Precipitation-runoff Relationships Research Articles

Identifying the possible driving mechanisms in Precipitation-Runoff relationships with nonstationary and nonlinear theory approaches

Climate change and complex anthropogenic activities have raised significant concerns regarding Precipitation-Runoff Relationships (PRR). Traditional methods, assuming stationary and linear conditions, often fail to adequately capture these intricate links. To address the limitations, we proposed an integrated framework, employing the Driving indices for Precipitation-Runoff relationships within the nonStationary and nonLinear theory approaches (DPRS and DPRL) to identify the possible driving mechanisms in PRR. The framework is validated across five sub-basins (WRB1-WRB5) within the Wei River Basin, known for its high spatiotemporal variability and intense anthropogenic activities. Spatiotemporal dynamics, nonstationary processes, and nonlinear interactions among various factors are assessed, including climate forcing, groundwater, vegetation dynamics, and anthropogenic influences. DPRS and DPRL assessments revealed that baseflow significantly influences PRR but with high uncertainty. Potential evapotranspiration plays a dominant role in driving negative PRR changes in WRB5 (weakening the correlation between precipitation and runoff), while vegetation dynamics negatively affect PRR with lower uncertainty. Anthropogenic influences represented by Impervious Surface Ratio (ISR), Night-Time Light (NTL), and population density (POP) exhibit varying driving levels, with ISR having the strongest and direct impact, closely linked to urbanization processes and scale within the study cases. The mutual validation of DPRS and DPRL confirms the dominance of baseflow in the Wei River Basin, with urbanization contributing to high ISR, NTL, and POP driving levels in WRB2 and WRB3. Afforestation policies intensify vegetation dynamics’ impact in WRB4 and WRB5. This framework extends its utility to analyze various land evapotranspiration and soil moisture content at different depths in the PRR, supported by a physically-based hydrological model. Basin complexity is further employed to validate the reliability of the assessment outcomes. These insights contribute to a more comprehensive understanding of hydrological processes and facilitate informed decisions for sustainable water resource management within the basin.

Climate elasticity of evapotranspiration shifts the water balance of Mediterranean climates during multi-year droughts

Abstract. Multi-year droughts in Mediterranean climates may shift the water balance, that is, the partitioning rule of precipitation across runoff, evapotranspiration, and sub-surface storage. Mechanisms causing these shifts remain largely unknown and are not well represented in hydrologic models. Focusing on measurements from the headwaters of California's Feather River, we found that also in these mixed rain–snow Mediterranean basins a lower fraction of precipitation was partitioned to runoff during multi-year droughts compared to non-drought years. This shift in the precipitation–runoff relationship was larger in the surface-runoff-dominated than subsurface-flow-dominated headwaters (−39 % vs. −18 % decline of runoff, respectively, for a representative precipitation amount). The predictive skill of the Precipitation Runoff Modeling System (PRMS) hydrologic model in these basins decreased during droughts, with evapotranspiration (ET) being the only water-balance component besides runoff for which the drop in predictive skill during drought vs. non-drought years was statistically significant. In particular, the model underestimated the response time required by ET to adjust to interannual climate variability, which we define as climate elasticity of ET. Differences between simulated and data-driven estimates of ET were well correlated with accompanying data-driven estimates of changes in sub-surface storage (ΔS, r=0.78). This correlation points to shifts in precipitation–runoff relationships being evidence of a hysteretic response of the water budget to climate elasticity of ET during and after multi-year droughts. This hysteresis is caused by carryover storage offsetting precipitation deficit during the initial drought period, followed by vegetation mortality when storage is depleted and subsequent post-drought vegetation expansion. Our results point to a general improvement in hydrologic predictions across drought and recovery cycles by including the climate elasticity of ET and better accounting for actual subsurface water storage in not only soil, but also deeper regolith that stores water accessible to roots. This can be done by explicitly parametrizing carryover storage and feedback mechanisms capturing vegetation response to atmospheric demand for moisture.

Predictive models for wastewater flow forecasting based on time series analysis and artificial neural network.

Wastewater flow forecasting is key for proper management of wastewater treatment plants (WWTPs). However, to predict the amount of incoming wastewater in WWTPs, wastewater engineers face challenges arising from numerous complexities and uncertainties, such as the nonlinear precipitation-runoff relationships in combined sewer systems, unpredictability due to aging infrastructure, and frequently inconsistent data quality. To address such challenges, a time series analysis model (i.e., the autoregressive integrated moving average, ARIMA) and an artificial neural network model (i.e., the multilayer perceptron neural network, MLPNN) were developed for predicting wastewater inflow. A case study of the Barrie Wastewater Treatment Facility in Barrie, Canada, was carried out to demonstrate the performance of the proposed models. Fifteen-minute flow data over a period of 1 year were collected, and the resampled daily flow data were used to train and validate the developed models. The model performances were examined using root mean square error, mean absolute percentage error, coefficient of determination, and Nash-Sutcliffe efficiency. The results indicate that both models provided reliable forecasts, while ARIMA showed a slightly better performance than MLPNN in this case study. The proposed models can provide useful decision support for the optimization and management of WWTPs.

Flood hazard mapping in an urban area using combined hydrologic-hydraulic models and geospatial technologies

Flooding is one of the most occurring natural hazards every year risking the lives and properties of the affected communities, especially in Philippine context. To visualize the extent and mitigate the impacts of flood hazard in Malingon River in Valencia City, Bukidnon, this paper presents the combination of Geographic Information System, high-resolution Digital Elevation Model, land cover, soil, observed hydro-meteorological data; and the combined Hydrologic Engineering Center-Hydrologic Modeling System and River Analysis System models. The hydrologic model determines the precipitation-runoff relationships of the watershed and the hydraulic model calculates the flood depth and flow pattern in the floodplain area. The overall performance of hydrologic model during calibration was “very good fit” based on the criterion of Nash-Sutcliffe Coefficient of Model Efficiency, Percentage Bias and Root Mean Square Error – Observations Standard Deviation Ratio with the values of 0.87, -8.62 and 0.46, respectively. On the other hand, the performance of hydraulic model during error computation was “intermediate fit” using F measure analysis with a value of 0.56, using confusion matrix with 80.5% accuracy and the Root Mean Square Error of 0.47 meters. Flood hazard maps in 2, 5, 10, 25, 50 and 100-year return periods were generated as well as the number of flooded buildings in each flood hazard level and in different return periods were determined. The output of the study served as an important basis for a more informed decision and science-based recommendations in formulating local and regional policies for more effective and cost-efficient strategies relative to flood hazards.

Net precipitation in burned and unburned subalpine forest stands after wildfire in the northern Rocky Mountains

Wildfire can exert considerable influence on many watershed processes, including the partitioning of precipitation by forest canopies. Despite general acknowledgement that canopy interception is reduced following wildfire, effects on net rainfall and snow accumulation have not been quantified. The objectives of this study were to document net rainfall and snow water equivalent (SWE) in burned and unburned (reference) forest stands over a 10-year period to characterise the effects of severe wildfire on net precipitation in the Canadian Rocky Mountains. Differences in summer (June–September) rainfall between burned and reference stands suggest that wildfire reduced rainfall interception by 65%, resulting in a 48% increase in net rainfall from 2006 to 2008. This represented an average annual increase in net rainfall of 122mm (36%) for 10 years after the fire. Similarly, a burned stand had 152mm (78%) higher mean annual peak SWE than a paired reference stand. Collectively, burned stands had 274mm (191–344mm; 51%) more mean annual net precipitation for the first decade after fire. These results suggest that increases in net precipitation are likely following wildfire in subalpine forests and that, owing to the slow growth of these forests, post-fire changes may alter precipitation–runoff relationships for many years.

A volumetric water budget of Devils Lake (USA): non-stationary precipitation–runoff relationships in an amplifier terminal lake

ABSTRACTDevils Lake, a terminal lake in eastern North Dakota, rose more than 9 m between 1992 and 2013, producing a 286% increase in lake area, and causing more than US$1 billion in direct damages. An annual volumetric lake water budget is developed from monthly hydroclimatological variables for the period 1951–2010 to investigate the rapid lake expansion. The lake is an amplifier terminal lake in which long-term climatic changes are amplified by positive feedback mechanisms, causing the lake to transition from a precipitation-dominated to a runoff-dominated water budget. Factors specific to the Devils Lake Basin further amplify this positive feedback relationship. These include principles of fill–spill hydrology that operate between individual sub-basins within the closed basin, and between the innumerable wetland complexes within each sub-basin. These factors create a pronounced non-stationary precipitation–runoff relationship in the basin during both long-term wetting and drying phases.

Considering Streamflow Trend Analyses Uncertainty in Urbanizing Watersheds: A Baseflow Case Study in the Central United States

Abstract Assuming pro rata reductions in baseflow resulting from urban development may not be valid in all urbanizing watersheds. Anthropogenic offsets or compensatory contributions to baseflow (e.g., net exfiltration from sewer lines, wastewater effluents, and lawn irrigation) may mask or confound fundamental changes in hydrologic pathways. These offsets illustrate the complexities of urban flow processes and the need for improved understanding to mitigate urban development impacts. The authors used two dissimilar automated baseflow separation algorithms and Monte Carlo techniques to evaluate urban baseflow and estimation uncertainty using data from a representative urban watershed in the central United States. Three uncertainties affecting trend determinations were assessed, including algorithm structure, precipitation–runoff relationships, and baseflow algorithm parameterization. Results indicate that, despite ongoing population growth and development, annual streamflow metrics in the authors' representative watershed have not significantly increased or decreased (p > 0.05) from 1967 to 2010. However, several streamflow metrics featured shallow insignificant (p > 0.05) slopes in the direction hypothesized for an urbanizing (less pervious) watershed, including a downward slope for baseflow index (BFI) and increases in runoff volume coefficient. Median annual baseflow estimations differed by 29% between techniques (85.3 versus 118.9 mm yr−1). In the absence of direct tracer measurements, uncertainties associated with precipitation–runoff relationships, algorithm structure, and parameterization should be included in analyses evaluating alterations from baseline hydrologic conditions in urban watersheds. To advance application of separation algorithms for urban watersheds and support regulatory reductions in runoff volume, future work should include calibration of model parameters to available hydrogeologic and tracer data.

Precipitation-runoff simulation for a Himalayan River Basin, India using artificial neural network algorithms

In the Himalayan regions, precipitation-runoff relationships are amongst the most complex hydrological phenomena, due to varying topography and basin characteristics. In this study, different artificial neural networks (ANNs) algorithms were used to simulate daily runoff at three discharge measuring sites in the Himalayan Kosi River Basin, India, using various combinations of precipitation-runoff data as input variables. The data used for this study was collected for the monsoon period (June to October) during the years of 2005 to 2009. ANNs were trained using different training algorithms, learning rates, length of data and number of hidden neurons. A comprehensive multi-criteria validation test for precipitation-runoff modeling has been undertaken to evaluate model performance and test its validity for generating scenarios. Global statistics have demonstrated that the multilayer perceptron with three hidden layers (MLP-3) is the best ANN for basin comparisons with other MLP networks and Radial Basis Functions (RBF). Furthermore, non-parametric tests also illustrate that the MLP-3 network is the best network to reproduce the mean and variance of observed runoff. The performance of ANNs was demonstrated for flows during the monsoon season, having different soil moisture conditions during period from June to October.

Special Section on Climate Change and Water Resources: Climate Nonstationarity and Water Resources Management

Over the past three decades, hydrologists and water resources specialists have been concerned with the issue of nonstationarity arising from several factors. First is the effect of human intervention on the landscape that may cause changes in the precipitation–runoff relationships at various temporal and spatial scales. Second is the occurrence of natural events such as volcanic explosions or forest fires that may cause changes in the composition of the air, the soil surface, and geomorphology. Third is the low-frequency component of oceanic–atmospheric phenomena that may have significant effects on the variability of hydrological processes such as annual runoff, peak flows, and droughts. Fourth is global warming, which may cause changes to oceanic and atmospheric processes, thereby affecting the hydrological cycle at various temporal and spatial scales. There has been a significant amount of literature on the subject and thousands of research and project articles and books published in recent decades. Examples of human intrusion on the landscape are the changes in land use resulting from agricultural developments in semiarid and arid lands (e.g., Pielke et al. 2007, 2011), changes caused by large-scale deforestation (e.g., Gash and Nobre 1997), changes resulting from open-pit mining operations (e.g., Salas et al. 2008), and changes from increasing urbanization in watersheds (e.g., Konrad and Booth 2002, Villarini et al. 2009). These intrusions change hydrologic response characteristics such as the magnitude and timing of floods. In many situations, current systems and management practices will be ill equipped to cope with such changes unless adjustments are made. Large-scale landscape changes such as deforestation in the tropical regions can potentially alter atmospheric circulation patterns, and consequently affect global weather and climate (e.g., Lee et al. 2008, 2009). Major natural events, such as the volcanic explosion of Mount St. Helens in 1980 or the El Chichon volcanic explosion of 1982 induce a shock to the climate system in the form of global cooling that continues for several years. These events can also affect global circulation. Low-frequency climate drivers of the oceanic– atmospheric system such as the El Nino/Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), and Arctic Oscillation (AO) modulate global climate at interannual and multidecadal time scales. These drivers are the main sources of nonstationarity in global climate and hydrology. Large numbers of papers documenting the effect of these drivers on global hydroclimatology continue to emerge (e.g., Dilley and Heyman 1995; Mantua et al. 1997; Enfield et al. 2001; Akintug and Rasmussen 2005; Hamlet et al. 2005). In addition to climate variability and change due to the previously mentioned factors, anthropogenic warming of the oceans and atmosphere because of increased greenhouse gas concentrations and the ensuing changes to the hydrologic cycle are topics of serious pursuit. The international scientific community is making strides in understanding the potential warming and its effects on all aspects of climate variability [Intergovernmental Panel on Climate Change (IPCC) 2007], but the impacts on the hydrologic cycle remain debatable and inconclusive (e.g., Cohn and Lins 2005; Legates et al. 2005; Hirsch and Ryberg 2011). Based on analyses of the global mean CO2 (GMCO2) and annual flood records in the United States, no strong statistical evidence for flood magnitudes increasing with GMCO2 increases were found (Hirsch and Ryberg 2011). Although general circulation models have had success in the attribution of warming global temperatures to anthropogenic causes, their credibility and utility in reproducing variables that are relevant to hydrology and water resources applications is less clear. For example, the IPCC Report for Latin America acknowledges that “the current GCMs do not produce projections of changes in the hydrological cycle at regional scales with confidence. In particular the uncertainty of projections of precipitation remain high : : :That is a great limiting factor to the practical use of such projections for guiding active adaptation or mitigation policies” (Magrin et al. 2007; Boulanger et al. 2007). A variety of methods exist that address the concern of nonstationarity in hydrological processes and the topic remains an active research area. For example, in watersheds in which increasing urbanization has been documented causing significant effects in the flood response and magnitude, watershed modeling has been utilized to estimate the possible changes in the flood frequency and magnitude. Frequency analysis methods also have been applied when the parameters (or the moments such as the mean and variance) of a given model (e.g., the Gumbel model) may vary with time (e.g., Strupczewski et al. 2001; Clarke 2002). In addition, the role that low-frequency components of the oceanic– atmospheric system (represented, for example, by large-scale oscillations such as ENSO, PDO, and AMO) have on extreme events such as floods has been recognized. These large-scale forcing factors have been shown to exert in-phase and out-of-phase oscillations in the magnitude of floods, mean flows, and droughts

Uncertainty of the Assumptions Required for Estimating the Regulatory Flood: Red River of the North

AbstractFederal guidelines specify the log-Pearson Type III (LP3) distribution as the basis for the estimation of the 100-year peak discharge that serves as the regulatory flood for floodplain management in the United States. The LP3 distribution has been shown to provide a reasonable and flexible model of flood risk. Use of the LP3 distribution involves a number of explicit assumptions about the annual maximum series that are often implicitly assumed but not shown directly to be satisfied in flood frequency analysis studies of individual stations. In this case study, the validity of these assumptions for the Red River of the North at Grand Forks gaging station is examined. None of the four examined assumptions are satisfied completely. The stationarity assumption is not met because the regional climate samples two separate climatic modes, the peak discharge time series is not a random and independent set of events, the precipitation—runoff relationships are not uniform over time, and the flood peaks resu...

Revealing the impact of forest exotic plantations on water yield in large scale watersheds in South-Central Chile

summary Land-use and forest cover change play important roles in socio-economic processes and have been linked with water supply and other ecosystem services in various regions of the world. Water yield from watersheds is a major ecosystem service for human activities but has been dramatically altered by landscape management superimposed on climatic variability and change. Many studies from different regions of the world have documented that in small watersheds ( 10,000 ha. In this paper, we examine the temporal variation of the residuals between best-fit precipitation–runoff relationships and instrumental streamflow records for two large watersheds (Purapel en Nirivilo, PNN and Cauquenes en el Arrayan, CQA) located in the Mediterranean-climate coastal range of South-Central Chile. In these watersheds, high resolution satellite imagery shows a decline in native forest cover from 52.3% to 14.2% for PPN and 36.1% to 8.1% in CQA, between 1975 and 2000. Conversely, in the same period the percentage area covered by forest plantations, mainly Pinus radiata, increased from 12% to 55% in PPN, and 4.7% to 42% in CQA. We observed a decreasing trend in summer runoff residuals regressed against annual precipitation in the same period, with slopes significantly different from zero for PPN (p = 0.035) and CQA (p = 0.008). We interpreted this pattern as an evidence of change in the hydrological regime in these watersheds as a consequence of forest cover and land-use changes. From a reanalysis of the observed data we estimate a decrease in runoff from 13.1 to 7.5 mm/summer for PPN and from 7.3 to 5 mm/summer for CQA, refer to the period 1991–2000 compared to 1981–1990. Multiple regression analyses of annual and seasonal flows show that besides precipitation, percentage-cover of forest plantations is a statistically significant predictor of summer flow with a partial negative correlation of �0.45 and � 0.44 for PPN and CQA, respectively, p< 0.05. This study clearly shows the important effect that landuse change can have on water yield and to our knowledge this is the first study documenting the decrease in summer runoff in a landscape where native forest cover has dramatically declined and forest exotic plantations have expanded. Similar methods could be used elsewhere to inform policy and decisionmaking regarding forest and land-use planning.

Effects of long-term drought on the hydrology and growth of a white pine plantation in the southern Appalachians

The southern Appalachians experienced record precipitation deficits for 4 consecutive years in the mid-1980s. We analyzed the impacts of the drought on the hydrology and stemwood growth of a 33-year-old white pine plantation. Increment cores and dendrometer bands indicated a significant reduction in basal area growth during the drought for all tree classes (dominant, codominant, and intermediate) and shifts in patterns of seasonal growth. There was little variation in pine foliage litterfall over the drought period, but substantial variation in other litterfall components (e.g. wood, cones, seeds, etc.) Precipitation-runoff ( P-RO) relationships indicated less variation in evapotranspiration ( ET) over the drought period than predicted by simulation modeling. The discrepancy between measured and modeled ET may be related to the importance of stored soil water to streamflow which dampens P-RO ET estimates. Regression analyses showed that growing season water potential explained as much as 61% of the variation in annual basal area growth. No significant relationships were established with climatic variables alone.

Originalarbeiten Isotopenhydrologische Untersuchugen – Arbeiten aus dem GSF-Institut für Radiohydrometrie

Environmental isotope contents labelling the water molecule or water ingredients arc particularly well suited for differentiating between flow processes of different time origins in ground- and surface water. The detectable lime intervals of such isotope hydrological investigations depend on the input function and on the half-life time of the applied nuclide. After a suvery on new instrumental and methodical developments in the GSF-Institut fur Radiohydrometric, examples are given for isotope hydrological investigations, such as the determination of accumulation on glaciers and icefields, the evaluation of precipitation-runoff relationships, bank filtration problems, and the age differentiation of deep groundwaters.