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streamflow</title> <meta name="description" content="Search results for: streamflow"> <meta name="keywords" content="streamflow"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button class="d-block d-lg-none navbar-toggler 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id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="streamflow"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 47</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: streamflow</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">47</span> Application of Stochastic Models to Annual Extreme Streamflow Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Karim%20Hamidi%20Machekposhti">Karim Hamidi Machekposhti</a>, <a href="https://publications.waset.org/abstracts/search?q=Hossein%20Sedghi"> Hossein Sedghi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=stochastic%20models" title="stochastic models">stochastic models</a>, <a href="https://publications.waset.org/abstracts/search?q=ARIMA" title=" ARIMA"> ARIMA</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20streamflow" title=" extreme streamflow"> extreme streamflow</a>, <a href="https://publications.waset.org/abstracts/search?q=Karkheh%20river" title=" Karkheh river"> Karkheh river</a> </p> <a href="https://publications.waset.org/abstracts/97759/application-of-stochastic-models-to-annual-extreme-streamflow-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/97759.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">148</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">46</span> Challenge of Baseline Hydrology Estimation at Large-Scale Watersheds</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Can%20Liu">Can Liu</a>, <a href="https://publications.waset.org/abstracts/search?q=Graham%20Markowitz"> Graham Markowitz</a>, <a href="https://publications.waset.org/abstracts/search?q=John%20Balay"> John Balay</a>, <a href="https://publications.waset.org/abstracts/search?q=Ben%20Pratt"> Ben Pratt</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Baseline or natural hydrology is commonly employed for hydrologic modeling and quantification of hydrologic alteration due to manmade activities. It can inform planning and policy related efforts for various state and federal water resource agencies to restore natural streamflow flow regimes. A common challenge faced by hydrologists is how to replicate unaltered streamflow conditions, particularly in large watershed settings prone to development and regulation. Three different methods were employed to estimate baseline streamflow conditions for 6 major subbasins the Susquehanna River Basin; those being: 1) incorporation of consumptive water use and reservoir operations back into regulated gaged records; 2) using a map correlation method and flow duration (exceedance probability) regression equations; 3) extending the pre-regulation streamflow records based on the relationship between concurrent streamflows at unregulated and regulated gage locations. Parallel analyses were perform among the three methods and limitations associated with each are presented. Results from these analyses indicate that generating baseline streamflow records at large-scale watersheds remain challenging, even with long-term continuous stream gage records available. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=baseline%20hydrology" title="baseline hydrology">baseline hydrology</a>, <a href="https://publications.waset.org/abstracts/search?q=streamflow%20gage" title=" streamflow gage"> streamflow gage</a>, <a href="https://publications.waset.org/abstracts/search?q=subbasin" title=" subbasin"> subbasin</a>, <a href="https://publications.waset.org/abstracts/search?q=regression" title=" regression"> regression</a> </p> <a href="https://publications.waset.org/abstracts/62920/challenge-of-baseline-hydrology-estimation-at-large-scale-watersheds" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/62920.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">324</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">45</span> Regression Analysis in Estimating Stream-Flow and the Effect of Hierarchical Clustering Analysis: A Case Study in Euphrates-Tigris Basin</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Goksel%20Ezgi%20Guzey">Goksel Ezgi Guzey</a>, <a href="https://publications.waset.org/abstracts/search?q=Bihrat%20Onoz"> Bihrat Onoz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The scarcity of streamflow gauging stations and the increasing effects of global warming cause designing water management systems to be very difficult. This study is a significant contribution to assessing regional regression models for estimating streamflow. In this study, simulated meteorological data was related to the observed streamflow data from 1971 to 2020 for 33 stream gauging stations of the Euphrates-Tigris Basin. Ordinary least squares regression was used to predict flow for 2020-2100 with the simulated meteorological data. CORDEX- EURO and CORDEX-MENA domains were used with 0.11 and 0.22 grids, respectively, to estimate climate conditions under certain climate scenarios. Twelve meteorological variables simulated by two regional climate models, RCA4 and RegCM4, were used as independent variables in the ordinary least squares regression, where the observed streamflow was the dependent variable. The variability of streamflow was then calculated with 5-6 meteorological variables and watershed characteristics such as area and height prior to the application. Of the regression analysis of 31 stream gauging stations' data, the stations were subjected to a clustering analysis, which grouped the stations in two clusters in terms of their hydrometeorological properties. Two streamflow equations were found for the two clusters of stream gauging stations for every domain and every regional climate model, which increased the efficiency of streamflow estimation by a range of 10-15% for all the models. This study underlines the importance of homogeneity of a region in estimating streamflow not only in terms of the geographical location but also in terms of the meteorological characteristics of that region. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hydrology" title="hydrology">hydrology</a>, <a href="https://publications.waset.org/abstracts/search?q=streamflow%20estimation" title=" streamflow estimation"> streamflow estimation</a>, <a href="https://publications.waset.org/abstracts/search?q=climate%20change" title=" climate change"> climate change</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrologic%20modeling" title=" hydrologic modeling"> hydrologic modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=HBV" title=" HBV"> HBV</a>, <a href="https://publications.waset.org/abstracts/search?q=hydropower" title=" hydropower"> hydropower</a> </p> <a href="https://publications.waset.org/abstracts/150162/regression-analysis-in-estimating-stream-flow-and-the-effect-of-hierarchical-clustering-analysis-a-case-study-in-euphrates-tigris-basin" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/150162.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">129</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">44</span> Streamflow Modeling Using the PyTOPKAPI Model with Remotely Sensed Rainfall Data: A Case Study of Gilgel Ghibe Catchment, Ethiopia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zeinu%20Ahmed%20Rabba">Zeinu Ahmed Rabba</a>, <a href="https://publications.waset.org/abstracts/search?q=Derek%20D%20Stretch"> Derek D Stretch</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Remote sensing contributes valuable information to streamflow estimates. Usually, stream flow is directly measured through ground-based hydrological monitoring station. However, in many developing countries like Ethiopia, ground-based hydrological monitoring networks are either sparse or nonexistent, which limits the manage water resources and hampers early flood-warning systems. In such cases, satellite remote sensing is an alternative means to acquire such information. This paper discusses the application of remotely sensed rainfall data for streamflow modeling in Gilgel Ghibe basin in Ethiopia. Ten years (2001-2010) of two satellite-based precipitation products (SBPP), TRMM and WaterBase, were used. These products were combined with the PyTOPKAPI hydrological model to generate daily stream flows. The results were compared with streamflow observations at Gilgel Ghibe Nr, Assendabo gauging station using four statistical tools (Bias, R², NS and RMSE). The statistical analysis indicates that the bias-adjusted SBPPs agree well with gauged rainfall compared to bias-unadjusted ones. The SBPPs with no bias-adjustment tend to overestimate (high Bias and high RMSE) the extreme precipitation events and the corresponding simulated streamflow outputs, particularly during wet months (June-September) and underestimate the streamflow prediction over few dry months (January and February). This shows that bias-adjustment can be important for improving the performance of the SBPPs in streamflow forecasting. We further conclude that the general streamflow patterns were well captured at daily time scales when using SBPPs after bias adjustment. However, the overall results demonstrate that the simulated streamflow using the gauged rainfall is superior to those obtained from remotely sensed rainfall products including bias-adjusted ones. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ethiopia" title="Ethiopia">Ethiopia</a>, <a href="https://publications.waset.org/abstracts/search?q=PyTOPKAPI%20model" title=" PyTOPKAPI model"> PyTOPKAPI model</a>, <a href="https://publications.waset.org/abstracts/search?q=remote%20sensing" title=" remote sensing"> remote sensing</a>, <a href="https://publications.waset.org/abstracts/search?q=streamflow" title=" streamflow"> streamflow</a>, <a href="https://publications.waset.org/abstracts/search?q=Tropical%20Rainfall%20Measuring%20Mission%20%28TRMM%29" title=" Tropical Rainfall Measuring Mission (TRMM)"> Tropical Rainfall Measuring Mission (TRMM)</a>, <a href="https://publications.waset.org/abstracts/search?q=waterBase" title=" waterBase"> waterBase</a> </p> <a href="https://publications.waset.org/abstracts/72279/streamflow-modeling-using-the-pytopkapi-model-with-remotely-sensed-rainfall-data-a-case-study-of-gilgel-ghibe-catchment-ethiopia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72279.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">284</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">43</span> Improvement of Environment and Climate Change Canada’s Gem-Hydro Streamflow Forecasting System </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Etienne%20Gaborit">Etienne Gaborit</a>, <a href="https://publications.waset.org/abstracts/search?q=Dorothy%20Durnford"> Dorothy Durnford</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniel%20Deacu"> Daniel Deacu</a>, <a href="https://publications.waset.org/abstracts/search?q=Marco%20Carrera"> Marco Carrera</a>, <a href="https://publications.waset.org/abstracts/search?q=Nathalie%20Gauthier"> Nathalie Gauthier</a>, <a href="https://publications.waset.org/abstracts/search?q=Camille%20Garnaud"> Camille Garnaud</a>, <a href="https://publications.waset.org/abstracts/search?q=Vincent%20Fortin"> Vincent Fortin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> A new experimental streamflow forecasting system was recently implemented at the Environment and Climate Change Canada’s (ECCC) Canadian Centre for Meteorological and Environmental Prediction (CCMEP). It relies on CaLDAS (Canadian Land Data Assimilation System) for the assimilation of surface variables, and on a surface prediction system that feeds a routing component. The surface energy and water budgets are simulated with the SVS (Soil, Vegetation, and Snow) Land-Surface Scheme (LSS) at 2.5-km grid spacing over Canada. The routing component is based on the Watroute routing scheme at 1-km grid spacing for the Great Lakes and Nelson River watersheds. The system is run in two distinct phases: an analysis part and a forecast part. During the analysis part, CaLDAS outputs are used to force the routing system, which performs streamflow assimilation. In forecast mode, the surface component is forced with the Canadian GEM atmospheric forecasts and is initialized with a CaLDAS analysis. Streamflow performances of this new system are presented over 2019. Performances are compared to the current ECCC’s operational streamflow forecasting system, which is different from the new experimental system in many aspects. These new streamflow forecasts are also compared to persistence. Overall, the new streamflow forecasting system presents promising results, highlighting the need for an elaborated assimilation phase before performing the forecasts. However, the system is still experimental and is continuously being improved. Some major recent improvements are presented here and include, for example, the assimilation of snow cover data from remote sensing, a backward propagation of assimilated flow observations, a new numerical scheme for the routing component, and a new reservoir model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=assimilation%20system" title="assimilation system">assimilation system</a>, <a href="https://publications.waset.org/abstracts/search?q=distributed%20physical%20model" title=" distributed physical model"> distributed physical model</a>, <a href="https://publications.waset.org/abstracts/search?q=offline%20hydro-meteorological%20chain" title=" offline hydro-meteorological chain"> offline hydro-meteorological chain</a>, <a href="https://publications.waset.org/abstracts/search?q=short-term%20streamflow%20forecasts" title=" short-term streamflow forecasts"> short-term streamflow forecasts</a> </p> <a href="https://publications.waset.org/abstracts/116891/improvement-of-environment-and-climate-change-canadas-gem-hydro-streamflow-forecasting-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/116891.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">130</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">42</span> Flow Duration Curves and Recession Curves Connection through a Mathematical Link</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elena%20Carcano">Elena Carcano</a>, <a href="https://publications.waset.org/abstracts/search?q=Mirzi%20Betasolo"> Mirzi Betasolo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This study helps Public Water Bureaus in giving reliable answers to water concession requests. Rapidly increasing water requests can be supported provided that further uses of a river course are not totally compromised, and environmental features are protected as well. Strictly speaking, a water concession can be considered a continuous drawing from the source and causes a mean annual streamflow reduction. Therefore, deciding if a water concession is appropriate or inappropriate seems to be easily solved by comparing the generic demand to the mean annual streamflow value at disposal. Still, the immediate shortcoming for such a comparison is that streamflow data are information available only for few catchments and, most often, limited to specific sites. Subsequently, comparing the generic water demand to mean daily discharge is indeed far from being completely satisfactory since the mean daily streamflow is greater than the water withdrawal for a long period of a year. Consequently, such a comparison appears to be of little significance in order to preserve the quality and the quantity of the river. In order to overcome such a limit, this study aims to complete the information provided by flow duration curves introducing a link between Flow Duration Curves (FDCs) and recession curves and aims to show the chronological sequence of flows with a particular focus on low flow data. The analysis is carried out on 25 catchments located in North-Eastern Italy for which daily data are provided. The results identify groups of catchments as hydrologically homogeneous, having the lower part of the FDCs (corresponding streamflow interval is streamflow Q between 300 and 335, namely: Q(300), Q(335)) smoothly reproduced by a common recession curve. In conclusion, the results are useful to provide more reliable answers to water request, especially for those catchments which show similar hydrological response and can be used for a focused regionalization approach on low flow data. A mathematical link between streamflow duration curves and recession curves is herein provided, thus furnishing streamflow duration curves information upon a temporal sequence of data. In such a way, by introducing assumptions on recession curves, the chronological sequence upon low flow data can also be attributed to FDCs, which are known to lack this information by nature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=chronological%20sequence%20of%20discharges" title="chronological sequence of discharges">chronological sequence of discharges</a>, <a href="https://publications.waset.org/abstracts/search?q=recession%20curves" title=" recession curves"> recession curves</a>, <a href="https://publications.waset.org/abstracts/search?q=streamflow%20duration%20curves" title=" streamflow duration curves"> streamflow duration curves</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20concession" title=" water concession"> water concession</a> </p> <a href="https://publications.waset.org/abstracts/131516/flow-duration-curves-and-recession-curves-connection-through-a-mathematical-link" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/131516.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">185</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">41</span> Changes in Forest Cover Regulate Streamflow in Central Nigerian Gallery Forests</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rahila%20Yilangai">Rahila Yilangai</a>, <a href="https://publications.waset.org/abstracts/search?q=Sonali%20Saha"> Sonali Saha</a>, <a href="https://publications.waset.org/abstracts/search?q=Amartya%20Saha"> Amartya Saha</a>, <a href="https://publications.waset.org/abstracts/search?q=Augustine%20Ezealor"> Augustine Ezealor</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Gallery forests in sub-Saharan Africa are drastically disappearing due to intensive anthropogenic activities thus reducing ecosystem services, one of which is water provisioning. The role played by forest cover in regulating streamflow and water yield is not well understood, especially in West Africa. This pioneering 2-year study investigated the interrelationships between plant cover and hydrology in protected and unprotected gallery forests. Rainfall, streamflow, and evapotranspiration (ET) measurements/estimates over 2015-2016 were obtained to form a water balance for both catchments. In addition, transpiration in the protected gallery forest with high vegetation cover was calculated from stomatal conductance readings of selected species chosen from plot level data of plant diversity and abundance. Results showed that annual streamflow was significantly higher in the unprotected site than the protected site, even when normalized by catchment area. However, streamflow commenced earlier and lasted longer in the protected site than the degraded unprotected site, suggesting regulation by the greater tree density in the protected site. Streamflow correlated strongly with rainfall with the highest peak in August. As expected, transpiration measurements were less than potential evapotranspiration estimates, while rainfall exceeded ET in the water cycle. The water balance partitioning suggests that the lower vegetation cover in the unprotected catchment leads to a larger runoff in the rainy season and less infiltration, thereby leading to streams drying up earlier, than in the protected catchment. This baseline information is important in understanding the contribution of plants in water cycle regulation, for modeling integrative water management in applied research and natural resource management in sustaining water resources with changing the land cover and climate uncertainties in this data-poor region. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=evapotranspiration" title="evapotranspiration">evapotranspiration</a>, <a href="https://publications.waset.org/abstracts/search?q=gallery%20forest" title=" gallery forest"> gallery forest</a>, <a href="https://publications.waset.org/abstracts/search?q=rainfall" title=" rainfall"> rainfall</a>, <a href="https://publications.waset.org/abstracts/search?q=streamflow" title=" streamflow"> streamflow</a>, <a href="https://publications.waset.org/abstracts/search?q=transpiration" title=" transpiration"> transpiration</a> </p> <a href="https://publications.waset.org/abstracts/95088/changes-in-forest-cover-regulate-streamflow-in-central-nigerian-gallery-forests" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95088.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">173</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">40</span> Hydrological Evaluation of Satellite Precipitation Products Using IHACRES Rainfall-Runoff Model over a Basin in Iran</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahmoud%20Zakeri%20Niri">Mahmoud Zakeri Niri</a>, <a href="https://publications.waset.org/abstracts/search?q=Saber%20Moazami"> Saber Moazami</a>, <a href="https://publications.waset.org/abstracts/search?q=Arman%20Abdollahipour"> Arman Abdollahipour</a>, <a href="https://publications.waset.org/abstracts/search?q=Hossein%20Ghalkhani"> Hossein Ghalkhani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The objective of this research is to hydrological evaluation of four widely-used satellite precipitation products named PERSIANN, TMPA-3B42V7, TMPA-3B42RT, and CMORPH over Zarinehrood basin in Iran. For this aim, at first, daily streamflow of Sarough-cahy river of Zarinehrood basin was simulated using IHACRES rainfall-runoff model with daily rain gauge and temperature as input data from 1988 to 2008. Then, the model was calibrated in two different periods through comparison the simulated discharge with the observed one at hydrometric stations. Moreover, in order to evaluate the performance of satellite precipitation products in streamflow simulation, the calibrated model was validated using daily satellite rainfall estimates from the period of 2003 to 2008. The obtained results indicated that TMPA-3B42V7 with CC of 0.69, RMSE of 5.93 mm/day, MAE of 4.76 mm/day, and RBias of -5.39% performs better simulation of streamflow than those PERSIANN and CMORPH over the study area. It is noteworthy that in Iran, the availability of ground measuring station data is very limited because of the sparse density of hydro-meteorological networks. On the other hand, large spatial and temporal variability of precipitations and lack of a reliable and extensive observing system are the most important challenges to rainfall analysis, flood prediction, and other hydrological applications in this country. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hydrological%20evaluation" title="hydrological evaluation">hydrological evaluation</a>, <a href="https://publications.waset.org/abstracts/search?q=IHACRES" title=" IHACRES"> IHACRES</a>, <a href="https://publications.waset.org/abstracts/search?q=satellite%20precipitation%20product" title=" satellite precipitation product"> satellite precipitation product</a>, <a href="https://publications.waset.org/abstracts/search?q=streamflow%20simulation" title=" streamflow simulation"> streamflow simulation</a> </p> <a href="https://publications.waset.org/abstracts/40319/hydrological-evaluation-of-satellite-precipitation-products-using-ihacres-rainfall-runoff-model-over-a-basin-in-iran" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40319.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">241</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">39</span> Application of Hydrological Model in Support of Streamflow Allocation in Arid Watersheds in Northwestern China</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Chansheng%20He">Chansheng He</a>, <a href="https://publications.waset.org/abstracts/search?q=Lanhui%20Zhang"> Lanhui Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Baoqing%20Zhang"> Baoqing Zhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Spatial heterogeneity of landscape significantly affects watershed hydrological processes, particularly in high elevation and cold mountainous watersheds such as the inland river (terminal lake) basins in Northwest China, where the upper reach mountainous areas are the main source of streamflow for the downstream agricultural oases and desert ecosystems. Thus, it is essential to take into account spatial variations of hydrological processes in streamflow allocation at the watershed scale. This paper adapts the Distributed Large Basin Runoff Model (DLBRM) to the Heihe River Watershed, the second largest inland river with a drainage area of about 128,000 km2 in Northwest China, for understanding the transfer and partitioning mechanism among the glacier and snowmelt, surface runoff, evapotranspiration, and groundwater recharge among the upper, middle, and lower reaches in the study area. Results indicate that the upper reach Qilian Mountain area is the main source of streamflow for the middle reach agricultural oasis and downstream desert areas. Large withdrawals for agricultural irrigation in the middle reach had significantly depleted river flow for the lower reach desert ecosystems. Innovative conservation and enforcement programs need to be undertaken to ensure the successful implementation of water allocation plan of delivering 0.95 x 109 m3 of water downstream annually by the State Council in the Heihe River Watershed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=DLBRM" title="DLBRM">DLBRM</a>, <a href="https://publications.waset.org/abstracts/search?q=Northwestern%20China" title=" Northwestern China"> Northwestern China</a>, <a href="https://publications.waset.org/abstracts/search?q=spatial%20variation" title=" spatial variation"> spatial variation</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20allocation" title=" water allocation"> water allocation</a> </p> <a href="https://publications.waset.org/abstracts/40864/application-of-hydrological-model-in-support-of-streamflow-allocation-in-arid-watersheds-in-northwestern-china" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40864.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">302</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">38</span> Analysis of the Extreme Hydrometeorological Events in the Theorical Hydraulic Potential and Streamflow Forecast</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Sara%20Patricia%20Ibarra-Zavaleta">Sara Patricia Ibarra-Zavaleta</a>, <a href="https://publications.waset.org/abstracts/search?q=Rabindranarth%20Romero-Lopez"> Rabindranarth Romero-Lopez</a>, <a href="https://publications.waset.org/abstracts/search?q=Rosario%20Langrave"> Rosario Langrave</a>, <a href="https://publications.waset.org/abstracts/search?q=Annie%20Poulin"> Annie Poulin</a>, <a href="https://publications.waset.org/abstracts/search?q=Gerald%20Corzo"> Gerald Corzo</a>, <a href="https://publications.waset.org/abstracts/search?q=Mathias%20Glaus"> Mathias Glaus</a>, <a href="https://publications.waset.org/abstracts/search?q=Ricardo%20Vega-Azamar"> Ricardo Vega-Azamar</a>, <a href="https://publications.waset.org/abstracts/search?q=Norma%20Angelica%20Oropeza"> Norma Angelica Oropeza</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The progressive change in climatic conditions worldwide has increased frequency and severity of extreme hydrometeorological events (EHE). Mexico is an example; this has been affected by the presence of EHE leaving economic, social and environmental losses. The objective of this research was to apply a Canadian distributed hydrological model (DHM) to tropical conditions and to evaluate its capacity to predict flows in a basin in the central Gulf of Mexico. In addition, the DHM (once calibrated and validated) was used to calculate the theoretical hydraulic power and the performance to predict streamflow before the presence of an EHE. The results of the DHM show that the goodness of fit indicators between the observed and simulated flows in the calibration process (NSE=0.83, RSR=0.021 and BIAS=-4.3) and validation: temporal was assessed at two points: point one (NSE=0.78, RSR=0.113 and BIAS=0.054) and point two (NSE=0.825, RSR=0.103 and BIAS=0.063) are satisfactory. The DHM showed its applicability in tropical environments and its ability to characterize the rainfall-runoff relationship in the study area. This work can serve as a tool for identifying vulnerabilities before floods and for the rational and sustainable management of water resources. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=HYDROTEL" title="HYDROTEL">HYDROTEL</a>, <a href="https://publications.waset.org/abstracts/search?q=hydraulic%20power" title=" hydraulic power"> hydraulic power</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20hydrometeorological%20events" title=" extreme hydrometeorological events"> extreme hydrometeorological events</a>, <a href="https://publications.waset.org/abstracts/search?q=streamflow" title=" streamflow"> streamflow</a> </p> <a href="https://publications.waset.org/abstracts/85335/analysis-of-the-extreme-hydrometeorological-events-in-the-theorical-hydraulic-potential-and-streamflow-forecast" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/85335.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">341</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">37</span> Potential Climate Change Impacts on the Hydrological System of the Harvey River Catchment </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hashim%20Isam%20Jameel%20Al-Safi">Hashim Isam Jameel Al-Safi</a>, <a href="https://publications.waset.org/abstracts/search?q=P.%20Ranjan%20Sarukkalige"> P. Ranjan Sarukkalige</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Climate change is likely to impact the Australian continent by changing the trends of rainfall, increasing temperature, and affecting the accessibility of water quantity and quality. This study investigates the possible impacts of future climate change on the hydrological system of the Harvey River catchment in Western Australia by using the conceptual modelling approach (HBV mode). Daily observations of rainfall and temperature and the long-term monthly mean potential evapotranspiration, from six weather stations, were available for the period (1961-2015). The observed streamflow data at Clifton Park gauging station for 33 years (1983-2015) in line with the observed climate variables were used to run, calibrate and validate the HBV-model prior to the simulation process. The calibrated model was then forced with the downscaled future climate signals from a multi-model ensemble of fifteen GCMs of the CMIP3 model under three emission scenarios (A2, A1B and B1) to simulate the future runoff at the catchment outlet. Two periods were selected to represent the future climate conditions including the mid (2046-2065) and late (2080-2099) of the 21<sup>st</sup> century. A control run, with the reference climate period (1981-2000), was used to represent the current climate status. The modelling outcomes show an evident reduction in the mean annual streamflow during the mid of this century particularly for the A1B scenario relative to the control run. Toward the end of the century, all scenarios show a relatively high reduction trends in the mean annual streamflow, especially the A1B scenario, compared to the control run. The decline in the mean annual streamflow ranged between 4-15% during the mid of the current century and 9-42% by the end of the century. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=climate%20change%20impact" title="climate change impact">climate change impact</a>, <a href="https://publications.waset.org/abstracts/search?q=Harvey%20catchment" title=" Harvey catchment"> Harvey catchment</a>, <a href="https://publications.waset.org/abstracts/search?q=HBV%20model" title=" HBV model"> HBV model</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrological%20modelling" title=" hydrological modelling"> hydrological modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=GCMs" title=" GCMs"> GCMs</a>, <a href="https://publications.waset.org/abstracts/search?q=LARS-WG" title=" LARS-WG"> LARS-WG</a> </p> <a href="https://publications.waset.org/abstracts/68726/potential-climate-change-impacts-on-the-hydrological-system-of-the-harvey-river-catchment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68726.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">263</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">36</span> Exploring the Impact of Input Sequence Lengths on Long Short-Term Memory-Based Streamflow Prediction in Flashy Catchments</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Farzad%20Hosseini%20Hossein%20Abadi">Farzad Hosseini Hossein Abadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Cristina%20Prieto%20Sierra"> Cristina Prieto Sierra</a>, <a href="https://publications.waset.org/abstracts/search?q=Cesar%20%C3%81lvarez%20D%C3%ADaz"> Cesar Álvarez Díaz</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Predicting streamflow accurately in flashy catchments prone to floods is a major research and operational challenge in hydrological modeling. Recent advancements in deep learning, particularly Long Short-Term Memory (LSTM) networks, have shown to be promising in achieving accurate hydrological predictions at daily and hourly time scales. In this work, a multi-timescale LSTM (MTS-LSTM) network was applied to the context of regional hydrological predictions at an hourly time scale in flashy catchments. The case study includes 40 catchments allocated in the Basque Country, north of Spain. We explore the impact of hyperparameters on the performance of streamflow predictions given by regional deep learning models through systematic hyperparameter tuning - where optimal regional values for different catchments are identified. The results show that predictions are highly accurate, with Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) metrics values as high as 0.98 and 0.97, respectively. A principal component analysis reveals that a hyperparameter related to the length of the input sequence contributes most significantly to the prediction performance. The findings suggest that input sequence lengths have a crucial impact on the model prediction performance. Moreover, employing catchment-scale analysis reveals distinct sequence lengths for individual basins, highlighting the necessity of customizing this hyperparameter based on each catchment’s characteristics. This aligns with well known “uniqueness of the place” paradigm. In prior research, tuning the length of the input sequence of LSTMs has received limited focus in the field of streamflow prediction. Initially it was set to 365 days to capture a full annual water cycle. Later, performing limited systematic hyper-tuning using grid search, revealed a modification to 270 days. However, despite the significance of this hyperparameter in hydrological predictions, usually studies have overlooked its tuning and fixed it to 365 days. This study, employing a simultaneous systematic hyperparameter tuning approach, emphasizes the critical role of input sequence length as an influential hyperparameter in configuring LSTMs for regional streamflow prediction. Proper tuning of this hyperparameter is essential for achieving accurate hourly predictions using deep learning models. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=LSTMs" title="LSTMs">LSTMs</a>, <a href="https://publications.waset.org/abstracts/search?q=streamflow" title=" streamflow"> streamflow</a>, <a href="https://publications.waset.org/abstracts/search?q=hyperparameters" title=" hyperparameters"> hyperparameters</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrology" title=" hydrology"> hydrology</a> </p> <a href="https://publications.waset.org/abstracts/184629/exploring-the-impact-of-input-sequence-lengths-on-long-short-term-memory-based-streamflow-prediction-in-flashy-catchments" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/184629.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">69</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">35</span> Hydrological Characterization of a Watershed for Streamflow Prediction</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Oseni%20Taiwo%20Amoo">Oseni Taiwo Amoo</a>, <a href="https://publications.waset.org/abstracts/search?q=Bloodless%20Dzwairo"> Bloodless Dzwairo</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we extend the versatility and usefulness of GIS as a methodology for any river basin hydrologic characteristics analysis (HCA). The Gurara River basin located in North-Central Nigeria is presented in this study. It is an on-going research using spatial Digital Elevation Model (DEM) and Arc-Hydro tools to take inventory of the basin characteristics in order to predict water abstraction quantification on streamflow regime. One of the main concerns of hydrological modelling is the quantification of runoff from rainstorm events. In practice, the soil conservation service curve (SCS) method and the Conventional procedure called rational technique are still generally used these traditional hydrological lumped models convert statistical properties of rainfall in river basin to observed runoff and hydrograph. However, the models give little or no information about spatially dispersed information on rainfall and basin physical characteristics. Therefore, this paper synthesizes morphometric parameters in generating runoff. The expected results of the basin characteristics such as size, area, shape, slope of the watershed and stream distribution network analysis could be useful in estimating streamflow discharge. Water resources managers and irrigation farmers could utilize the tool for determining net return from available scarce water resources, where past data records are sparse for the aspect of land and climate. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hydrological%20characteristic" title="hydrological characteristic">hydrological characteristic</a>, <a href="https://publications.waset.org/abstracts/search?q=stream%20flow" title=" stream flow"> stream flow</a>, <a href="https://publications.waset.org/abstracts/search?q=runoff%20discharge" title=" runoff discharge"> runoff discharge</a>, <a href="https://publications.waset.org/abstracts/search?q=land%20and%20climate" title=" land and climate"> land and climate</a> </p> <a href="https://publications.waset.org/abstracts/65719/hydrological-characterization-of-a-watershed-for-streamflow-prediction" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/65719.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">341</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">34</span> Modeling of Sediment Yield and Streamflow of Watershed Basin in the Philippines Using the Soil Water Assessment Tool Model for Watershed Sustainability</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Warda%20L.%20Panondi">Warda L. Panondi</a>, <a href="https://publications.waset.org/abstracts/search?q=Norihiro%20Izumi"> Norihiro Izumi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Sedimentation is a significant threat to the sustainability of reservoirs and their watershed. In the Philippines, the Pulangi watershed experienced a high sediment loss mainly due to land conversions and plantations that showed critical erosion rates beyond the tolerable limit of -10 ton/ha/yr in all of its sub-basin. From this event, the prediction of runoff volume and sediment yield is essential to examine using the country's soil conservation techniques realistically. In this research, the Pulangi watershed was modeled using the soil water assessment tool (SWAT) to predict its watershed basin's annual runoff and sediment yield. For the calibration and validation of the model, the SWAT-CUP was utilized. The model was calibrated with monthly discharge data for 1990-1993 and validated for 1994-1997. Simultaneously, the sediment yield was calibrated in 2014 and validated in 2015 because of limited observed datasets. Uncertainty analysis and calculation of efficiency indexes were accomplished through the SUFI-2 algorithm. According to the coefficient of determination (R2), Nash Sutcliffe efficiency (NSE), King-Gupta efficiency (KGE), and PBIAS, the calculation of streamflow indicates a good performance for both calibration and validation periods while the sediment yield resulted in a satisfactory performance for both calibration and validation. Therefore, this study was able to identify the most critical sub-basin and severe needs of soil conservation. Furthermore, this study will provide baseline information to prevent floods and landslides and serve as a useful reference for land-use policies and watershed management and sustainability in the Pulangi watershed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pulangi%20watershed" title="Pulangi watershed">Pulangi watershed</a>, <a href="https://publications.waset.org/abstracts/search?q=sediment%20yield" title=" sediment yield"> sediment yield</a>, <a href="https://publications.waset.org/abstracts/search?q=streamflow" title=" streamflow"> streamflow</a>, <a href="https://publications.waset.org/abstracts/search?q=SWAT%20model" title=" SWAT model"> SWAT model</a> </p> <a href="https://publications.waset.org/abstracts/133502/modeling-of-sediment-yield-and-streamflow-of-watershed-basin-in-the-philippines-using-the-soil-water-assessment-tool-model-for-watershed-sustainability" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/133502.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">209</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">33</span> High-Resolution Flood Hazard Mapping Using Two-Dimensional Hydrodynamic Model Anuga: Case Study of Jakarta, Indonesia </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hengki%20Eko%20Putra">Hengki Eko Putra</a>, <a href="https://publications.waset.org/abstracts/search?q=Dennish%20Ari%20Putro"> Dennish Ari Putro</a>, <a href="https://publications.waset.org/abstracts/search?q=Tri%20Wahyu%20Hadi"> Tri Wahyu Hadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Edi%20Riawan"> Edi Riawan</a>, <a href="https://publications.waset.org/abstracts/search?q=Junnaedhi%20Dewa%20Gede"> Junnaedhi Dewa Gede</a>, <a href="https://publications.waset.org/abstracts/search?q=Aditia%20Rojali"> Aditia Rojali</a>, <a href="https://publications.waset.org/abstracts/search?q=Fariza%20Dian%20Prasetyo"> Fariza Dian Prasetyo</a>, <a href="https://publications.waset.org/abstracts/search?q=Yudhistira%20Satya%20Pribadi"> Yudhistira Satya Pribadi</a>, <a href="https://publications.waset.org/abstracts/search?q=Dita%20Fatria%20Andarini"> Dita Fatria Andarini</a>, <a href="https://publications.waset.org/abstracts/search?q=Mila%20Khaerunisa"> Mila Khaerunisa</a>, <a href="https://publications.waset.org/abstracts/search?q=Raditya%20Hanung%20Prakoswa"> Raditya Hanung Prakoswa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Catastrophe risk management can only be done if we are able to calculate the exposed risks. Jakarta is an important city economically, socially, and politically and in the same time exposed to severe floods. On the other hand, flood risk calculation is still very limited in the area. This study has calculated the risk of flooding for Jakarta using 2-Dimensional Model ANUGA. 2-Dimensional model ANUGA and 1-Dimensional Model HEC-RAS are used to calculate the risk of flooding from 13 major rivers in Jakarta. ANUGA can simulate physical and dynamical processes between the streamflow against river geometry and land cover to produce a 1-meter resolution inundation map. The value of streamflow as an input for the model obtained from hydrological analysis on rainfall data using hydrologic model HEC-HMS. The probabilistic streamflow derived from probabilistic rainfall using statistical distribution Log-Pearson III, Normal and Gumbel, through compatibility test using Chi Square and Smirnov-Kolmogorov. Flood event on 2007 is used as a comparison to evaluate the accuracy of model output. Property damage estimations were calculated based on flood depth for 1, 5, 10, 25, 50, and 100 years return period against housing value data from the BPS-Statistics Indonesia, Centre for Research and Development of Housing and Settlements, Ministry of Public Work Indonesia. The vulnerability factor was derived from flood insurance claim. Jakarta's flood loss estimation for the return period of 1, 5, 10, 25, 50, and 100 years, respectively are Rp 1.30 t; Rp 16.18 t; Rp 16.85 t; Rp 21.21 t; Rp 24.32 t; and Rp 24.67 t of the total value of building Rp 434.43 t. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=2D%20hydrodynamic%20model" title="2D hydrodynamic model">2D hydrodynamic model</a>, <a href="https://publications.waset.org/abstracts/search?q=ANUGA" title=" ANUGA"> ANUGA</a>, <a href="https://publications.waset.org/abstracts/search?q=flood" title=" flood"> flood</a>, <a href="https://publications.waset.org/abstracts/search?q=flood%20modeling" title=" flood modeling"> flood modeling</a> </p> <a href="https://publications.waset.org/abstracts/58115/high-resolution-flood-hazard-mapping-using-two-dimensional-hydrodynamic-model-anuga-case-study-of-jakarta-indonesia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58115.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">275</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">32</span> Evaluation of Three Digital Graphical Methods of Baseflow Separation Techniques in the Tekeze Water Basin in Ethiopia</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Alebachew%20Halefom">Alebachew Halefom</a>, <a href="https://publications.waset.org/abstracts/search?q=Navsal%20Kumar"> Navsal Kumar</a>, <a href="https://publications.waset.org/abstracts/search?q=Arunava%20Poddar"> Arunava Poddar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The purpose of this work is to specify the parameter values, the base flow index (BFI), and to rank the methods that should be used for base flow separation. Three different digital graphical approaches are chosen and used in this study for the purpose of comparison. The daily time series discharge data were collected from the site for a period of 30 years (1986 up to 2015) and were used to evaluate the algorithms. In order to separate the base flow and the surface runoff, daily recorded streamflow (m³/s) data were used to calibrate procedures and get parameter values for the basin. Additionally, the performance of the model was assessed by the use of the standard error (SE), the coefficient of determination (R²), and the flow duration curve (FDC) and baseflow indexes. The findings indicate that, in general, each strategy can be used worldwide to differentiate base flow; however, the Sliding Interval Method (SIM) performs significantly better than the other two techniques in this basin. The average base flow index was calculated to be 0.72 using the local minimum method, 0.76 using the fixed interval method, and 0.78 using the sliding interval method, respectively. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=baseflow%20index" title="baseflow index">baseflow index</a>, <a href="https://publications.waset.org/abstracts/search?q=digital%20graphical%20methods" title=" digital graphical methods"> digital graphical methods</a>, <a href="https://publications.waset.org/abstracts/search?q=streamflow" title=" streamflow"> streamflow</a>, <a href="https://publications.waset.org/abstracts/search?q=Emba%20Madre%20Watershed" title=" Emba Madre Watershed"> Emba Madre Watershed</a> </p> <a href="https://publications.waset.org/abstracts/160630/evaluation-of-three-digital-graphical-methods-of-baseflow-separation-techniques-in-the-tekeze-water-basin-in-ethiopia" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/160630.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">79</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">31</span> Climate Change Effects in a Mediterranean Island and Streamflow Changes for a Small Basin Using Euro-Cordex Regional Climate Simulations Combined with the SWAT Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pier%20Andrea%20Marras">Pier Andrea Marras</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniela%20Lima"> Daniela Lima</a>, <a href="https://publications.waset.org/abstracts/search?q=Pedro%20Matos%20Soares"> Pedro Matos Soares</a>, <a href="https://publications.waset.org/abstracts/search?q=Rita%20Maria%20Cardoso"> Rita Maria Cardoso</a>, <a href="https://publications.waset.org/abstracts/search?q=Daniela%20Medas"> Daniela Medas</a>, <a href="https://publications.waset.org/abstracts/search?q=Elisabetta%20Dore"> Elisabetta Dore</a>, <a href="https://publications.waset.org/abstracts/search?q=Giovanni%20De%20Giudici"> Giovanni De Giudici</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Climate change effects on the hydrologic cycle are the main concern for the evaluation of water management strategies. Climate models project scenarios of precipitation changes in the future, considering greenhouse emissions. In this study, the EURO-CORDEX (European Coordinated Regional Downscaling Experiment) climate models were first evaluated in a Mediterranean island (Sardinia) against observed precipitation for a historical reference period (1976-2005). A weighted multi-model ensemble (ENS) was built, weighting the single models based on their ability to reproduce observed rainfall. Future projections (2071-2100) were carried out using the 8.5 RCP emissions scenario to evaluate changes in precipitations. ENS was then used as climate forcing for the SWAT model (Soil and Water Assessment Tool), with the aim to assess the consequences of such projected changes on streamflow and runoff of two small catchments located in the South-West Sardinia. Results showed that a decrease of mean rainfall values, up to -25 % at yearly scale, is expected for the future, along with an increase of extreme precipitation events. Particularly in the eastern and southern areas, extreme events are projected to increase by 30%. Such changes reflect on the hydrologic cycle with a decrease of mean streamflow and runoff, except in spring, when runoff is projected to increase by 20-30%. These results stress that the Mediterranean is a hotspot for climate change, and the use of model tools can provide very useful information to adopt water and land management strategies to deal with such changes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=EURO-CORDEX" title="EURO-CORDEX">EURO-CORDEX</a>, <a href="https://publications.waset.org/abstracts/search?q=climate%20change" title=" climate change"> climate change</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrology" title=" hydrology"> hydrology</a>, <a href="https://publications.waset.org/abstracts/search?q=SWAT%20model" title=" SWAT model"> SWAT model</a>, <a href="https://publications.waset.org/abstracts/search?q=Sardinia" title=" Sardinia"> Sardinia</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-model%20ensemble" title=" multi-model ensemble"> multi-model ensemble</a> </p> <a href="https://publications.waset.org/abstracts/141817/climate-change-effects-in-a-mediterranean-island-and-streamflow-changes-for-a-small-basin-using-euro-cordex-regional-climate-simulations-combined-with-the-swat-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/141817.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">213</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">30</span> Using Stable Isotopes and Hydrochemical Characteristics to Assess Stream Water Sources and Flow Paths: A Case Study of the Jonkershoek Catchment, South Africa</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Retang%20A.%20Mokua">Retang A. Mokua</a>, <a href="https://publications.waset.org/abstracts/search?q=Julia%20Glenday"> Julia Glenday</a>, <a href="https://publications.waset.org/abstracts/search?q=Jacobus%20M.%20Nel"> Jacobus M. Nel</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Understanding hydrological processes in mountain headwater catchments, such as the Jonkershoek Valley, is crucial for improving the predictive capability of hydrologic modeling in the Cape Fold Mountain region of South Africa, incorporating the influence of the Table Mountain Group fractured rock aquifers. Determining the contributions of various possible surface and subsurface flow pathways in such catchments has been a challenge due to the complex nature of the fractured rock geology, low ionic concentrations, high rainfall, and streamflow variability. The study aimed to describe the mechanisms of streamflow generation during two seasons (dry and wet). In this study, stable isotopes of water (18O and 2H), hydrochemical tracer electrical conductivity (EC), hydrometric data were used to assess the spatial and temporal variation in flow pathways and geographic sources of stream water. Stream water, groundwater, two shallow piezometers, and spring samples were routinely sampled at two adjacent headwater sub-catchments and analyzed for isotopic ratios during baseflow conditions between January 2018 and January 2019. From these results, no significance (p > 0.05) in seasonal variations in isotopic ratios were observed, the stream isotope signatures were consistent throughout the study period. However, significant seasonal and spatial variations in the EC were evident (p < 0.05). The findings suggest that, in the dry season, baseflow generation mechanisms driven by groundwater and interflow as discharge from perennial springs in these catchments are the primary contributors. The wet season flows were attributed to interflow and perennial and ephemeral springs. Furthermore, the observed seasonal variations in EC were indicative of a greater proportion of sub-surface water inputs. With these results, a conceptual model of streamflow generation processes for the two seasons was constructed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=electrical%20conductivity" title="electrical conductivity">electrical conductivity</a>, <a href="https://publications.waset.org/abstracts/search?q=Jonkershoek%20valley" title=" Jonkershoek valley"> Jonkershoek valley</a>, <a href="https://publications.waset.org/abstracts/search?q=stable%20isotopes" title=" stable isotopes"> stable isotopes</a>, <a href="https://publications.waset.org/abstracts/search?q=table%20mountain%20group" title=" table mountain group"> table mountain group</a> </p> <a href="https://publications.waset.org/abstracts/114550/using-stable-isotopes-and-hydrochemical-characteristics-to-assess-stream-water-sources-and-flow-paths-a-case-study-of-the-jonkershoek-catchment-south-africa" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/114550.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">109</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">29</span> Optimizing Groundwater Pumping for a Complex Groundwater/Surface Water System</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Emery%20A.%20Coppola%20Jr.">Emery A. Coppola Jr.</a>, <a href="https://publications.waset.org/abstracts/search?q=Suna%20Cinar"> Suna Cinar</a>, <a href="https://publications.waset.org/abstracts/search?q=Ferenc%20Szidarovszky"> Ferenc Szidarovszky</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Over-pumping of groundwater resources is a serious problem world-wide. In addition to depleting this valuable resource, hydraulically connected sensitive ecological resources like wetlands and surface water bodies are often impacted and even destroyed by over-pumping. Effectively managing groundwater in a way that satisfy human demand while preserving natural resources is a daunting challenge that will only worsen with growing human populations and climate change. As presented in this paper, a numerical flow model developed for a hypothetical but realistic groundwater/surface water system was combined with formal optimization. Response coefficients were used in an optimization management model to maximize groundwater pumping in a complex, multi-layered aquifer system while protecting against groundwater over-draft, streamflow depletion, and wetland impacts. Pumping optimization was performed for different constraint sets that reflect different resource protection preferences, yielding significantly different optimal pumping solutions. A sensitivity analysis on the optimal solutions was performed on select response coefficients to identify differences between wet and dry periods. Stochastic optimization was also performed, where uncertainty associated with changing irrigation demand due to changing weather conditions are accounted for. One of the strengths of this optimization approach is that it can efficiently and accurately identify superior management strategies that minimize risk and adverse environmental impacts associated with groundwater pumping under different hydrologic conditions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=numerical%20groundwater%20flow%20modeling" title="numerical groundwater flow modeling">numerical groundwater flow modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20management%20optimization" title=" water management optimization"> water management optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=groundwater%20overdraft" title=" groundwater overdraft"> groundwater overdraft</a>, <a href="https://publications.waset.org/abstracts/search?q=streamflow%20depletion" title=" streamflow depletion"> streamflow depletion</a> </p> <a href="https://publications.waset.org/abstracts/58470/optimizing-groundwater-pumping-for-a-complex-groundwatersurface-water-system" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58470.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">233</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">28</span> Application of an Analytical Model to Obtain Daily Flow Duration Curves for Different Hydrological Regimes in Switzerland</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ana%20Clara%20Santos">Ana Clara Santos</a>, <a href="https://publications.waset.org/abstracts/search?q=Maria%20Manuela%20Portela"> Maria Manuela Portela</a>, <a href="https://publications.waset.org/abstracts/search?q=Bettina%20Schaefli"> Bettina Schaefli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This work assesses the performance of an analytical model framework to generate daily flow duration curves, FDCs, based on climatic characteristics of the catchments and on their streamflow recession coefficients. According to the analytical model framework, precipitation is considered to be a stochastic process, modeled as a marked Poisson process, and recession is considered to be deterministic, with parameters that can be computed based on different models. The analytical model framework was tested for three case studies with different hydrological regimes located in Switzerland: pluvial, snow-dominated and glacier. For that purpose, five time intervals were analyzed (the four meteorological seasons and the civil year) and two developments of the model were tested: one considering a linear recession model and the other adopting a nonlinear recession model. Those developments were combined with recession coefficients obtained from two different approaches: forward and inverse estimation. The performance of the analytical framework when considering forward parameter estimation is poor in comparison with the inverse estimation for both, linear and nonlinear models. For the pluvial catchment, the inverse estimation shows exceptional good results, especially for the nonlinear model, clearing suggesting that the model has the ability to describe FDCs. For the snow-dominated and glacier catchments the seasonal results are better than the annual ones suggesting that the model can describe streamflows in those conditions and that future efforts should focus on improving and combining seasonal curves instead of considering single annual ones. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=analytical%20streamflow%20distribution" title="analytical streamflow distribution">analytical streamflow distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20process" title=" stochastic process"> stochastic process</a>, <a href="https://publications.waset.org/abstracts/search?q=linear%20and%20non-linear%20recession" title=" linear and non-linear recession"> linear and non-linear recession</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrological%20modelling" title=" hydrological modelling"> hydrological modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=daily%20discharges" title=" daily discharges"> daily discharges</a> </p> <a href="https://publications.waset.org/abstracts/98484/application-of-an-analytical-model-to-obtain-daily-flow-duration-curves-for-different-hydrological-regimes-in-switzerland" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/98484.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">162</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">27</span> Implications of Optimisation Algorithm on the Forecast Performance of Artificial Neural Network for Streamflow Modelling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Martins%20Y.%20Otache">Martins Y. Otache</a>, <a href="https://publications.waset.org/abstracts/search?q=John%20J.%20Musa"> John J. Musa</a>, <a href="https://publications.waset.org/abstracts/search?q=Abayomi%20I.%20Kuti"> Abayomi I. Kuti</a>, <a href="https://publications.waset.org/abstracts/search?q=Mustapha%20Mohammed"> Mustapha Mohammed</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The performance of an artificial neural network (ANN) is contingent on a host of factors, for instance, the network optimisation scheme. In view of this, the study examined the general implications of the ANN training optimisation algorithm on its forecast performance. To this end, the Bayesian regularisation (Br), Levenberg-Marquardt (LM), and the adaptive learning gradient descent: GDM (with momentum) algorithms were employed under different ANN structural configurations: (1) single-hidden layer, and (2) double-hidden layer feedforward back propagation network. Results obtained revealed generally that the gradient descent with momentum (GDM) optimisation algorithm, with its adaptive learning capability, used a relatively shorter time in both training and validation phases as compared to the Levenberg- Marquardt (LM) and Bayesian Regularisation (Br) algorithms though learning may not be consummated; i.e., in all instances considering also the prediction of extreme flow conditions for 1-day and 5-day ahead, respectively especially using the ANN model. In specific statistical terms on the average, model performance efficiency using the coefficient of efficiency (CE) statistic were Br: 98%, 94%; LM: 98 %, 95 %, and GDM: 96 %, 96% respectively for training and validation phases. However, on the basis of relative error distribution statistics (MAE, MAPE, and MSRE), GDM performed better than the others overall. Based on the findings, it is imperative to state that the adoption of ANN for real-time forecasting should employ training algorithms that do not have computational overhead like the case of LM that requires the computation of the Hessian matrix, protracted time, and sensitivity to initial conditions; to this end, Br and other forms of the gradient descent with momentum should be adopted considering overall time expenditure and quality of the forecast as well as mitigation of network overfitting. On the whole, it is recommended that evaluation should consider implications of (i) data quality and quantity and (ii) transfer functions on the overall network forecast performance. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=streamflow" title="streamflow">streamflow</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a>, <a href="https://publications.waset.org/abstracts/search?q=optimisation" title=" optimisation"> optimisation</a>, <a href="https://publications.waset.org/abstracts/search?q=algorithm" title=" algorithm"> algorithm</a> </p> <a href="https://publications.waset.org/abstracts/132874/implications-of-optimisation-algorithm-on-the-forecast-performance-of-artificial-neural-network-for-streamflow-modelling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132874.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">152</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">26</span> Application of ANN and Fuzzy Logic Algorithms for Runoff and Sediment Yield Modelling of Kal River, India</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mahesh%20Kothari">Mahesh Kothari</a>, <a href="https://publications.waset.org/abstracts/search?q=K.%20D.%20Gharde"> K. D. Gharde</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The ANN and fuzzy logic (FL) models were developed to predict the runoff and sediment yield for catchment of Kal river, India using 21 years (1991 to 2011) rainfall and other hydrological data (evaporation, temperature and streamflow lag by one and two day) and 7 years data for sediment yield modelling. The ANN model performance improved with increasing the input vectors. The fuzzy logic model was performing with R value more than 0.95 during developmental stage and validation stage. The comparatively FL model found to be performing well to ANN in prediction of runoff and sediment yield for Kal river. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=transferred%20function" title="transferred function">transferred function</a>, <a href="https://publications.waset.org/abstracts/search?q=sigmoid" title=" sigmoid"> sigmoid</a>, <a href="https://publications.waset.org/abstracts/search?q=backpropagation" title=" backpropagation"> backpropagation</a>, <a href="https://publications.waset.org/abstracts/search?q=membership%20function" title=" membership function"> membership function</a>, <a href="https://publications.waset.org/abstracts/search?q=defuzzification" title=" defuzzification "> defuzzification </a> </p> <a href="https://publications.waset.org/abstracts/33110/application-of-ann-and-fuzzy-logic-algorithms-for-runoff-and-sediment-yield-modelling-of-kal-river-india" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/33110.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">569</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">25</span> Potential Impacts of Climate Change on Hydrological Droughts in the Limpopo River Basin</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nokwethaba%20Makhanya">Nokwethaba Makhanya</a>, <a href="https://publications.waset.org/abstracts/search?q=Babatunde%20J.%20Abiodun"> Babatunde J. Abiodun</a>, <a href="https://publications.waset.org/abstracts/search?q=Piotr%20Wolski"> Piotr Wolski</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Climate change possibly intensifies hydrological droughts and reduces water availability in river basins. Despite this, most research on climate change effects in southern Africa has focused exclusively on meteorological droughts. This thesis projects the potential impact of climate change on the future characteristics of hydrological droughts in the Limpopo River Basin (LRB). The study uses regional climate model (RCM) measurements (from the Coordinated Regional Climate Downscaling Experiment, CORDEX) and a combination of hydrological simulations (using the Soil and Water Assessment Tool Plus model, SWAT+) to predict the impacts at four global warming levels (GWLs: 1.5℃, 2.0℃, 2.5℃, and 3.0℃) under the RCP8.5 future climate scenario. The SWAT+ model was calibrated and validated with a streamflow dataset observed over the basin, and the sensitivity of model parameters was investigated. The performance of the SWAT+LRB model was verified using the Nash-Sutcliffe efficiency (NSE), Percent Bias (PBIAS), Root Mean Square Error (RMSE), and coefficient of determination (R²). The Standardized Precipitation Evapotranspiration Index (SPEI) and the Standardized Precipitation Index (SPI) have been used to detect meteorological droughts. The Soil Water Index (SSI) has been used to define agricultural drought, while the Water Yield Drought Index (WYLDI), the Surface Run-off Index (SRI), and the Streamflow Index (SFI) have been used to characterise hydrological drought. The performance of the SWAT+ model simulations over LRB is sensitive to the parameters CN2 (initial SCS runoff curve number for moisture condition II) and ESCO (soil evaporation compensation factor). The best simulation generally performed better during the calibration period than the validation period. In calibration and validation periods, NSE is ≤ 0.8, while PBIAS is ≥ ﹣80.3%, RMSE ≥ 11.2 m³/s, and R² ≤ 0.9. The simulations project a future increase in temperature and potential evapotranspiration over the basin, but they do not project a significant future trend in precipitation and hydrological variables. However, the spatial distribution of precipitation reveals a projected increase in precipitation in the southern part of the basin and a decline in the northern part of the basin, with the region of reduced precipitation projected to increase with GWLs. A decrease in all hydrological variables is projected over most parts of the basin, especially over the eastern part of the basin. The simulations predict meteorological droughts (i.e., SPEI and SPI), agricultural droughts (i.e., SSI), and hydrological droughts (i.e., WYLDI, SRI) would become more intense and severe across the basin. SPEI-drought has a greater magnitude of increase than SPI-drought, and agricultural and hydrological droughts have a magnitude of increase between the two. As a result, this research suggests that future hydrological droughts over the LRB could be more severe than the SPI-drought projection predicts but less severe than the SPEI-drought projection. This research can be used to mitigate the effects of potential climate change on basin hydrological drought. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=climate%20change" title="climate change">climate change</a>, <a href="https://publications.waset.org/abstracts/search?q=CORDEX" title=" CORDEX"> CORDEX</a>, <a href="https://publications.waset.org/abstracts/search?q=drought" title=" drought"> drought</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrological%20modelling" title=" hydrological modelling"> hydrological modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=Limpopo%20River%20Basin" title=" Limpopo River Basin"> Limpopo River Basin</a> </p> <a href="https://publications.waset.org/abstracts/157605/potential-impacts-of-climate-change-on-hydrological-droughts-in-the-limpopo-river-basin" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/157605.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">128</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">24</span> Regional Hydrological Extremes Frequency Analysis Based on Statistical and Hydrological Models</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hadush%20Kidane%20Meresa">Hadush Kidane Meresa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The hydrological extremes frequency analysis is the foundation for the hydraulic engineering design, flood protection, drought management and water resources management and planning to utilize the available water resource to meet the desired objectives of different organizations and sectors in a country. This spatial variation of the statistical characteristics of the extreme flood and drought events are key practice for regional flood and drought analysis and mitigation management. For different hydro-climate of the regions, where the data set is short, scarcity, poor quality and insufﬁcient, the regionalization methods are applied to transfer at-site data to a region. This study aims in regional high and low flow frequency analysis for Poland River Basins. Due to high frequent occurring of hydrological extremes in the region and rapid water resources development in this basin have caused serious concerns over the flood and drought magnitude and frequencies of the river in Poland. The magnitude and frequency result of high and low flows in the basin is needed for flood and drought planning, management and protection at present and future. Hydrological homogeneous high and low flow regions are formed by the cluster analysis of site characteristics, using the hierarchical and C- mean clustering and PCA method. Statistical tests for regional homogeneity are utilized, by Discordancy and Heterogeneity measure tests. In compliance with results of the tests, the region river basin has been divided into ten homogeneous regions. In this study, frequency analysis of high and low flows using AM for high flow and 7-day minimum low flow series is conducted using six statistical distributions. The use of L-moment and LL-moment method showed a homogeneous region over entire province with Generalized logistic (GLOG), Generalized extreme value (GEV), Pearson type III (P-III), Generalized Pareto (GPAR), Weibull (WEI) and Power (PR) distributions as the regional drought and flood frequency distributions. The 95% percentile and Flow duration curves of 1, 7, 10, 30 days have been plotted for 10 stations. However, the cluster analysis performed two regions in west and east of the province where L-moment and LL-moment method demonstrated the homogeneity of the regions and GLOG and Pearson Type III (PIII) distributions as regional frequency distributions for each region, respectively. The spatial variation and regional frequency distribution of flood and drought characteristics for 10 best catchment from the whole region was selected and beside the main variable (streamflow: high and low) we used variables which are more related to physiographic and drainage characteristics for identify and delineate homogeneous pools and to derive best regression models for ungauged sites. Those are mean annual rainfall, seasonal flow, average slope, NDVI, aspect, flow length, flow direction, maximum soil moisture, elevation, and drainage order. The regional high-flow or low-flow relationship among one streamflow characteristics with (AM or 7-day mean annual low flows) some basin characteristics is developed using Generalized Linear Mixed Model (GLMM) and Generalized Least Square (GLS) regression model, providing a simple and effective method for estimation of flood and drought of desired return periods for ungauged catchments. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=flood" title="flood ">flood </a>, <a href="https://publications.waset.org/abstracts/search?q=drought" title=" drought"> drought</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency" title=" frequency"> frequency</a>, <a href="https://publications.waset.org/abstracts/search?q=magnitude" title=" magnitude"> magnitude</a>, <a href="https://publications.waset.org/abstracts/search?q=regionalization" title=" regionalization"> regionalization</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic" title=" stochastic"> stochastic</a>, <a href="https://publications.waset.org/abstracts/search?q=ungauged" title=" ungauged"> ungauged</a>, <a href="https://publications.waset.org/abstracts/search?q=Poland" title=" Poland "> Poland </a> </p> <a href="https://publications.waset.org/abstracts/19374/regional-hydrological-extremes-frequency-analysis-based-on-statistical-and-hydrological-models" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/19374.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">602</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">23</span> Estimation of Reservoir Capacity and Sediment Deposition Using Remote Sensing Data</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Odai%20Ibrahim%20Mohammed%20Al%20Balasmeh">Odai Ibrahim Mohammed Al Balasmeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Tapas%20Karmaker"> Tapas Karmaker</a>, <a href="https://publications.waset.org/abstracts/search?q=Richa%20Babbar"> Richa Babbar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this study, the reservoir capacity and sediment deposition were estimated using remote sensing data. The satellite images were synchronized with water level and storage capacity to find out the change in sediment deposition due to soil erosion and transport by streamflow. The water bodies spread area was estimated using vegetation indices, e.g., normalize differences vegetation index (NDVI) and normalize differences water index (NDWI). The 3D reservoir bathymetry was modeled by integrated water level, storage capacity, and area. From the models of different time span, the change in reservoir storage capacity was estimated. Another reservoir with known water level, storage capacity, area, and sediment deposition was used to validate the estimation technique. The t-test was used to assess the results between observed and estimated reservoir capacity and sediment deposition. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=satellite%20data" title="satellite data">satellite data</a>, <a href="https://publications.waset.org/abstracts/search?q=normalize%20differences%20vegetation%20index" title=" normalize differences vegetation index"> normalize differences vegetation index</a>, <a href="https://publications.waset.org/abstracts/search?q=NDVI" title=" NDVI"> NDVI</a>, <a href="https://publications.waset.org/abstracts/search?q=normalize%20differences%20water%20index" title=" normalize differences water index"> normalize differences water index</a>, <a href="https://publications.waset.org/abstracts/search?q=NDWI" title=" NDWI"> NDWI</a>, <a href="https://publications.waset.org/abstracts/search?q=reservoir%20capacity" title=" reservoir capacity"> reservoir capacity</a>, <a href="https://publications.waset.org/abstracts/search?q=sedimentation" title=" sedimentation"> sedimentation</a>, <a href="https://publications.waset.org/abstracts/search?q=t-test%20hypothesis" title=" t-test hypothesis"> t-test hypothesis</a> </p> <a href="https://publications.waset.org/abstracts/125321/estimation-of-reservoir-capacity-and-sediment-deposition-using-remote-sensing-data" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/125321.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">167</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">22</span> Impacts of Climate Change on Water Resources of Greater Zab and Lesser Zab Basins, Iraq, Using Soil and Water Assessment Tool Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Nahlah%20Abbas">Nahlah Abbas</a>, <a href="https://publications.waset.org/abstracts/search?q=Saleh%20A.%20Wasimi"> Saleh A. Wasimi</a>, <a href="https://publications.waset.org/abstracts/search?q=Nadhir%20Al-Ansari"> Nadhir Al-Ansari</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Greater Zab and Lesser Zab are the major tributaries of Tigris River contributing the largest flow volumes into the river. The impacts of climate change on water resources in these basins have not been well addressed. To gain a better understanding of the effects of climate change on water resources of the study area in near future (2049-2069) as well as in distant future (2080-2099), Soil and Water Assessment Tool (SWAT) was applied. The model was first calibrated for the period from 1979 to 2004 to test its suitability in describing the hydrological processes in the basins. The SWAT model showed a good performance in simulating streamflow. The calibrated model was then used to evaluate the impacts of climate change on water resources. Six general circulation models (GCMs) from phase five of the Coupled Model Intercomparison Project (CMIP5) under three Representative Concentration Pathways (RCPs) RCP 2.6, RCP 4.5, and RCP 8.5 for periods of 2049-2069 and 2080-2099 were used to project the climate change impacts on these basins. The results demonstrated a significant decline in water resources availability in the future. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tigris%20River" title="Tigris River">Tigris River</a>, <a href="https://publications.waset.org/abstracts/search?q=climate%20change" title=" climate change"> climate change</a>, <a href="https://publications.waset.org/abstracts/search?q=water%20resources" title=" water resources"> water resources</a>, <a href="https://publications.waset.org/abstracts/search?q=SWAT" title=" SWAT"> SWAT</a> </p> <a href="https://publications.waset.org/abstracts/72381/impacts-of-climate-change-on-water-resources-of-greater-zab-and-lesser-zab-basins-iraq-using-soil-and-water-assessment-tool-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72381.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">204</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">21</span> Flood Predicting in Karkheh River Basin Using Stochastic ARIMA Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Karim%20Hamidi%20Machekposhti">Karim Hamidi Machekposhti</a>, <a href="https://publications.waset.org/abstracts/search?q=Hossein%20Sedghi"> Hossein Sedghi</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdolrasoul%20Telvari"> Abdolrasoul Telvari</a>, <a href="https://publications.waset.org/abstracts/search?q=Hossein%20Babazadeh"> Hossein Babazadeh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Floods have huge environmental and economic impact. Therefore, flood prediction is given a lot of attention due to its importance. This study analysed the annual maximum streamflow (discharge) (AMS or AMD) of Karkheh River in Karkheh River Basin for flood predicting using ARIMA model. For this purpose, we use the Box-Jenkins approach, which contains four-stage method model identification, parameter estimation, diagnostic checking and forecasting (predicting). The main tool used in ARIMA modelling was the SAS and SPSS software. Model identification was done by visual inspection on the ACF and PACF. SAS software computed the model parameters using the ML, CLS and ULS methods. The diagnostic checking tests, AIC criterion, RACF graph and RPACF graphs, were used for selected model verification. In this study, the best ARIMA models for Annual Maximum Discharge (AMD) time series was (4,1,1) with their AIC value of 88.87. The RACF and RPACF showed residuals’ independence. To forecast AMD for 10 future years, this model showed the ability of the model to predict floods of the river under study in the Karkheh River Basin. Model accuracy was checked by comparing the predicted and observation series by using coefficient of determination (R<sup>2</sup>). <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=time%20series%20modelling" title="time series modelling">time series modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20processes" title=" stochastic processes"> stochastic processes</a>, <a href="https://publications.waset.org/abstracts/search?q=ARIMA%20model" title=" ARIMA model"> ARIMA model</a>, <a href="https://publications.waset.org/abstracts/search?q=Karkheh%20river" title=" Karkheh river"> Karkheh river</a> </p> <a href="https://publications.waset.org/abstracts/76660/flood-predicting-in-karkheh-river-basin-using-stochastic-arima-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/76660.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">287</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">20</span> Assessing Flood Risk and Mapping Inundation Zones in the Kelantan River Basin: A Hydrodynamic Modeling Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Fatemehsadat%20Mortazavizadeh">Fatemehsadat Mortazavizadeh</a>, <a href="https://publications.waset.org/abstracts/search?q=Amin%20Dehghani"> Amin Dehghani</a>, <a href="https://publications.waset.org/abstracts/search?q=Majid%20Mirzaei"> Majid Mirzaei</a>, <a href="https://publications.waset.org/abstracts/search?q=Nurulhuda%20Binti%20Mohammad%20Ramli"> Nurulhuda Binti Mohammad Ramli</a>, <a href="https://publications.waset.org/abstracts/search?q=Adnan%20Dehghani"> Adnan Dehghani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Flood is Malaysia's most common and serious natural disaster. Kelantan River Basin is a tropical basin that experiences a rainy season during North-East Monsoon from November to March. It is also one of the hardest hit areas in Peninsular Malaysia during the heavy monsoon rainfall. Considering the consequences of the flood events, it is essential to develop the flood inundation map as part of the mitigation approach. In this study, the delineation of flood inundation zone in the area of Kelantan River basin using a hydrodynamic model is done by HEC-RAS, QGIS and ArcMap. The streamflow data has been generated with the weather generator based on the observation data. Then, the data is statistically analyzed with the Extreme Value (EV1) method for 2-, 5-, 25-, 50- and 100-year return periods. The minimum depth, maximum depth, mean depth, and the standard deviation of all the scenarios, including the OBS, are observed and analyzed. Based on the results, generally, the value of the data increases with the return period for all the scenarios. However, there are certain scenarios that have different results, which not all the data obtained are increasing with the return period. Besides, OBS data resulted in the middle range within Scenario 1 to Scenario 40. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=flood%20inundation" title="flood inundation">flood inundation</a>, <a href="https://publications.waset.org/abstracts/search?q=kelantan%20river%20basin" title=" kelantan river basin"> kelantan river basin</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrodynamic%20model" title=" hydrodynamic model"> hydrodynamic model</a>, <a href="https://publications.waset.org/abstracts/search?q=extreme%20value%20analysis" title=" extreme value analysis"> extreme value analysis</a> </p> <a href="https://publications.waset.org/abstracts/175709/assessing-flood-risk-and-mapping-inundation-zones-in-the-kelantan-river-basin-a-hydrodynamic-modeling-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/175709.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">70</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">19</span> Assessment of the Impacts of Climate Change on Watershed Runoff Using Soil and Water Assessment Tool Model in Southeast Nigeria</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Samuel%20Emeka%20Anarah">Samuel Emeka Anarah</a>, <a href="https://publications.waset.org/abstracts/search?q=Kingsley%20Nnaemeka%20Ogbu"> Kingsley Nnaemeka Ogbu</a>, <a href="https://publications.waset.org/abstracts/search?q=Obasi%20Arinze"> Obasi Arinze</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Quantifying the hydrological response due to changes in climate change is imperative for proper management of water resources within a watershed. The impact of climate change on the hydrology of the Upper Ebony River (UER) watershed, South East Nigeria, was studied using the Soil and Water Assessment Tool (SWAT) hydrological model. A climatological time series analysis from 1985 - 2014 using non-parametric test showed significant negative trends in precipitation and relative humidity trend while minimum and maximum temperature, solar radiation and wind speed showed significant positive trends. Future hypothetical land-use change scenarios (Scenarios 1, 2, 3 and 4) representing urbanization and conversion of forest to agricultural land were combined with future downscaled climate model (CSIRO-Mk3-6-0) and simulated in SWAT model. Relative to the Baseline scenario (2005 - 2014), the results showed a decrease in streamflow by 10.29%, 26.20%, 11.80% and 26.72% for Scenarios 1, 2, 3, and 4 respectively. Model results suggest development of adaptation strategies to cope with the predicted hydrological conditions under future climate change in the watershed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=climate%20change" title="climate change">climate change</a>, <a href="https://publications.waset.org/abstracts/search?q=hydrology" title=" hydrology"> hydrology</a>, <a href="https://publications.waset.org/abstracts/search?q=runoff" title=" runoff"> runoff</a>, <a href="https://publications.waset.org/abstracts/search?q=SWAT%20model" title=" SWAT model"> SWAT model</a> </p> <a href="https://publications.waset.org/abstracts/87127/assessment-of-the-impacts-of-climate-change-on-watershed-runoff-using-soil-and-water-assessment-tool-model-in-southeast-nigeria" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/87127.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">143</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">18</span> River Analysis System Model for Proposed Weirs at Downstream of Large Dam, Thailand</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=S.%20Chuenchooklin">S. Chuenchooklin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research was conducted in the Lower Ping River Basin downstream of the Bhumibol Dam and the Lower Wang River Basin in Tak Province, Thailand. Most of the tributary streams of the Ping can be considered as ungauged catchments. There are 10- pumping station installation at both river banks of the Ping in Tak Province. Recently, most of them could not fully operate due to the water amount in the river below the level that would be pumping, even though included water from the natural river and released flow from the Bhumibol Dam. The aim of this research was to increase the performance of those pumping stations using weir projects in the Ping. Therefore, the river analysis system model (HEC-RAS) was applied to study the hydraulic behavior of water surface profiles in the Ping River with both cases of existing conditions and proposed weirs during the violent flood in 2011 and severe drought in 2013. Moreover, the hydrologic modeling system (HMS) was applied to simulate lateral streamflow hydrograph from ungauged catchments of the Ping. The results of HEC-RAS model calibration with existing conditions in 2011 showed best trial roughness coefficient for the main channel of 0.026. The simulated water surface levels fitted to observation data with R2 of 0.8175. The model was applied to 3 proposed cascade weirs with 2.35 m in height and found surcharge water level only 0.27 m higher than the existing condition in 2011. Moreover, those weirs could maintain river water levels and increase of those pumping performances during less river flow in 2013. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=HEC-RAS" title="HEC-RAS">HEC-RAS</a>, <a href="https://publications.waset.org/abstracts/search?q=HMS" title=" HMS"> HMS</a>, <a href="https://publications.waset.org/abstracts/search?q=pumping%20stations" title=" pumping stations"> pumping stations</a>, <a href="https://publications.waset.org/abstracts/search?q=cascade%20weirs" title=" cascade weirs "> cascade weirs </a> </p> <a href="https://publications.waset.org/abstracts/12884/river-analysis-system-model-for-proposed-weirs-at-downstream-of-large-dam-thailand" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12884.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">390</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=streamflow&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=streamflow&page=2" rel="next">&rsaquo;</a></li> </ul> </div> </main> <footer> <div id="infolinks" class="pt-3 pb-2"> <div class="container"> <div style="background-color:#f5f5f5;" class="p-3"> <div class="row"> <div class="col-md-2"> <ul class="list-unstyled"> About <li><a href="https://waset.org/page/support">About Us</a></li> <li><a href="https://waset.org/page/support#legal-information">Legal</a></li> <li><a target="_blank" rel="nofollow" href="https://publications.waset.org/static/files/WASET-16th-foundational-anniversary.pdf">WASET 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