Search Results (29)

Precipitation is central to the global hydrological cycle, and its accurate monitoring is vital for preventing meteorological disasters. Traditional satellite retrieval methods fail to model nonlinear relationships and adapt to regional heterogeneity. Using China’s new-generation geostationary satellite FY-4B/AGRI, this study develops a two-step machine learning model—separating precipitation identification from intensity estimation—for the complex terrain of Anhui Province and further conducts experiments in the Huaibei Plain, Jianghuai Hills, and Jiangnan mountainous areas. This design separately addresses precipitation occurrence and rainfall intensity, which represent distinct classification and regression tasks. The model takes 37 features as input, including multispectral brightness temperatures, brightness temperature differences, spatiotemporal cloud-top temperature dynamics, secondary cloud parameters, and terrain. For identification, XGBoost at a 1:4 precipitation/non-precipitation ratio performed best, with POD, FAR, CSI, and ETS of 0.6961, 0.3676, 0.4956, and 0.4422, outperforming the FY-4B QPE product (0.5876, 0.5703, 0.3301, 0.2607). Subregional modeling further improved CSI to 0.4716, 0.5186, and 0.5210 for the three areas. For rainfall estimation, XGBoost trained with the original precipitation class ratio was optimal in all subregions, markedly surpassing the QPE product. Spatial aggregation of the three regional models yielded a correlation coefficient of 0.5304 and RMSE of 0.6274 mm, outperforming the unified model and QPE during the study period. This study provides a useful machine learning approach for precipitation retrieval, and the results demonstrate the efficacy of incorporating regional heterogeneity into machine-learning-based precipitation retrieval, leading to enhanced precipitation estimation during the June–July 2024 Meiyu period over Anhui Province. Full article

Groundwater quality remains insufficiently characterized in the rural agriculture–residential interface of the Huaibei Plain, particularly with respect to nitrate (NO₃⁻) occurrence, hydrochemical controls, source contributions, and population-specific health risks. In this study, multivariate statistical analysis, source apportionment models, and health risk assessment models were applied to investigate the hydrochemical characteristics of groundwater and related non-carcinogenic risks to different populations. NO₃⁻ content exceeded the World Health Organization (WHO) guidelines for drinking water in 60.0% and 62.5% of wet- and dry-season groundwater, respectively. Groundwater NO₃⁻ was mainly influenced by agricultural non-point inputs and domestic sewage, whereas major-ion composition was primarily governed by water–rock interactions. Our deterministic health risk assessment model reveals that the hazard index (HI) exceeded the acceptable threshold of 1.0 in 76.25%, 65.00%, 66.25%, and 56.25% of groundwater samples for infants, children, adult females, and adult males, respectively. These results indicate that continuous monitoring, improved sewage collection, and more controlled nitrogen management are required in the rural agricultural–residential interface of the Huaibei Plain with regard to shallow domestic groundwater. Full article

Rapid urbanization imposes significant pressure on riverine water environments, yet the evolution of hydrochemical characteristics and dissolved organic matter (DOM) in rivers across urbanization gradients within developing regions, such as the Huaibei Plain, remains inadequately understood. Thus, this study investigates the hydrochemical and DOM characteristics of rivers across distinct urbanization gradients (suburban, peri-urban, and urban) in this area. Using an excitation–emission matrix coupled with a parallel factor analysis (EEM-PARAFAC) and hydrochemical analyses, we found that while rock weathering is the primary major ion source, human activities distinctly alter water profiles. Agriculturally dominated suburban rivers had significantly higher nitrate (NO₃⁻) concentrations than those in urban and peri-urban rivers. Their DOM was predominantly humic-like (C1, C3) with a high humification index (HIX), indicating a substantial input of soil-derived humic substances driven by runoff from the agricultural catchment. Conversely, urban and peri-urban rivers exhibited higher chloride (Cl⁻) concentrations due to domestic sewage. Their DOM was dominated by protein-like components (C2 and C4, averaging 65–68%), with high biological indices (BIX) reflecting autochthonous origins. Correlation analysis confirmed these anthropogenic impacts: NO₃⁻ positively correlated with humic-like components and HIX, while Cl⁻ strongly correlated with protein-like components. These findings confirm that DOM components and spectral indices are effective tracers of anthropogenic disturbance and hold promise for monitoring and predicting water quality, thus providing a scientific basis for improved water resource management and restoration strategies. Full article

Controlled drainage technology in farmland not only raises groundwater levels to provide additional water directly to crops but also improves rainfall utilization efficiency, thereby helping to alleviate agricultural water scarcity. In 2002, a large-scale field research area covering 80 km² was established and equipped with controlled sluices, a weather station, groundwater observation wells, and monitoring gauges. An analysis of the impacts of controlled projects on water levels in the main drainage ditches, groundwater dynamics, drainage processes, and overall water resource regulation showed that the average water storage capacity in the main ditches increased to 1.14 m, the groundwater level rose by 0.64 m, and the total volume of water regulated through the sluice control project ac-counted for approximately 10% of the annual precipitation. Therefore, implementing controlled drainage in main ditches for agricultural water resource regulation represents an effective strategy suited to the characteristics of the Huaibei Plain. This approach not only mitigates water scarcity but also enhances the farmland ecological environment and supports the rational spatiotemporal allocation of regional water resources. Moreover, it provides valuable insights for other regions facing similar challenges. Full article

Natural wetland loss constitutes a primary threat to waterbirds worldwide, increasingly forcing them to rely on expanding artificial wetlands. Extensive underground coal mining across the North China Plain has created numerous subsidence wetlands, which could serve as important alternative habitats for migratory and wintering waterbirds. However, the effects of different management regimes on waterbirds in these novel artificial wetlands remain poorly understood, hindering effective strategies for reconciling human development with waterbird conservation. Here, we conducted a long-term field survey (2017–2025) of wintering waterbirds across 15 subsidence wetlands under four distinct human management regimes in the Huaibei coal mining area. We recorded 22,712 waterbirds of 45 species. We found that high-intensity aquaculture and floating photovoltaic systems were associated with reduced waterbird diversity, increased community dissimilarity, altered species composition, and the loss of multiple threatened species from survey records. We also found that ecological aquaculture and unutilized wetlands may serve as favorable habitats as alternatives to natural wetlands. Our findings demonstrate that subsidence wetlands can provide vital wintering habitats when managed sustainably, but intensive development severely compromises their conservation value. Future research should integrate habitat variables and year-round surveys to optimize management strategies for these expanding artificial ecosystems. Full article

Understanding the characteristics of groundwater chemistry is essential for water resource development and utilization. However, few studies have focused on the chemical evolution processes of shallow groundwater in typical areas of the Huaibei Plain. We analyzed 28 water samples from the study area using hydrogeochemical mapping, multivariate statistical analysis, and other approaches. The study found that the hydrogeochemical facies of groundwater are mainly HCO₃-Ca·Mg (64.3%), mixed SO₄·Cl-Ca·Mg, and SO₄·Cl-Na. The hydrochemical composition is primarily controlled by natural water–rock interactions, including carbonate weathering and cation exchange processes. Correlation analysis and principal component analysis (PCA) revealed that mineral dissolution was the predominant source of Na⁺, Mg²⁺, Cl⁻, and SO₄²⁻ in shallow groundwater, significantly contributing to total dissolved solids (TDS) accumulation. Hierarchical cluster analysis (HCA) identified three characteristic zones: (1) agricultural/urban-influenced areas, (2) high-F⁻/low-hardness zones, and (3) nitrate-contaminated regions. These findings provide critical insights for assessing the geochemical status of groundwater in the Huaibei Plain and formulating targeted resource management strategies. Full article

Agricultural droughts are a threat to local economies, as they disrupt crops. The monitoring of agricultural droughts is of practical significance for mitigating loss. Even though satellite data have been extensively used in agricultural studies, realizing wide-range, high-resolution, and high-precision agricultural drought monitoring is still difficult. This study combined the high spatial resolution of unmanned aerial vehicle (UAV) remote sensing with the wide-range monitoring capability of Landsat-8 and employed the local average method for upscaling to match the remote sensing images of the UAVs with satellite images. Based on the measured ground data, this study employed two machine learning algorithms, namely, random forest (RF) and eXtreme Gradient Boosting (XGBoost1.5.1), to establish the inversion models for the relative soil moisture. The results showed that the XGBoost model achieved a higher accuracy for different soil depths. For a soil depth of 0–20 cm, the XGBoost model achieved the optimal result (R² = 0.6863; root mean square error (RMSE) = 3.882%). Compared with the corresponding model for soil depth before the upscaling correction, the UAV correction can significantly improve the inversion accuracy of the relative soil moisture according to satellite remote sensing. To conclude, a map of the agricultural drought grade of winter wheat in the Huaibei Plain in China was drawn up. Full article

With global climate change, flooding events are becoming more frequent. However, the mechanism of how waterlogging stress affects crop roots needs to be studied in depth. Waterlogging stress can also lead to soil nitrogen and phosphorus loss, resulting in agricultural surface pollution. The aim of this study is to clarify the relationship between soil nitrogen and phosphorus distribution, root growth characteristics, and nitrogen and phosphorus loss in runoff water under waterlogging stress during the winter wheat seedling stage. In this paper, Zhengmai 136 was selected as the experimental material, and two water management methods (waterlogging treatment and non-waterlogging control treatment) were set up. Field experiments were conducted at the Wudaogou Hydrological Experimental Station in 2022 to assess the nitrogen and phosphorus concentrations in runoff water under waterlogging stress. The study also aimed to analyze the nitrogen and phosphorus content and the root distribution characteristics in different soil layers under waterlogging stress. The results showed as the following: 1. Waterlogging stress increased the characteristic parameters of winter wheat roots in both horizontal and vertical directions. Compared with the control treatment, the root length increased by 1.2–29.9% in the waterlogging treatment, while the root surface area and volume increased by an average of 3.1% and 41.9%, respectively. 2. Nitrogen and phosphorus contents in waterlogged soils were enriched in the 0–20 cm soil layer, but both tended to decrease in the 20–60 cm soil layer. Additionally, there was an inverse relationship between the distribution of soil nutrients and the distribution of wheat roots. 3. During the seedling stage of winter wheat, nitrogen loss was the main factor in the runoff water. In addition, nitrate nitrogen concentration averaged 55.2% of the total nitrogen concentration, while soluble phosphorus concentration averaged 79.1% of the total phosphorus concentration. 4. The results of redundancy analysis demonstrated that available phosphorus in the soil was the key environmental factor affecting the water quality of runoff water. Total phosphorus and dissolved phosphorus in the water were identified as the dominant factors influencing root growth. Full article

To further quantitatively assess the water resources carrying capacity (WRCC) system and analyze and identify the regional water resources carrying state and the physical mechanism of the state change, WRCC and obstacle factor diagnosis were carried out. In this paper, we proposed the mobility matrix to determine the connection number components, considered the dynamic attributes of the difference degree coefficient, and calculated it using the semi-partial subtraction set pair potential and triangular fuzzy number, so as to construct the quantitative diagnosis method of regional WRCC obstacle factors based on the connection number and TOPSIS. The results applied to six cities in the Huaibei Plain showed that the WRCC fluctuated around grade 2 and was in a poor state, which was mainly due to the insufficient support force; the water resources carrying state of the six cities gradually improved from 2011 to 2018, but the state became worse in 2019, which was related to the low precipitation in that year, the reduction in water resources, and the high degree of water resource utilization. The WRCC of Fuyang and Huainan was worse than that of the other four cities; over the 9 years, the average grades of Fuyang and Huainan were 2.26 and 2.43, while those of Huainan, Bozhou, Suzhou, and Bengbu were 2.19, 2.12, 2.05, and 2.05, respectively. The key obstacles limiting the improvement in the WRCC of the Huaibei Plain were per capita water resources, annual water production modulus, per capita water supply, vegetation coverage ratio, utilization ratio of water resources, water consumption per 10⁴ yuan value-added by industry, and population density. In time, the key obstacle factors in neighboring years generally tended to have similarity, and conversely appeared as a difference; in space, neighboring regions showed similarity and conversely presented as a difference. The results of this study can offer technical support and a decision-making basis for water resources management in the Huaibei Plain. The method constructed in this paper is extremely interpretive, easy to calculate, highly sensitive, and reliable in application results, which opens up a new perspective for the rational determination of the connection number and the difference degree coefficient and provides a new intelligent way to determine the state of a complex set pair system and its causal mechanism analysis and diagnosis of obstacle factors. Full article

The frequency of heat events is likely to increase due to global climate change, posing an increasing risk to wheat production. To optimize crop management strategies for coping with future climates, it is crucial to quantify the high-temperature occurrence during cropping seasons. Here, sixty-six years (1955~2020) of meteorological data during wheat reproductive growth were collected from six meteorological stations in the Huaibei Plain of Anhui Province. These data were analyzed to quantify the pattern and characteristics of post-anthesis heat stress for wheat crops. Five levels of annual mean daily maximum temperature (Tmax) were defined, from normal to extreme temperatures. Six crop developmental phases of winter wheat, i.e., phase i to phase vi, were divided from flowering to maturity. The data suggest an annual mean temperature of 17~24 °C from flowering to maturity, with an annual effective cumulative temperature ranging from 725 °C d to 956 °C d. The mean temperature and effective cumulative temperature increased as crop growth progressed, along with more frequent heat events during phase ii (8~14 days after anthesis) and phase iii (15~21 days after anthesis). We also found that the frequency of extremely high temperatures (≥33 °C) from 1990 to 2020 was significantly greater than that from 1957 to 1990. Interestingly, it was found that the intensity of post-anthesis night temperatures also increased with crop growth, i.e., from phase i to phase vi. Wheat grain yield increased with increasing effective accumulative temperature and Tmax, but it started to decline when thresholds of effective accumulative temperature and Tmax were reached. Overall, these findings could provide guidelines for winter wheat cropping in the Huaibei Plain, China, or similar climate and cropping regions. Full article

The drainage modulus is an important indicator in the drainage system design of farmlands. Changes in the drainage modulus determine the effectiveness of drainage projects, and thus agricultural production. Thus, in this research, the trends in the drainage modulus of the Huaibei Plain, China were examined. The drainage modulus was estimated using the average draining method at 16 meteorological stations located in different areas of the Huaibei Plain during the period of 1960–2017. The trends of the drainage modulus were investigated using the Mann–Kendall test and Sen’s slope estimator. The periodicities of the drainage modulus were investigated using wavelet analysis. The major environmental factors affecting the drainage modulus were investigated using the contribution rate method. The results showed that the mean drainage modulus (q₁, q₃) had increasing trends and significant 2.4-year and 2.5-year periodicities, respectively. An increase in building lots was the main factor that influenced the variability in the drainage modulus. Rapid urbanization increased the risk of agricultural waterlogging. These results provide important references for scientific planning in agriculture and farmland drainage engineering. Full article

Damage from climate change is widespread throughout the world. This change has brought about calamities, the most prevalent of which is the emergence of numerous droughts which are increasingly threatening human lives. In this paper, we studied the spatial and temporal variations of drought under the effect of climate change in the Huaibei Plain, which is a very important agricultural zone in China. Drought has attracted increasing attention in research due to its heavy impact on agriculture, the environment, livelihood, and food security. The SPEI (Standardized Precipitation Evapotranspiration Index) has been used in this study to express and identify drought events in the Huaibei Plain due to climate change. A general circulation model (GCM), HadGEM2-AO, which was the most appropriate for the study area’s precipitation simulation, and three Representative Concentration Pathways (RCP), RCP 2.6, RCP 4.5, and RCP 8.5, were used to analyze and compare the drought effect for the baseline (1985–2017) and the future climate scenarios (2025–2090). At 3 and 6 months, the SPEI successfully detects agricultural drought in temporal and spatial variation. However, according to the analysis, more severe agricultural drought events are foreseen in the future than in the baseline because of climate change. SPEI performed better than SPI in detecting drought in the baseline and simulated data due to increased evapotranspiration. Between the SPEI-3 and SPEI-6, the Pearson coefficient correlation reveals a positive association. The Mann-Kendall test was used to cover the two studied periods in order to establish the drought trend. Both decreasing and increasing trends, in different timescales, were detected by Sen’s Slope in the baseline and future periods with all RCPs. Full article

Construction of an integrated drought index is a fundamental task to conducting drought disaster risk management and developing drought resistance planning strategies. Given the evident non-consistent features during the drought evolution process, firstly, the GAMLSS approach was utilized to construct multiple combination scenarios of time-variant parameters and corresponding probability distribution functions. Then, the time-variant comprehensive drought index integrating the variable characteristics of precipitation and soil moisture was established by means of the copula function. Finally, the reliability of the time-variant comprehensive drought index was verified through its application in frequency analysis and return period determination of drought hazard system in Huaibei Plain, China. The application results demonstrated that: (1) The variation of the time-variant integrated drought indicator presented strong consistency with both soil moisture and precipitation during historical years in Huaibei Plain. (2) The overall variation of the drought hazard system characterized by drought duration and severity presented a gradual mitigation trend from west to east and north to south in Huaibei Plain, which agrees with the geographic differences and water resources availability distribution features. (3) Drought recognition results, including the frequency of drought events and typical drought processes with extreme grades, are in agreement with the practical statistics and observed data series. On the whole, the proposed time-variant integrated drought indicator is capable of extracting complex variation characteristics within the drought hazard evolution process, and can be further applied in drought monitoring, recognition and assessment research fields. Full article

The purpose of this study was to explore the effective prevention and control method of ground fissures in plain coal mining subsidence. Firstly, the model experiment was carried out, and then two typical working faces, working face A (WF_A) and working face B (WF_B), in the Huaibei plain mining area were selected for the case study of the moisturization method. Model experimental results show that water content had a significant effect on cohesive soil fissure development, and the results of the case study show that the humidification method could effectively reduce the development degree of ground fissures. Therefore, this study provided a new approach for the effective prevention and control of ground fissures in plain coal mining subsidence. Full article

Groundwater contributes to the delivery of phreatic water to crop aeration zones via evapotranspiration, which is important for crop growth in drought-prone regions. Most studies on groundwater contribution have not considered the influence of crop growth stage or daily evapotranspiration. In this study, a neural network based on a genetic algorithm and the Levenberg–Marquardt backpropagation algorithm, as well as formula methods based on an accelerated genetic algorithm, were built to assess soybean groundwater contribution; in addition, a performance comparison was conducted. The results indicated that machine learning had the best performance for fitting errors, with values for relative mean error (RME), root mean square percentage error (RMSPE), and correlation coefficient of 1.088, 2.165, and 0.762, respectively; in addition, for validation errors, it had values for RME, RMSPE, and correlation coefficient of 1.069, 2.136, and 0.735, respectively. The machine learning method is recommended for readers seeking to calculate groundwater contribution. Full article