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The diffusive wave equation, a simplified form of the Saint‐Venant equations, is extensively used in flood routing. To solve the equation, numerous methods have been developed over the years. Most of them are numerical and hence their application generally requires case‐specific modeling and analysis to ensure stable solution. For many practical routing applications, however, simpler yet accurate methods are highly desirable that do not require problem‐specific numerical modeling. This work extends the previous analytical solutions with more flexible boundary conditions, presents two quasianalytical methods for solving the 1‐D linear diffusive wave equation on finite domains, and applies them to different types of routing problems. Referred to as the Symbolic Diffusive Wave Solutions, the proposed methods yield explicit symbolic expressions for time‐continuous solutions at discrete nodes in space and provide solutions that are accurate and computationally efficient. The methods are easy to implement and may be used in a variety of routing applications in which accurate explicit symbolic solutions for linear advection‐diffusion are desired for a set of discrete locations such as known river forecast points. This study describes the solutions and their application in different types of real‐world and synthetic routing problems. Key Points: Symbolic closed‐form solutions for 1‐D linear diffusive wave equation are developedThe solutions are valid at specific nodes and are compactly expressed as explicit functions of time and channel propertiesThe methods can handle various types of upstream inflow and downstream boundary conditions [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this study was to investigate the production of chitin and chitosan from both the exuvium and whole body of mealworm (Tenebrio molitor) larvae. Chitin from the exuvium and whole body of T. molitor larvae was chemically extracted with acid and alkali solutions to achieve demineralization (DM) and deproteinization (DP), respectively. The average DM (%) and DP (%) on a dry weight (DW) basis was 32.56 and 73.16% from larval exuvium, and 41.68 and 91.53% from whole body, respectively. To obtain chitosan, chitin particles from the exuvium and whole body of T. molitor larva were heated at various temperatures in different concentrations of NaOH. Average chitin yields were 18.01% and 4.92% of DW from the exuvium and whole body, respectively. The relative average yield of chitosan from whole body was 3.65% of DW. On average, over 90% of chitosan derived from whole body was deacetylated. The viscosity of chitosan from whole body was ranged from 48.0 cP to 54.0 cP. The chitin content of dry and wet byproducts from whole body were 17.32% and 16.94% respectively, compared to dry weight. The chitosan contents of byproducts on a DW basis were 14.48% in dry and 13.07% in wet byproduct. These results indicate that the exuvium and whole body of T. molitor larva may serve as a source of chitin and chitosan for use in domestic animal feed. [ABSTRACT FROM AUTHOR]

This paper evaluates a nonparametric technique for estimating the conditional probability distribution of a predictand given a vector of predictors. In the current application, the predictors are formed from a multimodel ensemble of simulated streamflows, such that the hydrologic uncertainties are modelled independently of any forcing uncertainties. The technique is based on Bayesian optimal linear estimation of indicator variables and is analogous to indicator cokriging (ICK) in geostatistics. By developing linear estimators for the conditional probability that the observed variable does not exceed several thresholds, ICK provides a discrete approximation of the full conditional probability distribution. The weights of the predictors can be chosen to minimize the expected error variance at each threshold (the Brier score) or, without loss of analytical tractability, a combination of the error variance and the expected square bias conditional upon the observation, i.e. the Type-II conditional bias (CB). The latter is referred to as CB-penalized ICK (CBP-ICK) and is an important enhancement to ICK. Indeed, the biases in atmospheric and hydrologic predictions generally increase towards the tails of their probability distributions. The performance of CBP-ICK is evaluated for selected basins in the eastern USA using a range of probabilistic verification metrics and associated confidence intervals for the sampling uncertainties. Overall, CBP-ICK produces unbiased and skillful estimates of the hydrologic uncertainties, with some sensitivity to the calibration data period at high flow thresholds. More generally, we argue that the common aim in statistical post-processing of 'maximizing sharpness subject to reliability (Type-I CB)' should be recast to accommodate both the Type-I and Type-II CBs, as both are important for practical applications of hydrologic predictions. Copyright © 2012 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Systematic biases in WSR-88D (Weather Surveillance Radar-1988 Doppler) hourly precipitation accumulation estimates are characterized from analyses of more than 1 year of WSR-88D data and rain gage data from the southern plains. Biases are examined in three contexts: (1) biases that arise from the range-dependent sampling of the WSR-88D, (2) systematic differences in radar rainfall estimates from two radars observing the same area, and (3) systematic differences between radar and rain gage estimates of rainfall. Range-dependent biases affect hourly rainfall accumulations products over much of the area covered by the WSR-88D. Significant underestimation of rainfall occurs within 40 km range of the radar due to bias in reflectivity observations at the higher elevation angles used for rainfall estimation close to the radar. Bright band and anomalous propagation (AP) lead to systematic overestimation of rainfall at intermediate range. Beyond 150 km in spring-summer and beyond 100 km in winter-fall, underestimation of precipitation is pronounced due to incomplete beam filling and overshooting of precipitation. Radar-radar intercomparison studies suggest that radar calibration is a significant problem at some sites. Anomalous propagation during clear-air conditions, a major problem with previous National Weather Service network radars, has been largely eliminated by the WSR-88D processing. AP remains a problem for cases in which AP returns are embedded in rain. Radar-rain gage intercomparison analyses indicate systematic underestimation by the WSR-88D relative to rain gages for paired gage-radar rainfall estimates. Analyses of spatial coverage of heavy rainfall, however, illustrate fundamental advantages of radar over rain gage networks for rainfall estimation. [ABSTRACT FROM AUTHOR]

The role of fractional coverage in climatological variability of mean areal rainfall is investigated. Under second-order homogeneity assumptions, climatological variability of mean areal rainfall, as measured by its coefficient of variation, is shown to be a function of mean fractional coverage, conditional coefficient of variation of point rainfall, and two correlation scales associated with inner variability and intermittency of point rainfall. To verify the analytical results, empirical analyses are performed using hourly rainfall data from nine Weather Surveillance Radar-1988 Doppier (WSR-88D) radars in the southern plains, United States. The results indicate that given the local rainfall climatology there exists a catchment scale at which the climatological variability of mean areal rainfall is at its maximum. Existence of such a scale has been hypothesized and demonstrated via an analytical treatment of an idealized situation by Eagleson and Wang [1985], but only in climatological variability of fractional coverage (i.e., variability due only to intermittency). Sensitivity analyses for the correlation-scale parameters indicate that intermittency plays as important a role as inner variability in shaping the catchment scale-climatological variability relationship of mean areal rainfall. Decomposition of total variability indicates that over the range of catchment scales that fall within a single WSR-88D radar umbrella (effective radius of 230 km) the integrated contribution from intermittency is almost as large as that from inner variability. [ABSTRACT FROM AUTHOR]

The relationship between catchment scale and climatological variability of surface-runoff volume is evaluated through theoretical and empirical analyses. Using a point description of surface-runoff volume following infiltration excess under the time compression approximation, climatological mean and variance of areal runoff volume over heterogeneous soil are evaluated by integrating second-order statistics of point runoff volume. Second-order statistics of rainfall duration and intensity, required for evaluation of those of point runoff volume, are obtained from mean and variance of areal rainfall volume under fractional coverage considerations. Hourly Weather Surveillance Radar-1988 Doppler rainfall data were used to estimate rainfall parameters following a set of simplifying assumptions on the space-time correlation structure. Two contrasting climate-soil systems were considered in specifying soil and soil moisture parameters following a set of assumptions on spatial variability and interdependency of the soil parameters. [ABSTRACT FROM AUTHOR]

Cokriging is used to merge rain gage measurements and radar rainfall data. The cokriging estimators included are ordinary, universal, and disjunctive. To evaluate the estimators, two simulation experiments are performed. The first experiment assumes that high-quality radar rainfall fields are ground truth rainfall fields. From each ground truth rainfall field, multiple combinations of rain gage measurement field and radar rainfall field are artificially generated with varying gage network density and error characteristics of radar rainfall. The second experiment uses a stochastic space-time rainfall model to generate assumed ground truth rainfall fields of various characteristics. Due to the sparsity of rain gage measurements, the second-order statistics required for cokriging can only be estimated with large uncertainty. The adverse effects of this uncertainty, and the point sampling error of rain gage measurements are explicitly assessed by cokriging the ground truth rainfall data and the radar rainfall data with near perfectly known second-order statistics. [ABSTRACT FROM AUTHOR]

An intraseasonal irrigation scheduling problem is dealt with via extended linear quadratic (ELQ) control. The ELQ control is well-suited for constrained multidimensional problems and provides openloop feedback control rules over the control horizon. A conceptual model is developed to describe the dynamics of water allocation and salt movement in the root zone of a crop. Moisture stress and osmotic stress are combined to obtain the integrated inhibitory effect of salinity on transpiration. For the intraseasonal model to be effective against perennial salt accumulation in the root zone, it should be able to yield control laws which will lead to favorable root zone conditions at the end of an irrigation season, thus avoiding any significant leaching prior to the next growing season. This long-term aspect of salinity control is handled via probabilistic state constraints which impose desired salinity and moisture levels with desired confidence level. The ELQ control is employed in a case study of expected net benefit maximization over an irrigation season of corn in Fort Morgan, Colorado. The results, in general, correspond well with expected irrigation schedules under different conditions and provide valuable information on both short- and long-term aspects of irrigation control under saline conditions. The ELQ control, being an analytic iterative solution scheme with theoretically guaranteed fast convergence, has a distinct computational advantage over state-of-the-art procedures. [ABSTRACT FROM AUTHOR]