Global Water Research Articles

Comparative study of teachable machine for forest fire and smoke detection by drone

Forests play a vital role in maintaining ecological equilibrium and serving as vital habitats for wildlife. They regulate global climate, safeguard soil and water resources, and provide crucial ecosystem services such as air and water purification, essential for human well-being and sustainable development. Forest fires wreak havoc on ecosystems and wildlife, emitting harmful pollutants, disrupting communities, and increasing the risk of erosion and landslides. Detecting forest fires through satellite imaging, aerial reconnaissance, and ground-based sensors is pivotal for early detection and containment, safeguarding human lives, wildlife, and preserving natural resources for future generations. Utilizing drones and deep learning (DL) algorithms can significantly enhance early fire detection and minimize their devastating impact. In this paper, we examine teachable machine, a Google tool for creating DL models. We compare the top model generated by teachable machine for fire and smoke detection to models obtained through transfer learning from established DL models in image recognition and computer vision (CV), such as VGG16, VGG19, MobileNet, MobileNetv2, and MobileNetv3. The results underscore the significance of employing the teachable machine model in specific fire and smoke detection scenarios.

Efficient Soil Health Monitoring and Irrigation Management System Using Fuzzy Logic

Abstract: The need for sustainable agriculture is acutely felt due to ever increasing global water crisis. Efficient irrigation management is crucial in this regard. The proposed system employs a network of soil moisture sensor distributed over a agricultural field, where continuous acquisition of real time data on soil moisture levels is done. Soil moisture measurement is a vital parameter in terms of precision agriculture, which affects the irrigation scheduling for ensuring optimal crop growth. Traditional methods related face challenges adapting to changing soil patterns at different conditions. The system proposes application of fuzzy logic algorithm for processing of data. Key advantages of using fuzzy logic in soil moisture measurement include improved precision in moisture detection, enhanced ability to make more informed irrigation decisions. The proposed system delivers a model for promoting water conservation, enhancing crop productivity and maintaining soil health.

An Atmospheric Water-Harvester with Ultrahigh Uptake-Release Efficiency at Low Humidity.

Atmospheric water harvesting is a practical strategy that is achieved by removing materials from air moisture to relieve global water scarcity. Here we design a water-harvester (i.e., MOF-303/thiolated polymer composite (MTC)) by using a metal-organic framework (MOF-303) and thiolated chitosan (TC) skeleton. Intermolecular hydrogen bonding between TC and MOF-303 facilitates porous structures with enlarged air-polymer interfaces for long cycling life and high capacity at low relative humidity. Benefiting from synergetic effects on porosity and anchorage for accelerating the uptake-release of moisture, MTC exhibits a rapid water uptake capacity of 0.135 g/g in 60 min under 12.5 RH% and ultrafast water desorption kinetics of 0.003 g/g/min at 8.5 RH%, which is superior to the as-reported MOF-303 based adsorbents. At low heat (∼40 °C), the water desorption and collection rate, respectively, are 0.0195 and 0.0168 g/g/min within 210 min, showing ultrahigh harvesting efficiency. These results highlight the enormous potential as promising materials for solving the world's water scarcity crisis. This study offers an insight into the design of AWH materials, which can be extended into applications in some realms, e.g., freshwater development for industry in arid areas, water engineering-related devices and systems, etc.

Design of Phytic Acid Crosslinked Xerogels as Organic Photocatalysts for Visible Light‐Assisted Degradation of Dyes

AbstractExtensive research is being carried out on the degradation of water pollutants using various strategies to overcome the global water crisis. In the present study, xerogels as a better alternative is utilized to metal oxides for the photocatalytic degradation of toxic water pollutants such as dyes. Xerogels of polyaniline (PANI) and polypyrrole (PPy) are synthesized using phytic acid as a dopant as well as cross‐linker in the weight ratios of 1:1, 1:2, and 2:1 via simple chemical oxidative polymerization. The synthesized xerogels are analyzed for their spectral, morphological, thermal, and optical properties using FTIR, UV–vis, XRD, SEM, and TGA techniques. The xerogels are also tested for their photocatalytic activity against textile dyes – Methylene Blue (MB), Alizarin Red S, (ARS), Rhodamine B (RhB), and Methyl Orange (MO). Among all the composite xerogels, PANI/PPy‐2/1 showed excellent degradation efficiency of 91% for MB dye, 88% for RhB dye, 96% for ARS dye, and 92% for MO dye respectively. The composite PANI/PPy xerogels showed better degradation efficiency than their pristine counterparts. The fragments of the degraded dyes are examined using the LCMS technique and a tentative dye degradation mechanism is proposed.

Artificial Intelligence in Water Management for Sustainable Farming: A Review

Artificial Intelligence (AI) is capable of enhancing water management for sustainable farming. The growing demand for agricultural productivity and sustainability in the context of finite water resources and climate change drives the necessity for more efficient water management practices. AI technologies, through automated and precision irrigation systems, AI-based predictive models, and AI-driven water quality monitoring, offer significant improvements in water efficiency and agricultural output. These systems optimize irrigation scheduling based on real-time data, enhance the precision of water application, and ensure water quality, thus supporting sustainable agricultural practices. However, the implementation of AI in water management is not without challenges. Technical difficulties in adapting AI to diverse agricultural environments, data privacy and security concerns, ethical considerations, and barriers to adoption among small-scale farmers are critical issues that need addressing. This study addresses both the transformative impacts and the inherent challenges of integrating AI technologies. Furthermore, the review identifies a gap in research regarding AI’s adaptability to variable climates and its integration with socio-economic data, suggesting that future studies focus on these areas. Policy recommendations are also discussed, emphasizing the need for developing standards and best practices, increasing funding and incentives for AI research, promoting training and capacity building, and establishing robust regulatory frameworks for data management. By tackling these challenges and leveraging AI’s full potential, water management in agriculture can be significantly improved, leading to enhanced global water security and sustainability in farming practices. The review concludes that while AI presents a promising future for agricultural water management, strategic and thoughtful approaches are required to overcome obstacles and fully realize the benefits of this technology.

Global total precipitable water variations and trends over the period 1958–2021

Abstract. Global responses of the hydrological cycle to climate change have been widely studied, but uncertainties still remain regarding water vapor responses to lower-tropospheric temperature. Here, we investigate the trends in global total precipitable water (TPW) and surface temperature from 1958 to 2021 using ERA5 and JRA-55 reanalysis datasets. We further validate these trends using radiosonde from 1979 to 2019 and Atmospheric Infrared Sounder (AIRS) and Special Sensor Microwave Imager/Sounder (SSMIS) observations from 2003 to 2021. Our results indicate a global increase in total precipitable water (TPW) of ∼ 2 % per decade from 1993–2021. These variations in TPW reflect the interactions of global warming feedback mechanisms across different spatial scales. Our results also revealed a significant near-surface temperature (T2 m) warming trend of ∼ 0.15 K decade−1 over the period 1958–2021. The consistent warming at a rate of ∼ 0.21 K decade−1 after 1993 corresponds to a strong water vapor response to temperature at a rate of 9.5 % K−1 globally, with land areas warming approximately twice as fast as the oceans. The relationship between TPW and T2 m showed a variation of around 6 % K−1–8 % K−1 in the 15–55° N latitude band, aligning with theoretical estimates from the Clausius–Clapeyron equation.

A Super-Hygroscopic Solar-Regenerated Alginate-Based Composite for Atmospheric Water Harvesting.

Global water scarcity is leading to increasingly tense competition across populations. In order to complement the largely fast-depleting fresh water sources and mitigate the challenges generated by brine discharge from desalination, atmospheric water harvesting (AWH) has emerged to support long-term water supply. This work presents a novel alginate-based hybrid material comprised of porous silico-aluminophosphate-34 (SAPO-34) as fast-transport channel medium as well as hydrophilicity and stability enhancer, and graphene-based sheets as light absorber for solar-enabled evaporation, both optimally incorporated in an alginate matrix, resulting in a composite sorbent capable of harvesting water from the atmosphere with a record intake of up to 6.85 gw gs -1. Natural sunlight is solely used to enable desorption achieving increase of the temperature of the developed network up to 60°C andresulting in release of the sorbed water, with impurities content well below the World Health Organization (WHO) upper limits. After 30 cycles of sorption and desorption, the composite hydrogel displayed unchanged water uptake and stability. This work provides an impactful perspective toward sustainable generation of water from humidity without external energy consumption supporting the emergence of alternative water production solutions.

Deficit Irrigation-Based Improvement in Growth and Yield of Quinoa in the Northwestern Arid Region in China

Given the current global water scarcity issues, which particularly affect arid regions such as northwestern China, it is crucial to find crop planting patterns that result in efficient water resource utilization. Quinoa, as a drought-resistant and highly nutritious crop, has garnered significant attention from agricultural researchers in recent years. From 2019 to 2020, a series of experimental studies were conducted under non-mulching drip irrigation conditions to investigate the growth adaptability and the response to different irrigation levels of quinoa in an arid region in northwestern China. A comparative analysis of quinoa’s dry matter accumulation, yield, thousand-grain weight, harvest index, and water use efficiency under varying irrigation levels revealed that increasing irrigation significantly enhanced quinoa’s dry matter accumulation and yield. By optimizing the irrigation strategies, we found that the water-saving practice of initiating moderate irrigation in the sensitive water-demanding stages (flowering and fruiting) of quinoa increased the yield. The experiment results showed that, in 2020, the optimal irrigation amount was 3675 m3·ha−1 during a 14-day irrigation cycle, meeting quinoa’s growth requirements while improving water resource utilization efficiency. This study not only provides a scientific basis for the efficient cultivation of quinoa in the arid regions of northwestern China, but also offers new insights into and technical support for agricultural water resource management in the region, contributing to the sustainable development of agriculture in arid areas.

In situ Electrical Impedance Tomography for Visualizing Water Transportation in Hygroscopic Aerogels.

The global water crisis demands immediate attention, and atmospheric water harvesting (AWH) provides a viable alternative. However, studying the real-time subtle relationship between water absorption, diffusion, and internal structure for hygroscopic materials is challenging. Herein, a dynamic visualization technique is proposed that utilizes an in situ electrical impedance tomography (EIT) system and a precise reconstruction algorithm to achieve real-time monitoring of the water sorption process within aerogels from an internal microstructural perspective. These results can be inferred that composites' pore sizes affecting the kinetics of their moisture absorption. In addition, the diffusion path of moisture absorption and the distribution of stored moisture inside aerogels exhibit intrinsic self-selective behavior, where the fiber skeleton of the aerogel plays a crucial role. In summary, this work proposes a generic EIT-based technique for the in situ and dynamic monitoring of the hygroscopic process, pointing to an entirely new approach regarding research on AWH materials.

Spatiotemporal coupling analysis of surface water and groundwater in Tibet based on multi-source sensors

Abstract. Lakes and groundwater are two crucial components of the global terrestrial water cycle, collectively forming a vital network for Earth's water resources. However, in the Tibetan region, the spatiotemporal relationship between lakes and groundwater and their impact on the local hydrological cycle remain inadequately understood. Satellite remote sensing serves as an effective observational tool, enabling comprehensive investigation and analysis of surface lakes and groundwater in Tibet with high spatial resolution. Therefore, this study integrates Landsat and Cryosat-2 satellite data to examine the spatiotemporal patterns of surface lake extents and water levels in Tibet. Additionally, combining Gravity Recovery and Climate Experiment (GRACE) satellite observations with the Global Land Data Assimilation System (GLDAS) model data, we quantitatively analyze the spatiotemporal variations in groundwater storage and its correlation with lake water. The results indicate that: 1) Rivers and lakes in Tibet are mainly located in the central and northwest regions, displaying noticeable intra-annual variations; 2) Substantial lagged relationships exist between groundwater storage and lake water levels and areas, revealing that lakes contribute significantly to groundwater replenishment, especially in the Ngari prefecture and Lhokha prefecture. This study comprehensively utilizes multi-source remote sensing data to dynamically monitor surface and groundwater in Tibet, providing robust support for a better understanding of the interaction between groundwater and surface water.

Solar-powered porous polymer materials-enabled rapid atmospheric water harvesting and storage of liquid water

Atmospheric water harvesting (AWH) is emerging as a promising strategy to produce fresh water from abundant airborne moisture to reduce the global clean water shortage. Hydrogels are considered attractive adsorbents due to their higher water retention and tunable polymer-water interactions. Here, we report the super hygroscopic polymer material (SHPMs) using modified NH2-MIL-101(Cr) as a functional crosslinker by copolymerization with acrylic acid and 2-Acrylamide-2-methylpropanesulfonic acid, achieving a water uptake of about 28.8–49.7 mg/g at 28–38 % RH. The material can desorption quickly under sunlight, and the desorbed water can be stored in a polymer skeleton for use by vegetation or crops during periods of water demand. Besides, the Water retention and storage performance and its outdoor experiment also proved that the application of this material in agriculture, forestry and desertification control laid the foundation to improve the effective availability of soil moisture and water harvesting and conservation. With its excellent water retention and atmospheric water harvesting performance, the material offers a sustainable method for rapid water extraction in arid climates.

Chinese architecture inspired smart roof tile integrating radiation cooling, water harvesting, and energy recycling

The development of new materials for resource and energy recycling has emerged as a primary focus in addressing global energy and environmental sustainability challenges. Inspired by traditional Chinese architecture, a smart roof tile (SRT) is scientifically designed, which incorporates hierarchical micro-nanostructured polyethylene/silica/barium sulfate composites (IH-PSB), semiconductor power generation modules, and LED chips. Leveraging the combined effects of surface and interface functionalities, the IH-PSB demonstrates exceptional sub-ambient cooling capabilities, resulting in its surface and bottom temperature being 5.4 °C and 12.1 °C lower than the ambient temperature, respectively. Additionally, the precisely controlled heterogeneous wettability, with a contact angle of approximately 151° and a roll-off angle of around 32°, allows the IH-PSB to efficiently condense moisture and transport droplets. Benefiting from the excellent radiation cooling performance and precisely controlled heterogeneous wettability, the IH-PSB exhibits remarkable passive sub-dewpoint cooling efficiency coupled with efficient water harvesting performance. During a one-month outdoor experiment, the IH-PSB operated stably and continuously without any electrical input, maintaining a mass flux ranging from ∼23.2–50.0 g m−2 h−1. Interestingly, the SRT system efficiently harnesses waste heat generated by the LEDs while simultaneously regulating their temperature effectively. The development and utilization of the SRT offer a sustainable, energy-efficient, and forward-thinking solution that addresses global water scarcity and energy crises.

Global WaterPack - The development of global surface water over the past 20 years at daily temporal resolution

Open surface water across the globe is essential for many life forms and is an important source for human settlements, agriculture, and industry. The presence and variation in time and space is influenced by different natural conditions (e.g. climate, topography, geology) and human use (e.g. irrigation, flood protection). The information on the spatial and temporal distribution of open surface water is fundamental for many disciplines and is also required as an essential parameter for hydrological and climatological modelling. Here, we present a dataset derived from satellite earth observation, which is based on more than 6.3 million single MODIS products with a volume of approx. 300 TB. The resulting dataset reflects the situation of open surface water on a global scale for each day over the time period from 2003 to 2022 at a spatial resolution of 250 m. The dataset enables the analysis of the development of lake and reservoir surface areas, freezing cycles, and inundation areas.

Quasi-biennial oscillation modulation of stratospheric water vapour in the Asian monsoon

Abstract. The Asian monsoon (AM) plays a key role in the transport of water vapour to the lower stratosphere and contributes significantly to the wet phase of the annual global stratospheric water vapour cycle. Although it is known that the quasi-biennial oscillation (QBO) is one of the main drivers of the interannual variability in the AM water vapour, the physical mechanisms responsible for this variability remain unclear. Here we have used daily microwave limb sounder data for the period 2005–2020 to characterize the QBO signature on the lower stratosphere AM water vapour during the boreal summer. We show that the QBO has the strongest impact during August, when QBO westerly minus QBO easterly differences may reach 1 ppmv at 100 hPa, although a significant signature is also observed during July. We find that the region whose temperature controls the QBO signal on water vapour over the AM differs between July and August. In July, when the key region is over the tropical Indian Ocean, the QBO modulation of the AM water vapour occurs in phase with the signal over the Equator, whereas in August, when the key region is at the subtropics, over the southern edge of the monsoon, the signal over the AM is opposite to that over the Equator. Our results reveal that the QBO signal on the temperature on the south side of the AM anticyclone, which ultimately has an impact on AM water vapour, is, in turn, modulated by the QBO impact on tropical clouds. Thus, we find that the QBO signature on clouds over the eastern Indian Ocean gives rise to Rossby wave trains that produce variations in the circulation over the southern side of the AM anticyclone such that weaker anticyclone over this region generates an increase in water vapour, and vice versa.

Two Decades of Integrated Flood Management: Status, Barriers, and Strategies

Losses from flood disasters are increasing globally due to climate-driven forces and human factors such as migration and land use changes. The risks of such floods involve multiple factors and stakeholders, and frameworks for integrated approaches have attracted a global community of experts. The paper reviews the knowledge base for integrated flood risk management frameworks, including more than twenty bibliometric reviews of their elements. The knowledge base illustrates how integrated strategies for the reduction of flood risk are required at different scales and involve responses ranging from climate and weather studies to the construction of infrastructure, as well as collective action for community resilience. The Integrated Flood Management framework of the Associated Programme on Flood Management of the World Meteorological Organization was developed more than twenty years ago and is explained in some detail, including how it fits within the Integrated Water Resources Management concept that is managed by the Global Water Partnership. The paper reviews the alignment of the two approaches and how they can be used in tandem to reduce flood losses. Success of both integrated management approaches depends on governance and institutional capacity as well as technological advances. The knowledge base for flood risk management indicates how technologies are advancing, while more attention must be paid to social and environmental concerns, as well as government measures to increase participation, awareness, and preparedness. Ultimately, integrated flood management will involve solutions tailored for individual situations, and implementation may be slow, such that perseverance and political commitment will be needed.

A Qualitative Study of Water Quality Using Landsat 8 and Station Water Quality-Monitoring Data to Support SDG 6.3.2 Evaluations: A Case Study of Deqing, China

Facing the challenge of the degradation of global water quality, it is urgent to realize the Sustainable Development Goal 6.3.2 (SDG 6.3.2), which focuses on improving global water quality. Currently, remote sensing technology is widely used for water quality monitoring. Existing water quality-monitoring studies have been conducted based on quantitative water quality inversion. It requires a high degree of the synchronization of the time and location of the collection of station monitoring data and remote sensing data (air–ground spatiotemporal synchronization), which can be resource intensive and time consuming. However, policymakers and the public are more interested in the quality of water (good or poor) than in the specific values of the water quality parameters, as evidenced by the emergence of SDG 6.3.2. In this study, we change the traditional idea of quantitative water quality research, focus on water quality qualitative research combined with the characteristics of water pollution, propose a remote sensing water quality sample enhancement method under the condition of “air–ground spatiotemporal asynchrony”, and construct a remote sensing water quality sample library. On the basis of this sample library, a random forest water quality classification model was constructed to classify water quality qualitatively. We obtained the distribution of good water bodies in Deqing County, China, for example, from 2013 to 2022. The results show that the model has high accuracy (Kappa = 0.6004, OA = 0.8387), and we found that the water quality in Deqing County improved in the order of “major rivers, lakes, and tributaries” during the period from 2013 to 2015. This also verifies the feasibility of using this sample enhancement method to conduct qualitative research on water quality. Based on this water quality classification model, a set of spatial-type evaluation processes of SDG 6.3.2 based on image elements was designed. The evaluation results show that the water quality situation in Deqing County can be divided into two stages: there is a trend of substantial improvement from 2013 (evaluated value of SDG 6.3.2 = 63.25) to 2015 (evaluated value of SDG 6.3.2 = 83.16); and it has remained stable and fluctuating after reaching the good environmental water quality since 2015. This study proposes a simple method for rapidly evaluating SDG 6.3.2 via utilizing easily accessible Landsat 8 and water quality-monitoring data to classify water quality. The method can directly obtain water quality category information without the need for additional sampling, thus saving costs. It is a very simple process that is easy to implement, while also providing a high level of accuracy. This significantly reduces the barriers to evaluating SDG 6.3.2, supports the realization of the sustainable management of water resources globally, and is highly generalizable.

Sandwiched solar interfacial evaporation system: Integrating phase change material/hydrogel/NiCo2O4 nanoflower for superior desalination

Solar-driven interfacial evaporation is a kind of sustainable and eco-friendly method of water treatment to alleviate the global water crisis. Here we demonstrate a novel sandwiched solar interfacial evaporator integrating phase change material (PCM), sodium alginate hydrogel (SA), and NiCo2O4 nanoflower featuring superb evaporation and glorious thermal energy management to achieve efficient energy utilization and long-term evaporation stability. After being combined with filter paper, NiCo2O4 nanoflower composites are adopted as the light absorber on the top layer, which can achieve an absorption of about 96.5 % in the full spectral range. SA hydrogel has been used as an intermediate layer for rapid water supply to the evaporation interface and to prevent salt deposition. Under one sun irradiation (1 kW m−2), the evaporator exhibits a high evaporation rate (1.94 kg m-2h−1) and excellent endurance in the treatment of high salt-concentration water. In particular, benefiting from the rational combination of PCM, the water production reached up to 12.13 kg m−2, which is 2.23 kg m-2higher than that of the evaporator without PCM under natural solar irradiation for 9 h. This work presents a promising concept for maximally utilizing intermittent solar irradiation energy and prolonged salt-free deposition desalination.

Drought Monitoring Using Moderate Resolution Imaging Spectroradiometer-Derived NDVI Anomalies in Northern Algeria from 2011 to 2022

Drought has emerged as a major challenge to global food and water security, and is particularly pronounced for Algeria, which frequently grapples with water shortages. This paper sought to monitor and assess the temporal and spatial distribution of drought severity across northern Algeria (excluding the Sahara) during the growing season from 2011 to 2022, while exploring the relationship between the normalized difference vegetation index (NDVI) anomaly and climate variables (rainfall and temperature). Temporal NDVI data from the Terra moderate resolution imaging spectroradiometer (MODIS) satellite covering the period 2000–2022 and climate data from the European Reanalysis 5th Generation (ERA5) datasets collected during the period 1990–2022 were used. The results showed that a considerable portion of northern Algeria has suffered from droughts of varying degrees of severity during the study period. The years 2022, 2021, 2016, and 2018 were the hardest hit, with 76%, 71%, 66%, and 60% of the area, respectively, experiencing drought conditions. While the relationship between the NDVI anomaly and the climatic factors showed variability across the different years, the steady decrease in vegetation health indicated by the NDVI anomaly corroborates the observed increase in drought intensity during the study period. We conclude that the MODIS-NDVI product offers a cost-efficient approach to monitor drought in data-scarce regions like Algeria, presenting a viable alternative to conventional climate-based drought indices, while serving as an initial step towards formulating drought mitigation plans.

A qualitative risk assessment model for water reuse: Risks related to agricultural irrigation in Brazil

Urbanization and industrialization are increasing extreme weather events, causing water quantity and quality reduction. Global water scarcity impacts 32.5 % of the urban population and is growing. Brazil has also witnessed water scarcity, notably in the southeast (2014–2015) and south (2019–2020), with reservoirs dropping below 20 % capacity. Water reuse is vital for mitigating scarcity, though it presents risks due to contaminants. Risk analysis studies are crucial for evaluating contamination sources, pathways, and exposure scenarios in water reuse practices. Various methodologies, including quantitative, semi-quantitative, and qualitative analyses, can be employed. Given the uncertainty and diverse factors, qualitative methods are recommended for non-potable water reuse risk analysis. This work presents a qualitative risk analysis methodology that allows to evaluate non-potable water reuse categories. It assesses factors affecting human health and the environment, considering exposure scenarios, characteristics of the receptors, and sources of reused water. The risk analysis of water reuse was carried out focusing on agricultural reuse, considering as alternatives the irrigation of soybean and sugarcane crops. By reviewing literature, the probability of occurrence and the magnitude of impact of the risk factors were identified and rated, using an increasing relative numeric scale. This process resulted in an overall risk value for comparing agricultural irrigation alternatives. The obtained results indicate a promising risk analysis model that can be adjusted and applied to various water reuse modalities and key factors. This adaptable risk analysis model is mainly related to water treatment methods, prompting the proposal of risk control measures.

Impact of Drip Irrigation on Crop Growth, Yield, Water Productivity, and Weed Dynamics: A Review

The global water scenario indicates efficient water management practices are required to sustain agricultural productivity. The scarcity of groundwater resources is a global issue that is caused by increasing global population and climate change in the form of global warming. To alleviate the issue, the major water-consuming area implemented drip irrigation projects. It is recognized for its water-saving potential and gained prominence in crop cultivation. This study aimed to investigate the effect of drip irrigation on the growth, yield, water productivity, and weed dynamics of various crops. Results revealed that wheat under drip irrigation exhibited enhanced growth parameters, including increased plant height, leaf area index, and dry matter accumulation attributed to optimized soil moisture content. Drip irrigation significantly improved yield and yield attributes compared to traditional irrigation methods. Importantly, drip irrigation increased water productivity while reducing water use per unit of production. These findings highlight the potential of drip irrigation to reduce water shortages and increase crop output in the current global water context.