Variation of Radio Refractivity with Respect to Moisture and Temperature and Influence on Radar Ray Path

In this study, the variation of radio refractivity with respect to temperature and moisture is analyzed. Also, the effects of vertical gradients in temperature and moisture on the propagation paths of electromagnetic waves of weather radar are examined for several sites across the United States using several years of sounding data from the National Weather Service. The ray path is important for identifying storm characteristics and for properly using the radar data in initializing numerical weather prediction models. It is found that during the warm season the radio refractivity gradient is more sensitive to moisture gradients than to temperature gradients. Ray paths from the commonly accepted vertical ray path model are compared to a ray path computed from a stepwise ray tracing algorithm using data from actual soundings. For the sample of about 16 000 soundings examined, we find that only a small fraction of the ray paths diverge significantly from those calculated using a ray path model based on the US Standard Atmosphere. While the problem of ray dueting in the presence of a temperature inversion is fairly well known, we identify the presence of a strong vertical moisture gradient as the culprit in the majority of the cases where significant deviations occurred.     

Reducing standard errors by incorporating spatial autocorrelation into a measurement scheme for soil carbon credits

Several studies have suggested that geostatistical techniques could be employed to reduce overall transactions costs associated with contracting for soil C credits by increasing the efficacy of sampling protocols used to measure C-credits. In this paper, we show how information about the range of spatial autocorrelation can be used in a measurement scheme to reduce the size of the confidence intervals that bound estimates of the mean number of C-credits generated per hectare. A tighter confidence interval around the mean number of C-credits sequestered could increase producer payments for each hectare enrolled in a contract to supply C-credits. An empirical application to dry land cropping systems in three regions of Montana shows that information about the spatial autocorrelation exhibited by soil C could be extremely valuable for reducing transactions costs associated with contracts for C-credits but the benefits are not uniform across all regions or cropping systems. Accounting for spatial autocorrelation greatly reduced the standard errors and narrowed the confidence intervals associated with sample estimates of the mean number of C-credits produced per hectare. For the payment mechanism considered in this paper, tighter confidence intervals around the mean number of C-credits created per hectare enrolled could increase producer payments by more than 100 percent under a C-contract.     

A modelling framework for evaluation of the hydrological impacts of nature‐based approaches to flood risk management,with application to in‐channel interventions across a 29‐km2 scale catchment in the United Kingdom

Nature‐based approaches to flood risk management are increasing in popularity. Evidence for the effectiveness at the catchment scale of such spatially distributed upstream measures is inconclusive. However, it also remains an open question whether, under certain conditions, the individual impacts of a collection of flood mitigation interventions could combine to produce a detrimental effect on runoff response. A modelling framework is presented for evaluation of the impacts of hillslope and in‐channel natural flood management interventions. It couples an existing semidistributed hydrological model with a new, spatially explicit, hydraulic channel network routing model. The model is applied to assess a potential flood mitigation scheme in an agricultural catchment in North Yorkshire, United Kingdom, comprising various configurations of a single variety of in‐channel feature. The hydrological model is used to generate subsurface and surface fluxes for a flood event in 2012. The network routing model is then applied to evaluate the response to the addition of up to 59 features. Additional channel and floodplain storage of approximately 70,000 m³ is seen with a reduction of around 11% in peak discharge. Although this might be sufficient to reduce flooding in moderate events, it is inadequate to prevent flooding in the double‐peaked storm of the magnitude that caused damage within the catchment in 2012. Some strategies using features specific to this catchment are suggested in order to improve the attenuation that could be achieved by applying a nature‐based approach.     

The potential for agricultural land use change to reduce flood risk in a large watershed

Effects of agricultural land management practices on surface runoff are evident at local scales, but evidence for watershed‐scale impacts is limited. In this study, we used the Soil and Water Assessment Tool model to assess changes in downstream flood risks under different land uses for the large, intensely agricultural, Raccoon River watershed in Iowa. We first developed a baseline model for flood risk based on current land use and typical weather patterns and then simulated the effects of varying levels of increased perennials on the landscape under the same weather patterns. Results suggest that land use changes in the Raccoon River could reduce the likelihood of flood events, decreasing both the number of flood events and the frequency of severe floods. The duration of flood events were not substantially affected by land use change in our assessment. The greatest flood risk reduction was associated with converting all cropland to perennial vegetation, but we found that converting half of the land to perennial vegetation or extended rotations (and leaving the remaining area in cropland) could also have major effects on reducing downstream flooding potential. We discuss the potential costs of adopting the land use change in the watershed to illustrate the scale of subsidies required to induce large‐scale conversion to perennially based systems needed for flood risk reduction. Copyright © 2013 John Wiley & Sons, Ltd.     

Testing the suitability of geologic frameworks for extrapolating hydraulic properties across regional scales

The suitability of geologic frameworks for extrapolating hydraulic conductivity (K) to length scales commensurate with hydraulic data is difficult to assess. A novel method is presented for evaluating assumed relations between K and geologic interpretations for regional-scale groundwater modeling. The approach relies on simultaneous interpretation of multiple aquifer tests using alternative geologic frameworks of variable complexity, where each framework is incorporated as prior information that assumes homogeneous K within each model unit. This approach is tested at Pahute Mesa within the Nevada National Security Site (USA), where observed drawdowns from eight aquifer tests in complex, highly faulted volcanic rocks provide the necessary hydraulic constraints. The investigated volume encompasses 40 mi³ (167 km³) where drawdowns traversed major fault structures and were detected more than 2 mi (3.2 km) from pumping wells. Complexity of the five frameworks assessed ranges from an undifferentiated mass of rock with a single unit to 14 distinct geologic units. Results show that only four geologic units can be justified as hydraulically unique for this location. The approach qualitatively evaluates the consistency of hydraulic property estimates within extents of investigation and effects of geologic frameworks on extrapolation. Distributions of transmissivity are similar within the investigated extents irrespective of the geologic framework. In contrast, the extrapolation of hydraulic properties beyond the volume investigated with interfering aquifer tests is strongly affected by the complexity of a given framework. Testing at Pahute Mesa illustrates how this method can be employed to determine the appropriate level of geologic complexity for large-scale groundwater modeling.     

Revisiting the death of geography in the era of Big Data: the friction of distance in cyberspace and real space

Many scholars have argued that the importance of geographic proximity in human interactions has been diminished by the use of the Internet, while others disagree with this argument. Studies have noted the distance decay effect in both cyberspace and real space, showing that interactions occur with an inverse relationship between the number of interactions and the distance between the locations of the interactors. However, these studies rarely provide strong evidence to show the influence of distance on interactions in cyberspace, nor do they quantify the differences in the amount of friction of distance between cyberspace and real space. To fill this gap, this study used massive amounts of social media data (Twitter) to compare the influence of distance decay on human interactions between cyberspace and real space in a quantitative manner. To estimate the distance decay effect in both cyberspace and real space, the distance decay function of interactions in each space was modeled. Estimating the distance decay in cyberspace in this study can help predict the degree of information flow across space through social media. Measuring how far ideas can be diffused through social media is useful for users of location-based services, policy advocates, public health officials, and political campaigners.