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1.
S.K. Sharma  K.N. Tiwari   《Journal of Hydrology》2009,374(3-4):209-222
Estimation of runoff is a prerequisite for many applications involving conservation and management of water resources. This study is undertaken in the Upper Damodar Valley Catchment (UDVC) having a drainage area of 17513.08 km2 for prediction of monthly runoff. Thirty one microwatersheds and 15 sub-watersheds were selected from a total of 716 microwatersheds in the catchment area for this study. The feasibility of using different soil attributes (particle size distribution, organic matter content and apparent density), topographic attributes (primary, secondary and compound), geomorphologic attributes (basin, relief and network indices) and vegetation attribute as Normalized Difference Vegetation Index (NDVI), on prediction of monthly runoff were explored in this study. Principal Component Analysis (PCA) was applied to minimize the data redundancy of the input variables. Ten significant input variables namely; watershed length (km), elongation ratio, bifurcation ratio, area ratio, coarse sand (%), fine sand (%), elevation (m), slope (°), profile curvature (rad/m) and NDVI were selected. The selected input variables were added in hierarchy with monthly rainfall (mm) as inputs for prediction of monthly runoff (mm) using Bootstrap based artificial neural networks (BANN). The performance of the models was tested using Spearman’s correlation coefficient (r), coefficient of efficiency (COE), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). Best performance was observed for model with monthly rainfall, slope, coarse sand, bifurcation ratio and Normalized Difference Vegetation Index (NDVI) as inputs (r = 0.925 and COE = 0.839). Increase in number of input variables did not necessarily yield better performances of the BANN models. Selection of relevant inputs and their combinations were found to be key elements in determining the performance of BANN models. Annual runoff map was generated for all the microwatersheds utilizing the weights of the best performing BANN model. This study reveals that the specific combinations of soil, topography, geomorphology and vegetation inputs can be utilized for better prediction of monthly runoff.  相似文献   

2.
Predicting and mapping high water table elevation in coastal landscapes is critical for both science application projects like inundation risk analysis and engineering projects like pond design and maintenance. Previous studies of water table mapping focused on the application of geostatistical methods, which cannot predict values beyond an observation spatial domain or generate an ideal pattern for regions with sparse measurements. In this study, we evaluated the multiple linear regression (MLR) and support vector machine (SVM) techniques for high water table prediction and mapping using fine spatial resolution lidar-derived Digital Elevation Model (DEM) data, and designed an application protocol of these two techniques for high water table mapping in a coastal landscape where groundwater, tide, and surface water are related. Testing results showed that SVM largely improved the high water table prediction with a mean absolute error (MAE) of 1.22 feet and root mean square error (RMSE) of 2.22 feet compared to the application of the ordinary Kriging method which could not generate a reasonable water table. MLR was also promising with a MAE of around 2 feet and RMSE of around 3 feet. The study suggests that both MLR and SVM are valuable alternatives to estimate high water table elevation in Florida. Fine resolution lidar DEMs are beneficial for high water table prediction and mapping.  相似文献   

3.
The recent transformation of wetlands into farmland in East Africa is accelerating due to growing food-demand, land shortages, and an increasing unpredictability of climatic conditions for crop production in uplands. However, the conversion of pristine wetlands into sites of production may alter hydrological attributes with negative effects on production potential. Particularly the amount and the dynamics of plant available soil moisture in the rooting zone of crops determine to a large extent the agricultural production potential of wetlands. Various methods exist to assess soil moisture dynamics with Frequency Domain Reflectometry (FDR) being among the most prominent. However, the suitability of FDR sensors for assessing plant available soil moisture has to date not been confirmed for wetland soils in the region. We monitored the seasonal and spatial dynamics of water availability for crop growth in an inland valley wetland of the Kenyan highlands using a FDR sensor which was site-specifically calibrated. Access tubes were installed within different wetland use types and hydrological situations along valley transects and soil properties affecting soil moisture (organic C, texture, and bulk density) were investigated. There was little variation in soil attributes between physical positions in the valley, and also between topsoil and subsoil attributes with the exception of organic C contents. With a root mean squared error of 0.073 m3/m3, the developed calibration function of the FDR sensor allows for reasonably accurate soil moisture prediction for both within-site comparisons and the monitoring of temporal soil moisture variations. Applying the calibration equation to a time series of profile probe readings over a period of one year illustrated not only the temporal variation of soil moisture, but also effects of land use.  相似文献   

4.
Spatiotemporal modeling of relative risk of dengue disease provides useful risk maps for surveillance and forecasting. The objective of the study was to generate smoothed estimates of relative risk applying hierarchical Bayesian spatiotemporal models, including covariates derived from satellite images containing land surface temperature (LST) and normalized difference vegetation index, for the period January 2009–December 2015, in a medium–sized Colombian city. Our models are based on the spatiotemporal interaction modeling framework of relative risk, where the interaction effects are unstructured, temporal, spatial or inseparable, at a small spatial and temporal scales. We fitted the models using Markov chain MonteCarlo Simulations, selecting the best model using leave-one-out cross-validation and widely applicable information criteria. Our best model was the inseparable spatiotemporal interaction-effects plus LST with constant coefficient model. We found a weak, positive association between LST and cases of dengue. We discussed the strengths and weaknesses of our spatiotemporal models given the spatial and temporal resolution selected in the study.  相似文献   

5.
Reliable modeling of river sediments transport is important as it is a defining factor of the economic viability of dams, the durability of hydroelectric-equipment, river susceptibility to pollution, suitability for navigation, and potential for aesthetics and fish habitat. The capability of a new machine learning model, fuzzy c-means based neuro-fuzzy system calibrated using the hybrid particle swarm optimization-gravitational search algorithm（ANFIS-FCM-PSOGSA） in improving the estimation accur...  相似文献   

6.
The interaction effects of different applied ratios of a hydrophilic polymer (Superab A200) (0, 0.2, 0.6% w/w) under various soil salinity levels (initial salinity, 4 and 8 ms/cm) were evaluated on available water content (AWC), biomass, and water use efficiency for corn grown in loamy sand and sandy clay loam soils. The results showed that the highest AWC was measured at the lowest soil salinity. The application of 0.6% w/w of the polymer at the lowest salinity level increased the AWC by 2.2 and 1.2 times greater than those of control in the loamy sand and sandy clay loam soils, respectively. The analysis of variance of data showed that the effect of salinity was significant on biomass and water use efficiency of corn in the loamy sand and sandy clay loam soils. The highest amounts of these traits were measured in soils with the lowest salinity level. Application of polymer at the rate of 0.6% in the loamy sand soil and at the rate of 0.2% in the sandy clay loam soil resulted in the highest aerial and root biomass and water use efficiency for corn. At these polymer rates the amounts of water use efficiency for corn were 2.6 and 1.7 times greater than those of control in the loamy sand and sandy clay loam soils, respectively. Thus, the use of hydrophilic polymer in soils especially in the sandy soils increases soil water holding capacity, yield, and water use efficiency of plant. On the other hand, decreases the negative effect of soil salinity on plant and helps for irrigation projects to succeed in arid and semi‐arid areas.  相似文献   

7.
Land surface soil moisture (SSM) is an important variable for hydrological, ecological, and meteorological applications. A multi‐linear model has recently been proposed to determine the SSM content from the combined diurnal evolution of both land surface temperature (LST) and net surface shortwave radiation (NSSR) with the parameters TN (the LST mid‐morning rising rate divided by the NSSR rising rate during the same period) and td (the time of daily maximum temperature). However, in addition to the problem that all the coefficients of the multi‐linear model depend on the atmospheric conditions, the model also suffers from the problems of the nonlinearity of TN as a function of the SSM content and the uncertainty of determining the td from the diurnal evolution of the LST. To address these problems, a modified multi‐linear model was developed using the logarithm of TN and normalizing td by the mid‐morning temperature difference instead of using the TN and td. Except for the constant term, the coefficients of all other variables in the modified multi‐linear model proved to be independent of the atmospheric conditions. Using the relevant simulation data, results from the modified multi‐linear model show that the SSM content can be determined with a root mean square error (RMSE) of 0.030m3/m3, provided that the constant term is known or estimated day to day. The validation of the model was conducted using the field measurements at the Langfang site in 2008 in China. A higher correlation is achieved (coefficient of determination: R2 = 0.624, RMSE = 0.107m3/m3) between the measured SSM content and the SSM content estimated using the modified multi‐linear model with the coefficients determined from the simulation data. Another experiment is also conducted to estimate the SSM content using the modified model with the constant term calibrated each day by one‐spot measurements at the site. The estimation result has a relatively larger error (RMSE = 0.125m3/m3). Additionally, the uncertainty of the determination of the coefficients is analysed using the field measurements, and the results indicate that the SSM content obtained using the modified model accurately characterizes the surface soil moisture condition. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

8.
Volcanogenic contamination of irrigation water, caused by effluent from the hyperacid Ijen crater lake, has severely affected the properties of agricultural soils in East Java, Indonesia. From a comparison of acidified topsoil with subsoil and with top- and subsoil in a reference area, we identified processes responsible for changes in soil and soil solution chemistry induced by acid irrigation water, with emphasis on the nutrients Ca, Mg, Fe, and Mn, and on Al, which may become phytotoxic under acid conditions in soils. Compositional data for bulk soil composition and selective extractions with 1 M KCl and 0.2 M acid ammonium oxalate are used in a mass balance approach to specify element fluxes, including uptake by rice plants. The results show that input via irrigation water has produced an increase in the total aluminum content in the affected topsoil, which is of the same order of magnitude as the increase in labile Al. High bioavailability of Al, as reflected by concentrations in KCl extracts, is consistent with elevated concentrations observed in rice plants. In contrast, and despite the high input via irrigation water, Ca and Mg concentrations have decreased in all measured soil fractions through dissolution of amorphous phases and minerals, and through competition of Al for adsorption sites on the exchange complex and plant roots. Strong leaching is also evident for Fe and especially Mn. In terms of the overall mass balance of the topsoil, plant uptake of Al, Ca, Fe, Mg and Mn is negligible. If the use of acid irrigation would be stopped and the soil pH were to increase to values above 4.5, the observed phytotoxicity of Al will be halted. However, crops may then become fully dependent on the input from irrigation water or fertilizer for essential elements, due to the previous removal from the topsoil through leaching.  相似文献   

9.
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10.
Weekly interflow and permeability data were obtained for 15 sites in two field plots in North Yorkshire. Both plots are similar in terms of lithology, slope, micro-relief, climate and soil type, one being dominated by rough pasture grasses and the second by bracken. One factor which explained 75 per cent of the variation in interflow was the difference between topsoil and subsoil permeabilities, the former always being the greater. This permeability difference is discussed in terms of soil texture, porosity and plant-rooting systems. Textural contrasts are considered insufficient to cause the large-scale variations in permeability observed throughout the year. Being a fixed variable, texture cannot influence a characteristic which varies from one week to the next. Contrasts in total porosity between topsoil and subsoil also effected no discernible influence on measured permeability differences, although measures of association increased as smaller pores were excluded from the analysis. Utilizing only those pores drained at 20 cm of water tension, highly significant correlations were established. In the plot dominated by bracken, greater ‘lateral permeabilities’ are produced by well-developed systems of Pteridium rhizomes. As the advancing front of such rhizomes extends forwards at quoted rates of up to 45 cm/yr, the rear portions decay, leaving horizontal ‘tubes’ in the soil. Recognized omissions from this analysis are the effects of soil fauna and desiccation fissures.  相似文献   

11.
新疆艾比湖湿地土壤水盐空间变异性分析   总被引：2，自引：0，他引：2  
赵明亮  李艳红  李发东 《湖泊科学》2016,28(6):1328-1337
为揭示艾比湖湿地土壤退化程度空间分布特征,在离艾比湖湖滨5~15 km,绕湖一周160 km范围内,以湖心质点为中心,将艾比湖划分为东北、东南、西南、西北4个区域,采用传统统计学和地统计学相结合的方法对表层(0~20 cm)土壤盐分、含水量与p H的空间分异特征进行研究.结果表明:绕湖一周不同区域的土壤盐分均属中等变异强度;土壤含水量在西北部属强变异性,而东北、东南和西南部均属中等变异强度;土壤p H在不同区域内均属弱变异强度.绕湖一周除西北部土壤盐分的半方差理论模型较符合球状模型外,其它区域土壤盐分、含水量和p H均符合高斯模型;受结构性因素影响,不同区域土壤盐分、含水量和p H均具有较强的空间相关性;西南部土壤盐分、含水量和p H的Moran's I系数比其它区域的波动大,表明空间相关性较强.艾比湖湿地常年大风、干旱、缺水及沙化盐化的自然因素与引水围堰、种植耐盐碱植物的人为活动造成了采样区表层土壤盐分、含水量和p H的空间分布多呈现不规则条带状格局.艾比湖湿地土壤以盐土为主,重度盐化土次之,土壤盐渍化日益严重.  相似文献   

12.
According to the soil particles data, DEM elevation, slope, distance to river, distance along river, land use, and soil type for 95 typical sampling profiles along the Tarim river mainstream, the generalized linear models (GLMs) and generalized additive models (GAMs) are used to identify the spatial variability pattern of soil particles on the watershed scale and associated driving forces. The results show that the drainage basin sand, silt and clay content along the Tarim river mainstream all present moderate variability. The spatial pattern of soil particles is mainly subjected to the influence of gravity, hydrodynamic force, soil parent material and human activities. Modeling results show that the GAMs performs better than GLMs in regard to the explanation of total deviation. The contribution degree of GAMs for total deviation is 44.19 % (sand), 38.68 % (silt) and 37.46 % (clay). This major influence factors of soil particles distribution are land use, hydrodynamic force, soil type and terrain. The study has provided a way to explore aspects of spatial heterogeneity and to discover how spatial pattern controls the distribution of the soil particles.  相似文献   

13.
The crucial role of root-zone soil moisture is widely recognized in land–atmosphere interaction, with direct practical use in hydrology, agriculture and meteorology. But it is difficult to estimate the root-zone soil moisture accurately because of its space-time variability and its nonlinear relationship with surface soil moisture. Typically, direct satellite observations at the surface are extended to estimate the root-zone soil moisture through data assimilation. But the results suffer from low spatial resolution of the satellite observation. While advances have been made recently to downscale the satellite soil moisture from Soil Moisture and Ocean Salinity (SMOS) mission using methods such as the Disaggregation based on Physical And Theoretical scale Change (DisPATCh), the assimilation of such data into high spatial resolution land surface models has not been examined to estimate the root-zone soil moisture. Consequently, this study assimilates the 1-km DisPATCh surface soil moisture into the Joint UK Land Environment Simulator (JULES) to better estimate the root-zone soil moisture. The assimilation is demonstrated using the advanced Evolutionary Data Assimilation (EDA) procedure for the Yanco area in south eastern Australia. When evaluated using in-situ OzNet soil moisture, the open loop was found to be 95% as accurate as the updated output, with the updated estimate improving the DisPATCh data by 14%, all based on the root mean square error (RMSE). Evaluation of the root-zone soil moisture with in-situ OzNet data found the updated output to improve the open loop estimate by 34% for the 0–30 cm soil depth, 59% for the 30–60 cm soil depth, and 63% for the 60–90 cm soil depth, based on RMSE. The increased performance of the updated output over the open loop estimate is associated with (i) consistent estimation accuracy across the three soil depths for the updated output, and (ii) the deterioration of the open loop output for deeper soil depths. Thus, the findings point to a combined positive impact from the DisPATCh data and the EDA procedure, which together provide an improved soil moisture with consistent accuracy both at the surface and at the root-zone.  相似文献   

14.
木本与草本是植物存在的两种主要生活型,生态功能差异明显,尤其在植物被周期性洪水淹没的湿地生态系统中.为此,以洞庭湖湿地二门闸、五门闸、藕池河口、白沙大桥4个研究点的原生柳属木本植被与薹草属草本植被为研究对象,通过对枯水期土壤理化性质与汛期水流速度、水环境的对比监测,揭示两者生态防护功能的差异.对土壤粒径组成而言,在二门闸与白沙大桥2个研究点,木本与草本植物群落土壤样本之间无显著差异;而在五门闸与藕池河,与草本植物相比,木本植物导致土壤上层(0~30 cm)与下层(60~90 cm)粉粒含量降低,砂粒含量增加,中层(30~60 cm)黏粒与粉粒含量增加,砂粒含量降低.对土壤化学性质而言,木本植物总体上导致土壤有机质与全氮含量升高,而对全磷与全钾含量无显著影响.与草本植物相比,木本植物能显著减缓水流速度,提高水体氧化还原电位与溶解氧浓度,而对水温与p H值无明显影响.可见,洞庭湖湿地木本与草本植物生活型的差异,是导致二者土壤与水环境特征差别的主要原因,与草本植物相比,木本植物具有更强的生态防护功能.  相似文献   

15.
针对砂土液化判别中影响因素与砂土状态间映射关系的不确定性及模糊性等问题,在邻域粗糙集(Neighborhood Rough Set, NRS)因素约简的基础上,利用多策略融合的改进麻雀搜索算法(Improved Sparrow Search Algorithm, ISSA)优化支持向量机(Support Vector Machine, SVM)参数C和g,构建了SVM砂土液化判别模型。以吉林松原地区的42组实例作为总体样本集,其中35组作为训练集,另外7组作为测试集,利用邻域粗糙集对9个影响因素约简得到4个因素,然后输入ISSA-SVM模型进行预测,并进行了约简得到的因素敏感性分析。结果表明：因素约简剔除了冗余属性,降低了模型复杂度;ISSA算法具有极强的探索性、收敛性和局部逃逸能力;相比于其他模型,NRS-ISSA-SVM砂土液化判别模型精度更高,泛化能力更强;建议要判别砂土的液化状态,需要准确查明水位埋深、地震烈度、标准贯入击数,非液化土层厚度这4个因素,尤其是前三个因素。通过易获取的影响因素建立NRS-ISSA-SVM砂土液化判别模型,不仅可准确地判断该区域其余未知点的砂土状态,...  相似文献   

16.
The prediction of PM2.5 concentrations with high spatiotemporal resolution has been suggested as a potential method for data collection to assess the health effects of exposure. This work predicted the weekly average PM2.5 concentrations in the Yangtze River Delta, China, by using a spatio-temporal model. Integrating land use data, including the areas of cultivated land, construction land, and forest land, and meteorological data, including precipitation, air pressure, relative humidity, temperature, and wind speed, we used the model to estimate the weekly average PM2.5 concentrations. We validated the estimated effects by using the cross-validated R2 and Root mean square error (RMSE); the results showed that the model performed well in capturing the spatiotemporal variability of PM2.5 concentration, with a reasonably large R2 of 0.86 and a small RMSE of 8.15 (μg/m3). In addition, the predicted values covered 94% of the observed data at the 95% confidence interval. This work provided a dataset of PM2.5 concentration predictions with a spatiotemporal resolution of 3 km × week, which would contribute to accurately assessing the potential health effects of air pollution.  相似文献   

17.
This study investigates the properties of the diurnal cycle of microwave brightness temperatures (TB), namely the phase and the amplitude, and their variability in time and space over the globe to infer information on key land surface parameters like changes in soil texture spatial distribution, soil moisture conditions, and vegetation density. The phase corresponds to the lag between Land Surface Temperature (LST) and TB diurnal cycles. The amplitude is determined as the difference between the maximum and the minimum of TB diurnal cycle. The diurnal cycle of TB was constructed using observations from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) and the Special Sensor Microwave/Imager (SSM/I). The latter offer a series of sensors, namely, F13, F14, and F15 that were used in this study for a higher temporal coverage and more accurate diurnal cycle determination. LST estimates, which are available every 3 h from the International Satellite Cloud Climatology Project (ISCCP) database were used to build the LST diurnal cycle. ISCCP LST data is an infrared-based temperature with almost no penetration and is the representative of top skin temperature.The analyses of the diurnal cycles showed that the diurnal amplitude of TB decreases as the vegetation density increases, especially in the case of low frequencies which penetrate deeper into the canopy which makes them more sensitive to changes in vegetation density. The interannual variations of TB diurnal amplitudes were also in agreement with the seasonality of the vegetation cover. Over desert and rain forest regions where surface conditions do not vary significantly throughout the year, the changes in diurnal amplitudes were the lowest. A relationship between phase and amplitude values was established. It was found that the amplitude of TB diurnal cycle decreases when the phase lag increases. The spatial distribution of the determined diurnal properties, namely, phase and amplitude of TB, showed an agreement with lithology maps in desert areas. Lower TB amplitudes were observed over regions with loose siliceous rocks. Phase lag values between 1.5 and 3 h corresponded to 83% of the class “loose siliceous rocks” in the Sahara Desert, which corroborates the potential of using the diurnal properties of TB as an indicator of land surface parameters.  相似文献   

18.
Agricultural land management requires strategies to reduce impacts on soil and water resources while maintaining food production. Models that capture the effects of agricultural and conservation practices on soil erosion and sediment delivery can help to address this challenge. Historic records of climatic variability and agricultural change over the last century also offer valuable information for establishing extended baselines against which to evaluate management scenarios. Here, we present an approach that combines centennial‐scale reconstructions of climate and agricultural land cover with modelling across four lake catchments in the UK where radiometric dating provides a record of lake sedimentation. We compare simulations using MMF‐TWI, a catchment‐scale model developed for humid agricultural landscapes that incorporates representation of seasonal variability in vegetation cover, soil water balance, runoff and sediment contributing areas. MMF‐TWI produced mean annual sediment exports within 9–20% of sediment core‐based records without calibration and using guide parameter values to represent vegetation cover. Simulations of land management scenarios compare upland afforestation and lowland field‐scale conservation measures to reconstructed historic baselines. Oak woodland versus conifer afforestation showed similar reductions in mean annual surface runoff (8–16%) compared to current moorland vegetation but a larger reduction in sediment exports (26–46 versus 4–30%). Riparian woodland buffers reduced upland sediment yields by 15–41%, depending on understorey cover levels, but had only minor effect on surface runoff. Planting of winter cover crops in the lowland arable catchment halved historic sediment exports. Permanent grass margins applied to sets of arable fields across 15% or more of the catchment led to further significant reduction in exports. Our findings show the potential for reducing sediment delivery at the catchment scale with land management interventions. We also demonstrate how MMF‐TWI can support hydrologically‐informed decision making to better target conservation measures in humid agricultural environments. Copyright © 2018 John Wiley & Sons, Ltd.  相似文献   

19.
There has, in recent years, been an increasing interest in developing nutrient load mitigation measures focussing on tile drains. To plan the location of such tile drain measures, it is important to know where in the landscape drain flow is generated and to understand the key factors governing drain flow dynamics. In the present study, we test two approaches to assess spatial patterns in drain flow generation and thereby assess the importance of including geological information. The approaches are the widely used topographical wetness index (TWI), based solely on elevation data, and hydrological models that include the subsurface geology. We set‐up an ensemble of 20 hydrological models based on 20 stochastically generated geological models to predict drain flow dynamics in the clay till Norsminde catchment in Denmark and test the results against TWI. We find that the hydrological models predict observed daily drain flow reasonably well. High drain flow volumes were found in stream valleys and in wetlands and lower drain flow volumes in the more hilly parts of the catchment. In spite of the apparent connection to the landscape, there was no statistically significant correlation between TWI and drain flow at grid scale (100 × 100 m). TWI was therefore not found to be a sufficient index on its own to assess where drain flow is generated, especially in the highlands of the catchment. The geology below 3 m was found to have a large impact on the drain flow, and correlations between sand percentage in the subsurface geology and drain flow volume were found to be statistically significant. Geological uncertainty therefore give rise to uncertainty on simulated drain flow, and this uncertainty was found to be high at the model grid scale but decreasing with increasing scale.  相似文献   

20.
A comparison between half‐hourly and daily measured and computed evapotranspiration (ET) using three models of different complexity, namely, the Priestley–Taylor (P‐T), the reference Penman–Monteith (P‐M) and the Common Land Model (CLM), was conducted using three AmeriFlux sites under different land cover and climate conditions (i.e. arid grassland, temperate forest and subhumid cropland). Using the reference P‐M model with a semiempirical soil moisture function to adjust for water‐limiting conditions yielded ET estimates in reasonable agreement with the observations [root mean square error (RMSE) of 64–87 W m?2 for half‐hourly and RMSE of 0.5–1.9 mm day?1 for daily] and similar to the complex Common Land Model (RMSE of 60–94 W m?2 for half‐hourly and RMSE of 0.4–2.1 mm day?1 for daily) at the grassland and cropland sites. However, the semiempirical soil moisture function was not applicable particularly for the P‐T model at the forest site, suggesting that adjustments to key model variables may be required when applied to diverse land covers. On the other hand, under certain land cover/environmental conditions, the use of microwave‐derived soil moisture information was found to be a reliable metric of regional moisture conditions to adjust simple ET models for water‐limited cases. Further studies are needed to evaluate the utility of the simplified methods for different landscapes. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

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