scholarly journals Water footprint assessment of the Colombian cocoa production

2015 ◽  
Vol 19 (9) ◽  
pp. 823-828 ◽  
Author(s):  
Oscar O. Ortiz-Rodriguez ◽  
Carlos A. Naranjo ◽  
Rafael G. García-Caceres ◽  
Raquel A. Villamizar-Gallardo
Keyword(s):  
Climatic Condition ◽  
Water Footprint ◽  
Meteorological Conditions ◽  
Water Requirement ◽  
Crop Evapotranspiration ◽  
Crop Water ◽  
Irrigation Requirement ◽  
Cocoa Production ◽  
Province Level ◽  
Theobroma Cacao L

ABSTRACTThe main objective of the present research was to calculate the water footprint of the Colombian cocoa (Theobroma cacao L.) production. The evaluation of crop water requirement and irrigation requirement were based on climate, soil and crop conditions in the country. The water requirement estimation was based on data from six municipalities selected for their representativeness of the highest yield, productivity and commercial dynamics of the country. The results show that the Water footprint reached 17,100 m3 t-1. At the province level, the highest record for this parameter was observed in Tolima, with 23,239 m3t-1, while Huila registered the lowest level, with 13,475 m3t-1. Water use per crop unit can be influenced not only by agro-meteorological conditions, but also by the level of production. Therefore, a region with a low water footprint value for a specific crop usually has a favorable climatic condition. Crop evapotranspiration was found to be relatively low, and the highest yields were obtained in association with more productive cropping levels. Given the complexity of a hydrological phenomenon like crop evapotranspiration, the magnitude of these differences may be considered to be small.

scholarly journals Crop water and irrigation requirements of some selected crops in southwestern hydrological zone of Nigeria

2021 ◽  
Vol 12 (1) ◽  
pp. 117-125
Author(s):  
GA Ali ◽  
TA Ademiju ◽  
JA Osunbitan
Keyword(s):  
Root Zone ◽  
Crop Coefficient ◽  
Field Capacity ◽  
Soil Parameters ◽  
Crop Evapotranspiration ◽  
Crop Water ◽  
Irrigation Requirement ◽  
Southwestern Nigeria ◽  
Hydrological Zone ◽  
Water Melon

This study was carried out to determine the crop water and irrigation requirement of some selected crops in southwestern Nigeria. The crops are cucumber, water melon, maize, groundnut, eggplant and tomato. Irrigation requirement and crop coefficient for each crops were determined from the interrelationships of the evapotranspiration, soil type, bulk density, field capacity and the effective root zone of the crops at the selected locations using CROPWAT for windows version 8. Soil parameters used for analysis were determined from laboratory experiment. The crop evapotranspiration and water requirement for cucumber varied from 2.52 to 7.21mm/day and 17 to 73.2mm/dec, respectively, for maize from 1.36 to 6.35mm/day and 5.1 to 63.5mm/dec respectively, for watermelon varied from 2.59 to 6.67mm/day and 25.9 to 73.3mm/dec respectively, for eggplant varied from 1.92 to 6.35 mm/day and 15.9 to 64.4mm/dec respectively. The irrigation requirement for water melon and cucumber recorded the highest value of 461.6 and 497.4mm/dec respectively, an indication that the two crops require more water for physiological activities. The reduction in the values of crop coefficient was observed during the study which could be attributed to the reduction in evapotranspiration at the late stage of growth. The findings also showed that known quantities of irrigation water could be used in producing crops optimally.

scholarly journals Temporal Downscaling of Crop Coefficient and Crop Water Requirement from Growing Stage to Substage Scales

2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Songhao Shang
Keyword(s):  
Water Management ◽  
Reference Evapotranspiration ◽  
Crop Coefficient ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Crop Evapotranspiration ◽  
Agricultural Water ◽  
Crop Water ◽  
Agricultural Water Management

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.

scholarly journals Estimation of Arecanut Crop Evapotranspiration Rate using Remote Sensing

2020 ◽  
Vol 9 (4) ◽  
pp. 1814-1817
Keyword(s):  
Remote Sensing ◽  
Hydrological Cycle ◽  
Remote Sensing Data ◽  
Global Scale ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Landsat 8 ◽  
Crop Evapotranspiration ◽  
Crop Water ◽  
Evapotranspiration Rate

Arecanut is a plantation crop sustains for decades and its crop water demand varies with the age. For scheduling and management of irrigation water, crop water requirement information is important. To calculate the crop water requirement, estimation of evapotranspiration is crucial. The term Evapotranspiration (ET) refers to transport of water molecules into the atmosphere from soil (soil evaporation) and vegetation (transpiration) surfaces. It is a most important component of hydrological cycle and also the most difficult factor to quantify. Crop water need is the amount of water required for balancing loss due to evapotranspiration. There are different methods proposed by researchers for the estimation of evapotranspiration. The conventional methods of evapotranspiration estimation from ground data are tedious. The advancement in remote sensing data provides estimation of evapotranspiration in a global scale. The invention of thermal remote sensing has benefitted greatly since it reduces the field data requirement for estimation of ET. It also helps to understand spatial distribution of landmass and different estimates also in estimation of evapotranspiration over a larger extent timely and periodically. In this study to estimate Arecanut crop evapotranspiration Hargreaves Samani, Penman Monteith and Priestly Taylor methods were used and compared. Arecanut crop evapotranspiration rate estimated form Landsat 8 and MODIS data are showed similar range of values between 3 to 4.45 mm/day. The study area covers an area of 835.3 hectares of Arecanut crop and the gross crop water need is found to be 23059 m 3 .

scholarly journals APPLICATION OF SIMPLIFIED SURFACE ENERGY BALANCE INDEX (S-SEBI) FOR CROP EVAPOTRANSPIRATION USING LANDSAT 8

2018 ◽  
Vol XLII-1 ◽  
pp. 33-37 ◽  
Author(s):  
A. Basit ◽  
R. Z. Khalil ◽  
S. Haque
Keyword(s):  
Energy Balance ◽  
Surface Energy ◽  
Surface Energy Balance ◽  
Irrigation Scheduling ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Landsat 8 ◽  
Crop Evapotranspiration ◽  
Crop Water ◽  
Balance Index

<p><strong>Abstract.</strong> Assessment and monitoring of crop water requirement (CWR) or crop evapotranspiration (ETc) over a large spatial scale is the critical component for irrigation and drought management. Due to growing competition and increasing shortage of water, careful utilization of water in irrigation is essential. The usage of water for irrigation/agriculture is a top priority for countries like Pakistan, where the GDP mostly based on agriculture, and its scarcity may affect the crop production. Remote sensing techniques can be used to estimate crop water requirement or crop evapotranspiration which can help in efficient irrigation. Simplified-surface energy balance index (SSEBI) model is used to estimate evapotranspiration (ET) of wheat during 2015&amp;ndash;16 growing period in Tando Adam, Sindh. Landsat-8 satellite data for the corresponding years were used. With the help of National Agromet Centre report chart of Crop coefficient (Kc) the CWR, ETc of all phonological stages were estimated. Results indicated that maximum ET and maximum CWR were found in the third leaf to tillering stage with a value of 0.75 and 0.89 respectively. This study will help in managing and monitoring of ET spatial distribution over irrigated crops which results in better irrigation scheduling and water consumption.</p>

scholarly journals Establishment of irrigation schedule for rice cropping seasons in the Long Xuyen Quadrangle, Vietnam using Cropwat model

2018 ◽  
Author(s):  
Truong An Dang
Keyword(s):  
Irrigation Water ◽  
Meteorological Data ◽  
Irrigation Schedule ◽  
Development Stage ◽  
Water Requirement ◽  
Crop Water ◽  
Irrigation Requirement ◽  
Proposed Model ◽  
Cropping Seasons ◽  
Water Amount

This study is conducted to determine the appropriate irrigation water amount for three main cropping seasons (TMCS) of rice in the Long Xuyen Quadrangle, Vietnam (LXQ). In the work, the Cropwat crop model was used to calculate irrigation water amount for winter-spring (WS), summer-autumn (SA) and autumn-winter (AW) crops based on meteorological data collected in period from 1998 to 2017. Simulation results carried out that WS crop was needed more irrigation water than SA and AW crops. The highest irrigation water requirement (IWR) of WS, SA and AW crops occurred on development stage with approximately values 207.1 mm, 205.8 mm and 102.3 mm respectively. The results showed that the proposed model is successfully applied to define crop water requirement (CWR) and irrigation requirement in the context of climate change leading to irrigation water scarcity.

scholarly journals Implication of Climate Change On Crop Water Requirement: A Regional Case Study in The Semi-Arid Region of Western Maharashtra, India

2021 ◽  
Author(s):  
Shubham Anil Gade ◽  
Devidas D Khedkar
Keyword(s):  
Climate Change ◽  
Water Management ◽  
Hydrological Cycle ◽  
Monsoon Season ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Present Condition ◽  
Crop Evapotranspiration ◽  
Crop Water ◽  
Reanalysis Dataset

Abstract The hydrological cycle has been massively impacted by climate change and human activities. Thus it is of the highest concern to examine the effect of climate change on water management, especially at the regional level, to understand possible future shifts in water supply and water-related crises, and to provide support for regional water management. Fortunately, there arises a high degree of ambiguity in determining the effect of climate change on water requirements. In this paper, the Statistical DownScaling (SDSM) model is applied to simulate the potential impact of climate on crop water requirement (CWR) by downscaling ET0 in the region of Western Maharashtra, India for the future periods viz., 2030s, 2050s, and 2080s across three meteorological stations (Pune, Rahuri, and Solapur). Four crops i.e. cotton, soybean, onion, and sugarcane are selected during the analysis. The Penman-Monteith equation is used to calculate reference crop evapotranspiration (ET0), which further in conjunction with the crop coefficient (Kc) equation is used to calculate crop evapotranspiration (ETc) / CWR. The predictor variables are extracted from the NCEP reanalysis dataset for the period 1961-2000 and the HadCM3 under H3A2 and H3B2 scenarios for the period of 1961 – 2099. The results indicated by SDSM profound good applicability in downscaling due to satisfactory performance during calibration and validation for all three stations. The projected ET0 indicated an increase in mean annual ET0 as compared to the present condition during the 2030s, 2050s, and 2080s. The ET0 would increase for all months (in summer, winter, and pre-monsoon seasons) and decrease from June to September (monsoon season). The estimated future CWR show variation in the range for cotton (-0.97 to 2.48%), soybean (-2.09 to 1.63 %), onion (0.49 to 4.62 %), and sugarcane (0.05 to 2.86 %).

Study on water requirement of rice using CROPWAT model for Lucknow division of Uttar Pradesh

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Amesh Verma ◽  
Anshu Gangwar ◽  
Munish Kumar ◽  
Ramesh Kumar Verma
Keyword(s):  
Water Stress ◽  
Water Balance ◽  
Uttar Pradesh ◽  
Water Requirement ◽  
Balance Model ◽  
Crop Evapotranspiration ◽  
Crop Water ◽  
Yield Responses ◽  
Crop Water Stress

Due to the overuse of available water resources, it has become very important to define appropriate strategies for planning and management of irrigated farmland one of the major practices adopted by the researchers for estimating water requirement of the crop is modeling. For determination of crop evapotranspiration and yield responses to water in agro-ecological units (AEUs) of Lakhimpur Kheri, Sitapur, Lucknow, Unnao, Hardoi, Rai Bareilly district of Uttar Pradesh, CROPWAT 8.0 model is used, it includes a simple water balance model that allows the simulation of crop water stress conditions and estimation of yield reductions based on well-established methodologies. This paper is been focused on the study of water requirement for rice crop in Lucknow division of Uttar Pradesh.

scholarly journals Application of FAO-CROPWAT Modelling on Estimation of Irrigation Scheduling for Paddy Cultivation in Batticaloa District, Sri Lanka

2020 ◽  
Author(s):  
A. Narmilan ◽  
M. Sugirtharan
Keyword(s):  
Sri Lanka ◽  
Irrigation Scheduling ◽  
Water Requirement ◽  
Management Approach ◽  
Crop Water ◽  
Irrigation Requirement ◽  
Water Requirements ◽  
The North ◽  
June July ◽  
Irrigation Requirements

Agriculture sector is one of the main sources of income in the North eastern and some of the North western parts of Sri Lanka. Over the past decade, many countries around the world have witnessed a growing scarcity and competition for water among different users. Since Agriculture is the major user of water, improving agricultural water management is essential to any irrigation management approach specially to apply the exact amount of water to the field in order to meet crop water requirement. This study aims to estimate water requirement of rice by using the model CROPWAT. According to the study, effective rainfall was found to be 601mm and 133 mm in Maha and Yala season respectively. Total crop water requirements are 349 mm and 436 mm in Maha and Yala season respectively. Irrigation scheduling carried out by CROPWAT revealed that, the gross irrigation requirement is 473 mm and net irrigation requirement is 331 mm. Net scheme irrigation requirements are 40, 106, 100 and 22 mm per month in May, June, July and August respectively. Further, flow of net scheme irrigation requirements is found to be 0.15, 0.41, 0.37 and 0.08 l/s/ha in May, June, July and August respectively. Therefore, the model for planning of irrigation water requirements of rice is very important for efficient utilization of water and to meet the possible change of climate in agricultural sector.

The use of earth observation methods for estimating regional crop evapotranspiration and yield for water footprint accounting

2017 ◽  
Vol 156 (5) ◽  
pp. 599-617 ◽  
Author(s):  
G. Papadavid ◽  
L. Toulios
Keyword(s):  
Remote Sensing ◽  
Crop Yield ◽  
Water Footprint ◽  
Earth Observation ◽  
Soil Parameters ◽  
Yield Prediction ◽  
Crop Evapotranspiration ◽  
Crop Water ◽  
Water Requirements ◽  
Remote Sensing Techniques

AbstractRemote sensing can efficiently support the quantification of crop water requirements included in the goal of assessing water footprints, which is to analyse how human activities or specific products relate to issues of water scarcity and pollution and identify how activities and products can become more sustainable from a water perspective. Remote sensing techniques have become popular in estimating actual crop evapotranspiration and hence crop water requirements in recent decades due to the advantages they offer to users, e.g. low cost, regional data and use of maps instead of point measurements as well as saving time. The use of earth observation data supports models’ accuracy in the procedure for assessing water footprint, since no average values are used: instead, users have real values for the specific parameters.The present study provides two examples of how remote sensing techniques are used essentially for estimating evapotranspiration along with crop yield, two basic parameters, for assessing water footprint. Two different case studies have been illustrated to define the methodology proposed, which refers to Mediterranean conditions and can be applied after inferring the necessary field data of each crop. The first case study refers to the application of Surface Energy Balance Algorithm for Land (SEBAL) for estimating evapotranspiration, while the second refers to the Crop Yield prediction. Both elements, such as evapotranspiration and crop yield, are vital for water footprint accounting. Firstly, the SEBAL was adopted, under the essential adaptations for local soil and meteorological conditions for estimating groundnut water requirements. Landsat-5 TM, Landsat-7 Enhanced Thematic Mapper+ and Landsat 8 OLI images were used to retrieve the required spectral data. The SEBAL model is enhanced with empirical equations regarding crop canopy factors, in order to increase the accuracy of crop evapotranspiration estimation. Maps were created for evapotranspiration (ET) using the SEBAL modified model for the area of interest. The results were compared with measurements from an evaporation pan, used as a reference. Statistical comparisons showed that the modified SEBAL can predict ETc in a very effective and accurate way and provide water footprint modellers with high-level crop water data. Yield prediction plays a vital role in calculating water footprint. Having real values rather than taking reference (or averaged) values from FAO is an advantage that Earth Observation means can provide. This is very important in econometric or any other prediction models used for estimating water footprint because using average data reduces accuracy. In this context, crop and soil parameters along with remotely sensed data can be used to develop models that can provide users with accurate yield estimations. In a second step, crop and soil parameters along with the normalized difference vegetation index were correlated to examine whether crop yield can be predicted and to define the actual time-window to predict the yield. Statistical and remote sensing techniques were then applied to derive and map a model that can predict crop yield. The algorithm developed for this purpose indicates that remote sensing observations can predict crop yields effectively and accurately. Using the statistical Student's t test, it was found that there was no statistically significant difference between predicted and real values for crop yield.

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