On the coupled geomorphological and ecohydrological organization of river basins

This paper examines the linkage between the drainage network and the patterns of soil water balance components determined by the organization of vegetation, soils and climate in a semiarid river basin. Research during the last 10 years has conclusively shown an increasing degree of organization and unifying principles behind the structure of the drainage network and the three-dimensional geometry of river basins. This cohesion exists despite the infinite variety of shapes and forms one observes in natural watersheds. What has been relatively unexplored in a quantitative and general manner is the question of whether or not the interaction of vegetation, soils, and climate also display a similar set of unifying characteristics among the very different patterns they presents in river basins. A recently formulated framework for the water balance at the daily level links the observed patterns of basin organization to the soil moisture dynamics. Using available geospatial data, we assign soil, climate, and vegetation properties across the basin and analyze the probabilistic characteristics of steady-state soil moisture distribution. We investigate the presence of organization through the analysis of the spatial patterns of the steady-state soil moisture distribution, as well as in the distribution of observed vegetation patterns, simulated vegetation dynamic water stress and hydrological fluxes such as transpiration. Here we show that the drainage network acts as a template for the organization of both vegetation and hydrological patterns, which exhibit self-affine characteristics in their distribution across the river basin. Our analyses suggest the existence of a balance between the large-scale determinants of vegetation pattern reflecting optimality in the response to water stress and the random small-scale patterns that arise from local factors and ecological legacies such as those caused by dispersal, disturbance, and founder effects.     

Hillslope‐scale probabilistic characterization of soil moisture dynamics and average water balance

Probabilistic water balance modelling provides a useful framework for investigating the interactions between soil, vegetation, and the atmosphere. It has been used to estimate temporal soil moisture dynamics and ecohydrological responses at a point. This study combines a nonlinear rainfall–runoff theory with probabilistic water balance model to represent varied source area runoff as a function of rainfall depth and a runoff coefficient at hillslope scale. Analytical solutions of the soil‐moisture probability density function and average water balance model are then developed. Based on a sensitivity analysis of soil moisture dynamics, we show that when varied source area runoff is incorporated, mean soil moisture is always lower and total runoff higher, compared with the original probabilistic water balance model. The increased runoff from the inclusion of varied source area runoff is mainly because of a reduction in leakage when the index of dryness is less than one and evapotranspiration when the index of dryness is greater than one. Inclusion of varied source area runoff in the model means that the actual evapotranspiration is limited by less available water (i.e. water limit), which is stricter than Budyko’s and Milly’s water limit. Application of the model to a catchment located in Western Australia showed that the method can predict annual value of actual evapotranspiration and streamflow accurately. Copyright © 2012 John Wiley & Sons, Ltd.     

The influence of soil properties on the formation of unstable vegetation patterns on hillsides of semiarid catchments

On hillsides of semiarid catchments regular bands of vegetation have been observed to form under low rainfall conditions. Many authors have observed the existence of a slope gradient threshold below which no banded patterns were observed; this increases with the mean annual rainfall. A simple model for soil moisture balance and vegetation growth, explicitly accounting for basic soil physics, is demonstrated and discussed. The influence of relevant soil characteristics on vegetation patterns and their patchiness is addressed by linear stability analysis. The results confirm the experimental evidence of a threshold slope gradient depending on the mean annual net water supply, and demonstrate the influence of the soil properties (saturated conductivity and capillary rise) on the stability condition and on the threshold slope. Nevertheless, the concluding remark concerns the oversimplified models for vegetation patterns, such as the one discussed here, that require properly defined effective soil parameters in order to become predictive tools.     

Ecohydrology of water-controlled ecosystems

Ecosystem dynamics in arid and semiarid climates are strongly dependent on the soil water availability which, in turn, is the result of a number of complex and mutually interacting hydrologic processes. This motivates the development of a process-based framework for the analysis of the soil water content in the root zone at the daily time scale. This paper reviews the results that the authors have obtained using a probabilistic–mechanistic model of soil water balance for the characterization of the seasonal regimes of soil moisture with different combinations of climate, soil, and vegetation. Average seasonal soil water content and level-crossing statistics have been used to study conditions of water stress in vegetation. The same framework has been applied to the analysis of the impact of interannual climate fluctuations on the seasonal regime of soil moisture and water stress.     

Modeling Water and Heat Balance Components for Large Agricultural Region Utilizing Information from Meteorological Satellites

The method has been developed to evaluate water and heat balance components for vegetation covered area of regional scale based on the refined physical-mathematical model of vertical water and heat exchange between land surface and atmosphere (Land Surface Model, LSM) for vegetation season adapted to satellite information on land surface and meteorological conditions. The LSM is accommodated for utilizing satellite-derived estimates of vegetation and meteorological characteristics as model parameters and input variables. Estimates of these characteristics presented as distributions of their values over the study area have been obtained from AVHRR/NOAA, MODIS/EOS Terra and Aqua, SEVIRI/Meteosat-9, -10 data. To build such estimates methods and technologies have been developed and refined using results of thematic processing measurement data from these sensors. Among them the original Multi Threshold Method (MTM) has been developed and tested to calculate daily precipitation sums using rainfall intensity estimates retrieved from AVHRR and SEVIRI data with subsequent replacement of ground-measured rainfall amounts by these daily rainfalls. All technologies have been adapted to the study area with square of 227300 km² being the part of the Central Black Earth Region of European Russia. Developed earlier procedures of utilizing satellitederived estimates of vegetation and meteorological characteristics (including precipitation) in the model have been refined and verified. Final result of modeling is the fields of soil water content, evapotranspiration and other water and heat balance components of the region under study for years 2012–2014 vegetation seasons.     

Significance of AIC differences for precipitation intensity distributions

Chain dependent models for daily precipitation typically model the occurrence process as a Markov chain and the precipitation intensity process using one of several probability distributions. It has been argued that the mixed exponential distribution is a superior model for the rainfall intensity process, since the value of its information criterion (Akaike information criterion or Bayesian information criterion) when fit to precipitation data is usually less than the more commonly used gamma distribution. The differences between the criterion values of the best and lesser models are generally small relative to the magnitude of the criterion value, which raises the question of whether these differences are statistically significant. Using a likelihood ratio statistic and nesting the gamma and mixed exponential distributions in a parent distribution, we show indirectly that generally the superiority of the mixed exponential distribution over the gamma distribution for modeling precipitation intensity is statistically significant. Comparisons are also made with a common-a gamma model, which are less informative.     

On the estimation of antecedent wetness conditions in rainfall–runoff modelling

The analysis of the physical processes involved in a conceptual model of soil water content balance is addressed with the objective of its application as a component of rainfall–runoff modelling. The model uses routinely measured meteorological variables (rainfall and air temperature) and incorporates a limited number of significant parameters. Its performance in estimating the soil moisture temporal pattern was tested through local measurements of volumetric water content carried out continuously on an experimental plot located in central Italy. The analysis was carried out for different periods in order to test both the representation of infiltration at the short time‐scale and drainage and evapotranspiration processes at the long time‐scale. A robust conceptual model was identified that incorporated the Green–Ampt approach for infiltration and a gravity‐driven approximation for drainage. A sensitivity analysis was performed for the selected model to assess the model robustness and to identify the more significant parameters involved in the principal processes that control the soil moisture temporal pattern. The usefulness of the selected model was tested for the estimation of the initial wetness conditions for rainfall–runoff modelling at the catchment scale. Specifically, the runoff characteristics (runoff depth and peak discharge) were found to be dependent on the pre‐event surface soil moisture. Both observed values and those estimated by the model gave good results. On the contrary, with the antecedent wetness conditions furnished by two versions of the antecedent precipitation index (API), large errors were obtained. Copyright © 2007 John Wiley & Sons, Ltd.     

Vegetation response to rainfall intermittency in drylands: Results from a simple ecohydrological box model

Vegetation in arid and semi-arid regions is affected by intermittent water availability. We discuss a simple stochastic model describing the coupled dynamics of soil moisture and vegetation, and study the effects of rainfall intermittency. Soil moisture dynamics is described by a ecohydrological box model, while vegetation is represented by site occupancy dynamics in a spatially-implicit model. We show that temporal rainfall intermittency allows for vegetation persistence at low values of annual rainfall volume, whereas it would go extinct if rainfall were constant. Rainfall intermittency also generates long-term fluctuations in vegetation cover, even in the absence of significant inter-annual variations in the statistical properties of precipitation.     

Year‐round estimation of soil moisture content using temporally variable soil hydraulic parameters

Soil moisture plays a key role in the hydrological cycle as it controls the flux of water between soil, vegetation, and atmosphere. This study is focused on a year‐round estimation of soil moisture in a forested mountain area using the bucket model approach. For this purpose, three different soil moisture models are utilised. The procedure is based on splitting the whole year into two complement periods (dormant and vegetation). Model parameters are allowed to vary between the two periods and also from year to year in the calibration procedure. Consequently, two sets of average model parameters corresponding to dormant and vegetation seasons are proposed. The process of splitting is strongly supported by the experimental data, and it enables us to variate saturated hydraulic conductivity and pore‐size characterisation. The use of the two different parameter sets significantly enhances the simulation of two (Teuling and Troch model and soil water balance model‐green–ampt [SWBM‐GA]) out of three models in the 6‐year period from 2009 to 2014. For these two models, the overall Nash‐Sutcliffe coefficient increased from 0.64 to 0.79 and from 0.55 to 0.80. The third model (the Laio approach) proved to be insensitive to parameter changes due to its insufficient drainage prediction. The variability of the warm and cold parameter sets between particular years is more pronounced in the warm periods. The cold periods exhibited approximately similar character during all 6 years.     

Soil water dynamics and water balance on a tropical coral island

Understanding soil water dynamics and the water balance of tropical coral islands is important for the utilization and management of their limited freshwater resources, which is only from rainfall. However, there is a significant knowledge gap in the influence of soil water on the water cycle of coral islands. Soil water dynamics and the water balance of Zhaoshu Island, Xisha Archipelago were thus investigated using soil moisture measurements and the Hydrus-1D model from October 2018 to September 2019. Over the study period, vegetation transpiration, soil evaporation, groundwater recharge and storage in the vadose zone were approximately 196, 330, 365 and 20 mm, occupying 22%, 36%, 40% and 2% of annual rainfall total (911 mm), respectively. For the wet season (from May to October) these values became 75, 202, 455 and 40 mm, occupying 10%, 26% and 59% and 5% of the seasonal rainfall total (772 mm), respectively. During the dry season (from November to April), a dry soil layer between 40 and 120 cm depth of the soil profile was identified that prevented water exchange between the upper soil layers and the groundwater resulting in the development of deep roots so that vegetation could extract groundwater to supplement their water requirements. Vegetation not only consumes all dry season rainfall (140 mm) but extracts water deeply from groundwater (90 mm) as well as from the vadose layer (20 mm). As such, the vegetation appears to be groundwater-dependent ecosystems. The research results aid us to better understand the process of water dynamics on coral islands and to protect coral island ecosystems.     

Soil moisture variability of root zone profiles within SMEX02 remote sensing footprints

Remote sensing of soil moisture effectively provides soil moisture at a large scale, but does not explain highly heterogeneous soil moisture characteristics within remote sensing footprints. In this study, field scale spatio-temporal variability of root zone soil moisture was analyzed. During the Soil Moisture Experiment 2002 (SMEX02), daily soil moisture profiles (i.e., 0–6, 5–11, 15–21, and 25–31 cm) were measured in two fields in Walnut Creek watershed, Ames, Iowa, USA. Theta probe measurements of the volumetric soil moisture profile data were used to analyze statistical moments and time stability and to validate soil moisture predicted by a simple physical model simulation. For all depths, the coefficient of variation of soil moisture is well explained by the mean soil moisture using an exponential relationship. The simple model simulated very similar variability patterns as those observed.As soil depth increases, soil moisture distributions shift from skewed to normal patterns. At the surface depth, the soil moisture during dry down is log-normally distributed, while the soil moisture is normally distributed after rainfall. At all depths below the surface, the normal distribution captures the soil moisture variability for all conditions. Time stability analyses show that spatial patterns of sampling points are preserved for all depths and that time stability of surface measurements is a good indicator of subsurface time stability. The most time stable sampling sites estimate the field average root zone soil moisture value within ±2.1% volumetric soil moisture.     

Multivariate analysis of soil moisture history for a hillslope

In this study, the spatial distribution of measured soil moisture was analyzed on the platform of multivariate modeling. Soil moisture time series for two seasons were selected and used for analysis to reveal similarities and differences in soil moisture responses for a few rainfall events. The development of a soil moisture transport process that considers the representative element volume and uncertainty of soil media provides the hydrological basis for time series modeling. The systematic procedure of Box–Jenkins with noise modeling was used to delineate the final models for all monitoring points. The physical basis of mass balance and the continuity in inflow contribution, as well as statistical criteria, were used in the model selection procedure. Heuristic approaches provide the spatial distribution of selected models along the transect of a hillside. Comparative analysis for two different depths and seasons provide an understanding of the variation in soil moisture transfer processes at the hillslope scale. Differences in soil moisture models for both depths and seasons are associated with eco-hydrological processes. The relationships between distributed topographic features and modeling results were explored to configure dominant hydrological processes for each season.     

Effects of differential hillslope‐scale water retention characteristics on rainfall–runoff response at the Landscape Evolution Observatory

Hillslopes turn precipitation into runoff and thus exert important controls on various Earth system processes. It remains difficult to collect reliable data necessary for understanding and modeling these Earth system processes in real catchments. To overcome this problem, controlled experiments are being conducted at the Landscape Evolution Observatory at Biosphere 2, The University of Arizona. Previous experiments have revealed differences in hydrological response between 2 landscapes within Landscape Evolution Observatory, even though both landscapes were designed to be identical. In an attempt to discover where the observed differences stem from, we use a fully 3‐dimensional hydrological model (CATchment HYdrology) to show the effect of soil water retention characteristics and saturated hydraulic conductivity on the hydrological response of these 2 hillslopes. We also show that soil water retention characteristics can be derived at hillslope scale from experimental observations of soil moisture and matric potential. It is found that differences in soil packing between the 2 landscapes may be responsible for the observed differences in hydrological response. This modeling study also suggests that soil water retention characteristics and saturated hydraulic conductivity have a profound effect on rainfall–runoff processes at hillslope scale and that parametrization of a single hillslope may be a promising step in modeling rainfall–runoff response in real catchments.     

Plants in water-controlled ecosystems: active role in hydrologic processes and response to water stress: II. Probabilistic soil moisture dynamics

A stochastic model for soil moisture dynamics at a point is studied in detail. Rainfall is described as a marked Poisson process, producing a state-dependent infiltration into the soil. Losses due to leakage and evapotranspiration also depend on the existing level of soil moisture through a simplifying but realistic representation of plant physiological characteristics and soil properties. The analytic solution of the steady-state probability distributions is investigated to assess the role of climate, soil, and vegetation in soil moisture dynamics and water balance.     

Modelling streamflow trends for a watershed with limited data: case of the Litani basin,Lebanon

Abstract

Streamflow variability in the Upper and Lower Litani basin, Lebanon was modelled as there is a lack of long-term measured runoff data. To simulate runoff and streamflow, daily rainfall was derived using a stochastic rainfall generation model and monthly rainfall data. Two distinct synthetic rainfall models were developed based on a two-part probabilistic distribution approach. The rainfall occurrence was described by a Markov chain process, while the rainfall distribution on wet days was represented by two different distributions (i.e. gamma and mixed exponential distributions). Both distributions yielded similar results. The rainfall data were then processed using water balance and routing models to generate daily and monthly streamflow. Compared with measured data, the model results were generally reasonable (mean errors ranging from 0.1 to 0.8?m³/s at select locations). Finally, the simulated monthly streamflow data were used to investigate discharge trends in the Litani basin during the 20th century using the Mann-Kendall and Sen slope nonparametric trend detection methods. A significant drying trend of the basin was detected, reaching a streamflow reduction of 0.8 and 0.7 m³/s per decade in January for the Upper and Lower basin, respectively.

Editor D. Koutsoyiannis; Associate editor Sheng Yue

Citation Ramadan, H.H., Beighley, R.E., and Ramamurthy, A.S., 2012. Modelling streamflow trends for a watershed with limited data: case of the Litani basin, Lebanon. Hydrological Sciences Journal, 57 (8), 1516–1529.     

Field studies on the influence of rainfall intensity,vegetation cover and slope length on soil moisture infiltration on typical watersheds of the Loess Plateau,China

Soil moisture is a key process in the hydrological cycle. During ecological restoration of the Loess Plateau, soil moisture status has undergone important changes, and infiltration of soil moisture during precipitation events is a key link affecting water distribution. Our study aims to quantify the effects of vegetation cover, rainfall intensity and slope length on total infiltration and the spatial variation of water flow. Infiltration data from the upper, middle and lower slopes of a bare slope, a natural grassland and an artificial shrub grassland were obtained using a simulated rainfall experiment. The angle of the study slope was 15° and rainfall intensity was set at 60, 90, 120, 150, and 180 mm/hr. The effect these factors have on soil moisture infiltration was quantified using main effect analysis. Our results indicate that the average infiltration depth (ID) of a bare slope, a grassland slope and an artificial shrub grassland slope was 46.7–73.3, 60–80, and 60–93.3 cm, respectively, and average soil moisture storage increment was 3.5–5.7, 5.0–9.4, and 5.7–10.2 mm under different rainfall intensities, respectively. Heavy rainfall intensity and vegetation cover reduced the difference of soil infiltration in the 0–40 cm soil layer, and rainfall intensity increased surface infiltration differences on the bare slope, the grassland slope and the artificial shrub grassland slope. Infiltration was dominated by rainfall intensity, accounting for 63.03–88.92%. As rainfall continued, the contribution of rainfall intensity to infiltration gradually decreased, and the contribution of vegetation cover and slope length to infiltration increased. The interactive contribution was: rainfall intensity * vegetation cover > vegetation cover * slope length > rainfall * slope length. In the grass and shrub grass slopes, lateral flow was found at a depth of 23–37 cm when the slope length was 5–10 m, this being related to the difference in soil infiltration capacity between different soil layers formed by the spatial cross-connection of roots.     

Evaluating the spatial distribution of water balance in a small watershed,Pennsylvania

A conceptual water‐balance model was modified from a point application to be distributed for evaluating the spatial distribution of watershed water balance based on daily precipitation, temperature and other hydrological parameters. The model was calibrated by comparing simulated daily variation in soil moisture with field observed data and results of another model that simulates the vertical soil moisture flow by numerically solving Richards' equation. The impacts of soil and land use on the hydrological components of the water balance, such as evapotranspiration, soil moisture deficit, runoff and subsurface drainage, were evaluated with the calibrated model in this study. Given the same meteorological conditions and land use, the soil moisture deficit, evapotranspiration and surface runoff increase, and subsurface drainage decreases, as the available water capacity of soil increases. Among various land uses, alfalfa produced high soil moisture deficit and evapotranspiration and lower surface runoff and subsurface drainage, whereas soybeans produced an opposite trend. The simulated distribution of various hydrological components shows the combined effect of soil and land use. Simulated hydrological components compare well with observed data. The study demonstrated that the distributed water balance approach is efficient and has advantages over the use of single average value of hydrological variables and the application at a single point in the traditional practice. Copyright © 2000 John Wiley & Sons, Ltd.     

A distributed monthly hydrological model for integrating spatial variations of basin topography and rainfall

Hydrological models at a monthly time‐scale are important tools for hydrological analysis, such as in impact assessment of climate change and regional water resources planning. Traditionally, monthly models adopt a conceptual, lumped‐parameter approach and cannot account for spatial variations of basin characteristics and climatic inputs. A large requirement for data often severely limits the utility of physically based, distributed‐parameter models. Based on the variable‐source‐area concept, we considered basin topography and rainfall to be two major factors whose spatial variations play a dominant role in runoff generation and developed a monthly model that is able to account for their influences in the spatial and temporal dynamics of water balance. As a hybrid of the Xinanjiang model and TOPMODEL, the new model is constructed by innovatively making use of the highly acclaimed simulation techniques in the two existing models. A major contribution of this model development study is to adopt the technique of implicit representation of soil moisture characteristics in the Xinanjiang model and use the TOPMODEL concept to integrate terrain variations into runoff simulation. Specifically, the TOPMODEL topographic index ln(a/tanβ) is converted into an index of relative difficulty in runoff generation (IRDG) and then the cumulative frequency distribution of IRDG is used to substitute the parabolic curve, which represents the spatial variation of soil storage capacity in the Xinanjiang model. Digital elevation model data play a key role in the modelling procedures on a geographical information system platform, including basin segmentation, estimation of rainfall for each sub‐basin and computation of terrain characteristics. Other monthly data for model calibration and validation are rainfall, pan evaporation and runoff. The new model has only three parameters to be estimated, i.e. watershed‐average field capacity WM, pan coefficient η and runoff generation coefficient α. Sensitivity analysis demonstrates that runoff is least sensitive to WM and, therefore, it can be determined by a prior estimation based on the climate and soil properties of the study basin. The other two parameters can be determined using optimization methods. Model testing was carried out in a number of nested sub‐basins of two watersheds (Yuanjiang River and Dongjiang River) in the humid region in central and southern China. Simulation results show that the model is capable of describing spatial and temporal variations of water balance components, including soil moisture content, evapotranspiration and runoff, over the watershed. With a minimal requirement for input data and parameterization, this terrain‐based distributed model is a valuable contribution to the ever‐advancing technology of hydrological modelling. Copyright © 2006 John Wiley & Sons, Ltd.     

The role of rainfall temporal and spatial averaging in seasonal simulations of the terrestrial water balance

The partitioning of rainfall into surface runoff and infiltration influences many other aspects of the hydrologic cycle including evapotranspiration, deep drainage and soil moisture. This partitioning is an instantaneous non-linear process that is strongly dependent on rainfall rate, soil moisture and soil hydraulic properties. Though all rainfall datasets involve some degree of spatial or temporal averaging, it is not understood how this averaging affects simulated partitioning and the land surface water balance across a wide range of soil and climate types. We used a one-dimensional physics-based model of the near-surface unsaturated zone to compare the effects of different rainfall discretization (5-min point-scale; hourly point-scale; hourly 0.125° gridded) on the simulated partitioning of rainfall for many locations across the United States. Coarser temporal resolution rainfall data underpredicted seasonal surface runoff for all soil types except those with very high infiltration capacities (i.e., sand, loamy sand). Soils with intermediate infiltration capacities (i.e., loam, sandy loam) were the most affected, with less than half of the expected surface runoff produced in most soil types when the gridded rainfall dataset was used as input. The impact of averaging on the water balance was less extreme but non-negligible, with the hourly point-scale predictions exhibiting median evapotranspiration, drainage and soil moisture values within 10% of those predicted using the higher resolution 5-min rainfall. Water balance impacts were greater using the gridded hourly dataset, with average underpredictions of ET up to 27% in fine-grained soils. The results suggest that “hyperresolution” modelling at continental to global scales may produce inaccurate predictions if there is not parallel effort to produce higher resolution precipitation inputs or sub-grid precipitation parameterizations.