Characterization of sudden and sustained base flow jump hydrologic behaviour in the humid seasonal tropics of the Panama Canal Watershed

Base flows are important for tropical regions with pronounced dry seasons, which are facing increasing water demands. Base flow generation, however, is one of the most challenging hydrological processes to characterize in the tropics. In many years during the May–December wet season in the Panama Canal Watershed (PCW), base flows in rivers abruptly increase. This increase persists until the start of the December–April dry season. Understanding this unusual base flow jump (BFJ) behaviour is critical to improve water provisioning in the seasonal tropics, especially during droughts and extended dry seasons. This study developed an integrated approach combining piecewise regression on cumulative average base flow and sensitivity analysis to calculate the timing and magnitude of BFJ. Rainfall, forest cover, mean land surface slope, catchment area, and estimated subsurface storage were tested as predictors for the occurrence and magnitude of the BFJs in seven subcatchments of the PCW. Sensitivity analysis on correlated predictors allowed ranking of predictor contributions due to isolated and cross-correlation effects. Correlations between observed BFJs and BFJs predicted by watershed and rainfall-related predictors were 0.92 and 0.65 for BFJ timing and magnitude, respectively. Forest cover was the second most significant predictor after cumulative rainfall for jump magnitude, owing to larger subsurface storage and groundwater recharge in forests than pastures. Catchments in the mountainous eastern PCW always generated larger jumps due to their higher rainfall and greater forest cover than the western PCW catchments. The cross-correlations between predictors contributed to more than 50% of the jump variances. The results demonstrate the importance of rainfall gradient and catchment characteristics in affecting the sudden and sustained BFJs, which can help inform land management decisions intended to enhance water supplies in the tropics. This study underscores the need for more research to further understand the hydrological processes involved in the BFJ phenomenon, including better BFJ models and field characterizations, to help improve tropical ecosystem services under a changing environment.     

挑坎体型对下游雾化影响的试验研究

以解决挑流消能工在泄洪期间为提高消能率而加重下游雾化问题为目标,探究不同体型挑坎的下游雾化特性。通过水力学模型试验,对典型的非对称舌型坎、标准舌型坎、扭面贴坎和连续坎的下游水舌风分布、下游溅水雨强和不同液滴体积分布以及挑流水舌水力特性与冲刷特性进行了研究。研究表明:①各种工况下,非对称舌型坎、标准舌型坎、扭面贴坎的下游水舌风风速均大于连续坎。②对于非对称舌型坎,其溢洪道轴线左侧溅水强度大于右侧,其雨强左右两侧峰值差值最大为5.625 g/(m 2·min);对于扭面贴坎,其溢洪道轴线右侧溅水强度更大,其雨强左右两侧峰值差值最大为45.125 g/(m 2·min)。③随着距离水舌入水点长度增大,大粒径水滴数量和体积占比均剧烈下降;连续坎和舌型坎的挑宽均随着角度的增加而增加;冲坑深度随着角度的减小而增大。④在挑坎合适边墙侧设置扭面贴角能改善下游雾化危害,同时适当增加挑角可以减弱下游冲刷破坏。     

An inter‐basin backwater overflow (the Buhai Brook and the Ezer reservoir on the Jijia River,Romania)

During the last few years, the north‐western part of Romania has been affected by catastrophic floods with most of the watercourses reaching their highest recorded discharges. This study reports the generation of a numerical terrain model and the simulation of a backwater phenomenon at elevation steps according to the volume of water accumulated at the confluence of the Buhai Brook with the Jijia River. The hydrological data are complemented by rainfall data and the careful recording of the flood behaviour during the entire period of its development. The main aim of the study is to identify the causes of the backwater phenomenon and to highlight the material damage inflicted on the town of Dorohoi. At the same time, the study uses cartographic model that was developed to establish which areas are at risk of flooding at various levels of probability. The catastrophic flood began on the Buhai Brook, a slow‐flowing stream that drains the areas to the west of the town of Dorohoi and discharged into the upstream sector of the Jijia confluence. The flood caused two types of backwater waves: one behind the bridges and the houses built on the floodplain and a second that followed the course of the main stem (Jijia) upstream from the confluence, flooding the Ezer Lake, which was created specifically to attenuate such floods. The spillway backwater phenomenon was inter‐basin as it did not occur in a single hydrographic basin. The causes of the catastrophic flash flood and of the inter‐basin backwater overflow are natural but also reflect anthropogenic influence. After the lake filled, the discharge into the Jijia was controlled and the flooding downstream was thus greatly diminished. Though fortuitous, the backwater flooding was important in mitigating the impact of the flood wave from the Jijia River. Copyright © 2013 John Wiley & Sons, Ltd.     

The potential for agricultural land use change to reduce flood risk in a large watershed

Effects of agricultural land management practices on surface runoff are evident at local scales, but evidence for watershed‐scale impacts is limited. In this study, we used the Soil and Water Assessment Tool model to assess changes in downstream flood risks under different land uses for the large, intensely agricultural, Raccoon River watershed in Iowa. We first developed a baseline model for flood risk based on current land use and typical weather patterns and then simulated the effects of varying levels of increased perennials on the landscape under the same weather patterns. Results suggest that land use changes in the Raccoon River could reduce the likelihood of flood events, decreasing both the number of flood events and the frequency of severe floods. The duration of flood events were not substantially affected by land use change in our assessment. The greatest flood risk reduction was associated with converting all cropland to perennial vegetation, but we found that converting half of the land to perennial vegetation or extended rotations (and leaving the remaining area in cropland) could also have major effects on reducing downstream flooding potential. We discuss the potential costs of adopting the land use change in the watershed to illustrate the scale of subsidies required to induce large‐scale conversion to perennially based systems needed for flood risk reduction. Copyright © 2013 John Wiley & Sons, Ltd.     

Configurations of community in flood risk management

ABSTRACT

Despite a notable increase in the literature on community resilience, the notion of ‘community’ remains underproblematised. This is evident within flood risk management (FRM) literature, in which the understanding and roles of communities may be acknowledged but seldom discussed in any detail. The purpose of the article is to demonstrate how community networks are configured by different actors, whose roles and responsibilities span spatial scales within the context of FRM. Accordingly, the authors analyse findings from semi-structured interviews, policy documents, and household surveys from two flood prone areas in Finnish Lapland. The analysis reveals that the ways in which authorities, civil society, and informal actors take on multiple roles are intertwined and form different types of networks. By implication, the configuration of community is fuzzy, elusive and situated, and not confined to a fixed spatiality. The authors discuss the implications of the complex nature of community for FRM specifically, and for community resilience more broadly. They conclude that an analysis of different actors across scales contributes to an understanding of the configuration of community, including community resilience, and how the meaning of community takes shape according to the differing aims of FRM in combination with differing geographical settings.     

Tropical Cyclone Genesis Potential Index for Bay of Bengal During Peak Post-Monsoon (October-November) Season Including Atmosphere-Ocean Parameters

Several studies on tropical cyclone genesis potential index (GPI) mainly using atmospheric parameters (relative/absolute vorticity, relative humidity, vertical wind shear, potential instability, vertical velocity etc.) have been reported earlier. Though the ocean plays a vital role in the genesis and intensification of cyclones, no ocean parameter has been included in most of the studies. In this study, we have made an attempt to develop a new GPI for Bay of Bengal during peak post-monsoon (October-November) season including upper ocean heat content (UOHC) using the data for the period 1995–2015. It is found that the new GPI is better correlated with the total number of depressions, cyclones and severe cyclones (TNDC) compared with the existing GPI which was developed for the north Indian Ocean and presently used by India Meteorological Department (IMD), New Delhi. The correlation has significantly enhanced (r=0.86:significant at >99% level) by using the first differences [year(0) –year(?1)] of the time series data. Since, the new GPI which considers atmosphere and ocean (UOHC) parameters, it appears to be more suitable for Bay of Bengal during the peak post-monsoon season.     

植被覆盖、放牧和季节对牧草种类组成和生物量的影响:以埃塞俄比亚南部Yabello牧场为例

Yabello牧场是埃塞俄比亚博拉纳的一个半干旱地区的牧场,目前面临着草场退化的严重挑战。植被覆盖的变化、过度放牧和季节性变化极大地影响了Yabello牧场的牧草组成和生物量。本文评估了植被覆盖、放牧和季节对Yabello牧场的牧草组成和生物量的影响。首先采用1 m×1 m的随机样方进行实验,根据植被覆盖类型和放牧变化选择样点,并对季节影响进行评估。使用SAS统计软件和MicrosoftExcel分析牧草组成、牧草高度和质量数据。本研究总共记录了26种草种,其中Chloris roxburghiana, Chrysopogon aucheri和Chrysopogon aucheri草种均表现出最高的平均单种覆盖高度和生物量产量。因此,建议将这些草种用于研究区域退化草地的恢复。研究结果还表明,植被覆盖类型、放牧和季节变化是决定牧草种类组成、牧草高度和生物量产量的关键因素。最后,研究结论还认为控制灌木丛植被并平衡放牧水平的可持续管理对于该地区的可持续牧草生产和生物多样性保护至关重要。     

2017年春季季风间期南海中北部浮游植物生长与微型浮游动物摄食

Phytoplankton growth rates and mortality rates were experimentally examined at 21 stations during the 2017 spring intermonsoon(April to early May) in the northern and central South China Sea(SCS) using the dilution technique, with emphasis on a comparison between the northern and central SCS areas which had different environmental factors. There had been higher temperature but lower nutrients and chlorophyll a concentrations in the central SCS than those in the northern SCS. The mean rates of phytoplankton growth(μ_0) and microzooplankton grazing(m) were(0.88±0.33) d~(–1) and(0.55±0.22) d~(–1) in the central SCS, and both higher than those in the northern SCS with the values of μ_0((0.81±0.16) d~(–1)) and m((0.30±0.09) d~(–1)), respectively.Phytoplankton growth and microzooplankton grazing rates were significantly coupled in both areas. The microzooplankton grazing impact(m/μ_0) on phytoplankton was also higher in the central SCS(0.63±0.12) than that in the northern SCS(0.37±0.06). The microzooplankton abundance was significantly correlated with temperature in the surface. Temperature might more effectively promote the microzooplankton grazing rate than phytoplankton growth rate, which might contribute to higher m and m/μ_0 in the central SCS. Compared with temperature, nutrients mainly affected the growth rate of phytoplankton. In the nutrient enrichment treatment,the phytoplankton growth rate(μn) was higher than μ_0 in the central SCS, suggesting phytoplankton growth in the central SCS was nutrient limited. The ratio of μ_0/μn was significantly correlated with nutrients concentrations in the both areas, indicating the limitation of nutrients was related to the concentrations of background nutrients in the study stations.     

A comparative analysis of the NDVIg and NDVI3g in monitoring vegetation phenology changes in the Northern Hemisphere

Phenology is a sensitive and critical feature of vegetation and is a good indicator for climate change studies. The global inventory modelling and mapping studies (GIMMS) normalized difference vegetation index (NDVI) has been the most widely used data source for monitoring of the vegetation dynamics over large geographical areas in the past two decades. With the release of the third version of the NDVI (GIMMS NDVI3g) recently, it is important to compare the NDVI3g data with those of the previous version (NDVIg) to link existing studies with future applications of the NDVI3g in monitoring vegetation phenology. In this study, the three most popular satellite start of vegetation growing season (SOS) extraction methods were used, and the differences between SOSg and SOS3g arising from the methods were explored. The amplitude and the peak values of the NDVI3g are higher than those of the NDVIg curve, which indicated that the SOS derived from the NDVIg (SOSg) was significantly later than that derived from the NDVI3g (SOS3g) based on all the methods, for the whole northern hemisphere. In addition, SOSg and SOS3g both showed an advancing trend during 1982–2006, but that trend was more significant with SOSg than with SOS3g in the results from all three methods. In summary, the difference between SOSg and SOS3g (in the multi-year mean SOS, SOS change slope and the turning point in the time series) varied among the methods and was partly related to latitude. For the multi-year mean SOS, the difference increased with latitude intervals in the low latitudes (0–30°N) and decreased in the mid- and high-latitude intervals. The GIMMS NDVI3g data-sets seemed more sensitive than the GIMMS NDVIg in detecting information about the ground, and the SOS3g data were better correlated both with the in situ observations and the SOS derived from the Moderate Resolution Imaging Spectroradiometer NDVI. For the northern hemisphere, previous satellite measures (SOS derived from GIMMS NDVIg) may have overestimated the advancing trend of the SOS by an average of 0.032 d yr^–1.     

A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods

Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the study case, this paper introduces a novel approach to mapping the flood in near real time by leveraging Twitter data in geospatial processes. Specifically, in this study, we first analyzed the spatiotemporal patterns of flood-related tweets using quantitative methods to better understand how Twitter activity is related to flood phenomena. Then, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges. The identified patterns of Twitter activity were used to assign the weights of flood model parameters. The feasibility and accuracy of the model was evaluated by comparing the model output with official inundation maps. Results show that the proposed approach could provide a consistent and comparable estimation of the flood situation in near real time, which is essential for improving the situational awareness during a flooding event to support decision-making.