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The Hydrologic Modeling System (HEC-HMS), designed to accurately simulate precipitation-runoff processes in various watershed types, was employed in our study to establish a model for a particular watershed. Consequently, we planned to create a rainfall-runoff model to investigate the specific characteristics of floods, assess some pre-diction models, and issue assumptions about their viability, which could be beneficial in establishing flood warning systems. The model was developed using daily precipitation data collected from different rain gauge stations in the Gilort watershed, located in southern Romania. The study employed the HEC-GeoHMS terrain processing tool, utilizing a digital elevation design to build a hydrological model. The statistical indicators used to evaluate the runoff mechanisms, specifically regression, coefficient of determination, correlation coefficient, index of agreement (Willmott index), and the root mean squared error (RMSE), showed a strong relationship between the simulated and recorded flow of the watershed. The leaking model was assessed using other statistical parameters, including the deviation of runoff volumes (Dv = 6.40%), Nash-Sutcliffe efficiency (NSE = 0.908), and Kling-Gupta efficiency (KGE = 0.901). These parameters confirmed that the simulated data closely matched the observed data, indicating an effective association, and were considered reliable indicators of the model's goodness of fit, ensuring its reliability and efficacy. [ABSTRACT FROM AUTHOR]

Purpose: Community health needs assessments are required for most state and local public health agencies and non-profit hospitals. Typically based on community health improvement planning models, these assessments encompass overall community health and multiple diseases to inform program planning. National Cancer Institute (NCI)-designated Cancer Centers and community-based cancer-focused programs share the goal of reducing cancer burden in the catchment areas they serve. However, to date, no published models exist to guide cancer-specific needs assessments for a determined geographic area that can inform both public health and research initiatives. The purpose of this article is to outline a cancer needs assessment (CNA) framework and community-engaged, mixed-methods process, along with a case study of how we applied it in Kentucky. Methods: We convened a steering committee of key organizational partners to provide input throughout the process. We developed a conceptual framework of multi-level determinants affecting cancer-related outcomes. We incorporated both quantitative and qualitative data gathered through a variety of means, including a novel application of group concept mapping to guide definition of priorities. Results: The resulting CNA has helped guide strategic planning and priorities for Kentucky's Cancer Action Plan, Markey Cancer Center, state agencies, and community-based organizations. Conclusion: This framework and process can be used collaboratively by cancer center Community Outreach and Engagement offices, public health agencies, oncology programs, and community partners to plan impactful cancer control programs and research in their catchment areas. Universities can also use them to inform the planning of community engagement and health equity research efforts. [ABSTRACT FROM AUTHOR]

Hidrological analysis is an important thing to do to support reservoir management activities. Hydrological data is needed as input in carrying out hydrological analysis. Quality of hudrological data is very dependent on the condition of the rainfall station network (number and location of rainfall stations). Therefore, a study is needed to review the rainfall station network in the Wonogiri Reservoir Water Catchment Area. The aim of this research is to obtain an effective and efficient rainfall station network in the catchment area to support Wonogiri Reservoir operational activities. This research uses the Kagan method for rationalization analysis of rainfall stations. Based on the analysi of the Kagan method in the Wonogiri Reservoir catchment area with an interpolation error of 5%, it produces eight recommended rainfall stations consisting of five existing rainfall stations and three new rainfall stations with a Kagan triangle length of 14.28 km. [ABSTRACT FROM AUTHOR]

Soil erosion and sediment yield is a global problem that increasingly contributes to soil degradation. Although erosion analysis requires the availability of erosion and sedimentation data, the lack of sediment monitoring stations and the resulting limitations in collecting sediment measurements have necessitated the use of experimental models in many areas. The present study aimed to compare Factorial Scoring Model (FSM) and Modified Pacific South-West Inter-Agency Committee (MPSIAC) model for estimating erosion in the Mazdaran Basin (Firoozkuh, Iran). For this purpose, the required maps were prepared for both models, and the sediment rate was estimated using the two models to compare their efficiency using the corresponding maximum error (ME) and coefficient of determination (R2) values. The results showed that considering sediment based on the FSM model, the studied catchment consisted of regions with a high and very high sediment yield, while the MPSIAC model identified regions with low, medium, and high sediment yield. With an R2 value of 0.62 and an ME value of 2.24, the MPSIAC model provided more accurate estimates of the sediment yield in the studied area. Using the MPSIAC model, sediment yield was 6687.86 tons per year or the equivalent of 2.64 tons/ha per year. [ABSTRACT FROM AUTHOR]

The run-off coefficients provide vital hydrological data used for river discharge forecasts and flood risk management. Selecting an appropriate method to determine this coefficient is essential for accurately estimating peak discharge. This study compared the effectiveness of the Hassing, Cook, and U.S. Forest Service methods integrating GIS in estimating run-off coefficients in the Lesti River catchment area from 2013 to 2019. The findings revealed that the run-off coefficient was determined to be 0.188–0.243 using the U.S. Forest Service method, 0.194–0.213 using the Hassing method, and 0.466–0.480 using the Cook method. These results showed a rapid increase in the run-off coefficient within the Lesti River catchment area, signifying a heightened susceptibility to flooding. This is particularly concerning as the Lesti River is a primary tributary to the Brantas River. The comparison of estimated versus observed peak discharge emphasised the superiority of the runoff coefficient associated with the Hassing method over alternative methodologies when utilised as input data for peak discharge estimation. This was evident by the notable measurement error values of 11% for MAPE and 0.58 for MAE. The Hassing method emerged as the most appropriate and reliable for reflecting run-off characteristics in the Lesti River catchment area. Additionally, it proved to be the most accurate for estimating run-off coefficients in the Nakayasu process for peak discharge estimation. Consequently, applying the Hassing method offers a viable strategy for effectively mitigating flood risks in the Lesti catchment area.

Abstract Zooplankton are critical indicators of pressures impacting freshwater ecosystems. We analyzed the response of zooplankton communities across different sub-catchment types—headwaters, natural, urban, urban-agricultural, and agricultural—within the Łyna river–lake system in Northern Poland. Using taxonomic groups and functional traits (body size, feeding strategies), we applied Partial Least Squares Regression (PLS-R) to elucidate the relationships between environmental conditions, land use, and zooplankton metacommunity structure. Two-Way Cluster Analysis (TWCA) identified local subsets with characteristic patterns, while Indicator Species Analysis (ISA) determined area-specific taxa. The natural river zone exhibited significant habitat heterogeneity and feeding niches, whereas urban areas created functional homogenization of zooplankton, dominated by small, broad-diet microphages. Agricultural areas promoted diversity among large filter feeders (Crustacea), active suctors (Rotifera), and amoebae (Protozoa). However, intensified agricultural activities, substantially diminished the zooplankton population, biomass, taxonomic richness, and overall ecosystem functionality. The impact of land cover change is more pronounced at small-scale sub-catchments than at the catchment level as a whole. Therefore, assessing these impacts requires detailed spatial and temporal analysis at the sub-catchment level to identify the most affected areas. This study introduces a new sub-catchment-based perspective on ecosystem health assessment and underscores the zooplankton's role as robust indicators of ecological change.

Abstract For managing water resources and operating reservoirs in dynamic contexts, accurate hydrological forecasting is essential. However, it is difficult to track complex hydrological time series with highly non-linear and non-stationary characteristics. The intricacy of the issue is further increased by the risk and uncertainty that are brought about by the dependence of several factors on the hydrological system’s output. To hydrologically model river outflows, a hybrid GARCH time series model technique has been applied in this study. To improve the precision of the proposed model estimation, this hybrid model employs a controllable fuzzy logic system to explore the impact of various input variables and an Archimedean detail function to account for the uncertainty in the dependence of the variables. The prediction error in this model is minimized by utilizing weighting factors and problem analysis parameters that are calculated using the water cycle algorithm. It was found that the minimum root-mean-square error values for the training and testing modeling stages are RMSE = 1.89 m and 1.92 m, respectively, by looking at the hydrological modeling results for a watershed of the Karaj dam. For extended lead (i.e., a 6-month rainfall lag), the weakest forecasting capacity was found. The modeling of the copula function using a higher percentage of answers in the confidence band and a smaller bandwidth resulted in less uncertainty for the estimation of the suggested model, according to the uncertainty analysis.

Zooplankton are critical indicators of pressures impacting freshwater ecosystems. We analyzed the response of zooplankton communities across different sub-catchment types—headwaters, natural, urban, urban-agricultural, and agricultural—within the Łyna river–lake system in Northern Poland. Using taxonomic groups and functional traits (body size, feeding strategies), we applied Partial Least Squares Regression (PLS-R) to elucidate the relationships between environmental conditions, land use, and zooplankton metacommunity structure. Two-Way Cluster Analysis (TWCA) identified local subsets with characteristic patterns, while Indicator Species Analysis (ISA) determined area-specific taxa. The natural river zone exhibited significant habitat heterogeneity and feeding niches, whereas urban areas created functional homogenization of zooplankton, dominated by small, broad-diet microphages. Agricultural areas promoted diversity among large filter feeders (Crustacea), active suctors (Rotifera), and amoebae (Protozoa). However, intensified agricultural activities, substantially diminished the zooplankton population, biomass, taxonomic richness, and overall ecosystem functionality. The impact of land cover change is more pronounced at small-scale sub-catchments than at the catchment level as a whole. Therefore, assessing these impacts requires detailed spatial and temporal analysis at the sub-catchment level to identify the most affected areas. This study introduces a new sub-catchment-based perspective on ecosystem health assessment and underscores the zooplankton's role as robust indicators of ecological change. [ABSTRACT FROM AUTHOR]

Geospatial information on river gauging stations, such as station locations, catchment boundaries, river flow paths and other hydrographic data are basic building blocks of hydrological analyses. Such information for India's river basins is available from Central Water Commission (CWC) and water resources information system (WRIS), but is limited in extent and unreliable. Using widely used global hydrography products, catchment boundaries were delineated for 100 gauging stations in the Ganga river basin (GRB), and their catchment areas were estimated. The delineated boundary for the GRB, and also station-wise catchment areas from the present study were much more consistent with global hydrography products than those available from CWC and WRIS. Lack of reliable, analysis-ready hydrography data is a hindrance to hydro-climatological research. The long-term objective of this study is to help build such a needed dataset using high-resolution remote sensing products. [ABSTRACT FROM AUTHOR]

The run-off coefficients provide vital hydrological data used for river discharge forecasts and flood risk management. Selecting an appropriate method to determine this coefficient is essential for accurately estimating peak discharge. This study compared the effectiveness of the Hassing, Cook, and U.S. Forest Service methods integrating GIS in estimating run-off coefficients in the Lesti River catchment area from 2013 to 2019. The findings revealed that the run-off coefficient was determined to be 0.188-0.243 using the U.S. Forest Service method, 0.194-0.213 using the Hassing method, and 0.466-0.480 using the Cook method. These results showed a rapid increase in the run-off coefficient within the Lesti River catchment area, signifying a heightened susceptibility to flooding. This is particularly concerning as the Lesti River is a primary tributary to the Brantas River. The comparison of estimated versus observed peak discharge emphasised the superiority of the runoff coefficient associated with the Hassing method over alternative methodologies when utilised as input data for peak discharge estimation. This was evident by the notable measurement error values of 11% for MAPE and 0.58 for MAE. The Hassing method emerged as the most appropriate and reliable for reflecting run-off characteristics in the Lesti River catchment area. Additionally, it proved to be the most accurate for estimating run-off coefficients in the Nakayasu process for peak discharge estimation. Consequently, applying the Hassing method offers a viable strategy for effectively mitigating flood risks in the Lesti catchment area. [ABSTRACT FROM AUTHOR]

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[Objective] The aims of this study are to analyze the quantitative relationship between runoff depth. soil erosion, and factors such as catchment area and slope to provide a scientific basis for the construction of physical models of soil erosion and the calibration of their parameters. [Methods] Based on measured field data of natural rainfall on runoff plots under different surface conditions, a multiple parameters nonlinear estimation model for annual rainfall runoff depth and soil erosion was established. [Results] The threshold of rainfall generating runoff initially decreased and then increased with the catchment area and slope before showing a trend of increasing followed by decreasing. The annual runoff depth (Y1) and annual soil loss (Y2) showed a pattern of first increase and then decrease with the increase in area. Y1 initially decreased and then rapidly increased with the slope while Y2. continuously increased with the slope. Both Y1, and Y2. increased with the increase in annual rainfall. When the slope arca increased to 130 square meters, both Y1, and Y2 reached to their maximum values. When the slope was 13.5 degrees. Y1 reached to its minimum value. The multi-parameter nonlinear regression estimation model for Y1, was highly accurate. with 70% of the data points having a relative error within±30%. [Conclusion] The interaction between catchment area. slope, and annual rainfall is the most significant in affecting annual rainfall runoff depth and erosion amounts. There exists a critical catchment area and a critical slope value for annual runoff depth and erosion amounts. [ABSTRACT FROM AUTHOR]

Scientific information on the spatial variability of soil properties is critical for sustainable production and designing appropriate measures for efficient soil–crop management. The growing urban areas in fertile landscapes are a major concern experiencing a huge anthropogenic onslaught and lack of information on spatial variability of soil properties. Therefore, the present study was carried out to delineate the spatial distribution of some selected soil properties from Balh Valley and its catchment area (Suketi basin) in lower Himachal Himalaya, India. A total of 468 geo-referenced surface soil samples were collected and analyzed for soil pH, EC, OC; primary nutrients (N, P, K); secondary nutrients (Ca and Mg); and DTPA-extractable micronutrients (Zn, Fe, Mn and Cu)following standard procedures. The results showed a significant variation in soil pH (acidic to alkaline), EC (0.08–0.70 dS/m), OC (3–26 g/kg), major nutrients N (41.96–208.03 mg/kg), P (5.80–18.75 mg/kg), and K (53.57–163.64 mg/kg). Among micronutrients, Zn was found below the critical limit toward the extreme fringes of the basin. The data were analyzed with descriptive statistics and geostatistical approach. The spatial maps were prepared with ordinary kriging (OK) technique after semivariogram modeling and cross-validation approach. The five principal components (PCs) chosen depicted a moderate correlation between the calculated soil attributes. The two management zones (MZs) were derived by performing the fuzzy c-means clustering analysis based on fuzzy performance index (FPI) and normalized classification entropy (NCE) analysis. The spatial maps represent the distribution of soil properties in the valley and its catchment area. The information generated provides baseline data for site-specific fertilizer recommendations for precision agriculture and minimize downstream adverse environmental impact in the Himalayan ecosystem. [ABSTRACT FROM AUTHOR]

The Hydrologic Modeling System (HEC-HMS), designed to accurately simulate precipitation-runoff processes in various watershed types, was employed in our study to establish a model for a particular watershed. Consequently, we planned to create a rainfall-runoff model to investigate the specific characteristics of floods, assess some pre-diction models, and issue assumptions about their viability, which could be beneficial in establishing flood warning systems. The model was developed using daily precipitation data collected from different rain gauge stations in the Gilort watershed, located in southern Romania. The study employed the HEC-GeoHMS terrain processing tool, utilizing a digital elevation design to build a hydrological model. The statistical indicators used to evaluate the runoff mechanisms, specifically regression, coefficient of determination, correlation coefficient, index of agreement (Willmott index), and the root mean squared error (RMSE), showed a strong relationship between the simulated and recorded flow of the watershed. The leaking model was assessed using other statistical parameters, including the deviation of runoff volumes (Dv = 6.40%), Nash−Sutcliffe efficiency (NSE = 0.908), and Kling-Gupta efficiency (KGE = 0.901). These parameters confirmed that the simulated data closely matched the observed data, indicating an effective association, and were considered reliable indicators of the model’s goodness of fit, ensuring its reliability and efficacy.

ObjectivesSmall area analysis is a health services research technique that facilitates geographical comparison of services supply and utilization rates between health service areas (HSAs). HSAs are functionally relevant regions around medical facilities within which most residents undergo treatment. We aimed to identify HSAs for psychiatric outpatient care (HSA-PSY) in Switzerland.MethodsWe used HSAr, a new and automated methodological approach, and comprehensive psychiatric service use data from insurances to identify HSA-PSY based on travel patterns between patients' residences and service sites. Resulting HSA-PSY were compared geographically, demographically and regarding the use of inpatient and outpatient psychiatric services.ResultsWe identified 68 HSA-PSY, which were reviewed and validated by local mental health services experts. The population-based rate of inpatient and outpatient service utilization varied considerably between HSA-PSY. Utilization of inpatient and outpatient services tended to be positively associated across HSA-PSY.ConclusionsWide variation of service use between HSA-PSY can hardly be fully explained by underlying differences in the prevalence or incidence of disorders. Whether other factors such as the amount of services supply did add to the high variation should be addressed in further studies, for which our functional mapping on a small-scale regional level provides a good analytical framework.

Background: National Cancer Institute (NCI) designated cancer centers are entrusted with assessing the cancer burden within their catchment areas and using this information to guide research and outreach efforts. Data visualizations, like Cancer InFocus, have emerged as essential tools for facilitating this effort. Integrating clinical trial accrual data can further enhance our understanding of the catchment area. However, these data must be de-identified in accordance with the Health Insurance Portability and Accountability Act (HIPAA). This study introduces a de-identification method through geographic aggregation, ensuring HIPAA compliance and enabling comprehensive catchment area surveillance.Methods: Home addresses of patients enrolled in clinical trials at an NCI-designated Comprehensive Cancer Center were geocoded to census tracts. Tracts with less than 20 accruals were merged using the R geographic aggregation tool. A risk assessment was conducted to ensure low re-identification risk. Accrual rates were calculated and integrated into Cancer InFocus.Results: Successful aggregation exceeded the 20-patient threshold for all merged tracts with low re-identification risk. Disparities between clinical trial accruals and social determinants of health were identified.Discussion: The geographic aggregation method, compliant with HIPAA standards and integrated with Cancer InFocus, can enhance catchment area surveillance, furthering cancer research and outreach by pinpointing area-specific needs.

Background: In 2022, the catchment area of the Fred Hutchinson/University of Washington/Seattle Children’s Cancer Consortium (the Consortium) grew from 13-counties in Western Washington State to include all 39 counties in Washington.Methods: Widening the catchment area provided new opportunities for the Consortium to monitor the cancer burden, identify cancer-related health disparities, use a bidirectional approach to develop cancer focused programming, and facilitate research in clinical and community settings.Results: In this commentary, we describe the exploratory process of catchment area change led by the Consortium’s Office of Community Outreach and Engagement and new initiatives that followed that growth.Discussion: We hope that by sharing the ongoing, data-driven community engagement approach in the Consortium’s current, statewide catchment area, our experience will be of value to other cancer centers looking to engage with communities and develop bidirectional partnerships in new areas.

Background. A key requirement of community outreach and engagement offices within National Cancer Institute-designated cancer centers is to conduct a comprehensive examination of their catchment area’s population, cancer burden, and assets. To accomplish this task, we describe the plan for implementing our initiative, the Cancer Health Assets and Needs Assessment (CHANA). CHANA compiles, into a single source, up-to-date data that describes the cancer landscape of North Carolina’s 100 counties.Methods. CHANA utilized a three phased approach: (1) compiling existing data from publicly available sources; (2) analyzing novel data source, which links state cancer registry, multi-payer insurance claims, and area-level contextual data; and (3) conducting surveys of the general public and cancer survivors and key informant interviews with cancer-related community organizations to understand their priorities and resources. These multifaceted data resources are curated and compiled into three key dissemination products: a summary report, county-level profile reports, and interactive online data dashboards.Discussion. Through data-driven efforts like CHANA, cancer centers and the communities they serve can better understand gaps in care and information needs, opportunities, and resources to improve health outcomes, and priorities for new research and programmatic endeavors focused on prevention, healthcare access, equity, and quality.

Background: Communicating complex and diverse catchment area data effectively can transform cancer prevention and care delivery and strengthen community engagement efforts of cancer centersObjective: Describe a systematic, stakeholder-driven, and theory-based approach for developing catchment area data visualization tools for cancer centersMethods: Cancer-relevant catchment area data were identified from cancer registries, national surveys, and administrative databases. A prototype for data visualization was designed, developed, and tested based on the Organize, Plan, Test, and Integrate framework. A working group collected stakeholder feedback through formative assessment. Understandability and actionability of the visualization tool were measured and open-ended feedback was collected.Results: A visualization dashboard, illustrating cancer incidence and mortality, risk factors, healthcare access, and social determinants for the Hollings Cancer Center catchment area, was developed. Color-coded maps, time-series plots, and graphs illustrated catchment area data. A total of 21 participants representing key stakeholders participated. Understandability and actionability scores exceeded 80%, and themes from qualitative data informed further improvisation. Integration of communication efforts and messages within a broader context is in progress.Discussion: A cancer center catchment area data visualization tool developed through a systematic, stakeholder-driven, and theory-based approach has high understandability and actionability, and is well-received by stakeholders.

The catchment geomorphology of the Zarqa River in Jordan was investigated using a three-dimensional model and interpretation of geology. There are three major elements that control the Zarqa River catchment and its drainage networks: lithological units, faults and paleovolcanism. The upper catchment is typical of a youthful stage of river development with relatively recent lava fields that have infilled and reduced the original size of the catchment. The lower part of the catchment includes a convex profile probably resulting from the coalescence of knickpoints generated by uplift along the Dead Sea fault. The lower and middle sections of the catchment contain remnants of an older, wider valley, 200–500 m above the present river level, that probably formed during a hiatus in tectonic and volcanic activity from ~ 22 to ~ 13 Ma. [ABSTRACT FROM AUTHOR]

This study proposes a Geographic Information System (GIS) based algorithmic design of surface road drainage systems. The algorithm identifies a mechanistic workflow based on the rational method to estimate runoff. The approach leverages satellite imagery to delineate contributing watersheds and predict the land-use class for design roads. Rainfall intensity is determined from high temporal resolution climate corrected Intensity-Duration-Frequency curves derived from cascade modelling and non-stationarity analysis based on Global Climate Models. The proposed algorithm predicts the cross-sectional area of drains considering climate change-induced rainfall correction factor of 1.14 derived from a multi ensemble of 9 RCMs with RCP4.5 scenario. The algorithm is applied to 27 roads in Bengaluru City to check the adequacy of drains. Results show an average increase of 15.7% in rainfall intensity for a five-year return, reflecting a 13.3% average increase in the cross-sectional area of roadside drains. [ABSTRACT FROM AUTHOR]

Background and objective: Political, economic, communicative and cultural borders still limit the accessibility of acute healthcare services for patients so that they frequently have to accept longer distances to travel to the next provider within their own country. In this paper, we analyze the impact of borders and opening of borders on acute medical care in hospitals and on patients in border regions. Methods: We develop a conceptual framework model of cross-border healthcare and apply it to the Polish–German border area. The model combines the distance decay effect, a catchment area analysis, economies of scale and the learning curve. Results: Borders have a major impact on acute medical care in hospitals and on patients. Setting of new borders will reduce the accessibility of health facilities for patients or require the establishment of new hospitals. Reopening borders might induce a vicious circle leading to the insolvency of a hospital which might result in poorer health for some patients. Conclusion: Strong effort should be invested to overcome political and cultural borders to improve the health of the population in border regions. Similarly, increased cross-border acute healthcare must be seen in the context of rural health and the special situation of small rural hospitals in rural peripheral areas. [ABSTRACT FROM AUTHOR]

This paper deals with the climate loading of tensile surface structures. The approaches for the snow load calculation were summarized and a new usage for tensile surface structures based on established procedures has been proposed. The snow load distribution and accumulation were presented in the form of an algorithm implemented in finite element software. The results of the algorithm for snow load accumulation were verified on simple examples with vertical, inclined, and curved surfaces. [ABSTRACT FROM AUTHOR]

ObjectiveInterfacility transfers represent a large proportion of neurosurgical admissions to tertiary care centers each year. In this study, the authors examined the impact of the COVID-19 pandemic on the number of transfers, timing of transfers, demographic profile of transfer patients, and clinical outcomes including rates of surgical intervention.MethodsA retrospective review of neurosurgical transfer patients at a single tertiary center was performed. Patients transferred from April to November 2020 (the "COVID Era") were compared with an institutional database of transfer patients collected before the COVID-19 pandemic (the "Pre-COVID Era"). During the COVID Era, both emergent and nonemergent neurosurgical services had resumed. A comparison of demographic and clinical factors between the 2 cohorts was performed.ResultsA total of 674 patients were included in the study (331 Pre-COVID and 343 COVID-Era patients). Overall, there was no change in the average monthly number of transfers (P = 0.66) or in the catchment area of referral hospitals. However, COVID-Era patients were more likely to be uninsured (1% vs. 4%), had longer transfer times (COVID vs. Pre-COVID Era: 18 vs. 9 hours; P < 0.001), required higher rates of surgical intervention (63% vs. 50%, P = 0.001), had higher rates of spine pathology (17% vs. 10%), and less frequently were admitted to the intensive care unit (34% vs. 52%, P < 0.001). Overall, COVID-Era patients did not experience delays to surgical intervention (3.1 days vs. 3.6 days, P = 0.2). When analyzing the subgroup of COVID-Era patients, COVID infection status did not impact the time of transfer or rates of operation, although COVID-infected patients experienced a longer time to surgery after admission (14 vs. 2.9 days, P < 0.001).ConclusionThe COVID-19 pandemic did not reduce the number of monthly transfers, operation rates, or catchment area for transfer patients. Transfer rates of uninsured patients increased during the COVID Era, potentially reflecting changes in access to community neurosurgery care. Shorter time to surgery seen in COVID-Era patients possibly reflects institutional policies that improved operating room efficiency to compensate for surgical backlogs. COVID status affeted time to surgery, reflecting the preoperative care that these patients require before intervention.

This study was conducted to evaluate the real cropping pattern of Khuzestan province in a normal water year (2018-2019) in terms of water withdrawal management from surface resources. For this purpose, the actual evapotranspiration of the products was calculated from the ratio of the available yield of different products (according to the agricultural statistics of 2018-2019) to the potential yield (the highest yield according to the agricultural statistics) by applying the country's water demand line system based on 10-year meteorological data. The results showed that the total water withdrawal from surface resources for the cultivated area of the crop year 2018-2019 (except greenhouses, livestock, poultry, and some products with a small area) was 18856 MCM, so the actual consumption (net irrigation requirement) was estimated 4310 MCM. Considering the Khuzestan Water Scarcity Adaptation Program, the total demand for agriculture and the environment with a confidence level of 80% in the Karun and Karkheh basins was 36 and 23.8% lower than the river flow, respectively, while it decreased to -72% in the Jarrahi basin, which indicated the failure to achieve the minimum environmental requirement. Since the Karkheh River flow has a more severe fluctuating behavior than that of Karun, this behavior cannot be predicted in the linear analysis of average values, and in droughts, it is less than the mentioned number. Therefore, dynamic planning in the field of cropping pattern change, providing various types of drought insurance, implementing infrastructure for the temporary purchase of water rights by the government, and other support policies are suggested in basins such as Karkheh, which has a highly fluctuating behavior in water supply.

The optical complexity of coastal waters is mostly caused by the water discharged from land carrying optical components (such as dissolved and particulate matter) into coastal bays and estuaries, and increasing the attenuation of light. This paper aims to investigate the links between in-water optical properties in four Swedish bays (from the northern Baltic proper up to the Bothnian bay) and the land use and land cover (LULC) in the respective catchment of each bay. The optical properties were measured in situ over the last decade by various research and monitoring groups while the LULC in each bay was classified using the Copernicus Land Monitoring Service based on Landsat 8/OLI data. The absorption coefficient of colored dissolve organic matter (CDOM) at 440 nm, aCDOM (440), was significantly correlated to Wetlands which may act as sources of CDOM, while Developed areas (Agricultural and Urban classes) were negatively correlated. The Agriculture class was also negatively related to suspended particulate organic matter (SPOM), whilst Coniferous Forests and Mixed Forests as well as Meadows were positively correlated. SPOM seems thus to mostly originate from Natural classes, possibly due to the release of pollen and other organic matter. Overall, the methods applied here allow for a better understanding of effects of land use and land cover on the bio-optical properties, and thus coastal water quality, on a macroscopic scale. [ABSTRACT FROM AUTHOR]

The extraction of drainage network and watershed information is prerequisite for the study of watershed characteristics like morphometric analysis, which provides a basis for hydrological planning and modeling. The advanced tools of algorithms, Shuttle Radar Topographic Mission (SRTM) Digital Elevation Model (DEM) data and Geographical Information System (GIS) software are used to extract drainage networks and their watershed boundaries. These tools are complicated to use or produce more errors in the extraction of elevation and drainage networks when applied to flat areas. For removal of errors and to improve the accuracy in preparation of DEM and extraction of drainage network, Burada Kalava River Basin, Andhra Pradesh, India has been taken for application of accuracy improvement algorithms. An automatic generation of drainage network and watershed using digital elevation model results in positional errors due to variations in slope and topography. This study aimed to generate a catchment area and stream network that closely represent the natural stream network and the streams' real positions. The step-by-step methodology using GRASS-interfaced Quantum GIS algorithms are given for pre-processing of DEM data to improve the positional accuracy before automatic extraction of the stream network and catchment area to resemble the real situation of the watershed. Secondly, efforts are made to analyze the DEM during automatic generation of the stream network and catchment area by assigning various area threshold values, including the application of pour point coordinates in improving the stream network and watershed characteristics. The results are verified and validated with the field information in order to improve the accuracy levels of DEM quality in generation of drainage network and catchment area. [ABSTRACT FROM AUTHOR]

IntroductionThe importance of heavy rainfall and its consequences have caused this phenomenon to be of special importance in environmental planning and water resources management. Using statistical methods and the discharge data of the Dez river, the heavy floods of this river were extracted to identify the effective factors in their creation. Among all systems leading to heavy rains, the Sudanian system has been the main factor of moisture advection in the lower layer of the troposphere with its expansion to the north and northeast. Due to its thermal characteristics, this system has been prone to receive considerable moisture from the surrounding warm seas. This system has provided the necessary conditions for the creation of surface instabilities in most transitional systems independently and in a smaller number in the integrated state with the Mediterranean system. In the investigation of the middle layer of the troposphere in all the systems that led to the floods of 1993 and 2005, it was observed that the anticyclone cell of Arabia was established over the Arabian and Oman seas and the east of the Arabian Peninsula by moving eastward. In this situation, a very deep trough has formed in the west of Iran, and the southern end of the trough has extended to southern Sudan and northern Ethiopia. The eastward movement of high pressure in Arabia and the significant southward expansion of the Mediterranean trough and the formation of a low-altitude center over Iraq is the most suitable pattern for the heavy cloud rains in the basin. Materials and MethodsIn terms of geographic location, the Dez basin is limited between 48°10' to 50°21' east longitude and 31°34' to 33°7' north latitude. The studied area is a part of the Dez river basin, which is located almost in the middle part to the end part. After the Karun branch of one of the largest and longest Dez rivers, Dez is formed from two main branches named Caesar and Bakhtiari, and after leaving the mountainous region north of Andimeshk and Dezful, it enters the plain of Khuzestan. For comprehensive and accurate interpretation of pressure systems and assessment of their environmental effects on the earth, the maps of the earth's surface and level of 500 hPa are very efficient. In most cases, the wind direction and temperature distribution at the 500 hPa level are completely affected by the topographic arrangement of the geopotential height at the 500 hPa level. Geopotential height maps are one of the most important and efficient atmospheric maps in synoptic analysis and interpretation. Heavy rains on representative days are analyzed, interpreted, and explained. Two statistical and synoptic methods were used for a more detailed investigation of the synoptic situation of heavy rains in the Dez river basin. In the statistical part, factor analysis, which is one of the widely used statistical methods in climatology, was used, and in the synoptic part, maps of different atmospheric levels were extracted and analyzed using Gardes software for the specified days. To determine the members of each group, the correlation of the scores of each factor with the sea level pressure map in the time period (1964-2020) was calculated, and the members of each group were determined. To determine the representative days, the correlation of the SLP maps of the days of each group was used, and the day that had a high correlation with more days was selected as the representative day. To perform factor analysis, the elements of the database were transferred from the Excel environment to the S-Plus2008 software environment, and then by performing various inferential analysis calculations, the most suitable method was selected to identify the main and effective factors. Results and DiscussionAs can be seen, the heavy rains of 2013 lasted for 6 days, and the system of 2011 lasted for 7 days. Of course, as mentioned, in some systems, days before or after the end of the activity period of the main system, scattered rains, even with high intensity, have been recorded in some stations. But these scattered rains are considered local rains. The highest peak flow rate of 8556 m3 belongs to the system in February 2013. This system has lasted for 4 days. It took 31 hours to reach the peak of the flood. ConclusionIn the investigation of the middle layer of the troposphere in all the systems that led to the floods of 1993 and 2005, it was observed that the Arabian anticyclone has been established over the Arabian and Oman seas and the east of the Arabian Peninsula by moving eastward. In this situation, a very deep trough has formed in the west of Iran, and the southern end of the trough has extended to southern Sudan and northern Ethiopia. Therefore, the eastward displacement of the high pressure in Arabia and the significant southward expansion of the Mediterranean trough, and the formation of a low-altitude center cut over Iraq is the most suitable pattern for heavy cloud precipitation in the Dez basin. The peak discharge of floods with a delay of 12 to 24 hours from the day of peak rainfall has created a very intense discharge system. So, the floods of 2005 with a peak discharge of 8556 m3 s-1 and the flood of 1993 with a peak discharge of 4022 m3 s-1, while they were very heavy floods, there were two study periods.

Research on cancer in dogs and cats, among other diseases, finds an important source of information in registry data collected from hospitals. These sources have proved to be decisive in establishing incidences and identifying temporal patterns and risk factors. However, the attendance of patients is not random, so the correct delimitation of the hospital catchment area (CA) as well as the identification of the factors influencing its shape is relevant to prevent possible biases in posterior inferences. Despite this, there is a lack of data-driven approaches in veterinary epidemiology to establish CA. Therefore, our aim here was to apply a Bayesian method to estimate the CA of a hospital. We obtained cancer (n = 27,390) and visit (n = 232,014) registries of dogs and cats attending the Veterinary Medical Teaching Hospital of the University of California, Davis from 2000 to 2019 with 2,707 census tracts (CTs) of 40 neighboring counties. We ran hierarchical Bayesian models with different likelihood distributions to define CA for cancer cases and visits based on the exceedance probabilities for CT random effects, adjusting for species and period (2000-2004, 2005-2009, 2010-2014, and 2015-2019). The identified CAs of cancer cases and visits represented 75.4 and 83.1% of the records, respectively, including only 34.6 and 39.3% of the CT in the study area. The models detected variation by species (higher number of records in dogs) and period. We also found that distance to hospital and average household income were important predictors of the inclusion of a CT in the CA. Our results show that the application of this methodology is useful for obtaining data-driven CA and evaluating the factors that influence and predict data collection. Therefore, this could be useful to improve the accuracy of analysis and inferences based on registry data.

BackgroundAntenatal care and skilled childbirth services are important interventions to improve maternal health and lower the risk of poor pregnancy outcomes and mortality. A growing body of literature has shown that geographic distance to clinics can be a disincentive towards seeking care during pregnancy. On the Thailand-Myanmar border antenatal clinics serving migrant populations have found high rates of loss to follow-up of 17.4%, but decades of civil conflict have made the underlying factors difficult to investigate. Here we perform a comprehensive study examining the geographic, demographic, and health-related factors contributing to loss to follow-up.MethodsUsing patient records we conducted a spatial and epidemiological analysis looking for predictors of loss to follow-up and pregnancy outcomes between 2007 and 2015. We used multivariable negative binomial regressions to assess for associations between distance travelled to the clinic and birth outcomes (loss to follow-up, pregnancy complications, and time of first presentation for antenatal care.) RESULTS: We found distance travelled to clinic strongly predicts loss to follow-up, miscarriage, malaria infections in pregnancy, and presentation for antenatal care after the first trimester. People lost to follow-up travelled 50% farther than people who had a normal singleton childbirth (a ratio of distances (DR) 1.5; 95% confidence interval (CI): 1.4 - 1.5). People with pregnancies complicated by miscarriage travelled 20% farther than those who did not have miscarriages (DR: 1.2; CI 1.1-1.3), and those with Plasmodium falciparum malaria in pregnancy travelled 60% farther than those without P. falciparum (DR: 1.6; CI: 1.6 - 1.8). People who delayed antenatal care until the third trimester travelled 50% farther compared to people who attended in the first trimester (DR: 1.5; CI: 1.4 - 1.5).ConclusionsThis analysis provides the first evidence of the complex impact of geography on access to antenatal services and pregnancy outcomes in the rural, remote, and politically complex Thailand-Myanmar border region. These findings can be used to help guide evidence-based interventions to increase uptake of maternal healthcare both in the Thailand-Myanmar region and in other rural, remote, and politically complicated environments.

The Adolescent Brain Cognitive Development (ABCD) Study is the largest single-cohort prospective longitudinal study of neurodevelopment and children's health in the United States. A cohort of n = 11,880 children aged 9-10 years (and their parents/guardians) were recruited across 22 sites and are being followed with in-person visits on an annual basis for at least 10 years. The study approximates the US population on several key sociodemographic variables, including sex, race, ethnicity, household income, and parental education. Data collected include assessments of health, mental health, substance use, culture and environment and neurocognition, as well as geocoded exposures, structural and functional magnetic resonance imaging (MRI), and whole-genome genotyping. Here, we describe the ABCD Study aims and design, as well as issues surrounding estimation of meaningful associations using its data, including population inferences, hypothesis testing, power and precision, control of covariates, interpretation of associations, and recommended best practices for reproducible research, analytical procedures and reporting of results.

The city of Tehran has experienced a significant population increase, approximately twenty times, in the last century. Consequently, it is plagued with traffic issues for most of the year. To alleviate congestion, one solution is to shift transportation mode shares from private motor vehicles to more sustainable modes, as proposed by Transit Oriented Development (TOD). The increasing traffic congestion problems in cities have made applying TOD more essential than ever. This research aims to evaluate, analyze, and plan development within the catchment area of Monirieh Metro Station based on TOD principles. The practical research methodology begins by introducing TOD principles and evaluating the characteristics of the study area according to ITDP standards. The results indicate that the catchment area of Monirieh metro station fails to meet TOD standards. In other words, the city planning prioritizes motor vehicles over pedestrians, suggesting a car-oriented approach.

Water erosion in mountainous areas is a major problem, especially on steep slopes exposed to intense precipitation. This paper presents the analysis of the topsoil loss using the SWAT (Soil and Water Assessment Tool) model. The SWAT model is a deterministic catchment model with a daily time step. It was designed to anticipate changes taking place in the catchment area, such as climate change and changes in land use and development, including the quantity and quality of water resources, soil erosion and agricultural production. In addition to hydrological and environmental aspects, the SWAT model is used to address socio-economic and demographic issues, such as water supply and food production. This program is integrated with QGIS software. The results were evaluated using the following statistical coefficients: determination (R2), Nash–Sutcliff model efficiency ( NS), and percentage deviation index ( PBIAS). An assessment of modelling results was made in terms of their variation according to different land cover scenarios. In the case of the scenario with no change in use, the average annual loss of topsoil (average upland sediment yield) was found to be 14.3 Mg∙ha –1. The maximum upland sediment yield was 94.6 Mg∙ha –1. On the other hand, there is an accumulation of soil material in the lower part of the catchment (in-stream sediment change), on average 13.27 Mg∙ha –1 per year.

This paper presents a study regarding the factors affecting the maximum distance travelers are willing to walk to a bus stop. The study focuses on bus services provided at and walking routes towards bus stops. Travelers’ evaluations are collected using a stated preference experiment. Based on 7911 evaluations of 879 respondents, a latent class ordered logit model is estimated showing that both bus service and walking route related attributes significantly contribute to the maximum distance travelers are willing to walk from home to a bus stop. The parameter estimates show that the most influential attributes are the bus frequency at the bus stop and the presence of street lighting along the route between home and bus stop. The model also shows that based on the evaluations three different classes of respondents can be distinguished. Membership of a class depends on traveler related characteristics: gender, residential area, and bus use.

Active modes can play a key role in the transition toward sustainable urban mobility, and transport systems should be designed to support and incentivize them. For instance, walking accessibility to main urban centralities is a factor to pay attention to, as well as the way in which pedestrians perceive the characteristics of the infrastructure and the surrounding environment should also be considered. This study proposes a method for computing a walkability index of the paths for accessing transport nodes (e.g., railway station). The index is based on individuals' perception of walkable infrastructure features (e.g., kerbside width, presence of urban furniture, greenery, etc.). It allows having a more realistic view of the catchment area of the node and to identify policies for improving pedestrian accessibility. The method has been validated using an ad-hoc survey in the area of the Milano Rogoredo railway station (Italy). The map of the estimated walkability indexes is consistent with the real conditions of the Milano Rogoredo neighbourhood and allows for identifying those areas where walkability can be improved. [ABSTRACT FROM AUTHOR]

Transport of terrestrial carbon through riverine systems to coastal water has a negative impact on oxygen concentration in coastal areas. However, information on seasonal variation and the impact of catchment composition on the bioavailability of allochthonous carbon is lacking. In this project we address this knowledge gap by investigating the reactivity of dissolved organic carbon (DOC) at river mouths which originate from agricultural or forested dominated catchments over a year. Using a high-capacity oxygen sensing system biological oxygen demand (BOD) was measured and converted to carbon utilization rate. This allowed a spatial and temporal resolution necessary to understand how concentrations of total nitrogen, total phosphorus, DOC, as well as carbon composition influence carbon bioavailability. Seasonality and the differing catchment compositions yielded variable results about which factors were significantly contributing to reactivity. In addition, we found that carbon utilization rate was highest during April, June, and October for most rivers. The bioavailable fraction (BFc) was significantly higher in rivers with agricultural compared to forest dominated catchments during January, April, June, and October. However, rivers with agricultural dominated catchment had a significantly higher carbon utilization rate in August. This indicate that rivers dominated by forest transport larger and more refractory pools of carbon, while rivers with agricultural dominated catchments have a higher percentage of BFc. Based on these results we suggest that management efforts, to reduce the transport of bioavailable carbon, would be most efficient during spring and autumn with equal importance on rivers with catchment areas dominated by agriculture and forest. [ABSTRACT FROM AUTHOR]

A sufficiently long time-series of daily discharges is needed to assess the discharge dynamics and calculate the water balance equation parameters of a spring (river source). The paper assumes that a catchment is gauged if a time-series of observations of at least 30 years is available, which is a rare case in Serbia. One-year monitoring is often set up to verify the reserves of a water source or spring intended for capture. Monitoring ceases after the final report is produced. The paper aims to show potential problems if there are no sufficiently long time-series and if no detailed hydrogeological investigations have been undertaken. The Gornji Dušnik Spring is used as an example. That spring drains the western parts of Suva Planina Mountain. It was captured many years ago to provide public water supply to the town of Gadžin Han and the nearby villages of Donji Dušnik and Gornji Dušnik. [ABSTRACT FROM AUTHOR]

In order to design an appropriate dewatering system in an open pit mine, it is necessary to know the hydrogeological conditions and factors affecting the condition of groundwater in the mining area. One of the important factors for investigating the hydrogeological conditions of a mining site is to know the status of the catchment area, temporal and spatial changes of the piezometric levels and the range of disturbances caused by mining activities, climate conditions and the tectonic state of the mining area. The hydrological and hydrogeological conditions of Sangan iron mine are also affected by climate factors such as precipitation and tectonic factors including the number of faults and their trends, their distances and their relationship with each other. Therefore, in this study, the influence of various factors including precipitation, distance from waterways, tectonic status and faults, and the pit development during the exploitation period on the fluctuation of groundwater were investigated. By examining the fluctuations of the piezometric levels caused by these factors in the period from March 2011 to March 2014 and statistical analysis of the results, it was found that among the affecting factors, the Cn-pit expansion has the greatest effect on the groundwater level fluctuation of the western anomalies of Sangan mine. By drawing the ccorrelation diagram between the distance from Cn-Pit and the groundwater level drop of observation piezometers of the nearby areas of the Cn-pit, and obtaining a coefficient of determination equal to 0.94 (R2 =0.94), it was found that the radius of the influence of the Cn-pit expansion on the changes in the groundwater level of the adjacent areas is about 700 meters. In addition, it was found that the amount of precipitation and the distance from the waterways do not have a significant effect on the groundwater level fluctuations in the study area. [ABSTRACT FROM AUTHOR]

Background: Perinatal health outcomes are influenced by a variety of socioeconomic, behavioral, and economic factors that reduce access to health services. Despite these observations, rural communities continue to face barriers, including a lack of resources and the fragmentation of health services. Objective: To evaluate patterns in health outcomes, health behaviors, socioeconomic vulnerability, and sociodemographic characteristics across rural and nonrural counties within a single health system catchment area. Methods: Socioeconomic vulnerability metrics, health care access as determined by licensed provider metrics, and behavioral data were obtained from FlHealthCHARTS.gov and the County Health Rankings. County-level birth and health data were obtained from the Florida Department of Health. The University of Florida Health Perinatal Catchment Area (UFHPCA) was defined as all Florida counties where ?5% of all infants were delivered at Shands Hospital between June 2011 and April 2017. Results: The UFHPCA included 3 nonrural and 10 rural counties that represented more than 64,000 deliveries. Nearly 1 in 3 infants resided in a rural county, and 7 out of 13 counties did not have a licensed obstetrician gynecologist. Maternal smoking rates (range 6.8%?24.8%) were above the statewide rate (6.2%). Except for Alachua County, breastfeeding initiation rates (range 54.9%?81.4%) and access to household computing devices (range 72.8%?86.4%) were below the statewide rate (82.9% and 87.9%, respectively). Finally, we found that childhood poverty rates (range 16.3%?36.9%) were above the statewide rate (18.5%). Furthermore, risk ratios suggested negative health outcomes for residents of counties within the UFHPCA for each measure, except for infant mortality and maternal deaths, which lacked sample sizes to adequately test. Conclusions: The health burden of the UFHPCA is characterized by rural counties with increased maternal death, neonatal death, and preterm birth, as well as adverse health behaviors that included increased smoking during pregnancy and lower levels of breastfeeding relative to nonrural counties. Understanding perinatal health outcomes across a single health system has potential to not only estimate community needs but also facilitate planning of health care initiatives and interventions in rural and low-resource communities.

The goal of this study is to interpret the cross-sectional increases of rinnenkarren systems with the use of analytical model and CFD simulation. In rinnenkarren, water accumulation from the catchment was approximated using an analytical method based on field data. The length of eddies appearing at tributary junctions was studied by CFD in model channels. The results of the analytical and numerical models were compared against morphometrical parameters of rinnenkarren surveyed in the Totes Gebirge (Austria). It is found that there is a relationship between catchment size and channel development. Along small catchments, channel development is random. However, channel development along large catchments is controlled by water concentration. Decrease in the slope angle of the catchment results in an increase in the volume of water entering the channel and development of tributary channels. When water inflow is not concentrated in a single place, several smaller tributary channels emerge. When it is concentrated, only one large-sized and long tributary develops. At the junctions of large tributaries significant vorticity was identified in the CFD models. In addition to the previous model studies, the similarity between the lengths of the simulated vorticity sections and the local field hollowings was revealed. [ABSTRACT FROM AUTHOR]

Introduction The importance of heavy rainfall and its consequences have caused this phenomenon to be of special importance in environmental planning and water resources management. Using statistical methods and the discharge data of the Dez river, the heavy floods of this river were extracted to identify the effective factors in their creation. Among all systems leading to heavy rains, the Sudanian system has been the main factor of moisture advection in the lower layer of the troposphere with its expansion to the north and northeast. Due to its thermal characteristics, this system has been prone to receive considerable moisture from the surrounding warm seas. This system has provided the necessary conditions for the creation of surface instabilities in most transitional systems independently and in a smaller number in the integrated state with the Mediterranean system. In the investigation of the middle layer of the troposphere in all the systems that led to the floods of 1993 and 2005, it was observed that the anticyclone cell of Arabia was established over the Arabian and Oman seas and the east of the Arabian Peninsula by moving eastward. In this situation, a very deep trough has formed in the west of Iran, and the southern end of the trough has extended to southern Sudan and northern Ethiopia. The eastward movement of high pressure in Arabia and the significant southward expansion of the Mediterranean trough and the formation of a low-altitude center over Iraq is the most suitable pattern for the heavy cloud rains in the basin. Materials and Methods In terms of geographic location, the Dez basin is limited between 48°10' to 50°21' east longitude and 31°34' to 33°7' north latitude. The studied area is a part of the Dez river basin, which is located almost in the middle part to the end part. After the Karun branch of one of the largest and longest Dez rivers, Dez is formed from two main branches named Caesar and Bakhtiari, and after leaving the mountainous region north of Andimeshk and Dezful, it enters the plain of Khuzestan. For comprehensive and accurate interpretation of pressure systems and assessment of their environmental effects on the earth, the maps of the earth's surface and level of 500 hPa are very efficient. In most cases, the wind direction and temperature distribution at the 500 hPa level are completely affected by the topographic arrangement of the geopotential height at the 500 hPa level. Geopotential height maps are one of the most important and efficient atmospheric maps in synoptic analysis and interpretation. Heavy rains on representative days are analyzed, interpreted, and explained. Two statistical and synoptic methods were used for a more detailed investigation of the synoptic situation of heavy rains in the Dez river basin. In the statistical part, factor analysis, which is one of the widely used statistical methods in climatology, was used, and in the synoptic part, maps of different atmospheric levels were extracted and analyzed using Gardes software for the specified days. To determine the members of each group, the correlation of the scores of each factor with the sea level pressure map in the time period (1964-2020) was calculated, and the members of each group were determined. To determine the representative days, the correlation of the SLP maps of the days of each group was used, and the day that had a high correlation with more days was selected as the representative day. To perform factor analysis, the elements of the database were transferred from the Excel environment to the S-Plus2008 software environment, and then by performing various inferential analysis calculations, the most suitable method was selected to identify the main and effective factors. Results and Discussion As can be seen, the heavy rains of 2013 lasted for 6 days, and the system of 2011 lasted for 7 days. Of course, as mentioned, in some systems, days before or after the end of the activity period of the main system, scattered rains, even with high intensity, have been recorded in some stations. But these scattered rains are considered local rains. The highest peak flow rate of 8556 m³ belongs to the system in February 2013. This system has lasted for 4 days. It took 31 hours to reach the peak of the flood. Conclusion In the investigation of the middle layer of the troposphere in all the systems that led to the floods of 1993 and 2005, it was observed that the Arabian anticyclone has been established over the Arabian and Oman seas and the east of the Arabian Peninsula by moving eastward. In this situation, a very deep trough has formed in the west of Iran, and the southern end of the trough has extended to southern Sudan and northern Ethiopia. Therefore, the eastward displacement of the high pressure in Arabia and the significant southward expansion of the Mediterranean trough, and the formation of a low-altitude center cut over Iraq is the most suitable pattern for heavy cloud precipitation in the Dez basin. The peak discharge of floods with a delay of 12 to 24 hours from the day of peak rainfall has created a very intense discharge system. So, the floods of 2005 with a peak discharge of 8556 m3 s -1 and the flood of 1993 with a peak discharge of 4022 m3 s -1, while they were very heavy floods, there were two study periods. [ABSTRACT FROM AUTHOR]