scholarly journals Sensitivity of the agroecosystem in the Ganges basin to inter-annual rainfall variability and associated changes in land use

2013 ◽  
Vol 34 (10) ◽  
pp. 3066-3077 ◽  
Author(s):  
C. Siderius ◽  
P. J. G. J. Hellegers ◽  
A. Mishra ◽  
E. C. van Ierland ◽  
P. Kabat
2016 ◽  
Vol 20 (7) ◽  
pp. 2841-2859 ◽  
Author(s):  
Claire Casse ◽  
Marielle Gosset ◽  
Théo Vischel ◽  
Guillaume Quantin ◽  
Bachir Alkali Tanimoun

Abstract. Since 1950, the Niger River basin has gone through three main climatic periods: a wet period (1950–1960), an extended drought (1970–1980) and since 1990 a recent partial recovery of annual rainfall. Hydrological changes co-occur with these rainfall fluctuations. In most of the basin, the rainfall deficit caused an enhanced discharge deficit, but in the Sahelian region the runoff increased despite the rainfall deficit. Since 2000 the Sahelian part of the Niger has been hit by an increase of flood hazards during the so-called red flood period. In Niamey city, the highest river levels and the longest flooded period ever recorded occurred in 2003, 2010, 2012 and 2013, with heavy casualties and property damage. The reasons for these changes, and the relative role of climate versus land use–land cover (LULC) changes are still debated and are investigated in this paper. The evolution of the Niger red flood in Niamey from 1950 to 2012 is analysed based on long-term records of rainfall (three data sets based on in situ and/or satellite data) and discharge, and a hydrological model. The model is first run with the present LULC conditions in order to analyse solely the effect of rainfall variability. The impact of LULC and drainage area modification is investigated in a second step. The simulations based on the current surface conditions are able to reproduce the observed trend in the red flood occurrence and intensity since the 1980s. This has been verified with three independent rainfall data sets and implies that rainfall variability is the main driver for the red flood intensification observed over the last 30 years. The simulation results since 1953 have revealed that LULC and drainage area changes need to be invoked to explain the changes over a 60-year period.


2022 ◽  
Vol 14 (2) ◽  
pp. 765
Author(s):  
Everlyne B. Obwocha ◽  
Joshua J. Ramisch ◽  
Lalisa Duguma ◽  
Levi Orero

This study integrated local and scientific knowledge to assess the impacts of climate change and variability on food security in West Pokot County, Kenya from 1980–2012. It characterized rainfall and temperature from 1980–2011 and the phenology of agricultural vegetation, assessed land use and land cover (LULC) changes, and surveyed local knowledge and perceptions of the relationships between climate change and variability, land use decisions, and food (in)security. The 124 respondents were aware of long-term changes in their environment, with 68% strongly believing that climate has become more variable. The majority of the respondents (88%) reported declining rainfall and rising temperatures, with respondents in the lowland areas reporting shortened growing seasons that affected food production. Meteorological data for 1980–2011 confirmed high inter-annual rainfall variability around the mean value of 973.4 mm/yr but with no notable trend. Temperature data showed an increasing trend between 1980 and 2012 with lowlands and highlands showing changes of +1.25 °C and +1.29 °C, respectively. Land use and land cover changes between 1984 and 2010 showed cropland area increased by +4176% (+33,138 ha), while grassland and forest areas declined by –49% (–96,988 ha) and –38% (–65,010 ha), respectively. These area changes illustrate human-mediated responses to the rainfall variability, such as increased stocking after good rainfall years and crop area expansion. The mean Normalized Difference Vegetation Index (NDVI) values ranged from 0.36–0.54 within a year, peaking in May and September. For weather-related planning, respondents relied on radio (64%) and traditional forecasters (26%) as predominant information sources. Supporting continuous climate change monitoring, intensified early warning systems, and disseminating relevant information to farmers could help farmers adopt appropriate adaptation strategies.


PLoS ONE ◽  
2016 ◽  
Vol 11 (3) ◽  
pp. e0149397 ◽  
Author(s):  
Christian Siderius ◽  
Hester Biemans ◽  
Paul E. V. van Walsum ◽  
Ekko C. van Ierland ◽  
Pavel Kabat ◽  
...  

Climate ◽  
2014 ◽  
Vol 3 (1) ◽  
pp. 63-77 ◽  
Author(s):  
Benewinde Zoungrana ◽  
Christopher Conrad ◽  
Leonard Amekudzi ◽  
Michael Thiel ◽  
Evariste Da

2021 ◽  
Vol 246 ◽  
pp. 106659
Author(s):  
Sunil Kumar Jha ◽  
Vinay Kumar Mishra ◽  
Chhedi Lal Verma ◽  
Navneet Sharma ◽  
Alok Kumar Sikka ◽  
...  

Water Policy ◽  
2013 ◽  
Vol 15 (S1) ◽  
pp. 9-25 ◽  
Author(s):  
Bharat R. Sharma ◽  
Devaraj de Condappa

The topography of the Ganges basin is highly variable, with the steep mountainous region of the Himalaya upstream and the large fertile plains in eastern India and Bangladesh downstream. The contribution from the glaciers to streamflows is supposed to be significant but there is uncertainty surrounding the impact of climate change on glaciers. An application of the Water Evaluation and Planning model was set up which contained an experimental glaciers module. The model also examined the possible impacts of an increase in temperature. The contribution from glaciated areas is significant (60–75%) in the Upper Ganges but reduces downstream, falling to about 19% at Farakka. Climate change-induced rise in temperature logically increases the quantity of snow and ice that melts in glaciated areas. However, this impact decreases from upstream (+8% to +26% at Tehri dam) to downstream (+1% to +4% at Farakka). Such increases in streamflows may create flood events more frequently, or of higher magnitude, in the upper reaches. Potential strategies to exploit this additional water may include the construction of new dams/reservoir storage and the development of groundwater in the basin through managed aquifer recharge. The riparian states of India, Nepal and Bangladesh could harness this opportunity to alleviate physical water scarcity and improve productivity.


2015 ◽  
Vol 17 (1) ◽  
pp. 195-210 ◽  
Author(s):  
Safat Sikder ◽  
Xiaodong Chen ◽  
Faisal Hossain ◽  
Jason B. Roberts ◽  
Franklin Robertson ◽  
...  

Abstract This study asks the question of whether GCMs are ready to be operationalized for streamflow forecasting in South Asian river basins, and if so, at what temporal scales and for which water management decisions are they likely to be relevant? The authors focused on the Ganges, Brahmaputra, and Meghna basins for which there is a gridded hydrologic model calibrated for the 2002–10 period. The North American Multimodel Ensemble (NMME) suite of eight GCM hindcasts was applied to generate precipitation forecasts for each month of the 1982–2012 (30 year) period at up to 6 months of lead time, which were then downscaled according to the bias-corrected statistical downscaling (BCSD) procedure to daily time steps. A global retrospective forcing dataset was used for this downscaling procedure. The study clearly revealed that a regionally consistent forcing for BCSD, which is currently unavailable for the region, is one of the primary conditions to realize reasonable skill in streamflow forecasting. In terms of relative RMSE (normalized by reference flow obtained from the global retrospective forcings used in downscaling), streamflow forecast uncertainty (RMSE) was found to be 38%–50% at monthly scale and 22%–35% at seasonal (3 monthly) scale. The Ganges River (regulated) experienced higher uncertainty than the Brahmaputra River (unregulated). In terms of anomaly correlation coefficient (ACC), the streamflow forecasting at seasonal (3 monthly) scale was found to have less uncertainty (>0.3) than at monthly scale (<0.25). The forecast skill in the Brahmaputra basin showed more improvement when the time horizon was aggregated from monthly to seasonal than the Ganges basin. Finally, the skill assessment for the individual seasons revealed that the flow forecasting using NMME data had less uncertainty during monsoon season (July–September) in the Brahmaputra basin and in postmonsoon season (October–December) in the Ganges basin. Overall, the study indicated that GCMs can have value for management decisions only at seasonal or annual water balance applications at best if appropriate historical forcings are used in downscaling. The take-home message of this study is that GCMs are not yet ready for prime-time operationalization for a wide variety of multiscale water management decisions for the Ganges and Brahmaputra River basins.


2021 ◽  
Author(s):  
Stefan Krause ◽  

<p>It is probably hard to overestimate the significance of the River Ganges for its spiritual, cultural and religious importance. As the worlds’ most populated river basin and a major water resource for the 400 million people inhabiting its catchment, the Ganges represents one of the most complex and stressed river systems globally. This makes the understanding and management of its water quality an act of humanitarian and geopolitical relevance. Water quality along the Ganges is critically impacted by multiple stressors, including agricultural, industrial and domestic pollution inputs, a lack and failure of water and sanitation infrastructure, increasing water demands in areas of intense population growth and migration, as well as the severe implications of land use and climate change. Some aspects of water pollution are readily visualised as the river network evolves, whilst others contribute to an invisible water crisis (Worldbank, 2019) that affects the life and health of hundreds of millions of people.</p><p>We report the findings of a large collaborative study to monitor the evolution of water pollution along the 2500 km length of the Ganges river and its major tributaries that was carried out over a six-week period in Nov/Dec 2019 by three teams of more than 30 international researchers from 10 institutions. Surface water and sediment were sampled from more than 80 locations along the river and analysed for organic contaminants, nutrients, metals, pathogen indicators, microbial activity and diversity as well as microplastics, integrating in-situ fluorescence and UV absorbance optical sensor technologies with laboratory sample preparation and analyses. Water and sediment samples were analysed to identify the co-existence of pollution hotspots, quantify their spatial footprint and identify potential source areas, dilution, connectivity and thus, derive understanding of the interactions between proximal and distal of sources solute and particulate pollutants.</p><p>Our results reveal the co-existence of distinct pollution hotspots for several contaminants that can be linked to population density and land use in the proximity of sampling sites as well as the contributing catchment area. While some pollution hotspots were characterised by increased concentrations of most contaminant groups, several hotspots of specific pollutants (e.g., microplastics) were identified that could be linked to specific cultural and religious activities. Interestingly, the downstream footprint of specific pollution hotspots from contamination sources along the main stem of the Ganges or through major tributaries varied between contaminants, with generally no significant downstream accumulation emerging in water pollution levels, bearing significant implications for the spatial reach and legacy of pollution hotspots. Furthermore, the comparison of the downstream evolution of multi-pollution profiles between surface water and sediment samples support interpretations of the role of in-stream fate and transport processes in comparison to patterns of pollution source zone activations across the channel. In reporting the development of this multi-dimensional pollution dataset, we intend to stimulate a discussion on the usefulness of large river network surveys to better understand the relative contributions, footprints and impacts of variable pollution sources and how this information can be used for integrated approaches in water resources and pollution management.</p>


2021 ◽  
Author(s):  
Dario Ruggiu ◽  
Salvatore Urru ◽  
Roberto Deidda ◽  
Francesco Viola

<p>The assessment of climate change and land use modifications effects on hydrological cycle is challenging. We propose an approach based on Budyko theory to investigate the relative importance of natural and anthropogenic drivers on water resources availability. As an example of application, the proposed approach is implemented in the island of Sardinia (Italy), which is affected by important processes of both climate and land use modifications. In details, the proposed methodology assumes the Fu’s equation to describe the mechanisms of water partitioning at regional scale and uses the probability distributions of annual runoff (Q) in a closed form. The latter is parametrized by considering simple long-term climatic info (namely first orders statistics of annual rainfall and potential evapotranspiration) and land use properties of basins.</p><p>In order to investigate the possible near future water availability of Sardinia, several climate and land use scenarios have been considered, referring to 2006-2050 and 2051-2100 periods. Climate scenarios have been generated considering fourteen bias corrected outputs of climatic models from EUROCORDEX’s project (RCP 8.5), while three land use scenarios have been created following the last century tendencies.</p><p>Results show that the distribution of annual runoff in Sardinia could be significantly affected by both climate and land use change. The near future distribution of Q generally displayed a decrease in mean and variance compared to the baseline.   </p><p>The reduction of  Q is more critical moving from 2006-2050 to 2051-2100 period, according with climatic trends, namely due to the reduction of annual rainfall and the increase of potential evapotranspiration. The effect of LU change on Q distribution is weaker than the climatic one, but not negligible.</p>


2004 ◽  
Vol 8 (5) ◽  
pp. 903-922 ◽  
Author(s):  
M. Bari ◽  
K. R. J. Smettem

Abstract. A conceptual water balance model is presented to represent changes in monthly water balance following land use changes. Monthly rainfall–runoff, groundwater and soil moisture data from four experimental catchments in Western Australia have been analysed. Two of these catchments, "Ernies" (control, fully forested) and "Lemon" (54% cleared) are in a zone of mean annual rainfall of 725 mm, while "Salmon" (control, fully forested) and "Wights" (100% cleared) are in a zone with mean annual rainfall of 1125 mm. At the Salmon forested control catchment, streamflow comprises surface runoff, base flow and interflow components. In the Wights catchment, cleared of native forest for pasture development, all three components increased, groundwater levels rose significantly and stream zone saturated area increased from 1% to 15% of the catchment area. It took seven years after clearing for the rainfall–runoff generation process to stabilise in 1984. At the Ernies forested control catchment, the permanent groundwater system is 20 m below the stream bed and so does not contribute to streamflow. Following partial clearing of forest in the Lemon catchment, groundwater rose steadily and reached the stream bed by 1987. The streamflow increased in two phases: (i) immediately after clearing due to reduced evapotranspiration, and (ii) through an increase in the groundwater-induced stream zone saturated area after 1987. After analysing all the data available, a conceptual monthly model was created, comprising four inter-connecting stores: (i) an upper zone unsaturated store, (ii) a transient stream zone store, (ii) a lower zone unsaturated store and (iv) a saturated groundwater store. Data such as rooting depth, Leaf Area Index, soil porosity, profile thickness, depth to groundwater, stream length and surface slope were incorporated into the model as a priori defined attributes. The catchment average values for different stores were determined through matching observed and predicted monthly hydrographs. The observed and predicted monthly runoff for all catchments matched well with coefficients of determination (R2) ranging from 0.68 to 0.87. Predictions were relatively poor for: (i) the Ernies catchment (lowest rainfall, forested), and (ii) months with very high flows. Overall, the predicted mean annual streamflow was within ±8% of the observed values. Keywords: monthly streamflow, land use change, conceptual model, data-based approach, groundwater


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