Assessment of climate change effect on crop water requirement for chickpea in Vijayapura Karnataka using CROPWAT model

Introduction

Agriculture is the largest (81%) consumer of water in India and hence more efficient use of water in agriculture needs to be top most. Water is an important input for agriculture so that this valuable resource is designed properly and deliverable. It is vital to have an understanding of crop water requirements (CWR) of crops grown especially in arid and semi-arid regions. This will then enable efficient use of water and better irrigation practices like scheduling in such areas as the supply of water through rainfall is limited. Chickpea (Cicer arietinum L.) is one of the most important pulse crops grown in India. Where Karnataka ranks 3rd in the cultivation of chickpea with an area of 20.9 lakh ha, 12.4 lakh tonnes of production and 0.6 tonnes/ha of productivity. Followed by Madhya Pradesh, Maharashtra. In Karnataka, Bijapur, occupies the second position in chickpea with area (1.19 lakh ha), production (0.65 lakh tonnes) and productivity (0.57 tonnes/ha). (Anonymous, 2021) [2] Vijayapura is city located at 16.83 • N and 75.71 • E with an area 102.38 km 2 and elevation 592.23 m above mean sea level. Receives average annual rainfall of 590 mm with 38 rainy days. Where chickpea is mainly grown as rainfed crop during rabi season (September -November). It requires 120 -210 mm of water in whole growing period, due to its better adaption with low water supply and meets its water requirement from conserved moisture in deep soils, cropping area of chickpea is increasing in this region from 0.35 lakh ha in (2000-01) to 1.19 lakh ha in (2019-20). This paper aims to estimate crop water requirement of chickpea variety BGD-11 by using CROPWAT Model. Past climate (2006-2020) taken as baseline and projected climate emission scenarios RCP 4.5 (2040-2054) and (2070-2084) The analysed climate, crop and soil data were collected from Experiment conducted at Regional agricultural research station, Vijayapura. The model was run under different growing conditions like sowing windows: early sowing (September 2 nd fortnight), optimum sowing (1 st and 2 nd fortnight October) and late sowing (1 st fortnight of November)

Materials and Methodology

The study was conducted at Regional Agricultural Research Station Vijayapura is located at 16.83 • N and 75.71 • E with area of 102.38 km 2 and elevation 592.23 m above mean sea level. Receives average annual rainfall of 590 mm with 38 rainy days. the experimental field comes under managolies soil type. with 150 -200 mm available soil moisture upto 60 cm. CROPWAT 8.0 is a software for the calculation of crop water requirements based on soil, climate and crop data and existing or new irrigation climate data and crop needs. In addition, the program allows the development of irrigation schedules for different management conditions and the calculation of the supply system of the variety of cropping patterns. The effect of the weather variable on the water demand of the crop can be analysed by the CROPWAT model which was developed by the FAO-Land and Water Development Division (Allen et al., 1998) [1] . Baseline weather data (2006-2020) i.e., rainfall, minimum and maximum temperature, for Vijayapura district (Fig 1) the soil data on total available soil moisture content (SMC), initial soil moisture depletion, maximum rooting depth and maximum rain infiltration rate for black clay and red sandy loam soils for vijayapura was collected from regional agricultural research station Vijayapura. The projected data for the period of coming 30 years from 2040-2084 was collected from Copernicus Climate Change Service (IPSL-CM5A model) (https://climate.copernicus.eu). According to RCP 4.5 scenario, there would be an increase around 1.0 °C both day and night temperature during the chickpea cropping period (Sep-Dec) under the projected climates (2040-2084) compared to baseline climates (2006-2020). The field experiment was conducted at regional agricultural research station Vijayapura in rabi seasons of 2020-21. The phenological data for initial, mid and late growth stages of chickpea variety BGD-11 collected from the field experiment were used in the model. The salient details of chickpea crop required for the study i.e., crop coefficients (Kc), phenological days, critical depletion fraction (p), yield response factor (Ky) were also taken from the available 18 published data of FAO (Allen,1998) [1] Results and Discussion Crop evapotranspiration (ETc): The model simulated the average ETc (256.9 mm) in Vijayapur district for the baseline climate (2006-2020) across four different dates of sowing (DOS). (Table 1). Among different DOS the model simulated highest average ETc (261.9 mm) for the crop sown on delayed sowing i.e., I fortnight of November, followed by II fortnight of September (259.6mm). This was because of the highest average temperature recorded and average ETo simulated in the cropping season. Where as the model simulated lowest ETc (246.8 mm) for the crop sown on II fortnight of October. The model simulated the average ETc (256.9 mm) in Vijayapur district for the projected climate RCP 4.5 scenario (2040-2054) across four different dates of sowing (DOS). Highest average ETc was simulated for the crop sown on II fortnight of September (265.8 mm) followed by I fortnight of October (252.5 mm) and the lowest was for DOS II fortnight of October (245.8 mm). The model simulated the average ETc (261.7 mm) in Vijayapur district for the projected climate RCP 4.5 scenario (2070-2084) across four different dates of sowing (DOS. the highest ETc was simulated for the crop sown on II fortnight of September (270.0 mm) followed by I fortnight of November (266.4 mm) and the lowest was for DOS II fortnight of October (252.9 mm), followed by DOS I fortnight of October (252.5 mm). (Table 1). Simulated outputs across dates of sowing suggest that ETc increased with delay in sowing. Simulated outputs across dates of sowing suggest that ETc increased with delay in sowing in Vijayapura districts under baseline climates This is due to increase in average ETo and decreased rainfall with delay in sowing i.e., October sowing received more rainfall than November sowing. In case of projected climates there was no significant change in ETc with delay in sowing. However, the highest ETc was for Nov-09 sowing because of minimum rainfall during second fortnight of November. similar findings was reported Thimmareddy et al (2021) [4] .

Effective Rainfall (ER):

The model simulated the average ER (218.4 mm) in Vijayapur district for the baseline climate (2006-2020) across four different dates of sowing (DOS). In the projected climates RCP 4.5 (2040-2054) the highest ER was simulated for the crop sown on II fortnight of September (94.6 mm) followed by I fortnight of October (85.7 mm) and the lowest was for DOS II fortnight of November (32.5 mm), followed by II fortnight of October (76.9 mm). In the projected climates RCP 4.5 (2070-2084) the highest ER was simulated for the crop sown on II fortnight of September (110.0 mm) followed by I fortnight of October (69.0 mm) and the lowest was for II fortnight of November (30.0 mm), followed by DOS II fortnight of October (61.5 mm). Simulated outputs across dates of sowing suggest that ER increased with Earlier in sowing. ER for chickpea crop significantly increased by 26.9 and 18.5 per cent, respectively in (2040-2054), (2070-2084) (RCP 4.5 scenario) compared to baseline period (2006-2020). The increase in ER is proportional to their respective increase in rainfall in chickpea cropping period projected climates. The CROPWAT simulated decline in ER with delay in sowing in both past and projected climates this can be explained by higher North-East monsoon rainfall in the early months (October) and rainfall dissipation of rainfall towards December month. (Table 1). similar findings was reported Thimmareddy et al (2021) [4] . ER and increased ETc during the cropping period Early sowing (October) receives more rainfall due to North-East monsoon onset which dissipates towards December. (Table 1) similar findings was reported Thimmareddy et al (2021) [4] .

Irrigation requirement (IR):

References

1. Allen RG, Pereira LS, Raes D, Smith M. Crop evapotranspiration: Guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper 56. Rome (Italy): FAO; 1998. p. 9-D05109.
2. Anonymous. Area, production, productivity of soybean in the world, India and Karnataka. 2021. https://www.indiastat.com
3. Onyancha DM, Gachene CK, Kironchi G. FAOCROPWAT model-based estimation of the crop water requirement of major crops in Mwala, Machakos County. Researchjournali's Journal of Ecology. 2017 Sep.
4. Thimmareddy H, Sumesh KG, Patil RH, Amith G, Mahesh H. Effect of changing climate on water requirement of chickpea in North Interior Karnataka: CROPWAT modelbased assessment. Legume Research. 2021.