Seasonal freeze-thaw processes affect soil water migration and distribution, especially in semi-arid agricultural areas. These processes play an important role in mitigating harsh environmental ...conditions and wind erosion. Soil water content (SWC) and soil temperature (ST) were monitored at different depths (0–2 m) and investigated under freeze-thaw conditions from November 2018 to May 2019 in a semi-arid agro-pastoral region of northern China. The initial SWC was the main factor that affected the freeze-thaw process. During the freeze-thaw process, differences in soil thermal conductivity caused the soil to thaw faster than the freezing process, and the upper soil layer (0–60 cm) was significantly affected by temperature changes. Changes in the potential energy of water and pore pressure gradient caused the migration of soil water to the upper layer, which led to a slight decrease in SWC in each layer before ST dropped to the freezing point. The vertical migration distance of soil water exceeded 70 cm, and the SWC above a depth of 100 cm increased significantly, as water was mainly obtained from the soil layer below a depth of 200 cm. Soil compaction was reduced when affected by freeze-thaw processes and the soil particles were more fragmented, leading to wind erosion and dust events. Our results partially explain the occurrence of wind erosion in spring and provide a scientific basis for predicting soil water status and appropriate farmland management strategies.
•Soil water content and soil temperature dynamic were quantified in farmland area.•Vertical migration distance of soil water exceeded 70 cm.•The initial SWC was the main factor that affected the freeze-thaw process.•Seasonal freeze-thaw processes will increase soil erodibility.
•Soil water content (SWC) is a key factor in wheat grain yield production in drylands.•We used Crop RS-Met model to find SWC-yield relations in 8 dryland wheat fields.•Water use patterns were ...accurately modeled by Crop RS-Met along the growing season.•Modeled SWC at heading was positively and significantly correlated to wheat grain yield.•Crop RS-Met may be used for grain yield predictions, aiding in resource decision making.
Wheat production in drylands is determined greatly by the available water at the critical growth stages. In dry years, farmers usually face the dilemma of whether to harvest at an early stage for hay or silage, with reduced profit, or leave the crop for grain production with the risk of a major economic loss. Thus, an early prediction of potential wheat grain yield production is essential for agricultural decision making, particularly in water-limited areas.
Here, we test whether using a proximal-based biophysical model of actual evapotranspiration (water use) and root-zone soil water content (SWC) – Crop RS-Met – may assist in providing early grain yield predictions in dryland wheat fields. Crop RS-Met was examined in eight experimental fields comprising a variety of spring wheat (Triticum aestivum L.) cultivars exposed to different treatments and amounts of water supply (185 mm - 450 mm). Crop RS-Met was first validated against SWC measurements at the root-zone profile. Then, modeled SWC at heading (SWCHeading) was regressed against end-of-season grain yields (GYEOS), which ranged from 1.30 tons ha−1 to 7.12 tons ha−1, for a total of 56 treatment blocks in 4 seasonal years (2014–2017).
Results show that Crop RS-Met accurately reproduce seasonal changes in SWC with an average R2 of 0.89 ± 0.05 and RMSE and bias of 0.014 ± 0.004 m3 m−3 and -0.002 ± 0.004 m3 m−3, respectively. Modeled SWCHeading showed high and significant positive linear relationship with GYEOS (GYEOStons ha-1 = 0.080×SWCHeadingmm - 5.387; R2 = 0.90; P < 0.001; N=56). Moreover, Crop RS-Met showed to be capable of accurately predicting GYEOS even in cases where water supply and grain yield had adverse relationships. Aggregating results to the field-scale level and classifying fields per water supply conditions resulted in an even stronger linear relationship (R2 = 0.94; P < 0.001; N=9). We conclude that Crop RS-Met may be used to predict GYEOS at heading in dryland fields for possible use by farmers in decision making at critical wheat growth stages.
After massive afforestation, the Loess Plateau is facing the severe challenge of water shortages. Water use efficiency (WUE) is an important indicator of plant drought resistance, and high WUE is an ...important way to reconcile the contradiction between vegetation growth and soil water consumption (SWC). Different vegetation types significantly influence hydrological cycle process and WUE. In this study, the Biome-BGC model was used to simulate and analyze the soil water storage (SWS), SWC, and WUE of 3 typical vegetation types in the Loess Plateau from 2005 to 2020. The results showed that the order of SWS of different vegetation types from largest to smallest was grassland (GL, 81.82 mm/day), abandoned farmland (AF, 66.92 mm/day), and Robinia pseudoacacia forest (RP, 55.64 mm/day); SWC was RP (480.09 mm/year), GL (464.68 mm/year), and AF (421.79 mm/year); WUE was RP (2.37 gC/kgH2O), GL (1.10 gC/kgH2O), and AF (0.60 gC/kgH2O). GL showed a better water retention capacity. Precipitation recharge did not meet the full SWC of vegetation. In years of high vegetation growth, as well as in the dry season when water was scarce, both RP and GL showed varying degrees of water deficit. Correlation analysis revealed that a positive effect of precipitation on WUE has a threshold effect, and the thresholds range from approximately 15–50 mm/day for RP, 15–25 mm/day for GL, and no clear pattern for AF. Overall, in water-stressed areas, a large expansion of forest land should be reduced and GL should be increased. In seasons and areas where vegetation is growing vigorously or extremely arid, irrigation regarding precipitation thresholds should be carried out to improve the WUE of vegetation and promote the sustainable development of regional ecology.
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•The multiyear simulations provide information on the expected loads of future vegetation water use.•The water deficit judgment of different vegetation types can guide the optimization of vegetation management in arid areas.•The positive influence of precipitation on WUE has a threshold effect. RP is 15-50 mm/day, GL is 15-25 mm/day.
Ecosystem water use efficiency (WUE) is an indicator of carbon-water interactions and is defined as the ratio of gross primary productivity (GPP) to evapotranspiration (ET). However, it is currently ...unclear how WUE responds to atmospheric and soil drought events in terrestrial ecosystems with different dryness conditions. Additionally, the contributions of GPP and ET to the WUE response remain poorly understood. Based on measurements from 26 flux tower sites distributed worldwide, the binning method and random forest model were employed to separate the sensitivities of daily ecosystem WUE, GPP, and ET to vapor pressure deficit (VPD) and soil water content (SWC) under different dryness conditions (dryness index = potential evapotranspiration/precipitation, DI). Results showed that the sensitivity of WUE to VPD was negative at humid sites (DI < 1), while the sensitivity of WUE to SWC was positive at arid sites (DI > 2). Furthermore, the contribution of GPP to VPD-induced WUE variability was 63 % at humid sites, and the contribution of ET to SWC-induced WUE variability was 68 % when SWC was less than the 60th percentile at arid sites. Consequently, one increasing VPD-induced decrease in GPP was generally linked to a decrease in WUE at humid sites, and one drying soil moisture-caused decrease in ET was linked to a WUE increase under low SWC conditions at arid sites. Finally, VPD had a stronger effect on WUE than SWC when VPD was less than the 90th percentile or SWC was greater than the 50th percentile. Our findings underscore the importance of considering ecosystem dryness when investigating the impacts of VPD and SWC on ecosystem carbon-water coupling.
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•The sensitivity of GPP to VPD is higher than the sensitivity of ET to VPD at humid sites.•A rise in VPD causes lower GPP and WUE at humid sites.•The sensitivity of ET to SWC is higher than the sensitivity of GPP to SWC at arid sites.•A drop in SWC causes lower ET and higher WUE under low SWC conditions at arid sites.
The Ethiopian government has exerted efforts to rehabilitate degraded agricultural lands using a range of sustainable land management (SLM) initiatives to enhance agricultural productivity. One of ...the key components was improved structural soil and water conservation (SWC) technologies. This study examines the effects of continuous SLM practices on agricultural land productivity, with particular emphasis on SWC technology adoption in Central Ethiopia. The analysis was based on the data collected from 525 sample household surveys in two districts, namely Kewet and Sebeta-hawas. A propensity score matching (PSM) model was used to investigate the effects on treated and non-treated plots. The study findings revealed a substantial and positive effect on treated agricultural plots compared to non-treated ones in the Kewet district. At the same time, the difference was found positive but not significant in the Sebeta-hawas counterpart. The insignificant impacts are justified because SWC efforts focused on constructing structures rather than tailoring them with soil-replenishment and productivity enhancement functions. The important conclusion is that continuous SWC adoption efforts positively impact agricultural productivity; however, its effect is more noticeable when SWC structures are integrated with productivity enhancement functions and applied in low moisture areas. Thus, policymakers and project planners should consider the role of integrating physical SWC structures with soil replenishment and agronomic activities.
The Smart Contract Weakness Classification Registry (SWC Registry) is a widely recognized list of smart contract weaknesses specific to the Ethereum platform. Despite the SWC Registry not being ...updated with new entries since 2020, the sustained development of smart contract analysis tools for detecting SWC-listed weaknesses highlights their ongoing significance in the field. However, evaluating these tools has proven challenging due to the absence of a large, unbiased, real-world dataset. To address this problem, we aim to build a large-scale SWC weakness dataset from real-world DApp projects. We recruited 22 participants and spent 44 person-months analyzing 1,199 open-source audit reports from 29 security teams. In total, we identified 9,154 weaknesses and developed two distinct datasets, i.e., DAppSCAN-Source and DAppSCAN-Bytecode . The DAppSCAN-Source dataset comprises 39,904 Solidity files, featuring 1,618 SWC weaknesses sourced from 682 real-world DApp projects. However, the Solidity files in this dataset may not be directly compilable for further analysis. To facilitate automated analysis, we developed a tool capable of automatically identifying dependency relationships within DApp projects and completing missing public libraries. Using this tool, we created DAppSCAN-Bytecode dataset, which consists of 6,665 compiled smart contract with 888 SWC weaknesses. Based on DAppSCAN-Bytecode , we conducted an empirical study to evaluate the performance of state-of-the-art smart contract weakness detection tools. The evaluation results revealed sub-par performance for these tools in terms of both effectiveness and success detection rate, indicating that future development should prioritize real-world datasets over simplistic toy contracts.
The adoption of soil and water conservation (SWC) technology is a key strategy for reducing global land degradation and improving agricultural productivity. This study uses survey data from ...households in the Loess Plateau in 2017 to evaluate the impact of social interaction on the decision-making process of SWC adoption by farmers. It measures the mediating effect of information acquisition and the moderating effect of internet use and deploys the probit model, general decomposition (KHB) model, and moderated effect model for analysis. The study found that the level of SWC adoption by farmers in the Loess Plateau of China remains relatively low, with only 57.3% of farmers adopting SWC, whereas social interaction increases the possibility of farmers adopting SWC by 10.0%. Accordingly, the paper argues that social interaction can encourage farmers to adopt SWC by improving their ability to acquire information, while internet use can positively moderate the impact of social interaction on farmers' adoption of SWC. Furthermore, the study found the positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies. Therefore, the research results provide a new perspective for promoting SWC in China, emphasizing the importance of enhancing social interaction improving farmers' ability to acquire information, and accelerating internet use.
•Social interaction plays a crucial role in promoting SWC adoption.•Improving farmers' ability to acquire information can promote SWC adoption.•Internet use can moderate the impact of social interaction on SWC adoption.
In the spring of 2022, an excessive amount of rainfall fell in Southwest China (SWC) under the background of frequent droughts in history. This extreme event occurred in the decaying phase of a La ...Niña event, and thus, presumably La Niña played a role in this extreme event. Based on observational diagnoses and model forecasts, the atmospheric circulation anomalies, contributions of remote forcing, and the predictability of this event were examined in this work. It is suggested that La Niña and the Tibetan Plateau upper-tropospheric warming are two major factors leading to the extreme event. In addition to the recognized impact of La Niña, the upper-tropospheric warming over the Tibetan Plateau modulates the Asian atmospheric circulation by inducing a northwest-southeast wave pattern extending from the Ural Mountains to the Indochina Peninsula via the western Tibetan Plateau. The meridional heat contrast associated with the Tibetan Plateau warming favors upward motion and excessive rainfall in SWC. The statistical connection between the SWC spring rainfall anomaly and the northwest-southeast wave pattern is confirmed by a climate model forecast. The model captured the wet pattern in SWC in spring 2022 in short (1–3 months) lead real-time predictions though there are biases in the area and severity. That may be due to that the model did not well capture the atmospheric circulation anomalies at the middle and high latitudes associated with the Tibetan Plateau upper-tropospheric warming. These results indicate that such an event is predictable to some extent if both the ENSO evolution and heat condition over the Tibetan Plateau can be well predicted.
•In 2022 spring, an excessive amount of rainfall fell in Southwest China under the background of frequent droughts in history.•La Niña and the Tibetan Plateau upper-tropospheric warming are two major factors leading to the extreme event.•Such an event is predictable if both the ENSO evolution and heat condition over the Tibetan Plateau can be well predicted.
A new and compact sensor based on the complementary split-ring resonator (CSRR) structure is proposed to characterize the relative permittivity of various dielectric materials, enabling the ...determination of soil water content (SWC). The proposed sensor consists of a circular microstrip patch antenna supporting a 3D-printed small cylindrical container made out of Acrylonitrile-Butadiene-Styrene (ABS) filament. The principle of operation is based on the shifting of two of the antenna resonant frequencies caused by changing the relative permittivity of the material under test (MUT). Simulations are performed enabling the development of an empirical model of analysis. The sensitivity of the sensor is investigated and its effectiveness is analyzed by characterizing typical dielectric materials. The proposed sensor, which can be applied to characterize different types of dielectric materials, is used to determine the percentage of water contained in different soil types. Prototypes are fabricated and measured and the obtained results are compared with results from other research works, to validate the proposed sensor effectiveness. Moreover, the sensor was used to determine the percentage of water concentration in quartz sand and red clay samples.
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