Investigating the Reliability of Irrigated Area Coverages from Fragmented Lands: The case of Tigray, Northern Ethiopia.

Year 2020, Volume: 7 Issue: 2, 172 - 183, 15.08.2020

Filmon Tquabo Gebremariam , Solomon Habtu Yemane Adane Tesfa-alem Gebreegziabher Negasi Solomon Eyasu Yazew

https://doi.org/10.30897/ijegeo.655595

Abstract

Consistent and well-timed information regarding the extent of irrigated areas is very important for the development of the agricultural sector. This study investigated the reliability of traditional estimates of irrigated area coverages from three micro-dam irrigation schemes. High resolution Google Earth (GE) and medium resolution satellite imagery coupled with an intensive ground survey were employed to determine irrigation area coverages. Landsat-8 image pre-processing and classification was carried out in ENVI 5.0 software. In comparison to the Landsat-8 based estimates, the traditional method over-estimated 87% of the total 14 cases considered. The level of discrepancies in scheme area coverages range from a minimum of -20% (underestimated) to a maximum of 224%. Besides this, the traditional estimates were ranging from -1.8 to 238% of GE-based estimates. Whereas, the Landsat-8 based estimates slightly overestimated it by 1.8% -16% of GE-based estimates. On the other hand, the traditional estimates tend to underestimate/ignore crops with smaller area coverages and overestimate crops with relatively larger area coverages. The results hinted that the using medium and low resolution satellite imagery could improve the data collection and reporting from irrigated agriculture in developing countries.

Keywords

Irrigated area, Landsat-8, Remote sensing, ethiopia

Supporting Institution

Mekelle University

Project Number

MU/RECURRENTBUDGET/24/2017

References

• Abdurahman, M. A. (2009). Assessment of micro-dam irrigation projects and runoff predictions for ungauged catchments in Northern Ethiopia 2009.
• Addis, K. (2009). Drought and famine: Ethiopia's cycle continues. Time Magazine, 15.
• Adler-Golden, S. M., Matthew, M. W., Bernstein, L. S., Levine, R. Y., Berk, A., Richtsmeier, S. C., . . . Burke, H.-h. K. (1999). Atmospheric correction for shortwave spectral imagery based on MODTRAN4 (Vol. 3753): SPIE.
• Ajaz, A., Karimi, P., & de Fraiture, C. (2016). National and global censuses or satellite-based estimates? Asia’s irrigated areas: In a muddle.
• Ambika, A. K., Wardlow, B. D., & Mishra, V. (2016). Data descriptor: Remotely sensed high resolution irrigated area mapping in india for 2000 to 2015.
• AQUASTAT, F. (2015). Country fact sheet: Ethiopia. Retrieved from
• Awulachew, S. B., Yilma, A. D., Loulseged, M., Loiskandl, W., Ayana, M., & Alamirew, T. (2007). Water resources and irrigation development in Ethiopia (Vol. 123): Iwmi.
• Berhane, G., Amare, M., Gebreyohannes, T., & Walraevens, K. (2017). Geological and geophysical investigation of water leakage from two micro-dam reservoirs: Implications for future site selection, northern Ethiopia. Journal of African Earth Sciences, 129, 82-93.
• Berhane, G., Martens, K., Al Farrah, N., & Walraevens, K. (2013). Water leakage investigation of micro-dam reservoirs in Mesozoic sedimentary sequences in Northern Ethiopia. Journal of African Earth Sciences, 79, 98-110.
• Bewket, W., & Conway, D. (2007). A note on the temporal and spatial variability of rainfall in the drought‐prone Amhara region of Ethiopia. International Journal of Climatology: A Journal of the Royal Meteorological Society, 27(11), 1467-1477.
• Biggs, T. W., Thenkabail, P. S., Gumma, M. K., Scott, C. A., Parthasaradhi, G. R., & Turral, H. N. (2006). Irrigated area mapping in heterogeneous landscapes with MODIS time series, ground truth and census data, Krishna Basin, India. International Journal of Remote Sensing, 27(19), 4245-4266. doi:10.1080/01431160600851801
• Brouwer, C., & Heibloem, M. (1986). Irrigation water management: Irrigation water needs. Training manual, 3.
• Cai, X., Magidi, J., Nhamo, L., & van Koppen, B. (2017). Mapping irrigated areas in the Limpopo Province, South Africa (Vol. 172): International Water Management Institute (IWMI).
• Carletto, C., Jolliffe, D., & Banerjee, R. (2013). The Emperor has no data! Agricultural statistics in sub-Saharan Africa. World Bank Working Paper. Crook, F. W. (1993). Underreporting of China’s cultivated land area: Implications for world agricultural trade. China International Agricultural and Trade Report, 33-39.
• Eyasu, Y. (2005). Development and management of irrigated lands in Tigray, Ethiopia: Balkema.
• FAO. (1996). The State of Food and Agriculture, . Retrieved from Roma, Italy:
• FAO. (2008). The Agricultural Bulletin Board on Data Collection, Dissemination and Quality of Statistics. Retrieved from
• FAO. (2012). Food and Agriculture Organization of the United Nations. 2012. FAO statistical yearbook.
• Forkuor, G., Conrad, C., Thiel, M., Zoungrana, B. J.-B., & Tondoh, J. E. (2017). Multiscale Remote Sensing to Map the Spatial Distribution and Extent of Cropland in the Sudanian Savanna of West Africa. Remote Sensing, 9(8), 839.
• Fritz, S., See, L., & Rembold, F. (2010). Comparison of global and regional land cover maps with statistical information for the agricultural domain in Africa. International Journal of Remote Sensing, 31(9), 2237-2256. doi:10.1080/01431160902946598
• Frolking, S., Xiao, X., Zhuang, Y., Salas, W., & Li, C. (1999). Agricultural land-use in China: a comparison of area estimates from ground-based census and satellite-borne remote sensing. Global Ecology and Biogeography, 8(5), 407-416. doi:10.1046/j.1365-2699.1999.00157.x
• Gebregziabher, G., Namara, R. E., & Holden, S. (2012). Technical Efficiency of Irrigated and Rain-Fed Smallholder Agriculture in Tigray, Ethiopia: A Comparative Stochastic Frontier Production Function Analysis51, 203-226. Retrieved from http://ageconsearch.umn.edu/record/155477/files/1_Gebregziabher.pdf doi:ISSN 0049-8599
• Ghebreamlak, A., Tanakamaru, H., Tada, A., Ahmed Adam, B., & Elamin, K. (2018). Satellite-Based Mapping of Cultivated Area in Gash Delta Spate Irrigation System, Sudan. Remote Sensing, 10(2), 186.
• Giordano, M. (2009). Global Groundwater? Issues and Solutions. Annual Review of Environment and Resources, 34(1), 153-178. doi:10.1146/annurev.environ.030308.100251
• Gleixner, S., Keenlyside, N., Viste, E., & Korecha, D. (2017). The El Niño effect on Ethiopian summer rainfall. Climate Dynamics, 49(5), 1865-1883. doi:10.1007/s00382-016-3421-z
• Gumma, M. K., Mohanty, S., Nelson, A., Arnel, R., Mohammed, I. A., & Das, S. R. (2015). Remote sensing based change analysis of rice environments in Odisha, India. Journal of Environmental Management, 148, 31-41. doi:https://doi.org/10.1016/j.jenvman.2013.11.039
• Hagos, E. Y., Schultz, B., & Depeweg, H. (2016). Reservoir Operation in View of Effective Utilization of Limited Water in Semi-Arid Areas The Case of Gumsalasa Earthen Dam Irrigation Scheme in Tigray, Ethiopia. Irrigation and Drainage, 65(3), 294-307. doi:10.1002/ird.1968
• Heller, E., Rhemtulla, J. M., Lele, S., Kalacska, M., Badiger, S., Sengupta, R., & Ramankutty, N. (2012). Mapping crop types, irrigated areas, and cropping intensities in heterogeneous landscapes of Southern India using multi-temporal medium-resolution imagery. Photogrammetric Engineering & Remote Sensing, 78(8), 815-827.
• IMF. (2016). Article IV Consultation—Press Release; Staff Report; and Statement by the Executive Director for The Federal Democratic Republic of Ethiopia (IMF Country Report No. 16/322). Retrieved from Washington, D.C.:
• Jacobson, A., Dhanota, J., Godfrey, J., Jacobson, H., Rossman, Z., Stanish, A., . . . Riggio, J. (2015). A novel approach to mapping land conversion using Google Earth with an application to East Africa. Environmental Modelling & Software, 72, 1-9.
• Knorn, J., Rabe, A., Radeloff, V. C., Kuemmerle, T., Kozak, J., & Hostert, P. (2009). Land cover mapping of large areas using chain classification of neighboring Landsat satellite images. Remote Sensing of Environment, 113(5), 957-964.
• Luedeling, E., & Buerkert, A. (2008). Typology of oases in northern Oman based on Landsat and SRTM imagery and geological survey data. Remote Sensing of Environment, 112(3), 1181-1195. doi:https://doi.org/10.1016/j.rse.2007.08.007
• Malarvizhi, K., Kumar, S. V., & Porchelvan, P. (2016). Use of High Resolution Google Earth Satellite Imagery in Landuse Map Preparation for Urban Related Applications. Procedia Technology, 24, 1835-1842. doi:https://doi.org/10.1016/j.protcy.2016.05.231
• Mandefro, H. (2016). Politics by numbers: poverty reduction discourse, contestations and regime legitimacy in Ethiopia. International Review of Sociology, 26(3), 386-406. doi:10.1080/03906701.2016.1244928
• MOFED. (2010a). Ethiopia: 2010 MDGs Report: Trends and Prospects for Meeting MDGs by 2015. Retrieved from http://www.et.undp.org/content/dam/ethiopia/docs/2010%20Ethiopia%20MDG%20Report.pdf
• MOFED. (2010b). Growth and Transformation Plan (GTP). 2010/11–2014/15. In: MoFED, FDRE Addis Ababa.
• Murthy Reddi, V. R., Gumma, M. K., Pyla, K. R., Eadara, A., & Gummapu, J. S. (2017). Monitoring Changes in Croplands Due to Water Stress in the Krishna River Basin Using Temporal Satellite Imagery. Land, 6(4), 72.
• Negeri, M. B. (2017). The Effects of El Nino on Agricultural GDP of Ethiopia. American Journal of Water Science and Engineering, 3(4), 45-49.
• Nickum, J. E. (2003). Irrigated Area Figures as Bureaucratic Construction of Knowledge: The Case of China. International Journal of Water Resources Development, 19(2), 249-262. doi:10.1080/0790062032000089347
• Oates, N., Hisberg, A., Rodríguez Ros, J., Solomon, H., Ludi, E., Marlet, S., & Jamin, J.-Y. The Implications of State Intervention for Self-Governed Irrigation Schemes: Insights From Tigray, Ethiopia. Irrigation and Drainage, 0(0). doi:10.1002/ird.2121
• Ozdogan, M., Yang, Y., Allez, G., & Cervantes, C. (2010). Remote Sensing of Irrigated Agriculture: Opportunities and Challenges. Remote Sensing, 2(9), 2274-2304.
• Pandey, B., & Seto, K. C. (2015). Urbanization and agricultural land loss in India: Comparing satellite estimates with census data. Journal of Environmental Management, 148, 53-66. doi:https://doi.org/10.1016/j.jenvman.2014.05.014
• Seaward, C. (2016). El Niño in Ethiopia: Programme observations on the impact of the Ethiopia drought and recommendations for action: Oxfam International.
• Standart, G. D., Stulken, K. R., Zhang, X., & Zong, Z. L. (2011). Geospatial visualization of global satellite images with Vis-EROS. Environmental Modelling & Software, 26(7), 980-982. doi:https://doi.org/10.1016/j.envsoft.2011.02.012
• Thenkabail, P. S., Biradar, C. M., Noojipady, P., Dheeravath, V., Li, Y., Velpuri, M., . . . Dutta, R. (2009). Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium. International Journal of Remote Sensing, 30(14), 3679-3733. doi:10.1080/01431160802698919
• Treitz, P., & Rogan, J. (2004). Remote sensing for mapping and monitoring land-cover and land-use change—an introduction. In: Pergamon.
• Velpuri, N., Thenkabail, P. S., Gumma, M. K., Biradar, C., Dheeravath, V., Noojipady, P., & Yuanjie, L. (2009). Influence of resolution in irrigated area mapping and area estimation. Photogrammetric Engineering & Remote Sensing, 75(12), 1383-1395.
• World_Bank. ( 2017). World Development Indicators: population dynamics. Retrieved from http://wdi.worldbank.org/table/2.1
• Yang, X., & Liu, Z. (2005). Using satellite imagery and GIS for land‐use and land‐cover change mapping in an estuarine watershed. International Journal of Remote Sensing, 26(23), 5275-5296. doi:10.1080/01431160500219224
• Yohannes, D. F., Ritsema, C., Solomon, H., Froebrich, J., & van Dam, J. (2017). Irrigation water management: Farmers’ practices, perceptions and adaptations at Gumselassa irrigation scheme, North Ethiopia. Agricultural Water Management, 191, 16-28.