Spatial Analysis and Characterisation of Lentic Ecosystems: A Case Study of Varthur Lake, Bangalore

Lentic ecosystems vital functions such as recycling of nutrients, purification of water, recharge of groundwater,augmenting and maintenance of stream flow and habitat provision for a wide variety of flora and fauna along with their recreation values necessitates their sustainable management through appropriate conservation mechanisms. Failure to restore these ecosystems will result in extinction of species or ecosystem types and cause permanent ecological damage. In Bangalore, lentic ecosystems (for example lakes) have played a prominent role serving the needs of agriculture and drinking water. But the burgeoning population accompanied by unplanned developmental activities has led to the drastic reduction in their numbers (from 262 in 1976 to 81). The existing water bodies are contaminated by residential, agricultural, commercial and industrial wastes/effluents. In order to restore the ecosystem, assessment of the level of contamination is crucial. This paper focuses on characterisation and restoration aspects of Varthur lake based on hydrological, morphometric, physical-chemical and socio-economic investigations for a period of six months covering post monsoon seasons. The results of the water quality analysis show that the lake is eutrophic with high concentrations of phosphorous and organic matter. The morphometric analysis indicates that the lake is shallow in relation to its surface area. Socio-economic analyses show dependence of local residents for irrigation, fodder, etc. These analyses highlight the need and urgency to restore the physical, chemical and biological integrity through viable restoration and sustainable watershed management strategies, which include pollution abatement, catchment treatment, desilting of the lake and educating all stakeholders on the conservation and restoration of lake ecosystems.

Aquatic Ecosystems: Conservation, Restoration and Management

Aquatic Ecosystems perform numerous valuable environmental functions. They recycle nutrients, purify water, recharge ground water, augment and maintain stream flow, and provide habitat for a wide variety of flora and fauna and recreation for people. A rapid population increase accompanied by unplanned developmental works has led to the pollution of surface waters due to residential, agricultural, commercial and industrial wastes/effluents and decline in the number of water bodies. Increased demands for drainage of wetlands have been accommodated by channelisation, resulting in further loss of stream habitat, which has led to aquatic organisms becoming extinct or imperiled in increasing numbers and to the impairment of many beneficial uses of water, including drinking, swimming and fishing. Various anthropogenic activities have altered the physical, chemical and biological processes within aquatic ecosystems. An integrated and accelerated effort toward environmental restoration and preservation is needed to stop further degradation of these fragile ecosystems. Failure to restore these ecosystems will result in sharply increased environmental costs later, in the extinction of species or ecosystem types, and in permanent ecological damage.

Reuse of treated sewage in Delhi city: Microbial evaluation of STPs and reuse options

Microbiological quality of the treated wastewater is an important parameter for its reuse. The data oil the Fecal Coliform (FC) and Fecal Streptococcus (FS) at different stages of treatment in the Sewage Treatment Plants (STPs) in Delhi watershed is not available, therefore in the present study microbial profiling of STPs was carried out to assess the effluent quality for present and future reuse options. This Study further evaluates the water quality profiles at different stages of treatment for 16 STPs in Delhi city. These STPs are based on conventional Activated Sludge Process (ASP), extended aeration, physical, chemical and biological treatment (BIOFORE), Trickling Filter and Oxidation Pond. The primary effluent quality produced from most of the STPs was suitable for Soil Aquifer Treatment (SAT). Extended Hydraulic Retention Time (HRT) as a result Of low inflow to the STPS Was responsible for high turbidity, COD and BODs removal. Conventional ASP based STPs achieved 1.66 log FC and 1.06 log FS removal. STPs with extended aeration treatment process produced better quality effluent with maximum 4 log order reduction in FC and FS levels. ``Kondli'' and ``Nilothi'' STPs employing ASP, produced better quality secondary effluent as compared to other STPs based oil similar treatment process. Oxidation Pond based STPs showed better FC and FS removals, whereas good physiochemical quality was achieved during the first half of the treatment. Based upon physical, chemical and microbiological removal efficiencies, actual integrated efficiency (IEa) of each STP was determined to evaluate its Suitability for reuse for irrigation purposes. Except Mehrauli'' and ``Oxidation Pond'', effluents from all other STPs require tertiary treatment for further reuse. Possible reuse options, depending Upon the geographical location, proximity of facilities of potential users based oil the beneficial uses, and sub-soil types, etc. for the Delhi city have been investigated, which include artificial groundwater recharge, aquaculture, horticulture and industrial uses Such as floor washing, boiler feed, and cooling towers, etc. (C) 2009 Elsevier B.V. All rights reserved.

Mahanadi streamflow: climate change impact assessment and adaptive strategies

Impacts of climate change on hydrology are assessed by downscaling large scale general circulation model (GCM) outputs of climate variables to local scale hydrologic variables. This modelling approach is characterized by uncertainties resulting from the use of different models, different scenarios, etc. Modelling uncertainty in climate change impact assessment includes assigning weights to GCMs and scenarios, based on their performances, and providing weighted mean projection for the future. This projection is further used for water resources planning and adaptation to combat the adverse impacts of climate change. The present article summarizes the recent published work of the authors on uncertainty modelling and development of adaptation strategies to climate change for the Mahanadi river in India.

Remote sensing applications in water resources

With the introduction of the earth observing satellites, remote sensing has become an important tool in analyzing the Earth's surface characteristics, and hence in supplying valuable information necessary for the hydrologic analysis. Due to their capability to capture the spatial variations in the hydro-meteorological variables and frequent temporal resolution sufficient to represent the dynamics of the hydrologic processes, remote sensing techniques have significantly changed the water resources assessment and management methodologies. Remote sensing techniques have been widely used to delineate the surface water bodies, estimate meteorological variables like temperature and precipitation, estimate hydrological state variables like soil moisture and land surface characteristics, and to estimate fluxes such as evapotranspiration. Today, near-real time monitoring of flood, drought events, and irrigation management are possible with the help of high resolution satellite data. This paper gives a brief overview of the potential applications of remote sensing in water resources.

Monitoring urbanization and its implications in a mega city from space: Spatiotemporal patterns and its indicators

Rapid and invasive urbanization has been associated with depletion of natural resources (vegetation and water resources), which in turn deteriorates the landscape structure and conditions in the local environment. Rapid increase in population due to the migration from rural areas is one of the critical issues of the urban growth. Urbanisation in India is drastically changing the land cover and often resulting in the sprawl. The sprawl regions often lack basic amenities such as treated water supply, sanitation, etc. This necessitates regular monitoring and understanding of the rate of urban development in order to ensure the sustenance of natural resources. Urban sprawl is the extent of urbanization which leads to the development of urban forms with the destruction of ecology and natural landforms. The rate of change of land use and extent of urban sprawl can be efficiently visualized and modelled with the help of geo-informatics. The knowledge of urban area, especially the growth magnitude, shape geometry, and spatial pattern is essential to understand the growth and characteristics of urbanization process. Urban pattern, shape and growth can be quantified using spatial metrics. This communication quantifies the urbanisation and associated growth pattern in Delhi. Spatial data of four decades were analysed to understand land over and land use dynamics. Further the region was divided into 4 zones and into circles of 1 km incrementing radius to understand and quantify the local spatial changes. Results of the landscape metrics indicate that the urban center was highly aggregated and the outskirts and the buffer regions were in the verge of aggregating urban patches. Shannon's Entropy index clearly depicted the outgrowth of sprawl areas in different zones of Delhi. (C) 2014 Elsevier Ltd. All rights reserved.

Prediction of Land Surface Temperature under Cloudy Conditions using Microwave Remote Sensing and ANN

Land surface temperature (LST) is an important variable in climate, hydrologic, ecological, biophysical and biochemical studies (Mildrexler et al., 2011). The most effective way to obtain LST measurements is through satellites. Presently, LST from moderate resolution imaging spectroradiometer (MODIS) sensor is applied in various fields due to its high spatial and temporal availability over the globe, but quite difficult to provide observations in cloudy conditions. This study evolves of prediction of LST under clear and cloudy conditions using microwave vegetation indices (MVIs), elevation, latitude, longitude and Julian day as inputs employing an artificial neural network (ANN) model. MVIs can be obtained even under cloudy condition, since microwave radiation has an ability to penetrate through clouds. In this study LST and MVIs data of the year 2010 for the Cauvery basin on a daily basis were obtained from MODIS and advanced microwave scanning radiometer (AMSR-E) sensors of aqua satellite respectively. Separate ANN models were trained and tested for the grid cells for which both LST and MVI were available. The performance of the models was evaluated based on standard evaluation measures. The best performing model was used to predict LST where MVIs were available. Results revealed that predictions of LST using ANN are in good agreement with the observed values. The ANN approach presented in this study promises to be useful for predicting LST using satellite observations even in cloudy conditions. (C) 2015 The Authors. Published by Elsevier B.V.