ObjectiveUrbanization has resulted in the occupation of gentle-slope cultivated land, whereas newly added cultivated land is concentrated on steeper slopes. As a major grain-producing province, it is of great significance to explore the evolution of cultivated land slope to ensure cultivated land quality and food security. MethodsBased on multi-source data from 1990 to 2020, this study employed methods including slope spectrum curve, slope index, and geodetector to analyze the upward trend of cultivated land slope and the occupation-compensation characteristics under different slope gradients, and to quantitatively identify the key driving factors. Results1) The proportion of cultivated land with a slope > 15° in the province increased by 0.55%. The slope of newly added cultivated land was consistently higher than that of lost cultivated land. The proportion of areas with "significant upward-sloping" was the highest during 2000–2005 (55.13%), which was mainly concentrated in Zone Ⅲ-4-1xt and Zone Ⅲ-4-2t. 2) The net change rate of cultivated land remained negative, with the highest intensity of construction occupation. Specifically, the proportion of cultivated land with a slope > 2°−6° occupied by construction reached 27.95%, and this phenomenon was most prominent in Zone Ⅲ-5-3fn. Gained cultivated land was mainly from the reclamation of forestland and grassland, with the proportion of supplementation in the > 6°−15° slope range accounting for up to 10.17%. The proportion of cultivated land gained from other reclamation was relatively high in Zone Ⅲ-5-2w. 3) Among single driving factors, precipitation had the strongest explanatory power (q = 0.201), followed by GDP (q = 0.164) and human activity intensity (q = 0.153). Two-factor interactions exhibited an enhancement effect. In Zone Ⅲ-5-3fn, the interaction between distance to roads and human activity intensity was relatively strong, while in other zones, the interaction between precipitation and human activity intensity exerted a dominant influence. ConclusionsThis study confirms that the upward-sloping phenomenon of cultivated land in Shandong province is the result of the synergistic effects of natural and anthropogenic factors, thereby providing a scientific basis for optimizing the cultivated land protection pattern from the perspective of slope.

Single-cropping rice dominates rice production in China, yet its regional differences and long-term variability in net irrigation water requirements (RIWR) remain poorly characterized at the national scale. This study estimates RIWR from 1951 to 2023 across five major rice-producing regions using a water balance method with the Penman-Monteith formula as the core meteorological component. Wavelet and time-frequency analyses are used to investigate the periodic variability of RIWR and its associated meteorological and circulation factors. Future changes are projected under SSP2-4.5 and SSP5-8.5 scenarios to quantify potential shifts in irrigation demand. Results show substantial temporal and spatial variations in RIWR. National annual averages ranged from 524.6 to 791.5 mm and declined by 0.93 mm/yr on average, being above the long-term mean between 1951 and 1980, below it from 1981 to 2000, and alternating from 2001 to 2023. Regionally, the variation range of RIWR follows Northeast > Central China > East China > South China > Southwest, with province-level values spanning 315.0-1250.1 mm/yr. RIWR exhibits an alternating pattern across regions, with high periods in Northeast China corresponding to low periods in South China, and vice versa. Cycles with periods of 15-25 years dominate RIWR variability, with interregional phase differences (i.e., differences in the phase of these same-frequency cycles) of up to 180 degrees, contributing to spatial heterogeneity. Using the proposed time-frequency approach, effective precipitation, sunshine duration, maximum air temperature, and relative humidity were identified as the primary meteorological drivers, confirmed by sensitivity analysis, with relative influences varying across regions. Future projections suggest the historical decline in RIWR may slow or reverse in some regions. Taken together, these findings underscore the importance of accounting for spatial, temporal, and frequency-domain variations when planning adaptive irrigation strategies.

Analyzing the impact of multiple water-blocking structures, such as bridge piers and wharf piles, on flood discharge is challenging due to difficulties in simulating large-scale scenarios and a lack of empirical methods. Based on the increased roughness, this paper presents an empirical approach to quickly estimate the reduction in flood discharge caused by pier groups. The increased roughness arises primarily from two types of water flow energy loss: (1) the loss due to drag force induced by pier groups; and (2) the loss due to the reduction in flow cross-sectional area at the bridge pier locations. The method for estimating equivalent roughness employs the Manning and Chezy formulas and a multiparameter formula, which includes coefficients for resistance, shielding influence, interference influence, and skew. A case study demonstrates that bridge bundling led to a 14.8% decrease in river flood discharge, offering practical insights for improving flood management strategies.

China faces severe water scarcity, but the gradual implementation of irrigation management informatization (IMI), evolving from basic systems to AI-driven digital twin technologies, is helping alleviate this issue by improving water use efficiency. This study aims to enhance the understanding of IMI by documenting its development history since the country's founding, ensuring that future research can build upon past advancements. To achieve this goal, this study explores the evolution of IMI in China, from basic data collection to the integration of advanced technologies such as AI and digital twins, highlighting the parallel development of policies and technologies. It emphasizes the synergy between policy-driven technological advancement and technology-driven policy innovation, which has been crucial for optimizing IMI systems. Economic development has also played a key role in advancing these efforts, enabling investments in infrastructure and technology. The research further examines the role of stakeholder roles and interests in shaping policy implementation and technology adoption, providing insights into balancing competing priorities. The results provide valuable guidance for understanding the driving forces and development model of China's IMI system, strengthening water resource management, enhancing agricultural sustainability and ensuring sustainable development in a global context, particularly in achieving SDGs 2 and 6.

Rainfall data collected from the flood-season rainfall stations could be used to improve the prediction accuracy and spatiotemporal variability of the rainfall erosivity (R-factor) in addition to the data from the annual rainfall stations. This study used the 1980-2018 daily rainfall data of 71 annual rainfall stations and 19 flood-season rainfall stations to construct a flood-season model and analyze spatiotemporal patterns of the R-factor in the Yimeng Mountain Area. Results show that the R-factor has a high monthly centrality with a Fournier Index of 399.88 and a Concentration Index of 0.24, mainly concentrated in the flood season (accounting for 85.92 %), during the year with unimodal distribution. A suitable rainfall model for the flood season is constructed (r(2) = 0.96, Root Mean Square Error (RMSE) = 126.61 MJmmha(-1)h(-1)a(-1)) based on daily rainfall data, with a similar spatial distribution to the daily rainfall model. Including flood-season stations improved the spatial prediction of the R-factor,reducing the Average Error by 64.76 % and the Root Mean Square Error reduced by 8 %. The average annual R-factor in the study area is 3652 MJmmha(-1)h(-1)a(-1), showing a trend of low in the north and west, and high in the south and east. The overall R-factor shows an insignificant upward trend from 1980 to 2018, with a significant upward trend in the northwest and southwest (z > 1.65). Therefore, by developing a rainfall erosivity calculation model based on flood season rainfall data, it is feasible to increase the number of rainfall stations, and enhance the spatial prediction accuracy of the R-factor's temporal and spatial variations. Concurrently, it's essential to implement more robust measures to cope with the soil erosion risks caused by the changed R-factor under the climate change.

Eco-revetments serve as essential infrastructure for intercepting agricultural non-point source pollution (ANSP), yet standardised and quantitative evaluation methods remain limited, especially in China where design practices often rely on qualitative experience rather than systematic assessment. This study proposes an empirical method to evaluate the pollutant interception efficiency of eco-revetments equipped with sediment interception measures, based on a design project along the Jinjingtang River in Changshu City, Jiangsu Province. The pollutant removal mechanisms operate via sediment capture in interception ditches, filtration by vegetation, and absorption within sand-gravel media. To enable systematic assessment of pollutant removal efficiency, four formulas were developed to simulate the concentration-time dynamics of key pollutants, including total nitrogen (TN), total phosphorus (TP), and suspended solids (SS), during rainfall events. Additionally, pollutant interception efficiency for both soluble and particulate pollutants, along with flow diversion ratios across different functional modules of the eco-revetment, were defined to support comprehensive evaluation. The empirical method was applied alongside field data on farmland pollution and artificial rainfall experiments to quantitatively assess the eco-revetment's performance of the designed eco-revetment in the Jinjingtang River case study. Results showed that pollutant concentrations decreased continuously over the rainfall event, with the most pronounced reductions occurring within the initial 2 h, emphasising the critical role of early-stage interception. Soil analyses revealed average TP and TN concentrations of 719 and 1256 mg/kg, respectively, with over 90% of these pollutants bound to soil particles, highlighting the importance of sediment control via interception ditches. The assessment demonstrated interception efficiencies of 73.4%, 90.6%, and 99.0% for TN, TP, and SS, respectively, with sediment ditches accounting for over 95% of the intercepted TN and TP, and 99% of the intercepted SS. This empirical approach provides an efficient and practical tool for rapid performance evaluation of eco-revetments without reliance on complex numerical simulations or large-scale field trials, offering valuable guidance for eco-revetment design and ANSP mitigation efforts.

The vertical displacement, which is the product of natural sources and human activities, is the key factor affecting the sluice safety. This study provides a systematic approach used for analyzing the law and early warning of sluice cluster vertical displacements in coastal soft soil locations. Two important methods, including probability analysis and principal component analysis (PCA), are used to obtain the necessary information in this study. Among them, PCA is mainly used to identify the risk indices during vertical deformations of sluice cluster. As case studies, 27 sluices in a cluster in Northern Jiangsu Province's coastal area in China are chosen and 14 variables related to sluice uplift, settlement and differential settlement deformations are used. The PCA and additional evidence from the sluice deformation law are used to identify three variables as risk indices, including maximum differential settlement (MMDS), maximum cumulative vertical settlement (MCVS) and maximum cumulative vertical uplift (MCVU). This study divides the risk levels into five grades (i.e., Level 1 to Level 5) based on the selected risk indices and determines their risk thresholds based on the in-situ deformation data from 2010 to 2020. In general, the results demonstrate that the newly proposed approach exhibits an acceptable performance. However, the influence of epistemic and aleatory uncertainties on this study is worthy of further discussion in the future.

The irrigation water effective utilization coefficient (IWEUC) is a critical indication of agricultural water use efficiency. To improve water-saving potential, the inter-annual variation of IWEUC from 2014 to 2021 in Jiangsu Province was analyzed. Taking consideration of natural factors, planting structure, management levels, and water-saving engineering, the primary influencing factors of IWEUC were investigated through principal component analysis. The results revealed that IWEUC in Jiangsu Province was higher than annual national level and showed an insignificant increasing trend. IWEUC and its trend were negatively correlated with irrigation district size. Water-saving irrigation areas had an extremely significant impact on IWEUC (P < 0.01). The positive load of water-saving engineering investment was rated first. Furthermore, economic and water-saving benefits for different irrigation district scales based on the TOPSIS model were evaluated. Despite restricted government support, the economic gains for large irrigation districts were superior to those for small irrigation districts. In the past decade, agricultural water declined while agricultural water conservation rose. The completion of integrated agricultural water pricing reform, as well as the improvement of water-saving engineering and optimization of management level, had a significant beneficial influence on IWEUC. Jiangsu's IWEUC has been efficiently implemented, and provides guidelines in other regions.