OPTIMIZING THE PERFORMANCE OF IRRIGATED AGRICULTURE IN EASTERN ENGLAND UNDER DIFFERENT WATER PRICING AND REGULATION STRATEGIES

Irrigation water shortage is becoming an increasingly serious problem in agricultural production. Growing pressure on water resources is leading to increasing restrictions on abstraction for irrigation and consideration of the use of economic instruments, such as increased abstraction charges and/or tradable licences, to restrict demand and encourage wiser use of water. We evaluate irrigation using selected economic, social, and environmental indicators of performance, including the value of water used for irrigation. A linear programming model is developed and used to simulate possible responses by irrigators and the impact on irrigation performance of intervention measures, namely abstraction quota restrictions and volumetric pricing that might be used to ration water and/or increase water use efficiency. Through the use of parametric programming a scenario analysis is performed to a case study in eastern England with regard to perturbations of irrigation water under alternative policy instruments.     

ARTIFICIAL NEURAL NETWORK MODELING FOR REFORESTATION DESIGN THROUGH THE DOMINANT TREES BOLE‐VOLUME ESTIMATION

Abstract In the management of restoration reforestations or recreational reforestations of trees, the density of the planted trees and the site conditions can influence the growth and bole volume of the dominant tree. The ability to influence growth of these trees in a reforestation contributes greatly to the formation of large dimension trees and thereby to the production of commercially valuable wood. The potential of two artificial neural network (ANN) architectures in modeling the dominant Pinus brutia tree bole volume in reforestation configuration at 12 years of age was investigated: (1) the multilayer perceptron architecture using a back‐propagation algorithm and (2) the cascade‐correlation architecture, utilizing (a) either the nonlinear Kalman's filter theory or (b) the adaptive gradient descent learning rule. The incentive for developing bole‐volume equations using ANN techniques was to demonstrate an alternative new methodology in the field of reforestation design, which would enable estimation and optimization of the bole volume of dominant trees in reforestations using easily measurable site and competition factors. The usage of the ANNs for the estimation of dominant tree bole volume through site and competition factors can be a very useful tool in forest management practice.     

THE TRANSFORMATION OF LANDSCAPE: MODELING POLICY AND SOCIAL IMPACTS ON THE AGRICULTURAL LANDSCAPE OF LESVOS

ABSTRACT. The term landscape is more and more used as an “umbrella‘ concept, covering a series of cultural, productive and ecological processes. In order to uncover mechanisms, monitor transformations and predict changes, a complicated set of interacting factors has to be taken into account. This paper presents a model for estimating social and policy impacts on agricultural landscapes, based on the assumption that agricultural landscapes are shaped at” macro “(landscape) level by” micro “interventions at farm level. The model consists of three parts: an” ecological processes “part, which deals with processes that shape the ecological and aesthetic value of a landscape, a” population dynamics “part, which examines farmer population dynamics and a” policy impact “part, which deals with direct or indirect impacts on farming systems and farmer dynamics and refers to CAP Rural Development Measures. The model is applied for the olive and graze land agricultural landscapes of Lesvos (Greece). Results, apart from revealing landscape change patterns; help to illustrate some mechanisms behind this change and indicate that Rural Development Measures are inherent with minor but important malfunctions that cannot lead to sustainable landscape management and rural development in the area.