Search Results (129)

This study evaluates the economic and agronomic performance of precision maize production under drought-stressed conditions using farm-level operational data from Hungary. A 2024 paired-field case study compared a conventionally managed field (46.65 ha) with a precision-managed field (67.61 ha) using variable-rate fertilization and seeding. Data collected via the John Deere Operations Center enabled 10 × 10 m spatial analysis. Results indicate that despite severe moisture limitations, the precision-managed field achieved a 3.85% higher mean yield (6.47 t ha⁻¹) than the conventional system (6.23 t ha⁻¹). The observed economic advantage was associated with a 5.58% reduction in total production costs through site-specific resource allocation. Consequently, net profit increased by 62.98%, rising from 168.95 USD ha⁻¹ to 275.36 USD ha⁻¹. Spatial analysis demonstrated that precision management synchronized economic outputs with inherent site potential, with management zones accounting for 70.70% of profit variance, compared to 53.3% in the conventional field. Regression models confirmed a tighter alignment between NDVI (Normalized Difference Vegetation Index) and profitability in the precision system. These findings suggest that under spatial heterogeneity and climatic stress, precision agriculture enhances economic resilience by mitigating inefficient expenditures, providing a strategic buffer against input costs and climate volatility. Full article

Beyond its role as a major source of dietary energy, potato (Solanum tuberosum L.) has a substantial contribution to food security. Increasing demand for potato production highlights the necessity of developing efficient and economically sustainable cultivation technologies. This study evaluated the effects of six fertilization systems on tuber yield and economic efficiency, including conventional, intensive conventional, organic, low-rate controlled-release, high-rate controlled-release, and conventional fertilization supplemented with potassium. For the study, two potato genotypes developed in the Potato Research and Development Station with different maturity were used: Secuiana (semi-early) and Redsec (semi-late). The study was performed under the pedoclimatic conditions of Târgu Secuiesc, Romania, during 2023–2025. Highly significant effects (p < 0.001) of year, genotype, fertilization system, and their interactions were observed. Climatic conditions were the primary factor influencing varietal performance, with mean yields ranging from 18.39 t ha⁻¹ during the drought year (2025) to 36.18 t ha⁻¹ in the favorable year (2024). The highest three-year average yield was obtained under the high-rate fertilization system (RV5) in the Redsec genotype (32.33 t ha⁻¹), whereas within the Secuiana genotype, the organic fertilization system (SV4) achieved the greatest economic efficiency by combining relatively high productivity (27.67 t ha⁻¹) with the lowest production costs (EUR 638.7 ha⁻¹) and the highest yield-to-cost ratio. These findings demonstrate that optimized nutrient management can significantly improve potato yield and economic efficiency under variable climatic conditions. Full article

This study addresses the dual challenges of seasonal water scarcity and urban flooding in the Garzan River basin, a region with a semi-arid climate. We propose and analyze an integrated water management system designed to mitigate these risks and promote both ecological and economic sustainability. Our methodology began with a comprehensive analysis of meteorological data from 2000 to 2024, which quantified the significant seasonal irregularity in the annual rainfall regime. The findings revealed that the bulk of the average 800 mm of rainfall occurs between January and May, while the summer months experience near-drought conditions. Based on this, we calculated the potential of various water conservation strategies. The system combines rainwater harvesting from a 1000 m² roof and a 500 m² parking lot, projected to collect 1020 m³ annually, with greywater reclamation and low-flow fixtures, which add a combined 400 m³ of annual savings. The total annual water savings of 1420 m³ were found to provide a gross annual economic benefit of $3550. Considering the installation and maintenance costs, the project’s payback period is estimated to be around 32 years. We also developed an annual precipitation prediction model providing a locally applicable early warning mechanism that forecasts total rainfall based on spring data. The use of proactive hydrometeorological data can improve the feasibility of long-term infrastructure projects to a certain extent. Finally, the proposed system’s design was confirmed to be eligible for multiple LEED certification credits, demonstrating its alignment with international sustainability standards. In conclusion, this research provides a comprehensive and viable solution that addresses local water issues and offers a valuable model for other regions facing similar challenges. Full article

The large-scale integration of renewable energy has significantly improved the low-carbon performance of power systems, but has also increased operational uncertainty. Under extreme weather conditions, wind and solar power may experience consecutive days of simultaneous output shortfalls—referred to as “renewable energy drought”—leading to persistently high net load and severe challenges to supply guarantee. To address this issue, this paper proposes a multi-source coordinated supply-guarantee dispatch strategy for consecutive-day renewable energy drought scenarios. First, net load is defined as the total system load minus the available wind and solar output. Based on magnitude and duration thresholds, renewable energy drought events are extracted from historical data to generate representative scarcity scenarios. Second, a multi-source coordinated optimization dispatch model is constructed, incorporating wind power, solar power, thermal units, battery energy storage, and pumped-storage hydro. The objective is to minimize the total system operating cost, which includes thermal fuel cost, start-up/shut-down costs, storage cycling cost, wind/solar curtailment penalty cost, and load shedding penalty cost. The load shedding penalty coefficient is set to a magnitude much higher than conventional costs to highlight the priority of supply guarantee. The model accounts for operational constraints such as minimum up/down times, deep regulation capability, ramping limits of thermal units, and charge/discharge power limits of storage. Taking a provincial power system in China for the year 2030 as a case study, a dispatch case covering four consecutive days (96 time periods) is designed. Based on a baseline scenario, eight groups of sensitivity analyses are conducted to comprehensively investigate the impacts of key factors on the supply-guarantee strategy, including: the minimum up/down time of thermal units, deep regulation capability, load shedding penalty cost, load level, rated energy capacity and charge/discharge efficiency of battery energy storage, rated energy capacity and pumping/generating efficiency of pumped-storage hydro, thermal fuel cost coefficient, and renewable energy capacity. Simulation results show that the proposed strategy can effectively coordinate multiple resources under consecutive-day drought conditions; reducing the minimum up/down time of thermal units improves supply flexibility but increases start-up/shut-down costs; enhancing deep regulation capability optimizes storage utilization and reduces total system cost; the load shedding penalty cost directly determines the trade-off between supply guarantee and economic efficiency; and as load level decreases by 5%, 10%, and 15%, the total system operating cost reduces by approximately 6.3%, 12.5%, and 18.8%, respectively. This study provides a quantitative method and technical support for supply-guarantee dispatch decisions and resource allocation in high-renewable power systems under persistent drought conditions. Full article

Hydropower-dependent electricity systems, such as Ecuador’s, face critical supply disruptions during droughts: a vulnerability exemplified by the 2024 power outages. This study assesses the technical, economic and environmental feasibility of a 200.84 MWp grid-connected solar photovoltaic (PV) plant proposed for the Pacific Refinery site in Manabi, Ecuador, as a strategy to diversify the energy matrix and reduce hydrological risk. Using site-specific solar resource data (4.65 kWh/m²/day) and PVSyst simulations, the plant achieves an annual energy production of 295 GWh with a performance ratio (PR) of 85.3%. A discounted cash flow analysis over 25 years, assuming a 7% discount rate and an electricity price of 60 USD/MWh, yields a net present value (NPV) of 104.9 MUSD, an internal rate of return (IRR) of 62.2%, and a levelized cost of energy (LCOE) of 14.5 USD/MWh, well below current industrial tariffs in Ecuador. Sensitivity analysis confirms project viability under ±15% variations in investment cost, energy price, and solar resource. Over its lifetime, the plant avoids 1.83 Mt of CO₂ emissions, supporting national decarbonization goals. The results demonstrate that large-scale PV deployment in high-radiation, low-latitude regions can be highly profitable and contribute to energy sovereignty in hydropower-dependent systems. Furthermore, this study provides a replicable model for repurposing unused industrial land for renewable energy generation, offering actionable insights for policymakers and investors in developing economies. Full article

Urban drought pressure is increasing the operational risk and cost of maintaining municipal green infrastructure. Irrigation is still widely managed through fixed routines and fragmented information. To address this challenge, the study develops an integrated operational analysis by combining water consumption records, maintenance data and a GIS inventory for twenty municipal green spaces. System characterisation and performance screening were carried out using hourly meter readings to distinguish typical scheduled irrigation peaks from non-standard consumption patterns. To move from monitoring to control, irrigation needs were estimated using evapotranspiration (ET₀) and a garden-coefficient logic adapted to urban planting conditions and compared with measured consumption. The comparison indicates a potential reduction of 29–61% through improved scheduling and system adjustment. Based on the diagnosis, technical intervention scenarios were defined and assessed using techno-economic metrics, including ground-cover redesign and Mediterranean-adapted planting strategies. To support implementation, options were organised into intervention priorities using a multicriteria tool that balances water savings, costs and feasibility under municipal operations. Coimbra, Portugal is used as a case study, and a pilot application in a city garden, supported by 797 user surveys, clarifies practical constraints for scaling beyond isolated pilots. Turf-free scenarios indicate a 53.4% reduction in water use and a 60.5% reduction in operational costs, with a payback period below three years. The results highlight the potential of data-driven irrigation management to support more resilient, cost-effective and water-efficient municipal green infrastructure across diverse urban contexts. Full article

Water scarcity is becoming an increasingly critical global challenge, driven by climate change, rapid population growth, pollution, and unsustainable water use. Drought further intensifies this crisis by reducing water availability across agricultural, environmental, and socio-economic systems. In this context, nanotechnology has emerged as a promising tool for improving water management and enhancing drought resilience. This review examines the role of nanotechnology in drought mitigation and water conservation through multiple pathways, including the enhancement of plant drought tolerance, improvement in soil water retention, the development of smart irrigation and nano-sensing systems, and the expansion of water resources through purification, desalination, and wastewater reuse. In addition, the broader drought–water nexus is discussed to position nano-enabled approaches within existing water management strategies. While numerous studies report improvements in water-use efficiency, stress tolerance, and treatment performance under controlled conditions, significant limitations remain. These include concerns related to environmental safety, nanotoxicity, scalability, cost, and the gap between laboratory findings and field-level applications. Overall, nanotechnology should be considered a complementary approach rather than a stand-alone solution for addressing water scarcity under drought conditions. Future research should focus on long-term environmental impacts, techno-economic feasibility, and large-scale field validation to support the safe and effective integration of nanotechnology into sustainable water management systems. Full article

Mediterranean water systems face intensifying drought pressure under climate change, yet the long-term macroeconomic consequences of recurrent water restrictions remain largely unquantified at the metropolitan scale. This study estimates the cumulative economic costs of drought-induced water restrictions in the Barcelona Metropolitan Area (AMB) over 2016–2099 using a supply-driven Input–Output (Ghosh) model driven by six hydro-climatic projections. Drought conditions persist in more than half of all simulated months across all climate projections, generating substantial cumulative undiscounted losses of €52–61 billion through repeated restriction episodes rather than isolated extreme events. The present value of total GDP losses ranges between €8.4 and €41.4 billion depending on the discount rate applied (1%, 3% and 5%). Losses concentrate in service sectors due to strong intersectoral propagation effects, despite agriculture exhibiting the highest direct water dependence. The framework provides a transferable approach for assessing long-term climate-driven drought costs in metropolitan urban or regional economies. Full article

Almond (Prunus dulcis (Mill.) D.A. Webb) is one of the most economically important nut crops worldwide, valued for its nutritional properties and adaptability to diverse agroecological environments. This review summarizes current knowledge on almond domestication, genetic diversity, production trends, and improvement strategies, with a focus on drought tolerance under climate change. Archaeobotanical and molecular evidence indicate central Asia and the eastern Mediterranean as key centers of origin, where recurrent introgression from wild Prunus species contributed to the high genetic variability of cultivated almond. Global production trends reveal increasing challenges due to prolonged drought, climate variability, and rising water and energy costs, particularly affecting major producers such as the United States. Mediterranean regions are transitioning from traditional low-density orchards to intensive systems, where cultivar and rootstock choice are crucial for sustainability. Self-fertile and late-blooming cultivars improve yield stability, while interspecific hybrid rootstocks enhance water use efficiency and tolerance to drought and poor soils. Drought stress impacts almond physiology and yield, although moderate deficit irrigation can maintain productivity and improve kernel quality. Future improvement relies on germplasm conservation, marker-assisted selection, and genomic tools to develop climate-resilient cultivars integrated with sustainable water management strategies. Full article

Sustainable land stewardship is increasingly essential in South Africa’s wine-producing regions (WPR), where climate variability, ecological sensitivity, and economic pressures interact to shape vineyard management practices. This study synthesizes data from 107 vineyard websites and 20 in-depth stakeholder interviews to examine how sustainability is conceptualized and practiced across the region. Results show that growers prioritize biodiversity conservation, soil health, and water-efficient management as foundational to long-term resilience, with widespread adoption of practices such as mulching, cover cropping, habitat restoration, and integrated pest management. Website-derived data reveal substantial participation in sustainability certifications, including the Integrated Production of Wine (IPW) program and WWF Conservation Champions, although implementation depth varies among producers. Interviews underscore that climate extremes—particularly drought—have intensified reliance on soil-moisture conservation and adaptive irrigation strategies. Producers also identified escalating input costs, shifting markets, and export barriers as central economic challenges, contributing to diversified business models that include tourism and direct-to-consumer sales. Collectively, these findings demonstrate that sustainable viticulture in South Africa’s WPR is shaped by dynamic interactions between environmental stewardship and economic adaptation. Strengthening collaboration and aligning local practices with global sustainability frameworks can enhance the region’s ecological resilience and support the long-term viability of its wine industry. Full article

The alpine grassland ecosystem in the Source Region of the Yellow River (SRYR) faces the dual pressures of ecological protection and economic development. Its ecological fragility and climate sensitivity make local animal husbandry susceptible to meteorological disasters. To overcome adverse selection and moral hazard in traditional animal husbandry insurance, this study integrates 963 field sampling observation data, over 400 valid herdsmen survey data, and long-term environmental time series variables. A random forest model (R² = 0.59, RMSE = 65.84 g/m², superior to the artificial neural network in this paper) was used to estimate grass yield. Hodrick–Prescott (HP) filtering was used to separate meteorological yield per unit area and derive yield loss rate. A joint distribution model of meteorological indicators and loss rate was constructed using a Copula function to capture tail-dependent structures, providing a basis for determining trigger thresholds and actuarial pricing of pure insurance premiums. The study reveals the transmission mechanism of climate disasters to feeding costs and designs regional drought and snow disaster index insurance. The compensation standard is based on meteorological indicators falling below the trigger threshold and a yield reduction rate greater than 5%. Using 10,000 Monte Carlo simulations, the drought premium rates for zones I-IV are determined to be 2.03–6.03%, and the snow premium rates to be 2.25–5.42%, corresponding to a premium of RMB 5.21–9.61 per mu for drought and RMB 5.78–8.64 per mu for snow. This design reduces basis risk through zoning and composite triggering, providing a scientific tool for climate risk management in alpine grasslands. Full article

The common bean (Phaseolus vulgaris L.) is of great food and economic importance in Brazil, but its productivity is highly affected by water deficit due to its superficial root system and short cycle. With the increase in prolonged droughts, irrigation has become a solution, albeit a costly one, for small farmers. In this scenario, bioinputs, such as Bacillus aryabhattai, represent a sustainable and low-cost strategy to improve crop performance under reduced irrigation conditions. The objective of this study was to evaluate the potential of B. aryabhattai to improve the agronomic performance of the common bean under reduced irrigation levels. A greenhouse experiment was conducted in randomized blocks with a 2 × 4 factorial design (presence/absence of B. aryabhattai and four irrigation levels: 40, 60, 80, and 100% of the ETc). Agronomic and productive variables were evaluated. The results showed better performance at 80 and 100% ETc, achieving 16 and 20 g per plant⁻¹. Inoculation increased water use efficiency by 13% and contributed to higher grain yield. It was concluded that rational irrigation management combined with the use of B. aryabhattai improves agronomic performance and water use efficiency under reduced irrigation levels. Full article

Optimizing public investment in urban green infrastructure under water scarcity is a core challenge in resource economics. Against the backdrop of global climate change—characterized by rising temperatures, increased frequency and intensity of droughts, and altered precipitation patterns—this study addresses the critical knowledge gap in quantifying the economic returns on the physiological adaptations of urban trees, which are central to their value as natural capital. We integrated dual-water isotope (δ²H, δ¹⁸O) and leaf carbon isotope (δ¹³C) analyses to mechanistically decode the water use strategy of Machilus yunnanensis (M. yunnanensis) in drought-prone Kunming, China. The results show strategic seasonal plasticity: a shift from shallow soil water (10–50 cm) in the wet season to deeper soil sources (50–90 cm) and stem reserves in the dry season, coupled with a dynamic, diurnally variable water use efficiency (WUE_13C). We then constructed a transparent economic valuation model translating these traits into three quantifiable benefit streams: (1) operational cost savings (EV₁) from reduced irrigation demand; (2) enhanced marginal productivity of water (EV₂) in ecosystem service generation; and (3) climate resilience value (EV₃) via mitigated mortality risk. Our “Water–Carbon–Economy” nexus framework provides a generalizable methodology for assessing the cost-effectiveness and risk-adjusted returns of urban forest species, demonstrating that tree selection based on such eco-efficient traits is not merely an ecological choice but a sound economic investment, offering direct implications for budget-constrained municipalities seeking to maximize green infrastructure benefits under climate uncertainty. Full article

Probabilistic streamflow models play a pivotal role in quantifying hydrological uncertainty and form the backbone of modern risk management strategies for flood and drought forecasting, water allocation planning, and the design of resilient infrastructure. Unlike deterministic approaches that yield single-point estimates, these models provide a spectrum of possible outcomes, enabling a more realistic assessment of extreme events and supporting informed, sustainable water resource decisions. By explicitly accounting for natural variability and uncertainty, probabilistic models promote transparent, robust, and equitable risk evaluations, helping decision-makers balance economic costs, societal benefits, and environmental protection for long-term sustainability. In this study, we introduce the bounded half-logistic distribution (BHLD), a novel heavy-tailed probability model constructed using the T–Y method for distribution generation, where T denotes a transformer distribution and Y represents a baseline generator. Although the BHLD is conceptually related to the Pareto and log-logistic families, it offers several distinctive advantages for streamflow modeling, including a flexible hazard rate that can be unimodal or monotonically decreasing, a finite lower bound, and closed-form expressions for key risk measures such as Value at Risk (VaR) and Tail Value at Risk (TVaR). The proposed distribution is defined on a lower-bounded domain, allowing it to realistically capture physical constraints inherent in flood processes, while a log-logistic-based tail structure provides the flexibility needed to model extreme hydrological events. Moreover, the BHLD is analytically characterized through a governing differential equation and further examined via its characteristic function and the maximum entropy principle, ensuring stable and efficient parameter estimation. It integrates a half-logistic generator with a log-logistic baseline, yielding a power-law tail decay governed by the parameter $\beta$, which is particularly effective for representing extreme flows. Fundamental properties, including the hazard rate function, moments, and entropy measures, are derived in closed form, and model parameters are estimated using the maximum likelihood method. Applied to four real streamflow data sets, the BHLD demonstrates superior performance over nine competing distributions in goodness-of-fit analyses, with notable improvements in tail representation. The model facilitates accurate computation of hydrological risk metrics such as VaR, TVaR, and tail variance, uncovering pronounced temporal variations in flood risk and establishing the BHLD as a powerful and reliable tool for streamflow modeling under changing environmental conditions. Full article

Maize (Zea mays L.), a vital crop for global food and economic security, faces intensifying biotic and abiotic stresses driven by climate change, including drought, heat, and erratic rainfall. This review synthesizes emerging biotechnology-driven strategies designed to enhance maize resilience under these shifting environmental conditions. We present an integrated framework that encompasses CRISPR/Cas9 and next-generation genome editing, Genomic Selection (GS), Environmental Genomic Selection (EGS), and multi-omics platforms—spanning transcriptomics, proteomics, metabolomics, and epigenomics. These approaches have significantly deepened our understanding of complex stress-adaptive traits and genotype-by-environment interactions, revealing precise targets for breeding climate-resilient cultivars. Furthermore, we highlight enabling technologies such as high-throughput phenotyping, artificial intelligence (AI), and nanoparticle-based gene delivery—including novel in planta and transformation-free protocols—that are accelerating translational breeding. Despite these technical breakthroughs, barriers such as genotype-dependent transformation efficiency, regulatory landscapes, and implementation costs in resource-limited settings remain. Bridging the gap between laboratory innovation and field deployment will require coordinated policy support and global collaboration. By integrating molecular breakthroughs with practical deployment strategies, this review offers a comprehensive roadmap for developing sustainable, climate-resilient maize varieties to meet future agricultural demands. Full article