Anthropogenic disturbances and their impact on vegetation in Western Himalaya,India

The present study assesses anthropogenic disturbances and their impacts on the vegetation in Western Himalaya, India on the basis of various disturbance parameters such as density, Total Basal Cover (TBC) of cut stumps, lopping percentage and grazing intensities. On the basis of canopy cover and frequency of disturbances (%), the studied forests were divided into highly disturbed (HD), moderately disturbed (MD) and least disturbed (LD) categories. The HD forests had the lowest canopy cover, lowest density and lowest TBC and the LD had the highest canopy cover, highest density and highest TBC. The MD forests occupied the intermediate position with respect to these parameters. Species richness was least in HD forests, highest in one of the MD forests while LD forest occupied an intermediate position. The percentage of regenerating species was lowest (54%) in HD and highest (72%) in MD. The density of seedlings and saplings was higher in one of the MD forests as compared to HD and LD. We concluded that the moderate disturbances do not affect the vegetation adversely; however the increased degree of disturbance causes loss in plant diversity; affects regeneration and changes community characteristics. Construction of hydroelectric projects at various places in the study area was found to be one of the most important sources of anthropogenic disturbances in addition to the routine anthropogenic disturbances like grazing, fuelwood collection and fodder extraction. If all proposed dams in the Indian Himalaya are constructed combined with weak national environmental impact assessment and implementation, it will result in a significant loss of species. Therefore, various agents of disturbances should be evaluated in cumulative manner and any developmental activities such as hydropower projects, which trigger various natural and anthropogenic disturbances, should be combined with proper cumulative environmental impact assessment and effective implementation to minimise the anticipated loss of vegetation.     

The influence of the South-west Indian monsoon on continental deposition over the past 130 kyr, Gujarat, western India

Ocean and ice core records of the intensity of the South-west Indian Monsoon (SwIM) show rapid shifts in most proxy indicators of climate over the past 125 kyr on decadal to millenial scales. However, the responses of continental environments to such perturbations remain unknown due to the absence of a suitable long-term continental record. The stratigraphic record from Gujarat, western India, an area where all sedimentological processes are governed by the vagaries of the SwIM, reveals three aggradation phases that represent deposits of seasonal rivers (AP1), ephemeral rivers (AP2) and dust storms (AP3). Based on a review of available dates and new ESR dates on the oldest exposed calcretes from palaeovertisols these phases are assigned the time brackets 135–100 kyr bp (AP1), 100–20 kyr bp (AP2) and 20–6 kyr bp (AP3). These results suggest that continental depositional environments respond in a subdued manner and are separated by thresholds. For climate shifts to effect durable changes in the continental depositional environment, a period between > 5 kyr and 16 kyr is the minimum time required to permanently change the landscape of an area. Alternatively, catastrophic changes in terrestrial depositional environments may also be effected by abrupt climatic shifts that are beyond the tolerance limits of the depositional systems.     

Modelling radar-rainfall estimation uncertainties using elliptical and Archimedean copulas with different marginal distributions

Abstract

Given that radar-based rainfall has been broadly applied in hydrological studies, quantitative modelling of its uncertainty is critically important, as the error of input rainfall is the main source of error in hydrological modelling. Using an ensemble of rainfall estimates is an elegant solution to characterize the uncertainty of radar-based rainfall and its spatial and temporal variability. This paper has fully formulated an ensemble generator for radar precipitation estimation based on the copula method. Each ensemble member is a probable realization that represents the unknown true rainfall field based on the distribution of radar rainfall (RR) error and its spatial error structure. An uncertainty model consisting of a deterministic component and a random error factor is presented based on the distribution of gauge rainfall conditioned on the radar rainfall (GR|RR). Two kinds of copulas (elliptical and Archimedean copulas) are introduced to generate random errors, which are imposed by the deterministic component. The elliptical copulas (e.g. Gaussian and t-copula) generate the random errors based on the multivariate distribution, typically of decomposition of the error correlation matrix using the LU decomposition algorithm. The Archimedean copulas (e.g. Clayton and Gumbel) utilize the conditional dependence between different radar pixels to obtain random errors. Based on those, a case application is carried out in the Brue catchment located in southwest England. The results show that the simulated uncertainty bands of rainfall encompass most of the reference raingauge measurements with good agreement between the simulated and observed spatial dependences. This indicates that the proposed scheme is a statistically reliable method in ensemble radar rainfall generation and is a useful tool for describing radar rainfall uncertainty.

Editor D. Koutsoyiannis; Associate editor S. Grimaldi     

Seasonal ensemble generator for radar rainfall using copula and autoregressive model

Uncertainty analysis of radar rainfall enables stakeholders and users have a clear knowledge of the possible uncertainty associated with the rainfall products. Long-term empirical modeling of the relationship between radar and gauge measurements is an efficient and practical method to describe the radar rainfall uncertainty. However, complicated variation of synoptic conditions makes the radar-rainfall uncertainty model based on historical data hard to extend in the future state. A promising solution is to integrate synoptic regimes with the empirical model and explore the impact of individual synoptic regimes on radar rainfall uncertainty. This study is an attempt to introduce season, one of the most important synoptic factor, into the radar rainfall uncertainty model and proposes a seasonal ensemble generator for radar rainfall using copula and autoregressive model. We firstly analyze the histograms of rainfall-weighted temperature, the radar-gauge relationships, and Box and Whisker plots in different seasons and conclude that the radar rainfall uncertainty has strong seasonal dependence. Then a seasonal ensemble generator is designed and implemented in a UK catchment under a temperate maritime climate, which can fully model marginal distribution, spatial dependence, temporal dependence and seasonal dependence of radar rainfall uncertainty. To test its performance, 12 typical rainfall events (4 for each season) are chosen to generate ensemble rainfall values. In each time step, 500 ensemble members are produced and the values of 5th to 95th percentiles are used to derive the uncertainty bands. Except several outliers, the uncertainty bands encompass the observed gauge rainfall quite well. The parameters of the ensemble generator vary considerably for each season, indicating the seasonal ensemble generator reflects the impact of seasons on radar rainfall uncertainty. This study is an attempt to simultaneously consider four key features of radar rainfall uncertainty and future study will investigate their impacts on the outputs of hydrological models with radar rainfall as input or initial conditions.     

Characteristics,modification and environmental application of Yemen’s natural bentonite

The bentonite deposit of Lahij Province, Yemen, has very promising commercial applications due to its mineralogy and physical and chemical properties. It was examined to determine its mineralogical composition, chemical and physical properties of the bentonite deposit, purity and sodium-exchanged bentonite. Modified bentonite was synthesized by exchanging cetyltrimethylammonium cations for inorganic ions on the bentonite and its adsorption properties for ammonium were characterized in batch experiments. Analytical methods were carried out to study the bentonite comprising X-ray diffraction (XRD), scanning electron microscopy (SEM), infrared spectroscopy, chemical analysis and kinetic and isotherm models were also tested. The results have shown that the purification of bentonite resulted in a bentonite fractions of the total sample composed of montmorillonite and <5 % quartz. The XRD data showed that the interlayer spacing (d ₀₀₁) of bentonite decreased from 15.3 to 12.5 Å and then increased to 19.7 Å. Moreover, high cation exchange capacity, good water absorption and high swelling capacity were also obtained. The results have shown that the modified bentonite was more effective than the natural bentonite for ammonium removal. In addition to that, pseudo-second-order kinetic model, Freundlich and the Langmuir models described the adsorption kinetics and isotherm well. It was concluded that Yemen (Alaslef) bentonite can be potential adsorbents for ammonium removal.     

Nonlinear magneto-acoustic dispersive waves

The multiple time scale method is applied to investigate the nonlinear magneto-acoustic dispersive waves in a collisional plasma. Whereas in the absence of collisions these waves are modulationally stable, the collisions render them modulationally unstable.     

Daily and seasonal dynamics of suspended particles in the Rhône River plume based on remote sensing and field optical measurements

Satellite ocean colour remote sensing can serve as a powerful tool to assess river plume characteristics because it provides daily mapping of surface suspended particulate matter (SPM) concentration at high spatial resolution. This study’s ultimate objective was to better understand daily and seasonal particle dynamics in a coastal area strongly influenced by freshwater discharge and wind—the Rhône River (France), this being the major source of terrestrial input to the Mediterranean Sea. SPM concentrations and biogenic composition (chlorophyll a, organic carbon) were investigated during several bio-optical field campaigns conducted in spring–autumn of 2010 both from aboard a research vessel and by means of an autonomous profiling float. Freshwater discharge and wind velocities varied significantly during the year, associated with marked fluctuations in surface SPM (upper 1 m), even within hours and not restricted to any specific season. Thus, the range was ca. 12–25 g m^–3 (dry mass basis) on 9 April (spring), and ca. 3–39 g m^–3 on 4–5 November (late autumn). Short-term variations were observed also in SPM composition in terms of POC (albeit not chl a), with POC/SPM ratios ranging between ca. 3 and 11% over ca. 3 weeks in spring. Nevertheless, the particulate backscattering coefficient (b _bp) proved to be a robust proxy of SPM concentration in the river plume (b _bp(770)?=?0.0076?×?SPM, R²?=?0.80, N?=?56). It has recently been demonstrated that 80% of the Rhône’s terrestrial discharge occurs during flood events. The results of the present study revealed that, under these conditions, SPM is constrained largely within surface waters (i.e. at depths <5 m), with only weak daily vertical variability. By implication, ocean colour satellite data are highly suitable in meaningfully estimating the overall SPM load exported by the Rhône River to the Mediterranean. These findings make a solid contribution to future improvements of three-dimensional sediment transport models for the region and similar settings.