Department Of Hydrology And Meteorology Research Articles

Farmers’ Perceptions of the impact of climate change on apple production in lower Mustang, Nepal

Undoubtedly, climate change is becoming a worldwide concern due to its great sensitivity and detrimental effects on livelihood. The government, policymakers, and other relevant stakeholders are striving to come up with novel and innovative approaches to combat the effects of climate change. Nevertheless, understanding and perceptions of the issue among local farmers are more crucial before making mitigation or adaptation plans. It’s them who are actually more exposed to these environmental works and who are on the frontlines of climate change. So, the study was conducted in 2022 at Lower Mustang to understand how farmers perceive climate change, how it has impacted apple production, and to find discrepancies between their perceptions and the actual change in climatic variability recorded by the Department of Hydrology and Meteorology (DHM). Temperature and precipitation were two climatic variables that were taken into account to investigate the significant effects they have on the rate of apple production. Altogether, 60 households from Lower Mustang were selected randomly for the study. Pre-tested interviews, focus group discussions, key informant interviews, as well as secondary data from DHM, the Ministry of Agriculture and Livestock Development (MoALD), etc. were used to collect the required information. The majority of farmers observed an increase in temperature (83.30%) and an unpredictable increase in rainfall (98%), which are consistent with the actual change in temperature and precipitation recorded between 1991 and 2021. Findings show that the average annual temperature and mean annual precipitation are increasing at a rate of 0.012°C per year and 0.4146 mm per year, respectively. This has resulted in the outbreak of significant amounts of diseases and insect pest infestations that have a direct impact on the quality and quantity of apples. The majority of farmers acknowledged that rainfall was the most significant climatic hazards that negatively impacted apple production, followed with hailstones having an impact on apples during flowering and fruiting. Farmers in the study area are limited to intercropping practices, mostly as an adaptation strategy to combat the impacts of climate change. The study concluded that farmers perceived climate change; they are aware of the term ‘Climate Change’ but haven’t taken any significant adaptation measures towards it. So, there is an immediate need for effective adaptation mechanisms, taking into account farmers' perspectives, to make Lower Mustang self-sufficient in apple production.

Climate change and adaptive strategies for agriculture in Panchkhal Municipality

Climate change is a modern global crisis caused by human activities that emit greenhouse gases and alter the Earth's natural systems. It is now an undeniable global burning issue, affecting the complex relationship between the physical landscape, natural resources, and how communities adapt to the effects of climate change. Climate change brings many uncertainties to the livelihoods of farming communities that depend on weather and climate. The purpose of this paper is to examine the climate change and adaptive strategies of the farmers in Panchkhal Municipality using an explanatory mixed-methods research design. Primary data were collected from field observation, questionnaires, and interviews. Secondary data were collected from the Center Bureau of Statistics (CBS) and the Department of Hydrology and Meteorology (DHM). The finding shows the many impacts of climate change, such as hot waves, floods, landslides, droughts, increased diseases in agriculture production, and drying up water resources. Similarly, it shows that traditional adaptive strategies have been changing due to a decline in food crop production over the last two decades. Thus, strong policy efforts need to be prepared to mitigate the adverse impact of climate change on traditional farming methods.

River channel dynamics and flooding: A case of motorable bridge collapse due to abrupt flood in Chhabdi Khola, Tanahun, Nepal

The monsoon season in Nepal brings calamitous events like riverbank erosion, toe cutting, and the structural failure of bridges due to floods. In July 2021, a motorable bridge in Bhadgaun, Tanahun district, Nepal, collapsed during a massive flood in Chhabdi Khola. The study aims to comprehensively document the aftermath, specifically focusing on the causal factors that led to the damage of the Chhabdi Khola Dovan Bridge. The study delves into an in-depth analysis of the stream's channel morphology, with the 5.85 kilometers Chhabdi Khola partitioned into 28 distinct segments, each spanning approximately 200 meters. These segments, sequentially labeled from Site 1 to Site 28, encompass the area extending from the upstream at Chhabdi Barah temple to the downstream at bridge’s location. Rigorous measurements of length, breadth, and depth at each site form the basis for volumetric assessments of the stream. The study revolves around contrasting paleo channel attributes with contemporary alterations within the Chhabdi Khola catchment. The analysis leverages precipitation data sourced from the Department of Hydrology and Meteorology (DHM) to discern precipitation trends within the Chhabdi Khola catchment area. The hydrographic data underwent trend analysis utilizing Mann-Kendall and Sen's slope method through R software (version 4.3.2). The collapse of the Chhabdi Khola Dovan Bridge resulted from intense water flow and debris due to heavy rainfall and a narrow outlet near the bridge, impacting the local population and land users facing the enduring aftermath of a catastrophic monsoon event. The study highlights the significance of understanding river dynamics in small streams and advocates for proactive disaster preparedness measures, even in seemingly small river channels.

Effect of Surface Characteristics and Rainfall in Infiltration Rate: A Case Study of Kaligandaki River Basin

Study of infiltration characteristics is crucial for effective watershed management, as it helps determine the water availability for crops, the need of irrigation, groundwater recharge, and surface runoff. This study is aimed at identifying the relation between infiltration rate and surface characteristics as well as rainfall rate in the Kaligandaki River basin of Nepal using Hydrologic Modelling System (HEC-HMS). HEC-HMS is a physically based, semi-distributed model that uses the weather and spatial information of soil and landuse of the basin for deriving the inputs for the model. A hydrological rainfall-runoff model is developed for the Kaligandaki River basin, with outlet at hydrological station 420, Kotgau, of Department of Hydrology and Meteorology (DHM). The model was then validated at DHM station 420, Angsing, of Kaligandaki River. Model generated subbasin wise infiltration rates and existing landuse were analysed and it was found that sub-basins with dominant landuse as forest had high infiltration rate among prevailing landuse types. Conversely, low infiltration rate was observed for barren area, snow/glacier and grassland landcover type dominated subbasins. A positive correlation among rainfall rate and infiltration rate was seen with linear increase in infiltration rate for an exponential increase of average rainfall intensity. Infiltration rate was found to have positive correlation with the Hydrologic Soil Group types as suggested by NRCS. Moreover, the study signified a greater impact of landcover over soil types on infiltration rates. Whereas, no significant impact of basin slope on infiltration rate could be identified, which may be due to preclusion of multiple topographic features. Understanding the impacts of rainfall intensity and surface characteristics on infiltration enables proactive measures to mitigate the issues like landslide and reduce flooding and soil erosion by improving infiltration rates through surface condition assessment.

Performance Assessment of Chirps, Persiann – CDR, IMERG, and TMPA Precipitation Products across Nepal

The observation of hydrological as well as meteorological data is very essential for any kind of hydraulic and hydrological study. In Nepal, due to the significant variation of topography and climatic characteristics as well it is necessary to establish the meteorological stations densely, here only 231 meteorological stations are available and are handled by government organizations Department of Hydrology and Meteorology (DHM). Even though, due to many limitations, the satellite data is very useful for the water resources study. There are so many satellite products available but the performance of these products varies from place to place. In this study, the performance of four satellite products i.e., Climate Hazards Group Infrared Precipitation with Station data (CHIRPS), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN-CDR), Integrated Multi-Satellite Retrievals for GPM (IMERG), and TRMM Multi-satellite Precipitation Analysis (TMPA) all over Nepal are evaluated with different elevation bands. The performance of each product is evaluated by Probability of Detection (POD), Critical Success Index (CSI), Frequency Bias Index (FBI), False Alarm Ratio (FAR), Root Mean Square Error (RMSE), and Percentage Bias (PBIAS). After analysis of each product, the PERSIANN-CDR data set gives a reasonable performance for all elevation bands after bias correction.

Changing Rainfall Pattern in Pokhara Valley, Nepal


 
 
 Pokhara valley lies on the southern slope of the Annapurna Range in the Himalayas, Nepal. The mountain range blocks the monsoon originating from the Bay of Bengal in the monsoon season. Based on the observed rainfall data from 1991 to 2021 AD from the Department of Hydrology and Meteorology (DHM), Government of Nepal (GoN), this study aims to assess the monthly, seasonal, and annual pattern of rainfall in Pokhara. Trend analysis for annual rainfall as well as seasonal and monthly rainfall was performed and a regression method was used to find the rate of increase or decrease of the rainfall. Pre- monsoon and monsoon seasons indicate both an upward and a downward trend, whereas post-monsoon and winter seasons illustrates the exact opposite. However, the average monthly rainfall indicates an upward trend, despite the fact that the annual rainfall exhibits both an increasing and a decreasing trend. According to the research, there are rising (+ve) and falling (-ve) trends for the different stations. Although both stations are very near, the precipitation varies broadly. Such massive variation within the short distance might be due to climate change, local wind effects, outflanking of hydraulic structures, and monsoon patterns.
 
 

Impact of Variation in Monsoonal Rainfall and Temperature on Paddy Production and its Adaptive Strategies: A Case Study from Bhaktapur District of Nepal

This study was carried out to assess the impact of climate change on paddy yield in Bhaktapur, Nepal. The study compared the summer rainfall variability, summer temperature variability, and farmers' perception of rainfall and temperature changes over a 30-year period. A household survey of 420 houses was conducted to collect information supplemented by meteorological data from the Department of Hydrology and Meteorology (DoHM). Following this, significant increases and decreases in temperature and rainfall were observed on annual and seasonal time scales, respectively. The obtained result shows the annual precipitation trend of the study area is increasing at a rate of 0.24 mm yr-1. The linear trend analysis of the pre-monsoon indicates that the rainfall is increasing at the rate of 0.18 mm yr-1 and the monsoon shows the rainfall is increasing at the rate of 0.57 mm yr-1, whereas the post-monsoon rainfall is decreasing at the rate of 0.02 mm yr-1. The biggest changes in precipitation were observed during the monsoon season. The monsoon precipitation trend in the time series was found to be increasing at a rate of 0.57 mm yr-1. This variation in monsoon rainfall is clearly unfavorable for the agriculture system of the study area. When these recent changes in the temperature and precipitation were compared over 30-year time series data from the weather station, it is apparent that the climate of the study area exhibits fluctuation over time, many of the changes being very erratic. As per the data, all kinds of temperatures are being increased annually. According to the linear trend shown below, average annual temperature, minimum temperature, and maximum temperature are increasing at rates of 0.038°C yr-1, 0.054°C yr-1, and 0.021°C yr-1, respectively. The results show that future climate change in Nepal, including higher temperatures and erratic rainfall, might have a negative impact on paddy productivity and yield in the study area.

Multi-year Prediction of Wheat Yield under the Changing Climatic Scenarios in Central-west Terai using DSSAT Crop Model

The central-west Terai region is one of the major production domains of wheat in Nepal; however, its yield over the past three decades has been greatly affected by climate anomalies such as fluctuating temperatures, decreased solar radiation and rainfall. NASA-POWER derived weather data of Taulihawa in Kapilbastu (27.55° N, 83.667° E) district in central Terai for the past 32–33 years (1984/85 - 2017/18) were purposively selected and downloaded and validated with recorded weather data (1985/86, 1995/96, 2005/06 and 2015/16) of Department of Hydrology and Meteorology (DHM). The trend analysis for grain yield of wheat yield in Kapilvastu was drawn with the historical data of maximum and minimum temperatures and rainfall. Positive correlations between grain yields and minimum temperature and rainfall each showed an acceptable coefficient of determinations (R2). The Cropping system Model - Crop Environment Resource Synthesis (CSM-CERES)- Wheat model, embedded in Decision Support Systems for Agro-technology Transfer (DSSAT) ver 4.7 was used for multi-year predictions of wheat yields using both historically recorded and simulated climatic scenarios. Model simulated results closely agreed with the observed wheat yields recorded by the Ministry of Agriculture and Livestock Development (MoALD) in Nepal. The correlation coefficient of minimum temperature and wheat yield was 0.272 (p<0.05). The correlation between precipitation and observed and DSSAT simulated wheat yield were 0.379 (p<0.01). The multi-year predicted wheat yields using the historical weather data and by the use of the International Panel on Climate Change (IPCC, 2007) scenario embedded in DSSAT crop model showed that yield of wheat could be sustained with use of the current crop cultivars only for 2050 scenarios. Agro-climatic index, mainly temperature, was found to be more sensitive to wheat production in the Nepalese central-west Terai region. This study suggests for the development of new temperature and drought tolerant ready wheat cultivars to feed the increasingly growing Nepalese population.

Multi-year Prediction of Rice Yield under the Changing Climatic Scenarios in Nepal Central Terai Using DSSAT Crop Model

NASA-POWER derived weather data of Dumkauli in Nawalparasi (27.68˚ N, 84.13˚E) district in the Nepal central Terai for the past 33-years (1984/85-2017/18) were purposively downloaded and validated with recorded weather data of Department of Hydrology and Meteorology (DHM). The trend analysis for grain yield of rice in Nawalparasi was drawn with the historical data of the maximum and minimum temperatures and rainfall. Positive correlations between grain yields and minimum temperature and rainfall each showed an acceptable coefficient of determination (R2). The CSM-CERES-Rice embedded in DSSAT ver 4.7 was used for multi-year prediction of rice yield using both historically recorded and simulated climatic scenarios. The model simulated results closely agreed with the observed rice yield recorded by the Ministry of Agriculture and Livestock Development (MoALD) in Nepal. The correlation between precipitation and observed rice yield was 0.71 and the correlation between precipitation and observed and DSSAT simulated yield was 0.379. The multi-year predicted rice yield using historical weather data and the DSSAT rice model showed that rice yield could be sustained with the use of the current crop cultivars only for the upcoming few years. The climate index, mainly the rainfall index, was found to be more sensitive to rice production in the Nepal central Terai region. This study suggests for the development of new climate change ready rice cultivars to feed the increasingly growing Nepalese population.

Weather radar in Nepal: opportunities and challenges in a mountainous region

Extreme rainfall is one of the major causes of natural hazards (for example flood, landslide, and debris flow) in the central Himalayan region, Nepal. The performance of strategies to manage these risks relies on the accuracy of quantitative rainfall estimates. Rain gauges have traditionally been used to measure the amount of rainfall at a given location. The point measurement often misrepresents the basin estimates, because of limited density and high spatial variability of rainfall fields across the Himalayas. The Department of Hydrology and Meteorology (DHM), Nepal has planned to install a network of three weather radars that cover the entire country. So far, the first weather radar has been installed in 2019 in the western region of the country. Two more radars will be added for the planned radar network in the near future covering the central and eastern regions of the country. Here we introduce the first installed weather radar in Nepal. We highlight both the opportunities and challenges with the radar observation in the mountainous regions. Radar rainfall estimates across the Himalayas are critical to issue severe weather warnings; forecast floods and landslides; and inform decision making in a broad range of sectors, including water and energy, construction, transportation, and agriculture.

Surface air temperature trends in Kathmandu Valley for 2011-2017

In this study, we reviewed the maximum and minimum temperature trends of the Kathmandu valley over the period of 2011-2017. In addition, the average monthly temperature trends were studied annually for the same period, with the data made available from the Department of Hydrology and Meteorology (DHM) of Nepal. The annual temperature trended in the same direction, with winter temperatures being lower and summer temperatures being higher. The annual average minimum and maximum air temperature trends were found to be slightly rising at 0.097˚C/year and 0.04˚C/year, respectively. The mean air temperature in Kathmandu valley is increasing at a rate of 0.06 degrees Celsius per year, with 2016 being the warmest year and 2012 being the least warm, with annual mean temperatures of 19.82˚C and 19.32˚C, respectively. The temperature difference is much smaller in the summer (less than ~12˚C) than in the winter. 
 BIBECHANA 18 (2) (2021) 95-104

Streamflow Variations across Nepal during 1986-2015

This paper presents a picture of the streamflow variation in major hydrologic stations across Nepal during 1986-2015 in two periods; before and after 2000. Our study selected 27 high-quality hydrologic monitoring stations maintained by the Department of Hydrology and Meteorology (DHM), Government of Nepal distributed across the country, representing a wide range of basin size, from ~308 to ~54100 km2. We compare the flow duration curves (FDCs) for two periods, T1: 1986-1999 and T2: 2000-2015. The study quantifies the changes of different streamflow indices including minimum, maximum, average daily streamflow, different percentiles and top 10, 20 and 50 maximum daily streamflow. Many studies reported that the climate (such as temperature and precipitation) showed an abrupt variation during the late 90s in the central Himalayas. This study explores whether similar effects are observed in the streamflow of the Himalayan catchments. The results of the study show a mixed pattern of positive and negative changes for different streamflow indices. However, about 60% of analyzed station (i.e. 17 out of 27) showed the positive deviation of the maximum daily streamflow meaning more extremes were observed in the latter period compared to the former period. Seven stations revealed > +20% shift in the maximum daily streamflow from period T1 to T2. In particular, East Rapti at Rajaiya showed more than 80% increase with respect to T1 which deviated from an average of 304 (ranging from 123 to 682) m3/s to an average of 555 (ranging from 171 to 1260) m3/s. Overall, about 10% of increment could be found on time-sliced averaged maximum daily discharge between two periods. Most importantly, the inter- and intra- annual variation of extreme streamflow show a clear tendency of the elevated peak streamflow recurrently over time.

Benchmarking Real-Time Streamflow Forecast Skill in the Himalayan Region

Improving decision-making in various areas of water policy and management (e.g., flood and drought preparedness, reservoir operation and hydropower generation) requires skillful streamflow forecasts. Despite the recent advances in hydrometeorological prediction, real-time streamflow forecasting over the Himalayas remains a critical issue and challenge, especially with complex basin physiography, shifting weather patterns and sparse and biased in-situ hydrometeorological monitoring data. In this study, we demonstrate the utility of low-complexity data-driven persistence-based approaches for skillful streamflow forecasting in the Himalayan country Nepal. The selected approaches are: (1) simple persistence, (2) streamflow climatology and (3) anomaly persistence. We generated the streamflow forecasts for 65 stream gauge stations across Nepal for short-to-medium range forecast lead times (1 to 12 days). The selected gauge stations were monitored by the Department of Hydrology and Meteorology (DHM) Nepal, and they represent a wide range of basin size, from ~17 to ~54,100 km2. We find that the performance of persistence-based forecasting approaches depends highly upon the lead time, flow threshold, basin size and flow regime. Overall, the persistence-based forecast results demonstrate higher forecast skill in snow-fed rivers over intermittent ones, moderate flows over extreme ones and larger basins over smaller ones. The streamflow forecast skill obtained in this study can serve as a benchmark (reference) for the evaluation of many operational forecasting systems over the Himalayas.

Assessing the Trend of Climate Change in the Western Nepal

This study assesses the change in the climatic variables in the western region of Nepal. Monthly data on minimum temperature, maximum temperature and rainfall for five stations, namely, Chame, Lumle, Khudibazar, Khairenitar and Dumkauli of Manang, Kaski, Lumjung, Tanahu and Nawalparasi districts respectively, obtained from the Department of Hydrology and Meteorology (DHM) of Nepal are considered. Data availability for these three variables are not uniform and ranges earlier from 1970 to the latest 2018. To measure the change in the climatic variables, the first data were deseasonalized using classical multiplicative technique taking a moving average of twelve periods and central moving average and finally, the ordinary least squared method was applied to estimate the trend. Further, the student's t-test confirmed whether there is any significant change or time trend in the variable. The study also performed both Mann-Kendall and Sen’s slope tests for robustness check to the trend. The study result shows that maximum temperature has increased in all stations; the minimum temperature has increased in Khudibazar, Khairenitar and Dumkauli stations; and rainfall has increased in Chame and, decreased in Lumle and Khairenitar stations. Further, both maximum temperature and minimum temperature have increased faster in higher altitudes; and rainfall has decreased slower in lower altitudes. Both Mann-Kendall and Sen’s slope tests are consistent with the result. The outcome of the study which is based on local stations could be useful information for making climate change adaption strategy at the local level.

Temperature Changes in Kaski District of Nepal: A Study of Trends (1970-2018)

Climate change is one of the most complex and crucial issues in the world. It has impacted environmental, social, and economic sectors of our planet. Unsurprisingly, Nepal is not immune to climate change. In fact, it is one of the most susceptible countries to climate change. One of the most impacted variables in Nepal due to climate change is the maximum temperature. The rate of change of temperature per year, in Nepal is ever-increasing. This paper examines the temperature trend and how it has affected environmental, social, and economic sustainability of Kaski District in Nepal. The paper utilizes the maximum temperature trend of Kaski District during 1970-2018. The monthly minimum and maximum temperatures are obtained from the Department of Hydrology and Meteorology (DHM). The study is done based on the data obtained from Pokhara Airport and Lumle stations. The paper uses three statistical tools alongside descriptive statistics to analyze the data. First, the Man-Kendall test is used to figure out the trend of temperature. Second, Sen’s slope is used to find the magnitude of a trend. Third, the Time series model has been used for forecasting temperature trends. Finally, SPSS and R software were used to calculate the results. The trend of maximum temperature has been significantly increased in Kaski District. The maximum temperature in Kaski during 1970-2018, recorded, was 24.99°C in 2005 and was closely followed by 24.66°C temperature in 2010. The average maximum temperature during the 1970-2018 period was 23.49°C. The maximum variation of maximum temperature during 1970-2018 was in 1992 with a standard deviation of 5.94°C. The minimum temperature during 1970-2018 was 21.12°C in 1978 and was closely followed by 22.19°C in 1997. There is an increasing trend of maximum temperature in Kaski District. In addition, the trend of maximum temperature is higher and faster after 1998 in Kaski District of Western Nepal during 1970-2018.

Soda Bottle Science—Citizen Science Monsoon Precipitation Monitoring in Nepal

Citizen science, as a compliment to ground-based and remotely-sensed precipitation measurements, is a promising approach for improving precipitation observations. During the 2018 monsoon (May to September), SmartPhones4Water (S4W) Nepal - a young researcher-led water monitoring network - partnered with 154 citizen scientists to generate 6,656 precipitation measurements in Nepal with low-cost (< 1 USD) S4W gauges constructed from repurposed soda bottles, concrete, and rulers. Measurements were recorded with Android-based smartphones using Open Data Kit Collect and included GPS-generated coordinates, observation date and time, photographs, and observer-reported readings. A year-long S4W gauge intercomparison revealed a -2.9 % error compared to the standard 203 mm (8-inch) gauge used by the Department of Hydrology and Meteorology (DHM), Nepal. We analyzed three sources of S4W gauge errors: evaporation, concrete soaking, and condensation, which were 0.5 mm day-1 (n = 33), 0.8 mm (n = 99), and 0.3 mm (n = 49), respectively. We recruited citizen scientists by leveraging personal relationships, outreach programs at schools/colleges, social media, and random site visits. We motivated ongoing participation with personal follow-ups via SMS, phone, and site visit; bulk SMS; educational workshops; opportunities to use data; lucky draws; certificates of involvement; and in certain cases, payment. The average citizen scientist took 42 measurements (min = 1, max = 148, stdev = 39). Paid citizen scientists (n = 37) took significantly more measurements per week (i.e. 54) than volunteers (i.e. 39; alpha level = 0.01). By comparing actual values (determined by photographs) with citizen science observations, we identified three categories of observational errors (n = 592; 9 % of total measurements): unit (n = 50; 8 % of errors; readings in centimeters instead of millimeters); meniscus (n = 346; 58 % of errors; readings of capillary rise), and unknown (n = 196; 33 % of errors). A cost per observation analysis revealed that measurements could be performed for as little as 0.07 and 0.30 USD for volunteers and paid citizen scientists, respectively. Our results confirm that citizen science precipitation monitoring with low-cost gauges can help fill precipitation data gaps in Nepal and other data scarce regions.

Farmers’ perception on climate change and ecological hazards in Riu and Rapti waterbasin, Chitwan, Nepal

A survey research was done to study the farmers’ perception on climate change and ecological hazards in Riu and Rapti water basin, Chitwan, Nepal. Altogether 120 households, 60 from each water basin in Riu and Rapti were selected randomly for the study. Pre-tested interview, direct observation, focus group discussion as well as secondary data from Department of Hydrology and Meteorology (DHM), Kathmandu were used to collect the required information. Majority of the farmers’ perceived the change in climatic condition in their locality in terms of increase in hotter days, decrease in colder days, variability in the number of rainy days, decrease in rainfall duration, increase in amount and intensity of rainfall, late onset and shift of usual monsoon pattern, prolonged occurrences of dry spells, decrease water level in the river as compared to the past decades. Farmers prioritized the floods/riverbank cutting (61.7%) and drought (63.4%) hazards for obtaining immediate solution/adaptation strategies in Riu water basin; and for drought (60%) and loss of wetland and declining water source (45%) in Rapti water basin. Analysis of the climatic data (last 42 years for rainfall and last 30 years for temperature) showed the increasing trend of annual rainfall (6.83 mm per year) and those of both maximum and minimum temperature (0.019°C per year and 0.069°C per year, respectively). These analyses strongly support the farmers’ perception about the climate change and for which immediately effective adaptation mechanism is required.

Accessing the capability of TRMM 3B42 V7 to simulate streamflow during extreme rain events: Case study for a Himalayan River Basin

The paper examines the quality of Tropical Rainfall Monitoring Mission (TRMM) 3B42 V7 precipitation product to simulate the streamflow using Soil Water Assessment Tool (SWAT) model for various rainfall intensities over the Himalayan region. The SWAT model has been set up for Gandak River Basin with 41 sub-basins and 420 HRUs. Five stream gauge locations are used to simulate the streamflow for a time span of 10 years (2000–2010). Daily streamflow for the simulation period is collected from Central Water Commission (CWC), India and Department of Hydrology and Meteorology (DHM), Nepal. The simulation results are found good in terms of Nash–Sutcliffe efficiency $$(\hbox {NSE}) {>}0.65$$ , coefficient of determination $$(R^{2}) {>}0.67$$ and Percentage Bias $$\hbox {(PBIAS)}{<}15\%$$ , at each stream gauge sites. Thereafter, we have calculated the PBIAS and RMSE-observations standard deviation ratio (RSR) statistics between TRMM simulated and observed streamflow for various rainfall intensity classes, viz., light ( $${<}7.5 \, \hbox {mm}/\hbox {d}$$ ), moderate (7.5 to 35.4 mm/d), heavy (35.5 to 124.4 mm/d) and extremely heavy ( $${>}124.4 \, \hbox {mm}/\hbox {d}$$ ). The PBIAS and RSR show that TRMM simulated streamflow is suitable for moderate to heavy rainfall intensities. However, it does not perform well for light- and extremely-heavy rainfall intensities. The finding of the present work is useful for the problems related to water resources management, irrigation planning and hazard analysis over the Himalayan regions.

Community-based early warning systems for flood risk mitigation in Nepal

Abstract. This paper focuses on the use of community-based early warning systems for flood resilience in Nepal. The first part of the work outlines the evolution and current status of these community-based systems, highlighting the limited lead times currently available for early warning. The second part of the paper focuses on the development of a robust operational flood forecasting methodology for use by the Nepal Department of Hydrology and Meteorology (DHM) to enhance early warning lead times. The methodology uses data-based physically interpretable time series models and data assimilation to generate probabilistic forecasts, which are presented in a simple visual tool. The approach is designed to work in situations of limited data availability with an emphasis on sustainability and appropriate technology. The successful application of the forecast methodology to the flood-prone Karnali River basin in western Nepal is outlined, increasing lead times from 2–3 to 7–8 h. The challenges faced in communicating probabilistic forecasts to the last mile of the existing community-based early warning systems across Nepal is discussed. The paper concludes with an assessment of the applicability of this approach in basins and countries beyond Karnali and Nepal and an overview of key lessons learnt from this initiative.

A Statistical Analysis of Wind Speed and Power Density Based on Weibull and Rayleigh Models of Jumla, Nepal

In the present study, wind speed data of Jumla, Nepal have been statistically analyzed. For this purpose, the daily averaged wind speed data for 10 year period (2004-2014: 2012 excluded) provided by Department of Hydrology and Meteorology (DHM) was analyzed to estimate wind power density. Wind speed as high as 18 m/s was recorded at height of 10 m. Annual mean wind speed was ascertained to be decreasing from 7.35 m/s in 2004 to 5.13 m/s in 2014 as a consequence of Global Climate Change. This is a subject of concern looking at government’s plan to harness wind energy. Monthly wind speed plot shows that the fastest wind speed is generally in month of June (Monsoon Season) and slowest in December/January (Winter Season). Results presented Weibull distribution to fit measured probability distribution better than the Rayleigh distribution for whole years in High altitude region of Nepal. Average value of wind power density based on mean and root mean cube seed approaches were 131.31 W/m2/year and 184.93 W/m2/year respectively indicating that Jumla stands in class III. Weibull distribution shows a good approximation for estimation of power density with maximum error of 3.68% when root mean cube speed is taken as reference.