ارزیابی پتانسیل برق آبی کوچک با استفاده از داده های سنجش از راه دور برای توسعه پایدار در هند

India being a developing country has witnessed a rapidly growing energy needs owing to fast industrialization. Sustainable and qualitative growth for developing economics and habitat requires increased energy input from various resources while maintaining balance in the ecosystem during exploitation. Paper discusses state of the resource potentials, achievements and various issues related to the power generation in India. The growing concern over environmental degradation caused by fossil fuel based systems, opposition to large hydropower projects on grounds of displacement of land and population, environmental problems with nuclear fuel based systems and the ever-rising shortage of power highlights the need for tapping alternate energy sources for power generation. Amongst the alternate sources utilization of hydropower on a smaller scale (small, mini and micro hydropower) has become the thrust area for sustainable growth in the power sector. Hydropower is an economical and environmentally clean source of renewable energy abundantly available in hilly regions of India. Hydropower stations have an inherent ability for instantaneous starting, stopping, load variations, etc., and help in improving the reliability of power system. Huge hydropower potential in India, yet to be explored is located at inaccessible mountainous region. However, development of this potential is challenging due to difficult and inaccessible terrain profile. Paper presents application of remote sensing data for identification and selection of probable site for hydropower projects. The algorithm for identification and assessment of water resources and its perennial is developed in Visual Basic (VB) platform and it is successfully applied for IRS-1D, LISS III Geo-coded False Color Composite (FCC) satellite image for plain as well as hilly and mountainous regions. Classification of satellite image in to different objects is modeled as the task of clustering based on the intensity of R-G-B values of pixels. Results obtained are presented and compared with the Survey of India Toposheets (53K/2, 53K/3 and 53J/16). Use of Remote sensing data provides a scientific method of hydropower identification and assessment.

India being a developing country has witnessed a rapidly growing energy needs owing to fast industrialization. Primary energy demands are met largely from conventional energy sources; coal, oil, natural gas, hydropower resources, etc. Hydroelectricity represents a large-scale alternative to fossil fuel generation, contributing only very small amount to green house gas emissions and other atmospheric pollution. Hydropower is a renewable and sustainable energy source to meet global challenges (Frey and Linke, 2002) but developing the remaining hydroelectric potential in a sustainable way offers many challenges (Balsar, 2002). Information in detailed project reports based up on survey and investigations works for a potential site are not adequate and reliable at the time of actual implementation. (Yogendra Prasad, 2000). Present task for the energy sector is to satisfy the growing demand for electric energy of the community while conserving resources for the benefit of future generation. Sustainable and qualitative growth for developing economics and habitat requires increased energy input from renewable sources, while maintaining balance in the ecosystem during exploitation (Palanichamy et al., 1999). The growing concern over environmental degradation caused by fossil fuel based systems, environmental problems with nuclear fuel based systems, opposition to large hydropower projects on grounds of displacement of land and population, and the ever-rising shortage of power have highlighted the need for development of new and alternate energy sources such as, small hydropower, ocean energy, solar energy, biomass, biogas, wind power, etc. Of these small hydropower is the most attractive source of energy because of its inherent advantages such as, flexibility of utilization, pollution free generation and non-inflationary tendencies after completion. The small hydropower technology is extremely robust and systems can last for 50 years or more with little maintenance. Small hydropower has a key role to play in meeting the challenges by reduction in carbon-dioxide (CO2) emissions (Tondi and Chiaramonti, 1999). Even many countries have thought of making big business by establishing small hydropower projects (Moxon, 1999). There are many hilly or mountainous regions of the country where the grid will probably never reach, but which have sufficient hydro resources to meet basic domestic and cottage industry needs of the local populations. In order to exploit the balance hydro potential to the full extent, it is necessary to adapt to new technologies such as Satellite image processing for planning, evaluation and implementation of hydro projects. Satellite Imagery has been available since the early 1970s, but is often overlooked as a powerful and cost effective tool in hydropower assessment and development. Potential uses of remote sensing is gaining importance in resource planning and management in various fields such as, ground water exploitation (Rao and Mohan, 1988), mapping of resources estimation of run off models, observation of water levels in channels (Al Khudhairy et al., 2002). Assessment of rural land use classification, (Adinarayana and Krishna, 1996; Chen and Stow, 2003). Attempt has been initiated to estimate soil erosion and slope profile of the land from the contour details (Mizukoshi and Aniya, 2002). The scope of the technology at present is limited to the study of area related parameters supported by field data. However, there are not many studies, which provide clearly the integrated application in hydropower development in particular hilly areas. In the proposed methodology the satellite image obtained from IRS-1D LISS-III is used for identification of water resources and neighboring objects such as forest/ vegetation, snow, inhabitation patterns, etc., which are the important parameters for selection of hydropower site. Though commercially available softwares such as, ARC/INFO, MAP/INFO, GEOMEDIA, IDRISI, ERDAS Imagine, MIKE BASIN, etc. more powerful and have greater flexibility, their prohibitive cost prevents developing countries from deploying them at the end user level. This paper describes a methodology for extraction of information from the remote sensing data for mapping of water resources and its perennial for a plain as well as hilly and mountainous region in relatively more comprehensive and scientific method.

Development of small hydropower projects can be an important contributor to meet the local needs of the people in remote and hilly area of the country and will enhance the quality of life. These projects benefits in terms of ease of smaller investments, shorter period for planning and construction, acquire smaller area, use of local labor and material and cheaper generation cost as compared to other power projects. As the number of sites for small hydropower potential are in the order of 420 development of database for the sites on a scientific basis will fasten the process of decision-making and implementation. The methodology presented in the paper demonstrates a systematic and comprehensive computational approach to extract information for identification and assessment of water resources and its associates such as inhabitation and settlement pattern, forest and vegetation coverage, snow coverage and selection of probable sites for small hydropower projects, etc. from satellite image in a scientific manner. Although cost comparisons of the proposed methodology with conventional methods of surveying is not presented in this paper, it is expected that saving of manpower and time required for surveying and updating the information of the potential sites will have significant impact on the cost. Manual surveys and site selection for pre-feasibility report are not only time consuming but also requires large manpower due to the undulating topography, dense forest cover and bad climatic conditions. Work can be further extended for development of regional flow duration model.