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.     

Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.     

On the prediction of the Toce alpine basin floods with distributed hydrologic models

With the objective of improving flood predictions, in recent years sophisticated continuous hydrologic models that include complex land‐surface sub‐models have been developed. This has produced a significant increase in parameterization; consequently, applications of distributed models to ungauged basins lacking specific data from field campaigns may become redundant. The objective of this paper is to produce a parsimonious and robust distributed hydrologic model for flood predictions in Italian alpine basins. Application is made to the Toce basin (area 1534 km²). The Toce basin was a case study of the RAPHAEL European Union research project, during which a comprehensive set of hydrologic, meteorological and physiographic data were collected, including the hydrologic analysis of the 1996–1997 period. Two major floods occurred during this period. We compare the FEST04 event model (which computes rainfall abstraction and antecedent soil moisture conditions through the simple Soil Conservation Service curve number method) and two continuous hydrologic models, SDM and TDM (which differ in soil water balance scheme, and base flow and runoff generation computations). The simple FEST04 event model demonstrated good performance in the prediction of the 1997 flood, but shows limits in the prediction of the long and moderate 1996 flood. More robust predictions are obtained with the parsimonious SDM continuous hydrologic model, which uses a simple one‐layer soil water balance model and an infiltration excess mechanism for runoff generation, and demonstrates good performance in both long‐term runoff modelling and flood predictions. Instead, the use of a more sophisticated continuous hydrologic model, the TDM, that simulates soil moisture dynamics in two layers of soil, and computes runoff and base flow using some TOPMODEL concepts, does not seem to be advantageous for this alpine basin. Copyright © 2006 John Wiley & Sons, Ltd.     

The value of remotely sensed surface soil moisture for model calibration using SWAT

Remotely sensed (RS) data can add value to a hydrological model calibration. Among this, RS soil moisture (SM) data have mostly been assimilated into conceptual hydrological models using various transformed variable or indices. In this study, raw RS surface SM is used as a calibration variable in the Soil and Water Assessment Tool model. This means the SM values were not transformed into another variable (e.g., soil water index and root zone SM index). Using a nested catchment, calibration based only on RS SM and optimizing model parameters sensitive to SM using particle swarm optimization improved variations in streamflow predictions at some of the gauging stations compared to the uncalibrated model. This highlighted part of the catchments where the SM signal directly influenced the flow distribution. Additionally, highlighted high and low flow signals were mostly influenced. The seasonal breakdown indicates that the SM signal is more useful for calibrating in wetter seasons and in areas with higher variations in elevation. The results identified that calibration only on RS SM improved the general rainfall–runoff response simulation by introducing delays but cannot correct the overall routing effect. Furthermore, catchment characteristics (e.g., land use, elevation, soil types, and precipitation) regulating SM variation in different seasons highlighted by the model calibration are identified. This provides further opportunities to improve model parameterization.     

Towards estimation of extreme floods: examination of the roles of runoff process changes and floodplain flows

This paper presents the development and application of a distributed rainfall-runoff model for extreme flood estimation, and its use to investigate potential changes in runoff processes, including changes to the ‘rating curve’ due to effects of over-bank flows, during the transition from ‘normal’ floods to ‘extreme’ floods. The model has two components: a hillslope runoff generation model based on a configuration of soil moisture stores in parallel and series, and a distributed flood routing model based on non-linear storage-discharge relationships for individual river reaches that includes the effects of floodplain geometries and roughnesses. The hillslope water balance model contains a number of parameters, which are measured or derived a priori from climate, soil and vegetation data or streamflow recession analyses. For reliable estimation of extreme discharges that may extend beyond recorded data, the parameters of the flood routing model are estimated from hydraulic properties, topographic data and vegetation cover of compound channels (main channel and floodplains). This includes the effects of the interactions between the main channel and floodplain sections, which tend to cause a change to the rating curve. The model is applied to the Collie River Basin, 2545 km², in Western Australia and used to estimate the probable maximum flood (PMF) from probable maximum precipitation estimates for this region. When moving from normal floods to the PMFs, application of the model demonstrates that the runoff generation process changes with a substantial increase of saturation excess overland flow through the expansion of saturated areas, and the dominant runoff process in the stream channel changes from in-bank to over-bank flows. The effects of floodplain inundation and floodplain vegetation can significantly reduce the magnitude of the estimated PMFs. This study has highlighted the need for the estimation of a number of critical parameters (e.g. cross-sectional geometry, floodplain vegetation, soil depths) through concerted field measurements or surveys, and targeted laboratory experiments.     

Sequential assimilation of soil moisture and streamflow data in a conceptual rainfall–runoff model

Soil moisture is a key hydrological variable in flood forecasting: it largely influences the partition of rain between runoff and infiltration and thus controls the flow at the outlet of a catchment. The methodology developed in this paper aims at improving the commonly used hydrological tools in an operational forecasting context by introducing soil moisture data into streamflow modelling. A sequential assimilation procedure, based on an extended Kalman filter, is developed and coupled with a lumped conceptual rainfall–runoff model. It updates the internal states of the model (soil and routing reservoirs) by assimilating daily soil moisture and streamflow data in order to better fit these external observations. We present in this paper the results obtained on the Serein, a Seine sub-catchment (France), during a period of about 2 years and using Time Domain Reflectivity probe soil moisture measurements from 0–10 to 0–100 cm and stream gauged data. Streamflow prediction is improved by assimilation of both soil moisture and streamflow individually and by coupled assimilation. Assimilation of soil moisture data is particularly effective during flood events while assimilation of streamflow data is more effective for low flows. Combined assimilation is therefore more adequate on the entire forecasting period. Finally, we discuss the adequacy of this methodology coupled with Remote Sensing data.     

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.     

DTM resolution controls the accuracy of estimating surface runoff indicators in flat,lowland landscapes

Surface runoff plays an important role in contaminant transport, nutrient loss, soil erosion and peak discharges in streams and rivers. Because it is the result of a variety of complex hydrological processes, estimating surface runoff using physically based hydrological models is challenging. Upscaling of physical soil properties is necessary to cope with the limits of computational power in surface runoff modelling. In flat landscapes, the (micro)topographic surface controls the onset and progression of surface runoff on saturated soils during rain events. Therefore, its proper representation is crucial when attempting to model and predict surface runoff. In this study, the influence of microtopography (centimetre scale) on estimations of maximum depression storage (MDS), random roughness (RR) and the connectivity threshold (CT) is explored. These properties are selected because they often serve as surface runoff indicators in hydrological modelling. To characterize microtopography, a terrestrial laser scanner (TLS) is used to generate a digital terrain model (DTM) of the study site with a horizontal spatial resolution of 5 cm. MDS, RR and CT are then calculated and compared to the values generated from the publicly available Dutch national DTM dataset with a resolution of 50 cm. Our results show considerable differences in MDS, RR and CT when calculated for the different input resolution datasets. Using DTMs that do not sufficiently capture microtopography leads to underestimation of MDS and RR, and to overestimation of CT. Our findings indicate that surface runoff indicators, and thereby the surface runoff response of a saturated surface to rainfall events, are defined at scales smaller than the scales of typically available DTMs. Understanding surface runoff through modelling studies therefore requires a framework that accounts for this lack of information arising from using coarser resolution DTMs. We demonstrate a linear relationship between MDS values generated from the different resolution DTMs. This opens the possibility of using empirical scaling relationships between high- and lower-resolution DTMs to account for microtopography. Repetition of our measurements on similar surfaces would contribute to establishing such empirical scaling relationships. Our results should be seen as indicative of flat landscapes and surfaces where centimetre scale microtopography is relevant.     

Evaluation of the soil water balance in an alluvial flood plain with a shallow groundwater table

Abstract

Many of the hydrological and ecological functions of alluvial flood plains within watersheds depend on the water flow exchanges between the vadoze soil zone and the shallow groundwater. The water balance of the soil in the flood plain is investigated, in order to evaluate the main hydrological processes that underlie the temporal dynamics of soil moisture and groundwater levels. The soil moisture and the groundwater level in the flood plain were monitored continuously for a three-year period. These data were integrated with the results derived from applying a physically-based numerical model which simulated the variably-saturated vertical water flow in the soil. The analysis indicated that the simultaneous processes of lateral groundwater flow and the vertical recharge from the unsaturated zone caused the observed water table fluctuations. The importance of these flows in determining the rises in the water table varied, depending on soil moisture and groundwater depth before precipitation. The monitoring period included two hydrological years (September 2009–September 2011). About 13% of the precipitation vertically recharged the groundwater in the first year and about 50% in the second. The difference in the two recharge coefficients was in part due to the lower groundwater levels in the recharge season of the first hydrological year, compared to those observed in the second. In the latter year, the shallow groundwater increased the soil moisture in the unsaturated zone due to capillary rise, and so the mean hydraulic conductivity of the unsaturated soil was high. This moisture state of soil favoured a more efficient conversion of infiltrated precipitation into vertical groundwater recharge. The results show that groundwater dynamics in the flood plain are an important source of temporal variability in soil moisture and vertical recharge processes, and this variability must be properly taken into account when the water balance is investigated in shallow groundwater environments.

Citation Pirastru, M. and Niedda, M., 2013. Evaluation of the soil water balance in an alluvial flood plain with a shallow groundwater table. Hydrological Sciences Journal, 58 (4), 898–911.     

Development and application of a spatially‐distributed Arctic hydrological and thermal process model (ARHYTHM)

A process‐based, spatially distributed hydrological model was developed to quantitatively simulate the energy and mass transfer processes and their interactions within arctic regions (arctic hydrological and thermal model, ARHYTHM). The model first determines the flow direction in each element, the channel drainage network and the drainage area based upon the digital elevation data. Then it simulates various physical processes: including snow ablation, subsurface flow, overland flow and channel flow routing, soil thawing and evapotranspiration. The kinematic wave method is used for conducting overland flow and channel flow routing. The subsurface flow is simulated using the Darcian approach. The energy balance scheme was the primary approach used in energy‐related process simulations (snowmelt and evapotranspiration), although there are options to model snowmelt by the degree‐day method and evapotranspiration by the Priestley–Taylor equation. This hydrological model simulates the dynamic interactions of each of these processes and can predict spatially distributed snowmelt, soil moisture and evapotranspiration over a watershed at each time step as well as discharge in any specified channel(s). The model was applied to Imnavait watershed (about 2·2 km²) and the Upper Kuparuk River basin (about 146 km²) in northern Alaska. Simulated results of spatially distributed soil moisture content, discharge at gauging stations, snowpack ablations curves and other results yield reasonable agreement, both spatially and temporally, with available data sets such as SAR imagery‐generated soil moisture data and field measurements of snowpack ablation, and discharge data at selected points. The initial timing of simulated discharge does not compare well with the measured data during snowmelt periods mainly because the effect of snow damming on runoff was not considered in the model. Results from the application of this model demonstrate that spatially distributed models have the potential for improving our understanding of hydrology for certain settings. Finally, a critical component that led to the performance of this modelling is the coupling of the mass and energy processes. Copyright © 2000 John Wiley & Sons, Ltd.     

Capabilities and limitations of detailed hillslope hydrological modelling

Hillslope hydrological modelling is considered to be of great importance for the understanding and quantification of hydrological processes in hilly or mountainous landscapes. In recent years a few comprehensive hydrological models have been developed at the hillslope scale which have resulted in an advanced representation of hillslope hydrological processes (including their interactions), and in some operational applications, such as in runoff and erosion studies at the field scale or lateral flow simulation in environmental and geotechnical engineering. An overview of the objectives of hillslope hydrological modelling is given, followed by a brief introduction of an exemplary comprehensive hillslope model, which stimulates a series of hydrological processes such as interception, evapotranspiration, infiltration into the soil matrix and into macropores, lateral and vertical subsurface soil water flow both in the matrix and preferential flow paths, surface runoff and channel discharge. Several examples of this model are presented and discussed in order to determine the model's capabilities and limitations. Finally, conclusions about the limitations of detailed hillslope modelling are drawn and an outlook on the future prospects of hydrological models on the hillslope scale is given.The model presented performed reasonable calculations of Hortonian surface runoff and subsequent erosion processes, given detailed information of initial soil water content and soil hydraulic conditions. The vertical and lateral soil moisture dynamics were also represented quite well. However, the given examples of model applications show that quite detailed climatic and soil data are required to obtain satisfactory results. The limitations of detailed hillslope hydrological modelling arise from different points: difficulties in the representations of certain processes (e.g. surface crusting, unsaturated–saturated soil moisture flow, macropore flow), problems of small‐scale variability, a general scarcity of detailed soil data, incomplete process parametrization and problems with the interdependent linkage of several hillslopes and channel–hillslope interactions. Copyright © 1999 John Wiley & Sons, Ltd.     

Evaluating explicit and implicit routing for watershed hydro‐ecological models of forest hydrology at the small catchment scale

This paper explores the behaviour and sensitivity of a watershed model used for simulating lateral soil water redistribution and runoff production. In applications such as modelling the effects of land‐use change in small headwater catchments, interactions between soil moisture, runoff and ecological processes are important. Because climate, soil and canopy characteristics are spatially variable, both the pattern of soil moisture and the associated outflow must be represented in modelling these processes. This study compares implicit and explicit routing approaches to modelling the evolution of soil moisture pattern and spatially variable runoff production. It also addresses the implications of using different landscape partitioning strategies. This study presents the results of calibration and application of these different routing and landscape partitioning approaches on a 60 ha forested watershed in Western Oregon. For comparison, the different approaches are incorporated into a physically based hydro‐ecological model, RHESSys, and the resulting simulated soil moisture, runoff production and sensitivity to unbiased error are examined. Results illustrate that both routing approaches can be calibrated to achieve a reasonable fit between observed and modelled outflow. Calibrated values for effective watershed hydraulic conductivity are higher for the explicit routing approach, which illustrates differences between the two routing approaches in their representation of internal watershed dynamics. The explicit approach illustrates a seasonal shift in drainage organization from watershed to more local control as climate goes from a winter wet to a summer dry period. Assumptions used in the implicit approach maintain the same pattern of drainage organization throughout the season. The implicit approach is also more sensitive to random error in soil and topographic input information, particularly during wetter periods. Comparison between the two routing approaches illustrates the advantage of the explicit routing approach, although the loss of computational efficiency associated with the explicit routing approach is noted. To compare different strategies for partitioning the landscape, the use of a non‐grid‐based method of partitioning is introduced and shown to be comparable to grid‐based partitioning in terms of simulated soil moisture and runoff production. Copyright © 2001 John Wiley & Sons, Ltd.     

大尺度水文模型TOPX构建及其与区域环境系统集成模式RIEMS的耦合

基于改进型SIMTOP参数化径流方案和新安江模型的三层土壤水量平衡计算方法,本文构建了一个输入数据和率定参数较少、同时具有地形指数尺度转换机制、较好描述二维水文过程的简单高效的大尺度水文模型TOPX,并将其与区域环境系统集成模式RIEMS紧密耦合,以增强区域气候模式对大尺度流域径流量的定量数值模拟能力．TOPX模型在酉水河流域和泾河流域的离线测试表明：该模型对小尺度流域的径流量模拟精度较高,能够较好地描述流域水文变化过程;同时,该模型在大尺度上具有较强的分布式模拟能力,能够捕捉陆面水文过程的主要特征和时空演变特点．TOPX与RIEMS的耦合模式在泾河流域进行了在线测试,借助TOPX模型中的地形指数降尺度转换和水文过程产汇流机制,耦合模式实现了利用区域气候模式模拟的气象资料来驱动水文模型进行大尺度流域日径流量的模拟．进一步分析还表明：区域气候模式RIEMS模拟的降水时空分布数据的精度是影响耦合模式对径流量模拟效果的关键因素．     

Analysis of long‐term water balance in the source area of the Yellow River basin

To analyse the long‐term water balance of the Yellow River basin, a new hydrological model was developed and applied to the source area of the basin. The analysis involved 41 years (1960–2000) of daily observation data from 16 meteorological stations. The model is composed of the following three sub‐models: a heat balance model, a runoff formation model and a river‐routing network model. To understand the heat and water balances more precisely, the original model was modified as follows. First, the land surface was classified into five types (bare, grassland, forest, irrigation area and water surface) using a high‐resolution land‐use map. Potential evaporation was then calculated using land‐surface temperatures estimated by the heat balance model. The maximum evapotranspiration of each land surface was calculated from potential evaporation using functions of the leaf area index (LAI). Finally, actual evapotranspiration was estimated by regulating the maximum evapotranspiration using functions of soil moisture content. The river discharge estimated by the model agreed well with the observed data in most years. However, relatively large errors, which may have been caused by the overestimation of surface flow, appeared in some summer periods. The rapid decrease of river discharge in recent years in the source area of the Yellow River basin depended primarily on the decrease in precipitation. Furthermore, the results suggested that the long‐term water balance in the source area of the Yellow River basin is influenced by land‐use changes. Copyright © 2007 John Wiley & Sons, Ltd.     

Impact of antecedent conditions on simulations of a flood in a mountain headwater basin

A devastating flood struck Southern Alberta in late June 2013, with much of its streamflow generation in the Front Ranges of the Rocky Mountains, west of Calgary. To better understand streamflow generation processes and their sensitivity to initial conditions, a physically based hydrological model was developed using the Cold Regions Hydrological Modelling platform (CRHM) to simulate the flood for the Marmot Creek Research Basin (~9.4 km²). The modular model includes major cold and warm season hydrological processes including snow redistribution, sublimation, melt, runoff over frozen and unfrozen soils, evapotranspiration, subsurface runoff on hillslopes, groundwater recharge and discharge and streamflow routing. Uncalibrated simulations were conducted for eight hydrological years and generally matched streamflow observations well, with a NRMSD of 52%, small model bias (?3%) and a Nash–Sutcliffe efficiency (NSE) of 0.71. The model was then used to diagnose the responses of hydrological processes in 2013 flood from different ecozones in Marmot Creek: alpine, treeline, montane forest and large and small forest clearings to better understand spatial variations in the flood runoff generation mechanisms. To examine the sensitivity to antecedent conditions, ‘virtual’ flood simulations were conducted using a week (17 to 24 June 2013) of flood meteorology imposed on the meteorology of the same period in other years (2005 to 2012), or switched with the meteorology of one week in different months (May to July) of 2013. Sensitivity to changing precipitation and land cover was assessed by varying the precipitation amount during the flood and forest cover and soil storage capacity in forest ecozone. The results show that runoff efficiency increases rapidly with antecedent snowpack and soil moisture storage with the highest runoff response to rainfall from locations in the basin where there are recently melted or actively melting snowpacks and resulting high soil moisture or frozen soils. The impact of forest canopy on flooding is negligible, but flood peak doubles if forest canopy removal is accompanied by 50% reduction in water storage capacity in the basin. Copyright © 2016 John Wiley & Sons, Ltd.     

Modelling hydrological processes influenced by soil,rock and vegetation in a small karst basin of southwest China

Hydrological processes in karst basins are controlled by permeable multimedia, consisting of soil pores, epikarst fractures, and underground conduits. Distributed modelling of hydrological dynamics in such heterogeneous hydrogeological conditions is a challenging task. Basing on the multilayer structure of the distributed hydrology‐soil‐vegetation model (DHSVM), a distributed hydrological model for a karst basin was developed by integrating mathematical routings of porous Darcy flow, fissure flow and underground channel flow. Specifically, infiltration and saturated flow movement within epikarst fractures are expressed by the ‘cubic law’ equation which is associated with fractural width, direction, and spacing. A small karst basin located in Guizhou province of southwest China was selected for this hydrological simulation. The model parameters were determined on the basis of field measurement and calibrated against the observed soil moisture contents, vegetation interception, surface runoff, and underground flow discharges from the basin outlet. The results show that due to high permeability of the epikarst zone, a significant amount of surface runoff is only generated after heavy rainfall events during the wet season. Rock exposure and the epikarst zone significantly increase flood discharge and decrease evapotranspiration (ET) loss; the peak flood discharge is directly proportional to the size of the aperture. Distribution of soil moisture content (SMC) primarily depends on topographic variations just after a heavy rainfall, while SMC and actual ET are dominated by land cover after a period of consecutive non‐rainfall days. The new model was able to capture the sharp increase and decrease of the underground streamflow hydrograph, and as such can be used to investigate hydrological effects in such rock features and land covers. Copyright © 2011 John Wiley & Sons, Ltd.     

A revisit of NRCS-CN inspired models coupled with RS and GIS for runoff estimation

The Natural Resource Conservation Service – Curve Number (NRCS-CN) methodology is a widely used tool for estimating surface runoff, which is of prime importance in hydrological engineering, agricultural planning and management, environmental impact assessment, flood forecasting, and others fields. This article reviews the methodology and associated hydrological models used for runoff estimation along with their advantages and limitations. Furthermore, discussion focuses on the potential applications of Remote Sensing (RS) and Geographical Information System (GIS) techniques for estimating hydrological variables, such as rainfall, soil moisture and CN required for the NRCS-CN methodology, as well as future research and opportunities for improved runoff estimation at the macro scale.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR A. Efstratiadis     

Could operational hydrological models be made compatible with satellite soil moisture observations?

Soil moisture is a significant state variable in flood forecasting. Nowadays more and more satellite soil moisture products are available, yet their usage in the operational hydrology is still limited. This is because the soil moisture state variables in most operational hydrological models (mostly conceptual models) are over‐simplified—resulting in poor compatibility with the satellite soil moisture observations. A case study is provided to discuss this in more detail, with the adoption of the XAJ model and the Soil Moisture and Ocean Salinity (SMOS) level‐3 soil moisture observation to illustrate the relevant issues. It is found that there are three distinct deficiencies existed in the XAJ model that could cause the mismatch issues with the SMOS soil moisture observation: (i) it is based on runoff generation via the field capacity excess mechanism (interestingly, such a runoff mechanism is called the saturation excess in XAJ while in fact it is clearly a misnomer); (ii) evaporation occurs at the potential rate in its upper soil layer until the water storage in the upper layer is exhausted, and then the evapotranspiration process from the lower layers will commence – leading to an abrupt soil water depletion in the upper soil layer; (iii) it uses the multi‐bucket concept at each soil layer – hence the model has varied soil layers. Therefore, it is a huge challenge to make an operational hydrological model compatible with the satellite soil moisture data. The paper argues that this is possible and some new ideas have been explored and discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

Application of a watershed runoff model to North-east Pond River,Newfoundland: to study water balance and hydrological characteristics owing to atmospheric change

The hydrological sensitivities to long-term climate change of a watershed in Eastern Canada were analysed using a deterministic watershed runoff model developed to simulate watershed acidification. This model was modified to study atmospheric change effects in the watershed. Water balance modelling techniques, modified for assessing climate effects, were developed and tested for a watershed using atmospheric change scenarios from both state of the art general circulation models and a series of hypothetical scenarios. The model computed daily surface, inter- and groundwater flows from the watershed. The moisture, infiltration and recharge rate are also computed in the soil reservoirs. The thirty years of simulated data can be used to evaluate the effects of climatic change on soil moisture, recharge rate and surface and subsurface flow systems. The interaction between surface and subsurface water is discussed in relation to climate change. These hydrological results raise the possibility of major environmental and socioeconomic difficulties and have significant implications for future water resource planning and management. © 1997 John Wiley & Sons, Ltd.     

Using a topographic index to distribute variable source area runoff predicted with the SCS curve‐number equation

Because the traditional Soil Conservation Service curve‐number (SCS‐CN) approach continues to be used ubiquitously in water quality models, new application methods are needed that are consistent with variable source area (VSA) hydrological processes in the landscape. We developed and tested a distributed approach for applying the traditional SCS‐CN equation to watersheds where VSA hydrology is a dominant process. Predicting the location of source areas is important for watershed planning because restricting potentially polluting activities from runoff source areas is fundamental to controlling non‐point‐source pollution. The method presented here used the traditional SCS‐CN approach to predict runoff volume and spatial extent of saturated areas and a topographic index, like that used in TOPMODEL, to distribute runoff source areas through watersheds. The resulting distributed CN–VSA method was applied to two subwatersheds of the Delaware basin in the Catskill Mountains region of New York State and one watershed in south‐eastern Australia to produce runoff‐probability maps. Observed saturated area locations in the watersheds agreed with the distributed CN–VSA method. Results showed good agreement with those obtained from the previously validated soil moisture routing (SMR) model. When compared with the traditional SCS‐CN method, the distributed CN–VSA method predicted a similar total volume of runoff, but vastly different locations of runoff generation. Thus, the distributed CN–VSA approach provides a physically based method that is simple enough to be incorporated into water quality models, and other tools that currently use the traditional SCS–CN method, while still adhering to the principles of VSA hydrology. Copyright © 2004 John Wiley & Sons, Ltd.