Estimating potential evapotranspiration without continuous daily data: possible errors and impact on water balance simulations     

Ludovic Oudin  Lætitia Moulin  Hocine Bendjoudi  Pierre Ribstein 《水文科学杂志》2013,58(2):209-222

Abstract

Alternative approaches to estimating monthly and annual potential evapotranspiration (PE) are explored in cases where daily climate data are not routinely recorded. A database consisting of data from 222 weather stations, representing a wide variety of climatic conditions, is used to draw general conclusions. In addition, two PE formulae with different data requirements are used: the standard FAO-56 Penman-Monteith equation, and a simple temperature-based equation. First, we tested the degree of bias introduced by using climate data averaged over long time periods instead of daily data. Second, we explored the sensitivity of PE estimation with respect to variations in sampling frequency of climate variables. The results show that using mean weather data has only a limited effect on monthly and annual PE estimates. Conversely, imperfect sampling of weather data may bias monthly and to a lesser extent annual PE estimates if the sampling period exceeds 5 and 10 days, respectively. Finally, we tested the impact of erroneous weather data on the simulations of annual actual evapotranspiration obtained with the Budyko model. The impact on the Budyko model outputs depends more on the dryness index of a given location than on annual PE; for regions under water stress, the errors in estimation of actual evapotranspiration are very limited, compared to humid regions where available energy is the dominating factor and the propagation of PE errors is important.

Citation Oudin, L., Moulin, L., Bendjoudi, H. & Ribstein, P. (2010) Estimating potential evapotranspiration without continuous daily data: possible errors and impact on water balance simulations. Hydrol. Sci. J. 55(2), 209–222.  相似文献   

Evapotranspiration in the Mekong and Yellow river basins / Evapotranspiration dans les bassins du Mekong et du Fleuve Jaune     

《水文科学杂志》2013,58(3):623-638

Abstract

Estimates of potential evapotranspiration (PET) and reference evapotranspiration (RET) were compared over the Mekong and Yellow river basins, representing humid and semi-arid Asian monsoon regions. Multiple regression relationships between monthly RET, PET, LAI (leaf area index) and climatic variables were explored for different vegetation types. Over the Mekong River basin, the spatial average of RET is only 1.7% lower than PET; however, RET is 140% higher than PET over parts of the Tibetan Plateau, due to the short and sparse grassland, and 30% lower than PET in parts of the lower basin due to the tall and well-developed forests. Over the Yellow River basin, RET is estimated to be higher than PET, on average about 50% higher across the whole basin, due to the generally sparse vegetation. A close linear relationship between annual RET and PET allows the establishment of a regional regression to predict monthly PET from monthly RET, climatic variables and/or vegetation LAI. However, the large prediction errors indicate that the Shuttleworth-Wallace (S-W) model, although it is more complex, should be recommended due to its more robust physical basis and because it successfully accounts for the effect of changing land surface conditions on PET. The limited available field data suggest that the S-W estimate may be more realistic. It was also found that vegetation conditions in summer are primarily controlled by the regional antecedent precipitation in the cold and dry seasons over the Loess Plateau in the middle reaches of the Yellow River.  相似文献   

Spatiotemporal variation and driving forces of reference evapotranspiration in Jing River Basin,northwest China   总被引：1，自引：0，他引：1       下载免费PDF全文

Lihong Xu  Zhongjie Shi  Shulan Zhang  Xinzheng Chu  Pengtao Yu  Wei Xiong  Haijun Zuo  Yunni Wang 《水文研究》2015,29(23):4846-4862

Evapotranspiration is an important component of the hydrological cycle, which integrates atmospheric demands and surface conditions. Research on spatial and temporal variations of reference evapotranspiration (ET_o) enables understanding of climate change and its effects on hydrological processes and water resources. In this study, ET_o was estimated by the FAO‐56 Penman–Monteith method in the Jing River Basin in China, based on daily data from 37 meteorological stations from 1960 to 2005. ET_o trends were detected by the Mann–Kendall test in annual, seasonal, and monthly timescales. Sensitivity coefficients were used to examine the contribution of important meteorological variables to ET_o. The influence of agricultural activities, especially irrigation on ET_o was also analyzed. We found that ET_o showed a decreasing trend in most of the basin in all seasons, except for autumn, which showed an increasing trend. Mean maximum temperature was generally the most sensitive parameter for ET_o, followed by relative humidity, solar radiation, mean minimum temperature, and wind speed. Wind speed was the most dominant factor for the declining trend in ET_o. The more significant decrease in ET_o for agricultural and irrigation stations was mainly because of the more significant decrease in wind speed and sunshine hours, a mitigation in climate warming, and more significant increase in relative humidity compared with natural stations and non‐irrigation stations. Changes in ET_o and the sensitivity coefficient of meteorological variables in relation to ET_o were also affected by topography. Better understanding of ET_o response to climate change will enable efficient use of agricultural production and water resources, which could improve the ecological environment in Jing River Basin. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

Precipitation,temperature and runoff analysis from 1950 to 2002 in the Yangtze basin,China / Analyse des précipitations,températures et débits de 1950 à 2002 dans le bassin du Yangtze,en Chine     

《水文科学杂志》2013,58(1)

Abstract

Abstract Monthly precipitation and temperature trends of 51 stations in the Yangtze basin from 1950–2002 were analysed and interpolated. The Mann-Kendall trend test was applied to examine the monthly precipitation and temperature data. Significant positive and negative trends at the 90, 95 and 99% significance levels were detected. The monthly mean temperature, precipitation, summer precipitation and monthly mean runoff at Yichang, Hankou and Datong stations were analysed. The results indicate that spatial distribution of precipitation and temperature trends is different. The middle and lower Yangtze basin is dominated by upward precipitation trend but by somewhat downward temperature trend; while downward precipitation trend and upward temperature trend occur in the upper Yangtze basin. This is because increasing precipitation leads to increasing cloud coverage and, hence, results in decreasing ground surface temperature. Average monthly precipitation and temperature analysis for the upper, middle and lower Yangtze basin, respectively, further corroborate this viewpoint. Analysis of precipitation trend for these three regions and of runoff trends for the Yichang, Hankou and Datong stations indicated that runoff trends respond well to the precipitation trends. Historical flood trend analysis also shows that floods in the middle and lower Yangtze basin are in upward trend. The above findings indicate that the middle and lower Yangtze basin is likely to face more serious flood disasters. The research results help in further understanding the influence of climatic changes on floods in the Yangtze basin, providing scientific background for the flood control activities in large catchments in Asia.  相似文献   

Estimation of future precipitation change in the Yangtze River basin by using statistical downscaling method   总被引：8，自引：3，他引：5  

Jin Huang  Jinchi Zhang  Zengxin Zhang  ChongYu Xu  Baoliang Wang  Jian Yao 《Stochastic Environmental Research and Risk Assessment (SERRA)》2011,25(6):781-792

In this study, the applicability of the statistical downscaling model (SDSM) in downscaling precipitation in the Yangtze River basin, China was investigated. The investigation includes the calibration of the SDSM model by using large-scale atmospheric variables encompassing NCEP/NCAR reanalysis data, the validation of the model using independent period of the NCEP/NCAR reanalysis data and the general circulation model (GCM) outputs of scenarios A2 and B2 of the HadCM3 model, and the prediction of the future regional precipitation scenarios. Selected as climate variables for downscaling were measured daily precipitation data (1961–2000) from 136 weather stations in the Yangtze River basin. The results showed that: (1) there existed good relationship between the observed and simulated precipitation during the calibration period of 1961–1990 as well as the validation period of 1991–2000. And the results of simulated monthly and seasonal precipitation were better than that of daily. The average R ² values between the simulated and observed monthly and seasonal precipitation for the validation period were 0.78 and 0.91 respectively for the whole basin, which showed that the SDSM had a good applicability on simulating precipitation in the Yangtze River basin. (2) Under both scenarios A2 and B2, during the prediction period of 2010–2099, the change of annual mean precipitation in the Yangtze River basin would present a trend of deficit precipitation in 2020s; insignificant changes in the 2050s; and a surplus of precipitation in the 2080s as compared to the mean values of the base period. The annual mean precipitation would increase by about 15.29% under scenario A2 and increase by about 5.33% under scenario B2 in the 2080s. The winter and autumn might be the more distinct seasons with more predicted changes of precipitation than in other seasons. And (3) there would be distinctive spatial distribution differences for the change of annual mean precipitation in the river basin, but the most of Yangtze River basin would be dominated by the increasing trend.  相似文献   

Combined analysis of precipitation and water deficit for drought hazard assessment     

Tamara Tokarczyk  Wiwiana Szalińska 《水文科学杂志》2013,58(9):1675-1689

Abstract

The combined analysis of precipitation and water scarcity was done with the use of the Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI), developed as a monthly, two-variable SPI-SRI indicator to identify different classes of hydrometeorological conditions. Stochastic analysis of a long-term time series (1966–2005) of monthly SPI-SRI indicator values was performed using a first-order Markov chain model. This provided characteristics of regional features of drought formation, evolution and persistence, as well as tools for statistical long-term drought hazard prediction. The study was carried out on two subbasins of the Odra River (Poland) of different orography and land use: the mountainous Nysa K?odzka basin and the lowland, agricultural Prosna basin. Classification obtained with the SPI-SRI indicator was compared with the output from the NIZOWKA model that provided identification of hydrological drought events including drought duration and deficit volume. Severe and long-duration droughts corresponded to SPI-SRI Class 3 (dry meteorological and dry hydrological), while severe but short-term droughts (lasting less than 30 days) corresponded to SPI-SRI Class 4 (wet meteorological and dry hydrological). The results confirm that, in Poland, meteorologically dry conditions often shift to hydrologically dry conditions within the same month, droughts rarely last longer than 2 months and two separate drought events can be observed within the same year.  相似文献   

A drought outlook study in Korea     

Young-Oh Kim  Jae-Kyoung Lee  Richard. N. Palmer 《水文科学杂志》2013,58(6):1141-1153

Abstract

Techniques are proposed for developing a monthly and weekly drought outlook and the drought outlook components are evaluated. A drought index, the surface water supply index (SWSI) was modified and used for the drought outlook. A water balance model (abcd) was successfully calibrated using a regional regression, including monthly and weekly factors, and was used to convert meteorology to hydrology. For the monthly drought outlook, an ensemble technique was applied, both with and without monthly industrial meteorology information (MIMI). For the weekly drought outlook, a deterministic forecasting technique was applied employing the Global Data Assimilation and Prediction System (GDAPS). The methodologies were applied to the Geum River basin in Korea. While only the weekly outlook using the GDAPS has sufficient forecasting capability to suggest it might be useful, the accuracy of the monthly drought outlook is expected to improve as the climate forecast accuracy increases.

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

Citation Kim, Y.-O., Lee, J.-K., and Palmer, R.N., 2012. A drought outlook study in Korea. Hydrological Sciences Journal, 57 (6), 1141–1153.  相似文献   

Estimating daily streamflow in the Congo Basin using satellite-derived data and a semi-distributed hydrological model     

Yolande A. Munzimi  Matthew C. Hansen  Kwabena O. Asante 《水文科学杂志》2013,58(12):1472-1487

ABSTRACT

The application of remotely-sensed data for hydrological modeling of the Congo Basin is presented. Satellite-derived data, including TRMM precipitation, are used as inputs to drive the USGS Geospatial Streamflow Model (GeoSFM) to estimate daily river discharge over the basin from 1998 to 2012. Physically-based parameterization was augmented with a spatially-distributed calibration that enables GeoSFM to simulate hydrological processes such as the slowing effect of the Cuvette Centrale. The resulting simulated long-term mean of daily flows and the observed flow at the Kinshasa gauge were comparable (40 631 and 40 638 m³/s respectively), in the 7-year validation period (2004–2010), with no significant bias and a Nash-Sutcliffe model efficiency coefficient of 0.70. Modeled daily flows and aggregated monthly river outflows (compared to historical averages) for additional sites confirm the model reliability in capturing flow timing and seasonality across the basin, but sometimes fails to accurately predict flow magnitude. The results of this model can be useful in research and decision-making contexts and validate the application of satellite-based hydrological models driven for large, data-scarce river systems such as the Congo.  相似文献   

Semi-empirical prediction method for monthly precipitation prediction based on environmental factors and comparison with stochastic and machine learning models     

Huihui Zhang  Hugo A. Loáiciga  Fu Ren  Da Ha 《水文科学杂志》2020,65(11):1928-1942

ABSTRACT

Precipitation prediction is central in hydrology and water resources planning and management. This paper introduces a semi-empirical predictive model to predict monthly precipitation and compares its predictive skill with those of machine learning (ML) methods. The stochastic method presented herein estimates monthly precipitation with one-step-ahead prediction properties. The ML predictive skill of the algorithms is evaluated by predicting monthly precipitation relying on the statistical association between precipitation and environmental and topographic factors. The semi-empirical predictive model features non-negative matrix factorization (NMF) for investigating the influence of multiple predictor variables on precipitation. The semi-empirical predictive model’s parameters are optimized with the hybrid genetic algorithm (GA) and Levenberg-Marquardt algorithm (LM), or GALMA, yielding a validated model with high predictive skill. The methodologies are illustrated with data from Hubei Province, China, which comprise 27 meteorological station datasets from 1988–2017. The empirical results provide valuable insights for developing semi-empirical rainfall prediction models.  相似文献   

Multiscale variability of streamflow changes in the Pearl River basin,China   总被引：1，自引：1，他引：0  

Yongqin David Chen  Qiang Zhang  Xiaohong Chen  Ping Wang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2012,26(2):235-246

The Pearl River basin bears the heavy responsibility for the water supply for the neighboring cities such as Macau, Hong Kong and others. Therefore, effective water resource management is crucial for sustainable use of water resource. However, good knowledge of changing properties of streamflow changes is the first step into the effective water resource management. With this in mind, stability and variability of streamflow changes in the Pearl River basin is thoroughly analyzed based on monthly streamflow data covering last half century using Mann–Kendall trend test and scanning t- and F-test techniques. The results indicate: (1) significant increasing monthly streamflow is observed mainly in January–April, June and October–December. Monthly streamflow during May–September is in not significant changes. Besides, stations characterized by significant monthly streamflow changes are located in the middle and the lower Pearl River basin; (2) changing points of monthly streamflow series are detected mainly during mid-1960s, early 1970s, mid-1970s, early 1980s and early 1990s and these periods are roughly in good agreement with those of annual, winter and summer precipitation across the Pearl River basin, implying tremendous influences of precipitation changes on streamflow variations; (3) abrupt behaviors tend to be ambiguous from the upper to the lower Pearl River basin, which should be due to enhancing combined effects of abrupt changes of precipitation. The streamflow comes to be lower stability in recent decades. However, high stability of streamflow changes are observed at hydrological stations in the lower Pearl River basin. The results of this study will be of great scientific and practical merits in terms of effective water resource management in the Pearl River basin under the influences of climate changes and human activities.  相似文献   

Assessment of hydropower potential using spatial technology and SWAT modelling in the Mat River,southern Mizoram,India     

Ashish Pandey  Daniel Lalrempuia  S.K. Jain 《水文科学杂志》2013,58(10):1651-1665

Abstract

In this study, a hydrological model and spatial technologies have been employed to assess water availability in the Mat River basin, southern Mizoram, India. Furthermore, the results obtained from the SWAT (Soil and Water Assessment Tool) model, satellite data and GIS tools were utilized to identify the hydropower potential in the basin. Thirty three sites with hydropower potential were identified within 147 km² of the Mat River basin. A total of 3039, 1127 and 805 kW can be harnessed with 50, 75 and 90% dependability, respectively. The study revealed that the hydropower potential of a river basin can be correctly assessed by employing a digital elevation model, stream network data and a hydrological model, such as the SWAT model, within a GIS framework.