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1.
Crop canopies and residues have been shown to intercept a significant amount of rainfall. However, rainfall or irrigation interception by crops and residues has often been overlooked in hydrologic modelling. Crop canopy interception is controlled by canopy density and rainfall intensity and duration. Crop residue interception is a function of crop residue type, residue density and cover, and rainfall intensity and duration. We account for these controlling factors and present a model for both interception components based on Merriam's approach. The modified Merriam model and the current modelling approaches were examined and compared with two field studies and one laboratory study. The Merriam model is shown to agree well with measurements and was implemented within the Agricultural Research Service's Root Zone Water Quality Model (RZWQM). Using this enhanced version of RZWQM, three simulation studies were performed to examine the quantitative effects of rainfall interception by corn and wheat canopies and residues on soil hydrological components. Study I consisted of 10 separate hypothetical growing seasons (1991–2000) for canopy effects and 10 separate non‐growing seasons (1991–2000) for residue effects for eastern Colorado conditions. For actual management practices in a no‐till wheat–corn–fallow cropping sequence at Akron, Colorado (study II), a continuous 10‐year RZWQM simulation was performed to examine the cumulative changes on water balance components and crop growth caused by canopy and residue rainfall interception. Finally, to examine a higher precipitation environment, a hypothetical, no‐till wheat–corn–fallow rotation scenario at Corvallis, Oregon, was simulated (study III). For all studies, interception was shown to decrease infiltration, runoff, evapotranspiration from soil, deep seepage of water and chemical transport, macropore flow, leaf area index, and crop/grain yield. Because interception decreased both infiltration and soil evapotranspiration, no significant change in soil water storage was simulated. Nonetheless, these findings and the new interception models are significant new contributions for hydrologists. Published in 2006 John Wiley & Sons, Ltd.  相似文献   

2.
卫星遥感数据评估黄土高原陆面干湿程度研究   总被引:1,自引:1,他引:0       下载免费PDF全文
康悦  文军  张堂堂  田辉  陈昊 《地球物理学报》2014,57(8):2473-2483
卫星遥感数据具有估算时空尺度上地表参量的优势,在陆地环境状况评估和监测等方面有很大的应用潜力.本文利用美国地球观测系统卫星搭载中等分辨率成像光谱仪(EOS/MODIS)在黄土高原2002-2010年期间获取的每16天归一化植被指数(NDVI)和每日地表温度(LST)数据,分析了黄土高原地区LST-NDVI空间的基本特征.结果发现:当研究区域足够大且遥感数据时间序列足够长时,LST-NDVI空间中(NDVI,LST)散点并非呈三角形或梯形分布.为了能够利用EOS/MODIS的NDVI和LST数据正确地评估陆面的干湿状况,本文给出了利用数据集合法确定LST-NDVI空间中干边和湿边的数值,即在LST-NDVI空间中,利用NDVI等值区间内LST最大值和最小值的集合代表干边和湿边的数值,并进一步证明了在LST-NDVI空间中干边和湿边数值并非呈线性关系.在分析LST-NDVI空间特征的基础上,通过构建地表温度-植被干旱指数(TVDI),探讨其在评估黄土高原地区陆面的干湿状况的应用潜力.结果表明:由TVDI距平表征的陆面的干湿程度与局地降水距平有很好的关联性,二者在时空分布上有较好的对应关系.在我国陇东黄土高原塬区,TDVI数值与地面观测的表层土壤湿度有很好的相关性,相关系数在0.67以上,并通过显著性为1%的检验.由此说明:如果合理选取干边和湿边的数值,TDVI可应用于区域陆面干湿程度的客观评估.  相似文献   

3.
Information on water balance components such as evapotranspiration and groundwater recharge are crucial for water management. Due to differences in physical conditions, but also due to limited budgets, there is not one universal best practice, but a wide range of different methods with specific advantages and disadvantages. In this study, we propose an approach to quantify actual evapotranspiration, groundwater recharge and water inflow, i.e. precipitation and irrigation, that considers the specific conditions of irrigated agriculture in warm, arid environments. This approach does not require direct measurements of precipitation or irrigation quantities and is therefore suitable for sites with an uncertain data basis. For this purpose, we combine soil moisture and energy balance monitoring, remote sensing data analysis and numerical modelling using Hydrus. Energy balance data and routine weather data serve to estimate ET0. Surface reflectance data from satellite images (Sentinel-2) are used to derive leaf area indices, which help to partition ET0 into energy limited evaporation and transpiration. Subsequently, first approximations of water inflow are derived based on observed soil moisture changes. These inflow estimates are used in a series of forward simulations that produce initial estimates of drainage and ETact, which in turn help improve the estimate of water inflow. Finally, the improved inflow estimates are incorporated into the model and then a parameter optimization is performed using the observed soil moisture as the reference figure. Forward simulations with calibrated soil parameters result in final estimates for ETact and groundwater recharge. The presented method is applied to an agricultural test site with a crop rotation of cotton and wheat in Punjab, Pakistan. The final model results, with an RMSE of 2.2% in volumetric water content, suggest a cumulative ETact and groundwater recharge of 769 and 297 mm over a period of 281 days, respectively. The total estimated water inflow accounts for 946 mm, of which 77% originates from irrigation.  相似文献   

4.
Songhao Shang 《水文研究》2012,26(22):3338-3343
Calculation of actual crop evapotranspiration under soil water stress conditions is crucial for hydrological modeling and irrigation water management. Results of actual evapotranspiration depend on the estimation of water stress coefficient from soil water storage in the root zone, which varies with numerical methods and time step used. During soil water depletion periods without irrigation or precipitation, the actual crop evapotranspiration can be calculated by an analytical method and various numerical methods. We compared the results from several commonly used numerical methods, including the explicit, implicit and modified Euler methods, the midpoint method, and the Heun's third‐order method, with results of the analytical method as the bench mark. Results indicate that relative errors of actual crop evapotranspiration calculated with numerical methods in one time step are independent of the initial soil water storage in the range of soil water stress. Absolute values of relative error decrease with the order of numerical methods. They also decrease with the number of time step, which can ensure the numerical stability of successive simulation of soil water balance. Considering the calculation complexity and calculation errors caused by numerical approximation for different time step and maximum crop evapotranspiration, the explicit Euler method is recommended for the time step of 1 day (d) or 2 d for maximum crop evapotranspiration less than 5 mm/d, the midpoint method or the modified Euler method for the time step of up to one week or 10 d for maximum crop evapotranspiration less than 5 mm/d, and the Heun's third‐order method for the time step of up to 15 d. Copyright © 2011 John Wiley & Sons, Ltd.  相似文献   

5.
Urban green spaces (UGS), like most managed land covers, are getting progressively affected by water scarcity and drought. Preserving, restoring and expanding UGS require sustainable management of green and blue water resources to fulfil evapotranspiration (ET) demand for green plant cover. The heterogeneity of UGS with high variation in their microclimates and irrigation practices builds up the complexity of ET estimation. In oversized UGS, areas too large to be measured with in situ ET methods, remote sensing (RS) approaches of ET measurement have the potential to estimate the actual ET. Often in situ approaches are not feasible or too expensive. We studied the effects of spatial resolution using different satellite images, with high-, medium- and coarse-spatial resolutions, on the greenness and ET of UGS using Vegetation Indices (VIs) and VI-based ET, over a 780-ha urban park in Adelaide, Australia. We validated ET with the ground-based ET method of Soil Water Balance. Three sets of imagery from WorldView2, Landsat and MODIS, and three VIs including the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI) and Enhanced Vegetation Index 2 (EVI2), were used to assess long-term changes of VIs and ET calculated from the different imagery acquired for this study (2011–2018). We found high correspondence between ET-MODIS and ET-Landsat (R2 > 0.99 for all VIs). Landsat-VIs captured the seasonal changes of greenness better than MODIS-VIs. We used artificial neural network (ANN) to relate the RS-ET and ground data, and ET-MODIS (EVI2) showed the highest correlation (R2 = 0.95 and MSE =0.01 for validation). We found a strong relationship between RS-ET and in situ measurements, even though it was not explicable by simple regressions; black box models helped us to explore their correlation. The methodology used in this research makes a strong case for the value of remote sensing in estimating and managing ET of green spaces in water-limited cities.  相似文献   

6.
杜明  赵鹏 《地球》2012,(11):104-109
干旱是影响社会发展和农业生产的重要因素之一。本文基于EOS/MODIS卫星遥感资料,选取江西省2001-2006年的NDVI时间序列数据,分析了NDVI对干旱的响应规律。计算了NDVI与气温、降水之间的关系。并提取植被状态指数(VCI),分析VCI与气温距平、降水距平的空间分布规律。结果表明:2003年江西夏季旱灾以高温少雨天气为主。这一时期的NDVI数值明显低于其他年份同一时期的NDVI值。气温温度越高,NDVI值越大;日照时数时间越长,NDVI值越大;降水量越高,NDVI值越大;降水距平百分率越高,VCI值越高;平均温度距平越小,VCI值越高。说明气候因素对NDVI指数和VCI指数有很大影响。研究表明,基于MODIS的植被指数可以反映旱灾的时空分布规律。  相似文献   

7.
L. Li  Q. Yu  Z. Su  C. van der Tol 《水文研究》2009,23(5):665-674
Estimation of evapotranspiration from a crop field is of great importance for detecting crop water status and proper irrigation scheduling. The Penman–Monteith equation is widely viewed as the best method to estimate evapotranspiration but it requires canopy resistance, which is very difficult to determine in practice. This paper presents a simple method simplified from the Penman–Monteith equation for estimating canopy temperature (Tc). The proposed method is a biophysically‐sound extended version of that proposed by Todorovic. The estimated canopy temperature is used to calculate sensible heat flux, and then latent heat flux is calculated as the residual of the surface energy balance. An eddy covariance (EC) system and an infrared thermometer (IRT) were installed in an irrigated winter wheat field on the North China Plain in 2004 and 2005, to measure Tc, and sensible and latent heat fluxes were used to test the modified Todorovic model (MTD). The results indicate that the original Todorovic model (TD) severely underestimates Tc and sensible heat flux, and hence severely overestimates the latent heat flux. However, the MTD model has good capability for estimating Tc, and gives acceptable results for latent heat flux at both half‐hourly and daily scales. The MTD model results also agreed well with the evapotranspiration calculated from the measured Tc. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

8.
We simulated the effects of irrigation on groundwater flow dynamics in the North China Plain by coupling the NIES Integrated Catchment‐based Ecohydrology (NICE) model with DSSAT‐wheat and DSSAT‐maize, two agricultural models. This combined model (NICE‐AGR) was applied to the Hai River catchment and the lower reach of the Yellow River (530 km wide by 840 km long) at a resolution of 5 km. It reproduced excellently the soil moisture, evapotranspiration and crop production of summer maize and winter wheat, correctly estimating crop water use. So, the spatial distribution of crop water use was reasonably estimated at daily steps in the simulation area. In particular, NICE‐AGR reproduced groundwater levels better than the use of statistical water use data. This indicates that NICE‐AGR does not need detailed statistical data on water use, making it very powerful for evaluating and estimating the water dynamics of catchments with little statistical data on seasonal water use. Furthermore, the simulation reproduced the spatial distribution of groundwater level in 1987 and 1988 in the Hebei Plain, showing a major reduction of groundwater level due mainly to overpumping for irrigation. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

9.
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   

10.
Jing Fu  Jun Niu  Bellie Sivakumar 《水文研究》2018,32(12):1814-1827
Vegetation cover plays an important role in linking the atmosphere, water, and land and is deemed as a key indicator in the terrestrial ecological system. Therefore, it is of great importance to monitor vegetation dynamics and understand the mechanisms of vegetation change, including that driven by climate change. This study examines (a) the evolution of vegetation dynamics over the Heihe River Basin in the typical arid zone in north‐western China using nonparametric Mann–Kendall test and Thiel Sen's slope; (b) the relationships between remotely sensed vegetation indices (normalized difference vegetation index [NDVI] and enhanced vegetation index [EVI]) and hydroclimatic variables based on correlation analysis; and (c) the prediction of vegetation anomalies using a multiple linear regression model. For the analysis, the Moderate Resolution Imaging Spectroradiometer NDVI/EVI product and the gridded daily meteorological data at a spatial resolution of 0.125° over the period 2001–2010 are considered. The results indicate that vegetation cover improved over a large proportion during 2001–2010, with a significant trend towards warm and wet, characterized by an increase in average annual temperature and precipitation by 0.042 °C/year and 5.8 mm/year, respectively. We test the feasibility of NDVI and EVI in quantifying the responses of vegetation anomaly to climate change and develop a statistical model to predict vegetation dynamics in the basin. The NDVI‐based model is found to be more reliable than the EVI‐based model, partly due to the vegetation characteristics and geomorphologic properties of the study region. The proposed model performs well when there is no lag time between meteorological factors and vegetation indices for grassland and cropland, whereas 1‐month lead time prediction is found to be best for forest. The soil water content is introduced as an extra explanatory variable, which effectively improves the prediction accuracy for different land use types. In general, the predictive ability of the proposed model is stable and satisfactory, and the model can provide useful early warning information for regional water resources management under changing climate.  相似文献   

11.
Land surface models are typically constrained by one or a few observed variables, while assuming that the internal water and energy partitioning is sensitive to those observed variables and realistic enough to simulate unobserved variables. To verify these assumptions, in situ soil climate analysis network (SCAN) observations in the Lower Mississippi Basin (2002–2008) are analysed to quantify water and energy budget components and they are compared to Community Land Model (CLM3·5) simulations. The local soil texture is identified as a major indicator for water storage characteristics and the Normalized Difference Vegetation Index shows potential as a drought indicator in summer months. Both observations and simulations indicate a regime where, except in some summer months, evapotranspiration controls soil moisture. CLM simulations with different soil texture assignments show discharge sensitivity to soil moisture, but almost no impact on evapotranspiration and other energy balance components. The observed and simulated water budgets show a similar partitioning. However, the SCAN observed water balance does not close because of precipitation measurement errors, unobserved irrigation, lack of specific storage change measurements and errors in the computed actual evapotranspiration. The simulated heat flux partitioning differs from that ‘observed’, with a larger (resp. smaller) fraction of net radiation being used by latent (resp. sensible) heat flux, and unobserved freeze and thaw events. The comparison between observations and model simulations suggests that a consistent observation collection for multiple variables would be needed to constrain and improve the full set of land surface variable estimates. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

12.
Jing Wang  Qiang Yu  Xuhui Lee 《水文研究》2007,21(18):2474-2492
Understanding the exchange processes of energy and carbon dioxide (CO2) in the soil–vegetation–atmosphere system is important for assessing the role of the terrestrial ecosystem in the global water and carbon cycle and in climate change. We present a soil–vegetation–atmosphere integrated model (ChinaAgrosys) for simulating energy, water and CO2 fluxes, crop growth and development, with ample supply of nutrients and in the absence of pests, diseases and weed damage. Furthermore, we test the hypotheses of whether there is any significant difference between simulations over different time steps. CO2, water and heat fluxes were estimated by the improving parameterization method of the coupled photosynthesis–stomatal conductance–transpiration model. Soil water evaporation and plant transpiration were calculated using a multilayer water and heat‐transfer model. Field experiments were conducted in the Yucheng Integrated Agricultural Experimental Station on the North China Plain. Daily weather and crop growth variables were observed during 1998–2001, and hourly weather variables and water and heat fluxes were measured using the eddy covariance method during 2002–2003. The results showed that the model could effectively simulate diurnal and seasonal changes of net radiation, sensible and latent heat flux, soil heat flux and CO2 fluxes. The processes of evapotranspiration, soil temperature and leaf area index agree well with the measured values. Midday depression of canopy photosynthesis could be simulated by assessing the diurnal change in canopy water potential. Moreover, the comparisons of simulated daily evapotranspiration and net ecosystem exchange (NEE) under different time steps indicated that time steps used by a model affect the simulated results. There is no significant difference between simulated evapotranspiration using the model under different time steps. However, simulated NEE produces large differences in the response to different time steps. Therefore, the accurate calculation of average absorbed photosynthetic active radiation is important for the scaling of the model from hourly steps to daily steps in simulating energy and CO2 flux exchanges between winter wheat and the atmosphere. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

13.
基于遥感特征指数的地表水体自动提取技术研究   总被引:4,自引:2,他引:2       下载免费PDF全文
为了从海量遥感数据中有效地提取地表水体信息,并提高自动化提取效率,提出了一种基于遥感特征指数的地表水体自动提取方法.该方法选取归一化植被指数(NDVI)、归一化建筑指数(NDBI)和修正归一化水体指数(MNDWI)作为遥感特征指数集,并根据这些指数构建了遥感特征指数曲线.通过分析,发现地表水体在特征曲线中单调上升,植被在特征曲线中单调下降,而其它地物并无此特征.因此,根据这一规律,利用ERDAS IMAGINE软件建立了自动化提取模型.通过与其他方法对比,表明所建立的模型在精度和自动化方面都明显优于其他方法,可用于海量数据地表水体的自动提取.最后,在ARCGIS环境下,并通过决策树模型初步实现了地表水体的自动分类.  相似文献   

14.
Adequate irrigation inputs are essential for the application of hydrological models in irrigated catchments, but reliable data on both the amount and the frequency of irrigation applications are often missing at an appropriate spatial scale. In this paper, we demonstrate and test approaches to estimate irrigation inputs for distributed hydrological modelling. In this context, the Soil and Water Assessment Tool was applied to simulate water balances for an irrigated catchment in southeast Australia during the period 2008–2010. Two methods for estimating irrigation inputs were tested. One method was based on a fixed irrigation application rate, whereas the other one had variable irrigation rates depending on season and the irrigated crop. These two approaches were also compared with the ‘auto‐irrigation’ method within the Soil and Water Assessment Tool model. The method with variable irrigation rates resulted in the most reasonable interpretation of the readily available irrigation data, consistent estimates of irrigation runoff coefficients throughout the year and the best fit to observed data on both drain flows at the catchment outlet and spatial evapotranspiration patterns. We also found that the different irrigation inputs significantly affected simulated water balances, in particular deep percolation under relatively dry climatic conditions. All these results suggest that it is possible to infer irrigation inputs from readily available data and local knowledge, adequate for hydrological modelling in irrigated catchments. Our study also demonstrates that, in order to predict reliable water balances in irrigated catchments, an accurate knowledge of irrigation scheduling and irrigation runoff is required. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

15.
The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi‐scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust‐producing sources. The representation of intra‐annual and inter‐annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter‐annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas. Copyright © 2012 John Wiley & Sons, Ltd.  相似文献   

16.
Study on NDVI-T_s space by combining LAI and evapotranspiration   总被引:1,自引:1,他引:1  
Vegetation index and land surface temperature (Ts) are important parameters for land surface process modeling. The remotely sensed data in visible/near infrared and thermal infrared wavelengths have proven to be well suited to monitoring vegetation status, soil surface moisture conditions, drought and crop yield. More useful information can be created by integrated analyses of these two kinds of data, which will help us to study main principles of the temporal and spatial variations of land su…  相似文献   

17.
A previous study analyzed errors in the numerical calculation of actual crop evapotranspiration (ETa) under soil water stress. Assuming no irrigation or precipitation, it constructed equations for ETa over limited soil‐water ranges in a root zone drying out due to evapotranspiration. It then used a single crop‐soil composite to provide recommendations about the appropriate usage of numerical methods under different values of the time step and the maximum crop evapotranspiration (ETc). This comment reformulates those ETa equations for applicability over the full range of soil water values, revealing a dependence of the relative error in numerical ETa on the initial soil water that was not seen in the previous study. It is shown that the recommendations based on a single crop‐soil composite can be invalid for other crop‐soil composites. Finally, a consideration of the numerical error in the time‐cumulative value of ETa is discussed besides the existing consideration of that error over individual time steps as done in the previous study. This cumulative ETa is more relevant to the final crop yield. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.  相似文献   

18.
In the Aral Sea Basin, where the Central Asian countries compete for limited water resources, reliable information on the actual water use for eight million ha of irrigated land are rare. In this study, spatially distributed land use data, seasonal actual evapotranspiration, and reference evapotranspiration derived from multitemporal MODIS data were combined with in situ water flow measurements for irrigation performance assessments in the upper Amu Darya Delta. The functioning of the major irrigation and drainage which supplies an agricultural area of 270,000 ha in the Uzbek province Khorezm was analysed using water balancing and adequacy indicators of irrigation water use.An average relative evapotranspiration of 95% indicated fulfilled water demands and partly over-irrigation, whereas values below 75% disclosed inadequate water supply in distant parts of the irrigation system. On the other hand, immense water withdrawals of approximately 24,000 m3 ha−1 recorded at the system boundaries between April and September 2005 clearly exceeded the field water demands for cotton cultivation. Only 46% of the total irrigation amounts were consumed for crop production at field level. Throughout the vegetation period, approximately 58% of the total available water left the region as drainage water. Monthly observations of the depleted fraction and the drainage ratio highlighted drainage problems and rising groundwater levels at regional scale. In the most distant downstream subsystem, a high risk of groundwater and soil salinity during the main irrigation phase was found.A combination of high conveyance losses, hydraulic problems, direct linkages between irrigation and drainage, and low field application efficiencies were identified as major reasons for underperforming irrigation. The findings underlined the necessity of water saving and of reconsidering water distribution in Khorezm. The remote sensing approach was concluded as a reliable data basis for regular performance assessments for all irrigation systems in Central Asia.  相似文献   

19.
青藏高原地区高精度的土壤水分反演对高原能水循环、全球大气循环研究有着极大的影响.因此,获取青藏高原土壤水分时空布信息是一个迫切需要解决的问题.温度植被干旱指数(TVDI),是基于光学与热红外遥感通道数据反演土壤水分的重要方法,但在研究区域较大、地表覆盖格局差异显著时,TVDI模型反演精度会受到地表温度(Ts)等因素的影响.被动微波AMSR-E数据精确记录了像元内的土壤水分信息,但空间分辨率低.本文利用同时期的MODIS与被动微波数据,发展了针对青藏高原地区高精度土壤水分反演算法.首先,在TVDI模型中,利用修正型土壤调整植被指数(MSAVI)代替归一化植被指数(NDVI),以改进NDVI易饱和的缺点;其次,利用ASTER GDEM数据,对地形高程和纬度差异引起的地表温度变化进行了校正;然后,通过神经网络训练建立基于TVDI、被动微波以及辅助气象数据的土壤水分反演模型,并应用该模型反演了青藏高原地区三个观测网(CAMP/Tibet、玛曲和那曲)的土壤水分;最后,利用实测土壤水分数据对反演结果进行验证,结果表明该模型的精度均方根误差(RMSE)数值可达到0.031~0.041 m~3·m~(-3).本文还应用该算法反演了青藏高原连续的土壤水分的空间分布,并比较了土壤水分的变化趋势与实测降水变化趋势,结果表明二者变化量的正负关系一致.  相似文献   

20.
Normalized Difference Vegetation Index (NDVI) is widely recognized as a good indicator of vegetation productivity. Diagnosing the NDVI trend and understanding climatic factors influences on NDVI can predict the productivity changes under different climatic scenarios. This paper examined NDVI dynamic and its response to climate factors during a 10 year period (1998–2008) in Inner Mongolia. The main findings are as follows: (1) The NDVI multi-scale characters can be revealed well by wavelet transform, and the average NDVI and the NDVI amplitude show a gradually decreased trend from northeast to southwest in Inner Mongolia during the past 10 years, furthermore, this trend is consistent with the heat and water distribution caused by latitude difference in north–south direction and Asia monsoon effect in east–west direction. (2) The relation between NDVI and temperature is the most close, followed by precipitation, sunshine hours and relative humidity. Different vegetation cover types show different strengths in correlation between NDVI and climate variables with the correlation values decreasing from forest, meadow steppe to desert steppe in whole. (3) The precipitation and temperature have the same change cycle, both nearly 290 days in the 20 selected stations. The NDVI has the same change cycle with the precipitation and temperature or either 10 days earlier or later than precipitation and temperature, which supports the significant correlation between NDVI and its climatic factors from a new perspective. The nearly 290 days change cycle implies that the vegetation growth cycle is nearly 10 months and there are no obvious differences change cycles in different vegetations. (4) Vegetation dynamic is significantly correlated to the temperature and precipitation at the time scale of 10, 20, 40, 80, 160, and 320-day, respectively, and the S3 scale (i.e., the time scale of 80-day), nearly 3 months (one season), is most significant and suitable for evaluating the vegetation dynamic to climatic factors.  相似文献   

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