On the basin-scale detection and attribution of human-induced climate change in monsoon precipitation and streamflow

Detecting and quantifying the presence of human-induced climate change in regional hydrology is important for studying the impacts of such changes on the water resources systems as well as for reliable future projections and policy making for adaptation. In this article a formal fingerprint-based detection and attribution analysis has been attempted to study the changes in the observed monsoon precipitation and streamflow in the rain-fed Mahanadi River Basin in India, considering the variability across different climate models. This is achieved through the use of observations, several climate model runs, a principal component analysis and regression based statistical downscaling technique, and a Genetic Programming based rainfall-runoff model. It is found that the decreases in observed hydrological variables across the second half of the 20th century lie outside the range that is expected from natural internal variability of climate alone at 95% statistical confidence level, for most of the climate models considered. For several climate models, such changes are consistent with those expected from anthropogenic emissions of greenhouse gases. However, unequivocal attribution to human-induced climate change cannot be claimed across all the climate models and uncertainties in our detection procedure, arising out of various sources including the use of models, cannot be ruled out. Changes in solar irradiance and volcanic activities are considered as other plausible natural external causes of climate change. Time evolution of the anthropogenic climate change ``signal'' in the hydrological observations, above the natural internal climate variability ``noise'' shows that the detection of the signal is achieved earlier in streamflow as compared to precipitation for most of the climate models, suggesting larger impacts of human-induced climate change on streamflow than precipitation at the river basin scale.

Multi-model climate change projections for India under representative concentration pathways

Climate projections for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) are made using the newly developed representative concentration pathways (RCPs) under the Coupled Model Inter-comparison Project 5 (CMIP5). This article provides multi-model and multi-scenario temperature and precipitation projections for India for the period 1860-2099 based on the new climate data. We find that CMIP5 ensemble mean climate is closer to observed climate than any individual model. The key findings of this study are: (i) under the business-as-usual (between RCP6.0 and RCP8.5) scenario, mean warming in India is likely to be in the range 1.7-2 degrees C by 2030s and 3.3-4.8 degrees C by 2080s relative to pre-industrial times; (ii) all-India precipitation under the business-as-usual scenario is projected to increase from 4% to 5% by 2030s and from 6% to 14% towards the end of the century (2080s) compared to the 1961-1990 baseline; (iii) while precipitation projections are generally less reliable than temperature projections, model agreement in precipitation projections increases from RCP2.6 to RCP8.5, and from short-to long-term projections, indicating that long-term precipitation projections are generally more robust than their short-term counterparts and (iv) there is a consistent positive trend in frequency of extreme precipitation days (e.g. > 40 mm/day) for decades 2060s and beyond. These new climate projections should be used in future assessment of impact of climate change and adaptation planning. There is need to consider not just the mean climate projections, but also the more important extreme projections in impact studies and as well in adaptation planning.

Decentralised carbon footprint analysis for opting climate change mitigation strategies in India

Carbon footprint (CF) refers to the total amount of carbon dioxide and its equivalents emitted due to various anthropogenic activities. Carbon emission and sequestration inventories have been reviewed sector-wise for all federal states in India to identify the sectors and regions responsible for carbon imbalances. This would help in implementing appropriate climate change mitigation and management strategies at disaggregated levels. Major sectors of carbon emissions in India are through electricity generation, transport, domestic energy consumption, industries and agriculture. A majority of carbon storage occurs in forest biomass and soil. This paper focuses on the statewise carbon emissions (CO2. CO and CH4), using region specific emission factors and statewise carbon sequestration capacity. The estimate shows that CO2, CO and CH4 emissions from India are 965.9, 22.5 and 16.9 Tg per year, respectively. Electricity generation contributes 35.5% of total CO2 emission, which is followed by the contribution from transport. Vehicular transport exclusively contributes 25.5% of total emission. The analysis shows that Maharashtra emits higher CO2, followed by Andhra Pradesh, Uttar Pradesh, Gujarat, Tamil Nadu and West Bengal. The carbon status, which is the ratio of annual carbon storage against carbon emission, for each federal state is computed. This shows that small states and union territories (UT) like Arunachal Pradesh, Mizoram and Andaman and Nicobar Islands, where carbon sequestration is higher due to good vegetation cover, have carbon status > 1. Annually, 7.35% of total carbon emissions get stored either in forest biomass or soil, out of which 34% is in Arunachal Pradesh, Madhya Pradesh, Chhattisgarh and Orissa. (C) 2012 Elsevier Ltd. All rights reserved.

Evolution of Texture and Microstructure in Commercially Pure Titanium with Change in Strain Path During Rolling

The evolution of microstructure and texture in commercially pure titanium has been studied as a function of strain path during rolling using experimental techniques and viscoplastic self-consistent simulations. Four different strain paths, namely unidirectional rolling, two-step cross rolling, multistep cross rolling, and reverse rolling, have been employed to decipher the effect of strain path change on the evolution of deformation texture and microstructure. The cross-rolled samples show higher hardness with lower microstrain and intragranular misorientation compared to the unidirectional rolled sample as determined from X-ray diffraction and electron backscatter diffraction, respectively. The higher hardness of the cross-rolled samples is attributed to orientation hardening due to the near basal texture. Viscoplastic self-consistent simulations are able to successfully predict the texture evolution of the differently rolled samples. Simulation results indicate the higher contribution of basal slip in the formation of near basal texture and as well as lower intragranular misorientation in the cross-rolled samples.

Optical properties change with the addition and diffusion of Bi to As2S3 in the Bi/As2S3 bilayer thin film

The role of Bi layer (thickness similar to 7 nm) on As2S3 film was extensively studied for different optical applications in which Bi (top layer) as active and diffusing layer and As2S3 as barrier (matrix) layer. Bilayer thin films of Bi/As2S3 were prepared from Bi and As2S3 by thermal evaporation technique under high vacuum. The decrease of optical band gap with the addition of Bi to As2S3 has been explained on the basis of density of states and the increase in disorder in the system. It was found that the efficient changes of optical parameters (transmission, optical band gap, refraction) could be realized due to the photo induced diffusion activated by the focused 532 nm laser irradiation and formation of different bonds. The diffusion of Bi into As2S3 matrix increases the optical band gap producing photo bleaching effect. The changes were characterised by different experimental techniques. (C) 2012 Elsevier B.V. All rights reserved.

Performance analysis of data and voice connections in a cognitive radio network

We study the performance of cognitive (secondary) users in a cognitive radio network which uses a channel whenever the primary users are not using the channel. The usage of the channel by the primary users is modelled by an ON-OFF renewal process. The cognitive users may be transmitting data using TCP connections and voice traffic. The voice traffic is given priority over the data traffic. We theoretically compute the mean delay of TCP and voice packets and also the mean throughput of the different TCP connections. We compare the theoretical results with simulations.

Assessing Indian cities for vulnerability to climate change

This paper critically evaluates the vulnerability of Indian cities to climate change in the context of sustainable development. City-scale indicators are developed for multiple dimensions of security and vulnerability. Factor analysis is employed to construct a vulnerability ranking of 46 major Indian cities. The analysis reveals that high aggregate levels of wealth do not necessarily make a city less vulnerable. Two, cities with diversified economic opportunities could adapt better to the new risks posed by climate change, than cities with unipolar opportunities. Three, highly polluted cities are more vulnerable to the health impacts of climate change, and cities with severe groundwater depletion will find it difficult to cope with increased rainfall variability. Policy and sustainability issues are discussed for these results.

Assessment of hydrologic impacts of climate change in Tunga-Bhadra river basin, India with HEC-HMS and SDSM

Climate change would significantly affect many hydrologic systems, which in turn would affect the water availability, runoff, and the flow in rivers. This study evaluates the impacts of possible future climate change scenarios on the hydrology of the catchment area of the TungaBhadra River, upstream of the Tungabhadra dam. The Hydrologic Engineering Center's Hydrologic Modeling System version 3.4 (HEC-HMS 3.4) is used for the hydrological modelling of the study area. Linear-regression-based Statistical DownScaling Model version 4.2 (SDSM 4.2) is used to downscale the daily maximum and minimum temperature, and daily precipitation in the four sub-basins of the study area. The large-scale climate variables for the A2 and B2 scenarios obtained from the Hadley Centre Coupled Model version 3 are used. After model calibration and testing of the downscaling procedure, the hydrological model is run for the three future periods: 20112040, 20412070, and 20712099. The impacts of climate change on the basin hydrology are assessed by comparing the present and future streamflow and the evapotranspiration estimates. Results of the water balance study suggest increasing precipitation and runoff and decreasing actual evapotranspiration losses over the sub-basins in the study area.

Impacts of climate change on regional water resources

Water is the most important medium through which climate change influences human life. Rising temperatures together with regional changes in precipitation patterns are some of the impacts of climate change that have implications on water availability, frequency and intensity of floods and droughts, soil moisture, water quality, water supply and water demands for irrigation and hydropower generation. In this article we provide an introduction to the emerging field of hydrologic impacts of climate change with a focus on water availability, water quality and irrigation demands. Climate change estimates on regional or local spatial scales are burdened with a considerable amount of uncertainty, stemming from various sources such as climate models, downscaling and hydrological models used in the impact assessments and uncertainty in the downscaling relationships. The present article summarizes the recent advances on uncertainty modeling and regional impacts of climate change for the Mahanadi and Tunga-Bhadra Rivers in India.

Modeling the vulnerability of an urban groundwater system due to the combined impacts of climate change and management scenarios

Climate change impact on a groundwater-dependent small urban town has been investigated in the semiarid hard rock aquifer in southern India. A distributed groundwater model was used to simulate the groundwater levels in the study region for the projected future rainfall (2012-32) obtained from a general circulation model (GCM) to estimate the impacts of climate change and management practices on groundwater system. Management practices were based on the human-induced changes on the urban infrastructure such as reduced recharge from the lakes, reduced recharge from water and wastewater utility due to an operational and functioning underground drainage system, and additional water extracted by the water utility for domestic purposes. An assessment of impacts on the groundwater levels was carried out by calibrating a groundwater model using comprehensive data gathered during the period 2008-11 and then simulating the future groundwater level changes using rainfall from six GCMs Institute of Numerical Mathematics Coupled Model, version 3.0 (INM-CM. 3.0); L'Institut Pierre-Simon Laplace Coupled Model, version 4 (IPSL-CM4); Model for Interdisciplinary Research on Climate, version 3.2 (MIROC3.2); ECHAM and the global Hamburg Ocean Primitive Equation (ECHO-G); Hadley Centre Coupled Model, version 3 (HadCM3); and Hadley Centre Global Environment Model, version 1 (HadGEM1)] that were found to show good correlation to the historical rainfall in the study area. The model results for the present condition indicate that the annual average discharge (sum of pumping and natural groundwater outflow) was marginally or moderately higher at various locations than the recharge and further the recharge is aided from the recharge from the lakes. Model simulations showed that groundwater levels were vulnerable to the GCM rainfall and a scenario of moderate reduction in recharge from lakes. Hence, it is important to sustain the induced recharge from lakes by ensuring that sufficient runoff water flows to these lakes.

Solvent-templated supramolecular isomerism in 2D coordination polymer constructed by (Ni2CoII)-Co-II nodes and dicyanamido spacers: drastic change in magnetic behaviours

Two heterometallic coordination polymers (CPs) have been prepared using (NiL)-L-II](2)Co-II (where H2L = N,N'-bis(salicylidene)-1,3-propanediamine) as nodes and dicyanamido spacers by varying the solvent for synthesis. Structural characterizations revealed that methanol assisted the formation of a two-dimensional (4,4) connected rhombic grid network of (NiL)(2)Co(NCNCN)2](infinity) (1a) whereas relatively less polar acetonitrile afforded a different superstructure {(NiL)(2)Co(NCNCN)(2)]center dot CH3CN}(infinity) (1b) with a two-dimensional (4,4) connected square grid network. The presence of acetonitrile molecules in the structure of 1b seems to change the spatial orientation of the terminal metalloligands NiL] from pseudo-eclipsed in 1a to staggered-like in 1b around the central Co(II). These structural changes in the nodes together with the conformationally flexible dicyanamido spacers, which are cis coordinated to the Co(II) in both trinuclear units, led to the differences in the final 2D network. Variable-temperature magnetic susceptibility measurements revealed that this supramolecular isomerism led to a drastic transition from spin-frustrated antiferromagnetism for 1a to a dominant ferromagnetic behaviour for 1b. The geometrical differences in Ni2Co coordination clusters (CCs) which are scalene triangular in 1a but nearly linear in 1b, are held responsible for the changes of the magnetic properties. The DFT calculations of exchange interactions between metal centres provide a clear evidence of the role played by the fundamental geometrical factors on the nature and magnitude of the magnetic coupling in these pseudo-polymorphic CPs.

Challenges in vulnerability assessment of forests under climate change

Forest-management goals in the context of climate change are to reduce the adverse impact of climate change on biodiversity, ecosystem services and carbon stocks. For developing an effective adaptation strategy, knowledge on nature and sources of vulnerability of forests is necessary to conserve or enhance carbon sinks. However, assessing the vulnerability of forest ecosystems is a challenging task, as the mechanisms that determine vulnerability cannot be observed directly. In this article, we list the challenges in forest vulnerability assessments and propose an assessment of inherent vulnerability by using process-based indicators under the current climate. We also suggest periodic assessment of vulnerability, which is necessary to review adaptation strategies for the management of forests and forest carbon stocks.

Asynchronous Measurement of Transient Phase-Shift Resulting From RF Receiver State-Change

In a wireless receiver, a down-converted RF signal undergoes a transient phase shift, when the gain state is changed to adjust for varying conditions in transmission and propagation. A method is developed, in which such phase shifts are detected asynchronously, and their undesirable effects on the bit error rate are corrected. The method was developed for and used in, the system-level characterization and calibration of a 65-nm CMOS UHF receiver. The phase-shifts associated with specific gain-state transitions were measured within a test framework, and used in the baseband signal processing blocks to compensate for errors, whenever the receiver anticipated a gain-state transition.

Regional impacts of climate change on irrigation water demands

This paper presents an approach to model the expected impacts of climate change on irrigation water demand in a reservoir command area. A statistical downscaling model and an evapotranspiration model are used with a general circulation model (GCM) output to predict the anticipated change in the monthly irrigation water requirement of a crop. Specifically, we quantify the likely changes in irrigation water demands at a location in the command area, as a response to the projected changes in precipitation and evapotranspiration at that location. Statistical downscaling with a canonical correlation analysis is carried out to develop the future scenarios of meteorological variables (rainfall, relative humidity (RH), wind speed (U-2), radiation, maximum (Tmax) and minimum (Tmin) temperatures) starting with simulations provided by a GCM for a specified emission scenario. The medium resolution Model for Interdisciplinary Research on Climate GCM is used with the A1B scenario, to assess the likely changes in irrigation demands for paddy, sugarcane, permanent garden and semidry crops over the command area of Bhadra reservoir, India. Results from the downscaling model suggest that the monthly rainfall is likely to increase in the reservoir command area. RH, Tmax and Tmin are also projected to increase with small changes in U-2. Consequently, the reference evapotranspiration, modeled by the Penman-Monteith equation, is predicted to increase. The irrigation requirements are assessed on monthly scale at nine selected locations encompassing the Bhadra reservoir command area. The irrigation requirements are projected to increase, in most cases, suggesting that the effect of projected increase in rainfall on the irrigation demands is offset by the effect due to projected increase/change in other meteorological variables (viz., Tmax and Tmin, solar radiation, RH and U-2). The irrigation demand assessment study carried out at a river basin will be useful for future irrigation management systems. Copyright (c) 2012 John Wiley & Sons, Ltd.