scholarly journals Flood Simulations in Mid-Latitude Agricultural Land Using Regional Current and Future Extreme Weathers

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2421
Author(s):  
Nobuaki Kimura ◽  
Hirohide Kiri ◽  
Sachie Kanada ◽  
Iwao Kitagawa ◽  
Ikuo Yoshinaga ◽  
...  
Keyword(s):  
Agricultural Land ◽  
Climate Model ◽  
Flood Disaster ◽  
Rainfall Data ◽  
Extreme Weather Events ◽  
Rainfall Runoff ◽  
The Future ◽  
Flood Simulations ◽  
Rainfall Runoff Model ◽  
Runoff Model

Recent extreme weather events like the August 2016 flood disaster have significantly affected farmland in mid-latitude regions like the Tokachi River (TR) watershed, the most productive farmland in Japan. The August 2016 flood disaster was caused by multiple typhoons that occurred in the span of two weeks and dealt catastrophic damage to agricultural land. This disaster was the focus of our flood model simulations. For the hydrological model input, the rainfall data with 0.04° grid space and an hourly interval were provided by a regional climate model (RCM) during the period of multiple typhoon occurrences. The high-resolution data can take account of the geographic effects, hardly reproduced by ordinary RCMs. The rainfall data drove a conceptual, distributed rainfall–runoff model, embedded in the integrated flood analysis system. The rainfall–runoff model provided discharges along rivers over the TR watershed. The RCM also provided future rainfall data with pseudo-global warming climate, assuming that the August 2016 disaster could reoccur again in the late 21st century. The future rainfall data were used to conduct a future flood simulation. With bias corrections, current and future flood simulations showed the potential inundated areas along riverbanks based on flood risk levels. The crop field-based agricultural losses in both simulations were estimated. The future cost may be two to three times higher as indicated by slightly higher simulated future discharge peaks in tributaries.

Effect of rainfall data errors on the optimized values of model parameters

Soil Research ◽  
1982 ◽  
Vol 20 (1) ◽  
pp. 15
Author(s):  
WC Boughton ◽  
FT Sefe
Keyword(s):  
Storage Capacity ◽  
Rainfall Data ◽  
Model Parameters ◽  
Similar Magnitude ◽  
Rainfall Runoff ◽  
Data Errors ◽  
Cast Doubt ◽  
Rainfall Runoff Model ◽  
Induced Changes ◽  
Runoff Model

The rainfall input to a rainfall-runoff model was arbitrarily increased and decreased in order to determine the magnitude of corresponding changes in optimized values of the model parameters. The optimized capacities of moisture stores representing surface storage capacity of a catchment changed by average amounts of +24% and -20% as rainfall input was changed by +10% and -10%, respectively. Values of other parameters showed changes of similar magnitude, but there was no uniformity in the magnitude of induced changes from catchment to catchment. The results cast doubt on the validity of relating optimized values of model parameters to physical characteristics of catchments.

The effect of rainfall measurement uncertainties on rainfall–runoff processes modelling

2007 ◽  
Vol 55 (4) ◽  
pp. 103-111 ◽  
Author(s):  
D. Stransky ◽  
V. Bares ◽  
P. Fatka
Keyword(s):  
Measurement Errors ◽  
Dynamic Test ◽  
Systematic Errors ◽  
Rain Gauge ◽  
Rainfall Data ◽  
Test Duration ◽  
Rainfall Runoff ◽  
Rainfall Volume ◽  
Rainfall Runoff Model ◽  
Runoff Model

Rainfall data are a crucial input for various tasks concerning the wet weather period. Nevertheless, their measurement is affected by random and systematic errors that cause an underestimation of the rainfall volume. Therefore, the general objective of the presented work was to assess the credibility of measured rainfall data and to evaluate the effect of measurement errors on urban drainage modelling tasks. Within the project, the methodology of the tipping bucket rain gauge (TBR) was defined and assessed in terms of uncertainty analysis. A set of 18 TBRs was calibrated and the results were compared to the previous calibration. This enables us to evaluate the ageing of TBRs. A propagation of calibration and other systematic errors through the rainfall–runoff model was performed on experimental catchment. It was found that the TBR calibration is important mainly for tasks connected with the assessment of peak values and high flow durations. The omission of calibration leads to up to 30% underestimation and the effect of other systematic errors can add a further 15%. The TBR calibration should be done every two years in order to catch up the ageing of TBR mechanics. Further, the authors recommend to adjust the dynamic test duration proportionally to generated rainfall intensity.

scholarly journals Enhancing Automated Water Level Control at Navigable Waterways by High-Resolution Weather Predictions

10.29007/tfbm ◽  
2018 ◽  
Author(s):  
Julia Kasper ◽  
Georg Pranner ◽  
Franz Simons ◽  
Michael Denhard ◽  
Carsten Thorenz
Keyword(s):  
High Resolution ◽  
Water Level ◽  
Extreme Weather Events ◽  
Rainfall Runoff ◽  
Level Control ◽  
Weather Events ◽  
Rainfall Runoff Model ◽  
Feed Forward Controller ◽  
Runoff Model ◽  
The Ideal

Heavy rainfall can cause large variations in the water level of navigable waterways when a lot of urban runoff is generated on sealed surfaces and discharged into the river. Due to climate change, extreme weather events will increase in intensity and frequency demanding a better automated water level control at impounded waterways. High- resolution forecasts of catchment rainfall are intended to serve as input to a rainfall- runoff model. Based on the resulting discharge forecasts, a model predictive feed forward controller calculates the ideal water level and discharge across the barrage. The control system is completed by a PI control loop. In this way water level deviations and discharge peaks resulting from stormwater overflow events can be reduced, which enhances the safety of shipping. Regarding the uncertainties of weather predictions, the consequences of an underestimated or overestimated overflow discharge are investigated.

Perhitungan ketersediaan air permukaan di Indonesia berdasarkan data satelit

2018 ◽  
Vol 13 (2) ◽  
pp. 115-130 ◽  
Author(s):  
Radhika Radhika ◽  
Rendy Firmansyah ◽  
Waluyo Hatmoko
Keyword(s):  
Surface Water ◽  
Water Resources ◽  
Water Availability ◽  
River Flow ◽  
Rainfall Data ◽  
Rainfall Runoff ◽  
Satellite Technology ◽  
Rainfall Runoff Model ◽  
The Tropics ◽  
Runoff Model

Information on water availability is vital in water resources management. Unfortunately, information on the condition of hydrological data, either river flow data, or rainfall data is very limited temporally and spatially. With the availability of satellite technology, rainfall in the tropics can be monitored and recorded for further analysis. This paper discusses the calculation of surface water availability based on rainfall data from TRMM satellite, and then Wflow, a distributed rainfall-runoff model generates monthly time runoff data from 2003 to 2015 for all river basin areas in Indonesia. It is concluded that the average surface water availability in Indonesia is 88.3 thousand m3/s or equivalent to 2.78 trillion m3/ year. This figure is lower than the study of Water Resources Research Center 2010 based on discharge at the post estimated water that produces 3.9 trillion m3/year, but very close to the study of Aquastat FAO of 2.79 trillion m3 / year. The main benefit of this satellite-based calculation is that at any location in Indonesia, potential surface water can be obtained by multiplying the area of the catchment and the runoff height.

scholarly journals Commercial microwave links as rainfall input data in urban hydrological modelling

2021 ◽  
Author(s):  
Greta Cazzaniga ◽  
Carlo De Michele ◽  
Cristina Deidda ◽  
Michele D'Amico ◽  
Antonio Ghezzi ◽  
...  
Keyword(s):  
River Discharge ◽  
Hydrological Model ◽  
Warning System ◽  
Signal Propagation ◽  
Rainfall Data ◽  
Data Availability ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
Runoff Model ◽  
Commercial Microwave Links

<p>Many studies in literature have showed that hydrological models are highly sensitive to spatial variability of the rainfall field. Limited and inaccurate rainfall observations can negatively affect flood forecasting and the decision-making processes based on warning system. This problem becomes much more evident in urban catchments which usually covers huge areas and where the runoff process is faster, due to the highly impervious surfaces. Given this, it is a priority to develop always new operational instruments which can improve rainfall data availability and accurately quantify rainfall variability in space. To face this challenge, in the recent years, it has been investigated the use of commercial microwave links (CML) as opportunistic rainfall sensors which could be integrated with traditional rainfall observations in areas lacking sensors. The technique relies on the well-established relationship between CML's signal attenuation and rainfall intensity across the signal propagation path. Here, we assess the operational potential of a CML network, located in the northern area of Lambro river (Lombardia region, Italy). This urbanized region is of great hydrological interest, since it is often subjected to flash floods, hence it requires a robust and accurate warning system. We considered a set of about 80 CMLs distributed quite uniformly over the entire study area and we assessed if and how rainfall data collected by them can improve river discharge predictions. To this aim, we implemented a semi-distributed rainfall-runoff model, which reproduces the river flow at the outlet section in Lesmo (Monza e Brianza), and we fed the hydrological model with CML rainfall data. We tested the use of CML rainfall data as input to the hydrological model. In particular, we used path-averaged rainfall intensities, calculated from CML path attenuation, as point measurements with a weight inversely proportional to CML length. To check the suitability of CML data as input to our urban rainfall-runoff model, we compared the observed river discharge with the predicted one, obtained using different rainfall data layouts. Indeed, we tested CML data but also rain gauges measurements and a combination of CML and rain gauge observations.</p>

Parameterization of the rainfall-runoff model in changing climate

2021 ◽  
Author(s):  
Milica Aleksić ◽  
Patrik Sleziak ◽  
Kamila Hlavčová
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Climate Scenario ◽  
Future Climate ◽  
Future Climate Change ◽  
Model Parameters ◽  
Rainfall Runoff ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

AbstractA conceptual rainfall-runoff model was used for estimating the impact of climate change on the runoff regime in the Myjava River basin. Changes in climatic characteristics for future decades were expressed by a regional climate model using the A1B emission scenario. The model was calibrated for 1981–1990, 1991–2000, 2001–2010, 2011–2019. The best set of model parameters selected from the recent calibration period was used to simulate runoff for three periods, which should reflect the level of future climate change. The results show that the runoff should increase in the winter months (December and January) and decrease in the summer months (June to August). An evaluation of the long-term mean monthly runoff for the future climate scenario indicates that the highest runoff will occur in March.

scholarly journals A Comparison of Design Storms for Urban Drainage System Applications

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 757 ◽  
Author(s):  
Balbastre-Soldevila ◽  
García-Bartual ◽  
Andrés-Doménech
Keyword(s):  
Temporal Pattern ◽  
Drainage System ◽  
Rainfall Data ◽  
Data Series ◽  
Rainfall Time Series ◽  
Rainfall Runoff ◽  
Maximum Rainfall ◽  
Intensity Duration Frequency ◽  
Rainfall Runoff Model ◽  
Runoff Model

The present research develops a systematic application of a selected family of 11 well-known design storms, all of them obtained from the same rainfall data sample. Some of them are fully consistent with the intensity–duration–frequency (IDF) curves, while others are built according to typical observed patterns in the historical rainfall series. The employed data series consists on a high-resolution rainfall time series in Valencia (Spain), covering the period from 1990 to 2012. The goal of the research is the systematic comparison of these design storms, paying special attention to some relevant quantitative properties, as the maximum rainfall intensity, the total cumulative rainfall depth or the temporal pattern characterising the synthetic storm. For comparison purposes, storm duration was set to 1 hour and return period equal to 25 years in all cases. The comparison is enhanced by using each of the design storms as rainfall input to a calibrated urban hydrology rainfall–runoff model, yielding to a family of hydrographs for a given neighbourhood of the city of Valencia (Spain). The discussion and conclusions derived from the present research refer to both, the comparison between design storms and the comparison of resulting hydrographs after the application of the mentioned rainfall–runoff model. Seven of the tested design storms yielded to similar overall performance, showing negligible differences in practice. Among them, only Average Variability Method (AVM) and Two Parameter Gamma function (G2P) incorporate in their definition a temporal pattern inferred from empirical patterns identified in the historical rainfall data used herein. The remaining four design storms lead to more significant discrepancies attending both to the rainfall itself and to the resulting hydrograph. Such differences are ~8% concerning estimated discharges.

scholarly journals Hydrological modelling under climate change considering nonstationarity and seasonal effects

2015 ◽  
Vol 47 (2) ◽  
pp. 260-273 ◽  
Author(s):  
Kue Bum Kim ◽  
Hyun-Han Kwon ◽  
Dawei Han
Keyword(s):  
Hydrological Model ◽  
Hydrological Modelling ◽  
Seasonal Effects ◽  
Model Parameters ◽  
Observation Data ◽  
Rainfall Runoff ◽  
Climate Condition ◽  
The Future ◽  
Rainfall Runoff Model ◽  
Runoff Model

Traditional hydrological modelling assumes that the catchment does not change with time. However, due to changes of climate and catchment conditions, this stationarity assumption may not be valid in the future. It is a challenge to make the hydrological model adaptive to the future climate and catchment conditions. In this study IHACRES, a conceptual rainfall–runoff model, is applied to a catchment in southwest England. Long observation data (1961–2008) are used and seasonal calibration (only the summer) has been done since there are significant seasonal rainfall patterns. Initially, the calibration is based on changing the model parameters with time by adapting the parameters using the step forward and backward selection schemes. However, in the validation, both models do not work well. The problem is that the regression with time is not reliable since the trend may not be in a monotonic linear relationship with time. Therefore, a new scheme is explored. Only one parameter is selected for adjustment while the other parameters are set as the fixed and the regression of one optimised parameter is made not only against time but climate condition. The result shows that this nonstationary model works well both in the calibration and validation periods.

scholarly journals Evaluating the impact of rainfall–runoff model structural uncertainty on the hydrological rating of regional climate model simulations

2021 ◽  
Author(s):  
Hamouda Dakhlaoui ◽  
Khalil Djebbi
Keyword(s):  
Climate Model ◽  
Regional Climate ◽  
Reference Period ◽  
Structural Uncertainty ◽  
Rainfall Runoff ◽  
Performance Indexes ◽  
Climate Model Evaluation ◽  
Rainfall Runoff Model ◽  
The Impact ◽  
Runoff Model

Abstract We propose to evaluate the impact of rainfall–runoff model (RRM) structural uncertainty on climate model evaluation, performed within a process-oriented framework using the RRM. Structural uncertainty is assessed with an ensemble approach using three conceptual RRMs (HBV, IHACRES and GR4J). We evaluate daily precipitation and temperature from 11 regional climate models forced by five general circulation models (GCM–RCMs), issued from EURO-CORDEX. The assessment was performed over the reference period (1970–2000) for five catchments situated in northern Tunisia. Seventeen discharge performance indexes were used to explore the representation of hydrological processes. The three RRMs performed well over the reference period, with Nash–Sutcliffe efficiency values ranging from 0.70 to 0.90 and bias close to 0%. The ranking of GCM–RCMs according to hydrological performance indexes is more meaningful before the bias correction, which considerably reduces the differences between GCM- and RCM-driven hydrological simulations. Our results illustrate a strong similarity between the different RRMs in terms of raw GCM–RCM performances over the reference period for the majority of performance indexes, in spite of their different model structures. This proves that the structural uncertainty induced by RRMs does not affect GCM–RCM evaluation and ranking, which contributes to consolidate the RRM as a standard tool for climate model evaluation.

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