Yunqing Xuan
Swansea University, Civil Engineering, Faculty Member
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The paper investigates compound flooding from waves, sea surge and river flow in northern Jakarta, Indonesia, which is a global hotspot of flooding, by combining process-based coastal and river models. The coastal hydrodynamic modelling... more
The paper investigates compound flooding from waves, sea surge and river flow in northern Jakarta, Indonesia, which is a global hotspot of flooding, by combining process-based coastal and river models. The coastal hydrodynamic modelling of Jakarta Bay in Indonesia shows that coastal storms can lead to a substantial increase in sea water level due to wind and wave setup in the nearshore areas, including Muara Angke river inlet. The compound flood hazard from a range of flood scenarios was simulated and analysed. The results reveal that low-lying areas around the river inlet are prone to flooding even during regular, low-intensity storm events, while rarer storms caused extensive floods. Floods were not caused by direct overwashing of sea defences but by overspill of the banks of the river inlet due to high sea water level caused by wind set up, wave setup, and sea surge obstructing the drainage of the river and elevating its water level during storms. We also found that the sea level...
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Complicated model structure and time consuming simulations increase the use of models in decision making process when the stakeholders are not familiar with the tools. Therefore, the user interface (UI) design for decision support system... more
Complicated model structure and time consuming simulations increase the use of models in decision making process when the stakeholders are not familiar with the tools. Therefore, the user interface (UI) design for decision support system (DSS) should not only maintain the scientific model structure but also simplify the interaction with models and the need for easy access. Nowadays, web-based techniques have been developed so fast and Web 2.0 brings the time when web-based systems challenge the desktop applications. This technology also needs to be taken into account in the DSS development for water resource management because the stakeholders are spatial distributed and the internet is the most commonly available resource. In this paper, we developed a WebDSS prototype named VisREACHER that is fully based on Free and Open Source Software (FOSS). It is a stand-alone web page with the decision model running behind which means it offers more than a visualization system of a prepared d...
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<p><span>This two-year trial aims to bring together academics and industrial partners from UK and China to conduct a pilot study on the use of the active phased array radar to provide early urban flood warnings... more
<p><span>This two-year trial aims to bring together academics and industrial partners from UK and China to conduct a pilot study on the use of the active phased array radar to provide early urban flood warnings for Chinese mega cities, which facing challenging urban flood issues. This is the first in the world of cascade modelling using the cutting-edge active phase array radar (APRA) to provide rainfall monitoring and nowcasting information for a real-time two-dimension urban drainage model. The collaboration built up by this project and the first-hand experiment data will serve well to further catalyse the taking-up of state-of-the-art weather radars for urban flood risk management, and to tackle the innovation in tuning the radar technology to fit the complex urban environment as well as advanced modelling facilities that are designed to link the observations, providing decision making support to the city government. Recommendations for applying high spatial-temporal resolution precipitation data to real-time flood forecasting on an urban catchment are provided and suggestions for further investigation are discussed.</span></p>
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<p> Flooding is widely regarded as one of the most dangerous natural hazards worldwide. It often arises from various sources either individually or combined such as extreme rainfall, storm surge, high sea level,... more
<p> Flooding is widely regarded as one of the most dangerous natural hazards worldwide. It often arises from various sources either individually or combined such as extreme rainfall, storm surge, high sea level, large river discharge or the combination of them. However, the concurrence or close succession of these different source mechanisms can lead to compound flooding, resulting in larger damages and even catastrophic consequences than those from the events caused by the individual mechanism. Here, we present a modelling framework aimed at supporting risk analysis of compound flooding in the context of climate change, where nonstationary joint probability of multiple variables and their interactions need to be quantified.The framework uses the Block Bootstrapping Mann-Kendall test to detect the temporal changes of marginals, and the correlation test associated with the Rolling Window method to estimate whether the correlation structure varies with time; it then evaluates various combinations of marginals and copulas under stationary and nonstationary assumptions. Meanwhile, a Bayesian Markov Chain Monte Carlo method is employed to estimate the time-varying parameters of copulas. </p>
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In this article, we present the use of the coupled land surface model and groundwater flow model SWAT-MODFLOW with the decision support tool WEAP (Water Evaluation and Planning software) to predict future surface water abstraction... more
In this article, we present the use of the coupled land surface model and groundwater flow model SWAT-MODFLOW with the decision support tool WEAP (Water Evaluation and Planning software) to predict future surface water abstraction scenarios in a complex river basin, under conditions of climate change. The modeling framework is applied to the Dee River catchment in Wales, United Kingdom. Regarding hydrology, the coupled model improves overall water balance and low streamflow conditions, compared to a stand-alone SWAT model. The calibrated SWAT-MODFLOW is employed with high resolution climate model data from the UKCP18 project with future scenario of RCP85 from 2020 to 2040. Then, water supply results from SWAT-MODFLOW are fed into WEAP as input for the river reach in the downstream region of the river basin. This system is utilized to create various future scenarios of surface water abstraction of public water supply in the downstream region: maximum licensed withdraw, 50 % authorize...
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Availability of water resources is one of the most fundamental factors that affect socio-economic development as well as environment. This is especially true in arid areas of China where this effect has always been highlighted by... more
Availability of water resources is one of the most fundamental factors that affect socio-economic development as well as environment. This is especially true in arid areas of China where this effect has always been highlighted by composition of vegetation and limited biosphere cycle. On the other hand, uncontrolled water utilization often causes desertification and disappearance of oases. Many oases in arid areas nowadays face threats from both changing climate and impacts from human activities such as the ...
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This paper presents an analysis of the annual precipitation observed by a network of 30 rain gauges in Iraq over a 65-year period (1941–2005). The simulated precipitation from 18 climate models in the CMIP5 project is investigated over... more
This paper presents an analysis of the annual precipitation observed by a network of 30 rain gauges in Iraq over a 65-year period (1941–2005). The simulated precipitation from 18 climate models in the CMIP5 project is investigated over the same area and time window. The Mann–Kendall test is used to assess the strength and the significance of the trends (if any) in both the simulations and the observations. Several exploratory techniques are used to identify the similarity (or disagreement) in the probability distributions that are fitted to both datasets. While the results show that large biases exist in the projected rainfall data compared with the observation, a clear agreement is also observed between the observed and modelled annual precipitation time series with respect to the direction of the trends of annual precipitation over the period.
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This paper presents an analysis of the temporary variation of the area-orientated annual maximum daily rainfall (AMDR) with respect to the three spatial properties: location, size and shape of the region-of-interest (ROI) in Great Britain... more
This paper presents an analysis of the temporary variation of the area-orientated annual maximum daily rainfall (AMDR) with respect to the three spatial properties: location, size and shape of the region-of-interest (ROI) in Great Britain and Australia using two century-long datasets. The Maximum Likelihood and Bayesian Markov-Chain-Monte-Carlo methods are employed to quantify the time-varying frequency of AMDR, where a large proportion of the ROIs shows a non-decreasing level of most frequent AMDR. While the most frequent AMDR values generally decrease with larger-sized ROIs, their temporal variation that can be attributed to the climate change impact does not show the same dependency on the size. Climate change impact on ROI-orientated extreme rainfall is seen higher for rounded shapes although the ROI shape is not as significant as the other two spatial properties. Comparison of the AMDR at different return levels shows an underestimation by conventionally used stationary models ...
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This paper presents the development and applications of a new, open-source toolbox that aims to provide automatic identification and classification of hydroclimatic patterns by their spatial features, i.e., location, size, orientation,... more
This paper presents the development and applications of a new, open-source toolbox that aims to provide automatic identification and classification of hydroclimatic patterns by their spatial features, i.e., location, size, orientation, and shape, as well as the physical features, i.e., the areal average, total volume, and spatial distribution. The highlights of this toolbox are: (1) incorporating an efficient algorithm for automatically identifying and classifying the spatial features that are linked to hydroclimatic extremes; (2) use as a frontend for supporting AI-based training in tracking and forecasting extremes; and (3) direct support for short-term nowcasting of extreme rainfall via tracking rainstorm centres and movement. The key design and implementation of the toolbox are discussed alongside three case studies demonstrating the application of the toolbox and its potential in helping build machine learning applications in hydroclimatic sciences. Finally, the availability of...
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We present a statistical method to quantify the contribution of urbanization to precipitation changes during 1958–2017 across the greater Beijing–Tianjin–Hebei metropolitan region in northern China. We find distinct trends in... more
We present a statistical method to quantify the contribution of urbanization to precipitation changes during 1958–2017 across the greater Beijing–Tianjin–Hebei metropolitan region in northern China. We find distinct trends in precipitation in the past six decades: decreasing in annual and summer while increasing in other seasons. The spatial patterns of precipitation show discernible terrain-induced characteristics with high values in the buffer zones of plain and mountain areas and low values in the northwestern mountainous regions. Our results indicate that although urbanization has limited impacts on the trends and spatial patterns of precipitation, it has a positive contribution to the changes in precipitation for about 80% of the comparisons conducted, especially in autumn (100%), with the negative contribution being dominant in summer (66.67%). In addition, these results are sensitive to the classifications of urban and rural stations, suggesting that how to classify urban/rur...
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Abstract The use of weather radars for precipitation forecasting in fast response river basins is very important for early warning systems. Some of the most used techniques, such as radar echo tracking, which is based on patterns and... more
Abstract The use of weather radars for precipitation forecasting in fast response river basins is very important for early warning systems. Some of the most used techniques, such as radar echo tracking, which is based on patterns and correlations, do not contemplate the decay/growth mechanism of rainfall systems. Numerical weather prediction models do consider much more information than radars, but their accuracy is less than the radar forecast; at least for a lead time of up to several hours. In this paper we explore the ...
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First of all, the reader has a hard work (I did) finding in the text the description of how the UK territory is separated in different zones, and the shape of these zones. Why considering only the mainland of UK ? Apparently, the... more
First of all, the reader has a hard work (I did) finding in the text the description of how the UK territory is separated in different zones, and the shape of these zones. Why considering only the mainland of UK ? Apparently, the territory is cut in non-rectangular zones , but why not simply using rectangular zones, since only the very mainland part of UK is studied ? (this is, in my opinion, an important issue with the paper). All the paragraph of the top of page 7 is rather obscure : what does the sentence "the focus is on the impact of location only" mean ? What do the lines 173-174 mean ? Do they mean that the zones have a common shape (that of Figure 1a ? Why this one ?) ? Why considering "randomized locations" ? It is not normal that such crucial description of what the study is about, is so badly described. And the reader can only wonder why a non-negligible part of the UK territory is not covered by the study (the seashores, and all the space between the ...
The use of weather radars for precipitation forecasting in fast response river basins is very important for early warning systems. Some of the most used techniques, such as radar echo tracking, which is based on patterns and correlations,... more
The use of weather radars for precipitation forecasting in fast response river basins is very important for early warning systems. Some of the most used techniques, such as radar echo tracking, which is based on patterns and correlations, do not contemplate the decay/growth mechanism of rainfall systems. Numerical weather prediction models do consider much more information than radars, but their accuracy is less than the radar forecast; at least for a lead time of up to several hours. In this paper we explore the integration of the two forecasting approaches. The MM5 numerical weather prediction model is set up for a region in southeast England. The Nimrod radar data, for the same region, from the British Atmospheric Database Centre (BADC) is adapted and used as reference. The M5 prime regression model tree is used for the integration of both models. The results show that the proposed integration reduced the error of tracking significantly. The results presented here have been evalu...
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Abstract This note provides a concise presentation of the state-of-the-art methods to assess climate change impacts on water systems with reference to the Nile basin. In particular, recent studies dealing with climate change in the Nile... more
Abstract This note provides a concise presentation of the state-of-the-art methods to assess climate change impacts on water systems with reference to the Nile basin. In particular, recent studies dealing with climate change in the Nile basin are summarized and guidelines for dealing with uncertainty in planning water resources in a changing climate are illustrated. The paper also includes potential strategy recommendations to policy and decision makers for planning adaptation measures in the water sector. In particular, the need to better ...
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Non-point source pollution from excessive use of fertilizers in agriculture is a major cause of the eutrophication problem in China. Understanding farmers’ decision-making concerning fertilization and identifying the influencing factors... more
Non-point source pollution from excessive use of fertilizers in agriculture is a major cause of the eutrophication problem in China. Understanding farmers’ decision-making concerning fertilization and identifying the influencing factors in this process are key to tackling overfertilization and related pollution issues. This paper reports a study on modelling decisions about fertilizer use based on data collected from 200 farmer households in the Three Gorges Reservoir area of China, using a well-fitted artificial neural network (ANN) with incorporated variance-based sensitivity analysis. The rate of fertilizer use estimated from the model is in good agreement with observed data. The model is further validated and tested by comparing the simulated and observed values. Results show that the model is able to identify the influencing factors and their interactions causing the variation in fertilizer use and to help pinpoint the underlying reasons. It is found that the farmers’ fertiliza...
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This paper presents an improved method of using threshold of peak rainfall intensity for robust flood/flash flood evaluation and warnings in the state of São Paulo, Brazil. The improvements involve the use of two tolerance levels and the... more
This paper presents an improved method of using threshold of peak rainfall intensity for robust flood/flash flood evaluation and warnings in the state of São Paulo, Brazil. The improvements involve the use of two tolerance levels and the delineating of an intermediate threshold by incorporating an exponential curve that relates rainfall intensity and Antecedent Precipitation Index (API). The application of the tolerance levels presents an average increase of 14% in the Probability of Detection (POD) of flood and flash flood occurrences above the upper threshold. Moreover, a considerable exclusion (63%) of non-occurrences of floods and flash floods in between the two thresholds significantly reduce the number of false alarms. The intermediate threshold using the exponential curves also exhibits improvements for almost all time steps of both hydrological hazards, with the best results found for floods correlating 8-h peak intensity and 8 days API, with POD and Positive Predictive Valu...
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Accurate simulation of both land surface and groundwater hydrologic processes in river catchments is an important step for integrated water resources management, particularly for catchments where both surface water and groundwater... more
Accurate simulation of both land surface and groundwater hydrologic processes in river catchments is an important step for integrated water resources management, particularly for catchments where both surface water and groundwater resources are used conjunctively. In this paper, we present a study on a complex river catchment – the Dee River catchment in the United Kingdom using a coupled land surface model (SWAT) and groundwater model (MODFLOW) to improve the performances of both models otherwise used separately, hence serving the IWRM goals of optimizing conjunctive use of surface and groundwater. The model can also be used to evaluate the sensitivity of stream flows to changing climate, groundwater extraction, and land use alternations. Preliminary results show that the coupled model can improve river flow simulation especially baseflow simulation while significantly improving the overall water balance model simulations during periods of low flow.
This study performed a rationality analysis of the delay time and embedding dimension value during phase space reconstruction in hydrological series and the effect on their chaotic characteristics. Using a monthly average runoff time... more
This study performed a rationality analysis of the delay time and embedding dimension value during phase space reconstruction in hydrological series and the effect on their chaotic characteristics. Using a monthly average runoff time series from the Ayanqian station (upstream) and the Jiangqiao station (midstream) in the Nen River Basin, we reached the following regularity conclusions. 1 Based on the flood season (4 months) in the Nen River Basin, we can deduce that the correlation sequence length for the runoff is 4~5 months, i.e., the delay time =3 or 4 is a reasonable choice. 2 Learn from the predictability experiment results for the monthly rainfall time series, we know that the calculation results of the G-P algorithm for the dimension of runoff series for the Nen River Basin are reasonable, i.e., the embedding dimension is no more than seven. 3 the most suitable parameters for the phase space reconstruction and its chaotic characteristic index in the Nen River Basin are as fol...
Effective representation of precipitation inputs is one of the essential components in hydrological model structures, especially when gauge measurements for the modelled catchment are sparse. Assessment of the impact of precipitation... more
Effective representation of precipitation inputs is one of the essential components in hydrological model structures, especially when gauge measurements for the modelled catchment are sparse. Assessment of the impact of precipitation pre-processing is often nontrivial as precipitation data are very limited in the first place. In this paper, we demonstrate a study using a semi-distributed hydrological model, the Soil and Water Assessment Tool (SWAT) to examine the impact of different precipitation pre-processing methods on model calibration and the overall model performance with regards to the operational use. A river catchment in the UK is modelled to test against the three pre-processing methods: the Centroid Point Estimation Method (CPEM), the Grid Area Method (GAM) and the Grid Point Method (GPM). Cross-calibration and validation are then carried out by using the high-resolution Centre for Ecology & Hydrology–Gridded Estimate Areal Rainfall (CEH-GEAR) dataset. The results show th...
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Conducting trend analysis of climatic variables is one of the key steps in many climate change impact studies where trend is often checked against aggregated variables. However, there is also a strong need to investigate the trend of the... more
Conducting trend analysis of climatic variables is one of the key steps in many climate change impact studies where trend is often checked against aggregated variables. However, there is also a strong need to investigate the trend of the data in different regimes – examples include high flow versus low flow, and heavy precipitation versus prolonged dry period. For this matter, quantile regression (QR) based methods are preferred as they can reveal the temporal dependencies of the variable in question for not only the mean value, but also its quantiles. As such, the tendencies revealed by the QR methods are more informative and helpful in studies where different mitigation methods need to be considered at different severity levels.In this paper, we demonstrate the use of several quantile regressions methods to analyse the long-term trend of rainfall records in two climatically different regions: The Dee River catchment in the United Kingdom, for which daily rainfall data of 1970–2004...
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High performance computing (HPC) has long been used in the disciplines of atmospheric and oceanic sciences, and remains the main tool of choice to extract numerical solutions to complex geophysical problems on the global scale, often... more
High performance computing (HPC) has long been used in the disciplines of atmospheric and oceanic sciences, and remains the main tool of choice to extract numerical solutions to complex geophysical problems on the global scale, often accompanied with very large numbers of degrees of freedoms. However, with the growing recognition that the spatially distributed feedback from the land surface is important to weather and the climate system, representation of the land surface is established with increasingly complex (and physically complete) models, which often leads to the coupling of heterogeneous models such as numerical weather prediction (NWP) models and hydrological models. As a result, the spatial grids and the temporal resolutions have become finer and thereby computers with far greater computational and storage capacity are in great demand than those used in the past. Additionally, impact-focused studies that require coupling of accurate simulations of weather/climate systems a...
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The advances in meso-scale numerical weather predication render hydrologists the capability to incorporate high-resolution NWP directly into flood forecasting systems in order to obtain an extended lead time. However, such a direct... more
The advances in meso-scale numerical weather predication render hydrologists the capability to incorporate high-resolution NWP directly into flood forecasting systems in order to obtain an extended lead time. However, such a direct application of rainfall outputs from the NWP model can contribute considerable uncertainties to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological domains and can also be highlighted by the scaling process. In this research, the ensemble hydrological forecasts driven by the ensemble weather prediction are investigated in an effort trying to understand both the potential and the implication of the ensemble rainfall inputs to the hydrological modelling systems in terms of uncertainty propagation. A data-rich catchment facilitated with dense rainguage network as well as high resolution weather radar was chosen to run the ensemble hydrological simulations of a distributed hydrological model driven by the h...
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ABSTRACT Advances in mesoscale numerical weather prediction make it possible to provide quantitative precipitation forecasts (QPF) along with many other data fields at increasingly higher spatial resolutions. It is currently possible to... more
ABSTRACT Advances in mesoscale numerical weather prediction make it possible to provide quantitative precipitation forecasts (QPF) along with many other data fields at increasingly higher spatial resolutions. It is currently possible to incorporate high-resolution NWPs directly into flood forecasting systems in order to obtain an extended lead time. It is recognised, however, that direct application of rainfall outputs from the NWP model contributes considerable uncertainty to the final river flow forecasts as the uncertainties inherent in the NWP are propagated into hydrological and hydraulic domains and can also be magnified by the scaling process. As more and more “modern” flood forecasting systems are adopting this coupled approach, it is necessary to study uncertainty propagation and interaction between the NWP and the real-time flood forecast system model cascade, which terminates technically with the decision support system (DSS). In this study, analysis is conducted to investigate the uncertainties in rainfall predictions that form the primary perturbation in a coupled NWP-hydrological model context. The ensemble method is used to account for both uncertainties due to incorrect/inaccurate initial conditions and those derived from model structure. Conventional statistics are employed to show variations over domains as well as point-wise targets. An adapted empirical orthogonal function analysis based upon principal components (EOF/PCA) is used to measure the diversity of ensemble members, which in turn provides a way to reconstruct a composite scenario that embodies most of the significant characteristics of ensemble forecast fields. The analyses of a typical ensemble QPF case over the catchment scale reveals that, although the NWP-based QPF can generally capture the rainfall pattern, uncertainties in rainfall at the scale of model grid relative to the catchment scale were always significant. Therefore, a cautious approach should be taken before the QPF, either deterministic or ensemble based, is injected into a flood forecasting system. Detailed results are discussed and comments made regarding the uncertainty propagation and the usability of the NWP-based QPF in the context of real-time flood forecasting systems.
A combination of population growth, climate change, urbanisation and economic development all pose potential threats towards water resource sustainability. This research aims to determine the potential barriers to reducing household water... more
A combination of population growth, climate change, urbanisation and economic development all pose potential threats towards water resource sustainability. This research aims to determine the potential barriers to reducing household water consumption in the UK. In order to overcome the barriers of water-intensive lifestyles, there is a need to gain a better understanding of the types of factors that may lead to long term reduced consumption. The research analyses the effects of consumer behaviour on ‘climate-change driven’ modifications to water utility companies’ business models. In particular, the research examines the important role of gaining consumer trust and the potential impact that values and emotional responses to predicted future scenarios may play in shaping behavioural intentions towards reducing water use.
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Rainfall is one of the key terms involved in many hydrological processes, and it is particularly important in the field of urban hydrology. In this study, the focus is set on the impact on the precipitation patterns in Beijing in term of... more
Rainfall is one of the key terms involved in many hydrological processes, and it is particularly important in the field of urban hydrology. In this study, the focus is set on the impact on the precipitation patterns in Beijing in term of spatial and temporal variation, from the urbanization over last 50 years in which time the fast and continuous expansion of the city at dramatic scales, the rapid growth of residents population as well as human activities especially building of ground constructions, collectively and inevitably bring changes to the local climatic characteristics of the urbanized areas. It has been found that the spatial distribution has demonstrated a clear pattern shift over the region; the temporal distribution, although shows insignificant (decreasing) trends on many average terms, gives a clear indication of stable, gradual increase in maximum 1-h rainfall intensity accompanying with the slow-urbanizing period and large fluctuations in the rapid development period.
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Computer based modelling has long been an established norm in hydrological studies. The demand of computing power in hydrological modelling domain, although keep steadily growing over past decades, it has never been higher as we now look... more
Computer based modelling has long been an established norm in hydrological studies. The demand of computing power in hydrological modelling domain, although keep steadily growing over past decades, it has never been higher as we now look into many impact studies due to climate change. While HPC has long been a major player in the neighbouring field of climate sciences, its role has yet to be defined when the resources become increasingly accessible to hydrological modellers attempting to address the impact of climate change in terms of extreme weather events. In this paper, we present a framework of HPC based hydrological modelling approach that can utilize and maximize the HPC power to support the study on extreme weather impact due to climate change. The framework is intended to achieve 1) seamlessly coupling of the hydrological models with the climate/numerical weather models that are supported by the same HPC platform; 2) supporting large-scale hydrological modelling in greater ...
Rainfall nowcasts from weather radars are of great value for flood forecasting when lead-time is among top priorities, for example, in the case of flash flooding. Although radar-based nowcasts generally outperforms its longer-term... more
Rainfall nowcasts from weather radars are of great value for flood forecasting when lead-time is among top priorities, for example, in the case of flash flooding. Although radar-based nowcasts generally outperforms its longer-term counterpart - the rainfall forecast from numerical weather prediction (NWP), the uncertainty associated with rainfall inputs when driving a hydrological forecast often still overwhelms those from raingauge observations, let alone model parameterisation. Furthermore, it too is very difficult to quantify for such coupled nowcast-driving hydrological forecast. The STEPS (Short Term Ensemble Prediction System), is one of the sophisticated operational nowcasting systems, aiming to address uncertainties from atmospheric dynamics at various scales using ensemble nowcasts. It is interesting, yet very desirable to see how a STEPS-driving hydrological forecast can as well benefit from this better uncertainty representation. We present this study on such a coupled ST...
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With regional socio-economic development, the gap between water use demand and available water resources in arid and humid semi-arid areas becomes increasingly serious. In this study, the size of regional water use in the Guanzhong region... more
With regional socio-economic development, the gap between water use demand and available water resources in arid and humid semi-arid areas becomes increasingly serious. In this study, the size of regional water use in the Guanzhong region and Shiyang river basin in northwest China are analyzed to identify important factors affecting it, with the aim of providing better and optimal development planning for the region. Information entropy is used to measure and characterize the diversity of regional water use. Agricultural development and meteorological factors are found to be the main issues affecting regional water use in both regions. A multiple-linear regression (MLR) model was built by applying correlation coefficient (R) and mutual information (MI) scores in the process. Results show that the low value of information entropy of water use in the Shiyang river basin is due to the high proportion of agriculture water use. Using input factors chosen by MI score was found to be the b...
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ABSTRACT Flow forecasting in poorly gauged, flood-prone Ribb and Gumara sub-catchments of the Blue Nile was studied with the aim of testing the performance of Quantitative Precipitation Forecasts (QPFs). Four types of QPFs namely MM5... more
ABSTRACT Flow forecasting in poorly gauged, flood-prone Ribb and Gumara sub-catchments of the Blue Nile was studied with the aim of testing the performance of Quantitative Precipitation Forecasts (QPFs). Four types of QPFs namely MM5 forecasts with a spatial resolution of 2 km; the Maximum, Mean and Minimum members (MaxEPS, MeanEPS and MinEPS where EPS stands for Ensemble Prediction System) of the fixed, low resolution (2.5 by 2.5 degrees) National Oceanic and Atmospheric Administration Global Forecast System (NOAA GFS) ensemble forecasts were used. Both the MM5 and the EPS were not calibrated (bias correction, downscaling (for EPS), etc.). In addition, zero forecasts assuming no rainfall in the coming days, and monthly average forecasts assuming average monthly rainfall in the coming days, were used. These rainfall forecasts were then used to drive the Hydrologic Engineering Center's-Hydrologic Modeling System, HEC-HMS, hydrologic model for flow predictions. The results show that flow predictions using MaxEPS and MM5 precipitation forecasts over-predicted the peak flow for most of the seven events analyzed, whereas under-predicted peak flow was found using zero- and monthly average rainfall. The comparison of observed and predicted flow hydrographs shows that MM5, MaxEPS and MeanEPS precipitation forecasts were able to capture the rainfall signal that caused peak flows. Flow predictions based on MaxEPS and MeanEPS gave results that were quantitatively close to the observed flow for most events, whereas flow predictions based on MM5 resulted in large overestimations for some events. In follow-up research for this particular case study, calibration of the MM5 model will be performed. The overall analysis shows that freely available atmospheric forecasting products can provide additional information on upcoming rainfall and peak flow events in areas where only base-line forecasts such as no-rainfall or climatology are available. (c) 2013 Elsevier Ltd. All rights reserved.
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Global warming will have direct impacts on regional water resources by accelerating the hydrological cycle. Hydrological simulation is an important approach to studying climate change impacts. In this paper, a snowmelt-based water balance... more
Global warming will have direct impacts on regional water resources by accelerating the hydrological cycle. Hydrological simulation is an important approach to studying climate change impacts. In this paper, a snowmelt-based water balance model (SWBM) was used to simulate the effect of climate change on runoff in the Kuye River catchment of the Loess Plateau, China. Results indicated that the SWBM is suitable for simulating monthly discharge into arid catchments. The response of runoff in the Kuye River catchment to climate change is nonlinear, and runoff is more sensitive to changes in precipitation than to changes in temperature. The projections indicated that the Kuye River catchment would undergo more flooding in the 2020s, and global warming would probably shorten the main flood season in the catchment, with greater discharge occurring in August. Although projected changes in annual runoff are uncertain, the possibilities of regional water shortages and regional flooding are es...
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Research Interests: Environmental Engineering, Civil Engineering, Environmental Science, Flood Forecasting, Hydrological modelling, and 9 moreWeather Forecasting, Uncertainty analysis, High Resolution, Uncertainty propagation, Spatial resolution, Ensemble Forecasting, Lead Time, Distributed Hydrological Model, and hydrologic model
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ABSTRACT Flow forecasting in poorly gauged, flood-prone Ribb and Gumara sub-catchments of the Blue Nile was studied with the aim of testing the performance of Quantitative Precipitation Forecasts (QPFs). Four types of QPFs namely MM5... more
ABSTRACT Flow forecasting in poorly gauged, flood-prone Ribb and Gumara sub-catchments of the Blue Nile was studied with the aim of testing the performance of Quantitative Precipitation Forecasts (QPFs). Four types of QPFs namely MM5 forecasts with a spatial resolution of 2 km; the Maximum, Mean and Minimum members (MaxEPS, MeanEPS and MinEPS where EPS stands for Ensemble Prediction System) of the fixed, low resolution (2.5 by 2.5 degrees) National Oceanic and Atmospheric Administration Global Forecast System (NOAA GFS) ensemble forecasts were used. Both the MM5 and the EPS were not calibrated (bias correction, downscaling (for EPS), etc.). In addition, zero forecasts assuming no rainfall in the coming days, and monthly average forecasts assuming average monthly rainfall in the coming days, were used. These rainfall forecasts were then used to drive the Hydrologic Engineering Center's-Hydrologic Modeling System, HEC-HMS, hydrologic model for flow predictions. The results show that flow predictions using MaxEPS and MM5 precipitation forecasts over-predicted the peak flow for most of the seven events analyzed, whereas under-predicted peak flow was found using zero- and monthly average rainfall. The comparison of observed and predicted flow hydrographs shows that MM5, MaxEPS and MeanEPS precipitation forecasts were able to capture the rainfall signal that caused peak flows. Flow predictions based on MaxEPS and MeanEPS gave results that were quantitatively close to the observed flow for most events, whereas flow predictions based on MM5 resulted in large overestimations for some events. In follow-up research for this particular case study, calibration of the MM5 model will be performed. The overall analysis shows that freely available atmospheric forecasting products can provide additional information on upcoming rainfall and peak flow events in areas where only base-line forecasts such as no-rainfall or climatology are available. (c) 2013 Elsevier Ltd. All rights reserved.
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Recently efforts have been made to utilise high resolution weather forecasts, in particular rainfall forecasts to improve real-time flood forecasting in terms of extending lead time and issuing earlier warnings of flash floods. For... more
Recently efforts have been made to utilise high resolution weather forecasts, in particular rainfall forecasts to improve real-time flood forecasting in terms of extending lead time and issuing earlier warnings of flash floods. For instance, different high resolution numerical weather ...
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Research Interests: Environmental Engineering, Civil Engineering, Environmental Science, Flood Forecasting, Hydrological modelling, and 9 moreWeather Forecasting, Uncertainty analysis, High Resolution, Uncertainty propagation, Spatial resolution, Ensemble Forecasting, Lead Time, Distributed Hydrological Model, and hydrologic model
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The use of weather radars for precipitation forecasting in fast response river basins is very important for early warning systems. Some of the most used techniques, such as radar echo tracking, which is based on patterns and correlations,... more
The use of weather radars for precipitation forecasting in fast response river basins is very important for early warning systems. Some of the most used techniques, such as radar echo tracking, which is based on patterns and correlations, do not contemplate the decay/growth mechanism of rainfall systems. Numerical weather prediction models do consider much more information than radars, but their accuracy is less than the radar forecast; at least for a lead time of up to several hours. In this paper we explore the ...
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A critical discussion of recent studies that analysed the effects of climate change on the water resources of the River Nile Basin (RNB) is presented. First, current water-related issues on the RNB showing the particular vulnerability to... more
A critical discussion of recent studies that analysed the effects of climate change on the water resources of the River Nile Basin (RNB) is presented. First, current water-related issues on the RNB showing the particular vulnerability to environmental changes of this large territory are described. Second, observed trends in hydrological data (such as temperature, precipitation, river discharge) as described in the recent literature are presented. Third, recent modelling exercises to quantify the effects of climate changes on ...
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This note provides a concise presentation of the state-of-the-art methods to assess climate change impacts on water systems with reference to the Nile basin. In particular, recent studies dealing with climate change in the Nile basin are... more
This note provides a concise presentation of the state-of-the-art methods to assess climate change impacts on water systems with reference to the Nile basin. In particular, recent studies dealing with climate change in the Nile basin are summarized and guidelines for dealing with uncertainty in planning water resources in a changing climate are illustrated. The paper also includes potential strategy recommendations to policy and decision makers for planning adaptation measures in the water sector. In particular, the need to better ...