Search Results (56)

Rice cultivation is a major source of methane (CH₄) emission in the agricultural sector, with a significantly higher global warming potential than carbon dioxide. Accurate and scalable quantification of CH₄ from rice paddies is essential for carbon accounting. This study presents an automated framework for estimating rice CH₄ emissions from irrigated paddies in the central plain of Thailand, integrating multi-sensor Synthetic Aperture Radar (SAR) observations with the IPCC methodology. The framework combines Sentinel-1 C-band SAR time series for phenological detection, ALOS-2 PALSAR-2 L-band full-polarimetric SAR for water regime classification, and IPCC water-scaling factors corresponding to Continuous Flooding, Single Drainage, or Multiple Drainage regimes. Evaluated across five stratified holdout sets, the phenology detection algorithm achieved planting and harvesting date Mean Absolute Errors of 6.1 ± 1.4 and 8.3 ± 1.7 days, with a 97.0% ± 2.7% operational detection rate. Water regime classification employed rice growth stage-specific Support Vector Machine classifiers with Radial Basis Function kernels (SVM-RBF), achieving per-stage test Balanced Accuracy ranging from 0.59 to 0.89. End-to-end integration using a four-track counterfactual decomposition yielded a full-pipeline mean absolute error of 18.5 ± 4.5 $\mathrm{kg}{\mathrm{CH}}_4{\mathrm{ha}}^{-1}$ (21.4% of the mean ground-based CH₄ calculation) and a mean bias of 3.5 ± 5.8 $\mathrm{kg}{\mathrm{CH}}_4{\mathrm{ha}}^{-1}$. Water level classification was confirmed as the dominant algorithmic uncertainty source, while the IPCC Tier 1 emission factor structural range (−32% to +48% of the default) exceeded all algorithmic errors combined. The proposed framework provides a spatially explicit approach for integrating multi-frequency SAR data into IPCC-compliant methane estimation, supporting Monitoring, Reporting, and Verification applications. Full article

Non-flooding irrigation is widely promoted as a carbon–water co-benefit strategy in paddy rice, but field-scale trials overlook return flow compensation within irrigation districts and therefore overstate water-saving potential. To reconcile this scale mismatch, we developed a semi-distributed multi-scale water balance model coupled with a carbon footprint and full-component blue–green–grey water footprint framework and applied it across field, district, and provincial scales in Heilongjiang Province—a leading cold-region japonica rice region in Northeast China—using the Qinglongshan Irrigation District on the Sanjiang Plain as the focal case, supported by two growing seasons of field observations and 35 years of provincial records. Under alternate wetting and drying, apparent field-level water savings of 50–60% converge to 33% after return flow correction, implying that field-based indicators overestimate savings by 40–50%. Carbon mitigation is decoupled from water volume: CH₄ suppression dominates total abatement and is governed by drying frequency rather than water saved. At the provincial scale, the water footprint has shifted from grey- to blue-water dominance, suggesting that blue-water efficiency now represents a principal remaining lever for further cold-region carbon–water co-benefits. Two-season coverage and fixed parameter assumptions affect magnitudes but not directions. Water-saving irrigation in cold-region paddy systems should therefore be evaluated at the district scale where data permit, rather than relying solely on field-scale indicators. Full article

The release of heavy metals into the environment due to human activities is increasing, and this has led to concern about heavy-metal contamination on farmland. Prior studies have primarily focused on short-term investigations or specific pollution sources, lacking systematic monitoring of cadmium’s long-term input-output fluxes and their mass balance at the scale of a complete farmland ecosystem. This study clarified the cadmium (Cd) pollution trends for a typical paddy system in southern China. A six-year long-term monitoring study (2019–2024 inclusive) of a Cd-contaminated paddy system in Ningxiang City, Hunan Province, China, was conducted. The Cd flux dynamics for three input pathways (atmospheric deposition, irrigation water, and fertilizer) and three output pathways (crop harvesting, surface runoff, and subsurface infiltration) were investigated. The results showed that atmospheric deposition is the primary source of Cd input, accounting for 76% of total inputs, and leads to persistent net accumulation of soil Cd. Straw removal serves as the dominant output mechanism, facilitating substantial Cd removal, representing 77% of total Cd exports, while straw retention significantly reduces export fluxes. The study found that the net Cd fluxes from 2019 to 2024 were 1.994, 2.624, 8.984, 11.299, 9.944, and 20.162 g·(hm²·a)⁻¹, straw removal was primarily adopted during the period. A net flux analysis showed that progressive soil Cd accumulation had occurred over the study period. The results suggest that science-based straw management is critical when attempting to mitigate soil Cd pollution and enhance safe land utilization. These findings can be used to improve region-specific pollutant source control strategies and soil management policies. Full article

With the large-scale cultivation of transgenic Bacillus thuringiensis (Bt) crops, the Bt toxin released from Bt crops is continuously introduced into the soil. Its environmental fate represents a key indicator for assessing the ecological safety of transgenic crops. However, the persistence of Bt toxin in soil is influenced by both biotic and abiotic processes, and their respective contributions under natural conditions remain unclear. This study measured water-dissolved Bt toxin concentrations in paddy soil (PS) and red soil (RS) to compare the influence of biotic and abiotic factors on the dynamic retention of exogenous Bt toxin under different sterilization methods: no sterilization, heat sterilization (HT), and irradiation sterilization (IS). The water-dissolved Bt toxin exhibited a dynamic decrease–increase–decrease trend across all three treatments in both soil types during the 30 day experimental period. Bt toxin displayed rapid adsorption during the initial 2 h stage in RS, but subsequently showed a high desorption, whereas PS probably achieved more stable bonding through soil organic matter (SOM). Different sterilization methods significantly influenced the results by altering abiotic factors: Compared to CK, HT affected soil physicochemical properties and enhanced adsorption resilience, whereas IS caused minimal impact on the soil physicochemical properties, thereby providing a more accurate reflection of abiotic processes. And microbial, as biotic facters, also influence the reduction process of Bt toxin by participating in the adsorption–desorption–degradation equilibrium process. Therefore, we infer that over time, the concentration of water-soluble Bt proteins in the soil will tend toward zero. Additionally, the initial Bt toxin concentration influenced dynamic balance by adjusting adsorption site saturability, with more pronounced desorption reversibility at 500 ng/g concentrations. Overall, this study systematically reveals the effects of soil properties, microorganisms, and sterilization methods on Bt toxin persistence. The findings underscore the importance of selecting and justifying sterilization methods in related environmental behavior studies, while providing essential guidance for the scientific assessment of environmental risks posed by transgenic crops. Full article

Chieng Hac in northern Vietnam is expanding maize cultivation, intensifying water competition and soil erosion. This study mapped regional water balance and erosion using remote sensing and GISs by coupling the Thornthwaite–Mather (TM) water balance model with the Revised Universal Soil Loss Equation (RUSLE) at 12.5 m resolution. Land cover was classified into maize, tree crops, paddy, forest, and other types using Random Forest. The TM model used 2021 precipitation and temperature measurements to estimate evapotranspiration, surplus, and deficit, while the RUSLE quantified soil loss. Two scenarios were evaluated: a baseline reflecting existing land use and an adjusted case applying strip cropping on 10–20° maize slopes and converting maize to tree crops on slopes > 20°. Tree crop conversion increased evapotranspiration and prolonged seasonal deficits relative to maize, increasing water deficit from 1013.6 to 1022.2 mm/year. In contrast, the interventions reduced mean soil loss from 15.52 to 11.51 t/ha/year, with the largest decline in the 5–25 t/ha/year class. Residual hotspots persisted on steep slopes and near drainage lines. The integrated framework highlights trade-offs between erosion control and seasonal water availability, supporting slope-based land-use planning in upland agricultural systems. These findings offer guidance for slope-based land-use planning by indicating that intervention priorities should vary depending on slope conditions and local water availability. Full article

Wetlands are highly productive ecosystems that play a vital role in maintaining ecological balance. This study presents a geospatial assessment of the Harike Wetland, Punjab, using hyperspectral (PRISMA) and multispectral (Landsat series) satellite data to analyze its ecological structure and water dynamics. Six spectral indices—Normalized Difference Vegetation Index (NDVI), Normalized Dif-ference Aquatic Vegetation Index (NDAVI), Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Floating Algal Index (FAI), and Algal Bloom Detection Index (ABDI)—were employed to map terrestrial agricultural cropland (paddy), aquatic vegetation and surface water. Threshold-based classification of index outputs was used to estimate the spatial extent of major land cover types. NDVI and NDAVI effectively captured vegetation patterns, while NDWI and MNDWI improved surface water delineation. Additionally, Z-spectral analysis was applied to extract and compare the reflectance profiles of agricultural cropland, open water, and algae, as well as built-up areas, enhancing spectral contrast and classification accuracy, particularly in spectrally mixed zones. The integration of index-based mapping with detailed spectral profiling demonstrates the advantage of combining multispectral and hyperspectral data for wetland monitoring and provides valuable insights to support wetland conservation and sustainable water management. Full article

Balancing food production, water conservation, and carbon emissions (CEs) is critical in Northeast China (NEC), yet food–carbon–water (FCW) interactions remain poorly quantified at pixel scale. Conceptually, we move beyond administrative-unit nexus assessments by providing a crop-explicit, grid-based FCW diagnosis that identifies where crop-specific bottlenecks emerge and supports zoning-oriented interventions. We fused multi-source datasets with process models to estimate CEs, water use efficiency (WUE), and yield for maize, rice, and soybean at 500 m resolution during 2001–2020 and evaluated synergies/trade-offs based on Sen’s slope trends and nexus performance using coupling coordination degree (CCD). Annual mean CE (230.8–37,300 kg CO₂-eq ha⁻¹), yield (0–10,031 kg ha⁻¹), and WUE (0–6 kg C m⁻³) exhibited pronounced spatial heterogeneity. Higher CEs and yield concentrated in the central–southern plains, whereas WUE showed a patchier pattern with localized high values. Temporally, CEs increased for all crops, with rice consistently exhibiting the highest CEs. Soybean showed the most pronounced WUE improvement, reaching >2.0 kg C m⁻³ after the early 2010s. Pixel-wise correlations revealed a robust CE–WUE antagonism for all crops (r = −0.33 to −0.60), while CE–yield coupling was crop-dependent (soybean positive, maize weakly negative, rice non-significant). Trend-based coupling further showed that synchronized CE and yield increases dominated 45.7% of croplands, whereas trade-offs were more common when WUE was involved (CE–WUE: 38.0%; WUE–yield: 41.8%), peaking in rice systems (61.8% and 54.0%, respectively). CCD mapping indicated widespread basic coordination but strong crop contrasts. Rice had the lowest coordination (mean CCD = 0.36 ± 0.17) and the largest shares of moderate-to-severe imbalance, identifying rice as the primary FCW bottleneck, whereas maize and soybean more frequently achieved good-to-high coordination. These results support a zoned strategy that consolidates coordinated maize/soybean areas, prioritizes paddy water-saving and low-emission upgrades, and limits further rice expansion in water-constrained zones. Full article

This study examines the hydrological response of the Klambu Dam Catchment in Central Java, Indonesia, to climatic and land cover changes from 2000–2023, with simulations extending to 2040. Utilizing CHIRPS satellite data calibrated with six ground stations, monthly precipitation and temperature datasets were analyzed and projected via linear regression aligned with IPCC scenarios, revealing a marginal temperature decline of 0.21 °C (from 28.25 °C in 2005 to 28.04 °C in 2023) and a 17% increase in rainfall variability. Land cover assessments from Landsat imagery highlighted drastic changes: a 73.8% reduction in forest area and a 467.8% increase in mixed farming areas, alongside moderate fluctuations in paddy fields and settlements. The Thornthwaite-Mather water balance method simulated monthly discharge, validated against observed data with Pearson correlations ranging from 0.5729 (2020) to 0.9439 (2015). Future projections using Cellular Automata-Markov modeling indicated stable volumetric flow but a temporal shift, including a 28.1% decrease in April rainfall from 2000 to 2040, contracting the wet season and extending dry spells. These shifts pose significant threats to agricultural and aquaculture activities, potentially exacerbating water scarcity and economic losses. The findings emphasize integrating dynamic land cover data, climate projections, and empirical runoff corrections for climate-resilient watershed management. Full article

Rice, as one of the world’s three major staple crops, provides a food source for nearly half of the global population. Timely and accurate acquisition of rice cultivation information is crucial for optimizing spatial distribution, guiding production practices, and safeguarding food security. Taking Bishan District of Chongqing as the study area, NDVI values were derived from Sentinel-2 satellite imagery to construct standard NDVI time-series curves for typical land-cover types, including paddy fields, dryland, water bodies, construction land, and forest and grassland. These curves were then used in the NDVI time-series characteristics method to identify paddy fields. First, the Euclidean distance between the standard NDVI time series of paddy fields and those of other land-cover types was calculated. The sum of these element-wise differences was used to determine the upper threshold for paddy field extraction. Second, the mean absolute deviation between elements of the rice sample dataset and the standard NDVI time series was calculated for each time step. The sum of these average deviations was used as the lower threshold to extract the initial paddy field data. On this basis, an extreme-value constraint was introduced to reduce the interference of mixed pixels from forest and grassland and construction land, effectively eliminating anomalous pixels and improving the accuracy of paddy field identification. Finally, the results were validated and compared with those from other extraction methods. The results indicate that: (1) Paddy fields exhibit distinct NDVI time-series characteristics throughout the entire growing season, which can serve as a reference standard. By calculating the Euclidean distance between the NDVI curves of other land-cover types and those of paddy fields, similarity can be quantified, enabling rice identification. (2) The extraction method based on NDVI time-series characteristics successfully identified paddy fields through the appropriate setting of thresholds. The overall accuracy and Kappa coefficient remained high, while the F1-score consistently exceeded 0.8, indicating a good balance between precision and recall. Furthermore, the bootstrap uncertainty analysis revealed narrow 95% confidence intervals across all metrics, confirming the robustness and statistical reliability of the results. Overall, the proposed method demonstrated excellent performance in paddy field classification and significantly outperformed traditional machine learning methods implemented on the GEE platform. (3) Mixed pixels considerably affected the accuracy of rice classification; however, the introduction of the extreme-value constraint effectively mitigated this influence and further improved classification results. Full article

Rice is a major dietary component for more than half of the world’s population, and its cultivation requires a careful balance of nutrients to ensure high yields and sustainable practices. Soil-derived N₂O fluxes represent a major environmental challenge with global implications. While agriculture is a necessary activity to feed a growing population, it must evolve to minimize its ecological footprint. This review provides an update on the effects of nitrogen fertilizer application, such as ammonium nitrate (NH₄NO₃), urea (CO(NH₂)₂), ammonium sulfate ((NH₄)₂SO₄), and calcium ammonium nitrate (CAN), on N₂O emissions from rice cultivation. The role of various nitrification inhibitors (e.g., dicyandiamide (DCD), 2-chloro-6-(trichloromethyl) pyridine (nitrapyrin) and 3,4-dimethylpyrazole phosphate (DMPP)) in minimizing the release of N₂O from soils to the atmosphere was also discussed. Here, we described N₂O production by nitrification and denitrification processes in the paddy rice field, and then summarized the strategies, such as optimized fertilizer use, improved drainage and water management, and the use of organic amendments, that can enhance crop productivity while promoting sustainable reductions in N₂O emissions. Full article

Making effective decisions about scaling up on-farm irrigation practices to the district level requires a comprehensive assessment of irrigation management at the farm level. In this context, a bucket-type water mass balance model was developed, calibrated, and validated over five irrigation seasons on a 121-hectare rice farm located in the lower Ter River valley (north-east Spain), to assess the water use efficiency and the impact of different irrigation practices on water savings. The model was implemented considering the spatial variability of the soils within the farm. It showed a satisfactory performance in both the calibration (2020, 2021, 2022) and validation (2023, 2024) cropping seasons, with NSE values greater than 0.50, PBIAS lower than ±20%, and RSR lower than 0.70. After model validation, the simulation of alternative water management practices revealed that the 10-day fixed-turn irrigation reduced irrigation water use by 30% compared to the traditional water management, although it may negatively impact rice yield. Simulations of an early irrigation cut-off at the end of the season and dry seeding with delayed flooding accounted for 17% and 15% irrigation water savings, respectively. The implementation of the no-runoff practice only accounted for a 6% reduction in water use. The water-saving potential of the simulated strategies was mainly driven by shortening the flooded period of rice paddies, thus demonstrating that managing the ponding water level is critical to diminishing water use in rice irrigation. Full article

Paddy cultivation in the black soil region of northeast China is faced with the problems of low irrigation water use efficiency (IWUE) and low temperature stress during sowing. Therefore, the combinations of film mulching and water-saving irrigation methods were adopted to adjust the balance between water and yield under the condition of suitable soil water and heat environment, and to quantify the relationship between irrigation water and yield formation. This study investigated the mechanisms of two kinds of biodegradable film mulching combined with two water-saving irrigation on soil hydrothermal conditions in cold-region paddy fields. The results show that film mulching improved the water retention capacity of the soil at different depths, with black film exhibiting better moisture conservation than white film. Overall, controlled irrigation resulted in higher soil moisture than ridge irrigation before the heading–flowering stage, but lower values in heading–flower stage and the later stage. Film mulching also increased soil temperature across different layers, with black film showing a more warming effect in the 0–5 cm soil layer. All combinations of biodegradable film mulching and water-saving irrigation enhanced the IWUE, with the ridge irrigation combined with black film mulching showing the most significant improvement. This research provides technical references for water-efficient rice cultivation in cold regions. Full article

Investigating soil temperature and the heat transfer process is essential for understanding water–heat changes and energy balance in farmland. The conversion from upland fields (UFs) to paddy fields (PFs) alters the land cover, irrigation regimes, and soil properties, leading to differences in soil temperature, thermal properties, and heat fluxes. Our study aimed to quantify the effects of converting UFs to PFs on soil temperature and heat transfer processes, and to elucidate its underlying mechanisms. A long-term cultivated UF and a newly developed PF (converted from a UF in May 2015) were selected for this study. Soil water content (SWC) and temperature were monitored hourly over two years (June 2017 to June 2019) in five soil horizons (i.e., 10, 20, 40, 60, and 90 cm) at both fields. The mean soil temperature differences between the UF and PF at each depth on the annual scale varied from −0.1 to 0.4 °C, while they fluctuated more significantly on the seasonal (−0.9~1.8 °C), monthly (−1.5~2.5 °C), daily (−5.6~4.9 °C), and hourly (−7.3~11.3 °C) scales. The SWC in the PF was significantly higher than that in the UF, primarily due to differences in tillage practices, which resulted in a narrower range of soil temperature variation in the PF. Additionally, the SWC and soil physicochemical properties significantly altered the soil’s thermal properties. Compared with the UF, the volumetric heat capacity (C_s) at the depths of 10, 20, 40, 60, and 90 cm in the PF changed by 8.6%, 19.0%, 5.5%, −4.3%, and −2.9%, respectively. Meanwhile, the thermal conductivity (λ_θ) increased by 1.5%, 18.3%, 19.0%, 9.0%, and 25.6%, respectively. Moreover, after conversion from the UF to the PF, the heat transfer direction changed from downward to upward in the 10–20 cm soil layer, resulting in a 42.9% reduction in the annual average soil heat flux (G). Furthermore, the differences in G between the UF and PF were most significant in the summer (101.9%) and most minor in the winter (12.2%), respectively. The conversion of the UF to the PF increased the C_s and λ_θ, ultimately reducing the range of soil temperature variation and changing the direction of heat transfer, which led to more heat release from the soil. This study reveals the effects of farmland use type conversion on regional land surface energy balance, providing theoretical underpinnings for optimizing agricultural ecosystem management. Full article

Wetland monitoring is a key means of protecting wetland ecosystems. In order to achieve continuous monitoring of wetlands and predict future patterns, this paper analyzes the spatiotemporal evolution characteristics of wetlands in the upper reaches of the Yellow River from 1990 to 2020, and uses the Patch Generation Land Use Simulation (PLUS) model to simulate the spatial distribution of wetlands from 2040 to 2060 under four scenarios: farmland protection (FPS), wetland protection (WPS), comprehensive protection (CPS) and natural development (NDS). The results show that the total area of wetlands in the upper reaches of the Yellow River is on the rise, increasing by 7.12% in 2020 compared with 1990. The changes in various types of wetlands are different: the areas of river and canals increased by 26.39% and 57.97%, respectively, paddy fields increased by 7.95%, lakes remained basically stable, and tidal flats decreased by 5.67%. The simulation results of the future spatial pattern of wetlands show that: under the FPS scenario, farmland and related land use will expand significantly, mainly through the development of beaches, dry land and unused land, while under the WPS scenario, wetlands will be strictly protected, the area of water resource features such as rivers, lakes and reservoirs will increase significantly, and land use changes will be more ecologically oriented. Compared with the CPS and NDS scenarios, the wetland protection and urbanization process in the upper reaches of the Yellow River can be balanced under the FPS and WPS scenarios. This study has important reference value for the protection and sustainable development of wetland ecosystems in the upper reaches of the Yellow River. Full article

Non-point source (NPS) pollution from agriculture accounts for more than 20% of the total pollution load in the Republic of Korea, with the highest nutrient balance among OECD countries. Rice paddy fields are among the most important NPSs because of their large area, intensive fertilizer use, intensive use of irrigation water, and subsequent drainage. Therefore, the use of controlled drainage in paddy fields (Test) was evaluated for reduction in the discharged volumes and pollutant loads in drainage and stormwater runoff in comparison to plots using traditional drainages (Control). The results show that the loads were highly variable and that the reductions in the annual load of biochemical oxygen demand (BOD), suspended solid (SS), total nitrogen (T-N), total phosphorus (T-P), and total organic carbon (TOC) in the Test compared to that of the Control were 31.0 ± 28.9%, 83.5 ± 11.8%, 65.4 ± 12.2%, 69.1 ± 21.7%, and 64.9 ± 12.9%, respectively. It was shown that discharge in the post-harrowing and transplanting drainage (HD) was predominantly responsible for the total loads; therefore, the load reduction in HD was evaluated further at additional sites. The reduction at all studied sites was highly variable and as follows: 30.0 ± 33.6%, 70.9 ± 24.6%, 32.2 ± 45.5%, 45.7 ± 37.0%, and 27.0 ± 71.5%, for BOD, SS, T-N, T-P, and TOC, respectively. It was also demonstrated that controlled drainage contributed significantly to reducing the loads and volume of stormwater runoff from paddy fields. Correlations between paddy field conditions and multiple regression showed that the loads were significantly related to paddy water quality. The results of this study strongly suggest that controlled drainage is an excellent alternative for reducing the discharge of NPS pollutants from paddy fields. It is also suggested that the best discharge control would be achieved by combinations of various discharge mitigation alternatives, such as the management of irrigation, drainage, and fertilization, as well as drainage treatment, supported by more field tests, identification of the fates of pollutants, effects of rainfall, and climate changes. Full article