HESSD - Latest Articles

Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

2010-09-02T00:00:00+02:00

Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals

Hydrology and Earth System Sciences Discussions, 7, 6699-6724, 2010

Author(s): Y. Y. Liu, R. M. Parinussa, W. A. Dorigo, R. A. M. de Jeu, W. Wagner, A. I. J. M. van Dijk, M. F. McCabe, and J. P. Evans

Combining information derived from satellite-based passive and active microwave sensors has the potential to offer improved retrievals of surface soil moisture variations at global scales. Here we propose a technique to take advantage of retrieval characteristics of passive (AMSR-E) and active (ASCAT) microwave satellite estimates over sparse-to-moderately vegetated areas to obtain an improved soil moisture product. To do this, absolute soil moisture values from AMSR-E and relative soil moisture derived from ASCAT are rescaled against a reference land surface model date set using a cumulative distribution function (CDF) matching approach. While this technique imposes the bias of the reference to the rescaled satellite products, it adjusts both satellite products to the same range and almost preserves the correlation between satellite products and in situ measurements. Comparisons with in situ data demonstrated that over the regions where the correlation coefficient between rescaled AMSR-E and ASCAT is above 0.65 (hereafter referred to as transitional regions), merging the different satellite products together increases the number of observations while minimally changing the accuracy of soil moisture retrievals. These transitional regions also delineate the boundary between sparsely and moderately vegetated regions where rescaled AMSR-E and ASCAT are respectively used in the merged product. Thus the merged product carries the advantages of better spatial coverage overall and increased number of observations particularly for the transitional regions. The combination approach developed in this study has the potential to be applied to existing microwave satellites as well as to new microwave missions. Accordingly, a long-term global soil moisture dataset can be developed and extended, enhancing basic understanding of the role of soil moisture in the water, energy and carbon cycles.

Application of quantitative composite fingerprinting technique to identify the main sediment sources in two small catchments of Iran

2010-09-02T00:00:00+02:00

Application of quantitative composite fingerprinting technique to identify the main sediment sources in two small catchments of Iran

Hydrology and Earth System Sciences Discussions, 7, 6677-6698, 2010

Author(s): A. Kouhpeima, S. Feiznia, H. Ahmadi, S. A. Hashemi, and A. R. Zareiee

The targeting of sediment management strategies is a key requirement in developing countries including Iran because of the limited resources available. These targeting is, however hampered by the lack of reliable information on catchment sediment sources. This paper reports the results of using a quantitative composite fingerprinting technique to estimate the relative importance of the primary potential sources within the Amrovan and Royan catchments in Semnan Province, Iran. Fifteen tracers were first selected for tracing and samples were analyzed in the laboratory for these parameters. Statistical methods were applied to the data including nonparametric Kruskal-Wallis test and Differentiation Function Analysis (DFA). For Amrovan catchment three parameters (N, Cr and Co) were found to be not significant in making the discrimination. The optimum fingerprint, comprising Oc, PH, Kaolinite and K was able to distinguish correctly 100% of the source material samples. For the Royan catchment, all of the 15 properties were able to distinguish between the six source types and the optimum fingerprint provided by stepwise DFA (Cholorite, XFD, N and C) correctly classifies 92.9% of the source material samples. The mean contributions from each sediment source obtained by multivariate mixing model varied at two catchments. For Amrovan catchment Upper Red formation is the main sediment sources as this sediment source approximately supplies 36% of the reservoir sediment whereas the dominant sediment source for the Royan catchment is from Karaj formation that supplies 33% of the reservoir sediments. Results indicate that the source fingerprinting approach appears to work well in the study catchments and to generate reliable results.

Interannual variations of the terrestrial water storage in the Lower Ob' basin from a multisatellite approach

2010-09-01T00:00:00+02:00

Interannual variations of the terrestrial water storage in the Lower Ob' basin from a multisatellite approach

Hydrology and Earth System Sciences Discussions, 7, 6647-6676, 2010

Author(s): F. Frappart, F. Papa, A. Güntner, S. Werth, G. Ramillien, C. Prigent, W. B. Rossow, and M.-P. Bonnet

Temporal variations of surface water volume over inundated areas of the Lower Ob' basin in Siberia, one of the largest contributor of freshwater to the Arctic Ocean, are estimated using combined observations from a multisatellite inundation dataset and water levels over rivers and floodplains derivec from the TOPEX/POSEIDON (T/P) altimetry satellite. We computed time-series of monthly maps of surface water volume over the period of common availability of T/P and the multisatellite data (1993–2004). The results exhibit similar interannual variabilities with precipitation estimates and river discharge observations. This study also presents monthly estimates of groundwater and permafrost mass anomalies during 2003–2004 based on a synergistic analysis using multisatellite observations and hydrological models. Water stored in aquifer is isolated from the total water storage measured by GRACE by removing the contributions of both the surface reservoir, derived from satellite imagery and radar altimetry, and the root zone reservoir simulated by hydrological models.

Large-scale runoff generation – parsimonious parameterisation using high-resolution topography

2010-09-01T00:00:00+02:00

Large-scale runoff generation – parsimonious parameterisation using high-resolution topography

Hydrology and Earth System Sciences Discussions, 7, 6613-6646, 2010

Author(s): L. Gong, S. Halldin, and C.-Y. Xu

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting a very small scales. Many hydrological models, e.g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TGR only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3'' (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

Uncertainties in using remote sensing for water use determination: a case study in a heterogeneous study area in South Africa

2010-09-01T00:00:00+02:00

Uncertainties in using remote sensing for water use determination: a case study in a heterogeneous study area in South Africa

Hydrology and Earth System Sciences Discussions, 7, 6581-6612, 2010

Author(s): L. A. Gibson, Z. Münch, J. Engelbrecht, and J. E. Conrad

South Africa is a water scarce country where it is important for water managers to have accurate information on water resource occurrence and use. A remote sensing project highlighted many uncertainties in using complex remote sensing models to determine water use in a heterogeneous study area. The severity of the uncertainties was confirmed as the results across the catchment showed a higher total evapotranspiration than precipitation. This paper illustrates some of the uncertainties and limitations using the evapotranspiration component of the water balance as calculated by the Surface Energy Balance System (SEBS) model, as an example.

The introduction of uncertainties in the derivation of evapotranspiration were identified as: (1) sensitivity to land surface and air temperature gradient; (2) the choice of fractional vegetation cover formula; (3) height of wind speed measurement in relation to displacement height indicating a maximum canopy height at which the SEBS model should be used; and (4) study area heterogeneity.

Uncertainties and errors are compounded when considering that the SEBS model is a complex model, requiring several image processing sequences that are combined to produce the final result. It was shown how the production and propagation of errors in the SEBS model can contribute to uncertainties in flux estimation and ultimately to uncertainties in the estimation of actual evapotranspiration.

State-space approach to evaluate spatial variability of field measured soil water status along a line transect in a volcanic-vesuvian soil

2010-09-01T00:00:00+02:00

State-space approach to evaluate spatial variability of field measured soil water status along a line transect in a volcanic-vesuvian soil

Hydrology and Earth System Sciences Discussions, 7, 6553-6579, 2010

Author(s): A. Comegna, A. Coppola, V. Comegna, G. Severino, A. Sommella, and C. Vitale

The spatial structures of soil water status, in terms of soil water content θ and tension h, had been examined on a bare volcanic soil in Ponticelli, Naples (Italy). Measurements were made in situ at 0.3 m depth on two transects consisting of 50 positions 1 m apart. The ACF and the PACF were used to identify the univariate ARMA(1,1) model for the analyzed series and the AR(1) model for the extracted signals. Relations with a state-space model are investigated and a bivariate AR(1) model fitted. The simultaneous relations between θ and h are considered and estimated.

Modeling moisture fluxes using artificial neural networks: can information extraction overcome data loss?

2010-09-01T00:00:00+02:00

Modeling moisture fluxes using artificial neural networks: can information extraction overcome data loss?

Hydrology and Earth System Sciences Discussions, 7, 6525-6551, 2010

Author(s): A. L. Neal, H. V. Gupta, S. A. Kurc, and P. D. Brooks

Eddy covariance sites can experience data losses as high as 30 to 45% on an annual basis. Artificial neural networks (ANNs) have been identified as powerful tools for gap filling, but their performance depends on the representativeness of data used to train the model. In this paper, we develop a normalization method, which has similar performance compared to conventional training approaches, but exhibits differences in the timing of fluxes, indicating different and previously unused information in the data record. Specifically, the differences between half-hourly model fluxes, especially during summer months, indicate that the structure of the information content in the data changes seasonally, diurnally and with the rate of data loss. This variation between gap-filling models complicates the application of their output as consistent data sets for land surface modeling, and points to the need for improved data and models to address flux behavior at critical times. We advise several approaches to address these concerns, including use of separate models for day and nighttime processes and the use of multiple data streams at dawn, when eddy covariance may be particularly ineffective due to the timing of the onset of turbulent mixing.

Big and small: menisci in soil pores affect water pressures, dynamics of groundwater levels, and catchment-scale average matric potentials

2010-09-01T00:00:00+02:00

Big and small: menisci in soil pores affect water pressures, dynamics of groundwater levels, and catchment-scale average matric potentials

Hydrology and Earth System Sciences Discussions, 7, 6491-6523, 2010

Author(s): G. H. de Rooij

Soil water is confined behind the menisci of its water-air interface. Catchment-scale fluxes (groundwater recharge, evaporation, transpiration, precipitation, etc.) affect the matric potential, and thereby the interface curvature and the configuration of the phases. In turn, these affect the fluxes (except precipitation), creating feedbacks between pore-scale and catchment-scale processes. Tracking pore-scale processes beyond the Darcy scale is not feasible. Instead, for a simplified system based on the classical Darcy's Law and Laplace-Young Law we i) clarify how menisci transfer pressure from the atmosphere to the soil water, ii) examine large-scale phenomena arising from pore-scale processes, and iii) analyze the relationship between average meniscus curvature and average matric potential. In stagnant water, changing the gravitational potential or the curvature of the air-water interface changes the pressure throughout the water. Adding small amounts of water can thus profoundly affect water pressures in a much larger volume. The pressure-regulating effect of the interface curvature showcases the meniscus as a pressure port that transfers the atmospheric pressure to the water with an offset directly proportional to its curvature. This property causes an extremely rapid rise of phreatic levels in soils once the capillary fringe extends to the soil surface and the menisci flatten. For large bodies of subsurface water, the curvature and vertical position of any meniscus quantify the uniform hydraulic potential under hydrostatic equilibrium. During unit-gradient flow, the matric potential corresponding to the mean curvature of the menisci should provide a good approximation of the intrinsic phase average of the matric potential.

Interrill erosion, runoff and sediment size distribution as affected by slope steepness and antecedent moisture content

2010-08-31T00:00:00+02:00

Interrill erosion, runoff and sediment size distribution as affected by slope steepness and antecedent moisture content

Hydrology and Earth System Sciences Discussions, 7, 6447-6489, 2010

Author(s): M. B. Defersha, S. Quraishi, and A. Melesse

Soil erosion is a two-phase process consisting of the detachment of individual particles and their transport by erosive agents such as flowing water. The rate at which erosion occurs depends upon the individual as well as interactive effects of different parameters responsible for soil erosion. The study discusses results of a laboratory analysis and evaluates the effect of slope steepness and antecedent moisture content on sediment yield (wash) and runoff rate. Interrill sediment yield, splash detachment, runoff, and sediment size distribution were measured in laboratory erosion pans under simulated total duration of 90 min. Rainfall intensity at 120 mm/hr, 70 mm/hr, and 55 mm/hr were applied sequentially at 9, 25, and 45% slope steepness for three soils (Alemaya Black soil, Regosols, and Cambisols) varied from clay to sandy clay loam in texture with wet and dry antecedent water contents. As slope steepness increased from 9 to 25% splash increased for five treatments and decreased for the remaining treatment; washed sediment increased for all treatments. As slope increased from 25 to 45% splash decreased for five treatments but increased for one treatment, and washed sediment increased for three treatments but decreased for the other three treatments. Pre-wetting decreased splash detachment for all soil treatments and rate of reduction was high for the highly aggregated soil, Alemaya Black soil and low for the less aggregated soil Regosols. Splash sediment and sediment yield was not correlated. Change in splash with increase in slope steepness was also not correlated with change in sediment yield. Change in runoff rate with increase in slope steepness was correlated (r=0.66) with change in sediment yield. For Alemaya Black soil and Regosols, splashed sediment size distribution was correlated with washed sediment size distribution. Interrill erosion models that include runoff and rainfall intensity parameters were a better fit for these data than the rainfall intensity based model. The exponent term, b, values in (E=a I^b) model did not approach 2.00 for all treatments. For the same slope steepness factor, both rainfall and rainfall-runoff based models provided different erodibility coefficients at different levels of slope and moisture contents.

Spatial interpolation of hourly rainfall – effect of additional information, variogram inference and storm properties

2010-08-31T00:00:00+02:00

Spatial interpolation of hourly rainfall – effect of additional information, variogram inference and storm properties

Hydrology and Earth System Sciences Discussions, 7, 6407-6446, 2010

Author(s): A. Verworn and U. Haberlandt

Hydrological modelling of floods relies on precipitation data with a high resolution in space and time. A reliable spatial representation of short time step rainfall is often difficult to achieve due to a low network density. In this study hourly precipitation was spatially interpolated with the multivariate geostatistical method kriging with external drift (KED) using additional information from topography, rainfall data from the denser daily networks and weather radar data. Investigations were carried out for several flood events in the time period between 2000 and 2005 caused by different meteorological conditions. The 125 km radius around the radar station Ummendorf in northern Germany covered the overall study region. One objective was to assess the effect of different approaches for estimation of semivariograms on the interpolation performance of short time step rainfall. Another objective was the refined application of the method kriging with external drift. Special attention was not only given to find the most relevant additional information, but also to combine the additional information in the best possible way. A multi-step interpolation procedure was applied to better consider sub-regions without rainfall.

The impact of different semivariogram types on the interpolation performance was low. While it varied over the events, an averaged semivariogram was sufficient overall. Weather radar data were the most valuable additional information for KED for convective summer events. For interpolation of stratiform winter events using daily rainfall as additional information was sufficient. The application of the multi-step procedure significantly helped to improve the representation of fractional precipitation coverage.

Ephemeral stream sensor design using state loggers

2010-08-31T00:00:00+02:00

Ephemeral stream sensor design using state loggers

Hydrology and Earth System Sciences Discussions, 7, 6381-6405, 2010

Author(s): R. Bhamjee and J. B. Lindsay

Ephemeral streamflow events have the potential to transport sediment and pollutants downstream, which, in predominently agricultural basins, is especially problematic. Despite the importance of ephemeral streamflow, the duration and timing of the events are characteristics that are rarely measured. Ephemeral streamflow sensors have been created in the past with varying degrees of success and this paper presents a solution which minimizes previous shortcomings in other designs. The design and setup of the sensor network in two agricultural basins, as well as considerations for data processing are explored in this paper with regard to monitoring ephemeral streamflow at high spatial and temporal resolutions.

Rainfall retrievals over West Africa using SEVIRI: evaluation with TRMM-PR and monitoring of the daylight time monsoon progression

2010-08-27T00:00:00+02:00

Rainfall retrievals over West Africa using SEVIRI: evaluation with TRMM-PR and monitoring of the daylight time monsoon progression

Hydrology and Earth System Sciences Discussions, 7, 6351-6380, 2010

Author(s): E. L. A. Wolters, B. J. J. M. van den Hurk, and R. A. Roebeling

This paper describes the application of the KNMI cloud physical properties – precipitation properties (CPP-PP) algorithm over West Africa. The algorithm combines condensed water path (CWP), cloud phase (CPH), cloud particle effective radius (r_e), and cloud-top temperature (CTT) information, retrieved from visible, near-infrared and infrared observations of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat-9 to estimate precipitation occurrence and intensity. It is investigated whether the CPP-PP algorithm is capable of retrieving rain occurrence and intensity over West Africa with a sufficient accuracy, using tropical monsoon measurement mission precipitation radar (TRMM-PR) and a small number of rain gauge observations as reference. As a second goal, it is assessed whether SEVIRI is capable of monitoring both the seasonal and synoptical evolution of the West African monsoon (WAM). It is shown that the SEVIRI-detected rainfall area agrees well with TRMM-PR, having a correlation coefficient of 0.86, with the areal extent of rainfall by SEVIRI being ~10% larger than TRMM-PR. The mean retrieved rain rate from CPP-PP is about 8% higher than from TRMM-PR. The frequency distributions of rain rate reveal that the median rain rates of CPP-PP and TRMM-PR are similar. However, rain rates >7 mm h⁻¹ are retrieved more frequently by SEVIRI than by TRMM-PR, which is partly explained by known biases in TRMM-PR. Finally, it is illustrated that both the seasonal and synoptical time scale of the WAM can be well detected from SEVIRI daytime observations. It was found that the daytime westward MCS travel speed fluctuates between 50 and 60 km h⁻¹. Furthermore, the ratio of MCS precipitation to the total precipitation was estimated to be about 27%. Our results indicate that rainfall retrievals from SEVIRI can be used to monitor the West African monsoon.

Water resource monitoring systems and the role of satellite observations

2010-08-26T00:00:00+02:00

Water resource monitoring systems and the role of satellite observations

Hydrology and Earth System Sciences Discussions, 7, 6305-6349, 2010

Author(s): A. I. J. M. van Dijk and L. J. Renzullo

Spatial water resource monitoring systems (SWRMS) can provide valuable information in support of water management, but current operational systems are few and provide only a subset of the information required. Necessary innovations include the explicit description of water redistribution and water use from river and groundwater systems, achieving greater spatial detail (particularly in key features such as irrigated areas and wetlands), and improving accuracy as assessed against hydrometric observations, as well as assimilating those observations. The Australian water resources assessment (AWRA) system aims to achieve this by coupling landscape models with models describing surface water and groundwater dynamics and water use. A review of operational and research applications demonstrates that satellite observations can improve accuracy and spatial detail in hydrological model estimation. All operational systems use dynamic forcing, land cover classifications and a priori parameterisation of vegetation dynamics that are partially or wholly derived from remote sensing. Satellite observations are used to varying degrees in model evaluation and data assimilation. The utility of satellite observations through data assimilation can vary as a function of dominant hydrological processes. Opportunities for improvement are identified, including the development of more accurate and higher spatial and temporal resolution precipitation products, and the use of a greater range of remote sensing products in a priori model parameter estimation, model evaluation and data assimilation. Operational challenges include the continuity of research satellite missions and data services, and the need to find computationally-efficient data assimilation techniques. The successful use of observations critically depends on the availability of detailed information on observational error and understanding of the relationship between remotely-sensed and model variables, as affected by conceptual discrepancies and spatial and temporal scaling.

Mapping daily evapotranspiration and dryness index in the East African highlands using MODIS and SEVIRI data

2010-08-26T00:00:00+02:00

Mapping daily evapotranspiration and dryness index in the East African highlands using MODIS and SEVIRI data

Hydrology and Earth System Sciences Discussions, 7, 6285-6303, 2010

Author(s): Z. Sun, M. Gebremichael, and H. A. R. de Bruin

Routine information on regional evapotranspiration (ET) and dryness index is essential for agricultural water management, drought monitoring, and studies of water cycle and climate. However, this information is not currently available for the East Africa highlands. The main purpose of this study is to develop (1) a new methodology that produces spatially gridded daily ET estimates on a (near) real-time basis exclusively from satellite data, and (2) a new dryness index that depends only on satellite data and weather forecast data. The methodology that calculates daily actual ET involves combining data from two sensors (MODIS and SEVIRI) onboard two kinds of platforms (Terra/Aqua – polar orbit satellite and MSG – geostationary orbit satellite). The methodology is applied to the East African highlands, and results are compared to eddy covariance measurements at one site. Results show that the methodology produces ET estimates that have high skills in reproducing the daily fluctuation in ET but tends to underestimate ET on the average. It is concluded that the synergistic use of the polar-orbiting MODIS data and the geostationary-orbiting SEVIRI data has potential to produce reliable daily ET, but further research is needed to improve the accuracy of the results. This study also proposes an operational new dryness index that can be calculated from the satellite-based actual daily ET estimates and reference daily ET estimates based on SEVIRI data and weather forecast air temperature. Comparison of this index against ground measurements of actual daily ET at one site indicates that the new dryness index is operational for drought monitoring.

The use of remote sensing to quantify wetland loss in the Choke Mountain range, Upper Blue Nile basin, Ethiopia

2010-08-25T00:00:00+02:00

The use of remote sensing to quantify wetland loss in the Choke Mountain range, Upper Blue Nile basin, Ethiopia

Hydrology and Earth System Sciences Discussions, 7, 6243-6284, 2010

Author(s): E. Teferi, S. Uhlenbrook, W. Bewket, J. Wenninger, and B. Simane

Wetlands provide multiple ecosystem services such as storing and regulating water flows and water quality, providing unique habitats to flora and fauna, and regulating micro-climatic conditions. Conversion of wetlands for agricultural use is a widespread practice in Ethiopia, particularly in the southwestern part where wetlands cover large areas. Although there are many studies on land cover and land use changes in this region, comprehensive studies on wetlands are still missing. Hence, extent and rate of wetland loss at regional scale is unknown. The objective of this paper is to quantify wetland dynamics and estimate wetland loss in the Choke Mountain range (area covering 17 443 km²) in the Upper Blue Nile basin, a key headwater region of the river Nile. Therefore, satellite remote sensing images of the period 1986–2005 were considered. To create images of surface reflectance that are radiometrically consistent, a combination of cross-calibration and atmospheric correction (Vogelman-DOS3) methods was used. A hybrid supervised/unsupervised classification approach was used to classify the images. Overall accuracies of 94.1% and 93.5% and Kappa Coefficients of 0.908 and 0.913 for the 1986 and 2005 imageries, respectively were obtained. The results showed that 607 km² of seasonal wetland with low moisture and 22.4 km² of open water are lost in the study area during the period 1986 to 2005. The current situation in the wetlands of Choke Mountain is characterized by further degradation which calls for wetland conservation and rehabilitation efforts through incorporating wetlands into watershed management plans.

Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops

2010-08-25T00:00:00+02:00

Combined use of optical and radar satellite data for the monitoring of irrigation and soil moisture of wheat crops

Hydrology and Earth System Sciences Discussions, 7, 6207-6242, 2010

Author(s): R. Fieuzal, B. Duchemin, L. Jarlan, M. Zribi, F. Baup, O. Merlin, G. Dedieu, J. Garatuza-Payan, C. Watt, and A. Chehbouni

The objective of this study is to get a better understanding of radar signal over irrigated wheat fields and to assess the potentialities of radar observations for the monitoring of soil moisture. Emphasis is put on the use of high spatial and temporal resolution satellite data (ENVISAT/ASAR and FORMOSAT-2). Time series of images were collected over the Yaqui irrigated area (Mexico) throughout one agricultural season from December 2007 to May 2008, together with measurements of soil and vegetation characteristics and agricultural practices. The comprehensive analysis of these data indicates that the sensitivity of the radar signal to vegetation is masked by the variability of soil conditions. On-going irrigated areas can be detected all over the wheat growing season. The empirical algorithm developed for the retrieval of topsoil moisture from ENVISAT/ASAR images takes advantage of the unique capabilities of the FORMOSAT-2 instrument to monitor the seasonality of wheat canopies. Topsoil moisture estimates are scattered at the timing of plant emergence and during plant senescence. Estimates are much more accurate from tillering to grain filling stages with an absolute error about 9% (0.09 m³ m⁻³, 35% in relative value). This result is attractive since topsoil moisture is estimated at a high spatial resolution (i.e. over subfields of about 5 ha) for a large range of biomass water content (from 5 and 65 t ha⁻¹) independently from the viewing angle of ASAR acquisition (incidence angles IS1 to IS6).

Remotely sensed latent heat fluxes for improving model predictions of soil moisture: a case study

2010-08-25T00:00:00+02:00

Remotely sensed latent heat fluxes for improving model predictions of soil moisture: a case study

Hydrology and Earth System Sciences Discussions, 7, 6179-6205, 2010

Author(s): J. M. Schuurmans, F. C. van Geer, and M. F. P. Bierkens

This paper investigates whether the use of remotely sensed latent heat fluxes improves the accuracy of spatially-distributed soil moisture predictions by a hydrological model. By using real data we aim to show the potential and limitations in practice. We use (i) satellite data of both ASTER and MODIS for the same two days in the summer of 2006 that, in association with the Surface Energy Balance Algorithm for Land (SEBAL), provides us the spatial distribution of daily ET_act and (ii) an operational physically based distributed (25 m×25 m) hydrological model of a small catchment (70 km²) in The Netherlands that simulates the water flow in both the unsaturated and saturated zone. Firstly, model outcomes of ET_act are compared to the processed satellite data. Secondly, we perform data assimilation that updates the modelled soil moisture. We show that remotely sensed ET_act is useful in hydrological modelling for two reasons. Firstly, in the procedure of model calibration: comparison of modeled and remotely sensed ET_act together with the outcomes of our data assimilation procedure points out potential model errors (both conceptual and flux-related). Secondly, assimilation of remotely sensed ET_act results in a realistic spatial adjustment of soil moisture, except for the area with forest and deep groundwater levels. As both ASTER and MODIS images were available for the same days, this study provides also an excellent opportunity to compare the worth of these two satellite sources. It is shown that, although ASTER provides much better insight in the spatial distribution of ET_act due to its higher spatial resolution than MODIS, they appeared in this study just as useful.

Mapping snow depth return levels: smooth spatial modeling versus station interpolation

2010-08-25T00:00:00+02:00

Mapping snow depth return levels: smooth spatial modeling versus station interpolation

Hydrology and Earth System Sciences Discussions, 7, 6129-6177, 2010

Author(s): J. Blanchet and M. Lehning

For adequate risk management in mountainous countries, hazard maps for extreme snow events are needed. This requires the computation of spatial estimates of return levels. In this article we use recent developments in extreme value theory and compare two main approaches for mapping snow depth return levels from in situ measurements. The first one is based on the spatial interpolation of pointwise extremal distributions (the so-called Generalized Extreme Value distribution, GEV henceforth) computed at station locations. The second one is new and based on the direct estimation of a spatially smooth GEV distribution with the joint use of all stations. We compare and validate the different approaches for modeling annual maximum snow depth measured at 100 sites in Switzerland during winters 1965–1966 to 2007–2008. The results show a better performance of the smooth GEV distribution fitting, in particular where the station network is sparser. Smooth return level maps can be computed from the fitted model without any further interpolation. Their regional variability can be revealed by removing the altitudinal dependent covariates in the model. We show how return levels and their regional variability are linked to the main climatological patterns of Switzerland.

Uncertainty in climate change impacts on water resources in the Rio Grande Basin, Brazil

2010-08-25T00:00:00+02:00

Uncertainty in climate change impacts on water resources in the Rio Grande Basin, Brazil

Hydrology and Earth System Sciences Discussions, 7, 6099-6128, 2010

Author(s): M. T. Nóbrega, W. Collischonn, C. E. M. Tucci, and A. R. Paz

We quantify uncertainty in the impacts of climate change on the discharge of the Rio Grande, a major tributary of the River Paraná in South America and one of the most important basins in Brazil for water supply and hydro-electric power generation. We consider uncertainty in climate projections associated with the SRES (greenhouse-gas) emission scenarios (A1b, A2, B1, B2) and increases in global mean air temperature of 1 to 6 °C for the HadCM3 GCM as well as uncertainties related to GCM structure. For the latter, multimodel runs using 6 GCMs (CCCMA CGCM31, CSIRO Mk30, IPSL CM4, MPI ECHAM5, NCAR CCSM30, UKMO HadGEM1) and HadCM3 as baseline, for a + 2 °C increase in global mean temperature. Pattern-scaled GCM-outputs are applied to a large-scale hydrological model (MGB-IPH) of the Rio Grande Basin. Based on simulations using HadCM3, mean annual river discharge increases, relative to the baseline period (1961–1990), by + 5% to + 10% under the SRES emissions scenarios and from + 8% to + 51% with prescribed increases in global mean air temperature of between 1 and 6 °C. Substantial uncertainty in projected changes to mean river discharge (− 28% to + 13%) under the 2 °C warming scenario is, however, associated with the choice of GCM. We conclude that, in the case of the Rio Grande Basin, the most important source of uncertainty derives from the GCM rather than the emission scenario or the magnitude of rise in mean global temperature.

Reconstructing the tropical storm Ketsana flood event in Marikina River, Philippines

2010-08-25T00:00:00+02:00

Reconstructing the tropical storm Ketsana flood event in Marikina River, Philippines

Hydrology and Earth System Sciences Discussions, 7, 6081-6097, 2010

Author(s): C. C. Abon, C. P. C. David, and N. E. B. Pellejera

In September 2009, tropical storm Ketsana (local name: TS Ondoy) hit Metro Manila and brought an anomalous volume of rain that exceeded the Philippines' forty-year meteorological record. The storm caused exceptionally high and extensive flooding. Part of this study was a survey conducted along the stretch of the Marikina River, one of the major rivers that flooded. Hydraulic and hydrologic modeling was carried out to understand the mechanism that brought the flood. The study revealed that while there were anthropogenic factors that exacerbated flooding in Marikina, the observed flood heights can be simulated in the models generated. Peak floods occurred at different hours along the river resulting from the transmission of water from the main watershed to the downstream areas and the contribution of smaller tributaries entering the main river. Prediction of flood heights and the use of the known time lag between the peak rainfall and the peak runoff could be utilized to issue timely flood forecasts to allow people to prepare for future flooding.