Policy Windows, Policy Change, and Organizational Learning: Watersheds in the Evolution of Watershed Management

Employing in-depth, elite interviews, this empirical research contributes to understanding the dynamics among policy windows, policy change, and organizational learning. First, although much of the research on agenda setting—how issues attract enough attention that action is taken to address them—has been conducted at the national scale, this work explores the subnational, regional scale. With decentralization, regional-scale environmental decision-making has become increasingly important. Second, this research highlights the role of policy windows and instances of related organizational learning identified by natural resources managers. Having practitioners identify focusing events contrasts with the more typical approach of the researcher identifying a particular focusing event or events to investigate. A focusing event is a sudden, exceptional experience that, because of how it leads to harm or exposes the prospect for great devastation, is perceived as the impetus for policy change.     

The Water Fluxes of the Yellow River to the Sea in the Past 50 Years, in Response to Climate Change and Human Activities

Since the 1970s, the water fluxes to the sea of the Yellow River have declined significantly. Based on data of precipitation, air temperature, the measured and “natural” river flow, the water diversion and consumption, and the areas of erosion and sediment control measures over the drainage basin, water fluxes to the sea of the Yellow River are studied in relation with the influences of changing climate and human activities. The Yellow River basin can be divided into different water source areas; multiple regression indicates that the variation in precipitation over different water source areas has different effect on water fluxes to the sea. In the period between 1970 and 1997, averaged air temperature over the whole Yellow River increased by about 1.0°C, from 16.5°C to 17.5°C, a factor that is negatively correlated with the water yield of the Yellow River. Water diversion and consumption has sharply increased and resulted in a significant decline in the water fluxes to the sea. Since the 1960s, erosion and sediment control measures have been practiced over the drainage basin. This factor, to a lesser degree, is also responsible for the decrease in water fluxes to the sea. A multiple regression equation has been established to estimate the change in water fluxes to the sea caused by the changes in precipitation, air temperature, water diversion and consumption, erosion, and sediment control measures, indicating that the contribution of water diversion and consumption to the variation in annual water flux to the sea is 41.3%, that of precipitation is 40.8%, that of temperature is 11.4%, and that of erosion and sediment control measures is 6.5%.     

Predicting land cover using GIS, Bayesian and evolutionary algorithm methods

Modelling land cover change from existing land cover maps is a vital requirement for anyone wishing to understand how the landscape may change in the future. In order to test any land cover change model, existing data must be used. However, often it is not known which data should be applied to the problem, or whether relationships exist within and between complex datasets. Here we have developed and tested a model that applied evolutionary processes to Bayesian networks. The model was developed and tested on a dataset containing land cover information and environmental data, in order to show that decisions about which datasets should be used could be made automatically. Bayesian networks are amenable to evolutionary methods as they can be easily described using a binary string to which crossover and mutation operations can be applied. The method, developed to allow comparison with standard Bayesian network development software, was proved capable of carrying out a rapid and effective search of the space of possible networks in order to find an optimal or near-optimal solution for the selection of datasets that have causal links with one another. Comparison of land cover mapping in the North-East of Scotland was made with a commercial Bayesian software package, with the evolutionary method being shown to provide greater flexibility in its ability to adapt to incorporate/utilise available evidence/knowledge and develop effective and accurate network structures, at the cost of requiring additional computer programming skills. The dataset used to develop the models included GIS-based data taken from the Land Cover for Scotland 1988 (LCS88), Land Capability for Forestry (LCF), Land Capability for Agriculture (LCA), the soil map of Scotland and additional climatic variables.     

Modeling the relationships between land use and land cover on private lands in the Upper Midwest, USA

This paper presents an approach to modeling land-cover change as a function of land-use change. We argue that, in order to model the link between socio-economic change and changes in forest cover in a region that is experiencing residential and recreational development and agricultural abandonment, land-use and land-cover change need to be represented as separate processes. Forest-cover change is represented here using two transition probabilities that were calculated from Landsat imagery and that, taken together, describe a Markov transition matrix between forest and non-forest over a 10-year period. Using a three-date land-use data set, compiled and interpreted from digitized parcel boundaries, and scanned aerial photography for 136 sites (c. 2500 ha) sampled from the Upper Midwest, USA, we test functional relationships between forest-cover transition probabilities, standardized to represent changes over a decade, and land-use conditions and changes within sample sites. Regression models indicated that about 60% of the variation in the average forest-cover transition probabilities (i.e. from forest to non-forest and vice versa) can be predicted using three variables: amount of agricultural land use in a site; amount of developed land use; and the amount of area increasing in development. In further analysis, time lags were evaluated, showing that agricultural abandonment had a relatively strong time-lag effect but development did not. We demonstrate an approach to using forest-cover transition probabilities to develop spatially-constrained simulations of forest-cover change. Because the simulations are based on transition probabilities that are indexed to a particular time and place, the simulations are improved over previous applications of Markov transition models. This modeling approach can be used to predict forest-cover changes as a result of socio-economic change, by linking to models that predict land-use change on the basis of exogenous human-induced drivers.     

HYDROLOGIC EFFECTS OF CLIMATE CHANGE IN THE DELAWARE RWER BASIN1

ABSTRACT: The Thornthwaite water balance and combinations of temperature and precipitation changes representing climate change were used to estimate changes in seasonal soil-moisture and runoff in the Delaware River basin. Winter warming may cause a greater proportion of precipitation in the northern part of the basin to fall as rain, which may increase winter runoff and decrease spring and summer runoff. Estimates of total annual runoff indicate that a 5 percent increase in precipitation would be needed to counteract runoff decreases resulting from a warming of 2°C; a 15 percent increase for a warming of 4°C. A warming of 2° to 4°C, without precipitation increases, may cause a 9 to 25 percent decrease in runoff. The general circulation model derived changes in annual runoff ranged from ?39 to +9 percent. Results generally agree with those obtained in studies elsewhere. The changes in runoff agree in direction but differ in magnitude. In this humid temperate climate, where precipitation is evenly distributed over the year, decreases in snow accumulation in the northern part of the basin and increases in evapotranspiration throughout the basin could change the timing of runoff and significantly reduce total annual water availability unless precipitation were to increase concurrently.