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The transboundary Sesan and Srepok sub-basins (2S) are the “hot-spot” areas for reservoir development in the Lower Mekong region, with 12 reservoirs built in the Vietnam territory. This study examines the impacts of reservoir operations in Vietnam and projected climate change on the downstream hydrologic regime of the 2S Rivers by jointly applying the Soil Water Assessment Tool (SWAT) and Water Evaluation and Planning (WEAP) models. Different scenarios of reservoir operation are considered and simulated to assess their impact on annual, seasonal, and monthly flow regimes under maximum hydropower capacity generation with and without taking into account the minimum flow requirement downstream near the Vietnam border with Cambodia. The precipitation and temperature projections from the high-resolution regional climate model HadGEM3-RA under two Representative Concentration Pathways, 4.5 and 8.5, of HadGEM2-AO are used as future climate change scenarios for the impact assessment. The study results show that reservoir operation leads to an increase in the dry season stream flows and a decrease in the wet season stream flows. The monthly flow regime exhibits considerable changes for both the Sesan and Srepok Rivers but with different magnitudes and patterns of increase and decrease. Climate change is likely to induce considerable changes in stream flows, though these changes are comparatively lower than those caused by reservoir operation. Climate change is likely to have both counterbalancing and reinforcing effects over the impact of reservoir operation, reducing changes during dry season but increasing changes in most of the other months. 相似文献
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Drought events are increasing worldwide. Socio-economic drought is the least investigated type of drought, and is the only type for which water demand is taken into consideration. In this research, socio-economic drought was studied in Lake Mead, USA, using a multivariate standardized water-scarcity index (MSWSI) over the period 1990–2014, combining two water-scarcity indices based on time series of inflow, outflow, reservoir storage, and water demand. The inflow and outflow were determined from streamgage data, and reservoir storage from lake level data; demand was based on water pumped by the Southern Nevada Water Authority. Missing observations in input streamgage data were filled through regression modeling. The results indicate that Lake Mead has been in socio-economic drought since 2000, with the most severe drought occurring between 2006 and 2012, and the highest intensity drought in April–July 2014. The Lake Mead droughts revealed through the MSWSI are consistent with those reported in US Drought Monitor (USDM) products. The temporal behavior of MSWSI provides an insight into the socio-economic effects of droughts not captured by USDM products. 相似文献
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Aditi Kulshrestha Deewan Singh Bisht Jamson Masih David Massey Suresh Tiwari Ajay Taneja 《Journal of Atmospheric Chemistry》2009,62(2):121-138
This paper deals with the atmospheric concentrations of PM5 and PM2.5 particulate matter and its water soluble constituents along with the size distribution of ions and spatial variation at three
different residential environments in a semiarid region in India. Samples were collected from the indoors and outdoors of
urban, rural and roadside sites of Agra during October 2007–March 2008. The mean concentrations of PM2.5 indoors and outdoors were 178 μgm−3 and 195 μgm−3 while the mean concentrations of PM5 indoors and outdoors were 231.8 μgm−3 and 265.2 μgm−3 respectively. Out of the total aerosol mass, water soluble constituents contributed an average of 80% (33% anions, 50% cations)
in PM5 and 70% (29% anions, 43% cations) in PM2.5. The indoor–outdoor ratio of water soluble components suggested additional aerosol indoor sources at rural and roadside sites.
Indoor–outdoor correlations were also determined which show poor relationships among concentrations of aerosol ions at all
three sites. Univariate Pearson correlation coefficients among water soluble aerosols were determined to evaluate the relationship
between aerosol ions in indoor and outdoor air. 相似文献
4.
This paper examines trends in streamflow and their links with local climate in the Karkheh River and its major tributaries,
which originate from the Zagros Mountains, Iran. Streamflow records from five mainstream stations for the period 1961–2001
were used to examine trends in a number of streamflow variables. The studied variables were mean annual and monthly flows,
1 and 7 days maximum and minimum flows, timing of the 1-day maxima and minima, and the number and duration of high and low
flow pulses. Similarly, the precipitation and temperature data from seven climate stations for the period from 1950s to 2003
were used to examine trends in climatic variables and their correlation with the streamflow. The Spearman Rank test was used
for the detection of trends and the correlation analysis was based on the Pearson method. The results reveal a number of significant
trends in streamflow variables both increasing (e.g. December flows) and decreasing (e.g. May flows) for all stations. However,
some trends were not spatially uniform. For example, decline in low flow characteristics were more significant in the upper
parts of the basin, whereas increasing trends in floods and winter flows were noteworthy in the middle parts of the basin.
Most of these trends could be attributed to precipitation changes. The results show that the decline in April and May precipitation
causes the decline in the low flows while the increase in winter (particularly March) precipitation coupled with temperature
changes lead to increase in the flood regime. The observed trends at the Jelogir station on the Karkheh River reflect the
combined effect of the upstream catchments. The significant trends observed in a number of streamflow variables at Jelogir,
1-day maximum, December flow and low pulse count and duration, point to the changes in hydrological regime of the entire Karkheh
River system and are attributed to the changes in climatic variables. 相似文献
5.
Hydrograph separation using tracers and digital filters to quantify runoff components in a semi‐arid mesoscale catchment 
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下载免费PDF全文 Aline Maraci Lopes Saraiva Okello Stefan Uhlenbrook Graham P.W. Jewitt Ilyas Masih Edward Sebastian Riddell Pieter Van der Zaag 《水文研究》2018,32(10):1334-1350
Chemical hydrograph separation using electrical conductivity and digital filters is applied to quantify runoff components in the 1,640 km2 semi‐arid Kaap River catchment and its subcatchments in South Africa. A rich data set of weekly to monthly water quality data ranging from 1978 to 2012 (450 to 940 samples per site) was analysed at 4 sampling locations in the catchment. The data were routinely collected by South Africa's national Department of Water and Sanitation, using standard sampling procedures. Chemical hydrograph separation using electrical conductivity (EC) as a tracer was used as reference and a recursive digital filter was then calibrated for the catchment. Results of the two‐component hydrograph separation indicate the dominance of baseflow in the low flow regime, with a contribution of about 90% of total flow; however, during the wet season, baseflow accounts for 50% of total flow. The digital filter parameters were very sensitive and required calibration, using chemical hydrograph separation as a reference. Calibrated baseflow estimates ranged from 40% of total flow at the catchment outlet to 70% in the tributaries. The study demonstrates that routinely monitored water quality data, especially EC, can be used as a meaningful tracer, which could also aid in the calibration of a digital filter method and reduce uncertainty of estimated flow components. This information enhances our understanding of how baseflow is generated and contributed to streamflow throughout the year, which can aid in quantification of environmental flows, as well as to better parameterize hydrological models used for water resources planning and management. Baseflow estimates can also be useful for groundwater and water quality management. 相似文献
6.
Hourly air temperature driven using multi-layer perceptron and radial basis function networks in arid and semi-arid regions 总被引：2，自引：0，他引：2
Mehdi Rezaeian-Zadeh Shahrookh Zand-Parsa Hirad Abghari Masih Zolghadr Vijay P. Singh 《Theoretical and Applied Climatology》2012,109(3-4):519-528
This study employed two artificial neural network (ANN) models, including multi-layer perceptron (MLP) and radial basis function (RBF), as data-driven methods of hourly air temperature at three meteorological stations in Fars province, Iran. MLP was optimized using the Levenberg–Marquardt (MLP_LM) training algorithm with a tangent sigmoid transfer function. Both time series (TS) and randomized (RZ) data were used for training and testing of ANNs. Daily maximum and minimum air temperatures (MM) and antecedent daily maximum and minimum air temperatures (AMM) constituted the input for ANNs. The ANN models were evaluated using the root mean square error (RMSE), the coefficient of determination (R 2) and the mean absolute error. The use of AMM led to a more accurate estimation of hourly temperature compared with the use of MM. The MLP-ANN seemed to have a higher estimation efficiency than the RBF ANN. Furthermore, the ANN testing using randomized data showed more accurate estimation. The RMSE values for MLP with RZ data using daily maximum and minimum air temperatures for testing phase were equal to 1.2°C, 1.8°C, and 1.7°C, respectively, at Arsanjan, Bajgah, and Kooshkak stations. The results of this study showed that hourly air temperature driven using ANNs (proposed models) had less error than the empirical equation. 相似文献
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