SLURP model and GIS for estimation of runoff in a part of Satluj catchment,India

Abstract

The snow and rain in the Himalayas are the main sources of supply for the rivers in the Indo-Gangetic plains. Irrigation, hydropower generation, and water supply are very much dependent on the availability of water in the Himalaya rivers. Mathematical models serve as important aids for the estimation of water availability in rivers. In the present study the SLURP watershed model is applied to a rainfed area of the Satluj catchment located in the western Himalayas, India. The SLURP model developed at NHRI, Canada, is a distributed conceptual model which simulates the behaviour of a watershed by carrying out vertical water balances for each element of a matrix of landcovers and subareas of a watershed and then routing the resulting runoff between subareas. The ILWIS geographic information system was used to prepare the input data required for SLURP and land use data were obtained from the IRS satellite LISS II visible and near infrared sensors. The simulated flows at the Bhakhra Dam outlet of the Satluj catchment were computed and found to compare well with the observed flows.     

Geospatial tools for assessing land degradation in Budgam district,Kashmir Himalaya,India

Land degradation reduces the ability of the land to perform many biophysical and chemical functions. The main aim of this study was to determine the status of land degradation in the Budgam area of Kashmir Himalaya using remote sensing and geographic information system. The satellite data together with other geospatial datasets were used to quantify different categories of land degradation. The results were validated in the field and an accuracy of 85% was observed. Land use/land cover of the study area was determined in order to know the effect of land use on the rate of land degradation. Normalized differential vegetation index (NDVI) and slope of the area were determined using LANDSAT-enhanced thematic mapper plus (ETM+) data, advanced space borne thermal emission and reflection radiometer, and digital elevation model along with other secondary data were analysed to create various thematic maps, viz., land use/land cover, geology, NDVI and slopes used in modelling land degradation in the Kashmir Himalayan region. The vegetation condition, elevation and land use/land cover information of the area were integrated to assess the land degradation scenario in the area using the ArcGIS ‘Spatial Analyst Module’. The results reveal that about 13.19% of the study area has undergone moderate to high degradation, whereas about 44.12% of the area has undergone slight degradation.     

Streamflow trend analysis by considering autocorrelation structure,long-term persistence,and Hurst coefficient in a semi-arid region of Iran

Due to the substantial decrease of water resources as well as the increase in demand and climate change phenomenon, analyzing the trend of hydrological parameters is of paramount importance. In the present study, investigations were carried out to identify the trends in streamflow at 20 hydrometric stations and 11 rainfall gauging stations located in Karkheh River Basin (KRB), Iran, in monthly, seasonal, and annual time scales during the last 38 years from 1974 to 2011. This study has been conducted using two versions of Mann–Kendall tests, including (i) Mann–Kendall test by considering all the significant autocorrelation structure (MK3) and (ii) Mann–Kendall test by considering LTP and Hurst coefficient (MK4). The results indicate that the KRB streamflow trend (using both test versions) has decreased in all three time scales. There is a significant decreasing trend in 78 and 73 % of the monthly cases using the MK3 and MK4 tests, respectively, while these percentages changed to 80 and 70 % on seasonal and annual time scales, respectively. Investigation of the trend line slope using Theil–Sen’s estimator showed a negative trend in all three time scales. The use of MK4 test instead of the MK3 test has caused a decrease in the significance level of Mann–Kendall Z-statistic values. The results of the precipitation trends indicate both increasing and decreasing trends. Also, the correlation between the area average streamflow and precipitation shows a strong correlation in annual time scale in the KRB.     

Evaluation of coal as adsorbent for phosphate removal

This paper reports the adsorption of phosphate ions on coal, charcoal, and coal ash. The influences of factors such as contact time, and initial adsorbate concentration have been studied. Adsorption of phosphate ions on virgin coal was significant compared to charcoal, coal and coal ash evacuated at 200°C. The significant adsorption capability of coal is due to the porosity as well as due to organic carbon and inorganic elements present in coal. The evacuation of coal proved to be ineffective in enhancing its capability for phosphate ions retention. The adsorption behaviors of all the three adsorbent used was conformed using Freundlich’s adsorption model. The results suggest that coal could be used as an efficient adsorbent for removing phosphate ions from wastewater.     

Extraction of extracellular polymeric substances from activated sludge using sodium oxalate

In this study, sodium oxalate was employed to extract extracellular polymeric substances (EPS) from activated sludge samples. The optimum dose of sodium oxalate was 1.34 g/g VSS (volatile suspended solids), and the extraction time was 60 min at pH 7. The total EPS contents obtained under the optimized conditions were approximately 191 mg/g VSS, and they predominantly consisted of proteins, polysaccharides and humic substances. The extraction efficiencies of the chosen method for the major biopolymers were 39, 43 and 410 % higher compared with the ethylenediaminetetraacetic acid (EDTA), cation exchange resin and control methods. Cell lysis measured in terms of deoxyribonucleic acid, and unidentified EPS were approximately 50 % lower in the sodium oxalate method than in the NaOH and EDTA methods. The EPS composition and the ratio of proteins/polysaccharides (1.38–2.21) were extremely dependent on the operating conditions maintained during the extraction. The inductively coupled plasma spectroscopic results demonstrated that the release of divalent metals, such as Ca²⁺ and Mg²⁺, from the sludge matrix was directly correlated with higher EPS extraction efficiencies in the sodium oxalate protocol. Moreover, the precipitation of Ca²⁺ and Mg²⁺ as metallic oxalates disrupted the floc structure and subsequently enhanced the EPS recovery. Fourier transform infrared studies revealed the presence of functional groups due to EPS molecules in all extracted samples.     

Survey of land subsidence – case study: The land subsidence formation in artificial recharge ponds at South Hamadan Power Plant,northwest of Iran

Journal of Earth System Science - The artificial recharge is a technique of aquifer conservation for land subsidence. But in this article, the phenomenon of land subsidence and the resulting cracks...     

Potential sea-level rise effects on the hydrodynamics and transport processes in Hudson–Raritan Estuary,NY–NJ

Ocean Dynamics - The climatic change has led to the sea-level rise (SLR), which is expected to continue based on the current industrial and human activities. Previous studies indicated that most of...     

Comparative study of multilayer perceptron-stochastic gradient descent and gradient boosted trees for predicting daily suspended sediment load: The case study of the Mississippi River,U.S.

Monitoring sediment transport is essential for managing and maintaining rivers.Estimation of the sediment load in rivers is fundamental for the study of sediment movement,erosion,and flood control.In the current study,three machine learning models-multi-layer perceptron(MLP),multi-layer perceptron-stochastic gradient descent(MLP-SGD),and gradient boosted tree(GBT)-were utilized to estimate the suspended sediment load(SSL)at the St.Louis(SL)and Chester(CH)stations on the Mississippi River,U.S.Four evaluation criteria including the Correlation Coefficient(CC),Nash Sutcliffe Efficiency(NSE),Scatter Index(SI),and Willmott’s Index(WI)were utilized to evaluate the performance of the used models.A sensitivity analysis of the models to the input variables revealed that the current day discharge variable had the most effect on the SSL at both stations,but in the absence of current-day discharge data(Qt),a combination of input parameters including SSL_t-3,SSL_t-2,SSL_t-1,Q_t-3,Q_t-2,Q_t-1 can be used to estimate the SSL.The comparative outcomes indicated the high accuracy of MLP-SGD-5 model with a CC of 0.983,SI of 0.254,WI of 0.991,and NSE of 0.967 at station CH and the MLP-SGD-6 model with a CC of 0.933,SI of 0.576,WI of 0.961,and NSE of 0.867,respectively,at station SL.The results of MLP models were improved by SGD optimization.Therefore,the MLP-SGD method is recommended as the most accurate model for SSL estimation.     

Simulating low and high streamflow driven by snowmelt in an insufficiently gauged alpine basin

Snowmelt and water infiltration are two important processes of the hydrological cycle in alpine basins where snowmelt water is a main contributor of streamflow. In insufficiently gauged basins, hydrologic modeling is a useful approach to understand the runoff formation process and to simulate streamflow. In this study, an existing hydrologic model based on the principles of system dynamics was modified by using the effective cumulative temperature (>0 °C) to calculate snowmelt rate, and the soil temperature to adjust the influence of the soil’s physical state on water infiltration. This modified model was used to simulate streamflows in the Kaidu River basin from 1982 to 2002, including normal, high, and low flows categorized by the Z index. Sensitivity analyses, visual inspection, and statistical measures were employed to evaluate the capability of the model to simulate various components of the streamflow. Results showed that the modified model was robust, and able to simulate the three categories of flows well. The model’s ability to reproduce streamflow in low-flow and normal-flow years was better than that in high-flow years. The model was also able to simulate the baseflow. Further, its ability to simulate spring-peak flow was much better than its ability to simulate the summer-peak flow. This study could provide useful information for water managers in determining water allocations as well as in managing water resources.     

Evaluating effectiveness of frequency ratio,fuzzy logic and logistic regression models in assessing landslide susceptibility: a case from Rudraprayag district,India

Rudraprayag in Garhwal Himalayan division is one of the most vulnerable districts to landslides in India. Heavy rainfall, steep slope and developmental activities are important factors for the occurrence of landslides in the district. Therefore, specific assessment of landslide susceptibility and its accuracy at regional level is essential for disaster management and proper land use planning. The article evaluates effectiveness of frequency ratio, fuzzy logic and logistic regression models for assessing landslide susceptibility in Rudraprayag district of Uttarakhand state, India. A landslide inventory map was prepared and verified by field data. Fourteen landslide parameters and generated inventory map were utilized to prepare landslide susceptibility maps through frequency ratio, fuzzy logic and logistic regression models. Landslide susceptibility maps generated through these models were classified into very high, high, medium, low and very low categories using natural breaks classification. Receiver operating characteristics (ROC) curve, spatially agreed area approach and seed cell area index (SCAI) method were used to validate the landslide models. Validation results revealed that fuzzy logic model was found to be more effective in assessing landslide susceptibility in the study area. The landslide susceptibility map generated through fuzzy logic model can be best utilized for landslide disaster management and effective land use planning.