Development Of Irrigation System Research Articles

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.

Development and evaluation of smart irrigation system to enhance the water use efficiency

<p>For this purpose, a moisture sensor device was designed and constructed in February and March 2019 to determine the appropriate time to stop irrigation in furrow irrigation. Testing the device in the laboratory and its application in the Farm of the Campus of Agriculture and Natural Resources, University of Tehran (Mohammad Shahr), Iran, from April to July 2019. The purpose of this study was to evaluate the performance of a smart sensor of soil moisture to determine the optimum depth of installation and recording of soil moisture at 10, 30, and 50 cm depths and different length ratios in furrow irrigation. Initially, calibration of the device was carried out on field soil, and based on the obtained validation, the device was transferred to the field. To achieve the goals of optimum depth of installation and optimum length, 36-meter furrows with a distance of 0.75 m were created in the field. Sensitive lengths in furrows with 0.5 L, 0.75 L, and 0.85 L ratios were selected as the starting points. The results showed that in the calibration and validation phases, the R<sup>2</sup> values were 0.93 and 0.95, respectively, and in the calibration and validation stages, the value of nRMSE was 80 and 13.81%, indicating good model training in the calibration stage. Also, the average RE parameter in estimating soil moisture was 2.74%, indicating the high accuracy of the device in estimating soil moisture. The results also showed that if the device was installed at a depth of 30 cm from the soil surface of the furrow and at 75% from the beginning of the field, the depth and runoff losses would be minimal and irrigation adequacy would be best compared to other depths and lengths. It is expected that with optimal water consumption and timely interruption of irrigation, deep losses and runoff will be avoided, and with low water consumption, the productivity of crops will increase.</p>

Improving Irrigation Performance by Using Adaptive Border Irrigation System

Shortages of water resources and labor make it urgent to improve irrigation efficiency and automation. To respond to this need, this study demonstrates the development of an adaptive border irrigation system. The inflow is adjusted based on the functional relationship between the advance time deviation and the optimal adjustment inflow rate, thereby avoiding the real-time calculation of infiltration parameters required by traditional real-time control irrigation systems. During the irrigation process, the inflow rate is automatically adjusted based only on the advance time deviation of the observation points. The proposed system greatly simplifies the calculation and reduces the requirements for field computing equipment compared with traditional real-time control irrigation systems. Field validation experiments show that the proposed system provides high-quality irrigation by improving the application efficiency, distribution uniformity, and comprehensive irrigation performance by 11.3%, 10.7%, and 11.0%, respectively. A sensitivity analysis indicates that the proposed system maintains a satisfactory irrigation performance for all scenarios of variations in natural parameters, flow rates, and border length. Due to its satisfactory irrigation performance, robustness, facile operation, and economical merit compared with traditional real-time control irrigation systems, the proposed system has the potential to be widely applied.

Fuzzy-IoT smart irrigation system for precision scheduling and monitoring

Adopting and developing sustainable precision irrigation systems allows for improving productivity, reducing water and energy losses in agricultural fields.This paper deals with the development and real-time implementation of a smart precision irrigation system (SPIS). The proposed system combines two irrigation approaches, processed by a feedback fuzzy logic (FL) controller, and long-range data transmission and monitoring via the LoRa protocol. The combined approaches not only enhance overall performance but also address several limitations commonly associated with existing approaches. The proposed system uses the collected data from the sensors unit to provide the optimal irrigation decisionand communicates it with the operator (farmer) via a developed IoT platform. Data from soil moisture, ambient temperature, solar irradiance, and rainfall sensors are processed through the FL controller to adjust the irrigation times. The inputs and outputs are fuzzified by trapezoidal and triangular membership functions. Mamdani's fuzzy inference is used to control the system through a set of linguistic control rules for a more accurate decision for each scenario. The field experimentation of the developed SPIS in the eastern region of Morocco shows high efficiency and reliability by saving water and energy compared to traditional irrigation control. The proposed system, with remote data monitoring, promotes better management of irrigation, water, and energy consumption, and it is suitable to be mounted with any type of irrigation installation in the field, without extensive modifications.

Mapping the vulnerability of irrigation sand traps in a tropical volcanic basin, Indonesia

Sand traps in irrigation networks are typically used in mitigating canal sedimentation. In irrigation networks located in basins of high sediment yield due to the presence of volcanoes, it is essential to assess the vulnerability of sand traps. Using sediment yield at irrigation scheme inlets, sand trap vulnerability can be evaluated. This study aims to understand the vulnerability of irrigation sand traps throughout the Progo–Opak–Serang (POS) Volcanic River Basin, Indonesia, via mapping the sediment yield distributions in the basin. We employed the Revised Universal Soil Loss Equation to estimate soil loss, where the results show that the average soil loss in the POS River Basin is 179.69 tons/ha/year that falls under the category of moderate erosion potential, while the average sediment yield for the whole basin is 51.04 tons/ha/year. Parts of the basin with high yields of more than 180 tons/ha/year were mostly found along the volcanic mountains such as Sindoro, Sumbing, Merapi, Merbabu, and Telomoyo, and the Menoreh Hills. The model demonstrated relatively high performance with R2, NSE, RMSE, and MAE of 0.89, 0.82, 0.14, and 0.11, respectively. Within the POS Basin, Badran, Kalibawang, and Blawong are the three most vulnerable irrigation sand traps, with sediment yield values of 252.83, 178.92, and 63.49 tons/ha/year, respectively; they are all located in sub-watershed outlets. The vulnerability assessment conducted in this study can be used for the decision support system to prioritize irrigation sand traps towards a more effective irrigation system development.

DEVELOPMENT OF AUTOMATIC IRRIGATION SYSTEM WITH SOLAR ENERGY-BASED TELEGRAM NOTIFICATION

This study aims to produce an irrigation system development product using Wemos D1 as an irrigation control system, monitoring the state of soil moisture in stages and the state of the water pump by sending data periodically through the Telegram Messenger application. The research was conducted using the R&D (Research and Development) method and the prototype development model. The development procedure includes the stages of needs analysis, system design and design, making system prototypes, testing and validation stages. The results of the Black Box test obtained a percentage of 100% indicating that the prototype was feasible to use. Testing the working system of the tool where on the results of Testing Tool Conditions the Water Pump can work well, the Capacitive Soil Moisture Sensor can detect dry soil moisture when <20% and the soil is wet> 20%, and the HC-SR04 Ultrasonic Sensor test can be used from 2 cm up to 22 cm as a reading of the tank contents. The results of testing user satisfaction with 20 respondents obtained a percentage of 90% in the very good category and 10% in the good category.

ANALYZING THE LONG-RUN AND SHORT-RUN IMPACTS OF CLIMATE CHANGE ON WHEAT AND MAIZE YIELD IN WESTERN HIMALAYAN REGION OF INDIA

This study attempts to analyze the impact of climate change on the productivity of agricultural crops (wheat and maize), in the western Himalayan region of India for the period 1998–2019. The study implies second-generation panel estimation techniques. The Panel Autoregressive Distributed Lags (ARDL) method is used to analyze the long-and short-run effect of climatic variables i.e., average temperature, temperature range, and average precipitation on the yield of wheat and maize. The finding of the Panel ARDL shows that the average temperature of kharif season negatively affects the maize yield both in long run and short run, whereas the average temperature of rabi season has a negatively significant effect on wheat yield in long run and positively significant effect on wheat yield in short run. The average precipitation of rabi season has a positively significant effect on wheat yield both in long run and short run. The study recommends the development of advanced irrigation system, and the implementation of the insurance scheme by the Government and to adopt climate-smart farming techniques.

Impact of climate change on rice production in African countries: A panel data analysis

Agriculture plays a key role in the overall economic and social wellbeing in Africa. Now, Africa appears to emerge as a key player in food production because there exists enormous unused land for cultivation. On the basis of availability of data, this study aims at investigating the impact of the climate change on rice production in the twenty-five African countries from 2002 to 2014 following a static panel data approach using World Bank and Food and Agricultural Organization (FAO) data. Considering CO2 (Carbon Di Oxide) emissions as average precipitation in depth and temperature change as climate change indicators along with other control variables such as fertilizer consumption and use of pesticides, this study observes that these climate indicators have significant adverse impact in explaining variations in spatial and temporal change in rice production in African countries. It may be demonstrated from the empirical analysis that those climate variables like CO2 emissions, pesticide use and temperature change are statistically significant at a 5 %, 10 % and 5 % levels, respectively. All the indicators have negative effects on rice production in African countries. The coefficients associated with these indicators are negative and statistically significant indicating that higher CO2 emissions adversely affect rice production in Africa. Moreover, pesticides used per kg in production have an inverse relation with rice production in this continent. Further, temperature harms rice production in African countries. Temperature changes negatively affect rice production as indicated by its coefficient value being -199958.10. The results also demonstrate that adaptation of new rice seed varieties that are more tolerant to higher temperature will be more effective in response to climate change. The study suggests that there is need for enormous development in the agriculture sector, to reach the ultimate goal. In particular, development of irrigation system and large-scale funding by the government in African countries is required. Key words: Rice Production, Climate Change, Static Panel Approach, Average Precipitation

An Efficient, Optimized and Solar Based Automatic Irrigation System using GSM Module

Abstract: The automatic solar-based irrigation system using a GSM modem is a novel solution to address the challenges faced by farmers in ensuring efficient use of water resources for crop cultivation. This system utilizes solar energy to power a water pump, which is controlled by a microcontroller. The GSM modem enables remote monitoring and control of the system, allowing farmers to receive real-time updates on the status of the irrigation system and make necessary adjustments as needed. The system also includes sensors to measure soil moisture levels and control the irrigation based on the crop water requirements, thus ensuring optimal water usage. This paper presents the design, development, and testing of the automatic solar-based irrigation system using a GSM modem, highlighting its potential to increase crop yields while conserving water resources.

Development of an IoT-Based Precision Irrigation System for Tomato Production from Indoor Seedling Germination to Outdoor Field Production

Proper irrigation management, especially for tomatoes that are sensitive to water, is the key to ensuring sustainable tomato production. Using a low-cost sensor coupled with IoT technology could help to achieve precise control of the moisture content in the plant root-zone soil and apply water on demand with minimum human intervention. An IoT-based precision irrigation system was developed for growing Momotaro tomato seedlings inside a dark chamber. Four irrigation thresholds, 5%, 8%, 12%, and 15%, and two irrigation systems, surface and subsurface drip irrigation, were compared to assess which threshold and irrigation system referred the ideal tomato seedling growth. As a result, the 12% soil moisture threshold applied through the subsurface drip irrigation system significantly (p < 0.05) increased tomato seedling growth in soil composed of a main blend of peat moss, vermiculite, and perlite. Furthermore, in two repeated experiments, a subsurface drip irrigation system with 0.86 distribution uniformity used 10% less water than the surface drip irrigation system. The produced tomato seedlings were transplanted to open fields for further assessment. A low-power wide area networking Long Range Wide Area Network (LoRaWAN) protocol was developed with remote monitoring and controlling capability for irrigation management. Two irrigation systems, including surface and subsurface drip irrigations, were used to compare which system resulted in higher tomato yields. The results showed that the subsurface drip irrigation system with 0.74 distribution uniformity produced 1243 g/plant, while each plant produced 1061 g in the surface drip irrigation system treatment. The results also indicated that the LoRaWAN-based subsurface drip irrigation system was suitable under outdoor conditions with easy operation and robust controlling capability for tomato production.

Development of Precision Overhead Watering and Boom Irrigation System for Fruit Vegetable Seedlings

본 연구에서는 육묘장에서 인력 또는 관행 자동관수장치의 활용도 조사를 통해 관수장치의 문제점과 그 개선점을 파악하여 균일관수가 가능한 스마트 관수장치를 개발하고 그 성능을 분석하였다. 자동관수와 인력관수의 평균 관수량은 각각 28.7 ±4.4g과 14.2±4.3g으로 두 조건 모두 변동계수가 30% 이내로 균일관수로 판단할 수 있다. 그렇지만 변동계수가 30%인 인력관수에 비해 자동관수는 15%로 균일도가 높았다. 개발된 균일관수장치에 탑재된 분사각이 80°인 노즐은 이론상 600mm 높이에서 가장 균일한 것으로 분석되었고, 균일관수장치를 이용한 관수시험 결과 중앙부의 관수 균일도는 평균 대비 20% 이내이지만 가장자리부는 중앙부에 비해 50% 이상 관수량이 적었다. 균일관수장치를 활용한 토마토 접목묘 재배시험 결과, 시험기간 10일간 중앙부는 초장이 평균 72mm 생장한 데 비해 가장자리부는 평균 28mm 생장하여 가장자리부에 대한 추가 관수가 필요한 것으로 나타났다. 가장자리부 추가 관수장치를 부착하여 관수할 경우 중앙부에 비해 가장자리부의 관수량은 50% 이상이었으며, 중앙부에서는 분사각의 겹침으로 인하여 관수량의 차이는 발생하였으나, 그 차이는 30% 이내였다. 가장자리 집중관수 시스템 활용 시 각 지점별 생장 차이는 있으나, 10일간 생육을 비교하면 양측 가장자리의 평균 생장률은 24%, 중앙부의 평균 생장률은 26%인 점을 고려하면 균일관수장치에 비해 생장 균일도가 높았다. 모종의 초장 균일도 향상을 위해서는 관수장치의 진행방향에 거리센서를 설치하여 작물의 생장에 따라 관수장치의 높이를 조절이 필요할 것으로 판단된다.

Development of Fuzzy-Based Smart Drip Irrigation System for Chili Cultivation

Chili plants often fail to harvest in the cultivation process due to improper irrigation. Soil temperature and humidity are essential parameters that affect the amount of water needed by plants in the watering process. This research aimed to apply fuzzy logic to the chili plants' irrigation system. The function of this system was to regulate watering due to the needs of the Chili plant automatically in a real-time fashion. The Sugeno fuzzy inference system (FIS) is embedded in a microcontroller to regulate the water based on the plant's needs appropriately. The system was tested on Chili plants located in the iSurf Computer Science Lab IPB University greenhouse. After four days of testing, the soil moisture sensor results were stable at optimal conditions, between 60%-80% after watering. It shows that the irrigation system has automatically regulated watering due to the Chili plant's needs.

Development and Evaluation of Arduino-Based Automatic Irrigation System for Regulation of Soil Moisture

Development and Evaluation of Arduino-Based Automatic Irrigation System for Regulation of Soil Moisture

Socio-economic analysis of Baroda branch canal of Som Kamla Amba irrigation project, Dungarpur, Rajasthan

Irrigation system development results in improvements of farmers' economy, followed by livelihood sustainability, standard of living and social attitude. Present analysis focused on socio-economic status of farming families in the command area of Baroda Branch Canal of Som Kamla Amba Irrigation Project. The study considered survey sampling of 10 per cent beneficiaries in the Baroda branch canal command which consisted 150 farming families having 787 persons in numbers. The socio-economic indicators viz., the family structures, employment pattern, education status, livestock ownership, farm asset distribution, cost of cultivation, and cost of returns were analysed. Results indicated that education and living standards are of farmers was low which may be one of the reasons for not adoption of newly farming technologies. Cost of cultivation per hectare for wheat, barley, gram, and mustard crops were found as Rs. 28,503.00, Rs. 26,727.00, Rs. 21,184.00 and Rs. 21,697.00, respectively and net benefits per hectare obtained from these crops were Rs. 13,297, Rs. 13,023, Rs. 14,416 and Rs. 18,303, respectively. The pattern of ownership of livestock showed that the average number of cows in the command area was about 1.97 per family. The productivity in the area is average due to low inputs use.

Smart Irrigation System for Urban Gardening using Logistic Regression algorithm and Raspberry Pi

People have shown an increasing interest in urban gardening. Irrigation is one of the common methods used to take care of the plant growth. However, the proper irrigation timing of plant is much unclear for most people. Moreover, the manual irrigation is impossible when people do not have physical access to the plant in a long period of time. Hence, a smart irrigation system using Raspberry Pi has been proposed to ease the irrigation. In this system, three different sensors, including moisture, humidity and temperature sensors are installed in the soil of the plant. The collected data from the sensors will be used to predict whether the plant need to be watered or not. This system implements a machine-learning algorithm called Binary Logistic Regression using Python library to test the accuracy of the system. The accuracy of the algorithm to predict the irrigation is 82%. The finding from this study is believed to be helpful as it may contribute to the development of better irrigation system.

Impacts of climate change on yield of cereal crops in northern climatic region of Pakistan.

This study investigates the impacts of climate change on yield of selected cereal crops (wheat and maize) in the northern climatic region of Khyber Pakhtunkhwa (KP) province of Pakistan for the period 1986-2015. The first-generation unit root tests such as the Levin, Lin, and Chu (LLC), augmented Dickey-Fuller (ADF)-Fisher, and the second-generation unit root tests such as cross-sectional augmented Im-Pesaran-Shin (CIPS) and cross-sectional ADF (CADF) are used to check stationarity of the series. The cointegration among the variables is discovered via Pedroni test and Westerlund method. The long- and short-run impacts of climatic variables (average precipitation, maximum temperature, and minimum temperature) on yield of wheat and maize crops are assessed through the autoregressive distributed lag (ARDL) model. The empirical findings reveal that average precipitation has a significantly positive impact on yield of both crops in long- as well as short-run. The results further reveal that the effect of average minimum temperature on both crops is insignificant in long-run. However, the short-run effect of average minimum temperature is significantly positive on yield of maize crop but insignificant on yield of wheat crop. In long-run, an increase in average maximum temperature negatively affects crop yield. In short-run, however, it positively affects the yield of wheat and maize crops. The study recommends that increase in area under cultivation, development of advanced irrigation system, and farmers' access to metrological information will help in lowering the drastic impacts of climate change on crop productivity.

Impacts of population growth and climate change on food production and irrigation and drainage needs: A world‐wide view*

AbstractThe world population is expected to grow from 7.8 billion at present to 9.7 billion by 2050 and 10.9 billion by the end of the century. The growth is especially expected in urban areas of the countries with a low, medium, and high human development index (HDI) in Africa and Asia. Especially because of the on‐going increase in farm sizes in the rural areas of the countries with a medium, high, and very high HDI, a reduction in population in these areas may be expected. In the countries with a low HDI, this reduction is expected to start at a later stage.Globally, prospects of increasing the gross cultivated area are limited by the decrease of suitable sites for land reclamation or large‐scale irrigation and drainage projects. Therefore, increase in food production will largely rely on a more accurate application of the crop water requirements and modernization or improved operation and maintenance of irrigation and drainage systems. These issues have to be analysed in light of the expected impacts of climate change and environmental sustainability.This paper presents the relevant impacts of these issues on the need to increase food production and for sustainable irrigation and drainage system development and management. In light of this, the goals and objectives of the International Commission on Irrigation and Drainage (ICID) Strategic Action Plan are presented.

Public Investments to Development of Irrigation System and Main Enlightenment Issues of Climate Change Adaptation in Agriculture of Azerbaijan

Climate change mitigation and adaptation strategy is one of the seventh goals of the Sustainable Development Goals committed by more than 190 leaders in 2015 year. Adaptation strategy in agriculture involves different options and actions by producers and public agencies seeking to maximize public good aspects of adaptation. Public investment to irrigation system of Azerbaijan is vital for country where only 1/3 of all agricultural lands are irrigated and arable. Besides this the water resources in Azerbaijan are very limited and country annually using the 70% of all renewable natural water recourses. Annual water shortage in Azerbaijan varies between 4.5-5 billion m3. The public financial capital should be invested to irrigation system of country as a part of national adaptation program. Public investments to climate change adaptation strategies should aim at maintaining, or even increasing, food production in key exporting developed and developing regions, or in regions key to regional food security.

Mechanical Concept on Design and Development of Irrigation System to Help Rural Farmers for Their Agriculture Purpose During Unavailability of External Power

Odisha is one of the states in India, where almost 70% families depend on agriculture. Odisha is a common destination for tropical cyclones that generally initiate in the Bay of Bengal. These cyclones destroy the total agriculture system and electricity infrastructure of Odisha every year. Agriculture is the backbone of the economy of any state. Economy can be boosted by the adoption of modern technology and advanced irrigation methods. Continuous irrigation is only possible by using pumps which is operated by diesel, petrol, kerosene or electric power connected with tube well. For such type of arrangement farmers generally depend on electricity, petrol or diesel. But due to continuous electric failure for number of days as a result of frequent cyclones, farmers suffer a lot. With continuous increase in the prices of petrol, diesel, kerosene or electricity, poor farmers find it difficult to bear the cost. The aim and purpose of this work is to develop an irrigation system to help farmers for irrigation purpose to obtain better yields in agriculture with minimum expenses. In the present work mechanical concepts such as Mechanical Advantage (MA), Velocity Ratio (VR), Efficiency, energy storage concepts are used. The system consists of gears, flywheel, handle, bearings and other assembly unit. This arrangement is placed on a frame which is made up of mild steel angles having dimension 40 x 40 x 5 mm. A shaft having 25 mm diameter is used with a flywheel and four numbers of bearings. Driver and driven gears having 200 and 40 number of teethes in simple gear train arrangement are taken in this work. The concept is very simple and its manufacturing process is also very easy. There will be no issue for such type of product as it is environmental friendly and the main purpose of this system is to save the environment and reduce pollution. The idea can be easily implemented because here the input materials are easily available. So by using this system there is no need of any electric supply for irrigation purpose. The work presented here is innovative in nature and has not been developed by any other researchers in the past. By using this system even weak and physically disabled persons can lift water for the purpose of agriculture without any difficulty.

Impact of Climate Change on Food Crop Production in Congo Brazzaville

Agriculture is a key for economic transformation, food security, and nutrition. It generates foreign currency through the export process of agricultural products. It creates a source of employment to the population through farming, business and research activities therefore raising the standard of living of individuals. Agriculture, especially food crop production has always been at the mercy of unpredictable weather, but a rapidly changing climate is making agriculture an even more vulnerable enterprise. Food crop production depends on a set of factors which contribute to the increase or decrease of its volume. These factors are essential to guarantee quality production, while others are complementary and serve to improve yields in terms of quality and quantity. However, among these factors, others are difficult to control such as climatic hazards. This study analyzes the impact of climate change on Congo agriculture using data from FAO STAT. Applying Autoregressive-Distributed Lag Regression or ARDL bounds testing approach for analysis of co-integration between the variables, the results reveal that, rainfall depreciates the production of food crops in the long run and has a negative effect on production in the short run; the cultivated area impacts positively food crop production in the long run, but has no effect in the short run. A better understanding of farmers’ perceptions of/and responses to climate change is important for decision-makers to design more effective adaptation policies. In order to lowering the drastic impacts of climate change on crop productivity, the study recommends a development of advanced irrigation system, farmers’ access to meteorological information and an increase in area under cultivation.