Subashisa Dutta

Evapotranspiration using MODIS data and limited ground observations over selected agroecosystems in India

Plant growth processes and productivity of agroecosystems depend highly on evapotranspiration from the land (soil‐crop cover complex) surface. A study was carried out using MODIS TERRA optical and thermal band data and ground observations to estimate evaporative fraction and daily actual evapotranspiration (AET) over agroecosystems in India. Five study regions, each covering a 10 km×10 km area falling in agricultural land use, were selected for ground observations at a time closest to TERRA overpasses. The data on radiation and crop parameters in paddy (irrigated and rainfed), cotton (rainfed), groundnut (residual moisture) crops were recorded at 14‐day intervals between August 2003 to January 2004 from 2 km×2 km homogeneous crop patches within each study region. Eight MODIS scenes in seven optical (1, 2, 3, 4, 5, 6, 7) and two thermal bands (31, 32) level 1B data acquired from the National Remote Sensing Agency, Hyderabad, India and resampled at 1 km, were used to generate surface albedo (α), land surface temperature (T s, MODIS) and emissivity (εs). Evaporative fraction and daily AET were generated using a single source energy balance approach with (i) ground based observations only (‘stand alone’ approach), and (ii) ‘fusion’ of MODIS derived land surface variables on cloud free dates and coincident ground observations. Land cover classes were assigned using a hierarchical decision rule applied to multi‐date Normalized Difference Vegetation Index (NDVI). The exponential model could be fitted between 1‐EFins, ground (ground based evaporative fraction) and difference between T s, MODIS and air temperature (T a) with R 2 = 0.77. Linear fit (R 2 = 0.74) could be obtained between 1‐EFins, ground and temperature vegetation dryness index (TVDI), derived from T s, MODIS‐NDVI triangle. Energy balance daily AET from the ‘fusion’ approach was found to deviate from water balance AET by between 4.3% to 24.5% across five study sites with a mean deviation of 11.6%. The root mean square error (RMSE) from the energy balance AET was found to be 8% of the mean water balance AET. The satellite based energy balance approach can be used to generate spatial AET, but needs more refinements before operational use in the light of progress in algorithms and their validation with huge datasets.

Impact of climate change on flood characteristics in Brahmaputra basin using a macro-scale distributed hydrological model

Being the highest specific discharge river system in the world, the Brahmaputra river experiences a number of long-duration flood waves during the monsoon season annually. In order to assess the flood characteristics at the basin and tributary scales, a physically based macro-scale distributed hydrological model (DHM) has been calibrated and validated for 9 wet years. The model performance has been evaluated in terms of prediction of the flood characteristics such as peak discharge, flood duration, arrival time of flood wave, timing of the peak flow and number of flood waves per season. Future changes in the flood wave characteristics of the basin have been evaluated using the validated model with bias-corrected future-projected meteorological scenario from a regional climate model (RCM). Likelihood analysis of the simulated flow time series reveals that significant increase in both peak discharge and flood duration is expected for both the pre-monsoonal and monsoonal seasons in the basin, but the number of flood waves per season would be reduced. Under the projected climate change scenario, it is expected that there will be more catastrophic floods in the basin.

Field Investigation and Modeling of Rapid Subsurface Stormflow through Preferential Pathways in a Vegetated Hillslope of Northeast India

A conceptual model for rapid lateral subsurface flow under extreme storm events in wet vegetated hillslopes with a high preferential flow network is presented. The kinematic form of Darcy’s equation and a continuity equation with a sink term to account for lateral preferential flow are used to formulate a subsurface flow equation. The resulting equation is numerically solved using a finite difference approximation. The physical parameters of the model are derived from field experiments conducted in a hillslope in the Brahmaputra River basin of India. Apart from capturing the rapid buildup and recession of a saturated profile in the hillslope, the model gives an indication of hydrologically active lateral macroporosity and its dependency on the rate of recharge. The computed flow hydrographs showed that for the hillslope under investigation, the rapid subsurface storm response is primarily controlled by lateral preferential flow.

Water Level Retrieval Using SARAL/AltiKa Observations in the Braided Brahmaputra River, Eastern India

In this study, water level retrieval over the Brahmaputra river was done using different retracking algorithms for the 40 Hz waveform data of SARAL/AltiKa satellite. Water level was retrieved at 10 different locations of the river to evaluate the performance and accuracy of Ka band altimeter over the braided river system. Different retracking algorithms such as ice-1, ice-2, threshold, and beta parameter were used to retrieve water levels. A correlation and error analysis between the in-situ and satellite altimetry derived river levels was carried out for all the stations. Performance and accuracy analysis has established that water level can be retrieved with less than 40 cm root mean square error (RMSE) for most of the braided reaches of the river. The statistical analysis have found that Beta parameter algorithm has performed best in most of the cases amongst the different retracking algorithms used in this study. The water levels derived from 10 different locations were used to generate water surface elevation profiles for the monsoon and nonmonsoon periods. The water levels and the water surface profiles derived from satellite altimetry indicate the potential use of altimeters for the parameterization and calibration of river hydrological, hydrodynamic and sediment transport models.

Predictive Capability of Bedload Equations Using Flume Data

Predictive Capability of Bedload Equations Using Flume Data The study on bedload transport behaviour is widely explored from the last few decades and many semiempirical or empirical equilibrium transport equations are developed. The phenomenon is a very complex due to its varied physical properties like velocity, depth, slope, particle size in the alluvial system. In practical applications, these formulae have appreciable deviation from each other in derivation and also their ranges of applications are different. Here, bedload transports have been categorized into moderate bedload transport and intense bedload transport depending upon the Einstein bedload transport parameter. Based on large database of different bedload measurements, a comparative analysis has been performed to ascertain prediction ability of different bedload equations based on various statistical criteria such as the coefficient of determination, Nash-Sutcliffe coefficient and index of agreement. It has been found that equations based on shear stress have worked better than other approaches (discharge, probabilistic and regression) for flume observations. Presnosť Rovníc Transportu Splavenín s Využitím Údajov z Hydraulického Žľabu Výskum transportu splavenín počas posledného obdobia bol relatívne intenzívny; jeho výsledkom bolo množstvo empirických a poloempirických rovníc kvantifikujúcich rovnovážny transport splavenín. Je to zložitá problematika; je to tak v dôsledku meniacich sa fyzikálnych vlastností ako je rýchlosť, hĺbka, sklon, zrnitostné zloženie splavenín v aluviálnom systéme. Výsledky výpočtu z týchto rovníc sa významne líšia a líši sa tiež oblasť ich možnej aplikácie. V tejto štúdii je transport splavenín rozdelený na priemerný a intenzívny, podľa Einsteinovho parametra transportu splavenín. S využitím štatistických metód sme uskutočnili komparatívnu analýzu presnosti rozdielnych rovníc transportu splavenín. Pri analýze bola použitá rozsiahla databáza výsledkov meraní. Výsledkom je, že rovnice založené na informácii o tangenciálnom napätí dávajú lepšie výsledky ako tie, ktoré využívajú pre výpočet transportu splavenín prietoky, pravdepodobnostný prístup a regresie.

Mapping monsoonal soil wetness regions from multi‐temporal VEGETATION dataset

Using the temporal and multi‐spectral signature of the soil wetness regions formed by monsoon storms in Indian river catchments, an analysis of time‐series VEGETATION images is proposed here to map the wetness regions and their spatial distribution for 1999, 2000 and 2001. The spatial distribution of the mapped regions was then compared with the corresponding distribution of topographic index range in 41 watersheds of the River Mahanadi. The comparison shows that there was a significant relationship (n = 41, r 2 = 0.65) between the two. Extending the same analysis for all other Indian river catchments, similar relationships were obtained, except in the Brahmaputra catchment, where the temporal and spatial patterns of monsoon storms are different from those of the other river catchments.

Using satellite-based soil moisture to detect and monitor spatiotemporal traces of agricultural drought over Bundelkhand region of India

Detection and monitoring of seasonal agricultural drought at sub-regional scale is a complex theme due to inefficient spatiotemporal indicators. This study presents a new time-based function of spaceborne soil moisture as an efficient indicator. Bundelkhand of Central India, a frequently agricultural drought affected region, was used as the study area. Rabi agricultural season (October–May) being the dominant agricultural return period, was chosen as the study period. Coarse resolution soil moisture (SMc) obtained from European space agency under climate change initiative program was spatially downscaled (SMd) to meet spatial scale at sub-regional level with overall root-mean-square error under 0.065 cm3/cm3. Indirect validation of SMd was done using temporal impact of rainfall/dry spell on SMd and spatiotemporal impact of SMd on vegetation condition. SMd was found to agree with phenomenon as expected in natural processes and hence it was assumed to be validated. The time-based function derived from spatiotemporal SMd (FSMs) was found to be better related with fluctuations in seasonal crop yield (Ys) at district level as compared to a similar function (FVCIs) derived using vegetation condition index (VCI) from Moderate Resolution Imaging Spectroradiometer. FSMs outperformed FVCIs having better correlation coefficient (R ≥0.8) and Nash–Sutcliffe efficiency coefficient (NSE) than FVCIs for most of the districts. Unlike FVCIs, it also efficiently detected the lowest and highest Ys for majority of the districts representing better association with agricultural drought. Subsequently, frequent soil moisture deficit areas were mapped by using FSMs to visualize the spatiotemporal severity of agricultural drought in the region during Rabi season.

Prediction of Short-Term Morphological Change in Large Braided River Using 2D Numerical Model

AbstractPrediction of annual changes in braided-river morphology is important to assess the performance of river-training works and channel navigability. A two-dimensional (2D) depth-averaged numerical model was used for a 12-km-long reach of the Brahmaputra River in India. Major issues addressed in the modeling included approximation of boundary conditions, design of a flood hydrograph, and evaluation of river morphology. Simulated flow depth and velocity were calibrated with the observed data under bankfull discharge conditions, and predicted bed levels were validated with observed bed levels during low-flow conditions. The model predictions of thalweg shifting for two consecutive flood seasons agreed well with observed changes obtained from satellite imagery. The calibrated model was subsequently used to assess morphological changes in different groyne fields. The best groyne field was determined based on overall performance in scouring, deposition, channel alignment, and dredging volume.

Evaluation of satellite-altimetry-derived river stage variation for the braided Brahmaputra River

In this study, river stage variation derived from satellite altimetry was used to assess the water level, monthly discharge, and annual water yield at six virtual gauging stations at the braided reaches of the Brahmaputra River. The braided reaches of the river dynamically change their planform, thalweg line, and aggradation or degradation period. Stage records derived from the Envisat satellite of the European Space Agency and Topex/Poseidon of NASA/CNES were used for the period 2002–2010. Spatial interpolation and datum correction were applied on altimetry-derived river stage records before analysis. A correlation and error analysis between the in situ and satellite-altimetry-derived stages was carried out for these stations for both monsoon and non-monsoon seasons. Yearly optical satellite images were used for qualitative assessment of temporal variations in aggradation/degradation phases at the gauging stations. Using the pseudo-rating curve, discharges at two virtual gauging stations were estimated. The results show that the altimetry-estimated discharges are of good agreement with observed discharge for the monsoon months (June–September) as compared with the non-monsoon months (October–May). In order to assess the annual water yield variability, yearly variation in annual water yield from the altimetry data was also estimated and compared to that observed. The estimated annual water yields were 90% accurate. Similarly, the long-term averaged monthly discharge series estimated from satellite altimetry closely follows the temporal trend of that of the observed series.

Vegetation Dynamics from Denoised NDVI Using Empirical Mode Decomposition

A novel approach to study vegetation dynamics is introduced, using the Empirical Mode Decomposition (EMD) to analyze NDVI time series. The NDVI time series which is nonlinear and nonstationary can be decomposed by EMD into components called intrinsic mode functions (IMFs), based on inherent temporal scales. The highest frequency component which has been found to represent noise is subtracted from the original NDVI series; thus smoothing the noisy signal. The different key features describing vegetation phenology have been extracted by analyzing the noise free signal. The lowest frequency component (last IMF) is the trend in the NDVI series. The trend in the series has been identified finding the Sen’s slope of last IMF, and the non-parametric seasonal Mann–Kendall test has been used to confirm the significance of the observed trend. The method has been applied on per–pixel basis to the SPOT Vegetation NDVI product covering Northeast India and surrounding regions for the time span of 1998–2009. Results show that the method has performed well in identifying the pixel clusters with significant trends. Hotspot regions with severe vegetation degeneration have been identified, and the relationship of the observed trends with the expected causative variables such as land use and land cover, topographic relief, and anthropogenic causes has been explored. The spatial locations of these critical regions closely matches with the findings of the previous studies carried out locally in the region, mainly indicating the shifting cultivation practice to be the main cause for land cover change.