Predict Water Balance Research Articles

Application of SWAT Model for Hydrological Simulation of Rapti River Basin

This study aimed at application of SWAT model for hydrological simulations of Rapti River Basin (RRB) water systems. The Rapti River originates from Nepal and then it comes in India. SWAT (Soil and Water Assessment Tool) model was used for hydrological simulation of the RRB surface and sub surface water systems. SWAT is a comprehensive, semi-distributed river basin model that requires a large number of input parameters, which complicates model parameterization and calibration. The RRB was discretised into 4 sub-basins and 630 hydrological response units (HRUs) and calibration and validation was carried out at Bagasoti using monthly flow data of 11 years, respectively. We first calibrated the model in SWAT-CUP which is a decision-making framework that incorporates a semi-automated approach (SUFI2) using manual calibration and incorporating sensitivity and uncertainty analysis. Parameter sensitivity analysis helps focus the calibration and uncertainty analysis and is used to provide statistics for goodness-of-fit. In this study Calibration has been done between simulated and observed discharge data (1974-1985) for 50 simulations with 6 parameters that is Curve number (CN2 = 0.945), Groundwater delay (GW_DELAY = 50), Baseflow alpha factor (ALPHA_BF = 0.58), Manning's "n" value for the main channel (CH_N2 = 0.15), Effective hydraulic conductivity in main channel alluvium (CH_K2 = 10.20) and Available water capacity of the soil layer (SOL_AWC = 0.28). The results were analysed and compared with the observational data. The model performance evaluation showed acceptable ranges of values (i.e., Nash Sutcliff was 0.75 and R2 was 0.71). After model calibration, in order to predict water balance, the model was validated by using the best parameter.

Investigating the projected changes in water balance components under climate change considering the effect of storage structures

ABSTRACT The objective of this study was the critical challenge of accurately predicting water balance components in the Upper Bhima River basin, which is also facing significant challenges due to climate change. A major challenge faced in water balance studies is inadequacy of existing hydrological models to account for the effects of storage structures. The study utilized the variable infiltration capacity–routing application for parallel computation of discharge hydrological model with a newly developed storage structure scheme to simulate water balance components for historical (1999–2010) and future (2019–2040) periods, with future climate forcing from 19 Coupled Model Intercomparison Project Phase 5 GCMs under Representative Concentration Pathway (RCP)4.5 and RCP8.5 scenarios. The performance of the model was evaluated against observed streamflow data and around 30% improvement is noticed for the Nash–Sutcliffe efficiency score. The results signify the adverse impacts of climate change in the region, particularly a significant decrease in monsoon precipitation which may intensify drought scenarios and affect monsoon-driven agriculture. Furthermore, the study emphasizes the high sensitivity of baseflow in the Upper Bhima River to climate alterations, indicating potential threats to biodiversity and river ecosystem health. This research offers indispensable findings crucial for future strategies concerning hydropower, flood management, and water resource management in the region.

Information base for forecasting water balance deficiency in irrigated crops for the dry Volga region

The article substantiates the relevance of further development of land irrigation in the southern and central zones of the European part of Russia in the context of global warming and the need for it to research on creating an information base for predicting water balance deficits in irrigated crops, the development and implementation of which will significantly improve the quality and scientific validity of irrigation projects. systems and planning for the development of irrigated agriculture in various regions of the arid Volga region.

Stochastic Merging of Soil Hydraulic Properties for Vadose Zone Hydrological Modeling

Soil hydraulic properties (SHPs) are commonly determined in soil samples with replicas. Whether these replicas are taken at a same location to represent a specific point or at several locations to represent a larger area, the results should be merged into a final data set to be used in modeling. For this data set to be representative, standard errors and a correlation matrix must be considered in the merging process. We present a method to perform this merging and give an example using stochastic realizations of van Genuchten-Mualem (VGM) parameters generated by Cholesky decomposition to merge the SHP and associated statistics into a merged parameter set. To do so, we used VGM parameters obtained at sample scale in three replicas from a Brazilian savanna soil through inverse modeling of laboratory evaporation experiments. The effectiveness and representativeness of the proposed methodology were evaluated by observing the frequency distribution of different levels of output, comparing individual and merged sample properties. The outputs include VGM parameters, retention and conductivity characteristics, and water balance components stochastically predicted by a hydrological model. The performed stochastic merging correctly represented the variability of the combined replicas, especially with respect to hydrological model outputs of soil water balance components. Using the mean hydraulic property parameter values to deterministically predict water balance components may yield values that are substantially different from the mean values of stochastic realizations. This suggests that the deterministic prediction using mean parameter values in vadose zone hydrological modeling may result in unrepresentative outputs.

DRAINMOD modeling framework for simulating controlled drainage effect on lateral seepage from artificially drained fields

We demonstrated a DRAINMOD modeling framework to predict controlled drainage (CD) effect on the fate of water in artificially drained agricultural fields, which is key for determining the water quality benefits of the practice. To demonstrate this modeling framework, DRAINMOD simulated the hydrology of a subsurface drained grass field in Eastern North Carolina, U.S. under both free drainage (FD) and CD. Three scenarios were simulated for each water management: no lateral seepage (LS) and LS with constant and dynamic hydraulic head (Hr). For each scenario, predicted water table depth (WTD) and subsurface drainage were compared to observed values using Mean Absolute Error, Nash-Sutcliffe Efficiency, and Normalized Percent Error. Predicted water balance components for different scenarios were also investigated. Results clearly showed that LS was a significant component of the water balance for CD. Model predictions showed that 96% of the reduction in subsurface drainage due to CD could be attributed to LS (33.5 cm yr−1). The large values of LS predicted by the model were attributed to the presence of a permeable sandy layer in the soil profile, the shallow management depth of the drain outlet, and the small size of the experimental field plots. Agreement between predicted and observed WTD and subsurface drainage ranged from acceptable to excellent for FD with and without considering LS. In contrast, DRAINMOD simulations for CD yielded acceptable predictions only for the scenario considering LS with dynamic Hr. This study demonstrated the power of process-based simulation models, such as DRAINMOD, for interpreting and explaining data of experimental studies and underscored the importance of using a proper model calibration strategy for yielding reliable predictions. This study highlights the need for well-coordinated experimental and modeling research to further investigate how seepage affect CD performance for reducing drainage flow and nitrogen losses from artificially drained agricultural fields.

Propagation of uncertainty of soil hydraulic parameterization in the prediction of water balance components: A stochastic analysis in kaolinitic clay soils

Hydrological models are powerful tools to understand soil–vegetation–atmosphere transport (SVAT) processes. These processes are partially controlled by soil water retention and hydraulic conductivity, in process-based models described by analytical functions (K-θ-h) that define the dependence between pressure head (h), soil water content (θ) and hydraulic conductivity (K). Given the nonlinearity of these process-based SVAT models, stochastic analysis is an interesting tool to get insight in the pattern of model outputs given the uncertainty in the K–θ–h functions. We developed a stochastic framework to evaluate outputs of the SWAP hydrological model according to the uncertainty in the van Genuchten-Mualem K–θ–h analytical functions (VGM). A multivariate Gaussian joint distribution analysis stochastically sampled VGM parameters using two statistical methods, one considering and one disregarding parameter correlations. We evaluated the relations of VGM parameters and simulation outputs (i) for an internal drainage scenario to predict pressure head at flux-based field capacity and (ii) for a cropped scenario to predict water balance components. We also assessed the relative importance of each parameter using linear regression and random forest methods. The hydrological stochastic simulations showed that the developed algorithm allowed to perform multiple SWAP model runs in a quick and unassisted manner on a common personal computer. Although the degree of VGM uncertainty of the studied soils did not affect the SWAP simulation results considerably, model output uncertainty increased when uncorrelated stochastic realizations of VGM parameters were used. The relative propagation of parameter uncertainty showed to be dependent on the simulated scenario (boundary conditions) and on the soil itself. For the correlated VGM stochastic realizations, both criteria used to analyze the parameter importance detected the VGM parameter l as one of the most relevant in determining water balance components variation. This is an interesting outcome, as this parameter is hardly ever determined, and commonly assumed to a predefined value.

Field monitoring and model predicted water balance of monolithic cover

The use of the evapotranspiration cover for landfill is increasing because of its long-term enhanced performance. However, the performance of evapotranspiration cover primarily depends on the onsite geo-climatic conditions. Therefore, field verification of cover performance through constructed test plots is required before actual implementation. Additionally, numerical modeling and comparison with field results are necessary for future performance prediction. The objective of this study was to simulate the water balance hydrology of evapotranspiration cover using the code SEEP/W. Drainage lysimeter was constructed with fine-grained soil and native vegetation. Field water balance data from the lysimeter were obtained through instrumentation. Onsite climatological data, laboratory and field investigated soil parameters and actual field studied plant parameters were used as model input. Based on one year’s simulation, it was observed that the code nearly captured the seasonal variations in the water balance quantities measured in the field. Surface runoff was reasonably predicted in the model where precipitation intensity appeared to be responsible to some extent. Evapotranspiration was slightly overpredicted and the fluctuation in soil water storage was similar to the field results. The model predicted annual percolation was approximately 45 mm, which is under-predicted than the actual field measured annual percolation of 62 mm.

Water balance analysis of Talau-Loes Watershed, a cross border watershed of Indonesia and East Timor

Abstract. Riwu-Kaho M, Mella WII, Mau YS, Riwu-Kaho NPLB, Nur MSM. 2020. Water balance analysis of Talau-Loes Watershed, a cross border watershed of Indonesia and East Timor. Trop Drylands 21: 17-24. The Talau-Loes watershed is a cross-border watershed in Indonesia and Timor Leste (East Timor) which has traditionally been a natural resource for living, cultivation and conservation areas for communities in several districts of Belu Regency, Indonesia, and several areas in the Timor Leste territory. Water shortages in the land system are thought to play a significant role in the low productivity of agricultural crops. This study aimed to predict water balance in the Talau watershed, and to estimate river discharge in Malibaka Sub-watershed of Talau-Loes watershed. The study results showed that the amount of annual precipitation of 1679 mm was smaller than the total amount of water lost, amounting to 1914.79 mm per year, originating from evapotranspiration (ET) of 1650.91 mm and runoff water of 263.85 mm. Thus, theoretically, there would be an annual deficit of 235.79 mm in the Talau watershed. However, at the peak of the groundwater deficit, it turned out that the Malibaka River in the Malibaka sub-watershed and the Talau watershed had a discharge of 18 mm3/sec. This gives a clue about the ability of the groundwater level to gradually release its water reservoir as a source of base flow. Soil and water conservation actions that combine integrated systems such as agroforestry systems with mechanical conservation actions are proposed as solutions that need to be studied and developed in the future.

Simulation of monthly streamflow using the SWAT model of the Ib River watershed, India

The objective of the study is simulating the streamflow and predicting water balance components using Soil and Water Assessment Tool (SWAT) model for Ib River watershed in Mahanadi River basin. Tropical Rainfall Measuring Mission (TRMM) daily rainfall and monthly streamflow data were used to develop the model from 1993 to 2011. The calibration showed better response than validation in which the determination of coefficient, Nash–Sutcliffe efficiency and percent of bias were 0.77; 0.75 and −19.1, respectively. The temporal and spatial variability of water balance components over study area were determined. This study shows that almost 26–50% of the rainfall was lost by evapotranspiration. The spatial variability of surface runoff was higher on the southern region, groundwater was lower due to the dominance of tile drainage, and lateral flow was higher on southern region. This study will enhance the understanding of hydrological components behaviour on the sparse rain network.

Hydrogeological Bayesian Hypothesis Testing through Trans-Dimensional Sampling of a Stochastic Water Balance Model

Conceptual uncertainty is considered one of the major sources of uncertainty in groundwater flow modelling. In this regard, hypothesis testing is essential to increase system understanding by refuting alternative conceptual models. Often a stepwise approach, with respect to complexity, is promoted but hypothesis testing of simple groundwater models is rarely applied. We present an approach to model-based Bayesian hypothesis testing in a simple groundwater balance model, which involves optimization of a model in function of both parameter values and conceptual model through trans-dimensional sampling. We apply the methodology to the Wildman River area, Northern Territory, Australia, where we set up 32 different conceptual models. A factorial approach to conceptual model development allows for direct attribution of differences in performance to individual uncertain components of the conceptual model. The method provides a screening tool for prioritizing research efforts while also giving more confidence to the predicted water balance compared to a deterministic water balance solution. We show that the testing of alternative conceptual models can be done efficiently with a simple additive and linear groundwater balance model and is best done relatively early in the groundwater modelling workflow.

Predicting water balance of wheat and crop rotations with a simple model: AqYield

Designing cropping systems that are well-adapted to water-limited conditions is one challenge of adapting agriculture to climate change. It requires estimating impacts of current and future cropping practices on crop water use and water resource availability in agricultural areas. Crop models such as AqYield are useful tools for evaluating effects of climate, soil and crop practices on evapotranspiration (ET) and drainage that directly impact soil available water (AW). AqYield is a simple model with few input data that has already been satisfactory evaluated for spring crops in southwestern France. Our main objective was to evaluate the ability of AqYield to predict components of soil water balance at the field level for crop rotations. First, we calibrated and evaluated AqYield predictions for winter wheat in France under a wide range of contrasting climatic and soil conditions. Fifty experimental situations (site × year × management) were chosen for calibration. AqYield was evaluated (i) for winter wheat in nine experimental situations, using daily drainage and ET data, and (ii) for two crop rotations on two fields with 7-years of continuous measurements of daily ET flux. During calibration, AqYield predicted soil AW in the contrasting situations with a model efficiency of 0.83, in the same range of accuracy as those of other widely published models. AqYield also predicted ET accurately from calibration and validation datasets, with a model efficiency of 0.84 and 0.69, respectively, for monthly ET. AqYield predicted daily and monthly drainage less accurately, although the range of drainage during the cropping period was predicted well. At the crop-rotation scale, AqYield yielded acceptable predictions of ET for contrasting climate conditions and crops. Whereas AqYield is simple and requires only a few input data, it accurately predicted ET of cropping systems. It therefore could be useful as a module in more complex modeling approaches.

Estimation of water balance and water yield in the Reedy Fork-Buffalo Creek Watershed in North Carolina using SWAT

To use water resources sustainably, it is important to understand the quantity of water resource spatially and temporally. Therefore, the work presented here attempts to preface future modeling applications within a watershed in North Carolina, by assessing the performance of the Soil and Water Assessment Tool (SWAT) model in analyzing watershed hydrology and variability of streamflow in the watershed. Statistical model performance measures, the coefficient of determination (R2) and Nash–Sutcliffe Efficiency (NSE) were used to evaluate the correlation between the observed and simulated monthly streamflow. The result shows a good agreement between the observed and simulated flow. Both NSE and R2 were found to be greater than 0.7 for the calibration and validation period. A scenario analysis performed to determine the effect of future land use change on runoff and water yield shows a 13.9% and 8.32% increase in the surface runoff and water yield respectively, in 2030, when impervious percentage increases from 24.2% in 2010 to 36.5% in 2030. This interesting performance obtained with the SWAT model suggests that SWAT model could be a promising decision support tool to predict water balance and water yield in other watersheds in North Carolina for sustainable water management of water resources where the impact of recent state mandates regarding water quality and quantity is a critical issue.

Development of a decision support system for precision management of conjunctive use of treated wastewater for irrigation in Oman

This research aimed at finding alternative options for conjunctive use of treated wastewater (TW) with groundwater (GW) minimizing the irrigation water from aquifers in the Al-Batinah region with the assistance of a Decision Support System (DSS). Oman is facing a three-facet problem of lowering of GW table, wastewater over-production and excess TW. Approved guidelines for use of TW with tertiary treatments are of two classes: class-A (for vegetables consumed raw), class-B (after cooking). The developed DSS is comprised of four management subsystems: (1) data management in Excel, (2) model and knowledge management by macro programming in Excel, (3) with linear programming (LP) optimization models including transportation algorithms, and (4) user interface with Excel or Visual Basic (VB). The results are based on two extreme scenarios: zero TW excess, and zero GW used for irrigation. The DSS could predict water balance for number of crop rotations, and based on adjustable cost variables farmer profit margins could be created. Crop selections and rotation could be done using LP optimizations while transportation algorithm could organize best locations and capacities for treatment plants and the wastewater collection and transportation to farming areas via treatment plants. The developed DSS will be very useful as a water management, optimization and planning tool.

Hydrogeological Model for Groundwater Prediction in the Shennan Mining Area, China

Coal mining can seriously affect groundwater systems in aquifers that overlie the coal seam, especially in dry and water-stressed areas where protection of groundwater resources is very important. Through generalization of the hydrogeological conditions and analysis of the actual groundwater flow field in a confined weathered bedrock aquifer overlying the Shennan mining area in northern Shaanxi, a hydrogeological conceptual model and numerical groundwater flow model were established. FEFLOW finite element software was used to solve the model and dynamic groundwater data were used to validate it. The study area was hydrogeologically modeled by repeatedly adjusting the parameters. The model was then used to simulate the effect of mining on the overlying aquifer based on the mining plan for the next 5 years by adjusting the quantity of water discharged, the hydrogeological parameters of the upper water-bearing zone, the characteristics of the groundwater flow field, and the predicted water balance after 5 years. The results show that the maximum drawdown could be as high as 50 m (northeast of the Zhangjiamao Mine). A cone of depression centered on the Ningtiaota, Zhangjiamao, and Hongliulin mines will be formed that will influence more than 75% of the simulation area.

Virtual Soils: Moisture Measurements and Their Interpretation by Inverse Modeling

Soils are structured on multiple spatial scales, originating from inhomogeneities of the parent material, pedogenesis, soil organisms, plant roots, or tillage. This leads to heterogeneities that cause variability of local measurements of hydraulic state variables and affects the flow behavior of water in soil. Whereas in real‐world systems, the true underlying structures can never be absolutely known, it is appealing to employ synthetic or “virtual” experiments for assessing general properties of flow in porous media and grasping the main physical mechanisms. With this aim, three two‐dimensional virtual realities with increasing structural complexity, representing cultivated soils with hierarchical spatial heterogeneity on multiple scales were constructed by the interdisciplinary research group Virtual Institute of the Helmholtz Association (INVEST). At these systems, numerical simulations of water dynamics including a heavy rain, a redistribution, and a long‐lasting evaporation period were performed. The technical aspects of the construction of the virtual soils and results of the forward simulations have been presented in a paper by Schlüter et al. (2012). In this follow‐up paper, we use inverse modeling to investigate measurements in virtual vertical soil profiles, mimicking typical field monitoring campaigns with moisture content and matric potential sensors placed at five depths. Contrary to the real situation, we can interpret observed data, their variability, estimated hydraulic properties, and predicted water balance in the light of the known truth. Our results showed that measurements, particularly those of water contents, varied strongly with measuring position. Using data from single profiles in systems similar to our virtual soils thus will lead to very different estimates of the soil hydraulic properties. As a consequence, the correct calculation of the water balance is rather a lucky coincidence than the rule. However, the average of the predicted water balances obtained from the one‐dimensional simulations, and the estimated soil hydraulic properties agreed very well with those attained from the two‐dimensional systems.

Impact of Land-use Changes on Water Balance

Due to rapid population growth, Goseng catchment has been subjected to considerable land-use changes over the last decade. The main objective of this research is to find out the impact of land-use changes on the hydrological processes and river discharge using the simulation of land cover changes. GenRiver model is used to analyze and predict water balance change in Goseng catchment by proposing some scenario of land cover changes. GenRiver calibration was achieved by NSE analysis, comparing observed and simulation discharge data in the period of 1974 - 1994. Calibration and validation results showed that the satisfaction model using daily test has the coefficient correlation of 0.73. Furthermore, the land cover simulation of community forest in scenario 2 has the highest buffering indicator value and the lowest in paddy field. Thus, the land-use changes play an important role in the water balance changes in Goseng catchment, indicated by increasing surface run-off along with the decline of vegetation cover.

Predicting water balance in a sandy soil: model sensitivity to the variability of measured saturated and near saturated hydraulic properties

Water balance modelling based on Richards’ equation requires accurate description of the soils’ hydraulic parameters. Unfortunately, these parameters vary spatially and temporally as well as between measurement techniques. For most field modelling exercises, the hydraulic parameters are obtained from a small number of measurements or predicted from soil properties using pedo-transfer functions. The effect of different measurement techniques on the description of soil hydraulic parameters has been the subject of many studies but the effect of the variability of the hydraulic parameters on the predicted water balance has not been widely investigated. In this study we compared the hydraulic parameters obtained solely from laboratory measurements with those obtained from a rapid wet end field measurement technique, augmented by dry end laboratory data. The water balance was modelled using the laboratory and field hydraulic parameter sets and compared to field water contents measured by time domain reflectometry (TDR). In a sandy soil, we found the total profile water content to be well modelled by both hydraulic parameter datasets, but the water content at a specific depth was less well predicted using either of the measured parameter sets. The water content at a specific depth was under-predicted prior to the rainfall event and over-predicted after the rainfall, regardless of whether the hydraulic parameters were obtained from laboratory or field measurements. Generally, the hydraulic parameters that were obtained from the field measurements gave a closer fit to the measured TDR water contents. The sensitivity of the modelled water balance to changes in the hydraulic parameters within the observed range of parameter values was also investigated. Parameter percentage coefficient of variation within measurement techniques ranged from 60% for air entry, he; 19% for residual water content, θr; 5% for slope of the water retention curve, n; and 7% for saturated water content, θs. The percentage differences between the parameters obtained from the laboratory and field measurement techniques for the topsoil and subsoil respectively were 47% and 50% for he, 100% for θr, 28% and 40% for n, and –14.4% and 4.0% for θs. Modelling water content changes at a particular depth in the sandy soil was found to be most influenced by variations in θs, and n. Predicted water contents were also affected by the θr but less influenced by the saturated hydraulic conductivity, Ks. The he was the least influential parameter but also the most variable. This suggests that measurement of θs, related to bulk density changes caused by tillage, wheel compaction, and consolidation, is required for water balance studies. Generally, n had small variability between measurements at a particular depth, which is promising for the use of pedo-transfer functions related to soil texture.

Calibration of effective soil hydraulic parameters of heterogeneous soil profiles

Distributed hydrological models are useful tools to analyse the performance of irrigation systems at different levels. For the successful application of these models, it is imperative that effective soil hydraulic parameters at the scale of model application are known. The majority of previous studies to define effective soil hydraulic parameters have considered only horizontal spatial variability of the parameters while neglecting textural layering at different spatial locations. In this paper, numerical experiments are conducted for seven vertical heterogeneous soil profiles (containing 4–5 soil layers) to generate different water balance components. Thereafter, information on evapotranspiration fluxes and water storage in the root zone profile is inversely used to identify effective soil hydraulic parameters. The aim is to assess whether effective soil hydraulic parameters can be assigned to vertically heterogeneous soil profiles. The performance of inversely identified soil hydraulic parameters is evaluated by their ability to reproduce the different components of water balance. Results showed that the evapotranspiration fluxes are sufficient to inversely identify soil hydraulic parameters for heterogeneous soil profiles under deep water table conditions and significant moisture stress. The identified soil hydraulic parameters are suitable to predict water balance components. However, appropriate formulation of soil evaporation simulation is very important if the surface soil layers have deviating soil hydraulic properties. Results also showed that general information on the textural layering of the area is an important input to inversely identify effective soil hydraulic parameters using evapotranspiration fluxes.

Model development for nutrient loading from paddy rice fields

The objective of this study was to develop a model groundwater loading effects of agricultural management systems in paddy fields (GLEAMS-PADDY) to predict nutrient loading to surface waters from paddy rice fields. This model was developed by modifying the GLEAMS model that is used for uplands. The GLEAMS-PADDY model is composed of hydrology and chemical sub-models. In the hydrology sub-model of the GLEAMS-PADDY model, the ponded depth routing method was used to handle ponded water condition of paddy fields. With the chemical sub-model, the soil was assumed to be saturated, and the soil profile in the root zone was divided into oxidized and reduced zones. Field experiments were performed at the Soro region, Chungbuk Province of South Korea, from May to September 1999 and 2000. Field data included rainfall amount, irrigation water input, drainage water output, and percolation. Concentrations of total nitrogen (T-N) and total phosphorus (T-P) in irrigation water, rain water, ponded water, surface drainage water, and percolated water were analyzed. The coefficient of determination ( r 2) and root mean square error (RMSE) between observed and model predicted surface drainage volume relative to the 1:1 line were 0.66 and 66.6 mm, respectively. The r 2 and RMSE between observed and predicted T-N concentrations in the ponded water were 0.74 and 1.43 mg l −1, respectively. The same statistics for T-P were 0.64 and 0.03 mg l −1, respectively. The observed and predicted total T-N loadings from surface drainage were 72.4 and 72.6 kg ha −1, respectively. The observed and predicted total T-P loadings were 1.70 and 1.69 kg ha −1, respectively. The r 2 and RMSE between observed and predicted T-N concentrations in the surface drainage water were 0.79 and 2.71 mg l −1, respectively. The same statistics for T-P were 0.73 and 0.04 mg l −1, respectively. Comparisons of observed and model predicted water balance components, nutrient concentrations, and loading rates exhibited reasonably good agreement. Hence, the GREAMS-PADDY model can be used to predict nutrient loading from paddy fields and to develop BMPs in paddy rice culture to reduce surface water pollution from paddy field drainage water.

Climate, soil, and vegetation controls upon the variability of water balance in temperate and semiarid landscapes: Downward approach to water balance analysis

Observed differences between water balance for temperate and semiarid catchments can be attributed to variability in the primary controls of the soil profile (soil water storage capacity and permeability), vegetation (surface coverage and water use efficiency), and climate (rainfall and potential evaporation). Motivated by the downward development methodology mooted by Klemes [1983], this paper explores the underlying climate and landscape interactions that cause differences in water balance between a number of temperate and semiarid benchmark catchments around Australia. A systematic parsimonious analysis based around a simple water balance model whose parameters are estimated from available data is used to observe and interpret signatures of annual, intra‐annual, and daily water balance behavior and variability. The essence of the downward analysis is that model complexity evolves from the simplest form to its final quasi‐distributed framework with multiple storages and process interactions in response to inadequacies in signature prediction. Consequently, each step in the process develops insight into local climate and landscape influences and sensitivity to their temporal and spatial variabilities. The results affirm that the relative influence of climate and landscape properties upon catchment response is manifested in a systematic transformation of process sensitivity with increasing timescales (annual, monthly, daily, and hourly). Significantly, drier catchments are shown to be more sensitive to small‐scale perturbation than humid catchments. We conclude that the downward analysis approach is a means to better understand the significance of landscape variability upon catchment response. Consequential knowledge can begin to explain data requirements and requisite model complexity and to provide insight into the ability to reliably predict water balance behavior. These are important first steps toward the longer‐term objective of reliably predicting water balance variability across ungauged basins.