Mapping and managing the command area of the distributaries in Gayathri irrigation project using GIS tools

Introduction

Global climate change threatens water resources, creating knock-on risks for food, employment, and energy security. (Patel et al., 2023) [7] . Shifting rainfall patterns across different regions and seasons are seriously harming crops. Extreme weather variations lead to contrasting disasters, brief, intense downpours trigger destructive flooding, while delayed and insufficient rainfall produces severe droughts. (Shah et al., 2015) [10] . Misusing water and natural resources lead to severe environmental disasters, with drought being the worst outcome (Kesarwani et al., 2023) [4] . To solve this problem, it is essential to check how much water is available across different areas and times. For assessing water availability, accurate and reliable data is essential. Irrigation management data is complex, highly localized, and constantly changing over time. This initiative spans from individual farms to entire catchment areas covering millions of hectares of irrigated land. GIS technologies such as Arc/Info software helped plan and manage water resources with high efficiency (Nandi et al., 2016) [6] . A well-established georeferenced database and map of climate, crop, soil and canal network is needed for estimation of regional irrigation water requirement of a command area. The database helps for computing effective rainfall, evapo-transpiration, crop coefficient, percolation application efficiency, cropping pattern distribution. GIS also helps in preparing the effective irrigation schedule based on available water for irrigation

Materials and Methods

Description of study area

The Gayathri Irrigation Project (GIP) is a medium-scale water scheme in Palakkad, Kerala, spanning two phases with the Meenkara and Chulliyar reservoirs in Muthalamada panchayat, Chittur. There were 19 distributaries in GIP, out of this, 11 distributaries in LBC and 8 distributaries in the RBC. The location map of the study area is shown in Fig. 1. The study area belongs to Agro Ecological Unit (AEU) 23 in the humid tropics. The area gets most of its rain from the southwest monsoon, and a smaller amount from the northeast monsoon. The annual rainfall in this area averages 1,500 to 2,000 mm, representing only half of the state average. (Surendran et al., 2015) [11] . Average annual temperatures fluctuate between a low of 23.7°C and a high of 32.4°C. Wind speeds peak between December and January at 9.5 km/h, while humidity levels remain high from June to September and around 84 to 88 per cent during this period (CGWB, 2013) [1] . Sandy clay loam and sandy loam dominate the area's soil texture (CGWB, 2013) [1] . Paddy is the primary crop in the eastern district study area, supplemented by coconut, mango, vegetables, and banana. It is cultivated across two distinct seasons: the first and second crop. Farmers grow the Kharif (Virippu) crop from May to August, and the Rabi (Mundakan) crop from November to February.

Net CDF

NetCDF software was used to convert the model output in an array form. This software had a set of interfaces for array-oriented data access. It supports a machineindependent format for representing the scientific data.

Geospatial database for distributary command

The geospatial database consists of point, line and polygon feature class created in ArcGIS platform. The database included maps for distributary command areas, land use, soil types, and interpolated meteorological parameters. The GIP distributaries were identified by comparing the ArcGIS canal map with official schematics and ground-truthing data.

Each distributary was then isolated using the ArcGIS Clip tool. The distributary boundary was demarcated using the ArcGIS buffer tool, with the calculated area subsequently verified against" Water Resource Dept., GoK.

The land use map for the Gayathri irrigation command was derived from the Bharathapuzha basin map provided by the Kerala Land Use Board. Using the ArcGIS Clip tool, the distributary command areas were isolated to analyze their specific buffer zones. This process determined the primary land-use categories and their respective areas across the various distributaries." The soil map of the study area was taken from Bharathapuzha basin soil map supplied by Directorate of Soil Survey and Soil Conservation, GoK. The soil map of the distributary command was clipped to determine the buffer area and identify the major soil series and their respective coverage. SPAW (Soil Plant Atmosphere Water), a hydrologic budget model developed by United States Department of Agriculture (USDA) -Agricultural Research Service (ARS) was used to prepare soil database. The soil properties like field capacity, wilting point and saturated hydraulic conductivity were determined using this model. Meteorological data including temperatures, humidity, wind velocity, sunshine hours, and rainfall was collected from RARS Pattambi and IMD Pune. Because some of the stations sit outside the command area, their zones of influence were estimated using the Inverse Distance Weighted (IDW) interpolation tool in ArcGIS. The cell value was estimated using a linear combination of sample points, where weights were inversely proportional to the distance from the prediction location raised to the power of p.

Weight adjustments depend directly on the value of p When p=0, the prediction equals the data mean. As p increases, the weight of distant points drops rapidly, leaving immediate surrounding points to dominate the prediction. ArcMap spatial distributions were developed on a monthly basis for all meteorological parameters, encompassing both historical datasets and predictive scenarios for 2026 (PD1) and 2031 (PD2).

Results and Discussion Distributary command area map

All distributaries in the head, middle, and tail reaches of the RBC and LBC were identified using the GIP distributary command area map (Fig. 2) and selected for study.

The area of each distributary found through GIS matches the data from the Water Resource Department of Kerala. Table 2 shows the distributaries in the GIP.

Land use map of distributary command

By clipping the GIP land use map to the distributary command area, major crops were identified. Paddy was dominant across all distributaries, followed by coconut, which closely aligns with the findings of Lakshmi et al.

(2018) [5] . Vegetables and banana were the other crops cultivated in the command area. The land use map of the distributary command area is shown in Fig. 3.

Fig 3: Land use map of distributary command

The major land use classification and its area coverage is shown in Table 3. Paddy was the main crop in e distributary command followed by coconut. Vegetables and banana were the other crops cultivated in the command area.

Soil map of distributary command in GIP

The soil map of the distributary command area (Fig. 4) was adapted from the original GIP soil map. The various soil series such as Bhavani Nagar, Mungilmada, Kozhinjampara, Karinganthodu, Tolanur and Vadavannur were identified in the study area. The soil series with its area, percentage of area, and the textural class is shown in Table 4. Covering 41.18 km², the Bhavani Nagar series makes up 30.99 percent of the command area. This soil series is located primarily between the eastern and central regions.

Two other soil series, Mungilmada and Vadavannur, occupy 14.77% and 3.40% of the command area respectively, appearing in parts of the eastern tract. The central and western regions of the command area are dominated by the Karinganthodu (28.56%) and Tolanur (11.62%) soil series, while the Kozhinjampara series (10.83%) occupies parts of the northwest. Among all identified groups, the Bhavani Nagar series exhibits the highest clay content, followed by the Karinganthodu and Mungilmada series. The soil series Bhavani Nagar and Mungilmada were mostly seen in the distributary command areas of head reach of canal irrigation system, whereas soil series Karinganthodu was more predominant in tail reach of distributary command.

Estimation of soil properties from SPAW model

The soil properties viz. field capacity, wilting point and saturated hydraulic conductivity of different soil series were estimated from SPAW model and the results are shown in Table 5. The Bhavani Nagar, Karinganthodu, and Mungilmada soil series exhibited higher field capacity and wilting points, alongside lower saturated hydraulic conductivity compared to other series. This pattern is likely attributed to the elevated clay content in these specific soils (Gülser C and Candemir F. (2014) [2] , Seema et al., 2019) [9] .

Spatial map of meteorological parameters

Spatial map of meteorological parameters in the distributary command was prepared for months from January to December for historical data. The spatial ArcMap of all climate parameters viz. maximum temperature, minimum temperature, humidity, wind velocity and sunshine hours were generated. For example, the variations in rainfall and maximum temperature during October are depicted in Fig. 5 and 6, respectively. Specifically, rainfall within the canal command fluctuated from 139.4 mm to 162.8 mm, as shown in Fig. 5. The head reach of the canal command, located near the Palakkad rain shadow area, recorded the lowest value of 139.4 mm. This finding closely aligns with the results reported by Raj and Azeez (2010) [8] . The second lowest value was observed in tail reach of canal command whereas highest values of rainfall were observed in the middle reach of the canal command. The average maximum temperature for the month October ranged from 31.96 to 32.03 o C and is shown in Fig. 6. In the canal command area, variations in maximum temperature were less pronounced than variations in rainfall. The highest maximum temperatures occurred in the head reach, situated near the Palakkad rain shadow region. Consequently, spatial maps for minimum temperature, humidity, and wind velocity were analysed across all months using historical data. 6. Tables 7 and8 display the CMIP5 climate model grid data within the study area used as predicted data for 2026 (PD1) and 2031 (PD2).

The forecast shows a rise in both high and low temperatures compared to past records. The maximum temperature of 43.3 °C recorded in March during PD2 aligns with the findings of Varughese and Hajilal (2016) [12] .

Spatial rainfall measurements and predicted climate model outputs

The peak monthly average rainfall of all distributaries occurred in July, reaching 400 to 500 mm, while June and August showed the next highest levels (Fig. 7). The data indicates that southwest monsoon season accounts for the majority of the annual rainfall. All other months, monthly average rainfall observed in distributary command was below 200 mm. The highest average annual rainfall values were recorded in distributaries 7 and 17, located at the mid and tail ends of the canal command, respectively, while the lowest values occurred at the head end distributary 1,5 and 2 and 6 (Fig. 8). These distributaries 1, 2, 5, and 6, were located in the head reach of the canal irrigation system. These low values indicate that the head-reach distributaries sit within the rain shadow area of the Palakkad Gap. This was in closely agreed with findings of Raj and Azeez (2010) [8] . Distributaries in the middle reach experienced relatively higher rainfall levels. Rainfall peaked in June and reached its lowest point in January for both cases. Consistent with Raj and Azeez (2010) [8] , the predicted year (PD2) exhibited an 11.7% decline in rainfall compared to PD1.

Conclusion

Geospatial database of distributary command of Gayathri irrigation project was created. This includes command area map, land use map, soil map and geospatial maps for various meteorological parameters maximum & minimum temperature, humidity, wind velocity, sunshine hour and rainfall for each distributary command. The analysis of spatial data revealed that Bhavani nagar soil series was most prevalent in the distributary command. Specifically, rainfall within the canal command one third of Kerala's annual average. The data indicates that southwest monsoon season accounts for the majority of the annual rainfall. In the canal command area, variations in maximum temperature were less pronounced than variations in rainfall. The head reach distributaries experienced maximum temperatures and minimal rainfall, confirming their location near the Western Ghats' Palakkad Gap rain shadow region.

Acknowledgement

AcknowledgementAuthor express gratitude to major advisor Dr.Asha Joseph and Dr.Anu Varughese, advisory committee member and Department of irrigation and drainage engineering KCAEFT, Tavanur

References

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