Watershed Analysis Research Articles

Morphometric Analysis and Prioritization of Watersheds for Flash Floods Management in Wadi Arab Catchment, North Jordan

Morphometric Analysis and Prioritization of Watersheds for Flash Floods Management in Wadi Arab Catchment, North Jordan

Comparison of Several Methods for Analysis Slope Length Index Factor at A Watershed Scale

Slope length and steepness factor index (LS) is one of the parameters for the Universal Soil Loss Equation (USLE) to estimate soil erosion. Currently, several methods for LS analysis, i.e. Wischmeier-Smith, Moore-Nieber, and Desmet – Govers. This study aims to compare the Wischmeier-Smith method, Moore–Nieber method, and Desmet–Govers method to analyze LS in the watershed in Manokwari – West Papua. This research consists of 4 main stages, i.e. data inventory, watershed boundary delineation, LS analysis, and LS comparison. The research showed that the Wischmeier-Smith method gave a higher LS value than the Moore – Nieber method and the Desmet – Govers method. Meanwhile, the Desmet – Gover method gives a lower average LS value than the Wischmeier-Smith method and the Moore – Nieber method. Based on the T-test, the LS produced by the Wischmeier-Smith, Moore-Nieber, and Desmet–Govers methods has significant differences in analyzing LS in the watershed in Manokwari – West Papua. Keywords: Desmet – Govers, Moore – Nieber, Universal Soil Loss Equation, Watershed, Wischmeier-Smith

Spatio-temporal characteristics and multi-scale risk identification of pollution load based on sensitivity analysis in small watersheds located in Tuojiang River Basin, China.

High-quality development of water resources supports high-quality socio-economic development. High-quality development connects high-quality life, and clarifying the key management contents of small watersheds plays an important role in building ecologically clean small watersheds and promoting regional production and life. Previous research on pollution loads has focused on examining the impact of various external drivers on pollution loads but still lacks research on the impact of changes in pollution sources themselves on pollution loads. In this study, sensitivity analysis was used to determine the impact of changes from different sources on the total pollution loads, which can recognize the critical pollution sources. We first employed the pollutant discharge coefficient method to quantify non-point source pollution loads in the small watershed in the upstream Tuojiang River basin from 2010 to 2021. Then, combination sensitivity analysis with Getis-Ord Gi* was used to identify the critical sources and their crucial areas at the global, districts (counties), and towns (streets) scales, respectively. The results indicate: (1) The pollution loads of COD, NH3-N, TN, and TP all show a decreasing trend, reducing by 18.3%, 16.2%, 18.6%, and 28.1% from 2010 to 2021, respectively; (2) Livestock and poultry breeding pollution source is the most critical source for majority areas across watershed; (3) High-risk areas are mainly concentrated in Jingyang district and its subordinate towns (streets). There is a trend of low-pollution risk areas transitioning to high-pollution risk areas, with high-risk areas predominantly concentrated in the southeast and exhibiting a noticeable phenomenon of pollution load spilling around. This study can promote other similar small watersheds, holding significant importance for non-point source pollution control in small watersheds.

Digital Elevation Model (DEM) from Google Earth Pro and Freely Downloadable DEMs – A Case Study

Digital Elevation Models (DEMs) play a crucial role in watershed modelling and hydrological analysis. In recent years, the availability of high-resolution satellite imagery and remote sensing data has made it easier to generate DEMs using different software and platforms. Google Earth Pro (GEP) is one such platform that offers a user-friendly interface for generating DEMs, making it a popular choice among researchers and practitioners. However, the accuracy and reliability of the DEMs generated by GEP in different regions and under different environmental conditions have not been fully investigated. The increasing development activities change the earth’s topography, which in turn makes it necessary more frequent production of DEM. As it is a costlier task urban areas are given priority. This article focuses on a new methodology for generating DEM from GEP for a small area in the Ernakulam District of Kerala State, India. DEM prepared from GEP is then compared with different DEMs like SRTM 30m, ALOS PALSAR 12.5m and Cartosat 10m as well as ground surveyed values. It is observed that DEM prepared from GEP is as precise as other freely available DEMs as well as Cartosat 10m. Hence this DEM can be used for planning micro level developmental activities for smaller areas.

Unveiling seasonal nitrate contamination dynamics in cropland sub-watersheds: A geo-morphological analysis of the bilate agricultural watershed

Cropland sub-watershed surface and groundwater contamination are pressing issues for water management. This study examines the impact of sediment transport indices (STI) on nitrate concentration in downstream water bodies. The research highlights rainfall's significant role in predicting seasonal nitrate levels. Employing GIS-SWPT tools and hydro-geomorphologic analysis, cropland sub-watersheds, particularly sub-watersheds one and three, are prioritized for their high contribution to downstream surface and groundwater nitrate contamination, with prioritization values of 105.58 and 180.63, respectively. Statistical analysis, conducted using Python's scikit-learn library, validated the findings of the study, with the model's F-statistic of 79.63 and a corresponding p-value of 0.0147 underscoring its overall significance. However, while STI alone showed a prioritization parametric correlation coefficient of 0.5077, suggesting other external factors also contribute to nitrate loading, a strong relationship between STI and nitrate concentration was revealed (R² of 0.993). This integrated approach enhances understanding of how geomorphologic parameters of cropland sub-watersheds influence water quality downstream. By clarifying the complex interactions between sediment transport and nitrate concentration, evidence-based strategies can be developed to mitigate surface and groundwater nitrate pollution. This research provides valuable insights into cropland sub-watershed pollution dynamics and informs targeted management interventions.

A multidirectional pairwise coupling approach with spectral features unmixing to quantify total phosphorus, total nitrogen, and chlorophyll-a in urban rivers

Comprehensive and effective water quality monitoring is vital to water environment management and prevention of water quality from degradation. Unmanned aerial vehicle (UAV) remote sensing techniques have gradually matured and prevailed in monitoring water quality of urban rivers, posing great opportunity for more effective and flexible quantitative estimation of water quality parameter (WQP) than satellite remote sensing techniques. However, current UAV remote sensing methods often entail large quantities of cost-prohibitive in-situ collected training samples with corresponding chemical analysis in different monitoring watersheds, laying time and fiscal pressure on local environmental protection department. They suffer relatively low calculation accuracy and stability and their applicability in various watersheds is constrained. This study developed a unified two-stage method, multidirectional pairwise coupling (MDPC) with information sharing and delivery of different modeling stages to efficiently predict concentrations of WQPs including total phosphorus (TP), total nitrogen (TN), and chlorophyll-a (Chl-a) from hyperspectral data. MDPC incorporates exterior and interior feature interaction and gravity model variant to improve prediction accuracy and stability with consideration of mutual effect in the proximity. The structure design and workflow of MDPC ensure high robustness and application prospect due to achievement of good performance with less training samples, improving applicability and feasibility. The experiments show that MDPC has achieved good performance on retrieval of WQPs concentrations including TP, TN, and Chl-a, the results mean absolute percent error (MAPE) and coefficient of determination (R2) ranging from 6.34 % to 11.94 % and from 0.74 to 0.93. This study provides a systematic and scientific reference to formulate a feasible and efficient water environment management scheme.

How much rainwater contributes to a spring discharge in the Guarani Aquifer System: insights from stable isotopes and a mass balance model

ABSTRACT Outcrops play an important role in groundwater recharge. Understanding groundwater origins, dynamics and its correlation with different water sources is essential for effective water resources management and planning in terms of quantity and quality. In the case of the Guarani Aquifer System (GAS) outcrop areas are particularly vulnerable to groundwater pollution due to direct recharge processes. This study focuses on the Alto Jacaré-Pepira sub-basin, a watershed near Brotas, a city in the central region of the state of São Paulo, Brazil, where groundwater is vital for supporting tourism, agriculture, urban water supply, creeks, river and wetlands. The area has a humid tropical climate with periods of both intense rainfall and drought, and the rivers remain perennial throughout the year. Therefore, the aim of this study is to investigate the interconnections between a spring and its potential sources of contribution, namely rain and groundwater, in order to elucidate the relationships between the different water sources. To achieve this, on-site monitoring of groundwater depth, rainfall amount, and stable isotope ratios (deuterium (2H) and oxygen-18 (18O)) from rain, spring discharge, and a monitoring well was carried out from 2013 to 2021. The results indicate that the mean and standard deviations for δ18O in rainwater exhibit higher variability, resulting in −4.49 ± 3.18 ‰ VSMOW, while δ18O values from the well show minor variations, similar to those of the spring, recording −7.25 ± 0.32 ‰ and −6.94 ± 0.28 ‰ VSMOW, respectively. The mixing model’s outcomes reveal seasonal variations in water sources contribution and indicate that groundwater accounts for approximately 80 % of spring discharge throughout the year. Incorporating stable isotopes into hydrological monitoring provides valuable data for complementing watershed analysis. The values obtained support the significance of the aquifer as a primary source, thereby offering critical insights into stream dynamics of the region.

Fill‐spill‐merge terrain analysis reveals topographical controls on Canadian river runoff

AbstractDigital Elevation Models (DEMs) are a crucial tool for watershed analysis, offering valuable insights into landscape‐scale hydrology. Traditional watershed delineations are derived by filling a DEM to force flow paths through topographic depressions, thus creating a continuous drainage network throughout the domain. However, this approach is challenged in landscapes with abundant real‐world depression storage, intermittently flowing stream channels, and internally drained lake basin (endorheic basin) such as the Canadian Shield (CS). The CS landscape is characterized by “fill‐and‐spill” surface water hydrology, with runoff flow paths controlled by bedrock sills and rocky cascades that overtop when water levels are high but cease flowing when water levels are low. To better represent these intermittent drainage networks, we apply a non‐traditional, less‐aggressive DEM filling model (Fill‐Spill‐Merge or FSM) to a continental‐scale DEM (MERIT) all of Canada. To ensure adequate filling of DEM noise while also preserving real‐world topographic depressions, we propose a climatic method to initialize a key FSM parameter (“runoff depth”) that calibrates observed discharges from 1690 Environment and Climate Change Canada (ECCC) river gauges with climate model P‐ET (precipitation minus evapotranspiration) data. Our application of FSM to all 1690 gauged watersheds identifies 916 significant topographical control points controlling >20% and/or 1000 km2 of their respective areas. The Geikie, Snare, Kazan, Tazin, and Seal rivers may be particularly affected, with impacted watershed areas ranging from 12% to 64%. Extending this approach to ungauged parts of the CS reveals an additional 635 significant topographical control points. Ensemble climate model projections suggest that around 10% of these control points are currently dry but will become active by 2100. This research explicitly determines how CS watersheds are affected by fill‐and‐spill hydrology, and demonstrates the importance of accurate terrain modelling for delineating surface water flow paths in depressional landscapes.

An Approach for Modeling the Orographic–Forcing Effect via Random Cascades and the Long‐Term Statistics of Mexico City's Daily Precipitation

AbstractThe orographic effect on the spatial structure of precipitation is a fundamental problem in hydrometeorology that still requires a better understanding of the physical processes involved in the emergence of rainfall patterns and their complex statistical structure. In tropical regions, where meteorological measurements are notoriously sparse and data quality control is often poor or missing, the study of precipitation modeling and prediction is challenging. This research aims to show an innovative approach based on a random cascade downscaling method to generate high‐resolution precipitation products from coarse‐scale precipitation products. This approach also includes a topographic enhancement function for describing the altitudinal variability of precipitation and a numerical diffusion filter to lessen the blockiness problem of random cascades. The suggested approach was applied to analyze some long‐term precipitation statistics in the metropolitan area of Mexico City. The model result agrees closely with the temporal statistics of the selected precipitation products and reflects complex orographic constraints. The proposed downscaling approach becomes an alternative to expensive computational methods and allows urban hydrology applications and analysis of small watersheds to incorporate the effects of complex orography.

Land scale division and multifunctional evaluation for Fuping County, China, based on DEM-based watershed analysis.

Land is the spatial background and basic carrier of human survival and development. The study of land function evaluation at different scales can promote the harmonious coexistence of humans and nature. Taking Fuping County, Hebei Province, China, as an example, this study establishes the theoretical framework of county-level land scale division using a digital elevation model (DEM)-based watershed analysis method and establishes the theory and methodological system of land function evaluation from the perspective of the characteristic scale. The multifunctionality of the land was evaluated using the Carnegie-Ames-Stanford approach (CASA), the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model and comprehensive index evaluation. By using the methods of DEM-based watershed analysis, dominant factor differentiation and layer superposition, a three-level scale system of 'subwatershed scale-land chain scale-land segment scale' and a multifunctional multiscale evaluation index system containing 18 evaluation indices were established. The single-function and multifunction evaluation results of land at different scales were obtained by the comprehensive index method and Getis-Ord Gi* index method. The accuracy of land function evaluation results mainly depends on the selection of the measurement scale. The land measurement scale determined by DEM-based watershed analysis is close to the intrinsic scale of land function evaluation. The scale effect of land function in different temporal and spatial ranges is also evident and shows obvious spatial heterogeneity and difference. At larger scales, individual functions show synergistic effects.

Hydrological Analysis of Agricultural Reservoir Watersheds Based on Water Utilization System Using the Catchment Hydrology Cycle Analysis Tool Model

In this study, the catchment hydrology cycle analysis tool (CAT) model was used to conduct a comprehensive hydrological analysis of the water balance of agricultural reservoirs. Data from 2010 to 2017, including precipitation, water level data in the reservoir, groundwater usage, and wastewater discharge, were collected and compiled for the upper reaches of the Hantan River Dam. The current conditions and content curves of the 11 reservoirs within the watershed were investigated and recorded. The results were analyzed by simulating three scenarios: treating the entire watershed as 1 unit, dividing the watershed into 5 sub-watersheds according to the standard watershed criteria, and further subdividing it into 27 watersheds, taking into account the presence of agricultural reservoirs. In cases where watershed information is lacking, it is deemed that subdividing the watershed can enhance efficiency. The highest model efficiency was observed in the 27 sub-basins, particularly when accounting for agricultural reservoirs. This study proposed an efficient method for hydrological analysis of watersheds including ungauged areas.

Clustering of small watersheds in hilly areas based on complex network theory and similarity analysis

ABSTRACT Clustering analysis of small watersheds is an effective tool for identifying the similarity of runoff generation and concentration. In this paper, 545 small watersheds in the hilly areas of Shandong Province were investigated, and 12 indicators representing their climate and subsurface characteristics were selected to identify communities based on hydrological similarity. We further analyzed the hydrological connections among the small watersheds within each community using three indicators (network mean, centrality, and k-core). Finally, the clustering results were evaluated on the basis of the small watershed flood peak modulus. The results of this complex network method indicate that the study area contained six large communities and nine small communities. The community-clustering results were reasonable and showed the interconnectedness of the watersheds within each community. The three network indicators adequately described the degree of similarity, the representativeness of the watersheds, and the spatial scales of similar hydrological features. This method should be helpful for addressing the issue of parameter transplantation in ungauged watersheds and implementation of a flood risk management strategy.

Morphometric analysis of the Middle Tuirial watershed, Mizoram, India and its significance for soil loss risk

This study aims to highlight the quantitative analysis of Middle Tuirial watershed in Mizoram, India and its significance for soil loss risk. In addition to understanding landscape evolution and hydrological characteristics of the river basin, it is crucial to implement appropriate soil and water conservation practices, to reduce further soil erosion risk in the basin. Linear, areal and relief aspects of morphometric parameters were analyzed using a survey of India topographical maps, advanced land observing satellite (ALOS) phased array type L-band synthetic aperture radar (PALSAR) digital elevation model (DEM), and geographic information system (GIS). The study reveals a high drainage density of 5.22 km/km2 and stream frequency of 10.58 km2, which denotes the basin exhibits high surface run-off with low groundwater recharge. In addition, it has 0.6 form factor, 0.3 elongated ratio and 0.43 circularity ratio indicating a highly elongated shape of the basin. Furthermore, the hypsometric integral values of 0.48 with an s-curve show the basin has attained a mature stage of landscape evolution.

Impact of revegetation and agricultural intensification on water storage variation in the Yellow River Basin

The Yellow River Basin (YRB) is experiencing a critical water resource shortage due to climate change and human activities. Thoroughly understanding water resource dynamics under the dual pressures of revegetation and agricultural intensification presents significant challenges. Development of satellite-based observations for vegetation and water storage has greatly facilitated large-scale and high-resolution watershed analysis, and enables understanding their dynamics. In this study, the effects of revegetation and agricultural intensification were assessed by incorporating multiple vegetation indices and phenological methods. Regression models were developed to determine how much water variation could be attributed to vegetation change driven by these human activities, using an expanded set of vegetation features to analyze seasonal water storage variation. The results indicate that both revegetation and agricultural intensification played important roles in the decline of water storage in the YRB and showed significant heterogeneity across the basin. In semi-humid and semi-arid regions, revegetation can explain over 60 % of groundwater reduction throughout the year, while in arid areas, the primary impact was particularly revealed in summer soil moisture, with the explanation rate reaching 70 %. Water storage in the downstream croplands decreased at a rate of 18 mm·yr−1 due to a combination of intensified irrigation and reduced precipitation. In the upstream croplands, crop structure changes and irrigation reduction led to a reduction in spring and winter water storage at a rate of 2 mm·yr−1. Consequently, the security of water, food, and ecosystems is challenged. This study benefits sustainable management of the YRB by providing comprehensive vegetation features and their impact on water storage.

Application of Multimedia Man-Machine Interaction in College Physical Education Teaching

In the realm of physical education in college, the traditional classroom teaching approach primarily relies on paper textbooks and demonstrations by the teacher. However, in today's physical education classrooms, there is a need to change these traditional teaching methods. Utilizing multimedia technology and interactive interfaces, teachers can demonstrate the essential actions and intricate details through multimedia videos and other formats such as push-pull and shaking. This chapter introduces a multi-segment human body tracking algorithm that focuses on real-time tracking. The human body target is divided into multiple segments, and an online learning method based on Hough Forests is used to learn the overall appearance of the human body and the appearance model of each segment. The research findings indicate that when the merged area exceeds 82.36% of the pre-segmentation area using watershed analysis, smaller areas lead to faster segmentation speed, while larger areas result in slower segmentation speed. Compared to other methods, this approach yields better recognition results.

A hybrid deep learning approach for streamflow prediction utilizing watershed memory and process-based modeling

Abstract Accurate streamflow prediction is essential for optimal water management and disaster preparedness. While data-driven methods’ performance often surpasses process-based models, concerns regarding their ‘black-box’ nature persist. Hybrid models, integrating domain knowledge and process modeling into a data-driven framework, offer enhanced streamflow prediction capabilities. This study investigated watershed memory and process modeling-based hybridizing approaches across diverse hydrological regimes – Korean and Ethiopian watersheds. Following watershed memory analysis, the Soil and Water Assessment Tool (SWAT) was calibrated using the recession constant and other relevant parameters. Three hybrid models, incorporating watershed memory and residual error, were developed and evaluated against standalone long short-term memory (LSTM) models. Hybrids outperformed the standalone LSTM across all watersheds. The memory-based approach exhibited superior and consistent performance across training, evaluation periods, and regions, achieving 17–66% Nash–Sutcliffe efficiency coefficient improvement. The residual error-based technique showed varying performance across regions. While hybrids improved extreme event predictions, particularly peak flows, all models struggled at low flow. Korean watersheds’ significant prediction improvements highlight the hybrid models’ effectiveness in regions with pronounced temporal hydrological variability. This study underscores the importance of selecting a specific hybrid approach based on the desired objectives rather than solely relying on statistical metrics that often reflect average performance.

Research on the Identification of Typical Terrain Patterns in Yunnan Province Based on the K-Means Technology

Wire icing is a prevalent challenge in both industrial and scientific domains, and it is widely acknowledged that terrain and water vapor are significant contributing factors in the formation of wire icing. Consequently, the identification of terrains that are prone to inducing water vapor uplift serves as the scientific foundation for predicting ice accumulation on power lines. Yunnan Province, a mountainous province in China, features a large elevation difference. In winter, this region is prone to wire, pole and tower icing, which can affect power transmission and cause economic and property losses. Therefore, it is necessary to conduct research on the identification of typical terrain patterns in this region. In previous terrain studies, more attention has been focused on slope and aspect, watershed analysis and terrain profile analysis. When the purpose of the terrain identification is to analyze which terrains are more prone to collecting water vapor, we hope to obtain slightly larger terrain blocks and analyze the water vapor sources for different terrains in order to identify typical terrains that are conducive to icing formation. A new technology for identifying terrain patterns based on the K-means clustering method is proposed in this study to explore the typical terrain in Yunnan province. Additionally, the influences of different terrain patterns on water vapor movement are also analyzed. The results indicate that the typical terrains in Yunnan are “Valley-Air Channel”, “Topographic Uplifting”, “Ravine”, “Mountain Pass” and “Alpine Divide” patterns. The results show that the identified typical terrain is consistent with observations from satellite images, which verifies the effectiveness of this identification method. Among these five typical terrains, the “Valley-Air Channel”, the “Topographic Uplifting” and the “Mountain Pass” terrains are prone to collecting water vapor and forming ice cover. The “Alpine Divide” terrain is also prone to accumulating water vapor on both sides to form ice cover. The identified typical terrain demonstrates that typical terrain patterns near water bodies are more prone to the occurrence of wire, pole and tower icing because these areas are abundant in water vapor, and the extensive water vapor is easily condensed under the effects of terrain uplifting and cooling. In these key areas, existing wires and towers, as well as those to be constructed in the future, deserve our special attention.

Fitting Power-Law Relations in Watershed Science and Analysis, with an Example Using the R Language

Many quantitative relationships in the environmental sciences, and specifically in watershed science, can effectively be modelled using a power-law function. Such relationships are often estimated using ordinary least squares regression after linearizing the relationship by log-transforming both the x and y variables. Alternative approaches include nonlinear least squares regression and generalized nonlinear least squares regression. However, there are some differences in the underlying characteristics of these models that can result in the generation of different relationships and associated prediction limits. This article provides an overview of the statistical models underlying these approaches, then illustrates their application using the R language for an example based on fitting a regional relationship to predict flood quantiles from catchment area. Keywords: law relationships, log-transformation, nonlinear least squares regression, generalized nonlinear least squares regression

Estimating Stream Bank and Bed Erosion and Deposition with Innovative and Traditional Methods

Understanding the contributions of stream bank and bed erosion will allow us to implement the most effective management practices. The objective of this study was to assess different methods to measure bank and bed erosion at different scales, specifically the watershed, reach and plot. Innovative and traditional methods were utilized. At the watershed scale, indices based on free satellite images were used. For the reach scale, indices were used, but the images with higher accuracy were purchased and captured by unmanned aerial vehicles (UAVs). At the plot scale, erosion pins, cross-sections and laser scanning were applied. The watershed scale analysis showcased “hot spots”. These “hot spots” were reaches vulnerable to erosion and deposition. The indices of the purchased images were applied to these “hot spots” and allowed us to narrow the length of the reaches where UAV flights took place. These flight images located where erosion and deposition occurred. Finally, at the plot scale, laser scanning provided more detailed and accurate data at a greater scale compared to the traditional methods. The implementation of these methods allows us to find the areas vulnerable to erosion and deposition. These are the areas where nature-based solutions should be implemented to effectively mitigate erosion problems.

Rating curve development and uncertainty analysis in mountainous watersheds for informed hydrology and resource management

Accurate measurement of continuous stream discharge poses both excitement and challenges for hydrologists and water resource planners, particularly in mountainous watersheds. This study centers on the development of rating curves utilizing the power law at three headwaters of the lesser Himalayas—Aglar, Paligaad, and Balganga—through the installation of water level recorders for stage measurement and salt dilution for discharge measurement from 2014 to 2016. The stream stage–discharge relationship, crucially known as the rating curve, is susceptible to numerous factors in mountainous watersheds that are often challenging to comprehend or quantify. Despite significant errors introduced during the rating curve development, such as stemming from observations, modeling, and parameterization, they are frequently overlooked. In this study, acknowledging the inherent uncertainty, we employ the maximum-likelihood method to assess uncertainty in the developed rating curve. Our findings reveal substantial inconsistency in the stage–discharge relationship, particularly during high flows. A novel contribution of this study is introducing a weighing factor concept that correlates uncertainty with the morphological parameters of the watershed. The higher value of the weighting factor in Paligaad (0.37) as compared to Balganga (0.35) and less in the case of Aglar (0.27) will have more uncertainty. The authors contend that precise rating curves and comprehensive uncertainty analyses can mitigate construction costs, foster robust decision-making, and enhance the perceived credibility of decisions in hydrology and water resource management.