Adaptive state estimation of groundwater contaminant boundary input flux in a 2-dimensional aquifer

In many circumstances involving heat and mass transfer issues,it is considered impractical to measure the input flux and the resulting state distribution in the domain.Therefore,the need to develop techniques to provide solutions for such problems and estimate the inverse mass flux becomes imperative.Adaptive state estimator(ASE)is increasingly becoming a popular inverse estimation technique which resolves inverse problems by incorporating the semi-Markovian concept into a Bayesian estimation technique,thereby developing an inverse input and state estimator consisting of a bank of parallel adaptively weighted Kalman filters.The ASE is particularly designed for a system that encompasses independent unknowns and/or random switching of input and measurement biases.The present study describes the scheme to estimate the groundwater input contaminant flux and its transient distribution in a conjectural two-dimensional aquifer by means of ASE,which in particular is because of its unique ability to efficiently handle the process noise giving an estimation of keeping the relative error range within 10%in 2-dimensional problems.Numerical simulation results show that the proposed estimator presents decent estimation performance for both smoothly and abruptly varying input flux scenarios.Results also show that ASE enjoys a better estimation performance than its competitor,Recursive Least Square Estimator(RLSE)due to its larger error tolerance in greater process noise regimes.ASE's inherent deficiency of being slower than the RLSE,resulting from the complexity of algorithm,was also noticed.The chosen input scenarios are tested to calculate the effect of input area and both estimators show improved results with an increase in input flux area especially as sensors are moved closer to the assumed input location.     

Spatial–temporal analysis of the shoreline change rate using automatic computation and geospatial tools along the Tetouan coast in Morocco

Natural Hazards - Analyzing and understanding coastline variability and dynamics are important for scientists and policy-makers. This study investigates the long-term process of shoreline change...     

On a damaging earthquake-induced landslide in the Algerian Alps: the March 20, 2006 Laâlam landslide (Babors chain,northeast Algeria), triggered by the Kherrata earthquake (<Emphasis Type="Italic">M</Emphasis><Subscript>w</Subscript> = 5.3)

On March 20, 2006, an earthquake (M _w = 5.3; SED) struck the mountainous region of the Babors chain (Wilaya of Bejaia, northeast Algeria). The seismic epicenter was located near the Kherrata village. This earthquake was felt on a large area of the northeastern part of Algeria. It reached an intensity of VII (EMS scale) at the Laalam village, situated at about 20 km northeast of Kherrata. Here, many old and recent houses were damaged or collapsed totally, four people died and 68 were injured. Field investigations revealed that these casualties were caused by a landslide triggered by the earthquake. Many fissures were visible on ground throughout the site. They were generated by both sliding and settling phenomena. The Laalam site is prone to landslide, as revealed by some evidences on old instabilities. This is due to two main factors: local geomorphology and geology. These factors intervene synchronously for reducing the slope instability at the Laalam village. The March 20, 2006 Kherrata earthquake was the trigger that released the Laalam landslide.     

The impact of salt diapirs on the quality of carbonate karst waters,Bastak, Iran

The Gavbast karstic aquifer located in southern Iran is in direct contact with an exposed salt diapir. To assess the influence of the diapir on the quality of groundwater in the karstic aquifer, electrical conductivity, total dissolved solids, flow rate, temperature and major ion concentrations were measured at 57 sampling sites, including springs, surface waters and wells. A conceptual model of groundwater flow is proposed for the Gavbast karstic aquifer based on the geological setting, water budget, local base of erosion, and hydrochemistry of the sampling sites. The model suggests two subbasins in the Gavbast Anticline draining into two distinct discharging alluvial sections. Unexpectedly, groundwater discharging from the carbonate Gavbast aquifer is saline or brackish and water is of chloride type. The study indicates that the source of salinity of the Gavbast aquifers is infiltration of surface diapir-derived brine into the aquifer. The contribution of the diapir brine in the Gavbast karst aquifer is calculated about 4 L/s, using chloride mass balance. Construction of salt basins to evaporate brine discharging from the diapir springs is proposed to reduce the salinity of karst water. A row of strategically placed wells in the Gavbast karst aquifer would potentially exploit large volumes of fresh groundwater before it is contaminated by the salt. Such low-cost remediation should allow the agricultural exploitation of 40 km² of currently barren land.     

Statistical analysis of stress transmission in wet granular materials

The micromechanics of wet granular materials encompasses complex microstructural and capillary interconnects that can be readily described through a formal derivation of stress transmission in such a 3‐phase medium. In the quest for defining an appropriate stress measure, the stress tensor expression that results from homogenization [Duriez et al. J Mech Phys Solids 99 (2017): 495‐511] of such a medium provides theoretical insights necessary to extract useful information on the relationship between capillary effects and microforce interactions via several small‐scale parameters whose evaluation can be challenging. Using instead a statistical approach where microvariable distributions are described by probability density functions, the current study provides simple estimates of stress components in terms of only a few tractable microvariables such as coordination number and fabric anisotropy. In particular, the latter recognizes details of contacts such as force interactions being either mechanical or capillary, including interactions with and without mechanical contact. The developed expressions are in a good agreement with discrete element method simulation results of the triaxial loading of a wet granular assembly, notably for hydrostatic (mean) pressure. A new set of dimensionless groups is also identified to characterize the significance of mechanical and capillary physics, which facilitates a better understanding of the contribution of dominating elements to stress, while also providing the opportunity to incorporate important capillary effects in micromechanically based constitutive formulations.     

Palaeoecological,sedimentological and stratigraphical insights into microbially induced sedimentary structures of the lower Cambrian successions of Iran

Micro-organisms producing microbially induced sedimentary structures, particularly epibenthic cyanobacteria, are not facies-dependent and could flourish in any environment if appropriate ecological conditions were provided. Hence, the changes in environmental parameters are the controlling factors on ecological tolerance of the producers. This study on the lower Cambrian successions of the Lalun Formation in Central Iran shows that paralic environments reacted differently to changes in parameters such as river and tide energy, palaeo-topography, the rate of sediment supply and fluctuations in sea-level, even though all were characterized by sandy substrates suitable for the development of microbially induced sedimentary structures. Therefore, the abundance and preservation of microbially induced sedimentary structures varied in the different paralic environments. From a sequence stratigraphic viewpoint, this study demonstrates that erosional discontinuities lacked the conditions required for the substrate stabilization by microbial communities. The distribution, size and type of microbially induced sedimentary structures within high frequency cycles generally follow the trends of changes in vertical facies stacking patterns. Within systems tracts, the pattern, morphological diversity and size of microbially induced sedimentary structures are not dependent on the type of systems tract, but on the type of depositional system developed such as delta, incised valley, coastal plain, estuaries and shoreline to shelf systems. Generally, estuarine and peritidal carbonates record an increase in the development of mat colonization during the transgressive systems tract, owing to decreased sedimentation rate as well as extended shallow water habitats. In contrast, the existence of microbially induced sedimentary structures depends on the pattern of shoreline shift in depositional systems developed during the highstand systems tract, such as open coast tidal flat and delta environments. If a shoreline regression was continuous (depositional trend and stacking pattern are a set of high frequency cycles), a greater increase in the aggradational component than the progradational component would cause intensified destructive processes hindering the development of microbial communities.     

Role of early warning systems for sustainable agriculture in Iran

Drought is a complex phenomenon in meteorology and can affect agriculture. Its impacts vary greatly since they depend not only on the magnitude, timing, duration, and frequency of rainfall deficits but also on the differing responses of various plants to water stress. The essence of good drought management is to use this range of responses to the best advantage. Iran is one of the world’s largest and most productive suppliers of food and fiber. The objective of this study was, therefore, to gather and analyze standardized information on the Role of Early Warning Systems for Sustainable Agriculture for cereals and leguminous and industrial crops in Iran environmental zones. Annual average rainfall (mm year^?1) and ET_O (mm year^?1) are 76.56 and 3001, respectively, in stations with very dry climate; 195.41 and 2249, respectively, in stations with dry climate; 343.9 and 1351, respectively, in stations with semi-dry climate; 583.8 and 1153, respectively, in stations with semi-humid climate; and 1272 and 949, respectively, in stations with humid climate. The maximum and minimum of annual average rainfall happened in Rasht (1337 mm year^?1) and Zabol (57 mm year^?1) stations, and the maximum and minimum for annual average ET_O happened in Chabahar (3909.15 mm year^?1) and Anzali harbor (890.6 mm year^?1), respectively. Therefore, 13.63 % of stations have suitable conditions for crop productions and 86.37 % are in critical conditions.     

On regularized time varying gravity field models based on grace data and their comparison with hydrological models

Determination of spherical harmonic coefficients of the Earth’s gravity field is often an ill-posed problem and leads to solving an ill-conditioned system of equations. Inversion of such a system is critical, as small errors of data will yield large variations in the result. Regularization is a method to solve such an unstable system of equations. In this study, direct methods of Tikhonov, truncated and damped singular value decomposition and iterative methods of ν, algebraic reconstruction technique, range restricted generalized minimum residual and conjugate gradient are used to solve the normal equations constructed based on range rate data of the gravity field and climate experiment (GRACE) for specific periods. Numerical studies show that the Tikhonov regularization and damped singular value decomposition methods for which the regularization parameter is estimated using quasioptimal criterion deliver the smoothest solutions. Each regularized solution is compared to the global land data assimilation system (GLDAS) hydrological model. The Tikhonov regularization with L-curve delivers a solution with high correlation with this model and a relatively small standard deviation over oceans. Among iterative methods, conjugate gradient is the most suited one for the same reasons and it has the shortest computation time.