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Climate Change Impact on the Tuul River Flow in a Semiarid Region in Mongolia
Sukhbaatar, Chinzorig,Sajjad, Raja Umer,Lunten, Janchivdorj,Yu, Seung-Hoon,Lee, Chang-Hee Wiley (John WileySons) 2017 Water environment research Vol.89 No.6
<P>This study investigated the impact of climate change on the Tuul River flow in a semiarid region in Mongolia using statistical methods and the Soil and Water Assessment Tool (SWAT). The authors found that the precipitation showed cyclic variability (three dry and two wet periods) at inter-and multi-decadal scales throughout the study period (1945-2012). Both river flow and actual evapotranspiration (ET) showed a positive relationship with precipitation. In addition, the river flow further decreased due to increased water loss in percentage via actual ET even though the amount of actual ET decreased during dry periods. A significant increase in air temperature by 1.3 to 1.8 degrees C was recorded during latest dry period (1996-2012). Increase in temperature resulted in an added stressor, where water loss in percentage via actual ET increased more and resulted in an additional decrease in the river flow. This study concluded that precipitation has a stronger influence on the Tuul River flow than temperature.</P>
Application of neural network for stormwater runoff classification from mix landuse site
( Sheeraz Memon ),( Ma. Cristina Paule ),( Raja Umer Sajjad ),( Imran Saleem ),( Seung-hoon Yu ),( Bum-yeon Lee ),( Chinzorig Sukhbaatar ),( Chang-hee Lee ) 한국물환경학회(구 한국수질보전학회) 2015 한국물환경학회·대한상하수도학회 공동 춘계학술발표회 Vol.2015 No.-
Predictive models play an important part in storm water monitoring due to impact on receiving waters and high cost for data collection. In this study, a neural network approach was used to characterize large amount of stormwater data from an outlet of multiple landuse sites including urban and construction in Korea. Out of total 400 data samples, 85% of the data was used for training the network while remaining 15% was used to test the model which is 1/7th of randomly data samples. An attempt was made using coefficient of determination and average relative error values to develop optimized network model. The results revealed that R2 for both estimation and validation varied significantly on different nodes configurations, whereas least generated average relative error for all output constituents were exhibited in the 8 hidden neurons configuration and therefore it was selected for further classification and comparison. The model performance was compared with multiple linear regression model results using R2 values and Nash coefficient. From the results, it was observed that ANN model produced better results because values of MLR were low for all of the constituents. From the findings, it can be suggested that neural network can be used for stormwater quality data.
하수도 시스템 유무에 따른 강우유출특성 분석 - 팔당호 유역을 대상으로
강동한 ( Dong Han Kang ),라자우말사자드 ( Umer Sajjad Raja ),김극태 ( Keuktae Kim ),이창희 ( Chang Hee Lee ) 한국물환경학회(구 한국수질보전학회) 2016 한국물환경학회지 Vol.32 No.2
토지이용이 혼재되고 하수관거 시스템이 미흡한 유역의 강우유출 특성을 파악하는 것은 매우 어렵다. 본 연구에서는 팔당호 유역에서 토지 이용 및 하수관거 형태에 따른 강우 유출 특성을 파악하고자 하였다. 이를 위해 팔당호유역 7개 시·군에서 공공 하수관거 시스템 지역 48개소, 개인하수처리시설 지역 28개소에 대한 강우 유출수 모니터링을 실시하였다. 개인하수처리시설 지역의 토지 이용은 산림과 논의 비율이 높았으며 SS, TN, TP EMCs와 초기세척 강도가 공공하수처리지역에 비해 높게 나타났다. 또한 초기강우 차집 시스템을 설치하여 초기강우 유출수 43%를 처리할 경우 59%의 TP 유출부하량을 저감할 수 있을 것으로 기대된다. 개인하수처리시설이 설치된 지역에서 강우량 및 강우지속시간과 영양염류 유출 부하량은 양의 상관관계 (R>0.6)를 나타내어 팔당호의 부영양화 문제를 관리하기 위해 개인하수처리지역에 대한 우선적 정책이 필요함을 알수 있다. The characterization of stormwater runoff from mix land-use catchments with an inadequate sewer network is a challenge. This study focused on characterizing stormwater runoff from the Paldang watershed area based on land-use type and sewer system coverage. A total of 76 sites were monitored during wet weather from seven different counties within Paldang watershed. Public sewer system (PSS) was installed at 48 sites, while 28 sites had no or individual sewer system (ISS) coverage. The results indicated that the sites included in the ISS group with higher forest and paddy land-use percentage exhibit higher values of average event mean concentrations (EMCs) and first flush intensity for suspended solids (SS), total nitrogen (TN), and total phosphorous (TP). In addition, upgrading runoff interception system can capture 59 % of the TP load in the first 43% of runoff within these sites. Similarly, rainfall depth and storm duration showed a positive correlation (R > 0.6) with nutrient loads within ISS group sites, as compared to PSS group. Therefore, these sites are likely to contribute higher TP and TN loads during heavier storm events and should be selected as priority management areas to combat the problem of eutrophication in Paldang reservoir.
Paule-Mercado, Ma. Cristina A.,Salim, Imran,Lee, Bum-Yeon,Memon, Sheeraz,Sajjad, Raja Umer,Sukhbaatar, Chinzorig,Lee, Chang-Hee Elsevier 2018 Ecological Indicators Vol.93 No.-
<P><B>Abstract</B></P> <P>Understanding the influence of land use and land cover (LULC) change in stormwater runoff is important for watershed management. In this study, integration of 31 storm events, monthly monitoring of LULC change, Pearson’s correlation, multiple linear regression analysis (MLR) and Personalized Computer Storm Water Management Model (PCSWMM) were applied to quantify the influence of LULC change on stormwater quality from mixed LULC catchment with ongoing land development in Yongin, South Korea. Due to ongoing land development in the catchment, bare land and urban LULC were exponentially increased while agriculture, forest, grassland and water LULC decreased in spatial extent. The correlation analysis showed that stormwater quality was positively correlated to bare land (0.595; Cl – 0.891; TSS, <I>p</I> < 0.05) and urban (0.768; TN – 0.987; TSS, <I>p</I> < 0.05); negatively correlated to forest (−0.593; Cu – 0.532; BOD<SUB>5</SUB>, <I>p</I> < 0.05) and grassland (−0.587; TSS – 0.512; BOD<SUB>5</SUB>, <I>p</I> < 0.05) and; either positively or no correlation to agriculture (0.064; Cu – 0.871; TSS, <I>p</I> < 0.05) and water (−0.131; Cl – 0.221; TP, <I>p</I> < 0.05). Furthermore, the MLR analysis showed that combinations of different LULC were able to describe the overall stormwater quality of the catchment. Moreover, the LULC scenario analysis demonstrate that under dominant agriculture (S1), bare land (S2) and urban areas (S5), the average pollutant concentrations would increase by as much as 13.22% (Cl; S2; pre-) to 59.25% (TSS; S5; early-active); while under dominant forest (S3) and grassland (S4) the average pollutant concentration would decrease by as much as −53% (Pb; S3; late-active) to −3.22% (BOD<SUB>5</SUB>; S4; pre-). These findings explained that the variability of pollutant concentrations in different phase of land development was affected by expansion of bare land and urban spatial extent, increase of hydrological characteristics (total rainfall and average rainfall intensity) and massive soil activities (soil digging and soil transfer). Therefore, results of this study will provide scientific information to establish a cost-effective stormwater management, development of empirical model, and designing monitoring strategies and guidelines to minimize the negative impact of LULC change on stormwater runoff.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Long-term LULC and stormwater monitoring advanced the current watershed management. </LI> <LI> PCSWMM was used to evaluate the influence of land development on stormwater runoff. </LI> <LI> Land development influences the variability of pollutant concentration in runoff. </LI> <LI> Conversion of vegetation to bare land and urban is the major stormwater stressor. </LI> <LI> Expansion of vegetation cover was not enough to achieve the water quality criteria. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>