Climatic Indices Influencing the Long-Term Variability of Mediterranean Heat and Water Fluxes: The North Atlantic and Mediterranean Oscillations

Interannual to interdecadal precipitation (P), evaporation (E), water deficit (E-P), and total heat flux have been correlated with North Atlantic Oscillation (NAO) and Mediterranean Oscillation (MO) indices to explore the influence of large-scale atmospheric forcing on the variability of the Mediterranean water and heat budgets. Basin-averaged precipitation decrease from the mid-1960s to the late 1980s clearly corresponds to a switch from a low to a high state of both indices. The variability of E-P is not so well correlated with the atmospheric indices because of the different sensitivity of E and P that leads to correlations of opposite sign in the eastern and western sub-basins. The effectiveness of the NAO and MO indices is quite similar for P and E-P but the regional MO index has turned out to be a more successful indicator of interdecadal evaporation and net heat flux because, from the mid-1970s to the early 1990s, correlation with the NAO index decreases considerably. Because the MO centre remains relatively steady, it influences most of the Mediterranean Sea year round, so it is more suitable for monitoring long-term water and especially heat budget variability.     

Temporal patterns of deforestation and fragmentation in lowland Bolivia: implications for climate change

The lowlands of eastern and northeastern Bolivia are characterized by a transition between the humid evergreen forests of the Amazon Basin and the deciduous thorn-scrub vegetation of the Gran Chaco. Within this landscape lies one of the world’s best preserved areas: the ecoregion known as the Chiquitano dry forest, where deforestation patterns over a 30 year period were analyzed. Results indicate that the area of the natural cover was reduced from 97.21 % before 1976 to 82.10 % in 2008, causing significant change in the landscape, especially in the spatial configuration of forest cover. The density of forest fragments increased from 0.073 patches per 100 ha before 1976 to 0.509 in 2008, with a mean distance between patches of 151 and 210 m over the same period, leading to a considerable reduction in the fragment sizes, from 1,204 ha before 1976 to a mere 54 in 2008. This pattern, observed in forests, does not occur in the savannas because, on one hand the savanna area is much lower compared to that of forests, and on the other because the deforestation process tended to be concentrated within forested areas. Based on the observed patterns, it is possible that in the future the natural landscapes will be substituted principally by anthropic landscapes, if there is no change in the economic and land distribution policies. If this process continues, it will stimulate the expansion of mechanized agriculture and the colonization of new areas, which will lead to further deforestation and landscape fragmentation.     

The Høvsøre Tall Wind-Profile Experiment: A Description of Wind Profile Observations in the Atmospheric Boundary Layer

We present an analysis of data from a nearly 1-year measurement campaign performed at Høvsøre, Denmark, a coastal farmland area where the terrain is flat. Within the easterly sector upstream of the site, the terrain is nearly homogenous. This topography and conditions provide a good basis for the analysis of vertical wind-speed profiles under a wide range of atmospheric stability, turbulence, and forcing conditions. One of the objectives of the campaign was to serve as a benchmark for flow over flat terrain models. The observations consist of combined wind lidar and sonic anemometer measurements at a meteorological mast. The sonic measurements cover the first 100 m and the wind lidar measures above 100 m every 50 m in the vertical. Results of the analysis of observations of the horizontal wind-speed components in the range 10–1200 m and surface turbulence fluxes are illustrated in detail, combined with forcing conditions derived from mesoscale model simulations. Ten different cases are presented. The observed wind profiles approach well the simulated gradient and geostrophic winds close to the simulated boundary-layer height during both barotropic and baroclinic conditions, respectively, except for a low-level jet case, as expected. The simulated winds are also presented for completeness and show good agreement with the measurements, generally underpredicting the turning of the wind in both barotropic and baroclinic cases.     

Estimation of daytime downward longwave radiation under clear and cloudy skies conditions over a sub-humid region

Downward longwave radiation (LW _↓ ) is a relevant variable for meteorological and climatic studies. Good estimates of this term are vitally important in correct determining of the net radiation, which, in turn, modulates the magnitude of the terms in the surface energy budget (e.g., evaporation). In remote sensing applications, the determination of daytime LW_↓ is required for estimation of the net radiation using satellite data. LW_↓ is not directly measured in weather stations and then is estimated using models with surface air temperature and humidity as input. In this paper, we identify the best models to estimate daytime downward longwave radiation from meteorological data in the sub-humid Pampean region. Several well-known models to estimate LW_↓ under clear and cloudy skies were tested. We use downward radiation components and meteorological data registered at Tandil (Argentina) from 2006 to 2010 (840 days). In addition, we propose two multiple linear regression models (MLRM-1 and MLRM-2) to estimate LW_↓ at the surface for all sky conditions. The new equations show better performance than the others models tested with root mean square errors between 12 and 16 W m^?2, bias close to zero and best agreements with measured data (r ²?≥?0.85).     

Artificial neural networks and geostatistical models for housing valuations in urban residential areas

Property valuation studies often use classical statistics techniques. Among these techniques, the Artificial Neural Networks are the most applied, overcoming the inflexibility and the linearity of the hedonic models. Other researchers have used Geostatistics techniques, specifically the Kriging Method, for interpreting spatial-temporal variability and to predict housing unit prices. The innovation of this study is to highlight how the Kriging Method can help to better understand the urban environment, improving the results obtained by classical statistics. This study presents two different methods that share the general objective of extracting information regarding a city’s housing from datasets. The procedures applied are Ordinary Kriging (Geostatistics) and Multi-Layer Perceptron algorithm (Artificial Neural Networks). These methods were used to predict housing unit prices in the municipality of Pozuelo de Alarcon (Madrid). The implementation of both methods provides us with the urban characteristics of the study area and the most significant variables related to price. The main conclusion is that the Ordinary Kriging models and the Neural Networks models, applied to predicting housing unit prices are necessary methodologies to improve the information obtained in classical statistical techniques.

Abbreviations: ANN: Artificial Neural Networks; OK: ordinary Kriging; MLP: multi-layer perceptron     

Models of local governing coalitions: city politics and policy effects in Spanish municipalities

Local governance involves coalitions between public and private actors on policy issues. Actors participating in these coalitions may vary according to the issue in question, even within the same city. Based on a survey carried out among actors from different sectors of the local political community in four Spanish cities, governance networks are analyzed across five different issues: public housing, cultural tourism, urban regeneration, social policy, and citizen participation. Using network analysis and indexes in a comparative examination of 20 policy networks, we show that variations across networks are explained by policy issue content and supra-municipal regulations, regardless of the cities’ political characteristics.     

Inundation extent as a key parameter for assessing the magnitude and return period of flooding events in southern Iceland

Abstract

River flow conditions in many watersheds of Iceland are particularly disturbed during winter by the formation, drifting and accumulation of river ice, whose impact on water encroachment and extent of inundations is not reflected in the discharge records. It is therefore necessary to use river discharge with great caution when assessing the magnitude of past inundations in Iceland, and to give attention to other flood magnitude parameters. A GIS-based methodology is presented that focuses on inundation extent as an alternative parameter for the assessment and ranking of the magnitude of past flooding events in the Ölfusá-Hvítá basin, known as one of the most dangerous flood-prone river complexes in Iceland. Relying ultimately on a macro-scale grid, the method enabled the reconstruction of the extent of inundations, the delineation of the flood plain, and, finally, some estimation of the likelihood of flooding of exposed areas that include marine submergences and river floods for both open water and ice conditions.

Citation Pagneux, E., Gísladóttir, G. & Snorrason, Á. (2010) Inundation extent as a key parameter for assessing the magnitude and return period of flooding events in southern Iceland. Hydrol. Sci. J. 55(5), 704–716.     

Modelling spatio-temporal patterns of sediment yield and connectivity in a semi-arid catchment with the WASA-SED model

Abstract

Rainfall–runoff induced soil erosion causes important environmental degradation by reducing soil fertility and impacting on water availability as a consequence of sediment deposition in surface reservoirs used for water supply, particularly in semi-arid areas. However, erosion models developed on experimental plots cannot be directly applied to estimate sediment yield at the catchment scale, since sediment redistribution is also controlled by the transport conditions along the landscape. In particular, representation of landscape connectivity relating to sediment transfer from upslope areas to the river network is required. In this study, the WASA-SED model is used to assess the spatial and temporal patterns of water and sediment connectivity for a semi-arid meso-scale catchment (933 km²) in Brazil. It is shown how spatial and temporal patterns of sediment connectivity within the catchment change as a function of landscape and event characteristics. This explains the nonlinear catchment response in terms of sediment yield at the outlet.

Citation Medeiros, P. H. A., Güntner, A., Francke, T., Mamede, G. L. & de Araújo, J. C. (2010) Modelling spatio-temporal patterns of sediment yield and connectivity in a semi-arid catchment with the WASA-SED model. Hydrol. Sci. J. 55(4), 636–648.     

Scholte waves on fluid-solid interfaces by means of an integral formulation

The present work shows the propagation of Scholte interface waves at the boundary of a fluid in contact with an elastic solid, for a broad range of solid materials. It has been demonstrated that by an analysis of diffracted waves in a fluid it is possible to infer the mechanical properties of the elastic solid medium, specifically, its propagation velocities. For this purpose, the diffracted wave field of pressures and displacements, due to an initial wave of pressure in the fluid, are expressed using boundary integral representations, which satisfy the equation of motion. The source in the fluid is represented by a Hankel’s function of second kind and zero order. The solution to this wave propagation problem is obtained by means of the Indirect Boundary Element Method, which is equivalent to the well-known Somigliana representation theorem. The validation of the results is carried out by using the Discrete Wave Number Method and the Spectral Element Method. Firstly, we show spectra of pressures that illustrate the behavior of the fluid for each solid material considered, then, we apply the Fast Fourier Transform to show results in time domain. Snapshots to exemplify the emergence of Scholte’s waves are also included.     

Arsenic Control During Aquifer Storage Recovery Cycle Tests in the Floridan Aquifer

Implementation of aquifer storage recovery (ASR) for water resource management in Florida is impeded by arsenic mobilization. Arsenic, released by pyrite oxidation during the recharge phase, sometimes results in groundwater concentrations that exceed the 10 µg/L criterion defined in the Safe Drinking Water Act. ASR was proposed as a major storage component for the Comprehensive Everglades Restoration Plan (CERP), in which excess surface water is stored during the wet season, and then distributed during the dry season for ecosystem restoration. To evaluate ASR system performance for CERP goals, three cycle tests were conducted, with extensive water‐quality monitoring in the Upper Floridan Aquifer (UFA) at the Kissimmee River ASR (KRASR) pilot system. During each cycle test, redox evolution from sub‐oxic to sulfate‐reducing conditions occurs in the UFA storage zone, as indicated by decreasing Fe²⁺/H₂S mass ratios. Arsenic, released by pyrite oxidation during recharge, is sequestered during storage and recovery by co‐precipitation with iron sulfide. Mineral saturation indices indicate that amorphous iron oxide (a sorption surface for arsenic) is stable only during oxic and sub‐oxic conditions of the recharge phase, but iron sulfide (which co‐precipitates arsenic) is stable during the sulfate‐reducing conditions of the storage and recovery phases. Resultant arsenic concentrations in recovered water are below the 10 µg/L regulatory criterion during cycle tests 2 and 3. The arsenic sequestration process is appropriate for other ASR systems that recharge treated surface water into a sulfate‐reducing aquifer.