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Spatiotemporal variability in spate irrigation systems in Khirthar National Range, Sindh, Pakistan (case study)

Abstract

Satellite remote sensing and geographical information system (GIS) have been used successfully to monitor and assess the land use and land cover (LULC) dynamics and their impacts on people and the environment. LULC change detection is essential for studying spatiotemporal conditions and for proposing better future planning and development options. The current research analyzes the detection of spatiotemporal variability of spate irrigation systems using remote sensing and GIS in the Khirthar National Range, Sindh Province of Pakistan. We use Landsat images to study the dynamics of LULC using ArcGIS software and categorize five major LULC types. We obtain secondary data related to precipitation and crop yield from the provincial department of revenue. The maximum likelihood supervised classification (MLSC) procedure, augmented with secondary data, reveals a significant increase of 86.25% in settlements, 83.85% in spate irrigation systems, and 65% in vegetation, and a substantial negative trend of 39.50% in water bodies and 20% in barren land during the period from 2013 to 2018. Our study highlights an increase in settlements due to the inflow of local population for better means of living and an increase in spate irrigation systems, which indicates the water conservation practices for land cultivation and human purpose lead to the shrinkage of water bodies. The confusion matrix using Google Earth data to rectify modeled (classified) data, which showed an overall accuracy of 82.8%–92%, and the Kappa coefficient estimated at 0.80–0.90 shows the satisfactory results of the LULC classification. The study suggests the need to increase water storage potential with the appropriate water conservation techniques to enhance the spate irrigation system in the hilly tracts for sustainable developments, which mitigates drought impact and reduces migration rate by providing more opportunities through agricultural activities in the study area.

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References

  1. Adolfo C, Rosalen EA (2007) Land use change and land degradation in Southeastern Mediterranean Spain Elias Symeonakis Æ. Environ Manag 40:80–94. https://doi.org/10.1007/s00267-004-0059-0

    Article  Google Scholar 

  2. Autónoma CJ, Díaz-Caravantes RE, Sánchez-Flores E (2011) Water transfer effects on peri-urban land use/land cover: a case study in a semi-arid region of Mexico. Appl Geogr 31:413–425

    Article  Google Scholar 

  3. Aydöner C, Maktav D (2009) The role of the integration of remote sensing and GIS in land use/land cover analysis after an earthquake. Int J Remote Sens. https://doi.org/10.1080/01431160802642289

    Article  Google Scholar 

  4. Betru T, Motuma T, Kefyalew S, Habtemariam K (2019) Trends and drivers of land use/land cover change in Western Ethiopia. Appl Geogr 104:83–93

    Article  Google Scholar 

  5. Birhanu A (2018) Impacts of land use and land cover changes on hydrology of the Gumara catchment, Ethiopia. Phys Chem Earth. https://doi.org/10.1016/j.pce.2019.01.006

    Article  Google Scholar 

  6. Bonato M, Cian F, Giupponi C (2019) Combining LULC data and agricultural statistics for A better identification and mapping of High nature value farmland: a case study in the veneto Plain, Italy. Land Use Policy 83:488–504

    Article  Google Scholar 

  7. Butt A, Shabbir R, Saeed Ahmad S, Aziz N (2015) Land use change mapping and analysis using remote sensing and GIS: a case study of Simly Watershed, Islamabad, Pakistan. Egypt J Remote Sens Space Sci. https://doi.org/10.1016/j.ejrs.2015.07.003

    Article  Google Scholar 

  8. Cai M, Kalnay E (2004) Response to the comments by Vose et al. and Trenberth. Impact of land-use change on climate. Nature 427:214

    Article  Google Scholar 

  9. Chase TN, Pielke RA, Kittel TGF, Nemani RR, Running SW (2000) Simulated impacts of historical land cover changes on global climate in northern winter. Climate Dyn 16:93–105

    Article  Google Scholar 

  10. Chignell SM, Anderson RS, Evangelista PH, Laituri MJ, Merritt DM (2015) Multi-temporal independent component analysis and Landsat8 for delineating maximum extent of the 2013 Colorado front range flood. Remote Sens 2015(7):9822–9843

    Article  Google Scholar 

  11. Chowdhury M, Hasan ME, Abdullah-Al-Mamun MM (2018) Land use/land cover change assessment of Halda watershed using remote sensing and GIS. Egypt J Remote Sens Space Sci. https://doi.org/10.1016/j.ejrs.2018.11.003

    Article  Google Scholar 

  12. Christy JR, Norris WB, Redmond K, Gallo KP (2006) Methodology and results of calculating central California surface temperature trends: evidence of human-induced climate change? J Climate 19:548–563

    Article  Google Scholar 

  13. Dimitrios DA, Athos A, Diofantos GH, Adrianos R (2012) Optimizing statistical classification accuracy of satellite remotely sensed imagery for supporting fast flood hydrological analysis. Acta Geophys 60(3):959–984. https://doi.org/10.2478/s11600-012-0025-9

    Article  Google Scholar 

  14. Djuma H, Bruggeman A, Camera C, Eliades M, Kostarelos K (2017) The impact of a check dam on groundwater recharge and sedimentation in an ephemeral stream. Water 9(10):813. https://doi.org/10.3390/w9100813

    Article  Google Scholar 

  15. El Bastawesy M (2014) Hydrological scenarios of the renaissance Dam in Thiopia and its hydro-environmental impact on the Nile downstream. J Hydrol Eng. https://doi.org/10.1061/(ASCE)HE.1943-5584.0001112

    Article  Google Scholar 

  16. El Bastawesy M, Ramadan Ali R, Faid A, El Osta M (2013) Assessment of water logging in agricultural megaprojects in the closed drainage basins of the Western Desert of Egypt. J Hydrol Earth Syst Sci 17:1493–1501. https://doi.org/10.5194/hess-17-1493-2013

    Article  Google Scholar 

  17. Ezber Y, Sen OL, Kindap T, Karaca M (2007) Climatic effects of urbanization in Istanbul: a statistical and modeling analysis. Int J Climatol 27:667–679

    Article  Google Scholar 

  18. Feddema JJ, Oleson KW, Bonan GB, Mearns LO, Buja LE, Meehl GA, Washington WM (2005) The importance of land-cover change in simulating future climates. Science 310:1674–1678

    Article  Google Scholar 

  19. Fiorella OW, Julián BB (2018) Assessment of satellite-based precipitation estimates over Paraguay. Acta Geophys 2018(66):369–379. https://doi.org/10.1007/s11600-018-0146-x

    Article  Google Scholar 

  20. Girma H, Hassan R (2014) Drivers of land-use change in the southern nations, nationalities and people’s region of Ethiopia. Afr J Agric Resour Econ 9(2):148–164

    Google Scholar 

  21. Haack B, Mahabir R (2019) Optical and radar data analysis for land use land cover mapping in Peru. Remote Sens Land 3(1):15–27

    Google Scholar 

  22. International Fund of Agricultural Development (IFAD) (2010) Spate Irrigation, Livelihood, Improvements, and Adaptation to Climate Change. MetaMeta & IFAD (2010), p 4

  23. Jain Figueroa A (2019) Sustainable agricultural management: a systems approach for examining food security tradeoffs (Doctoral dissertation, Massachusetts Institute of Technology)

  24. Kalnay E, Cai M (2003) Impact of urbanization and land use on climate change. Nature 423:528–531

    Article  Google Scholar 

  25. Mahmood R, Foster SA, Keeling T, Hubbard KG, Carlson C, Leeper R (2006) Impacts of irrigation on 20th century temperatures in the Northern Great Plains. Glob Planet Change 54:1–18

    Article  Google Scholar 

  26. Mahmood R, Pielke RA Sr, Hubbard KG, Niyogi D, Bonan G, Lawrence P et al (2010) Impacts of land use/land cover change on climate and future research priorities. Bull Am Meteorol Soc 91(1):37–46

    Article  Google Scholar 

  27. Markhi A, Laftouhi N, Grusson Y, Soulaimani A (2019) Assessment of potential soil erosion and sediment yield in the semi-arid N′fs basin (High Atlas, Morocco) using the SWAT model. Acta Geophys 2019(67):263–272. https://doi.org/10.1007/s11600-019-00251-z

    Article  Google Scholar 

  28. Mehari A, van Steenbergen F, Schultz B (2007) Water rights and rules, and management in Spate irrigation systems in Eritrea, Yemen, and Pakistan. Community-based water law and water resource management reform in developing countries, p 114

  29. Mehari A, Van Steenbergen F, Schultz B (2011) Modernization of Spate irrigated agriculture: a new approach. Irrig Drain 60(2):163–173

    Article  Google Scholar 

  30. Mercy MW (2015) Assessment of the effects of climate change on land use and land cover using remote sensing: a case study from Kenya. Working paper series. Dresden nexus conference. Dnc2015/03

  31. Milanova E, Telnova N (2007) Land-use and land-cover change study in the transboundary zone of Russia-Norway. Man in the landscape across frontiers: Landscape and land use change in central European border regions. In: CD-ROM conference proceedings of the IGU/LUCC central Europe conference, pp 123–133

  32. Mohaideen MMD, Varija K (2018) Improved vegetation parameterization for hydrological model and assessment of land cover change impacts on the flow regime of the Upper Bhima basin, India. Acta Geophys 2018(66):697–715. https://doi.org/10.1007/s11600-018-0161-y

    Article  Google Scholar 

  33. Nayak S, Mandal M (2012) Impact of land-use and land-cover changes on temperature trends over Western India. Curr Sci 102(8):1166–1173

    Google Scholar 

  34. Nuñez MN, Ciapessoni HH, Rolla A, Kalnay E, Cai M (2008) Impact of land use and precipitation changes on surface temperature trends in Argentina. J Geophys Res 113:D06111. https://doi.org/10.1029/2007JD008638

    Article  Google Scholar 

  35. Olaoye IA, Ortiz J, Jefferson A, Shakoor A (2019) Landuse/landcover (LULC) change modeling of Old Woman Creek (OWC)Watershed using Remote Sensing and GIS. Environmental Science & Design Research Initiative. Paper 35. https://digitalcommons.kent.edu/esdri2019/35

  36. Pakistan’s Bureau of Census (2017). http://www.pbs.gov.pk/sites/default/files/PAKISTAN%20TEHSIL%20WISE%20FOR%20WEB%20CENSUS_2017.pdf

  37. Pan Y, Gong H, Zhou D, Li X, Nakagoshi N (2011) Impact of land use change on groundwater recharge in Guishui River Basin, China. Chin Geogr Sci 21(6):734–743

    Article  Google Scholar 

  38. Rawat JS, Kumar M (2015) Monitoring land use/cover change using remote sensing and GIS techniques: a case study of Hawalbagh block, district Almora, Uttarkhand, India

  39. Rokni K, Ahmad A, Selamat A, Hazini S (2014) Water feature extraction and change detection using multitemporal landsat imagery. Remote Sens 2014(6):4173–4189

    Article  Google Scholar 

  40. Satya BA, Shashi M, Pratap D (2020) Effect of temporal-based land use–land cover change pattern on rainfall runoff. In: Applications of geomatics in civil engineering. Springer, Singapore, pp 175–182

  41. Tilman D, Balzer C, Hill J, Befort BL (2011) Global food demand and the sustainable intensification of agriculture. Proc Natl Acad Sci 108(50):20260–20264

    Article  Google Scholar 

  42. Trenberth KE (2004) Rural land-use change and climate. Nature 427:213

    Article  Google Scholar 

  43. Vogels MF, De Jong SM, Sterk G, Douma H, Addink EA (2019) Spatio-temporal patterns of smallholder irrigated agriculture in the horn of Africa using GEOBIA and Sentinel-2 imagery. Remote Sens 11(2):143

    Article  Google Scholar 

  44. Vose RS, Karl TR, Easterling DR, Williams CN, Menne MJ (2004) Impact of land-use change on climate. Nature 427:213–214

    Article  Google Scholar 

  45. Yin J, He F, Xiong YJ, Qiu GY (2017) Effects of land use/land cover and climate changes on surface runoff in a semi-humid and semi-arid transition zone in northwest China. Hydrol Earth Syst Sci 21(1):183–196. https://doi.org/10.5194/hess-21-183-2017

    Article  Google Scholar 

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Acknowledgements

The current research was conducted using the GIS and Computer Labs of the US-Pakistan Center for Advanced Studies in Water (USPCAS-W)/Mehran University of Engineering and Technology, Jamshoro. We also acknowledged the efforts, dedications, and knowledge of the local people who are engaged in the existing spate irrigation system; their dedicated efforts and expertise played a vital role in developing the current research. With great pleasure, the authors acknowledge the support provided by the FBLN/MetaMeta under “Africa to Asia and Back: Testing Adaptation in Flood Based Farming Systems” and the cooperation and supervision of the faculty of the USPCAS-W. Last but not least, many thanks go to USAID for providing technical support for the establishment of the Center.

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Correspondence to Abdul Ghani Soomro.

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Soomro, A.G., Babar, M.M., Arshad, M. et al. Spatiotemporal variability in spate irrigation systems in Khirthar National Range, Sindh, Pakistan (case study). Acta Geophys. 68, 219–228 (2020). https://doi.org/10.1007/s11600-019-00392-1

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Keywords

  • Spate irrigation
  • LULC
  • Remote sensing
  • GIS
  • Water bodies
  • Vegetation
  • Confusion matrix
  • Khirthar National Range