A Stochastic Model of Phosphorus Loading from Non-Point Sources

A stochastic model is presented and applied for Lake Balaton, Hungary to estimate the phosphorus (P) loading from non-point sources. Rainfall events cause surface runoff events and erosion events; all three events are random. P is carried by runoff into the lake in two forms: (1) dissolved P and (2) sediment, absorbed or fixed P. P loading is thus considered as a random variable, whose probability density function (pdf) per event is to be estimated. Pdf of seasonal (e.g. annual) loading is determined as the sum of a random number of random events. The annual mass balance of P stored in lake sediment leads to a first order difference equation, the solution of which can be used to predict the expected P available for release at future times The model is applied for the Tetves subwatershed (70 sq. km.) of Lake Balaton. Preliminary results show that during relatively short runoff events about as much P reaches the lake as during the rest of the year and that more sediment P is produced than dissolved P. Since a considerable variance apppears in the annual amounts of P loading, the use of stochastic models to estimate the loading conditions seems to be most appropriate. The stochastic loading model should be incorporated into a broader control model. Elements of such a control model are given in the form of possible P loading reduction measures; also, economic trade-off between these measures is discussed

Trade-off Between Cost and Effectiveness of Control of Nutrient Loading into a Water Body

A system consisting of a watershed and a water body is considered, and a methodology is presented for selecting the alternative scheme offering the best compromise between economic activity in the watershed and quality of the water body. The general problem is specified for the system of a watershed and a lake endangered by eutrophication. Both economic activity and eutrophication can be characterized by several criteria. The method is applied to actual data from a subwatershed of Lake Balaton, Hungary, where the economic objective is to minimize the sum of costs and losses for the various control measures and the environmental objective is to minimize the amount of P available for algal growth. Both of these objectives are decomposed into several criteria. The action space consists of six pure strategies, namely, the control of (1) point-source pollution, (2) fertilizer, (3) erosion, (4) land use, (5) runoff control, and (6) sediment yield. These six pure actions lead to the definition of eight mixed alternatives. The phosphorus-loading portion of the model is run repeatedly with different stochastic input sequences to account for hydrologic uncertainty and the corresponding environmental objective is expressed as the probability "uj" that alternative "j" results in the largest decrease of P-loading. Model parameters are estimated using available data or published tables and graphs. Compromise programming is used to find a trade-off (or satisfactum solution) that balances the two conflicting objectives. In order to facilitate further application of the methodology, several points are discussed such as the relationship between the lake and its catchment, the error in stochastic simulation, the consideration of various uncertainties, the effect of snowmelt, and possible coupling with detailed lake eutrophication models. Finally, a step-by-step summary of the methodology is given to facilitate application of the model to other cases. Multicriterion decision-making techniques are briefly reviewed in the appendix so that cases with more than two objectives may also be approached

Optimal Flood Levee Designs by Dynamic Programming

An economic optimal development of a levee system along a river is investigated and a dynamic programming (DP) approach is used to find the optima under various conditions. The system consists of a number of levee reaches or stages. A random input of flood wave is regarded at the upstream point of the system. There are two failure modes considered and, consequently, two parameters of the flood wave (state variables) to trigger failure modes in every stage. Stochastic DP is used since the state transition functions (flood routing along the stages) are random functions. Three methods are discussed. In Method I, the expected value of the objective function is taken first, then DP is used as a numerical technique. In Method II, a fixed design flood is chosen as an input under which both optimum cost and policy is determined. In Method III, the value of the expected optimum objective function is calculated. It is shown that the full power of DP cannot be used if Method I is applied. Future research involves comparing the solutions of the three methods

Local spatial regression models : a comparative analysis on soil contamination

Spatial data analysis focuses on both attribute and locational information. Local analyses deal with differences across space whereas global analyses deal with similarities across space. This paper addresses an experimental comparative study to analyse the spatial data by some weighted local regression models. Five local regression models have been developed and their estimation capacities have been evaluated. The experimental studies showed that integration of objective function based fuzzy clustering to geostatistics provides some accurate and general models structures. In particular, the estimation performance of the model established by combining the extended fuzzy clustering algorithm and standard regional dependence function is higher than that of the other regression models. Finally, it could be suggested that the hybrid regression models developed by combining soft computing and geostatistics could be used in spatial data analysis

A discursive review of the textual use of ‘trapped’ in environmental migration studies: The conceptual birth and troubled teenage years of trapped populations

First mooted in 2011, the concept of Trapped Populations referring to people unable to move from environmentally high-risk areas broadened the study of human responses to environmental change. While a seemingly straightforward concept, the underlying discourses around the reasons for being ‘trapped’, and the language describing the concept have profound influences on the way in which policy and practice approaches the needs of populations at risk from environmental stresses and shocks. In this article, we apply a Critical Discourse Analysis to the academic literature on the subject to reveal some of the assumptions implicit within discussing ‘trapped’ populations. The analysis reveals a dominant school of thought that assisted migration, relocation, and resettlement in the face of climate change are potentially effective adaptation strategies along a gradient of migrant agency and governance