Discussion on the dynamic mechanism of Great North China area based on the observed stress data

Introduction The Great North China, located at longitude 106E to 124E and latitude 31N to 42N, in-cludes three secondary active tectonic blocks, Ordos, Yanshan and North China plain (Figure 1). The geological tectonics of these three secondary blocks is much different from each other. As a stable block with high rigidity, the Ordos block is mostly surrounded by down-faulted basins with an inactive interior since Cenozoic, although the fault zones along its boundary are strongly active wi…     

Groundwater flow regime under natural conditions as inferred from past evidence and contemporary field observations in a semi-arid basin: Cuenca de la Independencia, Guanajuato, México

This study was carried out in the Cuenca de la Independencia, a semi-arid basin in Central Mexico. The objective is to describe the main features of a groundwater flow regime under natural conditions, based on groundwater discharge manifestations. Information obtained from paleoecological, paleontological, archaeological and historical data suggests that, prior to heavy development (starting in the 1950s), the hydrogeologic regime was characterized by a larger groundwater availability in a more humid and colder climate. Manifestations associated to groundwater discharges are springs, lagoons, wetlands, saline soils, chalcedony deposits, phreatophytes, thermalism, and artesianism. The different types of manifestations and their position in the basin indicate the influence of groundwater flow systems hierarchically nested, forming concentric zones at ground level. The groundwater flow regime corresponds to a classical gravity-induced flow system with generation of local, intermediate and regional patterns. Integrating several types of data to establish the flow geometry and its dynamics has proven a useful tool to increase understanding of the original groundwater regimes. This approach can also be applied in other over-exploited semi-arid basins.     

固沙林庇护区内降尘特征的初步观测

采用野外定位实测法,连续两年对科尔沁沙地24龄人工固沙杨树(Populussimonii)林庇护区内4～6月份及强沙尘暴事件中的降尘特征进行了观测研究。结果表明:(1)林地庇护区内4、5月份的降尘量较多,分别为273和437kg/hm2,6月份的降尘量较少,为171kg/hm2。(2)林地中央的滞尘效应在风蚀季节和强沙尘暴天气过程中十分显著。(3)林地庇护区内的降尘中粒径<0.02mm颗粒含量占60.7%,降尘中的全C、全N和速效P含量分别高达1.676%、0.163%和210.66mg/kg,这对风沙土表层土壤的细化和养分的积累具有重要的生态学意义。     

黄土区人类活动影响下的 产汇流模拟研究

日益频繁的人类活动改变了流域下垫面条件,对流域产汇流产生很大的影响。本文以黄河中游典型支流岔巴沟为研究区域,提出利用基于DEM的分布式水文模拟技术,探讨流域人类活动过程中的产汇流模拟,避免了经验公式的概化和由此引起的局限。模拟的结果证实了该方法的可行性。采用网格滞蓄的方法可以在子网格上体现人类活动引起的下垫面的变化及其对产汇流的影响,反映各个时期的产汇流条件,对降雨做出合理响应。     

Critical rainfall statistics for predicting watershed flood responses: rethinking the design storm concept

Recent advances have been made to modernize estimates of probable precipitation scenarios; however, researchers and engineers often continue to assume that rainfall events can be described by a small set of event statistics, typically average intensity and event duration. Given the easy availability of precipitation data and advances in desk‐top computational tools, we suggest that it is time to rethink the ‘design storm’ concept. Design storms should include more holistic characteristics of flood‐inducing rain events, which, in addition to describing specific hydrologic responses, may also be watershed or regionally specific. We present a sensitivity analysis of nine precipitation event statistics from observed precipitation events within a 60‐year record for Tompkins County, NY, USA. We perform a two‐sample Kolmogorov–Smirnov (KS) test to objectively identify precipitation event statistics of importance for two related hydrologic responses: (1) peak outflow from the Six Mile Creek watershed and (2) peak depth within the reservoir behind the Six Mile Creek Dam. We identify the total precipitation depth, peak hourly intensity, average intensity, event duration, interevent duration, and several statistics defining the temporal distribution of precipitation events to be important rainfall statistics to consider for predicting the watershed flood responses. We found that the two hydrologic responses had different sets of statistically significant parameters. We demonstrate through a stochastic precipitation generation analysis the effects of starting from a constrained parameter set (intensity and duration) when predicting hydrologic responses as opposed to utilizing an expanded suite of rainfall statistics. In particular, we note that the reduced precipitation parameter set may underestimate the probability of high stream flows and therefore underestimate flood hazard. Copyright © 2016 John Wiley & Sons, Ltd.     

Distinguishing streamflow trends caused by changes in climate,forest cover,and permafrost in a large watershed in northeastern China

Understanding how rivers respond to changes in land cover, climate, and subsurface conditions is critical for sustainably managing water resources and ecosystems. In this study, long‐term hydrologic, climate, and satellite data (1973–2012) from the Upper Tahe River watershed (2359 km²) in the Da Hinggan Mountains of northeast China were analysed to quantify the relative hydrologic effects of climate variability (system input) and the combined influences of forest cover change and permafrost thaw (system characteristics) on average annual streamflow (system response) using 2 methods: the sensitivity‐based method and the Kendall–Theil robust line method. The study period was subdivided into a forest harvesting period (1973–1987), a forest stability period (1988–2001), and a forest recovery period (2002–2012). The results indicated that the combined effects of forest harvesting and permafrost thaw on streamflow (+ 47.0 mm) from the forest harvesting period to the forest stability period was approximately twice as large as the effect associated with climate variability (+20.2 mm). Similarly, from the forest stability period to the forest recovery period, the decrease in average annual streamflow attributed to the combined effects of forest recovery and permafrost thaw (?38.0 mm) was much greater than the decrease due to climate variability (?22.2 mm). A simple method was used to separate the distinct impacts of forest cover change and permafrost thaw, but distinguishing these influences is difficult due to changes in surface and subsurface hydrologic connectivity associated with permafrost thaw. The results highlight the need to consider multiple streamflow drivers in future watershed and aquatic ecosystem management. Due to the ecological and hydrological susceptibility to disturbances in the Da Hinggan Mountains, forest harvesting will likely negatively impact ecohydrological processes in this region, and the effects of forest species transition in the forest recovery process should be further investigated.     

Exploration of remotely sensed forest structure and ultrasonic range sensor metrics to improve empirical snow models

Current methods to estimate snow accumulation and ablation at the plot and watershed levels can be improved as new technologies offer alternative approaches to more accurately monitor snow dynamics and their drivers. Here we conduct a meta‐analysis of snow and vegetation data collected in British Columbia to explore the relationships between a wide range of forest structure variables – obtained from Light Detection and Ranging (LiDAR), hemispherical photography (HP) and Landsat Thematic Mapper – and several indicators of snow accumulation and ablation estimated from manual snow surveys and ultrasonic range sensors. By merging and standardizing all the ground plot information available in the study area, we demonstrate how LiDAR‐derived forest cover above 0.5 m was the variable explaining the highest percentage of absolute peak snow water equivalent (SWE) (33%), while HP‐derived leaf area index and gap fraction (45° angle of view) were the best potential predictors of snow ablation rate (explaining 57% of variance). This study reveals how continuous SWE data from ultrasonic sensors are fundamental to obtain statistically significant relationships between snow indicators and structural metrics by increasing mean r² by 20% when compared to manual surveys. The relationships between vegetation and spectral indices from Landsat and snow indicators, not explored before, were almost as high as those shown by LiDAR or HP and thus point towards a new line of research with important practical implications. While the use of different data sources from two snow seasons prevented us from developing models with predictive capacity, a large sample size helped to identify outliers that weakened the relationships and suggest improvements for future research. A concise overview of the limitations of this and previous studies is provided along with propositions to consistently improve experimental designs to take advantage of remote sensing technologies, and better represent spatial and temporal variations of snow. Copyright © 2013 John Wiley & Sons, Ltd.     

Characterizing spatial and temporal variation in 18O and 2H content of New Zealand river water for better understanding of hydrologic processes

Time series of hydrogen and oxygen stable isotope ratios (δ²H and δ¹⁸O) in rivers can be used to quantify groundwater contributions to streamflow, and timescales of catchment storage. However, these isotope hydrology techniques rely on distinct spatial or temporal patterns of δ²H and δ¹⁸O within the hydrologic cycle. In New Zealand, lack of understanding of spatial and temporal patterns of δ²H and δ¹⁸O of river water hinders development of regional and national-scale hydrological models. We measured δ²H and δ¹⁸O monthly, together with river flow rates at 58 locations across New Zealand over a two-year period. Results show: (a) general patterns of decreasing δ²H and δ¹⁸O with increasing latitude were altered by New Zealand's major mountain ranges; δ²H and δ¹⁸O were distinctly lower in rivers fed from higher elevation catchments, and in eastern rain-shadow areas of both islands; (b) river water δ²H and δ¹⁸O values were partly controlled by local catchment characteristics (catchment slope, PET, catchment elevation, and upstream lake area) that influence evaporation processes; (c) regional differences in evaporation caused the slope of the river water line (i.e., the relationship between δ²H and δ¹⁸O in river water) for the (warmer) North Island to be lower than that of the (cooler, mountain-dominated) South Island; (d) δ²H seasonal offsets (i.e., the difference between seasonal peak and mean values) for individual sites ranged from 0.50‰ to 5.07‰. Peak values of δ¹⁸O and δ²H were in late summer, but values peaked 1 month later at the South Island sites, likely due to greater snow-melt contributions to streamflow. Strong spatial differences in river water δ²H and δ¹⁸O caused by orographic rainfall effects and evaporation may inform studies of water mixing across landscapes. Generally distinct seasonal isotope cycles, despite the large catchment sizes of rivers studied, are encouraging for transit time analysis applications.     

Hammond Hill Research Catchment: Supporting hydrologic investigations of rooting zone and vegetation water dynamics under climate change

The Hammond Hill Research Catchment (HH) is a small (120 ha), temperate, second order tributary to Six Mile Creek, Cayuga Lake, and the Great Lakes (42.42°, −76.32°). The HH has been monitored since January 2017 for the purpose of understanding how recent infiltration mixes with antecedent soil water on hillslope forest floors and the spatial and temporal patterns of Root Water Uptake (RWU) by temperate northeastern US tree species (eastern hemlock [Tsuga canadensis], American beech [Fagus grandifolia], and sugar maple [Acer saccharum]). These data are informing us about the hydrologic consequences of anticipated tree species composition change and supporting the development of more refined ecohydrological models. The glaciated catchment is underlain by a shallow confining siltstone layer (1–1.5 m depth) and densely covered with an approximately 60 year old regrowth mixed species forest of hemlock, beech, and other deciduous tree species common to the northeastern US. Current datasets from the HH include precipitation snow water equivalent, discharge, and associated isotopic water compositions, δ²H & δ¹⁸O. Measurements of (top 10 cm) soil water content, as well as bulk soil water and hemlock and beech xylem isotopic compositions are made at several locations across a topographic wetness gradient. The near-term role of the HH is to support an understanding of the environmental and ecological drivers of plant RWU competition. All data from the HH are publicly available.     

Prediction of river water temperature: a comparison between a new family of hybrid models and statistical approaches

River water temperature is a key physical variable controlling several chemical, biological and ecological processes. Its reliable prediction is a main issue in many environmental applications, which however is hampered by data scarcity, when using data‐demanding deterministic models, and modelling limitations, when using simpler statistical models. In this work we test a suite of models belonging to air2stream family, which are characterized by a hybrid formulation that combines a physical derivation of the key equation with a stochastic calibration of parameters. The air2stream models rely solely on air temperature and streamflow, and are of similar complexity as standard statistical models. The performances of the different versions of air2stream in predicting river water temperature are compared with those of the most common statistical models typically used in the literature. To this aim, a dataset of 38 Swiss rivers is used, which includes rivers classified into four different categories according to their hydrological characteristics: low‐land natural rivers, lake outlets, snow‐fed rivers and regulated rivers. The results of the analysis provide practical indications regarding the type of model that is most suitable to simulate river water temperature across different time scales (from daily to seasonal) and for different hydrological regimes. A model intercomparison exercise suggests that the family of air2stream hybrid models generally outperforms statistical models, while cross‐validation conducted over a 30‐year period indicates that they can be suitably adopted for long‐term analyses. Copyright © 2016 John Wiley & Sons, Ltd.