Modeling the effect of snow on seasonal runoff within the Truckee River drainage basin

EXTRACT (SEE PDF FOR FULL ABSTRACT): We estimate monthly runoff for a 2-dimensional solution domain containing those areas tributary to Pyramid Lake, Nevada (the Truckee River drainage basin) at a 1-kilometer grid cell spacing. ... To calculate the effect of snow on the hydrologic system, we perform two experiments. In the first we assume that all precipitation falls as rain; in the second we assume that some precipitation falls as snow, thus available water is a combination of rain and snowmelt. We find that considering the effect of snow results in a more accurate representation of mean monthly flow rates, in particular the peak flow during the melt season in the Sierra Nevada. These preliminary results indicate that a relatively simple snow model can improve the representation of Truckee River basin hydrology, significantly reducing errors in modeled seasonal runoff.

TIME RESOLVED REFLECTIVITY MEASUREMENTS APPLIED TO RAPID ISOTHERMAL ANNEALING OF ION IMPLANTED SILICON.

The annealing of ion implantation damage in silicon by rapid isothermal heating has been monitored by the time resolved reflectivity (TRR) method. This technique was applied simultaneously at a wavelength of 632. 8nm and also at 1152nm, where the optical absorption coefficient of silicon is less. The two wavelength method simplifies the interpretation of TRR results, extends the measurement depth and allows good resolution of the position of the interface between amorphous and crystalline silicon. The regrowth of amorphous layers in silicon, created by self implantation and implanted with electrically active impurities, was observed. Regrowth in rapid isothermal annealing occurs during the heating up stage of typical thermal cycles. Impurities such as B, P, and As increase the regrowth rate in a manner consistent with a vacancy model for regrowth. The maximum regrowth rate in boron implanted silicon is limited by the solid solubility.

Model structure and uncertainty for stochastic non-point source modelling applications

The uncertainty associated with a rainfall-runoff and non-point source loading (NPS) model can be attributed to both the parameterization and model structure. An interesting implication of the areal nature of NPS models is the direct relationship between model structure (i.e. sub-watershed size) and sample size for the parameterization of spatial data. The approach of this research is to find structural limitations in scale for the use of the conceptual NPS model, then examine the scales at which suitable stochastic depictions of key parameter sets can be generated. The overlapping regions are optimal (and possibly the only suitable regions) for conducting meaningful stochastic analysis with a given NPS model. Previous work has sought to find optimal scales for deterministic analysis (where, in fact, calibration can be adjusted to compensate for sub-optimal scale selection); however, analysis of stochastic suitability and uncertainty associated with both the conceptual model and the parameter set, as presented here, is novel; as is the strategy of delineating a watershed based on the uncertainty distribution. The results of this paper demonstrate a narrow range of acceptable model structure for stochastic analysis in the chosen NPS model. In the case examined, the uncertainties associated with parameterization and parameter sensitivity are shown to be outweighed in significance by those resulting from structural and conceptual decisions. © 2011 Copyright IAHS Press.

Model development & application for inland navigational canals

Several agencies in the United Kingdom have interest in the water quality of old navigational canals that have fallen into disuse after the decline of commercial canal transportation. The interested agencies desired a model to predict the water quantity and quality of inland navigational canals in order to evaluate management options to address the issues in the natural streams to which they discharge. Inland navigational canals have unique drivers of their hydrology and water quality compared to either natural streams, irrigation canals, or larger navigational canals connected to seas or oceans. Water in an inland canal is typically sourced from a reservoir and artificially pumped to a summit reach; its movement downhill is controlled by the activity of boats and overflow weirs. Stagnant impoundments between locks, which might normally be expected to result in a decrease in the concentration of sediment-associated pollutants, actually have surprisingly high levels of sediment due to boat traffic. Algal growth in the stagnant reach can be high. This paper describes a canal model developed to simulate hydrology and water quality in inland navigational canals. This model was successfully applied to the Kennet and Avon Canal to predict hydrology, sediment generation and transport, and algal growth and transport. The model is responsive to external influences such as sunlight, temperature, nutrient concentrations, boat traffic, and runoff from the contributing catchment area.

A non-linear perturbation model considering catchment wetness and its application in river flow forecasting

A non-linear perturbation model for river flow forecasting is developed, based on consideration of catchment wetness using an antecedent precipitation index (API). Catchment seasonality, of the form accounted for in the linear perturbation model (the LPM), and non-linear behaviour both in the runoff generation mechanism and in the flow routing processes are represented by a constrained nan-linear model, the NLPM-API. A total of ten catchments, across a range of climatic conditions and catchment area magnitudes, located in China and in other countries, were selected for testing daily rainfall-runoff forecasting with this model. It was found that the NLPM-API model was significantly more efficient than the original linear perturbation model (the LPM). However, restric tion of explicit nan-linearity to the runoff generation process, in the simpler LPM-API form of the model, did not produce a significantly lower value of the efficiency in flood forecasting, in terms of the model efficiency index R-2. (C) 1997 Elsevier Science B.V.

Detailed model and investigation of gain saturation and carrier spatial hole burning for a semiconductor optical amplifier with gain clamping by a vertical laser field

A detailed model for semiconductor linear optical amplifiers (LOAs) with gain clamping by a vertical laser field is presented, which accounts the carrier and photon density distribution in the longitudinal direction as well as the facet reflectivity. The photon iterative method is used in the simulation with output amplified spontaneous emission spectrum in the wide band as iterative variables. The gain saturation behaviors and the noise figure are numerically simulated, and the variation of longitudinal carrier density with the input power is presented which is associated with the ON-OFF state of the vertical lasers. The results show that the LOA can have a gain spectrum clamped in a wide wavelength range and have almost the same value of noise figure as that of conventional semiconductor optical amplifiers (SOAs). Numerical results also show that an LOA can have a noise figure about 2 dB less than that of the SOA gain clamped by a distributed Bragg reflector laser.

Impacts of water conservancy and soil conservation measures on annual runoff in the Chaohe River Basin during 1961-2005

National Key Technology RD Program [2006BAD03A02]

Model analysis of dissolved inorganic phosphorus exports from the Yangtze river to the estuary

In this paper, we estimate the inputs of phosphorus (P) to the Yangtze River Basin and exports of dissolved inorganic phosphorus (DIP) from the river to the estuary for the period 1970-2003, by using the global NEWS-DIP model. Modeled DIP yields range from 2.5 kg P km(-2) yr(-1) in 1970 to 4.6 kg P km(-2) yr(-1) in 1985, and then dramatically increase to 14.1 kg P km(-2) yr(-1) in 2003. No significant difference between the modeled and measured values at the level of P = 0.05 is observed. The study also demonstrates variable source contributions of P to the modeled DIP during the period 1970-2003. Point sewage P input accounted for approximately 100% in the period 1970-1985 and substantially decreased to 24.8% in 2003. Chemical fertilizer contributed 25.4% of DIP yields in 1986 and increased continuously to 50.3% in 2003, while a stable trend in manure P contribution averaging 22.9% of DIP yields was shown in the same period. The study concludes that P inputs to the Yangtze River Basin and the river DIP export to the estuary have substantially increased during the study period consequence to human pressure.

A new model to estimate significant wave heights with ERS-1/2 scatterometer data

A new model is proposed to estimate the significant wave heights with ERS-1/2 scatterometer data. The results show that the relationship between wave parameters and radar backscattering cross section is similar to that between wind and the radar backscattering cross section. Therefore, the relationship between significant wave height and the radar backscattering cross section is established with a neural network algorithm, which is, if the average wave period is <= 7s, the root mean square of significant wave height retrieved from ERS-1/2 data is 0.51 m, or 0.72 m if it is >7s otherwise.

On SAR wind speed ambiguities and related geophysical model functions

Recent investigations show that normalized radar cross sections for C-band microwave sensors decrease under high wind conditions with certain incident angles instead of increase, as is the case for low to moderate wind speeds. This creates the problem of ambiguities in high wind speed retrievals from synthetic aperture radar (SAR). In the present work, four geophysical model functions (GMFs) are studied, namely the high wind C-band model 4 (CMOD4HW), C-band model 5 (CMOD5), the high wind vertical polarized GMF (HWGMF_VV), and the high wind horizontal polarized GMF (HWGMF_HH). Our focus is on model behaviours relative to wind speed ambiguities. We show that, except for CMOD4HW, the other GMFs exhibit the wind speed ambiguity problem. To consider this problem in high wind speed retrievals from SAR, we focus on hurricanes and propose a method to remove the speed ambiguity using the dominant hurricane wind structure.

Near-Space Wide-Swath Radar Imaging With Multiaperture Antenna

Near-space, defined as the altitude region between 20 and 100 km, offers many capabilities that are not accessible for low Earth-orbit (LEO) satellites or airplanes because it is above storm and not constrained by orbital mechanics and high fuel consumption. Hence, a high flying speed can be obtained for the maneuvering vehicles operating in near-space. This offers a promising solution to simultaneous high-resolution and wide-swath synthetic aperture radar (SAR) imaging. As such, one near-space wide-swath SAR imaging technique is presented in this letter. The system configuration, signal model, and imaging scheme are described. An example near-space SAR system is designed, and its imaging performance is analyzed. Simulation results show that near-space maneuvering vehicle SAR indeed seems to be a promising solution to wide-swath SAR imaging.

Sublimation of snow from confierous forests in a climate model

Essery, R L H, Pomeroy, J W, Parvianen, J & Storck, P, Sublimation of snow from confierous forests in a climate model. Journal of Climate 16, pp 1855-1864 (2003).

Processing of Synthetic Aperture Radar Images by a Multiscale Boundary Contour System and Feature Contour System

An improved Boundary Contour System (BCS) and Feature Contour System (FCS) neural network model of preattentive vision is applied to large images containing range data gathered by a synthetic aperture radar (SAR) sensor. The goal of processing is to make structures such as motor vehicles, roads, or buildings more salient and more interpretable to human observers than they are in the original imagery. Early processing by shunting center-surround networks compresses signal dynamic range and performs local contrast enhancement. Subsequent processing by filters sensitive to oriented contrast, including short-range competition and long-range cooperation, segments the image into regions. The segmentation is performed by three "copies" of the BCS and FCS, of small, medium, and large scales, wherein the "short-range" and "long-range" interactions within each scale occur over smaller or larger distances, corresponding to the size of the early filters of each scale. A diffusive filling-in operation within the segmented regions at each scale produces coherent surface representations. The combination of BCS and FCS helps to locate and enhance structure over regions of many pixels, without the resulting blur characteristic of approaches based on low spatial frequency filtering alone.

Processing of Synthetic Aperture Radar Images by the Boundary Contour System and Feature Contour System

An improved Boundary Contour System (BCS) and Feature Contour System (FCS) neural network model of preattentive vision is applied to two large images containing range data gathered by a synthetic aperture radar (SAR) sensor. The goal of processing is to make structures such as motor vehicles, roads, or buildings more salient and more interpretable to human observers than they are in the original imagery. Early processing by shunting center-surround networks compresses signal dynamic range and performs local contrast enhancement. Subsequent processing by filters sensitive to oriented contrast, including short-range competition and long-range cooperation, segments the image into regions. Finally, a diffusive filling-in operation within the segmented regions produces coherent visible structures. The combination of BCS and FCS helps to locate and enhance structure over regions of many pixels, without the resulting blur characteristic of approaches based on low spatial frequency filtering alone.

Human respiration rate estimation using ultra-wideband distributed cognitive radar system

It has been shown that remote monitoring of pulmonary activity can be achieved using ultra-wideband (UWB) systems, which shows promise in home healthcare, rescue, and security applications. In this paper, we first present a multi-ray propagation model for UWB signal, which is traveling through the human thorax and is reflected on the air/dry-skin/fat/muscle interfaces. A geometry-based statistical channel model is then developed for simulating the reception of UWB signals in the indoor propagation environment. This model enables replication of time-varying multipath profiles due to the displacement of a human chest. Subsequently, a UWB distributed cognitive radar system (UWB-DCRS) is developed for the robust detection of chest cavity motion and the accurate estimation of respiration rate. The analytical framework can serve as a basis in the planning and evaluation of future measurement programs. We also provide a case study on how the antenna beamwidth affects the estimation of respiration rate based on the proposed propagation models and system architecture