Application of Remote Sensing and GIS for Identification and Assessment Proceedings of AIPA 2012, INDIA 79 APPLICATION OF REMOTE SENSING AND GIS FOR IDENTIFICATION AND ASSESSMENT OF CROP GROWTH IN WAZIRABAD COMMAND AREA BY CALCULATION OF IRRIGATION LOSSES AND DEMAND TO IMPROVE THE FARMING Ramesh Naidu 1, M.V.S.S. Giridhar 1 and Sanghamitra Ghosh 2 1 JNTU, Hyderabad, India 2 Vidyasagar University, West Bengal, India ABSTRACT Differentiating the land use and classification of crop precisely using Remote Sensing Satellite images and GIS analysis for calculating the irrigation demand and losses with respect to soil characteristics and topography is an added advantage in utilizing the optimum amount of water distribution to fields. Percolation losses are one of the main losses out of other losses in irrigating the crops. These losses accounts more in the case of course textured soils than finely textured. Integrating and analyzing the multi date satellite imagery and multiple themes using GPS based GIS helps to identify and estimate the crop acreage and assess the crop water requirements and optimum amount of water distribution through canals. Using geographical information systems helps the water resource engineers and managers for estimating the results both in the form of spatial and non-spatial. This paper is a part of research and highlights the advantages of GIS and Remote Sensing in identifying the crop and mapping the canal network in network model, delineating the Command Area in to Blocks/Sub-Blocks and calculating the percolation losses in the fields with a special emphasis on irrigation water management. In this study the parameters like canal network, detailed block boundaries under major to minor canals, crop classified satellite images and soil characteristics of the command area are taken as thematic inputs. Keywords: Remote Sensing, Chak, Block, GIS and GPS, Command Area. 1. INTRODUCTION In irrigation fields, water losses largely result from Evapotranspiration, percolation and seepage. Evapotranspiration is related to meteorological factors and to be calculated as separately for calculating the water requirement of crops. Seepage and percolation, when compared with ET which is relatively stable in a given period within given agroecological region with uniform climate, vary very much from place to place. Rice grown on sandy soils requires, on the average, about three times more water than rice grown on clay soils (Fukuda and Tsutsui 1968). Because of topography, crop type and soil characteristics, losses in irrigation system lead to overall in-efficiency in terms of water productivity. Percolation losses are a function of the local soil, crop type and extent and topographic conditions. Therefore, at any time the amount of rainfall or irrigation water entering a soil becomes greater than its water-holding capacity, loss by the downward movement of free water (vertical percolation) will occur. Percolation is often defined as the movement of moisture through saturated soils due to gravity, hydrostatic pressure or both. Percolation occurs in a vertical direction. Water is lost through seepage by its horizontal movement through a levee. In practice, percolation and seepage are combined and taken as a measure of the water-retaining capacity of a field. Percolation is largely affected by topography, soil characteristics, and the depth of the water table. In extreme cases, percolation plus seepage ranges from almost nil on heavy soils to greater than 100 mm on sandy soils. Seepage and percolation rates are mainly governed by the profile characteristics and topography and are much greater in sandy than clay soils. It also increases with increase of depth of standing water. The rate of seepage and percolation are about 6 mm/day in well drained soils and 3mm/day in poorly drained soils. Where the soil is heavy and the water table is close to the soil surface, percolation losses are low- about 1 mm/day or less. Where soil is light and water table is deep, percolation losses may be high-10mm/day or more. Other factors that affect percolation losses are presence of a crop, the amount and distribution of rainfall, soil shrinkage and cracking, soil contraction, flooding and depth of water and soil puddling. Researches have indicated that a percolation rate of 10 to 15 mm/day was favorable for supply of dissolved oxygen, the removal of harmful substances and the maintenance of root activity. However there is little benefit on yield under good soil conditions. Infect with some situations, the loss of plant nutrients are serious if the percolation rate is high. Various studies suggest that the range of percolation varies between wide limits from less than 1mm/day in compact soil up to several 100 mms/day in loose soil.
80 Agro-Informatics and Precision Agriculture 2012 (AIPA 2012) Using GIS and Remote Sensing Technology and its powerful tools helps to calculate the losses effectively by taking several parameters at one attempt. 2. STUDY AREA The selected Wazirabad Command Area is in Zone1 under block No. 5 of Left Main Canal in Nagarjunasagar Project (NSP). It is located between 16 39 2.84 and 16 56 40.81 N latitude and 79 25 16.01 and 79 40 52.90 E longitude. Mirialguda is the nearest town connected by ground road network. The total extent of command area is 26700 hectares. The study area is located flat and medium undulating terrain with maximum and minimum elevation ranging between 187 and 44 m above MSL. The area experiences semi-arid climatic conditions and receives an average annual rainfall of about 750 mm. In general, the slope of the command area is towards east. 3. METHODOLOGY As described in the introduction the percolation and seepage mainly depend on crop, soil, ground water and topography. In the Wazirabad command area the groundwater levels and fluctuations and the topography of the command area that serves by canals are almost uniform and there is no impact in calculating the losses. Hence Crop and Soil is taken as main parameter for calculating the percolation losses since the soils in command area are distributed with several different categories. GIS is used as a tool since the variability of losses can be correctly defined and calculated spatially and can be represented the calculated losses in a map format by overlaying all block/sub-block boundaries and canal network concerned to command areas for taking effective decisions during the release of water to canals. Using the canal network as one theme, crop and soil as supporting themes and block/sub-block are the reference theme the overlay analysis has been used for calculation of losses. Percolation losses have been calculated by GIS Overlay analysis by using union operation with Crop, Soil theme and sub-block theme. The criteria are based on the amount of percolation losses defined for each soil category as defined by International Institute for Aerospace Survey and Earth Sciences (ITC), The Netherlands. The flow chart of the detailed methodology of Crop identification and Classification is represented in Figure 1. Fig. 1 The following layers were generated in GIS Platform: Canal line Canal Node Crop Map Soil Map Contour and Digital Elevation Model Command Area Boundary including Block and chak boundary Water User Association Boundary.
Application of Remote Sensing and GIS for Identification and Assessment 81 3.1 Canal Network Database Creation Canal network is digitized from the Survey of India Topo maps and later converted to GIS database using ArcInfo were Software. The data was prepared in a network module which constitutes nodes and lines. The node data refers to Sluice OT and line refers to canal. The flow direction and continuity errors were taken care while digitization and later checked for continuity in the ArcGIS Network Module. The canal ID is created with a unique multi digit number constitutes a combination of alphabets and numbers. All canal reaches have only one upstream reach but have more than one downstream reaches. Only the upstream reach ID is kept for each section in the developed data system. The hierarchic relationship can be retrieved through the use of Upper id. 3.2 Crop Classification The crop acreage for Wazirabad Command Area was estimated based on the unsupervised classification using Erdas imagine software. The crop acreage reports were generated blockwise, chakwise and WUAwise using the GIS Analysis to find out the water demands for each canal and command area unit. In Rabi season the command area is covered with paddy and some small patches of non-paddy. There was difficulty in identifying crop and cultivated lands because of the coexistence of early and late stages of crop. However these growth stages were successfully identified or distinguished from taking the two images one in February and the second one in March. Uncultivated fields and fallow lands were identified using infrared band values due to surface reflectance of soil, while more advanced growth stage fields were identified with the brightness values. To improve accuracy the non-agricultural areas like settlements, water bodies, rocky, scrub and dense forest etc. were masked out by using non-agricultural mask. 3.3 Creation of Contour Map, Digital Elevation Model (DEM) and Aspect Map Digital representations of the terrain often form one of the main elements of the mapping process. Digital Elevation Model (DEM) represents continuous variation of topography over space that helps in assessing landscape characteristics and has a wide application in surface hydrology modeling. These characteristics help to determine slope, flow directions, areas, boundaries and outlets of drainage basins and ultimately in delineating the Block and Chak boundaries for this study. Using GRASS GIS the DEM is generated. Contours are digitized from the Block maps collected from the Irrigation Department. These contours used as an elevation data for creating the Digital Elevation Model. The DEM is used as an input for creating the Aspect Map. 3.4 Delineation of Command Area, block and Chak boundaries The delineation is based on surface modeling techniques available in many GIS and Remote Sensing software. GRASS Software is used for doing the surface modeling. The Chaks and Block Boundaries under each canal are delineated reference to canal network, DEM, Aspect and drainage network extracted from surface modeling and SOI Topo maps. The Chaks are mapped as per the type of canal and its flow direction. If the canal is a ridge canal Chaks are identified on both sides of it and if it is a contour canal Chaks are on one side only. Spread of a Chak is between the canal and the drainage line. 3.5 Calculation of Seepage/Percolation Losses According to US Bureau of Reclamation Data for unlined canals the seepage rate in various types of soils are given in Table 1. Table 1: Soilwise Percolation/Seepage Losses Texture Qs-Percolation/Seepage Losses(mm/Day) Clay 4 Loam 12 Sand 14 A simple linear equation has been used to calculate the seepage and percolation losses. The equation is: P = Qs * A where P is Percolation loss in lit/sec, Qs is in mm/day, A is the crop acreage in Hectares. Using the above criteria the canal network theme, soil theme and chak themes are overlaid for chakwise losses.
82 Agro-Informatics and Precision Agriculture 2012 (AIPA 2012) 4. RESULTS AND DISCUSSIONS The canal network and the types of soil in command area are shown in Figure 2 and Figure 5, respectively. The type of satellite imagery used and the classified crop map generated is shown in Figures 3 and 4, respectively. Delineation of Sub-block and Chak boundaries are shown in Figure 6. There are 13 canals mapped in network model and including major canal and under each canal the sub-blocks and chaks are identified with reference to DEM and identified topographic features. Due to the hierarchy and the unique identity of block and chak under each canal the spatial queries and retrieval of data and results are more convenient for decision making and planning of water releases. Clay soils are occupied around 13050 hectares of area, loamy soils distributed around 6035 hectares and sandy soils are occupied around 7636 hectares. The chaks under sandy soils influence high percolation losses and the chaks under clay soils influence low percolation losses. Within a sub-block under a minor canal there are different types of soils and influence varied amount of losses though the chak areas are equal in size. For canals of WX and WL2 are almost same lengths and the corresponding command areas of two canals are almost equal in area but the losses in canal WL2 are double than the canal WX. These results are tabulated in Tables 2 and 3. Fig. 2: Canal Network in GIS Platform Fig. 3: Satellite Imagery used for Crop Classification Fig. 4: Classified Crop Map. Pin Colour shown as Crop
Application of Remote Sensing and GIS for Identification and Assessment 83 Fig. 5: Soil Distribution in Command Area Fig. 6: Block and Chak Boundaries from GIS Analysis Table 2: Canal or Sub-blockwise Crop Acreage S. No. Block Area in Hectares Canal Canal-Length Late Paddy Paddy Fallow Total Paddy in Hectares 1. 213.098 WL1 1496.440 30.921 133.651 11.215 164.572 2. 3434.9674 WL2 26457.494 705.798 2491.292 66.18 3197.09 3. 209.4619 WL3 1492.796 28.017 167.037 0.074 195.054 4. 294.3726 WL4 1581.590 49.563 230.831 2.722 280.394 5. 7721.4262 WL5 57092.800 956.04 2168.691 86.629 3124.731 6. 1073.667 WL6 4049.046 119.129 449.747 0.147 568.876 7. 1185.734 WR1 11427.452 89.971 1032.19 5.81 1122.161 8. 383.5992 WR2 1897.032 88.832 259.068 18.973 347.9 9. 711.869 WR3 3650.757 45.592 630.352 2.867 675.944 10. 712.8629 WR4 4473.000 27.538 672.158 1.545 699.696 11. 803.6684 WR5 3486.690 72.948 686.607 14.67 759.555 12. 2141.2722 WR6 13784.440 419.12 510.635 25.774 929.755 13. 7839.4408 WX 24956.594 219.983 1036.381 21.252 1256.364 Total 26725.4396 155846.131 2853.452 10468.64 257.858 13322.092 Table 3: Canal or Sub-blockwise Percolation/Seepage Losses Sl. No. Canal-Id Sub-block Length (M) Command Area in Sq. Metres Percolation Losses in Cubic Metre/Sec 1. WX WX 24956.76 32421489.156 2.821 2. WL1 WL1 1496.46 2888445.532 0.467 3. WL2 WL2 26457.68 34349697.839 5.025 4. WL3 WL3 1492.82 2094636.229 0.339 5. WL4 WL4 1581.59 2943784.722 0.476 6. WL5 WL5 57093.04 77214212.748 6.584 7. WL6 WL6 4049.10 10736690.313 0.604 8. WR1 WR1 11427.41 11857393.828 1.920 9. WR2 WR2 1897.11 3835936.438 0.621 10. WR3 WR3 3650.75 7118706.768 1.153 11. WR4 WR4 4473.04 7128574.473 1.154 12. WR5 WR5 3486.65 8036570.211 0.998 13. WR6 WR6 13784.47 21412738.698 1.013
84 Agro-Informatics and Precision Agriculture 2012 (AIPA 2012) 5. CONCLUSIONS Integration of Crop classified data and Geospatial Database with Water Resources and Land Management domain has definitely an edge over conventional way of Planning and Management. Applying LISS-III images to paddy crop classification gives acceptable results. Most successful identification of paddy crops would have required multi-temporal images. Detailed Level of Chak/Block Statistics in calculating the conveyance losses increases Water Use Efficiency. Chakwise Percolation Losses are used to change the water allocation strategies for optimum utilization of water. Effective maintenance of irrigation projects is possible through Geospatial Data Integration and can be integrated with SCADA. Through this Modernization, maintenance and efficient operation of the irrigation system up to the Chak level is possible. Water allocation in an irrigation system is possible with due regard to equity and social justice. Disparities in the availability of water between head-reach and tail end farms and between large and small farms should be obviated by referring the actual need of irrigation with respect to losses calculated and supply on a volumetric basis subject to certain ceilings and rational pricing. REFERENCES Asawa, G.L., Irrigation and Water Resources Engineering. Chari, S.T., Jonna, S., Rajum P.V., Murthy, C.S. and Hakeem, K.A., System performance evaluation and diagnostic analysis of canal irrigation projects (ACRS 1994). Datta, Surajit K.D.E., Principles and Practices of Rice Production. Garg, Vimal and Seth, Ritu, Designing Decision Support Systems to aid Irrigation Water Planning and Management in command areas (Map India 2003). Hargreaves, George H. and Merkley, Gary P., Irrigation fundamentals: an applied technology text for teaching irrigation. Majumdar, D.K., Irrigation Water Management: Principles and Practice. Thiruvengadachari, S., Assessing irrigation performance of rice-based Bhadra project in India (ACRS 1996).