Streamflow trend analysis by considering autocorrelation structure,long-term persistence,and Hurst coefficient in a semi-arid region of Iran

Due to the substantial decrease of water resources as well as the increase in demand and climate change phenomenon, analyzing the trend of hydrological parameters is of paramount importance. In the present study, investigations were carried out to identify the trends in streamflow at 20 hydrometric stations and 11 rainfall gauging stations located in Karkheh River Basin (KRB), Iran, in monthly, seasonal, and annual time scales during the last 38 years from 1974 to 2011. This study has been conducted using two versions of Mann–Kendall tests, including (i) Mann–Kendall test by considering all the significant autocorrelation structure (MK3) and (ii) Mann–Kendall test by considering LTP and Hurst coefficient (MK4). The results indicate that the KRB streamflow trend (using both test versions) has decreased in all three time scales. There is a significant decreasing trend in 78 and 73 % of the monthly cases using the MK3 and MK4 tests, respectively, while these percentages changed to 80 and 70 % on seasonal and annual time scales, respectively. Investigation of the trend line slope using Theil–Sen’s estimator showed a negative trend in all three time scales. The use of MK4 test instead of the MK3 test has caused a decrease in the significance level of Mann–Kendall Z-statistic values. The results of the precipitation trends indicate both increasing and decreasing trends. Also, the correlation between the area average streamflow and precipitation shows a strong correlation in annual time scale in the KRB.     

Model selection in Bayesian framework to identify the best WorldView-2 based vegetation index in predicting green biomass of salt marshes in the northern Gulf of Mexico

Coastal wetlands are among the most productive ecosystems globally but have experienced dramatic degradation and loss within the past several decades. Vegetation biomass of coastal wetlands is not only the key component of blue carbon storage but also plays an important role in vertical accretion, important for maintaining these habitats under relative sea-level rise. Remote sensing offers a cost-effective approach to study vegetation biomass at a broad spatial scale. We developed statistical models to predict peak aboveground green biomass of Spartina alterniflora and Juncus roemerianus, two dominant species of salt marshes using WorldView-2 satellite imagery at the Grand Bay National Estuarine Research Reserve (NERR) on the Mississippi coast in the northern Gulf of Mexico. The model accounted for nested data structures in the sampled biomass, assimilated uncertainties from data, parameters and model structures, and helped determine the best vegetation index among a variety of commonly-used indices to predict aboveground green biomass. We developed a series of mixed-effects models, which included different combinations of fixed effect(s), random intercept, and random slope(s). The fixed effects were species and one of the 60 vegetation indices derived from a WorldView-2 image obtained on 6 October 2012. The random effect used was site. We implemented the models in a Bayesian framework and selected the best model structure and vegetation index based on minimum posterior predictive loss and deviance information criterion. The results showed that the best vegetation index to predict peak green biomass was the green chlorophyll index derived from the reflectance values of band 8 (near-infrared) and band 3 (green), and its effect on biomass prediction varied among sites. The inclusion of species as a fixed effect improved the model prediction. The study demonstrated the need to account for spatial dependence of data in developing a robust model, and the importance of the second WorldView-2 near-infrared band (860–1040 nm) in predicting aboveground green biomass for the Grand Bay NERR. The analysis using mixed-effects modeling in Bayesian inference which coherently combined field and WorldView-2 data with uncertainties accounted for provides a robust and nondestructive tool for resource managers to monitor the status of coastal wetlands at a high spatial resolution in a timely manner. Through this study, we hope to emphasize the importance of appropriately accounting for nested data structures using mixed-effects models and promote wider application of Bayesian inference to facilitate assimilation of uncertainties in remote sensing applications.     

Structural and metamorphic evolution of the rocks of the Jutogh Group, Chur half-klippe, Himachal Himalayas: A summary and comparison with the Simla area

The rocks of the Jutogh Group in the Himachal Himalayas and their equivalents elsewhere are now considered to represent a several km thick crustal scale ductile shear zone, the so called Main Central Thrust Zone. In this article we present a summary of structural and metamorphic evolution of the Jutogh Group of rocks in the Chur half-klippe and compare our results with those of Naha and Ray (1972) who worked in the adjacent Simla klippe. The deformational history of the Jutogh Group of rocks in the area around the Chur-peak, as deduced from small-scale structures, can be segmented into: (1) an early event giving rise to two sets of very tight to isoclinal and coaxial folds with gentle dip of axial planes and easterly or westerly trend of axes, (2) an event of superimposed progressive ductile shearing during which a plethora of small-scale structures have developed which includes successive generations of strongly non-cylindrical folds, several generations of mylonitic foliation, extensional structures and late-stage small-scale thrusts, and (3) a last stage deformation during which a set of open and upright folds developed, but these are regionally unimportant. The structure in the largest scale (tens of km) can be best described in terms of stacked up thin thrust sheets. Km-scale asymmetric recumbent folds with strongly non-cylindrical hinge lines, developed as a consequence of ductile shearing, are present in one of these thrust sheets. The ductile shearing, large-scale folding and thrusting can be related to the development of the Main Central Thrust Zone. The microstructural relations show that the main phase of regional low-to medium-grade metamorphism (T ≈ 430–600°C andP ≈ 4.5–8.5 kbar) is pre-kinematic with respect to the formation of the Main Central Thrust Zone. Growth zoned garnets with typical bell-shaped Mn profiles and compensating bowl-shaped Fe profiles are compatible with this phase of metamorphism. Some of the larger garnet grains, however, show flat compositional profiles; if they represent homogenization of growth zoning, it would be a possible evidence of a relict high-grade metamorphism. The ductile shearing was accompanied by a low-greenschist facies metamorphism during which mainly chlorite and occasionally biotite porphyroblasts crystallized.     

Deformation style in the Granulite-charnockite province of South India: An example from the Kusulmalai area in Salem district,Tamil Nadu,India

A multiple-deformation sequence is established for different types of gneisses, mafic-paleosomes and banded magnetite quartzites (BMQ) exposed within the area. In gneisses, the basin-shaped map pattern represents the type-i interference structure formed due to the overprinting of F₃ folds with ENE striking axial planes on F₂ folds with axial planes striking NNW. The BMQ band occurring as an enclave within the gneissic country, represents a large scale F₁ fold with relatively smaller scale F₂ folds developed on its limbs. Mafic-paleosomes within the streaky-charnockitic-gneisses exhibit structures formed due to the interference of more than two phases of folding (F₁,F_la,F₂,F₃). It is shown that the deformation plan in these rocks is consistent with the generalized deformation scheme for Granite-greenstone belts. The difference in the map pattern of Granite-greenstone belts and Granulite-charnockite terrains is ascribed to the variance in Theological properties, layerthickness ratios and local displacement directions during different phases of folding. These differences apart, both the Granite-greenstone and Granulite-charnockite provinces in South India are deformed by an early isoclinal folding which is successively overprinted by folding on NNW and ENE striking axial planes.     

On selection and scaling of ground motions for analysis of seismically isolated structures

A broader consensus on the number of ground motions to be used and the method of scaling to be adopted for nonlinear response history analysis (RHA) of structures is yet to be reached. Therefore, in this study, the effects of selection and scaling of ground motions on the response of seismically isolated structures, which are routinely designed using nonlinear RHA, are investigated. For this purpose, isolation systems with a range of properties subjected to bidirectional excitation are considered. Benchmark response of the isolation systems is established using large sets of unscaled ground motions systematically categorized into pulse-like, non-pulse-like, and mixed set of motions. Different subsets of seven to 14 ground motions are selected from these large sets using (a) random selection and (b) selection based on the best match of the shape of the response spectrum of ground motions to the target spectrum. Consequences of weighted scaling (also commonly referred to as amplitude scaling or linear scaling) as well as spectral matching are investigated. The ground motion selection and scaling procedures are evaluated from the viewpoint of their accuracy, efficiency, and consistency in predicting the benchmark response. It is confirmed that seven time histories are sufficient for a reliable prediction of isolation system displacement demands, for all ground motion subsets, selection and scaling procedures, and isolation systems considered. If ground motions are selected based on their best match to the shape of the target response spectrum (which should be preferred over randomly selected motions), weighted scaling should be used if pulse-like motions are considered, either of weighted scaling or spectral matching can be used if non-pulse-like motions are considered, and an average of responses from weighted-scaled and spectrum-matched ground motions should be used for a mixed set of motions. On the other hand, the importance of randomly selected motions in representing inherent variability of response is recognized and it is found that weighted scaling is more appropriate for such motions.     

Precipitable water vapor estimation in India from GPS-derived zenith delays using radiosonde data

One of the most recent applications of global positioning system (GPS) is the estimation of precipitable water vapor (PWV). It requires proper modeling to extract PWV from zenith wet delay (ZWD). The existing global models take no account of latitudinal and seasonal variation of meteorological parameters in the atmosphere. In fact, they ignore the atmospheric conditions at a specific location. Therefore, site-specific PWV models have been developed for five stations spread over the Indian subcontinent, using 3-year (2006–2008) radiosonde data from each of these stations. Furthermore, a similar regional PWV model is also developed for the Indian region. The purpose of the developed site-specific as well as regional model was to convert ZWDs into PWV without using surface meteorological parameters. It has been found that the developed regional and site-specific PWV models show about mm-level accuracy in estimating PWV using derived ZWD from radiosonde as input. The developed site-specific, regional models were also used to extract PWV from GPS-derived ZWD at Bangalore and New Delhi. The accuracy of the developed site-specific and regional model is of the same level. The PWV accuracy obtained with the developed regional model is about 6.28, 6.6 mm in comparison to radiosonde PWV at Bangalore and New Delhi, respectively.     

Evaluating Hyperspectral Imager for the Coastal Ocean (HICO) data for seagrass mapping in Indian River Lagoon,FL

Differentiation between benthic habitats, particularly seagrass and macroalgae, using satellite data is complicated because of water column effects plus the presence of chlorophyll-a in both seagrass and algae that result in similar spectral patterns. Hyperspectral imager for the coastal ocean data over the Indian River Lagoon, Florida, USA, was used to develop two benthic classification models, Slope_RED and Slope_NIR. Their performance was compared with iterative self-organizing data analysis technique and spectral angle mapping classification methods. The slope models provided greater overall accuracies (63–64%) and were able to distinguish between seagrass and macroalgae substrates more accurately compared to the results obtained using the other classifications methods.