Quantifying the Impact of Chashma Right Bank Irrigation Project on the Land use Dynamics and Cropping Pattern of Arid Region, Pakistan

Faheema Marwat; Atta Ur Rahman; Uzma Manglore; Tabassum Naz khalil; Zahid Khan; Bushra Zahid; Areej Khan; Shazia Dilbar

doi:10.33411/IJIST/880

Authors

Faheema Marwat Department of Geography and Geomatics University of Peshawar
Atta Ur Rahman Department of Geography and Geomatics University of Peshawar
Uzma Manglore Department of Geography and Geomatics University of Peshawar
Tabassum Naz Department of Geography and Geomatics University of Peshawar
Zahid Khan Department of Geography and Geomatics University of Peshawar
Bushra Zahid Department of Geography and Geomatics University of Peshawar
Areej Khan Department of Geography and Geomatics University of Peshawar
Shazia Dilbar Center for Plant Sciences and Biodiversity University of Swat

DOI:

https://doi.org/10.33411/IJIST/880

Keywords:

CRBIP, GIS, Spatio-Temporal, Land Use, Crop Production

Abstract

This research evaluates the impact of the Chashma Right Bank Irrigation Project (CRBIP) on land use dynamics and cropping patterns in an arid region of Pakistan. Initiated in 1984 and completed in three stages by 2003, the CRBIP encompasses 250,000 acres across Khyber Pakhtunkhwa and Punjab. The primary goal of the CRBIP was to enhance agricultural productivity and create employment opportunities.To analyze the geographical and temporal changes in land use dynamics, this study employed remote sensing and GIS techniques. Data were collected from both primary and secondary sources, with satellite images obtained from the years 1991 to 2021. Landsat 5(TM) images for 1991 and 2011, Landsat 7 (Enhanced Thematic Mapper) for 2001, and Landsat 8 (Operational Land Imager/Thermal Infrared Sensor) for 2021 were sourced from the USGS Earth Explorer. Additionally, crop production data were gathered from the statistics wing of the agriculture department.The results indicate notable changes over the past three decades: vegetation cover increased by 8.8%, built-up areas expanded by 15%, barren land decreased by 24%, and water bodies saw a slight reduction of 0.14%. The study also highlights significant spatial and temporal variations in vegetation cover. Following the implementation of the CRBIP, there has been a gradual increase in irrigated areas. The analysis reveals substantial improvements in the acreage of both Kharif and Rabi crops as a result of the CRBIP.These findings offer valuable insights for land-use planners, researchers, policymakers, and municipal authorities, contributing to informed decision-making and strategic planning in the region.

References

J. Liu et al., “Water conservancy projects in China: achievements, challenges and way forward,” Glob. Environ. Chang. Policy Dimens, vol. 23, no. 3, pp. 633–643, Jun. 2013, doi: 10.1016/j.gloenvcha.2013.02.002.

N. Khan, R. L. Ray, G. R. Sargani, M. Ihtisham, M. Khayyam, and S. Ismail, “Current Progress and Future Prospects of Agriculture Technology: Gateway to Sustainable Agriculture,” Sustain. 2021, Vol. 13, Page 4883, vol. 13, no. 9, p. 4883, Apr. 2021, doi: 10.3390/SU13094883.

A. Singh, “Poor quality water utilization for agricultural production: An environmental perspective,” Land use policy, vol. 43, pp. 259–262, Feb. 2015, doi: 10.1016/J.LANDUSEPOL.2014.11.015.

S. S. Shah, M. N. Shaikh, M. Y. Khan, M. A. Alfasane, M. M. Rahman, and M. A. Aziz, “Present Status and Future Prospects of Jute in Nanotechnology: A Review,” Chem. Rec., vol. 21, no. 7, pp. 1631–1665, Jul. 2021, doi: 10.1002/TCR.202100135.

L. Xu, H. Yang, and M. Ling, “Interpersonal contextual influences on the relationship between values and pro-environmental behaviors,” Sustain. Prod. Consum., vol. 32, pp. 532–540, Jul. 2022, doi: 10.1016/J.SPC.2022.05.012.

S. D. Vibhute, A. Sarangi, D. K. Singh, K. K. Bandhyopadhyay, S. S. Parihar, and D. Kumar, “Comparative evaluation of water budgeting parameters under different rice (Oryza sativa L.) cultivation methods,” J. Appl. Nat. Sci., vol. 9, no. 3, pp. 1373–1380, Sep. 2017, doi: 10.31018/JANS.V9I3.1370.

P. Saccon, “Water for agriculture, irrigation management,” Appl. Soil Ecol., vol. 123, pp. 793–796, Feb. 2018, doi: 10.1016/J.APSOIL.2017.10.037.

M. M. Khan et al., “Towards Sustainable Application of Wastewater in Agriculture: A Review on Reusability and Risk Assessment,” Agron. 2022, Vol. 12, Page 1397, vol. 12, no. 6, p. 1397, Jun. 2022, doi: 10.3390/AGRONOMY12061397.

S. R. Evett et al., “Past, Present, and Future of Irrigation on the U.S. Great Plains,” Trans. ASABE, vol. 63, no. 3, pp. 703–729, 2020, doi: 10.13031/TRANS.13620.

K. Kadiresan and P. R. Khanal, “Rethinking Irrigation for Global Food Security,” Irrig. Drain., vol. 67, no. 1, pp. 8–11, Feb. 2018, doi: 10.1002/IRD.2219.

M. R. Jalilvand, L. Nasrolahi Vosta, R. Khalilakbar, J. Khazaei Pool, and R. A. Tabaeeian, “The Effects of Internal Marketing and Entrepreneurial Orientation on Innovation in Family Businesses,” J. Knowl. Econ., vol. 10, no. 3, pp. 1064–1079, Sep. 2019, doi: 10.1007/S13132-017-0516-7/METRICS.

“A Study of Irrigation Intensity of Different Sources in Malshiras Tahsil.” Accessed: Jun. 24, 2024. [Online]. Available: https://www.researchgate.net/publication/331453799_A_Study_of_Irrigation_Intensity_of_Different_Sources_in_Malshiras_Tahsil

A. W. Siyal, P. W. Gerbens-Leenes, and S. Nonhebel, “Energy and carbon footprints for irrigation water in the lower Indus basin in Pakistan, comparing water supply by gravity fed canal networks and groundwater pumping,” J. Clean. Prod., vol. 286, p. 125489, Mar. 2021, doi: 10.1016/J.JCLEPRO.2020.125489.

Z. Raza, “The expected values of arithmetic bond connectivity and geometric indices in random phenylene chains,” Heliyon, vol. 6, no. 7, p. e04479, Jul. 2020, doi: 10.1016/j.heliyon.2020.e04479.

“Spatio-temporal distribution of actual evapotranspiration in the Indus Basin Irrigation System”, [Online]. Available: https://onlinelibrary.wiley.com/doi/10.1002/hyp.10401

M. Arshad, R. N. Oad, I. A. Khan, M. Farooq, A. Bakhsh, and M. R. Choudhry, “Chapter1 Water Resources and Irrigation Network of Pakistan”.

T. Zhou, C. Han, L. Qiao, C. Ren, T. Wen, and C. Zhao, “Seasonal dynamics of soil water content in the typical vegetation and its response to precipitation in a semi-arid area of Chinese Loess Plateau,” J. Arid Land, vol. 13, no. 10, pp. 1015–1025, Oct. 2021, doi: 10.1007/S40333-021-0021-5/METRICS.

A.-R. Atta-ur-Rahman and A. N. Khan, “Ex post Impact Evaluation of Chashma Right Bank Canal on Land Use in D. I. Khan District, Pakistan,” Arab World Geogr., vol. 15, no. 2, pp. 139–162, Jan. 2012, doi: 10.5555/ARWG.15.2.M3L32T670W516840.

H. Ali, E. Khan, and I. Ilahi, “Environmental Chemistry and Ecotoxicology of Hazardous Heavy Metals: Environmental Persistence, Toxicity, and Bioaccumulation,” J. Chem., vol. 2019, no. 1, p. 6730305, Jan. 2019, doi: 10.1155/2019/6730305.

C. C. Nnaji, C. N. Mama, and O. Ukpabi, “Hierarchical analysis of rainfall variability across Nigeria,” Theor. Appl. Climatol., vol. 123, no. 1–2, pp. 171–184, Jan. 2016, doi: 10.1007/S00704-014-1348-Z/METRICS.

G. (2017), “District Census Report of D I Khan, 2017,” Popul. Censes Organ. Pakistan, Islam..

“Remote Sensing and Image Interpretation, 7th Edition | Wiley.” Accessed: Jun. 24, 2024. [Online]. Available: https://www.wiley.com/en-sg/Remote+Sensing+and+Image+Interpretation%2C+7th+Edition-p-9781118343289

A. Massetti, M. M. Sequeira, A. Pupo, A. Figueiredo, N. Guiomar, and A. Gil, “Assessing the effectiveness of RapidEye multispectral imagery for vegetation mapping in Madeira Island (Portugal),” Eur. J. Remote Sens., vol. 49, pp. 643–672, Oct. 2016, doi: 10.5721/EUJRS20164934.

A. Vanjare, S. N. Omkar, and J. Senthilnath, “Satellite Image Processing for Land Use and Land Cover Mapping,” Int. J. Image, Graph. Signal Process., vol. 6, no. 10, pp. 18–28, Sep. 2014, doi: 10.5815/IJIGSP.2014.10.03.

“Satellite Images for Monitoring Mangrove Cover Changes in a Fast Growing Economic Region in Southern Peninsular Malaysia”, [Online]. Available: https://www.mdpi.com/2072-4292/7/11/14360

H. Dibs, H. A. Hasab, A. S. Mahmoud, and N. Al-Ansari, “Fusion Methods and Multi-classifiers to Improve Land Cover Estimation Using Remote Sensing Analysis,” Geotech. Geol. Eng., vol. 39, no. 8, pp. 5825–5842, Dec. 2021, doi: 10.1007/S10706-021-01869-X/FIGURES/13.

F. Ullah et al., “Quantifying the influence of Chashma Right Bank Canal on land-use/land-cover and cropping pattern using remote sensing,” Ecol. Indic., vol. 143, p. 109341, Oct. 2022, doi: 10.1016/J.ECOLIND.2022.109341.

M. F. Iqbal and I. A. Khan, “Spatiotemporal Land Use Land Cover change analysis and erosion risk mapping of Azad Jammu and Kashmir, Pakistan,” Egypt. J. Remote Sens. Sp. Sci., vol. 17, no. 2, pp. 209–229, Dec. 2014, doi: 10.1016/J.EJRS.2014.09.004.

B. Haack, R. Mahabir, and J. Kerkering, “Remote sensing-derived national land cover land use maps: a comparison for Malawi,” Geocarto Int., vol. 30, no. 3, pp. 270–292, Mar. 2015, doi: 10.1080/10106049.2014.952355.

G. M. Foody, “Explaining the unsuitability of the kappa coefficient in the assessment and comparison of the accuracy of thematic maps obtained by image classification,” Remote Sens. Environ., vol. 239, p. 111630, Mar. 2020, doi: 10.1016/J.RSE.2019.111630.

N. Kussul, L. Mykola, A. Shelestov, and S. Skakun, “Crop inventory at regional scale in Ukraine: developing in season and end of season crop maps with multi-temporal optical and SAR satellite imagery,” Eur. J. Remote Sens., vol. 51, no. 1, pp. 627–636, Jan. 2018, doi: 10.1080/22797254.2018.1454265.

V. Sagan et al., “Field-scale crop yield prediction using multi-temporal WorldView-3 and PlanetScope satellite data and deep learning,” ISPRS J. Photogramm. Remote Sens., vol. 174, pp. 265–281, Apr. 2021, doi: 10.1016/J.ISPRSJPRS.2021.02.008.

H. Chahal, R. C. Dangwal, and S. Raina, “Marketing orientation, strategic orientation and their synergistic impact on business performance: A case of SMEs in emerging context (India),” J. Res. Mark. Entrep., vol. 18, no. 1, pp. 27–52, 2016, doi: 10.1108/JRME-03-2016-0004/FULL/XML.

L. Gao et al., “Remote sensing algorithms for estimation of fractional vegetation cover using pure vegetation index values: A review,” ISPRS J. Photogramm. Remote Sens., vol. 159, pp. 364–377, Jan. 2020, doi: 10.1016/J.ISPRSJPRS.2019.11.018.

S. Huang, L. Tang, J. P. Hupy, Y. Wang, and G. Shao, “A commentary review on the use of normalized difference vegetation index (NDVI) in the era of popular remote sensing,” J. For. Res., vol. 32, no. 1, pp. 1–6, Feb. 2021, doi: 10.1007/S11676-020-01155-1/FIGURES/2.

J. D. Stamford, S. Vialet-Chabrand, I. Cameron, and T. Lawson, “Development of an accurate low cost NDVI imaging system for assessing plant health,” Plant Methods, vol. 19, no. 1, pp. 1–19, Dec. 2023, doi: 10.1186/S13007-023-00981-8/FIGURES/10.

G. M. Gandhi, S. Parthiban, N. Thummalu, and A. Christy, “Ndvi: Vegetation Change Detection Using Remote Sensing and Gis – A Case Study of Vellore District,” Procedia Comput. Sci., vol. 57, pp. 1199–1210, Jan. 2015, doi: 10.1016/J.PROCS.2015.07.415.

Y. Ding, K. Zhao, X. Zheng, and T. Jiang, “Temporal dynamics of spatial heterogeneity over cropland quantified by time-series NDVI, near infrared and red reflectance of Landsat 8 OLI imagery,” Int. J. Appl. Earth Obs. Geoinf., vol. 30, no. 1, pp. 139–145, Aug. 2014, doi: 10.1016/J.JAG.2014.01.009.

A. K. Bhandari, A. Kumar, and G. K. Singh, “Feature Extraction using Normalized Difference Vegetation Index (NDVI): A Case Study of Jabalpur City,” Procedia Technol., vol. 6, pp. 612–621, Jan. 2012, doi: 10.1016/J.PROTCY.2012.10.074.

S. Janjua, I. Hassan, S. Muhammad, S. Ahmed, and A. Ahmed, “Water management in Pakistan’s Indus Basin: challenges and opportunities,” Water Policy, vol. 23, no. 6, pp. 1329–1343, Dec. 2021, doi: 10.2166/WP.2021.068.

A. M. Abdi, “Land cover and land use classification performance of machine learning algorithms in a boreal landscape using Sentinel-2 data,” GIScience Remote Sens., vol. 57, no. 1, pp. 1–20, Jan. 2020, doi: 10.1080/15481603.2019.1650447.