Heavy rainfall in mountainous regions typically triggers extreme flood events, and accurate simulation of the spatiotemporal evolution of floods is crucial for flood management and damage mitigation at the watershed scale. This study takes the Juhe River basin in the Beijing region as the study area. Rainfall-runoff processes were simulated using a CNN-BiLSTM-Attention model, and the spatiotemporal evolution of flood events was further modeled using the integrated flood modeling system (IFMS). On this basis, the flood risks of different heavy rainfall-flood events (HRFEs) under land use and land cover (LULC) scenarios from different periods were analyzed. Optimization of the key parameters of the CNN-BiLSTM-Attention model using a population-based algorithm significantly improved simulation accuracy, with NSE values exceeding 0.75 and relative errors in peak discharge remaining below 10

Accurate monitoring of water spatiotemporal dynamics is critical for hydrological process analysis and climate impact assessment. While remote sensing enables effective water monitoring, public satellite imagery is limited by mixed-pixel effects that hinder small river detection, and high-resolution commercial data suffers from low temporal frequency and restricted coverage. To address these limitations, this study proposes a deep learning-based super-resolution (SR) framework for multispectral remote sensing imagery. This paper constructs a matched dataset for GF2 and Sentinel-2 imagery and develops an Attention Enhanced Super Resolution Generative Adversarial Network (AESRGAN). By integrating attention mechanisms and a spectral-structural loss design, the network is optimized to adapt to the characteristics of multispectral remote sensing imagery. Experimental results demonstrate that AESRGAN achieves strong reconstruction performance, with a Peak Signal-to-Noise Ratio (PSNR) of 33.83 dB and a Structural Similarity Index Measure (SSIM) of 0.882. Water extraction based on the reconstructed imagery using the U-Net++ model achieved an overall accuracy of 0.97 and a Kappa coefficient of 0.92. In addition, the reconstructed imagery improved the estimation accuracy of river length, width, and area by 0.34%, 3.28%, and 8.51%, respectively. The proposed framework provides an effective solution for multi-source remote sensing data fusion and high-precision surface water monitoring, offering new potential for long-term hydrological observation using medium-resolution satellite imagery.

Soil moisture (SM) remote sensing is widely used for agricultural drought monitoring, yet most applications still emphasize static moisture states rather than event-scale wetting responses. We developed an interpretable Earth observation (EO) framework to evaluate precipitation–SM product consistency and diagnose wetting processes across China’s croplands. Multi-source precipitation and SM products, including ERA5-Land, Soil Moisture Active Passive (SMAP), Soil Moisture of China by in situ data (SMCI), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), and Grid-based Precipitation dataset for Mainland China (CHM_PRE), were assessed using lagged consistency between rainfall forcing and relative soil moisture increments. The selected pairing was then used to model daily wetting increments at three depths with eXtreme Gradient Boosting (XGBoost), Shapley additive explanations (SHAPs), generalized additive models (GAMs), and quantile regression (QR). ERA5-Land precipitation paired with ERA5-Land SM showed the strongest reanalysis-constrained event-scale consistency (peak mean r = 0.43 at a 1-day lag), providing an internal-consistency baseline for comparison with independent satellite-derived combinations rather than an absolute accuracy ranking. EO-derived wetting signals showed depth-dependent lags, with a 1-day surface response and an approximately 2-day delayed profile signal at 28–100 cm; this pattern should not be interpreted as direct evidence of rapid physical infiltration to 100 cm. Precipitation transition thresholds followed a U-shaped dependence on antecedent wetness, with higher rainfall requirements under extremely dry and near-saturated states. These findings indicate that event-scale EO diagnostics can characterize product consistency, lagged wetting responses, and state-dependent precipitation thresholds, while same-system and deep-layer interpretations remain constrained by reanalysis coupling and model-assisted root-zone products.

River channels are fundamental geomorphological and hydrological features that play a critical role in regulating the Earth’s water cycle and ecosystems and influencing human activities. This study utilized Digital Elevation Model (DEM) data and multi-source remote sensing imagery (including GF-1 WFV, Sentinel-1, and Sentinel-2) to determine river channel dimensions. River water masks were obtained from multiple remote sensing imagery sources and processed through triangulation and segmentation to generate river reach results. Based on these segmented river reaches, buffer analysis was conducted. The buffer analysis results were then used to refine and clip the 5 m DEM and 12.5 m DEM datasets. Finally, river channels were extracted from the clipped DEM data using the natural breaks classification method. The classification accuracy was assessed using a confusion matrix. Experimental results demonstrate a high overall classification accuracy, reaching or exceeding 0.985, with classification consistency (Kappa coefficient) ranging from 0.78 to 0.81. The 5 m resolution DEM exhibited superior performance compared to the 12.5 m resolution DEM in river channel extraction, especially regarding the classification consistency (Kappa coefficient), with the 5 m resolution model outperforming the latter. This approach effectively delineates the river channel boundaries, transcends the constraints of a singular data source, enhances the precision and resilience of river extraction, and possesses several practical applications. The extracted data can support analyses of river evolution, facilitate hydrological modeling at the basin scale, improve flood disaster monitoring, and contribute to various other research domains.

Agricultural drought significantly affects crop growth and food production, making accurate drought thresholds essential for effective monitoring and discrimination. This study aims to monitor the threshold ranges for different drought levels of winter wheat during three growth periods using a multispectral Unmanned Aerial Vehicle (UAV). Firstly, based on controlled field experiments, six vegetation indices were used to develop UAV optimal inversion models for the Leaf Area Index (LAI) and Soil–Plant Analysis Development (SPAD) during the jointing–heading period, heading–filling period, and filling–maturity period of winter wheat. The results show that during the three growth periods, the DVI-LAI, NDVI-LAI, and RVI-LAI models, along with the DVI-SPAD, RVI-SPAD, and TCARI-SPAD models, achieved the highest inversion accuracy. Based on the UAV-inversed LAI and SPAD indices, threshold ranges for different drought levels were determined for each period. The accuracy of LAI threshold monitoring during three periods was 92.8%, 93.6%, and 90.5%, respectively, with an overall accuracy of 92.4%. For the SPAD index, the threshold monitoring accuracy during three periods was 93.1%, 93.0%, and 92%, respectively, with an overall accuracy of 92.7%. Finally, combined with yield data, this study explores UAV-based drought disaster monitoring for winter wheat. This research enriches and expands the crop drought monitoring system using a multispectral UAV. The proposed drought threshold ranges can enhance the scientific and precise monitoring of crop drought, which is highly significant for agricultural management.

Accurate monitoring of crop drought thresholds at different growth periods is crucial for drought monitoring. In this study, the canopy temperature (Tc) of winter wheat (‘Weilong 169’ variety) during the three main growth periods was extracted from high-resolution thermal and multispectral images taken by a complete unmanned aerial vehicle (UAV) system. Canopy-air temperature difference (ΔT) and statistic Crop Water Stress Index (CWSIsi) indicators were constructed based on Tc. Combined experiment data from the field and drought thresholds for the ΔT and CWSIsi indicators for different drought levels at three main growth periods were monitored. The results showed a strong correlation between the Tc extracted using the NDVI-OTSU method and ground-truth temperature, with an R2 value of 0.94. The CWSIsi was more stable than the ΔT index in monitoring the drought level affecting winter wheat. The threshold ranges of the CWSIsi for different drought levels of winter wheat at three main growth periods were as follows: the jointing–heading period, where the threshold ranges for normal, mild drought, moderate drought, and severe drought are <0.30, 0.30–0.42, 0.42–0.48, and >0.48, respectively; the heading–filling period, where the threshold ranges for normal, and mild, moderate, and severe drought are <0.33, 0.33–0.47, 0.44–0.53, and >0.53, respectively; and the filling–maturation period, where the threshold ranges for normal, mild drought, moderate drought, and severe drought are <0.41, 0.41–0.54, 0.54–0.59, and >0.59, respectively. The UAV thermal threshold method system can improve the accuracy of crop drought monitoring and has considerable potential in crop drought disaster identification.

在充分借鉴洪水灾害防御"四个链条"基础上,考虑干旱及其灾害孕育、发生及发展规律和特点等,明晰干旱灾害"四个链条",构建"四预"措施和"四个链条"相结合的干旱灾害防御矩阵迫在眉睫.提出要遵循"气象干旱—水文干旱—社会经济干旱"链式传导规律,加强雨情、水情、墒情、旱情的"四情"监测,精准"范围—对象—调度",贯通"技术—料物—队伍—组织"的旱灾防御"四个链条",实现滚动更新旱情预报、及时发布旱情预警信息、动态预演干旱灾害影响以及迭代更新抗旱预案.

Based on an analysis of water resources availability and the spatial distribution of drought disaster risks, this study estimates the impacts of drought disasters under different frequencies by calculating the differences between current annual water supply capacity and historical typical annual capacity. The aim is to reveal the distribution characteristics of agricultural drought disaster risks in China. The results show that the areas with a high risk of drought disasters are mainly distributed in grain-producing areas. In the case of a 5-year, 10-year, and 20-year return period, the regions with high risk are mainly distributed in northern regions, such as the Huanghuaihai Plain, Northeast China, and Northwest China. In the case of a 50-year and 100-year return period, the risk of drought in the areas with relatively abundant water resources, such as the Southwest region and middle and lower reaches of the Yangtze River, increases sharply. These regions will face great challenges in food security, water supply security, and even ecological security.

Most dams in China have been operating for a long time and are products of the economic and technical limitations at the time of construction. Due to decades of aging engineering and ancillary problems, these reservoirs pose great threats to the safety of local people and the development of the surrounding economy. In this study, the surface deformation information for the Banqiao Reservoir is monitored with the small baseline subset–synthetic aperture radar interferometry (SBAS-InSAR) method using 80 Sentinel-1A images acquired from 3 January 2020 to 20 August 2022. Additionally, ground measurements from the BeiDou ground-based deformation monitoring stations were collected to validate the InSAR results. Based on the InSAR results, the spatiotemporal deformation features of the dam were analyzed in detail. The results show that the deformation in most areas, including the dam in the study area, is relatively stable, and the regional deformation velocity of the Banqiao Reservoir dam and other hydraulic engineering facilities varies between −1 mm/y and −4 mm/y. The Ru River area has a relatively obvious subsidence trend, and the maximum subsidence velocity reaches 30 mm/y. The InSAR monitoring results are consistent with the change trend in the BeiDou ground-based deformation measurement results. The monitoring results for the reservoir dam area provide a reference for local sustainable development and geological disaster prevention.

2022年的长江流域大旱对农业、能源、生态等方面产生了严重影响.8 月 11 日,水利部针对干旱影响最为严重的安徽省、江西省、湖北省、湖南省、重庆市和四川省启动了抗旱 IV 级响应,有关六省(市)生态系统受旱程度的定量评估亟待开展.鉴于此,本研究基于标准化生态缺水指数和改进的归一化差异水体指数,分别评估了干旱对六省(市)陆地和水域生态系统产生的影响,基于干旱事件特征分析研究区夏秋季生态干旱综合强度的年际变化,最后探讨了 2022 年生态干旱的主要原因.结果表明:(1)6 月为生态干旱的起始阶段,7-9 月陆地系统生态干旱严重程度和影响范围均不断增加,10-11 月随着降雨量增加、植被需水量减小,干旱缓解,水域系统生态干旱不断加重并持续至 11 月;(2)1982-2022 年六省(市)生态干旱综合强度呈波动增加态势,2022 年均达到或接近历史同期的最大值,高强度区的面积占比高于历史平均水平的 67.4%;(3)2022 年降水和地表水偏少导致的低生态供水强度,与高温日数较长导致的高生态需水强度相叠加,引发了 1982 年以来最为严重的生态干旱.

我国河流、湖泊众多,历史文化底蕴丰厚,水文化是中华文化的重要组成部分,同时也是我国水利事业发展不可或缺的精神元素,先进水文化更是建设幸福河湖所追求的最高境界.本文对文化之河的概念进行了初步解析,基于保护好、传承好、利用好和弘扬好水文化的原则,建立了文化之河评价的三级指标体系,并将指标体系成果应用于全国十个水资源一级区的文化之河评价中.整体看来,我国文化之河幸福河湖评价等级处于中等水平,长江区的太湖流域文化之河评价得分最高,达到中等偏上等级.文化之河距离实现"大河文明、精神家园"的最高目标尚有较大的差距.

Soil moisture is a crucial factor that directly influences agricultural drought. As such, investigating drought-monitoring methods utilizing soil moisture data is of significant importance for accurately evaluating and predicting agricultural drought. However, the current soil moisture data for the Daling River Basin is insufficient. Therefore, the variable infiltration capacity (VIC) hydrological model was utilized to simulate soil moisture in the Daling River Basin. The simulated data were then analyzed in conjunction with the standardized moisture anomaly index (SMAPI) to analyze and evaluate the spatio-temporal characteristics of agricultural drought in the Darling River Basin. The results indicate that the frequency of drought occurrence in the basin follows a seasonal pattern of winter > spring > autumn > summer. Between 1981 and 2019, 24 out of 39 years experienced slight or greater drought, 15 years experienced moderate or more severe drought, and 4 years experienced severe drought. Drought conditions have become exceptionally severe in the 21st century. Specifically, the frequency of drought occurrence from 2001 to 2019 was nearly 10 times higher compared to the period from 1981 to 2000. The droughts were most severe in the southeast and southwest of the Daling River Basin, while the northeast and northwest experienced relatively mild drought. Agricultural drought is influenced by numerous complex factors. The contribution of climate change (CC) and other factors (OF) to agricultural drought was quantified by using a partial derivative under six different scenarios. Results showed that SMAPI was positively correlated with precipitation and solar radiation, while negatively correlated with temperature. From 1981 to 2000, SMAPI exhibited an increasing trend that accounted for 61.66% of variability, while a decreasing trend accounted for 38.34%. From 2001 to 2019, SMAPI exhibited a significant decreasing trend that accounted for 93.53% of the variability, while the increasing trend only accounted for 6.47%. CC was the dominant factor in most of the areas with increased SMAPI. OF was the main controlling factor for areas with decreased SMAPI.

干旱灾害是宁夏最常见、影响范围最广、损失最大的一种自然灾害.为摸清区域旱灾风险底数,掌握不同区(县)干旱灾害风险严重程度及其空间分布情况,对全区(县)开展干旱灾害风险评估与区划研究.基于长序列水资源量和历史干旱致灾数据,采用典型年法、利用供水能力折算系数确定现状年不同干旱频率下不同类型干旱受灾情况,利用ArcGIS空间分析、栅格计算器等功能,生成各类专题图层.结果显示,宁夏干旱灾害危险性均值小于全国均值,表明干旱灾害危险性较高;危险性等级以中高和高为主,区县个数占比为81.82%,面积占比90.96%.100年一遇时,农业干旱灾害高和中高风险区(县)个数占比36.37%,主要分布在中卫市西部、固原市西南部、吴忠市西部及银川市北部,而因旱人饮困难高和中高风险区(县)个数占比22.73%,主要分布在吴忠市大部、中卫市南部和固原市西部.由此,宁夏回族自治区干旱灾害高危险性区域主要分布在中部干旱区.农业干旱灾害和因旱人饮困难风险空间分布存在明显差异,与农业干旱灾害风险相比,因旱人饮困难风险和城镇干旱灾害风险普遍较低.干旱灾害综合风险区划高风险区主要分布在中部干旱区,其次是引黄灌区,中高风险区在三大区均有分布,但整体分布较小.本研究得到的干旱灾害风险评估和区划结果可为全区干旱管理和决策提供参考.

Droughts are serious natural disasters that adversely affect water resources, agriculture, the economy, and the environment. Reconstructing historical drought records is necessary to assess the impact of droughts and their evolution and has become a top priority to support and improve sustainable water management decisions. In this study, we used Shanxi Province as the research area, and meteorological data from the early years of Guangxu in the Qing Dynasty were reconstructed using historical rain and snow records. The Variable Infiltration Capacity (VIC) model is driven by the reconstruction of historical meteorological data. The study area's monthly runoff and soil water sequence from 1875 to 1879 were simulated, and the hydrology and soil of the ancient historical period were reproduced in the absence of data. The results show the following: (1) The idea of reconstructing hydrological parameters using historical data is feasible and the VIC model can be used to study drought characteristics under specific scenarios. (2) The proportions of areas with runoff depths less than 10 mm throughout Shanxi from 1875 to 1879 were 55%, 48%, 58%, 19%, and 30%. The annual runoff depth in each region from 1875 to 1877 was less than 60 mm. The hydrological drought from 1875 to 1877 was very serious, and the area covered by the drought was relatively large. (3) The annual average soil water content of various regions was stable between 150 and 510 mm from 1875 to 1879. The soil water content had no apparent interannual variation. The area with soil water content less than 180 mm accounted for ratios as high as 31%. This research provides new ideas for ancient drought research and a scientific basis for regional drought prevention, mitigation, and water resources management, and ensures the orderly progress of agricultural production activities.

加快构建具有"四预"(预报、预警、预演、预案)功能的智慧水利体系,是国家智慧水利建设的明确要求,数据底板是"四预"功能的必要支撑.全国多个智慧水利和数字孪生流域先行先试成功案例,发挥各自数据和技术优势,建设完成相应层级的数据底板,为数字孪生流域和防洪"四预"应用提供了支撑.在梳理数据底板相关技术基础上,结合试点工作经验,提出了面向防洪"四预"的数据底板建设框架和主要技术路线,从数据采集整编、多源异构数据汇聚、多维多尺度数据融合、业务信息资源库、底板专题图、专业模型数据标准化、数据资源共享管理平台和可视化技术等方面阐述了主要内容和关键技术路线,探讨了数据底板建设存在的不足和预期,以期为面向防洪"四预"的数字孪生流域数据底板建设提供参考.

水利部防洪抗旱减灾工程技术研究中心(以下简称减灾中心)成立于2002年,20年来,减灾中心始终坚持以人民为中心,将提高防洪抗旱科技水平、保障人民生命财产安全、降低水旱灾害损失视为己任,在宏观战略与对策、微观技术与方法、科研平台与应用等方面,取得了诸多重大突破.介绍了减灾中心在防洪减灾、抗旱减灾、遥感技术与应用、水利史与水文化等领域开展的相关研究,总结了取得的防洪抗旱减灾特色成果,为我国防洪抗旱减灾事业的高水平发展提供有力支撑.

基于1949-2020年全国及各省(自治区、直辖市)作物播种面积、因旱受灾面积、成灾面积及因旱粮食损失量等数据系列,构建了我国干旱灾害综合评价指标系列,分析了我国干旱灾害的时空分布特征及其变化趋势.分析结果表明,时间尺度上,1949-2000年全国干旱受灾率、成灾率和因旱粮食损失率都呈现增加趋势,增加速率分别为1.72％/10 a、1.26％/10 a和0.61％/10 a,而2001-2020年干旱灾害呈逐步减缓趋势.空间分布上,我国北方地区的东北、黄淮海、西北和内蒙古是干旱灾害发生频繁且较为严重的地区,受灾率和成灾率均超过15％和10％;而南方地区的华南、西南和长江中下游受旱成灾相对较轻,受灾率和成灾率低于10％和5％.由干旱灾害综合评价指标分析可得,1949-2020年全国发生重旱以上有26 a,发生特旱有13 a;1980年前发生重旱以上干旱范围的有10个省(自治区、直辖市),1980年以后扩大到了16个,反映出我国是一个干旱灾害多发、频发的国家.气候变暖和人类活动是干旱灾害形成的主要因素,1961-2020年黄淮海、西南等地区年降水量呈减少趋势,1951-2020年中国地表年平均气温呈显著上升趋势,升温速率为0.26℃/10 a;人类活动通过干扰作物的水分收入和支出对干旱灾害形成产生作用,在一定程度上使得干旱灾害更加严峻.

Periodically monitor the deformation of water conservancy projects and actively prevent the occurrence of geological disasters along the reservoir coast, which is of great significance to ensure the safety of life and property of surrounding residents and ensure the safety operation of reservoir dam. In this paper, the surface deformation of the Banqiao Reservoir is monitored by the SBAS-InSAR method based on 60 Sentinel-1A image data acquired from January 8, 2019 to November 5, 2021. The results show that the Banqiao Reservoir and its surrounding areas are generally very stable in most areas, with the deformation rate between -1mm/year and -5mm/year. The subsiding area is mainly distributed in some arable land around the village, the Ru River area and other areas, with the maximum subsidence velocity > 20mm/year. The monitoring results could provide reference for reservoir dam safety monitoring and early warning.

Drought risk assessment provides a vital basis for drought relief and prevention. We developed a dynamic agricultural drought risk (DADR) assessment model to predict drought trends and their impacts on crop yield in real time. A weather generator was employed to produce daily meteorological scenarios to simulate drought trends stochastically. Then, it was used to drive a crop model for simulating drought-induced yield loss. The yield loss rate was calculated to assess the DADR, whereas the cumulative yield loss rate was calculated to measure the cumulative impacts of drought on yield. The drought that occurred in the Liaoning Province in 2000 was selected as a case study, and the DADR was assessed weekly during the maize growth period. The statistical parameters of historical meteorological data were used to prove the rationality of meteorological scenarios. The crop data from 1996 to 2012 were used for crop model calibration and verification. The results showed that, on July 3, 2000, the majority of the Liaoning Province experienced severe or moderate DADR, which showed an increasing trend from east to west, while the highest DADR (over 35%) was noted in Fuxin and Chaoyang. The drought during the maize growth period in 2000 caused an average cumulative yield loss rate of 62.4%. The drought in the early seeding and milk maturity stages had a negligible impact on maize yield, contrary to that in the jointing to tasseling period. Our study provides insights into the implementation of drought relief measures and the development of drought monitoring systems.

气候变化背景下,干旱发生频率及旱灾造成的影响增加趋势显著.高效精准的旱情监测评估利于及时有效地采取抗旱措施来消除或减缓旱情发展,将旱灾防御关口提前,最大限度地降低灾害损失.本研究针对旱情监测评估业务中亟待解决的"哪里旱、有多旱、旱多久、怎么办"等关键问题,构建了融入"空、天、地"多源数据的旱情综合监测评估关键技术;文中从技术原理、功能及先进性、主要应用领域、实施效果及效益等方面介绍了研究团队在旱情综合监测评估方面实现的技术创新及相关应用推广情况;后续研究中将契合智慧化旱灾防御新需求,逐步提升旱情监测预警技术水平并深入推广.