Medium-sized River Basin Research Articles

Short-Term Flood Prediction Model Based on Pre-Training Enhancement

With the rapid advancement of deep learning techniques, deep learning-based flood prediction models have drawn significant attention. However, for short-term prediction in small- and medium-sized river basins, models typically rely on hydrological data spanning from the past several hours to one day, utilizing a fixed-length input window. Such input limits the models’ adaptability to diverse rainfall events and restricts their capability to comprehend historical temporal patterns. To address the underutilization of historical information by existing models, we introduce a Pre-training Enhanced Short-term Flood Prediction Method (PE-SFPM) to enrich the model’s temporal understanding without necessitating changes to the input window size. In the pre-training stage, the model uses a random masking and prediction strategy to learn segment features, capturing a more comprehensive evolutionary trend of historical floods. In the flow forecasting stage, temporal features and spatial features are captured and fused using the temporal attention, spatial attention, and gated fusion. Features are further enhanced by integrating segment features using a feed-forward network. Experimental results demonstrate that the proposed PE-SFPM model achieves excellent performance in short-term flood prediction tasks.

GIS-based landslide and rockfall susceptibility zoning in Chepelarska River Basin (Western Rhodope Mountains, Bulgaria)

Landslides and rockfalls are one of the most widespread hazardous phenomena in the Western Rhodopes, Bulgaria. These mass-wasting types occur together with other dangerous phenomena such as river bank erosion and soil degradation, and can cause a lot of infrastructural damage. The main purpose of this paper is to perform GIS-based landslide and rockfall susceptibility zoning and to elaborate susceptibility maps at a scale of а river basin on the example of the Chepelarska River Basin (RB). In order to achieve this goal, nine causal factors have been selected, and map of landslides and field study have been used. These factors were reclassified using histograms and the natural breaks method. In addition, the frequency ratio values of each class have been calculated. To obtain the causal factors impact on sliding and rockfalls, the weights and weighted averages sum of their classes were calculated and analysed. For the complex analysis and elaboration of mass-wasting susceptibility maps, weighted overlay and weighted sum methods have been applied. The obtained results show that from the total 38 landslides and rockfalls in the study area, 26 of them fall into the very high susceptibility zone applying a weighted overlay, and 25 of them fall into the same zone using the weighted sum method. These results and the used methods could be used for other small and medium-sized river basins.

Flood Risk Forecasting and Early Warning Technology for Medium and Small Rivers in the Yellow River Basin Induced by Heavy Rain

The Yellow River Basin is one of the important sand-producing and sediment-transporting areas in China, and one of the three most important sand-producing areas in the world. The amount of sand and dust days in the “Three Norths” (Dongbei, Xibei, and Huabei) area has increased, and regional sand and dust storms have occurred frequently. There are generally more serious hidden danger points of debris flow geological disasters in small and medium-sized river basins. The technical achievements of flood risk forecasting and early warning for medium and small rivers in the Yellow River Basin based on rainstorm-induced floods are important technical supports for flood forecasting and early warning for medium and small rivers. Based on this, a case study was carried out on the problems such as the weak forecasting and early warning ability of flood disasters induced by heavy rain and the low accuracy of flood disaster loss assessment in the flood disasters of medium and small rivers, for the reference of relevant personnel.

Evaluating Magnitude Agreement and Occurrence Consistency of CHIRPS Product with Ground-Based Observations over Medium-Sized River Basins in Nepal

High spatio-temporal resolution and accurate long-term rainfall estimates are critical in sustainable water resource planning and management, assessment of climate variability and extremes, and hydro-meteorology-related water system decisions. The recent advent of improved higher-resolution open-access satellite-based rainfall products has emerged as a viable complementary to ground-based observations that can often not capture the rainfall variability on a spatial scale. In a developing country such as Nepal, where the rain-gauge monitoring network is sparse and unevenly distributed, satellite rainfall estimates are crucial. However, substantial errors associated with such satellite rainfall estimates pose a challenge to their application, particularly in complex orographic regions such as Nepal. Therefore, these precipitation products must be validated before practical usage to check their accuracy and occurrence consistency. This study aims to assess the reliability of the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) product against ground-based observations from 1986 to 2015 in five medium-sized river basins in Nepal, namely, Babai, Bagmati, Kamala, Kankai, and the West Rapti river basin. A set of continuous evaluation metrics (correlation coefficient, root mean square error, relative bias, and Kling-Gupta efficiency) were used in analyzing the accuracy of CHIRPS and categorical metrics (probability of detection, critical success index, false alarm ratio, and frequency bias index). The Probability of Detection and Critical Success Index values were found to be considerably low (<0.4 on average), while the false alarm ratio was significant (>0.4 on average). It was found that CHIRPS showed better performance in seasonal and monthly time scales with high correlation and indicated greater consistency in non-monsoon seasons. Rainfall amount (less than 10 mm and greater than 150 mm) and rainfall frequency was underestimated by CHIRPS in all basins, while the overestimated rainfall was between 10 and 100 mm in all basins except Kamala. Additionally, CHIRPS overestimated dry days and maximum consecutive dry days in the study area. Our study suggests that CHIRPS rainfall products cannot supplant the ground-based observations but complement rain-gauge networks. However, the reliability of this product in capturing local extreme events (such as floods and droughts) seems less prominent. A high-quality rain gauge network is essential to enhance the accuracy of satellite estimations.

The analysis of spatial distribution of artificial reservoirs as anthropogenic fragmentation elements of rivers in the Dnipropetrovsk Region, Ukraine

The purpose of the research is to summarise quantitative characteristics and to analyse the spatial distribution of artificial water bodies as anthropogenic fragmentation elements of medium and small rivers within the Dnipropetrovsk Region, Ukraine. The paper uses current data pertaining to existing reservoirs and mineralisation of water in rivers. Comparison included quantitative characteristics, water surface area, and the volume water in ponds and reservoirs. It has been established that although the total ratio was 97% for ponds to 3% for reservoirs, whereas their water surface area 48%, and the volume of water stored only 23% of the total resources. The paper shows the inexpediency and low efficiency of using ponds as water reservoirs feeding small rivers. Increasing the number of ponds in the river basin has a negative impact on the quality of water resources, in particular, by increasing water mineralisation – total dissolved solids ( TDS). Depending on the river, the following indicator of river basin fragmentation has been determined: 6–20 reservoirs per 100 km2 of the river catchment area, and on average 18–36 ponds and reservoirs are built for every 100 km of the river in relation to the length of the hydrographic network. It has shown the regularity of growing water mineralisation due to the fragmentation of rivers by a large number of artificial reservoirs. A strong correlation between regulation and fragmentation of river basins has been established (coefficient of determination R 2 ranges from 0.72 to 0.91). It proves the possibility to estimate the degree of change (increase) of water mineralisation based on the water flow coefficient K w and the river fragmentation coefficient K s fr in the Dnipropetrovsk Region. The paper offers ways of further research for planning and implementation of a water management strategy concerning ecologically safe levels of water use in small and medium-sized river basins.

Using multisource remote sensing data to predict the maximum flood extent in poorly gauged basins

For small- or medium-sized river basins that suffer from floods, the lack of river gauging data is an important reason why flood warning at the appropriate time is difficult for local stakeholders. As a valuable dataset observed from spaceborne or airborne platforms, remote sensing images can capture slices of time-series information to cover the whole river basin. We consider the Nilwara Ganga tributaries in southern Sri Lanka for our research. The maximum flood extents and the corresponding elevations of flooded areas were determined in the post-flood Sentinel-1 images. Relying only on commonly available remote sensing datasets, the rainfall-triggered flood inundation models were proposed to simulate the maximum inundation extent of a potential flood. The results show that the models proposed here can be well applied in the determination of peak stage, especially for the non-tributary river reach (root mean square error = 0.59, R-square = 0.76). The average of Intersection over Union (IoU) accuracy of the maximum flood extent predictions was 0.75. Validations of two flood events had the IoU accuracy of 0.79 and 0.69, respectively. For gauging data-scarce areas, this approach has great potential to provide a different perspective for flood early warning and will benefit the subsequent risk assessment and disaster mitigation.

Application of the TOPKAPI Model in Flood Forecasting of the Upstream of the Zhenjiang River in China

The lumped hydrological model and empirical model have the problems of low accuracy and short forecasting period in real-time flood forecasting of small- and medium-sized rivers in a mountainous watershed. The sharing of underlying surface data such as high-resolution DEM, land use data, soil data, and the popularization and application of the Internet of Things, big data, cloud computing, and intelligent calculation methods makes distributed hydrological model an effective method for real-time runoff simulation and prediction. The topographic, kinematic, approximation, and integration (TOPKAPI) model is a distributed hydrological model whose physical mechanism developed gradually in the late 20th century. It has great advantages in real-time flood forecasting in small- and medium-sized watersheds. Based on the data required by the TOPKAPI model, in this study, 26 selected flood events were simulated from 2000 to 2013 at the outlet section of the upper reach of the Zhenjiang River in Guangdong Province, and the effect of application of the model in flood forecasting of small- and medium-sized rivers was evaluated. The results show that the pass rate (considering the peak discharge as the evaluation item) of 18 flood events in the calibration period was 66.67%, and that of 8 flood events in the validation period was 75%, while the mean Nash efficiency coefficient of the selected 26 flood events was 0.789. According to the simulation results, real-time flood forecasting should be closely combined with the dispatching of the small- and medium-sized reservoirs in the basin. The application of the TOPKAPI model can make a scientific and rapid analysis of the flood control situation in the whole basin and provide accurate information and maximum convenience for flood forecasting consultation and decision making. Additionally, it can improve the efficiency of disaster prevention and mitigation work in small- and medium-sized river basins, and has a major significance in enhancing the modernization level of flood forecasting.

Geoecological passport for small and medium river basins

The paper presents the main provisions characterizing the geoecological passport of small and medium-sized river basins and its significance as a scientific and technical document. The paper highlights the need to create geoecological passports to assess the modern geoecological state of water bodies on the basis of reliable data and develop a set of measures for ecological recovery and minimization of anthropogenic impact in river basins. The novelty and uniqueness of the study is determined by the creation of an individual geoecological passport of the water body using an integral approach, which includes a combination of classical and modern analyses for geoecological assessment of the anthropogenic impact on the Osetr river basin.

Feasibility analysis on the construction of a web solution for hydrometeorological forecasting considering water body management and indicators for the SARS-COV-2 pandemic

The current scenario of a global pandemic caused by the virus SARS-CoV-2 (COVID19), highlights the importance of water studies in sewage systems. In Brazil, about 35 million Brazilians still do not have treated water and more than 100 million do not have basic sanitation. These people, already exposed to a range of diseases, are among the most vulnerable to COVID-19. According to studies, places that have poor sanitation allow the proliferation of the coronavirus, been observed a greater number of infected people being found in these regions. This social problem is strongly related to the lack of effective management of water resources, since they are the sources for the population's water supply and the recipients of effluents stemming from sanitation services (household effluents, urban drainage and solid waste). In this context, studies are needed to develop technologies and methodologies to improve the management of water resources. The application of tools such as artificial intelligence and hydrometeorological models are emerging as a promising alternative to meet the world's needs in water resources planning, assessment of environmental impacts on a region's hydrology, risk prediction and mitigation. The main model of this type, WRF-Hydro Weather Research and Forecasting Model), represents the state of the art regarding water resources, as well as being the object of study of small and medium-sized river basins that tend to have less water availability. hydrometeorological data and analysis. Thus, this article aims to analyze the feasibility of a web tool for greater software usability and computational cost use, making it possible to use the WRF-Hydro model integrated with Artificial Intelligence tools for short and medium term, optimizing the time of simulations with reduced computational cost, so that it is able to monitor and generate a predictive analysis of water bodies in the MATOPIBA region (Maranhão-Tocantins-Piauí-Bahia), constituting an instrument for water resources management. The results obtained show that the WRF-Hydro model proves to be an efficient computational tool in hydrometeorological simulation, with great potential for operational, research and technological development purposes, being considered viable to implement the web tool for analysis and management of water resources and consequently, assist in monitoring and mitigating the number of cases related to the current COVID-19 pandemic. This research are in development and represents a preliminary results with future perspectives.

Geoecological screening of the state of small and medium-sized river basins to assess the impact of measures for the operation of hydraulic structures

The relevance of the work is due to the annual increase in anthropogenic load on components of geosystems of basins of small and medium rivers. The paper proposes an integrated approach to solving the main problem using a combination of classical and modern methods of analyzing natural systems - the screening method. This paper notes the need for screening control during the implementation of measures for the operation of hydraulic structures to assess the current state of catchment basins of small and medium-sized rivers, which includes the forecast of possible changes in the components of geosystems under the influence of anthropogenic load in order to prevent, minimize or eliminate negative environmental and related socio-economic and other consequences and maintain optimal living conditions for the population. Solving the problem using the screening method will make it possible to better analyze the state of catchment areas, in particular, the basins of small and medium rivers with a high anthropogenic load, which will make it possible to promptly identify environmental risks that have a negative impact on the components of geosystems and take more effective measures to eliminate them. The development of a methodology for screening control will make it possible to comprehensively assess the impact of anthropogenic factors on the geoecological state of the catchment area of the Osetr river, to study the current ecological state of the study area, identify the main factors of impact, as well as assess the degree of pollution, zone the study area according to the degree of anthropogenic load, and develop a geoecological passport for the catchment area of the Osetr river.

Оценка эластичности стока рек восточной части бассейна Амура

Taking into account the unstable moisture regime and the diversity of landscapes within the Amur River basin, the problem of assessing the impact of climatic changes on the processes of surface water cycle in the region becomes multifaceted, associated with the solution of particular problems. This work studied the reaction of a river runoff to changes in the amount of atmospheric precipitation on the basis of the elasticity coefficient. Small and medium-sized river basins (52 in total) belonging to the system of the Middle and Lower Amur are the objects of this study. The data of standard observations at hydrological posts and meteorological points for the summer-autumn flood hazard period (June-September) were used. The data series were selected to include different moisture conditions. It was found that with an increase in precipitation by 1 %, the river runoff in the flood hazard season has increased by 1.02–3.86 % in 48 cases, and decreased in 4 cases. The results of the work are fundamentally close to the regional estimates within the basin of the Amur River on the base of the analysis of factual material (including the near abroad) and simulation results, as well as to the values of the runoff elasticity coefficient obtained in different geographic zones and given in the specialized literature. The relationship between the elasticity coefficient values of runoff with various basin indicators has been studied. For the rivers in the Primorsky Kray (catchment area of the Ussuri River), the relationship between the elasticity coefficient values and the seasonal runoff and precipitation, the runoff coefficient, average height, catchments slopes and average river network slopes has been revealed. The influence of local conditions of runoff formation on the river basins response to changes in the amount of atmospheric precipitation is discussed.

Research on Water Allocation Method of Juzhang River in Yichang City

Water allocation refers to the gradual allocation of the total available water resources or the amount of water that can be allocated to the administrative area, and determines the share of water consumption or the share of water used for living and production in the administrative area. The total amount of available water resources includes the amount of surface water resources and the amount of groundwater resources that can be exploited, minus the overlap between the two. Aiming at the water allocation problem of the Juzhang River, this paper discusses the basic principles of water allocation and the technical route of water allocation plan formulation. A water allocation plan for the Juzhang River Basin was drawn up through steps such as supply and demand forecasting and supply and demand balance analysis. The research can provide a certain reference for the development of water allocation schemes in small and medium-sized river basins.

Studies on changes in extreme flood peaks resulting from land-use changes need to consider roughness variations

ABSTRACTThe impacts of changes in forest coverage on extreme floods have drawn much attention globally. This study quantifies the sensitivity of flood peaks to forest coverage and roughness changes. With this objective, a framework is first introduced that includes a variance-based sensitivity analysis approach and a water and energy budget-based distributed hydrological model with a vegetation module. The influence of forest coverage changes is simulated by altering land-use types that are based on physical parameters. A variance decomposition approach is used to quantify the contribution of influential factors, i.e. event size, forest coverage and roughness changes, to extreme flood peak variations. The results in a medium-sized river basin show forest coverage changes have little influence: variations in canopy interception, ground surface water retention, soil moisture and groundwater table resulting from changing forest coverage did not alter flood peaks considerably. In contrast, it is found that flood peaks are more sensitive to roughness variations.

Warming temperatures are impacting the hydrometeorological regime of Russian rivers in the zone of continuous permafrost

Abstract. Large Arctic river basins experience substantial variability in climatic, landscape, and permafrost conditions. However, the processes behind the observed changes at the scale of these basins are relatively poorly understood. While most studies have been focused on the “Big 6” Arctic rivers – the Ob', Yenisey, Lena, Mackenzie, Yukon, and Kolyma – few or no assessments exist for small and medium-sized river basins, such as the Yana and Indigirka River basins. Here, we provide a detailed analysis of streamflow data from 22 hydrological gauges in the Yana and Indigirka River basins with a period of observation ranging from 35 to 79 years up to 2015. These river basins are fully located in the zone of continuous permafrost. Our analysis reveals statistically significant (p<0.05) positive trends in the monthly streamflow time series during the autumn–winter period for most of the gauges. The streamflow increases in a stepwise pattern (post-1981) for 17 out of 22 gauges in September (average trend value for the period of record is 58 % or 9.8 mm) and 15 out of 22 gauges in October (61 % or 2.0 mm). The positive trends are seen in 9 out of 19 rivers that do not freeze in November (54 %, 0.4 mm) and 6 out of 17 rivers that do not freeze in December (95 %, 0.15 mm). Precipitation is shown to decrease in late winter by up to 15 mm over the observational period. Additionally, about 10 mm of precipitation that used to fall as snow at the beginning of winter now falls as rain. Despite the decrease in winter precipitation, no decrease in streamflow has been observed during the spring freshet in May and June in the last 50 years (from 1966); moreover, five gauges show an increase of 86 % or 12.2 mm in spring floods via an abrupt change in 1987–1993. The changes in spring freshet start date are identified for 10 gauges; the earlier onset in May varies from 4 to 10 d over the observational period. We conclude that warmer temperatures due to climate change are impacting the hydrological regime of these rivers via changes in precipitation type (rain replacing snow). Other factors, such as the melting of permafrost, glaciers, and aufeis or changes in groundwater conditions, are likely to contribute as well; however, no direct observations of these changes are available. The changes in streamflow can have a significant impact on the ecology of the zone of continuous permafrost, while the increasing freshwater fluxes to the Arctic Ocean can impact the Arctic thermohaline circulation.

A framework to quantify impacts of elevated CO2 concentration, global warming and leaf area changes on seasonal variations of water resources on a river basin scale

With concerns about future catastrophic disasters, elevated CO2 concentration (eCO2), global warming and vegetation changes have received much attention globally. In recent years, studies have suggested controlling climate change should be based on regional impacts. However, regional quantitative assessments of respective and combination influences of CO2, temperature and vegetation variations on water resources remain limited. To address this issue, a comprehensive framework is developed. This framework integrates a dynamic vegetation simulation approach, a biosphere hydrological model and a variance-based sensitivity analysis approach which enables identification of predominant influential factors including their combinations. A medium-sized river basin in northeast China is used to illustrate the application based on different CO2 concentration and temperature rise assumptions. Validation using MODIS products shows the proposed approach can simulate Leaf Area Index (LAI) changes well. Results show sum of the influences of LAI and temperature variations on transpiration are more than 1.6 times higher than physiological effects of eCO2 in growing seasons, which implies more water could be transpired than conserved with eCO2, global warming and LAI changes. Results also show runoff increases with eCO2 and decreases with increasing temperatures, but LAI changes play a dominate role in runoff decrease in hot summer. Therefore, considering LAI changes is of utmost importance in projections of future water resources, and severity of future water shortage could be underestimated if LAI changes are neglected. This research is useful in gaining insights into the complicated impacts of eCO2, global warming and LAI changes on regional water security and sustainability.

Spatial-temporal variability of soil moisture: Addressing the monitoring at the catchment scale

Soil moisture plays a fundamental role in the mass and energy balance between the land surface and the atmosphere, making its knowledge essential for several hydrological and climatic applications. The aim of this study is to extend the current knowledge of soil moisture spatial-temporal variability at the catchment scale (up to 500 km2). The main implication is to provide guidelines to obtain soil moisture values representative of the mean behaviour at the medium-sized river basin scale, which is useful for remote sensing validation analysis and rainfall-runoff modeling. To this end, 23 measurements campaigns were carried out during a time span of 14 months at 20 sites located within the Upper Chiascio River Basin, a catchment with a drainage area of about 460 km2 in the Umbria Region (central Italy). The data set allowed the analysis of both soil moisture temporal stability and its dynamics. On the basis of statistical and temporal stability approaches, it was investigated how factors such as climatic regime and geomorphology influence soil moisture behaviour. For the investigated area, the spatial variability of soil moisture was higher in dry periods with respect to wet periods, mainly due to the rainfall pattern characteristics during different periods of the year. Soil moisture values recorded during wet periods showed a better correlation than those recorded during dry periods. The maximum number of required samples, to obtain the mean areal soil moisture with an absolute error of 3% vol/vol, was found equal to 12. The temporal stability analysis showed that during wet periods just one “optimal” measurement point can provide values of soil moisture representative of the catchment-mean behaviour, while during dry periods the number of “optimal” measurement points became equal to two. Therefore, at the adopted spatial scale the use of a single measurement point can lead to significant errors. From the perspective of soil moisture dynamics, the decomposition of the spatial variance showed that the contribution of the time-invariant component (temporal mean of each site) was predominant on respect to the total spatial variance of absolute soil moisture data, for almost the whole observation period. Results provided guidance to optimize soil moisture sampling by performing targeted measurements at a few selected points representative of the catchment-mean behaviour.

乘坡河流域洪水预报模型比较研究

中小流域山洪资料积累较少，洪水预报方案编制困难。针对该问题，以南方湿润地区海南乘坡河流域为例，选取以蓄满产流为基础的集总式新安江模型和分布式TOPMODEL模型开展洪水模拟研究。结果表明，对于海南湿润地区，新安江模型和TOPMODEL模型产汇流模拟效果都较好，均可用于指导中小流域进行洪水预报预警。但相对而言，前期土壤较为湿润时，新安江模型的模拟效果较好；对于大洪水及时间序列较长的洪水而言，TOPMODEL模型的模拟效果较好。 The accumulation of flash floods is low and the preparation of flood forecasting schemes is difficult. To address this issue, we take the Chengpo river basin in Hainan, one of the humid areas in south part of China. The lumped Xinanjiang model based on the runoff generation and the distributed TOPMODEL model were selected for flood simulation. The results of both models are good for humid regions in Hainan. These two models can be used to guide the small and medium-sized river basin for flood forecasting and early warning. Generally speaking, Xinanjiang model is more accurate when the pre-soil is wetter; the TOPMODEL model performs better for the larger flood events.

Spatio-temporal downscaling of projected precipitation in the 21st century: indication of a wetter monsoon over the Upper Mahanadi Basin, India

ABSTRACTAn attempt is made to assess the future trend of spatio-temporal variation of precipitation over a medium-sized river basin. The Statistical Downscaling Model (SDSM, version 4.2) is used to downscale the outputs from two general circulation models (GCMs) for three future epochs: epoch-1 (2011–2040), epoch-2 (2041–2070) and epoch-3 (2071–2100). Considering the Upper Mahanadi Basin as a test bed, the study results indicate a “wetter” monsoon (June–September) and the annual increase in precipitation is 12% during epoch-3, which is consistent for both GCMs. Monthly analyses indicate that the precipitation totals are likely to increase and the magnitude of increase is greater during monsoon months than non-monsoon months. The number of month-wise daily extremes increases in most months in the year. However, the maximum percentage increase (with respect to baseline period, 1971–2000) in the number of extreme events is found in the non-monsoon months (specifically before and after the monsoon).

River continuity under difficult boundary conditions–useful steps and practical hints for designing a fish way

Most large and medium sized river basins in Germany have, over time, been affected by anthropogenic changes due to navigation, hydropower generation, and straightening and shortening of river courses for land reclamation. Consequently, there are many weirs inhibiting fish migration. The Ruhr River is affected by several such barriers or obstacles of which Baldeney Weir is the biggest. The search for an appropriate fish pass structure has not been easy given that the location is embedded in urban surroundings and used for traffic or recreation. This situation led to the establishment of an expert working group chaired by the Ruhrverband to discuss the problems and find a common solution. In a step by step approach, all necessary basic information was elaborated and evaluated, including consideration of diverse fish pass types. Setting up a working group of experts and responsible decision makers was found to be an appropriate method of overcoming differing opinions, sometimes based only on subjective, one-sided assessments, and reaching a mutually acceptable solution.

Water Poverty Situation of Medium-sized River Basins in Nepal

Water and poverty are closely related to each other. The Water Poverty Index (WPI) can identify and track the drivers (physical, environmental, social and economic) that link water and poverty. This study uses WPI framework to assess water poverty situation of medium-sized river basins in Nepal that cover 8.7 % of the country’s territory, produce 6.5 % of the country’s water resources and host 23.1 % of the country’s population. The study results show that water poverty index varies from 40.6 (in West Rapti basin) to 55.5 (in Kankai basin). Based on the WPI results, the basins in decreasing order of priority need for water poverty situation improvement can be listed as West Rapti, Babai, Bagmati, Kamala and Kankai. Even in the basin with high water poverty (i.e., West Rapti basin), suggested priority order for the areas of intervention need is Use > Environment > Capacity > Resources > Access. The results are useful to prioritize areas and extent of policy intervention need at different scales.