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1.
The Caatinga biome, located in the northeastern region of Brazil, is the most populated dryland region on the planet and extremely vulnerable to land degradation due to climatological and anthropogenic factors. Energy partitioning substantially influences the local climate and affects the water cycle, which is of utmost importance for the economy and livelihood of the region. Recently, eddy covariance (EC) towers were installed in the area; thus, the scientific community can thoroughly assess the water and energy fluxes over this unique biome. While EC towers have a high degree of accuracy, they only measure energy fluxes over a small land footprint. Given the biome spatial heterogeneity, the use of EC-based techniques has the limitation of not comprehensively representing water and energy fluxes profiles over the entire region. Incorporating remote sensing (RS) data into the landscape analysis is a feasible solution to overcome this issue, given that satellite data can capture the phenomena represented by the EC measurements across large spatial scales. Our research studied the capability of the Surface Energy Balance Algorithm for Land (SEBAL) and MOD16-ET products to represent the EC measurements regarding energy and mass exchange, with an ultimate objective of applying the best approach to assess these fluxes regionally. We applied the SEBAL model using only remote sensing data from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The MOD16-ET model uses a different approach but is also based on MODIS data. Our analysis was based on three years (2014–2016) of data, which was limited to the availability of the EC tower data. We found that for the EC-based measurements, energy balance closure (EBC) achieved an average of 0.84, which is considerably high for the region. This is possibly due to the EC tower being installed on a preserved Caatinga plot, with reduced heterogeneity and higher plant density. When analyzing RS-based products to represent ET profiles in the region, we found that the SEBAL model accurately represented water fluxes during the wet season but not the dry season, whereas the MOD16-ET showed a better agreement with EC-based water fluxes throughout all the seasons. SEBAL inaccuracy in drylands is partially due to the narrow range between the cold and hot pixels in an image, as the algorithm relies on this range for input parameters, especially in the dry season. Therefore, we concluded that MOD16-ET is capable of better-representing water fluxes in the Caatinga region. We analyzed the fluxes regionally and quantified annual ET for the three years. These results are especially relevant for local policymakers on dealing with water and landscape issues in a region where the livelihood and well-being of the population is inextricably bound to water availability.  相似文献   

2.
Estimating the water budgets of large basins is a challenge because of the lack of data and information. It becomes more complicated in endorheic basins that consist of separate land and water phases. The application of remotely-sensed data is one solution in this regard. The present study addresses this issue and develops a modeling framework to evaluate a water budget based on remotely-sensed data for endorheic basins. To explore the methodology, Lake Urmia basin was selected as a case study. The lake water level has declined steeply since 1995 and stakeholders have agreed to allocate 3100 MCM of water per year to the lake. This makes it necessary to monitor river inflow into the lake to fulfill the agreement. Gauging stations have been employed around the lake, but they could not account for shortages such as water uptake below the stations. To do this, separate water budgets for the water body and the land were required. More specifically, it was necessary to estimate actual evapotranspiration (ET a ) from freshwater (E f ) and saltwater (E s ) estimated using the SEBAL model. Different methods were applied to estimate soil moisture, groundwater exploitation, and surface-groundwater inflow into the lake. A comparison of the observed and estimated amounts showed good agreement. For instance, the coefficient of determination for the observed/reported and estimated ET a and E f were 0.83 and 0.84, respectively. The average annual inflow was estimated to be 2.2 BCM/year for 2002–2008 using the RS model, which is about 84 % of the total inflow from the last recording stations before the lake and shows influence of water exploitation after these stations. Future study should focus on increasing temporal and spatial resolution of the method  相似文献   

3.
Evapotranspiration (ET) is a vital process in land surface atmosphere research. In this study, Surface Energy Balance Algorithm for Land (SEBAL) for the assessment of ET (for 23 December 2010, 8 January 2011, 24 January 2011, 9 February 2011, 25 February 2011, 29 March 2011 and 14 April 2011) from LANDSAT7-ETM+ and validation with Lysimeter data set is illustrated. It is based on the evaporative fraction concept, and it has been applied to LANDSAT7-ETM + (30 m resolution) data acquired over the Indian Agricultural Research Institute’s agricultural farm land. The ET from SEBAL was compared with Lysimeter ET using four statistical tests (root-mean-square error (RMSE), relative root-mean-square error (R-RMSE), mean absolute error (MAE), and normalized root-mean square error (NRMSE)), and each test showed a good correlation between the predicted and observed ET values. Results from this study revealed that the RMSE of crop-growing period was 0.51 mm d?1 for ETSEBAL, i.e. ETSEBAL having good accuracy with respect to observed ETLysimeter. Results were also validated using R-RMSE test, which also proved that ETSEBAL data are having good accuracy with respect to observed ETLysimeter as R-RMSE of crop-growing period is 0.19 mm d?1. MAE (0.19), NRMSE (0.21) and r2 (0.91) tests indicated that model prediction is significant, and model can be effectively used for the estimation of ET from SEBAL as input of remote sensing data sets. Finally, the SEBAL has been useful for remote agricultural land where ground-based data (Lysimeter data) are not available for daily ET (ET24 h) estimation. The temporal study of the ET24 h values analysed has revealed that the highest ET24 h values are owing to the higher development (high greenness) of crops, whereas the lower values are related to the lower development (low greenness) or null crop.  相似文献   

4.
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5.
Estimation and monitoring of crop evapotranspiration (ETc) or consumptive water use over large-area holds the key to irrigation management plans and regional drought preparedness. The objective of this study was to estimate ETc by applying the simplified-surface energy balance index (S-SEBI) model to Landsat-8 data for the 2014–2015 period in parts of North India. An average ETc was estimated 2.72 and 2.47 in mm day?1 with 0.22, 0.18 standard deviation and 0.11, 0.07 standard error for Kharif and Rabi crops, respectively. On validation part, a close relationship was observed between S-SEBI derived and scintillometer observed evaporative fraction with 0.85 correlation coefficient and 0.86 agreement index. The statistical analysis also endorses the results accuracy and reliability with 0.026 and 0.602, relative root-mean square errors and model efficiency for wheat crop, respectively. The study showed that normalized difference vegetation index and LST are closely related and serve as a proxy for qualitative representation of ETc.  相似文献   

6.
Evapotranspiration is a key parameter for water stress assessment as it is directly related to the moisture status of the soil-vegetation system and describes the moisture transfer from the surface to the atmosphere. With the launch of the Meteosat Second Generation geostationary satellites and the setup of the Satellite Application Facilities, it became possible to operationally produce evapotranspiration data with high spatial and temporal evolution over the entire continents of Europe and Africa. In the frame of this study we present an evaluation of the potential of the evapotranspiration (ET) product from the EUMETSAT Satellite Application Facility on Land Surface Analysis (LSA-SAF) for drought assessment and monitoring in Europe.To assess the potential of this product, the LSA-SAF ET was used as input for the ratio of ET to reference evapotranspiration (ET0), the latter estimated from the ECMWF interim reanalysis. In the analysis two case studies were considered corresponding to the drought episodes of spring/summer 2007 and 2011. For these case studies, the ratio ET/ET0 was compared with meteorological drought indices (SPI, SPEI and Sc-PDSI for 2007 and SPI for 2011) as well as with the anomalies of the fraction of absorbed photosynthetic active radiation (fAPAR) derived from remote sensing data. The meteorological and remote sensing indicators were taken from the European Drought Observatory (EDO) and the CARPATCLIM climatological atlas.Results show the potential of ET/ET0 to characterize soil moisture variability, and to give additional information to fAPAR and to precipitation distribution for drought assessment. The main limitations of the proposed ratio for drought characterization are discussed, including options to overcome them. These options include the use of filters to discriminate areas with a low percentage vegetation cover or areas that are not in their growing period and the use of evapotranspiration without water restriction (ETwwr), obtained as output of the LSA-SAF model instead of ET0. The ET/ETwwr ratio was tested by comparing its accumulated values per growing period with the winter wheat yield values per country published by Eurostat. The results point to the potential of using the remote sensing based LSA-SAF evapotranspiration and the ET/ETwwr ratio for vegetation monitoring at large scale, especially in areas where data is generally lacking.  相似文献   

7.
Reference evapotranspiration (ETo) is a key component in efficient water management, especially in arid and semi-arid environments. However, accurate ETo assessment at the regional scale is complicated by the limited number of weather stations and the strict requirements in terms of their location and surrounding physical conditions for the collection of valid weather data. In an attempt to overcome this limitation, new approaches based on the use of remote sensing techniques and weather forecast tools have been proposed.Use of the Land Surface Analysis Satellite Application Facility (LSA SAF) tool and Geographic Information Systems (GIS) have allowed the design and development of innovative approaches for ETo assessment, which are especially useful for areas lacking available weather data from weather stations. Thus, by identifying the best-performing interpolation approaches (such as the Thin Plate Splines, TPS) and by developing new approaches (such as the use of data from the most similar weather station, TS, or spatially distributed correction factors, CITS), errors as low as 1.1% were achieved for ETo assessment. Spatial and temporal analyses reveal that the generated errors were smaller during spring and summer as well as in homogenous topographic areas.The proposed approaches not only enabled accurate calculations of seasonal and daily ETo values, but also contributed to the development of a useful methodology for evaluating the optimum number of weather stations to be integrated into a weather station network and the appropriateness of their locations. In addition to ETo, other variables included in weather forecast datasets (such as temperature or rainfall) could be evaluated using the same innovative methodology proposed in this study.  相似文献   

8.
Actual evapotranspiration is one of the most important component for efficient water management and planning. Until recently, evapotranspiration computations and measurements have been performed locally. But, in recent years, actual evapotranspiration computations can be calculated regionally thanks to improvements on remote sensing discipline and satellites. Surface Energy Balance Algorithm for Land (SEBAL) is one of the most commonly preferred technics for actual evapotranspiration mapping. However, this algorithm has some difficulties such as mismatch with Landsat 8 and hot–wet pixel selection which require expert knowledge. In this paper, a novel SEBAL based approach (SEBAL-BSA), which can use Landsat 8 images as data and can automatically perform hot–wet pixel selection using Backtracking Search Algorithm (BSA) with ground control points, has been proposed. SEBAL-BSA was developed and tested using January 22–2015, April 28–2015 and July 01–2015 dated Landsat 8 images in Akarsu Irrigation Water User Association command area in the Çukurova Region of Turkey and actual evapotranspiration mapping was realized without albedo measurements. Accuracy of SEBAL-BSA has been examined by comparing values of predefined ground truth points and values obtained from proposed approach. According to results of parametric matched pairs T test and nonparametric Wilcoxon sign rank test, SEBAL-BSA is highly successful. Applications also show that the SEBAL-BSA is a user-friendly approach for institutions and organizations related to water authorization and management.  相似文献   

9.
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10.
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11.
Efficient water-resource management is essential with regard to food security, growing populations and climate change. This is especially important for low- and middle-income (LMC) countries where food is often locally produced by traditional smallholder farming. Detailed knowledge of the spatio-temporal distribution of irrigation-water consumption provides valuable information to anticipate local food shortages and water scarcity as a result of climate variability. Yet, adequate techniques to quantify irrigation-water consumption at field level over large areas are lacking. Irrigation estimates generally have a coarse resolution making them inadequate for field-level assessments.This study developed a remote-sensing-based approach to quantify spatio-temporal patterns of irrigation-water consumption at field level using the MODIS evapotranspiration product (MOD16A2) and existing land-use maps on the spatio-temporal distribution of irrigated agriculture. Object-based image analysis was used to establish local evapotranspiration differences between irrigated and rainfed fields on a monthly basis, which are the irrigation-water consumption rates of the irrigated fields. This novel method was applied to a study area in the Central Rift Valley in Ethiopia where smallholder farming is dominant and only a few large-scale farms are present. Comparison with irrigation-water-consumption values of a local irrigation scheme showed that the monthly temporal dynamics were captured quite well, but lower values were calculated compared to the scheme's field data. Comparison with two validated remote-sensing based studies in Africa showed good agreement as irrigation-water-consumption estimates were in the same order of magnitude. Irrigation-water consumption follows the temporal rainfall pattern, i.e. irrigation practices intensify with increased water availability. Surface water is commonly used for irrigation in the study area.Our study shows that smallholder practices have a lower irrigation-water consumption compared to modern large-scale farms by approximately a factor 3. Irrigation-water consumption in the area is considerable, especially during the dry season. On average 32 % of excess water (precipitation – evapotranspiration) is consumed for irrigation. For smallholder irrigation and large-scale irrigation specifically this is 28 % and 63 % respectively.The object-based approach presented here is an operational mapping method for field-level irrigation-water-consumption over large areas. MOD16A2 is a global open-source readily-available evapotranspiration product used here although an evapotranspiration product with a higher spatial resolution might be preferred. Our approach can provide irrigation-water-consumption estimates over large areas in data-poor regions, which will increase the understanding of spatio-temporal patterns of smallholder irrigation and provide information to optimize water use.  相似文献   

12.
A remote sensing-based approach was applied to study the impact of changes in cropping system on the exploitation of water resources in two districts namely Ludhiana in central Punjab and Muktsar in South-Western Punjab. Rice-wheat remained dominant rotation in Ludhiana while cottonwheat rotation was replaced partially by rice-wheat in Muktsar within a span of over five years (1998–99 to 2003–04). The solo rice-wheat system in Ludhiana district has resulted in large-scale ground water exploitation as is evident from the faster decline in water table (up to 0.9m year−1) and higher tube-wells density (440 per 1000 ha). As a result, nearly 60 per cent of the total area of Ludhiana district has the water table depth greater than 10m and in some blocks, it has reached to a depth of 22 m. In Muktsar district, corresponding rise in water table is 0.2m per year and tube well density is 114 per 1000 ha. Irrigation water associated with paddy cultivation in Ludhiana and adjoining areas moves laterally through the buried paleo-channels of Sutlaj in the deeper soil profile and gets accumulated in the basin lands of Muktsar and adjoining areas and causes an extra water flux and subsequent rise in water table, recorded at 3 to 7m depth. To minimize the hydrological imbalance of the state, it is suggested to diversify some of the area in the central districts from irrigation water intensive rice-wheat system to less water intensive cropping system.  相似文献   

13.

Background

Large spatial, seasonal and annual variability of major drivers of the carbon cycle (precipitation, temperature, fire regime and nutrient availability) are common in the Sahel region. This causes large variability in net ecosystem exchange and in vegetation productivity, the subsistence basis for a major part of the rural population in Sahel. This study compares the 2005 dry and wet season fluxes of CO2 for a grass land/sparse savanna site in semi arid Sudan and relates these fluxes to water availability and incoming photosynthetic photon flux density (PPFD). Data from this site could complement the current sparse observation network in Africa, a continent where climatic change could significantly impact the future and which constitute a weak link in our understanding of the global carbon cycle.

Results

The dry season (represented by Julian day 35–46, February 2005) was characterized by low soil moisture availability, low evapotranspiration and a high vapor pressure deficit. The mean daily NEE (net ecosystem exchange, Eq. 1) was -14.7 mmol d-1 for the 12 day period (negative numbers denote sinks, i.e. flux from the atmosphere to the biosphere). The water use efficiency (WUE) was 1.6 mmol CO2 mol H2O-1 and the light use efficiency (LUE) was 0.95 mmol CO2 mol PPFD-1. Photosynthesis is a weak, but linear function of PPFD. The wet season (represented by Julian day 266–273, September 2005) was, compared to the dry season, characterized by slightly higher soil moisture availability, higher evapotranspiration and a slightly lower vapor pressure deficit. The mean daily NEE was -152 mmol d-1 for the 8 day period. The WUE was lower, 0.97 mmol CO2 mol H2O-1 and the LUE was higher, 7.2 μmol CO2 mmol PPFD-1 during the wet season compared to the dry season. During the wet season photosynthesis increases with PPFD to about 1600 μmol m-2s-1 and then levels off.

Conclusion

Based on data collected during two short periods, the studied ecosystem was a sink of carbon both during the dry and wet season 2005. The small sink during the dry season is surprising and similar dry season sinks have not to our knowledge been reported from other similar savanna ecosystems and could have potential management implications for agroforestry. A strong response of NEE versus small changes in plant available soil water content was found. Collection and analysis of flux data for several consecutive years including variations in precipitation, available soil moisture and labile soil carbon are needed for understanding the year to year variation of the carbon budget of this grass land/sparse savanna site in semi arid Sudan.  相似文献   

14.
Quasi-Analytical Algorithms (QAAs) are based on radiative transfer equations and have been used to derive inherent optical properties (IOPs) from the above surface remote sensing reflectance (Rrs) in aquatic systems in which phytoplankton is the dominant optically active constituents (OACs). However, Colored Dissolved Organic Matter (CDOM) and Non Algal Particles (NAP) can also be dominant OACs in water bodies and till now a QAA has not been parametrized for these aquatic systems. In this study, we compared the performance of three widely used QAAs in two CDOM dominated aquatic systems which were unsuccessful in retrieving the spectral shape of IOPS and produced minimum errors of 350% for the total absorption coefficient (a), 39% for colored dissolved matter absorption coefficient (aCDM) and 7566.33% for phytoplankton absorption coefficient (aphy). We re-parameterized a QAA for CDOM dominated (hereafter QAACDOM) waters which was able to not only achieve the spectral shape of the OACs absorption coefficients but also brought the error magnitude to a reasonable level. The average errors found for the 400–750 nm range were 30.71 and 14.51 for a, 14.89 and 8.95 for aCDM and 25.90 and 29.76 for aphy in Funil and Itumbiara Reservoirs, Brazil respectively. Although QAACDOM showed significant promise for retrieving IOPs in CDOM dominated waters, results indicated further tuning is needed in the estimation of a(λ) and aphy(λ). Successful retrieval of the absorption coefficients by QAACDOM would be very useful in monitoring the spatio-temporal variability of IOPS in CDOM dominated waters.  相似文献   

15.
三峡区域气温变化长期以来受到科研人员和公众的关注。受三峡复杂地形的影响,仅仅基于气象站点观测数据很难准确获取区域气温变化的空间格局,遥感技术则可以通过提供空间连续的地表观测数据来辅助气温变化分析。以广义加性模型GAM (General Additive Model)为插值算法,以高程和夜间地表温度(LSTnight)遥感产品为辅助变量,估算三峡库区1979年—2014年1 km空间分辨率的月气温数据,在此基础上分析了气温变化趋势的时空特征及其与高程和森林覆盖率的关系。研究表明,(1)在插值算法中引入遥感产品LSTnight作为辅助变量可以明显改善气温估算精度,冬春季的改善幅度高于夏秋季;(2)三峡库区年平均气温在1997年后明显上升,但在2003年库区蓄水后无明显变化趋势,几乎所有月(除12月以外)的气温都呈现上升趋势,增温趋势最显著是3月和9月,3月增温主要来自于库区东部山区的贡献,而9月增温主要来自于库区西部平原的贡献;(3)多数月份(除7月、8月、9月以外)的低温上升速度超过高温上升速度,导致区域气温的动态变化范围缩小;(4)三峡库区年平均气温上升速度与高程呈正相关,即海拔越高,升温越快,但在同一海拔高度处,森林覆盖率越高,年均气温上升速度越慢,暗示森林具有抑制增温的作用。  相似文献   

16.
Rice is the most consumed staple food in the world and a key crop for food security. Much of the world’s rice is produced and consumed in Asia where cropping intensity is often greater than 100% (more than one crop per year), yet this intensity is not sufficiently represented in many land use products. Agricultural practices and investments vary by season due to the different challenges faced, such as drought, salinity, or flooding, and the different requirements such as varietal choice, water source, inputs, and crop establishment methods. Thus, spatial and temporal information on the seasonal extent of rice is an important input to decision making related to increased agricultural productivity and the sustainable use of limited natural resources. The goal of this study was to demonstrate that hyper temporal moderate-resolution imaging spectroradiometer (MODIS) data can be used to map the spatial distribution of the seasonal rice crop extent and area. The study was conducted in Bangladesh where rice can be cropped once, twice, or three times a year.MODIS normalized difference vegetation index (NDVI) maximum value composite (MVC) data at 500 m resolution along with seasonal field-plot information from year 2010 were used to map rice crop extent and area for three seasons, boro (December/January–April), aus (April/May–June/July), and aman (July/August–November/December), in Bangladesh. A subset of the field-plot information was used to assess the pixel-level accuracy of the MODIS-derived rice area. Seasonal district-level rice area statistics were used to assess the accuracy of the rice area estimates. When compared to field-plot data, the maps of rice versus non-rice exceeded 90% accuracy in all three seasons and the accuracy of the five rice classes varied from 78% to 90% across the three seasons. On average, the MODIS-derived rice area estimates were 6% higher than the sub-national statistics during boro, 7% higher during aus, and 3% higher during the aman season. The MODIS-derived sub-national areas explained (R2 values) 96%, 93%, and 96% of the variability at the district level for boro, aus, and aman seasons, respectively.The results demonstrated that the methods we applied for analysing and interpreting moderate spatial and high temporal resolution imagery can accurately capture the seasonal variability in rice crop extent and area. We discuss the robustness of the approach and highlight issues that must be addressed before similar methods are used across other areas of Asia where a mix of rainfed, irrigated, or supplemental irrigation permits single, double, and triple cropping in a single calendar year.  相似文献   

17.
The spatial and temporal distribution of absorption of chromophoric dissolved organic matter at 440 nm (aCDOM (440)) in the Mandovi and Zuari estuaries situated along the west coast of India, has been analysed. The study was carried out using remotely sensed data, obtained from the Ocean Colour Monitor (OCM) on board the Indian Remote Sensing satellite — P4, together with in situ data during the period January to December 2005. Satellite retrieval of CDOM absorption was carried out by applying an algorithm developed for the site. A good correlation (R=0.98) was obtained between satellite derived CDOM and in situ data. Time series analysis revealed that spatial distribution of CDOM has a direct link with the seasonal hydrodynamics of the estuaries. The effect of remnant fresh water on CDOM distribution could be analysed by delineating a plume in the offshore region of the Zuari estuary. Though fresh water flux from terrestrial input plays a major role in the distribution of CDOM throughout the Mandovi estuary, its role in the Zuari estuary is significant up to the middle zone. Other processes responsible for feeding CDOM in both the estuaries are coastal advection, in situ production and resuspension of bottom settled sediments. The highest value of aCDOM(440) was observed in the middle zone of the Mandovi estuary during the post-monsoon season. The relation between aCDOM(440) and S (spectral slope coefficient of CDOM) could differentiate CDOM introduced in to estuaries through multiple sources. The algorithm developed for the Mandovi estuary is S=0.003 [aCDOM(440)−0.7091] while for the Zuari estuary, S=0.0031 [aCDOM(440)−0.777], respectively.  相似文献   

18.
Irrigation water requirements of wheat and mustard crops grown in Western Yamuna Canal Command area were estimated using FAO model CROPWAT with the help of agrometeorological and remote sensing data (1986–1998 and 2008). The variations in irrigation water requirements of these two crops were judged by calculating coefficient of Variations (CVs) of yearly data. Crop coefficient values were obtained through FAO (1993) method. Supervised Maximum Likelihood Classification (MXL) of IRS 1B image was done to estimate area under wheat and mustard in the canal command. Water need was calculated from amount of supply and water requirement for the whole area. Results showed that ETcrop values of both wheat and mustard varied very little over different years (CVs 4.7% and 5.6% respectively). Irrigation water requirements of both these crops were having relatively large variations (CVs 14.1% and 22.6% respectively) which were mainly because of high variations of their effective rainfall (CVs 61.1% and 69.2% respectively). In general, increase in amount of irrigation enhanced the growth performance of the wheat crop. Increase in distribution equity within soil associations slightly improved the growth performance of the wheat crop. Agro-climatic data merged with satellite image approximated the deficiency of applied irrigation amount (549.5 ha-m for wheat and 692.7 ha-m for mustard) as compared to requirement.  相似文献   

19.
The spectroradiometric retrieved reflectance of a local crop, namely, beans (Phaseolus vulgaris), is directly compared to the reflectance of Landsat 5TM and 7ETM+ atmospherically corrected and uncorrected satellite images. Also, vegetation indices from the same satellite images—atmospherically corrected and uncorrected—are compared with the corresponding vegetation indices produced from field measurements using a spectroradiometer. Vegetation Indices are vital in the estimation of crop evapotransiration under standard conditions (ETc) because they are used in stochastic or empirical models for describing crop canopy parameters such as the Leaf Area Index (LAI) or crop height. ETc is finally determined using the FAO Penman-Monteith method adapted to satellite data, and is used to examine the impact of atmospheric effects. Regarding the reflectance comparison, the main problem was observed in Band 4 of Landsat 5TM and 7ETM+, where the difference, for uncorrected images, was more than 20% and statistically significant. Results regarding ETc show that omission or ineffective atmospheric corrections in Landsat 5TM,/7ETM+ satellite images always results in a water deficit when estimating crop water demand. Diminished estimated crop water requirements can result in a reduction in output or, if critical, crop failure. The paper seeks to illustrate the importance of removing atmospheric effects from satellite images designated for hydrological purposes.  相似文献   

20.
An approach for estimating soil moisture is presented and tested by using surface-temperature-based soil evaporation transfer coefficient (ha), a coefficient recently proposed through the equation ha = (Ts − Ta)/(Tsd − Ta), where Ts, Tsd, and Ta are land surface temperature (LST), reference soil (dry soil without evaporation) surface temperature, and air temperature respectively. Our analysis and controllable experiment indicated that ha closely related to soil moisture, and therefore, a relationship between field soil moisture and ha could be developed for soil moisture estimation. Field experiments were carried out to test the relationship between ha and soil moisture. Time series Aqua-MODIS images were acquired between 11 Sep. 2006 and 1 Nov. 2007. Then, MODIS derived ha and simultaneous measured soil moisture for different soil depths were used to establish the relations between the two variables. Results showed that there was a logarithmic relationship between soil moisture and ha (P < 0.01). These logarithmic models were further validated by introducing another ground-truth data gathered from 46 meteorological stations in Hebei Province. Good agreement was observed between the measured and estimated soil moisture with RMSE of 0.0374 cm3/cm3 and 0.0503 cm3/cm3 for surface energy balance method at two soil depths (10 cm and 20 cm), with RMSE of 0.0467 cm3/cm3 and 0.0581 cm3/cm3 for maximum temperature method at two soil depths. For vegetated surfaces, the ratio of ha and NDVI suggested to be considered. The proposed approach has a great potential for soil moisture and drought evaluation by remote sensing.  相似文献   

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