The use of indicators in environmental policy appraisal: lessons from the design and evolution of water security policy measures

Drawing up environmental policy options is a complex activity which involves defining and weighing the merits and risks of various alternative courses of action governments could pursue. In its modern version, this task typically involves formal policy analysis or ‘policy appraisal’, that is, policy work specifically undertaken to generate and evaluate policy options in order to address problems or issues on a policy agenda. Indicators play a powerful but under-investigated role in this process. To shed light on this issue, the paper conducts a case study of the design and evolution of policy indicators in water security policy formulation, examining both their utilization and impact. The paper documents the origins of water security policy indicators; assesses their relevance and influence in policy formulation and identifies the reasons for the emergence of certain preferred indices, despite their having several well-known limitations. In particular, the discussion flags the significance of the political advantages surrounding their ease of use and interpretation, rather than their technical merits, as a key factor affecting the continued utilization and influence of specific indicators in environmental policy and planning.     

From robustness to resilience: avoiding policy traps in the long term

The likelihood of being faced with trap-like situations is a worrisome aspect of long-term policy-making, such as for climate change adaptation. Even when a policy may be effective in the short-term, changes in problem or policy contexts may render it ineffective over time. The design of ‘robust’ policies, meaning those which are able to self-adjust to linear changes in their environment, can be contrasted with ‘resilient’ ones which are able to adjust not only to linear, but also non-linear shifts in their contexts. Building on Boonstra and de Boer (AMBIO 43:260–274, 2014)’s argument that traps should not be considered as a static phenomenon; rather their emergence and development is often directly influenced by history and path-dependency, this paper elaborates how trap-like situations can emerge with increase in climate uncertainty over time. Three strategies to address policy traps due to climate change form subjects of inquiry in this paper: avoiding traps in the first place, designing against traps, and overcoming traps once in them. Each requires a specific type of design thinking and practice.     

Soil carbon storage in silvopastoral systems and a treeless pasture in northwestern Spain

Soil particle size and land management practices are known to have considerable influence on carbon (C) storage in soils, but such information is lacking for silvopastoral systems in Spain. This study quantified the amounts of soil C stored at various depths to 100 cm under silvopastoral plots of radiata pine ( D. Don) and birch ( Roth) in comparison to treeless pasture in Galicia, Spain. Soils were fractionated into three size classes (<53, 53-250, and 250-2000 μm), and C stored in them and in the whole (nonfractionated) soil was determined. Overall, the C stock to 1 m ranged from 80.9 to 176.9 Mg ha in these soils. Up to 1 m depth, 78.82% of C was found in the 0- to 25-cm soil depth, with 12.9, 4.92, and 3.36% in the 25- to 50-, 50- to 75-, and 75- to 100-cm depths, respectively. Soils under birch at 0 to 25 cm stored more C in the 250- to 2000-μm size class as compared with those under radiata pine; at that depth, pasture had more C than pine silvopasture in the smaller soil fractions (<53 and 53-250 μm). In the 75- to 100-cm depth, there was significantly more storage of C in the 250- to 2000-μm fraction in both silvopastures as compared with the pasture. The higher storage of soil C in larger fraction size in lower soil depths of silvopasture suggests that planting of trees into traditional agricultural landscapes will promote longer-term storage of C in the soil.     

Soil carbon storage as influenced by tree cover in the Dehesa cork oak silvopasture of central-western Spain

The extent of carbon (C) stored in soils depends on a number of factors including soil characteristics, climatic and other environmental conditions, and management practices. Such information, however, is lacking for silvopastoral systems in Spain. This study quantified the amounts of soil C stored at various depths (0-25, 25-50, 50-75, and 75-100 cm) under a Dehesa cork oak (Quercus suber L.) silvopasture at varying distances (2, 5, and 15 m) to trees. Soil C in the whole soil and three soil fractions (<53, 53-250, and 250-2000 μm) was determined. Results showed soil depth to be a significant factor in soil C stocks in all soil particle sizes. Distance to tree was a significant factor determining soil C stocks in the whole soil and the 250-2000 μm soil fraction. To 1 m depth, mean total C storage at 2, 5, and 15 m from cork oak was 50.2, 37, and 26.5 Mg ha(-1), respectively. Taking into account proportions of land surface area containing these C stocks at varying distances to trees to 1 m depth, with a tree density of 35 stems ha(-1), estimated landscape soil C is 29.9 Mg ha(-1). Greater soil C stocks directly underneath the tree canopy suggest that maintaining or increasing tree cover, where lost from disease or management, may increase long term storage of soil C in Mediterranean silvopastoral systems. The results also demonstrate the use of soil aggregate characteristics as better indicators of soil C sequestration potential and thus a tool for environmental monitoring.     

Calibrating climate change policies: the causes and consequences of sustained under-reaction

We apply insights from the recent literature on disproportionate policy reactions to the case of climate change policy-making. We show when and why climate change exhibits features of a sustained under-reaction: Governments may react to concerns about climate change not through substantive change but by efforts to manage blame strategically. As long as they can avoid blame for potential negative policy outcomes policy-makers can act to deny problems, or implement only small-scale or symbolic reforms. While this pattern may change as climate change problems worsen and public recognition of the issue and what can be done about it alters, opportunities to manage blame will still exist. Governments will only revert to more substantive interventions when attempts to fatalistically frame the problem as unavoidable fail in the face of increased public visibility.     

An Application of the Pump-to-Fill Policy for Management of Urban Stormwater

We consider the management of urban stormwater in two connected dams. Stormwater generated by local rainfall flows into a capture dam and is subsequently pumped into a similar sized holding dam. We assume random gross inflow and constant demand. If we wish to minimise overflow from the system then the optimal management policy is to pump as much water as possible each day from the capture dam to the holding dam without allowing the holding dam to overflow. We shall refer to this policy as the pump-to-fill policy. The model is based on the Parafield stormwater management system in the City of Salisbury (CoS) but assumes constant demand instead of level dependent outflow. If there is insufficient water in the holding dam to meet the desired daily demand then all water in the holding dam is used and the shortfall is obtained from other sources. CoS, in suburban Adelaide in South Australia, is recognised in local government circles as a world leader in urban stormwater management. The water is supplied to local industry to replace regular mains water and is also used to restore and maintain urban wetlands. In mathematical terms the pump-to-fill policy defines a Markov chain with a large transition matrix and a characteristic regular block structure. We use specialised Matrix Analytic Methods to decompose the event space and find simplified equations for the steady state probability vector. In this way we enable an elementary solution procedure which we illustrate by solving the modified Parafield problem. The optimal nature of the pump-to-fill policy is established in a recent paper by Pearce et al. (JIMO 3(2):313–320, 2007). The purpose of the current study is to find optimal management policies for urban stormwater systems. Work supported by the Australian Research Council.     

Generating Synthetic Rainfall on Various Timescales—Daily, Monthly and Yearly

The main objective of this paper is to present a model for generating synthetic rainfall totals on various timescales to be applicable for a variety of uses. Many large-scale ecological and water resource models require daily, monthly and yearly rainfall data as input to the model. As historical data provides only one realisation, synthetic generated rainfall totals are needed to assess the impact of rainfall variability on water resources systems (Srikanthan, In: MODSIM2005, Melbourne, Dec. 2005, pp. 1915–1921, 2005). Thus, our preferred model should simulate rainfall for yearly, monthly and daily periods. We believe that, for water supply issues, no higher resolution is needed, although higher resolution would be useful in models designed to measure the risk of local flooding. The critical factors are daily, monthly and yearly totals and daily, monthly and yearly variation. A model for generating yearly totals will be described using traditional time series methods. This model, along with a similarly constructed daily generation model by Piantadosi et al. (A New Model for Correlated Daily Rainfall, 2008), will be cascaded to start with a synthetic yearly total, then generate a synthetic sequence of monthly totals (through selection from a large number of realisations) that match the yearly total, and subsequently perform a similar operation for sequences of daily totals to match the required monthly totals. We present a new model for the generation of synthetic monthly rainfall data, which we demonstrate for Parafield in Adelaide, South Australia. The rainfall for each month of the year is modelled as a non-negative random variable from a mixed distribution with either a zero outcome or a strictly positive outcome. We use maximum likelihood to find parameters for both the probability of a zero outcome and the gamma distribution that best matches the observed probability density for the strictly positive outcomes. We describe a new model that generates correlated monthly rainfall totals using a diagonal band copula with a single parameter to generate lag-1 correlated random numbers. Our model preserves the marginal monthly distributions and, hence, also preserves the monthly and yearly means. We show that, for Parafield, the correlation between rainfall totals for successive months is not significant, and so, it is reasonable to assume independence. This is, however, not true for daily rainfall. We describe a new model that generates correlated daily rainfall totals using a diagonal band copula with a single parameter to generate lag-1 correlated random numbers. This is an extended version of a paper presented at the 17th Biennial Congress on Modelling and Simulation, Christchurch, New Zealand, December 2007.