A Long–Term Response-Based Rainfall-Runoff Hydrologic Model: Case Study of The Upper Blue Nile

This study develops a response-based hydrologic model for long-term (continuous) rainfall-runoff simulations over the catchment areas of big rivers. The model overcomes the typical difficulties in estimating infiltration and evapotranspiration parameters using a modified version of the Soil Conservation Service curve number SCS-CN method. In addition, the model simulates the surface and groundwater hydrograph components using the response unit-hydrograph approach instead of using a linear reservoir routing approach for routing surface and groundwater to the basin outlet. The unit-responses are Geographic Information Systems (GIS)-pre-calculated on a semi-distributed short-term basis and applied in the simulation in every time step. The unit responses are based on the time-area technique that can better simulate the real routing behavior of the basin. The model is less sensitive to groundwater infiltration parameters since groundwater is actually controlled by the surface component and not the opposite. For that reason, the model is called the SCHydro model (Surface Controlled Hydrologic model). The model is tested on the upper Blue Nile catchment area using 28 years daily river flow data set for calibration and validation. The results show that SCHydro model can simulate the long-term transforming behavior of the upper Blue Nile basin. Our initial assessment of the model indicates that the model is a promising tool for long-term river flow simulations, especially for long-term forecasting purposes due to its stability in performing the water balance.

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Application of Remotely Sensed Rainfall Data in Rainfall-Runoff Modelling. A Case of Pangani River Basin, Tanzania

Tanzania Journal of Engineering and Technology ◽

10.52339/tjet.v35i1.465 ◽

2014 ◽

Vol 35 (1) ◽

pp. 1-14

Author(s):

Joel Nobert ◽

Patric Kibasa

Keyword(s):

River Basin ◽

Average Method ◽

River Flow ◽

Tropical Rainfall Measuring Mission ◽

Rainfall Data ◽

Coefficient Of Determination ◽

Rainfall Runoff ◽

Data Set ◽

Satellite Rainfall ◽

Areal Rainfall

Rainfall runoff modelling in a river basin is vital for number of hydrologic applicationincluding water resources assessment. However, rainfall data from sparse gauging stationsare usually inadequate for modelling which is a major concern in Tanzania. This studypresents the results of comparison of Tropical Rainfall Measuring Mission (TRMM)satellite rainfall products at daily and monthly time-steps with ground stations rainfalldata; and explores the possibility of using satellite rainfall data for rainfall runoffmodelling in Pangani River Basin, Tanzania. Statistical analysis was carried out to find thecorrelation between the ground stations data and TRMM estimates. It was found thatTRMM estimates at monthly scale compare reasonably well with ground stations data.Time series comparison was also done at daily and annual time scales. Monthly and annualtime series compared well with coefficient of determination of 0.68 and 0.70, respectively.It was also found that areal rainfall comparison in the northern parts of the study area hadpoor results compared to the rest of areas. On the other hand, rainfall runoff modellingwith ground stations data alone and TRMM data set alone was carried out using five Real-Time River Flow Forecasting System models and then outputs combined by Models OutputsCombination Techniques. The results showed that ground stations data performed betterduring calibration period with coefficient of efficiency of 76.7%, 81.7% and 89.1% forSimple Average Method, Weight Average Method and Neural Network Method respectively.Simulation results using TRMM data were 59.8%, 73.5% and 76.8%. It can therefore beconcluded that TRMM data are adequate and promising in hydrological modelling.

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Stochastic generation and disaggregation of hourly rainfall series for continuous hydrological modelling and flood control reservoir design

Water Science & Technology ◽

10.2166/wst.2002.0035 ◽

2002 ◽

Vol 45 (2) ◽

pp. 113-119 ◽

Cited By ~ 5

Author(s):

B. Hingray ◽

E. Monbaron ◽

I. Jarrar ◽

A.C. Favre ◽

D. Consuegra ◽

...

Keyword(s):

Flood Control ◽

Statistical Information ◽

Rainfall Series ◽

Rainfall Runoff ◽

Time Step ◽

Detention Basin ◽

Hourly Rainfall ◽

State Frequency ◽

Detention Basins

In the urban environment, stormwater detention basins are a powerful means to limit the frequency of sewer system failures and consecutive urban flooding. To design such waterworks or to check their efficiency, it is possible to carry out continuous rainfall-runoff modelling. A long-term discharge series obtained from a long-term rainfall series is used as input for a storage model describing the detention basin behaviour: the basin behaviour may be consequently studied over a long period. The provided statistical information on the working state frequency, failure frequency, … of the detention basin is of high interest for the basin diagnostic or for its design. This paper presents the whole methodology which leads to production of such statistical information and especially: the models used to generate long term rainfall series with a short time step, the rainfall-runoff model used to transform the later series into a long term discharge series, and the model used to describe the behaviour of the detention basin. This methodology was applied to evaluate the efficiency of 4 detention basins built for stormwater control and flood mitigation. They are situated on a Swiss urban catchment (Chamberonne catchment – 40 km2) collecting water from the Mèbre and Sorge rivers.

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A Long-Term Land Surface Hydrologic Fluxes and States Dataset for China

Journal of Hydrometeorology ◽

10.1175/jhm-d-13-0170.1 ◽

2014 ◽

Vol 15 (5) ◽

pp. 2067-2084 ◽

Cited By ~ 86

Author(s):

Xue-Jun Zhang ◽

Qiuhong Tang ◽

Ming Pan ◽

Yin Tang

Keyword(s):

Soil Moisture ◽

Water Balance ◽

Snow Cover ◽

Land Surface ◽

Hydrologic Model ◽

Reliable Estimate ◽

Time Step ◽

Snow Cover Extent ◽

Monthly Streamflow

Abstract A long-term consistent and comprehensive dataset of land surface hydrologic fluxes and states will greatly benefit the analysis of land surface variables, their changes and interactions, and the assessment of land–atmosphere parameterizations for climate models. While some offline model studies can provide balanced water and energy budgets at land surface, few of them have presented an evaluation of the long-term interaction of water balance components over China. Here, a consistent and comprehensive land surface hydrologic fluxes and states dataset for China using the Variable Infiltration Capacity (VIC) hydrologic model driven by long-term gridded observation-based meteorological forcings is developed. The hydrologic dataset covers China with a 0.25° spatial resolution and a 3-hourly time step for 1952–2012. In the dataset, the simulated streamflow matches well with the observed monthly streamflow at the large river basins in China. Given the water balance scheme in the VIC model, the overall success at runoff simulations suggests that the long-term mean evapotranspiration is also realistically estimated. The simulated soil moisture generally reproduces the seasonal variation of the observed soil moisture at the ground stations where long-term observations are available. The modeled snow cover patterns and monthly dynamics bear an overall resemblance to the Northern Hemisphere snow cover extent data from the National Snow and Ice Data Center. Compared with global product of a similar nature, the dataset can provide a more reliable estimate of land surface variables over China. The dataset, which will be publicly available via the Internet, may be useful for hydroclimatological studies in China.

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A weather dependent approach to estimate the annual course of vegetation parameters for water balance simulations on the meso- and macroscale

Advances in Geosciences ◽

10.5194/adgeo-32-15-2012 ◽

2012 ◽

Vol 32 ◽

pp. 15-21 ◽

Cited By ~ 8

Author(s):

K. Förster ◽

M. Gelleszun ◽

G. Meon

Keyword(s):

Climate Change ◽

Water Balance ◽

Hydrologic Model ◽

Climate Change Scenarios ◽

Time Step ◽

Area Index ◽

Vegetation Height ◽

Current Climate ◽

Vegetation Parameters

Abstract. In order to simulate long-term water balances hydrologic models have to be parameterized for several types of vegetation. Furthermore, a seasonal dependence of vegetation parameters has to be accomplished for a successful application. Many approaches neglect inter-annual variability and shifts due to climate change. In this paper a more comprehensive approach from literature was evaluated and applied to long-term water balance simulations, which incorporates temperature, humidity and maximum bright sunshine hours per day to calculate a growing season index (GSI). A validation of this threshold-related approach is carried out by comparisons with normalized difference vegetation index (NDVI) data and observations from the phenological network in the state of Lower Saxony. The annual courses of GSI and NDVI show a good agreement for numerous sites. A comparison with long-term observations of leaf onset and offset taken from the phenological network also revealed a good model performance. The observed trends indicating a shift toward an earlier leaf onset of 3 days per decade in the lowlands were reproduced very well. The GSI approach was implemented in the hydrologic model Panta Rhei. For the common vegetation parameters like leaf area index, vegetated fraction, albedo and the vegetation height a minimum value and a maximum value were defined for each land surface class. These parameters were scaled with the computed GSI for every time step to obtain a seasonal course for each parameter. Two simulations were carried out each for the current climate and for future climate scenarios. The first run was parameterized with a static annual course of vegetation parameters. The second run incorporates the new GSI approach. For the current climate both models produced comparable results regarding the water balance. Although there are no significant changes in modeled mean annual evapotranspiration and runoff depth in climate change scenarios, mean monthly values of these water balance components are shifted toward a lower runoff in spring and higher values during the winter months.

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Exploring the added value of a long-term multidisciplinary dataset in drought research – a drought catalogue for southwestern Germany dating back to 1801

10.5194/nhess-2019-424 ◽

2020 ◽

Author(s):

Mathilde Erfurt ◽

Georgios Skiadaresis ◽

Erik Tijdeman ◽

Veit Blauhut ◽

Jürgen Bauhus ◽

...

Keyword(s):

River Flow ◽

Historical Context ◽

Added Value ◽

Drought Indices ◽

Data Set ◽

Tree Ring Data ◽

Multiple Variables ◽

Societal Impacts ◽

Hydrological Droughts

Abstract. Droughts are multidimensional hazards that can lead to substantial environmental and societal impacts. To understand causes and impacts, multiple variables need to be considered. Many studies identified past drought events and investigated drought propagation from meteorological droughts via soil moisture to hydrological droughts and some studies have included the impacts of these different types of drought. Here, we analyse different droughts and their impacts in a regional context using a multidisciplinary approach and compiled a comprehensive and long-term data set to place recent drought events into a historical context. We assembled a dataset of drought indices and recorded impacts over the last 218 years in southwestern Germany. Meteorological and river-flow indices were used to assess the natural drought dynamics. In addition, tree-ring data and recorded impacts were utilized to investigate drought events from an ecological and social perspective. Since 1801, 20 extreme droughts were identified as common extreme events when applying the different indicators. All events were associated with societal impacts. Our multi-dataset approach provides insights into similarities but also the unique aspects of different drought indices and highlights the unprecedented frequency and severity of droughts in the 21st century.

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Identifying rainfall-runoff events in discharge time series: A data-driven method based on Information Theory

10.5194/hess-2018-427 ◽

2018 ◽

Author(s):

Stephanie Thiesen ◽

Paul Darscheid ◽

Uwe Ehret

Keyword(s):

Predictive Power ◽

Conditional Entropy ◽

Data Driven ◽

Rainfall Runoff ◽

Discharge Time ◽

Time Step ◽

Data Set ◽

Discharge Data ◽

Previous Time Step ◽

Runoff Events

Abstract. In this study, we propose a data-driven approach to automatically identify rainfall-runoff events in discharge time series. The core of the concept is to construct and apply discrete multivariate probability distributions to obtain probabilistic predictions of each time step being part of an event. The approach permits any data to serve as predictors, and it is non-parametric in the sense that it can handle any kind of relation between the predictor(s) and the target. Each choice of a particular predictor data set is equivalent to formulating a model hypothesis. Among competing models, the best is found by comparing their predictive power in a training data set with user-classified events. For evaluation, we use measures from Information Theory such as Shannon Entropy and Conditional Entropy to select the best predictors and models and, additionally, measure the risk of overfitting via Cross Entropy and Kullback–Leibler Divergence. As all these measures are expressed in bit, we can combine them to identify models with the best tradeoff between predictive power and robustness given the available data. We applied the method to data from the Dornbirnerach catchment in Austria distinguishing three different model types: Models relying on discharge data, models using both discharge and precipitation data, and recursive models, i.e., models using their own predictions of a previous time step as an additional predictor. In the case study, the additional use of precipitation reduced predictive uncertainty only by a small amount, likely because the information provided by precipitation is already contained in the discharge data. More generally, we found that the robustness of a model quickly dropped with the increase in the number of predictors used (an effect well known as the Curse of Dimensionality), such that in the end, the best model was a recursive one applying four predictors (three standard and one recursive): discharge from two distinct time steps, the relative magnitude of discharge in a 65-hour time window and event predictions from the previous time step. Applying the model reduced the uncertainty about event classification by 77.8 %, decreasing Conditional Entropy from 0.516 to 0.114 bits. Given enough data to build data-driven models, their potential lies in the way they learn and exploit relations between data unconstrained by functional or parametric assumptions and choices. And, beyond that, the use of these models to reproduce a hydrologist's way to identify rainfall-runoff events is just one of many potential applications.

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Subsurface runoff and recharge dynamics in a Mediterranean catchment based on StorAge Selection functions and end-member splitting analysis

10.5194/egusphere-egu2020-829 ◽

2020 ◽

Author(s):

Matthias Sprenger ◽

Pilar Llorens ◽

Francesc Gallart ◽

Jérôme Latron

Keyword(s):

Stream Water ◽

Pore Space ◽

Data Driven ◽

High Temporal Resolution ◽

Rainfall Runoff ◽

Catchment Scale ◽

Data Set ◽

Isotope Data ◽

Subsurface Runoff

Investigations at the long-term experimental catchment Vallcebre in the Pyrenees revealed that rainfall-runoff dynamics are highly variable due to the Mediterranean climatic conditions affecting the storage and release of water in the subsurface1. In a changing climate, to the consequences of which could lead to more variations in catchment wetness due to an increase in both droughts and high intensity rainfalls, there is a strong need to better understand subsurface storage and runoff processes.While our previous isotope studies (using 2H and 18O) demonstrated a pronounced heterogeneity of water flow in the unsaturated zone at the plot scale2, we also observed that the contributions of young waters to catchment runoff are highly dependent on the catchments wetness3. These analyses provided a basis from which we present new insights into the relationship between subsurface runoff and storage dynamics applying StorAge Selection functions4 and end-member splitting analysis5. Thus, we combined modeling and data-driven approaches to disentangle the partitioning of subsurface waters into storage and runoff based on water age dynamics.We gathered an extensive isotope data set with >550 rainfall samples and >980 stream samples taken at high temporal resolution (30 minutes to one week), with highest frequencies during high discharge to improve the coverage of rainfall-runoff events. Using this high-frequency isotope data set, we calibrated the StorAge Selection functions and put special emphasis on the representation of the isotopic response during high flow rainfall-runoff periods. We further tested if time-variant representations of StorAge Selection functions dependent on varying wetness improves the stream water isotope simulations and the ways in which isotope data from different compartments (groundwater and tree water) can assist in constraining the parameter space. Furthermore, end-member splitting analysis provided an independent view into the flow dynamics based on these long-term isotope data sets. As such, the analysis allowed us to derive estimates of the dynamics of rainfall partitioning into runoff and evapotranspiration. Therefore, the combination of the modeling and data-driven approaches enabled an assessment of the dynamics of subsurface runoff at the catchment scale underlining the relevance of heterogeneous flow pattern that were observed on the plot scale.References<ol><li>Llorens, P. et al. What have we learnt about mediterranean catchment hydrology? 30 years observing hydrological processes in the Vallcebre research catchments. Geogr. Res. Lett. 44, 475&#8211;502; 10.18172/cig.3432 (2018).</li> <li>Sprenger, M., Llorens, P., Cayuela, C., Gallart, F. & Latron, J. Mechanisms of consistently disjunct soil water pools over (pore) space and time. Hydrol. Earth Syst. Sci. 23, 2751&#8211;2762; 10.5194/hess-23-2751-2019 (2019).</li> <li>Gallart, F. et al. Investigating young water fractions in a small Mediterranean mountain catchment: both precipitation forcing and sampling frequency matter. Hydrol. Process. (in review).</li> <li>Benettin, P. & Bertuzzo, E. tran-SAS v1.0: a numerical model to compute catchment-scale hydrologic transport using StorAge Selection functions. Geosci. Model Dev. 11, 1627&#8211;1639; 10.5194/gmd-11-1627-2018 (2018).</li> <li>Kirchner, J. W. & Allen, S. T. Seasonal partitioning of precipitation between streamflow and evapotranspiration, inferred from end-member splitting analysis. Hydrology and Earth System Sciences, 24, 17&#8211;39; 10.5194/hess-24-17-2020 (2020).</li> </ol>

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Comparison and evaluation of satellite derived precipitation products for hydrological modeling of the Zambezi River Basin

Hydrology and Earth System Sciences ◽

10.5194/hess-16-489-2012 ◽

2012 ◽

Vol 16 (2) ◽

pp. 489-500 ◽

Cited By ~ 81

Author(s):

T. Cohen Liechti ◽

J. P. Matos ◽

J.-L. Boillat ◽

A. J. Schleiss

Keyword(s):

Water Resource Management ◽

Hydrological Modeling ◽

Warning System ◽

Volume Ratio ◽

Hydrologic Model ◽

Time Step ◽

Data Set ◽

Operation Rules ◽

Threshold Criterion ◽

Trmm 3B42

Abstract. In the framework of the African DAms ProjecT (ADAPT), an integrated water resource management study in the Zambezi Basin is currently under development. In view of the sparse gauging network for rainfall monitoring, the observations from spaceborne instrumentation currently produce the only available rainfall data for a large part of the basin. Three operational and acknowledged high resolution satellite derived estimates: the Tropical Rainfall Measuring Mission product 3B42 (TRMM 3B42), the Famine Early Warning System product 2.0 (FEWS RFE2.0) and the National Oceanic and Atmospheric Administration/Climate Prediction Centre (NOAA/CPC) morphing technique (CMORPH) are analyzed in terms of spatial and temporal repartition of the precipitations. They are compared to ground data for the wet seasons of the years 2003 to 2009 on a point to pixel basis at daily, 10-daily and monthly time steps and on a pixel to pixel basis for the wet seasons of the years 2003 to 2007 at monthly time steps. The general North-South gradient of precipitation is captured by all the analyzed products. Regarding the spatial heterogeneity, FEWS pixels are much more inter-correlated than TRMM and CMORPH pixels. For a rainfall homogeneity threshold criterion of 0.5 global mean correlation coefficient, the area of each sub-basin should not exceed a circle of 2.5° latitude/longitude radius for FEWS and a circle of 0.75° latitude/longitude radius for TRMM and CMORPH considering rectangular meshes. In terms of reliability, the correspondence of all estimates with ground data increases with the time step chosen for the analysis. The volume ratio computation indicates that CMORPH is overestimating the rainfall by nearly 50%. The statistics of TRMM and FEWS estimates show quite similar results. Due to its lower inter-correlation and longer data set, the TRMM 3B42 product is chosen as input for the hydraulic-hydrologic model of the basin. Further work will focus on the calibration of the hydraulic-hydrological model of the basin, including the major existing hydraulic structures with their operation rules.

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Assessing the impact of PET estimation methods on hydrologic model performance

Hydrology Research ◽

10.2166/nh.2020.066 ◽

2020 ◽

Author(s):

Dilhani Ishanka Jayathilake ◽

Tyler Smith

Keyword(s):

Potential Evapotranspiration ◽

Model Performance ◽

Monte Carlo Sampling ◽

Hydrologic Model ◽

Estimation Methods ◽

Rainfall Runoff ◽

Data Set ◽

Rainfall Runoff Model ◽

The Impact ◽

Runoff Model

Abstract Evapotranspiration is a necessary input and one of the most uncertain hydrologic variables for quantifying the water balance. Key to accurately predicting hydrologic processes, particularly under data scarcity, is the development of an understanding of the regional variation of the impact of potential evapotranspiration (PET) data inputs on model performance and parametrization. This study explores this impact using four different potential evapotranspiration products (of varying quality). For each data product, a lumped conceptual rainfall–runoff model (GR4J) is tested on a sample of 57 catchments included in the MOPEX data set. Monte Carlo sampling is performed, and the resulting parameter sets are analyzed to understand how the model responds to differences in the forcings. Test catchments are classified as energy- or water-limited using the Budyko framework and by eco-region, and the results are further analyzed. While model performance (and parameterization) in water-limited sites was found to be largely unaffected by the differences in the evapotranspiration inputs, in energy-limited sites model performance was impacted as model parameterizations were clearly sensitive to evapotranspiration inputs. The quality/reliability of PET data required to avoid negatively impacting rainfall–runoff model performance was found to vary primarily based on the water and energy availability of catchments.

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LONG-TERM VARIABILITY OF THE ABSOLUTE ANNUAL MINIMUM WATER FLOW OF THE RIVERS OF UKRAINE

Visnyk of Taras Shevchenko National University of Kyiv Geology ◽

10.17721/1728-2713.87.13 ◽

2019 ◽

pp. 89-95 ◽

Cited By ~ 1

Author(s):

O. Obodovskiy ◽

O. Lukianets ◽

О. Pochievets ◽

S. Moskalenko

Keyword(s):

Water Flow ◽

River Flow ◽

River Basins ◽

The Black Sea ◽

Left Bank ◽

Small Catchment ◽

Carpathian Region ◽

Catchment Areas ◽

The Absolute

Studies of the variability of the minimum flow of water, which relates to the extreme regime characteristics of river water flow during periods of low water, are relevant. Such information, in general, is the limiting criteria for water consumption, water use and protection of water resources from pollution and depletion, and sometimes are indicators of danger and catastrophe, in particular, during periods of prolonged droughts. This is especially important in the conditions of modern climate change, in which the probability of occurrence of extreme hydrological phenomena increases significantly. To assess the long-term variability of the absolute annual minima of the flow of water from the rivers of Ukraine, sequences of minimum daily average water flows for a multi-year period from 294 gauging stations from the beginning of the observations to 2015 inclusive were formed. The methods of statistical processing of random variables (for determining the norms of runoff, coefficients of variation and asymmetry) and random functions (for constructing integral difference curves) were used. The study of the spatial specifics of changes in the absolute minima of the water flow of the rivers of Ukraine is based on the "Hydrographic zoning of Ukraine's territory". According to it, the territory of Ukraine is divided into hydrographic units — nine areas of river basins and nine sub-basins. The absolute annual minima of river runoff on the territory of Ukraine are recorded during periods of summer-autumn or winter low-water periods. High values of absolute annual minima in the modules of water flow are observed on the rivers of the Carpathian region and reach 8,7 l· s – 1 · km – 2. Basically, such values are on mountain rivers with small catchment areas; on rivers with large catchment areas that extend from the mountain and foothill areas of their flow to the plains, up to 0,9 l· s – 1 · km – 2; on the rivers of the Crimea, the absolute annual minimums in the water flow modules, in the vast majority, vary from 0,0 to 1,8 l· s – 1 · km – 2. Regarding flat river basins, for the rivers of the Vistula basin, the sub-basins of the Pripyat and the Desna, the left-bank part of the Dniester river basin, the range of changes in the absolute annual minima of the water flow modules is 0,20 ÷ 2,9 l·s– 1 ·km– 2. To the south of the indicated flat river basins, the ranges of absolute annual minima are gradually decreasing. On the rivers of the sub-basin of the Middle Dnieper there is 0, 19 ÷ 1,19 l·s– 1 ·km– 2, the subbasin of the Lower Dnieper – 0,04 ÷ 0,42 l · s – 1 · km – 2, the basin of the Southern Bug – 0,09 ÷ 1,75 l· s – 1 · km – 2. And in the basin of the rivers of the Black Sea region there is 0,0 ÷ 0,001 l· s – 1 · km – 2. For river basins of the flat part of Ukraine, the variation of annual minima is within 0,30 ÷ 2,83, the smaller one is the range of variability for the rivers of the Carpathian region – 0,20 ÷ 0,90. The asymmetry coefficients of the minimum river flow during the year for the whole territory of Ukraine range from negative -0,11 ÷ -2,01 to positive values 1,30 ÷ 6,4. The long-term variability of the absolute annual minima of the water flow of the rivers of Ukraine has been studied. Analysis of generalized difference integral curves for the entire set of rivers within the basins and sub-basins of the hydrographic zoning of Ukraine showed for the period of joint observations from 1947 to 2015 marked cyclic component. It manifests itself in a long period of decreasing absolute annual minimum values until 1968-1974, then there is an increase, and at the present time period, after 2006-2010, there is a tendency to decrease.

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