Development of a continuous soil moisture accounting procedure for curve number methodology and its behaviour with different evapotranspiration methods

The curve number (CN) method is widely used for rainfall–runoff modelling in continuous hydrologic simulation models. A sound continuous soil moisture accounting procedure is necessary for models using the CN method. For shallow soils and soils with low storage, the existing methods have limitations in their ability to reproduce the observed runoff. Therefore, a simple one‐parameter model based on the Soil Conservation Society CN procedure is developed for use in continuous hydrologic simulation. The sensitivity of the model parameter to runoff predictions was also analysed. In addition, the behaviour of the procedure developed and the existing continuous soil moisture accounting procedure used in hydrologic models, in combination with Penman–Monteith and Hargreaves evapotranspiration (ET) methods was also analysed. The new CN methodology, its behaviour and the sensitivity of the depletion coefficient (model parameter) were tested in four United States Geological Survey defined eight‐digit watersheds in different water resources regions of the USA using the SWAT model. In addition to easy parameterization for calibration, the one‐parameter model developed performed adequately in predicting runoff. When tested for shallow soils, the parameter is found to be very sensitive to surface runoff and subsurface flow and less sensitive to ET. Copyright © 2007 John Wiley & Sons, Ltd.     

中国不同气候区域Hargreaves模型的修正

在计算参考作物蒸散量的模型中,FAO Penman-Monteith模型计算准确但需要气象参量过多,而Hargreaves模型只需要气温数据却无法保证较高的准确性。为了提高Hargreaves模型在中国不同气候类型条件下的适用性,以FAO Penman-Monteith模拟值为参考,建立了Hargreaves模型的修正系数。CLIMWAT数据库中156个站点的应用表明,修正前R2、RMSE分别为88.1%、3.803mm/d,修正后分别为97.3%、0.233mm/d;北京站多年的应用表明,修正前R2、RMSE分别为94.4%、4.861mm/d,修正后分别为97.2%、0.442mm/d。在此基础上,利用GIS分区运算工具建立了中国不同气候区域的修正系数表。研究结果有助于提高常规气象观测条件下(无风速、辐射观测)不同气候区域参考作物蒸散量的估算精度。     

Seasonal climate patterns and their influence on calibration of the Hargreaves-Samani equation

Abstract

Annual patterns in climate parameters were studied to evaluate how these influence the quality of reference evapotranspiration (ETo) estimates obtained from the Hargreaves-Samani (HS) equation, since the method only uses the measured temperature directly. The work evaluates how these patterns can be used to improve the HS ETo estimates. Ten-year moving averages from a set of California Irrigation Management Information System (CIMIS) stations were used to evaluate the relationships between solar radiation (R_s), temperature (T) and ETo. The results indicate that T treads behind solar radiation and its value peaks some 25 days later. Thus, the main irrigation season in the Mediterranean climate (1 May–30 September) can be divided into three phases: increasing R_s and T; decreasing R_s with increasing T; and decreasing R_s and T. Non-univocal annual cycles were observed between R_s and T, ETo and R_s, and ETo and T. These annual patterns result in important seasonal changes in the ratio between the HS and Penman-Monteith (FAO PM) ETo estimates. The changes are particularly important during the irrigation season, where the FAO PM initially calculates greater ETo values than the HS methodology, and from the end of May to early September, where the HS equation overestimates the ETo values (by 17 mm, or 3%). These patterns obtained from 2000–2009 data were used to calibrate and improve HS ETo estimates at new sites for the 2010–2011 period. Calibration based on the proposed seasonal region-wide FAO PM/HS ETo ratios improved both the bias (decreased from 0.40 to 0.36 mm d^-1) and r² (increased from 0.67 to 0.87) of the ETo estimates for the irrigation season. The proposed methodology can be easily applied to other regions, even when the existing weather stations are sparse.

Editor Z.W. Kundzewicz     

The potential of different ANN techniques in evapotranspiration modelling

The potential of three different artificial neural network (ANN) techniques, the multi‐layer perceptrons (MLPs), radial basis neural networks (RBNNs) and generalized regression neural networks (GRNNs), in modelling of reference evapotranspiration (ET₀) is investigated in this paper. Various daily climatic data, that is, solar radiation, air temperature, relative humidity and wind speed from two stations, Pomona and Santa Monica, in Los Angeles, USA, are used as inputs to the ANN techniques so as to estimate ET₀ obtained using the FAO‐56 Penman–Monteith (PM) equation. In the first part of the study, a comparison is made between the estimates provided by the MLP, RBNN and GRNN and those of the following empirical models: The California Irrigation Management Information System (CIMIS) Penman (1985), Hargreaves (1985) and Ritchie (1990). In this part of the study, the empirical models are calibrated using the standard FAO‐56 PM ET₀ values. The estimates of the ANN techniques are also compared with those of the calibrated empirical models. Mean square errors, mean absolute errors and determination coefficient statistics are used as comparing criteria for the evaluation of the models' performances. Based on the comparisons, it is found that the MLP and RBNN techniques could be employed successfully in modelling the ET₀ process. In the second part of the study, the potential of ANN techniques and the empirical methods in ET₀ estimation using nearby station data is investigated. Among the models, the calibrated Hargreaves model is found to perform better than the others. Copyright © 2007 John Wiley & Sons, Ltd.     

Hargreaves公式在塔克拉玛干沙漠腹地的适用性

对运用Hargreaves公式计算参考作物蒸散量(ET0)在干旱区的适用性存在不同观点。为了求证Hargreaves公式在极端干旱区塔克拉玛干沙漠腹地的适用性,利用2005-2010年塔克拉玛干沙漠研究站的气象资料,以利用Penman-Monteith公式计算的结果为标准,对利用Hargreaves公式计算的ET0进行了对比分析,并对两种计算结果差异的成因进行了阐释。结果表明:在年时间尺度上,利用Hargreaves公式计算的结果略大于利用Penman-Monteith公式计算的结果,标准差介于32.86~35.00 mm,年参考作物蒸散量计算结果呈现弱变异程度;在月时间尺度上,用两种方法计算的参考作物蒸散量呈现中等变异程度,蒸散量绝对偏差介于-3.26~8.73 mm,相对偏差介于-12.20%~29.02%,除了10月与11月,其余月份相对偏差均保持在10%之内。用两种方法计算的10月与11月份ET0产生差异的最主要原因在于有较高的温度较差。最后,经过对年、月参考作物蒸散量进行t-检验及建立回归方程,表明Hargreaves公式适用于极端干旱的塔克拉玛干沙漠腹地。     

蒸散发模拟的Valiantzas方法在中国的应用

根据一种简化的Penman模型,建立了一个无需风速的参考作物蒸散发模型(Penman-Valiantzas模型),在此基础上又结合Hargreaves辐射方程建立了无需风速和日照时数的Penman-Valiantzas-Hargreaves模型.利用世界粮食组织的CLIMWAT数据库中156个气象站点多年月平均资料对此...     

东北地区参考作物蒸散确定方法研究

运用FAO-Penman-monteith方法和Hargreaves方法对中国东北地区4个气候大区16个气象台站的参考作物蒸散(ET₀)进行了研究,并对FAO-Penman-monteith方法和Hargreaves方法的计算结果进行分析。发现:Hargreaves方法可适用于东北地区,尤其是亚湿润地区,但是相对于FAO-Penman-monteith方法,该方法还存在偏差,特别是半干旱地区。为了进一步提高Hargreaves方法的精度,对其进行了修正,得出比Hargreaves方法精度更高的适于东北地区参考作物蒸散计算的方程,为精确、实用地确定作物需水量和合理的灌溉制度提供了科学依据,有利于水资源的合理利用,尤其是水资源缺乏的半干旱地区。     

A simple temperature method for the estimation of evapotranspiration

Accurate estimation of evapotranspiration (ET) is essential in water resources management and hydrological practices. Estimation of ET in areas, where adequate meteorological data are not available, is one of the challenges faced by water resource managers. Hence, a simplified approach, which is less data intensive, is crucial. The FAO‐56 Penman–Monteith (FAO‐56 PM) is a sole global standard method, but it requires numerous weather data for the estimation of reference ET. A new simple temperature method is developed, which uses only maximum temperature data to estimate ET. Ten class I weather stations data were collected from the National Meteorological Agency of Ethiopia. This method was compared with the global standard PM method, the observed Piche evaporimeter data, and the well‐known Hargreaves (HAR) temperature method. The coefficient of determination (R²) of the new method was as high as 0.74, 0.75, and 0.91, when compared with that of PM reference evapotranspiration (ET_o), Piche evaporimeter data, and HAR methods, respectively. The annual average R² over the ten stations when compared with PM, Piche, and HAR methods were 0.65, 0.67, and 0.84, respectively. The Nash–Sutcliff efficiency of the new method compared with that of PM was as high as 0.67. The method was able to estimate daily ET with an average root mean square error and an average absolute mean error of 0.59 and 0.47 mm, respectively, from the PM ET_o method. The method was also tested in dry and wet seasons and found to perform well in both seasons. The average R² of the new method with the HAR method was 0.82 and 0.84 in dry and wet seasons, respectively. During validation, the average R² and Nash–Sutcliff values when compared with Piche evaporation were 0.67 and 0.51, respectively. The method could be used for the estimation of daily ET_o where there are insufficient data. Copyright © 2013 John Wiley & Sons, Ltd.     

Hargreaves公式的全局校正及适用性评价

Hargreaves公式是计算参考作物腾发量(ET<,0>)最为简便的经验公式之一,但目前对于该公式在不同气候类型区域的适用性及误差影响因素尚缺乏系统评价.在月时间尺度上,以Penman-Monteith公式计算的ET<,0>为基准值,利用洗牌复合形进化算法(SCE-UA),在中国105个气象站对Hargreaves公...     

Comparison of the Penman‐Monteith method and regional calibration of the Hargreaves equation for actual evapotranspiration using SWAT-simulated results in the Seolma-cheon basin,South Korea

ABSTRACT

The Hargreaves method provides reference evapotranspiration (ET_o) estimates when only air temperature data are available, although it requires previous local calibration for an acceptable performance. This method was evaluated using the data from 71 meteorological stations in the Seolma-cheon basin (8.48 km²), South Korea, comparing daily estimates against those from the Penman‐Monteith (PM) method, which was used as the standard. To estimate reference ET_o more exactly, considering the climatological characteristics in South Korea, parameter regionalization of the Hargreaves equation is carried out. First, the modified Hargreaves equation is presented after an analysis of the relationship between solar radiation and temperature. Second, parameter (K_ET) optimization of the regional calibration of the Hargreaves equation (RCH) is performed using the PM method and the modified equation at 71 meteorological stations. Next, an application was carried out to evaluate the evapotranspiration methods (PM, original Hargreaves and RCH) in the SWAT (Soil and Water Assessment Tool) model by comparing these with the measured actual evapotranspiration (AET) in the basin. The SWAT model was calibrated using 3 years (2007–2009) of daily streamflow at the watershed outlet and 3 years (2007–2009) of daily AET measured at a mixed forest. The model was validated with 3 years (2010‐2012) of streamflow and AET. RCH will contribute to a better understanding of evapotranspiration of an ungauged watershed in areas where meteorological information is scarce.

EDITOR D. Koutsoyiannis ASSOCIATE EDITOR Not assigned