Satellite-based assessment of hailstorm-affected potato crop for insurance purpose

Natural Hazards - This paper aims to identify indicators of community preparedness for disasters and apply these indicators to a critical case study context, namely the local communities in two...     

Methane flux dynamics in relation to methanogenic and methanotrophic populations in the soil of Indian Sundarban mangroves

The dynamics of methane (CH₄) flux in relation to populations of methanogenic and methanotrophic bacteria was studied under the different biophysical conditions of the Indian Sundarban mangrove ecosystem. Soil depth profile analysis (up to 60 cm) in the lower littoral zone (LLZ) revealed that a methanogenic population of 6.45 ± 0.19 × 10⁴ cells/g dry weight (dry wt) of soil accounted for a CH₄ production rate of 6.23 ± 3.53 × 10³ µmol m^?2 day^?1, whereas in the surface soil, a methanogenic population of 3.34 ± 0.37 × 10⁴ cells/g dry wt of soil accounted for a CH₄ production rate of 31.6 ± 0.57 µmol m^?2 day^?1. The CH₄ oxidation rate at 60 cm depth in the LLZ was 24.42 ± 1.28 µmol m^?2 day^?1, with an average methanotrophic population of 1.33 ± 0.43 × 10⁴ cells/g dry wt of soil, whereas in the surface soil, the oxidation rate and average population were 3.38 ± 1.43 × 10³ µmol m^?2 day^?1 and 12.80 ± 2.54 × 10⁴ cells/g dry wt of soil, respectively. A similar soil profile in terms of CH₄ dynamics and the populations of methanogenic and methanotrophic bacteria was found in the mid‐littoral and upper littoral zones of the studied area. The results demonstrate that most of the produced CH₄ (approximately 60%) was oxidized by methanotrophic bacteria present in the soil, thus revealing their principal role in regulating the CH₄ flux from this unique ecosystem.     

An interactive multi-objective optimization framework for groundwater inverse modeling

The groundwater inverse problem of estimating heterogeneous groundwater model parameters (hydraulic conductivity in this case) given measurements of aquifer response (such as hydraulic heads) is known to be an ill-posed problem, with multiple parameter values giving similar fits to the aquifer response measurements. This problem is further exacerbated due to the lack of extensive data, typical of most real-world problems. In such cases, it is desirable to incorporate expert knowledge in the estimation process to generate more reasonable estimates. This work presents a novel interactive framework, called the ‘Interactive Multi-Objective Genetic Algorithm’ (IMOGA), to solve the groundwater inverse problem considering different sources of quantitative data as well as qualitative expert knowledge about the site. The IMOGA is unique in that it looks at groundwater model calibration as a multi-objective problem consisting of quantitative objectives – calibration error and regularization – and a ‘qualitative’ objective based on the preference of the geological expert for different spatial characteristics of the conductivity field. All these objectives are then included within a multi-objective genetic algorithm to find multiple solutions that represent the best combination of all quantitative and qualitative objectives. A hypothetical aquifer case-study (based on the test case presented by Freyberg [Freyberg DL. An exercise in ground-water model calibration and prediction. Ground Water 1988;26(3)], for which the ‘true’ parameter values are known, is used as a test case to demonstrate the applicability of this method. It is shown that using automated calibration techniques without using expert interaction leads to parameter values that are not consistent with site-knowledge. Adding expert interaction is shown to not only improve the plausibility of the estimated conductivity fields but also the predictive accuracy of the calibrated model.     

Model Averaging Techniques for Quantifying Conceptual Model Uncertainty

In recent years a growing understanding has emerged regarding the need to expand the modeling paradigm to include conceptual model uncertainty for groundwater models. Conceptual model uncertainty is typically addressed by formulating alternative model conceptualizations and assessing their relative likelihoods using statistical model averaging approaches. Several model averaging techniques and likelihood measures have been proposed in the recent literature for this purpose with two broad categories—Monte Carlo-based techniques such as Generalized Likelihood Uncertainty Estimation or GLUE (Beven and Binley 1992) and criterion-based techniques that use metrics such as the Bayesian and Kashyap Information Criteria (e.g., the Maximum Likelihood Bayesian Model Averaging or MLBMA approach proposed by Neuman 2003) and Akaike Information Criterion-based model averaging (AICMA) (Poeter and Anderson 2005). These different techniques can often lead to significantly different relative model weights and ranks because of differences in the underlying statistical assumptions about the nature of model uncertainty. This paper provides a comparative assessment of the four model averaging techniques (GLUE, MLBMA with KIC, MLBMA with BIC, and AIC-based model averaging) mentioned above for the purpose of quantifying the impacts of model uncertainty on groundwater model predictions. Pros and cons of each model averaging technique are examined from a practitioner's perspective using two groundwater modeling case studies. Recommendations are provided regarding the use of these techniques in groundwater modeling practice.     

Incorporating subjective and stochastic uncertainty in an interactive multi-objective groundwater calibration framework

The interactive multi-objective genetic algorithm (IMOGA) combines traditional optimization with an interactive framework that considers the subjective knowledge of hydro-geological experts in addition to quantitative calibration measures such as calibration errors and regularization to solve the groundwater inverse problem. The IMOGA is inherently a deterministic framework and identifies multiple large-scale parameter fields (typically head and transmissivity data are used to identify transmissivity fields). These large-scale parameter fields represent the optimal trade-offs between the different criteria (quantitative and qualitative) used in the IMOGA. This paper further extends the IMOGA to incorporate uncertainty both in the large-scale trends as well as the small-scale variability (which can not be resolved using the field data) in the parameter fields. The different parameter fields identified by the IMOGA represent the uncertainty in large-scale trends, and this uncertainty is modeled using a Bayesian approach where calibration error, regularization, and the expert’s subjective preference are combined to compute a likelihood metric for each parameter field. Small-scale (stochastic) variability is modeled using a geostatistical approach and added onto the large-scale trends identified by the IMOGA. This approach is applied to the Waste Isolation Pilot Plant (WIPP) case-study. Results, with and without expert interaction, are analyzed and the impact that expert judgment has on predictive uncertainty at the WIPP site is discussed. It is shown that for this case, expert interaction leads to more conservative solutions as the expert compensates for some of the lack of data and modeling approximations introduced in the formulation of the problem.     

Stability analysis of rock slopes along Gangadarshan,Pauri, Garhwal,Uttarakhand

The rock mass rating (RMR) and slope mass rating (SMR) has been carried out to classify the slope in terms of slope instability. To understand the RMR and SMR various geostructural, geomorphologic and hydrological parameters of the slopes were measured and analyzed. 32 rock slopes/rock cum debris slopes were identified in the study area. The present RMR and SMR study is an outcome of extensive field study along a stretch of about 10 km on road leading from Srinagar to Pauriarea along Alaknanda valley. The technique followed incorporates the relation between discontinuities and slope along with rock mass rating (RMR) and slope mass rating (SMR). The analysis of the 32 studied slopes shows that in the Gangadarshan area out of six rock slope facets, two falls in class II (stable) and four in class IV (unstable). It is significant to note that the slope facets coming under class IV are comprised of active landslide portions. While the slopes under class II show minor failure or old landslide debris.     

Easy to Use Empirical Correlations for Liquefaction and No Liquefaction Conditions

Considerable damages during an earthquake (EQ) are the consequence of in situ soil losing its shear strength which is popularly known as liquefaction. A number of methodologies are available to quantify the safety of a site against liquefaction occurrence. Widely accepted recent methodologies follow iterative process making it cumbersome for the field engineer. In the present work, empirical correlations are proposed in accordance with widely accepted methodology, analysing the effect of various parameters such as overburden pressure, fines content (FC), factor of safety (FOS) etc. These proposed correlations are easy to use for the designers and the field engineers to determine the liquefaction potential of a site. Considering data from 207 global sites, proposed correlations are validated by comparing with standard methodology. Three different graphical validations are presented supporting that the results based on the proposed correlations are closely matching with the standard methodology. In case a site is found susceptible to liquefaction, so far no correlations are available to determine the shear strength required to be achieved after ground improvement which will ensure no liquefaction during future EQ. Proposed correlations in this work can also be used easily to determine improved shear strength required for a known FOS, FC and EQ magnitude (M) from ground improvement. Two flowcharts explaining the use of proposed correlations to determine FOS of a site and improvement shear strength required for a liquefied site from ground improvement respectively are developed in this work. Based on the second flowchart, determination of shear strength required from ground improvement are done for 45 random sites out of 207 liquefied sites during worldwide EQ in this work.     

Upper mantle anisotropy beneath northeast India–Asia collision zone from shear-wave splitting analysis

Teleseismic earthquake data recorded by 11 broadband digital seismic stations deployed in the India–Asia collision zone in the eastern extremity of the Himalayan orogen (Tidding Suture) are analyzed to investigate the seismic anisotropy in the upper mantle. Shear-wave splitting parameters (Φ and δt) derived from the analysis of core-refracted SKS phases provide first hand information about seismic anisotropy and deformation in the upper mantle beneath the region. The analysis shows considerable strength of anisotropy (delay time ~0.85–1.9 s) with average ENE–WSW-oriented fast polarization direction (FPD) at most of the stations. The FPD observed at stations close to the Tidding Suture aligns parallel to the strike of local geological faults and orthogonal to absolute plate motion direction of the Indian plate. The average trend of FPD at each station indicates that the anisotropy is primarily originated by lithospheric deformation due to India–Asia collision. The splitting data analyzed at closely spaced stations suggest a shallow source of anisotropy originated in the crust and upper mantle. The observed delay times indicate that the primary source of anisotropy is located in the upper mantle. The shear-wave splitting analysis in the Eastern Himalayan syntaxis (EHS) and surrounding regions suggests complex strain partitioning in the mantle which is accountable for evolution of the EHS and complicated syntaxial tectonics.     

Correction to: Application of analytical hierarchy process (AHP) for flood risk assessment: a case study in Malda district of West Bengal,India

Flow pulsations in two-phase and single-phase near-critical fluids are considered as a possible source of ultra-low-frequency seismo-electromagnetic variations. The conditions for generation and suppression of density wave instability in the crust are analyzed and the surface electromagnetic effect due to streaming potential generation is estimated. The upper limit of amplitude of magnetic field variations due to density wave instability is about 0.1 nT for single-phase supercritical and 1 nT for two-phase flow oscillations in the frequency range \(10^{-4}{-}10^{-2}~\) Hz for the temperature gradients and spatial scales possible during strike slip events. The signal is characterized by a decaying amplitude with typical relaxation time of about several quasi-periods. The possibility of generation of very low-frequency flow pulsations in two-phase fluids via individual bubble evolution and interaction with external acoustic waves is discussed.