Water reuse for irrigation in Jordan: perceptions of water quality among farmers

The reuse of treated wastewater (reclaimed water) for irrigation is a valuable strategy to maximise available water resources, but the often marginal quality of the water can present agricultural challenges. Semi-structured interviews were held with Jordanian farmers to explore how they perceive the quality of reclaimed water. Of the 11 farmers interviewed who irrigate with reclaimed water directly near treatment plants, 10 described reclaimed water either positively or neutrally. In contrast, 27 of the 39 farmers who use reclaimed water indirectly, after it is blended with fresh water, viewed the resource negatively, although 23 of the indirect reuse farmers also recognised the nutrient benefits. Farmer perception of reclaimed water may be a function of its quality, but consideration should also be given to farmers’ capacity to manage the agricultural challenges associated with reclaimed water (salinity, irrigation system damage, marketing of produce), their actual and perceived capacity to control where and when reclaimed water is used, and their capacity to influence the quality of the water delivered to the farm.

Water reuse for irrigation in Jordan: plant beneficial nutrients, farmers’ awareness and management strategies

The reuse of treated wastewater (reclaimed water) is particularly well suited for irrigated agriculture as it often contains significant quantities of plant essential nutrients. This work has shown that reclaimed water in Jordan can have adequate concentrations of potassium, phosphate, sulphate and magnesium to meet all or part of the crop’s requirements. To fully benefit from these inputs farmers must have an awareness of the water quality and reduce the application of chemical fertilisers accordingly. Interviews with farmers have shown that 75 per cent of farmers indirectly using reclaimed water are aware of the nutrients. Farmers’ decision making as to the application of chemical fertilisers appears to be influenced by a range of factors which include the type of crops being cultivated, the provision of training on nutrient management and the availability of information on the nutrient content of the reclaimed water.

Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence

In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SI-MRLS) algorithm. The SI-MRLS algorithm applies the particle swarm optimization (PSO) to construct a flexible radial basis function (RBF) model so that both the model structure and output weights can be adapted. By replacing an insignificant RBF node with a new one based on the increment of error variance criterion at every iteration, the model remains at a limited size. The multi-innovation RLS algorithm is used to update the RBF output weights which are known to have better accuracy than the classic RLS. The proposed method can produces a parsimonious model with good performance. Simulation result are also shown to verify the SI-MRLS algorithm.

Advanced methods in adaptive control for industrial applications

This volume is based on a seminar concerned with advanced methods in adaptive control for industrial applications which was held in Prague in May 1990 and which brought together experts in the UK and Czechoslovakia in order to suggest solutions to specific current and anticipated problems faced by industry.