Estimation and mapping of water erosion and soil loss:Application of Gavrilovic erosion potential model(EPM)using GIS and remote sensing in the Assif el mal Watershed,Western high Atlas

Water erosion is a serious problem that leads to soil degradation,loss,and the destruction of structures.Assessing the risk of erosion and determining the affected areas has become crucial in order to understand the main factors influencing its evolution and to minimize its impacts.This study focuses on evaluating the risk of erosion in the Assif el mal watershed,which is located in the High Atlas Mountains.The Erosion Potential Model(EPM)is used to estimate soil losses depending on various parameters such as lithology,hydrology,topography,and morphometry.Geographic information systems and remote sensing techniques are employed to map areas with high erosive potential and their relationship with the distribution of factors involved.Different digital elevation models are also used in this study to highlight the impact of data quality on the accuracy of the results.The findings reveal that approximately 59%of the total area in the Assif el mal basin has low to very low potential for soil losses,while 22%is moderately affected and 19.9%is at high to very high risk.It is therefore crucial to implement soil conservation measures to mitigate and prevent erosion risks.

Assessment of Soil Water Content and Remote Sensing Techniques--Case Study of Kiwi Orchard （Portugal）

Soil water management plays an important role in the response of kiwi plants （Actinidia deliciosa A. Chev.）. In GuimarSes district soil moisture content is monitored in kiwifi＇uit orchard as a routine parameter. Drip irrigation system is the method used. This crop tends to have high water requirements and extends over a wide area in Portugal, requiring innovative solutions to achieve better benefits. A method that correlates soil and crop conditions with the parameters of remote sensing was established in this study. To assess the level of accuracy of soil moisture measurements from satellites, it is important to compare satellite image with ground real data （namely the frequency domain reflectometry （FDR）, Diviner 2000）. The combination of multispectral satellite images produces an image representative of vegetation vigour, density and health. In this study, Landsat satellite images （2011 and 2013） are used and vegetation indexes are calculated for different periods of time, using the software Idrisi Taiga. The information of vegetation indexes is crossed with data of soil moisture, in situ, to establish a correlation between both of them. Thus, it allows to improve the soil water content monitoring, in particular for the soil water balance optimization and its effect on kiwi biornass production.

A STUDY OF SOIL CONSERVATION MONITORING INFORMATION SYSTEM BASED ON REMOTELY SENSED DATA FOR A CATCHMENT ON THE LOESS PLATEAU

The Soil Conservation Monitorins Information System (SCMIS) presented in this paper is oriented to soil erosion control, resources exploitation, utilization, planning and management for a small watershed (about 10 sq. km.) on the Loess Plateau. It sums up Remote sensing (RS), Geographical Information System (GIS) and Expert System (ES) and consists of a integrated system. As a basic level information system of Loess Plateau, its perfection and psreading will bring about a great advance in resources exploitation and management of Loess Plateau.

Soil Erosion Changes over the Past Five Decades in the Red Soil Region of Southern China

This paper reports the dynamic changes of soil and water loss in the red soil region of Southern China since the 1950s. The red soil region covers eight provinces: Jiangxi, Zhejiang, Fujian, Anhui, Hubei, Hunan, Guangdong and Hainan. From the 1950s to 1986, the annual rate of soil erosion increased by 3.4%. From 1986 to 1996 and from 1996 to 2000, the annual rates of soil erosion decreased by 2.0% and 0.32%, respectively. Field surveys showed that from 2000 to 2005, the area of soil and water loss decreased annually by 1.2%. This decrease was a result of large-scale erosion control activities across China. Although the eroded soil has been restored, the restoration process is very slow and full restoration will take a long time. Our report suggests that controlling soil and water loss is a challenging task, and additional measures must be taken to effectively control the soil erosion in the red soil region.

Mapping of Soil Erosion Zones of Meghadrigedda Catchment, Visakhapatnam, India for Conservation <br/>—A Geospatial Approach

Meghadrigedda, a non-perennial drainage system is one of the major water resources of Vishakhapatnam city located in the northern coastal region of Andhra Pradesh, India. It traverses through the hilly terrain of Eastern GhatMobile Belt (EGMB) characterized by khondalitic rock formations. Excessive siltation scenario aggravated due to soil erosion in its catchment is threatening the very existence of Meghadrigedda reservoir. In order to assess the intensity of soil erosion as well as silt deposition in the reservoir, an integrated study has been undertaken which takes into consideration various topographic, morphological, soil, and land use/land cover characteristics of the basin. The study aims at identification and mapping of erosion prone zones with respect to silt deposition using remote sensing and GIS techniques.Alteration in human induced land use practices in its catchment due to rapid growth in population, urbanization and industrialization are found to be of prime reasons for various forms of erosion. The study has noticed that various forms of erosion like sheet, gully and stream erosion are responsible for the siltation at large scale which is causing reduction of its designed storage capacity by 40%. Various sub-watersheds of the basin have been prioritized on the basis of erosion intensity for suggesting various mitigation measures like check-dam construction, afforestation etc. to protect the reservoir from the silting problem.

A Comparison of SWAT Model Calibration Techniques for Hydrological Modeling in the Ganga River Watershed

The Ganga River, the longest river in India, is stressed by extreme anthropogenic activity and climate change, particularly in the Varanasi region. Anticipated climate changes and an expanding populace are expected to further impede the efficient use of water. In this study, hydrological modeling was applied to Soil and Water Assessment Tool （SWAT） modeling in the Ganga catchment, over a region of 15 621.612 km2 in the southern part of Uttar Pradesh. The primary goals of this study are： ① To test the execution and applicability of the SWAT model in anticipating runoff and sediment yield; and ② to compare and determine the best calibration algorithm among three popular algorithms-sequential uncertainty fitting version 2 （SUFI-2）, the generalized likelihood uncertainty estimation （GLUE）, and par-allel solution （ParaSol）. The input data used in the SWAT were the Shuttle Radar Topography Mission （SRTM） digital elevation model （DEM）, Landsat-8 satellite imagery, soil data, and daily meteorological data. The watershed of the study area was delineated into 46 sub-watersheds, and a land use/land cover （LULC） map and soil map were used to create hydrological response units （HRUs）. Models utilizing SUFI- 2, GLUE, and ParaSol methods were constructed, and these algorithms were compared based on five cat-egories： their objective functions, the concepts used, their performances, the values of P-factors, and the values of R-factors. As a result, it was observed that SUFI-2 is a better performer than the other two algo-rithms for use in calibrating Indian watersheds, as this method requires fewer runs for a computational model and yields the best results among the three algorithms. ParaSol is the worst performer among the three algorithms. After calibrating using SUFI-2, five parameters including the effective channel hydraulic conductivity （CH_K2）, the universal soil-loss equation （USLE） support parameter （USLE_P）, Manning＇s n value for the main channel （CH_N2）, the surface runoff lag time （SURLAG）, and the available water capac-ity of the soil layer （SOL_AWC） were observed to be the most sensitive parameters for modeling the pre-sent watershed. It was also found that the maximum runoff occurred in sub-watershed number 40 （SW#40）, while the maximum sediment yield was 50 t.a ^1 for SW#36, which comprised barren land. The average evapotranspiration for the basin was 411.55 mm.a ^1. The calibrated model can be utilized in future to facilitate investigation of the impacts of LULC, climate change, and soil erosion.

Land Use/Land Cover Change Detection in Pokhara Metropolitan, Nepal Using Remote Sensing

Land use and land cover are essential for maintaining and managing the natural resources on the earth surface. A complex set of economic, demographic, social, cultural, technological, and environmental processes usually result in the change in the land use/land cover change (LULC). Pokhara Metropolitan is influenced mainly by the combination of various driving forces: geographical location, high rate of population growth, economic opportunity, globalization, tourism activities, and political activities. In addition to this, geographically steep slope, rugged terrain, and fragile geomorphic conditions and the frequency of earthquakes, floods, and landslides make the Pokhara Metropolitan region a disaster-prone area. The increment of the population along with infrastructure development of a given territory leads towards the urbanization. It has been rapidly changing due to urbanization, industrialization and internal migration since the 1970s. The landscapes and ground patterns are frequently changing on time and prone to disaster. Here a study has been carried to study on LULC for the last 18 years (2000-2018). The supervised classification on Landsat Imagery was performed and verified the classification through computing the error matrix. Besides, the water bodies and vegetation area were extracted through the Normalized Difference Water Index (NDWI) and Normalized Difference Vegetation Index (NDWI) respectively. This research shows that during the last 18 years the agricultural areas diminishing by 15.66% while urban area is increasing by 13.2%. This research is beneficial for preparing the plan and policy in the sustainable development of Pokhara Metropolitan.

Improved spatial resolution in soil moisture retrieval at arid mining area using apparent thermal inertia

A surface soil moisture model with improved spatial resolution was developed using remotely sensed apparent thermal inertia（ATI）.The model integrates the surface temperature derived from TM/ETM＋ image and the mean surface temperature from MODIS images to improve the spatial resolution of soil temperature difference based on the heat conduction equation,which is necessary to calculate the ATI.Consequently,the spatial resolution of ATI and SMC can be enhanced from 1 km to 120 m（TM） or 60m（ETM＋）.Moreover,the enhanced ATI has a much stronger correlation coefficient（R^2） with SMC（0.789） than the surface reflectance（0.108） or the ATI derived only from MODIS images（0.264）.Based on the regression statistics of the field SMC measurement and enhanced ATI,a linear regression model with an RMS error of 1.90%was found.

Determination of regional distribution of crop transpiration and soil water use efficiency using quantitative remote sensing data through inversion

A two-layer model used to get the estimated values of crop transpiration by inversion using remote sensing data, which has been proved effective at some agricultural-ecological sta-tions, is first discussed. An important part of it is the temperature separation model (in which thesurface temperature in a mixed pixel is separated into soil surface temperature and crop canopysurface temperature) on the basis of bi-temporal radiometric temperature in a mixed pixel and its thermal inertia. To improve the inversion, the authors put forward some new algorithms, including an algorithm for the estimation of regional emissivities, a static feedback algorithm using surfacetemperature for the extension of air temperature at ecological stations to the region surroundingthem and a spatial extension algorithm for calculating the wind speed 2 m above the ground withsurface roughness and radiometric temperature. Finally, regional distributions of crop transpiration (CT) and soil water use efficiency (SWUE) in North China were calculated pixel by pixel usingNOAA-AVHRR data and surface measurements and calibrations. The results provide a way toassess the effects of various agricultural practices on SWUE by using remote sensing data inNorth China in spring.

基于Landsat 8的节水改造背景下盐渍化土壤含盐量反演

为探明沈乌灌域节水改造后因渠道衬砌、引排水量减少引起的土壤含盐量时空分布特征及变化规律,采用区域土壤信息定点监测,结合经典统计学、空间插值以及机器学习建模反演等技术手段,利用Landsat 8卫星获取光谱数据,通过对实测土壤含盐量、光谱指数及波段反射率进行处理,运用Adaboost回归、BP神经网络回归、梯度提升树回归、KNN回归、决策树回归、随机森林回归方法构建了沈乌灌域土壤含盐量空间反演模型。采用最优反演模型对沈乌灌域土壤含盐量空间分布特征进行了遥感反演。结果表明:通过全变量单一回归法筛选出相关系数大于0.55的9个光谱因子,使用SPSS PRO软件构建6种机器学习反演模型,对比6种反演模型精度,验证集决定系数R2由大到小依次为随机森林回归、梯度提升树回归、Adaboost回归、KNN回归、决策树回归、BP神经网络回归。其中随机森林回归模型的拟合精度最佳,训练集与验证集的决定系数R2分别为0.834和0.86,说明随机森林回归模型的反演效果较好。反演结果表明:节水改造后非盐渍土面积增加391.7 km^(2),占灌域总面积的21%,中度盐渍土面积、重度盐渍土面积、盐土面积分别减少95.61、63.37、45.7 km^(2),分别占灌域总面积的5%、3%、2%。综上所述,节水改造工程完成后,沈乌灌域土壤盐渍化程度减轻,作物生长安全区面积增加,但由于渠道衬砌以及引排水量减少,土壤盐分淋洗效果减弱,土壤盐分在灌域内部运移,整体土壤环境得到改善,局部地区出现盐分聚集。

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.

基于Radarsat2与Landsat8协同反演植被覆盖地表土壤水分的一种新方法

主动微波遥感与被动光学遥感在反演地表土壤水分方面分别具有各自的优缺点,为了将这两者的优势结合弥补缺点,提出了一种基于Radarsat 2与Landsat 8数据协同反演植被覆盖地表土壤水分的半经验耦合模型.该模型基于水云模型,将光学遥感反演得到的植被冠层含水量作为水云模型的关键输入参数,并同时考虑植被冠层与土壤以及其之间的部分对雷达后向散射系数的影响,以此来去除雷达回波中的植被部分.最后选用内蒙古呼伦贝尔市额尔古纳市大兴安岭西侧研究区的Radarsat 2与Landsat 8遥感数据,利用新的耦合模型反演得到植被覆盖区土壤水分含量,并利用地面测量数据对模型进行验证.结果表明:利用Landsat 8数据反演植被含水量算法精度较高(R2=0.89),论文提出的耦合模型反演植被覆盖地表土壤水分精度比之前算法也有了较大的提高,其中HH极化效果最好,R2由0.27提高至0.65.这表明该耦合模型具有较好的反演精度,可以应用于植被覆盖区土壤水分含量的反演.

基于Landsat遥感影像解译的神农架林区近30年土地覆盖动态变化

利用神农架林区1987年、2000年、2013年Landsat卫星遥感影像,结合地面调查信息,运用ERDAS软件分别解译出这3个时期地表覆盖类型,同时对比3个时期地表覆盖类型的变化,统计分析出3个时期神农架林区森林变化面积和来源。结果显示:1987—2000年森林面积增长缓慢,净增长了14.70 km2,变化主要来自灌丛和草地的转化;2000—2013年期间森林面积增长迅速,净增长了207.49 km2,变化主要来自灌丛、草地和农田的转化。运用遥感技术连续、宏观、动态地监测神农架林区地表覆盖变化,不仅丰富了神农架林区的本底资料,同时也为生态环境监测与生物多样性保护提供了重要的数据。

基于遥感影像的阿拉尔垦区不同土地利用类型土壤有机质含量研究

土壤有机质是土壤肥力的重要指标,对阿拉尔垦区土壤有机质空间分布制图可以更好了解其分布和变化规律。本研究以阿拉尔垦区为研究区,基于257个表层土壤有机质含量数据,采用监督分类法将研究区划分为5种典型土地利用类型,提取9种不同的植被指数作为建模因子,采用随机森林算法进行建模,对研究区内不同土地利用类型土壤有机质含量和空间分布情况进行对比分析。研究结果表明,随机森林(RF)模型能够准确评估土壤有机质含量,其建模集R2值为0.73,RPD值为1.87,RMSE值为1.59g·kg^(-1);验证集R^(2)值为0.71,RPD值为1.91,RMSE值为1.59g·kg^(-1)。基于RF模型对阿拉尔垦区不同土地利用类型土壤有机质含量进行制图,结果表明,土壤有机质由耕地土壤向外围区域递减,耕地土壤有机质含量最多,荒漠的有机质含量最少,林草地和未利用地有机质含量适中呈现西高东低的趋势。研究结果可为阿拉尔垦区土壤肥力提升以及土壤有机质监测提供科学依据。

Progresses on microwave remote sensing of land surface parameters

Highly accurate observations at various scales on the land surface are urgently needed for the studies of many areas,such as hydrology,meteorology,and agriculture.With the rapid development of remote sensing techniques,remote sensing has had the capacity of monitoring many factors of the Earth's land surface.Especially,the space-borne microwave remote sensing systems have been widely used in the quantitative monitoring of global snow,soil moisture,and vegetation parameters with their all-weather,all-time observation capabilities and their sensitivities to the characteristics of land surface factors.Based on the electromagnetic theories and microwave radiative transfer equations,researchers have achieved great successes in the microwave remote sensing studies for different sensors in recent years.This article has systematically reviewed the progresses on five research areas including microwave theoretical modeling,microwave inversion on soil moisture,snow,vegetation and land surface temperatures.Through the further enrichment of remote sensing datasets and the development of remote sensing theories and inversion techniques,remote sensing including microwave remote sensing will play a more important role in the studies and applications of the Earth systems.

The potential information in the temperature difference between shadow and sunlit of surfaces and a new way of retrieving the soil moisture

The thermal inertia and plant water stress index are oftenadopted to estimate soil moisture available for crops or plants. However, it is not very easy to obtain two temporal temperatures for thermal inertia model and air temperature for the plant water stress mode. Shadows of ground objects are often referred to noise on visible and near infrared remote sensing. But the difference of temperature between shadows and sunlit contains rich information concerning with heat-water status for soil. This paper presented a new way to excavate just by temperature difference usually between shadow and sunlit surface. Experiments validated the ideal. We can adopt thermal camera to measure the differences in the field measurements. However, we must use inversion based on multianglar thermal infrared remote sensing data in airborne and spaceborne. An inverting model was also presented by using Monte-Carlo and the least square method. Results show that this way is feasible.

基于Landsat 8 OLI卫星遥感数据的黄前水库水源地保护区水土流失监测

近年来,为了提升饮用水水源地的综合监管水平,遥感监测技术得到了广泛应用。本文中基于landsat8 OLI卫星遥感数据,采用ENVI、Arc GIS等遥感图像处理技术,研究了黄前水库水源地保护区的植被覆盖度及水土流失分布特征。结果表明:黄前水库饮用水水源地保护区的林草覆盖度较高,占保护区总面积的57.32%;而水土流失较为严重,土壤侵蚀面积占55.30%,其中,以轻度、中度为主。该成果为黄前水库饮用水水源地保护区的水土流失监测和生态环境综合治理提供了技术支撑。

基于混合象元分解的Landsat8与MODIS数据融合反演土壤墒情方法研究

【目的】及时准确地获取灌区土壤墒情信息。【方法】以河南省焦作市广利灌区为研究对象,利用Landsat8及MODIS遥感数据分别以表观热惯量及植被供水指数法反演土壤墒情,以混合象元分解的植被和土壤的丰度作为权重因子,对2种方法反演的土壤墒情进行了融合计算。【结果】利用植被供水指数法和表观热惯量反演的土壤含水率与实测含水率相关系数分别为0.47和0.51,同时将2种方法相结合得到的反演结果精度更高,实测含水率与计算的土壤含水率相关系数达到0.73。【结论】融合方法可以更好地计算灌区非均匀覆盖区的土壤墒情。

Assessment of Spatial Expansion of Rift Valley Lakes Using Satellite Data

The present work assessed the expansion and fluctuation of Lake Nakuru in Kenya by using satellite data and information. Surface water magnitude was measured from optical sensors, such as Landsat. ENVI software was used to process and analyze data from the satellite images. The data was then used to create shapefile to get the area of the lake only. The shapefiles were classified using both Supervised and Unsupervised classification, and the area of the lake was obtained in hectares. The obtained area in hectares was recorded in a table and graphs were plotted to show the trend of the lake in the years 1972-2019. Furthermore, correlation was done by assuming the area of the shapefile before any classification is more accurate, therefore it was compared with the other results obtained by using different methods. Maximum likelihood gave the best correlation values. For R2 it gave 0.8627 and R was 0.9312.

遥感技术新进展赋能水利行业应用

随着遥感技术的不断发展和水利信息化进程的加快,水利遥感有了飞速的发展,与水利现代化发展同步。目前,遥感技术在水利行业的应用范围非常广,在为水利高质量发展提供有力支撑和强力驱动的数字孪生水利建设中发挥了重要的作用。近十多年来,快速发展的遥感技术为提升水利遥感应用能力提供了强有力的支撑,具体表现在数据源的丰富化和多源化、数据获取的速度和效率显著提升、定量估算与反演精度大大提高、专题信息可获得性不断增加、数据处理和信息提取的智能化水平取得长足进步。介绍了遥感技术发展赋能水利遥感应用领域的现状和前景展望,为遥感技术赋能水利新质生产力提供参考。