Irrigation Water Management Research Articles

Estimation of crop coefficient for radish using digital lysimeter under polyhouse

Accurate quantification of crop water requirements of any crop is essential for irrigation scheduling and water management. The objective of this study was to estimate the crop coefficient of radish for different phenological stages under protected cultivation using digital lysimeter. The experiment was carried in the Agricultural Engineering College and Research Institute, Kumulur, Trichy. The experiment layout has been made to accommodate the three treatments (T1 - 120 % of ETc, T2 - 100 % of ETc and T3- 80 % of ETc) and four replications in drip irrigated polyhouse. The actual crop evapotranspiration (mm day-1) measured from digital lysimeter and ETo is the reference evapotranspiration (mm day-1) measured from Hargreaves model. The crop coefficient value of radish grown under protected cultivation during initial stage (Kcin), development stage (Kcdev), mid-stage (Kcmid) and final stage (Kcfin) for T1 was 0.72, 0.99, 1.01 and 0.81, T2 was 0.58, 0.84, 0.85 and 0.63 and T3 was 0.43, 0.61, 0.62 and 0.48 respectively. The study demonstrated that supplying additional water had no significant effect in radish yield under polyhouse. The crop coefficient (Kc) value obtained for treatment 100 % of ETc is suggested for optimal use of irrigation water for cultivating of radish crop in naturally ventilated greenhouse.

Efficient and Effective Irrigation Water Management Using Sprinkler Robot

This manuscript addresses the issue of irrigation water management with high efficiency and effectiveness and focuses on systems associated with significant water losses, which is sprinkler irrigation. This article presents mathematical modeling that enables the application of precision irrigation using a gun sprinkler robot. The sprinkler robot was fabricated in the Faculty of Agriculture and Natural Resources workshop at As-wan University. The experiments were conducted using 12, 14, and 16 mm nozzle sizes and three gun heights, 1.25, 1.5, and 2 m, at three forward speeds, 25, 50, and 75 m/h. The results revealed that at nozzle 12, the actual wetted diameter would be less than the theoretical diameter by a percentage of 2–5%, while at nozzle 14, it ranged from 2 to 7%, but at nozzle 16, it increased from 6 to 9%. The values of evaporation and wind drift losses were always less than 2.8 mm. The highest efficiency was achieved at the lowest forward speed (25 m/h) and using a 1.5 m gun height. The highest water application efficiency was 81.8, 82.5, and 81.1% using nozzle 12, nozzle 14, and nozzle 16, respectively. Precise irrigation control using sensor and variable rate technology will be the preferred option in the future.

Enhancing Temperature Data Quality for Agricultural Decision-Making with Emphasis to Evapotranspiration Calculation: A Robust Framework Integrating Dynamic Time Warping, Fuzzy Logic, and Machine Learning

This study introduces a comprehensive framework for assessing and enhancing the quality of hourly temperature data collected from a six-station agrometeorological network in the Arta plain, Epirus, Greece, spanning the period 2015–2023. By combining traditional quality control (QC) techniques with advanced methods—Dynamic Time Warping (DTW), Fuzzy Logic, and XGBoost machine learning—the framework effectively identifies anomalies and reconstructs missing or erroneous temperature values. The DTW–Fuzzy Logic approach reliably detected spatial inconsistencies, while the machine learning reconstruction achieved low root mean squared error (RMSE) values (0.40–0.66 °C), ensuring the high fidelity of the corrected dataset. A Data Quality Index (DQI) was developed to quantify improvements in both completeness and accuracy, providing a transparent and standardized metric for end users. The enhanced temperature data significantly improve the reliability of inputs for applications such as evapotranspiration (ET) estimation and agricultural decision support systems (DSS). Designed to be scalable and automated, the proposed framework ensures robust Internal Consistency across the network—even when stations are intermittently offline—yielding direct benefits for irrigation water management, as well as broader agrometeorological applications.

Empirically derived crop coefficient values for tomatoes grown in protected structures under climatic condition of Jalandhar, Punjab

In modern agriculture, calculating the Crop Water Requirement (CWR) for tomato crops under protected cultivation often relies on FAO-56 crop coefficient (Kc) values. However, these values may not fully account for the unique microclimatic variations within protected structures, creating a need for adjusted Kc values. This study aimed to develop growth-stage-specific Kc values for tomatoes grown under protected conditions in Jalandhar, Punjab. Results showed that daily microclimatic parameters, excluding relative humidity, were consistently higher in open-field conditions and lowest within protected environments. Pooled data indicated growth-stage-specific Kc values of 0.51, 1.05, and 0.61 for shed net houses; 0.53, 1.08, and 0.63 for polyhouses with insect net ventilation; and 0.51, 1.10, and 0.67 for open-field conditions, corresponding to the initial, mid, and late growth stages, respectively. Water consumption was highest during the mid-stage, decreasing progressively toward crop maturity. These empirically derived Kc values support precise CWR calculations through climatological irrigation scheduling, benefiting tomato cultivation in protected environments and similar agro-climatic regions. The development of growth-stage-specific Kc values provides a scientific foundation for improving irrigation water management and resource efficiency, offering valuable insights for farmers, policymakers, and water resource planners.

Building Climate-Resilient Food Systems Through the Water–Energy–Food–Environment Nexus

Climate change disrupts global food systems by affecting water, energy, ecosystems, and agricultural productivity. Building climate resilience demands integrated approaches that recognize interdependencies among water, energy, food, and environmental (WEF-E) systems. This review synthesizes current research on how the WEF-E nexus can guide climate adaptation strategies. It highlights interdisciplinary solutions—such as solar-powered irrigation, agrivoltaics, agroforestry, conservation agriculture, and nature-based water management—that enhance resource efficiency, stabilize yields, and reduce environmental degradation. Effective implementation requires governance innovation, stakeholder participation, and coherent cross-sector policies. The paper also outlines research priorities, including the development of resilience metrics, modeling tools, and inclusive decision-making mechanisms. Emphasizing both adaptation and mitigation, the WEF-E nexus offers a transformative lens for sustainable, equitable, and climate-resilient food systems. As climate pressures intensify, advancing this integrated framework presents both an urgent necessity and a strategic opportunity to align food security with environmental stewardship.

Modern Approach of Evapotranspiration Estimation for Precision irrigation water management

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The sensitivity of rice production to transplanting date and irrigation water management in a drier climate future scenario

The sensitivity of rice production to transplanting date and irrigation water management in a drier climate future scenario

Solar Based Irrigation System Application as an Option for Energy Source for Irrigation Water Management in Ethiopia: A Review

Electricity is the most cost-effective and efficient energy source for pumping water, but farmers with small, scattered plots might not have access to it. To raise water for irrigation, farmers rely on diesel or gasoline pumps, which is expensive and non-sustainable. For better management of water and economic benefit, considering another option for irrigation such as the solar pumped irrigation system could be important. Solar power enhances efficiency, productivity, and sustainability in agricultural operations in addition to offering a clean alternative to fossil fuels. In agriculture, it is increasingly being integrated through several innovative applications that are transforming traditional farming practices. The future of solar energy in agriculture is promising, driven by technological advancements, supportive policies, and increasing awareness of sustainable practices. The objective of the study is to identify the practical applicability of solar pump in other countries and the challenges and opportunities for its applicability in Ethiopia in irrigated agriculture. Existing scholarly research that has been published as journal articles serves as the study's methodology. The resources (Scopus and Google customized search), eligibility and exclusion criteria, review process phases, data abstraction, and analysis are all part of the methods used. The study shows that the solar radiation is the primary source of energy for solar pump and it depends on the climatic condition and geographical location of the area. Most African countries are practicing the solar pump and it was highly practiced in sub-Saharan African countries such as Kenya, Ethiopia, Sudan and also other equatorial and sub-equatorial countries. Additionally, since the North and South hemisphere are linked with permanent cloud cover and only intermittent bright sunshine, the future installation of solar pump will also be practiced in these areas such as the Congo, Gabon, Rwanda, and Senegal. It is also highly practiced in Mali for irrigation, livestock production and for domestic use. There is a growing demand for solar pump irrigation in Ethiopia. Accordingly, one of the government’s strategy is to transit existing motor pump users to solar, while also introducing new solar pump irrigation to those not currently irrigating. The primary challenges of utilizing solar pumps in Ethiopia was high initial costs, while the country's abundant solar radiation and potential for increased agricultural productivity were the best opportunities for its implementation. However, this technology has to be supported through evidence by conducting research and creating awareness for the end users and other policy makers.

Participatory Irrigation Management: A Case Study of the Waghad Project, Maharashtra State, India

ABSTRACT In this paper, an attempt has been made to study community participation in irrigation water management for sustainability of the farming business in the state of Maharashtra, India. Waghad irritation project has been selected for detailed investigation. Waghad irrigation project is located in the tribal area of Nashik district of Maharashtra, India. Waghad irrigation project is a unique case in which complete control of management, operation and maintenance has been transferred to the federation formed by 24 WUAs existing in this project. This federation is the apex organization called Waghad Project Level Water Users’ Association (WPLWUA). The study reveals that the cluster of WUAs of Waghad project is supplying equitable, judicious, timely and assured water to farming community which is the result of an innovative and sustainable irrigation management transfer. It builds up a sense of responsibility amongst the farming community. The assured water supply has an in built incentive to promote micro irrigation techniques, which has led to improvement in water use efficiency as well as crop productivity in the command area of the project. Waghad model of community participation in irrigation water management is very successful and have got several state and national level awards for participatory irrigation management, operation and maintenance of irrigation system in India. Keywords: Participation irrigation management,Water Users’ Association, Waghad Irrigation Project

District to subdistrict scale optimum irrigation water management planning at multi-week lead time

District to subdistrict scale optimum irrigation water management planning at multi-week lead time

A Historical Review of the Land Subsidence Phenomena Interaction with Flooding, Land Use Changes, and Storms at the East Thessaly Basin—Insights from InSAR Data

The Thessaly Plain, Greece’s largest alluvial basin, has undergone significant geological, hydrological, and anthropogenic transformations. This study synthesises historical records, geological and hydrogeological studies to assess the evolution of the East Thessaly Plain, focusing on land use changes, groundwater management, and environmental challenges. Intensive agricultural practices, particularly from the 1970s onward, have led to groundwater overexploitation, land subsidence, and declining water quality. The overexploitation of the aquifers, exacerbated by extensive irrigation and inefficient water management, has resulted in critical groundwater shortages and widespread subsidence, particularly in the Larissa–Karla and Titarisios Cone systems. Additionally, recent extreme weather events, including Medicane Daniel (2023) and Medicane Ianos (2020), have highlighted the region’s vulnerability to hydrological hazards, with extensive flooding affecting urban and agricultural areas. The re-emergence of Lake Karla as a flood retention area underscores the unintended consequences of past drainage efforts. Remote sensing, geodetic surveys, and historical records have been examined to assess the interplay between groundwater withdrawals, land subsidence, and flood risks.

Smart Irrigation Technologies and Prospects for Enhancing Water Use Efficiency for Sustainable Agriculture

Rapid population growth, rising food demand, and climate change have created significant challenges to meet the water demands for agriculture. Effective irrigation water management is essential to address the world’s water crisis. The transition from conventional, frequently ineffective gravity-driven irrigations to contemporary, pressure-driven precision irrigation methods are explored in this article, addressing the difficulties associated with water-intensive irrigation, the possibility of updating conventional techniques, and the developments in smart and precision irrigation technologies. This study comprehensively analyses published literature of 150 articles from the year 2005 to 2024, based on titles, abstract, and conclusions that contain keywords such as precision irrigation scheduling, water-saving technologies, and smart irrigation systems, in addition to providing potential solutions to achieve sustainable development goals and smart agricultural production systems. Moreover, it explores the fundamentals and processes of smart irrigation, such as open- and closed-loop control, precision monitoring and control systems, and smart monitoring methods based on soil data, plant water status, weather data, remote sensing, and participatory irrigation management. Likewise, to emphasize the potential of these technologies for a more sustainable agricultural future, several smart techniques, including IoT, wireless sensor networks, deep learning, and fuzzy logic, and their effects on crop performance and water conservation across various crops are discussed. The review concludes by summarizing the limitations and challenges of implementing precision irrigation systems and AI in agriculture along with highlighting the relationship of adopting precision irrigation and ultimately achieving various sustainable development goals (SDGs).

Major Crops Water Requirements and Automated Irrigation Scheduling System

Agriculture is a critical factor that impacts a country's economy. The agriculture sector uses 70% of the available fresh water. There are challenges in water management and irrigation scheduling that require resolution. Farmers are using traditional irrigation methods that use a lot of water with low water efficiency. Smart irrigation and farm management technology is crucial to sustainable agriculture, as it saves water and provides farmers with more information about crop water requirements. However, managing irrigation water is a complex task that depends on factors such as soil, weather, and environment. Robust modeling is necessary to accurately estimate the water requirements of a crop. In this we developed a smart irrigation model to automate the irrigation system according to water requirements of crops. To estimate the water requirements of crops a review was done on different crop water requirements and crops features. To develop the automated irrigation system an analysis is done on different irrigation methods, irrigation scheduling and requirements of irrigation scheduling. The proposed system is used to automated irrigation system and real time data is sent to think speak server for regular monitoring. The developed automated irrigation system is working up to expectations and help farmers to control the irrigation and conserve water by avoiding over irrigation.

Analysis of agricultural practices' impact on the quality of irrigation water for growing vegetables in the Urban Commune of N'Zérékoré, Republic of Guinea

Irrigation water quality is a crucial factor influencing agricultural productivity and food safety. In the urban commune of N'Zérékoré, vegetable farming is a predominant activity. However, most local growers lack precise information on the quality of the water used for irrigation due to the absence of systematic monitoring by agricultural and public health authorities. This study, conducted in February 2024 in the Nyèn I and Nyèn II districts, aimed to assess the physico-chemical and biological characteristics of irrigation water used for vegetable cultivation. Water samples were collected weekly from both districts and analyzed using volumetric analysis and molecular absorption spectrophotometry. Data were processed using XLSTAT 2016 software, followed by an ANOVA with NSK’s test at a 5% significance level. The results showed that the concentrations of chemical elements, as well as total and fecal coliforms, were statistically similar across both sites. No significant variations were observed between the different sampling weeks. The mean concentrations of potassium (11.15 mg/L), manganese (0.34 mg/L), sulfates (11 mg/L), nitrates (42.02 mg/L), nitrites (1.9 mg/L), and total iron (2.94 mg/L) remained within acceptable levels for agricultural use. However, microbiological analysis revealed significant contamination, with fecal coliform counts averaging 869.75 CFU/100 mL and total coliform counts reaching 1142.50 CFU/100 mL, indicating potential health risks for crops and the environment. These findings highlight the need for phytoremediation measures, improved water treatment, and better irrigation water management to ensure safer and more sustainable agricultural practices in N'Zérékoré.

AGRICULTURALLY MANAGED AQUIFER RECHARGE (AgMAR) / FLOOD MAR ADAPTATION FOR KAZAKHSTAN

Climate change is transforming water systems worldwide, bringing more unpredictable weather patterns and challenging water management practices. Prolonged droughts, intensified storms, diminishing snowpacks, and shifting runoff dynamics complicate efforts to ensure water security. In Kazakhstan, attempts to mitigate flooding through dam construction have proven inadequate for managing urban stormwater runoff effectively. This study explores the implementation of Agricultural Managed Aquifer Recharge (AgMAR) in Kazakhstan, leveraging 3D visualizations created with the PyVista library to model soil layers, water flow dynamics, and the MAR principle. The findings highlight AgMAR as a promising solution for irrigation and rural water management, offering benefits such as groundwater stabilization, aquifer recharge during seasonal precipitation, purification of underground water sources, and increased freshwater availability.

Assessment of Evapotranspiration, Water Productivity and Yield Response Factor for Groundnut under Deficit Irrigation Using Lysimeter in a Hot Arid Ecosystem

In this study, we focused on precise determination of actual crop evapotranspiration (ETc) of groundnut in an arid region of India using single load cell-based mini-lysimeters. This study, for the first time, integrated two water saving techniques, i.e., pressurized irrigation system through mini-sprinklers and deficit irrigation strategy. The groundnut crop (var. Girnar-2) was grown in lysimeter as well as in field plots under deficit irrigation treatments based on cumulative pan evaporation (CPE), i.e., T1 (100% of CPE), T2 (80% of CPE), T3 (60% of CPE) and T4 (40% of CPE) with three replications during 2014-2018. Lysimeters’ weights were monitored daily to determine ETc and soil moisture at weekly interval. Yield response factor (Ky) and crop water productivity were computed in all four treatments. The ETc (661-817 mm) and pod yield (4.2 t ha-1) for groundnut were obtained as the highest in treatment T1. However, water productivity was maximum (0.61 kg m-3) in treatment T2 on sacrificing 8.7% of the yield obtained in treatment T1. The mean Ky value for groundnut under deficit irrigation was computed as 0.63 and varied from 0.68 (T2) to 1.34 (T4). This finding indicates that groundnut can tolerate up to 80% deficit irrigation, and beyond this level, the crop becomes sensitive to water stress with large reduction in pod yield. On the other hand, the pod yield revealed 24% and 46% reductions at 60% and 40% deficit irrigation levels, respectively. Therefore, in arid climate, where water is a precious and limited natural resource, irrigation at 80% CPE in groundnut crop is plausible and profitable irrigation water management strategy.

Assessing capacitance soil moisture sensors for precision irrigation scheduling in wheat crop

Abstract Water resources influence agricultural production, yet efficient utilization, particularly water conservation in irrigation still remains a significant challenge in developing nations. This study aimed to calibrate and evaluate three capacitance soil moisture sensors, namely, capacitive v1.2, capacitive v2.0 and capacitive waterproof sensors for various soil textures at the Indian Agricultural Research Institute (IARI; New Delhi) research farm. The study assessed the sensors’ adaptability for irrigation scheduling and their impact on yield and water productivity in wheat crops during the years 2021–2022 and 2022–2023. Experimental results demonstrated that location-specific calibrated capacitive waterproof soil moisture sensor outperformed the others, with the lowest prediction error statistics, including MAE (0.30 to 0.43), RMSE (0.35 to 0.46) and NMBE close to zero, along with high accuracy (NSE > 0.97). Irrigation scheduling using capacitive waterproof soil moisture sensors of two wheat cultivars (HD:2967 and HD:3086) under three irrigation regimes (Field capacity, 20% and 40% deficit irrigation) indicated that soil moisture sensors measured the soil moisture content closely aligned with the measured values for all irrigation regimes. Grain yields for HD:2967 were 5.66 t/ha and 5.21 t/ha, and for HD:3086, 5.45 t/ha and 4.89 t/ha under field capacity irrigation regimes for 2021–2022 and 2022–2023, respectively. Correspondingly, crop water productivity (CWP) was highest under the 40% deficit irrigation regime, with values reaching 19.8 kg/ha.mm for HD:2967 and 19.42 kg/ha.mm for HD:3086 in 2021–2022. In 2022–2023, the CWP values were 17.35 kg/ha.mm for HD:2967 and 16.74 kg/ha.mm for HD:3086 under the same regime. These findings suggested that soil moisture sensors, when calibrated for specific locations, can effectively manage irrigation water in field crops, thereby improving both grain yield and CWP.

Human health risk assessment of dietary metal intake through commonly consumed vegetables in Gaya District, Bihar, India

ABSTRACT This study assessed the concentration of Al, As, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Se, and Zn in commonly grown vegetables collected from the Gaya district of Bihar. Metals were determined using Inductively Coupled Plasma Mass Spectrometry following sample preparation and digestion. As, Cr, Ni, Pb and Zn exceeded the maximum allowable concentration of Food and Agricultural Organization in some of the vegetable samples. Non-carcinogenic human health risk assessment due to ingestion of vegetables was estimated using Hazard Quotient (HQ) and Hazard Index (HI) which revealed that non-carcinogenic risks were primarily due to Co, followed by Cr and Fe. The risk was higher in the leafy and underground vegetables as compared to the fruit vegetables. Of all the locations, the highest risk was estimated for Fatehpur, followed by Manpur and Bodhgaya, which was attributed to the anthropogenic activities of the locations. The HI exceeded unity in 64.3% of the vegetable samples, indicating potential health risks to the consumers and suggesting that vegetables from some locations in the Gaya district might have food safety issues. Periodic soil testing, irrigation water management, and avoidance of leafy vegetables from polluted sites are suggested to lower the health risks associated with vegetable consumption.

Estimation of Crop Evapotranspiration of Wheat Using Remote Sensing & GIS Based Crop Coefficient

The practice of planning and controlling irrigation water applications to satisfy crop water needs without wasting water, soil, or plant nutrients is known as irrigation water management. Usage of the FAO-56 bulletin's instructions, which use tabular crop coefficients (Kc), is popular when evaluating agricultural water requirements. Crop evapotranspiration (ETc), which is directly dependent on crop coefficient curves, is based on point-based crop coefficients. The trend of multispectral vegetation indices (VIs) produced from remote sensing is comparable to that of crop coefficients (Kc). As such, VIs can serve as a Kc alternative and be used to estimate crop coefficients. The use of VI may provide Kc a spatial dimension, allowing for the accurate recording of the spatial variability in water requirements. Therefore, the main objective of the current study, was to determine which VI is most appropriate for the rabi wheat crop for the 2022–2023 crop year and has a tight correlation with crop coefficients. The study was carried out in the North Maharashtra district of Nashik. The Sentinel 2A, MIS sensor's multi-date and multi-spectral images were utilized to create the multi-temporal vegetation indices (NDVI, NDWI, SAVI, and MSAVI2) for the 2022–2023 year. The agricultural acreages were determined by applying hybrid classification utilizing K means clustering and visual analysis of remote sensing. These estimates for wheat showed 3.83 percent variations from the Department of Agriculture's predictions for the year 2022–2023. The multidate vegetation index data for NDVI, NDWI, SAVI, and MSAVI 2 were ordered for the years 2022–2023 based on age given in weeks. To establish a relationship with VIs, week wise crop coefficients (Kc), as recommended by MPKV Rahuri, were used. Through the use of linear regression analysis, the correlations were created into prediction models. In the situations of wheat year 2022–2023 among all the VIs, the NDWI model performed best it shown that NDWI showed the greatest collaboration with the crop coefficient. Its R2 and D values were highly significant, at 0.9365 and 0.986, respectively. It also had the lowest PD, SE, and RMSE values-0.095, 0.0891, and 3.34, respectively. Thus, it is possible to calculate the geographical crop coefficients for wheat using the NDWI-Kc model (Kc = 4.2302NDWI + 0.3716). The NDWI-Kc model was utilized to derive the week-wise crop coefficients (Kc) for wheat, and the FAO Penman-Monteith method was used to estimate the reference evapotranspiration (ETo). After that, the crop evapotranspiration (ETc) was estimated by multiplying the corresponding Kc values by ETo. 397.13 mm of water was anticipated to be needed overall for the wheat crop in the Nashik district. Thus, it was determined that the study area's total water need for wheat was 22907238.307 ha.cm, or 229.07 Mm3. Because there is less rainfall during the rabi season, the amount of water required for irrigation nearly equals the amount needed for crops in the area. "This study investigates the use of multispectral remote sensing data from Sentinel-2A to estimate wheat evapotranspiration (ETc) using GIS-based crop coefficients. Vegetation indices such as NDVI, NDWI, SAVI, and MSAVI2 were evaluated to identify the most accurate model for predicting crop water demand. The results show that the NDWI-Kc model demonstrated the strongest correlation and accuracy in estimating spatial crop coefficients".

Production of Panicum maximum cv. Mombaça Under Fertilization Management and Ozonation of Irrigation Water

Ozonation of irrigation water is a promising technology that improves the efficiency of irrigation systems. However, it is necessary to investigate the potential adverse effects of the continuous application of this technology on pastures, particularly on Mombaça grass (Panicum maximum cv. Mombaça), to ensure that its benefits are not outweighed by negative impacts. This study aimed to evaluate the impact of ozonated irrigation water on the production of Mombaça grass under different fertilization management practices. The experiment was conducted in a controlled environment using 4.5 L pots, following a completely randomized design with five replications. The experimental setup employed a factorial arrangement, involving two irrigation water sources (with and without ozonation) and two fertilization managements (with and without N and K2O), resulting in 20 experimental units. A 60-day uniformity cycle and three 30-day cycles were performed, assessing water consumption as well as the morphogenic and agronomic characteristics of Mombaça grass. Fertilization with N and K2O increased water consumption and improved the agronomic characteristics of Mombaça grass, promoting greater development and growth in line with its morphogenic traits. Regardless of fertilization, ozonation of irrigation water did not cause harm to growth and biomass yield. Therefore, the technique of ozonating irrigation water can be used in the cultivation of Mombaça grass.