Cost-effective Irrigation Research Articles

Harnessing rain hose technology for water-saving sustainable irrigation and enhancing blackgram productivity in garden land

Blackgram, a protein-rich pulse crop (24%), is crucial for combating food insecurity, particularly in malnourished and economically weak countries. Enhancing blackgram production requires improved, input-saving management practices. Given the challenges of climate change and population growth, efficient water management is vital for increasing pulse productivity and water use efficiency with minimal investment. This study aimed to identify cost-effective irrigation methods to optimise blackgram yields. Experiments were conducted at the National Pulses Research Centre in Vamban, Pudukkottai, and the Agricultural College and Research Institute in Kumulur, Tiruchirappalli, during the kharif season of 2021 and 2022. The study compared different treatments of irrigation methods, such as check basin, raised bed, drip, sprinkler and rain hose irrigation. Results showed that the rain hose system maintained the highest soil moisture (23.93% at 10 cm depth and 19.71% at 20 cm depth). Even though drip irrigation resulted in a higher seed yield (1363 kg ha−1), the rain hose system proved to be more cost-effective, saving 27.09% in costs and achieving a 15.23% higher benefit–cost ratio. These findings suggest that the rain hose method, combined with current agronomic practices, is a viable low-cost technique for sustainable blackgram cultivation, optimising water use and maximising profits. This research provides valuable insights into water-saving irrigation methods for pulse crops.

Design and Development of a Time Saving and Cost-Effective Irrigation Facility for Peasants and Urban Vegetable Production

Design and Development of a Time Saving and Cost-Effective Irrigation Facility for Peasants and Urban Vegetable Production

Effects of full and deficit irrigation on the growth and quality of cool-season turfgrasses under subsurface drip irrigation

Irrigation is necessary in terms of achieving high-quality turfgrass. However, it is evident that more efficient and cost effective irrigation methods should be adapted for the sake of water conservation strategies since water consumption is high during turf irrigation. The objective of this study is to determine the effects of full and deficit irrigation with subsurface drip irrigation on growth and quality of perennial ryegrass (Lolium perenne L.) and tall fescue (Festuca arundinaceae Schreb) in a sub-humid climate of Turkey. Three irrigation treatments [I1 (full irrigation), I2 (mild water deficit, 75%), and I3 (moderate water deficit, 50%) were applied to the plants. Turf color and quality of each plot were rated visually, and clipping yields were collected. The amount of irrigation applied varied between 457.3 - 833.9 mm and 356.7 - 710.1 mm and seasonal crop evapotranspiration (ETa) values ranged from 578.4 to 1053.0 mm for tall fescue and 551.2 to 1044.0 mm for perennial ryegrass in 2018 and 2019, respectively. Among the species, tall fescue showed higher visual color, quality ratings and clipping yields. In cases where it does not matter for one or two weeks to be below the acceptable quality (<6) minimum annual irrigation amounts required to maintain quality was 689.1 mm for perennial ryegrass and 578.4 for tall fescue. The results have suggested that acceptable visual color and quality are sustainable in the tall fescue with mild water deficit application in regions where irrigation water is limited in sub-humid climates. Studies on water-saving strategies to turfgrass in regions where the climates varies from year to year are lacking in literature.

Techno-economic analysis of a solar-powered agricultural irrigation system using PV*Sol software: A case study in Konya

Agricultural irrigation is essential for crop growth and yield, but traditional irrigation systems are often associated with high costs, energy consumption, and negative environmental impacts. The development of alternative irrigation systems, such as solar-powered systems, has gained increasing attention in recent years. In this study, a techno-economic analysis of a grid-connected solar photovoltaic (PV) system was carried out for the electrical energy needed in irrigation of an agricultural area located in Konya, Turkiye. The electrical energy produced by the solar energy system was used to meet the energy needs of the electrical equipment and the water pumping system required for agricultural irrigation. According to the simulation results, the annual energy requirement for agricultural irrigation is 6,735 kWh and the peak load is 2.1 kW. In addition, in line with the simulation results, the PV system can feed the load with a self-consumption of 15.9%, a self-sufficiency level of 46.6% and a performance rate of 83% when the desired rate is set as 115% for a year reference period. When the financial analysis of the simulation is examined, it is estimated (or computed) that an asset return of 9.14% and a depreciation period of 8.7 years. The annual gain loss of the energy system due to shading is 1.5% and the annual CO2 emission prevented by the system is 9.201 kg. Considering these results, it could be stated that the proposed energy system is technically and economically appropriate for agricultural irrigation systems. At the same time, these results might provide valuable insights for farmers and policymakers seeking to adopt sustainable and cost-effective irrigation systems for agricultural production.

Growing of cabbage in water efficient irrigation methods in Uzbekistan

In world agriculture, efforts are being made to reduce water consumption in crop irrigation, to study the level of soil moisture and water consumption in different irrigation methods, to improve the agrophysical, agrochemical and microbiological properties of the soil, and to increase its productivity. Also, large-scale scientific research is being carried out on increasing the yield of vegetable crops in different irrigation methods and reducing the phytosanitary condition of the field (density of weeds and pests, level of disease). The development, improvement and widespread implementation of optimal and cost-effective irrigation methods for planting and caring for vegetable crops in the spring and summer periods in the conditions of water scarcity is one of the urgent issues in agriculture. The development of water saving irrigation technologies in conditions of Uzbekistan does not influence essentially on agro-application physical properties of typical grey soils. At application of water saving irrigation in conditions of a climate of Uzbekistan, it was noticed that the most effective way is drip irrigation. At this way of irrigation, water is saved by 50% and productivity of vegetable crops and fertility of soil increases by 10-15%.

Development of green energy based micro-sprinkler irrigation system for small holdings of SAT region

The Indian agriculture in the region of semi-arid tropics (SAT), characterized by small holders, small water harvesting and recycling system assumes a significant potential to sustain agricultural productivity by providing supplemental as well aslifesaving irrigation and mitigating mid-season drought. In Indian Agriculture, major energy consuming activities include on-farm water management. Efficient and cost-effective irrigation system matching the small-scale water harvesting and storage, are anot available in this region. In view of this, a carry-and-irrigate type micro-sprinkler irrigation system was designed and developedin order to achieve the holistic utilization of water resources and niche-potential of solar energy and gravity. The performance was measured on various parameters of application rate, Christiansen uniformity coefficient and pattern efficiency and were quantified as 14.2 mm/h, 91.3% and 89.01% respectively. The develop irrigation system qualified the performance criteria as standardized by ASAE, 1996. Given the characteristics of low cost and portability, it can considerably substantiate the vegetable production at household scale. Though, this system is developed exclusively for the location representing typical dryland agriculture of India, it can be easily and effectively replicated in other part of the world having similar agro-ecosystem. This simple water management technique utilizing the niche potential of gravity and solar energy can significantly contribute to the various objectives of sustainable development goal.

Exploring Machine Learning Models in Predicting Irrigation Groundwater Quality Indices for Effective Decision Making in Medjerda River Basin, Tunisia

Over the last years, the global application of machine learning (ML) models in groundwater quality studies has proved to be a robust alternative tool to produce highly accurate results at a low cost. This research aims to evaluate the ability of machine learning (ML) models to predict the quality of groundwater for irrigation purposes in the downstream Medjerda river basin (DMB) in Tunisia. The random forest (RF), support vector regression (SVR), artificial neural networks (ANN), and adaptive boosting (AdaBoost) models were tested to predict the irrigation quality water parameters (IWQ): total dissolved solids (TDS), potential salinity (PS), sodium adsorption ratio (SAR), exchangeable sodium percentage (ESP), and magnesium adsorption ratio (MAR) through low-cost, in situ physicochemical parameters (T, pH, EC) as input variables. In view of this, seventy-two (72) representative groundwater samples have been collected and analysed for major cations and anions during pre-and post-monsoon seasons of 3 years (2019–2021) to compute IWQ parameters. The performance of the ML models was evaluated according to Pearson’s correlation coefficient (r), the root means square error (RMSE), and the relative bias (RBIAS). The model sensitivity analysis was evaluated to identify input parameters that considerably impact the model predictions using the one-factor-at-time (OFAT) method of the Monte Carlo (MC) approach. The results show that the AdaBoost model is the most appropriate model for predicting all parameters (r was ranged between 0.88 and 0.89), while the random forest model is suitable for predicting only four parameters: TDS, PS, SAR, and ESP (r was with 0.65 to 0.87). Added to that, this study found out that the ANN and SVR models perform well in predicting three parameters (TDS, PS, SAR) and two parameters (PS, SAR), respectively, with the most optimal value of generalization ability (GA) close to unity (between 1 and 0.98). Moreover, the results of the uncertainty analysis confirmed the prominent superiority and robustness of the ML models to produce excellent predictions with only a few physicochemical parameters as inputs. The developed ML models are relevant for predicting cost-effective irrigation water quality indices and can be applied as a DSS tool to improve water management in the Medjerda basin.

Water Hammer In Irrigation Systems

Irrigation system design includes pump sizing and selection, valve sizing and selection, and pipe sizing as well as the proper selection and placement of many other components. Good design involves selecting and sizing components to perform their intended tasks within the constraints of the system, to ensure an efficient, cost effective, and durable irrigation system. Cost effectiveness will result when oversizing is avoided. Undersizing of components will cut initial costs but often results in poor irrigation distribution uniformity or the complete or partial failure of the system through ruptured pipes, damaged valves, or pump damage. Like any other moving fluid, flowing water has momentum. When subjected to a sudden change in flow, shock waves propagate through the system. This occurrence is referred to as "water hammer." Flow changes can occur due to operation of valves, starting and stopping of pumps, or directional changes caused by pipe fittings. The intensity of water hammer effects will depend upon the rate of change in the velocity or momentum. This publication discusses the causes of water hammer and the importance of proper system design and management to ensure a cost effective, long-lasting irrigation system.

Data-based groundwater quality estimation and uncertainty analysis for irrigation agriculture

Accurate groundwater quality estimation is of great significance for effective irrigation management in agricultural areas. However, due to lack of data, the parameterization of the physical models is restricted for large areas with diverse underlying surface conditions. To obtain effective and convenient estimations of groundwater quality with the most accessible data is urgently needed. In this study, the validity of the data-based models in irrigation water quality index estimation was investigated by only using physical groundwater parameters as inputs. 15 combination scenarios of the physical parameters including temperature, pH, electrical conductivity, and dissolved oxygen were examined by support vector machine (SVM), random forests (RF), artificial neural networks (ANN) and extreme learning machine (ELM) models for total dissolved solids (TDS), potential salinity (PS), and sodium adsorption ratio (SAR) estimation for the Zhangye Basin, northwest China. Performance of the artificial intelligence (AI) models was evaluated according to the coefficient of correlation (R), root mean squared error (RMSE), mean absolute percentage error (MAPE), and Nash-Sutcliffe efficiency (NS). The Monte Carlo (MC) approach was performed to assess the uncertainty of the physical groundwater parameters and the sensitivity of the AI models. The results revealed an input pattern, which emphasized the important role of EC and the improving function of pH, in revealing the nature of data-based irrigation water quality index estimation. Results of the uncertainty analysis also confirmed the prominent superiority and robustness of the SVM, RF and ELM models in producing excellent estimations with only physical parameters as inputs. The developed AI models were valuable in estimating irrigation water quality indexes, thus could help decision makers manage irrigation strategies. By using physical groundwater parameters as input variables, the AI models showed prospects in convenient and cost-effective irrigation water quality index estimating.

Possibilities of drip irrigation of vegetables in agricultural land of Uzbekistan

Reducing water consumption in crop irrigation in the world agriculture, studying soil moisture and water consumption by different irrigation methods, improving soil agrophysical properties and increasing productivity, as well as increasing the productivity of vegetable crops by various irrigation methods and improving phytosanitary conditions (weed and pest density, disease). Extensive research is being conducted to assess the level of one of the most pressing issues in agriculture is the development, improvement and widespread introduction of cost-effective irrigation methods in the spring and summer planting and care of vegetable crops in conditions of water scarcity.

Application of a dynamic model for regulating the hydrothermal regime in early potato cultivation in the Volgograd region

The article presents the results of research on the dynamics of development and water consumption of early potatoes, obtained from field observations in a multi-factor experiment, which formed the basis of the initial database of water adaptive regulation, temperature and food regimes based on simulation. The dynamic simulation model “POTATO” developed on this basis is aimed at displaying the processes of phenological development of potatoes and predicting crop yields during irrigation and fertigation. The model provides a forecast of the timing of the early potato development phenological phases, its yield depending on specific soil and weather conditions, as well as irrigation modes (sprinkling, drip and combined ones) and the level of mineral nutrition. The forecast of the dynamics of the culture phenological development allows to adjust the schedule of reclamation measures to regulate water and temperature regimes, taking into account current and forecast meteorological information. The simulation model allows to perform operational management of the hydrothermal and food regime of the agrocoenosis in order to obtain the planned yields. The developed method of regulating the hydrothermal regime based on the “POTATO” simulation model makes it possible to implement operational irrigation management and choose the optimal and cost-effective irrigation strategy.

Examination of drought stress of two genotype maize hybrids with different fertilization

In the growing season of 2019, we analysed stress resulting from climatic factors on maize hybrids of different genotypes, with the aim of gaining a better understanding of the physiological responses of each hybrid, which might support the elaboration of a cost-effective irrigation plan.&#x0D; Our experiments were carried out at the Látókép Experimental Station of the University of Debrecen on calcareous chernozem soil in a small-plot long-term field trial with strip plot design. In the scope of the experiment, N-fertilizer doses were applied as basic fertilizer and top-dressing in addition to the non-fertilized (control) treatment. The 60 and 120 kg N/ha doses applied as basic fertilizers in the spring were followed by top-dressing in the V6 phenophase with a +30 kg N/ha dose. Measurements were carried out with the involvement of the Renfor early (FAO 320) and Fornad (FAO 420) late maturity hybrids-&#x0D; The stomata of the plants became more and more closed with the progression of the phenological phases; their stomatal conductance decreased. However, the hybrids responded differently to environmental stress. In the case of the Renfor hybrid, the highest conductance (669 mmol/m2-s) was recorded in the V12 phenophase with the 150 kg N/ha treatment. The stomata were more open due to the high turgor pressure, allowing plants to evaporate properly. The plant was in its worst physiological condition on 2nd July, at the time of the appearance of the last leaf in the case of the 120 kg N dose (224 mmol/m2-s). The value measured in the V12 phenophase has already shown that the stomata were closing due to the self-regulating system of the plant. It would have been necessary to dispense irrigation water following the measurement. This confirms the finding that water stress can be prevented by measuring stomatal conductance.&#x0D; In the case of the Fornad hybrid, stomatal conductance was the highest on 12th June (630 mmol/m2-s) in the 90 kg N/ha treatment and it was the lowest (183 mmol/m2-s) in VT (emergence of the last leaf) phenophase in the 60 kg N/ha treatment. In this case, the appropriate time for applying irrigation water would have been early July, when the conditions for the plants were still adequate. Subsequently, the stomata began to close due to a reduction of the water resources available to them.&#x0D; There was a significant correlation between soil moisture and stomatal conductance, as well as between temperature and stomatal conductance.

Effect of farmers’ management on movable sprinkler solid-set systems

Farmer's management is considered a key factor for efficient, cost-effective irrigation. In this study, the effect of proper irrigation management in the solid-set systems of Kurdistan province in Iran was investigated. Performance indices including Coefficient of Uniformity (CU), Potential Application Efficiency of the Low Quarter (PELQ), Wind Drift and Evaporation Loss (WDEL), Adequacy of Irrigation (ADirr), Deep Percolation Losses (DP), and Application Efficiency (AE) were measured in ten different local plots in 2007 and 2017. The performance of selected systems remained similar in 2007 and 2017. The management of the plots evaluated in 2017 was modified, taking into account the preliminary design considerations and applying changes such as irrigation scheduling and sprinkler type. These plots with improved management were re-evaluated. Results showed that CU and PELQ were improved by 29% and 82%, respectively, in all systems. In addition, deep percolation losses (DP) were reduced by more than 40%. Insufficient training for farmers and the use of unskilled labor are of the main reasons for sustained underperformance in the study area. Actions are required in farmers’ education and in public performance monitoring. Additionally, the results of this research have shown that management improvement measurements are urgently required for the satisfactory performance of the above-mentioned systems.

An Overview of Configuration Strategies and Control Techniques for Solar Water Pumps

In view of dwindling scenario of conventional energy sources, governments, scientists and researchers worldwide are engaged tirelessly to explore the renewable energy sources in every walk of life. Most of the developing countries like India, heavily depends upon the agriculture for their survival. Irrigation is an essential task to be performed for better agriculture output. Due to global warming and ecological issues, the cost-effective irrigation harnessing cleanest form of energy such as solar energy is preferable. The main purpose of this paper is to develop an overview of efficient solar based water pumping systems for irrigation in India by using different configuration strategies of converter/inverter and Maximum Peak Power Tracking (MPPT) techniques. In addition, it also discusses the scope and constraints of photo-voltaic based solar water pumping system. Conventional irrigation systems harnessing the fossil fuels emits large amount of greenhouse gases which causes global warming. In order to make the irrigation system cost effective, prodigious and sophisticated irrigation techniques using an optimal solar tracking mechanism have been highlighted.

Farm-based Evaluation of Sustainable Alternative Irrigation Practices

Water management is one crucial component of agribusiness and municipal policy. One of the water-oriented dimensions is irrigation. In Pakistan, there is a lack of water system planning and water conservation management. This study is an effort to focus on water conservation and optimum crop yield using cost effective irrigation practices. This study is based on the comparative analysis among four irrigation techniques: flood irrigation (conventional), furrow, alternate furrow, and raised bed on wheat crop in order to decide the most efficient irrigation technique on clay loam soil. The wheat crop was cultivated in Rabi season from November 2015 to March 2018 on a one-acre area of a local farmer of Sajawal district, Sindh. Randomize complete block design (RCBD) method was used to design and allocate 3 irrigation sub-plots. The results show significance p

Cost-effective smart irrigation controller using automatic weather stations

Water has become increasingly scarce and valuable resource due to the increasing population and misuse of the same. Agriculture is the largest sector using water with low-efficiency and low-cost. Traditional irrigation methodology uses a qualitative approach to schedule irrigation that does not measure actual environmental condition whereas the quantitative approach requires additional setup for climate measurement. Low cost innovative water-saving technology is the need of the hour. The presented work proposes the cost-effective smart irrigation controller using automatic weather stations(AWS). The proposed smart controller makes real-time irrigation decision by gathering climatic data from nearby AWS. AWS's data are available on an hourly basis from Indian meteorological department. The primary challenge in designing irrigation controller is to acquire real-time data, to validate and to reconstruct the missing data. These problems are addressed in the presented paper. Evapotranspiration computed from nearby AWS are comparable with evapotranspiration provided by Indian Agricultural Research Institute.

English

The study analyzed energy input-output of irrigated rice production at the Jere Bowl Borno State, Nigeria. One hundred and thirty farms were sampled through multistage sampling procedure. The data collected were analyzed using descriptive statistics and energy equations. The result showed that total of 36,397.85 MJ/ha of energy was consumed in the irrigated rice production with the highest energy input taken up by irrigation water (48.51%) and fuel (23.58%). The forms of energy estimated showed that direct energy contributed much to rice production (76.21%) than the indirect energy with 23.77%; similarly, renewable energy constituted higher energy (59.98%) to the production system, while non-renewable energy constituted only 39.99% of energy to the production system. The results on energy indices of rice production indicated energy ratio of 2.47, specific energy of 31.38 MJ/kg, energy productivity of 0.147 kg/MJ, water productivity of 0.103 kg/M3 and net energy of 53,598.71 Mj/ha. The lower values of energy indices indicate inefficient use of energy. The study recommended that farmers should adopt efficient and cost effective irrigation system which will ensure efficient utilization of energy. Key words: Input-output, energy, direct energy, indirect energy, renewable energy, indices, water productivity.

Identifying efficient agricultural irrigation strategies in Crete

Water scarcity and droughts are a major concern in most Mediterranean countries. Agriculture is a major user of water in the region and releases significant amounts of surface and ground waters, endangering the sustainable use of the available resources. Best Management Practices (BMPs) can mitigate the agriculture impacts on quantity of surface waters in agricultural catchments. However, identification of efficient BMPs strategies is a complex task, because BMPs costs and effectiveness can vary significantly within a basin. In this study, sustainable agricultural practices were studied based on optimal allocation of irrigation water use for dominant irrigated crops in the island of Crete, Greece. A decision support tool that integrates the Soil and Water Assessment Tool (SWAT) watershed model, an economic model, and multi-objective optimization routines, was used to identify and locate optimal irrigation strategies by considering crop water requirements, impact of irrigation changes on crop productivity, management strategies costs, and crop market prices. Three spatial scales (crop type, fields, and administrative regions) were considered to point out different approaches of efficient management. According to the analysis, depending on the spatial scale and complexity of spatial optimization, water irrigation volumes could be reduced by 32%–70% while preserving current agricultural benefit. Specific management strategies also looked at ways to relocate water between administrative regions (4 prefectures in the case of Crete) to optimize crop benefit while reducing global water use. It was estimated that an optimal reallocation of water could reduce irrigation water volumes by 52% (148 Mm3/y) at the cost of a 7% (48 M€) loss of agricultural income, but maintaining the current agricultural benefit (626.9 M€). The study showed how the identification of optimal, cost-effective irrigation management strategies can potentially address the water scarcity issue that is becoming crucial for the viability of agriculture in the Mediterranean region.

MOLDING OF SOIL WATER REGIME UNDER DRIP IRRIGATION IN EGYPT

ABSTRACT Information about the horizontal and vertical distances by which water spreads in soils under a point source is essential for the design of cost effective and efficient drip irrigation systems. The size of the wetting pattern influenced by many factors, including soil physical properties, soil initial conditions as well as emitter discharge rate, irrigation management, crop root characteristics and evapotranspiration. Models can help to predict soil water movement under point source irrigation for a wide range of soil and environmental conditions and varied design parameters and therefore save time and financial resources compared to field experiments.

Quasi 3D modelling of vadose zone soil-water flow for optimizing irrigation strategies: Challenges, uncertainties and efficiencies

A quasi 3D modelling approach was developed by integrating a crop growth (LINGRA-N) and a hydrological model (Hydrus-1D) to simulate and visualize water flow, soil-water storage, water stress and crop yield over a heterogeneous sandy field. We assessed computational efficiency and uncertainty with low-to high-spatial resolution input factors (soil-hydraulic properties, soil-layer thickness and groundwater level) and evaluated four irrigation scenarios (no, current, optimized and triggered) to find the optimal and cost-effective irrigation scheduling. Numerical results showed that the simulation uncertainty was reduced when using the high-resolution information while a fast performance was maintained. The approach accurately determined the field scale irrigation requirements, taking into account spatial variations of input information. Optimal irrigation scheduling is obtained by triggered-irrigation resulting in saving up to ∼300% water as compared to the current-irrigation, while yield increased ∼1%. Overall, the approach can be useful to help decision makers and applicants in precision farming.