scholarly journals Modelling of River Flow Using Particle Swarm Optimized Cascade-Forward Neural Networks: A Case Study of Kelantan River in Malaysia

2020 ◽  
Vol 10 (23) ◽  
pp. 8670
Author(s):  
Gasim Hayder ◽  
Mahmud Iwan Solihin ◽  
Hauwa Mohammed Mustafa
Keyword(s):  
Water Resource ◽  
Water Resource Management ◽  
River Flow ◽  
Particle Swarm ◽  
Predictive Performance ◽  
Resource Planning ◽  
Weather Data ◽  
Percentage Error ◽  
History Of ◽  
Flooding Events

Water resources management in Malaysia has become a crucial issue of concern due to its role in the economic and social development of the country. Kelantan river (Sungai Kelantan) basin is one of the essential catchments as it has a history of flood events. Numerous studies have been conducted in river basin modelling for the prediction of flow and mitigation of flooding events as well as water resource management. This paper presents river flow modelling based on meteorological and weather data in the Sungai Kelantan region using a cascade-forward neural network trained with particle swarm optimization algorithm (CFNNPSO). The result is compared with those trained with the Levenberg–Marquardt (LM) and Bayesian Regularization (BR) algorithm. The outcome of this study indicates that there is a strong correlation between river flow and some meteorological and weather variables (weighted rainfall, average evaporation and temperatures). The correlation scores (R) obtained between the target variable (river flow) and the predictor variables were 0.739, −0.544, and −0.662 for weighted rainfall, evaporation, and temperature, respectively. Additionally, the developed nonlinear multivariable regression model using CFNNPSO produced acceptable prediction accuracy during model testing with the regression coefficient (R2), root mean square error (RMSE), and mean of percentage error (MPE) of 0.88, 191.1 cms and 0.09%, respectively. The reliable result and predictive performance of the model is useful for decision makers during water resource planning and river management. The constructed modelling procedure can be adopted for future applications.

scholarly journals Adaptation of water resource systems to an uncertain future

2016 ◽  
Vol 20 (5) ◽  
pp. 1869-1884 ◽  
Author(s):  
Claire L. Walsh ◽  
Stephen Blenkinsop ◽  
Hayley J. Fowler ◽  
Aidan Burton ◽  
Richard J. Dawson ◽  
...  
Keyword(s):  
Water Resources ◽  
Population Growth ◽  
Water Resource ◽  
Water Resource Management ◽  
Resource Planning ◽  
Integrated Modelling ◽  
Climate Projections ◽  
Median Frequency ◽  
Changing Climate ◽  
Adaptation Options

Abstract. Globally, water resources management faces significant challenges from changing climate and growing populations. At local scales, the information provided by climate models is insufficient to support the water sector in making future adaptation decisions. Furthermore, projections of change in local water resources are wrought with uncertainties surrounding natural variability, future greenhouse gas emissions, model structure, population growth, and water consumption habits. To analyse the magnitude of these uncertainties, and their implications for local-scale water resource planning, we present a top-down approach for testing climate change adaptation options using probabilistic climate scenarios and demand projections. An integrated modelling framework is developed which implements a new, gridded spatial weather generator, coupled with a rainfall-runoff model and water resource management simulation model. We use this to provide projections of the number of days and associated uncertainty that will require implementation of demand saving measures such as hose pipe bans and drought orders. Results, which are demonstrated for the Thames Basin, UK, indicate existing water supplies are sensitive to a changing climate and an increasing population, and that the frequency of severe demand saving measures are projected to increase. Considering both climate projections and population growth, the median number of drought order occurrences may increase 5-fold by the 2050s. The effectiveness of a range of demand management and supply options have been tested and shown to provide significant benefits in terms of reducing the number of demand saving days. A decrease in per capita demand of 3.75 % reduces the median frequency of drought order measures by 50 % by the 2020s. We found that increased supply arising from various adaptation options may compensate for increasingly variable flows; however, without reductions in overall demand for water resources such options will be insufficient on their own to adapt to uncertainties in the projected changes in climate and population. For example, a 30 % reduction in overall demand by 2050 has a greater impact on reducing the frequency of drought orders than any of the individual or combinations of supply options; hence, a portfolio of measures is required.

scholarly journals Assessing the value of seasonal hydrological forecasts for improving water resource management: insights from a pilot application in the UK

2020 ◽  
Vol 24 (12) ◽  
pp. 6059-6073
Author(s):  
Andres Peñuela ◽  
Christopher Hutton ◽  
Francesca Pianosi
Keyword(s):  
Decision Maker ◽  
Water Resource ◽  
Water Resource Management ◽  
Forecast Skill ◽  
Weather Data ◽  
Ensemble Size ◽  
Streamflow Prediction ◽  
Seasonal Forecasts ◽  
Hydrological Conditions ◽  
The Uk

Abstract. Improved skill of long-range weather forecasts has motivated an increasing effort towards developing seasonal hydrological forecasting systems across Europe. Among other purposes, such forecasting systems are expected to support better water management decisions. In this paper we evaluate the potential use of a real-time optimization system (RTOS) informed by seasonal forecasts in a water supply system in the UK. For this purpose, we simulate the performances of the RTOS fed by ECMWF seasonal forecasting systems (SEAS5) over the past 10 years, and we compare them to a benchmark operation that mimics the common practices for reservoir operation in the UK. We also attempt to link the improvement of system performances, i.e. the forecast value, to the forecast skill (measured by the mean error and the continuous ranked probability skill score) as well as to the bias correction of the meteorological forcing, the decision maker priorities, the hydrological conditions and the forecast ensemble size. We find that in particular the decision maker priorities and the hydrological conditions exert a strong influence on the forecast skill–value relationship. For the (realistic) scenario where the decision maker prioritizes the water resource availability over energy cost reductions, we identify clear operational benefits from using seasonal forecasts, provided that forecast uncertainty is explicitly considered by optimizing against an ensemble of 25 equiprobable forecasts. These operational benefits are also observed when the ensemble size is reduced up to a certain limit. However, when comparing the use of ECMWF-SEAS5 products to ensemble streamflow prediction (ESP), which is more easily derived from historical weather data, we find that ESP remains a hard-to-beat reference, not only in terms of skill but also in terms of value.

scholarly journals An improved framework to predict river flow time series data

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7183 ◽  
Author(s):  
Hafiza Mamona Nazir ◽  
Ijaz Hussain ◽  
Ishfaq Ahmad ◽  
Muhammad Faisal ◽  
Ibrahim M. Almanjahie
Keyword(s):  
Time Series ◽  
Water Resource Management ◽  
River Flow ◽  
Time Series Data ◽  
Flow Time ◽  
Indus Basin ◽  
Series Data ◽  
Percentage Error ◽  
Empirical Bayesian ◽  
Noise Characteristics

Due to non-stationary and noise characteristics of river flow time series data, some pre-processing methods are adopted to address the multi-scale and noise complexity. In this paper, we proposed an improved framework comprising Complete Ensemble Empirical Mode Decomposition with Adaptive Noise-Empirical Bayesian Threshold (CEEMDAN-EBT). The CEEMDAN-EBT is employed to decompose non-stationary river flow time series data into Intrinsic Mode Functions (IMFs). The derived IMFs are divided into two parts; noise-dominant IMFs and noise-free IMFs. Firstly, the noise-dominant IMFs are denoised using empirical Bayesian threshold to integrate the noises and sparsities of IMFs. Secondly, the denoised IMF’s and noise free IMF’s are further used as inputs in data-driven and simple stochastic models respectively to predict the river flow time series data. Finally, the predicted IMF’s are aggregated to get the final prediction. The proposed framework is illustrated by using four rivers of the Indus Basin System. The prediction performance is compared with Mean Square Error, Mean Absolute Error (MAE) and Mean Absolute Percentage Error (MAPE). Our proposed method, CEEMDAN-EBT-MM, produced the smallest MAPE for all four case studies as compared with other methods. This suggests that our proposed hybrid model can be used as an efficient tool for providing the reliable prediction of non-stationary and noisy time series data to policymakers such as for planning power generation and water resource management.

Water resource management in ancient Iran with emphasis on technological approaches: a cultural heritage

2013 ◽  
Vol 13 (3) ◽  
pp. 582-589 ◽  
Author(s):  
Gagik Badalians Gholikandi ◽  
Mandana Sadrzadeh ◽  
Shervin Jamshidi ◽  
Morteza Ebrahimi
Keyword(s):  
Resource Management ◽  
Cultural Heritage ◽  
Water Resource ◽  
Water Resource Management ◽  
Hydraulic Systems ◽  
Water Demands ◽  
Wide Range ◽  
History Of ◽  
Engineered Structures ◽  
Water Conveyance

Water is an essential component in the history of Iran. Due to the unfavorable distribution of surface water and the fluctuation of yearly seasonal streams, to fulfill water demands, ancient Iranians have tried to provide a better condition for utilization of water. Accordingly, elegant designs like qanats became an indispensable element of hydraulic systems, while institutional frameworks were innovated to be combined with in water resource management. Evidence shows that hydraulic structures and water establishments date back thousands of years known as cultural heritage. Besides, the ancient Iranians have realized the importance of an organization to supervise irrigation and water conveyance. Thus, during the Achaemenid and Sasanian Empires, water engineering was developed significantly through the whole territory. The governmental endorsements associated with contemporary engineered structures have made extensive innovations in water systems, such as canals, watermills, water treatment, water storage, piping and construction. The infrastructure fulfilled a wide range of necessities of a civilized country and assisted in achieving its golden era. Consequently, this paper is aimed at studying ancient water resource management and technological approaches in Iran.

scholarly journals Assessing the value of seasonal hydrological forecasts for improving water resource management: insights from a pilot application in the UK

2020 ◽  
Author(s):  
Andres Peñuela ◽  
Christopher Hutton ◽  
Francesca Pianosi
Keyword(s):  
Decision Maker ◽  
Water Resource ◽  
Water Resource Management ◽  
Skill Score ◽  
Forecast Skill ◽  
Weather Data ◽  
Seasonal Forecasts ◽  
Weather Forecasts ◽  
The Common ◽  
The Uk

Abstract. Improved skill of long-range weather forecasts has motivated an increasing effort towards developing seasonal hydrological forecasting systems across Europe. Among other purposes, such forecasting systems are expected to support better water management decisions. In this paper we evaluate the potential use of a real-time optimisation system (RTOS) informed by seasonal forecasts in a water supply system in the UK. For this purpose, we simulate the performances of the RTOS fed by ECMWF seasonal forecasting systems (SEAS5) over the past ten years, and we compare them to a benchmark operation that mimics the common practices for reservoir operation in the UK. We also attempt to link the improvement of system performances, i.e. the forecast value, to the forecast skill (measured by the mean error and the Continuous Ranked Probability Skill Score) as well as other factors such as bias correction, the decision maker priorities, hydrological conditions and level of uncertainty consideration. We find that some of these factors control the forecast value much more strongly than the forecast skill. For the (realistic) scenario where the decision-maker prioritises water resource availability over energy cost reductions, we identify clear operational benefits from using seasonal forecasts, provided that forecast uncertainty is explicitly considered. However, when comparing the use of ECMWF-SEAS5 products to ensemble streamflow predictions (ESP), which are more easily derived from historical weather data, we find that ESP remains a hard-to-beat reference not only in terms of skill but also in terms of value.

scholarly journals A Bi-Objective Pseudo-Interval T2 Linear Programming Approach and Its Application to Water Resources Management Under Uncertainty

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1545
Author(s):  
Lei Jin ◽  
Haiyan Fu ◽  
Younggy Kim ◽  
Jiangxue Long ◽  
Guohe Huang
Keyword(s):  
Linear Programming ◽  
Resource Management ◽  
Water Resource ◽  
Water Resource Management ◽  
Optimal Allocation ◽  
Water System ◽  
Resource Planning ◽  
Programming Approach ◽  
Fuzzy Constraints ◽  
Linear Programming Approach

In realistic water resource planning, fuzzy constraints can be violated but still allowed to certain acceptance degrees. To address this issue, in this study, a bi-objective pseudo-interval type 2 (T2) linear programming approach with a ranking order relation between the intervals is proposed for water system allocation. This developed approach can transform normal T2 fuzzy sets, including both trapezoidal and triangular types, into the bi-objective linear programming approach solved with the proposed algorithm with mathematical rigor, which improves the flexibility of the decision supports. The new model is applied in the utilization of regional water resource management in Xiamen city, China. Concurrently, a local water system model is established by considering the aspects of industrial, agricultural, and municipal requirements. Thus, by analysis of the solution algorithm, decision-makers can obtain different optimal results by selecting different acceptance degrees. The results also demonstrate the superiority of the proposed method. Therefore, this approach not only augments the theory of the optimal allocation method in water resource management, but also provides the support for meeting the requirements of the 13th five-year plan for Xiamen ecological planning.

scholarly journals Mapping Interflow Potential and the Validation of Index-Overlay Weightings by Using Coupled Surface Water and Groundwater Flow Model

Water ◽  
2021 ◽  
Vol 13 (17) ◽  
pp. 2452
Author(s):  
Chuen-Fa Ni ◽  
Quoc-Dung Tran ◽  
I-Hsien Lee ◽  
Minh-Hoang Truong ◽  
Shaohua Marko Hsu
Keyword(s):  
Surface Water ◽  
Water Resource ◽  
Water Resource Management ◽  
River Flow ◽  
High Elevation ◽  
Coastal Zones ◽  
Near Surface ◽  
Practical Applications ◽  
Index Overlay ◽  
Overlay Model

Interflow is an important water source contributing to river flow. It directly influences the near-surface water cycles for water resource management. This study focuses on assessing the interflow potential and quantifying the interflow in the downstream area along the Kaoping River in southern Taiwan. The interflow potential is first determined based on the modified index-overlay model, which employs the analytical hierarchy process (AHP) to calculate the ratings and weightings of the selected factors. The groundwater and surface water flow (GSFLOW) numerical model is then used to link the index-overlay model to quantify the interflow potential for practical applications. This study uses the Monte Carlo simulations to assess the influence of rainfall-induced variations on the interflow uncertainty in the study area. Results show that the high potential interflow zones are located in the high to middle elevation regions along the Kaoping River. Numerical simulations of the GSFLOW model show an interflow variation pattern that is similar to the interflow potential results obtained from the index-overlay model. The average interflow rates are approximately 3.5 × 104 (m3/d) in the high elevation zones and 2.0 × 104 (m3/d) near the coastal zones. The rainfall uncertainty strongly influences interflow rates in the wet seasons, especially the peaks of the storms or heavy rainfall events. Interflow rates are relatively stable in the dry seasons, indicating that interflow is a reliable water resource in the study area.

scholarly journals Assessing risks for integrated water resource management: coping with uncertainty and the human factor

2014 ◽  
Vol 364 ◽  
pp. 285-291 ◽  
Author(s):  
M. J. Polo ◽  
C. Aguilar ◽  
A. Millares ◽  
J. Herrero ◽  
R. Gómez-Beas ◽  
...  
Keyword(s):  
Water Resource ◽  
Water Resource Management ◽  
Human Factor ◽  
Water Security ◽  
Resource Planning ◽  
Planning Horizon ◽  
Irrigated Area ◽  
Risk Increase ◽  
Semi Arid ◽  
New Reservoir

Abstract. Risk assessment for water resource planning must deal with the uncertainty associated with excess/scarcity situations and their costs. The projected actions for increasing water security usually involve an indirect "call-effect": the territory occupation/water use is increased following the achieved protection. In this work, flood and water demand in a mountainous semi-arid watershed in southern Spain are assessed by means of the stochastic simulation of extremes, when this human factor is/is not considered. The results show how not including this call-effect induced an underestimation of flood risk after protecting the floodplain of between 35 and 78 % in a 35-year planning horizon. Similarly, the pursued water availability of a new reservoir resulted in a 10-year scarcity risk increase up to 38 % when the trend of expanding the irrigated area was included in the simulations. These results highlight the need for including this interaction in the decision-making assessment.

How Perceptions of Risks Affect Responses to Climate Change: Implications for Water Resource Planning

2020 ◽  
Author(s):  
Sonia Akter ◽  
Shaleen Khanal
Keyword(s):  
Climate Change ◽  
Risk Perception ◽  
Water Resource ◽  
Water Resource Management ◽  
National Level ◽  
Large Body ◽  
Resource Planning ◽  
Climate Change Risk ◽  
Risk Response ◽  
The Individual

The link between risk perception and risk response is not straightforward. There are several individual, community, and national factors that determine how climate change risk is perceived and how much of the perception translates to response. The nexus between risk perception and risk response in the context of water resource management at the individual, household, community, and institutional level has been subject of a large body of theoretical and empirical studies from around the globe. At the individual level, vulnerability, exposure, and cognitive factors are important determinants of climate change risk perception and response. At the community level, risk perception is determined by culture, social pressure, and group identity. Responses to risk vary depending on the level of social cohesion and collective action. At the national level, public support is a key determinant of institutional response to climate change, particularly for democratic nations. The level of global cooperation and major polluting countries’ willingness to curb their fair share of greenhouse gas emissions also deeply influence policymakers’ decisions to respond to climate change risk.

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