Cropping pattern classification using artificial neural networks and evapotranspiration estimation in the Eastern Mediterranean region of Turkey (original) (raw)
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Estimation of Potential Crop Evapotranspiration Using Remote Sensing Techniques
In arid and semi-arid regions Potential crop evapotranspiration is a good index for crop water requirements calculation. Irrigation in north Sinai during winter depends on rainfall, but in summer depends on underground water or/and water harvested during rainfall season. Drip irrigation is common irrigation system in study area. The aim of this paper is determining potential crop evapotranspiration (ETc) using satellite data. ETc estimated from ETo and Crop coefficient (Kc). Reference evapotranspiration (ETo) estimated using agro-meteorological data according to FAO-Penman-Monteith and Hargreaves methods. FAO-Penman-Monteith method used to calibrate Hargreaves under the same conditions. The difference between air temperature (Tair) and Land Surface Temperature (LST) varies particularly by surface water status. Linear relation between Tair and LST was established and R 2 was 0.86. LST used to predict maximum, minimum, and mean Tair (o C). Red (R) and Near Infra-Red (NIR) measurements...
The main goal of this study was to evaluate the different feed-forward backpropagation artificial neural networks' (ANNs) potential to estimate and interpolate the reference crop evapotranspiration (ET 0 ) in Fars province of Iran. ET 0 was calculated using the FAO-56 Penman-Monteith method over 24 synoptic stations. Then, altitude, latitude, longitude and the month's number as inputs and the monthly ET 0 as output (target) were used to train the ANNs. In addition, the three-layered ANNs optimized with different training algorithms including gradient descent back-propagation (gd), gradient descent with adaptive learning rate back-propagation (gda), gradient descent with momentum and adaptive learning rate back-propagation (gdx) and scaled conjugate gradient back-propagation (scg). The results indicated that scg algorithm with architecture (4 2 1) had more satisfactory results with the RMSE and R correlation coefficient equal to 18.538 mm and 0.967 in validation phase, respectively. Based on the mentioned architecture of scg algorithm, and input data form different parts of Fars province and surrounding areas, monthly ET 0 maps were produced and annual one achieved by summation of monthly maps. The maps particularly annual one showed that highest values of ET 0 could be found in the southern and especially southeastern regions, while the lowest values of ET 0 could be seen in the northern parts. Contribution of geographic and topographic variables improved the accuracy and spatial details of the resulting maps. It is interesting to note that the fundamental capability of this model is the usage of just a few parameters for ET 0 mapping. Since ET 0 is a key parameter in water demand planning, therefore, the derived maps could be useful and applicable for many purposes mainly irrigation scheduling in Fars province, Iran.
Irrigation water use monitoring at watershed scale using series of high-resolution satellite images
Remote Sensing for Agriculture, Ecosystems, and Hydrology XI, 2009
The integration of time series of high-resolution remote sensing images in the FAO crop evapotranspiration (ET) model is receiving growing interest in the last years, specially for operational applications in irrigated areas. In this study, a simplified methodology to estimate actual ET for these areas in large watersheds was developed. Then it was applied to the Guadalquivir river watershed (Southern Spain) in the 2007 and 2008 irrigation seasons. The evolution of vegetation indices, obtained from 10 Landsat and IRS images per season, was used for two purposes. Firstly, it was used for identifying crop types based on a classification algorithm. This algorithm used training data from a screened subset of the information declared by farmers for EU agriculture subsidies purposes. Secondly, the vegetation indices were used to obtain basal crop coefficients (K cb , the component of the crop coefficient that represents transpiration). The last step was the parameterization of the influence of evaporation from the soil surface, considering the averaged effect of a given rain distribution and irrigation schedule. The results showed only small discrepancies between the crop coefficients calculated using the simplified model and those calculated based on a soil water balance and the dual approach proposed by FAO. Therefore, it was concluded that the simplified method can be applied to large irrigation areas where detailed information about soils and/or water applied by farmers lacks.
Irrigation Performance using Hydrological and Remote Sensing Modeling
Journal of Irrigation and Drainage Engineering-asce, 2002
Development of water saving measures requires a thorough understanding of the water balance. Irrigation performance and water accounting are useful tools to assess water use and related productivity. Remote sensing and a hydrological model were applied to an irrigation project in western Turkey to estimate the water balance to support water use and productivity analyses. Remote sensing techniques can produce high spatial coverage of important terms in the water balance for large areas, but at the cost of a rather sparse temporal resolution. Hydrological models can produce all the terms of the water balance at a high temporal, but low spatial resolution. Actual evapotranspiration for an irrigated area in western Turkey was calculated using the surface energy balance algorithm for land ͑SEBAL͒ remote sensing land algorithm for two Landsat images. The hydrological model soil-water-atmosphere-plant ͑SWAP͒ was setup to simulate the water balance for the same area, assuming a certain distribution in soil properties, planting dates and irrigation practices. A comparison between evapotranspiration determined from SEBAL and from SWAP was made and differences were minimized by adapting the distribution in planting date and irrigation practice. The optimized input data for SWAP were used to simulate all terms of the accumulated water balance for the entire irrigation project, and subsequently used to derive the irrigation performance indicators. The innovative methodology presented is attractive as it diminishes the need of field data and combines the strong points of remotely sensed techniques and hydrological models.
Crop Water Requirements in Egypt Using Remote Sensing Techniques
Journal of Agricultural Chemistry and Environment, 2014
The common Soil in Egypt is clay soil so common irrigation system is tradition surface irrigation with 60% irrigation efficiency. Agricultural sector consumes more than 80% of water resources under surface irrigation (tradition methods). In arid and semi-arid regions consumptive use is the best index for irrigation requirements. A large part of the irrigation water applied to farm land is consumed by Evapotranspiration (ET). Irrigation water consumption under each of the physical and climatic conditions for large scale will be easier with remote sensing techniques. In Egypt, Agricultural cycle is often tow agricultural seasons yearly; summer and winter. Common summer crops are Maize, Rice and Cotton while common winter crops are Clover and Wheat. Landsat8 bands 4 and 5 provide Red (R) and Near Infra-Red (NIR) measurements and it used to calculate Normalized Deference Vegetation Index (NDVI) and monitoring cultivated areas. The cultivated land area was 3,277,311 ha in August 2013. In this paper Kc = 2 * NDVI − 0.2 represents the relation between crop coefficient (Kc) and NDVI. Kc and Reference evapotranspiration (ETo) used to estimate ETc in Egypt. The main objective of this paper is studying the potential crop Evapotranspiration in Egypt using remote sensing techniques.
Estimation of Crop Water Productivity Using GIS and Remote Sensing Techniques
Sustainability
The global demand for food is growing with the population and urbanization, which puts pressure on water resources, which need assessing and quantifying water requirements. Adopting efficient irrigation methods to optimize water use is essential in this situation. In this study, crop water productivity (CWP) of major crops in the Rohri canal command area was estimated by the ratio of yield and actual evapotranspiration (ETa). Analyzing the CWP of major crops, water scarcity challenges can be tackled by selecting the most feasible irrigation methods. However, ETa was calculated and aggregated for all four stages of the crop growth period: initial, crop development, flowering stage, and maturity seasons. The crop yield data were obtained from the districts’ agricultural statistics. For this purpose, evapotranspiration products of Landsat 5 and 8 were downloaded from Earth Engine Evapotranspiration Flux (EEFlux). Landsat images were processed in a GIS environment to calculate ETa. The ...
Estimating actual irrigation application by remotely sensed evapotranspiration observations
Agricultural Water Management, 2010
Water managers and policy makers need accurate estimates of real (actual) irrigation applications for effective monitoring of irrigation and efficient irrigation management. However, this information is not readily available at field level for larger irrigation areas. An innovative inverse modeling approach was tested for a field in an irrigation scheme in southern Spain where observed actual evapotranspiration by satellites was used to assess irrigation application amounts. The actual evapotranspiration was used as the basis for an optimization procedure using the physical based SWAP model and the parameter optimization tool PEST. To evaluate the proposed techniques two steps were taken. First, actual observed evapotranspiration from remote sensing was used to optimize two parameters of the SWAP model to determine irrigation applications. Second, a forward-backward approach was applied to test the minimum overpass return time of satellites and the required accuracy of remotely sensed actual evapotranspiration for accurate assessment of irrigation applications. Results indicate that irrigation application amounts can be estimated reasonably accurately, providing data are available at an interval of 15 days or shorter and the accuracy of the signal is 90% or higher.
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To increase agricultural productivity and ensure food security, it is important to understand the reasons for variations in irrigation over time. However, researchers often avoid investigating water productivity due to data availability challenges. This study aimed to assess the performance of the irrigation system for winter wheat crops using a high-resolution satellite, Sentinel 2 A/B, combined with meteorological data and Google Earth Engine (GEE)-based remote sensing techniques. The study area is located north of Erbil city in the Kurdistan region of Iraq (KRI) and consists of 143 farmer-owned center pivots. This study also aimed to analyze the spatiotemporal variation of key variables (Normalized Difference Moisture Index (NDMI), Normalized Difference Vegetation Index (NDVI), Precipitation (mm), Evapotranspiration (ETo), Crop evapotranspiration (ETc), and Irrigation (Hours), during the wheat-growing winter season in the drought year 2021 to understand the reasons for the varian...