Basin Scale Water Resources Systems Modeling Under Cascading Uncertainties

Global change in climate and consequent large impacts on regional hydrologic systems have, in recent years, motivated significant research efforts in water resources modeling under climate change. In an integrated future hydrologic scenario, it is likely that water availability and demands will change significantly due to modifications in hydro-climatic variables such as rainfall, reservoir inflows, temperature, net radiation, wind speed and humidity. An integrated regional water resources management model should capture the likely impacts of climate change on water demands and water availability along with uncertainties associated with climate change impacts and with management goals and objectives under non-stationary conditions. Uncertainties in an integrated regional water resources management model, accumulating from various stages of decision making include climate model and scenario uncertainty in the hydro-climatic impact assessment, uncertainty due to conflicting interests of the water users and uncertainty due to inherent variability of the reservoir inflows. This paper presents an integrated regional water resources management modeling approach considering uncertainties at various stages of decision making by an integration of a hydro-climatic variable projection model, a water demand quantification model, a water quantity management model and a water quality control model. Modeling tools of canonical correlation analysis, stochastic dynamic programming and fuzzy optimization are used in an integrated framework, in the approach presented here. The proposed modeling approach is demonstrated with the case study of the Bhadra Reservoir system in Karnataka, India.

Evaluation of TRMM PR Sampling Error Over a Subtropical Basin Using Bootstrap Technique

Quantitative use of satellite-derived rainfall products for various scientific applications often requires them to be accompanied with an error estimate. Rainfall estimates inferred from low earth orbiting satellites like the Tropical Rainfall Measuring Mission (TRMM) will be subjected to sampling errors of nonnegligible proportions owing to the narrow swath of satellite sensors coupled with a lack of continuous coverage due to infrequent satellite visits. The authors investigate sampling uncertainty of seasonal rainfall estimates from the active sensor of TRMM, namely, Precipitation Radar (PR), based on 11 years of PR 2A25 data product over the Indian subcontinent. In this paper, a statistical bootstrap technique is investigated to estimate the relative sampling errors using the PR data themselves. Results verify power law scaling characteristics of relative sampling errors with respect to space-time scale of measurement. Sampling uncertainty estimates for mean seasonal rainfall were found to exhibit seasonal variations. To give a practical example of the implications of the bootstrap technique, PR relative sampling errors over a subtropical river basin of Mahanadi, India, are examined. Results reveal that the bootstrap technique incurs relative sampling errors < 33% (for the 2 degrees grid), < 36% (for the 1 degrees grid), < 45% (for the 0.5 degrees grid), and < 57% (for the 0.25 degrees grid). With respect to rainfall type, overall sampling uncertainty was found to be dominated by sampling uncertainty due to stratiform rainfall over the basin. The study compares resulting error estimates to those obtained from latin hypercube sampling. Based on this study, the authors conclude that the bootstrap approach can be successfully used for ascertaining relative sampling errors offered by TRMM-like satellites over gauged or ungauged basins lacking in situ validation data. This technique has wider implications for decision making before incorporating microwave orbital data products in basin-scale hydrologic modeling.

Fire and soil temperatures during controlled burns in seasonally dry tropical forests of southern India

Fire and soil temperatures were measured during controlled burns conducted by the Forest Department at two seasonally dry tropical forest sites in southern India, and their relationships with fuel load, fuel moisture and weather variables assessed using stepwise regression. Fire temperatures at the ground level varied between 79 degrees C and 760 degrees C, with higher temperatures recorded at high fuel loads and ambient temperatures, whereas lower temperatures were recorded at high relative humidity. Fire temperatures did not vary with fuel moisture or wind speed. Soil temperatures varied between <79 degrees C and 302 degrees C and were positively correlated with ground-level fire temperatures. Results from the study imply that fuel loads in forested areas have to be reduced to ensure low intensity fires in the dry season. Low fire temperatures would ensure lower mortality of above-ground saplings and minimal damage to root stocks of tree species that would maintain the regenerative capacity of a tropical dry forest subject to dry season wildfires.

Species and acoustic diversity of bats in a palaeotropical wet evergreen forest in southern India

The Western Ghats of India is among the top 25 biodiversity hotspots in the world. About 43% of the reported 117 bat species in India are found in this region, but few quantitative studies of bat echolocation calls and diversity have been carried out here thus far. A quantitative study of bat diversity was therefore conducted using standard techniques, including mist-netting, acoustical and roost surveys in the wet evergreen forests of Kudremukh National Park in the Western Ghats of Karnataka. A total of 106 bats were caught over 108 sampling nights, representing 17 species, 3 belonging to Megachiroptera and 14 to Microchiroptera. Acoustical and roost surveys added three more species, two from Microchiroptera and one from Megachiroptera. Of these 20 species, 4 belonged to the family Pteropodidae, 10 to Vespertilionidae, 3 to Rhinolophidae, 2 to Megadermatidae and 1 to Hipposideridae. We recorded the echolocation calls of 13 of the 16 microchiropteran species, of which the calls of 4 species (Pipistrellus coromandra, Pipistrellus affinis, Pipistrellus ceylonicus and Harpiocephalus harpia) have been recorded for the first time. Discriminant function analyses of the calls of 11 species provided 91.7% correct classification of individuals to their respective species, indicating that the echolocation calls could be used successfully for non-invasive acoustic surveys and monitoring of bat species in the future.

Combining data sets of satellite-retrieved products for basin-scale water balance study: 2. Evaluation on the Mississippi Basin and closure correction model

In this study, we applied the integration methodology developed in the companion paper by Aires (2014) by using real satellite observations over the Mississippi Basin. The methodology provides basin-scale estimates of the four water budget components (precipitation P, evapotranspiration E, water storage change Delta S, and runoff R) in a two-step process: the Simple Weighting (SW) integration and a Postprocessing Filtering (PF) that imposes the water budget closure. A comparison with in situ observations of P and E demonstrated that PF improved the estimation of both components. A Closure Correction Model (CCM) has been derived from the integrated product (SW+PF) that allows to correct each observation data set independently, unlike the SW+PF method which requires simultaneous estimates of the four components. The CCM allows to standardize the various data sets for each component and highly decrease the budget residual (P - E - Delta S - R). As a direct application, the CCM was combined with the water budget equation to reconstruct missing values in any component. Results of a Monte Carlo experiment with synthetic gaps demonstrated the good performances of the method, except for the runoff data that has a variability of the same order of magnitude as the budget residual. Similarly, we proposed a reconstruction of Delta S between 1990 and 2002 where no Gravity Recovery and Climate Experiment data are available. Unlike most of the studies dealing with the water budget closure at the basin scale, only satellite observations and in situ runoff measurements are used. Consequently, the integrated data sets are model independent and can be used for model calibration or validation.

A Comparison of Machine Learning Techniques for Modeling River Flow Time Series: The Case of Upper Cauvery River Basin

Models of river flow time series are essential in efficient management of a river basin. It helps policy makers in developing efficient water utilization strategies to maximize the utility of scarce water resource. Time series analysis has been used extensively for modeling river flow data. The use of machine learning techniques such as support-vector regression and neural network models is gaining increasing popularity. In this paper we compare the performance of these techniques by applying it to a long-term time-series data of the inflows into the Krishnaraja Sagar reservoir (KRS) from three tributaries of the river Cauvery. In this study flow data over a period of 30 years from three different observation points established in upper Cauvery river sub-basin is analyzed to estimate their contribution to KRS. Specifically, ANN model uses a multi-layer feed forward network trained with a back-propagation algorithm and support vector regression with epsilon intensive-loss function is used. Auto-regressive moving average models are also applied to the same data. The performance of different techniques is compared using performance metrics such as root mean squared error (RMSE), correlation, normalized root mean squared error (NRMSE) and Nash-Sutcliffe Efficiency (NSE).

Phytoplankton size structure in the southern Bay of Bengal modified by the Summer Monsoon Current and associated eddies: Implications on the vertical biogenic flux

The present study combines field and satellite observations to investigate how hydrographical transformations influence phytoplankton size structure in the southern Bay of Bengal during the peak Southwest Monsoon/Summer Monsoon (July-August). The intrusion of the Summer Monsoon Current (SMC) into the Bay of Bengal and associated changes in sea surface chemistry, traceable eastward up to 90 degrees E along 8 degrees N, seems to influence biology of the region significantly. Both in situ and satellite (MODIS) data revealed low surface chlorophyll except in the area influenced by the SMC During the study period, two well-developed cydonic eddies (north) and an anti-cyclonic eddy (south), closely linked to the main eastward flow of the SMC, were sampled. Considering the capping effect of the low-saline surface water that is characteristic of the Bay of Bengal, the impact of the cyclonic eddy, estimated in terms of enhanced nutrients and chlorophyll, was mostly restricted to the subsurface waters (below 20 m depth). Conversely, the anti-cyclonic eddy aided by the SMC was characterized by considerably higher nutrient concentration and chlorophyll in the upper water column (upper 60 m), which was contrary to the general characteristic of such eddies. Albeit smaller phytoplankton predominated the southern Bay of Bengal (60-95% of the total chlorophyll), the contribution of large phytoplankton was double in the regions influenced by the SMC and associated eddies. Multivariate analysis revealed the extent to which SMC-associated eddies spatially influence phytoplankton community structure. The study presents the first direct quantification of the size structure of phytoplankton from the southern Bay of Bengal and demonstrates that the SMC-associated hydrographical ramifications significantly increase the phytoplankton biomass contributed by larger phytoplankton and thereby influence the vertical opal and organic carbon flux in the region. (C) 2014 Elsevier B.V. All rights reserved.

Cryogenian magmatism and crustal reworking in the Southern Granulite Terrane, India

Understanding Neoproterozoic crustal evolution is fundamental to reconstructing the Gondwana supercontinent, which was assembled at this time. Here we report evidence of Cryogenian crustal reworking in the Madurai Block of the Southern Granulite Terrane of India. The study focuses on a garnet-bearing granite-charnockite suite, where the granite shows in situ dehydration into patches and veins of incipient charnockite along the contact with charnockite. The granite also carries dismembered layers of Mg-Al-rich granulite. Micro-textural evidence for dehydration of granite in the presence of CO2-rich fluids includes the formation of orthopyroxene by the breakdown of biotite, neoblastic zircon growth in the dehydration zone, at around 870 degrees C and 8kbar. The zircon U-Pb ages suggest formation of the granite, charnockite, and incipient charnockite at 836 +/- 73, 831 +/- 31, and 772 +/- 49Ma, respectively. Negative zircon epsilon Hf (t) (-5 to -20) values suggest that these rocks were derived from a reworked Palaeoproterozoic crustal source. Zircon grains in the Mg-Al-rich granulite record a spectrum of ages from ca. 2300 to ca. 500Ma, suggesting multiple provenances ranging from Palaeoproterozoic to mid-Neoproterozoic, with neoblastic zircon growth during high-temperature metamorphism in the Cambrian. We propose that the garnet-bearing granite and charnockite reflect the crustal reworking of aluminous crustal material indicated by the presence of biotite+quartz+aluminosilicate inclusions in the garnet within the granite. This crustal source can be the Mg-Al-rich layers carried by the granite itself, which later experienced high-temperature regional metamorphism at ca. 550Ma. Our model also envisages that the CO2 which dehydrated the garnet-bearing granite generating incipient charnockite was sourced from the proximal massive charnockite through advection. These Cryogenian crustal reworking events are related to prolonged tectonic activities prior to the final assembly of the Gondwana supercontinent.

Regeneration of Juvenile Woody Plants after Fire in a Seasonally Dry Tropical Forest of Southern India

Woody tree species in seasonally dry tropical forests are known to have traits that help them to recover from recurring disturbances such as fire. Two such traits are resprouting and rapid post-fire growth. We compared survival and growth rates of regenerating small-sized individuals (juveniles) of woody tree species after dry season fire (February-March) at eight adjacent pairs of burnt and unburnt transects in a seasonally dry tropical forest in southern India. Juveniles were monitored at 3-mo intervals between August 2009 and August 2010. High juvenile survivorship (>95%) was observed in both burnt and unburnt areas. Growth rates of juveniles, analyzed at the community level as well as for a few species individually (especially fast-growing ones), were distinctly higher in burnt areas compared to unburnt areas after a fire event, particularly during the pre-monsoon season immediately after a fire. Rapid growth by juveniles soon after a fire may be due to lowered competition from other vegetative forms such as grasses, possibly aided by the availability of resources stored belowground. Such an adaptation would allow a juvenile bank to be retained in the understory of a dry forest, from where individuals can grow to a possible fire-tolerant size during favorable conditions.

Probable maximum precipitation estimation for catchments in Mahanadi river basin

Probable maximum precipitation (PMP) is a theoretical concept that is widely used by hydrologists to arrive at estimates for probable maximum flood (PMF) that find use in planning, design and risk assessment of high-hazard hydrological structures such as flood control dams upstream of populated areas. The PMP represents the greatest depth of precipitation for a given duration that is meteorologically possible for a watershed or an area at a particular time of year, with no allowance made for long-term climatic trends. Various methods are in use for estimation of PMP over a target location corresponding to different durations. Moisture maximization method and Hershfield method are two widely used methods. The former method maximizes the observed storms assuming that the atmospheric moisture would rise up to a very high value estimated based on the maximum daily dew point temperature. On the other hand, the latter method is a statistical method based on a general frequency equation given by Chow. The present study provides one-day PMP estimates and PMP maps for Mahanadi river basin based on the aforementioned methods. There is a need for such estimates and maps, as the river basin is prone to frequent floods. Utility of the constructed PMP maps in computing PMP for various catchments in the river basin is demonstrated. The PMP estimates can eventually be used to arrive at PMF estimates for those catchments. (C) 2015 The Authors. Published by Elsevier B.V.

Use of Data Driven Techniques for Short Lead Time Streamflow Forecasting in Mahanadi basin

Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

Stable isotope evidence for ca. 2.7-Ga-old Archean cap carbonates from the Dharwar Supergroup, southern India

Carbon isotope compositions of carbonate rocks from similar to 2.7-Ga-old Neoarchean Vanivilas Formation of the Dharwar Supergroup presented earlier by us are re-evaluated in this study, besides oxygen isotope compositions of a few silica dolomite pairs. The purpose of such a revisit assumes significance in view of recent field evidences that suggest a glaciomarine origin for the matrix-supported conglomerate member, the Talya conglomerate, which underlies the carbonate rocks of the Vanivilas Formation. An in-depth analysis of carbon isotope data reveals preservation of their pristine character despite the rocks having been subjected to metamorphism to different degrees (from lower greenschist to lower amphibolite facies). The dolomitic member of Vanivilas Formation of Marikanive area is characterized by highly depleted delta C-13 value (up to -5 parts per thousand VPDB) and merits as the Indian example of ca. 2.7-Ga-old cap carbonate. This inference is further supported by estimated low temperature of equilibration documented by a few silica dolomite pairs from the Vanivilas Formation collected near Kalche area. These pairs show evidence for oxygen isotopic equilibrium at low temperatures (similar to 0-20 degrees C) with depleted water (delta O-18 = -21 parts per thousand to -15 parts per thousand VSMOW) of glacial origin. We propose that the mineral pairs were deposited during the deglaciation period when the ocean temperature was in its gradual restoration phase. The dolomite of Marikanive area is the first record of cap carbonates from the Indian subcontinent with Neoarchean antiquity.

Distribution, relative abundance, and conservation status of Asian elephants in Karnataka, southern India

Karnataka state in southern India supports a globally significant and the country's largest population of the Asian elephant Elephas maximus. A reliable map of Asian elephant distribution and measures of spatial variation in their abundance, both vital needs for conservation and management action, are unavailable not only in Karnataka, but across its global range. Here, we use various data gathered between 2000 and 2015 to map the distribution of elephants in Karnataka at the scale of the smallest forest management unit, the `beat', while also presenting data on elephant dung density for a subset of `elephant beats.' Elephants occurred in 972 out of 2855 forest beats of Karnataka. Sixty percent of these 972 beats and 55% of the forest habitat lay outside notified protected areas (PM), and included lands designated for agricultural production and human dwelling. While median elephant dung density inside protected areas was nearly thrice as much as outside, elephants routinely occurred in or used habitats outside PM where human density, land fraction under cultivation, and the interface between human-dominated areas and forests were greater. Based on our data, it is clear that India's framework for elephant conservation which legally protects the species wherever it occurs, but protects only some of its habitats while being appropriate in furthering their conservation within PM, seriously falters in situations where elephants reside in and/or seasonally use areas outside PAs. Attempts to further elephant conservation in production and dwelling areas have extracted high costs in human, elephant, material and monetary terms in Karnataka. In such settings, conservation planning exercises are necessary to determine where the needs of elephants or humans must take priority over the other, and to achieve that in a manner that is based not only on reliable scientific data but also on a process of public reasoning. (C) 2015 Elsevier Ltd. All rights reserved.

Differences in host species relationships and biogeographic influences produce contrasting patterns of prevalence, community composition and genetic structure in two genera of avian malaria parasites in southern Melanesia

1. Host-parasite interactions have the potential to influence broadscale ecological and evolutionary processes, levels of endemism, divergence patterns and distributions in host populations. Understanding the mechanisms involved requires identification of the factors that shape parasite distribution and prevalence. 2. A lack of comparative information on community-level host-parasite associations limits our understanding of the role of parasites in host population divergence processes. Avian malaria (haemosporidian) parasites in bird communities offer a tractable model system to examine the potential for pathogens to influence evolutionary processes in natural host populations. 3. Using cytochrome b variation, we characterized phylogenetic diversity and prevalence of two genera of avian haemosporidian parasites, Plasmodium and Haemoproteus, and analysed biogeographic patterns of lineages across islands and avian hosts, in southern Melanesian bird communities to identify factors that explain patterns of infection. 4. Plasmodium spp. displayed isolation-by-distance effects, a significant amount of genetic variation distributed among islands but insignificant amounts among host species and families, and strong local island effects with respect to prevalence. Haemoproteus spp. did not display isolation-by-distance patterns, showed marked structuring of genetic variation among avian host species and families, and significant host species prevalence patterns. 5. These differences suggest that Plasmodium spp. infection patterns were shaped by geography and the abiotic environment, whereas Haemoproteus spp. infection patterns were shaped predominantly by host associations. Heterogeneity in the complement and prevalence of parasite lineages infecting local bird communities likely exposes host species to a mosaic of spatially divergent disease selection pressures across their naturally fragmented distributions in southern Melanesia. Host associations for Haemoproteus spp. indicate a capacity for the formation of locally co-adapted host-parasite relationships, a feature that may limit intraspecific gene flow or range expansions of closely related host species.

Crustal Evolution of Kolli-Massif, Southern India

Southern India is a collage of numerous crustal fragments formed since the Archean (2500 Ma ago) and reworked several times during the geological history. A close look at these terrains provides a window to understand the crustal evolutionary processes experienced by the continental crust in the past, such as crustal growth (formation of crust through addition of new magma) and crustal reworking (modification of an already existing crust). Here we discuss the evolutionary history of such a crustal fragment from the Southern Granulite Terrain (SGT) in peninsular India, namely Kolli-massif. Geology, structural deformation through time, and the implications in crustal assembly of southern India are exponded.