Spectral models for estimation of chlorophyll content, growth and yield of wheat crop

Field experiments were conducted during 1998–99 and 1999–2000 at research farm of the Department of Agricultural Meteorology, CCS Haryana Agricultural University, Hisar. Five wheat cultivars: WH 542, PBW 343, UP 2338, Raj 3765 and Sonak were sown on 25^th November, 10^th and 25^th December with four nitrogen levels viz., no nitrogen. 50, 100 and 150% of recommended dose. Leaf area index, dry matter at anthesis, final dry biomass and grain yield were recorded in all the treatments. Chlorophyll and wax contents of wheat leaves were estimated at different growth stages. Multiband spectral reflectance was measured using hand-held radiometer. Spectral indices such as simple ratio, normalized difference, transformed vegetation index, perpendicular vegetation index and greenness index were computed using the multiband spectral data. Values of all the spectral indices were maximum in 25 November sown crop with maximum dose of nitrogen (180 kg N ha^-1). PBW 343 showed higher values of all the spectral indices in comparison with other cultivars. The spectral indices recorded during maximum leaf area index stage were correlated with crop parameters. Using stepwise regression, empirical models for chlorophyll, leaf area index, dry biomass and yield prediction were developed. The ’R²’ values of these models ranged between 0.87 and 0.95.     

Ground-motion models for average spectral acceleration in a period range: direct and indirect methods

Average spectral acceleration, AvgSA, is defined as the geometric mean of spectral acceleration values over a range of periods and it is a ground motion intensity measure used for structural response prediction. One of its advantages stands on the assumption that its distribution is computable from the available GMPEs for spectral acceleration, GMPE-SA, (called here indirect method) without the need for deriving new specific GMPEs for AvgSA, GMPE-AvgSA, (called here direct method). To what extent this assumption is valid, however, has never been verified. As such, we derived an empirical GMPE-AvgSA based on RESORCE ground motion dataset and we compared its predicted values with those from a GMPE-SA via the indirect approach. As expected, the results show that the indirect approach yields median AvgSA estimates that are identical to those of the direct approach. However, the estimates of AvgSA variance of the two methods are identical only if both the GMPE-SA and their empirical correlation coefficients among different SA ordinates are derived from the same record dataset.     

Application-driven ground motion prediction equation for seismic hazard assessments in non-cratonic moderate-seismicity areas

We present a ground motion prediction equation (GMPE) for probabilistic seismic hazard assessments (PSHA) in low-to-moderate seismicity areas, such as Germany. Starting from the NGA-West2 flat-file (Ancheta et al. in Earthquake Spectra 30:989–1005, 2014), we develop a model tailored to the hazard application in terms of data selection and implemented functional form. In light of such hazard application, the GMPE is derived for hypocentral distance (along with the Joyner-Boore one), selecting recordings at sites with vs30 ≥ 360 m/s, distances within 300 km, and magnitudes in the range 3 to 8 (being 7.4 the maximum magnitude for the PSHA in the target area). Moreover, the complexity of the considered functional form is reflecting the availability of information in the target area. The median predictions are compared with those from the NGA-West2 models and with one recent European model, using the Sammon’s map constructed for different scenarios. Despite the simplification in the functional form, the assessed epistemic uncertainty in the GMPE median is of the order of those affecting the NGA-West2 models for the magnitude range of interest of the hazard application. On the other hand, the simplification of the functional form led to an increment of the apparent aleatory variability. In conclusion, the GMPE developed in this study is tailored to the needs for applications in low-to-moderate seismic areas and for short return periods (e.g., 475 years); its application in studies where the hazard is involving magnitudes above 7.4 and for long return periods is not advised.     

Longitudinal profiling and elevation-relief analysis of the Indus

The Indus basin—one of the largest fluvial-controlled landscapes of the world, provides a major agro-economic resource base while showcasing unique morphometry along its course. However, despite its large socio-economic relevance in South Asia, a distinct account of morphometric variations down its course still remains elusive. Here, for the first time a quantitative demarcation of the Indus basin into—upper, middle, and lower basin is proposed based on analyses of critical morphometric parameters (viz. gradient/river length ratio, elevation-relief ratio, channel width, sinuosity, and slope). Geostatistical and hydrological operations performed on digital elevation models, suggest that the highest and lowest relief sectors are tectonically more stable than the middle relief sector, inferred from a convex hypsometric curve. Elevation-relief ratio for the basin indicates tectonic stability with ~?31% of remnant rock still in place. Cross-sectional transects also demonstrate anomalous patterns that deviate from predictive characteristics of youthful, mature, and senile stages of river development. All parameters are spatially coalesced to provide a first-ever holistic morphometric account of the Indus basin while describing fine-scale planform variations of the spectacular dynamics of this enormous river basin.     

Partially non-ergodic region specific GMPE for Europe and Middle-East

The ergodic assumption considers the time sampling of ground shaking generated in a given region by successive earthquakes as equivalent to a spatial sampling of observed ground motion across different regions. In such cases the estimated aleatory variability in source, propagation, and site seismic processes in ground motion prediction equations (GMPEs) is usually larger than with a non-ergodic approach. With the recently published datasets such as RESORCE for Europe and Middle-East regions, and exploiting algorithms like the non-linear mixed effects regression it became possible to introduce statistically well-constrained regional adjustments to a GMPE, thus ‘partially’ mitigating the impact of the assumption on regional ergodicity. In this study, we quantify the regional differences in the apparent attenuation of high frequency ground motion with distance and in linear site amplification with V_s30, between Italy, Turkey, and rest of the Europe-Middle-East region. With respect to a GMPE without regional adjustments, we obtain up to 10 % reduction in the aleatory variability σ, primarily contributed by a 20 % reduction in the between-station variability. The reduced aleatory variability is translated into an epistemic uncertainty, i.e. a standard error on the regional adjustments which can be accounted for in the hazard assessment through logic-tree branches properly weighted. Furthermore, the between-event variability is reduced by up to 30 % by disregarding in regression the events with empirically estimated moment magnitude. Therefore, we conclude that a further refinement of the aleatory variability could be achieved by choosing a combination of proxies for the site response, and through the homogenization of the magnitude scales across regions.     

The terrace like feature in the mid-continental slope region off Trivandrum and a plausible model for India–Madagascar juxtaposition in immediate pre-drift scenario

Bathymetry of the southwestern continental margin of India reveals the presence of an anomalous terrace like feature in the mid-continental slope region off Trivandrum. The genesis of this terrace of large areal extent ( 9000 sq. km.) is yet to be established. Based on exercises with several existing paleogeographic reconstruction models and updated compilation of identified offshore tectonic elements, this study attempts to identify a plausible model of India–Madagascar juxtaposition in immediate pre-drift scenario, which provides idea about genesis of this terrace. It is inferred that the terrace off Trivandrum and an anomalous bathymetric notch located in the northern Madagascar Ridge are conjugate features related to India–Madagascar separation and the rifted and sheared segments of the pre-drift plate boundary have shaped their outlines. The drifting of India from Madagascar is suggested to have commenced at about 86.5 Ma.     

A regionally adaptable ground-motion model for fourier amplitude spectra of shallow crustal earthquakes in Europe

Bulletin of Earthquake Engineering - Typical seismic ground-motion models predict the response spectral ordinates (GMM-SA), which are the damped responses of a suite of single-degree-of-freedom...     

Application of machine learning techniques in groundwater potential mapping along the west coast of India

ABSTRACT

Groundwater potential mapping (GWPM) in the coastal zone is crucial for the planning and development of society and the environment. The current study is aimed to map the groundwater potential zones of Sindhudurg coastal stretch on the west coast of India, using three machine learning models: random forest (RF), boosted regression tree (BRT), and the ensemble of RF and support vector machine (SVM). In order to achieve the objective, 15 groundwater influencing factors including elevation, slope, aspect, slope length (LS), profile curvature, plan curvature, topographical wetness index (TWI), distance from streams, distance from lineaments, lithology, geomorphology, soil, land use, normalized difference vegetation index (NDVI), and rainfall were considered for inter-thematic correlations and overlaid with spring and well occurrences in a spatial database. A total of 165 spring and well locations were identified, which had been divided into two classes: training and validation, at the ratio of 70:30, respectively. The RF, BRT, and RF-SVM ensemble models have been applied to delineate the groundwater potential zones and categorized into five classes, namely very high, high, moderate, low, and very low. RF, BRT, and ensemble model results showed that 33.3%, 35.6%, and 36.8% of the research area had a very high groundwater potential zone. These models were validated with area under the receiver operating characteristics (AUROC) curve. The accuracy of RF (94%) and hybrid model (93.4%) was more efficient than BRT (89.8%) model. In order to further evaluate and validate, four different sites were subsequently chosen, and we obtained similar results, ensuring the validity of the applied models. Additionally, ground-penetrating radar (GPR) technique was applied to predict the groundwater table and validated by measured wells. The mean difference between measured and GPR predicted groundwater table was 14 cm, which reflected the importance of GPR to guide the location of new wells in the study region. The outcomes of the study will help the decision-makers, government agencies, and private sectors for sustainable planning of groundwater in the area. Overall, the present study provides a comprehensive high-precision machine learning and GPR-based groundwater potential mapping.     

Relationship of wheat grain yield with spectral indices

An experiment was conducted during 1996–97 and 1997–98 to study spectral indices and their relationships with grain yield of wheat. Variations of ratio vegetation index (RVI), normalized differences vegetation index (NDVI). difference vegetation index (DVI), transformed vegetation index (TVI), perpendicular vegetation index (PVI) and greenness vegetation index (GVI) have been studied at anthesis stage under different moisture and nitrogen levels. Spectral indices were correlated with crop parameters and it was found that GVI was the best index for yield estimation (r = 0.91 ).