Discussion of “Effective Rainfall and Irrigation Water Requirements”

1965 ◽  
Vol 91 (1) ◽  
pp. 215-218
Author(s):  
Tyler H. Quackenbush ◽  
Harry F. Blaney
2013 ◽  
Vol 340 ◽  
pp. 961-965
Author(s):  
Xin Hua Wang ◽  
Mei Hua Guo ◽  
Hui Mei Liu

According to Kunming 1980-2010 monthly weather data and CROPWAT software and the corresponding crop data, crop water requirements and irrigation water use are calculated. By frequency analysis, irrigation water requirement was get for different guaranteed rate. The results show that: corn, potatoes, tobacco, and soybeans average crop water requirements were 390.7mm, 447.9mm, 361.8mm and 328.4mm, crop water dispersion coefficient is small, period effective rainfall during crop growth in most of the year can meet the crop water requirements, so irrigation water demand is small. While the multi-year average crop water requirements were 400.8mm, 353.5mm, 394.3mm for small spring crops of wheat, beans, rape. Because the effective rainfall for these crops during growth period is relative less, crop irrigation water requirements for small spring crop is much. Vegetables and flowers are plant around the year, so the crop water and irrigation water requirements are the largest.


2019 ◽  
Vol 10 (2) ◽  
pp. 61-68
Author(s):  
Hanan Shalsabillah ◽  
Khairul Amri ◽  
Gusta Gunawan

The Irrigation Area of Air Nipis is located in Regency of South Bengkulu at Bengkulu Province with irrigation area 3.116 Ha. Planning and management of irrigation systems is one of the important steps to determine the irrigation water requirement as a whole. The purpose of this research is aim to analyze the water requirement to get value prediction of minimum and maximum irrigation water requirement in irrigation area of Air Nipis using the CROPWAT Version 8.0 method. Irrigation water requirements obtained from CROPWAT Version 8.0 are based on climate data, soil data and plants.The parameters that were reference plant evapotranspiration, effective rainfall, soil treatment, soil data, and plants. The results of the research showed that the maximum irrigation requirement for calculation using CROPWAT 8.0 software occurred in the first 10 days of December (14,49 m3/sec), while the minimum irrigation water requirements for CROPWAT 8.0 occurs in mid to end March (0,04 m3/sec).


2015 ◽  
Vol 7 (1) ◽  
pp. 39-51 ◽  
Author(s):  
Ali Fares ◽  
Ripendra Awal ◽  
Samira Fares ◽  
Alton B. Johnson ◽  
Hector Valenzuela

The impact of potential future climate change scenarios on the irrigation water requirements (IRRs) of two major agricultural crops (coffee and seed corn) in Hawai'i was studied using the Irrigation Management System (IManSys) model. In addition to IRRs calculations, IManSys calculates runoff, deep percolation, canopy interception, and effective rainfall based on plant growth parameters, site specific soil hydrological properties, irrigation system efficiency, and long-term daily weather data. Irrigation water requirements of two crops were simulated using historical climate data and different levels of atmospheric CO2 (330, 550, 710 and 970 ppm), temperature (+1.1 and +6.4 °C) and precipitation (±5, ±10 and ±20%) chosen based on the Intergovernmental Panel on Climate Change (IPCC) AR4 projections under reference, B1, A1B1 and A1F1 emission scenarios. IRRs decreased as CO2 emission increased. The average percentage decrease in IRRs for seed corn is higher than that of coffee. However, runoff, rain canopy interception, and deep percolation below the root zone increased as precipitation increased. Canopy interception and drainage increased with increased CO2 emission. Evapotranspiration responded positively to air temperature rise, and as a result, IRRs increased as well. Further studies using crop models will predict crop yield responses to these different irrigation scenarios.


2007 ◽  
Vol 7 (3) ◽  
pp. 149-159 ◽  
Author(s):  
J. A. Rodríguez Díaz ◽  
E. K. Weatherhead ◽  
J. W. Knox ◽  
E. Camacho

2021 ◽  
Vol 11 (21) ◽  
pp. 10379
Author(s):  
Mohammed El Hafyani ◽  
Ali Essahlaoui ◽  
Kimberley Fung-Loy ◽  
Jason A. Hubbart ◽  
Anton Van Rompaey

This work was undertaken to develop a low-cost but reliable assessment method for agricultural water requirements in semi-arid locations based on remote sensing data/techniques. In semi-arid locations, water resources are often limited, and long-term water consumption may exceed the natural replenishment rates of groundwater reservoirs. Sustainable land management in these locations must include tools that facilitate assessment of the impact of potential future land use changes. Agricultural practices in the Boufakrane River watershed (Morocco) were used as a case study application. Land use practices were mapped at the thematic resolution of individual crops, using a total of 13 images generated from the Sentinel-2 satellites. Using a supervised classification scheme, crop types were identified as cereals, other crops followed by cereals, vegetables, olive trees, and fruit trees. Two classifiers were used, namely Support vector machine (SVM) and Random forest (RF). A validation of the classified parcels showed a high overall accuracy of 89.76% for SVM and 84.03% for RF. Results showed that cereal is the most represented species, covering 8870.43 ha and representing 52.42% of the total area, followed by olive trees with 4323.18 ha and a coverage rate of 25%. Vegetables and other crops followed by cereals cover 1530.06 ha and 1661.45 ha, respectively, representing 9.4% and 9.8% of the total area. In the last rank, fruit trees occupy only 3.67% of the total area, with 621.06 ha. The Food and Agriculture Organization (FAO) free software was used to overlay satellite data images with those of climate for agricultural water resources management in the region. This process facilitated estimations of irrigation water requirements for all crop types, taking into account total potential evapotranspiration, effective rainfall, and irrigation water requirements. Results showed that olive trees, fruit trees, and other crops followed by cereals are the most water demanding, with irrigation requirements exceeding 500 mm. The irrigation requirements of cereals and vegetables are lower than those of other classes, with amounts of 300 mm and 150 mm, respectively.


Author(s):  
Jesús Garrido-Rubio ◽  
Alfonso Calera Belmonte ◽  
Lorena Fraile Enguita ◽  
Irene Arellano Alcázar ◽  
Mario Belmonte Mancebo ◽  
...  

Abstract. Temporal series maps of irrigated areas, and the corresponding irrigation water requirements based on remote sensing, is a recognized tool contributing to water governance at different scales, from water user associations to whole river basin districts. These thematic cartographies offer a first estimation of the crop irrigation requirements, and a biophysical based approach of the temporal and spatial distribution of the crop water use in the cultivated areas. This work describes the operational application of these methodologies, providing valuable information for water governance and management purposes. The basic products obtained in the whole Spanish part of the Iberian Peninsula during the period 2014–2017 were: (i) annual maps of irrigated crops based on time series of multispectral satellite imagery; and (ii) the direct remote sensing-based water accounting, by quantifying agricultural water flows (e.g. rainfall, irrigation, evapotranspiration, drainage and recharge), through a remote sensing-based soil water balance. Hence this paper provides a remote sensing based water accounting approach, which relies on dense time series of multispectral imagery acquired by the multisensor constellation arranged by Landsat 8 and Sentinel-2 satellites, jointly with meteorological data and agronomic knowledge. Then, based on these purpose and approach, annual and monthly maps of net irrigation water requirements have been elaborated at the most practical spatial and temporal scales for water governance purposes over big areas such river basin districts. This work summarizes the methodologies used and discuss the technical and non-technical feasibility of the proposed approach.


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