A modified ISBA surface scheme for modeling the hydrology of Athabasca River Basin with GCM-scale data

A soil–vegetation–atmosphere transfer model (SVAT), interactions between the soil–biosphere–atmosphere (ISBA) of Météo France, is modified and applied to the Athabasca River Basin (ARB) to model its water and energy fluxes. Two meteorological datasets are used: the archived forecasts from the Meteorological Survey of Canada’s Global Environmental Multiscale Model (GEM) and the European Centre for Mid-range Weather Forecasts global re-analysis (ERA-40), representing spatial scales typical of a weather forecasting model and a global circulation model (GCM), respectively. The original treatment of soil moisture and rainfall in ISBA (OISBA) is modified to statistically account for sub-grid heterogeneity of soil moisture and rainfall to produce new, highly non-linear formulations for surface and sub-surface runoff (MISBA). These new formulations can be readily applied to most existing SVATs. Stand alone mode simulations using the GEM data demonstrate that MISBA significantly improves streamflow predictions despite requiring two fewer parameters than OISBA. Simulations using the ERA-40 data show that it is possible to reproduce the annual variation in monthly, mean annual, and annual minimum flows at GCM scales without using downscaling techniques. Finally, simulations using a simple downscaling scheme show that the better performance of higher resolution datasets can be primarily attributed to improved representation of local variation of land cover, topography, and climate.     

Phytoplankton diversity in a tropical bay,North Borneo,Malaysia as revealed by light microscopy and Next-Generation Sequencing

Assessments of phytoplankton diversity in Sabah waters, North Borneo, have primarily relied on morphology-based identification, which has inherent biases and can be time-consuming. Next-Generation Sequencing (NGS) technology has been shown to be capable of overcoming several limitations of morphology-based methods. Samples were collected from the Sepanggar Bay over the course of the year 2018 in different monsoon seasons. Morphology-based identification and NGS sequencing of the V8–V9 region of the 18S LSU rDNA were used to investigate the diversity of the phytoplankton community. Microscopy and NGS showed complementary results with more diatom taxa detected by microscopy whereas NGS detected smaller and rarer taxa. The harmful algal genera in the study site comprised of Skeletonema, Margalefidinium, Pyrodinium, Takayama, and Alexandrium as detected by NGS. This study showed that that an integrative approach of both morphological and molecular techniques could provide more comprehensive information about the phytoplankton community as the approach captured quantitative variability as well as the diversity of phytoplankton species.     

Scaling properties of Canadian flood flows

This study investigated the spatial scaling properties of Canadian flood flows, namely, annual maximum mean 1‐, 5‐ and 7‐day flows using both the product moments (PMs) and probability weighted moments (PWMs). Both approaches demonstrate that flood flows in climatic regions 1 (Pacific), 2 (South British Columbia mountains), 3 (Yukon and northern British Columbia), 6 (Northeastern forest), 7 (Great Lakes and St. Lawrence rivers), 8 (Atlantic), and 10 (Arctic tundra) exhibit simple scaling with scaling exponent θ/H close to 0·90, while flood flows in regions 4 (Prairie provinces), 5 (Northwestern forest), and 9 (Mackenzie) does not with scaling exponent θ/H close to 0·50. The plots of coefficient of variations of flood flows versus drainage area indicate that Cv remains almost constant in regions 1, 2, 3, 6, 7, 8, and 10, while it decreases as drainage area increases in regions 4, 5, and 9. These results demonstrate that the index flood method is applicable in climatic regions 1, 2, 3, 6, 7, 8, and 10, while it is not in climatic regions 4, 5, and 9. The physical backgroud of the simple scaling of flood flows in most Canadian climatic regions is that snowmelt or rain‐on‐snow runoff is a dominant flood‐generating mechanism across the country. Copyright © 2008 John Wiley & Sons, Ltd.     

Climate change impact to Mackenzie river Basin projected by a regional climate model

Climate Dynamics - A regional climate model, WRF (Weather Research and Forecasting model), was set-up and fine-tuned to simulate the possible impacts of climate change to the Mackenzie River Basin...     

A simple estimation model for basal heave stability of braced excavations in anisotropic clay

Acta Geotechnica - The basal heave stability of the excavation and support system is a major concern to geotechnical design engineers, particularly in soft clay deposits. Conventional methods for...     

Estimation of rainfall from infrared‐microwave satellite data for basin‐scale hydrologic modelling

The infrared‐microwave rainfall algorithm (IMRA) was developed for retrieving spatial rainfall from infrared (IR) brightness temperatures (TBs) of satellite sensors to provide supplementary information to the rainfall field, and to decrease the traditional dependency on limited rain gauge data that are point measurements. In IMRA, a SLOPE technique (ST) was developed for discriminating rain/no‐rain pixels through IR image cloud‐top temperature gradient, and 243K as the IR threshold temperature for minimum detectable rainfall rate. IMRA also allows for the adjustment of rainfall derived from IR‐TB using microwave (MW) TBs. In this study, IMRA rainfall estimates were assessed on hourly and daily basis for different spatial scales (4, 12, 20, and 100 km) using NCEP stage IV gauge‐adjusted radar rainfall data, and daily rain gauge data. IMRA was assessed in terms of the accuracy of the rainfall estimates and the basin streamflow simulated by the hydrologic model, Sacramento soil moisture accounting (SAC‐SMA), driven by the rainfall data. The results show that the ST option of IMRA gave accurate satellite rainfall estimates for both light and heavy rainfall systems while the Hessian technique only gave accurate estimates for the convective systems. At daily time step, there was no improvement in IR‐satellite rainfall estimates adjusted with MW TBs. The basin‐scale streamflow simulated by SAC‐SMA driven by satellite rainfall data was marginally better than when SAC‐SMA was driven by rain gauge data, and was similar to the case using radar data, reflecting the potential applications of satellite rainfall in basin‐scale hydrologic modelling. Copyright © 2010 John Wiley & Sons, Ltd.     

A comparison of cumulus parameterization schemes in a numerical weather prediction model for a monsoon rainfall event

In order to evaluate cumulus parameterization (CP) schemes for hydrological applications, the Pennsylvania State University–National Center for Atmospheric Research's fifth‐generation mesoscale model (MM5) was used to simulate a summer monsoon in east China. The performances of five CP schemes (Anthes–Kuo, Betts–Miller, Fritsch–Chappell, Kain–Fritsch, and Grell) were evaluated in terms of their ability to simulate amount of rainfall during the heavy, moderate, and light phases of the event. The Grell scheme was found to be the most robust, performing well at all rainfall intensity and spatial scales. The Betts–Miller scheme also performed well, particularly at larger scales, but its assumptions may make it inapplicable to non‐tropical environments and at smaller scales. The Kain–Fritsch scheme was the best at simulating moderate rainfall rates, and was found to be superior to the Fritsch–Chappell scheme on which it was based. The Anthes–Kuo scheme was found to underpredict precipitation consistently at the mesoscale. Simulation performance was found to improve when schemes that included downdrafts were used in conjunction with schemes that did not include downdrafts. Copyright © 2005 John Wiley & Sons, Ltd.     

Assessment of apparent earth pressure for braced excavations in anisotropic clay

Acta Geotechnica - The evaluation of strut forces is critical to ensure the system stability of braced excavation in urban areas. The most common empirical approach to determine the forces in the...     

Modelling snowpack surface temperature in the Canadian Prairies using simplified heat flow models

Three practical schemes for computing the snow surface temperature T_s, i.e. the force–restore method (FRM), the surface conductance method (SCM), and the Kondo and Yamazaki method (KYM), were assessed with respect to T_s retrieved from cloud‐free, NOAA‐AVHRR satellite data for three land‐cover types of the Paddle River basin of central Alberta. In terms of R², the mean T_s, the t‐test and F‐test, the FRM generally simulated more accurate T_s than the SCM and KYM. The bias in simulated T_s is usually within several degrees Celsius of the NOAA‐AVHRR T_s for both the calibration and validation periods, but larger errors are encountered occasionally, especially when T_s is substantially above 0 °C. Results show that the simulated T_s of the FRM is more consistent than that of the SCM, which in turn was more consistent than that of the KYM. This is partly because the FRM considers two aspects of heat conduction into snow, a stationary‐mean diurnal (sinusoidal) temperature variation at the surface coupled to a near steady‐state ground heat flux, whereas the SCM assumes a near steady‐state, simple heat conduction, and other simplifying assumptions, and the KYM does not balance the snowpack heat fluxes by assuming the snowpack having a vertical temperature profile that is linear. Copyright © 2005 John Wiley & Sons, Ltd.