Spatiotemporal Dynamics of Land Surface Temperature and Its Impact on the Vegetation

Due to global warming under climate change scenarios, Indus delta region of Pakistan is under serious threat since the last few decades. The present study was thus conducted to determine the spatiotemporal variations in the LST and its impact on the vegetation of the Indus delta, using satellite data for the past 27 years (1990-2017). The analysis revealed that on average, there was an increase of 1.74 oC in LST during the last 27 years. The temporal variation in the Normalized Difference Vegetation Index (NDVI), an indicator of vegetation, showed the highest NDVI of 0.725 in the year 2005 followed by the year 2010 with NDVI of 0.712. While the lowest NDVI of 0.545 was observed during the year 2017. The LST was integrated with NDVI which showed a fair but negative statistical correlation with a coefficient of determination R2 = 0.65. A correlation analysis between NDVI and the yield of the wheat crop of the Delta showed a positive relationship with R2 = 0.89. Several factors may contribute to an increase in LST, such as an increase in residential areas, change in the cropping pattern and overall global climate change. Such studies are important for determining the climatic influences on ecological parameters

Analysis of Indus Delta Groundwater and Surface water Suitability for Domestic and Irrigation Purposes

The present study was conducted to analyze the suitability of groundwater and surface water of the Indus Delta, Pakistan for domestic and irrigation purposes based on the concentrations of arsenic (As), total dissolved solids (TDS), and chloride (Cl). Around 180 georeferenced groundwater and 50 surface water samples randomly collected were analyzed and mapped spatially using ArcGIS 10.5 software. The results were compared with their respective WHO and FAO guidelines. The analysis revealed that as in groundwater and surface water samples ranged up to 200, and 25 µg/L respectively. Similarly, the TDS in the groundwater and surface water ranged from 203 to 17, 664 mg/L and 378 to 38,272 mg/L respectively. The Cl in groundwater and surface water varied between 131 and 6,275 mg/L and 440 to 17,406 mg/L respectively. Overall, about 18%, 87% and 94% of the groundwater, and 10%, 92% and 56% of the surface waters possessed higher concentrations of As, TDS, and Cl, respectively. The higher levels of Cl in the samples are attributed to subsurface seawater intrusion in the delta. Analysis results and GIS mapping of water quality parameters revealed that in most of the delta, the quality of water was not suitable for drinking and agricultural purposes, thus should be properly treated before its use

Indication of subsurface seawater intrusion into the Indus delta, Sindh, Pakistan

Due to climate change impacts, seawater intrusion is a major issue in various river deltas around the globe, including the Indus delta, Pakistan. The seawater intrusion has severely affected the freshwater resources as well as the livelihood of the people living in the Indus delta. Thus, this study was aimed to evaluate the subsurface seawater intrusion into the Indus delta based on the groundwater quality data. Around 180 groundwater samples, randomly collected from the study area, were analyzed for chloride, carbonate, and bicarbonate concentrations. Based on these concentrations, the indication of subsurface seawater intrusion was determined using Simpson’s ratio and ionic analysis, such as the ratio of chloride to bicarbonate. Also, an interpolated map using the analysis results of these ratios was developed using ArcGIS 10.5. Overall, the present study revealed that about 88% of the Indus delta is affected by the subsurface seawater intrusion. Also, the impact of subsurface seawater intrusion was observed in the wells near the Thatta and Sujawal towns of the study area. However, about 12% of the delta is still unaffected by the subsurface seawater intrusion. Various factors such as reduction in freshwater flow into the delta, climate change, sea-level rise are potential causes of subsurface seawater intrusion in the study area. This study may be taken as a baseline by the policymakers to start mitigation measures against the degradation of the delta to save the environment from further deterioration. Also, further an isotopic analysis of subsurface seawater intrusion in the study area is recommended

Study of Soil, Water, and Cropping Pattern in Danastar Wah (Manchar Lake) Command Area Using Geospatial Tools

The effluent water brought by RBOD (Right Bank Outfall Drain) is not only threat to the aquatic life of Manchar Lake but also the fertile agricultural lands which are being cultivated by use of lake water through Danastar Wah are at risk of salinization. The farming community of the area is scary of continual use of irrigation waters received through the Danastar Wah; they are of the view that the constant use of this water will ruin their fertile lands into salt-affected soils. Thus, keeping in view the fears of the farmers of the command area of Danastar Wah, a study was carried out to investigate the water quality of the Manchar Lake, RBOD MNV (Main Nara Valley) drain and Danastar Wah, and to examine soil salinity status of the area using Geo-referenced field and satellite imagery data for Kharif season of the year 2015. The results of the study showed that the EC (Electrical Conductivity) of the Danastar Wah water was below 1.2 dS/m. Thus, the water was suitable for irrigation purpose. In all the water samples, Na+, Ca2+ + Mg2+ and CO3 concentrations were found within the permissible limits, while no concentration of HCO3 was found in any of the water samples. In the command area, clay texture was dominant down to a depth of 60 cm soil profile. In the area about 37, 28, and 30% of the soils were normal (non-saline), saline and sodic, respectively; while only 5% of soils were saline-sodic. The cotton crop was identified as the major Kharif crop, occupying about 13.76% (2,844 ha) of the total command area, followed by rice crop grown on about 5.21% (1,078 ha) of the command area. The overall accuracy of image classification was 90% with a kappa coefficient of 0.86. Based on this study, it can be concluded that the water of the Danastar Wah can be used for irrigation purpose during Kharif season only with the condition that adequate land drainage is maintained. It is also suggested that before using the water of Manchar Lake, RBOD and Danastar Wah for Rabi season, analysis for water quality be conducted. GeoInformatics (GIS and RS) tools can be employed for spatial and temporal monitoring of water quality of the Manchar Lake

Health and Safety Assessment in Lakhra Coal Mines and Its Mitigation Measures

oai:ojs.localhost:article/200The coal mine excavation, transportation and coal cutting process are involved in hazards and risks that can result in fatalities, injuries and diseases, if these are not properly managed. This study has been undertaken for assessment of the safety and health issues amongst the mines workers. Convenience sampling technique was exercised upon 97 mine workers and interviewed with the help of set questionnaire. Personnel protection to workplace environment was monitored by using physical observation and scientific analysis. All parameters were measured against national and international protocols pertaining to labor law at coal mines. It has been determined that very high risk was persisting while mine excavation, coal cutting and transportation processes. Previous record of last five years was suggesting that 04 deaths happened due to roof fall, 03 fatalities occurred through suffocation by inhaling toxic gases, one causality happened via rope haulage pulley, and also one death due to stone fall down from mine shaft. 121 workers injured in different kinds of accidents within five years. It has been learnt from in-depth analysis that maximum of health risk and subsequent health damages are triggering due to lack of awareness, non-compliance of labor as well as mines laws. Thus, it is recommended that government should not allow coal mining contractors and companies, those which are failing in compliance with the suggested standards

Impact of Rising Groundwater on Sustainable Irrigated Agriculture in the Command Area of Gadeji Minor,Sindh, Pakistan

A study has been conducted in the command area of Gadeji minor, Sindh, Pakistan to compute the amount of net groundwater recharge and its effect on sustainable irrigated agriculture. In this connection, Water budget equation was used and three groundwater recharging components along with one discharging component were computed for both Rabi and Kharif crop seasons for the period (2001-2013). Data shows that groundwater is rising at rapid rate during the Kharif season. The percolation rate through cropped fields is the major recharge component; accounting for 81% in the total mean recharge of 8.42 million m3, moreover the rice area is the major contributor to net groundwater recharge during Kharif season. The contributions of canal seepage and rainfall are estimated to be 16 and 04% respectively for the above period. However, during the Rabi season groundwater is rising at low rate where canal seepage is the major recharging component with an average contribution of 48% in the total mean recharge of 2.32 million m3, the contribution of deep percolation from cropped fields is estimated to be 47% as compared to the rainfall of only 05%. Survey shows non-functionality of most of the tubewells, groundwater withdrawal is not sufficient to fully offset groundwater recharge which has increased water table and caused waterlogging and soil salinity in more than 40% of agricultural land. To overcome this rising water table problem, it is recommended: to change existing cropping pattern (i.e. minimize or no cultivation of rice crop), lining of minor and all its watercourses, adopt salt tolerant crops and increase groundwater withdrawals by operating tube-wells on emergency basis

Groundwater Quality Mapping using Geographic Information System: A Case Study of District Thatta, Sindh

Access to safe and affordable drinking water for all is an important goal of SDGs (Sustainable Development Goals). Degradation of water quality of coastal aquifers is a major concern throughout the world including the Indus River delta. Looking at the present changing climate scenario, the study was conducted to assess and map the spatial variation in the groundwater quality of district Thatta using GIS (Geographic Information System). The groundwater samples from hundred (100) randomly selected hand pumps of the district were collected such that all union councils of the district were sampled. The water samples were analyzed for different physicochemical parameters, i.e. taste, color, odor, pH, turbidity, EC (Electrical Conductivity), calcium, magnesium, total hardness, chloride, total dissolved solids, and arsenic using standard laboratory techniques. The results of water analysis revealed that 85% of the groundwater samples had TDS (Total Dissolved Solids) concentration beyond the permissible limit described by WHO (World Health Organization). Whereas, all the groundwater samples had chloride concentration beyond permissible limit of 250 mg/l. Analysis for arsenic revealed that only 20% of groundwater samples had a concentration higher than the safe limit of 10 ppb. The study indicated that in most of the areas, the groundwater quality was not as per drinking standards prescribed by WHO, hence was not suitable for drinking purpose. The GIS maps of groundwater quality parameters were prepared using spatial interpolation Kriging tool. These maps provide the visual analysis and interpretation of spatial variability of different groundwater quality parameters, hence are supportive in monitoring and managing the vulnerability of groundwater contamination

Impact of Watercourse Lining on Water Conservation in the Gadeji Minor Command, Sindh, Pakistan

Looming water scarcity could be curtailed with intelligent water losses control. Present study was designed to assess the relative effect of watercourse lining in prospect of seepage minimization. Qualitative as well as quantitative analysis was undertaken using water conveyance efficiency, annual water saving, increase in cropping intensities, time and land saving along with labor saving indictors over Gadeji minor in Sindh, Pakistan. Primary data was collected from field measurements while secondary data was gathered from NPIW (National Program for Improvement of Watercourses), Irrigation Department, personal interviews and site survey. The analysis revealed that lining of 30% initial portion of watercourses resulted average annual water saving of 10.32 hectare-m. Similarly, the cropping intensity increased 15% in Rabi and 14% in Kharif seasons. Crop yield increased by 17% for wheat crop, 14% for cottoncrop, 12% for sugarcane, 17% for chilies, 11% for onion crop and 20% for rice crop after lining the selected watercourses. Thus, it is concluded that watercourse lining has noticeable effect for seepage control which yielded a significant water saving. In future, economic viability of watercourse lining may be assessed for obtaining optimum benefits

Machine learning, Water Quality Index, and GIS-based analysis of groundwater quality

Water is essential for life, as it supports bodily functions, nourishes crops, and maintains ecosystems. Drinking water is crucial for maintaining good health and can also contribute to economic development by reducing healthcare costs and improving productivity. In this study, we employed five different machine learning algorithms – logistic regression (LR), decision tree classifier (DTC), extreme gradient boosting (XGB), random forest (RF), and K-nearest neighbors (KNN) – to analyze the dataset, and their prediction performance were evaluated using four metrics: accuracy, precision, recall, and F1 score. Physiochemical parameters of 30 groundwater samples were analyzed to determine the Water Quality Index (WQI) of Pano Aqil city, Pakistan. The samples were categorized into the following four classes based on their WQI values: excellent water, good water, poor water, and unfit for drinking. The WQI scores showed that only 43.33% of the samples were deemed acceptable for drinking, indicating that the majority (56.67%) were unsuitable. The findings suggest that the DTC and XGB algorithms outperform all other algorithms, achieving overall accuracies of 100% each. In contrast, RF, KNN, and LR exhibit overall accuracies of 88, 75, and 50%, respectively. Researchers seeking to enhance water quality using machine learning can benefit from the models described in this study for water quality prediction. HIGHLIGHTS Groundwater quality is evaluated using the Water Quality Index method.; Machine learning algorithms are used for forecasting groundwater quality.; The predictive capabilities of decision tree classifier, extreme gradient boosting, logistic regression, random forest, and K-nearest neighbors models have been evaluated and compared.

Investigation of Irrigation Water Requirements for Major Crops Using CROPWAT Model Based on Climate Data

Water is one of the most important natural resources and is widely used around the globe for various purposes. In fact, the agricultural sector consumes 70% of the world’s accessible water, of which about 60% is wasted. Thus, it needs to be managed scientifically and efficiently to maximize food production to meet the requirements of an ever-increasing population. There is a lack of information on water requirements of crops and irrigation scheduling concerning the Shaheed Benazirabad district, Pakistan. Thus, the present study was conducted to determine the irrigation water requirements (IWR) and irrigation scheduling for the major crops in the Shaheed Benazirabad district, Sindh, Pakistan, using agro-climatic data and the CROPWAT model. Agro-climatic data such as rainfall, maximum and minimum temperature, sunshine hours, humidity, and wind speed were obtained from the NASA website, CLIMWAT 2.0, and world weather However, data about studied crops and soils were obtained from FAO (Food and Agriculture Organization). Analysis revealed that the IWRs per irrigation round for the four major crops—sugarcane, banana, cotton, and wheat—were as 3108.0 mm, 1768.5 mm, 1655.7 mm, and 402.5 mm, respectively. It was observed the IWRs are more sensitive in the hot season because of high temperatures and low relative humidity, and vice versa in the cold season. The use of scientific tools such as CROPWAT is recommended to assess IWRs with a high degree of accuracy and to compute irrigation scheduling. Accordingly, the study results will be helpful for improving food production and supervision of water resources