Your search found 4 records
1 Mehmood, Q.; Mehmood, W.; Awais, M.; Rashid, H.; Rizwan, M.; Anjum, L.; Muneer, M. A.; Niaz, Y.; Hamid, S. 2020. Optimizing groundwater quality exploration for irrigation water wells using geophysical technique in semi-arid irrigated area of Pakistan. Groundwater for Sustainable Development, 11:100397. (Online first) [doi: https://doi.org/10.1016/j.gsd.2020.100397]
Groundwater ; Water quality ; Irrigation water ; Tube wells ; Semiarid zones ; Geophysics ; Techniques ; Aquifers ; Pumping ; Hydrogeology ; Models / Pakistan / Punjab / Okara District / Indus Basin
(Location: IWMI HQ Call no: e-copy only Record No: H049764)
(1.45 MB)
Geophysical method using vertical electrical sounding (VES) technique, in combination with borehole lithological data analysis was used to locate the subsurface layers containing good quality water in District Okara, Punjab Pakistan. Ten VES surveys (VES-1-10) were conducted by utilizing the Schlumberger electrode configuration. A calibrated model was developed for the study area by integrating the resistivity and lithological data. The model showed that the study area has three geoelectric layers below the water table with resistivities 50-100 O-m, 25-50 O-m and <25 O-m describing the good, marginal and poor quality water layers respectively. Integrated data analysis show that six sites (i.e., VES-1, VES-2, VES-3, VES-5, VES-7, & VES-10) have layers of good quality water at different depths. Out of these 6 sites, 3 sites (VES-3, VES-7 and VES-10) are suitable for installing the irrigation water wells in terms of water quality and potential while the remaining three sites (VES-1, VES-2 and VES-5) were not suitable due to shallow thickness of good quality aquifer. Three sites VES-3, VES-5 and VES-10 were selected for drilling in order to validate the modeled results, samples were collected from each 1.5–3.0 m depth for the laboratory analysis. The results showed that the resistivity data were in close agreement with the lithological data and VES-10 was most suitable for groundwater extraction. An Irrigation tube-well was installed at VES-10 and its quality was monitored for one year which showed successful supply of groundwater in terms of quality and potential.
2 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.
3 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.
4 Ijaz, M. A.; Ashraf, M.; Hamid, S.; Niaz, Y.; Waqas, M. M.; Tariq, M. A. U. R.; Saifullah, M.; Bhatti, Muhammad Tousif; Tahir, A. A.; Ikram, K.; Shafeeque, M.; Ng, A. W. M. 2022. Prediction of sediment yield in a data-scarce river catchment at the sub-basin scale using gridded precipitation datasets. Water, 14(9):1480. (Special issue: Innovate Approaches to Sustainable Water Resource Management under Population Growth, Lifestyle Improvements, and Climate Change) [doi: https://doi.org/10.3390/w14091480]
Sediment yield ; Forecasting ; River basins ; Catchment areas ; Precipitation ; Datasets ; Hydrological modelling ; Watershed management ; Dams ; Runoff ; Sediment load ; Soil erosion ; Soil types ; Land use ; Rain ; Semiarid zones ; Spatial distribution / Pakistan / Gomal River Catchment / Kot Murtaza Barrage / Gomal Zam Dam
(Location: IWMI HQ Call no: e-copy only Record No: H051151)
https://www.mdpi.com/2073-4441/14/9/1480/pdf?version=1652347380
https://vlibrary.iwmi.org/pdf/H051151.pdf
https://vlibrary.iwmi.org/pdf/H051151.pdf
(2.15 MB) (2.15 MB)
Water-related soil erosion is a major environmental concern for catchments with barren topography in arid and semi-arid regions. With the growing interest in irrigation infrastructure development in arid regions, the current study investigates the runoff and sediment yield for the Gomal River catchment, Pakistan. Data from a precipitation gauge and gridded products (i.e., GPCC, CFSR, and TRMM) were used as input for the SWAT model to simulate runoff and sediment yield. TRMM shows a good agreement with the data of the precipitation gauge (˜1%) during the study period, i.e., 2004–2009. However, model simulations show that the GPCC data predicts runoff better than the other gridded precipitation datasets. Similarly, sediment yield predicted with the GPCC precipitation data was in good agreement with the computed one at the gauging site (only 3% overestimated) for the study period. Moreover, GPCC overestimated the sediment yield during some years despite the underestimation of flows from the catchment. The relationship of sediment yields predicted at the sub-basin level using the gauge and GPCC precipitation datasets revealed a good correlation (R2 = 0.65) and helped identify locations for precipitation gauging sites in the catchment area. The results at the sub-basin level showed that the sub-basin located downstream of the dam site contributes three (3) times more sediment yield (i.e., 4.1%) at the barrage than its corresponding area. The findings of the study show the potential usefulness of the GPCC precipitation data for the computation of sediment yield and its spatial distribution over data-scarce catchments. The computations of sediment yield at a spatial scale provide valuable information for deciding watershed management strategies at the sub-basin level.
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