scholarly journals Estimating Growing Season Evapotranspiration and Transpiration of Major Crops over a Large Irrigation District from HJ-1A/1B Data Using a Remote Sensing-Based Dual Source Evapotranspiration Model

2020 ◽  
Vol 12 (5) ◽  
pp. 865
Author(s):  
Bing Yu ◽  
Songhao Shang
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Water Consumption ◽  
Irrigation Water ◽  
Growing Season ◽  
Irrigation District ◽  
Planting Density ◽  
Growing Seasons ◽  
Dual Source ◽  
Crop Planting

Crop evapotranspiration (ET) is the largest water consumer of agriculture water in an irrigation district. Remote sensing (RS) technique has provided an effective way to map regional ET using various RS-based ET models over the past several decades. To map growing season ET of different crops and partition ET into evaporation (E) and transpiration (T) at regional scale, appropriate ET models should be further integrated with crop distribution maps in different years and crop growing seasons determined for each crop pixel. In this study, a hybrid dual-source scheme and trapezoid framework-based ET Model (HTEM) fed with HJ-1A/1B data was applied in Hetao Irrigation District (HID) of China from 2009 to 2015 to map crop growing season ET and T at 30 m resolution. The HTEM model with HJ-1A/1B data performed well in estimating ET in HID, and the finer spatial resolution of model input data can improve the estimation accuracy of ET. Combined with the annual crop planting map identified in previous study, and crop growing seasons determined from fitted Normalized Difference Vegetation Index (NDVI) curves for crop pixels, the spatial and temporal variations of growing season ET and T of major crops (maize and sunflower) were examined. The results indicate that ET and T of maize and sunflower reach their minimum values in the southwest HID with smaller crop planting density, and reach their maximum values in northwest HID with higher crop planting density. Over the study period with a decreasing trend of available irrigation water, ET and T in maize and sunflower growing seasons show decreasing trends, while ratios of T/ET show increasing trends, which implies that the adverse effect of decreased irrigation water diversion on crop growth is diminished due to the favorable portioning of E and T in cropland of HID. In addition, the calculation results of crop coefficients show that there is water stress to crop growth in the study area. The present results are helpful to better understand the spatial pattern of crop water consumption and water stress of different crops during crop growing season, and provide the basis for optimizing the spatial distribution of crop planting with less water consumption and more crop yield.

Red spruce seedling gas exchange in response to elevated CO2, water stress, and soil fertility treatments

1994 ◽  
Vol 24 (5) ◽  
pp. 954-959 ◽  
Author(s):  
L.J. Samuelson ◽  
J.R. Seiler
Keyword(s):  
Water Stress ◽  
Gas Exchange ◽  
Soil Fertility ◽  
Net Photosynthesis ◽  
Growing Season ◽  
Red Spruce ◽  
Fertility Treatment ◽  
Sink Strength ◽  
Growth Enhancement ◽  
Growing Seasons

The interactive influences of ambient (374 μL•L−1) or elevated (713 μL•L−1) CO2, low or high soil fertility, well-watered or water-stressed treatment, and rooting volume on gas exchange and growth were examined in red spruce (Picearubens Sarg.) grown from seed through two growing seasons. Leaf gas exchange throughout two growing seasons and growth after two growing seasons in response to elevated CO2 were independent of soil fertility and water-stress treatments, and rooting volume. During the first growing season, no reduction in leaf photosynthesis of seedlings grown in elevated CO2 compared with seedlings grown in ambient CO2 was observed when measured at the same CO2 concentration. During the second growing season, net photosynthesis was up to 21% lower for elevated CO2-grown seedlings than for ambient CO2-grown seedlings when measured at 358 μL•L−1. Thus, photosynthetic acclimation to growth in elevated CO2 occurred gradually and was not a function of root-sink strength or soil-fertility treatment. However, net photosynthesis of seedlings grown and measured at an elevated CO2 concentration was still over 2 times greater than the photosynthesis of seedlings grown and measured at an ambient CO2 concentration. Growth enhancement by CO2 was maintained, since seedlings grown in elevated CO2 were 40% larger in both size and weight after two growing seasons.

Estimating rice water requirements in the Lis Valley (Portugal) using remote sensing platforms: preliminary results for the 2020 cultivation season

2021 ◽  
Author(s):  
Romeu G. Jorge ◽  
Isabel P. de Lima ◽  
João L.M.P. de Lima
Keyword(s):  
Water Management ◽  
Remote Sensing ◽  
Irrigation Water ◽  
Crop Yields ◽  
Irrigation District ◽  
Water Requirements ◽  
Local Conditions ◽  
Preliminary Results ◽  
Sentinel 2A ◽  
Rice Water

<p>In irrigated agricultural areas, where the availability of water for irrigation does not rely on any water storage, water management requires special attention, in particular under large annual and inter-annual variability in the hydrological regime and the uncertainty of climate change. The inherent increased vulnerability of the agro-ecosystem, makes the monitoring of crop conditions and water requirements a valuable tool for improving water use efficiency and, therefore, crop yields.</p><p>This presentation focus on one such agricultural area, located in the Lis Valley (Centre of Portugal), which is a rather vulnerable area also facing drainage and salinity problems. The study aims at contributing to better characterizing the temporal and spatial distribution of rice water requirements during the growing season. Irrigation water sources are the Lis River and its tributaries, which discharges depend directly from precipitation. The most important problems of water distribution in the Lis Valley irrigation district are water shortage and poor water quality in the dry summer period, aggravated by limitations of the irrigation and drainage systems that date back to the end of the 1950’s.</p><p>We report preliminary results on using remote sensing data to better understand rice cropping local conditions, obtained within project GO Lis (PDR2020-101-030913) and project MEDWATERICE (PRIMA/0006/2018). Rice irrigation is traditionally conducted applying continuous flooding, which requires much more irrigation water than non-ponded crops, and therefore needs special attention. In particular, data obtained from satellite Sentinel-2A land surface imagery are compared with data obtained using an unmanned aerial vehicle (UAV). Data for rice cultivated areas during the 2020 cultivation season, together with weather and crop parameters, are used to calculate biophysical indicators and indices of water stress in the vegetation. Actual crop evapotranspiration was appraised with remote sensing based estimates of the crop coefficient (Kc) and used to assess rice water requirements. Procedures and methodologies to estimate Kc were tested, namely those based on vegetation indices such as the Normalized Difference Vegetation Index (NDVI). Results are discussed bearing in mind the usefulness of the diverse tools, based on different resolution data (Sentinel-2A and UAV), for improving the understanding of the impacts of irrigation practices on crop yield and main challenges of rice production and water management in the Lis Valley irrigation district.</p>

Combining the FAO56 agrohydrological model and remote sensing data to assess water demand in a Sicilian irrigation district

2020 ◽  
Author(s):  
Matteo Ippolito ◽  
Mario Minacapilli ◽  
Giuseppe Provenzano
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Water Use ◽  
Irrigation Water ◽  
Remote Sensing Data ◽  
Irrigation Scheduling ◽  
Irrigation District ◽  
Sensing Data ◽  
Spatiotemporal Distributions ◽  
Crop Parameters

<p>Agricultural water use in irrigated areas plays a key role in the Mediterranean regions characterized by semi-arid climate and water shortage. In the face of optimizing irrigation water use, farmers must revise their irrigation practices to increase the drought resilience of agricultural systems and to avoid severe damages in agro-ecosystems. In this direction, during the last decades, the research has been focused on mathematical models to simulate the process of driving mass transport and energy exchanges in the Soil-Plant-Atmosphere system.</p><p>The objective of the paper was to test the suitability of the combination of FAO56 agro-hydrological model with remote sensing data retrieved from the Moderate Resolution Imaging Spectroradiometer (MODIS) platform, to assess the spatiotemporal distributions of crop water requirement and to schedule irrigation in an irrigation district of the south-west of Sicily, Italy.</p><p>The proposed approach allowed obtaining the spatiotemporal distributions of soil and crop parameters used in the FAO56 model implemented in a GIS environment to simulate the water balance, as well as to assess the actual irrigation strategy. The GIS database was organized to include soil and crop parameters, as well as the irrigation volumes actually delivered to each farmer; the latter data can be used not only as input for water balance to evaluate the efficiency of the actual irrigation strategies but also to identify different irrigation scheduling scenario obtained by the FAO56 procedure.</p><p>The first application was carried out for the period 2014-2017, to identify a combination of irrigation scheduling parameters to be implemented in the model aimed at reproducing the ordinary strategy adopted by the farmers, based on the spatiotemporal variability of soil and climate forcings. When the model outputs were aggregated for single crop types, a fairly good agreement was found between simulated and actual seasonal irrigation volumes delivered either at the level of district and secondary units. Alternative scenarios of irrigation water distribution were then identified and analyzed, to provide irrigation technicians and policymakers a decision support tool to improve the efficiency of irrigation systems and to optimize the distribution based on the availability of water resources.</p>

scholarly journals Budset and Growth of Eastern White Pine Following Application of 6-Benzylaminopurine to Seedlings Fertilized with Different Levels of Nitrogen

1988 ◽  
Vol 6 (2) ◽  
pp. 42-45
Author(s):  
L. Eric Hinesley ◽  
Robert D. Wright
Keyword(s):  
Irrigation Water ◽  
Pinus Strobus ◽  
Dry Weight ◽  
Growing Season ◽  
First Year ◽  
White Pine ◽  
Eastern White Pine ◽  
Growing Seasons ◽  
One Year ◽  
Different Levels

Eastern white pine (Pinus strobus L.) were potted and solution fed once weekly during 2 growing seasons with 5 levels of N in the irrigation water: 50, 100, 200, 300 and 400 ppm. Leaders were treated with 750 ppm 6-benzylaminopurine (BA) in late June of the first year. The higher N levels resulted in greater stem diameter, greater foliage dry weight, longer and heavier needle fascicles, better foliage color, greater budset after application of BA, and more and longer branches on the BA-treated leader the second growing season. BA should be applied to trees with N concentration ≥ 1.5% in one-year-old foliage.

scholarly journals Evapotranspiration and evaporation/transpiration partitioning with dual source energy balance models in agricultural lands

2018 ◽  
Vol 380 ◽  
pp. 17-22 ◽  
Author(s):  
Gilles Boulet ◽  
Emilie Delogu ◽  
Sameh Saadi ◽  
Wafa Chebbi ◽  
Albert Olioso ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Water Stress ◽  
Energy Balance ◽  
Surface Temperature ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Stress Levels ◽  
Dual Source ◽  
Energy Balance Models

Abstract. EvapoTranspiration (ET) is an important component of the water cycle, especially in semi-arid lands. Its quantification is crucial for a sustainable management of scarce water resources. A way to quantify ET is to exploit the available surface temperature data from remote sensing as a signature of the surface energy balance, including the latent heat flux. Remotely sensed energy balance models enable to estimate stress levels and, in turn, the water status of most continental surfaces. The evaporation and transpiration components of ET are also just as important in agricultural water management and ecosystem health monitoring. Single temperatures can be used with dual source energy balance models but rely on specific assumptions on raw levels of plant water stress to get both components out of a single source of information. Additional information from remote sensing data are thus required, either something specifically related to evaporation (such as surface water content) or transpiration (such as PRI or fluorescence). This works evaluates the SPARSE dual source energy balance model ability to compute not only total ET, but also water stress and transpiration/evaporation components. First, the theoretical limits of the ET component retrieval are assessed through a simulation experiment using both retrieval and prescribed modes of SPARSE with the sole surface temperature. A similar work is performed with an additional constraint, the topsoil surface soil moisture level, showing the significant improvement on the retrieval. Then, a flux dataset acquired over rainfed wheat is used to check the robustness of both stress levels and ET retrievals. In particular, retrieval of the evaporation and transpiration components is assessed in both conditions (forcing by the sole temperature or the combination of temperature and soil moisture). In our example, there is no significant difference in the performance of the total ET retrieval, since the evaporation rate retrieved from the sole surface temperature is already fairly close to the one we can reconstruct from observed surface soil moisture time series, but current work is underway to test it over other plots.

scholarly journals The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat

2015 ◽  
Vol 19 (11) ◽  
pp. 4653-4672 ◽  
Author(s):  
G. Boulet ◽  
B. Mougenot ◽  
J.-P. Lhomme ◽  
P. Fanise ◽  
Z. Lili-Chabaane ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Energy Balance ◽  
Surface Temperature ◽  
Series Resistance ◽  
Water Status ◽  
Soil Evaporation ◽  
Stress Levels ◽  
Dual Source ◽  
Rainfed Wheat

Abstract. Evapotranspiration is an important component of the water cycle, especially in semi-arid lands. A way to quantify the spatial distribution of evapotranspiration and water stress from remote-sensing data is to exploit the available surface temperature as a signature of the surface energy balance. Remotely sensed energy balance models enable one to estimate stress levels and, in turn, the water status of continental surfaces. Dual-source models are particularly useful since they allow derivation of a rough estimate of the water stress of the vegetation instead of that of a soil–vegetation composite. They either assume that the soil and the vegetation interact almost independently with the atmosphere (patch approach corresponding to a parallel resistance scheme) or are tightly coupled (layer approach corresponding to a series resistance scheme). The water status of both sources is solved simultaneously from a single surface temperature observation based on a realistic underlying assumption which states that, in most cases, the vegetation is unstressed, and that if the vegetation is stressed, evaporation is negligible. In the latter case, if the vegetation stress is not properly accounted for, the resulting evaporation will decrease to unrealistic levels (negative fluxes) in order to maintain the same total surface temperature. This work assesses the retrieval performances of total and component evapotranspiration as well as surface and plant water stress levels by (1) proposing a new dual-source model named Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE) in two versions (parallel and series resistance networks) based on the TSEB (Two-Source Energy Balance model, Norman et al., 1995) model rationale as well as state-of-the-art formulations of turbulent and radiative exchange, (2) challenging the limits of the underlying hypothesis for those two versions through a synthetic retrieval test and (3) testing the water stress retrievals (vegetation water stress and moisture-limited soil evaporation) against in situ data over contrasted test sites (irrigated and rainfed wheat). We demonstrated with those two data sets that the SPARSE series model is more robust to component stress retrieval for this cover type, that its performance increases by using bounding relationships based on potential conditions (root mean square error lowered by up to 11 W m−2 from values of the order of 50–80 W m−2), and that soil evaporation retrieval is generally consistent with an independent estimate from observed soil moisture evolution.

Optimizing mungbean productivity and irrigation water use efficiency through the use of low water- consumption during plant growth stages

2017 ◽  
Vol 40 (04) ◽  
Author(s):  
Fathy S. El-Nakhlawy ◽  
Saleh M. Ismail ◽  
Jalal M. Basahi
Keyword(s):  
Saudi Arabia ◽  
Water Stress ◽  
Water Use Efficiency ◽  
Water Use ◽  
Water Consumption ◽  
Irrigation Water ◽  
Full Irrigation ◽  
Irrigation Water Use Efficiency ◽  
Irrigation Water Use ◽  
Use Efficiency

This research was conducted during 2014/2015 and 2015/2016 seasonsin the Agricultural Research Station, King Abdulaziz University at Hada Al-Sham region, Saudi Arabia to produce mungbean as a new legume crop in Saudi Arabia using low water consumption through maximizing crop yield with optimizing irrigation water use efficiency under drought stress during vegetative and flowering growth stages.No significant differences were found between the yield and yield components when practicing water stress during vegetative stage compared with full irrigation treatment in the two seasons. MN96 cv. was significantly dominated over NMf cv. in all studied traits except flowering date.The highest IWUE and seed yield/ha were obtained from the MN96 cv. under full irrigation and water stress during vegetative stage without significantly differences between them in the two seasons.

scholarly journals Assessing Irrigation Water Use with Remote Sensing-Based Soil Water Balance at an Irrigation Scheme Level in a Semi-Arid Region of Morocco

2021 ◽  
Vol 13 (6) ◽  
pp. 1133
Author(s):  
Mohamed Hakim Kharrou ◽  
Vincent Simonneaux ◽  
Salah Er-Raki ◽  
Michel Le Page ◽  
Saïd Khabba ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Balance ◽  
Soil Water ◽  
Irrigation Water ◽  
Management Practices ◽  
Irrigation District ◽  
Soil Water Balance ◽  
Balance Model ◽  
Irrigation Water Use ◽  
Semi Arid

This study aims to evaluate a remote sensing-based approach to allow estimation of the temporal and spatial distribution of crop evapotranspiration (ET) and irrigation water requirements over irrigated areas in semi-arid regions. The method is based on the daily step FAO-56 Soil Water Balance model combined with a time series of basal crop coefficients and the fractional vegetation cover derived from high-resolution satellite Normalized Difference Vegetation Index (NDVI) imagery. The model was first calibrated and validated at plot scale using ET measured by eddy-covariance systems over wheat fields and olive orchards representing the main crops grown in the study area of the Haouz plain (central Morocco). The results showed that the model provided good estimates of ET for wheat and olive trees with a root mean square error (RMSE) of about 0.56 and 0.54 mm/day respectively. The model was then used to compare remotely sensed estimates of irrigation requirements (RS-IWR) and irrigation water supplied (WS) at plot scale over an irrigation district in the Haouz plain through three growing seasons. The comparison indicated a large spatio-temporal variability in irrigation water demands and supplies; the median values of WS and RS-IWR were 130 (175), 117 (175) and 118 (112) mm respectively in the 2002–2003, 2005–2006 and 2008–2009 seasons. This could be attributed to inadequate irrigation supply and/or to farmers’ socio-economic considerations and management practices. The findings demonstrate the potential for irrigation managers to use remote sensing-based models to monitor irrigation water usage for efficient and sustainable use of water resources.

scholarly journals Crop water stress maps for entire growing seasons from visible and thermal UAV imagery

2016 ◽  
Author(s):  
Helene Hoffmann ◽  
Rasmus Jensen ◽  
Anton Thomsen ◽  
Hector Nieto ◽  
Jesper Rasmussen ◽  
...  
Keyword(s):  
Water Stress ◽  
Air Temperature ◽  
Land Surface ◽  
Surface Air Temperature ◽  
Growing Season ◽  
Color Images ◽  
Crop Water ◽  
Crop Water Stress Index ◽  
Growing Seasons ◽  
Crop Water Stress

Abstract. This study investigates whether a Water Deficit Index (WDI) based on imagery from Unmanned Aerial Vehicles (UAVs) can provide accurate crop water stress maps at different growth stages of barley and in differing weather situations. Data from both the early and the late growing season are included to investigate whether the WDI index has the unique potential to be applicable both when the land surface is partly composed of bare soil and when crops on the land surface are senescing. The WDI index differs from the more commonly applied Crop Water Stress Index (CWSI) in that it uses both a spectral vegetation index (VI), to determine the degree of surface greenness, and the composite land surface temperature (LST) (not solely canopy temperature). Lightweight thermal and RGB (Red-Green-Blue) cameras were mounted on a UAV on three occasions during the growing season, 2014, and provided composite LST and color images, respectively. From the LST, maps of surface-air temperature differences were computed. From the color images, the Normalized Green-Red Difference Index (NGRDI), constituting the indicator of surface greenness, was computed. Advantages of the WDI as an irrigation map, as compared with simpler maps of the surface-air temperature difference, are discussed, and the suitability of the NGRDI index is assessed. Final WDI maps had a spatial resolution of 0.25 m. It was found that the UAV-based WDI index determines accurate crop water status. Further, the WDI index is especially valuable in the late growing season because at this stage the remote sensing data represent crop water availability to a greater extent than they do in the early growing season, and because the WDI index accounts for areas of ripe crops that no longer have the same need of irrigation. WDI maps can potentially serve as water stress maps, showing the farmer where irrigation is needed to ensure healthy growing plants, during entire growing seasons.

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