasi-Global Precipitation Time Series for Drought Monitoring (USGS, 2014).

  • Hersbach, H. et al. ERA5 Monthly Averaged Data on Single Levels from 1979 to Present (Copernicus Climate Change Service, 2019); https://doi.org/10.24381/cds.f17050d7

  • Yamazaki, D. et al. MERIT DEM: a new high-accuracy global digital elevation model and its merit to global hydrodynamic modeling. In: American Geophysical Union, Fall Meeting 2017 abstr. H12C-04 (2017).

  • Hengl, T. et al. Mapping soil properties of Africa at 250 m resolution: random forests significantly improve current predictions. PLoS ONE 10, e0125814 (2015).

    Article 

    Google Scholar
     

  • Sebastian, K. Agro-ecological Zones of Africa (International Food Policy Research Institute, 2009).

  • Pérez-Hoyos, A. Global Crop and Rangeland Masks (JRC, 2018); http://data.europa.eu/89h/jrc-10112-10005