Evaluation of the CSM-CROPSIM-CERES-Wheat Model as a Tool for Crop Water Management

2010 ◽  
Vol 53 (1) ◽  
pp. 87-102 ◽  
Author(s):  
K. R. Thorp ◽  
D. J. Hunsaker ◽  
A. N. French ◽  
J. W. White ◽  
T. R. Clarke ◽  
...  
Keyword(s):  
Water Management ◽  
Crop Water

scholarly journals Water Management Using Drones and Satellites in Agriculture

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 874 ◽  
Author(s):  
Javier J. Cancela ◽  
Xesús P. González ◽  
Mar Vilanova ◽  
José M. Mirás-Avalos
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Water Status ◽  
Irrigation Management ◽  
Irrigation Efficiency ◽  
Agricultural Systems ◽  
Special Issue ◽  
Crop Water ◽  
Water Requirements ◽  
Remote Sensing Techniques

This document intends to be a presentation of the Special Issue “Water Management Using Drones and Satellites in Agriculture”. The objective of this Special Issue is to provide an overview of recent advances in the methodology of using remote sensing techniques for managing water in agricultural systems. Its eight peer-reviewed articles focus on three topics: new equipment for characterizing water bodies, development of satellite-based technologies for determining crop water requirements in order to enhance irrigation efficiency, and monitoring crop water status through proximal and remote sensing. Overall, these contributions explore new solutions for improving irrigation management and an efficient assessment of crop water needs, being of great value for both researchers and advisors.

scholarly journals Variation in the estimations of ET<sub>o</sub> and crop water use due to the sensor accuracy of the meteorological variables

2013 ◽  
Vol 13 (6) ◽  
pp. 1401-1410 ◽  
Author(s):  
R. Moratiel ◽  
A. Martínez-Cob ◽  
B. Latorre
Keyword(s):  
Water Management ◽  
Wind Speed ◽  
Relative Humidity ◽  
Irrigation Water ◽  
Meteorological Variables ◽  
Crop Water ◽  
Water Requirements ◽  
Crop Water Use ◽  
Irrigation Districts ◽  
Annual Scale

Abstract. In agricultural ecosystems the use of evapotranspiration (ET) to improve irrigation water management is generally widespread. Commonly, the crop ET (ETc) is estimated by multiplying the reference crop evapotranspiration (ETo) by a crop coefficient (Kc). Accurate estimation of ETo is critical because it is the main factor affecting the calculation of crop water use and water management. The ETo is generally estimated from recorded meteorological variables at reference weather stations. The main objective of this paper was assessing the effect of the uncertainty due to random noise in the sensors used for measurement of meteorological variables on the estimation of ETo, crop ET and net irrigation requirements of grain corn and alfalfa in three irrigation districts of the middle Ebro River basin. Five scenarios were simulated, four of them individually considering each recorded meteorological variable (temperature, relative humidity, solar radiation and wind speed) and a fifth scenario combining together the uncertainty of all sensors. The uncertainty in relative humidity for irrigation districts Riegos del Alto Aragón (RAA) and Bardenas (BAR), and temperature for irrigation district Canal de Aragón y Cataluña (CAC), were the two most important factors affecting the estimation of ETo, corn ET (ETc_corn), alfalfa ET (ETc_alf), net corn irrigation water requirements (IRncorn) and net alfalfa irrigation water requirements (IRnalf). Nevertheless, this effect was never greater than ±0.5% over annual scale time. The wind speed variable (Scenario 3) was the third variable more influential in the fluctuations (±) of evapotranspiration, followed by solar radiation. Considering the accuracy for all sensors over annual scale time, the variation was about ±1% of ETo, ETc_corn, ETc_alf, IRncorn, and IRnalf. The fluctuations of evapotranspiration were higher at shorter time scale. ETo daily fluctuation remained lower than 5 % during the growing season of corn and alfalfa. This estimation fluctuation in ETo, ETc_corn, ETc_alf , IRncorn, and IRnalf at daily time scale was within an acceptable range, and it can be considered that the sensor accuracy of the meteorological variables is not significant in the estimation of ETo.

scholarly journals Evaluating Irrigation Performance and Water Productivity Using EEFlux ET and NDVI

2021 ◽  
Vol 13 (14) ◽  
pp. 7967
Author(s):  
Usha Poudel ◽  
Haroon Stephen ◽  
Sajjad Ahmad
Keyword(s):  
Water Management ◽  
Sugar Beet ◽  
Crop Yield ◽  
Water Conservation ◽  
Irrigation System ◽  
Water Productivity ◽  
Google Earth ◽  
Geographical Information ◽  
Irrigation Performance ◽  
Crop Water

Southern California’s Imperial Valley (IV) faces serious water management concerns due to its semi-arid environment, water-intensive crops and limited water supply. Accurate and reliable irrigation system performance and water productivity information is required in order to assess and improve the current water management strategies. This study evaluates the spatially distributed irrigation equity, adequacy and crop water productivity (CWP) for two water-intensive crops, alfalfa and sugar beet, using remotely sensed data and a geographical information system for the 2018/2019 crop growing season. The actual crop evapotranspiration (ETa) was mapped in Google Earth Engine Evapotranspiration Flux, using the linear interpolation method in R version 4.0.2. The approx() function in the base R was used to produce daily ETa maps, and then totaled to compute the ETa for the whole season. The equity and adequacy were determined according to the ETa’s coefficient of variation (CV) and relative evapotranspiration (RET), respectively. The crop classification was performed using a machine learning approach (a random forest algorithm). The CWP was computed as a ratio of the crop yield to the crop water use, employing yield disaggregation to map the crop yield, using county-level production statistics data and normalized difference vegetation index (NDVI) images. The relative errors (RE) of the ETa compared to the reported literature values were 7–27% for alfalfa and 0–3% for sugar beet. The average ETa variation was low; however, the spatial variation within the fields showed that 35% had a variability greater than 10%. The RET was high, indicating adequate irrigation; 31.5% of the alfalfa and 12% of the sugar beet fields clustered in the Valley’s central corner were consuming more water than their potential visibly. The CWP showed wide variation, with CVs of 32.92% for alfalfa and 25.4% for sugar beet, signifying a substantial scope for CWP enhancement. The correlation between the CWP, ETa and yield showed that reducing the ETa to approximately 1500 mm for alfalfa and 1200 mm for sugar beet would help boost the CWP without decreasing the yield, which is nearly equivalent to 44.52M cu. m (36,000 acre-ft) of water. The study’s results could help water managers to identify poorly performing fields where water conservation and management could be focused.

Potential evapotranspiration for the south coast of Puerto Rico with the Hargreaves-Samani technique

1969 ◽  
Vol 72 (1) ◽  
pp. 57-63 ◽  
Author(s):  
Megh R. Goyal
Keyword(s):  
Water Management ◽  
Puerto Rico ◽  
Potential Evapotranspiration ◽  
South Coast ◽  
Semiarid Region ◽  
Crop Water ◽  
The South ◽  
Water Requirements ◽  
Vegetables And Fruits ◽  
Maximum Minimum

The Hargreaves and Samani model was used to estimate monthly potential evapotranspiration (PET) for Central Aguirre, Fortuna and Lajas substations and Magueyes Island located on the south coast of Puerto Rico. The model uses maximum, minimum and average temperatures. Daily PET varies from 3.68 to 5.37 mm/day in the region with minimum in December and maximum in July. Annual PET was 1613.3 mm/year for Central Aguirre, 1653.5 for Fortuna, 1846.9 for Lajas, 1857.9 for Magueyes Island, with a regional average of 1704.6. These PET values can be used to estimate crop water requirements for vegetables and fruits, to plan irrigation and water management projects, and to schedule irrigation in the semiarid region of Puerto Rico.

BAITSSS Model: An Opportunity to Integrate Remote Sensing and Energy Balance Modeling for In-Season Crop Water Management

2021 ◽  
Author(s):  
Ramesh Dhungel ◽  
Rob Aiken ◽  
Xiaomao Lin ◽  
Paul D. Colaizzi ◽  
R. Louis Baumhardt ◽  
...  
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Energy Balance ◽  
Crop Water

scholarly journals Stable Carbon Isotope Evidence for Neolithic and Bronze Age Crop Water Management in the Eastern Mediterranean and Southwest Asia

PLoS ONE ◽  
2015 ◽  
Vol 10 (6) ◽  
pp. e0127085 ◽  
Author(s):  
Michael P. Wallace ◽  
Glynis Jones ◽  
Michael Charles ◽  
Rebecca Fraser ◽  
Tim H. E. Heaton ◽  
...  
Keyword(s):  
Water Management ◽  
Bronze Age ◽  
Carbon Isotope ◽  
Eastern Mediterranean ◽  
Stable Carbon Isotope ◽  
Southwest Asia ◽  
Stable Carbon ◽  
Crop Water ◽  
Isotope Evidence

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.

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