Hydrological modelling and anthropogenic water use

2021 ◽  
Author(s):  
Ponnambalam Rameshwaran ◽  
Ali Rudd ◽  
Vicky Bell ◽  
Matt Brown ◽  
Helen Davies ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Use ◽  
Hydrological Model ◽  
Model Performance ◽  
River Flows ◽  
Discharge Data ◽  
New Approach ◽  
Water Demands ◽  
The Impact ◽  
Grid Based

<p>Despite Britain’s often-rainy maritime climate, anthropogenic water demands have a significant impact on river flows, particularly during dry summers. In future years, projected population growth and climate change are likely to increase the demand for water and lead to greater pressures on available freshwater resources.</p><p>Across England, abstraction (from groundwater, surface water or tidal sources) and discharge data along with ‘Hands off Flow’ conditions are available for thousands of individual locations; each with a licence for use, an amount, an indication of when abstraction can take place, and the actual amount of water abstracted (generally less than the licence amount). Here we demonstrate how these data can be used in combination to incorporate anthropogenic artificial influences into a grid-based hydrological model. Model simulations of both high and low river flows are generally improved when abstractions and discharges are included, though for some catchments model performance decreases. The new approach provides a methodological baseline for further work investigating the impact of anthropogenic water use and projected climate change on future river flows.</p>

scholarly journals Hydrological model optimization using multi-gauge calibration (MGC) in a mountainous region

2020 ◽  
Author(s):  
Sead Ahmed Swalih ◽  
Ercan Kahya
Keyword(s):  
Climate Change ◽  
Model Calibration ◽  
Hydrological Model ◽  
Model Performance ◽  
Spatial Dimension ◽  
Model Parameters ◽  
Climate Projections ◽  
Predictive Capacity ◽  
Black Sea Region ◽  
The Impact

Abstract It is a challenge for hydrological models to capture complex processes in a basin with limited data when estimating model parameters. This study aims to contribute in this field by assessing the impact of incorporating spatial dimension on the improvement of model calibration. Hence, the main objective of this study was to evaluate the impact of multi-gauge calibration in hydrological model calibration for Ikizdere basin, Black Sea Region in Turkey. In addition, we have incorporated the climate change impact assessment for the study area. Four scenarios were tested for performance assessment of calibration: (1) using downstream flow data (DC), (2) using upstream data (UC), (3) using upstream and downstream data (Multi-Gauge Calibration – MGC), and (4) using upstream and then downstream data (UCDC). The results have shown that using individual gauges for calibration (1 and 2) improve the local predictive capacity of the model. MGC calibration significantly improved the model performance for the whole basin unlike 1 and 2. However, the local gauge calibrations statistical performance, compared to MGC outputs, was better for local areas. The UCDC yields the best model performance and much improved predictive capacity. Regarding the climate change, we did not observe an agreement amongst the future climate projections for the basin towards the end of the century.

scholarly journals Effect of baseline snowpack assumptions in the HySIM model in predicting future hydrological behaviour of a Himalayan catchment

2018 ◽  
Vol 50 (2) ◽  
pp. 691-708 ◽  
Author(s):  
Renji Remesan ◽  
Sazeda Begam ◽  
Ian P. Holman
Keyword(s):  
Climate Change ◽  
Model Performance ◽  
High Elevation ◽  
Climate Impact ◽  
Snow Accumulation ◽  
Response Surfaces ◽  
Impact Response ◽  
Discharge Data ◽  
Climate Impact Assessment ◽  
The Impact

Abstract Glaciers and snowpacks influence streamflow by altering the volume and timing of discharge. Without reliable data on baseline snow and ice volumes, properties and behaviour, initializing hydrological models for climate impact assessment is challenging. Two contrasting HySIM model builds were calibrated and validated against observed discharge data (2000–2008) assuming that snowmelt of the baseline permanent snowpack reserves in the high-elevation sub-catchment are either constrained (snowmelt is limited to the seasonal snow accumulation) or unconstrained (snowmelt is only energy-limited). We then applied both models within a scenario-neutral framework to develop impact response surface of hydrological response to future changes in annual temperature and precipitation. Both models had similar baseline model performance (NSE of 0.69–0.70 in calibration and 0.64–0.66 in validation), but the impact response surfaces differ in the magnitude and (for some combinations) direction of model response to climate change at low (Q10) and high (Q90) daily flows. The implications of historical data inadequacies in snowpack characterization for assessing the impacts of climate change and the associated timing of hydrological tipping points are discussed.

scholarly journals A simulation study on the effect of climate change on crop water use and chill unit accumulation

2017 ◽  
Vol 113 (7/8) ◽  
Author(s):  
Abiodun A. Ogundeji ◽  
Henry Jordaan
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Use ◽  
Irrigation System ◽  
Future Climate ◽  
Crop Water ◽  
Crop Water Use ◽  
Chill Unit ◽  
The Future ◽  
The Impact

Climate change and its impact on already scarce water resources are of global importance, but even more so for water scarce countries. Apart from the effect of climate change on water supply, the chill unit requirement of deciduous fruit crops is also expected to be affected. Although research on crop water use has been undertaken, researchers have not taken the future climate into consideration. They also have focused on increasing temperatures but failed to relate temperature to chill unit accumulation, especially in South Africa. With a view of helping farmers to adapt to climate change, in this study we provide information that will assist farmers in their decision-making process for adaptation and in the selection of appropriate cultivars of deciduous fruits. Crop water use and chill unit requirements are modelled for the present and future climate. Results show that, irrespective of the irrigation system employed, climate change has led to increases in crop water use. Water use with the drip irrigation system was lower than with sprinkler irrigation as a result of efficiency differences in the irrigation technologies. It was also confirmed that the accumulated chill units will decrease in the future as a consequence of climate change. In order to remain in production, farmers need to adapt to climate change stress by putting in place water resources and crop management plans. Thus, producers must be furnished with a variety of adaptation or management strategies to overcome the impact of climate change.

scholarly journals Benefits and limitations of data assimilation for discharge forecasting using an event-based rainfall–runoff model

2013 ◽  
Vol 13 (3) ◽  
pp. 583-596 ◽  
Author(s):  
M. Coustau ◽  
S. Ricci ◽  
V. Borrell-Estupina ◽  
C. Bouvier ◽  
O. Thual
Keyword(s):  
Data Assimilation ◽  
Hydrological Model ◽  
Peak Discharge ◽  
State Variables ◽  
Rainfall Runoff ◽  
Discharge Data ◽  
Southern France ◽  
Flood Peak ◽  
Event Based ◽  
The Impact

Abstract. Mediterranean catchments in southern France are threatened by potentially devastating fast floods which are difficult to anticipate. In order to improve the skill of rainfall-runoff models in predicting such flash floods, hydrologists use data assimilation techniques to provide real-time updates of the model using observational data. This approach seeks to reduce the uncertainties present in different components of the hydrological model (forcing, parameters or state variables) in order to minimize the error in simulated discharges. This article presents a data assimilation procedure, the best linear unbiased estimator (BLUE), used with the goal of improving the peak discharge predictions generated by an event-based hydrological model Soil Conservation Service lag and route (SCS-LR). For a given prediction date, selected model inputs are corrected by assimilating discharge data observed at the basin outlet. This study is conducted on the Lez Mediterranean basin in southern France. The key objectives of this article are (i) to select the parameter(s) which allow for the most efficient and reliable correction of the simulated discharges, (ii) to demonstrate the impact of the correction of the initial condition upon simulated discharges, and (iii) to identify and understand conditions in which this technique fails to improve the forecast skill. The correction of the initial moisture deficit of the soil reservoir proves to be the most efficient control parameter for adjusting the peak discharge. Using data assimilation, this correction leads to an average of 12% improvement in the flood peak magnitude forecast in 75% of cases. The investigation of the other 25% of cases points out a number of precautions for the appropriate use of this data assimilation procedure.

scholarly journals Estimating the impact of climate change on residential water use using panel data analysis: a case study of Lilongwe, Malawi

2017 ◽  
Vol 8 (2) ◽  
pp. 217-226 ◽  
Author(s):  
Chikondi Makwiza ◽  
Musandji Fuamba ◽  
Fadoua Houssa ◽  
Heinz Erasmus Jacobs
Keyword(s):  
Climate Change ◽  
Water Use ◽  
Water Conservation ◽  
Linear Models ◽  
Panel Data Analysis ◽  
Empirical Relationship ◽  
Residential Water Use ◽  
The Impact ◽  
Residential Water ◽  
Emissions Scenario

Abstract In this study, panel linear models were used to develop an empirical relationship between metered household water use and the independent variables plot size and theoretical irrigation requirement. The estimated statistical model provides a means of estimating the climate-sensitive component of residential water use. Ensemble averages of temperature and rainfall projections were used to quantify potential changes in water use due to climate change by 2050. Annual water use per household was estimated to increase by approximately 1.5% under the low emissions scenario or 2.3% under the high emissions scenario. The model results provide information that can enhance water conservation initiatives relating particularly to outdoor water use. The model approach presented utilizes data that are readily available to water supply utilities and can therefore be easily replicated elsewhere.

scholarly journals Effect of length of the observed dataset on the calibration of a distributed hydrological model

2015 ◽  
Vol 368 ◽  
pp. 305-311 ◽  
Author(s):  
X. Cui ◽  
W. Sun ◽  
J. Teng ◽  
H. Song ◽  
X. Yao
Keyword(s):  
Hydrological Model ◽  
Assessment Tool ◽  
Swat Model ◽  
Model Performance ◽  
Hydrological Models ◽  
Distributed Hydrological Model ◽  
Discharge Data ◽  
One Year ◽  
Parameter Values ◽  
Discharge Measurements

Abstract. Calibration of hydrological models in ungauged basins is now a hot research topic in the field of hydrology. In addition to the traditional method of parameter regionalization, using discontinuous flow observations to calibrate hydrological models has gradually become popular in recent years. In this study, the possibility of using a limited number of river discharge data to calibrate a distributed hydrological model, the Soil and Water Assessment Tool (SWAT), was explored. The influence of the quantity of discharge measurements on model calibration in the upper Heihe Basin was analysed. Calibration using only one year of daily discharge measurements was compared with calibration using three years of discharge data. The results showed that the parameter values derived from calibration using one year’s data could achieve similar model performance with calibration using three years’ data, indicating that there is a possibility of using limited numbers of discharge data to calibrate the SWAT model effectively in poorly gauged basins.

scholarly journals Simulation and analysis of the impact of projected climate change on the spatially distributed waterbalance in Thuringia, Germany

2009 ◽  
Vol 21 ◽  
pp. 33-48 ◽  
Author(s):  
P. Krause ◽  
S. Hanisch
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Hydrological Model ◽  
Actual Evapotranspiration ◽  
Climate Data ◽  
Runoff Generation ◽  
Entire Area ◽  
Spatially Distributed ◽  
The Impact ◽  
Conceptual Hydrological Model

Abstract. The impact of projected climate change on the long-term hydrological balance and seasonal variability in the federal German state of Thuringia was assessed and analysed. For this study projected climate data for the scenarios A2 and B1 were used in conjunction with a conceptual hydrological model. The downscaled climate data are based on outputs of the general circulation model ECHAM5 and provide synthetic climate time series for a large number of precipitation and climate stations in Germany for the time period of 1971 to 2100. These data were used to compute the spatially distributed hydrological quantities, i.e. precipitation, actual evapotranspiration and runoff generation with a conceptual hydrological model. This paper discusses briefly the statistical downscaling method and its validation in Thuringia and includes an overview of the hydrological model. The achieved results show that the projected climate conditions in Thuringia follow the general European climate trends – increased temperature, wetter winters, drier summers. But, in terms of the spatial distribution and interannual variability regional differences occur. The analysis showed that the general increase of the winter precipitation is more distinct in the mid-mountain region and less pronounced in the lowland whereas the decrease of summer precipitation is higher in the lowland and less distinct in the mid-mountains. The actual evapotranspiration showed a statewide increase due to higher temperatures which is largest in the summer period. The resulting runoff generation in winter was found to increase in the mid-mountains and to slightly decrease in the lowland region. In summer and fall a decrease in runoff generation was estimated for the entire area due to lower precipitation and higher evapotranspiration rates. These spatially differentiated results emphasize the need of high resolution climate input data and distributed modelling for regional impact analyses.

scholarly journals How might climate change affect river flows across West Africa?

2021 ◽  
Vol 169 (3-4) ◽  
Author(s):  
Ponnambalam Rameshwaran ◽  
Victoria A. Bell ◽  
Helen N. Davies ◽  
Alison L. Kay
Keyword(s):  
Climate Change ◽  
West Africa ◽  
Regional Scale ◽  
Weather Data ◽  
Eastern Region ◽  
Water Shortages ◽  
River Flows ◽  
Considerable Uncertainty ◽  
Modelling Framework ◽  
The Impact

AbstractWest Africa and its semi-arid Sahelian region are one of the world’s most vulnerable regions to climate change with a history of extreme climate variability. There is still considerable uncertainty as to how projected climate change will affect precipitation at local and regional scales and the consequent impact on river flows and water resources across West Africa. Here, we aim to address this uncertainty by configuring a regional-scale hydrological model to West Africa. The model (hydrological modelling framework for West Africa—HMF-WA) simulates spatially consistent river flows on a 0.1° × 0.1° grid (approximately 10 km × 10 km) continuously across the whole domain and includes estimates of anthropogenic water use, wetland inundation, and local hydrological features such as endorheic regions. Regional-scale hydrological simulations driven by observed weather data are assessed against observed flows before undertaking an analysis of the impact of projected future climate scenarios from the CMIP5 on river flows up to the end of the twenty-first century. The results indicate that projected future changes in river flows are highly spatially variable across West Africa, particularly across the Sahelian region where the predicted changes are more pronounced. The study shows that median peak flows are projected to decrease by 23% in the west (e.g. Senegal) and increase by 80% in the eastern region (e.g. Chad) by the 2050s. The projected reductions in river flows in western Sahel lead to future droughts and water shortages more likely, while in the eastern Sahel, projected increases lead to future frequent floods.

scholarly journals Generalization of parameters in the storage–discharge relation for a low flow based on the hydrological analysis of sensitivity

2015 ◽  
Vol 371 ◽  
pp. 69-73 ◽  
Author(s):  
K. Fujimura ◽  
Y. Iseri ◽  
S. Kanae ◽  
M. Murakami
Keyword(s):  
Climate Change ◽  
Sensitivity Analysis ◽  
Water Resource Management ◽  
Hydrological Model ◽  
Low Flow ◽  
Optimum Parameters ◽  
Proportional Relationship ◽  
Two Parameters ◽  
The Impact ◽  
Different Climates

Abstract. The storage-discharge relations have been widely used for water resource management and have led to reliable estimation of the impact of climate change on water resources. In a previous study, we carried out a sensitivity analysis of the parameters in a discharge-storage relation in the form of a power function and found that the optimum parameters can be characterized by an exponential function (Fujimura et al., 2014). The aim of this study is to extend the previous study to clarify the properties of the parameters in the storage–discharge relations by carrying out a sensitivity analysis of efficiency using a hydrological model. The study basins are four mountainous basins in Japan with different climates and geologies. The results confirm that the two parameters in the storage–discharge relations can be expressed in an inversely proportional relationship. In addition, we can conveniently assume a practical function for the storage–discharge relations where only one parameter is used on the basis of the new relationship between the two parameters.

scholarly journals How Would We Cycle Today If We Had the Weather of Tomorrow? An Analysis of the Impact of Climate Change on Bicycle Traffic

2021 ◽  
Vol 13 (18) ◽  
pp. 10254
Author(s):  
Anton Galich ◽  
Simon Nieland ◽  
Barbara Lenz ◽  
Jan Blechschmidt
Keyword(s):  
Climate Change ◽  
Global Climate ◽  
Winter Season ◽  
Model Performance ◽  
Weather Conditions ◽  
Planning And Design ◽  
Validation Procedure ◽  
The Impact ◽  
The City ◽  
Local Weather

Bicycle usage is significantly affected by weather conditions. Climate change is, therefore, expected to have an impact on the volume of bicycle traffic, which is an important factor in the planning and design of bicycle infrastructures. To predict bicycle traffic in a changed climate in the city of Berlin, this paper compares a traditional statistical approach to three machine learning models. For this purpose, a cross-validation procedure is developed that evaluates model performance on the basis of prediction accuracy. XGBoost showed the best performance and is used for the prediction of bicycle counts. Our results indicate that we can expect an overall annual increase in bicycle traffic of 1–4% in the city of Berlin due to the changes in local weather conditions caused by global climate change. The biggest changes are expected to occur in the winter season with increases of 11–14% due to rising temperatures and only slight increases in precipitation.

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