Antecedent Moisture Conditions Research Articles

Changes in plot-scale runoff generation processes from the spring–summer transition period to the summer months in a permafrost-dominated catchment

The hydrological regimes in permafrost-dominated catchments have unique characteristics. However, studies based on plot-scale experiments of runoff generation processes and the factors influencing these processes are limited on the Tibetan Plateau, which is experiencing rapid warming and permafrost degradation. Runoff generation processes were studied on a standard runoff plot (5 × 20 m) in a permafrost-dominated catchment on the Tibetan Plateau with an alpine meadow cover to analyze these processes during the spring–summer transition period (from mid-May to early June) and in the summer months of June and July. The discharge, including surface and subsurface runoff, the soil hydrothermal and moisture conditions, and the meteorological conditions were monitored from May 2018 to May 2019. Partial Least-Squares Path Modeling was used to identify the influencing factors in the two time periods. The lateral subsurface flow at 30–60 cm depth accounted for the majority of the discharge from the runoff plot (>99%) and showed a sharp increase when the soil water contents of the thawed soil layers exceeded a threshold value that varied from 0.41 to 0.52. During the spring–summer transition period, the lateral subsurface flow at 30–60 cm depth was promoted by both event precipitation and the antecedent precipitation with an average runoff ratio of 1.7, indicating that the antecedent moisture condition maintained by the underlying permafrost drives runoff generation via meltwater from snow and frozen soil. In the summer months, the lateral subsurface flow at 30–60 cm depth was directly promoted by event precipitation, especially the moderate precipitation that occurred in this period, with a reduced runoff ratio of 0.5 as a result of deepening of the thawed soil layer from 30 to >60 cm, enhanced evapotranspiration and an increased soil water storage capacity caused by an increase of air temperature and the soil temperature. Prediction models obtained via Multiple Linear Regressions of the identified influencing factors were able to accurately estimate the discharge. This study shows the important role of lateral subsurface flow in runoff generation processes in this permafrost area and the most important influencing factors in different seasons.

Hydrological modelling in desert areas of the eastern Mediterranean

The performances of hydrological models in arid areas are significantly lower than other climates. The reasons are numerous, from the scales involved, to specific processes and the lack of adequate measurements. Effective parameters have been often observed to change between runoff events, limiting the predictive capacity of the models. We look at the problems that can be found in an operational setting and present an analysis to improve the understanding of the errors. Our method characterizes the conditions where the model fails systematically, and the conditions where the parameterization holds between floods. We applied KINEROS2 to 24 years of radar rainfall and streamflow data in 6 arid catchments. A GLUE probabilistic framework is used to characterize model performance, and a method is developed to identify floods with similar calibration. The analysis shows that uninformative conditions are difficult to generalize. A basin-specific analysis can help to identify conditions where the model fails and exclude them from calibration. Despite the large uncertainties, similar catchments display groups of floods with similar parameterization. In some basin we find that it is important to quantify antecedent moisture conditions. Hydrological models show some consistency within limited conditions. These conditions, however, depend on the errors involved, and are site-specific. There is some potential for parameter transfer, but proximity alone might not be enough, and other factors such as mean annual rainfall or storm type, should be taken into account.

Improved SMA-based SCS-CN method incorporating storm duration for runoff prediction on the Loess Plateau, China

Abstract In the Soil Conservation Service Curve Number (SCS-CN) method for estimating runoff, three antecedent moisture condition (AMC) levels produce a discrete relation between the curve number (CN) and soil water content, which results in corresponding sudden jumps in estimated runoff. An improved soil moisture accounting (SMA)-based SCS-CN method that incorporates a continuous function for the AMC was developed to obviate sudden jumps in estimated runoff. However, this method ignores the effect of storm duration on surface runoff, yet this is an important component of rainfall-runoff processes. In this study, the SMA-based method for runoff estimation was modified by incorporating storm duration and a revised SMA procedure. Then, the performance of the proposed method was compared to both the original SCS-CN and SMA-based methods by applying them in three experimental watersheds located on the Loess Plateau, China. The results indicate that the SCS-CN method underestimates large runoff events and overestimates small runoff events, yielding an efficiency of 0.626 in calibration and 0.051 in validation; the SMA-based method has improved runoff estimation in both calibration (efficiency = 0.702) and validation (efficiency = 0.481). However, the proposed method performed significantly better than both, yielding model efficiencies of 0.810 and 0.779 in calibration and validation, respectively.

Evaluation and validity of the antecedent moisture condition (AMC) of Natural Resources Conservation Service-Curve Number (NRCS-CN) procedure in undeveloped arid basins

The available conversion formulae for AMC-CN are estimated in an environment that is not arid. The validity of these formulae in arid regions is questionable. Therefore, in the current study, a focus is made on studying the validity of the NRCS-CN theory, its AMC, formulas, and derivation of conversion formulae of CN for some arid basins in the southwest Saudi Arabia (SA). One hundred sixty-one rainfall-runoff events have been collected over a period of 4 years on 19 sub-basins in the study area. The results show that in arid regions the AMCI antecedent moisture condition at (dry) conditions is dominant. It has been shown that the abstraction ratio, λ = 0.01, is the best to fit the NRCS-CN theory when compared with λ = 0.2 or 0.3. The observed and estimated runoff show that the root mean square error (RMSE) is the lowest for λ = 0.01 (1.8 mm, 3.69 mm, and 1.36 mm) when compared with λ = 0.2 (4.21 mm, 12.13 mm, and 3.15 mm) and λ = 0.3 (5.74 mm, 13.92 mm, and 3.1 mm) for CNI (CN at dry condition), CNII (CN at normal condition), and CNIII (CN at wet condition) respectively. The upper and lower limits of λ, in SA, are 0.02 (90% probability) and 0.00001 (10% probability) respectively. The runoff coefficient is less than 0.4. This is due to high transmission losses which is typical in arid regions. The study recommends using λ = 0.01 and the developed AMC-CN formulae for enhanced runoff predictions in SA.

Chemical leaching behaviour of a full-scale green roof in a cold and semi-arid climate

Despite the benefits of green roofs in managing urban stormwater quantity and quality, a number of studies have demonstrated that green roofs can pose negative impacts on the urban environment due to chemical leaching, in particular in their early age. Besides design variables such as growing media composition and depth, the roof age and hydro-meteorological variables are also expected to affect or govern the temporal evolution of chemical leaching. To characterize the chemical leaching behavior of green roofs and explore possible modeling approaches, a full-scale extensive green roof and a reference roof, which are located in a cold and semi-arid climate region, were monitored in both rain and snowmelt events in 2015–2018. The temporal evolution of chemical leaching was examined at both intra- and inter-annual time scales. The roles of hydro-meteorological variables including the growing media temperature (GMT), moisture condition (antecedent moisture condition (AMC) for rain events, and moisture condition (MC) for snowmelt), event rainfall amount (Ra), and cumulative inflow/precipitation amount on chemical leaching were investigated. The field observations demonstrated the leaching of nutrients (i.e., both nitrogen (N) and phosphorous (P)) and conductivity from the green roof, whereas the roof acted as a sink for metals (Zn, Cu, and Pb). The leaching of N appeared to cease, whereas P leaching was still ongoing at the end of the study period. Although the degree of nutrient leaching was not significantly different between the rain and snowmelt events, the nutrient leaching in rain events appeared to be relatively higher in the spring than in the summer and fall. Furthermore, the leaching of nutrients was found to decline annually, but at different rates for different nutrients. Among the investigated hydro-meteorological variables, the cumulative inflow was identified influencing the temporal evolution of chemical leaching considerably. In addition, the results from two modeling approaches, namely multiple linear regression modeling and semi-physically based modeling adapted from the pollutant wash-off concept for urban stormwater runoff, confirmed the critical role of the cumulative inflow on chemical leaching. Besides the cumulative inflow, the GMT was the other important explanatory variable for P leaching. The results suggested that chemical leaching from green roofs in semi-arid regions, where precipitation and moisture level are low, could persist longer but at a lower degree compared to that in mild and temperate climate regions.

High-Resolution, In Situ Monitoring of Stable Isotopes of Water Revealed Insight into Hydrological Response Behavior

High temporal resolution (20-min intervals) measurements of stable isotopes from groundwater, stream water and precipitation were investigated to understand the hydrological response behavior and control of precipitation and antecedent wetness conditions on runoff generation. Data of 20 precipitation events were collected by a self-sufficient mobile system for in situ measurements over four months in the Schwingbach Environmental Observatory (SEO, temperate climate), Germany. Isotopic hydrograph separation indicated that more than 79% of the runoff consisted of pre-event water. Short response times of maximum event water fractions in stream water and groundwater revealed that shallow subsurface flow pathways rapidly delivered water to the stream. Macropore and soil pipe networks along relatively flat areas in stream banks were likely relevant pathways for the rapid transmission of water. Event water contribution increased with increasing precipitation amount. Pre-event water contribution was moderately affected by precipitation, whereas, the antecedent wetness conditions were not strong enough to influence pre-event water contribution. The response time was controlled by mean precipitation intensity. A two-phase system was identified, at which the response times of stream water and groundwater decreased after reaching a threshold of mean precipitation intensity of 0.5 mm h−1. Our results suggest that high temporal resolution measurements of stable isotopes of multiple water sources combined with hydrometrics improve the understanding of the hydrological response behavior and runoff generation mechanisms.

Multi-scale analysis of runoff from a statistical perspective in a small Sahelian catchment under semi-arid climate

In Sahelian and semi-arid regions, understanding the runoff processes and at different spatial scales is critical to assess sources of variation and further improve distributed modelling. In this study, through a multi-scale analysis, runoff measurements on different soil surface features and at different scales of observation were carried over 6 years of monitoring in a typical Sahelian landscape in Burkina Faso. Statistical and dimensional analyses were used to investigate significant differences in runoff response behaviour on plots of 1 m2, 50 m2 and 150 m2, hydrologic units of 6 and 34 ha and the catchment of 37 km2. Results showed that on both cultivated and bare soils, the runoff excess decreases as the area increases, under similar rainfall pattern and prior antecedent soil moisture conditions. On degraded soils, the processes of runoff generation on the plots of 50 and 150 m2 are identical and significantly different from those observed on the unit plot (1 m2). A minimum plot length of 10 m was found to be sufficient to accurately estimate runoff on degraded soils. On cultivated soils, runoff is significantly different from one site to another because of the spatial variability of hydrodynamic properties of the soil. Such results show that the scale effect on runoff is related to the spatial heterogeneity of soils and is further intensified by the rainfall intensity. Such results highlight the value of quantification of runoff on homogeneous units, hence allowing an innovative approach to the problem of scale transfer.

Understanding the dynamic nature of Time-to-Peak in UK streams

In flood forecasting and design for peak flows, understanding and characterizing the hydrologic response to rainfall events is vitally important. One of the key parameters utilized to characterize the catchment response time is the Time-to-Peak (Tp), which represents the net rise time of a storm hydrograph, or the time from when a precipitation event begins to contribute to stream discharge, to the time that peak flow (Qp) is reached. Previously, influencing factors on Tp have been static in nature with no consideration of the variability in Tp due to size of the storm event and the antecedent moisture conditions of the watershed (seasonal effects). Using ~1400 storm event observations and the corresponding catchment characteristics of 153 stream gauges across the United Kingdom (UK), the importance of different factors on estimating Tp are evaluated. These data points span three decades, and this breadth of temporal data allowed meaningful annual trends to be observed, and seasonal variations in soil moisture to be identified and applied. A new “wetness coefficient” is applied herein, to reflect the antecedent conditions within a catchment. The Qp is selected as a dynamic variable, utilized to represent the magnitude of a given storm, due to the demonstrated correlation with Tp. An explicit equation based on gene expression programming is designed, which accounts for the dynamic nature of Tp through Qp and seasonal moisture effects. The results of the proposed model are compared to the results of the existing equation for Tp prediction in the UK, outlined by the Flood Estimation Handbook (FEH). The proposed equation (with Nash-Sutcliffe Coefficient, R2 and RMSE values equal to 0.60, 0.66 and 3.64, respectively), has improved characteristics compared with the traditional FEH equation (Nash = 0.42, R2 = 0.54, and RMSE = 4.37). A forensic analysis of the contributing factors for Tp involves development of an empirical model with improved prediction accuracy, by accounting for the dynamic inputs, improving previous models both statistically, as well as in the hydrologic understanding of the catchment response.

Multiple Temporal Scales Assessment in the Hydrological Response of Small Mediterranean-Climate Catchments

Mediterranean-climate catchments are characterized by significant spatial and temporal hydrological variability caused by the interaction of natural as well human-induced abiotic and biotic factors. This study investigates the non-linearity of rainfall-runoff relationship at multiple temporal scales in representative small Mediterranean-climate catchments (i.e., <10 km2) to achieve a better understanding of their hydrological response. The rainfall-runoff relationship was evaluated in 43 catchments at annual and event—203 events in 12 of these 43 catchments—scales. A linear rainfall-runoff relationship was observed at an annual scale, with a higher scatter in pervious (R2: 0.47) than impervious catchments (R2: 0.82). Larger scattering was observed at the event scale, although pervious lithology and agricultural land use promoted significant rainfall-runoff linear relations in winter and spring. These relationships were particularly analysed during five hydrological years in the Es Fangar catchment (3.35 km2; Mallorca, Spain) as a temporal downscaling to assess the intra-annual variability, elucidating whether antecedent wetness conditions played a significant role in runoff generation. The assessment of rainfall-runoff relationships under contrasted lithology, land use and seasonality is a useful approach to improve the hydrological modelling of global change scenarios in small catchments where the linearity and non-linearity of the hydrological response—at multiple temporal scales—can inherently co-exist in Mediterranean-climate catchments.

Verification of a New Spatial Distribution Function of Soil Water Storage Capacity Using Conceptual and SWAT Models

The Soil Conservation Service Curve Number (SCS-CN) method is widely used in conceptual rainfall-runoff models for describing the runoff response with a curve, which is a function of the cumulative storm rainfall and antecedent wetness conditions. To improve the SCS-CN method, a new distribution function was recently proposed to unify the surface runoff modeling of the SCS-CN method and probability-distributed functions in the variable infiltration capacity (VIC) and Xin’anjiang models. This study aims to verify the new distribution function in a conceptual rainfall-runoff model and in the Soil and Water Assessment Tool (SWAT) by using real catchments. The Xunhe River basin in China and other basins in the United States were used as case studies. Results show that more observed variability in streamflow is captured when using the new spatial distribution function of soil water storage capacity in the conceptual runoff model. Specifically, there is a 9.8% average increase in the Nash-Sutcliffe efficiency (NSE), while simultaneously reducing the bias and mean relative absolute error (MRAE). When using the new distribution in SWAT, the model is able to better estimate the observed streamflow as indicated by higher NSE values for most of the basins. Akaike information criterion (AIC) is used for validating the goodness-of-fit when the number of parameters and model structure change. Further findings suggest that the estimated variance is more sensitive to the value of the new shape parameter a when soil water content is low in the early stage of rainfall. Therefore, the proposed new distribution function is shown to be effective in improving the accuracy of simulating streamflow for both conceptual and SWAT models.

Flood Size Increases Nonlinearly Across the Western United States in Response to Lower Snow‐Precipitation Ratios

AbstractMany mountainous and high‐latitude regions have experienced more precipitation as rain rather than snow due to warmer winter temperatures. Further decreases in the annual snow fraction are projected under continued global warming, with potential impacts on flood risk. Here, we quantify the size of streamflow peaks in response to both seasonal and event‐specific rain‐fraction using stream gage observations from watersheds across the western United States. Across the study watersheds, the largest rainfall‐driven streamflow peaks are >2.5 times the size of the largest snowmelt‐driven peaks. Using a panel regression analysis of individual precipitation and snowmelt events, we show that the empirical streamflow response grows approximately exponentially as the liquid precipitation input increases, with rain‐dominated runoff leading to proportionately larger streamflow increases than snowmelt or mixed rain‐and‐snow runoff. We find that the response to changes in rain percentage is largest in the wettest watersheds, where wet antecedent conditions are important for increasing runoff efficiency. Similarly, the effect of rain percentage is larger across watersheds in the Northwest and West regions compared to watersheds in the Northern Rockies and Southwest regions. Overall, as a higher percentage of precipitation falls as rain, increases in the size of rainfall‐driven and “rain‐on‐snow”‐driven floods have the potential to more than offset decreases in the size of snowmelt‐driven floods.

Preferential flow of surface‐applied solutes: Effect of lysimeter design and initial soil water content

AbstractUndisturbed lysimeters are widely used to study water and solute transport, where both natural and unnatural preferential flow can greatly influence leaching rates. The objective of this study was to use chemical and isotopic tracers to quantify the effect of initial soil water content and lysimeter design on preferential flows. Ten undisturbed lysimeters (900 cm2) were collected from an agricultural field, with the gap between the soil and lysimeter casing sealed with petroleum jelly for five lysimeters. Lysimeters were subjected to two rainfall simulations (3.3 cm h−1) under contrasting initial soil water contents, and leachate near the soil‐casing interface was collected separately from leachate through the bulk soil. Three‐component hydrograph separation revealed that event water comprised 21–59% of total leachate irrespective of initial soil water content and lysimeter design. Sealing the edges of the lysimeters with petroleum jelly greatly reduced but did not eliminate edge flow during rainfall simulations. Although water and solute transport were similar in both sealed and unsealed lysimeters under dry antecedent conditions due to the formation of shrinkage cracks on the soil surface, edge flow was substantially greater for the unsealed lysimeters under wet antecedent conditions. Unsealed edges under wet antecedent conditions facilitated the preferential transport of both event and pre‐event water, resulting in greater solute leaching. Using multiple tracers to contrast lysimeter designs under different initial soil water contents not only allowed for rigorous testing of a commonly used edge‐flow suppression technique but also provided new insights into preferential flow processes and patterns.

Analysis of surface runoff potential in ungauged basin using basin parameters and SCS-CN method

The present research work was carried out to understand the influence of basin morphometric parameters on runoff potential in an ungauged basin using satellite images, topographical maps, and rainfall data combined with geospatial techniques. The upper Gosthani river basin is an ungauged basin which is located in the Eastern Ghats of Visakhapatnam District, Andhra Pradesh State, Southern India. The river Gosthani and its tributaries are draining through the basin area covering about 321.1 km2. The quantitative analysis of basin morphometry reveals that the area is under influenced by steep ground slopes, with moderate to less permeable rocks, leading to high runoff. The basin is elongated in shape resulting to flatter peak of flow for longer duration. The daily rainfall data during 2008–2016 were used in the estimation of runoff potential with the help of the Soil Conservation Service-Curve Number (SCS-CN) model. The weighted curve number was determined by the integration of land use and land cover, antecedent moisture condition, and hydrological soil groups. It was observed from the analysis that the overall increase in runoff corresponding to the rainfall. The area receives a good amount of rainfall, but most of it lost as surface runoff (nearly 40% of total rainfall) due to rapid overland flow and impermeable rocks. Analysis of morphometric parameters combined with SCS-CN-based approaches can be explored as an alternative for simulating the hydrological response of the basins.

Probabilistic estimation of design runoff curve number: a case study for Shakkar river watershed, India

In this study, one-day, two-day and three-day maximum surface runoff were calculated. The curve number (CN) are dealt with as arbitrary factors with the CN connected with antecedent moisture condition (AMC-II) representing 50%, AMC-I, AMC-III representative of 10% and 90% CN value, respectively. The maximum surface runoff for one, two and three-day was fitted with three probability distribution [log-normal (LN), Gumbel and log-Pearson-III]. Out of three probability distribution, log-Pearson-III showed the best fit for the data. The maximum surface runoff (1/2/3 day) was estimated at 2, 5, 10, 25, 50, 100 and 200 years return periods. For all the return periods and rain durations, the design CN runoff and conventional design runoff found satisfactory performance. Probabilistic estimation of one, two and three-day maximum runoff is important for safe and cost effective planning and design of surface runoff storage system.

Patterns and Drivers of Atmospheric River Precipitation and Hydrologic Impacts across the Western United States

AbstractAtmospheric rivers (ARs) significantly influence precipitation and hydrologic variability in many areas of the world, including the western United States. As ARs are increasingly recognized by the research community and the public, there is a need to more precisely quantify and communicate their hydrologic impacts, which can vary from hazardous to beneficial depending on location and on the atmospheric and land surface conditions prior to and during the AR. This study leverages 33 years of atmospheric and hydrologic data for the western United States to 1) identify how water vapor amount, wind direction and speed, temperature, and antecedent soil moisture conditions influence precipitation and hydrologic responses (runoff, recharge, and snowpack) using quantile regression and 2) identify differences in hydrologic response types and magnitudes across the study region. Results indicate that water vapor amount serves as a primary control on precipitation amounts. Holding water vapor constant, precipitation amounts vary with wind direction, depending on location, and are consistently greater at colder temperatures. Runoff efficiencies further covary with temperature and antecedent soil moisture, with precipitation falling as snow and greater available water storage in the soil column mitigating flood impacts of large AR events. This study identifies the coastal and maritime mountain ranges as areas with the greatest potential for hazardous flooding and snowfall impacts. This spatially explicit information can lead to better understanding of the conditions under which ARs of different precipitation amounts are likely to be hazardous at a given location.

Effects of Deforestation on Water Flow in the Vadose Zone

The effects of land use change on the occurrence and frequency of preferential flow (fast water flow through a small fraction of the pore space) and piston flow (slower water flow through a large fraction of the pore space) are still not fully understood. In this study, we used a five year high resolution soil moisture monitoring dataset in combination with a response time analysis to identify factors that control preferential and piston flow before and after partial deforestation in a small headwater catchment. The sensor response times at 5, 20 and 50 cm depths were classified into one of four classes: (1) non-sequential preferential flow, (2) velocity based preferential flow, (3) sequential (piston) flow, and (4) no response. The results of this analysis showed that partial deforestation increased sequential flow occurrence and decreased the occurrence of no flow in the deforested area. Similar precipitation conditions (total precipitation) after deforestation caused more sequential flow in the deforested area, which was attributed to higher antecedent moisture conditions and the lack of interception. At the same time, an increase in preferential flow occurrence was also observed for events with identical total precipitation. However, as the events in the treatment period (after deforestation) generally had lower total, maximum, and mean precipitation, this effect was not observed in the overall occurrence of preferential flow. The results of this analysis demonstrate that the combination of a sensor response time analysis and a soil moisture dataset that includes pre- and post-deforestation conditions can offer new insights in preferential and sequential flow conditions after land use change.

Event‐based deep drainage and percolation dynamics in Vertosols and Chromosols

AbstractThe quantification of percolation processes and deep drainage rates in cracking clays is challenging due to the existence of multiple flow pathways, including desiccation crack networks, and the effect of variability in antecedent soil moisture and rain event properties. While most previous research on this topic focuses on long‐term average rates, this study focusses on inter‐event dynamics. The study uses data from soil moisture sensors distributed vertically down 4 m profiles of Vertosol and Chromosol soils across 13 sites over an area of approximately 20 km2. The objectives were to estimate the temporal and spatial variability of deep drainage rates and to investigate the effect of antecedent soil moisture conditions and rain event properties on deep drainage rates and percolation dynamics. 35 deep drainage events over a 40‐month period contributed 78 % of the total deep drainage of 254 mm at 4 m depth. Average deep drainage estimates were about 15 % (ranging from 0 – 80 % between sites) of total rainfall and irrigation in the Vertosol and 8% (0 – 24 %) in the Chromosol. The event water travel times at 4 m depth were 0.25 – 38 hr and 14 – 39 hr in the Vertosol and Chromosol respectively. The event deep drainage rates averaged across sites were associated with event rainfall volumes (linear regression R2 = 0.40), with the effect of antecedent conditions evident only when looking at inter‐site differences. The percolation response time was strongly associated with higher rainfall intensities (R2 = 0.33) with no evidence from the linear regression of an antecedent moisture effect.

A rational runoff coefficient for a revisited rational formula

ABSTRACTThe Rational Formula (RF) is probably the most frequently applied equation in practical hydrology to compute the peak discharge, due to its simplicity and effective compromise between theory and data availability. Thus, after more than a century, the estimation of peak discharge through the RF is still an important and challenging issue in hydrology. The RF assumes response linearity and sometimes assumes that the return period does not depend on the runoff coefficient and neglects the time to ponding and the antecedent moisture condition. Moreover, the RF requires the critical duration of rainfall and the runoff coefficient to be estimated, both of which are highly controversial. This paper proposes an advanced RF that makes it possible to derive the peak discharge at the hillslope scale, where the above RF assumptions are mostly relaxed. Physically based runoff coefficient tables, which are not affected by subjectivity, are presented and application of the derived procedure is performed.

Statistically-based projected changes in the frequency of flood events across the U.S. Midwest

There is growing empirical evidence that many river basins across the U.S. Midwest have been experiencing an increase in the frequency of flood events over the most recent decades. Albeit these detected changes are important to understand what happened in our recent past, they cannot be directly extrapolated to obtain information about possible future changes in the frequency of flood events. Building on recent statistically-based attribution studies, we project seasonal changes in the frequency of flood events at 286 U.S. Geological Survey gauging stations across the U.S. Midwest using projections of precipitation, antecedent wetness conditions and temperature as drivers. The projections of the covariates are obtained from two datasets obtained by downscaling global circulation models from the Fifth Coupled Model Intercomparison Project (CMIP5). We focus on the representative concentration pathway (RCP) 8.5 and on four different flood thresholds (i.e., from more common to less frequent flood events). We find that the frequency of flood events during the 21st century increases during spring at most of the analyzed gauging stations, with larger changes in the Northern Great Plains and regardless of the flood threshold value. Our findings also point to a projected increasing number of flood events during the winter, especially in the stations in the southern and western part of the domain (Iowa, Missouri, Illinois, Ohio, Indiana and Michigan). A marked change in the frequency of flood events is not projected for the summer and fall.

Role of Extreme Precipitation and Initial Hydrologic Conditions on Floods in Godavari River Basin, India

AbstractFloods are the most frequent natural calamity in India. The Godavari river basin (GRB) witnessed several floods in the past 50 years. Notwithstanding the large damage and economic loss, the role of extreme precipitation and antecedent moisture conditions on floods in the GRB remains unexplored. Using the observations and the well‐calibrated Variable Infiltration Capacity model, we estimate the changes in the extreme precipitation and floods in the observed (1955–2016) and projected future (2071–2100) climate in the GRB. We evaluate the role of initial hydrologic conditions and extreme precipitation on floods in both observed and projected future climate. We find a statistically significant increase in annual maximum precipitation for the catchments upstream of four gage stations during the 1955–2016 period. However, the rise in annual maximum streamflow at all the four gage stations in GRB was not statistically significant. The probability of floods driven by extreme precipitation (PFEP) varies between 0.55 and 0.7 at the four gage stations of the GRB, which declines with the size of the basins. More than 80% of extreme precipitation events that cause floods occur on wet antecedent moisture conditions at all the four locations in the GRB. The frequency of extreme precipitation events is projected to rise by two folds or more (under RCP 8.5) in the future (2071–2100) at all four locations. However, the increased frequency of floods under the future climate will largely be driven by the substantial rise in the extreme precipitation events rather than wet antecedent moisture conditions.