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 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 %).

scholarly journals Crop Pattern Change and Crop Water Requirement Judgment using Remote Sensing and GIS Techniques: a research on Tungabhadra Dam Right Canal

2019 ◽  
Vol 8 (2S3) ◽  
pp. 652-657
Keyword(s):  
Remote Sensing ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Delta Method ◽  
Geographical Information ◽  
Command Area ◽  
Cropping Pattern ◽  
Crop Water ◽  
Irrigation Project ◽  
Gis Techniques

Agriculture is most important resources of any country worldwide which is a major renewable source and is dynamic. The study area selected was command area under Basavanna canal which is one of the canals to Tungabhadra river on right side bank. This selected canal for cropping pattern analysis has a command of 1240.00 hectare and is located at Vallabhpur, Bellary district. Basavanna canal has a designed discharge capacity of 125 cusecs for serving the cropping area. Every irrigation project has planned cropping pattern, the crop water requirement (CWR) for which is calculated based on Duty / Delta method. However due to growing population and increase demand for food products crop violation is found in every command leading to more irrigation. Remote Sensing (RS) and Geographical Information System (GIS) techniques have emerged as powerful tools for crop water management. Remotely sensed land use-land cover data was used for analysing the cropping pattern in the area and also to estimate the change in the cropping pattern. This study was performed using ArcGIS 9.3 and ERDAS 9 software. Crop water requirement was calculated using Modified Penman Equation for present cropping pattern. The study finds that, approximately 50% of water could be saved using modified Penmen method compared to crop water requirement calculated using Duty Delta method as adopted in project report and the same water may be diverted to meet other needs

scholarly journals IMPACT OF CLIMATIC PARAMETERS ON CROP WATER REQUIREMENTS IN DIFFERENT AGRO ECOLOGICAL ZONES OF PAKISTAN

2020 ◽  
Vol 4 (1) ◽  
pp. 21-24
Author(s):  
Imran Shaukat ◽  
Hafiz Ihsan -ul-Haq ◽  
Hafiz M. Safdar ◽  
Rao Husnain Arshad
Keyword(s):  
Climate Change ◽  
Climate Changes ◽  
Global Scale ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Climatic Parameters ◽  
Crop Water ◽  
Ecological Zones ◽  
Anthropogenic Processes ◽  
Agro Ecological Zones

The problem of climate change has become very strongly during last two decades on global scale in view of the projected consequences on the environment of unguarded states. Gradually rising temperature and its effects on the crops here and rainfall are obvious in many areas around the world. Climate change related to natural and anthropogenic processes in Pakistan is the major source of study in this report. The impacts of these climate changes appear to be additional component of the large number of existing water related problems in every station of Pakistan. The objective of this report is to analyze the global warming effect on CWR. For this purpose, we made seven scenarios So, S1, S2, S3, S4, S5 and S6. From So-S3 crop water requirement increases in all regions but from S4-S6 crop water requirement remains same. For this purpose we selected different cities from agro ecological stations to check the effect of climate change on CWR. Faisalabad, Gupis, Jacobabad, Kalat, Karachi, Multan, Nawabshah, Peshawar and Zhob are the regions selected for this research. Different scenarios have been made such that, in So scenario temperature remains same but from S1, S2 and S3 scenarios temperature is increases 1, 2 and 3 degree centigrade respectively. While, in S4, S5 and S6 scenarios precipitation increases or decreases according to the climatic changes of that area (So, S1, S2, S3, ) and then we increase or decrease the precipitation rate by 5%, 10% and 15% (S4, S5, S6) in accordance with the zone. From result it is concluded that the crop water requirement in arid and in semi-arid is increasing annually on the other hand the total value of effective rainfall in Pakistan is decreasing.

scholarly journals Monitoring Crop Evapotranspiration and Crop Coefficients over an Almond and Pistachio Orchard Throughout Remote Sensing

2018 ◽  
Author(s):  
Joaquim Bellvert ◽  
Karine Adeline ◽  
Shahar Baram ◽  
Lars Pierce ◽  
Blake Sanden ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Remotely Sensed ◽  
Actual Evapotranspiration ◽  
Water Evaporation ◽  
Landsat 8 ◽  
Crop Evapotranspiration ◽  
Crop Water ◽  
Field Scale ◽  
Crop Coefficients

In California, water is a perennial concern. As competition for water resources increases due to growth in population, California&rsquo;s tree nut farmers are committed to improving the efficiency of water used for food production. There is an imminent need to have reliable methods that provide information about the temporal and spatial variability of crop water requirements, which allow farmers to make irrigation decisions at field scale. This study focuses on estimating the actual evapotranspiration and crop coefficients of an almond and pistachio orchard located in Central Valley (California) during an entire growing season by combining a simple crop evapotranspiration model with remote sensing data. A dataset of the vegetation index NDVI derived from Landsat-8 was used to facilitate the estimation of the basal crop coefficient (Kcb), or potential crop water use. The soil water evaporation coefficient (Ke) was measured from microlysimeters. The water stress coefficient (Ks) was derived from airborne remotely sensed canopy thermal-based methods, using seasonal regressions between the crop water stress index (CWSI) and stem water potential (Ystem). These regressions were statistically-significant for both crops, indicating clear seasonal differences in pistachios, but not in almonds. In almonds, the estimated maximum Kcb values ranged between 1.05 to 0.90, while for pistachios, it ranged between 0.89 to 0.80. The model indicated a difference of 97 mm in transpiration over the season between both crops. Soil evaporation accounted for an average of 16% and 13% of the total actual evapotranspiration for almonds and pistachios, respectively. Verification of the model-based daily crop evapotranspiration estimates was done using eddy-covariance and surface renewal data collected in the same orchards, yielding an r2 &gt;= 0.7 and average root mean square errors (RMSE) of 0.74 and 0.91 mm day-1 for almond and pistachio, respectively. It is concluded that the combination of crop evapotranspiration models with remotely-sensed data is helpful for upscaling irrigation information from plant to field scale and thus may be used by farmers for making day-to-day irrigation management decisions.

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 Mapping Agewise Discrimination of Arecanut Crop Water Requirement Using Hyperspectral Remote Sensing

2015 ◽  
Vol 4 ◽  
pp. 1437-1444 ◽  
Author(s):  
B.E. Bhojaraja ◽  
Gaurav Hegde ◽  
U. Pruthviraj ◽  
Amba Shetty ◽  
M.K. Nagaraj
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Remote Sensing ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Crop Water

Spatiotemporal Evaluation of Remote Sensing Derived Soil Moisture Deficit for the Sugarcane Crop: A Case Study for the Indo-Gangetic Basin

2020 ◽  
Author(s):  
Anudeep Sure ◽  
Onkar Dikshit
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Crop Production ◽  
Meteorological Parameters ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Crop Water ◽  
Soil Moisture Deficit ◽  
Sugarcane Crop ◽  
Moisture Deficit

&lt;p&gt;This study focuses on the estimation of soil moisture deficit from root zone soil moisture information derived from remotely sensed passive microwave surface soil moisture data for a period of fifteen years (2002 to 2016) for the Indo-Gangetic basin. The remote sensing datasets used to estimate soil moisture deficit are Advanced Microwave Scanning Radiometer for EOS (AMSR-E) and Advanced Microwave Scanning Radiometer - 2 (AMSR-2) by JAXA and NASA. As India is an agrarian country, it is one of the largest producers of sugarcane at the global level and hence, this is the test crop considered for this work. The Indo-Gangetic basin has numerous culturable command areas with dynamic meteorological patterns, soil type, land use and land cover, agricultural practices, water and crop management with different sources of irrigation. Rain-fed irrigation is the primary source of water for crop production in this basin. Sugarcane crop is characterised by specific root depth, crop water requirement, crop length and crop phenology. In India, meteorological parameters primarily, precipitation, temperature and evapotranspiration and the meteorological seasons define the agricultural season (irrigation to harvesting). Here, an interrelationship between soil moisture deficit (at varying depth) and meteorological parameters, precipitation based meteorological indices (Rainfall Anomaly Index, Standardized Precipitation Index and Effective Drought Index), ground-based crop indices (crop yield index, crop area index and crop production index) is analysed at the annual and seasonal scale. The study indicates the paramount effect of the aforementioned factors on soil moisture deficit variable. The temporal variation of soil moisture deficit being served as a proxy for crop water requirement and the model developed from the same provides vital information for an efficient irrigation scheduling, sustainable water resource management for increased crop production and developing crop insurance schemes and policies at the basin level.&lt;/p&gt;

scholarly journals Monitoring Crop Evapotranspiration and Crop Coefficients over an Almond and Pistachio Orchard Throughout Remote Sensing

2018 ◽  
Vol 10 (12) ◽  
pp. 2001 ◽  
Author(s):  
Joaquim Bellvert ◽  
Karine Adeline ◽  
Shahar Baram ◽  
Lars Pierce ◽  
Blake Sanden ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Remotely Sensed ◽  
Actual Evapotranspiration ◽  
Water Evaporation ◽  
Landsat 8 ◽  
Crop Evapotranspiration ◽  
Crop Water ◽  
Field Scale ◽  
Crop Coefficients

In California, water is a perennial concern. As competition for water resources increases due to growth in population, California’s tree nut farmers are committed to improving the efficiency of water used for food production. There is an imminent need to have reliable methods that provide information about the temporal and spatial variability of crop water requirements, which allow farmers to make irrigation decisions at field scale. This study focuses on estimating the actual evapotranspiration and crop coefficients of an almond and pistachio orchard located in Central Valley (California) during an entire growing season by combining a simple crop evapotranspiration model with remote sensing data. A dataset of the vegetation index NDVI derived from Landsat-8 was used to facilitate the estimation of the basal crop coefficient (Kcb), or potential crop water use. The soil water evaporation coefficient (Ke) was measured from microlysimeters. The water stress coefficient (Ks) was derived from airborne remotely sensed canopy thermal-based methods, using seasonal regressions between the crop water stress index (CWSI) and stem water potential (Ψstem). These regressions were statistically-significant for both crops, indicating clear seasonal differences in pistachios, but not in almonds. In almonds, the estimated maximum Kcb values ranged between 1.05 to 0.90, while for pistachios, it ranged between 0.89 to 0.80. The model indicated a difference of 97 mm in transpiration over the season between both crops. Soil evaporation accounted for an average of 16% and 13% of the total actual evapotranspiration for almonds and pistachios, respectively. Verification of the model-based daily crop evapotranspiration estimates was done using eddy-covariance and surface renewal data collected in the same orchards, yielding an R2 ≥ 0.7 and average root mean square errors (RMSE) of 0.74 and 0.91 mm·day−1 for almond and pistachio, respectively. It is concluded that the combination of crop evapotranspiration models with remotely-sensed data is helpful for upscaling irrigation information from plant to field scale and thus may be used by farmers for making day-to-day irrigation management decisions.

scholarly journals Recent advances in space-borne optical remote sensing systems for monitoring global terrestrial ecosystems

2016 ◽  
Vol 40 (2) ◽  
pp. 322-351 ◽  
Author(s):  
Jadunandan Dash ◽  
Booker O. Ogutu
Keyword(s):  
Remote Sensing ◽  
Terrestrial Ecosystem ◽  
Remote Sensing Data ◽  
Terrestrial Ecosystems ◽  
Global Scale ◽  
Data Availability ◽  
Landsat 8 ◽  
Optical Remote Sensing ◽  
Ecosystem Monitoring ◽  
Sensing Data

Since the launch of the first Landsat satellite in the early 1970s, the field of space-borne optical remote sensing has made significant progress. Advances have been made in all aspects of optical remote sensing data, including improved spatial, temporal, spectral and radiometric resolutions, which have increased the uptake of these data by wider scientific communities. Flagship satellite missions such as NASA’s Terra and Aqua and ESA’s Envisat with their high temporal (<3days) and spectral (15–36 bands) resolutions opened new opportunities for routine monitoring of various aspects of terrestrial ecosystems at the global scale and have provided greater understanding of critical biophysical processes in the terrestrial ecosystem. The launch of new satellite sensors such as Landsat 8 and the European Space Agency’s Copernicus Sentinel missions (e.g. Sentinel 2 with improved spatial resolution (10–60 m) and potential revisit time of five days) is set to revolutionise the availability and use of remote sensing data in global terrestrial ecosystem monitoring. Furthermore, the recent move towards use of constellations of nanosatellites (e.g. the Flock missions by Planet Labs) to collect on-demand high spatial and temporal resolution optical remote sensing data would enable uptake of these data for operational monitoring. As a result of increase in data availability, optical remote sensing data are now increasingly used to support a number of operational services (e.g. land monitoring, atmosphere monitoring and climate change studies). However, many challenges still remain in exploiting the growing volume of optical remote sensing data to monitor global terrestrial ecosystems. These challenges include ensuring the highest data quality both in terms of the sensitivity of sensors and the derived biophysical products, affordability and availability of the data and continuity of data acquisition. This review provides an overview of the developments in space-borne optical remote sensing in the past decade and discusses a selection of aspects of global terrestrial ecosystems where the data are currently used. It concludes by highlighting some of the challenges and opportunities of using optical remote sensing data in monitoring global terrestrial ecosystems.

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