基于遥感的地表蒸散发研究进展

地表蒸散发是整个生物圈、大气圈和水圈中水分循环和能量传输的重要控制因素。遥感技术的应用使得区域尺度的蒸散发估算成为可能,并在过去的几十年中快速发展。研究对遥感蒸散发估算进行了总结与归纳,在此基础上展望了今后的发展方向,明确指出了遥感蒸散发未来研究的突破点及发展方向。提出未来应加强蒸散发尺度效应、夜间蒸散发、不同蒸散发产品的统一真实性检验、国产卫星数据的使用、更高时空分辨率产品的研发以及机器学习在遥感蒸散发产品中的应用。     

Development and validation of a coupled heat and mass transfer model for green roofs

This paper describes a dynamic model of transient heat and mass transfer across a green roof component. The thermal behavior of the green roof layers is modeled and coupled to the water balance in the substrate that is determined accounting for evapotranspiration. The water balance variations over time directly impact the physical properties of the substrate and the evapotranspiration intensity. This thermal and hydric model incorporates wind speed effects within the foliage through a new calculation of the resistance to heat and mass transfer within the leaf canopy. The developed model is validated with experimental data from a one-tenth-scale green roof located at the University of La Rochelle. A comparison between the numerical and the experimental results demonstrates the accuracy of the model for predicting the substrate temperature and water content variations. The heat and mass transfer mechanisms through green roofs are analyzed and explained using the modeled energy balances, and parametric studies of green roof behavior are presented. A surface temperature difference of up to 25 °C was found among green roofs with a dry growing medium or a saturated growing medium. Furthermore, the thermal inertia effects, which are usually simplified or neglected, are taken into account and shown to affect the temperature and flux results. This study highlights the importance of a coupled evapotranspiration process model for the accurate assessment of the passive cooling effect of green roofs.     

Effect of Lateral Water Surface Profile on Side Weir Discharge

The average water surface slope in the lateral direction is taken into account as a local parameter ψ to study flow over a side weir. It was later shown that for smaller side weir lengths and side weir portions with no entrance and exit transition effects, ψ can be obtained from a numerical integral and also from the measurements of water surface elevations in the lateral direction. The effect of elemental weir length was further determined. Dividing the weir length into smaller computational segments has the effect of lowering the water surface to approach the measured profile, the downstream ends being coincident. The model was verified using experimental data.     

Impacts of Climate Change on Water Resources Availability and Agricultural Water Demand in the West Bank

Global climate change is predicted as a result of increased concentrations of greenhouse gasses in the atmosphere. It is predicted that climate change will result in increasing temperature by 2 to 6°C and a possible reduction of precipitation of up to 16% in the Mediterranean basin. In this study, the West Bank is taken as a case study from the Mediterranean basin to evaluate the effects of such climate change on water resources availability and agricultural water demands. Due to the uncertainty in climate change impacts on temperature and precipitation, a number of scenarios for these impacts were assumed within the range of predicted changes. For temperature, three scenarios of 2, 4 and 6°C increase were assumed. For precipitation, two scenarios of no change and 16% precipitation reduction were assumed. Based on these scenarios, monthly evapotranspiration and monthly precipitation excess depths were estimated at seven weather stations distributed over the different climatic and geographical areas of the West Bank. GIS spatial analyses showed that the increase in temperature predicted by climate change could potentially increase agricultural water demands by up to 17% and could also result in reducing annual groundwater recharge by up to 21% of existing values. However, the effects of reduced precipitation resulting from climate change are more enormous as a 16% reduction in precipitation could result in reducing annual groundwater recharge in the West Bank by about 30% of existing value. When this effect is combined with a 6°C increase in temperature, the reduction in groundwater recharge could reach 50%.     

Noise Reduction Methods for Weighing Lysimeters

Mechanical vibration of the grass and crop weighing lysimeters, located at the University of California West Side Field Research and Extension Station at Five Points, Calif. generated noise in lysimeter mass measurements and reduced the quality of evapotranspiration (ET) data. The estimated power spectral density (PSD) for grass lysimeter mass data acquired at 1.3?ms intervals contained a large peak at 11?Hz. Crop lysimeter data produced similar peaks at frequencies greater than 1?Hz. An effective method for eliminating this noise source is arithmetic averaging of the data, which should be acquired sufficiently rapidly to avoid aliasing. The PSD also increased with decreasing frequency in the range 1.0–0.1?Hz. This noise was addressed by Savitsky–Golay (SG) filtering using 7-, 11-, and 15-point filters. Each filter was applied to the same data set consisting of 2,560 measurements taken during a 1-min interval every 10?min over a 26.3-h period. Noise reduction factors, defined as the ratio of standard deviation of filtered lysimeter mass to standard deviation of unfiltered mean values of lysimeter mass for subsequences of the same data, were 0.90, 0.88, and 0.86 for the 7-, 11-, and 15-point filters, respectively. For the daytime data only, the factors were 0.88, 0.85, and 0.83. The SG filters were more effective during daytime when most of the lysimeter ET occurs. These methods are simple enough to be programmed into commercially available dataloggers for real time filtering. Hourly averages of the standard deviations of lysimeter mass measurements bear a distinct nonlinear relationship to hourly mean wind speed confirming earlier suppositions that wind loading causes noise in counterbalanced weighing lysimeters.     

Evapotranspiration on western U.S. rivers estimated using the Enhanced Vegetation Index from MODIS and data from eddy covariance and Bowen ratio flux towers

We combined remote sensing and in-situ measurements to estimate evapotranspiration (ET) from riparian vegetation over large reaches of western U.S. rivers and ET by individual plant types. ET measured from nine flux towers (eddy covariance and Bowen ratio) established in plant communities dominated by five major plant types on the Middle Rio Grande, Upper San Pedro River, and Lower Colorado River was strongly correlated with Enhanced Vegetation Index (EVI) values from the Moderate Resolution Imaging Spectrometer (MODIS) sensor on the NASA Terra satellite. The inclusion of maximum daily air temperatures (T_a) measured at the tower sites further improved this relationship. Sixteen-day composite values of EVI and T_a were combined to predict ET across species and tower sites (r² = 0.74); the regression equation was used to scale ET for 2000-2004 over large river reaches with T_a from meteorological stations. Measured and estimated ET values for these river segments were moderate when compared to historical, and often indirect, estimates and ranged from 851-874 mm yr^− 1. ET of individual plant communities ranged more widely. Cottonwood (Populus spp.) and willow (Salix spp.) stands generally had the highest annual ET rates (1100-1300 mm yr^− 1), while mesquite (Prosopis velutina) (400-1100 mm yr^− 1) and saltcedar (Tamarix ramosissima) (300-1300 mm yr^− 1) were intermediate, and giant sacaton (Sporobolus wrightii) (500-800 mm yr^− 1) and arrowweed (Pluchea sericea) (300-700 mm yr^− 1) were the lowest. ET rates estimated from the flux towers and by remote sensing in this study were much lower than values estimated for riparian water budgets using crop coefficient methods for the Middle Rio Grande and Lower Colorado River.     

Satellite-Based Energy Balance to Assess Within-Population Variance of Crop Coefficient Curves

Quantifying evapotranspiration (ET) from agricultural fields is important for field water management, water resources planning, and water regulation. Traditionally, ET from agricultural fields has been estimated by multiplying the weather-based reference ET by crop coefficients (Kc) determined according to the crop type and the crop growth stage. Recent development of satellite remote sensing ET models has enabled us to estimate ET and Kc for large populations of fields. This study evaluated the distribution of Kc over space and time for a large number of individual fields by crop type using ET maps created by a satellite based energy balance (EB) model. Variation of Kc curves was found to be substantially larger than that for the normalized difference vegetation index because of the impacts of random wetting events on Kc, especially during initial and development growth stages. Two traditional Kc curves that are widely used in Idaho for crop management and water rights regulation were compared against the satellite-derived Kc curves. Simple adjustment of the traditional Kc curves by shifting dates for emergence, effective full cover, and termination enabled the traditional curves to better fit Kc curves as determined by the EB model. Applicability of the presented techniques in humid regions having higher chances of cloudy dates was discussed.     

Evaluating the Impact of Daily Net Radiation Models on Grass and Alfalfa-Reference Evapotranspiration Using the Penman-Monteith Equation in a Subhumid and Semiarid Climate

Net radiation (Rn) is the main driving force of evapotranspiration (ET) and is a key input variable to the Penman-type combination and energy balance equations. However, Rn is not commonly measured. This paper analyzes the impact of 19 net radiation models that differ in model structure and intricacy on estimated grass and alfalfa-reference ET (ETo and ETr, respectively) and investigates how climate, season and cloud cover influence the impact of the Rn models on ETo and ETr. Datasets from two locations (Clay Center, Nebraska, subhumid; and Davis, California, a Mediterranean-type semiarid climate) were used. Rn values computed from the 19 models were used in the standardized ASCE-EWRI Penman-Monteith equation to estimate ETo and ETr on a daily time step. The influence of seasons on the estimation of Rn and on estimated ETo and ETr was investigated in winter (November–March) and summer (May–September) months. To analyze the influence of clouds on the impact of Rn models, relative shortwave radiation (Rrs) was used as a means to express the cloudiness of the days as: 0 ≤ Rrs ≤ 0.35 for completely cloudy days; 0.35相似文献   

Performance Evaluation of ANN and ANFIS Models for Estimating Garlic Crop Evapotranspiration

Estimation of evapotranspiration (ET) is necessary in water resources management, farm irrigation scheduling, and environmental assessment. Hence, in practical hydrology, it is often necessary to reliably and consistently estimate evapotranspiration. In this study, two artificial intelligence (AI) techniques, including artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS), were used to compute garlic crop water requirements. Various architectures and input combinations of the models were compared for modeling garlic crop evapotranspiration. A case study in a semiarid region located in Hamedan Province in Iran was conducted with lysimeter measurements and weather daily data, including maximum temperature, minimum temperature, maximum relative humidity, minimum relative humidity, wind speed, and solar radiation during 2008–2009. Both ANN and ANFIS models produced reasonable results. The ANN, with 6-6-1 architecture, presented a superior ability to estimate garlic crop evapotranspiration. The estimates of the ANN and ANFIS models were compared with the garlic crop evapotranspiration (ETc) values measured by lysimeter and those of the crop coefficient approach. Based on these comparisons, it can be concluded that the ANN and ANFIS techniques are suitable for simulation of ETc.     

Assessing Reference Evapotranspiration by the Hargreaves Method in Southern Spain

The Hargreaves method enables reference crop evapotranspiration (ET0) estimation in areas where meteorological information is scarce, as, for example, southern Spain. However, this method is known to produce considerable bias in this region, especially during the dry, hot summer months. An evaluation of the method is made by comparing daily estimates with those made by the more commonly recommended Penman–Monteith method at 16 meteorological stations. Computed ET0 values at the coastal stations are, on average, 0.69 mm?d?1 smaller than the Penman–Monteith estimates whereas at inland stations a small average overestimation of 0.13 mm?d?1 is shown. The adjusted Hargreaves coefficient (AHC), obtained through regression analysis, increases at the coastal stations, on average, to 0.0029, and decreases at the inland stations to 0.0022. Adjustment with the Samani method does generally not produce more accurate estimates in this region. Finally a linear relationship between the AHC and the rate of the average temperature to the average daily temperature range is proposed for the regional adjustment of the Hargreaves coefficient.