Water Resource Planning Research Articles

Journal of Water Resources Planning and Management ’s Reproducibility Review Program: Accomplishments, Lessons, and Next Steps

<i>Journal of Water Resources Planning and Management</i> ’s Reproducibility Review Program: Accomplishments, Lessons, and Next Steps

Responses of runoff to changes in climate and human activities in the Liuhe River Basin, China

Since the 1950s, numerous soil and water conservation measures have been implemented to control severe soil erosion in the Liuhe River Basin (LRB), China. While these measures have protected the upstream soil and water ecological environment, they have led to a sharp reduction in the downstream flow and the deterioration of the river ecological environment. Therefore, it is important to evaluate the impact of soil and water conservation measures on hydrological processes to assess long-term runoff changes. Using the Soil and Water Assessment Tool (SWAT) models and sensitivity analyses based on the Budyko hypothesis, this study quantitatively evaluated the effects of climate change, direct water withdrawal, and soil and water conservation measures on runoff in the LRB during different periods, including different responses to runoff discharge, hydrological regime, and flood processes. The runoff series were divided into a baseline period (1956–1969) and two altered periods, i.e., period 1 (1970–1999) and period 2 (2000–2020). Human activities were the main cause of the decrease in runoff during the altered periods, contributing 86.03% (−29.61 mm), while the contribution of climate change was only 13.70% (−4.70 mm). The impact of climate change manifests as a decrease in flood volume caused by a reduction in precipitation during the flood season. Analysis of two flood cases indicated a 66.00%–84.00% reduction in basin runoff capacity due to soil and water conservation measures in the upstream area. Soil and water conservation measures reduced the peak flow and total flood volume in the upstream runoff area by 77.98% and 55.16%, respectively, even with nearly double the precipitation. The runoff coefficient in the reservoir area without soil and water conservation measures was 4.0 times that in the conservation area. These results contribute to the re-evaluation of soil and water conservation hydrological effects and provide important guidance for water resource planning and water conservation policy formulation in the LRB.

Artificial wetlands in the conservation of water resources: An ecocentrism perspective

Background: Water pollution is a kind of environmental damage. Water pollution occurs in developing countries and developed countries. The government has made efforts to preserve water resources. However, it has only reached some levels of society because there are still many facilities that are more important than transportation, food security, and the security system. This research sees ecocentrism given the artificial marsh technique as the conservation of water resources as well as highlights equality of the purpose of the artificial marsh technique with the principle proposed ecocentrism about morality against the universe, so the proposed environmental ethics principles that have to be met in the implementation of the artificial marsh technique on sustainable preservation of water resources planning. Method: This research is library research. The research analysis is an analysis of the approach to a concept; the first phase is the interpretation and categorization, the second phase is data classification, the third phase is the analysis of synthesis, and the fourth phase is a critical evaluation by using element methodical as description, verstehen, interpretation, hermeneutic, inductive, and heuristic. Findings: The result shows that human beings have a duty to manage and preserve nature, and man is forbidden to exploit nature. Views ecocentrism is seen in the preservation of water resources as an effort to protect and preserve nature. Conclusion: Human beings are a part of the universe and are obliged to manage and preserve the guard, so the artificial marsh technique can be used in planning to preserve sustainable water resources. Novelty/Originality of this study: This research could lead to a new model for engaging communities in water conservation projects emphasizing the ethical relationship between humans and nature. This model could include educational programs and practical activities that help communities understand and apply the principles of ecocentrism in their daily lives.

Derivation of Rainfall Intensity-Duration- Frequency (IDF) Curves of Gainesville, Georgia, United States

This research presents a set of Intensity-Duration-Frequency (IDF) curves of Gainesville, Georgia, USA for duration of 15 minutes to 24 hours, and return periods of 2 to 100 years. The objective of this research focuses on the development of IDF curves for the Gainesville, Georgia, USA. Gumbel and Log Pearson Type III models were used to develop the IDF curves. The best rainfall model between Log Pearson III and Gumbel model for the predication of rainfall in the study area was determined for the different return periods and durations. The Gumbel and Log Pearson Type III distributions give maximum intensities of 138.17 mm/hr and 137.75 mm/hr at return period of 100 years with duration of 0.25 hours, respectively. The result of this study can be used by water resource planners and managers for the city of Gainesville, Georgia.

Blue and green water availability under climate change in arid and semi-arid regions

Challenges involving water scarcity have raised concerns about sustainability and human well-being in many regions of Iran. Uncertainty related to the effects of climate change further complicates the use of projections for water resources planning. Hence, investigating the impacts of climate change on water resources is essential for their efficient management. In the present study, water availability was assessed under different climate change projections using eight CMIP6 General Circulation Models (GCMs) to create a multi-model ensemble of well-performing GCMs over the Hamedan-Bahar watershed in western Iran for three futures, near (2026 to 2050), mid (2051 to 2075), and far (2076 to 2100). Impacts of climate change on blue and green water availability was assessed by coupling Soil and Water Assessment Tool (SWAT) with modelled climate change projections and applying distribution mapping bias correction under three Shared Socioeconomic Pathways Scenarios (SSPs). The results showed that three GCMs (MIROC6, CMCC-ESM2, and NorESM2-MM) agreed well with observed climate in the region. The mean annual precipitation was projected to decrease at most by 16.3% under the SSP5–8.5 scenario during mid-future. Maximum and minimum temperatures are expected to increase by 2.3 and 2.4 °C, respectively, under the SSP5–8.5 scenario for the far future. The highest reductions of green and blue water storage and blue water flow were projected at 22%, 28.5% and 35%, respectively, under the SSP5–8.5 scenario during the mid-future. In contrast, green flow was projected to increase by 18% under SSP5–8.5 during the far future. Thus, the water resources of Hamedan-Bahar are sensitive to future climatic changes requiring considerations for adaptation strategies to mitigate water deficits.

Research on the Path and Practice of Ideological and Political Construction in the Course of Water Resources and Hydropower Planning

Through the construction path of courses’ ideological and political teaching objectives, education goals, teaching methods, assessment systems, etc., the corresponding knowledge points of course ideological and political education are constructed in this course, and ideological and political elements are integrated into the teaching module. Find the right entry point for ideological and political education based on the course content and infiltrate ideological and political education in a targeted manner. Integrating ideological and political practice cases of comprehensive utilization of water resources, regulation of benefits, flood regulation, and water energy calculation into the entire teaching process. Fully utilize the advantages of professional course resources and combine them with the needs and development resources of the country, transforming them into unique advantages in ideological and political education through courses. At the same time, we will deeply explore and extract the core values and concepts of patriotism, social responsibility, and cultural confidence contained in professional courses, ensuring that ideological and political education can be fully integrated into all aspects of this course teaching. By integrating the connotation of teaching and educating people into the main aspects of classroom teaching, we can enhance the attractiveness of ideological and political education in the Water Resources and Hydropower Planning professional course and effectively promote the construction and development of this professional course.

Integrated hydrological modeling and water resource assessment in the Mayurakshi River Basin: A comprehensive study from historical data to future predictions

This study employs the SWAT hydrologic model to integrate climatological and hydrological processes for an in-depth analysis of the Mayurakshi River Basin. Utilizing the Markov chain model, the study evaluates water availability, flow patterns, and the basin's response to various climatic and land-use scenarios. Over 30 years of daily observed river discharge data were rigorously calibrated, validated, and analyzed for uncertainty, with critical data from the Massanjore Dam and Tilpara Barrage gauge stations characterizing the river's hydrological behavior. The result suggests the watershed received an average annual precipitation of 1432.4 mm, with evapotranspiration accounting for 40% of total water loss (578.4 mm). Surface runoff constituted over 90% of the total discharge, highlighting its importance for agricultural practices, particularly during the dry season. However future projections (2021–2031) indicate a significant decrease in mean annual precipitation (1404.7 mm) and a drop in evapotranspiration (542.1 mm or 38% of mean precipitation), attributed to reduced vegetation cover and increased settlement, leading to enhanced surface runoff. By quantifying internal renewable blue water, evapotranspiration, and soil water, this research provides crucial data for long-term water resource planning and assessment. The findings are valuable for national, regional, and transboundary water management agencies, offering insights into sustainable water resource management under changing climatic and different land-use conditions.

Times series record of water quality analysis during flood time in Cauvery River basin, Tamil Nadu, India

We determine the spatial and temporal changes in the physicochemical and nutritional parameters of water quality in the Cauvery River basin. We also analyze the effects of anthropogenic and natural factors on the physicochemical and nutritional parameters. The river water samples were collected over a time series record of 6-h intervals for 6 days during and after flooding time. The combination of physicochemical and nutritional parameters generated a large dataset, which was processed using statistical analysis. In addition, statistical analysis was used to calculate the correlation coefficients and plot the regression equations relating various parameters to electrical conductivity (EC). The resulting average values of pH, EC, and total dissolved solids (TDS) showed significant differences in the time series record of the study period (i.e., pH = 8.24, EC = 220 S/m, and TDS = 157.1 mg/L). The values of the following nutritional parameters in floodwater were also determined: orthophosphate = 0.13 mg/L, phosphate = 0.1 mg/L, nitrite = 2.11 mg/L, nitrate = 0.79 mg/L, and ammonia = 4.47 mg/L. Our findings indicates that flooding can deteriorate the groundwater quality, resulting in a decrease in water quality and an increase in contamination levels, which can have detrimental effects on both the environment and human health. This information is crucial to decision making in flood risk management, water resource planning, and conservation efforts to protect both human and ecological systems.

Simulation and Prediction of Snowmelt Runoff in the Tangwang River Basin Based on the NEX-GDDP-CMIP6 Climate Model

In this study, the future snowmelt runoff in the chilly northeast region’s Tangwang River Basin was simulated and predicted using the SWAT model, which was built and used based on the NEX-GDDP-CMIP6 climate model. This study conducted a detailed analysis of the spatial and temporal distribution characteristics of snowmelt runoff using high-resolution DEM, land use, and soil data, along with data from historical and future climatic scenarios. Using box plots and the Bflow digital filtering approach, this study first determined the snowmelt runoff period before precisely defining the snowmelt periods. Sensitivity analysis and parameter rate determination ensured the simulation accuracy of the SWAT model, and the correlation coefficients of the total runoff validation period and rate period were 0.75 and 0.76, with Nashiness coefficients of 0.75 for both. The correlation coefficients of the snowmelt runoff were 0.73 and 0.74, with Nashiness coefficients of 0.7 and 0.68 for both, and the model was in good agreement with the measured data. It was discovered that while temperatures indicate an increasing tendency across all future climate scenarios, precipitation is predicted to increase under the SSP2-4.5 scenario. The SSP2-4.5 scenario predicted a decreasing trend regarding runoff, while the SSP1-2.6 and SSP5-8.5 scenarios showed an increasing trend with little overall change and the SSP5-8.5 scenario even showed a decrease of 6.35%. These differences were evident in the monthly runoff simulation projections. Overall, the findings point to the possibility that, despite future climate change having a negligible effect on the hydrological cycle of the Tangwang River Basin, it may intensify and increase the frequency of extreme weather events, creating difficulties for the management of water resources and the issuing of flood warnings. For the purpose of planning water resources and studying hydrological change in this basin and other basins in cold regions, this study offers a crucial scientific foundation. An in-depth study of snowmelt runoff is of great practical significance for optimizing water resource management, rational planning of water use, spring flood prevention, and disaster mitigation and prevention, and provides valuable data support for future research on snowmelt runoff.

Applicability of sediment rating curves: analysis in the state of Rio Grande do Sul

The transport of sediments is present in all watercourses, occurring naturally, however, in different ways and characteristics. Its quantification in watersheds becomes extremely important for the planning and management of water resources. The sediment rating curve, which empirically describes the relationship between stream flow and suspended sediment concentration (Css), is an alternative tool to the lack of continuous monitoring of sediment transport. The aim of this research was to evaluate the use of rating curves in sedimentometric stations in Rio Grande do Sul, Brazil. Three Css data handling scenarios were tested for the analytical fitting of sediment rating curves considering a power function as follows: complete data sets, data sets subdivided into 10-year periods and subdivided into stream flow ranges. The approaches adopted in the present study were evaluated taking as reference 58 sedimentometric stations in the state. The goodness-of-fit tests used in this study - coefficient of determination, Relative Average Percentage Error and Nash Sutcliffe coefficient, indicated that the best results of the estimation of sediment transport were observed when the sediment rating curve was fitted to the 10-year period data set.

Hydrological modelling using SWAT for the assessment of streamflow dynamics in the Ganga River basin.

Growing concerns over water availability arise from the problems of population growth, rapid industrialization, and human interferences, necessitating accurate streamflow estimation at the river basin scale. It is extremely challenging to access stream flow data of a transboundary river at a spatio-temporal scale due to data unavailability caused by water conflicts for assessing the water availability.Primarily, this estimation is done using rainfall-runoff models. The present study addresses this challenge by applying the soil and water assessment tool (SWAT) for hydrological modelling, utilizing high-resolution geospatial inputs. Hydrological modelling using remote sensing and GIS (Geographic Information System) through this model is initiated to assess the water availability in the Ganga River basin at different locations. The outputs are calibrated and validated using the observed station data from Global Runoff Data Centre (GRDC). To check the performance of the model, Nash-Sutcliffe efficiency (NSE), percent bias (PBIAS), coefficient of determination (R2), and RSR efficacy measures are initiated in ten stations using the observed and simulated stream flow data. The R2 values of eight stations range from 0.82 to 0.93, reflecting the efficacy of the model in rainfall-runoff modelling. Moreover, the results obtained from this hydrological modelling can serve as valuable resources for water resource planners and geographers for future reference.

Influence of large scale climate drivers on hydro-climate variability in Dwangwa River Basin, Malawi

Large-scale climate processes such as the Indian Ocean Dipole (IOD) have significant roles in modulating rainfall and hydrological systems. Understanding such processes can inform adaptation measures for climate change and variability, as well as water resource management and planning. This study investigated the impact of the Indian Ocean Dipole (IOD) on rainfall and discharge variability in the Dwangwa River Basin (DRB) in Malawi, a key inflow to Lake Malawi. Specifically, the study analysed annual rainfall variability trends from 1985 to 2015 using the Coefficient of Variation (CV) and the annual Precipitation Concentration Index (PCI). The significance and direction of rainfall and discharge trends were quantified using the Mann–Kendall trend test at α = 0.05 significance level. To evaluate the association between rainfall and IOD, the Pearson product moment used three IOD phases: positive, negative, and neutral. Simple linear regression was utilised to check the response of the river during the concerned IOD phases. The study found CVs between 20 and 30%, typical of climates with moderate monthly rainfall variability. The PCI ranged from 20 to 30%, suggesting a strongly seasonal and highly variable temporal intra-annual rainfall distribution in the DRB. Moreover, the Mann–Kendall test statistics showed insignificant decrease in annual rainfall trends. Further, the findings demonstrated an insignificant negative correlation between rainfall and positive IOD, with rainfall increases associated with negative IOD, whereas positive IOD is associated with decreased river discharge. Consequently, El Niño and a positive IOD could cause DRB to have low water availability. Therefore, the study demonstrates that rainfall is experiencing a decreasing trend, which is driven by large-scale mechanics.

Significance of Having Integrated Water Resource Plan in a Complex Watershed System for Better Water Management during Covid Pandemic: The Case of Mahaweli River Basin

Significance of Having Integrated Water Resource Plan in a Complex Watershed System for Better Water Management during Covid Pandemic: The Case of Mahaweli River Basin

Bee-inspired insights: Unleashing the potential of artificial bee colony optimized hybrid neural networks for enhanced groundwater level time series prediction.

Analysis of the change in groundwater used as a drinking and irrigation water source is of critical importance in terms of monitoring aquifers, planning water resources, energy production, combating climate change, and agricultural production. Therefore, it is necessary to model groundwater level (GWL) fluctuations to monitor and predict groundwater storage. Artificial intelligence-based models in water resource management have become prevalent due to their proven success in hydrological studies. This study proposed a hybrid model that combines the artificial neural network (ANN) and the artificial bee colony optimization (ABC) algorithm, along with the ensemble empirical mode decomposition (EEMD) and the local mean decomposition (LMD) techniques, to model groundwater levels in Erzurum province, Türkiye. GWL estimation results were evaluated with mean square error (MSE), coefficient of determination (R2), and residual sum of squares (RSS) and visually with violin, scatter, and time series plot. The study results indicated that the EEMD-ABC-ANN hybrid model was superior to other models in estimating GWL, with R2 values ranging from 0.91 to 0.99 and MSE values ranging from 0.004 to 0.07. It has also been revealed that promising GWL predictions can be made with previous GWL data.

Non-stationary models for hydrological extremes in the mountain rivers of the Argentinean Central Andes

ABSTRACT The assessment of extreme hydrological events relies on the assumption that time series are independent and identically distributed. However, empirical evidence contradicts this assumption, indicating the presence of nonstationarity, including trends, step changes, or both, in the river records of the Argentinean Central Andes. This study proposes the use of generalized additive models in location, scale and shape (GAMLSS) to model the annual maximum and minimum flow of seven rivers. Firstly, the presence of trends and step changes was assessed. Subsequently, the models were formulated considering time and various climatic indices as covariates. The findings reveal declining trends and negative jumps over the past 50 to 70 years. The location parameters of the models exhibit linear or smoothing dependence with time or climate indices covariates. Different modes of climate variability are associated with hydrological extremes. The nonstationary models provide a novel complementary framework for water resource planning in the region.

Six years of high-resolution climatic data collected along an elevation gradient in the Italian Alps

The complex meso- and microclimatic heterogeneity inherent to mountainous regions, driven by both topographic and biotic factors, and the lack of observations, poses significant challenges to using climate models to predict and understand impacts at various scales. We present here a six-year dataset (2017–2022) of continuous climatic measurements collected at five elevations from 983 m to 2705 m above sea level in the Val Mazia - Matschertal valley in the Italian Alps. The measurements include the air temperature, relative humidity, wind speed and direction, solar radiation, soil properties, precipitation, and snow height. Collected within the European Long-Term Ecological Research program (LTER), this dataset is freely available in an open access repository. The time series may be valuable for the validation of regional climate models, atmospheric exchange modelling, and providing support for hydrological models and remote sensing products in mountain environments. Additionally, our data may be useful for research on the influence of elevation on ecological processes such as vegetation growth, plant composition, and soil biology. Beyond its utility in advancing such fundamental research, meteorological monitoring data contribute to informed socio-political decisions on climate adaptation strategies, land management, and water resource planning, enhancing the safety and resilience of mountain communities and biodiversity.

Numerical simulation of groundwater in hyporheic zone with coupled parameter stochastic scheme

Groundwater numerical modeling is a crucial scientific tool for understanding groundwater circulation and supporting regional water resource planning and management. The effectiveness of these models depends largely on the accuracy of hydrogeological parameters within aquifers, which are often spatially heterogeneous and randomly distributed due to complex geological and tectonic factors. Traditional modeling approaches frequently overlook this randomness, compromising the precision and resolution of groundwater simulations. This study focuses on a section of the Qingshui River in the Huaihe River Basin. Using field and laboratory data, probability distribution functions for key parameters like hydraulic conductivity, specific yield, and specific storage were developed. These functions were integrated into the groundwater model to reflect the inherent stochastic nature of aquifer properties. This integration significantly enhanced model accuracy, reducing the root mean square error of simulated water levels from 0.47–1.43 m to 0.13–0.16 m and improving the Nash-Sutcliffe efficiency coefficients (NSE) from −2.96–0.73 to 0.94–0.98. Additionally, the model facilitated analysis of the interactions between river and groundwater, particularly in the hyporheic zone, under various scenarios. It identified spatial and temporal variations in groundwater recharge dynamics and delay effects at different distances from the river channel. For instance, recharge rates at 50 m and 150 m from the river were 0.295 m/day and 0.015 m/day, respectively, indicating stronger recharge closer to the river. The study also assessed the impact of varying river flows, riverbed permeability, and irrigation practices on water exchanges between the river and groundwater. These factors were found to significantly influence the intensity of water exchange, seepage, and groundwater reserves. This research provides valuable insights for managing river-groundwater interactions and analyzing the ecological environment of surrounding groundwater systems, underscoring the importance of incorporating stochastic characteristics into groundwater modeling.

Research on Runoff Prediction Based on Time2Vec-TCN-Transformer Driven by Multi-Source Data

Due to the frequent occurrence of extreme weather in recent years, accurate runoff prediction is crucial for the rational planning and management of water resources. Addressing the high uncertainty and multiple influencing factors in runoff prediction, this paper proposes a runoff prediction method driven by multi-source data. Based on multivariate observed data of runoff, water level, temperature, and precipitation, a Time2Vec-TCN-Transformer model is proposed for runoff prediction research and compared with LSTM, TCN, and TCN-Transformer models. The results show that the Time2Vec-TCN-Transformer model outperforms other models in metrics including MAE, RRMSE, MAPE, and NSE, demonstrating higher prediction accuracy and reliability. By effectively combining Time2Vec, TCN, and Transformer, the proposed model improves the MAPE for forecasting 1–4 days in the future by approximately 7% compared to the traditional LSTM model and 4% compared to the standalone TCN model, while maintaining NSE consistently between 0.9 and 1. This model can better capture the periodicity, long-term scale information, and relationships among multiple variables of runoff data, providing reliable predictive support for flood forecasting and water resources management.

Water yield forecast in Shandong Province based on InVEST model

A better understanding of the effects of land use change and climate change on water yield is highly important for water resource planning and sustainable management. Land use changes in Shandong Province were analyzed over recent years. The PLUS Model was applied to forecast the land use layout for 2032, with adjustments made based on actual conditions and utilizing various CMIP6 scenarios for precipitation and actual evapotranspiration. The 2032 Water Yield was quantified using the InVEST Model at both grid and administrative scales, and its temporal-spatial characteristics and spatial correlation were analyzed. The findings revealed several key points: first, a decrease of 16.92% in arable land area, along with diminishing trends in grassland and unused land, and an increase of 33.92% in built-up land area, accompanied by growth in forest and water area. Second, the water yield decreases from southeast to northwest in Shandong Province, with significant inter-annual variations. Third, future predictions suggest that the annual water yield generally increases during flat water years, with offshore areas exhibiting greater water yield depth compared to inland areas. Rizhao is projected to have the highest water yield depth, while Binzhou and Dongying are expected to have the lowest depths, with a spatially positive correlation between them.

Effects of Climate Change and Human Activities on Runoff in the Upper Reach of Jialing River, China

In recent years, the runoff of numerous rivers has experienced substantial changes owing to the dual influences of climate change and human activities. This study focuses on the Lixian hydrological station’s controlled basin, located in the upper reaches of the Jialing River in China. The objective is to assess and quantify the impacts of human activities and climate change on runoff variations. This study analyzed runoff variations from 1960 to 2016 and employed the Soil and Water Assessment Tool (SWAT) model, the long short-term memory (LSTM) model, and eight Budyko framework formulations to assess factors influencing runoff. Additionally, it used the patch-generating land use simulation (PLUS) and SWAT models to simulate future runoff scenarios under various conditions. The results indicate the following. (1) The study area has witnessed a significant decline in runoff (p &lt; 0.01), while potential evapotranspiration shows a significant upward trend (p &lt; 0.01). Precipitation displays a nonsignificant decreasing trend (p &gt; 0.1). An abrupt change point in runoff occurred in 1994, dividing the study period into baseline and change periods. (2) The Budyko results reveal that human activities contributed 50% to 60% to runoff changes. According to the SWAT and LSTM models, the contribution rates of human activities are 63.21% and 52.22%, respectively. Human activities are thus identified as the predominant factor in the decline in runoff. (3) Human activities primarily influence runoff through land cover changes. Conservation measures led to a notable increase in forested areas from 1990 to 2010, representing the most significant change among land types. (4) Future land use scenarios suggest that the highest simulated runoff occurs under a comprehensive development scenario, while the lowest is observed under an ecological conservation scenario. Among the 32 future climate scenarios, runoff increases significantly with a 10% increase in precipitation and decreases substantially with a 15% reduction in precipitation. These findings underscore the significant impact of human activities and climate change on runoff variations in the upper reaches of the Jialing River, highlighting the importance of incorporating both factors in water resource management and planning.