Rainstorm-generated sediment yield model based on soil moisture proxies (SMP)     

Sushindra Kumar Gupta  Pushpendra K. Singh  Jaivir Tyagi  Gunwant Sharma  Ajay Singh Jethoo 《水文研究》2020,34(16):3448-3463

This study develops improved Soil Moisture Proxies (SMP) based suspended sediment yield (SMPSY) models corresponding to three antecedent moisture conditions (AMCs) (i.e., AMC-I-AMC-III) by coupling the improved initial abstraction (I_a-λ) model, the SMA procedure and the SMP concept for modelling the rainfall generated suspended sediment yield. The SMPSY models specifically incorporate a watershed storage index (S) model to accentuate the transformation from storm to storm and to avoid the sudden jumps in sediment yield computation. The workability of the SMPSY models is tested using a large dataset of rainfall and sediment yield (98 storm events) from twelve small watersheds and a comparison has been made with the existing MSY model. The goodness-of-fit (GOF) statistics is evaluated in terms of the Nash Sutcliffe efficiency (NSE), and error indices, i.e., root mean square error (RMSE), normalized root mean square error (nRMSE), standard error (SE), mean absolute error (MAE), and RMSE-observations standard deviation ratio (RSR). The NSE values vary from 74.31% to 96.57% and from 75.21% to 91.78%, respectively for the SPMSY and MSY model. The NSE statistics indicate that the SMPSY model has lower uncertainty in simulating sediment yield as compared to the MSY model. The error indices are lower for the SMPSY model than the MSY model for most of the watersheds. These results show that the SMPSY model has less uncertainty and performs better than the MSY model. A sensitivity analysis of the SMPSY model shows that the parameter β is most sensitive followed by parameter S, α and A. Overall, the results show that the characterization of soil moisture variability in terms of SMPs and incorporation of improved delivery ratio and runoff coefficient relationship improves the simulation of the erosion and sediment yield generation process.  相似文献   

High-Resolution Quasi-3D Electric Resistivity Tomography for Deciphering Groundwater Potential Zones in Lateritic Terrain     

Rupesh  Tiwari  Prarabdh  Sharma  S. P. 《Natural Resources Research》2021,30(5):3339-3353

Natural Resources Research - Groundwater is under constant threat of exploitation with increasing demands. Therefore, there is a need for more advanced methods for exploring potential groundwater...  相似文献   

Change detection of linear features in temporally spaced remotely sensed images using edge-based grid analysis     

Arati Paul  V. M. Chowdary  Y. K. Srivastava  D. Dutta  J. R. Sharma 《国际地球制图》2017,32(6):640-654

Automatic change detection of land cover features using high-resolution satellite images, is a challenging problem in the field of intelligent remote sensing data interpretation, and is becoming more and more effective for its applications viz. urban planning and monitoring, disaster assessment etc. In the present study, a change in detection approach based on the image morphology that analyses change in the local image grids is proposed. In this approach, edges from both the images are extracted and grid wise comparison is made by probabilistic thresholding and power spectral density analysis for identifying change area. One of the advantages of the proposed methodology is that the temporal images used in the change analysis need not be radiometrically corrected as analysis is based on edge extractions. The grid-based analysis further reduces the error, which might have been introduced by image mis-registration. The proposed methodology is validated by finding the temporal changes in the linear land cover features in parts of Kolkata city, India using three different image data-sets from LISS IV, Cartosat-1 and Google earth having varied spatial resolutions of 5.8 m, 2.5 m and about 1 m, respectively. The overall accuracy in identifying changes is found to be 64.82, 73.86 and 80.93% for LISS IV, Cartosat-1 and Google earth data-set, respectively.  相似文献   

Study of Aerosol Direct and Indirect Effects and Auto-conversion Processes over the West African Monsoon Region Using a Regional Climate Model     

Zeinab SALAH  Ahmed SHALABY  Allison L.STEINER  Ashraf S.ZAKEY  Ritesh GAUTAM  Mohamed M.ABDEL WAHAB 《大气科学进展》2018,35(2):182-194

This study assesses the direct and indirect effects of natural and anthropogenic aerosols(e.g., black carbon and sulfate)over West and Central Africa during the West African monsoon(WAM) period(June–July–August). We investigate the impacts of aerosols on the amount of cloudiness, the influences on the precipitation efficiency of clouds, and the associated radiative forcing(direct and indirect). Our study includes the implementation of three new formulations of auto-conversion parameterization [namely, the Beheng(BH), Tripoli and Cotton(TC) and Liu and Daum(R6) schemes] in Reg CM4.4.1,besides the default model's auto-conversion scheme(Kessler). Among the new schemes, BH reduces the precipitation wet bias by more than 50% over West Africa and achieves a bias reduction of around 25% over Central Africa. Results from detailed sensitivity experiments suggest a significant path forward in terms of addressing the long-standing issue of the characteristic wet bias in Reg CM. In terms of aerosol-induced radiative forcing, the impact of the various schemes is found to vary considerably(ranging from-5 to-25 W m~(-2)).  相似文献   

Multi-criteria evaluation of CMIP5 GCMs for climate change impact analysis   总被引：1，自引：0，他引：1  

Ali?AhmadalipourEmail author  Arun?Rana  Hamid?Moradkhani  Ashish?Sharma 《Theoretical and Applied Climatology》2017,128(1-2):71-87

Climate change is expected to have severe impacts on global hydrological cycle along with food-water-energy nexus. Currently, there are many climate models used in predicting important climatic variables. Though there have been advances in the field, there are still many problems to be resolved related to reliability, uncertainty, and computing needs, among many others. In the present work, we have analyzed performance of 20 different global climate models (GCMs) from Climate Model Intercomparison Project Phase 5 (CMIP5) dataset over the Columbia River Basin (CRB) in the Pacific Northwest USA. We demonstrate a statistical multicriteria approach, using univariate and multivariate techniques, for selecting suitable GCMs to be used for climate change impact analysis in the region. Univariate methods includes mean, standard deviation, coefficient of variation, relative change (variability), Mann-Kendall test, and Kolmogorov-Smirnov test (KS-test); whereas multivariate methods used were principal component analysis (PCA), singular value decomposition (SVD), canonical correlation analysis (CCA), and cluster analysis. The analysis is performed on raw GCM data, i.e., before bias correction, for precipitation and temperature climatic variables for all the 20 models to capture the reliability and nature of the particular model at regional scale. The analysis is based on spatially averaged datasets of GCMs and observation for the period of 1970 to 2000. Ranking is provided to each of the GCMs based on the performance evaluated against gridded observational data on various temporal scales (daily, monthly, and seasonal). Results have provided insight into each of the methods and various statistical properties addressed by them employed in ranking GCMs. Further; evaluation was also performed for raw GCM simulations against different sets of gridded observational dataset in the area.  相似文献   

Metals in Sediments of the Upper Laguna Madre   总被引：2，自引：0，他引：2  

Virender K Sharma  Kurtis B Rhudy  Robert Koening  Felipe G Vazquez 《Marine pollution bulletin》1999,38(12):1213-1226

The Laguna Madre system is the largest hypersaline coastal basin in the United States. Surface sediments from 22 Upper Laguna Madre (ULM) sites were analyzed for grain size and metals (Cd, Cu, Ba, Cr, Mn, Ni, Pb, V, Zn, Fe, and Al) to assess the extent of contamination in the area. Sediments were found to consist mainly of sand texture. Clay and silts were minor constituents (<10%) of the sediments. Anomalies in metal concentrations were found at some sites and were related to probable sources, i.e., recreational and industrial activities. Concentrations of metals were normalized to grain size, Al, and Fe to distinguish natural and anthropogenic sources. Most metals showed positive correlations (p < 0.001) with Fe and Al, suggesting a natural variability of metal concentrations in sediments. Concentrations of metals, except Cd and Pb, at most sites were found to be below threshold concentrations thought to produce toxic effects in marine and estuarine organisms.  相似文献   

Interannual Variation of Eddy Kinetic Energy from TOPEX Altimeter Observations   总被引：1，自引：0，他引：1  

Rashmi Sharma  A. K. S. Gopalan  M. M. Ali 《Marine Geodesy》1999,22(4):239-248

Monthly mesoscale eddy kinetic energy (EKE) per unit mass has been computed for four years, 1993-1996, from TOPEX altimeter data in the Indian Ocean. It ranges from 50 cm²/s² to 2,700 cm²/s² (about 4,000 cm²/s² near the Somali region in a few months). In the Arabian Sea and the Bay of Bengal, regions of high energies associated with various current systems under the influence of monsoonal winds have been delineated. Monthly variation of EKE near the Somali region has been studied. In this region the maximum EKE per unit mass has been observed during August every year, with variations in magnitude from year to year. The mesoscale eddy kinetic energy computed from TOPEX altimeter-derived SSH during 1993-1996 is highest near the Somali region during the SW monsoon, due to formation of mesoscale eddies and also because of upwelling. In the Bay of Bengal, high eddy kinetic energy is seen toward the western side during nonmonsoonal months due to the western boundary current. In the South Indian Ocean, it is high at a few places in some of the months. A large part of the Indian Ocean exhibits low eddy kinetic energy (less than 300 cm²/s²) year-round.  相似文献   

Monitoring litter interception of rainfall using leaf wetness sensor under controlled and field conditions   总被引：2，自引：0，他引：2       下载免费PDF全文

Bharat Sharma Acharya  Elaine Stebler  Chris B. Zou 《水文研究》2017,31(1):240-249

Leaf litter interception of water is an integral component of the water budget for some vegetated ecosystems. However, loss of rainfall to litter receives considerably less attention than canopy interception due to lack of suitable sensors to measure changes in litter water content. In this study, a commercially available leaf wetness sensor was calibrated to the gravimetric water content of eastern redcedar (Juniperus virginiana ) litter and used to estimate litter interception in a subhumid eastern redcedar woodland in north‐central Oklahoma. Under controlled laboratory conditions, a strong positive correlation between the leaf wetness sensor output voltage (mV) and measured gravimetric litter water content (? _g) was determined: ? _g = (.0009 × mV²) ? (0.14 × mV) ? 11.41 (R ² = .94, p  < .0001). This relationship was validated with field sampling and the output voltage (mV) accounted for 48% of the observed variance in the measured water content. The maximum and minimum interception storage capacity ranged between 1.16 and 12.04 and 1.12 and 9.62 mm, respectively. The maximum and minimum amount of intercepted rain was positively correlated to rainfall amount and intensity. The continuous field measurements demonstrated that eastern redcedar litter intercepted approximately 8% of the gross rainfall that fell between December 16, 2014 and May 31, 2015. Therefore, rainfall loss to litter can constitute a substantial component of the annual water budget. Long‐term in situ measurement of litter interception loss is necessary to gain a better estimate of water availability for streamflow and recharge. This is critical to manage water resources in the south‐central Great Plains, USA where grasslands are rapidly being transformed to woodland or woody dominated savanna.  相似文献   

Simulating rainfall time-series: how to account for statistical variability at multiple scales?     

Fabio?OrianiEmail authorView author&#;s OrcID profile  Raj?Mehrotra  Grégoire?Mariethoz  Julien?Straubhaar  Ashish?Sharma  Philippe?Renard 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(2):321-340

Daily rainfall is a complex signal exhibiting alternation of dry and wet states, seasonal fluctuations and an irregular behavior at multiple scales that cannot be preserved by stationary stochastic simulation models. In this paper, we try to investigate some of the strategies devoted to preserve these features by comparing two recent algorithms for stochastic rainfall simulation: the first one is the modified Markov model, belonging to the family of Markov-chain based techniques, which introduces non-stationarity in the chain parameters to preserve the long-term behavior of rainfall. The second technique is direct sampling, based on multiple-point statistics, which aims at simulating a complex statistical structure by reproducing the same data patterns found in a training data set. The two techniques are compared by first simulating a synthetic daily rainfall time-series showing a highly irregular alternation of two regimes and then a real rainfall data set. This comparison allows analyzing the efficiency of different elements characterizing the two techniques, such as the application of a variable time dependence, the adaptive kernel smoothing or the use of low-frequency rainfall covariates. The results suggest, under different data availability scenarios, which of these elements are more appropriate to represent the rainfall amount probability distribution at different scales, the annual seasonality, the dry-wet temporal pattern, and the persistence of the rainfall events.  相似文献   

Estimation of carbon stock for greenhouse gas emissions from hydropower reservoirs     

Amit?KumarEmail authorView author&#;s OrcID profile  M.?P.?Sharma  Tao?Yang 《Stochastic Environmental Research and Risk Assessment (SERRA)》2018,32(11):3183-3193

The identification and accurate quantification of sources or sinks of greenhouse gas (GHG) have become a key challenge for scientists and policymakers working on climate change. The creation of a hydropower reservoir, while damming a river for power generation, converts the terrestrial ecosystems into aquatic and subsequently aerobic and anaerobic decomposition of flooded terrestrial soil organic matter resulting in the emission of significant quantity of GHG to the atmosphere. Tropical/subtropical hydropower reservoirs are more significant sources of GHG compared to boreal or temperate one. This paper aims to estimate the emission factor (gCO₂eq./kWh) and net GHG emission from Koteshwar hydropower reservoir in Uttarakhand, India. Further, estimated GHG are compared with those from global reservoirs located in the same eco-region so that its impact could be timely minimized/mitigated. Results have shown that emission factor and net GHG emission of Koteshwar reservoir are, respectively, estimated as 13.87 gCO₂eq./kWh and 167.70 Gg C year^?1 which are less than other global reservoirs located in the same eco-region. This information could be helpful for the hydropower industries to construct reservoirs in tropical eco-regions.  相似文献