Factors driving riverbed scouring and sedimentation in the Bayangaole to Toudaoguai reaches of the Upper Yellow River

The Inner Mongolia reaches of the Yellow River face problems of severe sedimentation caused by a variety of complex factors. The sedimentation process in those reaches has been characterized using the sediment balance method, and the key factors affecting the process have been analyzed using the correlation analysis method. The results show that during the period 1952–2012 the Bayangaole (Bayan Gol) to Toudaoguai reaches in Inner Mongolia have undergone successive processes of accumulative sedimentation, then relative balance, and then accumulative sedimentation once again. The total annual sedimentation is 12.0341×10⁸ m³, of which accumulations from July to October account for 95.1% and the reaches from Sanhuhekou to Toudaoguai account for 98.5%. The main factor affecting scouring and sedimentation of the Bayangaole to Sanhuhekou reaches is the combined water and sediment condition. The critical conditions for equilibrium are an incoming sediment coefficient < 0.007 kg·s·m^–6 and a flow discharge > 700 m³·s^–1. The main factor affecting scouring and sedimentation of the Sanhuhekou to Toudaoguai reaches is the incoming sediment from the tributaries on the south bank and the combined water and sediment condition of the main stream. The critical conditions of the main stream for maintaining equilibrium status are a flow discharge of the main stream exceeding 800 m³·s^–1 and a comprehensive incoming sediment coefficient < 0.005 kg·s·m^–6. The incoming sediment from the tributaries has little impact on the main stream when the annual sediment load is less than 0.1×10⁸ t. The incoming sediment coefficient of the main stream and the incoming sediment from the tributaries both play vital roles in the riverbed evolution of the Inner Mongolia reaches, but the latter contributes the most.     

Natural background levels and threshold values for groundwater in fluvial Pleistocene and Tertiary marine aquifers in Flanders,Belgium

Aquifers from the same typology can have strongly different groundwater chemistry. Deducing the groundwater quality of less well-characterized aquifers from well-documented aquifers belonging to the same typology should be done with great reserve, and can only be considered as a preliminary approach. In the EU’s 6th FP BRIDGE project “Background cRiteria for the IDentification of Groundwater thrEsholds”, a methodology for the derivation of threshold values (TV) for groundwater bodies is proposed. This methodology is tested on four aquifers in Flanders of the sand and gravel typology. The methodology works well for all but the Ledo-Paniselian aquifer, where the subdivision into a fresh and saline part is disproved, as a gradual natural transition from fresh to saline conditions in the aquifer is observed. The 90 percentile is proposed as natural background level (NBL) for the unconfined Pleistocene deposits, ascribing the outliers to possible influence of pollution. For the Tertiary aquifers, high values for different parameters have a natural origin and the 97.7 percentile is preferred as NBL. The methodology leads to high TVs for parameters presenting low NBL, when compared to the standard used as a reference. This would allow for substantial anthropogenic inputs of these parameters.     

New classes of spectral densities for lattice processes and random fields built from simple univariate margins

Quasi arithmetic and Archimedean functionals are used to build new classes of spectral densities for processes defined on any d-dimensional lattice \mathbbZ^d{\mathbb{Z}^d} and random fields defined on the d-dimensional Euclidean space \mathbbR^d{\mathbb{R}^d}, given simple margins. We discuss the mathematical features of the proposed constructions, and show rigorously as well as through examples, that these new classes of spectra generalize celebrated classes introduced in the literature. Additionally, we obtain permissible spectral densities as linear combinations of quasi arithmetic or Archimedean functionals, whose associated correlation functions may attain negative values or oscillate between positive and negative ones. We finally show that these new classes of spectral densities can be used for nonseparable processes that are not necessarily diagonally symmetric.     

Patterns of carbon sequestration in forests of western ghats and study of applicability of remote sensing in generating carbon credits through afforestation/reforestation

Satellite remote sensing is a proven tool for mapping landuse patterns and estimating vegetation biomass/carbon. Present study aims at estimating the potential of forests of Radhanagari WLS (Western Ghats, India) to sequester the atmospheric carbon-di-oxide, using ground based observations coupled with satellite remote sensing. The study area was stratified for dominant forest types based on the structure and composition of vegetation and elevation variations. Permanent sample plots were laid down in these homogeneous vegetation strata (HVS) to make different observations during time 1 and time 2. Carbon sequestration by plantations was also studied and compared with natural forests. Species and area-specific biomass equations were used for estimating carbon pool and sequestration. Among natural forests ‘mixed moist deciduous’ forests exhibited highest sequestration rate (8%), whereas, plantation as obvious had a comparatively higher sequestration rate than natural forests (20.27%). Total carbon sequestration by forests of the Radhanagari WLS between 2004 and 2006 is 78742.09 tons. Eligible land for reforestation activity under clean development mechanism (CDM) of Kyoto Protocol was identified using satellite remote sensing using 1989 and 2005 datasets and it was observed that the potential land that can be used for reforestation activity is 10080 ha.     

From global to local: Testing the potential of cross-scaling in global data sets

The present study investigates the potential of readily available and easily accessible global data sets to understand regional/local level interactions in wetland systems. The biogeographical zones of India were used a base-frame to select three sites. The study well fits the interests of National Wetland Committee of India to investigate and document fundamental information on wetland extent/distribution. The national partnership with SACON represents this interest. SACON commenced the inland wetland inventory module at national scale using geospatial data, although the provincial scale analysis is underway. In addition, the global irrigated area mapping (GIAM-IWMI) project generated multi-scalar spatial outputs for irrigated/rain-fed areas. With the existing information base, a multi-level geospatial analysis using Arc GIS algorithmic modelling was used to derive comprehensive appraisal of wetland systems complementing the data from GIAM and SACON. It was observed that the overlap between the two layers was 58 percent for Gujarat and 10 percent in Tamil Nadu. In Krishna basin the wetland’s cover 1.04 million hectare excluding the rice agro-ecosystem. The difference in the biogeography of the case sites governs the gradient of information derived from both data layers. Additionally, the global lakes and wetlands database (GLWD) database added thematic information on coastal wetlands. In summary we describe the cross-scaling the global data layers to compliment the regional/national level monitoring assignments.     

Simultaneous estimation of cross-validation errors in least squares collocation applied for statistical testing and evaluation of the noise variance components

The cross-validation technique is a popular method to assess and improve the quality of prediction by least squares collocation (LSC). We present a formula for direct estimation of the vector of cross-validation errors (CVEs) in LSC which is much faster than element-wise CVE computation. We show that a quadratic form of CVEs follows Chi-squared distribution. Furthermore, a posteriori noise variance factor is derived by the quadratic form of CVEs. In order to detect blunders in the observations, estimated standardized CVE is proposed as the test statistic which can be applied when noise variances are known or unknown. We use LSC together with the methods proposed in this research for interpolation of crustal subsidence in the northern coast of the Gulf of Mexico. The results show that after detection and removing outliers, the root mean square (RMS) of CVEs and estimated noise standard deviation are reduced about 51 and 59%, respectively. In addition, RMS of LSC prediction error at data points and RMS of estimated noise of observations are decreased by 39 and 67%, respectively. However, RMS of LSC prediction error on a regular grid of interpolation points covering the area is only reduced about 4% which is a consequence of sparse distribution of data points for this case study. The influence of gross errors on LSC prediction results is also investigated by lower cutoff CVEs. It is indicated that after elimination of outliers, RMS of this type of errors is also reduced by 19.5% for a 5 km radius of vicinity. We propose a method using standardized CVEs for classification of dataset into three groups with presumed different noise variances. The noise variance components for each of the groups are estimated using restricted maximum-likelihood method via Fisher scoring technique. Finally, LSC assessment measures were computed for the estimated heterogeneous noise variance model and compared with those of the homogeneous model. The advantage of the proposed method is the reduction in estimated noise levels for those groups with the fewer number of noisy data points.     

The mean value concept in mono-linear regression of multi-variables and its application to trace studies in geosciences

The "mean value concept" in a mono-linear regression of multi-variables is clarified.Its applications to reconstruction of the past 90-year salinity of the sea surface water in Xisha Islands and to tracing the past 80 ka paleo-geomagnetic events from the Luochuan loess 10Be record are introduced in detail,which show the significance and the potential of the "mean value concept" in geoscience research.     

Automatic Interpretation of Magnetic Data Using Euler Deconvolution with Nonlinear Background

The voluminous gravity and magnetic data sets demand automatic interpretation techniques like Naudy, Euler and Werner deconvolution. Of these techniques, the Euler deconvolution has become a popular choice because the method assumes no particular geological model. However, the conventional approach to solving Euler equation requires tentative values of the structural index preventing it from being fully automatic and assumes a constant background that can be easily violated if the singular points are close to each other. We propose a possible solution to these problems by simultaneously estimating the source location, depth and structural index assuming nonlinear background. The Euler equation is solved in a nonlinear fashion using the optimization technique like conjugate gradient. This technique is applied to a published synthetic data set where the magnetic anomalies were modeled for a complex assemblage of simple magnetic bodies. The results for close by singular points are superior to those obtained by assuming linear background. We also applied the technique to a magnetic data set collected along the western continental margin of India. The results are in agreement with the regional magnetic interpretation and the bathymetric expressions.     

Evolution and preservation potential of fluvial and transgressive deposits on the Louisiana inner shelf: understanding depositional processes to support coastal management

The barrier-island systems of the Mississippi River Delta plain are currently undergoing some of the highest rates of shoreline retreat in North America (~20 m/year). Effective management of this coastal area requires an understanding of the processes involved in shoreline erosion and measures that can be enacted to reduce loss. The dominant stratigraphy of the delta plain is fluvial mud (silts and clays), delivered in suspension via a series of shallow-water delta lobes that prograded across the shelf throughout the Holocene. Abandonment of a delta lobe through avulsion leads to rapid land subsidence through compaction within the muddy framework. As the deltaic headland subsides below sea level, the marine environment transgresses the bays and wetlands, reworking the available sands into transgressive barrier shorelines. This natural process is further complicated by numerous factors: (1) global sea-level rise; (2) reduced sediment load within the Mississippi River; (3) diversion of the sediment load away from the barrier shorelines to the deep shelf; (4) storm-induced erosion; and (5) human alteration of the littoral process through the construction of hardened shorelines, canals, and other activities. This suite of factors has led to the deterioration of the barrier-island systems that protect interior wetlands and human infrastructure from normal wave activity and periodic storm impact. Interior wetland loss results in an increased tidal prism and inlet cross-sectional areas, and expanding ebb-tidal deltas, which removes sand from the littoral processes through diversion and sequestration. Shoreface erosion of the deltaic headlands does not provide sufficient sand to balance the loss, resulting in thinning and dislocation of the islands. Abatement measures include replenishing lost sediment with similar material, excavated from discrete sandy deposits within the muddy delta plain. These sand bodies were deposited by the same cyclical processes that formed the barrier islands, and understanding these processes is necessary to characterize their location, extent, and resource potential. In this paper we demonstrate the dominant fluvial and marine-transgressive depositional processes that occur on the inner shelf, and identify the preservation and resource potential of fluvio-deltaic deposits for coastal management in Louisiana.