Brahmaputra Meghna River Basin Research Articles

Strong trade-offs characterise water-energy-food related sustainable development goals in the Ganges–Brahmaputra–Meghna River basin

The United Nations’ sustainable development goals (SDGs) set ambitious policy targets for 2030 to overcome poverty while preserving the planet. These goals are not perfectly aligned; trade-offs emerge during implementation at regional and local levels, such as in a river basin. Here, we quantify important trade-offs between water, energy, and food-related SDGs in the Ganges–Brahmaputra–Meghna River basin, a climate vulnerability hotspot, using multi-objective optimisation based on detailed water resources and crop production modelling and accounting for uncertainties in the costs of water, labour, and land. The trade-off between food production and agricultural profit is strong; the amount of people fed would be reduced by more than two-thirds, were profitability maximized. However, we do see the potential to achieve higher profitability in agriculture against limited loss of food and hydropower production and limited impact on downstream environmental flows, although continued reliance on groundwater and energy, currently unsustainable, needs to be mitigated.

Implications for planning of hydroelectric projects in Northeast India: an analysis of the impacts of the Tipaimukh project

In recent years, while developed countries are decommissioning hydroelectric projects (HEPs)/dams at a higher rate than constructing new ones, developing economies are doing the opposite. Although HEPs are regarded green, renewable and cheap, recent studies reveal that they do more harm than good. The impacts of HEPs are multiple, including socio-economic, environmental and geopolitical. India’s Northeastern (NE) region is a part of the Ganges–Brahmaputra–Meghna river basin, and has immense hydropower potential. A large number of HEPs are planned or under construction in the region, mainly in the hilly states of Arunachal Pradesh, Manipur, Meghalaya, Sikkim and Mizoram. One such mega project is the Tipaimukh multipurpose HEP, to be constructed on the Barak river in the state of Manipur. The project is highly controversial, and is being protested against by the locals, academicians, researchers, social activists, NGOs, as well as Bangladesh. Further, a serious cost–benefit analysis, judicious environmental impact assessment and democratic public hearings have been questioned. The area submergence of the project is disproportionately high compared to other such projects of NE India, and the project site and the adjoining areas form a part of Indo-Burma global biodiversity hotspot. The present study details the impacts of the project from multidisciplinary perspectives, categorized into bio-physical, socio-economic and geopolitical impacts, including impacts on the downstream riparian nation—Bangladesh. Based on the study, we have provided recommendations, if ever the construction of project is actualized. Since there is lack of any such analysis, the present study is of immense significance on the decision making of the project, and paves a guideline for impact analysis of the upcoming large number of projects of the region.

A Hydroclimatological Analysis of Precipitation in the Ganges–Brahmaputra–Meghna River Basin

Understanding seasonal precipitation input into river basins is important for linking large-scale climate drivers with societal water resources and the occurrence of hydrologic hazards such as floods and riverbank erosion. Using satellite data at 0.25-degree resolution, spatial patterns of monsoon (June-July-August-September) precipitation variability between 1983 and 2015 within the Ganges–Brahmaputra–Meghna (GBM) river basin are analyzed with Principal Component (PC) analysis and the first three modes (PC1, PC2 and PC3) are related to global atmospheric-oceanic fields. PC1 explains 88.7% of the variance in monsoonal precipitation and resembles climatology with the center of action over Bangladesh. The eigenvector coefficients show a downward trend consistent with studies reporting a recent decline in monsoon rainfall, but little interannual variability. PC2 explains 2.9% of the variance and shows rainfall maxima to the far western and eastern portions of the basin. PC2 has an apparent decadal cycle and surface and upper-air atmospheric height fields suggest the pattern could be forced by tropical South Atlantic heating and a Rossby wave train stemming from the North Atlantic, consistent with previous studies. Finally, PC3 explains 1.5% of the variance and has high spatial variability. The distribution of precipitation is somewhat zonal, with highest values at the southern border and at the Himalayan ridge. There is strong interannual variability associated with PC3, related to the El Nino/Southern Oscillation (ENSO). Next, we perform a hydroclimatological downscaling, as precipitation attributed to the three PCs was averaged over the Pfafstetter level-04 sub-basins obtained from the World Wildlife Fund (Gland, Switzerland). While PC1 was the principal contributor of rainfall for all sub-basins, PC2 contributed the most to rainfall in the western Ganges sub-basin (4524) and PC3 contributed the most to the rainfall in the northern Brahmaputra (4529). Monsoon rainfall within these two sub-basins were the only ones to show a significant relationship (negative) with ENSO, whereas four of the eight sub-basins had a significant relationship (positive) with sea surface temperature (SST) anomalies in the tropical South Atlantic. This work demonstrates a geographic dependence on climate teleconnections in the GBM that deserves further study.

Mismatched Diplomacy: China–India Water Relations Over the Ganges–Brahmaputra–Meghna River Basin

ABSTRACTThis article sheds light on the nature, forms and outcomes of China’s diplomacy over transboundary water resources. Water diplomacy bears unique and complex features and approaches for forming cooperative partnerships in the contextual settings where it is developed. By surveying the development and effectiveness of water diplomacy, it argues that water diplomacy is unlikely to succeed in conditions where power relations are unstable, or among countries experiencing low economic growth.The Ganges–Brahmaputra–Meghna (GBM) River Basin is examined as a case study. It is noticed that distrust has resulted in the development of complicated dynamics in Sino–Indian water disputes. China has displayed vested interests in its water diplomacy. Not only is the Chinese government seeking economic profits such as through the generation of hydropower, it also seeks to protect its strategic interests through the domination of hydrological data and water policy information. Such strategic interests may obstruct foreign relations unless substantial cooperative water sharing initiatives are implemented. As India has displayed varying interests in the diplomatic process, the outcomes are proving limited and risky. In the absence of substantive collaborative initiatives over water management, the mismatched interests over the GBM Basin have the potential to further strain the already unstable relations between two of the major powers in South Asia.

Assessing regional climate simulations of the last 30 years (1982–2012) over Ganges–Brahmaputra–Meghna River Basin

The Ganges–Brahmaputra–Meghna (GBM) River Basin presents a spatially diverse hydrological regime due to it’s complex topography and escalating demand for freshwater resources. This presents a big challenge in applying the current state-of-the-art regional climate models (RCMs) for climate change impact studies in the GBM River Basin. In this study, several RCM simulations generated by RegCM4.4 and PRECIS are assessed for their seasonal and interannual variations, onset/withdrawal of the Indian monsoon, and long-term trends in precipitation and temperature from 1982 to 2012. The results indicate that in general, RegCM4.4 and PRECIS simulations appear to reasonably reproduce the mean seasonal distribution of precipitation and temperature across the GBM River Basin, although the two RCMs are integrated over a different domain size. On average, the RegCM4.4 simulations overestimate monsoon precipitation by $${\sim }26$$ and $${\sim }5\%$$ in the Ganges and Brahmaputra–Meghna River Basin, respectively, while PRECIS simulations underestimate (overestimate) the same by $${\sim }7\%$$ ( $${\sim }16\%$$ ). Both RegCM4.4 and PRECIS simulations indicate an intense cold bias (up to $$10\,^\circ \hbox {C}$$ ) in the Himalayas, and are generally stronger in the RegCM4.4 simulations. Additionally, they tend to produce high precipitation between April and May in the Ganges (RegCM4.4 simulations) and Brahmaputra–Meghna (PRECIS simulations) River Basins, resulting in early onset of the Indian monsoon in the Ganges River Basin. PRECIS simulations exhibit a delayed monsoon withdrawal in the Brahmaputra–Meghna River Basin. Despite large spatial variations in onset and withdrawal periods across the GBM River Basin, the basin-averaged results agree reasonably well with the observed periods. Although global climate model (GCM) driven simulations are generally poor in representing the interannual variability of precipitation and winter temperature variations, they tend to agree well with observed precipitation anomalies when driven by perfect boundary conditions. It is also seen that all GCM driven simulations feature significant positive surface temperature trends consistent with the observed datasets.

Changes and variability of precipitation and temperature in the Ganges–Brahmaputra–Meghna River Basin based on global high‐resolution reanalyses

ABSTRACTPrevious studies suggest that climate change impacts significantly on the hydro‐climatic processes within the Ganges–Brahmaputra–Meghna (GBM) River Basin (RB). This study examines the observed climate characteristics and potential strengths and limitations of three global high‐resolution reanalyses and satellite remote‐sensing products over the GBM RB for period 1980–2013 by (1) estimating trends and interannual variations of precipitation and temperature, and (2) isolating precipitation variations likely associated with El Niño Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD). The surface temperature trends show widespread warming across the basin with a maximum increase of 0.6 °C decade−1 over western Nepal and southern Tibet from 1980 to 2013. Rainfall changes from 1980 to 2013 indicate pronounced decline over high rainfall regions of northeast India, Bhutan, Nepal, and Bangladesh, especially from 1998 to 2013. Basin‐wide averaged trends show rainfall decline of up to 39 mm decade−1 in June–August in the Brahmaputra–Meghna RB from 1998 to 2013. Temperature variability based on Principal Component Analysis indicates that the first mode is associated with sea surface temperature (SST) warming in the Arabian Sea and the western tropical Pacific Ocean, while the second mode appears to be significantly correlated to SST anomalies in the western (eastern) tropical Indian (Pacific) Ocean. ENSO and IOD events are found to significantly influence rainfall variability contributing to about 10–20% (ENSO) and 8–10% (IOD) of the annual rainfall, mainly over Bhutan, Nepal, Bangladesh, and north‐eastern India. Among the three reanalysis products: European Centre for Medium‐Range Weather Forecasts (ECMWF) retrospective analysis (ERA‐Interim), Modern‐Era Retrospective Analysis for Research and Applications (MERRA), and Climate Forecast System Reanalysis (CFSR), ERA‐Interim (and MERRA) agrees well with the observed precipitation (temperature) data sets while, CFSR shows the least skills in representing the spatio‐temporal variations of precipitation and temperature.

Interannual variability of temperature in the UTLS region over Ganges–Brahmaputra–Meghna river basin based on COSMIC GNSS RO data

Abstract. Poor reliability of radiosonde records across South Asia imposes serious challenges in understanding the structure of upper-tropospheric and lower-stratospheric (UTLS) region. The Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission launched in April 2006 has overcome many observational limitations inherent in conventional atmospheric sounding instruments. This study examines the interannual variability of UTLS temperature over the Ganges–Brahmaputra–Meghna (GBM) river basin in South Asia using monthly averaged COSMIC radio occultation (RO) data, together with two global reanalyses. Comparisons between August 2006 and December 2013 indicate that MERRA (Modern-Era Retrospective Analysis for Research Application) and ERA-Interim (European Centre for Medium-Range Weather Forecasts reanalysis) are warmer than COSMIC RO data by 2 °C between 200 and 50 hPa levels. These warm biases with respect to COSMIC RO data are found to be consistent over time. The UTLS temperature show considerable interannual variability from 2006 to 2013 in addition to warming (cooling) trends in the troposphere (stratosphere). The cold (warm) anomalies in the upper troposphere (tropopause region) are found to be associated with warm ENSO (El Niño–Southern Oscillation) phase, while quasi-biennial oscillation (QBO) is negatively (positively) correlated with temperature anomalies at 70 hPa (50 hPa) level. PCA (principal component analysis) decomposition of tropopause temperatures and heights over the basin indicate that ENSO accounts for 73 % of the interannual (non-seasonal) variability with a correlation of 0.77 with Niño3.4 index whereas the QBO explains about 10 % of the variability. The largest tropopause anomaly associated with ENSO occurs during the winter, when ENSO reaches its peak. The tropopause temperature (height) increased (decreased) by about 1.5 °C (300 m) during the last major El Niño event of 2009/2010. In general, we find decreasing (increasing) trend in tropopause temperature (height) between 2006 and 2013.

Estimation of flood damage functions for river basin planning: a case study in Bangladesh

Located at the low-lying deltaic floodplain of Ganges–Brahmaputra–Meghna river basin, Bangladesh suffers damages from flooding with regularity. From the perspective of long-term planning and management, a reliable flood damage function is a critical component in the estimation of flood-induced economic loss. Such functions are, however, notoriously difficult to develop. This study utilizes in-stream water level and flood-affected area (FAA) data from Flood Forecasting and Warning Center and Bangladesh Water Development Board to evaluate the best form and data input characteristics of flood damage functions for Bangladesh. The performance of various function configurations (geographic data, water level data, and function form) was tested. The Nash–Sutcliffe efficiency and residual error analysis results suggest that, in general, the logistic function performs better than the other two function forms, and the maximum of daily-maximal water level is the best suited to estimate (FAA). As expected, when information is available from all basins (the Ganges, the Brahmaputra, and the Meghna), the resulting flood damage functions provide the most accurate estimations of FAA. Furthermore, the comparison between single- and multivariable flood damage functions does not demonstrate a clear advantage of using multivariate function in our study area. When flood damage functions with finer spatial and temporal resolution can be constructed using remote sensing technology or hydrodynamic modeling, the intra-year and district-level changes to FAA can be evaluated. These findings provide a better flood management plan for Bangladesh and have potential to be generalized to other similarly flood-affected nations.

COMMUNITY-BASED FLOOD VULNERABILITY AND ADAPTATION ASSESSMENT: A CASE STUDY FROM BANGLADESH

The Intergovernmental Panel on Climate Change (IPCC) (2007, 2012:11) warned that the mega deltas in South Asia (e.g. the Ganges Brahmaputra Meghna River Basin) will be at great risk due to increased flooding, and the region's poverty would reduce the capacity of the inhabitants to adapt to change. This paper provides a "bottom up" impact approach which focuses on a methodological contribution for assessment of vulnerability and adaptation (V & A) in a riverine flood-prone area, "Islampur" in Bangladesh, where various impact assessment guidelines have been taken into consideration. In this study the evaluation of V & A assessments at community level has been accomplished mainly by a weighted matrix index value derived from two participatory rapid appraisals (PRAs). Based on the distribution pattern of various weighted value indices of V & A issues, the required adaptation techniques can be adopted for immediate policy-making, and appropriate actions should be undertaken through establishing community-based adaptation committees (CBAC).

Hydrology, management and rising water vulnerability in the Ganges–Brahmaputra–Meghna River basin

A water vulnerability analysis is made of how sensitivity characteristics of the Ganges–Brahmaputra–Meghna (GBM) River basin may affect adaptive capacity. A co-riparian ‘country perspective’ highlights the importance of local level management actions. Results reveal that vulnerabilities in India and Bangladesh stem from hydrological and ecological factors, but are more linked to poverty and underdevelopment in Nepal. Poor political governance and underinvestment in the water sector add to vulnerability in Bangladesh and Nepal. Overall, Bangladesh is the most sensitive country while Nepal has the least capacity to adapt.

Regional Differences in Overland Rainfall Estimation from PR-Calibrated TMI Algorithm

Abstract The Tropical Rainfall Measuring Mission (TRMM) satellite carries a combination of active [precipitation radar (PR)] and multichannel passive microwave [the TRMM Microwave Imager (TMI)] sensors, which advance our ability to estimate rainfall over land. Rain retrieval from the TRMM PR is associated with an unprecedented accuracy and resolution but is limited in terms of sampling because of the narrow PR swath width (215 km). TMI provides wider coverage (760 km), but its observations are associated with a more complex relationship to precipitation in comparison with PR (especially over land). The PR rain estimates are used here for calibrating an overland TMI rain algorithm. The algorithm consists of 1) multichannel-based rain screening and convective/stratiform (C/S) classification schemes, and 2) nonlinear (linear) regressions for the rain-rate retrieval of stratiform (convective) rain regimes. This study examines regional differences in the algorithm performance. Four geographic regions consisting of central Africa (AFC), the Amazon (AMZ), the U.S. southern Plains (USA), and the Ganges–Brahmaputra–Meghna River basin (GBM) in south Asia are selected. Data from three summer months of 2000 and 2001 are used for calibration; validation is done using summer 2002 data. The current algorithm is also compared with the latest [version 6 (V6)] TRMM 2A12 product in terms of rain detection, and rain-rate retrieval error statistics on the basis of PR reference rainfall. The performance of the algorithm is different for the different regions. For instance, the reduction in random error (relative to 2A12 V6) is about 24%, 36%, 57%, and 165% for USA, AFC, AMZ, and GBM, respectively. However, significant difference between global (the four regions combined) and regional calibration is observed only for the GBM region.