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Spatio-temporal distribution of irrigation water components was evaluated at the canal command area in Indus Basin Irrigation System (IBIS) by using a remote sensing-based geo-informatics approach. Satellite-derived MODIS product-based Surface Energy Balance Algorithm for Land (SEBAL) was used for the estimation of the actual evapotranspiration (ETa). The ground data-based advection aridity method (AA) was used to calibrate and validate the model. Statistical analysis of the SEBAL based ETa and AA shows the mean values of 87.1 mm and 47.9 mm during Kharif season (May–November) and 100 mm and 77 mm during the Rabi Season (December–April). Mean NSEs of 0.72 and 0.85 and RMSEs 34.9 and 5.76 during the Kharif and the Rabi seasons were observed for ETa and AA, respectively. Rainfall data were calibrated with the point observatory data of the metrological stations. The average annual ETa was found 899 mm for defined four cropping years (2011–2012 to 2014–2015) with the minimum average value of 63.3 mm in January and the maximum average value of 110.6 mm in August. Average of the sum of net canal water use (NCWU) and rainfall during the study period of four years was 548 mm (36% of ETa). Seasonal analysis revealed 39% and 61% of groundwater extraction proportion during Rabi and Kharif seasons, dependent upon the occurrence of rainfall and crop phenology. Overall, the results provide insight into the interrelationships between key water resources management components and the variation of these through time, offering information to improve the strategic planning and management of available water resources in this region.
Muhammad Mohsin Waqas; Muhammad Waseem; Sikandar Ali; Megersa Kebede Leta; Adnan Noor Shah; Usman Khalid Awan; Syed Hamid Hussain Shah; Tao Yang; Sami Ullah. Evaluating the Spatio-Temporal Distribution of Irrigation Water Components for Water Resources Management Using Geo-Informatics Approach. Sustainability 2021, 13, 8607 .
AMA StyleMuhammad Mohsin Waqas, Muhammad Waseem, Sikandar Ali, Megersa Kebede Leta, Adnan Noor Shah, Usman Khalid Awan, Syed Hamid Hussain Shah, Tao Yang, Sami Ullah. Evaluating the Spatio-Temporal Distribution of Irrigation Water Components for Water Resources Management Using Geo-Informatics Approach. Sustainability. 2021; 13 (15):8607.
Chicago/Turabian StyleMuhammad Mohsin Waqas; Muhammad Waseem; Sikandar Ali; Megersa Kebede Leta; Adnan Noor Shah; Usman Khalid Awan; Syed Hamid Hussain Shah; Tao Yang; Sami Ullah. 2021. "Evaluating the Spatio-Temporal Distribution of Irrigation Water Components for Water Resources Management Using Geo-Informatics Approach." Sustainability 13, no. 15: 8607.
Forests across the world are considered to be a huge socio-economic and environmental benefit to host and adjacent communities. This study focuses on assessing the impacts of fuelwood and timber consumption on the livelihood of households in the Baltistan region in Pakistan. Primary and secondary sources of data were employed for the study. The primary sources involved the use of questionnaire survey and interview while the secondary sources involved the use of documented information in textbooks and internet materials. The study revealed that 82% of the people within the region were involved in agricultural activities, 71% depended on the extraction of forest resources for their livelihood, while 18% depended on off-farm activities for their livelihood. The study also observed that among the number that depended on forest resources for their livelihood, 59% were involved in the extraction of non-timber forest products while 41% were involved in the extraction of timber forest resources. The study further revealed that there was no significant difference in the level of benefits from the forest across the seven districts under investigation with a chi square value. The volume of forest products extraction was found to be high closest to the forest and to be low with increasing distance from the communities. The major benefits from the forest range were due to employment that increases the individual and family income. Forest also helps to control erosion and enhances aesthetic beautification and temperature regulation. The research suggests that the policy makers must provide a sustainable solution to reduce the overexploitation of the forest resources by providing better alternative earning resources to the resident communities.
Saif Ullah; Rana Noor; Ali Abid; Richard Mendako; Muhammad Waqas; Adnan Shah; Gang Tian. Socio-Economic Impacts of Livelihood from Fuelwood and Timber Consumption on the Sustainability of Forest Environment: Evidence from Basho Valley, Baltistan, Pakistan. Agriculture 2021, 11, 596 .
AMA StyleSaif Ullah, Rana Noor, Ali Abid, Richard Mendako, Muhammad Waqas, Adnan Shah, Gang Tian. Socio-Economic Impacts of Livelihood from Fuelwood and Timber Consumption on the Sustainability of Forest Environment: Evidence from Basho Valley, Baltistan, Pakistan. Agriculture. 2021; 11 (7):596.
Chicago/Turabian StyleSaif Ullah; Rana Noor; Ali Abid; Richard Mendako; Muhammad Waqas; Adnan Shah; Gang Tian. 2021. "Socio-Economic Impacts of Livelihood from Fuelwood and Timber Consumption on the Sustainability of Forest Environment: Evidence from Basho Valley, Baltistan, Pakistan." Agriculture 11, no. 7: 596.
The conservation of forest in the northern areas of Pakistan is the major priority of the national environmental policy to fight against global warming. Despite the policy for the protection of forest, rural residents’ behavior toward economic incentives for deforestation may undermine their conservation goals. Therefore, the purpose of this study was to understand the factors that affect the illegal behaviors related to deforestation in the northern areas of Pakistan. The present study applied the socio-psychological theory of planned behavior to predict the behavioral intention of rural residents toward economic incentives for deforestation. Correlations were explored between background factors toward motivations for deforestation based on positive and negative views through open-ended questions. Attitude and descriptive norm were found good predictors to perceive the behaviors. The findings of the study suggest that rural communities’ support for compliance with policies is vital for the long-term efficacy and protection of the forest in the region. Further, change in the behaviors of inhabitants toward the ecosystem through training can be improved to manage the forest.
Saif Ullah; Ali Abid; Waqas Aslam; Rana Noor; Muhammad Waqas; Tian Gang. Predicting Behavioral Intention of Rural Inhabitants toward Economic Incentive for Deforestation in Gilgit-Baltistan, Pakistan. Sustainability 2021, 13, 617 .
AMA StyleSaif Ullah, Ali Abid, Waqas Aslam, Rana Noor, Muhammad Waqas, Tian Gang. Predicting Behavioral Intention of Rural Inhabitants toward Economic Incentive for Deforestation in Gilgit-Baltistan, Pakistan. Sustainability. 2021; 13 (2):617.
Chicago/Turabian StyleSaif Ullah; Ali Abid; Waqas Aslam; Rana Noor; Muhammad Waqas; Tian Gang. 2021. "Predicting Behavioral Intention of Rural Inhabitants toward Economic Incentive for Deforestation in Gilgit-Baltistan, Pakistan." Sustainability 13, no. 2: 617.
Low planting density and deficient nitrogen application are factors that significantly decrease the yield of pearl millet in Pakistan. Optimizing their management is imperative in increasing millet production efficiency, especially with N fertilization, which can strongly affect hybrid millet response. Therefore, a field experiment was conducted at the Agronomic Research Area, University of Agriculture, Faisalabad (semi-arid) and the Agronomic Research Station, Karor Lal Eason, District Layyah (arid) over two summer seasons (2015 and 2016). The experiment consisted of three intra-row spacings (10, 15, and 20 cm) as main plots, while four nitrogen rates (0, 150, 200, and 250 kg ha−1) were randomized in subplots. The treatments were triplicated each year at both locations. The results depicted a significant change in millet crop development with a change in planting density and nitrogen rate in semi-arid and arid environments. The decrease in planting density resulted 1–2 day(s) delay in 50% flowering, milking, and maturity in semi-arid and arid region during both years of study. Higher dry matter accumulation was observed at medium planting density (15 cm intra-row spacing) and higher levels of nitrogen (250 kg ha−1) at both locations and growing seasons. The yield and attributed yield performed well with 15-cm plant spacing coupled with N application from 150–200 kg ha−1, and resulted in high nitrogen use efficiency (NUE). The results of the quadratic relationship and economic analysis linked with yield and nitrogen levels at 15-cm spacing showed 176 and 181 kg N ha−1 optimum levels (mean of years) against the economic N levels of 138 and 137 kg N ha−1 for Faisalabad and Layyah, respectively. The benefit–cost ratio (BCR) showed 31% and 45% mean excessive N at 200 and 250 kg N ha−1, in Faisalabad and Layyah, respectively. So, it is concluded that the optimum economic level of N should be sought out according to the soil and climate of an area for the production of hybrid pearl millet on a sustainable basis.
Asmat Ullah; Ishfaq Ahmad; Muhammad Ur Rahman; Muhammad Waseem; Muhammad Waqas; Muhammad Bhatti; Ashfaq Ahmad. Optimizing Management Options through Empirical Modeling to Improve Pearl Millet Production for Semi-Arid and Arid Regions of Punjab, Pakistan. Sustainability 2020, 12, 7715 .
AMA StyleAsmat Ullah, Ishfaq Ahmad, Muhammad Ur Rahman, Muhammad Waseem, Muhammad Waqas, Muhammad Bhatti, Ashfaq Ahmad. Optimizing Management Options through Empirical Modeling to Improve Pearl Millet Production for Semi-Arid and Arid Regions of Punjab, Pakistan. Sustainability. 2020; 12 (18):7715.
Chicago/Turabian StyleAsmat Ullah; Ishfaq Ahmad; Muhammad Ur Rahman; Muhammad Waseem; Muhammad Waqas; Muhammad Bhatti; Ashfaq Ahmad. 2020. "Optimizing Management Options through Empirical Modeling to Improve Pearl Millet Production for Semi-Arid and Arid Regions of Punjab, Pakistan." Sustainability 12, no. 18: 7715.
The frozen water reserves on the Earth are not only very dynamic in their nature, but also have significant effects on hydrological response of complex and dynamic river basins. The Indus basin is one of the most complex river basins in the world and receives most of its share from the Asian Water Tower (Himalayas). In such a huge river basin with high-altitude mountains, the regular quantification of snow cover is a great challenge to researchers for the management of downstream ecosystems. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) daily (MOD09GA) and 8-day (MOD09A1) products were used for the spatiotemporal quantification of snow cover over the Indus basin and the western rivers’ catchments from 2008 to 2018. The high-resolution Landsat Enhanced Thematic Mapper Plus (ETM+) was used as a standard product with a minimum Normalized Difference Snow Index (NDSI) threshold (0.4) to delineate the snow cover for 120 scenes over the Indus basin on different days. All types of errors of commission/omission were masked out using water, sand, cloud, and forest masks at different spatiotemporal resolutions. The snow cover comparison of MODIS products with Landsat ETM+, in situ snow data and Google Earth imagery indicated that the minimum NDSI threshold of 0.34 fits well compared to the globally accepted threshold of 0.4 due to the coarser resolution of MODIS products. The intercomparison of the time series snow cover area of MODIS products indicated R2 values of 0.96, 0.95, 0.97, 0.96 and 0.98, for the Chenab, Jhelum, Indus and eastern rivers’ catchments and Indus basin, respectively. A linear least squares regression analysis of the snow cover area of the Indus basin indicated a declining trend of about 3358 and 2459 km2 per year for MOD09A1 and MOD09GA products, respectively. The results also revealed a decrease in snow cover area over all the parts of the Indus basin and its sub-catchments. Our results suggest that MODIS time series NDSI analysis is a useful technique to estimate snow cover over the mountainous areas of complex river basins.
Sikandar Ali; Muhammad Cheema; Muhammad Waqas; Muhammad Waseem; Usman Awan; Tasneem Khaliq. Changes in Snow Cover Dynamics over the Indus Basin: Evidences from 2008 to 2018 MODIS NDSI Trends Analysis. Remote Sensing 2020, 12, 2782 .
AMA StyleSikandar Ali, Muhammad Cheema, Muhammad Waqas, Muhammad Waseem, Usman Awan, Tasneem Khaliq. Changes in Snow Cover Dynamics over the Indus Basin: Evidences from 2008 to 2018 MODIS NDSI Trends Analysis. Remote Sensing. 2020; 12 (17):2782.
Chicago/Turabian StyleSikandar Ali; Muhammad Cheema; Muhammad Waqas; Muhammad Waseem; Usman Awan; Tasneem Khaliq. 2020. "Changes in Snow Cover Dynamics over the Indus Basin: Evidences from 2008 to 2018 MODIS NDSI Trends Analysis." Remote Sensing 12, no. 17: 2782.
The ongoing global warming and changing patterns of precipitation have significant implications for crop yields. Process-based models are the most commonly used method to assess the impacts of projected climate changes on crop yields. In this study, the crop-environment resource synthesis (CERES)-Maize 4.6.7 model was used to project the maize crop yield in the Shaanxi Province of China over future periods. In this context, the downscaled ensemble projections of 17 general circulation models (GCMs) under four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5) were used as input for the calibrated CERES-Maize model. Results showed a negative correlation between temperature and maize yield in the study area. It is expected that each 1.0 °C rise in seasonal temperature will cause up to a 9% decrease in the yield. However, the influence of CO2 fertilization showed a positive response, as witnessed by the increase in the crop yield. With CO2 fertilization, the average increase in the maize crop yield compared to without CO2 fertilization per three decades was 10.5%, 11.6%, TA7.8%, and 6.5% under the RCP2.6, RCP4.5, RCP6.0, and RCP8.5 scenarios, respectively. An elevated CO2 concentration showed a pronounced positive impact on the rain-fed maize yield compared to the irrigated maize yield. The average water use efficiency (WUE) was better at elevated CO2 concentrations and improved by 7–21% relative to the without CO2 fertilization of the WUE. Therefore, future climate changes with elevated CO2 are expected to be favorable for maize yields in the Shaanxi Province of China, and farmers can expect further benefits in the future from growing maize.
Qaisar Saddique; Muhammad Khan; Muhammad Habib Ur Rahman; Xu Jiatun; Muhammad Waseem; Thomas Gaiser; Muhammad Mohsin Waqas; Ijaz Ahmad; Li Chong; Huanjie Cai. Effects of Elevated Air Temperature and CO2 on Maize Production and Water Use Efficiency under Future Climate Change Scenarios in Shaanxi Province, China. Atmosphere 2020, 11, 843 .
AMA StyleQaisar Saddique, Muhammad Khan, Muhammad Habib Ur Rahman, Xu Jiatun, Muhammad Waseem, Thomas Gaiser, Muhammad Mohsin Waqas, Ijaz Ahmad, Li Chong, Huanjie Cai. Effects of Elevated Air Temperature and CO2 on Maize Production and Water Use Efficiency under Future Climate Change Scenarios in Shaanxi Province, China. Atmosphere. 2020; 11 (8):843.
Chicago/Turabian StyleQaisar Saddique; Muhammad Khan; Muhammad Habib Ur Rahman; Xu Jiatun; Muhammad Waseem; Thomas Gaiser; Muhammad Mohsin Waqas; Ijaz Ahmad; Li Chong; Huanjie Cai. 2020. "Effects of Elevated Air Temperature and CO2 on Maize Production and Water Use Efficiency under Future Climate Change Scenarios in Shaanxi Province, China." Atmosphere 11, no. 8: 843.
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.
Muhammad Mohsin Waqas; Syed Hamid Hussain Shah; Usman Khalid Awan; Muhammad Waseem; Ishfaq Ahmad; Muhammad Fahad; Yasir Niaz; Sikandar Ali. Evaluating the Impact of Climate Change on Water Productivity of Maize in the Semi-Arid Environment of Punjab, Pakistan. Sustainability 2020, 12, 3905 .
AMA StyleMuhammad Mohsin Waqas, Syed Hamid Hussain Shah, Usman Khalid Awan, Muhammad Waseem, Ishfaq Ahmad, Muhammad Fahad, Yasir Niaz, Sikandar Ali. Evaluating the Impact of Climate Change on Water Productivity of Maize in the Semi-Arid Environment of Punjab, Pakistan. Sustainability. 2020; 12 (9):3905.
Chicago/Turabian StyleMuhammad Mohsin Waqas; Syed Hamid Hussain Shah; Usman Khalid Awan; Muhammad Waseem; Ishfaq Ahmad; Muhammad Fahad; Yasir Niaz; Sikandar Ali. 2020. "Evaluating the Impact of Climate Change on Water Productivity of Maize in the Semi-Arid Environment of Punjab, Pakistan." Sustainability 12, no. 9: 3905.
Aftab Nazeer; Muhammad Mohsin Waqas; Sikandar Ali; Usman Khalid Awan; Muhammad Jehanzeb Masu Cheema; Allah Baksh. LAND USE LAND COVER CLASSIFICATION AND WHEAT YIELD PREDICTION IN THE LOWER CHENAB CANAL SYSTEM USING REMOTE SENSING AND GIS. Big Data In Agriculture 2020, 2, 47 -51.
AMA StyleAftab Nazeer, Muhammad Mohsin Waqas, Sikandar Ali, Usman Khalid Awan, Muhammad Jehanzeb Masu Cheema, Allah Baksh. LAND USE LAND COVER CLASSIFICATION AND WHEAT YIELD PREDICTION IN THE LOWER CHENAB CANAL SYSTEM USING REMOTE SENSING AND GIS. Big Data In Agriculture. 2020; 2 (2):47-51.
Chicago/Turabian StyleAftab Nazeer; Muhammad Mohsin Waqas; Sikandar Ali; Usman Khalid Awan; Muhammad Jehanzeb Masu Cheema; Allah Baksh. 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, no. 2: 47-51.