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.     

English Jurassic Limestone Country: Stroud,Central Cotswolds

The area around Stroud, a small English market town perched on the steep west‐facing Cotswold escarpment, offers some of the most dramatic outcrops of Jurassic limestone in the UK. From sweeping vistas of the Severn Vale, to the deeply wooded river valleys that indent the escarpment, its landscape is undeniably one of the area's greatest assets. Recently, the geology and physiography of the landscape has been drawn into close focus by several notable UK media stories: protests against hydraulic fracturing (fracking) in the underlying Lias clays; landslides causing weeks of repeated disruption across the Cotswold road and railway networks; and the recent death of a local engineer in a pit collapse of Fuller's Earth. In order to understand these stories in greater depth, it is useful to consider the story of Stroud's unique physical setting.     

Joint modelling of wave spectral parameters for extreme sea states

Characterising the dependence between extremes of wave spectral parameters such as significant wave height (H_S) and spectral peak period (T_P) is important in understanding extreme ocean environments and in the design and assessment of marine structures. For example, it is known that mean values of wave periods tend to increase with increasing storm intensity. Here we seek to characterise joint dependence in a straightforward manner, accessible to the ocean engineering community, using a statistically sound approach.Many methods of multivariate extreme value analyses are based on models which assume implicitly that in some joint tail region each parameter is either independent of or asymptotically dependent on other parameters; yet in reality the dependence structure in general is neither of these. The underpinning assumption of multivariate regular variation restricts these methods to estimation of joint regions in which all parameters are extreme; but regions where only a subset of parameters are extreme can be equally important for design. The conditional approach of Heffernan and Tawn (2004), similar in spirit to that of Haver (1985) but with better theoretical foundation, overcomes these difficulties.We use the conditional approach to characterise the dependence structure of H_S and T_P. The key elements of the procedure are: (1) marginal modelling for all parameters, (2) transformation of data to a common standard Gumbel marginal form, (3) modelling dependence between data for extremes of pairs of parameters using a form of regression, (4) simulation of long return periods to estimate joint extremes. We demonstrate the approach in application to measured and hindcast data from the Northern North Sea, the Gulf of Mexico and the North West Shelf of Australia. We also illustrate the use of data re-sampling techniques such as bootstrapping to estimate the uncertainty in marginal and dependence models and accommodate this uncertainty in extreme quantile estimation.We discuss the current approach in the context of other approaches to multivariate extreme value estimation popular in the ocean engineering community.     

A diatom‐inferred record of lake variability during the last 900 years in Lützow–Holm Bay,East Antarctica

Decadal–centennial‐scale climate variability in coastal Antarctica remains poorly understood due to the limited number of highly resolved, well‐dated records. We present a 900‐year, decadal‐scale reconstruction based on sedimentary diatoms from Lake Abi in Lützow–Holm Bay, East Antarctica. Hydrological change is inferred from diatom ecological preferences in conjunction with an existing regional training set and implies that lake water specific conductivity, depth and nitrogen availability are the key drivers of diatom assemblage change. Lake Abi underwent a series of subtle environmental changes related to these environmental variables, possibly driven by changes in catchment snow melt and the duration of seasonal ice cover. Ordination is used to trace the major patterns of change in the diatom community, with notable shifts identified between 470 and 400 and at ～350 cal a BP (where present = CE 1950). The frequency of environmental variability at Lake Abi is broadly consistent with a record of the Interdecadal Pacific Oscillation during the last millennium, but contrasts with the apparent climate stability elsewhere in eastern Antarctica. Further research is required to constrain the limnological and ecological responses of lakes in coastal Antarctica to obtain more rigorous palaeoclimate reconstructions from these sites of immense potential.     

Approach to calculating spatial similarity degrees of the same river basin networks on multi-scale maps

Obtaining spatial similarity degrees among the same objects on multi-scale maps is of importance in map generalization. This paper firstly defines the concepts of ‘map scale change’ and ‘spatial similarity degree’; then it proposes a model for calculating the spatial similarity degree between a river basin network at one scale and its generalized version at another scale. After this, it validates the new model and gets 16 points in the model validation process. The x-coordinate and y-coordinate of each point are map scale change and spatial similarity degree, respectively. Last, a formula for calculating spatial similarity degree taking map scale change as the only variable is obtained by the curve fitting method. The formula along with the model can be used to automate the algorithms for simplifying river basin networks.