scholarly journals Hydrological implications of spatial and altitudinal variation in temperature in the upper Indus basin

2004 ◽  
Vol 35 (3) ◽  
pp. 209-222 ◽  
Author(s):  
David Archer
Keyword(s):  
River Flow ◽  
Daily Rainfall ◽  
Indus Basin ◽  
Design Flood ◽  
Freezing Level ◽  
Correlation And Regression Analysis ◽  
Energy Inputs ◽  
Flood Estimation ◽  
Seasonal Correlation ◽  
Practical Implications

Runoff in the upper Indus in Pakistan is primarily fed by meltwater from snow and ice. Successful modelling of runoff thus depends on knowledge of the energy inputs for melt, and temperature provides a practical index. In this study, spatial and altitudinal variations in air temperature are investigated using correlation and regression analysis. The high levels of seasonal correlation between widely separated stations and with altitude suggest that conditions over a wide surrounding area and up to the freezing level may be inferred with reasonable reliability from climate stations at the valley level. Investigation of concurrent daily rainfall, temperature and runoff in extreme monsoon incursions shows that precipitation is accompanied by a sharp fall in temperature, reduced ablation and, most frequently, a decrease in river flow. Such temperature reductions have practical implications for short term flood forecasting and for design flood estimation.

scholarly journals An assessment of scale issues related to the configuration of the ACRU model for design flood estimation

2011 ◽  
Vol 42 (5) ◽  
pp. 401-412
Author(s):  
K. Chetty ◽  
J. C. Smithers
Keyword(s):  
Daily Rainfall ◽  
Simulation Modelling ◽  
Research Unit ◽  
Physical Parameters ◽  
Design Flood ◽  
Critical Question ◽  
Continuous Simulation ◽  
Agricultural Catchments ◽  
Flood Estimation ◽  
Modelling Process

A continuous simulation modelling approach to design flood estimation has many advantages and overcomes many limitations of commonly used design event approaches. A major concern with continuous simulation using a hydrological model is the scale at which modelling should take place. According to researchers, the level of representation that will preserve the physical chain of hydrological processes, both in terms of scale of representation and level of description of the physical parameters for the modelling process, is a critical question which must be addressed. Objectives of this research were to determine the optimum levels of catchment discretization and soil and land cover information and to assess the optimum use of daily rainfall stations for the configuration of the Agricultural Catchments Research Unit (ACRU) agrohydrological model when used for design flood estimation. Results obtained for selected quaternary catchments in the Thukela catchment and Lions River catchment indicated that modelling at the level of hydrological response units (HRUs), using area-weighted soils information and more than one driver rainfall station where possible, produced the most realistic streamflow volume results when compared with observed streamflows. Design flood estimates from simulated peak flows did not compare well with observed data.

The Influence of Geographical Factors on Extreme Rainfalls in Lampung Province

2019 ◽  
Vol 1 (1) ◽  
pp. 33
Author(s):  
M Welly
Keyword(s):  
Geographical Location ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Design Flood ◽  
Extreme Rainfall Events ◽  
Rainfall Events ◽  
Ungauged Basin ◽  
Flood Discharge ◽  
Design Rainfall ◽  
Geographical Factors

Many people in Indonesia calculate design rainfall before calculating the design flooddischarge. The design rainfall with a certain return period will eventually be convertedinto a design flood discharge by combining it with the characteristics of the watershed.However, the lack of a network of rainfall recording stations makes many areas that arenot hydrologically measured (ungauged basin), so it is quite difficult to know thecharacteristics of rain in the area concerned. This study aims to analyze thecharacteristics of design rainfall in Lampung Province. The focus of the analysis is toinvestigate whether geographical factors influence the design rainfall that occurs in theparticular area. The data used in this study is daily rainfall data from 15 rainfallrecording stations spread in Lampung Province. The method of frequency analysis usedin this study is the Gumbel method. The research shows that the geographical location ofan area does not have significant effect on extreme rainfall events. The effect of risingearth temperatures due to natural exploitation by humans tends to be stronger as a causeof extreme events such as extreme rainfall.Keywords: Influence, geographical, factors, extreme, rainfall.

Revisiting design flood estimation of Nam River Dam basin considering climate change

2016 ◽  
Vol 49 (8) ◽  
pp. 719-729
Author(s):  
Hyunseung Lee ◽  
Taesam Lee ◽  
Taewoong Park ◽  
Chanyoung Son
Keyword(s):  
Climate Change ◽  
Design Flood ◽  
Flood Estimation

Flood estimation for ungauged catchments in the Philippines using multiple archival data records

2021 ◽  
Author(s):  
Trevor Hoey ◽  
Pamela Tolentino ◽  
Esmael Guardian ◽  
Richard Williams ◽  
Richard Boothroyd ◽  
...  
Keyword(s):  
Catchment Area ◽  
Daily Rainfall ◽  
The Philippines ◽  
Data Availability ◽  
Estimation Methods ◽  
Annual Maximum ◽  
Ungauged Catchments ◽  
Pearson Type ◽  
Flood Estimation ◽  
Best Fit

<p>Assessment of flood and drought risks, and changes to these risks under climate change, is a critical issue worldwide. Statistical methods are commonly used in data-rich regions to estimate the magnitudes of river floods of specified return period at ungauged sites. However, data availability can be a major constraint on reliable estimation of flood and drought magnitudes, particularly in the Global South. Statistical flood and drought magnitude estimation methods rely on the availability of sufficiently long data records from sites that are representative of the hydrological region of interest. In the Philippines, although over 1000 locations have been identified where flow records have been collected at some time, very few records exist of over 20 years duration and only a limited number of sites are currently being gauged. We collated data from three archival sources: (1) Division of Irrigation, Surface Water Supply (SWS) (1908-22; 257 sites in total); (2) Japan International Cooperation Agency (JICA) (1955-91; 90 sites); and, (3) Bureau of Research and Standards (BRS) (1957-2018; 181 sites). From these data sets, 176 contained sufficiently long and high quality records to be analysed. Series of annual maximum floods were fit using L-moments with Weibull, Log-Pearson Type III and Generalised Logistic Distributions, the best-fit of these being used to estimate 2-, 10- and 100-year flood events, Q<sub>2</sub>, Q<sub>10</sub> and Q<sub>100</sub>. Predictive equations were developed using catchment area, several measures of annual and extreme precipitation, catchment geometry and land-use. Analysis took place nationally, and also for groups of hydrologically similar regions, based on similar flood growth curve shapes, across the Philippines. Overall, the best fit equations use a combination of two predictor variables, catchment area and the median annual maximum daily rainfall. The national equations have R<sup>2</sup> of 0.55-0.65, being higher for shorter return periods, and regional groupings R<sup>2</sup> are 0.60-0.77 for Q<sub>10</sub>. These coefficients of determination, R<sup>2</sup>, are lower than in some comprehensive studies worldwide reflecting in part the short individual flow records. Standard errors of residuals for the equations are between 0.19 and 0.51 (log<sub>10</sub> units), which lead to significant uncertainty in flood estimation for water resource and flood risk management purposes. Improving the predictions requires further analysis of hydrograph shape across the different climate types, defined by seasonal rainfall distributions, in the Philippines and between catchments of different size. The results here represent the most comprehensive study to date of flood magnitudes in the Philippines and are being incorporated into guidance for river managers alongside new assessments of river channel change across the country. The analysis illustrates the potential, and the limitations, for combining information from multiple data sources and short individual records to generate reliable estimates of flow extremes.</p>

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.

Mitigation of Climate Change Impacts Through Treatment and Management of Low Quality Water for Irrigation in Pakistan

2020 ◽  
pp. 1181-1198
Author(s):  
Ghulam Murtaza ◽  
Muhammad Saqib ◽  
Saifullah ◽  
Muhammad Zia-ur-Rehman ◽  
Muhammad Naveed ◽  
...  
Keyword(s):  
Climate Change ◽  
Ground Water ◽  
Large Scale ◽  
River Flow ◽  
Indus Basin ◽  
Change Scenario ◽  
Soluble Salts ◽  
Quality Water ◽  
To Come ◽  
Carry Over

The Indus Plains of Pakistan are situated in arid to semi-arid climate where monsoon rains are erratic and mostly fall in the months of July and August. These rains are not only insufficient to grow even a single crop without artificial irrigation but also cause flood havoc very frequently that is associated with the climate change. The Indus river transports water for agriculture, industry and domestic usage within the basin and downstream. The Indus Basin is among the few basins severely affected by global warming and resulting climate change. The alteration in temporal and spatial patterns of rainfall has resulted in unexpected drought and floods. About 70 to 80% of total river flows occur in summer season due to snow melt and monsoonal rainfalls. Lack of storage reservoirs has decreased the ability to regulate flood water as well as its potential use during the drought season along with cheap hydro-electricity generation. The sedimentation in the system has limited the storage capacity of the existing three reservoirs by 28%. Consequently carry over capacity of these storage structures is only 30 days compared to 120 to 220 days in India and 900 days in Colorado Basin. Pakistan is facing shortage of good quality water due to competition among agricultural and non-agricultural sectors, this scenario will continue rather will further aggravate in future. According to the climate change scenario, the warming is reflected in the river-flow data of Pakistan, especially during the past 2-3 decades. To bridge the gap between fresh water availability and demand, ground water is being pumped to meet the irrigation requirements of crops. The pumped ground water (70-80%) is brackish and could become a sustainability issue in the long run. The prolonged agricultural uses of such water will deteriorate soils, crops and human living environments. Water quality parameters usually considered include electrical conductivity (EC) for total soluble salts, and sodium adsorption ratio (SAR) and residual sodium carbonate (RSC) reflect the sodicity hazards. In order to limit or even to eliminate adverse effects of such waters, certain treatment and/or management options are considered as important pre-requisites. For bringing down high concentration of total soluble salts, dilution with good quality water is the doable practice. To decrease high SAR of irrigation water, a source of calcium is needed, dilution (with good quality water) will decrease SAR by the square root times of the dilution factor, while use of acids will be cost-intensive rather may adversely impact the soil health. For high RSC, dilution with low CO32-+HCO3- water will serve the purpose, addition of Ca-salts will raise Ca2++Mg2+ to bring a decrease in water RSC, while acids will neutralize CO32-+HCO3- to lower water RSC. Gypsum is the most economical and safe amendment while acids could also decrease RSC but at higher relative cost. City wastewater and seed priming in aerated gypsum solution is also presented. Such practices at small and/or large scale surely will help a lot to sustain the food security and the environment in the days to come where climate change has to be experienced round the world. Therefore, a well-coordinated program is necessary to create awareness among different sections of the society including the policy makers, general public, organizations, industrialists and farmers.

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