Under changing climate scenario, groundwater aquifers in the coastal areas of Pakistan are under serious threat. Looking at the gravity of the problem, and concerns of the civil society, this study was conducted to evaluate and map the quality of groundwater in the Sujawal district, a coastal area of Pakistan based on the physicochemical analysis of 94 samples using two standard numerical models and geospatial techniques. The WQI model revealed that 2.13%, 6.38%, 55.32%, 22.34%, and 13.83% of water samples were excellent, good, poor, very poor, and unsuitable for drinking purposes. Also, the SPI model identified that 32%, 13.83%, 20.12%, 18.1%, and 15.95% of samples were slightly polluted, moderately polluted, highly polluted, suitable, and unsuitable. Though the model's input is different, the proportionate of ranking revealed a significant correlation (R²=0.78) between the outcomes of both models. Overall, the study revealed that groundwater in most of the areas does not meet WHO guidelines. The prevalence of water-related diseases in the area suggests that groundwater is contaminated and using that water is of high risk for human health. The study highlights the significance of using numerical models and geospatial techniques for water quality evaluation in the coastal areas of the world.

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.

The world is facing an acute water shortage. The present irrigation techniques used in the Hyderabad district, Pakistan, are not demand-driven. The present study was carried out to determine the crop water requirement (CWR), irrigation water requirement (IWR), and irrigation scheduling for major crops grown in the Hyderabad district using the CROPWAT model based on climatic, soil, and crop data. The analysis revealed that the total CWR for the entire growing season for sugarcane, banana, cotton, and wheat were 3,127.0; 2,012.3; 1,073.5; and 418.9 mm, respectively. However, the IWR for sugarcane, banana, cotton, and wheat for the entire growing season was found to be 2,964.0; 1,966.7; 1,052.7; and 407.6 mm, respectively. However, the contribution of rainfall was 163.0, 45.6, 20.8, and 11.3 mm during sugarcane, banana, cotton, and wheat, respectively. The CWR and IWR were higher during the dry season due to high temperatures and low relative humidity. However, the IWR of each crop was low in the initial stage which increased with the growing stage until the peak at the full growth stage. The study recommends the use of CROPWAT to investigate the irrigation water requirements with accuracy.

The study was conducted in Nagarparker area, Thar, Pakistan to assess the small dam’s impact on groundwater quality for domestic use and water level variance in wells during pre and post-monsoon periods. The water samples collected from various locations of the study area were analyzed for twenty physicochemical parameters and their appropriateness was assessed using the water quality index (WQI) and geographicinformationsystem (GIS) techniques. The results revealed that groundwater level increased from 15-25 ft near the dams and 8-14 ft away from the dam after rainfall, a minor change was observed in the concentration of chemical and trace elements. Physico-chemical parameters analysis indicated that the concentrations of the 40% parameters (pH, SO₄, Fe, CU, Mn, Zn, As and fluoride) were within the World Health Organization (WHO) guidelines, whereas 60% exceeded the thresholds. The WQI revealed that the quality of only 20% of the water samples was excellent, 25% good, 15% poor, 15% very poor and 25% unsuitable for drinking purposes. The spread of water related diseases in the area also indicated the groundwater contamination. Overall, the quality of water is poor to unsuitable for drinking purposes. Thus, such water should be treated properly before use to avoid toxic and hazardous effects on human health.

Due to seawater intrusion into the Indus delta, Pakistan under changing climate scenarios, the local communities of the delta are under threat of land and livelihood. The present study was initiated to analyze community perceptions about the social and ecological climate change vulnerability in the Indus delta, Pakistan. About 500 permanent residents of the delta were interviewed using a well-structured questionnaire. The IBM SPSS software was used to analyze the data based on the Pearson chi-square, Goodman, Kruskal's analyses, and Foster Greer Thorbeck (FGT) techniques. Analysis of the data revealed that the people in the delta had poor infrastructure and living standards, and limited social activities. Most of the people were illiterate, and the average family size was 11. On average, 4.7 members lived in a single room, and most of the houses were made of wood. Based on FGT techniques, about 88.4% of the population were living below the poverty line. The statistical analysis identified seawater intrusion and climate change as the most significant parameters affecting soil fertility, water quality, vegetation, mangroves, and livelihood. A large portion of the respondents strongly demanded the ensured freshwater flow to save the ecosystem, water resources, and the livelihood of the delta communities.