Geodetic observation crucial to sea level monitoring

The relative rate of rise of the sea levels measured by a tide gauge is made of a sea and a land component. The first is usually restricted to the global short-term effect of melting icecaps and expansion of water mass due to global temperature change. The second is often limited to the regional long-term effects of glacial isostatic adjustment (GIA). Sometimes, the regional subsidence, due to compaction and ground water withdrawal, is considered. Here we show as this assumption of regional subsidence fails to represent the relative sea level patterns of Sandy Hook, NJ, and The Battery, NY, as well as of Venezia Punta Della Salute, Venezia II, Trieste and Trieste II. The subsidence of the tide gauge instrument may only be addressed by the precise monitoring of the tide gauge vs. a Global Navigation Satellite System (GNSS) antenna, even if the GNSS tracking is only recent and not yet very accurate. The relative sea level records are much more complicated than what is thought.     

Assessment of spatial distribution of contaminants and their levels in soil and water resources of Calabar,Nigeria using geophysical and geological data

The contamination levels of soils and water resources in Calabar, Nigeria have been investigated using resistivity (vertical electrical sounding and electrical resistivity tomography), geochemical analyses of soil and water resources and textural analysis. Sixty randomly sited VES sites were investigated in two seasons while ERT investigations were performed along four profiles. The geochemical investigations were spread across seasons in order to track seasonal changes in physico-chemical parameters: hydrogen ion concentration (pH), electrical conductivity, total dissolved solids, chloride ion (Cl^?), nitrate ion (\( {\text{NO}}_{ 3}^{ - } \)), bicarbonate (\( {\text{HCO}}_{ 3}^{ - } \)), sulphate ion (\( {\text{SO}}_{ 4}^{2 - } \)), calcium ion (Ca²⁺), sodium ion (Na⁺), potassium ion (K⁺) and magnesium ion (Mg²⁺). Additionally, concentrations of ammonium, aluminium and nitrite ions in soils were determined. Results show that ionic concentrations in the sand-dominated soils and water are within permissible limits and baseline standards. The resistivities follow known trends in the area. However, at the central waste disposal site, a localised thin (< 5 m), low resistivity (< 15 Ωm) anomaly suspected to be due to contamination by leachates was observed. Comparatively, the contaminated area is also characterised by marginal increase in ionic concentrations. Strong attenuation capacities of overlying and adjoining clay/lateritic sediments and optimal design of the waste dump site probably reduced the spread of contaminants. The contaminated zone need to be closely monitored so that it does not extend to the aquifers. Hence, all strategies presently being used in managing wastes in Calabar should be sustained.     

A micro–macro investigation of the capillary strengthening effect in wet granular materials

Wet granular materials are three-dimensionally simulated by the discrete element method with water bridges incorporated between particles. The water bridges are simplified as toroidal shapes, and the matric suction is constantly maintained in the material. A comparison with experimental tests in the literature indicates that the toroidal shape approximation may be one of the best choices with high practicability and decent accuracy. Mechanical behaviours of wet granular materials are studied by triaxial tests. Effects of particle size distributions and void ratios are investigated systematically in this study. The hydraulic limit of the pendular state is also discussed. It gives the capillary cohesion function which is not only determined by the degree of saturation but also positively correlated to relative density and particle size polydispersity and inversely proportional to mean particle size. Furthermore, the capillary strengthening effect is also analysed microscopically in aid of the Stress–Force–Fabric relationship, mainly in fabric anisotropy, coordination number and stress transmission pattern, which revealed the micro-mechanisms of the additional effective stress induced by capillary effect.     

GaRiRO: Gradient and residual integrated rank ordering of stations in rainfall monitoring network

This paper presents a new method that integrates gradient and residual values for rank ordering of stations in a monitoring network (GaRiRO). The innovation is derived from the fact that the parameter (dependent variable) gauged through the monitoring network is modelled using independent variables that influence its measured quantity. And the dependent variable exhibit non-stationary spatial gradient with respect to the independent variables, particularly in complex terrain. GaRiRO technique was developed to prioritize the rain gauge stations for optimizing the existing network and selection of the best locations for relocation or installation of gauges. Although initially aimed to assist hydrologists with a ranking scheme for rain gauge stations, it can be applied to any environmental, meteorological or hydro-meteorological monitoring network. The new procedure is based on deriving gradient and residual value at each station by modeling the spatial relationship of dependent-independent variable using geographically weighted regression (GWR) technique. For the prospective stations with no record, the gradient value is estimated using GWR model and the residual value is derived from the residual map generated by applying kriging technique on the residual derived at all gauged locations. The method combines the decision factor with analytical strength of GIS for prioritizing the stations which results in limited number of trials for installation or relocation of gauges to yield optimized network configuration.     

Towards a Digital Earth: using archetypes to enable knowledge interoperability within geo-observational sensor systems design

Earth System Science (ESS) observational data are often inadequately semantically enriched by geo-observational information systems to capture the true meaning of the associated data sets. Data models underpinning these information systems are often too rigid in their data representation to allow for the ever-changing and evolving nature of ESS domain concepts. This impoverished approach to observational data representation reduces the ability of multi-disciplinary practitioners to share information in a computable way. Object oriented techniques that are typically employed to model data in a complex domain (with evolving domain concepts) can unnecessarily exclude domain specialists from the design process, invariably leading to a mismatch between the needs of the domain specialists, and how the concepts are modelled. In many cases, an over simplification of the domain concept is captured by the computer scientist. This paper proposes that two-level modelling methodologies developed by health informaticians to tackle problems of domain specific use-case knowledge modelling can be re-used within ESS informatics. A translational approach to enable a two-level modelling process within geo-observational sensor systems design is described. We show how the Open Geospatial Consortium’s (OGC) Observations & Measurements (O&M) standard can act as a pragmatic solution for a stable reference-model (necessary for two-level modelling), and upon which more volatile domain specific concepts can be defined and managed using archetypes. A rudimentary use-case is presented, followed by a worked example showing the implementation methodology and considerations leading to an O&M based, two-level modelling design approach, to realise semantically rich and interoperable Earth System Science based geo-observational sensor systems.     

Using landscape indicators and Analytic Hierarchy Process (AHP) to determine the optimum spatial scale of urban land use patterns in Wuhan,China

Quantifying land use patterns and functions is critical for modeling urban ecological processes, and an emerging challenge is to apply models at multiple spatial scales. Methods of determining the optimum scale of land use patterns are commonly considered using landscape metrics. Landscape metrics are quantitative indicators for analyzing landscape heterogeneity at the landscape level. In this study, due to their widespread use in urban landscape analyses and well-documented effectiveness in quantifying landscape patterns, landscape metrics that represent dominance, shape, fragmentation and connectivity were selected. Five metrics include Patch Density, Contagion, Landscape Shape Index, Aggregation Index and Connectivity. Despite a wide application of landscape metrics for land use studies, the majority mainly focuses on the qualitative analysis of the characteristics of landscape metrics. The previous models are limited in exploring the optimum scale of land use patterns for their lack of quantitation. Therefore, taking the City of Wuhan as an example, the land use unit was treated as a patch, and the landscape pattern metrics at different spatial scales were calculated and compared so as to find the optimum one. Furthermore, a mathematical model of landscape metrics was proposed to quantify the scale effect of urban land use patterns, generating a complementary tool to select the optimum scale. In addition, Analytic Hierarchy Process (AHP) was introduced to determine the respective weights of the chosen landscape metrics in this model. Fractal dimension was ultimately applied to verify the chosen optimum scale of our study region. The results indicated that 60 m is confirmed to be the optimum scale for capturing the spatial variability of land use patterns in this study area.     

A fine-granularity scheduling algorithm for parallel XDraw viewshed analysis

Viewshed analysis is widely used in many terrain applications such as siting problem, path planning problem, and etc. But viewshed computation is very time-consuming, in particular for applications with large-scale terrain data. Parallel computing as a mainstream technique with the tremendous potential has been introduced to enhance the computation performance of viewshed analysis. This paper presents a revised parallel viewshed computation approach based on the existing serial XDraw algorithm in a distributed parallel computing environment. A layered data-dependent model for processing data dependency in the XDraw algorithm is built to explore scheduling strategy so that a fine-granularity scheduling strategy on the process-level and thread-level parallel computing model can be accepted to improve the efficiency of the viewshed computation. And a parallel computing algorithm, XDraw-L, is designed and implemented taken into account this scheduling strategy. The experimental results demonstrate a distinct improvement of computation performance of the XDraw-L algorithm in this paper compared with the coarse-partition algorithm, like XDraw-E which is presented by Song et al. (Earth Sci Inf 10(5):511–523, 2016), and XDraw-B that is the basic algorithm of serial XDraw. Our fine-granularity scheduling algorithm can greatly improve the scheduling performance of the grid cells between the layers within a triangle region.     

Development of an efficient surrogate model based on aquifer dimensions to prevent seawater intrusion in anisotropic coastal aquifers,case study: the Qom aquifer in Iran

Coastal aquifers are usually exposed to saltwater intrusion. Therefore, groundwater extracted from these aquifers should be regulated considering their dimensions and effective parameters. In this paper, optimum discharge from a large number of exploitation wells is evaluated according to variations of width, length, and anisotropy coefficient in the Qom aquifer near the salt lake in central Iran. First, the wells are divided into clusters to decrease the number of decision variables. Then, the location and discharge from each cluster is obtained using SEAWAT and charged system search (CSS) simulation–optimization model with the assumption of three-dimensional variable density flow. The maximum discharge considering various anisotropy rates is computed based on different values of lengths and widths of the aquifer. Finally, an M5-tree model is trained using the obtained samples to derive a linear relationship between input and output data. Based on the results, for various ranges of width and length of an aquifer with impermeable boundaries, different linear equations for optimum discharge are obtained. Also, it was found that for an aquifer with a small width, the critical discharge is a function of the length while the effect of the boundaries is negligible. Sensitivity analysis of the anisotropy coefficient reveals that with increasing the anisotropy rate, thickness and slope of the transition zone decrease and as the maximum discharge increases consequently. However, the sensitivity of the discharge to anisotropy rate is not remarkable. A comparison between the results of this study with those of the analytical method based on sharp interface assumption is carried out. For the critical condition, the best agreement between analytical equation (\(\overline {L} =0.87\overline {W} +0.62\)) and proposed method (\(\overline {L} =0.83\overline {W} - 1.41\)) is achieved for the anisotropic aquifer when the 50% isochlor is assumed as the measure of salt water intrusion.     

Hydrology models approach to estimation of the groundwater recharge: case study in the Bulgarian Danube watershed

The groundwater (GW) makes an important part of a region runoff. GW bodies playing the role of accumulating reservoirs regulate the GW discharge enabling the river flow to have more uniform long-term distribution. Along with other important advantages, the GW offers the users stable water abstraction rate independent from the recharge rate. The GW recharge quantification belongs to the uneasy tasks in the water resource management. Applying the conventional methods needs multiyear observation records of the variation of the groundwater body (GWB) characteristics. The employment of hydrology models avoids that necessity but requires great amount of data related to the soil hydraulic properties, the land topography and cover of the GWB watershed and long-term records of the climatic effects. The paper presents an introduction of the mathematical model CLM3 into the GW recharge estimation problem. It is a complex and advanced model with adequate interpretation of the water-related processes in the soil and on the land surface under atmospheric effects. The input is available from NCEP/NCAR reanalysis atmosphere data and the International Geosphere-Biosphere Program (IGBP) data base. The model is applied to GW recharge assessment of the Bulgarian Danube district for the year 2013. The obtained monthly and yearly total district values and the areal distribution of the infiltration intensity are matched to the existing field observation-based estimates. The study shows that the CLM3 model approach leads to encouraging results. The method comes very useful with GWB lacking regime observation data as well as for GW recharge prognostic assessments under climatic scenarios.