Flood Peak Research Articles

Impact and analysis of urban water system connectivity project on regional water environment based on Storm Water Management Model (SWMM)

SWMM stands as a dynamic rainfall-runoff urban hydrological model, crafted by the U.S. Environmental Protection Agency. It adeptly replicates urban rainfall production and ground runoff, and the Pressure-State-Response (PSR) theory artfully reflects human-environment interactions. Urban Water System Connectivity (UWSC) fortifies connections among regional rivers, transforming them into an intricate, dense network. To study the improvement of the regional water environment by the UWSC project, this study takes the UWSC project in Runan County, Zhumadian, China as the research object, constructs a hydrodynamic and water quality model based on SWMM, and simulates it under different rainfall situations. At the same time, the ecological service value theory and PSR theory are used to establish an ecological effect index system to analyze the ecological effect before and after the UWSC project. This paper evaluates the urban water system connectivity project from three aspects: hydrodynamic, water quality, and ecological effects. Results underscore that the post-UWSC era witnesses decreased river flood flows in varied design rainfalls, accompanied by delayed flood peaks. Under P = 10a and P = 20a rainfalls, peak flow reductions of 6.6% and 4.96% respectively, manifest with peak time lags of 0.17h. Flow rate adjustments align with flow behavior, exhibiting decreased peak flow rates accompanied by temporal lags. Initial river flow increases by about 30%, amplifying river water body exchange capacity. Following the UWSC implementation, the study area's five primary rivers display TSS reductions ranging from 46% to 86.94%, COD from 36.98% to 92.43%, TN from 45.9% to 92.96%, TP from 35.71% to 84.78%, and NH3–N from 38.52% to 92.19%. Simulated point source pollution, under comparable initial conditions, indicates pollutant decay rates escalating from 3.2%–20%–35.71%–92.43%. Ecological impact ascends from 6.33 × 108 RMB to 9.65 × 108 RMB, reflecting a 52.5% escalation. The UWSC initiative enriches urban river flood resilience and water quality, emblematic of urban water ecological civilization progress.

Enhancing the predictability of flood forecasts by combining Numerical Weather Prediction ensembles with multiple hydrological models

Ensemble Prediction Systems (EPS) from a single Numerical Weather Prediction (NWP) model often miss out on a few extreme events. Similarly, a single hydrological model cannot capture all types of flows, such as flood peaks, occurring within a watershed due to the inaccurate representation of the real world processes in their mathematical structure. To focus on these aspects, this study proposes five ‘NWP+HM’ combinations (HM refers to Hydrologic Model) to investigate which combination performs better in providing quality flood forecasts. The EPS obtained from THORPEX Interactive Grand Global Ensemble (TIGGE) archive are forced into calibrated hydrologic models to generate ensemble flood forecasts (EFFs). The methodology also includes a machine-learning post-processing technique, Quantile Regression Forests (QRF), for temporal correction of bias and under-dispersion in the raw EPS data. The study finds that both the EPS used show similar performance in generating flood forecasts. However, the study demonstrates that the hydrologic model uncertainty has a more significant impact on capturing flood peaks compared to input model uncertainty. Finally, the simulated flood forecasts are verified for their quality using both deterministic and probabilistic metrics. For the above five combinations, an increase in leadtime up to 10 days is observed when the raw data are post-processed using QRF technique. The study identifies a computationally efficient ‘NWP+HM’ combination for use in the hydrological forecasting system, which improves the predictability of flood forecasts several days ahead.

Temporal evolution of lake level fluctuations under flood conditions and impacts on the littoral ecosystems

Lake levels fluctuations are conditioned by seasonal variability, water resources management and climate change. Recent studies have shown that global warming potentially affects the risk of flooding and that the decisive factor for flood events is not temperature, but precipitation characteristics and hydrological conditions. Flood events have numerous impacts on social, economic and environmental aspects depending on how humans have altered lands, natural rivers and lake dynamics. Flood protection measures can cause conflicts with conservation measures and with ecosystem services because natural capital is not considered able to control floods and to contribute control floods and that it can contribute to human health and safety. In this paper we analysed the flood events in Lake Maggiore for return time periods of 3 – 5 – 10 – 25 – 50 – 100 – 250 – 500 years, considering the flood frequency in the last ten years using 1868-2021 as a reference period. We discussed the probability distribution of flood peaks, the correlation and linear regression between the lake level fluctuations and macroinvertebrates occurrence. We also presented lake coasts flood hazard mapping. The probability distribution that better describes the annual peak level is the Gumbel function, while for spring and autumn flood events the better distribution is the Log-Pearson type III. One of the historical flood events in terms of magnitude was in 2000, characterized by a return time of about 50 years. The last flood event in 2020, was characterized by a return period of about 10 years. Considering the seasonal frequency of flood, the autumn magnitude was higher than the spring one, and the differences between seasonal flood events progressively increased. The results suggested a high probability of a flood event every three years and also a forecast of a flood of about 197 m asl (3.14 m above the average lake level) every 10 years. Raising the lake level will affect the reed bed area from 193 m asl, and it will be more effective at 194.5 m (up to a 10% reduction). During flood events, the whole reed bed area is submerged. As regard macroinvertebrates composition and abundance, the first results show significant negative relationships between all sampling stations altogether vs the abundance of Cladotanytarsus sp. (Chironominae) and nearly significant positive relationships between water levels at Magadino vs Pscectrocladius sordidellus (Orthocladiinae) abundances. These few results are perhaps due to the current limited data availability.

Flood Extent and Volume Estimation Using Remote Sensing Data

Floods are natural events that can have a significant impacts on the economy and society of affected regions. To mitigate their effects, it is crucial to conduct a rapid and accurate assessment of the damage and take measures to restore critical infrastructure as quickly as possible. Remote sensing monitoring using artificial intelligence is a promising tool for estimating the extent of flooded areas. However, monitoring flood events still presents some challenges due to varying weather conditions and cloud cover that can limit the use of visible satellite data. Additionally, satellite observations may not always correspond to the flood peak, and it is essential to estimate both the extent and volume of the flood. To address these challenges, we propose a methodology that combines multispectral and radar data and utilizes a deep neural network pipeline to analyze the available remote sensing observations for different dates. This approach allows us to estimate the depth of the flood and calculate its volume. Our study uses Sentinel-1, Sentinel-2 data, and Digital Elevation Model (DEM) measurements to provide accurate and reliable flood monitoring results. To validate the developed approach, we consider a flood event occurred in 2021 in Ushmun. As a result, we succeeded to evaluate the volume of that flood event at 0.0087 km3. Overall, our proposed methodology offers a simple yet effective approach to monitoring flood events using satellite data and deep neural networks. It has the potential to improve the accuracy and speed of flood damage assessments, which can aid in the timely response and recovery efforts in affected regions.

Declines in the Mekong’s Megadiverse Larval Fish Assemblages: Implications for Sustainable Development

Migratory fishes of the Mekong Basin are facing challenges from human-induced stressors. Quantifying the patterns of fish’s early life stages provides important information on spawning seasons, spawning and nursery habitats, reproductive strategies, migration and dispersal patterns, and stock status. However, the ecology of the Mekong larval fishes, including patterns and drivers of larval fish dispersal, is not well understood. Here, we investigate the temporal variability of drifting larval and juvenile fish assemblages in the Cambodian Mekong River and identify their environmental drivers using long-term (10 year) daily fish larval/juvenile data collections. We found that, in the Mekong main channel, the larval and juvenile assemblages were dominated by longitudinal migrants from the families Cyprinidae and Pangasiidae. Peak abundance and richness were found to occur in July and August, respectively. We detected a significant decline in larval and juvenile abundance and richness over the study period. Cross-wavelet analysis revealed that water levels always lead larval abundance, but lag richness. In addition, cross-correlation analysis observed that peak abundance and richness occurred eight weeks and one week, respectively, before the peak water level. We also discovered that species abundance and richness had a strongly positive relationship with maximum water levels. Variation in fish larval and juvenile abundance and richness was also related to total phosphorus, nitrate, alkalinity, and conductivity. Maximum water levels and the key water quality parameters (e.g., phosphorus, nitrate, alkalinity, and conductivity) significantly influence larval and juvenile fish abundance and richness patterns. Therefore, safeguarding natural seasonal flows, especially maximum flows associated with the peak flood pulse, as well as maintaining good water quality, are key to the reproductive success of many migratory fishes and effective dispersal of offspring to the lower floodplain for nursing, rearing, and growth. Clean and unregulated rivers support productive and diverse fisheries.

Runoff and sediment characteristics of a typical watershed after continuous soil erosion control in the red soil region of Southern China

To investigate the runoff and sediment characteristics of the watershed after continuous soil erosion control in the red soil region of southern China, hydrological data were collected from 2013 to 2020 in the Zhuxi watershed, which is located in the southeast of the red soil region. The results showed that the monthly suspended sediment concentration and annual sediment yield have significantly decreased since 2017. At the event scale, 180 floods were classified into four flood patterns (A, B, C and D) by the K-medoids clustering method based on the flood duration, runoff depth and peak discharge. Each flood pattern resulted in differing levels of the event sediment yield (D > C > B > A), and Pattern C contributed the most to runoff and sediment yield. The study period was divided into two stages according to the annual sediment yield. Compared with 2013–2016, the total runoff and sediment yield of the 3 major flood patterns (A, B and C) in 2017–2020 decreased by 17.88%∼25.12% and 78.92%∼90.34%, respectively. These flood patterns decreased not only in frequency but also in suspended sediment concentration, which was caused by the changes in the runoff-sediment relationships of flood events. Six types of suspended sediment concentration and discharge (SSC-Q) relations appeared in the flood events, indicating that the sediment sources and sediment transport processes were complex and dynamic. In 2017–2020, the single-valued relation became the dominant type of SSC-Q relations for all flood patterns, which suggests that the sediment supply was inhibited. The results provide a more comprehensive understanding of the runoff and sediment processes of a watershed after continuous soil erosion control, which is beneficial for revealing the development of soil erosion in the red soil region of southern China.

Future projections of worst floods and dam break analysis in Mahanadi River Basin under CMIP6 climate change scenarios.

This study provides a comprehensive analysis of the hydrological effects and flood risks of the Hirakud Reservoir, considering different CMIP6 climate change scenarios. Using the HEC-HMS and HEC-RAS models, the study evaluates future flow patterns and the potential repercussions of dam breaches. The following summary of the work: firstly, the HEC-HMS model is calibrated and validated using daily stage-discharge observations from the Basantpur station. With coefficient of determination (R2) values of 0.764 and 0.858 for calibration and validation, respectively, the model demonstrates satisfactory performance. Secondly, The HEC-HMS model predicts future flow for the Hirakud Reservoir under three climate change scenarios (SSP2-4.5, SSP3-7.0 and SSP5-8.5) and for three future periods (near future, mid future and far future). Thirdly, by analyzing time-series hydrographs, the study identifies peak flooding events. In addition, the HEC-RAS model is used to assess the effects of dam breaches. Downstream of the Hirakud Dam, the analysis highlights potential inundation areas and depth variations. The study determines the following inundation areas for the worst flood scenarios: 3651.52 km2, 2931.46 km2 and 4207.6 km2 for the near-future, mid-future and far-future periods, respectively. In addition, the utmost flood depths for these scenarios are determined to be 31 m, 29 m and 39 m for the respective future periods. The study area identifies 105 vulnerable villages and several towns. This study emphasizes the importance of contemplating climate change scenarios and implementing proactive measures to mitigate the peak flooding events in the Hirakud reservoir region.

Copula-Based Joint Flood Frequency Analysis: The Case of Guder River, Upper Blue Nile Basin, Ethiopia

The univariate analysis of hydrological extremes is a well-established practice in developing countries such as Ethiopia. However, for the design of hydrological and hydraulic systems, it is essential to have a thorough understanding of flood event characteristics, including volumes, peaks, time of occurrence, and duration. This study utilizes copula functions for bivariate modeling of flood peak and volume characteristics, examining the performance of four Archimedean copulas in the Guder basin located in Ethiopia from 1987 to 2017. Flood peak and volume were extracted using the theory of runs for analysis of their joint characteristics with the truncation level chosen as equal to the lowest annual maximum event. Univariate distributions with the best fitness on both variables were determined, and results showed that gamma and GEV-fitted flood peaks and lognormal-fitted flood volumes are the most suitable. Four Archimedean copulas were evaluated, and the Gumbel-Hougaard copula was found to be the best fit for the data based on graphical and measurable tests. Bivariate probability and return period were computed in “AND” and “OR” states. The joint return period for flood peak (97.49 m3/s) and volume (77.35 m3/s) was found to be 15 years in the “AND” state and approximately 4 years in the “OR” state. The study also evaluates univariate and conditional return periods, comparing them with the primary one. The copula method was an effective method for distributing marginal variables, highlighting its potential as a valuable tool in flood management.

Alibeyköy Havzası İçin En Uygun Taşkın Olasılık Dağılımı

Determination of peak flow rates is crucial in reducing the economic and social impact of flood. Therefore, the investigation of various methods for estimating flood is of paramount importance. Flood frequency analysis can be used as a practical method in predicting the peak flow values as the flood peaks have return periods that are typically much larger than the recording length. In this study, 7 different probability distributions (normal (N), two-parameter lognormal (LN2), three-parameter lognormal (LN3), extreme value type I (Gumbel), generalized extreme value (GEV), Pearson Type III (P3) and Log-Pearson Type III (LP3)) are employed for flood frequency analysis of Alibeyköy Watershed using 44-years of measured annual maximum flow. K-S and PPCC tests are applied to determine the most suitable distributions to estimate the flood flow rate. Based on these tests, GEV and Gumbel distributions appear to be the most preferable distributions in flood flow estimation.

Frequency and trend analyses of annual peak discharges in the Lower Mekong Basin

The effectiveness of annual peak discharges under the anthropogenic impact and climate change has significance for disaster management and planning. Therefore, an attempt has been made to study the trend of annual maximum series (AMS) discharges and flood frequency in the Lower Mekong Basin (LMB). The AMS data of five stations in the LMB were procured from the Mekong River Commission for analyses of trends of the AMS and flood frequency. The Mann-Kendall test showed a significant decrease in the magnitude of annual peak floods for all the discharge gauging sites in the LMB. Likewise, the analysis of the annual discharge departure from the mean reveals noteworthy variations and departure (positive and negative) in the annual peak discharges. The goodness-of-fit (GoF) tests showed that Log-Pearson Type-III (LP-III) is the best distribution for AMS of the Mekong River than Gumbel Extreme Value Type-I (GEVI). Therefore, predicted discharges for different return periods and predicted recurrence intervals for average annual discharges (Qm), large floods (Qlf), and maximum annual peak discharge during the recording period (Qmax) by LP-III are trustworthy. The flood frequency curve specified that all the observed discharges were fairly on the best-fitted line and falls between upper and lower confidence limits. Inclusively, the results of the trend in annual peak discharges and flood frequency are consistent and can be used for water management, controlling flood disasters, and flood planning in the LMB.

Variation characteristics of hydrological response to water conservancy construction in the Qinhe River Basin of the Loess Plateau, China

AbstractInvestigating the response characteristics of various hydrological factors to water conservancy projects area in basin and evaluating their impact on the ecological environment are crucial for ecological protection and restoration on the Loess Plateau, China, with a complex environment. In this study, we employed a geomorphology‐based hydrological model to simulate the hydrological elements of the Qinhe River Basin on the Loess Plateau. We explored the response characteristics of the water cycle and hydrological processes to the construction of reservoirs in the basin. Additionally, we also examined multiyear changes in peak flood volume and sediment discharge during flood seasons influenced by reservoirs. The sub‐basins hosting reservoirs initialled an increase in evaporation, followed by a decrease. During the change periods, both runoff and soil water decreased, but remained higher than the mean values for the basin during the same period. The Normalized Difference Vegetation Index of sub‐basins associated with five reservoirs was obviously higher than the mean value for the basin during the same period. The peak flood volume and sediment discharge in the basin were characterized by decreasing trends, with the latter showing weak sustainability. The value of each index for a sub‐basin associated with a reservoir was higher than the average value for the basin. The construction and operation of reservoirs had a positive impact on the ecology of the basin. Water and soil conservation measures, including sediment regulation and storage using reservoirs, effectively decreased water hazard and soil erosion in the basin. This study provides a scientific basis for the construction of water conservancy projects and ecological governance in the basin.

Long Short-Term Memory (LSTM) Based Model for Flood Forecasting in Xiangjiang River

Due to rapid development, the occurrence of flood has become more and more frequent. However, due to the complex nature and limited knowledge, the conventional hydrological model for flood forecasting purposes faces drawbacks in terms of technical difficulties. Hence, it is essential to have a model which can provide a considerably high level of accuracy for flood forecasting. This study selected the area between the Xiangtan station and Changsha station, located in Xiangjiang River as the study area. Recurrent neural network (RNN), gated recurrent unit (GRU) and long short-term memory (LSTM) were applied for model development purposes. The models were used to forecast the flood disasters occurring in 2017, 2019, 2020 and 2022 for 1h, 6h and 12h in advance. A series of statistical analyses have been conducted to evaluate the model performance. The LSTM model outperformed than the RNN and GRU models. In terms of the overall analysis, the LSTM model achieved relatively good accuracy with a NSE of above 0.98, and RMSE of lower than 0.2 m. In addition, the model with a 6h in advance is the most suitable model to predict the peak flood arrival time with an absolute error of less than 3 hours.

Flood hazard modelling using HEC-RAS in the Pathariya Khola, Far-western Nepal

Flood hazards are a common problem in flat-lying areas, particularly in southern Nepal due to heavy precipitation and the consequent large transportation of sediments from hilly regions. Bank erosion, flooding, inundation, and sedimentation are the major problems in the plain area of the Kailali District along the riverbanks of Pathariya Khola, which is located on the southern flanks of the Churia Range. The study has been focused on flood hazards and vulnerability evaluation. The river discharge was calculated by WECS/DHM method and flood frequency in various return periods was analysed using HEC-RAS, RAS-Mapper, and geographic information system (GIS) for hazard modelling to delineate the flood-prone areas. The flood hazard zones were categorized as moderate (26.29%), high (39.59%), and very high (34.12%) based on the computed water depths of peak floods. The agricultural land is the most vulnerable to flooding followed by built-up areas. The results have revealed that the flood hazard areas are ever-expanding with the increased discharge levels of different return periods.

Analisa Erosi dan Sedimentasi Di Hilir Kali Acai Guna Mencegah Daya Rusak Air

The characteristics of the watershed (DAS) have an influence on the size of the discharge, erosion, and sediment in a watershed. Erosion is the process of wearing away topsoil by water or wind. The rate of erosion and sedimentation that occurs is often caused and influenced by climate, soil, topography, plants, land use, human activities, river hydraulic characteristics, and cross-sectional characteristics. The purpose of this study is to obtain information on the magnitude of erosion and sedimentation per unit area in the Acai River. The methods used for this research activity are primary and secondary data analysis methods, using the tools of the ArcGis, and Hecras programs and manual observations and measurements in the laboratory to obtain sedimentation values and shear stresses. The results obtained based on the observations and analysis carried out, the erosion rate using the USLE method was 110.90 tons/ha/year, the peak flood discharge was 18.64 m3/s (Q10) which could not be accommodated by the Acai River and the amount of sedimentation per unit area in the study location for the downstream area is 84,564,439 tons/ha

Catchment and lake network modify export of anaerobic oxidation capacity in boreal freshwaters

Anaerobic terminal electron acceptors (aTEAs, i.e. NO3, Fe, SO4) enable anaerobic respiration, and each has a specific ability to oxidize reduced compounds. However, little is known about how seasonal and lake-specific aTEA fluxes form anaerobic oxidation capacity (AOC) to oxidize organic carbon in boreal systems. We compiled 26 years of data from two interconnected semi-pristine boreal lakes and defined mean daily imports, pools, and exports of aTEAs. In both lakes, the export of NO3 formed 2 %–3 % of the total AOC in summer and autumn, and up to 11 % in winter and spring. In a predominantly monomictic humic lake surrounded by peatlands, Fe was responsible for 15 %–31 % of the seasonal export of AOC, with a large proportion of Fe originating from the lake bottom. A dimictic clear-water lake downstream retained Fe and exported 87 %–95 % of AOC as SO4. In the humic lake, the annual SO4:Fe:NO3 export ratio for AOC was 10:3:1 and in the clear-water lake 15:0.4:1. In the monomictic lake, exports were specifically regulated by stratification; in the dimictic lake, exports were more regulated by spring flooding and the ascending and descending side of the peak flood. These events modified lake dynamics and caused lake-specific NO3, Fe, and SO4 exports which continued for months. We conclude that a catchment and lake network can cause spatial and temporal variation in exports of NO3, Fe, and SO4 affecting AOC export. Such natural variations in exports have significant potential to modify the system's capacity to oxidize C and resist changes in oxidation-reduction reactions coupled to nutrient cycling and the formation of greenhouse gases in downstream water bodies.

Dynamics of Hydro Landscape in and Around Yamuna River in Parts of Delhi with Special Refrence to Eco Green Areas

The study has been done with the aim to dilute the existing pollution level in the Yamuna River. The study suggests the establishment of water bodies along the river bank, so as to trap the water during peak flood period and its utilization in other seasons. The present study involves dividing the stretch 22km stretch of the river in capital city Delhi into six zones and directs to understand the rivers hydrology and environment on the whole in a stretch from Old Rail Bridge to IP Barrage (ITO area).

Projections of flood regime changes over the upper-middle Huaihe River Basin in China based on CMIP6 models

Introduction: Climate change alters the hydrological cycle to different extents, in particular the intensification of extreme precipitation and floods, which has garnered more attention as a significant scientific issue in the last few decades. The last Coupled Model Inter-comparison Project 6 (CMIP6) was designed with new shared socioeconomic pathways (SSPs) to combine socioeconomic development with greenhouse gas emissions to project future climate.Method: In this study, we used 22 global climate models (GCMs) from CMIP6 to investigate future variations in extreme precipitation and temperature under SSP2-4.5 and SSP5-8.5 scenarios over the upper-middle Huaihe River Basin (UMHRB). Then, the modified Xinanjiang model integrating the flood control module was driven to obtain projections of the daily streamflow and to evaluate the future variations in flood regimes.Results: The results show that 1) the characteristics of future extreme precipitation, such as the average intensity and amount of annual precipitation and extreme precipitation, are projected to increase, and the average, maximum, and minimum temperature values also display substantial increasing trends in the future over the UMHRB; 2) warmer climate will lead to a more severe flood magnitude under the SSP5-8.5 scenario in the far future (2071–2100) over the UMHRB. The results of the multi-model ensemble show that the annual maximum flood peaks (15-day flood volumes) of Wangjiaba and Wujiadu stations are projected to increase by 46.4% (43.1%) and 45.4% (51.1%), respectively, in the far future (2071–2100) under the SSP5-8.5 scenario; and 3) variations in the flood frequency tend to resemble variations in flood magnitude, and the return period of the design flood will obviously decrease under future climate scenarios. For instance, in the far future, under SSP5-8.5 scenarios, the return period of the design flood with a 100-year return period will become 38 years and 31 years for Wangjiaba and Wujiadu stations, respectively.Discussion: The study enhances a more realistic understanding that the occurrence of future extreme precipitation and floods is projected to be more frequent and severe, thereby resulting in an urgent imperative to develop pertinent adaptation strategies to enhance social resilience toward the warming climate.

In-situ characterisation of fluvial dune morphology and dynamics under limited sediment supply conditions, Seine River, France

Dune dynamics and associated sedimentary fluxes have been estimated over a period of a week in the river Seine characterised by limited sediment supply. Distributed into two corridors, typical medium and small dunes associated with fluvial environments have been characterised from multibeam data acquired on four dates, 23-29 March 2021, after a limited peak flood. Dune morphometric parameters have been quantified on cross-dune 1 m spacing of bed elevation profiles and dune migration rates have been calculated by analysing successive multibeam acquisitions. Evidence of limited sediment supply conditions have been recognised from areas uncovered by mobile sediment in the troughs between medium dunes. Under such conditions, bedload transport associated with dune migration has been estimated using three methods: differential bathymetry, dune tracking and the Van Rijn empirical formula using a correction factor accounting for limited sediment supply conditions. The three methods provide similar bedload fluxes (less than an order of magnitude difference), and the small differences are related to input data uncertainties and the capability of these methods to capture sediment transport processes, such as sediment bypassing dunes. Based on field observations, this paper brings new constrains to the relationships between dune morphological parameters, migration rates and sedimentary fluxes and environmental parameters (sediment grain size, flow velocity and water depth) under limited supply conditions in a real river.

Effects of soil and water conservation measures of slope surfaces on flood peaks of small watersheds: A study based on three extreme rainstorm events in northern China

Flash floods resulting from extreme rainstorms seriously threaten regional socioeconomic development. However, few studies have explored the general impacts of soil and water conservation measures (SWCMs) on flood peaks during extreme rainstorms through multiple field investigations. On the basis of field surveys of three rainstorm events in Shaanxi, Shandong, and Henan provinces, the effects of vegetation and agricultural terraces on flood peaks were investigated in 75 small watersheds in northern China. Compared with watersheds dominated by sloping cropland, the flood peak modulus of watersheds dominated by forest land, grass land, and agricultural terraces decreased by 54.75%, 47.80%, and 53.65%, respectively; the peak shaving effects (PSEs) of SWCMs were stronger during minor floods. Soil and water conservation measures reduced the flood magnitudes of small watersheds and their sensitivities to rainstorm events; the PSEs were positively correlated with the area of SWCMs. In earth-rocky mountainous areas, the PSEs of forest land were stronger than those of grassland and agricultural terraces, while in the loess hilly-gully areas, the PSEs of agricultural terraces were stronger than those of other SWCMs. In loess hilly-gully areas, the flash floods demonstrated a phenomenon of small rainfall amounts but substantial flood peaks. Besides the reasonable installation of SWCMs on slopes, appropriate channel measures (e.g., check dams) are warranted to cope with extreme rainstorm events. In northern earth-rocky mountainous areas, intercropping management should be promoted to cover bare soil on orchard agricultural terraces. Our results provide a theoretical basis for combating extreme rainstorm disasters.

Evaluation of CMIP6 HighResMIP for Hydrologic Modeling of Annual Maximum Discharge in Iowa

AbstractThe High‐Resolution Model Intercomparison Project (HighResMIP) experiments from the Coupled Model Intercomparison Phase 6 represent a broad effort to improve the resolution, and performance of climate models. The HighResMIP suite provides high spatial resolution (i.e., 25‐ and 50‐km) forcings that have been shown to improve the representation of climate processes. However, little is known about their suitability for hydrologic applications. We use outputs from the HighResMIP suite to simulate annual maximum discharge with the Hillslope‐Link Model (HLM) at ∼1,000 river communities across Iowa. First, we assess whether the runoff from the climate models can be directly routed through the river network model in HLM to estimate annual maximum discharge. Runoff‐based simulations can capture the empirical distribution of flood peaks in five of the 10 models/members assessed. Next, we force the HLM with precipitation, temperature, and potential evapotranspiration from HighResMIP models to simulate flood peaks, finding all models/members produce empirical distributions similar to our reference. However, significant biases exist in the model/member forcings as correct flood response is being generated for the wrong reason. To improve their suitability for community‐level assessment, we use nine statistical approaches to bias‐correct and downscale HighResMIP precipitation to a 4‐km resolution. The bias‐correction and downscaling of climate model precipitation performs well for all models/members. Furthermore, we do not find significant changes in the magnitude flood peak projections for Iowa based on the HLM forced with HighResMIP outputs, or based on routed runoff, while there are indications that the variability in flood peaks is projected to increase across the state.