Search Results (65)

The ameliorative mechanism of biochar in reducing soil greenhouse gas emissions in arid saline farmland remains unclear. A two-year field study in sorghum farmland in China’s Hetao Irrigation District was conducted to assess the influence of corn straw-derived biochar on GHG emissions and explore the role of soil physicochemical properties in regulating GHG fluxes. Four different biochar application rates were tested: 0 (CK), 15 (C15), 30 (C30), and 45 t hm⁻² (C45). Compared to CK, C15 reduced CH₄ emissions by 15.2% and seasonal CH₄ flux by 77.0%. The N₂O flux followed CK > C45 > C30 > C15 from 2021 to 2022. C15 and C30 significantly decreased GWP, mitigating GHG emission intensity. Biochar application enhanced sorghum grain yield. Soil temperature was the primary determinant of CH₄ flux (total effect = 0.92). In the second year, biochar’s influence on CH₄ emissions increased by 0.76. Multivariate SEM identified soil moisture (total effect = −0.72) and soil temperature (total effect = −0.70) as primary negative regulators of N₂O fluxes. C40 lead to salt accumulation, which increases CH₄ emissions but inhibits N₂O emissions. Averaged over two years, GWP under C15 and C30 decreased by 76.5–106.7% and 5.3–56.1%, respectively, compared to CK. Overall, the application of biochar at a rate of 15 t hm⁻² significantly reduced CH₄ and N₂O emissions and increased sorghum yield. Full article

Reliable soil moisture projections are critical for optimizing crop productivity and water savings in irrigation in arid and semi-arid regions. However, capturing their spatial and temporal variability is difficult when using individual observations, modeling, or satellite-based methods. Here, we present an integrated framework that combines satellite-derived soil moisture estimates, ground-based observations, the HYDRUS-1D vadose zone model, and the ensemble Kalman filter (EnKF) data assimilation method to improve soil moisture simulations over saline-affected farmland in the Hetao irrigation district. Vegetation effects were first removed using the water cloud model; after correction, a cubic regression using the vertical transmit/vertical receive (VV) signal retrieved surface moisture with an R² value of 0.7964 and a root mean square error (RMSE) of 0.021 cm³·cm⁻³. HYDRUS-1D, calibrated against multi-depth field data (0–80 cm), reproduced soil moisture profiles at 17 sites with RMSEs of 0.017–0.056 cm³·cm⁻³. The EnKF assimilation of satellite and ground observations further reduced the errors to 0.008–0.017 cm³·cm⁻³, with the greatest improvement in the 0–20 cm layer; the accuracy declined slightly with depth but remained superior to either data source alone. Our study improves soil moisture simulation accuracy and closes the knowledge gaps in multi-source data integration. This framework supports sustainable land management and irrigation policy in vulnerable farming regions. Full article

Sustainable cropland management is essential in maintaining national food security. In the black soil regions of China, which are key areas for commercial grain production, sustainable land use must be achieved urgently. To address the absence of integrated, large-scale, remote sensing-based sustainability frameworks in China’s black soil zones, we developed a comprehensive evaluation system with 13 indicators from four dimensions: the soil capacity, the natural capacity, the management level, and crop productivity. With this system and the entropy weight method, we systematically analyzed the spatiotemporal patterns of cropland sustainability in the selected black soil regions from 2010 to 2020. Additionally, a diagnostic model was applied to identify the key limiting factors constraining improvements in cropland sustainability. The results revealed that cropland sustainability in Heilongjiang Province has increased by 7% over the past decade, largely in the central and northeastern regions of the study area, with notable gains in soil capacity (+15.6%), crop productivity (+22.4%), and the management level (+4.8%). While the natural geographical characteristics show no obvious improvement in the overall score, they display significant spatial heterogeneity (with better conditions in the central/eastern regions than in the west). Sustainability increased the most in sloping dry farmland and paddy fields, followed by plain dry farmland and arid windy farmland areas. The soil organic carbon content and effective irrigation amount were the main obstacles affecting improvements in cropland sustainability in black soil regions. Promoting the implementation of technical models, strengthening investment in cropland infrastructure, and enhancing farmer engagement in black soil conservation are essential in ensuring long-term cropland sustainability. These findings provide a solid foundation for sustainable agricultural development, contributing to global food security and aligning with SDG 2 (zero hunger). Full article

Large-scale inter-basin water transfer is an important means to alleviate the pressure on water resources in water shortage regions. However, the long-term impacts of inter-basin transfers on the regional water–salt balance and associated land productivity remain poorly understood, especially in salt-affected arid environments. To fill this gap, the core objective of this study was to reveal the implications of inter-basin water transfer on soil salinity and sodicity and the crop yield response under different irrigation practices. We conducted a case study on the Karamay irrigation district (KID), an artificial oasis with a 30-year history of inter-basin water transfer in northwestern China, using trend and correlation analyses, water–salt balance analyses, and salt-controlled yield reduction functions as well as field comprehensive measurements over 1996–2023. The results indicate that soil salinity and sodicity profiles, overall, exhibited a clear vertical stratification under both the early and late crop growing stages, and the degree of the soil salinization was decreasing, and the area of non-saline land was increasing significantly from 1996 to 2023 in the KID. Owing to the lack of salt-washing water and the poor irrigation water quality, the water-saving irrigated farmland was in the slight salt-aggregating state in the topsoil layer, while the other soil layers were in the salt-expelling or salt-equilibrating state in the KID. The profile distribution and exchange fluxes of soil salinity and sodicity are mainly characterized by climate, irrigation, and groundwater dynamics, as well as the plant salt tolerance, soil properties, and agronomic management which also influence the soil salt accumulation. With the transformation of irrigation schemes from traditional flood irrigation to modern water-saving irrigation during 1996–2023, the impact of soil salinity on relative crop yields has been substantially reduced in the KID, especially for salt-sensitive crops. This revealed that optimizing the drainage facilities, precise field irrigation and fertilization measures, and rational crop selection and agronomic practices are vital for high-quality development in the KID. Capitalizing on these research findings, we would provide effective directives for maintaining the sustainability of agricultural development in other similar inter-basin water transfer zones in the world. Full article

Agricultural greenhouse gas emissions continue to rise year after year, contributing significantly to global warming—an escalating crisis that demands urgent attention. In order to address this issue, it is crucial to investigate the relationship between greenhouse gas emissions from farmland and crop yield and quality through comprehensive regulation of the soil micro-environment by inputting water, fertilizer, gas, and heat. Therefore, we conducted field experiments in 2024 to examine the effects of different water, fertilizer, gas, and heat conditions on the yield, quality, greenhouse gas emissions, net global warming potential (NGWP), and greenhouse gas emission intensity (GHGI) of processing tomatoes in Xinjiang, China. This study established two irrigation water temperatures (T0: the local irrigation water temperature, approximately 10–15 °C; and T1: warming irrigation, 20–25 °C), two humic acid application rates (H0: 0% and H1: 0.5%, % as a percentage of total fertilizer application), and three aeration methods (A0: no aeration, A1: Venturi aerated, and A2: micro–nano aerated) during the growth period. The results showed that the number of fruits per hectare (NP), vitamin C (VC) content, titratable acidity and lycopene content were all significantly increased with increasing temperature, application of 0.5% humic acid, and aeration. Warming has little effect on GHGI, while humic acid application and aeration have significant and extremely significant effects on GHGI. The GHGI of humic acid treatment was 7.70% lower than that of H0, and the GHGI of micro–nano aeration and Venturi aeration treatment was 18.95% and 6.85% lower than that of A0, respectively. We employed a comprehensive evaluation model that focused on overall differences to assess yield, quality, economic benefits, and environmental impact (GHGI, global warming potential). The optimal strategy identified comprised 20–25 °C irrigation, micro–nano aeration, and 0.5% humic acid, which collectively achieved the highest scores in yield, quality, and emission reduction. This study establishes a theoretical and technical foundation for the sustainable and efficient production of tomatoes in the arid regions of Northern Xinjiang. Full article

The salt distribution characteristics in arid areas are directly related to the sustainable development of agriculture. We study the characteristics of spatial changes of soil water and salt in farmland under the full anniversary of different culvert pipe arrangements and optimize the salt drainage parameters of underground drains suitable for the local area so as to promote the management of saline and alkaline land in Xinjiang. A subsurface drainpipe salinity test was conducted in the Yanqi Basin (Bayingoleng Mongolian Autonomous Prefecture, Xinjiang Uygur Autonomous Region, China) to analyze changes in soil water and salt dynamics before and after irrigation-induced salt flushing, assessing the impact of drainpipe deployment parameters. It was found that at a 1.4 m depth of burial, the maximum desalination rates of soil in different soil layers from the subsurface drainpipes in 20, 30, and 40 m spacing plots were 78.28%, 50.91%, and 54.52%, respectively. At a 1.6 m depth of burial, the maximum desalination rates of soil in different soil layers from the subsurface drainpipes in 20, 30, and 40 m spacing plots were 70.94%, 61.27%, and 44.12%. Reasonable deployment of subsurface drainpipes can effectively reduce soil salinity, increase the desalination rate, and improve soil water salinity condition. This study reveals the influence of the laying parameters of subsurface drainpipes on soil water salinity distribution characteristics in arid zones, which provides theoretical support and practical guidance for the management of soil salinization in arid zones. Full article

In this study of constructing gross primary production (GPP) based on solar-induced chlorophyll fluorescence (SIF) and analyzing its spatial–temporal characteristics and influencing factors, numerous challenges are encountered, especially in arid regions with fragile ecologies. Coupling SIF with other factors to construct the GPP and elucidating the influencing mechanisms of environmental factors could offer a novel theoretical method for the comprehensive analysis of GPP in arid regions. Therefore, we used the GPP station data from three different ecosystems (grasslands, farmlands, and desert vegetation) as well as the station and satellite data of environmental factors (including photosynthetically active radiation (PAR), a vapor pressure deficit (VPD), the air temperature (Tair), soil temperature (Tsoil), and soil moisture content (SWC)), and combined these with the TROPOMI SIF (RTSIF, generated through the reconstruction of SIF from the Sentinel-5P sensor), whose spatiotemporal precision was improved, the mechanistic light reaction model (MLR model), and different weather conditions. Then, we explored the spatiotemporal characteristics of GPP and its driving factors in local areas of Xinjiang. The results indicated that the intra-annual variation of GPP showed an inverted “U” shape, with the peak from June to July. The spatial attributes were positively correlated with vegetation coverage and sun radiation. Moreover, inverting GPP referred to the process of estimating the GPP of an ecosystem through models and remote sensing data. Based on the MLR model and RTSIF, the inverted GPP could capture more than 80% of the GPP changes in the three ecosystems. Furthermore, in farmland areas, PAR, VPD, Tair, and Tsoil jointly dominate GPP under sunny, cloudy, and overcast conditions. In grassland areas, PAR was the main influencing factor of GPP under all weather conditions. In desert vegetation areas, the dominant influencing factor of GPP was PAR on sunny days, VPD and Tair on cloudy days, and Tair on overcast days. Regarding the spatial correlation, the high spatial correlation between PAR, VPD, Tair, Tsoil, and GPP was observed in regions with dense vegetation coverage and low radiation. Similarly, the strong spatial correlation between SWC and GPP was found in irrigated farmland areas. The characteristics of a low spatial correlation between GPP and environmental factors were the opposite. In addition, it was worth noting that the impact of various environmental factors on GPP in farmland areas was comprehensively expressed based on a linear pattern. However, in grassland and desert vegetation areas, the impact of VPD on GPP was expressed based on a linear pattern, while the impact of other factors was more accurately represented through a non-linear pattern. This study demonstrated that SIF data combined with the MLR model effectively estimated GPP and revealed its spatial patterns and driving factors. These findings may serve as a foundation for developing targeted carbon reduction strategies in arid regions, contributing to improved regional carbon management. Full article

Groundwater is a significant source of water, and evaluating its hydrochemical attributes, quality, and associated health risks holds paramount importance in guaranteeing safe water access for the population and fostering sustainable socio-economic progress. Situated within a semi-arid region, the Dianbu area (DBA) features numerous greenhouses interspersed amongst open farmlands. An examination revealed a discernible decline in the overall water chemistry environment in this area. This study extensively examined the fundamental water chemistry characteristics of groundwater and surface water samples through a statistical analysis, Piper’s trilinear diagram, ion ratios, and other analytical methods. The assessment of irrigation water quality was conducted using the entropy weight water quality index (EWQI), sodium adsorption ratio (SAR), percentage of soluble sodium (Na%), among other relevant indicators. The findings demonstrate multiple key aspects: 1. Water cations are chiefly composed of Ca²⁺ and Na⁺, while groundwater anions are notably NO₃⁻ and SO₄²⁻ dominant, defining the water type as NO₃-SO₄-Ca. Conversely, surface water primarily displays HCO₃⁻ and SO₄²⁻ anions, aligning it with an HCO₃-SO₄-Ca water type. 2. The extensive agricultural activities in the region, coupled with the excessive utilization of pesticides, chemical fertilizers, as well as the discharge of domestic sewage, contribute to heightened NO₃⁻ concentrations in groundwater. 3. The water quality assessments indicate that approximately 53% of agricultural water quality meets irrigation standards based on EWQI, with SAR results suggesting around 65.52% suitability for irrigation and Na% findings indicating approximately 55.88% viability for this purpose. Proper water selection tailored to specific conditions is advised to mitigate potential soil salinization risks associated with long-term irrational irrigation practices. Full article

A sophisticated precision irrigation system was created to precisely determine the water requirements of crops and implement effective irrigation control strategies for automated, real-time, and targeted crop irrigation in the semi-arid regions of India. This system incorporates ZigBee technology, wireless sensor networks, and fuzzy logic-based control methodologies. This system discussed by the author actively gathers data for the most prominent parameters of the targeted area, such as soil water potential and meteorological conditions, encompassing ambient temperature, humidity, solar radiation, and wind speed. These data obtained from the sensors then processed with the fuzzy logic-based algorithms is utilized to transmit precise irrigation control instructions to the system. Moreover, this proposed system employs the Priestley and Taylor model (PTM) so as to calculate farmland evapotranspiration (ET). This algorithm has been chosen instead of the Penman & Monteith model (PMM) because of its better accuracy and simple calculations. Both field evapotranspiration and soil water potential serve as crucial inputs for the suggested fuzzy controller-based system. A comprehensive multi-factor control rule library is established, facilitating the implementation of fuzzy control mechanisms for regulating crop irrigation water requirements with enhanced performance. The testing results obtained from this proposed system demonstrate the system’s economic viability and practicality, underscoring its reliability in communication, high control accuracy, and suitability for precision irrigation in semi-arid regions in India that, in turn, enhances the crop yield. Full article

The risk of soil salinization is prevalent in arid and semi-arid regions, posing a critical challenge to sustainable agriculture. This study addresses the need for accurate assessment of regional root-zone soil salt content (SSC) and understanding of underlying driving mechanisms, which are essential for developing effective salinization mitigation and water management strategies. A remote sensing inversion technique, initially proposed to estimate root-zone SSC in cotton fields, was adapted and validated more widely to non-cotton farmlands. Validation results (with a coefficient of determination R² > 0.53) were obtained using data from a three-year (2020–2022) regional survey conducted in the arid Manas River Basin (MRB), Xinjiang, China. Based on this adapted technique, we analyzed the spatiotemporal distributions of root-zone SSC across all farmlands in MRB from 2001 to 2022. Findings showed that root-zone SSC decreased significantly from 5.47 to 3.77 g kg⁻¹ over the past 20 years but experienced a slight increase of 0.15 g kg⁻¹ in recent five years (2017–2022), attributed to cultivated area expansion and reduced irrigation quotas due to local water shortages. The driving mechanisms behind root-zone SSC distributions were analyzed using an approach combined with two machine learning algorithms, eXtreme Gradient Boosting (XGBoost) and SHapley Additive exPlanation (SHAP), to identify influential factors and quantify their impacts. The approach demonstrated high predictive accuracy (R² = 0.96 ± 0.01, root mean squared error RMSE = 0.19 ± 0.03 g kg⁻¹, maximum absolute error MAE = 0.14 ± 0.02 g kg⁻¹) in evaluating SSC drivers. Factors such as initial SSC, crop type distribution, duration of film mulched drip irrigation implementation, normalized difference vegetation index (NDVI), irrigation amount, and actual evapotranspiration (ET_a), with mean ($\left|\mathrm{SHAP} \mathrm{value}\right|$) ≥ 0.02 g kg⁻¹, were found to be more closely correlated with root-zone SSC variations than other factors. Decreased irrigation amount appeared as the primary driver for recent increased root-zone SSC, especially in the mid- and down-stream sections of MRB. Recommendations for secondary soil salinization risk reduction include regulation of the planting structure (crop choice and extent of planting area) and maintenance of a sufficient irrigation amount. Full article

The construction of underground reservoirs in coal goaf is a new technology aimed to realize the sustainable development of coal mining-water storage-surface ecology in arid areas of northwest China. The key to the feasibility of this technology is that underground coal mining cannot affect the near-surface aquifer, and the amount of water entering the underground reservoir must meet the needs of the coal mine. Taking Buertai Coal Mine, one of the largest underground coal mines in the world, as an example, this article used similar simulation, numerical simulation and in-situ test methods to study the height of the water-conducting fracture zone of overlying strata and water inflow of underground reservoirs. The results show that, under the repeated mining of the 22- and 42-coal seams, the maximum height of the water-conducting fracture zone is 178 m, and the distance between the near-surface aquifer and the 42 coal is about 240 m, so the mining has little effect on the near-surface aquifer. During the mining period of the 22-coal seam, the groundwater of the Zhidan and Zhiluo Formations was mainly discharged vertically, while the groundwater of the Yanan Formation was mainly a horizontal flow during the period of the 42-coal mining. In this way, the total water inflow of Buertai Coal Mine reaches 500 m³/h, which not only meets the needs of the mine, but also, the rest of the water can irrigate about 98 hectares of farmland nearby. Underground reservoirs in coal goaf could achieve sustainable development of coal mining, groundwater storage and surface ecology in semi-arid areas. Full article

The depth and width of drip infiltration play a critical role in designing effective irrigation strategies. However, existing models primarily focus on continuous irrigation and fail to predict wetting patterns under intermittent drip irrigation. This study developed an infiltration model to estimate soil moisture depth and width under intermittent drip irrigation and identified strategies that enhance effective water storage. Indoor soil box simulations were conducted, with continuous drip irrigation as the control. Results showed that intermittent irrigation increased infiltration width and reduced depth, maximizing water storage efficiency. We recommend adopting an intermittent irrigation system with 1.5 h of irrigation followed by a 0.5 h interval, repeated four times. This system increased effective water storage by up to 16.23% compared to continuous irrigation. The proposed method is suitable for sandy loam farmland in southern Xinjiang and can significantly improve water use efficiency in arid regions. Full article

Green manure is widely applied in agricultural production due to its beneficial soil modification and fertilization effects. However, the mechanisms underlying the effects of green manure return methods on soil respiration (Rs) and its components remain unclear. This study aimed to investigate the effects of green manure return methods on Rs in maize fields by quantifying Rs levels. A field experiment was conducted from 2021 to 2023 in the inland river oasis irrigation area of Gansu, with five treatment conditions: tillage with a full quantity of green manure incorporated into the soil (TG), no tillage with a full quantity of green manure mulched on the soil surface (NTG), tillage with roots incorporated into the soil and above-ground green manure removed (T), no tillage with above-ground manure removed (NT), and conventional tillage and leisure (CT). The results showed that, compared with CT, the NTG treatment increased the maize grain yield while reducing the soil heterotrophic respiration rate (Rh) by 8.5–9.8% and Rs by 6.7–8.7%, but did not significantly affect the soil autotrophic respiration rate (Ra), and decreased the carbon emission efficiency (CEE) by 20.8–25.6%. The increase in the soil water content (SWC) significantly reduced Rh during all growth periods, which was the primary factor in the reduction of Rs. Additionally, the net ecosystem productivity carbon sequestration (NEP-C) of the farmland ecosystem was positive under this system, indicating that the soil acts as a carbon “sink”. Therefore, a no-tillage treatment with a full quantity of green manure mulched on the soil surface can be used as a reasonable green manure return method to reduce carbon emissions from farmland in arid oasis irrigation regions. Full article

In response to water scarcity in the Bashang area of northwest Hebei Province, a cold and arid region in north China, and to address the diminishing groundwater levels caused by pumping irrigation, this study investigated the impact of rainwater tank size and water supply on kidney beans production in greenhouses under various precipitation scenarios to determine the production potential and development strategies for regional precipitation resources. Under the background of average annual precipitation, kidney bean yield increased with increasing reservoir volume and shorter irrigation cycles. Under a 4-day irrigation cycle, the water demand satisfaction rate of kidney beans reached 100% water demand when the rainwater tank size was 15.7 m³. Against the wide variation in multi-year regional precipitation from 1992 to 2023, the annual effect of rainwater harvest was simulated using precipitation data collected 20 years with an 80% precipitation guarantee rate. The average minimum yield reduction rate obtained was 9.4%, and the corresponding minimum rainwater tank size was 29.5 m³. By superimposing the rainwater harvested in the shed and nonshed areas, the volume of the reservoir without yield reduction could be reduced to 20.0 m³. The sum of discharged and inventory water was much greater than the water scarcity in each water supply situation. Simulating and analyzing the effect of the relationship between rainwater tank size and water supply on rainwater harvesting in regional farmland by year provides important data affecting the construction of regional rainwater storage facilities and water supply efficiency. To achieve a high, stable yield of kidney beans grown in a greenhouse with shed film and shed area rainwater harvesting in north China, 2.6 m³ supplementary groundwater irrigation is still needed during the annual growing season. Full article

Accurate and rapid estimation of soil organic matter (SOM) content is of great significance for advancing precision agriculture. Compared with traditional chemical methods, the hyperspectral estimation is superior in rapidly estimating SOM content. Soil grain size affects soil spectral reflectance, thereby affecting the accuracy of hyperspectral estimation. However, the appropriate soil grain size for the hyperspectral analysis is nearly unknown. This study propose a best hyperspectral estimation method for determining SOM content of farmland soil in the Ibinur Lake Irrigation Area (ILIA) of the northwest arid zones of China. The original spectral reflectance of the 20-mesh (0.85 mm) and 60-mesh (0.25 mm) sieved soil were obtained, and the feature wavebands were selected using five types of spectral transformations. Then, hyperspectral estimation models were constructed based on the partial least squares regression (PLSR), support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost) models. Results show that the SOM content had relatively higher correlation coefficient with spectral reflectance of the 0.85 mm sieved soil than that of the 0.25 mm sieved soil. The transformation of original spectral reflectance of soil effectively enhanced the spectral characteristics related to SOM content. Soil grain size obviously affected spectral reflectance and the accuracy of hyperspectral estimation models. The overall stability and estimation accuracy of RF model was significantly higher compared with the PLSR, SVM, and XGBoost. Finally, the RF model combined with the root mean first-order differentiation (RMSFD) of spectral reflectance of the 0.85 mm sieved soil (R² = 0.82, RMSE = 2.37, RPD = 2.27) was identified as the best method for estimating SOM content of farmland soil in the ILIA. Full article