Towards an integrated understanding of green space in the European built environment

In recent years social, economic and environmental considerations have led to a reevaluation of the factors that contribute to sustainable urban environments. Increasingly, urban green space is seen as an integral part of cities providing a range of services to both the people and the wildlife living in urban areas. With this recognition and resulting from the simultaneous provision of different services, there is a real need to identify a research framework in which to develop multidisciplinary and interdisciplinary research on urban green space. In order to address these needs, an iterative process based on the delphi technique was developed, which comprised email-mediated discussions and a two-day symposium involving experts from various disciplines. The two outputs of this iterative process were (i) an integrated framework for multidisciplinary and interdisciplinary research and (ii) a catalogue of key research questions in urban green space research. The integrated framework presented here includes relevant research areas (i.e. ecosystem services, drivers of change, pressures on urban green space, human processes and goals of provision of urban green space) and emergent research themes in urban green space studies (i.e. physicality, experience, valuation, management and governance). Collectively these two outputs have the potential to establish an international research agenda for urban green space, which can contribute to the better understanding of people's relationship with cities.     

Micro-scaled high-throughput digestion of plant tissue samples for multi-elemental analysis

Background  

Quantitative multi-elemental analysis by inductively coupled plasma (ICP) spectrometry depends on a complete digestion of solid samples. However, fast and thorough sample digestion is a challenging analytical task which constitutes a bottleneck in modern multi-elemental analysis. Additional obstacles may be that sample quantities are limited and elemental concentrations low. In such cases, digestion in small volumes with minimum dilution and contamination is required in order to obtain high accuracy data.     

Bahiagrass crop coefficients from eddy correlation measurements in central Florida

Bahiagrass (Paspalum notatum) is a warm-season grass used primarily in pastures and along highways and other low maintenance public areas in Florida. It is also used in landscapes to some extent because of its drought tolerance. Bahiagrass can survive under a range of moisture conditions from no irrigation to very wet conditions. Its well-watered consumptive use has not been reported previously. In this study, bahiagrass crop coefficients (K _c) for an irrigated pasture were determined for July 2003 through December 2006 in central Florida. The eddy correlation method was used to estimate crop evapotranspiration (ET_c) rates. The standardized reference evapotranspiration (ET_o) equation (ASCE-EWRI standardization of reference evapotranspiration task committee report, 2005) was applied to calculate ET_o values using on site weather data. Daily K _c values were estimated from the ratio of the measured ET_c and the calculated ET_o. The recommended K _c values for bahiagrass are 0.35 for January–February, 0.55 for March, 0.80 for April, 0.90 for May, 0.75 for June, 0.70 for July–August, 0.75 for September, 0.70 for October, 0.60 for November, and 0.45 for December in central Florida. The highest K _c value of 0.9 in May corresponded with maximum vapor pressure deficit conditions as well as cloud free conditions and the highest incoming solar radiation as compared to the rest of the year. During the summer (June to August), frequent precipitation events increased the cloud cover and reduced grass water use. The K _c annual trend was similar to estimated K _c values from another well-watered warm-season grass study in Florida.     

Evaluating eddy covariance cotton ET measurements in an advective environment with large weighing lysimeters

Eddy covariance (EC) systems are being used to assess the accuracy of remote sensing methods in mapping surface sensible and latent heat fluxes and evapotranspiration (ET) from local to regional scales, and in crop coefficient development. Therefore, the objective was to evaluate the accuracy of EC systems in measuring sensible heat (H) and latent heat (LE) fluxes. For this purpose, two EC systems were installed near large monolithic weighing lysimeters, on irrigated cotton fields in the Texas High Plains, during the months of June and July 2008. Sensible and latent heat fluxes were underestimated with an average error of about 30%. Most of the errors were from nocturnal measurements. Energy balance (EB) closure was 73.2–78.0% for daytime fluxes. Thus, daylight fluxes were adjusted for lack of EB closure using the Bowen ratio/preservation of energy principle, which improved the resulting EC heat flux agreement with lysimetric values. Further adjustments to EC-based ET included nighttime ET (composite) incorporation, and the use of ‘heat flux source area’ (footprint) functions to compensate ET when the footprint expanded beyond the crop field boundary. As a result, ET values remarkably matched lysimetric ET values, with a ‘mean bias error ± root mean square error’ of −0.03 ± 0.5 mm day⁻¹ (or −0.6 ± 10.2%).     

Estimation of actual evapotranspiration for a drip-irrigated Merlot vineyard using a three-source model

A study was performed in order to evaluate the three-source model (Clumped model) for direct estimation of actual evapotranspiration (ET_a) and latent heat flux (LE) over a drip-irrigated Merlot vineyard trained on a vertical shoot positioned system (VSP) under semi-arid conditions. The vineyard, with an average fractional cover of 30%, is located in the Talca Valley, Region del Maule, Chile. The performance of the Clumped model was evaluated using an eddy covariance system during the 2006/2007 and 2007/2008 growing seasons. Results indicate that the Clumped model was able to predict ET_a with a root mean square error (RMSE), mean bias error (MBE), and model efficiency (EF) of 0.33, −0.15 mm day⁻¹ and 74%, respectively. Also, the Clumped model simulated the daytime variation of LE with a RMSE of 36 W m⁻², MBE of −8 W m⁻², and EF of 83%. Major disagreement (underestimated values) between observed and estimated values of ET_a was found for clear days after rainfall or foggy days, but underestimated values were less than 10% of the data analysis. The results obtained in this study indicate that the Clumped model could be used to directly estimate vine water requirements for a drip-irrigated vineyard trained on a VSP. However, application of the Clumped model requires a good characterization of the drip-irrigated vineyard architecture.     

Effects of water table management on soil salinity and alfalfa yield in a semi-arid climate

A lysimeter experiment was conducted to investigate the effect of water table management (WTM) on distribution of soil salinity and annual alfalfa (Medicago scutellata) yield. Subirrigations with three levels of water table namely, 0.5 (WT0.5), 0.7 (WT0.7), and 1.0 m (WT1.0) and a free drainage (FD) conventional irrigation treatment were selected for this study. All treatments were arranged in a complete randomized block design with three replicates. The results of this study indicated that the average soil electrical conductivity of the saturated extract (ECe) in the root zone gradually increased and exceeded the designated crop threshold value (4 dS/m) after the first forage harvest in subirrigated lysimeters. A higher salt accumulation was observed at the WT0.5 treatment. The average dry matter yield of annual alfalfa in WT0.5 and WT0.7 treatments was found to be 52 and 73% higher compared with the control treatment, respectively.     

Temporal variability in water quality of agricultural tailwaters: Implications for water quality monitoring

Accurate assessments of non-point source pollution and the associated evaluation of mitigation strategies depend on effective water quality monitoring programs. Intensive irrigation season water quality monitoring was conducted on three agricultural drains (6 h to daily sampling) along with analysis of decade long records from two larger agricultural drains (biweekly to monthly sampling) in the San Joaquin Valley, California. Analyses revealed significant temporal variability in concentrations of nutrients, salts, and turbidity over short time-scales (<1 day), as well as significant differences in monthly and annual mean concentrations. Statistical techniques were used to evaluate the sampling intensity required to meet rigorous confidence and accuracy criteria, as well as to evaluate the efficacy of different sampling strategies (e.g. grab samples versus composite samples). The number of samples required to determine mean constituent concentrations within 20% of the mean at a 95% confidence level ranged from 2 to 39 samples per month (SPM) for total phosphorus, 1-16 SPM for total nitrogen, 5-25 SPM for turbidity, and 1-3 SPM for electrical conductivity. Using a daily composite sample (4 subsamples per composite) instead of discrete samples was shown to maintain the same accuracy and confidence standards, while reducing the required sample number by up to 50%. This study emphasizes the value of a statistical approach for evaluating water quality monitoring strategies, and provides a framework through which cost-benefit analysis can be implemented in the development of monitoring plans.     

Combined use of optical and radar satellite data for the detection of tillage and irrigation operations: Case study in Central Morocco

The objective of this study is to present a new application of optical and radar remote sensing with high spatial (∼10 m) and temporal (a few days) resolutions for the detection of tillage and irrigation operations. The analysis was performed for irrigated wheat crops in the semi-arid Tensift/Marrakech plain (Central Morocco) using three FORMOSAT-2 images and two ASAR images acquired within one week at the beginning of the 2005/2006 agricultural season.The approach we developed uses simple mapping algorithms (band thresholding and decision tree) for the characterisation of soil surface states. The first images acquired by FORMOSAT and ASAR were processed to classify fields into three main categories: ploughed (in depth), prepared to be sown (harrowed), and not ploughed-not harrowed. This information was combined with a change detection analysis based on multitemporal images to identify harrowing and irrigation operations which occurred between two satellite observations.The performance of the algorithm was evaluated using data related to land use and agricultural practices collected on 124 fields. The analysis shows that drastic changes of surface states caused by ploughing or irrigation are detected without ambiguity (consistency index of 96%). This study provided evidence that optical and radar data contain complementary information for the detection of agricultural operations at the beginning of agricultural season. This information could be useful in regional decision support systems to refine crop calendars and to improve prediction of crop water needs over large areas.     

Information technology and innovative drainage management practices for selenium load reduction from irrigated agriculture to provide stakeholder assurances and meet contaminant mass loading policy objectives

Many perceive the implementation of environmental regulatory policy, especially concerning non-point source pollution from irrigated agriculture, as being less efficient in the United States than in many other countries. This is partly a result of the stakeholder involvement process but is also a reflection of the inability to make effective use of Environmental Decision Support Systems (EDSS) to facilitate technical information exchange with stakeholders and to provide a forum for innovative ideas for controlling non-point source pollutant loading. This paper describes one of the success stories where a standardized Environmental Protection Agency (EPA) methodology was modified to better suit regulation of a trace element in agricultural subsurface drainage and information technology was developed to help guide stakeholders, provide assurances to the public and encourage innovation while improving compliance with State water quality objectives. The geographic focus of the paper is the western San Joaquin Valley where, in 1985, evapo-concentration of selenium in agricultural subsurface drainage water, diverted into large ponds within a federal wildlife refuge, caused teratogenecity in waterfowl embryos and in other sensitive wildlife species. The fallout from this environmental disaster was a concerted attempt by State and Federal water agencies to regulate non-point source loads of the trace element selenium. The complexity of selenium hydrogeochemistry, the difficulty and expense of selenium concentration monitoring and political discord between agricultural and environmental interests created challenges to the regulation process. Innovative policy and institutional constructs, supported by environmental monitoring and the web-based data management and dissemination systems, provided essential decision support, created opportunities for adaptive management and ultimately contributed to project success. The paper provides a retrospective on the contentious planning process and offers suggestions as to how the technical and institutional issues could have been resolved faster through early adoption of some of the core principles of sound EDSS design.