Comparison of different methods describing the peak runoff contributing areas during floods

In the last few years, the scientific community has developed several hydrological models aimed at the simulation of hydrological processes acting at the basin scale. In this context, the portion of peak runoff contributing areas represents a critical variable for a correct estimate of surface runoff. Such areas are strongly influenced by the saturated portion of a river basin (influenced by antecedent conditions) but may also evolve during a specific rainfall event. In the recent years, we have developed 2 theoretically derived probability distributions that attempt to interpret these 2 processes adopting daily runoff and flood‐peak time series. The probability density functions (PDFs) obtained by these 2 schematisations were compared for humid river basins in southern Italy. Results highlighted that the PDFs of the peak runoff contributing areas can be interpreted by a gamma distribution and that the PDF of the relative saturated area provides a good interpretation of such process that can be used for flood prediction.     

Stream network expansion: a riparian water quality factor

Little is known about how active stream network expansion during rainstorms influences the ability of riparian buffers to improve water quality. We used aerial photographs to quantify stream network expansion during the wet winter season in five agricultural catchments in western Oregon, USA. Winter stream drainage densities were nearly two orders of magnitude greater than summer stream densities, and agricultural land use was much more abundant along transient portions (e.g. swales, road ditches) of stream networks. Water moving from agricultural fields into expanded stream networks during large hydrologic events has the opportunity to bypass downstream riparian buffers along perennial streams and contribute nonpoint‐source pollutants directly into perennial stream channels. Copyright © 2005 John Wiley & Sons, Ltd.     

Real‐time monitoring and estimation of the discharge of flash floods in a steep mountain catchment

Synchronously and accurately estimating the flood discharges and dynamic changes in the fluid density is essential for hydraulic analysis and forecasting of flash floods, as well as for risk assessment. However, such information is rare for steep mountain catchments, especially in regions that are hotspots for earthquakes. Therefore, six hydrological monitoring sites were established in the main stream and tributaries of the 78.3‐km² Longxi River catchment, an affected region of the Wenchuan earthquake region in China. Direct real‐time monitoring equipment was installed to measure the flow depths, velocities, and fluid total pressures of the flood hydrographs. On the basis of field measurements, real‐time mean cross‐sectional velocities during the flood hydrographs could be derived from easily obtainable parameters: cross‐sectional maximum velocities and the calibrated dimensionless parameter K_h . Real‐time discharges were determined on the basis of a noncontact method to establish the effective rating curves of this mountainous stream, ranging from 1.46 to 386.34 m³/s with the root mean square errors of ≤10.22 m³/s. Compared with the traditional point‐velocity method and empirical Manning's formula, the proposed noncontact method was reliable and safe for monitoring whole flood hydrographs. Additionally, the real‐time fluid density during the flood hydrographs was calculated on the basis of the direct monitoring parameters for fluid total pressures and water depths. During the flood hydrograph, transient flow behaviour with higher fluid density generally occurred downstream during the flood peak periods when the flow was in the supercritical flow regime. The observed behaviour greatly increased the threat of damage to infrastructure and human life near the river. Thus, it is important to accurately estimate flood discharge and identify for fluid densities so that people at risk from an impending flash flood are given reliable, advanced warning.     

综合危险性指数法在苍山县地质灾害易发区划分中的应用

地质灾害的发生和发展是地质环境因素和人类工程经济活动共同作用的结果，其易发性主要受自然因素和人为因素的共同影响。以山东省苍山县地质灾害易发区划分为例，探讨性地采用了地质灾害综合危险性指数法，定量划分了苍山县地质灾害易发区，结果符合当地地质灾害发育的实际情况，为苍山县地质灾害的预防和治理工作提供了科学依据。     

Space–time rainfall variability in the Paute basin,Ecuadorian Andes

Despite the importance of mountain ranges as water providers, knowledge of their climate variability is still limited, mostly due to a combination of data scarcity and heterogeneous orography. The tropical Andes share many of the main features of mountain ranges in general, and are subject to several climatic influences that have an effect on rainfall variability. Although studies have addressed the large-scale variation, the basin scale has received little attention. Thus, the purpose of this study was to obtain a better understanding of rainfall variability in the tropical Andes at the basin scal, utilizing the Paute River basin of southern Ecuador as a case study. Analysis of 23 rainfall stations revealed a high spatial variability in terms of: (i) large variations of mean annual precipitation in the range 660–3400 mm; (ii) the presence of a non-monotonic relation between annual precipitation and elevation; and (iii) the existence of four, sometimes contrasting, rainfall regimes. Data from seven stations for the period 1964–1998 was used to study seasonality and trends in annual, seasonal and monthly precipitation. Seasonality is less pronounced at higher elevations, confirming that in the páramo region, the main water source for Andean basins, rainfall is well distributed year round. Additionally, during the period of record, no station has experienced extreme concentrations of annual rainfall during the wet season, which supports the concept of mountains as reliable water providers. Although no regional or basin-wide trends are found for annual precipitation, positive (negative) trends during the wet (dry) season found at four stations raises the likelihood of both water shortages and the risk of precipitation-triggered disasters. The study demonstrates how variable the precipitation patterns of the Andean mountain range are, and illustrates the need for improved monitoring. Copyright © 2007 John Wiley & Sons, Ltd.     

Sources and biodegradability of dissolved organic matter in two headwater peatland catchments at the Marcell Experimental Forest,northern Minnesota,USA

Where they are present in catchments, peatlands are a dominant source of dissolved organic matter (DOM) to surrounding waterways due, in part, to high production rates. Despite the preponderance of peatlands in northern latitudes and expected peatland vulnerability to climate change, little is known about peatland DOM degradation relative to a more comprehensive understanding of degradation when DOM is sourced from upland-dominated catchments. We compared DOM biodegradability of various sources of stream water in two catchments having peatlands (22%–33% of the area) surrounded by upland forests (70%–90% of the area, either deciduous or coniferous). We measured total organic carbon (TOC), and biodegradable dissolved organic carbon concentrations; bacterial respiration rates; streamflow; and upland runoff during and after snowmelt (March to June, 2009–2011). We also explored if DOM in upland runoff stimulated biodegradation of peatland-derived DOM (i.e., a priming effect), and if forest cover type affected DOM biodegradability. As expected, the peatlands were the largest sources of both water (72%–80%) and TOC (92%–96%) to the streams although more area in each catchment was in uplands (70%–90%). Several results were unexpected, yet revealing: (1) DOM from peatlands sometimes had the same biodegradability as DOM from uplands, (2) upland sources of DOM had negligible effects on biodegradability in the peatland and downstream, and (3) upland deciduous cover did not yield more degradable DOM than conifer cover. The most pronounced effect of upland runoff was dilution of downstream TOC concentrations when there was upland runoff. Overall, the effects of upland DOM may have been negligible due to the overriding effect of the large amount of biodegradable DOM that originated in bogs. This research highlights that peatland-sourced DOM has important effects on downstream DOM biodegradability even in catchments where upland area is substantially larger than peatland area.     

Unravelling evapotranspiration controls and components in tropical Andean tussock grasslands

The study of the environmental factors that control evapotranspiration and the components of evapotranspiration leads to a better understanding of the actual evapotranspiration (ET) process that links the functioning of the soil, water and atmosphere. It also improves local, regional and global ET modelling. Globally, few studies so far focussed on the controls and components of ET in alpine grasslands, especially in mountainous sites such as the tussock grasslands located in the páramo biome (above 3300 m a.s.l.). The páramo occupies 35 000 km² and provides water resources for many cities in the Andes. In this article, we unveiled the controls on ET and provided the first insights on the contribution of transpiration to ET. We found that the wet páramo is an energy-limited region and net radiation (Rn) is primarily controlling ET. ET was on average 1.7 mm/day. The monthly average evaporative fraction (ET/Rn) was 0.47 and it remained similar for wet and dry periods. The secondary controls on ET were wind speed, aerodynamic resistance and surface resistance that appeared more important for dry periods, where significantly higher ET rates were found (20% increase). During dry events, transpiration was on average 1.5 mm/day (range 0.7–2.7 mm/day), similar to other tussock grasslands in New Zealand (range 0.6–3.3 mm/day). Evidence showed interception contributes more to ET than transpiration. This study sets a precedent towards a better understanding of the evapotranspiration process and will ultimately lead to a better land-atmosphere fluxes modelling in the tropics.     

Fine-grained landuse characterization using ground-based pictures: a deep learning solution based on globally available data

ABSTRACT

We study the problem of landuse characterization at the urban-object level using deep learning algorithms. Traditionally, this task is performed by surveys or manual photo interpretation, which are expensive and difficult to update regularly. We seek to characterize usages at the single object level and to differentiate classes such as educational institutes, hospitals and religious places by visual cues contained in side-view pictures from Google Street View (GSV). These pictures provide geo-referenced information not only about the material composition of the objects but also about their actual usage, which otherwise is difficult to capture using other classical sources of data such as aerial imagery. Since the GSV database is regularly updated, this allows to consequently update the landuse maps, at lower costs than those of authoritative surveys. Because every urban-object is imaged from a number of viewpoints with street-level pictures, we propose a deep-learning based architecture that accepts arbitrary number of GSV pictures to predict the fine-grained landuse classes at the object level. These classes are taken from OpenStreetMap. A quantitative evaluation of the area of Île-de-France, France shows that our model outperforms other deep learning-based methods, making it a suitable alternative to manual landuse characterization.     

An evaluation of approaches for modelling hydrological processes in high‐elevation,glacierized Andean watersheds

We use two hydrological models of varying complexity to study the Juncal River Basin in the Central Andes of Chile with the aim to understand the degree of conceptualization and the spatial structure that are needed to model present and future streamflows. We use a conceptual semi‐distributed model based on elevation bands [Water Evaluation and Planning (WEAP)], frequently used for water management, and a physically oriented, fully distributed model [Topographic Kinematic Wave Approximation and Integration ETH Zurich (TOPKAPI‐ETH)] developed for research purposes mainly. We evaluate the ability of the two models to reproduce the key hydrological processes in the basin with emphasis on snow accumulation and melt, streamflow and the relationships between internal processes. Both models are capable of reproducing observed runoff and the evolution of Moderate‐resolution Imaging Spectroradiometer snow cover adequately. In spite of WEAP's simple and conceptual approach for modelling snowmelt and its lack of glacier representation and snow gravitational redistribution as well as a proper routing algorithm, this model can reproduce historical data with a similar goodness of fit as the more complex TOPKAPI‐ETH. We show that the performance of both models can be improved by using measured precipitation gradients of higher temporal resolution. In contrast to the good performance of the conceptual model for the present climate, however, we demonstrate that the simplifications in WEAP lead to error compensation, which results in different predictions in simulated melt and runoff for a potentially warmer future climate. TOPKAPI‐ETH, using a more physical representation of processes, depends less on calibration and thus is less subject to a compensation of errors through different model components. Our results show that data obtained locally in ad hoc short‐term field campaigns are needed to complement data extrapolated from long‐term records for simulating changes in the water cycle of high‐elevation catchments but that these data can only be efficiently used by a model applying a spatially distributed physical representation of hydrological processes. Copyright © 2013 John Wiley & Sons, Ltd.     

How well can the subsurface storage–discharge relation be interpreted and predicted using the geometric factors in headwater areas?

Headwater storage–discharge (S–Q) remains one of the least understood processes, and there is renewed interest in the S–Q relation. How well can the S–Q relation be interpreted mechanistically using geometric factors? In this paper, the hillslope storage Boussinesq and hillslope storage kinematic wave equation were adopted to guide the theoretical derivations. Analytical solutions were derived based on the hsKW equation for nine idealized hillslope aquifers, which were subdivided into two groups, i.e. hillslope aquifers with exponential hillslope width function (C1) and hillslope aquifers with Gaussian hillslope width function (C2). We found that analytical expressions of the S–Q relation can be derived for C1 hillslope aquifers. For more compound hillslope aquifers, i.e. C2, no explicit S–Q relation can be obtained. The whole subsurface recession after a rainstorm is simulated by applying the initial saturation condition. We found that the simulated S–Q processes can be characterized by a two‐phase recession, i.e. quick and slow recession. The time (t_b) at the dividing point of the quick and slow recessions depends on the geometric factors, such as the plan and profile curvature. In the quick recession for C1, many of the S–Q curves can be described as linear or quasi‐linear functions, which indicate that linear reservoir models can be applied approximately for recession simulations. However, during the slow recession phase of C1 and during the whole recession of C2, the S–Q relations are highly non‐linear. Finally, we compared the hillslope storage kinematic wave and hillslope storage Boussinesq models for simulating subsurface water recession after a rainstorm event in a real‐world headwater catchment (G5) in China. Through comparison of the recession slope curves, we found that the simulated results of the models employing the Gaussian hillslope width function match the observed hydrograph. The results indicated that appropriate organization of the hillslope geometric factors enhances our ability to make S–Q predictions. Copyright © 2016 John Wiley & Sons, Ltd.