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Mr. Talha Mahmood
Geoecology, Institut für Geowissenschaften und Geographie,Martin Luther Universität Halle

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Research Keywords & Expertise

0 Agricultural Engineering
0 Water Resources
0 Sythetic aperture radar imaging
0 Remote sensing & GIS applications in Agriculture and Forestry
0 Crop Modeling

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Journal article
Published: 16 November 2020 in Sustainability
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Water crises are becoming severe in recent times, further fueled by population increase and climate change. They result in complex and unsustainable water management. Spatial estimation of consumptive water use is vital for performance assessment of the irrigation system using Remote Sensing (RS). For this study, its estimation is done using the Soil Energy Balance Algorithm for Land (SEBAL) approach. Performance indicators including equity, adequacy, and reliability were worked out at various spatiotemporal scales. Moreover, optimization and sustainable use of water resources are not possible without knowing the factors mainly influencing consumptive water use of major crops. For that purpose, random forest regression modelling was employed using various sets of factors for site-specific, proximity, and cropping system. The results show that the system is underperforming both for Kharif (i.e., summer) and Rabi (i.e., winter) seasons. Performance indicators highlight poor water distribution in the system, a shortage of water supply, and unreliability. The results are relatively good for Rabi as compared to Kharif, with an overall poor situation for both seasons. Factors importance varies for different crops. Overall, distance from canal, road density, canal density, and farm approachability are the most important factors for explaining consumptive water use. Auditing of consumptive water use shows the potential for resource optimization through on-farm water management by the targeted approach. The results are based on the present situation without considering future changes in canal water supply and consumptive water use under climate change.

ACS Style

Muhammad Usman; Talha Mahmood; Christopher Conrad; Habib Bodla. Remote Sensing and Modelling Based Framework for Valuing Irrigation System Efficiency and Steering Indicators of Consumptive Water Use in an Irrigated Region. Sustainability 2020, 12, 9535 .

AMA Style

Muhammad Usman, Talha Mahmood, Christopher Conrad, Habib Bodla. Remote Sensing and Modelling Based Framework for Valuing Irrigation System Efficiency and Steering Indicators of Consumptive Water Use in an Irrigated Region. Sustainability. 2020; 12 (22):9535.

Chicago/Turabian Style

Muhammad Usman; Talha Mahmood; Christopher Conrad; Habib Bodla. 2020. "Remote Sensing and Modelling Based Framework for Valuing Irrigation System Efficiency and Steering Indicators of Consumptive Water Use in an Irrigated Region." Sustainability 12, no. 22: 9535.

Original article
Published: 23 September 2020 in Environmental Earth Sciences
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Land use and land cover (LULC) change is one of the key driving elements responsible for altering the hydrology of a watershed. In this study, we investigated the spatio-temporal LULC changes between 2001 and 2018 and their impacts on the water balance of the Jhelum River Basin. The Soil and Water Assessment Tool (SWAT) was used to analyze the impacts on water yield (WY) and evapotranspiration (ET). The model was calibrated and validated with discharge data between 1995 and 2005 and then simulated with different land use. The increase was observed in forest, settlement and water areas during the study period. At the catchment scale, we found that afforestation has reduced the WY and surface runoff, while enhanced the ET. Moreover, this change was more pronounced at the sub-basin scale. Some sub-basins, especially in the northern part of the study area, exhibited an increase in WY due to an increase in the snow cover area. Similarly, extremes land use scenarios also showed significant impact on water balance components. The basin WY has decreased by 38 mm/year and ET has increased about 36 mm/year. The findings of this study could guide the watershed manager in the development of sustainable LULC planning and water resources management.

ACS Style

Naeem Saddique; Talha Mahmood; Christian Bernhofer. Quantifying the impacts of land use/land cover change on the water balance in the afforested River Basin, Pakistan. Environmental Earth Sciences 2020, 79, 1 -13.

AMA Style

Naeem Saddique, Talha Mahmood, Christian Bernhofer. Quantifying the impacts of land use/land cover change on the water balance in the afforested River Basin, Pakistan. Environmental Earth Sciences. 2020; 79 (19):1-13.

Chicago/Turabian Style

Naeem Saddique; Talha Mahmood; Christian Bernhofer. 2020. "Quantifying the impacts of land use/land cover change on the water balance in the afforested River Basin, Pakistan." Environmental Earth Sciences 79, no. 19: 1-13.

Proceedings
Published: 16 November 2017 in Proceedings
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Drought is a continuous process in Thar Desert, Pakistan. The extent of this drought needs to be assessed for future land use and adaptation. The effect of previous drought on vegetation cover of the Thar region was studied, through combined use of drought indices and geographic information (GIS) techniques. Five years (2002, 2005, 2008, 2011 and 2014) were selected to analyze the drought conditions and land use pattern of the Thar region. The drought indices used in this study included the Normalized Difference Vegetation Index (NDVI) and the Standard Precipitation Index (SPI). Images of past drought were compared with post-drought images of our targeted area and land use maps were developed for spatio-temporal analysis. The results of the study revealed that vegetation in Thar showed an improving trend from 2002 to 2011 and then declined from 2011 to 2014. The rainfall occurred at a below average rate and SPI values for each year were calculated to be negative, indicating below average rainfall. This actual precipitation data was then compared with the data obtained from the Tropical Rainfall Measuring Mission (TRMM) satellite and R2; Pearson correlation coefficients were also calculated. The R2 values for the years 2002 and 2014 were 0.519 and 0.670 respectively. In the same manner, the Pearson correlation coefficient values for the years 2002 and 2014 were 0.721 and 0.867 respectively. The results showed the TRMM satellite’s over-estimation in calculating rainfall data. Further, the average temperature for the five years under study was analyzed by graphical representation and it was revealed that the temperature of Thar has increased by almost 1 °C during the last decade.

ACS Style

Muhammad Bilal; Muhammad Usman Liaqat; Muhammad Jehanzeb Masud Cheema; Talha Mahmood; Qasim Khan. Spatial Drought Monitoring in Thar Desert Using Satellite-Based Drought Indices and Geo-Informatics Techniques. Proceedings 2017, 2, 179 .

AMA Style

Muhammad Bilal, Muhammad Usman Liaqat, Muhammad Jehanzeb Masud Cheema, Talha Mahmood, Qasim Khan. Spatial Drought Monitoring in Thar Desert Using Satellite-Based Drought Indices and Geo-Informatics Techniques. Proceedings. 2017; 2 (5):179.

Chicago/Turabian Style

Muhammad Bilal; Muhammad Usman Liaqat; Muhammad Jehanzeb Masud Cheema; Talha Mahmood; Qasim Khan. 2017. "Spatial Drought Monitoring in Thar Desert Using Satellite-Based Drought Indices and Geo-Informatics Techniques." Proceedings 2, no. 5: 179.

Journal article
Published: 01 June 2017 in Computers and Electronics in Agriculture
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Crop yield estimation for food security and management plans.Prediction performance between MODIS and LANDSAT 8 for yield estimation.SAVI exhibited strong relationship in cropping area of Irrigated Indus Basin.Wheat yield estimated by Landsat SAVI has strong relationship rather than MODIS. Crop yield estimation has significant importance for policy makers to make timely dicisions on import/export of particular crop. Traditionally, in Pakistan crop yield estimation is being carried out by Village Master Sampling (VMS) that is laborious and time-consuming. Satellite imagery is also being used as an alternative to estimate vegetation health and yield. Various vegetation indices are being used for the purpose however, their efficiency to estimate yield has not been tested. In this study, a comparison was performed among various satellite-based vegetation indices e.g. Soil Adjusted Vegetation Index (SAVI), Modified Soil Adjusted Vegetation Index (MSAVI) Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), to evaluate most appropriate index that performs better in cropping area of irrigated Indus Basin (a complex basin with spatially heterogeneous land use). A stepwise regression based model was developed for remotely sensed crop (i.e. Wheat) using multi-band MODIS and Landsat 8 products based on Land use and Land cover map developed by Semi-Supervised Classification. The results revealed that SAVI showed a fairly acceptable association with reported yield data as compared to other indices. The correlation coefficient (R2) was estimated at 0.60. Yield estimated by SAVI obtained from Landsat 8 showed good results with R2 and Pearson correlation (r), estimated at 0.74 and 0.88 as compared to SAVI obtained from MODIS with 0.63 and 0.79 respectively. The results support that SAVI vegetation indices is reliable for quick and efficient wheat area mapping under Pakistanis farm conditions.

ACS Style

Muhammad Usman Liaqat; Muhammad Jehanzeb Masud Cheema; Wenjiang Huang; Talha Mahmood; Muhammad Zaman; Muhammad Mohsin Khan. Evaluation of MODIS and Landsat multiband vegetation indices used for wheat yield estimation in irrigated Indus Basin. Computers and Electronics in Agriculture 2017, 138, 39 -47.

AMA Style

Muhammad Usman Liaqat, Muhammad Jehanzeb Masud Cheema, Wenjiang Huang, Talha Mahmood, Muhammad Zaman, Muhammad Mohsin Khan. Evaluation of MODIS and Landsat multiband vegetation indices used for wheat yield estimation in irrigated Indus Basin. Computers and Electronics in Agriculture. 2017; 138 ():39-47.

Chicago/Turabian Style

Muhammad Usman Liaqat; Muhammad Jehanzeb Masud Cheema; Wenjiang Huang; Talha Mahmood; Muhammad Zaman; Muhammad Mohsin Khan. 2017. "Evaluation of MODIS and Landsat multiband vegetation indices used for wheat yield estimation in irrigated Indus Basin." Computers and Electronics in Agriculture 138, no. : 39-47.