This page has only limited features, please log in for full access.

Unclaimed
Ankur Srivastava
School of Engineering, The University of Newcastle, Callaghan, NSW 2308, Australia

Basic Info


Fingerprints

Evapotranspiration
Landscape evolution
Remote sensing & GIS applications
Ecohydrology
Geomorphology

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 26 August 2021 in Water
Reads 0
Downloads 0

Increased population and increasing demands for food in the Indo-Gangetic plain are likely to exert pressure on fresh water due to rise in demand for drinking and irrigation water. The study focuses on Bhojpur district, Bihar located in the central Ganga basin, to assess the groundwater quality for drinking and irrigation purpose and discuss the issues and challenges. Groundwater is mostly utilized in the study area for drinking and irrigation purposes (major crops sown in the area are rice and wheat). There were around 45 groundwater samples collected across the study region in the pre-monsoon season (year 2019). The chemical analytical results show that Ca2+, Mg2+ and HCO3 ions are present in abundance in groundwater and governing the groundwater chemistry. Further analysis shows that 66%, 69% and 84% of the samples exceeded the acceptable limit of arsenic (As), Fe and Mn respectively and other trace metals (Cu, Zn, Pb, Cd) are within the permissible limit of drinking water as prescribed by Bureau of Indian Standard for drinking water. Generally, high as concentration has been found in the aquifer (depth ranges from 20 to 40 m below ground surface) located in proximity of river Ganga. For assessing the irrigation water quality, sodium adsorption ratio (SAR) values, residual sodium carbonate (RSC), Na%, permeability index (PI) and calcium alteration index (CAI) were calculated and found that almost all the samples are found to be in good to excellent category for irrigation purposes. The groundwater facie has been classified into Ca-Mg-HCO3 type.

ACS Style

Sumant Kumar; Manish Kumar; Veerendra Kumar Chandola; Vinod Kumar; Ravi K. Saini; Neeraj Pant; Nikul Kumari; Ankur Srivastava; Surjeet Singh; Rajesh Singh; Gopal Krishan; Shashi Poonam Induwar; Sudhir Kumar; Brijesh Kumar Yadav; Nityanand Singh Maurya; Anju Chaudhary. Groundwater Quality Issues and Challenges for Drinking and Irrigation Uses in Central Ganga Basin Dominated with Rice-Wheat Cropping System. Water 2021, 13, 2344 .

AMA Style

Sumant Kumar, Manish Kumar, Veerendra Kumar Chandola, Vinod Kumar, Ravi K. Saini, Neeraj Pant, Nikul Kumari, Ankur Srivastava, Surjeet Singh, Rajesh Singh, Gopal Krishan, Shashi Poonam Induwar, Sudhir Kumar, Brijesh Kumar Yadav, Nityanand Singh Maurya, Anju Chaudhary. Groundwater Quality Issues and Challenges for Drinking and Irrigation Uses in Central Ganga Basin Dominated with Rice-Wheat Cropping System. Water. 2021; 13 (17):2344.

Chicago/Turabian Style

Sumant Kumar; Manish Kumar; Veerendra Kumar Chandola; Vinod Kumar; Ravi K. Saini; Neeraj Pant; Nikul Kumari; Ankur Srivastava; Surjeet Singh; Rajesh Singh; Gopal Krishan; Shashi Poonam Induwar; Sudhir Kumar; Brijesh Kumar Yadav; Nityanand Singh Maurya; Anju Chaudhary. 2021. "Groundwater Quality Issues and Challenges for Drinking and Irrigation Uses in Central Ganga Basin Dominated with Rice-Wheat Cropping System." Water 13, no. 17: 2344.

Journal article
Published: 30 June 2021 in Climate
Reads 0
Downloads 0

The Himalayas constitute one of the richest and most diverse ecosystems in the Indian sub-continent. Vegetation greenness driven by climate in the Himalayan region is often overlooked as field-based studies are challenging due to high altitude and complex topography. Although the basic information about vegetation cover and its interactions with different hydroclimatic factors is vital, limited attention has been given to understanding the response of vegetation to different climatic factors. The main aim of the present study is to analyse the relationship between the spatiotemporal variability of vegetation greenness and associated climatic and hydrological drivers within the Upper Khoh River (UKR) Basin of the Himalayas at annual and seasonal scales. We analysed two vegetation indices, namely, normalised difference vegetation index (NDVI) and enhanced vegetation index (EVI) time-series data, for the last 20 years (2001–2020) using Google Earth Engine. We found that both the NDVI and EVI showed increasing trends in the vegetation greening during the period under consideration, with the NDVI being consistently higher than the EVI. The mean NDVI and EVI increased from 0.54 and 0.31 (2001), respectively, to 0.65 and 0.36 (2020). Further, the EVI tends to correlate better with the different hydroclimatic factors in comparison to the NDVI. The EVI is strongly correlated with ET with r2 = 0.73 whereas the NDVI showed satisfactory performance with r2 = 0.45. On the other hand, the relationship between the EVI and precipitation yielded r2 = 0.34, whereas there was no relationship was observed between the NDVI and precipitation. These findings show that there exists a strong correlation between the EVI and hydroclimatic factors, which shows that changes in vegetation phenology can be better captured using the EVI than the NDVI.

ACS Style

Nikul Kumari; Ankur Srivastava; Umesh Dumka. A Long-Term Spatiotemporal Analysis of Vegetation Greenness over the Himalayan Region Using Google Earth Engine. Climate 2021, 9, 109 .

AMA Style

Nikul Kumari, Ankur Srivastava, Umesh Dumka. A Long-Term Spatiotemporal Analysis of Vegetation Greenness over the Himalayan Region Using Google Earth Engine. Climate. 2021; 9 (7):109.

Chicago/Turabian Style

Nikul Kumari; Ankur Srivastava; Umesh Dumka. 2021. "A Long-Term Spatiotemporal Analysis of Vegetation Greenness over the Himalayan Region Using Google Earth Engine." Climate 9, no. 7: 109.

Journal article
Published: 29 April 2021 in Remote Sensing
Reads 0
Downloads 0

Atmospheric transmissivity (τ) is a critical factor in climatology, which affects surface energy balance, measured at a limited number of meteorological stations worldwide. With the limited availability of meteorological datasets in remote areas across different climatic regions, estimation of τ is becoming a challenging task for adequate hydrological, climatic, and crop modeling studies. The availability of solar radiation data is comparatively less accessible on a global scale than the temperature and precipitation datasets, which makes it necessary to develop methods to estimate τ. Most of the previous studies provided region specific datasets of τ, which usually provide local assessments. Hence, there is a necessity to give the empirical models for τ estimation on a global scale that can be easily assessed. This study presents the analysis of the τ relationship with varying geographic features and climatic factors like latitude, aridity index, cloud cover, precipitation, temperature, diurnal temperature range, and elevation. In addition to these factors, the applicability of these relationships was evaluated for different climate types. Thus, empirical models have been proposed for each climate type to estimate τ by using the most effective factors such as cloud cover and aridity index. The cloud cover is an important yet often overlooked factor that can be used to determine the global atmospheric transmissivity. The empirical relationship and statistical indicator provided the best performance in equatorial climates as the coefficient of determination (r 2) was 0.88 relatively higher than the warm temperate (r 2 = 0.74) and arid regions (r 2 = 0.46). According to the results, it is believed that the analysis presented in this work is applicable for estimating the τ in different ecosystems across the globe.

ACS Style

Ankur Srivastava; Jose Rodriguez; Patricia Saco; Nikul Kumari; Omer Yetemen. Global Analysis of Atmospheric Transmissivity Using Cloud Cover, Aridity and Flux Network Datasets. Remote Sensing 2021, 13, 1716 .

AMA Style

Ankur Srivastava, Jose Rodriguez, Patricia Saco, Nikul Kumari, Omer Yetemen. Global Analysis of Atmospheric Transmissivity Using Cloud Cover, Aridity and Flux Network Datasets. Remote Sensing. 2021; 13 (9):1716.

Chicago/Turabian Style

Ankur Srivastava; Jose Rodriguez; Patricia Saco; Nikul Kumari; Omer Yetemen. 2021. "Global Analysis of Atmospheric Transmissivity Using Cloud Cover, Aridity and Flux Network Datasets." Remote Sensing 13, no. 9: 1716.

Research article
Published: 17 April 2021 in Journal of the Indian Society of Remote Sensing
Reads 0
Downloads 0

Crop coefficient (Kc) represents the actual crop growth of the crop. It plays an important role in estimating water requirements at the different growth stages of the crop. However, FAO 56 Penman–Monteith Kc method does not account for spatial heterogeneity and uncertainty for regional climatic conditions significantly. Therefore, this study aims to develop the relation between Kc and normalized difference vegetation index (NDVI) using a linear regression and back calculations. These relationships were adjusted to local conditions using information from survey data obtained during Rabi season (2014–2015). The NDVI–Kc model (r2 = 0.86) has developed using NDVI–Kc from a fine resolution Landsat 8 remote sensing data. NDVI–Kc regression equation was utilized for generating crop coefficient for different month of season. The Vegetation Index-based AET estimated was evaluated with lysimeter data for different crop growth stage across the season. The results have shown that NDVI–Kc estimated AET has been better correlated with NDVI–Kc remote sensing model. Thus, the output of this research can help to calculate actual water demand in a command area and be helpful in allocating water from less demand area toward more demand area.

ACS Style

Utkarsh Kumar; Ankur Srivastava; Nikul Kumari; Rashmi; Bhabagrahi Sahoo; Chandranath Chatterjee; Narendra Singh Raghuwanshi. Evaluation of Spatio-Temporal Evapotranspiration Using Satellite-Based Approach and Lysimeter in the Agriculture Dominated Catchment. Journal of the Indian Society of Remote Sensing 2021, 49, 1939 -1950.

AMA Style

Utkarsh Kumar, Ankur Srivastava, Nikul Kumari, Rashmi, Bhabagrahi Sahoo, Chandranath Chatterjee, Narendra Singh Raghuwanshi. Evaluation of Spatio-Temporal Evapotranspiration Using Satellite-Based Approach and Lysimeter in the Agriculture Dominated Catchment. Journal of the Indian Society of Remote Sensing. 2021; 49 (8):1939-1950.

Chicago/Turabian Style

Utkarsh Kumar; Ankur Srivastava; Nikul Kumari; Rashmi; Bhabagrahi Sahoo; Chandranath Chatterjee; Narendra Singh Raghuwanshi. 2021. "Evaluation of Spatio-Temporal Evapotranspiration Using Satellite-Based Approach and Lysimeter in the Agriculture Dominated Catchment." Journal of the Indian Society of Remote Sensing 49, no. 8: 1939-1950.

Research article
Published: 25 November 2020 in Hydrological Processes
Reads 0
Downloads 0

Previous studies on semi‐arid ecosystems have shown high values of soil moisture variability (SMV) primarily induced by the combined effects of non‐uniform precipitation, incoming solar radiation, and soil and vegetation properties. However, the relative impact of these various factors on SMV has been difficult to evaluate due to limited availability of field data. In addition, only a limited number of studies have analyzed the role of landscape morphology on SMV. Here we use numerical simulations of a simple hydrological model, the Bucket Grassland Model (BGM), to systematically analyze the effect of each contributing factor on SMV on two different landscape morphologies. The two different landform morphologies represent landscapes dominated respectively by either diffusive erosion or fluvial erosion processes. We conducted various simulations driven by a stochastically generated 100‐year climate time series, which is long enough to capture climatic fluctuations, in order to understand the effect of various soil moisture controlling factors on the spatiotemporal SMV. Our modeling results show that the fluvial dominated landscapes promote higher spatial SMV than the diffusive dominated ones. Further, the role of landform morphology on SMV is more pronounced in regions where the spatial variability of incoming solar radiation and precipitation is high.

ACS Style

Ankur Srivastava; Patricia M. Saco; Jose F. Rodriguez; Nikul Kumari; Kwok Pan Chun; Omer Yetemen. The role of landscape morphology on soil moisture variability in semi‐arid ecosystems. Hydrological Processes 2020, 35, 1 .

AMA Style

Ankur Srivastava, Patricia M. Saco, Jose F. Rodriguez, Nikul Kumari, Kwok Pan Chun, Omer Yetemen. The role of landscape morphology on soil moisture variability in semi‐arid ecosystems. Hydrological Processes. 2020; 35 (1):1.

Chicago/Turabian Style

Ankur Srivastava; Patricia M. Saco; Jose F. Rodriguez; Nikul Kumari; Kwok Pan Chun; Omer Yetemen. 2020. "The role of landscape morphology on soil moisture variability in semi‐arid ecosystems." Hydrological Processes 35, no. 1: 1.

Article
Published: 23 September 2020 in Journal of Earth System Science
Reads 0
Downloads 0

Present study assesses the effect of finer land-use classification in simulating the rainfall-runoff response of Kangsabati reservoir catchment (3,627 km2) and command (7,112 km2) by considering cropland heterogeneity in variable infiltration capacity (VIC) model. High resolution LISS-IV satellite imageries were used for the land-use classification. Global sensitivity analysis was performed using VIC-ASSIST to identify the most and least influential parameters based on the sensitivity index of elementary effects. A fully distributed calibration approach was employed using 16 (detailed) and 8 (lumped) vegetation classes. Low flows during lean periods were over-estimated and peak flows were under-estimated by both the model setups at Kangsabati reservoir site. Detailed land-use classification resulted in the reduction in streamflow over-estimation (Percent Bias (PBIAS) from −20.99 to −14.41 during calibration and from –22.83 to –7.17 during validation) at daily time step. It further demonstrates the improvement in simulating the peak flows; hence, highlighting the importance of detailed land-use classification for vegetation parameterization in VIC model setup. River discharge regulation at Kangsabati reservoir resulted in poor model performance at Mohanpur, downstream site of Kangsabati reservoir. Therefore, calibration for Mohanpur was performed after updating the VIC simulated streamflow with routed reservoir spillage using Hydrologic Engineering Center-River Analysis System (HEC-RAS) model. Streamflow updation employing HEC-RAS at Mohanpur improved the modelling efficiency (Nash–Sutcliffe efficiency (NSE) from 0.50 to 0.65 during calibration and from 0.55 to 0.67 during validation) and reduced bias (PBIAS from 6.25 to –2.23 during calibration and from 15.06 to 7.40 during validation) considerably for daily flows. Model performance with reasonable accuracy was achieved at both the calibration locations which demonstrates the potential applicability of VIC model to predict streamflow in the monsoon dominated Kangsabati reservoir catchment and command. LISS-IV satellite imageries were classified using ground truth survey data obtained for different crop types in the study area Crop specific vegetation parameterization was used in setting up VIC modeling framework Modeling efficacy was assessed for two vegetation parameterization schemes using single crop type and multiple crops Global sensitivity analysis and fully distributed automatic calibration was performed using VIC-ASSIST software package Utility of HEC-RAS was shown in routing reservoir spillage to the downstream gauging point in VIC modeling framework in the absence of integrated reservoir module

ACS Style

Minotshing Maza; Ankur Srivastava; Deepak Singh Bisht; Narendra Singh Raghuwanshi; Arnab Bandyopadhyay; Chandranath Chatterjee; Aditi Bhadra. Simulating hydrological response of a monsoon dominated reservoir catchment and command with heterogeneous cropping pattern using VIC model. Journal of Earth System Science 2020, 129, 1 -16.

AMA Style

Minotshing Maza, Ankur Srivastava, Deepak Singh Bisht, Narendra Singh Raghuwanshi, Arnab Bandyopadhyay, Chandranath Chatterjee, Aditi Bhadra. Simulating hydrological response of a monsoon dominated reservoir catchment and command with heterogeneous cropping pattern using VIC model. Journal of Earth System Science. 2020; 129 (1):1-16.

Chicago/Turabian Style

Minotshing Maza; Ankur Srivastava; Deepak Singh Bisht; Narendra Singh Raghuwanshi; Arnab Bandyopadhyay; Chandranath Chatterjee; Aditi Bhadra. 2020. "Simulating hydrological response of a monsoon dominated reservoir catchment and command with heterogeneous cropping pattern using VIC model." Journal of Earth System Science 129, no. 1: 1-16.

Article
Published: 18 August 2020 in Water Resources Management
Reads 0
Downloads 0

Hydrological responses corresponding to the agricultural land use alterations are critical for planning crop management strategies, water resources management, and environmental evaluations. However, accurate estimation and evaluation of these hydrological responses are restricted by the limited availability of detailed crop classification in land use and land cover. An innovative approach using state-of-the-art Variable Infiltration Capacity (VIC) model is utilized by setting up the crop-specific vegetation parameterization and analyse the effect of uniform and heterogeneous agricultural land use over the hydrological responses of the basin, in the Kangsabati River Basin (KRB). Thirteen year simulations (1998–2010) based on two different scenarios i.e., single-crop in agricultural land use (SC-ALU) and multi-crop in agricultural land use (MC-ALU) patterns are incorporated in the model and calibrated (1998–2006) and validated (2007–2010) for the streamflow at Reservoir and Mohanpur in the KRB. The results demonstrated that the VIC model improved the estimates of hydrological components, especially surface runoff and evapotranspiration (ET) at daily and monthly timescales corresponding to MC-ALU than SC-ALU (NSC > 0.7). Grid-scale ET estimates are improved after incorporating heterogeneous agricultural land use (NSC > 0.55 and R2 > 0.55) throughout the period of 1998–2010. This study improves our understanding on how the change in agricultural land use in the model settings alters the basin hydrological characteristics, and to provide model-based approaches for best management practices in irrigation scheduling, crop water requirement, and management strategies in the absence of flux towers, eddy covariance, and lysimeters in the basin.

ACS Style

Ankur Srivastava; Nikul Kumari; Minotshing Maza. Hydrological Response to Agricultural Land Use Heterogeneity Using Variable Infiltration Capacity Model. Water Resources Management 2020, 34, 3779 -3794.

AMA Style

Ankur Srivastava, Nikul Kumari, Minotshing Maza. Hydrological Response to Agricultural Land Use Heterogeneity Using Variable Infiltration Capacity Model. Water Resources Management. 2020; 34 (12):3779-3794.

Chicago/Turabian Style

Ankur Srivastava; Nikul Kumari; Minotshing Maza. 2020. "Hydrological Response to Agricultural Land Use Heterogeneity Using Variable Infiltration Capacity Model." Water Resources Management 34, no. 12: 3779-3794.

Research letter
Published: 24 July 2020 in Geophysical Research Letters
Reads 0
Downloads 0

Our current understanding of semiarid ecosystems is that they tend to display higher vegetation greenness on polar‐facing slopes (PFS) than on equatorial‐facing slopes (EFS). However, recent studies have argued that higher vegetation greenness can occur on EFS during part of the year. To assess whether this seasonal reversal of aspect‐driven vegetation is a common occurrence, we conducted a global‐scale analysis of vegetation greenness on a monthly time scale over an 18‐year period (2000‐2017). We examined the influence of climate seasonality on the normalized difference vegetation index (NDVI) values of PFS and EFS at 60 different catchments with aspect‐controlled vegetation located across all continents except Antarctica. Our results show that an overwhelming majority of sites (70%) display seasonal reversal, associated with transitions from water‐limited to energy‐limited conditions during wet winters. These findings highlight the need to consider seasonal variations of aspect‐driven vegetation patterns in ecohydrology, geomorphology, and Earth system models.

ACS Style

Nikul Kumari; Patricia M. Saco; Jose F. Rodriguez; Samuel A. Johnstone; Ankur Srivastava; Kwok P. Chun; Omer Yetemen. The Grass Is Not Always Greener on the Other Side: Seasonal Reversal of Vegetation Greenness in Aspect‐Driven Semiarid Ecosystems. Geophysical Research Letters 2020, 47, 1 .

AMA Style

Nikul Kumari, Patricia M. Saco, Jose F. Rodriguez, Samuel A. Johnstone, Ankur Srivastava, Kwok P. Chun, Omer Yetemen. The Grass Is Not Always Greener on the Other Side: Seasonal Reversal of Vegetation Greenness in Aspect‐Driven Semiarid Ecosystems. Geophysical Research Letters. 2020; 47 (15):1.

Chicago/Turabian Style

Nikul Kumari; Patricia M. Saco; Jose F. Rodriguez; Samuel A. Johnstone; Ankur Srivastava; Kwok P. Chun; Omer Yetemen. 2020. "The Grass Is Not Always Greener on the Other Side: Seasonal Reversal of Vegetation Greenness in Aspect‐Driven Semiarid Ecosystems." Geophysical Research Letters 47, no. 15: 1.

Journal article
Published: 06 July 2020 in Science of The Total Environment
Reads 0
Downloads 0

Spatial-temporal information of different water resources is essential to rationally manage, sustainably develop, and optimally utilize water. This study focused on simulating future water footprint (WF) of two agronomically important crops (i.e., wheat and maize) using deep neural networks (DNN) method in Nile delta. DNN model was calibrated and validated by using 2006–2014 and 2015–2017 datasets. Moreover, future data (2022–2040) were obtained from three Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5, and incorporated into DNN prediction set. The findings showed that determination-coefficient between historical-predicted crop evapotranspiration (ETc) varied from 0.92 to 0.97 for two crops. The yield prediction values of wheat-maize deviated within the ranges of −3.21% to 3.47% and −4.93% to 5.88%, respectively. Based on the ensemble of RCP, precipitation was forecasted to decease by 667.40% and 261.73% in winter and summer in western as compared to eastern, respectively, which will ultimately be dropped to 105.02% and 60.87%, respectively parallel to historical. Therefore, the substantial fluctuations in precipitation caused an obvious decrease in green WF of wheat (i.e., 24.96% and 37.44%) in western and eastern, respectively. Additionally, for maize, it induced a 103.93% decrease in western and an 8.96% increase in eastern. Furthermore, increasing ETc by 8.46% and 12.45% gave rise to substantially increasing (i.e., 8.96% and 17.21%) in western for wheat-maize compared to the east, respectively. Likewise, grey wheat-maize WF findings reveals that there was an increase of 3.07% and 5.02% in western as compared to −14.51% and 12.37% in eastern. Hence, our results highly recommend the optimal use of the eastern delta to save blue-water by 16.58% and 40.25% of total requirements for wheat-maize in contrast to others. Overall, the current research framework and results derived from the adopted methodology will help in optimal planning of future water under climate change in the agricultural sector.

ACS Style

Ahmed Elbeltagi; Muhammad Rizwan Aslam; Anurag Malik; Behrouz Mehdinejadiani; Ankur Srivastava; Amandeep Singh Bhatia; Jinsong Deng. The impact of climate changes on the water footprint of wheat and maize production in the Nile Delta, Egypt. Science of The Total Environment 2020, 743, 140770 .

AMA Style

Ahmed Elbeltagi, Muhammad Rizwan Aslam, Anurag Malik, Behrouz Mehdinejadiani, Ankur Srivastava, Amandeep Singh Bhatia, Jinsong Deng. The impact of climate changes on the water footprint of wheat and maize production in the Nile Delta, Egypt. Science of The Total Environment. 2020; 743 ():140770.

Chicago/Turabian Style

Ahmed Elbeltagi; Muhammad Rizwan Aslam; Anurag Malik; Behrouz Mehdinejadiani; Ankur Srivastava; Amandeep Singh Bhatia; Jinsong Deng. 2020. "The impact of climate changes on the water footprint of wheat and maize production in the Nile Delta, Egypt." Science of The Total Environment 743, no. : 140770.

Preprint content
Published: 23 March 2020
Reads 0
Downloads 0

Aspect-controlled vegetation over opposing hillslopes are driven by non-uniform distribution of incoming solar radiation in semi-arid ecosystems. This leads to variation in soil and vegetation characteristics. In mid- to high-latitudes where available soil moisture is a limiting factor for vegetation growth, poleward-facing slopes develop denser vegetation cover providing greater erosion protection than the equatorward-facing hillslopes. The variation in erosion rates across opposing hillslopes leads to the development of topographic asymmetry of hillslopes over long timescales. This asymmetry is quantified by the hillslope asymmetry index (HAI), a metric given as the ratio of the median slope angles of opposite hillslopes. We present a combined approach of modelling and observed data analysis to investigate the relationships of HAI with climatological, geomorphic, and ecologic variables at a global scale. We analysed these relationships using digital elevation topographic data to compute observed HAI for 80 different catchments across the world, where aspect-controlled vegetation has been reported in the literature. Further, we used the CHILD landscape evolution model (LEM), which uses the continuity equation for water, sediment, and biomass, to investigate the control of climatological, geomorphic, and ecologic variables on the development of hillslope asymmetry through a modelling approach,. The outcomes of the study highlights that latitude and mean topographic gradient are the two dominant factors affecting hillslope asymmetry due to their vital role in controlling vegetation density through the modulation of incoming solar radiation. These results improve our understanding on how different climatic variables and geographic properties affect the magnitude of hillslope asymmetry and their implications on landform evolution modelling.

ACS Style

Nikul Kumari; Omer Yetemen; Ankur Srivastava; Jose F. Rodriguez; Patricia M. Saco. Observations and Modelling Results Help to Understand Global Hillslope Asymmetry. 2020, 1 .

AMA Style

Nikul Kumari, Omer Yetemen, Ankur Srivastava, Jose F. Rodriguez, Patricia M. Saco. Observations and Modelling Results Help to Understand Global Hillslope Asymmetry. . 2020; ():1.

Chicago/Turabian Style

Nikul Kumari; Omer Yetemen; Ankur Srivastava; Jose F. Rodriguez; Patricia M. Saco. 2020. "Observations and Modelling Results Help to Understand Global Hillslope Asymmetry." , no. : 1.

Preprint content
Published: 09 March 2020
Reads 0
Downloads 0

Topography plays an important role in controlling the amount and the spatial distribution of precipitation due to orographic lift mechanisms. Thus, it affects the existing climate and vegetation distribution. Recent landscape modelling efforts show how the orographic effects on precipitation result in the development of asymmetric topography. However, these modelling efforts do not include vegetation dynamics that inhibits sediment transport. Here, we use the CHILD landscape evolution model (LEM) coupled with a vegetation dynamics component that explicitly tracks above- and below-ground biomass. We ran the model under three scenarios. A spatially‑uniform precipitation scenario, a scenario with increasing rainfall as a function of elevation, and another one that includes rain shadow effects in which leeward hillslopes receive less rainfall than windward ones. Preliminary results of the model show that competition between increased shear stress due to increased runoff and vegetation protection affects the shape of the catchment. Hillslope asymmetry between polar- and equator-facing hillslopes is enhanced (diminished) when rainfall coincides with a windward (leeward) side of the mountain range. It acts to push the divide (i.e., the boundary between leeward and windward flanks) and leads to basin reorganization through reach capture. Our findings suggest that there exists a strong coupling between climate and landform evolution processes, and that orographic precipitation can imprint its influence on landforms in semi-arid ecosystems.  

ACS Style

Ankur Srivastava; Omer Yetemen; Nikul Kumari; Patricia M. Saco. Influence of orographic precipitation on the co-evolution of landforms and vegetation. 2020, 1 .

AMA Style

Ankur Srivastava, Omer Yetemen, Nikul Kumari, Patricia M. Saco. Influence of orographic precipitation on the co-evolution of landforms and vegetation. . 2020; ():1.

Chicago/Turabian Style

Ankur Srivastava; Omer Yetemen; Nikul Kumari; Patricia M. Saco. 2020. "Influence of orographic precipitation on the co-evolution of landforms and vegetation." , no. : 1.

Article
Published: 13 December 2019 in Water Resources Management
Reads 0
Downloads 0

Estimation of terrestrial water budget at global and regional scales are essential for efficient agricultural water management, flood predictions, and, hydrological modeling. In hydrological modeling, it is a challenging task to quantify the major hydrological components like runoff, evapotranspiration (ET), and total water storage (TWS) due to improper and limited availability of detailed meteorological datasets. Furthermore, there has been no consensus to answer a-decade-long critical question that a less data-intensive models can be an alternate to robust data-intensive models in data scarce conditions. This study aims at multi-model approach over the single models usage for representing the hydrological behaviour in the Kangsabati River Basin (KRB), India. It is done by applying the standard model selection criteria over various hydrological models. Two hydrological models are selected, a semi- distributed model, Variable Infiltration Capacity (VIC-3 L), and a conceptually lumped model, Identification of unit Hydrograph and Component flows from Rainfall, Evapotranspiration and Streamflow (IHACRES). Both models were calibrated against the observed daily discharge at the KRB outlet for the period of 2001–2006 and validated for 2008–2010. The results show that both VIC-3 L and IHACRES produce reasonable runoff estimates at daily and monthly time scale in the KRB. The ET estimates show that VIC-3 L and IHACRES captured the seasonal variations with the percent change of 0.4% and 6.6% respectively. As IHACRES is simpler, parsimonious, fewer parameters, and better performances, it can be useful for hydrological modeling in data-scarce regions.

ACS Style

Ankur Srivastava; Proloy Deb; Nikul Kumari. Multi-Model Approach to Assess the Dynamics of Hydrologic Components in a Tropical Ecosystem. Water Resources Management 2019, 34, 327 -341.

AMA Style

Ankur Srivastava, Proloy Deb, Nikul Kumari. Multi-Model Approach to Assess the Dynamics of Hydrologic Components in a Tropical Ecosystem. Water Resources Management. 2019; 34 (1):327-341.

Chicago/Turabian Style

Ankur Srivastava; Proloy Deb; Nikul Kumari. 2019. "Multi-Model Approach to Assess the Dynamics of Hydrologic Components in a Tropical Ecosystem." Water Resources Management 34, no. 1: 327-341.

Full length research article
Published: 27 November 2019 in Agricultural Research
Reads 0
Downloads 0

Evapotranspiration (ET) is one of the important components of the hydrological cycle which is essential for sustainable water resource management and ecohydrological studies. Accurate estimation of ET is a crucial task in data-scarce regions due to limited meteorological variables. There exist a number of indirect methods among which the standard method for computing ET is FAO-56-Penman–Monteith (PM) method. However, due to paucity of flux data such as the components of net radiation, relative humidity, vapour pressure, and wind speed in many parts of the world, the use of standard benchmark method is limited. This limitation provides the widespread acceptance of the method which uses fewer variables and can give an accurate estimation of ET for water resource management. In this study, we have developed a framework to standardize the Hargreaves-based ET in the Kangsabati River basin. We utilize the weather datasets from six stations, namely Purulia, Bankura, Mohanpur, Jhargram, Kharagpur, and Midnapore to apply the ET standardization method. We have compared both the raw and corrected ET from Hargreaves with FAO-56-PM ET prior and after correction by using harmonization method. Performance evaluation of harmonization technique is done using statistical and graphical indicators for the duration of 2006–2010. It is observed that Purulia (r = 0.83 and d = 0.80) and Mohanpur (r = 0.85 and d = 0.87) stations are almost standardized appropriately on daily scale. Further, the highest r and R2 was obtained for Mohanpur station (r = 0.972; d = 0.940), while least for Jhargram station (r = 0.961; d = 0.741) at monthly scale. Overall, this approach can be used to provide the utility in data-scarce conditions irrespective of agro-climatic conditions.

ACS Style

Nikul Kumari; Ankur Srivastava. An Approach for Estimation of Evapotranspiration by Standardizing Parsimonious Method. Agricultural Research 2019, 9, 301 -309.

AMA Style

Nikul Kumari, Ankur Srivastava. An Approach for Estimation of Evapotranspiration by Standardizing Parsimonious Method. Agricultural Research. 2019; 9 (3):301-309.

Chicago/Turabian Style

Nikul Kumari; Ankur Srivastava. 2019. "An Approach for Estimation of Evapotranspiration by Standardizing Parsimonious Method." Agricultural Research 9, no. 3: 301-309.

Original paper
Published: 30 July 2018 in Irrigation Science
Reads 0
Downloads 0

Computation of reference evapotranspiration (ETO) at different spatiotemporal scales is constrained by limited in situ meteorological data availability which, in turn, led to alternate ET estimation methods using the commonly available meteorological data of maximum and minimum temperatures. In this study, the Hargreaves–Samani model and the water budget approach of the Variable Infiltration Capacity (VIC-3L) land surface model was evaluated for grid-scale actual ET estimation using the benchmark FAO-56 Penman–Monteith (PM) equation and crop coefficient relationships. These approaches were field-tested in the Kangsabati River basin in eastern India, a tropical monsoon-type climate region with dominant paddy land uses. The results revealed that the VIC model could estimate the grid-scale ET reasonably well; however, the corresponding estimates by the Hargreaves method were highly overestimated. To enhance the field applicability of the Hargreaves method for data-scarce regions, this method was coupled with a genetic algorithm-based bias correction approach that improved the Nash–Sutcliffe efficiency significantly. Hence, this study reveals that there is a need for regional-scale standardization of the Hargreaves ET estimates using the FAO-56 PM, lysimeter data or the VIC-3L model.

ACS Style

Ankur Srivastava; Bhabagrahi Sahoo; Narendra Singh Raghuwanshi; Chandranath Chatterjee. Modelling the dynamics of evapotranspiration using Variable Infiltration Capacity model and regionally calibrated Hargreaves approach. Irrigation Science 2018, 36, 289 -300.

AMA Style

Ankur Srivastava, Bhabagrahi Sahoo, Narendra Singh Raghuwanshi, Chandranath Chatterjee. Modelling the dynamics of evapotranspiration using Variable Infiltration Capacity model and regionally calibrated Hargreaves approach. Irrigation Science. 2018; 36 (4-5):289-300.

Chicago/Turabian Style

Ankur Srivastava; Bhabagrahi Sahoo; Narendra Singh Raghuwanshi; Chandranath Chatterjee. 2018. "Modelling the dynamics of evapotranspiration using Variable Infiltration Capacity model and regionally calibrated Hargreaves approach." Irrigation Science 36, no. 4-5: 289-300.

Journal article
Published: 01 August 2017 in Journal of Irrigation and Drainage Engineering
Reads 0
Downloads 0

With the limited availability of meteorological variables in many remote areas, estimation of evapotranspiration (ET) at different spatiotemporal scales for efficient irrigation water management and hydrometeorological studies is becoming a challenging task. Hence, in this study, indirect ET estimation methods, such as moderate resolution imaging spectroradiometer (MODIS) satellite-based remote-sensing techniques and the water-budget approach built into the semidistributed variable infiltration capacity (VIC-3L) land-surface model are evaluated using the Penman-Monteith (PM) equation approach suggested in the literature together with a crop coefficient approach. To answer the research question of whether regional or local controls of a river basin with tropical monsoon-type climatology affect the accuracy of the VIC and MODIS-based ET estimates, these methodologies are applied in the Kangsabati River Basin in eastern India at 25×25 km resolutions attributed with dominant paddy land uses. The results reveal that the VIC-estimated ET values are reasonably matched with the PM-based ET estimates with the Nash-Sutcliffe efficiency (NSE) of 54.14–71.94%; however, the corresponding MODIS-ET values are highly underestimated with a periodic shift that may be attributed to the cloud cover and leaf shadowing effects. To enhance the field applicability of the satellite-based MODIS-ET products, these estimates are standardized by using a genetic-algorithm-based transformation that improves the NSE from −390.83 to 99.57%. Hence, this study reveals that there is the need of a regional-scale standardization of the MODIS-ET products using the PM or lysimeter data or possible modification of the MOD16A2 algorithm built-into the MODIS for generalization. Conversely, the satisfactory grid-scale ET estimates by the VIC model show that this model could be reliably used for the world’s river basins; however, at smaller temporal scales, the estimates could be slightly inconsistent.

ACS Style

Ankur Srivastava; Bhabagrahi Sahoo; Narendra Singh Raghuwanshi; Rajendra Singh. Evaluation of Variable-Infiltration Capacity Model and MODIS-Terra Satellite-Derived Grid-Scale Evapotranspiration Estimates in a River Basin with Tropical Monsoon-Type Climatology. Journal of Irrigation and Drainage Engineering 2017, 143, 04017028 .

AMA Style

Ankur Srivastava, Bhabagrahi Sahoo, Narendra Singh Raghuwanshi, Rajendra Singh. Evaluation of Variable-Infiltration Capacity Model and MODIS-Terra Satellite-Derived Grid-Scale Evapotranspiration Estimates in a River Basin with Tropical Monsoon-Type Climatology. Journal of Irrigation and Drainage Engineering. 2017; 143 (8):04017028.

Chicago/Turabian Style

Ankur Srivastava; Bhabagrahi Sahoo; Narendra Singh Raghuwanshi; Rajendra Singh. 2017. "Evaluation of Variable-Infiltration Capacity Model and MODIS-Terra Satellite-Derived Grid-Scale Evapotranspiration Estimates in a River Basin with Tropical Monsoon-Type Climatology." Journal of Irrigation and Drainage Engineering 143, no. 8: 04017028.