Risk Analysis of Water Demand for Agricultural Crops under Climate Change
This article is a reply.
VIEW THE ORIGINAL ARTICLEThis article is a reply.
VIEW THE ORIGINAL ARTICLEThis article has a reply.
VIEW THE REPLYThis article has a reply.
VIEW THE REPLYPublication: Journal of Hydrologic Engineering
Volume 20, Issue 4
Abstract
This paper assesses the risk of increase in water demand for a wide range of irrigated crops in an irrigation network located downstream of the Aidoghmoush Dam in East Azerbaijan by considering climate change conditions for the period 2026–2039. Atmosphere-ocean global circulation models (AOGCMs) are used to simulate climatic variables such as temperature and precipitation. The Bayesian approach is used to consider uncertainties of AOGCMs. Climate change scenarios of climatic variables are first weighted by using the mean observed temperature-precipitation (MOTP) method, and related probability distribution functions are produced. Outputs of AOGCMs are used as input to water requirement models. Then, produced by using the Monte Carlo method, 200 samples (discrete values) from the probability distribution functions of monthly downscaled temperature and precipitation in the study area are extracted by using a software for sensitivity and uncertainty analysis. Time series of climatic variables in future periods are then generated (temperature variable to calculate potential evapotranspiration and rainfall variable to calculate effective rainfall). To estimate crop water requirements, crop evapotranspiration (from the product of potential evapotranspiration in the previous step and coefficient of crop computed) and effective precipitation (from time series of the previous step) are calculated. The Food and Agricultural Organization of the United Nations (FAO) methods, FAO-24 and Penman-Monteith, were used to compute crop and potential evapotranspiration, respectively. Because of lack of required data, potential evapotranspiration in future periods is computed through the relationship of temperature and potential evapotranspiration in the baseline period; the same procedure is conducted for temperature. Net water requirement (NWR) and the risk of changes in water demand volume of crops (e.g., wheat, barley, alfalfa, soybean, feed corn, forage, potato, and walnut orchards) are computed by entering 200 monthly time series of downscaled temperature and precipitation in future periods. The results indicate that risk of changes in crop water requirements increases by approximately 3% for a 25% risk, approximately 17% for a 50% risk, and approximately 33% for a 75% risk. Also, based on the current cultivated area, on average, the volume of water demand only for the aforementioned crops will be approximately with a risk of 25%, approximately with a risk of 50%, and approximately with a risk of 75%. Wheat and barley are more resistant and less sensitive to climate change than other crops considered.
Get full access to this article
View all available purchase options and get full access to this article.
References
Afshar, A., Shafii, M., and Bozorg Haddad, O. (2010). “Optimizing multi-reservoir operation rules: An improved HBMO approach.” J. Hydroinf., 13(1), 121–139.
Alexandrov, V., and Genev, M. (2004). “The effect of climate variability and change on water resources in Bulgaria.” Hydrology: Science and practice for the 21st century, Vol. 1, B. Webb, N. Arnell, C. Onof, N. Maclntyre, R. Gurney, and C. Kirby, eds., British Hydrological Society, Krips, Netherlands, 1–8.
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M. (1998). “Crop evapotranspiration. Guidelines for computing crop water requirements.”, Food and Agricultural Organization of the United Nations, Rome, Italy.
Ashofteh, P.-S., Bozorg Haddad, O., and Mariño, M. A. (2013a). “Climate change impact on reservoir performance indices in agricultural water supply.” J. Irrig. Drain. Eng., 85–97.
Ashofteh, P.-S., Bozorg Haddad, O., and Mariño, M. A. (2013b). “Scenario assessment of streamflow simulation and its transition probability in future periods under climate change.” Water Resour. Manage., 27(1), 255–274.
Bozorg Haddad, O., Adams, B. J., and Mariño, M. A. (2008a). “Optimum rehabilitation strategy of water distribution systems using the HBMO algorithm.” J. Water Supply Res. Technol. AQUA, 57(5), 337–350.
Bozorg Haddad, O., Afshar, A., and Mariño, M. A. (2008b). “Design-operation of multi-hydropower reservoirs: HBMO approach.” Water Resour. Manage., 22(12), 1709–1722.
Bozorg Haddad, O., Afshar, A., and Mariño, M. A. (2008c). “Honey-bee mating optimization (HBMO) algorithm in deriving optimal operation rules for reservoirs.” J. Hydroinf., 10(3), 257–264.
Bozorg Haddad, O., Afshar, A., and Mariño, M. A. (2009). “Optimization of non-convex water resource problems by honey-bee mating optimization (HBMO) algorithm.” Eng. Comput., 26(3), 267–280.
Bozorg Haddad, O., Afshar, A., and Mariño, M. A. (2011a). “Multireservoir optimisation in discrete and continuous domains.” Proc. Inst. Civ. Eng. Water Manage., 164(2), 57–72.
Bozorg Haddad, O., and Mariño, M. A. (2007). “Dynamic penalty function as a strategy in solving water resources combinatorial optimization problems with honey-bee optimization (HBMO) algorithm.” J. Hydroinf., 9(3), 233–250.
Bozorg Haddad, O., and Mariño, M. A. (2011). “Optimum operation of wells in coastal aquifers.” Proc. Inst. Civ. Eng. Water Manage., 164(3), 135–146.
Bozorg Haddad, O., Moradi-Jalal, M., and Mariño, M. A. (2011b). “Design-operation optimisation of run-of-river power plants.” Proc. Inst. Civ. Eng. Water Manage., 164(9), 463–475.
Data Distribution Centre (DDC). (1988). “Data Distribution Centre.” IPCC, Geneva, 〈http://ipcc-ddc.cru.uea.ac.uk/〉 (Jun. 20, 2010).
Diaz-Nieto, J., and Wilby, R. L. (2005). “A comparison of statistical and climate change factor methods: Impacts on low flows in the River Thames, United Kingdom.” Clim. Change, 69(2–3), 245–268.
Doorenbos, J., and Pruitt, W. O. (1984). “Guidelines for predicting crop water requirements.”, Food and Agricultural Organization of the United Nations, Rome.
Fallah-Mehdipour, E., Bozorg Haddad, O., Beygi, S., and Mariño, M. A. (2011a). “Effect of utility function curvature of Young’s bargaining method on the design of WDNs.” Water Resour. Manage., 25(9), 2197–2218.
Fallah-Mehdipour, E., Bozorg Haddad, O., and Mariño, M. A. (2011b). “MOPSO algorithm and its application in multipurpose multireservoir operations.” J. Hydroinf., 13(4), 794–811.
Fallah-Mehdipour, E., Bozorg Haddad, O., and Mariño, M. A. (2012). “Real-time operation of reservoir system by genetic programming.” Water Resour. Manage., 26(14), 4091–4103.
Ghajarnia, N., Bozorg Haddad, O., and Mariño, M. A. (2011). “Performance of a novel hybrid algorithm in the design of water networks.” Proc. Inst. Civ. Eng.: Water Manage., 164(4), 173–191.
Giglioli, N., and Saltelli, A. (2000). “SimLab 1.1, software for sensitivity and uncertainty analysis, tool for sound modeling.” 〈http://arxiv.org/abs/cs/0011031〉 (Jul. 10, 2010).
Haan, C. T. (2002). Statistical methods in hydrology, 2nd Ed., Iowa State University Press, IA.
Intergovernmental Panel on Climate Change (IPCC). (2007). “Climate change 2007: The physical science basis.” Contribution of Working Group I to the Fourth Assessment Rep. of the Intergovernmental Panel on Climate Change, S. Solomon, et al., eds., Cambridge University Press, Cambridge, U.K.
Jones, J. W., et al. (2003). “The DSSAT cropping system model.” Eur. J. Agron., 18(3–4), 235–265.
Joyce, B., et al. (2006). “Climate change impacts on water for agriculture in California: A case study in the Sacramento Valley.” White Paper (Rep.) for the California Climate Change Center #CEC-500-2005-194-SF, Sacramento, CA.
Karimi-Hosseini, A., Bozorg Haddad, O., and Mariño, M. A. (2011). “Site selection of raingauges using entropy methodologies.” Proc. Inst. Civ. Eng. Water Manage., 164(7), 321–333.
Katz, R. W. (2002). “Techniques for estimating uncertainty in climate change scenarios and impact studies.” Clim. Res., 20(2), 167–185.
Knox, J. W., Rodríguez Díaz, J. A., Nixon, D. J., and Mkhwanazi, M. (2009). “A preliminary assessment of climate change impacts on sugarcane in Swaziland.” Agric. Syst., 103(2), 63–72.
Meza, F., Silva, D., and Vigil, H. (2008). “Climate change impacts on irrigated maize in Mediterranean climates: Evaluation of double cropping as an emerging adaptation alternative.” Agric. Syst., 98(1), 21–30.
Moradi-Jalal, M., Bozorg Haddad, O., Karney, B. W., and Mariño, M. A. (2007). “Reservoir operation in assigning optimal multi-crop irrigation areas.” Agric. Water Manage., 90(1–2), 149–159.
Nkomozepi, T., and Chung, S. (2012). “Assessing the trends and uncertainty of maize net irrigation water requirement estimated from climate change projections for Zimbabwe.” Agric. Water Manage., 111, 60–67.
Noory, H., Liaghat, A. M., Parsinejad, M., and Bozorg Haddad, O. (2012). “Optimizing irrigation water allocation and multicrop planning using discrete PSO algorithm.” J. Irrig. Drain. Eng., 437–444.
Rasoulzadeh-Gharibdousti, S., Bozorg Haddad, O., and Mariño, M. A. (2011). “Optimal design and operation of pumping stations using NLP-GA.” Proc. Inst. Civ. Eng. Water Manage., 164(4), 163–171.
Rosenweig, C., et al. (2004). “Water resources for agriculture in a changing climate: International case studies.” J. Global Environ. Change, 14(4), 345–360.
Sabbaghpour, S., Naghashzadehgan, M., Javaherdeh, K., and Bozorg Haddad, O. (2012). “HBMO algorithm for calibrating water distribution network of Langarud City.” Water Sci. Technol., 65(9), 1564–1569.
Seifollahi-Aghmiuni, S., Bozorg Haddad, O., Omid, M. H., and Mariño, M. A. (2011). “Long-term efficiency of water networks with demand uncertainty.” Proc. Inst. Civ. Eng. Water Manage., 164(3), 147–159.
Smith, M. (1992). “CROPWAT—A computer program for irrigation planning and management.”, Food and Agricultural Organization of the United Nations, Rome, Italy.
Soltanjalili, M., Bozorg Haddad, O., and Mariño, M. A. (2011). “Effect of breakage level one in design of water distribution networks.” Water Resour. Manage., 25(1), 311–337.
Steinemann, A., and Cavalcanti, L. (2006). “Developing multiple indicators and triggers for drought plans.” J. Water Resour. Plann. Manage., 164–174.
Task Group on Scenarios for Climate Impact Assessment (TGCIA). (1999). Guidelines on the use of scenario data for climate impact and adaptation assessment, version 1, T. R. Carter, M. Hulme, and M. Lal, eds., IPCC, Geneva, Switzerland.
Wilby, R. L., and Harris, I. (2006). “A framework for assessing uncertainties in climate change impacts: Low-flow scenarios for the River Thames, UK.” Water Resour. Res., 42(2), W02419.
Xiong, W., et al. (2010). “Climate change, water availability and future cereal production in China.” Agric. Ecosyst. Environ., 135(1–2), 58–69.
Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 20 • Issue 4 • April 2015
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Dec 7, 2013
Accepted: Jun 30, 2014
Published online: Aug 18, 2014
Discussion open until: Jan 18, 2015
Published in print: Apr 1, 2015
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.