Integrating biodiversity and conservation with modern agricultural landscapes

To achieve food security and meet the demands of the ever-growing human populations, farming systems have assumed unsustainable practices to produce more from a finite land area. This has been cause for concern mainly due to the often-irreversible damage done to the otherwise productive agricultural landscapes. Agro-ecology is proclaimed to be deteriorating due to eroding integrity of connected ecological mosaics and vulnerability to climate change. This has contributed to declining species diversity, loss of buffer vegetation, fragmentation of habitats, and loss of natural pollinators or predators, which eventually leads to decline in ecosystem services. Currently, a hierarchy of conservation initiatives is being considered to restore ecological integrity of agricultural landscapes. However, the challenge of identifying a suitable conservation strategy is a daunting task in view of socio-ecological factors that may constrain the choice of available strategies. One way to mitigate this situation and integrate biodiversity with agricultural landscapes is to implement offset mechanisms, which are compensatory and balancing approaches to restore the ecological health and function of an ecosystem. This needs to be tailored to the history of location specific agricultural practices, and the social, ecological and environmental conditions. The offset mechanisms can complement other initiatives through which farmers are insured against landscape-level risks such as droughts, fire and floods. For countries in the developing world with significant biodiversity and extensive agriculture, we should promote a comprehensive model of sustainable agricultural landscapes and ecosystem services, replicable at landscape to regional scales. Arguably, the model can be a potential option to sustain the integrity of biodiversity mosaic in agricultural landscapes.

Hydrologic drought prediction under climate change: Uncertainty modeling with Dempster-Shafer and Bayesian approaches

Representation and quantification of uncertainty in climate change impact studies are a difficult task. Several sources of uncertainty arise in studies of hydrologic impacts of climate change, such as those due to choice of general circulation models (GCMs), scenarios and downscaling methods. Recently, much work has focused on uncertainty quantification and modeling in regional climate change impacts. In this paper, an uncertainty modeling framework is evaluated, which uses a generalized uncertainty measure to combine GCM, scenario and downscaling uncertainties. The Dempster-Shafer (D-S) evidence theory is used for representing and combining uncertainty from various sources. A significant advantage of the D-S framework over the traditional probabilistic approach is that it allows for the allocation of a probability mass to sets or intervals, and can hence handle both aleatory or stochastic uncertainty, and epistemic or subjective uncertainty. This paper shows how the D-S theory can be used to represent beliefs in some hypotheses such as hydrologic drought or wet conditions, describe uncertainty and ignorance in the system, and give a quantitative measurement of belief and plausibility in results. The D-S approach has been used in this work for information synthesis using various evidence combination rules having different conflict modeling approaches. A case study is presented for hydrologic drought prediction using downscaled streamflow in the Mahanadi River at Hirakud in Orissa, India. Projections of n most likely monsoon streamflow sequences are obtained from a conditional random field (CRF) downscaling model, using an ensemble of three GCMs for three scenarios, which are converted to monsoon standardized streamflow index (SSFI-4) series. This range is used to specify the basic probability assignment (bpa) for a Dempster-Shafer structure, which represents uncertainty associated with each of the SSFI-4 classifications. These uncertainties are then combined across GCMs and scenarios using various evidence combination rules given by the D-S theory. A Bayesian approach is also presented for this case study, which models the uncertainty in projected frequencies of SSFI-4 classifications by deriving a posterior distribution for the frequency of each classification, using an ensemble of GCMs and scenarios. Results from the D-S and Bayesian approaches are compared, and relative merits of each approach are discussed. Both approaches show an increasing probability of extreme, severe and moderate droughts and decreasing probability of normal and wet conditions in Orissa as a result of climate change. (C) 2010 Elsevier Ltd. All rights reserved.

Groundwater Management in India:Physical, Institutional and Policy Alternatives

Groundwater constitutes a vital natural resource for sustaining India’s agricultural economy and meeting the country’s social, ecological and environmental goals. It is a unique resource, widely available, providing security against droughts and yet it is closely linked to surface-water resources and the hydrological cycle. Its availability depends on geo-hydrological conditions and characteristics of aquifers, from deep to alluvium, sediment crystalline rocks to basalt formations; and agro-climate from humid to subhumid and semi-arid to arid. Its reliable supply, uniform quality and temperature, relative turbidity, pollution-safe, minimal evaporation losses, and low cost of development are attributes making groundwater more attractive compared to other resources. It plays a key role in the provision of safe drinking water to rural populations. For example, already almost 80% of domestic water use in rural areas in India is groundwater-supplied, and much of it is being supplied to farms, villages and small towns. Inadequate control of the use of groundwater, indiscriminate application of agrochemicals and unrestrained pollution of the rural environment by other human activities make groundwater usage unsustainable, necessitating proper management in the face of the twin demand for water of good quality for domestic supply and adequate supply for irrigation, ensuring equity, efficiency and sustainability of the resource. Groundwater irrigation has overtaken surface irrigation in the early 1980s, supported by well energization. It is estimated that there are about 24 million energised wells and tube wells now and it is driven by demand rather than availability, evident through the greater occurrence of wells in districts with high population densities. Apart from aquifer characteristics, land fragmentation and landholding size are the factors that decide the density of wells. The ‘rise and fall’ of local economies dependent on groundwater can be summarized as: the green revolution of 1980s, groundwaterbased agrarian boom, early symptoms of groundwater overdraft, and decline of the groundwater socio-ecology. The social characteristics and policy interventions typical of each stage provide a fascinating insight into the human-resource dynamics. This book is a compilation of nine research papers discussing various aspects of groundwater management. It attempts to integrate knowledge about the physical system, the socio-economic system, the institutional set-up and the policy environment to come out with a more realistic analysis of the situation with regard to the nature, characteristics and intensity of resource use, the size of the economy the use generates, and the negative socioeconomic consequences. Complex variables addressed in this regard focusing on northern Gujarat are the stock of groundwater available in the region, its hydrodynamics, its net outflows against inflows, the economics of its intensive use (particularly irrigation in semi-arid and arid regions), its criticality in the regional hydroecological regime, ethical aspects and social aspects of its use. The first chapter by Dinesh Kumar and Singh, dwells on complex groundwater socio-ecology of India, while emphasizing the need for policy measures to address indiscriminate over-exploitation of dwindling resources. The chapter also explores the nature of groundwater economy and the role of electricity prices on it. The next chapter on groundwater issue in north Gujarat provides a description of groundwater resource characteristics followed by a detailed analysis of the groundwater depletion and quality deterioration problems in the region and their undesirable consequences on the economy, ecosystem health and the society. Considering water-buyers and wellowning farmers individually, a methodology for economic valuation of groundwater in regions where its primary usage is in agriculture, and as assessment of the groundwater economy based on case studies from north Gujarat is presented in the fourth chapter. The next chapter focuses on the extent of dependency of milk production on groundwater, which includes the water embedded in green and dry fodder and animal feed. The study made a realistic estimate of irrigation water productivity in terms of the physics and economics of milk production. The sixth chapter analyses the extent of reduction in water usage, increase in yield and overall increase in physical productivity of alfalfa with the use of the drip irrigation system. The chapter also provides a detailed synthesis of the costs and benefits associated with the use of drip irrigation systems. A linear programmingbased optimization model with the objective to minimize groundwater use taking into account the interaction between two distinct components – farming and dairying under the constraints of food security and income stability for different scenarios, including shift in cropping pattern, introduction of water-efficient crops, water- saving technologies in addition to the ‘business as usual’ scenario is presented in the seventh chapter. The results show that sustaining dairy production in the region with reduced groundwater draft requires crop shifts and adoption of water-saving technologies. The eighth chapter provides evidences to prove that the presence of adequate economic incentive would encourage farmers to adopt water-saving irrigation devices, based on the findings of market research with reference to the level of awareness among farmers of technologies and the factors that decide the adoption of water-saving technologies. However, now the marginal cost of using electricity for agricultural pumping is almost zero. The economic incentives are strong and visible only when the farmers are either water-buyers or have to manage irrigation with limited water from tube-well partnerships. The ninth chapter explores the socio-economic viability of increasing the power tariff and inducing groundwater rationing as a tool for managing energy and groundwater demand, considering the current estimate of the country’s annual economic loss of Rs 320 billion towards electricity subsidy in the farm sector. The tenth chapter suggests private tradable property rights and development of water markets as the institutional tool for achieving equity, efficiency and sustainability of groundwater use. It identifies the externalities for local groundwater management and emphasizes the need for managing groundwater by local user groups, supported by a thorough analysis of groundwater socio-ecology in India. An institutional framework for managing the resource based on participatory approach that is capable of internalizing the externalities, comprising implementation of institutional and technical alternatives for resource management is also presented. Major findings of the analyses and key arguments in each chapter are summarized in the concluding chapter. Case studies of the social and economic benefits of groundwater use, where that use could be described as unsustainable, are interesting. The benefits of groundwater use are outlined and described with examples of social and economic impacts of groundwater and the negative aspects of groundwater development with the compilation of environmental problems based on up-to-date research results. This publication with a well-edited compilation of case studies is informative and constitutes a useful publication for students and professionals.

Community-based Natural Resource Management: Issues and Cases from South Asia

Community-based natural resource management (CBNRM) is the joint management of natural resources by a community based on a community strategy, through a participatory mechanism involving all legitimate stakeholders. The approach is community-based in that the communities managing the resources have the legal rights, the local institutions and the economic incentives to take substantial responsibility for sustained use of these resources. This implies that the community plays an active role in the management of natural resources, not because it asserts sole ownership over them, but because it can claim participation in their management and benefits for practical and technical reasons1–4. This approach emerged as the dominant conservation concept in the late 1970s and early 1980s, of the disillusionment with the developmental state. Governments across South and South East Asia, Africa and Latin America have adopted and implemented CBNRM in various ways, viz. through sectoral programmes such as forestry, irrigation or wildlife management, multisectoral programmes such as watershed development and efforts towards political devolution. In India, the principle of decentralization through ‘gram swaraj’ was introduced by Mahatma Gandhi. The 73rd and 74th constitution amendments in 1992 gave impetus to the decentralized planning at panchayat levels through the creation of a statutory three-level local self-government structure5,6. The strength of this book is that it includes chapters by CBNRM advocates based on six seemingly innovative initiatives being implemented by nongovernmental organizations (NGOs) in ecologically vulnerable regions of South Asia: two in the Himalayas (watershed development programme in Lingmutechhu, Bhuthan and Thalisain tehsil, Paudi Grahwal District, Uttarakhand), three in semi-arid parts of western India (watershed development in Hivre Bazar, Maharashtra and Nathugadh village, Gujarat and water-harvesting structures in Gopalapura, Rajasthan) and one in the flood-plains of the Brahmaputra–Jamuna (Char land, Galibanda and Jamalpur districts, Bangladesh). Watersheds in semi-arid regions fall in the low-rainfall region (500–700 mm) and suffer the vagaries of drought 2–3 years in every five-year cycle. In all these locations, the major occupation is agriculture, most of which is rainfed or dry. The other two cases (in Uttarakhand) fall in the Himalayan region (temperate/sub-temperate climate), which has witnessed extensive deforestation in the last century and is now considered as one of the most vulnerable locations in South Asia. Terraced agriculture is being practised in these locations for a long time. The last case (Gono Chetona) falls in the Brahmaputra–Jamuna charlands which are the most ecologically vulnerable regions in the sub-continent with constantly changing landscape. Agriculture and livestock rearing are the main occupations, and there is substantial seasonal emigration for wage labour by the adult males. River erosion and floods force the people to adopt a semi-migratory lifestyle. The book attempts to analyse the potential as well as limitations of NGOdriven CBNRM endeavours across agroclimatic regions of South Asia with emphasis on four intrinsically linked normative concerns, namely sustainability, livelihood enhancement, equity and demographic decentralization in chapters 2–7. Comparative analysis of these case studies done in chapter 8, highlights the issues that require further research while portraying the strengths and limits of NGO-driven CBNRM. In Hivre Bazar, the post-watershed intervention scenario is such that farmers often grow three crops in a year – kharif bajra, rabi jowar and summer vegetable crops. Productivity has increased in the dry lands due to improvement in soil moisture levels. The revival of johads in Gopalpura has led to the proliferation of wheat and increased productivity. In Lingmuteychhu, productivity gains have also arisen, but more due to the introduction of both local and high-yielding, new varieties as opposed to increased water availability. In the case of Gono Chetona, improvements have come due to diversification of agriculture; for example, the promotion of vegetable gardens. CBNRM interventions in most cases have also led to new avenues of employment and income generation. The synthesis shows that CBNRM efforts have made significant contributions to livelihood enhancement and only limited gains in terms of collective action for sustainable and equitable access to benefits and continuing resource use, and in terms of democratic decentralization, contrary to the objectives of the programme. Livelihood benefits include improvements in availability of livelihood support resources (fuelwood, fodder, drinking water), increased productivity (including diversification of cropping pattern) in agriculture and allied activities, and new sources of livelihood. However, NGO-driven CBNRM has not met its goal of providing ‘alternative’ forms of ‘development’ due to impediments of state policy, short-sighted vision of implementers and confrontation with the socio-ecological reality of the region, which almost always are that of fragmented communities (or communities in flux) with unequal dependence and access to land and other natural resources along with great gender imbalances. Appalling, however, is the general absence of recognition of the importance of and the will to explore practical ways to bring about equitable resource transfer or benefit-sharing and the consequent innovations in this respect that are evident in the pioneering community initiatives such as pani panchayat, etc. Pertaining to the gains on the ecological sustainability front, Hivre Bazar and Thalisain initiatives through active participation of villagers have made significant regeneration of the water table within the village, and mechanisms such as ban on number of bore wells, the regulation of cropping pattern, restrictions on felling of trees and free grazing to ensure that in the future, the groundwater is neither over-exploited nor its recharge capability impaired. Nevertheless, the longterm sustainability of the interventions in the case of Ghoga and Gopalpura initiatives as the focus has been mostly on regeneration of resources, and less on regulating the use of regenerated resources. Further, in Lingmuteychhu and Gono Chetona, the interventions are mainly household-based and the focus has been less explicit on ecological components. The studies demonstrate the livelihood benefits to all of the interventions and significant variation in achievements with reference to sustainability, equity and democratic decentralization depending on the level and extent of community participation apart from the vision of implementers, strategy (or nature of intervention shaped by the question of community formation), the centrality of community formation and also the State policy. Case studies show that the influence of State policy is multi-faceted and often contradictory in nature. This necessitates NGOs to engage with the State in a much more purposeful way than in an ‘autonomous space’. Thus the role of NGOs in CBNRM is complementary, wherein they provide innovative experiments that the State can learn. This helps in achieving the goals of CBNRM through democratic decentralization. The book addresses the vital issues related to natural resource management and interests of the community. Key topics discussed throughout the book are still at the centre of the current debate. This compilation consists of well-written chapters based on rigorous synthesis of CBNRM case studies, which will serve as good references for students, researchers and practitioners in the years to come.

Assessing severe Drought and wet events over India in a future climate using a nested bias-correction approach

General circulation models (GCMs) are routinely used to simulate future climatic conditions. However, rainfall outputs from GCMs are highly uncertain in preserving temporal correlations, frequencies, and intensity distributions, which limits their direct application for downscaling and hydrological modeling studies. To address these limitations, raw outputs of GCMs or regional climate models are often bias corrected using past observations. In this paper, a methodology is presented for using a nested bias-correction approach to predict the frequencies and occurrences of severe droughts and wet conditions across India for a 48-year period (2050-2099) centered at 2075. Specifically, monthly time series of rainfall from 17 GCMs are used to draw conclusions for extreme events. An increasing trend in the frequencies of droughts and wet events is observed. The northern part of India and coastal regions show maximum increase in the frequency of wet events. Drought events are expected to increase in the west central, peninsular, and central northeast regions of India. (C) 2013 American Society of Civil Engineers.

Regional hydrological impacts of climate change: implications for water management in India

Climate change is most likely to introduce an additional stress to already stressed water systems in developing countries. Climate change is inherently linked with the hydrological cycle and is expected to cause significant alterations in regional water resources systems necessitating measures for adaptation and mitigation. Increasing temperatures, for example, are likely to change precipitation patterns resulting in alterations of regional water availability, evapotranspirative water demand of crops and vegetation, extremes of floods and droughts, and water quality. A comprehensive assessment of regional hydrological impacts of climate change is thus necessary. Global climate model simulations provide future projections of the climate system taking into consideration changes in external forcings, such as atmospheric carbon-dioxide and aerosols, especially those resulting from anthropogenic emissions. However, such simulations are typically run at a coarse scale, and are not equipped to reproduce regional hydrological processes. This paper summarizes recent research on the assessment of climate change impacts on regional hydrology, addressing the scale and physical processes mismatch issues. Particular attention is given to changes in water availability, irrigation demands and water quality. This paper also includes description of the methodologies developed to address uncertainties in the projections resulting from incomplete knowledge about future evolution of the human-induced emissions and from using multiple climate models. Approaches for investigating possible causes of historically observed changes in regional hydrological variables are also discussed. Illustrations of all the above-mentioned methods are provided for Indian regions with a view to specifically aiding water management in India.

Predicting the extremes of Indian summer monsoon rainfall with coupled ocean-atmosphere models

An analysis of the retrospective predictions by seven coupled ocean atmosphere models from major forecasting centres of Europe and USA, aimed at assessing their ability in predicting the interannual variation of the Indian summer monsoon rainfall (ISMR), particularly the extremes (i.e. droughts and excess rainfall seasons) is presented in this article. On the whole, the skill in prediction of extremes is not bad since most of the models are able to predict the sign of the ISMR anomaly for a majority of the extremes. There is a remarkable coherence between the models in successes and failures of the predictions, with all the models generating loud false alarms for the normal monsoon season of 1997 and the excess monsoon season of 1983. It is well known that the El Nino and Southern Oscillation (ENSO) and the Equatorial Indian Ocean Oscillation (EQUINOO) play an important role in the interannual variation of ISMR and particularly the extremes. The prediction of the phases of these modes and their link with the monsoon has also been assessed. It is found that models are able to simulate ENSO-monsoon link realistically, whereas the EQUINOO-ISMR link is simulated realistically by only one model the ECMWF model. Furthermore, it is found that in most models this link is opposite to the observed, with the predicted ISMR being negatively (instead of positively) correlated with the rainfall over the western equatorial Indian Ocean and positively (instead of negatively) correlated with the rainfall over the eastern equatorial Indian Ocean. Analysis of the seasons for which the predictions of almost all the models have large errors has suggested the facets of ENSO and EQUINOO and the links with the monsoon that need to be improved for improving monsoon predictions by these models.

Tree-ring based hydroclimate reconstruction over northern Vietnam from Fokienia hodginsii: eighteenth century mega-drought and tropical Pacific influence

We present here the first statistically calibrated and verified tree-ring reconstruction of climate from continental Southeast Asia.The reconstructed variable is March-May (MAM) Palmer Drought Severity Index (PDSI) based on ring widths from 22 trees (42 radial cores) of rare and long-lived conifer, Fokienia hodginsii (Po Mu as locally called) from northern Vietnam. This is the first published tree ring chronology from Vietnam as well as the first for this species. Spanning 535 years, this is the longest cross-dated tree-ring series yet produced from continental Southeast Asia. Response analysis revealed that the annual growth of Fokienia at this site was mostly governed by soil moisture in the pre-monsoon season. The reconstruction passed the calibration-verification tests commonly used in dendroclimatology, and revealed two prominent periods of drought in the mid-eighteenth and late-nineteenth enturies. The former lasted nearly 30 years and was concurrent with a similar drought over northwestern Thailand inferred from teak rings, suggesting a ``mega-drought'' extending across Indochina in the eighteenth century. Both of our reconstructed droughts are consistent with the periods of warm sea surface temperature (SST)anomalies in the tropical Pacific. Spatial correlation analyses with global SST indicated that ENSO-like anomalies might play a role in modulating droughts over the region, with El Nio (warm) phases resulting in reduced rainfall. However, significant correlation was also seen with SST over the Indian Ocean and the north Pacific,suggesting that ENSO is not the only factor affecting the climate of the area. Spectral analyses revealed significant peaks in the range of 53.9-78.8 years as well as in the ENSO-variability range of 2.0 to 3.2 years.

Urban Floods: Case Study of Bangalore

Bangalore is one of the fastest growing cities in India and is branded as ‘Silicon Valley of India’ for heralding and spearheading the growth of Information Technology (IT) based industries in the country. With the advent and growth of IT industry, as well as numerous industries in other sectors and the onset of economic liberalisation since the early 1990s, Bangalore has taken lead in service-based industries fuelling substantial growth of the city both economically and spatially. Bangalore has become a cosmopolitan city attracting people and business alike, within and across nations. This profile notes the urban setting and provides an overview of the urban fabric, while discussing various prospects related to infrastructure and governance (Sudhira, et al. 2007).

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.

A divide and conquer strategy for scaling weather simulations with multiple regions of interest

Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.

Predictability of nonstationary time series using wavelet and EMD based ARMA models

Research has been undertaken to ascertain the predictability of non-stationary time series using wavelet and Empirical Mode Decomposition (EMD) based time series models. Methods have been developed in the past to decompose a time series into components. Forecasting of these components combined with random component could yield predictions. Using this ideology, wavelet and EMD analyses have been incorporated separately which decomposes a time series into independent orthogonal components with both time and frequency localizations. The component series are fit with specific auto-regressive models to obtain forecasts which are later combined to obtain the actual predictions. Four non-stationary streamflow sites (USGS data resources) of monthly total volumes and two non-stationary gridded rainfall sites (IMD) of monthly total rainfall are considered for the study. The predictability is checked for six and twelve months ahead forecasts across both the methodologies. Based on performance measures, it is observed that wavelet based method has better prediction capabilities over EMD based method despite some of the limitations of time series methods and the manner in which decomposition takes place. Finally, the study concludes that the wavelet based time series algorithm can be used to model events such as droughts with reasonable accuracy. Also, some modifications that can be made in the model have been discussed that could extend the scope of applicability to other areas in the field of hydrology. (C) 2013 Elesvier B.V. All rights reserved.

Bivariate frequency analysis of floods using a diffusion based kernel density estimator

Recent focus of flood frequency analysis (FFA) studies has been on development of methods to model joint distributions of variables such as peak flow, volume, and duration that characterize a flood event, as comprehensive knowledge of flood event is often necessary in hydrological applications. Diffusion process based adaptive kernel (D-kernel) is suggested in this paper for this purpose. It is data driven, flexible and unlike most kernel density estimators, always yields a bona fide probability density function. It overcomes shortcomings associated with the use of conventional kernel density estimators in FFA, such as boundary leakage problem and normal reference rule. The potential of the D-kernel is demonstrated by application to synthetic samples of various sizes drawn from known unimodal and bimodal populations, and five typical peak flow records from different parts of the world. It is shown to be effective when compared to conventional Gaussian kernel and the best of seven commonly used copulas (Gumbel-Hougaard, Frank, Clayton, Joe, Normal, Plackett, and Student's T) in estimating joint distribution of peak flow characteristics and extrapolating beyond historical maxima. Selection of optimum number of bins is found to be critical in modeling with D-kernel.