GIS based diagnostic analysis of irrigation system performance assessment of Bhadra command area at disaggregated level
Institute of Remote Sensing, Anna University, Chennai
Dr. M. Karmegam
Center for Water Resources,Anna University,Chennai
Dr. K. Venugopa1
Institute of Remote Sensing, Anna University, Chennai
Satellite remote sensing (SRS) and geographic information (GIS) techniques for improved water management in canal irrigation schemes. The Bhadra command area was brought under NWMP(National water management project) to improve agricultural productivity and farm income through a predictable, equitable and reliable irrigation service. Satellite remote sensing technique has been applied to historic and 1995 Rabi season data by National Remote Sensing Agency to generate primary data on irrigated area, cropping pattern and crop yield at disaggregated level and to access the improvement in agricultural productivity and water management after MWMP implementation. The GIS technique helps in integration of satellite and ground information to evaluate the system performance and to diagnose the inequality in the performance to aid in improving the water management.
The primary objective is to diagnose the factors for poor performance of selected distributaries using satellite data and s ground data collected by specially designed sample survey and to improve performance by prescribing corrective measures. The distributaries 9A, 12 and 15 of Malabennur division of Bhadra project in Karnataka state covering about 2350 ha area, is considered for this study. The performance of 12th distributory is good whereas the other two were poor performing. Hence to find the causative factors for poor performance were studied in comparison with a good performing area.
The satellite inputs (crop map and condition map) geometrically corrected wit respect to topographic maps are generated with ARIES and EASI/PACE software and transported to PAMAP environment. The revenue survey map in 1:8000 scale is photographically reduced to 1:16000 scale, digitized, edited and corrected with respect to top map and satellite imagery. Conducting sample survey designed for this purpose and compiled in Dbase collects the ground data for the analysis of identified problem distributaries. The system performance of the problem distributaries are characterized based on satellite reported acreage and yield gaps and analyzed with reference to ground sample survey data. The diagnostic analysis of the problem distributaries is carried out on the aspects of irrigation, agriculture and socio-economic. A questionnaire to this effect was designed and the information collected from the ground was organized and analyzed in the GIS. The causative factors are identified and prioritized for corrective measures to ensure better performance within the framework of NWMP. The analysis is performed by comparing the good with the bad performing distributaries.
The physical and socio-economic data were interpolated with different considerations and methods and analyzed. A Conjunctive analysis of remote sensing- derived, irrigation, agricultural and socio-economic data was attempted. Various causative factors pertaining to all these three activities were identified, ranging from poor physical condition, improper fertilizer consumption to poor interaction between the officials and the farmers. Here GIS served as a platform to analyze the effect of each component of the system based on the results.
Need for Irrigation Water Management
Irrigation water use is by far the largest use of water by mankind worldwide. The ever-increasing water demand compared with the depleting water resources warrants refined water use practices in irrigated agriculture to attain improved socioeconomic benefits. In the past years the improvement in the irrigation system concentrated in the hardware component namely the physical aspects like structures but limited on the software part namely water usage for agricultural purpose.
Water is not a free commodity. With increasing standards of living and fast growing population, the available water resources may not be able to meet various demands of mankind. It becomes necessary to put the available resource more effectively for more benefits. It is unto the managers of water resources to devise ways and means of optimally using resources to meet the ever-increasing demand. The aim of efficient irrigation water management or precisely, maximum yield with available water. A good management, proper and timely application of water may result in better yield and reduction in drainage problems.
Actually the irrigation system performance is characterized by the effectiveness of the irrigation throughout the season in a timely pattern averting the losses thereby improving the economic gains (Martin Hvidit, 1997). If the control over irrigation water and its distribution in time and space according to the cropping pattern can be exercised, the system output in terms of production and economic gains will be realized. On the other hand, the water availability in time and space will command the agricultural practices such as cropping pattern, calendar, etc. Such a synchronization of cultivation and irrigation is possible only when the water control in terms of adequacy, timeliness and uniformity is practiced in a command. For this purpose the irrigation system operation should be so devised to create a potential for high performance irrigation resulting in an application system that farmer can use to irrigate his field uniformly in right time, with right amount (Skewes M.A, 1998). With this viewpoint, government of India with assistance from World Bank launched the “National Water Management Program (NWMP) which aims at RELIABLE, PREDICTABLE AND EQUITABLE supply of water. The timely and reliable assessment and monitoring of water resources and systematic exploration and developing new ones is of paramount importance. Considering the stupendous task and the constraint of time, it is necessary to employ modern methods of surveying, investigations, design and implementation. Remote sensing and GIS are viewed as an efficient tool for irrigation water management.
Fig. 2: Analysis on the cultivation – irrigation practices
Remote sensing techniques are useful for Irrigation water management in the following areas (NRSA 1993)
Fig. 3: Analysis on the crop performance
This primary information on the crop and water availability derived from remote sensing methods form a reliable databases for further investigation and analysis across space and time at desegregated levels of spatial parcels. This integration of remote sensing and ground inputs can be very effectively organized and analyzed in GIS environment. Such augmentation of the basic information of the system and the expert knowledge results in a system that addresses the present scenario of the system and future development in the system (Wolfe D.S , 1997). One of the advantages of GIS is that it gives a clear picture of effect of any action plan employed in the system through “if-then “ simulation.
Significance of the study
Here an attempt is made to integrate satellite-derived crop information with ground- collected inputs with respect to agricultural, irrigation and socioeconomic practices, in GIS environment for a diagnostic analysis of the irrigation system across space and time. Two systems were developed; one addressing the performance evaluation of the entire command at distributary level from satellite-derived crop information, yield model, water use efficiency, etc.; second addressing the diagnostic analysis of a few selected distributors to find the causative factors (Chari S.T et al, 1995,1996). Three distributor commands of Bhadra Irrigation system, Karnataka were selected for this study. This is an extension of system which addresses the performance evaluation of Irrigation command and compares the good and poor performance in distributaries reported by the first system. An analysis is carried out to analyze these distributories with respect to report practices add the performance to find out the causative factors for poor performance. This is to basically establish GIS as a tool aid analysis irrigation system at different levels and to help the time- manned location-wise decision-making process for enhancing the efficiency of the system.
Fig. 4: Analysis on fertilizer application
The Bhadra Dam is located across Bhadra river near Lakkavalli Village , Chikmagalur district of Karnataka state, at an elevation of 610m above MSL. Bhadra project comprises of a storage reservoir with a capacity of 2025 m3 a left bank canal and a Right Bank canal. The three distributories for the diagnostic analysis having no. 9A, 12 and 15 belonging to Malebennur branch canal of the right bank canal. The Malebennur branch canal is 48km in length and a full supply depth of 2.44m. The full supply discharge is 20.10 cusec and the irrigated area is 23,710 ha. The 9A distributory is in a very good condition with about 80% cement concrete lining. The minors are lined to some portion. The 12 and 15 distributaries are partially lined with about 10 m portion being lined on both sides of the PO. The 15 distributary is in a very poor condition with the entire portion of the channel being weeded and with lot of physical damages to the system. Farmers at the head reaches in all the three distributaries are going only for paddy and those at 15 distributary for crops like sugarcane and other semi-dry crops.
Fig. 5: Analysis on farmers involvement
Probable reasons for the contrasting performances of the distribution
Three distributaries selected for the study and their performance indicators are listed below in table 1
The following are the 15 probable reasons identified for the contrasting performances of the different distributaries under almost similar climatic and agro_ecological conditions:
To obtain all the important information for the diagnostic analysis, the questionnaire based on the experience gained from the reconnaissance survey is designed for the irrigation officials, agricultural authorities and the farmers soak s to obtain information from the relevant sources. The questionnaire to the irrigation authorities covers questions related to irrigation water management, canal conditions, interaction with the farmers and the agricultural officials. The questionnaire prepared to the agricultural authorities covers questions related to the crops to be grown in the study area, their interaction with the farmers and the irrigation officials, type of agricultural extension and other miscellaneous information regarding the soil fertility conditions in the study area. The questionnaire executed to The farmers covers apart from other information, information related to their identification, the details regarding the inputs and the production in the current season, their involvement in the various NWMP activities, their views about the irrigation and the agricultural authorities, and their knowledge about the various agricultural aspects.
Digital map base preparation
The digital map base preparation is the first step towards the presentation of a GIS module for the irrigation water management. The map base is prepared by scanning the topo maps and the available revenue survey maps of the three distributaries and are reduced to a scale of 1:16000 to 1:8000 and are digitized edited and corrected with respect to topo maps. From the base of revenue levels, the base maps of reach and distributary level are prepared. The three map bases are stored in 3 levels of GIS. The revenue survey numbers were given a reference numbers in the GIS map base so that the data transfer can be done. A total of 878 polygons was formed in the base map and was given sequential numbering. The distributory map base consists of 3 polygons, each representing one distributary. Each polygon was given a reference for data transfer. Similarly, the reach map base consists of 9 polygons and was also sequentially numbered.
Sampling procedure for the selection of the farmers
The questionnaire designed is to be executed for the farmers in the 3 distributaries to get the attribute data. However, the total number of farmers in the 3 distributaries sum up to 1000 forcing the sampling to ease the complexity involved in the collection of data. The sampling done for the present study is a sort of stratified random sampling based on the yield variability such that the reaches having high variability in yield have more samples. Once the number of farmers in a particular reach were selected, the further selection was totally based on random sampling so as to see that the farmers selected were having their evenly located within a reach.
Detailed field survey
A total of 100 farmers were selected for the detailed field survey. Apart from this, the questionnaires to the agricultural and the irrigation authorities were also executed to the concerned officials. The questionnaire to the farmers was executed by the team comprising of 4 scientists, two having water resources background and other 2 with agricultural background. During the interview, questions on farmer’s personal views and wishes were noted and the farmer’s personal experiences with the dept. people were also noted. The collection of data from the irrigation department was done by distributing the questionnaires containing field conditions and field operations, to various officials at different Levels. Office data in the form of discharge data, structural condition records and other relevant data were also collected. The questionnaire to the officials of the agricultural dept. was administered through personal interview to the asst. agricultural director. The data such as soil fertility tests records for the areas covering the 3 distributaries was also collected.
Interpolation of physical resources data
As a first step, the ground reported yield was interpolated using the weighted average interpolation technique to generate a yield map. This ground report yield map is cross checked with the satellite-driven yield to:
Cluster analysis for socio-economic data:
Socio-economic factors such as farmer’s awareness, response and involvement in various NWMP works and views on the various govt. agencies are spatialised by performing a cluster analysis using theissen polygon method.
Using third method, the following maps were generated
Analysis on the primary and derived data
The data analysis was performed in two different environments. The primary or the first level analysis was performed in dBase III plus where the typical and most important trends for the performance of three distributaries were analyzed. The second level was in the GIS environment to cluster and group the inputs.
The following analysis were performed
The importance of this index, as shown by fig. 5 is related to the review of the farmers status and responsiveness Particularly with yield information, this would indicate the future coordination and education that has to be taken up for better results.
The timely and reliable assessment and monitoring of water resources and systematic exploration for development are of paramount importance. Considering the stupendous task and constraint of time in developing the ultimate irrigation potential, it is necessary to use the modern methods of surveying and analysis tools. Remote sensing and GIS with their capability of data collection and analysis are now viewed as efficient and effective tools for irrigation water management. The capability of GIS to analyze the information across space and time would help in managing such dynamic systems as irrigation systems. The study shows the efficacy of this tool to analyze the information on irrigation system in various domains in an integrated manner to understand the system and upgrade the activities. Much of the research has been done on augmenting the resource information and analyzing them for better management . It is also required to improve the methodologies to realize the field –important information in Gis environment.
In this study , an attempt has been made to analyze the irrigation system from the viewpoints namely, irrigation, agriculture and socio-economics. Any system needs to account for the human or socio-economic component to realize the fruit of the effort. The capability of SRS and GIS to address the complex spatial problems and to assist in spatial decision making process qualifies it to handle water resources problem. Water management will be successful only if the human part of the system is considered. This study shows that the operation plan and its adherence had a greater impact on the overall performance of the system. The analysis on the match between the operation plan and the agricultural operations (fig 1) illustrates the efficacy of the Gis to handle the data across space and time. The decision-making and statistical approaches used for formulating the indices that would have a positive relation to the performance within the system is one example of integration. The study also showed that various socio-economic patterns can be derived and studied for management purpose. One important observation is that the farmers views on the Government Agencies were better in the areas of good yield. This shows the direction to be taken by the governmental agencies to bring about higher and sustainable productivity.
The sampling procedure can be improved after studying various socio-economic patterns of the area under study to have faithful representation of the population. The stratification for sampling can be done on the basis of more than one criteria. More time and effort can be spent for the field survey and interview with farmers, as this is the basic input for the system. More time would have educated the farmers with respect to the importance of their response. More queries can be added to the questionnaire after consulting the experts in this particular field of study. The spatial statistical techniques applied to convert the farmers response to queries to surface pattern itself need to be studied in detail. This holds paramount importance in deriving the indices for diagnostic analysis. Also the indices derived have to refine with the help of socio-economic and statisticians. This particular area of spatial statistics has greater scope in the years to come.
I express my sincere thanks to Dr. S.T Chari, Group Director, Water resources division, National Remote Sensing Agency, who is the brain behind this study. I also appreciate the unabated enthusiasm shown by Mr. D.Srinivas to carry out the work as directed. I place on record my acknowledgement to Ms. Radhika and Ms. Shamla for their helping hand with ARC view software
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