Including spatial distribution in a data‐driven rainfall‐runoff model to improve reservoir inflow forecasting in Taiwan

Multi‐step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3‐h warning to be issued before any reservoir releases are made. However, the complex spatial and temporal heterogeneity of typhoon rainfall, coupled with a remote and mountainous physiographic context, makes the development of real‐time rainfall‐runoff models that can accurately predict reservoir inflow several hours ahead of time challenging. Consequently, there is an urgent, operational requirement for models that can enhance reservoir inflow prediction at forecast horizons of more than 3 h. In this paper, we develop a novel semi‐distributed, data‐driven, rainfall‐runoff model for the Shihmen catchment, north Taiwan. A suite of Adaptive Network‐based Fuzzy Inference System solutions is created using various combinations of autoregressive, spatially lumped radar and point‐based rain gauge predictors. Different levels of spatially aggregated radar‐derived rainfall data are used to generate 4, 8 and 12 sub‐catchment input drivers. In general, the semi‐distributed radar rainfall models outperform their less complex counterparts in predictions of reservoir inflow at lead times greater than 3 h. Performance is found to be optimal when spatial aggregation is restricted to four sub‐catchments, with up to 30% improvements in the performance over lumped and point‐based models being evident at 5‐h lead times. The potential benefits of applying semi‐distributed, data‐driven models in reservoir inflow modelling specifically, and hydrological modelling more generally, are thus demonstrated. Copyright © 2012 John Wiley & Sons, Ltd.     

Severe soil erosion during a 3‐day exceptional rainfall event: combining modelling and field data for a fallow cereal field

Exceptional rainfall events cause significant losses of soil, although few studies have addressed the validation of model predictions at field scale during severe erosive episodes. In this study, we evaluate the predictive ability of the enhanced Soil Erosion and Redistribution Tool (SERT‐2014) model for mapping and quantifying soil erosion during the exceptional rainfall event (~235 mm) that affected the Central Spanish Pyrenees in October 2012. The capacity of the simulation model is evaluated in a fallow cereal field (1.9 ha) at a high spatial scale (1 × 1 m). Validation was performed with field‐quantified rates of soil loss in the rills and ephemeral gullies and also with a detailed map of soil redistribution. The SERT‐2014 model was run for the six rainfall sub‐events that made up the exceptional event, simulating the different hydrological responses of soils with maximum runoff depths ranging between 40 and 1017 mm. Predicted average and maximum soil erosion was 11 and 117 Mg ha^?1 event^?1, respectively. Total soil loss and sediment yield to the La Reina gully amounted to 16.3 and 9.0 Mg event^?1. These rates are in agreement with field estimations of soil loss of 20.0 Mg event^?1. Most soil loss (86%) occurred during the first sub‐event. Although soil accumulation was overestimated in the first sub‐event because of the large amount of detached soil, the enhanced SERT‐2014 model successfully predicted the different spatial patterns and values of soil redistribution for each sub‐event. Further research should focus on stream transport capacity. Copyright © 2014 John Wiley & Sons, Ltd.     

Stormflow concentration–discharge dynamics of suspended sediment and dissolved phosphorus in an agricultural watershed

Concentration–discharge (C-Q) relationships are an effective tool for identifying watershed biogeochemical source and transport dynamics over short and long timescales. We examined stormflow C-Q, hysteresis, and flushing patterns of total suspended sediment (TSS) and soluble reactive phosphorus (SRP) in two stream reaches of a severely impaired agricultural watershed in northeastern Wisconsin, USA. The upper watershed reach—draining a relatively flat, row crop-dominated contributing area—showed predominantly anti-clockwise TSS hysteresis during storms, suggesting that particulate materials were mobilized more from distal upland sources than near- and in-channel areas. In contrast, the incised lower watershed reach produced strong TSS flushing responses on the rising limb of storm hydrographs and clockwise hysteresis, signalling rapid mobilization of near- and in-channel materials with increasing event flows. C-Q relationships for SRP showed complex patterns in both the upper and lower reaches, demonstrating largely non-linear chemodynamic C-Q behaviour during events. As with TSS, anti-clockwise SRP hysteresis in the upper reach suggested a delay in the hydrologic connectivity between SRP sources and the stream, with highly variable SRP concentrations during some events. A broad range of clockwise, anti-clockwise, and complex SRP hysteresis patterns occurred in the lower watershed, possibly influenced by in-channel legacy P stores and connection to tile drainage networks in the lower watershed area. Total suspended sediment and SRP responses were also strongly related to precipitation event characteristics including antecedent precipitation, recovery period, and precipitation intensity, highlighting the complexity of stormflow sediment and phosphorus responses in this severely impaired agricultural stream.     

The data‐driven approach as an operational real‐time flood forecasting model

Accurate water level forecasts are essential for flood warning. This study adopts a data‐driven approach based on the adaptive network–based fuzzy inference system (ANFIS) to forecast the daily water levels of the Lower Mekong River at Pakse, Lao People's Democratic Republic. ANFIS is a hybrid system combining fuzzy inference system and artificial neural networks. Five ANFIS models were developed to provide water level forecasts from 1 to 5 days ahead, respectively. The results show that although ANFIS forecasts of water levels up to three lead days satisfied the benchmark, four‐ and five‐lead‐day forecasts were only slightly better in performance compared with the currently adopted operational model. This limitation is imposed by the auto‐ and cross‐correlations of the water level time series. Output updating procedures based on the autoregressive (AR) and recursive AR (RAR) models were used to enhance ANFIS model outputs. The RAR model performed better than the AR model. In addition, a partial recursive procedure that reduced the number of recursive steps when applying the AR or the RAR model for multi‐step‐ahead error prediction was superior to the fully recursive procedure. The RAR‐based partial recursive updating procedure significantly improved three‐, four‐ and five‐lead‐day forecasts. Our study further shows that for long lead times, ANFIS model errors are dominated by lag time errors. Although the ANFIS model with the RAR‐based partial recursive updating procedure provided the best results, this method was able to reduce the lag time errors significantly for the falling limbs only. Improvements for the rising limbs were modest. Copyright © 2011 John Wiley & Sons, Ltd.     

The Upstream “Strong Signals” of the Water Vapor Transport over the Tibetan Plateau during a Heavy Rainfall Event in the Yangtze River Basin

A heavy rainfall event that occurred over the middle and lower reaches of the Yangtze River Basin(YRB) during July11–13 2000 is explored in this study. The potential/stream function is used to analyze the upstream "strong signals" of the water vapor transport in the Tibetan Plateau(TP). The studied time period covers from 2000 LST 5 July to 2000 LST 15 July(temporal resolution: 6 hours). By analyzing the three-dimensional structure of the water vapor flux, vorticity and divergence prior to and during the heavy rainfall event, the upstream "strong signals" related to this heavy rainfall event are revealed. A strong correlation exists between the heavy rainfall event in the YRB and the convective clouds over the TP. The "convergence zone" of the water vapor transport is also identified, based on correlation analysis of the water vapor flux two days and one day prior to, and on the day of, the heavy rainfall. And this "convergence zone" coincides with the migration of the maximum rainfall over the YRB. This specific coupled structure actually plays a key role in generating heavy rainfall over the YRB. The eastward movement of the coupled system with a divergence/convergence center of the potential function at the upper/lower level resembles the spatiotemporal evolution of the heavy rainfall event over the YRB. These upstream "strong signals" are clearly traced in this study through analyzing the three-dimensional structure of the potential/stream function of upstream water vapor transport.     

鄱阳湖生态环境动态监测服务系统

针对目前生态环境监测中多源多尺度数据获取、定量遥感模型半自动化条件制约海量数据的快速处理与分析以及静态的时空快照服务难以表达动态变化过程等问题,该文从基于传感网的数据多元化实时感知获取、基于数据仓库的生态信息主题化动态汇聚、基于多尺度WFS的智能化服务、基于动态数据驱动的仿真动态模拟知识化应用方面考虑,设计湖泊流域生态环境动态监测服务系统。以鄱阳湖为例进行验证,为鄱阳湖流域的生态监测以及江西省生态文明试验区建设提供服务。     

敦密断裂带白垩纪两期重要的变形事件

本文报道了敦密断裂带糜棱岩中黑云母~(40)Ar/~(39)Ar定年结果和大规模走滑-逆冲断裂的几何学、运动学特征及其形成时代,以便揭示断裂带两期变形事件的构造属性。黑龙江省密山市花岗质糜棱岩中黑云母~(40)Ar/~(39)Ar加权平均年龄为132.2±1.2Ma,它是敦密断裂带经历伸展事件的冷却年龄,也是东北亚大陆边缘在早白垩世Hauterivian期-Albian期发生强烈区域伸展作用的产物。密山市至辽宁省清原县系列大型走滑-逆冲断层和断层相关褶皱揭示出在晚白垩世晚期-末期发生右旋走滑-逆冲事件,该事件规模大,影响范围广,导致整个断裂带遭受到强烈改造,形成对冲式断裂系统。将研究区走滑-逆冲断裂与山东省郯庐断裂带中段挤压构造对比,认为郯庐断裂带北段和中段在晚白垩世末期都发生了强烈的走滑-逆冲事件,它们具有相同的构造特征和构造属性。     

Oil dispersal modelling: reanalysis of the Rena oil spill using open-source modelling tools

ABSTRACT

Oil spill forecast modelling is typically used immediately after a spill to predict oil dispersal and promote mobilisation of more effective response operations. The aim of this work was to map oil dispersal after the grounding of the MV Rena on Astrolabe Reef and to verify the results against observations. Model predictions were broadly consistent with observed distribution of oil contamination. However, some hot spots of oil accumulation, likely due to surf-zone and rip current circulation, were not well represented. Additionally, the model was run with 81 differing wind conditions to show that the events occurring during the grounding represented the typical likely behaviour of an oil spill on Astrolabe Reef. Oil dispersal was highly dependent on prevailing wind patterns; more accurate prediction would require better observations of local wind patterns. However, comparison of predictions with observations indicated that the GNOME model was an effective low-cost approach.     

Occurrence and Chemical Compositions of Amphiboles in Altered Dioritic Rocks of Laiwu Skarn‐Type Iron Deposit in West Shandong Area,China

The Laiwu Fe deposit is the largest skarn‐type deposit in West Shandong in China, with an estimated reserve of 290 Mt of iron ore. Here, we investigate the occurrence and chemical composition of amphiboles in altered dioritic rocks of this deposit. Three generations of amphibole group minerals were identified in these rocks. The first type (Type 1) is a hornblende with a generally euhedral crystal shape, 150–500 μm in size, and dominantly occurs in the host monzonite. The second type (Type 2) of hornblende occurs as fine grains (<100 μm) or concentric rims, less than 50 μm in thickness, around the Type 1 hornblende. The third type (Type 3) of amphibole is anhedral actinolite occurring along the boundary or the cracks of the Type 1 or 2 hornblende grains. The Type 1 hornblende has higher FeO (12.5–15.6 wt.%) and lower MgO contents (11.2–14.6 wt.%) than the Type 2 hornblende, which has an FeO content ranging from 8.8 to 10.5 wt.% and MgO content ranging from 14.2 to 17.1 wt.%. The Type 3 actinolite shows the lowest FeO (4.6–6.4 wt.%) and highest MgO (19.8–21.2 wt.%) contents. We infer that the Type 2 hornblende formed from Fe‐rich hydrothermal fluids released during rapid upwelling of the crystallizing magma. The fluids were relatively reduced and enriched in Fe. The Type 3 actinolite formed by coupled dissolution and reprecipitation, and its formation is one of the features denoting Fe‐enrichment events. Our study of these types of amphibole provides insights into the ore formation process.