共查询到20条相似文献，搜索用时 484 毫秒
1.
In this study, a methodology for clustering 18 lakes in Alberta, Canada using the data of 19 water quality parameters for a period of 11 years (1988–2002) is presented. The methods consist of (i) principal component analysis (PCA) to determine the dominant water quality parameters, (ii) cluster analysis techniques to develop the characteristics of the clusters, and (iii) pattern‐match lakes to determine the appropriate cluster for each of the lakes. The PCA revealed that three principal components (PCs) were able to explain ～88% of the variability and the dominant water quality parameters were total dissolved solids, total phosphorus, and chlorophyll‐a. We obtained five clusters for the period 1994–1997 by using the dominant parameters with water quality deteriorating as the cluster number increased from 1 to 5. Upon matching cluster patterns with the entire dataset, it was observed that some of the lakes belonged to the same cluster all the time (e.g., cluster 1 for lakes Elkwater, Gregg, and Jarvis; cluster 3 for Sturgeon; cluster 4 for Moonshine; and cluster 5 for Saskatoon), while others changed with time. This methodology could be applied in other regions of the world to identify the most suitable source waters and prioritize their management. It could be helpful to analyze the natural controlling processes, pollution types, impact of seasonal changes and overall quality of source waters. This methodology could be used for monitoring water bodies in a cost effective and efficient way by sampling only less number of dominant parameters instead of using a large set of parameters. 相似文献
2.
Rajtantra Lilhare Scott Pokorny Stephen J. Déry Tricia A. Stadnyk Kristina A. Koenig 《水文研究》2020,34(9):2057-2075
In this study, we evaluate uncertainties propagated through different climate data sets in seasonal and annual hydrological simulations over 10 subarctic watersheds of northern Manitoba, Canada, using the variable infiltration capacity (VIC) model. Further, we perform a comprehensive sensitivity and uncertainty analysis of the VIC model using a robust and state-of-the-art approach. The VIC model simulations utilize the recently developed variogram analysis of response surfaces (VARS) technique that requires in this application more than 6,000 model simulations for a 30-year (1981–2010) study period. The method seeks parameter sensitivity, identifies influential parameters, and showcases streamflow sensitivity to parameter uncertainty at seasonal and annual timescales. Results suggest that the Ensemble VIC simulations match observed streamflow closest, whereas global reanalysis products yield high flows (0.5–3.0 mm day−1) against observations and an overestimation (10–60%) in seasonal and annual water balance terms. VIC parameters exhibit seasonal importance in VARS, and the choice of input data and performance metrics substantially affect sensitivity analysis. Uncertainty propagation due to input forcing selection in each water balance term (i.e., total runoff, soil moisture, and evapotranspiration) is examined separately to show both time and space dimensionality in available forcing data at seasonal and annual timescales. Reliable input forcing, the most influential model parameters, and the uncertainty envelope in streamflow prediction are presented for the VIC model. These results, along with some specific recommendations, are expected to assist the broader VIC modelling community and other users of VARS and land surface schemes, to enhance their modelling applications. 相似文献
3.
Stormwater infiltration systems are a popular method for urban stormwater control. They are often designed using an assumption of one‐dimensional saturated outflow, although this is not very accurate for many typical designs where two‐dimensional (2D) flows into unsaturated soils occur. Available 2D variably saturated flow models are not commonly used for design because of their complexity and difficulties with the required boundary conditions. A purpose‐built stormwater infiltration system model was thus developed for the simulation of 2D flow from a porous storage. The model combines a soil moisture–based model for unsaturated soils with a ponded storage model and uses a wetting front‐tracking approach for saturated flows. The model represents the main physical processes while minimizing input data requirements. The model was calibrated and validated using data from laboratory 2D stormwater infiltration trench experiments. Calibrations were undertaken using five different combinations of calibration data to examine calibration data requirements. It was found that storage water levels could be satisfactorily predicted using parameters calibrated with either data from laboratory soils tests or observed water level data, whereas the prediction of soil moistures was improved through the addition of observed soil moisture data to the calibration data set. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
4.
The spatial–temporal variation of dry and wet periods in Iran based on comparing SPI and RDI indices
Drought is a natural hazard which can cause harmful effects on water resources. To monitor drought, the use of an indicator and determination of wet and dry period trend seem to have an important role in quantifying the drought analysis. In this paper, in addition to the comparison of Reconnaissance Drought Index (RDI) and Standardized Precipitation Index (SPI), based on the most appropriate probability distribution function, it was tried to examine the trends of dry and wet periods based on the mentioned indices. Accordingly, the meteorological data of 30 synoptic stations in Iran (1960–2014) was used and the trend was analyzed using the Mann–Kendall test by eliminating the effect of any significant autocorrelation coefficients at 95% confidence level (modified Mann–Kendall). Comparing results between the time series of RDI and SPI drought indices based on statistical indicators (RMSE?<?0.434, R2?>?0.819 and T-statistic?<?0.419) in all studied stations revealed that the behavior of the two indices was roughly the same and the difference between them was not significant. The trend analysis results of RDI and SPI indices based on modified Mann–Kendall test showed that the variation of dry and wet periods was decreasing in most of the studied stations (five cases were significant). In addition, the results of the trend line slope of dry and wet periods related to the drought indices in the studied area indicated that the slope was negative for SPI and RDI indices in 70% and 50% of stations, respectively. 相似文献
5.
M.G. Orozco‐del‐Castillo M. Cárdenas‐Soto C. Ortiz‐Alemán C. Couder‐Castañeda J. Urrutia‐Fucugauchi A. Trujillo‐Alcántara 《Geophysical Prospecting》2017,65(1):97-105
We present a novel approach to automated volume extraction in seismic data and apply it to the detection of allochthonous salt bodies. Using a genetic algorithm, we determine the optimal size of volume elements that statistically, according to the U‐test, best characterize the contrast between the textures inside and outside of the salt bodies through a principal component analysis approach. This information was used to implement a seeded region growing algorithm to directly extract the bodies from the cube of seismic amplitudes. We present the resulting three‐dimensional bodies and compare our final results to those of an interpreter, showing encouraging results. 相似文献
6.
《水文科学杂志》2013,58(2):434-447
Abstract The behaviour of statistical performance indices, namely, reliability, resilience and vulnerability for a multipurpose storage reservoir is examined. Monte Carlo simulations were carried using data of the Dharoi Reservoir (India) and the inflows to the reservoir were generated by following two approaches: long-memory models and short-memory models. Statistical behaviour of three indices were examined for two cases: (i) municipal and industrial water supply; and (ii) irrigation, thus making a total of six indices for the analysis. To interpret the behaviour of these indices, a probabilistic approach was followed. It was noted that when inflows generated using long-memory models were input in simulation, there were large variations in reliability, resilience and vulnerability among the runs. In contrast, when data from short-memory models were used, the indices were confined to a narrow band. Average values of reliabilities and their variance for both the demands were much higher when the data generated using short-memory models were used. Since natural geophysical hydrological data series display persistence, the results pertaining to long-memory model are closer to reality. It was also shown that the framework of analysis presented can be very useful for multicriteria analysis and interpretation of trade-offs in the reliability space. 相似文献
7.
《Limnologica》2016
The Guayas river basin is one of the major watersheds in Ecuador, where increasing human activities are affecting water quality and related ecosystem services. The aims of this study were (1) to assess the ecological water quality based on macroinvertebrate indices and (2) to determine the major environmental variables affecting these macroinvertebrate indices. To do so, we performed an integrated water quality assessment at 120 locations within the river basin. Biological and physical–chemical data were collected to analyze the water quality. Two biotic indices were calculated to assess the water quality with an ecological approach: the Biological Monitoring Working Party Colombia (BMWP-Col) and the Neotropical Low-land Stream Multimetric Index (NLSMI). Both the BMWP-Col and NLSMI indicated good water quality at the (upstream) forested locations, lower water quality for sites situated at arable land and bad water quality at residential areas. Both indices gave relevant assessment outcomes and can be considered valuable for supporting the local water management. A correspondence analysis (CA) applied on both indices suggested that flow velocity, chlorophyll concentration, conductivity, land use, sludge layer and sediment type were the major environmental variables determining the ecological water quality. We also suggested that nutrient and pesticide measurements are important to study water quality in the area where intensive agriculture activities take place. The nutrient levels detected in agricultural areas were relatively low and illustrated that the types of crops and the current cultivation methods were not leading to eutrophication. The applied methods and results of this study can be used to support the future water management of the Guayas river basin and similar basins situated in the tropics. 相似文献
8.
Jorge Ramón Alicia Correa Edison Timbe Giovanny M. Mosquera Enma Mora Patricio Crespo 《水文研究》2021,35(6):e14209
Hydrogeochemical based mixing models have been successfully used to investigate the composition and source identification of streamflow. The applicability of these models is limited due to the high costs associated with data collection and the hydrogeochemical analysis of water samples. Fortunately, a variety of mixing models exist, requiting different amount of data as input, and in data scarce regions it is likely that preference will be given to models with the lowest requirement of input data. An unanswered question is if models with high or low input requirement are equally accurate. To this end, the performance of two mixing models with different input requirement, the mixing model analysis (MMA) and the end-member mixing analysis (EMMA), were verified on a tropical montane headwater catchment (21.7 km2) in the Ecuadorian Andes. Nineteen hydrogeochemical tracers were measured on water samples collected weekly during 3 years in streamflow and eight potential water sources or end-members (precipitation, lake water, soil water from different horizons and springs). Results based on 6 conservative tracers, revealed that EMMA (using all tracers) and MMA (using pair-combinations out of the 6 conservative ones), identified the same end-members: rainfall, soil water and spring water., as well as, similar contribution fractions to streamflow from rainfall 21.9% and 21.4%, soil water 52.7% and 52.3%, and spring water 26.1% and 28.7%, respectively. Our findings show that a hydrogeochemical mixing model requiring a few tracers can provide similar outcomes than models demanding more tracers as input data. This underlines the value of a preliminary detailed hydrogeochemical characterization as basis to derive the most cost-efficient monitoring strategy. 相似文献
9.
ABSTRACTAn appropriate streamflow forecasting method is a prerequisite for implementation of efficient water resources management in the water-limited, arid regions that occupy much of Iran. In the current research, monthly streamflow forecasting was combined with three data-driven methods based on large input datasets involving 11 precipitation stations, a natural streamflow, and four climate indices through a long period. The major challenges of rainfall–runoff modelling are generally attributed to complex interacting processes, the large number of variables, and strong nonlinearity. The sensitivity of data-driven methods to the dimension of input/output datasets would be another challenge, so large datasets should be compressed into independently standardized principal components. In this study, three pre-processing techniques were applied: singular value decomposition (SVD) provided more efficient forecasts in comparison to principal component analysis (PCA) and average values of inputs in all networks. Among the data-driven methods, the multi-layer perceptron (MLP) with 1-month lag-time outperformed radial basis and fuzzy-based networks. In general, an increase in monthly lag-time of streamflow forecasting resulted in a decline in forecasting accuracy. The results reveal that SVD was highly effective in pre-processing of data-driven evaluations. 相似文献
10.
Good modelling practice requires the incorporation of uncertainty analysis into hydrologic/water quality models. The generalized likelihood uncertainty estimation procedure was used to evaluate the uncertainty in DRAINMOD predictions of daily, monthly, and yearly subsurface drain flow. A variance‐based sensitivity analysis technique, the extended Fourier amplitude sensitivity test, was used to identify the main sources of prediction uncertainty. The analysis was conducted for the experimental drainage field at the Southeast Purdue Agricultural Center in Indiana. Six years of data were used and the uncertainties in eight model parameters were considered to analyse how uncertainties in input parameters propagate to model outputs. The width of 90% confidence interval bands of drain flow ranged from 0 to 0·6 cm day?1 for daily predictions, from 0 to 3·1 cm month?1 for the monthly predictions, and from 7·6 to 12·4 cm year?1 for yearly predictions. Annual drain flow predicted by DRAINMOD fell well within the 90% confidence bounds. Model results were most sensitive to the vertical saturated hydraulic conductivity of the restrictive layer and the lateral hydraulic conductivity of the deepest soil layer, followed by the lateral hydraulic conductivity of the top soil layer and surface micro‐storage. Parameter interactions also contributed to the prediction uncertainty. Copyright © 2006 John Wiley & Sons, Ltd. 相似文献
11.
An improved, iteratively re‐weighted factor analysis procedure is presented to interpret engineering geophysical sounding logs in shallow unsaturated sediments. We simultaneously process cone resistance, electric resistivity, and nuclear data acquired by direct‐push tools to give robust estimates of factor variables and water content in unconsolidated heterogeneous formations. The statistical procedure is based on the iterative re‐weighting of the deviations between the measured and calculated data using the most frequent value method famous for its robustness and high statistical efficiency. The iterative approach improves the result of factor analysis for not normally distributed data and extremely noisy measurements. By detecting a strong regression relation between one of the extracted factors and the fractional volume of water, we establish an independent method for water content estimation along the penetration hole. We verify the estimated values of water volume by using a highly over‐determined, quality‐checked interval inversion procedure. The multidimensional extension of the statistical method allows the estimation of water content distribution along both the vertical and the horizontal coordinates. Numerical tests using engineering geophysical sounding data measured in a Hungarian loessy–sandy formation demonstrate the feasibility of the most frequent value‐based factor analysis, which can be efficiently used for a more reliable hydrogeophysical characterisation of the unsaturated zone. 相似文献
12.
In this paper, we analyse the uncertainty and parameter sensitivity of a conceptual water quality model, based on a travel time distribution (TTD) approach, simulating electrical conductivity (EC) in the Duck River, Northwest Tasmania, Australia for a 2-year period. Dynamic TTDs of stream water were estimated using the StorAge Selection (SAS) approach, which was coupled with two alternate methods to model stream water EC: (1) a solute-balance approach and (2) a water age-based approach. Uncertainty analysis using the Differential Evaluation Adoptive Metropolis (DREAM) algorithm showed that: 1. parameter uncertainty was a small contribution to the overall uncertainty; 2. most uncertainty was related to input data uncertainty and model structure; 3. slightly lower total error was obtained in the water age-based model than the solute-balance model; 4. using time-variant SAS functions reduced the model uncertainty markedly, which likely reflects the effect of dynamic hydrological conditions over the year affecting the relative importance of different flow pathways over time. Model parameter sensitivity analysis using the Variogram Analysis of Response Surfaces (VARS-TOOL) framework found that parameters directly related to the EC concentration were most sensitive. In the solute-balance model, the rainfall concentration Crain and in the age-based model, the parameter controlling the rate of change of EC with age (λ) were the most sensitive parameter. Model parameters controlling the age mixes of both evapotranspiration and streamflow water fluxes (i.e., the SAS function parameters) were influential for the solute-balance model. Little change in parameter sensitivity over time was found for the age-based concentration relationship; however, the parameter sensitivity was quite dynamic over time for the solute-balance approach. The overarching outcomes provide water quality modellers, engineers and managers greater insight into catchment functioning and its dependence on hydrological conditions. 相似文献
13.
现有水色卫星主要是针对大洋清洁水体设计,内陆浑浊水体多数波段经常饱和;而发展可以业务化运行的内陆水体叶绿素a算法,为生产实践服务,一直是水色遥感的重点和难点之一.利用2013年巢湖星地同步数据(N=55),通过经验正交函数(empirical orthogonal function,EOF)分析方法,选用MODIS唯一不饱和的4个波段(469、555、645、859 nm)数据进行分解,然后回归建模;并使用第三方独立的巢湖实测数据(N=40)进行验证(R2=0.63,URMSE=85.46%).结果表明:该算法用于MODIS影像上,空间分布合理,季节差异明显,且在高悬浮物水体、不同气溶胶条件下均有很好的抗扰动性.实践证明EOF算法可以应用于业务化运行的内陆水体叶绿素a浓度估算,并对其他水色参数反演具有一定的借鉴意义. 相似文献
14.
Spatiotemporal estimation of snow depth using point data from snow stakes,digital terrain models,and satellite data 
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下载免费PDF全文 Antonio‐Juan Collados‐Lara Eulogio Pardo‐Igúzquiza David Pulido‐Velazquez 《水文研究》2017,31(10):1966-1982
Snow availability in Alpine catchments plays an important role in water resources management. In this paper, we propose a method for an optimal estimation of snow depth (areal extension and thickness) in Alpine systems from point data and satellite observations by using significant explanatory variables deduced from a digital terrain model. It is intended to be a parsimonious approach that may complement physical‐based methodologies. Different techniques (multiple regression, multicriteria analysis, and kriging) are integrated to address the following issues: We identify the explanatory variables that could be helpful on the basis of a critical review of the scientific literature. We study the relationship between ground observations and explanatory variables using a systematic procedure for a complete multiple regression analysis. Multiple regression models are calibrated combining all suggested model structures and explanatory variables. We also propose an evaluation of the models (using indices to analyze the goodness of fit) and select the best approaches (models and variables) on the basis of multicriteria analysis. Estimation of the snow depth is performed with the selected regression models. The residual estimation is improved by applying kriging in cases with spatial correlation. The final estimate is obtained by combining regression and kriging results, and constraining the snow domain in accordance with satellite data. The method is illustrated using the case study of the Sierra Nevada mountain range (Southern Spain). A cross‐validation experiment has confirmed the efficiency of the proposed procedure. Finally, although it is not the scope of this work, the snow depth is used to asses a first estimation of snow water equivalent resources. 相似文献
15.
Girma Yimer Ebrahim Kelly Hamonts Ann van Griensven Andreja Jonoski Winnie Dejonghe Arthur Mynett 《水文研究》2013,27(11):1634-1645
Groundwater interacts with surface water features nearly in all types of landscapes. Understanding these interactions has practical consequences on the quantity and quality of water in either system, because the depletion or contamination of one of the systems will eventually affect the other one. Many studies have shown that the use of heat as natural tracer in conjunction with water level measurements is an effective method for estimating water flow (fluxes) between groundwater and surface water. A number of studies have explored the effects of spatial and temporal variability of groundwater–surface water flux exchanges using temperature and water level measurements; however, the effect of temporal resolution of water level and temperature data on estimating flux remains unexplored. Therefore, this study investigated the effect of temporal resolution of input data on temporal variation of groundwater–surface water flux exchanges. To this end, we calibrated a variably saturated two‐dimensional groundwater flow and heat transport model (VS2DH) at hourly and daily time scales using temperatures measured at multiple depths below the riverbed of the Zenne River, located at a well‐known Belgian brownfield site. Results of the study showed that the computed water flux through the streambed ranged between ?32 mm/day and +25 mm/day using the hourly model and from ?10 mm/day to ?37 mm/day using the daily model. The hourly model resulted in detecting reversal of flow direction inducing short‐term surface water flow into the streambed. However, such events were not captured if daily temperature and water level measurements were used as input. These findings have important implications for understanding contaminant mass flux and their attenuation in the mixing zone of groundwater and surface water. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
16.
Although previous seismic monitoring studies have revealed several relationships between seismic responses and changes in reservoir rock properties, the quantitative evaluation of time‐lapse seismic data remains a challenge. In most cases of time‐lapse seismic analysis, fluid and/or pressure changes are detected qualitatively by changes in amplitude strength, traveltime and/or Poisson's ratio. We present the steps for time‐lapse seismic analysis, considering the pressure effect and the saturation scale of fluids. We then demonstrate a deterministic workflow for computing the fluid saturation in a reservoir in order to evaluate time‐lapse seismic data. In this approach, we derive the physical properties of the water‐saturated sandstone reservoir, based on the following inputs: VP, VS, ρ and the shale volume from seismic analysis, the average properties of sand grains, and formation‐water properties. Next, by comparing the in‐situ fluid‐saturated properties with the 100% formation‐water‐saturated reservoir properties, we determine the bulk modulus and density of the in‐situ fluid. Solving three simultaneous equations (relating the saturations of water, oil and gas in terms of the bulk modulus, density and the total saturation), we compute the saturation of each fluid. We use a real time‐lapse seismic data set from an oilfield in the North Sea for a case study. 相似文献
17.
The stream hydrograph is an integration of spatial and temporal variations in water input, storage and transfer processes within a catchment. For glacier basins in particular, inferences concerning catchment‐scale processes have been developed from the varying form and magnitude of the diurnal hydrograph in the proglacial river. To date, however, such classifications of proglacial diurnal hydrographs have developed in a relatively subjective manner. This paper develops an objective approach to the classification of diurnal discharge hydrograph ‘shape’ and ‘magnitude’ using a combination of principal components analysis and cluster analysis applied to proglacial discharge time‐series and to diurnal bulk flow indices. The procedure is applied to discharge time‐series from two different glacier basins and four separate ablation seasons representing a gradient of increasing hydrological perturbation as a result of (i) variable water inputs generated by rainstorm activity and (ii) variable location and response of hydrological stores through a systematic decrease in catchment glacierized area. The potential of the technique for application in non‐glacial hydrological contexts is discussed. Copyright © 2000 John Wiley & Sons, Ltd. 相似文献
18.
Rehan Sadiq Solomon Tesfamariam 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(4):495-505
Environmental indices (EI) constitute a common communication tool that is often used to describe the overall status of environmental
systems (air, water and soil). EI development entails the use of mathematical operators to aggregate various non-commensurate
input parameters in a logical manner. The ordered weighted averaging (OWA) operator is a general mean type operator that provides
flexibility in the aggregation process such that the aggregated value is bounded between minimum and maximum values of the
input parameters. This flexibility of the OWA operator is realized through the concept of orness, which is a surrogate for
decision maker’s attitude. The type of input parameters also affects the choice of aggregation operators. If the input parameters
are linguistic or fuzzy, the aggregation through OWA operators is not possible, and the use of fuzzy arithmetic is warranted.
The concept of fuzzy number OWA (FN-OWA) operators is explored to handle situations in which one or more input parameter has
fuzzy (or linguistic) values. The proposed approach is demonstrated using data provided in an earlier study by Swamee and
Tyagi (ASCE J Environ Eng 126(5):451–455, 2000) for establishing water quality indices. Multiple hypothetical scenarios are also generated to highlight the utility and
sensitivity of the proposed approach. 相似文献
19.
Application and evaluation of a snowmelt runoff model in the Tamor River basin,Eastern Himalaya using a Markov Chain Monte Carlo (MCMC) data assimilation approach 总被引：2，自引：0，他引：2 下载免费PDF全文
下载免费PDF全文 Previous studies have drawn attention to substantial hydrological changes taking place in mountainous watersheds where hydrology is dominated by cryospheric processes. Modelling is an important tool for understanding these changes but is particularly challenging in mountainous terrain owing to scarcity of ground observations and uncertainty of model parameters across space and time. This study utilizes a Markov Chain Monte Carlo data assimilation approach to examine and evaluate the performance of a conceptual, degree‐day snowmelt runoff model applied in the Tamor River basin in the eastern Nepalese Himalaya. The snowmelt runoff model is calibrated using daily streamflow from 2002 to 2006 with fairly high accuracy (average Nash–Sutcliffe metric ~0.84, annual volume bias < 3%). The Markov Chain Monte Carlo approach constrains the parameters to which the model is most sensitive (e.g. lapse rate and recession coefficient) and maximizes model fit and performance. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall compared with simulations using observed station precipitation. The average snowmelt contribution to total runoff in the Tamor River basin for the 2002–2006 period is estimated to be 29.7 ± 2.9% (which includes 4.2 ± 0.9% from snowfall that promptly melts), whereas 70.3 ± 2.6% is attributed to contributions from rainfall. On average, the elevation zone in the 4000–5500 m range contributes the most to basin runoff, averaging 56.9 ± 3.6% of all snowmelt input and 28.9 ± 1.1% of all rainfall input to runoff. Model simulated streamflow using an interpolated precipitation data set decreases the fractional contribution from rainfall versus snowmelt compared with simulations using observed station precipitation. Model experiments indicate that the hydrograph itself does not constrain estimates of snowmelt versus rainfall contributions to total outflow but that this derives from the degree‐day melting model. Lastly, we demonstrate that the data assimilation approach is useful for quantifying and reducing uncertainty related to model parameters and thus provides uncertainty bounds on snowmelt and rainfall contributions in such mountainous watersheds. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
20.
A computational fluid dynamics (CFD)‐based methodology is proposed to derive convective mass‐transfer coefficients (wind functions) that are required for estimating evaporation of water bodies with the mass‐transfer method. Three‐dimensional CFD was applied to model heat transfer in two water bodies: a Class‐A tank evaporimeter and an on‐farm artificial pond. The standard k–? model assuming isotropic turbulence was adopted to describe turbulent heat transport, whereas the heat and mass transfer analogy was assumed to derive the wind functions. The CFD‐derived wind functions were very similar to those empirically derived from the experimental water bodies. The evaporation rates calculated with the synthetic wind functions were in good agreement with hourly and daily evaporation measurements for the tank and pond, respectively. The proposed CFD‐approach is generalisable and cost effective, because it has low input data requirements. Besides, it provides additional capability of modelling the spatial distribution of the evaporation rate over the water surface. Although the application of CFD to water bodies evaporation modelling is still in development, it looks very promising. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献