LES of flow through and around a finite patch of thin plates

Large eddy simulations (LESs) are performed for turbulent flow through and around a porous patch of thin vertical plates at a plate Reynolds number of Rep=5,800. The plates are arranged in a staggered pattern, presenting an elliptical planform and mimicking streamwise‐oriented blades of emergent vegetation. The immersed boundary method is employed to explicitly resolve the interaction between flow and plates. Three flow cases, each with a different number of plates within the same planform area, that is, different patch density, are studied. The Reynolds number based on freestream velocity and plate length is the same in all cases. Inspection of the distribution of velocity and vorticity in the horizontal plane reveals that downstream plates are significantly impacted by the wakes from upstream plates. It is therefore proposed that the plates can be divided into two groups based on the local flow characteristics, which are a function of position within the patch: a free group and a wake group. This classification is subsequently used in the quantitative analysis of boundary layer development and drag force at plate scale. The thickness and character of the simulated boundary layers on the plates differ significantly from predictions based on analytical or empirical relationships, which is due to wake effects and the finite length of the plates. The simulations demonstrate the so‐called sheltering effect; that is, the drag forces acting on downstream plates (in the wake group) are significantly lower than those acting on upstream plates, a result of the lower approach flow speed. Although the front‐area‐to‐lateral‐area ratio of the plates is low (1/40), pressure drag is observed to be larger than friction drag for each plate. The ratio of pressure drag to the total drag at patch scale shows only very little dependence on the plate density of the patch

Probabilistic thresholds for landslides warning by integrating soil moisture conditions with rainfall thresholds

Various methods have been proposed to define the rainfall thresholds for the landslide prediction. Once the threshold is determined, it remains the same regardless of the antecedent soil moisture conditions. However, given the important role of the antecedent soil moisture in the initiation of landslides, it is considered if the rainfall threshold level varies according to the antecedent soil moisture conditions, the prediction performance will be improved. Therefore, in this study we propose a probabilistic threshold to integrate antecedent soil moisture conditions with rainfall thresholds. In order to take into account the conditions with landslides and without landslides, the Bayesian analysis is applied to estimate the landslide occurrence probability given the various combinations of two factors: the antecedent soil moisture and the severity of the recent rainfall event. These combinations are then divided into conditions that are likely to trigger landslides and those unlikely to trigger landslides by comparing their probabilities with a critical value. In this way, the probabilistic threshold is determined. Here the soil moisture is estimated using the distributed hydrological model, and the severity of the rainfall event is characterized by the cumulated event rainfall-rainfall duration (ED) thresholds with different exceedance probabilities. The proposed approach was applied to a sub-region of the Emilia-Romagna region in northern Italy. The results show that the probabilistic threshold has a better prediction performance than the ED rainfall threshold, especially in terms of reducing false alarms. This study provides an effective approach to improve the prediction capability of the ED rainfall threshold, benefiting its application in the landslide prediction

Estimation of soil moisture using modified antecedent precipitation index with application in landslide predictions

Soil moisture plays a key role in land-atmosphere interaction systems. Although it can be estimated through in situ measurements, satellite remote sensing, and hydrological modelling, using indicators to index soil moisture conditions is another useful way. In this study, one of these indicators, the antecedent precipitation index (API), is explored. Modifications were proposed to the conventional version of API by introducing two parameters to make it more in line with the physical process. First, the recession coefficient is allowed to vary with the change of air temperature, which could take into account the variation of the evapotranspiration process. Second, the API value is restricted by the maximum value of API, accounting for the maximum water holding capacity of the soil. The modified API was then calibrated and validated by comparing with the in situ measured soil moisture. The better correlation between these two datasets demonstrates that the modified API could better indicate soil moisture conditions, compared with the conventional API. The capability of the modified API to index soil moisture conditions was further explored by applying it to landslide predictions in the Emilia-Romagna region, northern Italy. Here, the recent 3-day rainfall vs the antecedent soil wetness thresholds (RS thresholds) were constructed, in which the soil wetness is indexed by the modified API. The validation of RS thresholds was carried out with the use of the contingency matrix and receiver operating characteristic (ROC) curves. By comparing the prediction performance between RS thresholds and rainfall thresholds, it is found that RS threshold could provide better prediction capabilities in terms of higher hit rate and lower false alarm rate. The positive results indicate that the modified API could provide superior performance of indexing soil moisture conditions, demonstrating the effectiveness of the proposed modifications

Antecedent wetness and rainfall information in landslide threshold definition

For rainfall-induced landslides, their occurrence is attributed to both the antecedent wetness condition and the recent rainfall condition. However, when defining rainfall thresholds for the landslide occurrence, these two types of information have been used incompletely or implicitly, which may affect the threshold's predictive capability. This study aims to investigate how to make a better use of these two types of information in the landslide threshold definition. Here four types of thresholds are proposed, by including different variables that are responsible for landslide occurrences, these thresholds could represent different cases, like whether to include the antecedent wetness information or whether to consider the recent rainfall condition explicitly. The predictive capability of these thresholds is then compared crossly with the help of the receiver operating characteristic (ROC) approach. We carry out this study in a northern Italian region called Emilia-Romagna. Results show that the antecedent wetness condition plays a crucial role in the occurrence of rainfall-induced landsides. It is beneficial for the threshold's predictive capability to explicitly include the antecedent wetness information and the recent rainfall in the definition of landslide thresholds. When including soil moisture information in landslide threshold, the reliability of the soil moisture measurement is a key factor affecting the threshold's prediction performance

Water level management of lakes connected to regulated rivers: An integrated modeling and analytical methodology

Reservoir operations significantly alter the hydrological regime of the downstream river and river-connected lake, which has far-reaching impacts on the lake ecosystem. To facilitate the management of lakes connected to regulated rivers, the following information must be provided: (1) the response of lake water levels to reservoir operation schedules in the near future and (2) the importance of different rivers in terms of affecting the water levels in different lake regions of interest. We develop an integrated modeling and analytical methodology for the water level management of such lakes. The data-driven method is used to model the lake level as it has the potential of producing quick and accurate predictions. A new genetic algorithm-based synchronized search is proposed to optimize input variable time lags and data-driven model parameters simultaneously. The methodology also involves the orthogonal design and range analysis for extracting the influence of an individual river from that of all the rivers. The integrated methodology is applied to the second largest freshwater lake in China, the Dongting Lake. The results show that: (1) the antecedent lake levels are of crucial importance for the current lake level prediction; (2) the selected river discharge time lags reflect the spatial heterogeneity of the rivers’ impacts on lake level changes; (3) the predicted lake levels are in very good agreement with the observed data (RMSE ≤ 0.091 m; R2 ≥ 0.9986). This study demonstrates the practical potential of the integrated methodology, which can provide both the lake level responses to future dam releases and the relative contributions of different rivers to lake level changes

Longitudinal hydrodynamic characteristics in reservoir tributary embayments and effects on algal blooms.

Three Gorges Reservoir (TGR) is one of the largest man-made lakes in the world. Since the impoundment in 2003, however, algal blooms have been often observed in the tributary embayments. To control the algal blooms, a thorough understanding of the hydrodynamics (e.g., flow regime, velocity gradient, and velocity magnitude and direction) in the tributary embayments is particularly important. Using a calibrated three-dimensional hydrodynamic model, we carried out a hydrodynamic analysis of a typical tributary embayment (i.e., Xiangxi Bay) with emphasis on the longitudinal patterns. The results show distinct longitudinal gradients of hydrodynamics in the study area, which can be generally characterized as four zones: riverine, intermediate, lacustrine, and mainstream influenced zones. Compared with the typical longitudinal zonation for a pure reservoir, there is an additional mainstream influenced zone near the mouth due to the strong effects of TGR mainstream. The blooms are prone to occur in the intermediate and lacustrine zones; however, the hydrodynamic conditions of riverine and mainstream influence zones are not propitious for the formation of algal blooms. This finding helps to diagnose the sensitive areas for algal bloom occurrence

Environmentally driven risk assessment for algal bloom occurrence in shallow lakes

An algal bloom is a complex hydro-biological phenomenon driven by multi-attribute environmental processes and thus is still difficult to predict. In this paper, a comprehensive modelling framework for forecasting algal bloom risks in shallow lakes is presented, which is based on long-term field observation and modelling of eutrophic shallow lakes. In the procedure, the major factors and their suitable ranges are investigated, and the individual influence of various driving factors is evaluated quantitatively, using an integrated approach of orthogonal design and regression analysis. By analysing the possible combined effects of the major driving factors and the relationship between algal bloom risk and major bloom-driving factors, a cost-effective environmentally driven risk assessment model is developed to forecast the likelihood of algal bloom occurrence, through a parameter optimization and prediction comparison routine. The risk model has been calibrated and validated against long-term field observations of algal blooms in Taihu Lake, with the prediction accuracy higher than 70%, which only requires readily available meteorological and water quality data. It is noted that for the closed shallow lake, the influence of hydrodynamics can be indirectly reflected by the variation of wind speed; and, total phosphorus, water temperature, photosynthetically active radiation, and average wind speed could be used as major bloom-driving factors in Taihu Lake generally. This study provides a practical framework for the development of algal bloom early warning schemes for shallow lakes and helps to understand the combined function of complex bloom-driving factors

Temperature profiles at Station Xiakou: (a) comparisons between simulation and measurement in March, April, and May 2007; (b) observed values in June 2007; (c) and (d) observed values in July and August 2008 (after Ref [<b>34</b>]<b>); (e) observed values in October 2007.</b>

<p>Temperature profiles at Station Xiakou: (a) comparisons between simulation and measurement in March, April, and May 2007; (b) observed values in June 2007; (c) and (d) observed values in July and August 2008 (after Ref <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0068186#pone.0068186-Yi1" target="_blank">[<b>34</b>]</a><b>); (e) observed values in October 2007.</b></p