Kwok Pan Chun

Precipitation downscaling under climate change: Recent developments to bridge the gap between dynamical models and the end user

Precipitation downscaling improves the coarse resolution and poor representation of precipitation in global climate models and helps end users to assess the likely hydrological impacts of climate change. This paper integrates perspectives from meteorologists, climatologists, statisticians, and hydrologists to identify generic end user (in particular, impact modeler) needs and to discuss downscaling capabilities and gaps. End users need a reliable representation of precipitation intensities and temporal and spatial variability, as well as physical consistency, independent of region and season. In addition to presenting dynamical downscaling, we review perfect prognosis statistical downscaling, model output statistics, and weather generators, focusing on recent developments to improve the representation of space-time variability. Furthermore, evaluation techniques to assess downscaling skill are presented. Downscaling adds considerable value to projections from global climate models. Remaining gaps are uncertainties arising from sparse data; representation of extreme summer precipitation, subdaily precipitation, and full precipitation fields on fine scales; capturing changes in small-scale processes and their feedback on large scales; and errors inherited from the driving global climate model.

Factors affecting the implementation of green specifications in construction

Green specifications constitute one of the important elements in green construction. New sustainability requirements and changing priorities in construction management have spurred the emerging green specifications to a faster pace of development. A cross-sectional survey has been conducted in Hong Kong in 2007 to identify principal factors leading to the success of preparing green specifications. Based on extensive construction management literature, 20 variables concerning sustainable construction were summarized. Using the Mann-Whitney U-test, the subtle differences between stakeholders in specifying construction work have been detected even with the high consistency of the responses among the groups. Moreover, five independent factors for successful specification of green construction have been categorized by factor analysis. They are related to (1) green technology and techniques, (2) reliability and quality of specification, (3) leadership and responsibility, (4) stakeholder involvement, and (5) guide and benchmarking systems. Whilst the first and fourth factors are generally more important, different stakeholder groups have different emphases. The results of the survey have been validated against established principles.

Environmental management system vs green specifications: How do they complement each other in the construction industry?

Environmental Management System (EMS) has been one of the important tools for sustainable construction for around two decades. However, many issues concerning sustainable development have not been properly addressed, and there is a need for the introduction of green specifications to advance green performance in construction through contract management. This paper defines green specifications, identifies the reasons for adopting green specifications and highlights the environmental issues that may not be addressed by solely adopting EMS. It also presents the results of a recent survey of practitioners concerning their opinions towards green specifications and possible impacts arising from their adoption. From the results of the survey, a framework for developing green specifications is deemed valuable for the cities striving for sustainability. Interestingly, the level of acceptable changes brought about by green specifications as perceived by different industry stakeholders is found to be unrelated to whether they were from organizations implementing EMS or not.

Temporal dynamics of catchment transit times from stable isotope data

Time variant catchment transit time distributions are fundamental descriptors of catchment function but yet not fully understood, characterized, and modeled. Here we present a new approach for use with standard runoff and tracer data sets that is based on tracking of tracer and age information and time variant catchment mixing. Our new approach is able to deal with nonstationarity of flow paths and catchment mixing, and an irregular shape of the transit time distribution. The approach extracts information on catchment mixing from the stable isotope time series instead of prior assumptions of mixing or the shape of transit time distribution. We first demonstrate proof of concept of the approach with artificial data; the Nash-Sutcliffe efficiencies in tracer and instantaneous transit times were >0.9. The model provides very accurate estimates of time variant transit times when the boundary conditions and fluxes are fully known. We then tested the model with real rainfall-runoff flow and isotope tracer time series from the H.J. Andrews Watershed 10 (WS10) in Oregon. Model efficiencies were 0.37 for the 18O modeling for a 2 year time series; the efficiencies increased to 0.86 for the second year underlying the need of long time tracer time series with a long overlap of tracer input and output. The approach was able to determine time variant transit time of WS10 with field data and showed how it follows the storage dynamics and related changes in flow paths where wet periods with high flows resulted in clearly shorter transit times compared to dry low flow periods.

Divergent Perspectives on Water Security: Bridging the Policy Debate

Environmental policy discussion is replete with references to water security, food security, ecosystem health, community resilience, sustainable development, and sustainable urbanism. These terms are, by their very nature, ambiguous and difficult to define; they allow room, however, for a variety of actors to conceptualize water, food, ecological, economic, and urban problems in ways that allow them to move forward on contentious issues. This article focuses on the idea of water security and asks how it is conceptualized and used for regional policy debate in western Canada. We asked fifty-eight water stakeholders from the Saskatchewan River Basin to define water security, identify major barriers to security, and prioritize water problems. Responses showed there are myriad ways to think about water security, ranging from narrow conceptualizations, such as reliability, quality, and quantity, to broader sustainability perspectives about the nature of resource development and its social and economic consequences. The human dimensions of water security (governance, land use, and competing demands) were assigned higher priority than its biophysical aspects (flooding, droughts, and climate change). Framing water security to emphasize the human capacity to manage uncertain and rapid biophysical and societal change offers the opportunity to unite actors who otherwise would be separated by core environmental values, definitions of water security, provincial context (Alberta vs. Saskatchewan), and occupation.

Who Smells? Forecasting Taste and Odor in a Drinking Water Reservoir.

Taste and odor problems can impede public trust in drinking water and impose major costs on water utilities. The ability to forecast taste and odor events in source waters, in advance, is shown for the first time in this paper. This could allow water utilities to adapt treatment, and where effective treatment is not available, consumers could be warned. A unique 24-year time series, from an important drinking water reservoir in Saskatchewan, Canada, is used to develop forecasting models of odor using chlorophyll a, turbidity, total phosphorus, temperature, and the following odor producing algae taxa: Anabaena spp., Aphanizemenon spp., Oscillatoria spp., Chlorophyta, Cyclotella spp., and Asterionella spp. We demonstrate, using linear regression and random forest models, that odor events can be forecast at 0-26 week time lags, and that the models are able to capture a significant increase in threshold odor number in the mid-1990 s. Models with a fortnight time-lag show a high predictive capacity (R(2) = 0.71 for random forest; 0.52 for linear regression). Predictive skill declines for time lags from 0 to 15 weeks, then increases again, to R(2) values of 0.61 (random forest) and 0.48 (linear regression) at a 26-week lag. The random forest model is also able to provide accurate forecasting of TON levels requiring treatment 12 weeks in advance-93% true positive rate with a 0% false positive rate. Results of the random forest model demonstrate that phytoplankton taxonomic data outperform chlorophyll a in terms of predictive importance.

Precipitation downscaling in Canadian Prairie Provinces using the LARS-WG and GLM approaches

Two stochastic precipitation simulation models, namely the Long Ashton Research Station weather generator (LARS-WG) and a Generalized Linear Model-based weather generator (GLM-WG), are evaluated for downscaling daily precipitation at four selected locations (Banff, Calgary, Saskatoon and Winnipeg) in the Canadian Prairies. These weather generators model precipitation occurrence and amount components separately. Large-scale climate variables (including mean temperature, sea level pressure and relative humidity, derived from National Centers for Environmental Prediction reanalysis data) and observed precipitation records are used to calibrate and validate GLM-WG, while only observed precipitation records are used to calibrate and validate LARS-WG. A comparison of common statistical properties (i.e. annual/monthly means, variability of daily and monthly precipitation and monthly proportion of dry days) and characteristics of drought and extreme precipitation events derived from simulated and observed daily precipitation for the calibration (1961–1990) and validation (1991–2003) periods shows that both weather generators are able to simulate most of the statistical properties of the historical precipitation records, but GLM-WG appears to perform better than LARS-WG for simulating precipitation extremes and temporal variability of drought severity indices. For developing projected changes to precipitation characteristics, a change factor approach based on Canadian Global Climate Model (CGCM) simulated current (1961–1990) and future (2071–2100) period precipitation is used for driving simulations of LARS-WG, while for driving GLM-WG simulations, large-scale predictor variables derived from CGCM current and future period outputs are used. Results of both weather generators suggest significant increases to the mean annual precipitation for the 2080s. Changes to selected return levels of annual daily precipitation extremes are found to be both location- and generator-dependent, with highly significant increases noted for Banff with LARS-WG and for both Banff and Calgary with GLM-WG. Overall, 5- and 10-yr return levels are associated with increases (with the exception of Winnipeg) while 30- and 50-yr return levels are associated with site-dependent increases or decreases. A simple precipitation-based drought severity index suggests decreases in drought severity for the 2080s.

Projecting and hindcasting potential evaporation for the UK between 1950 and 2099

Evaporation estimation is important for the assessment of a wide range of potential impacts of climate change, yet there are significant questions concerning the relevance of alternative methods for climate change studies, and the uncertainty associated with downscaled driving variables. Using principal components analysis, climate variables related to evaporation have been examined; results show significant differences in correlation structures between observed UK data and climate outputs from a Hadley Centre Global Climate Model (HadCM3). Although employing the GCM data directly in the Penman-Monteith combination equation appears to be practical for estimating current potential evaporation, this approach does not project realistic potential evaporation in the 2080s. A local calibration approach is taken to the derivation of an alternative empirical model for estimating potential evaporation based on GCM outputs, using the Generalised Linear Model (GLM) framework. This appears to provide a robust method for impacts assessment. From the GLM projections, the envisaged change in evaporation will be spatially variable across the UK. It is expected that the southern part of the UK will be more sensitive to the change in evaporation than the north. Moreover, in the 2080s, the range (variance) of the monthly potential evaporation appears to change more than the mean.

Effects of initial soil water content and saturated hydraulic conductivity variability on small watershed runoff simulation using LISEM

Abstract Soil water content (θ) and saturated hydraulic conductivity (Ks) vary in space. The objective of this study was to examine the effects of initial soil water content (θi) and Ks variability on runoff simulations using the LImburg Soil Erosion Model (LISEM) in a small watershed in the Chinese Loess Plateau, based on model parameters derived from intensive measurements. The results showed that the total discharge (TD) and peak discharge (PD) were underestimated when the variability of θi and Ks was partially considered or completely ignored compared with those when the variability was fully considered. Time to peak (TP) was less affected by the spatial variability compared to TD and PD. Except for TP in some cases, significant differences were found in all hydrological variables (TD, PD and TP) between the cases in which spatial variability of θi or Ks was fully considered and those in which spatial variability was partially considered or completely ignored. Furthermore, runoff simulations were affected more strongly by Ks variability than by θi variability. The degree of spatial variability influences on runoff simulations was related to the rainfall pattern and θi. Greater rainfall depth and instantaneous rainfall intensity corresponded to a smaller influence of the spatial variability. Stronger effects of the θi variability on runoff simulation were found in wetter soils, while stronger effects of the Ks variability were found in drier soils. For accurate runoff simulation, the θi variability can be completely ignored in cases of a 1-h duration storm with a return period greater than 10 years, while Ks variability should be fully considered even in the case of a 1-h duration storm with a return period of 20 years. Editor D. Koutsoyiannis; Associate editor A. Fiori

Dynamic water quality modelling and uncertainty analysis of phytoplankton and nutrient cycles for the upper South Saskatchewan River

The surface water quality of the upper South Saskatchewan River was modelled using Water Quality Analysis Simulation Program (WASP) 7.52. Model calibration and validation were based on samples taken from four long-term water quality stations during the period 2007–2009. Parametric sensitivities in winter and summer were examined using root mean square error (RMSE) and relative entropy. The calibration and validation results show good agreement between model prediction and observed data. The two sensitivity methods confirmed pronounced parametric sensitivity to model state variables in summer compared to winter. Of the 24 parameters examined, dissolved oxygen (DO) and ammonia (NH3-N) are the most influenced variables in summer. Instream kinetic processes including nitrification, nutrient uptake by algae and algae respiration induce a higher sensitivity on DO in summer than in winter. Moreover, in summer, soluble reactive phosphorus (SRP) and chlorophyll-a (Chla) variables are more sensitive to algal processes (nutrient uptake and algae death). In winter however, there exists some degree of sensitivity of algal processes (algae respiration and nutrient uptake) to DO and NH3-N. Results of this study provide information on the state of the river water quality which impacts Lake Diefenbaker and the need for additional continuous monitoring in the river. The results of the sensitivity analysis also provide guidance on most sensitive parameters and kinetic processes that affect eutrophication for preliminary surface water quality modelling studies in cold regions.