watershed
Karim Solaimani; Seyedhossien Alavi; Fatemeh Shokrian; Esmaeil Mokhtarpour
Abstract
This study investigated the trend of hydroclimate parameters of the Miankaleh wetland using the Mann-Kendall test and Sen slope estimator. Temperature, precipitation, and evaporation parameters were used from the synoptic stations . Also, the discharge data were used from the hydrometric stations of ...
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This study investigated the trend of hydroclimate parameters of the Miankaleh wetland using the Mann-Kendall test and Sen slope estimator. Temperature, precipitation, and evaporation parameters were used from the synoptic stations . Also, the discharge data were used from the hydrometric stations of Khalil Mahalleh, Tazeh Abad, Baghoo, and Vatana stations. The results of the Mann-Kendall test showed that the temperature in the Dashte-Naz station in spring and summer seasons has a significant increasing trend with 95% confidence and a significant decreasing trend in winter. Also, there is an increasing trend in Hashem Abad station, with a 95% confidence level in the spring and autumn seasons. Precipitation in Dashte-Naz station with a 95% confidence level has a decreasing and increasing trend, respectively. The most frequent trend changes in Dubai are related to Vatana station, which has a decreasing trend on an annual scale. Evaporation in Dashte-Naz station has a decreasing trend in the autumn and winter seasons and has an increasing trend in spring. Also, in Hashem Abad station, the evaporation rate in autumn has a decreasing trend. The Sen slope estimator method results showed that precipitation in Dashte-Naz station in December was -2.983, and on the annual scale, it is related to Hashem Abad station with -6.283. The highest monthly positive trend line slope of all parameters is related to August precipitation in Dashte- Naz station with a value of 3.20, and the highest annual scale is related to evaporation in Hashem Abad station with a value of 2.157.
Alireza Donyaii; Amirpouya Sarraf
Abstract
1- Introduction Climate evolutionary theory reveals that climate change has already been evident in the planet's history, but when opposed to historical climate changes, the climatic changes of the last century have two unique characteristics. First, through the nature of the ongoing climate change, ...
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1- Introduction Climate evolutionary theory reveals that climate change has already been evident in the planet's history, but when opposed to historical climate changes, the climatic changes of the last century have two unique characteristics. First, through the nature of the ongoing climate change, human actions play a significant role Second; the speed of recent climatic changes is greater, so that, many changes will be occurring in the Earth's atmosphere during a short term [Telmer et al. 2004]. Nowadays, global warming has significant effects on precipitation and runoff yield and water resources due to the increased concentration of greenhouse gases [Donyaii et al. 2020]. The average meteorological parameters, in particular the annual or seasonal components of temperature, precipitation and runoff, play a significant role in the hydrological cycle and are typically used as an indicator for climate change evaluation on the water supplies available to Iran now and particularly in the future [Donyaii et al. 2020]. Based on the IPCC Fourth Assessment Report Models [AR4], a number of studies have been undertaken to examine the effect of climate change on the hydrological components of watersheds in Iran. In contrast with the Fifth Assessment Study [AR5] models, these models, along with older pollution scenarios, have limited resolution. Therefore, in the watersheds of Iran, climate change experiments with higher resolution climate models under the latest pollution scenarios [RCPs] of the AR5 seem appropriate. According to historical evidence of Gorganroud's high flood capacity in the province of Golestan, Iran, the recognition of the impact of climate change on the watershed's hydrological regime is important for water resource planners. 2- Methodology 2-1- Study area and data set The Gorganroud Watershed is located in Golestan Province, Iran. In this study, the Soil and Water Assessment Tool [SWAT] was employed for hydrological simulation of the watershed based on the downscaled outputs [using the Bias Correction and Spatial Disaggregation [BCSD] method] of fifth assessment report climate change model [MIROC-ESM] for historical and future periods. The trend analysis of hydro-climatic records was done according to the non-parametric Mann-Kendall test. The future projection was conducted for the near [2025-2050], mid [2051-2075], and far [2075-2100] future periods related to historical records in the period of 1985-2005. 2-2- SWAT set-up and calibration, validation and uncertainty analysis In this study, runoff was estimated using the Soil Conservation Service [SCS] method. The Manning equation and Muskingum method were utilized to calculate flow velocity and routing phase, respectively. On the other hand, the SUFI-2 algorithm was employed to calibrate and analyze the sensitivity, and uncertainty of the SWAT model. The sensitivity analysis is based on linear approximation and the degree of uncertainty is calculated by two factors called r-factor and P-factor. The calibration and validation were performed using runoff data in the periods of 1995-2015 and 2016-2019, respectively. The coefficients of determination [R2] and Nash-Sutcliffe [NS] were used as the objective function to determine the goodness of fitness. 2-3- Climate Change scenarios and AR models In the AR5 new emission scenarios based on emission forcing level until 2100 were employed. In order to investigate the future climate change, the Model for Interdisciplinary Research on Climate-Earth System Models [MIROC-ESM] was selected among the newest extracted models presented in the AR5, because the result of this model in Gorganroud watershed showed the highest agreement with observational data. This model consists of four emission forcing scenarios [RCP2.6, RCP.4.5, RCP6.0 and RCP8.5. 3- Results and Discussion 3-1- SWAT sensitivity analysis, calibration and validation analysis Seventeen parameters were chosen for SWAT sensitivity analysis using the 500 simulations of SUFI-2. Results showed that the parameters CN, SOL_BD and SOL_K have the highest relative sensitivity. Based on the results, the coefficients R2 and NS for runoff simulation were estimated to be 0.79-0.77 and 0.74-0.71 in the calibration and validation stage, respectively. Therefore, the results of the model are acceptable and its uncertainty metrics is satisfactory in general. The study results showed that the model has estimated the amount of peak discharge less than the actual amounts, which is confirmed by the average monthly simulated discharge during calibration and validation periods. The results also showed that more than 50% of the observational data in both calibration and validation phases are bracketed by the 95PPU uncertainty estimation band, which indicate a rather acceptable degree of certainty in simulation. 3-2- Climate change simulation results and trend analysis In the near and mid-future, there are increasing changes under the RCP2.6 scenario, but the trends of rainfall are not statistically significant at the 5% level. In the far- future a significant increasing trend is observed under the RCP2.6 scenario, meanwhile in far-future under the RCP4.5 scenario there are increasing changes, but the trends are not statistically significant. In the mid and far future under the RCP6.0 scenario, a significant increasing trend has been observed. Finally, in the mid- future under the RCP8.5 scenario, there is a significant increasing trend. However, the increasing changes in the near and far-future periods are not statistically significant at the confidence level of 95%. The trend analysis of variables indicates that the amount of rainfall will decrease in this watershed during the future periods by the end of the 21st century. The most decreasing alterations in the rainfall and the highest increase in the temperature are achieved under the highest concentration of greenhouse gases [RCP8.5]. Moreover, in the near, mid, and far future, the runoff changes are decreasing under the RCP2.6 scenario, but the trend is not statistically significant. In the mid and far-future periods under the RCP4.5 scenario, there is a statistical significant decreasing trend in runoff; however, the decreasing variation in the near future is not significant. In the near, mid, and far future under the RCP6.0, runoff variations are declining, but the trend is not statistically significant. In the far-future period, under the RCP8.5, there is a significant decreasing trend; however, in the near and mid-future, runoff declining changes are not statistically significant. Reduced rainfall and increased temperature in the watershed will reduce the rate of runoff in the future periods in such a way that the security of the inhabitants of the region will be severely affected. 4- Conclusions Results of evaluation criteria [R2 and NS] showed that the SWAT performance for the simulation of runoff in the Gorganroud watershed was not satisfactory, but it was in an acceptable range. Climate change simulation indicated a decreasing trend for rainfall in all future periods, but this trend was not statistically significant. The temperature variable in all RCPs had an increasing trend. However, temperature trend analysis under the RCP4.5 scenario during the near and mid- future and under the RCP6.0 scenario during the near, mid, and far-future showed a significant upward trend. Runoff under the RCP4.5 scenario during the mid to far-future and under the RCP8.5 scenario during the far-future period followed a significant downward trend. Runoff during the near-future period under the RCP4.5 scenario and throughout the near to mid-future under the RCP8.5 scenario, had declining variations, but its trend was not statistically significant. In general, these results indicated that the amount of temperature will follow an increasing tendency; while rainfall and runoff will follow a decreasing movement in this watershed by the end of the 21st century.
soghra andaryani; Vahid Nourani
Abstract
1-IntroductionMining industry has almost negative and destructive effects on the environment and ecosystems of regions and can affect the health of humans and other living organisms including animals, plants, soil, water, and the entire biosystem of the region on a local and regional scale.2-MethodologyThe ...
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1-IntroductionMining industry has almost negative and destructive effects on the environment and ecosystems of regions and can affect the health of humans and other living organisms including animals, plants, soil, water, and the entire biosystem of the region on a local and regional scale.2-MethodologyThe study area is located in East Azerbaijan and it belongs to the sub-basins of the western part of the Aras Basin.2.1-DataLandsat 5, 8 data available in July (1984-2019), monthly and annually value of temperature and precipitation data (1998-2017) in Varzeqan station.2.2-Method In the present study, land-cover density using Normalized Differential vegetation Index (NDVI) was extracted from satellite imagery of Landsat (Thematic Mapper and Operational Land Imager) as time series for the period of June 1984-2019. 27 images were analyzed after correction and NDVI extraction. See question 1: (1)Where, NIR is reflectance value of near infrared and RED is reflectance value of red band.To determine the trend in vegetation, first, the land-cover density extracted from satellite images were pre-whited in time series and then the trend analysis was done by Mann-Kendall (MK) method in each of the pixels, and also beginning of the trends were analyzed by Mann-Kendall sequence (SMK) in per case studies. SMK was used in MATLAB software (Ye et al., 2013; Moraes et al., 1998). 3-Results and DiscussionThe average values of land-cover in all three case studies (i.e., case 1, case 2, and case 3) have increased in the period 1984-2019 and have almost had the same fluctuations over the period under study. Therefore, that linear regression was derived between the land-cover of cases 1 and 2, 1 and 3, and finally 2 and 3 with the average correlation coefficient of 96%, 96%, and 98%, respectively. The highest vegetation peak was in 1992, 2004, 2013, and 2018 to 2019, however, such an increase in the average occurred in all three study units. The peak of average land-cover density in different years is consistent with the peak of precipitation and decrease in temperature on an annual scale. According to the results, in studying the trend of vegetation changes, it is not possible to generalize the numerical average of vegetation for the whole region or analyze the trend. By emphasizing this result in each of the pixels as a time series, trend analysis was performed by MK method. Case 1 experienced the most fluctuation and case 3 (downstream of the mined area) experienced the least fluctuation trends. The significant decreasing trend in both levels of reliability, 95% and 99% has the highest level of the mining area (Fig. 1). Fig. (1): Classification of trend analysis at 95% and 99% confidence levels, (a) case 1, (b) case 2 and (c) case 3. Figures 1-3, which have been resulted from Fig. 6 (a), indicate areas with significant decrease. Figs. 1 and 2 are the mining areas and Fig. 3 is the Andaryan village0.48% of the case 1 area is under the significant decreasing trend, which is 0.18% and 0.22% in case 2 and 3, respectively. Therefore, there is a significant decrease in all three case studies. Approximately, 5%, 2%, and 3% of the area of cases 1, 2, and 3 have a decreasing trend, respectively. The percentage of areas with a significant increasing trend at both 95% and 99% confidence levels are equal to 35.5%, 54%, and 36.5% for each of the 1-3 case studies, respectively. According to Varzeqan station data, these areas have received good rainfall in the last decade, so the area of vegetation has increased significantly. The existence of 88% correlation between the area where the mining took place and the area that is untouched in terms of exploration operations shows the insignificant impact of exploration operations and smelting services on the vegetation of the area. Although most of land-cover of about 51 hectares has been lost due to road construction on steep slopes for mining and smelting services, based on sustainable development goals, the affected vegetation can be restored to the original state and at the same time to make the best use of existing minerals and consider future generations (Thenepalli et al., 2019). 4- ConclusionThe results show fluctuations in land-cover density; however, in general, high dense areas in terms of vegetation are observed in all three areas. The case studies 1- 2, 1 - 3, and 2 -3 have a correlation of 96%, 96%, and 98% with each other, respectively. Therefore, using the Mann- Kendall statistical model, NDVI values were analyzed pixel by pixel as a time series. The results show a significant decrease in the vegetation of regions 1-3 equal to 0.48%, 0.19% of the area in all three regions, respectively. The results of the Mann-Kendall sequence and correlation in the areas with a significant reduction in vegetation and the considered various hypotheses showed no chemical leakage to downstream of the basin.Keywords: Impact of mining, Land-cover, NDVI, Mann-Kendall Test, Varzegan, Northwestern Iran 5-References Ye, X., Zhang, Q., Liu, J., Li, X., & Xu, C.Y. (2013). Distinguishing the relative impacts of climate change and human activities on variation of streamflow in the Poyang Lake catchment, China. Journal of Hydrology, 494, 83–95.Moraes, J.M., Pellegrino, H.Q., Ballester, M.V., Martinelli, L.A., Victoria, R.L., & Krusche, A.V. (1998). Trends in hydrological parameters of southern Brazilian watershed and its relation to human induced changes. Water Resources Management, 12, 295–311.Thenepalli, T., Chilakala, R., Habte, L., Quang Tuan, L., & Sik Kim, C. (2019). A Brief Note on the Heap Leaching Technologies for the Recovery of Valuable Metals. Sustainability, 11, 334.
Khadijeh Haji; Shahnaz Mirzaei; Raoof Mostafazadeh; Habib Nazarnejad
Volume 4, Issue 13 , March 2018, , Pages 121-146
Abstract
Extended Abstract
Considering the relative stability of the physical characteristics of a watershed, the variability of the precipitation over space and time, and the direct relationship between rainfall and runoff, the variations of runoff can be expected and analyzed to understand the nature of variability. ...
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Extended Abstract
Considering the relative stability of the physical characteristics of a watershed, the variability of the precipitation over space and time, and the direct relationship between rainfall and runoff, the variations of runoff can be expected and analyzed to understand the nature of variability. Determining changes in the amount of runoff caused by rainfall and detecting the time of rivers' floods can provide a prediction of floods' occurrence and, consequently, reduce their damages. The increasing importance of water resources management in recent years, erosion, and sediment highlights the need for understanding the rivers' behavior and regimes. Regarding the changes in the river flow rate, estimating temporal and spatial variations of runoff changes can be effective in determining and controlling the dependent processes of soil erosion in a watershed and river bank, droughts, floods, and water quality and utilization. The analysis of the river flow variability, its duration and influencing factors, is necessary for an optimal river management/operation as the main sources of water uses.
Methodology
The monthly and annual runoff volumes of different stations were calculated based on the monthly discharge data in different years during the study period. Then, the variability indices were used to study the seasonal variations in the runoff volume at each hydrometric station. Next, using Annual Distribution of Regulating Coefficient and Concentration Rate indices, the seasonal variation in runoff volume of twenty river gauge stations located in Golestan Province were evaluated in 38 years. The values of Annual Distribution of Regulating Coefficient indicated the uniformity/ non-uniformity of changes in runoff volume at the studied river gauge stations. In addition, the annual variation of runoff volume was plotted in triple diagram models based on average runoff volume and time variables. The Kriging method was also used to draw the triple diagram models using two independent variables in a surfer environment. The Annual Distribution of Regulating Coefficient and Concentration Rate indices were considered as dependent variables. The variability of the implemented indices were analyzed over a time period of 38 years.
Results and Discussion
According to discharge data in different years, the monthly and annual runoff volumes of the stations were calculated during the study period. Based on the monthly spatial distribution, the results showed that the maximum amount of runoff volume of the stations were observed in March. The highest amount of surface runoff amounts occurred in Aghghala, Ghazagli, and Basirabad which respectively had an average annual runoff of 33.9, 33.5, and 32.6 million cubic meters. The highest uniformity in runoff occurrence was related to Nodehkhandoz, Tamar, Galikesh, and Gholitappeh stations, respectively with an annual Distribution of Regulating Coefficient of 0.19, 0.21, 0.23, and 0.24. The lowest Rate of runoff concentration was at Nodehkhandoz and Tamar stations respectively with 0.26% and 0.25%. The results also indicated a direct and significant relationship (R2 = 0.60) between Annual Distribution of Regulating Coefficient and Concentration Rate (p < .05). Ramian station had the highest Concentration Rate with a value of 0.62%. The highest significant decreasing and increasing trends, in Mann-Kendall test, were observed at Shirabad and Nodehkhandoz stations
Conclusions
According to the findings, there was a correlation between the annual distribution of regulating coefficient and the concentration rate. The higher values of the Annual Distribution of Regulating Coefficient and the Concentration Rate of runoff volume can be attributed to physiographic properties of watershed such as its slope, vegetation, and soil permeability. In other words, the process of changes in the runoff volume at these stations can indicate the temporal and spatial variations of precipitation, human protection measures such as dam construction in the basin, or the amount of permeability during the statistical period. In conclusion, with the non-uniform distribution of runoff volume in different months of the year, it can be expected that variations between the minimum and maximum values of runoff volume will also be high. Indeed, the higher the uniformity of the monthly distribution of runoff volume, the lower the variations between the minimum and maximum changes in the runoff volume. Variations in the amount of monthly runoff in the studied area can be related to the characteristics of the area, the hydrological response, and land use (agricultural land plowing season), as one of the main factors controlling runoff.
Vahid Nourani; Narges Azad; Mahsa Ghasemzade; Elnaz Sharghi
Volume 3, Issue 7 , October 2016, , Pages 141-159
Abstract
Vahid Nourani[1] Narges Azad*[2] Mahsa Ghasemzade[3] Elnaz Sharghi[4] Abstract This paper aims to detect trends and investigate the relationship between long-term time series of the Urmia lake water level and other hydro-climatologic parameters, including precipitation, runoff, temperature and relative ...
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Vahid Nourani[1] Narges Azad*[2] Mahsa Ghasemzade[3] Elnaz Sharghi[4] Abstract This paper aims to detect trends and investigate the relationship between long-term time series of the Urmia lake water level and other hydro-climatologic parameters, including precipitation, runoff, temperature and relative humidity, in monthly, seasonal and annual scales using Mann-Kendall (MK) and discrete wavelet transform (DWT). The MK test and sequential MK analysis were applied to different combinations of DWT to calculate components responsible for trend of time series.The results showed that 8-month period was important in the involved trend at the original monthly time series. Also there is a significant negative trend in different scales of lake water levels and runoff time series. In general, rainfall, relative humidity and temperature time series did not show significant trends.The results of this research indicate that downward trend in the rainfall time series has more effective role in Urmia lake drying. In addition, the sequential MK test was used to find the start points of changes in monthly time series. The results showed a significant decreasing trend from 1377 in the lake water level and runoff time series. Finally, the results of Sen’s trend analysis, also confirmed the results of the proposed wavelet-based MK test. [1]- Professor of Water Resources Engineering. [2]- Master Degree Student of Water Resources Engineering (Corresponding Author), Email:narges.azad1991@gamil.com [3]- Master Degree Student of Water Resources Engineering. [4]- Assistant Professor of Water Resources Engineering Department of Water Resources Engineering Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran.
