Your search found 6 records
1 Rehman, G.; Hussain, A.; Ahmad, Mobin-ud -Din; Munawar, H. Z. 1996. Issues in spatial analysis for salinity management: A synthesis across irrigation units of Lower Chenab Canal System, Punjab, Pakistan. In Badruddin, M.; Skogerboe, G. V.; Shafique, M. S. (Eds.), Proceedings of the National Conference on Managing Irrigation for Environmentally Sustainable Agriculture in Pakistan, Islamabad, November 5-7, 1996. Volume IV - Papers on the theme, environmental management of irrigated lands. Lahore, Pakistan: IIMI Pakistan. National Program. pp.118-169.
Salinity control ; Irrigation canals ; Irrigation systems ; Soil surveys ; Groundwater ; Water use ; Water table ; Water allocation ; Tube wells ; Water quality ; Monitoring ; GIS / Pakistan / Punjab / Lower Chenab Canal System / Rechna Doab
(Location: IWMI-HQ Call no: IIMI 631.7 G730 BAD Record No: H020200)
2 Rehman, A.; Rehman, G.; Jehangir, W. A.; Aslam, M. 1996. Predicting sustainable irrigated agricultural adjustments, across the Lower Chenab Canal System. In Badruddin, M.; Skogerboe, G. V.; Shafique, M. S. (Eds.), Proceedings of the National Conference on Managing Irrigation for Environmentally Sustainable Agriculture in Pakistan, Islamabad, November 5-7, 1996. Volume IV - Papers on the theme, environmental management of irrigated lands. Lahore, Pakistan: IIMI Pakistan. National Program. pp.190-218.
Irrigated farming ; Sustainable agriculture ; Irrigation canals ; Models ; Crop yield ; Groundwater ; Recharge ; Pumping ; Simulation ; Water shortage ; Water stress / Pakistan / Punjab / Lower Chenab Canal System
(Location: IWMI-HQ Call no: IIMI 631.7 G730 BAD Record No: H020202)
3 Badruddin, M.; Skogerboe, G. V.; Shafique, M. S. (Eds.) 1996. Proceedings of the National Conference on Managing Irrigation for Environmentally Sustainable Agriculture in Pakistan, Islamabad, Pakistan, 5-7 November 1996. Volume IV - papers on the theme, Environmental management of irrigated lands. Lahore, Pakistan: International Irrigation Management Institute (IIMI) Pakistan. National Program. 218p.
Irrigation management ; Soil salinity ; Sodic soils ; Soil degradation ; Soil reclamation ; GIS ; Agricultural production ; Salinity control ; Irrigated farming ; Sustainable agriculture / Pakistan / Punjab / Chishtian Sub-Division / Rechna Doab / Lower Chenab Canal System
(Location: IWMI HQ Call no: IIMI 631.7 G730 BAD Record No: H020194)
4 Waqas, M. M.; Shah, S. H. H.; Awan, Usman Khalid; Waseem, M.; Ahmad, I.; Fahad, M.; Niaz, Y.; Ali, S. 2020. Evaluating the impact of climate change on water productivity of maize in the semi-arid environment of Punjab, Pakistan. Sustainability, 12(9):3905. (Special issue: Climate Resilient Sustainable Agricultural Production Systems) [doi: https://doi.org/10.3390/su12093905]
Climate change ; Impact assessment ; Water productivity ; Crop production ; Maize ; Semiarid zones ; Soil hydraulic properties ; Groundwater recharge ; Irrigation systems ; Precipitation ; Temperature ; Rain ; Models / Pakistan / Punjab / Lower Chenab Canal system
(Location: IWMI HQ Call no: e-copy only Record No: H050210)
(1.37 MB) (1.37 MB)
Impact assessments on climate change are essential for the evaluation and management of irrigation water in farming practices in semi-arid environments. This study was conducted to evaluate climate change impacts on water productivity of maize in farming practices in the Lower Chenab Canal (LCC) system. Two fields of maize were selected and monitored to calibrate and validate the model. A water productivity analysis was performed using the Soil–Water–Atmosphere–Plant (SWAP) model. Baseline climate data (1980–2010) for the study site were acquired from the weather observatory of the Pakistan Meteorological Department (PMD). Future climate change data were acquired from the Hadley Climate model version 3 (HadCM3). Statistical downscaling was performed using the Statistical Downscaling Model (SDSM) for the A2 and B2 scenarios of HadCM3. The water productivity assessment was performed for the midcentury (2040–2069) scenario. The maximum increase in the average maximum temperature (Tmax) and minimum temperature (Tmin) was found in the month of July under the A2 and B2 scenarios. The scenarios show a projected increase of 2.8 C for Tmax and 3.2 C for Tmin under A2 as well as 2.7 C for Tmax and 3.2 C for Tmin under B2 for the midcentury. Similarly, climate change scenarios showed that temperature is projected to decrease, with the average minimum and maximum temperatures of 7.4 and 6.4 C under the A2 scenario and 7.7 and 6.8 C under the B2 scenario in the middle of the century, respectively. However, the highest precipitation will decrease by 56 mm under the A2 and B2 scenarios in the middle of the century for the month of September. The input and output data of the SWAP model were processed in R programming for the easy working of the model. The negative impact of climate change was found under the A2 and B2 scenarios during the midcentury. The maximum decreases in Potential Water Productivity (WPET) and Actual Water Productivity (WPAI) from the baseline period to the midcentury scenario of 1.1 to 0.85 kgm-3 and 0.7 to 0.56 kgm-3 were found under the B2 scenario. Evaluation of irrigation practices directs the water managers in making suitable water management decisions for the improvement of water productivity in the changing climate.
5 Nazeer, A.; Waqas, M. M.; Ali, S.; Awan, U. K.; Cheema, M. J. M.; Baksh, A. 2020. Land use land cover classification and wheat yield prediction in the Lower Chenab Canal System using remote sensing and GIS. Big Data In Agriculture, 2(2):47-51. [doi: https://doi.org/10.26480/bda.02.2020.47.51]
Crop yield ; Forecasting ; Wheat ; Land use ; Land cover ; Normalized difference vegetation index ; Remote sensing ; Geographical information systems ; Landsat ; Satellite imagery ; Canals / Pakistan / Lower Chenab Canal System / Khurrian Wala Distributary / Killian Wala Distributary / Mungi Distributary
(Location: IWMI HQ Call no: e-copy only Record No: H050212)
https://bigdatainagriculture.com/paper/issue2%202020/2bda2020-47-51.pdf
https://vlibrary.iwmi.org/pdf/H050212.pdf
https://vlibrary.iwmi.org/pdf/H050212.pdf
(1.40 MB) (1.40 MB)
Reliable and timely information regarding area under wheat and its yield prediction can help in better management of the commodity. The remotely sensed data especially in combination with Geographic Information System (GIS) can provide an important and powerful tool for both, land use land cover (LULC) classification and crop yield prediction. The study objectives include LULC classification and wheat yield prediction. The study was conducted for Rabi Season from Nov. 2011 to April 2012, in the command area of three distributaries i.e. Khurrian Wala, Killian Wala and Mungi of Lower Chennai Canal (LCC) system. The Landsat-7 imagery data with spatial resolution of 30 m was used for this study. Physical features were monitored and assessed using Normalized Difference Vegetative Index (NDVI). LULC classification was done for wheat and non-wheat area which shows wheat proportion and area 87.22% and 28867.95 Ha in Khurrian wala, 71.07% and 22423.20 Ha in Killian Wala and 79.18% and 17974.34 Ha in Mungi distributary, respectively. The correlation values between maximum NDVI value and yield data were 0.45, 0.36 and 0.39 for Khurrian Wala, Killian Wala and Mungi distributary, respectively. On the basis of this correlation, average wheat yield was estimated as 3.48 T/Ha, 3.83 T/Ha and 3.80 T/Ha for Khurrian Wala, Killian Wala and Mungi distributary, respectively.
6 Waqas, M. M.; Niaz, Y.; Ali, S.; Ahmad, I.; Fahad, M.; Rashid, H.; Awan, U. K. 2020. Soil salinity mapping using satellite remote sensing: a case study of Lower Chenab Canal System, Punjab. Earth Sciences Pakistan, 4(1):07-09. [doi: https://doi.org/10.26480/esp.01.2020.07.09]
Soil salinity ; Mapping ; Canals ; Irrigation schemes ; Satellite imagery ; Remote sensing ; Groundwater ; Landsat ; Normalized difference vegetation index ; Case studies / Pakistan / Punjab / Indus Basin / Lower Chenab Canal System
(Location: IWMI HQ Call no: e-copy only Record No: H050213)
https://earthsciencespakistan.com/archives/1esp2020/1esp2020-07-09.pdf
https://vlibrary.iwmi.org/pdf/H050213.pdf
https://vlibrary.iwmi.org/pdf/H050213.pdf
(0.31 MB) (318 KB)
Salinity is the most important factor of consideration for the water management policies. The water availability from the rootzone reduced with the increase in the soil salinity due to the increase in the osmatic pressure. In Pakistan, salinity is the major threat to the agriculture land due to the tradition practices of irrigation and extensive utilization of the groundwater to meet the cope the irrigation water requirement of high intensity cropping system. The salinity impact is spatially variable on the canal commands area of the irrigation system. There is dire need to map the spatially distributed soil salinity with the high resolution. Landsat satellite imagery provides an opportunity to have 30m pixel information in seven spectral wavelength ranges. In this study, the soil salinity mapping was performed using pixel information on visible and infrared bands for 2015. These bands were also used to infer Normalized Difference Vegetation Index (NDVI). The raw digital numbers were converted into soil salinity information. The accuracy assessment was carried out using ground trothing information obtained using the error matrix method. Four major classes of non-saline, marginal saline, moderate saline and strongly, saline area was mapped. The overall accuracy of the classified map was found 83%. These maps can be helpful to delineate hot spots with severe problem of soil salinity in order to prepare reciprocate measures for improvement.
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