Rainfall–runoff modelling and water balance analysis for Al-Hindiyah barrage, Iraq using remote sensing and GIS

References

• Al-Ansari N, Ali AA, Knutsson S. 2015. Iraq water resources planning: perspectives and prognoses. In: Proceedings of the ICCCE. Baghdad, Iraq; 2097–2108.
   Google Scholar
• Allen RG, Perira RD, Smith M. 1998. Crop evapotranspiration, guide lines for computing crop water requirements, Irrigation and Drainage Paper No 56. Rome: Food and Agriculture Organization of the United Nations.
   Google Scholar
• Baig MAA, Mallikarjuna P, Krishna Reddy T. 2008. Rainfall-runoff modelling – a case study. ISH J Hydraul Eng. 14:18–35.10.1080/09715010.2008.10514902
   Google Scholar
• Blanco C, Santos S, Quintas M, Vinagre M, Mesquita A. 2013. Contribution to hydrological modelling of small Amazonian catchments: application of rainfall-runoff models to simulate flow duration curves. Hydrolog Sci J. 58:1423–1433.10.1080/02626667.2013.830727
   Web of Science ®Google Scholar
• Cheng Q, Ko C, Yuan Y, Ge Y, Zhang S. 2006. GIS modeling for predicting river runoff volume in ungauged drainages in the greater Toronto area, Canada. Comput Geosci. 32:1108–1119.
   Web of Science ®Google Scholar
• Deshmukh DS, Chaube UC, Hailu AE, Gudeta DA, Kassa MT. 2013. Estimation and comparision of curve numbers based on dynamic land use land cover change, observed rainfall-runoff data and land slope. J Hydrol. 492:89–101.10.1016/j.jhydrol.2013.04.001
   Web of Science ®Google Scholar
• FAO. 1974. FAO-UNESCO soil map of the world, 1:5.000.000. Paris: UNESCO.
   Google Scholar
• Gad MA. 2013. A useful automated rainfall-runoff model for engineering applications in semi-arid regions. Comput Geosci. 52:443–452.
   Web of Science ®Google Scholar
• Isaev V, Mikhailova M. 2009. The hydrography, evolution, and hydrological regime of the mouth area of the Shatt Al-Arab River. Water Res. 36:380–395.10.1134/S0097807809040022
   Web of Science ®Google Scholar
• Jain MK, Kothyari UC, Raju KGR. 2004. A GIS based distributed rainfall-runoff model. J Hydrol. 299:107–135.10.1016/j.jhydrol.2004.04.024
   Web of Science ®Google Scholar
• Janssen L. 2000. Principles of remote sensing. Enschede, Netherlands: The International Institute for Aerospace Survey and Earth Science (ITC).
   Google Scholar
• Jensen JR. 1996. Introductory digital image processing. 2nd ed. New Jersey, NY: Prentice Hall; 750 p.
   Google Scholar
• Jensen JR. 2005. Introductory digital image processing. 2nd ed. Open access, remote sensing. ISSN 2072-4292. Upper Saddle River, NJ: Prentice Hall.
   Google Scholar
• Kato T, Kuroda H, Yoshida K. 2013. GIS analysis of conjunctive water resource use in Nganjuk district, East Java, Indonesia. Paddy Water Environ. 11:193–205.
   Web of Science ®Google Scholar
• Kisi O, Shiri J, Tombul M. 2013. Modeling rainfall-runoff process using soft computing techniques. Comput Geosci. 51:108–117.
   Web of Science ®Google Scholar
• Liu Y. 2004. Development and application of a GIS-based hydrological model for flood prediction and watershed management. Brussel: Vrije Universiteit Brussel Press; p. 315.
   Google Scholar
• Mahmoud SH. 2014. Investigation of rainfall-runoff modeling for Egypt by using remote sensing and GIS integration. Catena. 120:111–121.10.1016/j.catena.2014.04.011
   Web of Science ®Google Scholar
• Mahmoud SH, Mohammad F, Alazba A. 2013. A GIS-based approach for determination of potential runoff coefficient for Al-Baha region, Saudi Arabia. In: 2013 International Conference on Sustainable Environment and Agriculture IPCBEE. Saudi Arabia.
   Google Scholar
• Masoud M. 2014. Rainfall-runoff modeling of ungauged wadis in arid environments (case study wadi Rabigh – Saudi arabia). Arab J Geosci. 8:2587–2606.
   Web of Science ®Google Scholar
• Melesse AM, Shih S. 2002. Spatially distributed storm runoff depth estimation using Landsat images and GIS. Comput Electron Agric. 37:173–183.10.1016/S0168-1699(02)00111-4
   Web of Science ®Google Scholar
• Mockus V. 2010. Estimation of direct runoff from storm rainfall. National engineering handbook, Section 4 – hydrology. Washington, DC.
   Google Scholar
• O’Loughlin G, Huber W, Chocat B. 1996. Rainfall-runoff processes and modelling. J Hydraul Res. 34:733–751.10.1080/00221689609498447
   Web of Science ®Google Scholar
• Ponce VM, Hawkins RH. 1996. Runoff curve number: has it reached maturity? J Hydrol Eng. 1:11–19.10.1061/(ASCE)1084-0699(1996)1:1(11)
   Web of Science ®Google Scholar
• Ramakrishnan D, Bandyopadhyay A, Kusuma K. 2009. SCS-CN and GIS-based approach for identifying potential water harvesting sites in the Kali Watershed, Mahi River Basin, India. J Earth Syst Sci. 118:355–368.10.1007/s12040-009-0034-5
   Web of Science ®Google Scholar
• Schultz G. 1994. Meso-scale modelling of runoff and water balances using remote sensing and other GIS data. Hydrol Sci J. 39:121–142.10.1080/02626669409492729
   Web of Science ®Google Scholar
• Senay G, Verdin J. 2004. Developing index maps of water-harvest potential in Africa. Appl Eng Agric. 20:789–799.10.13031/2013.17725
   Web of Science ®Google Scholar
• Taguas E, Gómez J, Denisi P, Mateos L. 2015. Modelling the rainfall-runoff relationships in a large olive orchard catchment in Southern Spain. Water Resour Manage. 29:2361–2375.10.1007/s11269-015-0946-6
   Web of Science ®Google Scholar
• USDA. 2004. Estimation of direct runoff from storm rainfall. National engineering hand- book. p. 79.Washington, DC: Department of Agriculture, Natural Resources Conservation Service.
   Google Scholar
• Vaze J, Chiew F, Perraud J, Viney N, Post D, Teng J, Goswami M. 2010. Rainfall-runoff modelling across Southeast Australia: datasets, models and results. Aust J Water Res. 14:101–116.
   Google Scholar