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 Health Organization states that every year more than 3.4 million human deaths occur as a result of waterborne diseases. Here, we reported an innovative and amino functionalized electrochemical biosensor for the rapid detection of Escherichia coli (E. coli). Functionalized Fe₃O₄ NPs developed the sensor with L-cysteine, and cyclic voltammetry (CV) was employed to detect the bacteria. The results from this work are the first step toward the development of a portable water sensor that addresses the challenges of conventional time consuming and more expensive laboratory-based analyses. The detection of the targeted bacteria was performed with different bacteria to check the validity of the developed biosensor. Hence, the biosensor was highly selective to detect the E. coli from tap water samples. The signals current were increasing linearly while increasing the concentration of E. coli with the ranging from 10¹ to 10⁵ CFU/mL with the linear correlation of (r² = 0.879). The proposed electrochemical biosensor detects the E. coli in a lower concentration of 10¹ CFU/mL and with the maximum range of 10⁵ CFU/mL. The results from this work demonstrate the first step in a portable biosensor for the routine monitoring of microbial contamination from water.