Impact of planned water resource development on current and future water demand in the Koshi River basin, Nepal

Chinnasamy, Pennan; Bharati, Luna; Bhattarai, Utsav; Khadka, Ambika; Dahal, Vaskar; Wahid, Shahriar

doi:10.1080/02508060.2015.1099192

Cited by 54 publications

(22 citation statements)

References 10 publications

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“…The development of effective strategies to mitigate water stress problems requires good knowledge of water resources originating in the HKKH region, which are commonly investigated using hydrological (Jain et al, 2010;Singh & Jain, 2003) and water resource systems (Chinnasamy et al, 2015;Momblanch et al, 2019;Sharma & De Condappa, 2013) models. In mountainous regions, hydrological models are highly sensitive to errors in precipitation data, which is one of the key inputs used to force them (Andermann et al, 2011;Li et al, 2017;Meng et al, 2014;Remesan & Holman, 2015;Wulf et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Bias Correction of High‐Resolution Regional Climate Model Precipitation Output Gives the Best Estimates of Precipitation in Himalayan Catchments

et al. 2019

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The need to provide accurate estimates of precipitation over catchments in the Hindu Kush, Karakoram, and Himalaya mountain ranges for hydrological and water resource systems assessments is widely recognized, as is identifying precipitation extremes for assessing hydro‐meteorological hazards. Here, we investigate the ability of bias‐corrected Weather Research and Forecasting model output at 5‐km grid spacing to reproduce the spatiotemporal variability of precipitation for the Beas and Sutlej river basins in the Himalaya, measured by 44 stations spread over the period 1980 to 2012. For the Sutlej basin, we find that the raw (uncorrected) model output generally underestimated annual, monthly, and (particularly low‐intensity) daily precipitation amounts. For the Beas basin, the model performance was better, although biases still existed. It is speculated that the cause of the dry bias over the Sutlej basin is a failure of the model to represent an early‐morning maximum in precipitation during the monsoon period, which is related to excessive precipitation falling upwind. However, applying a nonlinear bias‐correction method to the model output resulted in much better results, which were superior to precipitation estimates from reanalysis and two gridded datasets. These findings highlight the difficulty in using current gridded datasets as input for hydrological modeling in Himalayan catchments, suggesting that bias‐corrected high‐resolution regional climate model output is in fact necessary. Moreover, precipitation extremes over the Beas and Sutlej basins were considerably underrepresented in the gridded datasets, suggesting that bias‐corrected regional climate model output is also necessary for hydro‐meteorological risk assessments in Himalayan catchments.

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Section: Introductionmentioning

confidence: 99%

Bias Correction of High‐Resolution Regional Climate Model Precipitation Output Gives the Best Estimates of Precipitation in Himalayan Catchments

et al. 2019

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“…Stationarity of a variable implies that its probability density function is time invariant, because the natural system that gives rise to this variable fluctuates only within an unchanging envelop of variability [3,4]. Hitherto, most of the hydrological modeling, water resources management, infrastructural design, and operation processes have relied upon the fundamental assumption of stationarity of temperature and precipitation [5][6][7][8]. But the concept of stationarity has been compromised by anthropogenic interventions in the water basins, as well as by the effects of climate change.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Long-term Precipitation Trend in Illinois and Its Implications for Agricultural Production

Dahal

Gautam

Bhattarai

2018

Water

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Climate change is expected to modify the hydrological cycle resulting in a change in the amount, frequency, and intensity of surface precipitation. How the future hydrological pattern will look is uncertain. Climate change is expected to bring about intense periods of dryness and wetness, and such behavior is expected to be difficult to predict. Such uncertainty does not bode well for the agricultural systems of the United States (US) Midwest that are reliant on natural precipitation systems. Therefore, it is necessary to analyze the behavior of precipitation during the cropping period. The manifestation of global-warming-related changes has already been reported for the last couple of decades and more so in the current decade. Thus, precipitation data from the recent past can provide vital information on what is about to come. In this study, the precipitation data of Illinois, a Midwestern state of the US with rain-fed agriculture, was analyzed with a focus on the climate dynamics during the cropping period. It was observed that even though there has been some increase in the annual precipitation amount (+1.84 mm/year) due to the increase in precipitation frequency and intensity, such change happened outside of the cropping period, thereby ensuring that climate change has not manifested itself during the cropping period.

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“…In a study in the Yushugou River Basin, China, Wang et al (2015) used δ 18 O to infer the percentage contributions of snowmelt (63%) and groundwater (springs 27%) to flooding of the Yushugou River. Such information on splitting the sources of floods is also critical in the Himalayan region, especially in the Koshi River Basin where annual floods are common (Chinnasamy et al 2015). In another study in Iraq, Mustafa et al (2015) studied the δ 18 O and δ 2 H composition in eight springs to distinguish spring origins, and identified three aquifers in the region: Behkme aquifer, Kometan aquifer and Shiranish aquifer, contributing to spring flow.…”

Section: Isotopes As Tracersmentioning

confidence: 99%

Methods to investigate the hydrology of the Himalayan springs: a review

Chinnasamy¹,

Prathapar²

2016

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Springs are the major source of freshwater in many small mountainous watersheds within the Himalayan region. In recent years, their flow rates have diminished, but the reasons for this are not self-evident, and hence this paper reviews the methods to investigate Himalayan springs. The review reveals that chemical and isotope analyses – mostly water dating and stable isotope (e.g., d18O) analyses – could be an appropriate entry point to commence field investigations, because of their potential to map complex spring pathways, including linkages between aquifers. This should be combined with the building of hydrogeological maps with the available data. Output from desktop analyses, field investigations and hydrogeological maps could then contribute to the establishment of a conceptual model, which could form the basis for a numerical model

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Impact of planned water resource development on current and future water demand in the Koshi River basin, Nepal

Cited by 54 publications

References 10 publications

Bias Correction of High‐Resolution Regional Climate Model Precipitation Output Gives the Best Estimates of Precipitation in Himalayan Catchments

Bias Correction of High‐Resolution Regional Climate Model Precipitation Output Gives the Best Estimates of Precipitation in Himalayan Catchments

Analysis of the Long-term Precipitation Trend in Illinois and Its Implications for Agricultural Production

Methods to investigate the hydrology of the Himalayan springs: a review

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