Scale impacts on spatial variability in reference evapotranspiration

ABSTRACT

Evapotranspiration (ET) is one of the most important components in the hydrological cycle, and a key variable in hydrological modelling and water resources management. However, understanding the impacts of spatial variability in ET and the appropriate scale at which ET data should be incorporated into hydrological models, particularly at the regional scale, is often overlooked. This is in contrast to dealing with the spatial variability in rainfall data where existing guidance is widely available. This paper assesses the impacts of scale on the estimation of reference ET (ETo) by comparing data from individual weather stations against values derived from three national datasets, at varying resolutions. These include the UK Climate Impacts Programme 50 km climatology (UKCP₅₀), the UK Met Office 5 km climatology (UKMO₅) and the regional values published in the Agricultural Climate of England and Wales (ACEW). The national datasets were compared against the individual weather station data and the UKMO₅ was shown to provide the best estimate of ETo at a given site. The potential impacts on catchment modelling were then considered by mapping variance in ETo to show how geographical location and catchment size can have a major impact, with small lowland catchments having much higher variance than those with much larger areas or in the uplands. Some important implications for catchment hydrological modelling are highlighted.

Editor D. Koutsoyiannis; Associate editor L. Ruiz     

Correlation dimension estimation of hydrological series and data size requirement: myth and reality/Estimation de la dimension de corrélation de séries hydrologiques et taille nécessaire du jeu de données: mythe et réalité

Abstract

The issue of data size (length) requirement for correlation dimension estimation continues to be the nucleus of criticisms on the (low) correlation dimensions reported for hydrological series. The present study addresses this issue from the viewpoints of both the existing theoretical guidelines and the practical reality. For this purpose, correlation dimension analysis is carried out for various data sizes from each of three types of series: (a) stochastic series (artificially generated using a random number generation technique); (b) chaotic series (artificially generated using the Henon map equation); and (c) hydrological series (real flow data observed on the Göta River in Sweden). The outcomes of the analysis of the (artificial) stochastic and chaotic series are used as a basis for interpreting the outcomes of the hydrological series. It is found that reliable dimension results for the stochastic and chaotic series are obtained even when the data size is only a few hundred points (i.e. no underestimation of dimension for small data sizes is visible), with no significant change in the scaling regimes (of the dimension plots) with respect to data size. This implies that the dimension results obtained for the hydrological series even with a few hundred points are also close to the actual ones. The insignificant difference in the scaling regimes for the various data sizes further supports this point. These results lead to the conclusions that: (1) the issue of data size requirement for correlation dimension estimation is more of a myth than reality; (2) the dimension estimates reported thus far for hydrological series could indeed be close to the actual ones (unless influenced by factors other than data size, e.g. delay time, noise, zeros, intermittency).     

Hydrological response characteristics of Mediterranean catchments at different time scales: a meta-analysis

ABSTRACT

This work examines 140 hydrological studies conducted in the Mediterranean region. It identifies key characteristics of the hydrological responses of Mediterranean catchments at various time scales and compares different methods and modelling approaches used for individual-catchment studies. The study area is divided into the northwestern (NWM), eastern (EM) and southern (SM) Mediterranean. The analysis indicates regional discrepancies in which the NWM shows the most extreme rainfall regime. A tendency for reduced water resources driven by both anthropogenic and climatic pressures and a more extreme rainfall regime are also noticeable. Catchments show very heterogeneous responses over time and space, resulting in limitations in hydrological modelling and large uncertainties in predictions. However, few models have been developed to address these issues. Additional studies are necessary to improve the knowledge of Mediterranean hydrological features and to account for regional specificities.

Editor D. Koutsoyiannis Associate editor A. Efstratiadis     

Quality assessment from a hydrological perspective of a digital elevation model derived from WorldView-2 remote sensing data

Abstract

A digital elevation model (DEM) derived from a stereo pair of WorldView-2 (WV-2) images was assessed against ground-truth GPS point datasets. Two assessment methods were used: (a) vertical accuracy assessment and (b) hydrological assessment of surface runoff variables. Three agricultural plots with different topographic slopes were selected to perform a vertical accuracy assessment, followed by a comparative assessment of a set of hydrological variables. The results show an overall vertical accuracy of 0.45 m, confirming the potential of WV-2 stereo images to extract elevation information at high spatial resolution. Concerning plot-scale micro-topographic features, the WV-2 DEM performed better on the plot with rolling slopes (5–10%), extracting variables such as the total length and drainage area of flow paths with relative errors lower than 20%. However, some limitations were detected in the extraction of variables such as terrain slope, drainage points of flow paths and terrain depressions in areas of flatter slopes (<5%).

Editor Z.W. Kundzewicz; Associate editor D. Gerten     

Incentives for field hydrology and data sharing: collaboration and compensation: reply to “A need for incentivizing field hydrology,especially in an era of open data”*

ABSTRACT

We thank Allen and Berghuijs for continuing the discussion on field hydrology and data sharing and discuss two incentives to promote data collection and sharing in hydrological sciences: a collaborative attitude and additional funding to make data publicly available.     

Estimating the uncertainty in simulating the impacts of small farm dams on streamflow regimes in South Africa

Abstract

Small dams represent an important local-scale resource designed to increase water supply reliability in many parts of the world where hydrological variability is high. There is evidence that the number of farm dams has increased substantially over the last few decades. These developments can have a substantial impact on downstream flow volumes and patterns, water use and ecological functioning. The study reports on the application of a hydrological modelling approach to investigate the uncertainty associated with simulating the impacts of farm dams in several South African catchments. The focus of the study is on sensitivity analysis and the limitations of the data that would be typically available for water resources assessments. The uncertainty mainly arises from the methods and information that are available to estimate the dam properties and the water use from the dams. The impacts are not only related to the number and size of dams, but also the extent to which they are used for water supply as well as the nature of the climate and the natural hydrological regimes. The biggest source of uncertainty in South Africa appears to be associated with a lack of reliable information on volumes and patterns of water abstraction from the dams.

Citation Hughes, D. A. & Mantel, S. K. (2010) Estimating the uncertainty in simulating the impacts of small farm dams on streamflow regimes in South Africa. Hydrol. Sci. J. 55(4), 578–592.     

Precipitation patterns and associated hydrological extremes in the Yangtze River basin,China, using TRMM/PR data and EOF analysis

Abstract

A decadal-scale study to retrieve the spatio-temporal precipitation patterns of the Yangtze River basin, China, using the Tropical Rain Mapping Mission, Precipitation Radar (TRMM/PR) data is presented. The empirical orthogonal function (EOF) based on monthly TRMM/PR data extracts several leading precipitation patterns, which are largely connected with physical implications at the basin scale. With the aid of gauge station data, the amplitudes of major principal components (PCs) were used to examine the generic relationships between precipitation variations and hydrological extremes (e.g. floods and droughts) during summer seasons over the past decade. The emergence of such major precipitation patterns clearly reveals the possible linkages with hydrological processes, and the oscillations in relation to the amplitude of major PCs are consistent with these observed hydrological extremes. Although the floods in some sections of the Yangtze River were, to some extent, tied to human activities, such as the removal of wetlands, the variations in major precipitation patterns are recognized as the primary driving force of the flow extremes associated with floods and droughts. The research findings indicate that long-distance hydro-meteorological signals of large-scale precipitation variations over such a large river basin can be successfully identified with the aid of EOF analysis. The retrieved precipitation patterns and their low-frequency jumps of amplitude in relation to PCs are valuable tools to help understand the association between the precipitation variations and the occurrence of hydrological extremes. Such a study can certainly aid in disaster mitigation and decision-making in water resource management.

Editor Z.W. Kundzewicz; Associate editor A. Montanari

Citation Sun, Z., Chang, N.-B., Huang, Q., and Opp, C., 2013. Precipitation patterns and associated hydrological extremes in the Yangtze River basin, China, using TRMM/PR data and EOF analysis. Hydrological Sciences Journal, 57 (7), 1315–1324.     

The effective management of national hydrometric data: experiences from the United Kingdom

Abstract

Access to hydrometric information underpins many areas of effective water management. This paper explores the operational practices of one national hydrological information service, the UK National River Flow Archive, in collating, managing and providing access to river flow data. An information lifecycle approach to hydrometric data management is advocated, with the paper detailing current UK procedures in the areas of: monitoring network design and development; data sensing and recording; validation and archival; synthesis and analysis; and data dissemination. The methods and policies outlined herein are widely transferable to other hydrological data archives around the world.

Editor D. Koutsoyiannis

Citation Dixon, H., Hannaford, J., and Fry, M.J., 2013. The effective management of national hydrometric data: experiences from the United Kingdom. Hydrological Sciences Journal, 58 (7), 1383–1399.     

Integration of remote sensing data into hydrological models for reservoir management

Abstract

The purpose of this paper is to present the methodology set up to derive catchment soil moisture from Earth Observation (EO) data using microwave spaceborne Synthetic Aperture Radar (SAR) images from ERS satellites and to study the improvements brought about by an assimilation of this information into hydrological models. The methodology used to derive EO data is based on the appropriate selection of land cover types for which the radar signal is mainly sensitive to soil moisture variations. Then a hydrological model is chosen, which can take advantage of the new information brought by remote sensing. The assimilation of soil moisture deduced from EO data into hydrological models is based principally on model parameter updating. The main assumption of this method is that the better the model simulates the current hydrological system, the better the following forecast will be. Another methodology used is a sequential one based on Kalman filtering. These methods have been put forward for use in the European AIMWATER project on the Seine catchment upstream of Paris (France) where dams are operated to alleviate floods in the Paris area.     

The role of experimental work in hydrological sciences – insights from a community survey

ABSTRACT

This opinion paper summarizes the results of an online survey on the role of experimental work in the hydrological sciences. The 20 survey questions covered various topics, such as advancements, needs, potentials and challenges in the hydrological sciences, and also touched on the issue of data sharing and data publication. A total of 336 hydrologists with both modelling and experimental backgrounds participated.     

Hydrologic simulation approach for El Niño Southern Oscillation (ENSO)-affected watershed with limited raingauge stations

ABSTRACT

Since the performance of hydrological models relies on numerous factors, the selection of an appropriate modeling approach for hydrological study has always been a crucial issue. The major objective of this research is to demonstrate that data-driven models such as the Adaptive Neuro-Fuzzy Inference system (ANFIS) are more suitable in a region where spatially distributed precipitation datasets are not available. Since precipitation has a teleconnection with the El Niño Southern Oscillation (ENSO) in different parts of the world, the sea surface temperatures (SSTs) and sea level pressures (SLPs) of the equatorial Pacific can be expected to act as surrogates for the precipitation if there are insufficient raingauge stations in the watershed. Moreover, in contrast to conceptual and physically-based models, data driven models can incorporate SST and SLP in their input vectors, and hence additional forcing of SST with precipitation has been experimented with in past studies. Therefore, our second objective is to test whether the additional forcing of SST and SLP will improve the hydrologic simulation. For this, various ANFIS models for the winter season were developed considering 10 raingauge stations situated at various locations in the watershed. Rainfall from each raingauge station was considered in the ANFIS model one at a time with and without SST/SLP. The results show that the performance of the ANFIS model improved with the additional fusion of SST and SLP, especially when a raingauge station from a remote location was considered. However, this improvement was observed when the analysis was primarily focused on the winter season which is a period with a strong ENSO signal.

Editor D. Koutsoyiannis Associate editor L. See     

A need for incentivizing field hydrology,especially in an era of open data: discussion of “The role of experimental work in hydrological sciences – insights from a community survey”*

ABSTRACT

The sharing of data and collection of new data are both essential, but they are not inherently complementary. When data are openly available, researchers may be motivated to use those data rather than collect more because field work has costs and risks. The competitive advantage to those who do not put resources towards fieldwork may discourage field hydrology. Allocating efforts towards generating field data, which benefits hydrological sciences, is not necessarily best for individual hydrologists, especially in an era of open data. The objective of this work is to open a conversation on whether individuals’ best interests may contrast with the community’s desire for new observations. If the community wants new field observations, there is a need to consider the shifting balance of incentives and disincentives for pursuing field studies in hydrology.     

Probabilistic forecasting of hydrological events using geostatistical analysis / Prévision probabiliste d'événements hydrologiques par analyse géostatistique

Abstract

A method is introduced for probabilistic forecasting of hydrological events based on geostatistical analysis. In this method, the predictors of a hydrological variable define a virtual field such that, in this field, the observed dependent variables are considered as measurement points. Variography of the measurement points enables the use of the system of kriging equations to estimate the value of the variable at non-measured locations of the field. Non-measured points are the forecasts associated with specific predictors. Calculation of the estimation variance facilitates probabilistic analysis of the forecast variables. The method is applied to case studies of the Red River in Manitoba, Canada and Karoon River in Khoozestan, Iran. The study analyses the advantages and limitations of the proposed method in comparison with a K-nearest neighbour approach and linear and nonlinear multiple regression. The utility of the proposed method for forecasting hydrological variables with a conditional probability distribution is demonstrated.     

A revisit of NRCS-CN inspired models coupled with RS and GIS for runoff estimation

The Natural Resource Conservation Service – Curve Number (NRCS-CN) methodology is a widely used tool for estimating surface runoff, which is of prime importance in hydrological engineering, agricultural planning and management, environmental impact assessment, flood forecasting, and others fields. This article reviews the methodology and associated hydrological models used for runoff estimation along with their advantages and limitations. Furthermore, discussion focuses on the potential applications of Remote Sensing (RS) and Geographical Information System (GIS) techniques for estimating hydrological variables, such as rainfall, soil moisture and CN required for the NRCS-CN methodology, as well as future research and opportunities for improved runoff estimation at the macro scale.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR A. Efstratiadis     

One decade of multi-objective calibration approaches in hydrological modelling: a review

Abstract

One decade after the first publications on multi-objective calibration of hydrological models, we summarize the experience gained so far by underlining the key perspectives offered by such approaches to improve parameter identification. After reviewing the fundamentals of vector optimization theory and the algorithmic issues, we link the multi-criteria calibration approach with the concepts of uncertainty and equifinality. Specifically, the multi-criteria framework enables recognition and handling of errors and uncertainties, and detection of prominent behavioural solutions with acceptable trade-offs. Particularly in models of complex parameterization, a multi-objective approach becomes essential for improving the identifiability of parameters and augmenting the information contained in calibration by means of both multi-response measurements and empirical metrics (“soft” data), which account for the hydrological expertise. Based on the literature review, we also provide alternative techniques for dealing with conflicting and non-commeasurable criteria, and hybrid strategies to utilize the information gained towards identifying promising compromise solutions that ensure consistent and reliable calibrations.

Citation Efstratiadis, A. & Koutsoyiannis, D. (2010) One decade of multi-objective calibration approaches in hydrological modelling: a review. Hydrol. Sci. J. 55(1), 58–78.     

Review of the Kalman-type hydrological data assimilation

ABSTRACT

There is great potential in Data Assimilation (DA) for the purposes of uncertainty identification, reduction and real-time correction of hydrological models. This paper reviews the latest developments in Kalman filters (KFs), particularly the Extended KF (EKF) and the Ensemble KF (EnKF) in hydrological DA. The hydrological DA targets, methodologies and their applicability are examined. The recent applications of the EKF and EnKF in hydrological DA are summarized and assessed critically. Furthermore, this review highlights the existing challenges in the implementation of the EKF and EnKF, especially error determination and joint parameter estimation. A detailed review of these issues would benefit not only the Kalman-type DA but also provide an important reference to other hydrological DA types.

Editor D. Koutsoyiannis; Associate editor F. Pappenberger     

A new measure for assessing the efficiency of hydrological data-driven forecasting models

Abstract

There is a lack of consistency and generality in assessing the performance of hydrological data-driven forecasting models, and this paper presents a new measure for evaluating that performance. Despite the fact that the objectives of hydrological data-driven forecasting models differ from those of the conventional hydrological simulation models, criteria designed to evaluate the latter models have been used until now to assess the performance of the former. Thus, the objectives of this paper are, firstly, to examine the limitations in applying conventional methods for evaluating the data-driven forecasting model performance, and, secondly, to present new performance evaluation methods that can be used to evaluate hydrological data-driven forecasting models with consistency and objectivity. The relative correlation coefficient (RCC) is used to estimate the forecasting efficiency relative to the naïve model (unchanged situation) in data-driven forecasting. A case study with 12 artificial data sets was performed to assess the evaluation measures of Persistence Index (PI), Nash-Sutcliffe coefficient of efficiency (NSC) and RCC. In particular, for six of the data sets with strong persistence and autocorrelation coefficients of 0.966–0.713 at correlation coefficients of 0.977–0.989, the PIs varied markedly from 0.368 to 0.930 and the NSCs were almost constant in the range 0.943–0.972, irrespective of the autocorrelation coefficients and correlation coefficients. However, the RCCs represented an increase of forecasting efficiency from 2.1% to 37.8% according to the persistence. The study results show that RCC is more useful than conventional evaluation methods as the latter do not provide a metric rating of model improvement relative to naïve models in data-driven forecasting.

Editor D. Koutsoyiannis, Associate editor D. Yang

Citation Hwang, S.H., Ham, D.H., and Kim, J.H., 2012. A new measure for assessing the efficiency of hydrological data-driven forecasting models. Hydrological Sciences Journal, 57 (7), 1257–1274.     

Regionalisation of hydrological responses under land-use change and variable data quality

ABSTRACT

Estimating river flows at ungauged sites is generally recognised as an important area of research. In countries or regions with rapid land development and sparse hydrological gauging networks, three particular challenges may arise—data scarcity, data quality, and hydrological non-stationarity. Using data from 44 gauged sub-catchments of the upper Ping catchment in northern Thailand from the period 1995–2006, three relevant flow response indices (runoff coefficient, base flow index and seasonal elasticity of flow) were regionalised by regression against available catchment properties. The runoff coefficient was the most successfully regionalised, followed by base flow index and lastly the seasonal elasticity. The non-stationarity (represented by the differences between two 6-year sub-periods) was significant both in the flow response indices and in land use indices; however relationships between the two sets of indices were weak. The regression equations derived from regionalisation were not helpful in predicting the non-stationarity in the flow indices except somewhat for the runoff coefficient. A partly subjective data quality scoring system was devised, and showed the clear influence of rainfall and flow data quality on regionalisation uncertainty. Recommendations towards improving data support for hydrological regionalisation in Thailand include more relevant soils databases, improved records of abstractions and investment in the gauge network. Widening of the regionalisation beyond the upper Ping and renewed efforts at using remotely sensed rainfall data are other possible ways forward.

EDITOR Z.W. Kundzewicz ASSOCIATE EDITOR T. Wagener     

Impacts of climate change on water resources in Spain

Abstract

Impacts on water resources produced by climate change can be exacerbated when occurring in regions already presenting low water resources levels and frequent droughts, and subject to imbalances between water demands and available resources. Within Europe, according to existing climate change scenarios, water resources will be severely affected in Spain. However, the detection of those effects is not simple, because the natural variability of the water cycle and the effects of water abstractions on flow discharges complicate the establishment of clear trends. Therefore, there is a need to improve the assessment of climate change impacts by using hydrological simulation models. This paper reviews water resources and their variability in Spain, the recent modelling studies on hydrological effects of climate change, expected impacts on water resources, the implications in river basins and the current policy actions.

Editor Z.W. Kundzewicz

Citation Estrela, T., Pérez-Martin, M.A., and Vargas, E., 2012. Impacts of climate change on water resources in Spain. Hydrological Sciences Journal, 57 (6), 1154–1167.     

Something old,something new,something red,something blue*

Abstract

Hydrologists responsible for flood management need real-time data in order to manage imminent or ongoing floods. In this paper, innovative methods for accessing hydrological data and their spatial visualization are introduced. A multitude of relevant real-time, forecast and historical information is provided in a single, self-updating hydrological map information system. The system consists of a central database and a cartographic user interface and provides harmonized and filtered data in the form of interactive, customizable maps. Maps may also be cross-referenced with historical maps or may be animated for improved comprehension and decision making. Emphasis is placed on the development of the hydrological real-time database that manages large amounts of spatial, temporal and attributive data. The paper focuses on the cartographic user interface, its functionality and the resulting interactive hydrological maps.

Citation Lienert, C., Weingartner, R. &; Hurni, L. (2011) An interactive, web-based, real-time hydrological map information system. Hydrol. Sci. J. 56(1), 1–16