Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin

Abstract

Remote sensing is considered the most effective tool for estimating evapotranspiration (ET) over large spatial scales. Global terrestrial ET estimates over vegetated land surfaces are now operationally produced at 1-km spatial resolution using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the MOD16 algorithm. To evaluate the accuracy of this product, ground-based measurements of energy fluxes obtained from eddy covariance sites installed in tropical biomes and from a hydrological model (MGB-IPH) were used to validate MOD16 products at local and regional scales. We examined the accuracy of the MOD16 algorithm at two sites in the Rio Grande basin, Brazil, one characterized by a sugar-cane plantation (USE), the other covered by natural savannah vegetation (PDG) for the year 2001. Inter-comparison between 8-day average MOD16 ET estimates and flux tower measurements yielded correlations of 0.78 to 0.81, with root mean square errors (RMSE) of 0.78 and 0.46 mm d^-1, at PDG and USE, respectively. At the PDG site, the annual ET estimate derived by the MOD16 algorithm was 19% higher than the measured amount. For the average annual ET at the basin-wide scale (over an area of 145 000 km²), MOD16 estimates were 21% lower than those from the hydrological model MGB-IPH. Misclassification of land use and land cover was identified as the largest contributor to the error from the MOD16 algorithm. These estimates improve significantly when results are integrated into monthly or annual time intervals, suggesting that the algorithm has a potential for spatial and temporal monitoring of the ET process, continuously and systematically, through the use of remote sensing data.

Editor D. Koutsoyiannis; Associate editor T. Wagener

Citation Ruhoff, A.L., Paz, A.R., Aragao, L.E.O.C., Mu, Q., Malhi, Y., Collischonn, W., Rocha, H.R., and Running, S.W., 2013. Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin. Hydrological Sciences Journal, 58 (8), 1658–1676.     

Verification of land surface evapotranspiration estimation from remote sensing spatial contextual information

Estimation of evapotranspiration (ET) is of great significance in modeling the water and energy interactions between land and atmosphere. Negative correlation of surface temperature (T_s) versus vegetation index (VI) from remote sensing data provides diagnosis on the spatial pattern of surface soil moisture and ET. This study further examined the applicability of T_s–VI triangle method with a newly developed edges determination technique in estimating regional evaporative fraction (EF) and ET at MODIS pixel scale through comparison with large aperture scintillometer (LAS) and high‐level eddy covariance measurements collected at Changwu agro‐ecological experiment station from late June to late October, 2009. An algorithm with merely land and atmosphere products from MODIS onboard Terra satellite was used to estimate the surface net radiation (R_n) and soil heat flux. In most cases, the estimated instantaneous R_n was in good agreement with surface measurement with slight overestimation by 12 W/m². Validation results from LAS measurement showed that the root mean square error is 0.097 for instantaneous EF, 48 W/m² for instantaneous sensible heat flux, and 30 W/m² for daily latent heat flux. This paper successfully presents a miniature of the overall capability of T_s–VI triangle in estimating regional EF and ET from limited number of data. For a thorough interpretation, further comprehensive investigation needs to be done with more integration of remote sensing data and in‐situ surface measurements. Copyright © 2011 John Wiley & Sons, Ltd.     

Can satellite land surface temperature data be used similarly to river discharge measurements for distributed hydrological model calibration?

Abstract

A new methodology is proposed for the calibration of distributed hydrological models at the basin scale by constraining an internal model variable using satellite data of land surface temperature (LST). The model algorithm solves the system of energy and mass balances in terms of a representative equilibrium temperature that governs the fluxes of energy and mass over the basin domain. This equilibrium surface temperature, which is a critical model state variable, is compared to operational satellite LST, while calibrating soil hydraulic parameters and vegetation variables differently in each pixel, minimizing the errors. This procedure is compared to the traditional calibration using only discharge measurements. The distributed energy water balance model, Flash-flood Event-based Spatially-distributed rainfall–runoff Transformation – Energy Water Balance model (FEST-EWB), is used to test this approach. This methodology is applied to the Upper Yangtze River basin (China) using MODIS LST retrieved from satellite data in the framework of the NRSCC-ESA DRAGON-2 Programme. The calibration procedure based on LST seems to outperform the calibration based on discharge, with lower relative error and higher Nash-Sutcliffe efficiency index on cumulated volume.

Editor D. Koutsoyiannis; Associate editor C. Perrin     

Coupling SEBAL with a new radiation module and MODIS products for better estimation of evapotranspiration

ABSTRACT

Evapotranspiration (ET) is an important ecohydrological process especially in arid and semi-arid regions. In this study, a new radiation module based on MODIS data has been coupled with the Surface Energy Balance Algorithms for Land (SEBAL) to better estimate ET. The accuracies of the coupled model for estimating available energy and sensible heat (H) were improved significantly compared with the outputs from the original SEBAL which was based on empirical equations. The coupled SEBAL modelled instantaneous λET agreed much better with observations in the arid land of Central Asia than the original SEBAL, with a bias of ?2.86 W m^-2, root mean square error (RMSE) of 9.75 W m^-2, and normalized RMSE (NRMSE) of 0.13. The accuracy was blurred when scaling ET to a daily or monthly scale, mainly due to the uncertainties associated with temporal upscaling methods that were applied. Sensitivity analysis, which was conducted using numerical variance-based techniques, indicated that the estimated ET is sensitive to the available energy, suggesting the importance of obtaining accurate estimates of net radiation when applying the coupled SEBAL to estimate ET. This study provides a simple and reliable way to utilize MODIS products and contains sensitivity analysis for helping to correctly interpret the outputs, which are both important for large-scale ET estimation.     

Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes

Abstract

Reliable estimation of sensible heat flux (H) is important in energy balance models for quantifying evapotranspiration (ET). This study was conducted to evaluate the value of adding the Priestley-Taylor (PT) equation to the METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model. METRIC was used to estimate energy fluxes for 10 Landsat images from the 2005, 2006 and 2007 crop growing seasons in south-central Nebraska, USA, where each image owing to recent rainfall exhibited high residual moisture content even at the hot pixel. The METRIC model performed satisfactorily for net radiation (R_n ) and soil heat flux (G) estimation with a root mean square error (RMSE) of 52 and 24 W m^-2, respectively. A RMSE of 122 W m^-2 for H indicated the limitation of the METRIC model in estimating H for high residual moisture content of the hot pixel (Alfalfa reference ET fraction, ET _r F > 0.15). The modified METRIC model (wet METRIC or wMETRIC) incorporating the PT equation was applied to calculate H at the anchor pixels (hot and cold) for high residual moisture content of the hot pixel. The α coefficient of the PT equation was locally calibrated using hourly meteorological data from an automatic weather station and R_n and G data from a Bowen ratio flux tower. The mean α coefficient value was 1.14. The wMETRIC model reduced the RMSE of H from 122 to 64 W m^-2 and that of latent heat flux, LE, from 163 to 106 W m^-2. The RMSE of daily ET decreased from 1.7 to 1.1 mm d^-1 with wMETRIC. The results indicate that treatment of anchor pixels for high residual moisture content with the PT approach gives improved estimation of H, LE and daily ET. It is recommended that the wMETRIC model be used for estimating ET if the hot pixel has high residual moisture (i.e. reference ET fraction > 0.15).

Citation Singh, R. K. & Irmak, A. (2011) Treatment of anchor pixels in the METRIC model for improved estimation of sensible and latent heat fluxes. Hydrol. Sci. J. 56(5), 895–906.     

Evaluating the SEBS‐estimated evaporative fraction from MODIS data for a complex underlying surface

With the complex nature of land surfaces, more attention should be paid to the performance of remotely sensed models to estimate evapotranspiration from moderate and low spatial resolution data. Taking into account the characteristic of a stable evaporative fraction (EF) in the daytime, this paper uses the surface energy balance system (SEBS) to estimate the EF from MODIS data for a subtropical evergreen coniferous plantation in southern China and evaluates the stability of the SEBS model in estimating the EF under complex surface conditions. The results show that the SEBS‐estimated EF is larger than the measured EF partly because of the serious lack of energy‐balance closure. This difference can be largely reduced by the residual energy correction method. More evaporative land cover within the MODIS pixel is a main reason for the overestimated EF. SEBS underestimates sensible heat flux, and the underestimation of surface available energy also contributes to the overestimation of the EF. The EF estimated from MODIS/Terra data is in agreement with that from MODIS/Aqua data with a coefficient of determination (R²) of 0.552, a mean bias error (BIAS) of 0.028, and a root mean square error (RMSE) of 0.079, which is consistent with the result from in situ measurements. In addition, the estimation of surface available energy from remotely sensed data is evaluated on this complex underlying surface. Compared with in situ measurements, the available energy is underestimated by 28 W m^?2 with an RMSE = 50 W m^?2 and an R² = 0.87. Copyright © 2012 John Wiley & Sons, Ltd.     

Soil moisture estimation using ERS 2 SAR data: a case study in the Solani River catchment/Estimation de l’humidité du sol grâce à des données ERS-2 SAR: étude de cas dans le bassin de la rivière Solani

Abstract

Abstract The information regarding spatial and temporal variation of soil moisture in a catchment is of utmost importance in hydrological, as well as many other studies. Point measurements from gravimetric and other methods for soil moisture determination are insufficient to understand the spatial behaviour of soil moisture in a region. Microwave remote sensing data from active sensors on board various satellites are increasingly being used to map spatial distribution of soil moisture within the 0–10 cm top surface. The northern part of India has a network of large rivers and canals and, therefore, spatial and temporal distribution of soil moisture in this region has a significant bearing on the hydrology of the region. In this paper, results on estimation of soil moisture from an ERS-2 SAR image in the catchment of the Solani River (a tributary to the River Ganga) in and around the town of Roorkee, India, have been presented. The radar backscatter coefficient for each pixel of the image has been modelled from the digital numbers of the SAR image. Gravimetric measurements have been made simultaneously during the satellite pass to determine the concurrent value of volumetric soil moisture at a large number of sample points within the satellite sweep area. The backscatter coefficient is found to vary from –30 dB to –42 dB for a variation in soil moisture from 30 to 75%. Regression analyses between volumetric soil moisture and both the digital numbers and backscatter coefficients were performed. Strong correlations between volumetric soil moisture and digital number were observed with R ² values of 0.84, 0.75 and 0.83 for bare soil, vegetative and combined surfaces, respectively. A similar trend was observed with the relationship between backscatter and volumetric soil moisture with R ² values of 0.60, 0.89 and 0.67 for bare soil, vegetative and combined surfaces, respectively. These results demonstrate the utilization of SAR data for estimation of spatial distribution of soil moisture in the region of the present study.     

Information and complexity measures applied to observed and simulated soil moisture time series

Abstract

Time series of soil moisture-related parameters provide important insights into the functioning of soil water systems. Analysis of patterns within such time series has been used in several studies. The objective of this work was to compare patterns in observed and simulated soil moisture contents to understand whether modelling leads to a substantial loss of information or complexity. The time series were observed at four plots in sandy soils within the USDA-ARS OPE3 experimental watershed, for a year; precipitation and evapotranspiration (ET) were measured and estimated, respectively, and used for soil water flow simulation with the HYDRUS-1D software. The information content measures are the metric entropy and the mean information gain, and complexity measures are the fluctuation complexity and the effective measure complexity. These measures were computed based on the binary encoding of soil moisture time series, and used probabilities of patterns, i.e. probabilities of joint or sequential appearance of symbol sequences. The information content of daily soil moisture time series was much smaller than that of rainfall data, and had higher complexity, indicating that soil worked essentially as an information filter. Information content and complexity decreased and increased with depth, respectively, demonstrating the increase in the information filtering action of soil. The information measures of simulated soil moisture content were close to those of the measurements, indicating the successful simulation of patterns in the data. The spatial variability of the information measures for simulated soil moisture content at all depths was less pronounced than the one of measured time series. Compared with precipitation and estimated ET, soil moisture time series had more structure and less randomness in this work. The information measures can provide useful complementary knowledge about model performance and patterns in observation and modelling results.

Citation Pan, F., Pachepsky, Y. A., Guber, A. K., & Hill, R. L. (2011) Information and complexity measures applied to observed and simulated soil moisture time series. Hydrol. Sci. J. 56(6), 1027–1039.     

A method for estimating soil moisture storage in regions under water stress and storage depletion: a case study of Hai River Basin,North China

Soil moisture is a consideration for soil conservation, agricultural production and climate modelling. This article presents a simple method for estimating soil moisture storage under water stress and storage depletion conditions. The method is driven by the common agro‐hydrologic variables of precipitation (PPT), irrigation (IRR) and evapotranspiration (ET). The proposed method is successfully tested for the 152 000 km² floodplain region of Hai River Basin using 48 consecutive months (2003–2006) of data. Soil moisture data from global land data assimilation system/Noah land surface model are validated with ground‐truth data from 102 soil moisture monitoring sites. The validated soil moisture is used in combination with in situ groundwater data to quantify total water storage change (TWSC) in the region. The estimated storage change is in turn compared with gravity recovery and climate experiment‐derived TWSC for the study area. The soil moisture and TWSC terms show favourable agreements, with discrepancies of < 10% on the average. While there is no consistent seasonal trend in soil moisture, TWSC shows a strong seasonality. It is low in spring and high in summer. This trend corresponds with the IRR–PPT season in the study area. Change in groundwater and total water storage indicates storage depletion in the basin. Storage depletion in the region is driven mainly by groundwater IRR and ET loss. Despite the low PPT and high ET, there is narrowing seasonal trend in soil moisture. This is achieved at the expense of groundwater storage. IRR pumping has induced extensive groundwater depletion in the basin. It is therefore vital to develop cultivation strategies that aim at limiting IRR pumping and ET loss. Water management practices that not only reduce waste but also ensure high productivity and ecological sustainability could also mitigate storage depletion in the region. These measures could reduce further not only the seasonal trend in soil moisture but also that in groundwater storage. Copyright © 2011 John Wiley & Sons, Ltd.     

Impact of land-use changes on snow in a forested region with heavy snowfall in Hokkaido,Japan

Abstract

We simulated snow processes in a forested region with heavy snowfall in Japan, and evaluated both the regional-scale snow distribution and the potential impact of land-use changes on the snow cover and water balances over the entire domain. SnowModel reproduced the snow processes at open and forested sites, which were confirmed by snow water equivalent (SWE) measurements at two intensive observation sites and snow depth measurements at the Automated Meteorological Data Acquisition System sites. SnowModel also reproduced the observed snow distribution (from the MODIS snow cover data) over the simulation domain during thaw. The observed SWE was less at the forested site than at the open site. The SnowModel simulations showed that this difference was caused mainly by differences in sublimation. The type of land use changed the maximum SWE, onset and duration of snowmelt, and the daily snowmelt rate due to canopy snow interception.

Citation Suzuki, K., Kodama, Y., Nakai, T., Liston, G. E., Yamamoto, K., Ohata, T., Ishii, Y., Sumida, A., Hara, T. & Ohta, T. (2011) Impact of land-use changes in a forested region with heavy snowfall in Hokkaido, Japan. Hydrol. Sci. J. 56(3), 443–467.     

Grid parameterization of a conceptual distributed hydrological model through integration of a sub-grid topographic index: necessity and practicability

Abstract

Grid-based distributed models have become popular for describing spatial hydrological processes. However, the influence of non-homogeneity within a grid on streamflow simulation was not adequately addressed in the literature. In this study, we investigated how the statistical characteristics of soil moisture storage within a grid impacts on streamflow simulations. The spatial variation of the topographic index, TI, within a grid was used to determine parameter B of the statistical curve of soil moisture storage in the Xinanjiang model. For comparison of influences of the non-homogeneity within a grid on streamflow simulation, two parameterization schemes of soil moisture storage capacity were developed: a grid-parameterization scheme for a distributed model and a catchment-averaged scheme for a semi-distributed model. The practicability and usefulness of the grid-parameterization method were evaluated through model comparisons. The two models were applied in Jiangwan experimental catchment Zhejiang Province, China. Streamflow discharge data at the catchment outlet from 1971 to 1986 at different temporal resolutions, e.g. 15 min and daily time step, were used for model calibration and validation. Statistical results for different grid scales demonstrated that the mean and variation of TI and B decline significantly as the grid scale increases. The simulated streamflow discharges of the two models were similar and the semi-distributed model outperformed the distributed model slightly when the streamflow at the outlet of the catchment was used as the only basis for comparison. In addition, a relatively larger bias in the predicted discharges between these two models was observed along with an abrupt increase of soil moisture saturation ratio. A further analysis of the simulated soil moisture content distribution revealed that the distributed model can provide a reasonable representation of the variable source area concept, which was justified to some extent by the field experiment data.

Editor D. Koutsoyiannis

Citation Liu, J.T., Chen, X., Wu, J.C., Zhang, X.N., Feng, D.Z. and Xu, C.-Y., 2012. Grid parameterization of a conceptual, distributed hydrological model through integration of a sub-grid topographic index: necessity and practicability. Hydrological Sciences Journal, 57 (2), 282–297.     

Seasonal variation of land–atmosphere coupling strength over the West African monsoon region in an atmospheric general circulation model

Abstract

The seasonal variation of land–atmosphere coupling strength has been examined using an extended series of atmospheric general circulation model (AGCM) simulations. In the Western Sahel of Africa, strong coupling strength for precipitation is found in April and May, just prior to and at the beginning of the monsoon season. At this time, heat and water fluxes from the surface are strongly controlled by land conditions, and the unstable conditions in the lower level of the troposphere, as induced by local land state, allow the surface fluxes to influence the variability of convective precipitation—and thus the timing of monsoon onset.

Editor Z. W. Kundzewicz

Citation Yamada, T.J., Kanae, S., Oki, T., and Koster, R.D., 2013. Seasonal variation of land–atmosphere coupling strength over the West African monsoon region in an atmospheric general circulation model. Hydrological Sciences Journal, 58 (6), 1276–1286.     

Water resources and climate change impact modelling on a daily time scale in the Peruvian Andes

Abstract

Estimating water resources is important for adequate water management in the future, but suitable data are often scarce. We estimated water resources in the Vilcanota basin (Peru) for the 1998–2009 period with the semi-distributed hydrological model PREVAH using: (a) raingauge measurements; (b) satellite rainfall estimates from the TRMM Multi-satellite Precipitation Analysis (TMPA); and (c) ERA-Interim re-analysis data. Multiplicative shift and quantile mapping were applied to post-process the TMPA estimates and ERA-Interim data. This resulted in improved low-flow simulations. High-flow simulations could only be improved with quantile mapping. Furthermore, we adopted temperature and rainfall anomalies obtained from three GCMs for three future periods to make estimations of climate change impacts (Delta-change approach) on water resources. Our results show more total runoff during the rainy season from January to March, and temporary storages indicate that less water will be available in this Andean region, which has an effect on water supply, especially during dry season.

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

A wavelet-neural network hybrid modelling approach for estimating and predicting river monthly flows

Abstract

A wavelet-neural network (WNN) hybrid modelling approach for monthly river flow estimation and prediction is developed. This approach integrates discrete wavelet multi-resolution decomposition and a back-propagation (BP) feed-forward multilayer perceptron (FFML) artificial neural network (ANN). The Levenberg-Marquardt (LM) algorithm and the Bayesian regularization (BR) algorithm were employed to perform the network modelling. Monthly flow data from three gauges in the Weihe River in China were used for network training and testing for 48-month-ahead prediction. The comparison of results of the WNN hybrid model with those of the single ANN model show that the former is able to significantly increase the prediction accuracy.

Editor D. Koutsoyiannis; Associate editor H. Aksoy

Citation Wei, S., Yang, H., Song, J.X., Abbaspour, K., and Xu, Z.X., 2013. A wavelet-neural network hybrid modelling approach for estimating and predicting river monthly flows. Hydrological Sciences Journal, 58 (2), 374–389.     

Effects of land-use/cover change on hydrological processes using a GIS/RS-based integrated hydrological model: case study of the East River,China

Abstract

An integrated model, combining a surface energy balance system, an LAI-based interception model and a distributed monthly water balance model, was developed to predict hydrological impacts of land-use/land-cover change (LUCC) in the East River basin, China, with the aid of GIS/RS. The integrated model is a distributed model that not only accounts for spatial variations in basin terrain, rainfall and soil moisture, but also considers spatial and temporal variation of vegetation cover and evapotranspiration (ET), in particular, thus providing a powerful tool for investigating the hydrological impact of LUCC. The model was constructed using spatial data on topography, soil types and vegetation characteristics together with time series of precipitation from 170 stations in the basin. The model was calibrated and validated based on river discharge data from three stations in the basin for 21 years. The calibration and validation results suggested that the model is suitable for application in the basin. The results show that ET has a positive relationship with LAI (leaf area index), while runoff has a negative relationship with LAI in the same climatic zone that can be described by the surface energy balance and water balance equation. It was found that deforestation would cause an increase in annual runoff and a decrease in annual ET in southern China. Monthly runoff for different land-cover types was found to be inversely related to ET. Also, for most of the scenarios, and particularly for grassland and cropland, the most significant changes occurred in the rainy season, indicating that deforestation would cause a significant increase in monthly runoff in that season in the East River basin. These results are important for water resources management and environmental change monitoring.

Editor Z.W. Kundzewicz     

An integrated hydrological and meteorological approach for the simulation of terrestrial evapotranspiration / Une approche hydrologique et météorologique intégrée pour la simulation de l'évapotranspiration terrestre

Abstract

Terrestrial evapotranspiration (ET) plays an important role in determining water and heat balances in the water cycle between the land surface and the atmosphere. In the present research a dynamic approach is developed to simulate actual ET distribution for large-scale spatial and temporal scales based on an integration of meteorological and hydrological methods. The method developed has been used to examine the impacts of climate change, complex land cover features, and soil moisture on actual ET. The distribution characteristics of actual ET demonstrate that ET in eastern China is greater than that in western China, and that ET is greater in low-latitude regions of China than in high-latitude regions. Actual monthly and annual ET values in most regions show an increasing tendency from the year 1991 to 2000, especially in arid and semi-arid regions. The results of the present study also confirm that soil moisture is one of the critical factors that affect regional ET in China. It is demonstrated that the integrated hydrological-meteorological approach is effective for simulating actual ET on large spatial and temporal scales.     

Input data measurement-induced uncertainty in watershed modelling

Abstract

This study presents a new methodology for estimation of input data measurement-induced uncertainty in simulated dissolved oxygen (DO) and nitrate-nitrogen (NO₃-N) concentrations using the Hydrological Simulation Program–FORTRAN (HSPF) model and data from the Amite River, USA. Simulation results show that: (1) a multiplying factor of 1.3 can be used to describe the maximum error in temperature measurements; similarly, a multiplying factor of 1.9 was estimated to accommodate the maximum of ±5% error in rainfall measurements; (2) the uncertainty in simulated DO concentration due to positive temperature measurement errors can be described with a normal distribution, N(0.062, 0.567); (3) the uncertainty in simulated NO₃-N concentration due to rainfall measurement errors follows a generalized extreme value distribution; and (4) the probability density functions can be utilized to determine the measurement-induced uncertainty in simulated DO and NO₃-N concentrations according to the risk level acceptable in water quality management.

Editor D. Koutsoyiannis

Citation Patil, A. and Deng, Z.-Q., 2012. Input data measurement-induced uncertainty in watershed modelling. Hydrological Sciences Journal, 57 (1), 118–133.     

BIBLIOGRAPHIES

Abstract

On a regional scale (from about 10 to 10⁵km²) estimations of actual evapotranspiration ET for water balance equations are generally missing. The various methods available at present are briefly described and discussed. The use of remote sensing, in particular infra-red thermometry by satellite, in conjunction with soil energy budget data, is the only method to provide satisfactory data on the same scale in space and lime for water balance models. This method is being studied at the INRA Bioclimatology Station at Avignon in the framework of the European ‘Tellus’ project for using HCMM satellite data. Systems for continuously recording the components of the energy budget and ET have been installed in the Crau plain, north of Marseilles, in both a dry area and a large area of irrigated pastures. By combining the recorded measurements with the satellite data and starting from values for elements of 25 ha (500 m × 500 m), the ET for the whole of the Crau plain can be estimated. First results are analysed and the possibilities and limitations of the method are discussed.     

Improvement of a drainage system for flood management with assessment of the potential effects of climate change

Abstract

Runoff discharge in the Tuku lowlands, Taiwan, has increased with land development. Frequent floods caused by extreme weather conditions have resulted in considerable economic and social losses in recent years. Currently, numerous infrastructures have been built in the lowland areas that are prone to inundation; the measures and solutions for flood mitigation focus mainly on engineering aspects. Public participation in the development of principles for future flood management has helped both stakeholders and engineers. An integrated drainage–inundation model, combining a drainage flow model with a two-dimensional overland-flow inundation model is used to evaluate the flood management approaches with damage loss estimation. The proposed approaches include increasing drainage capacity, using fishponds as retention ponds, constructing pumping stations, and building flood diversion culverts. To assess the effects on the drainage system of projected increase of rainfall due to climate change, for each approach simulations were performed to obtain potential inundation extent and depth in terms of damage losses. The results demonstrate the importance of assessing the impacts of climate change for implementing appropriate flood management approaches.

Editor Z.W. Kundzewicz

Citation Chang, H.-K., Tan, Y.-C., Lai, J.-S., Pan, T.-Y., Liu, T.-M., and Tung, C.-P., 2013. Improvement of a drainage system for flood management with assessment of the potential effects of climate change. Hydrological Sciences Journal, 58 (8), 1581–1597.