Multiple approaches for estimation of reference evapotranspiration in Halayapura micro-watershed

Introduction

Water is one of the most vital natural resources for life and agriculture. Its demand is rising sharply across the world. Climate variability and population growth are the main drivers. Rapid urbanization has added further pressure on limited supplies. Irrigated agriculture alone consumes more than 80 per cent of available water in arid regions. Efficient water management has therefore become a global priority (Al-Ghobari, 2000) [2] . Semi-arid regions face the greatest water stress. Rainfall is scarce and unevenly distributed here. Evaporative demand remains consistently high through the year. Agricultural production in these areas depends heavily on irrigation. Accurate estimation of crop water requirement is essential under such conditions. This requirement is best derived from reference evapotranspiration (ET o ). Evapotranspiration (ET) is a key process in the hydrological cycle. It links the surface water balance with the surface energy balance (Zhao et al., 2013) [25] . ET represents combined water loss from soil and vegetation. Evaporation dominates from bare soil during early crop stages. Transpiration becomes dominant once the canopy fully develops (Rosenberg et al., 1983; Mavi and Tupper, 2004) [19,15] . ET is closely linked to crop growth, drought monitoring and irrigation scheduling (Allen et al., 2007; Mousumi et al., 2019) [3, 16] .

Direct measurement of crop evapotranspiration is difficult in practice. Lysimeters and micrometeorological systems are costly to install. Their operation also demands continuous skilled maintenance (Rosenberg et al., 1983) [19] . Reference evapotranspiration was therefore introduced as a practical alternative. It quantifies the evaporative demand of a hypothetical reference surface. This surface is independent of crop type, growth stage, and management (Allen et al., 1998) [1] . Numerous methods exist for estimating ET o . Development of these methods began in the nineteenth century (Brutsaert, 1982) [7] . Xu and Singh (2002) [24] grouped them into six broad categories. These are water budget, mass transfer, combination, radiation based, temperature based, and pan evaporation methods. Harbeck (1962) [10] contributed early work on mass-transfer based evaporation estimation. Thornthwaite (1948) [23] proposed one of the first temperature-based classifications for climate and water balance studies. Penman (1948) first combined energy balance and aerodynamic principles for open-water evaporation. Monteith (1965) extended this approach by adding canopy and surface resistance terms. This combination became the basis of the Penman-Monteith method. The FAO-56 Penman-Monteith method is now the globally accepted standard (Allen et al., 1998) [1] . Its strong physical basis gives reliable results across diverse climates (Pereira et al., 2015; Feng et al., 2016; Tabari et al., 2013) [17,9,22] . The Penman-Monteith method, however, needs extensive meteorological inputs. Temperature, humidity, wind speed, and solar radiation must all be recorded accurately. Such complete datasets are often unavailable in developing regions. Simpler empirical methods have therefore gained wide acceptance as alternatives. The Hargreaves method estimates ET o using only temperature data. The Priestley-Taylor method relies mainly on radiation and temperature. These simplified methods reduce data requirements considerably. Their accuracy, however, varies with local climatic conditions. Advective energy from dry surroundings can inflate evapotranspiration estimates (Tanner, 1967). Local calibration is therefore recommended before wider application. Berti et al. (2014) [6] reported Hargreaves overestimation of ET o in northeastern Italy. Aschonitis et al. (2015) [5] reassessed Priestley-Taylor performance under Italian climatic conditions. CROPWAT software offers a further practical option for ETo estimation. It applies the FAO-56 Penman-Monteith equation internally (Reddy et al., 2020) [18] . It further supports crop water requirement and irrigation scheduling calculations. Saha et al. (2018) [20] used CROPWAT for barley water requirement estimation in Punjab. Reddy et al. (2020) [18] applied it for irrigation planning in Raichur, Karnataka. Both studies confirmed its practical value for Indian field conditions. Comparative evaluation of ET o methods is an active research area worldwide. Lang et al. (2017) [12] compared eight methods against Penman-Monteith in south-western China. Karimi et al. (2017) [11] tested method performance across humid stations in South Korea. Chattopadhyay and Hulme (1997) [8] examined evaporation trends over India under climatic change. Shahid (2011) [21] linked climate change to rising irrigation demand in Bangladesh. These studies confirm that method performance is strongly climate dependent. Semi-arid watersheds present particular estimation challenges. Temperature swings are large across seasons here. Wind-driven advection is also common in open agricultural land. Simplified methods may therefore show systematic bias under such conditions. Local performance evaluation is essential before any method is adopted for irrigation planning. Comparative studies of this kind remain limited for Karnataka's semi-arid microwatersheds. The Halayapura-1 micro-watershed reflects these regional challenges closely. It lies within the Eastern Dry Zone of Karnataka. Annual rainfall here is both scarce and erratic. Groundwater pumping through bore wells is therefore common practice. Accurate ET o estimation is essential for sustainable groundwater use in this setting. An Automatic Weather Station was recently installed here under the REWARD project. This has created a valuable long-term dataset for local method comparison.

No earlier study has compared multiple ET o methods for this micro-watershed. This is a clear gap in the local knowledge base. Filling this gap can guide method selection for similar semi-arid watersheds elsewhere. It can also support day-to-day irrigation decisions taken by local farmers. The present study was designed to address this need directly. The present study was carried out with the following specific objectives: 1. To estimate the monthly and annual reference evapotranspiration (ET o ) of the Halayapura-1 microwatershed using the CROPWAT, FAO-56 Penman-Monteith, Hargreaves, and Priestley-Taylor methods for the period 2016-2024, and to assess their seasonal and interannual variations. 2. To identify the most suitable reference evapotranspiration estimation method for irrigation scheduling and water resource planning under the semi-arid conditions of the study area.

Materials and Methods

The Halayapura-1 micro-watershed henceforth nomenclatured as study area is a part of Hosalaya sub-watershed, Tumkur Taluk and District covering an area of 503 ha is located at North latitudes 13°08'31" to 13°10'04" and East longitudes 77°05'45" to 77°07'19" spread across Thondagere, Niduvalalu, Chikkanahalli and Thavarekere, Thondagere Kavalu and Sugganahalli villages.

The micro watershed code is 4B3C5n1 and is located at an elevation of 840 m above mean sea level (MSL) (Fig. 1).

The study area is a part of the Eastern Dry-Zone of Karnataka. December is the coldest month with mean daily minimum temperature of 16.50 ºC, while May is the hottest month with mean daily maximum temperature of 38.10º C. Relative humidity of over 87 per cent is common during monsoon period. Wind speed exceeding 25.8 km/h during the months of July and August. CROPWAT also evaluates the impact of water deficits on crop yield.

The FAO-56 Penman-Monteith equation (Allen et al., 1998) [1] was used as the reference method for estimating ET o because it incorporates both energy balance and aerodynamic components. Daily meteorological observations from the AWS were used in The Priestley-Taylor method was applied using net radiation and temperature data obtained from the AWS. A Priestley-Taylor coefficient 𝑎 𝑝𝑡 of 1.26 was adopted, which the standard value is recommended for reference evapotranspiration estimation in the absence of local calibration (Allen et al., 1998) [1] . Coefficient of determination is widely used to evaluate the goodness of fit. It ranges from 0.0 to 1.0, with higher values indicating better agreement and was calculated by using the following equation;

Results and Discussion

The reference evapotranspiration (ET o ) was estimated using CROPWAT model from the year 2016 to 2024 for the Halayapura-1 micro-watershed (Table1 [18] with the result of Evapotranspiration ET o and monthly effective rainfall calculated using CROPWAT model. The ET o was low in December (63.34 mm/month), increased during the Jan-May, reached maximum value of 170.70 mm/months. Saha et al., 2018 [20] reported that the monthly ET o during the barley growing season was higher at Ludhiana (2.74 mm day⁻¹) than at Gurdaspur (2.17 mm day⁻¹), with maximum values observed in April and minimum in December. The higher ET o at Ludhiana was attributed to higher temperature, wind speed, sunshine hours, and lower relative humidity. [12] studied in western China and got similar results with respect their climatic regions. The ET o estimated using the Hargreaves method for the years 2016 to 2024 are shown in Fig. 2. Similar to other methods, the highest monthly values were observed during the summer months, particularly in March, April, and May ranging from 148.69 to 189.99 mm when higher temperatures lead to greater evaporative demand. The monsoon and post-monsoon months exhibited relatively lower values ranging from 101.68 to 140.37 mm consistent with reduced temperature and increased cloudiness. The annual totals ranged between 1302.28 mm in 2016 and 1760.72 mm in 2018, indicating inter-annual variability influenced by climatic conditions. These results emphasize the importance of understanding seasonal evapotranspiration dynamics for effective water management in the micro-watershed especially where irrigation is being done using harvested water and pumping from bore wells strictly following irrigation scheduling and micro irrigation methods. The Hargreaves method in the present study showed comparatively higher ET o values during summer months, which may be attributed to its strong dependence on temperature. Hargreaves depends mainly on temperature Semi-arid regions have high temperature amplitude Therefore overestimation occurs during hot months. Similar observations were reported in Berti. et al., 2014 [6] studies where the uncalibrated Hargreaves method overestimated ET₀ by about 18.9% with a mean error of 0.44 mm d⁻¹, and the discrepancies became more pronounced during summer, reaching nearly 1 mm d⁻¹. This indicates that although the Hargreaves method performs reasonably well in semi-arid conditions with limited climatic data, it tends to overestimate. s The monthly and annual ET o estimated using the Priestley-Taylor method are given in [5] in Italy, Similar findings were reported, where regions with extremely high ET o values (>1300 mm year⁻¹) were mainly observed in hot lowland areas, while mountainous regions exhibited much lower ET o values (<500 mm year⁻¹).

As shown in Fig. 4 and Table.

Conclusion

The present study evaluated and compared reference evapotranspiration (ET o ) estimated using the CROPWAT model, Penman-Monteith, Hargreaves, and Priestley-Taylor methods for the Halayapura-1 micro-watershed under semi-arid climatic conditions during the period 2016-2024. The results revealed clear seasonal and inter-annual variations in ET o , with higher evapotranspiration observed during the summer months (March-May) due to elevated temperature and solar radiation, while lower values occurred during the monsoon and post-monsoon periods because of increased humidity and cloud cover. Among the methods evaluated, the CROPWAT and Hargreaves methods produced comparatively higher annual ET o values, indicating greater sensitivity to temperature variations and a tendency to overestimate evapotranspiration under hot semi-arid climatic conditions. In contrast, the Priestley-Taylor method generated relatively lower ET o estimates because it primarily depends on radiation parameters and does not adequately account for aerodynamic effects. The FAO Penman-Monteith method, which incorporates multiple meteorological parameters, provided more reliable and physically based ET o estimates and was therefore considered the standard method for comparison. Regression analysis revealed strong agreement between all methods and the Penman-Monteith method, with coefficient of determination values greater than 0.89. Among the evaluated methods, the CROPWAT model showed the highest agreement with the Penman-Monteith method (R² = 0.9245), followed closely by the Hargreaves method (R² = 0.922), indicating that both methods are suitable for estimating reference evapotranspiration in data-scarce semi-arid regions.

Overall, the study demonstrates that all the evaluated methods can effectively estimate reference evapotranspiration under semi-arid conditions, although their performance varies depending on climatic factors. The findings provide useful information for irrigation scheduling, crop water requirement estimation, and sustainable water resource management in the micro-watershed.

The study also highlights the importance of selecting appropriate ET o estimation methods for efficient utilization of limited water resources in semi-arid agricultural regions.

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