Functional and molecular characterization of Tachykinins and tachykinin receptors in the mouse uterus

The aim of this study was to analyze the function and expression of tachykinins, tachykinin receptors, and neprilysin (NEP) in the mouse uterus. A previous study showed that the uterotonic effects of substance P (SP), neurokinin A (NKA), and neurokinin B (NKB) in estrogen-treated mice were mainly mediated by the tachykinin NK, receptor. In the present work, further contractility studies were undertaken to determine the nature of the receptors mediating responses to tachykinins in uteri of late pregnant mice. Endpoint and real-time quantitative RTPCR were used to analyze the expression of the genes that encode the tachykinins SP/NKA, NKB, and hemokinin-1 (HK-1) (Tac1, Tac2, and Tac4); and the genes that encode tachykinin NK1 (Tacr1), NK2 (Tacr2), and NK3 (Tacr3) receptors in uteri from pregnant and nonpregnant mice. The data show that the mRNAs of tachykinins (particularly NKB and HK-1), tachykinin receptors, and NEP are locally expressed in the mouse uterus, and their expression changes during the estrous cycle and during pregnancy. The tachykinin INK, receptor is the predominant tachykinin receptor in the nonpregnant and early pregnant mouse and may mediate tachykinin-induced uterine contractions in the nonpregnant mouse. The tachykinin NK, receptor is predominant in the late pregnant mouse and is the main receptor mediating uterotonic responses to tachykinins at late pregnancy. The tachykinin NK, receptor is expressed in considerable amounts only in uteri from nonpregnant diestrous animals, and its physiological significance remains to be clarified.

Automatic near real-time selection of flood water levels from high resolution Synthetic Aperture Radar images for assimilation into hydraulic models: a case study

Flood extents caused by fluvial floods in urban and rural areas may be predicted by hydraulic models. Assimilation may be used to correct the model state and improve the estimates of the model parameters or external forcing. One common observation assimilated is the water level at various points along the modelled reach. Distributed water levels may be estimated indirectly along the flood extents in Synthetic Aperture Radar (SAR) images by intersecting the extents with the floodplain topography. It is necessary to select a subset of levels for assimilation because adjacent levels along the flood extent will be strongly correlated. A method for selecting such a subset automatically and in near real-time is described, which would allow the SAR water levels to be used in a forecasting model. The method first selects candidate waterline points in flooded rural areas having low slope. The waterline levels and positions are corrected for the effects of double reflections between the water surface and emergent vegetation at the flood edge. Waterline points are also selected in flooded urban areas away from radar shadow and layover caused by buildings, with levels similar to those in adjacent rural areas. The resulting points are thinned to reduce spatial autocorrelation using a top-down clustering approach. The method was developed using a TerraSAR-X image from a particular case study involving urban and rural flooding. The waterline points extracted proved to be spatially uncorrelated, with levels reasonably similar to those determined manually from aerial photographs, and in good agreement with those of nearby gauges.

Scheduling satellite-based SAR acquisition for sequential assimilation of water level observations into flood modelling

Satellite-based Synthetic Aperture Radar (SAR) has proved useful for obtaining information on flood extent, which, when intersected with a Digital Elevation Model (DEM) of the floodplain, provides water level observations that can be assimilated into a hydrodynamic model to decrease forecast uncertainty. With an increasing number of operational satellites with SAR capability, information on the relationship between satellite first visit and revisit times and forecast performance is required to optimise the operational scheduling of satellite imagery. By using an Ensemble Transform Kalman Filter (ETKF) and a synthetic analysis with the 2D hydrodynamic model LISFLOOD-FP based on a real flooding case affecting an urban area (summer 2007,Tewkesbury, Southwest UK), we evaluate the sensitivity of the forecast performance to visit parameters. We emulate a generic hydrologic-hydrodynamic modelling cascade by imposing a bias and spatiotemporal correlations to the inflow error ensemble into the hydrodynamic domain. First, in agreement with previous research, estimation and correction for this bias leads to a clear improvement in keeping the forecast on track. Second, imagery obtained early in the flood is shown to have a large influence on forecast statistics. Revisit interval is most influential for early observations. The results are promising for the future of remote sensing-based water level observations for real-time flood forecasting in complex scenarios.

Detection of flooded urban areas in high resolution Synthetic Aperture Radar images using double scattering

Flooding is a particular hazard in urban areas worldwide due to the increased risks to life and property in these regions. Synthetic Aperture Radar (SAR) sensors are often used to image flooding because of their all-weather day-night capability, and now possess sufficient resolution to image urban flooding. The flood extents extracted from the images may be used for flood relief management and improved urban flood inundation modelling. A difficulty with using SAR for urban flood detection is that, due to its side-looking nature, substantial areas of urban ground surface may not be visible to the SAR due to radar layover and shadow caused by buildings and taller vegetation. This paper investigates whether urban flooding can be detected in layover regions (where flooding may not normally be apparent) using double scattering between the (possibly flooded) ground surface and the walls of adjacent buildings. The method estimates double scattering strengths using a SAR image in conjunction with a high resolution LiDAR (Light Detection and Ranging) height map of the urban area. A SAR simulator is applied to the LiDAR data to generate maps of layover and shadow, and estimate the positions of double scattering curves in the SAR image. Observations of double scattering strengths were compared to the predictions from an electromagnetic scattering model, for both the case of a single image containing flooding, and a change detection case in which the flooded image was compared to an un-flooded image of the same area acquired with the same radar parameters. The method proved successful in detecting double scattering due to flooding in the single-image case, for which flooded double scattering curves were detected with 100% classification accuracy (albeit using a small sample set) and un-flooded curves with 91% classification accuracy. The same measures of success were achieved using change detection between flooded and un-flooded images. Depending on the particular flooding situation, the method could lead to improved detection of flooding in urban areas.

Calibration of structure in a distributed forecasting model for a semiarid flash flood: dynamic surface storage and channel roughness

Flash floods pose a significant danger for life and property. Unfortunately, in arid and semiarid environment the runoff generation shows a complex non-linear behavior with a strong spatial and temporal non-uniformity. As a result, the predictions made by physically-based simulations in semiarid areas are subject to great uncertainty, and a failure in the predictive behavior of existing models is common. Thus better descriptions of physical processes at the watershed scale need to be incorporated into the hydrological model structures. For example, terrain relief has been systematically considered static in flood modelling at the watershed scale. Here, we show that the integrated effect of small distributed relief variations originated through concurrent hydrological processes within a storm event was significant on the watershed scale hydrograph. We model these observations by introducing dynamic formulations of two relief-related parameters at diverse scales: maximum depression storage, and roughness coefficient in channels. In the final (a posteriori) model structure these parameters are allowed to be both time-constant or time-varying. The case under study is a convective storm in a semiarid Mediterranean watershed with ephemeral channels and high agricultural pressures (the Rambla del Albujón watershed; 556 km 2 ), which showed a complex multi-peak response. First, to obtain quasi-sensible simulations in the (a priori) model with time-constant relief-related parameters, a spatially distributed parameterization was strictly required. Second, a generalized likelihood uncertainty estimation (GLUE) inference applied to the improved model structure, and conditioned to observed nested hydrographs, showed that accounting for dynamic relief-related parameters led to improved simulations. The discussion is finally broadened by considering the use of the calibrated model both to analyze the sensitivity of the watershed to storm motion and to attempt the flood forecasting of a stratiform event with highly different behavior.

A real-time measurement system for long-life flood monitoring and warning applications

A flood warning system incorporates telemetered rainfall and flow/water level data measured at various locations in the catchment area. Real-time accurate data collection is required for this use, and sensor networks improve the system capabilities. However, existing sensor nodes struggle to satisfy the hydrological requirements in terms of autonomy, sensor hardware compatibility, reliability and long-range communication. We describe the design and development of a real-time measurement system for flood monitoring, and its deployment in a flash-flood prone 650 km2 semiarid watershed in Southern Spain. A developed low-power and long-range communication device, so-called DatalogV1, provides automatic data gathering and reliable transmission. DatalogV1 incorporates self-monitoring for adapting measurement schedules for consumption management and to capture events of interest. Two tests are used to assess the success of the development. The results show an autonomous and robust monitoring system for long-term collection of water level data in many sparse locations during flood events.

Land use and climate change impacts on soil organic carbon stocks in semi-arid Spain

Purpose The sensitivity of soil organic carbon to global change drivers, according to the depth profile, is receiving increasing attention because of its importance in the global carbon cycle and its potential feedback to climate change. A better knowledge of the vertical distribution of SOC and its controlling factors—the aim of this study—will help scientists predict the consequences of global change. Materials and methods The study area was the Murcia Province (S.E. Spain) under semiarid Mediterranean conditions. The database used consists of 312 soil profiles collected in a systematic grid, each 12 km2 covering a total area of 11,004 km2. Statistical analysis to study the relationships between SOC concentration and control factors in different soil use scenarios was conducted at fixed depths of 0–20, 20–40, 40–60, and 60–100 cm. Results and discussion SOC concentration in the top 40 cm ranged between 6.1 and 31.5 g kg−1, with significant differences according to land use, soil type and lithology, while below this depth, no differences were observed (SOC concentration 2.1–6.8 g kg−1). The ANOVA showed that land use was the most important factor controlling SOC concentration in the 0–40 cm depth. Significant differences were found in the relative importance of environmental and textural factors according to land use and soil depth. In forestland, mean annual precipitation and texture were the main predictors of SOC, while in cropland and shrubland, the main predictors were mean annual temperature and lithology. Total SOC stored in the top 1 m in the region was about 79 Tg with a low mean density of 7.18 kg Cm−3. The vertical distribution of SOC was shallower in forestland and deeper in cropland. A reduction in rainfall would lead to SOC decrease in forestland and shrubland, and an increase of mean annual temperature would adversely affect SOC in croplands and shrubland. With increasing depth, the relative importance of climatic factors decreases and texture becomes more important in controlling SOC in all land uses. Conclusions Due to climate change, impacts will be much greater in surface SOC, the strategies for C sequestration should be focused on subsoil sequestration, which was hindered in forestland due to bedrock limitations to soil depth. In these conditions, sequestration in cropland through appropriate management practices is recommended.

Geophysical characterization of the complex dynamics of groundwater and seawater exchange in a highly stressed aquifer system linked to a coastal lagoon (SE Spain)

Anthropogenic pressure influences the two-way interactions between shallow aquifers and coastal lagoons. Aquifer overexploitation may lead to seawater intrusion, and aquifer recharge from rainfall plus irrigation may, in turn, increase the groundwater discharge into the lagoon. We analyse the evolution, since the 1950s up to the present, of the interactions between the Campo de Cartagena Quaternary aquifer and the Mar Menor coastal lagoon (SE Spain). This is a very heterogeneous and anisotropic detrital aquifer, where aquifer–lagoon interface has a very irregular geometry. Using electrical resistivity tomography, we clearly identified the freshwater–saltwater transition zone and detected areas affected by seawater intrusion. Severity of the intrusion was spatially variable and significantly related to the density of irrigation wells in 1950s–1960s, suggesting the role of groundwater overexploitation. We distinguish two different mechanisms by which water from the sea invades the land: (a) horizontal advance of the interface due to a wide exploitation area and (b) vertical rise (upconing) caused by local intensive pumping. In general, shallow parts of the geophysical profiles show higher electrical resistivity associated with freshwater mainly coming from irrigation return flows, with water resources mostly from deep confined aquifers and imported from Tagus river, 400 km north. This indicates a likely reversal of the former seawater intrusion process.

Investigating hydrological regimes and processes in a set of catchments with temporary waters in Mediterranean Europe

Seven catchments of diverse size in Mediterranean Europe were investigated in order to understand the main aspects of their hydrological functioning. The methods included the analysis of daily and monthly precipitation, monthly potential evapotranspiration rates, flow duration curves, rainfall runoff relationships and catchment internal data for the smaller and more instrumented catchments. The results showed that the catchments were less dry than initially considered. Only one of them was really semi-arid throughout the year. All the remaining catchments showed wet seasons when precipitation exceeded potential evapotrans-piration, allowing aquifer recharge, wet runoff generation mechanisms and relevant baseflow contribution. Nevertheless, local infiltration excess (Hortonian) overland flow was inferred during summer storms in some catchments and urban overland flow in some others. The roles of karstic groundwater, human disturbance and low winter temperatures were identified as having an important impact on the hydrological regime in some of the catchments.

Evidence of a topographic signal in surface soil moisture derived from ENVISAT ASAR wide swath data

The susceptibility of a catchment to flooding is affected by its soil moisture prior to an extreme rainfall event. While soil moisture is routinely observed by satellite instruments, results from previous work on the assimilation of remotely sensed soil moisture into hydrologic models have been mixed. This may have been due in part to the low spatial resolution of the observations used. In this study, the remote sensing aspects of a project attempting to improve flow predictions from a distributed hydrologic model by assimilating soil moisture measurements are described. Advanced Synthetic Aperture Radar (ASAR) Wide Swath data were used to measure soil moisture as, unlike low resolution microwave data, they have sufficient resolution to allow soil moisture variations due to local topography to be detected, which may help to take into account the spatial heterogeneity of hydrological processes. Surface soil moisture content (SSMC) was measured over the catchments of the Severn and Avon rivers in the South West UK. To reduce the influence of vegetation, measurements were made only over homogeneous pixels of improved grassland determined from a land cover map. Radar backscatter was corrected for terrain variations and normalized to a common incidence angle. SSMC was calculated using change detection. To search for evidence of a topographic signal, the mean SSMC from improved grassland pixels on low slopes near rivers was compared to that on higher slopes. When the mean SSMC on low slopes was 30–90%, the higher slopes were slightly drier than the low slopes. The effect was reversed for lower SSMC values. It was also more pronounced during a drying event. These findings contribute to the scant information in the literature on the use of high resolution SAR soil moisture measurement to improve hydrologic models.

Satellite-supported flood forecasting in river networks: a real case study

Satellite-based (e.g., Synthetic Aperture Radar [SAR]) water level observations (WLOs) of the floodplain can be sequentially assimilated into a hydrodynamic model to decrease forecast uncertainty. This has the potential to keep the forecast on track, so providing an Earth Observation (EO) based flood forecast system. However, the operational applicability of such a system for floods developed over river networks requires further testing. One of the promising techniques for assimilation in this field is the family of ensemble Kalman (EnKF) filters. These filters use a limited-size ensemble representation of the forecast error covariance matrix. This representation tends to develop spurious correlations as the forecast-assimilation cycle proceeds, which is a further complication for dealing with floods in either urban areas or river junctions in rural environments. Here we evaluate the assimilation of WLOs obtained from a sequence of real SAR overpasses (the X-band COSMO-Skymed constellation) in a case study. We show that a direct application of a global Ensemble Transform Kalman Filter (ETKF) suffers from filter divergence caused by spurious correlations. However, a spatially-based filter localization provides a substantial moderation in the development of the forecast error covariance matrix, directly improving the forecast and also making it possible to further benefit from a simultaneous online inflow error estimation and correction. Additionally, we propose and evaluate a novel along-network metric for filter localization, which is physically-meaningful for the flood over a network problem. Using this metric, we further evaluate the simultaneous estimation of channel friction and spatially-variable channel bathymetry, for which the filter seems able to converge simultaneously to sensible values. Results also indicate that friction is a second order effect in flood inundation models applied to gradually varied flow in large rivers. The study is not conclusive regarding whether in an operational situation the simultaneous estimation of friction and bathymetry helps the current forecast. Overall, the results indicate the feasibility of stand-alone EO-based operational flood forecasting.

Rainfall estimation by rain gauge-radar combination: a concurrent multiplicative-additive approach

A procedure (concurrent multiplicative-additive objective analysis scheme [CMA-OAS]) is proposed for operational rainfall estimation using rain gauges and radar data. On the basis of a concurrent multiplicative-additive (CMA) decomposition of the spatially nonuniform radar bias, within-storm variability of rainfall and fractional coverage of rainfall are taken into account. Thus both spatially nonuniform radar bias, given that rainfall is detected, and bias in radar detection of rainfall are handled. The interpolation procedure of CMA-OAS is built on Barnes' objective analysis scheme (OAS), whose purpose is to estimate a filtered spatial field of the variable of interest through a successive correction of residuals resulting from a Gaussian kernel smoother applied on spatial samples. The CMA-OAS, first, poses an optimization problem at each gauge-radar support point to obtain both a local multiplicative-additive radar bias decomposition and a regionalization parameter. Second, local biases and regionalization parameters are integrated into an OAS to estimate the multisensor rainfall at the ground level. The procedure is suited to relatively sparse rain gauge networks. To show the procedure, six storms are analyzed at hourly steps over 10,663 km2. Results generally indicated an improved quality with respect to other methods evaluated: a standard mean-field bias adjustment, a spatially variable adjustment with multiplicative factors, and ordinary cokriging.

Anthropogenic nutrient sources and loads from a Mediterranean catchment into a coastal lagoon: Mar Menor, Spain

The Mar Menor is a coastal lagoon increasingly threatened by urban and agricultural pressures. The main watercourse draining into the lagoon is the Rambla del Albujón. A fortnightly campaign carried out over one annual cycle enabled us to characterize the treated urban sewage effluents and agricultural sources which contribute to the nutrient fluxes in the watercourse. Multivariate analysis provided information for establishing chemical signatures and for assessing the relative influence of the various sources on the water quality at the outlet. Mass balances were used to examine net gains and losses, and cross-correlations with rainfall to analyze climatic influence and control factors in the trends of the nutrient flux. The rainfall pattern was significantly cross-correlated with nitrate and phosphorus fluxes from agricultural sources, while fluctuations in the resident population explained the phosphorus flux trend in urban sources. 50% of dissolved inorganic nitrogen was from agricultural sources, while 70% of total phosphate and 91% of total organic carbon were from urban point sources. The net amounts of all the nutrients fell as a result of plant uptake and/or denitrification in the channel. The control of urban point sources (phosphorus-enriched) is suggested as a promptly action for improving the health of the coastal lagoon.

Efficient incorporation of channel cross-section geometry uncertainty into regional and global scale flood inundation models

This paper investigates the challenge of representing structural differences in river channel cross-section geometry for regional to global scale river hydraulic models and the effect this can have on simulations of wave dynamics. Classically, channel geometry is defined using data, yet at larger scales the necessary information and model structures do not exist to take this approach. We therefore propose a fundamentally different approach where the structural uncertainty in channel geometry is represented using a simple parameterization, which could then be estimated through calibration or data assimilation. This paper first outlines the development of a computationally efficient numerical scheme to represent generalised channel shapes using a single parameter, which is then validated using a simple straight channel test case and shown to predict wetted perimeter to within 2% for the channels tested. An application to the River Severn, UK is also presented, along with an analysis of model sensitivity to channel shape, depth and friction. The channel shape parameter was shown to improve model simulations of river level, particularly for more physically plausible channel roughness and depth parameter ranges. Calibrating channel Manning’s coefficient in a rectangular channel provided similar water level simulation accuracy in terms of Nash-Sutcliffe efficiency to a model where friction and shape or depth were calibrated. However, the calibrated Manning coefficient in the rectangular channel model was ~2/3 greater than the likely physically realistic value for this reach and this erroneously slowed wave propagation times through the reach by several hours. Therefore, for large scale models applied in data sparse areas, calibrating channel depth and/or shape may be preferable to assuming a rectangular geometry and calibrating friction alone.