Sprinkler Irrigation Research Articles

Sustainable Green Development: Water-Saving Irrigation Technologies

In the context of global climate change and increasing demand for natural resources, sustainable development requires the introduction of innovative technologies that contribute to the conservation and rational use of water resources. This article aims to examine water-saving irrigation technologies. The efficiency of the sprinkler irrigation system is affected by the wind flow and evaporation. Therefore, the comparison of designed and measured values of discharge from a nozzle and throwing radius of three sprinklers for 6 pressured head were done. Experiment was conducted at Uchxoz district, Tashkent region, Uzbekistan with latitude 69.248903 and longitude 41.037240. The place is 2 ha and experiment were at wheat crop. Irrigation system has been taken from Chirchik river. Sprinkler system installed with 9 to 12 m distances connect with a soil condition and slope. Because of importance of natural conditions, especially wind drift and radiation connect with the evaporation, research was performed at these losses. Furthermore, the calculation of wind drift and evaporation losses based on the observed values was calculated. The measured values of the discharges were lower as the designed one in all cases from 71% to 83%. Furthermore, we can conclude that the smallest differences were observed during the experiment with highest radius with smallest pressure head. The real radius of wetter area was from 80% to 88% of the designed radius by producer. The results showed the need to use the higher number of sprinklers or higher pressure to irrigate the required area.

Dinámica del desarrollo vegetativo del cultivo de banano mediante estimulación radical bajo riego por aspersión

The production of bananas (Musa spp.) represents the most important item for the economy of the Province of El Oro. The penetration of the root system in this crop is weak, so the distribution is related to the texture and structure of the soil. This study was to evaluate the effect of different root stimulation programs on the vegetative development of banana crops under a sprinkler irrigation system. The research work was developed in the "Adrianita" farm in the Province of El Oro - Ecuador, which is located in the localities of Sabalucal-Parish Barbones del Canton el Guabo, a completely randomized block design (DBCA) was carried out, applying six treatments, T1 (Control), T2 (Carving), T3 (Rooting based on seaweed), T4 (Humic Acids), T5 (Rooting + Humic Acids), and T6 (Herculization), divided into four blocks, the Data were statistically analyzed by analysis of variance (ANOVA), using the Agrostat® software (Barbosa and Maldonado, 2010). The results obtained were plant height 3.59 m in T6, pseudostem diameter 90.61 cm in T6, number of leaves 8.07 in T1, chlorophyll levels 52.85 (SPAD) in T6, total root mass 85.92 g in T6.

The Impact of Climate Change on the Performance of Center-Pivot and Fixed Sprinkler Irrigation Systems in Sandy Soil

The Impact of Climate Change on the Performance of Center-Pivot and Fixed Sprinkler Irrigation Systems in Sandy Soil

Assessment of Irrigation Potential in Jewuha Watershed, Middle Awash River Basin, Ethiopia

Ethiopia is endowed with immense water and land resources that could be tapped and used for irrigation development. However, little has been done so far due mainly to lack of comprehensive knowledge on the potential of these resources. This study was, therefore, taken up to assess the irrigation potential in data scarce Jewuha watershed of the Awash River Basin. To achieve the objective of the study, the suitability of the land for both surface and pressurized irrigations was estimated using a parametric evaluation technique combined with the FAO land evaluation framework in the GIS environment with multi-criteria analysis of irrigation suitability factors. The irrigation water demands of major crops adopted in the area were determined using CROPWAT software. The surface water potential at the sub watershed was estimated using a combination of SWAT model and the spatial proximity regionalization technique. The performance of the SWAT model was checked by statistical parameters. The irrigation suitability analysis reveals that 51372ha of the study area are suitable and 16274ha are unsuitable for surface irrigation system. Furthermore, 52768ha of the area are suitable and 15088ha are unsuitable for a sprinkler irrigation system. For drip irrigation, 52751ha are suitable and 14855ha are unsuitable. The calibration and validation of SWAT model showed that the model has performed well to simulate the hydrology of the watershed with a coefficient of determination (R2), Nash-Sutcliffe efficiency (NSE) and Percent of bias (PBIAS) of 0.74, 0.73 and 0.80 for calibration and 0.71, 0.70 and 7.90 for validation, respectively. From a combined analysis of the available land and water resources, the gross irrigation potential of the area is estimated to be 12,997ha, of which 3098ha of land is exclusively suitable for surface irrigation and 9,899ha is suitable for pressurized irrigation systems.

Study on the application of sprinkler irrigation technology for the growth of carrots and cauliflowers

Study on the application of sprinkler irrigation technology for the growth of carrots and cauliflowers

Development of technical solutions for environmentally safe irrigation

The article presents technical solutions to reduce the negative impact on soil. Scientists have developed and continue to study ways to eliminate the negative effects of sprinkling irrigation occurring due to the mechanical impact of droplets on the soil leading to its compaction and the formation of soil crust depending on the type of soil. The useful model refers to the technique of sprinkler irrigation and can be used in mobile and stationary sprinkler systems to produce rain with droplet sizes acceptable for irrigation of a wide range of cultivated crops. The claimed design provides reduction of dynamic impact of drops on the soil, as a result of changes in the deflector, due to the installation of wedge-shaped flow dissectors on the surface of the flutes.

IoT-enable smart agriculture using multiple sensors for sprinkle irrigation systems

The Internet of Things (IoT) has experienced considerable expansion and development in recent years, offering a multitude of prospects for technological progress in the agricultural sector, with the aim of improving efficiency and providing help to farmers on a global scale. This paper outlines the conceptualization and development of an smart sprinkle irrigation system that incorporates the Internet of Things (IoT) technology, leveraging the ESP32 platform. The aim of this study is to develop a smart irrigation-based internet of things utilizing multiple sensors for sprinkle irrigation system. This will be achieved by integrating several sensors to monitor and control the irrigation process. The facilitation of communication between the ESP32 device and the Blynk application simplifies the acquisition of irrigation data, initiation of plant watering, deactivation of the automated watering functionality, and generation of graphical representations derived from sensor measurements. The irrigation system that has been created encompasses three distinct ways, particularly manual, semi-automatic, and automatic. The manual irrigation method enables users to directly administer irrigation, but the semi-automatic method necessitates users to select the timing and length of watering. The automated approach employs irrigation systems that are capable of responding to soil moisture levels, triggering the activation of the pump when the moisture content decreases beyond a predetermined threshold. The device is equipped with a pH sensor that enables the monitoring of soil pH values, a critical factor in facilitating optimal plant growth and development. The system has the capability to present the rate at which water flows and the total amount of water utilized in a singular irrigation event, as well as to aggregate the water consumption across many irrigation instances. In general, the experiments demonstrate the satisfactory performance of the three irrigation systems, including the capability to manually initiate the pump.

Distribusi Kadar Air Tanah Dengan Irigasi Curah Pada Budidaya Tanaman Stevia (Stevia rebaudiana B.)

Sprinkler irrigation emulates rainfall patterns to supply plant water, improving soil conditions and ensuring sustained field performance. This study investigated the impact of sprinkler irrigation on Stevia's Coefficient of Uniformity (CU), soil moisture level, and crop coefficient (Kc). The experiment was conducted in Karangploso Village, Malang Regency, 700 m above sea level. Stevia plants were cultivated using sprinkler irrigation, and their water requirements were assessed by analyzing changes in soil moisture after irrigation. The results showed that sprinkler irrigation significantly increased soil moisture content. At a depth of 0-20 cm, soil moisture increased by an average of 0.135 cm3/cm3 (water depth of 27 mm), while at depths of 20-40 cm and 40-60 cm, the increase was 0.121 cm3/cm3 (24 mm) and 0.065 cm3/cm3 (13 mm), respectively, with a total water depth of 64 mm for 0-60 cm soil depth of 70 mm irrigation event. The crop coefficient (Kc) of Stevia varied during its growth stage, starting from 0.55 in the first week and gradually increasing to 0.57 in the 6th week. The total water requirement for Stevia until harvest at 60 days reached 279.8 mm. This finding emphasize the importance of monitoring and adjusting irrigation practices to ensure optimal growth of Stevia. Sprinkler irrigation effectively increased soil moisture content and determined the appropriate water requirement and Kc value for Stevia cultivation.

On‐farm evaluations of overhead irrigation sprinkler packages at full and reduced rates

AbstractIrrigation is a critical resource in meeting the global demand for food, feed, fiber, and fuel. One water optimization method with high potential and interest is the use of more efficient irrigation systems. In many areas where pivots are used, the most common sprinkler package is mid‐elevation sprinkler application (MESA), which typically has application efficiencies near 80%. Low‐energy precision application (LEPA) and mobile drip irrigation (MDI) can have greater than 95% application efficiency. The objective of this research was to evaluate the ability of LEPA and MDI to maintain crop yield and quality in alfalfa (Medicago sativa L.) and silage corn (Zea mays L.), at similar and reduced irrigation rates as MESA. The intent of the reduced rate was to determine if the decreased application losses with LEPA and MDI could result in sustained crop production with a 20% irrigation rate reduction. Actual reductions ranged from 5% to 55% depending on system and site due to equipment constraints. Data from two farms in Utah during 2018–2020 provided evidence that these systems can often maintain yield and forage quality with 5%–55% less applied water. However, there were also many instances where yield was reduced by LEPA and MDI, even with similar application rates to MESA. This indicates that the two higher efficiency systems will not save water in all cases and that the application system must be carefully evaluated in small on‐farm trials over multiple years for its ability to succeed in specific field conditions.

Sensor-based precision nutrient and irrigation management enhances the physiological performance, water productivity, and yield of soybean under system of crop intensification.

Sensor-based decision tools provide a quick assessment of nutritional and physiological health status of crop, thereby enhancing the crop productivity. Therefore, a 2-year field study was undertaken with precision nutrient and irrigation management under system of crop intensification (SCI) to understand the applicability of sensor-based decision tools in improving the physiological performance, water productivity, and seed yield of soybean crop. The experiment consisted of three irrigation regimes [I1: standard flood irrigation at 50% depletion of available soil moisture (DASM) (FI), I2: sprinkler irrigation at 80% ETC (crop evapo-transpiration) (Spr 80% ETC), and I3: sprinkler irrigation at 60% ETC (Spr 60% ETC)] assigned in main plots, with five precision nutrient management (PNM) practices{PNM1-[SCI protocol], PNM2-[RDF, recommended dose of fertilizer: basal dose incorporated (50% N, full dose of P and K)], PNM3-[RDF: basal dose point placement (BDP) (50% N, full dose of P and K)], PNM4-[75% RDF: BDP (50% N, full dose of P and K)] and PNM5-[50% RDF: BDP (50% N, full P and K)]} assigned in sub-plots using a split-plot design with three replications. The remaining 50% N was top-dressed through SPAD assistance for all the PNM practices. Results showed that the adoption of Spr 80% ETC resulted in an increment of 25.6%, 17.6%, 35.4%, and 17.5% in net-photosynthetic rate (Pn), transpiration rate (Tr), stomatal conductance (Gs), and intercellular CO2 concentration (Ci), respectively, over FI. Among PNM plots, adoption of PNM3 resulted in a significant (p=0.05) improvement in photosynthetic characters like Pn (15.69 µ mol CO2 m-2 s-1), Tr (7.03m mol H2O m-2 s-1), Gs (0.175 µmol CO2 mol-1 year-1), and Ci (271.7mol H2O m2 s-1). Enhancement in SPAD (27% and 30%) and normalized difference vegetation index (NDVI) (42% and 52%) values were observed with nitrogen (N) top dressing through SPAD-guided nutrient management, helped enhance crop growth indices, coupled with better dry matter partitioning and interception of sunlight. Canopy temperature depression (CTD) in soybean reduced by 3.09-4.66°C due to adoption of sprinkler irrigation. Likewise, Spr 60% ETc recorded highest irrigation water productivity (1.08kg ha-1 m-3). However, economic water productivity (27.5 INR ha-1 m-3) and water-use efficiency (7.6kg ha-1 mm-1 day-1) of soybean got enhanced under Spr 80% ETc over conventional cultivation. Multiple correlation and PCA showed a positive correlation between physiological, growth, and yield parameters of soybean. Concurrently, the adoption of Spr 80% ETC with PNM3 recorded significantly higher grain yield (2.63t ha-1) and biological yield (8.37t ha-1) over other combinations. Thus, the performance of SCI protocols under sprinkler irrigation was found to be superior over conventional practices. Hence, integrating SCI with sensor-based precision nutrient and irrigation management could be a viable option for enhancing the crop productivity and enhance the resource-use efficiency in soybean under similar agro-ecological regions.

Adaptation to climate change: The irrigation technology mix of Italian farmers

AbstractFarmers should increasingly adopt more water‐efficient irrigation technologies—such as drip irrigation—as a result of climate warming and aggravating water scarcity. We analyze how Italian farmers adapt to climate change by changing their irrigation technology mix. We apply a two‐stage econometric model to data from 5876 Italian farms. We find that farmers' initial reaction to increasing temperatures is reducing their surface‐irrigated fractions. When temperatures increase further, farmers switch toward more sprinkler irrigation. Our results show that farmers are not autonomously moving to drip irrigation in response to climate change, suggesting that government incentives are needed to encourage this transition.

The tradeoff between water savings and salinization prevention in dryland irrigation

Soil salinization is a global phenomenon that affects large tracts of arid farmland worldwide. It contributes to the loss of soil fertility, declining yields, and – in the most severe cases – land unsuitability for cultivation. Irrigation water applications are both the main cause of and the solution to, anthropogenic (or ‘secondary’) salinization because salt typically enters the soil column as dissolved in irrigation water and leaves it through excess water applications (e.g., leaching). Excess leaching, which places additional water costs in areas affected by water scarcity, can be achieved with different irrigation techniques and practices. Here, by complementing a process-based crop water model with a salt balance of the shallow soil, we investigate the tradeoff between root zone salinization and water conservation to limit withdrawals from the water source. We evaluate how such a tradeoff is achieved under different irrigation technology and excess leaching practices. Considering as a case study the cultivation of tomatoes in Egypt, we find that drip and furrow irrigation allows for better control of salt accumulation, thus preventing crop exposure to salt stress. Drip irrigation achieves this goal with minimal water applications because it maintains the soil wetter. Thus, the (rare) rainfall events find more suitable conditions to drain the excess moisture. Conversely, by using more irrigation water (and ‘less efficiently’), furrow irrigation allows for higher rates of soil drainage and salt leaching. The irrigation schedule typically adopted with sprinkler irrigation allows for soil drying, thus limiting the ability of rainfall events to drain the soil and leach its salts. Collectively, these results highlight the key role of irrigation technology and practices in the management of secondary salinity in dryland agriculture. Specifically, there is a tradeoff between minimizing water use and preventing salt accumulation in the root zone. Drip irrigation exhibits the co-benefit of achieving both goals, while furrow irrigation limits soil salinity at the cost of requiring greater volumes of applied irrigation water.

Sprinkler irrigation machines: effect of a growing maize canopy on water partitioning, drop characteristics, and energy dissipation

Sprinkler irrigation machines: effect of a growing maize canopy on water partitioning, drop characteristics, and energy dissipation

GERMINATION AND SURVIVAL OF Nidularium innocentii Lem. (BROMELIACEAE), ORNAMENTAL BROMELIAD ON LOW-COST SUBSTRATES FOR CULTIVATION: AN ALTERNATIVE TO EXTRATIVISM

The extractivism of bromeliads in Paraná for ornamental purposes has been occurring since the 70's, due to the easy access in the forests, the high demand of consumers, and the small number of producers in the region. Among the species of this group stands out Nidularium innocentii Lem. as the second most extracted species with commercial purpose. The reversal of this situation may be associated with the implantation of agronomic crops, but there are few and sparse studies on the germination of this species. Thus, in this context a study was carried out in order to evaluate seed germination and survival on different substrates. Six alternative types of substrates that were easily accessible to the rural producer were tested: peat, coconut husk fiber, plantmax®, earthworm humus, humid pine bark and sieved agricultural soil. The experiment was carried out in a completely randomized design, with four replicates and 25 seeds per experimental unit, at room temperature, in a greenhouse, with sprinkler irrigation for a period of 90 days. Nidularium inocentii showed germination on average at 7 days and maximum germination point was reached at 15.2 days, with an average of 65.8% of germination. Among the substrates tested, coconut husk fiber, peat and humid pine bark obtained the best results on seedling survival after seed germination. The study confirms the feasibility of sexual reproduction of the species for agronomic crops using low cost and locally abundant substrates.

مقارنة الكفاءة الاقتصادية لنظم الري التقليدي والحديث لإنتاج علف البرسيم

مقارنة الكفاءة الاقتصادية لنظم الري التقليدي والحديث لإنتاج علف البرسيم

Manfaat Irigasi Springkler pada Lahan Fasum untuk Peningkatan Produksi Pertanian Kampung Tangguh Poharin

This community service is the result of research in 2022 which will be poured on community service on the fasum land in Pondok Harapan Indah housing, Jalan Sigura-Gura Malang. Installation of pipes and sprinkler nozzles based on distance and height according to the type of plant that exists. With the potential for water sources and limited land area, farmers' businesses are expected to be able to utilize water efficiently. The sprinkler irrigation system is thought to be an alternative in the provision of irrigation and for this reason it is necessary to test the ability of the irrigation system to vary the distance between the sprinklers and the high sticks to the irrigation radius and its uniformity within a few minutes duration. For a stick height of 1 m with the same sprinkler spacing, a uniformity coefficient of less than 80% is obtained and the optimal irrigation radius is with an average spacing of 6 meters

Artificial Neural Networks versus Multiple Linear Regressions to Predict the Christiansen Uniformity Coefficient in Sprinkler Irrigation

The Christiansen Uniformity Coefficient (CUC) describes the distribution of water in a sprinkler system. In this study, two types of models were developed to predict the Christiansen Uniformity Coefficient (CUC) of sprinkler irrigation systems: Artificial Neural Network (ANN), specifically the feed-forward neural networks, and multiple linear regression (MLR) models. The models were trained on a dataset of published research on the CUC of sprinkler irrigation systems, which included data on a variety of design, operating, and meteorological condition variables. In order to build the predictive model of CUC, 10 input parameters were used including sprinkler height (H), working pressure (P), nozzle diameter (D and da), sprinkler line spacing (SL), sprinkler spacing (SS), wind speed (WS), wind direction (WD), temperature (T), and relative humidity (RH). Fifty percent (50%) of the data was used to train ANN models and the remaining data for cross-validation (25%) and for testing (25%). Multiple linear regression models were built using the training data. Four statistical criteria were used to evaluate the model’s predictive quality: the correlation coefficient (R), the index of agreement (d), the root mean square error (RMSE), and the mean absolute error (MAE). Statistical analysis demonstrated that the best predictive ability was obtained when the models (ANN and MLR) utilized all the input variables. The results demonstrated that the accuracy of ANN models, predicting the CUC of sprinkler irrigation systems, is higher than that of the MLR ones. During the training stage, the ANN models were more accurate in predicting CUC than MLR, with higher R (0.999) and d (0.999) values and lower MAE (0.167) and RMSE (0.456) values. The R values of the MLR model fluctuated between 0.226 and 0.960, the d values oscillated from 0.174 to 0.979, the MAE values were in the range of 2.458% and 10.792%, and the RMSE values fluctuated from 2.923% to 13.393%. Furthermore, the study revealed that WS and WD are the most influential climatic parameters. The ANN model can be used to develop more accurate tools for predicting the CUC of sprinkler irrigation systems. This can help farmers to design and operate their irrigation systems more efficiently, which can save them time and money.

Design and implementation of a wireless communication-based sprinkler irrigation system with seed sowing functionality

This study addresses the critical health risks faced by farmers owing to the use of harmful chemical pesticides in agriculture. The primary objective is to create an effective solution to minimize these risks and reduce the use of pesticides. To achieve this, a smart irrigation system has been implemented by connecting various sensors, such as moisture sensors and thermal imagers through the Internet of Things. These sensors collect vital data on crop moisture levels and thermal images that are securely stored in a cloud-based system. The data collected were subjected to extensive analysis to ensure accurate pesticide use and to identify specific pests affecting crops. In addition, the smart irrigation system includes an Android phone for remote monitoring and pesticide spray detection, thus offering a convenient remote-based operating system for farmers. This innovative system not only proved to be cost-effective but also proved to be significantly more efficient than traditional methods, resulting in reduced labor costs. Importantly, it not only addressed the health risks associated with pesticide use but also led to a significant reduction in overall pesticide use in agriculture. This research provides a comprehensive and effective approach to address the health risks farmers face from harmful pesticides, thereby promoting sustainable and safe farming practices for the future.

Real-Time Sprinkler Irrigation (RTSI) Scheduling for Improving Wheat Crop Water Productivity in Vertisols

An experiment was conducted at ICAR- Central Institute of Agricultural Engineering (CIAE) Bhopal, Madhya Pradesh, India, during the rabi seasons of 2017-18 and 2018-19 with the objectives of to study improved irrigation scheduling for enhancing water productivity of wheat crops in Vertisols. The experiment involved permanent raised bed cultivation in Vertisols and was laid out in Randomized Block Design (RBD) with two planting systems (elevated bed and flatbed) replicated three times. The elevated bed levels were set as 5, 10, 15 and 20 cm. Soil moisture was continuously monitored using a real-time sensor network sprinkler irrigation, during crop growth period. Field data on soil moisture, crop performance, and yield were regularly recorded at different crop growth stages. The results indicated that both conventional sprinkler irrigation and real-time moisture sensor-based sprinkler irrigation led to substantial water savings of 27 and 35%, respectively with corresponding yield increase of 9 and 15% when compared to gravity (flood) irrigation, showing their effectiveness. Soil moisture variability study revealed that average soil moisture levels significantly varied when bed elevation was 10 cm or more, as compared to control (bed with normal field level) in different crop physiological stages. This variation occurred under sprinkler irrigation in Vertisols for recommended irrigation water depth. Under recommended irrigation water application through sprinkler, the wheat crop yield increased for elevation variations up to 10 cm bed elevation and the yield reduced significantly for more than 15 cm bed elevation. For sprinkler irrigation, the developed irrigation water application prescriptions (water depth/irrigation) include 400 mm irrigation depth (ID) for bed of 0 cm elevation, 476 mm ID for bed of 20 cm elevation and 552 mm ID for 30 cm bed elevation to sustain the wheat crop yield under soil moisture variability in Vertisols.

Prediction of water distribution uniformity of sprinkler irrigation system based on machine learning algorithms

The coefficients of uniformity Christiansen's uniformity coefficient (CU) and distribution uniformity (DU) are an important parameter for designing irrigation systems, and are an accurate measure for water lose. In this study, three machine learning algorithms Random forest (RF), extreme gradient boosting (XGB) and random forest-extreme gradient boosting (XGB-RF) were developed to predict the water distribution uniformity based on operating pressure, heights of sprinkler, discharge, nozzle diameter, wind speed, humidity, highest and lowest temperature for three different impact sprinklers (KA-4, FOX and 2520) for square and triangular system layout based on four scenarios (input combinations). The main findings were; the highest CU value was 86.7% in the square system of 2520 sprinkler under 200 kPa, 0.5 m height and 0.855 m3/h (Nozzle 2.5 mm). Meanwhile, in the triangular system, it was 87.3% under the same pressure and discharge and 1 m height. For applied machine learning, the highest values of R2 were 0.796, 0.825 and 0.929 in RF, XGB and XGB-RF respectively in the first scenario for CU. Moreover, for the DU, the highest values of R2 were 0.701, 0.479 and 0.826 in RF, XGB and XGB-RF respectively in the first scenario. The obtained results revealed that the sprinkler height had the lowest impact on modeling of the water distribution uniformity.