Monitoring acidic water in a polluted river with hyperspectral remote sensing (HyMap)

Abstract

Sulphide mine waste extensively contaminates the Odiel River (southwest Spain), releasing sulphuric acid into the water body. Acidic water in this river precipitates and dissolves variably hydrated iron sulphate in a complex geological pattern controlled by climate. Local abrupt changes in the water pH in the vicinity of highly contaminated tributaries can be mapped by means of imaging spectroscopy using hyperspectral remote sensing (HyMap) data. Also, increased pH through mixing of acidic river water with marine water can be detected when the river reaches the area influenced by sea tides. Mapping the quality of water with hyperspectral data is confounded by vegetation, either dry or wet, rooted or floating. The spectral features of acidic water measured with a field spectrometer revealed the spectral influence of green vegetation, similar to the influence of the depth and transparency of water. Careful mapping of such parameters with HyMap data must therefore precede any spectral evaluation of water related to acidity in a river course. The spectral features detectable by HyMap data and associated with pH changes caused by contamination in river water by iron sulphide mine waste, and their controls, are described and references established for routine monitoring through hyperspectral image processing.     

The fetch effect on aeolian sediment transport on a sandy beach: a case study from Magilligan Strand,Northern Ireland

Experiments were conducted on Magilligan Strand, Northern Ireland, to assess the influence of the fetch effect on aeolian sediment transport. During each experiment surface sediments were uniformly dry and unhindered by vegetation or debris. The leading edge of erodible material was well defined, with the limit of wave up‐rush demarcating the wet–dry boundary; the work was conducted during low tides. A number of electronic and integrating traps were utilised, with two ultrasonic anemometers used to measure wind direction and velocity at 1 Hz. The combination of 1^o direction data and trap locations resulted in a range of fetch distances, from 2 to 26 m. Data integrated over 15‐minute intervals (corresponding to the integrating trap data) revealed a distinct trend for all the experiments. An initial rapid increase in the transport rate occurred over a short distance (4–9 m). This maximum transport rate was maintained for a further 5–6 m before a steady decay in the flux followed, as fetch distance increased. A measured reduction in wind speed (6–8%) across the beach suggests a negative feedback mechanism may be responsible for the diminishing transport rate: the saltating grains induce energy dissipation, thus reducing the capability of the wind to maintain transport. For one experiment, the presence of compact sediment patches may also have contributed to the reduction of the transport rate. The decay trend calls into question the utility of the fetch effect as an important parameter in aeolian studies that seek to understand sediment budgets of the foredune‐beach zone. Copyright © 2016 John Wiley & Sons, Ltd.     

利用陆基高光谱遥感捕捉太湖蓝藻水华日内快速变化过程

受蓝藻自身垂直迁移和频繁风浪扰动影响,太湖蓝藻水华漂浮混合和迁移堆积等变化迅速,在传统的湖面定位和断面监测中总感觉蓝藻水华有些"来无影、去无踪",限制了对其形成过程、驱动机制和防控治理的深入认识.卫星遥感可以实现蓝藻水华空间分布同步观测,但由于观测频次的限制很难捕捉蓝藻水华快速动态变化过程.本文利用与杭州海康威视数字技术股份有限公司联合自主研发的陆基（地基、岸基或者平台、船舶、桩基等能固定安装的均可）高光谱多参数水质遥感监测仪,架设于中国科学院太湖湖泊生态系统研究站（简称太湖站）水上观测场,通过对叶绿素a浓度及其他关键水质参数秒-分钟级的连续观测,有效捕捉了一天内蓝藻水华短期突然和快速变化过程.研究结果显示,在微风和小风条件下蓝藻容易在表层水体漂浮,盛行西北风驱动湖面开敞水域蓝藻水华快速漂浮集聚到太湖站岸边,短短半小时内表层水体叶绿素a浓度可以由10 μg/L快速攀升到100 μg/L以上,一天内会出现多个叶绿素a峰值,清晰展示了蓝藻快速日内动态变化过程.受蓝藻快速日内变化影响,透明度、总氮、总磷和高锰酸盐指数等水质参数也呈现出快速日内变化,叶绿素a浓度与透明度存在极显著负相关,与总氮、总磷和高锰酸盐指数存在极显著正相关,叶绿素a能解释总氮、总磷80%以上的变化,说明蓝藻短期内的漂浮和集聚深刻影响到湖泊水质.     

Quantification of bedform dynamics and bedload sediment flux in sandy braided rivers from airborne and satellite imagery

Images from specially-commissioned aeroplane sorties (manned aerial vehicle, MAV), repeat unmanned aerial vehicle (UAV) surveys, and Planet CubeSat satellites are used to quantify dune and bar dynamics in the sandy braided South Saskatchewan River, Canada. Structure-from-Motion (SfM) techniques and application of a depth-brightness model are used to produce a series of Digital Surface Models (DSMs) at low and near-bankfull flows. A number of technical and image processing challenges are described that arise from the application of SfM in dry and submerged environments. A model for best practice is presented and analysis suggests a depth-brightness model approach can represent the different scales of bedforms present in sandy braided rivers with low-turbidity and shallow (< 2 m deep) water. The aerial imagery is used to quantify the spatial distribution of unit bar and dune migration rate in an 18 km reach and three ~1 km long reaches respectively. Dune and unit bar migration rates are highly variable in response to local variations in planform morphology. Sediment transport rates for dunes and unit bars, obtained by integrating migration rates (from UAV) with the volume of sediment moved (from DSMs using MAV imagery) show near-equivalence in sediment flux. Hence, reach-based sediment transport rate estimates can be derived from unit bar data alone. Moreover, it is shown that reasonable estimates of sediment transport rate can be made using just unit bar migration rates as measured from 2D imagery, including from satellite images, so long as informed assumptions are made regarding average bar shape and height. With recent availability of frequent, repeat satellite imagery, and the ease of undertaking repeat MAV and UAV surveys, for the first time, it may be possible to provide global estimates of bedload sediment flux for large or inaccessible low-turbidity rivers that currently have sparse information on bedload sediment transport rates. © 2018 The Authors. Earth Surface Processes and Landforms published by John Wiley & Sons Ltd.     

Impact of spatial variations of land surface parameters on regional evaporation: a case study with remote sensing data

Most precipitation in watersheds is consumed by evaporation, thus techniques to appraise regional evaporation are important to assess the availability of water resources. Many algorithms to estimate evaporation from remotely sensed spectral data have been developed in the recent past. In addition to differences in the physical parameterization of surface fluxes, these algorithms have different solutions for describing spatial variations of the parameters in the soil–vegetation–atmosphere–transfer (SVAT) continuum. In this study, the necessity to spatially distinguish SVAT parameters for computing surface heat fluxes is analysed for the Naivasha watershed in the Kenyan Rift Valley. Landsat Thematic Mapper (TM) spectral data have been used to first delineate the watershed into 15 hydrological units using surface temperature, normalized difference vegetation index and surface albedo as attributes. Thereafter, semi‐empirical relationships between these TM‐based parameters and other SVAT parameters have been applied to compute the spatial variation of SVAT parameters and the associated evaporation from the different hydrological units. The impact of using watershed‐constant or watershed‐distributed SVAT parameters on the fluxes is analysed. The determination of watershed averaged evaporation with area‐aggregated SVAT parameters is feasible without significant loss of accuracy. Distributed evaporation in heterogeneous watersheds, however, can be investigated only with remote sensing flux algorithms that can account for spatially variable air temperature, surface roughness, surface albedo and the stability correction of the temperature profile due to buoyancy. Erroneous results can be expected if area‐aggregated SVAT parameters are used to calculate local evaporation. As most of the recently developed remote sensing flux algorithms are based on areal constant SVAT parameters, direct applications in watersheds are still limited. Copyright © 2001 John Wiley & Sons, Ltd.     

On the usefulness of remote sensing input data for spatially distributed hydrological modelling: case of the Tarim River basin in China

The ecological situation of the Tarim River basin in China seriously declined since the early 1950s, mainly due to a strong increase in water abstraction for irrigation purposes. To restore the ecological system and support sustainable development of the Tarim River basin region in China, more hydrological studies are demanded to properly understand the processes of the watershed and efficiently manage the water resources. Such studies are, however, complicated due to the limited data availability, especially in the mountainous headwater regions of the Tarim River basin. This study investigated the usefulness of remote sensing (RS) data to overcome that lack of data in the spatially distributed hydrological modelling of the basin. Complementary to the conventional station‐based (SB) data, the RS products that are directly used in this study include precipitation, evapotranspiration and leaf area index. They are derived from raw image data of the Chinese Fengyun meteorological satellite and from the Moderate Resolution Imaging Spectroradiometer (MODIS). The MODIS land surface temperature was used to calculate the atmospheric temperature lapse rate to describe the temperature dependency on topographical variations. Moreover, MODIS‐based snow cover images were used to obtain model initial conditions and as validation reference for the snow model component. Comparison of model results based on RS input versus conventional SB input exhibited similar results in terms of high and low river runoff extremes, cumulative runoff volumes in both runoff and snow melting seasons and spatial and temporal variability of snow cover. During summer time, when the snow cover shrinks in the permanent glacier region, it was found that the model resolution influences the model results dramatically, hence, showing the importance of detailed (RS based) spatially distributed input data. Copyright © 2011 John Wiley & Sons, Ltd.     

A case study of airborne and satellite remote sensing of a spring bloom event in the Gulf of Finland

The concentrations of chlorophyll-a (chl-a), total suspended solids (TSS) and the absorption coefficient of colored dissolved organic matter (a_CDOM(400)) are estimated in Case II waters using medium resolution imaging spectrometer (MERIS) satellite (full resolution [FR] level 1b, 300 m resolution) and AISA airborne spectrometer data acquired during a spring bloom in the Gulf of Finland, Baltic Sea on April 27, 2004. The accuracy of the estimation is analyzed using empirical band-ratio algorithms together with in situ observations that include water samples analyzed in a laboratory (variation ranges: 22–130 μg/l, 2.9–20 mg/l, and 1.29–2.61 m⁻¹ for chl-a, TSS and a_CDOM(400), respectively). Additional in situ estimates (transects) on these characteristics are available through absorption and scattering coefficients measured with an ac-9 absorption and attenuation meter installed in a flow-through system. The retrieval accuracy (R²) of all three water quality characteristics with MERIS data is close to or above 0.9, while the RMSE is 7.8 μg/l (22%), 0.74 mg/l (16%) and 0.08 m⁻¹ (5%), for chl-a, TSS and a_CDOM(400), respectively. The validity of the chl-a algorithm is tested using nine additional data points. The BIAS-error for these points is 5.2 μg/l and the RMSE is 10.6 μg/l. The effects of changes in the atmospheric characteristics on band-ratio algorithms in cases where no concurrent in situ reference data are available are analyzed using the MODerate spectral resolution atmospheric TRANSmittance algorithm and computer model (MODTRAN). The additional error due to these changes is estimated to be below 20% for the applied ratio algorithms. The water quality data available in the level 2 MERIS-product distributed by the European Space Agency did not include valid results for the date investigated here.     

Lichens and mosses moisture content assessment through high‐spectral resolution remote sensing technology: a case study of the Hudson Bay Lowlands,Canada

Assessing moisture contents of lichens and mosses using ground‐based high‐spectral resolution spectrometers offers immense opportunities for a comprehensive monitoring of peatland moisture status by satellite/airborne imagery. This study investigates the impact of various moisture conditions of common subarctic lichen and moss species upon the spectral signatures obtained. The lichens are Cladina stellaris and Cladina rangiferina, and the mosses are Dicranum elongatum and Tomenthypnum nitens. Reflectance and moisture content measurements of these species were made in a laboratory setting, while maintaining the natural moisture conditions of the samples; once the moisture and spectral measurements were complete, the samples were returned to the field and placed in their natural setting, continuously receiving moisture from precipitation and groundwater and losing water through evaporation and drainage. Changes in reflectance of the visible to shortwave infrared (SWIR) range (400–2500 nm) at various moisture contents were examined, as well as the potential of current spectral reflectance indices to evaluate the plants' moisture contents was examined. Results indicate that the SWIR region is useful in identifying variations in plants moisture conditions, while the unique spectral signatures of the lichens and mosses in the visible and near‐infrared range suggest that these species may be detected by satellite and airborne imagery. Of current spectral indices, the normalized difference infrared index (NDII) was most successful in identifying the above plants' moisture content (details are discussed in the paper). Future study should focus on the development of improved moisture content spectral indices, as well as upscaling reflectance data and spectral indices. Copyright © 2010 John Wiley & Sons, Ltd.     

The relative impact of climate change and urban expansion on peak flows: a case study in central Belgium

An essential part of hydrological research focuses on hydrological extremes, such as river peak flows and associated floods, because of their large impact on economy, environment, and human life. These extremes can be affected by potential future environmental change, including global climate change and land cover change. In this paper, the relative impact of both climate change and urban expansion on the peak flows and flood extent is investigated for a small‐scale suburban catchment in Belgium. A rainfall‐runoff model was coupled to a hydrodynamic model in order to simulate the present‐day and future river streamflow. The coupled model was calibrated based on a series of measured water depths and, after model validation, fed with different climate change and urban expansion scenarios in order to evaluate the relative impact of both driving factors on the peak flows and flood extent. The three climate change scenarios that were used (dry, wet winter, wet summer) were based on a statistical downscaling of 58 different RCM and GCM scenario runs. The urban expansion scenarios were based on three different urban growth rates (low, medium, high urban expansion) that were set up by means of an extrapolation of the observed trend of urban expansion. The results suggest that possible future climate change is the main source of uncertainty affecting changes in peak flow and flood extent. The urban expansion scenarios show a more consistent trend. The potential damage related to a flood is, however, mainly influenced by land cover changes that occur in the floodplain. Copyright © 2011 John Wiley & Sons, Ltd.     

Application of ensemble kalman filter to geophysical parameters retrieval in remote sensing:A case study of kernel-driven BRDF model inversion

Remote sensing can provide multi-spatial resolution, multi-temporal resolution multi-spectral band and multi-angular data for the observation of land surface. At present, one of research focuses is how to make the best of these data to retrieve geophysical parameters in conjunction with their a priori knowledge and simul-taneously consider the influence of data uncertainties on inversion results[1-5]. The essence of remote sensing lies in inversion. It is difficult to precisely retrieve parame…     

MERIS影像水环境遥感大气校正算法评价——以鄱阳湖叶绿素a浓度反演为例

MERIS是2002年发射的在轨运行近10年的ENVISAT-1卫星上搭载的主要传感器之一,在波段设置和辐射灵敏度等方面有非常突出的优势,能够较好地运用于Ⅱ类水体叶绿素a浓度反演,但Ⅱ类水体的大气校正仍然是亟待解决的一个关键问题.以我国第一大淡水湖——鄱阳湖为研究区域,采用FLAASH、6S、BEAM和QUAC共4种大气校正算法对2005和2011年具有同步实测光谱数据的鄱阳湖ENVISAT-1卫星MERIS影像进行大气校正处理,并对12种叶绿素a浓度反演模型的波段组合因子进行大气校正效果的对比分析.结果表明:(1)4种大气校正中,大气校正结果精度由高到低表现为FLAASH6SBEAMQUAC,平均相对误差分别为31.13%、31.88%、69.48%和42.64%;决定系数(R2)分别为0.60、0.57、0.38和0.24;(2)在12种叶绿素a浓度反演模型的波段组合因子中,FLAASH得到的结果最优,其次是6S,BEAM和QUAC最差,在FLAASH算法中,由665、708和753 nm 3个波段遥感因子((Rrs(510)/[Rrs(443)/Rrs(560)])组成的模型精度最高,平均相对误差为25.12%,R2为0.74.建议采用FLAASH大气校正结果组成这个波段组合进行鄱阳湖叶绿素a浓度反演.     

Remote sensing and GIS‐based flood vulnerability assessment of human settlements: a case study of Gangetic West Bengal,India

Flooding due to excessive rainfall in a short period of time is a frequent hazard in the flood plains of monsoon Asia. In late September 2000, a devastating flood stuck Gangetic West Bengal, India. This particular event has been selected for this study. Instead of following the conventional approach of flooded area delineation and overall damage estimation, this paper seeks to identify the rural settlements that are vulnerable to floods of a given magnitude. Vulnerability of a rural settlement is perceived as a function of two factors: the presence of deep flood water in and around the settlement and its proximity to an elevated area for temporary shelter during an extreme hydrological event. Landsat ETM⁺ images acquired on 30 September 2000 have been used to identify the non‐flooded areas within the flooded zone. Particular effort has been made to differentiate land from water under cloud shadow. ASTER digital elevation data have been used to assess accuracy and rectify the classified image. The presence of large numbers of trees around rural settlements made it particularly difficult to extract the flooded areas from their spectral signatures in the visible and infrared bands. ERS‐1 synthetic aperture radar data are found particularly useful for extracting the settlement areas surrounded by trees. Finally, all information extracted from satellite imageries are imported into ArcGIS, and spatial analysis is carried out to identify the settlements vulnerable to river inundation. Copyright © 2005 John Wiley & Sons, Ltd.     

Effects of lateral confinement in natural and leveed reaches of a gravel‐bed river: Snake River,Wyoming, USA

This study examined the effects of natural and anthropogenic changes in confining margin width by applying remote sensing techniques – fusing LiDAR topography with image‐derived bathymetry – over a large spatial extent: 58 km of the Snake River, Wyoming, USA. Fused digital elevation models from 2007 and 2012 were differenced to quantify changes in the volume of stored sediment, develop morphological sediment budgets, and infer spatial gradients in bed material transport. Our study spanned two similar reaches that were subject to different controls on confining margin width: natural terraces versus artificial levees. Channel planform in reaches with similar slope and confining margin width differed depending on whether the margins were natural or anthropogenic. The effects of tributaries also differed between the two reaches. Generally, the natural reach featured greater confining margin widths and was depositional, whereas artificial lateral constriction in the leveed reach produced a sediment budget that was closer to balanced. Although our remote sensing methods provided topographic data over a large area, net volumetric changes were not statistically significant due to the uncertainty associated with bed elevation estimates. We therefore focused on along‐channel spatial differences in bed material transport rather than absolute volumes of sediment. To complement indirect estimates of sediment transport derived by morphological sediment budgeting, we collected field data on bed mobility through a tracer study. Surface and subsurface grain size measurements were combined with bed mobility observations to calculate armoring and dimensionless sediment transport ratios, which indicated that sediment supply exceeded transport capacity in the natural reach and vice versa in the leveed reach. We hypothesize that constriction by levees induced an initial phase of incision and bed armoring. Because levees prevented bank erosion, the channel excavated sediment by migrating rapidly across the restricted braidplain and eroding bars and islands. Copyright © 2017 John Wiley & Sons, Ltd.     

Land use changes,torrent control works and sediment mining: effects on channel morphology and sediment flux,case study of the Reno River (Northern Italy)

As with most Italian rivers, the Reno River has a long history of human modification, related also to morphological changes of the lower Po River since Roman times, but in the last decades, significant land use changes in the headwaters, dam construction, torrent control works and extensive bed material mining have caused important channel morphology and sediment budget changes. In this paper, two main types of channel adjustment, riverbed incision and channel narrowing, are analysed. Riverbed degradation is discussed by comparing four different longitudinal profiles surveyed in 1928, 1951, 1970 and 1998 in the 120 km long reach upstream of the outlet. The analysis of channel narrowing is carried out by comparing a number of cross‐sections surveyed in different years across the same downstream reach. Field sediment transport measurements of seven major floods that occurred between 2003 and 2006 are compared with the bedload transport rates predicted by the most renowned equations. The current low bedload yield is discussed in terms of sediment supply limited conditions due to land use changes, erosion‐control works and extensive and out of control bed material mining that have affected the Reno during the last decades. Copyright © 2011 John Wiley & Sons, Ltd.     

Empirical and conceptual modelling of the suspended sediment dynamics in a large tropical African river: the Upper Niger river basin

A 7-year sediment transport monitoring on the Upper Niger rivers was used to study the relationship between suspended sediment concentration and river discharge. During annual floods, these relationships show positive hysteresis. This paper presents the results of two models that estimate the time evolution of suspended sediment concentration using water discharge data only. The first model is based on a statistical approach using two relationships, one for the rising stage period of the flood and one for the recession period of the annual flood; the second model is a lumped conceptual one; it supposes that the sediment flux observed in the river comes from two different sources of sediment and that these two sources may be regarded as two different reservoirs. The erosion of the first reservoir represents hillslope erosion observed during the runoff season. Sediment supply from this ‘reservoir’ is limited in time because depletion occurs during the runoff season. The second reservoir is unlimited in time and quantity and its erosion represents contributions coming from bank erosion and mobilisation of deposits in the channel network.

Both of the models are compared with a simple rating curve based model. The model results show that the conceptual model has the highest efficiency to reproduce from weekly discharge only the time evolution of weekly suspended sediment concentrations, the time evolution of weekly sediment fluxes, and the global annual sediment yields.     

Hydrologic-hydraulic modeling of sediment transport along the main stem of a watershed: role of tributaries and channel geometry

ABSTRACT

Current estimations of sediment transport at the watershed scale are limited by the difficulty of accurately simulating the sediment transfer along the main stem. The typical approach to simulating watershed sediment transport involves the adoption of hydrologic sediment routing schemes that do not fully capture the contribution and timing of side tributaries, and the inclusion of a simplified channel geometry that does not include its hydraulic feedback. In this paper, we present the results of a coupled hydrologic-hydraulic model of sediment transport applied to a small watershed of Iowa. The model was developed to simulate both the hydrologic network and non-equilibrium sediment transport that occur during a flood. The model results highlight the importance of including side tributaries in order to capture a realistic duration of shear stress that ultimately affects sediment transport. Comparisons with bank erosion measurements indicate that the presented approach is also promising to estimate sediment sources along the main stem.     

Assessment of the geometry and volumes of small surface water reservoirs by remote sensing in a semi-arid region with high reservoir density

Water fluxes in highly impounded regions are heavily dependent on reservoir properties. However, for large and remote areas, this information is often unavailable. In this study, the geometry and volume of small surface reservoirs in the semi-arid region of Brazil were estimated using terrain and shape attributes extracted by remote sensing. Regression models and data classification were used to predict the volumes, at different water stages, of 312 reservoirs for which topographic information is available. The power function used to describe the reservoir shapes tends to overestimate the volumes; therefore, a modified shape equation was proposed. Among the methods tested, four were recommended based on performance and simplicity, for which the mean absolute percentage errors varied from 24 to 39%, in contrast to the 94% error achieved with the traditional method. Despite the challenge of precisely deriving the flooded areas of reservoirs, water management in highly reservoir-dense environments should benefit from volume prediction based on remote sensing.     

Assessment of soil erosion and sediment delivery ratio using remote sensing and GIS： a case study of upstream Chaobaihe River catchment, north China

Soil erosion in catchment areas reduces soil productivity and causes a loss of reservoir capacity. Several parametric models have been developed to predict soil erosion at drainage basins, hill slopes and field levels. The well-known Universal Soil Loss Equation （USLE） represents a standardized approach. Miyun reservoir, which sits on Chaobaihe River, is the main surface source of drinking water for Beijing, the capital of China. Water and soil loss are the main reasons for sediment to enter a reservoir. Sediment yield is assessed using a version of the universal soil loss equation modified by Chinese researchers. All year 2001 and 2002 data for factors in the equation are obtained from remote sensing or collected to form an analysis database. These factors are computed and mapped using Geographic Information System tools. Based on the complex database, the modified model is developed. Through pixel-based computing the sediment yield per hydrological unit is calculated. The model does not consider sediment deposition occurring on hillslopes. Gross soil loss is often higher than the sum of those measured at catchment outlets. The sediment delivery ratio （SDR） per hydrological unit is also computed. This study analyzes the main contributions of sediment yields on sub-basins of the Chaobaihe River to the Miyun Reservoir, and discusses the possible reasons for the difference between SDRs in 2001 and 2002 at different outlets. The result shows that in the upper basin of the Miyun Reservoir, in 2001 the area of erosion that could be neglected was 8,202.76 km^2, the area of low erosion 3,269.59 km^2, the area of moderate erosion 3,400.97 km^2, the area of high erosion 436.89 km^2, the area of strong erosion 52.19 km^2 and the area of severe erosion 3.13 km^2. The highest soil loss was 70,353 t/km^2. yr in Fengning County in 2001, followed by 64,418 t/km^2. yr by Chicheng County in 2001. The SDR in 2002 was lower than that in 2001. The main reasons are the decreasing rainfall erosivity and total runoff.     

Comparative study of multilayer perceptron-stochastic gradient descent and gradient boosted trees for predicting daily suspended sediment load: The case study of the Mississippi River,U.S.

Monitoring sediment transport is essential for managing and maintaining rivers.Estimation of the sediment load in rivers is fundamental for the study of sediment movement,erosion,and flood control.In the current study,three machine learning models-multi-layer perceptron(MLP),multi-layer perceptron-stochastic gradient descent(MLP-SGD),and gradient boosted tree(GBT)-were utilized to estimate the suspended sediment load(SSL)at the St.Louis(SL)and Chester(CH)stations on the Mississippi River,U.S.Four evaluation criteria including the Correlation Coefficient(CC),Nash Sutcliffe Efficiency(NSE),Scatter Index(SI),and Willmott’s Index(WI)were utilized to evaluate the performance of the used models.A sensitivity analysis of the models to the input variables revealed that the current day discharge variable had the most effect on the SSL at both stations,but in the absence of current-day discharge data(Qt),a combination of input parameters including SSL_t-3,SSL_t-2,SSL_t-1,Q_t-3,Q_t-2,Q_t-1 can be used to estimate the SSL.The comparative outcomes indicated the high accuracy of MLP-SGD-5 model with a CC of 0.983,SI of 0.254,WI of 0.991,and NSE of 0.967 at station CH and the MLP-SGD-6 model with a CC of 0.933,SI of 0.576,WI of 0.961,and NSE of 0.867,respectively,at station SL.The results of MLP models were improved by SGD optimization.Therefore,the MLP-SGD method is recommended as the most accurate model for SSL estimation.     

Estimation of maize yield by using a process-based model and remote sensing data in the Northeast China Plain

Climate change significantly impact on agriculture in recent year, the accurate estimation of crop yield is of great importance for the food security. In this study, a process-based mechanism model was modified to estimate yield of C₄ crop by modifying the carbon metabolic pathway in the photosynthesis sub-module of the RS–P–YEC (Remote-Sensing–Photosynthesis–Yield estimation for Crops) model. The yield was calculated by multiplying net primary productivity (NPP) and the harvest index (HI) derived from the ratio of grain to stalk yield. The modified RS–P–YEC model was used to simulate maize yield in the Northeast China Plain during the period 2002–2011. The 111 statistical data of maize yield from study area was used to validate the simulated results at county-level. The results showed that the Pearson correlation coefficient (R) was 0.827 (p < 0.01) between the simulated yield and the statistical data, and the root mean square error (RMSE) was 712 kg/ha with a relative error (RE) of 9.3%. From 2002 to 2011, the yield of maize planting zone in the Northeast China Plain was increasing with smaller coefficient of variation (CV). The spatial pattern of simulated maize yield was consistent with the actual distribution in the Northeast China Plain, with an increasing trend from the northeast to the southwest. Hence the results demonstrated that the modified process-based model coupled with remote sensing data was suitable for yield prediction of maize in the Northeast China Plain at the spatial scale.