scholarly journals Irrigation water requirement of rice in Long Xuyen Quadrangle area, Vietnam in the context of climate change

2021 ◽  
Vol 21 (1) ◽  
pp. 18-23
Author(s):  
SEUNG KYU, LEE ◽  
TRUONG AN, DANG

Climate variability is deeply affecting all aspects of human life including agricultural sector. In the present study the CROPWAT model was used to estimate reference evapotranspiration (ETo), crop evapotranspiration (ETc), effective rainfall (ER) and crop water requirement (CWR) of summer-autumn rice crop and its yield during baseline period (2002-2017) and also under representative concentration pathways (RCPs) 4.5 scenario for 2020s, 2055s and 2090s-time scales for Long Xuyen Quadrangle (LXQ) area of Vietnam. It was found that the ER significantly increased by 6.2, 16.9 and 15.4 per cent, respectively in 2020, 2055 and 2090; ETo and ETc increased by 2.1 and 2.3 per cent, respectively in 2020s; 4.4 and 5.8 in 2055; and 5.8 and 7.7 per cent in 2090 compared to baseline. The CWR also increased approximately 4.6, 4.4 and 3.5 per cent, respectively in 2020, 2055 and 2090 and consequent decrease in rice yield by 6.5, 7.9 and 10.4 per cent, respectively. Results showed that if the crop planting date is delayed by 20 days, the rice yield would increase approximately 4.9, 7.9 and 9.9 per cent, respectively in three-time scales of RCP 4.5 scenario, compared to base line period.

2021 ◽  
Author(s):  
Smaranika Mahapatra ◽  
Madan Kumar Jha

<p>Agricultural sector, being the largest consumer of water is greatly affected by climatic variability and disasters. Most parts of the world already face an enormous challenge in meeting competitive and conflicting multi-sector water demands. Climate change has further exacerbated this challenge by putting the sustainability of current cropping patterns and irrigation practices in question. For ensuring climate-resilient food production, it is crucial to examine the patterns of the projected climate and potential impacts on the agricultural sector at a basin scale. Hence, this study was carried out for an already water-scarce basin, Rushikulya River basin (RRB), located in the coastal region of eastern India. The bias-corrected NorESM2-MM general circulation model of Coupled Model Intercomparison Project-6 (CMIP6) was used in this study under four shared socioeconomic pathway (SSPs) scenarios, namely SSP126, SSP245, SSP370 and SSP585. The projected climatic parameters and crop water demands of the basin were analyzed assuming existing cropping pattern in the future. Analysis of the results reveals a significant and rapid increase in the temperature at a rate of 0.02-0.5ºC/year during 2026-2100 under all SSPs except SSP126, whereas the rainfall is expected to increase slightly during 2026-2100 as compared to the baseline period (1990-2016), especially in the far future (2076-2100) under all the SSPs. In contrast, monsoon rainfall is predicted to decrease under SSP245 and SSP370, while a slight increase in the monsoon rainfall is evident under SSP126 and SSP585. Although the rainy days will decrease slightly in the future 25-year time window, the number of heavy rainfall events is predicted to increase by two to three times. Also, retrospective analysis of rainfall and evapotranspiration suggested an existence of rainfall deficit (rainfall-evapotranspiration) in the basin throughout the year, except during July to September. The rainfall deficit in the basin during 2026-2100 is found to remain more or less same in the non-monsoon season, except for the month of October under SSP245, SSP370 and SSP585 scenarios where deficit increases by two folds. Rainfall is expected to be in surplus by 4 to 5 times higher under all SSPs except for SSP245. As to the evapotranspiration, an insignificant increasing trend is observed under future climatic condition with only 2 to 4% rise in the crop water demand compared to the baseline period. As the basin is already water stressed during most months in a year under baseline and future climatic conditions, continuing the current practice of monsoon paddy dominant cultivation in the basin will further aggravate this situation. The results of this study will be helpful in formulating sustainable irrigation plans and adaptation measures to address climate-induced water stress in the basin.</p><p><strong>Keywords:</strong> Climate change; CMIP6; SSP; Monsoon rainfall; Temperature; Crop water demand.</p>


2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Songhao Shang

Crop water requirement is essential for agricultural water management, which is usually available for crop growing stages. However, crop water requirement values of monthly or weekly scales are more useful for water management. A method was proposed to downscale crop coefficient and water requirement from growing stage to substage scales, which is based on the interpolation of accumulated crop and reference evapotranspiration calculated from their values in growing stages. The proposed method was compared with two straightforward methods, that is, direct interpolation of crop evapotranspiration and crop coefficient by assuming that stage average values occurred in the middle of the stage. These methods were tested with a simulated daily crop evapotranspiration series. Results indicate that the proposed method is more reliable, showing that the downscaled crop evapotranspiration series is very close to the simulated ones.


2021 ◽  
Author(s):  
Dires Tewabe ◽  
Atklte Abebe ◽  
Amare Tsige ◽  
Alebachew Enyew ◽  
Mulugeta Worku

Abstract Background Population growth, high water competition, and the effect of climate change have caused water shortage problems in the Nile basin, Ethiopia. Proper water management improves water efficiency; determining the water requirement of field crops is an option for improving water productivity. Methods In this study, the CROPWAT 8.0 model, local climate, and soil data were used to determine crop water requirement (CWR) and irrigation scheduling of wheat at Koga and Rib irrigation scheme, Nile basin. The Penman-Monteith and United States Department of Agriculture (USDA) soil conservation service methods were used to compute the reference evapotranspiration (ETo) and effective rainfall. Five levels of water depth (50%, 75%, 100%, 125%, and 150%) of the model and two irrigation intervals (14 and 21 days) were arranged in a Randomized Completely Block Design (RCBD). Results The results showed that at Koga, irrigating 75% of CROPWAT simulated water depth (9.3 mm, 22.9 mm, 44.1 mm, and 25.8 mm at initial, development, middle and late-stage respectively) gave 3.37 t ha− 1 wheat yield and 1.01 kg m− 3 water productivity. The result at Rib showed that irrigating 75% of the model (9.1 mm, 23.6 mm, 47.2 mm, and 34.2 mm at initial, development, middle, late-stage) respectively) gave 4.27 t ha− 1 yield and 1.81 kg m− 3 water productivity of wheat. The reference evapotranspiration was varied from 4.86 mm day− 1 to 3.14 mm day− 1 at Koga and from 4.67 mm day− 1 to 2.36 mm day− 1 at Rib scheme. The irrigation requirement of wheat at Koga was 376.9 mm dec− 1 while at Rib was 379.9 mm dec− 1. Conclusions This study showed that the CROPWAT model is an important tool to compute the crop water requirement of field crops in irrigated agriculture.


2018 ◽  
Vol 8 (03) ◽  
Author(s):  
Deepika Yadav ◽  
M. K. Awasthi ◽  
R. K. Nema

Improved and efficient irrigation water management through precise estimation of crop water requirement has a vital role to play in ensuring food security. However, the crop water requirement data of field crops are not locally available. In view of this, present investigation was aimed at quantifying the crop water requirement of rabi and kharif season crops grown under paired row planting in different agro climatic conditions of Madhya Pradesh. The crop water requirement was calculated based on the already developed crop coefficient and reference evapotranspiration. Daily weather data of 35 years (1979 to 2013) for twenty districts of Madhya Pradesh was collected to determine the reference evapotranspiration using Aquacrop model. The study revealed that the daily ETo increased continuously from 1st SMW to its maximum values during 21st-22nd SMW, thereafter decreased sharply and remains low from 30th to 34th SMW in all selected districts. The highest value of ETo (11.0 mm day-1) was found in Datia at 21st SMW and lowest in Betul i.e. 2.2 mm day-1 at 32nd SMW. The daily water requirement estimates showed that the water requirement of chickpea, wheat and lentil i.e. 1.73 lpd, 0.70 lpd and 0.49 lpd respectively is highest in Jabalpur. Sugarcane has the highest water requirement 13.56 lpd in Narsinghpur during mid season. In all kharif crops cotton has highest water requirement 6.53 lpd in Harda followed by sesame and groundnut i.e. 2.75 lpd and 2.46 lpd respectively in Datia. These results can be used in efficient management of irrigation water under drip irrigation system in selected district of Madhya Pradesh.


2021 ◽  
Vol 21 (4) ◽  
pp. 427-433
Author(s):  
Laishram Kanta Singh ◽  
Madan K. Jha ◽  
V.M. Chowdary ◽  
Srikanta Sannigrahi

The agricultural sector is the primary consumer of water resources around the world, and the need for additional food production for growing population further exerts more pressure on water resources. In this study, crop water demand was assessed spatially and temporally for a case study area, Damodar Canal Command (DCC) using geospatial techniques. Crop evapotranspiration was estimated for all the crop seasons using reference evapotranspiration and Fraction of Vegetation cover (FV) that was used as a surrogate for crop coefficient. The reference evapotranspiration (ET ) was calculated using the FAO o Penman-Monteith method. FV was computed based on Normalized Difference Vegetation Index (NDVI) derived from MODIS satellite imagery and its value ranges from 0 to 1. The maximum and minimum reference evapotranspiration values were estimated as 8.44 and 1.88 mmday-1 in May and September, respectively during the normal year 2004. The average monthly crop water demand was maximum in May i.e. 8.08 mmday-1. Among all crop seasons, Boro season has the maximum crop water demand followed by Aus and Aman seasons with maximum ET as 496, 438 and 328 mm, respectively. Total annual crop c water demand for normal year, 2004 was estimated at 1237 mmyr-1 in the study area. Spatially and temporally distributed crop water demand estimates help the irrigation planners to devise the strategies for effective irrigation management.


2021 ◽  
Author(s):  
Hanish Dadool ◽  
Sai Jagadeesh Gaddam ◽  
Prasanna Venkatesh Sampath

<p>Increasing anthropogenic stresses have challenged the global population's ability to meet the growing demands of food, energy, and water (FEW). With the population set to hit 9 billion by 2050, it becomes indispensable to manage these three vital resources sustainably. Moreover, climate change is expected to have adverse consequences on agriculture, which is one of the primary occupations in developing countries like India. Extreme weather events caused by climate change could impact agricultural productivity severely, affecting economic-food-water-energy security. Hence, there is a dire need to study the impact of climate on agricultural production and its supporting resources – water and energy. Although studying the nexus between FEW is gaining attention lately, evaluating the future FEW interactions in the agricultural sector with an emphasis on climate change is missing. Therefore, this study employs a data-intensive approach to quantify the current and future FEW interactions under the impact of climate change.</p><p>First, FAO's CROPWAT 8.0 model was used to estimate crop water requirements for major crops like paddy, sugarcane, groundnut, cotton, and maize in the study area of Andhra Pradesh state, India. CROPWAT uses a soil water balance approach that requires information about several datasets like evapotranspiration, rainfall, soil, and crop information. Massive datasets such as farm-level agricultural data, station-wise rainfall data, and reference evapotranspiration data were incorporated into the model. Second, we calculate the future crop water requirements using future rainfall and temperature datasets, available till 2095, from Global Climate Models (GCMs) under the Representative Concentration Pathway (RCP) 4.5 emission scenario. To achieve this at the district-scale, we downscaled the information regarding temperature using the delta change method and applied the Thornthwaite method to estimate the reference evapotranspiration. Then, energy consumed by each crop in every district was quantified. Third, we estimated the current and future FEW interactions using the commonly employed two-at-one-time methodology.</p><p>Results indicated that water-intensive crops like paddy and sugarcane account for most groundwater and energy consumption. Southern districts of the state consume relatively more groundwater and energy than the northern regions. Further, high water-intensive crops like paddy were being cultivated in several dry regions, furthering the groundwater resources depletion and rising energy costs. For instance, in Kurnool district, the irrigation water requirements for paddy increased by almost 20% from the 2020s (644 mm) to the 2090s (772 mm). Clearly, such an increase can be attributed to a changing climate causing increased evapotranspiration. The resulting increase in groundwater and energy consumption, has the potential to endanger food and water security in countries like India. The approach outlined in this study also allows us to identify vulnerable hotspots that would enable policymakers to design effective adaptation strategies in the agricultural sector. The synergistic benefits offered by FEW nexus approaches have the potential to ensure food security at local and global scales.</p>


Reference evapotranspiration (ET0) is a rudimental variable in the estimation of crop water requirement, and preparation of irrigation schedule. Prediction of ET0 is a necessitous one for estimation of crop water requirement in future time step. In this paper ET0 is predicted using Artificial Neural Network (ANN) by different inputs Like Temperature, Cloud cover, Vapor pressure, Precipitation and its combinations by various models. Before prediction, the predictability of all the input time series is calculated individually and the effect of predictability on prediction is analyzed in models having single predictor. In spite of inserting additional predictor in input, the reason for increase of Root mean squared error is justified in terms of predictability in the models having multiple predictors. Also it is seen that the performance of models with multiple predictors is better when compared to single predictor models in the estimation of ET0.


2017 ◽  
Vol 9 (1) ◽  
pp. 441-444
Author(s):  
J. N. Lokhande ◽  
M. U. Kale ◽  
S. B. Wadatkar

Climate change scenario badly affects the agriculture. The present study aimed to characterize the trend in maximum temperature and crop water requirement over a last decade at Akola station (Maharashtra State), because of changing trend in meteorological parameters. Study investigated the trends in temperature and reference evapotranspiration using various statistical parameters like mean, coefficient of variation, coefficient of skewness and coefficient of kurtosis. Monthly maximum air temperature showed slightly decreasing trend over summer season while increasing trend over monsoon and winter season. On the contrary, the monthly reference evapotranspiration showed decreasing linear trend over monsoon and winter season, while increasing trend over summer season. The study concluded that as the monthly reference evapotranspiration showed decreasing linear trend over cropping seasons (i.e. monsoon and winter), the crop water requirement at Akola station shall decrease in future.


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