渭河干流浅层地下水与地表水中重金属Cd污染特征及风险评价

为了解渭河流域水体重金属污染现状及健康危害风险,沿渭河干流采集浅层地下水和地表水水样,采用单因子指数法和美国环境保护署(USEPA)健康风险评价模型揭示了水体中重金属Cd污染现状和健康风险。结果表明:2018年渭河干流地下水和地表水中Cd浓度分别为426.40~1104.27 ng·L^-1和224.70~1154.12 ng·L^-1;参照《地下水质量标准》(GB/T 14848-2017)和《地表水环境质量标准》(GB 3838-2002)得知,地下水和地表水中Cd浓度均在GB/T 14848—2017和GB 3838-2002Ⅰ~Ⅲ类标准限值内;水体中Cd浓度表现出明显的空间分异性,沿河流流向均表现为逐渐增加的趋势;地下水与地表水中Cd浓度高值区相一致,即集中分布于陕西省兴平市和渭南市临渭区;由水体中Cd浓度单因子指数评价结果可知,渭河干流水体中Cd污染属于清洁水平;沿河流流向,渭河中游和下游水体中Cd浓度单因子污染指数远高于上游;水体中重金属Cd对成人和儿童产生的致癌风险分别为(1.48~2.05)×10^-4和(1.84~2.55)×10^-4,说明水体中Cd对人体可能会产生一定的健康风险。     

River Classification as a Geographic Tool in the Age of Big Data and Global Change

Spatial classification is a well‐defined analysis method in geography, which involves defining regions of the Earth based on shared characteristics. An analogy can be made between classification in geography and taxonomy in biology, because both are used to reduce complexity. Just as modern evolutionary theory and genetics technologies have transformed biological taxonomy from the sometimes arbitrary classification of living things based on superficial similarities and differences into a system that reflects the history of life and relationships among organisms, modern advances in conceptual understanding and development of technology have similarly revolutionized classification in geography as a powerful method for describing and quantifying processes. Here, I describe the history and current trends of geographic classifications relevant to river systems. Overall, there is significant emerging potential in classification as a tool for understanding river processes     

Coding random self-similar river networks and calculating geometric distances: 2. Application to runoff simulations / Codage de réseaux hydrographiques auto-similaires aléatoires et calcul de distances géométriques: 2. Application à la simulation de l'écoulement

Abstract

A preliminary method for coding random self-similar river networks and the corresponding distance calculations are proposed in a companion paper. The coding method is applied to generate random self-similar river networks, and the corresponding algorithm for calculating the geometric distances of the links is employed to determine the width function of the river networks, and thus evaluates the adaptability of the process. The width function-based geomorphological instantaneous unit hydrograph (WF-GIUH) model is then applied to estimate the runoff of the Po-bridge watershed in northern Taiwan. The results imply that the separately random self-similar generating algorithm can be used to simulate river networks during the rainfall–runoff process. It can also help analyse the variations of the river network when rainfall locations change and study the influence on hydrological responses (IUH) when the shape of river network changes.     

Estimation of river discharge from non-trapezoidal open channel using QuickBird-2 satellite imagery/Utilisation des images satellites de Quickbird-2 pour le calcul des débits fluviaux en chenaux ouverts non-trapézoïdaux

Abstract

Abstract River discharge is traditionally acquired by measuring water stage and then converting the water stage to discharge by using a stage–discharge rating curve. The possibility of monitoring river discharge by satellite has not been adequately studied hitherto, because of the difficulty in making sufficiently precise measurements of the water surface. Since the successful launch of commercial satellites with very-high-resolution sensors, it has become possible to derive ground information from satellite data. To determine river discharge in a non-trapezoidal open channel, an efficient approach has been developed that uses mainly satellite data. The method, which focuses on the measurement of surface water width coupled with river width–stage and ?remote? stage–discharge rating curves, was applied to the Yangtze River (Changjiang) and an accurate estimate of river discharge was obtained. The method can be regarded as ancillary to traditional field measurement methods or other remote sensing methods.     

Temporal scaling in river flow: can it be chaotic? / L’invariance d’échelle de l’écoulement fluvial peut-elle être chaotique?

Abstract

Abstract Identification of the presence of scaling in the river flow process has been a challenging problem in hydrology. Studies conducted thus far have viewed this problem essentially from a stochastic perspective, because the river flow process has traditionally been assumed to be a result of a very large number of variables. However, recent studies employing nonlinear deterministic and chaotic dynamic concepts have reported that the river flow process could also be the outcome of a deterministic system with only a few dominant variables. In the wake of such reports, a preliminary attempt is made in this study to investigate the type of scaling behaviour in the river flow process (i.e. chaotic or stochastic). The investigation is limited only to temporal scaling. Flow data of three different scales (daily, 5-day and 7-day) observed in each of three rivers in the USA: the Kentucky River in Kentucky, the Merced River in California and the Stillaguamish River in Washington, are analysed. It is assumed that the dynamic behaviour of the river flow process at these individual scales provides clues about the scaling behaviour between these scales. The correlation dimension is used as an indicator to distinguish between chaotic and stochastic behaviours. The results are mixed with regard to the type of flow behaviour at individual scales and, hence, to the type of scaling behaviour, as some data sets show chaotic behaviour while others show stochastic behaviour. They suggest that characterization (chaotic or stochastic) of river flow should be a necessary first step in any scaling study, as it could provide important information on the appropriate approach for data transformation purposes.     

Long-range forecasts of River Po discharges based on predictable solar activity and a fuzzy neural network model / Prévisions à long terme des débits du Fleuve Pô basées sur l’activité solaire prévisible et sur un modèle de réseau de neurones flou

Abstract

Abstract Is it possible to make seasonal and interannual forecasts of hydrological variables if one cannot predict next week’s rainfall? Contrary to common view, some scientists support the hypothesis that variations in mean global temperature and precipitation are controlled more by external forcing (solar variability and volcanic eruptions) than by increasing atmospheric concentration of greenhouse gases. Temperature and precipitation are connected with special phases of the 11-year sunspot cycle, which coincide with significant accumulation of energetic solar eruptions. Because of the possibility of identifying years with many solar eruptions, the attractive prospect emerges of the long-term hydrological forecasting based on cycles of solar activity. Starting from this assumption, an expert system was built based on a fuzzy neural network model for seasonal and interannual forecasting of the Po River discharge. It was found that indices of solar activity and of global circulation are sufficient to yield useful forecasts of hydrological variables.     

Influence of snow accumulation and snowmelt on streamflow in the central Spanish Pyrenees / Influence de l’accumulation et de la fonte de la neige sur les écoulements dans les Pyrénées centrales espagnoles

Abstract

Abstract Results of studies related to the effect of snow accumulation and snowmelt on river regimes of the central Spanish Pyrenees are presented. Streamflow of the Pyrenean rivers is characterized by low and constant discharges during winter because of accumulation of snow in the basins above 1600 m a.s.l., and high and fluctuating discharges during spring due to snowmelt and rainfall. Regional discharge contrasts have been assessed in relation to the Atlantic influence and the percentage of high altitude areas in each basin. In most of the Pyrenean basins, snowmelt contributes more to the discharge than rainfall in the spring. The analysis of data shows a decrease in winter precipitation in the last 50 years causing a decrease in both winter and spring discharges and introducing changes in the distribution of streamflow throughout the year.     

Spatial and temporal intensification of lateral hyporheic flux in narrowing intra‐meander zones

Meander bends in alluvial rivers morphologically evolve towards meander cut‐off with narrowing intra‐meander necks, and this should steepen hydraulic gradients and intensify intra‐meander hyporheic flux. This research used dye tracking and head loss measurements in a 1 : 500 planimetrically scaled laboratory river table to quantify the spatial and temporal intensification of intra‐meander flux rates at two evolution ages. The younger meander bend, M1, had a sinuosity of 2.3, a river neck width of 0.39 cm, and 0.6% river slope, and the older meander bend, M3, had a sinuosity of 5.2, a river neck width of 0.12 cm, and 0.5% river slope. Flux into and out of the meander bend was estimated along the normalized curvilinear distance s*, with the meander neck at s* = 0.1 and s* = 0.9, the meander centroid at s* = 0.37 and s* = 0.63, and the apex at s* = 0.5. Between the meander centroid and neck, we documented a 60% spatial intensification for M1 and a 90% spatial intensification for M3. Between M1 and M3, we documented a 135% temporal intensification at the neck and a 100% intensification at the centroid. Our empirical spatial and temporal intensification rates involving the M1 and the M3 scenario were one to three times lower than theoretical rates derived from a river evolution model with equivalent M1 and M3 planimetry. Overestimation by the theoretical model was attributed to exaggerated head loss caused by the model neglecting groundwater contributions to river stage. Hyporheic exchange provides critical ecosystem services, and its spatial and temporal variation with meander evolution should be considered in river management. Copyright © 2012 John Wiley & Sons, Ltd.     

Temporal variation of river flow renewability in the middle Yellow River and the influencing factors

In the past 30 years, the measured annual river flow of the Yellow River has declined significantly. After adding the diverted water back to get the ‘natural’ annual river flow, the tendency of decrease can still be seen. This indicates that the river flow renewability of the Yellow River has changed. The river flow renewability is indexed as the ratio of annual ‘natural’ river flow to annual precipitation over a river drainage basin, where the ‘natural’ river flow is the measured annual river flow plus the annual ‘net’ water diversion from the river. By using this index, based on the data from the drainage area between Hekouzhen and Longmen stations on the middle Yellow River, a study has been made of the river flow renewability of the Yellow River in the changing environment of the past 50 years. The river flow renewability index (I_rr) in the drainage area between Hekouzhen and Longmen in the middle Yellow River basin has been found to decline significantly with time. In the meantime, annual precipitation decreased, annual air temperature increased, but the area of water and soil conservation measures has been increased. It has been found that I_rr is positively correlated with the areal averaged annual precipitation, but negatively correlated with annual air temperature. There is close, negative correlation between I_rr and the area of water and soil conservation measures including land terracing, tree and grass planting and checkdam building, implying that water and soil conservation measures have reduced the river flow renewability. Copyright © 2005 John Wiley & Sons, Ltd.     

A phenology based geo-informatics approach to map land use and land cover (2003–2013) by spatial segregation of large heterogenic river basins

Accurate information on land use and land cover (LULC) is critical for policy decisions especially for management of land and water resources’ activities in large river basins around the world. Phenology based LULC classification is the most promising approach particularly in the areas with diversified cropping patterns. Sometimes in large river basins, local climate and topography provides two different phenological information sets for the same crops in the same season. Based on accurate phenological information of the main crops in spatially segregated units, the remote sensing based classification was used to map the LULC changes for a period of 2003–2013 in the Kabul River Basin (KRB) of Afghanistan. We used remotely sensed Normalized Difference Vegetation Index (NDVI) products of Moderate-resolution Imaging Spectroradiometer (MODIS) from Terra (MOD13Q1) and Aqua (MYD13Q1) with 250 m spatial resolution for this study. The overall accuracy (mean) of the LULC classification throughout the study period was around 68.15% ± 9.45while the producer and user accuracies (mean) were 75.9 ± 11.3% and 76.4 ± 11.2%, respectively. Results show that the cropping patterns vary significantly in the spatially disaggregated units. From 2003 till 2013, the ground coverage of wheat, barley and rice was increased by 31%, 7% and 32%, respectively. Overall, there has been only 2% increment in the agricultural area across the KRB between 2003 and 2013. This relatively increased trend of land cover change has taken place as a result of partial improvement in political stability as well as investment in irrigation infrastructure and agricultural development in the region. This study further provides insight to develop new agriculture strategies in order to maintain the ecosystem required to fulfil the rising food demands.