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Rainwater harvesting for the management of agricultural droughts in arid and semi-arid regions

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Abstract

Human activities, which affect ecosystem dynamics, pose a continuous challenge to individuals and communities trying to survive in arid and semi-arid regions. The development of a method to employ rainwater harvesting (RWH) in the management of agricultural drought in arid and semi-arid regions comprised two phases: (i) detection of agricultural drought in Egypt’s El-Beheira governorate using a normalized difference vegetation index differencing technique and (ii) the delineation of RWH locations potentially suitable for the management of agricultural drought in the region using a GIS decision support system (DSS). Temporal vegetation cover analysis showed significant spatio-temporal changes that have occurred in the last 40 years: a general decrease in vegetation cover reflecting a trend towards ecosystem degradation, contrasted by a greening trend in some pockets within the region. Potentially suitable rainwater harvesting areas for agricultural drought management and attendant vegetation recovery were delineated in the region using DSS. The model generated a RWH map with five categories of suitability: excellent, good, moderate, poor and unsuitable. On average, 10.9 % (1104.17 km2) and 12 % (1215 km2) of the study area was classified as excellent and good for RWH, respectively, while 11.7 % (1185.21 km2), 15.4 % (1560 km2) and 50 % (5065 km2) of the area were classified as moderate, unsuitable and poor, respectively. Most of the areas with excellent to good suitability predominantly lie in areas which faced severe drought between 2010 and 2014. To successfully implement the drought management plan, a number of RWH sites within the excellent areas must be developed.

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References

  • Adamowski J, Adamowski K, Bougadis J (2010) Influence of trend on short duration design storms. Water Resour Manag 24:401–413

  • Adamowski J, Chan H, Prasher S, Sharda VN (2012) Comparison of multivariate adaptive regression splines with coupled wavelet transform artificial neural networks for runoff forecasting in Himalayan micro-watersheds with limited data. J Hydroinform 3:731–744

  • Anane M, Bouziri L, Limam A, Jellali S (2012) Ranking suitable sites for irrigation with reclaimed water in the Nabeul-Hammamet region (Tunisia) using GIS and AHP-multicriteria decision analysis. Resour Conserv Recycl 65:36–46

    Article  Google Scholar 

  • Anonymous (2013) Ethiopia dam could lead to ‘disaster’ for Egypt—DireTube, Latest Ethiopian News (2013, June 5). DireTube. http://www.diretube.com/articles/read-ethiopia-dam-could-lead-to-disaster-for-egypt_2981.html. Retrieved 26 Sept 2014

  • Belayneh A, Adamowski J (2012) Standard precipitation index drought forecasting using neural networks, wavelet neural networks and support vector regression. J Appl Comput Intell Soft Comput 794061:1–13

    Google Scholar 

  • Belayneh A, Adamowski J, Khalil B, Ozga-Zielinski B (2014) Long-term SPI drought forecasting in the Awash River Basin in Ethiopia using wavelet-support vector regression models. J Hydrol 508:418–429

    Article  Google Scholar 

  • Benedetti R, Rossini P (1993) On the use of NDVI profiles as a tool for agricultural statistics: the case study of wheat yield estimate and forecast in Emilia Romagna. Remote Sens Environ 45:311–326

    Article  Google Scholar 

  • Campisi S, Adamowski J, Oron G (2012) Forecasting urban water demand via wavelet-denoising and neural network models. Case study: City of Syracuse, Italy. Water Resour Manag 26:3539–3558

  • Critchley WRS, Reij C (1989) Water harvesting for plant production: Part 2. Case studies and conclusions from Sub Sahara Africa

  • Daneshmand F, Karimi A, Nikoo M, Bazargan-Lari M, Adamowski J (2014) Mitigating socio-economic–environmental impacts during drought periods by optimizing the conjunctive management of water resources. Water Resour Manag 28(6):1517–1529

    Article  Google Scholar 

  • Eidenshink JC, Hass RH (1992) Analyzing vegetation dynamics of land systems with satellite data. GeoCarto Int 1:53–61

    Article  Google Scholar 

  • Evenari ML, Shanan L, Tadmor NH (1971) The Negev: the challenge of a desert. Harvard University Press, Cambridge

    Google Scholar 

  • FAO (2003) Land and Water Digital Media Series, 26. Training Course on RWH (CDROM). Planning of Water Harvesting Schemes, Unit 22. Food and Agriculture Organization of the United Nations (FAO), Rome

  • Fewkes A (1999) The use of rainwater for WC flushing: the field-testing of a collection system. Build Environ 34:765–772

    Article  Google Scholar 

  • Foley JA, Ramankutty N, Leff B, Gibbs HK (2007) “Global land use changes. In: King MD, Parkinson CL, Partington KC, Williams RG (eds) Our changing planet: the view from space. Cambridge University Press, New York, pp 262–265

    Google Scholar 

  • Forman E, Gass S (2001) The analytic hierarchy process—an exposition. Oper Res 49(4):469–486

    Article  Google Scholar 

  • Garfì M, Tondelli S, Bonoli A (2009) Multi-criteria decision analysis for waste management in Saharawi refugee camps. Waste Manag 29(10):2729–2739

    Article  PubMed  Google Scholar 

  • Garfì M, Ferrer-Martí L, Bonoli A, Tondelli S (2011) Multi-criteria analysis for improving strategic environmental assessment of water programmes. A case study in semi-arid region of Brazil. J Environ Manag 92(3):665–675

    Article  Google Scholar 

  • Gould J, Nissen-Petersen E (1999) Rainwater catchment systems for domestic supply: design, construction, and implementation. Intermediate Technology Publications, London

    Book  Google Scholar 

  • Goward SA, Tucker CJ, Dye D (1985) North American vegetation patterns observed with the NOAA-7 advanced very high-resolution radiometer. Vegetatio 64:3–14

    Article  Google Scholar 

  • Gupta KK, Deelstra J, Sharma KD (1997) Estimation of water harvesting potential for a semiarid area using GIS and remote sensing. IAHS Publications—Series of Proceedings and Reports-Intern Assoc Hydrological Sciences, vol 242, p 63

  • Haidary A, Amiri B, Adamowski J, Fohrer N, Nakane K (2013) Assessing the impacts of four land use types on the water quality of wetlands in Japan. J Water Resour Manag 27(7):2217–2229

  • Hossain MS, Chowdhury SR, Das NG, Rahaman MM (2007) Multi-criteria evaluation approach to GIS-based land-suitability classification for tilapia farming in Bangladesh. Aquac Int 15(6):425–443

    Article  Google Scholar 

  • Houghton RA (1991) Releases of carbon to the atmosphere from degradation of forests in tropical Asia. Can J For Res 21:132–142

    Article  CAS  Google Scholar 

  • Jabr WM, El-Awar FA (2005) GIS & analytic hierarchy process for siting water harvesting reservoirs, Beirut, Lebanon. J Environ Eng 122(6):515–523

    Google Scholar 

  • Jackson RB (2001) Water in changing world. J Ecol Appl 11:1027–1045

    Article  Google Scholar 

  • Janssen R, Van Herwijnen M (1994) Multi-object decision support for environmental management. Kluwer, Dordrecht

    Google Scholar 

  • Justice CO, Townshend JRG, Holben BN, Tucker CJ (1985) Analysis of the phenology of global vegetation using meteorological satellite data. Int J Remote Sens 6:1271–1318

    Article  Google Scholar 

  • Kahinda JM, Lillie ESB, Taigbenu AE, Taute M, Boroto RJ (2008) Developing suitability maps for rainwater harvesting in South Africa. Phys Chem Earth 33:788–799

    Article  Google Scholar 

  • Krishna H (2003) An overview of rainwater harvesting systems and guidelines in the United States

  • Kumar S, Vaidya O (2006) Analytic hierarchy process: an overview of applications. Eur J Oper Res 169(1):1–29

    Article  Google Scholar 

  • Ludwig JA, Wilcox BP, Breshears DD, Tongway DJ, Imeson AC (2005) Vegetation patches and runoff-erosion as interacting eco hydrological processes in semiarid landscapes. Ecology 86:288–297

    Article  Google Scholar 

  • Mahmoud SH (2014a) Investigation of rainfall–runoff modeling for Egypt by using remote sensing and GIS integration. CATENA 120:111–121

    Article  Google Scholar 

  • Mahmoud SH (2014b) Delineation of potential sites for groundwater recharge using a GIS-based decision support system. DOI, Environ Earth Sci. doi:10.1007/s12665-014-3249-y

    Google Scholar 

  • Mahmoud SH, Alazba AA (2014) The potential of in situ rainwater harvesting in arid regions: developing a methodology to identify suitable areas using GIS-based decision support system. Arab J Geosci. doi:10.1007/s12517-014-1535-3

    Google Scholar 

  • Mahmoud SH, Alazba AA, Amin MT (2014a) Identification of potential sites for groundwater recharge using a GIS-based decision support system in Jazan region-Saudi Arabia. Water Resour Manag 28(10):3319–3340

    Article  Google Scholar 

  • Mahmoud SH, Mohammad FS, Alazba AA (2014b) Delineation of potential sites for water harvesting structures using GIS-based decision support system. Hydrol Res. doi:10.2166/nh.2014.054

    Google Scholar 

  • Mahmoud SH, Mohammad FS, Alazba AA (2014c) Determination of potential runoff coefficient for Al-Baha Region, Saudi Arabia. Arab J Geosci 7(5):2041–2057

    Article  CAS  Google Scholar 

  • Malczewski J (2004) GIS-based land-use suitability analysis: a critical overview. Prog Plan 62(1):3–65

    Article  Google Scholar 

  • Mas JF (1999) Monitoring land-cover changes: a comparison of change detection techniques. Int J Remote Sens 20(1):139–152

    Article  Google Scholar 

  • Moulin SA, Bondeau A, Delecolle R (1998) Combining agricultural crop models and satellite observations: from field to regional scales. Int J Remote Sens 19:1021–1036

    Article  Google Scholar 

  • Munyati C (2000) Wetland change detection on the Kafue Flats, Zambia, by classification of a multitemporal remote sensing image dataset. Int J Remote Sens 21(9):1787–1806

    Article  Google Scholar 

  • Nalley D, Adamowski J, Khalil B (2012) Using discrete wavelet transforms to analyze trends in streamflow and precipitation in Quebec and Ontario (1954 – 2008). J Hydrol 475:204–228

  • Owrangi A, Adamowski J, Rahnemaei M, Mohammadzadeh A, Sharifan RA (2011) Drought monitoring methodology based on AVHRR images and SPOT vegetation maps. J Water Resour Prot 3:325–334

    Article  Google Scholar 

  • Pacey A, Cullis A (1986) Rainwater harvesting: the collection of rainfall and run-off in rural areas. Intermediate Technology Publications, London

    Book  Google Scholar 

  • Potter C, Genovese V, Gross P, Boriah S, Steinbach M, Kumar V (2007) Revealing land cover change in california with satellite data. EOS 88(26):269–274

    Article  Google Scholar 

  • Ramakrishnan D, Bandyopadhyay A, Kusuma KN (2008) 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(4):355–368

    Article  Google Scholar 

  • Rao KHVD, Bhaumik MK (2003) Spatial expert support system in selecting suitable sites for water harvesting structures—a case study of Song Watershed, Uttaranchal, India. Geocarto Int 18:43–50

    Article  Google Scholar 

  • Rao BRM, Dwivedi RS, Kushwaha SPS, Bhattacharya SN, Anand JB, Dasgupta S (1999) Monitoring the spatial extent of coastal wetlands ERS-1-SAR data. Int J Remote Sens 20(13):2509–2517

    Article  Google Scholar 

  • Roy RS, Ranganath BK, Diwakar PG, Vohra TPS, Bhan SK, Singh JJ, Pandian VC (1991) Tropical forest mapping and monitoring using remote sensing. Int J Remote Sens 11:2205–2225

    Article  Google Scholar 

  • Ryan PJ, Wilson PR (2008) Field operations. In: McKenzie NJ, Grundy MJ, Webster R, Ringrose-Voase AJ (eds) Guidelines for surveying soil and land resources, 2nd edn. CSIRO Publishing, Melbourne, pp 241–262

    Google Scholar 

  • Saadat H, Adamowski J, Bonnell R, Sharifi F, Namdar M, Ale-Ebrahim S (2011) Land use and land cover classification over a large area in Iran based on single date analysis of satellite imagery. J Photogramm Remote Sens 66:608–619

  • Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15:57–68

    Article  Google Scholar 

  • Saaty TL (1980) The analytic hierarchy process. McGraw-Hill, New York

    Google Scholar 

  • Saaty TL (1990) How to make a decision: the analytic hierarchy process. Eur J Oper Res 48:9–26

    Article  Google Scholar 

  • Saaty TL (1994) Fundamentals of decision making and priority theory with the AHP. RWS Publications, Pittsburgh

    Google Scholar 

  • Sharma KD (1986) Runoff behaviour of water harvesting microcatchments. Agric Water Manag 11(2):137–144

    Article  Google Scholar 

  • Tiwari M, Adamowski J (2014) Urban water demand forecasting and uncertainty assessment using ensemble wavelet-bootstrap-neural network models. Water Resour Res 49(10):6486–6507

  • Triantaphyllou E, Mann SH (1995) Using the analytic hierarchy process for decision making in engineering applications: some challenges. Int J Ind Eng: Appl Pract 2(1):35–44

    Google Scholar 

  • Tucker CJ, Choudhury BJ (1987) Satellite remote sensing of drought conditions. Remote Sens Environ 23:243–251

    Article  Google Scholar 

  • Tucker CJ, Townshend JRG, Goff TE (1985) African land-cover classification using satellite data. Science 227:369–375

    Article  PubMed  CAS  Google Scholar 

  • Vahidnia MH, Alesheikh A, Alimohammadi A, Bassiri A (2008) Fuzzy analytical hierarchy process in GIS application. Int Arch Photogram Remote Sens Spatial Inf Sci 37(B2):593–596

  • Vargas L (1990) An overview of the analytic hierarchy process and its applications. Eur J Oper Res 48(1):2–8

    Article  Google Scholar 

  • Wang WD, Xie CM, Du XG (2009) Landslides susceptibility mapping based on geographical information system, Guizhou, south-west China. Environ Geol 58(1):33–43

    Article  Google Scholar 

  • Weiner J (2003) Incorporating rainwater harvesting in the suburban landscape. In: Proceedings of 11th international conference on rainwater catchment systems, Texcoco

  • Yelwa SA (2005) Land cover changes across Nigeria as detected from high temporal resolution meteorological data. Maiduguri J Arts Soc Sci 3(2):73–79

    Google Scholar 

  • Young KD, Younos T, Dymond RL, Kibler DF, Lee DH (2010) Application of the analytic hierarchy process for selecting and modeling stormwater best management practices. J Contemp Water Res Educ 146(1):50–63

    Article  Google Scholar 

  • Yu M, Gao Q, Epstein HE, Zhang X (2008) An ecohydrological analysis for optimal use of redistributed water among vegetation patches. Ecol Appl 18:1679–1688

    Article  PubMed  Google Scholar 

  • Zahedi F (1986) The analytic hierarchy process: a survey of the method and its applications. Interface 16(4):96–108

    Article  Google Scholar 

  • Zaunderer J, Hutchinson CF (1988) A review of water harvesting techniques of the Arid Southwestern US and North Mexico. Working Paper for the World Bank’s Sub-Sahara Water Harvesting Study

Download references

Acknowledgments

This project was financially supported by King Saud University, Deanship of Scientific Research, College of Food and Agricultural Sciences, Research Center. The results can help decision-makers and water resources planners in El-Beheira governorate and similar governorates in Egypt to use the newly developed RWH maps for the management of agricultural drought. This study has the potential to help planners manage rainwater in arid and semi-arid regions. Furthermore, a feasibility study can be conducted for various techniques used in harvesting rainwater to identify site-specific mechanisms that augment groundwater recharge from catchment areas, such as the construction of small dams, bounds, soil pits, recharge wells, tanks, etc. which can be used during drought events. Therefore, capturing rainwater runoff may increase water availability and reduce water demand.

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Authors and Affiliations

  1. Alamoudi Water Research Chair, King Saud University, PO Box 2460, Riyadh, 11451, Saudi Arabia

    Shereif H. Mahmoud & A. A. Alazba

  2. Department of Bioresource Engineering, Faculty of Agricultural and Environmental Sciences, McGill University, Montreal, Canada

    J. Adamowski

  3. Department of Agriculture Engineering, Ain Shams University, Cairo, Egypt

    A. M. El-Gindy

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  1. Shereif H. Mahmoud
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  2. J. Adamowski
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  3. A. A. Alazba
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  4. A. M. El-Gindy
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Correspondence to Shereif H. Mahmoud.

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Mahmoud, S.H., Adamowski, J., Alazba, A.A. et al. Rainwater harvesting for the management of agricultural droughts in arid and semi-arid regions. Paddy Water Environ 14, 231–246 (2016). https://doi.org/10.1007/s10333-015-0493-z

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