• Energy Research

In the context of Integrated Energy System (IES), accurate short-term power demand forecasting is crucial for ensuring system reliability, optimizing operational efficiency through resource allocation, and supporting effective real-time decision-making in energy management. However, achieving high forecasting accuracy faces significant challenges due to the inherent complexity and stochastic nature of IES’s short-term load profiles, resulting from diverse consumption patterns among end-users and the intricate coupling within the network of interconnected energy sources. To address this issue, a dedicated Short-Term Power Load Forecasting (STPLF) framework for IES is proposed, which relies on a newly developed hybrid deep learning architecture. The framework seamlessly combines Long Short-Term Memory (LSTM) with Temporal Convolutional Network (TCN), enhanced by an attention mechanism module. By merging these methodologies, the network leverages the parallel processing prowess of TCN alongside LSTM’s ability to retain long-range temporal information, thus enabling it to dynamically concentrate on relevant sections of time series data. This synergy leads to improved prediction accuracy and broader applicability. Furthermore, the integration of residual connections within the network structure serves to deepen its learning capabilities and enhance overall performance. Ultimately, results from a real case study of a user-level IES demonstrate that the Mean Absolute Percentage Error (MAPE) of the proposed framework on the test set is 2.35%. This error rate is lower than the averages of traditional methods (3.43%) and uncombined single submodules (2.80%).

The change in snow cover under climate change is poorly understood in Tianshan Mountains. Here, we investigate the spatiotemporal characteristics and trends of snow-covered area (SCA) and snow-covered days (SCD) in the Tianshan Mountains by using the cloud-removed MODIS fractional snow cover datasets from 2001–2015. The possible linkage between the snow cover and temperature and precipitation changes over the Tianshan Mountains is also investigated. The results are as follows: (1) The distribution of snow cover over the Tianshan Mountains exhibits a large spatiotemporal heterogeneity. The areas with SCD greater than 120 days are distributed in the principal mountains with elevations of above 3000 m. (2) In total, 26.39% (5.09% with a significant decline) and 34.26% (2.81% with a significant increase) of the study area show declining and increasing trend in SCD, respectively. The SCD mainly decreases in Central and Eastern Tianshan (decreased by 11.88% and 8.03%, respectively), while it increases in Northern and Western Tianshan (increased by 9.36% and 7.47%). (3) The snow cover variations are linked to the temperature and precipitation changes. Temperature tends to be the major factor effecting the snow cover changes in the Tianshan Mountains during 2001–2015.

Abstract. Realistically representing spatial heterogeneity and lateral land surface processes within and between modeling units in earth system models is important because of their implications to surface energy and water exchanges. The traditional approach of using regular grids as computational units in land surface models and earth system models may lead to inadequate representation of subgrid heterogeneity and lateral movements of water, energy and carbon fluxes, especially when the grid resolution increases. Here a new subbasin-based framework is introduced in the Community Land Model (CLM), which is the land component of the Community Earth System Model (CESM). Local processes are represented assuming each subbasin as a grid cell on a pseudo grid matrix with no significant modifications to the existing CLM modeling structure. Lateral routing of water within and between subbasins is simulated with the subbasin version of a recently-developed physically based routing model, Model for Scale Adaptive River Routing (MOSART). As an illustration, this new framework is implemented in the topographically diverse region of the US Pacific Northwest. The modeling units (subbasins) are delineated from high-resolution Digital Elevation Models (DEMs) while atmospheric forcing and surface parameters are remapped from the corresponding high resolution datasets. The impacts of this representation on simulating hydrologic processes are explored by comparing it with the default (grid-based) CLM representation. In addition, the effects of DEM resolution on parameterizing topography and the subsequent effects on runoff processes are investigated. Limited model evaluation and comparison showed that small difference between the averaged forcing can lead to more significant difference in the simulated runoff and streamflow because of nonlinear lateral processes. Topographic indices derived from high resolution DEMs may not improve the overall water balance, but affect the partitioning between surface and subsurface runoff. More systematic analyses are needed to determine the relative merits of the subbasin representation compared to the commonly used grid-based representation, especially when land surface models are approaching higher resolutions.

Abstract. As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e., two floods or two droughts that occurred in the same area. The 45 coupled events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed, and in the quantity of socio-hydrological data. The benchmark dataset inclues: 1) detailed review style reports about the events and key processes between the two events of a pair; 2) the key data table containing variables that assess the indicators which characterise management shortcomings, hazard, exposure, vulnerability and impacts of all events; 3) a table of the indicators-of-change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the coupled events based on the indicators-of-change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analytics e.g. focused on causal links between risk management, changes in hazard, exposure and vulnerability and flood or drought impacts. The data can also be used for the development, calibration and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al. 2023, link for review: https://dataservices.gfz-potsdam.de/panmetaworks/review/923c14519deb04f83815ce108b48dd2581d57b90ce069bec9c948361028b8c85/). Abstract. As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e., two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed, and in the quantity of socio-hydrological data. The benchmark dataset comprises: 1) detailed review style reports about the events and key processes between the two events of a pair; 2) the key data table containing variables that assess the indicators which characterise management shortcomings, hazard, exposure, vulnerability and impacts of all events; 3) a table of the indicators-of-change that indicate the differences between the first and second event of a pair. The advantages of the dataset are that it enables comparative analyses across all the paired events based on the indicators-of-change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses e.g. focused on causal links between risk management, changes in hazard, exposure and vulnerability and flood or drought impacts. The data can also be used for the development, calibration and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al. 2023, link for review: https://dataservices.gfz-potsdam.de/panmetaworks/review/923c14519deb04f83815ce108b48dd2581d57b90ce069bec9c948361028b8c85/). Abstract. As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions and feedbacks in complex human-water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e., two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed, and in the quantity of socio-hydrological data. The benchmark dataset includes: 1) detailed review style reports about the events and key processes between the two events of a pair; 2) the key data table containing variables that assess the indicators which characterise management shortcomings, hazard, exposure, vulnerability and impacts of all events; 3) a table of the indicators-of-change that indicates the differences between the first and second events of a pair. The advantages of the dataset are that it enables comparative analyses across all the paird events based on the indicators-of-change and allows for detailed context- and location-specific assessments based on the extensive data and reports of the individual study areas. The dataset can be used by the scientific community for exploratory data analyses e.g. focused on causal links between risk management, changes in hazard, exposure and vulnerability and flood or drought impacts. The data can also be used for the development, calibration and validation of socio-hydrological models. The dataset is available to the public through the GFZ Data Services (Kreibich et al. 2023, link for review: https://dataservices.gfz-potsdam.de/panmetaworks/review/923c14519deb04f83815ce108b48dd2581d57b90ce069bec9c948361028b8c85/). الخلاصة: مع زيادة الآثار السلبية للظواهر الهيدرولوجية المتطرفة في العديد من مناطق العالم، يعد الفهم الأفضل لدوافع التغيرات في المخاطر والآثار أمرًا ضروريًا للإدارة الفعالة لمخاطر الفيضانات والجفاف والتكيف مع المناخ. ومع ذلك، هناك حاليًا نقص في البيانات التجريبية الشاملة حول العمليات والتفاعلات والتغذية المرتدة في أنظمة المياه البشرية المعقدة التي تؤدي إلى آثار الفيضانات والجفاف. نقدم هنا مجموعة بيانات مرجعية تحتوي على بيانات اجتماعية هيدرولوجية للأحداث المزدوجة، أي فيضانان أو موجتي جفاف وقعتا في نفس المنطقة. وقعت الأحداث الـ 45 المزدوجة في 42 منطقة دراسة مختلفة وتغطي مجموعة واسعة من الظروف الاجتماعية والاقتصادية والمائية المناخية. مجموعة البيانات فريدة من نوعها في تغطية كل من الفيضانات والجفاف، وفي عدد الحالات التي تم تقييمها، وفي كمية البيانات الاجتماعية الهيدرولوجية. تتضمن مجموعة البيانات المعيارية ما يلي: 1) تقارير أسلوب المراجعة التفصيلية حول الأحداث والعمليات الرئيسية بين حدثين للزوج؛ 2) جدول البيانات الرئيسية الذي يحتوي على متغيرات تقيم المؤشرات التي تميز أوجه القصور في الإدارة والمخاطر والتعرض والضعف وتأثيرات جميع الأحداث؛ 3) جدول مؤشرات التغيير الذي يشير إلى الاختلافات بين الحدثين الأول والثاني للزوج. تتمثل مزايا مجموعة البيانات في أنها تمكن التحليلات المقارنة عبر جميع الأحداث الثنائية بناءً على مؤشرات التغيير وتسمح بإجراء تقييمات مفصلة للسياق والموقع بناءً على البيانات والتقارير الشاملة لمناطق الدراسة الفردية. يمكن للمجتمع العلمي استخدام مجموعة البيانات لتحليل البيانات الاستكشافية، على سبيل المثال التركيز على الروابط السببية بين إدارة المخاطر والتغيرات في المخاطر والتعرض والضعف وآثار الفيضانات أو الجفاف. يمكن أيضًا استخدام البيانات لتطوير النماذج الاجتماعية الهيدرولوجية ومعايرتها والتحقق من صحتها. مجموعة البيانات متاحة للجمهور من خلال خدمات بيانات GFZ (Kreibich et al. 2023، رابط للمراجعة: https://dataservices.gfz-potsdam.de/panmetaworks/review/923c14519deb04f83815ce108b48dd2581d57b90ce069bec9c948361028b8c85/).

Le bassin supérieur de la rivière Tarim soutient environ 50 millions de personnes en faisant fondre les glaciers et la neige, qui sont très vulnérables et sensibles au changement climatique. Par conséquent, l'évaluation des effets relatifs du changement climatique sur le ruissellement de cette région est essentielle non seulement pour comprendre le mécanisme de réponse hydrologique sur les zones montagneuses du sud du Xinjiang, mais aussi pour la gestion locale des ressources en eau. Cette étude a étudié quantitativement le changement climatique dans la zone montagneuse du bassin supérieur de la rivière Tarim, en utilisant les données actualisées sur les précipitations et la température, les données APHRODITE (1961-2010, 0,25°) ; analysé les liens potentiels entre les données de ruissellement, observées à la station Alar, et les variables climatiques clés ; et discuté des modèles de régression sur la simulation du ruissellement sur la base des données sur les précipitations et la température. Les principales conclusions de cette étude sont : (1) les précipitations annuelles et la température augmentent généralement à des taux de 0,85 mm/an et 0,25 La cuenca superior del río Tarim está apoyando a unos 50 millones de personas mediante el derretimiento de los glaciares y la nieve, que son altamente vulnerables y sensibles al cambio climático. Por lo tanto, evaluar los efectos relativos del cambio climático en la escorrentía de esta región es esencial no solo para comprender el mecanismo de respuesta hidrológica en las áreas montañosas del sur de Xinjiang, sino también para la gestión local de los recursos hídricos. Este estudio investigó cuantitativamente el cambio climático en el área montañosa de la cuenca superior del río Tarim, utilizando los datos actualizados de precipitación y temperatura de 'verdad terrestre', los datos de AFRODITA (1961-2010, 0.25°); analizó las conexiones potenciales entre los datos de escorrentía, observados en la estación Alar, y las variables climatológicas clave; y discutió los modelos de regresión para simular la escorrentía basados en datos de precipitación y temperatura. Los principales hallazgos de este estudio son: (1) tanto la precipitación anual como la temperatura generalmente aumentan a tasas de 0.85 mm/año y 0.25 The upper Tarim River basin is supporting about 50 million people by melting the glaciers and snow, which are highly vulnerable and sensitive to climate change.Therefore, assessing the relative effects of climate change on runoff of this region is essential not only for understanding the mechanism of hydrological response over the mountainous areas in Southern Xinjiang but also for local water resources management.This study quantitatively investigated the climate change in the mountainous area of the upper Tarim River basin, using the up-to-date 'ground-truth' precipitation and temperature data, the APHRODITE (1961-2010, 0.25°) data; analyzed the potential connections between runoff data, observed at Alar station, and the key climatological variables; and discussed the regression models on simulating the runoff based on precipitation and temperature data.The main findings of this study are: (1) both annual precipitation and temperature generally increases at rates of 0.85 mm/year and 0.25 يدعم حوض نهر تاريم العلوي حوالي 50 مليون شخص عن طريق ذوبان الأنهار الجليدية والثلوج، المعرضة بشدة وحساسة لتغير المناخ. لذلك، فإن تقييم الآثار النسبية لتغير المناخ على الجريان السطحي لهذه المنطقة أمر ضروري ليس فقط لفهم آلية الاستجابة الهيدرولوجية على المناطق الجبلية في جنوب شينجيانغ ولكن أيضًا لإدارة الموارد المائية المحلية. حققت هذه الدراسة كميًا في تغير المناخ في المنطقة الجبلية لحوض نهر تاريم العلوي، باستخدام بيانات هطول الأمطار ودرجة الحرارة "الأرضية" الحديثة، وبيانات أفروديت (1961-2010، 0.25درجة) ؛ تحليل الروابط المحتملة بين بيانات الجريان السطحي، التي لوحظت في محطة ألار، والمتغيرات المناخية الرئيسية ؛ وناقشت نماذج الانحدار في محاكاة الجريان السطحي بناءً على بيانات هطول الأمطار ودرجة الحرارة. النتائج الرئيسية لهذه الدراسة هي: (1) كل من هطول الأمطار السنوي وزيادة درجة الحرارة بشكل عام بمعدلات 0.85 مم/سنة و 0.25

Image segmentation as a main applying field in parallel computing with high performance, its time complexity and real-time requirements of algorithm needs to continue to improve computer hardware technology and parallel computing algorithm. Mean Shift algorithm is relatively classical in image segmentation fields, which needs no prior knowledge in the process and is an unsupervised segmentation process, attracting widespread attention for its good applicability. The paper makes a parallel improvement of Mean Shift algorithm using TBB on multi-core. The paper first analyzes the most time-consuming part Mean Shift clustering in the process of Mean Shift image segmentation, then makes a parallel improvement of Mean Shift clustering base on TBB and gets a preferable accelerating effect.