Changes in land use and land cover affect the social, economic and natural aspects of any area. Mostly land use and land cover (LULC) changes are the result of population growth and human activities in the form of urban agglomerations and industrialization etc. Physical factors like soil structure and type, slope condition, topography are main aspects. Land use change defines the historical pattern that how people used that specific land which depends on the availability of resources and economic conditions. LULC changes may trigger the detrimental effects like increase in natural hazard events and changes in climatic patterns. Climatic pattern directly affects the precipitation, groundwater recharge, the amount of evapotranspiration and runoff generation. On regional and local scale, LULC change is a far-reaching issue because environment and climate condition depend on it
When calamity strikes, it causes damage but it also provides opportunities for newer learnings opportunities and better preparedness to combat menace. Pakistan is agrarian economy and comprises fertile plains. According to Pakistan Bureau of Statistics, agriculture contributes to 24 percent of national Gross Domestic Product. Agriculture is dependent on water needs, met through water channels fed by rivers originating mostly from glacial sources existing in northern part of the country. The country hosts five major rivers, namely Indus Jhelum, Chenab, Ravi, and Sutlej. The dendritic river patterns follow gravity flow causing frequent morphological changes and riverbank erosion is the most significant phenomenon which acts as hazard for farming communities in terms of loss of shelter, livelihood, and landholdings. An in-time identification of the issue is the real concern nowadays. Presently, different tools are available for instant interpretation of riverbank erosion like Remote Sensing (RS) and Geographical Information System (GIS), which are not only good for instant identification but also helpful for precise estimation of historical losses. Landsat images for years 2009, 2013, and 2017 have used to make an initial assessment of erosion hotspots. High-resolution satellite imagery from Google Earth is also used for meticulous analysis. The analysis shows that beyond other factors, average riverbank displacement rate due to erosion directly depends on rise in water levels. The study provides systematic bases to estimate the losses precisely. The study is useful for damages assessment of land and livelihood to device relief packages for the affected communities. The study also builds the capacity in resolving land settlement issues consequent to the riverbank erosion phenomenon.
Coal is a carbon containing non-renewable fossil fuel and one of the major contributors of climate change and global warming. We used TANSO FTS instrument in order to obtain the level of atmospheric carbon dioxide through datasets obtained from GOSAT satellite. GIOVANNI was also used to obtain atmospheric concentration of various gases. Burning of coal causes emission of greenhouse gases (GHG) and black carbon (BC) in atmosphere which are responsible for nearly 0.3°C of 1°C rise in temperature. The annual average value of carbon emission for the year 2010 and 2019 is 388.4 ppm and 409 ppm respectively. Since the pre-industrial times CO2 concentrations have increased up to100 PPM (36%) in the last two and a half centuries (250 years).In South Asia Dhaka has the worst quality of air as CO2 concentration (6.7%) is higher than the country’s GDP (5.25%) and energy consumption (4.77%). While an increasing trend GHG has been observed in Lahore up to 5.5 %. This study concludes that the high concentration of carbon dioxide in atmosphere is responsible for average rise of 1.2 °C temperature annually. This temperature rise can lead to adverse climatic conditions i.e., melting of glaciers which will consequently rise the sea level various landmasses may disappear by 2050.
Hypsometric Integral (HI) displays the effect of active tectonics and sensitivity on geomorphic structures. In this study we calculated HI values for Hunza valley to investigate neotectonics, development of topographic structures and process of erosion using SRTM DEM 90m. ArcGIS and MATLAB is used to generate HI and hypsometric curve (HC). We generated HI and HC values by using D8 algorithm in MATLAB to extract drainage basins for 5 and 6 Strahler orders. HI and HC values show the stages of erosion for instance high values of HI and convex HC displays young and tectonically active stage. We used different grid sizes in ArcGIS to calculate maximum, mean and minimum elevation utilizing different statistical techniques. We used Local Indicator of Spatial Autocorrelation (LISA) instead of Global Moran Index to determine the extent of distribution of clustered, dispersed and randomized HI values. This technique indicates high positive z score for auto correlated data. Regions with high HI value indicate relative uplift, undissected and young structures while low HI values indicate sediment accumulation and shallow earthquakes.
Snow and glaciers in the mountain ranges of Hindu-Kush, Karakoram, and Himalayas (HKH), are supposed to be shrinking. Consequently, serious significances occur in respect of water accessibility for inhabitants of down streams. This investigation is an effort o identify the temporal variation in snow covers of Gilgit Baltistan (GB), northern Pakistan. For the calculation of the Normalized Difference Snow Index (NDSI) and estimation of snow-covered area (SCA), MODIS images for the period of 2000 to 2020 were used. Hunza, Astore, Gilgit, Diamir, Shyok, Ghanche, Skardu and Shigar are major sub-basins lying in GB with Hunza and Skardu being the mostly glaciated areas. Annual fluctuation in snow cover within GB was 10 to 80%. In accumulation season, from December to February, snow cover was almost 80% while in melting season, from July to September this area was reduced to 65-75%. The maximum and minimum Snow-Covered Area (SCA) detected in 2009 was almost 57687.85 km2 and 12083.40 km2 respectively. These results show fluctuations in SCA within the time duration of the last two decades.
The irrigation system throughout the world is affected by the variations in water content due to different soil structure, textures and climate change. The irrigation system supplies sufficient water to the agricultural fields in order to fulfill the prerequisites. The measurement of soil moisture content (62%) is crucial for precision irrigation and sustainable agricultural system. Site specific agricultural system was utilized to overcome all issues related to soil water moisture contents in the paddock. Smart technology was utilized to record GPS signals utilizing the signals reflected on the Earth’s surface. The GPS was utilized to analyze dielectric soil properties and moisture content in proposed areas. The main objective of this study was to determine water content with stimulus soil type, ground cover and compaction on the irrigation system by utilizing the GPS-based techniques. The result indicated positive relation between soil moisture content and the signals reflected on the earth surface. All factors affecting the irrigation system were not related to the reflected signals and did not affect the soil moisture content. The reflectivity was not reduced by ground cover. Whereas, comparative relationship was found between soil moisture content and reflectivity index i.e. soil moisture contents were increased with reflectivity index up to 0.02 %. The results showed that GPS signals system have significant impact on estimation of soil moisture content in precise irrigation system.
Neotectonics amend the river base and causes landscape erosion. This study explores the DEM based differentiation of neotectonics in the northern regions of Pakistan. This method involves vertical and non-linear dissection base on digital evaluation method. This study uses Gliding Box Technique (GBM and GBT) and Box Counting method to evaluate Lacunarity (LA), Succolarity (SA) or 3-Fractals, and Fractal Dimensions (FD). 3-fractals are an attribute used for the recognition of spatial patterns, specifically to compute and differentiate natural textures including natural patterns. This study also investigates vertical dissection using DEM SRTM having spatial resolution of 90m. DEM SRTM measures surface area, plane area as well as the surface ratio. The vertical areas are investigated to make dissection maps and to identify the affects of neotectonics on the roughness of surface. Low value of surface roughness indicates flattened drainage basins and inclination of slope. The Raikot Fault shows higher values of surface roughness towards NE- SW. The surface roughness is mapped to recognize relative uplifts, uneven regions, depressions and pits. Analysis through non-linear method identifies the regions affected by neotectonics activity. Tectonics activity causes deformation and instability in drainage networks.
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