A reliable rainfall–runoff model for flood forecasting: review and application to a semi-urbanized watershed at high flood risk in Italy

Many rainfall–runoff (RR) models are available in the scientific literature. Selecting the best structure and parameterization for a model is not straightforward and depends on a broad number of factors, including climatic conditions, catchment characteristics, temporal/spatial resolution and model objectives. In this study, the RR model 'Modello Idrologico Semi-Distribuito in continuo' (MISDc), mainly developed for flood simulation in Mediterranean basins, was tested on the Seveso basin, which is stressed several times a year by flooding events mainly caused by excessive urbanization. The work summarizes a compendium of the MISDc applications over a wide range of catchments in European countries and then it analyses the performances over the Seveso basin. The results show a good fit behaviour during both the calibration and the validation periods with a Nash–Sutcliffe coefficient index larger than 0.9. Moreover, the median volume and peak discharge errors calculated on several flood events were less than 25%. In conclusion, we can be assured that the reliability and computational speed could make the MISDc model suitable for flood estimation in many catchments of different geographical contexts and land use characteristics. Moreover, MISDc will also be useful for future support of real-time decision-making for flood risk management in the Seveso basin

MSWEP : 3-hourly 0.25° global gridded precipitation (1979-2015) by merging gauge, satellite, and reanalysis data

Current global precipitation (P) datasets do not take full advantage of the complementary nature of satellite and reanalysis data. Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) version 1.1, a global P dataset for the period 1979-2015 with a 3hourly temporal and 0.25 degrees ffi spatial resolution, specifically designed for hydrological modeling. The design philosophy of MSWEP was to optimally merge the highest quality P data sources available as a function of timescale and location. The long-term mean of MSWEP was based on the CHPclim dataset but replaced with more accurate regional datasets where available. A correction for gauge under-catch and orographic effects was introduced by inferring catchment-average P from streamflow (Q) observations at 13 762 stations across the globe. The temporal variability of MSWEP was determined by weighted averaging of P anomalies from seven datasets; two based solely on interpolation of gauge observations (CPC Unified and GPCC), three on satellite remote sensing (CMORPH, GSMaP-MVK, and TMPA 3B42RT), and two on atmospheric model reanalysis (ERA-Interim and JRA-55). For each grid cell, the weight assigned to the gauge-based estimates was calculated from the gauge network density, while the weights assigned to the satellite-and reanalysis-based estimates were calculated from their comparative performance at the surrounding gauges. The quality of MSWEP was compared against four state-of-the-art gauge-adjusted P datasets (WFDEI-CRU, GPCP-1DD, TMPA 3B42, and CPC Unified) using independent P data from 125 FLUXNET tower stations around the globe. MSWEP obtained the highest daily correlation coefficient (R) among the five P datasets for 60.0% of the stations and a median R of 0.67 vs. 0.44-0.59 for the other datasets. We further evaluated the performance of MSWEP using hydrological modeling for 9011 catchments (< 50 000 km(2)) across the globe. Specifically, we calibrated the simple conceptual hydrological model HBV (Hydrologiska Byrans Vattenbalansavdelning) against daily Q observations with P from each of the different datasets. For the 1058 sparsely gauged catchments, representative of 83.9% of the global land surface (excluding Antarctica), MSWEP obtained a median calibration NSE of 0.52 vs. 0.29-0.39 for the other P datasets. MSWEP is available via http://www.gloh2o.org

Evaluation of two new-generation global soil databases for macro-scale hydrological modelling in Norway

Lack of national soil property maps limits the studies of soil moisture (SM) dynamics in Norway. One alternative is to apply the global soil data as input for macro-scale hydrological modelling, but the quality of these data is still unknown. The objectives of this study are 1) to evaluate two recent global soil databases (Wise30sec and SoilGrids) in comparison with data from local soil profiles; 2) to evaluate which database supports better model performance in terms of river discharge and SM for three macro-scale catchments in Norway and 3) to suggest criteria for the selection of soil data for models with different complexity. The global soil databases were evaluated in three steps: 1) the global soil data are compared directly with the Norwegian forest soil profiles; 2) the simulated discharge based on the two global soil databases is compared with observations and 3) the simulated SM is compared with three global SM products. Two hydrological models were applied to simulate discharge and SM: the Soil and Water Integrated Model (SWIM) and the Variable Infiltration Capacity (VIC) model. The comparison with data from local soil profiles shows that SoilGrids has smaller mean errors than Wise30sec, especially for upper soil layers, but both soil databases have large root mean squared errors and poor correlations. SWIM generally performs better in terms of discharge using SoilGrids than using Wise30sec and the simulated SM has higher correlations with the SM products. In contrast, the VIC model is less sensitive to soil input data and the simulated SM using Wise30sec is higher correlated with the SM products than using SoilGrids. Based on the results, we conclude that the global soil databases can provide reasonable soil property information at coarse resolutions and large areas. The selection of soil input data should depend on the characteristics of both models and study areas.publishedVersio

Opportunities and challenges in using catchment-scale storage estimates from cosmic ray neutron sensors for rainfall-runoff modelling

Acknowledgements We thank the Macaulay Development Trust and School of Geosciences, University of Aberdeen for KDPs scholarship. JG would like to acknowledge funding from the Royal Society and the Carnegie Trust for the Universities of Scotland (project 70112). JG and LV acknowledge funding from the UK Natural Environment Research Council (project NE/N007611/1 and CC13_080). MW was supported by the Rural & Environment Science & Analytical Services Division of the Scottish Government. RR received funding from the Natural Environment Research Council (projects NE/M003086/1, NE/R004897/1 and NE/T005645/1) and from the International Atomic Energy Agency of the United Nations (IAEA/UN) (project CRP D12014). Special thanks to Carol Taylor, Jessica Fennell, Alice Poli and many more for assistance with fieldwork. Finally, we would like to acknowledge Kenneth Loades for providing us with essential equipment for soil sampling and thank David Finlay and his team for enabling land access in Elsick.Peer reviewedPostprin

Combining satellite radar altimetry, SAR surface soil moisture and GRACE total storage changes for hydrological model calibration in a large poorly gauged catchment

The availability of data is a major challenge for hydrological modelling in large parts of the world. Remote sensing data can be exploited to improve models of ungauged or poorly gauged catchments. In this study we combine three datasets for calibration of a rainfall-runoff model of the poorly gauged Okavango catchment in Southern Africa: (i) surface soil moisture (SSM) estimates derived from radar measurements onboard the Envisat satellite; (ii) radar altimetry measurements by Envisat providing river stages in the tributaries of the Okavango catchment, down to a minimum river width of about one hundred meters; and (iii) temporal changes of the Earth's gravity field recorded by the Gravity Recovery and Climate Experiment (GRACE) caused by total water storage changes in the catchment. The SSM data are shown to be helpful in identifying periods with over-respectively underestimation of the precipitation input. The accuracy of the radar altimetry data is validated on gauged subbasins of the catchment and altimetry data of an ungauged subbasin is used for model calibration. The radar altimetry data are important to condition model parameters related to channel morphology such as Manning's roughness. GRACE data are used to validate the model and to condition model parameters related to various storage compartments in the hydrological model (e.g. soil, groundwater, bank storage etc.). As precipitation input the FEWS-Net RFE, TRMM 3B42 and ECMWF ERA-Interim datasets are considered and compared

Global-scale regionalization of hydrologic model parameters

Current state-of-the-art models typically applied at continental to global scales (hereafter called macroscale) tend to use a priori parameters, resulting in suboptimal streamflow (Q) simulation. For the first time, a scheme for regionalization of model parameters at the global scale was developed. We used data from a diverse set of 1787 small-to-medium sized catchments ( 10-10,000 km(2)) and the simple conceptual HBV model to set up and test the scheme. Each catchment was calibrated against observed daily Q, after which 674 catchments with high calibration and validation scores, and thus presumably good-quality observed Q and forcing data, were selected to serve as donor catchments. The calibrated parameter sets for the donors were subsequently transferred to 0.5 degrees grid cells with similar climatic and physiographic characteristics, resulting in parameter maps for HBV with global coverage. For each grid cell, we used the 10 most similar donor catchments, rather than the single most similar donor, and averaged the resulting simulated Q, which enhanced model performance. The 1113 catchments not used as donors were used to independently evaluate the scheme. The regionalized parameters outperformed spatially uniform (i.e., averaged calibrated) parameters for 79% of the evaluation catchments. Substantial improvements were evident for all major Koppen-Geiger climate types and even for evaluation catchments>5000 km distant from the donors. The median improvement was about half of the performance increase achieved through calibration. HBV with regionalized parameters outperformed nine state-of-the-art macroscale models, suggesting these might also benefit from the new regionalization scheme. The produced HBV parameter maps including ancillary data are available via

Development of a semi-automatic approach to estimate pre-event soil moisture for Flash Flood Guidance in low mountain ranges (Saxony)

This thesis is written as a cumulative dissertation based on peer-reviewed papers and supplemented by yet unpublished results. It presents methods and results that contribute to a novel approach for estimating water storage within the soil-water-plant system at a single site or in a small catchment (< 100 km2). The focus is on estimating the current/pre-event condition of a study area using simulated soil moisture and applying it as an indicator for flash flood forecasting. These two steps were combined in a semi-automatic framework that was used as a tool for flash flood monitoring after the Flash Flood Guidance (FFG) concept. This includes catchments for which Hydro-meteorological data and reliable site characteristics are not available. The overall objective was to demonstrate the capabilities and limitations of the regionally applicable modeling framework based on a lumped-physical model and open-source input data. The questions to be answered are: How reliable are the model outputs estimated by an uncalibrated-lumped model based on regional parameterization and forcing data? What are the potential uncertainties and limitations of such a framework? What are the potential applications of water storage in flood monitoring? The data were derived from freely available datasets. Meteorological input data can come from various sensor networks integrated in an open sensor web, mainly from the German Meteorological Service (DWD) and e.g., the forest climate stations of Sachsenforst. The model description required datasets for elevation (10 m, State Office for Environment, Agriculture and Geology-LfULG), land cover (Copernicus: Land Cover 100m), soil characteristics (BK50, LfULG) and soil profiles from the German National Forest Inventory (NFI). In addition, satellite-based soil moisture product (SMAP-L4-GPH from the National Aeronautics and Space Administration-NASA), water gauges data (LfULG) and eddy covariance flux cluster sites of the chair Meteorology at TU Dresden were used for validation. The first publication provides the framework and elaborates on the integration of a model into the open-data platform. The BROOK90 model (R version) was embedded in an open sensor web to estimate daily water balance components for more than 6,000 (sub-) catchments in Saxony. The model performance was validated with stream gauge observations in ten selected head catchments for discharge and with SMAP-L4-GPH for evapotranspiration and soil moisture. The results indicate that the framework is able to provide reliable soil retention estimates in high resolution. The second publication addresses the potential use of radar precipitation in this framework. Here the focus is on examining long-term radar-derived precipitation to improve water balance estimates due to its advantages in spatial coverage. The DWD’s re-analysis radar product, RADKLIM, was applied and aggregated for daily model input. A comparison between radar and rain gauge precipitation was performed to evaluate the quality of the product at the study sites, including the compensation for the catch loss in precipitation using the Richter correction. The results show the satisfactory performance of the framework with radar precipitation. The third publication demonstrates the application of model output to flood warnings. FFG was modified and applied to estimate rainfall thresholds considering the effects of antecedent soil moisture. Once rainfall threshold curves are calculated, only information on rainfall and soil moisture information is needed to issue a warning of a potential flash flood. The method was applied in the Wernersbach catchment in the Tharandt Forest and validated with historical events. The results of the contingency table show the potential of this tool for flash flood warning, but it should be tested with other rainfall runoff models and more catchments prone to flash floods.:Abstract/Zusammenfassung/Tóm tắt 1. Introduction 1.1 Motivation and scope 1.2 Problem formulation 1.3 Target setting 1.4 Structure of the thesis 2. Adjusted Flash Flood Guidance (FFG) framework 2.2 Terminology and definitions 2.2.1 Flash flood 2.2.2 Small catchment 2.3 FFG concept 2.4 Adjusted FFG framework 3. Core publications of the PhD thesis 4. Major findings 5. Conclusions and outlook References List of Abbreviations List of figures List of the author’s publication Appendixes including the core publications ErklärungDie vorliegende Arbeit ist eine kumulative Dissertation, die auf begutachteten Arbeiten basiert und durch bisher unveröffentlichte Ergebnisse ergänzt wird. Sie stellt Methoden und Ergebnisse vor, die zu einem neuartigen Ansatz zur Abschätzung der Wasserspeicherung im System Boden-Wasser-Pflanze an einem einzelnen Standort oder in einem kleinen Einzugsgebiet (< 100 km2) beitragen. Der Schwerpunkt liegt auf der Abschätzung des aktuellen/vor einem Ereignis herrschenden Zustands eines Untersuchungsgebiets unter Verwendung simulierter Bodenfeuchte und deren Anwendung als Indikator für die Vorhersage von Sturzfluten. Diese beiden Schritte wurden in einem halbautomatischen Modell zusammengefasst, das als Werkzeug für die Überwachung von Sturzfluten nach dem Konzept des Flash Flood Guidance (FFG) verwendet wird. Dies schließt Standorte/Einzugsgebiete ein, für die keine hydrometeorologischen Daten und/oder zuverlässige Standortmerkmale verfügbar sind. Das Gesamtziel bestand darin, die Fähigkeiten und Grenzen des regional anwendbaren Modells auf der Grundlage eines pauschalen physikalischen Modells und von Open-Source-Eingangsdaten zu demonstrieren. Die zu beantwortenden Fragen lauten: Wie zuverlässig sind die von einem unkalibrierten eindimensionalen Modell auf der Grundlage regionaler Parametrisierungs- und Antriebsdaten geschätzten Modellergebnisse? Was sind die potenziellen Unsicherheiten und Grenzen eines solchen Modells? Welches sind die möglichen Anwendungen der simulierten Komponenten des Wasserhaushalts bei der Überwachung von Hochwasser? Die Daten werden aus frei verfügbaren Datensätzen abgeleitet. Die meteorologischen Eingangsdaten stammen aus verschiedenen Sensornetzwerken, die in einem Open Sensor Web integriert sind, hauptsächlich vom Deutschen Wetterdienst (DWD) und z.B. den Waldklimastationen von Sachsenforst. Für die Modellbeschreibung wurden Datensätze für Geländehöhe (10 m, Landesamt für Umwelt, Landwirtschaft und Geologie - LfULG), Landbedeckung (Copernicus: Land Cover 100m), Bodeneigenschaften (BK50, LfULG) und Bodenprofile aus der Bundeswaldinventur (BWI) benötigt. Darüber hinaus werden satellitengestützte Bodenfeuchteprodukte (SMAP-L4-GPH der National Aeronautics and Space Administration-NASA), Pegeldaten (LfULG) und Eddy-Kovarianz-Flusscluster-Standorte des Lehrstuhls für Meteorologie der TU Dresden zur Validierung verwendet. Die erste Veröffentlichung liefert den Rahmen und erläutert die Integration eines Modells in die offene Datenplattform. Das Modell BROOK90 (R-Version) wurde in ein offenes Sensornetz eingebettet, um tägliche Wasserhaushaltskomponenten für mehr als 6,000 (Teil-)Einzugsgebiete in Sachsen zu schätzen. Die Leistung des Modells wurde anhand von Pegelbeobachtungen in zehn ausgewählten Einzugsgebieten für den Abfluss und mit SMAP-L4-GPH für die Evapotranspiration und Bodenfeuchte validiert. Die Ergebnisse zeigen, dass das System in der Lage ist, zuverlässige Schätzungen der Bodenretention in hoher Auflösung zu liefern. Die zweite Veröffentlichung befasst sich mit der möglichen Nutzung von Radarniederschlägen in diesem Rahmen. Hier liegt der Schwerpunkt auf der Untersuchung des langfristigen, vom Radar abgeleiteten Niederschlags zur Verbesserung der Wasserbilanzschätzungen aufgrund seiner Vorteile bei der räumlichen Abdeckung. Das Reanalyse-Radarprodukt des DWD, RADKLIM, wurde verwendet und für tägliche Modelleingaben aggregiert. Es wurde ein Vergleich zwischen Radar- und Regenmesser-Niederschlag durchgeführt, um die Qualität des Produkts an den Untersuchungsstandorten zu bewerten, einschließlich der Kompensation des Niederschlagsverlusts durch die Richter-Korrektur. Die Ergebnisse zeigen die zufriedenstellende Leistung des Rahmens mit Radarniederschlag. Die dritte Veröffentlichung demonstriert die Anwendung der Modelldaten auf Hochwasserwarnungen. Der Leitfaden für Sturzflutwarnungen wurde modifiziert und zur Schätzung der Niederschlagsschwellen unter Berücksichtigung der Auswirkungen der vorherrschenden Bodenfeuchte angewandt. Sobald die Niederschlagsschwellenkurven berechnet sind, werden nur noch Informationen über Niederschlag und Bodenfeuchte benötigt, um eine Warnung vor einer möglichen Sturzflut auszusprechen. Die Methode wurde im Einzugsgebiet des Wernersbachs und im Tharandter Wald angewandt und mit historischen Ereignissen validiert. Die Ergebnisse der Kontingenztabelle zeigen das Potenzial dieses Werkzeugs für die Sturzflutwarnung, es sollte jedoch mit anderen Niederschlagsabflussmodellen und weiteren Einzugsgebieten, die für Sturzfluten anfällig sind, getestet werden.:Abstract/Zusammenfassung/Tóm tắt 1. Introduction 1.1 Motivation and scope 1.2 Problem formulation 1.3 Target setting 1.4 Structure of the thesis 2. Adjusted Flash Flood Guidance (FFG) framework 2.2 Terminology and definitions 2.2.1 Flash flood 2.2.2 Small catchment 2.3 FFG concept 2.4 Adjusted FFG framework 3. Core publications of the PhD thesis 4. Major findings 5. Conclusions and outlook References List of Abbreviations List of figures List of the author’s publication Appendixes including the core publications ErklärungLuận án tiến sĩ này được viết như một luận án tích lũy dựa trên các bài báo đã được bình duyệt và được bổ sung bởi các kết quả chưa được công bố. Nó trình bày các phương pháp và kết quả góp phần vào một cách tiếp cận mới để ước tính trữ lượng nước trong hệ thống đất-nước- thực vật tại một địa điểm hoặc trong một lưu vực nhỏ (<100 km2). Trọng tâm là ước tính tình trạng hiện tại / trước sự kiện của khu vực nghiên cứu bằng cách sử dụng độ ẩm đất mô phỏng và áp dụng nó như một chỉ báo để dự báo lũ quét. Hai bước này được kết hợp trong một khuôn khổ bán tự động được sử dụng như một công cụ để giám sát lũ quét dựa theo khái niệm Hướng dẫn về lũ quét (FFG). Điều này bao gồm các địa điểm / lưu vực không có sẵn dữ liệu khí tượng thủy văn và / hoặc các đặc điểm thiếu thông tin mô tả chia tiết đáng tin cậy. Mục tiêu tổng thể là chứng minh các khả năng và hạn chế của khung mô hình áp dụng trong khu vực dựa trên một mô hình vật lý tổng hợp và dữ liệu đầu vào nguồn mở. Các câu hỏi cần được trả lời là: Các kết quả đầu ra của mô hình được ước tính bằng một mô hình gộp chưa hiệu chỉnh dựa trên tham số vùng và dữ liệu đáng tin cậy đến mức nào? Những điểm không chắc chắn và hạn chế tiềm ẩn của một khuôn khổ như vậy là gì? Các ứng dụng tiềm năng của thành phần cân bằng nước mô phỏng trong giám sát lũ lụt là gì? Dữ liệu được lấy từ các bộ dữ liệu miễn phí và có sẵn. Dữ liệu đầu vào về khí tượng đến từ các mạng cảm biến khác nhau được tích hợp trong một Open Sensor Web, chủ yếu từ Cơ quan Khí tượng Đức (DWD) và các trạm khí hậu rừng của Sachsenforst. Mô tả mô hình yêu cầu bộ dữ liệu về độ cao (10 m, Văn phòng bang về Môi trường, Nông nghiệp và Địa chất-LfULG), lớp phủ đất (Copernicus: Land Cover 100m), đặc điểm của đất (BK50, LfULG) và cấu hình đất từ Kiểm kê Rừng Quốc gia Đức (NFI). Ngoài ra, sản phẩm độ ẩm của đất dựa trên vệ tinh (SMAP-L4-GPH từ Cơ quan Hàng không và Vũ trụ Quốc gia-NASA), dữ liệu các trạm thủy văn (LfULG) và các cụm địa điểm eddy covariance được giám sát bởi khoa Khí tượng học tại TU Dresden được sử dụng để xác nhận kết quả mô hình đầu ra. Ấn phẩm đầu tiên cung cấp khuôn khổ và trình bày chi tiết về việc tích hợp một mô hình vào nền tảng dữ liệu mở. Mô hình BROOK90 (phiên bản R) được nhúng vào một trang web cảm biến mở để ước tính các thành phần cân bằng nước hàng ngày cho hơn 6000 lưu vực (phụ) ở Sachsen. Hiệu suất của mô hình đã được xác nhận với các quan sát bằng dữ liệu dòng chảy ở mười lưu vực đầu nguồn được chọn và với SMAP-L4-GPH cho thành phần thoát hơi nước và độ ẩm của đất. Kết quả chỉ ra rằng khung có thể cung cấp các ước tính đáng tin cậy về khả năng giữ nước của đất ở độ phân giải cao. Ấn phẩm thứ hai đề cập đến khả năng sử dụng lượng mưa radar trong khuôn khổ này. Ở đây, trọng tâm là kiểm tra lượng mưa dài hạn có nguồn gốc từ radar để cải thiện ước tính cân bằng nước do lợi thế của nó trong phạm vi bao phủ không gian. Sản phẩm radar phân tích lại của DWD, RADKLIM, đã được áp dụng và tổng hợp để nhập mô hình hàng ngày. So sánh giữa lượng mưa bằng radar và máy đo mưa đã được thực hiện để đánh giá chất lượng của sản phẩm tại các điểm nghiên cứu, bao gồm cả việc bù đắp cho lượng mưa thất thoát bằng cách sử dụng hiệu chỉnh độ Richter. Kết quả cho thấy hiệu suất khả quan của khung với lượng mưa radar. Ấn phẩm thứ ba trình bày việc áp dụng đầu ra mô hình để cảnh báo lũ lụt. Hướng dẫn về lũ quét đã được sửa đổi và áp dụng để ước tính ngưỡng lượng mưa xem xét ảnh hưởng của độ ẩm đất trước đây. Khi đường cong ngưỡng mưa được tính toán, chỉ cần thông tin về lượng mưa và thông tin về độ ẩm của đất để đưa ra cảnh báo về khả năng xảy ra lũ quét. Phương pháp này đã được áp dụng ở lưu vực Wernersbach, trong Rừng Tharandt và được xác nhận với các sự kiện lịch sử. Kết quả của bảng dự phòng cho thấy tiềm năng của công cụ này để cảnh báo lũ quét, nhưng nó nên được thử nghiệm với các mô hình dòng chảy lượng mưa khác và các lưu vực dễ xảy ra lũ quét hơn.:Abstract/Zusammenfassung/Tóm tắt 1. Introduction 1.1 Motivation and scope 1.2 Problem formulation 1.3 Target setting 1.4 Structure of the thesis 2. Adjusted Flash Flood Guidance (FFG) framework 2.2 Terminology and definitions 2.2.1 Flash flood 2.2.2 Small catchment 2.3 FFG concept 2.4 Adjusted FFG framework 3. Core publications of the PhD thesis 4. Major findings 5. Conclusions and outlook References List of Abbreviations List of figures List of the author’s publication Appendixes including the core publications Erklärun

Combining satellite radar altimetry, SAR surface soil moisture and GRACE total storage changes for model calibration and validation in a large ungauged catchment

The availability of data is a major challenge for hydrological modelling in large parts of the world. Remote sensing data can be exploited to improve models of ungauged or poorly gauged catchments. In this study we combine three datasets for calibration and validation of a rainfall-runoff model of the ungauged Okavango catchment in Southern Africa: (i) Surface soil moisture (SSM) estimates derived from SAR measurements onboard the Envisat satellite; (ii) Radar altimetry measurements by Envisat providing river stages in the tributaries of the Okavango catchment, down to a minimum width of about one hundred meters; and (iii) Temporal changes of the Earth’s gravity field recorded by the Gravity Recovery and Climate Experiment (GRACE) caused by total water storage changes in the catchment. The SSM data are compared to simulated moisture conditions in the top soil layer. They cannot be used for model calibration but support bias identification in the precipitation data. The accuracy of the radar altimetry data is validated on gauged subbasins of the catchment and altimetry data of an ungauged subbasin is used for model calibration. The radar altimetry data are important to condition model parameters related to channel morphology such as Manning’s roughness. GRACE data are used to validate the model and to condition model parameters related to various storage compartments in the hydrological model (e.g. soil, groundwater, bank storage etc.). As precipitation input the FEWS-Net RFE, TRMM 20 3B42 and ECMWF ERA-Interim data sets are considered and compared

Soil moisture-runoff relation at the catchment scale as observed with coarse resolution microwave remote sensing

International audienceMicrowave remote sensing offers emerging capabilities to monitor global hydrological processes. Instruments like the two dedicated soil moisture missions SMOS and HYDROS or the Advanced Scatterometer onboard METOP will provide a flow of coarse resolution microwave data, suited for macro-scale applications. Only recently, the scatterometer onboard of the European Remote Sensing Satellite, which is the precursor instrument of the Advanced Scatterometer, has been used successfully to derive soil moisture information at global scale with a spatial resolution of 50 km. Concepts of how to integrate macro-scale soil moisture data in hydrologic models are however still vague. In fact, the coarse resolution of the data provided by microwave radiometers and scatterometers is often considered to impede hydrological applications. Nevertheless, even if most hydrologic models are run at much finer scales, radiometers and scatterometers allow monitoring of atmosphere-induced changes in regional soil moisture patterns. This may prove to be valuable information for modelling hydrological processes in large river basins (>10 000 km2. In this paper, ERS scatterometer derived soil moisture products are compared to measured runoff of the Zambezi River in south-eastern Africa for several years (1992?2000). This comparison serves as one of the first demonstrations that there is hydrologic relevant information in coarse resolution satellite data. The observed high correlations between basin-averaged soil moisture and runoff time series (R2>0.85) demonstrate that the seasonal change from low runoff during the dry season to high runoff during the wet season is well captured by the ERS scatterometer. It can be expected that the high correlations are to a certain degree predetermined by the pronounced inter-annual cycle observed in the discharge behaviour of the Zambezi. To quantify this effect, time series of anomalies have been compared. This analysis showed that differences in runoff from year to year could, to some extent, be explained by soil moisture anomalies