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Crop mapping and its health monitoring are of key importance for a country like Pakistan where a considerable share of the GDP originates from agricultural production. Currently, extensive capital and human resource are utilized to record the crop types and monitor crop health due to variations in crop pattern and intercropping practices being observed in many parts of the country. Satellite Remote Sensing, however, can be utilized very efficiently to identify crop types and estimate acreage by using unique phenological cycles derived from NDVI thresholds. In this research, we proposed a semi-automated, efficient and cost-effective state-of-the-art technique for crop classification using satellite remote sensing datasets and GIS techniques to replace outdated conventional survey-based crop estimations procedures. This research was conducted in Sahiwal district, Pakistan to categorise several crop types using two major inputs: satellite (Sentinel-2, 10m) imagery and local crop calendar. The research adopted a semi-automatic approach to find the main crops of Rabi (winter) and Kharif (summer) using orthorectified and atmospherically corrected Level-1C images to extract phenological information based on Normalized Difference Vegetation Index (NDVI). The complete phenological life cycle of crops including sowing, growing, and harvesting stages were deeply analyzed with the help of crop calendar and NDVI profiles. Then this information passed through iterative selforganizing (ISO Data Model) of unsupervised classification technique in the form of temporal stacked images. The NDVI profiles of each crop were synchronized with the crop calendar of the study area to develop the crop categorization procedure. The results were validated with the statistics of the agriculture department Lahore and field samples gave about 85% and 88% accuracy for Rabi and Kharif cropping seasons respectively. It is concluded from the research that the tested methodology is capable of providing a fast, cost-efficient, and reliable solution for crop mapping instead of conventional survey-based crop area assessment techniques (conventional Girdawri) which requires a vast number of resources and time, and it can be replicated in different areas with minor changes. [ABSTRACT FROM AUTHOR]

Rainwater harvesting is an ancient technique to irrigate agriculture land in arid and semi-arid regions. Kirthar mountain range, Sindh Pakistan, receives an average annual rainfall of 250 mm, mainly during monsoon season from June to September, which is used to irrigate the agricultural land. Rainwater is also stored by local farmers in the form of small ponds which is not sufficient to fulfill agricultural requirements throughout the year. Rainwater storage structures like irrigation dams can be used to augment water supplies in the agricultural areas. Therefore, the objective of this study is to identify potential sites for rainwater storage. For this, the understanding of spatial and temporal patterns of rainfall is important factor for annual run off estimation. Due to scarcity of weather station in the county, both the gauge data of Dadu station and satellite estimates were used to determine annual rainfall runoff using soil conservation service curve number (SCS-CN) method. Analytic Hierarchy Process (AHP) was employed to calculate the relative importance of different spatially varying parameters like geology, runoff potential, landuse/ land cover, stream network, settlement and slope. Then the relative percentage weights of each influencing factors were processed using weighted overlay analysis to identify potential sites. The analysis identified five, the most suitable sites for rainwater storage structure. Out of these five sites, site-3 is already under construction which validates the findings. The study showed strong potential of building water storage structure to store rainwater during intense rainfall events in monsoon. Subsequently these structures can help to increase gross productivity of agriculture as well as to enhance the socioeconomic status of the local community and farmers living in nearby villages [ABSTRACT FROM AUTHOR]

Hudiara drain, a big sewage water body originating from India, is an important tributary of river Ravi in Pakistan. In present study, role of the drain in build-up/depletion of metal micronutrients Cu, Fe, Mn and Zn in surrounding agricultural lands has been investigated. Soil samples, up to a vertical distance of 1200 m on both sides of the drain and drain water samples were collected and analysed for metal micronutrients. Soil analysis results were interpolated by using the best optimized interpolator to generate continuous variation of the selected metals. Further patterns have been identified using proximity stat with consecutive neighbouring zones of 100 m extent. Cu and Mn concentrations were higher in some drain water samples, whereas Fe and Zn were found below guidelines in all collected water samples. In adjacent agricultural land the metals did not show uniform dispersal pattern along the drain length. However, vertical pattern of distribution indicated that drain water was controlling Cu and Zn concentrations, positively, whereas it was causing a dilution effect on Fe and Mn build-up in the surrounding agricultural lands. [ABSTRACT FROM AUTHOR]

Agriculture land suitability plays an important role in sustainable agriculture production by improving the use of current land resources and in the identification of new land that maybe prepare for agriculture. The present research aimed to focus on the agricultural land suitability of Azad Jammu and Kashmir (AJK), where the existing agriculture land is only 8% and dense forest and glaciers are covering 46.06% of the total area. Based on the literature review and local expert’s knowledge, eight different criteria have been taken to scale the available land for the suitability of agriculture practices. These parameters are soil orders, soil pH, Land-use Land-cover (LULC), slope, elevation, temperature, precipitation, and Potential Evapotranspiration (PET). Analytical Hierarchy Process (AHP) technique in integration with Geographical Information System (GIS) and Weighted Overlay Analysis (WOA) had been incorporated to classify the land for agriculture production. In AHP, weights were determined with the use of pairwise comparison matrix based on expert opinions. According to the guidelines of the United Nations Food and Agriculture Organization (FAO), the land suitability map was divided into five zones. After subtracting the areas of permanent features like mountains, forest, and glaciers, it was estimated that a highly suitable area was 13.21%, moderately suitable area was 11.61%, marginally suitable area was 13.14% and 62.05% was not suitable permanently. It is concluded that the integration of GIS and AHP in land suitability, is efficient and it will help the policymakers to improve the management of their land resources [ABSTRACT FROM AUTHOR]

Ochratoxin (OTA) is a potent carcinogen which may pose a tremendous threat to human health when found beyond permissible levels. This study aims at evaluating ochratoxin contamination in corn. The corn samples (n=80) were collected from 4 major districts (Bahawalpur, Faisalabad, Lahore and Rawalpindi) of Punjab Pakistan. The quantification of OTA in collected corn samples was carried out by High Performance Liquid Chromatographic technique. Different methods (physical, chemical and natural/biological) were used for the detoxification of contaminated corn. It was found that 59% of total 80 samples were contaminated with ochratoxin. Among contaminated samples, 26% samples were beyond permissible levels i.e. 5μg/kg OTA in corn samples as set by European Commission Regulation while 33% samples were found contaminated within permissible levels. However, 41% samples were not contaminated with OTA. Highest level 231.49+29.39μg/kg of OTA was found in corn sample of Faisalabad. The corn samples collected during summer season were found more contaminated than winter season. OTA contamination in corn seems to be a very serious issue in Punjab, Pakistan. Different environment-friendly, easy and cheap detoxification approaches were adopted to decontaminate OTA contaminated corn. Maximum detoxification of OTA in corn was found 48.17% by cooking, 64.25% by 0.5% hydrochloric acid and 52.38% by probiotic among physical, chemical and biological methods respectively. Proper handling, suitable storage conditions and proper management may be helpful to avoid ochratoxin contamination in corn and corn products. [ABSTRACT FROM AUTHOR]

It is quite challenging to assess the crop water requirement with limited time and resources on a regional scale. The study focuses on developing a spatial decision support system (SDSS) for crop water requirement and to determine the efficacy of existing irrigation systems by utilizing advanced geo-spatial techniques. Selected region was Punjab province of Pakistan that covers a total area of 105227 sq.km. Reflectance based crop coefficient approach was used forcrop water requirement estimation. Various metrological, climatic, geographical vector layers and statistical data of irrigation supply along with satellite imageries were used for monitoring the crop health on8-days periodic intervals for the summer (Kharif) season in the year 2018. For accurate quantification and mapping of crop water requirement, Landsat, MODIS and SPOT imageries were processed for crop classification, top of the atmosphere radiation calculation and actual and reference measurements, respectively. Reference evapotranspiration (ETo) was calculated using Penman method leading to provide water demand and consumption by further calculations in each irrigation circle. The results show that the regions lying at the tail of the canal command area (CCA) facing higher water deficit. In addition, irrigation circles facing insufficient irrigation water supplies (upper and lower Jhelum canal, Pothoar region) also demonstrating higher crop water deficits. Comparing southern with northern parts of the province high water deficits observed in images in the year 2018, reflecting these regions are relatively hotter and receive less average precipitation. Similarly, high water deficit observed at northeast of the Punjab due to insufficient irrigation water supply. The results have been validated by comparing the water demand with the irrigation supply in each CCA, which provides the water being utilized other than irrigation sources to satisfy crop water needs. This study is quite effective in water budget estimation and mitigation of water scarcity issues. [ABSTRACT FROM AUTHOR]

Water is one of the basic necessities to survive on earth, access to clean drinking water is the right of every human being but unfortunately water resources are getting polluted due to industrialization, improper management of waste and overpopulation. The objective of this research is to evaluate drinking water quality in Western Lahore. For convenience in sample collection the area under observation was divided into six zones and a total number of 72 drinking water samples were obtained and put to wide-ranging physicochemical analysis. Each sample was tested for 12 parameters including pH, turbidity, total dissolved solids (TDS), electrical conductivity (EC), Total Hardness, Calcium, Magnesium, total Alkalinity, Chloride, Nitrate, Carbonate and bicarbonate. The outcomes were compared with standards of World Health organization (WHO) and national standards for drinking water quality (NSDWQ). Inverse Distance Weighted (IDW) technique was used to create zone wise maps within GIS environment. At last Water Quality Index (WQI) was calculated to discover the fitness of water for human consumption. The results showed that TDS in 11Z5 (1099.2 ppm), EC in 8Z1 (119.8 ppm), 10Z1 (113.2 ppm), 7Z2 (132.4 ppm), 10Z2 (138.9 ppm), 11Z5 (174.5 ppm), 1Z6 (114.8 ppm) and Calcium (296 ppm) in 3Z3 are exceeding the permissible limits. Moreover, samples from 8Z2, 8Z4, 11Z5 and 12Z5 have poor WQI. So, water from these locations is unfit for human consumption and need better water quality management. [ABSTRACT FROM AUTHOR]