Effects of Irrigation and Field Management Practices within Water Resources Systems

Yıl 2020, Cilt: 4 Sayı: 1, 77 - 108, 17.01.2020

Mehmet Can Güçlü , Abebe Demissie Chukalla Pieter Van Oel

https://doi.org/10.31807/tjwsm.584862

Öz

World
population is prospected to increase to 9.8 billion people in 2050 and global
food and water demands can also be presumed to rise concurrently. Regarding
these future demands and considering climate change and depletion in water
sources; new approaches, management strategies, and models are needed. In this
study, the AquaCrop model, which may simplify the complexities of the
real-system assessments, is used as an analytical tool to predict the effects
of different management practices within winter wheat, spring wheat, winter
barley, and maize in a specific location (middle Guadiana sub-catchment,
Spain). The primary drivers from the model were determined as actual
evapotranspiration (ET_a), yield (Y), and water productivity (WP). Model
runs were executed within three different management strategies; which are irrigation
technologies, irrigation strategies, and mulching practices. Thereafter, the
yield gaps (Y_g) and water productivity gap (WP_g) were analyzed,
and water scarcity/shortage degrees were compared. The results of this study
showed that the AquaCrop model is a sophisticated model to estimate ET_a,
Y, and WP parameters. Yield productions in deficit irrigation were mostly more
than supplementary irrigation. Full irrigation showed the highest yield within
non-limited water conditions; however, some adverse effects of the full
irrigation strategy such as salinity should not be ignored. Mulching practices positively
affected the ET_a reduction. Full irrigation and no mulching scenario
showed the worst impacts on the water resources system. Supplementary
irrigation and synthetic mulching practices depicted the least surface water
resource deterioration. Deficit irrigation and synthetic mulching practices
resulted in remarkable water savings with fewer yield losses compared to the
scenario with the highest yield production levels.

Anahtar Kelimeler

AquaCrop model, management practice, water productivity, yield gap

Kaynakça

• Alcamo, J., Henrichs, T. & Rösch, T. (2000) World Water in 2025 – Global Modeling Scenarios for the World Commission on Water for the 21st Century. World Water Series Report 2, Center for Environmental Systems Research, University of Kassel, Germany.
• Aldaya, M. M., Llamas, M. R. (2008). Water Footprint Analysis for the Guadiana River Basin. Papeles de Agua Virtual. ISBN: 978-84-96655-23-2.
• Aldaya, M. M., Llamas, M. R. (2008). Water Footprint Analysis (Hydrologic and Economic) of the Guadiana River Basin. United Nations World Water Assessment Programme. ISBN 978-92-3-104117-4.
• Camacho, S., Moura, D., Connor, S., Boski, T., Gomes, A. (2014). Geochemical characteristics of sediments along the margins of an atlantic-mediterranean estuary (the Guadiana, Southeast Portugal): spatial and seasonal variations. Journal of Integrated Coastal Zone Management. 14(1): 129-148. DOI: 10.5894/rgci452.
• Chukalla, A. D., Krol, M. S., Hoekstra, A. Y. (2015). Green and blue water footprint reduction in irrigated agriculture: effect of irrigation techniques, irrigation strategies and mulching Hydrol. Earth Syst. Sci., 19, 4877–4891.
• Döll, P., Siebert, S. (2002). Global Modelling of Irrigation Water Requirements. Water Resources Research, 38 (4), 8-1-8-10.
• Ewans, R. G., Sadler, E. J. (2008). Methods and technologies to improve efficiency of water use. Water Resources Research, 44, W00E04, doi:10.1029/2007WR006200.
• Falkenmark, M. (1989). The massive water scarcity now threatening Africa: why isn't it being addressed? Ambio, 112-118.
• FAO, 2017. Irrigated Crop Calendars. Retrieved from (access 2 September 2017) http://www.fao.org/nr/water/aquastat/water_use_agr/index2.stm
• GYGA, 2017. Global yield gap atlas. Retrieved from (access 3 June 2017): http://www.yieldgap.org
• GuaSEEAW, 2015. New developments in Water Accounts Implementation in Guadina River Basin. Technical Report. Retrived from (access 20 September 2017): http://ec.europa.eu/environment/water/blueprint/pdf/D%201.3.%20Final%20Technical%20Report%20v1.3.pdf
• Hamdan, I., Oweis, T., Hamdallah, G. (eds.) AARINENA Water Use Efficiency Network: Proceedings of the Expert Consultation Meeting, 26-27 November 2006, Aleppo, Syria. ICARDA, Aleppo, Syria. iv + 244 pp.
• Hoekstra, A. Y., et al., (2011). The Water Footprint Assessment Manual. . <http://waterfootprint.org/media/downloads/TheWaterFootprintAssessmentManual_2.pdf>.
• Hoekstra, A.Y., Mekonnen, M. M., Chapagain, A.K., Mathews, R.E., Richter, B. D. (2012). Global Monthly Water Scarcity: Blue Water Footprints versus Blue Water Availability. PLoS ONE, 7(2), e32688. doi:10.1371/journal.pone.0032688.
• Klein Tank, A.M.G. and Coauthors, 2002. Daily dataset of 20th-centry surface air temperature and precipitation series for the European Climate Assessment. Int. J. of Climatol., 22, 1441-1453. Data and metadata available at http://www.ecad.eu (access 11 June 2017)
• Kummu, M., Guillaume, J.H.A., de Moel,H., Eisner, S., Flörke, M., Porkka, M., Siebert, S., Veldkamp, T.I.E., Ward, P.J. 2016. The world’s road to water scarcity: shortage and stress in the 20th century and pathways towards sustainability. Scientific Reports. Vol 6:38495, DOI: 10.1038/srep38495.
• MAPAMA, 2010. Agro-alimentary Statistics Yearbook. Spanish Ministry of Agriculture, Fisheries and Food. Retrived from ( accessed 10 October 2017) : http://www.mapama.gob.es/es/estadistica/temas/estadisticas-agrarias/agricultura/superficies-producciones-anuales-cultivos/
• OECD, 2015. Crop yield. Retrieved from (access 14 June 2017): https://data.oecd.org/agroutput/crop-yields.htm
• Oweis, T., Hachum, A., Kijne, J., Water harvesting and supplemental irrigation for improved water use efficiency in dry areas (1999). Vol 7. IWMI.
• Pedro- Monzonís, M., Solera, A., Ferrer, J., Estrela, T., Paredes-Arqiola, J. (2015). A review of water scarcity and drought indexes in water resources planning and managment. Journal of Hydrology. 527, 482–493.
• Raskin, P., Gleick, P., Kirshen, P., Pontius, G. & Strzepek, K. (1997) Water futures: assessment of long-range patterns and problems. Comprehensive assessment of the freshwater resources of the world, Stockholm Environment Institute, Stockholm, Sweden.
• SAIH, 2017. The Sytem of Hydrological Information, SAIH del Guadiana.Retrived from (access 1 October 2017): http://www.saihguadiana.com/ Smakhtin, V. Y., Revenga, C., Döll, P., (2004). Taking into account environmental water requirements in global-scale water resources assessments (Vol. 2). IWMI.
• Steduto, P., T. C. Hsiao, D. Raes, and E. Fereres. 2009. AquaCrop—The FAO Crop Model to Simulate Yield Response to Water: I. Concepts and Underlying Principles All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. . Agron. J. 101:426-437. doi:10.2134/agronj2008.0139s.
• Steduto, P., Hsiao, T. C., Raes, D., and Fereres, E. 2012. Crop yield response to water, Food and Agriculture Organization of the United Nations Italy, Rome.
• Sullivan CA, Meigh JR, Giacomello AM, Fediw T, Lawrence P, Samad M, Mlote S, Hutton C. (2003). The Water Poverty Index: Development and application at the community scale. Natural Resources Forum. 27:189–199. doi: 10.1111/1477-8947.00054.
• Uhlenbrook, S., Savenije, H. H. G. (2017).(Online lecture)Hydrology of catchments, river basins, deltas: Part one- Catchment and water balance. TU DELFT, DELFT. Retrieved from (access 28 June 2017): https://collegerama.tudelft.nl/Mediasite/Play/d5535e795d9d4f0b90d4da81cd1f1e9c1d?playFrom=17028&autoStart=true
• UN (United Nations). (2017). World population prospects. Accessed October 20, 2017 from https://esa.un.org/unpd/wpp/Publications/Files/WPP2017_KeyFindings.pdf.
• Van Ittersum, M.K. V., Cassman, K.G., Grassini, P., Wolf, J., Tittonell, P., Hochman, Z., 2013. Yield gap analysis with local to global relevance–a review. Field Crop Res. 143, 4–17.
• Wada, Y., Van Beek, L.P.H. and Bierkens, M.F. 2011. Modelling global water stress of the recent past: on the relative importance of trends in water demand and climate variability. Hydrology and Earth System Sciences, 15(12), pp.3785-3805.
• Wart, J. W., Bussel, L. G. J. V., Wolf, J., Licker, L., Grassini, P., Nelson, A., Boogaard, H., Gerber, J., Mueller, N. D., Claessens, L., Ittersum, M. K. V., Cassman, K. G. (2013). Use of agro-climatic zones to upscale simulated crop yield potential. Field Crops Research, 144, 44-55.
• Wnuk, A., Górny, A. G., Bocianowski, J., Kozak, M. (2013). Visualizing harvest index in crops. Communications in Biometry and Crop Science, 8(2), 48-59.
• WWF. (2003). Results overview for the Guadiana river basin (Portugal). WWF Water and Wetland Index – Critical issues in water policy across Europe (2003). Retrived from (access 6 June 2017): assets.panda.org/downloads/wwiguadianaportugal.pdf.
• WWF. (2003). Results overview for the Guadiana river basin (Spain). WWF Water and Wetland Index – Critical issues in water policy across Europe (2003). Retrived from (access 6 June 2017): assets.panda.org/downloads/wwiguadianaspain.pdf.
• Zhang, L., Walker, G.R., Dawes, W.R. (2002). Water balance modelling: concepts and applications. In: McVicar, T.R., Li Rui, Walker, J., Fitz- patrick, R.W. and Liu Changming (eds), Regional Water and Soil Assessment for Managing Sustainable Agriculture in China and Australia, ACIAR Monograph No. 84, 31–47.