Abstract. Nonlinear relations between rain input and hillslope outflow are common observations in hillslope hydrology field studies. In this paper we use percolation theory to model the threshold relationship between rainfall amount and outflow and show that this nonlinear relationship may arise from simple linear processes at the smaller scale. When the rainfall amount exceeds a threshold value, the underlying elements become connected and water flows out of the base of the hillslope. The percolation approach shows how random variations in storage capacity and connectivity at the small spatial scale cause a threshold relationship between rainstorm amount and hillslope outflow.As a test case, we applied percolation theory to the well characterized experimental hillslope at the Panola Mountain Research Watershed. Analysing the measured rainstorm events and the subsurface stormflow with percolation theory, we could determine the effect of bedrock permeability, spatial distribution of soil properties and initial water content within the hillslope. The measured variation in the relationship between rainstorm amount and subsurface flow could be reproduced by modelling the initial moisture deficit, the loss of free water to the bedrock, the limited size of the system and the connectivity that is a function of bedrock topography and existence of macropores. The values of the model parameters were in agreement with measured values of soil depth distribution and water saturation.
Assisted colonization—the deliberate translocation of species from unsuitable to suitable regions—is a controversial management tool that aims to prevent the extinction of populations that are unable to migrate in response to climate change or to survive in situ. The identification of suitable translocation sites is therefore a pressing issue. Correlative species distribution models, which are based on occurrence data, are of limited use for site selection for species with historically restricted distributions. In contrast, mechanistic species distribution models hold considerable promise in selecting translocation sites. Here we integrate ecoenergetic and hydrological models to assess the longer-term suitability of the current habitat of one of the world’s rarest chelonians, the Critically Endangered Western Swamp Tortoise (Psuedemydura umbrina). Our coupled model allows us to understand the interaction between thermal and hydric constraints on the foraging window of tortoises, based on hydrological projections of its current habitat. The process can then be repeated across a range of future climates to identify regions that would fall within the tortoise’s thermodynamic niche. The predictions indicate that climate change will result in reduced hydroperiods for the tortoises. However, under some climate change scenarios, habitat suitability may remain stable or even improve due to increases in the heat budget. We discuss how our predictions can be integrated with energy budget models that can capture the consequences of these biophysical constraints on growth, reproduction and body condition.
[1] Temporal patterns of solute transport and transformation through the vadose zone are driven by the stochastic variability of water fluxes. This is determined by the hydrologic filtering of precipitation variability into infiltration, storage, drainage, and evapotranspiration. In this work we develop a framework for examining the role of the hydrologic filtering and, in particular, the effect of evapotranspiration in determining the travel time and delivery of sorbing, reacting solutes transported through the vadose zone by stochastic rainfall events. We describe a 1-D vertical model in which solute pulses are tracked as point loads transported to depth by a series of discrete infiltration events. Numerical solutions of this model compare well to the Richards equation-based HYDRUS model for some typical cases. We then utilize existing theory of the stochastic dynamics of soil water to derive analytical and semianalytical expressions for the probability density functions (pdf's) of solute travel time and delivery. The moments of these pdf's directly relate the mean and variance of expected travel times to the water balance and show how evapotranspiration tends to reduce (and make more uncertain) the mass of a degrading solute delivered to the base of the vadose zone. The framework suggests a classification of different modes hydrologic filtering depending on hydroclimatic and landscape controls. Results suggest that variability in travel times decreases with soil depth in wet climates but increases with soil depth in dry climates. In dry climates, rare large storms can be an important mechanism for leaching to groundwater.
Abstract. The episodic nature of hydrological flows such as surface runoff and preferential flow is a result of the nonlinearity of their triggering and the intermittency of rainfall. In this paper we examine the temporal dynamics of threshold processes that are triggered by either an infiltration excess (IE) mechanism when rainfall intensity exceeds a specified threshold value, or a saturation excess (SE) mechanism governed by a storage threshold. We use existing and newly derived analytical results to describe probabilistic measures of the time between successive events in each case, and in the case of the SE triggering, we relate the statistics of the time between events (the inter-event time, denoted IET) to the statistics of storage and the underlying water balance. In the case of the IE mechanism, the temporal dynamics of flow events is found to be simply scaled statistics of rainfall timing. In the case of the SE mechanism the time between events becomes structured. With increasing climate aridity the mean and the variance of the time between SE events increases but temporal clustering, as measured by the coefficient of variation (CV) of the IET, reaches a maximum in deep stores when the climatic aridity index equals 1. In very humid and also very arid climates, the temporal clustering disappears, and the pattern of triggering is similar to that seen for the IE mechanism. In addition we show that the mean and variance of the magnitude of SE events decreases but the CV increases with increasing aridity. The CV of IETs is found to be approximately equal to the CV of the magnitude of SE events per storm only in very humid climates with the CV of event magnitude tending to be much larger than the CV of IETs in arid climates. In comparison to storage the maximum temporal clustering was found to be associated with a maximum in the variance of soil moisture. The CV of the time till the first saturation excess event was found to be greatest when the initial storage was at the threshold.
[1] In terrestrial systems limited by water availability the spatial distribution of vegetation can self-organize into a mosaic of vegetated patches and bare soil. Spatially extensive competition for water and short-range facilitation underpin many models that describe the process of vegetation pattern formation. Earlier studies investigating this self-organized patchiness have largely considered smooth landscapes. However, topographic variations can significantly alter the redistribution of surface water flow and therefore the pattern-forming process. Here, we consider how microtopographic variations, at the scale of individual plants, alters self-organized vegetation patterns with the use of a simple ecohydrological model. We show that increasing microtopography can induce a change from banded vegetation, oriented across the slope, to irregular drainage patterns, oriented in the downslope direction. The mechanism responsible is shown to be a change in the spatial redistribution of infiltration around plants and plant patches. Only small increases in microtopography are required to cause banded systems with weak facilitation to change to downslope-oriented patterns. When non-periodic boundary conditions were considered, band orientation tended to become oblique to the topographic contour and in some circumstances their migration upslope ceased. These results suggest that diffusive sediment transport processes may be essential for the maintenance of regular periodic vegetation patterns, which implies that erosion may be critical for understanding the susceptibility of these ecosystems to catastrophic shifts.
[1] How can leaching risk be assessed if the chemical flux and/or the toxicity is highly uncertain? For many strongly sorbing pesticides it is known that their transport through the unsaturated zone occurs intermittently through preferential flow, triggered by significant rainfall events. In these circumstances the timing and frequency of these rainfall events may allow quantification of leaching risk to overcome the limitations of flux prediction. In this paper we analyze the leaching behavior of bromide and two herbicides, methabenzthiazuron and ethidimuron, using data from twelve uncropped lysimeters, with high-resolution climate data, in order to identify the rainfall controls on rapid solute leaching. A regression tree analysis suggested that a coarse-scale fortnightly to monthly water balance was a good predictor of short-term increases in drainage and bromide transport. Significant short-term herbicide leaching, however, was better predicted by the occurrence of a single storm with a depth greater than a 19 mm threshold. Sampling periods where rain events exceeded this threshold accounted for between 38% and 56% of the total mass of herbicides leached during the experiment. The same threshold only accounted for between 1% and 10% of the total mass of bromide leached. On the basis of these results, we conclude that in this system, the leaching risks of strongly sorbing chemicals can be quantified by the timing and frequency of these large rainfall events. Empirical and modeling approaches are suggested to apply this frequentist approach to leaching risk assessment to other soil-climate systems.
We investigated the scaling and topology of engineered urban drainage networks (UDNs) in two cities, and further examined UDN evolution over decades. UDN scaling was analyzed using two power law scaling characteristics widely employed for river networks: (1) Hack's law of length (L)‐area (A) [ L∝Ah] and (2) exceedance probability distribution of upstream contributing area (δ) [ P(A≥δ)∼aδ−ɛ]. For the smallest UDNs (<2 km2), length‐area scales linearly (h ∼ 1), but power law scaling (h ∼ 0.6) emerges as the UDNs grow. While P(A≥δ) plots for river networks are abruptly truncated, those for UDNs display exponential tempering [ P(A≥δ)=aδ−ɛexp(−cδ)]. The tempering parameter c decreases as the UDNs grow, implying that the distribution evolves in time to resemble those for river networks. However, the power law exponent ɛ for large UDNs tends to be greater than the range reported for river networks. Differences in generative processes and engineering design constraints contribute to observed differences in the evolution of UDNs and river networks, including subnet heterogeneity and nonrandom branching.
The Big Dry, a recent drought over southeast Australia, began around 1997 and continued until 2011. We show that between 2002–2010, instead of a localized drought, there was a continent‐wide reduction in water storage, vegetation and rainfall, spanning the northwest to the southeast of Australia. Trends in water storage and vegetation were assessed using Gravity Recovery and Climate Experiment (GRACE) and Normalized Difference Vegetation Index (NDVI) data. Water storage and NDVI are shown to be significantly correlated across the continent and the greatest losses of water storage occurred over northwest Australia. The frequency of tropical cyclones over northwest Australia peaked just prior to the launch of the GRACE mission in 2002. Indeed, since 1981, decade‐scale fluctuations in tropical cyclone numbers coincide with similar variation in rainfall and vegetation over northwest Australia. Rainfall and vegetation in southeast Australia trended oppositely to the northwest prior to 2001. Despite differences between the northwest and southeast droughts, there is reason to believe that continental droughts may occur when the respective climate drivers align.
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