An Artificial Intelligence Model to Predict Crop Water Requirement Using Weather, Soil Moisture, and Plant Health Monitoring Data

2020 ◽  
Author(s):  
M. Fayzul K. Pasha ◽  
Nandakishor Srinivasamurthy ◽  
Dayadeepak Singh ◽  
Dilruba Yeasmin ◽  
Guillermo Valenzuela
Keyword(s):  
Artificial Intelligence ◽  
Soil Moisture ◽  
Health Monitoring ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Plant Health ◽  
Monitoring Data ◽  
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

<p>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.</p>

Numerical Techniques to Analyze Crop Water Requirement Using Weather and Soil Moisture Data

2020 ◽  
Author(s):  
M. Fayzul K. Pasha ◽  
Nandakishor Srinivasamurthy ◽  
Dilruba Yeasmin ◽  
Guillermo Valenzuela
Keyword(s):  
Soil Moisture ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Crop Water ◽  
Numerical Techniques ◽  
Soil Moisture Data

Improved large-scale crop water requirement estimation through new high-resolution reanalysis dataset

2020 ◽  
Author(s):  
Matteo Rolle ◽  
Stefania Tamea ◽  
Pierluigi Claps
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Large Scale ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Balance Model ◽  
Blue Water ◽  
Crop Water ◽  
Water Requirements ◽  
Reanalysis Dataset

<p>Estimation of crop water needs is essential to understand the role of agriculture in the water balance modeling at various scales. In turn, this is relevant for water management purposes and for the fulfilling of water-related environmental regulations. In this study, a comprehensive assessment of crop water requirement at large scale is presented, both in terms of rainfall (green water) and irrigation (blue water).</p><p>A water-balance model is built to provide estimates of actual evapotranspiration and accompanying soil moisture by using high space-time resolution data. The new ERA5 reanalysis dataset, published by the ECMWF within the Copernicus monitoring system and obtained from satellite data and ground measurements, provides the precipitation and temperature input variables to the model. Data available at the hourly time scale are all aggregated on a daily scale and used in the water balance model over  a grid of cultivated areas from the MIRCA2000 dataset. Cultivated areas are available for 26 crops for year 2000 at a spatial resolution of 5 arcmin (about 9 km at the Equator). Data from MIRCA2000 are separated between rainfed areas and areas equipped for irrigation and are characterized by specific monthly calendars of the crop growing seasons.</p><p>The model performs the daily soil water balance throughout the whole year, considering all crops at their growth stage and assuming as initial condition at each crop sowing date a monthly average soil moisture. Results quantify the volumes of green and blue water necessary for crop growth and describe the spatial variability of the water requirements of each individual crop. The high spatial and temporal resolution of Copernicus ERA5 data enables a great improvement in the characterization of hydro-climatic forcings with respect to previous assessments and a greater accuracy in the crop water requirement estimates.</p><p>Finally, the knowledge of water requirements is an important step to quantify the irrigation volumes used in agriculture, on which there is a high uncertainty and little spatially distributed information. The model proposed enables the investigation of spatio-temporal variability associated to varying meteorological forcings and of the effects of different irrigation techniques, enabling an improved management of water resources.</p>

scholarly journals ESTIMATION OF CROP WATER REQUIREMENT AND CROP COEFFICIENT OF TOMATO CROP USING METEOROLOGICAL DATA IN PAMPAIDA MILLENNIUM VILLAGE, KADUNA STATE, NIGERIA

2020 ◽  
Vol 4 (3) ◽  
pp. 538-546
Author(s):  
A. Ahmed ◽  
M. A. Oyebode ◽  
H. E. Igbadun ◽  
Ezekiel Oiganji
Keyword(s):  
Soil Moisture ◽  
Water Use ◽  
Crop Coefficient ◽  
Water Requirement ◽  
Crop Water Requirement ◽  
Growth Stages ◽  
Crop Water ◽  
Tomato Crop ◽  
Crop Water Use ◽  
Crop Coefficients

This report presents a study of crop water requirement and crop coefficient (Kc) for Tomato crop cultivated under irrigation in Pampaida Millennium Village Cluster, Ikara Local Government Area of Kaduna State, Nigeria, during the 2009/2010 dry season. A total of 7 tomato farmers were selected out of 45 farmers for the assessment exercise. Water applied per irrigation and soil moisture contents before and after irrigation was monitored throughout the seasons, while Tomato bulbs were harvested at the end of season and weighed. Average  crop water use were estimated from the soil moisture content using the gypsum block, while daily reference Evapotranspiration (ETo) were computed from weather data using method Hargreaves equation. Crop coefficient values (Kc) were computed as the ratio of crop water use to ETo. The values of crop coefficients and seasonal crop water requirement per irrigation for different growth stages were determined, the computed *Kc values for different growth stage for the tomato crop grown in the study area was found to be between 0.77-1.15, the initial stage (*Kc =0.81; 20 mm/irrigation), crop development stage (*Kc = 1.09; 28 mm/irrigation), mid-season (*Kc = 1.15; 29 mm/ irrigation) and Late stage (*Kc = 0.77; 19 mm/irrigation), hence the mid-season gave the highest Kc value. However, the crop seasonal water requirement was found to be 386mm, which was within the recommended range. The crop coefficients and seasonal water requirement estimated in this study are reliable and could be used in irrigation design and scheduling for Tomato in the study area.

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