technology for natural resources management · the response of a watershed to different...

INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 1, No 4, 2011

© Copyright 2010 All rights reserved Integrated Publishing services Research article ISSN 0976 – 4380

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Micro watershed characterization and prioritization using Geomatics technology for natural resources management

Binay Kumar 1 , Uday Kumar 2 1 Project Leader, Geomatics Solutions Development Group, Centre for Development of

Advanced Computing (CDAC), Pune 2 Head, University Department of Geology, Ranchi University, Ranchi

[email protected]

ABSTRACT

Management of watershed encompasses various activities from watershed delineation to monitoring. The suitability of land for development is not only based on a set of physical parameters (geography/terrain, soils, slopes, forest, geology etc.) of the land but also very much on the economic factors. The cumulative effect of these factors determine the degree of suitability and also helps in further categorization of land into different priority orders for development. Sanjai river watershed is located in the central west part of the Subernarekha basin under Kolhan Division of Jharkhand. The study area is totally rain fed and availability of water for drinking and domestic use is a big problem. The natural recharge process in the area is very poor due to hard compact granite terrain. The response of a watershed to different hydrological processes and its behaviour depends upon various physiographic, hydrogeological and geomorphological parameters. The characterization of a watershed provides an idea about its behaviour. The various parameter characteristics of a watershed behave in more or less perceptible manner.

Watershed prioritization is the ranking of different microwatersheds of a watershed according to the order in which they have to be taken up for development. Holistic integrated planning, involving remote sensing and GIS has been found to be effective in planning for regional development based on watershed approach. Saaty's analytic hierarchy process is a most widely accepted method for scaling the weights of parameters by constructing a pair wise comparison matrix of parameters where entries indicate the strength with which one element dominates over another visàvis the relative criterion.

The pairwise comparison of parameters results into the "importance matrix" which is based on a scale of importance intensities A Composite Suitability Index (CSI) has been calculated for each composite unit by multiplying weightages with rank of each parameter and summing up the values of all the parameters. Categorization of the CSI is achieved by ranging the CSI into classes, where each range indicates the amount of limitation acceptable for each class.

Keywords: Watershed, Composite Suitability Index, Watershed Characterization, Watershed Prioritization, Integration Analysis, Ranking, Importance Matrix



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1. Introduction

Identification of suitable land for development is one of the critical issues of regional planning. The suitability of the land for development, as well as, for ground water occurrence is influenced by climate, physiography, drainage, geology, degree of weathering, etc. The various parameter characteristics of a watershed behave in more or less perceptible manner. Also any change made to factors upstream directly affects the downstream of watershed. A watershed is an area from which runoff, resulting from precipitation, flows past a single point into a large stream, a river, lake or an ocean. While remote sensing can provide a variety of latest and updated information on natural resources, GIS has the capability for captures, storage, manipulation, analysis, retrieval of multiple layer resource information occurring both in spatial and aspatial forms.

The response of a watershed to different hydrological processes and its behaviour depends upon various physiographic, hydrogeological and geomorphological parameters. Though these are watershed specific and thereby unique, the characterization of a watershed provides an idea about its behaviour. Watershed characterization involves measurement of parameters that influence the characteristic behaviour of a watershed whereas analysis aims at the critical study of these parameters to arrive at conclusions on watershed response and behaviour.

The large variety of factors that can affect the behaviour of a watershed fall into two categories, first the permanent characteristics of the drainage basin, such as, its size or drainage density i.e., drainage morphometry and second, transient or variable characteristics, such as the amount of precipitation, type of land use and so on (Sebastian et. al., 1995). Most of these permanent characteristics and some of the parameters from which inferences can be drawn about the transient characteristics can be drawn from remotely sensed data and other ancillary data.

The resource considerations for implementation of watershed management programmes (Dept. of Wasteland Development, 1997) or various other reasons pertaining to administration or even political considerations may limit the implementation to a few watersheds. Even otherwise, it is always better to start management measures from the highest priority microwatershed available. Watershed prioritization is the ranking of different microwatersheds of a watershed according to the order in which they have to be taken up treatment and soil conservation measures (Naik S.D. et. al., 1995).

2. Study Area

Upper Sanjai river watershed is located (Figure 1) in the western part of the Subernarekha basin covering an area of about 893.48 sq. km in the Kolhan Division of Jharkhand. The area is bounded by Latitude 22°25'54.73” N & 22°51'36.11” N and Longitude 85°17'32.53'' E & 85°41'58.35” E and is covered in SOI topographic sheets Nos. 73 F/5, F/6, F/7, F/9 and F/10.



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Figure 1: Location map of the study area

3. Database and Methodology

In the present study various types of data have been used. Both satellite borne remote sensing data and other published maps and reports constitute the database necessary for the interpretation and delineation of various thematic layers and information. Multidate IRS 1D/P6 LISS III data in digital format were used in conjunction with secondary or collateral data.

Basic technical guidelines provided by the Integrated Mission for Sustainable Development (IMSD, 1985) and National (Natural) Resources Information System (NRIS, 2000) have been adopted for delineating various thematic classes. The thematic map depicting the various classes was prepared using digitally enhanced satellite data. ArcINFO software package was used for creation of digital database, data integration and analysis.

3.1 Micro watershed delineation

Watersheds are those areas from which runoff resulting from precipitation, flows past a single point into a large stream a river, lake or an ocean. These are natural hydrologic entities that cover a specific aerial extent of land from which rainwater flows to a defined gully, stream or river of a particular point. The size of the watershed is dependent on the size of interception of the stream or river and the drainage density and its distribution. The drainage network helps in delineation of watershed for a particular river system. The



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Watershed Atlas of India published All India Soil & Land Use Survey, Ministry of Agriculture and Cooperation, Govt. of India (1990) has been referred for delineation up to watershed level. The further classification starting from subwatershed to micro watershed ((Figure 2) is done following the guidelines of Watershed Atlas of India over the drainage network as prepared using SOI toposheets.

Figure 2: Micro Watershed Map

3.2 Watershed Characterization

To characterize the watershed different factors that were taken into consideration may be broadly grouped on the basis of their interrelationship with one another. The natural resources which are taken into consideration are slope, geomorphology, soil and landuse cover. The monitoring of natural resources is a must because the improper and inhuman use has resulted in degradation of these. Although, the natural resources comprise all the parameters that affect the watershed, among the factors that influence the watershed, slope, geomorphology, soil and landuse play significant role.

3.2.1 Landuse/landcover: The different landuse classes (Figure 3) that cause problem in the natural resource management are the existence of wasteland in the area to be taken up for the development purpose. Similarly the depletion of the forest cover, presence of forest blanks in the dense or open forest, presence of scrubs in the larger area, degradation of dense forest into open forest and open into scrubs pose serious problems to the environment.



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3.2.2 Slope: The varying degree of slope leads to severe erosion of land and soil. The effect of slope on geomorphology, soil and land use was studied and a direct relationship was observed. Different percentage slope classes (Figure 4) and their areal extents were calculated at microwatershed level and were assigned class.

3.2.3 Geomorphology: Different geomorphic units, their ground water prospect and proneness to erosion and areal extent were calculated at microwatershed level. Different geomorphic units (Figure 5) based upon their origin and nature was assigned specific classes/ranks.

3.2.4 Soil: As the soils in the study area are very much prone to erosion and have high erodibility, necessary measures are required for their conservation. Different classes of soils (Figure 6), their areal extent and percentage distribution were calculated at micro watershed level and based upon their erodibity were assigned class/ ranks to be taken up for development.

Figure 3: Landuse/Landcover map Figure 4: Slope map

Figure 5: Geomorphological map Figure 6: Soil map



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3.3 Watershed Prioritization

Watershed prioritization is the ranking of different microwatersheds of a watershed according to the order in which they have to be taken up for treatment and conservation measures. A particular microwatershed may get the top priority due to various reasons, but, often, the intensity of land degradation is taken as the basis. The resource considerations for implementation of watershed management programme or various other reasons pertaining to administration or even political considerations may limit the implementation to a few microwatersheds. Even otherwise, it is always better to start management measures from the highest priority micro watershed which makes mandatory to prioritize the microwatershed available.

4. Analysis and Discussion

The assessment of the physical parameters of the land is possible by analysing the slope, soil, geomorphology, land use, terrain parameters etc. and which is very much amenable to GIS analysis. However, the assessments of physical parameters give an indication of the limitation of the land to watershed development and thus in turn, can be used as a "qualitative measure" of the natural aspect of development.

Generally, four zones of suitability / priority delineation can be defined based on the limitations that the land offers to watershed development as follows:

a) Zone 1: Minimal Limitations Suitability for selection is high b) Zone 2: Moderate Limitations c) Zone 3: High Limitations d) Zone 4: Maximal Limitations Suitability for selection is low

The concept of limitation is derived from the quality of land. For example, if the slope (which is one of the land parameters) is high the limitation it offers is more than a land which has gently slope or is flat. This concept is true for all the land parameters that are assessed.

4.1 Suitability Assessment Weighted Indexing Method

There are different ways is which the suitability assessment can be done. There have been studies of suitability assessment employing a "maximization" or "worstcase" model (Space Applications Centre, 1999), where the "worst" parameter determines the suitability. This model is very conservative and also too general in nature because it does not consider the importance of parameter from micro watershed development point of view. As a result, a relatively less important parameter could determine the suitability in the final analysis. This anomaly arises because all parameters are considered to be of equal importance.



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Saaty's Analytic Hierarchy Process (Rao Mukund et. al., 1991) is a most widely accepted method for scaling the weights of parameters by constructing a pair wise comparison matrix of parameters where entries indicate the strength with which one element dominates over another visàvis the relative criterion. The pairwise comparison of parameters results into the "importance matrix" which is based on a scale of importance intensities. The Saaty's scale of importance is shown in Table 1. The importance matrix can then be analyzed by various methods "EigenVector method or "Least Square" method, to arrive at the weightages of each parameter in the matrix. Experimental analysis has shown that the weightages obtained by these two methods are similar and are comparable. However, in the present study, Eigen vector method is employed for obtaining the weights of different parameters.

Table 1: Criteria for Generating Comparison Matrix

4.1.1 Eigen Vector Method

In this method the basic input is the pairwise comparison matrix of n parameters given by the form of

A = [ aij ], where i, j = 1, 2, 3, . . . . . . . , n .. . . . . . .(1)

The matrix A has generally the property of reciprocality and also the consistency. This is mathematically,

aij = 1/a .. . . . . . . (2) and, aij = aik / ajk ………….(3)

Assigned Value Definition Explanation

1 Parameters are of equal importance

Two parameters contribute equally to the objective

3 Parameter j is of weak importance compared to parameter i

Experience and Judgment slightly favour parameter i over j

5 Essential or strong importance of parameter i compared to j

Experience and Judgment strongly favour parameter i over j

7 Demonstrated importance

Criteria i is strongly favoured over j and its dominance is demonstrated in practice

9 Absolute importance The evidence favouring parameter i over j to the highest possible order of affirmation

2,4, 6,8

Intermediate values between two adjacent judgment

Judgment is not precise enough to assign values of 1, 3, 5, 7 and 9



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Thus, multiplying equation (1) with the weighting vector W of (nx1) size yields

(A nI ) W = 0 …………(4)

Where, I is an identity matrix of (n x n).

According to matrix theory, it the comparison matrix A has the property of consistency, the system of equations has trivial solution. The matrix A is, however, a judgment matrix and it may not be possible to determine the elements of A accurately to satisfy the property of consistency. Therefore, it is estimated by a set of linear homogenous equations:

A* W* = λmax W* . . . . . . . (5) Where A* is the estimate of A and W* is the corresponding priority vector and λmax is the largest Eigen value for the matrix A. The equation (3) yields the weightages W which are normalized to 1.

4.1.2 Implementation of the model for Priority Delineation / Suitability Assessment The methodology described above has been implemented for the Upper Sanjai River Watershed to determine the suitability of land for microwatershed development. The methodology for the suitability assessment / prioritization has been actually implemented in the ARC/INFO GIS environment by using the weightages.

4.1.3 Parameters Considered for the Model

The prioritization at microwatershed level for the Upper Sanjai river watershed is based on the following parameters.

1] Landuse/ landcover parameters

For wasteland development (Table 2) i) Gullied land Forest blank ii) Stony waste iii) Wasteland with/without scrubs iv) Sandy area

2] Landuse/ landcover parameters

For forest management (Table 3) i) Forest blank ii) Scrubs iii) Open forest iv) Dense Forest v) Forest plantation



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Table 2: Importance matrix for the suitability analysis / prioritization based on wasteland

Sl. No.

Parameters Gullied land

Stony waste

Wasteland with/without

scrubs

Sandy area

1 Gullied land 1 3 5 5 2 Stony waste 1/3 1 5 5 3 Wasteland

with/without scrubs

1/5 1/5 1 3

4 Sandy area 1/5 1/5 1/3 1

Matrix Consistency:

EV Weights λmax = 4.315 Gullied land = 0.528 Consistency Index = 0.105 Stony waste = 0.305 Consistency Ratio = 0.094 Scrubs = 0.106 Sandy area = 0.061

Table 3: Importance matrix for the suitability analysis / prioritization based on forest degradation

Sl. No. Parameters Forest blank Scrubs Open

forest Dense forest

Plantatio n

1 Forest blank 1 3 5 5 5 2 Scrubs 1/3 1 3 5 5 3 Open forest 1/5 1/3 1 3 5 4 Dense forest 1/5 1/5 1/3 1 1 5 Plantation 1/5 1/5 1/5 1 1

Matrix Consistency:

EV Weights λmax = 5.359 Forest blank = 0.478 Consistency Index = 0.072 Scrubs = 0.265 Consistency Ratio = 0.090 Open forest = 0.145 Dense forest = 0.058 Plantation = 0.054

4.2 Assignment of ranks

After determining the weightages for the parameters, it is necessary to rank each category of the parameters for the suitability assessment. The ranks of the individual categories are



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assigned in such a way that higher the rank, higher is the suitability i.e. higher the priority and lesser are the limitations. Lower is the rank, lower the priority for amelioration and higher are the limitations for development. So, the categories of parameters considered for suitability/priority are studied carefully and arranged in four ranges for the assignments of ranks. The ranks assigned for all the categories related to the different parameters are given in table 4.

Integration analysis has been carried out and a composite watershed development map has been generated. Composite Suitability Indices have been obtained by multiplying weightages with rank numbers of each category and by summing up the values of all categories. The entire area is then divided into four categories based on mean and standard deviation values.

Table 4: Ranking system for the categories under each theme/parameter considered for the Priority delineation

Range of Values Parameter Rank 4 Rank3 Rank 2 Rank1 Slope >15% 1015% 510% <5%

Geomorphology Hilly area Buried Pediments

Buried Pediplains and Pediments

Valley Fills

Soil Red Sandy Red Loamy Red & yellow Laterite

Landuse Wasteland Forest Cropland Built up Area and Waterbodies

Wasteland Gullied Land

Stony Waste Scrubs Sandy area

Forest Forest blank Scrubs Open forest Dense forest and

Plantations

A Composite Suitability Index (CSI) has been calculated for each composite unit by multiplying weightages with rank of each parameter and summing up the values of all the parameters. Categorization of the CSI is achieved by ranging the CSI into classes, where each range indicates the amount of limitation acceptable for each class. Maximum, minimum, average/mean and standard deviation of CSI have been used to categorization.

Four classes have been generated using the following method: Class I: Maximum > CSI >= Minimum+3σ Class II: Minimum+3σ > CSI >= Minimum+2σ Class III: Minimum+2σ > CSI >= Minimum+1σ Class IV: Minimum+1σ > CSI > Minimum

Where σ = Standard deviation.



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Higher the CSI value, higher is the priority for watershed development. Lower the CSI value, lower is the priority for watershed development. Finally, the CSI values of composite coverage have been grouped into four categories of land use suitability for taken up for the development purpose in the watershed tables 5 and 6.

Table 5: Statistics showing number of prioritized microwatersheds to be taken up for development based on Wasteland

Cumulative Weight RANK No. of Watersheds Priority

CSI > 0.6 I 42 HIGH

0.4 < CSI =< 0.6 IV 22

0.2 < CSI =< 0.4 III 19

0.0 < CSI =< 0.2 II 28 LOW

CSI = 0.0 I 12 No action required

Figure 7: Wasteland based Watershed Prioritization

As per the statistics in table 5, out of the total 123 microwatershed in the study area 42 micro watersheds are of the highest priority and 28 microwatersheds are of low priority whereas 12 microwatersheds require no immediate action for development based on wasteland (Figure 7).



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Table 6: Statistics showing number of prioritized microwatersheds to be taken up for development based on forest classes

Cumulative Weight RANK No. of Watersheds Priority

CSI > 6 IV 7 HIGH

4 < CSI =< 6 III 1

2 < CSI =< 4 II 9

0 < CSI =< 2 I 106 LOW

The statistics in table 6 show that forest classes in the study area depleting fast and require immediate action for their conservation. Out of the total 123 microwatershed in the study area 7 micro watersheds are of the highest priority whereas 106 are of low priority (Figure 8).

Figure 8: Watershed Prioritization based on Forest Degradation

5. Conclusion Proper planning of watershed is essential for the conservation of water and land resources i.e. natural resources and their productivity. Characterization and analysis of watershed is a prerequisite for this. Management of watershed encompasses various activities from watershed delineation to monitoring. The concept of limitation is derived from the quality of land. This concept is true for all the land parameters that are assessed. Saaty’s analytic hierarchy process is a most widely accepted method for scaling the weights of parameters



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by constructing a pair wise comparison strength with which one element dominates over another visàvis the relative criterion. The pair wise comparison of parameters result into the ‘importance matrix’ which is based on a scale of importance intensities. The method of suitability assessment is based on a combination of mathematical analysis. An attempt has been made to characterize and prioritize the entire study area at micro watershed level. The severity of the problem have been taken into consideration and based upon the land degradation, they are ranked in order to prioritize.

A particular microwatershed may get the top priority due to various reasons, but, often, the intensity of land degradation is taken as the basis. The assessment of the physical parameters of the land is possible by analyzing the slope, soil, geomorphology, land use, terrain parameters etc. which are very much amenable to GIS analysis. However, the assessment of physical parameters gives an indication of the limitation of the land to watershed development and thus in turn, can be used as a "qualitative measure" of the natural aspect of development.

6. References

1. Department of Wasteland Development (1997), Guidelines for Watershed Development, Ministry of Rural Areas & Employment, Govt. of India.

2. All India Soil & Land Use Survey (1990), Watershed Atlas of India, All India Soil & Land Use Survey, Ministry of Agriculture and Cooperation, Govt. of India.

3. Naik S.D. and Das S.N. (1995), Watershed Prioritization of Dhansiri Catchment, Brahmaputra Basin, using Remote Sensing Techniques, Project Report RSAM/RSAG/WSP/95/1, All India Soil & Land Use Survey and Space Applications Centre (1995)

4. National Natural Resources Management System/ISRO HQ (2000), National (Natural) Resources Information System (NRIS) Node Design and Standards, ISRO HQ, Bangalore

5. National Remote Sensing Agency (NRSA) (1985), Integrated Mission for Sustainable Development Technical Guidelines, Department. of Space, Hyderabad

6. Rao Mukund et. al. (1991), A Weighted Index Model for Urban Suitability Assessment A GIS Approach Case Study for Bombay Metropolitan Region, Project Report SAC/RSA/NRISURIS/TN03/February 1991 – Space Applications Centre (ISRO) & Bombay Metropolitan Region Development Authority



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7. Sebastian M, Jeyaraman V. and Chandrasekhar M. G. (1995), Space Technology Applications for Sustainable Development of Watersheds. Technical Report, ISROHQTR10495. ISRO

8. Space Applications Centre (1999), Remote Sensing and GIS Inputs for the Preparation of Development Plan of PimpriChinchwad Municipal Corporation Area 2018, Technical Report, Space Applications Centre (ISRO) and Pimpri Chinchwad Municipal Corporation

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