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[en] The basin was calibrated through monthly discharge for the period (2002–2008) including 2 years as warm-up (2000–2001), after that model was validated on 5 years of hydrometeorological datasets (2009–2013) at two gauge sites located at Neemsar (upstream gauge) and Lucknow (downstream gauge). It is found that the most sensitive parameter for moisture condition II (CN2) was initial curve number. The p-factor and r-factor were obtained in calibration period at Neemsar 0.73 and 0.58 while at Lucknow values are 0.79 and 0.51, whereas in validation period values are 0.61, 0.45 and 1.22, 0.75, respectively. Three statistical parameters have been used to evaluate the SWAT model performance such as Coefficient of Determination (R2), Nash–Sutcliff efficiency (NSE), percent bias (PBIAS). The NSE and R2 values were observed as 0.85, 0.84 and 0.87, 0.86, respectively, in the time of calibration period and values is 0.76, 0.76 and 0.79, 0.83, respectively, in the time of validation period at two above said gauging stations. The PBIAS values during calibration and validation period are − 13.3, − 14.7 and − 4.0, − 15.7, respectively, at the same gauge site which indicates good model performance result.
[en] The MTT (Mean Transit Time) of a catchment without significant surface flow is normally taken to be the sum of mean residence time in the unsaturated zone and mean residence time in the saturated zone. However, the Chalk is a multi-porosity limestone aquifer, with a microporous matrix. This means that the movement of water through the Chalk can occur in complex ways, making the prediction of MTT far from straightforward. Although the Chalk is a regionally-important aquifer, no study of catchment MTT has yet been published. The present study is based on the catchment of the River Lambourn in Berkshire, UK, with an area of 235 km2. Interfluve areas rarely rise above 200 m asl (above sea level), whereas river elevation at the foot of the catchment is ∼50 m asl. Mean annual precipitation is 731 mm. The thickness of the Chalk unsaturated zone reaches a maximum of over 100 m at the water divide at the top of the escarpment on the northern flank of the catchment.
[en] This study investigates the long-term trends in precipitation, runoff and runoff coefficient in major urban watersheds in the United States. The seasonal Mann–Kendall trend test was performed on monthly precipitation, runoff and runoff coefficient data from 1950 to 2009 obtained from 62 urban watersheds covering 21 major urban centers in the United States. The results indicate that only five out of 21 urban centers in the United States showed an uptrend in precipitation. Twelve urban centers showed an uptrend in runoff coefficient. However, six urban centers did not show any trend in runoff coefficient, and three urban centers showed a significant downtrend. The highest rate of change in precipitation, runoff and runoff coefficient was observed in the Houston urban watershed. Based on the results obtained, we also attributed plausible causes for the trends. Our analysis indicated that while a human only influence is observed in most of the urban watersheds, a combined climate and human influence is observed in the central United States. (letter)
[en] Prediction of sediment volume and sediment load is always one of the important issues for decision-makers of watershed basins. The present study investigated the daily suspended sediment load in a watershed basin using the improved support vector machine method. Since in most of the previous studies, the coefficients of the support vector machine method had been calculated based on trial and error, in the present study, the combination of the support vector machine and the genetic algorithm is used. In the first step, the unknown parameters of the support vector machine are calculated and then, the sediment load simulation is performed. Two case studies in the present work involve two earth dams in Semnan Province called Veynakeh and Royan. Furthermore, multivariate adaptive regression spline (MARS) and MT tree model (M5T) methods are used for comparison. The results indicated that the input combination of discharge data at the current time and one, two, and three previous days has the best performance for all models. Also, the support vector machine-genetic algorithm (SVM-GA) model has a lower root mean square error (RMSE) and mean absolute error (MAE) compared to the MARS and M5T models for both stations. In addition, comparing observational data with simulation data based on the R2 coefficient suggested that the SVM-GA model offers more accurate results than the other two methods. Accordingly, the SVM-GA method used in this study has a high potential for simulating sediment volume.
[en] In this study, the Load ESTimator (LOADEST) and eight-parameter regression models were evaluated to estimate instantaneous pollutant loads under various criteria and optimization methods. As shown in the results, LOADEST, commonly used in interpolating pollutant loads, could not necessarily provide the best results with the automatically selected regression model. The various regression models in LOADEST need to be considered to find the best solution based on the characteristics of watersheds. The recently developed eight-parameter model integrated with a genetic algorithm (GA) and the gradient descent method (GDM) was also compared with LOADEST, indicating that the eight-parameter model performed better than LOADEST; however, depending on whether the eight-parameter model was used for calibration or validation, its performance varied. The eight-parameter model with GDM could reproduce the nitrogen loads properly outside the calibration period (validation). Furthermore, the accuracy and precision of model estimations were evaluated using various criteria (e.g., R2, gradient, and constant of a linear regression line). The results showed higher precisions with the R2 values close to 1.0 in LOADEST and better accuracy with the constants (in linear regression line) close to 0.0 in the eight-parameter model with GDM. Hence, on the basis of these findings, we recommend that users need to evaluate the regression models under various criteria and calibration methods to ensure more accurate and precise results for nitrogen load estimations.
[en] water erosion is a complicated phenomenon, largely obvious in north Africa, especially in the watershed of Siliana, where natural factors and the aggressiveness of the environment do affect the loss of soil there, which characterized by a form so uneven with attitudes that vary from 700 to 1350 m rigid going from 5 to 10 pour cent and sometimes more. Moreover, it has drained with a thick hydrographic network. Generally, water erosion depends of the importance and the frequent agent factor of this erosion ( rain and streaming), soil type, the topography and the occupation of soil. The usage of mathematic models has to take on consideration of these parameters. The main objective of this work consist in developing put into affect a geomatic approach of stimulation which aims at estimate in time and space, the impact of the climate, and the soil occupation on the water erosion and the transportation of the sediments diversions into sliding of a small watershed. Locally, this approach allows evaluating the parameters of water erosion of SEAGIS model (USLE/RUSLE) to an extent that is identifies and drowing the emergency areas of intervention in the watershed of Siliana.
[en] The watershed basins with a plain system has been recognized as the factors which has direct effect on environment and human life. The beginning source of disturbing natural basins is where the unnecessary demands appears. Because of increasing demand for food in future, there fore, with increasing destruction on environment in world wide activity, on the other hand, it force use improving new technique and systems to over-come our demands. This reason seems to be enough for use to grow our activity through sustainable development of living sources. The present paper try to define and Explain the sustainable development and permanent stability base on general characteristics of Karkheh's watershed basin
[en] Rainfall patterns have a potential impact on floods, and the accuracy of peak flow determinations can directly affect the accuracy of rainfall warning index values. Therefore, it is necessary to explore the impact of rainfall pattern on the uncertainty of rainfall warning index for a small watershed. Xiawan, in the small Peihe watershed in Henan Province, China, was used as a case study. Based on an analysis of rainfall characteristics, a fuzzy recognition method was used to identify common rainfall patterns in the study area, following which they were compared with the regional design rainfall pattern. Design rainstorm flood calculation and a water level/flow inversion method were used to analyze the rainfall warning indices for different rainfall patterns and to establish the relationship between rainfall patterns and the values of rainfall warning index. The results show that: (1) rainfall pattern has a major impact on rainfall warning index values, and the rationality of the rainfall pattern requires consideration. (2) Deviations in peak flow between different rainfall patterns were large, and the timing of peak rainfall had a considerable influence on peak flood flow; (3) within the same early warning time interval, the rainfall warning indices where the timing of peak rainfall was at the start and in middle of the event were 1.67 times and 1.39 times that where rainfall peaked at the end, respectively. Further study of the rainfall pattern and its impact on rainfall warning index can provide technical support and an empirical reference value for the analysis and calculation of early warning indices for flash flood events in small watersheds.
[en] Twenty selected watersheds were divided into five small watershed sets according to location in Liaoning Province (LN), China. Watersheds and slopes were extracted from a 1:50,000 DEM, and gully data for each watershed were obtained by remote sensing interpretation. The gullies and associated slopes within the small watersheds were identified, and the distributions of gully density, proportion of dissected land, and gully length-width ratio in each small LN watershed and in the five small watershed sets were obtained. The correlations between the small watershed sets and the gully distributions throughout LN demonstrate regional distribution differences, and the watershed area has a great influence on both the area and length of gullies. Regional differences are present in the gully density and the proportion of dissected land in the small watersheds. The distribution of gullies with respect to slope depends on both the gully parameters and the proportion of terrain in the different slope grade ranges. The distribution results for the five small watershed sets are similar to those from a census of the Liaoning-Around Bohai mountainous and hilly sub-region. The gully density and proportion of dissected land in LN showed a single-peak curve with respect to slope, with slope thresholds of 8° and 5°, respectively. The constructed distribution equation has a high degree of fit. The comprehensive distributions of gully density, proportion of dissected land, and length-width ratio with slope indicate that gully erosion in LN is serious within the slope range of 3~8°.