甘肃北部短时强降水中尺度特征及物理量配置

利用甘肃北部27个国家级自动气象站及635个区域气象站降水资料,结合常规高空、地面和欧洲中期天气预报中心（ECMWF）再分析物理量场资料,选取了2016—2019年5—9月104个典型短时强降水个例,对甘肃北部短时强降水天气发生发展的环境条件进行了中尺度综合分析,揭示了区域内短时强降水的一些特征和规律。结果表明：（1） 甘肃北部短时强降水集中出现在6—8月,短时强降水的强度多为10~20 mm。（2） 甘肃北部短时强降水天气的典型特征,分为副高边缘型、低压槽型、西北气流型和河套阻高型4种流型。（3） 通过分析不同天气形势、不同类别、不同物理量参数间的联系与区别,总结出各类短时强降水天气的环流特征和物理量要素指标和阈值。（4） 地面辐合线（冷锋）是甘肃北部触发强对流天气的关键系统,地面辐合线（冷锋）的分析对短时临近预报至关重要。（5） 低空偏南风急流（显著流线）在110°E左右北上及在37°N左右产生辐合是判断甘肃北部能否产生短时强降水的重要依据。并对2020年短时强降水预报效果进行检验,预报准确率达63.6%,说明建立的短时强降水预报指标预报能力较强,为提高短时强降水预报预警能力提供了一种新途径。     

Is rainfall intensity significant in the rainfall–runoff process within tropical rainforests of northeast Queensland? The Hewlett regression analyses revisited

Following the statistical analyses of long‐term rainfall‐runoff records from research basins in humid temperate latitudes, Hewlett and co‐workers extended the global challenge to disprove their findings that rainfall intensity was non‐significant. This paper responds to Hewlett's challenge as no preceding analyses have involved forested basins in a tropical cyclone‐prone area. Based on a 7 year rainfall‐runoff record, quickflow (QF), peak flow (QP) and quickflow response ratios (QRR) were regressed as dependent variables against rainfall parameters (intensity, P_i, amount, P), storm duration, D and antecedent flow, I. These data sets were categorised into total streamflow (Q) classes and stratified into three seasons, (monsoon, post‐monsoon and dry) for forested and cleared catchments. Where rainfall variable collinearity met acceptable levels, the addition of P_i to regression models including P, D, I contributed up to 9% and 66% of the respective variations in quickflow and peak flow. For the highest Q storm classes (monsoon), P_i alone accounted for up to 67% and 91% of the variation in Q_F and Q_P respectively and was the dominant influence on Q_P for all seasons. The very high rainfall intensities experienced in the monsoon season is a causal factor why these results differ from those of other research drainage basins. Surprisingly, P_i continued to have a significant influence on Q_F for dry season classes when less‐intense rainfall occurs. Further the results were similar for both catchments across all seasons. P was the dominant independent variable affecting Q_F above a threshold Q of 50 mm (monsoon), as rainfall contributes directly to saturation overland flow and return flow under saturated conditions. Further although QRR increased with increasing Q for each season, the regression results for that parameter were poor possibly due to the non‐linearity of the rainfall‐runoff relationship. Copyright © 2010 John Wiley & Sons, Ltd.     

Extreme value modelling of daily areal rainfall over Mediterranean catchments in a changing climate

Heavy rainfall events during the fall season are causing extended damages in Mediterranean catchments. A peaks‐over‐threshold model is developed for the extreme daily areal rainfall occurrence and magnitude in fall over six catchments in Southern France. The main driver of the heavy rainfall events observed in this region is the humidity flux (FHUM) from the Mediterranean Sea. Reanalysis data are used to compute the daily FHUM during the period 1958–2008, to be included as a covariate in the model parameters. Results indicate that the introduction of FHUM as a covariate can improve the modelling of extreme areal precipitation. The seasonal average of FHUM can improve the modelling of the seasonal occurrences of heavy rainfall events, whereas daily FHUM values can improve the modelling of the events magnitudes. In addition, an ensemble of simulations produced by five different general circulation models are considered to compute FHUM in future climate with the emission scenario A1B and hence to evaluate the effect of climate change on the heavy rainfall distribution in the selected catchments. This ensemble of climate models allows the evaluation of the uncertainties in climate projections. By comparison to the reference period 1960–1990, all models project an amplification of the mean seasonal FHUM from the Mediterranean Sea for the projection period 2070–2099, on average by +22%. This increase in FHUM leads to an increase in the number of heavy rainfall events, from an average of 2.55 events during the fall season in present climate to 3.57 events projected for the period 2070–2099. However, the projected changes have limited effects on the magnitude of extreme events, with only a 5% increase in the median of the 100‐year quantiles. Copyright © 2011 John Wiley & Sons, Ltd.     

Ensemble rainfall forecasting with numerical weather prediction and radar‐based nowcasting models

The overall objective of this study is to improve the forecasting accuracy of the precipitation in the Singapore region by means of both rainfall forecasting and nowcasting. Numerical Weather Predication (NWP) and radar‐based rainfall nowcasting are two important sources for quantitative precipitation forecast. In this paper, an attempt to combine rainfall prediction from a high‐resolution mesoscale weather model and a radar‐based rainfall model was performed. Two rainfall forecasting methods were selected and examined: (i) the weather research and forecasting model (WRF); and (ii) a translation model (TM). The WRF model, at a high spatial resolution, was run over the domain of interest using the Global Forecast System data as initializing fields. Some heavy rainfall events were selected from data record and used to test the forecast capability of WRF and TM. Results obtained from TM and WRF were then combined together to form an ensemble rainfall forecasting model, by assigning weights of 0.7 and 0.3 weights to TM and WRF, respectively. This paper presented results from WRF and TM, and the resulting ensemble rainfall forecasting; comparisons with station data were conducted as well. It was shown that results from WRF are very useful as advisory of anticipated heavy rainfall events, whereas those from TM, which used information of rain cells already appearing on the radar screen, were more accurate for rainfall nowcasting as expected. The ensemble rainfall forecasting compares reasonably well with the station observation data. Copyright © 2012 John Wiley & Sons, Ltd.     

A physically constrained wavelet-aided statistical model for multi-decadal groundwater dynamics predictions

A physically constrained wavelet-aided statistical model (PCWASM) is presented to analyse and predict monthly groundwater dynamics on multi-decadal or longer time scales. The approach retains the simplicity of regression modelling but is constrained by temporal scales of processes responsible for groundwater level variation, including aquifer recharge and pumping. The methodology integrates statistical correlations enhanced with wavelet analysis into established principles of groundwater hydraulics including convolution, superposition and the Cooper–Jacob solution. The systematic approach includes (1) identification of hydrologic trends and correlations using cross-correlation and multi-time scale wavelet analyses; (2) integrating temperature-based evapotranspiration and groundwater pumping stresses and (3) assessing model prediction performances using fixed-block k-fold cross-validation and split calibration-validation methods. The approach is applied at three hydrogeologicaly distinct sites in North Florida in the United States using over 40 years of monthly groundwater levels. The systematic approach identifies two patterns of cross-correlations between groundwater levels and historical rainfall, indicating low-frequency variabilities are critical for long-term predictions. The models performed well for predicting monthly groundwater levels from 7 to 22 years with less than 2.1 ft (0.7 m) errors. Further evaluation by the moving-block bootstrap regression indicates the PCWASM can be a reliable tool for long-term groundwater level predictions. This study provides a parsimonious approach to predict multi-decadal groundwater dynamics with the ability to discern impacts of pumping and climate change on aquifer levels. The PCWASM is computationally efficient and can be implemented using publicly available datasets. Thus, it should provide a versatile tool for managers and researchers for predicting multi-decadal monthly groundwater levels under changing climatic and pumping impacts over a long time period.     

How does afforestation affect the hydrology of a blanket peatland? A modelling study

Over the last century, afforestation in Ireland has increased from 1% of the land area to 10%, with most plantations on upland drained blanket peatlands. This land use change is considered to have altered the hydrological response and water balance of upland catchments with implications for water resources. Because of the difficulty of observing these long‐term changes in the field, the aim of this study was to utilize a hydrological model to simulate the rainfall runoff processes of an existing pristine blanket peatland and then to simulate the hydrology of the peatland if it were drained and afforested. The hydrological rainfall runoff model (GEOtop) was calibrated and validated for an existing small (76 ha) pristine blanket peatland in the southwest of Ireland for the 2‐year period, 2007–2008. The current hydrological response of the pristine blanket peatland catchment with regard to streamflow and water table (WT) levels was captured well in the simulations. Two land use change scenarios of afforestation were also examined, (A) a young 10‐year‐old and (B) a semi‐mature 15‐year‐old Sitka Spruce forest. Scenario A produced similar streamflow dynamics to the pristine peatland, whereas total annual streamflow from Scenario B was 20% lower. For Scenarios A and B, on an annual average basis, the WT was drawn down by 16 and 20 cm below that observed in the pristine peatland, respectively. The maximum WT draw down in Scenario B was 61 cm and occurred in the summer months, resulting in a significant decrease in summer streamflow. Occasionally in the winter (following rainfall), the WT for Scenario B was just 2 cm lower than the pristine peatland, which when coupled with the drainage networks associated with afforestation led to higher peak streamflows. Copyright © 2012 John Wiley & Sons, Ltd.     

Input data resolution‐induced uncertainty in watershed modelling

The temporal‐spatial resolution of input data‐induced uncertainty in a watershed‐based water quality model, Hydrologic Simulation Program‐FORTRAN (HSPF), is investigated in this study. The temporal resolution‐induced uncertainty is described using the coefficient of variation (CV). The CV is found to decrease with decreasing temporal resolution and follow a log‐normal relation with time interval for temperature data while it exhibits a power‐law relation for rainfall data. The temporal‐scale uncertainties in the temperature and rainfall data follow a general extreme value distribution and a Weibull distribution, respectively. The Nash‐Sutcliffe coefficient (NSC) is employed to represent the spatial resolution induced uncertainty. The spatial resolution uncertainty in the dissolved oxygen and nitrate‐nitrogen concentrations simulated using HSPF is observed to follow a general extreme value distribution and a log‐normal distribution, respectively. The probability density functions (PDF) provide new insights into the effect of temporal‐scale and spatial resolution of input data on uncertainties involved in watershed modelling and total maximum daily load calculations. This study exhibits non‐symmetric distributions of uncertainty in water quality modelling, which simplify weather and water quality monitoring and reducing the cost involved in flow and water quality monitoring. Copyright © 2011 John Wiley & Sons, Ltd.     

Spatial and temporal variability of the hydrological response in a small Mediterranean research catchment (Vallcebre,Eastern Pyrenees)

This paper analyses the spatial and temporal variability of the hydrological response in a small Mediterranean catchment (Cal Rodó). The first part of the analysis focuses on the rainfall–runoff relationship at seasonal and monthly scale, using an 8‐year data set. Then, using storm‐flow volume and coefficient, the temporal variability of the rainfall–runoff relationship and its relationship with several hydrological variables are analysed at the event scale from hydrographs observed over a 3‐year period. Finally, the spatial non‐linearity of the hydrological response is examined by comparing the Cal Rodó hydrological response with the Can Vila sub‐catchment response at the event scale. Results show that, on a seasonal and monthly scale, there is no simple relationship between rainfall and runoff depths, and that evapotranspiration is a factor that introduced some non‐linearity in the rainfall–runoff relationship. The analysis of monthly values also reveals the existence of a threshold in the relationship between rainfall and runoff depths, denoting a more contrasted hydrological response than the one usually observed in humid catchments. At the event scale, the storm‐flow coefficient has a clear seasonal pattern with an alternance between a wet period, when the catchment is hydrologically responsive, and a dry summer period, when the catchment is much less reactive to any rainfall. The relationship between the storm‐flow coefficient and rainfall depth, rainfall maximum intensity and base‐flow shows that observed correlations are the same as those observed for humid conditions, even if correlation coefficients are notably lower. Comparison with the Can Vila sub‐catchment highlights the spatial heterogeneity of the rainfall‐runoff relationship at the small catchment scale. Although interpretation in terms of runoff processes remains delicate, heterogeneities between the two catchments seem to be related to changes in the ratio between infiltration excess and saturation processes in runoff formation. Copyright © 2007 John Wiley & Sons, Ltd.     

Seasonal rainfall–runoff relationships in a lowland forested watershed in the southeastern USA

Hydrological processes of lowland watersheds of the southern USA are not well understood compared to a hilly landscape due to their unique topography, soil compositions, and climate. This study describes the seasonal relationships between rainfall patterns and runoff (sum of storm flow and base flow) using 13 years (1964–1976) of rainfall and stream flow data for a low‐gradient, third‐order forested watershed. It was hypothesized that runoff–rainfall ratios (R/P) are smaller during the dry periods (summer and fall) and greater during the wet periods (winter and spring). We found a large seasonal variability in event R/P potentially due to differences in forest evapotranspiration that affected seasonal soil moisture conditions. Linear regression analysis results revealed a significant relationship between rainfall and runoff for wet (r² = 0·68; p < 0·01) and dry (r² = 0·19; p = 0·02) periods. Rainfall‐runoff relationships based on a 5‐day antecedent precipitation index (API) showed significant (r² = 0·39; p < 0·01) correspondence for wet but not (r² = 0·02; p = 0·56) for dry conditions. The same was true for rainfall‐runoff relationships based on 30‐day API (r² = 0·39; p < 0·01 for wet and r² = 0·00; p = 0·79 for dry). Stepwise regression analyses suggested that runoff was controlled mainly by rainfall amount and initial soil moisture conditions as represented by the initial flow rate of a storm event. Mean event R/P were higher for the wet period (R/P = 0·33), and the wet antecedent soil moisture condition based on 5‐day (R/P = 0·25) and 30‐day (R/P = 0·26) prior API than those for the dry period conditions. This study suggests that soil water status, i.e. antecedent soil moisture and groundwater table level, is important besides the rainfall to seasonal runoff generation in the coastal plain region with shallow soil argillic horizons. Copyright © 2011 John Wiley & Sons, Ltd.