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GIS in Small Hydro Plannning Resource Management

Arun K. Saraf
Department of Earth Sciences, Alternate Hydro Energy Centre
University of Roorkee, Roorkee

Energy is one of the main basic inputs for the accelerated economic development. Small hydro power is probably the oldest and yet the most reliable and environment friendly source of all renewable energy, with bulk of its potential yet to be harnessed in many countries including India. Though hydro power development started with small units of 100 KW and more in the beginning, the attention was diverted to harnessing medium and major hydro because their comparative economics. However continous oil crunch has forced the attention of the concerned for harnessing small hydro at the toe of existing dams, at canal drops and exploiting hill streams to supplement the energy generation. Being environmentally benign and having small gestation period has led many countries to harness these resources in concerted manner with China in the forefront.

The integrated approach of GIS and Remote Sensing is being is being recognised universally as an unique highly effective and extremely versatile technology for evaluation, management and monitoring of natural resources and environment. With the concept of multidisciplinary integrated approach got an impetus in monitoring and management of resources and environment. Through, aerial photography, the forerunner of present day satellite remote sensing, has been in vogue for a very long time, however the real spurt in the worldwide usage of the technology came in the launch of Landsat series of satellites, the first of which as put in orbit in 1972. The real advantage of staellite remote sensing system is evident from the fact that they provide a vantage point in space to study the earth and its environment and provide a unique opportunity for inventoring, mapping, and monitoring. Data available from various operational remote sensing satellite are improving in terms of spatial, spectral and temporal resolutions. After alunch of IRS-1C in December 1995, now 5.6m spatial resolution data of any part of the earth can be acquired (Saraf, 1997; Saraf, Kumar 1997). Few potential uses of GIS and RS in SHP planning and resource management have been discussed by Jagdeesha and Adiga (1997) and Rajpal and Mettle (1997) Kulkarni et al., (1997) discussed stream flow simulation study in snow covered areas for estimation of hydropower potential using remote sensing data. Faucher et. Al. (1993) have developed a hydraulic model designed to make use of remote sensing and GIS in SHP planning.

However, there are not many studies which provide clearly the integrated application of GIS and RS in SHP and particularly in hilly areas such as the Himalayas. The present article brings some applications of integrated GIS and RS in SHP planning and development.

Any study pertaining to the environs of the developmental activity must encompass spatial, dynamic and temporal attributes of the environment to obtain comprehensive and reliable results. The simplest way of finding out changes over a period of time is to compare remotely sensed temporal data and demarcate the changed areas using either visual or digital analysis techniques. Remote sensing data can be used to show the quantity and pattern of deforestation, current and historical land use, identify load centres and larger streams, to locate rocky and erosion prone area, and to provide a foundation upon which all other digital data can be georefrenced in the GIS (Rajpal and Mettel, 1997) . Remote sensing data particularly from IRS-1C PAN sensor can also be utilized to generate digital elevation model (DEM) to further support SHP planning and development, however, Himalayas frequent cloud and snow covers poses some problems in acquiring data sets. RS data can also be utilised to assess the positive impacts associated with the development of SHP in the Himalayas, where deforestation is taking place at an alarming rate.

GIS have become of increasing significance in recent years. One main reason for this in the field of SHP is the need to compare a great number of area-related data describing the natural resources and environment. Since GIS can be used to couple area-related data will their attributes, and can overlay these, they represent highly efficient instruments for such planning tasks.

UNDP-GEF-Hilly Hydro Project Experience
In the UNDP-GEF-Hilly Project (UNDP-GEF-HHP) about six hundred Survey of India (SOI) toposheets of 1:50,000 scale were scanned manually about 1700 potential small hydro sites based on perennial channel (>5.0 km)l, catchment area (>10km2), accessibility etc. criteria were identified. All drawing of such sites contain various attribute information as show in Table 1. Many of the information which collected / retrieve from SOI toposheets were utilized for potential head and regional flow duration curves determinations. All the attribute information were computerised / fed into the Lotus spreadsheet programms.

One of the objective of the UNDP-GEF-HHP was to prepare Zonal plan with maps of all thirteen states in order to identify potential clusters for development purpose. It is general belief that if potential sites form clusters than development of such clusters would be preferred by the developers rather than having scattered sites. To achieve this goal, SOI 1:1,000,000 scale map were digitized using ILWIS GIS software (then available with authors). During digitization various information such as river network (all blue lines in SOI maps), state and district boundaries, rail and road network and location of major towns, graticules (latitude and longitude) which were useful for planning and development were digitized and kept in geographic co-ordinate system for further analysis and utilization in GIS . On the base map as discussed above all potential sites location (main channel meeting point with the main river) were plotted in order to prepare cluster maps for all thirteen states. Such maps have been utilized to identify cluster of potential SHP.

Table 1 Showing details of information parameters of catchment extracted form SOI Topographic maps under UNDP-GEF-HHP.

S. No. Information/parameters of cathllinformation/parameters of catchment
1 SOI toposheets references
2 Name of the stream as mentioned in the SOI toposheet
3 Name of river basin in which potential sites exists
4 Catchment area (in Km2) measured using Planimeter
5 Length of main channel (in Km) measured using Rotometer
6 Catchment perimeter (in Km) measured using Planimeter
7 Highest elevation point of the catchment (in meter above msl)
8 Elevation at stream meeting point with the main river (in meter above msl
9 Stream meeting point coordinates (Latitude and longitude) with the main river (in degree and minutes)
10 Information about the snow / glacier/ rain fed of the catchment ( it is possible to identify glaciers and snow covered areas in the SOI toposheets)
11 Name of the state in which the potential catchment is situated
12 Name of the district in which the potential catchment is situated.
13 Major contour lines cutting the main channel near the main river meeting points were also marked I order to extract information regarding available hydraulic head for power generation
14 Major roads available near the potential site
15 Locations of villages and town were also marked in all drawings to have an idea about the load/power consumption centres.
16 Latitude and longitude (in degree and minutes) on all sides of the drawing

Figure 1

Seismicity also plays important role in SHP planning and development. Separate maps containing epicentre locations of all earthquakes (>4.0 magnitude) occurred after 1928 (information was obtained from United State Geological Survey) were also plotted (Figure 1) on the digital base map in GIS. Various seismic zones relevant with different states were also retrieved from Zoning Map of India and overlaid on seismic maps prepared under this project. A combined sets of maps were also prepared under this project. A combined sets of maps were also prepared for all thirteen sates containing base map, potential SHP locations and earthquakes epicentres (Figure 2). The main purpose of this was to provide information about the coincidence of potential SHP cluster with the earthquake epicentre locations, so that necessary.

Figure 2

Precautionary / remedial measured during design of the project can be considered and appropriately incorporated. A quantitative analysis based on spatial random distribution vs nearest – neighbour was also performed using SHP cluster maps and earthquake epicentre maps. This analysis provides further support to quantify cluster identification process (Table 2a & 2b).

Table 2 (a): Quantitative analysis of clustering phenomenona using mean Distance to Nearest Technique (Uttar Pradesh: Potential Sites)

Order Observed value Assumed with CSR*
1 554.03 7701.77
2 1286.60 11552.65
3 1713.89 14440.81
4 2276.63 16846.85
5 2679.67 18954.05
6 3080.90 20848.68

Table 2(b): Quantitative analysis of clustering phenomena using mean distance to Nearest Neighbour technique (Uttar Pradesh: Potential Sites)

Order Observed value Assumed with CSR*
1 1927.13 3511.79
2 2153.82 5267.68
3 2316.77 6584.60
4 2486.02 7681.69
5 2608.62 8642.51
6 2779.82 9506.41

Figure 3

If the mean distance for the data set is much smaller than the one for CSR (COMPLETE State Randomness), the points tend to cluster.

Geological maps containing lithological and major structural information were also prepared digitally, in order to utilise these maps along with Potential SHP and earthquake epicentre locations for better planning and development (Figure 3). Digital base map and all potential site attribute information were integrated in the SPANS GIS to perform various types of queries / questions provided by the users / potential developers. The major advantage of such integrated GIS spatial database is that any new and relevant information with individual SHP can be brought into the system and further improved analysis can be performed with minimum efforts (Figure 4).

Figure 4

Analysis of Remote sensing data
Initially it was thought that various information such as catchment boundaries, main channe, habitation, concentration, road network etc. can directly be gathered from remote sensing data, however, later on it was realised that the data available from IRS-1A, 1B (LISS-III) sensors are not good enough for all requisite parameters for identification and confirmation of potential small hydro site . Though it is not difficult to identify catchment boundary and main channel in the remote sensing data in order to have other information related with small hydro, particulary for slope along main channel for potential head identification, name of the channel, location and name of the villages etc. Topographical maps of the area have to be referred and hence, it was decided to use remote sensing data of only those areas for which SOI 1:50,000 toposheets were not available.

It is true that in last two decades remote sensing has a powerful tool for any work related with natural resources and environment, however, in the present project the study area coverage was enormous and complete satellite coverage would require more than 200-LISS-II scenes. Further, the study area is an high altitude terrain, and hence perennial cloud and associated shadow problems and snow cover makes it difficult to get cloud-free and snow-free scenes.

GIS application in alternate sites identification
As discussed above that GIS is a very powerful analysis and data management systemand can also be utilized for various purposed e. g. spatial and non-spatial analysis cluster analysis, alternate site selection etc. Alternate site selection analysis using GIS has been performed in a sample area in Darjeeling tea estate area (Rungsun Khola catchment). Contour information using SOI 1:50,000 topographic maps were digitized and DEM of the Rungsung Khola has been overlaid on the DEM. Some proposed channels within one tea estate boundary were also overlaid on the DEM and drainage information. This overlay procedure provided slope information / available head along the Rungsung Khola. Applying certain constrains four alternate sites were selected (Table 3) which provides various options and available potential power etc. Using DEM catchment characterization has been performed and catchment boundary, stream slope calculation were determined .

Table 3: Various alternatives are provided on GIS based analysis for SHP planning purposes in Rungsung Khola catchment of Darjeeling tea estate area

Rungsuns Khola-I Discharge = 0.5 Cumec

Alternative Channel Length (Km) Penstock (m) Head(m) Power(kw)
1 1.50(Ch-1) 1.25 140 490
2 1.75(Ch-2) 0.50 100 350

Rungsung Khola-II Discharge=0.3 cumec

Alternative Channel Length (Km) Penstock (m) Head (m) Power (kw)
1 0.75 (Ch-3) 1.25 140 490
2 0.65 (Ch-4) 0.50 100 350

Combined (Khola-I + Khola-II)

Alternative Channel Length (Km) Penstock (m) Head(m) Power(kw)
1 2.25 (Ch1+3) 2.5 480 980
2 1.75 (Ch2+4) 1.0 200 700

As discussed above that integrated approach of GIS and RS can play very important role in the field of SHP planning and development. With the development and availability of fast and efficient computer and hardware and software GIS and RS tools are going to have more vital roles in natural resources development and environment. The spatial database which has been developed under the UNDP-GEF-HPP programme can further be augumented with new sets of data on meteorological, socio-economic and environment to support planning and decision making processes.

The author wish to acknowledge with gratitude about the cooperation received from the faculty and staff of AHEC, DES, CED, and NIH for conducting an study under an assignment from UNDP-GEF-Hilly Hydro Project, Ministry of Non-conventional Energy Sources, Govt. of India. The authors thanks for the kind permission to UNDP-GEF HH Project and Director AHEC for allowing the presentation of the study.


  • Fucher, C., P. spal, Adamowski, S. Enns, K. D. harvey, R. Leconte, D. W. Mullins, P. Tang and R. Hudson (1993), A hydrioigic model designed to make use of remotely sensed and GIS data, Geographic Information Systems and Water Resources : American Water Resources Association, March 1993, pp.231-239.
  • Jagadeesha, C. J., and S Adiga, (1997), some aspectsof selection of small hydro project sites using remote sensingand GIS, First international conference on Frenewable Energy-small Hydro, 3-7 Feb. 1997, Hyderbad, India pp 381-391.
  • Kulkarni, A. V., S. S. Randhawa and R. K. Sood, (1997), A, Stream flow Simulation model in snow covered areas to estimate hydro-power potential; a case study of Malana Nala, H. P. First International Conference on Renewable Energy-smal Hydro, 3-7 Feb, 1997, Hyderabad, India pp 761-770.
  • Rajpal, A. K. and C. Mettel. (1997), tools to benefit small hydro development First International Conference on Renewable Energy-small Hydro, 3-7 Feb, 1997, Hyderabad, India, (handouts during the conference).
  • Saraf, A. K. (1997), Integrated and remote sensing and GIS technologies for environmental impact assessment of mining project, proceedings of the V-Annual mines environment and Mineral Conservation Week 1996-97, pp 135-142.
  • Saraf, A. K. and A. Kumar (1997), Remote ssensing and GIS application in small hydro projects planning and development, Proceedings of International Conference on Small Hydro Power System, 13-14 March 1997, British Council Division, New Delhi.