Impacts of climatic variability on agriculture and options for adaptation in the Surma River basin, Bangladesh

Author(s):  
Md. Nazir Hossain ◽  
Paromita Paul
2018 ◽  
Vol 13 (1) ◽  
pp. 32-43 ◽  
Author(s):  
Umesh Kumar Singh ◽  
Balwant Kumar

Anthropogenic greenhouse gas emission is altering the global hydrological cycle due to change in rainfall pattern and rising temperature which is responsible for alteration in the physical characteristics of river basin, melting of ice, drought, flood, extreme weather events and alteration in groundwater recharge. In India, water demand for domestic, industrial and agriculture purposes have already increased many folds which are also influencing the water resource system. In addition, climate change has induced the surface temperature of the Indian subcontinent by 0.48 ºC in just last century. However, Ganges–Brahmaputra–Meghna (GBM) river basins have great importance for their exceptional hydro-geological settings and deltaic floodplain wetland ecosystems which support 700 million people in Asia. The climatic variability like alterations in precipitation and temperature over GBM river basins has been observed which signifies the GBM as one of the most vulnerable areas in the world under the potential impact of climate change. Consequently, alteration in river discharge, higher runoff generation, low groundwater recharge and melting of glaciers over GBM river basin could be observed in near future. The consequence of these changes due to climate change over GBM basin may create serious water problem for Indian sub-continents. This paper reviews the literature on the historical climate variations and how climate change affects the hydrological characteristics of different river basins.


Hydrology ◽  
2019 ◽  
Vol 6 (2) ◽  
pp. 35 ◽  
Author(s):  
Mahtsente Tibebe Tadese ◽  
Lalit Kumar ◽  
Richard Koech ◽  
Birhanu Zemadim

The objective of this study was to characterize, quantify and validate the variability and trends of hydro-climatic variables in the Awash River Basin (ARB) in Ethiopia using graphical and statistical methods. The rainfall and streamflow trends and their relationships were evaluated using the regression method, Mann–Kendall (MK) test and correlation analysis. The analysis focused on rainfall and streamflow collected from 28 and 18 stations, respectively. About 85.7% and 75.3% of the rainfall stations exhibited normal to moderate variability in annual and June to September rainfall, respectively, whereas 96.43% of rainfall stations showed high variability in March to May. The MK test showed that most of the significant trends in annual rainfall were decreasing except in two stations. These research findings provide valuable information on the characteristics, variability, and trend of rainfall and streamflow necessary for the design of sustainable water management strategies and to reduce the impact of droughts and floods in the ARB.


2013 ◽  
Vol 116 (3-4) ◽  
pp. 681-694 ◽  
Author(s):  
Bhogendra Mishra ◽  
Mukand S. Babel ◽  
Nitin K. Tripathi

2021 ◽  
Author(s):  
Alessandro Amaranto ◽  
Dinis Juizo ◽  
Andrea Castelletti

Abstract. Water management in sub-Saharan African river basins is challenged by uncertain future climatic, social and economical patterns, potentially causing diverging water demands and availability, as well as by multi-stakeholder dynamics, resulting in evolving conflicts and tradeoffs. In such contexts, a better understanding of the sensitivity of water management to the different sources of uncertainty can support policy makers in identifying robust water supply policies balancing optimality and low vulnerability against likely adverse future conditions. This paper contributes an integrated decision-analytic framework combining optimization, robustness, sensitivity and uncertainty analysis to retrieve the main sources of vulnerability to optimal and robust reservoir operating policies across multi-dimensional objective spaces. We demonstrate our approach onto the lower Umbeluzi river basin, Mozambique, an archetypal example of sub-Saharan river basin, where surface water scarcity compounded by substantial climatic variability, uncontrolled urbanization rate, and agricultural expansion are hampering the Pequenos Lipompos dam ability of supplying the agricultural, energy and urban sectors. We adopt an Evolutionary Multi-Objective Direct Policy Search optimization approach for designing optimal operating policies, whose robustness against social, agricultural, infrastructural and climatic uncertainties is assessed via robustness analysis. We then implement the GLUE and PAWN uncertainty and sensitivity analysis methods for disentangling the main challenges to the sustainability of the operating policies and quantifying their impacts on the urban, agricultural and energy sectors. Numerical results highlight the importance of robustness analysis when dealing with uncertain scenarios, with optimal-non robust reservoir operating policies largely dominated by robust control strategies across all stakeholders. Furthermore, while robust policies are usually vulnerable only to hydrological perturbations and are able to sustain the majority of population growth and agricultural expansion scenarios, non-robust policies are sensitive also to social and agricultural changes, and require structural interventions to ensure stable supply.


2018 ◽  
Vol 22 (9) ◽  
pp. 4667-4683 ◽  
Author(s):  
Gaby J. Gründemann ◽  
Micha Werner ◽  
Ted I. E. Veldkamp

Abstract. Sufficient and accurate hydro-meteorological data are essential to manage water resources. Recently developed global reanalysis datasets have significant potential in providing these data, especially in regions such as Southern Africa that are both vulnerable and data poor. These global reanalysis datasets have, however, not yet been exhaustively validated and it is thus unclear to what extent these are able to adequately capture the climatic variability of water resources, in particular for extreme events such as floods. This article critically assesses the potential of a recently developed global Water Resources Reanalysis (WRR) dataset developed in the European Union's Seventh Framework Programme (EU-FP7) eartH2Observe (E2O) project for identifying floods, focussing on the occurrence of floods in the Limpopo River basin in Southern Africa. The discharge outputs of seven global models and ensemble mean of those models as available in the WRR dataset are analysed and compared against two benchmarks of flood events in the Limpopo River basin. The first benchmark is based on observations from the available stations, while the second is developed based on flood events that have led to damages as reported in global databases of damaging flood events. Results show that, while the WRR dataset provides useful data for detecting the occurrence of flood events in the Limpopo River basin, variation exists amongst the global models regarding their capability to identify the magnitude of those events. The study also reveals that the models are better able to capture flood events at stations with a large upstream catchment area. Improved performance for most models is found for the 0.25° resolution global model, when compared to the lower-resolution 0.5° models, thus underlining the added value of increased-resolution global models. The skill of the global hydrological models (GHMs) in identifying the severity of flood events in poorly gauged basins such as the Limpopo can be used to estimate the impacts of those events using the benchmark of reported damaging flood events developed at the basin level, though this could be improved if further details on location and impacts are included in disaster databases. Large-scale models such as those included in the WRR dataset are used by both global and continental forecasting systems, and this study sheds light on the potential these have in providing information useful for local-scale flood risk management. In conclusion, this study offers valuable insights in the applicability of global reanalysis data for identifying impacting flood events in data-sparse regions.


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