Showing papers in "Journal of Hydrologic Engineering in 2011"
TL;DR: In this paper, different regionalization methods were applied, including the spatial proximity, kriging, inverse distance weighted (IDW), and mean parameters, and regression-based approaches.
Abstract: Regionalization, a process of transferring hydrological information [i.e., parameters of a conceptual rainfall-runoff model, namely, the McMaster University-Hydrologiska Byrans Vattenbalansavdelning (MAC-HBV)] from gauged to ungauged basins, was applied to estimate continuous flows in ungauged basins across Ontario, Canada. To identify appropriate regionalization methods, different regionalization methods were applied, including the spatial proximity [i.e., kriging, inverse distance weighted (IDW), and mean parameters], physical similarity, and regression-based approaches. Furthermore, an approach coupling the spatial-proximity (IDW) method and the physical similarity approach is proposed. The analysis results show that the coupled regionalization approach as well as the IDW and kriging produce better model performances than the remaining three. Further investigations show that the coupled-regionalization approach provides slightly better performances than the other two spatial proximity methods. In addit...
189 citations
TL;DR: In this paper, traditional and geo- statistical interpolation methods, including Thiessen polygon, inverse distance weighting (IDW), linear regression, ordinary kriging (OK), and simple Kriging with varying local means (SKlm), were used to estimate wet and dry season rainfall.
Abstract: A total of 21 gauges across the mountainous leeward portion of the island of Oʻahu, Hawaiʻi, were used to compare rainfall interpolation methods and assess rainfall spatial variability over a 34-month monitoring period from 2005 to 2008. Traditional and geo- statistical interpolation methods, including Thiessen polygon, inverse distance weighting (IDW), linear regression, ordinary kriging (OK), and simple kriging with varying local means (SKlm), were used to estimate wet and dry season rainfall. The linear regression and SKlm methods were used to incorporate two types of exhaustive secondary information: (1) elevation extracted from a digital elevation model (DEM), and (2) distance to a regional rainfall maximum. The Thiessen method produced the highest error, whereas OK produced the lowest error in all but one period. The OK method produced more accurate predictions than linear regression of rainfall against elevation when the correlation between rainfall and elevation is moderate (R < 0:82). The SKlm method produced lower error than linear regression and IDW methods in all periods. Comparison of the OK interpolation map with gridded isohyet data indicate that the areas of greatest rainfall deficit were confined to the mountainous region of west Oʻahu. DOI: 10.1061/(ASCE)HE.1943-5584.0000330. © 2011 American Society of Civil Engineers. CE Database subject headings: Rainfall; Spatial analysis; Hawaiʻi; Mountains; Tropical regions; Estimation. Author keywords: Rainfall; Spatial analysis; Hawaiʻi; Estimation.
175 citations
TL;DR: In this paper, a modified topographic index (TIm) computed from a digital elevation model (DEM) is used to delineate the exposure to flooding by adopting a modified TIm.
Abstract: The availability of new technologies for the measurement of surface elevation has addressed the lack of high-resolution elevation data, which has led to an increase in the attraction of automated procedures based on digital elevation models (DEMs) for hydrological applications, including the delineation of floodplains. In particular, the exposure to flooding may be delineated quite well by adopting a modified topographic index (TIm) computed from a DEM. The comparison of TIm and flood inundation maps (obtained from hydraulic simulations) shows that the portion of a basin exposed to flood inundation is generally characterized by a TIm higher than a given threshold, τ (e.g., equal to 2.89 for DEMs with cell size of 20 m). This allows the development of a simple procedure for the identification of flood-prone areas that requires only two parameters for the calibration: the threshold τ and the exponent of TIm. Because the modified topographic index is sensitive to the spatial resolution of the DEM, the optima...
151 citations
TL;DR: Results indicate that the NMS algorithm is efficient for the estimating parameters of the nonlinear Muskingum models, which is easy to be programmed, and it is quite efficient for finding an optimal solution very quickly.
Abstract: The linear form of the Muskingum model has been widely applied to river flood routing. However, a nonlinear relationship between weighted-flow and storage volume exists in most rivers, making the use of the linear Muskingum model inappropriate. On the other hand, the application of the nonlinear Muskingum model suffers from hydrologic parameters estimation. The current study aims at presenting the objective approach of the Nelder-Mead simplex (NMS) algorithm for the purpose of estimating the parameters of the nonlinear Muskingum model. The performance of this algorithm is compared with other reported parameter estimation techniques together with a historical example. Results of the implementation of this procedure indicate that the NMS algorithm is efficient for the estimating parameters of the nonlinear Muskingum models. This algorithm is easy to be programmed, and it is quite efficient for finding an optimal solution very quickly. Although this technique requires an initial guess for the parameter estim...
148 citations
TL;DR: In this article, the Hargreaves (HG) and Priestley-Taylor (P-T) equations were calibrated on the basis of the FAO-56 method in arid and cold climates of Iran using data from 12 stations during 1994-2005.
Abstract: The Food and Agricultural Organization of the United Nations (FAO)-56 version of Penman-Monteith (PMF-56) model has been established as a standard for calculating reference evapotranspiration (ETo). An important constraint of application of the PMF-56 model is the requirement of solar radiation, wind speed, air temperature, and humidity data, which may not be available for a given location, especially in developing countries. The Hargreaves (HG) and Priestley-Taylor (P-T) equations are simple equations that require few weather data inputs, although regional calibration of the equations is needed for acceptable performance before applying them for ETo estimation. In this study, the HG and P-T equations were calibrated on the basis of the PMF-56 method in arid and cold climates of Iran using data from 12 stations during 1994–2005. After calibration of the HG equation, the average value of the adjusted HG coefficient for arid climate was 0.0031, which is about 34% higher than the original value (0.0023). Sim...
130 citations
TL;DR: In this paper, the authors focus on the physical applications of the entropy theory, wherein the theory is coupled with the laws of mathematical physics and solutions are derived either in a time or space domain rather than the frequency domain.
Abstract: An entropy theory, comprising the Shannon entropy, the principle of maximum entropy, and the concentration theorem, has been applied in recent years to a wide range of problems in hydrology. From a hydrologic point of view, the applications can be organized into three classes: (1) physical, (2) statistical, and (3) mixed. This study focuses on the physical applications of the entropy theory, wherein the theory is coupled with the laws of mathematical physics and solutions are derived either in a time or space domain rather than the frequency domain. It is shown that a general framework can be developed to derive solutions to a wide range of seemingly disparate problems. The theory seems to have much potential that remains yet to be fully exploited.
128 citations
TL;DR: In this article, the authors considered artificial neural network (ANN), wavelet analysis and ANN combination (WANN), multilinear regression (MLR), and sediment rating curve (SRC) models for daily suspended sediment load (S) modeling in the Iowa River gauging station in the United States.
Abstract: Accurate suspended sediment prediction is an integral component of sustainable water resources and environmental systems. This study considered artificial neural network (ANN), wavelet analysis and ANN combination (WANN), multilinear regression (MLR), and sediment rating curve (SRC) models for daily suspended sediment load (S) modeling in the Iowa River gauging station in the United States. In the proposed WANN model, discrete wavelet transform was linked to the ANN method. For this purpose, observed time series of river discharge (Q) and S were decomposed into several subtime series at different scales by discrete wavelet transform. Then these subtime series were imposed as inputs to the ANN method to predict one-day-ahead S. The results showed that the WANN model was in good agreement with the observed S values and that it performed better than the other models. The coefficient of efficiency was 0.81 for the WANN model and 0.67, 0.6, and 0.39 for the ANN, MLR, and SRC models, respectively. In addition, ...
123 citations
TL;DR: This work employed independent component analysis (ICA) for predictor selection that determines spatially independent GCM variables and cross-validation of the independent components is employed to find the predictor combination that describes the regional precipitation over the upper Willamette basin with minimum error.
Abstract: Various methods have been proposed to downscale the coarse resolution general circulation model (GCM) climatological variables to the fine-scale regional variables; however, fewer studies have been focused on the selection of GCM predictors. Additionally, the results obtained from one downscaling technique may not be robust and the uncertainties related to the downscaling scheme are not realized. To address these issues, the writers employed independent component analysis (ICA) for predictor selection that determines spatially independent GCM variables. Cross-validation of the independent components is employed to find the predictor combination that describes the regional precipitation over the upper Willamette basin with minimum error. These climate variables, along with the observed precipitation, are used to calibrate three downscaling models: multilinear regression (MLR), support vector machine (SVM), and adaptive-network-based fuzzy inference system (ANFIS). The presented method incorporates several ...
104 citations
TL;DR: In this paper, a methodology for maximum precipitation estimation that uses a physically based numerical atmospheric model is proposed for the American River watershed (ARW) in California for the December 1996-January 1997 flood event.
Abstract: A methodology for maximum precipitation (MP) estimation that uses a physically based numerical atmospheric model is proposed in this paper. As a case study, the model-based 72-h MP was estimated for the American River watershed (ARW) in California for the December 1996–January 1997 flood event. First, a regional atmospheric model, MM5, was calibrated and validated for the December 1996–January 1997 historical major storm event for the ARW, on the basis of the U.S. National Center for Atmospheric Research (NCAR) reanalysis data to demonstrate the model capability during the historical period. Then, the model-simulated historical storm event was maximized by modifying its boundary conditions. The model-simulated precipitation field in the ARW was successfully validated at nine individual rain gauge stations in the watershed. The computed basin-averaged precipitation was somewhat higher than observations obtained by the spatial interpolation of the rain gauge observations. This result suggests a limitation o...
93 citations
TL;DR: This study proposes a novel parameter-setting-free technique interfaced with a harmony search algorithm and applies it to the parameter estimation of the nonlinear Muskingum model, which is an optimization problem with continuous decision variables.
Abstract: Although phenomenon-mimicking algorithms, such as genetic algorithms, particle swarm optimization, and harmony search, have overcome the disadvantages of mathematical algorithms, such as the nonlinear least-squares method, segmented least-squares method, Lagrange multiplier method, a hybrid of pattern search and local search, and the Broyden-Fletcher-Goldfarb-Shanno technique, the algorithms have an inherent shortcoming. They require a tedious and skillful parameter-setting process for the algorithm parameters, such as the crossover rate, mutation rate, acceleration coefficients, harmony memory considering rate, and pitch-adjusting rate. Thus, this study proposes a novel parameter-setting-free technique interfaced with a harmony search algorithm and applies it to the parameter estimation of the nonlinear Muskingum model, which is an optimization problem with continuous decision variables. Results show that the proposed technique found good model parameter values while outperforming a classical harmony sea...
87 citations
TL;DR: In this article, the authors investigate the presence of trends in extreme precipitation (denoted MAXP and defined as the annual maximum daily precipitation depth) time series for coastal northern New England and assess changes in the magnitude of the so-called 100-year storm MAXP depths from 48 stations with long, continuous records in Maine, New Hampshire, and Massachusetts.
Abstract: The objective of this study was to investigate the presence of trends in extreme precipitation (denoted MAXP and defined as the annual maximum daily precipitation depth) time series for coastal northern New England and to assess changes in the magnitude of the so-called 100-year storm MAXP depths from 48 stations with long, continuous records in Maine, New Hampshire, and Massachusetts were analyzed At those same stations, the number of daily precipitation depths ≥ 2i n: (51 mm, denoted as GT2in) was also quantified for each year Although the seasonally averaged MAXP was found to be fairly uniform throughout the year, the frequency of MAXP is highest during August through October, the typical hurricane season in New England The presence of trends in MAXP and GT2in was evaluated over four time frames (1954-2005, 1954-2008, 1970-2005, and 1970-2008) using two statistical methods (linear regression and the Mann-Kendall trend test) and at two scales (at-site and regional) The trend analysis over the time period 1954-2005 indicated that MAXP was amazingly stationary; however, a trend in GT2in was found at some stations More trends in both MAXP and GT2in were present in the time period 1954-2008 The majority of stations in southern New Hampshire and eastern Massachusetts showed evidence of trends in MAXP (but not GT2in) for the time period 1970-2008 That the number of trends in MAXP increased despite the shorter record length suggests a strong increase in the magnitude of extreme precipitation in northern coastal New England in the last few decades The stationarity of the 1954-2005 record was confirmed by the regional trend analysis, as was the presence of stronger trends in coastal stations when the record was extended through 2008 Most stations that had trends in MAXP also had trends in GT2in The generalized extreme value (GEV) distribution was used to estimate 100-year precipitation depth quantiles for the 1954-2005 record, which were then compared with Technical Paper No 40 (TP-40) 100-year, 24-h precipitation depths Estimates for stations along coastal Massachusetts, New Hampshire, and Maine all exceeded 7 in (180 mm) and exceeded TP-40 by 1 in (25 mm) or more Stations in northeastern Massachusetts, southeastern New Hampshire, and southern Maine exceeded 8 in (200 mm) and also exceeded TP-40 estimates by more than 2 in (51 mm) These findings indicate that TP-40 underrepresents coastal storm depths This study, as well as recent record-breaking events in northern New England, strongly suggests the need for updating of design storm estimates Furthermore, extreme precipitation events of longer than one-day duration have caused large-scale flooding in the region over the last decade The magnitude of longer duration storms (particularly two-day storms) may also be increasing, calling for engineered infrastructure that can accommodate increases in both storm magnitude and duration DOI: 101061/(ASCE)HE1943-55840000303 © 2011 American Society of Civil Engineers
TL;DR: In this article, the projected changes in the 6-hour, 100-year design-storm depth for a watershed in Las Vegas Valley, Nevada, are calculated from several climate scenarios by using regional frequency analysis.
Abstract: One of the goals of storm-water infrastructure design is to mitigate effects resulting from extreme hydrologic events. Projected changes in climate are expected to lead to an increase in the frequency and magnitude of extreme rainfall events for many regions. Accordingly, existing storm-water infrastructure may not meet design standards in future decades. The North American Regional Climate Change Assessment Program is currently disseminating high resolution climate data to facilitate climate change impact assessments. A simple framework is presented for assessment of storm-water infrastructure in response to climate change. First, the projected changes in the 6-hour, 100-year design-storm depth for a watershed in Las Vegas Valley, Nevada, are calculated from several climate scenarios by using regional frequency analysis. Climate model projections vary substantially for this region and time scale. Climate model performance is assessed by using gridded reanalysis data. The projected changes in design-storm...
TL;DR: In this article, the authors developed an entropy theory for deriving two-dimensional distribution of velocity in open channels, which comprises five parts: (1) Tsallis entropy, (2) the principle of maximum entropy (POME), (3) specification of information on velocity in terms of constraints, (4) the maximization of entropy, and (5) the derivation of the probability distribution.
Abstract: Assuming time-averaged velocity as a random variable, this study develops an entropy theory for deriving two-dimensional (2D) distribution of velocity in open channels. The theory comprises five parts: (1) Tsallis entropy; (2) principle of maximum entropy (POME); (3) specification of information on velocity in terms of constraints; (4) maximization of entropy; and (5) derivation of the probability distribution of velocity. The entropy theory is then combined with a hypothesis on the cumulative distribution function of velocity in terms of flow depth to derive a 2D velocity distribution. The derived distribution is tested using field as well as laboratory observations reported in the literature and is compared with known velocity distributions. Agreement between velocity values computed using the entropy-based distribution and observed values is found satisfactory. Also, the derived distribution compares favorably with known distributions.
TL;DR: In this article, an algorithm for selecting the best management practices (BMPs) to improve the system performance and reliability in dealing with urban flash floods is proposed that considers the anthropogenic and climate change effects.
Abstract: Urban floods have adverse impacts on the performance of urban infrastructures and the life of residents. The floods cause heavy damages and perturbation in the serviceability of urban infrastructures as well as transportation. Therefore, different factors affecting the urban water flood characteristics should be considered in urban development planning, especially in metropolitan areas. In recent years, climate change and its consequences have affected the total components of the water cycle as well as floods. These effects are intensified in urban areas because of the anthropogenic effects they have on the water cycle, such as reducing the infiltration capacity of basins, construction regardless of the channel’s right of way, and disposal of sediment and solid wastes into channels that will decrease the channels’ safe carrying capacity. In this way, incorporating climate change impact on urban water studies could help to achieve more reliable results to be applied in real-time planning of urban areas through selection of best management practices (BMPs). In this study, an algorithm for selecting the BMPs to improve the system performance and reliability in dealing with urban flash floods is proposed that considers the anthropogenic and climate change effects. The suggested algorithm is applied to the Tehran metropolitan area drainage system as a case study. First, the future rainfall pattern of the study area under climate change impact is simulated. Then, the effectiveness of present and future development projects for improvement of drainage system performance is evaluated under different scenarios. Also, the effect of solid wastes and sediments carried with surface runoff in system performance is considered. Finally, feasibility of suggested BMPs and their effectiveness in urban flood management as well as their related costs and benefits are considered. The results of the study show the significance of using analytical and management tools in assessing and improving the urban drainage system.
TL;DR: In this article, the spatial and temporal patterns of trends for reference evapotranspiration (RET) at 34 meteorological stations (between 1957 and 2007) in the Haihe River basin, China, were analyzed using the Mann-Kendall (MK) test and the Sen's method.
Abstract: In this study, the spatial and temporal patterns of trends for reference evapotranspiration (RET) at 34 meteorological stations (between 1957 and 2007) in the Haihe River basin, China, were analyzed using the Mann-Kendall (MK) test and the Sen’s method. To reveal the possible causes and main driving forces of the changing patterns of RET, the spatial distribution and temporal patterns of trends for four meteorological variables (i.e., temperature, wind speed, relative humidity, and sunshine duration) were examined for each station. In addition, partial relative analysis between RET and meteorological variables and a sensitivity analysis of RET to meteorological variables were conducted. The results show the following: First, the Haihe River basin is dominated by a significant decreasing MK trend in annual RET at >95% confidence level, which is observed at most stations in the eastern and southern areas of the basin. There are no observed trends or significant increasing MK trends in annual RET in the west...
TL;DR: In this article, the authors compared the bioretention outflow from three small, nonurban watersheds, located in Piedmont, part of central North Carolina, to the natural watershed in North Carolina.
Abstract: Bioretention, a key structural practice of low impact development (LID), has been proved to decrease peak flow rates and volumes, promote infiltration and evapotranspiration, and improve water quality. Exactly how well bioretention mimics predevelopment (or “natural”) hydrology is an important research question. Do bioretention outflow rates mirror shallow groundwater interevent stream recharge flow associated with natural or nonurban watersheds? Streamflow from three small, nonurban watersheds, located in Piedmont, part of central North Carolina, was compared with bioretention outflow from four cells also in North Carolina’s Piedmont region. Each benchmark watershed drained to a small stream, where flow rate was monitored for an extended period of time. After normalizing the flow rates and volumes by watershed size, data were combined to form two data sets: bioretention outflow and stream interevent flow. Results indicate that there is no statistical difference between flow rates in streams draining unde...
TL;DR: In this paper, an approach based on the assessment of all possible regression types was used to select the predictors among the NCEP reanalysis data set, and artificial neural network (ANN)based downscaling models were designed separately for each station in the basin.
Abstract: Statistical downscaling methods describe a statistical relationship between large-scale atmospheric variables such as temperature, humidity, precipitation, etc., and local-scale meteorological variables like precipitation. This study examines the potential predictor variables selected from the National Center for Environmental Prediction and National Center for Atmospheric Research (NCEP/NCAR) reanalysis data set for downscaling monthly precipitation in Tahtali watershed in Turkey. An approach based on the assessment of all possible regression types was used to select the predictors among the NCEP reanalysis data set, and artificial neural network (ANN)–based downscaling models were designed separately for each station in the basin. The results of the study showed that precipitation, surface and sea level pressures, air temperatures at surface, 850-, 500-, and 200-hPa pressure levels, and geopotential heights at 850- and 200-hPa pressure levels are the most explanatory NCEP/NCAR parameters for the study a...
TL;DR: In this article, the advantages and shortcomings of using simple distribution functions with finite support (namely, beta and generalized standard two-sided power distributions) to represent and synthesize direct runoff hydrographs are investigated.
Abstract: The primary characteristics that influence the potential of defining a synthetic design hydrograph (SDH), are the hydrograph shape, peak discharge (Qp), volume (V), and duration (D). This paper studies the advantages and shortcomings of using simple distribution functions with finite support (namely, beta and generalized standard two-sided power distributions) to represent and synthesize direct runoff hydrographs. The relationships among Qp, V, D, and distribution parameters are explored on a few flood events selected by a recursive digital filter algorithm and an overthreshold approach. The results obtained indicate that the adopted procedure provides a good compromise between simplicity and accuracy for building SDHs with two assigned flood characteristics (e.g., Qp and V) and a defined shape.
TL;DR: In this article, a modified Green-Ampt model (MGAM) was proposed to simulate water infiltration in layered soils with consideration of entrapped air, and a saturation coefficient S(a) was introduced in MGAM to account for the resistance effect of air entrapment on infiltration.
Abstract: Air entrapment in soil is common in cases of farmland flood irrigation or intense rain. A simple, physically based model would be more useful than the complex two-phase (gaseous and liquid phase) flow model to describe water infiltration in layered soils with air entrapment. This study proposed a modified Green-Ampt model (MGAM) to simulate water infiltration in layered soils with consideration of entrapped air. A saturation coefficient S(a) was introduced in MGAM to account for the resistance effect of air entrapment on infiltration. S(a) had robust physical meaning, and was approximately equal to one minus the plus of the residual air and residual water saturation degree that could be determined from the soil water retention curve equation. In MGAM, the actual water content and hydraulic conductivity of the wetted zone were determined by multiplying S(a) with the saturated values. Infiltration experiments in a 300-cm-long five-layered soil column and a 280-cm-deep eight-layered field soil profile were conducted to test the applicability of MGAM. For comparison, the infiltration process was also simulated by the traditional Green-Ampt model (TGAM), in which the wetted zone was assumed to be fully saturated, and the Bouwer Green-Ampt model (BGAM), in which the hydraulic conductivity of the wetted zone was half that of the saturated hydraulic conductivity. The estimated S(a) values were very close to the measured saturation degree of soil layers at the termination of the experiment. The simulation results indicated that the TGAM overestimated the infiltration rate and cumulative infiltration, whereas the BGAM underestimated the infiltration rate and cumulative infiltration. Furthermore, the depths of the wetting fronts simulated by TGAM and BGAM were considerably smaller than those measured. The MGAM provided satisfactory simulation results and adequately described the infiltration process in both the laboratory soil column and the field soil profile. DOI:10.1061/(ASCE)HE.1943-5584.0000360. (C) 2011 American Society of Civil Engineers.
TL;DR: In this paper, the authors developed an entropy theory for deriving the one-dimensional distribution of velocity in open channels, which includes five parts: (1) Tsallis entropy, (2) the principle of maximum entropy (POME), (3) the specification of information on velocity for constraints, (4) the maximization of entropy, and (5) the probability distribution of the velocity and its entropy.
Abstract: Assuming time-averaged velocity as a random variable, this study develops an entropy theory for deriving the one-dimensional distribution of velocity in open channels. The theory includes five parts: (1) Tsallis entropy; (2) the principle of maximum entropy (POME); (3) the specification of information on velocity for constraints; (4) the maximization of entropy; and (5) the probability distribution of velocity and its entropy. An application of the entropy theory is illustrated by deriving a one-dimensional velocity distribution in open channels in which the dimension is vertical or the flow depth. The derived distribution is tested with field and laboratory observations and is compared to Chiu’s velocity distribution derived from Shannon entropy. The agreement between velocity values are computed with the entropy-based distribution.
TL;DR: In this article, a family of rainfall runoff/storage curves were developed based on the duration and intensity of rainfall events for prediction of surface water runoff in the three wadis and water storage in the dams in response to different rainfall events.
Abstract: Hydrologic Engineering Center-Hydrologic Modeling System model is used to estimate the water storage in the lakes of three dams due to rainfall events in three wadis located in the northern area of the United Arab Emirates (UAE). Like other arid and semiarid regions, rainfall events in the three wadis are limited, scattered, and random. For model calibration, the simulated results were compared with the observed water storage data for several storm events. A family of rainfall-runoff/storage curves was developed based on the duration and intensity of rainfall events. These curves can be used for prediction of surface water runoff in the three wadis and water storage in the dams in response to different rainfall events. The same rainfall event in wadi Bih generates almost twice as much of the surface water runoff generated in each of wadi Ham and wadi Tawiyean. This is mainly attributed to the large catchment area of wadi Bih as compared to the other two wadis. The sensitivity analysis revealed that the am...
TL;DR: In this paper, the authors report on a study that was performed during 2001-2006, in which the climate change simulations of the coupled global climate model of the Canadian Center for Climate Modeling and Analysis were downscaled by a regional hydroclimate model of Peninsular Malaysia (RegHCM-PM) to assess the effect of future climate change on its water resources.
Abstract: The future projections of climate change by means of global climate models of the Earth provide fundamental coarse-grid-resolution hydroclimate data for studies of the effect of climate change on water resources. This paper reports on a study that was performed during 2001–2006, in which the climate change simulations of the coupled global climate model of the Canadian Center for Climate Modeling and Analysis were downscaled by a regional hydroclimate model of Peninsular Malaysia (RegHCM-PM) to the scale of the subregions and watersheds of Peninsular Malaysia (PM), to assess the effect of future climate change on its water resources. On the basis of the simulations of hydroclimatic conditions during the historical period of 1984–1993 and future periods of 2025–2034 and 2041–2050, this report concludes that the overall mean monthly streamflow is approximately the same during both the future period, and the historical period for most of the watersheds of Peninsular Malaysia, except Kelantan and Pahang. In t...
TL;DR: In this article, a case study was conducted in the Teesta subcatchment in Bangladesh for determining design flood flows and corresponding flood stages for different return periods using frequency analysis and MIKE 11 model.
Abstract: A case study was conducted in the Teesta subcatchment in Bangladesh for determining design flood flows and corresponding flood stages for different return periods using frequency analysis and MIKE 11 model. Different distribution functions of frequency analysis were tested for their goodness of fit. The observed discharge data at Kaunia on the river Teesta were used for estimation of design flood. The Pearson type-III distribution was found best fitted by the Kolmogorov-Smirnov, D-index, and L-moment diagram ratio tests, and accordingly 25-, 50-, and 100-year return period design floods were computed. The river network of Teesta River was extracted from SRTM 90-m digital elevation model. The river network of Teesta subcatchment was then simulated by MIKE 11 rainfall-runoff Nedbor-Afstromnings-Model (NAM) and HD model. The resultant time series of river stage was then compared with corresponding observed values. From the model, a stage-discharge relationship ( Q-h ) curve and respective equation were devel...
TL;DR: In this article, the authors characterize the variability of precipitation in a small, mountainous watershed and quantifies the uncertainty of precipitation estimates caused by sparse precipitation gauging stations, finding that the use of 4 or more gauges implicitly allowed a close approximation of the best available daily mean catchment precipitation estimates.
Abstract: Watershed modeling requires reliable climate input data that provide a reasonable representation of spatial variability. In many cases, limited access, complex terrain, and remoteness make it difficult to acquire good data. This work characterizes the variability of precipitation in a small, mountainous watershed and quantifies the uncertainty of precipitation estimates caused by sparse precipitation gauging stations. Spatial precipitation variability was found to be of particular concern during the summer months. When one gauge within the watershed is recording precipitation, integration times of more than 8 days are necessary for all gauges to record. In the study catchment, the absolute error in daily mean catchment precipitation exponentially decreased with the increased number of precipitation gauges compared with the best available estimate. The use of 4 or more gauges implicitly allowed a close approximation of the best available daily mean catchment precipitation estimates. Fuzzy multiple linear r...
TL;DR: Liuxihe model as discussed by the authors is a physically based, distributed hydrological model for river basin flood forecasting/simulation, which can be employed by other physically-based, distributive hydrologogical models also.
Abstract: Past research shows that physically based distributed hydrological model has the advantage of better representing the basin characteristics and the hydrologic processes to potentially simulate/predict river basin flood. But how to physically derive model parameters directly from terrain data and to acquire channel cross-sectional size are still difficult jobs in physically based distributed hydrological modeling that prevented its operational application in river basin flood forecasting. To deal with these challenges, this paper first presents a physically based, distributed hydrological model for river basin flood forecasting/simulation, called the Liuxihe model. Then a method for estimating channel cross-sectional size was proposed that utilizes a readily accessible public data set acquired by remote sensing techniques, which could be employed by other physically based, distributed hydrological models also. Finally, a method for deriving model parameters was proposed that adjusts model parameters with i...
TL;DR: In this article, the authors analyzed hydrological extremes defined by 7-day high flow and low flow of the Pearl River Basin by using a copula family and concluded that the concurrent occurrence of extreme high and low flows is of small probability.
Abstract: It is believed that the currently increasing temperature, also known as global warming, has altered the hydrological cycle and thus the hydrometeorological extremes become frequent. In this study, the authors analyze hydrological extremes defined by 7-day high flow and low flow of the Pearl River Basin by using a copula family. The results indicate that the concurrent occurrence of extreme high and low flow is of small probability. It implies that the probability is small that the lower Pearl River Basin is attacked by heavy droughts or floods because of the combined effects of high or low flow of the two major tributaries of the Pearl River, i.e., the West and North Rivers. Therefore, the authors can conclude that the joint probability of hydrological extremes of two tributaries of a river basin could be small, albeit the occurrence of hydrological extremes of an individual river is of large probability. Besides, the results of this study also reveal increasing 7-day low flow in winter, which should be b...
TL;DR: The Green-Ampt model as discussed by the authors is an approximate analytical solution to Richards' equation that is commonly used to simulate infiltration processes in hydrological models and land surface schemes and investigates the limiting conditions under which the green-ampt model is appropriate and how individual assumptions about lower boundary conditions affect the validity of the model.
Abstract: The Green-Ampt model is an approximate analytical solution to Richards’ equation that is commonly used to simulate infiltration processes in hydrological models and land surface schemes. The Green-Ampt model assumes that neither a water table nor an impermeable layer (e.g., bedrock or a frost table) exist near the soil surface. In regional-scale applications these idealized conditions will often not be met, and it is presently unclear what implications this has for regional water resource models. This paper investigates the limiting conditions under which the Green-Ampt model is appropriate and how individual assumptions about lower boundary conditions affect the validity of the model. Guided by the comparison between the Green-Ampt model and numerical solutions to Richards’ equation, various simple revisions to the Green-Ampt model are suggested. Results demonstrate that even when the traditional assumptions are relaxed, the Green-Ampt model often still provides reasonable results for regional-scale anal...
TL;DR: In this paper, the performance of an M5 model tree and the effects of pruning and smoothing applied to reservoir inflow prediction were compared with conventional univariate autoregressive integrated moving average (stochastic) models.
Abstract: This study reports the performance of an M5 model tree (MT) and the effects of pruning and smoothing applied to reservoir inflow prediction. The full year and seasonal monthly time step MT predictions were compared with conventional univariate autoregressive integrated moving average (stochastic) models. It was found that stochastic models could not predict the future inflows in a better way, because the observed series had not followed any particular distribution. However, it was found that the stochastic models showed better improvement using a logarithmic-transformed series, but the logarithmic-transformed MT results showed otherwise. The model validation was performed using the comparison of goodness of fit measures, standard statistics, time series, and scatter plots of predicted inflows with observed inflows. The effect of pruning each leaf in the MT model was also studied. Instead of pruning all the leaves, leading to lesser predictive accuracy, selective pruning was carried out based on the import...
TL;DR: In this paper, the Mann-Kendall method was applied to analyze the trend of flow complexity change in the upper reaches of the Yangtze River, and the influencing factor of the flow-complexity change was analyzed.
Abstract: Flow complexity, which means the degree of uncertainty or the rate of information production of a flow series, is analyzed for the upper reaches of the Yangtze River. Sample entropy (SampEn) is applied to measure flow complexity, and the Mann-Kendall method is applied to analyze the trend of flow-complexity change. Except for the flow complexity of the Jinsha River, which is increasing, the flow complexity of the upper reaches of the Yangtze River is decreasing. The influencing factor of the flow-complexity change is analyzed. On the basis of analysis of the rainfall complexity, which is also measured by SampEn, it is considered that the flow-complexity increase of the Jinsha River may be attributed to the rainfall-complexity increase, while the flow-complexity loss of the upper reaches of the Yangtze River may be attributed to the underlying surface-condition change influenced by human activities, especially reservoir construction. The reservoir operation makes the flow series more regular and self-simil...
TL;DR: In this article, the authors used the downscaled CRCM4.2 data to simulate streamflow and reservoir inflow in a hydrologic model and found that the model's ability to accurately simulate stream flow and reservoir infllow is significantly improved as compared to the use of the raw CRCM 4.2.
Abstract: Climate change impact studies have generally downscaled large-scale global climate model (GCM) output data; however, few studies have considered downscaling regional climate model (RCM) data. It is unclear whether further downscaling raw RCM data could be beneficial or not in a hydrologic impact study. This study provides some experimental results to address that question. Raw Canadian regional climate model (CRCM4.2) data are downscaled by using a common statistical downscaling method (SDSM) and a data-driven technique called a time-lagged feedforward network (TLFN). Regardless of the downscaling methods and the predictands (e.g., precipitation, temperature), the downscaled CRCM4.2 data are found to be much closer to the observed data than the raw CRCM4.2 data. When the downscaled CRCM4.2 data are used in a hydrologic model (HBV), the model’s ability to accurately simulate streamflow and reservoir inflow is significantly improved as compared to the use of the raw CRCM4.2 data. Simulations of future river...