Yanbin Li

This study presents a comprehensive bibliometric analysis of the DSSAT crop modeling field from 1990 to 2024, identifying its evolutionary trajectory and emerging frontiers. A comprehensive bibliometric analysis and network visualization were conducted using VOSviewer, CiteSpace, and Bibliometrix. Analyzing 6165 Scopus-indexed publications, we found the research focus has shifted from foundational yield simulation and calibration toward addressing complex climate-water-food challenges. Three distinct developmental phases were identified: an initial establishment phase, a methodological refinement phase, and a current technology integration phase dominated by machine learning and remote sensing applications. The results reveal that machine learning, model-data fusion, and sustainability assessment represent the most active research frontiers. This analysis provides a systematic map of the field’s intellectual structure and offers evidence-based predictions for its future development, highlighting the transition of DSSAT from a specialized crop model to an interdisciplinary decision-support platform for sustainable agriculture.

The Gravity Recovery and Climate Experiment (GRACE) tracks drought events by detecting changes in the global gravitational field and capturing abnormal information on the reserves of surface water, soil water, and groundwater, which makes it possible for a more comprehensive and unified global and regional monitoring of groundwater drought. This study adopted the gravity satellite GRACE data and combined it with the hydrological model dataset. Additionally, we assessed the temporal evolution and spatial pattern of groundwater drought in the Yangtze River Basin (YRB) and its sub-basins from 2003 to 2022, determined the change points of the hidden seasonal and trend components in groundwater drought, and identified the direct/indirect driving contributions of the main climatic and circulation factors to groundwater drought. The results show that (1) as a normalized index, the groundwater drought index (GDI) can reflect direct evidence of any surplus and deficit in groundwater availability. During the study period, the minimum value (−1.66) of the GDI occurred in July 2020 (severe drought). (2) The average value of GDI in the entire basin ranged from −1.66 (severe drought) to 0.52 (no drought). (3) The average Z_s values (Mann–Kendall Z-statistic) of GDI were −0.23, −0.16, −0.43, and 0.14, respectively, and the proportions of areas with aggravated drought reached 65.21%, 61.05%, 89.70% and 43.67%, respectively. (4) Partial wavelet coherence analysis can simultaneously reveal the local correlations of time series at different time scales and frequencies. Based on partial wavelet analysis, precipitation was the best factor for explaining the dynamic changes in groundwater drought. (5) The North Pacific Index (NPI), the Pacific/North American Index (PNA), and the Sunspot Index (SSI) can serve as the main predictors that can effectively capture the drought changes in groundwater in the YRB. The GRACE satellite can provide a new tool for monitoring, tracking, and assessing groundwater drought situations, which is of great significance for guiding the development of the drought early warning system in the YRB and effectively preventing and responding to drought disasters.

Under the extensive influence of the monsoon climate, droughts in the Yangtze River Basin (YRB) occur frequently and pose a serious threat to grain security. To better understand the evolution and drivers of soil drought, this study employed remote sensing-based soil moisture and atmospheric circulation data from 2000 to 2022. It assessed the spatiotemporal characteristics of soil drought across the YRB and its sub-basins, identified the main mutation points and types, and quantified the relative contributions of climatic and circulation factors. The results show that: (1) the most severe soil drought month occurred in August 2022 (Standardized Soil Moisture Index SSMI = –1.69), with two major mutation points in May 2011 (“decrease to increase”) and June 2019 (“increase to decrease”); (2) drought mutations were mainly categorized as “interrupted decrease” (9 sub-basins) and “increase to decrease” (1 sub-basin), most occurring after 2010; (3) the year 2022 experienced the most severe annual drought (SSMI = –0.94), with extreme drought covering 39.36% of the basin in August; (4) precipitation (PC) was the dominant climatic factor influencing drought (percentage area of significant coherence PASC = 15.48%), while the Interannual Pacific Oscillation (IPO), Pacific Decadal Oscillation (PDO), and Dipole Mode Index (DMI) all showed significant remote-correlation effects, with mean Shapley additive explanations (SHAP) values of 0.138, 0.111, and 0.090, respectively. This study clarifies the spatiotemporal patterns and drivers of soil drought in the YRB, providing a scientific basis for improved drought monitoring and agricultural risk management.

Terrestrial water storage includes soil water storage, groundwater storage, surface water storage, snow water equivalent, plant canopy water storage, biological water storage, etc., which can comprehensively reflect the total change in water volume during processes such as precipitation, evapotranspiration, runoff, and human water use in the basin hydrological cycle. The Gravity Recovery and Climate Experiment (GRACE) satellite provides a powerful tool and a new approach for observing changes in terrestrial water storage and groundwater storage. The North China Plain (NCP) is a major agricultural region in the northern arid area of China, and long-term overexploitation of groundwater has led to increasingly prominent ecological vulnerability issues. This study uses GRACE and Global Land Data Assimilation System (GLDAS) hydrological model data to assess the spatiotemporal patterns of groundwater drought in the NCP and its various sub-regions from 2003 to 2022, identify the locations, occurrence probabilities, and confidence intervals of seasonal and trend mutation points, quantify the complex interactive effects of multiple climate factors on groundwater drought, and reveal the propagation time from groundwater drought to agricultural drought. The results show that: (1) from 2003 to 2022, the linear tendency rate of groundwater drought index (GDI) was −0.035 per 10 years, indicating that groundwater drought showed a gradually worsening trend during the study period; (2) on an annual scale, the most severe groundwater drought occurred in 2021 (GDI = −1.59). In that year, the monthly average GDI in the NCP ranged from −0.58 to −2.78, and the groundwater drought was most severe in July (GDI = −2.02); (3) based on partial wavelet coherence, the best univariate, bivariate for groundwater drought were soil moisture (PASC = 19.13%); and (4) in Beijing, Tianjin and Hebei, the propagation time was mainly concentrated in 1–5 months, with average lag times of 2.87, 3.20, and 2.92 months, respectively. This study can not only reduce and mitigate the harm of groundwater drought to agricultural production, social life, and ecosystems by monitoring changes in groundwater storage, but also provide a reference for the quantitative identification of the dominant factors of groundwater drought.

Ecological drought in terrestrial systems is a vegetation-functional degradation phenomenon triggered by the long-term imbalance between ecosystem water supply and demand. This process involves nonlinear coupling of multiple climatic factors, ultimately forming a compound ecological stress mechanism characterized by spatiotemporal heterogeneity. Based on meteorological and remote sensing datasets from 1982 to 2022, this study identified the spatial distribution and temporal variability of ecological drought in China, elucidated the dynamic evolution and return periods of typical drought events, unveiled the scale-dependent effects of climatic factors under both univariate dominance and multivariate coupling, as well as deciphered the response mechanisms of ecological drought to meteorological drought. The results demonstrated that (1) terrestrial ecological drought in China exhibited a pronounced intensification trend during the study period, with the standardized ecological water deficit index (SEWDI) reaching its minimum value of −1.21 in February 2020. Notably, the Alpine Vegetation Region (AVR) displayed the most significant deterioration in ecological drought severity (−0.032/10a). (2) A seasonal abrupt change in SEWDI was detected in January 2003 (probability: 99.42%), while the trend component revealed two mutation points in January 2003 (probability: 96.35%) and November 2017 (probability: 43.67%). (3) The drought event with the maximum severity (6.28) occurred from September 2019 to April 2020, exhibiting a return period exceeding the 10-year return level. (4) The mean values of gridded trend eigenvalues ranged from −1.06 in winter to 0.19 in summer; 87.01% of the area exhibited aggravated ecological drought in winter, with the peak period (88.51%) occurring in January. (5) Evapotranspiration (ET) was identified as the dominant univariate driver, contributing a percentage of significant power (POSP) of 18.75%. Under multivariate driving factors, the synergistic effects of ET, soil moisture (SM), and air humidity (AH) exhibited the strongest explanatory power (POSP = 19.21%). (6) The response of ecological drought to meteorological drought exhibited regional asynchrony, with the maximum correlation coefficient averaging 0.48 and lag times spanning 1–6 months. Through systematic analysis of ecological drought dynamics and driving mechanisms, a dynamic assessment framework was constructed. These outcomes strengthen the scientific basis for regional drought risk early-warning systems and spatially tailored adaptive management strategies.

This research investigates the influence of water–nitrogen coupling on soil water content, nitrogen dynamics, and root distribution in farmland, along with the interactions among soil water, nitrogen transport, root distribution, and crop yield. A field experiment was conducted under moderate drought stress (50–60% of field capacity) and three nitrogen application rates (100, 200, and 300 kg·ha⁻¹, split-applied at 50% during sowing and 50% at the jointing stage, labeled as N₁, N₂, and N₃) at the two critical growth stages (jointing stage P₁ and tasseling-silking stage P₂) of maize (Denghai 605). The results demonstrated that maize root morphological parameters exhibited the trend N₂ > N₁ > N₃ under different nitrogen treatments. Compared to N₂, low nitrogen (N₁) decreased root morphological parameters by 35.01–49.60% on average, whereas high nitrogen (N₃) led to a reduction of 49.93–61.37%. The N₂ treatment consistently maintained greater water uptake, with the highest yield of 13,336 kg·ha⁻¹ observed under the CKN₂ treatment, representing increases of 16.1% and 9.2% compared to the P₁N₂ and P₂N₂ treatments, respectively. Drought stress at the jointing stage (P₁) inhibited root development more severely than at the tasseling-silking stage (P₂), demonstrating a bidirectional adaptation strategy characterized by deeper vertical penetration under water stress and increased horizontal expansion under nitrogen imbalance. Correlation analysis revealed a positive correlation between soil nutrient content and maize yield indicators. At the same time, root characteristic values were significantly negatively correlated with yield (p < 0.05). Appropriate water–nitrogen management effectively stimulated root growth, mitigated nitrogen leaching risks, and improved yield. These findings offer a theoretical foundation for optimizing water and nitrogen management in maize production within the Yellow River Basin.

In recent years, the increasing frequency of extreme rainfall has exacerbated urban waterlogging, which has seriously constrained the sustainable development of cities. Given the problem that the impact of social information on waterlogging risk is easy to ignore in the urban risk waterlogging assessment process, it is of great significance to carry out a comprehensive waterlogging risk assessment and identify the waterlogging risk for urban waterlogging prevention and control. Based on the hazard–vulnerability assessment framework, this study comprehensively considers the flood disaster hazard and socio-economic vulnerability to carry out a multi-scenario urban waterlogging risk assessment in the central urban area of Zhoukou. The results show that, in comprehensive risk assessment, the area proportions are expressed as medium risk > low risk > higher risk > high risk. For a single waterlogging hazard assessment, the area proportions are shown as low risk > medium risk > higher risk > high risk. The difference ranges in area proportions of low, medium, higher, and high risk are (−61.00%, −54.00%), (49.00%, 56.00%), (1.30%, 2.70%), and (1.80%, 4.00%), respectively. It can be seen that compared with the single waterlogging hazard assessment, in the comprehensive waterlogging risk assessment with the introduction of the vulnerability factor, the waterlogging risk in the area with highly waterlogging vulnerability increases correspondingly, while the waterlogging risk in the area with low waterlogging vulnerability decreases relatively, and the waterlogging risk assessment results are more in line with the actual situation.

The combined effects of tillage and organic amendments on microbial respiration and its contribution to soil hydraulic conductivity are still uncertain in the 0–40 cm layer of a loess soil. We conducted a two-year field experiment to explore the effects of organic amendments, tillage and their interaction on soil microbial respiration, aggregate stability, pore parameters, and hydraulic conductivity on the Loess Plateau. Three tillage methods (conventional tillage (CT), deep tillage (DT) and no tillage (NT)) plus five fertilizer treatments (mineral fertilizer (control) alone and along with 20 t ha⁻¹ wheat straw (MWS), wheat husk (MWH), farmyard soil (MFS) and bioorganic fertilizer (MBF)) were set up as experimental treatments. The findings demonstrated that the organic amendments significantly increased the soil microbial respiration and saturated hydraulic conductivity compared to the control in the 0–10 cm and 10–20 cm layers. Soil microbial respiration had indirect effects on hydraulic conductivity by improving the water aggregate stability and macroporosity. Additionally, the interaction effects of tillage and organic amendments on the pore and hydrological parameters were significant in the 20–40 cm layer. NT-MBF resulted in the greatest saturated hydraulic conductivity, which was directly correlated with the soil’s strong pore organization. Given the issue of subsurface soil compaction in our study area, it is recommended that local farmers adopt NT-MBF to enhance the soil’s microbial, structural and hydrological properties.

In the context of water scarcity, understanding the mechanisms influencing and altering agricultural water consumption can offer valuable insights into the scientific management of limited water resources. Using Henan Province as a case study, this research applies the Mann–Kendall test method, the spatial Markov transfer chain model, the optimal parameter geo-detector model, and the Logarithmic Mean Divisia Index (LMDI) decomposition method to investigate the evolution characteristics of agricultural water consumption in Henan Province and its key influencing factors. The findings revealed the following: (1) Agricultural water consumption has shown a significant decline from 1999 to 2022. (2) According to observations, the stability of agricultural water consumption exceeds the spillover effect, and cross-border grade transfer is challenging. Moreover, this phenomenon is influenced by the neighboring regions. (3) The key influencing factors of added agricultural value are the sown area of food crops, total sown area, irrigated area, and average annual air temperature. (4) Among the decomposition effects on agricultural water consumption, the contribution of each decomposition effect to changes in agricultural water consumption and the role of spatial distribution exhibit notable differences. Overall, these findings provide theoretical references for the efficient use of agricultural water resources and sustainable development in the region.

With the constant advancement of irrigation technology and the continuous expansion of irrigation areas, non-point source pollution (NPS) caused by agricultural activities has posed a persistent threat to ecosystems and biological safety. Against this backdrop, it is imperative to lay scientific foundations for green, sustainable, and high-quality agricultural development through a thorough review of the relevant research progress. In this study, bibliometric methods are adopted to comprehensively analyze and visualize the current state and key literature on agricultural irrigation and NPS pollution from 2010 to July 2024. The focus of this study is specifically on summarizing the research hotspots and development trends of different irrigation methods and the mechanisms behind their impacts on NPS pollution. The results indicate that publications from the United States and China account for 63.8% of the total, but the fragmentation of research efforts remains, suggesting a necessity to strengthen international and regional collaboration. There are three institutions with the highest publication output, namely Northwest A&F University, Hohai University, and the Chinese Academy of Sciences. The subjects identified as the key areas of research on irrigation-related NPS pollution (IRR-NPS) include precision irrigation, rapid water pollution response, spatiotemporal management, interdisciplinary integration, wastewater treatment, and crop models. Regarding future research, it is necessary to focus attention on real-time precision irrigation, standardized crop models, data accuracy, spatiotemporal pollution coordination, pollution purification technology development, interdisciplinary integrated governance, and the innovative applications of soil improvement technologies. In addition to offering theoretical support and practical guidance for the management of agricultural NPS pollution, this study also provides management and technical support for policymakers, which is beneficial for advancing agricultural irrigation technology and environmental preservation.