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.     

Performance of an artificial neural network on forecasting the daily occurrence and annual depth of rainfall at a tropical site

Performance of a feed‐forward back‐propagation artificial neural network on forecasting the daily occurrence and annual depth of rainfall at a single meteorological station is presented. Both short‐term and long‐term forecasting was attempted, with ground level data collected by the meteorological station in Colombo, Sri Lanka (79° 52′E, 6° 54′N) during two time periods, 1994–2003 and 1869–2003. Two neural network models were developed; a one‐day‐ahead model for predicting the rainfall occurrence of the next day, which was able to make predictions with a 74·3% accuracy, and one‐year‐ahead model for yearly rainfall depth predictions with an 80·0% accuracy within a ± 5% error bound. Each of these models was extended to make predictions several time steps into the future, where accuracies were found to decrease rapidly with the number of time steps. The success rates and rainfall variability within the north‐east and south‐west monsoon seasons are also discussed. Copyright © 2007 John Wiley & Sons, Ltd.     

A network theory approach for a better understanding of overland flow connectivity

Hydrological connectivity describes the physical coupling (linkages) of different elements within a landscape regarding (sub‐) surface flows. A firm understanding of hydrological connectivity is important for catchment management applications, for example, habitat and species protection, and for flood resistance and resilience improvement. Thinking about (geomorphological) systems as networks can lead to new insights, which has also been recognized within the scientific community, seeing the recent increase in the use of network (graph) theory within the geosciences. Network theory supports the analysis and understanding of complex systems by providing data structures for modelling objects and their linkages, and a versatile toolbox to quantitatively appraise network structure and properties. The objective of this study was to characterize and quantify overland flow connectivity dynamics on hillslopes in a humid sub‐Mediterranean environment by using a combination of high‐resolution digital‐terrain models, overland flow sensors and a network approach. Results showed that there are significant differences between overland flow connectivity on agricultural areas and semi‐natural shrubs areas. Significant positive correlations between connectivity and precipitation characteristics were found. Significant negative correlations between connectivity and soil moisture were found, most likely because of soil water repellency and/or soil surface crusting. The combination of structural networks and dynamic networks for determining potential connectivity and actual connectivity proved a powerful tool for analysing overland flow connectivity. Copyright © 2016 John Wiley & Sons, Ltd.     

Extreme value statistics for annual minimum and trough-under-threshold precipitation at different spatio-temporal scales

Abstract

The aim of this paper is to quantify meteorological droughts and assign return periods to these droughts. Moreover, the relation between meteorological and hydrological droughts is explored. This has been done for the River Meuse basin in Western Europe at different spatial and temporal scales to enable comparison between different data sources (e.g. stations and climate models). Meteorological drought is assessed in two ways: using annual minimum precipitation amounts as a function of return period, and using troughs under threshold as a function of return period. The Weibull extreme value type 3 distribution has been fitted to both sources of information. Results show that the trough-under-threshold precipitation is larger than the annual minimum precipitation for a specific return period. Annual minimum precipitation values increase with spatial scale, being most pronounced for small temporal scales. The uncertainty in annual minimum point precipitation varies between 68% for the 30-day precipitation with a return period of 100 years, and 8% for the 120-day precipitation with a return period of 10 years. For spatially-averaged values, these numbers are slightly lower. The annual discharge deficit is significantly related to the annual minimum precipitation.

Citation Booij, M. J. & de Wit, M. J. M. (2010) Extreme value statistics for annual minimum and trough-under-threshold precipitation at different spatio-temporal scales. Hydrol. Sci. J. 55(8), 1289–1301.     

夏县痕量氢气背景值突变分析

应用ATG6118H痕量氢分析仪在山西夏县地震台开展了试验测试,记录到比较翔实的观测数据。根据观测数据结果分析,地震前观测到断层氢气的异常特征是高值突跳,异常幅度大、时间短。对2012年3-11月痕量氢观测的背景值突变现象进行重点分析,对观测资料的进一步使用奠定基础,为新型仪器观测提供事实依据。     

河北张北6.2级地震中农村房屋破坏特征分析

对１９９８年１月１０日河北张北６．２级地震灾区的房屋建筑类型进行了划分,概述了各类建筑物的平面布置、墙体、屋顶、承重结构和地基等情况,总结了各类房屋建筑的破坏特点,并对造成破坏严重的原因进行了分析     

Watershed studies at the Hubbard Brook Experimental Forest: Building on a long legacy of research with new approaches and sources of data

The Hubbard Brook Experimental Forest (HBEF) was established in 1955 by the U.S. Department of Agriculture, Forest Service out of concerns about the effects of logging increasing flooding and erosion. To address this issue, within the HBEF hydrological and micrometeorological monitoring was initiated in small watersheds designated for harvesting experiments. The Hubbard Brook Ecosystem Study (HBES) originated in 1963, with the idea of using the small watershed approach to study element fluxes and cycling and the response of forest ecosystems to disturbances, such as forest management practices and air pollution. Early evidence of acid rain was documented at the HBEF and research by scientists at the site helped shape acid rain mitigation policies. New lines of investigation at the HBEF have built on the long legacy of watershed research resulting in a shift from comparing inputs and outputs and quantifying pools and fluxes to a more mechanistic understanding of ecosystem processes within watersheds. For example, hydropedological studies have shed light on linkages between hydrologic flow paths and soil development that provide valuable perspective for managing forests and understanding stream water quality. New high frequency in situ stream chemistry sensors are providing insights about extreme events and diurnal patterns that were indiscernible with traditional weekly sampling. Additionally, tools are being developed for visual and auditory data exploration and discovery by a broad audience. Given the unprecedented environmental change that is occurring, data from the small watersheds at the HBEF are more relevant now than ever and will continue to serve as a basis for sound environmental decision-making.     

A comparison of gauge and radar precipitation data for simulating an extreme hydrological event in the Severn Uplands,UK

This paper provides a comparison of gauge and radar precipitation data sources during an extreme hydrological event. November–December 2006 was selected as a time period of intense rainfall and large river flows for the Severn Uplands, an upland catchment in the United Kingdom. A comparison between gauge and radar precipitation time‐series records for the event indicated discrepancies between data sources, particularly in areas of higher elevation. The HEC‐HMS rainfall‐runoff model was selected to assess the accuracy of the precipitation to simulate river flows for the extreme event. Gauge, radar and gauge‐corrected radar rainfall were used as model inputs. Universal cokriging was used to geostatistically interpolate gauge data with radar and elevation data as covariates. This interpolated layer was used to calculate the mean‐field bias and correct the radar composites. Results indicated that gauge‐ and gauge‐corrected radar‐driven models replicated flows adequately for the extreme event. Gauge‐corrected flow predictions produced an increase in flow prediction accuracy when compared with the raw radar, yet predictions were comparative in accuracy to those using the interpolated gauge network. Subsequent investigations suggested this was due to an adequate spatial and temporal resolution of the precipitation gauge network within the Severn Uplands. Results suggested that the six rain gauges could adequately represent precipitation variability of the Severn Uplands to predict flows at an approximately equal accuracy to that obtained by radar. Temporally, radar produced an increase in flow prediction accuracy in mountainous reaches once the gauge time step was in excessive of an hourly interval. Copyright © 2010 John Wiley & Sons, Ltd.     

Comparison of artificial neural network models for hydrologic predictions at multiple gauging stations in an agricultural watershed

This paper reports on an evaluation of the use of artificial neural network (ANN) models to forecast daily flows at multiple gauging stations in Eucha Watershed, an agricultural watershed located in north‐west Arkansas and north‐east Oklahoma. Two different neural network models, the multilayer perceptron (MLP) and the radial basis neural network (RBFNN), were developed and their abilities to predict stream flow at four gauging stations were compared. Different scenarios using various combinations of data sets such as rainfall and stream flow at various lags were developed and compared for their ability to make flow predictions at four gauging stations. The input vector selection for both models involved quantification of the statistical properties such as cross‐, auto‐ and partial autocorrelation of the data series that best represented the hydrologic response of the watershed. Measured data with 739 patterns of input–output vector were divided into two sets: 492 patterns for training, and the remaining 247 patterns for testing. The best performance based on the RMSE, R² and CE was achieved by the MLP model with current and antecedent precipitation and antecedent flow as model inputs. The MLP model testing resulted in R² values of 0·86, 0·86, 0·81, and 0·79 at the four gauging stations. Similarly, the testing R² values for the RBFNN model were 0·60, 0·57, 0·58, and 0·56 for the four gauging stations. Both models performed satisfactorily for flow predictions at multiple gauging stations, however, the MLP model outperformed the RBFNN model. The training time was in the range 1–2 min for MLP, and 5–10 s for RBFNN on a Pentium IV processor running at 2·8 GHz with 1 MB of RAM. The difference in model training time occurred because of the clustering methods used in the RBFNN model. The RBFNN uses a fuzzy min‐max network to perform the clustering to construct the neural network which takes considerably less time than the MLP model. Results show that ANN models are useful tools for forecasting the hydrologic response at multiple points of interest in agricultural watersheds. Copyright © 2008 John Wiley & Sons, Ltd.     

The Kiryu Experimental Watershed: 50-years of rainfall-runoff data for a forest catchment in central Japan

The Kiryu Experimental Catchment (KEW) is a small (5.99 ha) forest catchment located in Shiga Prefecture, central Japan (34°58′ N, 136°00′ E; www.bluemoon.kais.kyoto-u.ac.jp/kiryu/contents.html ). Around this area, forest devastation occurred from ca. 1250 to ca. 150 years ago because of overuse of forest and timbers. Then, hillside forestation was carried out for more than 100 years to prevent soil erosion and support the timber industry, and consequently, most of this area is now covered with plantation forests mainly by Chamaecyparis obtusa Sieb. et Zucc. (Japanese cypress) planted around 1960's. This plantation forest is not actively managed. The KEW is one of the leading experimental forests with long-term monitoring data in Japan. Research in the KEW began in 1967 to elucidate the hydrological and biogeochemical processes in the forested catchment in relation to climate, geology, soil, and vegetation growth. Since then, the long-term hydrological data of precipitation, runoff and sediment transport are continuously monitoring. In this study, we provide the data and preliminarily discuss the rainfall–runoff patterns and sediment transport through 50 years in the KEW. The annual precipitation and the maximum daily rainfall have been greater than the average over the last decade. In response to the rainfall patterns, the ratio of annual direct runoff to precipitation was also larger in the last decade. The sediment transport in this decade was consequently larger than the preceding decades. Our data presented here suggest that a close relationship exists between the climate condition, rainfall–runoff response, sediment dynamics, as well as a slowly progressing change of forest condition.     

Performance evaluation of interpolation methods for incorporating rain gauge measurements into NEXRAD precipitation data: a case study in the Upper Guadalupe River Basin

High spatial and temporal resolution of precipitation data is critical input for hydrological budget estimation and flash flood modelling. This study evaluated four methods [Bias Adjustment (BA), Simple Kriging with varying Local Means (SKlm), Kriging with External Drift (KED), and Regression Kriging (RK)] for their performances in incorporating gauge rainfall measurements into Next Generation Weather Radar (NEXRAD) multi‐sensor precipitation estimator (MPE; hourly and 4 × 4 km²). Measurements from a network of 50 gauges at the Upper Guadalupe River Basin, central Texas and MPE data for the year 2004 were used in the study. We used three evaluation coefficients percentage bias (PB), coefficient of determination (R²), and Nash–Sutcliffe efficiency (NSE) to examine the performance of the four methods for preserving regional‐ and local‐scale characteristics of observed precipitation data. The results show that the two Kriging‐based methods (SKlm and RK) are in general better than BA and KED and that the PB and NSE criteria are better than the R² criterion in assessing the performance of the four methods. It is also worth noting that the performance of one method at regional scale may be different from its performance at local scale. Critical evaluation of the performance of different methods at local or regional scale should be conducted according to the different purposes. The results obtained in this study are expected to contribute to the development of more accurate spatial rainfall products for hydrologic budget and flash flood modelling. Copyright © 2011 John Wiley & Sons, Ltd.     

The role of hydrological processes in ecosystem conservation: Comprehensive water management for a wetland in an arid climate

Water agreements between Mexico and the United States have been crucial to preserving and restoring the Colorado River Delta's wetlands. Nowadays, increased water demand and climate change in the Colorado River Basin could threaten the conservation of the Ciénega de Santa Clara, a 4709 ha coastal wetland at the Sonoran Desert's edge. The international Ramsar convention recognizes the Ciénega de Santa Clara ecosystem for providing vital ecological services, including habitat for endemic, endangered, and migratory species. The hydrology of this wetland has not been completely understood since the 2010–2011 trial run of the Yuma Desalting Plant. Therefore, this study was conducted to identify and quantify the hydrological elements essential for the conservation of this wetland, under three scenarios: (a) normal inflow conditions of the water source – the Wellton-Mohawk canal; (b) inflow reductions, and; (c) an increase of temperature due to global warming. Water and mass balances estimates were conducted every month during 2014–2015; in situ measurements of inflows were carried out on Southern International Boundary in Wellton-Mohawk canal, the Riíto Drain, groundwater, and precipitation: evapotranspiration outputs were estimated using local weather stations and Penman-Monteith formulations. Temperature increases were based on the Intergovernmental Panel on Climate Change projections for the next 100 years. Results showed disconnection in the surface flow of water from the wetland to the adjacent Gulf of California. This behaviour was observed mainly in the summer months in the three scenarios. The disconnections reduced the wetland area and water storage. The hydrological functionality of the Ciénega de Santa Clara wetland depends on the water supply from the Wellton-Mohawk canal, with a minimum continuous discharge of 5.10 m³ s⁻¹ during the summer months.     

Modelling streamflow trends for a watershed with limited data: case of the Litani basin,Lebanon

Abstract

Streamflow variability in the Upper and Lower Litani basin, Lebanon was modelled as there is a lack of long-term measured runoff data. To simulate runoff and streamflow, daily rainfall was derived using a stochastic rainfall generation model and monthly rainfall data. Two distinct synthetic rainfall models were developed based on a two-part probabilistic distribution approach. The rainfall occurrence was described by a Markov chain process, while the rainfall distribution on wet days was represented by two different distributions (i.e. gamma and mixed exponential distributions). Both distributions yielded similar results. The rainfall data were then processed using water balance and routing models to generate daily and monthly streamflow. Compared with measured data, the model results were generally reasonable (mean errors ranging from 0.1 to 0.8?m³/s at select locations). Finally, the simulated monthly streamflow data were used to investigate discharge trends in the Litani basin during the 20th century using the Mann-Kendall and Sen slope nonparametric trend detection methods. A significant drying trend of the basin was detected, reaching a streamflow reduction of 0.8 and 0.7 m³/s per decade in January for the Upper and Lower basin, respectively.

Editor D. Koutsoyiannis; Associate editor Sheng Yue

Citation Ramadan, H.H., Beighley, R.E., and Ramamurthy, A.S., 2012. Modelling streamflow trends for a watershed with limited data: case of the Litani basin, Lebanon. Hydrological Sciences Journal, 57 (8), 1516–1529.     

Floodnet: a telenetwork for acquisition,processing and dissemination of earth observation data for monitoring and emergency management of floods

The aim of FLOODNET is to provide a communications and data distribution facility specifically designed to meet the demanding temporal requirements of flood monitoring within the European Union (EU). Currently, remotely sensed data are not fully utilized for flood applications because potential users are not familiar with the procedure for acquiring the data and do not have a defined route for obtaining help in processing and interpreting the data. FLOODNET will identify the potential user groups within the EU and will, by demonstration, education and the use of telematics, increase the awareness of users to the capabilities of earth observation (EO) and the means by which they can acquire EO data. FLOODNET will act as a filter between users and satellite operation planners to help assign priorities for data acquisition against previously agreed criteria. The network will encourage a user community and will facilitate cross-sector information transfer, particularly between ‘flood experts’ and administrative decision makers. The requirement for two levels of flood mapping is identified: (1) a rapid, ‘broad-brush’ approach to assess the general flood situation and identify areas at greatest risk and in need of immediate assistance; (2) a detailed mapping approach, less critical in time, suitable for input to hydrological models or for flood risk evaluation. A likely networking technology is outlined, the basic functionality of a FLOODNET demonstrator is described and some of the economic benefits of the network are identified. © 1997 John Wiley & Sons, Ltd.     

An Asymptotic Analysis of a Simple Model for the Structure and Dynamics of the Ramdas Layer

This paper presents a complete asymptotic analysis of a simple model for the evolution of the nocturnal temperature distribution on bare soil in calm clear conditions. The model is based on a simplified flux emissivity scheme that provides a nondiffusive local approximation for estimating longwave radiative cooling near ground. An examination of the various parameters involved shows that the ratio of the characteristic radiative to the diffusive timescale in the problem is of order 10⁻³, and can therefore be treated as a small parameter (μ). Certain other plausible approximations and linearization lead to a new equation whose asymptotic solution as μ → 0 can be written in closed form. Four regimes, consisting of a transient at nominal sunset, a radiative-diffusive boundary (‘Ramdas’) layer on ground, a boundary layer transient and a radiative outer solution, are identified. The asymptotic solution reproduces all the qualitative features of more exact numerical simulations, including the occurrence of a lifted temperature minimum and its evolution during night, ranging from continuing growth to relatively sudden collapse of the Ramdas layer.     

The phosphoric acid leak from the wreck of the MV Ece in the English Channel in 2006: Assessment with a ship of opportunity, an operational ecosystem model and historical data

This study evaluates the ship of opportunity (Ferrybox) concept for both sustained monitoring of UK shelf sea waters and numerical model validation. Release of phosphate from the wreck of a chemical tanker (MV Ece) in the western English Channel (49.73 degrees N, 3.25 degrees W) in March 2006 is used to demonstrate the importance of sustained observations in decision support systems and policy development. The Ferrybox system continuously collects sea surface (5m) data from a suite of autonomous electronic sensors installed on a passenger ferry operating year-round between Portsmouth (UK) and Bilbao (Spain). The detection of anomalously high concentrations of phosphate (1.54mmolm(-3), four times the usual level) and onset of phytoplankton growth close to the wreck site in March 2006 was placed in the context of multiple years of measurements (phosphate, nitrate, silicate and chlorophyll) collected from the Ferrybox system (2003-2006) and the long-term time series station E1 (50.03 degrees N, 4.65 degrees W, 1930-1987) in the English Channel. With regard to decision support, release of phosphate from the tanker is unlikely to pose a threat as phytoplankton growth at the end of winter is not unusual in this region and dissolved inorganic nitrogen rather than phosphate (DIN:DIP=10-18) is likely to ultimately limit algal growth in spring 2006. With regard to policy development, the Oslo and Paris (OSPAR) commissions recommendation of sampling every three years in "non-problem areas" is likely to provide statistically inadequate data, given the interannual and decadal variability identified in the Ferrybox and E1 data: the Ferrybox data show that oceanic winter nutrient concentrations varied by 35-50% between 2003/2004 and 2005/2006 due to deeper mixing of water off-shelf in early 2005/2006 and comparisons between the Ferrybox and E1 years show that the western English Channel is currently experiencing a low in phosphate concentrations similar to those in the 1960s. The importance of Ferrybox data in evaluating the reliability of predictive operational models needed in decision support is also demonstrated, by highlighting both strengths and weaknesses in a state-of-the-art ecosystem model designed for UK shelf waters.     

Sampling epifauna, a necessity for a better assessment of benthic ecosystem functioning: an example of the epibenthic aggregated species Ophiothrix fragilis from the Bay of Seine

Sampling the sea bottom surface remains difficult because of the surface hydraulic shock due to water flowing through the gear (i.e., the bow wave effect) and the loss of epifauna organisms due to the gear’s closing mechanism. Slow-moving mobile epifauna, such as the ophiuroid Ophiothrix fragilis, form high-density patches in the English Channel, not only on pebbles like in the Dover Strait or offshore Brittany but also on gravel in the Bay of Seine (>5000 ind m⁻²). Such populations form high biomasses and control the water transfer from the water column to the sediment. Estimating their real density and biomass is essential for the assessment of benthic ecosystem functioning using trophic web modelling. In this paper, we present and discuss the patch patterns and sampling efficiency of the different methods for collecting in the dense beds of O. fragilis in the Bay of Seine. The large Hamon grab (0.25 m⁻²) highly under-estimated the ophiuroid density, while the Smith McIntyre appeared adequate among the tested sampling grabs. Nowadays, diving sampling, underwater photography and videos with remote operated vehicle appear to be the recommended alternatives to estimate the real density of such dense slow-moving mobile epifauna.