Validation Of Hydrological Models Research Articles

Debates—Perspectives on socio‐hydrology: Socio‐hydrologic modeling: Tradeoffs, hypothesis testing, and validation

AbstractSocio‐hydrology focuses on studying the dynamics and co‐evolution of coupled human and water systems. Recently, several new socio‐hydrologic models have been published that explore these dynamics, and these models offer unique opportunities to better understand these coupled systems and to understand how water problems evolve similarly in different regions. These models also offer challenges, as decisions need to be made by the modeler on trade‐offs between generality, precision, and realism. In addition, traditional hydrologic model validation techniques, such as evaluating simulated streamflow, are insufficient, and new techniques must be developed. As socio‐hydrology progresses, these models offer a robust, invaluable tool to test hypotheses about the relationships between aspects of coupled human‐water systems. They will allow us to explore multiple working hypotheses to greatly expand insights and understanding of coupled socio‐hydrologic systems.

Estimation of evaporative loss based on the stable isotope composition of water using Hydrocalculator

Summary Accurate quantification of evaporative losses to the atmosphere from surface water bodies is essential for calibration and validation of hydrological models, particularly in remote arid and semi-arid regions, where intermittent rivers are generally minimally gauged. Analyses of the stable hydrogen and oxygen isotope composition of water can be used to estimate evaporative losses from individual pools in such regions in the absence of instrumental data but calculations can be complex, especially in highly variable systems. In this study, we reviewed and combined the most recent equations required for estimation of evaporative losses based on the revised Craig–Gordon model. The updated procedure is presented step-by-step, increasing ease of replication of all calculations. The main constraints and sources of uncertainties in the model were also evaluated. Based on this procedure we have designed a new software, Hydrocalculator, that allows quick and robust estimation of evaporative losses based on isotopic composition of water. The software was validated against measures of field pan evaporation under arid conditions in northwest Australia as well as published data from other regions. We found that the major factor contributing to the overall uncertainty in evaporative loss calculations using this method is uncertainty in estimation of the isotope composition of ambient air moisture.

A novel use of the caesium-137 technique to estimate human interference and historical water level in a Mediterranean Temporary Pond

The sustainability of, and the effects of human pressures on, Omalos Mediterranean Temporary Pond (MTP), Chanea, Greece was assessed. The 137Cs technique was used to identify alleged anthropogenic interference (excavation) in the studied area. It was found that about one third of the ponds bed surface material had been removed and disposed of on the northeast edge, confirming unplanned excavations that took place in the MTP area some years ago. Nonetheless, five years after the excavation, the MTP's ecosystem (flora and fauna) had recovered, which indicates that these small ecosystems are resilient to direct human pressures, like excavations. Moreover, with the 137Cs technique it was possible to identify the historical water level of Omalos MTP, when the fallout from the Chernobyl accident reached this area, in May of 1986. Therefore, the 137Cs technique can be useful in the identification of the historical water level of small MTPs and other ephemeral water bodies. Applications include the verification and validation of hydrological models.

Towards hydrological model calibration and validation: simulation of stable water isotopes using the isoWATFLOOD model

AbstractCalibration and validation of hydrological models is a challenge, particularly in remote regions that are minimally gauged. This paper develops a novel methodology for large‐scale (>1000 km2) hydrological model calibration and validation using stable water isotopes founded on the rigorous constraints imposed by the need to conserve both water mass and stable isotopes simultaneously. The isoWATFLOOD model is applied to five basins within the Fort Simpson, Northwest Territories region of northern Canada to simulate stream discharge and oxygen‐18 signals over a 3‐year period. The isotopic variation of river discharge, runoff components, and evaporative fractionation are successfully simulated on both a seasonal and continual basis over the watershed domain to demonstrate the application of isotope tracers to regional hydrologic calibration. The intended application of this research is to remote, large‐scale basins, showing promise for improving predictions in minimally gauged basins and climate change research where traditional, rigorous approaches to constraining parameter uncertainty may be impractical. This coupled isotope‐hydrological (i.e. iso‐hydrological) approach to modelling reduces the number of possible parameterizations, resulting in potentially more physically‐based hydrological predictions. isoWATFLOOD provides a tool for water resource managers and utilities to use operationally for water use, allocation, and runoff generation estimations. Copyright © 2012 John Wiley & Sons, Ltd.

A multi-source satellite data approach for modelling Lake Turkana water level: calibration and validation using satellite altimetry data

Abstract. Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of inter- and intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellite-driven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004–2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1–2 m. The lake level fluctuated in the range up to 4 m between the years 1998–2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance model for (i) quantitative assessment of the impact of basin developmental activities on lake levels and for (ii) forecasting lake level changes and their impact on fisheries. From this study, we suggest that globally available satellite altimetry data provide a unique opportunity for calibration and validation of hydrologic models in ungauged basins.

Validation of hydrological models: Conceptual basis, methodological approaches and a proposal for a code of practice

In this paper, we discuss validation of hydrological models, namely the process of evaluating performance of a simulation and/or prediction model. We briefly review the validation procedures that are frequently used in hydrology making a distinction between scientific validation and performance validation. Finally, we propose guidelines for carrying out model validation with the aim of providing agreed methodologies to efficiently assess model peculiarities and limitations, and to quantify simulation performance.

The use of stable isotopes to partition evapotranspiration fluxes into evaporation and transpiration

It is crucial to partition evapotranspiration ( ET) into evaporation ( E) and transpiration ( T) components for better understanding eco-hydrological processes and their underlying mechanisms, and improving the establishment and validation of hydrological models at the ecosystem scale. Traditional eddy covariance technique serves as a useful tool to estimate ET, but it encounters difficulties in quantifying the relative contribution of E and T to ET. Combining with eddy covariance technique, it is possible to partition ET based on the measurements of stable oxygen and hydrogen isotopes in liquid and vapor phases of water in the Soil–Plant–Atmosphere Continuum (SPAC) system. The key challenge is to precisely determine the oxygen-18 and deuterium isotopic compositions of ET ( δ ET ), E ( δ E ) and T ( δ T ). δ E can be estimated based on the Craig–Gordon model. δ T is usually approximated by the δ 18O and δD of water in xylem or twig ( δ x ), assuming δ T equals δ x under isotopic steady state (SSA). However, the SSA is only likely satisfied during midday in field conditions. The diurnal variations of δ T is affected by isotopic composition of atmospheric water vapor ( δ v ) and leaf water at the evaporating sites ( δ L , e ), and relative humidity, resulting in the non-steady-state behavior of δ T at the sub-daily cycles. δ ET can be estimated using the flux-gradient approach or the Keeling plot by measuring the vapor mixing ratio and δ v at different heights in the surface layer. However, δ v observations by the traditional cold trap/mass spectrometer method are limited to a coarse time resolution, leading to discrete time series of δ ET . It is now possible to make in situ and high time resolution measurements of δ v and to analyze a large number of plant and soil samples due to technical and instrumental advances in recent years. It provides an opportunity to improve the model prediction of δ L , e , and more importantly, to calculate δ T from δ L , e without invoking the SSA. Combining with the flux-gradient approach or the Keeling plot technique, continuous δ ET measurements can be made. It offers us a premise for accurate ET partitioning on diurnal time scale. In this review we introduced the recent advances, foci and challenges for studies on ET partitioning using the stable isotopes technique.

Autocalibration of HSPF for Simulation of Streamflow Using a Genetic Algorithm

Hydrologic models are essential to watershed planning and management, particularly in the San Antonio River watershed where competition for scarce water resources is a challenge. As a result, the calibration and validation of hydrologic models are essential steps for their successful application. In this study, we examined the use of a loosely coupled genetic algorithm (GA) as an autocalibration tool for optimization of model parameters for the Hydrologic Simulation Program - Fortran (HSPF), a model frequently used in surface hydrology and water quality modeling. The GA-HSPF model is a more objective and less time-consuming alternative to traditional trial-and-error methods. The objective function was optimized by minimizing the mean absolute error (MAE) between corresponding simulated and observed average daily streamflow in the San Antonio River watershed. The MAE was used to evaluate the fitness of the parameter set in the GA. The calibrated model parameters (LZSN, INFILT, AGWRC, UZSN, DEEPFR, LZETP, and INTFW) were selected based on a sensitivity analysis from a previous study. Goodness-of-fit of the GA calibrated model was evaluated using the Nash-Sutcliffe coefficient of efficiency, MAE, root mean square error, flow duration curves, wavelet analysis, and total volume error. Overall simulation time with 2000 model simulations was 11 days, which can be improved significantly under parallel computing, as GA-HSPF simulations are highly independent. The objective function ceased improvement after approximately 250 simulations, with a minimized MAE of 25.8 m3/s. With the exception of DEEPFR, all optimized model parameter values were within the range cited in the literature. Nash-Sutcliffe coefficients in all simulations were above 0.5, suggesting that the simulated flows were in good agreement with the observed flows. Visual comparison between observed and simulated stream flow using time series and flow duration curves showed that the GA calibrated model was unable to simulate peak flow events accurately, particularly in the 0% to 10% exceedence range. It is hypothesized that the storage-based routing scheme in HSPF limits its ability to predict peak flows in this watershed. Comparison between observed and simulated flows in the wavelet domain indicated that the GA calibrated model was not able to preserve the scale and location of some high frequencies, but the scale and location of lower frequencies were preserved. The cyclic nature of the streamflow in this watershed was more prominent in lower frequencies. While overall flow rates were adequately predicted using a GA-HSPF approach, future work in this watershed needs to focus on multi-objective optimization that optimizes both volumes and peak flows. The GA-HSPF model offers an objective and efficient method for calibration and validation, a useful tool in watershed planning efforts.

Use of regional climate model simulations as input for hydrological models for the Hindukush-Karakorum-Himalaya region

Abstract. The most important climatological inputs required for the calibration and validation of hydrological models are temperature and precipitation that can be derived from observational records or alternatively from regional climate models (RCMs). In this paper, meteorological station observations and results of the PRECIS (Providing REgional Climate for Impact Studies) RCM driven by the outputs of reanalysis ERA 40 data and HadAM3P general circulation model (GCM) results are used as input in the hydrological model. The objective is to investigate the effect of precipitation and temperature simulated with the PRECIS RCM nested in these two data sets on discharge simulated with the HBV model for three river basins in the Hindukush-Karakorum-Himalaya (HKH) region. Six HBV model experiments are designed: HBV-Met, HBV-ERA and HBV-Had, HBV-MetCRU-corrected, HBV-ERABenchmark and HBV-HadBenchmark where HBV is driven by meteorological stations data, data from PRECIS nested in ERA-40 and HadAM3P, meteorological stations CRU corrected data, ERA-40 reanalysis and HadAM3P GCM data, respectively. Present day PRECIS simulations possess strong capacity to simulate spatial patterns of present day climate characteristics. However, also some quantitative biases exist in the HKH region, where PRECIS RCM simulations underestimate temperature and overestimate precipitation with respect to CRU observations. The calibration and validation results of the HBV model experiments show that the performance of HBV-Met is better than the HBV models driven by other data sources. However, using input data series from sources different from the data used in the model calibration shows that HBV-Had is more efficient than other models and HBV-Met has the least absolute relative error with respect to all other models. The uncertainties are higher in least efficient models (i.e. HBV-MetCRU-corrected and HBV-ERABenchmark) where the model parameters are also unrealistic. In terms of both robustness and uncertainty ranges the HBV models calibrated with PRECIS output performed better than other calibrated models except for HBV-Met which has shown a higher robustness. This suggests that in data sparse regions such as the HKH region data from regional climate models may be used as input in hydrological models for climate scenarios studies.

Validation of hydrological models for climate scenario simulation: the case of Saguenay watershed in Quebec

AbstractThis paper presents the results of an investigation into the problems associated with using downscaled meteorological data for hydrological simulations of climate scenarios. The influence of both the hydrological models and the meteorological inputs driving these models on climate scenario simulation studies are investigated. A regression‐based statistical tool (SDSM) is used to downscale the daily precipitation and temperature data based on climate predictors derived from the Canadian global climate model (CGCM1), and two types of hydrological model, namely the physically based watershed model WatFlood and the lumped‐conceptual modelling system HBV‐96, are used to simulate the flow regimes in the major rivers of the Saguenay watershed in Quebec. The models are validated with meteorological inputs from both the historical records and the statistically downscaled outputs. Although the two hydrological models demonstrated satisfactory performances in simulating stream flows in most of the rivers when provided with historic precipitation and temperature records, both performed less well and responded differently when provided with downscaled precipitation and temperature data. By demonstrating the problems in accurately simulating river flows based on downscaled data for the current climate, we discuss the difficulties associated with downscaling and hydrological models used in estimating the possible hydrological impact of climate change scenarios. Copyright © 2007 John Wiley & Sons, Ltd.

Statistical characterization of the spatial variability of soil moisture in a cutover peatland

AbstractSoil moisture is a significant variable in its importance to the validation of hydrological models, but it is also the one defining variable that ties in all components of the surface energy balance and as such is of major importance to climate models and their surface schemes. Changing the scale of representation (e.g. from the observation to modelling scale) can further complicate the description of the spatial variability in any hydrological system. We examine this issue using soil moisture and vegetation cover data collected at two contrasting spatial scales and at three different times in the snow‐free season from a cutover peat bog in Cacouna, Québec. Soil moisture was measured using Time Domain Reflectometry (TDR) over 90 000 m2 and 1200 m2 grids, at intervals of 30 and 2 m respectively. Analyses of statistical structure, variance and spatial autocorrelation were conducted on the soil moisture data at different sampling resolutions and over different grid sizes to determine the optimal spatial scale and sampling density at which these data should be represented. Increasing the scale of interest without adequate resolution in the measurement can lead to significant inconsistency in the representation of these variables. Furthermore, a lack of understanding of the nature of the variability of soil moisture at different scales may produce spurious representation in a modelling context. The analysis suggests that in terms of the distribution of soil moisture, the extent of sampling within a grid is not as significant as the density, or spacing, of the measurements. Both the scale and resolution of the sampling scheme have an impact on the mean of the distribution. Only approximately 60% of the spatial pattern in soil moisture of both the large and small grid is persistent over time, suggesting that the pattern of moisture differs for wetting and drying cycles. Copyright © 2003 John Wiley & Sons, Ltd.