Irrigation Scheduling Using Remote Sensing Data Assimilation Approach

Remote sensing and crop growth models have enhanced our ability to understand soil water balance in irrigated agriculture. However, limited efforts have been made to adopt data assimilation methodologies in these linked models that use stochastic parameter estimation with genetic algorithm (GA) to improve irrigation scheduling. In this study, an innovative irrigation scheduling technique, based on soil moisture and crop water productivity, was evaluated with data from Sirsa Irrigation Circle of Haryana State, India. This was done by integrating SEBAL (Surface Energy Balance Algorithm for Land)-based evapotranspiration (ET) rates with the SWAP (Soil-Water-Atmosphere-Plant), a process-based crop growth model, using a GA. Remotely sensed ET and ground measurements from an experiment field were combined to estimate SWAP model parameters such as sowing and harvesting dates, irrigation scheduling, and groundwater levels to estimate soil moisture. Modeling results showed that estimated sowing, harvesting, and irrigation application dates were within ±10 days of observations and produced good estimates of ET and soil moisture fluxes. The SWAP-GA model driven by the remotely sensed ET moderately improved surface soil moisture estimates suggesting that it has the potential to serve as an operational tool for irrigation scheduling purposes.

Digital mapping of pesticides bioconcentration by integrating remote sensing techniques and plant uptake model

Although pesticides have been widely used worldwide to enhance crop yield and product quality,most pesticides are harmful to the environment and human health.Plants absorb pesticides mainly from air and soil.Therefore,the soil-plant pathway is essential for pesticide absorption.Bioconcentration factor(BCF)has extensively been applied to evaluate potential plant contamination by pesticides from soil.Hence,this study developed a simplified plant transpiration-based plant uptake model(PT-model)to estimate plant pesticides’BCF from soil based on plant transpiration.Remote sensing techniques were employed to generate spatiotemporal continuous plant transpiration via evapotranspiration.Pesticide BCF mapping was achieved by integrating PT-model with Moderate Resolution Imaging Spectroradiometer(MODIS)remotely sensed data.The results were compared with a verified model driven by relative humidity and air temperature(RA-model),which has been confirmed byfindings from previous studies.The estimated BCF was within the boundaries of the RA-model,indicating the simulation’s overall acceptability.In this study,the BCF temporal trend estimated by the proposed method agreed with the RA-model assimilating meteorology datasets,while the spatial distribution was partially inconsistent.Overall,the proposed method generates the spatiotemporal patterns of pesticide BCF with relatively consistent results supported by previous records andfindings.

An operational two-layer remote sensing model to estimate surface flux in regional scale: Physical background

Based on the improved interaction mechanism of two-layer model, this paper proposed Pixel Component Arranging and Comparing Algorithm (PCACA) and theoretically positioning algorithm, estimated the true temperature of mixed pixel in four extreme points in combination with the measurements of dry and wet points in calibration fields and improved the reliability of positioning dry and wet line. A new two-layer energy-separation algorithm was proposed,which was simple and direct without resistance network parameters for each pixel. We also proposed a new thought about the effect of advection. The albedo of mixed pixel was also separated with PCACA. In combination with two-layer energy-separation algorithm, the net radiation of mixed pixel was separated to overcome the uncertainty of conventional energy-separation algorithm using Beer's Law. Through the validation of retrieval result, this method is proved to be feasible and operational. At the same time, the uncertainty of this algorithm was objectively analyzed.

Estimation of the Actual Evapotranspiration by the SEBAL Method in the Irrigated Rice Perimeter of Zatta (Yamoussoukro—Côte d’Ivoire)

In this study, the SEBAL (Surface Energy Balance Algorithm for Land) model was used to map the spatio-temporal distribution of actual evapotranspiration in the Yamoussoukro department (Côte d’Ivoire). Like other regions of the country, the Yamoussoukro district is confronted with the phenomenon of evapotranspiration (ET). This is a very important component that comes into play in the water balance but also in the calculation of the water needs of agricultural crops. Consequently, its estimation is of paramount importance in research related to the rational management of water resources, particularly agricultural water. The objective of this study was to analyze the spatio-temporal distribution of actual evapotranspiration (AET) as a function of land cover and land use. The methodology used is based on the SEBAL model which uses remote sensing (Landsat 8_OLI/TIRS) and climatic data to estimate actual evapotranspiration and analyze the spatio-temporal distribution of AET. The results reveal that the AET varied from 0 to 5.44 mm/day over the period from December 2019 to February 2020 with an average value of 4.92 mm/day. The highest average values occurred for water bodies (4.90 mm/day) and flooded vegetation (4.88 mm/day) while the lowest values occurred in residential areas (2.04 mm/day). Furthermore, the results show that the difference between the SEBAL model and the FAO-Penman-Monteith method is minimal with an average RMSE of 0.36 mm/day for all the satellite images. This study demonstrates the considerable potential of remote sensing for the characterization and estimation of spatial evapotranspiration in the Zatta irrigated rice-growing area.

Simplified SEBAL method for estimating vast areal evapotranspiration with MODIS data

The SEBAL （surface energy balance algorithm for land） model provides an efficient tool for estimating the spatial distribution of evapotranspiration, and performs a simple adjustment procedure to calculate sensible heat flux using the wind speed data set from only one weather station. This paper proposes a simplified method to modify the traditional SEBAL model for calculating the 24-hour evapotranspiration （ ETduly ） in the Haihe Basin with data from 34 weather stations. We interpolated the wind speeds using the inverse distance weighting method to establish a wind field and then used it to calculate the friction velocity directly. This process also simplifies the iterative computation process of sensible heat flux. To validate the feasibility of this simplified method, we compared the results with those obtained with an appropriate but more complex method proposed by Tasumi, which separates a vast area into several sub-areas based on the weather conditions, and runs the SEBAL model separately in each sub-area. The results show good agreement between the evapotranspiration generated by the two methods, with a coefficient of determination （r2） of 0.966, which indicates the feasibility of estimating evapotranspiration over a large region with the simplified method.

Application of Spatially Distributed Calibrated Hydrological Model in Evapotranspiration Simulation of Three Gorges Reservoir Area of China:A Case Study in the Madu River Basin

Evapotranspiration(ET)is the key to the water cycle process and an important factor for studying near-surface water and heat balance.Accurately estimating ET is significant for hydrology,meteorology,ecology,agriculture,etc..This paper simulates ET in the Madu River Basin of Three Gorges Reservoir Area of China during 2009-2018 based on the Soil and Water Assessment Tool(SWAT)model,which was calibrated and validated using the MODIS(Moderate-resolution Imaging Spectroradiometer)/Terra Net ET 8-Day L4 Global 500 m SIN Grid(MOD16A2)dataset and measured ET.Two calibration strategies(lumped calibration(LC)and spatially distributed calibration(SDC))were used.The basin was divided into 34 sub-basins,and the coefficient of determination(R^(2))and NashSutcliffe efficiency coefficient(NSE)of each sub-basin were greater than 0.6 in both the calibration and validation periods.The R2 and NSE were higher in the validation period than those in the calibration period.Compared with the measured ET,the accuracy of the model on the daily scale is:R^(2)=0.704 and NSE=0.759(SDC results).The model simulation accuracy of LC and SDC for the sub-basin scale was R^(2)=0.857,R^(2)=0.862(monthly)and R^(2)=0.227,R^(2)=0.404(annually),respectively;for the whole basin scale was R^(2)=0.902,R^(2)=0.900(monthly)and R^(2)=0.507 and R^(2)=0.519(annually),respectively.The model performed acceptably,and SDC performed the best,indicating that remote sensing data can be used for SWAT model calibration.During 2009-2018,ET generally increased in the Madu River Basin(SDC results,7.21 mm/yr),with a multiyear average value of 734.37 mm/yr.The annual ET change rate for the sub-basin was relatively low upstream and downstream.The linear correlation analysis between ET and meteorological factors shows that on the monthly scale,precipitation,solar radiation and daily maximum and minimum temperature were significantly correlated with ET;annually,solar radiation and wind speed had a moderate correlation with ET.The correlation between maximum temperature and ET is best on the monthly scale(Pearson correlation coefficient R=0.945),which may means that the increasing ET originating from increasing temperature(global warming).However,the sub-basins near Shennongjia Nature Reserve that are in upstream have a negative ET change rate,which means that ET decreases in these sub-basins,indicating that the’Evaporation Paradox’exists in these sub-basins.This study explored the potential of remote-sensing-based ET data for hydrological model calibration and provides a decision-making reference for water resource management in the Madu River Basin.

Application of MODIS-Based Monthly Evapotranspiration Rates in Runoff Modeling: A Case Study in Nebraska,USA

Daily and monthly flow-rates of the Little Nemaha River in Nebraska were simulated by the lumped-parameter Jakeman-Hornberger as well as a distributed-parameter water-balance accounting procedure for the 2003-2008 and 2000-2009 periods, respectively, with and without the help of the MODIS-based monthly estimates of evapotranspiration (ET) rates. While the daily lumped-parameter model simulation accuracy remained practically unchanged with the inclusion of the monthly MODIS-based ET rates interpolated into daily values (R2 of 0.66 vs 0.68, simulated to measured runoff ratio remaining the same 96%), the monthly water-balance accounting model outcomes did improve to some extent (from an R2 of 0.67 to 0.7 with simulated to measured runoff ratio of 72% vs 115%). In both cases the models had to be slightly modified for accommodation of the ET rates as predefined input values, not present in the original model setups. These results indicate the potential practical usefulness of satellite-derived ET estimates (CREMAP values in the present case) in monthly water-balance modeling. CREMAP is a calibration-free ET estimation method based on MODIS-derived daytime surface temperature values in combination of basic climatic variables, such as air temperature, humidity and solar radiation within a Complementary Relationship framework of evaporation.

基于RUSLE模型的京津冀地区土壤侵蚀时空变化分析

【目的】土壤侵蚀是一种日益严重的生态问题,已经成为全球性的环境挑战,对人类的生存和可持续发展产生了极大的威胁。因此基于多源遥感数据,【方法】通过RUSLE模型和地理探测器模型研究了1990—2020年京津冀地区土壤侵蚀在时空尺度上的动态变化,并对其驱动因素进行了分析。【结果】结果显示:(1) 1990—2020年京津冀地区的土壤侵蚀总体呈现东南低西北高的分布特征,且以微度和轻度侵蚀为主,其百分比达到73.79%。(2)京津冀大部分地区土壤侵蚀等级主要由高向微强度侵蚀转移,且转移比例都在50%以上,整体有所好转,但存在局部加剧。(3)各个影响因子对土壤侵蚀的解释力依次为:坡度>高程>土地覆盖类型>植被覆盖度>降雨量>人口密度>GDP。【结论】相关结论可为水土流失治理以及防治提供一定的科学参考,同时也可为其他地区的土壤侵蚀治理提供参考。

SEBAL模型及其在区域蒸散研究中的应用

蒸散是地表能量平衡与水量平衡的重要参数,遥感技术的发展促进了区域蒸散的研究。基于地表能量平衡方程,SEBAL模型利用遥感影像的可见光、近红外与热红外波段及少量气象数据可计算出区域的日蒸散量,是一个物理概念较为清楚的模型。采用Landsat7ETM+数据利用SE-BAL模型对河北省栾城县进行了遥感蒸散研究,计算获得相关地面特征参数与日蒸散量,模拟结果较为合理。

应用Landsat数据和SEBAL模型反演区域蒸散发及其参数估算

随着遥感技术的进步,人们发展了多种通过遥感计算区域蒸散发的方法。SEBAL模型是通过遥感反演地面蒸散的典型方法,它以陆面能量平衡为基础,物理意义明确,只利用遥感影像和少量的气象数据(风速、气温)就能反演蒸散量。Landsat数据的波谱信息丰富、空间分辨率高,数据源稳定,是通过遥感技术反演蒸散发的理想数据源。如果能合理地估算SEBAL模型中的基本参数,将会获得较高精度的反演结果,能够满足在水文、生态、林业等研究或应用中的需要,对区域水资源的管理与利用具有重要意义。从SEBAL模型的基本原理出发,分析了利用SEBAL模型采用Landsat的TM/ETM+数据反演区域蒸散发的基本过程,针对TM/ETM+数据特点对模型所需要的基本参数进行估算求解,为SEBAL模型在蒸散量反演中的广泛应用提供了一定的指导。

基于SEBAL模型的漓江流域蒸散量变化分析

基于1993年、1999年、2006年和2010年Landsat TM/ETM+影像,应用SEBAL模型估算了漓江流域四期不同时相的日蒸散量,并应用P-M公式对估算结果进行验证。通过对研究区蒸散量结果进行分析,得出以下结论:(1)日蒸散量分布受到季节及气候的影响,植被生长季的蒸散量明显高于其他季节;(2)漓江流域的蒸散分布具有明显的空间差异性,不同土地利用类型的蒸散均值相差较大,不同时期的蒸散量均表现出林地>水体>灌木/草地>耕地>建设用地的规律;(3)近20a来漓江流域土地利用变化显著,除去气候及降水量等因素的影响,蒸散量受到土地利用变化的影响明显。随着漓江水源林地的减少与退化,日蒸散量呈现下降的趋势,进一步揭示了经济发展与人类活动对漓江流域生态环境及水热平衡的影响。

基于SEBAL模型的盘锦湿地日蒸散估算及其分布特征

为了验证SEBAL模型对湿地蒸散量估算的准确性,本研究基于Landsat 8卫星数据和SEBAL模型,以盘锦湿地生态系统野外观测站的涡动相关实测数据为检验,估算盘锦湿地2013—2015年典型晴天卫星过境时刻的瞬时蒸散量,并利用正弦函数法将遥感反演订正后的蒸散瞬时值转换为日尺度的蒸散值,分析芦苇和稻田湿地的日蒸散量分布特征。结果表明:SEBAL模型反演的盘锦湿地瞬时蒸散量比实测值偏高,平均相对误差为31.6%,但相关系数达0.79,为了提高反演精度,利用线性方程进行订正,订正后的遥感估算值与实测值平均相对误差为6.4%,提高了25.2%;芦苇湿地日蒸散量集中在3.4~4.0 mm/d之间,占总面积的64.7%~82.4%;稻田湿地日蒸散量集中在3.6~4.1 mm/d之间,占总面积的67.4%~86.6%;稻田湿地日蒸散量普遍比芦苇湿地高0.1~0.2 mm/d。应用订正后的SEBAL模型反演湿地蒸散量,可为湿地区域蒸散估算及湿地水资源管理提供依据。

利用SEBAL模型与P-M公式估算乌裕尔河下游地表蒸散

先通过SEBAL模型估算了乌裕尔河下游沼泽旱地交错区1992年7月9日、1994年7月15日、1995年7月18日、1999年7月13日4个时相的日蒸散量,并通过P-M公式与作物系数进行时间尺度扩展得到了这4个时相所处月份的蒸散量,最后对日蒸散量、作物系数、月蒸散量的特征及其影响因素进行分析。结果表明:日蒸散量的频率分布图呈双峰结构,分别体现了旱地的蒸散特征、湿地与水体的蒸散特征;平均日蒸散量依照1994-07-15、1999-07-13、1995-07-18、1992-07-09的顺序依次降低;时相1994-07-15的平均日蒸散量与平均作物系数最高;通过逐步回归分析发现日平均风速、日照时数、日最低气温对参考作物日蒸散量的影响较为明显。

基于水热平衡的分布式水文模型研究与应用

分布式水文模型在水利部“四预”建设中发挥了至关重要的作用,但无径流资料区(简称无资料区)分布式水文模拟技术仍需进一步完善。从水热循环产汇流理论、模型构建与求解、模型参数率定三个方面入手,改进传统分布式水文模型。提出了耦合热量平衡的流域产汇流理论,揭示了水量热量动力学过程耦合机理和水热循环通量量化关系。构建了系统完整的物理机制水热平衡分布式水文模型及其数值求解方法,实现了流域地表温度和水位的分布式数值模拟。明确了模型结构和参数的物理意义,降低了需要率定的参数个数。将参数率定目标由径流量转换为地表温度和水位,综合利用遥感反演和台站观测资料率定模型参数。将研发的模型在江西赣江流域进行应用,结果表明,构建的模型具有较强的物理机制,数值求解方法精度高、稳定性好,实现了无资料区参数率定和水文模拟,为无资料区分布式水文模型研发与应用提供了新思路。

基于SEBAL模型的冀蒙接壤区ET反演

以位于半干旱地区的冀蒙接壤带为研究对象,利用SEBAL模型和邻近研究区10个气象站点的气象数据,反演得到研究区内各种土地覆被/利用类型的日蒸散规律,并与来自张家口市的蒸散数据作了比较,反演得到的蒸散发精度较高.研究结果表明:1)水体、林地蒸散呈现双峰结构,其他土地覆被/利用类型呈现单峰结构;2)研究区域内日蒸散发量的排序是:林地、水体、草地、居民点、未利用地、耕地、沙地.

基于SEBAL模型的土默特右旗腾发量研究

【目的】评价SEBAL模型在估算内蒙古包头市土默特右旗腾发量时的适用性。【方法】基于2015年作物生育期内的Landsat8遥感影像,建立SEBAL模型,估算腾发量,利用FAO Penman-Monteith公式与水量平衡法估算得到腾发量进行了验证及评价,并采用多元逐步回归方法对其影响因素进行了分析。【结果】日腾发量的分布具有明显的空间差异性,呈现出"山峰型"变化趋势。SEBAL模型腾发量估算值与水量平衡法估算值相比,相对误差的平均值为6.053%;Penman-Monteith公式计算得到的日腾发量与水量平衡法估算值相差7.682%,都在10%以内,达到了精度要求,且SEBAL模型估算腾发量的精度高于Penman-Monteith公式。日腾发量与NDVI和地表温度相关性显著,由二者建立了最优的多元逐步回归方程。【结论】在缺乏数据的情况下,利用SEBAL模型可以较为准确地估算出土右旗的腾发量,且NDVI和地表温度对其的影响较大。

SEBAL模型在干旱区区域蒸散发估算中的应用

蒸散发是水量平衡和能量平衡的重要环节,传统的计算方法只能以点为基础进行计算。为排除蒸散发空间变异特性的影响,在遥感技术的基础上,引入了基于地表能量平衡原理的SEBAL模型,对新疆焉耆盆地的日蒸散发情况进行了计算模拟,获取了相关地面特征参数及日蒸散量,并根据盆地内具有大面积湖泊这一实地情况对模型进行了改进。

基于SEBAL模型的老哈河流域蒸散发研究

针对传统的蒸散发计算方法存在的不足,采用基于地表热量平衡的SEBAL模型,利用1 km分辨率的MODIS影像数据估算了位于半干旱地区的老哈河流域的实际蒸散发量及其时空分布特征,并综合分析了蒸散发量与土地利用、土地覆被、地表温度、植被指数、高程、坡度的关系。结果表明,该流域蒸散发时空分布不均匀,且实际蒸散发与地表温度呈指数相关,与归一化植被指数和高程等参数呈线性相关。该方法可为国内半干旱地区的实际蒸散发研究提供参考。

Spatio-temporal pattern and changes of evapotranspiration in arid Central Asia and Xinjiang of China

Accurate inversion of land surface evapotranspiration （ET） in arid areas is of great significance for understanding global eco-hydrological process and exploring the spatio-temporal variation and ecological response of water resources. It is also important in the functional evaluation of regional water cycle and water balance, as well as the rational allocation and management of water resources. This study, based on model validation analysis at varied scales in fiwe Central Asian countries and China＇s Xinjiang, developed an appropriate approach for ET inversion in arid lands. The actual ET during growing seasons of the study area was defined, and the changes in water participating in evaporation in regional water cycle were then educed. The results show the simulation error of SEBS （Surface Energy Balance System） model under cloud amount consideration was 1.34% at 30-m spatial scale, 2.75% at 1-km spatial scale and 6,37% at 4-kin spatial scale. ET inversion for 1980-2007 applying SEBS model in the study area indicates： （1） the evaporation depth （May-September） by land types descends in the order of waters （660.24 ram） 〉 cultivated land （464.66 mm） 〉 woodland （388.44 mm） 〉 urbanized land （168.16 mm） 〉 grassland （160.48 mm） 〉 unused land （83.08 mm）; and （2） ET during the 2005 growing season in Xinjiang and Central Asia was 2,168.68x108 m3 （with an evaporation/precipitation ratio of 1.05） and 9,741.03x108 m3 （with an evaporation/precipitation ratio of 1.4）, respectively. The results unveiled the spatio-temporal variation rules of ET process in arid areas, providing a reference for further research on the water cycle and water balance in similar arid regions.