Polynomial chaos expansion and response surface method for nonlinear modelling of reference evapotranspiration

The feasibility of polynomial chaos expansion (PCE) and response surface method (RSM) models is investigated for modelling reference evapotranspiration (ET₀). The modelling results of the proposed models are validated against the M5 model tree and multi-layer perceptron neural network (MLPNN) methods. Two meteorological stations, Isparta and Antalya, in the Mediterranean region of Turkey, are inspected. Various input combinations of daily air temperature, solar radiation, wind speed and relative humidity are constructed as input attributes for the ET₀. Generally, the modelling accuracy is increased by increasing the number of inputs. Including wind speed in the model inputs considerably increases their accuracy in modelling ET₀. Mean absolute error (MAE), root mean square error (RMSE), agreement index (d) and Nash-Sutcliffe efficiency (NSE) are used as comparison criteria. The PCE is the most accurate model in estimating daily ET₀, giving the lowest MAE (0.036 and 0.037 mm) and RMSE (0.047 and 0.050 mm) and the highest d (0.9998 and 0.9999) and NSE (0.9992 and 0.9996) with the four-input PCE models for Isparta and Antalya, respectively.     

Spatially distributed hydrotope‐based modelling of evapotranspiration and runoff in mountainous basins

River basins in mountainous regions are characterized by strong variations in topography, vegetation, soils, climatic conditions and snow cover conditions, and all are strongly related to altitude. The high spatial variation needs to be considered when modelling hydrological processes in such catchments. A complex hydrological model, with a great potential to account for spatial variability, was developed and applied for the hourly simulation of evapotranspiration, soil moisture, water balance and the runoff components for the period 1993 and 1994 in 12 subcatchments of the alpine/pre‐alpine basin of the River Thur (area 1703 km²). The basin is located in the north‐east of the Swiss part of the Rhine Basin and has an elevation range from 350 to 2500 m a.s.l. A considerable part of the Thur Basin is high mountain area, some of it above the tree‐line and a great part of the basin is snow covered during the winter season. In the distributed hydrological model, the 12 sub‐basins of the Thur catchment were spatially subdivided into sub‐areas (hydrologically similar response units—HRUs or hydrotopes) using a GIS. Within the HRUs a hydrologically similar behaviour was assumed. Spatial interpolations of the meteorological input variables wereemployed for each altitudinal zone. The structure of the model components for snow accumulation and melt, interception, soil water storage and uptake by evapotranspiration, runoff generation and flow routing are briefly outlined. The results of the simulated potential evapotranspiration reflect the dominant role of altitudinal change in radiation and albedo of exposure, followed by the influence of slope. The actual evapotranspiration shows, in comparison with the potential evapotranspiration, a greater variability in the lower and medium altitudinal zones and a smaller variability in the upper elevation zones, which was associated with limitations of available moisture in soil and surface depression storages as well as with the evaporative demand of the local vegetation. The higher altitudinal dependency and variability of runoff results from the strong increase in precipitation and the decrease in evaporation with increased altitude. An increasing influence of snow cover on runoff as well as evapotranspiration with altitude is obvious. The computed actual evapotranspiration and runoff were evaluated against the observed values of a weighting lysimeter and against runoff hydrographs. Copyright © 1999 John Wiley & Sons, Ltd.     

一种基于植被指数-地表温度特征空间的蒸散指数

利用遥感获取的植被指数和地表温度信息,进行地表能量和水分平衡过程研究是目前陆表过程研究的前沿。根据地表能量和水分平衡原理,对地表温度(Ts)、植被指数(VI),地表蒸散发(ET)之间的空间关系进行了分析,并基于假设条件,构建了温度植被蒸散指数(TVETI)。为验证TVETI表征地表蒸散的能力,利用环境卫星数据和SEBAL模型,对SEBAL模型中各能量通量构建的蒸散指数与TVETI进行线性回归分析,从2012年4~9月6个不同日期的确定性系数分别为:0.838、0.935、0.912、0.921、0.926、0.825, TVETI能很好的表征地表蒸散能力。通过对SEBAL模型估算的ET和TVETI估算的ET进行交叉验证发现,两者大小一致性显著, TVETI可以实现区域尺度地表蒸散发的快速估算。     

1971-2010年若尔盖湿地潜在蒸散量及地表湿润度的变化趋势

利用若尔盖、红原、玛曲3个气象站1971-2010年的地面气象观测资料,根据Penman-Monteith模型计算了若尔盖湿地的潜在蒸散量,发现若尔盖湿地年潜在蒸散量呈明显上升的趋势,上升趋势为9.1 mm/10a;若尔盖湿地潜在蒸散量在2001年出现了增大突变,2001-2010年平均潜在蒸散量比1971-2000年上升了28.6 mm;各季节潜在蒸散量均呈上升趋势,其中以秋季上升最明显,上升趋势为4.3 mm/10a。导致若尔盖湿地潜在蒸散量上升的主要气象因子是温度上升、相对湿度下降和降水量的减少,虽然日照时数减少和风速减小有利于潜在蒸散量的下降,但由于气温上升的趋势更明显,影响更大,所以若尔盖湿地潜在蒸散量呈明显的上升趋势。近40 a若尔盖湿地地表湿润度以-0.03/10a的趋势减小,其中2001-2010年比1981-1990年下降了0.11,下降十分明显;与此同时,年平均气温以0.41℃/10a的趋势上升,降水量以-13.5 mm/10a的趋势减少,虽然若尔盖湿地仍属于湿润区,但出现了明显的暖干化趋势。     

Evaluating actual evapotranspiration and impacts of groundwater storage change in the North China Plain

As a critical water discharge term in basin‐scale water balance, accurate estimation of evapotranspiration (ET) is therefore important for sustainable water resources management. The understanding of the relationship between ET and groundwater storage change can improve our knowledge on the hydrological cycle in such regions with intensive agricultural land usage. Since the 1960s, the North China Plain (NCP) has experienced groundwater depletion because of overexploitation of groundwater for agriculture and urban development. Using meteorological data from 23 stations, the complementary relationship areal evapotranspiration model is evaluated against estimates of ET derived from regional water balance in the NCP during the period 1993–2008. The discrepancies between calculated ET and that derived by basin water balance indicate seasonal and interannual variations in model parameters. The monthly actual ET variations during the period from 1960 to 2008 are investigated by the calibrated model and then are used to derive groundwater storage change. The estimated actual ET is positively correlated with precipitation, and the general higher ET than precipitation indicates the contributions of groundwater irrigation to the total water supply. The long term decreasing trend in the actual ET can be explained by declining in precipitation, sunshine duration and wind speed. Over the past ~50 years, the calculated average annual water storage change, represented by the difference between actual ET and precipitation, was approximately 36 mm, or 4.8 km³; and the cumulative groundwater storage depletion was approximately 1700 mm, or 220 km³ in the NCP. The significantly groundwater storage depletion conversely affects the seasonal and interannual variations of ET. Irrigation especially during spring cause a marked increase in seasonal ET, whereas the rapid increasing of agricultural coverage over the NCP reduces the annual ET and is the primary control factor of the strong linear relationship between actual and potential ET. Copyright © 2013 John Wiley & Sons, Ltd.     

林下植被遥感反演研究进展

林下植被在森林生态系统碳、水和营养元素的累积和循环方面有着重要作用与科学意义。多角度、高光谱和激光雷达遥感系统凭借对森林分层结构的敏感性,成为量化林下植被的重要手段。本文综述了森林林下植被的遥感反演研究进展：首先讨论了林下植被的定义,其次对当前林下植被的遥感反演现状作了深入分析,总结了多角度、高光谱和激光雷达遥感观测的森林背景的反射率、林下植被的叶面积指数、高度和覆盖度的遥感反演原理和方法。基于不同卫星观测角度下森林冠层和森林背景对总反射的贡献差异,林下反射率可通过多个角度的观测数据进行反演。此外,借助激光雷达穿透冠层直接观测林下植被的优势,总结了激光点云数据和回波波形信息反演林下植被的覆盖度和高度的方法,以及今后使用遥感技术反演的难点和获取林下植被信息的主要发展方向。     

Evapotranspiration Estimation Based on MODIS Products and Surface Energy Balance Algorithms for Land （SEBAL） Model in Sanjiang Plain, Northeast China

In this study,the Surface Energy Balance Algorithms for Land(SEBAL) model and Moderate Resolution Imaging Spectroradiometer(MODIS) products from Terra satellite were combined with meteorological data to estimate evapotranspiration(ET) over the Sanjiang Plain,Northeast China.Land cover/land use was classified by using a recursive partitioning and regression tree with MODIS Normalized Difference Vegetation Index(NDVI) time series data,which were reconstructed based on the Savitzky-Golay filtering approach.The MODIS product Quality Assessment Science Data Sets(QA-SDS) was analyzed and all scenes with valid data covering more than 75% of the Sanjiang Plain were selected for the SEBAL modeling.This provided 12 overpasses during 184-day growing season from May 1st to October 31st,2006.Daily ET estimated by the SEBAL model was misestimaed at the range of-11.29% to 27.57% compared with that measured by Eddy Covariance system(10.52% on average).The validation results show that seasonal ET from the SEBAL model is comparable to that from ground observation within 8.86% of deviation.Our results reveal that the time series daily ET of different land cover/use increases from vegetation on-going until June or July and then decreases as vegetation senesced.Seasonal ET is lower in dry farmland(average(Ave):491 mm) and paddy field(Ave:522 mm) and increases in wetlands to more than 586 mm.As expected,higher seasonal ET values are observed for the Xingkai Lake in the southeastern part of the Sanjiang Plain(Ave:823 mm),broadleaf forest(Ave:666 mm) and mixed wood(Ave:622 mm) in the southern/western Sanjiang Plain.The ET estimation with SEBAL using MODIS products can provide decision support for operational water management issues.     

Estimation of monthly reference evapotranspiration using novel hybrid machine learning approaches

ABSTRACT

In this research, five hybrid novel machine learning approaches, artificial neural network (ANN)-embedded grey wolf optimizer (ANN-GWO), multi-verse optimizer (ANN-MVO), particle swarm optimizer (ANN-PSO), whale optimization algorithm (ANN-WOA) and ant lion optimizer (ANN-ALO), were applied for modelling monthly reference evapotranspiration (ET_o) at Ranichauri (India) and Dar El Beida (Algeria) stations. The estimates yielded by hybrid machine learning models were compared against three models, Valiantzas-1, 2 and 3 based on root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), Pearson correlation coefficient (PCC) and Willmott index (WI). The results of comparison show that the ANN-GWO-1 model with five input variables (T_min, T_max, RH, U_s, R_s) provides better estimates at both study stations (RMSE = 0.0592/0.0808, NSE = 0.9972/0.9956, PCC = 0.9986/0.9978, and WI = 0.9993/0.9989). Also, the adopted modelling strategy can build a truthful expert intelligent system for estimating the monthly ET_o at study stations.     

Sensitivity of hydrological variables to climate change in the Haihe River basin,China

Using the defined sensitivity index, the sensitivity of streamflow, evapotranspiration and soil moisture to climate change was investigated in four catchments in the Haihe River basin. Climate change contained three parts: annual precipitation and temperature change and the change of the percentage of precipitation in the flood season (P_f). With satisfying monthly streamflow simulation using the variable infiltration capacity model, the sensitivity was estimated by the change of simulated hydrological variables with hypothetical climatic scenarios and observed climatic data. The results indicated that (i) the sensitivity of streamflow would increase as precipitation or P_f increased but would decrease as temperature increased; (ii) the sensitivity of evapotranspiration and soil moisture would decrease as precipitation or temperature increased, but it to P_f varied in different catchments; and (iii) hydrological variables were more sensitive to precipitation, followed by P_f, and then temperature. The nonlinear response of streamflow, evapotranspiration and soil moisture to climate change could provide a reference for water resources planning and management under future climate change scenarios in the Haihe River basin. Copyright © 2011 John Wiley & Sons, Ltd.