Journal of Hydrology and Meteorology

Performance Evaluation of Rainfall-Runoff Models for Predictions of Inflows to Bhumibol Reservoir in Thailand

Dilip K. Gautam — 2023-11-02

The Bhumibol reservoir in the Ping River basin is the largest reservoir in the Kingdom of Thailand. This reservoir has contributed to economic development of the country by supplying increased electricity and irrigation water demands as well as flood mitigation in riparian areas along the Ping and the Chao Phraya River. The prediction of inflows to the reservoir is crucial for the optimal management of water for irrigation, power generation and flood control. Properly customized rainfall-runoff models of the catchment could provide the basis for predicting the inflows to the reservoir. Hence, five lumped conceptual rainfall-runoff models were developed for the Ping River basin to simulate daily inflows to the Bhumibol reservoir. The rainfall-runoff models are Australian Water Balance Model (AWBM), Sacramento Soil Moisture Accounting Model, Simplified Hydrolog Model (SIMHYD), Soil Moisture Accounting and Routing Model (SMAR) and Tank Model. The evaluation of the performances of these models showed that all models are capable of predicting inflows. However, the SIMHYD, Sacramento, AWBM and Tank models perform better than SMAR model. Hence, these models could be employed for prediction of inflows to the reservoir with acceptable accuracy.

Spatio-Temporal Variability of Rainfall Over Kathmandu Valley of Nepal

Damodar Bagale — 2023-11-02

The present study used and analyzed rainfall data from 18 meteorological stations from 1971 to 2013 to examine the spatial and temporal variability of seasonal and annual rainfall based on rain gauge measurements. The monthly to annual rainfall analysis was carried out for each site of Kathmandu Valley. Rainfall amounts in Kathmandu Valley vary considerably in space and time. The minimum mean monthly rainfall is observed in November which is 6.5 mm and maximums of 447.8 mm in July. Monsoon is the main contributor of the rainfall which is 80% followed by pre-monsoon with 13.6%, post-monsoon with 3.6% and winter with 2.8%. Spatial interpolation was used to explore spatial variability of seasonal and annual rainfall over Kathmandu Valley. There is large spatial variability of monsoon rainfall; generally, the upper parts of the Kathmandu Valley received the heavy monsoon rainfall than the lower parts of the Valley floor. The rainfall of Kathmandu has marked decreasing in recent a couple of decades. Annual rainfall has decreased by 0.96 mm/year observed in Kathmandu Valley.

Flow Transfer through Spatially Distributed Hydrological (SPHY) Model in Tamakoshi River Basin of Nepal

Bhumi Raj Budhathoki — 2023-11-02

The availability of continuous hydrological records, both spatially and temporally, is often limited. This research employed a fully distributed Spatial Process in HYdrology (SPHY) model within the Tamakoshi River Basin to address this gap. The SPHY model was calibrated from 2004 to 2008 with NSE 0.62 at Busti station of Tamakoshi [2933.29 km²] and validated from 2004 to 2008 with NSE 0.76 at Rasnalu station of Khimti [322.58 km²]. Conversely, SPHY model was calibrated from 2004 to 2008 with NSE 0.79 at Rasnalu station of Khimti and validated from 2004 to 2008 with NSE 0.61 at Busti station of Tamakoshi. The observed annual average discharge at Busti station was 1632 m³ /s and Rasnalu station was 261 m³ /s during the simulation period. The annual average discharges at Benighat [862.09 km² downstream] transferred from Busti and Rasnalu models are 1963.1 m³ /s and 1961.32 m³ /s, respectively. Daily streamflow generated at Benighat from Busti and Rasnalu stations, closely aligns and perfectly matches and highly correlates, with the coefficient of determination 0.99. SPHY model is a good technique for prediction of flows in ungauged basins of Himalayan region. The SPHY model emerges as a robust technique for predicting discharge within the Himalayan River basin. This research holds the potential to serve as a valuable reference for generating streamflow data at ungauged locations, that are vital for planning, management and development of water resource projects.

Assessment of Climate Change Effects on the Hydrological Regime of Bagmati River Basin using SWAT Model

Smriti Shrestha — 2023-11-02

Developing economies have been particularly vulnerable to the consequences of climate change due to their quickly growing populations and underdeveloped social and economic infrastructure. The Bagmati River Basin (BRB) belonging to such an economy is susceptible to the effects of climate change, including droughts and floods brought upon by changes in discharge. This study assessed the potential effects of climate change on discharge in BRB using the Soil and Water Assessment Tool (SWAT). The model was calibrated and validated based on observed flow data from 2000-2010 at two outlets: Khokana and Padhera Dovan. Using R², NSE, PBIAS, RSR, and p-factor, the goodness of fit between the final simulated values and the observed values were evaluated. Historical data from three meteorological stations and bias-corrected global climate model (GCM) outputs from the ACCESS-CM2 model were used to drive the calibrated SWAT model under two scenarios (SSP 2-4.5 and SSP 5-8.5) from the IPCC Sixth Assessment Report (AR6). The study demonstrated long-term spatial and temporal variations in hydrologic responses to future climate changes, providing insights for water resources managers and those involved in mitigating natural hazards in the region.

Urban Heat Variation and Temperature Lapse Rate in the Kathmandu Valley

Nabin Thapa — 2023-11-02

The rate of urbanization growth has accelerated and made urban areas comparatively warmer than surroundings which are the main issues of urban heat worldwide. The Kathmandu Valley is one of the million plus cities with the fastest rate of urbanization and consequent extreme heat. In this study, urban heat was analyzed using both in-situ and satellite-based observation and estimated temperature lapse rate. The Mann Kendell test, Sen’s slope, raster image analysis and lapse rate estimation methods were used. The results showed that average temperature difference in between urban core and surrounding was 4.07°C from 1990 to 2020. Likewise, the summer day temperature in Putalisadak was 8.8°C higher than the Nagarkot. The maximum temperature has increased in all stations where Godavari station has increased significantly (0.073°Cyr⁻¹, p<0.0001). During all seasons, the daytime temperature is higher than the nighttime temperature. The maximum 32.86°C daytime temperature was recorded on August 4, 1pm and the minimum temperature was 3.67°C on Jan 20, 6am, 2020 at the city core. Similarly, the highest temperature was recorded at 31°C in Bagbazar and 33°C in Patan on July 10 and July 11, 2022 respectively when the humidity was lower. Satellite-based observation also shows that the urban heat scenario of the Kathmandu Valley was higher in the urban core which was ranges from 21.06 to 26.09 during 2000-2020. The temperature of the city has increased. However, temperature lapse rate in response to Nagarkot (reference station) is normal i.e decreased temperature in response to increased height. The higher lapse rate is generally found in the Godavari and lower was observed in the Machhegaoun. Overall, the Kathmandu Valley is getting more warmer compared to the surroundings. This comprehensive study is useful to explore the understanding of urban heat islands and temperature lapse rate in the major cities in compared to the surroundings in Nepal.

Charting the Course to Resilience: Hydrodynamic Modeling for Socio-economic Insights for Flood Risk Management in Nepal’s Ungauged Roshi River Catchment

Sunil Duwal — 2023-11-02

Nepal, a Himalayan country with diverse topography, faces significant flood risks yearly. This study focuses on flood hazard mapping and vulnerability assessments for the Roshi River catchment (RRC), situated in the mid-hills of Nepal, by using hydrodynamic modeling and scenario-based approaches. The results obtained from probability distribution methods revealed varying flood magnitudes from 100 m³ /s to 1100 m³ /s. Inundation’s analysis showed plains near the Araniko Highway (AH42) and Panauti Municipality to be high-risk flood-prone areas. Croplands are the most susceptible, while the estimated number of people and buildings at risk varies from 4,000 to 7000 people in 1200 to 2600 buildings. Socio-economic analysis shows that a major portion of the population is from Tamang ethnicity, with relatively lower economic and educational status. Similarly, women in economically and socially disadvantaged communities are particularly at risk, emphasizing the need for increased awareness and support. Proactive flood disaster management strategies are crucial, especially for marginalized and agriculture-dependent communities. The strategically important RRC’s link to key cities, including Kathmandu, demands effective flood control measures. Hydrodynamic modeling with possible scenarios relating to socio-economic aspects can aid decision-making processes from local to central government levels to create a more resilient and disaster-resistant future for Nepal.