scholarly journals Analysis of low flow indices under varying climatic conditions in Poland

2017 ◽  
Vol 49 (2) ◽  
pp. 373-389 ◽  
Author(s):  
Marzena Osuch ◽  
Renata Romanowicz ◽  
Wai K. Wong
Keyword(s):  
Climate Models ◽  
Climatic Conditions ◽  
Low Flow ◽  
Test Results ◽  
Rainfall Runoff ◽  
Objective Functions ◽  
Rcp 8.5 ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Simulated Time

Abstract Changes in low flow indices under future climates are estimated for eight catchments in Poland. A simulation approach is used to derive daily flows under changing climatic conditions, following RCP 4.5 and RCP 8.5 emission scenarios. The HBV rainfall–runoff model is used to simulate low flows. The model is calibrated and validated using streamflow observations from periods 1971–2000 and 2001–2010. Two objective functions are used for calibration: Nash–Sutcliffe and log transformed Nash–Sutcliffe. Finally, the models are run using the bias-corrected precipitation and temperature data simulated by GCM/RCM models for the periods 2021–2050 and 2071–2100. We estimate low flow indices for the simulated time series, including annual minima of 7-day mean river flows and number, severity and duration of low flow events. We quantify the biases of low flow indices by N-way analysis of variance (ANOVA) analysis and Tukey test. Results indicate a large effect of climate models, as well as objective functions, on the low flow indices obtained. A comparison of indices from the two future periods with the reference period 1971–2000 confirms the trends obtained in previous studies, in the form of a projected decrease in the frequency and intensity of low flow events.

scholarly journals Impact of climate change on the streamflow of the Arjo-Didessa catchment under RCP scenarios

2021 ◽  
Author(s):  
Wudeneh Temesgen Bekele ◽  
Alemseged Tamiru Haile ◽  
Tom Rientjes
Keyword(s):  
Climate Change ◽  
Rainy Season ◽  
Climate Models ◽  
Annual Rainfall ◽  
Rainfall Runoff ◽  
Impact Of Climate Change ◽  
Rcp 8.5 ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

Abstract In this study, the impact of climate change on the streamflow of the Arjo-Didessa catchment, Upper Blue Nile basin, is evaluated. We used the outputs of four climate models for two representative concentration pathway (RCP) climate scenarios, which are RCP 4.5 and RCP 8.5. Streamflow simulation was done by using the HEC-HMS rainfall-runoff model, which was satisfactorily calibrated and validated for the study area. For the historic period (1971–2000), all climate models significantly underestimated the observed rainfall amount for the rainy season. We therefore bias-corrected the climate data before using them as input for the rainfall-runoff model. The results of the four climate models for the period 2041 to 2070 show that annual rainfall is likely to decrease by 0.36 to 21% under RCP 4.5. The projected increases in minimum and maximum temperature will lead to an increase in annual evapotranspiration by 3 to 7%, which will likely contribute to decreasing the annual flows of Arjo-Didessa by 1 to 3%. Our results show that the impact is season dependent, with an increased streamflow in the main rainy season but a decreased flow in the short rainy season and the dry seasons. The magnitudes of projected changes are more pronounced under RCP 8.5 than under RCP 4.5.

scholarly journals Constraining a lumped rainfall-runoff model with piezometry to improve low-flow simulation

2021 ◽  
Author(s):  
Antoine Pelletier ◽  
Vakzen Andréassian
Keyword(s):  
Flow Simulation ◽  
Daily Rainfall ◽  
Climatic Conditions ◽  
Low Flow ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Low Flows ◽  
Sample Test ◽  
Rainfall Runoff Model ◽  
Runoff Model

<p>Most lumped hydrological models are focused on the rainfall-runoff relationship, since climatic conditions are the driving force of the hydrological behaviour of a catchment. Many hydrological models, like the ones used by the French national PREMHYCE platform, only take climatic variables as inputs – daily rainfall and potential evaporation – to simulate and forecast low-flows. Yet, a hydrological drought is generally a medium- to long-term phenomenon, which is the consequence of long records of dry climatic conditions. Daily lumped hydrological models often struggle to integrate these records to reproduce catchment memory.</p><p>In many French catchments, it was observed that this memory of past hydroclimatic conditions is well represented in piezometric signals that are broadly available over the national territory. Indeed, aquifers, especially the large ones, do store water on the long, feeding rivers during droughts: aquifers are not only <em>water carriers</em> – the etymology for the word <em>aquifer </em>– they are also <em>memory carriers</em>. A dataset of 108 catchments, each of them being associated with one or several piezometers, was used to investigate whether the GR6J daily lumped rainfall-runoff model could be constrained by piezometric time series to improve low-flow simulations. We found that a particular state of the model, the exponential store, is particularly well correlated with piezometry in most studied catchments.</p><p>In order to get a univocal relationship between the exponential store and piezometry, a multi-objective calibration approach was implemented, optimising both (i) flow simulation with a criterion focused on low-flows and (ii) affine correspondence between the exponential store level and piezometry. For that purpose, a new parameter was added to the model. The modified calibration was then evaluated through a split-sample test and the performance in simulating particular drought events. The calibrated store-piezometry relationship can now be used for data assimilation to improve low-flow forecasting.</p>

scholarly journals Sensitivity Analysis to Investigate the Reliability of the Grid-Based Rainfall-Runoff Model

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1839 ◽  
Author(s):  
Mun-Ju Shin ◽  
Yun Choi
Keyword(s):  
Water Movement ◽  
Parameter Sensitivity ◽  
Low Flow ◽  
Rainfall Runoff ◽  
Runoff Simulation ◽  
Rainfall Events ◽  
Flow Calculation ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Grid Based

This study aimed to assess the suitability of the parameters of a physically based, distributed, grid-based rainfall-runoff model. We analyzed parameter sensitivity with a dataset of eight rainfall events that occurred in two catchments of South Korea, using the Sobol’ method. Parameters identified as sensitive responded adequately to the scale of the rainfall events and the objective functions employed. Parameter sensitivity varied depending on rainfall scale, even in the same catchment. Interestingly, for a rainfall event causing considerable runoff, parameters related to initial soil saturation and soil water movement played a significant role in low flow calculation and high flow calculation, respectively. The larger and steeper catchment exhibited a greater difference in parameter sensitivity between rainfall events. Finally, we found that setting an incorrect parameter range that is physically impossible can have a large impact on runoff simulation, leading to substantial uncertainty in the simulation results. The proposed analysis method and the results from our study can help researchers using a distributed rainfall-runoff model produce more reliable analysis results.

scholarly journals Component Combination Test to Investigate Improvement of the IHACRES and GR4J Rainfall–Runoff Models

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2126
Author(s):  
Mun-Ju Shin ◽  
Chung-Soo Kim
Keyword(s):  
Flow Simulation ◽  
High Flow ◽  
Low Flow ◽  
Effective Rainfall ◽  
Rainfall Runoff ◽  
Flow Simulations ◽  
New Models ◽  
Pros And Cons ◽  
Rainfall Runoff Model ◽  
Runoff Model

Rainfall–runoff models are not perfect, and the suitability of a model structure depends on catchment characteristics and data. It is important to investigate the pros and cons of a rainfall–runoff model to improve both its high- and low-flow simulation. The production and routing components of the GR4J and IHACRES models were combined to create two new models. Specifically, the GR_IH model is the combination of the production store of the GR4J model and the routing store of the IHACRES model (vice versa in the IH_GR model). The performances of the new models were compared to those of the GR4J and IHACRES models to determine components improving the performance of the two original models. The suitability of the parameters was investigated with sensitivity analysis using 40 years’ worth of spatiotemporally different data for five catchments in Australia. These five catchments consist of two wet catchments, one intermediate catchment, and two dry catchments. As a result, the effective rainfall production and routing components of the IHACRES model were most suitable for high-flow simulation of wet catchments, and the routing component improved the low-flow simulation of intermediate and one dry catchments. Both effective rainfall production and routing components of the GR4J model were suitable for low-flow simulation of one dry catchment. The routing component of the GR4J model improved the low- and high-flow simulation of wet and dry catchments, respectively, and the effective rainfall production component improved both the high- and low-flow simulations of the intermediate catchment relative to the IHACRES model. This study provides useful information for the improvement of the two models.

scholarly journals Impact of the Mean Areal Rainfall Calculation on a Modular Rainfall-Runoff Model

2020 ◽  
Vol 8 (12) ◽  
pp. 980
Author(s):  
Jose Valles ◽  
Gerald Corzo ◽  
Dimitri Solomatine
Keyword(s):  
Divide And Conquer ◽  
Low Flow ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
The Mean ◽  
Areal Rainfall ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
The Relationship ◽  
Runoff Model

Hydrological models are based on the relationship between rainfall and discharge, which means that a poor representation of rainfall produces a poor streamflow result. Typically, a poor representation of rainfall input is produced by a gauge network that is not able to capture the rainfall event. The main objective of this study is to evaluate the impact of the mean areal rainfall on a modular rainfall-runoff model. These types of models are based on the divide-and-conquer approach and two specialized hydrological models for high and low regimes were built and then combined to form a committee of model that takes the strengths of both specialized models. The results show that the committee of models produces a reasonable reproduction of the observed flow for high and low flow regimes. Furthermore, a sensitivity analysis reveals that Ilopango and Jerusalem rainfall gauges are the most beneficial for discharge calculation since they appear in most of the rainfall subset that produces low Root Mean Square Error (RMSE) values. Conversely, the Puente Viejo and Panchimalco rainfall gauges are the least beneficial for the rainfall-runoff model since these gauges appear in most of the rainfall subset that produces high RMSE value.

Construction and Application of Rainfall-Runoff Model during Low Flow at Youngsan River Watershed

2017 ◽  
Vol 13 (6) ◽  
pp. 111-122
Author(s):  
Hyung San Kim ◽  
◽  
Seung Jin Maeng ◽  
Ju Ha Hwang ◽  
Ji Sung Park ◽  
...  
Keyword(s):  
Low Flow ◽  
Rainfall Runoff ◽  
River Watershed ◽  
Rainfall Runoff Model ◽  
Runoff Model

scholarly journals Determination of evaporation from a catchment water balance at a monthly time scale

1997 ◽  
Vol 1 (1) ◽  
pp. 93-100 ◽  
Author(s):  
H. H. G. Savenije
Keyword(s):  
Water Balance ◽  
Time Scale ◽  
Climate Models ◽  
Rainfall Runoff ◽  
Soil Moisture Storage ◽  
Moisture Storage ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Term Storage

Abstract. A method is presented to determine total evaporation from the earth's surface at a spatial scale that is adequate for linkage with climate models. The method is based on the water balance of catchments, combined with a calibrated autoregressive rainfall-runoff model. The time scale used is in the order of decades (10 days) to months. The rainfall-runoff model makes a distinction between immediate processes (interception and short term storage) and the remaining longer-term processes. Besides the calibrated rainfall-runoff model and the time series of observed rainfall and runoff, the method requires a relation between transpiration and soil moisture storage. The method is applied to data of the Bani catchment in Mali, a sub-catchment of the Niger river basin.

scholarly journals From aquifers’ and rivers’ memory to a better low-flow forecasting model

2020 ◽  
Author(s):  
Antoine Pelletier ◽  
Vazken Andréassian
Keyword(s):  
Monitoring Network ◽  
Low Flow ◽  
Rainfall Runoff ◽  
Surface Models ◽  
Forecasting System ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Prior Analysis ◽  
Selection Of ◽  
Made In

<p>The 2019 major drought in northern France highlighted the necessity to design an efficient and reliable low-flow forecasting system. Most forecasting tools, based on rainfall-runoff surface models, could benefit from an utilization of piezometric data, broadly available over the French metropolitan territory: obviously, surface water/groundwater interaction are a key process to explain low-flow dynamics.</p><p>Indeed, aquifers carry most of the hydroclimatic memory of a catchment, which determines the intensity and duration of droughts: a catchment beginning summer with empty aquifers will not have the same trajectory as the same catchment with higher than average piezometric levels. However, the piezometric data itself is not straightforward to use in a hydrological model, since aquifer-river connexions are often equivocal. Thus, a prior analysis of available data is necessary.</p><p>In this work, using 100 catchments of the national French hydroclimatic database and available piezometric data from the national aquifer monitoring network, we performed a comparative memory analysis of piezometry and streamflow, through a simple convolution function. The results were then compared to the behaviour of GR6J, a conceptual lumped rainfall-runoff model. For each catchment of the dataset, a selection of relevant piezometers was made, in the perspective of developing a model incorporating their levels as input data.</p>

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