Journal of Hydrology最新文献

{"title":"Response of urban flood resilience to climate change: An exploration with a novel performance-based metric considering the socioeconomic impacts of damage costs","authors":"Jiaxuan Zheng ,&nbsp;Xi Chen ,&nbsp;Kenji Kawaike ,&nbsp;Kazuki Yamanoi ,&nbsp;Takahiro Koshiba ,&nbsp;Guoru Huang","doi":"10.1016/j.jhydrol.2024.132260","DOIUrl":"10.1016/j.jhydrol.2024.132260","url":null,"abstract":"<div><div>Climate change stimulates the emergence of floods and increases flood risk for communities, resulting in extensive casualties and economic loss. Thus, flood resilience has been the focus of much attention. Integrated and holistic metrics are important for an accurate urban flood resilience evaluation. However, performance-based metrics involving surface inundation do not consider the socioeconomic impacts of damage costs on the recovery ability of the urban systems. This hinders the investigation of climate change-induced effects on flood resilience. Therefore, this study proposed a performance-based resilience metric considering the negative impacts of flooding damage costs. The proposed metric was then piloted in a highly urbanized area in Osaka City, Japan to explore the responses of flood resilience to climate change. The results suggest that climate change exerts non-negligible pressure on the study area to maintain its economic characteristics during flooding. Rainfall intensity primarily affects the urban system’s most unfavorable state, while the total amount and duration of rainfall mostly impact the relatively stable state following flooding. Climate change severity is positively linked to the reduction in overall flood resilience. Continued climate change will further expand the spatial coverage of flood resilience losses on a global scale. Furthermore, the negative impacts of economic losses on flood resilience are more noticeable during rainfall events with higher rainfall intensities. This study improves the comprehensiveness of performance-based flood resilience evaluations and provides a reference for the effective enhancement of urban flood resilience under climate change.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132260"},"PeriodicalIF":5.9,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571945","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cunninghamia lanceolata cannot Depend solely on xylem embolism resistance to Withstand prolonged seasonal drought","authors":"Xinlei Ren ,&nbsp;Jianbo Jia ,&nbsp;Yuwen Hu ,&nbsp;Bo Han ,&nbsp;Pu Peng ,&nbsp;Mengjie Zhang ,&nbsp;Ming Liu","doi":"10.1016/j.jhydrol.2024.132255","DOIUrl":"10.1016/j.jhydrol.2024.132255","url":null,"abstract":"<div><div>As global climate change leads to increased spatial and temporal heterogeneity in precipitation patterns, seasonal droughts are becoming more frequent in subtropical monsoon regions. Some conifer species despite having high embolism resistance, still succumb to the effects of climatic drought. Therefore, assessing a plant’s drought resistance based solely on hydraulic traits does not provide a comprehensive picture. <em>Cunninghamia lanceolata</em> (<em>C. lanceolata</em>)<em>,</em> a species extensively cultivated in the subtropical monsoon regions due to its rapid growth, drought resistance, and high economic value, plays a dominant role in fast-growing and high-yielding forestry. Investigating the drought response of <em>C. lanceolata</em> is crucial for ensuring sustainable timber production, maintaining ecosystem balance, and enhancing ecological hydrological functions. To this end, from July 2022 to October 2023, we conducted a comparative experiment simulating seasonal drought on 15-year-old <em>C. lanceolata</em>. We assessed the embolism resistance of <em>C. lanceolata</em> by constructing vulnerability curves and analyzed its water use patterns using hydrogen and oxygen isotope compositions. The research findings indicate that in October 2022, the hydraulic safety margin (HSM₅₀) of <em>C. lanceolata</em> increased from 0.99 ± 0.23 MPa to 1.12 ± 0.13 MPa under water input exclusion, suggesting that <em>C. lanceolata</em> can enhance its xylem embolism resistance to counteract short-term drought stress. Despite the ability of <em>C. lanceolata</em> to adjust its root distribution, <em>C. lanceolata</em> primarily relies on shallow soil moisture for survival, with the maximum water uptake from the 0–10 cm soil layer reaching up to 53.0 %±9.0 %. This mismatch between the tree’s water use pattern and soil moisture dynamics exacerbates drought stress during the dry season, leading to irreversible embolism accumulation over prolonged seasonal droughts. During the 2023 dry season, the natural percentage loss of conductivity (NPLC) in <em>C. lanceolata</em> trees from both the drought and control groups significantly increased to 27.45 ± 1.03 % and 19.60 ± 1.05 %, respectively, both higher than in the 2022 dry season (increases of 8.06 ± 3.01 % and 8.58 ± 2.36 %, respectively). Therefore, we believe that HSM can only assess a plant’s short-term resistance to sudden drought but cannot accurately determine its long-term adaptability to repeated extreme drought stress. A comprehensive assessment should be made by considering both the tree’s water use patterns and hydraulic characteristics.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132255"},"PeriodicalIF":5.9,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142560981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How has the latest IMERG V07 improved the precipitation estimates and hydrologic utility over CONUS against IMERG V06?","authors":"Siyu Zhu ,&nbsp;Zhi Li ,&nbsp;Mengye Chen ,&nbsp;Yixin Wen ,&nbsp;Shang Gao ,&nbsp;Jiaqi Zhang ,&nbsp;Jiao Wang ,&nbsp;Yi Nan ,&nbsp;Sebastian C. Ferraro ,&nbsp;Theresa E. Tsoodle ,&nbsp;Yang Hong","doi":"10.1016/j.jhydrol.2024.132257","DOIUrl":"10.1016/j.jhydrol.2024.132257","url":null,"abstract":"<div><div>Precipitation, a crucial element of the water cycle, significantly impacts surface streamflow and flooding dynamics. The latest version of Integrated Multi-satellitE Retrievals for GPM (IMERG V07) has garnered global attention for its advancements over its predecessor, IMERG V06. However, the improvement in precipitation rates has not yet been fully quantified, especially when translated into improvements in hydrologic predictions. In this study, we aim to quantify the improvements of IMERG V07 over V06 in the contiguous United States (CONUS) in the aspects of (1) Evaluating the accuracy of precipitation data against Multi-Radar Multi-Sensor (MRMS); and (2) Comparing their hydrologic performance using a hydrologic model, the Coupled Routing and Excess Storage (CREST), against United States Geological Survey (USGS) streamgages. This study mainly finds that: (1) Metrics for both precipitation and streamflow from CREST show that IMERG V07 significantly outperforms IMERG V06. Specifically, the CC improved from 0.391 to 0.443 for precipitation and from 0.487 to 0.515 for streamflow; (2) The improvements in IMERG V07 are region-dependent. Significant improvements are found in basins with small areas (&lt; 1000 km²), in mid-latitudes (41° N to 43° N), at low average elevations (&lt; 800 m), and those located in the northeastern CONUS; (3) In certain cases, IMERG V07 demonstrates a better capability in estimating extreme precipitation, whereas IMERG V06 tends to underestimate it. This is also reflected in the streamflow data, where IMERG V07 better captures flood peaks compared to IMERG V06. This research enhances our understanding of flood dynamics by analyzing IMERG V07′s advancements and their effects on hydrologic predictions. It offers valuable insights into improved precipitation data’s role in hydrological modeling, giving potential benefits for simulating better flood prediction and helping in water management.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132257"},"PeriodicalIF":5.9,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663565","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sensitivity of mass flux reduction and mass removal of perfluoroalkyl substances to groundwater flow and transport parameter variability and heterogeneity","authors":"Ruba A.M. Mohamed ,&nbsp;Mohamad R. Soltanian ,&nbsp;Dengjun Wang ,&nbsp;Kenneth C. Carroll","doi":"10.1016/j.jhydrol.2024.132268","DOIUrl":"10.1016/j.jhydrol.2024.132268","url":null,"abstract":"<div><div>Heterogeneity of soil hydraulic (e.g., hydraulic conductivity (<em>K_S</em>), porosity (<em>θ_S</em>)) and chemical (e.g., solid-phase adsorption (<em>K_d</em>)) properties complicates contaminant transport by creating spatial variability in sources of contaminant leaching. There is a knowledge gap on the effect of the interplay between these properties on the retardation and transport of per- and polyfluoroalkyl substances (PFAS) with different properties including carbon–fluorine chain-length and functional groups even in water-saturated conditions. Breakthrough curves have been used to evaluate PFAS transport behavior through heterogeneous media, including arrival time, maximum concentration, and tailing behavior. Contaminant mass flux reduction and mass removal correlations are also compared using numerical modeling to characterize PFAS transport through different source zones within a two-domain, heterogeneous system with comparison to homogeneous scenarios under water-saturated conditions. With heterogeneous properties, model sensitivity to <em>K_S</em> was the highest among the other parameters and was controlled by the <em>K_S</em> ratio between the different soils. The PFAS models in the homogeneous and heterogeneous scenarios were both sensitive to <em>θ_S</em>, depending on PFAS chain length. However, long-chain PFAS were less sensitive to <em>θ_S</em> variability compared to short-chain PFAS due to their higher <em>K_d</em>. The homogeneous and heterogeneous scenarios were equally sensitive to <em>K_d</em> variability, which was dependent on PFAS chain length.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132268"},"PeriodicalIF":5.9,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142663567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An analytical two-stage risk analysis model in the real-time reservoir operation","authors":"Yu Gong ,&nbsp;Pan Liu ,&nbsp;Dedi Liu ,&nbsp;Xiaoqi Zhang ,&nbsp;Weifeng Xu ,&nbsp;Daifeng Xiang","doi":"10.1016/j.jhydrol.2024.132256","DOIUrl":"10.1016/j.jhydrol.2024.132256","url":null,"abstract":"<div><div>Flood risk analysis is vital for real-time reservoir operation. The reservoir operation horizon (OH) is generally longer than the streamflow forecast horizon (FH), while the gap between the FH and the OH was seldom considered in analytical flood risk models. This study develops an analytical two-stage risk model covering the period within the FH (the first stage) and from the FH to the OH (the second stage). In the first stage, the errors in forecasted streamflow and reservoir water level-storage relationships are considered using the multinormal distribution within the FH. In the second stage, design flood hydrographs are used to estimate the flood risk by conducting reservoir routing. Finally, the total flood risk is calculated by using the copula method to combine the flood risks from the first and second stages. Results for a case study using China’s Three Gorges Reservoir indicate that an effective FH can be identified to minimize flood risk, and balance between the forecast accuracy and length of the horizon. The length of the effective FH is not fixed and depends on reservoir inflow. Moreover, larger errors will not always lead to greater flood risks. The proposed method provides useful information on flood risk for real-time reservoir operation.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132256"},"PeriodicalIF":5.9,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142578681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating time series Sentinel-2 images and tide height to mapping tidal flats in the Chinese mainland","authors":"Ke Wen ,&nbsp;Pengren Liao ,&nbsp;Aiwu Jiang","doi":"10.1016/j.jhydrol.2024.132264","DOIUrl":"10.1016/j.jhydrol.2024.132264","url":null,"abstract":"<div><div>As a unique and important ecosystem, tidal flats provide a variety of ecosystem functions and services. Mapping tidal flats is essential for the protection and management of coastal ecosystems. However, large-scale tidal flats mapping still faces challenges due to the tidal variation and spectral similarity between tidal flats and inland wetlands. Previous methods rely on the coastlines or maximum seawater extent to exclude inland areas, which is limited by its inability to effectively differentiate tidal flats from spectrally similar inland wetlands. To address these issues, we proposed a new tidal-flat mapping method by integrating Sentinel-2 time series imagery with tide height (TH) data from ground-based tide stations on Google Earth Engine. We first generated images at the lowest and highest tidal stages, established the statistical relationship between the Normalized Difference Water Index (NDWI) of each pixel and TH, and then concatenated them into a Random Forest classifier for further classification. The statistical relationship between NDWI and TH amplified the difference between tidal flats and inland wetlands, thus significantly reducing the influence of spectral similarity. This method could produce a high-precision tidal flats map with an overall accuracy of 97.30% in the coastal zone of the Chinese mainland. By quantitatively comparing with the previous tidal flat maps, we found that the strategies of tidal-level information simulation and inland area exclusion were the two main reasons producing the differences among the maps. The proposed method does not rely on space constraints to exclude inland wetlands and can capture more estuarine tidal flats, so it can be used as a reliable means to monitor the tidal flats in large-scale areas.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132264"},"PeriodicalIF":5.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application potential and spatiotemporal uncertainty assessment of multi-layer soil moisture estimation in different climate zones using multi-source data","authors":"Jiaxin Qian ,&nbsp;Jie Yang ,&nbsp;Weidong Sun ,&nbsp;Lingli Zhao ,&nbsp;Lei Shi ,&nbsp;Hongtao Shi ,&nbsp;Chaoya Dang ,&nbsp;Qi Dou","doi":"10.1016/j.jhydrol.2024.132229","DOIUrl":"10.1016/j.jhydrol.2024.132229","url":null,"abstract":"<div><div>Accurately estimating multi-layer soil moisture (SM) through remote sensing methods presents inherent challenges and limitations. Multi-layer SM provides valuable insights into the intricate interactions within the “soil-vegetation-atmosphere” system. This study explored the temporal dynamics of multi-layer SM in the Shandian River Basin, China, from 2019 to 2020. Through sensitivity analysis, we demonstrated the feasibility of using multi-source data for estimating multi-layer SM, including dual polarization radar data, optical vegetation descriptors, terrain factors, soil parameters, and meteorological indices. Initially, surface soil moisture (SSM) at depths of 3 cm and 5 cm was estimated using the modified change detection (MCD) model, which reduces the impact of vegetation. Incorporating constraints from soil parameters during the solving process improved the estimation accuracy of multi-layer SM. Subsequently, the water balance model, involving precipitation and evaporation, was applied to further correct the estimation results of SSM. Based on this, the infiltration process was considered to estimate deeper SM, including near-surface soil moisture (NSSM) at depths of 10 cm and 20 cm, and root zone soil moisture (RZSM) at depths of 40–50 cm. Under this framework, the estimation errors for multi-layer SM were satisfactory (RMSE = 0.041–0.045 cm³/cm³). Finally, we explored the upper limits of multi-layer SM estimation using multi-input and multi-output machine learning regression (MLR) algorithms. With the incorporation of multi-source data, advanced MLR algorithms achieved higher estimation accuracy (RMSE = 0.015–0.022 cm³/cm³) and showed potential for cross-temporal transfer (RMSE = 0.030–0.037 cm³/cm³). Moreover, spatiotemporal robustness revalidation of multi-layer SM was conducted across 17 observation networks distributed cross different climatic zones in China. The results shown that the MCD model achieved satisfactory results in estimating multi-layer SM (RMSE = 0.053–0.064 cm³/cm³), whereas the regression models displayed higher accuracy (RMSE = 0.039–0.051 cm³/cm³). Both the MCD and MLR models yielded similar conclusions, indicating that the estimation accuracy of NSSM and RZSM surpassed that of SSM, primarily due to the relatively lower variability of the former and their strong coupling with vegetation productivity. This study also specifically discussed the influence of factors such as radar incidence angles, soil texture types, and vegetation types on the estimation accuracy of multi-layer SM. This study introduced a novel concept and framework for regional multi-layer and profile SM estimation and real-time prediction through multi-source data, exhibiting high potential for practical applications.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132229"},"PeriodicalIF":5.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hydrological conditions determine the assembly processes of zooplankton in the largest Yangtze River-connected Lake in China","authors":"Qingji Zhang ,&nbsp;Yongjiu Cai ,&nbsp;Qiqi Yuan ,&nbsp;Jianghua Yang ,&nbsp;Rui Dong ,&nbsp;Zhijun Gong ,&nbsp;Thibault Datry ,&nbsp;Boqiang Qin","doi":"10.1016/j.jhydrol.2024.132252","DOIUrl":"10.1016/j.jhydrol.2024.132252","url":null,"abstract":"<div><div>In floodplain lakes, alterations in hydrological conditions can lead to changes in the structure of aquatic communities, potentially affecting biodiversity. Despite their critical role, the influence of specific hydrological and ecological factors on zooplankton community assembly and diversity remains poorly understood. We employed various methods to clarify how aquatic communities assemble and maintain diversity in these habitats. We calculated water age with the Environmental Fluid Dynamics Code (EFDC) and identified zooplankton using environmental DNA (eDNA) technology. We used these data to explore the relationship between zooplankton assembly, water age, and other ecological factors in Poyang Lake, China’s largest freshwater lake. We identified 1,142 operational taxonomic units (OTUs), mainly from Rotifera and Copepoda, representing the zooplankton community. The main driving factors for community differences were water age and total nitrogen. Water age ranged from 179 days to less than 1 day, with substantial spatial differences increasing from the western to the eastern region, particularly during the flood period (April-October). Spatial heterogeneity in other environmental factors, such as total nitrogen, dissolved organic carbon, and chlorophyll-a, also significantly impacted the zooplankton community composition. The assembly of the zooplankton community in Poyang Lake was primarily influenced by homogeneous selection, dispersal limitation, and ecological drift. During the flooding season, strong hydrodynamic forces created quick flush conditions that increased dispersal limitations, affecting the assembly process. Additionally, homogeneous selection played a major role in shaping community composition in seasonally inundated alluvial lands. This study found that water age, total nitrogen, dissolved organic carbon, and chlorophyll-a all contribute to intra-lake differences in the assembly processes of zooplankton communities in floodplain lakes. These findings improve our understanding of floodplain lake ecology, offering valuable insights for conservation biodiversity in floodplain lake.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132252"},"PeriodicalIF":5.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142554608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Study on the consistency of evaluation methods for river network connectivity in data-scarce watersheds","authors":"Zhang Xingyuan,&nbsp;Li Fawen,&nbsp;Shi Shuhui","doi":"10.1016/j.jhydrol.2024.132267","DOIUrl":"10.1016/j.jhydrol.2024.132267","url":null,"abstract":"<div><div>Hydrological connectivity, the capacity of a river network to transport water and associated materials, can be evaluated through structural and functional approaches. Structural connectivity, often assessed using readily available topographic and network data, describes the static arrangement of the river network. Functional connectivity, however, reflects the dynamic flow processes within the network, typically measured through flow data which may be scarce. While numerous structural indicators exist, their ability to represent actual (functional) connectivity remains uncertain.There is still no clear method for accurately evaluating connectivity. Functional connectivity index (FCI) provides a realistic and dynamic representation of connectivity. This study established a research framework that evaluates the consistency between structural connectivity and functional connectivity (considering FCI as actual connectivity). The research framework uses topography and graph model to calculate structural indicators and employs intraclass correlation coefficient (ICC) to evaluate the consistency. Taking the Haihe River basin as an example, the study analyzes the ability of structural indicators to characterize actual connectivity, and proposes new indicator. The results show that Betweenness Centrality (BC) has the highest consistency with FCI, with an ICC of 0.32, while other structural indicators are relatively weak. In multiple scenarios, BC defined by the network and Topographic Connectivity Index (TCI) defined by topography have the potential to characterize connectivity, and there are significant spatial differences between them. The combined index BC&amp;TCI, which considers both network and topography, can better characterize connectivity, with an ICC of 0.40 and reaching an ICC of 0.55 in mountain area. The research framework also reveals the non-consistency between structural connectivity and functional connectivity. And the non-consistency between them can serve as a measure of river network renovation and reconstruction to avoid ecological problems caused by an imbalanced structure and function.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132267"},"PeriodicalIF":5.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Land-atmosphere and ocean–atmosphere couplings dominate the dynamics of agricultural drought predictability in the Loess Plateau, China","authors":"Jing Luo ,&nbsp;Shengzhi Huang ,&nbsp;Yu Wang ,&nbsp;Vijay P. Singh ,&nbsp;Junguo Liu ,&nbsp;Qiang Huang ,&nbsp;Guoyong Leng ,&nbsp;Ji Li ,&nbsp;Haijiang Wu ,&nbsp;Xudong Zheng ,&nbsp;Wenwen Guo ,&nbsp;Xue Lin ,&nbsp;Jian Peng","doi":"10.1016/j.jhydrol.2024.132225","DOIUrl":"10.1016/j.jhydrol.2024.132225","url":null,"abstract":"<div><div>Accurate agricultural drought prediction is crucial for preparation for regional agricultural drought disasters. However, existing prediction models, while making some progress, have trade-offs between high accuracy and computational complexity and a poor understanding of prediction mechanisms. To bridge this gap, this study introduces the Meta-Gaussian model, a state-of-the-art statistical forecasting tool that requires no parameter adjustment for agricultural drought prediction. Its forecasting performance was used to characterize drought predictability. Four types of elements, including atmosphere elements (AT), ocean–atmosphere coupling (OA), land–atmosphere coupling (LA), and land surface elements (LD), were applied to the attribution of predictability on the Loess Plateau in China from both spatial and temporal perspectives, based on Geodetector and Random Forest, respectively. Results indicated that: (1) the spatial pattern of predictability was high in the northeast and southwest, while it was low in the middle. LD, such as soil moisture, were the most important factors dominating the spatial changes in predictability; (2) from a seasonal perspective, winter exhibited the highest predictability, while summer had the lowest; and (3) generally, most areas showed a significant downward trend at both annual and seasonal scales, except for summer. LA drove 48% of spring and 62% of autumn predictability decline areas. Meanwhile, OA drove 46% of summer predictability increase areas, and 44% of winter predictability decrease areas. Overall, the findings of this study provide valuable insights for regional drought prediction and further support the development of effective drought forecasting systems.</div></div>","PeriodicalId":362,"journal":{"name":"Journal of Hydrology","volume":"645 ","pages":"Article 132225"},"PeriodicalIF":5.9,"publicationDate":"2024-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}