Abstract
To restructure land- and irrigation-water use in Khorezm towards sustainability and economical feasibility, the current water use demands improvement. This requires increasing water use efficiency as much as possible, while at the same time minimizing negative impacts on the production system. These objectives can be reached with an integrated management of the irrigation and drainage system. To develop optimal management strategies, models describing the water distribution (irrigation scheduling model) and analyzing the impact on the groundwater (groundwater models) will be very helpful. In the Water Users Association (WUA) Shomakhulum, located in the southwest of Khorezm and with an irrigated area of approximately 2,000 ha, current irrigation strategies were monitored. Overall irrigation efficiency of the sub-unit representing the WUA is rather low (33%). Besides the poor state of the irrigation infrastructure, major reasons for the low efficiency are on the one hand a lack of detailed and up-to-date information on the system and its temporal behavior, and on the other hand missing options to consider detailed information in the procedures to establish water distribution plans. To tackle these issues, the irrigation scheduling model FAO CROPWAT was applied as an alternative to the current rather rigid water distribution planning. Feeding the model with detailed information on the irrigation system and its behavior (application efficiency by field-water balancing, network efficiency based on ponding experiments) provided a powerful tool to improve water use. As the groundwater in Shomakhulum is shallow, the model was further developed in order to assess the importance of the capillary rise. Therefore, the soil-water model Hydrus-1D was applied. The results of the study show that capillary rise is an important factor in water balancing and can contribute a maximum of 28% of crop-specific evapotranspiration in cotton, 12% in vegetables and 9% in winter wheat. In-practice irrigation scheduling, when simulated and assessed with the CROPWAT model, showed a 7–42% reduction in cotton yield. If the overall irrigation efficiency is improved to 56%, water saving of 41% can be achieved. Introducing alternative crops to cotton can result in 6% water saving. About 15–20% of the water can be saved by leaving marginal lands, i.e., land of low quality, out of the production.
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Allen RG, Pereira LS, Raes D, Smith M (1998) Crop evapotranspiration: guidelines for computing crop requirements. Irrigation and drainage paper 56. FAO, Rome
Awan UK (2010) Coupling hydrological and irrigation schedule models for the management of surface and groundwater resources in Khorezm, Uzbekistan. Ecology and development series no. 73. ZEF/University of Bonn, Bonn
Ayars JE, Schoneman RR (1986) Use of saline water from a shallow water table by cotton. Trans ASAE 29:1674–1678
Bastiaanssen WGM, Allen RG, Droogers P, D’Urso G, Steduto P (2004) Inserting man’s irrigation and drainage wisdom into soil water flow models and bringing it back out: how far have we progressed? In: Feddes RA, de Rooij GH, van Dam JC (eds) Unsaturatedzone modeling, UR frontis series. Kluwer Academic, Wageningen, pp 263–299
Bitterlich S, Durner W, Iden SC, Knabner P (2004) Inverse estimation of the unsaturated soil hydraulic properties from column outflow experiments using free-form parameterizations. Vadose Zone J 3(3):971–981
Bobojonov I, Lamers J, Martius C, Berg E (2008) A decision support tool for ecological improvement and income generation for smallholder farms in irrigated dry lands, Uzbekistan. In: Environmental problems of Central Asia and their economic, social and security impacts, NATO Advanced Research Workshop, Tashkent, 01–05 Oct 2007
Bos MG, Nugteren J (1974) On irrigation efficiencies. International Institute for Land Reclamation and Improvement (ILRI), Wageningen, 19:138
Bos MG, Burton MA, Molden DJ (2005) Irrigation and drainage performance assessment: practical guidelines. CABI Publishing, Trowbridge, p pp. 155
Brown KW, Turner FT, Thomas JC, Deuel LE, Keener ME (1978) Water balance of flooded rice paddies. Agric Water Manag 1:277–291
Clarke D, Smith M, El-Askari K (1998) Cropwat for Windows: user guide. University of Southampton, Southampton
Costantini EAC, Castelli F, Raimondi S, Lorenzoni P (2002) Assessing soil moisture regimes with traditional and new methods. Soil Sci Soc Am J 66:1889–1896
Cressie N (1992) Statistics for spatial data. Wiley, New York
Djanibekov N (2008) A micro-economic analysis of farm restructuring in Khorezm region, Uzbekistan. PhD dissertation, Bonn University, Bonn
Doorenbos J, Kassam AH (1979) Yield response to water. Irrigation and drainage paper 33: 193. FAO, Rome
Doorenbos J, Pruitt WO (1977) Crop water requirements. Irrigation and drainage paper 24: 144. FAO, Rome
Forkutsa I, Sommer R, Shirokova YI, Lamers JPA, Kienzler K, Tischbein B, Martius C, Vlek PLG (2009) Modeling irrigated cotton with shallow groundwater in the Aral Sea Basin of Uzbekistan: I. Water dynamics. Irrig Sci 27(4):331–346
George BA, Shende SA, Raghuwanshi NS (2000) Development and testing of an irrigation scheduling model. Agric Water Manag 46(2):121–136
Hammel K, Weller U, Stahr K (2000) In: Graef F et al (eds) Soil water balance in Southern Benin - characteristics and conclusions. Adapted farming in West Africa: issues, potentials and perspectives. Verlag Ulrich e.Grauer, Stuttgart, pp 321–330
Hanks RJ (1983) Yield and water-use relationships: an overview. In: Taylor HM, Jordan WR, Sinclair TR (eds) Limitations to efficient water use in crop production. ASA, CSSA, and SSSA, Madison, pp 393–411
Hernandez TX (2001) Rainfall-runoff modeling in humid shallow water table environments. MSc dissertation, University of South Florida, Tampa
Howell TA (1990) Relationships between crop production and transpiration, evapotranspiration, and irrigation. In: Steward BA, Nielson DR (eds) Irrigation of agricultural crops, agronomy monograph 30. ASA, CSSA, and SSSA, Madison, pp 391–434
Ibrakhimov M, Khamzina A, Forkutsa I, Paluasheva G, Lamers JPA, Tischbein B, Vlek PLG, Martius C (2007) Groundwater table and salinity: spatial and temporal distribution and influence on soil salinization in Khorezm region (Uzbekistan, Aral Sea Basin). Irrig Drain Syst 21(3/4):219–236
Jurriens M, Zerihun D, Boonstra J (2001) SURDEV: surface irrigation software. International Institute for Land Reclamation and Improvement, Wageningen
Kahlown MA, Ashraf M, Zia-ul-Haq (2005) Effect of shallow groundwater table on crop water requirements and crop yields. Agric Water Manag 76(1):24
Khepar SD, Yadav AK, Sondhi SK, Siag M (2000) Water balance model for paddy fields under intermittent irrigation practices. Irrig Sci 19(4):199–208
Kincaid DC, Heermann DF (1974) Scheduling irrigations using a programmable calculator. Agricultural Research Service-NC-12, p 55
Knight HG (1937) New size limits for silt and clay. Soil Sci Soc Am Proc 2:592
Malano HM, Chien NV, Turral HN (1999) Asset management for irrigation and drainage infrastructure: principles and case study. Irrig Drain Syst 13(2):109–129
Mandal UK, Sarma KSS, Victor US (2002) Profile water balance model under irrigated and rain fed systems. Agron J 94:1204–1211
Martius C, Lamers JPA, Wehrheim P, Schoeller-Schletter A, Eshchanov R, Tupitsa A, Khamzina A, Akramkhanov A, Vlek PLG (2004) Developing sustainable land and water management for the Aral Sea Basin through an interdisciplinary research. In: Seng V, Craswell E, Fukai S, Fischer K (eds) Water in Agriculture, ACIAR Proceedings, Canberra 116:45–60
Martius C, Froebrich J, Nuppenau EA (2009) Water resource management for improving environmental security and rural livelihoods in the irrigated Amudarya lowlands. In: Brauch HG, Spring UO, Grin J, Mesjasz C, Kameri-Mbote P, Behera NC, Chourou B, Krummenacher H (eds) Facing global environmental change: environmental, human, energy, food, health and water security concepts, Hexagon series on human and environmental security and peace, 4. Springer, Berlin/Heidelberg/New York, pp 749–762
Masharipova H (2009) Effect of laser leveled field to irrigation application efficiency. MSc Dissertation, Urgench State University, Urgench
Mateos L, Lopez-Cortijio I, Sagardoy JA (2002) SIMIS: the FAO decision support system for irrigation scheme management. Agric Water Manag 56:193–206
Meiwirth K, Mermoud A (2004) Simulation of herbicide transport in an alluvial plain. In: Pahl-Wostl C, Schmidt S, Rizzoli AE, Jakeman AJ (eds) iEMSs 2004 international congress: complexity and integrated resources management. iEMSs, Switzerland, pp 951–955
Mishra A (1999) Irrigation and drainage needs of transplanted rice in diked rice fields of rain fed medium lands. Irrig Sci 19:47–56
Nalder IA, Wein RW (1998) Spatial interpolation of climatic normals: test of a new methods in the Canadian boreal forest. Agric For Meteorol 92:211–225
Odhiambo LO, Murty VVN (1996) Modeling water balance components in relation to field layout in lowlandpaddy fields. II. Model application. Agric Water Manag 30(2):201–216
Paulo AM, Pereira LA, Teixeira JL, Pereira LS (1995) Modelling paddy irrigation. In: Pereira LS, vanden Broek BJ, Kabat P, Allen RG (eds) Crop water simulation models in practice. Wageningen Press, Wageningen
Pereira LA (1989) Rice water management. PhD dissertation, Technical University, Lisbon
Pereira LS, Paredes P, Cholpankulov ED (2009) Irrigation scheduling strategies for cotton to cope with water scarcity in the Fergana Valley, Central Asia. Agric Water Manag 96(5):723–735
Pratharpar SA, Qureshi AS (1998) Modeling the efficacy of deficit irrigation on soil salinity, depth of water table transpiration in semiarid zones with monsoonal rains. Water Resour Dev 15:141–159
Rakhimbaev FM, Bezpalov NF, Khamidov MK, Isabaev KT, Alieva D (1992) Peculiarities of crop irrigation in lower Amu Darya river areas. Fan, Tashkent
Rudenko I (2008) Value chains for rural and regional development: the case of cotton, wheat, fruit, and vegetable value chains in the lower reaches of the Amu Darya River, Uzbekistan. PhD dissertation, Hannover University, Hannover
Sadikov AS (1979) Irrigation of Uzbekistan: contemporary state and perspectives of irrigation development in the Amu Darya River Basin. Fan, Tashkent, 3:255
Sarma PBS, Rao VV (1997) Evaluation of an irrigation water management scheme - a case study. Agric Water Manag 32(2):181
Simunek J, Sejna M, van Genuchten MT (1998) The HYDRUS-1D software package for simulating the one-dimensional movement of water, heat and multiple solutes in variably-saturated media, Version 2.0. US salinity laboratory. Agricultural research service, US department of agriculture, Riverside, pp 1–177
Smith M (1992) CROPWAT, a computer program for irrigation planning and management. Irrigation and drainage paper 46. FAO, Rome
Sommer R, Vlek PLG, Deane de Abreu T, Vielhauer K, de Fátima Rodrigues Coelho R, Fölster H (2004) Nutrient balance of shifting cultivation by burning or mulching in the Eastern Amazon - evidence for subsoil nutrient accumulation. Nutr Cycl Agroecosyst 68:257–271
Srinivasulu A, Rao CS, Lakshmi GV, Satyanarayana TV, Boonstra J (2004) Model studies on salt and water balances at Konanki pilot area, Andhra Pradesh, India. Irrig Drain Syst 18:1–17
Suslov SP (1961) Physical geography of Asiatic Russia. W. H Freeman and Company, San Francisco/London
Tischbein B, Awan UK, Abdullaev I, Bobojonov I, Conrad C, Forkutsa I, Ibrakhimov M, Poluasheva G (2011) Water management in Khorezm: current situation and options for improvement (hydrological perspective). In: Martius C, Rudenko I, Lamers JPA, Vlek PLG (eds) Cotton, water, salts and Soums – economic and ecological restructuring in Khorezm, Uzbekistan. Springer, Dordrecht
van der Grift B, Passier H, Rozemeijer J, Griffioen J (2004) Integrated modeling of cadmium and zinc contamination in groundwater and surface water of the Kempen Region, The Netherlands. IEMSs 2004 international congress: complexity and integrated resources management, Switzerland, Jan 2011, pp 1235–1240
Vanderborght J, Kasteela R, Herbst M, Javaux M, Thiéry D, Vanclooster M, Mouvet C, Vereecken H (2005) A set of analytical benchmarks to test numerical models of flow and transport in soils. Vadose Zone J 4:206–221
Vaux HJJ, Pruitt WO (1983) Crop-water production functions. In: Hillel D (ed) Advances in irrigation 2. Academic, New York, pp 61–97
Ventrella D, Mohanty BP, Simunek J, Losavio N, van Genuchten MT (2000) Water and chloride transport in a fine-textured soil: field experiments and modeling. Soil Sci SocAm J 165(8):624–631
Vrugt JA, Bouten W (2002) Validity of first-order approximations to describe parameter uncertainty in soil hydrologic models. Soil Sci Soc Am J 66:1740–1751
Wallender WW, Grimes DW, Henderson DW, Stromberg LK (1979) Estimating the contribution of a perched water table to the seasonal evapotranspiration of cotton. Agron J 71:1056–1060
Zavattaro L, Grignani C (2001) Deriving hydrological parameters for modelling water flow under field conditions. Soil Sci Soc Am J 65:655–667
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Awan, U.K., Tischbein, B., Kamalov, P., Martius, C., Hafeez, M. (2012). Modeling Irrigation Scheduling Under Shallow Groundwater Conditions as a Tool for an Integrated Management of Surface and Groundwater Resources. In: Martius, C., Rudenko, I., Lamers, J., Vlek, P. (eds) Cotton, Water, Salts and Soums. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-1963-7_19
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