Abstract
Climate variability impacts the components of hydrological cycle especially evapotranspiration (ET) and soil moisture, that plays a crucial role in determining water flux of an agriculture system and is thus, essential to study the response of ET to climate change. The present study is an attempt to understand the trend in observed ET (1978–2003) and variation in projected ET RegCM4.0, RCP 4.5 scenario during 2040–2060. Observed ET is compared with simulated ET using NCEP, NASA Power, RegCM4.0 and agriculture field data. Apart from studying the effect of relative humidity (RH), solar radiation (SLR), minimum and maximum temperature and wind speed (WS) on ET, the FAO Penman–Monteith and Priestly–Taylor methods in CERES Rice and CERES Wheat crop model were used to simulate ET. Further, the cumulative impact of rainfall and ET on agriculture drought has been estimated based on standardized Reconnaissance Drought Index (RDIst). The result shows a declining trend of ET during 1978–2003, but an increase during 2040s (2040–2061) for both wheat and rice. Overall, the ET simulated using weather data input from agriculture field shows highest concordance with observed ET, followed by NASA/RegCM4 and NCEP. Moreover, the FAO Penman–Monteith gives more accurate result in comparison to the Priestley–Taylor method. Environmental modification suggests that RH is the most influential parameter for ET followed by temperature, SLR and WS. Based on RDIst it was observed that rainfall is negatively associated with ET and their cumulative effect on water availability can be efficiently estimated using drought index.
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References
Abtew W, Melesse A (2013) Evaporation and Evapotranspiration: Measurements and Estimations. Springer Science Business Media, Dordrecht, pp 197–202
Aggarwal PK, Mall RK (2002) Climate Change and Rice Yields in Diverse Agro-Environments of India. II. Effect of uncertainties in scenarios and crop models on impact assessment. Clim Change 52:331–343
Babatunde OA, Abiye OE, Sunmonu LA, Olufemi AP, Ayoola MA, Akinola OE, Ogolo EO (2017) A comparative evaluation of four evapotranspiration models based on Eddy Covariance measurement over a grass-covered surface in Ile-Ife, Southwestern Nigeria. Model Earth Syst Environ 3(4):1273–1283
Bai H, Tao F (2017) Sustainable intensification options to improve yield potential and eco-efficiency for rice-wheat rotation system in China. Field Crops Res 211: 59(4):89–105
Banerjee S, Chatterjee S, Sarkar S, Jena S (2016) Projecting future crop evapotranspiration and irrigation requirement of potato in lower gangetic plains of India using the CROPWAT 8.0 model. Am J Potato Res 59(4):313–327
Blaney HF, Criddle WD (1950) Determining water requirements in irrigated areas from climatological and irrigation data. USDA(SCS) 96:48
Doorenbos J, WO Pruitt (1975) Pruitt WO (1975) Guidelines for predicting crop water requirements irrigation and drainage paper 24. FAO, Rome, pp 1–144
Espadafor M, Lorite IJ, Gavilan P, Berengena J (2011) An analysis of the tendency of reference evapotranspiration estimates and other climate variables during the last 45 years in Southern Spain. Agric Water Manag 98:1045–1061
Federer CA, Vorosmarty C, Fekete B (1996) Intercomparison of methods for calculating potential evaporation in regional and global water balance model. Water Resour Res 32:2315–2321
Gao Z, He J, Dong K, Li X (2017) Trends in reference evapotranspiration and their causative factors in the West Liao River basin (China). Agric For Meteorol 232:106–117
Giorgi F (2012) RegCM4: model description and preliminary tests over multiple CORDEX domains. Clim Res 52:7–29
Grace B, Quick B (2013) A comparison of methods for the calculation of potential evapotranspiration under the windy semi-arid conditions of southern Alberta. Can Water Resour J 13:9–19
Guo D, Westra S, Maier HR (2017) Sensitivity of potential evapotranspiration to changes in climate variables for different Australian climatic zones. Hydrol Earth Syst Sci 21:2107–2126
Hamed KH (2008) Trend detection in hydrologic data: the Mann–Kendall trend test under the scaling hypothesis. J Hydrol 349:350–363
Hargreaves GH, Samani ZA (1985) Reference crop evapotranspiration from temperature. Appl Eng Agric 1:96–99
Irmak S, Kabenge I, Skaggs KE, Mutiibwa D (2012) Trend and magnitude of changes in climate variables and reference evapotranspiration over 116-yr period in the Platte River Basin, central Nebraska–USA. J Hydrol 421:228–244
IPCC (2013) Working group 1 fifth assessment report on climate change 2013: the physical science basis Geneva, Switzerland
Jepsen SM, Harmon TC, Ficklin DL, Molotch NP, Guan B (2018) Evapotranspiration sensitivity to air temperature across a snow-influenced watershed: Space-for-time substitution versus. J Hydrol 556:645–659
Jhajharia D, kumar R, Dabral PP, Singh VP, Choudhary RR, Dinpashoh Y (2015) Reference evapotranspiration under changing climate over the Thar Desert in India. Meteorol Appl 22(3):425–435
Jones JW, Hoogenboom G, Porter CH, Boote KJ, Batchelor WD, Hunt LA, Wilkens PW, Singh U, Gijsman AJ, Ritchie JT (2003) The DSSAT cropping system model. Eur J Agron 18:235–265
Kendall MG (1975) Rank correlation methods, 4th edn. Charles Griffin, London
Kumar M, Denis DM, Suryavanshi S (2016) Long-term climatic trend analysis of Giridih district, Jharkhand (India) using statistical approach. Model Earth Syst Environ 2:116. https://doi.org/10.1007/s40808-016-0162-2
Kundu S, Khare D, Mondal A (2017) Interrelationship of rainfall, temperature and reference evapotranspiration trends and their net response to the climate change in Central India. Theor Appl Climatol 130(4):879–900
Lal R, Stewart BA, Uphoff N, Hansen DO (2005) Climate change, soil carbon dynamics and global food. CRC Press, Boca Raton, pp 113–143
Lei H, Gong T, Zhang Y, Yang D (2018) Biological factors dominate the interannual variability of evapotranspiration in an irrigated cropland in the North China Plain. Agric For Meteorol 251:262–276
Lv Z, Liu X, Cao W, Zhu Y (2017) A model-based estimate of regional wheat yield gaps and water use efficiency in main winter wheat production regions of china. Sci Rep 7(1):6081
Madhu S, Kumar TVL, Barbosa H, Rao KK, Bhaskar VV (2015) Trend Analysis of evapotranspiration and its response to drought over India. Theor Appl Climatol 121(2):41–51
Mall RK, Aggarwal PK (2002) Climate change and rice yields in diverse agro-environments India. Evaluation of impact assessment models. Clim Change 52:315–330
Mall RK, Gupta BRD (2000) Wheat yield forecast models based on meteorological parameters. J Agrometerol 2(1):83–87
Mall RK, Gupta BRD (2002) Comparison of evapotranspiration models. Mausam 53(2):119–126
Mall RK, Sonkar G, Bhatt D, Sharma NK, Singh KK (2016) Managing impact of extreme weather events in sugarcane. Mausam 67(1):233–250
Mall RK, Gupta A, Sonkar G (2017) Effect of climate change on agricultural crops. Cur Dev Biotechnol Bioeng 1:23–46
Mall RK, Singh N, Singh KK, Sonkar G, Gupta A (2018) Evaluating the performance of RegCM4.0 climate model for climate change impact assessment on wheat and rice crop in diverse agro-climatic zones of Uttar Pradesh, India. Clim Change 149(3):503–515
Mann HB (1945) Non-parametric tests against trend. Econometrica 13:245–259
Meshram S, Kant S, Sahu KC (2014) Identification of meterological drought year for Varanasi. Recent Res Sci Technol 6(1):245–247
Milly PC, Dunne KA (2016) Potential evapotranspiration and continental drying. Nat Clim Change 6:946–949
Mishra A, Singh R, Raghuwanshi NS, Chatterjee C, Froebrich J (2013) Spatial variability of climate change impacts on yield of rice and wheat in the Indian Ganga Basin. Sci Total Environ 469:132–138
Pawar GS, Kale MU, Lokhande JN (2017) Response of AquaCrop model to different irrigation schedules for irrigated cabbage. Agric Res 6(1):73–81
Prabnakorn S, Maskey S, Suryadi FX, Fraiture CD (2018) Rice yield in response to climate trends and drought Index in the Mun River Basin, Thailand. Sci Total Environ 621:108–119
Priestly CHB, Taylor RJ (1972) On the assessment of surface heat flux and evaporation using large-scale parameters. Mon Weather Rev 100:81–92
Priya A, Islam A, Nema AK, Sikka AK (2015) Assessing sensitivity of reference evapotranspiration to changes in climate variables: a case study of Akola. India Mausam 66(4):777–784
Qian B, Jong RD, Huffman T, Wang H, Yang J (2016) Projecting yield changes of spring wheat under future climate scenarios on the Canadian Prairies. Theor Appl Climatol 123:651–669
Sentelhas PC, Gillespie TJ, Santos EA (2010) Evaluation of Penman–Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada. Agric Water Manag 975:635–644
Shelia V, Simunek J, Boote K, Hoogenboom G (2018) Coupling DSSAT and HYDRUS-1D for simulation of soil water dynamics in the soil-plant-atmosphere system. J Hydrol Hydromech 66(2):232–245
Shrivastava S, Kar SC, Sharma AR (2018) The DSSAT model simulations of soil moisture and evapotranspiration over central India and comparison with remotely-sensed data. Model Earth Syst Environ 4(1):27–37
Shweta, Krishna AP (2015) Selection of the best method of ETo estimation other than Penman–Monteith and their application for the humid subtropical region. Agric Res 4(2):215–219
Singh KK, Mall RK, Singh RS, Srivastava AK (2010) Evaluation of CANEGRO sugarcane model in East Uttar Pradesh, India. J Agrometerol 12(2):181–186
Singh PK, Singh KK, Rathore LS, Baxla AK, Bhan SC, Gupta A, G. B., et al (2016) Rice (Oryza sativa L.) yield gap using the CERES-rice model of climate variability for different agroclimatic zones of India. Curr Sci 110:405–413
Singh N, Mall RK, Sonkar G, Singh KK, Gupta A (2018)) Evaluation of RegCM4 climate model for assessment of climate change impact on crop production. Mausam 69(3):389–400
Tasakiris G, Vangelis H (2005) Establishing a drought Index incorporating evapotranspiration. Eur Water 9(10):3–11
Taxak AK, Murumkar AR, Arya DS (2014) Long-term spatial and temporal rainfall trends and homogeneity analysis in Wainganga basin, Central India. Weather Clim Extreme 4:50–61
Thornthwaite CW (1948) An approach toward a rational classification of climate. Geogr Rev 38:55–94
Wang W, Li C, Xing W, Fu (2017) Projecting the potential evapotranspiration by coupling different formulations and input data reliabilities: the possible uncertainty source for climate change impacts on hydrological regime. J Hydrol 555:298–313
White JW, Hoogenboom G, Kimball BA, Wall GW (2011) Methodologies for simulating impacts of climate change on crop production. Field Crop Res 124:357–368
Xu Z, Liu Z, Fu G, Chen Y (2010) Trends of major hydroclimatic variables in the Tarim River basin during the past 50 years. J Arid Environ 74(2):256–267
Zhao H, Xu Z, Zhao J, Huang W (2017) A drought rarity and evapotranspiration-based index as a suitable agricultural drought indicator. Ecol Indic 82:530–538
Acknowledgements
Authors thank the Climate Change Programme, Department of Science and Technology-New Delhi (Grant no: DST/CCP/CoE/80/2017(G)), for financial support. The authors wish to express their gratitude to India Meteorological Department, New Delhi for providing observed Evapotranspiration data. We are thankful to Department of Agronomy, Institute of Agricultural Sciences, B.H.U. for providing observed temperature, solar radiation, rainfall and wind speed data. We are grateful to CCCR- IITM for RegCM outputs from the domain CORDEX- South Asia. All contributors are thankfully acknowledged.
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Tyagi, S., Singh, N., Sonkar, G. et al. Sensitivity of evapotranspiration to climate change using DSSAT model in sub humid climate region of Eastern Uttar Pradesh. Model. Earth Syst. Environ. 5, 1–11 (2019). https://doi.org/10.1007/s40808-018-0513-2
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DOI: https://doi.org/10.1007/s40808-018-0513-2