Crowdsourced approaches for stage measurements at ungauged locations using smartphones

ABSTRACT

The growing availability of smart devices with advanced sensors has increased the opportunities for citizen science applications for environmental monitoring. Accurate and widespread monitoring of river stage is vital for modeling water resources. Reliable data points are required for model calibration and validation in forecast studies. While current embedded monitoring systems provide accurate measurements, the cost to replicate these systems on a large domain is prohibitively expensive, limiting the quantity of data available. This project describes a new method to accurately measure river levels using smartphone sensors. Pictures of the same point on the river’s surface are taken to perform calculations based on the GPS location and spatial orientation of the smartphone. The proposed implementation is significantly more accessible than existing water measuring systems while offering similar accuracy. A case study is performed to evaluate the accuracy and sensitivity of the measurements to changes in distance.     

Precipitation regional extreme mapping as a tool for ungauged areas and the assessment of climate changes

The spatial‐temporal characteristics of mean annual daily maximum precipitation events in the upper Yangtze River basin in China are examined using a framework termed precipitation regional extreme mapping (PREM). The framework consists of regional analyses and mapping methods, which have the capability to assess the presence or absence of climate change. The findings confirm the homogeneous regions identified by Wang (2002) using a heterogeneity measure, where all three regions have heterogeneity less than 1.0. The Pearson type III (PE3) distribution was found to be acceptable for all three regions, while the generalized extreme‐value distribution performs better than PE3 for Region I (eastern portion of the upper Yangtze basin). Two indices, root mean square error and mean bias, were used to access the performance of the extreme map, and the results show that the map of extreme can predict precipitation for ungauged regions with acceptable accuracy. The regional frequency maps were used in conjunction with the Student's t‐test to identify the statistical significance of changes of extremes in precipitation. Results indicate that there have been no significant changes in maximum daily precipitation magnitudes over the past four decades, a finding that is valuable for the safe planning of major hydraulic projects and the management and planning of water resources in the upper Yangtze River basin. Copyright © 2015 John Wiley & Sons, Ltd.     

Generation of runoff series at ungauged locations using empirical orthogonal functions in combination with kriging

The method of Empirical Orthogonal Functions (EOF method) is combined with an objective interpolation technique, kriging, to generate runoff series at ungauged locations. In a case study the results are compared to series interpolated by a combination of EOF analysis and regression using catchment characteristics as independent variables. The results are also compared to linear weighting of an existing runoff series, a commonly used method for spatial interpolation. The influence of altitude on the runoff is studied comparing kriging based on 2 and 3 coordinates. The study showed that the capacity of EOF analysis combined with kriging is as good as the traditionally used linear weighting. The results, when altitude is included in the kriging, are improved.     

Comparison of the return period for landslide-triggering rainfall events in Japan based on standardization of the rainfall period

The intensity of rainfall events with potential to cause landslides has varying temporal characteristics. In this study, the time at which the 72-h accumulated rainfall reached its maximum was used to standardize the period of rainfall measurement. The proposed standardization of the rainfall period was used in conjunction with the return level of rainfall intensity, obtained from intensity–duration–frequency curves, to investigate rainfall intensity anomalies associated with 10 hazardous rainfall events that triggered numerous landslides at the regional scale in Japan. These landslides included shallow landslides in volcanic and non-volcanic areas, as well as deep-seated landslides. The rainfall events that triggered the shallow landslides were divided into two types: downpours that repeatedly reached close to the 100-year return level within approximately 3–4 h, and accumulated rainfall that reached close to 200–400 mm over longer time intervals but within 72 h. Lithological differences seemed unrelated to the differences between the two types of shallow-landslide-triggering rainfall; however, precipitation >1000 mm was necessary to trigger deep-seated landslides. Although the characteristics of the hyetographs differed markedly among the landslide-triggering rainfall events, all the landslides could have been triggered when the mean rainfall intensity reached the 100-year rainfall level during the standardized period. Thus, the landslide trigger can be evaluated indirectly based on the increase in the return level of the mean rainfall intensity, which could provide a means for estimating the time of landslide occurrence.     

Characteristic scales, temporal variability modes and simulation of monthly Elbe River flow time series at ungauged locations

Spatial and temporal patterns of the long-range extreme monthly Elbe River flows across Germany are investigated, using various statistical methods, among others, principal component and wavelet analysis. Characteristic time scales are derived for various time series statistics. The wavelet analysis of the raw river discharge data as well as of the major principal component reveal the main oscillatory components and their temporal behavior, namely low frequency oscillations at interannual (6.9 yr) and interdecadal (13.9 yr) scales. The EOFs at ungauged stations are estimated from the principal components of the observed time series sampled over a limited time span whose length equals the major temporal variability scale (≈7 yr). The EOFs (empirical orthogonal functions) obtained in this way are subsequently used to simulate long-range flows at these locations. A comparison of this method with linear interpolation and ordinary kriging of the EOF shows the superiority of the former in representing the distributional properties of the observed time series. The simulated time series preserve also short and long-memory.     

Comparison of SDSM and LARS-WG for simulation and downscaling of extreme precipitation events in a watershed

Future climate projections of Global Climate Models (GCMs) under different emission scenarios are usually used for developing climate change mitigation and adaptation strategies. However, the existing GCMs have only limited ability to simulate the complex and local climate features, such as precipitation. Furthermore, the outputs provided by GCMs are too coarse to be useful in hydrologic impact assessment models, as these models require information at much finer scales. Therefore, downscaling of GCM outputs is usually employed to provide fine-resolution information required for impact models. Among the downscaling techniques based on statistical principles, multiple regression and weather generator are considered to be more popular, as they are computationally less demanding than the other downscaling techniques. In the present study, the performances of a multiple regression model (called SDSM) and a weather generator (called LARS-WG) are evaluated in terms of their ability to simulate the frequency of extreme precipitation events of current climate and downscaling of future extreme events. Areal average daily precipitation data of the Clutha watershed located in South Island, New Zealand, are used as baseline data in the analysis. Precipitation frequency analysis is performed by fitting the Generalized Extreme Value (GEV) distribution to the observed, the SDSM simulated/downscaled, and the LARS-WG simulated/downscaled annual maximum (AM) series. The computations are performed for five return periods: 10-, 20-, 40-, 50- and 100-year. The present results illustrate that both models have similar and good ability to simulate the extreme precipitation events and, thus, can be adopted with confidence for climate change impact studies of this nature.     

Validation and calibration of solar radiation equations for estimating daily reference evapotranspiration at cool semi-arid and arid locations

ABSTRACT

In this work, the applicability of 12 solar radiation (R_S) estimation models and their impacts on daily reference evapotranspiration (ET_o) estimates using the Penman‐Monteith FAO-56 (PMF-56) method were tested under cool arid and semi-arid conditions in Iran. The results indicated that the average increase in accuracy of the ET_o estimates by the calibrated R_S models, quantified by the decrease in RMSE, was 2.8% and 6.4% for semi-arid and arid climates, respectively. Mean daily deviations in the estimated ET_o by the calibrated R_S equations in semi-arid climates varied from ?0.283?mm/d^-1 for the Glover‐McCulloch model to 0.080?mm/d for the El-Sebaii model, with an average of ?0.109?mm/d^-1, and in arid climates, they ranged from ?0.522?mm/d^-1 for the Samani model to 0.668?mm/d for the El-Sebaii model, with an average of 0.125?mm/d^-1.

Editor D. Koutsyiannis; Associate editor Not assigned     

An efficient methodology for estimating irrigation return flow coefficients of irrigated crops at watershed and seasonal scale

Irrigation return flow coefficients, i.e. the ratio between the quantity of water returned from the cultivated area to the groundwater system and the amount of abstraction, vary by more than 50% for rice cultivation using standing water irrigation to 0% in the case of drip irrigation technique. This component of the groundwater budget plays an important role, particularly in intensively irrigated areas. Thus, to avoid any inaccurate aquifer budgeting, modelling and consequently any erroneous watershed management, this component needs to be accurately assessed for a particular time‐step (e.g. weekly, seasonally) onto the studied area. The present paper proposes a cost‐effective and useful methodology for assessing irrigation return flow coefficients (C_f = irrigation return flow/pumping flow) based on (i) basic crops field survey and meteorological data and (ii) the use of a simple hydraulic model that combines both water balance technique and unsaturated/saturated flow theory. An attempt to estimate the uncertainty of irrigation return flow coefficient estimates based on the uncertainty introduced by the pumping and the natural spatial variability of the soil characteristics is also proposed. Results have been compared to real field conditions and allow us to (i) estimate the uncertainty and (ii) validate and demonstrate the robustness of the applied methodology. The proposed methodology allows relatively good estimates of the irrigation return flow coefficients at watershed and seasonal scale. The irrigation return flow coefficients are calculated as: 51 ± 8% in rainy season (Kharif) and 48 ± 4% in summer (Rabi) for rice; 26 ± 11% in rainy season and 24 ± 4% in summer for vegetables; 13 ± 8% in rainy season and 11 ± 3% in summer for flowers. These results were found to be consistent with the existing literature. Copyright © 2007 John Wiley & Sons, Ltd.     

Formulae for estimating extreme changes of lengths in spatial affine transformation

Summary Formulae (27) and (28) which make it possible to estimate the minimum and maximum value of the deformation in length in affine transformation in space have been derived. Both values are determined by means of the elements of the given transformation matrixA without having to form the productAA ^T, or compute the corresponding eigenvalues explicitly. The derived formulae hold true under the assumption that both extreme values do not differ from each other too much.Dedicated to 90th Birthday of Professor Frantiek Fiala     

Comparison of design peak flow estimation methods for ungauged basins in Iran

ABSTRACT

Determining the catchment design peak flow is crucial in hydrological practice. In this paper, the conceptual rainfall–runoff model EBA4SUB (Event-Based Approach for Small and Ungauged Basins) was applied in six catchments in Iran. The aims were to test EBA4SUB in reconstructing runoff hydrographs for the investigated case studies and to provide a suitable alternative for the review and updating of design peak flow estimation in Iran. The EBA4SUB output was compared with previous studies on selected catchments. The results show, for all case studies, a large variability in the peak flow values; the EBA4SUB model gave flow values similar to the other methodologies. The EBA4SUB model can be recommended for the following reasons: (i) it minimizes the subjectivity of the modeller. (ii) its modules are based on state-of-the-art procedures, which have been appropriately optimized for ungauged basins; and (iii) it furnishes the whole design flood hydrograph.     

Multivariate approaches optimize locations of groundwater pumping facilities for different hydrogeological scales

A number of optimization approaches regarding the design location of groundwater pumping facilities in heterogeneous porous media have elicited little discussion. However, the location of groundwater pumping facilities is an important factor because it affects water resource usage. This study applies two optimization approaches to estimate the best recharge zone and suitable locations of the pumping facilities in southwestern Taiwan for different hydrogeological scales. First, for the regional scale, this study employs numerical modelling, MODFLOW‐96, to simulate groundwater direction and the optimal recharge zone in the study area. Based on the model's calibration and verification results, this study preliminarily utilizes the simulated spatial direction of groundwater and compares the safe yield for each well group in order to determine the best recharge zone. Additionally, for the local scale, the micro‐hydrogeological characteristics are considered before determining the design locations of the pumping facilities. According to drawdown record data from six observation wells derived from pumping tests at the best recharge area, this study further utilizes the modified artificial neural network approach to improve the accuracy of the estimation parameters as well as to analyse the direction and anisotropy of the hydraulic conductivities of an equivalent homogeneous aquifer. The results suggested that the best locations for the pumping facilities are along the more permeable major direction. Copyright © 2011 John Wiley & Sons, Ltd.     

Trend and extreme occurrence of precipitation in a mid‐latitude Eurasian steppe watershed at various time scales

The confounding effects of step change invalidate the stationarity assumption of commonly used trend analysis methods such as the Mann–Kendall test technique, so previous studies have failed to explain inconsistencies between detected trends and observed large precipitation anomalies. The objectives of this study were to (1) formulate a trend analysis approach that considers nonstationarity due to step changes, (2) use this approach to detect trends and extreme occurrences of precipitation in a mid‐latitude Eurasian steppe watershed in North China, and (3) examine how runoff responds to precipitation trends in the study watershed. Our results indicate that annual precipitation underwent a marginal step jump around 1995. The significant annual downward trend after 1994 was primarily due to a decrease in summer rainfall; other seasons exhibited no significant precipitation trends. At a monthly scale, July rainfall after 1994 exhibited a significant downward trend, whereas precipitation in other months had no trend. The percentage of wet days also underwent a step jump around 1994 following a significant decreasing trend, although the precipitation intensity exhibited neither a step change nor any significant trend. However, both low‐frequency and high‐frequency precipitation events in the study watershed occurred more often after than before 1994; probably as either a result or an indicator of climate change. In response to these precipitation changes, the study watershed had distinctly different precipitation‐runoff relationships for observed annual precipitations of less than 300 mm, between 300 and 400 mm, and greater than 400 mm. Copyright © 2013 John Wiley & Sons, Ltd.     

Formation of homogeneous regions for regional frequency analysis of extreme precipitation events in the Czech Republic

Extreme high precipitation amounts are among environmental events with the most disastrous consequences for human society. This paper deals with the identification of ‘homogeneous regions’ according to statistical characteristics of precipitation extremes in the Czech Republic, i.e. the basic and most important step toward the regional frequency analysis. Precipitation totals measured at 78 stations over 1961–2000 are used as an input dataset. Preliminary candidate regions are formed by the cluster analysis of site characteristics, using the average-linkage clustering and Ward’s method. Several statistical tests for regional homogeneity are utilized, based on the 10-yr event and the variation of L-moment statistics. In compliance with results of the tests, the area of the Czech Republic has been divided into four homogeneous regions. The findings are supported by simulation experiments proposed to evaluate stability of the test results. Since the regions formed reflect also climatological differences in precipitation regimes and synoptic patterns causing high precipitation amounts, their future application may not be limited to the frequency analysis of extremes.     

Comparison of methods for estimating earth resistivity from airborne electromagnetic measurements

Earth resistivity estimates from frequency domain airborne electromagnetic data can vary over more than two orders of magnitude depending on the half-space estimation method used. Lookup tables are fast methods for estimating half-space resistivities, and can be based on in-phase and quadrature measurements for a specified frequency, or on quadrature and sensor height. Inverse methods are slower, but allow sensor height to be incorporated more directly. Extreme topographic relief can affect estimates from each of the methods, particularly if the portion of the line over the topographic feature is not at a constant height above ground level. Quadrature–sensor height lookup table estimates are generally too low over narrow valleys. The other methods are also affected, but behave less predictably. Over very good conductors, quadrature–sensor height tables can yield resistivity estimates that are too high. In-phase–quadrature tables and inverse methods yield resistivity estimates that are too high when the earth has high magnetic susceptibility, whereas quadrature–sensor height methods are unaffected. However, it is possible to incorporate magnetic susceptibility into the in-phase–quadrature lookup table. In-phase–quadrature lookup tables can give different results according to whether the tables are ordered according to the in-phase component or the quadrature component. The rules for handling negative in-phase measurements are particularly critical. Although resistivity maps produced from the different methods tend to be similar, details can vary considerably, calling into question the ability to make detailed interpretations based on half-space models.     

Nonlinear dynamics and recurrence analysis of extreme precipitation for observed and general circulation model generated climates

A statistical framework based on nonlinear dynamics theory and recurrence quantification analysis of dynamical systems is proposed to quantitatively identify the temporal characteristics of extreme (maximum) daily precipitation series. The methodology focuses on both observed and general circulation model (GCM) generated climates for present (1961–2000) and future (2061–2100) periods which correspond to 1xCO₂ and 2xCO₂ simulations. The daily precipitation has been modelled as a stochastic process coupled with atmospheric circulation. An automated and objective classification of daily circulation patterns (CPs) based on optimized fuzzy rules was used to classify both observed CPs and ECHAM4 GCM‐generated CPs for 1xCO₂ and 2xCO₂ climate simulations (scenarios). The coupled model ‘CP‐precipitation’ was suitable for precipitation downscaling. The overall methodology was applied to the medium‐sized mountainous Mesochora catchment in Central‐Western Greece. Results reveal substantial differences between the observed maximum daily precipitation statistical patterns and those produced by the two climate scenarios. A variable nonlinear deterministic behaviour characterizes all climate scenarios examined. Transitions’ patterns differ in terms of duration and intensity. The 2xCO₂ scenario contains the strongest transitions highlighting an unusual shift between floods and droughts. The implications of the results to the predictability of the phenomenon are also discussed. Copyright © 2013 John Wiley & Sons, Ltd.     

Comparison of two approaches for generation of daily rainfall data

There has been extensive research on the problem of stochastically generating daily rainfall sequences for use in water management applications. Srikanthan and McMahon [Australia Water Resources Council, Canberra, 1985] proposed a transition probability matrix (TPM) model that performs better for Australian rainfall than many alternative models, particularly where long records (say 100 years) are available. Boughton [Report 99/9, CRC for Catchment Hydrology, Monash University, Melbourne, 21pp, 1999] incorporated an empirical adjustment into the TPM model that allows the model to reproduce the observed variability in the annual rainfall. More recently, Harrold et al. [Water Resour Res 39(10, 12):1300, 1343, 2003a,b] proposed nonparametric models for the generation of daily rainfall occurrences and rainfall amounts on wet days. By conditioning on short, medium and long-term characteristics, this approach is also able to preserve the variability in annual rainfall. In this study, the above two approaches were used to generate daily rainfall data for Sydney and Melbourne, and the results evaluated. Both approaches preserved most of the daily, monthly and annual characteristics that were compared, with the nonparametric approach providing marginally better performance at the cost of greater model complexity. The nonparametric approach was also able to preserve the variability and persistence in the annual number of wet days.     

Comparison of approaches for predicting solute transport: sandbox experiments

The main purpose of this paper was to compare three approaches for predicting solute transport. The approaches include: (1) an effective parameter/macrodispersion approach (Gelhar and Axness 1983); (2) a heterogeneous approach using ordinary kriging based on core samples; and (3) a heterogeneous approach based on hydraulic tomography. We conducted our comparison in a heterogeneous sandbox aquifer. The aquifer was first characterized by taking 48 core samples to obtain local-scale hydraulic conductivity (K). The spatial statistics of these K values were then used to calculate the effective parameters. These K values and their statistics were also used for kriging to obtain a heterogeneous K field. In parallel, we performed a hydraulic tomography survey using hydraulic tests conducted in a dipole fashion with the drawdown data analyzed using the sequential successive linear estimator code (Yeh and Liu 2000) to obtain a K distribution (or K tomogram). The effective parameters and the heterogeneous K fields from kriging and hydraulic tomography were used in forward simulations of a dipole conservative tracer test. The simulated and observed breakthrough curves and their temporal moments were compared. Results show an improvement in predictions of drawdown behavior and tracer transport when the K tomogram from hydraulic tomography was used. This suggests that the high-resolution prediction of solute transport is possible without collecting a large number of small-scale samples to estimate flow and transport properties that are costly to obtain at the field scale.