Potential of time‐lapse photography for identifying saturation area dynamics on agricultural hillslopes

Mapping saturation areas during rainfall events is important for understanding the dynamics of overland flow. In this study, we evaluate the potential of high temporal resolution time‐lapse photography for mapping the dynamics of saturation areas (i.e., areas where water is visually ponding on the surface) on the hillslope scale during natural rainfall. We take 1 image per minute over a 100 × 15 m² depression area on an agricultural field in the Hydrological Open Air Laboratory, Austria. The images are georectified and classified by an automated procedure, using grey intensity as a threshold to identify saturation area. The optimum threshold T is obtained by comparing saturation areas from the automated analysis with the manual analysis of 149 images. T is found to be highly correlated with an image brightness characteristic defined as the greyscale image histogram mode M (Pearson correlation r = 0.91). We estimate T as T = M + C where C is a calibration parameter assumed to be constant during each event. The automated procedure estimates the total saturation area close to the manual analysis with mean normalized root mean square error of 9% and 21% if C is calibrated for each event and taken constant for all events, respectively. The spatial patterns of saturation are estimated with a geometric mean accuracy index of 94% as compared to the manual analysis of the same photos. The patterns are tested against field observations for one date as a preliminary demonstration, which yields a root mean square error of the shortest distance between the measured boundary points and the automatically classified boundary as 23 cm. The usefulness of the patterns is illustrated by exploring run‐off generation processes of an example event. Overall, the proposed classification method based on grey intensity is found to process images with highly varying brightnesses well. It is more efficient than the manual tracing for a large number of images, which allows the exploration of surface flow processes at high temporal resolution.     

Ensemble-based characterization of uncertain environmental features

This paper considers the characterization of uncertain spatial features that cannot be observed directly but must be inferred from noisy measurements. Examples of interest in environmental applications include rainfall patterns, solute plumes, and geological features. We formulate the characterization process as a Bayesian sampling problem and solve it with a non-parametric version of importance sampling. All images are concisely described with a small number of image attributes. These are derived from a multidimensional scaling procedure that maps high dimensional vectors of image pixel values to much lower dimensional vectors of attribute values. The importance sampling procedure is carried out entirely in terms of attribute values. Posterior attribute probabilities are derived from non-parametric estimates of the attribute likelihood and proposal density. The likelihood is inferred from an archive of noisy operational images that are paired with more accurate ground truth images. Proposal samples are generated from a non-stationary multi-point statistical algorithm that uses training images to convey distinctive feature characteristics. To illustrate concepts we carry out a virtual experiment that identifies rainy areas on the Earth’s surface from either one or two remote sensing measurements. The two sensor case illustrates the method’s ability to merge measurements with different error properties. In both cases, the importance sampling procedure is able to identify the proposals that most closely resemble a specified true image.     

Reconstructing extreme post‐wildfire floods: a comparison of convective and mesoscale events

In much of western United States destructive floods after wildfire are frequently caused by localized, short‐duration convective thunderstorms; however, little is known about post‐fire flooding from longer‐duration, low‐intensity mesoscale storms. In this study we estimate and compare peak flows from convective and mesoscale floods following the 2012 High Park Fire in the ungaged 15.5 km² Skin Gulch basin in the northcentral Colorado Front Range. The convective storm on 6 July 2012 came just days after the wildfire was contained. Radar data indicated that the total rainfall was 20–47 mm, and the maximum rainfall intensities (upwards of 50 mm h^?1) were concentrated over portions of the watershed that burned at high severity. The mesoscale storm on 9–15 September 2013 produced 220–240 mm of rain but had maximum 15‐min intensities of only 25–32 mm h^?1. Peak flows for each flood were estimated using three independent techniques. Our best estimate using a 2D hydraulic model was 28 m³ s^?1 km^?2 for the flood following the convective storm, placing it among the largest rainfall‐runoff floods per unit area in the United States. In contrast, the flood associated with the mesoscale flood was only 6 m³ s^?1 km^?2, but the long‐duration flood caused extensive channel incision and widening, indicating that this storm was much more geomorphically effective. The peak flow estimates for the 2013 flood had a higher relative uncertainty and this stemmed from whether we used pre‐ or post‐flood channel topography. The results document the extent to which a high and moderate severity forest fire can greatly increase peak flows and alter channel morphology, illustrate how indirect peak flow estimates have larger errors than is generally assumed, and indicate that the magnitude of post‐fire floods and geomorphic change can be affected by the timing, magnitude, duration, and sequence of rainstorms. Copyright © 2017 John Wiley & Sons, Ltd.     

Application of AVHRR to monitoring a climatically sensitive playa. case study: Chott El Djerid,Southern Tunisia

The importance of monitoring changes in the levels of lakes within endorheic basins using remotely sensed data as a means of assessing changes in regional aridity is noted. Large salt playas are highlighted as ephemeral lakes that can display extreme sensitivity to changes in regional rainfall patterns, and which commonly do not have extensively managed catchments. To explore the application of high temporal frequency monitoring of salt playas using remote sensing, the Chott el Djerid, a large salt playa situated in southern Tunisia was targeted. A short time series of 39 Advanced Very High Resolution Radiometer (AVHRR; resolution 1.1 km at nadir) images of the Chott el Djerid (spanning 36 months between 1987 and 1990) were compiled along with climate information from a weather station at Tozeur. Using image histogram manipulation, lake areas were extracted from the time series. A good level of agreement was observed between recorded rainfall events and the presence of surface water on the playa, and for a limited sample of large flood events it was found that there were significant relationships between rainfall, evaporation and estimated lake areas (r² = 98.5, p < 0.001). Overall, these data suggest that contemporary lake formation is largely controlled by temporal changes in effective precipitation within the basin. In addition, it was found that the coefficient of variation of the time series, and a combination of temporal reflectance profiles extracted from it, could be used to give a direct indication of which sedimentary surfaces on the playa are affected by large flood events, and the extent to which these events may be preserved within the recent sedimentary record at these sites. Copyright © 1999 John Wiley & Sons, Ltd.     

Impact of ATOVS Radiance on the Analysis and Forecasts of a Mesoscale Model over the Indian Region During the 2008 Summer Monsoon

Assimilation experiments are performed with the Weather Research and Forecasting (WRF) models’ three-dimensional variational data assimilation (3D-Var) scheme to evaluate the impact of directly assimilating the Advanced Television and Infrared Observation Satellite Operational Vertical Sounder (ATOVS) radiance, including AMSU-A, AMSU-B and HIRS, on the analysis and forecasts of a mesoscale model over the Indian region. The present study is, to our knowledge, the first where the impact of ATOVS radiance has been evaluated on the analysis and forecasts of a mesoscale model over the Indian region. The control (without ATOVS radiance) as well as experimental (which assimilated ATOVS radiance) run were made for 48 h starting at 0000 UTC during the entire July 2008. The impacts of assimilating the radiances from different instruments (e.g., AMSU-A, AMSU-B and HIRS) were measured in comparison to the control run. The assimilation experiments for July 2008 (30 cases) demonstrated a positive impact of the assimilated ATOVS radiance on both the analysis state as well as subsequent short-range forecasts. Relative to the control run, the moisture analysis was improved with the assimilation of AMSU-B and HIRS radiance, while AMSU-A was mainly responsible for improved temperature analysis. The comparison of the model-predicted temperature, moisture and wind with NCEP analysis indicated that a positive forecast impact is achieved from each of the three instruments. HIRS and AMSU-A radiance yielded only a slight positive forecast impact, while AMSU-B radiance had the largest positive forecast impact for moisture, temperature and wind. The comparison of model-predicted rainfall with observed rainfall indicates that ATOVS radiance, particularly AMSU-B and HIRS, impacted the rainfall positively. This study clearly shows that the improved analysis of mid-tropospheric moisture, due to the assimilation of AMSU-B radiances, is a key factor to improve the short-term forecast skill of a mesoscale model.     

Coupled rainfall and water vapour stable isotope time series reveal tropical atmospheric processes on multiple timescales

High-frequency stable isotope data are useful for validating atmospheric moisture circulation models and provide improved understanding of the mechanisms controlling isotopic compositions in tropical rainfall. Here, we present a near-continuous 6-month record of O- and H-isotope compositions in both water vapour and daily rainfall from Northeast Australia measured by laser spectroscopy. The data set spans both wet and dry seasons to help address a significant data and knowledge gap in the southern hemisphere tropics. We interpret the isotopic records for water vapour and rainfall in the context of contemporaneous meteorological observations. Surface air moisture provided near-continuous tracking of the links between isotopic variations and meteorological events on local to regional spatial scales. Power spectrum analysis of the isotopic variation showed a range of significant periodicities, from hourly to monthly scales, and cross-wavelet analysis identified significant regions of common power for hourly averaged water vapour isotopic composition and relative humidity, wind direction, and solar radiation. Relative humidity had the greatest subdiurnal influence on isotopic composition. On longer timescales (weeks to months), isotope variability was strongly correlated with both wind direction and relative humidity. The high-frequency records showed diurnal isotopic variations in O- and H-isotope compositions due to local dew formation and, for deuterium excess, as a result of evapotranspiration. Several significant negative isotope anomalies on a daily scale were associated with the activity of regional mesoscale convective systems and the occurrence of two tropical cyclones. Calculated air parcel back trajectories identified the predominant moisture transport paths from the Southwest Pacific Ocean, whereas moisture transport from northerly directions occurred mainly during the wet season monsoonal airflow. Water vapour isotope compositions reflected the same meteorological events as recorded in rainfall isotopes but provided much more detailed and continuous information on atmospheric moisture cycling than the intermittent isotopic record provided by rainfall. Improved global coverage of stable isotope data for atmospheric water vapour is likely to improve simulations of future changes to climate drivers of the hydrological cycle.     

X射线断层扫描投影图像背景不一致的校准

在X射线断层扫描(X-ray CT)成像过程中,经常会出现射线源、样品和探测器三者之间的相对移动,导致采集的投影图像(Projection image)以及亮场图像(flat field image)的空间位置配准关系出现偏差。这直接影响了投影图像背景的正常扣除,以及后续的CT图像重建。本文利用互相关方法,求出各投影图像背景与探测器原始采集位置之间的不一致量。然后将投影图像和亮场图像作相应变换,最后扣除背景得到校准后的图像。由于该方法对图像灰度较为敏感,所以在对实际样品校准之前,本文先对该样品投影图像及亮场图像进行了照度归一化。实验结果表明,该方法能够有效校正由射线源、样品和探测器之间相对移动造成的CT投影图像背景不一致,获得较好的CT投影图像和重建切片。      

中尺度模拟土壤油污染区探地雷达探测效果分析

为使物理模拟实验效果与实际探测情形更为接近,在室外自然条件下建立中尺度土壤石油污染实验模型,油污染区扩展深度超过1 m,采用实地探测中常用的500 MHz雷达天线进行长期定时探测.通过实测雷达图像特征、土壤含水量含油量分析,并对比前人开展的小尺度室内模拟试验结果,综合评价探地雷达对油污染区的探测效果.研究表明探地雷达探测图像异常特征与污染区扩散阶段密切相关:包气带内油污染区会引起振幅增强;毛细带的油污染区则表现为水位面反射轴附近清晰可辨的高幅异常区,且水位面反射轴呈下凹状;随扩散过程持续进行,异常区下移与水位面反射轴相交,并产生水平扩张.当污染土含油饱和度大于20%时,可通过雷达图像异常区圈定污染范围;当污染土含油饱和度大于15%时,可通过频谱图出现低频响应的位置圈定污染区水平范围.中尺度实验结果与室内小尺度模拟结果具有一致性,可作为油污染区雷达图像异常的解译依据.     

Searching regional rainfall homogeneity using atmospheric fields

The correct identification of homogeneous areas in regional rainfall frequency analysis is fundamental to ensure the best selection of the probability distribution and the regional model which produce low bias and low root mean square error of quantiles estimation. In an attempt at rainfall spatial homogeneity, the paper explores a new approach that is based on meteo-climatic information. The results are verified ex-post using standard homogeneity tests applied to the annual maximum daily rainfall series. The first step of the proposed procedure selects two different types of homogeneous large regions: convective macro-regions, which contain high values of the Convective Available Potential Energy index, normally associated with convective rainfall events, and stratiform macro-regions, which are characterized by low values of the Q vector Divergence index, associated with dynamic instability and stratiform precipitation. These macro-regions are identified using Hot Spot Analysis to emphasize clusters of extreme values of the indexes. In the second step, inside each identified macro-region, homogeneous sub-regions are found using kriging interpolation on the mean direction of the Vertically Integrated Moisture Flux. To check the proposed procedure, two detailed examples of homogeneous sub-regions are examined.     

A mesoscale eddy detection method of specific intensity and scale from SSH image in the South China Sea and the Northwest Pacific

Mesoscale eddies exist almost everywhere in the ocean and play important roles in the ocean circulation of the world. These eddies may cause sound spread singular regions and bring great influences to the upwater ship and underwater aircraft. Due to the lack of hydrographic survey datasets, study of mesoscale eddies has been greatly restricted. Fortunately, satellite altimeter provided an effective way to study mesoscale eddies. An automatic detection algorithm is introduced to detect mesoscale eddies of specific intensity and spatial/temporal scale based on satellite sea surface height (SSH) data and the algorithm is applied in a strong eddy activity region: the South China Sea and the Northwest Pacific. The algorithm includes four steps. The first step is preprocessing of the SSH image, which includes elimination of error SSH data and interpolation. The second step is to detect suspected mesoscale eddies from preprocessed SSH images by dynamic threshold adjustment and morphological method, and the suspected mesoscale eddy detection includes two procedures: suspected mesoscale eddy core region detection and suspected mesoscale eddy brim extraction. The third step is to pick out mesoscale eddies satisfied with specified criteria from suspected mesoscale eddies. The criteria include three items, that is, intensity criterion, spatial scale, criterion and temporal scale criterion. The last step is algorithm performance analysis and verification. The algorithm has the capability of adaptive parameter adjustment, and can extract mesoscale eddies of interested intensity and spatial/temporal scale. The paper can provide a basis for analyzing space-time characteristics of mesoscale eddy in the South China Sea and the Northwest Pacific.     

Sensitivity of the Weather Research and Forecasting (WRF) model to downscaling ratios and storm types in rainfall simulation

Accurate information of rainfall is needed for sustainable water management and more reliable flood forecasting. The advances in mesoscale numerical weather modelling and modern computing technologies make it possible to provide rainfall simulations and forecasts at increasingly higher resolutions in space and time. However, being one of the most difficult variables to be modelled, the quality of the rainfall products from the numerical weather model remains unsatisfactory for hydrological applications. In this study, the sensitivity of the Weather Research and Forecasting (WRF) model is investigated using different domain settings and various storm types to improve the model performance of rainfall simulation. Eight 24‐h storm events are selected from the Brue catchment, southwest England, with different spatial and temporal distributions of the rainfall intensity. Five domain configuration scenarios designed with gradually changing downscaling ratios are used to run the WRF model with the ECMWF 40‐year reanalysis data for the periods of the eight events. A two‐dimensional verification scheme is proposed to evaluate the amounts and distributions of simulated rainfall in both spatial and temporal dimensions. The verification scheme consists of both categorical and continuous indices for a first‐level assessment and a more quantitative evaluation of the simulated rainfall. The results reveal a general improvement of the model performance as we downscale from the outermost to the innermost domain. Moderate downscaling ratios of 1:7, 1:5 and 1:3 are found to perform better with the WRF model in giving more reasonable results than smaller ratios. For the sensitivity study on different storm types, the model shows the best performance in reproducing the storm events with spatial and temporal evenness of the observed rainfall, whereas the type of events with highly concentrated rainfall in space and time are found to be the trickiest case for WRF to handle. Finally, the efficiencies of several variability indices are verified in categorising the storm events on the basis of the two‐dimensional rainfall evenness, which could provide a more quantitative way for the event classification that facilitates further studies. It is important that similar studies with various storm events are carried out in other catchments with different geographic and climatic conditions, so that more general error patterns can be found and further improvements can be made to the rainfall products from mesoscale numerical weather models. Copyright © 2011 John Wiley & Sons, Ltd.     

Storm solute behaviour in a montane Mediterranean forested catchment

The results of an extensive study of streamwater chemistry during stormflow events, for a montane Mediterranean area, are presented. Four groups of variables are identified as having contrasting behaviour: alkalinity and pH; nitrate and potassium; sulphate and chloride; sodium, calcium and magnesium. The results show a complex pattern of response to flow that can be broadly linked to: (1) antecedent hydrological conditions; (2) rainfall intensity; (3) supplies of water from chemically distinct areas within the catchment. However, comparisons between this study and a parallel one which examined the composition of waters within the catchment, show that it is presently impossible to quantify the relative supplies from each part of the catchment. The findings are reviewed in relation to analogous studies within a European setting and in relation to modelling initiatives.     

Coupling between landslides and eroding stream channels reconstructed from spruce tree rings (examples from the Carpathians and Sudetes – Central Europe)

The analysis of the positive feedback between landslides and erosion requires determination of the precise temporal and spatial relations between events of colluvium delivery and fluvial erosion. In our study we use decennial datasets on the occurrence of landsliding and erosion achieved through dendrochronological methods. Four sites covering areas of landslide slopes and adjacent valley floors with stream channels were studied. Landsliding on slopes was dated from the tree‐ring eccentricity developed in stems tilted due to bedrock instability. Erosion in channels was dated using the wood anatomy of roots exposed by erosion of the soil cover. Analysis of the temporal relations between dated landsliding, erosion and precipitation record has revealed that two types of repeating sequences can be observed: (1) rainfall → landsliding → erosion; (2) rainfall → erosion → landsliding. These sequences are an indication of the occurrence of slope‐channel positive feedback in the sites studied. In the first type, landsliding triggered by rainfall delivers colluvia into the valley floor and causes its narrowing, which in turn causes increased erosion. In the second type erosion triggered by rainfall disturbs the slope equilibrium and causes landsliding. Landsliding and erosion, once triggered by precipitation, can occur alternately in years with average precipitation and reinforce one another. Bidirectional coupling between landsliding and channel erosion was shown notably through the effects of channel shifting and forced sinuosity and by increased erosion of the slopes opposite the active landslides. Observations also suggest that the repetition of sequences described over longer periods of time can lead to a general widening of the valley floor at the expense of slopes and to a gradual change of the valley cross‐profile from narrow, V‐shaped into a wide flat‐bottomed. Thus landsliding–erosion coupling/positive feedback was recognized as an important factor shaping hillslope–valley topography of the mid‐mountain areas studied. Copyright © 2014 John Wiley & Sons, Ltd.     

Net rainfall estimation by the inversion of a geomorphology-based transfer function and discharge deconvolution

The assessment of net rainfall, defined as the intermediate hydrological variable linked in between the hillslope and the river network, is a challenge. This paper presents a method for net rainfall estimation, using inverse modelling associated to a geomorphology-based transfer function. The analysis is carried out in semi-arid Tunisia, with a dataset from event discharges in a mesoscale dryland basin. A complete sensitivity analysis is developed, along with a discussion of validity limits for simplifying assumptions and the identification of paths for improvement. This work could be relevant for data-scarce areas, thanks to the use of simple dynamic conceptualization and being based on observable geomorphological features, adjusted to the available data and knowledge.     

A preliminary investigation on the scaling behaviour of rainfall observed in two different climates

Abstract

The problem of transformation of rainfall data from one scale to another has been gaining considerable importance in recent years. Though the application of the concept of fractal theory, in the studies conducted thus far, nearly unanimously points at the possibility of such a transformation, the suitability of the theory to the highly variable rainfall in time and space has very often been questioned. A preliminary attempt is made herein to address this issue by investigating the existence of temporal scaling behaviour in rainfall data observed in two different climatic regions: (a) a subtropical climatic region (Leaf River basin, Mississippi, USA) and (b) an equatorial climatic region (Singapore). Rainfall data of three different resolutions, six-hourly, daily, and weekly, observed over a period of 25 years, are investigated. A mono- or simple-scaling method (box dimension method) is employed. The results achieved for the different data sets clearly indicate the existence of temporal scaling in rainfall observed in the two regions, an encouraging news on the suitability of fractal theory in understanding and modelling the rainfall process. However, the insufficiency of a single dimension to characterize the rainfall behaviour is realized, as the dimension depends on the rainfall intensity level, which, in turn, may be related to the rainfall generating mechanisms. A comparison of the box-dimension results obtained for data of different resolutions, from each of the regions, seems to indicate a possible connection between them, a prospect of tremendous practical importance. Another interesting observation is the similarity between the box dimension results obtained for rainfall data from Leaf River basin and Singapore, but this is also clearly related to the intensity level. The dependence of the dimension on the intensity threshold suggests the use of a multi-dimensional fractal approach, where the process is characterized by more than one dimension (or a dimension function) instead of one single dimension. On the basis of the present results, some potential areas for further study are identified.     

Improving NWP through radar rainfall-driven land surface parameters: A case study on convective precipitation forecasting

In this study we investigate the effect of forcing the land surface scheme of an atmospheric mesoscale model with radar rainfall data instead of the model-generated rainfall fields. The goal is to provide improved surface conditions for the atmospheric model in order to achieve accurate simulations of the mesoscale circulations that can significantly affect the timing, distribution and intensity of convective precipitation. The performance of the approach is evaluated in a set of numerical experiments on the basis of a 2-day-long mesoscale convective system that occurred over the US Great Plains in July 2004. The experimental design includes multiple runs covering a variety of forcing periods. Continuous data integration was initially used to investigate the sensitivity of the model’s performance in varying soil state conditions, while shorter time windows prior to the storm event were utilized to assess the effectiveness of the procedure for improving convective precipitation forecasting. Results indicate that continuous integration of radar rainfall data brings the simulated precipitation fields closer to the observed ones, as compared to the control simulation. The precipitation forecasts (up to 48 h) appear improved also in the cases of shorter integration periods (24 and 36 h), making this technique potentially useful for operational settings of weather forecasting systems. A physical interpretation of the results is provided on the basis of surface moisture and energy exchange.     

Land transformation and pond sediment information

Five years of observations on sedimentation rates in two ponds located near transformed land areas in the Kobe district of central Japan have shown the relationship between sedimentation and development during land transformation. One of the ponds observed has artificial land transformation in its drainage area (KR), whereas the other does not (KN). The sedimentation rate in the pond without artificial land transformation is roughly proportional to the rainfall intensity, whereas in the pond with land transformation it is related to change in the transformed area as well as the rainfall intensity. The relative sedimentation rate (sedimentation rate divided by the catchment area and rainfall intensity) is also related to loss on ignition and grain density; large relative sedimentation rates correspond to low loss on ignition and high grain density, suggesting that these factors are very sensitive to land transformation. Changes in catchment factors, which indicate the topographical and hydrological conditions in the catchment area, are inversely proportional to change in the ratio of the reclaimed to the natural area; this is indicative of change in the erodibility of the surface material in the catchment area. © 1997 John Wiley & Sons, Ltd.     

应用代数重建法编程重建数字图像

对已知和未知数字图像分别沿射线作Radon变换(线积分),用同一种布置射线特殊方法布置射线,每条射线积分步长易知皆为常数。从而,得到已知数字图像每条射线的线积分近似值(“观测值”);易建立未知数字图像线性代数方程组。应用“代数重建法”加法修正迭代编制Matlab程序,用此程序处理“观测值”数据,重建未知数字图像,其数值计算结果较好,与已知数字图像相对误差不超过2%。本文是ART加法修正迭代的基础工作,可为有关部门提供研究“代数重建法”实际应用参考。      

Submesoscale features and their interaction with fronts and internal tides in a high-resolution coupled atmosphere-ocean-wave model of the Bay of Bengal

Large freshwater fluxes into the Bay of Bengal by rainfall and river discharges result in strong salinity fronts in the bay. In this study, a high-resolution coupled atmosphere-ocean-wave model with comprehensive physics is used to model the weather, ocean circulation, and wave field in the Bay of Bengal. Our objective is to explore the submesoscale activity that occurs in a realistic coupled model that resolves mesoscales and allows part of the submesoscale field. Horizontal resolution in the atmosphere varies from 2 to 6 km and is 13 km for surface waves, while the ocean model is submesoscale permitting with resolutions as high as 1.5 km and a vertical resolution of 0.5 m in the upper 10 m. In this paper, three different cases of oceanic submesoscale features are discussed. In the first case, heavy rainfall and intense downdrafts produced by atmospheric convection are found to force submesoscale currents, temperature, and salinity anomalies in the oceanic mixed layer and impact the mesoscale flow. In a second case, strong solitary-like waves are generated by semidiurnal tides in the Andaman Sea and interact with mesoscale flows and fronts and affect submesoscale features generated along fronts. A third source of submesoscale variability is found further north in the Bay of Bengal where river outflows help maintain strong salinity gradients throughout the year. For that case, a comparison with satellite observations of sea surface height anomalies, sea surface temperature, and chlorophyll shows that the model captures the observed mesoscale eddy features of the flow field, but in addition, submesoscale upwelling and downwelling patterns associated with ageostrophic secondary circulations along density fronts are also captured by the model.     

Radar remote sensing of the source areas from the Coët-Dan catchment

As interest shifts to the development of models for predicting runoff quality, identification of the source areas for runoff becomes increasingly important. Active microwave remote sensing has a unique potential for surveying source areas at the catchment scale. Thresholding of the back-scattering coefficient was initially proposed but proved unsatisfactory when applied to the ERS-1 SAR multitemporal images acquired during winter 1992 over the Coët-Dan catchment, concomitantly with ground observations. Difference images may, instead, allow the wettest part of the catchment to be identified provided that the two images encompass a marked hydrological event. A saturation plot could not however be obtained for each date; the use of a pair of images may be further limited by the residual speckle (although carefully filtered using the multitemporal information) and a slight inaccuracy in the SAR image calibration. It is therefore argued that considering the whole temporal back-scatter profile would be, at present, a safer approach to the remote sensing of saturated areas. The back-scatter temporal standard deviation appears, in this light, as a possible good indicator of the local saturation likelihood during the period of study: it is based on the fact that saturation develops on parts of the catchment that are wetter than the others through lateral recharge. Possible applications within the TOPMODEL framework are discussed. © 1998 John Wiley & Sons, Ltd.