The Projected Impact of Climate Change on Water Availability and Development in the Koshi Basin, Nepal

Bharati, Luna; Gurung, Pabitra; Jayakody, Priyantha; Smakhtin, Vladimir; Bhattarai, Utsav

doi:10.1659/mrd-journal-d-13-00096.1

Cited by 82 publications

(61 citation statements)

References 16 publications

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“…The area shares its northern border with China, and its eastern border with India. The KRB consists of three main sub-river basins, the Arun, Sunkoshi, and Tamor [17], and has vast water resources (48 billion cubic meters/year) [27]. The Tamor sub-basin is located in the eastern part of the study area, while the Arun sub-basin is in the central part and the Sunkoshi sub-basin is in the western part.…”

Section: Study Areamentioning

confidence: 99%

Changes in Cropland Status and Their Driving Factors in the Koshi River Basin of the Central Himalayas, Nepal

et al. 2016

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Abstract:In recent decades, human activities have significantly transformed land use and land cover (LULC) and the environment of the Central Himalayas region. LULC is a major component of environmental and climatic research. The aim of this study was to determine the changes in cropland status and its drivers in the Koshi River Basin (KRB) of the Central Himalayas region of Nepal between 1978 and 2010. The cropland status in 1978 was obtained from the Land Resources Mapping Project (LRMP) datasets. The cropland status in 1992 and 2010 was determined on the basis of satellite imagery, with an object-oriented classification method, together with field investigations. Advanced geographical tools were used for data processing and binary logistic regression models were used for the statistical analysis of potential driving factors of cropland change. A noticeable overall change in cropland area was found, with rapid increases from 1978 onward at differing rates and to different extents. The cropland area covered 7165 km 2 in 1978. It peaked at 7867.49 km 2 in 1992, and had reduced slightly (by 90 km 2 ) to 7776.66 km 2 by 2010. The change in cropland area was mainly related to four potential driving factors: topography (elevation, slope, and soil types), socioeconomics (population and foreign labor migration), climate (annual mean temperature and precipitation), and neighborhood factors (roads, rivers, and settlements). However, the effects of the different variables have occurred over various stages and at different rates. An understanding of long-term changes in cropland status in the KRB would be useful, and this could be extended to spatial reconstructions with the help of historical data, including cropland and climatic archives.

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Section: Study Areamentioning

confidence: 99%

Changes in Cropland Status and Their Driving Factors in the Koshi River Basin of the Central Himalayas, Nepal

et al. 2016

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“…The DSSAT weather file generator was developed for use with the DSSAT crop model, but can also be used to produce rainfall, temperature, and solar radiation information for other model applications. MarkSim has been applied globally (Bharati et al, 2014;De Trincheria et al, 2015;Rao et al, 2015); however, limited information exists in the peer-reviewed literature regarding testing and validation of the tool. Some evaluation articles (Mavromatis and Hansen, 2001;Mzirai et al, 2005;Kahimba et al, 2009) indicate that MarkSim can perform acceptably, but for some locations does not do well at reproducing interannual variability and may not always perform as well as other weather generators at specific locations.…”

Section: Methodsmentioning

confidence: 99%

A Simple Technique for Obtaining Future Climate Data Inputs for Natural Resource Models

2016

Appl. Eng. Agric

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“…(1) the monsoon season, from April to September, including the early monsoon, whose influence seems to be increasing with the current climate change (Bharati et al, 2014); (2) the winter season, dominated by westerly entrances with a substantial spatio-temporal variability.…”

Section: Data and Associated Uncertainties 21 Meteorological Stationmentioning

confidence: 99%

“…However, these products are not accurate enough at the resolution required for this study. The most recent analysis (Bharati et al, 2014;Ragettli et al, 2015) exclusively used knowledge garnered from the literature. To detail the approach, in this study the parametrization was based on in situ measurements.…”

Section: Parametrization Of Surfacesmentioning

confidence: 99%

Providing a non-deterministic representation of spatial variability of precipitation in the Everest region

Eeckman¹,

Chevallier²,

Boone³

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. This paper provides a new representation of the effect of altitude on precipitation that represents spatial and temporal variability in precipitation in the Everest region. Exclusive observation data are used to infer a piecewise linear function for the relation between altitude and precipitation and significant seasonal variations are highlighted. An original ensemble approach is applied to provide non-deterministic water budgets for middle and high-mountain catchments. Physical processes at the soilatmosphere interface are represented through the Interactions Soil-Biosphere-Atmosphere (ISBA) surface scheme. Uncertainties associated with the model parametrization are limited by the integration of in situ measurements of soils and vegetation properties. Uncertainties associated with the representation of the orographic effect are shown to account for up to 16 % of annual total precipitation. Annual evapotranspiration is shown to represent 26 % ± 1 % of annual total precipitation for the mid-altitude catchment and 34% ± 3 % for the high-altitude catchment. Snowfall contribution is shown to be neglectable for the mid-altitude catchment, and it represents up to 44 % ± 8 % of total precipitation for the highaltitude catchment. These simulations on the local scale enhance current knowledge of the spatial variability in hydroclimatic processes in high-and mid-altitude mountain environments.

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The Projected Impact of Climate Change on Water Availability and Development in the Koshi Basin, Nepal

Cited by 82 publications

References 16 publications

Changes in Cropland Status and Their Driving Factors in the Koshi River Basin of the Central Himalayas, Nepal

Changes in Cropland Status and Their Driving Factors in the Koshi River Basin of the Central Himalayas, Nepal

A Simple Technique for Obtaining Future Climate Data Inputs for Natural Resource Models

Providing a non-deterministic representation of spatial variability of precipitation in the Everest region

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