Search Results (373)

Biochar is a carbon-rich material produced from biomass pyrolysis whose properties can be tailored for various applications, including soil improvement, water purification, and catalysis. Its light absorption capacity also makes it promising for solar-driven processes like water evaporation. Photothermal membrane distillation (PMD) combines membrane separation with light-induced heating for efficient water purification. Unlike conventional membrane distillation, PMD utilizes light-absorbing materials to enhance vapor pressure and overcome temperature polarization, a common issue in membrane distillation. This study explored the potential of biochars and activated biochars, as filler materials for photothermal membranes, in line with circular economy principles. The mixed matrix membranes were prepared in a single step, via non-solvent induced phase separation starting from a uniform dispersion of the filler in a polyvinylidene fluoride solution. These materials exhibited great heating performance, reaching surface temperature up to 36 °C under a 125 W/m² light source. Increasing the biochar loading up to 15 wt.% resulted in an 85% increase in distillation flux under light irradiation. Full article

In order to investigate the effects of bentonite and glass fiber on the macroscopic mechanical properties and microscopic mechanisms of cement soil in dry environments, a series of laboratory tests were conducted in this study, including drying tests under controlled environments (30 °C, 50% humidity), unconfined compressive strength (UCS) tests, digital image processing technology, and scanning electron microscopy (SEM) analyses. The moisture evaporation law, surface crack development process, UCS variation, and microstructure evolution of cement soil with different mix proportions (bentonite content: 0–9%; glass fiber content: 0–0.5%) were systematically analyzed. The results show that bentonite can significantly enhance the water retention capacity of cement soil, reduce the water evaporation rate, and increase the unconfined compressive strength by filling internal pores to densify the microstructure. Glass fibers form a three-dimensional network structure in the matrix, exerting a bridging effect to inhibit crack initiation and propagation, and optimize the mechanical properties. The unconfined compressive strength increases significantly with an increase in bentonite content (3–9%), and the optimal fiber content for strength improvement is determined as 0.3%. The synergistic effect of bentonite and fibers optimizes the interfacial bonding force between fibers and the matrix, which remarkably improves the anti-cracking performance of cement soil. Specifically, when the bentonite content is 6–9% and the fiber content is 0.3–0.5%, the cement soil maintains complete integrity after drying, with no obvious cracks on the surface. SEM analysis reveals that the addition of bentonite and fibers inhibits the expansion and connection of internal voids, avoiding the cycle of “void enlargement–stress concentration–crack propagation”. This study provides a scientific basis for the engineering application of cement soil in a dry environment. Full article

The Changbai Mountain–Liaodong region is a crucial component of the global black soil belt in Northeast China and a significant national grain production base. However, like many high-latitude agricultural regions worldwide, it faces persistent challenges during the spring sowing period, including low soil temperatures and excessive moisture. Therefore, developing region-specific, effective methods of reducing soil moisture and increasing temperature while improving soil fertility is essential for improving agricultural productivity. To this aim, a field experiment was conducted with two factors: a main plot subjected to ridge tillage (RT) and flat tillage (FT) and subplots with biochar (BC) and straw (ST) amendments. A subplot with no amendment (CK) was used as a control. During maize growth, the daily soil temperature and moisture were monitored, and the soil water evaporation rates and physical structure, as well as the maize yield performance, were evaluated. The results showed that biochar and straw application significantly decreased the soil monthly water content by 1.69–2.22% (p < 0.05) in the surface soil layer (0–15 cm) from May to June, with a more pronounced effect under RT. In contrast, biochar application increased soil moisture and water storage from July to September, indicating that the influence of biochar on soil moisture depends on time and field aging processes. Biochar amendment raised the soil maximum temperature by 0.32–0.79 °C in the top 0–15 cm layer, while straw incorporation decreased the minimum soil temperature by 0.11–0.52 °C. The increase in soil temperature was primarily due to the biochar’s darker color, which facilitated solar radiation absorption, while the decrease in soil temperature was caused by the “Wind Leakage Effect” induced by the large particle size of the straw. Biochar and straw incorporation effectively enhanced maize dry matter accumulation by an average of 15.8% and 8.2%, respectively, and grain yield by 13.0% and 7.8%, respectively. Correlation analysis indicates that these increments are primarily due to enhanced soil moisture and available N content during the middle to late stages of maize growth. Therefore, the integration of straw and biochar with high-ridge cultivation is an effective strategy for excessive moisture reduction and warming in spring soil and it also contributes positively to maize yield. Full article

Xinjiang, a key grain production region in arid Northwest China, faces severe water scarcity and low agricultural water use efficiency. Although subsurface drip irrigation (SDI) has been widely studied for horticultural crops, a comprehensive synthesis focusing on SDI system design, water–fertilizer management, and soil–crop responses in wheat production under arid conditions remains limited. This knowledge gap restricts the development of optimized irrigation strategies for wheat cultivation in Xinjiang, where extreme aridity, widespread oasis agriculture, soil salinization risk, and the dominance of densely planted wheat create management requirements that differ from those of humid regions and horticultural production systems. Therefore, this review summarizes the development of SDI technology, its system design parameters, and integrated water–fertilizer management strategies, while systematically integrating recent advances in soil–crop–microbial interactions and resource use efficiency under arid conditions, which have rarely been synthesized in previous SDI reviews. Synthesizing current knowledge on the impacts of SDI on soil water dynamics, soil properties, microbial communities, crop root architecture, biomass production, and resource use efficiency, this review further discusses general advances in SDI in the context of their relevance to Xinjiang, with particular emphasis on how regional soil–climate conditions and wheat production practices influence system design, fertigation management, and field applicability. Multiple studies indicate that SDI can simultaneously reduce evaporation and deep percolation, mitigate surface salt accumulation, promote deeper root development, and improve crop productivity and resource use efficiency. However, high initial investment and maintenance costs, along with risks of emitter clogging, still hinder its large-scale adoption. For Xinjiang’s wheat and other densely planted crops, future research should prioritize optimizing subsurface drip irrigation (SDI) systems, as studies have shown that SDI can increase water use efficiency (WUE) by 20–30% and enhance crop yield by 10–15%, particularly under water-scarce conditions. The study’s findings are as follows: (1) optimize SDI system parameters for local soil–climate conditions, (2) elucidate the synergistic mechanisms between water–fertilizer coupling and soil–crop systems, and (3) develop cost-effective and durable system components. Importantly, these findings are particularly relevant for Xinjiang, where extreme aridity, soil salinization, and limited water resources require region-specific optimization of SDI systems. These efforts will support efficient and sustainable wheat production in Xinjiang and other arid regions. Full article

Soil salinization represents a growing threat to agricultural productivity, particularly in arid and semi-arid regions where evaporation-driven salt accumulation forms surface crusts that inhibit further moisture transport. This study introduces a novel passive and low-cost remediation strategy consisting of vertically inserted fired-clay ceramic sheets that function as capillary wicks, enabling the simultaneous enhancement of evaporative flux and salt removal from saline-irrigated soils. Controlled laboratory experiments were conducted on soil columns irrigated with saline water (180 and 250 g/L) and equipped with one to four ceramic sheets (porosity = 0.33). Evaporation tests showed that saline soil without inserts lost 34 g of water over 120 h, compared to 47 g with one ceramic sheet and up to 68 g with four sheets. Salt extraction increased similarly, reaching 59% removal with four sheets versus 20% with a single sheet. Most extraction occurred within the first 72 h, after which performance declined due to salt crystallization within ceramic pores. These findings establish that vertically inserted fired-clay ceramics represent a viable, scalable, and low-cost technology for passive soil desalinization, with optimal operational cycles of 72–120 h recommended before periodic sheet replacement. Full article

The prolonged use of traditional polyethylene mulch (PM) films has resulted in significant environmental issues, such as soil residues and white pollution, which pose challenges to sustainable agriculture. The transition from PM to fully biodegradable mulch (BDM) films has emerged as a prominent trend in contemporary farming practices. This study investigates the effects of various colors of biodegradable mulches on watermelon production and quality, with a particular emphasis on BDM in comparison to conventional PM. Within the 0.2–15.3 µm wavelength range, transparent variants demonstrate high light transmission, while the silver–black treatment exhibits greater reflectivity. The silver–black surface effectively reduces evaporation, maintaining soil water content 5–8% higher than that of PM. However, its thermal profile reveals periodic temperature increases similar to those observed with PM. The results indicate that BDM silver–black enhances biomass, root N and P levels, and leaf NPK retention compared to PM. Notably, among the BDM treatments, silver–black yielded the highest average fruit weight and width (7.68 kg, 22.83 cm), although these differences were not statistically significant when compared to PM. Additionally, it produced the highest soluble solids content (13.2 °Brix) at a significance level of p < 0.05 relative to PM. This finding suggests an enhancement in the soil’s capacity to retain moisture and its nutrient availability, thereby fostering plant growth. All treatments proved profitable and economically viable; however, the total inputs and outputs associated with BDM silver–black and CK-PM transparent yielded a satisfactory profit, ranging from $1937 to $2503 per hectare. These results advocate for the utilization of sensor-embedded mulch films and the silver–black color to optimize water and nutrient utilization, thereby promoting sustainable watermelon cultivation. Full article

Against the backdrop of accelerated terrestrial hydrological cycling and the increasing concurrence of drought-heatwave compound extremes under global warming, regional land-atmosphere coupling has emerged as a central mechanism shaping climate feedbacks and trajectories of ecosystem carbon uptake. However, prior studies spanning climatic regimes, observational scales, and data sources have often yielded contradictory conclusions. Here, we challenge these fragmented perspectives by constructing an integrated LST-SM-ET-GPP chain that jointly represents land surface temperature, soil moisture, evapotranspiration, and gross primary productivity, thereby linking water availability, surface energy balance, and plant physiological processes within a unified framework. We synthesize a conceptual diagnostic roadmap for interpreting land-atmosphere coupling across observations and models. When ecosystems operate in humid, energy-limited environments, radiative and advective controls should be prioritized to diagnose system forcing. By contrast, as the system becomes water-depleted, attribution must shift to a nonlinear regime transition framework governed by a critical soil moisture threshold. This threshold mechanism implies that, once the system enters the moisture-limited regime, even modest declines in soil moisture can trigger a rapid weakening of evaporative cooling, substantially amplifying LST anomalies and strongly suppressing GPP. The competitive regulation of stomatal conductance by atmospheric demand (vapor pressure deficit, VPD) and terrestrial supply (rootzone soil moisture) further explains why the “dominant” controlling factor can dynamically reverse across hydrothermal states, timescales, and stages of extreme-event evolution. Notably, the steady-state coupling assumption may break down under flux “flooring” during extreme drought, or when structural buffering such as deep root water uptake is present, delineating strict applicability bounds for existing diagnostic frameworks. Finally, current assessments remain constrained by multiple uncertainties, particularly the lack of ET partitioning constraints, representativeness biases arising from clear-sky observations and sampling-depth limitations, and systematic errors in Earth system model simulations during the warm season. Full article

Soil moisture (SM) in the mountains is critical for agropastoral productivity, and it is subject to both large-scale climate gradients and fine-scale effects of terrain, vegetation and soil. However, how the climate, topography, soil and vegetation factors impact surface SM spatiotemporal dynamics remains elusive in mountainous terrains, due to their complex interactions. Based on multi-source datasets, this study employs the structural equation model to investigate the impact pathways of climate and vegetation factors on annual surface SM dynamics from the year 2000 to 2022 in the Tianshan Mountains of China (TS). We also utilize the factor and interaction detectors of Geographical Detector to explore the individual and interactive effects of climate, topography, soil and vegetation factors on the spatial pattern of the annual surface SM. Moreover, their integrated impacts on the spatiotemporal dynamics of annual surface SM were investigated based on the explanatory power from the factor detector and total effects from structural equation modeling. The results showed that the multi-year average surface SM was 0.21 m³·m⁻³ for the whole region, with greater values in areas with dense vegetation and high elevation. Annual surface SM exhibited significant increasing trends across different land cover classifications and elevation zones, which was directly influenced by vegetation greenness enhancement. Precipitation (PRE) and relative humidity (RH) also significantly influenced the temporal variations in surface SM through their indirect effect on vegetation greenness, while these indirect effects were much lower than the direct effect of vegetation greenness. RH, PRE and surface net solar radiation (SSR) showed strong individual and interactive effects on the spatial distribution of surface SM, particularly the interactive effects of RH and PRE with wind speed (WS). Surface SM was highly sensitive to RH and PRE in the central TS. Overall, vegetation greenness, PRE and RH were the main drivers of surface SM variations across both temporal and spatial scales, while SSR, total evaporation and WS primarily shaped its spatial distribution. These insights enhance our understanding of land–atmosphere interactions in mountainous areas and provide scientific references for sustainable agropastoral water resource management under global warming. Full article

Precise estimation of evapotranspiration (ET) is essential for sustainable water management in arid agroecosystems, particularly for high-water-demand crops such as rice. This study integrated very-high-resolution UAV thermal–multispectral imagery with a Two-Source Energy Balance model (UAV–TSEB) and a field-calibrated AquaCrop model to quantify daily ET and its components under continuous flooding on the arid Peruvian coast during the 2024–2025 season. A network of 24 drainage lysimeters provided an independent observational benchmark (ET_lys); to represent the treatment-level response, lysimeter observations were aggregated as the mean across the 24 units for each UAV campaign. Thirteen UAV surveys supplied radiometric surface temperature and biophysical inputs (e.g., NDVI and fractional cover) to derive spatially explicit ET, while AquaCrop provided continuous daily simulations between flight dates. Direct lysimeter-based validation indicated high agreement for AquaCrop (R² = 0.85; RMSE = 0.26 mm d⁻¹; MBE = 0.01 mm d⁻¹) and moderate agreement for UAV–TSEB (R² = 0.66; RMSE = 0.81 mm d⁻¹; MBE = 1.01 mm d⁻¹). Model intercomparison further showed consistent temporal dynamics of ET (R² = 0.70; RMSE = 1.35 mm d⁻¹) and robust partitioning of crop transpiration (R² = 0.79; RMSE = 0.99 mm d⁻¹) and soil evaporation (R² = 0.76; RMSE = 1.03 mm d⁻¹) while revealing a systematic divergence under near-complete canopy cover: AquaCrop tended to suppress evaporation, whereas UAV–TSEB detected residual evaporation from the flooded surface. Overall, the results highlight the complementarity of both approaches—UAV–TSEB as a spatial diagnostic tool and AquaCrop as a temporally continuous simulator—providing a robust framework for ET monitoring, flux partitioning, and water-use-efficiency assessment in water-scarce rice systems. Full article

The arid region of Northwest China (ARNWC) faces severe desertification, posing a major threat to ecological sustainability and socio-economic development. However, systematic evaluation of desertification across the entire northwestern arid zone remains limited. To address the uncertainty caused by mixed pixels in sparsely vegetated drylands, this study innovatively integrates vegetation and soil indices to develop a robust machine learning-based system for classifying desertification levels in the ARNWC over three decades. In addition, the geographical detector method is employed to quantify the driving factors influencing desertification. The key findings are as follows: (1) Desertification expansion predominantly occurred between 1990 and 1995, followed by a gradual improvement from 1995 to 2020. Transitions between severe and moderate desertification were the most frequent, with approximately 15 × 10⁴ km² shifting from severe to moderate desertification. (2) Physiographic factors were the primary drivers of changes in desertification level, followed by climatic factors. Fractional Vegetation Cover (FVC) had the strongest influence, with an average q-value of 0.72. (3) The explanatory power of the drivers increased significantly through interactions, with the combination of FVC and evaporation (EVA) showing the most pronounced effect. Overall, the methods and findings of this study provide critical insights for targeted desertification control and ecological restoration strategies in arid regions. Although this approach primarily captures desertification symptoms related to surface cover, it offers a valuable long-term perspective on surface cover dynamics. Full article

Precision field measurements were conducted to evaluate the mechanism of organic basin mulching on water and thermal dynamics in arid date palm orchards in central Saudi Arabia. Partly mulched zones (20 m radius) and fully mulched basins were compared with adjacent bare soil using micrometeorological sensors and microlysimeters. In partly mulched areas, soil heat flux (G) decreased by 68.3% while sensible heat flux (H) increased up to 86.9% during late spring, indicating enhanced energy redistribution. Bare soil exhibited slightly negative latent heat flux (λE) in early spring, reflecting vapor adsorption, whereas fully mulched basins substantially reduced evaporation, with Water Conservation Efficiency Index (WCEĪ) values of 0.33 in spring and 0.27 in summer, corresponding to 33% and 27% water savings, respectively. Root-zone thermal moderation, quantified by the Root-Zone Thermal Moderation Index (RTMI), confirmed effective buffering of subsurface temperatures by 6–7 °C across 2–10 cm depths, despite slightly elevated surface temperatures. These results demonstrate that basin mulching stabilizes soil moisture, moderates diurnal thermal fluctuations, and optimizes soil–atmosphere energy partitioning under arid conditions. By integrating direct lysimeter measurements with continuous energy flux observations and index-based analysis, this study provides novel, field-based insights into the dual role of organic mulching in enhancing water conservation and thermal regulation in arid date palm orchards. Full article

How to achieve the goal of water–carbon synergistic optimization in greenhouse crop production under water-saving irrigation strategies constitutes a key pathway for the development of protected agriculture. Our study takes muskmelon and tomato with drip irrigation in greenhouses as an example and establishes different irrigation levels based on cumulative surface evaporation (E_p) from a 20 cm pan. Here, four irrigation amounts (0.6 E_p, 0.8 E_p, 1.0 E_p, and 1.2 E_p) were set for muskmelon, and three irrigation amounts (0.5 E_p, 0.7 E_p, and 0.9 E_p) were set for tomato, and then a two-year fixed-site field experiment was conducted. The growth rates of both crops were significantly higher under full-water-supply treatments (M1.0 and M1.2 for muskmelon, T0.9 for tomato) than under water-deficient treatments (M0.8 and M0.6 for muskmelon, T0.5 for tomato) (p < 0.05) at the flowering stage, while the opposite was true at the harvesting stage. More than 85% of root systems were distributed in the soil layer, ranging from 0 to 40 cm, and the average RLD under M1.0 and T0.9 was significantly higher than that under other treatments by 14.3%~27.6% (p < 0.05). Muskmelon yields at 1.0 E_p were 22.9%~45.7% higher than those at 0.6 E_p and 0.8 E_p, while tomato yields peaked at 0.9 E_p and were 17.0%~19.4% higher than those under the other two treatments. Daily average soil CO₂ emission fluxes of muskmelon under M1.2 were 9.2%~32.2% higher than those of other treatments respectively, and that of tomato under T0.9 was more than 20% higher than under T0.7 and T0.5 treatments, respectively. The WHCNS-Veg model demonstrated excellent performance in simulating SWC, LAI, and soil CO₂ emission fluxes. The RMSE for SWC simulation ranged from 0.013 to 0.022 cm³·cm⁻³, for LAI simulation, it varied from 0.103 to 0.210 cm²·cm⁻², and for soil CO₂ emission flux simulation, it changed from 1.057 to 2.188 kg·hm⁻². It should be noted that the performance was higher under high irrigation levels than under water deficit levels. These results can provide a scientific basis for optimizing greenhouse irrigation schedules and regulating water–carbon synergy under different water resource conditions. Full article

Soil salinization represents a critical constraint to sustainable agriculture in arid and semi-arid regions, where salinity threatens soil productivity, water quality, and ecosystem resilience. Soil salinity pattern prediction is complicated by tightly coupled landscape hydro-climatic processes, wherein the central Sabkha acts as a persistent salt sink, episodic inundation and intense evaporation concentrate dissolved salts, and a shallow saline groundwater table interacts with the semi-arid climate to drive surface salinization. Conventional mapping is laborious and lacks the precision needed to capture the spatio-temporal dynamics of soil salinity across landscapes. This study developed an integrated framework uniting multi-temporal Landsat imagery (2000–2025), hypsometric data, climatic indicators, and in situ soil electrical conductivity (ECe) measurements to model soil salinity dynamics using machine learning (ML), over the Sehb El Masjoune (SEM) semi-arid region, Morocco. A total of 233 soil samples were collected in the investigated area in 2022, 2023, 2024, and 2025 to assess the spatial variability to calibrate and validate modeling findings. To this end, three predictive algorithms, i.e., Gradient-Boosted Trees (GBT), Support Vector Regression (SVR), and Random Forest (RF) were assessed. Our findings showed that SVR achieved the highest predictive capability (R² = 0.76; RMSE = 32.91 dS/m), whereas SVR-based salinity maps revealed a distinct spatial organization of salinization processes, characterized by extremely saline soils (≥64 dS/m) concentrated in the central study area (i.e., SEM center) and a progressive decline toward adjacent agricultural lands (0–8 dS/m). Our results demonstrated that from 2000 to 2025, moderately to highly saline areas (≥16 dS/m) expanded by nearly 10%, driven by recurrent droughts and inefficient drainage. Hydroclimatic analysis confirmed that dry years (SPI: Standardized Precipitation Index ≤ −0.5) promoted net salinity build-up through the expansion and persistence of moderate-to-high salinity classes (≥16 dS/m), whereas wet years (SPI ≥ +0.5) favored temporary leaching and partial recovery, mainly within the low-to-moderate range. This integrative remote sensing–ML approach provides a robust and scalable framework for operational soil salinity monitoring, offering valuable insights for sustainable land-use planning in similar Sabkha’s data-scarce agroecosystems. Full article

Irrigation depth plays a critical role in regulating soil water availability and root water uptake in perennial orchards, yet its mechanistic effects remain poorly understood in subtropical red-soil hilly regions characterized by strong evaporative demand and shallow effective soil water storage. Here, a field experiment was conducted in a citrus orchard with three irrigation depths—shallow (25 cm), intermediate (50 cm), and deep (100 cm)—under a uniform irrigation amount. Soil water dynamics, root traits, and root water uptake sources across a 0–200 cm soil profile were investigated using soil moisture monitoring, root morphological analysis, dual stable isotopes (δ²H and δ¹⁸O), and the MixSIAR Bayesian mixing model. Irrigation depth markedly restructured vertical soil moisture patterns, with the 40–120 cm layer identified as the most responsive zone. Intermediate irrigation maintained the highest and most stable soil water content in this layer, whereas shallow irrigation intensified surface drying and deep irrigation failed to improve water availability within the hydraulically active root zone. Root surface area and dry mass were maximized under intermediate irrigation, indicating enhanced root–soil coupling. Isotopic analysis revealed the strongest evaporative fractionation under shallow irrigation, while intermediate irrigation substantially alleviated surface evaporation. MixSIAR results further showed that shallow irrigation progressively increased reliance on surface soil water (up to 93% in November), whereas intermediate irrigation promoted coordinated uptake from shallow, middle, and deep soil layers, with deep soil water contributing up to 30.7% in November. These results demonstrate that irrigation depth exerts a stronger control over root water uptake strategies by stabilizing water availability within the active root zone and reducing non-productive evaporative losses. Optimizing subsurface irrigation depth therefore represents an effective pathway to improve water-use efficiency in citrus orchards of subtropical hilly regions. Full article

To clarify the effects and mechanisms of the solution formed by mixing flaxseed meal powder with water on soil water movement in sandy land, this study conducted laboratory simulation experiments using three extraction forms of flaxseed meal solution (supernatant, suspension, and precipitate) and five application rates (5 kg·m⁻², 8 kg·m⁻², 11 kg·m⁻², 14 kg·m⁻², and 17 kg·m⁻²), with untreated aeolian sandy soil set as the control (CK). The results showed that: (1) Flaxseed meal can significantly reduce the soil water infiltration rate, with the sediment treatment group exhibiting the optimal effect. After the application of the three flaxseed meal treatments, soil infiltration indices decreased significantly, and the magnitude of the reduction became more pronounced with the increase in flaxseed meal application rate. (2) Flaxseed meal exhibited a significant effect on water retention and evaporation inhibition; after continuous evaporation for 35 days following the spraying of different flaxseed meal treatments, the cumulative evaporation of CK was significantly higher than that of the other treatments. Compared with CK, the cumulative evaporation of the groups treated with the supernatant, suspension, and precipitate of flaxseed meal solution decreased by 11.69%, 24.13%, and 43.22%, respectively. The sediment group achieved the optimal effect, and the evaporation inhibition effect was enhanced with the increase in application rate. (3) All three flaxseed meal mixture treatments increased soil bulk density and decreased soil total porosity, and saturated water-holding capacity and minimum water-holding capacity, with the sediment treatment exerting the most significant effect. The efficacy of all treatments became more notable as the application rate increased. There was a highly significant correlation between soil physical properties and water movement rate. Flaxseed meal affects soil water movement by altering soil physical properties. In conclusion, spraying flaxseed meal on the surface of sandy soil can effectively reduce infiltration and inhibit evaporation, with the sediment treatment group achieving the optimal improvement effect. The soil crust formed by flaxseed meal has a strong water-binding capacity, which can maintain water supply for plant growth over a long period, making it highly suitable for popularization and application in sandy farmland. Full article