Modelling and Evaluation of the Effect of Afforestation on the Runoff Generation Within the Glinščica River Catchment (Central Slovenia)

2020 ◽  
Author(s):  
Gregor Johnen ◽  
Klaudija Sapač ◽  
Simon Rusjan ◽  
Vesna Zupanc ◽  
Andrej Vidmar ◽  
...  
Keyword(s):  
Runoff Generation ◽  
River Catchment ◽  
Central Slovenia

scholarly journals Comparing Statistical and Semi-Distributed Rainfall–Runoff Models for a Large Subtropical Watershed: A Case Study of Jiulong River Catchment, China

Atmosphere ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 62 ◽  
Author(s):  
XianXian Han ◽  
GaoYang Li ◽  
WenFang Lu ◽  
YuWu Jiang
Keyword(s):  
Ridge Regression ◽  
Partial Information ◽  
Type I ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
K Nearest Neighbor ◽  
Time Step ◽  
Jiulong River ◽  
River Catchment ◽  
Hspf Model

In this contribution, the authors present their preliminary investigations into modeling the rainfall–runoff generation relation in a large subtropical catchment (Jiulong River catchment) on the southeast coast of China. Previous studies have mostly focused on modeling the streamflow and water quality of its small rural subcatchments. However, daily runoff on the scale of the whole catchment has not been modeled before, and hourly runoff data are desirable for some oceanographic applications. Three methods are proposed for modeling streamflow using rainfall outputted by the Weather Research Forecast (WRF) model, calculated potential evaporation (PET), and land cover type: (i) a ridge regression model; (ii) NPRED-KNN: a nonparametric k-nearest neighbor model (KNN) employing a parameter selection method (NPRED) based on partial information coefficient; (iii) the Hydrological Simulation Program-Fortran (HSPF) model with an hourly time step. Results show that the NPRED-KNN approach is the most unsuitable method of those tested. The HSPF model was manually calibrated, and ridge regression performs no worse than HSPF based on daily verification, whilst HSPF can produce realist daily flow time series, of which ridge regression is incapable. The HSPF model seems less prone to systematic underprediction when replicating monthly-annual water balance, and it successfully replicates the baseflow index (the flow intensity) of the Jiulong River catchment system.

A Comparative Study of Different Hydrological Model and their Application in Little River Catchment

2014 ◽  
Vol 641-642 ◽  
pp. 9-13
Author(s):  
Shu Yan ◽  
Zhong Yuan Zhang ◽  
Feng Lin Zuo ◽  
Wei Hua Zhang
Keyword(s):  
Hydrological Model ◽  
Rainfall Runoff ◽  
Runoff Generation ◽  
Optimal Model ◽  
Humid Climate ◽  
Tank Model ◽  
Southeastern Usa ◽  
River Catchment ◽  
Total Runoff ◽  
Error Coefficient

Sacramento, SimHyd and Tank model were selected and their structure, principles and characteristics were briefly described. Then by taking Little River Catchment in Georgia, USA as an example, the rainfall-runoff process was simulated by using the Rainfall Runoff Library. The results showed that: Nash-Sutcliffe coefficient reached more than 80% and RE (relative error coefficient of the total runoff) of Sacramento model also meets the requirements. Considering the Sacramento model is the best one on the Nash-Sutcliffe coefficient, the model is selected as the optimal model of Little River Catchment in this study.As the catchment is located in the southeastern USA, with humid climate, and saturated storage-based runoff generation, which is similar to Chongqing region, it provides relatively good reference for Chongqing as well as the entire southwestern region.

Oxygen and deuterium isotope characteristics of Teesta river catchment from Sikkim Himalaya, India: Implications of different moisture sources

2020 ◽  
Vol 54 (5) ◽  
pp. 327-336
Author(s):  
Sheikh Nawaz Ali ◽  
Anupam Sharma ◽  
Shailesh Agrawal ◽  
M. G. Yadava ◽  
R. A. Jani ◽  
...  
Keyword(s):  
Sikkim Himalaya ◽  
River Catchment ◽  
Moisture Sources

SIMULATION AND CONTROL OF FLOODS IN A WATER NETWORK. CASE STUDY OF JIJIA RIVER CATCHMENT

2017 ◽  
Vol 16 (3) ◽  
pp. 587-595
Author(s):  
Vasile Mircea Cristea ◽  
Ph.m Thai Hoa ◽  
Mihai Mogos-Kirner ◽  
Csavdari Alexandra ◽  
Paul Serban Agachi
Keyword(s):  
Water Network ◽  
River Catchment ◽  
Simulation And Control ◽  
And Control

scholarly journals Effects of Soil and Water Conservation Measures on Soil Quality Indicators: The Case of Geshy Subcatchment, Gojeb River Catchment, Ethiopia

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Melku Dagnachew ◽  
Awdenegest Moges ◽  
Asfaw Kebede ◽  
Adane Abebe
Keyword(s):  
Soil Quality ◽  
Quality Indicators ◽  
Water Conservation ◽  
Soil And Water Conservation ◽  
Land Resources ◽  
Soil Quality Indicators ◽  
Volumetric Soil Water Content ◽  
River Catchment ◽  
The Status ◽  
Soil And Water

Land degradation is a global negative environmental process that causes the decline in the productivity of land resources’ capacity to perform their functions. Though soil and water conservation (SWC) technologies have been adopted in Geshy subcatchment, their effects on soil quality were limitedly studied. The study was conducted to evaluate the effects SWC measures on soil quality indicators in Geshy subcatchment, Gojeb River Catchment, Ethiopia. A total of 54 soil samples (two treatments–farmlands with and without SWC measures ∗ three slope classes ∗ three terrace positions ∗ three replications) were collected at a depth of 20 cm. Statistical differences in soil quality indicators were analyzed using multivariate analysis of variance (ANOVA) following the general linear model procedure of SPSS Version 20.0 for Windows. Means that exhibited significant differences were compared using Tukey’s honest significance difference at 5% probability level. The studied soils are characterized by low bulk density, slightly acidic with clay and clay loam texture. The results revealed that farmlands with SWC measures had significantly improved soil physical (silt and clay fractions, and volumetric soil water content (VSWC)) and chemical (pH, SOC, TN, C : N ratio, and Av. phosphorus) quality indicators as compared with farmlands without SWC measures. The significantly higher VSWC, clay, SOC, TN, C : N ratio, and Av. P at the bottom slope classes and terrace positions could be attributed to the erosion reduction and deposition effects of SWC measures. Generally, the status of the studied soils is low in SOC contents, TN, C : N ratio, and Av. P (deficient). Thus, integral use of both physical and biological SWC options and agronomic interventions would have paramount importance in improving soil quality for better agricultural production and productivity.

scholarly journals Spatial Variation of Water Chemistry in Aries River Catchment Western Romania

2021 ◽  
Vol 11 (14) ◽  
pp. 6592
Author(s):  
Ana Moldovan ◽  
Maria-Alexandra Hoaghia ◽  
Anamaria Iulia Török ◽  
Marius Roman ◽  
Ionut Cornel Mirea ◽  
...  
Keyword(s):  
Heavy Metals ◽  
Water Quality ◽  
Water Chemistry ◽  
Water Samples ◽  
Mine Drainage ◽  
Pollution Indices ◽  
Mining Activities ◽  
River Catchment ◽  
High Concentrations ◽  
The Impact

This study aims to investigate the quality and vulnerability of surface water (Aries River catchment) in order to identify the impact of past mining activities. For this purpose, the pollution and water quality indices, Piper and Durov plots, as well vulnerability modeling maps were used. The obtained results indicate that the water samples were contaminated with As, Fe, Mn, Pb and have relatively high concentrations of SO42−, HCO3−, TDS, Ca, K, Mg and high values for the electrical conductivity. Possible sources of the high content of chemicals could be the natural processes or the inputs of the mine drainage. Generally, according to the pollution indices, which were correlated to high concentrations of heavy metals, especially with Pb, Fe and Mn, the water samples were characterized by heavy metals pollution. The water quality index classified the studied water samples into five different classes of quality, namely: unsuitable for drinking, poor, medium, good and excellent quality. Similarly, medium, high and very high vulnerability classes were observed. The Durov and Piper plots classified the waters into Mg-HCO3− and Ca-Cl− types. The past and present mining activities clearly change the water chemistry and alter the quality of the Aries River, with the water requiring specific treatments before use.

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