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Dive into the research topics where Nidhi Nagabhatla is active.

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Featured researches published by Nidhi Nagabhatla.


European Journal of Remote Sensing | 2012

Assessment and change analyses (1987–2002) for tropical wetland ecosystem using earth observation and socioeconomic data

Nidhi Nagabhatla; C. Max Finlayson; Sonali Seneratna Sellamuttu

Abstract The two components of the study reflect assessment and change analysis of a tropical wetland in Sri Lanka. The first section explains spatial classification using pixel level-disaggregated image analysis and refined aggregated image analysis and comparison of information extracted by all methods to analyse a better classifier. The second section illustrates change analysis calibrating the land change modeller (LCM) [IDRISI-Andes]. Key observations: a) visual interpretation provides comprehensive blueprint of the wetlandscape compared to supervised and unsupervised classifiers b) change in landscape pattern reflect substantial transition in wetland use. Validation using field coordinates and socioeconomic data showed kappa value (%) of 87.


Journal of Environmental Management | 2015

LCLUC as an entry point for transdisciplinary research – Reflections from an agriculture land use change study in South Asia

Nidhi Nagabhatla; Martina Padmanabhan; Peter Kühle; Suma Vishnudas; Lydia Betz; Bastian Niemeyer

This article highlights applied understanding of classifying earth imaging data for land cover land use change (LCLUC) information. Compared to the many previous studies of LCLUC, the present study is innovative in that it applied geospatial data, tools and techniques for transdisciplinary research. It contributes to a wider discourse on practical decision making for multi-level governance. Undertaken as part of the BioDIVA project, the research adopted a multi-tiered methodical approach across three key dimensions: socioecology as the sphere of interest, a transdisciplinary approach as the disciplinary framework, and geospatial analysis as the applied methodology. The area of interest was the agroecosystem of Wayanad district in Kerala, India (South Asia). The methodology was structured to enable analysis of multi-scalar and multi-temporal data, using Wayanad as a case study. Three levels of analysis included: District (Landsat TM-30m), Taluk or sub-district (ASTER-15m) and Village or Gram Panchayat (GeoEye-0.5m). Our hypothesis, that analyzing patterns of land use change is pertinent for up-to-date assessment of agroecosystem resources and their wise management is supported by the outcome of the multi-tiered geospatial analysis. In addition, two examples from the project that highlight the adoption of LCLUC by different disciplinary experts are presented. A sociologist assessed the land ownership boundary for a selected tribal community. A faunal ecologist used it to assess the effect of landscape structure on arthropods and plant groups in rice fields. Furthermore, the Google Earth interface was used to support the overall validation process. Our key conclusion was that a multi-level understanding of the causes, effects, processes and mechanisms that govern agroecosystem transformation requires close attention to spatial, temporal and seasonal dynamics, for which the incorporation of local knowledge and participation of local communities is crucial.


Advances in Meteorology | 2015

Impacts of the Two Biggest Lakes on Local Temperature and Precipitation in the Yellow River Source Region of the Tibetan Plateau

Lijuan Wen; Shihua Lv; Zhaoguo Li; Lin Zhao; Nidhi Nagabhatla

The Tibetan Plateau harbors thousands of lakes; however few studies focus on impacts of lakes on local climate in the region. To investigate and quantify impacts of the two biggest lakes (Ngoring Lake and Gyaring Lake) of the Yellow River source region in the Tibetan Plateau on local climate, two simulations (with and without the two large lakes) from May 2010 to July 2011 are performed and analyzed using the WRF-CLM model (the weather research and forecasting model coupled with the community land model). Differences between simulated results show that the WRF-CLM model could provide realistic reproduction of surface observations and has better simulation after considering lakes. Lakes mostly reduce the maximum temperature all year round and increase the minimum temperature except in March due to the large heat capacity that makes lakes absorb (release) more energy for the same temperature change compared to land. Lakes increase precipitation over the lake area and in the nearby region, mostly during 02–14 BT (Beijing Time) of July to October when the warm lake surface induces the low level horizontal convergence and updraft over lake and provides energy and vapor to benefit the development of the convection for precipitation.


Journal of International Wildlife Law & Policy | 2012

The Ramsar Convention's Wise Use Concept in Theory and Practice: An Inter-Disciplinary Investigation of Practice in Kolleru Lake, India

Sonali Senaratna Sellamuttu; Sanjiv de Silva; Nidhi Nagabhatla; C. Max Finlayson; Chiranjibi Pattanaik; Narendra Prasad

The Ramsar Conventions Wise Use Concept in Theory and Practice: An Inter-Disciplinary Investigation of Practice in Kolleru Lake, India Sonali Senaratna Sellamuttu a , Sanjiv de Silva b , Nidhi Nagabhatla c , C. Max Finlayson d , Chiranjibi Pattanaik e & Narendra Prasad e a International Water Management Institute (IWMI) b Institutional and Policy Analysis, International Water Management Institute (IWMI) c APEC Climate Centre d Institute for Land, Water and Society, Charles Sturt University e Salim Ali Centre for Ornithology and Natural History (SACON)


Agricultural and Food Science | 2017

Impacts of temperature and rainfall variation on rice productivity in major ecosystems of Bangladesh

Abiar Rahman; Suchul Kang; Nidhi Nagabhatla; Robert Macnee

BackgroundInconsistency in climate regimes of rainfall and temperature is a source of biotic and abiotic stresses in agricultural systems worldwide. Several studies from Bangladesh report that this variability is a cause of poor yield potential and crop failure. This study investigates the impact of temperature and rainfall variation on rice productivity for different ecosystems in Bangladesh. Three ecosystems under investigation include: dry (Rajshahi), terrace (Mymensingh) and coastal (Barisal).ResultsThe terrace ecosystem recorded the highest rainfall, followed by coastal and dry ecosystems. The temperature variation, both maximum and minimum, showed an increasing trend; however, the incremental rate was higher in case of minimum temperature. Monsoon rainfall showed an increasing trend, while dry season (November to March) decreased slightly. The climatic variations and impacts were captured using a standardized precipitation index (SPI), diurnal temperature range (DTR) and rice productivity index (RPI). The rainfed rice crop (aman) observed a significant trend between RPI and seasonal SPI, and between RPI and seasonal DTR. Overall, the SPI indicated the prevalence of frequent dry and wet periods and DTR recorded a decreasing trend. The multiple regression analysis identified a significant correlation between RPI, SPI and DTR accounting for 41, 45 and 49% of yield variability in dry, terrace and coastal ecosystems, respectively.ConclusionRainfall has shifted with an increasing trend during monsoon and almost static during other seasons. Rice production, especially rainfed rice, is at risk due to frequent drought and decreasing DTR. Stress-tolerant rice varieties requiring less irrigation water and survive at high temperature should be introduced. Research on rescheduling crop calendar and cropping pattern is necessary to mitigate the adverse climatic conditions.


Chinese Journal of Oceanology and Limnology | 2015

Impacts of salinity parameterizations on temperature simulation over and in a hypersaline lake

Lijuan Wen; Nidhi Nagabhatla; Lin Zhao; Zhaoguo Li; Shiqiang Chen

In this paper, we introduced parameterizations of the salinity effects (on heat capacity, thermal conductivity, freezing point and saturated vapor pressure) in a lake scheme integrated in the Weather Research and Forecasting model coupled with the Community Land Model (WRF-CLM). This was done to improve temperature simulation over and in a saline lake and to test the contributions of salinity effects on various water properties via sensitivity experiments. The modified lake scheme consists of the lake module in the CLM model, which is the land component of the WRF-CLM model. The Great Salt Lake (GSL) in the USA was selected as the study area. The simulation was performed from September 3, 2001 to September 30, 2002. Our results show that the modified WRF-CLM model that includes the lake scheme considering salinity effects can reasonably simulate temperature over and in the GSL. This model had much greater accuracy than neglecting salinity effects, particularly in a very cold event when that effect alters the freezing point. The salinity effect on saturated vapor pressure can reduce latent heat flux over the lake and make it slightly warmer. The salinity effect on heat capacity can also make lake temperature prone to changes. However, the salinity effect on thermal conductivity was found insignificant in our simulations.


Current Opinion in Environmental Sustainability | 2015

The role of cultural ecosystem services in landscape management and planning

Tobias Plieninger; Claudia Bieling; Nora Fagerholm; Anja Byg; Tibor Hartel; Patrick T. Hurley; César A. López-Santiago; Nidhi Nagabhatla; Elisa Oteros-Rozas; Christopher M. Raymond; Dan van der Horst; Lynn Huntsinger


International Journal of Applied Earth Observation and Geoinformation | 2015

New vegetation type map of India prepared using satellite remote sensing: Comparison with global vegetation maps and utilities

P. S. Roy; M. D. Behera; M.S.R. Murthy; Arijit Roy; Sarnam Singh; S. P. S. Kushwaha; C.S. Jha; S. Sudhakar; P. K. Joshi; Ch. Sudhakar Reddy; Stutee Gupta; Girish Pujar; C.B.S. Dutt; V.K. Srivastava; M.C. Porwal; Poonam Tripathi; J. S. Singh; V. S. Chitale; Andrew K. Skidmore; G. Rajshekhar; Deepak Kushwaha; Harish Karnatak; Sameer Saran; Amarnath Giriraj; Hitendra Padalia; Manish P. Kale; Subrato Nandy; C. Jeganathan; C.P. Singh; C.M. Biradar


European Journal of Remote Sensing | 2016

Tropical Agrarian landscape classification using high-resolution GeoEYE data and segmentationbased approach

Nidhi Nagabhatla; Peter Kühle


Handbook of Climate Change Adaptation | 2014

Understanding Impacts of Climate Variation in Varied Socio-ecological Domains: A Prerequisite for Climate Change Adaptation and Management

Nidhi Nagabhatla; Sobhan Sahu; Armando Gaetaniello; Lijuan Wen; Wooseop Lee

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Lijuan Wen

Chinese Academy of Sciences

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Lin Zhao

Chinese Academy of Sciences

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Zhaoguo Li

Chinese Academy of Sciences

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Lydia Betz

University of Göttingen

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Shiqiang Chen

Chinese Academy of Sciences

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Abiar Rahman

Bangabandhu Sheikh Mujibur Rahman Agricultural University

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Amarnath Giriraj

International Water Management Institute

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Sanjiv de Silva

International Water Management Institute

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