Improving soil moisture accounting and streamflow prediction in SWAT by incorporating a modified time‐dependent Curve Number method

The objective of this study is to incorporate a time‐dependent Soil Moisture Accounting (SMA) based Curve Number method (SMA_CN) in Soil and Water Assessment Tool (SWAT) and compare its performance with the existing CN method in SWAT by simulating the hydrology of two agricultural watersheds in Indiana, USA. Results show that fusion of the SMA_CN method causes decrease in runoff volume and increase in profile soil moisture content, associated with larger groundwater contribution to the streamflow. In addition, the higher amount of moisture in the soil profile slightly elevates the actual evapotranspiration. The SMA‐based SWAT configuration consistently produces improved goodness‐of‐fit scores and less uncertain outputs with respect to streamflow during both calibration and validation. The SMA_CN method exhibits a better match with the observed data for all flow regimes, thereby addressing issues related to peak and low flow predictions by SWAT in many past studies. Comparison of the calibrated model outputs with field‐scale soil moisture observations reveals that the SMA overhauling enables SWAT to represent soil moisture condition more accurately, with better response to the incident rainfall dynamics. While the results from the modification of the CN method in SWAT are promising, more studies including watersheds with various physical and climatic settings are needed to validate the proposed approach. Copyright © 2015 John Wiley & Sons, Ltd.     

A model for computing small-scale wind variations over a water surface

Based on the primitive equations, a one-level model is described for computing surface winds under the meso-scale influences of orography, friction and heating. The effects of atmospheric stability and land-water contrasts are examined in detail. Results of testing the model with data collected during the International Field Year for the Great Lakes (IFYGL) in 1972 are given. The model is able to simulate land and lake breezes as well as meso-scale effects due to gradients in surface water temperature. Compared to simple methods of computing surface winds, use of the model reduces the vector error in estimates of surface winds by about 1.25 m s^–1 on the average.     

Inclusion of ice cover in a storm surge model for the Beaufort Sea

Storm surges in the Beaufort Sea present a severe problem for navigation as well as for offshore oil drilling activities. Influence of ice cover on storm surges in the Beaufort Sea is examined making use of a numerical model as well as a set of observations. The automated shallow-water model of Henry has been modified to incorporate ice cover and is adapted to the Beaufort Sea. The leading edge of the permanent ice is calculated from the loci of identifiable points. Generalized similarity theory is employed to compute wind stresses. Simulations are made using model-predicted ice concentrations and observed ice concentrations. Ice motion is relatively small in units of model grid distance (approximately 18 km) during surges. Spherical effects are important and should be included in future adaptations of the model. Comparison of the computed surges with observed surges for eight different events showed reasonable agreement.     

Secondary instability as a possible mechanism for clear-air turbulence: a case study

Many theories and mechanisms have been proposed to explain the phenomenon of clear-air turbulence (CAT), and some of them have been successful in predicting light, moderate and, in some cases, severe turbulence. It is only recently that skill in the forecasting of the severe form of CAT, which could lead to injuries to passengers and damage to aircraft, has improved. Recent observations and simulations suggest that some severe to extreme turbulence could be caused by horizontal vortex tubes resulting from secondary instabilities of regions of high shear in the atmosphere. We have conducted direct numerical simulations to understand the scale relationship between primary structures (larger-scale structures related to one of the causes mentioned above) and secondary structures (smaller-sized, shear structures of the size of aircraft). From shear layer simulations, we find that the ratio of sizes of primary and secondary vortices is of the right order to generate aircraft-scale vortex tubes from typical atmospheric shear layers. We have also conducted simulations with a mesoscale atmospheric model, to understand possible causes of turbulence experienced by a flight off the west coast of India. Our simulations show the occurrence of primary flow structures related to synoptic conditions around the time of the incident. The evidence presented for this mechanism also has implications for possible methods of detection and avoidance of severe CAT.     

The oil spill behaviour model of the Canadian atmospheric environment service Part I: Theory and model evaluation

Abstract

This paper describes a model to simulate the behaviour of oil spills in marine environments. The model includes parametrizations of various physical processes representing the movement and weathering of an oil slick. The movement of the slick is affected by wind‐driven, tidal and residual water currents. Turbulent dispersion is an important mechanism influencing the horizontal spreading of the slick for time periods greater than about a day.

The model is used to simulate successfully the movement of spill‐following buoys deployed in the Bay of Fundy, where some of the strongest tidal currents in the world occur. The ability of the model to simulate the horizontal spreading of an oil slick was evaluated with observed data from the Argo Merchant oil spill for a 10‐day period. It was found that the observed shape and extent of the spill could be fairly well described by the parametrization of turbulent dispersion effects.     

Storm surges in Canadian waters

Abstract

Storm surges in various Canadian waters are reviewed. Following a brief discussion of the weather systems that cause storm surges in Canadian coastal and inland waters, the mathematical formulations to describe the development of storm surges are given. In reviewing storm surges in the different Canadian waters, particular attention is given to describe the influence of the presence of sea ice on surge development and the impact of shallow coastal areas, where the coastline configuration is itself changed by the surge, on inland penetration of the storm surge. The Canadian waters that may be affected by storm surges include the east and west coasts, the Beaufort Sea, the Gulf of St. Lawrence and the St. Lawrence estuary, Hudson Bay and the Great Lakes.     

A multidimensional fuzzy least-squares regression approach for estimating hydraulic gradients in unconfined aquifer formations and its application to the Gulf Coast aquifer in Goliad County,Texas

Epistemic uncertainties arise during the estimation of hydraulic gradients in unconfined aquifers due to planar approximation of the water table as well as data gaps arising from factors such as instrument failures and site inaccessibility. A multidimensional fuzzy least-squares regression approach is proposed here to estimate hydraulic gradients in situations where epistemic uncertainty is present in the observed water table measurements. The hydraulic head at a well is treated as a normal (Gaussian) fuzzy variable characterized by a most likely value and a spread. This treatment results in hydraulic gradients being characterized as normal fuzzy numbers as well. The multidimensional fuzzy least-squares regression has an exact analytical form and as such can be implemented easily using matrix algebra methods. However, the method was noted to be sensitive to round-off and truncation errors when the epistemic uncertainties are small. A closeness index based on the cardinality of a fuzzy number is used to evaluate how well the regression model fits the fuzzy hydraulic head observations. A fuzzy Euclidian distance measure is used to compare two fuzzy numbers and to evaluate how fuzziness in the observed hydraulic heads affects the fuzziness in the estimated hydraulic gradients. The Euclidian distance measure is also used to ascertain the influence of each well on the fuzzy hydraulic gradient estimation. The fuzzy regression framework is illustrated by applying it to evaluate hydraulic gradients in the unconfined portion of the Gulf Coast aquifer in Goliad County, TX. The results from the case-study indicate that there is greater uncertainty associated with the estimation of the hydraulic gradients in the vertical (Z-axis) direction. The epistemic uncertainties in the hydraulic head data at the wells have a significant impact on the gradient estimates when they are of the same order of magnitude as the most likely values of the observed heads. The influence analysis indicated that 5 of the 13 wells in the network had a critical influence on at least one of the hydraulic gradients. Three wells along the northeastern section of the study area and bordering the Victoria County were noted to have the least influence on the regression estimates. The fuzzy regression framework along with the associated goodness-of-fit and influence measures provides a useful set of tools to characterize the uncertainties in the hydraulic heads and gradients arising from data gaps and planar water table approximation.