•Reasons for use of distributed process-based hydrological models are reviewed.•Avenues for developments of process-based hydrological models are presented.•Hydrology will depend on appropriate use ...of process-based models.
Process-based hydrological models have a long history dating back to the 1960s. Criticized by some as over-parameterized, overly complex, and difficult to use, a more nuanced view is that these tools are necessary in many situations and, in a certain class of problems, they are the most appropriate type of hydrological model. This is especially the case in situations where knowledge of flow paths or distributed state variables and/or preservation of physical constraints is important. Examples of this include: spatiotemporal variability of soil moisture, groundwater flow and runoff generation, sediment and contaminant transport, or when feedbacks among various Earth’s system processes or understanding the impacts of climate non-stationarity are of primary concern. These are situations where process-based models excel and other models are unverifiable. This article presents this pragmatic view in the context of existing literature to justify the approach where applicable and necessary. We review how improvements in data availability, computational resources and algorithms have made detailed hydrological simulations a reality. Avenues for the future of process-based hydrological models are presented suggesting their use as virtual laboratories, for design purposes, and with a powerful treatment of uncertainty.
•The seasonal distributions of daily rainfall extremes are different.•A hybrid model mixing the seasonal distributions can represent the annual one.•Orography controls the mean of the distribution of ...daily rainfall extremes.
This study uses daily rainfall records of a dense network of 240 gauges in central Arizona to gain insights on (i) the variability of the seasonal distributions of rainfall extremes; (ii) how the seasonal distributions affect the shape of the annual distribution; and (iii) the presence of spatial patterns and orographic control for these distributions. For this aim, recent methodological advancements in peak-over-threshold analysis and application of the Generalized Pareto Distribution (GPD) were used to assess the suitability of the GPD hypothesis and improve the estimation of its parameters, while limiting the effect of short sample sizes. The distribution of daily rainfall extremes was found to be heavy-tailed (i.e., GPD shape parameter ξ > 0) during the summer season, dominated by convective monsoonal thunderstorms. The exponential distribution (a special case of GPD with ξ = 0) was instead showed to be appropriate for modeling wintertime daily rainfall extremes, mainly caused by cold fronts transported by westerly flow. The annual distribution exhibited a mixed behavior, with lighter upper tails than those found in summer. A hybrid model mixing the two seasonal distributions was demonstrated capable of reproducing the annual distribution. Organized spatial patterns, mainly controlled by elevation, were observed for the GPD scale parameter, while ξ did not show any clear control of location or orography. The quantiles returned by the GPD were found to be very similar to those provided by the National Oceanic and Atmospheric Administration (NOAA) Atlas 14, which used the Generalized Extreme Value (GEV) distribution. Results of this work are useful to improve statistical modeling of daily rainfall extremes at high spatial resolution and provide diagnostic tools for assessing the ability of climate models to simulate extreme events.
► We discuss the process of evaluating performances of a simulation and/or prediction hydrological model. ► We briefly review the validation procedures that are frequently used in hydrology. ► A ...distinction between scientific validation and performance validation is considered. ► We propose guidelines for model validation based on SWOT analysis.
In this paper, we discuss validation of hydrological models, namely the process of evaluating performance of a simulation and/or prediction model. We briefly review the validation procedures that are frequently used in hydrology making a distinction between scientific validation and performance validation. Finally, we propose guidelines for carrying out model validation with the aim of providing agreed methodologies to efficiently assess model peculiarities and limitations, and to quantify simulation performance.
Understanding the food-energy-water nexus is necessary to identify risks and inform strategies for nexus governance to support resilient, secure, and sustainable societies. To manage risks and ...realize efficiencies, we must understand not only how these systems are physically connected but also how they are institutionally linked. It is important to understand how actors who make planning, management, and policy decisions understand the relationships among components of the systems. Our question is: How do stakeholders involved in food, energy, and water governance in Phoenix, Arizona understand the nexus and what are the implications for integrated nexus governance? We employ a case study design, generate qualitative data through focus groups and interviews, and conduct a content analysis. While stakeholders in the Phoenix area who are actively engaged in food, energy, and water systems governance appreciate the rationale for nexus thinking, they recognize practical limitations to implementing these concepts. Concept maps of nexus interactions provide one view of system interconnections that be used to complement other ways of knowing the nexus, such as physical infrastructure system diagrams or actor-networks. Stakeholders believe nexus governance could be improved through awareness and education, consensus and collaboration, transparency, economic incentives, working across scales, and incremental reforms.
Intensity–duration–frequency (IDF) analyses of rainfall extremes provide critical information to mitigate, manage, and adapt to urban flooding. The accuracy and uncertainty of IDF analyses depend on ...the availability of historical rainfall records, which are more accessible at daily resolution and, quite often, are very sparse in developing countries. In this work, we quantify performances of different IDF models as a function of the number of available high-resolution (N
τ) and daily (N24h) rain gauges. For this aim, we apply a cross-validation framework that is based on Monte Carlo bootstrapping experiments on records of 223 high-resolution gauges in central Arizona. We test five IDF models based on (two) local, (one) regional, and (two) scaling frequency analyses of annual rainfall maxima from 30-min to 24-h durations with the generalized extreme value (GEV) distribution. All models exhibit similar performances in simulating observed quantiles associated with return periods up to 30 years. When N
τ>10, local and regional models have the best accuracy; bias correcting the GEV shape parameter for record length is recommended to estimate quantiles for large return periods. The uncertainty of all models, evaluated via Monte Carlo experiments, is very large when N
τ ≤ 5; however, if N24h ≥ 10 additional daily gauges are available, the uncertainty is greatly reduced and accuracy is increased by applying simple scaling models, which infer estimates on subdaily rainfall statistics from information at daily scale. For all models, performances depend on the ability to capture the elevation control on their parameters. Although our work is site specific, its results provide insights to conduct future IDF analyses, especially in regions with sparse data.
Two-sample tests are widely used in hydrologic and climate studies to investigate whether two samples of a variable of interest could be considered drawn from different populations. Despite this, the ...information on the power (i.e., the probability of correctly rejecting the null hypothesis) of these tests applied to hydroclimatic variables is limited. Here, this need is addressed considering four popular two-sample tests applied to daily and extreme precipitation, and annual peak flow series. The chosen tests assess differences in location (t-Student and Wilcoxon) and distribution (Kolmogorov–Smirnov and likelihood-ratio). The power was quantified through Monte Carlo simulations relying on pairs of realistic samples of the three variables with equal size, generated with a procedure based on suitable parametric distributions and copulas. After showing that differences in sample skewness are monotonically related to differences in spread, power surfaces were built as a function of the relative changes in location and spread of the samples and utilized to interpret three case studies comparing samples of observed precipitation and discharge series in the U.S. It was found that (1) the t-Student applied to the log-transformed samples has the same power as the Wilcoxon test; (2) location (distribution) tests perform better than distribution (location) tests for small (moderate-to-large) differences in spread and skewness; (3) the power is relatively lower (higher) if the differences in location and spread or skewness have concordant (discordant) sign; and (4) the power increases with the sample size but could be quite low for tests applied to extreme precipitation and discharge records that are commonly short. This work provides useful recommendations for selecting and interpreting two-sample tests in a broad range of hydroclimatic applications.
The statistical properties of the rainfall regime in central Arizona are investigated using observations from the early 1980s of the Flood Control District of Maricopa County (FCDMC) network, ...currently consisting of 310 gauges ranging in elevation from 220 to 2325 m MSL. A set of techniques is applied to analyze the properties across a wide range of temporal scales (from 1 min to years) and the associated spatial variability. Rainfall accumulation is characterized by (i) high interannual variability, which is partially explained by teleconnections with El Niño–Southern Oscillation; (ii) marked seasonality, with two distinct maxima in summer (July–September) and winter (November–March); (iii) significant orographic control; and (iv) strong diurnal cycle in summer, peaking in early afternoon at higher elevations and at nighttime in lower desert areas. The annual maximum rainfall intensities occur in the summer months and increase with elevation, suggesting that higher terrain enhances the strength of thermal convective activity. The intergauge correlation of wintertime rainfall is high even at short aggregation times (<1 h) because of the widespread nature of the weather systems, while summer monsoonal thunderstorms are more localized in space and time. Spectral and scale invariance analyses show the presence of different scaling regimes in summer and winter, which are related to the typical meteorological phenomena of the corresponding time scales (frontal systems and isolated convective cells). Results of this work expand previous studies on the dominant meteorological features in the region and support the development of rainfall downscaling models from coarse products of climate, meteorological, or other statistical models.
The linkages between land and water use are often neglected when considering resource management. Here, we examined regional changes in land and water use along the US-Mexico border in the decades ...following the North American Free Trade Agreement, using bi-national land cover maps from 1992-2011, a process-based hydrology and irrigation model driven with long-term meteorological data, and agricultural production and urban water demand statistics. During the study period, land and water use in the region partially re-oriented around the needs of US cities, leading to crop to urban conversions and water savings in the US, while agricultural and urban expansion in Mexico resulted in local aquifer exploitation and reduced river flows. We identified that land uses with lower rates of water consumption (urban in US and agriculture in Mexico) expanded more than those with higher demands (irrigated agriculture in US and urban in Mexico) due to the water scarcity in the region. This resulted in divergent trends in the US and Mexico that in aggregate has led to an unsustainable trajectory in land and water resources.
Soil moisture control on evapotranspiration is poorly understood in ecosystems experiencing seasonal greening. In this study, we utilize a set of multi-year observations at four eddy covariance sites ...along a latitudinal gradient in vegetation greening to infer the ET- relation during the North American monsoon. Results reveal significant seasonal, interannual and ecosystem variations in the observed ET- relation directly linked to vegetation greening. In particular, monsoon-dominated ecosystems adjust their ET- relation, through changes in unstressed ET and plant stress threshold, to cope with differences in water availability. Comparisons of the observed relations to the North American Regional Reanalysis dataset reveal large biases that increase where vegetation greening is more significant. The analysis presented here can be used to guide improvements in land surface model parameterization in water-limited ecosystems.
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