Water Conservation Research Articles

Pinus densiflora var. ussuriensis Forest Alliance

The Pinus densiflora var. ussuriensis forest is a unique pine forest type in Northeast China. The species grows normally under extremely adverse conditions because it has a strong tolerance to poor soils and drought. It also benefits the ecological environment significantly through water conservation, soil improvement and windbreak and sand fixation, thus making it an important pioneer species for improving site conditions. This paper systematically analyzes the geographical distribution, ecological and community characteristics, species composition and classification of Pinus densiflora var. ussuriensis forests in China through field surveys and literature review. The main findings are: (1) Based on the dominant species of each layer, Pinus densiflora var. ussuriensis forests can be divided into two categories of associations: Pinus densiflora var. ussuriensis - Rhododendron dauricum - Carex callitrichos association and Pinus densiflora var. ussuriensis + Quercus mongolica - Lespedeza bicolor - Carex caespitosa association. (2) According to sample plot surveys, a total of 134 vascular plant species, belonging to 59 families and 104 genera, were recorded in natural Pinus densiflora var. ussuriensis forests. Amongst them were one fern species, two gymnosperm species and 131 angiosperm species. (3) The composition of life forms in Pinus densiflora var. ussuriensis forests is dominated by terrestrial herbs, with fewer woody plants and with vines making up the smallest proportion. (4) The Pinus densiflora var. ussuriensis forests located on the hillocks of Xingkai Lake are in decline. If the soil in this area continues to increase in wetness, this community may eventually evolve into a broad-leaved mixed forest.

Impact of Eco-Friendly Practices on Resort Profitability in the Maldives

Purpose: The aim of the study was to analyze the impact of eco-friendly practices on resort profitability in the Maldives. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Studies on the impact of eco-friendly practices on resort profitability in the Maldives show that sustainable practices, such as renewable energy use, water conservation, and waste reduction, positively affect profitability. Resorts adopting green initiatives benefit from lower operational costs, such as reduced energy and water consumption, while also attracting environmentally conscious tourists willing to pay premium prices. These practices also enhance brand reputation and long-term resilience, reducing dependency on finite resources. However, the initial investment in eco-friendly infrastructure can be high, and profitability gains are more evident in the long term. Unique Contribution to Theory, Practice and Policy: Sustainable tourism theory, corporate social responsibility (CSR) theory, resource-based View (RBV) theory may be used to anchor future studies on the role of technological advancements on customer satisfaction in Japan’s hospitality. Practically, resorts in the Maldives can use this research to improve their profitability while simultaneously enhancing their environmental sustainability. At a policy level, this research can provide empirical evidence for policymakers in the Maldives to promote and regulate eco-friendly practices in the tourism sector.

Single-cell analysis of osmoregulation reveals heterogeneity of aquaporin 4 functionality in human astrocytes.

The water channel aquaporin 4 (AQP4) contributes to water flow and waste removal across the blood-brain barrier and its levels, organization and localization are perturbed in various neurological diseases, including Alzheimer's Disease. This renders AQP4 a potentially valuable therapeutic target. However, most functional assays aimed at identifying modulators of AQP4 function are performed with primary rodent cells and do not consider inter-cellular variations in AQP4 abundance and presentation. To address this, we have established and applied a robust live cell microscopy assay that captures the contribution of AQP4 in the osmotically driven (de-)quenching of the vital dye Calcein-AM with single-cell resolution. Using human astrocytoma cells, we found that performing measurements on cellular regions instead of whole fields of view yielded a more sensitive readout of the osmotic response, which correlated with AQP4 abundance. Stable co-expression of the two major AQP4 isoforms, but not of the individual isoforms, provoked a faster adaptation to osmotic changes, while siRNA-mediated knockdown of AQP4 had the opposite effect. Post-hoc correlation with the canonical membrane marker CD44 revealed that the speed of the osmotic response scaled with AQP4 membrane enrichment. Coating the substrate with laminin promoted AQP4 membrane enrichment, while cell confinement with fixed-size micropatterns further increased the speed of osmoregulation, underscoring the influence of extracellular factors. The osmotic response of primary fetal astrocytes and human iPSC-derived astrocyte models was comparable to AQP4-deficient astrocytoma cells, in line with their low AQP4 levels and indicative of their immature state. In conclusion, a correlative single-cell approach based on the quantification of Calcein-AM quenching capacity, AQP4 abundance and AQP4 membrane enrichment, allows resolving osmoregulation in a more sensitive manner and reveals heterogeneity between and within human astrocyte (-like) cultures, which could prove crucial for future screens aimed at identifying AQP4 modulators.

Quantification of streamflow response to climate change and human activities within upstream mountainous areas of the Daqing River Basin, Northern China

The Daqinghe River Basin is located in the North China Plain. In recent years, however, climate warming, drying, and intense human activities have led to declining ecosystem functions and shrinking wetlands in the region. Understanding streamflow changes in the upstream mountainous areas of the Daqinghe River Basin in this changing environment and identifying the driving factors can provide a scientific basis for water resources management and optimization in these areas. This study focuses on the Beihedian River watershed, the Xidayang Reservoir watershed, and the Wangkuai Reservoir watershed in the upstream mountainous areas of the Daqinghe River. It is based on hydro-meteorological data collected between 1963 and 2019. The methods used in the study include the linear tendency estimation method, the non-parametric Mann-Kendall trend test, the elasticity coefficient method, and hydrological simulation methods. The results of this study suggest that the streamflow, precipitation, and potential evapotranspiration (PET) in the three watersheds showed an overall decreasing trend. The minimum precipitation decrease rate ranged from −1.09 to −0.55 mm/a, and the minimum streamflow decreasing rate at the Beihedian Hydrological Station was −1.32 mm/a, with a minimum range of 0–176.03 mm. Change-point analysis revealed that the streamflow in the Beihedian River and Xidayang Reservoir watersheds experienced a significant change point around 1999, with a significant level of α=0.05. As for the Wangkuai Reservoir watershed, a significant change point was observed around 1980, which is likely attributable to land system reforms and protective forest projects. The attribution analysis which combined both climate change and human activities using the elasticity coefficient method and hydrological simulation methods indicated that climate change contributed an average of 32.93%, 34.50%, and 35.12% to the reduction in streamflow in the three watersheds, respectively. Human activities accounted for an average contribution of 67.07%, 65.50%, and 64.88%, respectively. Water conservancy projects, afforestation, and other human activities were identified as the primary factors contributing to streamflow decreases.

Watershed Grouping Based on Suspended Sediment Yield Using Morphological Criteria: A Comparison of Hierarchical and Nonhierarchical Techniques

ABSTRACTRegional sediment analysis methods have traditionally been used to reliably estimate sediment yield in ungauged watersheds with adequate hydrometric stations. Watershed‐grouping techniques are a suitable approach for estimating sediment load, which can be used to assess erosion processes, and surface water quality, and plan soil and water conservation measures. Additionally, the relationship between sediment yield and watershed characteristics can be used to identify different stages of erosion evolution and prioritize watersheds for conservation efforts. To this end, this study aimed to assess the applicability of various analytical hierarchy process (AHP) methods, including Ward's, Single linkage, and β‐flexible methods, as well as the nonhierarchical fuzzy C‐means (FCM) method in the Gorganroud and Qareh‐Sou watersheds of northern Iran based on hydrological, geological, climatic, physiographical, and land‐use characteristics. Furthermore, the study evaluated clustering methods to determine the optimal number of subwatershed clusters. The AHP methods identified two, three, or four clusters, while the FCM method identified three clusters as the best number of clusters. The results indicated that the FCM method had a well‐regionalized estimation in the study area with the maximum amount of validation indices (The highest Dunn coefficient 0.31–0.65, the lowest TESS 16.62–36.8, and acceptable Pseudo‐F coefficient 8.1–10.4). Notably, the fuzzy clustering methods associated each input sample with two or more clusters, which reduced the uncertainty of sediment yield estimation. The recommended clustering method can be used for regional sediment analysis in ungauged watersheds and evaluated against other hydrological variables in the study area.

Enhancement of Tomato Fruit Quality Through Moderate Water Deficit

In arid areas, water shortage has become a major bottleneck limiting the sustainable development of agriculture, necessitating improved water use efficiency and the full development of innovative water-saving irrigation management technologies to improve quality. In the present study, tomato (Solanum lycopersicum cv. Micro Tom) fruits were used as materials, and different irrigation frequencies were set during the fruit expansion stage. The normal treatment (CK) was irrigated every three days, while the water deficit treatments were irrigated at varying frequencies: once every 4 days (T1), 5 days (T2), 6 days (T3), 7 days (T4), and 8 days (T5). These corresponded to 80%, 70%, 60%, 50%, and 40% of the maximum field moisture capacity (FMC), respectively, with CK maintaining full irrigation at 90% of the maximum FMC. The water deficit treatment T3, with less stress damage to plants and the most significant effect on fruit quality improvement, was selected based on plant growth indices, photosynthetic characteristics, chlorophyll fluorescence parameters, and fruit quality indices, and its effects on carotenoids, glycolic acid fractions, and volatile compounds during tomato fruit ripening were further investigated. The outcome indicated that moderate water deficit significantly increased the carotenoid components of the tomato fruits, and their lycopene, lutein, α-carotene, and β-carotene contents increased by 11.85%, 12.28%, 20.87%, and 63.89%, respectively, compared with the control fruits at the ripening stage. The contents of glucose and fructose increased with the development and ripening of the tomato fruits, and reached their maximum at the ripening stage. Compared to the control treatment, the moderate water deficit treatment significantly increased the glucose and fructose levels during ripening by 86.70% and 19.83%, respectively. Compared to the control conditions, water deficit conditions reduced the sucrose content in the tomato fruits by 27.14%, 18.03%, and 18.42% at the mature green, turning, and ripening stages, respectively. The moderate water deficit treatment significantly increased the contents of tartaric acid, malic acid, shikimic acid, alpha ketoglutaric acid, succinic acid, and ascorbic acid, and decreased the contents of oxalic acid and citric acid compared to the control. The contents of total soluble sugar and total organic acid and the sugar–acid ratio were significantly increased by 48.69%, 3.71%, and 43.09%, respectively, compared with the control at the ripening stage. The moderate water deficit treatment increased the fruit response values to each sensor of the electronic nose, especially W5S, which was increased by 28.40% compared to the control at the ripening stage. In conclusion, during the ripening process of tomato fruit, its nutritional quality and flavor quality contents can be significantly improved under moderate (MD) deficit irrigation treatment. The results of this experiment can lay the foundation for the research on the mechanism of water deficit aiming to promote the quality of tomato fruit, and, at the same time, provide a theoretical basis and reference for tomato water conservation and high-quality cultivation.

Conservation Agriculture and Crop Residue Management

India being a populous country the intensification of the cropping system is mandatory. However, this intensification of the cropping system results in the degradation of soil and other natural resources. Considering this situation, conservation agriculture is the most suitable alternative to achieving sustainable yield and productivity. Conservation agriculture is based on three major principles those are minimum disturbance of soil, crop rotation, and maintenance of crop residue. Crop residue management plays a major role in conservation agriculture as it helps in improving soil productivity, soil organic matter content, soil structure, soil water conservation, air quality, and reduction in soil erosion. India produces 273 Mt of crop residues annually which contain a total of 7.16 Mt of nutrients (N-1.28, P2O5-1.97, K2O-3.91). In modern agriculture, green manure crops like Sesbania and sunhemp increase the quantity and quality of the crop residues in the crop field. Among various residue management practices mulching has been practiced prominently in dry lands as it increases the resource use efficiency. The residue decomposition is affected by various factors like quality of crop residue, edaphic, management, and climatic factors. In modern scientific research crop residues are being used especially for site-specific nutrient management. It is observed in most studies that zero tillage or reduced tillage with crop residue gives comparatively higher net returns, water use efficiency, and resource use efficiency than conventional agriculture. In Indian context. The management of rice residue particularly in the Indo-Gangetic Plains of India is challenging, where the rice-wheat cropping system is intensively followed and the farmers are more anxious about timely seeding of wheat in combine harvested paddy fields (Sidhu et al., 2007; Singh et al., 2020).

Smart agriculture as source of sustainability in intensive greenhouse production

Abstract The article addresses the interaction between smart agriculture and sustainability within the specific context of intensive greenhouse agriculture in southeast Spain. Combining a literature review and expert interviews, the methodology is based on a qualitative data analysis, whose main goal is to gain a comprehensive understanding of the phenomenon under study. The results identify three key areas of technology that strongly influence this type of agriculture. The first relates to soil, water savings, sensor utilization, and environmental improvement, while the second encompasses robot use, labor reduction, resulting cost improvement, and economic sustainability. Finally, the third group, albeit of lesser importance, links artificial intelligence with ethical issues such as data control, usage, and technological dependence. In summary, the application of smart agriculture is projected to have positive impacts on economic and environmental sustainability, relegating the social dimension to a more distant level. This imbalance suggests that social and ethical aspects could be subordinated to more immediate benefits. The results also suggest that the need for future investments could create polarization in the sector. Not all farmers and businesses can afford these investments, leading to progressive deterioration and even abandonment of agricultural activities in some cases.

Vetiver [Chrysopogon zizanioides (L.) Roberty]: An Aromatic Root Crop for Soil and Water Conservation

Khus grass or vetiver (Chrysopogon zizanioides (L.) Roberty) is a hardy perennial aromatic grass with long enormous tufted fibrous root system. Commercially, dry roots are used for extraction of essential oil that acts as a fixative in perfumery industry worldwide. Besides, vetiver roots are used in medicinal and pharmaceutical industries to treat rheumatism, arthritis, gouty joints, paralysis and indigestion. Roots and root oil have strong anti-oxidant, stimulant, carminative and cooling properties and used in Ayurvedic medicines. Traditionally, vetiver plants are being used to cultivate across hill slopes, waterways and wastelands to reduce runoff and soil conservation. During 1990’s World bank was promoting use of vetiver grass as contour vegetative barrier in upland farming systems of Asian and African countries. Further, recent studies report the use of vetiver in phytoremediation, reclamation of mined lands and soil and water detoxification in addition to carbon sequestration. Due to introduction of modern cultivation practices, traditional soil conservation practices are being vanished gradually over a period of time. In this regard, an attempt has been made to review the scientific evidence for use of vetiver grass as a soil and water conservation measure along with phytoremediation.

Structural Health Monitoring and Failure Analysis of Large-Scale Hydro-Steel Structures, Based on Multi-Sensor Information Fusion

Large-scale hydro-steel structures (LS-HSSs) are vital to hydraulic engineering, supporting critical functions such as water resource management, flood control, power generation, and navigation. However, due to prolonged exposure to severe environmental conditions and complex operational loads, these structures progressively degrade, posing increased risks over time. The absence of effective structural health monitoring (SHM) systems exacerbates these risks, as undetected damage and wear can compromise safety. This paper presents an advanced SHM framework designed to enhance the real-time monitoring and safety evaluation of LS-HSSs. The framework integrates the finite element method (FEM), multi-sensor data fusion, and Internet of Things (IoT) technologies into a closed-loop system for real-time perception, analysis, decision-making, and optimization. The system was deployed and validated at the Luhun Reservoir spillway, where it demonstrated stable and reliable performance for real-time anomaly detection and decision-making. Monitoring results over time were consistent, with stress values remaining below allowable thresholds and meeting safety standards. Specifically, stress monitoring during radial gate operations (with a current water level of 1.4 m) indicated that the dynamic stress values induced by flow vibrations at various points increased by approximately 2 MPa, with no significant impact loads. Moreover, the vibration amplitude during gate operation was below 0.03 mm, confirming the absence of critical structural damage and deformation. These results underscore the SHM system’s capacity to enhance operational safety and maintenance efficiency, highlighting its potential for broader application across water conservancy infrastructure.

Using computational fluid dynamics and deep learning for leak detection and localization in a smart water management system

Water leakages in distribution systems offer significant challenges, resulting in water loss, infrastructure damage, and environmental hazards. As urban populations grow and water resources become scarcer, water management systems’ efficiency becomes increasingly important. Traditional leak detection methods are inadequate and labour-intensive, making them unsuitable for large-scale infrastructure. In addition, limitations in the data representing pipes of varying diameters and materials under various leak scenarios leads to complexity in automatic water leak detection and localization. In response to this challenge, this research effort combines Computational Fluid Dynamics (CFD) and Deep Learning (DL) to enhance leak detection and localization. The study simulates water flow in pipes of varying diameters and materials under various leak scenarios using CFD. Consequentially deep learning models like the Bi-Layered ReLU Encoder + Softmax and Tri-Layered ReLU Encoder + Softmax are trained and tested. The results indicate improvements in detection accuracy by 2.4% and localization by 5.6%, highlighting the potential of this hybrid approach to enhance the reliability and efficiency of water management systems, ultimately promoting water conservation and reducing infrastructure damage.

Biophysical and socioeconomic characterization of Agewmariam experimental watershed in Northern Ethiopia: insights and management options.

Watershed characterization is essential for sustainable watershed management and effective resource utilization, particularly in assessing changes resulting from interventions. This study investigates the biophysical and socio-economic conditions of the Agewmariam watershed, aiming to develop land capability and suitability maps while identifying viable management options. Biophysical data, including land slope, soil properties, erosion severity, stoniness/rockiness cover, and vegetation cover, were collected through field surveys and analyzed using overlay analysis in ArcGIS. Socio-economic data, encompassing population demographics, income, and expenditure, were gathered via individual interviews, complete census, and focus group discussions and summarized using descriptive statistics. The study identified 259 households with an average family size of 4 and a demographic dependency ratio of 96.6%. The major sources of income are crop production and livestock rearing supplemented by casual labor and food aid. The average farmland holding size is 0.5ha, with sorghum, barley, teff, and wheat as the dominant crops. The watershed is characterized by six land capability classes (classes II, III, IV, VI, VII, and VIII). The suitability analysis indicated that the watershed is not currently suitable for wheat and teff crops unless physical, chemical, and biological management improvements are implemented. The study revealed that the major limiting factors for land capability and suitability were slope, erosion severity, stoniness, soil organic matter, and soil texture. The socio-economic characterization enhanced awareness about the local socio-economic condition, informing appropriate planning and management strategies. The study recommends intensive soil and water conservation intervention, afforestation on hillsides, changing the land use system, and the addition of organic matter and fertilizers to enhance land capability and suitability for sustainable agricultural practices.

Environmental impacts of floating solar panels on freshwater systems and their techno-ecological synergies

Abstract Renewable energy sources, such as floating photovoltaic systems (FPVs), are crucial to mitigating the climate crisis. FPV deployments on freshwater bodies are rapidly growing, as they avert land-use change, operate with increased efficiency, and potentially improve water availability by reducing evaporation and the frequency of algal blooms. However, understanding of the ecological consequences for water bodies is very limited despite the variable and far-reaching range of potential impacts. Here, we bring novel insight by combining an established theoretical approach – techno-ecological synergies (TES) - with robust understanding of water body functioning, to direct sustainable FPV deployments. Specifically, we show the potential to integrate consideration of both energy and ecological systems for FPV deployment decisions based on current evidence and fundamental understanding of freshwater body states and processes. Based on 422 pieces of evidence from a systematic review of known physical (n=283), chemical (n=96) and biological (n=43) effects of FPV on freshwater systems, we outline eight potential TES that could be realised through FPV location, design, and operation decisions. There was most evidence (n=114) for the Water Use Efficiency TES, which all reported decreased evaporation rates, or increased water savings, due to panel shading. We highlight a lack of understanding of chemical and biological effects of FPV on hosting water bodies, as well as a need for comprehensive studies in which physical, chemical, and biological aspects of water body dynamics are integrated. Finally, we detail research priorities to ensure future FPV deployments bring benefit for both energy and water bodies. Ultimately, integrated energy and water body system knowledge, FPV deployments could mitigate both the climate and ecological emergencies, with notable benefits for society.

Towards Achieving Circular Economy in the Production of Silica from Rice Husk as a Sustainable Adsorbent

The growing concern over water pollution and waste management requires innovative solutions that promote resource efficiency within a circular economy. This study aims to utilize rice husk (RH) as a sustainable feedstock to develop highly porous silica particles and generate valuable by-products, addressing the dual challenges of waste reduction and water contamination. We hypothesize that optimizing the production of amorphous silica from acid-washed RH will enhance its adsorptive properties and facilitate the concurrent generation of bio-oil and syngas. Amorphous silica particles were extracted from acid-washed RH with a yield of 15 wt% using a combination of acid washing at 100 °C, pyrolysis at 500 °C, and calcination at 700 °C with controlled heating at 2 °C/min. The optimized material (RH2-SiO2), composed of small (60–200 nm) and large (50–200 µm) particles, had a specific surface area of 320 m2/g, with funnel-shaped pores with diameters from 17 nm to 4 nm and showed a maximum cadmium adsorption capacity of 407 mg Cd/g SiO2. Additionally, the pyrolysis process yielded CO-rich syngas and bio-oil with an elevated phenolic content, demonstrating a higher bio-oil yield and reduced gas production compared to untreated RH. Some limitations were identified, including the need for bio-oil upgrading, further research into the application of RH2-SiO2 for wastewater treatment, and the scaling-up of adsorbent production. Despite the challenges, these results contribute to the development of a promising adsorbent for water pollution control while enhancing the value of agricultural waste and moving closer to a circular economy model.

Intercropping increases plant water availability and water use efficiency: A synthesis

Intercropping, involving the incorporation of annual crops with alternative crops or non-crop cash crops, has the potential to enhance water conservation and stabilize agroecosystems. However, few studies have comprehensively explored the effects of intercropping on water cycling. Here, we investigated the impacts of intercropping on five crucial water cycle processes (states): soil water content (SWC), runoff (RO), soil evaporation (E), leaf transpiration (LT), and water use efficiency (WUE). To this end, a meta-analysis was carried out utilizing a global dataset comprising 1285 paired observations from 64 publications. We found that intercropping reduced SWC (1.31 %), RO (29.17 %), and E (10.30 %), but increased LT (9.85 %) and WUE (29.46 %). The effects of intercropping on SWC, E, and RO did not exhibit significant fluctuations over the course of a year, but SWC initially decreased then increased in multi-year planting durations. Moreover, the intercropping effect was contingent upon climatic conditions (mean annual precipitation and temperature), soil characteristics (organic matter content, bulk density, and total nitrogen content), and agricultural practices (crop type, fertilization, and irrigation). We determined that resource complementarity, abiotic facilitation, and biotic feedback mechanisms may underlie the effect of intercropping on the water cycle. This research underscores the potential of using intercropping to improve plant water usage and the sustainability and productivity of cropping systems.

Estimation of Monthly Irrigation Water Requirement of Crops Using CROPWAT

Water is increasingly becoming a limited resource due to rising demands for various uses, including hydropower generation, irrigation, and domestic supply. As the population grows, the need for water across different sectors constantly increases. However, the availability of water resources is restricted both spatially and temporally. Therefore, there is an urgent need for systematic and scientific planning to ensure its optimal use. Agriculture sector being the major consumer of water resources, the adoption of modern irrigation techniques can significantly reduce water consumption and promote water conservation. This advancement will expand the irrigated areas and ultimately lead to increased agricultural productivity. Irrigation water requirements of major crops, namely, Paddy, maize, sugarcane etc. are determined using the CROPWAT model. The present study aimed to find out the irrigation water requirement for the major crops grown in Krishna Central Delta, Andhra Pradesh. Results revealed that irrigation water requirement for kharif season ranges from 89-475 mm and in rabi season varies from 320-821 mm. For sugarcane irrigation water requirement was found to be 927 mm.

Dynamic evolution trend and driving mechanisms of water conservation in the Yellow River Basin, China

Water conservation (WC) is a critical ecological service function in the Yellow River Basin (YRB). There is currently a lack of detailed exploration of WC development processes and the impact mechanisms of driving factors at spatiotemporal scales in the YRB. By collecting data on DEM, land use, soil, meteorology, reservoirs, and observed discharge, this study established a large-scale WC model using the soil and water assessment tool (SWAT). The abrupt change test, empirical orthogonal function (EOF), wavelet analysis, hierarchical partitioning analysis (HPA), geodetectors, and aridity index were employed to analyze the multi-spatiotemporal characteristics and driving forces of WC calculated using the water balance method. The results are as follows: (1) The average WC among the YRB was 9.11 mm (74.68 × 108 m3) from 1960 to 2020. Pasture and forests contributed to 48.65% and 22.05% of the average annual WC, respectively. (2) WC exhibited four forms: less/more in the YRB, more in the southeast (northwest), and less in the northwest (southeast). (3) Forests and pastures in land use had higher average WC capacity, while Gansu, Shaanxi, and Qinghai ranked in the top three for average WC among the nine provinces. (4) Precipitation was the major driving force affecting WC variations, with the interaction between precipitation and actual evapotranspiration being the most significant. (5) Drought was a significant cause of negative WC. Protecting and managing crucial WC areas was essential for improving the ecological environment. This research elucidates the driving forces of WC in the YRB, providing scientific support for improving regional WC and promoting sustainable development.

Digital twin water conservancy early warning system based on physical level and numerical simulation in intelligent water conservancy construction

Abstract. In 2023, the Central Committee of the Communist Party of China and The State Council issued the Overall Layout Plan for the Construction of Digital China, emphasizing the construction of a smart water conservancy system with digital twin basins as the core. The Guangxi Zhuang Autonomous Region government has clearly proposed to actively build a "digital twin Pinglu Canal", and attaches great importance to the construction of digital twin platform application services during the construction of the Western land-Sea New Passage (Pinglu) canal. Aiming at the problems such as unsatisfactory early warning effect, inaccurate data and imprecise model of existing smart water conservancy technology, this paper proposes a digital twin system for disaster early warning based on physical level and numerical simulation technology, establishes a visual digital water conservancy model and digital twin smart water conservancy cloud platform, and combines multi-physics field and multi-dimensional coupling algorithm to respond to technical pain points. To achieve scientific and accurate monitoring and intelligent management, and contribute to the construction of digitally empowered Pinglu Canal.

Nitrogen cycling and associated grey water footprint in croplands under different irrigation practices

The pervasive application of nitrogen (N) fertilisers in agriculture poses a significant threat to freshwater ecosystems. The grey water footprint (GWF) is a measure of the volume of freshwater required to assimilate the relative water pollutants resulted from N leaching-runoff processes. The responses of N cycling and associated regional GWF to crop production under different irrigation methods have not been investigated. In this study, the N leaching-runoff rate, N₂O, and NH₃ emissions in croplands and the associated GWF per unit crop yield (UGWF) and annual total GWF (TGWF) of winter wheat-summer maize crop rotations across the Hebei, Shandong, and Henan Region (HSHR) of China were simulated and evaluated at the prefecture level over the 2004–2020 period. Four irrigation scenarios were modelled: furrow, sprinkler, surface drip, and subsurface drip irrigation. The results showed significant spatial and temporal heterogeneity in N leaching-runoff rates and emissions of N2O, and NH3. The N leaching-runoff rates for winter wheat and summer maize ranged from 3.9% to 10.9% and 15.0%–32.3%, respectively. With changing different irrigation methods, N leaching-runoff rates exhibited greater sensitivity than N₂O and NH₃ emissions; this sensitivity was more pronounced in winter wheat than in summer maize. Findings reveal that N pollution is influenced not only by irrigation methods but also by weather conditions, crop-specific rooting characteristics, sowing time, and soil texture. Winter wheat UGWF under the four irrigation methods mostly followed the order of furrow > sprinkler irrigation > surface drip irrigation > subsurface drip irrigation. Conversely, for summer maize, subsurface drip irrigation resulted in a higher UGWF compared to furrow irrigation, mainly due to increased water percolation thus higher N leaching-runoff rate in near-saturated soil with higher rainfall. This result reveals the potential conflict between water-saving irrigation and N pollution control. This analysis underscores the necessity of recognising the combined effects of agricultural management practices on water conservation and environmental safeguarding.

Soil erosion assessment for prioritizing soil and water conservation interventions in Gotu watershed, Northeastern Ethiopia.

Soil erosion by water is a serious problem in Ethiopia, contributing to diminishing crop yields and food shortages. Apart from understanding the magnitude, risk, and spatial distribution of the problem, identifying erosion hotspot areas is essential for effectively reversing the problem. This study aims to identify erosion hotspots in the Gotu watershed, in northeastern Ethiopia, using the revised universal soil loss equation (RUSLE) and incorporating local farmers' perspectives to prioritize conservation efforts. The RUSLE model reveals that 29,744.3 metric tons of soil is lost annually from the Gotu watershed, with an average loss of 65.3 to t ha⁻1year⁻1. The main contributing factors to soil erosion in the watershed include undulating topography, loss of plant cover, and continuous cultivation. The highest soil loss rates (> 80 t ha⁻1year⁻1) were found in the western, northern, and southern parts of the watershed, where cultivation occurs on moderate to steep slopes with sparse vegetation cover. These areas should be prioritized for conservation interventions. Farmers identified poor crop yields and damaged conservation structures as key indicators of soil erosion prevalence in the watershed. Increasing farmer's understanding of soil erosion and the importance of soil and water conservation is essential for effectively controlling soil erosion and improving food security in the area.